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Sample records for zachary wasserman python

  1. Python import replacement

    SciTech Connect

    2011-10-01

    SmartImport.py is a Python source-code file that implements a replacement for the standard Python module importer. The code is derived from knee.py, a file in the standard Python diestribution , and adds functionality to improve the performance of Python module imports in massively parallel contexts.

  2. Fast retreat of Zachariæ Isstrøm, northeast Greenland.

    PubMed

    Mouginot, J; Rignot, E; Scheuchl, B; Fenty, I; Khazendar, A; Morlighem, M; Buzzi, A; Paden, J

    2015-12-11

    After 8 years of decay of its ice shelf, Zachariæ Isstrøm, a major glacier of northeast Greenland that holds a 0.5-meter sea-level rise equivalent, entered a phase of accelerated retreat in fall 2012. The acceleration rate of its ice velocity tripled, melting of its residual ice shelf and thinning of its grounded portion doubled, and calving is now occurring at its grounding line. Warmer air and ocean temperatures have caused the glacier to detach from a stabilizing sill and retreat rapidly along a downward-sloping, marine-based bed. Its equal-ice-volume neighbor, Nioghalvfjerdsfjorden, is also melting rapidly but retreating slowly along an upward-sloping bed. The destabilization of this marine-based sector will increase sea-level rise from the Greenland Ice Sheet for decades to come.

  3. The Calibrated Phylogeny of the Drosophila fasciola Subgroup (D. repleta Group Wasserman) Indicates Neogene Diversification of Its Internal Branches.

    PubMed

    Franco, F F; Silva, E C C; Barrios-Leal, D Y; Sene, F M; Manfrin, M H

    2017-01-31

    The species of the Drosophila fasciola subgroup Wasserman represent the dominant section of the Drosophila repleta group Wasserman in the American rainforests and have a broad geographical distribution in the New World. However, despite of its wide range, the D. fasciola subgroup is one of the most overlooked D. repleta subgroups. Here, we report a molecular phylogenetic analysis focused on the D. fasciola subgroup using two mitochondrial [cytochrome oxidase subunit I (COI), cytochrome oxidase subunit II (COII)] and two nuclear [elongation factor-1alpha F1 (EF-alphaF1) and transformer (tra)] genes. Overall, we found that this subgroup is a monophyletic taxon, subdivided into two main internal branches: named Fas1 and Fas2 clades. The diversification of these clades is estimated to have begun in the middle Miocene, around 12 Ma [95% high posterior density (HPD) 9.0-15 Ma], and might be associated with the colonization of South America by Central America populations after the closure of Isthmus of Panama due to the temporal congruence between these events. The terminal branches had their origins estimated to be in the Pliocene or the Plio-Pleistocene transition. For the later estimates, both the geomorphological influences and the climatic oscillations of the Pleistocene may have played a role in shaping the diversification of the D. fasciola group.

  4. Python for Ecology

    EPA Science Inventory

    Python is a high-level scripting language that is becoming increasingly popular for scientific computing. This all-day workshop is designed to introduce the basics of Python programming to ecologists. Some scripting/programming experience is recommended (e.g. familiarity with R)....

  5. Python to learn programming

    NASA Astrophysics Data System (ADS)

    Bogdanchikov, A.; Zhaparov, M.; Suliyev, R.

    2013-04-01

    Today we have a lot of programming languages that can realize our needs, but the most important question is how to teach programming to beginner students. In this paper we suggest using Python for this purpose, because it is a programming language that has neatly organized syntax and powerful tools to solve any task. Moreover it is very close to simple math thinking. Python is chosen as a primary programming language for freshmen in most of leading universities. Writing code in python is easy. In this paper we give some examples of program codes written in Java, C++ and Python language, and we make a comparison between them. Firstly, this paper proposes advantages of Python language in relation to C++ and JAVA. Then it shows the results of a comparison of short program codes written in three different languages, followed by a discussion on how students understand programming. Finally experimental results of students' success in programming courses are shown.

  6. Python in Astronomy 2016

    NASA Astrophysics Data System (ADS)

    Jenness, Tim; Robitaille, Thomas; Tollerud, Erik; Mumford, Stuart; Cruz, Kelle

    2016-04-01

    The second Python in Astronomy conference will be held from 21-25 March 2016 at the University of Washington eScience Institute in Seattle, WA, USA. Similarly to the 2015 meeting (which was held at the Lorentz Center), we are aiming to bring together researchers, Python developers, users, and educators. The conference will include presentations, tutorials, unconference sessions, and coding sprints. In addition to sharing information about state-of-the art Python Astronomy packages, the workshop will focus on improving interoperability between astronomical Python packages, providing training for new open-source contributors, and developing educational materials for Python in Astronomy. The meeting is therefore not only aimed at current developers, but also users and educators who are interested in being involved in these efforts.

  7. NEURON and Python

    PubMed Central

    Hines, Michael L.; Davison, Andrew P.; Muller, Eilif

    2008-01-01

    The NEURON simulation program now allows Python to be used, alone or in combination with NEURON's traditional Hoc interpreter. Adding Python to NEURON has the immediate benefit of making available a very extensive suite of analysis tools written for engineering and science. It also catalyzes NEURON software development by offering users a modern programming tool that is recognized for its flexibility and power to create and maintain complex programs. At the same time, nothing is lost because all existing models written in Hoc, including graphical user interface tools, continue to work without change and are also available within the Python context. An example of the benefits of Python availability is the use of the xml module in implementing NEURON's Import3D and CellBuild tools to read MorphML and NeuroML model specifications. PMID:19198661

  8. NEURON and Python.

    PubMed

    Hines, Michael L; Davison, Andrew P; Muller, Eilif

    2009-01-01

    The NEURON simulation program now allows Python to be used, alone or in combination with NEURON's traditional Hoc interpreter. Adding Python to NEURON has the immediate benefit of making available a very extensive suite of analysis tools written for engineering and science. It also catalyzes NEURON software development by offering users a modern programming tool that is recognized for its flexibility and power to create and maintain complex programs. At the same time, nothing is lost because all existing models written in Hoc, including graphical user interface tools, continue to work without change and are also available within the Python context. An example of the benefits of Python availability is the use of the xml module in implementing NEURON's Import3D and CellBuild tools to read MorphML and NeuroML model specifications.

  9. Python Data Visualization

    SciTech Connect

    2011-08-15

    PDV is a Python module that reads in ULTRA data files and allows the user to perform data analysis and to create high-quality plots of the data. Features include the ability to perform integrals, take derivatives, perform arithmetic on data-sets, and to produce publication-quality plots. PDV is deliberaltely designed so that ULTRA users will be able to start running PDV with minimal training. PDV is easily customizable and extendible by anyone who knows a little Python.

  10. 75 FR 38069 - Injurious Wildlife Species; Listing the Boa Constrictor, Four Python Species, and Four Anaconda...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-07-01

    ... Constrictor, Four Python Species, and Four Anaconda Species as Injurious Reptiles AGENCY: Fish and Wildlife... regulations to add Indian python (Python molurus, including Burmese python Python molurus bivittatus), reticulated python (Broghammerus reticulatus or Python reticulatus), Northern African python (Python...

  11. Python and computer vision

    SciTech Connect

    Doak, J. E.; Prasad, Lakshman

    2002-01-01

    This paper discusses the use of Python in a computer vision (CV) project. We begin by providing background information on the specific approach to CV employed by the project. This includes a brief discussion of Constrained Delaunay Triangulation (CDT), the Chordal Axis Transform (CAT), shape feature extraction and syntactic characterization, and normalization of strings representing objects. (The terms 'object' and 'blob' are used interchangeably, both referring to an entity extracted from an image.) The rest of the paper focuses on the use of Python in three critical areas: (1) interactions with a MySQL database, (2) rapid prototyping of algorithms, and (3) gluing together all components of the project including existing C and C++ modules. For (l), we provide a schema definition and discuss how the various tables interact to represent objects in the database as tree structures. (2) focuses on an algorithm to create a hierarchical representation of an object, given its string representation, and an algorithm to match unknown objects against objects in a database. And finally, (3) discusses the use of Boost Python to interact with the pre-existing C and C++ code that creates the CDTs and CATS, performs shape feature extraction and syntactic characterization, and normalizes object strings. The paper concludes with a vision of the future use of Python for the CV project.

  12. Python/Lua Benchmarks

    SciTech Connect

    Busby, L.

    2014-08-01

    This is an adaptation of the pre-existing Scimark benchmark code to a variety of Python and Lua implementations. It also measures performance of the Fparser expression parser and C and C++ code on a variety of simple scientific expressions.

  13. Parallel distributed computing using Python

    NASA Astrophysics Data System (ADS)

    Dalcin, Lisandro D.; Paz, Rodrigo R.; Kler, Pablo A.; Cosimo, Alejandro

    2011-09-01

    This work presents two software components aimed to relieve the costs of accessing high-performance parallel computing resources within a Python programming environment: MPI for Python and PETSc for Python. MPI for Python is a general-purpose Python package that provides bindings for the Message Passing Interface (MPI) standard using any back-end MPI implementation. Its facilities allow parallel Python programs to easily exploit multiple processors using the message passing paradigm. PETSc for Python provides access to the Portable, Extensible Toolkit for Scientific Computation (PETSc) libraries. Its facilities allow sequential and parallel Python applications to exploit state of the art algorithms and data structures readily available in PETSc for the solution of large-scale problems in science and engineering. MPI for Python and PETSc for Python are fully integrated to PETSc-FEM, an MPI and PETSc based parallel, multiphysics, finite elements code developed at CIMEC laboratory. This software infrastructure supports research activities related to simulation of fluid flows with applications ranging from the design of microfluidic devices for biochemical analysis to modeling of large-scale stream/aquifer interactions.

  14. Pythons in Burma: Short-tailed python (Reptilia: Squamata)

    USGS Publications Warehouse

    Zug, George R.; Gotte, Steve W.; Jacobs, Jeremy F.

    2011-01-01

    Short-tailed pythons, Python curtus species group, occur predominantly in the Malayan Peninsula, Sumatra, and Borneo. The discovery of an adult female in Mon State, Myanmar, led to a review of the distribution of all group members (spot-mapping of all localities of confirmed occurrence) and an examination of morphological variation in P. brongersmai. The resulting maps demonstrate a limited occurrence of these pythons within peninsular Malaya, Sumatra, and Borneo with broad absences in these regions. Our small samples limit the recognition of regional differentiation in the morphology of P. brongersmai populations; however, the presence of unique traits in the Myanmar python and its strong allopatry indicate that it is a unique genetic lineage, and it is described as Python kyaiktiyo new species.

  15. Use of the Wasserman equation in optimization of the duration of the power ramp in a cardiopulmonary exercise test: a study of Brazilian men.

    PubMed

    Costa, D C; Santi, G L de; Crescêncio, J C; Seabra, L P; Carvalho, E E V; Papa, V; Marques, F; Gallo Junior, L; Schmidt, A

    2015-12-01

    This study aimed to analyze the agreement between measurements of unloaded oxygen uptake and peak oxygen uptake based on equations proposed by Wasserman and on real measurements directly obtained with the ergospirometry system. We performed an incremental cardiopulmonary exercise test (CPET), which was applied to two groups of sedentary male subjects: one apparently healthy group (HG, n=12) and the other had stable coronary artery disease (n=16). The mean age in the HG was 47±4 years and that in the coronary artery disease group (CG) was 57±8 years. Both groups performed CPET on a cycle ergometer with a ramp-type protocol at an intensity that was calculated according to the Wasserman equation. In the HG, there was no significant difference between measurements predicted by the formula and real measurements obtained in CPET in the unloaded condition. However, at peak effort, a significant difference was observed between oxygen uptake (V˙O2)peak(predicted)and V˙O2peak(real)(nonparametric Wilcoxon test). In the CG, there was a significant difference of 116.26 mL/min between the predicted values by the formula and the real values obtained in the unloaded condition. A significant difference in peak effort was found, where V˙O2peak(real)was 40% lower than V˙O2peak(predicted)(nonparametric Wilcoxon test). There was no agreement between the real and predicted measurements as analyzed by Lin's coefficient or the Bland and Altman model. The Wasserman formula does not appear to be appropriate for prediction of functional capacity of volunteers. Therefore, this formula cannot precisely predict the increase in power in incremental CPET on a cycle ergometer.

  16. Use of the Wasserman equation in optimization of the duration of the power ramp in a cardiopulmonary exercise test: a study of Brazilian men

    PubMed Central

    Costa, D. C.; de Santi, G. L.; Crescêncio, J. C.; Seabra, L. P.; Carvalho, E. E. V.; Papa, V.; Marques, F.; Gallo, L.; Schmidt, A.

    2015-01-01

    This study aimed to analyze the agreement between measurements of unloaded oxygen uptake and peak oxygen uptake based on equations proposed by Wasserman and on real measurements directly obtained with the ergospirometry system. We performed an incremental cardiopulmonary exercise test (CPET), which was applied to two groups of sedentary male subjects: one apparently healthy group (HG, n=12) and the other had stable coronary artery disease (n=16). The mean age in the HG was 47±4 years and that in the coronary artery disease group (CG) was 57±8 years. Both groups performed CPET on a cycle ergometer with a ramp-type protocol at an intensity that was calculated according to the Wasserman equation. In the HG, there was no significant difference between measurements predicted by the formula and real measurements obtained in CPET in the unloaded condition. However, at peak effort, a significant difference was observed between oxygen uptake (V˙O2)peak(predicted)and V˙O2peak(real)(nonparametric Wilcoxon test). In the CG, there was a significant difference of 116.26 mL/min between the predicted values by the formula and the real values obtained in the unloaded condition. A significant difference in peak effort was found, where V˙O2peak(real)was 40% lower than V˙O2peak(predicted)(nonparametric Wilcoxon test). There was no agreement between the real and predicted measurements as analyzed by Lin’s coefficient or the Bland and Altman model. The Wasserman formula does not appear to be appropriate for prediction of functional capacity of volunteers. Therefore, this formula cannot precisely predict the increase in power in incremental CPET on a cycle ergometer. PMID:26397972

  17. Learning Scientific Programming with Python

    NASA Astrophysics Data System (ADS)

    Hill, Christian

    2016-02-01

    1. Introduction; 2. The core Python language I; 3. Interlude: simple plotting with pylab; 4. The core Python language II; 5. IPython and IPython notebook; 6. NumPy; 7. Matplotlib; 8. SciPy; 9. General scientific programming; Appendix A; Solutions; Index.

  18. Cardiovascular actions of python bradykinin and substance P in the anesthetized python, Python regius.

    PubMed

    Wang, T; Axelsson, M; Jensen, J; Conlon, J M

    2000-08-01

    The cardiovascular actions of python bradykinin (BK) and substance P (SP) have been investigated in the anesthetized ball python, Python regius. Bolus intra-arterial injections of python BK (0.03-3 nmol/kg) produced concentration-dependent increases in arterial blood pressure, heart rate (HR), and cardiac output concomitant with small decreases in systemic resistance and stroke volume. Intra-arterial injection of 3 nmol/kg python BK produced a tenfold increase in circulating concentration of norepinephrine, but epinephrine levels did not change. BK-induced tachycardia was attenuated (>90%) by the beta-adrenergic receptor antagonist sotalol, and the hypertensive response was attenuated (>70%) by the alpha-adrenergic receptor antagonist prazosin, indicating that effects of python BK are mediated at least in part by activation of the extensive network of adrenergic neurons present in vascular tissues. Bolus intra-arterial injections of python SP in the range 0. 01-30 pmol/kg produced concentration-dependent decreases in arterial blood pressure and systemic peripheral resistance concomitant with increases in cardiac output and stroke volume but with only minor effects on HR. The data suggest that kinins play a physiologically important role in cardiovascular regulation in the python.

  19. Endocardial fibrosarcoma in a reticulated python (Python reticularis).

    PubMed

    Gumber, Sanjeev; Nevarez, Javier G; Cho, Doo-Youn

    2010-11-01

    A female, reticulated python (Python reticularis) of unknown age was presented with a history of lethargy, weakness, and distended coelom. Physical examination revealed severe dystocia and stomatitis. The reticulated python was euthanized due to a poor clinical prognosis. Postmortem examination revealed marked distention of the reproductive tract with 26 eggs (10-12 cm in diameter), pericardial effusion, and a slightly firm, pale tan mass (3-4 cm in diameter) adhered to the endocardium at the base of aorta. Based on histopathologic and transmission electron microscopic findings, the diagnosis of endocardial fibrosarcoma was made.

  20. Python fiber optic seal

    SciTech Connect

    Ystesund, K.; Bartberger, J.; Brusseau, C.; Fleming, P.; Insch, K.; Tolk, K.

    1993-08-01

    Sandia National Laboratories has developed a high security fiber optic seal that incorporates tamper resistance features that are not available in commercial fiber optic seals. The Python Seal is a passive fiber optic loop seal designed to give indication of unauthorized entry. The seal includes a fingerprint feature that provides seal identity information in addition to the unique fiber optic pattern created when the seal is installed. The fiber optic cable used for the seal loop is produced with tamper resistant features that increase the difficulty of attacking that component of a seal. A Seal Reader has been developed that will record the seal signature and the fingerprint feature of the seal. A Correlator software program then compares seal images to establish a match or mismatch. SNL is also developing a Polaroid reader to permit hard copies of the seal patterns to be obtained directly from the seal.

  1. Pynamic: the Python Dynamic Benchmark

    SciTech Connect

    Lee, G L; Ahn, D H; de Supinksi, B R; Gyllenhaal, J C; Miller, P J

    2007-07-10

    Python is widely used in scientific computing to facilitate application development and to support features such as computational steering. Making full use of some of Python's popular features, which improve programmer productivity, leads to applications that access extremely high numbers of dynamically linked libraries (DLLs). As a result, some important Python-based applications severely stress a system's dynamic linking and loading capabilities and also cause significant difficulties for most development environment tools, such as debuggers. Furthermore, using the Python paradigm for large scale MPI-based applications can create significant file IO and further stress tools and operating systems. In this paper, we present Pynamic, the first benchmark program to support configurable emulation of a wide-range of the DLL usage of Python-based applications for large scale systems. Pynamic has already accurately reproduced system software and tool issues encountered by important large Python-based scientific applications on our supercomputers. Pynamic provided insight for our system software and tool vendors, and our application developers, into the impact of several design decisions. As we describe the Pynamic benchmark, we will highlight some of the issues discovered in our large scale system software and tools using Pynamic.

  2. Humoral regulation of heart rate during digestion in pythons (Python molurus and Python regius).

    PubMed

    Enok, Sanne; Simonsen, Lasse Stærdal; Pedersen, Signe Vesterskov; Wang, Tobias; Skovgaard, Nini

    2012-05-15

    Pythons exhibit a doubling of heart rate when metabolism increases several times during digestion. Pythons, therefore, represent a promising model organism to study autonomic cardiovascular regulation during the postprandial state, and previous studies show that the postprandial tachycardia is governed by a release of vagal tone as well as a pronounced stimulation from nonadrenergic, noncholinergic (NANC) factors. Here we show that infusion of plasma from digesting donor pythons elicit a marked tachycardia in fasting snakes, demonstrating that the NANC factor resides in the blood. Injections of the gastrin and cholecystokinin receptor antagonist proglumide had no effect on double-blocked heart rate or blood pressure. Histamine has been recognized as a NANC factor in the early postprandial period in pythons, but the mechanism of its release has not been identified. Mast cells represent the largest repository of histamine in vertebrates, and it has been speculated that mast cells release histamine during digestion. Treatment with the mast cell stabilizer cromolyn significantly reduced postprandial heart rate in pythons compared with an untreated group but did not affect double-blocked heart rate. While this study indicates that histamine induces postprandial tachycardia in pythons, its release during digestion is not stimulated by gastrin or cholecystokinin nor is its release from mast cells a stimulant of postprandial tachycardia.

  3. Extension Modules for the Python Interpretive language

    SciTech Connect

    Busby, Lee; Dubois, Paul F.; Motteler, Zane C.; Yang, Tser-Yuan; Eme, William; Taylor, Lee; Miller, Douglas

    2006-12-29

    Python is an interpreted computer language, freely available to all, which may be extended by user developed "modules". These modules ay be written in a complied language such as 'C', and then linked into the Python program

  4. Algorithmic synthesis using Python compiler

    NASA Astrophysics Data System (ADS)

    Cieszewski, Radoslaw; Romaniuk, Ryszard; Pozniak, Krzysztof; Linczuk, Maciej

    2015-09-01

    This paper presents a python to VHDL compiler. The compiler interprets an algorithmic description of a desired behavior written in Python and translate it to VHDL. FPGA combines many benefits of both software and ASIC implementations. Like software, the programmed circuit is flexible, and can be reconfigured over the lifetime of the system. FPGAs have the potential to achieve far greater performance than software as a result of bypassing the fetch-decode-execute operations of traditional processors, and possibly exploiting a greater level of parallelism. This can be achieved by using many computational resources at the same time. Creating parallel programs implemented in FPGAs in pure HDL is difficult and time consuming. Using higher level of abstraction and High-Level Synthesis compiler implementation time can be reduced. The compiler has been implemented using the Python language. This article describes design, implementation and results of created tools.

  5. Accessing the VO with Python

    NASA Astrophysics Data System (ADS)

    Plante, R.; Fitzpatrick, M.; Graham, M.; Tody, D.; Young, W.

    2014-05-01

    We introduce two products for accessing the VO from Python: PyVO and VOClient. PyVO is built on the widely-used Astropy package and is well suited for integrating automated access to astronomical data into highly customizable scripts and applications for data analysis in Python. VOClient is built on a collection of C-libraries and is well suited for integrating with multi-language analysis packages. It also provides a framework for integrating legacy software into the Python environment. In this demo, we will run through several examples demonstrate basic data discovery and retrieval of data. This includes finding archives containing data of interest (VO registry), retrieving datasets (SIA, SSA), and exploring (Cone Search, SLAP). VOClient features some extended capabilities including the ability to communicate to other desktop applications from a script using the SAMP protocol.

  6. Anatomy of the python heart.

    PubMed

    Jensen, Bjarke; Nyengaard, Jens R; Pedersen, Michael; Wang, Tobias

    2010-12-01

    The hearts of all snakes and lizards consist of two atria and a single incompletely divided ventricle. In general, the squamate ventricle is subdivided into three chambers: cavum arteriosum (left), cavum venosum (medial) and cavum pulmonale (right). Although a similar division also applies to the heart of pythons, this family of snakes is unique amongst snakes in having intracardiac pressure separation. Here we provide a detailed anatomical description of the cardiac structures that confer this functional division. We measured the masses and volumes of the ventricular chambers, and we describe the gross morphology based on dissections of the heart from 13 ball pythons (Python regius) and one Burmese python (P. molurus). The cavum venosum is much reduced in pythons and constitutes approximately 10% of the cavum arteriosum. We suggest that shunts will always be less than 20%, while other studies conclude up to 50%. The high-pressure cavum arteriosum accounted for approximately 75% of the total ventricular mass, and was twice as dense as the low-pressure cavum pulmonale. The reptile ventricle has a core of spongious myocardium, but the three ventricular septa that separate the pulmonary and systemic chambers--the muscular ridge, the bulbuslamelle and the vertical septum--all had layers of compact myocardium. Pythons, however, have unique pads of connective tissue on the site of pressure separation. Because the hearts of varanid lizards, which also are endowed with pressure separation, share many of these morphological specializations, we propose that intraventricular compact myocardium is an indicator of high-pressure systems and possibly pressure separation.

  7. Astropysics: Astrophysics utilities for python

    NASA Astrophysics Data System (ADS)

    Tollerud, Erik

    2012-07-01

    Astropysics is a library containing a variety of utilities and algorithms for reducing, analyzing, and visualizing astronomical data. Best of all, it encourages the user to leverage the existing capabilities of Python to make this quick, easy, and as painless as cutting-edge science can even actually be. There do exist other Python packages with some of the capabilities of this project, but the goal of this project is to integrate all these tools together and make them interact in the most straightforward ways possible.

  8. Python-ARM Radar Toolkit

    SciTech Connect

    Jonathan Helmus, Scott Collis

    2013-03-17

    The Python-ARM Radar Toolkit (Py-ART) is a collection of radar quality control and retrieval codes which all work on two unifying Python objects: the PyRadar and PyGrid objects. By building ingests to several popular radar formats and then abstracting the interface Py-ART greatly simplifies data processing over several other available utilities. In addition Py-ART makes use of Numpy arrays as its primary storage mechanism enabling use of existing and extensive community software tools.

  9. MontePython: Implementing Quantum Monte Carlo using Python

    NASA Astrophysics Data System (ADS)

    Nilsen, Jon Kristian

    2007-11-01

    We present a cross-language C++/Python program for simulations of quantum mechanical systems with the use of Quantum Monte Carlo (QMC) methods. We describe a system for which to apply QMC, the algorithms of variational Monte Carlo and diffusion Monte Carlo and we describe how to implement theses methods in pure C++ and C++/Python. Furthermore we check the efficiency of the implementations in serial and parallel cases to show that the overhead using Python can be negligible. Program summaryProgram title: MontePython Catalogue identifier: ADZP_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADZP_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 49 519 No. of bytes in distributed program, including test data, etc.: 114 484 Distribution format: tar.gz Programming language: C++, Python Computer: PC, IBM RS6000/320, HP, ALPHA Operating system: LINUX Has the code been vectorised or parallelized?: Yes, parallelized with MPI Number of processors used: 1-96 RAM: Depends on physical system to be simulated Classification: 7.6; 16.1 Nature of problem: Investigating ab initio quantum mechanical systems, specifically Bose-Einstein condensation in dilute gases of 87Rb Solution method: Quantum Monte Carlo Running time: 225 min with 20 particles (with 4800 walkers moved in 1750 time steps) on 1 AMD Opteron TM Processor 2218 processor; Production run for, e.g., 200 particles takes around 24 hours on 32 such processors.

  10. Hemodynamic effects of python neuropeptide gamma in the anesthetized python, Python regius.

    PubMed

    Skovgaard, Nini; Galli, Gina; Taylor, Edwin W; Conlon, J Michael; Wang, Tobias

    2005-05-15

    The effects of python neuropeptide gamma (NPgamma) on hemodynamic parameters have been investigated in the anesthetized ball python (Python regius). Bolus intra-arterial injections of synthetic python NPgamma (1-300 pmol kg-1) produced a dose-dependent decrease in systemic arterial blood pressure (Psys) concomitant with increases in systemic vascular conductance (Gsys), total cardiac output and stroke volume, but only minor effects on heart rate. The peptide had no significant effect on pulmonary arterial blood pressure (Ppul) and caused only a small increase in pulmonary conductance (Gpul) at the highest dose. In the systemic circulation, the potency of the NK1 receptor-selective agonist [Sar9,Met(0(2))11] substance P was >100-fold greater than the NK2 receptor-selective agonist [betaAla8] neurokinin A-(4-10)-peptide suggesting that the python cardiovascular system is associated with a receptor that resembles the mammalian NK1 receptor more closely than the NK2 receptor. Administration of the inhibitor of nitric oxide synthesis, L-nitro-arginine-methylester (L-NAME; 150 mg kg-1), resulted in a significant (P<0.05) increase in Psys as well as a decrease in Gsys, but no effect on Ppul and Gpul. Conversely, the nitric oxide donor, sodium nitroprusside (SNP; 60 microg kg-1) produced a significant (P<0.05) decrease in Psys along with an increase in Gsys and pulmonary blood flow. However, neither L-NAME nor indomethacin (10 mg kg-1) reduced the cardiovascular responses to NPgamma. Thus, nitric oxide is involved in regulation of basal vascular tone in the python, but neither nitric oxide nor prostaglandins mediate the vasodilatory action of NPgamma.

  11. Pybus -- A Python Software Bus

    SciTech Connect

    Lavrijsen, Wim T.L.P.

    2004-10-14

    A software bus, just like its hardware equivalent, allows for the discovery, installation, configuration, loading, unloading, and run-time replacement of software components, as well as channeling of inter-component communication. Python, a popular open-source programming language, encourages a modular design on software written in it, but it offers little or no component functionality. However, the language and its interpreter provide sufficient hooks to implement a thin, integral layer of component support. This functionality can be presented to the developer in the form of a module, making it very easy to use. This paper describes a Pythonmodule, PyBus, with which the concept of a ''software bus'' can be realized in Python. It demonstrates, within the context of the ATLAS software framework Athena, how PyBus can be used for the installation and (run-time) configuration of software, not necessarily Python modules, from a Python application in a way that is transparent to the end-user.

  12. Imagining a Stata / Python Combination

    NASA Technical Reports Server (NTRS)

    Fiedler, James

    2012-01-01

    There are occasions when a task is difficult in Stata, but fairly easy in a more general programming language. Python is a popular language for a range of uses. It is easy to use, has many high ]quality packages, and programs can be written relatively quickly. Is there any advantage in combining Stata and Python within a single interface? Stata already offers support for user-written programs, which allow extensive control over calculations, but somewhat less control over graphics. Also, except for specifying output, the user has minimal programmatic control over the user interface. Python can be used in a way that allows more control over the interface and graphics, and in so doing provide a roundabout method for satisfying some user requests (e.g., transparency levels in graphics and the ability to clear the results window). My talk will explore these ideas, present a possible method for combining Stata and Python, and give examples to demonstrate how this combination might be useful.

  13. Python in Astronomy 2016 Unproceedings

    NASA Astrophysics Data System (ADS)

    Robitaille, Thomas; Cruz, Kelle; Greenfield, Perry; Jeschke, Eric; Juric, Mario; Mumford, Stuart; Prescod-Weinstein, Chanda; Sosey, Megan; Tollerud, Erik; VanderPlas, Jake; Ford, Jes; Foreman-Mackey, Dan; Jenness, Tim; Aldcroft, Tom; Alexandersen, Mike; Bannister, Michele; Barbary, Kyle; Barentsen, Geert; Bennett, Samuel; Boquien, Médéric; Campos Rozo, Jose Ivan; Christe, Steven; Corrales, Lia; Craig, Matthew; Deil, Christoph; Dencheva, Nadia; Donath, Axel; Douglas, Stephanie; Ferreira, Leonardo; Ginsburg, Adam; Goldbaum, Nathan; Gordon, Karl; Hearin, Andrew; Hummels, Cameron; Huppenkothen, Daniela; Jennings, Elise; King, Johannes; Lawler, Samantha; Leonard, Andrew; Lim, Pey Lian; McBride, Lisa; Morris, Brett; Nunez, Carolina; Owen, Russell; Parejko, John; Patel, Ekta; Price-Whelan, Adrian; Ruggiero, Rafael; Sipocz, Brigitta; Stevens, Abigail; Turner, James; Tuttle, Sarah; Yanchulova Merica-Jones, Petia; Yoachim, Peter

    2016-03-01

    This document provides proceedings for unconference sessions as well as hacks/sprints which took place at the Python in Astronomy 2016 workshop, which was held at the University of Washington eScience Institute in Seattle from March 21st to 25th 2016.

  14. Pyomo : Python Optimization Modeling Objects.

    SciTech Connect

    Siirola, John; Laird, Carl Damon; Hart, William Eugene; Watson, Jean-Paul

    2010-11-01

    The Python Optimization Modeling Objects (Pyomo) package [1] is an open source tool for modeling optimization applications within Python. Pyomo provides an objected-oriented approach to optimization modeling, and it can be used to define symbolic problems, create concrete problem instances, and solve these instances with standard solvers. While Pyomo provides a capability that is commonly associated with algebraic modeling languages such as AMPL, AIMMS, and GAMS, Pyomo's modeling objects are embedded within a full-featured high-level programming language with a rich set of supporting libraries. Pyomo leverages the capabilities of the Coopr software library [2], which integrates Python packages (including Pyomo) for defining optimizers, modeling optimization applications, and managing computational experiments. A central design principle within Pyomo is extensibility. Pyomo is built upon a flexible component architecture [3] that allows users and developers to readily extend the core Pyomo functionality. Through these interface points, extensions and applications can have direct access to an optimization model's expression objects. This facilitates the rapid development and implementation of new modeling constructs and as well as high-level solution strategies (e.g. using decomposition- and reformulation-based techniques). In this presentation, we will give an overview of the Pyomo modeling environment and model syntax, and present several extensions to the core Pyomo environment, including support for Generalized Disjunctive Programming (Coopr GDP), Stochastic Programming (PySP), a generic Progressive Hedging solver [4], and a tailored implementation of Bender's Decomposition.

  15. Steering object-oriented computations with Python

    SciTech Connect

    Yang, T.-Y.B.; Dubois, P.F.; Furnish, G.; Beazley, D.M.

    1996-10-01

    We have described current approaches and future plans for steering C++ application, running Python on parallel platforms, and combination of Tk interface and Python interpreter in steering computations. In addition, there has been significant enhancement in the Gist module. Tk mega widgets has been implemented for a few physics applications. We have also written Python interface to SIJLO, a data storage package used as an interface to a visualization system named MeshTv. Python is being used to control large-scale simulations (molecular dynamics in particular) running on the CM-5 and T3D at LANL as well. A few other code development projects at LLNL are either using or considering Python as their steering shells. In summary, the merits of Python have been appreciated by more and more people in the scientific computation community.

  16. Computed tomography of ball pythons (Python regius) in curled recumbency.

    PubMed

    Hedley, Joanna; Eatwell, Kevin; Schwarz, Tobias

    2014-01-01

    Anesthesia and tube restraint methods are often required for computed tomography (CT) of snakes due to their natural tendency to curl up. However, these restraint methods may cause animal stress. The aim of this study was to determine whether the CT appearance of the lungs differs for ball pythons in a curled position vs. tube restraint. Whole body CT was performed on ten clinically healthy ball pythons, first in curled and then in straight positions restrained in a tube. Curved multiplanar reformatted (MPR) lung images from curled position scans were compared with standard MPR lung images from straight position scans. Lung attenuation and thickness were measured at three locations for each scan. Time for positioning and scanning was 12 ± 5 min shorter for curled snakes compared to tube restraint. Lung parenchyma thickness and attenuation declined from cranial to caudal on both straight and curled position images. Mean lung parenchyma thickness was greater in curled images at locations 1 (P = 0.048) and 3 (P = 0.044). Mean lung parenchyma thickness decreased between location 1 and 2 by 86-87% (straight: curled) and between location 1 and 3 by 51-50% (straight: curled). Mean lung attenuation at location 1 was significantly greater on curled position images than tube restraint images (P = 0.043). Findings indicated that CT evaluation of the lungs is feasible for ball pythons positioned in curled recumbency if curved MPR is available. However, lung parenchyma thickness and attenuation in some locations may vary from those acquired using tube restraint.

  17. Computed tomography for the diagnosis and treatment monitoring of bacterial pneumonia in Indian pythons (Python molurus).

    PubMed

    Pees, M; Kiefer, I; Oechtering, G; Krautwald-Junghanns, M-E

    2008-08-02

    Eight Indian pythons (Python molurus) with clinical and microbiological evidence of pneumonia were examined by computed tomography (ct) before and after treatment. The results were assessed subjectively and measurements were taken following a standard protocol. Changes in the lung tissue of all the pythons were diagnosed, and the extent of the disease could be assessed. ct examinations after treatment showed an improvement in the six pythons whose clinical condition had improved, but in the other two pythons they demonstrated the severity of the disease. The subjective assessments were superior to the evaluation of measurements of attenuation in regions of interest. However, the average and the maximum attenuation provided additional information on the extent of the disease. Except for one python with only mild clinical signs, the attenuation after successful treatment was still higher than in healthy pythons.

  18. Retroviral particles in neoplasms of Burmese pythons (Python molurus bivittatus).

    PubMed

    Chandra, A M; Jacobson, E R; Munn, R J

    2001-09-01

    Neoplastic diseases associated with retroviruses were diagnosed in four Burmese pythons (Python molurus bivattatus) from a single collection. Snake No. 1 was a 7-year-old female with recurrent undifferentiated mesenchymal round cell tumor (lymphosarcoma) of the oral cavity. At necropsy, similar neoplastic masses were evident in the uterus and ovary, and there was diffuse involvement of the spleen. Snake No. 2 was a 4.5-year-old female that was euthanatized because of complications following resection of a segmental colonic adenocarcinoma. Snake No. 3 was a 5-year-old female that was euthanatized because of a large transitional cell carcinoma of the right kidney. Snake No. 4 was a 19-year-old female that was euthanatized following recurrence of an intermandibular fibrosarcoma. Ultrastructural examination revealed few to numerous extracellular and intracellular (intravacuolar) type C-like retroviral particles in all tumors. Tumors were about 90-95 nm in diameter, with an electron-dense core and bilaminar external membrane. The relationship of the intraneoplastic viral particles to the etiology of the tumors is uncertain.

  19. A field test of attractant traps for invasive Burmese pythons (Python molurus bivittatus) in southern Florida

    USGS Publications Warehouse

    Reed, R.N.; Hart, K.M.; Rodda, G.H.; Mazzotti, F.J.; Snow, R.W.; Cherkiss, M.; Rozar, R.; Goetz, S.

    2011-01-01

    Context. Invasive Burmese pythons (Python molurus bivittatus) are established over thousands of square kilometres of southern Florida, USA, and consume a wide range of native vertebrates. Few tools are available to control the python population, and none of the available tools have been validated in the field to assess capture success as a proportion of pythons available to be captured. Aims. Our primary aim was to conduct a trap trial for capturing invasive pythons in an area east of Everglades National Park, where many pythons had been captured in previous years, to assess the efficacy of traps for population control.Wealso aimed to compare results of visual surveys with trap capture rates, to determine capture rates of non-target species, and to assess capture rates as a proportion of resident pythons in the study area. Methods.Weconducted a medium-scale (6053 trap nights) experiment using two types of attractant traps baited with live rats in the Frog Pond area east of Everglades National Park.Wealso conducted standardised and opportunistic visual surveys in the trapping area. Following the trap trial, the area was disc harrowed to expose pythons and allow calculation of an index of the number of resident pythons. Key results. We captured three pythons and 69 individuals of various rodent, amphibian, and reptile species in traps. Eleven pythons were discovered during disc harrowing operations, as were large numbers of rodents. Conclusions. The trap trial captured a relatively small proportion of the pythons that appeared to be present in the study area, although previous research suggests that trap capture rates improve with additional testing of alternative trap designs. Potential negative impacts to non-target species were minimal. Low python capture rates may have been associated with extremely high local prey abundances during the trap experiment. Implications. Results of this trial illustrate many of the challenges in implementing and interpreting results

  20. Parallel, Distributed Scripting with Python

    SciTech Connect

    Miller, P J

    2002-05-24

    Parallel computers used to be, for the most part, one-of-a-kind systems which were extremely difficult to program portably. With SMP architectures, the advent of the POSIX thread API and OpenMP gave developers ways to portably exploit on-the-box shared memory parallelism. Since these architectures didn't scale cost-effectively, distributed memory clusters were developed. The associated MPI message passing libraries gave these systems a portable paradigm too. Having programmers effectively use this paradigm is a somewhat different question. Distributed data has to be explicitly transported via the messaging system in order for it to be useful. In high level languages, the MPI library gives access to data distribution routines in C, C++, and FORTRAN. But we need more than that. Many reasonable and common tasks are best done in (or as extensions to) scripting languages. Consider sysadm tools such as password crackers, file purgers, etc ... These are simple to write in a scripting language such as Python (an open source, portable, and freely available interpreter). But these tasks beg to be done in parallel. Consider the a password checker that checks an encrypted password against a 25,000 word dictionary. This can take around 10 seconds in Python (6 seconds in C). It is trivial to parallelize if you can distribute the information and co-ordinate the work.

  1. Development of hemipenes in the ball python snake Python regius.

    PubMed

    Leal, Francisca; Cohn, Martin J

    2015-01-01

    Within amniotes, external copulatory organs have undergone extensive morphological diversification. One of the most extreme examples is squamate (lizards and snakes) hemipenes, which are paired copulatory organs that extend from the lateral margins of the cloaca. Here, we describe the development of hemipenes in a basal snake, the ball python (Python regius). Snake hemipenes arise as a pair of lateral swellings on either side of the caudal part of the cloaca, and these paired outgrowths persist to form the left and right hemipenes. In non-squamate amniotes, external genitalia form from paired swellings that arise on the anterior side of the cloaca, which then fuse medially to form a single genital tubercle, the anlagen of the penis or clitoris. Whereas in non-squamate amniotes, Sonic hedgehog (Shh)-expressing cells of the cloacal endoderm form the urethral or sulcus epithelium and are required for phallus outgrowth, the hemipenes of squamates lack an endodermal contribution, and the sulcus does not express Shh. Thus, snake hemipenes differ from the genital tubercles of non-squamate amniotes both in their embryonic origins and in at least part of patterning mechanisms, which raises the possibility that hemipenes may not be direct homologs of the unpaired amniote penis. Nonetheless, we find that some developmental genes show similar expression patterns in snake hemipenes buds and non-squamate genital tubercles, suggesting that homologous developmental mechanisms are involved in aspects of external genital development across amniotes, even when these structures may have different developmental origins and may have arisen independently during evolution.

  2. Reflection-Based Python-C++ Bindings

    SciTech Connect

    Generowicz, Jacek; Lavrijsen, Wim T.L.P.; Marino, Massimo; Mato, Pere

    2004-10-14

    Python is a flexible, powerful, high-level language with excellent interactive and introspective capabilities and a very clean syntax. As such, it can be a very effective tool for driving physics analysis. Python is designed to be extensible in low-level C-like languages, and its use as a scientific steering language has become quite widespread. To this end, existing and custom-written C or C++ libraries are bound to the Python environment as so-called extension modules. A number of tools for easing the process of creating such bindings exist, such as SWIG and Boost. Python. Yet, the process still requires a considerable amount of effort and expertise. The C++ language has few built-in introspective capabilities, but tools such as LCGDict and CINT add this by providing so-called dictionaries: libraries that contain information about the names, entry points, argument types, etc. of other libraries. The reflection information from these dictionaries can be used for the creation of bindings and so the process can be fully automated, as dictionaries are already provided for many end-user libraries for other purposes, such as object persistency. PyLCGDict is a Python extension module that uses LCG dictionaries, as PyROOT uses CINT reflection information, to allow /cwPython users to access C++ libraries with essentially no preparation on the users' behalf. In addition, and in a similar way, PyROOT gives ROOT users access to Python libraries.

  3. Python based high-level synthesis compiler

    NASA Astrophysics Data System (ADS)

    Cieszewski, Radosław; Pozniak, Krzysztof; Romaniuk, Ryszard

    2014-11-01

    This paper presents a python based High-Level synthesis (HLS) compiler. The compiler interprets an algorithmic description of a desired behavior written in Python and map it to VHDL. FPGA combines many benefits of both software and ASIC implementations. Like software, the mapped circuit is flexible, and can be reconfigured over the lifetime of the system. FPGAs therefore have the potential to achieve far greater performance than software as a result of bypassing the fetch-decode-execute operations of traditional processors, and possibly exploiting a greater level of parallelism. Creating parallel programs implemented in FPGAs is not trivial. This article describes design, implementation and first results of created Python based compiler.

  4. Python-CPL: Python interface for the ESO Common Pipeline Library

    NASA Astrophysics Data System (ADS)

    Streicher, O.

    2016-12-01

    Python-CPL is a framework to configure and execute pipeline recipes written with the Common Pipeline Library (CPL) (ascl:1402.010) with Python2 or Python3. The input, calibration and output data can be specified as FITS files or as astropy.io.fits objects in memory. The package is used to implement the MUSE pipeline in the AstroWISE data management system.

  5. Python-Based Applications for Hydrogeological Modeling

    NASA Astrophysics Data System (ADS)

    Khambhammettu, P.

    2013-12-01

    Python is a general-purpose, high-level programming language whose design philosophy emphasizes code readability. Add-on packages supporting fast array computation (numpy), plotting (matplotlib), scientific /mathematical Functions (scipy), have resulted in a powerful ecosystem for scientists interested in exploratory data analysis, high-performance computing and data visualization. Three examples are provided to demonstrate the applicability of the Python environment in hydrogeological applications. Python programs were used to model an aquifer test and estimate aquifer parameters at a Superfund site. The aquifer test conducted at a Groundwater Circulation Well was modeled with the Python/FORTRAN-based TTIM Analytic Element Code. The aquifer parameters were estimated with PEST such that a good match was produced between the simulated and observed drawdowns. Python scripts were written to interface with PEST and visualize the results. A convolution-based approach was used to estimate source concentration histories based on observed concentrations at receptor locations. Unit Response Functions (URFs) that relate the receptor concentrations to a unit release at the source were derived with the ATRANS code. The impact of any releases at the source could then be estimated by convolving the source release history with the URFs. Python scripts were written to compute and visualize receptor concentrations for user-specified source histories. The framework provided a simple and elegant way to test various hypotheses about the site. A Python/FORTRAN-based program TYPECURVEGRID-Py was developed to compute and visualize groundwater elevations and drawdown through time in response to a regional uniform hydraulic gradient and the influence of pumping wells using either the Theis solution for a fully-confined aquifer or the Hantush-Jacob solution for a leaky confined aquifer. The program supports an arbitrary number of wells that can operate according to arbitrary schedules. The

  6. Julia and Python in Astronomy: Better Together

    NASA Astrophysics Data System (ADS)

    Barbary, Kyle

    2016-03-01

    Astronomers love Python because it is open source, easy to learn, and has a tremendous ecosystem for scientific computing. The Julia programming language has many of those same characteristics. In this talk, I'll discuss the use of Julia in astronomy and the growing ecosystem of astronomy packages, particularly those managed by the JuliaAstro organization (http://JuliaAstro.github.io). Most importantly, I will highlight some areas ripe for collaboration between Python and Julia developers in astronomy.

  7. A Python Geospatial Language Toolkit

    NASA Astrophysics Data System (ADS)

    Fillmore, D.; Pletzer, A.; Galloy, M.

    2012-12-01

    The volume and scope of geospatial data archives, such as collections of satellite remote sensing or climate model products, has been rapidly increasing and will continue to do so in the near future. The recently launched (October 2011) Suomi National Polar-orbiting Partnership satellite (NPP) for instance, is the first of a new generation of Earth observation platforms that will monitor the atmosphere, oceans, and ecosystems, and its suite of instruments will generate several terabytes each day in the form of multi-spectral images and derived datasets. Full exploitation of such data for scientific analysis and decision support applications has become a major computational challenge. Geophysical data exploration and knowledge discovery could benefit, in particular, from intelligent mechanisms for extracting and manipulating subsets of data relevant to the problem of interest. Potential developments include enhanced support for natural language queries and directives to geospatial datasets. The translation of natural language (that is, human spoken or written phrases) into complex but unambiguous objects and actions can be based on a context, or knowledge domain, that represents the underlying geospatial concepts. This poster describes a prototype Python module that maps English phrases onto basic geospatial objects and operations. This module, along with the associated computational geometry methods, enables the resolution of natural language directives that include geographic regions of arbitrary shape and complexity.

  8. The Python Interface to Antelope and Applications

    NASA Astrophysics Data System (ADS)

    Lindquist, K. G.; Clemesha, A.; Newman, R. L.; Vernon, F. L.

    2008-12-01

    The Antelope Environmental Monitoring System from Boulder Real-Time Technologies, Inc. (http://www.brtt.com) is widely used for acquiring, processing, distributing, and archiving near-real-time monitoring data, especially in seismological networks. We have contributed a new Python interface to the Antelope toolkit, paralleling other commercial and open-source language interfaces in Matlab, PHP, TCL/Tk, and C. The Python programming language (http://www.python.org) is well suited both to scientific computing applications and to interactive web-based applications. In the latter, Python serves as the programming interface through which to connect to standardized open-source frameworks. Community development of these frameworks has advanced in parallel with cross-browser standardization and increasing broadband data transfer rates, making web-based applications the defacto standard for platform-agnostic access to large, heterogeneous datasets. These web-based solutions are starting to mirror some of the capabilities of standard desktop-based applications. We describe the functionality of the new Python interface to Antelope, applications of the interface to the interactive exploration of time-series data on the web using the Twisted open-source framework, and web-based prototype tools developed for the Earthscope Array Network Facility to provide community access to network monitoring and seismic event datasets.

  9. SunPy—Python for solar physics

    NASA Astrophysics Data System (ADS)

    SunPy Community; Mumford, Stuart J.; Christe, Steven; Pérez-Suárez, David; Ireland, Jack; Shih, Albert Y.; Inglis, Andrew R.; Liedtke, Simon; Hewett, Russell J.; Mayer, Florian; Hughitt, Keith; Freij, Nabil; Meszaros, Tomas; Bennett, Samuel M.; Malocha, Michael; Evans, John; Agrawal, Ankit; Leonard, Andrew J.; Robitaille, Thomas P.; Mampaey, Benjamin; Campos-Rozo, Jose Iván; Kirk, Michael S.

    2015-01-01

    This paper presents SunPy (version 0.5), a community-developed Python package for solar physics. Python, a free, cross-platform, general-purpose, high-level programming language, has seen widespread adoption among the scientific community, resulting in the availability of a large number of software packages, from numerical computation (NumPy, SciPy) and machine learning (scikit-learn) to visualization and plotting (matplotlib). SunPy is a data-analysis environment specializing in providing the software necessary to analyse solar and heliospheric data in Python. SunPy is open-source software (BSD licence) and has an open and transparent development workflow that anyone can contribute to. SunPy provides access to solar data through integration with the Virtual Solar Observatory (VSO), the Heliophysics Event Knowledgebase (HEK), and the HELiophysics Integrated Observatory (HELIO) webservices. It currently supports image data from major solar missions (e.g., SDO, SOHO, STEREO, and IRIS), time-series data from missions such as GOES, SDO/EVE, and PROBA2/LYRA, and radio spectra from e-Callisto and STEREO/SWAVES. We describe SunPy's functionality, provide examples of solar data analysis in SunPy, and show how Python-based solar data-analysis can leverage the many existing tools already available in Python. We discuss the future goals of the project and encourage interested users to become involved in the planning and development of SunPy.

  10. Gist: A scientific graphics package for Python

    SciTech Connect

    Busby, L.E.

    1996-05-08

    {open_quotes}Gist{close_quotes} is a scientific graphics library written by David H. Munro of Lawrence Livermore National Laboratory (LLNL). It features support for three common graphics output devices: X Windows, (Color) PostScript, and ANSI/ISO Standard Computer Graphics Metafiles (CGM). The library is small (written directly to Xlib), portable, efficient, and full-featured. It produces X versus Y plots with {open_quotes}good{close_quotes} tick marks and tick labels, 2-dimensional quadrilateral mesh plots with contours, vector fields, or pseudo color maps on such meshes, with 3-dimensional plots on the way. The Python Gist module utilizes the new {open_quotes}Numeric{close_quotes} module due to J. Hugunin and others. It is therefore fast and able to handle large datasets. The Gist module includes an X Windows event dispatcher which can be dynamically added (e.g., via importing a dynamically loaded module) to the Python interpreter after a simple two-line modification to the Python core. This makes fast mouse-controlled zoom, pan, and other graphic operations available to the researcher while maintaining the usual Python command-line interface. Munro`s Gist library is already freely available. The Python Gist module is currently under review and is also expected to qualify for unlimited release.

  11. Building a programmable interface for physics codes using numeric python

    SciTech Connect

    Yang, T.-Y.B.; Dubois, P.F.; Motteler, Z.C.

    1996-04-16

    With its portability, ease to add built-in functions and objects in C, and fast array facility among many other features, Python proved to be an excellent language for creating programmable scientific applications. In addition to the two modules presented, there are also other progresses at LLNL in using Python. For example, Python interfaces are being developed for at least three graphics packages, and Python interpreter and applications have been built on distributed platforms such as meiko and Cray T3D.

  12. Cosmic Microwave Background Anisotropy: Python V Results

    NASA Astrophysics Data System (ADS)

    Coble, K.; Dragovan, M.; Kovac, J.; Halverson, N. W.; Holzapfel, W. L.; Knox, L.; Dodelson, S.; Ganga, K.; Peterson, J. B.; Alvarez, D.; Griffin, G.; Newcomb, M.; Miller, K.; Platt, S. R.; Novak, G.

    1999-05-01

    Observations of the microwave sky using the Python telescope in its fifth season of operation at the Amundsen-Scott South Pole Station in Antarctica are presented. The system consists of a 0.75 m off-axis telescope instrumented with a HEMT amplifier-based radiometer having continuum sensitivity from 37-45 GHz in two frequency bands. With a 0.91 x 1.02 deg beam the instrument fully sampled 598 deg(2) of sky, including fields measured during the previous four seasons of Python observations. Interpreting the observed fluctuations as anisotropy in the cosmic microwave background, we place constraints on the angular power spectrum of fluctuations in multipole bands up to l ~ 260. The observed spectrum is consistent with both the COBE experiment and previous Python results. There is no significant contamination from known foregrounds. The results show a discernible rise in the angular power spectrum from large (l ~ 40) to small (l ~ 200) angular scales.

  13. Python for large-scale electrophysiology.

    PubMed

    Spacek, Martin; Blanche, Tim; Swindale, Nicholas

    2008-01-01

    Electrophysiology is increasingly moving towards highly parallel recording techniques which generate large data sets. We record extracellularly in vivo in cat and rat visual cortex with 54-channel silicon polytrodes, under time-locked visual stimulation, from localized neuronal populations within a cortical column. To help deal with the complexity of generating and analysing these data, we used the Python programming language to develop three software projects: one for temporally precise visual stimulus generation ("dimstim"); one for electrophysiological waveform visualization and spike sorting ("spyke"); and one for spike train and stimulus analysis ("neuropy"). All three are open source and available for download (http://swindale.ecc.ubc.ca/code). The requirements and solutions for these projects differed greatly, yet we found Python to be well suited for all three. Here we present our software as a showcase of the extensive capabilities of Python in neuroscience.

  14. A field test of attractant traps for invasive Burmese pythons (Python molurus bivittatus) in southern Florida

    USGS Publications Warehouse

    Reed, Robert N.; Hart, Kristen M.; Rodda, Gordon H.; Mazzotti, Frank J.; Snow, Ray W.; Cherkiss, Michael; Rozar, Rondald; Goetz, Scott

    2011-01-01

    Conclusions: The trap trial captured a relatively small proportion of the pythons that appeared to be present in the study area, although previous research suggests that trap capture rates improve with additional testing of alternative trap designs. Potential negative impacts to non-target species were minimal. Low python capture rates may have been associated with extremely high local prey abundances during the trap experiment. Implications: Results of this trial illustrate many of the challenges in implementing and interpreting results from tests of control tools for large cryptic predators such as Burmese pythons.

  15. Hemodynamic consequences of cardiac malformations in two juvenile ball pythons (Python regius).

    PubMed

    Jensen, Bjarke; Wang, Tobias

    2009-12-01

    Two cases of bifid ventricles and cardiac malformations in juvenile ball python (Python regius) were investigated by blood pressure measurements and macro- and microscopic sectioning. A study of a normal ball python was included for reference. In both cases, all cardiac chambers were enlarged and abnormally shaped. Internal assessment of the ventricles revealed a pronounced defect of the muscular ridge, which normally is responsible for separating the systemic and pulmonary circuits. Consistent with the small muscular ridge, systolic pressures were identical in the pulmonary and systemic arteries, but, the snakes, nevertheless, lived to reach body weights severalfold of their hatchling weight.

  16. Consumption of bird eggs by invasive Burmese Pythons in Florida

    USGS Publications Warehouse

    Dove, Carla J.; Reed, Robert N.; Snow, Ray W.

    2012-01-01

    Burmese Pythons (Python molurus bivittatus or P. bivittatus) have been reported to consume 25 species of adult birds in Everglades National Park, Florida (Dove et al. 2011), but until now no records documented this species eating bird eggs. Here we report three recent cases of bird-egg consumption by Burmese Pythons and discuss egg-eating in basal snakes.

  17. THE PYTHON SHELL FOR THE ORBIT CODE

    SciTech Connect

    Shishlo, Andrei P; Gorlov, Timofey V; Holmes, Jeffrey A

    2009-01-01

    A development of a Python driver shell for the ORBIT simulation code is presented. The original ORBIT code uses the SuperCode shell to organize accelerator-related simulations. It is outdated, unsupported, and it is an obstacle to future code development. The necessity and consequences of replacing the old shell language are discussed. A set of core modules and extensions that are currently in PyORBIT are presented. They include particle containers, parsers for MAD and SAD lattice files, a Python wrapper for MPI libraries, space charge calculators, TEAPOT trackers, and a laser stripping extension module.

  18. Physiology: postprandial cardiac hypertrophy in pythons.

    PubMed

    Andersen, Johnnie B; Rourke, Bryan C; Caiozzo, Vincent J; Bennett, Albert F; Hicks, James W

    2005-03-03

    Oxygen consumption by carnivorous reptiles increases enormously after they have eaten a large meal in order to meet metabolic demands, and this places an extra load on the cardiovascular system. Here we show that there is an extraordinarily rapid 40% increase in ventricular muscle mass in Burmese pythons (Python molurus) a mere 48 hours after feeding, which results from increased gene expression of muscle-contractile proteins. As this fully reversible hypertrophy occurs naturally, it could provide a useful model for investigating the mechanisms that lead to cardiac growth in other animals.

  19. SymPy: symbolic computing in Python

    DOE PAGES

    Meurer, Aaron; Smith, Christopher P.; Paprocki, Mateusz; ...

    2017-01-02

    SymPy is an open source computer algebra system written in pure Python. It is built with a focus on extensibility and ease of use, through both interactive and programmatic applications. These characteristics have led SymPy to become a popular symbolic library for the scientific Python ecosystem. This paper presents the architecture of SymPy, a description of its features, and a discussion of select submodules. The supplementary material provide additional examples and further outline details of the architecture and features of SymPy.

  20. The zoonotic implications of pentastomiasis in the royal python (python regius).

    PubMed

    Ayinmode, Ab; Adedokun, Ao; Aina, A; Taiwo, V

    2010-09-01

    Pentastomes are worm-like endoparasites of the phylum Pentastomida found principally in the respiratory tract of reptiles, birds, and mammals. They cause a zoonotic disease known as pentastomiasis in humans and other mammals. The autopsy of a Nigerian royal python (Python regius) revealed two yellowish-white parasites in the lungs, tissue necrosis and inflammatory lesions. The parasite was confirmed to be Armillifer spp (Pentastomid); this is the first recorded case of pentastomiasis in the royal python (Python regius) in Nigeria. This report may be an alert of the possibility of on-going zoonotic transmission of pentastomiasis from snake to man, especially in the sub-urban/rural areas of Nigeria and other West African countries where people consume snake meat.

  1. PyXNAT: XNAT in Python

    PubMed Central

    Schwartz, Yannick; Barbot, Alexis; Thyreau, Benjamin; Frouin, Vincent; Varoquaux, Gaël; Siram, Aditya; Marcus, Daniel S.; Poline, Jean-Baptiste

    2012-01-01

    As neuroimaging databases grow in size and complexity, the time researchers spend investigating and managing the data increases to the expense of data analysis. As a result, investigators rely more and more heavily on scripting using high-level languages to automate data management and processing tasks. For this, a structured and programmatic access to the data store is necessary. Web services are a first step toward this goal. They however lack in functionality and ease of use because they provide only low-level interfaces to databases. We introduce here PyXNAT, a Python module that interacts with The Extensible Neuroimaging Archive Toolkit (XNAT) through native Python calls across multiple operating systems. The choice of Python enables PyXNAT to expose the XNAT Web Services and unify their features with a higher level and more expressive language. PyXNAT provides XNAT users direct access to all the scientific packages in Python. Finally PyXNAT aims to be efficient and easy to use, both as a back-end library to build XNAT clients and as an alternative front-end from the command line. PMID:22654752

  2. SymPy: Symbolic computing in python

    SciTech Connect

    Muller, Richard P.; Meurer, Aaron; Certik, Ondrej; Moore, Jason K.; Bonazzi, Francesco; Vats, Shivam; Kumar, Amit; Gupta, Harsh; Fernando, Isuru; Saboo, Ashutosh; Singh, Sartaj; Johansson, Fredrik; Rathnayake, Thilina; Pedregosa, Fabian; Scopatz, Anthony; Granger, Brian E.; Cimrman, Robert

    2016-05-01

    Here, SymPy is a full featured computer algebra system (CAS) written in the Python programming language. It is open source, being licensed under the extremely permissive 3-clause BSD license. SymPy was started by Ondrej Certik in 2005, and it has since grown into a large open source project, with over 500 contributors.

  3. A Gene Ontology Tutorial in Python.

    PubMed

    Vesztrocy, Alex Warwick; Dessimoz, Christophe

    2017-01-01

    This chapter is a tutorial on using Gene Ontology resources in the Python programming language. This entails querying the Gene Ontology graph, retrieving Gene Ontology annotations, performing gene enrichment analyses, and computing basic semantic similarity between GO terms. An interactive version of the tutorial, including solutions, is available at http://gohandbook.org .

  4. Osteosarcoma in a woma python (Aspidites ramsayi).

    PubMed

    Cowan, M L; Monks, D J; Raidal, S R

    2011-12-01

    Osteosarcoma of the axial skeleton in an 18-month-old woma python (Aspidites ramsayi) is described. A subcutaneous mass overlying the costal arches enlarged progressively over a period of 5 months and, in that time, became ulcerated and more invasive of surrounding tissues. A punch biopsy of the lesion under general anaesthesia provided tissue for histopathology and diagnosis of low-grade osteosarcoma.

  5. SymPy: Symbolic computing in python

    DOE PAGES

    Muller, Richard P.; Meurer, Aaron; Certik, Ondrej; ...

    Here, SymPy is a full featured computer algebra system (CAS) written in the Python programming language. It is open source, being licensed under the extremely permissive 3-clause BSD license. SymPy was started by Ondrej Certik in 2005, and it has since grown into a large open source project, with over 500 contributors.

  6. Python scripting in the nengo simulator.

    PubMed

    Stewart, Terrence C; Tripp, Bryan; Eliasmith, Chris

    2009-01-01

    Nengo (http://nengo.ca) is an open-source neural simulator that has been greatly enhanced by the recent addition of a Python script interface. Nengo provides a wide range of features that are useful for physiological simulations, including unique features that facilitate development of population-coding models using the neural engineering framework (NEF). This framework uses information theory, signal processing, and control theory to formalize the development of large-scale neural circuit models. Notably, it can also be used to determine the synaptic weights that underlie observed network dynamics and transformations of represented variables. Nengo provides rich NEF support, and includes customizable models of spike generation, muscle dynamics, synaptic plasticity, and synaptic integration, as well as an intuitive graphical user interface. All aspects of Nengo models are accessible via the Python interface, allowing for programmatic creation of models, inspection and modification of neural parameters, and automation of model evaluation. Since Nengo combines Python and Java, it can also be integrated with any existing Java or 100% Python code libraries. Current work includes connecting neural models in Nengo with existing symbolic cognitive models, creating hybrid systems that combine detailed neural models of specific brain regions with higher-level models of remaining brain areas. Such hybrid models can provide (1) more realistic boundary conditions for the neural components, and (2) more realistic sub-components for the larger cognitive models.

  7. Size, but not experience, affects the ontogeny of constriction performance in ball pythons (Python regius).

    PubMed

    Penning, David A; Dartez, Schuyler F

    2016-03-01

    Constriction is a prey-immobilization technique used by many snakes and is hypothesized to have been important to the evolution and diversification of snakes. However, very few studies have examined the factors that affect constriction performance. We investigated constriction performance in ball pythons (Python regius) by evaluating how peak constriction pressure is affected by snake size, sex, and experience. In one experiment, we tested the ontogenetic scaling of constriction performance and found that snake diameter was the only significant factor determining peak constriction pressure. The number of loops applied in a coil and its interaction with snake diameter did not significantly affect constriction performance. Constriction performance in ball pythons scaled differently than in other snakes that have been studied, and medium to large ball pythons are capable of exerting significantly higher pressures than those shown to cause circulatory arrest in prey. In a second experiment, we tested the effects of experience on constriction performance in hatchling ball pythons over 10 feeding events. By allowing snakes in one test group to gain constriction experience, and manually feeding snakes under sedation in another test group, we showed that experience did not affect constriction performance. During their final (10th) feedings, all pythons constricted similarly and with sufficiently high pressures to kill prey rapidly. At the end of the 10 feeding trials, snakes that were allowed to constrict were significantly smaller than their non-constricting counterparts.

  8. Challenges to a molecular approach to prey identification in the Burmese python, Python molurus bivittatus

    USGS Publications Warehouse

    Falk, Bryan; Reed, Robert N.

    2015-01-01

    Molecular approaches to prey identification are increasingly useful in elucidating predator–prey relationships, and we aimed to investigate the feasibility of these methods to document the species identities of prey consumed by invasive Burmese pythons in Florida. We were particularly interested in the diet of young snakes, because visual identification of prey from this size class has proven difficult. We successfully extracted DNA from the gastrointestinal contents of 43 young pythons, as well as from several control samples, and attempted amplification of DNA mini-barcodes, a 130-bp region of COX1. Using a PNA clamp to exclude python DNA, we found that prey DNA was not present in sufficient quality for amplification of this locus in 86% of our samples. All samples from the GI tracts of young pythons contained only hair, and the six samples we were able to identify to species were hispid cotton rats. This suggests that young Burmese pythons prey predominantly on small mammals and that prey diversity among snakes of this size class is low. We discuss prolonged gastrointestinal transit times and extreme gastric breakdown as possible causes of DNA degradation that limit the success of a molecular approach to prey identification in Burmese pythons

  9. PythonTeX: reproducible documents with LaTeX, Python, and more

    NASA Astrophysics Data System (ADS)

    Poore, Geoffrey M.

    2015-01-01

    PythonTeX is a LaTeX package that allows Python code in LaTeX documents to be executed and provides access to the output. This makes possible reproducible documents that combine results with the code required to generate them. Calculations and figures may be next to the code that created them. Since code is adjacent to its output in the document, editing may be more efficient. Since code output may be accessed programmatically in the document, copy-and-paste errors are avoided and output is always guaranteed to be in sync with the code that generated it. This paper provides an introduction to PythonTeX and an overview of major features, including performance optimizations, debugging tools, and dependency tracking. Several complete examples are presented. Finally, advanced features are summarized. Though PythonTeX was designed for Python, it may be extended to support additional languages; support for the Ruby and Julia languages is already included. PythonTeX contains a utility for converting documents into plain LaTeX, suitable for format conversion, sharing, and journal submission.

  10. Challenges to a molecular approach to prey identification in the Burmese python, Python molurus bivittatus.

    PubMed

    Falk, Bryan G; Reed, Robert N

    2015-01-01

    Molecular approaches to prey identification are increasingly useful in elucidating predator-prey relationships, and we aimed to investigate the feasibility of these methods to document the species identities of prey consumed by invasive Burmese pythons in Florida. We were particularly interested in the diet of young snakes, because visual identification of prey from this size class has proven difficult. We successfully extracted DNA from the gastrointestinal contents of 43 young pythons, as well as from several control samples, and attempted amplification of DNA mini-barcodes, a 130-bp region of COX1. Using a PNA clamp to exclude python DNA, we found that prey DNA was not present in sufficient quality for amplification of this locus in 86% of our samples. All samples from the GI tracts of young pythons contained only hair, and the six samples we were able to identify to species were hispid cotton rats. This suggests that young Burmese pythons prey predominantly on small mammals and that prey diversity among snakes of this size class is low. We discuss prolonged gastrointestinal transit times and extreme gastric breakdown as possible causes of DNA degradation that limit the success of a molecular approach to prey identification in Burmese pythons.

  11. Evidence that neurotensin mediates postprandial intestinal hyperemia in the python, Python regius.

    PubMed

    Skovgaard, Nini; Conlon, J Michael; Wang, Tobias

    2007-09-01

    Digestion of large meals in pythons produces substantial increases in heart rate and cardiac output, as well as a dilation of the mesenteric vascular bed leading to intestinal hyperemia, but the mediators of these effects are unknown. Bolus intra-arterial injections of python neurotensin ([His(3), Val(4), Ala(7)]NT) (1 - 1,000 pmol/kg) into the anesthetized ball python Python regius (n = 7) produced a dose-dependent vasodilation that was associated with a decrease in systemic pressure (P(sys)) and increase in systemic blood flow (Q(sys)). There was no effect on pulmonary pressure and conductance. A significant (P < 0.05) increase in heart rate (f(H)) and total cardiac output (Q(tot)) was seen only at high doses (>30 pmol/kg). The systemic vasodilation and increase in Q(tot) persisted after beta-adrenergic blockade with propranolol, but the rise in f(H) was abolished. Also, the systemic vasodilation persisted after histamine H(2)-receptor blockade. In unanesthetized pythons (n = 4), bolus injection of python NT in a dose as low as 1 pmol/kg produced a significant increase in blood flow to the mesenteric artery (177% +/- 54%; mean +/- SE) and mesenteric conductance (219% +/- 74%) without any increase in Q(sys), systemic conductance, P(sys), and f(H). The data provide evidence that NT is an important hormonal mediator of postprandial intestinal hyperemia in the python, but its involvement in mediating the cardiac responses to digestion may be relatively minor.

  12. Experimentally derived salinity tolerance of hatchling Burmese pythons (Python molurus bivittatus) from the Everglades, Florida (USA)

    USGS Publications Warehouse

    Hart, Kristen M.; Schofield, Pamela J.; Gregoire, Denise R.

    2012-01-01

    In a laboratory setting, we tested the ability of 24 non-native, wild-caught hatchling Burmese pythons (Python molurus bivittatus) collected in the Florida Everglades to survive when given water containing salt to drink. After a one-month acclimation period in the laboratory, we grouped snakes into three treatments, giving them access to water that was fresh (salinity of 0, control), brackish (salinity of 10), or full-strength sea water (salinity of 35). Hatchlings survived about one month at the highest marine salinity and about five months at the brackish-water salinity; no control animals perished during the experiment. These results are indicative of a "worst-case scenario", as in the laboratory we denied access to alternate fresh-water sources that may be accessible in the wild (e.g., through rainfall). Therefore, our results may underestimate the potential of hatchling pythons to persist in saline habitats in the wild. Because of the effect of different salinity regimes on survival, predictions of ultimate geographic expansion by non-native Burmese pythons that consider salt water as barriers to dispersal for pythons may warrant re-evaluation, especially under global climate change and associated sea-level-rise scenarios.

  13. Experimentally derived salinity tolerance of hatchling Burmese pythons (Python molurus bivittatus) from the Everglades, Florida (USA)

    USGS Publications Warehouse

    Hart, K.M.; Schofield, P.J.; Gregoire, D.R.

    2012-01-01

    In a laboratory setting, we tested the ability of 24 non-native, wild-caught hatchling Burmese pythons (Python molurus bivittatus) collected in the Florida Everglades to survive when given water containing salt to drink. After a one-month acclimation period in the laboratory, we grouped snakes into three treatments, giving them access to water that was fresh (salinity of 0, control), brackish (salinity of 10), or full-strength sea water (salinity of 35). Hatchlings survived about one month at the highest marine salinity and about five months at the brackish-water salinity; no control animals perished during the experiment. These results are indicative of a "worst-case scenario", as in the laboratory we denied access to alternate fresh-water sources that may be accessible in the wild (e.g., through rainfall). Therefore, our results may underestimate the potential of hatchling pythons to persist in saline habitats in the wild. Because of the effect of different salinity regimes on survival, predictions of ultimate geographic expansion by non-native Burmese pythons that consider salt water as barriers to dispersal for pythons may warrant re-evaluation, especially under global climate change and associated sea-level-rise scenarios. ?? 2011.

  14. Matched regulation of gastrointestinal performance in the Burmese python, Python molurus.

    PubMed

    Cox, Christian L; Secor, Stephen M

    2008-04-01

    In Burmese pythons fasting and feeding cause dramatic regulation of gastric acid production and intestinal nutrient uptake. Predictably, other components of their gastrointestinal tract are similarly regulated with each meal. We therefore assessed the matched regulation of gastrointestinal performance by comparing the postprandial activities and capacities of gastric (pepsin), pancreatic (amylase and trypsin) and intestinal (aminopeptidase-N and maltase) enzymes, and intestinal nutrient uptake. Tissue samples were collected from pythons fasted and at 0.25, 0.5, 1, 2, 3, 4, 6, 10 and 15 days following their consumption of rodent meals equaling 25% of snake body mass. With feeding, pythons experience no significant change in stomach mass, whereas both the pancreas and small intestine doubled in mass. Feeding also triggered a depletion of gastric mucosal pepsinogen, a respective 5.7- and 20-fold increase in the peak activities of pancreatic trypsin and amylase, and a respective 2.3- and 5.5-fold increase in the peak activities of intestinal maltase and aminopeptidase-N. Enzyme activities peaked between 2 and 4 days postfeeding and returned to fasting levels by day 10. Independent of digestive stage, python intestine exhibited a proximal to distal decline in enzyme activity. For both sugars and proteins, intestinal capacities for enzyme activity were significantly correlated with nutrient uptake capacities. The concomitant postprandial upregulation of tissue morphology, intestinal nutrient transport rates and enzyme activities illustrate, for the python, the matched regulation of their gastrointestinal performance with each meal.

  15. Ball Python Nidovirus: a Candidate Etiologic Agent for Severe Respiratory Disease in Python regius

    PubMed Central

    Stenglein, Mark D.; Jacobson, Elliott R.; Wozniak, Edward J.; Wellehan, James F. X.; Kincaid, Anne; Gordon, Marcus; Porter, Brian F.; Baumgartner, Wes; Stahl, Scott; Kelley, Karen; Towner, Jonathan S.

    2014-01-01

    ABSTRACT A severe, sometimes fatal respiratory disease has been observed in captive ball pythons (Python regius) since the late 1990s. In order to better understand this disease and its etiology, we collected case and control samples and performed pathological and diagnostic analyses. Electron micrographs revealed filamentous virus-like particles in lung epithelial cells of sick animals. Diagnostic testing for known pathogens did not identify an etiologic agent, so unbiased metagenomic sequencing was performed. Abundant nidovirus-like sequences were identified in cases and were used to assemble the genome of a previously unknown virus in the order Nidovirales. The nidoviruses, which were not previously known to infect nonavian reptiles, are a diverse order that includes important human and veterinary pathogens. The presence of the viral RNA was confirmed in all diseased animals (n = 8) but was not detected in healthy pythons or other snakes (n = 57). Viral RNA levels were generally highest in the lung and other respiratory tract tissues. The 33.5-kb viral genome is the largest RNA genome yet described and shares canonical characteristics with other nidovirus genomes, although several features distinguish this from related viruses. This virus, which we named ball python nidovirus (BPNV), will likely establish a new genus in Torovirinae subfamily. The identification of a novel nidovirus in reptiles contributes to our understanding of the biology and evolution of related viruses, and its association with lung disease in pythons is a promising step toward elucidating an etiology for this long-standing veterinary disease. PMID:25205093

  16. Effect of feeding on circulating micronutrient concentrations in the Burmese python (Python molurus).

    PubMed

    Secor, S M; Nagy, T R; Johnston, K E; Tamura, T

    2001-06-01

    Burmese pythons (Python molurus) regulate digestive performance and metabolism with the ingestion of each meal. To explore the python's postprandial responses, we monitored the concentrations of blood micronutrients and homocysteine during fasting and for 15 days after feeding. Plasma folate concentrations peaked with a 270% increase over fasting levels 3 days after feeding, whereas plasma B-12 peaked with a 66% increase within 1 day. Erythrocyte folate concentrations were highest 15 days after feeding with a 44% increase. The major plasma folate was 5-methyltetrahydrofolate during fasting and was non-5-methyltetrahydrofolate during digestion, whereas erythrocytes contained polyglutamyl forms of non-5-methyltetrahydrofolate. Plasma homocysteine concentrations peaked with a 56% increase 3 days after feeding, and were markedly greater than those of mammals. Plasma zinc and copper did not change significantly. Plasma zinc concentrations were 20 times greater than plasma copper and approximately 30 times higher than those of mammals. Pythons showed a significant postprandial decline of 25% in hematocrit. Plasma pyridoxal 5'-phosphate (coenzyme form of vitamin B-6) was not detected probably due to its tight protein binding. Most micronutrient concentrations appear to plateau 3 days after feeding, suggesting that pythons have relatively rapid homeostasis of micronutrients despite the ingestion of large meals.

  17. Postprandial increase of oleoylethanolamide mobilization in small intestine of the Burmese python (Python molurus).

    PubMed

    Astarita, Giuseppe; Rourke, Bryan C; Andersen, Johnnie B; Fu, Jin; Kim, Janet H; Bennett, Albert F; Hicks, James W; Piomelli, Daniele

    2006-05-01

    Oleoylethanolamide (OEA) is an endogenous lipid mediator that inhibits feeding in rats and mice by activating the nuclear receptor peroxisome proliferator-activated receptor-alpha (PPAR-alpha). In rodents, intestinal OEA levels increase about threefold upon refeeding, a response that may contribute to the induction of between-meal satiety. Here, we examined whether feeding-induced OEA mobilization also occurs in Burmese pythons (Python molurus), a species of ambush-hunting snakes that consume huge meals after months of fasting and undergo massive feeding-dependent changes in gastrointestinal hormonal release and gut morphology. Using liquid chromatography/mass spectrometry (LC/MS), we measured OEA levels in the gastrointestinal tract of fasted (28 days) and fed (48 h after feeding) pythons. We observed a nearly 300-fold increase in OEA levels in the small intestine of fed compared with fasted animals (322 +/- 121 vs. 1 +/- 1 pmol/mg protein, n = 3-4). In situ OEA biosynthesis was suggested by the concomitant increase of N-acyl phosphatidylethanolamine species that serve as potential biosynthetic precursors for OEA. Furthermore, we observed a concomitant increase in saturated, mono- and diunsaturated, but not polyunsaturated fatty-acid ethanolamides (FAE) in the small intestine of fed pythons. The identification of OEA and other FAEs in the gastrointestinal tract of Python molurus suggests that this class of lipid messengers may be widespread among vertebrate groups and may represent an evolutionarily ancient means of regulating energy intake.

  18. Stimfit: quantifying electrophysiological data with Python

    PubMed Central

    Guzman, Segundo J.; Schlögl, Alois; Schmidt-Hieber, Christoph

    2013-01-01

    Intracellular electrophysiological recordings provide crucial insights into elementary neuronal signals such as action potentials and synaptic currents. Analyzing and interpreting these signals is essential for a quantitative understanding of neuronal information processing, and requires both fast data visualization and ready access to complex analysis routines. To achieve this goal, we have developed Stimfit, a free software package for cellular neurophysiology with a Python scripting interface and a built-in Python shell. The program supports most standard file formats for cellular neurophysiology and other biomedical signals through the Biosig library. To quantify and interpret the activity of single neurons and communication between neurons, the program includes algorithms to characterize the kinetics of presynaptic action potentials and postsynaptic currents, estimate latencies between pre- and postsynaptic events, and detect spontaneously occurring events. We validate and benchmark these algorithms, give estimation errors, and provide sample use cases, showing that Stimfit represents an efficient, accessible and extensible way to accurately analyze and interpret neuronal signals. PMID:24600389

  19. Simulation of Planetary Formation using Python

    NASA Astrophysics Data System (ADS)

    Bufkin, James; Bixler, David

    2015-03-01

    A program to simulate planetary formation was developed in the Python programming language. The program consists of randomly placed and massed bodies surrounding a central massive object in order to approximate a protoplanetary disk. The orbits of these bodies are time-stepped, with accelerations, velocities and new positions calculated in each step. Bodies are allowed to merge if their disks intersect. Numerous parameters (orbital distance, masses, number of particles, etc.) were varied in order to optimize the program. The program uses an iterative difference equation approach to solve the equations of motion using a kinematic model. Conservation of energy and angular momentum are not specifically forced, but conservation of momentum is forced during the merging of bodies. The initial program was created in Visual Python (VPython) but the current intention is to allow for higher particle count and faster processing by utilizing PyOpenCl and PyOpenGl. Current results and progress will be reported.

  20. Writing analytic element programs in Python.

    PubMed

    Bakker, Mark; Kelson, Victor A

    2009-01-01

    The analytic element method is a mesh-free approach for modeling ground water flow at both the local and the regional scale. With the advent of the Python object-oriented programming language, it has become relatively easy to write analytic element programs. In this article, an introduction is given of the basic principles of the analytic element method and of the Python programming language. A simple, yet flexible, object-oriented design is presented for analytic element codes using multiple inheritance. New types of analytic elements may be added without the need for any changes in the existing part of the code. The presented code may be used to model flow to wells (with either a specified discharge or drawdown) and streams (with a specified head). The code may be extended by any hydrogeologist with a healthy appetite for writing computer code to solve more complicated ground water flow problems.

  1. Meteor Shower Identification and Characterization with Python

    NASA Technical Reports Server (NTRS)

    Moorhead, Althea

    2015-01-01

    The short development time associated with Python and the number of astronomical packages available have led to increased usage within NASA. The Meteoroid Environment Office in particular uses the Python language for a number of applications, including daily meteor shower activity reporting, searches for potential parent bodies of meteor showers, and short dynamical simulations. We present our development of a meteor shower identification code that identifies statistically significant groups of meteors on similar orbits. This code overcomes several challenging characteristics of meteor showers such as drastic differences in uncertainties between meteors and between the orbital elements of a single meteor, and the variation of shower characteristics such as duration with age or planetary perturbations. This code has been proven to successfully and quickly identify unusual meteor activity such as the 2014 kappa Cygnid outburst. We present our algorithm along with these successes and discuss our plans for further code development.

  2. POPPY: Physical Optics Propagation in PYthon

    NASA Astrophysics Data System (ADS)

    Perrin, Marshall; Long, Joseph; Douglas, Ewan; Sivaramakrishnan, Anand; Slocum, Christine

    2016-02-01

    POPPY (Physical Optics Propagation in PYthon) simulates physical optical propagation including diffraction. It implements a flexible framework for modeling Fraunhofer and Fresnel diffraction and point spread function formation, particularly in the context of astronomical telescopes. POPPY provides the optical modeling framework for WebbPSF (ascl:1504.007) and was developed as part of a simulation package for JWST, but is available separately and is broadly applicable to many kinds of imaging simulations.

  3. Python in gamma-ray astronomy

    NASA Astrophysics Data System (ADS)

    Deil, Christoph Deil

    2016-03-01

    Gamma-ray astronomy is a relatively new window on the cosmos. The first source detected from the ground was the Crab nebula, seen by the Whipple telescope in Arizona in 1989. Today, about 150 sources have been detected at TeV energies using gamma-ray telescopes from the ground such as H.E.S.S. in Namibia or VERITAS in Arizona, and about 3000 sources at GeV energies using the Fermi Gamma-ray Space Telescope. Soon construction will start for the Cherenkov Telescope Array (CTA), which will be the first ground-based gamma-ray telescope array operated as an open observatory, with a site in the southern and a second site in the northern hemisphere. In this presentation I will give a very brief introduction to gamma-ray astronomy and data analysis, as well as a short overview of the software used for the various missions. The main focus will be on recent attempts to build open-source gamma-ray software on the scientific Python stack and Astropy: ctapipe as a CTA Python pipeline prototype, Fermipy and the Fermi Science Tools for Fermi-LAT analysis, Gammapy as a community-developed gamma-ray Python package and naima as a non-thermal spectral modeling and fitting package.

  4. Predators in training: operant conditioning of novel behavior in wild Burmese pythons (Python molurus bivitattus).

    PubMed

    Emer, Sherri A; Mora, Cordula V; Harvey, Mark T; Grace, Michael S

    2015-01-01

    Large pythons and boas comprise a group of animals whose anatomy and physiology are very different from traditional mammalian, avian and other reptilian models typically used in operant conditioning. In the current study, investigators used a modified shaping procedure involving successive approximations to train wild Burmese pythons (Python molurus bivitattus) to approach and depress an illuminated push button in order to gain access to a food reward. Results show that these large, wild snakes can be trained to accept extremely small food items, associate a stimulus with such rewards via operant conditioning and perform a contingent operant response to gain access to a food reward. The shaping procedure produced robust responses and provides a mechanism for investigating complex behavioral phenomena in massive snakes that are rarely studied in learning research.

  5. Saccular lung cannulation in a ball python (Python regius) to treat a tracheal obstruction.

    PubMed

    Myers, Debbie A; Wellehan, James F X; Isaza, Ramiro

    2009-03-01

    An adult male ball python (Python regius) presented in a state of severe dyspnea characterized by open-mouth breathing and vertical positioning of the head and neck. The animal had copious discharge in the tracheal lumen acting as an obstruction. A tube was placed through the body wall into the caudal saccular aspect of the lung to allow the animal to breathe while treatment was initiated. The ball python's dyspnea immediately improved. Diagnostics confirmed a bacterial respiratory infection with predominantly Providencia rettgeri. The saccular lung (air sac) tube was removed after 13 days. Pulmonary endoscopy before closure showed minimal damage with a small amount of hemorrhage in the surrounding muscle tissue. Respiratory disease is a common occurrence in captive snakes and can be associated with significant morbidity and mortality. Saccular lung cannulation is a relatively simple procedure that can alleviate tracheal narrowing or obstruction, similar to air sac cannulation in birds.

  6. HOPE: Just-in-time Python compiler for astrophysical computations

    NASA Astrophysics Data System (ADS)

    Akeret, Joel; Gamper, Lukas; Amara, Adam; Refregier, Alexandre

    2014-11-01

    HOPE is a specialized Python just-in-time (JIT) compiler designed for numerical astrophysical applications. HOPE focuses on a subset of the language and is able to translate Python code into C++ while performing numerical optimization on mathematical expressions at runtime. To enable the JIT compilation, the user only needs to add a decorator to the function definition. By using HOPE, the user benefits from being able to write common numerical code in Python while getting the performance of compiled implementation.

  7. The Virtual Observatory for the Python Programmer

    NASA Astrophysics Data System (ADS)

    Plante, Raymond L.; Fitzpatrick, M. J.; Graham, M.; Tody, D.; Virtual Astronomical Observatory, US

    2014-01-01

    The web of astronomical data centers that we refer to as the virtual observatory (VO) has led to the development of a variety of web and desktop applications that can discover and download data from most archives around the world. These are made possible by standard interfaces which archives provide and the applications understand that provide a common way to search for information and retrieve discovered datasets. For some applications, retrieving data through the VO is simply an extra feature that enhances the main purpose of the tool. Despite the accessibility to VO data provided by such tools, the VO offers greater flexibility to developers that access the standard services directly within their own software. This applies not only to those who build tools but also to research astronomers that create highly-customized scripts for data analysis. One of the goals of the US Virtual Astronomical Observatory (VAO) project is to make the VO more accessible to both tool developers and astronomer-programmers. To this end, we announce the release of two products with a special focus on supporting access to the VO via Python. PyVO (http://dev.usvao.org/pyvo) is a pure Python library built on Astropy (astropy.org) that can be used to discover data in the VO. In particular, one can search the registry for archives with data, search archives for images and spectra, and query remote catalogs and spectral line databases. While it provides full support for the VO standards, its API is designed to make processing the most common types of queries simple without requiring knowledge about the underlying standards. It also makes available the full power of Astropy for processing tabular information. VOClient (http://dev.usvao.org/voclient), which provides scripting and programming libraries for a variety of languages, also supports Python programming. While the two products share a common API, VOClient provides higher level interfaces that assist with managing data from many

  8. Extensible message passing application development and debugging with Python

    SciTech Connect

    Beazley, D.M.; Lomdahl, P.S.

    1996-09-19

    The authors describe how they have parallelized Python, an interpreted object oriented scripting language, and used it to build an extensible message-passing C/C++ applications for the CM-5, Cray T3D, and Sun multiprocessor servers running MPI. Using a parallelized Python interpreter, it is possible to interact with large-scale parallel applications, rapidly prototype new features, and perform application specific debugging. It is even possible to write message passing programs in Python itself. The authors describe some of the tools they have developed to extend Python and applications of this approach.

  9. Leveraging Python Interoperability Tools to Improve Sapphire's Usability

    SciTech Connect

    Gezahegne, A; Love, N S

    2007-12-10

    The Sapphire project at the Center for Applied Scientific Computing (CASC) develops and applies an extensive set of data mining algorithms for the analysis of large data sets. Sapphire's algorithms are currently available as a set of C++ libraries. However many users prefer higher level scripting languages such as Python for their ease of use and flexibility. In this report, we evaluate four interoperability tools for the purpose of wrapping Sapphire's core functionality with Python. Exposing Sapphire's functionality through a Python interface would increase its usability and connect its algorithms to existing Python tools.

  10. Re-imagining a Stata/Python Combination

    NASA Technical Reports Server (NTRS)

    Fiedler, James

    2013-01-01

    At last year's Stata Conference, I presented some ideas for combining Stata and the Python programming language within a single interface. Two methods were presented: in one, Python was used to automate Stata; in the other, Python was used to send simulated keystrokes to the Stata GUI. The first method has the drawback of only working in Windows, and the second can be slow and subject to character input limits. In this presentation, I will demonstrate a method for achieving interaction between Stata and Python that does not suffer these drawbacks, and I will present some examples to show how this interaction can be useful.

  11. Ureka: A Distribution of Python and IRAF Software for Astronomy

    NASA Astrophysics Data System (ADS)

    Hirst, P.; Slocum, C.; Turner, J.; Sienkiewicz, M.; Greenfield, P.; Hogan, E.; Simpson, M.; Labrie, K.

    2014-05-01

    As astronomical data processing expands from our historical platforms into modern Python applications, users are faced with installing and maintaining large numbers of heterogeneous dependencies. A handful of scientific Python distributions make installing key packages easy, but don't cater for specific needs such as integration with IRAF. We have therefore recently released a beta version of a new astronomical software distribution for Linux and OSX, known as Ureka. Ureka is based around STScI Python and dependencies, notably Python, NumPy, IRAF, SciPy, AstroPy, Matplotlib and Tk. It also contains data reduction packages for Gemini, HST, JWST and other observatories, alongside various complementary tools.

  12. Subspectacular nematodiasis caused by a novel Serpentirhabdias species in ball pythons (Python regius).

    PubMed

    Hausmann, J C; Mans, C; Dreyfus, J; Reavill, D R; Lucio-Forster, A; Bowman, D D

    2015-01-01

    Subspectacular nematodiasis was diagnosed in three captive-bred juvenile ball pythons (Python regius) from two unrelated facilities within a 6-month period. The snakes were presented with similar lesions, including swelling of facial, periocular and oral tissues. Bilaterally, the subspectacular spaces were distended and filled with an opaque fluid, which contained nematodes and eggs. Histopathology showed nematodes throughout the periocular tissue, subspectacular space and subcutaneous tissue of the head. The nematodes from both facilities were morphologically indistinguishable and most closely resembled Serpentirhabdias species. Morphological characterization and genetic sequencing indicate this is a previously undescribed rhabdiasid nematode.

  13. Trypanosoma cf. varani in an imported ball python (Python reginus) from Ghana.

    PubMed

    Sato, Hiroshi; Takano, Ai; Kawabata, Hiroki; Une, Yumi; Watanabe, Haruo; Mukhtar, Maowia M

    2009-08-01

    Peripheral blood from a ball python (Python reginus) imported from Ghana was cultured in Barbour-Stoenner-Kelly (BSK) medium for Borrelia spp. isolation, resulting in the prominent appearance of free, and clusters of, trypanosomes in a variety of morphological forms. The molecular phylogenetic characterization of these cultured trypanosomes, using the small subunit rDNA, indicated that this python was infected with a species closely related to Trypanosoma varani Wenyon, 1908, originally described in the Nile monitor lizard (Varanus niloticus) from Sudan. Furthermore, nucleotide sequences of glycosomal glyceraldehyde-3-phosphate dehydrogenase gene of both isolates showed few differences. Giemsa-stained blood smears, prepared from the infected python 8 mo after the initial observation of trypanosomes in hemoculture, contained trypomastigotes with a broad body and a short, free flagellum; these most closely resembled the original description of T. varani, or T. voltariae Macfie, 1919 recorded in a black-necked spitting cobra (Naja nigricollis) from Ghana. It is highly possible that lizards and snakes could naturally share an identical trypanosome species. Alternatively, lizards and snakes in the same region might have closely related, but distinct, Trypanosoma species as a result of sympatric speciation. From multiple viewpoints, including molecular phylogenetic analyses, reappraisal of trypanosome species from a wide range of reptiles in Africa is needed to clarify the relationship of recorded species, or to unmask unrecorded species.

  14. scikit-image: image processing in Python

    PubMed Central

    Schönberger, Johannes L.; Nunez-Iglesias, Juan; Boulogne, François; Warner, Joshua D.; Yager, Neil; Gouillart, Emmanuelle; Yu, Tony

    2014-01-01

    scikit-image is an image processing library that implements algorithms and utilities for use in research, education and industry applications. It is released under the liberal Modified BSD open source license, provides a well-documented API in the Python programming language, and is developed by an active, international team of collaborators. In this paper we highlight the advantages of open source to achieve the goals of the scikit-image library, and we showcase several real-world image processing applications that use scikit-image. More information can be found on the project homepage, http://scikit-image.org. PMID:25024921

  15. MPDAF: MUSE Python Data Analysis Framework

    NASA Astrophysics Data System (ADS)

    Bacon, Roland; Piqueras, Laure; Conseil, Simon; Richard, Johan; Shepherd, Martin

    2016-11-01

    MPDAF, the MUSE Python Data Analysis Framework, provides tools to work with MUSE-specific data (for example, raw data and pixel tables), and with more general data such as spectra, images, and data cubes. Originally written to work with MUSE data, it can also be used for other data, such as that from the Hubble Space Telescope. MPDAF also provides MUSELET, a SExtractor-based tool to detect emission lines in a data cube, and a format to gather all the information on a source in one FITS file. MPDAF was developed and is maintained by CRAL (Centre de Recherche Astrophysique de Lyon).

  16. scikit-image: image processing in Python.

    PubMed

    van der Walt, Stéfan; Schönberger, Johannes L; Nunez-Iglesias, Juan; Boulogne, François; Warner, Joshua D; Yager, Neil; Gouillart, Emmanuelle; Yu, Tony

    2014-01-01

    scikit-image is an image processing library that implements algorithms and utilities for use in research, education and industry applications. It is released under the liberal Modified BSD open source license, provides a well-documented API in the Python programming language, and is developed by an active, international team of collaborators. In this paper we highlight the advantages of open source to achieve the goals of the scikit-image library, and we showcase several real-world image processing applications that use scikit-image. More information can be found on the project homepage, http://scikit-image.org.

  17. TRIPPy: Python-based Trailed Source Photometry

    NASA Astrophysics Data System (ADS)

    Fraser, Wesley C.; Alexandersen, Mike; Schwamb, Megan E.; Marsset, Michael E.; Pike, Rosemary E.; Kavelaars, JJ; Bannister, Michele T.; Benecchi, Susan; Delsanti, Audrey

    2016-05-01

    TRIPPy (TRailed Image Photometry in Python) uses a pill-shaped aperture, a rectangle described by three parameters (trail length, angle, and radius) to improve photometry of moving sources over that done with circular apertures. It can generate accurate model and trailed point-spread functions from stationary background sources in sidereally tracked images. Appropriate aperture correction provides accurate, unbiased flux measurement. TRIPPy requires numpy, scipy, matplotlib, Astropy (ascl:1304.002), and stsci.numdisplay; emcee (ascl:1303.002) and SExtractor (ascl:1010.064) are optional.

  18. A facility for creating Python extensions in C++

    SciTech Connect

    Dubois, P F

    1998-07-14

    Python extensions are usually created by writing the glue that connects Python to the desired new functionality in the C language. While simple extensions do not require much effort, to do the job correctly with full error checking is tedious and prone to errors in reference counting and to memory leaks, especially when errors occur. The resulting program is difficult to read and maintain. By designing suitable C++ classes to wrap the Python C API, we are able to produce extensions that are correct and which clean up after themselves correctly when errors occur. This facility also integrates the C++ and Python exception facilities. This paper briefly describes our package for this purpose, named CXX. The emphasis is on our design choices and the way these contribute to the construction of accurate Python extensions. We also briefly relate the way CXX's facilities for sequence classes allow use of C++'s Standard Template Library (STL) algorithms on C++ sequences.

  19. Report on the observed response of Javan lutungs (Trachypithecus auratus mauritius) upon encountering a reticulated python (Python reticulatus).

    PubMed

    Tsuji, Yamato; Prayitno, Bambang; Suryobroto, Bambang

    2016-04-01

    We observed an encounter between a reticulated python (Python reticulatus) and a group of wild Javan lutungs (Trachypithecus auratus mauritius) at the Pangandaran Nature Reserve, West Java, Indonesia. A python (about 2 m in length) moved toward a group of lutungs in the trees. Upon seeing the python, an adult male and several adult female lutungs began to emit alarm calls. As the python approached, two adult and one sub-adult female jumped onto a branch near the python and began mobbing the python by shaking the branch. During the mobbing, other individuals in the group (including an adult lutung male) remained nearby but did not participate. The python then rolled into a ball-like shape and stopped moving, at which point the lutungs moved away. The total duration of the encounter was about 40 min, during which time the lutungs stopped feeding and grooming. Group cohesiveness during and after the encounter was greater than that before the encounter, indicating that lutungs adjust their daily activity in response to potential predation risk.

  20. SunPy: Solar Physics in Python

    NASA Astrophysics Data System (ADS)

    Ryan, Daniel; Christe, Steven; Mumford, Stuart; Perez Suarez, David; Ireland, Jack; Shih, Albert Y.; Inglis, Andrew; Liedtke, Simon; Hewett, Russel

    2015-04-01

    SunPy is a community-developed open-source software library for solar physics. It is written in Python, a free, cross-platform, general-purpose, high-level programming language which is being increasingly adopted throughout the scientific community as well as further afield. This has resulted in a wide array of software packages useful for scientific computing, from numerical computation (NumPy, SciPy, etc.), to machine learning (scifitlearn), to visualization and plotting (matplotlib). SunPy aims to provide required specialised software for analysing solar and heliospheric datasets in Python. The current version is 0.5 with 0.6 expected to be released later this year. SunPy provides solar data access through integration with the Virtual Solar Observatory (VSO), the Heliophysics Event Knowledgebase (HEK), and the HELiophysics Integrated Observatory (HELIO) webservices. It supports common data types from major solar missions such as images (SDO/AIA, STEREO, PROBA2/SWAP etc.), time series (GOES/XRS, SDO/EVE, PROBA2/LYRA), and radio spectra (e-Callisto, STEREO/WAVES). SunPy’s code base is publicly available through github.com and can be contributed to by anyone. In this poster we demonstrate SunPy’s functionality and future goals of the project. We also encourage interested users to become involved in further developing SunPy.

  1. PyMOOSE: Interoperable Scripting in Python for MOOSE.

    PubMed

    Ray, Subhasis; Bhalla, Upinder S

    2008-01-01

    Python is emerging as a common scripting language for simulators. This opens up many possibilities for interoperability in the form of analysis, interfaces, and communications between simulators. We report the integration of Python scripting with the Multi-scale Object Oriented Simulation Environment (MOOSE). MOOSE is a general-purpose simulation system for compartmental neuronal models and for models of signaling pathways based on chemical kinetics. We show how the Python-scripting version of MOOSE, PyMOOSE, combines the power of a compiled simulator with the versatility and ease of use of Python. We illustrate this by using Python numerical libraries to analyze MOOSE output online, and by developing a GUI in Python/Qt for a MOOSE simulation. Finally, we build and run a composite neuronal/signaling model that uses both the NEURON and MOOSE numerical engines, and Python as a bridge between the two. Thus PyMOOSE has a high degree of interoperability with analysis routines, with graphical toolkits, and with other simulators.

  2. Responses of python gastrointestinal regulatory peptides to feeding.

    PubMed

    Secor, S M; Fehsenfeld, D; Diamond, J; Adrian, T E

    2001-11-20

    In the Burmese python (Python molurus), the rapid up-regulation of gastrointestinal (GI) function and morphology after feeding, and subsequent down-regulation on completing digestion, are expected to be mediated by GI hormones and neuropeptides. Hence, we examined postfeeding changes in plasma and tissue concentrations of 11 GI hormones and neuropeptides in the python. Circulating levels of cholecystokinin (CCK), glucose-dependent insulinotropic peptide (GIP), glucagon, and neurotensin increase by respective factors of 25-, 6-, 6-, and 3.3-fold within 24 h after feeding. In digesting pythons, the regulatory peptides neurotensin, somatostatin, motilin, and vasoactive intestinal peptide occur largely in the stomach, GIP and glucagon in the pancreas, and CCK and substance P in the small intestine. Tissue concentrations of CCK, GIP, and neurotensin decline with feeding. Tissue distributions and molecular forms (as determined by gel-permeation chromatography) of many python GI peptides are similar or identical to those of their mammalian counterparts. The postfeeding release of GI peptides from tissues, and their concurrent rise in plasma concentrations, suggests that they play a role in regulating python-digestive responses. These large postfeeding responses, and similarities of peptide structure with mammals, make pythons an attractive model for studying GI peptides.

  3. Lectin histochemical aspects of mucus function in the oesophagus of the reticulated python (Python reticulatus).

    PubMed

    Meyer, W; Luz, S; Schnapper, A

    2009-08-01

    Using lectin histochemistry, the study characterizes basic functional aspects of the mucus produced by the oesophageal epithelium of the Reticulated python (Python reticulatus). Reaction staining varied as related to the two epithelium types present, containing goblet cells and ciliary cells. Remarkable intensities were achieved especially in the luminal mucus layer and the fine mucus covering the epithelial ciliary border for Con A (alpha-D-Man; alpha-D-Glc) as part of neutral glycoproteins, Limax flavus agglutinin (NeuNac = NeuNgc), emphasizing that water binding hyaluronan provides a hydrated interface conductive to the passage of material and UEA-I (alpha-L-Fuc), corroborating the view that fucose-rich highly viscous mucus is helpful against mechanical stress during prey transport.

  4. Ultrasonographic diagnosis of an endocarditis valvularis in a Burmese python (Python molurus bivittatus) with pneumonia.

    PubMed

    Schroff, Sandra; Schmidt, Volker; Kiefer, Ingmar; Krautwald-Junghanns, Maria-Elisabeth; Pees, Michael

    2010-12-01

    An 11-yr-old Burmese python (Python molurus bivittatus) was presented with a history of respiratory symptoms. Computed tomography and an endoscopic examination of the left lung were performed and revealed severe pneumonia. Microbiologic examination of a tracheal wash sample and an endoscopy-guided sample from the lung confirmed infection with Salmonella enterica ssp. IV, Enterobacter cloacae, and Klebsiella pneumoniae. Computed tomographic examination demonstrated a hyperattenuated structure within the heart. Echocardiographic examination revealed a hyperechoic mass at the pulmonic valve as well as a dilated truncus pulmonalis. As therapy for pneumonia was ineffective, the snake was euthanized. Postmortem examination confirmed pneumonia and infective endocarditis of the pulmonic valve caused by septicemia with Salmonella enterica ssp. IV. Focal arteriosclerosis of the pulmonary trunk was also diagnosed. The case presented here demonstrates the possible connection between respiratory and cardiovascular diseases in snakes.

  5. Osteitis deformans (Paget's disease) in a Burmese python (Python molurus bivittatus)--a case report.

    PubMed

    Preziosi, Rosario; Diana, Alessia; Florio, Daniela; Gustinelli, Andrea; Nardini, Giordano

    2007-11-01

    Osteitis deformans (Paget's disease of bone) is a chronic focal disorder of bone remodelling characterized by an initial increase in osteoclast-mediated bone resorption, with subsequent compensatory increase in new bone formation, resulting in a disorganized mosaic of woven and lamellar bone. In the Burmese python (Python molurus bivittatus) of this report, multifocal gross swellings involving the proximal third of the vertebral spine were observed and associated with anorexia, a relative inability to move or to fully extend the body, and to strike at prey. Serum biochemistry revealed elevated alkaline-phosphatase activity. Radiographic changes (irregular bone proliferation along the vertebral margins), computed tomography scan results (abnormal mineral density), and histopathological features (generalized thickening of the bony trabeculae at the expense of the intertrabecular spaces and irregular patches of lamellar bone with a characteristic "mosaic" pattern) indicated osteitis deformans.

  6. Postprandial morphological response of the intestinal epithelium of the Burmese python (Python molurus).

    PubMed

    Lignot, Jean-Hervé; Helmstetter, Cécile; Secor, Stephen M

    2005-07-01

    The postprandial morphological changes of the intestinal epithelium of Burmese pythons were examined using fasting pythons and at eight time points after feeding. In fasting pythons, tightly packed enterocytes possess very short microvilli and are arranged in a pseudostratified fashion. Enterocyte width increases by 23% within 24 h postfeeding, inducing significant increases in villus length and intestinal mass. By 6 days postfeeding, enterocyte volume had peaked, following as much as an 80% increase. Contributing to enterocyte hypertrophy is the cellular accumulation of lipid droplets at the tips and edges of the villi of the proximal and middle small intestine, but which were absent in the distal small intestine. At 3 days postfeeding, conventional and environmental scanning electron microscopy revealed cracks and lipid extrusion along the narrow edges of the villi and at the villus tips. Transmission electron microscopy demonstrated the rapid postprandial lengthening of enterocyte microvilli, increasing 4.8-fold in length within 24 h, and the maintaining of that length through digestion. Beginning at 24 h postfeeding, spherical particles were found embedded apically within enterocytes of the proximal and middle small intestine. These particles possessed an annular-like construction and were stained with the calcium-stain Alizarine red S suggesting that they were bone in origin. Following the completion of digestion, many of the postprandial responses were reversed, as observed by the atrophy of enterocytes, the shortening of villi, and the retraction of the microvilli. Further exploration of the python intestine will reveal the underlying mechanisms of these trophic responses and the origin and fate of the engulfed particles.

  7. Reduction of blood oxygen levels enhances postprandial cardiac hypertrophy in Burmese python (Python bivittatus).

    PubMed

    Slay, Christopher E; Enok, Sanne; Hicks, James W; Wang, Tobias

    2014-05-15

    Physiological cardiac hypertrophy is characterized by reversible enlargement of cardiomyocytes and changes in chamber architecture, which increase stroke volume and via augmented convective oxygen transport. Cardiac hypertrophy is known to occur in response to repeated elevations of O2 demand and/or reduced O2 supply in several species of vertebrate ectotherms, including postprandial Burmese pythons (Python bivittatus). Recent data suggest postprandial cardiac hypertrophy in P. bivittatus is a facultative rather than obligatory response to digestion, though the triggers of this response are unknown. Here, we hypothesized that an O2 supply-demand mismatch stimulates postprandial cardiac enlargement in Burmese pythons. To test this hypothesis, we rendered animals anemic prior to feeding, essentially halving blood oxygen content during the postprandial period. Fed anemic animals had heart rates 126% higher than those of fasted controls, which, coupled with a 71% increase in mean arterial pressure, suggests fed anemic animals were experiencing significantly elevated cardiac work. We found significant cardiac hypertrophy in fed anemic animals, which exhibited ventricles 39% larger than those of fasted controls and 28% larger than in fed controls. These findings support our hypothesis that those animals with a greater magnitude of O2 supply-demand mismatch exhibit the largest hearts. The 'low O2 signal' stimulating postprandial cardiac hypertrophy is likely mediated by elevated ventricular wall stress associated with postprandial hemodynamics.

  8. Preliminary single-dose pharmacokinetics of marbofloxacin in ball pythons (Python regius).

    PubMed

    Coke, Rob L; Isaza, Ramiro; Koch, David E; Pellerin, Marie A; Hunter, Robert P

    2006-03-01

    Pharmacokinetics of marbofloxacin in two male and four female adult ball pythons (Python regius) was determined after i.v. and p.o. administration of a single dose. Using a crossover design, each snake was given a single 10 mg/kg dose of marbofloxacin i.v. and p.o. Blood samples were collected prior to and 0.5, 1, 1.5, 3, 6, 12, and 24 hr after marbofloxacin administration. Marbofloxacin was quantitated by use of liquid chromatography-mass spectrometry. Following p.o. administration, marbofloxacin had a peak plasma concentration (Cmax) of 9.40 microg/ml and a time to Cmax (Tmax) of 9.0 hr. Based on the plasma pharmacokinetics generated in this study and pending any further studies to evaluate potential toxicity and multi-dose pharmacokinetics, we suggest a dosage for marbofloxacin in ball pythons of 10 mg/kg p.o. at least every 48 hr, depending on the sensitivity of the pathogen and as a basis for further research.

  9. Report on the ''ESO Python Boot Camp — Pilot Version''

    NASA Astrophysics Data System (ADS)

    Dias, B.; Milli, J.

    2017-03-01

    The Python programming language is becoming very popular within the astronomical community. Python is a high-level language with multiple applications including database management, handling FITS images and tables, statistical analysis, and more advanced topics. Python is a very powerful tool both for astronomical publications and for observatory operations. Since the best way to learn a new programming language is through practice, we therefore organised a two-day hands-on workshop to share expertise among ESO colleagues. We report here the outcome and feedback from this pilot event.

  10. Implementation of quantum game theory simulations using Python

    NASA Astrophysics Data System (ADS)

    Madrid S., A.

    2013-05-01

    This paper provides some examples about quantum games simulated in Python's programming language. The quantum games have been developed with the Sympy Python library, which permits solving quantum problems in a symbolic form. The application of these methods of quantum mechanics to game theory gives us more possibility to achieve results not possible before. To illustrate the results of these methods, in particular, there have been simulated the quantum battle of the sexes, the prisoner's dilemma and card games. These solutions are able to exceed the classic bottle neck and obtain optimal quantum strategies. In this form, python demonstrated that is possible to do more advanced and complicated quantum games algorithms.

  11. ScrumPy: metabolic modelling with Python.

    PubMed

    Poolman, M G

    2006-09-01

    ScrumPy is a software package used for the definition and analysis of metabolic models. It is written using the Python programming language that is also used as a user interface. ScrumPy has features for both kinetic and structural modelling, but the emphasis is on structural modelling and those features of most relevance to analysis of large (genome-scale) models. The aim is at describing ScrumPy's functionality to readers with some knowledge of metabolic modelling, but implementation, programming and other computational details are omitted. ScrumPy is released under the Gnu Public Licence, and available for download from http://mudshark.brookes.ac.uk/ ScrumPy.

  12. Neutron Scattering Experiment Automation with Python

    SciTech Connect

    Zolnierczuk, Piotr A; Riedel, Richard A

    2010-01-01

    The Spallation Neutron Source (SNS) at Oak Ridge National Laboratory currently holds the Guinness World Record as the world most powerful pulsed spallation neutron source. Neutrons scattered off atomic nuclei in a sample yield important information about the position, motions, and magnetic properties of atoms in materials. A neutron scattering experiment usually involves sample environment control (temperature, pressure, etc.), mechanical alignment (slits, sample and detector position), magnetic field controllers, neutron velocity selection (choppers) and neutron detectors. The SNS Data Acquisition System (DAS) consists of real-time sub-system (detector read-out with custom electronics, chopper interface), data preprocessing (soft real-time) and a cluster of control and ancillary PCs. The real-time system runs FPGA firmware and programs running on PCs (C++, LabView) typically perform one task such as motor control and communicate via TCP/IP networks. PyDas is a set of Python modules that are used to integrate various components of the SNS DAS system. It enables customized automation of neutron scattering experiments in a rapid and flexible manner. It provides wxPython GUIs for routine experiments as well as IPython command line scripting. Matplotlib and numpy are used for data presentation and simple analysis. We will present an overview of SNS Data Acquisition System and PyDas architectures and implementation along with the examples of use. We will also discuss plans for future development as well as the challenges that have to be met while maintaining PyDas for 20+ different scientific instruments.

  13. galpy: A python LIBRARY FOR GALACTIC DYNAMICS

    SciTech Connect

    Bovy, Jo

    2015-02-01

    I describe the design, implementation, and usage of galpy, a python package for galactic-dynamics calculations. At its core, galpy consists of a general framework for representing galactic potentials both in python and in C (for accelerated computations); galpy functions, objects, and methods can generally take arbitrary combinations of these as arguments. Numerical orbit integration is supported with a variety of Runge-Kutta-type and symplectic integrators. For planar orbits, integration of the phase-space volume is also possible. galpy supports the calculation of action-angle coordinates and orbital frequencies for a given phase-space point for general spherical potentials, using state-of-the-art numerical approximations for axisymmetric potentials, and making use of a recent general approximation for any static potential. A number of different distribution functions (DFs) are also included in the current release; currently, these consist of two-dimensional axisymmetric and non-axisymmetric disk DFs, a three-dimensional disk DF, and a DF framework for tidal streams. I provide several examples to illustrate the use of the code. I present a simple model for the Milky Way's gravitational potential consistent with the latest observations. I also numerically calculate the Oort functions for different tracer populations of stars and compare them to a new analytical approximation. Additionally, I characterize the response of a kinematically warm disk to an elliptical m = 2 perturbation in detail. Overall, galpy consists of about 54,000 lines, including 23,000 lines of code in the module, 11,000 lines of test code, and about 20,000 lines of documentation. The test suite covers 99.6% of the code. galpy is available at http://github.com/jobovy/galpy with extensive documentation available at http://galpy.readthedocs.org/en/latest.

  14. galpy: A python Library for Galactic Dynamics

    NASA Astrophysics Data System (ADS)

    Bovy, Jo

    2015-02-01

    I describe the design, implementation, and usage of galpy, a python package for galactic-dynamics calculations. At its core, galpy consists of a general framework for representing galactic potentials both in python and in C (for accelerated computations); galpy functions, objects, and methods can generally take arbitrary combinations of these as arguments. Numerical orbit integration is supported with a variety of Runge-Kutta-type and symplectic integrators. For planar orbits, integration of the phase-space volume is also possible. galpy supports the calculation of action-angle coordinates and orbital frequencies for a given phase-space point for general spherical potentials, using state-of-the-art numerical approximations for axisymmetric potentials, and making use of a recent general approximation for any static potential. A number of different distribution functions (DFs) are also included in the current release; currently, these consist of two-dimensional axisymmetric and non-axisymmetric disk DFs, a three-dimensional disk DF, and a DF framework for tidal streams. I provide several examples to illustrate the use of the code. I present a simple model for the Milky Way's gravitational potential consistent with the latest observations. I also numerically calculate the Oort functions for different tracer populations of stars and compare them to a new analytical approximation. Additionally, I characterize the response of a kinematically warm disk to an elliptical m = 2 perturbation in detail. Overall, galpy consists of about 54,000 lines, including 23,000 lines of code in the module, 11,000 lines of test code, and about 20,000 lines of documentation. The test suite covers 99.6% of the code. galpy is available at http://github.com/jobovy/galpy with extensive documentation available at http://galpy.readthedocs.org/en/latest.

  15. Enrico: Python package to simplify Fermi-LAT analysis

    NASA Astrophysics Data System (ADS)

    Sanchez, David; Deil, Christoph

    2015-01-01

    Enrico analyzes Fermi data. It produces spectra (model fit and flux points), maps and lightcurves for a target by editing a config file and running a python script which executes the Fermi science tool chain.

  16. Using the Scientific Python ecosystem to advance open radar science

    NASA Astrophysics Data System (ADS)

    Collis, S. M.; Helmus, J.

    2015-12-01

    The choice of a programming language or environment is rarely made with consideration of its benefits and disadvantages. Often it is something inherited from mentor or enforced by an institution. Python, developed as a "hobby" programming project, has seen increased migration of users from more traditional domain specific environments. This presentation charts our own journey in using the scientific python ecosystem, first as users and then as the developers of a community based toolkit for working with weather radar data, the Python ARM Radar Toolkit, Py-ART. We will highlight how a data model driven design approach can extend the usefulness and reusability of code and act as a bridge between amorphous mathematical algorithms and domain specific data. Finally we will showcase how Python and Py-ART can be used on clusters to tackle pleasantly parallel problems like deriving climatologies swiftly, painlessly and most importantly: reproducibly.

  17. Rapid Development of Interferometric Software Using MIRIAD and Python

    NASA Astrophysics Data System (ADS)

    Williams, Peter K. G.; Law, Casey J.; Bower, Geoffrey C.

    2012-06-01

    State-of-the-art radio interferometers are complex systems that unleash torrents of data. If current and planned instruments are to routinely meet their performance goals, standard analysis techniques must be significantly improved, becoming simultaneously more sophisticated, more automatic, and more scalable. While there is no shortage of ideas for next-generation algorithms, there is a shortage of development resources, so it is vital that programming environments for interferometric software allow for rapid, flexible development. We present an open-source software package, miriad-python, that provides access to the MIRIAD interferometric reduction system in the Python programming language. The modular design of MIRIAD and the high productivity and accessibility of Python provide an excellent foundation for rapid development of interferometric software. Several other projects with similar goals exist, and we describe them and compare miriad-python with them in detail. Along with an overview of the package design, we present sample code and applications, including the detection of millisecond astrophysical transients, determination and application of nonstandard calibration parameters, interactive data visualization, and a reduction pipeline using a directed acyclic graph dependency model analogous to that of the traditional UNIX tool make. The key aspects of the miriad-python software project are documented. We find that miriad-python provides an extremely effective environment for prototyping new interferometric software, though certain existing packages provide far more infrastructure for some applications. While equivalent software written in compiled languages can be much faster than Python, there are many situations in which execution time is profitably exchanged for speed of development, code readability, accessibility to nonexpert programmers, quick interlinking with foreign software packages, and other virtues of the Python language.

  18. CVXPY: A Python-Embedded Modeling Language for Convex Optimization

    PubMed Central

    Diamond, Steven; Boyd, Stephen

    2016-01-01

    CVXPY is a domain-specific language for convex optimization embedded in Python. It allows the user to express convex optimization problems in a natural syntax that follows the math, rather than in the restrictive standard form required by solvers. CVXPY makes it easy to combine convex optimization with high-level features of Python such as parallelism and object-oriented design. CVXPY is available at http://www.cvxpy.org/ under the GPL license, along with documentation and examples. PMID:27375369

  19. CVXPY: A Python-Embedded Modeling Language for Convex Optimization.

    PubMed

    Diamond, Steven; Boyd, Stephen

    2016-04-01

    CVXPY is a domain-specific language for convex optimization embedded in Python. It allows the user to express convex optimization problems in a natural syntax that follows the math, rather than in the restrictive standard form required by solvers. CVXPY makes it easy to combine convex optimization with high-level features of Python such as parallelism and object-oriented design. CVXPY is available at http://www.cvxpy.org/ under the GPL license, along with documentation and examples.

  20. PyMultiNest: Python interface for MultiNest

    NASA Astrophysics Data System (ADS)

    Buchner, Johannes

    2016-06-01

    PyMultiNest provides programmatic access to MultiNest (ascl:1109.006) and PyCuba, integration existing Python code (numpy, scipy), and enables writing Prior & LogLikelihood functions in Python. PyMultiNest can plot and visualize MultiNest's progress and allows easy plotting, visualization and summarization of MultiNest results. The plotting can be run on existing MultiNest output, and when not using PyMultiNest for running MultiNest.

  1. MEG and EEG data analysis with MNE-Python.

    PubMed

    Gramfort, Alexandre; Luessi, Martin; Larson, Eric; Engemann, Denis A; Strohmeier, Daniel; Brodbeck, Christian; Goj, Roman; Jas, Mainak; Brooks, Teon; Parkkonen, Lauri; Hämäläinen, Matti

    2013-12-26

    Magnetoencephalography and electroencephalography (M/EEG) measure the weak electromagnetic signals generated by neuronal activity in the brain. Using these signals to characterize and locate neural activation in the brain is a challenge that requires expertise in physics, signal processing, statistics, and numerical methods. As part of the MNE software suite, MNE-Python is an open-source software package that addresses this challenge by providing state-of-the-art algorithms implemented in Python that cover multiple methods of data preprocessing, source localization, statistical analysis, and estimation of functional connectivity between distributed brain regions. All algorithms and utility functions are implemented in a consistent manner with well-documented interfaces, enabling users to create M/EEG data analysis pipelines by writing Python scripts. Moreover, MNE-Python is tightly integrated with the core Python libraries for scientific comptutation (NumPy, SciPy) and visualization (matplotlib and Mayavi), as well as the greater neuroimaging ecosystem in Python via the Nibabel package. The code is provided under the new BSD license allowing code reuse, even in commercial products. Although MNE-Python has only been under heavy development for a couple of years, it has rapidly evolved with expanded analysis capabilities and pedagogical tutorials because multiple labs have collaborated during code development to help share best practices. MNE-Python also gives easy access to preprocessed datasets, helping users to get started quickly and facilitating reproducibility of methods by other researchers. Full documentation, including dozens of examples, is available at http://martinos.org/mne.

  2. Using Python to Develop Graphical Interfaces to Scientific Data

    SciTech Connect

    MacFarland, L; Streletz, G J

    1999-09-24

    At Lawrence Livermore National Laboratory (LLNL), Python has proven to be a convenient language for the development of graphical user interfaces (GUIs) which allow scientists to view, plot, and analyze scientific data. Two such applications are described in this paper. The first, EOSView, is a browser application for an equation of state data library at LLNL. EOSView is used by scientists throughout the laboratory who use simulation codes that access the data library, or who need equation of state data for other purposes. EOSView provides graphical visualization capabilities, as well as the capability to analyze the data in many different ways. The second application, Zimp, is a GUI that allows interactive use of the Stark Line Shape Database. It is used to access and plot data. The quick construction of Zimp from elements of the EOSView code provides a useful lesson in code reuse, and illustrates how the object-oriented nature of Python facilitates this goal. In general, Python has proven to be an appropriate choice of language for applications of this type for several reasons, including the easy access to GUI functionality provided by Tkinter, the ease with which C functions can be called from Python, and the convenient handling of strings in Python. Moreover, the features of the Python language, combined with the fact that it is interpreted rather than compiled, have allowed for extremely quick prototyping.

  3. Ecological correlates of invasion impact for Burmese pythons in Florida

    USGS Publications Warehouse

    Reed, R.N.; Willson, J.D.; Rodda, G.H.; Dorcas, M.E.

    2012-01-01

    An invasive population of Burmese pythons (Python molurus bivittatus) is established across several thousand square kilometers of southern Florida and appears to have caused precipitous population declines among several species of native mammals. Why has this giant snake had such great success as an invasive species when many established reptiles have failed to spread? We scored the Burmese python for each of 15 literature-based attributes relative to predefined comparison groups from a diverse range of taxa and provide a review of the natural history and ecology of Burmese pythons relevant to each attribute. We focused on attributes linked to spread and magnitude of impacts rather than establishment success. Our results suggest that attributes related to body size and generalism appeared to be particularly applicable to the Burmese python's success in Florida. The attributes with the highest scores were: high reproductive potential, low vulnerability to predation, large adult body size, large offspring size and high dietary breadth. However, attributes of ectotherms in general and pythons in particular (including predatory mode, energetic efficiency and social interactions) might have also contributed to invasion success. Although establishment risk assessments are an important initial step in prevention of new establishments, evaluating species in terms of their potential for spreading widely and negatively impacting ecosystems might become part of the means by which resource managers prioritize control efforts in environments with large numbers of introduced species.

  4. Pythons metabolize prey to fuel the response to feeding.

    PubMed Central

    Starck, J. Matthias; Moser, Patrick; Werner, Roland A.; Linke, Petra

    2004-01-01

    We investigated the energy source fuelling the post-feeding metabolic upregulation (specific dynamic action, SDA) in pythons (Python regius). Our goal was to distinguish between two alternatives: (i) snakes fuel SDA by metabolizing energy depots from their tissues; or (ii) snakes fuel SDA by metabolizing their prey. To characterize the postprandial response of pythons we used transcutaneous ultrasonography to measure organ-size changes and respirometry to record oxygen consumption. To discriminate unequivocally between the two hypotheses, we enriched mice (= prey) with the stable isotope of carbon (13C). For two weeks after feeding we quantified the CO2 exhaled by pythons and determined its isotopic 13C/12C signature. Ultrasonography and respirometry showed typical postprandial responses in pythons. After feeding, the isotope ratio of the exhaled breath changed rapidly to values that characterized enriched mouse tissue, followed by a very slow change towards less enriched values over a period of two weeks after feeding. We conclude that pythons metabolize their prey to fuel SDA. The slowly declining delta13C values indicate that less enriched tissues (bone, cartilage and collagen) from the mouse become available after several days of digestion. PMID:15255044

  5. Ecological correlates of invasion impact for Burmese pythons in Florida.

    PubMed

    Reed, Robert N; Willson, John D; Rodda, Gordon H; Dorcas, Michael E

    2012-09-01

    An invasive population of Burmese pythons (Python molurus bivittatus) is established across several thousand square kilometers of southern Florida and appears to have caused precipitous population declines among several species of native mammals. Why has this giant snake had such great success as an invasive species when many established reptiles have failed to spread? We scored the Burmese python for each of 15 literature-based attributes relative to predefined comparison groups from a diverse range of taxa and provide a review of the natural history and ecology of Burmese pythons relevant to each attribute. We focused on attributes linked to spread and magnitude of impacts rather than establishment success. Our results suggest that attributes related to body size and generalism appeared to be particularly applicable to the Burmese python's success in Florida. The attributes with the highest scores were: high reproductive potential, low vulnerability to predation, large adult body size, large offspring size and high dietary breadth. However, attributes of ectotherms in general and pythons in particular (including predatory mode, energetic efficiency and social interactions) might have also contributed to invasion success. Although establishment risk assessments are an important initial step in prevention of new establishments, evaluating species in terms of their potential for spreading widely and negatively impacting ecosystems might become part of the means by which resource managers prioritize control efforts in environments with large numbers of introduced species.

  6. Sequencing the genome of the Burmese python (Python molurus bivittatus) as a model for studying extreme adaptations in snakes.

    PubMed

    Castoe, Todd A; de Koning, Jason A P; Hall, Kathryn T; Yokoyama, Ken D; Gu, Wanjun; Smith, Eric N; Feschotte, Cédric; Uetz, Peter; Ray, David A; Dobry, Jason; Bogden, Robert; Mackessy, Stephen P; Bronikowski, Anne M; Warren, Wesley C; Secor, Stephen M; Pollock, David D

    2011-07-28

    The Consortium for Snake Genomics is in the process of sequencing the genome and creating transcriptomic resources for the Burmese python. Here, we describe how this will be done, what analyses this work will include, and provide a timeline.

  7. Surgical management of maxillary and premaxillary osteomyelitis in a reticulated python (Python reticulatus).

    PubMed

    Latney, La'Toya V; McDermott, Colin; Scott, Gregory; Soltero-Rivera, Maria M; Beguesse, Kyla; Sánchez, Melissa D; Lewis, John R

    2016-05-01

    CASE DESCRIPTION A 1-year-old reticulated python (Python reticulatus) was evaluated because of a 2-week history of wheezing and hissing. CLINICAL FINDINGS Rostral facial cellulitis and deep gingival pockets associated with missing rostral maxillary teeth were evident. Tissues of the nares were swollen, resulting in an audible wheeze during respiration. Multiple scars and superficial facial wounds attributed to biting by live prey were apparent. Radiographic examination revealed bilateral, focal, rostral maxillary osteomyelitis. TREATMENT AND OUTCOME Wound irrigation, antimicrobials, and anti-inflammatory drug treatment resulted in reduced cellulitis. A 3-week regimen that included empirical antimicrobial treatment and improved husbandry resulted in resolution of the respiratory sounds and partial healing of bite wounds, but radiographic evaluation revealed progressive maxillary osteomyelitis. Microbial culture of blood yielded scant gram-positive cocci and Bacillus spp, which were suspected sample contaminants. Bilateral partial maxillectomies were performed; microbial culture and histologic examination of resected bone confirmed osteomyelitis with gram-positive cocci. Treatment with trimethoprim-sulfamethoxazole was initiated on the basis of microbial susceptibility tests. Four months later, follow-up radiography revealed premaxillary osteomyelitis; surgery was declined, and treatment with trimethoprim-sulfamethoxazole was reinstituted. Eight months after surgery, the patient was reevaluated because of recurrent clinical signs; premaxillectomy was performed, and treatment with trimethoprim-sulfamethoxazole was prescribed on the basis of microbial culture of bone and microbial susceptibility testing. Resolution of osteomyelitis was confirmed by CT 11 months after the initial surgery. CONCLUSIONS AND CLINICAL RELEVANCE Focal maxillectomies and premaxillectomy were successfully performed in a large python. Surgical management and appropriate antimicrobial treatment

  8. Renal plasticity in response to feeding in the Burmese python, Python molurus bivittatus.

    PubMed

    Esbaugh, A J; Secor, S M; Grosell, M

    2015-10-01

    Burmese pythons are sit-and-wait predators that are well adapted to go long periods without food, yet subsequently consume and digest single meals that can exceed their body weight. These large feeding events result in a dramatic alkaline tide that is compensated by a hypoventilatory response that normalizes plasma pH; however, little is known regarding how plasma HCO3(-) is lowered in the days post-feeding. The current study demonstrated that Burmese pythons contain the cellular machinery for renal acid-base compensation and actively remodel the kidney to limit HCO3(-) reabsorption in the post-feeding period. After being fed a 25% body weight meal plasma total CO2 was elevated by 1.5-fold after 1 day, but returned to control concentrations by 4 days post-feeding (d pf). Gene expression analysis was used to verify the presence of carbonic anhydrase (CA) II, IV and XIII, Na(+) H(+) exchanger 3 (NHE3), the Na(+) HCO3(-) co-transporter (NBC) and V-type ATPase. CA IV expression was significantly down-regulated at 3 dpf versus fasted controls. This was supported by activity analysis that showed a significant decrease in the amount of GPI-linked CA activity in isolated kidney membranes at 3 dpf versus fasted controls. In addition, V-type ATPase activity was significantly up-regulated at 3 dpf; no change in gene expression was observed. Both CA II and NHE3 expression was up-regulated at 3 dpf, which may be related to post-prandial ion balance. These results suggest that Burmese pythons actively remodel their kidney after feeding, which would in part benefit renal HCO3(-) clearance.

  9. Functional changes with feeding in the gastro-intestinal epithelia of the Burmese python (Python molurus).

    PubMed

    Helmstetter, Cécile; Reix, Nathalie; T'Flachebba, Mathieu; Pope, Robert K; Secor, Stephen M; Le Maho, Yvon; Lignot, Jean-Hervé

    2009-09-01

    The morphology of the digestive system in fasting and refed Burmese pythons was determined, as well as the localization of the proton (H(+), K(+)-ATPase) and sodium (Na(+), K(+)-ATPase) pumps. In fasting pythons, oxyntopeptic cells located within the fundic glands are typically non-active, with a thick apical tubulovesicular system and numerous zymogen granules. They become active Immediately after feeding but return to a non-active state 3 days after the Ingestion of the prey. The proton pump, expressed throughout the different fasting/feeding states, is either sequestered in the tubulovesicular system in non-active cells or located along the apical digitations extending within the crypt lumen in active cells. The sodium pump is rapidly upregulated in fed animals and is classically located along the baso-lateral membranes of the gastric oxyntopeptic cells. In the Intestine, it is only expressed along the lateral membranes of the enterocytes, i.e., above the lateral spaces and not along the basal side of the cells. Thus, solute transport within the Intestinal lining is mainly achieved through the apical part of the cells and across the lateral spaces while absorbed fat massively crosses the entire height of the cells and flows into the Intercellular spaces. Therefore, in the Burmese python, the gastrointestinal cellular system quickly upregulates after feeding, due to Inexpensive cellular changes, passive mechanisms, and the progressive activation and synthesis of key enzymes such as the sodium pump. This cell plasticity also allows anticipation of the next fasting and feeding periods.

  10. Azithromycin metabolite identification in plasma, bile, and tissues of the ball python (Python regius).

    PubMed

    Hunter, R P; Koch, D E; Coke, R L; Goatley, M A; Isaza, R

    2003-04-01

    Azithromycin is the first of a class of antibiotics classified as azalides. Six ball pythons (Python regius) were given a single dose of azithromycin at 10 mg/kg p.o. and i.v. in a crossover design. Serial blood samples were collected for unchanged azithromycin and to determine, if possible, the structure and number of circulating azithromycin metabolites. After a 4-month wash-out period, the snakes were given azithromycin p.o. as a single dose of 10 mg/kg for the study of azithromycin metabolism and metabolite tissue distribution. Bile, liver, lung, kidney, and skin samples were analyzed for the metabolites identified from the first experiment. Unchanged azithromycin accounted for 80, 68, and 60% of the total material at 12, 24, and 48 h postadministration in plasma, independent of route of administration. At both 24 and 72 h postadministration, azithromycin accounted for 70% of total azithromycin- associated material in bile. In liver and kidney, unchanged azithromycin accounted for 40% of the total azithromycin-associated material; this doubled in lung and skin. Fifteen metabolites were positively or tentatively identified in plasma, bile, or tissues of all snakes. Four of these possible metabolites: 3'-desamine-3-ene-azithromycin, descladinose dehydroxy-2-ene-azithromycin, 3'-desamine-3-ene descladinose-azithromycin, and 3'-N-nitroso,9a-N-desmethyl-azithromycin are unique to this species. Descladinose-azithromycin, 3'-N-desmethyl,9a-N-desmethyl-azithromycin, and 3'-N-desmethyl, 3'-O-desmethyl-azithromycin were the only metabolites identified in skin. Kidney tissue contained a greater number of metabolites than liver tissue, with 3'-N-didesmethyl-azithromycin being identified only in the kidney. Compared with the dog and cat, a greater number of metabolites were identified in ball python plasma. The percentage of unchanged azithromycin in bile is not different between the three species.

  11. Hydropy: Python package for hydrological time series handling based on Python Pandas

    NASA Astrophysics Data System (ADS)

    Van Hoey, Stijn; Balemans, Sophie; Nopens, Ingmar; Seuntjens, Piet

    2015-04-01

    Most hydrologists are dealing with time series frequently. Reading in time series, transforming them and extracting specific periods for visualisation are part of the daily work. Spreadsheet software is used a lot for these operations, but has some major drawbacks. It is mostly not reproducible, it is prone to errors and not easy to automate, which results in repetitive work when dealing with large amounts of data. Scripting languages like R and Python on the other hand, provide flexibility, enable automation and reproducibility and, hence, increase efficiency. Python has gained popularity over the last years and currently, tools for many aspects of scientific computing are readily available in Python. An increased support in controlling and managing the dependencies between packages (e.g. the Anaconda environment) allows for a wide audience to use the huge variety of available packages. Pandas is a powerful Python package for data analysis and has a lot of functionalities related to time series. As such, the package is of special interest to hydrologists. Some other packages, focussing on hydrology (e.g. Hydroclimpy by Pierre Gerard-Marchant and Hydropy by Javier Rovegno Campos), stopped active development, mainly due to the superior implementation of Pandas. We present a (revised) version of the Hydropy package that is inspired by the aforementioned packages and builds on the power of Pandas. The main idea is to add hydrological domain knowledge to the already existing Pandas functionalities. Besides, the package attempts to make the time series handling intuitive and easy to perform, thus with a clear syntax. Some illustrative examples of the current implementation starting from a Pandas DataFrame named flowdata: Creating the object flow to work with: flow = HydroAnalysis(flowdata) Retrieve only the data during winter (across all years): flow.get_season('winter') Retrieve only the data during summer of 2010: flow.get_season('summer').get_year('2010') which is

  12. Morphological respiratory diffusion capacity of the lungs of ball pythons (Python regius).

    PubMed

    Starck, J Matthias; Aupperle, Heike; Kiefer, Ingmar; Weimer, Isabel; Krautwald-Junghanns, Maria-Elisabeth; Pees, Michael

    2012-08-01

    This study aims at a functional and morphological characterization of the lung of a boid snake. In particular, we were interested to see if the python's lungs are designed with excess capacity as compared to resting and working oxygen demands. Therefore, the morphological respiratory diffusion capacity of ball pythons (Python regius) was examined following a stereological, hierarchically nested approach. The volume of the respiratory exchange tissue was determined using computed tomography. Tissue compartments were quantified using stereological methods on light microscopic images. The tissue diffusion barrier for oxygen transport was characterized and measured using transmission electron micrographs. We found a significant negative correlation between body mass and the volume of respiratory tissue; the lungs of larger snakes had relatively less respiratory tissue. Therefore, mass-specific respiratory tissue was calculated to exclude effects of body mass. The volume of the lung that contains parenchyma was 11.9±5.0mm(3)g(-1). The volume fraction, i.e., the actual pulmonary exchange tissue per lung parenchyma, was 63.22±7.3%; the total respiratory surface was, on average, 0.214±0.129m(2); it was significantly negatively correlated to body mass, with larger snakes having proportionally smaller respiratory surfaces. For the air-blood barrier, a harmonic mean of 0.78±0.05μm was found, with the epithelial layer representing the thickest part of the barrier. Based on these findings, a median diffusion capacity of the tissue barrier ( [Formula: see text] ) of 0.69±0.38ml O(2)min(-1)mmHg(-1) was calculated. Based on published values for blood oxygen concentration, a total oxygen uptake capacity of 61.16mlO(2)min(-1)kg(-1) can be assumed. This value exceeds the maximum demand for oxygen in ball pythons by a factor of 12. We conclude that healthy individuals of P. regius possess a considerable spare capacity for tissue oxygen exchange.

  13. Bioinformatic pipelines in Python with Leaf

    PubMed Central

    2013-01-01

    Background An incremental, loosely planned development approach is often used in bioinformatic studies when dealing with custom data analysis in a rapidly changing environment. Unfortunately, the lack of a rigorous software structuring can undermine the maintainability, communicability and replicability of the process. To ameliorate this problem we propose the Leaf system, the aim of which is to seamlessly introduce the pipeline formality on top of a dynamical development process with minimum overhead for the programmer, thus providing a simple layer of software structuring. Results Leaf includes a formal language for the definition of pipelines with code that can be transparently inserted into the user’s Python code. Its syntax is designed to visually highlight dependencies in the pipeline structure it defines. While encouraging the developer to think in terms of bioinformatic pipelines, Leaf supports a number of automated features including data and session persistence, consistency checks between steps of the analysis, processing optimization and publication of the analytic protocol in the form of a hypertext. Conclusions Leaf offers a powerful balance between plan-driven and change-driven development environments in the design, management and communication of bioinformatic pipelines. Its unique features make it a valuable alternative to other related tools. PMID:23786315

  14. Matriarch: A Python Library for Materials Architecture.

    PubMed

    Giesa, Tristan; Jagadeesan, Ravi; Spivak, David I; Buehler, Markus J

    2015-10-12

    Biological materials, such as proteins, often have a hierarchical structure ranging from basic building blocks at the nanoscale (e.g., amino acids) to assembled structures at the macroscale (e.g., fibers). Current software for materials engineering allows the user to specify polypeptide chains and simple secondary structures prior to molecular dynamics simulation, but is not flexible in terms of the geometric arrangement of unequilibrated structures. Given some knowledge of a larger-scale structure, instructing the software to create it can be very difficult and time-intensive. To this end, the present paper reports a mathematical language, using category theory, to describe the architecture of a material, i.e., its set of building blocks and instructions for combining them. While this framework applies to any hierarchical material, here we concentrate on proteins. We implement this mathematical language as an open-source Python library called Matriarch. It is a domain-specific language that gives the user the ability to create almost arbitrary structures with arbitrary amino acid sequences and, from them, generate Protein Data Bank (PDB) files. In this way, Matriarch is more powerful than commercial software now available. Matriarch can be used in tandem with molecular dynamics simulations and helps engineers design and modify biologically inspired materials based on their desired functionality. As a case study, we use our software to alter both building blocks and building instructions for tropocollagen, and determine their effect on its structure and mechanical properties.

  15. Matriarch: A Python Library for Materials Architecture

    PubMed Central

    Buehler, Markus J.

    2016-01-01

    Biological materials, such as proteins, often have a hierarchical structure ranging from basic building blocks at the nanoscale (e.g., amino acids) to assembled structures at the macroscale (e.g., fibers). Current software for materials engineering allows the user to specify polypeptide chains and simple secondary structures prior to molecular dynamics simulation, but is not flexible in terms of the geometric arrangement of unequilibrated structures. Given some knowledge of a larger-scale structure, instructing the software to create it can be very difficult and time-intensive. To this end, the present paper reports a mathematical language, using category theory, to describe the architecture of a material, i.e., its set of building blocks and instructions for combining them. While this framework applies to any hierarchical material, here we concentrate on proteins. We implement this mathematical language as an open-source Python library called Matriarch. It is a domain-specific language that gives the user the ability to create almost arbitrary structures with arbitrary amino acid sequences and, from them, generate Protein Data Bank (PDB) files. In this way, Matriarch is more powerful than commercial software now available. Matriarch can be used in tandem with molecular dynamics simulations and helps engineers design and modify biologically inspired materials based on their desired functionality. As a case study, we use our software to alter both building blocks and building instructions for tropocollagen, and determine their effect on its structure and mechanical properties. PMID:27570830

  16. TRIPPy: Trailed Image Photometry in Python

    NASA Astrophysics Data System (ADS)

    Fraser, Wesley; Alexandersen, Mike; Schwamb, Megan E.; Marsset, Michaël; Pike, Rosemary E.; Kavelaars, J. J.; Bannister, Michele T.; Benecchi, Susan; Delsanti, Audrey

    2016-06-01

    Photometry of moving sources typically suffers from a reduced signal-to-noise ratio (S/N) or flux measurements biased to incorrect low values through the use of circular apertures. To address this issue, we present the software package, TRIPPy: TRailed Image Photometry in Python. TRIPPy introduces the pill aperture, which is the natural extension of the circular aperture appropriate for linearly trailed sources. The pill shape is a rectangle with two semicircular end-caps and is described by three parameters, the trail length and angle, and the radius. The TRIPPy software package also includes a new technique to generate accurate model point-spread functions (PSFs) and trailed PSFs (TSFs) from stationary background sources in sidereally tracked images. The TSF is merely the convolution of the model PSF, which consists of a moffat profile, and super-sampled lookup table. From the TSF, accurate pill aperture corrections can be estimated as a function of pill radius with an accuracy of 10 mmag for highly trailed sources. Analogous to the use of small circular apertures and associated aperture corrections, small radius pill apertures can be used to preserve S/Ns of low flux sources, with appropriate aperture correction applied to provide an accurate, unbiased flux measurement at all S/Ns.

  17. Python algorithms in particle tracking microrheology

    PubMed Central

    2012-01-01

    Background Particle tracking passive microrheology relates recorded trajectories of microbeads, embedded in soft samples, to the local mechanical properties of the sample. The method requires intensive numerical data processing and tools allowing control of the calculation errors. Results We report the development of a software package collecting functions and scripts written in Python for automated and manual data processing, to extract viscoelastic information about the sample using recorded particle trajectories. The resulting program package analyzes the fundamental diffusion characteristics of particle trajectories and calculates the frequency dependent complex shear modulus using methods published in the literature. In order to increase conversion accuracy, segmentwise, double step, range-adaptive fitting and dynamic sampling algorithms are introduced to interpolate the data in a splinelike manner. Conclusions The presented set of algorithms allows for flexible data processing for particle tracking microrheology. The package presents improved algorithms for mean square displacement estimation, controlling effects of frame loss during recording, and a novel numerical conversion method using segmentwise interpolation, decreasing the conversion error from about 100% to the order of 1%. PMID:23186362

  18. Python-Assisted MODFLOW Application and Code Development

    NASA Astrophysics Data System (ADS)

    Langevin, C.

    2013-12-01

    The U.S. Geological Survey (USGS) has a long history of developing and maintaining free, open-source software for hydrological investigations. The MODFLOW program is one of the most popular hydrologic simulation programs released by the USGS, and it is considered to be the most widely used groundwater flow simulation code. MODFLOW was written using a modular design and a procedural FORTRAN style, which resulted in code that could be understood, modified, and enhanced by many hydrologists. The code is fast, and because it uses standard FORTRAN it can be run on most operating systems. Most MODFLOW users rely on proprietary graphical user interfaces for constructing models and viewing model results. Some recent efforts, however, have focused on construction of MODFLOW models using open-source Python scripts. Customizable Python packages, such as FloPy (https://code.google.com/p/flopy), can be used to generate input files, read simulation results, and visualize results in two and three dimensions. Automating this sequence of steps leads to models that can be reproduced directly from original data and rediscretized in space and time. Python is also being used in the development and testing of new MODFLOW functionality. New packages and numerical formulations can be quickly prototyped and tested first with Python programs before implementation in MODFLOW. This is made possible by the flexible object-oriented design capabilities available in Python, the ability to call FORTRAN code from Python, and the ease with which linear systems of equations can be solved using SciPy, for example. Once new features are added to MODFLOW, Python can then be used to automate comprehensive regression testing and ensure reliability and accuracy of new versions prior to release.

  19. The spectacle of the ball python (Python regius): a morphological description.

    PubMed

    Da Silva, Mari-Ann O; Heegaard, Steffen; Wang, Tobias; Nyengaard, Jens R; Bertelsen, Mads F

    2014-05-01

    A detailed morphological description of the spectacle of the ball python (Python regius) is provided. The eyes of 21 snakes were examined by light microscopy and/or transmission electron microscopy. Additionally, eyes of nine live snakes were examined using optical coherence tomography (OCT) and Scheimpflug scanning (Pentacam). The spectacle consists of three layers: outer epithelium, stroma and inner epithelium. The outer epithelium is made up of flat basal cells overlaid by keratin, the stroma consists of organized layers of collagen fibrils with interweaving nerve fibers and blood vessels, and the inner epithelium holds squamous cells containing vesicles and microvilli. At the rim of the spectacle, there is a transition zone, where the spectacle merges with the epidermis and dermis of the periocular scales. This zone is characterized by a greater height of the basal cells of the outer epithelium and a less orderly organization of the stroma compared with the spectacle proper. The thickness of the spectacle was uniform throughout. It averaged 96 ± 10 µm in histological specimens and 108 ± 13 µm using OCT. The subspectacular space was extremely narrow in the live snakes; however, the space was visible at the periphery of the spectacle with OCT.

  20. The influence of mechanical ventilation on physiological parameters in ball pythons (Python regius).

    PubMed

    Jakobsen, Sashia L; Williams, Catherine J A; Wang, Tobias; Bertelsen, Mads F

    2017-02-10

    Mechanical ventilation is widely recommended for reptiles during anesthesia, and while it is well-known that their low ectothermic metabolism requires much lower ventilation than in mammals, very little is known about the influence of ventilation protocol on the recovery from anesthesia. Here, 15 ball pythons (Python regius) were induced and maintained with isoflurane for 60min at one of three ventilation protocols (30, 125, or 250mlmin(-1)kg(-1) body mass) while an arterial catheter was inserted, and ventilation was then continued on 100% oxygen at the specified rate until voluntary extubation. Mean arterial blood pressure and heart rate (HR) were measured, and arterial blood samples collected at 60, 80, 180min and 12 and 24h after intubation. In all three groups, there was evidence of a metabolic acidosis, and snakes maintained at 30mlmin(-1)kg(-1) experienced an additional respiratory acidosis, while the two other ventilation protocols resulted in normal or low arterial PCO2. In general, normal acid-base status was restored within 12h in all three protocols. HR increased by 143±64% during anesthesia with high mechanical ventilation (250mlmin(-1)kg(-1)) in comparison with recovered values. Recovery times after mechanical ventilation at 30, 125, or 250mlmin(-1)kg(-1) were 289±70, 126±16, and 68±7min, respectively. Mild overventilation may result in a faster recovery, and the associated lowering of arterial PCO2 normalised arterial pH in the face of metabolic acidosis.

  1. The effect of meal composition on specific dynamic action in burmese pythons (Python molurus).

    PubMed

    McCue, M D; Bennett, A F; Hicks, J W

    2005-01-01

    We quantified the specific dynamic action (SDA) resulting from the ingestion of various meal types in Burmese pythons (Python molurus) at 30 degrees C. Each snake was fed a series of experimental meals consisting of amino acid mixtures, simple proteins, simple or complex carbohydrates, or lipids as well as meals of whole animal tissue (chicken breast, beef suet, and mouse). Rates of oxygen consumption were measured for approximately 4 d after feeding, and the increment above standard metabolic rate was determined and compared to energy content of the meals. While food type (protein, carbohydrate, and lipid) had a general influence, SDA was highly dependent on meal composition (i.e., amino acid composition and carbohydrate structure). For chicken breast and simple carbohydrates, the SDA coefficient was approximately one-third the energetic content of the meal. Lard, suet, cellulose, and starch were not digested and did not produce measurable SDA. We conclude that the cost of de novo protein synthesis is an important component of SDA after ingestion of protein meals because (1) simple proteins, such as gelatin and collagen, did not stimulate levels of SDA attained after consumption of complete protein, (2) incomplete mixtures of amino acids failed to elicit the SDA of a complete mixture, and (3) the inhibition of de novo protein synthesis with the drug cycloheximide caused a more than 70% decrease in SDA. Stomach distension and mechanical digestion of intact prey did not cause measurable SDA.

  2. Purification and characterization of islet hormones (insulin, glucagon, pancreatic, polypeptide and somatostatin) from the Burmese python, Python molurus.

    PubMed

    Conlon, J M; Secor, S M; Adrian, T E; Mynarcik, D C; Whittaker, J

    1997-08-29

    Insulin was purified from an extract of the pancreas of the Burmese python, Python molurus (Squamata:Serpentes) and its primary structure established as: A Chain: Gly-Ile-Val-Glu-Gln-Cys-Cys-Glu-Asn-Thr10-Cys-Ser-Leu-Tyr-Glu-Leu- Glu-Asn-Tyr-Cys20-Asn. B-Chain: Ala-Pro-Asn-Gln-His-Leu-Cys-Gly-Ser-His10-Leu-Val-Glu-Ala-Leu-Tyr- Leu-Val-Cys-Gly20-Asp-Arg-Gly-Phe-Tyr-Tyr-Ser-Pro-Arg-Ser30. With the exception of the conservative substitution Phe --> Tyr at position B25, those residues in human insulin that comprise the receptor-binding and those residues involved in dimer and hexamer formation are fully conserved in python insulin. Python insulin was slightly more potent (1.8-fold) than human insulin in inhibiting the binding of [125I-Tyr-A14] insulin to the soluble full-length recombinant human insulin receptor but was slightly less potent (1.5-fold) than human insulin for inhibiting binding to the secreted extracellular domain of the receptor. The primary structure of python glucagon contains only one amino acid substitution (Ser28 --> Asn) compared with turtle/duck glucagon and python somatostatin is identical to that of mammalian somatostatin-14. In contrast, python pancreatic polypeptide (Arg-Ile-Ala-Pro-Val-Phe-Pro-Gly-Lys-Asp10-Glu-Leu-Ala-Lys-Phe- Tyr20-Thr-Glu-Leu-Gln-Gln-Tyr-Leu-Asn-Ser-Ile30-Asn-Arg-Pro-Arg -Phe.NH2) contains only 35 instead of the customary 36 residues and the amino acid sequence of this peptide has been poorly conserved between reptiles and birds (18 substitutions compared with alligator and 20 substitutions compared with chicken).

  3. Cosmic Microwave Background Anisotropy Measurement from Python V

    NASA Astrophysics Data System (ADS)

    Coble, K.; Dodelson, S.; Dragovan, M.; Ganga, K.; Knox, L.; Kovac, J.; Ratra, B.; Souradeep, T.

    2003-02-01

    We analyze observations of the microwave sky made with the Python experiment in its fifth year of operation at the Amundsen-Scott South Pole Station in Antarctica. After modeling the noise and constructing a map, we extract the cosmic signal from the data. We simultaneously estimate the angular power spectrum in eight bands ranging from large (l~40) to small (l~260) angular scales, with power detected in the first six bands. There is a significant rise in the power spectrum from large to smaller (l~200) scales, consistent with that expected from acoustic oscillations in the early universe. We compare this Python V map to a map made from data taken in the third year of Python. Python III observations were made at a frequency of 90 GHz and covered a subset of the region of the sky covered by Python V observations, which were made at 40 GHz. Good agreement is obtained both visually (with a filtered version of the map) and via a likelihood ratio test.

  4. Scripting MODFLOW Model Development Using Python and FloPy.

    PubMed

    Bakker, M; Post, V; Langevin, C D; Hughes, J D; White, J T; Starn, J J; Fienen, M N

    2016-09-01

    Graphical user interfaces (GUIs) are commonly used to construct and postprocess numerical groundwater flow and transport models. Scripting model development with the programming language Python is presented here as an alternative approach. One advantage of Python is that there are many packages available to facilitate the model development process, including packages for plotting, array manipulation, optimization, and data analysis. For MODFLOW-based models, the FloPy package was developed by the authors to construct model input files, run the model, and read and plot simulation results. Use of Python with the available scientific packages and FloPy facilitates data exploration, alternative model evaluations, and model analyses that can be difficult to perform with GUIs. Furthermore, Python scripts are a complete, transparent, and repeatable record of the modeling process. The approach is introduced with a simple FloPy example to create and postprocess a MODFLOW model. A more complicated capture-fraction analysis with a real-world model is presented to demonstrate the types of analyses that can be performed using Python and FloPy.

  5. Scripting MODFLOW model development using Python and FloPy

    USGS Publications Warehouse

    Bakker, Mark; Post, Vincent E. A.; Langevin, Christian D.; Hughes, Joseph D.; White, Jeremy; Starn, Jeffrey; Fienen, Michael N.

    2016-01-01

    Graphical user interfaces (GUIs) are commonly used to construct and postprocess numerical groundwater flow and transport models. Scripting model development with the programming language Python is presented here as an alternative approach. One advantage of Python is that there are many packages available to facilitate the model development process, including packages for plotting, array manipulation, optimization, and data analysis. For MODFLOW-based models, the FloPy package was developed by the authors to construct model input files, run the model, and read and plot simulation results. Use of Python with the available scientific packages and FloPy facilitates data exploration, alternative model evaluations, and model analyses that can be difficult to perform with GUIs. Furthermore, Python scripts are a complete, transparent, and repeatable record of the modeling process. The approach is introduced with a simple FloPy example to create and postprocess a MODFLOW model. A more complicated capture-fraction analysis with a real-world model is presented to demonstrate the types of analyses that can be performed using Python and FloPy.

  6. PvaPy: Python API for EPICS PV Access

    SciTech Connect

    Veseli, S.

    2016-01-01

    As the number of sites deploying and adopting EPICS Version 4 grows, so does the need to support PV Access from multiple languages. Especially important are the widely used scripting languages that tend to reduce both software development time and the learning curve for new users. In this paper we describe PvaPy, a Python API for the EPICS PV Access protocol and its accompanying structured data API. Rather than implementing the protocol itself in Python, PvaPy wraps the existing EPICS Version 4 C++ libraries using the Boost.Python framework. This approach allows us to benefit from the existing code base and functionality, and to significantly reduce the Python API development effort. PvaPy objects are based on Python dictionaries and provide users with the ability to access even the most complex of PV Data structures in a relatively straightforward way. Its interfaces are easy to use, and include support for advanced EPICS Version 4 features such as implementation of client and server Remote Procedure Calls (RPC).

  7. pyam: Python Implementation of YaM

    NASA Technical Reports Server (NTRS)

    Myint, Steven; Jain, Abhinandan

    2012-01-01

    pyam is a software development framework with tools for facilitating the rapid development of software in a concurrent software development environment. pyam provides solutions for development challenges associated with software reuse, managing multiple software configurations, developing software product lines, and multiple platform development and build management. pyam uses release-early, release-often development cycles to allow developers to integrate their changes incrementally into the system on a continual basis. It facilitates the creation and merging of branches to support the isolated development of immature software to avoid impacting the stability of the development effort. It uses modules and packages to organize and share software across multiple software products, and uses the concepts of link and work modules to reduce sandbox setup times even when the code-base is large. One sidebenefit is the enforcement of a strong module-level encapsulation of a module s functionality and interface. This increases design transparency, system stability, and software reuse. pyam is written in Python and is organized as a set of utilities on top of the open source SVN software version control package. All development software is organized into a collection of modules. pyam packages are defined as sub-collections of the available modules. Developers can set up private sandboxes for module/package development. All module/package development takes place on private SVN branches. High-level pyam commands support the setup, update, and release of modules and packages. Released and pre-built versions of modules are available to developers. Developers can tailor the source/link module mix for their sandboxes so that new sandboxes (even large ones) can be built up easily and quickly by pointing to pre-existing module releases. All inter-module interfaces are publicly exported via links. A minimal, but uniform, convention is used for building modules.

  8. Synthetic seismogram web service and Python tools

    NASA Astrophysics Data System (ADS)

    Heimann, Sebastian; Cesca, Simone; Kriegerowski, Marius; Dahm, Torsten

    2014-05-01

    Many geophysical methods require knowledge of Green's functions (GF) or synthetic seismograms in dependence of ranges of source and receiver coordinates. Examples include synthetic seismogram generation, moment tensor inversion, the modeling of depth phases for regional and teleseismic earthquakes, or the modeling of pressure diffusion induced static displacement and strain. Calculation of Green's functions is a computationally expensive operation and it can be of advantage to calculate them in advance: the same Green's function traces can then be reused several or many times as required in a typical application. Regarding Green's function computation as an independent step in a use-case's processing chain encourages to store these in an application independent form. They can then be shared between different applications and they can also be passed to other researchers, e.g. via a web service. Starting now, we provide such a web service to the seismological community (http://kinherd.org/), where a researcher can share Green's function stores and retrieve synthetic seismograms for various point and extended earthquake source models for many different earth models at local, regional and global scale. This web service is part of a rich new toolset for the creation and handling of Green's functions and synthetic seismograms (http://emolch.github.com/pyrocko/gf). It can be used off-line or in client mode. Its core features are: greatly simplified generation of Green's function stores supports various codes for Green's function computation extensible Green's function storage format flexible spacial indexing of Green's functions integrated travel time computation support for other types of Green's functions; e.g. poro-elastic GFs written in Python

  9. A Python interface with Narcisse graphics

    SciTech Connect

    Motteler, Z.C.

    1996-04-15

    Narcisse is a graphics package developed by our French colleagues at Centre d`Etudes de Limeil Valenton of the Commissariat d`Energie Atomique. Narcisse is quite comprehensive; it can do two-, three-, and four-dimensional plots (the latter meaning that the surface is colored according to the values of an arbitrary function). One can open and send plots to a Narcisse window on a distant machine. Narcisse has a user-friendly graphical user interface (GUI) which, once a graph has appeared, allows the user to change its characteristics interactively. This enables one to find the best appearance for a particular plot without having to graph it repeatedly from the user program. Previously created files in various formats can also be imported directly into the Narcisse GUI and manipulated from there. Narcisse runs independently, as a graphics server. The user program communicates with Narcisse via Unix sockets. This communication is quite low level and very complex. The appearance of a plot is controlled by nearly 150 parameters for determining such things as the color palette, type of shading, axis scales, curve and surface labels, titles, angle and distance of view (for three- and four-dimensional graphs), hidden line removal, etc. Most end users do not wish to spend time learning the tedious details of such interfaces; they would just like to specify data and ask to have it plotted. This paper describes a high level, easy to use graphics interface which hides (as much as possible) the low level details of whatever graphics system is actually being used, so that the low level can be essentially ``plug-and-play.`` Then, whenever a better system becomes available, it should only be necessary to change low level interface routines not normally accessed by ordinary users. Python, with its easy extendability, was ideally suited for this job.

  10. The effects of UV light on calcium metabolism in ball pythons (Python regius).

    PubMed

    Hedley, J; Eatwell, K

    2013-10-12

    Despite the popularity of keeping snakes in captivity, there has been limited investigation into the effects of UV radiation on vitamin D levels in snakes. The aim of this study was to investigate the effects of UV-b radiation on plasma 25-hydroxyvitamin D3 levels and ionised calcium concentrations in ball pythons (Python regius). Blood samples were taken from 14 ball pythons, which had never been exposed to UV-b light, to obtain baseline 25-hydroxyvitamin D3 levels and ionised calcium concentrations. Blood samples were then taken again from the same snakes 70 days later after one group (Group 1, n=6 females) were exposed to UV-b radiation daily, and the other group (Group 2, n=5 males and 3 females) were exposed to no UV-b radiation. Mean±sd 25-hydroxyvitamin D3 levels on day 0 in Group 1 were 197±35 nmol/l, and on day 70 were 203.5±13.8 nmol/l. Mean±sd 25-hydroxyvitamin D3 levels in Group 2 on day 0 were 77.7±41.5 nmol/l, and on day 70 were 83.0±41.9 nmol/l. Mean±sd ionised calcium levels at day 0 were 1.84±0.05 mmol/l for Group 1, and on day 70 were 1.78±0.07 mmol/l. Mean±sd ionised calcium levels at day 0 were 1.79±0.07 mmol/l for Group 2, and on day 70 were 1.81±0.05 mmol/l. No association was demonstrated between exposure to UV-b radiation and plasma 25-hydroxyvitamin D3 and ionised calcium concentrations. These results may provide baseline parameters for future studies in this and other snake species to determine ability to utilise UV-b light for vitamin D production.

  11. Leveraging Comparative Genomics to Identify and Functionally Characterize Genes Associated with Sperm Phenotypes in Python bivittatus (Burmese Python).

    PubMed

    Irizarry, Kristopher J L; Rutllant, Josep

    2016-01-01

    Comparative genomics approaches provide a means of leveraging functional genomics information from a highly annotated model organism's genome (such as the mouse genome) in order to make physiological inferences about the role of genes and proteins in a less characterized organism's genome (such as the Burmese python). We employed a comparative genomics approach to produce the functional annotation of Python bivittatus genes encoding proteins associated with sperm phenotypes. We identify 129 gene-phenotype relationships in the python which are implicated in 10 specific sperm phenotypes. Results obtained through our systematic analysis identified subsets of python genes exhibiting associations with gene ontology annotation terms. Functional annotation data was represented in a semantic scatter plot. Together, these newly annotated Python bivittatus genome resources provide a high resolution framework from which the biology relating to reptile spermatogenesis, fertility, and reproduction can be further investigated. Applications of our research include (1) production of genetic diagnostics for assessing fertility in domestic and wild reptiles; (2) enhanced assisted reproduction technology for endangered and captive reptiles; and (3) novel molecular targets for biotechnology-based approaches aimed at reducing fertility and reproduction of invasive reptiles. Additional enhancements to reptile genomic resources will further enhance their value.

  12. Leveraging Comparative Genomics to Identify and Functionally Characterize Genes Associated with Sperm Phenotypes in Python bivittatus (Burmese Python)

    PubMed Central

    Rutllant, Josep

    2016-01-01

    Comparative genomics approaches provide a means of leveraging functional genomics information from a highly annotated model organism's genome (such as the mouse genome) in order to make physiological inferences about the role of genes and proteins in a less characterized organism's genome (such as the Burmese python). We employed a comparative genomics approach to produce the functional annotation of Python bivittatus genes encoding proteins associated with sperm phenotypes. We identify 129 gene-phenotype relationships in the python which are implicated in 10 specific sperm phenotypes. Results obtained through our systematic analysis identified subsets of python genes exhibiting associations with gene ontology annotation terms. Functional annotation data was represented in a semantic scatter plot. Together, these newly annotated Python bivittatus genome resources provide a high resolution framework from which the biology relating to reptile spermatogenesis, fertility, and reproduction can be further investigated. Applications of our research include (1) production of genetic diagnostics for assessing fertility in domestic and wild reptiles; (2) enhanced assisted reproduction technology for endangered and captive reptiles; and (3) novel molecular targets for biotechnology-based approaches aimed at reducing fertility and reproduction of invasive reptiles. Additional enhancements to reptile genomic resources will further enhance their value. PMID:27200191

  13. The Astropy Project: A community Python library for astronomy

    NASA Astrophysics Data System (ADS)

    Sipocz, Brigitta; Robitaille, Thomas; Tollerud, Erik

    2016-03-01

    The Astropy Project is a community effort to develop a single core package for Astronomy in Python and foster interoperability between Python Astronomy packages, and is one of the largest open-source collaborations in Astronomy. In this talk I present an overview of the project, provide an update on the latest status of the core package, which saw the v1.1 release late last year, and discuss our plans for the coming year. In addition, I describe the "affiliated packages": Python packages that use Astropy and are associated with the project, but are not actually a part of the core library itself. I also briefly talk about the infrastructural tools we provide for these packages.

  14. High performance Python for direct numerical simulations of turbulent flows

    NASA Astrophysics Data System (ADS)

    Mortensen, Mikael; Langtangen, Hans Petter

    2016-06-01

    Direct Numerical Simulations (DNS) of the Navier Stokes equations is an invaluable research tool in fluid dynamics. Still, there are few publicly available research codes and, due to the heavy number crunching implied, available codes are usually written in low-level languages such as C/C++ or Fortran. In this paper we describe a pure scientific Python pseudo-spectral DNS code that nearly matches the performance of C++ for thousands of processors and billions of unknowns. We also describe a version optimized through Cython, that is found to match the speed of C++. The solvers are written from scratch in Python, both the mesh, the MPI domain decomposition, and the temporal integrators. The solvers have been verified and benchmarked on the Shaheen supercomputer at the KAUST supercomputing laboratory, and we are able to show very good scaling up to several thousand cores. A very important part of the implementation is the mesh decomposition (we implement both slab and pencil decompositions) and 3D parallel Fast Fourier Transforms (FFT). The mesh decomposition and FFT routines have been implemented in Python using serial FFT routines (either NumPy, pyFFTW or any other serial FFT module), NumPy array manipulations and with MPI communications handled by MPI for Python (mpi4py). We show how we are able to execute a 3D parallel FFT in Python for a slab mesh decomposition using 4 lines of compact Python code, for which the parallel performance on Shaheen is found to be slightly better than similar routines provided through the FFTW library. For a pencil mesh decomposition 7 lines of code is required to execute a transform.

  15. Record length, mass, and clutch size in the nonindigenous Burmese Python, Python bivittatus Kuhl 1820 (Squamata: Pythonidae), in Florida

    USGS Publications Warehouse

    Krysko, Kenneth L.; Hart, Kristen M.; Smith, Brian J.; Selby, Thomas H.; Cherkiss, Michael S.; Coutu, Nicholas T.; Reichart, Rebecca M.; Nuñez, Leroy P.; Mazzotti, Frank J.; Snow, Ray W.

    2012-01-01

    The Burmese Python, Python bivittatus Kuhl 1820 (Squamata: Pythonidae), is indigenous to northern India,east to southern China, and south to Vietnam and a few islands in Indonesia (Barker and Barker 2008, Reed and Rodda 2009). This species has been introduced since at least 1979 in southern Florida, USA, where it likely began reproducing and became established during the 1980s (Meshaka et al. 2000, Snowet al. 2007b,Kraus 2009, Krysko et al. 2011, Willson et al. 2011). Python bivittatus has been documented in Florida consuming a variety of mammals and birds, and the American Alligator(Alligator mississippiensis) (Snowet al. 2007a, 2007b; Harvey et al. 2008; Rochford et al. 2010b; Holbrook and Chesnes 2011), many of which are protected species. Herein, we provide details on two of the largest known wild P. bivittatus in Florida to date, including current records on length,mass,clutch size, and diet.

  16. The big squeeze: scaling of constriction pressure in two of the world's largest snakes, Python reticulatus and Python molurus bivittatus.

    PubMed

    Penning, David A; Dartez, Schuyler F; Moon, Brad R

    2015-11-01

    Snakes are important predators that have radiated throughout many ecosystems, and constriction was important in their radiation. Constrictors immobilize and kill prey by using body loops to exert pressure on their prey. Despite its importance, little is known about constriction performance or its full effects on prey. We studied the scaling of constriction performance in two species of giant pythons (Python reticulatus and Python molurus bivittatus) and propose a new mechanism of prey death by constriction. In both species, peak constriction pressure increased significantly with snake diameter. These and other constrictors can exert pressures dramatically higher than their prey's blood pressure, suggesting that constriction can stop circulatory function and perhaps kill prey rapidly by over-pressurizing the brain and disrupting neural function. We propose the latter 'red-out effect' as another possible mechanism of prey death from constriction. These effects may be important to recognize and treat properly in rare cases when constrictors injure humans.

  17. Photodermatitis and photokeratoconjunctivitis in a ball python (Python regius) and a blue-tongue skink (Tiliqua spp.).

    PubMed

    Gardiner, David W; Baines, Frances M; Pandher, Karamjeet

    2009-12-01

    A male ball python (Python regius) and a female blue tongue skink (Tiliqua spp.) of unknown age were evaluated for anorexia, lethargy, excessive shedding, corneal opacity (python), and weight loss (skink) of approximately three weeks' duration. These animals represented the worst affected animals from a private herpetarium where many animals exhibited similar signs. At necropsy, the python had bilateral corneal opacity and scattered moderate dysecdysis. The skink had mild dysecdysis, poor body condition, moderate intestinal nematodiasis, and mild liver atrophy. Microscopic evaluation revealed epidermal erosion and ulceration, with severe epidermal basal cell degeneration and necrosis, and superficial dermatitis (python and skink). Severe bilateral ulcerative keratoconjunctivitis with bacterial colonization was noted in the ball python. Microscopic findings within the skin and eyes were suggestive of ultraviolet (UV) radiation damage or of photodermatitis and photokeratoconjunctivitis. Removal of the recently installed new lamps from the terrariums of the surviving reptiles resulted in resolution of clinical signs. Evaluation of a sample lamp of the type associated with these cases revealed an extremely high UV output, including very-short-wavelength UVB, neither found in natural sunlight nor emitted by several other UVB lamps unassociated with photokeratoconjunctivitis. Exposure to high-intensity and/or inappropriate wavelengths of UV radiation may be associated with significant morbidity, and even mortality, in reptiles. Veterinarians who are presented with reptiles with ocular and/or cutaneous disease of unapparent cause should fully evaluate the specifics of the vivarium light sources. Further research is needed to determine the characteristics of appropriate and of toxic UV light for reptiles kept in captivity.

  18. Double valvular insufficiency in a Burmese python (Python molurus bivittatus, Linnaeus, 1758) suffering from concomitant bacterial pneumonia.

    PubMed

    Schilliger, Lionel; Tréhiou-Sechi, Emilie; Petit, Amandine M P; Misbach, Charlotte; Chetboul, Valérie

    2010-12-01

    Ultrasonography, and, to a lesser extent, echocardiography are now well-established, noninvasive, and painless diagnostic tools in herpetologic medicine. Various cardiac lesions have been previously described in reptiles, but valvulopathy is rarely documented in these animals and, consequently, is poorly understood. In this report, sinoatrial and atrioventricular insufficiencies were diagnosed in a 5-yr-old captive dyspneic Burmese python (Python molurus bivittatus) on the basis of echocardiographic and Doppler examination. This case report is the first to document Doppler assessment of valvular regurgitations in a reptile.

  19. OMPC: an Open-Source MATLAB-to-Python Compiler.

    PubMed

    Jurica, Peter; van Leeuwen, Cees

    2009-01-01

    Free access to scientific information facilitates scientific progress. Open-access scientific journals are a first step in this direction; a further step is to make auxiliary and supplementary materials that accompany scientific publications, such as methodological procedures and data-analysis tools, open and accessible to the scientific community. To this purpose it is instrumental to establish a software base, which will grow toward a comprehensive free and open-source language of technical and scientific computing. Endeavors in this direction are met with an important obstacle. MATLAB((R)), the predominant computation tool in many fields of research, is a closed-source commercial product. To facilitate the transition to an open computation platform, we propose Open-source MATLAB((R))-to-Python Compiler (OMPC), a platform that uses syntax adaptation and emulation to allow transparent import of existing MATLAB((R)) functions into Python programs. The imported MATLAB((R)) modules will run independently of MATLAB((R)), relying on Python's numerical and scientific libraries. Python offers a stable and mature open source platform that, in many respects, surpasses commonly used, expensive commercial closed source packages. The proposed software will therefore facilitate the transparent transition towards a free and general open-source lingua franca for scientific computation, while enabling access to the existing methods and algorithms of technical computing already available in MATLAB((R)). OMPC is available at http://ompc.juricap.com.

  20. SunPy: Python for Solar Physics Data Analysis

    NASA Astrophysics Data System (ADS)

    Hughitt, V. Keith; Christe, S.; Ireland, J.; Shih, A.; Mayer, F.; Earnshaw, M. D.; Young, C.; Perez-Suarez, D.; Schwartz, R.

    2012-05-01

    In recent years, Python, a free cross platform general purpose high-level programming language, has seen widespread adoption among the scientific community resulting in the availability of wide range of software, from numerical computation and machine learning to spectral analysis and visualization. SunPy is a software suite specializing in providing the tools necessary to analyze solar and heliospheric datasets in Python. It provides a free and open-source alternative to the IDL-based SolarSoft (SSW) solar data analysis environment. We present the current capabilities of SunPy which include WCS-aware map objects that allow simple overplotting of data from multiple image FITS files; time-series objects that allow overplotting of multiple lightcurves, and integration with online services such as The Virtual Solar Observatory (VSO) and The Heliophysics Event Knowledgebase (HEK). SunPy also provides functionality that is not currently available in SSW such as advanced time series manipulation routines and support for working with solar data stored using JPEG 2000. We present examples of solar data analysis in SunPy, and show how Python-based solar data-analysis can leverage the many existing data analysis tools currently available in Python. We discuss the future goals of the project and encourage interested users to become involved in the planning and development of SunPy.

  1. Rabacus: A Python package for analytic cosmological radiative transfer calculations

    NASA Astrophysics Data System (ADS)

    Altay, G.; Wise, J. H.

    2015-04-01

    We describe RABACUS, a Python package for calculating the transfer of hydrogen ionizing radiation in simplified geometries relevant to astronomy and cosmology. We present example solutions for three specific cases: (1) a semi-infinite slab gas distribution in a homogeneous isotropic background, (2) a spherically symmetric gas distribution with a point source at the center, and (3) a spherically symmetric gas distribution in a homogeneous isotropic background. All problems can accommodate arbitrary spectra and density profiles as input. The solutions include a treatment of both hydrogen and helium, a self-consistent calculation of equilibrium temperatures, and the transfer of recombination radiation. The core routines are written in Fortran 90 and then wrapped in Python leading to execution speeds thousands of times faster than equivalent routines written in pure Python. In addition, all variables have associated units for ease of analysis. The software is part of the Python Package Index and the source code is available on Bitbucket at https://bitbucket.org/galtay/rabacus. In addition, installation instructions and a detailed users guide are available at http://pythonhosted.org//rabacus.

  2. pypet: A Python Toolkit for Data Management of Parameter Explorations

    PubMed Central

    Meyer, Robert; Obermayer, Klaus

    2016-01-01

    pypet (Python parameter exploration toolkit) is a new multi-platform Python toolkit for managing numerical simulations. Sampling the space of model parameters is a key aspect of simulations and numerical experiments. pypet is designed to allow easy and arbitrary sampling of trajectories through a parameter space beyond simple grid searches. pypet collects and stores both simulation parameters and results in a single HDF5 file. This collective storage allows fast and convenient loading of data for further analyses. pypet provides various additional features such as multiprocessing and parallelization of simulations, dynamic loading of data, integration of git version control, and supervision of experiments via the electronic lab notebook Sumatra. pypet supports a rich set of data formats, including native Python types, Numpy and Scipy data, Pandas DataFrames, and BRIAN(2) quantities. Besides these formats, users can easily extend the toolkit to allow customized data types. pypet is a flexible tool suited for both short Python scripts and large scale projects. pypet's various features, especially the tight link between parameters and results, promote reproducible research in computational neuroscience and simulation-based disciplines. PMID:27610080

  3. batman: BAsic Transit Model cAlculatioN in Python

    NASA Astrophysics Data System (ADS)

    Kreidberg, Laura

    2015-10-01

    batman provides fast calculation of exoplanet transit light curves and supports calculation of light curves for any radially symmetric stellar limb darkening law. It uses an integration algorithm for models that cannot be quickly calculated analytically, and in typical use, the batman Python package can calculate a million model light curves in well under ten minutes for any limb darkening profile.

  4. PyKrige: Development of a Kriging Toolkit for Python

    NASA Astrophysics Data System (ADS)

    Murphy, B. S.

    2014-12-01

    While Python continues to grow in popularity as a convenient and powerful means of data manipulation and analysis, the language still lacks a package that provides easy access to commonly utilized geostatistical routines. PyKrige is a new contribution that attempts to create a Python library that can be used for basic geostatistical tasks, such as creating water level maps using Ordinary and Universal Kriging. While written in pure Python, the code makes extensive use of NumPy in order to enable fast processing. Supported drift terms for Universal Kriging currently include a regional linear drift (such as would be used to simulate an overall groundwater gradient, as discussed in Tonkin and Larson, Groundwater, 2002), a point-logarithmic drift (such as would be used to simulate wells, as discussed in Tonkin and Larson, Groundwater, 2002), and an external digital elevation model drift (such as would be used to simulate a topographically controlled groundwater surface, as discussed in Desbarats et al., Journal of Hydrology, 2002). The package is intended primarily for kriging of two-dimensional data, but limited support for three-dimensional kriging is currently under development. Though similar tools already exist for other commonly utilized scientific languages, such as R and MATLAB, PyKrige is intended to ease data processing by providing further functionality in Python that can be implemented in a single analysis pipeline. The code will be made available on GitHub.

  5. Wyrm: A Brain-Computer Interface Toolbox in Python.

    PubMed

    Venthur, Bastian; Dähne, Sven; Höhne, Johannes; Heller, Hendrik; Blankertz, Benjamin

    2015-10-01

    In the last years Python has gained more and more traction in the scientific community. Projects like NumPy, SciPy, and Matplotlib have created a strong foundation for scientific computing in Python and machine learning packages like scikit-learn or packages for data analysis like Pandas are building on top of it. In this paper we present Wyrm ( https://github.com/bbci/wyrm ), an open source BCI toolbox in Python. Wyrm is applicable to a broad range of neuroscientific problems. It can be used as a toolbox for analysis and visualization of neurophysiological data and in real-time settings, like an online BCI application. In order to prevent software defects, Wyrm makes extensive use of unit testing. We will explain the key aspects of Wyrm's software architecture and design decisions for its data structure, and demonstrate and validate the use of our toolbox by presenting our approach to the classification tasks of two different data sets from the BCI Competition III. Furthermore, we will give a brief analysis of the data sets using our toolbox, and demonstrate how we implemented an online experiment using Wyrm. With Wyrm we add the final piece to our ongoing effort to provide a complete, free and open source BCI system in Python.

  6. pypet: A Python Toolkit for Data Management of Parameter Explorations.

    PubMed

    Meyer, Robert; Obermayer, Klaus

    2016-01-01

    pypet (Python parameter exploration toolkit) is a new multi-platform Python toolkit for managing numerical simulations. Sampling the space of model parameters is a key aspect of simulations and numerical experiments. pypet is designed to allow easy and arbitrary sampling of trajectories through a parameter space beyond simple grid searches. pypet collects and stores both simulation parameters and results in a single HDF5 file. This collective storage allows fast and convenient loading of data for further analyses. pypet provides various additional features such as multiprocessing and parallelization of simulations, dynamic loading of data, integration of git version control, and supervision of experiments via the electronic lab notebook Sumatra. pypet supports a rich set of data formats, including native Python types, Numpy and Scipy data, Pandas DataFrames, and BRIAN(2) quantities. Besides these formats, users can easily extend the toolkit to allow customized data types. pypet is a flexible tool suited for both short Python scripts and large scale projects. pypet's various features, especially the tight link between parameters and results, promote reproducible research in computational neuroscience and simulation-based disciplines.

  7. Cold-induced mortality of invasive Burmese pythons in south Florida

    USGS Publications Warehouse

    Mazzotti, Frank J.; Cherkiss, Michael S.; Hart, Kristen M.; Snow, Ray W.; Rochford, Michael R.; Dorcas, Michael E.; Reed, Robert N.

    2011-01-01

    A recent record cold spell in southern Florida (2-11 January 2010) provided an opportunity to evaluate responses of an established population of Burmese pythons (Python molurus bivittatus) to a prolonged period of unusually cold weather. We observed behavior, characterized thermal biology, determined fate of radio-telemetered (n = 10) and non-telemetered (n = 104) Burmese pythons, and analyzed habitat and environmental conditions experienced by pythons during and after a historic cold spell. Telemetered pythons had been implanted with radio-transmitters and temperature-recording data loggers prior to the cold snap. Only one of 10 telemetered pythons survived the cold snap, whereas 59 of 99 (60%) non-telemetered pythons for which we determined fate survived. Body temperatures of eight dead telemetered pythons fluctuated regularly prior to 9 January 2010, then declined substantially during the cold period (9-11 January) and exhibited no further evidence of active thermoregulation indicating they were likely dead. Unusually cold temperatures in January 2010 were clearly associated with mortality of Burmese pythons in the Everglades. Some radiotelemetered pythons appeared to exhibit maladaptive behavior during the cold spell, including attempting to bask instead of retreating to sheltered refugia. We discuss implications of our findings for persistence and spread of introduced Burmese pythons in the United States and for maximizing their rate of removal.

  8. Flexible Environmental Modeling with Python and Open - GIS

    NASA Astrophysics Data System (ADS)

    Pryet, Alexandre; Atteia, Olivier; Delottier, Hugo; Cousquer, Yohann

    2015-04-01

    Numerical modeling now represents a prominent task of environmental studies. During the last decades, numerous commercial programs have been made available to environmental modelers. These software applications offer user-friendly graphical user interfaces that allow an efficient management of many case studies. However, they suffer from a lack of flexibility and closed-source policies impede source code reviewing and enhancement for original studies. Advanced modeling studies require flexible tools capable of managing thousands of model runs for parameter optimization, uncertainty and sensitivity analysis. In addition, there is a growing need for the coupling of various numerical models associating, for instance, groundwater flow modeling to multi-species geochemical reactions. Researchers have produced hundreds of open-source powerful command line programs. However, there is a need for a flexible graphical user interface allowing an efficient processing of geospatial data that comes along any environmental study. Here, we present the advantages of using the free and open-source Qgis platform and the Python scripting language for conducting environmental modeling studies. The interactive graphical user interface is first used for the visualization and pre-processing of input geospatial datasets. Python scripting language is then employed for further input data processing, call to one or several models, and post-processing of model outputs. Model results are eventually sent back to the GIS program, processed and visualized. This approach combines the advantages of interactive graphical interfaces and the flexibility of Python scripting language for data processing and model calls. The numerous python modules available facilitate geospatial data processing and numerical analysis of model outputs. Once input data has been prepared with the graphical user interface, models may be run thousands of times from the command line with sequential or parallel calls. We

  9. Emerge - A Python environment for the modeling of subsurface transfers

    NASA Astrophysics Data System (ADS)

    Lopez, S.; Smai, F.; Sochala, P.

    2014-12-01

    The simulation of subsurface mass and energy transfers often relies on specific codes that were mainly developed using compiled languages which usually ensure computational efficiency at the expense of relatively long development times and relatively rigid software. Even if a very detailed, possibly graphical, user-interface is developed the core numerical aspects are rarely accessible and the smallest modification will always need a compilation step. Thus, user-defined physical laws or alternative numerical schemes may be relatively difficult to use. Over the last decade, Python has emerged as a popular and widely used language in the scientific community. There already exist several libraries for the pre and post-treatment of input and output files for reservoir simulators (e.g. pytough). Development times in Python are considerably reduced compared to compiled languages, and programs can be easily interfaced with libraries written in compiled languages with several comprehensive numerical libraries that provide sequential and parallel solvers (e.g. PETSc, Trilinos…). The core objective of the Emerge project is to explore the possibility to develop a modeling environment in full Python. Consequently, we are developing an open python package with the classes/objects necessary to express, discretize and solve the physical problems encountered in the modeling of subsurface transfers. We heavily relied on Python to have a convenient and concise way of manipulating potentially complex concepts with a few lines of code and a high level of abstraction. Our result aims to be a friendly numerical environment targeting both numerical engineers and physicist or geoscientists with the possibility to quickly specify and handle geometries, arbitrary meshes, spatially or temporally varying properties, PDE formulations, boundary conditions…

  10. Postprandial remodeling of the gut microbiota in Burmese pythons.

    PubMed

    Costello, Elizabeth K; Gordon, Jeffrey I; Secor, Stephen M; Knight, Rob

    2010-11-01

    The vertebrate gut microbiota evolved in an environment typified by periodic fluctuations in nutrient availability, yet little is known about its responses to host feeding and fasting. As many model species (for example, mice) are adapted to lifestyles of frequent small meals, we turned to the Burmese python, a sit-and-wait foraging snake that consumes large prey at long intervals (>1 month), to examine the effects of a dynamic nutrient milieu on the gut microbiota. We used multiplexed 16S rRNA gene pyrosequencing to characterize bacterial communities harvested from the intestines of fasted and digesting snakes, and from their rodent meal. In this unprecedented survey of a reptilian host, we found that Bacteroidetes and Firmicutes numerically dominated the python gut. In the large intestine, fasting was associated with increased abundances of the genera Bacteroides, Rikenella, Synergistes and Akkermansia, and with reduced overall diversity. A marked postprandial shift in bacterial community configuration occurred. Between 12 h and 3 days after feeding, Firmicutes, including the taxa Clostridium, Lactobacillus and Peptostreptococcaceae, gradually outnumbered the fasting-dominant Bacteroidetes, and overall 'species'-level diversity increased significantly. Most lineages seemed to be indigenous to the python rather than ingested with the meal, but a dietary source of Lactobacillus could not be ruled out. Thus, the observed large-scale alterations of the gut microbiota that accompany the Burmese python's own dramatic physiological and morphological changes during feeding and fasting emphasize the need to consider both microbial and host cellular responses to nutrient flux. The Burmese python may provide a unique model for dissecting these interrelationships.

  11. Rapid microsatellite marker development using next generation pyrosequencing to inform invasive Burmese python -- Python molurus bivittatus -- management

    USGS Publications Warehouse

    Hunter, Margaret E.; Hart, Kristen M.

    2013-01-01

    Invasive species represent an increasing threat to native ecosystems, harming indigenous taxa through predation, habitat modification, cross-species hybridization and alteration of ecosystem processes. Additionally, high economic costs are associated with environmental damage, restoration and control measures. The Burmese python, Python molurus bivittatus, is one of the most notable invasive species in the US, due to the threat it poses to imperiled species and the Greater Everglades ecosystem. To address population structure and relatedness, next generation sequencing was used to rapidly produce species-specific microsatellite loci. The Roche 454 GS-FLX Titanium platform provided 6616 di-, tri- and tetra-nucleotide repeats in 117,516 sequences. Using stringent criteria, 24 of 26 selected tri- and tetra-nucleotide loci were polymerase chain reaction (PCR) amplified and 18 were polymorphic. An additional six cross-species loci were amplified, and the resulting 24 loci were incorporated into eight PCR multiplexes. Multi-locus genotypes yielded an average of 61% (39%–77%) heterozygosity and 3.7 (2–6) alleles per locus. Population-level studies using the developed microsatellites will track the invasion front and monitor population-suppression dynamics. Additionally, cross-species amplification was detected in the invasive Ball, P. regius, and Northern African python, P. sebae. These markers can be used to address the hybridization potential of Burmese pythons and the larger, more aggressive P. sebae.

  12. Rapid Microsatellite Marker Development Using Next Generation Pyrosequencing to Inform Invasive Burmese Python-Python molurus bivittatus-Management.

    PubMed

    Hunter, Margaret E; Hart, Kristen M

    2013-02-28

    Invasive species represent an increasing threat to native ecosystems, harming indigenous taxa through predation, habitat modification, cross-species hybridization and alteration of ecosystem processes. Additionally, high economic costs are associated with environmental damage, restoration and control measures. The Burmese python, Python molurus bivittatus, is one of the most notable invasive species in the US, due to the threat it poses to imperiled species and the Greater Everglades ecosystem. To address population structure and relatedness, next generation sequencing was used to rapidly produce species-specific microsatellite loci. The Roche 454 GS-FLX Titanium platform provided 6616 di-, tri- and tetra-nucleotide repeats in 117,516 sequences. Using stringent criteria, 24 of 26 selected tri- and tetra-nucleotide loci were polymerase chain reaction (PCR) amplified and 18 were polymorphic. An additional six cross-species loci were amplified, and the resulting 24 loci were incorporated into eight PCR multiplexes. Multi-locus genotypes yielded an average of 61% (39%-77%) heterozygosity and 3.7 (2-6) alleles per locus. Population-level studies using the developed microsatellites will track the invasion front and monitor population-suppression dynamics. Additionally, cross-species amplification was detected in the invasive Ball, P. regius, and Northern African python, P. sebae. These markers can be used to address the hybridization potential of Burmese pythons and the larger, more aggressive P. sebae.

  13. Pharmacokinetics of a long-acting ceftiofur formulation (ceftiofur crystalline free acid) in the ball python (Python regius).

    PubMed

    Adkesson, Michael J; Fernandez-Varon, Emilio; Cox, Sherry; Martín-Jiménez, Tomás

    2011-09-01

    The objective of this study was to determine the pharmacokinetics of a long-acting formulation of ceftiofur crystalline-free acid (CCFA) following intramuscular injection in ball pythons (Python regius). Six adult ball pythons received an injection of CCFA (15 mg/kg) in the epaxial muscles. Blood samples were collected by cardiocentesis immediately prior to and at 0.5, 1, 2, 4, 8, 12, 18, 24, 48, 72, 96, 144, 192, 240, 288, 384, 480, 576, 720, and 864 hr after CCFA administration. Plasma ceftiofur concentrations were determined by high-performance liquid chromatography. A noncompartmental pharmacokinetic analysis was applied to the data. Maximum plasma concentration (Cmax) was 7.096 +/- 1.95 microg/ml and occurred at (Tmax) 2.17 +/- 0.98 hr. The area under the curve (0 to infinity) for ceftiofur was 74.59 +/- 13.05 microg x h/ml and the elimination half-life associated with the terminal slope of the concentration-time curve was 64.31 +/- 14.2 hr. Mean residence time (0 to infinity) was 46.85 +/- 13.53 hr. CCFA at 15 mg/kg was well tolerated in all the pythons. Minimum inhibitory concentration (MIC) data for bacterial isolates from snakes are not well established. For MIC values of < or =0.1 microg/ml, a single dose of CCFA (15 mg/kg) provides adequate plasma concentrations for at least 5 days in the ball python. For MICs > or =0.5 microg/ml, more frequent dosing or a higher dosage may be required.

  14. Betrayal: radio-tagged Burmese pythons reveal locations of conspecifics in Everglades National Park

    USGS Publications Warehouse

    Smith, Brian J.; Cherkiss, Michael S.; Hart, Kristen M.; Rochford, Michael R.; Selby, Thomas H.; Snow, Ray W; Mazzotti, Frank J.

    2016-01-01

    The “Judas” technique is based on the idea that a radio-tagged individual can be used to “betray” conspecifics during the course of its routine social behavior. The Burmese python (Python bivittatus) is an invasive constrictor in southern Florida, and few methods are available for its control. Pythons are normally solitary, but from December–April in southern Florida, they form breeding aggregations containing up to 8 individuals, providing an opportunity to apply the technique. We radio-tracked 25 individual adult pythons of both sexes during the breeding season from 2007–2012. Our goals were to (1) characterize python movements and determine habitat selection for betrayal events, (2) quantify betrayal rates of Judas pythons, and (3) compare the efficacy of this tool with current tools for capturing pythons, both in terms of cost per python removed (CPP) and catch per unit effort (CPUE). In a total of 33 python-seasons, we had 8 betrayal events (24 %) in which a Judas python led us to new pythons. Betrayal events occurred more frequently in lowland forest (including tree islands) than would be expected by chance alone. These 8 events resulted in the capture of 14 new individuals (1–4 new pythons per event). Our effort comparison shows that while the Judas technique is more costly than road cruising surveys per python removed, the Judas technique yields more large, reproductive females and is effective at a time of year that road cruising is not, making it a potential complement to the status quo removal effort.

  15. Expyriment: a Python library for cognitive and neuroscientific experiments.

    PubMed

    Krause, Florian; Lindemann, Oliver

    2014-06-01

    Expyriment is an open-source and platform-independent lightweight Python library for designing and conducting timing-critical behavioral and neuroimaging experiments. The major goal is to provide a well-structured Python library for script-based experiment development, with a high priority being the readability of the resulting program code. Expyriment has been tested extensively under Linux and Windows and is an all-in-one solution, as it handles stimulus presentation, the recording of input/output events, communication with other devices, and the collection and preprocessing of data. Furthermore, it offers a hierarchical design structure, which allows for an intuitive transition from the experimental design to a running program. It is therefore also suited for students, as well as for experimental psychologists and neuroscientists with little programming experience.

  16. Developing PYTHON Codes for the Undergraduate ALFALFA Team

    NASA Astrophysics Data System (ADS)

    Troischt, Parker; Ryan, Nicholas; Alfalfa Team

    2016-03-01

    We describe here progress toward developing a number of new PYTHON routines to be used by members of the Undergraduate ALFALFA Team. The codes are designed to analyze HI spectra and assist in identifying and categorizing some of the intriguing sources found in the initial blind ALFALFA survey. Numerical integration is performed on extragalactic sources using 21cm line spectra produced with the L-Band Wide receiver at the National Astronomy and Ionosphere Center. Prior to the integration, polynomial fits are employed to obtain an appropriate baseline for each source. The codes developed here are part of a larger team effort to use new PYTHON routines in order to replace, upgrade, or supplement a wealth of existing IDL codes within the collaboration. This work has been supported by NSF Grant AST-1211005.

  17. Characterization of carbonic anhydrase XIII in the erythrocytes of the Burmese python, Python molurus bivittatus.

    PubMed

    Esbaugh, A J; Secor, S M; Grosell, M

    2015-09-01

    Carbonic anhydrase (CA) is one of the most abundant proteins found in vertebrate erythrocytes with the majority of species expressing a low activity CA I and high activity CA II. However, several phylogenetic gaps remain in our understanding of the expansion of cytoplasmic CA in vertebrate erythrocytes. In particular, very little is known about isoforms from reptiles. The current study sought to characterize the erythrocyte isoforms from two squamate species, Python molurus and Nerodia rhombifer, which was combined with information from recent genome projects to address this important phylogenetic gap. Obtained sequences grouped closely with CA XIII in phylogenetic analyses. CA II mRNA transcripts were also found in erythrocytes, but found at less than half the levels of CA XIII. Structural analysis suggested similar biochemical activity as the respective mammalian isoforms, with CA XIII being a low activity isoform. Biochemical characterization verified that the majority of CA activity in the erythrocytes was due to a high activity CA II-like isoform; however, titration with copper supported the presence of two CA pools. The CA II-like pool accounted for 90 % of the total activity. To assess potential disparate roles of these isoforms a feeding stress was used to up-regulate CO2 excretion pathways. Significant up-regulation of CA II and the anion exchanger was observed; CA XIII was strongly down-regulated. While these results do not provide insight into the role of CA XIII in the erythrocytes, they do suggest that the presence of two isoforms is not simply a case of physiological redundancy.

  18. Python as a federation tool for GENESIS 3.0.

    PubMed

    Cornelis, Hugo; Rodriguez, Armando L; Coop, Allan D; Bower, James M

    2012-01-01

    The GENESIS simulation platform was one of the first broad-scale modeling systems in computational biology to encourage modelers to develop and share model features and components. Supported by a large developer community, it participated in innovative simulator technologies such as benchmarking, parallelization, and declarative model specification and was the first neural simulator to define bindings for the Python scripting language. An important feature of the latest version of GENESIS is that it decomposes into self-contained software components complying with the Computational Biology Initiative federated software architecture. This architecture allows separate scripting bindings to be defined for different necessary components of the simulator, e.g., the mathematical solvers and graphical user interface. Python is a scripting language that provides rich sets of freely available open source libraries. With clean dynamic object-oriented designs, they produce highly readable code and are widely employed in specialized areas of software component integration. We employ a simplified wrapper and interface generator to examine an application programming interface and make it available to a given scripting language. This allows independent software components to be 'glued' together and connected to external libraries and applications from user-defined Python or Perl scripts. We illustrate our approach with three examples of Python scripting. (1) Generate and run a simple single-compartment model neuron connected to a stand-alone mathematical solver. (2) Interface a mathematical solver with GENESIS 3.0 to explore a neuron morphology from either an interactive command-line or graphical user interface. (3) Apply scripting bindings to connect the GENESIS 3.0 simulator to external graphical libraries and an open source three dimensional content creation suite that supports visualization of models based on electron microscopy and their conversion to computational models

  19. pysimm: A python package for simulation of molecular systems

    NASA Astrophysics Data System (ADS)

    Fortunato, Michael E.; Colina, Coray M.

    In this work, we present pysimm, a python package designed to facilitate structure generation, simulation, and modification of molecular systems. pysimm provides a collection of simulation tools and smooth integration with highly optimized third party software. Abstraction layers enable a standardized methodology to assign various force field models to molecular systems and perform simple simulations. These features have allowed pysimm to aid the rapid development of new applications specifically in the area of amorphous polymer simulations.

  20. AstroAsciiData: ASCII table Python module

    NASA Astrophysics Data System (ADS)

    Kümmel, Martin; Haase, Jonas

    2013-11-01

    ASCII tables continue to be one of the most popular and widely used data exchange formats in astronomy. AstroAsciiData, written in Python, imports all reasonably well-formed ASCII tables. It retains formatting of data values, allows column-first access, supports SExtractor style headings, performs column sorting, and exports data to other formats, including FITS, Numpy/Numarray, and LaTeX table format. It also offers interchangeable comment character, column delimiter and null value.

  1. PyRAT - python radiography analysis tool (u)

    SciTech Connect

    Temple, Brian A; Buescher, Kevin L; Armstrong, Jerawan C

    2011-01-14

    PyRAT is a radiography analysis tool used to reconstruction images of unknown 1-0 objects. The tool is written in Python and developed for use on LINUX and Windows platforms. The tool is capable of performing nonlinear inversions of the images with minimal manual interaction in the optimization process. The tool utilizes the NOMAD mixed variable optimization tool to perform the optimization.

  2. Psyplot: Visualizing rectangular and triangular Climate Model Data with Python

    NASA Astrophysics Data System (ADS)

    Sommer, Philipp

    2016-04-01

    The development and use of climate models often requires the visualization of geo-referenced data. Creating visualizations should be fast, attractive, flexible, easily applicable and easily reproducible. There is a wide range of software tools available for visualizing raster data, but they often are inaccessible to many users (e.g. because they are difficult to use in a script or have low flexibility). In order to facilitate easy visualization of geo-referenced data, we developed a new framework called "psyplot," which can aid earth system scientists with their daily work. It is purely written in the programming language Python and primarily built upon the python packages matplotlib, cartopy and xray. The package can visualize data stored on the hard disk (e.g. NetCDF, GeoTIFF, any other file format supported by the xray package), or directly from the memory or Climate Data Operators (CDOs). Furthermore, data can be visualized on a rectangular grid (following or not following the CF Conventions) and on a triangular grid (following the CF or UGRID Conventions). Psyplot visualizes 2D scalar and vector fields, enabling the user to easily manage and format multiple plots at the same time, and to export the plots into all common picture formats and movies covered by the matplotlib package. The package can currently be used in an interactive python session or in python scripts, and will soon be developed for use with a graphical user interface (GUI). Finally, the psyplot framework enables flexible configuration, allows easy integration into other scripts that uses matplotlib, and provides a flexible foundation for further development.

  3. Sarment: Python modules for HMM analysis and partitioning of sequences.

    PubMed

    Guéguen, Laurent

    2005-08-15

    Sarment is a package of Python modules for easy building and manipulation of sequence segmentations. It provides efficient implementation of usual algorithms for hidden Markov Model computation, as well as for maximal predictive partitioning. Owing to its very large variety of criteria for computing segmentations, Sarment can handle many kinds of models. Because of object-oriented programming, the results of the segmentation are very easy tomanipulate.

  4. A Community Python Library for Solar Physics (SunPy)

    NASA Astrophysics Data System (ADS)

    Christe, Steven; Shih, A. Y.; Ireland, J.; Perez-Suarez, D.; Mumford, S.; Hughitt, V. K.; Hewett, R.; Mayer, F.; SunPy Dev Team

    2013-07-01

    Python, a free, cross platform, general purpose, high-level programming language, has seen widespread adoption among the scientific community resulting in the availability of a large range of software, from numerical computation (NumPy, SciPy) and machine learning to spectral analysis and visualization (Matplotlib). SunPy is a data analysis toolkit specializing in providing the software necessary to analyze solar and heliospheric datasets in Python. It aims to provide a free and open-source alternative to the IDL-based SolarSoft (SSW) solar data analysis environment. We present the latest release of SunPy (0.3). This release includes a major refactor of the main SunPy code to improve ease of use for the user as well as a more consistent interface. SunPy provides downloading capability through integration with the Virtual Solar Observatory (VSO) and the the Heliophysics Event Knowledgebase (HEK). It can open image fits files from major solar missions (SDO/AIA, SOHO/EIT, SOHO/LASCO, STEREO) into WCS-aware maps. SunPy provides advanced time-series tools for data from mission such as GOES, SDO/EVE, and Proba2/LYRA as well as support for radio spectra (e.g. e-Callisto). We present examples of solar data analysis in SunPy, and show how Python-based solar data-analysis can leverage the many existing data analysis tools already available in Python. We discuss the future goals of the project and encourage interested users to become involved in the planning and development of SunPy.

  5. ObsPy: A Python Toolbox for Seismology

    NASA Astrophysics Data System (ADS)

    Wassermann, J. M.; Krischer, L.; Megies, T.; Barsch, R.; Beyreuther, M.

    2013-12-01

    Python combines the power of a full-blown programming language with the flexibility and accessibility of an interactive scripting language. Its extensive standard library and large variety of freely available high quality scientific modules cover most needs in developing scientific processing workflows. ObsPy is a community-driven, open-source project extending Python's capabilities to fit the specific needs that arise when working with seismological data. It a) comes with a continuously growing signal processing toolbox that covers most tasks common in seismological analysis, b) provides read and write support for many common waveform, station and event metadata formats and c) enables access to various data centers, webservices and databases to retrieve waveform data and station/event metadata. In combination with mature and free Python packages like NumPy, SciPy, Matplotlib, IPython, Pandas, lxml, and PyQt, ObsPy makes it possible to develop complete workflows in Python, ranging from reading locally stored data or requesting data from one or more different data centers via signal analysis and data processing to visualization in GUI and web applications, output of modified/derived data and the creation of publication-quality figures. All functionality is extensively documented and the ObsPy Tutorial and Gallery give a good impression of the wide range of possible use cases. ObsPy is tested and running on Linux, OS X and Windows and comes with installation routines for these systems. ObsPy is developed in a test-driven approach and is available under the LGPLv3 open source licence. Users are welcome to request help, report bugs, propose enhancements or contribute code via either the user mailing list or the project page on GitHub.

  6. Python as a Federation Tool for GENESIS 3.0

    PubMed Central

    Cornelis, Hugo; Rodriguez, Armando L.; Coop, Allan D.; Bower, James M.

    2012-01-01

    The GENESIS simulation platform was one of the first broad-scale modeling systems in computational biology to encourage modelers to develop and share model features and components. Supported by a large developer community, it participated in innovative simulator technologies such as benchmarking, parallelization, and declarative model specification and was the first neural simulator to define bindings for the Python scripting language. An important feature of the latest version of GENESIS is that it decomposes into self-contained software components complying with the Computational Biology Initiative federated software architecture. This architecture allows separate scripting bindings to be defined for different necessary components of the simulator, e.g., the mathematical solvers and graphical user interface. Python is a scripting language that provides rich sets of freely available open source libraries. With clean dynamic object-oriented designs, they produce highly readable code and are widely employed in specialized areas of software component integration. We employ a simplified wrapper and interface generator to examine an application programming interface and make it available to a given scripting language. This allows independent software components to be ‘glued’ together and connected to external libraries and applications from user-defined Python or Perl scripts. We illustrate our approach with three examples of Python scripting. (1) Generate and run a simple single-compartment model neuron connected to a stand-alone mathematical solver. (2) Interface a mathematical solver with GENESIS 3.0 to explore a neuron morphology from either an interactive command-line or graphical user interface. (3) Apply scripting bindings to connect the GENESIS 3.0 simulator to external graphical libraries and an open source three dimensional content creation suite that supports visualization of models based on electron microscopy and their conversion to computational

  7. DREAMTools: a Python package for scoring collaborative challenges

    PubMed Central

    Cokelaer, Thomas; Bansal, Mukesh; Bare, Christopher; Bilal, Erhan; Bot, Brian M.; Chaibub Neto, Elias; Eduati, Federica; de la Fuente, Alberto; Gönen, Mehmet; Hill, Steven M.; Hoff, Bruce; Karr, Jonathan R.; Küffner, Robert; Menden, Michael P.; Meyer, Pablo; Norel, Raquel; Pratap, Abhishek; Prill, Robert J.; Weirauch, Matthew T.; Costello, James C.; Stolovitzky, Gustavo; Saez-Rodriguez, Julio

    2016-01-01

    DREAM challenges are community competitions designed to advance computational methods and address fundamental questions in system biology and translational medicine. Each challenge asks participants to develop and apply computational methods to either predict unobserved outcomes or to identify unknown model parameters given a set of training data. Computational methods are evaluated using an automated scoring metric, scores are posted to a public leaderboard, and methods are published to facilitate community discussions on how to build improved methods. By engaging participants from a wide range of science and engineering backgrounds, DREAM challenges can comparatively evaluate a wide range of statistical, machine learning, and biophysical methods. Here, we describe DREAMTools, a Python package for evaluating DREAM challenge scoring metrics. DREAMTools provides a command line interface that enables researchers to test new methods on past challenges, as well as a framework for scoring new challenges. As of March 2016, DREAMTools includes more than 80% of completed DREAM challenges. DREAMTools complements the data, metadata, and software tools available at the DREAM website http://dreamchallenges.org and on the Synapse platform at https://www.synapse.org. Availability:  DREAMTools is a Python package. Releases and documentation are available at http://pypi.python.org/pypi/dreamtools. The source code is available at http://github.com/dreamtools/dreamtools. PMID:27134723

  8. ELLIPT2D: A Flexible Finite Element Code Written Python

    SciTech Connect

    Pletzer, A.; Mollis, J.C.

    2001-03-22

    The use of the Python scripting language for scientific applications and in particular to solve partial differential equations is explored. It is shown that Python's rich data structure and object-oriented features can be exploited to write programs that are not only significantly more concise than their counter parts written in Fortran, C or C++, but are also numerically efficient. To illustrate this, a two-dimensional finite element code (ELLIPT2D) has been written. ELLIPT2D provides a flexible and easy-to-use framework for solving a large class of second-order elliptic problems. The program allows for structured or unstructured meshes. All functions defining the elliptic operator are user supplied and so are the boundary conditions, which can be of Dirichlet, Neumann or Robbins type. ELLIPT2D makes extensive use of dictionaries (hash tables) as a way to represent sparse matrices.Other key features of the Python language that have been widely used include: operator over loading, error handling, array slicing, and the Tkinter module for building graphical use interfaces. As an example of the utility of ELLIPT2D, a nonlinear solution of the Grad-Shafranov equation is computed using a Newton iterative scheme. A second application focuses on a solution of the toroidal Laplace equation coupled to a magnetohydrodynamic stability code, a problem arising in the context of magnetic fusion research.

  9. Computational modeling of multiphase flow and transport with Python

    NASA Astrophysics Data System (ADS)

    Kees, C. E.; Farthing, M. W.; Hines, A. M.; Howington, S. E.

    2008-12-01

    Computational flow and transport models play an important role in many hydrological investigations. Unfortunately, developing simulators that are efficient, widely applicable, and robust is a challenge. This is particularly true if the target applications include complications like multiple fluid phases with multiple components and material heterogeneity. To be specific, these problems often involve physical phenomena at multiple spatial and temporal scales. The appropriate formulation may evolve, and the systems of partial differential equations (PDEs) that arise from traditional formulations can be hard to solve efficiently at the desired resolution. Here, we discuss the development of a Python-based modeling framework for finite element approximation of systems of nonlinear PDEs with an emphasis on multiphase, multicomponent systems relevant for surface and subsurface hydrology. In addition to the overall approach and application, we consider the role of Python in managing code complexity, providing user interfaces, developing solution algorithms, and implementing numerical methods for execution on serial and parallel platforms. We evaluate trade-offs and design choices that follow from our use of Python versus other languages like C++ or Fortran and consider the impact on performance measured in terms of metrics like memory usage, execution time, and developer time.

  10. BioC implementations in Go, Perl, Python and Ruby.

    PubMed

    Liu, Wanli; Islamaj Doğan, Rezarta; Kwon, Dongseop; Marques, Hernani; Rinaldi, Fabio; Wilbur, W John; Comeau, Donald C

    2014-01-01

    As part of a communitywide effort for evaluating text mining and information extraction systems applied to the biomedical domain, BioC is focused on the goal of interoperability, currently a major barrier to wide-scale adoption of text mining tools. BioC is a simple XML format, specified by DTD, for exchanging data for biomedical natural language processing. With initial implementations in C++ and Java, BioC provides libraries of code for reading and writing BioC text documents and annotations. We extend BioC to Perl, Python, Go and Ruby. We used SWIG to extend the C++ implementation for Perl and one Python implementation. A second Python implementation and the Ruby implementation use native data structures and libraries. BioC is also implemented in the Google language Go. BioC modules are functional in all of these languages, which can facilitate text mining tasks. BioC implementations are freely available through the BioC site: http://bioc.sourceforge.net. Database URL: http://bioc.sourceforge.net/

  11. VPython: Python plus Animations in Stereo 3D

    NASA Astrophysics Data System (ADS)

    Sherwood, Bruce

    2004-03-01

    Python is a modern object-oriented programming language. VPython (http://vpython.org) is a combination of Python (http://python.org), the Numeric module from LLNL (http://www.pfdubois.com/numpy), and the Visual module created by David Scherer, all of which have been under continuous development as open source projects. VPython makes it easy to write programs that generate real-time, navigable 3D animations. The Visual module includes a set of 3D objects (sphere, cylinder, arrow, etc.), tools for creating other shapes, and support for vector algebra. The 3D renderer runs in a parallel thread, and animations are produced as a side effect of computations, freeing the programmer to concentrate on the physics. Applications include educational and research visualization. In the Fall of 2003 Hugh Fisher at the Australian National University, John Zelle at Wartburg College, and I contributed to a new stereo capability of VPython. By adding a single statement to an existing VPython program, animations can be viewed in true stereo 3D. One can choose several modes: active shutter glasses, passive polarized glasses, or colored glasses (e.g. red-cyan). The talk will demonstrate the new stereo capability and discuss the pros and cons of various schemes for display of stereo 3D for a large audience. Supported in part by NSF grant DUE-0237132.

  12. GAiN: Distributed Array Computation with Python

    SciTech Connect

    Daily, Jeffrey A.

    2009-05-01

    Scientific computing makes use of very large, multidimensional numerical arrays - typically, gigabytes to terabytes in size - much larger than can fit on even the largest single compute node. Such arrays must be distributed across a "cluster" of nodes. Global Arrays is a cluster-based software system from Battelle Pacific Northwest National Laboratory that enables an efficient, portable, and parallel shared-memory programming interface to manipulate these arrays. Written in and for the C and FORTRAN programming languages, it takes advantage of high-performance cluster interconnections to allow any node in the cluster to access data on any other node very rapidly. The "numpy" module is the de facto standard for numerical calculation in the Python programming language, a language whose use is growing rapidly in the scientific and engineering communities. numpy provides a powerful N-dimensional array class as well as other scientific computing capabilities. However, like the majority of the core Python modules, numpy is inherently serial. Our system, GAiN (Global Arrays in NumPy), is a parallel extension to Python that accesses Global Arrays through numpy. This allows parallel processing and/or larger problem sizes to be harnessed almost transparently within new or existing numpy programs.

  13. BioC implementations in Go, Perl, Python and Ruby

    PubMed Central

    Liu, Wanli; Islamaj Doğan, Rezarta; Kwon, Dongseop; Marques, Hernani; Rinaldi, Fabio; Wilbur, W. John; Comeau, Donald C.

    2014-01-01

    As part of a communitywide effort for evaluating text mining and information extraction systems applied to the biomedical domain, BioC is focused on the goal of interoperability, currently a major barrier to wide-scale adoption of text mining tools. BioC is a simple XML format, specified by DTD, for exchanging data for biomedical natural language processing. With initial implementations in C++ and Java, BioC provides libraries of code for reading and writing BioC text documents and annotations. We extend BioC to Perl, Python, Go and Ruby. We used SWIG to extend the C++ implementation for Perl and one Python implementation. A second Python implementation and the Ruby implementation use native data structures and libraries. BioC is also implemented in the Google language Go. BioC modules are functional in all of these languages, which can facilitate text mining tasks. BioC implementations are freely available through the BioC site: http://bioc.sourceforge.net. Database URL: http://bioc.sourceforge.net/ PMID:24961236

  14. Python for information theoretic analysis of neural data.

    PubMed

    Ince, Robin A A; Petersen, Rasmus S; Swan, Daniel C; Panzeri, Stefano

    2009-01-01

    Information theory, the mathematical theory of communication in the presence of noise, is playing an increasingly important role in modern quantitative neuroscience. It makes it possible to treat neural systems as stochastic communication channels and gain valuable, quantitative insights into their sensory coding function. These techniques provide results on how neurons encode stimuli in a way which is independent of any specific assumptions on which part of the neuronal response is signal and which is noise, and they can be usefully applied even to highly non-linear systems where traditional techniques fail. In this article, we describe our work and experiences using Python for information theoretic analysis. We outline some of the algorithmic, statistical and numerical challenges in the computation of information theoretic quantities from neural data. In particular, we consider the problems arising from limited sampling bias and from calculation of maximum entropy distributions in the presence of constraints representing the effects of different orders of interaction in the system. We explain how and why using Python has allowed us to significantly improve the speed and domain of applicability of the information theoretic algorithms, allowing analysis of data sets characterized by larger numbers of variables. We also discuss how our use of Python is facilitating integration with collaborative databases and centralised computational resources.

  15. Rodents as intermediate hosts of Hepatozoon ayorgbor (Apicomplexa: Adeleina: Hepatozoidae) from the African ball python, Python regius?

    PubMed

    Sloboda, Michal; Kamler, Martin; Bulantová, Jana; Votýpka, Jan; Modrý, David

    2008-03-01

    Two experimental trials were performed to elucidate the role of rodents in the life cycle of Hepatozoon species using snakes as intermediate hosts. In one trial, two ball pythons, Python regius Shaw, 1802 were force fed livers of laboratory mice previously inoculated with sporocysts of Hepatozoon ayorgbor Sloboda, Kamler, Bulantová, Votýpka et Modrý, 2007. Transmission was successful in these experimentally infected snakes as evidenced by the appearance of intraerythrocytic gamonts, which persisted until the end of trial, 12 months after inoculation. Developmental stages of haemogregarines were not observed in histological sections from mice. In another experimental trial, a presence of haemogregarine DNA in mice inoculated with H. ayorgbor was demonstrated by PCR in the liver, lungs and spleen.

  16. Hearing with an atympanic ear: good vibration and poor sound-pressure detection in the royal python, Python regius.

    PubMed

    Christensen, Christian Bech; Christensen-Dalsgaard, Jakob; Brandt, Christian; Madsen, Peter Teglberg

    2012-01-15

    Snakes lack both an outer ear and a tympanic middle ear, which in most tetrapods provide impedance matching between the air and inner ear fluids and hence improve pressure hearing in air. Snakes would therefore be expected to have very poor pressure hearing and generally be insensitive to airborne sound, whereas the connection of the middle ear bone to the jaw bones in snakes should confer acute sensitivity to substrate vibrations. Some studies have nevertheless claimed that snakes are quite sensitive to both vibration and sound pressure. Here we test the two hypotheses that: (1) snakes are sensitive to sound pressure and (2) snakes are sensitive to vibrations, but cannot hear the sound pressure per se. Vibration and sound-pressure sensitivities were quantified by measuring brainstem evoked potentials in 11 royal pythons, Python regius. Vibrograms and audiograms showed greatest sensitivity at low frequencies of 80-160 Hz, with sensitivities of -54 dB re. 1 m s(-2) and 78 dB re. 20 μPa, respectively. To investigate whether pythons detect sound pressure or sound-induced head vibrations, we measured the sound-induced head vibrations in three dimensions when snakes were exposed to sound pressure at threshold levels. In general, head vibrations induced by threshold-level sound pressure were equal to or greater than those induced by threshold-level vibrations, and therefore sound-pressure sensitivity can be explained by sound-induced head vibration. From this we conclude that pythons, and possibly all snakes, lost effective pressure hearing with the complete reduction of a functional outer and middle ear, but have an acute vibration sensitivity that may be used for communication and detection of predators and prey.

  17. Marsh rabbit mortalities tie pythons to the precipitous decline of mammals in the Everglades

    USGS Publications Warehouse

    McCleery, Robert A.; Sovie, Adia; Reed, Robert N.; Cunningham, Mark W.; Hunter, Margaret E.; Hart, Kristen M.

    2015-01-01

    To address the ongoing debate over the impact of invasive species on native terrestrial wildlife, we conducted a large-scale experiment to test the hypothesis that invasive Burmese pythons (Python molurus bivittatus) were a cause of the precipitous decline of mammals in Everglades National Park (ENP). Evidence linking pythons to mammal declines has been indirect and there are reasons to question whether pythons, or any predator, could have caused the precipitous declines seen across a range of mammalian functional groups. Experimentally manipulating marsh rabbits, we found that pythons accounted for 77% of rabbit mortalities within 11 months of their translocation to ENP and that python predation appeared to preclude the persistence of rabbit populations in ENP. On control sites, outside of the park, no rabbits were killed by pythons and 71% of attributable marsh rabbit mortalities were classified as mammal predations. Burmese pythons pose a serious threat to the faunal communities and ecological functioning of the Greater Everglades Ecosystem, which will probably spread as python populations expand their range.

  18. First record of invasive Burmese Python oviposition and brooding inside an anthropogenic structure

    USGS Publications Warehouse

    Hanslowe, Emma; Falk, Bryan; Collier, Michelle A. M.; Josimovich, Jillian; Rahill, Thomas; Reed, Robert

    2016-01-01

    We discovered an adult female Python bivittatus (Burmese Python) coiled around a clutch of 25 eggs in a cement culvert in Flamingo, FL, in Everglades National Park. To our knowledge, this is the first record of an invasive Burmese Python laying eggs and brooding inside an anthropogenic structure in Florida. A 92% hatch-success rate suggests that the cement culvert provided suitable conditions for oviposition, embryonic development, and hatching. Given the plenitude of such anthropogenic structures across the landscape, available sites for oviposition and brooding may not be limiting for the invasive Burmese Python population.

  19. Marsh rabbit mortalities tie pythons to the precipitous decline of mammals in the Everglades

    PubMed Central

    McCleery, Robert A.; Sovie, Adia; Reed, Robert N.; Cunningham, Mark W.; Hunter, Margaret E.; Hart, Kristen M.

    2015-01-01

    To address the ongoing debate over the impact of invasive species on native terrestrial wildlife, we conducted a large-scale experiment to test the hypothesis that invasive Burmese pythons (Python molurus bivittatus) were a cause of the precipitous decline of mammals in Everglades National Park (ENP). Evidence linking pythons to mammal declines has been indirect and there are reasons to question whether pythons, or any predator, could have caused the precipitous declines seen across a range of mammalian functional groups. Experimentally manipulating marsh rabbits, we found that pythons accounted for 77% of rabbit mortalities within 11 months of their translocation to ENP and that python predation appeared to preclude the persistence of rabbit populations in ENP. On control sites, outside of the park, no rabbits were killed by pythons and 71% of attributable marsh rabbit mortalities were classified as mammal predations. Burmese pythons pose a serious threat to the faunal communities and ecological functioning of the Greater Everglades Ecosystem, which will probably spread as python populations expand their range. PMID:25788598

  20. PyEEG: an open source Python module for EEG/MEG feature extraction.

    PubMed

    Bao, Forrest Sheng; Liu, Xin; Zhang, Christina

    2011-01-01

    Computer-aided diagnosis of neural diseases from EEG signals (or other physiological signals that can be treated as time series, e.g., MEG) is an emerging field that has gained much attention in past years. Extracting features is a key component in the analysis of EEG signals. In our previous works, we have implemented many EEG feature extraction functions in the Python programming language. As Python is gaining more ground in scientific computing, an open source Python module for extracting EEG features has the potential to save much time for computational neuroscientists. In this paper, we introduce PyEEG, an open source Python module for EEG feature extraction.

  1. Isolation and characterisation of crocodile and python ovotransferrins.

    PubMed

    Ciuraszkiewicz, Justyna; Olczak, Mariusz; Watorek, Wiesław

    2007-01-01

    Transferrins play a major role in iron homeostasis and metabolism. In vertebrates, these proteins are synthesised in the liver and dispersed within the organism by the bloodstream. In oviparous vertebrates additional expression is observed in the oviduct and the synthesised protein is deposited in egg white as ovotransferrin. Most research on ovotransferrin has been performed on the chicken protein. There is a limited amount of information on other bird transferrins, and until our previous paper on red-eared turtle protein there was no data on the isolation, sequencing and biochemical properties of reptilian ovotransferrins. Recently our laboratory deposited ten new sequences of reptilian transferrins in the EMBL database. A comparative analysis of these sequences indicates a possibility of different mechanisms of iron release among crocodile and snake transferrin. In the present paper we follow with the purification and analysis of the basic biochemical properties of two crocodile (Crocodilus niloticus, C. rhombifer) and one snake (Python molurus bivittatus) ovotransferrins. The proteins were purified by anion exchange and hydrophobic chromatography, and their N-terminal amino-acid sequences, molecular mass and isoelectric points were determined. All three proteins are glycosylated and their N-glycan chromatographic profiles show the largest contribution of neutral oligosaccharides in crocodile and disialylated glycans in python ovotransferrin. The absorption spectra of iron-saturated transferrins were analysed. Iron release from these proteins is pH-dependent, showing a biphasic character in crocodile ovotransferrins and a monophasic type in the python protein. The reason for the different types of iron release is discussed.

  2. MTpy - Python Tools for Magnetotelluric Data Processing and Analysis

    NASA Astrophysics Data System (ADS)

    Krieger, Lars; Peacock, Jared; Thiel, Stephan; Inverarity, Kent; Kirkby, Alison; Robertson, Kate; Soeffky, Paul; Didana, Yohannes

    2014-05-01

    We present the Python package MTpy, which provides functions for the processing, analysis, and handling of magnetotelluric (MT) data sets. MT is a relatively immature and not widely applied geophysical method in comparison to other geophysical techniques such as seismology. As a result, the data processing within the academic MT community is not thoroughly standardised and is often based on a loose collection of software, adapted to the respective local specifications. We have developed MTpy to overcome problems that arise from missing standards, and to provide a simplification of the general handling of MT data. MTpy is written in Python, and the open-source code is freely available from a GitHub repository. The setup follows the modular approach of successful geoscience software packages such as GMT or Obspy. It contains sub-packages and modules for the various tasks within the standard work-flow of MT data processing and interpretation. In order to allow the inclusion of already existing and well established software, MTpy does not only provide pure Python classes and functions, but also wrapping command-line scripts to run standalone tools, e.g. modelling and inversion codes. Our aim is to provide a flexible framework, which is open for future dynamic extensions. MTpy has the potential to promote the standardisation of processing procedures and at same time be a versatile supplement for existing algorithms. Here, we introduce the concept and structure of MTpy, and we illustrate the workflow of MT data processing, interpretation, and visualisation utilising MTpy on example data sets collected over different regions of Australia and the USA.

  3. The fast azimuthal integration Python library: pyFAI

    PubMed Central

    Ashiotis, Giannis; Deschildre, Aurore; Nawaz, Zubair; Wright, Jonathan P.; Karkoulis, Dimitrios; Picca, Frédéric Emmanuel; Kieffer, Jérôme

    2015-01-01

    pyFAI is an open-source software package designed to perform azimuthal integration and, correspondingly, two-dimensional regrouping on area-detector frames for small- and wide-angle X-ray scattering experiments. It is written in Python (with binary submodules for improved performance), a language widely accepted and used by the scientific community today, which enables users to easily incorporate the pyFAI library into their processing pipeline. This article focuses on recent work, especially the ease of calibration, its accuracy and the execution speed for integration.1 PMID:25844080

  4. Spherical Panorama Visualization of Astronomical Data with Blender and Python

    NASA Astrophysics Data System (ADS)

    Kent, Brian R.

    2016-06-01

    We describe methodology to generate 360 degree spherical panoramas of both 2D and 3D data. The techniques apply to a variety of astronomical data types - all sky maps, 2D and 3D catalogs as well as planetary surface maps. The results can be viewed in a desktop browser or interactively with a mobile phone or tablet. Static displays or panoramic video renderings of the data can be produced. We review the Python code and usage of the 3D Blender software for projecting maps onto 3D surfaces and the various tools for distributing visualizations.

  5. Python GST Implementation v. 0.9 beta

    SciTech Connect

    Nielsen, Erik; Blume-Kohout, Robin; Rudinger, Kenneth; Gamble, John

    2015-12-18

    PyGSTi is an implementation of Gate Set Tomography in the python programming language. Gate Set Tomography (GST) is a theory and protocol for simultaneously estimating the state preparation, gate operations, and measurement effects of a physical system of one or many quantum bits (qubits). These estimates are based entirely on the statistics of experimental measurements, and their interpretation and analysis can provide a detailed understanding of the types of errors/imperfections in the physical system. In this way, GST provides not only a means of certifying the "goodness" of qubits but also a means of debugging (i.e. improving) them.

  6. Respiratory consequences of feeding in the snake Python molorus.

    PubMed

    Overgaard, J; Busk, M; Hicks, J W; Jensen, F B; Wang, T

    1999-11-01

    Snakes can ingest large meals and exhibit marked increases in metabolic rate during digestion. Because postprandial oxygen consumption in some snakes may surpass that attained during exercise, studies of digestion offers an alternative avenue to understand the cardio-respiratory responses to elevated metabolic rate in reptiles. The effects of feeding on metabolic rate, arterial oxygen levels, and arterial acid-base status in the snake Python molorus are described. Four snakes (180-250 g) were cannulated in the dorsal aorta and blood samples were obtained during 72 h following ingestion of a meal (rat pups) exceeding 20% of body weight. Oxygen consumption increased from a fasting value of 1.71 +/- 0.08 to 5.54 +/- 0.42 ml kg-1 min-1 at 48 h following feeding, and the respiratory gas exchange ratio increased from 0.67 +/- 0.02 to a maximum of 0.92 +/- 0.03 at 32 h. Plasma lactate was always less than 0.5 mM, so the postprandial increase in metabolic rate was met by aerobic respiration. In fasting animals, arterial PO2 was 66 +/- 4 mmHg and haemoglobin-O2 saturation was 92 +/- 3%; similar values were recorded during digestion, but haematocrit decreased from 15.8 +/- 1.0 to 9.8 +/- 0.8 due to repeated blood sampling. Plasma [HCO3-] increased from a fasting level of 19.3 +/- 0.8 to 25.8 +/- 1.0 mmol l-1 at 24 h after feeding. However, because arterial PCO2 increased from 21.1 +/- 0.5 to 27.9 +/- 1.4 mmHg, there was no significant change in arterial pH from the fasting value of 7.52 +/- 0.01. Acid-base status returned to pre-feeding levels at 72 h following feeding. The increased arterial PCO2 is most likely explained by a reduction in ventilation relative to metabolism, but we predict that lung PO2 does not decrease below 115 mmHg. Although ingestion of large meals is associated with large metabolic changes in pythons, the attendant changes in blood gases are relatively small. In particular, the small changes in plasma [HCO3-] and stable pH show that pythons respond

  7. The fast azimuthal integration Python library: pyFAI.

    PubMed

    Ashiotis, Giannis; Deschildre, Aurore; Nawaz, Zubair; Wright, Jonathan P; Karkoulis, Dimitrios; Picca, Frédéric Emmanuel; Kieffer, Jérôme

    2015-04-01

    pyFAI is an open-source software package designed to perform azimuthal integration and, correspondingly, two-dimensional regrouping on area-detector frames for small- and wide-angle X-ray scattering experiments. It is written in Python (with binary submodules for improved performance), a language widely accepted and used by the scientific community today, which enables users to easily incorporate the pyFAI library into their processing pipeline. This article focuses on recent work, especially the ease of calibration, its accuracy and the execution speed for integration.

  8. PyVO: Python access to the Virtual Observatory

    NASA Astrophysics Data System (ADS)

    Graham, Matthew; Plante, Ray; Tody, Doug; Fitzpatrick, Mike

    2014-02-01

    PyVO provides access to remote data and services of the Virtual observatory (VO) using Python. It allows archive searches for data of a particular type or related to a particular topic and query submissions to obtain data to a particular archive to download selected data products. PyVO supports querying the VAO registry; simple data access services (DAL) to access images (SIA), source catalog records (Cone Search), spectra (SSA), and spectral line emission/absorption data (SLAP); and object name resolution (for converting names of objects in the sky into positions). PyVO requires both AstroPy and NumPy.

  9. Amateur Image Pipeline Processing using Python plus PyRAF

    NASA Astrophysics Data System (ADS)

    Green, Wayne

    2012-05-01

    A template pipeline spanning observing planning to publishing is offered as a basis for establishing a long term observing program. The data reduction pipeline encapsulates all policy and procedures, providing an accountable framework for data analysis and a teaching framework for IRAF. This paper introduces the technical details of a complete pipeline processing environment using Python, PyRAF and a few other languages. The pipeline encapsulates all processing decisions within an auditable framework. The framework quickly handles the heavy lifting of image processing. It also serves as an excellent teaching environment for astronomical data management and IRAF reduction decisions.

  10. Fatty acids identified in the Burmese python promote beneficial cardiac growth.

    PubMed

    Riquelme, Cecilia A; Magida, Jason A; Harrison, Brooke C; Wall, Christopher E; Marr, Thomas G; Secor, Stephen M; Leinwand, Leslie A

    2011-10-28

    Burmese pythons display a marked increase in heart mass after a large meal. We investigated the molecular mechanisms of this physiological heart growth with the goal of applying this knowledge to the mammalian heart. We found that heart growth in pythons is characterized by myocyte hypertrophy in the absence of cell proliferation and by activation of physiological signal transduction pathways. Despite high levels of circulating lipids, the postprandial python heart does not accumulate triglycerides or fatty acids. Instead, there is robust activation of pathways of fatty acid transport and oxidation combined with increased expression and activity of superoxide dismutase, a cardioprotective enzyme. We also identified a combination of fatty acids in python plasma that promotes physiological heart growth when injected into either pythons or mice.

  11. Supersize me: Remains of three white-tailed deer (Odocoileus virginianus) in an invasive Burmese python (Python molurus bivittatus) in Florida

    USGS Publications Warehouse

    Boback, Scott M.; Snow, Ray W.; Hsu, Teresa; Peurach, Suzanne C.; Dove, Carla J.; Reed, Robert N.

    2016-01-01

    Snakes have become successful invaders in a wide variety of ecosystems worldwide. In southern Florida, USA, the Burmese python (Python molurus bivittatus) has become established across thousands of square kilometers including all of Everglades National Park (ENP). Both experimental and correlative data have supported a relationship between Burmese python predation and declines or extirpations of mid- to large-sized mammals in ENP. In June 2013 a large python (4.32 m snout-vent length, 48.3 kg) was captured and removed from the park. Subsequent necropsy revealed a massive amount of fecal matter (79 cm in length, 6.5 kg) within the snake’s large intestine. A comparative examination of bone, teeth, and hooves extracted from the fecal contents revealed that this snake consumed three white-tailed deer (Odocoileus virginianus). This is the first report of an invasive Burmese python containing the remains of multiple white-tailed deer in its gut. Because the largest snakes native to southern Florida are not capable of consuming even mid-sized mammals, pythons likely represent a novel predatory threat to white-tailed deer in these habitats. This work highlights the potential impact of this large-bodied invasive snake and supports the need for more work on invasive predator-native prey relationships.

  12. Programming biological models in Python using PySB.

    PubMed

    Lopez, Carlos F; Muhlich, Jeremy L; Bachman, John A; Sorger, Peter K

    2013-01-01

    Mathematical equations are fundamental to modeling biological networks, but as networks get large and revisions frequent, it becomes difficult to manage equations directly or to combine previously developed models. Multiple simultaneous efforts to create graphical standards, rule-based languages, and integrated software workbenches aim to simplify biological modeling but none fully meets the need for transparent, extensible, and reusable models. In this paper we describe PySB, an approach in which models are not only created using programs, they are programs. PySB draws on programmatic modeling concepts from little b and ProMot, the rule-based languages BioNetGen and Kappa and the growing library of Python numerical tools. Central to PySB is a library of macros encoding familiar biochemical actions such as binding, catalysis, and polymerization, making it possible to use a high-level, action-oriented vocabulary to construct detailed models. As Python programs, PySB models leverage tools and practices from the open-source software community, substantially advancing our ability to distribute and manage the work of testing biochemical hypotheses. We illustrate these ideas using new and previously published models of apoptosis.

  13. Hardware-accelerated interactive data visualization for neuroscience in Python.

    PubMed

    Rossant, Cyrille; Harris, Kenneth D

    2013-01-01

    Large datasets are becoming more and more common in science, particularly in neuroscience where experimental techniques are rapidly evolving. Obtaining interpretable results from raw data can sometimes be done automatically; however, there are numerous situations where there is a need, at all processing stages, to visualize the data in an interactive way. This enables the scientist to gain intuition, discover unexpected patterns, and find guidance about subsequent analysis steps. Existing visualization tools mostly focus on static publication-quality figures and do not support interactive visualization of large datasets. While working on Python software for visualization of neurophysiological data, we developed techniques to leverage the computational power of modern graphics cards for high-performance interactive data visualization. We were able to achieve very high performance despite the interpreted and dynamic nature of Python, by using state-of-the-art, fast libraries such as NumPy, PyOpenGL, and PyTables. We present applications of these methods to visualization of neurophysiological data. We believe our tools will be useful in a broad range of domains, in neuroscience and beyond, where there is an increasing need for scalable and fast interactive visualization.

  14. SCoT: a Python toolbox for EEG source connectivity.

    PubMed

    Billinger, Martin; Brunner, Clemens; Müller-Putz, Gernot R

    2014-01-01

    Analysis of brain connectivity has become an important research tool in neuroscience. Connectivity can be estimated between cortical sources reconstructed from the electroencephalogram (EEG). Such analysis often relies on trial averaging to obtain reliable results. However, some applications such as brain-computer interfaces (BCIs) require single-trial estimation methods. In this paper, we present SCoT-a source connectivity toolbox for Python. This toolbox implements routines for blind source decomposition and connectivity estimation with the MVARICA approach. Additionally, a novel extension called CSPVARICA is available for labeled data. SCoT estimates connectivity from various spectral measures relying on vector autoregressive (VAR) models. Optionally, these VAR models can be regularized to facilitate ill posed applications such as single-trial fitting. We demonstrate basic usage of SCoT on motor imagery (MI) data. Furthermore, we show simulation results of utilizing SCoT for feature extraction in a BCI application. These results indicate that CSPVARICA and correct regularization can significantly improve MI classification. While SCoT was mainly designed for application in BCIs, it contains useful tools for other areas of neuroscience. SCoT is a software package that (1) brings combined source decomposition and connectivtiy estimation to the open Python platform, and (2) offers tools for single-trial connectivity estimation. The source code is released under the MIT license and is available online at github.com/SCoT-dev/SCoT.

  15. Novel divergent nidovirus in a python with pneumonia.

    PubMed

    Bodewes, Rogier; Lempp, Charlotte; Schürch, Anita C; Habierski, Andre; Hahn, Kerstin; Lamers, Mart; von Dörnberg, Katja; Wohlsein, Peter; Drexler, Jan Felix; Haagmans, Bart L; Smits, Saskia L; Baumgärtner, Wolfgang; Osterhaus, Albert D M E

    2014-11-01

    The order Nidovirales contains large, enveloped viruses with a non-segmented positive-stranded RNA genome. Nidoviruses have been detected in man and various animal species, but, to date, there have been no reports of nidovirus in reptiles. In the present study, we describe the detection, characterization, phylogenetic analyses and disease association of a novel divergent nidovirus in the lung of an Indian python (Python molurus) with necrotizing pneumonia. Characterization of the partial genome (>33 000 nt) of this virus revealed several genetic features that are distinct from other nidoviruses, including a very large polyprotein 1a, a putative ribosomal frameshift signal that was identical to the frameshift signal of astroviruses and retroviruses and an accessory ORF that showed some similarity with the haemagglutinin-neuraminidase of paramyxoviruses. Analysis of genome organization and phylogenetic analysis of polyprotein 1ab suggests that this virus belongs to the subfamily Torovirinae. Results of this study provide novel insights into the genetic diversity within the order Nidovirales.

  16. Conservative constraints on early cosmology with MONTE PYTHON

    SciTech Connect

    Audren, Benjamin; Lesgourgues, Julien; Benabed, Karim; Prunet, Simon E-mail: Julien.Lesgourgues@cern.ch E-mail: prunet@iap.fr

    2013-02-01

    Models for the latest stages of the cosmological evolution rely on a less solid theoretical and observational ground than the description of earlier stages like BBN and recombination. As suggested in a previous work by Vonlanthen et al., it is possible to tweak the analysis of CMB data in such way to avoid making assumptions on the late evolution, and obtain robust constraints on ''early cosmology parameters''. We extend this method in order to marginalise the results over CMB lensing contamination, and present updated results based on recent CMB data. Our constraints on the minimal early cosmology model are weaker than in a standard ΛCDM analysis, but do not conflict with this model. Besides, we obtain conservative bounds on the effective neutrino number and neutrino mass, showing no hints for extra relativistic degrees of freedom, and proving in a robust way that neutrinos experienced their non-relativistic transition after the time of photon decoupling. This analysis is also an occasion to describe the main features of the new parameter inference code MONTE PYTHON, that we release together with this paper. MONTE PYTHON is a user-friendly alternative to other public codes like COSMOMC, interfaced with the Boltzmann code CLASS.

  17. New Python-based methods for data processing

    SciTech Connect

    Sauter, Nicholas K. Hattne, Johan; Grosse-Kunstleve, Ralf W.; Echols, Nathaniel

    2013-07-01

    The Computational Crystallography Toolbox (cctbx) is a flexible software platform that has been used to develop high-throughput crystal-screening tools for both synchrotron sources and X-ray free-electron lasers. Plans for data-processing and visualization applications are discussed, and the benefits and limitations of using graphics-processing units are evaluated. Current pixel-array detectors produce diffraction images at extreme data rates (of up to 2 TB h{sup −1}) that make severe demands on computational resources. New multiprocessing frameworks are required to achieve rapid data analysis, as it is important to be able to inspect the data quickly in order to guide the experiment in real time. By utilizing readily available web-serving tools that interact with the Python scripting language, it was possible to implement a high-throughput Bragg-spot analyzer (cctbx.spotfinder) that is presently in use at numerous synchrotron-radiation beamlines. Similarly, Python interoperability enabled the production of a new data-reduction package (cctbx.xfel) for serial femtosecond crystallography experiments at the Linac Coherent Light Source (LCLS). Future data-reduction efforts will need to focus on specialized problems such as the treatment of diffraction spots on interleaved lattices arising from multi-crystal specimens. In these challenging cases, accurate modeling of close-lying Bragg spots could benefit from the high-performance computing capabilities of graphics-processing units.

  18. Programming biological models in Python using PySB

    PubMed Central

    Lopez, Carlos F; Muhlich, Jeremy L; Bachman, John A; Sorger, Peter K

    2013-01-01

    Mathematical equations are fundamental to modeling biological networks, but as networks get large and revisions frequent, it becomes difficult to manage equations directly or to combine previously developed models. Multiple simultaneous efforts to create graphical standards, rule-based languages, and integrated software workbenches aim to simplify biological modeling but none fully meets the need for transparent, extensible, and reusable models. In this paper we describe PySB, an approach in which models are not only created using programs, they are programs. PySB draws on programmatic modeling concepts from little b and ProMot, the rule-based languages BioNetGen and Kappa and the growing library of Python numerical tools. Central to PySB is a library of macros encoding familiar biochemical actions such as binding, catalysis, and polymerization, making it possible to use a high-level, action-oriented vocabulary to construct detailed models. As Python programs, PySB models leverage tools and practices from the open-source software community, substantially advancing our ability to distribute and manage the work of testing biochemical hypotheses. We illustrate these ideas using new and previously published models of apoptosis. PMID:23423320

  19. Pythran: enabling static optimization of scientific Python programs

    NASA Astrophysics Data System (ADS)

    Guelton, Serge; Brunet, Pierrick; Amini, Mehdi; Merlini, Adrien; Corbillon, Xavier; Raynaud, Alan

    2015-01-01

    Pythran is an open source static compiler that turns modules written in a subset of Python language into native ones. Assuming that scientific modules do not rely much on the dynamic features of the language, it trades them for powerful, possibly inter-procedural, optimizations. These optimizations include detection of pure functions, temporary allocation removal, constant folding, Numpy ufunc fusion and parallelization, explicit thread-level parallelism through OpenMP annotations, false variable polymorphism pruning, and automatic vector instruction generation such as AVX or SSE. In addition to these compilation steps, Pythran provides a C++ runtime library that leverages the C++ STL to provide generic containers, and the Numeric Template Toolbox for Numpy support. It takes advantage of modern C++11 features such as variadic templates, type inference, move semantics and perfect forwarding, as well as classical idioms such as expression templates. Unlike the Cython approach, Pythran input code remains compatible with the Python interpreter. Output code is generally as efficient as the annotated Cython equivalent, if not more, but without the backward compatibility loss.

  20. PyFACT: Python and FITS analysis for Cherenkov telescopes

    NASA Astrophysics Data System (ADS)

    Raue, Martin; Deil, Christoph

    2012-12-01

    Ground-based very-high energy (VHE; E>100 GeV) gamma-ray astronomy is growing from being conducted by small teams in closed collaborations into a full-fledged branch of astronomy with open observatories. This is best illustrated by the number of known sources: it increased by one order of magnitude in the past ten years, from 10 in the year 2000 to more than 100 in 2010. It is expected that this trend will continue with the next-generation instrument Cherenkov Telescope Array (CTA). This transformation has a profound impact on the data format and analysis of Imaging Atmospheric Cherenkov Telescopes (IACTs). Up to now, IACT data analysis was an internal task performed by specialists with no public access to the data or software. In the future, a large community of VHE astronomers from different scientific topics should be enabled to work with the data. Ease of use, compatibility, and integration with existing astronomy standards and tools will be key. In this contribution, a collection of Python tools for the analysis of data in FITS format (PyFACT; Python and FITS Analysis for Cherenkov Telescopes) is presented, which connects with existing tools like xspec, sherpa, and ds9. The package is available as open source (https://github.com/mraue/pyfact, comments and contributions welcome). Advantages of the chosen ansatz are discussed and implications for future observatories and data archival are presented.

  1. A Distributed Python HPC Framework: ODIN, PyTrilinos, & Seamless

    SciTech Connect

    Grant, Robert

    2015-11-23

    Under this grant, three significant software packages were developed or improved, all with the goal of improving the ease-of-use of HPC libraries. The first component is a Python package, named DistArray (originally named Odin), that provides a high-level interface to distributed array computing. This interface is based on the popular and widely used NumPy package and is integrated with the IPython project for enhanced interactive parallel distributed computing. The second Python package is the Distributed Array Protocol (DAP) that enables separate distributed array libraries to share arrays efficiently without copying or sending messages. If a distributed array library supports the DAP, it is then automatically able to communicate with any other library that also supports the protocol. This protocol allows DistArray to communicate with the Trilinos library via PyTrilinos, which was also enhanced during this project. A third package, PyTrilinos, was extended to support distributed structured arrays (in addition to the unstructured arrays of its original design), allow more flexible distributed arrays (i.e., the restriction to double precision data was lifted), and implement the DAP. DAP support includes both exporting the protocol so that external packages can use distributed Trilinos data structures, and importing the protocol so that PyTrilinos can work with distributed data from external packages.

  2. precession: Dynamics of spinning black-hole binaries with python

    NASA Astrophysics Data System (ADS)

    Gerosa, Davide; Kesden, Michael

    2016-06-01

    We present the numerical code precession, a new open-source python module to study the dynamics of precessing black-hole binaries in the post-Newtonian regime. The code provides a comprehensive toolbox to (i) study the evolution of the black-hole spins along their precession cycles, (ii) perform gravitational-wave-driven binary inspirals using both orbit-averaged and precession-averaged integrations, and (iii) predict the properties of the merger remnant through fitting formulas obtained from numerical-relativity simulations. precession is a ready-to-use tool to add the black-hole spin dynamics to larger-scale numerical studies such as gravitational-wave parameter estimation codes, population synthesis models to predict gravitational-wave event rates, galaxy merger trees and cosmological simulations of structure formation. precession provides fast and reliable integration methods to propagate statistical samples of black-hole binaries from/to large separations where they form to/from small separations where they become detectable, thus linking gravitational-wave observations of spinning black-hole binaries to their astrophysical formation history. The code is also a useful tool to compute initial parameters for numerical-relativity simulations targeting specific precessing systems. precession can be installed from the python Package Index, and it is freely distributed under version control on github, where further documentation is provided.

  3. Installing python software packages : the good, the bad and the ugly.

    SciTech Connect

    Hart, William Eugene

    2010-11-01

    These slides describe different strategies for installing Python software. Although I am a big fan of Python software development, robust strategies for software installation remains a challenge. This talk describes several different installation scenarios. The Good: the user has administrative privileges - Installing on Windows with an installer executable, Installing with Linux application utility, Installing a Python package from the PyPI repository, and Installing a Python package from source. The Bad: the user does not have administrative privileges - Using a virtual environment to isolate package installations, and Using an installer executable on Windows with a virtual environment. The Ugly: the user needs to install an extension package from source - Installing a Python extension package from source, and PyCoinInstall - Managing builds for Python extension packages. The last item referring to PyCoinInstall describes a utility being developed for the COIN-OR software, which is used within the operations research community. COIN-OR includes a variety of Python and C++ software packages, and this script uses a simple plug-in system to support the management of package builds and installation.

  4. Python erythrocytes are resistant to α-hemolysin from Escherichia coli.

    PubMed

    Larsen, Casper K; Skals, Marianne; Wang, Tobias; Cheema, Muhammad U; Leipziger, Jens; Praetorius, Helle A

    2011-12-01

    α-Hemolysin (HlyA) from Escherichia coli lyses mammalian erythrocytes by creating nonselective cation pores in the membrane. Pore insertion triggers ATP release and subsequent P2X receptor and pannexin channel activation. Blockage of either P2X receptors or pannexin channels reduces HlyA-induced hemolysis. We found that erythrocytes from Python regius and Python molurus are remarkably resistant to HlyA-induced hemolysis compared to human and Trachemys scripta erythrocytes. HlyA concentrations that induced maximal hemolysis of human erythrocytes did not affect python erythrocytes, but increasing the HlyA concentration 40-fold did induce hemolysis. Python erythrocytes were more resistant to osmotic stress than human erythrocytes, but osmotic stress tolerance per se did not confer HlyA resistance. Erythrocytes from T. scripta, which showed higher osmotic resistance than python erythrocytes, were as susceptible to HlyA as human erythrocytes. Therefore, we tested whether python erythrocytes lack the purinergic signalling known to amplify HlyA-induced hemolysis in human erythrocytes. P. regius erythrocytes increased intracellular Ca²⁺ concentration and reduced cell volume when exposed to 3 mM ATP, indicating the presence of a P2X₇-like receptor. In addition, scavenging extracellular ATP or blocking P2 receptors or pannexin channels reduced the HlyA-induced hemolysis. We tested whether the low HlyA sensitivity resulted from low affinity of HlyA to the python erythrocyte membrane. We found comparable incorporation of HlyA into human and python erythrocyte membranes. Taken together, the remarkable HlyA resistance of python erythrocytes was not explained by increased osmotic resistance, lack of purinergic hemolysis amplification, or differences in HlyA affinity.

  5. Python interface generator for Fortran based codes (a code development aid)

    SciTech Connect

    Grote, D. P.

    2012-02-22

    Forthon generates links between Fortran and Python. Python is a high level, object oriented, interactive and scripting language that allows a flexible and versatile interface to computational tools. The Forthon package generates the necessary wrapping code which allows access to the Fortran database and to the Fortran subroutines and functions. This provides a development package where the computationally intensive parts of a code can be written in efficient Fortran, and the high level controlling code can be written in the much more versatile Python language.

  6. Myiasis by Megaselia scalaris (Diptera: Phoridae) in a python affected by pulmonitis.

    PubMed

    Vanin, S; Mazzariol, S; Menandro, M L; Lafisca, A; Turchetto, M

    2013-01-01

    Myiases are caused by the presence of maggots in vertebrate tissues and organs. Myiases have been studied widely in humans, farm animals, and pets, whereas reports of myiasis in reptiles are scarce. We describe a case of myiasis caused by the Megaselia scalaris (Loew) in an Indian python (Python molurus bivittatus, Kuhl) (Ophida: Boidae). The python, 15 yr old, born and reared in a terrarium in the mainland of Venice (Italy), was affected by diffuse, purulent pneumonia caused by Burkholderia cepacia. The severe infestation of maggots found in the lungs during an autopsy indicated at a myiasis.

  7. PyORBIT: A Python Shell For ORBIT

    SciTech Connect

    Jean-Francois Ostiguy; Jeffrey Holmes

    2003-07-01

    ORBIT is code developed at SNS to simulate beam dynamics in accumulation rings and synchrotrons. The code is structured as a collection of external C++ modules for SuperCode, a high level interpreter shell developed at LLNL in the early 1990s. SuperCode is no longer actively supported and there has for some time been interest in replacing it by a modern scripting language, while preserving the feel of the original ORBIT program. In this paper, we describe a new version of ORBIT where the role of SuperCode is assumed by Python, a free, well-documented and widely supported object-oriented scripting language. We also compare PyORBIT to ORBIT from the standpoint of features, performance and future expandability.

  8. Python package for model STructure ANalysis (pySTAN)

    NASA Astrophysics Data System (ADS)

    Van Hoey, Stijn; van der Kwast, Johannes; Nopens, Ingmar; Seuntjens, Piet

    2013-04-01

    methods on a fair basis. We developed and present pySTAN (python framework for STructure Analysis), a python package containing a set of functions for model structure evaluation to provide the analysis of (hydrological) model structures. A selected set of algorithms for optimization, uncertainty and sensitivity analysis is currently available, together with a set of evaluation (objective) functions and input distributions to sample from. The methods are implemented model-independent and the python language provides the wrapper functions to apply administer external model codes. Different objective functions can be considered simultaneously with both statistical metrics and more hydrology specific metrics. By using so-called reStructuredText (sphinx documentation generator) and Python documentation strings (docstrings), the generation of manual pages is semi-automated and a specific environment is available to enhance both the readability and transparency of the code. It thereby enables a larger group of users to apply and compare these methods and to extend the functionalities.

  9. PyRAT (python radiography analysis tool): overview

    SciTech Connect

    Armstrong, Jerawan C; Temple, Brian A; Buescher, Kevin L

    2011-01-14

    PyRAT was developed as a quantitative tool for robustly characterizing objects from radiographs to solve problems such as the hybrid nonlinear inverse problem. The optimization software library that was used is the nonsmooth optimization by MADS algorithm (NOMAD). Some of PyRAT's features are: (1) hybrid nonlinear inverse problem with calculated x-ray spectrum and detector response; (2) optimization based inversion approach with goal of identifying unknown object configurations - MVO problem; (3) using functionalities of Python libraries for radiographic image processing and analysis; (4) using the Tikhonov regularization method of linear inverse problem to recover partial information of object configurations; (5) using a priori knowledge of problem solutions to define feasible region and discrete neighbor for the MVO problem - initial data analysis + material library {yields} a priori knowledge; and (6) using the NOMAD (C++ version) software in the object.

  10. Multiple papillomas in a diamond python, Morelia spilota spilota.

    PubMed

    Gull, Jessica M; Lange, Christian E; Favrot, Claude; Dorrestein, Gerry M; Hatt, Jean-Michel

    2012-12-01

    A 4-yr-old male diamond python (Morelia spilota spilota) was evaluated for multiple black papillated exophytic skin proliferations and signs of pneumonia. The histopathologic structure of the skin biopsy specimens led to the diagnosis of a benign papilloma-like neoplasia. In this case, papillomavirus DNA could be amplified from a biopsy sample with a broad range polymerase chain reaction. Nested pan-herpes polymerase chain reaction was negative, and herpesvirus inclusion bodies were not found. Because of the histologically benign nature of the papilloma, the skin proliferations were left untreated. Ten mo after the first presentation, the skin lesions had regressed almost completely; 34 mo later, only scars from the biopsies were left.

  11. Intraspecific scaling of arterial blood pressure in the Burmese python.

    PubMed

    Enok, Sanne; Slay, Christopher; Abe, Augusto S; Hicks, James W; Wang, Tobias

    2014-07-01

    Interspecific allometric analyses indicate that mean arterial blood pressure (MAP) increases with body mass of snakes and mammals. In snakes, MAP increases in proportion to the increased distance between the heart and the head, when the heart-head vertical distance is expressed as ρgh (where ρ is the density of blood, G: is acceleration due to gravity and h is the vertical distance above the heart), and the rise in MAP is associated with a larger heart to normalize wall stress in the ventricular wall. Based on measurements of MAP in Burmese pythons ranging from 0.9 to 3.7 m in length (0.20-27 kg), we demonstrate that although MAP increases with body mass, the rise in MAP is merely half of that predicted by heart-head distance. Scaling relationships within individual species, therefore, may not be accurately predicted by existing interspecific analyses.

  12. A cross-validation package driving Netica with python

    USGS Publications Warehouse

    Fienen, Michael N.; Plant, Nathaniel G.

    2014-01-01

    Bayesian networks (BNs) are powerful tools for probabilistically simulating natural systems and emulating process models. Cross validation is a technique to avoid overfitting resulting from overly complex BNs. Overfitting reduces predictive skill. Cross-validation for BNs is known but rarely implemented due partly to a lack of software tools designed to work with available BN packages. CVNetica is open-source, written in Python, and extends the Netica software package to perform cross-validation and read, rebuild, and learn BNs from data. Insights gained from cross-validation and implications on prediction versus description are illustrated with: a data-driven oceanographic application; and a model-emulation application. These examples show that overfitting occurs when BNs become more complex than allowed by supporting data and overfitting incurs computational costs as well as causing a reduction in prediction skill. CVNetica evaluates overfitting using several complexity metrics (we used level of discretization) and its impact on performance metrics (we used skill).

  13. Larch: X-ray Analysis for Synchrotron Applications using Python

    NASA Astrophysics Data System (ADS)

    Newville, Matthew

    2017-03-01

    Larch is an open-source library and toolkit written in Python for processing and analyzing X-ray spectroscopic data. The primary emphasis is on X-ray spectroscopic and scattering data collected at modern synchrotron sources. Larch provides a wide selection of general-purpose processing, analysis, and visualization tools for processing X-ray data; its related target application areas include X-ray absorption fine structure (XAFS), micro-X-ray fluorescence (XRF) maps, quantitative X-ray fluorescence, X-ray absorption near edge spectroscopy (XANES), and X-ray standing waves and surface scattering. Larch provides a complete set of XAFS Analysis tools and has support for visualizing and analyzing XRF maps and spectra, and additional tools for X-ray spectral analysis, data handling, and general-purpose data modeling.

  14. One-dimensional statistical parametric mapping in Python.

    PubMed

    Pataky, Todd C

    2012-01-01

    Statistical parametric mapping (SPM) is a topological methodology for detecting field changes in smooth n-dimensional continua. Many classes of biomechanical data are smooth and contained within discrete bounds and as such are well suited to SPM analyses. The current paper accompanies release of 'SPM1D', a free and open-source Python package for conducting SPM analyses on a set of registered 1D curves. Three example applications are presented: (i) kinematics, (ii) ground reaction forces and (iii) contact pressure distribution in probabilistic finite element modelling. In addition to offering a high-level interface to a variety of common statistical tests like t tests, regression and ANOVA, SPM1D also emphasises fundamental concepts of SPM theory through stand-alone example scripts. Source code and documentation are available at: www.tpataky.net/spm1d/.

  15. pyIAST: Ideal adsorbed solution theory (IAST) Python package

    NASA Astrophysics Data System (ADS)

    Simon, Cory M.; Smit, Berend; Haranczyk, Maciej

    2016-03-01

    Ideal adsorbed solution theory (IAST) is a widely-used thermodynamic framework to readily predict mixed-gas adsorption isotherms from a set of pure-component adsorption isotherms. We present an open-source, user-friendly Python package, pyIAST, to perform IAST calculations for an arbitrary number of components. pyIAST supports several common analytical models to characterize the pure-component isotherms from experimental or simulated data. Alternatively, pyIAST can use numerical quadrature to compute the spreading pressure for IAST calculations by interpolating the pure-component isotherm data. pyIAST can also perform reverse IAST calculations, where one seeks the required gas phase composition to yield a desired adsorbed phase composition.

  16. Homing of invasive Burmese pythons in South Florida: evidence for map and compass senses in snakes

    USGS Publications Warehouse

    Pittman, Shannon E.; Hart, Kristen M.; Cherkiss, Michael S.; Snow, Ray W.; Fujisaki, Ikuko; Mazzotti, Frank J.; Dorcas, Michael E.

    2014-01-01

    Navigational ability is a critical component of an animal's spatial ecology and may influence the invasive potential of species. Burmese pythons (Python molurus bivittatus) are apex predators invasive to South Florida. We tracked the movements of 12 adult Burmese pythons in Everglades National Park, six of which were translocated 21–36 km from their capture locations. Translocated snakes oriented movement homeward relative to the capture location, and five of six snakes returned to within 5 km of the original capture location. Translocated snakes moved straighter and faster than control snakes and displayed movement path structure indicative of oriented movement. This study provides evidence that Burmese pythons have navigational map and compass senses and has implications for predictions of spatial spread and impacts as well as our understanding of reptile cognitive abilities.

  17. PyTrilinos: Recent Advances in the Python Interface to Trilinos

    SciTech Connect

    Spotz, William F.

    2012-01-01

    PyTrilinos is a set of Python interfaces to compiled Trilinos packages. This collection supports serial and parallel dense linear algebra, serial and parallel sparse linear algebra, direct and iterative linear solution techniques, algebraic and multilevel preconditioners, nonlinear solvers and continuation algorithms, eigensolvers and partitioning algorithms. Also included are a variety of related utility functions and classes, including distributed I/O, coloring algorithms and matrix generation. PyTrilinos vector objects are compatible with the popular NumPy Python package. As a Python front end to compiled libraries, PyTrilinos takes advantage of the flexibility and ease of use of Python, and the efficiency of the underlying C++, C and Fortran numerical kernels. This paper covers recent, previously unpublished advances in the PyTrilinos package.

  18. Homing of invasive Burmese pythons in South Florida: evidence for map and compass senses in snakes

    PubMed Central

    Pittman, Shannon E.; Hart, Kristen M.; Cherkiss, Michael S.; Snow, Ray W.; Fujisaki, Ikuko; Smith, Brian J.; Mazzotti, Frank J.; Dorcas, Michael E.

    2014-01-01

    Navigational ability is a critical component of an animal's spatial ecology and may influence the invasive potential of species. Burmese pythons (Python molurus bivittatus) are apex predators invasive to South Florida. We tracked the movements of 12 adult Burmese pythons in Everglades National Park, six of which were translocated 21–36 km from their capture locations. Translocated snakes oriented movement homeward relative to the capture location, and five of six snakes returned to within 5 km of the original capture location. Translocated snakes moved straighter and faster than control snakes and displayed movement path structure indicative of oriented movement. This study provides evidence that Burmese pythons have navigational map and compass senses and has implications for predictions of spatial spread and impacts as well as our understanding of reptile cognitive abilities. PMID:24647727

  19. Homing of invasive Burmese pythons in South Florida: evidence for map and compass senses in snakes.

    PubMed

    Pittman, Shannon E; Hart, Kristen M; Cherkiss, Michael S; Snow, Ray W; Fujisaki, Ikuko; Smith, Brian J; Mazzotti, Frank J; Dorcas, Michael E

    2014-03-01

    Navigational ability is a critical component of an animal's spatial ecology and may influence the invasive potential of species. Burmese pythons (Python molurus bivittatus) are apex predators invasive to South Florida. We tracked the movements of 12 adult Burmese pythons in Everglades National Park, six of which were translocated 21-36 km from their capture locations. Translocated snakes oriented movement homeward relative to the capture location, and five of six snakes returned to within 5 km of the original capture location. Translocated snakes moved straighter and faster than control snakes and displayed movement path structure indicative of oriented movement. This study provides evidence that Burmese pythons have navigational map and compass senses and has implications for predictions of spatial spread and impacts as well as our understanding of reptile cognitive abilities.

  20. The Python ARM Radar Toolkit (Py-ART), a library for working with weather radar data in the Python programming language

    SciTech Connect

    Helmus, Jonathan J.; Collis, Scott M.

    2016-07-18

    The Python ARM Radar Toolkit is a package for reading, visualizing, correcting and analysing data from weather radars. Development began to meet the needs of the Atmospheric Radiation Measurement Climate Research Facility and has since expanded to provide a general-purpose framework for working with data from weather radars in the Python programming language. The toolkit is built on top of libraries in the Scientific Python ecosystem including NumPy, SciPy, and matplotlib, and makes use of Cython for interfacing with existing radar libraries written in C and to speed up computationally demanding algorithms. As a result, the source code for the toolkit is available on GitHub and is distributed under a BSD license.

  1. The Python ARM Radar Toolkit (Py-ART), a library for working with weather radar data in the Python programming language

    DOE PAGES

    Helmus, Jonathan J.; Collis, Scott M.

    2016-07-18

    The Python ARM Radar Toolkit is a package for reading, visualizing, correcting and analysing data from weather radars. Development began to meet the needs of the Atmospheric Radiation Measurement Climate Research Facility and has since expanded to provide a general-purpose framework for working with data from weather radars in the Python programming language. The toolkit is built on top of libraries in the Scientific Python ecosystem including NumPy, SciPy, and matplotlib, and makes use of Cython for interfacing with existing radar libraries written in C and to speed up computationally demanding algorithms. As a result, the source code for themore » toolkit is available on GitHub and is distributed under a BSD license.« less

  2. Environmental DNA (eDNA) sampling improves occurrence and detection estimates of invasive Burmese pythons

    USGS Publications Warehouse

    Hunter, Margaret E.; Oyler-McCance, Sara J.; Dorazio, Robert M.; Fike, Jennifer A.; Smith, Brian J.; Hunter, Charles T.; Reed, Robert N.; Hart, Kristen M.

    2015-01-01

    Environmental DNA (eDNA) methods are used to detect DNA that is shed into the aquatic environment by cryptic or low density species. Applied in eDNA studies, occupancy models can be used to estimate occurrence and detection probabilities and thereby account for imperfect detection. However, occupancy terminology has been applied inconsistently in eDNA studies, and many have calculated occurrence probabilities while not considering the effects of imperfect detection. Low detection of invasive giant constrictors using visual surveys and traps has hampered the estimation of occupancy and detection estimates needed for population management in southern Florida, USA. Giant constrictor snakes pose a threat to native species and the ecological restoration of the Florida Everglades. To assist with detection, we developed species-specific eDNA assays using quantitative PCR (qPCR) for the Burmese python (Python molurus bivittatus), Northern African python (P. sebae), boa constrictor (Boa constrictor), and the green (Eunectes murinus) and yellow anaconda (E. notaeus). Burmese pythons, Northern African pythons, and boa constrictors are established and reproducing, while the green and yellow anaconda have the potential to become established. We validated the python and boa constrictor assays using laboratory trials and tested all species in 21 field locations distributed in eight southern Florida regions. Burmese python eDNA was detected in 37 of 63 field sampling events; however, the other species were not detected. Although eDNA was heterogeneously distributed in the environment, occupancy models were able to provide the first estimates of detection probabilities, which were greater than 91%. Burmese python eDNA was detected along the leading northern edge of the known population boundary. The development of informative detection tools and eDNA occupancy models can improve conservation efforts in southern Florida and support more extensive studies of invasive constrictors

  3. Environmental DNA (eDNA) Sampling Improves Occurrence and Detection Estimates of Invasive Burmese Pythons

    PubMed Central

    Hunter, Margaret E.; Oyler-McCance, Sara J.; Dorazio, Robert M.; Fike, Jennifer A.; Smith, Brian J.; Hunter, Charles T.; Reed, Robert N.; Hart, Kristen M.

    2015-01-01

    Environmental DNA (eDNA) methods are used to detect DNA that is shed into the aquatic environment by cryptic or low density species. Applied in eDNA studies, occupancy models can be used to estimate occurrence and detection probabilities and thereby account for imperfect detection. However, occupancy terminology has been applied inconsistently in eDNA studies, and many have calculated occurrence probabilities while not considering the effects of imperfect detection. Low detection of invasive giant constrictors using visual surveys and traps has hampered the estimation of occupancy and detection estimates needed for population management in southern Florida, USA. Giant constrictor snakes pose a threat to native species and the ecological restoration of the Florida Everglades. To assist with detection, we developed species-specific eDNA assays using quantitative PCR (qPCR) for the Burmese python (Python molurus bivittatus), Northern African python (P. sebae), boa constrictor (Boa constrictor), and the green (Eunectes murinus) and yellow anaconda (E. notaeus). Burmese pythons, Northern African pythons, and boa constrictors are established and reproducing, while the green and yellow anaconda have the potential to become established. We validated the python and boa constrictor assays using laboratory trials and tested all species in 21 field locations distributed in eight southern Florida regions. Burmese python eDNA was detected in 37 of 63 field sampling events; however, the other species were not detected. Although eDNA was heterogeneously distributed in the environment, occupancy models were able to provide the first estimates of detection probabilities, which were greater than 91%. Burmese python eDNA was detected along the leading northern edge of the known population boundary. The development of informative detection tools and eDNA occupancy models can improve conservation efforts in southern Florida and support more extensive studies of invasive constrictors

  4. Obtaining and processing Daymet data using Python and ArcGIS

    USGS Publications Warehouse

    Bohms, Stefanie

    2013-01-01

    This set of scripts was developed to automate the process of downloading and mosaicking daily Daymet data to a user defined extent using ArcGIS and Python programming language. The three steps are downloading the needed Daymet tiles for the study area extent, converting the netcdf file to a tif raster format, and mosaicking those rasters to one file. The set of scripts is intended for all levels of experience with Python programming language and requires no scripting by the user.

  5. Severe mammal declines coincide with proliferation of invasive Burmese pythons in Everglades National Park

    USGS Publications Warehouse

    Dorcas, Michael E.; Wilson, John D.; Reed, Robert N.; Snow, Ray W.; Rochford, Michael R.; Miller, Melissa A.; Meshaka, Walter E.; Andreadis, Paul T.; Mazzotti, Frank J.; Romagosa, Christina M.; Hart, Kristen M.

    2012-01-01

    Invasive species represent a significant threat to global biodiversity and a substantial economic burden. Burmese pythons, giant constricting snakes native to Asia, now are found throughout much of southern Florida, including all of Everglades National Park (ENP). Pythons have increased dramatically in both abundance and geographic range since 2000 and consume a wide variety of mammals and birds. Here we report severe apparent declines in mammal populations that coincide temporally and spatially with the proliferation of pythons in ENP. Before 2000, mammals were encountered frequently during nocturnal road surveys within ENP. In contrast, road surveys totaling 56,971 km from 2003–2011 documented a 99.3% decrease in the frequency of raccoon observations, decreases of 98.9% and 87.5% for opossum and bobcat observations, respectively, and failed to detect rabbits. Road surveys also revealed that these species are more common in areas where pythons have been discovered only recently and are most abundant outside the python's current introduced range. These findings suggest that predation by pythons has resulted in dramatic declines in mammals within ENP and that introduced apex predators, such as giant constrictors, can exert significant top-down pressure on prey populations. Severe declines in easily observed and/or common mammals, such as raccoons and bobcats, bode poorly for species of conservation concern, which often are more difficult to sample and occur at lower densities.

  6. Molecular identification of python species: development and validation of a novel assay for forensic investigations.

    PubMed

    Ciavaglia, Sherryn A; Tobe, Shanan S; Donnellan, Stephen C; Henry, Julianne M; Linacre, Adrian M T

    2015-05-01

    Python snake species are often encountered in illegal activities and the question of species identity can be pertinent to such criminal investigations. Morphological identification of species of pythons can be confounded by many issues and molecular examination by DNA analysis can provide an alternative and objective means of identification. Our paper reports on the development and validation of a PCR primer pair that amplifies a segment of the mitochondrial cytochrome b gene that has been suggested previously as a good candidate locus for differentiating python species. We used this DNA region to perform species identification of pythons, even when the template DNA was of poor quality, as might be the case with forensic evidentiary items. Validation tests are presented to demonstrate the characteristics of the assay. Tests involved the cross-species amplification of this marker in non-target species, minimum amount of DNA template required, effects of degradation on product amplification and a blind trial to simulate a casework scenario that provided 100% correct identity. Our results demonstrate that this assay performs reliably and robustly on pythons and can be applied directly to forensic investigations where the presence of a species of python is in question.

  7. Severe mammal declines coincide with proliferation of invasive Burmese pythons in Everglades National Park

    PubMed Central

    Dorcas, Michael E.; Willson, John D.; Reed, Robert N.; Snow, Ray W.; Rochford, Michael R.; Miller, Melissa A.; Meshaka, Walter E.; Andreadis, Paul T.; Mazzotti, Frank J.; Romagosa, Christina M.; Hart, Kristen M.

    2012-01-01

    Invasive species represent a significant threat to global biodiversity and a substantial economic burden. Burmese pythons, giant constricting snakes native to Asia, now are found throughout much of southern Florida, including all of Everglades National Park (ENP). Pythons have increased dramatically in both abundance and geographic range since 2000 and consume a wide variety of mammals and birds. Here we report severe apparent declines in mammal populations that coincide temporally and spatially with the proliferation of pythons in ENP. Before 2000, mammals were encountered frequently during nocturnal road surveys within ENP. In contrast, road surveys totaling 56,971 km from 2003–2011 documented a 99.3% decrease in the frequency of raccoon observations, decreases of 98.9% and 87.5% for opossum and bobcat observations, respectively, and failed to detect rabbits. Road surveys also revealed that these species are more common in areas where pythons have been discovered only recently and are most abundant outside the python's current introduced range. These findings suggest that predation by pythons has resulted in dramatic declines in mammals within ENP and that introduced apex predators, such as giant constrictors, can exert significant top-down pressure on prey populations. Severe declines in easily observed and/or common mammals, such as raccoons and bobcats, bode poorly for species of conservation concern, which often are more difficult to sample and occur at lower densities. PMID:22308381

  8. Environmental temperatures, physiology and behavior limit the range expansion of invasive Burmese pythons in southeastern USA.

    PubMed

    Jacobson, Elliott R; Barker, David G; Barker, Tracy M; Mauldin, Richard; Avery, Michael L; Engeman, Richard; Secor, Stephen

    2012-09-01

    A well-established population of Burmese pythons resides in the Everglades of southern Florida. Prompted in part by a report that identified much of southern USA as suitable habitat for expansion or establishment of the Burmese python, we examined the plausibility of this snake to survive winters at sites north of the Everglades. We integrated daily low and high temperatures recorded from October to February from 2005-2011 at Homestead, Orlando and Gainesville, Florida; and Aiken, South Carolina, with minimum temperatures projected for python digestion (16 °C), activity (5 °C) and survival (0 °C). Mean low and high temperatures decreased northward from Homestead to Aiken and the number of days of freezing temperatures increased northward. Digestion was impaired or inhibited for 2 months in the Everglades and up to at least 5 months in Aiken, and activity was increasingly limited northward during these months. Reports of overwinter survivorship document that a single bout of low and freezing temperatures results in python death. The capacity for Burmese pythons to successfully overwinter in more temperate regions of the USA is seemingly prohibited because they lack the behaviors to seek refuge from, and the physiology to tolerate, cold temperatures. As tropical Southeast Asia is the source of the Everglades Burmese pythons, we predict it is unlikely that they will be able to successfully expand to or colonize more temperate areas of Florida and adjoining states due to their lack of behavioral and physiological traits to seek refuge from cold temperatures.

  9. batman: BAsic Transit Model cAlculatioN in Python

    NASA Astrophysics Data System (ADS)

    Kreidberg, Laura

    2015-11-01

    I introduce batman, a Python package for modeling exoplanet transit light curves. The batman package supports calculation of light curves for any radially symmetric stellar limb darkening law, using a new integration algorithm for models that cannot be quickly calculated analytically. The code uses C extension modules to speed up model calculation and is parallelized with OpenMP. For a typical light curve with 100 data points in transit, batman can calculate one million quadratic limb-darkened models in 30 seconds with a single 1.7 GHz Intel Core i5 processor. The same calculation takes seven minutes using the four-parameter nonlinear limb darkening model (computed to 1 ppm accuracy). Maximum truncation error for integrated models is an input parameter that can be set as low as 0.001 ppm, ensuring that the community is prepared for the precise transit light curves we anticipate measuring with upcoming facilities. The batman package is open source and publicly available at https://github.com/lkreidberg/batman .

  10. photPARTY: Python automated square-aperture photometry

    NASA Astrophysics Data System (ADS)

    Symons, Teresa A.; Anthony-Twarog, Barbara J.

    2017-01-01

    As CCD’s have drastically increased the amount of information recorded per frame, so too have they increased the time and effort needed to sift through the data. For observations of a single star, information from millions of pixels needs to be distilled into one number: the magnitude. Various computer systems have been used to streamline this process over the years. The CCDPhot photometer, in use at the Kitt Peak 0.9-m telescope in the 1990’s, allowed for user settings and provided real time magnitudes during observation of single stars. It is this level of speed and convenience that inspired the development of the Python-based software analysis system photPARTY, which can quickly and efficiently produce magnitudes for a set of single-star or un-crowded field CCD frames. Seeking to remove the need for manual interaction after initial settings for a group of images, photPARTY automatically locates stars, subtracts the background, and performs square-aperture photometry. Rather than being a package of available functions, it is essentially a self-contained, one-click analysis system, with the capability to process several hundred frames in just a couple of minutes. Results of comparisons against present systems such as IRAF will be presented. The support of the National Science Foundation through grant AST-1211621 is gratefully acknowledged.

  11. A python framework for environmental model uncertainty analysis

    USGS Publications Warehouse

    White, Jeremy; Fienen, Michael; Doherty, John E.

    2016-01-01

    We have developed pyEMU, a python framework for Environmental Modeling Uncertainty analyses, open-source tool that is non-intrusive, easy-to-use, computationally efficient, and scalable to highly-parameterized inverse problems. The framework implements several types of linear (first-order, second-moment (FOSM)) and non-linear uncertainty analyses. The FOSM-based analyses can also be completed prior to parameter estimation to help inform important modeling decisions, such as parameterization and objective function formulation. Complete workflows for several types of FOSM-based and non-linear analyses are documented in example notebooks implemented using Jupyter that are available in the online pyEMU repository. Example workflows include basic parameter and forecast analyses, data worth analyses, and error-variance analyses, as well as usage of parameter ensemble generation and management capabilities. These workflows document the necessary steps and provides insights into the results, with the goal of educating users not only in how to apply pyEMU, but also in the underlying theory of applied uncertainty quantification.

  12. SPOTting Model Parameters Using a Ready-Made Python Package.

    PubMed

    Houska, Tobias; Kraft, Philipp; Chamorro-Chavez, Alejandro; Breuer, Lutz

    2015-01-01

    The choice for specific parameter estimation methods is often more dependent on its availability than its performance. We developed SPOTPY (Statistical Parameter Optimization Tool), an open source python package containing a comprehensive set of methods typically used to calibrate, analyze and optimize parameters for a wide range of ecological models. SPOTPY currently contains eight widely used algorithms, 11 objective functions, and can sample from eight parameter distributions. SPOTPY has a model-independent structure and can be run in parallel from the workstation to large computation clusters using the Message Passing Interface (MPI). We tested SPOTPY in five different case studies to parameterize the Rosenbrock, Griewank and Ackley functions, a one-dimensional physically based soil moisture routine, where we searched for parameters of the van Genuchten-Mualem function and a calibration of a biogeochemistry model with different objective functions. The case studies reveal that the implemented SPOTPY methods can be used for any model with just a minimal amount of code for maximal power of parameter optimization. They further show the benefit of having one package at hand that includes number of well performing parameter search methods, since not every case study can be solved sufficiently with every algorithm or every objective function.

  13. SPOTting Model Parameters Using a Ready-Made Python Package

    PubMed Central

    Houska, Tobias; Kraft, Philipp; Chamorro-Chavez, Alejandro; Breuer, Lutz

    2015-01-01

    The choice for specific parameter estimation methods is often more dependent on its availability than its performance. We developed SPOTPY (Statistical Parameter Optimization Tool), an open source python package containing a comprehensive set of methods typically used to calibrate, analyze and optimize parameters for a wide range of ecological models. SPOTPY currently contains eight widely used algorithms, 11 objective functions, and can sample from eight parameter distributions. SPOTPY has a model-independent structure and can be run in parallel from the workstation to large computation clusters using the Message Passing Interface (MPI). We tested SPOTPY in five different case studies to parameterize the Rosenbrock, Griewank and Ackley functions, a one-dimensional physically based soil moisture routine, where we searched for parameters of the van Genuchten-Mualem function and a calibration of a biogeochemistry model with different objective functions. The case studies reveal that the implemented SPOTPY methods can be used for any model with just a minimal amount of code for maximal power of parameter optimization. They further show the benefit of having one package at hand that includes number of well performing parameter search methods, since not every case study can be solved sufficiently with every algorithm or every objective function. PMID:26680783

  14. Screening_mgmt: a Python module for managing screening data.

    PubMed

    Helfenstein, Andreas; Tammela, Päivi

    2015-02-01

    High-throughput screening is an established technique in drug discovery and, as such, has also found its way into academia. High-throughput screening generates a considerable amount of data, which is why specific software is used for its analysis and management. The commercially available software packages are often beyond the financial limits of small-scale academic laboratories and, furthermore, lack the flexibility to fulfill certain user-specific requirements. We have developed a Python module, screening_mgmt, which is a lightweight tool for flexible data retrieval, analysis, and storage for different screening assays in one central database. The module reads custom-made analysis scripts and plotting instructions, and it offers a graphical user interface to import, modify, and display the data in a uniform manner. During the test phase, we used this module for the management of 10,000 data points of various origins. It has provided a practical, user-friendly tool for sharing and exchanging information between researchers.

  15. Oxygen transport is not compromised at high temperature in pythons.

    PubMed

    Fobian, Dannie; Overgaard, Johannes; Wang, Tobias

    2014-11-15

    To evaluate whether the 'oxygen and capacity limited thermal tolerance' model (OCLTT) applies to an air-breathing ectothermic vertebrate, we measured oxygen uptake (V̇(O₂)), cardiac performance and arterial blood gases during a progressive rise of temperature from 30 to 40°C in the snake Python regius. V̇(O₂) of fasting snakes increased exponentially with temperature whereas V̇(O₂) of digesting snakes at high temperatures plateaued at a level 3- to 4-fold above fasting. The high and sustained aerobic metabolism over the entire temperature range was supported by pronounced tachycardia at all temperatures, and both fasting and digesting snakes maintained a normal acid-base balance without any indication of anaerobic metabolism. All snakes also maintained high arterial PO2, even at temperatures close to the upper lethal temperature. Thus, there is no evidence of a reduced capacity for oxygen transport at high temperatures in either fasting or digesting snakes, suggesting that the upper thermal tolerance of this species is limited by other factors.

  16. Python for hydrological modeling: interfacing C code with ctypes, dynamic typing and introspection

    NASA Astrophysics Data System (ADS)

    Bogaart, P. W.

    2008-12-01

    The Python programming language has several features that make it an ideal front-end language for user-friendly numerical modelling of hydrological systems. In this presentation we will demonstrate this with a comprehensive hillslope hydrological modelling framework, where the following features are highlighted: •[Extensibility:] Often a low-level langage like C is better suited for the core functionality of numerical models, for instance because of the inherent higher computational speed, or the availability of specialized algorithms, like the well-known Numerical Recipes or the open source GNU Scientific Library. The now standard Python "ctypes" enables easy manipulation of the C functions and datastructures, provided the C code is compiled into a shared library. High-level Python wrapper functions or classes are easily constructed. •[Flexibility and introspection:] Python is strong but dynamically typed, meaning that variables can change type. This enables the construction of highly flexible functions that operate on a single model parameter, or a list of parameters, or a function that yields parameter values. Related to this, is the capacity of Python to inspect its own types and variables during runtime. So, depending on the actual type of a function argument (scalar, list, function) different actions are taken. Python classes are highly flexibly in the sense that member fields can be added to them during runtime. Python's introspection capacities enables finding out which member fields are actually present. This enables the construction of 'smart' functions that probe an object for the presence or absence of specified members (using their name), and then taking action. On example that will be worked out is a flexible parameter optimizer that takes a reference to a model object, and a list of a parameter names that are to be optimized.

  17. Prioritizing blood flow: cardiovascular performance in response to the competing demands of locomotion and digestion for the Burmese python, Python molurus.

    PubMed

    Secor, Stephen M; White, Scott E

    2010-01-01

    Individually, the metabolic demands of digestion or movement can be fully supported by elevations in cardiovascular performance, but when occurring simultaneously, vascular perfusion may have to be prioritized to either the gut or skeletal muscles. Burmese pythons (Python molurus) experience similar increases in metabolic rate during the digestion of a meal as they do while crawling, hence each would have an equal demand for vascular supply when these two actions are combined. To determine, for the Burmese python, whether blood flow is prioritized when snakes are digesting and moving, we examined changes in cardiac performance and blood flow in response to digestion, movement, and the combination of digestion and movement. We used perivascular blood flow probes to measure blood flow through the left carotid artery, dorsal aorta, superior mesenteric artery and hepatic portal vein, and to calculate cardiac output, heart rate and stroke volume. Fasted pythons while crawling experienced a 2.7- and 3.3-fold increase, respectively, in heart rate and cardiac output, and a 66% decrease in superior mesenteric flow. During the digestion of a rodent meal equaling in mass to 24.7% of the snake's body mass, heart rate and cardiac output increased by 3.3- and 4.4-fold, respectively. Digestion also resulted in respective 11.6- and 14.1-fold increases in superior mesenteric and hepatic portal flow. When crawling while digesting, cardiac output and dorsal aorta flow increased by only 21% and 9%, respectively, a modest increase compared with that when they start to crawl on an empty stomach. Crawling did triggered a significant reduction in blood flow to the digesting gut, decreasing superior mesenteric and hepatic portal flow by 81% and 47%, respectively. When faced with the dual demands of digestion and crawling, Burmese pythons prioritize blood flow, apparently diverting visceral supply to the axial muscles.

  18. Review of the reticulated python (Python reticulatus Schneider, 1801) with the description of new subspecies from Indonesia.

    PubMed

    Auliya, M; Mausfeld, P; Schmitz, A; Böhme, W

    2002-05-01

    The geographically widespread Python reticulatus, the world's longest snake, has been largely neglected by taxonomists. Dwarfed individuals from Tanahjampea Island, Indonesia, differ strikingly in morphology. Phylogenetic relationships were analyzed using a 345-bp fragment of the cytochrome b gene for 12 specimens from different populations. Both genetic differences and morphological characters distinctly revealed two taxonomic subunits. The island populations of Tanahjampea and Selayar form two monophyletic lineages, supported by high bootstrap values, with distinct differences in color pattern and scalation. We consider these forms to represent two new subspecies. The Tanahjampea form is genetically related to populations of the Sunda Islands and mainland Southeast Asia, whereas the Selayar form is related to populations of Southwest Sulawesi. We conclude that, due to strong directional surface currents in this region, gene flow between Tanahjampea and Selayar is prevented. Sea-level changes during the Pleistocene probably contributed to the isolation of the two taxa described. Aspects of ecology and conservation status are briefly discussed. Electronic supplementary material to this paper can be obtained by using the Springer LINK server located at http://dx.doi.org/10.1007/s00114-002-0320-4.

  19. Review of the reticulated python (Python reticulatus Schneider, 1801) with the description of new subspecies from Indonesia

    NASA Astrophysics Data System (ADS)

    Auliya, M.; Mausfeld, P.; Schmitz, A.; Böhme, W.

    2002-04-01

    The geographically widespread Python reticulatus, the world's longest snake, has been largely neglected by taxonomists. Dwarfed individuals from Tanahjampea Island, Indonesia, differ strikingly in morphology. Phylogenetic relationships were analyzed using a 345-bp fragment of the cytochrome b gene for 12 specimens from different populations. Both genetic differences and morphological characters distinctly revealed two taxonomic subunits. The island populations of Tanahjampea and Selayar form two monophyletic lineages, supported by high bootstrap values, with distinct differences in color pattern and scalation. We consider these forms to represent two new subspecies. The Tanahjampea form is genetically related to populations of the Sunda Islands and mainland Southeast Asia, whereas the Selayar form is related to populations of Southwest Sulawesi. We conclude that, due to strong directional surface currents in this region, gene flow between Tanahjampea and Selayar is prevented. Sea-level changes during the Pleistocene probably contributed to the isolation of the two taxa described. Aspects of ecology and conservation status are briefly discussed. Electronic supplementary material to this paper can be obtained by using the Springer LINK server located at http://dx.doi.org/10.1007/s00114-002-0320-4.

  20. ObsPy: a bridge for seismology into the scientific Python ecosystem

    NASA Astrophysics Data System (ADS)

    Krischer, Lion; Megies, Tobias; Barsch, Robert; Beyreuther, Moritz; Lecocq, Thomas; Caudron, Corentin; Wassermann, Joachim

    2015-01-01

    The Python libraries NumPy and SciPy are extremely powerful tools for numerical processing and analysis well suited to a large variety of applications. We developed ObsPy (http://obspy.org), a Python library for seismology intended to facilitate the development of seismological software packages and workflows, to utilize these abilities and provide a bridge for seismology into the larger scientific Python ecosystem. Scientists in many domains who wish to convert their existing tools and applications to take advantage of a platform like the one Python provides are confronted with several hurdles such as special file formats, unknown terminology, and no suitable replacement for a non-trivial piece of software. We present an approach to implement a domain-specific time series library on top of the scientific NumPy stack. In so doing, we show a realization of an abstract internal representation of time series data permitting I/O support for a diverse collection of file formats. Then we detail the integration and repurposing of well established legacy codes, enabling them to be used in modern workflows composed in Python. Finally we present a case study on how to integrate research code into ObsPy, opening it to the broader community. While the implementations presented in this work are specific to seismology, many of the described concepts and abstractions are directly applicable to other sciences, especially to those with an emphasis on time series analysis.

  1. SunPy - Python for Solar Physics, Version 0.4

    NASA Astrophysics Data System (ADS)

    Christe, Steven; Mumford, Stuart; Perez-Suarez, David; Ireland, Jack; Shih, Albert Y.; Inglis, Andrew; Liedtke, Simon; Hewett, Russel

    2014-06-01

    We presents version 0.4 of SunPy, a community-developed Python package for solar physics. Python, a free, cross-platform, general-purpose, high-level programming language, has seen widespread adoption among the scientific community, resulting in the availability of a large number of software packages, from numerical computation NumPy, SciPy and machine learning (scikit-learn) to visualisation and plotting (matplotlib).SunPy is a data-analysis environment specialising in providing the software necessary to analyse solar and heliospheric datasets in Python. SunPy is open-source software (BSD licence) and has an open and transparent development workflow that anyone can contribute to. SunPy provides access to solar data through integration with the Virtual Solar Observatory (VSO), the Heliophysics Event Knowledgebase (HEK), and the HELiophysics Integrated Observatory (HELIO) webservices. It currently supports image data from major solar missions (e.g., SDO, SOHO, STEREO, and IRIS), time-series data from missions such as GOES, SDO/EVE, and PROBA2/LYRA, and radio spectra from e-Callisto and STEREO/SWAVES. We describe SunPy's functionality, provide examples of solar data analysis in SunPy, and show how Python-based solar data-analysis can leverage the many existing tools already available in Python. We discuss the future goals of the project and encourage interested users to become involved in the planning and development of SunPy.

  2. Analyzing rasters, vectors and time series using new Python interfaces in GRASS GIS 7

    NASA Astrophysics Data System (ADS)

    Petras, Vaclav; Petrasova, Anna; Chemin, Yann; Zambelli, Pietro; Landa, Martin; Gebbert, Sören; Neteler, Markus; Löwe, Peter

    2015-04-01

    GRASS GIS 7 is a free and open source GIS software developed and used by many scientists (Neteler et al., 2012). While some users of GRASS GIS prefer its graphical user interface, significant part of the scientific community takes advantage of various scripting and programing interfaces offered by GRASS GIS to develop new models and algorithms. Here we will present different interfaces added to GRASS GIS 7 and available in Python, a popular programming language and environment in geosciences. These Python interfaces are designed to satisfy the needs of scientists and programmers under various circumstances. PyGRASS (Zambelli et al., 2013) is a new object-oriented interface to GRASS GIS modules and libraries. The GRASS GIS libraries are implemented in C to ensure maximum performance and the PyGRASS interface provides an intuitive, pythonic access to their functionality. GRASS GIS Python scripting library is another way of accessing GRASS GIS modules. It combines the simplicity of Bash and the efficiency of the Python syntax. When full access to all low-level and advanced functions and structures from GRASS GIS library is required, Python programmers can use an interface based on the Python ctypes package. Ctypes interface provides complete, direct access to all functionality as it would be available to C programmers. GRASS GIS provides specialized Python library for managing and analyzing spatio-temporal data (Gebbert and Pebesma, 2014). The temporal library introduces space time datasets representing time series of raster, 3D raster or vector maps and allows users to combine various spatio-temporal operations including queries, aggregation, sampling or the analysis of spatio-temporal topology. We will also discuss the advantages of implementing scientific algorithm as a GRASS GIS module and we will show how to write such module in Python. To facilitate the development of the module, GRASS GIS provides a Python library for testing (Petras and Gebbert, 2014) which

  3. The Atomic Simulation Environment - A Python library for working with atoms.

    PubMed

    Larsen, Ask; Mortensen, Jens; Blomqvist, Jakob; Castelli, Ivano; Christensen, Rune; Dulak, Marcin; Friis, Jesper; Groves, Michael; Hammer, Bjork; Hargus, Cory; Hermes, Eric; Jennings, Paul; Jensen, Peter; Kermode, James; Kitchin, John; Kolsbjerg, Esben; Kubal, Joseph; Kaasbjerg, Kristen; Lysgaard, Steen; Maronsson, Jon; Maxson, Tristan; Olsen, Thomas; Pastewka, Lars; Peterson, Andrew; Rostgaard, Carsten; Schiøtz, Jakob; Schütt, Ole; Strange, Mikkel; Thygesen, Kristian; Vegge, Tejs; Vilhelmsen, Lasse; Walter, Michael; Zeng, Zhenhua; Jacobsen, Karsten Wedel

    2017-03-21

    The Atomic Simulation Environment (ASE) is a software package written in the Python programming language with the aim of setting up, steering, and analyzing atomistic simula- tions. In ASE, tasks are fully scripted in Python. The powerful syntax of Python combined with the NumPy array library make it possible to perform very complex simulation tasks. For example, a sequence of calculations may be performed with the use of a simple "for-loop" construction. Calculations of energy, forces, stresses and other quantities are performed through interfaces to many external electronic structure codes or force fields using a uniform interface. On top of this calculator interface, ASE provides modules for performing many standard simulation tasks such as structure optimization, molecular dynamics, handling of constraints and performing nudged elastic band calculations.

  4. The mechanical properties of the systemic and pulmonary arteries of Python regius correlate with blood pressures.

    PubMed

    van Soldt, Benjamin J; Danielsen, Carl Christian; Wang, Tobias

    2015-12-01

    Pythons are unique amongst snakes in having different pressures in the aortas and pulmonary arteries because of intraventricular pressure separation. In this study, we investigate whether this correlates with different blood vessel strength in the ball python Python regius. We excised segments from the left, right, and dorsal aortas, and from the two pulmonary arteries. These were subjected to tensile testing. We show that the aortic vessel wall is significantly stronger than the pulmonary artery wall in P. regius. Gross morphological characteristics (vessel wall thickness and correlated absolute amount of collagen content) are likely the most influential factors. Collagen fiber thickness and orientation are likely to have an effect, though the effect of collagen fiber type and cross-links between fibers will need further study.

  5. Pteros 2.0: Evolution of the fast parallel molecular analysis library for C++ and python.

    PubMed

    Yesylevskyy, Semen O

    2015-07-15

    Pteros is the high-performance open-source library for molecular modeling and analysis of molecular dynamics trajectories. Starting from version 2.0 Pteros is available for C++ and Python programming languages with very similar interfaces. This makes it suitable for writing complex reusable programs in C++ and simple interactive scripts in Python alike. New version improves the facilities for asynchronous trajectory reading and parallel execution of analysis tasks by introducing analysis plugins which could be written in either C++ or Python in completely uniform way. The high level of abstraction provided by analysis plugins greatly simplifies prototyping and implementation of complex analysis algorithms. Pteros is available for free under Artistic License from http://sourceforge.net/projects/pteros/.

  6. Meningoencephalitis in a Boelen's python (Morelia boeleni) associated with paramyxovirus infection.

    PubMed

    West, G; Garner, M; Raymond, J; Latimer, K S; Nordhausen, R

    2001-09-01

    An adult male Boelen's python, Morelia boeleni, presented with acute neurologic disease and was euthanatized. Histologic examination revealed nonsuppurative meningoencephalitis. Occasional eosinophilic intracytoplasmic inclusions were noted in glial cells. On the basis of clinical signs and histopathology, inclusion body disease of boid snakes was suspected, but inclusions were not seen in other organs commonly affected with the disease. Moreover, electron microscopy revealed that the inclusions contained stacks of filaments 13-14 nm wide. With the use of a generic paramyxovirus cDNA probe, sections of brain and esophageal ganglion demonstrated hybridization. The findings indicate that paramyxovirus was the likely cause of the encephalomyelitis in this python, and this virus should be included in the differential diagnosis of pythons exhibiting central nervous system disease.

  7. The role of python eggshell permeability dynamics in a respiration-hydration trade-off.

    PubMed

    Stahlschmidt, Zachary R; Heulin, Benoit; DeNardo, Dale F

    2010-01-01

    Parental care is taxonomically widespread because it improves developmental conditions and thus fitness of offspring. Although relatively simplistic compared with parental behaviors of other taxa, python egg-brooding behavior exemplifies parental care because it mediates a trade-off between embryonic respiration and hydration. However, because egg brooding increases gas-exchange resistance between embryonic and nest environments and because female pythons do not adjust their brooding behavior in response to the increasing metabolic requirements of developing offspring, python egg brooding imposes hypoxic costs on embryos during the late stages of incubation. We conducted a series of experiments to determine whether eggshells coadapted with brooding behavior to minimize the negative effects of developmental hypoxia. We tested the hypotheses that python eggshells (1) increase permeability over time to accommodate increasing embryonic respiration and (2) exhibit permeability plasticity in response to chronic hypoxia. Over incubation, we serially measured the atomic and structural components of Children's python (Antaresia childreni) eggshells as well as in vivo and in vitro gas exchange across eggshells. In support of our first hypothesis, A. childreni eggshells exhibited a reduced fibrous layer, became more permeable, and facilitated greater gas exchange as incubation progressed. Our second hypothesis was not supported, as incubation O(2) concentration did not affect the shells' permeabilities to O(2) and H(2)O vapor. Our results suggest that python eggshell permeability changes during incubation but that the alterations over time are fixed and independent of environmental conditions. These findings are of broad evolutionary interest because they demonstrate that, even in relatively simple parental-care models, successful parent-offspring relationships depend on adjustments made by both the parent (i.e., egg-brooding behavioral shifts) and the offspring (i

  8. HOPE: A Python just-in-time compiler for astrophysical computations

    NASA Astrophysics Data System (ADS)

    Akeret, J.; Gamper, L.; Amara, A.; Refregier, A.

    2015-04-01

    The Python programming language is becoming increasingly popular for scientific applications due to its simplicity, versatility, and the broad range of its libraries. A drawback of this dynamic language, however, is its low runtime performance which limits its applicability for large simulations and for the analysis of large data sets, as is common in astrophysics and cosmology. While various frameworks have been developed to address this limitation, most focus on covering the complete language set, and either force the user to alter the code or are not able to reach the full speed of an optimised native compiled language. In order to combine the ease of Python and the speed of C++, we developed HOPE, a specialised Python just-in-time (JIT) compiler designed for numerical astrophysical applications. HOPE focuses on a subset of the language and is able to translate Python code into C++ while performing numerical optimisation on mathematical expressions at runtime. To enable the JIT compilation, the user only needs to add a decorator to the function definition. We assess the performance of HOPE by performing a series of benchmarks and compare its execution speed with that of plain Python, C++ and the other existing frameworks. We find that HOPE improves the performance compared to plain Python by a factor of 2 to 120, achieves speeds comparable to that of C++, and often exceeds the speed of the existing solutions. We discuss the differences between HOPE and the other frameworks, as well as future extensions of its capabilities. The fully documented HOPE package is available at http://hope.phys.ethz.ch and is published under the GPLv3 license on PyPI and GitHub.

  9. Python-based geometry preparation and simulation visualization toolkits for STEPS.

    PubMed

    Chen, Weiliang; De Schutter, Erik

    2014-01-01

    STEPS is a stochastic reaction-diffusion simulation engine that implements a spatial extension of Gillespie's Stochastic Simulation Algorithm (SSA) in complex tetrahedral geometries. An extensive Python-based interface is provided to STEPS so that it can interact with the large number of scientific packages in Python. However, a gap existed between the interfaces of these packages and the STEPS user interface, where supporting toolkits could reduce the amount of scripting required for research projects. This paper introduces two new supporting toolkits that support geometry preparation and visualization for STEPS simulations.

  10. Enhancements to Ginga: a Python Package for Building Astronomical Data Viewers

    NASA Astrophysics Data System (ADS)

    Jeschke, E.; Inagaki, T.; Kackley, R.

    2015-09-01

    Ginga is a toolkit for building astronomical image viewers. The package is available under a BSD license at github.com and has undergone continuous development since its introduction at ADASS 2012. The package may may be of interest to software developers who are looking for a solution for integrating FITS or numpy-based data visualization into their python programs and end users interested in FITS viewers (via the example reference viewer). We present the updates and enhanced capabilities of the package, including: support for additional GUI toolkits, WCS-based image mosaicing, image overlays, customizable user interface bindings, support for python3 and more.

  11. pyGeno: A Python package for precision medicine and proteogenomics.

    PubMed

    Daouda, Tariq; Perreault, Claude; Lemieux, Sébastien

    2016-01-01

    pyGeno is a Python package mainly intended for precision medicine applications that revolve around genomics and proteomics. It integrates reference sequences and annotations from Ensembl, genomic polymorphisms from the dbSNP database and data from next-gen sequencing into an easy to use, memory-efficient and fast framework, therefore allowing the user to easily explore subject-specific genomes and proteomes. Compared to a standalone program, pyGeno gives the user access to the complete expressivity of Python, a general programming language. Its range of application therefore encompasses both short scripts and large scale genome-wide studies.

  12. STEPS: Modeling and Simulating Complex Reaction-Diffusion Systems with Python.

    PubMed

    Wils, Stefan; De Schutter, Erik

    2009-01-01

    We describe how the use of the Python language improved the user interface of the program STEPS. STEPS is a simulation platform for modeling and stochastic simulation of coupled reaction-diffusion systems with complex 3-dimensional boundary conditions. Setting up such models is a complicated process that consists of many phases. Initial versions of STEPS relied on a static input format that did not cleanly separate these phases, limiting modelers in how they could control the simulation and becoming increasingly complex as new features and new simulation algorithms were added. We solved all of these problems by tightly integrating STEPS with Python, using SWIG to expose our existing simulation code.

  13. ModFossa: A library for modeling ion channels using Python.

    PubMed

    Ferneyhough, Gareth B; Thibealut, Corey M; Dascalu, Sergiu M; Harris, Frederick C

    2016-06-01

    The creation and simulation of ion channel models using continuous-time Markov processes is a powerful and well-used tool in the field of electrophysiology and ion channel research. While several software packages exist for the purpose of ion channel modeling, most are GUI based, and none are available as a Python library. In an attempt to provide an easy-to-use, yet powerful Markov model-based ion channel simulator, we have developed ModFossa, a Python library supporting easy model creation and stimulus definition, complete with a fast numerical solver, and attractive vector graphics plotting.

  14. Prospects and limitations of citizen science in invasive species management: A case study with Burmese pythons in Everglades National Park

    USGS Publications Warehouse

    Falk, Bryan; Snow, Raymond W.; Reed, Robert

    2016-01-01

    Citizen-science programs have the potential to contribute to the management of invasive species, including Python molurus bivittatus (Burmese Python) in Florida. We characterized citizen-science–generated Burmese Python information from Everglades National Park (ENP) to explore how citizen science may be useful in this effort. As an initial step, we compiled and summarized records of Burmese Python observations and removals collected by both professional and citizen scientists in ENP during 2000–2014 and found many patterns of possible significance, including changes in annual observations and in demographic composition after a cold event. These patterns are difficult to confidently interpret because the records lack search-effort information, however, and differences among years may result from differences in search effort. We began collecting search-effort information in 2014 by leveraging an ongoing citizen-science program in ENP. Program participation was generally low, with most authorized participants in 2014 not searching for the snakes at all. We discuss the possible explanations for low participation, especially how the low likelihood of observing pythons weakens incentives to search. The monthly rate of Burmese Python observations for 2014 averaged ~1 observation for every 8 h of searching, but during several months, the rate was 1 python per >40 h of searching. These low observation-rates are a natural outcome of the snakes’ low detectability—few Burmese Pythons are likely to be observed even if many are present. The general inaccessibility of the southern Florida landscape also severely limits the effectiveness of using visual searches to find and remove pythons for the purposes of population control. Instead, and despite the difficulties in incentivizing voluntary participation, the value of citizen-science efforts in the management of the Burmese Python population is in collecting search-effort information.

  15. SPOTting model parameters using a ready-made Python package

    NASA Astrophysics Data System (ADS)

    Houska, Tobias; Kraft, Philipp; Breuer, Lutz

    2015-04-01

    The selection and parameterization of reliable process descriptions in ecological modelling is driven by several uncertainties. The procedure is highly dependent on various criteria, like the used algorithm, the likelihood function selected and the definition of the prior parameter distributions. A wide variety of tools have been developed in the past decades to optimize parameters. Some of the tools are closed source. Due to this, the choice for a specific parameter estimation method is sometimes more dependent on its availability than the performance. A toolbox with a large set of methods can support users in deciding about the most suitable method. Further, it enables to test and compare different methods. We developed the SPOT (Statistical Parameter Optimization Tool), an open source python package containing a comprehensive set of modules, to analyze and optimize parameters of (environmental) models. SPOT comes along with a selected set of algorithms for parameter optimization and uncertainty analyses (Monte Carlo, MC; Latin Hypercube Sampling, LHS; Maximum Likelihood, MLE; Markov Chain Monte Carlo, MCMC; Scuffled Complex Evolution, SCE-UA; Differential Evolution Markov Chain, DE-MCZ), together with several likelihood functions (Bias, (log-) Nash-Sutcliff model efficiency, Correlation Coefficient, Coefficient of Determination, Covariance, (Decomposed-, Relative-, Root-) Mean Squared Error, Mean Absolute Error, Agreement Index) and prior distributions (Binomial, Chi-Square, Dirichlet, Exponential, Laplace, (log-, multivariate-) Normal, Pareto, Poisson, Cauchy, Uniform, Weibull) to sample from. The model-independent structure makes it suitable to analyze a wide range of applications. We apply all algorithms of the SPOT package in three different case studies. Firstly, we investigate the response of the Rosenbrock function, where the MLE algorithm shows its strengths. Secondly, we study the Griewank function, which has a challenging response surface for

  16. Evaluation of the role of the cyclooxygenase signaling pathway during inflammation in skin and muscle tissues of ball pythons (Python regius).

    PubMed

    Sadler, Ryan A; Schumacher, Juergen P; Rathore, Kusum; Newkirk, Kim M; Cole, Grayson; Seibert, Rachel; Cekanova, Maria

    2016-05-01

    OBJECTIVE To determine degrees of production of cyclooxygenase (COX)-1 and -2 and other mediators of inflammation in noninflamed and inflamed skin and muscle tissues in ball pythons (Python regius). ANIMALS 6 healthy adult male ball pythons. PROCEDURES Biopsy specimens of noninflamed skin and muscle tissue were collected from anesthetized snakes on day 0. A 2-cm skin and muscle incision was then made 5 cm distal to the biopsy sites with a CO2 laser to induce inflammation. On day 7, biopsy specimens of skin and muscle tissues were collected from the incision sites. Inflamed and noninflamed tissue specimens were evaluated for production of COX-1, COX-2, phosphorylated protein kinase B (AKT), total AKT, nuclear factor κ-light-chain-enhancer of activated B cells, phosphorylated extracellular receptor kinases (ERKs) 1 and 2, and total ERK proteins by western blot analysis. Histologic evaluation was performed on H&E-stained tissue sections. RESULTS All biopsy specimens of inflamed skin and muscle tissues had higher histologic inflammation scores than did specimens of noninflamed tissue. Inflamed skin specimens had significantly greater production of COX-1 and phosphorylated ERK than did noninflamed skin specimens. Inflamed muscle specimens had significantly greater production of phosphorylated ERK and phosphorylated AKT, significantly lower production of COX-1, and no difference in production of COX-2, compared with production in noninflamed muscle specimens. CONCLUSIONS AND CLINICAL RELEVANCE Production of COX-1, but not COX-2, was significantly greater in inflamed versus noninflamed skin specimens from ball pythons. Additional research into the reptilian COX signaling pathway is warranted.

  17. [Transfer of exotic tick Aponomma latum (Koch, 1844) (Acari: Ixodida: Ixodidae) on ball pythons (Python regius Shaw, 1802) brought to Poland].

    PubMed

    Siuda, Krzysztof; Nowak, Magdalena; Kedryna, Mariusz

    2004-01-01

    103 specimens of Python regius brought to Poland between October 2002 and March 2004 were examined. Occurrence of tick Aponomma latum was reported from 80.6% of the examined reptiles. 549 specimens of A. latum were collected including 341 males, 149 females and 59 nymphs at the various stage of engorgement. Tick A. latum is frequently transferred beyond its natural range of occurrence--Afrotropical region.

  18. CLIMLAB: a Python-based software toolkit for interactive, process-oriented climate modeling

    NASA Astrophysics Data System (ADS)

    Rose, B. E. J.

    2015-12-01

    Global climate is a complex emergent property of the rich interactions between simpler components of the climate system. We build scientific understanding of this system by breaking it down into component process models (e.g. radiation, large-scale dynamics, boundary layer turbulence), understanding each components, and putting them back together. Hands-on experience and freedom to tinker with climate models (whether simple or complex) is invaluable for building physical understanding. CLIMLAB is an open-ended software engine for interactive, process-oriented climate modeling. With CLIMLAB you can interactively mix and match model components, or combine simpler process models together into a more comprehensive model. It was created primarily to support classroom activities, using hands-on modeling to teach fundamentals of climate science at both undergraduate and graduate levels. CLIMLAB is written in Python and ties in with the rich ecosystem of open-source scientific Python tools for numerics and graphics. The IPython notebook format provides an elegant medium for distributing interactive example code. I will give an overview of the current capabilities of CLIMLAB, the curriculum we have developed thus far, and plans for the future. Using CLIMLAB requires some basic Python coding skills. We consider this an educational asset, as we are targeting upper-level undergraduates and Python is an increasingly important language in STEM fields. However CLIMLAB is well suited to be deployed as a computational back-end for a graphical gaming environment based on earth-system modeling.

  19. PyHelp - An automatic multi-output documentation generator for Python

    SciTech Connect

    Nissen, W I

    2005-02-10

    The DRACO code creates geometry and meshes through a command-line Python interface consisting of hundreds of classes and modules which must be accompanied by current documentation. The standard Python utility pydoc performs introspection on objects and prints their associated documentation strings verbatim. However, pydoc supports only very rudimentary formatting and cannot produce printable documentation. We decided to modify pydoc to process formatted ''docstrings'' and use the Doxygen tool to generate the needed forms of documentation. Codes with complex interfaces often require substantial effort to keep user documentation current with interface changes. The DRACO code creates geometry and meshes through a command-line Python interface consisting of hundreds of classes and thousands of functions. A previous attempt to write documentation manually quickly fell out of date, so the development team needed to find an alternative. The existing tools did not provide the flexibility we needed, and the team was already conversant in Doxygen, a C++ code-documenting utility with a simple tag-based markup. Python comes with a utility, pydoc, that performs introspection on objects and prints their docstrings verbatim. However, pydoc supports only very rudimentary formatting and cannot produce printable documentation. Thus we decided to create ''docstrings'' written in Doxygen syntax for each object and process them with a modified pydoc to generate the needed forms of documentation.

  20. Data management routines for reproducible research using the G-Node Python Client library

    PubMed Central

    Sobolev, Andrey; Stoewer, Adrian; Pereira, Michael; Kellner, Christian J.; Garbers, Christian; Rautenberg, Philipp L.; Wachtler, Thomas

    2014-01-01

    Structured, efficient, and secure storage of experimental data and associated meta-information constitutes one of the most pressing technical challenges in modern neuroscience, and does so particularly in electrophysiology. The German INCF Node aims to provide open-source solutions for this domain that support the scientific data management and analysis workflow, and thus facilitate future data access and reproducible research. G-Node provides a data management system, accessible through an application interface, that is based on a combination of standardized data representation and flexible data annotation to account for the variety of experimental paradigms in electrophysiology. The G-Node Python Library exposes these services to the Python environment, enabling researchers to organize and access their experimental data using their familiar tools while gaining the advantages that a centralized storage entails. The library provides powerful query features, including data slicing and selection by metadata, as well as fine-grained permission control for collaboration and data sharing. Here we demonstrate key actions in working with experimental neuroscience data, such as building a metadata structure, organizing recorded data in datasets, annotating data, or selecting data regions of interest, that can be automated to large degree using the library. Compliant with existing de-facto standards, the G-Node Python Library is compatible with many Python tools in the field of neurophysiology and thus enables seamless integration of data organization into the scientific data workflow. PMID:24634654

  1. Automating Geographic Information Systems (GIS) through Python for the Hydrological Sciences

    NASA Astrophysics Data System (ADS)

    Madsen, K.

    2013-12-01

    Geographic Information Systems (GIS) have many applications in the hydrological sciences. However, GIS software is often expensive and difficult to automate. This paper will demonstrate how to automate GRASS GIS software using the Python programming language. Both GRASS GIS and Python are open source projects that are free for anyone to use. Automation of GIS processes is important when dealing with large-scale geographic studies, as large GIS maps are usually divided into discrete tiles. When conducting GIS transformations on such maps, the user must repeat the action for each tile, a process that is greatly expedited through automation. The paper will work through several examples of automated GIS processes and provide complete Python codes that demonstrate correct syntax for working with GRASS GIS applications. The provided examples will demonstrate automation of the following processes 1.) using raster math to calculate foliage thickness from LIDAR and DEM data; 2.) conducting raster interpolation from a set of vector points to develop a continuous hydraulic conductivity coverage; 3.) automating raster coloration to sync the coloration of a large number of raster tiles for website display, and 4.) constructing contoured vector lines from topography rasters. These examples programs will serve as the building blocks for readers, giving them the tools to automate any GIS process using Python and GRASS GIS.

  2. PyMercury: Interactive Python for the Mercury Monte Carlo Particle Transport Code

    SciTech Connect

    Iandola, F N; O'Brien, M J; Procassini, R J

    2010-11-29

    Monte Carlo particle transport applications are often written in low-level languages (C/C++) for optimal performance on clusters and supercomputers. However, this development approach often sacrifices straightforward usability and testing in the interest of fast application performance. To improve usability, some high-performance computing applications employ mixed-language programming with high-level and low-level languages. In this study, we consider the benefits of incorporating an interactive Python interface into a Monte Carlo application. With PyMercury, a new Python extension to the Mercury general-purpose Monte Carlo particle transport code, we improve application usability without diminishing performance. In two case studies, we illustrate how PyMercury improves usability and simplifies testing and validation in a Monte Carlo application. In short, PyMercury demonstrates the value of interactive Python for Monte Carlo particle transport applications. In the future, we expect interactive Python to play an increasingly significant role in Monte Carlo usage and testing.

  3. GPAW - massively parallel electronic structure calculations with Python-based software.

    SciTech Connect

    Enkovaara, J.; Romero, N.; Shende, S.; Mortensen, J.

    2011-01-01

    Electronic structure calculations are a widely used tool in materials science and large consumer of supercomputing resources. Traditionally, the software packages for these kind of simulations have been implemented in compiled languages, where Fortran in its different versions has been the most popular choice. While dynamic, interpreted languages, such as Python, can increase the effciency of programmer, they cannot compete directly with the raw performance of compiled languages. However, by using an interpreted language together with a compiled language, it is possible to have most of the productivity enhancing features together with a good numerical performance. We have used this approach in implementing an electronic structure simulation software GPAW using the combination of Python and C programming languages. While the chosen approach works well in standard workstations and Unix environments, massively parallel supercomputing systems can present some challenges in porting, debugging and profiling the software. In this paper we describe some details of the implementation and discuss the advantages and challenges of the combined Python/C approach. We show that despite the challenges it is possible to obtain good numerical performance and good parallel scalability with Python based software.

  4. Tomopy: A Python toolbox to perform X-Ray data proessing and image reconstruction.

    SciTech Connect

    2014-01-30

    Tomopy is a Python toolbox to perform x-ray data processing, image reconstruction and data exchange tasks at synchrotron facilities. The dependencies of the software are currently as follows: -Python related python standard library (http://docs.python.org/2/library/) numpy (http://www.numpy.org/) scipy (http://scipy.org/) matplotlib (http://matplotlip.org/) sphinx (http://sphinx-doc.org) pil (http://www.pythonware.com/products/pil/) pyhdf (http://pysclint.sourceforge.net/pyhdf/) h5py (http://www.h5py.org) pywt (http://www.pybytes.com/pywavelets/) file.py (https://pyspec.svn.sourceforge.net/svnroot/pyspec/trunk/pyspec/ccd/files.py) -C/C++ related: gridec (anonymous?? C-code written back in 1997 that uses standard C library) fftw (http://www.fftw.org/) tomoRecon (multi-threaded C++ verion of gridrec. Author: Mark Rivers from APS. http://cars9.uchicago.edu/software/epics/tomoRecon.html) epics (http://www.aps.anl.gov/epics/)

  5. Digestive physiology of the Burmese python: broad regulation of integrated performance.

    PubMed

    Secor, Stephen M

    2008-12-01

    As an apparent adaptation to predictably long episodes of fasting, the sit-and-wait foraging Burmese python experiences unprecedented regulation of gastrointestinal and cardiovascular performance with feeding and fasting. The ingestion of a meal signals the quiescent gut tissues to start secreting digestive acid and enzymes, to upregulate intestinal brush-border enzymes and nutrient transporters, and to grow. An integrated phenomenon, digestion is also characterized by increases in the mass, and presumably the function, of the heart, pancreas, liver and kidneys. Once digestion is complete, the python's stomach and small intestine rapidly downregulate performance. Much of the modulation of intestinal function can be explained by the 5-fold increase in microvillus length and apical surface area with feeding, and the subsequent shortening of the microvilli after digestion has finished. Digestion for the Burmese python is a relatively expensive endeavor, evident by the as much as a 44-fold increase in metabolic rate and equivalent in cost to as much as 37% of the meal's energy. Their large metabolic response is supported by substantial increases in ventilation and cardiac output and the apparent catabolism of glucose and lipids. Unmatched in the magnitude of its numerous physiological responses to feeding, the Burmese python is a very attractive model for examining the capacities and regulatory mechanisms of physiological performance.

  6. Python and Roles of Variables in Introductory Programming: Experiences from Three Educational Institutions

    ERIC Educational Resources Information Center

    Nikula, Uolevi; Sajaniemi, Jorma; Tedre, Matti; Wray, Stuart

    2007-01-01

    Students often find that learning to program is hard. Introductory programming courses have high drop-out rates and students do not learn to program well. This paper presents experiences from three educational institutions where introductory programming courses were improved by adopting Python as the first programming language and roles of…

  7. History Revenged: Monty Python Translates Chretien de Troyes's "Perceval, or the Story of the Grail" (Again).

    ERIC Educational Resources Information Center

    Murrell, Elizabeth

    1998-01-01

    Finds "Monty Python and the Holy Grail" functions as a "surprisingly accurate cultural translation" of de Troyes's "Perceval" text. Suggests that using such films helps students open a door upon film studies and discursive studies that will serve them well as they adapt to their own historical moment. (PA)

  8. SWMM5 Application Programming Interface and PySWMM: A Python Interfacing Wrapper

    EPA Science Inventory

    In support of the OpenWaterAnalytics open source initiative, the PySWMM project encompasses the development of a Python interfacing wrapper to SWMM5 with parallel ongoing development of the USEPA Stormwater Management Model (SWMM5) application programming interface (API). ...

  9. Assessing risks to humans from invasive Burmese pythons in Everglades National Park, Florida, USA

    USGS Publications Warehouse

    Reed, Robert N.; Snow, Ray W.

    2014-01-01

    Invasive Burmese pythons (Python molurus bivittatus) are now established across a large area of southern Florida, USA, including all of Everglades National Park (NP). The presence of these large-bodied snakes in the continental United States has attracted intense media attention, including regular reference to the possibility of these snakes preying on humans. Over the course of a decade (2003–2012), we solicited reports of apparently unprovoked strikes directed at humans in Everglades NP. We summarize the circumstances surrounding each of the 5 reported incidents, which occurred between 2006 and 2012. All strikes were directed toward biologists moving through flooded wetlands; 2 strikes resulted in minor injury and none resulted in constriction. We consider most of these strikes to be cases of “mistaken identity,” in which the python initiated a strike at a potential prey item but aborted its predatory behavior prior to constriction and ingestion. No strikes are known to have been directed at park visitors despite visitation rates averaging over one million per year during this period. We conclude that while risks to humans should not be completely discounted, the relative risk of a human being killed by a python in Everglades NP appears to be extremely low.

  10. Using Python Packages in 6D (Py)Ferret: EOF Analysis, OPeNDAP Sequence Data

    NASA Astrophysics Data System (ADS)

    Smith, K. M.; Manke, A.; Hankin, S. C.

    2012-12-01

    PyFerret was designed to provide the easy methods of access, analysis, and display of data found in the Ferret under the simple yet powerful Python scripting/programming language. This has enabled PyFerret to take advantage of a large and expanding collection of third-party scientific Python modules. Furthermore, ensemble and forecast axes have been added to Ferret and PyFerret for creating and working with collections of related data in Ferret's delayed-evaluation and minimal-data-access mode of operation. These axes simplify processing and visualization of these collections of related data. As one example, an empirical orthogonal function (EOF) analysis Python module was developed, taking advantage of the linear algebra module and other standard functionality in NumPy for efficient numerical array processing. This EOF analysis module is used in a Ferret function to provide an ensemble of levels of data explained by each EOF and Time Amplitude Function (TAF) product. Another example makes use of the PyDAP Python module to provide OPeNDAP sequence data for use in Ferret with minimal data access characteristic of Ferret.

  11. Data management routines for reproducible research using the G-Node Python Client library.

    PubMed

    Sobolev, Andrey; Stoewer, Adrian; Pereira, Michael; Kellner, Christian J; Garbers, Christian; Rautenberg, Philipp L; Wachtler, Thomas

    2014-01-01

    Structured, efficient, and secure storage of experimental data and associated meta-information constitutes one of the most pressing technical challenges in modern neuroscience, and does so particularly in electrophysiology. The German INCF Node aims to provide open-source solutions for this domain that support the scientific data management and analysis workflow, and thus facilitate future data access and reproducible research. G-Node provides a data management system, accessible through an application interface, that is based on a combination of standardized data representation and flexible data annotation to account for the variety of experimental paradigms in electrophysiology. The G-Node Python Library exposes these services to the Python environment, enabling researchers to organize and access their experimental data using their familiar tools while gaining the advantages that a centralized storage entails. The library provides powerful query features, including data slicing and selection by metadata, as well as fine-grained permission control for collaboration and data sharing. Here we demonstrate key actions in working with experimental neuroscience data, such as building a metadata structure, organizing recorded data in datasets, annotating data, or selecting data regions of interest, that can be automated to large degree using the library. Compliant with existing de-facto standards, the G-Node Python Library is compatible with many Python tools in the field of neurophysiology and thus enables seamless integration of data organization into the scientific data workflow.

  12. Expression of venom gene homologs in diverse python tissues suggests a new model for the evolution of snake venom.

    PubMed

    Reyes-Velasco, Jacobo; Card, Daren C; Andrew, Audra L; Shaney, Kyle J; Adams, Richard H; Schield, Drew R; Casewell, Nicholas R; Mackessy, Stephen P; Castoe, Todd A

    2015-01-01

    Snake venom gene evolution has been studied intensively over the past several decades, yet most previous studies have lacked the context of complete snake genomes and the full context of gene expression across diverse snake tissues. We took a novel approach to studying snake venom evolution by leveraging the complete genome of the Burmese python, including information from tissue-specific patterns of gene expression. We identified the orthologs of snake venom genes in the python genome, and conducted detailed analysis of gene expression of these venom homologs to identify patterns that differ between snake venom gene families and all other genes. We found that venom gene homologs in the python are expressed in many different tissues outside of oral glands, which illustrates the pitfalls of using transcriptomic data alone to define "venom toxins." We hypothesize that the python may represent an ancestral state prior to major venom development, which is supported by our finding that the expansion of venom gene families is largely restricted to highly venomous caenophidian snakes. Therefore, the python provides insight into biases in which genes were recruited for snake venom systems. Python venom homologs are generally expressed at lower levels, have higher variance among tissues, and are expressed in fewer organs compared with all other python genes. We propose a model for the evolution of snake venoms in which venom genes are recruited preferentially from genes with particular expression profile characteristics, which facilitate a nearly neutral transition toward specialized venom system expression.

  13. Zachary D. Barker: Final DHS HS-STEM Report

    SciTech Connect

    Barker, Z D

    2008-08-14

    Working at Lawrence Livermore National Laboratory (LLNL) this summer has provided a very unique and special experience for me. I feel that the research opportunities given to me have allowed me to significantly benefit my research group, the laboratory, the Department of Homeland Security, and the Department of Energy. The researchers in the Single Particle Aerosol Mass Spectrometry (SPAMS) group were very welcoming and clearly wanted me to get the most out of my time in Livermore. I feel that my research partner, Veena Venkatachalam of MIT, and I have been extremely productive in meeting our research goals throughout this summer, and have learned much about working in research at a national laboratory such as Lawrence Livermore. I have learned much about the technical aspects of research while working at LLNL, however I have also gained important experience and insight into how research groups at national laboratories function. I believe that this internship has given me valuable knowledge and experience which will certainly help my transition to graduate study and a career in engineering. My work with Veena Venkatachalam in the SPAMS group this summer has focused on two major projects. Initially, we were tasked with an analysis of data collected by the group this past spring in a large public environment. The SPAMS instrument was deployed for over two months, collecting information on many of the ambient air particles circulating through the area. Our analysis of the particle data collected during this deployment concerned several aspects, including finding groups, or clusters, of particles that seemed to appear more during certain times of day, analyzing the mass spectral data of clusters and comparing them with mass spectral data of known substances, and comparing the real-time detection capability of the SPAMS instrument with that of a commercially available biological detection instrument. This analysis was performed in support of a group report to the Department of Homeland Security on the results of the deployment. The analysis of the deployment data revealed some interesting applications of the SPAMS instrument to homeland security situations. Using software developed in-house by SPAMS group member Dr. Paul Steele, Veena and I were able to cluster a subset of data over a certain timeframe (ranging from a single hour to an entire week). The software used makes clusters based on the mass spectral characteristics of the each particle in the data set, as well as other parameters. By looking more closely at the characteristics of individual clusters, including the mass spectra, conclusions could be made about what these particles are. This was achieved partially through examination and discussion of the mass spectral data with the members of the SPAMS group, as well as through comparison with known mass spectra collected from substances tested in the laboratory. In many cases, broad conclusions could be drawn about the identity of a cluster of particles.

  14. Morphological Pulmonary Diffusion Capacity for Oxygen of Burmese Pythons (Python molurus): a Comparison of Animals in Healthy Condition and with Different Pulmonary Infections.

    PubMed

    Starck, J M; Weimer, I; Aupperle, H; Müller, K; Marschang, R E; Kiefer, I; Pees, M

    2015-11-01

    A qualitative and quantitative morphological study of the pulmonary exchange capacity of healthy and diseased Burmese pythons (Python molurus) was carried out in order to test the hypothesis that the high morphological excess capacity for oxygen exchange in the lungs of these snakes is one of the reasons why pathological processes extend throughout the lung parenchyma and impair major parts of the lungs before clinical signs of respiratory disease become apparent. Twenty-four Burmese pythons (12 healthy and 12 diseased) were included in the study. A stereology-based approach was used to quantify the lung parenchyma using computed tomography. Light microscopy was used to quantify tissue compartments and the respiratory exchange surface, and transmission electron microscopy was used to measure the thickness of the diffusion barrier. The morphological diffusion capacity for oxygen of the lungs and the anatomical diffusion factor were calculated. The calculated anatomical diffusion capacity was compared with published values for oxygen consumption of healthy snakes, and the degree to which the exchange capacity can be obstructed before normal physiological function is impaired was estimated. Heterogeneous pulmonary infections result in graded morphological transformations of pulmonary parenchyma involving lymphocyte migration into the connective tissue and thickening of the septal connective tissue, increasing thickness of the diffusion barrier and increasing transformation of the pulmonary epithelium into a columnar pseudostratified or stratified epithelium. The transformed epithelium developed by hyperplasia of ciliated cells arising from the tip of the faveolar septa and by hyperplasia of type II pneumocytes. These results support the idea that the lungs have a remarkable overcapacity for oxygen consumption and that the development of pulmonary disease continuously reduces the capacity for oxygen consumption. However, due to the overcapacity of the lungs, this

  15. Molecular cloning and characterization of satellite DNA sequences from constitutive heterochromatin of the habu snake (Protobothrops flavoviridis, Viperidae) and the Burmese python (Python bivittatus, Pythonidae).

    PubMed

    Matsubara, Kazumi; Uno, Yoshinobu; Srikulnath, Kornsorn; Seki, Risako; Nishida, Chizuko; Matsuda, Yoichi

    2015-12-01

    Highly repetitive DNA sequences of the centromeric heterochromatin provide valuable molecular cytogenetic markers for the investigation of genomic compartmentalization in the macrochromosomes and microchromosomes of sauropsids. Here, the relationship between centromeric heterochromatin and karyotype evolution was examined using cloned repetitive DNA sequences from two snake species, the habu snake (Protobothrops flavoviridis, Crotalinae, Viperidae) and Burmese python (Python bivittatus, Pythonidae). Three satellite DNA (stDNA) families were isolated from the heterochromatin of these snakes: 168-bp PFL-MspI from P. flavoviridis and 196-bp PBI-DdeI and 174-bp PBI-MspI from P. bivittatus. The PFL-MspI and PBI-DdeI sequences were localized to the centromeric regions of most chromosomes in the respective species, suggesting that the two sequences were the major components of the centromeric heterochromatin in these organisms. The PBI-MspI sequence was localized to the pericentromeric region of four chromosome pairs. The PFL-MspI and the PBI-DdeI sequences were conserved only in the genome of closely related species, Gloydius blomhoffii (Crotalinae) and Python molurus, respectively, although their locations on the chromosomes were slightly different. In contrast, the PBI-MspI sequence was also in the genomes of P. molurus and Boa constrictor (Boidae), and additionally localized to the centromeric regions of eight chromosome pairs in B. constrictor, suggesting that this sequence originated in the genome of a common ancestor of Pythonidae and Boidae, approximately 86 million years ago. The three stDNA sequences showed no genomic compartmentalization between the macrochromosomes and microchromosomes, suggesting that homogenization of the centromeric and/or pericentromeric stDNA sequences occurred in the macrochromosomes and microchromosomes of these snakes.

  16. Identification and comparison of marbofloxacin metabolites from the plasma of ball pythons (Python regius) and blue and gold macaws (Ara ararauna).

    PubMed

    Hunter, R P; Koch, D E; Coke, R L; Carpenter, J W; Isaza, R

    2007-06-01

    Marbofloxacin is a veterinary only, synthetic, broad spectrum fluoroquinolone antimicrobial agent. In mammals, approximately 40% of the oral dose of marbofloxacin is excreted unchanged in the urine; the remaining is excreted via the bile as unchanged drug in the feces. The Vd ranges from 1.1 (cattle) to 1.3 (dog, goat, swine) L/kg. Because of extra-label use of marbofloxacin in birds and reptiles, this study was designed to determine the profile of metabolites in plasma and compare the circulating metabolite profile between a reptile and an avian species. Six adult ball pythons (Python regius) and 10 blue and gold macaws (Ara ararauna) were used in this study. The macaws were dosed both i.v. and p.o. with a single 2.5 mg/kg administration where as the pythons received a single 10 mg/kg dose both i.v. and p.o. The metabolite profiles of marbofloxacin in the plasma of these species were determined using a high performance liquid chromatography system with a mass spectrometer for detection (LC/MS/MS). Mass spectra data generated from the snake and bird plasma samples were compared with previously reported LC/MS/MS mass spectral data. Evidence does not suggest differences due to route of administration (i.v. vs. p.o.) in either species. Four chromatographic peaks with resulting daughter spectrum were identified and represent 12 possible metabolite structures. All of the proposed metabolites, except for the N-oxide, appear to be unique to macaws. The potential metabolites identified in macaws appear to be very different than those reported for chickens.

  17. GMES: A Python package for solving Maxwell’s equations using the FDTD method

    NASA Astrophysics Data System (ADS)

    Chun, Kyungwon; Kim, Huioon; Kim, Hyounggyu; Jung, Kil Su; Chung, Youngjoo

    2013-04-01

    This paper describes GMES, a free Python package for solving Maxwell’s equations using the finite-difference time-domain (FDTD) method. The design of GMES follows the object-oriented programming (OOP) approach and adopts a unique design strategy where the voxels in the computational domain are grouped and then updated according to its material type. This piecewise updating scheme ensures that GMES can adopt OOP without losing its simple structure and time-stepping speed. The users can easily add various material types, sources, and boundary conditions into their code using the Python programming language. The key design features, along with the supported material types, excitation sources, boundary conditions and parallel calculations employed in GMES are also described in detail. Catalog identifier: AEOK_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEOK_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: GNU General Public License v3.0 No. of lines in distributed program, including test data, etc.: 17700 No. of bytes in distributed program, including test data, etc.: 89878 Distribution format: tar.gz Programming language: C++, Python. Computer: Any computer with a Unix-like system with a C++ compiler, and a Python interpreter; developed on 2.53 GHz Intel CoreTM i3. Operating system: Any Unix-like system; developed under Ubuntu 12.04 LTS 64 bit. Has the code been vectorized or parallelized?: Yes. Parallelized with MPI directives (optional). RAM: Problem dependent (a simulation with real valued electromagnetic field uses roughly 0.18 KB per Yee cell.) Classification: 10. External routines: SWIG [1], Cython [2], NumPy [3], SciPy [4], matplotlib [5], MPI for Python [6] Nature of problem: Classical electrodynamics Solution method: Finite-difference time-domain (FDTD) method Additional comments: This article describes version 0.9.5. The most recent version can be downloaded at the GMES

  18. Selected regulation of gastrointestinal acid-base secretion and tissue metabolism for the diamondback water snake and Burmese python.

    PubMed

    Secor, Stephen M; Taylor, Josi R; Grosell, Martin

    2012-01-01

    Snakes exhibit an apparent dichotomy in the regulation of gastrointestinal (GI) performance with feeding and fasting; frequently feeding species modestly regulate intestinal function whereas infrequently feeding species rapidly upregulate and downregulate intestinal function with the start and completion of each meal, respectively. The downregulatory response with fasting for infrequently feeding snakes is hypothesized to be a selective attribute that reduces energy expenditure between meals. To ascertain the links between feeding habit, whole-animal metabolism, and GI function and metabolism, we measured preprandial and postprandial metabolic rates and gastric and intestinal acid-base secretion, epithelial conductance and oxygen consumption for the frequently feeding diamondback water snake (Nerodia rhombifer) and the infrequently feeding Burmese python (Python molurus). Independent of body mass, Burmese pythons possess a significantly lower standard metabolic rate and respond to feeding with a much larger metabolic response compared with water snakes. While fasting, pythons cease gastric acid and intestinal base secretion, both of which are stimulated with feeding. In contrast, fasted water snakes secreted gastric acid and intestinal base at rates similar to those of digesting snakes. We observed no difference between fasted and fed individuals for either species in gastric or intestinal transepithelial potential and conductance, with the exception of a significantly greater gastric transepithelial potential for fed pythons at the start of titration. Water snakes experienced no significant change in gastric or intestinal metabolism with feeding. Fed pythons, in contrast, experienced a near-doubling of gastric metabolism and a tripling of intestinal metabolic rate. For fasted individuals, the metabolic rate of the stomach and small intestine was significantly lower for pythons than for water snakes. The fasting downregulation of digestive function for pythons is

  19. Python-Based Scientific Analysis and Visualization of Precipitation Systems at NASA Marshall Space Flight Center

    NASA Technical Reports Server (NTRS)

    Lang, Timothy J.

    2015-01-01

    At NASA Marshall Space Flight Center (MSFC), Python is used several different ways to analyze and visualize precipitating weather systems. A number of different Python-based software packages have been developed, which are available to the larger scientific community. The approach in all these packages is to utilize pre-existing Python modules as well as to be object-oriented and scalable. The first package that will be described and demonstrated is the Python Advanced Microwave Precipitation Radiometer (AMPR) Data Toolkit, or PyAMPR for short. PyAMPR reads geolocated brightness temperature data from any flight of the AMPR airborne instrument over its 25-year history into a common data structure suitable for user-defined analyses. It features rapid, simplified (i.e., one line of code) production of quick-look imagery, including Google Earth overlays, swath plots of individual channels, and strip charts showing multiple channels at once. These plotting routines are also capable of significant customization for detailed, publication-ready figures. Deconvolution of the polarization-varying channels to static horizontally and vertically polarized scenes is also available. Examples will be given of PyAMPR's contribution toward real-time AMPR data display during the Integrated Precipitation and Hydrology Experiment (IPHEx), which took place in the Carolinas during May-June 2014. The second software package is the Marshall Multi-Radar/Multi-Sensor (MRMS) Mosaic Python Toolkit, or MMM-Py for short. MMM-Py was designed to read, analyze, and display three-dimensional national mosaicked reflectivity data produced by the NOAA National Severe Storms Laboratory (NSSL). MMM-Py can read MRMS mosaics from either their unique binary format or their converted NetCDF format. It can also read and properly interpret the current mosaic design (4 regional tiles) as well as mosaics produced prior to late July 2013 (8 tiles). MMM-Py can easily stitch multiple tiles together to provide a

  20. PLACE: an open-source python package for laboratory automation, control, and experimentation.

    PubMed

    Johnson, Jami L; Tom Wörden, Henrik; van Wijk, Kasper

    2015-02-01

    In modern laboratories, software can drive the full experimental process from data acquisition to storage, processing, and analysis. The automation of laboratory data acquisition is an important consideration for every laboratory. When implementing a laboratory automation scheme, important parameters include its reliability, time to implement, adaptability, and compatibility with software used at other stages of experimentation. In this article, we present an open-source, flexible, and extensible Python package for Laboratory Automation, Control, and Experimentation (PLACE). The package uses modular organization and clear design principles; therefore, it can be easily customized or expanded to meet the needs of diverse laboratories. We discuss the organization of PLACE, data-handling considerations, and then present an example using PLACE for laser-ultrasound experiments. Finally, we demonstrate the seamless transition to post-processing and analysis with Python through the development of an analysis module for data produced by PLACE automation.

  1. Cold induced mortality of the Burmese Python: An explanation via stochastic analysis

    NASA Astrophysics Data System (ADS)

    Quansah, Emmanuel; Parshad, Rana D.; Mondal, Sumona

    2017-02-01

    The Burmese python (Python bivitatus) is an invasive species, wreaking havoc on indigenous species in the Florida everglades. Data suggests an exponential growth in their population from 1995 to 2009, with a sharp decline however in 2010-2012 (Dorcas et al., 2012). In Mazzotti et al. (2011) an explanation is provided, citing the unusually cold winter that year, as the primary reason for this decline. We provide a first mathematical model, in the form of a system of stochastic differential equations, that supports the explanation in Mazzotti et al. (2011), by accurately matching the field data presented in Dorcas et al. (2012). More generally, our model provides a tool to predict the population dynamics of rapidly growing alien species, in the advent of climate change.

  2. Two-dimensional echocardiographic anatomy of the snake heart (Python molurus bivittatus).

    PubMed

    Snyder, P S; Shaw, N G; Heard, D J

    1999-01-01

    Two-dimensional echocardiography was performed on Burmese pythons (Python molurus bivittatus) to determine an optimal echocardiographic imaging technique for snakes and to describe the echocardiographic anatomy of the snake heart. Five snakes immobilized with tiletamine/zolazepam and maintained on isoflurane in oxygen were imaged in dorsal recumbency. The portion of the snake's body containing the heart was submerged in warm water to reduce the artifact created by air trapped between and under the scales. Imaging in sagittal planes demonstrated the caudal vena cava, sinus venous valve, right atrium, various portions of the ventricle, horizontal septum, the left aortic arch, and pulmonary artery. Transverse imaging depicted the spatial relationship of the left and right aortic arches and pulmonary artery and the horizontal septum. Basic knowledge of cardiac blood flow in the reptile was necessary to understand the echocardiographic anatomy.

  3. ZonalMetrics - a Python toolbox for zonal landscape structure analysis

    NASA Astrophysics Data System (ADS)

    Adamczyk, Joanna; Tiede, Dirk

    2017-02-01

    We present a Python toolbox for the calculation of zonal landscape metrics. Instead of global calculations focusing on the whole landscape, the proposed ZonalMetrics toolbox allows the calculation of landscape metrics for user-defined zones. Such zones can be defined through regular units (e.g. hexagons, grids) that can be created within the toolbox. In addition, any polygonal set specified by the user (e.g. administrative units) can be used. The implemented set of landscape metrics is specifically selected and valid for calculations within zones. The tool is demonstrated based on a case study for the Warsaw metropolitan area and the possibilities of applying the toolbox for different zonal layers are illustrated. The implementation is based on the Python toolbox introduced in ArcGIS 10.1, offering an easy to use graphical user interface and batch calculation possibilities. The source code is free and open to the community and extendable to specific needs.

  4. InfraPy: Python-Based Signal Analysis Tools for Infrasound

    SciTech Connect

    Blom, Philip Stephen; Marcillo, Omar Eduardo; Euler, Garrett Gene

    2016-05-31

    InfraPy is a Python-based analysis toolkit being development at LANL. The algorithms are intended for ground-based nuclear detonation detection applications to detect, locate, and characterize explosive sources using infrasonic observations. The implementation is usable as a stand-alone Python library or as a command line driven tool operating directly on a database. With multiple scientists working on the project, we've begun using a LANL git repository for collaborative development and version control. Current and planned work on InfraPy focuses on the development of new algorithms and propagation models. Collaboration with Southern Methodist University (SMU) has helped identify bugs and limitations of the algorithms. The current focus of usage development is focused on library imports and CLI.

  5. PlasmaPy: beginning a community developed Python package for plasma physics

    NASA Astrophysics Data System (ADS)

    Murphy, Nicholas A.; Huang, Yi-Min; PlasmaPy Collaboration

    2016-10-01

    In recent years, researchers in several disciplines have collaborated on community-developed open source Python packages such as Astropy, SunPy, and SpacePy. These packages provide core functionality, common frameworks for data analysis and visualization, and educational tools. We propose that our community begins the development of PlasmaPy: a new open source core Python package for plasma physics. PlasmaPy could include commonly used functions in plasma physics, easy-to-use plasma simulation codes, Grad-Shafranov solvers, eigenmode solvers, and tools to analyze both simulations and experiments. The development will include modern programming practices such as version control, embedding documentation in the code, unit tests, and avoiding premature optimization. We will describe early code development on PlasmaPy, and discuss plans moving forward. The success of PlasmaPy depends on active community involvement and a welcoming and inclusive environment, so anyone interested in joining this collaboration should contact the authors.

  6. Modular Python-based Code for Thomson Scattering System on NSTX-U

    NASA Astrophysics Data System (ADS)

    Horowitz, Benjamin; Diallo, Ahmed; Feibush, Eliot; Leblanc, Benoit

    2013-10-01

    Fast accurate and reliable measurements of electron temperature and density profiles within magnetically confined plasmas are essential for full operation of fusion devices. We detail the design and implementation of a modular Pythonbased code for the Thomson Scattering diagnostic system of NSTX-U which offers improvements in speed by making full use of the Python's architecture, open-source module packages, and ability to be parallelized across many processors. SciPy's weave package allows the implementation of C/C++ code within our program to clear up bottlenecks in data fitting while not loosing the flexibility and clarity of Python, while Numpy and MatplotLib allow calculations and plotting of the processed data. Using the standard MDSplus input, we create a flexible and expandable algorithm structure which can be implemented on any fusion device utilizing polychromator-based Thomson scattering diagnostic system. Supported by DOE SULI Fellowship at Princeton Plasma Physics Lab.

  7. Calculations of lattice vibrational mode lifetimes using Jazz: a Python wrapper for LAMMPS

    NASA Astrophysics Data System (ADS)

    Gao, Y.; Wang, H.; Daw, M. S.

    2015-06-01

    Jazz is a new python wrapper for LAMMPS [1], implemented to calculate the lifetimes of vibrational normal modes based on forces as calculated for any interatomic potential available in that package. The anharmonic character of the normal modes is analyzed via the Monte Carlo-based moments approximation as is described in Gao and Daw [2]. It is distributed as open-source software and can be downloaded from the website http://jazz.sourceforge.net/.

  8. Factors affecting hematology and plasma biochemistry in the southwest carpet python (Morelia spilota imbricata).

    PubMed

    Bryant, Gillian L; Fleming, Patricia A; Twomey, Leanne; Warren, Kristin A

    2012-04-01

    Despite increased worldwide popularity of keeping reptiles as pets, we know little about hematologic and biochemical parameters of most reptile species, or how these measures may be influenced by intrinsic and extrinsic factors. Blood samples from 43 wild-caught pythons (Morelia spilota imbricata) were collected at various stages of a 3-yr ecological study in Western Australia. Reference intervals are reported for 35 individuals sampled at the commencement of the study. As pythons were radiotracked for varying lengths of time (radiotransmitters were surgically implanted), repeated sampling was undertaken from some individuals. However, because of our ad hoc sampling design we cannot be definitive about temporal factors that were most important or that exclusively influenced blood parameters. There was no significant effect of sex or the presence of a hemogregarine parasite on blood parameters. Erythrocyte measures were highest for pythons captured in the jarrah forest and at the stage of radiotransmitter implantation, which was also linked with shorter time in captivity. Basophil count, the only leukocyte influenced by the factors tested, was highest when the python was anesthetized, as was globulin concentration. Albumin and the albumin:globulin ratio were more concentrated in summer (as was phosphorous) and at the initial stage of radiotransmitter placement (as was calcium). No intrinsic or extrinsic factors influenced creatinine kinase, aspartate aminotransferase, uric acid, or total protein. This study demonstrates that factors including season, location, surgical radiotransmitter placement, and anesthetic state can influence blood parameters of M. s. imbricata. For accurate diagnosis, veterinarians should be aware that the current reference intervals used to identify the health status of individuals for this species are outdated and the interpretation and an understanding of the influence of intrinsic and extrinsic factors are limited.

  9. RESTRICTIVE CARDIOMYOPATHY AND SECONDARY CONGESTIVE HEART FAILURE IN A MCDOWELL'S CARPET PYTHON (MORELIA SPILOTA MCDOWELLI).

    PubMed

    Schilliger, Lionel; Chetboul, Valérie; Damoiseaux, Cécile; Nicolier, Alexandra

    2016-12-01

    Echocardiography is an established and noninvasive diagnostic tool used in herpetologic cardiology. Various cardiac lesions have been previously described in reptiles with the exception of restrictive cardiomyopathy. In this case report, restrictive cardiomyopathy and congestive heart failure associated with left atrial and sinus venosus dilation were diagnosed in a 2-yr-old captive lethargic McDowell's carpet python ( Morelia spilota mcdowelli), based on echocardiographic, Doppler, and histopathologic examinations. This cardiomyopathy was also associated with thrombosis within the sinus venosus.

  10. The Burmese python genome reveals the molecular basis for extreme adaptation in snakes.

    PubMed

    Castoe, Todd A; de Koning, A P Jason; Hall, Kathryn T; Card, Daren C; Schield, Drew R; Fujita, Matthew K; Ruggiero, Robert P; Degner, Jack F; Daza, Juan M; Gu, Wanjun; Reyes-Velasco, Jacobo; Shaney, Kyle J; Castoe, Jill M; Fox, Samuel E; Poole, Alex W; Polanco, Daniel; Dobry, Jason; Vandewege, Michael W; Li, Qing; Schott, Ryan K; Kapusta, Aurélie; Minx, Patrick; Feschotte, Cédric; Uetz, Peter; Ray, David A; Hoffmann, Federico G; Bogden, Robert; Smith, Eric N; Chang, Belinda S W; Vonk, Freek J; Casewell, Nicholas R; Henkel, Christiaan V; Richardson, Michael K; Mackessy, Stephen P; Bronikowski, Anne M; Bronikowsi, Anne M; Yandell, Mark; Warren, Wesley C; Secor, Stephen M; Pollock, David D

    2013-12-17

    Snakes possess many extreme morphological and physiological adaptations. Identification of the molecular basis of these traits can provide novel understanding for vertebrate biology and medicine. Here, we study snake biology using the genome sequence of the Burmese python (Python molurus bivittatus), a model of extreme physiological and metabolic adaptation. We compare the python and king cobra genomes along with genomic samples from other snakes and perform transcriptome analysis to gain insights into the extreme phenotypes of the python. We discovered rapid and massive transcriptional responses in multiple organ systems that occur on feeding and coordinate major changes in organ size and function. Intriguingly, the homologs of these genes in humans are associated with metabolism, development, and pathology. We also found that many snake metabolic genes have undergone positive selection, which together with the rapid evolution of mitochondrial proteins, provides evidence for extensive adaptive redesign of snake metabolic pathways. Additional evidence for molecular adaptation and gene family expansions and contractions is associated with major physiological and phenotypic adaptations in snakes; genes involved are related to cell cycle, development, lungs, eyes, heart, intestine, and skeletal structure, including GRB2-associated binding protein 1, SSH, WNT16, and bone morphogenetic protein 7. Finally, changes in repetitive DNA content, guanine-cytosine isochore structure, and nucleotide substitution rates indicate major shifts in the structure and evolution of snake genomes compared with other amniotes. Phenotypic and physiological novelty in snakes seems to be driven by system-wide coordination of protein adaptation, gene expression, and changes in the structure of the genome.

  11. Embryonic development of Python sebae - II: Craniofacial microscopic anatomy, cell proliferation and apoptosis.

    PubMed

    Buchtová, Marcela; Boughner, Julia C; Fu, Katherine; Diewert, Virginia M; Richman, Joy M

    2007-01-01

    This study explores the microscopic craniofacial morphogenesis of the oviparous African rock python (Python sebae) spanning the first two-thirds of the post-oviposition period. At the time of laying, the python embryo consists of largely undifferentiated mesenchyme and epithelium with the exception of the cranial base and trabeculae cranii, which are undergoing chondrogenesis. The facial prominences are well defined and are at a late stage, close to the time when lip fusion begins. Later (11-12d), specializations in the epithelia begin to differentiate (vomeronasal and olfactory epithelia, teeth). Dental development in snakes is different from that of mammals in several aspects including an extended dental lamina with the capacity to form 4 sets of generational teeth. In addition, the ophidian olfactory system is very different from the mammalian. There is a large vomeronasal organ, a nasal cavity proper and an extraconchal space. All of these areas are lined with a greatly expanded olfactory epithelium. Intramembranous bone differentiation is taking place at stage 3 with some bones already ossifying whereas most are only represented as mesenchymal condensations. In addition to routine histological staining, PCNA immunohistochemistry reveals relatively higher levels of proliferation in the extending dental laminae, in osseous mesenchymal condensations and in the olfactory epithelia. Areas undergoing apoptosis were noted in the enamel organs of the teeth and osseous mesenchymal condensations. We propose that localized apoptosis helps to divide a single condensation into multiple ossification centres and this is a mechanism whereby novel morphology can be selected in response to evolutionary pressures. Several additional differences in head morphology between snakes and other amniotes were noted including a palatal groove separating the inner and outer row of teeth in the upper jaw, a tracheal opening within the tongue and a pharyngeal adhesion that closes off the

  12. Generation of Test Questions from RDF Files Using PYTHON and SPARQL

    NASA Astrophysics Data System (ADS)

    Omarbekova, Assel; Sharipbay, Altynbek; Barlybaev, Alibek

    2017-02-01

    This article describes the development of the system for the automatic generation of test questions based on the knowledge base. This work has an applicable nature and provides detailed examples of the development of ontology and implementation the SPARQL queries in RDF-documents. Also it describes implementation of the program generating questions in the Python programming language including the necessary libraries while working with RDF-files.

  13. And now for something completely different: Inattentional blindness during a Monty Python's Flying Circus sketch.

    PubMed

    Wiseman, Richard; Watt, Caroline

    2015-01-01

    Perceptual science has frequently benefited from studying illusions created outside of academia. Here, we describe a striking, but little-known, example of inattentional blindness from the British comedy series "Monty Python's Flying Circus." Viewers fail to attend to several highly incongruous characters in the sketch, despite these characters being clearly visible onscreen. The sketch has the potential to be a valuable research and teaching resource, as well as providing a vivid illustration of how people often fail to see something completely different.

  14. Mushu, a free- and open source BCI signal acquisition, written in Python.

    PubMed

    Venthur, Bastian; Blankertz, Benjamin

    2012-01-01

    The following paper describes Mushu, a signal acquisition software for retrieval and online streaming of Electroencephalography (EEG) data. It is written, but not limited, to the needs of Brain Computer Interfacing (BCI). It's main goal is to provide a unified interface to EEG data regardless of the amplifiers used. It runs under all major operating systems, like Windows, Mac OS and Linux, is written in Python and is free- and open source software licensed under the terms of the GNU General Public License.

  15. The Burmese python genome reveals the molecular basis for extreme adaptation in snakes

    PubMed Central

    Castoe, Todd A.; de Koning, A. P. Jason; Hall, Kathryn T.; Card, Daren C.; Schield, Drew R.; Fujita, Matthew K.; Ruggiero, Robert P.; Degner, Jack F.; Daza, Juan M.; Gu, Wanjun; Reyes-Velasco, Jacobo; Shaney, Kyle J.; Castoe, Jill M.; Fox, Samuel E.; Poole, Alex W.; Polanco, Daniel; Dobry, Jason; Vandewege, Michael W.; Li, Qing; Schott, Ryan K.; Kapusta, Aurélie; Minx, Patrick; Feschotte, Cédric; Uetz, Peter; Ray, David A.; Hoffmann, Federico G.; Bogden, Robert; Smith, Eric N.; Chang, Belinda S. W.; Vonk, Freek J.; Casewell, Nicholas R.; Henkel, Christiaan V.; Richardson, Michael K.; Mackessy, Stephen P.; Bronikowski, Anne M.; Yandell, Mark; Warren, Wesley C.; Secor, Stephen M.; Pollock, David D.

    2013-01-01

    Snakes possess many extreme morphological and physiological adaptations. Identification of the molecular basis of these traits can provide novel understanding for vertebrate biology and medicine. Here, we study snake biology using the genome sequence of the Burmese python (Python molurus bivittatus), a model of extreme physiological and metabolic adaptation. We compare the python and king cobra genomes along with genomic samples from other snakes and perform transcriptome analysis to gain insights into the extreme phenotypes of the python. We discovered rapid and massive transcriptional responses in multiple organ systems that occur on feeding and coordinate major changes in organ size and function. Intriguingly, the homologs of these genes in humans are associated with metabolism, development, and pathology. We also found that many snake metabolic genes have undergone positive selection, which together with the rapid evolution of mitochondrial proteins, provides evidence for extensive adaptive redesign of snake metabolic pathways. Additional evidence for molecular adaptation and gene family expansions and contractions is associated with major physiological and phenotypic adaptations in snakes; genes involved are related to cell cycle, development, lungs, eyes, heart, intestine, and skeletal structure, including GRB2-associated binding protein 1, SSH, WNT16, and bone morphogenetic protein 7. Finally, changes in repetitive DNA content, guanine-cytosine isochore structure, and nucleotide substitution rates indicate major shifts in the structure and evolution of snake genomes compared with other amniotes. Phenotypic and physiological novelty in snakes seems to be driven by system-wide coordination of protein adaptation, gene expression, and changes in the structure of the genome. PMID:24297902

  16. PyXel: A Python Package for Astronomical X-ray Data Modeling

    NASA Astrophysics Data System (ADS)

    Ogrean, Georgiana

    2016-06-01

    PyXel is an new Python package for modeling astronomical X-ray imaging data. It is built on NumPy, SciPy, matplotlib, and Astropy, and distributed under an open-source license. The package aims to provide a common set of image analysis tools for astronomers working with extended X-ray sources. I will present an overview of its existing and planned features, and analysis examples based on public Chandra data.

  17. A HIGH-LEVEL PYTHON INTERFACE TO THE FERMILAB ACNET CONTROL SYSTEM

    SciTech Connect

    Piot, P.; Halavanau, A.

    2016-10-19

    This paper discusses the implementation of a python- based high-level interface to the Fermilab acnet control system. The interface has been successfully employed during the commissioning of the Fermilab Accelerator Science & Technology (FAST) facility. Specifically, we present examples of applications at FAST which include the interfacing of the elegant program to assist lattice matching, an automated emittance measurement via the quadrupole-scan method and tranverse transport matrix measurement of a superconducting RF cavity.

  18. ObsPy: A Python Toolbox for Seismology and Seismological Observatories

    NASA Astrophysics Data System (ADS)

    Krischer, Lion; Megies, Tobias; Barsch, Robert; Beyreuther, Moritz; Wassermann, Joachim

    2013-04-01

    Python combines the power of a full-blown programming language with the flexibility and accessibility of an interactive scripting language. Its extensive standard library and large variety of freely available high quality scientific modules cover most needs in developing scientific processing workflows. ObsPy extends Python's capabilities to fit the specific needs that arise when working with seismological data. It a) comes with a continuously growing signal processing toolbox that covers most tasks common in seismological analysis, b) provides read and write support for many common waveform, station and event metadata formats and c) enables access to various data centers, webservices and databases to retrieve waveform data and station/event metadata. In combination with mature and free Python packages like NumPy, SciPy, Matplotlib, IPython and PyQt, ObsPy makes it possible to develop complete workflows in Python, ranging from reading locally stored data or requesting data from one or more different data centers via signal analysis and data processing to visualization in GUI and web applications, output of modified/derived data and the creation of publication-quality figures. All functionality is extensively documented and the ObsPy Tutorial and Gallery give a good impression of the wide range of possible use cases. ObsPy is tested and running on Linux, OS X and Windows and comes with installation routines for these systems. ObsPy is developed in a test-driven approach and is available under the GPL/LGPLv3 open source licences. Users are welcome to request help, report bugs, propose enhancements or contribute code via either the user mailing list or the project page on GitHub.

  19. Computed tomography of the lung of healthy snakes of the species Python regius, Boa constrictor, Python reticulatus, Morelia viridis, Epicrates cenchria, and Morelia spilota.

    PubMed

    Pees, Michael; Kiefer, Ingmar; Thielebein, Jens; Oechtering, Gerhard; Krautwald-Junghanns, Maria-Elisabeth

    2009-01-01

    Thirty-nine healthy boid snakes representing six different species (Python regius, Boa constrictor, Python reticulatus, Morelia viridis, Epicrates cenchria, and Morelia spilota) were examined using computed tomography (CT) to characterize the normal appearance of the respiratory tissue. Assessment was done subjectively and densitometry was performed using a defined protocol. The length of the right lung was calculated to be 11.1% of the body length, without a significant difference between species. The length of the left lung in proportion to the right was dependent on the species examined. The most developed left lung was in P. regius (81.2%), whereas in B. constrictor, the left lung was vestigial or absent (24.7%). A median attenuation of -814.6 HU and a variability of 45.9 HU were calculated for all species with no significant difference between species. Within the species, a significantly higher attenuation was found for P. regius in the dorsal and cranial aspect of the lung compared with the ventral and caudal part. In B. constrictor, the reduced left lung was significantly hyperattenuating compared with the right lung. Results of this study emphasize the value of CT and provide basic reference data for assessment of the snake lung in these species. Veterinary Radiology &

  20. Development of a PYTHON-based emittance calculator at Fermilab Accelerator Science and Technology (FAST) facility

    NASA Astrophysics Data System (ADS)

    Green, A. T.

    Beam emittance is an important characteristic describing charged particle beams. In linear accelerators (linac), it is critical to characterize the beam phase space parameters and, in particular, to precisely measure transverse beam emittance. The quadrupole scan (quad-scan) is a well-established technique used to characterize transverse beam parameters in four-dimensional phase space, including beam emittance. A computational algorithm with PYTHON scripts has been developed to estimate beam parameters, in particular beam emittance, using the quad-scan technique in the electron linac at the Fermilab Accelerator Science and Technology (FAST) facility. This script has been implemented in conjunction with an automated quad-scan tool (also written in PYTHON) and has decreased the time it takes to perform a single quad-scan from an hour to a few minutes. From the experimental data, the emittance calculator quickly delivers several results including: geometrical and normalized transverse emittance, Courant-Snyder parameters, and plots of the beam size versus quadrupole field strength, among others. This paper will discuss the details of the techniques used, the results from several quad-scans preformed at FAST during the electron injector commissioning, and the PYTHON code used to obtain the results.

  1. Anisotropy in the Cosmic Microwave Background at Degree Angular Scales: Python V Results

    NASA Astrophysics Data System (ADS)

    Coble, K.; Dragovan, M.; Kovac, J.; Halverson, N. W.; Holzapfel, W. L.; Knox, L.; Dodelson, S.; Ganga, K.; Alvarez, D.; Peterson, J. B.; Griffin, G.; Newcomb, M.; Miller, K.; Platt, S. R.; Novak, G.

    1999-07-01

    Observations of the microwave sky using the Python telescope in its fifth season of operation at the Amundsen-Scott South Pole Station in Antarctica are presented. The system consists of a 0.75 m off-axis telescope instrumented with a HEMT amplifier-based radiometer having continuum sensitivity from 37 to 45 GHz in two frequency bands. With a 0.91d×1.02d beam, the instrument fully sampled 598 deg2 of sky, including fields measured during the previous four seasons of Python observations. Interpreting the observed fluctuations as anisotropy in the cosmic microwave background, we place constraints on the angular power spectrum of fluctuations in eight multipole bands up to l~260. The observed spectrum is consistent with both the COBE experiment and previous Python results. There is no significant contamination from known foregrounds. The results show a discernible rise in the angular power spectrum from large (l~40) to small (l~200) angular scales. The shape of the observed power spectrum is not a simple linear rise, but has a sharply increasing slope starting at l~150.

  2. Data Reduction and Analysis of the Python V Cosmic Microwave Background Anisotropy Experiment

    NASA Astrophysics Data System (ADS)

    Coble, Kimberly Ann

    1999-11-01

    Observations of the microwave sky using the Python telescope in its fifth season of operation at the Amundsen-Scott South Pole Station in Antarctica are presented. The system consists of a 0.75 m off-axis telescope instrumented with a HEMT amplifier-based radiometer having continuum sensitivity from 37-45 GHz in two frequency bands. With a 0.91(°) × 1.02(°) beam the instrument fully sampled 598 deg(2) of sky, including fields measured during the previous four seasons of Python observations. Interpreting the observed fluctuations as anisotropy in the cosmic microwave background, we place constraints on the angular power spectrum of fluctuations in eight multipole bands up to l ˜ 260. The observed spectrum is consistent with both the COBE experiment and previous Python results. Total-power Wiener-filtered maps of the CMB are also presented. There is no significant contamination from known foregrounds. The results show a discernible rise in the angular power spectrum from large (l ˜ 40) to small (l ˜ 200) angular scales.

  3. ExoData: A Python package to handle large exoplanet catalogue data

    NASA Astrophysics Data System (ADS)

    Varley, Ryan

    2016-10-01

    Exoplanet science often involves using the system parameters of real exoplanets for tasks such as simulations, fitting routines, and target selection for proposals. Several exoplanet catalogues are already well established but often lack a version history and code friendly interfaces. Software that bridges the barrier between the catalogues and code enables users to improve the specific repeatability of results by facilitating the retrieval of exact system parameters used in articles results along with unifying the equations and software used. As exoplanet science moves towards large data, gone are the days where researchers can recall the current population from memory. An interface able to query the population now becomes invaluable for target selection and population analysis. ExoData is a Python interface and exploratory analysis tool for the Open Exoplanet Catalogue. It allows the loading of exoplanet systems into Python as objects (Planet, Star, Binary, etc.) from which common orbital and system equations can be calculated and measured parameters retrieved. This allows researchers to use tested code of the common equations they require (with units) and provides a large science input catalogue of planets for easy plotting and use in research. Advanced querying of targets is possible using the database and Python programming language. ExoData is also able to parse spectral types and fill in missing parameters according to programmable specifications and equations. Examples of use cases are integration of equations into data reduction pipelines, selecting planets for observing proposals and as an input catalogue to large scale simulation and analysis of planets.

  4. NEVESIM: event-driven neural simulation framework with a Python interface.

    PubMed

    Pecevski, Dejan; Kappel, David; Jonke, Zeno

    2014-01-01

    NEVESIM is a software package for event-driven simulation of networks of spiking neurons with a fast simulation core in C++, and a scripting user interface in the Python programming language. It supports simulation of heterogeneous networks with different types of neurons and synapses, and can be easily extended by the user with new neuron and synapse types. To enable heterogeneous networks and extensibility, NEVESIM is designed to decouple the simulation logic of communicating events (spikes) between the neurons at a network level from the implementation of the internal dynamics of individual neurons. In this paper we will present the simulation framework of NEVESIM, its concepts and features, as well as some aspects of the object-oriented design approaches and simulation strategies that were utilized to efficiently implement the concepts and functionalities of the framework. We will also give an overview of the Python user interface, its basic commands and constructs, and also discuss the benefits of integrating NEVESIM with Python. One of the valuable capabilities of the simulator is to simulate exactly and efficiently networks of stochastic spiking neurons from the recently developed theoretical framework of neural sampling. This functionality was implemented as an extension on top of the basic NEVESIM framework. Altogether, the intended purpose of the NEVESIM framework is to provide a basis for further extensions that support simulation of various neural network models incorporating different neuron and synapse types that can potentially also use different simulation strategies.

  5. pyNSMC: A Python Module for Null-Space Monte Carlo Uncertainty Analysis

    NASA Astrophysics Data System (ADS)

    White, J.; Brakefield, L. K.

    2015-12-01

    The null-space monte carlo technique is a non-linear uncertainty analyses technique that is well-suited to high-dimensional inverse problems. While the technique is powerful, the existing workflow for completing null-space monte carlo is cumbersome, requiring the use of multiple commandline utilities, several sets of intermediate files and even a text editor. pyNSMC is an open-source python module that automates the workflow of null-space monte carlo uncertainty analyses. The module is fully compatible with the PEST and PEST++ software suites and leverages existing functionality of pyEMU, a python framework for linear-based uncertainty analyses. pyNSMC greatly simplifies the existing workflow for null-space monte carlo by taking advantage of object oriented design facilities in python. The core of pyNSMC is the ensemble class, which draws and stores realized random vectors and also provides functionality for exporting and visualizing results. By relieving users of the tedium associated with file handling and command line utility execution, pyNSMC instead focuses the user on the important steps and assumptions of null-space monte carlo analysis. Furthermore, pyNSMC facilitates learning through flow charts and results visualization, which are available at many points in the algorithm. The ease-of-use of the pyNSMC workflow is compared to the existing workflow for null-space monte carlo for a synthetic groundwater model with hundreds of estimable parameters.

  6. Xray: N-dimensional, labeled arrays for analyzing physical datasets in Python

    NASA Astrophysics Data System (ADS)

    Hoyer, S.

    2015-12-01

    Efficient analysis of geophysical datasets requires tools that both preserve and utilize metadata, and that transparently scale to process large datas. Xray is such a tool, in the form of an open source Python library for analyzing the labeled, multi-dimensional array (tensor) datasets that are ubiquitous in the Earth sciences. Xray's approach pairs Python data structures based on the data model of the netCDF file format with the proven design and user interface of pandas, the popular Python data analysis library for labeled tabular data. On top of the NumPy array, xray adds labeled dimensions (e.g., "time") and coordinate values (e.g., "2015-04-10"), which it uses to enable a host of operations powered by these labels: selection, aggregation, alignment, broadcasting, split-apply-combine, interoperability with pandas and serialization to netCDF/HDF5. Many of these operations are enabled by xray's tight integration with pandas. Finally, to allow for easy parallelism and to enable its labeled data operations to scale to datasets that does not fit into memory, xray integrates with the parallel processing library dask.

  7. Food composition influences metabolism, heart rate and organ growth during digestion in Python regius.

    PubMed

    Henriksen, Poul Secher; Enok, Sanne; Overgaard, Johannes; Wang, Tobias

    2015-05-01

    Digestion in pythons is associated with a large increase in oxygen consumption (SDA), increased cardiac output and growth in visceral organs assisting in digestion. The processes leading to the large postprandial rise in metabolism in snakes is subject to opposing views. Gastric work, protein synthesis and organ growth have each been speculated to be major contributors to the SDA. To investigate the role of food composition on SDA, heart rate (HR) and organ growth, 48 ball pythons (Python regius) were fed meals of either fat, glucose, protein or protein combined with carbonate. Our study shows that protein, in the absence or presence of carbonate causes a large SDA response, while glucose caused a significantly smaller SDA response and digestion of fat failed to affect metabolism. Addition of carbonate to the diet to stimulate gastric acid secretion did not increase the SDA response. These results support protein synthesis as a major contributor to the SDA response and show that increased gastric acid secretion occurs at a low metabolic cost. The increase in metabolism was supported by tachycardia caused by altered autonomic regulation as well as an increased non-adrenergic, non-cholinergic (NANC) tone in response to all diets, except for the lipid meal. Organ growth only occurred in the small intestine and liver in snakes fed on a high protein diet.

  8. The microvasculature of python pit organs: morphology and blood flow microkinetics.

    PubMed

    Goris, Richard C; Atobe, Yoshitoshi; Nakano, Masato; Hisajima, Tatsuya; Funakoshi, Kengo; Kadota, Tetsuo

    2003-05-01

    Boid snakes have infrared sensing pits that resemble crotaline pits in electrophysiological function and ultrastructure, but differ in gross morphology, number, and location: boids have three or more simple pits in the labial scales vs a single facial pair with more complex morphology in the crotalines. We studied the morphology of the capillary bed and the microkinetics of blood flow in a boid snake, the ball python, Python regius, and compared them with the already known condition in crotalines. We used a Doppler blood flow recorder in conjunction with an electrocardiograph to measure blood flow and heartbeat, and resin casts, transmission electron microscopy, and laser confocal microscopy to study capillary morphology. Blood flow in response to infrared stimulus was virtually identical in the two taxa, but the morphology of the capillary bed differed drastically. In the ball python pits, the capillary bed consisted of a forest of vertically oriented loops with a characteristic dome at the top in contact with the receptor layer of the fundus. Immunohistochemical staining showed pericytes constricting the capillaries and domes with smooth muscle alpha-actin-labeled processes. Since latency of response was as short as 1 ms, the capillaries were apparently responding under local control to provide both nutrition and cooling to the heat-sensitive receptors. We concluded that mitochondria-filled receptors provided with a swiftly responding cooling system were nature's most efficient way of attaining infrared imaging.

  9. NEVESIM: event-driven neural simulation framework with a Python interface

    PubMed Central

    Pecevski, Dejan; Kappel, David; Jonke, Zeno

    2014-01-01

    NEVESIM is a software package for event-driven simulation of networks of spiking neurons with a fast simulation core in C++, and a scripting user interface in the Python programming language. It supports simulation of heterogeneous networks with different types of neurons and synapses, and can be easily extended by the user with new neuron and synapse types. To enable heterogeneous networks and extensibility, NEVESIM is designed to decouple the simulation logic of communicating events (spikes) between the neurons at a network level from the implementation of the internal dynamics of individual neurons. In this paper we will present the simulation framework of NEVESIM, its concepts and features, as well as some aspects of the object-oriented design approaches and simulation strategies that were utilized to efficiently implement the concepts and functionalities of the framework. We will also give an overview of the Python user interface, its basic commands and constructs, and also discuss the benefits of integrating NEVESIM with Python. One of the valuable capabilities of the simulator is to simulate exactly and efficiently networks of stochastic spiking neurons from the recently developed theoretical framework of neural sampling. This functionality was implemented as an extension on top of the basic NEVESIM framework. Altogether, the intended purpose of the NEVESIM framework is to provide a basis for further extensions that support simulation of various neural network models incorporating different neuron and synapse types that can potentially also use different simulation strategies. PMID:25177291

  10. Luminal and systemic signals trigger intestinal adaptation in the juvenile python.

    PubMed

    Secor, S M; Whang, E E; Lane, J S; Ashley, S W; Diamond, J

    2000-12-01

    Juvenile pythons undergo large rapid upregulation of intestinal mass and intestinal transporter activities upon feeding. Because it is also easy to do surgery on pythons and to maintain them in the laboratory, we used a python model to examine signals and agents for intestinal adaptation. We surgically isolated the middle third of the small intestine from enteric continuity, leaving its mesenteric nerve and vascular supply intact. Intestinal continuity was restored by an end-to-end anastomosis between the proximal and distal thirds. Within 24 h of the snake's feeding, the reanastomosed proximal and distal segments (receiving luminal nutrients) had upregulated amino acid and glucose uptakes by up to 15-fold, had doubled intestinal mass, and thereby soon achieved total nutrient uptake capacities equal to those of the normal fed full-length intestine. At this time, however, the isolated middle segment, receiving no luminal nutrients, experienced no changes from the fasted state in either nutrient uptakes or in morphology. By 3 days postfeeding, the isolated middle segment had upregulated nutrient uptakes to the same levels as the reanastomosed proximal and distal segments, but it still lacked any appreciable morphological response. These contrasting results for the reanastomosed intestine and for the isolated middle segment suggest that luminal nutrients and/or pancreatic biliary secretions are the agents triggering rapid upregulation of transporters and of intestinal mass and that systemic nerve or hormonal signals later trigger transporter regulation but no trophic response.

  11. Ursgal, Universal Python Module Combining Common Bottom-Up Proteomics Tools for Large-Scale Analysis.

    PubMed

    Kremer, Lukas P M; Leufken, Johannes; Oyunchimeg, Purevdulam; Schulze, Stefan; Fufezan, Christian

    2016-03-04

    Proteomics data integration has become a broad field with a variety of programs offering innovative algorithms to analyze increasing amounts of data. Unfortunately, this software diversity leads to many problems as soon as the data is analyzed using more than one algorithm for the same task. Although it was shown that the combination of multiple peptide identification algorithms yields more robust results, it is only recently that unified approaches are emerging; however, workflows that, for example, aim to optimize search parameters or that employ cascaded style searches can only be made accessible if data analysis becomes not only unified but also and most importantly scriptable. Here we introduce Ursgal, a Python interface to many commonly used bottom-up proteomics tools and to additional auxiliary programs. Complex workflows can thus be composed using the Python scripting language using a few lines of code. Ursgal is easily extensible, and we have made several database search engines (X!Tandem, OMSSA, MS-GF+, Myrimatch, MS Amanda), statistical postprocessing algorithms (qvality, Percolator), and one algorithm that combines statistically postprocessed outputs from multiple search engines ("combined FDR") accessible as an interface in Python. Furthermore, we have implemented a new algorithm ("combined PEP") that combines multiple search engines employing elements of "combined FDR", PeptideShaker, and Bayes' theorem.

  12. pyOpenMS: a Python-based interface to the OpenMS mass-spectrometry algorithm library.

    PubMed

    Röst, Hannes L; Schmitt, Uwe; Aebersold, Ruedi; Malmström, Lars

    2014-01-01

    pyOpenMS is an open-source, Python-based interface to the C++ OpenMS library, providing facile access to a feature-rich, open-source algorithm library for MS-based proteomics analysis. It contains Python bindings that allow raw access to the data structures and algorithms implemented in OpenMS, specifically those for file access (mzXML, mzML, TraML, mzIdentML among others), basic signal processing (smoothing, filtering, de-isotoping, and peak-picking) and complex data analysis (including label-free, SILAC, iTRAQ, and SWATH analysis tools). pyOpenMS thus allows fast prototyping and efficient workflow development in a fully interactive manner (using the interactive Python interpreter) and is also ideally suited for researchers not proficient in C++. In addition, our code to wrap a complex C++ library is completely open-source, allowing other projects to create similar bindings with ease. The pyOpenMS framework is freely available at https://pypi.python.org/pypi/pyopenms while the autowrap tool to create Cython code automatically is available at https://pypi.python.org/pypi/autowrap (both released under the 3-clause BSD licence).

  13. Embedded Analytical Solutions Improve Accuracy in Convolution-Based Particle Tracking Models using Python

    NASA Astrophysics Data System (ADS)

    Starn, J. J.

    2013-12-01

    Particle tracking often is used to generate particle-age distributions that are used as impulse-response functions in convolution. A typical application is to produce groundwater solute breakthrough curves (BTC) at endpoint receptors such as pumping wells or streams. The commonly used semi-analytical particle-tracking algorithm based on the assumption of linear velocity gradients between opposing cell faces is computationally very fast when used in combination with finite-difference models. However, large gradients near pumping wells in regional-scale groundwater-flow models often are not well represented because of cell-size limitations. This leads to inaccurate velocity fields, especially at weak sinks. Accurate analytical solutions for velocity near a pumping well are available, and various boundary conditions can be imposed using image-well theory. Python can be used to embed these solutions into existing semi-analytical particle-tracking codes, thereby maintaining the integrity and quality-assurance of the existing code. Python (and associated scientific computational packages NumPy, SciPy, and Matplotlib) is an effective tool because of its wide ranging capability. Python text processing allows complex and database-like manipulation of model input and output files, including binary and HDF5 files. High-level functions in the language include ODE solvers to solve first-order particle-location ODEs, Gaussian kernel density estimation to compute smooth particle-age distributions, and convolution. The highly vectorized nature of NumPy arrays and functions minimizes the need for computationally expensive loops. A modular Python code base has been developed to compute BTCs using embedded analytical solutions at pumping wells based on an existing well-documented finite-difference groundwater-flow simulation code (MODFLOW) and a semi-analytical particle-tracking code (MODPATH). The Python code base is tested by comparing BTCs with highly discretized synthetic steady

  14. AIMBAT: A Python/Matplotlib Tool for Measuring Teleseismic Arrival Times

    NASA Astrophysics Data System (ADS)

    Lou, X.; van der Lee, S.; Lloyd, S.

    2013-12-01

    Python is an open-source, platform-independent, and object-oriented scripting language. It became more popular in the seismologist community since the appearance of ObsPy (Beyreuther et al. 2010, Megies et al. 2011), which provides a powerful framework for seismic data access and processing. This study introduces a new Python-based tool named AIMBAT (Automated and Interactive Measurement of Body-wave Arrival Times) for measuring teleseismic body-wave arrival times on large-scale seismic event data (Lou et al. 2013). Compared to ObsPy, AIMBAT is a lighter tool that is more focused on a particular aspect of seismic data processing. It originates from the widely used MCCC (Multi-Channel Cross-Correlation) method developed by VanDecar and Crosson (1990). On top of the original MCCC procedure, AIMBAT is automated in initial phase picking and is interactive in quality control. The core cross-correlation function is implemented in Fortran to boost up performance in addition to Python. The GUI (graphical user interface) of AIMBAT depends on Matplotlib's GUI-neutral widgets and event-handling API. A number of sorting and (de)selecting options are designed to facilitate the quality control of seismograms. By using AIMBAT, both relative and absolute teleseismic body-wave arrival times are measured. AIMBAT significantly improves efficiency and quality of the measurements. User interaction is needed only to pick the target phase arrival and to set a time window on the array stack. The package is easy to install and use, open-source, and is publicly available. Graphical user interface of AIMBAT.

  15. SMMP v. 3.0—Simulating proteins and protein interactions in Python and Fortran

    NASA Astrophysics Data System (ADS)

    Meinke, Jan H.; Mohanty, Sandipan; Eisenmenger, Frank; Hansmann, Ulrich H. E.

    2008-03-01

    We describe a revised and updated version of the program package SMMP. SMMP is an open-source FORTRAN package for molecular simulation of proteins within the standard geometry model. It is designed as a simple and inexpensive tool for researchers and students to become familiar with protein simulation techniques. SMMP 3.0 sports a revised API increasing its flexibility, an implementation of the Lund force field, multi-molecule simulations, a parallel implementation of the energy function, Python bindings, and more. Program summaryTitle of program:SMMP Catalogue identifier:ADOJ_v3_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADOJ_v3_0.html Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Licensing provisions:Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html Programming language used:FORTRAN, Python No. of lines in distributed program, including test data, etc.:52 105 No. of bytes in distributed program, including test data, etc.:599 150 Distribution format:tar.gz Computer:Platform independent Operating system:OS independent RAM:2 Mbytes Classification:3 Does the new version supersede the previous version?:Yes Nature of problem:Molecular mechanics computations and Monte Carlo simulation of proteins. Solution method:Utilizes ECEPP2/3, FLEX, and Lund potentials. Includes Monte Carlo simulation algorithms for canonical, as well as for generalized ensembles. Reasons for new version:API changes and increased functionality. Summary of revisions:Added Lund potential; parameters used in subroutines are now passed as arguments; multi-molecule simulations; parallelized energy calculation for ECEPP; Python bindings. Restrictions:The consumed CPU time increases with the size of protein molecule. Running time:Depends on the size of the simulated molecule.

  16. Development of Conceptual Benchmark Models to Evaluate Complex Hydrologic Model Calibration in Managed Basins Using Python

    NASA Astrophysics Data System (ADS)

    Hughes, J. D.; White, J.

    2013-12-01

    For many numerical hydrologic models it is a challenge to quantitatively demonstrate that complex models are preferable to simpler models. Typically, a decision is made to develop and calibrate a complex model at the beginning of a study. The value of selecting a complex model over simpler models is commonly inferred from use of a model with fewer simplifications of the governing equations because it can be time consuming to develop another numerical code with data processing and parameter estimation functionality. High-level programming languages like Python can greatly reduce the effort required to develop and calibrate simple models that can be used to quantitatively demonstrate the increased value of a complex model. We have developed and calibrated a spatially-distributed surface-water/groundwater flow model for managed basins in southeast Florida, USA, to (1) evaluate the effect of municipal groundwater pumpage on surface-water/groundwater exchange, (2) investigate how the study area will respond to sea-level rise, and (3) explore combinations of these forcing functions. To demonstrate the increased value of this complex model, we developed a two-parameter conceptual-benchmark-discharge model for each basin in the study area. The conceptual-benchmark-discharge model includes seasonal scaling and lag parameters and is driven by basin rainfall. The conceptual-benchmark-discharge models were developed in the Python programming language and used weekly rainfall data. Calibration was implemented with the Broyden-Fletcher-Goldfarb-Shanno method available in the Scientific Python (SciPy) library. Normalized benchmark efficiencies calculated using output from the complex model and the corresponding conceptual-benchmark-discharge model indicate that the complex model has more explanatory power than the simple model driven only by rainfall.

  17. Functional morphology and patterns of blood flow in the heart of Python regius.

    PubMed

    Starck, J Matthias

    2009-06-01

    Brightness-modulated ultrasonography, continuous-wave Doppler, and pulsed-wave Doppler-echocardiography were used to analyze the functional morphology of the undisturbed heart of ball pythons. In particular, the action of the muscular ridge and the atrio-ventricular valves are key features to understand how patterns of blood flow emerge from structures directing blood into the various chambers of the heart. A step-by-step image analysis of echocardiographs shows that during ventricular diastole, the atrio-ventricular valves block the interventricular canals so that blood from the right atrium first fills the cavum venosum, and blood from the left atrium fills the cavum arteriosum. During diastole, blood from the cavum venosum crosses the muscular ridge into the cavum pulmonale. During middle to late systole the muscular ridge closes, thus prohibiting further blood flow into the cavum pulmonale. At the same time, the atrio-ventricular valves open the interventricular canal and allow blood from the cavum arteriosum to flow into the cavum venosum. In the late phase of ventricular systole, all blood from the cavum pulmonale is pressed into the pulmonary trunk; all blood from the cavum venosum is pressed into both aortas. Quantitative measures of blood flow volume showed that resting snakes bypass the pulmonary circulation and shunt about twice the blood volume into the systemic circulation as into the pulmonary circulation. When digesting, the oxygen demand of snakes increased tremendously. This is associated with shunting more blood into the pulmonary circulation. The results of this study allow the presentation of a detailed functional model of the python heart. They are also the basis for a functional hypothesis of how shunting is achieved. Further, it was shown that shunting is an active regulation process in response to changing demands of the organism (here, oxygen demand). Finally, the results of this study support earlier reports about a dual pressure

  18. PyCOOL — A Cosmological Object-Oriented Lattice code written in Python

    SciTech Connect

    Sainio, J.

    2012-04-01

    There are a number of different phenomena in the early universe that have to be studied numerically with lattice simulations. This paper presents a graphics processing unit (GPU) accelerated Python program called PyCOOL that solves the evolution of scalar fields in a lattice with very precise symplectic integrators. The program has been written with the intention to hit a sweet spot of speed, accuracy and user friendliness. This has been achieved by using the Python language with the PyCUDA interface to make a program that is easy to adapt to different scalar field models. In this paper we derive the symplectic dynamics that govern the evolution of the system and then present the implementation of the program in Python and PyCUDA. The functionality of the program is tested in a chaotic inflation preheating model, a single field oscillon case and in a supersymmetric curvaton model which leads to Q-ball production. We have also compared the performance of a consumer graphics card to a professional Tesla compute card in these simulations. We find that the program is not only accurate but also very fast. To further increase the usefulness of the program we have equipped it with numerous post-processing functions that provide useful information about the cosmological model. These include various spectra and statistics of the fields. The program can be additionally used to calculate the generated curvature perturbation. The program is publicly available under GNU General Public License at https://github.com/jtksai/PyCOOL. Some additional information can be found from http://www.physics.utu.fi/tiedostot/theory/particlecosmology/pycool/.

  19. Interfacing MATLAB and Python Optimizers to Black-Box Environmental Simulation Models

    NASA Astrophysics Data System (ADS)

    Matott, L. S.; Leung, K.; Tolson, B.

    2009-12-01

    A common approach for utilizing environmental models in a management or policy-analysis context is to incorporate them into a simulation-optimization framework - where an underlying process-based environmental model is linked with an optimization search algorithm. The optimization search algorithm iteratively adjusts various model inputs (i.e. parameters or design variables) in order to minimize an application-specific objective function computed on the basis of model outputs (i.e. response variables). Numerous optimization algorithms have been applied to the simulation-optimization of environmental systems and this research investigated the use of optimization libraries and toolboxes that are readily available in MATLAB and Python - two popular high-level programming languages. Inspired by model-independent calibration codes (e.g. PEST and UCODE), a small piece of interface software (known as PIGEON) was developed. PIGEON allows users to interface Python and MATLAB optimizers with arbitrary black-box environmental models without writing any additional interface code. An initial set of benchmark tests (involving more than 20 MATLAB and Python optimization algorithms) were performed to validate the interface software - results highlight the need to carefully consider such issues as numerical precision in output files and enforcement (or not) of parameter limits. Additional benchmark testing considered the problem of fitting isotherm expressions to laboratory data - with an emphasis on dual-mode expressions combining non-linear isotherms with a linear partitioning component. With respect to the selected isotherm fitting problems, derivative-free search algorithms significantly outperformed gradient-based algorithms. Attempts to improve gradient-based performance, via parameter tuning and also via several alternative multi-start approaches, were largely unsuccessful.

  20. PyR@TE 2: A Python tool for computing RGEs at two-loop

    NASA Astrophysics Data System (ADS)

    Lyonnet, F.; Schienbein, I.

    2017-04-01

    Renormalization group equations are an essential tool for the description of theories across different energy scales. Even though their expressions at two-loop for an arbitrary gauge field theory have been known for more than thirty years, deriving the full set of equations for a given model by hand is very challenging and prone to errors. To tackle this issue, we have introduced in Lyonnet et al. (2014) a Python tool called PyR@TE; Python Renormalization group equations @ Two-loop for Everyone. With PyR@TE, it is easy to implement a given Lagrangian and derive the complete set of two-loop RGEs for all the parameters of the theory. In this paper, we present the new version of this code, PyR@TE 2, which brings many new features and in particular it incorporates kinetic mixing when several U(1) gauge groups are involved. In addition, the group theory part has been greatly improved as we introduced a new Python module dubbed PyLie that deals with all the group theoretical aspects required for the calculation of the RGEs as well as providing very useful model building capabilities. This allows the use of any irreducible representation of the SU(n) , SO(2 n) and SO(2n + 1) groups. Furthermore, it is now possible to implement terms in the Lagrangian involving fields which can be contracted into gauge singlets in more than one way. As a byproduct, results for a popular model (SM + complex triplet) for which, to our knowledge, the complete set of two-loop RGEs has not been calculated before are presented in this paper. Finally, the two-loop RGEs for the anomalous dimension of the scalar and fermion fields have been implemented as well. It is now possible to export the coupled system of beta functions into a numerical C++ function, leading to a consequent speed up in solving them.

  1. ObsPy: A Python Toolbox for Seismology - Recent Developments and Applications

    NASA Astrophysics Data System (ADS)

    Megies, T.; Krischer, L.; Barsch, R.; Sales de Andrade, E.; Beyreuther, M.

    2014-12-01

    ObsPy (http://www.obspy.org) is a community-driven, open-source project dedicated to building a bridge for seismology into the scientific Python ecosystem. It offersa) read and write support for essentially all commonly used waveform, station, and event metadata file formats with a unified interface,b) a comprehensive signal processing toolbox tuned to the needs of seismologists,c) integrated access to all large data centers, web services and databases, andd) convenient wrappers to legacy codes like libtau and evalresp.Python, currently the most popular language for teaching introductory computer science courses at top-ranked U.S. departments, is a full-blown programming language with the flexibility of an interactive scripting language. Its extensive standard library and large variety of freely available high quality scientific modules cover most needs in developing scientific processing workflows. Together with packages like NumPy, SciPy, Matplotlib, IPython, Pandas, lxml, and PyQt, ObsPy enables the construction of complete workflows in Python. These vary from reading locally stored data or requesting data from one or more different data centers through to signal analysis and data processing and on to visualizations in GUI and web applications, output of modified/derived data and the creation of publication-quality figures.ObsPy enjoys a large world-wide rate of adoption in the community. Applications successfully using it include time-dependent and rotational seismology, big data processing, event relocations, and synthetic studies about attenuation kernels and full-waveform inversions to name a few examples. All functionality is extensively documented and the ObsPy tutorial and gallery give a good impression of the wide range of possible use cases.We will present the basic features of ObsPy, new developments and applications, and a roadmap for the near future and discuss the sustainability of our open-source development model.

  2. The Python pit organ: imaging and immunocytochemical analysis of an extremely sensitive natural infrared detector.

    PubMed

    Grace, M S; Church, D R; Kelly, C T; Lynn, W F; Cooper, T M

    1999-01-01

    The Python infrared-sensitive pit organ is a natural infrared imager that combines high sensitivity, ambient temperature function, microscopic dimensions, and self-repair. We are investigating the spectral sensitivity and signal transduction process in snake infrared-sensitive neurons, neither of which is understood. For example, it is unknown whether infrared receptor neurons function on a thermal or a photic mechanism. We imaged pit organs in living Python molurus and Python regius using infrared-sensitive digital video cameras. Pit organs were significantly more absorptive and/or emissive than surrounding tissues in both 3-5 microns and 8-12 microns wavelength ranges. Pit organs exhibited greater absorption/emissivity in the 8-12 microns range than in the 3-5 microns range. To directly test the relationship between photoreceptors and pit organ infrared-sensitive neurons, we performed immunocytochemistry using antisera directed against retinal photoreceptor opsins. Retinal photoreceptors were labeled with antisera specific for retinal opsins, but these antisera failed to label terminals of infrared-sensitive neurons in the pit organ. Infrared-receptive neurons were also distinguished from retinal photoreceptors on the basis of their calcium-binding protein content. These results indicate that the pit organ absorbs infrared radiation in two major atmospheric transmission windows, one of which (8-12 microns) matches emission of targeted prey, and that infrared receptors are biochemically distinct from retinal photoreceptors. These results also provide the first identification of prospective biochemical components of infrared signal transduction in pit organ receptor neurons.

  3. PySpike-A Python library for analyzing spike train synchrony

    NASA Astrophysics Data System (ADS)

    Mulansky, Mario; Kreuz, Thomas

    Understanding how the brain functions is one of the biggest challenges of our time. The analysis of experimentally recorded neural firing patterns (spike trains) plays a crucial role in addressing this problem. Here, the PySpike library is introduced, a Python package for spike train analysis providing parameter-free and time-scale independent measures of spike train synchrony. It allows to compute similarity and dissimilarity profiles, averaged values and distance matrices. Although mainly focusing on neuroscience, PySpike can also be applied in other contexts like climate research or social sciences. The package is available as Open Source on Github and PyPI.

  4. And now for something completely different: Inattentional blindness during a Monty Python's Flying Circus sketch

    PubMed Central

    Wiseman, Richard; Watt, Caroline

    2015-01-01

    Perceptual science has frequently benefited from studying illusions created outside of academia. Here, we describe a striking, but little-known, example of inattentional blindness from the British comedy series “Monty Python's Flying Circus.” Viewers fail to attend to several highly incongruous characters in the sketch, despite these characters being clearly visible onscreen. The sketch has the potential to be a valuable research and teaching resource, as well as providing a vivid illustration of how people often fail to see something completely different. PMID:26034570

  5. Powerlaw: a Python package for analysis of heavy-tailed distributions.

    PubMed

    Alstott, Jeff; Bullmore, Ed; Plenz, Dietmar

    2014-01-01

    Power laws are theoretically interesting probability distributions that are also frequently used to describe empirical data. In recent years, effective statistical methods for fitting power laws have been developed, but appropriate use of these techniques requires significant programming and statistical insight. In order to greatly decrease the barriers to using good statistical methods for fitting power law distributions, we developed the powerlaw Python package. This software package provides easy commands for basic fitting and statistical analysis of distributions. Notably, it also seeks to support a variety of user needs by being exhaustive in the options available to the user. The source code is publicly available and easily extensible.

  6. SpacePy: Python-Based Tools for the Space Science Community

    NASA Astrophysics Data System (ADS)

    Morley, Steve; Koller, Josef; Welling, Dan; Larsen, Brian; Niehof, Jon

    2014-01-01

    SpacePy provides data analysis and visualization tools for the space science community. Written in Python, it builds on the capabilities of the NumPy and MatPlotLib packages to make basic data analysis, modeling and visualization easier. It contains modules for handling many complex time formats, obtaining data from the OMNI database, and accessing the powerful Onera library. It contains a library of commonly used empirical relationships, performs association analysis, coordinate transformations, radiation belt modeling, and CDF reading, and creates publication quality plots.

  7. Instrumentino: An open-source modular Python framework for controlling Arduino based experimental instruments

    NASA Astrophysics Data System (ADS)

    Koenka, Israel Joel; Sáiz, Jorge; Hauser, Peter C.

    2014-10-01

    Instrumentino is an open-source modular graphical user interface framework for controlling Arduino based experimental instruments. It expands the control capability of Arduino by allowing instruments builders to easily create a custom user interface program running on an attached personal computer. It enables the definition of operation sequences and their automated running without user intervention. Acquired experimental data and a usage log are automatically saved on the computer for further processing. The use of the programming language Python also allows easy extension. Complex devices, which are difficult to control using an Arduino, may be integrated as well by incorporating third party application programming interfaces into the Instrumentino framework.

  8. Assocplots: a Python package for static and interactive visualization of multiple-group GWAS results.

    PubMed

    Khramtsova, Ekaterina A; Stranger, Barbara E

    2016-10-14

    Over the last decade, genome-wide association studies (GWAS) have generated vast amounts of analysis results, requiring development of novel tools for data visualization. Quantile-quantile (QQ) plots and Manhattan plots are classical tools which have been utilized to visually summarize GWAS results and identify genetic variants significantly associated with traits of interest. However, static visualizations are limiting in the information that can be shown. Here, we present ASSOCPLOTS: , a Python package for viewing and exploring GWAS results not only using classic static Manhattan and QQ plots, but also through a dynamic extension which allows to interactively visualize the relationships between GWAS results from multiple cohorts or studies.

  9. Note: Tormenta: An open source Python-powered control software for camera based optical microscopy

    NASA Astrophysics Data System (ADS)

    Barabas, Federico M.; Masullo, Luciano A.; Stefani, Fernando D.

    2016-12-01

    Until recently, PC control and synchronization of scientific instruments was only possible through closed-source expensive frameworks like National Instruments' LabVIEW. Nowadays, efficient cost-free alternatives are available in the context of a continuously growing community of open-source software developers. Here, we report on Tormenta, a modular open-source software for the control of camera-based optical microscopes. Tormenta is built on Python, works on multiple operating systems, and includes some key features for fluorescence nanoscopy based on single molecule localization.

  10. Note: Tormenta: An open source Python-powered control software for camera based optical microscopy.

    PubMed

    Barabas, Federico M; Masullo, Luciano A; Stefani, Fernando D

    2016-12-01

    Until recently, PC control and synchronization of scientific instruments was only possible through closed-source expensive frameworks like National Instruments' LabVIEW. Nowadays, efficient cost-free alternatives are available in the context of a continuously growing community of open-source software developers. Here, we report on Tormenta, a modular open-source software for the control of camera-based optical microscopes. Tormenta is built on Python, works on multiple operating systems, and includes some key features for fluorescence nanoscopy based on single molecule localization.

  11. PREdator: a python based GUI for data analysis, evaluation and fitting

    PubMed Central

    2014-01-01

    The analysis of a series of experimental data is an essential procedure in virtually every field of research. The information contained in the data is extracted by fitting the experimental data to a mathematical model. The type of the mathematical model (linear, exponential, logarithmic, etc.) reflects the physical laws that underlie the experimental data. Here, we aim to provide a readily accessible, user-friendly python script for data analysis, evaluation and fitting. PREdator is presented at the example of NMR paramagnetic relaxation enhancement analysis.

  12. i-PI: A Python interface for ab initio path integral molecular dynamics simulations

    NASA Astrophysics Data System (ADS)

    Ceriotti, Michele; More, Joshua; Manolopoulos, David E.

    2014-03-01

    Recent developments in path integral methodology have significantly reduced the computational expense of including quantum mechanical effects in the nuclear motion in ab initio molecular dynamics simulations. However, the implementation of these developments requires a considerable programming effort, which has hindered their adoption. Here we describe i-PI, an interface written in Python that has been designed to minimise the effort required to bring state-of-the-art path integral techniques to an electronic structure program. While it is best suited to first principles calculations and path integral molecular dynamics, i-PI can also be used to perform classical molecular dynamics simulations, and can just as easily be interfaced with an empirical forcefield code. To give just one example of the many potential applications of the interface, we use it in conjunction with the CP2K electronic structure package to showcase the importance of nuclear quantum effects in high-pressure water. Catalogue identifier: AERN_v1_0 Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AERN_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: GNU General Public License, version 3 No. of lines in distributed program, including test data, etc.: 138626 No. of bytes in distributed program, including test data, etc.: 3128618 Distribution format: tar.gz Programming language: Python. Computer: Multiple architectures. Operating system: Linux, Mac OSX, Windows. RAM: Less than 256 Mb Classification: 7.7. External routines: NumPy Nature of problem: Bringing the latest developments in the modelling of nuclear quantum effects with path integral molecular dynamics to ab initio electronic structure programs with minimal implementational effort. Solution method: State-of-the-art path integral molecular dynamics techniques are implemented in a Python interface. Any electronic structure code can be patched to receive the atomic

  13. QuTiP 2: A Python framework for the dynamics of open quantum systems

    NASA Astrophysics Data System (ADS)

    Johansson, J. R.; Nation, P. D.; Nori, Franco

    2013-04-01

    We present version 2 of QuTiP, the Quantum Toolbox in Python. Compared to the preceding version [J.R. Johansson, P.D. Nation, F. Nori, Comput. Phys. Commun. 183 (2012) 1760.], we have introduced numerous new features, enhanced performance, and made changes in the Application Programming Interface (API) for improved functionality and consistency within the package, as well as increased compatibility with existing conventions used in other scientific software packages for Python. The most significant new features include efficient solvers for arbitrary time-dependent Hamiltonians and collapse operators, support for the Floquet formalism, and new solvers for Bloch-Redfield and Floquet-Markov master equations. Here we introduce these new features, demonstrate their use, and give a summary of the important backward-incompatible API changes introduced in this version. Catalog identifier: AEMB_v2_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEMB_v2_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: GNU General Public License, version 3 No. of lines in distributed program, including test data, etc.: 33625 No. of bytes in distributed program, including test data, etc.: 410064 Distribution format: tar.gz Programming language: Python. Computer: i386, x86-64. Operating system: Linux, Mac OSX. RAM: 2+ Gigabytes Classification: 7. External routines: NumPy, SciPy, Matplotlib, Cython Catalog identifier of previous version: AEMB_v1_0 Journal reference of previous version: Comput. Phys. Comm. 183 (2012) 1760 Does the new version supercede the previous version?: Yes Nature of problem: Dynamics of open quantum systems Solution method: Numerical solutions to Lindblad, Floquet-Markov, and Bloch-Redfield master equations, as well as the Monte Carlo wave function method. Reasons for new version: Compared to the preceding version we have introduced numerous new features, enhanced performance, and made changes in

  14. powerlaw: A Python Package for Analysis of Heavy-Tailed Distributions

    PubMed Central

    Alstott, Jeff; Bullmore, Ed; Plenz, Dietmar

    2014-01-01

    Power laws are theoretically interesting probability distributions that are also frequently used to describe empirical data. In recent years, effective statistical methods for fitting power laws have been developed, but appropriate use of these techniques requires significant programming and statistical insight. In order to greatly decrease the barriers to using good statistical methods for fitting power law distributions, we developed the powerlaw Python package. This software package provides easy commands for basic fitting and statistical analysis of distributions. Notably, it also seeks to support a variety of user needs by being exhaustive in the options available to the user. The source code is publicly available and easily extensible. PMID:24489671

  15. PyXel: A Python Package for Astronomical X-ray Data Modeling

    NASA Astrophysics Data System (ADS)

    Ogrean, Georgiana

    2017-01-01

    PyXel is a open-source Python package for modeling astronomical X-ray imaging data. It is primarily built on NumPy, SciPy, Astropy, and emcee. The package aims to provide a common set of image analysis tools for astronomers working with extended X-ray sources. I will present an overview of its features, and analysis examples based on public Chandra data.The code is available for download on GitHub (https://github.com/gogrean/PyXel), and contributions to it are welcome.

  16. Digesting pythons quickly oxidize the proteins in their meals and save the lipids for later.

    PubMed

    McCue, Marshall D; Guzman, R Marena; Passement, Celeste A

    2015-07-01

    Pythons digesting rodent meals exhibit up to 10-fold increases in their resting metabolic rate (RMR); this increase in RMR is termed specific dynamic action (SDA). Studies have shown that SDA is partially fueled by oxidizing dietary nutrients, yet it remains unclear whether the proteins and the lipids in their meals contribute equally to this energy demand. We raised two populations of mice on diets labeled with either [(13)C]leucine or [(13)C]palmitic acid to intrinsically enrich the proteins and lipids in their bodies, respectively. Ball pythons (Python regius) were fed whole mice (and pureed mice 3 weeks later), after which we measured their metabolic rates and the δ(13)C in the breath. The δ(13)C values in the whole bodies of the protein- and lipid-labeled mice were generally similar (i.e. 5.7±4.7‰ and 2.8±5.4‰, respectively) but the oxidative kinetics of these two macronutrient pools were quite different. We found that the snakes oxidized 5% of the protein and only 0.24% of the lipids in their meals within 14 days. Oxidation of the dietary proteins peaked 24 h after ingestion, at which point these proteins provided ∼90% of the metabolic requirement of the snakes, and by 14 days the oxidation of these proteins decreased to nearly zero. The oxidation of the dietary lipids peaked 1 day later, at which point these lipids supplied ∼25% of the energy demand. Fourteen days after ingestion, these lipids were still being oxidized and continued to account for ∼25% of the metabolic rate. Pureeing the mice reduced the cost of gastric digestion and decreased SDA by 24%. Pureeing also reduced the oxidation of dietary proteins by 43%, but it had no effect on the rates of dietary lipid oxidation. Collectively, these results demonstrate that pythons are able to effectively partition the two primary metabolic fuels in their meals. This approach of uniquely labeling the different components of the diet will allow researchers to examine new questions about

  17. Py4CAtS - Python tools for line-by-line modelling of infrared atmospheric radiative transfer

    NASA Astrophysics Data System (ADS)

    Schreier, Franz; García, Sebastián Gimeno

    2013-05-01

    Py4CAtS — Python scripts for Computational ATmospheric Spectroscopy is a Python re-implementation of the Fortran infrared radiative transfer code GARLIC, where compute-intensive code sections utilize the Numeric/Scientific Python modules for highly optimized array-processing. The individual steps of an infrared or microwave radiative transfer computation are implemented in separate scripts to extract lines of relevant molecules in the spectral range of interest, to compute line-by-line cross sections for given pressure(s) and temperature(s), to combine cross sections to absorption coefficients and optical depths, and to integrate along the line-of-sight to transmission and radiance/intensity. The basic design of the package, numerical and computational aspects relevant for optimization, and a sketch of the typical workflow are presented.

  18. TelluSim: A Python Plug-in Based Computational Framework for Spatially Distributed Environmental and Earth Sciences Modelling

    NASA Astrophysics Data System (ADS)

    Willgoose, G. R.

    2008-12-01

    TelluSim is a python-based computational framework for integrating and manipulating modules written in a variety of computer languages. TelluSim consists of a main program that dynamically, at run time, assembles a series of modules. These modules can be written in any language that can be accessed by Python. Currently we have modules in Fortran and Python, with C to be supported soon. New modules are incorporated as plug-ins like done for a browser or Photoshop, simply by copying the module binary into a plug-in directory. TelluSim automatically generates a GUI for parameter and state I/O, and automatically creates the intermodule communication mechanisms needed for the computations. A decision to use Python was arrived at after detailed trials using other languages including C, Tcl/Tk and Fortran. An important aspect of the design of TelluSim was to minimise the overhead in interfacing the modules with TelluSim, and minimise any requirement for recoding of existing software, so eliminating a major disadvantage of more complex frameworks (e.g. JAMS, openMI). Several significant Fortran codes developed by the author have been incorporated as part of the design process and as proof of concept. In particular the SIBERIA landform evolution code (a high performance F90 code, including parallel capability) has been broken up into a series of TelluSim modules, so that the SIBERIA now consists of a Python script of 20 lines. These 20 lines assemble and run the underlying modules (about 50,000 lines of Fortran code). The presentation will discuss in more detail the design of TelluSim, and our experiences of the advantages and disadvantages of using Python relative to other approaches.

  19. cloudPEST - A python module for cloud-computing deployment of PEST, a program for parameter estimation

    USGS Publications Warehouse

    Fienen, Michael N.; Kunicki, Thomas C.; Kester, Daniel E.

    2011-01-01

    This report documents cloudPEST-a Python module with functions to facilitate deployment of the model-independent parameter estimation code PEST on a cloud-computing environment. cloudPEST makes use of low-level, freely available command-line tools that interface with the Amazon Elastic Compute Cloud (EC2(TradeMark)) that are unlikely to change dramatically. This report describes the preliminary setup for both Python and EC2 tools and subsequently describes the functions themselves. The code and guidelines have been tested primarily on the Windows(Registered) operating system but are extensible to Linux(Registered).

  20. Mocking the weak lensing universe: The LensTools Python computing package

    NASA Astrophysics Data System (ADS)

    Petri, A.

    2016-10-01

    We present a newly developed software package which implements a wide range of routines frequently used in Weak Gravitational Lensing (WL). With the continuously increasing size of the WL scientific community we feel that easy to use Application Program Interfaces (APIs) for common calculations are a necessity to ensure efficiency and coordination across different working groups. Coupled with existing open source codes, such as CAMB (Lewis et al., 2000) and Gadget2 (Springel, 2005), LensTools brings together a cosmic shear simulation pipeline which, complemented with a variety of WL feature measurement tools and parameter sampling routines, provides easy access to the numerics for theoretical studies of WL as well as for experiment forecasts. Being implemented in PYTHON (Rossum, 1995), LensTools takes full advantage of a range of state-of-the art techniques developed by the large and growing open-source software community (Jones et al., 2001; McKinney, 2010; Astrophy Collaboration, 2013; Pedregosa et al., 2011; Foreman-Mackey et al., 2013). We made the LensTools code available on the Python Package Index and published its documentation on http://lenstools.readthedocs.io.

  1. Jungle Giants: Assessing Sustainable Harvesting in a Difficult-to-Survey Species (Python reticulatus)

    PubMed Central

    Natusch, Daniel J. D.; Lyons, Jessica A.; Mumpuni; Riyanto, Awal; Shine, Richard

    2016-01-01

    Sustainability of wildlife harvests is critical but difficult to assess. Evaluations of sustainability typically combine modelling with the measurement of underlying abundances. For many taxa harvested in developing countries, however, abundances are near-impossible to survey and a lack of detailed ecological information impedes the reliability of models. In such cases, repeated surveys of the attributes of harvested individuals may provide more robust information on sustainability. If the numbers, sizes and other demographic attributes of animals taken for the commercial trade do not change over biologically significant time intervals (decades), there is a prima facie case that the harvest is indeed sustainable. Here, we report the results of examinations of > 4,200 reticulated pythons (Python reticulatus) taken for the commercial leather industry in northern and southern Sumatra, Indonesia. The numbers, mean body sizes, clutch sizes, sizes at maturity and proportion of giant specimens have not decreased between our first surveys (1995) and repeat surveys (2015). Thus, despite assumptions to the contrary, the harvest appears to be sustainable. We use our data to inform the design of future monitoring programs for this species. Our study underpins the need for robust science to inform wildlife trade policy and decision-making, and urges wildlife managers to assess sustainability of difficult-to-survey terrestrial wildlife by drawing inferences directly from the harvest itself. PMID:27391138

  2. Pyff – A Pythonic Framework for Feedback Applications and Stimulus Presentation in Neuroscience

    PubMed Central

    Venthur, Bastian; Scholler, Simon; Williamson, John; Dähne, Sven; Treder, Matthias S.; Kramarek, Maria T.; Müller, Klaus-Robert; Blankertz, Benjamin

    2010-01-01

    This paper introduces Pyff, the Pythonic feedback framework for feedback applications and stimulus presentation. Pyff provides a platform-independent framework that allows users to develop and run neuroscientific experiments in the programming language Python. Existing solutions have mostly been implemented in C++, which makes for a rather tedious programming task for non-computer-scientists, or in Matlab, which is not well suited for more advanced visual or auditory applications. Pyff was designed to make experimental paradigms (i.e., feedback and stimulus applications) easily programmable. It includes base classes for various types of common feedbacks and stimuli as well as useful libraries for external hardware such as eyetrackers. Pyff is also equipped with a steadily growing set of ready-to-use feedbacks and stimuli. It can be used as a standalone application, for instance providing stimulus presentation in psychophysics experiments, or within a closed loop such as in biofeedback or brain–computer interfacing experiments. Pyff communicates with other systems via a standardized communication protocol and is therefore suitable to be used with any system that may be adapted to send its data in the specified format. Having such a general, open-source framework will help foster a fruitful exchange of experimental paradigms between research groups. In particular, it will decrease the need of reprogramming standard paradigms, ease the reproducibility of published results, and naturally entail some standardization of stimulus presentation. PMID:21160550

  3. Optimizing physical parameters in 1-D particle-in-cell simulations with Python

    NASA Astrophysics Data System (ADS)

    Ragan-Kelley, Benjamin; Verboncoeur, John P.; Lin, Ming-Chieh

    2014-10-01

    A particle-in-cell (PIC) simulation tool, OOPD1, is wrapped in the Python programming language, enabling automated algorithmic optimization of physical and numerical parameters. The Python-based environment exposes internal variables, enabling modification of simulation parameters, as well as run-time generation of new diagnostics based on calculations with internal data. For problems requiring an iterative optimization approach, this enables a programmable interactive feedback loop style simulation model, where the input to one simulation is a programmable function of the output of the previous one. This approach is applied to field-emission of electrons in a diode, in order to explore space charge effects in bipolar flow. We find an analytical solution for maximizing the space-charge limited current through a diode with an upstream ion current, and confirm the result with simulations, demonstrating the efficacy of the feedback scheme. We also demonstrate and analyze a modeling approach for scaling the ion mass, which can shorten simulation time without changing the ultimate result. The methods presented can be generalized to handle other applications where it is desirable to evolve simulation parameters based on algorithmic results from the simulation, including models in which physical or numerical parameter tuning is used to converge or optimize a system in one or more variables.

  4. Cygrid: A fast Cython-powered convolution-based gridding module for Python

    NASA Astrophysics Data System (ADS)

    Winkel, B.; Lenz, D.; Flöer, L.

    2016-06-01

    Context. Data gridding is a common task in astronomy and many other science disciplines. It refers to the resampling of irregularly sampled data to a regular grid. Aims: We present cygrid, a library module for the general purpose programming language Python. Cygrid can be used to resample data to any collection of target coordinates, although its typical application involves FITS maps or data cubes. The FITS world coordinate system standard is supported. Methods: The regridding algorithm is based on the convolution of the original samples with a kernel of arbitrary shape. We introduce a lookup table scheme that allows us to parallelize the gridding and combine it with the HEALPix tessellation of the sphere for fast neighbor searches. Results: We show that for n input data points, cygrids runtime scales between O(n) and O(nlog n) and analyze the performance gain that is achieved using multiple CPU cores. We also compare the gridding speed with other techniques, such as nearest-neighbor, and linear and cubic spline interpolation. Conclusions: Cygrid is a very fast and versatile gridding library that significantly outperforms other third-party Python modules, such as the linear and cubic spline interpolation provided by SciPy. http://https://github.com/bwinkel/cygrid

  5. Automatic Parallelization of Numerical Python Applications using the Global Arrays Toolkit

    SciTech Connect

    Daily, Jeffrey A.; Lewis, Robert R.

    2011-11-30

    Global Arrays is a software system from Pacific Northwest National Laboratory that enables an efficient, portable, and parallel shared-memory programming interface to manipulate distributed dense arrays. The NumPy module is the de facto standard for numerical calculation in the Python programming language, a language whose use is growing rapidly in the scientific and engineering communities. NumPy provides a powerful N-dimensional array class as well as other scientific computing capabilities. However, like the majority of the core Python modules, NumPy is inherently serial. Using a combination of Global Arrays and NumPy, we have reimplemented NumPy as a distributed drop-in replacement called Global Arrays in NumPy (GAiN). Serial NumPy applications can become parallel, scalable GAiN applications with only minor source code changes. Scalability studies of several different GAiN applications will be presented showing the utility of developing serial NumPy codes which can later run on more capable clusters or supercomputers.

  6. How the python heart separates pulmonary and systemic blood pressures and blood flows.

    PubMed

    Jensen, Bjarke; Nielsen, Jan M; Axelsson, Michael; Pedersen, Michael; Löfman, Carl; Wang, Tobias

    2010-05-01

    The multiple convergent evolution of high systemic blood pressure among terrestrial vertebrates has always been accompanied by lowered pulmonary pressure. In mammals, birds and crocodilians, this cardiac separation of pressures relies on the complete division of the right and left ventricles by a complete ventricular septum. However, the anatomy of the ventricle of most reptiles does not allow for complete anatomical division, but the hearts of pythons and varanid lizards can produce high systemic blood pressure while keeping the pulmonary blood pressure low. It is also known that these two groups of reptiles are characterised by low magnitudes of cardiac shunts. Little, however, is known about the mechanisms that allow for this pressure separation. Here we provide a description of cardiac structures and intracardiac events that have been revealed by ultrasonic measurements and angioscopy. Echocardiography revealed that the atrioventricular valves descend deep into the ventricle during ventricular filling and thereby greatly reduce the communication between the systemic (cavum arteriosum) and pulmonary (cavum pulmonale) ventricular chambers during diastole. Angioscopy and echocardiography showed how the two incomplete septa, the muscular ridge and the bulbuslamelle - ventricular structures common to all squamates - contract against each other in systole and provide functional division of the anatomically subdivided ventricle. Washout shunts are inevitable in the subdivided snake ventricle, but we show that the site of shunting, the cavum venosum, is very small throughout the cardiac cycle. It is concluded that the python ventricle is incapable of the pronounced and variable shunts of other snakes, because of its architecture and valvular mechanics.

  7. PylotDB - A Database Management, Graphing, and Analysis Tool Written in Python

    SciTech Connect

    Barnette, Daniel W.

    2012-01-04

    PylotDB, written completely in Python, provides a user interface (UI) with which to interact with, analyze, graph data from, and manage open source databases such as MySQL. The UI mitigates the user having to know in-depth knowledge of the database application programming interface (API). PylotDB allows the user to generate various kinds of plots from user-selected data; generate statistical information on text as well as numerical fields; backup and restore databases; compare database tables across different databases as well as across different servers; extract information from any field to create new fields; generate, edit, and delete databases, tables, and fields; generate or read into a table CSV data; and similar operations. Since much of the database information is brought under control of the Python computer language, PylotDB is not intended for huge databases for which MySQL and Oracle, for example, are better suited. PylotDB is better suited for smaller databases that might be typically needed in a small research group situation. PylotDB can also be used as a learning tool for database applications in general.

  8. Complete mitochondrial genome sequence from an endangered Indian snake, Python molurus molurus (Serpentes, Pythonidae).

    PubMed

    Dubey, Bhawna; Meganathan, P R; Haque, Ikramul

    2012-07-01

    This paper reports the complete mitochondrial genome sequence of an endangered Indian snake, Python molurus molurus (Indian Rock Python). A typical snake mitochondrial (mt) genome of 17258 bp length comprising of 37 genes including the 13 protein coding genes, 22 tRNA genes, and 2 ribosomal RNA genes along with duplicate control regions is described herein. The P. molurus molurus mt. genome is relatively similar to other snake mt. genomes with respect to gene arrangement, composition, tRNA structures and skews of AT/GC bases. The nucleotide composition of the genome shows that there are more A-C % than T-G% on the positive strand as revealed by positive AT and CG skews. Comparison of individual protein coding genes, with other snake genomes suggests that ATP8 and NADH3 genes have high divergence rates. Codon usage analysis reveals a preference of NNC codons over NNG codons in the mt. genome of P. molurus. Also, the synonymous and non-synonymous substitution rates (ka/ks) suggest that most of the protein coding genes are under purifying selection pressure. The phylogenetic analyses involving the concatenated 13 protein coding genes of P. molurus molurus conformed to the previously established snake phylogeny.

  9. A multi-model Python wrapper for operational oil spill transport forecasts

    NASA Astrophysics Data System (ADS)

    Hou, X.; Hodges, B. R.; Negusse, S.; Barker, C.

    2015-01-01

    The Hydrodynamic and oil spill modeling system for Python (HyosPy) is presented as an example of a multi-model wrapper that ties together existing models, web access to forecast data and visualization techniques as part of an adaptable operational forecast system. The system is designed to automatically run a continual sequence of hindcast/forecast hydrodynamic models so that multiple predictions of the time-and-space-varying velocity fields are already available when a spill is reported. Once the user provides the estimated spill parameters, the system runs multiple oil spill prediction models using the output from the hydrodynamic models. As new wind and tide data become available, they are downloaded from the web, used as forcing conditions for a new instance of the hydrodynamic model and then applied to a new instance of the oil spill model. The predicted spill trajectories from multiple oil spill models are visualized through Python methods invoking Google MapTM and Google EarthTM functions. HyosPy is designed in modules that allow easy future adaptation to new models, new data sources or new visualization tools.

  10. Nmrglue: an open source Python package for the analysis of multidimensional NMR data.

    PubMed

    Helmus, Jonathan J; Jaroniec, Christopher P

    2013-04-01

    Nmrglue, an open source Python package for working with multidimensional NMR data, is described. When used in combination with other Python scientific libraries, nmrglue provides a highly flexible and robust environment for spectral processing, analysis and visualization and includes a number of common utilities such as linear prediction, peak picking and lineshape fitting. The package also enables existing NMR software programs to be readily tied together, currently facilitating the reading, writing and conversion of data stored in Bruker, Agilent/Varian, NMRPipe, Sparky, SIMPSON, and Rowland NMR Toolkit file formats. In addition to standard applications, the versatility offered by nmrglue makes the package particularly suitable for tasks that include manipulating raw spectrometer data files, automated quantitative analysis of multidimensional NMR spectra with irregular lineshapes such as those frequently encountered in the context of biomacromolecular solid-state NMR, and rapid implementation and development of unconventional data processing methods such as covariance NMR and other non-Fourier approaches. Detailed documentation, install files and source code for nmrglue are freely available at http://nmrglue.com. The source code can be redistributed and modified under the New BSD license.

  11. PyMVPA: A python toolbox for multivariate pattern analysis of fMRI data.

    PubMed

    Hanke, Michael; Halchenko, Yaroslav O; Sederberg, Per B; Hanson, Stephen José; Haxby, James V; Pollmann, Stefan

    2009-01-01

    Decoding patterns of neural activity onto cognitive states is one of the central goals of functional brain imaging. Standard univariate fMRI analysis methods, which correlate cognitive and perceptual function with the blood oxygenation-level dependent (BOLD) signal, have proven successful in identifying anatomical regions based on signal increases during cognitive and perceptual tasks. Recently, researchers have begun to explore new multivariate techniques that have proven to be more flexible, more reliable, and more sensitive than standard univariate analysis. Drawing on the field of statistical learning theory, these new classifier-based analysis techniques possess explanatory power that could provide new insights into the functional properties of the brain. However, unlike the wealth of software packages for univariate analyses, there are few packages that facilitate multivariate pattern classification analyses of fMRI data. Here we introduce a Python-based, cross-platform, and open-source software toolbox, called PyMVPA, for the application of classifier-based analysis techniques to fMRI datasets. PyMVPA makes use of Python's ability to access libraries written in a large variety of programming languages and computing environments to interface with the wealth of existing machine learning packages. We present the framework in this paper and provide illustrative examples on its usage, features, and programmability.

  12. Nmrglue: An Open Source Python Package for the Analysis of Multidimensional NMR Data

    PubMed Central

    Helmus, Jonathan J.; Jaroniec, Christopher P.

    2013-01-01

    Nmrglue, an open source Python package for working with multidimensional NMR data, is described. When used in combination with other Python scientific libraries, nmrglue provides a highly flexible and robust environment for spectral processing, analysis and visualization and includes a number of common utilities such as linear prediction, peak picking and lineshape fitting. The package also enables existing NMR software programs to be readily tied together, currently facilitating the reading, writing and conversion of data stored in Bruker, Agilent/Varian, NMRPipe, Sparky, SIMPSON, and Rowland NMR Toolkit file formats. In addition to standard applications, the versatility offered by nmrglue makes the package particularly suitable for tasks that include manipulating raw spectrometer data files, automated quantitative analysis of multidimensional NMR spectra with irregular lineshapes such as those frequently encountered in the context of biomacromolecular solid-state NMR, and rapid implementation and development of unconventional data processing methods such as covariance NMR and other non-Fourier approaches. Detailed documentation, install files and source code for nmrglue are freely available at http://nmrglue.com. The source code can be redistributed and modified under the New BSD license. PMID:23456039

  13. Neuroimaging, Genetics, and Clinical Data Sharing in Python Using the CubicWeb Framework

    PubMed Central

    Grigis, Antoine; Goyard, David; Cherbonnier, Robin; Gareau, Thomas; Papadopoulos Orfanos, Dimitri; Chauvat, Nicolas; Di Mascio, Adrien; Schumann, Gunter; Spooren, Will; Murphy, Declan; Frouin, Vincent

    2017-01-01

    In neurosciences or psychiatry, the emergence of large multi-center population imaging studies raises numerous technological challenges. From distributed data collection, across different institutions and countries, to final data publication service, one must handle the massive, heterogeneous, and complex data from genetics, imaging, demographics, or clinical scores. These data must be both efficiently obtained and downloadable. We present a Python solution, based on the CubicWeb open-source semantic framework, aimed at building population imaging study repositories. In addition, we focus on the tools developed around this framework to overcome the challenges associated with data sharing and collaborative requirements. We describe a set of three highly adaptive web services that transform the CubicWeb framework into a (1) multi-center upload platform, (2) collaborative quality assessment platform, and (3) publication platform endowed with massive-download capabilities. Two major European projects, IMAGEN and EU-AIMS, are currently supported by the described framework. We also present a Python package that enables end users to remotely query neuroimaging, genetics, and clinical data from scripts. PMID:28360851

  14. Jungle Giants: Assessing Sustainable Harvesting in a Difficult-to-Survey Species (Python reticulatus).

    PubMed

    Natusch, Daniel J D; Lyons, Jessica A; Mumpuni; Riyanto, Awal; Shine, Richard

    2016-01-01

    Sustainability of wildlife harvests is critical but difficult to assess. Evaluations of sustainability typically combine modelling with the measurement of underlying abundances. For many taxa harvested in developing countries, however, abundances are near-impossible to survey and a lack of detailed ecological information impedes the reliability of models. In such cases, repeated surveys of the attributes of harvested individuals may provide more robust information on sustainability. If the numbers, sizes and other demographic attributes of animals taken for the commercial trade do not change over biologically significant time intervals (decades), there is a prima facie case that the harvest is indeed sustainable. Here, we report the results of examinations of > 4,200 reticulated pythons (Python reticulatus) taken for the commercial leather industry in northern and southern Sumatra, Indonesia. The numbers, mean body sizes, clutch sizes, sizes at maturity and proportion of giant specimens have not decreased between our first surveys (1995) and repeat surveys (2015). Thus, despite assumptions to the contrary, the harvest appears to be sustainable. We use our data to inform the design of future monitoring programs for this species. Our study underpins the need for robust science to inform wildlife trade policy and decision-making, and urges wildlife managers to assess sustainability of difficult-to-survey terrestrial wildlife by drawing inferences directly from the harvest itself.

  15. Streamlining an IRAF data reduction process Pythonically with Astropy and NDMapper

    NASA Astrophysics Data System (ADS)

    Turner, James

    2016-03-01

    In the course of re-writing my typical top-level GMOS-IFU data reduction sequence in Python for a research project, I have developed a small module that helps express the scientific process in a relatively intuitive way as a Pythonic series of operations on NDData collections, mapped to files, with existing IRAF steps integrated almost seamlessly (pending their eventual replacement). For scientific end-user purposes, this experiment aims to obviate a need for pipeline machinery, favouring simple control flow in the main script and retaining a smooth transition from high-level process description to lower-level libraries by encapsulating necessary bookeeping within the data representation and simple wrappers. The I/O abstraction should make support for file formats other than FITS (eg. ASDF) straightforward to add. This work-in-progress can be found at https://github.com/jehturner/ndmapper and I intend to split its functionality involving IRAF or instrument processing into a separate "ndprocess" module as the prototype nears completion, leaving a core "ndmapper" package, without any special dependencies, as a general add-on for nddata.

  16. A parallelized Python based Multi-Point Thomson Scattering analysis in NSTX-U

    NASA Astrophysics Data System (ADS)

    Miller, Jared; Diallo, Ahmed; Leblanc, Benoit

    2014-10-01

    Multi-Point Thomson Scattering (MPTS) is a reliable and accurate method of finding the temperature, density, and pressure of a magnetically confined plasma. Nd:YAG (1064 nm) lasers are fired into the plasma with a frequency of 60 Hz, and the light is Doppler shifted by Thomson scattering. Polychromators on the midplane of the tokamak pick up the light at various radii/scattering angles, and the avalanche photodiode's voltages are added to an MDSplus tree for later analysis. This project ports and optimizes the prior serial IDL MPTS code into a well-documented Python package that runs in parallel. Since there are 30 polychromators in the current NSTX setup (12 more will be added when NSTX-U is completed), using parallelism offers vast savings in performance. NumPy and SciPy further accelerate numerical calculations and matrix operations, Matplotlib and PyQt make an intuitive GUI with plots of the output, and Multiprocessing parallelizes the computationally intensive calculations. The Python package was designed with portability and flexibility in mind so it can be adapted for use in any polychromator-based MPTS system.

  17. Species identification of protected carpet pythons suitable for degraded forensic samples.

    PubMed

    Ciavaglia, Sherryn; Donnellan, Stephen; Henry, Julianne; Linacre, Adrian

    2014-09-01

    In this paper we report on the identification of a section of mitochondrial DNA that can be used to identify the species of protected and illegally traded pythons of the genus Morelia. Successful enforcement of wildlife laws requires forensic tests that can identify the species nominated in the relevant legislation. The potentially degraded state of evidentiary samples requires that forensic investigation using molecular genetic species identification is optimized to interrogate small fragments of DNA. DNA was isolated from 35 samples of Morelia spilota from which the complete cytochrome b was sequenced. The ND6 gene was also sequenced in 32 of these samples. Additional DNA sequences were generated from 9 additional species of Morelia. The sequences were aligned by Geneious and imported into MEGA to create phylogenetic trees based on the entire complex of approximately 1,706 base pairs (bp). To mimic degraded DNA, which is usually found in forensic cases, short sub-sections of the full alignment were used to generate phylogenetic trees. The sub-sections that had the greatest DNA sequence information were in parts of the cytochrome b gene. Our results highlight that legislation is presently informed by inadequate taxonomy. We demonstrated that a 278 bp region of the cytochrome b gene recovered the topology of the phylogenetic tree found with the entire gene sequence and correctly identified species of Morelia with a high degree of confidence. The locus described in this report will assist in the successful prosecution of alleged illegal trade in python species.

  18. Maternal brooding in the children's python (Antaresia childreni) promotes egg water balance.

    PubMed

    Lourdais, Olivier; Hoffman, Ty C M; Denardo, Dale F

    2007-07-01

    Parental care provides considerable benefits to offspring and is widespread among animals, yet it is relatively uncommon among squamate reptiles (e.g., lizards and snakes). However, all pythonine snakes show extended maternal egg brooding with some species being facultatively endothermic. While facultative endothermy provides thermal benefits, the presence of brooding in non-endothermic species suggests other potential benefits of brooding. In this study we experimentally tested the functional significance of maternal brooding relative to water balance in the children's python, Antaresia childreni, a small species that does not exhibit facultative endothermy. Clutch evaporative water loss (EWL) was positively correlated with clutch mass and was much lower than expected values based on individual eggs. The conglomerate clutch behaved as a single unit with a decreasing surface area to volume ratio as clutch size increased. Maternal brooding had a dramatic impact on evaporation from eggs, reducing and possibly eliminating clutch EWL. In a separate experiment, we found that viability of unattended eggs is highly affected by humidity level, even in the narrow range from 75 to 100% relative humidity at 30.5 degrees C (20-33 mg m(-3 )absolute humidity). However, the presence of the brooding female ameliorated this sensitivity, as viability of brooded clutches at 75% relative humidity was higher than that of non-brooded eggs at either the same absolute humidity or at near-saturated conditions. Overall, these results demonstrate that brooding behavior strongly promotes egg water balance (and thus egg viability) in children's pythons.

  19. Effects of temperature on the metabolic response to feeding in Python molurus.

    PubMed

    Wang, Tobias; Zaar, Morten; Arvedsen, Sine; Vedel-Smith, Christina; Overgaard, Johannes

    2002-11-01

    As ectothermic vertebrates, reptiles undergo diurnal and seasonal changes in body temperature, which affect many biological functions. In conjunction with a general review regarding the effects of temperature on digestion in reptiles, we describe the effects of various temperatures (20-35 degrees C) on the metabolic response to digestion in the Burmese python (Python molurus). The snakes were fed mice amounting to 20% of their body weight and gas exchange (oxygen uptake and CO(2) production) were measured until digestion had ended and gas exchange returned to fasting levels. Elevated temperature was associated with a faster and larger metabolic increase after ingestion, and the time required to return to fasting levels was markedly longer at low temperature. The factorial increase between fasting oxygen consumption (VO(2)) and maximal VO(2) during digestion was, however, similar at all temperatures studied. Furthermore, the integrated SDA response was not affected by temperature suggesting the costs associated with digestion are temperature-independent. Other studies on reptiles show that digestive efficiency is only marginally affected by temperature and we conclude that selection of higher body temperatures during digestion (postprandial thermophilic response) primarily reduces the time required for digestion.

  20. The Profile Envision and Splicing Tool (PRESTO): Developing an Atmospheric Wind Analysis Tool for Space Launch Vehicles Using Python

    NASA Technical Reports Server (NTRS)

    Orcutt, John M.; Barbre, Robert E., Jr.; Brenton, James C.; Decker, Ryan K.

    2017-01-01

    Launch vehicle programs require vertically complete atmospheric profiles. Many systems at the ER to make the necessary measurements, but all have different EVR, vertical coverage, and temporal coverage. MSFC Natural Environments Branch developed a tool to create a vertically complete profile from multiple inputs using Python. Forward work: Finish Formal Testing Acceptance Testing, End-to-End Testing. Formal Release

  1. Whole transcriptome analysis of the fasting and fed Burmese python heart: insights into extreme physiological cardiac adaptation.

    PubMed

    Wall, Christopher E; Cozza, Steven; Riquelme, Cecilia A; McCombie, W Richard; Heimiller, Joseph K; Marr, Thomas G; Leinwand, Leslie A

    2011-01-01

    The infrequently feeding Burmese python (Python molurus) experiences significant and rapid postprandial cardiac hypertrophy followed by regression as digestion is completed. To begin to explore the molecular mechanisms of this response, we have sequenced and assembled the fasted and postfed Burmese python heart transcriptomes with Illumina technology using the chicken (Gallus gallus) genome as a reference. In addition, we have used RNA-seq analysis to identify differences in the expression of biological processes and signaling pathways between fasted, 1 day postfed (DPF), and 3 DPF hearts. Out of a combined transcriptome of ∼2,800 mRNAs, 464 genes were differentially expressed. Genes showing differential expression at 1 DPF compared with fasted were enriched for biological processes involved in metabolism and energetics, while genes showing differential expression at 3 DPF compared with fasted were enriched for processes involved in biogenesis, structural remodeling, and organization. Moreover, we present evidence for the activation of physiological and not pathological signaling pathways in this rapid, novel model of cardiac growth in pythons. Together, our data provide the first comprehensive gene expression profile for a reptile heart.

  2. Rapid Microsatellite Marker Development Using Next Generation Pyrosequencing to Inform Invasive Burmese Python—Python molurus bivittatus—Management

    PubMed Central

    Hunter, Margaret E.; Hart, Kristen M.

    2013-01-01

    Invasive species represent an increasing threat to native ecosystems, harming indigenous taxa through predation, habitat modification, cross-species hybridization and alteration of ecosystem processes. Additionally, high economic costs are associated with environmental damage, restoration and control measures. The Burmese python, Python molurus bivittatus, is one of the most notable invasive species in the US, due to the threat it poses to imperiled species and the Greater Everglades ecosystem. To address population structure and relatedness, next generation sequencing was used to rapidly produce species-specific microsatellite loci. The Roche 454 GS-FLX Titanium platform provided 6616 di-, tri- and tetra-nucleotide repeats in 117,516 sequences. Using stringent criteria, 24 of 26 selected tri- and tetra-nucleotide loci were polymerase chain reaction (PCR) amplified and 18 were polymorphic. An additional six cross-species loci were amplified, and the resulting 24 loci were incorporated into eight PCR multiplexes. Multi-locus genotypes yielded an average of 61% (39%–77%) heterozygosity and 3.7 (2–6) alleles per locus. Population-level studies using the developed microsatellites will track the invasion front and monitor population-suppression dynamics. Additionally, cross-species amplification was detected in the invasive Ball, P. regius, and Northern African python, P. sebae. These markers can be used to address the hybridization potential of Burmese pythons and the larger, more aggressive P. sebae. PMID:23449030

  3. Escript: Open Source Environment For Solving Large-Scale Geophysical Joint Inversion Problems in Python

    NASA Astrophysics Data System (ADS)

    Gross, Lutz; Altinay, Cihan; Fenwick, Joel; Smith, Troy

    2014-05-01

    The program package escript has been designed for solving mathematical modeling problems using python, see Gross et al. (2013). Its development and maintenance has been funded by the Australian Commonwealth to provide open source software infrastructure for the Australian Earth Science community (recent funding by the Australian Geophysical Observing System EIF (AGOS) and the AuScope Collaborative Research Infrastructure Scheme (CRIS)). The key concepts of escript are based on the terminology of spatial functions and partial differential equations (PDEs) - an approach providing abstraction from the underlying spatial discretization method (i.e. the finite element method (FEM)). This feature presents a programming environment to the user which is easy to use even for complex models. Due to the fact that implementations are independent from data structures simulations are easily portable across desktop computers and scalable compute clusters without modifications to the program code. escript has been successfully applied in a variety of applications including modeling mantel convection, melting processes, volcanic flow, earthquakes, faulting, multi-phase flow, block caving and mineralization (see Poulet et al. 2013). The recent escript release (see Gross et al. (2013)) provides an open framework for solving joint inversion problems for geophysical data sets (potential field, seismic and electro-magnetic). The strategy bases on the idea to formulate the inversion problem as an optimization problem with PDE constraints where the cost function is defined by the data defect and the regularization term for the rock properties, see Gross & Kemp (2013). This approach of first-optimize-then-discretize avoids the assemblage of the - in general- dense sensitivity matrix as used in conventional approaches where discrete programming techniques are applied to the discretized problem (first-discretize-then-optimize). In this paper we will discuss the mathematical framework for

  4. SpacePy - a Python-based library of tools for the space sciences

    SciTech Connect

    Morley, Steven K; Welling, Daniel T; Koller, Josef; Larsen, Brian A; Henderson, Michael G

    2010-01-01

    Space science deals with the bodies within the solar system and the interplanetary medium; the primary focus is on atmospheres and above - at Earth the short timescale variation in the the geomagnetic field, the Van Allen radiation belts and the deposition of energy into the upper atmosphere are key areas of investigation. SpacePy is a package for Python, targeted at the space sciences, that aims to make basic data analysis, modeling and visualization easier. It builds on the capabilities of the well-known NumPy and MatPlotLib packages. Publication quality output direct from analyses is emphasized. The SpacePy project seeks to promote accurate and open research standards by providing an open environment for code development. In the space physics community there has long been a significant reliance on proprietary languages that restrict free transfer of data and reproducibility of results. By providing a comprehensive, open-source library of widely used analysis and visualization tools in a free, modern and intuitive language, we hope that this reliance will be diminished. SpacePy includes implementations of widely used empirical models, statistical techniques used frequently in space science (e.g. superposed epoch analysis), and interfaces to advanced tools such as electron drift shell calculations for radiation belt studies. SpacePy also provides analysis and visualization tools for components of the Space Weather Modeling Framework - currently this only includes the BATS-R-US 3-D magnetohydrodynamic model and the RAM ring current model - including streamline tracing in vector fields. Further development is currently underway. External libraries, which include well-known magnetic field models, high-precision time conversions and coordinate transformations are wrapped for access from Python using SWIG and f2py. The rest of the tools have been implemented directly in Python. The provision of open-source tools to perform common tasks will provide openness in the

  5. A Pure-Python Robust Frequency Band Automatic Phase Picker for Seismic Monitoring

    NASA Astrophysics Data System (ADS)

    Chen, C.; Holland, A. A.

    2013-12-01

    We modify the FPPICK algorithm of Lomax et al. (2012) and implement an automatic phase picking algorithm implemented in Python. The algorithm takes advantage of existing seismological Python libraries, Obspy. The algorithm is designed to work on a variety of instrumentation and automatically adapts to different sampling rates. The time series signals are band-pass filtered for each band, octave, considered within the picker algorithm. The energy of the signal is calculated over an averaging window and multiplied by the instantaneous energy of the signal. This energy time-series is the statistic we can then examine for each frequency band considered. The summary statistic, which allows the identification of a trigger, is simply the maximum value of any frequency bands energy statistic at each sample time. A trigger is identified by using a control chart type statistic to identify when our statistics summary is changing rapidly and exceeds a specified number of standard deviations from the mean of the summary energy statistic. This has the advantage that the picker parameters don't necessarily need to be modified when processing data from a wide variety of instrumentation with different response characteristics. The algorithm also contains a method to determine the first motion direction associated with a pick as well as an uncertainty for the pick. As with any automatic phase identification system false picks can and do occur. A few simple algorithms are implemented to avoid false-picks, the picker can be configured not to include these checks. These algorithms remove picks that occur very close in time, and picks for which a phase has a smaller RMS than the previous time interval. The algorithm uses many techniques within Numpy to improve computation times. The algorithm effectively picks both P- and S-phase from local and regional earthquakes with only small amounts of picker parameter modifications. The picker can pick both P and S phases on local and regional

  6. Data Provenance as a Tool for Debugging Hydrological Models based on Python

    NASA Astrophysics Data System (ADS)

    Wombacher, A.; Huq, M.; Wada, Y.; Van Beek, R.

    2012-12-01

    There is an increase in data volume used in hydrological modeling. The increasing data volume requires additional efforts in debugging models since a single output value is influenced by a multitude of input values. Thus, it is difficult to keep an overview among the data dependencies. Further, knowing these dependencies, it is a tedious job to infer all the relevant data values. The aforementioned data dependencies are also known as data provenance, i.e. the determination of how a particular value has been created and processed. The proposed tool infers the data provenance automatically from a python script and visualizes the dependencies as a graph without executing the script. To debug the model the user specifies the value of interest in space and time. The tool infers all related data values and displays them in the graph. The tool has been evaluated by hydrologists developing a model for estimating the global water demand [1]. The model uses multiple different data sources. The script we analysed has 120 lines of codes and used more than 3000 individual files, each of them representing a raster map of 360*720 cells. After importing the data of the files into a SQLite database, the data consumes around 40 GB of memory. Using the proposed tool a modeler is able to select individual values and infer which values have been used to calculate the value. Especially in cases of outliers or missing values it is a beneficial tool to provide the modeler with efficient information to investigate the unexpected behavior of the model. The proposed tool can be applied to many python scripts and has been tested with other scripts in different contexts. In case a python code contains an unknown function or class the tool requests additional information about the used function or class to enable the inference. This information has to be entered only once and can be shared with colleagues or in the community. Reference [1] Y. Wada, L. P. H. van Beek, D. Viviroli, H. H. Drr, R

  7. Effect of water deprivation on baseline and stress-induced corticosterone levels in the Children's python (Antaresia childreni).

    PubMed

    Dupoué, Andréaz; Angelier, Frédéric; Lourdais, Olivier; Bonnet, Xavier; Brischoux, François

    2014-02-01

    Corticosterone (CORT) secretion is influenced by endogenous factors (e.g., physiological status) and environmental stressors (e.g., ambient temperature). Heretofore, the impact of water deprivation on CORT plasma levels has not been thoroughly investigated. However, both baseline CORT and stress-induced CORT are expected to respond to water deprivation not only because of hydric stress per se, but also because CORT is an important mineralocorticoid in vertebrates. We assessed the effects of water deprivation on baseline CORT and stress-induced CORT, in Children's pythons (Antaresia childreni), a species that experiences seasonal droughts in natural conditions. We imposed a 52-day water deprivation on a group of unfed Children's pythons (i.e., water-deprived treatment) and provided water ad libitum to another group (i.e., control treatment). We examined body mass variations throughout the experiment, and baseline CORT and stress-induced CORT at the end of the treatments. Relative body mass loss averaged ~10% in pythons without water, a value 2 to 4 times higher compared to control snakes. Following re-exposition to water, pythons from the water-deprived treatment drank readily and abundantly and attained a body mass similar to pythons from the control treatment. Together, these results suggest a substantial dehydration as a consequence of water deprivation. Interestingly, stress-induced but not baseline CORT level was significantly higher in water-deprived snakes, suggesting that baseline CORT might not respond to this degree of dehydration. Therefore, possible mineralocorticoid role of CORT needs to be clarified in snakes. Because dehydration usually induces adjustments (reduced movements, lowered body temperature) to limit water loss, and decreases locomotor performances, elevated stress-induced CORT in water-deprived snakes might therefore compensate for altered locomotor performances. Future studies should test this hypothesis.

  8. libNeuroML and PyLEMS: using Python to combine procedural and declarative modeling approaches in computational neuroscience.

    PubMed

    Vella, Michael; Cannon, Robert C; Crook, Sharon; Davison, Andrew P; Ganapathy, Gautham; Robinson, Hugh P C; Silver, R Angus; Gleeson, Padraig

    2014-01-01

    NeuroML is an XML-based model description language, which provides a powerful common data format for defining and exchanging models of neurons and neuronal networks. In the latest version of NeuroML, the structure and behavior of ion channel, synapse, cell, and network model descriptions are based on underlying definitions provided in LEMS, a domain-independent language for expressing hierarchical mathematical models of physical entities. While declarative approaches for describing models have led to greater exchange of model elements among software tools in computational neuroscience, a frequent criticism of XML-based languages is that they are difficult to work with directly. Here we describe two Application Programming Interfaces (APIs) written in Python (http://www.python.org), which simplify the process of developing and modifying models expressed in NeuroML and LEMS. The libNeuroML API provides a Python object model with a direct mapping to all NeuroML concepts defined by the NeuroML Schema, which facilitates reading and writing the XML equivalents. In addition, it offers a memory-efficient, array-based internal representation, which is useful for handling large-scale connectomics data. The libNeuroML API also includes support for performing common operations that are required when working with NeuroML documents. Access to the LEMS data model is provided by the PyLEMS API, which provides a Python implementation of the LEMS language, including the ability to simulate most models expressed in LEMS. Together, libNeuroML and PyLEMS provide a comprehensive solution for interacting with NeuroML models in a Python environment.

  9. libNeuroML and PyLEMS: using Python to combine procedural and declarative modeling approaches in computational neuroscience

    PubMed Central

    Vella, Michael; Cannon, Robert C.; Crook, Sharon; Davison, Andrew P.; Ganapathy, Gautham; Robinson, Hugh P. C.; Silver, R. Angus; Gleeson, Padraig

    2014-01-01

    NeuroML is an XML-based model description language, which provides a powerful common data format for defining and exchanging models of neurons and neuronal networks. In the latest version of NeuroML, the structure and behavior of ion channel, synapse, cell, and network model descriptions are based on underlying definitions provided in LEMS, a domain-independent language for expressing hierarchical mathematical models of physical entities. While declarative approaches for describing models have led to greater exchange of model elements among software tools in computational neuroscience, a frequent criticism of XML-based languages is that they are difficult to work with directly. Here we describe two Application Programming Interfaces (APIs) written in Python (http://www.python.org), which simplify the process of developing and modifying models expressed in NeuroML and LEMS. The libNeuroML API provides a Python object model with a direct mapping to all NeuroML concepts defined by the NeuroML Schema, which facilitates reading and writing the XML equivalents. In addition, it offers a memory-efficient, array-based internal representation, which is useful for handling large-scale connectomics data. The libNeuroML API also includes support for performing common operations that are required when working with NeuroML documents. Access to the LEMS data model is provided by the PyLEMS API, which provides a Python implementation of the LEMS language, including the ability to simulate most models expressed in LEMS. Together, libNeuroML and PyLEMS provide a comprehensive solution for interacting with NeuroML models in a Python environment. PMID:24795618

  10. NuPyCEE: NuGrid Python Chemical Evolution Environment

    NASA Astrophysics Data System (ADS)

    Ritter, Christian; Côté, Benoit

    2016-10-01

    The NuGrid Python Chemical Evolution Environment (NuPyCEE) simulates the chemical enrichment and stellar feedback of stellar populations. It contains three modules. The Stellar Yields for Galactic Modeling Applications module (SYGMA) models the enrichment and feedback of simple stellar populations which can be included in hydrodynamic simulations and semi-analytic models of galaxies. It is the basic building block of the One-zone Model for the Evolution of GAlaxies (OMEGA) module which allows the modelling of the chemical evolution of galaxies such as the Milky Way and its dwarf satellites. The STELLAB (STELLar ABundances) module provides a library of observed stellar abundances useful for comparing predictions of SYGMA and OMEGA.

  11. psst: An Open-Source Power System Simulation Toolbox in Python

    SciTech Connect

    Krishnamurthy, Dheepak

    2016-11-21

    This paper is an overview of Power System Simulation Toolbox (psst). psst is an open-source Python application for the simulation and analysis of power system models. psst simulates the wholesale market operation by solving a DC Optimal Power Flow (DCOPF), Security Constrained Unit Commitment (SCUC) and a Security Constrained Economic Dispatch (SCED). psst also includes models for the various entities in a power system such as Generator Companies (GenCos), Load Serving Entities (LSEs) and an Independent System Operator (ISO). psst features an open modular object oriented architecture that will make it useful for researchers to customize, expand, experiment beyond solving traditional problems. psst also includes a web based Graphical User Interface (GUI) that allows for user friendly interaction and for implementation on remote High Performance Computing (HPCs) clusters for parallelized operations. This paper also provides an illustrative application of psst and benchmarks with standard IEEE test cases to show the advanced features and the performance of toolbox.

  12. An Open-Source Automated Peptide Synthesizer Based on Arduino and Python.

    PubMed

    Gali, Hariprasad

    2017-01-01

    The development of the first open-source automated peptide synthesizer, PepSy, using Arduino UNO and readily available components is reported. PepSy was primarily designed to synthesize small peptides in a relatively small scale (<100 µmol). Scripts to operate PepSy in a fully automatic or manual mode were written in Python. Fully automatic script includes functions to carry out resin swelling, resin washing, single coupling, double coupling, Fmoc deprotection, ivDde deprotection, on-resin oxidation, end capping, and amino acid/reagent line cleaning. Several small peptides and peptide conjugates were successfully synthesized on PepSy with reasonably good yields and purity depending on the complexity of the peptide.

  13. Integrating computation and visualization for biomolecular analysis: an example using python and AVS.

    PubMed

    Sanner, M F; Duncan, B S; Carrillo, C J; Olson, A J

    1999-01-01

    One of the challenges in biocomputing is to enable the efficient use of a wide variety of fast-evolving computational methods to simulate, analyze, and understand the complex properties and interactions of molecular systems. Our laboratory investigates several areas including molecular visualization, protein-ligand docking, protein-protein docking, molecular surfaces, and the derivation of phenomenological potentials. In this paper we present an approach based on the Python programming language to achieve a high level of integration between these different computational methods and our primary visualization system AVS. This approach removes many limitations of AVS while increasing dramatically the inter-operability of our computational tools. Several examples are shown to illustrate how this approach enables a high level of integration and inter-operability between different tools, while retaining modularity and avoiding the creation of a large monolithic package that is difficult to extend and maintain.

  14. uPy: a ubiquitous CG Python API with biological-modeling applications.

    PubMed

    Autin, Ludovic; Johnson, Graham; Hake, Johan; Olson, Arthur; Sanner, Michel

    2012-01-01

    The uPy Python extension module provides a uniform abstraction of the APIs of several 3D computer graphics programs (called hosts), including Blender, Maya, Cinema 4D, and DejaVu. A plug-in written with uPy can run in all uPy-supported hosts. Using uPy, researchers have created complex plug-ins for molecular and cellular modeling and visualization. uPy can simplify programming for many types of projects (not solely science applications) intended for multihost distribution. It's available at http://upy.scripps.edu. The first featured Web extra is a video that shows interactive analysis of a calcium dynamics simulation. YouTube URL: http://youtu.be/wvs-nWE6ypo. The second featured Web extra is a video that shows rotation of the HIV virus. YouTube URL: http://youtu.be/vEOybMaRoKc.

  15. Pyrcca: Regularized Kernel Canonical Correlation Analysis in Python and Its Applications to Neuroimaging

    PubMed Central

    Bilenko, Natalia Y.; Gallant, Jack L.

    2016-01-01

    In this article we introduce Pyrcca, an open-source Python package for performing canonical correlation analysis (CCA). CCA is a multivariate analysis method for identifying relationships between sets of variables. Pyrcca supports CCA with or without regularization, and with or without linear, polynomial, or Gaussian kernelization. We first use an abstract example to describe Pyrcca functionality. We then demonstrate how Pyrcca can be used to analyze neuroimaging data. Specifically, we use Pyrcca to implement cross-subject comparison in a natural movie functional magnetic resonance imaging (fMRI) experiment by finding a data-driven set of functional response patterns that are similar across individuals. We validate this cross-subject comparison method in Pyrcca by predicting responses to novel natural movies across subjects. Finally, we show how Pyrcca can reveal retinotopic organization in brain responses to natural movies without the need for an explicit model. PMID:27920675

  16. TEMPy: a Python library for assessment of three-dimensional electron microscopy density fits

    PubMed Central

    Farabella, Irene; Vasishtan, Daven; Joseph, Agnel Praveen; Pandurangan, Arun Prasad; Sahota, Harpal; Topf, Maya

    2015-01-01

    Three-dimensional electron microscopy is currently one of the most promising techniques used to study macromolecular assemblies. Rigid and flexible fitting of atomic models into density maps is often essential to gain further insights into the assemblies they represent. Currently, tools that facilitate the assessment of fitted atomic models and maps are needed. TEMPy (template and electron microscopy comparison using Python) is a toolkit designed for this purpose. The library includes a set of methods to assess density fits in intermediate-to-low resolution maps, both globally and locally. It also provides procedures for single-fit assessment, ensemble generation of fits, clustering, and multiple and consensus scoring, as well as plots and output files for visualization purposes to help the user in analysing rigid and flexible fits. The modular nature of TEMPy helps the integration of scoring and assessment of fits into large pipelines, making it a tool suitable for both novice and expert structural biologists. PMID:26306092

  17. Python based integration of GEM detector electronics with JET data acquisition system

    NASA Astrophysics Data System (ADS)

    Zabołotny, Wojciech M.; Byszuk, Adrian; Chernyshova, Maryna; Cieszewski, Radosław; Czarski, Tomasz; Dalley, Simon; Hogben, Colin; Jakubowska, Katarzyna L.; Kasprowicz, Grzegorz; Poźniak, Krzysztof; Rzadkiewicz, Jacek; Scholz, Marek; Shumack, Amy

    2014-11-01

    This paper presents the system integrating the dedicated measurement and control electronic systems for Gas Electron Multiplier (GEM) detectors with the Control and Data Acquisition system (CODAS) in the JET facility in Culham, England. The presented system performs the high level procedures necessary to calibrate the GEM detector and to protect it against possible malfunctions or dangerous changes in operating conditions. The system also allows control of the GEM detectors from CODAS, setting of their parameters, checking their state, starting the plasma measurement and to reading the results. The system has been implemented using the Python language, using the advanced libraries for implementation of network communication protocols, for object based hardware management and for data processing.

  18. Soapy: an adaptive optics simulation written purely in Python for rapid concept development

    NASA Astrophysics Data System (ADS)

    Reeves, Andrew

    2016-07-01

    Soapy is a newly developed Adaptive Optics (AO) simulation which aims be a flexible and fast to use tool-kit for many applications in the field of AO. It is written purely in the Python language, adding to and taking advantage of the already rich ecosystem of scientific libraries and programs. The simulation has been designed to be extremely modular, such that each component can be used stand-alone for projects which do not require a full end-to-end simulation. Ease of use, modularity and code clarity have been prioritised at the expense of computational performance. Though this means the code is not yet suitable for large studies of Extremely Large Telescope AO systems, it is well suited to education, exploration of new AO concepts and investigations of current generation telescopes.

  19. FragBuilder: an efficient Python library to setup quantum chemistry calculations on peptides models.

    PubMed

    Christensen, Anders S; Hamelryck, Thomas; Jensen, Jan H

    2014-01-01

    We present a powerful Python library to quickly and efficiently generate realistic peptide model structures. The library makes it possible to quickly set up quantum mechanical calculations on model peptide structures. It is possible to manually specify a specific conformation of the peptide. Additionally the library also offers sampling of backbone conformations and side chain rotamer conformations from continuous distributions. The generated peptides can then be geometry optimized by the MMFF94 molecular mechanics force field via convenient functions inside the library. Finally, it is possible to output the resulting structures directly to files in a variety of useful formats, such as XYZ or PDB formats, or directly as input files for a quantum chemistry program. FragBuilder is freely available at https://github.com/jensengroup/fragbuilder/ under the terms of the BSD open source license.

  20. The adaptive significance of ontogenetic colour change in a tropical python.

    PubMed

    Wilson, David; Heinsohn, Robert; Endler, John A

    2007-02-22

    Ontogenetic colour change is typically associated with changes in size, vulnerability or habitat, but assessment of its functional significance requires quantification of the colour signals from the receivers' perspective. The tropical python, Morelia viridis, is an ideal species to establish the functional significance of ontogenetic colour change. Neonates hatch either yellow or red and both the morphs change to green with age. Here, we show that colour change from red or yellow to green provides camouflage from visually oriented avian predators in the different habitats used by juveniles and adults. This reflects changes in foraging behaviour and vulnerability as individuals mature and provides a rare demonstration of the adaptive value of ontogenetic colour change.

  1. ObsPy: A Python toolbox for seismology - Current state, applications, and ecosystem around it

    NASA Astrophysics Data System (ADS)

    Krischer, L.; Megies, T.; Sales de Andrade, E.; Barsch, R.; Beyreuther, M.

    2015-12-01

    ObsPy (http://www.obspy.org) is a community-driven, open-source project offering a bridge for seismology into the scientific Python ecosystem. It provides read and write support for essentially all commonly used waveform, station, and event metadata formats with a unified interface, a comprehensive signal processing toolbox tuned to the needs of seismologists, integrated access to all large data centers, web services and databases, and convenient wrappers to third party codes like libmseed and evalresp. Python, in contrast to many other languages and tools, is simple enough to enable an exploratory and interactive coding style desired by many scientists. At the same time it is a full-fledged programming language usable by software engineers to build complex and large programs. This combination makes it very suitable for use in seismology where research code often has to be translated to stable and production ready environments. It furthermore offers many freely available high quality scientific modules covering most needs in developing scientific software.ObsPy has been in constant development for more than 5 years and nowadays enjoys a large rate of adoption in the community with thousands of users. Successful applications include time-dependent and rotational seismology, big data processing, event relocations, and synthetic studies about attenuation kernels and full-waveform inversions to name a few examples. Additionally it sparked the development of several more specialized packages slowly building a modern seismological ecosystem around it.This contribution will give a short introduction and overview of ObsPy and highlight a number of us cases and software built around it. We will furthermore discuss the issue of sustainability of scientific software.

  2. PySP : modeling and solving stochastic mixed-integer programs in Python.

    SciTech Connect

    Woodruff, David L.; Watson, Jean-Paul

    2010-08-01

    Although stochastic programming is a powerful tool for modeling decision-making under uncertainty, various impediments have historically prevented its widespread use. One key factor involves the ability of non-specialists to easily express stochastic programming problems as extensions of deterministic models, which are often formulated first. A second key factor relates to the difficulty of solving stochastic programming models, particularly the general mixed-integer, multi-stage case. Intricate, configurable, and parallel decomposition strategies are frequently required to achieve tractable run-times. We simultaneously address both of these factors in our PySP software package, which is part of the COIN-OR Coopr open-source Python project for optimization. To formulate a stochastic program in PySP, the user specifies both the deterministic base model and the scenario tree with associated uncertain parameters in the Pyomo open-source algebraic modeling language. Given these two models, PySP provides two paths for solution of the corresponding stochastic program. The first alternative involves writing the extensive form and invoking a standard deterministic (mixed-integer) solver. For more complex stochastic programs, we provide an implementation of Rockafellar and Wets Progressive Hedging algorithm. Our particular focus is on the use of Progressive Hedging as an effective heuristic for approximating general multi-stage, mixed-integer stochastic programs. By leveraging the combination of a high-level programming language (Python) and the embedding of the base deterministic model in that language (Pyomo), we are able to provide completely generic and highly configurable solver implementations. PySP has been used by a number of research groups, including our own, to rapidly prototype and solve difficult stochastic programming problems.

  3. Heavy Analysis and Light Virtualization of Water Use Data with Python

    NASA Astrophysics Data System (ADS)

    Kim, H.; Bijoor, N.; Famiglietti, J. S.

    2014-12-01

    Water utilities possess a large amount of water data that could be used to inform urban ecohydrology, management decisions, and conservation policies, but such data are rarely analyzed owing to difficulty in analyzation, visualization, and interpretion. We have developed a high performance computing resource for this purpose. We partnered with 6 water agencies in Orange County who provided 10 years of parcel-level monthly water use billing data for a pilot study. The first challenge that we overcame was to refine all human errors and unify the many different formats of data over all agencies. Second, we tested and applied experimental approaches to the data, including complex calculations, with high efficiency. Third, we developed a method to refine the data so it can be browsed along a time series index and/or geo-spatial queries with high efficiency, no matter how large the data. Python scientific libraries were the best match to handle arbitrary data sets in our environment. Further milestones include agency entry, sets of formulae, and maintaining 15M rows X 70 columns of data with high performance of cpu-bound processes. To deal with billions of rows, we performed an analysis virtualization stack by leveraging iPython parallel computing. With this architecture, one agency could be considered one computing node or virtual machine that maintains its own data sets respectively. For example, a big agency could use a large node, and a small agency could use a micro node. Under the minimum required raw data specs, more agencies could be analyzed. The program developed in this study simplifies data analysis, visualization, and interpretation of large water datasets, and can be used to analyze large data volumes from water agencies nationally or worldwide.

  4. ObsPy: A Python toolbox for seismology - Current state, applications, and ecosystem around it

    NASA Astrophysics Data System (ADS)

    Lecocq, Thomas; Megies, Tobias; Krischer, Lion; Sales de Andrade, Elliott; Barsch, Robert; Beyreuther, Moritz

    2016-04-01

    ObsPy (http://www.obspy.org) is a community-driven, open-source project offering a bridge for seismology into the scientific Python ecosystem. It provides * read and write support for essentially all commonly used waveform, station, and event metadata formats with a unified interface, * a comprehensive signal processing toolbox tuned to the needs of seismologists, * integrated access to all large data centers, web services and databases, and * convenient wrappers to third party codes like libmseed and evalresp. Python, in contrast to many other languages and tools, is simple enough to enable an exploratory and interactive coding style desired by many scientists. At the same time it is a full-fledged programming language usable by software engineers to build complex and large programs. This combination makes it very suitable for use in seismology where research code often has to be translated to stable and production ready environments. It furthermore offers many freely available high quality scientific modules covering most needs in developing scientific software. ObsPy has been in constant development for more than 5 years and nowadays enjoys a large rate of adoption in the community with thousands of users. Successful applications include time-dependent and rotational seismology, big data processing, event relocations, and synthetic studies about attenuation kernels and full-waveform inversions to name a few examples. Additionally it sparked the development of several more specialized packages slowly building a modern seismological ecosystem around it. This contribution will give a short introduction and overview of ObsPy and highlight a number of use cases and software built around it. We will furthermore discuss the issue of sustainability of scientific software.

  5. HydroUnits: A Python-based Physical Units Management Tool in Hydrologic Computing Systems

    NASA Astrophysics Data System (ADS)

    Celicourt, P.; Piasecki, M.

    2015-12-01

    While one objective of data management systems is to provide the units when annotating the collected data, another is that the units must be correctly manipulated during conversion steps. This is not a trivial task however and the units conversion time and errors for large datasets can be quite expensive. To date, more than a dozen Python modules have been developed to deal with units attached to quantities. However, they fall short in many ways and also suffer from not integrating with a units controlled vocabulary. Moreover, none of them permits the encoding of some complex units defined in the Consortium of Universities for the Advancement of Hydrologic Sciences, Inc.'s Observations Data Model (CUAHSI ODM) as a vectorial representation for storage demand reduction and does not incorporate provision to accommodate unforeseen standards-based units. We developed HydroUnits, a Python-based units management tool for three specific purposes: encoding of physical units in the Transducer Electronic Data Sheet (TEDS) as defined in the IEEE 1451.0 standard, performing dimensional analysis and on-the-fly conversion of time series allowing users to retrieve data from a data source in a desired equivalent unit while accommodating unforeseen and user-defined units. HydroUnits differentiates itself to existing tools by a number of factors including the implementation approach adopted, the adoption of standard-based units naming conventions and more importantly the emphasis on units controlled vocabularies which are a critical aspect of units treatment. Additionally, HydroUnits supports unit conversion for quantities with additive scaling factor, and natively supports time series conversion and takes leap years into consideration for units consisting of the time dimension (e.g., month, minute). Due to its overall implementation approach, HydroUnits exhibits a high level of versatility that no other tool we are aware of has achieved.

  6. An Introduction to Programming for Bioscientists: A Python-Based Primer

    PubMed Central

    Mura, Cameron

    2016-01-01

    Computing has revolutionized the biological sciences over the past several decades, such that virtually all contemporary research in molecular biology, biochemistry, and other biosciences utilizes computer programs. The computational advances have come on many fronts, spurred by fundamental developments in hardware, software, and algorithms. These advances have influenced, and even engendered, a phenomenal array of bioscience fields, including molecular evolution and bioinformatics; genome-, proteome-, transcriptome- and metabolome-wide experimental studies; structural genomics; and atomistic simulations of cellular-scale molecular assemblies as large as ribosomes and intact viruses. In short, much of post-genomic biology is increasingly becoming a form of computational biology. The ability to design and write computer programs is among the most indispensable skills that a modern researcher can cultivate. Python has become a popular programming language in the biosciences, largely because (i) its straightforward semantics and clean syntax make it a readily accessible first language; (ii) it is expressive and well-suited to object-oriented programming, as well as other modern paradigms; and (iii) the many available libraries and third-party toolkits extend the functionality of the core language into virtually every biological domain (sequence and structure analyses, phylogenomics, workflow management systems, etc.). This primer offers a basic introduction to coding, via Python, and it includes concrete examples and exercises to illustrate the language’s usage and capabilities; the main text culminates with a final project in structural bioinformatics. A suite of Supplemental Chapters is also provided. Starting with basic concepts, such as that of a “variable,” the Chapters methodically advance the reader to the point of writing a graphical user interface to compute the Hamming distance between two DNA sequences. PMID:27271528

  7. An Introduction to Programming for Bioscientists: A Python-Based Primer.

    PubMed

    Ekmekci, Berk; McAnany, Charles E; Mura, Cameron

    2016-06-01

    Computing has revolutionized the biological sciences over the past several decades, such that virtually all contemporary research in molecular biology, biochemistry, and other biosciences utilizes computer programs. The computational advances have come on many fronts, spurred by fundamental developments in hardware, software, and algorithms. These advances have influenced, and even engendered, a phenomenal array of bioscience fields, including molecular evolution and bioinformatics; genome-, proteome-, transcriptome- and metabolome-wide experimental studies; structural genomics; and atomistic simulations of cellular-scale molecular assemblies as large as ribosomes and intact viruses. In short, much of post-genomic biology is increasingly becoming a form of computational biology. The ability to design and write computer programs is among the most indispensable skills that a modern researcher can cultivate. Python has become a popular programming language in the biosciences, largely because (i) its straightforward semantics and clean syntax make it a readily accessible first language; (ii) it is expressive and well-suited to object-oriented programming, as well as other modern paradigms; and (iii) the many available libraries and third-party toolkits extend the functionality of the core language into virtually every biological domain (sequence and structure analyses, phylogenomics, workflow management systems, etc.). This primer offers a basic introduction to coding, via Python, and it includes concrete examples and exercises to illustrate the language's usage and capabilities; the main text culminates with a final project in structural bioinformatics. A suite of Supplemental Chapters is also provided. Starting with basic concepts, such as that of a "variable," the Chapters methodically advance the reader to the point of writing a graphical user interface to compute the Hamming distance between two DNA sequences.

  8. morphforge: a toolbox for simulating small networks of biologically detailed neurons in Python

    PubMed Central

    Hull, Michael J.; Willshaw, David J.

    2014-01-01

    The broad structure of a modeling study can often be explained over a cup of coffee, but converting this high-level conceptual idea into graphs of the final simulation results may require many weeks of sitting at a computer. Although models themselves can be complex, often many mental resources are wasted working around complexities of the software ecosystem such as fighting to manage files, interfacing between tools and data formats, finding mistakes in code or working out the units of variables. morphforge is a high-level, Python toolbox for building and managing simulations of small populations of multicompartmental biophysical model neurons. An entire in silico experiment, including the definition of neuronal morphologies, channel descriptions, stimuli, visualization and analysis of results can be written within a single short Python script using high-level objects. Multiple independent simulations can be created and run from a single script, allowing parameter spaces to be investigated. Consideration has been given to the reuse of both algorithmic and parameterizable components to allow both specific and stochastic parameter variations. Some other features of the toolbox include: the automatic generation of human-readable documentation (e.g., PDF files) about a simulation; the transparent handling of different biophysical units; a novel mechanism for plotting simulation results based on a system of tags; and an architecture that supports both the use of established formats for defining channels and synapses (e.g., MODL files), and the possibility to support other libraries and standards easily. We hope that this toolbox will allow scientists to quickly build simulations of multicompartmental model neurons for research and serve as a platform for further tool development. PMID:24478690

  9. In Silico Analysis of Gene Expression Network Components Underlying Pigmentation Phenotypes in the Python Identified Evolutionarily Conserved Clusters of Transcription Factor Binding Sites

    PubMed Central

    2016-01-01

    Color variation provides the opportunity to investigate the genetic basis of evolution and selection. Reptiles are less studied than mammals. Comparative genomics approaches allow for knowledge gained in one species to be leveraged for use in another species. We describe a comparative vertebrate analysis of conserved regulatory modules in pythons aimed at assessing bioinformatics evidence that transcription factors important in mammalian pigmentation phenotypes may also be important in python pigmentation phenotypes. We identified 23 python orthologs of mammalian genes associated with variation in coat color phenotypes for which we assessed the extent of pairwise protein sequence identity between pythons and mouse, dog, horse, cow, chicken, anole lizard, and garter snake. We next identified a set of melanocyte/pigment associated transcription factors (CREB, FOXD3, LEF-1, MITF, POU3F2, and USF-1) that exhibit relatively conserved sequence similarity within their DNA binding regions across species based on orthologous alignments across multiple species. Finally, we identified 27 evolutionarily conserved clusters of transcription factor binding sites within ~200-nucleotide intervals of the 1500-nucleotide upstream regions of AIM1, DCT, MC1R, MITF, MLANA, OA1, PMEL, RAB27A, and TYR from Python bivittatus. Our results provide insight into pigment phenotypes in pythons. PMID:27698666

  10. ParFit: A Python-Based Object-Oriented Program for Fitting Molecular Mechanics Parameters to ab Initio Data.

    PubMed

    Zahariev, Federico; De Silva, Nuwan; Gordon, Mark S; Windus, Theresa L; Dick-Perez, Marilu

    2017-03-27

    A newly created object-oriented program for automating the process of fitting molecular-mechanics parameters to ab initio data, termed ParFit, is presented. ParFit uses a hybrid of deterministic and stochastic genetic algorithms. ParFit can simultaneously handle several molecular-mechanics parameters in multiple molecules and can also apply symmetric and antisymmetric constraints on the optimized parameters. The simultaneous handling of several molecules enhances the transferability of the fitted parameters. ParFit is written in Python, uses a rich set of standard and nonstandard Python libraries, and can be run in parallel on multicore computer systems. As an example, a series of phosphine oxides, important for metal extraction chemistry, are parametrized using ParFit. ParFit is in an open source program available for free on GitHub ( https://github.com/fzahari/ParFit ).

  11. Dracunculus mulbus n. sp. (Nematoda: Spirurida) from the water python Liasis fuscus (Serpentes: Boidae) in northern Australia.

    PubMed

    Jones, Hugh I; Mulder, Eridani

    2007-03-01

    A new species of Dracunculus Reichard, 1759 (Nematoda: Spirurida) is described from the tissues surrounding organs in the body-cavity of the water python Liasis fuscus Peters in northern Australia. One to 14 worms were recovered from 22% (27/120) of pythons examined. Males were located principally around the lungs, liver and heart of the hosts, and females were recovered from peritoneal tissue surrounding the intestines and lining the body-cavity. This species differs from previously described species of Dracunculus in the position of the papillae at the posterior end in males, and in the possession of thick, narrow caudal alae. Submedian cephalic papillae are single in both sexes. Dorsal and ventral anterior cephalic papillae are absent in males. This is the first report of a species of Dracunculus from the Australian region.

  12. ParFit: A Python-Based Object-Oriented Program for Fitting Molecular Mechanics Parameters to ab Initio Data

    DOE PAGES

    Zahariev, Federico; De Silva, Nuwan; Gordon, Mark S.; ...

    2017-02-23

    Here, a newly created object-oriented program for automating the process of fitting molecular-mechanics parameters to ab initio data, termed ParFit, is presented. ParFit uses a hybrid of deterministic and stochastic genetic algorithms. ParFit can simultaneously handle several molecular-mechanics parameters in multiple molecules and can also apply symmetric and antisymmetric constraints on the optimized parameters. The simultaneous handling of several molecules enhances the transferability of the fitted parameters. ParFit is written in Python, uses a rich set of standard and nonstandard Python libraries, and can be run in parallel on multicore computer systems. As an example, a series of phosphine oxides,more » important for metal extraction chemistry, are parametrized using ParFit.« less

  13. Fine structure of the development of Sarcocystis singaporensis in Python reticulatus from macrogamont to sporulated oocyst stage.

    PubMed

    Paperna, I; Martelli, P

    2000-09-01

    Three, 4-month old reticulated pythons (Python reticulatus) hatched from eggs laid by a newly caught female from Singapore Island, were fed on muscles of Sarcocystis singaporensis-infected Rattus rattus caught in Singapore. Snakes were sacrificed five, six and eight days later. The infected tissues were studied by transmission electron microscope. The present communication summarizes findings on macrogamont and oocyst stages. In the premature stages, rough endoplasmic reticulum consolidate into a large rectangular array; the electron-dense wall-forming-like bodies reveal a laminar structure. Macrogamont parasitophorous vacuoles became filled with granular matrix and electron-dense strands, which later on consolidate into a coat around the fertilized zygote. The oocyst wall is constructed from several formed membranes combined with deposited substance. All development to the sporulated oocyst stage occurs in the mucosal epithelium.

  14. Complete Genome Sequence of Akkermansia glycaniphila Strain PytT, a Mucin-Degrading Specialist of the Reticulated Python Gut.

    PubMed

    Ouwerkerk, Janneke P; Koehorst, Jasper J; Schaap, Peter J; Ritari, Jarmo; Paulin, Lars; Belzer, Clara; de Vos, Willem M

    2017-01-05

    Akkermansia glycaniphila is a novel Akkermansia species that was isolated from the intestine of the reticulated python and shares the capacity to degrade mucin with the human strain Akkermansia muciniphila Muc(T) Here, we report the complete genome sequence of strain Pyt(T) of 3,074,121 bp. The genomic analysis reveals genes for mucin degradation and aerobic respiration.

  15. What parts of the US mainland are climatically suitable for invasive alien pythons spreading from Everglades National Park?

    USGS Publications Warehouse

    Rodda, G.H.; Jarnevich, C.S.; Reed, R.N.

    2009-01-01

    The Burmese Python (Python molurus bivittatus) is now well established in southern Florida and spreading northward. The factors likely to limit this spread are unknown, but presumably include climate or are correlated with climate. We compiled monthly rainfall and temperature statistics from 149 stations located near the edge of the python's native range in Asia (Pakistan east to China and south to Indonesia). The southern and eastern native range limits extend to saltwater, leaving unresolved the species' climatic tolerances in those areas. The northern and western limits are associated with cold and aridity respectively. We plotted mean monthly rainfall against mean monthly temperature for the 149 native range weather stations to identify the climate conditions inhabited by pythons in their native range, and mapped areas of the coterminous United States with the same climate today and projected for the year 2100. We accounted for both dry-season aestivation and winter hibernation (under two scenarios of hibernation duration). The potential distribution was relatively insensitive to choice of scenario for hibernation duration. US areas climatically matched at present ranged up the coasts and across the south from Delaware to Oregon, and included most of California, Texas, Oklahoma, Arkansas, Louisiana, Mississippi, Alabama, Florida, Georgia, and South and North Carolina. By the year 2100, projected areas of potential suitable climate extend northward beyond the current limit to include parts of the states of Washington, Colorado, Illinois, Indiana, Ohio, West Virginia, Pennsylvania, New Jersey, and New York. Thus a substantial portion of the mainland US is potentially vulnerable to this ostensibly tropical invader. ?? 2008 Springer Science+Business Media B.V.

  16. Embryonic development of Python sebae - I: Staging criteria and macroscopic skeletal morphogenesis of the head and limbs.

    PubMed

    Boughner, Julia C; Buchtová, Marcela; Fu, Katherine; Diewert, Virginia; Hallgrímsson, Benedikt; Richman, Joy M

    2007-01-01

    This study explores the post-ovipositional craniofacial development of the African Rock Python (Python sebae). We first describe a staging system based on external characteristics and next use whole-mount skeletal staining supplemented with Computed tomography (CT) scanning to examine skeletal development. Our results show that python embryos are in early stages of organogenesis at the time of laying, with separate facial prominences and pharyngeal clefts still visible. Limb buds are also visible. By 11 days (stage 3), the chondrocranium is nearly fully formed; however, few intramembranous bones can be detected. One week later (stage 4), many of the intramembranous upper and lower jaw bones are visible but the calvaria are not present. Skeletal elements in the limbs also begin to form. Between stages 4 (day 18) and 7 (day 44), the complete set of intramembranous bones in the jaws and calvaria develops. Hindlimb development does not progress beyond stage 6 (33 days) and remains rudimentary throughout adult life. In contrast to other reptiles, there are two rows of teeth in the upper jaw. The outer tooth row is attached to the maxillary and premaxillary bones, whereas the inner row is attached to the pterygoid and palatine bones. Erupted teeth can be seen in whole-mount stage 10 specimens and are present in an unerupted, mineralized state at stage 7. Micro-CT analysis reveals that all the young membranous bones can be recognized even out of the context of the skull. These data demonstrate intrinsic patterning of the intramembranous bones, even though they form without a cartilaginous template. In addition, intramembranous bone morphology is established prior to muscle function, which can influence bone shape through differential force application. After careful staging, we conclude that python skeletal development occurs slowly enough to observe in good detail the early stages of craniofacial skeletogenesis. Thus, reptilian animal models will offer unique

  17. Large-scale automated image analysis for computational profiling of brain tissue surrounding implanted neuroprosthetic devices using Python

    PubMed Central

    Rey-Villamizar, Nicolas; Somasundar, Vinay; Megjhani, Murad; Xu, Yan; Lu, Yanbin; Padmanabhan, Raghav; Trett, Kristen; Shain, William; Roysam, Badri

    2014-01-01

    In this article, we describe the use of Python for large-scale automated server-based bio-image analysis in FARSIGHT, a free and open-source toolkit of image analysis methods for quantitative studies of complex and dynamic tissue microenvironments imaged by modern optical microscopes, including confocal, multi-spectral, multi-photon, and time-lapse systems. The core FARSIGHT modules for image segmentation, feature extraction, tracking, and machine learning are written in C++, leveraging widely used libraries including ITK, VTK, Boost, and Qt. For solving complex image analysis tasks, these modules must be combined into scripts using Python. As a concrete example, we consider the problem of analyzing 3-D multi-spectral images of brain tissue surrounding implanted neuroprosthetic devices, acquired using high-throughput multi-spectral spinning disk step-and-repeat confocal microscopy. The resulting images typically contain 5 fluorescent channels. Each channel consists of 6000 × 10,000 × 500 voxels with 16 bits/voxel, implying image sizes exceeding 250 GB. These images must be mosaicked, pre-processed to overcome imaging artifacts, and segmented to enable cellular-scale feature extraction. The features are used to identify cell types, and perform large-scale analysis for identifying spatial distributions of specific cell types relative to the device. Python was used to build a server-based script (Dell 910 PowerEdge servers with 4 sockets/server with 10 cores each, 2 threads per core and 1TB of RAM running on Red Hat Enterprise Linux linked to a RAID 5 SAN) capable of routinely handling image datasets at this scale and performing all these processing steps in a collaborative multi-user multi-platform environment. Our Python script enables efficient data storage and movement between computers and storage servers, logs all the processing steps, and performs full multi-threaded execution of all codes, including open and closed-source third party libraries. PMID:24808857

  18. Complete Genome Sequence of Akkermansia glycaniphila Strain PytT, a Mucin-Degrading Specialist of the Reticulated Python Gut

    PubMed Central

    Ouwerkerk, Janneke P.; Schaap, Peter J.; Ritari, Jarmo; Paulin, Lars; Belzer, Clara

    2017-01-01

    ABSTRACT Akkermansia glycaniphila is a novel Akkermansia species that was isolated from the intestine of the reticulated python and shares the capacity to degrade mucin with the human strain Akkermansia muciniphila MucT. Here, we report the complete genome sequence of strain PytT of 3,074,121 bp. The genomic analysis reveals genes for mucin degradation and aerobic respiration. PMID:28057747

  19. Fast prototyping of wavelet spatio-temporal RS fusion with Raingauge time series with GDAL and Python-DWT

    NASA Astrophysics Data System (ADS)

    Chemin, Yann

    2013-04-01

    Availability of rainfall time-series is limited in many parts of the World, and the continuity of such records is variable. This research endeavors to extend actual daily rainfall observations to ungauged areas using vegetation response as witnessed by remote sensing data and taking into account rainfall event histograms as well as cumulative total daily rainfall, over a period of 11 years. Open Source code development permitted to gain on several aspects. The first one pertains to space, Python and its numerical part (NumPy) are scientifically concise, as a bonus to be expressive. The second is the availability of the Discrete Wavelet Transform (DWT) in Python already, which permitted to reduce the Wavelet Transform to a small set of instructions, clarifying and simplifying the understanding of the code once it reaches the Public Domain. GDAL interface permitted to load satellite imagery and write fused rainfall time-series in spatio-temporal dimensions. Other scientific tool from Numerical Python were also used in the process of developing the algorithm (scipy.stats.stats and scipy.interpolate.griddata). Due to the large amount of days (4019) and the kilometer based resolution of the vegetation RS data, it takes about a week for the code to resolve the fusion problem. An attempt at using an multicore interpolation implementation in Python (hpgl) which unfortunately was not an active project anymore, though certainly deserving interest. Results show that rainfall events histograms can be reconstructed, and that total cumulative rainfall is estimated with 85% accuracy, using a surrounding network of rain gauges at 30-50 km of distance from the point of study. This research can strengthen various types of research and applications such as ungauged basins research, regional climate modeling, agricultural insurance systems, etc. Further development aims at porting the code to distributed computing.

  20. Large-scale automated image analysis for computational profiling of brain tissue surrounding implanted neuroprosthetic devices using Python.

    PubMed

    Rey-Villamizar, Nicolas; Somasundar, Vinay; Megjhani, Murad; Xu, Yan; Lu, Yanbin; Padmanabhan, Raghav; Trett, Kristen; Shain, William; Roysam, Badri

    2014-01-01

    In this article, we describe the use of Python for large-scale automated server-based bio-image analysis in FARSIGHT, a free and open-source toolkit of image analysis methods for quantitative studies of complex and dynamic tissue microenvironments imaged by modern optical microscopes, including confocal, multi-spectral, multi-photon, and time-lapse systems. The core FARSIGHT modules for image segmentation, feature extraction, tracking, and machine learning are written in C++, leveraging widely used libraries including ITK, VTK, Boost, and Qt. For solving complex image analysis tasks, these modules must be combined into scripts using Python. As a concrete example, we consider the problem of analyzing 3-D multi-spectral images of brain tissue surrounding implanted neuroprosthetic devices, acquired using high-throughput multi-spectral spinning disk step-and-repeat confocal microscopy. The resulting images typically contain 5 fluorescent channels. Each channel consists of 6000 × 10,000 × 500 voxels with 16 bits/voxel, implying image sizes exceeding 250 GB. These images must be mosaicked, pre-processed to overcome imaging artifacts, and segmented to enable cellular-scale feature extraction. The features are used to identify cell types, and perform large-scale analysis for identifying spatial distributions of specific cell types relative to the device. Python was used to build a server-based script (Dell 910 PowerEdge servers with 4 sockets/server with 10 cores each, 2 threads per core and 1TB of RAM running on Red Hat Enterprise Linux linked to a RAID 5 SAN) capable of routinely handling image datasets at this scale and performing all these processing steps in a collaborative multi-user multi-platform environment. Our Python script enables efficient data storage and movement between computers and storage servers, logs all the processing steps, and performs full multi-threaded execution of all codes, including open and closed-source third party libraries.

  1. VarPy: A python library for volcanology and rock physics data analysis

    NASA Astrophysics Data System (ADS)

    Filgueira, Rosa; Atkinson, Malcom; Bell, Andrew; Snelling, Brawen; Main, Ian

    2014-05-01

    The increasing prevalence of digital instrumentation in volcanology and rock physics is leading to a wealth of data, which in turn is increasing the need for computational analyses and models. Today, these are largely developed by each individual or researcher. The introduction of a shared library that can be used for this purpose has several benefits: 1. when an existing function in the library meets a need recognised by a researcher it is usually much less effort than developing ones own code; 2. once functions are established and multiply used they become better tested, more reliable and eventually trusted by the community; 3. use of the same functions by different researchers makes it easier to compare results and to compare the skill of rival analysis and modelling methods; and 4. in the longer term the cost of maintaining these functions is shared over a wide community and they therefore have greater duration. Python is a high-level interpreted programming language, with capabilities for object-oriented programming. Often scientists choose this language to program their programs because of the increased productivity it provides. Although, there are many software tools available for interactive data analysis and development, there are not libraries designed specifically for volcanology and rock physics data. Therefore, we propose a new Python open-source toolbox called "VarPy" to facilitate rapid application development for rock physicists and volcanologists, which allow users to define their own workflows to develop models, analyses and visualisations. This proposal is triggered by our work on data assimilation in the NERC EFFORT (Earthquake and Failure Forecasting in Real Time) project, using data provided by the NERC CREEP 2 experimental project and volcanic experiments from INVG observatory Etna and IGN observatory Hierro as a test cases. In EFFORT project we are developing a scientist gateway which offers services for collecting and sharing volcanology

  2. Enabling grand-canonical Monte Carlo: extending the flexibility of GROMACS through the GromPy python interface module.

    PubMed

    Pool, René; Heringa, Jaap; Hoefling, Martin; Schulz, Roland; Smith, Jeremy C; Feenstra, K Anton

    2012-05-05

    We report on a python interface to the GROMACS molecular simulation package, GromPy (available at https://github.com/GromPy). This application programming interface (API) uses the ctypes python module that allows function calls to shared libraries, for example, written in C. To the best of our knowledge, this is the first reported interface to the GROMACS library that uses direct library calls. GromPy can be used for extending the current GROMACS simulation and analysis modes. In this work, we demonstrate that the interface enables hybrid Monte-Carlo/molecular dynamics (MD) simulations in the grand-canonical ensemble, a simulation mode that is currently not implemented in GROMACS. For this application, the interplay between GromPy and GROMACS requires only minor modifications of the GROMACS source code, not affecting the operation, efficiency, and performance of the GROMACS applications. We validate the grand-canonical application against MD in the canonical ensemble by comparison of equations of state. The results of the grand-canonical simulations are in complete agreement with MD in the canonical ensemble. The python overhead of the grand-canonical scheme is only minimal.

  3. Using the Python language and the CMOR2 library to create PMIPn-CMIPn compliant model output

    NASA Astrophysics Data System (ADS)

    Peterschmitt, Jean-Yves; Doutriaux, Charles

    2015-04-01

    The Paleoclimate Modelling Intercomparison Project (PMIP) is a long standing initiative that has provided an efficient mechanism for coordinating paleoclimate modelling activities that provide valuable information on the mechanisms of climate change, the identification of key feedbacks operating in the climate system and, through model evaluation, the capability of climate models to reproduce climates different from today. The third phase of PMIP (aka PMIP 3) started in 2009 (the fourth phase is about to start) and followed the requirements specified by CMIP5 (Coupled Model Intercomparison Project). Generating data files following strict Model Intercomparison Projects (MIPs) standards (NetCDF format, file and variable names, file structure, metadata information, directory hierarchy, etc…) has been a key to the success of many recent Model Intercomparison Projects. It is unfortunately not always easy to convert proprietary model output format to the required standards, and this has prevented some smaller modelling groups from sharing their data. We will present how the Python version of the CMOR2 (Climate Model Output Rewriter) library bundled with the UV-CDAT Python distribution (Ultrascale Visualization Climate Data Analysis Tools) can be used to easily convert raw model output to the appropriate MIP shareable format. References: http://pmip3.lsce.ipsl.fr/ http://cmip-pcmdi.llnl.gov/cmip5/output_req.html http://www2-pcmdi.llnl.gov/cmor http://uvcdat.llnl.gov/ https://www.python.org/

  4. Zephyr: Open-source Parallel Seismic Waveform Inversion in an Integrated Python-based Framework

    NASA Astrophysics Data System (ADS)

    Smithyman, B. R.; Pratt, R. G.; Hadden, S. M.

    2015-12-01

    Seismic Full-Waveform Inversion (FWI) is an advanced method to reconstruct wave properties of materials in the Earth from a series of seismic measurements. These methods have been developed by researchers since the late 1980s, and now see significant interest from the seismic exploration industry. As researchers move towards implementing advanced numerical modelling (e.g., 3D, multi-component, anisotropic and visco-elastic physics), it is desirable to make use of a modular approach, minimizing the effort developing a new set of tools for each new numerical problem. SimPEG (http://simpeg.xyz) is an open source project aimed at constructing a general framework to enable geophysical inversion in various domains. In this abstract we describe Zephyr (https://github.com/bsmithyman/zephyr), which is a coupled research project focused on parallel FWI in the seismic context. The software is built on top of Python, Numpy and IPython, which enables very flexible testing and implementation of new features. Zephyr is an open source project, and is released freely to enable reproducible research. We currently implement a parallel, distributed seismic forward modelling approach that solves the 2.5D (two-and-one-half dimensional) viscoacoustic Helmholtz equation at a range modelling frequencies, generating forward solutions for a given source behaviour, and gradient solutions for a given set of observed data. Solutions are computed in a distributed manner on a set of heterogeneous workers. The researcher's frontend computer may be separated from the worker cluster by a network link to enable full support for computation on remote clusters from individual workstations or laptops. The present codebase introduces a numerical discretization equivalent to that used by FULLWV, a well-known seismic FWI research codebase. This makes it straightforward to compare results from Zephyr directly with FULLWV. The flexibility introduced by the use of a Python programming environment makes

  5. FMC: a one-liner Python program to manage, classify and plot focal mechanisms

    NASA Astrophysics Data System (ADS)

    Álvarez-Gómez, José A.

    2014-05-01

    The analysis of earthquake focal mechanisms (or Seismic Moment Tensor, SMT) is a key tool on seismotectonics research. Each focal mechanism is characterized by several location parameters of the earthquake hypocenter, the earthquake size (magnitude and scalar moment tensor) and some geometrical characteristics of the rupture (nodal planes orientations, SMT components and/or SMT main axes orientations). The aim of FMC is to provide a simple but powerful tool to manage focal mechanism data. The data should be input to the program formatted as one of two of the focal mechanisms formatting options of the GMT (Generic Mapping Tools) package (Wessel and Smith, 1998): the Harvard CMT convention and the single nodal plane Aki and Richards (1980) convention. The former is a SMT format that can be downloaded directly from the Global CMT site (http://www.globalcmt.org/), while the later is the simplest way to describe earthquake rupture data. FMC is programmed in Python language, which is distributed as Open Source GPL-compatible, and therefore can be used to develop Free Software. Python runs on almost any machine, and has a wide support and presence in any operative system. The program has been conceived with the modularity and versatility of the classical UNIX-like tools. Is called from the command line and can be easily integrated into shell scripts (*NIX systems) or batch files (DOS/Windows systems). The program input and outputs can be done by means of ASCII files or using standard input (or redirection "<"), standard output (screen or redirection ">") and pipes ("|"). By default FMC will read the input and write the output as a Harvard CMT (psmeca formatted) ASCII file, although other formats can be used. Optionally FMC will produce a classification diagram representing the rupture type of the focal mechanisms processed. In order to count with a detailed classification of the focal mechanisms I decided to classify the focal mechanism in a series of fields that include

  6. Python tools for rapid development, calibration, and analysis of generalized groundwater-flow models

    NASA Astrophysics Data System (ADS)

    Starn, J. J.; Belitz, K.

    2014-12-01

    National-scale water-quality data sets for the United States have been available for several decades; however, groundwater models to interpret these data are available for only a small percentage of the country. Generalized models may be adequate to explain and project groundwater-quality trends at the national scale by using regional scale models (defined as watersheds at or between the HUC-6 and HUC-8 levels). Coast-to-coast data such as the National Hydrologic Dataset Plus (NHD+) make it possible to extract the basic building blocks for a model anywhere in the country. IPython notebooks have been developed to automate the creation of generalized groundwater-flow models from the NHD+. The notebook format allows rapid testing of methods for model creation, calibration, and analysis. Capabilities within the Python ecosystem greatly speed up the development and testing of algorithms. GeoPandas is used for very efficient geospatial processing. Raster processing includes the Geospatial Data Abstraction Library and image processing tools. Model creation is made possible through Flopy, a versatile input and output writer for several MODFLOW-based flow and transport model codes. Interpolation, integration, and map plotting included in the standard Python tool stack also are used, making the notebook a comprehensive platform within on to build and evaluate general models. Models with alternative boundary conditions, number of layers, and cell spacing can be tested against one another and evaluated by using water-quality data. Novel calibration criteria were developed by comparing modeled heads to land-surface and surface-water elevations. Information, such as predicted age distributions, can be extracted from general models and tested for its ability to explain water-quality trends. Groundwater ages then can be correlated with horizontal and vertical hydrologic position, a relation that can be used for statistical assessment of likely groundwater-quality conditions

  7. Uncertainty quantification of surface-water/groundwater exchange estimates in large wetland systems using Python

    NASA Astrophysics Data System (ADS)

    Hughes, J. D.; Metz, P. A.

    2014-12-01

    Most watershed studies include observation-based water budget analyses to develop first-order estimates of significant flow terms. Surface-water/groundwater (SWGW) exchange is typically assumed to be equal to the residual of the sum of inflows and outflows in a watershed. These estimates of SWGW exchange, however, are highly uncertain as a result of the propagation of uncertainty inherent in the calculation or processing of the other terms of the water budget, such as stage-area-volume relations, and uncertainties associated with land-cover based evapotranspiration (ET) rate estimates. Furthermore, the uncertainty of estimated SWGW exchanges can be magnified in large wetland systems that transition from dry to wet during wet periods. Although it is well understood that observation-based estimates of SWGW exchange are uncertain it is uncommon for the uncertainty of these estimates to be directly quantified. High-level programming languages like Python can greatly reduce the effort required to (1) quantify the uncertainty of estimated SWGW exchange in large wetland systems and (2) evaluate how different approaches for partitioning land-cover data in a watershed may affect the water-budget uncertainty. We have used Python with the Numpy, Scipy.stats, and pyDOE packages to implement an unconstrained Monte Carlo approach with Latin Hypercube sampling to quantify the uncertainty of monthly estimates of SWGW exchange in the Floral City watershed of the Tsala Apopka wetland system in west-central Florida, USA. Possible sources of uncertainty in the water budget analysis include rainfall, ET, canal discharge, and land/bathymetric surface elevations. Each of these input variables was assigned a probability distribution based on observation error or spanning the range of probable values. The Monte Carlo integration process exposes the uncertainties in land-cover based ET rate estimates as the dominant contributor to the uncertainty in SWGW exchange estimates. We will discuss

  8. The InSAR Scientific Computing Environment (ISCE): A Python Framework for Earth Science

    NASA Astrophysics Data System (ADS)

    Rosen, P. A.; Gurrola, E. M.; Agram, P. S.; Sacco, G. F.; Lavalle, M.

    2015-12-01

    The InSAR Scientific Computing Environment (ISCE, funded by NASA ESTO) provides a modern computing framework for geodetic image processing of InSAR data from a diverse array of radar satellites and aircraft. ISCE is both a modular, flexible, and extensible framework for building software components and applications as well as a toolbox of applications for processing raw or focused InSAR and Polarimetric InSAR data. The ISCE framework contains object-oriented Python components layered to construct Python InSAR components that manage legacy Fortran/C InSAR programs. Components are independently configurable in a layered manner to provide maximum control. Polymorphism is used to define a workflow in terms of abstract facilities for each processing step that are realized by specific components at run-time. This enables a single workflow to work on either raw or focused data from all sensors. ISCE can serve as the core of a production center to process Level-0 radar data to Level-3 products, but is amenable to interactive processing approaches that allow scientists to experiment with data to explore new ways of doing science with InSAR data. The NASA-ISRO SAR (NISAR) Mission will deliver data of unprecedented quantity and quality, making possible global-scale studies in climate research, natural hazards, and Earth's ecosystems. ISCE is planned as the foundational element in processing NISAR data, enabling a new class of analyses that take greater advantage of the long time and large spatial scales of these new data. NISAR will be but one mission in a constellation of radar satellites in the future delivering such data. ISCE currently supports all publicly available strip map mode space-borne SAR data since ERS and is expected to include support for upcoming missions. ISCE has been incorporated into two prototype cloud-based systems that have demonstrated its elasticity in addressing larger data processing problems in a "production" context and its ability to be

  9. Geospatial Data Stream Processing in Python Using FOSS4G Components

    NASA Astrophysics Data System (ADS)

    McFerren, G.; van Zyl, T.

    2016-06-01

    One viewpoint of current and future IT systems holds that there is an increase in the scale and velocity at which data are acquired and analysed from heterogeneous, dynamic sources. In the earth observation and geoinformatics domains, this process is driven by the increase in number and types of devices that report location and the proliferation of assorted sensors, from satellite constellations to oceanic buoy arrays. Much of these data will be encountered as self-contained messages on data streams - continuous, infinite flows of data. Spatial analytics over data streams concerns the search for spatial and spatio-temporal relationships within and amongst data "on the move". In spatial databases, queries can assess a store of data to unpack spatial relationships; this is not the case on streams, where spatial relationships need to be established with the incomplete data available. Methods for spatially-based indexing, filtering, joining and transforming of streaming data need to be established and implemented in software components. This article describes the usage patterns and performance metrics of a number of well known FOSS4G Python software libraries within the data stream processing paradigm. In particular, we consider the RTree library for spatial indexing, the Shapely library for geometric processing and transformation and the PyProj library for projection and geodesic calculations over streams of geospatial data. We introduce a message oriented Python-based geospatial data streaming framework called Swordfish, which provides data stream processing primitives, functions, transports and a common data model for describing messages, based on the Open Geospatial Consortium Observations and Measurements (O&M) and Unidata Common Data Model (CDM) standards. We illustrate how the geospatial software components are integrated with the Swordfish framework. Furthermore, we describe the tight temporal constraints under which geospatial functionality can be invoked when

  10. Increased blood oxygen affinity during digestion in the snake Python molurus.

    PubMed

    Overgaard, Johannes; Wang, Tobias

    2002-11-01

    Many snakes exhibit large increases in metabolic rate during digestion that place extensive demands on efficient oxygen transport. In the present study, we describe blood oxygen affinity following three weeks of fasting and 48 h after feeding in the Burmese python (Python molurus). We also report simultaneous measurements of arterial blood gases and haematological parameters. Arterial blood was obtained from chronically implanted catheters, and blood oxygen-dissociation curves were constructed from oxygen content measurements at known oxygen partial pressure (P(O(2))) values at 2% and 5% CO(2). Arterial pH remained constant at approximately 7.6 after feeding, but digestion was associated with an approximately 6 mmol l(-1) increase in [HCO(3)(-)], while CO(2) partial pressure (P(CO(2))) increased from 2.21+/-0.13 kPa in fasted animals to 2.89+/-0.17 kPa at 48 h after feeding. Blood oxygen affinity in vivo was predicted on the basis of pH in vivo and the blood oxygen-dissociation curves obtained in vitro. The blood oxygen affinity in vivo increased during digestion, with P(50) values decreasing from 4.58+/-0.11 kPa to 3.53+/-0.24 kPa. This increase was associated with a significant decrease in the red blood cell [NTP]/[Hb(4)] ratio (relationship between the concentrations of organic phosphates and total haemoglobin) and a significant decrease in mean cellular haemoglobin content, which is indicative of swelling of the red blood cells. Our data for blood oxygen affinity and arterial oxygen levels, together with previously published values of oxygen uptake and blood flows, allow for a quantitative evaluation of oxygen transport during digestion. This analysis shows that a large part of the increased metabolism during digestion is supported by an increased venous extraction, while arterial P(O(2)) (Pa(O(2))) and haemoglobin saturation do not vary with digestive status. Thus, we predict that venous P(O(2)) (Pv(O(2))) is reduced from a fasting value of 5.2 kPa to 1.6 k

  11. IB2d: a Python and MATLAB implementation of the immersed boundary method.

    PubMed

    Battista, Nicholas A; Strickland, W Christopher; Miller, Laura A

    2017-03-29

    The development of fluid-structure interaction (FSI) software involves trade-offs between ease of use, generality, performance, and cost. Typically there are large learning curves when using low-level software to model the interaction of an elastic structure immersed in a uniform density fluid. Many existing codes are not publicly available, and the commercial software that exists usually requires expensive licenses and may not be as robust or allow the necessary flexibility that in house codes can provide. We present an open source immersed boundary software package, IB2d, with full implementations in both MATLAB and Python, that is capable of running a vast range of biomechanics models and is accessible to scientists who have experience in high-level programming environments. IB2d contains multiple options for constructing material properties of the fiber structure, as well as the advection-diffusion of a chemical gradient, muscle mechanics models, and artificial forcing to drive boundaries with a preferred motion.

  12. Analysis and Visualization of Multi-Scale Astrophysical Simulations using Python and NumPy

    SciTech Connect

    Turk, M.; /KIPAC, Menlo Park

    2008-09-30

    The study the origins of cosmic structure requires large-scale computer simulations beginning with well-constrained, observationally-determined, initial conditions. We use Adaptive Mesh Refinement to conduct multi-resolution simulations spanning twelve orders of magnitude in spatial dimensions and over twenty orders of magnitude in density. These simulations must be analyzed and visualized in a manner that is fast, accurate, and reproducible. I present 'yt,' a cross-platform analysis toolkit written in Python. 'yt' consists of a data-management layer for transporting and tracking simulation outputs, a plotting layer, a parallel analysis layer for handling mesh-based and particle-based data, as well as several interfaces. I demonstrate how the origins of cosmic structure--from the scale of clusters of galaxies down to the formation of individual stars--can be analyzed and visualized using a NumPy-based toolkit. Additionally, I discuss efforts to port this analysis code to other adaptive mesh refinement data formats, enabling direct comparison of data between research groups using different methods to simulate the same objects.

  13. MSNoise: a Python Package for Monitoring Seismic Velocity Changes using Ambient Seismic Noise

    NASA Astrophysics Data System (ADS)

    Lecocq, T.; Caudron, C.; Brenguier, F.

    2013-12-01

    Earthquakes occur every day all around the world and are recorded by thousands of seismic stations. In between earthquakes, stations are recording "noise". In the last 10 years, the understanding of this noise and its potential usage have been increasing rapidly. The method, called "seismic interferometry", uses the principle that seismic waves travel between two recorders and are multiple-scattered in the medium. By cross-correlating the two records, one gets an information on the medium below/between the stations. The cross-correlation function (CCF) is a proxy to the Green Function of the medium. Recent developments of the technique have shown those CCF can be used to image the earth at depth (3D seismic tomography) or study the medium changes with time. We present MSNoise, a complete software suite to compute relative seismic velocity changes under a seismic network, using ambient seismic noise. The whole is written in Python, from the monitoring of data archives, to the production of high quality figures. All steps have been optimized to only compute the necessary steps and to use 'job'-based processing. We present a validation of the software on a dataset acquired during the UnderVolc[1] project on the Piton de la Fournaise Volcano, La Réunion Island, France, for which precursory relative changes of seismic velocity are visible for three eruptions betwee 2009 and 2011.

  14. ORBKIT: A modular python toolbox for cross-platform postprocessing of quantum chemical wavefunction data.

    PubMed

    Hermann, Gunter; Pohl, Vincent; Tremblay, Jean Christophe; Paulus, Beate; Hege, Hans-Christian; Schild, Axel

    2016-06-15

    ORBKIT is a toolbox for postprocessing electronic structure calculations based on a highly modular and portable Python architecture. The program allows computing a multitude of electronic properties of molecular systems on arbitrary spatial grids from the basis set representation of its electronic wavefunction, as well as several grid-independent properties. The required data can be extracted directly from the standard output of a large number of quantum chemistry programs. ORBKIT can be used as a standalone program to determine standard quantities, for example, the electron density, molecular orbitals, and derivatives thereof. The cornerstone of ORBKIT is its modular structure. The existing basic functions can be arranged in an individual way and can be easily extended by user-written modules to determine any other derived quantity. ORBKIT offers multiple output formats that can be processed by common visualization tools (VMD, Molden, etc.). Additionally, ORBKIT possesses routines to order molecular orbitals computed at different nuclear configurations according to their electronic character and to interpolate the wavefunction between these configurations. The program is open-source under GNU-LGPLv3 license and freely available at https://github.com/orbkit/orbkit/. This article provides an overview of ORBKIT with particular focus on its capabilities and applicability, and includes several example calculations. © 2016 Wiley Periodicals, Inc.

  15. Open-Source Python Modules to Estimate Level Ice Thickness from Ice Charts

    NASA Astrophysics Data System (ADS)

    Geiger, C. A.; Deliberty, T. L.; Bernstein, E. R.; Helfrich, S.

    2012-12-01

    A collaborative research effort between the University of Delaware (UD) and National Ice Center (NIC) addresses the task of providing open-source translations of sea ice stage-of-development into level ice thickness estimates on a 4km grid for the Interactive Multisensor Snow and Ice Mapping System (IMS). The characteristics for stage-of-development are quantified from remote sensing imagery with estimates of level ice thickness categories originating from World Meteorological Organization (WMO) egg coded ice charts codified since the 1970s. Conversions utilize Python scripting modules which transform electronic ice charts with WMO egg code characteristics into five level ice thickness categories, in centimeters, (0-10, 10-30, 30-70, 70-120, >120cm) and five ice types (open water, first year pack ice, fast ice, multiyear ice, and glacial ice with a reserve slot for deformed ice fractions). Both level ice thickness categories and ice concentration fractions are reported with uncertainties propagated based on WMO ice stage ranges which serve as proxy estimates for standard deviation. These products are in preparation for use by NCEP, CMC, and NAVO by 2014 based on their modeling requirements for daily products in near-real time. In addition to development, continuing research tests the value of these estimated products against in situ observations to improve both value and uncertainty estimates.

  16. Web-based application for inverting one-dimensional magnetotelluric data using Python

    NASA Astrophysics Data System (ADS)

    Suryanto, Wiwit; Irnaka, Theodosius Marwan

    2016-11-01

    One-dimensional modeling of magnetotelluric (MT) data has been performed using an online application on a web-based virtual private server. The application was developed with the Python language using the Django framework with HTML and CSS components. The input data, including the apparent resistivity and phase as a function of period or frequency with standard deviation, can be entered through an interactive web page that can be freely accessed at https://komputasi.geofisika.ugm.ac.id. The subsurface models, represented by resistivity as a function of depth, are iteratively improved by changing the model parameters, such as the resistivity and the layer depth, based on the observed apparent resistivity and phase data. The output of the application displayed on the screen presents resistivity as a function of depth and includes the RMS error for each iteration. Synthetic and real data were used in comparative tests of the application's performance, and it is shown that the application developed accurate subsurface resistivity models. Hence, this application can be used for practical one-dimensional modeling of MT data.

  17. Excel2SVM: a stand-alone Python tool for data analysis via support vector machines.

    PubMed

    Hellman, Matthew; Jett, Marti; Hammamieh, Rasha

    2008-03-01

    The creation of classification kernel models to categorize unknown data samples of massive magnitude is an extremely advantageous tool for the scientific community. Excel2SVM, a stand-alone Python mathematical analysis tool, bridges the gap between researchers and computer science to create a simple graphical user interface that allows users to examine data and perform maximal margin classification. This valuable ability to train support vector machines and classify unknown data files is harnessed in this fast and efficient software, granting researchers full access to this complicated, high-level algorithm. Excel2SVM offers the ability to convert data to the proper sparse format while performing a variety of kernel functions along with cost factors/modes, grids, crossvalidation, and several other functions. This program functions with any type of quantitative data making Excel2SVM the ideal tool for analyzing a wide variety of input. The software is free and available at www.bioinformatics.org/excel2svm. A link to the software may also be found at www.kernel-machines.org. This software provides a useful graphical user interface that has proven to provide kernel models with accurate results and data classification through a decision boundary.

  18. Bifrost: a Modular Python/C++ Framework for Development of High-Throughput Data Analysis Pipelines

    NASA Astrophysics Data System (ADS)

    Cranmer, Miles; Barsdell, Benjamin R.; Price, Danny C.; Garsden, Hugh; Taylor, Gregory B.; Dowell, Jayce; Schinzel, Frank; Costa, Timothy; Greenhill, Lincoln J.

    2017-01-01

    Large radio interferometers have data rates that render long-term storage of raw correlator data infeasible, thus motivating development of real-time processing software. For high-throughput applications, processing pipelines are challenging to design and implement. Motivated by science efforts with the Long Wavelength Array, we have developed Bifrost, a novel Python/C++ framework that eases the development of high-throughput data analysis software by packaging algorithms as black box processes in a directed graph. This strategy to modularize code allows astronomers to create parallelism without code adjustment. Bifrost uses CPU/GPU ’circular memory’ data buffers that enable ready introduction of arbitrary functions into the processing path for ’streams’ of data, and allow pipelines to automatically reconfigure in response to astrophysical transient detection or input of new observing settings. We have deployed and tested Bifrost at the latest Long Wavelength Array station, in Sevilleta National Wildlife Refuge, NM, where it handles throughput exceeding 10 Gbps per CPU core.

  19. PyMix - The Python mixture package - a tool for clustering of heterogeneous biological data

    PubMed Central

    2010-01-01

    Background Cluster analysis is an important technique for the exploratory analysis of biological data. Such data is often high-dimensional, inherently noisy and contains outliers. This makes clustering challenging. Mixtures are versatile and powerful statistical models which perform robustly for clustering in the presence of noise and have been successfully applied in a wide range of applications. Results PyMix - the Python mixture package implements algorithms and data structures for clustering with basic and advanced mixture models. The advanced models include context-specific independence mixtures, mixtures of dependence trees and semi-supervised learning. PyMix is licenced under the GNU General Public licence (GPL). PyMix has been successfully used for the analysis of biological sequence, complex disease and gene expression data. Conclusions PyMix is a useful tool for cluster analysis of biological data. Due to the general nature of the framework, PyMix can be applied to a wide range of applications and data sets. PMID:20053276

  20. pyAudioAnalysis: An Open-Source Python Library for Audio Signal Analysis

    PubMed Central

    Giannakopoulos, Theodoros

    2015-01-01

    Audio information plays a rather important role in the increasing digital content that is available today, resulting in a need for methodologies that automatically analyze such content: audio event recognition for home automations and surveillance systems, speech recognition, music information retrieval, multimodal analysis (e.g. audio-visual analysis of online videos for content-based recommendation), etc. This paper presents pyAudioAnalysis, an open-source Python library that provides a wide range of audio analysis procedures including: feature extraction, classification of audio signals, supervised and unsupervised segmentation and content visualization. pyAudioAnalysis is licensed under the Apache License and is available at GitHub (https://github.com/tyiannak/pyAudioAnalysis/). Here we present the theoretical background behind the wide range of the implemented methodologies, along with evaluation metrics for some of the methods. pyAudioAnalysis has been already used in several audio analysis research applications: smart-home functionalities through audio event detection, speech emotion recognition, depression classification based on audio-visual features, music segmentation, multimodal content-based movie recommendation and health applications (e.g. monitoring eating habits). The feedback provided from all these particular audio applications has led to practical enhancement of the library. PMID:26656189

  1. A python-based docking program utilizing a receptor bound ligand shape: PythDock.

    PubMed

    Chung, Jae Yoon; Cho, Seung Joo; Hah, Jung-Mi

    2011-09-01

    PythDock is a heuristic docking program that uses Python programming language with a simple scoring function and a population based search engine. The scoring function considers electrostatic and dispersion/repulsion terms. The search engine utilizes a particle swarm optimization algorithm. A grid potential map is generated using the shape information of a bound ligand within the active site. Therefore, the searching area is more relevant to the ligand binding. To evaluate the docking performance of PythDock, two well-known docking programs (AutoDock and DOCK) were also used with the same data. The accuracy of docked results were measured by the difference of the ligand structure between x-ray structure, and docked pose, i.e., average root mean squared deviation values of the bound ligand were compared for fourteen protein-ligand complexes. Since the number of ligands' rotational flexibility is an important factor affecting the accuracy of a docking, the data set was chosen to have various degrees of flexibility. Although PythDock has a scoring function simpler than those of other programs (AutoDock and DOCK), our results showed that PythDock predicted more accurate poses than both AutoDock4.2 and DOCK6.2. This indicates that PythDock could be a useful tool to study ligand-receptor interactions and could also be beneficial in structure based drug design.

  2. A python module to normalize microarray data by the quantile adjustment method.

    PubMed

    Baber, Ibrahima; Tamby, Jean Philippe; Manoukis, Nicholas C; Sangaré, Djibril; Doumbia, Seydou; Traoré, Sekou F; Maiga, Mohamed S; Dembélé, Doulaye

    2011-06-01

    Microarray technology is widely used for gene expression research targeting the development of new drug treatments. In the case of a two-color microarray, the process starts with labeling DNA samples with fluorescent markers (cyanine 635 or Cy5 and cyanine 532 or Cy3), then mixing and hybridizing them on a chemically treated glass printed with probes, or fragments of genes. The level of hybridization between a strand of labeled DNA and a probe present on the array is measured by scanning the fluorescence of spots in order to quantify the expression based on the quality and number of pixels for each spot. The intensity data generated from these scans are subject to errors due to differences in fluorescence efficiency between Cy5 and Cy3, as well as variation in human handling and quality of the sample. Consequently, data have to be normalized to correct for variations which are not related to the biological phenomena under investigation. Among many existing normalization procedures, we have implemented the quantile adjustment method using the python computer language, and produced a module which can be run via an HTML dynamic form. This module is composed of different functions for data files reading, intensity and ratio computations and visualization. The current version of the HTML form allows the user to visualize the data before and after normalization. It also gives the option to subtract background noise before normalizing the data. The output results of this module are in agreement with the results of other normalization tools.

  3. Simulation of the hyperspectral data from multispectral data using Python programming language

    NASA Astrophysics Data System (ADS)

    Tiwari, Varun; Kumar, Vinay; Pandey, Kamal; Ranade, Rigved; Agarwal, Shefali

    2016-04-01

    Multispectral remote sensing (MRS) sensors have proved their potential in acquiring and retrieving information of Land Use Land (LULC) Cover features in the past few decades. These MRS sensor generally acquire data within limited broad spectral bands i.e. ranging from 3 to 10 number of bands. The limited number of bands and broad spectral bandwidth in MRS sensors becomes a limitation in detailed LULC studies as it is not capable of distinguishing spectrally similar LULC features. On the counterpart, fascinating detailed information available in hyperspectral (HRS) data is spectrally over determined and able to distinguish spectrally similar material of the earth surface. But presently the availability of HRS sensors is limited. This is because of the requirement of sensitive detectors and large storage capability, which makes the acquisition and processing cumbersome and exorbitant. So, there arises a need to utilize the available MRS data for detailed LULC studies. Spectral reconstruction approach is one of the technique used for simulating hyperspectral data from available multispectral data. In the present study, spectral reconstruction approach is utilized for the simulation of hyperspectral data using EO-1 ALI multispectral data. The technique is implemented using python programming language which is open source in nature and possess support for advanced imaging processing libraries and utilities. Over all 70 bands have been simulated and validated using visual interpretation, statistical and classification approach.

  4. The Integrated Plasma Simulator: A Flexible Python Framework for Coupled Multiphysics Simulation

    SciTech Connect

    Foley, Samantha S; Elwasif, Wael R; Bernholdt, David E

    2011-11-01

    High-fidelity coupled multiphysics simulations are an increasingly important aspect of computational science. In many domains, however, there has been very limited experience with simulations of this sort, therefore research in coupled multiphysics often requires computational frameworks with significant flexibility to respond to the changing directions of the physics and mathematics. This paper presents the Integrated Plasma Simulator (IPS), a framework designed for loosely coupled simulations of fusion plasmas. The IPS provides users with a simple component architecture into which a wide range of existing plasma physics codes can be inserted as components. Simulations can take advantage of multiple levels of parallelism supported in the IPS, and can be controlled by a high-level ``driver'' component, or by other coordination mechanisms, such as an asynchronous event service. We describe the requirements and design of the framework, and how they were implemented in the Python language. We also illustrate the flexibility of the framework by providing examples of different types of simulations that utilize various features of the IPS.

  5. pyAudioAnalysis: An Open-Source Python Library for Audio Signal Analysis.

    PubMed

    Giannakopoulos, Theodoros

    2015-01-01

    Audio information plays a rather important role in the increasing digital content that is available today, resulting in a need for methodologies that automatically analyze such content: audio event recognition for home automations and surveillance systems, speech recognition, music information retrieval, multimodal analysis (e.g. audio-visual analysis of online videos for content-based recommendation), etc. This paper presents pyAudioAnalysis, an open-source Python library that provides a wide range of audio analysis procedures including: feature extraction, classification of audio signals, supervised and unsupervised segmentation and content visualization. pyAudioAnalysis is licensed under the Apache License and is available at GitHub (https://github.com/tyiannak/pyAudioAnalysis/). Here we present the theoretical background behind the wide range of the implemented methodologies, along with evaluation metrics for some of the methods. pyAudioAnalysis has been already used in several audio analysis research applications: smart-home functionalities through audio event detection, speech emotion recognition, depression classification based on audio-visual features, music segmentation, multimodal content-based movie recommendation and health applications (e.g. monitoring eating habits). The feedback provided from all these particular audio applications has led to practical enhancement of the library.

  6. Cluster-lensing: A Python Package for Galaxy Clusters and Miscentering

    NASA Astrophysics Data System (ADS)

    Ford, Jes; VanderPlas, Jake

    2016-12-01

    We describe a new open source package for calculating properties of galaxy clusters, including Navarro, Frenk, and White halo profiles with and without the effects of cluster miscentering. This pure-Python package, cluster-lensing, provides well-documented and easy-to-use classes and functions for calculating cluster scaling relations, including mass-richness and mass-concentration relations from the literature, as well as the surface mass density {{Σ }}(R) and differential surface mass density {{Δ }}{{Σ }}(R) profiles, probed by weak lensing magnification and shear. Galaxy cluster miscentering is especially a concern for stacked weak lensing shear studies of galaxy clusters, where offsets between the assumed and the true underlying matter distribution can lead to a significant bias in the mass estimates if not accounted for. This software has been developed and released in a public GitHub repository, and is licensed under the permissive MIT license. The cluster-lensing package is archived on Zenodo. Full documentation, source code, and installation instructions are available at http://jesford.github.io/cluster-lensing/.

  7. NIFTY - Numerical Information Field Theory. A versatile PYTHON library for signal inference

    NASA Astrophysics Data System (ADS)

    Selig, M.; Bell, M. R.; Junklewitz, H.; Oppermann, N.; Reinecke, M.; Greiner, M.; Pachajoa, C.; Enßlin, T. A.

    2013-06-01

    NIFTy (Numerical Information Field Theory) is a software package designed to enable the development of signal inference algorithms that operate regardless of the underlying spatial grid and its resolution. Its object-oriented framework is written in Python, although it accesses libraries written in Cython, C++, and C for efficiency. NIFTy offers a toolkit that abstracts discretized representations of continuous spaces, fields in these spaces, and operators acting on fields into classes. Thereby, the correct normalization of operations on fields is taken care of automatically without concerning the user. This allows for an abstract formulation and programming of inference algorithms, including those derived within information field theory. Thus, NIFTy permits its user to rapidly prototype algorithms in 1D, and then apply the developed code in higher-dimensional settings of real world problems. The set of spaces on which NIFTy operates comprises point sets, n-dimensional regular grids, spherical spaces, their harmonic counterparts, and product spaces constructed as combinations of those. The functionality and diversity of the package is demonstrated by a Wiener filter code example that successfully runs without modification regardless of the space on which the inference problem is defined. NIFTy homepage http://www.mpa-garching.mpg.de/ift/nifty/; Excerpts of this paper are part of the NIFTy source code and documentation.

  8. A three-dimensional kinematic analysis of tongue flicking in Python molurus.

    PubMed

    de Groot, Jurriaan H; van der Sluijs, Inke; Snelderwaard, Peter Ch; van Leeuwen, Johan L

    2004-02-01

    The forked snake tongue is a muscular organ without hard skeletal support. A functional interpretation of the variable arrangement of the intrinsic muscles along the tongue requires a quantitative analysis of the motion performance during tongue protrusion and flicking. Therefore, high-speed fluoroscopy and high-speed stereo photogrammetry were used to analyse the three-dimensional shape changes of the tongue in Python molurus bivittatus (Boidae). The posterior protruding part of the tongue elongated up to 130% while the flicking anterior portion elongated maximally 60%. The differences in tongue strains relate to the absence or presence, respectively, of longitudinal muscle fibres in the peripheral tongue. Maximum overall protrusion velocity (4.3 m s(-1)) occurred initially when the tongue tip left the mouth. Maximum tongue length of approximately 0.01 body length (20 mm) was reached during the first tongue flick. These observations are discussed within the scope of the biomechanical constraints of hydrostatic tongue protrusion: a negative forward pressure gradient, longitudinal tongue compliance and axial tongue stiffness. The three-dimensional deformation varied along the tongue with a mean curvature of 0.06 mm(-1) and a maximum value of 0.5 mm(-1). At the basis of the anterior forked portion of the tongue tips, extreme curvatures up to 2.0 mm(-1) were observed. These quantitative results support previously proposed inferences about a hydrostatic elongation mechanism and may serve to evaluate future dynamic models of tongue flicking.

  9. Dispel4py: An Open-Source Python library for Data-Intensive Seismology

    NASA Astrophysics Data System (ADS)

    Filgueira, Rosa; Krause, Amrey; Spinuso, Alessandro; Klampanos, Iraklis; Danecek, Peter; Atkinson, Malcolm

    2015-04-01

    Scientific workflows are a necessary tool for many scientific communities as they enable easy composition and execution of applications on computing resources while scientists can focus on their research without being distracted by the computation management. Nowadays, scientific communities (e.g. Seismology) have access to a large variety of computing resources and their computational problems are best addressed using parallel computing technology. However, successful use of these technologies requires a lot of additional machinery whose use is not straightforward for non-experts: different parallel frameworks (MPI, Storm, multiprocessing, etc.) must be used depending on the computing resources (local machines, grids, clouds, clusters) where applications are run. This implies that for achieving the best applications' performance, users usually have to change their codes depending on the features of the platform selected for running them. This work presents dispel4py, a new open-source Python library for describing abstract stream-based workflows for distributed data-intensive applications. Special care has been taken to provide dispel4py with the ability to map abstract workflows to different platforms dynamically at run-time. Currently dispel4py has four mappings: Apache Storm, MPI, multi-threading and sequential. The main goal of dispel4py is to provide an easy-to-use tool to develop and test workflows in local resources by using the sequential mode with a small dataset. Later, once a workflow is ready for long runs, it can be automatically executed on different parallel resources. dispel4py takes care of the underlying mappings by performing an efficient parallelisation. Processing Elements (PE) represent the basic computational activities of any dispel4Py workflow, which can be a seismologic algorithm, or a data transformation process. For creating a dispel4py workflow, users only have to write very few lines of code to describe their PEs and how they are

  10. pyLIDEM: A Python-Based Tool to Delineate Coastal Watersheds Using LIDAR Data

    NASA Astrophysics Data System (ADS)

    O'Banion, R.; Alameddine, I.; Gronewold, A.; Reckhow, K.

    2008-12-01

    Accurately identifying the boundary of a watershed is one of the most fundamental and important steps in any hydrological assessment. Representative applications include defining a study area, predicting overland flow, estimating groundwater infiltration, modeling pollutant accumulation and wash-off rates, and evaluating effectiveness of pollutant mitigation measures. The United States Environmental Protection Agency (USEPA) Total Maximum Daily Load (TMDL) program, the most comprehensive water quality management program in the United States (US), is just one example of an application in which accurate and efficient watershed delineation tools play a critical role. For example, many impaired water bodies currently being addressed through the TMDL program drain small coastal watersheds with relatively flat terrain, making watershed delineation particularly challenging. Most of these TMDL studies use 30-meter digital elevation models (DEMs) that rarely capture all of the small elevation changes in coastal watersheds, leading to errors not only in watershed boundary delineation, but in subsequent model predictions (such as watershed runoff flow and pollutant deposition rate predictions) for which watershed attributes are key inputs. Manually delineating these low-relief coastal watersheds through the use of expert knowledge of local water flow patterns, often produces relatively accurate (and often more accurate) watershed boundaries as compared to the boundaries generated by the 30-meter DEMs. Yet, manual delineation is a costly and time consuming procedure that is often not opted for. There is a growing need, therefore, particularly to address the ongoing needs of the TMDL program (and similar environmental management programs), for software tools which can utilize high resolution topography data to more accurately delineate coastal watersheds. Here, we address this need by developing pyLIDEM (python LIdar DEM), a python-based tool which processes bare earth high

  11. Akkermansia glycaniphila sp. nov., an anaerobic mucin-degrading bacterium isolated from reticulated python faeces.

    PubMed

    Ouwerkerk, Janneke P; Aalvink, Steven; Belzer, Clara; de Vos, Willem M

    2016-11-01

    A Gram-stain-negative, non-motile, strictly anaerobic, oval-shaped, non-spore-forming bacterium (strain PytT) was isolated from reticulated python faeces. Strain PytT was capable of using mucin as sole carbon, energy and nitrogen source. Cells could grow singly, in pairs, and were also found to aggregate. Scanning electron microscopy revealed the presence of filamentous structures connecting individual bacterial cells. Strain PytT could grow on a limited number of single sugars, including N-acetylglucosamine, N-acetylgalactosamine, glucose, lactose and galactose, but only when a plentiful protein source was provided. Phylogenetic analysis based on 16S rRNA gene sequencing showed strain PytT to belong to the Verrucomicrobiae class I, family Akkermansiaceae, genus Akkermansia, with Akkermansia muciniphila MucT as the closest relative (94.4 % sequence similarity). DNA-DNA hybridization revealed low relatedness of 28.3 % with A. muciniphila MucT. The G+C content of DNA from strain PytT was 58.2 mol%. The average nucleotide identity (ANI) of the genome of strain PytT compared to the genome of strain MucT was 79.7 %. Chemotaxonomic data supported the affiliation of strain PytT to the genus Akkermansia. Based on phenotypic, phylogenetic and genetic characteristics, strain PytT represents a novel species of the genus Akkermansia, for which the name Akkermansia glycaniphila sp. nov. is proposed. The type strain is PytT (=DSM 100705T=CIP 110913T).

  12. Multi-basin, Multi-sector Drought Economic Impact Model in Python: Development and Applications

    NASA Astrophysics Data System (ADS)

    Gutenson, J. L.; Zhu, L.; Ernest, A. N. S.; Oubeidillah, A.; Bearden, B.; Johnson, T. G.

    2015-12-01

    Drought is one of the most economically disastrous natural hazards, one whose impacts are exacerbated by the lack of abrupt onset and offset that define tornados and hurricanes. In the United States, about 30 billion dollars losses is caused by drought in 2012, resulting in widespread economic impacts for societies, industries, agriculture, and recreation. And in California, the drought cost statewide economic losses about 2.2 billion, with a total loss of 17,100 seasonal and part-time jobs. Driven by a variety of factors including climate change, population growth, increased water demands, alteration to land cover, drought occurs widely all over the world. Drought economic consequence assessment tool are greatly needed to allow decision makers and stakeholders to anticipate and manage effectively. In this study, current drought economic impact modeling methods were reviewed. Most of these models only deal with the impact in the agricultural sector with a focus on a single basin; few of these models analyze long term impact. However, drought impacts are rarely restricted to basin boundaries, and cascading economic impacts are likely to be significant. A holistic approach to multi-basin, multi-sector drought economic impact assessment is needed.In this work, we developed a new model for drought economic impact assessment, Drought Economic Impact Model in Python (PyDEM). This model classified all business establishments into thirteen categories based on NAICS, and using a continuous dynamic social accounting matrix approach, coupled with calculation of the indirect consequences for the local and regional economies and the various resilience. In addition, Environmental Policy Integrated Climate model was combined for analyzing drought caused soil erosion together with agriculture production, and then the long term impacts of drought were achieved. A visible output of this model was presented in GIS. In this presentation, Choctawhatchee-Pea-Yellow River Basins, Alabama

  13. Structural and performance costs of reproduction in a pure capital breeder, the Children's python Antaresia childreni.

    PubMed

    Lourdais, Olivier; Lorioux, Sophie; DeNardo, Dale F

    2013-01-01

    Females often manage the high energy demands associated with reproduction by accumulating and storing energy in the form of fat before initiating their reproductive effort. However, fat stores cannot satisfy all reproductive resource demands, which include considerable investment of amino acids (e.g., for the production of yolk proteins or gluconeogenesis). Because capital breeders generally do not eat during reproduction, these amino acids must come from internal resources, typically muscle proteins. Although the energetic costs of reproduction have been fairly well studied, there are limited data on structural and performance costs associated with the muscle degradation required to meet amino acid demands. Thus, we examined structural changes (epaxial muscle width) and performance costs (constriction and strength) over the course of reproduction in a pure capital breeder, the children's python (Antaresia childreni). We found that both egg production (i.e., direct resource allocation) and maternal care (egg brooding) induce muscle catabolism and affect performance of the female. Although epaxial muscle loss was minimal in nonreproductive females, it reached up to 22% (in females after oviposition) and 34% (in females after brooding) of initial muscle width. Interestingly, we found that individuals with higher initial muscular condition allocated more of their muscle into reproduction. The amount of muscle loss was significantly linked to clutch mass, underscoring the role of structural protein in egg production. Egg brooding significantly increased proteolysis and epaxial loss despite no direct allocation to the offspring. Muscle loss was linked to a significant reduction in performance in postreproductive females. Overall, these results demonstrate that capital-breeding females experience dramatic costs that consume structural resources and jeopardize performance.

  14. Nipype: A Flexible, Lightweight and Extensible Neuroimaging Data Processing Framework in Python

    PubMed Central

    Gorgolewski, Krzysztof; Burns, Christopher D.; Madison, Cindee; Clark, Dav; Halchenko, Yaroslav O.; Waskom, Michael L.; Ghosh, Satrajit S.

    2011-01-01

    Current neuroimaging software offer users an incredible opportunity to analyze their data in different ways, with different underlying assumptions. Several sophisticated software packages (e.g., AFNI, BrainVoyager, FSL, FreeSurfer, Nipy, R, SPM) are used to process and analyze large and often diverse (highly multi-dimensional) data. However, this heterogeneous collection of specialized applications creates several issues that hinder replicable, efficient, and optimal use of neuroimaging analysis approaches: (1) No uniform access to neuroimaging analysis software and usage information; (2) No framework for comparative algorithm development and dissemination; (3) Personnel turnover in laboratories often limits methodological continuity and training new personnel takes time; (4) Neuroimaging software packages do not address computational efficiency; and (5) Methods sections in journal articles are inadequate for reproducing results. To address these issues, we present Nipype (Neuroimaging in Python: Pipelines and Interfaces; http://nipy.org/nipype), an open-source, community-developed, software package, and scriptable library. Nipype solves the issues by providing Interfaces to existing neuroimaging software with uniform usage semantics and by facilitating interaction between these packages using Workflows. Nipype provides an environment that encourages interactive exploration of algorithms, eases the design of Workflows within and between packages, allows rapid comparative development of algorithms and reduces the learning curve necessary to use different packages. Nipype supports both local and remote execution on multi-core machines and clusters, without additional scripting. Nipype is Berkeley Software Distribution licensed, allowing anyone unrestricted usage. An open, community-driven development philosophy allows the software to quickly adapt and address the varied needs of the evolving neuroimaging community, especially in the context of increasing demand for

  15. pyGrav, a Python-based program for handling and processing relative gravity data

    NASA Astrophysics Data System (ADS)

    Hector, Basile; Hinderer, Jacques

    2016-06-01

    pyGrav is a Python-based open-source software dedicated to the complete processing of relative-gravity data. It is particularly suited for time-lapse gravity surveys where high precision is sought. Its purpose is to bind together single-task processing codes in a user-friendly interface for handy and fast treatment of raw gravity data from many stations of a network. The intuitive object-based implementation allows to easily integrate additional functions (reading/writing routines, processing schemes, data plots) related to the appropriate object (a station, a loop, or a survey). This makes pyGrav an evolving tool. Raw data can be corrected for tides and air pressure effects. The data selection step features a double table-plot graphical window with either manual or automatic selection according to specific thresholds on data channels (tilts, gravity values, gravity standard deviation, duration of measurements, etc.). Instrumental drifts and gravity residuals are obtained by least square analysis of the dataset. This first step leads to the gravity simple differences between a reference point and any point of the network. When different repetitions of the network are done, the software computes then the gravity double differences and associated errors. The program has been tested on two specific case studies: a large dataset acquired for the study of water storage changes on a small catchment in West Africa, and a dataset operated and processed by several different users for geothermal studies in northern Alsace, France. In both cases, pyGrav proved to be an efficient and easy-to-use solution for the effective processing of relative-gravity data.

  16. Preliminary Third Year Results from the Python Microwave Background Anisotropy Experiment

    NASA Astrophysics Data System (ADS)

    Platt, S. R.; Dragovan, M.; Ruhl, J. E.; Kovak, J.

    1995-05-01

    We report preliminary results from the third year of observations from Amundsen-Scott South Pole Station with the Python microwave background anisotropy experiment. The instrument is a five channel bolometer array, with detectors operating at 50 mK, cooled by a hybrid (3) He-Adiabatic demagnetization refrigerator. Single-mode waveguide optics center the passband at 90 GHz, and couple the detector system to the 0.75m off-axis parabolic primary mirror of the telescope. The measured beamwidths are 0.75(deg) . We combine a fast 5 Hz 3-beam chop of a vertical flat plate with slow .025 Hz telescope beamswitches to produce a gradient-free 4-beam pattern on the sky. The chop amplitude is 2.75(deg) . In each of the first two years of observations with this system we scanned the same 22 fields, centered at alpha = 23.32, delta = -49.5. In both years we detected statistically significant fluctuations with an amplitude of Delta T / T ~ 3.3 times 10(-5) for an anisotropy model with a Gaussian autocorrelation function with a coherence angle of theta_c = 1(deg) . Our new results incorporate observations made in December 1994 that intersperse these fields and sample more fully this region of sky. The entire three year data set will be used to make a difference map of the structure of anisotropy at intermediate angular scales across a 6(deg) times 22(deg) region of sky. This work was supported by the National Science Foundation under a cooperative agreement with the Center for Astrophysical Research in Antarctica (CARA), grant number NSF OPP 89-20223, M.D.'s PYI grant NSF AST 90-57089, and the James S. McDonnell Foundation. CARA is a National Science Foundation Science and Technology Center.

  17. Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in python.

    PubMed

    Gorgolewski, Krzysztof; Burns, Christopher D; Madison, Cindee; Clark, Dav; Halchenko, Yaroslav O; Waskom, Michael L; Ghosh, Satrajit S

    2011-01-01

    Current neuroimaging software offer users an incredible opportunity to analyze their data in different ways, with different underlying assumptions. Several sophisticated software packages (e.g., AFNI, BrainVoyager, FSL, FreeSurfer, Nipy, R, SPM) are used to process and analyze large and often diverse (highly multi-dimensional) data. However, this heterogeneous collection of specialized applications creates several issues that hinder replicable, efficient, and optimal use of neuroimaging analysis approaches: (1) No uniform access to neuroimaging analysis software and usage information; (2) No framework for comparative algorithm development and dissemination; (3) Personnel turnover in laboratories often limits methodological continuity and training new personnel takes time; (4) Neuroimaging software packages do not address computational efficiency; and (5) Methods sections in journal articles are inadequate for reproducing results. To address these issues, we present Nipype (Neuroimaging in Python: Pipelines and Interfaces; http://nipy.org/nipype), an open-source, community-developed, software package, and scriptable library. Nipype solves the issues by providing Interfaces to existing neuroimaging software with uniform usage semantics and by facilitating interaction between these packages using Workflows. Nipype provides an environment that encourages interactive exploration of algorithms, eases the design of Workflows within and between packages, allows rapid comparative development of algorithms and reduces the learning curve necessary to use different packages. Nipype supports both local and remote execution on multi-core machines and clusters, without additional scripting. Nipype is Berkeley Software Distribution licensed, allowing anyone unrestricted usage. An open, community-driven development philosophy allows the software to quickly adapt and address the varied needs of the evolving neuroimaging community, especially in the context of increasing demand for

  18. Toward a Tree-of-Life for the boas and pythons: multilocus species-level phylogeny with unprecedented taxon sampling.

    PubMed

    Graham Reynolds, R; Niemiller, Matthew L; Revell, Liam J

    2014-02-01

    Snakes in the families Boidae and Pythonidae constitute some of the most spectacular reptiles and comprise an enormous diversity of morphology, behavior, and ecology. While many species of boas and pythons are familiar, taxonomy and evolutionary relationships within these families remain contentious and fluid. A major effort in evolutionary and conservation biology is to assemble a comprehensive Tree-of-Life, or a macro-scale phylogenetic hypothesis, for all known life on Earth. No previously published study has produced a species-level molecular phylogeny for more than 61% of boa species or 65% of python species. Using both novel and previously published sequence data, we have produced a species-level phylogeny for 84.5% of boid species and 82.5% of pythonid species, contextualized within a larger phylogeny of henophidian snakes. We obtained new sequence data for three boid, one pythonid, and two tropidophiid taxa which have never previously been included in a molecular study, in addition to generating novel sequences for seven genes across an additional 12 taxa. We compiled an 11-gene dataset for 127 taxa, consisting of the mitochondrial genes CYTB, 12S, and 16S, and the nuclear genes bdnf, bmp2, c-mos, gpr35, rag1, ntf3, odc, and slc30a1, totaling up to 7561 base pairs per taxon. We analyzed this dataset using both maximum likelihood and Bayesian inference and recovered a well-supported phylogeny for these species. We found significant evidence of discordance between taxonomy and evolutionary relationships in the genera Tropidophis, Morelia, Liasis, and Leiopython, and we found support for elevating two previously suggested boid species. We suggest a revised taxonomy for the boas (13 genera, 58 species) and pythons (8 genera, 40 species), review relationships between our study and the many other molecular phylogenetic studies of henophidian snakes, and present a taxonomic database and alignment which may be easily used and built upon by other researchers.

  19. Application of MATLAB and Python optimizers to two case studies involving groundwater flow and contaminant transport modeling

    NASA Astrophysics Data System (ADS)

    Matott, L. Shawn; Leung, Kenny; Sim, Junyoung

    2011-11-01

    One approach for utilizing geoscience models for management or policy analysis is via a simulation-based optimization framework—where an underlying model is linked with an optimization search algorithm. In this regard, MATLAB and Python are high-level programming languages that implement numerous optimization routines, including gradient-based, heuristic, and direct-search optimizers. The ever-expanding number of available algorithms makes it challenging for practitioners to identify optimizers that deliver good performance when applied to problems of interest. Thus, the primary contribution of this paper is to present a series of numerical experiments that investigated the performance of various MATLAB and Python optimizers. The experiments considered two simulation-based optimization case studies involving groundwater flow and contaminant transport. One case study examined the design of a pump-and-treat system for groundwater remediation, while the other considered least-squares calibration of a model of strontium (Sr) transport. Using these case studies, the performance of 12 different MATLAB and Python optimizers was compared. Overall, the Hooke-Jeeves direct search algorithm yielded the best performance in terms of identifying least-cost and best-fit solutions to the design and calibration problems, respectively. The IFFCO (implicit filtering for constrained optimization) direct search algorithm and the dynamically dimensioned search (DDS) heuristic algorithm also consistently yielded good performance and were up to 80% more efficient than Hooke-Jeeves when applied to the pump-and-treat problem. These results provide empirical evidence that, relative to gradient- and population-based alternatives, direct search algorithms and heuristic variants, such as DDS, are good choices for application to simulation-based optimization problems involving groundwater management.

  20. Distribution of lipids from the yolk to the tissues during development of the water python (Liasis fuscus).

    PubMed

    Speake, B K; Thompson, M B; Thacker, F E; Bedford, G S

    2003-09-01

    Energy metabolism during embryonic development of snakes differs in several respects from the patterns displayed by other reptiles. There are, however, no previous reports describing the main energy source for development, the yolk lipids, in snake eggs. There is also no information on the distribution of yolk fatty acids to the tissues during snake development. In eggs of the water python ( Liasis fuscus), we report that triacylglycerol, phospholipid, cholesteryl ester and free cholesterol, respectively, form 70.3%, 14.1%, 5.7% and 2.1% of the total lipid. The main polyunsaturate of the yolk lipid classes is 18:2n-6. The yolk phospholipid contains 20:4n-6 and 22:6n-3 at 13.0% and 3.6% (w/w), respectively. Approximately 10% and 30% of the initial egg lipids are respectively recovered in the residual yolk and the fat body of the hatchling. A major function of yolk lipid is, therefore, to provision the neonate with large energy reserves. The proportion of 22:6n-3 in brain phospholipid of the hatchling is 11.1% (w/w): this represents only 0.24% of the amount of 22:6n-3 originally present in the egg. This also contrasts with values for free-living avian species where the proportion of DHA in neonatal brain phospholipid is 16-19%. In the liver of the newly hatched python, triacylglycerol, phospholipid and cholesteryl ester, respectively, form 68.2%, 7.7% and 14.3% of total lipid. This contrasts with embryos of birds where cholesteryl ester forms up to 80% of total liver lipid and suggests that the mechanism of lipid transfer in the water python embryo differs in some respects from the avian situation.

  1. Topographica: Building and Analyzing Map-Level Simulations from Python, C/C++, MATLAB, NEST, or NEURON Components.

    PubMed

    Bednar, James A

    2009-01-01

    Many neural regions are arranged into two-dimensional topographic maps, such as the retinotopic maps in mammalian visual cortex. Computational simulations have led to valuable insights about how cortical topography develops and functions, but further progress has been hindered by the lack of appropriate tools. It has been particularly difficult to bridge across levels of detail, because simulators are typically geared to a specific level, while interfacing between simulators has been a major technical challenge. In this paper, we show that the Python-based Topographica simulator makes it straightforward to build systems that cross levels of analysis, as well as providing a common framework for evaluating and comparing models implemented in other simulators. These results rely on the general-purpose abstractions around which Topographica is designed, along with the Python interfaces becoming available for many simulators. In particular, we present a detailed, general-purpose example of how to wrap an external spiking PyNN/NEST simulation as a Topographica component using only a dozen lines of Python code, making it possible to use any of the extensive input presentation, analysis, and plotting tools of Topographica. Additional examples show how to interface easily with models in other types of simulators. Researchers simulating topographic maps externally should consider using Topographica's analysis tools (such as preference map, receptive field, or tuning curve measurement) to compare results consistently, and for connecting models at different levels. This seamless interoperability will help neuroscientists and computational scientists to work together to understand how neurons in topographic maps organize and operate.

  2. Prey targeting by the infrared-imaging snake Python molurus: effects of experimental and congenital visual deprivation.

    PubMed

    Grace, M S; Woodward, O M; Church, D R; Calisch, G

    2001-02-15

    Boid and crotaline snakes possess two distinct types of organ evolved to image radiant electromagnetic energy: the lateral eye, which responds to visible light, and the pit organ, which responds to infrared radiation. While infrared imaging may allow accurate predatory targeting in complete absence of visual information, both infrared and visual information are probably normally involved in prey targeting. We examined the roles of vision and infrared imaging in Python molurus predatory performance under conditions of (1) high visual contrast; (2) very low visual contrast; (3) complete blinding; (4) experimental monocular occlusion; and (5) congenital monocularity. Normally sighted pythons were equally successful at targeting white (BALB/c) and black (C57BL6/J) mice (Mus domesticus) against a black background. Binocularly occluded snakes exhibited strike angles and distances similar to non-occluded snakes, but exhibited lower strike success, suggesting that high visible contrast is not required for accurate targeting, but that precise targeting depends to some degree upon visual information. Strike angles, distances and latencies were indistinguishable between snakes subjected to experimental monocular occlusion and normally sighted snakes. However, snakes congenitally lacking one eye preferentially targeted on the sighted side. Thus, accurate targeting of highly mobile homeothermic prey by Python can be accomplished with little or no visual information, but performance can be affected by complete visual deprivation or by alteration of visual input during development. The developmental effects of early visual deprivation in this system provide a novel opportunity to investigate the neural integration of two electromagnetic radiation-imaging systems in a single animal.

  3. Annotated checklist of the recent and extinct pythons (Serpentes, Pythonidae), with notes on nomenclature, taxonomy, and distribution

    PubMed Central

    Schleip, Wulf D.; O’Shea, Mark

    2010-01-01

    Abstract McDiarmid et al. (1999) published the first part of their planned taxonomic catalog of the snakes of the world. Since then, several new python taxa have been described in both the scientific literature and non-peer-reviewed publications. This checklist evaluates the nomenclatural status of the names and discusses the taxonomic status of the new taxa, and aims to continue the work of McDiarmid et al. (1999) for the family Pythonidae, covering the period 1999 to 2010. Numerous new taxa are listed, and where appropriate recent synonymies are included and annotations are made. A checklist and a taxonomic identification key of valid taxa are provided. PMID:21594030

  4. Combustion-chamber Performance Characteristics of a Python Turbine-propeller Engine Investigated in Altitude Wind Tunnel

    NASA Technical Reports Server (NTRS)

    Campbell, Carl E

    1951-01-01

    Combustion-chamber performance characteristics of a Python turbine-propeller engine were determined from investigation of a complete engine over a range of engine speeds and shaft horsepowers at simulated altitudes. Results indicated the effect of engine operating conditions and altitude on combustion efficiency and combustion-chamber total pressure losses. Performance of this vaporizing type combustion chamber was also compared with several atomizing type combustion chambers. Over the range of test conditions investigated, combustion efficiency varied from approximately 0.95 to 0.99.

  5. Brainlab: A Python Toolkit to Aid in the Design, Simulation, and Analysis of Spiking Neural Networks with the NeoCortical Simulator.

    PubMed

    Drewes, Rich; Zou, Quan; Goodman, Philip H

    2009-01-01

    Neuroscience modeling experiments often involve multiple complex neural network and cell model variants, complex input stimuli and input protocols, followed by complex data analysis. Coordinating all this complexity becomes a central difficulty for the experimenter. The Python programming language, along with its extensive library packages, has emerged as a leading "glue" tool for managing all sorts of complex programmatic tasks. This paper describes a toolkit called Brainlab, written in Python, that leverages Python's strengths for the task of managing the general complexity of neuroscience modeling experiments. Brainlab was also designed to overcome the major difficulties of working with the NCS (NeoCortical Simulator) environment in particular. Brainlab is an integrated model-building, experimentation, and data analysis environment for the powerful parallel spiking neural network simulator system NCS.

  6. Giant Constrictors: Biological and Management Profiles and an Establishment Risk Assessment for Nine Large Species of Pythons, Anacondas, and the Boa Constrictor

    USGS Publications Warehouse

    Reed, Robert N.; Rodda, Gordon H.

    2009-01-01

    Giant Constrictors: Biological and Management Profiles and an Establishment Risk Assessment for Nine Large Species of Pythons, Anacondas, and the Boa Constrictor, estimates the ecological risks associated with colonization of the United States by nine large constrictors. The nine include the world's four largest snake species (Green Anaconda, Eunectes murinus; Indian or Burmese Python, Python molurus; Northern African Python, Python sebae; and Reticulated Python, Broghammerus reticulatus), the Boa Constrictor (Boa constrictor), and four species that are ecologically or visually similar to one of the above (Southern African Python, Python natalensis; Yellow Anaconda, Eunectes notaeus; DeSchauensee's Anaconda, Eunectes deschauenseei; and Beni Anaconda, Eunectes beniensis). At present, the only probable pathway by which these species would become established in the United States is the pet trade. Although importation for the pet trade involves some risk that these animals could become established as exotic or invasive species, it does not guarantee such establishment. Federal regulators have the task of appraising the importation risks and balancing those risks against economic, social, and ecological benefits associated with the importation. The risk assessment quantifies only the ecological risks, recognizing that ecosystem processes are complex and only poorly understood. The risk assessment enumerates the types of economic impacts that may be experienced, but leaves quantification of economic costs to subsequent studies. Primary factors considered in judging the risk of establishment were: (1) history of establishment in other countries, (2) number of each species in commerce, (3) suitability of U.S. climates for each species, and (4) natural history traits, such as reproductive rate and dispersal ability, that influence the probability of establishment, spread, and impact. In addition, the risk assessment reviews all management tools for control of invasive giant

  7. Novel phospholipase A2 inhibitors from python serum are potent peptide antibiotics.

    PubMed

    Samy, Ramar Perumal; Thwin, Maung Maung; Stiles, Brad G; Satyanarayana-Jois, Seetharama; Chinnathambi, Arunachalam; Zayed, M E; Alharbi, Sulaiman Ali; Siveen, Kodappully Sivaraman; Sikka, Sakshi; Kumar, Alan Prem; Sethi, Gautam; Lim, Lina Hsiu Kim

    2015-04-01

    Antimicrobial peptides (AMPs) play a vital role in defense against resistant bacteria. In this study, eight different AMPs synthesized from Python reticulatus serum protein were tested for bactericidal activity against various Gram-positive and Gram-negative bacteria (Staphylococcus aureus, Burkholderia pseudomallei (KHW and TES strains), and Proteus vulgaris) using a disc-diffusion method (20 μg/disc). Among the tested peptides, phospholipase A2 inhibitory peptide (PIP)-18[59-76], β-Asp65-PIP[59-67], D-Ala66-PNT.II, and D60,65E-PIP[59-67] displayed the most potent bactericidal activity against all tested pathogens in a dose-dependent manner (100-6.8 μg/ml), with a remarkable activity noted against S. aureus at 6.8 μg/ml dose within 6 h of incubation. Determination of minimum inhibitory concentrations (MICs) by a micro-broth dilution method at 100-3.125 μg/ml revealed that PIP-18[59-76], β-Asp65-PIP[59-67] and D-Ala66-PNT.II peptides exerted a potent inhibitory effect against S. aureus and B. pseudomallei (KHW) (MICs 3.125 μg/ml), while a much less inhibitory potency (MICs 12.5 μg/ml) was noted for β-Asp65-PIP[59-67] and D-Ala66-PNT.II peptides against B. pseudomallei (TES). Higher doses of peptides had no effect on the other two strains (i.e., Klebsiella pneumoniae and Streptococcus pneumoniae). Overall, PIP-18[59-76] possessed higher antimicrobial activity than that of chloramphenicol (CHL), ceftazidime (CF) and streptomycin (ST) (30 μg/disc). When the two most active peptides, PIP-18[59-76] and β-Asp65-PIP[59-67], were applied topically at a 150 mg/kg dose for testing wound healing activity in a mouse model of S. aureus infection, the former accelerates faster wound healing than the latter peptide at 14 days post-treatment. The western blot data suggest that the topical application of peptides (PIP-18[59-67] and β-Asp65-PIP[59-67]) modulates NF-kB mediated wound repair in mice with relatively little haemolytic (100-1.56 μg/ml) and cytotoxic (1000

  8. A Python Implementation of an Intermediate-Level Tropical Circulation Model and Implications for How Modeling Science is Done

    NASA Astrophysics Data System (ADS)

    Lin, J. W. B.

    2015-12-01

    Historically, climate models have been developed incrementally and in compiled languages like Fortran. While the use of legacy compiledlanguages results in fast, time-tested code, the resulting model is limited in its modularity and cannot take advantage of functionalityavailable with modern computer languages. Here we describe an effort at using the open-source, object-oriented language Pythonto create more flexible climate models: the package qtcm, a Python implementation of the intermediate-level Neelin-Zeng Quasi-Equilibrium Tropical Circulation model (QTCM1) of the atmosphere. The qtcm package retains the core numerics of QTCM1, written in Fortran, to optimize model performance but uses Python structures and utilities to wrap the QTCM1 Fortran routines and manage model execution. The resulting "mixed language" modeling package allows order and choice of subroutine execution to be altered at run time, and model analysis and visualization to be integrated in interactively with model execution at run time. This flexibility facilitates more complex scientific analysis using less complex code than would be possible using traditional languages alone and provides tools to transform the traditional "formulate hypothesis → write and test code → run model → analyze results" sequence into a feedback loop that can be executed automatically by the computer.

  9. Rapid changes in gene expression direct rapid shifts in intestinal form and function in the Burmese python after feeding.

    PubMed

    Andrew, Audra L; Card, Daren C; Ruggiero, Robert P; Schield, Drew R; Adams, Richard H; Pollock, David D; Secor, Stephen M; Castoe, Todd A

    2015-05-01

    Snakes provide a unique and valuable model system for studying the extremes of physiological remodeling because of the ability of some species to rapidly upregulate organ form and function upon feeding. The predominant model species used to study such extreme responses has been the Burmese python because of the extreme nature of postfeeding response in this species. We analyzed the Burmese python intestine across a time series, before, during, and after feeding to understand the patterns and timing of changes in gene expression and their relationship to changes in intestinal form and function upon feeding. Our results indicate that >2,000 genes show significant changes in expression in the small intestine following feeding, including genes involved in intestinal morphology and function (e.g., hydrolases, microvillus proteins, trafficking and transport proteins), as well as genes involved in cell division and apoptosis. Extensive changes in gene expression occur surprisingly rapidly, within the first 6 h of feeding, coincide with changes in intestinal morphology, and effectively return to prefeeding levels within 10 days. Collectively, our results provide an unprecedented portrait of parallel changes in gene expression and intestinal morphology and physiology on a scale that is extreme both in the magnitude of changes, as well as in the incredibly short time frame of these changes, with up- and downregulation of expression and function occurring in the span of 10 days. Our results also identify conserved vertebrate signaling pathways that modulate these responses, which may suggest pathways for therapeutic modulation of intestinal function in humans.

  10. Graph-based active learning of agglomeration (GALA): a Python library to segment 2D and 3D neuroimages.

    PubMed

    Nunez-Iglesias, Juan; Kennedy, Ryan; Plaza, Stephen M; Chakraborty, Anirban; Katz, William T

    2014-01-01

    The aim in high-resolution connectomics is to reconstruct complete neuronal connectivity in a tissue. Currently, the only technology capable of resolving the smallest neuronal processes is electron microscopy (EM). Thus, a common approach to network reconstruction is to perform (error-prone) automatic segmentation of EM images, followed by manual proofreading by experts to fix errors. We have developed an algorithm and software library to not only improve the accuracy of the initial automatic segmentation, but also point out the image coordinates where it is likely to have made errors. Our software, called gala (graph-based active learning of agglomeration), improves the state of the art in agglomerative image segmentation. It is implemented in Python and makes extensive use of the scientific Python stack (numpy, scipy, networkx, scikit-learn, scikit-image, and others). We present here the software architecture of the gala library, and discuss several designs that we consider would be generally useful for other segmentation packages. We also discuss the current limitations of the gala library and how we intend to address them.

  11. Rapid changes in gene expression direct rapid shifts in intestinal form and function in the Burmese python after feeding

    PubMed Central

    Andrew, Audra L.; Card, Daren C.; Ruggiero, Robert P.; Schield, Drew R.; Adams, Richard H.; Pollock, David D.; Secor, Stephen M.

    2015-01-01

    Snakes provide a unique and valuable model system for studying the extremes of physiological remodeling because of the ability of some species to rapidly upregulate organ form and function upon feeding. The predominant model species used to study such extreme responses has been the Burmese python because of the extreme nature of postfeeding response in this species. We analyzed the Burmese python intestine across a time series, before, during, and after feeding to understand the patterns and timing of changes in gene expression and their relationship to changes in intestinal form and function upon feeding. Our results indicate that >2,000 genes show significant changes in expression in the small intestine following feeding, including genes involved in intestinal morphology and function (e.g., hydrolases, microvillus proteins, trafficking and transport proteins), as well as genes involved in cell division and apoptosis. Extensive changes in gene expression occur surprisingly rapidly, within the first 6 h of feeding, coincide with changes in intestinal morphology, and effectively return to prefeeding levels within 10 days. Collectively, our results provide an unprecedented portrait of parallel changes in gene expression and intestinal morphology and physiology on a scale that is extreme both in the magnitude of changes, as well as in the incredibly short time frame of these changes, with up- and downregulation of expression and function occurring in the span of 10 days. Our results also identify conserved vertebrate signaling pathways that modulate these responses, which may suggest pathways for therapeutic modulation of intestinal function in humans. PMID:25670730

  12. Continued Development of Python-Based Thomson Data Analysis and Associated Visualization Tool for NSTX-U

    NASA Astrophysics Data System (ADS)

    Wallace, William; Miller, Jared; Diallo, Ahmed

    2015-11-01

    MultiPoint Thomson Scattering (MPTS) is an established, accurate method of finding the temperature, density, and pressure of a magnetically confined plasma. Two Nd:YAG (1064 nm) lasers are fired into the plasma with a effective frequency of 60 Hz, and the light is Doppler shifted by Thomson scattering. Polychromators on the NSTX-U midplane collect the scattered photons at various radii/scattering angles, and the avalanche photodiode voltages are saved to an MDSplus tree for later analysis. IDL code is then used to determine plasma temperature, pressure, and density from the captured polychromator measurements via Selden formulas. [1] Previous work [2] converted the single-processor IDL code into Python code, and prepared a new architecture for multiprocessing MPTS in parallel. However, that work was not completed to the generation of output data and curve fits that match with the previous IDL. This project refactored the Python code into a object-oriented architecture, and created a software test suite for the new architecture which allowed identification of the code which generated the difference in output. Another effort currently underway is to display the Thomson data in an intuitive, interactive format. This work was supported in part by the U.S. Department of Energy, Office of Science, Office of Workforce Development for Teachers and Scientists (WDTS) under the Community College Internship (CCI) program.

  13. Darwin and evolutionary tales in leukemia. The Ham-Wasserman Lecture.

    PubMed

    Greaves, Mel

    2009-01-01

    All cancers evolve by a process of genetic diversification and "natural selection" akin to the process first described by Charles Darwin for species evolution. The evolutionary, natural history of childhood acute lymphoblastic leukemia (ALL) is almost entirely covert, clinically silent and well advanced by the point of diagnosis. It has, however, been possible to backtrack this process by molecular scrutiny of appropriate clinical samples: (i) leukemic clones in monozygotic twins that are either concordant or discordant for ALL; (ii) archived neonatal blood spots or Guthrie cards from individuals who later developed leukemia; and (iii) stored, viable cord blood cells. These studies indicate prenatal initiation of leukemia by chromosome translocation and gene fusion (or hyperdiploidy) and the post-natal acquisition of multiple, gene copy number alterations (CNAs), mostly deletions. The prenatal or first "hit" occurs very commonly, exceeding the clinical rate of ALL by some 100x and indicating a low rate of penetrance or evolutionary progression. The acquisition of the critical, secondary CNAs requires some Darwinian selective advantage to expand numbers of cells at risk, and the cytokine TGF beta is able to exercise this function. The clonal architecture of ALL has been investigated by single cell analysis with multicolor probes to mutant genes. The data reveal not a linear sequence of mutation acquisition with clonal succession but rather considerable complexity with a tree-like or branching structure of genetically distinct subclones very reminiscent of Darwin's original 1837 evolutionary divergence diagram. This evolutionary pattern has important implications for stem cells in ALL, for the origins of relapse and for therapeutic targeting.

  14. The Social Tunnel Versus the Python: A New Way to Understand the Impact of Baby Booms and Baby Busts on a Society.

    ERIC Educational Resources Information Center

    McFalls, Joseph A.; And Others

    1986-01-01

    Maintains that the "python analogy," often used to help students understand the negative societal impact of unusually small or large age cohorts, is better replaced by the social tunnel analogy, which is diagramed and illustrated with reference to the educational problems experienced in the United States as a result of the World War II baby boom.…

  15. Using Python for scientific computing: Efficient and flexible evaluation of the statistical characteristics of functions with multivariate random inputs

    NASA Astrophysics Data System (ADS)

    Chudoba, R.; Sadílek, V.; Rypl, R.; Vořechovský, M.

    2013-02-01

    This paper examines the feasibility of high-level Python based utilities for numerically intensive applications via an example of a multidimensional integration for the evaluation of the statistical characteristics of a random variable. We discuss the approaches to the implementation of mathematically formulated incremental expressions using high-level scripting code and low-level compiled code. Due to the dynamic typing of the Python language, components of the algorithm can be easily coded in a generic way as algorithmic templates. Using the Enthought Development Suite they can be effectively assembled into a flexible computational framework that can be configured to execute the code for arbitrary combinations of integration schemes and versions of instantiated code. The paper describes the development cycle using a simple running example involving averaging of a random two-parametric function that includes discontinuity. This example is also used to compare the performance of the available algorithmic and executional features. The implemented package including further examples and the results of performance studies have been made available via the free repository [1] and CPCP library. Program summaryProgram title: spirrid Catalogue identifier: AENL_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AENL_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Special licence provided by the author No. of lines in distributed program, including test data, etc.: 10722 No. of bytes in distributed program, including test data, etc.: 157099 Distribution format: tar.gz Programming language: Python and C. Computer: PC. Operating system: LINUX, UNIX, Windows. Classification: 4.13, 6.2. External routines: NumPy (http://numpy.scipy.org/), SciPy (http://www.scipy.com) Nature of problem: Evaluation of the statistical moments of a function of random variables. Solution method: Direct multidimensional

  16. scraps: An open-source Python-based analysis package for analyzing and plotting superconducting resonator data

    SciTech Connect

    Carter, Faustin Wirkus; Khaire, Trupti S.; Novosad, Valentyn; Chang, Clarence L.

    2016-11-07

    We present "scraps" (SuperConducting Analysis and Plotting Software), a Python package designed to aid in the analysis and visualization of large amounts of superconducting resonator data, specifically complex transmission as a function of frequency, acquired at many different temperatures and driving powers. The package includes a least-squares fitting engine as well as a Monte-Carlo Markov Chain sampler for sampling the posterior distribution given priors, marginalizing over nuisance parameters, and estimating covariances. A set of plotting tools for generating publication-quality figures is also provided in the package. Lastly, we discuss the functionality of the software and provide some examples of its utility on data collected from a niobium-nitride coplanar waveguide resonator fabricated at Argonne National Laboratory.

  17. Visualization and processing of computed solid-state NMR parameters: MagresView and MagresPython.

    PubMed

    Sturniolo, Simone; Green, Timothy F G; Hanson, Robert M; Zilka, Miri; Refson, Keith; Hodgkinson, Paul; Brown, Steven P; Yates, Jonathan R

    2016-09-01

    We introduce two open source tools to aid the processing and visualisation of ab-initio computed solid-state NMR parameters. The Magres file format for computed NMR parameters (as implemented in CASTEP v8.0 and QuantumEspresso v5.0.0) is implemented. MagresView is built upon the widely used Jmol crystal viewer, and provides an intuitive environment to display computed NMR parameters. It can provide simple pictorial representation of one- and two-dimensional NMR spectra as well as output a selected spin-system for exact simulations with dedicated spin-dynamics software. MagresPython provides a simple scripting environment to manipulate large numbers of computed NMR parameters to search for structural correlations.

  18. scraps: An open-source Python-based analysis package for analyzing and plotting superconducting resonator data

    DOE PAGES

    Carter, Faustin Wirkus; Khaire, Trupti S.; Novosad, Valentyn; ...

    2016-11-07

    We present "scraps" (SuperConducting Analysis and Plotting Software), a Python package designed to aid in the analysis and visualization of large amounts of superconducting resonator data, specifically complex transmission as a function of frequency, acquired at many different temperatures and driving powers. The package includes a least-squares fitting engine as well as a Monte-Carlo Markov Chain sampler for sampling the posterior distribution given priors, marginalizing over nuisance parameters, and estimating covariances. A set of plotting tools for generating publication-quality figures is also provided in the package. Lastly, we discuss the functionality of the software and provide some examples of itsmore » utility on data collected from a niobium-nitride coplanar waveguide resonator fabricated at Argonne National Laboratory.« less

  19. Python-based finite element code used as a universal and modular tool for electronic structure calculation

    NASA Astrophysics Data System (ADS)

    Cimrman, Robert; Tůma, Miroslav; Novák, Matyáš; Čertík, Ondřej; Plešek, Jiří; Vackář, Jiří

    2013-10-01

    Ab-initio calculations of electronic states within the density-functional framework has been performed by means of the open source finite element package SfePy (Simple Finite Elements in Python, http://sfepy.org). We describe a new robust ab-initio real-space code based on (i) density functional theory, (ii) finite element method and (iii) environment-reflecting pseudopotentials. This approach brings a new quality to solving Kohn-Sham equations, calculating electronic states, total energy, Hellmann-Feynman forces and material properties particularly for non-crystalline, non-periodic structures. The main asset of the above approach is an efficient combination of excellent convergence control of standard, universal basis used in industrially proved finite-element method, high precision of ab-initio environment-reflecting pseudopotentials, and applicability not restricted to electrically neutral periodic environment. We present also numerical examples illustrating the outputs of the method.

  20. ESMPy and OpenClimateGIS: Python Interfaces for High Performance Grid Remapping and Geospatial Dataset Manipulation

    NASA Astrophysics Data System (ADS)

    O'Kuinghttons, Ryan; Koziol, Benjamin; Oehmke, Robert; DeLuca, Cecelia; Theurich, Gerhard; Li, Peggy; Jacob, Joseph

    2016-04-01

    The Earth System Modeling Framework (ESMF) Python interface (ESMPy) supports analysis and visualization in Earth system modeling codes by providing access to a variety of tools for data manipulation. ESMPy started as a Python interface to the ESMF grid remapping package, which provides mature and robust high-performance and scalable grid remapping between 2D and 3D logically rectangular and unstructured grids and sets of unconnected data. ESMPy now also interfaces with OpenClimateGIS (OCGIS), a package that performs subsetting, reformatting, and computational operations on climate datasets. ESMPy exposes a subset of ESMF grid remapping utilities. This includes bilinear, finite element patch recovery, first-order conservative, and nearest neighbor grid remapping methods. There are also options to ignore unmapped destination points, mask points on source and destination grids, and provide grid structure in the polar regions. Grid remapping on the sphere takes place in 3D Cartesian space, so the pole problem is not an issue as it can be with other grid remapping software. Remapping can be done between any combination of 2D and 3D logically rectangular and unstructured grids with overlapping domains. Grid pairs where one side of the regridding is represented by an appropriate set of unconnected data points, as is commonly found with observational data streams, is also supported. There is a developing interoperability layer between ESMPy and OpenClimateGIS (OCGIS). OCGIS is a pure Python, open source package designed for geospatial manipulation, subsetting, and computation on climate datasets stored in local NetCDF files or accessible remotely via the OPeNDAP protocol. Interfacing with OCGIS has brought GIS-like functionality to ESMPy (i.e. subsetting, coordinate transformations) as well as additional file output formats (i.e. CSV, ESRI Shapefile). ESMPy is distinguished by its strong emphasis on open source, community governance, and distributed development. The user

  1. eCo-Pylot - A Python-Based Script for Sending Parsed Email Data to a Database

    SciTech Connect

    Barnette, Daniel W.

    2012-01-04

    eCo-PylotDB, written completely in Python, provides a script that parses incoming emails and prepares extracted data for submission to a database table. The script extracts the database server, the database table, the server password, and the server username all from the email address to which the email is sent. The database table is specified on the Subject line. Any text in the body of the email is extracted as user comments for the database table. Attached files are extracted as data files with each file submitted to a specified table field but in separate rows of the targeted database table. Other information such as sender, date, time, and machine from which the email was sent is extracted and submitted to the database table as well. An email is sent back to the user specifying whether the data from the initial email was accepted or rejected by the database server. If rejected, the return email includes details as to why.

  2. LANL12-RS-107J PYTHON Radiography Analysis Tool (PyRAT). Mid-Year Deliverable Report for FY15

    SciTech Connect

    Temple, Brian Allen; Armstrong, Jerawan Chudoung

    2015-04-14

    This document is a mid-year report on a deliverable for the PYTHON Radiography Analysis Tool (PyRAT) for project LANL12-RS-107J in FY15. The deliverable is deliverable number 2 in the work package and is titled “Add the ability to read in more types of image file formats in PyRAT”. Right now PyRAT can only read in uncompressed TIF files (tiff files). It is planned to expand the file formats that can be read by PyRAT, making it easier to use in more situations. A summary of the file formats added include jpeg, jpg, png and formatted ASCII files.

  3. Multi-Pivot Quicksort: an Experiment with Single, Dual, Triple, Quad, and Penta-Pivot Quicksort Algorithms in Python

    NASA Astrophysics Data System (ADS)

    Budiman, M. A.; Zamzami, E. M.; Rachmawati, D.

    2017-03-01

    Dual-pivot quicksort, which was proposed by Yaroslavsky, has been experimentally proven to be more efficient than the classical single-pivot quicksort under the Java Virtual Machine [6]. Moreover, Kushagara, López-Ortiz, and Munro [4] has shown that triple-pivot quicksort runs 7-8% faster than dual-pivot quicksort in C, mutatis mutandis. In this research, we implement and experiment with single, dual, triple, quad, and penta-pivot quicksort algorithms in Python. Our experimental results are as follows. Firstly, the quicksort with single pivot is the slowest among the five variants. Secondly, at least until five (penta) pivots are being used, it is proven that the more pivots are used in a quicksort algorithm, the faster its performance becomes. Thirdly, the increase of speed resulted by adding more pivots tends to decrease gradually.

  4. Wilber 3: A Python-Django Web Application For Acquiring Large-scale Event-oriented Seismic Data

    NASA Astrophysics Data System (ADS)

    Newman, R. L.; Clark, A.; Trabant, C. M.; Karstens, R.; Hutko, A. R.; Casey, R. E.; Ahern, T. K.

    2013-12-01

    Since 2001, the IRIS Data Management Center (DMC) WILBER II system has provided a convenient web-based interface for locating seismic data related to a particular event, and requesting a subset of that data for download. Since its launch, both the scale of available data and the technology of web-based applications have developed significantly. Wilber 3 is a ground-up redesign that leverages a number of public and open-source projects to provide an event-oriented data request interface with a high level of interactivity and scalability for multiple data types. Wilber 3 uses the IRIS/Federation of Digital Seismic Networks (FDSN) web services for event data, metadata, and time-series data. Combining a carefully optimized Google Map with the highly scalable SlickGrid data API, the Wilber 3 client-side interface can load tens of thousands of events or networks/stations in a single request, and provide instantly responsive browsing, sorting, and filtering of event and meta data in the web browser, without further reliance on the data service. The server-side of Wilber 3 is a Python-Django application, one of over a dozen developed in the last year at IRIS, whose common framework, components, and administrative overhead represent a massive savings in developer resources. Requests for assembled datasets, which may include thousands of data channels and gigabytes of data, are queued and executed using the Celery distributed Python task scheduler, giving Wilber 3 the ability to operate in parallel across a large number of nodes.

  5. The Profile Envision and Splice Tool (PRESTO): Developing an Atmospheric Wind Analysis Tool for Space Launch Vehicles Using Python

    NASA Technical Reports Server (NTRS)

    Orcutt, John M.; Barbre, Robert E., Jr.; Brenton, James C.; Decker, Ryan K.

    2017-01-01

    Tropospheric winds are an important driver of the design and operation of space launch vehicles. Multiple types of weather balloons and Doppler Radar Wind Profiler (DRWP) systems exist at NASA's Kennedy Space Center (KSC), co-located on the United States Air Force's (USAF) Eastern Range (ER) at the Cape Canaveral Air Force Station (CCAFS), that are capable of measuring atmospheric winds. Meteorological data gathered by these instruments are being used in the design of NASA's Space Launch System (SLS) and other space launch vehicles, and will be used during the day-of-launch (DOL) of SLS to aid in loads and trajectory analyses. For the purpose of SLS day-of-launch needs, the balloons have the altitude coverage needed, but take over an hour to reach the maximum altitude and can drift far from the vehicle's path. The DRWPs have the spatial and temporal resolutions needed, but do not provide complete altitude coverage. Therefore, the Natural Environments Branch (EV44) at Marshall Space Flight Center (MSFC) developed the Profile Envision and Splice Tool (PRESTO) to combine balloon profiles and profiles from multiple DRWPs, filter the spliced profile to a common wavelength, and allow the operator to generate output files as well as to visualize the inputs and the spliced profile for SLS DOL operations. PRESTO was developed in Python taking advantage of NumPy and SciPy for the splicing procedure, matplotlib for the visualization, and Tkinter for the execution of the graphical user interface (GUI). This paper describes in detail the Python coding implementation for the splicing, filtering, and visualization methodology used in PRESTO.

  6. QuTiP: An open-source Python framework for the dynamics of open quantum systems

    NASA Astrophysics Data System (ADS)

    Johansson, J. R.; Nation, P. D.; Nori, Franco

    2012-08-01

    We present an object-oriented open-source framework for solving the dynamics of open quantum systems written in Python. Arbitrary Hamiltonians, including time-dependent systems, may be built up from operators and states defined by a quantum object class, and then passed on to a choice of master equation or Monte Carlo solvers. We give an overview of the basic structure for the framework before detailing the numerical simulation of open system dynamics. Several examples are given to illustrate the build up to a complete calculation. Finally, we measure the performance of our library against that of current implementations. The framework described here is particularly well suited to the fields of quantum optics, superconducting circuit devices, nanomechanics, and trapped ions, while also being ideal for use in classroom instruction. Catalogue identifier: AEMB_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEMB_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU General Public License, version 3 No. of lines in distributed program, including test data, etc.: 16 482 No. of bytes in distributed program, including test data, etc.: 213 438 Distribution format: tar.gz Programming language: Python Computer: i386, x86-64 Operating system: Linux, Mac OSX, Windows RAM: 2+ Gigabytes Classification: 7 External routines: NumPy (http://numpy.scipy.org/), SciPy (http://www.scipy.org/), Matplotlib (http://matplotlib.sourceforge.net/) Nature of problem: Dynamics of open quantum systems. Solution method: Numerical solutions to Lindblad master equation or Monte Carlo wave function method. Restrictions: Problems must meet the criteria for using the master equation in Lindblad form. Running time: A few seconds up to several tens of minutes, depending on size of underlying Hilbert space.

  7. Pse-Analysis: a python package for DNA/RNA and protein/ peptide sequence analysis based on pseudo components and kernel methods.

    PubMed

    Liu, Bin; Wu, Hao; Zhang, Deyuan; Wang, Xiaolong; Chou, Kuo-Chen

    2017-01-05

    To expedite the pace in conducting genome/proteome analysis, we have developed a Python package called Pse-Analysis. The powerful package can automatically complete the following five procedures: (1) sample feature extraction, (2) optimal parameter selection, (3) model training, (4) cross validation, and (5) evaluating prediction quality. All the work a user needs to do is to input a benchmark dataset along with the query biological sequences concerned. Based on the benchmark dataset, Pse-Analysis will automatically construct an ideal predictor, followed by yielding the predicted results for the submitted query samples. All the aforementioned tedious jobs can be automatically done by the computer. Moreover, the multiprocessing technique was adopted to enhance computational speed by about 6 folds. The Pse-Analysis Python package is freely accessible to the public at http://bioinformatics.hitsz.edu.cn/Pse-Analysis/, and can be directly run on Windows, Linux, and Unix.

  8. Processing of terabytes of data for seismic noise analysis with the Python codes of the Whisper Suite. (Invited)

    NASA Astrophysics Data System (ADS)

    Briand, X.; Campillo, M.; Brenguier, F.; Boue, P.; Poli, P.; Roux, P.; Takeda, T.

    2013-12-01

    The Whisper Suite, as part of the ERC project Whisper (whisper.obs.ujf-grenoble.fr), is developed with the high-level programming language Python and uses intensively the scientific libraries Scipy and Obspy, which is dedicated to the seismological community (www.obspy.org). The Whisper Suite consists of several tools. It provides a flexible way to specify a pipeline of seismogram processing. The user can define his own sequence of treatments, can use the Python libraries he needs and eventually, can add his processing procedure to the Whisper Suite. Another package is dedicated to the computation of correlations. When dealing with large data set, computational time becomes a major difficulty and we devoted a lot of efforts to make possible the fast processing of the large data sets produced by the present day dense seismic networks. With the Whisper Suite, we manage currently more than 150TB of data for ambient noise analysis. For the computations of 68 millions correlations (daily, 5Hz, correlation window 3600s) on a 50 core cluster, with a dedicated disk array, the required time is 4 days. With a distributed storage (Irods) and a grid of clusters (mode best effort), both provided by the University of Grenoble, we compute currently one year of 4-hours correlations for 550 3C stations of the Hi-Net Japanese Network in one day (about 350 millions individual correlations) . Note that the quadratic space complexity can be critical. We developed also codes for the analysis of the correlations. The Whisper Suite is used to make challenging observations using cross-correlation techniques at various scales in the Earth. We present some examples of applications. Using a global data set of available broadband stations, we discuss the emergence of the complete teleseismic body wave wave field, including the deep phases used for imaging of the mantle and the core. The giant 2011 Tohoku-oki earthquake and the records of the dense Hi-Net array offer an opportunity to analyze

  9. prepare_taxa_charts.py: A Python program to automate generation of publication ready taxonomic pie chart images from QIIME.

    PubMed

    Lakhujani, Vijay; Badapanda, Chandan

    2017-06-01

    QIIME (Quantitative Insights Into Microbial Ecology) is one of the most popular open-source bioinformatics suite for performing metagenome, 16S rRNA amplicon and Internal Transcribed Spacer (ITS) data analysis. Although, it is very comprehensive and powerful tool, it lacks a method to provide publication ready taxonomic pie charts. The script plot_taxa_summary.py bundled with QIIME generate a html file and a folder containing taxonomic pie chart and legend as separate images. The images have randomly generated alphanumeric names. Therefore, it is difficult to associate the pie chart with the legend and the corresponding sample identifier. Even if the option to have the legend within the html file is selected while executing plot_taxa_summary.py, it is very tedious to crop a complete image (having both the pie chart and the legend) due to unequal image sizes. It requires a lot of time to manually prepare the pie charts for multiple samples for publication purpose. Moreover, there are chances of error while identifying the pie chart and legend pair due to random alphanumeric names of the images. To bypass all these bottlenecks and make this process efficient, we have developed a python based program, prepare_taxa_charts.py, to automate the renaming, cropping and merging of taxonomic pie chart and corresponding legend image into a single, good quality publication ready image. This program not only augments the functionality of plot_taxa_summary.py but is also very fast in terms of CPU time and user friendly.

  10. Co-PylotDB - A Python-Based Single-Window User Interface for Transmitting Information to a Database

    SciTech Connect

    Barnette, Daniel W.

    2012-01-05

    Co-PylotDB, written completely in Python, provides a user interface (UI) with which to select user and data file(s), directories, and file content, and provide or capture various other information for sending data collected from running any computer program to a pre-formatted database table for persistent storage. The interface allows the user to select input, output, make, source, executable, and qsub files. It also provides fields for specifying the machine name on which the software was run, capturing compile and execution lines, and listing relevant user comments. Data automatically captured by Co-PylotDB and sent to the database are user, current directory, local hostname, current date, and time of send. The UI provides fields for logging into a local or remote database server, specifying a database and a table, and sending the information to the selected database table. If a server is not available, the UI provides for saving the command that would have saved the information to a database table for either later submission or for sending via email to a collaborator who has access to the desired database.

  11. Influence of temperature on the corticosterone stress-response: an experiment in the Children's python (Antaresia childreni).

    PubMed

    Dupoué, Andréaz; Brischoux, François; Lourdais, Olivier; Angelier, Frédéric

    2013-11-01

    To cope with environmental challenges, organisms have to adjust their behaviours and their physiology to the environmental conditions they face (i.e. allostasis). In vertebrates, such adjustments are often mediated through the secretion of glucocorticoids (GCs) that are well-known to activate and/or inhibit specific physiological and behavioural traits. In ectothermic species, most processes are temperature-dependent and according to previous studies, low external temperatures should be associated with low GC concentrations (both baseline and stress-induced concentrations). In this study, we experimentally tested this hypothesis by investigating the short term influence of temperature on the GC stress response in a squamate reptile, the Children's python (Antaresia childreni). Snakes were maintained in contrasting conditions (warm and cold groups), and their corticosterone (CORT) stress response was measured (baseline and stress-induced CORT concentrations), within 48h of treatment. Contrary to our prediction, baseline and stress-induced CORT concentrations were higher in the cold versus the warm treatment. In addition, we found a strong negative relationship between CORT concentrations (baseline and stress-induced) and temperature within the cold treatment. Although it remains unclear how cold temperatures can mechanistically result in increased CORT concentrations, we suggest that, at suboptimal temperature, high CORT concentrations may help the organism to maintain an alert state.

  12. Autonomic control of heart rate during orthostasis and the importance of orthostatic-tachycardia in the snake Python molurus.

    PubMed

    Armelin, Vinicius Araújo; da Silva Braga, Victor Hugo; Abe, Augusto Shinya; Rantin, Francisco Tadeu; Florindo, Luiz Henrique

    2014-10-01

    Orthostasis dramatically influences the hemodynamics of terrestrial vertebrates, especially large and elongated animals such as snakes. When these animals assume a vertical orientation, gravity tends to reduce venous return, cardiac filling, cardiac output and blood pressure to the anterior regions of the body. The hypotension triggers physiological responses, which generally include vasomotor adjustments and tachycardia to normalize blood pressure. While some studies have focused on understanding the regulation of these vasomotor adjustments in ectothermic vertebrates, little is known about regulation and the importance of heart rate in these animals during orthostasis. We acquired heart rate and carotid pulse pressure (P PC) in pythons in their horizontal position, and during 30 and 60° inclinations while the animals were either untreated (control) or upon muscarinic cholinoceptor blockade and a double autonomic blockade. Double autonomic blockade completely eradicated the orthostatic-tachycardia, and without this adjustment, the P PC reduction caused by the tilts became higher than that which was observed in untreated animals. On the other hand, post-inclinatory vasomotor adjustments appeared to be of negligible importance in counterbalancing the hemodynamic effects of gravity. Finally, calculations of cardiac autonomic tones at each position revealed that the orthostatic-tachycardia is almost completely elicited by a withdrawal of vagal drive.

  13. Presentation of the PyDEF post-treatment Python software to compute publishable charts for defect energy formation

    NASA Astrophysics Data System (ADS)

    Péan, Emmanuel; Vidal, Julien; Jobic, Stéphane; Latouche, Camille

    2017-03-01

    In this paper we present a new software, Python for Defect Energy Formation (PyDEF), especially dedicated to the calculation of defect formation energy including its various corrections as developed by the theoretical community through the years. This program offers an intuitive graphical user interface which allows one to easily compute the corrected formation energy of any defect using theoretical calculation results. PyDEF is particularly suited for semiconductor materials as it includes finite size error corrections due to spurious intercell interactions as it is able to plot the formation energy of the different charge states and to determine the more stable ones as a function of the Fermi energy. Moreover PyDEF is able to plot Density Of States (DOS) with various parameters such as the projection on atoms or atomic species allowing a more comprehensive representation of defect-related electronic states. This software is developed in such a way that even non specialist or coder can use it and easily and quickly obtain reliable results.

  14. C++QEDv2 Milestone 10: A C++/Python application-programming framework for simulating open quantum dynamics

    NASA Astrophysics Data System (ADS)

    Sandner, Raimar; Vukics, András

    2014-09-01

    The v2 Milestone 10 release of C++QED is primarily a feature release, which also corrects some problems of the previous release, especially as regards the build system. The adoption of C++11 features has led to many simplifications in the codebase. A full doxygen-based API manual [1] is now provided together with updated user guides. A largely automated, versatile new testsuite directed both towards computational and physics features allows for quickly spotting arising errors. The states of trajectories are now savable and recoverable with full binary precision, allowing for trajectory continuation regardless of evolution method (single/ensemble Monte Carlo wave-function or Master equation trajectory). As the main new feature, the framework now presents Python bindings to the highest-level programming interface, so that actual simulations for given composite quantum systems can now be performed from Python. Catalogue identifier: AELU_v2_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AELU_v2_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: yes No. of lines in distributed program, including test data, etc.: 492422 No. of bytes in distributed program, including test data, etc.: 8070987 Distribution format: tar.gz Programming language: C++/Python. Computer: i386-i686, x86 64. Operating system: In principle cross-platform, as yet tested only on UNIX-like systems (including Mac OS X). RAM: The framework itself takes about 60MB, which is fully shared. The additional memory taken by the program which defines the actual physical system (script) is typically less than 1MB. The memory storing the actual data scales with the system dimension for state-vector manipulations, and the square of the dimension for density-operator manipulations. This might easily be GBs, and often the memory of the machine limits the size of the simulated system. Classification: 4.3, 4.13, 6.2. External routines: Boost C

  15. NMRbot: Python scripts enable high-throughput data collection on current Bruker BioSpin NMR spectrometers.

    PubMed

    Clos, Lawrence J; Jofre, M Fransisca; Ellinger, James J; Westler, William M; Markley, John L

    2013-06-01

    To facilitate the high-throughput acquisition of nuclear magnetic resonance (NMR) experimental data on large sets of samples, we have developed a simple and straightforward automated methodology that capitalizes on recent advances in Bruker BioSpin NMR spectrometer hardware and software. Given the daunting challenge for non-NMR experts to collect quality spectra, our goal was to increase user accessibility, provide customized functionality, and improve the consistency and reliability of resultant data. This methodology, NMRbot, is encoded in a set of scripts written in the Python programming language accessible within the Bruker BioSpin TopSpin™ software. NMRbot improves automated data acquisition and offers novel tools for use in optimizing experimental parameters on the fly. This automated procedure has been successfully implemented for investigations in metabolomics, small-molecule library profiling, and protein-ligand titrations on four Bruker BioSpin NMR spectrometers at the National Magnetic Resonance Facility at Madison. The investigators reported benefits from ease of setup, improved spectral quality, convenient customizations, and overall time savings.

  16. Tribological analysis of the ventral scale structure in a Python regius in relation to laser textured surfaces

    NASA Astrophysics Data System (ADS)

    Abdel-Aal, H. A.; El Mansori, M.

    2013-09-01

    Laser texturing is one of the leading technologies applied to modify surface topography. To date, however, a standardized procedure to generate deterministic textures is virtually non-existent. In nature, especially in squamata, there are many examples of deterministic structured textures that allow species to control friction and condition their tribological response for efficient function. In this work, we draw a comparison between industrial surfaces and reptilian surfaces. We chose the Python regius species as a bio-analogue with a deterministic surface. We first study the structural make up of the ventral scales of the snake (both construction and metrology). We further compare the metrological features of the ventral scales to experimentally recommended performance indicators of industrial surfaces extracted from open literature. The results indicate the feasibility of engineering a laser textured surface based on the reptilian ornamentation constructs. It is shown that the metrological features, key to efficient function of a rubbing deterministic surface, are already optimized in the reptile. We further show that optimization in reptilian surfaces is based on synchronizing surface form, textures and aspects to condition the frictional response. Mimicking reptilian surfaces, we argue, may form a design methodology potentially capable of generating advanced deterministic surface constructs capable of efficient tribological function.

  17. Forecast of spatially distributed runoff dynamics in the Finger Lakes region using an interactive web tool and Python

    NASA Astrophysics Data System (ADS)

    Dahlke, H. E.; Easton, Z. M.; Fuka, D. R.; Rao, N. S.; Steenhuis, T. S.

    2008-12-01

    To optimize NPS pollution reduction efficiency of Best Management Practices (BMPs) in NY State, various models have been developed that can effectively delineate runoff and contaminant source areas in the landscape. In the Finger Lakes region with shallow, permeable soils, underlain by a restricting layer, saturation excess runoff is the dominant mechanism of nutrient transport. In watersheds characterized by these conditions, runoff originates from areas in the landscape that expand and contract seasonally and are therefore often termed as variable source areas (VSAs). Hence, consideration should be given to the spatial distribution of VSA in the watershed during the planning process of BMPs. However, in practice the applied hydrological models often require extensive expertise and effort to be used on a routine basis for BMP planning. In order to simplify the BMP planning process, we developed an interactive web-based tool for Salmon Creek watershed, NY that locates VSA and calculates their probability of saturation. The interactive web tool incorporates hydrologic, geographic and land management information in an ESRI ArcIMS framework and presents the resulting VSA maps online. For the web tool we developed a Python-based application that calculates the surface runoff potential of the 230 km2 Salmon Creek watershed on the basis of a water balance model and free precipitation and temperature data from the National Climatic Data Center. Areas of high surface runoff potential are distributed via a soil topographic index to capture VSA dynamics. Further, the application is used to calculate a one to two day prediction of the spatial extent of VSA using free web- provided weather forecasts. The web tool is designed to interactively assist planners and especially farmers in the BMP planning process on a simplified expertise level. It can be used on a daily basis to locate fields with low runoff risk that could, potentially receive more liberal nutrient applications

  18. Constraint Network Analysis (CNA): a Python software package for efficiently linking biomacromolecular structure, flexibility, (thermo-)stability, and function.

    PubMed

    Pfleger, Christopher; Rathi, Prakash Chandra; Klein, Doris L; Radestock, Sebastian; Gohlke, Holger

    2013-04-22

    For deriving maximal advantage from information on biomacromolecular flexibility and rigidity, results from rigidity analyses must be linked to biologically relevant characteristics of a structure. Here, we describe the Python-based software package Constraint Network Analysis (CNA) developed for this task. CNA functions as a front- and backend to the graph-based rigidity analysis software FIRST. CNA goes beyond the mere identification of flexible and rigid regions in a biomacromolecule in that it (I) provides a refined modeling of thermal unfolding simulations that also considers the temperature-dependence of hydrophobic tethers, (II) allows performing rigidity analyses on ensembles of network topologies, either generated from structural ensembles or by using the concept of fuzzy noncovalent constraints, and (III) computes a set of global and local indices for quantifying biomacromolecular stability. This leads to more robust results from rigidity analyses and extends the application domain of rigidity analyses in that phase transition points ("melting points") and unfolding nuclei ("structural weak spots") are determined automatically. Furthermore, CNA robustly handles small-molecule ligands in general. Such advancements are important for applying rigidity analysis to data