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.
GPAW - massively parallel electronic structure calculations with Python-based software.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Enkovaara, J.; Romero, N.; Shende, S.
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 thismore » 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.« less
NASA Astrophysics Data System (ADS)
Barrett, P. E.
This BoF will be chaired by Paul Barrett and will begin with an introduction to Python in astronomy, be followed by reports of current Python projects, and conclude with a discussion about the current state of Python in astronomy. The introduction will give a brief overview of the language, highlighting modules, resources, and aspects of the language that are important to scientific programming and astronomical data analysis. The closing discussion will provide an opportunity for questions and comments.
Endocardial fibrosarcoma in a reticulated python (Python reticularis).
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.
DOE Office of Scientific and Technical Information (OSTI.GOV)
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, andmore » (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.« less
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.
Hoon-Hanks, Laura L; Layton, Marylee L; Ossiboff, Robert J; Parker, John S L; Dubovi, Edward J; Stenglein, Mark D
2018-04-01
Circumstantial evidence has linked a new group of nidoviruses with respiratory disease in pythons, lizards, and cattle. We conducted experimental infections in ball pythons (Python regius) to test the hypothesis that ball python nidovirus (BPNV) infection results in respiratory disease. Three ball pythons were inoculated orally and intratracheally with cell culture isolated BPNV and two were sham inoculated. Antemortem choanal, oroesophageal, and cloacal swabs and postmortem tissues of infected snakes were positive for viral RNA, protein, and infectious virus by qRT-PCR, immunohistochemistry, western blot and virus isolation. Clinical signs included oral mucosal reddening, abundant mucus secretions, open-mouthed breathing, and anorexia. Histologic lesions included chronic-active mucinous rhinitis, stomatitis, tracheitis, esophagitis and proliferative interstitial pneumonia. Control snakes remained negative and free of clinical signs throughout the experiment. Our findings establish a causal relationship between nidovirus infection and respiratory disease in ball pythons and shed light on disease progression and transmission. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.
Pythons in Burma: Short-tailed python (Reptilia: Squamata)
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.
Humoral regulation of heart rate during digestion in pythons (Python molurus and Python regius).
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.
Ball Python Nidovirus: a Candidate Etiologic Agent for Severe Respiratory Disease in Python regius
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
Using Python as a first programming environment for computational physics in developing countries
NASA Astrophysics Data System (ADS)
Akpojotor, Godfrey; Ehwerhemuepha, Louis; Echenim, Myron; Akpojotor, Famous
2011-03-01
Python unique features such its interpretative, multiplatform and object oriented nature as well as being a free and open source software creates the possibility that any user connected to the internet can download the entire package into any platform, install it and immediately begin to use it. Thus Python is gaining reputation as a preferred environment for introducing students and new beginners to programming. Therefore in Africa, the Python African Tour project has been launched and we are coordinating its use in computational science. We examine here the challenges and prospects of using Python for computational physics (CP) education in developing countries (DC). Then we present our project on using Python to simulate and aid the learning of laboratory experiments illustrated here by modeling of the simple pendulum and also to visualize phenomena in physics illustrated here by demonstrating the wave motion of a particle in a varying potential. This project which is to train both the teachers and our students on CP using Python can easily be adopted in other DC.
Acariasis on pet Burmese python, Python molurus bivittatus in Malaysia.
Mariana, A; Vellayan, S; Halimaton, I; Ho, T M
2011-03-01
To identify the acari present on pet Burmese pythons in Malaysia and to determine whether there is any potential public health risk related to handling of the snakes. Two sub-adult Burmese pythons kept as pets for a period of about 6 to 7 months by different owners, were brought to an exotic animal practice for treatment. On a complete medical examination, some ticks and mites (acari) were detected beneath the dorsal and ventral scales along body length of the snakes. Ticks were directly identified and mites were mounted prior to identification. A total of 12 ticks represented by 3 males, 2 females and 7 nymphal stages of Rhipicephalus sanguineus (R. sanguineus) were extracted from the first python while the other one was with 25 female Ophionyssus natricis (O. natricis) mesostigmatid mites. Only adult female mites were found. These mites are common ectoparasites of Burmese pythons. Both the acarine species found on the Burmese pythons are known vectors of pathogens. This is the first record that R. sanguineus has been reported from a pet Burmese python in Malaysia. Copyright © 2011 Hainan Medical College. Published by Elsevier B.V. All rights reserved.
Ball python nidovirus: a candidate etiologic agent for severe respiratory disease in Python regius.
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; DeRisi, Joseph L
2014-09-09
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. Ball pythons are popular pets because of their diverse coloration, generally nonaggressive behavior, and relatively small size. Since the 1990s, veterinarians have been aware of an infectious respiratory disease of unknown cause in ball pythons that can be fatal. We used unbiased shotgun sequencing to discover a novel virus in the order Nidovirales that was
TEMPy: a Python library for assessment of three-dimensional electron microscopy density fits.
Farabella, Irene; Vasishtan, Daven; Joseph, Agnel Praveen; Pandurangan, Arun Prasad; Sahota, Harpal; Topf, Maya
2015-08-01
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.
The zoonotic implications of pentastomiasis in the royal python (python regius).
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.
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.
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.
Morphological respiratory diffusion capacity of the lungs of ball pythons (Python regius).
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. Copyright © 2012 Elsevier Gmb
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
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)....
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
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.
pypet: A Python Toolkit for Data Management of Parameter Explorations.
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.
The spectacle of the ball python (Python regius): a morphological description.
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. Copyright © 2013 Wiley Periodicals, Inc.
Huder, Jon B.; Böni, Jürg; Hatt, Jean-Michel; Soldati, Guido; Lutz, Hans; Schüpbach, Jörg
2002-01-01
Boid inclusion body disease (BIBD) is a fatal disorder of boid snakes that is suspected to be caused by a retrovirus. In order to identify this agent, leukocyte cultures (established from Python molurus specimens with symptoms of BIBD or kept together with such diseased animals) were assessed for reverse transcriptase (RT) activity. Virus from cultures exhibiting high RT activity was banded on sucrose density gradients, and the RT peak fraction was subjected to highly efficient procedures for the identification of unknown particle-associated retroviral RNA. A 7-kb full retroviral sequence was identified, cloned, and sequenced. This virus contained intact open reading frames (ORFs) for gag, pro, pol, and env, as well as another ORF of unknown function within pol. Phylogenetic analysis showed that the virus is distantly related to viruses from both the B and D types and the mammalian C type but cannot be classified. It is present as a highly expressed endogenous retrovirus in all P. molurus individuals; a closely related, but much less expressed virus was found in all tested Python curtus individuals. All other boid snakes tested, including Python regius, Python reticulatus, Boa constrictor, Eunectes notaeus, and Morelia spilota, were virus negative, independent of whether they had BIBD or not. Virus isolated from P. molurus could not be transmitted to the peripheral blood mononuclear cells of B. constrictor or P. regius. Thus, there is no indication that this novel virus, which we propose to name python endogenous retrovirus (PyERV), is causally linked with BIBD. PMID:12097574
Amebiasis in four ball pythons, Python reginus.
Kojimoto, A; Uchida, K; Horii, Y; Okumura, S; Yamaguch, R; Tateyama, S
2001-12-01
Between September 13th and November 18th in 1999, four ball pythons, Python reginus kept in the same display, showed anorexia and died one after another. At necropsy, all four snakes had severe hemorrhagic colitis. Microscopically, all snakes had severe necrotizing hemorrhagic colitis, in association with ameba-like protozoa. Some of the protozoa had macrophage-like morphology and others formed protozoal cysts with thickened walls. These protozoa were distributed throughout the wall in the large intestine. Based on the pathological findings, these snakes were infested with a member of Entamoeba sp., presumably with infection by Entamoeba invadens, the most prevalent type of reptilian amoebae.
Hemodynamic consequences of cardiac malformations in two juvenile ball pythons (Python regius).
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.
The atomic simulation environment-a Python library for working with atoms.
Hjorth Larsen, Ask; Jørgen Mortensen, Jens; Blomqvist, Jakob; Castelli, Ivano E; Christensen, Rune; Dułak, Marcin; Friis, Jesper; Groves, Michael N; Hammer, Bjørk; Hargus, Cory; Hermes, Eric D; Jennings, Paul C; Bjerre Jensen, Peter; Kermode, James; Kitchin, John R; Leonhard Kolsbjerg, Esben; Kubal, Joseph; Kaasbjerg, Kristen; Lysgaard, Steen; Bergmann Maronsson, Jón; Maxson, Tristan; Olsen, Thomas; Pastewka, Lars; Peterson, Andrew; Rostgaard, Carsten; Schiøtz, Jakob; Schütt, Ole; Strange, Mikkel; Thygesen, Kristian S; Vegge, Tejs; Vilhelmsen, Lasse; Walter, Michael; Zeng, Zhenhua; Jacobsen, Karsten W
2017-07-12
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 simulations. 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.
The atomic simulation environment—a Python library for working with atoms
NASA Astrophysics Data System (ADS)
Hjorth Larsen, Ask; Jørgen Mortensen, Jens; Blomqvist, Jakob; Castelli, Ivano E.; Christensen, Rune; Dułak, Marcin; Friis, Jesper; Groves, Michael N.; Hammer, Bjørk; Hargus, Cory; Hermes, Eric D.; Jennings, Paul C.; Bjerre Jensen, Peter; Kermode, James; Kitchin, John R.; Leonhard Kolsbjerg, Esben; Kubal, Joseph; Kaasbjerg, Kristen; Lysgaard, Steen; Bergmann Maronsson, Jón; Maxson, Tristan; Olsen, Thomas; Pastewka, Lars; Peterson, Andrew; Rostgaard, Carsten; Schiøtz, Jakob; Schütt, Ole; Strange, Mikkel; Thygesen, Kristian S.; Vegge, Tejs; Vilhelmsen, Lasse; Walter, Michael; Zeng, Zhenhua; Jacobsen, Karsten W.
2017-07-01
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 simulations. 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.
pypet: A Python Toolkit for Data Management of Parameter Explorations
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
Pynamic: the Python Dynamic Benchmark
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lee, G L; Ahn, D H; de Supinksi, B R
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, wemore » 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.« less
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.
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
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.
Banzato, Tommaso; Russo, Elisa; Finotti, Luca; Milan, Maria C; Gianesella, Matteo; Zotti, Alessandro
2012-05-01
To determine the ultrasonographic features of the coelomic organs of healthy snakes belonging to the Boidae and Pythonidae families. 16 ball pythons (Python regius; 7 males, 8 females, and 1 sexually immature), 10 Indian rock pythons (Python molurus molurus; 5 males, 4 females, and 1 sexually immature), 12 Python curtus (5 males and 7 females), and 8 boa constrictors (Boa constrictor imperator; 4 males and 4 females). All snakes underwent complete ultrasonographic evaluation of the coelomic cavity; chemical restraint was not necessary. A dorsolateral approach to probe placement was chosen to increase image quality and to avoid injury to the snakes and operators. Qualitative and quantitative observations were recorded. The liver, stomach, gallbladder, pancreas, small and large intestines, kidneys, cloaca, and scent glands were identified in all snakes. The hemipenes were identified in 10 of the 21 (48%) male snakes. The spleen was identified in 5 of the 46 (11%) snakes, and ureters were identified in 6 (13%). In 2 sexually immature snakes, the gonads were not visible. One (2%) snake was gravid, and 7 (15%) had small amounts of free fluid in the coelomic cavity. A significant positive correlation was identified between several measurements (diameter and thickness of scent glands, gastric and pyloric walls, and colonic wall) and body length (snout to vent) and body weight. The study findings can be used as an atlas of the ultrasonographic anatomy of the coelomic cavity in healthy boid snakes. Ultrasonography was reasonably fast to perform and was well tolerated in conscious snakes.
ERIC Educational Resources Information Center
Ashraf, Rasha
2017-01-01
This article presents Python codes that can be used to extract data from Securities and Exchange Commission (SEC) filings. The Python program web crawls to obtain URL paths for company filings of required reports, such as Form 10-K. The program then performs a textual analysis and counts the number of occurrences of words in the filing that…
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
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.
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. © 2016 Wiley Periodicals, Inc.
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.
Unilateral microphthalmia or anophthalmia in eight pythons (Pythonidae).
Da Silva, Mari-Ann O; Bertelsen, Mads F; Wang, Tobias; Pedersen, Michael; Lauridsen, Henrik; Heegaard, Steffen
2015-01-01
To provide morphological descriptions of microphthalmia or anophthalmia in eight pythons using microcomputerized tomography (μCT), magnetic resonance imaging (MRI), and histopathology. Seven Burmese pythons (Python bivittatus) and one ball python (P. regius) with clinically normal right eyes and an abnormal or missing left eye. At the time of euthanasia, four of the eight snakes underwent necropsy. Hereafter, the heads of two Burmese pythons and one ball python were examined using μCT, and another Burmese python was subjected to MRI. Following these procedures, the heads of these four pythons along with the heads of an additional three Burmese pythons were prepared for histology. All eight snakes had left ocular openings seen as dermal invaginations between 0.2 and 2.0 mm in diameter. They also had varying degrees of malformations of the orbital bones and a limited presence of nervous, glandular, and muscle tissue in the posterior orbit. Two individuals had small but identifiable eyes. Furthermore, remnants of the pigmented embryonic framework of the hyaloid vessels were found in the anophthalmic snakes. Necropsies revealed no other macroscopic anomalies. Eight pythons with unilateral left-sided microphthalmia or anophthalmia had one normal eye and a left orbit with malformed or incompletely developed ocular structures along with remnants of fetal structures. These cases lend further information to a condition that is often seen in snakes, but infrequently described. © 2014 American College of Veterinary Ophthalmologists.
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.
Pybus -- A Python Software Bus
DOE Office of Scientific and Technical Information (OSTI.GOV)
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 conceptmore » 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.« less
PyMOOSE: Interoperable Scripting in Python for MOOSE
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. PMID:19129924
Detection of nidoviruses in live pythons and boas.
Marschang, Rachel E; Kolesnik, Ekaterina
2017-02-09
Nidoviruses have recently been described as a putative cause of severe respiratory disease in pythons in the USA and Europe. The objective of this study was to establish the use of a conventional PCR for the detection of nidoviruses in samples from live animals and to extend the list of susceptible species. A PCR targeting a portion of ORF1a of python nidoviruses was used to detect nidoviruses in diagnostic samples from live boas and pythons. A total of 95 pythons, 84 boas and 22 snakes of unknown species were included in the study. Samples tested included oral swabs and whole blood. Nidoviruses were detected in 27.4% of the pythons and 2.4% of the boas tested. They were most commonly detected in ball pythons (Python [P.] regius) and Indian rock pythons (P. molurus), but were also detected for the first time in other python species, including Morelia spp. and Boa constrictor. Oral swabs were most commonly tested positive. The PCR described here can be used for the detection of nidoviruses in oral swabs from live snakes. These viruses appear to be relatively common among snakes in captivity in Europe and screening for these viruses should be considered in the clinical work-up. Nidoviruses are believed to be an important cause of respiratory disease in pythons, but can also infect boas. Detection of these viruses in live animals is now possible and can be of interest both in diseased animals as well as in quarantine situations.
Trypanosoma cf. varani in an imported ball python (Python reginus) from Ghana.
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.
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.
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.
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.
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
PyMidas: Interface from Python to Midas
NASA Astrophysics Data System (ADS)
Maisala, Sami; Oittinen, Tero
2014-01-01
PyMidas is an interface between Python and MIDAS, the major ESO legacy general purpose data processing system. PyMidas allows a user to exploit both the rich legacy of MIDAS software and the power of Python scripting in a unified interactive environment. PyMidas also allows the usage of other Python-based astronomical analysis systems such as PyRAF.
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.
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
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.
Olesen, Mette G; Bertelsen, Mads F; Perry, Steve F; Wang, Tobias
2008-12-15
To characterize physiologic responses of ball pythons (Python regius) following a minor surgical procedure and investigate the effects of 2 commonly used analgesics on this response. 15 healthy ball pythons. Snakes were randomly assigned to receive 1 of 3 treatments: meloxicam (0.3 mg/kg [0.14 mg/lb]; n = 5), butorphanol (5 mg/kg [2.3 mg/lb]; 5), or saline (0.9% NaCl) solution (5) before catheterization of the vertebral artery. Plasma concentrations of catecholamines and cortisol, blood pressure, heart rate, and blood gas values were measured at various times for 72.5 hours after catheterization. The 72.5-hour point was defined as baseline. Heart rate of ball pythons increased significantly during the first hour following surgery. Mean plasma epinephrine concentration increased slightly at 2.5 hours after surgery, whereas mean plasma cortisol concentration increased beginning at 1.5 hours, reaching a maximum at 6.5 hours. Mean blood pressure increased within the first hour but returned to the baseline value at 2.5 hours after surgery. After 24.5 hours, blood pressure, heart rate, and plasma hormone concentrations remained stable at baseline values. There were no significant differences in values for physiologic variables between snakes that received saline solution and those that received meloxicam or butorphanol. Measurement of physiologic variables provides a means of assessing postoperative pain in snakes. Meloxicam and butorphanol at the dosages used did not decrease the physiologic stress response and did not appear to provide analgesic effects in ball pythons.
Automating tasks in protein structure determination with the clipper python module
McNicholas, Stuart; Croll, Tristan; Burnley, Tom; Palmer, Colin M.; Hoh, Soon Wen; Jenkins, Huw T.; Dodson, Eleanor
2017-01-01
Abstract Scripting programming languages provide the fastest means of prototyping complex functionality. Those with a syntax and grammar resembling human language also greatly enhance the maintainability of the produced source code. Furthermore, the combination of a powerful, machine‐independent scripting language with binary libraries tailored for each computer architecture allows programs to break free from the tight boundaries of efficiency traditionally associated with scripts. In the present work, we describe how an efficient C++ crystallographic library such as Clipper can be wrapped, adapted and generalized for use in both crystallographic and electron cryo‐microscopy applications, scripted with the Python language. We shall also place an emphasis on best practices in automation, illustrating how this can be achieved with this new Python module. PMID:28901669
MEG and EEG data analysis with MNE-Python.
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.
Cold-induced mortality of invasive Burmese pythons in south Florida
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 radio-telemetered 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.
Leveraging Python Interoperability Tools to Improve Sapphire's Usability
DOE Office of Scientific and Technical Information (OSTI.GOV)
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.
Responses of python gastrointestinal regulatory peptides to feeding
Secor, Stephen M.; Fehsenfeld, Drew; Diamond, Jared; Adrian, Thomas E.
2001-01-01
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. PMID:11707600
MEG and EEG data analysis with MNE-Python
Gramfort, Alexandre; Luessi, Martin; Larson, Eric; Engemann, Denis A.; Strohmeier, Daniel; Brodbeck, Christian; Goj, Roman; Jas, Mainak; Brooks, Teon; Parkkonen, Lauri; Hämäläinen, Matti
2013-01-01
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. PMID:24431986
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.
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.
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.
Saccular lung cannulation in a ball python (Python regius) to treat a tracheal obstruction.
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.
A modern Python interface for the Generic Mapping Tools
NASA Astrophysics Data System (ADS)
Uieda, L.; Wessel, P.
2017-12-01
Figures generated by The Generic Mapping Tools (GMT) are present in countless publications across the Earth sciences. The command-line interface of GMT lends the tool its flexibility but also creates a barrier to entry for begginers. Meanwhile, adoption of the Python programming language has grown across the scientific community. This growth is largely due to the simplicity and low barrier to entry of the language and its ecosystem of tools. Thus, it is not surprising that there have been at least three attempts to create Python interfaces for GMT: gmtpy (github.com/emolch/gmtpy), pygmt (github.com/ian-r-rose/pygmt), and PyGMT (github.com/glimmer-cism/PyGMT). None of these projects are currently active and, with the exception of pygmt, they do not use the GMT Application Programming Interface (API) introduced in GMT 5. The two main Python libraries for plotting data on maps are the matplotlib Basemap toolkit (matplotlib.org/basemap) and Cartopy (scitools.org.uk/cartopy), both of which rely on matplotlib (matplotlib.org) as the backend for generating the figures. Basemap is known to have limitations and is being discontinued. Cartopy is an improvement over Basemap but is still bound by the speed and memory constraints of matplotlib. We present a new Python interface for GMT (GMT/Python) that makes use of the GMT API and of new features being developed for the upcoming GMT 6 release. The GMT/Python library is designed according to the norms and styles of the Python community. The library integrates with the scientific Python ecosystem by using the "virtual files" from the GMT API to implement input and output of Python data types (numpy "ndarray" for tabular data and xarray "Dataset" for grids). Other features include an object-oriented interface for creating figures, the ability to display figures in the Jupyter notebook, and descriptive aliases for GMT arguments (e.g., "region" instead of "R" and "projection" instead of "J"). GMT/Python can also serve as a backend
Python for large-scale electrophysiology.
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.
A New Python Library for Spectroscopic Analysis with MIDAS Style
NASA Astrophysics Data System (ADS)
Song, Y.; Luo, A.; Zhao, Y.
2013-10-01
The ESO MIDAS is a system for astronomers to analyze data which many astronomers are using. Python is a high level script language and there are many applications for astronomical data process. We are releasing a new Python library which realizes some MIDAS commands in Python. People can use it to write a MIDAS style Python code. We call it PydasLib. It is a Python library based on ESO MIDAS functions, which is easily used by astronomers who are familiar with the usage of MIDAS.
Practical Approach for Hyperspectral Image Processing in Python
NASA Astrophysics Data System (ADS)
Annala, L.; Eskelinen, M. A.; Hämäläinen, J.; Riihinen, A.; Pölönen, I.
2018-04-01
Python is a very popular programming language among data scientists around the world. Python can also be used in hyperspectral data analysis. There are some toolboxes designed for spectral imaging, such as Spectral Python and HyperSpy, but there is a need for analysis pipeline, which is easy to use and agile for different solutions. We propose a Python pipeline which is built on packages xarray, Holoviews and scikit-learn. We have developed some of own tools, MaskAccessor, VisualisorAccessor and a spectral index library. They also fulfill our goal of easy and agile data processing. In this paper we will present our processing pipeline and demonstrate it in practice.
Cox, Christian L; Secor, Stephen M
2007-12-01
We explored meal size and clutch (i.e., genetic) effects on the relative proportion of ingested energy that is absorbed by the gut (apparent digestive efficiency), becomes available for metabolism and growth (apparent assimilation efficiency), and is used for growth (production efficiency) for juvenile Burmese pythons (Python molurus). Sibling pythons were fed rodent meals equaling 15%, 25%, and 35% of their body mass and individuals from five different clutches were fed rodent meals equaling 25% of their body mass. For each of 11-12 consecutive feeding trials, python body mass was recorded and feces and urate of each snake was collected, dried, and weighed. Energy contents of meals (mice and rats), feces, urate, and pythons were determined using bomb calorimetry. For siblings fed three different meal sizes, growth rate increased with larger meals, but there was no significant variation among the meal sizes for any of the calculated energy efficiencies. Among the three meal sizes, apparent digestive efficiency, apparent assimilation efficiency, and production efficiency averaged 91.0%, 84.7%, and 40.7%, respectively. In contrast, each of these energy efficiencies varied significantly among the five different clutches. Among these clutches production efficiency was negatively correlated with standard metabolic rate (SMR). Clutches containing individuals with low SMR were therefore able to allocate more of ingested energy into growth.
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.
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.
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
pyMOOGi - python wrapper for MOOG
NASA Astrophysics Data System (ADS)
Adamow, Monika M.
2017-06-01
pyMOOGi is a python wrapper for MOOG. It allows to use MOOG in a classical, interactive way, but with all graphics handled by python libraries. Some MOOG features have been redesigned, like plotting with abfind driver. Also, new funtions have been added, like automatic rescaling of stellar spectrum for synth driver. pyMOOGi is an open source project.
Python for Large-Scale Electrophysiology
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. PMID:19198646
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.
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.
Banzato, Tommaso; Russo, Elisa; Finotti, Luca; Zotti, Alessandro
2012-07-01
To develop a technique for radiographic evaluation of the gastrointestinal tract in ball pythons (Python regius). 10 ball python cadavers (5 males and 5 females) and 18 healthy adult ball pythons (10 males and 8 females). Live snakes were allocated to 3 groups (A, B, and C). A dose (25 mL/kg) of barium sulfate suspension at 3 concentrations (25%, 35%, and 45% [wt/vol]) was administered through an esophageal probe to snakes in groups A, B, and C, respectively. Each evaluation ended when all the contrast medium had reached the large intestine. Transit times through the esophagus, stomach, and small intestine were recorded. Imaging quality was evaluated by 3 investigators who assigned a grading score on the basis of predetermined criteria. Statistical analysis was conducted to evaluate differences in quality among the study groups. The esophagus and stomach had a consistent distribution pattern of contrast medium, whereas 3 distribution patterns of contrast medium were identified in the small intestine, regardless of barium concentration. Significant differences in imaging quality were detected among the 3 groups. Radiographic procedures were tolerated well by all snakes. The 35% concentration of contrast medium yielded the best imaging quality. Use of contrast medium for evaluation of the cranial portion of the gastrointestinal tract could be a reliable technique for the diagnosis of gastrointestinal diseases in ball pythons. However, results of this study may not translate to other snake species because of variables identified in this group of snakes.
Automating tasks in protein structure determination with the clipper python module.
McNicholas, Stuart; Croll, Tristan; Burnley, Tom; Palmer, Colin M; Hoh, Soon Wen; Jenkins, Huw T; Dodson, Eleanor; Cowtan, Kevin; Agirre, Jon
2018-01-01
Scripting programming languages provide the fastest means of prototyping complex functionality. Those with a syntax and grammar resembling human language also greatly enhance the maintainability of the produced source code. Furthermore, the combination of a powerful, machine-independent scripting language with binary libraries tailored for each computer architecture allows programs to break free from the tight boundaries of efficiency traditionally associated with scripts. In the present work, we describe how an efficient C++ crystallographic library such as Clipper can be wrapped, adapted and generalized for use in both crystallographic and electron cryo-microscopy applications, scripted with the Python language. We shall also place an emphasis on best practices in automation, illustrating how this can be achieved with this new Python module. © 2017 The Authors Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.
Gist: A scientific graphics package for Python
DOE Office of Scientific and Technical Information (OSTI.GOV)
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 ismore » 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.« less
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
Strike kinematics and performance in juvenile ball pythons (Python regius).
Ryerson, William G; Tan, Weimin
2017-08-01
The rapid strike of snakes has interested researchers for decades. Although most work has focused on the strike performance of vipers, recent work has shown that other snakes outside of the Viperidae can strike with the same velocities and accelerations. However, to date all of these examples focus on performance in adult snakes. Here, we use high-speed video to measure the strike kinematics and performance of 10 juvenile (<6 months of age) ball pythons, Python regius. We find that juvenile P. regius strike at levels comparable to larger snakes, but with shorter durations and over shorter distances. We conclude that the juvenile P. regius maintain performance likely through manipulation of the axial musculature and accompanying elastic tissues, and that this is a first step to understanding ontogenetic changes in behavior and a potential avenue for understanding how captivity may also impact behavior. © 2017 Wiley Periodicals, Inc.
McFadden, Michael S; Bennett, R Avery; Reavill, Drury R; Ragetly, Guillaume R; Clark-Price, Stuart C
2011-09-15
To assess the clinical differences between induction of anesthesia in ball pythons with intracardiac administration of propofol and induction with isoflurane in oxygen and to assess the histologic findings over time in hearts following intracardiac administration of propofol. Prospective randomized study. 30 hatchling ball pythons (Python regius). Anesthesia was induced with intracardiac administration of propofol (10 mg/kg [4.5 mg/lb]) in 18 ball pythons and with 5% isoflurane in oxygen in 12 ball pythons. Induction time, time of anesthesia, and recovery time were recorded. Hearts from snakes receiving intracardiac administration of propofol were evaluated histologically 3, 7, 14, 30, and 60 days following propofol administration. Induction time with intracardiac administration of propofol was significantly shorter than induction time with 5% isoflurane in oxygen. No significant differences were found in total anesthesia time. Recovery following intracardiac administration of propofol was significantly longer than recovery following induction of anesthesia with isoflurane in oxygen. Heart tissue evaluated histologically at 3, 7, and 14 days following intracardiac administration of propofol had mild inflammatory changes, and no histopathologic lesions were seen 30 and 60 days following propofol administration. Intracardiac injection of propofol in snakes is safe and provides a rapid induction of anesthesia but leads to prolonged recovery, compared with that following induction with isoflurane. Histopathologic lesions in heart tissues following intracardiac injection of propofol were mild and resolved after 14 days.
Computed tomography of ball pythons (Python regius) in curled recumbency.
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. © 2014 American College of Veterinary Radiology.
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.
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. Copyright © 2014 Elsevier Ltd. All rights reserved.
SpiceyPy, a Python Wrapper for SPICE
NASA Astrophysics Data System (ADS)
Annex, A.
2017-06-01
SpiceyPy is an open source Python wrapper for the NAIF SPICE toolkit. It is available for macOS, Linux, and Windows platforms and for Python versions 2.7.x and 3.x as well as Anaconda. SpiceyPy can be installed by running: “pip install spiceypy.”
modlAMP: Python for antimicrobial peptides.
Müller, Alex T; Gabernet, Gisela; Hiss, Jan A; Schneider, Gisbert
2017-09-01
We have implemented the lecular esign aboratory's nti icrobial eptides package ( ), a Python-based software package for the design, classification and visual representation of peptide data. modlAMP offers functions for molecular descriptor calculation and the retrieval of amino acid sequences from public or local sequence databases, and provides instant access to precompiled datasets for machine learning. The package also contains methods for the analysis and representation of circular dichroism spectra. The modlAMP Python package is available under the BSD license from URL http://doi.org/10.5905/ethz-1007-72 or via pip from the Python Package Index (PyPI). gisbert.schneider@pharma.ethz.ch. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com
DOE Office of Scientific and Technical Information (OSTI.GOV)
Busby, L.
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.
Pythons metabolize prey to fuel the response to feeding.
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
Python in the NERSC Exascale Science Applications Program for Data
DOE Office of Scientific and Technical Information (OSTI.GOV)
Ronaghi, Zahra; Thomas, Rollin; Deslippe, Jack
We describe a new effort at the National Energy Re- search Scientific Computing Center (NERSC) in performance analysis and optimization of scientific Python applications targeting the Intel Xeon Phi (Knights Landing, KNL) many- core architecture. The Python-centered work outlined here is part of a larger effort called the NERSC Exascale Science Applications Program (NESAP) for Data. NESAP for Data focuses on applications that process and analyze high-volume, high-velocity data sets from experimental/observational science (EOS) facilities supported by the US Department of Energy Office of Science. We present three case study applications from NESAP for Data that use Python. These codesmore » vary in terms of “Python purity” from applications developed in pure Python to ones that use Python mainly as a convenience layer for scientists without expertise in lower level programming lan- guages like C, C++ or Fortran. The science case, requirements, constraints, algorithms, and initial performance optimizations for each code are discussed. Our goal with this paper is to contribute to the larger conversation around the role of Python in high-performance computing today and tomorrow, highlighting areas for future work and emerging best practices« less
Python as a federation tool for GENESIS 3.0.
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
Python as a Federation Tool for GENESIS 3.0
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
Python erythrocytes are resistant to α-hemolysin from Escherichia coli.
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.
On Parallel Software Engineering Education Using Python
ERIC Educational Resources Information Center
Marowka, Ami
2018-01-01
Python is gaining popularity in academia as the preferred language to teach novices serial programming. The syntax of Python is clean, easy, and simple to understand. At the same time, it is a high-level programming language that supports multi programming paradigms such as imperative, functional, and object-oriented. Therefore, by default, it is…
PYCHEM: a multivariate analysis package for python.
Jarvis, Roger M; Broadhurst, David; Johnson, Helen; O'Boyle, Noel M; Goodacre, Royston
2006-10-15
We have implemented a multivariate statistical analysis toolbox, with an optional standalone graphical user interface (GUI), using the Python scripting language. This is a free and open source project that addresses the need for a multivariate analysis toolbox in Python. Although the functionality provided does not cover the full range of multivariate tools that are available, it has a broad complement of methods that are widely used in the biological sciences. In contrast to tools like MATLAB, PyChem 2.0.0 is easily accessible and free, allows for rapid extension using a range of Python modules and is part of the growing amount of complementary and interoperable scientific software in Python based upon SciPy. One of the attractions of PyChem is that it is an open source project and so there is an opportunity, through collaboration, to increase the scope of the software and to continually evolve a user-friendly platform that has applicability across a wide range of analytical and post-genomic disciplines. http://sourceforge.net/projects/pychem
Charming Users into Scripting CIAO with Python
NASA Astrophysics Data System (ADS)
Burke, D. J.
2011-07-01
The Science Data Systems group of the Chandra X-ray Center provides a number of scripts and Python modules that extend the capabilities of CIAO. Experience in converting the existing scripts—written in a variety of languages such as bash, csh/tcsh, Perl and S-Lang—to Python, and conversations with users, led to the development of the ciao_contrib.runtool module. This allows users to easily run CIAO tools from Python scripts, and utilizes the metadata provided by the parameter-file system to create an API that provides the flexibility and safety guarantees of the command-line. The module is provided to the user community and is being used within our group to create new scripts.
Federal Register 2010, 2011, 2012, 2013, 2014
2010-07-01
... Python Species, and Four Anaconda Species as Injurious Reptiles AGENCY: Fish and Wildlife Service... regulations to add Indian python (Python molurus, including Burmese python Python molurus bivittatus), reticulated python (Broghammerus reticulatus or Python reticulatus), Northern African python (Python sebae...
Facultative thermogenesis during brooding is not the norm among pythons.
Brashears, Jake; DeNardo, Dale F
2015-08-01
Facultative thermogenesis is often attributed to pythons in general despite limited comparative data available for the family. While all species within Pythonidae brood their eggs, only two species are known to produce heat to enhance embryonic thermal regulation. By contrast, a few python species have been reported to have insignificant thermogenic capabilities. To provide insight into potential phylogenetic, morphological, and ecological factors influencing thermogenic capability among pythons, we measured metabolic rates and clutch-environment temperature differentials at two environmental temperatures-python preferred brooding temperature (31.5 °C) and a sub-optimal temperature (25.5 °C)-in six species of pythons, including members of two major phylogenetic branches currently devoid of data on the subject. We found no evidence of facultative thermogenesis in five species: Aspidites melanocephalus, A. ramsayi, Morelia viridis, M. spilota cheynei, and Python regius. However, we found that Bothrochilus boa had a thermal metabolic sensitivity indicative of facultative thermogenesis (i.e., a higher metabolic rate at the lower temperature). However, its metabolic rate was quite low and technical challenges prevented us from measuring temperature differential to make conclusions about facultative endothermy in this species. Regardless, our data combined with existing literature demonstrate that facultative thermogenesis is not as widespread among pythons as previously thought.
Consumption of bird eggs by invasive Burmese Pythons in Florida
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.
Python scripting in the nengo simulator.
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.
Python Scripting in the Nengo Simulator
Stewart, Terrence C.; Tripp, Bryan; Eliasmith, Chris
2008-01-01
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. PMID:19352442
Betrayal: radio-tagged Burmese pythons reveal locations of conspecifics in Everglades National Park
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.
Uccellini, Lorenzo; Ossiboff, Robert J; de Matos, Ricardo E C; Morrisey, James K; Petrosov, Alexandra; Navarrete-Macias, Isamara; Jain, Komal; Hicks, Allison L; Buckles, Elizabeth L; Tokarz, Rafal; McAloose, Denise; Lipkin, Walter Ian
2014-08-08
Respiratory infections are important causes of morbidity and mortality in reptiles; however, the causative agents are only infrequently identified. Pneumonia, tracheitis and esophagitis were reported in a collection of ball pythons (Python regius). Eight of 12 snakes had evidence of bacterial pneumonia. High-throughput sequencing of total extracted nucleic acids from lung, esophagus and spleen revealed a novel nidovirus. PCR indicated the presence of viral RNA in lung, trachea, esophagus, liver, and spleen. In situ hybridization confirmed the presence of intracellular, intracytoplasmic viral nucleic acids in the lungs of infected snakes. Phylogenetic analysis based on a 1,136 amino acid segment of the polyprotein suggests that this virus may represent a new species in the subfamily Torovirinae. This report of a novel nidovirus in ball pythons may provide insight into the pathogenesis of respiratory disease in this species and enhances our knowledge of the diversity of nidoviruses.
Scripting MODFLOW Model Development Using Python and FloPy.
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. © 2016, National Ground Water Association.
Scripting MODFLOW model development using Python and FloPy
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.
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.
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.
The Discovery of XY Sex Chromosomes in a Boa and Python.
Gamble, Tony; Castoe, Todd A; Nielsen, Stuart V; Banks, Jaison L; Card, Daren C; Schield, Drew R; Schuett, Gordon W; Booth, Warren
2017-07-24
For over 50 years, biologists have accepted that all extant snakes share the same ZW sex chromosomes derived from a common ancestor [1-3], with different species exhibiting sex chromosomes at varying stages of differentiation. Accordingly, snakes have been a well-studied model for sex chromosome evolution in animals [1, 4]. A review of the literature, however, reveals no compelling support that boas and pythons possess ZW sex chromosomes [2, 5]. Furthermore, phylogenetic patterns of facultative parthenogenesis in snakes and a sex-linked color mutation in the ball python (Python regius) are best explained by boas and pythons possessing an XY sex chromosome system [6, 7]. Here we demonstrate that a boa (Boa imperator) and python (Python bivittatus) indeed possess XY sex chromosomes, based on the discovery of male-specific genetic markers in both species. We use these markers, along with transcriptomic and genomic data, to identify distinct sex chromosomes in boas and pythons, demonstrating that XY systems evolved independently in each lineage. This discovery highlights the dynamic evolution of vertebrate sex chromosomes and further enhances the value of snakes as a model for studying sex chromosome evolution. Copyright © 2017 Elsevier Ltd. All rights reserved.
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.
Fatty acids identified in the Burmese python promote beneficial cardiac growth.
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.
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.
NASA Astrophysics Data System (ADS)
Merticariu, Vlad; Misev, Dimitar; Baumann, Peter
2017-04-01
While python has developed into the lingua franca in Data Science there is often a paradigm break when accessing specialized tools. In particular for one of the core data categories in science and engineering, massive multi-dimensional arrays, out-of-memory solutions typically employ their own, different models. We discuss this situation on the example of the scalable open-source array engine, rasdaman ("raster data manager") which offers access to and processing of Petascale multi-dimensional arrays through an SQL-style array query language, rasql. Such queries are executed in the server on a storage engine utilizing adaptive array partitioning and based on a processing engine implementing a "tile streaming" paradigm to allow processing of arrays massively larger than server RAM. The rasdaman QL has acted as blueprint for forthcoming ISO Array SQL and the Open Geospatial Consortium (OGC) geo analytics language, Web Coverage Processing Service, adopted in 2008. Not surprisingly, rasdaman is OGC and INSPIRE Reference Implementation for their "Big Earth Data" standards suite. Recently, rasdaman has been augmented with a python interface which allows to transparently interact with the database (credits go to Siddharth Shukla's Master Thesis at Jacobs University). Programmers do not need to know the rasdaman query language, as the operators are silently transformed, through lazy evaluation, into queries. Arrays delivered are likewise automatically transformed into their python representation. In the talk, the rasdaman concept will be illustrated with the help of large-scale real-life examples of operational satellite image and weather data services, and sample python code.
Pybel: a Python wrapper for the OpenBabel cheminformatics toolkit
O'Boyle, Noel M; Morley, Chris; Hutchison, Geoffrey R
2008-01-01
Background Scripting languages such as Python are ideally suited to common programming tasks in cheminformatics such as data analysis and parsing information from files. However, for reasons of efficiency, cheminformatics toolkits such as the OpenBabel toolkit are often implemented in compiled languages such as C++. We describe Pybel, a Python module that provides access to the OpenBabel toolkit. Results Pybel wraps the direct toolkit bindings to simplify common tasks such as reading and writing molecular files and calculating fingerprints. Extensive use is made of Python iterators to simplify loops such as that over all the molecules in a file. A Pybel Molecule can be easily interconverted to an OpenBabel OBMol to access those methods or attributes not wrapped by Pybel. Conclusion Pybel allows cheminformaticians to rapidly develop Python scripts that manipulate chemical information. It is open source, available cross-platform, and offers the power of the OpenBabel toolkit to Python programmers. PMID:18328109
Pybel: a Python wrapper for the OpenBabel cheminformatics toolkit.
O'Boyle, Noel M; Morley, Chris; Hutchison, Geoffrey R
2008-03-09
Scripting languages such as Python are ideally suited to common programming tasks in cheminformatics such as data analysis and parsing information from files. However, for reasons of efficiency, cheminformatics toolkits such as the OpenBabel toolkit are often implemented in compiled languages such as C++. We describe Pybel, a Python module that provides access to the OpenBabel toolkit. Pybel wraps the direct toolkit bindings to simplify common tasks such as reading and writing molecular files and calculating fingerprints. Extensive use is made of Python iterators to simplify loops such as that over all the molecules in a file. A Pybel Molecule can be easily interconverted to an OpenBabel OBMol to access those methods or attributes not wrapped by Pybel. Pybel allows cheminformaticians to rapidly develop Python scripts that manipulate chemical information. It is open source, available cross-platform, and offers the power of the OpenBabel toolkit to Python programmers.
Automating Disk Forensic Processing with SleuthKit, XML and Python
2009-05-01
1 Automating Disk Forensic Processing with SleuthKit, XML and Python Simson L. Garfinkel Abstract We have developed a program called fiwalk which...files themselves. We show how it is relatively simple to create automated disk forensic applications using a Python module we have written that reads...software that the portable device may contain. Keywords: Computer Forensics; XML; Sleuth Kit; Python I. INTRODUCTION In recent years we have found many
Nunez-Iglesias, Juan; Blanch, Adam J; Looker, Oliver; Dixon, Matthew W; Tilley, Leann
2018-01-01
We present Skan (Skeleton analysis), a Python library for the analysis of the skeleton structures of objects. It was inspired by the "analyse skeletons" plugin for the Fiji image analysis software, but its extensive Application Programming Interface (API) allows users to examine and manipulate any intermediate data structures produced during the analysis. Further, its use of common Python data structures such as SciPy sparse matrices and pandas data frames opens the results to analysis within the extensive ecosystem of scientific libraries available in Python. We demonstrate the validity of Skan's measurements by comparing its output to the established Analyze Skeletons Fiji plugin, and, with a new scanning electron microscopy (SEM)-based method, we confirm that the malaria parasite Plasmodium falciparum remodels the host red blood cell cytoskeleton, increasing the average distance between spectrin-actin junctions.
Looker, Oliver; Dixon, Matthew W.; Tilley, Leann
2018-01-01
We present Skan (Skeleton analysis), a Python library for the analysis of the skeleton structures of objects. It was inspired by the “analyse skeletons” plugin for the Fiji image analysis software, but its extensive Application Programming Interface (API) allows users to examine and manipulate any intermediate data structures produced during the analysis. Further, its use of common Python data structures such as SciPy sparse matrices and pandas data frames opens the results to analysis within the extensive ecosystem of scientific libraries available in Python. We demonstrate the validity of Skan’s measurements by comparing its output to the established Analyze Skeletons Fiji plugin, and, with a new scanning electron microscopy (SEM)-based method, we confirm that the malaria parasite Plasmodium falciparum remodels the host red blood cell cytoskeleton, increasing the average distance between spectrin-actin junctions. PMID:29472997
Status of parallel Python-based implementation of UEDGE
NASA Astrophysics Data System (ADS)
Umansky, M. V.; Pankin, A. Y.; Rognlien, T. D.; Dimits, A. M.; Friedman, A.; Joseph, I.
2017-10-01
The tokamak edge transport code UEDGE has long used the code-development and run-time framework Basis. However, with the support for Basis expected to terminate in the coming years, and with the advent of the modern numerical language Python, it has become desirable to move UEDGE to Python, to ensure its long-term viability. Our new Python-based UEDGE implementation takes advantage of the portable build system developed for FACETS. The new implementation gives access to Python's graphical libraries and numerical packages for pre- and post-processing, and support of HDF5 simplifies exchanging data. The older serial version of UEDGE has used for time-stepping the Newton-Krylov solver NKSOL. The renovated implementation uses backward Euler discretization with nonlinear solvers from PETSc, which has the promise to significantly improve the UEDGE parallel performance. We will report on assessment of some of the extended UEDGE capabilities emerging in the new implementation, and will discuss the future directions. Work performed for U.S. DOE by LLNL under contract DE-AC52-07NA27344.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Helmus, Jonathan J.; Collis, Scott M.
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
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
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.
Marsh rabbit mortalities tie pythons to the precipitous decline of mammals in the Everglades
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.
Marsh rabbit mortalities tie pythons to the precipitous decline of mammals in the Everglades.
McCleery, Robert A; Sovie, Adia; Reed, Robert N; Cunningham, Mark W; Hunter, Margaret E; Hart, Kristen M
2015-04-22
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. © 2015 The Author(s) Published by the Royal Society. All rights reserved.
Marsh rabbit mortalities tie pythons to the precipitous decline of mammals in the Everglades
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
Ecological correlates of invasion impact for Burmese pythons in Florida
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.
Young, L A; Schumacher, J; Papich, M G; Jacobson, E R
1997-03-01
Eleven juvenile Burmese pythons (Python molurus bivittatus) weighing 0.75-1.75 kg were randomly divided into two groups. Blood samples were obtained through surgically placed anterior carotid artery cannulas. Six pythons received a single i.m. injection of enrofloxacin at 5 mg/kg. Blood samples were obtained at 0.5, 1, 3, 6, 12, 24, 48, 72, and 96 hr postinjection. A mean (+/- SD) maximal plasma concentration of 1.66 (+/- 0.42) micrograms/ml was measured at 5.75 hr postinjection. The harmonic mean half-life was calculated to be 6.37 hr. The second group of five snakes received enrofloxacin at 5 mg/kg i.m. s.i.d. for 5 days. Blood was collected immediately before each injection and at 6 hr after each injection. Over the 5-day period, there was a stepwise increase in mean trough plasma concentrations of enrofloxacin. Clinically effective peak plasma enrofloxacin concentrations were attained after the first injection but did not significantly increase during the sampling period. Pharmacokinetic data were assessed against minimum inhibitory concentrations of enrofloxacin for Pseudomonas ssp. isolates in snakes obtained from historical data at the Veterinary Medical Teaching Hospital, University of Florida. Enrofloxacin should be administered at 10 mg/kg i.m. every 48 hr when treating Pseudomonas ssp. infections in juvenile Burmese pythons. Treatment of infections of more enrofloxacin-sensitive gram-negative bacteria could be achieved with the administration of an initial i.m. dose of 10 mg/kg followed by 5 mg/kg every 48 hr.
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
Accelerating wave propagation modeling in the frequency domain using Python
NASA Astrophysics Data System (ADS)
Jo, Sang Hoon; Park, Min Jun; Ha, Wan Soo
2017-04-01
Python is a dynamic programming language adopted in many science and engineering areas. We used Python to simulate wave propagation in the frequency domain. We used the Pardiso matrix solver to solve the impedance matrix of the wave equation. Numerical examples shows that Python with numpy consumes longer time to construct the impedance matrix using the finite element method when compared with Fortran; however we could reduce the time significantly to be comparable to that of Fortran using a simple Numba decorator.
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.
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
p3d--Python module for structural bioinformatics.
Fufezan, Christian; Specht, Michael
2009-08-21
High-throughput bioinformatic analysis tools are needed to mine the large amount of structural data via knowledge based approaches. The development of such tools requires a robust interface to access the structural data in an easy way. For this the Python scripting language is the optimal choice since its philosophy is to write an understandable source code. p3d is an object oriented Python module that adds a simple yet powerful interface to the Python interpreter to process and analyse three dimensional protein structure files (PDB files). p3d's strength arises from the combination of a) very fast spatial access to the structural data due to the implementation of a binary space partitioning (BSP) tree, b) set theory and c) functions that allow to combine a and b and that use human readable language in the search queries rather than complex computer language. All these factors combined facilitate the rapid development of bioinformatic tools that can perform quick and complex analyses of protein structures. p3d is the perfect tool to quickly develop tools for structural bioinformatics using the Python scripting language.
CSB: a Python framework for structural bioinformatics.
Kalev, Ivan; Mechelke, Martin; Kopec, Klaus O; Holder, Thomas; Carstens, Simeon; Habeck, Michael
2012-11-15
Computational Structural Biology Toolbox (CSB) is a cross-platform Python class library for reading, storing and analyzing biomolecular structures with rich support for statistical analyses. CSB is designed for reusability and extensibility and comes with a clean, well-documented API following good object-oriented engineering practice. Stable release packages are available for download from the Python Package Index (PyPI) as well as from the project's website http://csb.codeplex.com. ivan.kalev@gmail.com or michael.habeck@tuebingen.mpg.de
Introduction to Python for CMF Authority Users
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pritchett-Sheats, Lori A.
This talk is a very broad over view of Python that highlights key features in the language used in the Common Model Framework (CMF). I assume that the audience has some programming experience in a shell scripting language (C shell, Bash, PERL) or other high level language (C/C++/ Fortran). The talk will cover Python data types, classes (objects) and basic programming constructs. The talk concludes with slides describing how I developed the basic classes for a TITANS homework assignment.
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
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. © 2014. Published by The Company of Biologists Ltd.
Gautier, Laurent
2010-12-21
Computer languages can be domain-related, and in the case of multidisciplinary projects, knowledge of several languages will be needed in order to quickly implements ideas. Moreover, each computer language has relative strong points, making some languages better suited than others for a given task to be implemented. The Bioconductor project, based on the R language, has become a reference for the numerical processing and statistical analysis of data coming from high-throughput biological assays, providing a rich selection of methods and algorithms to the research community. At the same time, Python has matured as a rich and reliable language for the agile development of prototypes or final implementations, as well as for handling large data sets. The data structures and functions from Bioconductor can be exposed to Python as a regular library. This allows a fully transparent and native use of Bioconductor from Python, without one having to know the R language and with only a small community of translators required to know both. To demonstrate this, we have implemented such Python representations for key infrastructure packages in Bioconductor, letting a Python programmer handle annotation data, microarray data, and next-generation sequencing data. Bioconductor is now not solely reserved to R users. Building a Python application using Bioconductor functionality can be done just like if Bioconductor was a Python package. Moreover, similar principles can be applied to other languages and libraries. Our Python package is available at: http://pypi.python.org/pypi/rpy2-bioconductor-extensions/.
Ecological correlates of invasion impact for Burmese pythons in Florida.
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. © 2012 Wiley Publishing Asia Pty Ltd, ISZS and IOZ/CAS.
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.
Wyrm: A Brain-Computer Interface Toolbox in Python.
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.
Renal plasticity in response to feeding in the Burmese python, Python molurus bivittatus.
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. Copyright © 2015 Elsevier Inc. All rights reserved.
2010-01-01
Background Computer languages can be domain-related, and in the case of multidisciplinary projects, knowledge of several languages will be needed in order to quickly implements ideas. Moreover, each computer language has relative strong points, making some languages better suited than others for a given task to be implemented. The Bioconductor project, based on the R language, has become a reference for the numerical processing and statistical analysis of data coming from high-throughput biological assays, providing a rich selection of methods and algorithms to the research community. At the same time, Python has matured as a rich and reliable language for the agile development of prototypes or final implementations, as well as for handling large data sets. Results The data structures and functions from Bioconductor can be exposed to Python as a regular library. This allows a fully transparent and native use of Bioconductor from Python, without one having to know the R language and with only a small community of translators required to know both. To demonstrate this, we have implemented such Python representations for key infrastructure packages in Bioconductor, letting a Python programmer handle annotation data, microarray data, and next-generation sequencing data. Conclusions Bioconductor is now not solely reserved to R users. Building a Python application using Bioconductor functionality can be done just like if Bioconductor was a Python package. Moreover, similar principles can be applied to other languages and libraries. Our Python package is available at: http://pypi.python.org/pypi/rpy2-bioconductor-extensions/ PMID:21210978
Alxneit, Ivo
2018-03-30
A python module (HRTEMFringeAnalyzer) is reported to evaluate the local crystallinity of samples from high-resolution transmission electron microscopy images in a mostly automated fashion. The user only selects the size of a square analyser window and a step size which translates the window in the micrograph. Together they define the resolution of the results obtained. Regions where fringe patterns are visible are identified and their lattice spacing d and direction ϕ as well as the corresponding mean errors σ determined. 1/σd is proportional to the coherence length of the structure, whereas σφ is a measure of how well the direction of the fringes is defined. Maps of these four indicators are computed. The performance of the program is demonstrated on two very different samples: ill-crystalline carbon deposits on a coked Ni/LFNO (reduced LaFe 0.8 Ni 0.2 O3±δ) catalyst and well-crystallized nanoparticles of zinc doped ceria. In the latter case, the automatic segmentation of large aggregates into individual crystalline domains is achieved by ϕ maps. © 2018 The Authors Journal of Microscopy © 2018 Royal Microscopical Society.
PyEEG: an open source Python module for EEG/MEG feature extraction.
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.
PyEEG: An Open Source Python Module for EEG/MEG Feature Extraction
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. PMID:21512582
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. © 2015. Published by The Company of Biologists Ltd.
Cole, Grayson L; Lux, Cassie N; Schumacher, Juergen P; Seibert, Rachel L; Sadler, Ryan A; Henderson, Andrea L; Odoi, Agricola; Newkirk, Kim M
2015-10-01
To evaluate effects of laser treatment on incisional wound healing in ball pythons (Python regius). 6 healthy adult ball pythons. Snakes were sedated, a skin biopsy specimen was collected for histologic examination, and eight 2-cm skin incisions were made in each snake; each incision was closed with staples (day 0). Gross evaluation of all incision sites was performed daily for 30 days, and a wound score was assigned. Four incisions of each snake were treated (5 J/cm(2) and a wavelength of 980 nm on a continuous wave sequence) by use of a class 4 laser once daily for 7 consecutive days; the other 4 incisions were not treated. Two excisional skin biopsy specimens (1 control and 1 treatment) were collected from each snake on days 2, 7, 14, and 30 and evaluated microscopically. Scores were assigned for total inflammation, degree of fibrosis, and collagen maturity. Generalized linear models were used to investigate the effect of treatment on each variable. Wound scores for laser-treated incisions were significantly better than scores for control incisions on day 2 but not at other time points. There were no significant differences in necrosis, fibroplasia, inflammation, granuloma formation, or bacterial contamination between control and treatment groups. Collagen maturity was significantly better for the laser-treated incisions on day 14. Laser treatment resulted in a significant increase in collagen maturity at day 14 but did not otherwise significantly improve healing of skin incisions.
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.
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.
First record of invasive Burmese Python oviposition and brooding inside an anthropogenic structure
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.
OMPC: an Open-Source MATLAB®-to-Python Compiler
Jurica, Peter; van Leeuwen, Cees
2008-01-01
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®, 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®-to-Python Compiler (OMPC), a platform that uses syntax adaptation and emulation to allow transparent import of existing MATLAB® functions into Python programs. The imported MATLAB® modules will run independently of MATLAB®, 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®. OMPC is available at http://ompc.juricap.com. PMID:19225577
OMPC: an Open-Source MATLAB-to-Python Compiler.
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.
Using Blackboard and Skype for Mentoring Beginning Teachers
ERIC Educational Resources Information Center
Suk Hwang, Young; Vrongistinos, Konstantinos
2012-01-01
The purpose of this article is to examine the nature of the Blackboard and Skype-based electronic mentoring system for beginning teachers. The Quality Teachers for Quality Students project developed an electronic mentoring system between beginning teachers and experienced teachers to support beginning teachers' instructional and classroom…
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.
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.
The effects of UV light on calcium metabolism in ball pythons (Python regius).
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.
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.
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.
Martínez, Jorge; Segura, Pablo; García, David; Aduriz, Gorka; Ibabe, José C; Peris, Bernardo; Corpa, Juan M
2006-09-01
A seven-year-old female Indian python (Python molurus) weighing about 35kg was euthanased after several clinical episodes of stomatitis, pneumonia, ophthalmitis and dystocia over a period of four years. The animal had been maintained in a terrarium in a circus truck at an adequate temperature. During shows, however, the snake was considered to be exposed to stressful conditions for several hours at a time at low temperatures and with noise and bright lights. A post-mortem examination indicated ulcerative stomatitis, osteomyelitis, severe pneumonia and numerous granulomata and multifocal necrosis in stomach and spleen. Corynebacterium macginleyi was isolated in pure culture from the ulcerative stomatitis, and mixed with Stenotrophomonas maltophilia from the lungs and spleen. The findings indicated that the snake had died from a septicaemic process caused by C. macginleyi, probably originating from the stomatitis. The role of S. maltophilia as a secondary agent is discussed. The stress of the circus show and poor husbandry may have predisposed the animal to infection and septicaemia. This is the first report of C. macginleyi causing disease in a snake.
Postprandial remodeling of the gut microbiota in Burmese pythons
Costello, Elizabeth K.; Gordon, Jeffrey I.; Secor, Stephen M.; Knight, Rob
2014-01-01
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. Because many model species (e.g., 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 employed 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 reduced overall diversity. A marked postprandial shift in bacterial community configuration occurred. Between 12 hours 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 appeared 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. PMID:20520652
DendroPy: a Python library for phylogenetic computing.
Sukumaran, Jeet; Holder, Mark T
2010-06-15
DendroPy is a cross-platform library for the Python programming language that provides for object-oriented reading, writing, simulation and manipulation of phylogenetic data, with an emphasis on phylogenetic tree operations. DendroPy uses a splits-hash mapping to perform rapid calculations of tree distances, similarities and shape under various metrics. It contains rich simulation routines to generate trees under a number of different phylogenetic and coalescent models. DendroPy's data simulation and manipulation facilities, in conjunction with its support of a broad range of phylogenetic data formats (NEXUS, Newick, PHYLIP, FASTA, NeXML, etc.), allow it to serve a useful role in various phyloinformatics and phylogeographic pipelines. The stable release of the library is available for download and automated installation through the Python Package Index site (http://pypi.python.org/pypi/DendroPy), while the active development source code repository is available to the public from GitHub (http://github.com/jeetsukumaran/DendroPy).
graphkernels: R and Python packages for graph comparison
Ghisu, M Elisabetta; Llinares-López, Felipe; Borgwardt, Karsten
2018-01-01
Abstract Summary Measuring the similarity of graphs is a fundamental step in the analysis of graph-structured data, which is omnipresent in computational biology. Graph kernels have been proposed as a powerful and efficient approach to this problem of graph comparison. Here we provide graphkernels, the first R and Python graph kernel libraries including baseline kernels such as label histogram based kernels, classic graph kernels such as random walk based kernels, and the state-of-the-art Weisfeiler-Lehman graph kernel. The core of all graph kernels is implemented in C ++ for efficiency. Using the kernel matrices computed by the package, we can easily perform tasks such as classification, regression and clustering on graph-structured samples. Availability and implementation The R and Python packages including source code are available at https://CRAN.R-project.org/package=graphkernels and https://pypi.python.org/pypi/graphkernels. Contact mahito@nii.ac.jp or elisabetta.ghisu@bsse.ethz.ch Supplementary information Supplementary data are available online at Bioinformatics. PMID:29028902
graphkernels: R and Python packages for graph comparison.
Sugiyama, Mahito; Ghisu, M Elisabetta; Llinares-López, Felipe; Borgwardt, Karsten
2018-02-01
Measuring the similarity of graphs is a fundamental step in the analysis of graph-structured data, which is omnipresent in computational biology. Graph kernels have been proposed as a powerful and efficient approach to this problem of graph comparison. Here we provide graphkernels, the first R and Python graph kernel libraries including baseline kernels such as label histogram based kernels, classic graph kernels such as random walk based kernels, and the state-of-the-art Weisfeiler-Lehman graph kernel. The core of all graph kernels is implemented in C ++ for efficiency. Using the kernel matrices computed by the package, we can easily perform tasks such as classification, regression and clustering on graph-structured samples. The R and Python packages including source code are available at https://CRAN.R-project.org/package=graphkernels and https://pypi.python.org/pypi/graphkernels. mahito@nii.ac.jp or elisabetta.ghisu@bsse.ethz.ch. Supplementary data are available online at Bioinformatics. © The Author(s) 2017. Published by Oxford University Press.
GillesPy: A Python Package for Stochastic Model Building and Simulation.
Abel, John H; Drawert, Brian; Hellander, Andreas; Petzold, Linda R
2016-09-01
GillesPy is an open-source Python package for model construction and simulation of stochastic biochemical systems. GillesPy consists of a Python framework for model building and an interface to the StochKit2 suite of efficient simulation algorithms based on the Gillespie stochastic simulation algorithms (SSA). To enable intuitive model construction and seamless integration into the scientific Python stack, we present an easy to understand, action-oriented programming interface. Here, we describe the components of this package and provide a detailed example relevant to the computational biology community.
GillesPy: A Python Package for Stochastic Model Building and Simulation
Abel, John H.; Drawert, Brian; Hellander, Andreas; Petzold, Linda R.
2017-01-01
GillesPy is an open-source Python package for model construction and simulation of stochastic biochemical systems. GillesPy consists of a Python framework for model building and an interface to the StochKit2 suite of efficient simulation algorithms based on the Gillespie stochastic simulation algorithms (SSA). To enable intuitive model construction and seamless integration into the scientific Python stack, we present an easy to understand, action-oriented programming interface. Here, we describe the components of this package and provide a detailed example relevant to the computational biology community. PMID:28630888
Goloborodko, Anton A; Levitsky, Lev I; Ivanov, Mark V; Gorshkov, Mikhail V
2013-02-01
Pyteomics is a cross-platform, open-source Python library providing a rich set of tools for MS-based proteomics. It provides modules for reading LC-MS/MS data, search engine output, protein sequence databases, theoretical prediction of retention times, electrochemical properties of polypeptides, mass and m/z calculations, and sequence parsing. Pyteomics is available under Apache license; release versions are available at the Python Package Index http://pypi.python.org/pyteomics, the source code repository at http://hg.theorchromo.ru/pyteomics, documentation at http://packages.python.org/pyteomics. Pyteomics.biolccc documentation is available at http://packages.python.org/pyteomics.biolccc/. Questions on installation and usage can be addressed to pyteomics mailing list: pyteomics@googlegroups.com.
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.
MontePython 3: Parameter inference code for cosmology
NASA Astrophysics Data System (ADS)
Brinckmann, Thejs; Lesgourgues, Julien; Audren, Benjamin; Benabed, Karim; Prunet, Simon
2018-05-01
MontePython 3 provides numerous ways to explore parameter space using Monte Carlo Markov Chain (MCMC) sampling, including Metropolis-Hastings, Nested Sampling, Cosmo Hammer, and a Fisher sampling method. This improved version of the Monte Python (ascl:1307.002) parameter inference code for cosmology offers new ingredients that improve the performance of Metropolis-Hastings sampling, speeding up convergence and offering significant time improvement in difficult runs. Additional likelihoods and plotting options are available, as are post-processing algorithms such as Importance Sampling and Adding Derived Parameter.
ACPYPE - AnteChamber PYthon Parser interfacE.
Sousa da Silva, Alan W; Vranken, Wim F
2012-07-23
ACPYPE (or AnteChamber PYthon Parser interfacE) is a wrapper script around the ANTECHAMBER software that simplifies the generation of small molecule topologies and parameters for a variety of molecular dynamics programmes like GROMACS, CHARMM and CNS. It is written in the Python programming language and was developed as a tool for interfacing with other Python based applications such as the CCPN software suite (for NMR data analysis) and ARIA (for structure calculations from NMR data). ACPYPE is open source code, under GNU GPL v3, and is available as a stand-alone application at http://www.ccpn.ac.uk/acpype and as a web portal application at http://webapps.ccpn.ac.uk/acpype. We verified the topologies generated by ACPYPE in three ways: by comparing with default AMBER topologies for standard amino acids; by generating and verifying topologies for a large set of ligands from the PDB; and by recalculating the structures for 5 protein-ligand complexes from the PDB. ACPYPE is a tool that simplifies the automatic generation of topology and parameters in different formats for different molecular mechanics programmes, including calculation of partial charges, while being object oriented for integration with other applications.
PyPDB: a Python API for the Protein Data Bank.
Gilpin, William
2016-01-01
We have created a Python programming interface for the RCSB Protein Data Bank (PDB) that allows search and data retrieval for a wide range of result types, including BLAST and sequence motif queries. The API relies on the existing XML-based API and operates by creating custom XML requests from native Python types, allowing extensibility and straightforward modification. The package has the ability to perform many types of advanced search of the PDB that are otherwise only available through the PDB website. PyPDB is implemented exclusively in Python 3 using standard libraries for maximal compatibility. The most up-to-date version, including iPython notebooks containing usage tutorials, is available free-of-charge under an open-source MIT license via GitHub at https://github.com/williamgilpin/pypdb, and the full API reference is at http://williamgilpin.github.io/pypdb_docs/html/. The latest stable release is also available on PyPI. wgilpin@stanford.edu. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.
Ciavaglia, Sherryn; Linacre, Adrian
2018-05-01
Reptile species, and in particular snakes, are protected by national and international agreements yet are commonly handled illegally. To aid in the enforcement of such legislation, we report on the development of three 11-plex assays from the genome of the carpet python to type 24 loci of tetra-nucleotide and penta-nucleotide repeat motifs (pure, compound and complex included). The loci range in size between 70 and 550 bp. Seventeen of the loci are newly characterised with the inclusion of seven previously developed loci to facilitate cross-comparison with previous carpet python genotyping studies. Assays were optimised in accordance with human forensic profiling kits using one nanogram template DNA. Three loci are included in all three of the multiplex reactions as quality assurance markers, to ensure sample identity and genotyping accuracy is maintained across the three profiling assays. Allelic ladders have been developed for the three assays to ensure consistent and precise allele designation. A DNA reference database of allele frequencies is presented based on 249 samples collected from throughout the species native range. A small number of validation tests are conducted to demonstrate the utility of these multiplex assays. We suggest further appropriate validation tests that should be conducted prior to the application of the multiplex assays in criminal investigations involving carpet pythons. Copyright © 2018 Elsevier B.V. All rights reserved.
pysimm: A Python Package for Simulation of Molecular Systems
NASA Astrophysics Data System (ADS)
Fortunato, Michael; Colina, Coray
pysimm, short for python simulation interface for molecular modeling, is a python package designed to facilitate the structure generation and simulation of molecular systems through convenient and programmatic access to object-oriented representations of molecular system data. This poster presents core features of pysimm and design philosophies that highlight a generalized methodology for incorporation of third-party software packages through API interfaces. The integration with the LAMMPS simulation package is explained to demonstrate this methodology. pysimm began as a back-end python library that powered a cloud-based application on nanohub.org for amorphous polymer simulation. The extension from a specific application library to general purpose simulation interface is explained. Additionally, this poster highlights the rapid development of new applications to construct polymer chains capable of controlling chain morphology such as molecular weight distribution and monomer composition.
pyPaSWAS: Python-based multi-core CPU and GPU sequence alignment.
Warris, Sven; Timal, N Roshan N; Kempenaar, Marcel; Poortinga, Arne M; van de Geest, Henri; Varbanescu, Ana L; Nap, Jan-Peter
2018-01-01
Our previously published CUDA-only application PaSWAS for Smith-Waterman (SW) sequence alignment of any type of sequence on NVIDIA-based GPUs is platform-specific and therefore adopted less than could be. The OpenCL language is supported more widely and allows use on a variety of hardware platforms. Moreover, there is a need to promote the adoption of parallel computing in bioinformatics by making its use and extension more simple through more and better application of high-level languages commonly used in bioinformatics, such as Python. The novel application pyPaSWAS presents the parallel SW sequence alignment code fully packed in Python. It is a generic SW implementation running on several hardware platforms with multi-core systems and/or GPUs that provides accurate sequence alignments that also can be inspected for alignment details. Additionally, pyPaSWAS support the affine gap penalty. Python libraries are used for automated system configuration, I/O and logging. This way, the Python environment will stimulate further extension and use of pyPaSWAS. pyPaSWAS presents an easy Python-based environment for accurate and retrievable parallel SW sequence alignments on GPUs and multi-core systems. The strategy of integrating Python with high-performance parallel compute languages to create a developer- and user-friendly environment should be considered for other computationally intensive bioinformatics algorithms.
James, Lauren E; Williams, Catherine Ja; Bertelsen, Mads F; Wang, Tobias
2018-05-01
To characterise the minimum dose of intramuscular alfaxalone required to facilitate intubation for mechanical ventilation, and to investigate the impact of cranial versus caudal injection on anaesthetic depth. Randomised crossover study. Six healthy juvenile ball pythons (Python regius). Three dosages (10, 20 and 30 mg kg -1 ) of alfaxalone were administered to each python in a caudal location with a minimum 2 weeks washout. Induction and recovery were monitored by assessing muscle tone, righting reflex, response to a noxious stimulus and the ability to intubate. A subsequent experiment assessed the influence of injection site by comparing administration of 20 mg kg -1 alfaxalone in a cranial location (1 cm cranial to the heart) with the caudal site. Respiration rate was monitored throughout, and when intubation was possible, snakes were mechanically ventilated. Regardless of dose and injection site, maximum effect was reached within 10.0 ± 2.7 minutes. When administered at the caudal injection site, intubation was only successful after a dosage of 30 mg kg- 1 , which is higher than in previous reports for other reptiles. However, intubation was possible in all cases after 7.2 ± 1.6 minutes upon cranial administration of 20 mg kg -1 , and anaesthetic duration was significantly lengthened (p < 0.001). Both 30 mg kg -1 at the caudal site and 20 mg kg -1 at the cranial site led to apnoea approximately 10 minutes post-injection, at which time the snakes were intubated and mechanically ventilated. Alfaxalone provided rapid, smooth induction when administered intramuscularly to pythons, and may serve as a useful induction agent prior to provision of volatile anaesthetics. The same dosage injected in the cranial site led to deeper anaesthesia than when injected caudally, suggesting that shunting to the liver and first-pass metabolism of alfaxalone occur when injected caudally, via the renal portal system. Copyright © 2018 Association of Veterinary Anaesthetists and
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
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.
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
A Python Script to Compute Isochrones for MODFLOW.
Feo, Alessandra; Zanini, Andrea; Petrella, Emma; Celico, Fulvio
2018-03-01
MODFLOW constitutes today the most popular modeling tool in the study of water flow in aquifers and in modeling aquifers. To simplify the interface to MODFLOW various GUI have been developed for the creation of model definition files and for the visualization and interpretation of results. Recently Bakker et al. (2016) developed the FloPy interface to MODFLOW that allows to import and use the produced simulation data using Python. This allows to construct model input files, run the models, read and plot simulations results through Python scripts. In this note, we present a Python program (that uses FloPy) interface that allows us to generate time-related capture zones (isochrones) for confined 2D steady-state groundwater flow in unbounded domains, with one or more wells. As an application, we show a validation of the approach and the results of four basic test cases: a homogenous aquifer with one well, a heterogeneous aquifer with one well, an aquifer with four wells located both longitudinal and perpendicular to the flow direction. © 2017, National Ground Water Association.
Python Scripts for Automation of Current-Voltage Testing of Semiconductor Devices (FY17)
2017-01-01
ARL-TR-7923 ● JAN 2017 US Army Research Laboratory Python Scripts for Automation of Current- Voltage Testing of Semiconductor...manual device-testing procedures is reduced or eliminated through automation. This technical report includes scripts written in Python , version 2.7, used ...nothing. 3.1.9 Exit Program The script exits the entire program. Line 505, sys.exit(), uses the sys package that comes with Python to exit system
CVXPY: A Python-Embedded Modeling Language for Convex Optimization.
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.
CVXPY: A Python-Embedded Modeling Language for Convex Optimization
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
Nidovirus-Associated Proliferative Pneumonia in the Green Tree Python (Morelia viridis).
Dervas, Eva; Hepojoki, Jussi; Laimbacher, Andrea; Romero-Palomo, Fernando; Jelinek, Christine; Keller, Saskia; Smura, Teemu; Hepojoki, Satu; Kipar, Anja; Hetzel, Udo
2017-08-09
In 2014 we observed a noticeable increase in sudden deaths of green tree pythons ( Morelia viridis ). Pathological examination revealed accumulation of mucoid material within airways and lung, associated with enlargement of the entire lung. We performed full necropsy and histological examination on 12 affected green tree pythons from 7 different breeders to characterise the pathogenesis of this "mucinous" pneumonia. By histology we could show a marked hyperplasia of the airway epithelium and of faveolar type II pneumocytes. Since routine microbiological tests failed to identify a causative agent, we studied lung samples of a few diseased snakes by next-generation sequencing (NGS). From the NGS data we could assemble a piece of RNA genome <85% identical to nidoviruses previously identified in ball pythons and Indian pythons. We then employed RT-PCR to demonstrate the presence of the novel nidovirus in all diseased snakes. To attempt virus isolation, we established primary cell cultures of Morelia viridis liver and brain, which we inoculated with lung homogenates of infected individuals. Ultrastructural examination of concentrated cell culture supernatants showed the presence of nidovirus particles, and subsequent NGS analysis yielded the full genome of the novel virus, Morelia viridis nidovirus (MVNV). We then generated an antibody against MVNV nucleoprotein, which we used alongside RNA in situ hybridisation to demonstrate viral antigen and RNA in the affected lungs. This suggests that in natural infection MVNV damages the respiratory tract epithelium which then results in epithelial hyperplasia, most likely as an exaggerated regenerative attempt in association with increased epithelial turnover. Importance Fairly recently novel nidoviruses associated with severe respiratory disease were identified in ball pythons and Indian pythons. Herein we report isolation and identification of a further nidovirus from green tree pythons ( Morelia viridis ) with fatal pneumonia
Bayesian Models for Astrophysical Data Using R, JAGS, Python, and Stan
NASA Astrophysics Data System (ADS)
Hilbe, Joseph M.; de Souza, Rafael S.; Ishida, Emille E. O.
2017-05-01
This comprehensive guide to Bayesian methods in astronomy enables hands-on work by supplying complete R, JAGS, Python, and Stan code, to use directly or to adapt. It begins by examining the normal model from both frequentist and Bayesian perspectives and then progresses to a full range of Bayesian generalized linear and mixed or hierarchical models, as well as additional types of models such as ABC and INLA. The book provides code that is largely unavailable elsewhere and includes details on interpreting and evaluating Bayesian models. Initial discussions offer models in synthetic form so that readers can easily adapt them to their own data; later the models are applied to real astronomical data. The consistent focus is on hands-on modeling, analysis of data, and interpretations that address scientific questions. A must-have for astronomers, its concrete approach will also be attractive to researchers in the sciences more generally.
Development of hemipenes in the ball python snake Python regius.
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.
pymzML--Python module for high-throughput bioinformatics on mass spectrometry data.
Bald, Till; Barth, Johannes; Niehues, Anna; Specht, Michael; Hippler, Michael; Fufezan, Christian
2012-04-01
pymzML is an extension to Python that offers (i) an easy access to mass spectrometry (MS) data that allows the rapid development of tools, (ii) a very fast parser for mzML data, the standard data format in MS and (iii) a set of functions to compare or handle spectra. pymzML requires Python2.6.5+ and is fully compatible with Python3. The module is freely available on http://pymzml.github.com or pypi, is published under LGPL license and requires no additional modules to be installed. christian@fufezan.net.
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.
Food consumption increases cell proliferation in the python brain.
Habroun, Stacy S; Schaffner, Andrew A; Taylor, Emily N; Strand, Christine R
2018-04-06
Pythons are model organisms for investigating physiological responses to food intake. While systemic growth in response to food consumption is well documented, what occurs in the brain is currently unexplored. In this study, male ball pythons ( Python regius ) were used to test the hypothesis that food consumption stimulates cell proliferation in the brain. We used 5-bromo-12'-deoxyuridine (BrdU) as a cell-birth marker to quantify and compare cell proliferation in the brain of fasted snakes and those at 2 and 6 days after a meal. Throughout the telencephalon, cell proliferation was significantly increased in the 6 day group, with no difference between the 2 day group and controls. Systemic postprandial plasticity occurs quickly after a meal is ingested, during the period of active digestion; however, the brain displays a surge of cell proliferation after most digestion and absorption is complete. © 2018. Published by The Company of Biologists Ltd.
Myiasis by Megaselia scalaris (Diptera: Phoridae) in a python affected by pulmonitis.
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.
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…
GenomeDiagram: a python package for the visualization of large-scale genomic data.
Pritchard, Leighton; White, Jennifer A; Birch, Paul R J; Toth, Ian K
2006-03-01
We present GenomeDiagram, a flexible, open-source Python module for the visualization of large-scale genomic, comparative genomic and other data with reference to a single chromosome or other biological sequence. GenomeDiagram may be used to generate publication-quality vector graphics, rastered images and in-line streamed graphics for webpages. The package integrates with datatypes from the BioPython project, and is available for Windows, Linux and Mac OS X systems. GenomeDiagram is freely available as source code (under GNU Public License) at http://bioinf.scri.ac.uk/lp/programs.html, and requires Python 2.3 or higher, and recent versions of the ReportLab and BioPython packages. A user manual, example code and images are available at http://bioinf.scri.ac.uk/lp/programs.html.
ConKit: a python interface to contact predictions.
Simkovic, Felix; Thomas, Jens M H; Rigden, Daniel J
2017-07-15
Recent advances in protein residue contact prediction algorithms have led to the emergence of many new methods and a variety of file formats. We present ConKit , an open source, modular and extensible Python interface which allows facile conversion between formats and provides an interface to analyses of sequence alignments and sets of contact predictions. ConKit is available via the Python Package Index. The documentation can be found at http://www.conkit.org . ConKit is licensed under the BSD 3-Clause. hlfsimko@liverpool.ac.uk or drigden@liverpool.ac.uk. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.
Nidovirus-Associated Proliferative Pneumonia in the Green Tree Python (Morelia viridis)
Dervas, Eva; Hepojoki, Jussi; Laimbacher, Andrea; Romero-Palomo, Fernando; Jelinek, Christine; Keller, Saskia; Smura, Teemu; Hetzel, Udo
2017-01-01
ABSTRACT In 2014 we observed a noticeable increase in the number of sudden deaths among green tree pythons (Morelia viridis). Pathological examination revealed the accumulation of mucoid material within the airways and lungs in association with enlargement of the entire lung. We performed a full necropsy and histological examination on 12 affected green tree pythons from 7 different breeders to characterize the pathogenesis of this mucinous pneumonia. By histology we could show a marked hyperplasia of the airway epithelium and of faveolar type II pneumocytes. Since routine microbiological tests failed to identify a causative agent, we studied lung tissue samples from a few diseased snakes by next-generation sequencing (NGS). From the NGS data we could assemble a piece of RNA genome whose sequence was <85% identical to that of nidoviruses previously identified in ball pythons and Indian pythons. We then employed reverse transcription-PCR to demonstrate the presence of the novel nidovirus in all diseased snakes. To attempt virus isolation, we established primary cultures of Morelia viridis liver and brain cells, which we inoculated with homogenates of lung tissue from infected individuals. Ultrastructural examination of concentrated cell culture supernatants showed the presence of nidovirus particles, and subsequent NGS analysis yielded the full genome of the novel virus Morelia viridis nidovirus (MVNV). We then generated an antibody against MVNV nucleoprotein, which we used alongside RNA in situ hybridization to demonstrate viral antigen and RNA in the affected lungs. This suggests that in natural infection MVNV damages the respiratory tract epithelium, which then results in epithelial hyperplasia, most likely as an exaggerated regenerative attempt in association with increased epithelial turnover. IMPORTANCE Novel nidoviruses associated with severe respiratory disease were fairly recently identified in ball pythons and Indian pythons. Herein we report on the
PyMC: Bayesian Stochastic Modelling in Python
Patil, Anand; Huard, David; Fonnesbeck, Christopher J.
2010-01-01
This user guide describes a Python package, PyMC, that allows users to efficiently code a probabilistic model and draw samples from its posterior distribution using Markov chain Monte Carlo techniques. PMID:21603108
PCSIM: A Parallel Simulation Environment for Neural Circuits Fully Integrated with Python
Pecevski, Dejan; Natschläger, Thomas; Schuch, Klaus
2008-01-01
The Parallel Circuit SIMulator (PCSIM) is a software package for simulation of neural circuits. It is primarily designed for distributed simulation of large scale networks of spiking point neurons. Although its computational core is written in C++, PCSIM's primary interface is implemented in the Python programming language, which is a powerful programming environment and allows the user to easily integrate the neural circuit simulator with data analysis and visualization tools to manage the full neural modeling life cycle. The main focus of this paper is to describe PCSIM's full integration into Python and the benefits thereof. In particular we will investigate how the automatically generated bidirectional interface and PCSIM's object-oriented modular framework enable the user to adopt a hybrid modeling approach: using and extending PCSIM's functionality either employing pure Python or C++ and thus combining the advantages of both worlds. Furthermore, we describe several supplementary PCSIM packages written in pure Python and tailored towards setting up and analyzing neural simulations. PMID:19543450
PyMercury: Interactive Python for the Mercury Monte Carlo Particle Transport Code
DOE Office of Scientific and Technical Information (OSTI.GOV)
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 improvesmore » 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.« less
Xarray: multi-dimensional data analysis in Python
NASA Astrophysics Data System (ADS)
Hoyer, Stephan; Hamman, Joe; Maussion, Fabien
2017-04-01
xarray (http://xarray.pydata.org) is an open source project and Python package that provides a toolkit and data structures for N-dimensional labeled arrays, which are the bread and butter of modern geoscientific data analysis. Key features of the package include label-based indexing and arithmetic, interoperability with the core scientific Python packages (e.g., pandas, NumPy, Matplotlib, Cartopy), out-of-core computation on datasets that don't fit into memory, a wide range of input/output options, and advanced multi-dimensional data manipulation tools such as group-by and resampling. In this contribution we will present the key features of the library and demonstrate its great potential for a wide range of applications, from (big-)data processing on super computers to data exploration in front of a classroom.
Stimfit: quantifying electrophysiological data with Python
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
Writing analytic element programs in Python.
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. Copyright © 2009 The Author(s). Journal Compilation © 2009 National Ground Water Association.
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.
Ujvari, Beata; Madsen, Thomas
2009-10-16
Telomere length (TL) has been found to be associated with life span in birds and humans. However, other studies have demonstrated that TL does not affect survival among old humans. Furthermore, replicative senescence has been shown to be induced by changes in the protected status of the telomeres rather than the loss of TL. In the present study we explore whether age- and sex-specific telomere dynamics affect life span in a long-lived snake, the water python (Liasis fuscus). Erythrocyte TL was measured using the Telo TAGGG TL Assay Kit (Roche). In contrast to other vertebrates, TL of hatchling pythons was significantly shorter than that of older snakes. However, during their first year of life hatchling TL increased substantially. While TL of older snakes decreased with age, we did not observe any correlation between TL and age in cross-sectional sampling. In older snakes, female TL was longer than that of males. When using recapture as a proxy for survival, our results do not support that longer telomeres resulted in an increased water python survival/longevity. In fish high telomerase activity has been observed in somatic cells exhibiting high proliferation rates. Hatchling pythons show similar high somatic cell proliferation rates. Thus, the increase in TL of this group may have been caused by increased telomerase activity. In older humans female TL is longer than that of males. This has been suggested to be caused by high estrogen levels that stimulate increased telomerase activity. Thus, high estrogen levels may also have caused the longer telomeres in female pythons. The lack of correlation between TL and age among old snakes and the fact that longer telomeres did not appear to affect python survival do not support that erythrocyte telomere dynamics has a major impact on water python longevity.
A high level interface to SCOP and ASTRAL implemented in python.
Casbon, James A; Crooks, Gavin E; Saqi, Mansoor A S
2006-01-10
Benchmarking algorithms in structural bioinformatics often involves the construction of datasets of proteins with given sequence and structural properties. The SCOP database is a manually curated structural classification which groups together proteins on the basis of structural similarity. The ASTRAL compendium provides non redundant subsets of SCOP domains on the basis of sequence similarity such that no two domains in a given subset share more than a defined degree of sequence similarity. Taken together these two resources provide a 'ground truth' for assessing structural bioinformatics algorithms. We present a small and easy to use API written in python to enable construction of datasets from these resources. We have designed a set of python modules to provide an abstraction of the SCOP and ASTRAL databases. The modules are designed to work as part of the Biopython distribution. Python users can now manipulate and use the SCOP hierarchy from within python programs, and use ASTRAL to return sequences of domains in SCOP, as well as clustered representations of SCOP from ASTRAL. The modules make the analysis and generation of datasets for use in structural genomics easier and more principled.
Comparison of cyclic correlation algorithm implemented in matlab and python
NASA Astrophysics Data System (ADS)
Carr, Richard; Whitney, James
Simulation is a necessary step for all engineering projects. Simulation gives the engineers an approximation of how their devices will perform under different circumstances, without hav-ing to build, or before building a physical prototype. This is especially true for space bound devices, i.e., space communication systems, where the impact of system malfunction or failure is several orders of magnitude over that of terrestrial applications. Therefore having a reliable simulation tool is key in developing these devices and systems. Math Works Matrix Laboratory (MATLAB) is a matrix based software used by scientists and engineers to solve problems and perform complex simulations. MATLAB has a number of applications in a wide variety of fields which include communications, signal processing, image processing, mathematics, eco-nomics and physics. Because of its many uses MATLAB has become the preferred software for many engineers; it is also very expensive, especially for students and startups. One alternative to MATLAB is Python. The Python is a powerful, easy to use, open source programming environment that can be used to perform many of the same functions as MATLAB. Python programming environment has been steadily gaining popularity in niche programming circles. While there are not as many function included in the software as MATLAB, there are many open source functions that have been developed that are available to be downloaded for free. This paper illustrates how Python can implement the cyclic correlation algorithm and com-pares the results to the cyclic correlation algorithm implemented in the MATLAB environment. Some of the characteristics to be compared are the accuracy and precision of the results, and the length of the programs. The paper will demonstrate that Python is capable of performing simulations of complex algorithms such cyclic correlation.
BioC implementations in Go, Perl, Python and Ruby
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
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
Sharma's Python Sign: A New Tubal Sign in Female Genital Tuberculosis.
Sharma, Jai Bhagwan
2016-01-01
Female genital tuberculosis (FGTB) is an important cause of infertility in developing countries. Various type of TB salpingitis can be endosalpingitis, exosalpingitis, interstitial TB salpingitis, and salpingitis isthmica nodosa. The fallopian tubes are thickened enlarged and tortuous. Unilateral or bilateral hydrosalpinx or pyosalpinx may be formed. A new sign python sign is presented in which fallopian tube looks like a blue python on dye testing in FGTB.
A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository.
Smelter, Andrey; Moseley, Hunter N B
2018-01-01
The Metabolomics Workbench Data Repository is a public repository of mass spectrometry and nuclear magnetic resonance data and metadata derived from a wide variety of metabolomics studies. The data and metadata for each study is deposited, stored, and accessed via files in the domain-specific 'mwTab' flat file format. In order to improve the accessibility, reusability, and interoperability of the data and metadata stored in 'mwTab' formatted files, we implemented a Python library and package. This Python package, named 'mwtab', is a parser for the domain-specific 'mwTab' flat file format, which provides facilities for reading, accessing, and writing 'mwTab' formatted files. Furthermore, the package provides facilities to validate both the format and required metadata elements of a given 'mwTab' formatted file. In order to develop the 'mwtab' package we used the official 'mwTab' format specification. We used Git version control along with Python unit-testing framework as well as continuous integration service to run those tests on multiple versions of Python. Package documentation was developed using sphinx documentation generator. The 'mwtab' package provides both Python programmatic library interfaces and command-line interfaces for reading, writing, and validating 'mwTab' formatted files. Data and associated metadata are stored within Python dictionary- and list-based data structures, enabling straightforward, 'pythonic' access and manipulation of data and metadata. Also, the package provides facilities to convert 'mwTab' files into a JSON formatted equivalent, enabling easy reusability of the data by all modern programming languages that implement JSON parsers. The 'mwtab' package implements its metadata validation functionality based on a pre-defined JSON schema that can be easily specialized for specific types of metabolomics studies. The library also provides a command-line interface for interconversion between 'mwTab' and JSONized formats in raw text and a
DREAMTools: a Python package for scoring collaborative challenges
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
Obtaining and processing Daymet data using Python and ArcGIS
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.
Fatal Purpureocillium lilacinum pneumonia in a green tree python.
Meyer, Jean; Loncaric, Igor; Richter, Barbara; Spergser, Joachim
2018-03-01
A 10-y-old female green tree python ( Morelia viridis) died of fungal pneumonia caused by Purpureocillium lilacinum, which was confirmed histologically and by PCR and subsequent DNA sequencing. The same fungal species was cultivated from a swab taken from the terrarium in which the snake was housed. Clinical and environmental P. lilacinum isolates were indistinguishable by the typing method applied, strongly suggesting clonal relatedness of both isolates. Because no other underlying predisposing respiratory infection could be detected by virus-specific PCR or histopathology, P. lilacinum was considered a primary pulmonary pathogen in this tree python.
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.
NASA Astrophysics Data System (ADS)
Mangantar Pardamean Sianturi, Markus; Jumilawaty, Erni; Delvian; Hartanto, Adrian
2018-03-01
Blood python (Python brongersmai Stull, 1938) is one of heavily exploited wildlife in Indonesia. The high demands on its skin trade have made its harvesting regulated under quota-based setting by the government to prevent over-harvesting. To gain understanding on the sustainability of P. brongersmai in the wild, biological characters of wild-caught specimens were studied. Samples were collected from two slaughterhouses from Rantau Prapat and Langkat. Parameters measured were morphological (Snout-vent length (SVL), body mass, abdomen width) and anatomical characters (Fat classes). Total samples of P. brongersmai in this research were 541 with 269 male and 272 female snakes. Female snakes had the highest proportion of individuals with the best quality of abdominal fat reserves (Class 3). Linear models are built and tested for its significance in relation between fat classes as anatomical characters and morphological characters. All tested morphological characters were significant in female snakes. By using linear equation models, we generate size limit to prioritize harvesting in the future. We suggest the use of SVL and stomach width ranging between 139,7 – 141,5 cm and 24,72 – 25,71 cm respectively to achieve sustainability of P. brongersmai in the wild.
Krysko, Kenneth L.; Gillett-Kaufman, Jennifer L.; Kawahara, Akito Y.; Connelly, C. Roxanne
2018-01-01
The Burmese python, Python bivittatus Kuhl, is a well-established invasive species in the greater Everglades ecosystem of southern Florida, USA. Most research on its ecological impacts focuses on its role as a predator and its trophic interactions with native vertebrate species, particularly mammals. Beyond predation, there is little known about the ecological interactions between P. bivittatus and native faunal communities. It is likely that established populations of P. bivittatus in southern Florida serve as hosts for native mosquito communities. To test this concept, we used mitochondrial cytochrome c oxidase subunit I DNA barcoding to determine the hosts of blood fed mosquitoes collected at a research facility in northern Florida where captive P. bivittatus and Argentine black and white tegu, Salvator merianae (Duméril and Bibron), are maintained in outdoor enclosures, accessible to local mosquitoes. We recovered python DNA from the blood meals of three species of Culex mosquitoes: Culex erraticus (Dyar and Knab), Culex quinquefasciatus Say, and Culex pilosus (Dyar and Knab). Culex erraticus conclusively (P = 0.001; Fisher’s Exact Test) took more blood meals from P. bivittatus than from any other available host. While the majority of mosquito blood meals in our sample were derived from P. bivittatus, only one was derived from S. merianae. These results demonstrate that local mosquitoes will feed on invasive P. bivittatus, a recently introduced host. If these interactions also occur in southern Florida, P. bivittatus may be involved in the transmission networks of mosquito-vectored pathogens. Our results also illustrate the potential of detecting the presence of P. bivittatus in the field through screening mosquito blood meals for their DNA. PMID:29342169
Reeves, Lawrence E; Krysko, Kenneth L; Avery, Michael L; Gillett-Kaufman, Jennifer L; Kawahara, Akito Y; Connelly, C Roxanne; Kaufman, Phillip E
2018-01-01
The Burmese python, Python bivittatus Kuhl, is a well-established invasive species in the greater Everglades ecosystem of southern Florida, USA. Most research on its ecological impacts focuses on its role as a predator and its trophic interactions with native vertebrate species, particularly mammals. Beyond predation, there is little known about the ecological interactions between P. bivittatus and native faunal communities. It is likely that established populations of P. bivittatus in southern Florida serve as hosts for native mosquito communities. To test this concept, we used mitochondrial cytochrome c oxidase subunit I DNA barcoding to determine the hosts of blood fed mosquitoes collected at a research facility in northern Florida where captive P. bivittatus and Argentine black and white tegu, Salvator merianae (Duméril and Bibron), are maintained in outdoor enclosures, accessible to local mosquitoes. We recovered python DNA from the blood meals of three species of Culex mosquitoes: Culex erraticus (Dyar and Knab), Culex quinquefasciatus Say, and Culex pilosus (Dyar and Knab). Culex erraticus conclusively (P = 0.001; Fisher's Exact Test) took more blood meals from P. bivittatus than from any other available host. While the majority of mosquito blood meals in our sample were derived from P. bivittatus, only one was derived from S. merianae. These results demonstrate that local mosquitoes will feed on invasive P. bivittatus, a recently introduced host. If these interactions also occur in southern Florida, P. bivittatus may be involved in the transmission networks of mosquito-vectored pathogens. Our results also illustrate the potential of detecting the presence of P. bivittatus in the field through screening mosquito blood meals for their DNA.
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
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
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
Sharma's Python Sign: A New Tubal Sign in Female Genital Tuberculosis
Sharma, Jai Bhagwan
2016-01-01
Female genital tuberculosis (FGTB) is an important cause of infertility in developing countries. Various type of TB salpingitis can be endosalpingitis, exosalpingitis, interstitial TB salpingitis, and salpingitis isthmica nodosa. The fallopian tubes are thickened enlarged and tortuous. Unilateral or bilateral hydrosalpinx or pyosalpinx may be formed. A new sign python sign is presented in which fallopian tube looks like a blue python on dye testing in FGTB. PMID:27365923
A Gene Ontology Tutorial in Python.
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 .
PESO - The Python Based Control System of the Ondrejov 2m Telescope
NASA Astrophysics Data System (ADS)
Skoda, P.; Fuchs, J.; Honsa, J.
2005-12-01
Python has been gaining a good reputation and respectability in many areas of software development. We have chosen Python after getting the new CCD detector for the coudé spectrograph of Ondřejov observatory 2m telescope. The VersArray detector from Roper Scientific came only with the closed source library PVCAM of low-level camera control functions for Linux, so we had to write the whole astronomical data acquisition system from scratch and integrate it with the current spectrograph and telescope control systems. The final result of our effort, PESO (Python Exposure System for Ondřejov) is a highly comfortable GUI-based environment allowing the observer to change the spectrograph configuration, choose the detector acquisition mode, select the exposure parameters, and monitor the exposure progress. All of the relevant information from the control computers is written into the FITS headers by the PyFITS module, and the acquired CCD frame is immediately displayed in an SAO DS9 window using XPA calls. The GTK-based front end design was drawn in the Glade visual development tool, giving the shape and position of all widgets in single XML file, which is used in Python by a simple call of the PyGlade module. We describe our experience with the design and implementation of PESO, stressing the easiness of quick changes of the GUI, together with the capability of separate testing of every module using the Python debugger, IPython.
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.
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. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.
SymPy: Symbolic computing in python
Meurer, Aaron; Smith, Christopher P.; Paprocki, Mateusz; ...
2017-01-02
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.
HyDe: a Python Package for Genome-Scale Hybridization Detection.
Blischak, Paul D; Chifman, Julia; Wolfe, Andrea D; Kubatko, Laura S
2018-03-19
The analysis of hybridization and gene flow among closely related taxa is a common goal for researchers studying speciation and phylogeography. Many methods for hybridization detection use simple site pattern frequencies from observed genomic data and compare them to null models that predict an absence of gene flow. The theory underlying the detection of hybridization using these site pattern probabilities exploits the relationship between the coalescent process for gene trees within population trees and the process of mutation along the branches of the gene trees. For certain models, site patterns are predicted to occur in equal frequency (i.e., their difference is 0), producing a set of functions called phylogenetic invariants. In this paper we introduce HyDe, a software package for detecting hybridization using phylogenetic invariants arising under the coalescent model with hybridization. HyDe is written in Python, and can be used interactively or through the command line using pre-packaged scripts. We demonstrate the use of HyDe on simulated data, as well as on two empirical data sets from the literature. We focus in particular on identifying individual hybrids within population samples and on distinguishing between hybrid speciation and gene flow. HyDe is freely available as an open source Python package under the GNU GPL v3 on both GitHub (https://github.com/pblischak/HyDe) and the Python Package Index (PyPI: https://pypi.python.org/pypi/phyde).
BioC implementations in Go, Perl, Python and Ruby.
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/ Published by Oxford University Press 2014. This work is written by US Government employees and is in the public domain in the US.
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.
Python-based geometry preparation and simulation visualization toolkits for STEPS
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. PMID:24782754
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.
Optics simulations: a Python workshop
NASA Astrophysics Data System (ADS)
Ghalila, H.; Ammar, A.; Varadharajan, S.; Majdi, Y.; Zghal, M.; Lahmar, S.; Lakshminarayanan, V.
2017-08-01
Numerical simulations allow teachers and students to indirectly perform sophisticated experiments that cannot be realizable otherwise due to cost and other constraints. During the past few decades there has been an explosion in the development of numerical tools concurrently with open source environments such as Python software. This availability of open source software offers an incredible opportunity for advancing teaching methodologies as well as in research. More specifically it is possible to correlate theoretical knowledge with experimental measurements using "virtual" experiments. We have been working on the development of numerical simulation tools using the Python program package and we have concentrated on geometric and physical optics simulations. The advantage of doing hands-on numerical experiments is that it allows the student learner to be an active participant in the pedagogical/learning process rather than playing a passive role as in the traditional lecture format. Even in laboratory classes because of constraints of space, lack of equipment and often-large numbers of students, many students play a passive role since they work in groups of 3 or more students. Furthermore these new tools help students get a handle on numerical methods as well simulations and impart a "feel" for the physics under investigation.
Python for Information Theoretic Analysis of Neural Data
Ince, Robin A. A.; Petersen, Rasmus S.; Swan, Daniel C.; Panzeri, Stefano
2008-01-01
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. PMID:19242557
A python tool for the implementation of domain-specific languages
NASA Astrophysics Data System (ADS)
Dejanović, Igor; Vaderna, Renata; Milosavljević, Gordana; Simić, Miloš; Vuković, Željko
2017-07-01
In this paper we describe textX, a meta-language and a tool for building Domain-Specific Languages. It is implemented in Python using Arpeggio PEG (Parsing Expression Grammar) parser library. From a single language description (grammar) textX will build a parser and a meta-model (a.k.a. abstract syntax) of the language. The parser is used to parse textual representations of models conforming to the meta-model. As a result of parsing, a Python object graph will be automatically created. The structure of the object graph will conform to the meta-model defined by the grammar. This approach frees a developer from the need to manually analyse a parse tree and transform it to other suitable representation. The textX library is independent of any integrated development environment and can be easily integrated in any Python project. The textX tool works as a grammar interpreter. The parser is configured at run-time using the grammar. The textX tool is a free and open-source project available at GitHub.
PyPathway: Python Package for Biological Network Analysis and Visualization.
Xu, Yang; Luo, Xiao-Chun
2018-05-01
Life science studies represent one of the biggest generators of large data sets, mainly because of rapid sequencing technological advances. Biological networks including interactive networks and human curated pathways are essential to understand these high-throughput data sets. Biological network analysis offers a method to explore systematically not only the molecular complexity of a particular disease but also the molecular relationships among apparently distinct phenotypes. Currently, several packages for Python community have been developed, such as BioPython and Goatools. However, tools to perform comprehensive network analysis and visualization are still needed. Here, we have developed PyPathway, an extensible free and open source Python package for functional enrichment analysis, network modeling, and network visualization. The network process module supports various interaction network and pathway databases such as Reactome, WikiPathway, STRING, and BioGRID. The network analysis module implements overrepresentation analysis, gene set enrichment analysis, network-based enrichment, and de novo network modeling. Finally, the visualization and data publishing modules enable users to share their analysis by using an easy web application. For package availability, see the first Reference.
cyvcf2: fast, flexible variant analysis with Python.
Pedersen, Brent S; Quinlan, Aaron R
2017-06-15
Variant call format (VCF) files document the genetic variation observed after DNA sequencing, alignment and variant calling of a sample cohort. Given the complexity of the VCF format as well as the diverse variant annotations and genotype metadata, there is a need for fast, flexible methods enabling intuitive analysis of the variant data within VCF and BCF files. We introduce cyvcf2 , a Python library and software package for fast parsing and querying of VCF and BCF files and illustrate its speed, simplicity and utility. bpederse@gmail.com or aaronquinlan@gmail.com. cyvcf2 is available from https://github.com/brentp/cyvcf2 under the MIT license and from common python package managers. Detailed documentation is available at http://brentp.github.io/cyvcf2/. © The Author 2017. Published by Oxford University Press.
SpacePy - a Python-based library of tools for the space sciences
DOE Office of Scientific and Technical Information (OSTI.GOV)
Morley, Steven K; Welling, Daniel T; Koller, Josef
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 tomore » 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 role of python eggshell permeability dynamics in a respiration-hydration trade-off.
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
Gala: A Python package for galactic dynamics
NASA Astrophysics Data System (ADS)
Price-Whelan, Adrian M.
2017-10-01
Gala is an Astropy-affiliated Python package for galactic dynamics. Python enables wrapping low-level languages (e.g., C) for speed without losing flexibility or ease-of-use in the user-interface. The API for Gala was designed to provide a class-based and user-friendly interface to fast (C or Cython-optimized) implementations of common operations such as gravitational potential and force evaluation, orbit integration, dynamical transformations, and chaos indicators for nonlinear dynamics. Gala also relies heavily on and interfaces well with the implementations of physical units and astronomical coordinate systems in the Astropy package (astropy.units and astropy.coordinates). Gala was designed to be used by both astronomical researchers and by students in courses on gravitational dynamics or astronomy. It has already been used in a number of scientific publications and has also been used in graduate courses on Galactic dynamics to, e.g., provide interactive visualizations of textbook material.
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.
Transcriptome analysis of the response of Burmese python to digestion
Sanggaard, Kristian Wejse; Schauser, Leif; Lauridsen, Sanne Enok; Enghild, Jan J.
2017-01-01
Abstract Exceptional and extreme feeding behaviour makes the Burmese python (Python bivittatus) an interesting model to study physiological remodelling and metabolic adaptation in response to refeeding after prolonged starvation. In this study, we used transcriptome sequencing of 5 visceral organs during fasting as well as 24 hours and 48 hours after ingestion of a large meal to unravel the postprandial changes in Burmese pythons. We first used the pooled data to perform a de novo assembly of the transcriptome and supplemented this with a proteomic survey of enzymes in the plasma and gastric fluid. We constructed a high-quality transcriptome with 34 423 transcripts, of which 19 713 (57%) were annotated. Among highly expressed genes (fragments per kilo base per million sequenced reads > 100 in 1 tissue), we found that the transition from fasting to digestion was associated with differential expression of 43 genes in the heart, 206 genes in the liver, 114 genes in the stomach, 89 genes in the pancreas, and 158 genes in the intestine. We interrogated the function of these genes to test previous hypotheses on the response to feeding. We also used the transcriptome to identify 314 secreted proteins in the gastric fluid of the python. Digestion was associated with an upregulation of genes related to metabolic processes, and translational changes therefore appear to support the postprandial rise in metabolism. We identify stomach-related proteins from a digesting individual and demonstrate that the sensitivity of modern liquid chromatography/tandem mass spectrometry equipment allows the identification of gastric juice proteins that are present during digestion. PMID:28873961
EMPIRE and pyenda: Two ensemble-based data assimilation systems written in Fortran and Python
NASA Astrophysics Data System (ADS)
Geppert, Gernot; Browne, Phil; van Leeuwen, Peter Jan; Merker, Claire
2017-04-01
We present and compare the features of two ensemble-based data assimilation frameworks, EMPIRE and pyenda. Both frameworks allow to couple models to the assimilation codes using the Message Passing Interface (MPI), leading to extremely efficient and fast coupling between models and the data-assimilation codes. The Fortran-based system EMPIRE (Employing Message Passing Interface for Researching Ensembles) is optimized for parallel, high-performance computing. It currently includes a suite of data assimilation algorithms including variants of the ensemble Kalman and several the particle filters. EMPIRE is targeted at models of all kinds of complexity and has been coupled to several geoscience models, eg. the Lorenz-63 model, a barotropic vorticity model, the general circulation model HadCM3, the ocean model NEMO, and the land-surface model JULES. The Python-based system pyenda (Python Ensemble Data Assimilation) allows Fortran- and Python-based models to be used for data assimilation. Models can be coupled either using MPI or by using a Python interface. Using Python allows quick prototyping and pyenda is aimed at small to medium scale models. pyenda currently includes variants of the ensemble Kalman filter and has been coupled to the Lorenz-63 model, an advection-based precipitation nowcasting scheme, and the dynamic global vegetation model JSBACH.
pyGeno: A Python package for precision medicine and proteogenomics.
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.
ModFossa: A library for modeling ion channels using Python.
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.
PyPanda: a Python package for gene regulatory network reconstruction
van IJzendoorn, David G.P.; Glass, Kimberly; Quackenbush, John; Kuijjer, Marieke L.
2016-01-01
Summary: PANDA (Passing Attributes between Networks for Data Assimilation) is a gene regulatory network inference method that uses message-passing to integrate multiple sources of ‘omics data. PANDA was originally coded in C ++. In this application note we describe PyPanda, the Python version of PANDA. PyPanda runs considerably faster than the C ++ version and includes additional features for network analysis. Availability and implementation: The open source PyPanda Python package is freely available at http://github.com/davidvi/pypanda. Contact: mkuijjer@jimmy.harvard.edu or d.g.p.van_ijzendoorn@lumc.nl PMID:27402905
PyPanda: a Python package for gene regulatory network reconstruction.
van IJzendoorn, David G P; Glass, Kimberly; Quackenbush, John; Kuijjer, Marieke L
2016-11-01
PANDA (Passing Attributes between Networks for Data Assimilation) is a gene regulatory network inference method that uses message-passing to integrate multiple sources of 'omics data. PANDA was originally coded in C ++. In this application note we describe PyPanda, the Python version of PANDA. PyPanda runs considerably faster than the C ++ version and includes additional features for network analysis. The open source PyPanda Python package is freely available at http://github.com/davidvi/pypanda CONTACT: mkuijjer@jimmy.harvard.edu or d.g.p.van_ijzendoorn@lumc.nl. © The Author 2016. Published by Oxford University Press.
pyGeno: A Python package for precision medicine and proteogenomics
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. PMID:27785359
HTSeq--a Python framework to work with high-throughput sequencing data.
Anders, Simon; Pyl, Paul Theodor; Huber, Wolfgang
2015-01-15
A large choice of tools exists for many standard tasks in the analysis of high-throughput sequencing (HTS) data. However, once a project deviates from standard workflows, custom scripts are needed. We present HTSeq, a Python library to facilitate the rapid development of such scripts. HTSeq offers parsers for many common data formats in HTS projects, as well as classes to represent data, such as genomic coordinates, sequences, sequencing reads, alignments, gene model information and variant calls, and provides data structures that allow for querying via genomic coordinates. We also present htseq-count, a tool developed with HTSeq that preprocesses RNA-Seq data for differential expression analysis by counting the overlap of reads with genes. HTSeq is released as an open-source software under the GNU General Public Licence and available from http://www-huber.embl.de/HTSeq or from the Python Package Index at https://pypi.python.org/pypi/HTSeq. © The Author 2014. Published by Oxford University Press.
ChemoPy: freely available python package for computational biology and chemoinformatics.
Cao, Dong-Sheng; Xu, Qing-Song; Hu, Qian-Nan; Liang, Yi-Zeng
2013-04-15
Molecular representation for small molecules has been routinely used in QSAR/SAR, virtual screening, database search, ranking, drug ADME/T prediction and other drug discovery processes. To facilitate extensive studies of drug molecules, we developed a freely available, open-source python package called chemoinformatics in python (ChemoPy) for calculating the commonly used structural and physicochemical features. It computes 16 drug feature groups composed of 19 descriptors that include 1135 descriptor values. In addition, it provides seven types of molecular fingerprint systems for drug molecules, including topological fingerprints, electro-topological state (E-state) fingerprints, MACCS keys, FP4 keys, atom pairs fingerprints, topological torsion fingerprints and Morgan/circular fingerprints. By applying a semi-empirical quantum chemistry program MOPAC, ChemoPy can also compute a large number of 3D molecular descriptors conveniently. The python package, ChemoPy, is freely available via http://code.google.com/p/pychem/downloads/list, and it runs on Linux and MS-Windows. Supplementary data are available at Bioinformatics online.
Naval Observatory Vector Astrometry Software (NOVAS) Version 3.1, Introducing a Python Edition
NASA Astrophysics Data System (ADS)
Barron, Eric G.; Kaplan, G. H.; Bangert, J.; Bartlett, J. L.; Puatua, W.; Harris, W.; Barrett, P.
2011-01-01
The Naval Observatory Vector Astrometry Software (NOVAS) is a source-code library that provides common astrometric quantities and transformations. NOVAS calculations are accurate at the sub-milliarcsecond level. The library can supply, in one or two subroutine or function calls, the instantaneous celestial position of any star or planet in a variety of coordinate systems. NOVAS also provides access to all of the building blocks that go into such computations. NOVAS Version 3.1 introduces a Python edition alongside the Fortran and C editions. The Python edition uses the computational code from the C edition and, currently, mimics the function calls of the C edition. Future versions will expand the functionality of the Python edition to harness the object-oriented nature of the Python language, and will implement the ability to handle large quantities of objects or observers using the array functionality in NumPy (a third-party scientific package for Python). NOVAS 3.1 also adds a module to transform GCRS vectors to the ITRS; the ITRS to GCRS transformation was already provided in NOVAS 3.0. The module that corrects an ITRS vector for polar motion has been modified to undo that correction upon demand. In the C edition, the ephemeris-access functions have been revised for use on 64-bit systems and for improved performance in general. NOVAS, including documentation, is available from the USNO website (http://www.usno.navy.mil/USNO/astronomical-applications/software-products/novas).
pyOpenMS: a Python-based interface to the OpenMS mass-spectrometry algorithm library.
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). © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
interPopula: a Python API to access the HapMap Project dataset
2010-01-01
Background The HapMap project is a publicly available catalogue of common genetic variants that occur in humans, currently including several million SNPs across 1115 individuals spanning 11 different populations. This important database does not provide any programmatic access to the dataset, furthermore no standard relational database interface is provided. Results interPopula is a Python API to access the HapMap dataset. interPopula provides integration facilities with both the Python ecology of software (e.g. Biopython and matplotlib) and other relevant human population datasets (e.g. Ensembl gene annotation and UCSC Known Genes). A set of guidelines and code examples to address possible inconsistencies across heterogeneous data sources is also provided. Conclusions interPopula is a straightforward and flexible Python API that facilitates the construction of scripts and applications that require access to the HapMap dataset. PMID:21210977
Parallel, Distributed Scripting with Python
DOE Office of Scientific and Technical Information (OSTI.GOV)
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 librarymore » 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.« less
The influence of mechanical ventilation on physiological parameters in ball pythons (Python regius).
Jakobsen, Sashia L; Williams, Catherine J A; Wang, Tobias; Bertelsen, Mads F
2017-05-01
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 PCO 2 . 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 PCO 2 normalised arterial pH in the face of metabolic acidosis. Copyright © 2017 Elsevier Inc. All rights reserved.
Python Turboprop Prepared for a Test in the Altitude Wind Tunnel
1949-08-21
A 3670-horsepower Armstrong-Siddeley Python turboprop being prepared for tests in the Altitude Wind Tunnel at the National Advisory Committee for Aeronautics (NACA) Lewis Flight Propulsion Laboratory. In 1947 Lewis researcher Walter Olsen led a group of representatives from the military, industry, and the NACA on a fact finding mission to investigate the technological progress of British turbojet manufacturers. Afterwards several British engines, including the Python, were brought to Cleveland for testing in Lewis’s altitude facilities. The Python was a 14-stage axial-flow compressor turboprop with a fixed-area nozzle and contra-rotating propellers. Early turboprops combined the turbojet and piston engine technologies. They could move large quantities of air so required less engine speed and thus less fuel. This was very appealing to the military for some applications. The military asked the NACA to compare the Python’s performance at sea to that at high altitudes. The NACA researchers studied the Python in the Altitude Wind Tunnel from July 1949 through January 1950. It was the first time the tunnel was used to study an engine with the sole purpose of learning about, not improving it. They analyzed the engine’s dynamic response using a frequency response method at altitudes between 10,000 to 30,000 feet. Lewis researchers found that they could predict the dynamic response characteristics at any altitude from the data obtained from any other specific altitude. This portion of the testing was completed during a single test run.
Transcriptome analysis of the response of Burmese python to digestion.
Duan, Jinjie; Sanggaard, Kristian Wejse; Schauser, Leif; Lauridsen, Sanne Enok; Enghild, Jan J; Schierup, Mikkel Heide; Wang, Tobias
2017-08-01
Exceptional and extreme feeding behaviour makes the Burmese python (Python bivittatus) an interesting model to study physiological remodelling and metabolic adaptation in response to refeeding after prolonged starvation. In this study, we used transcriptome sequencing of 5 visceral organs during fasting as well as 24 hours and 48 hours after ingestion of a large meal to unravel the postprandial changes in Burmese pythons. We first used the pooled data to perform a de novo assembly of the transcriptome and supplemented this with a proteomic survey of enzymes in the plasma and gastric fluid. We constructed a high-quality transcriptome with 34 423 transcripts, of which 19 713 (57%) were annotated. Among highly expressed genes (fragments per kilo base per million sequenced reads > 100 in 1 tissue), we found that the transition from fasting to digestion was associated with differential expression of 43 genes in the heart, 206 genes in the liver, 114 genes in the stomach, 89 genes in the pancreas, and 158 genes in the intestine. We interrogated the function of these genes to test previous hypotheses on the response to feeding. We also used the transcriptome to identify 314 secreted proteins in the gastric fluid of the python. Digestion was associated with an upregulation of genes related to metabolic processes, and translational changes therefore appear to support the postprandial rise in metabolism. We identify stomach-related proteins from a digesting individual and demonstrate that the sensitivity of modern liquid chromatography/tandem mass spectrometry equipment allows the identification of gastric juice proteins that are present during digestion. © The Authors 2017. Published by Oxford University Press.
A Pythonic Approach for Computational Geosciences and Geo-Data Processing
NASA Astrophysics Data System (ADS)
Morra, G.; Yuen, D. A.; Lee, S. M.
2016-12-01
Computational methods and data analysis play a constantly increasing role in Earth Sciences however students and professionals need to climb a steep learning curve before reaching a sufficient level that allows them to run effective models. Furthermore the recent arrival and new powerful machine learning tools such as Torch and Tensor Flow has opened new possibilities but also created a new realm of complications related to the completely different technology employed. We present here a series of examples entirely written in Python, a language that combines the simplicity of Matlab with the power and speed of compiled languages such as C, and apply them to a wide range of geological processes such as porous media flow, multiphase fluid-dynamics, creeping flow and many-faults interaction. We also explore ways in which machine learning can be employed in combination with numerical modelling. From immediately interpreting a large number of modeling results to optimizing a set of modeling parameters to obtain a desired optimal simulation. We show that by using Python undergraduate and graduate can learn advanced numerical technologies with a minimum dedicated effort, which in turn encourages them to develop more numerical tools and quickly progress in their computational abilities. We also show how Python allows combining modeling with machine learning as pieces of LEGO, therefore simplifying the transition towards a new kind of scientific geo-modelling. The conclusion is that Python is an ideal tool to create an infrastructure for geosciences that allows users to quickly develop tools, reuse techniques and encourage collaborative efforts to interpret and integrate geo-data in profound new ways.
Expyriment: a Python library for cognitive and neuroscientific experiments.
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.
Tanaka, Hiroki; Okuda, Katsuhiro; Ohtani, Seiji; Asari, Masaru; Horioka, Kie; Isozaki, Shotaro; Hayakawa, Akira; Ogawa, Katsuhiro; Hiroshi, Shiono; Shimizu, Keiko
2018-05-01
Electrical injury is damage caused by an electrical current passing through the body. We have previously reported that irregular stripes crossing skeletal muscle fibers (python pattern) and multiple small nuclei arranged in the longitudinal direction of the muscle fibers (chained nuclear change) are uniquely observed by histopathological analysis in the skeletal muscle tissues of patients with electrical injury. However, it remains unclear whether these phenomena are caused by the electrical current itself or by the joule heat generated by the electric current passing through the body. To clarify the causes underlying these changes, we applied electric and heat injury to the exteriorized rat soleus muscle in situ. Although both the python pattern and chained nuclear change were induced by electric injury, only the python pattern was induced by heat injury. Furthermore, a chained nuclear change was induced in the soleus muscle cells by electric current flow in physiological saline at 40 °C ex vivo, but a python pattern was not observed. When the skeletal muscle was exposed to electrical injury in cardiac-arrested rats, a python pattern was induced within 5 h after cardiac arrest, but no chained nuclear change was observed. Therefore, a chained nuclear change is induced by an electrical current alone in tissues in vital condition, whereas a python pattern is caused by joule heat, which may occur shortly after death. The degree and distribution of these skeletal muscle changes may be useful histological markers for analyzing cases of electrical injury in forensic medicine. Copyright © 2017 Elsevier B.V. All rights reserved.
Homing of invasive Burmese pythons in South Florida: evidence for map and compass senses in snakes
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
Homing of invasive Burmese pythons in South Florida: evidence for map and compass senses in snakes
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.
New Python-based methods for data processing
Sauter, Nicholas K.; Hattne, Johan; Grosse-Kunstleve, Ralf W.; Echols, Nathaniel
2013-01-01
Current pixel-array detectors produce diffraction images at extreme data rates (of up to 2 TB h−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. PMID:23793153
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.
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.
Teaching CS1 with Python GUI Game Programming
NASA Astrophysics Data System (ADS)
Wang, Hong
2010-06-01
Python is becoming a popular programming language in teaching freshman programming courses. The author designed a sequence of game programming labs using Pygame to further help engage students and to improve their programming skills. The class survey showed that the adoption of Pygame is successful.
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. PMID:24772079
Brian: a simulator for spiking neural networks in python.
Goodman, Dan; Brette, Romain
2008-01-01
"Brian" is a new simulator for spiking neural networks, written in Python (http://brian. di.ens.fr). It is an intuitive and highly flexible tool for rapidly developing new models, especially networks of single-compartment neurons. In addition to using standard types of neuron models, users can define models by writing arbitrary differential equations in ordinary mathematical notation. Python scientific libraries can also be used for defining models and analysing data. Vectorisation techniques allow efficient simulations despite the overheads of an interpreted language. Brian will be especially valuable for working on non-standard neuron models not easily covered by existing software, and as an alternative to using Matlab or C for simulations. With its easy and intuitive syntax, Brian is also very well suited for teaching computational neuroscience.
Hodshon, Rebecca T; Sura, Patricia A; Schumacher, Juergen P; Odoi, Agricola; Steeil, James C; Newkirk, Kim M
2013-03-01
To evaluate first-intention healing of CO(2) laser, 4.0-MHz radiowave radiosurgery (RWRS), and scalpel incisions in ball pythons (Python regius). 6 healthy adult ball pythons. A skin biopsy sample was collected, and 2-cm skin incisions (4/modality) were made in each snake under anesthesia and closed with surgical staples on day 0. Incision sites were grossly evaluated and scored daily. One skin biopsy sample per incision type per snake was obtained on days 2, 7, 14, and 30. Necrotic and fibroplastic tissue was measured in histologic sections; samples were assessed and scored for total inflammation, histologic response (based on the measurement of necrotic and fibroplastic tissues and total inflammation score), and other variables. Frequency distributions of gross and histologic variables associated with wound healing were calculated. Gross wound scores were significantly greater (indicating greater separation of wound edges) for laser incisions than for RWRS and scalpel incisions at all evaluated time points. Necrosis was significantly greater in laser and RWRS incisions than in scalpel incision sites on days 2 and 14 and days 2 and 7, respectively; fibroplasia was significantly greater in laser than in scalpel incision sites on day 30. Histologic response scores were significantly lower for scalpel than for other incision modalities on days 2, 14, and 30. In snakes, skin incisions made with a scalpel generally had less necrotic tissue than did CO(2) laser and RWRS incisions. Comparison of the 3 modalities on the basis of histologic response scores indicated that use of a scalpel was preferable, followed by RWRS and then laser.
Parallel selective pressures drive convergent diversification of phenotypes in pythons and boas.
Esquerré, Damien; Scott Keogh, J
2016-07-01
Pythons and boas are globally distributed and distantly related radiations with remarkable phenotypic and ecological diversity. We tested whether pythons, boas and their relatives have evolved convergent phenotypes when they display similar ecology. We collected geometric morphometric data on head shape for 1073 specimens representing over 80% of species. We show that these two groups display strong and widespread convergence when they occupy equivalent ecological niches and that the history of phenotypic evolution strongly matches the history of ecological diversification, suggesting that both processes are strongly coupled. These results are consistent with replicated adaptive radiation in both groups. We argue that strong selective pressures related to habitat-use have driven this convergence. Pythons and boas provide a new model system for the study of macro-evolutionary patterns of morphological and ecological evolution and they do so at a deeper level of divergence and global scale than any well-established adaptive radiation model systems. © 2016 John Wiley & Sons Ltd/CNRS.
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.
STEPS: Modeling and Simulating Complex Reaction-Diffusion Systems with Python
Wils, Stefan; Schutter, Erik De
2008-01-01
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. PMID:19623245
PyGOLD: a python based API for docking based virtual screening workflow generation.
Patel, Hitesh; Brinkjost, Tobias; Koch, Oliver
2017-08-15
Molecular docking is one of the successful approaches in structure based discovery and development of bioactive molecules in chemical biology and medicinal chemistry. Due to the huge amount of computational time that is still required, docking is often the last step in a virtual screening approach. Such screenings are set as workflows spanned over many steps, each aiming at different filtering task. These workflows can be automatized in large parts using python based toolkits except for docking using the docking software GOLD. However, within an automated virtual screening workflow it is not feasible to use the GUI in between every step to change the GOLD configuration file. Thus, a python module called PyGOLD was developed, to parse, edit and write the GOLD configuration file and to automate docking based virtual screening workflows. The latest version of PyGOLD, its documentation and example scripts are available at: http://www.ccb.tu-dortmund.de/koch or http://www.agkoch.de. PyGOLD is implemented in Python and can be imported as a standard python module without any further dependencies. oliver.koch@agkoch.de, oliver.koch@tu-dortmund.de. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com
Py4Syn: Python for synchrotrons.
Slepicka, H H; Canova, H F; Beniz, D B; Piton, J R
2015-09-01
In this report, Py4Syn, an open-source Python-based library for data acquisition, device manipulation, scan routines and other helper functions, is presented. Driven by easy-to-use and scalability ideals, Py4Syn offers control system agnostic solution and high customization level for scans and data output, covering distinct techniques and facilities. Here, most of the library functionalities are described, examples of use are shown and ideas for future implementations are presented.
CMCpy: Genetic Code-Message Coevolution Models in Python
Becich, Peter J.; Stark, Brian P.; Bhat, Harish S.; Ardell, David H.
2013-01-01
Code-message coevolution (CMC) models represent coevolution of a genetic code and a population of protein-coding genes (“messages”). Formally, CMC models are sets of quasispecies coupled together for fitness through a shared genetic code. Although CMC models display plausible explanations for the origin of multiple genetic code traits by natural selection, useful modern implementations of CMC models are not currently available. To meet this need we present CMCpy, an object-oriented Python API and command-line executable front-end that can reproduce all published results of CMC models. CMCpy implements multiple solvers for leading eigenpairs of quasispecies models. We also present novel analytical results that extend and generalize applications of perturbation theory to quasispecies models and pioneer the application of a homotopy method for quasispecies with non-unique maximally fit genotypes. Our results therefore facilitate the computational and analytical study of a variety of evolutionary systems. CMCpy is free open-source software available from http://pypi.python.org/pypi/CMCpy/. PMID:23532367
Novel divergent nidovirus in a python with pneumonia.
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. © 2014 The Authors.
ssbio: a Python framework for structural systems biology.
Mih, Nathan; Brunk, Elizabeth; Chen, Ke; Catoiu, Edward; Sastry, Anand; Kavvas, Erol; Monk, Jonathan M; Zhang, Zhen; Palsson, Bernhard O
2018-06-15
Working with protein structures at the genome-scale has been challenging in a variety of ways. Here, we present ssbio, a Python package that provides a framework to easily work with structural information in the context of genome-scale network reconstructions, which can contain thousands of individual proteins. The ssbio package provides an automated pipeline to construct high quality genome-scale models with protein structures (GEM-PROs), wrappers to popular third-party programs to compute associated protein properties, and methods to visualize and annotate structures directly in Jupyter notebooks, thus lowering the barrier of linking 3D structural data with established systems workflows. ssbio is implemented in Python and available to download under the MIT license at http://github.com/SBRG/ssbio. Documentation and Jupyter notebook tutorials are available at http://ssbio.readthedocs.io/en/latest/. Interactive notebooks can be launched using Binder at https://mybinder.org/v2/gh/SBRG/ssbio/master?filepath=Binder.ipynb. Supplementary data are available at Bioinformatics online.
Charming the Snake: Student Experiences with Python Programming as a Data Analysis Tool
NASA Astrophysics Data System (ADS)
Booker, Melissa; Ivers, C. B.; Piper, M.; Powers, L.; Ali, B.
2014-01-01
During the past year, twelve high school students and one undergraduate student participated in the NASA/IPAC Teacher Archive Research Program (NITARP) alongside three high school educators and one informal educator, gaining experience in using Python as a tool for analyzing the vast amount of photometry data available from the Herschel and Spitzer telescopes in the NGC 281 region. Use of Python appeared to produce two main positive gains: (1) a gain in student ability to successfully write and execute Python programs for the bulk analysis of data, and (2) a change in their perceptions of the utility of computer programming and of the students’ abilities to use programming to solve problems. We outline the trials, tribulations, successes, and failures of the teachers and students through this learning exercise and provide some recommendations for incorporating programming in scientific learning.
Sanchez-Migallon Guzman, David; Garcia, Valentina E.; Layton, Marylee L.; Hoon-Hanks, Laura L.; Boback, Scott M.; Keel, M. Kevin; Drazenovich, Tracy
2017-01-01
ABSTRACT Inclusion body disease (IBD) is an infectious disease originally described in captive snakes. It has traditionally been diagnosed by the presence of large eosinophilic cytoplasmic inclusions and is associated with neurological, gastrointestinal, and lymphoproliferative disorders. Previously, we identified and established a culture system for a novel lineage of arenaviruses isolated from boa constrictors diagnosed with IBD. Although ample circumstantial evidence suggested that these viruses, now known as reptarenaviruses, cause IBD, there has been no formal demonstration of disease causality since their discovery. We therefore conducted a long-term challenge experiment to test the hypothesis that reptarenaviruses cause IBD. We infected boa constrictors and ball pythons by cardiac injection of purified virus. We monitored the progression of viral growth in tissues, blood, and environmental samples. Infection produced dramatically different disease outcomes in snakes of the two species. Ball pythons infected with Golden Gate virus (GoGV) and with another reptarenavirus displayed severe neurological signs within 2 months, and viral replication was detected only in central nervous system tissues. In contrast, GoGV-infected boa constrictors remained free of clinical signs for 2 years, despite high viral loads and the accumulation of large intracellular inclusions in multiple tissues, including the brain. Inflammation was associated with infection in ball pythons but not in boa constrictors. Thus, reptarenavirus infection produces inclusions and inclusion body disease, although inclusions per se are neither necessarily associated with nor required for disease. Although the natural distribution of reptarenaviruses has yet to be described, the different outcomes of infection may reflect differences in geographical origin. IMPORTANCE New DNA sequencing technologies have made it easier than ever to identify the sequences of microorganisms in diseased tissues, i
MGtoolkit: A python package for implementing metagraphs
NASA Astrophysics Data System (ADS)
Ranathunga, D.; Nguyen, H.; Roughan, M.
In this paper we present MGtoolkit: an open-source Python package for implementing metagraphs - a first of its kind. Metagraphs are commonly used to specify and analyse business and computer-network policies alike. MGtoolkit can help verify such policies and promotes learning and experimentation with metagraphs. The package currently provides purely textual output for visualising metagraphs and their analysis results.
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.
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. ExoData is a Python package available freely on GitHub.
A Python-based interface to examine motions in time series of solar images
NASA Astrophysics Data System (ADS)
Campos-Rozo, J. I.; Vargas Domínguez, S.
2017-10-01
Python is considered to be a mature programming language, besides of being widely accepted as an engaging option for scientific analysis in multiple areas, as will be presented in this work for the particular case of solar physics research. SunPy is an open-source library based on Python that has been recently developed to furnish software tools to solar data analysis and visualization. In this work we present a graphical user interface (GUI) based on Python and Qt to effectively compute proper motions for the analysis of time series of solar data. This user-friendly computing interface, that is intended to be incorporated to the Sunpy library, uses a local correlation tracking technique and some extra tools that allows the selection of different parameters to calculate, vizualize and analyze vector velocity fields of solar data, i.e. time series of solar filtergrams and magnetograms.
Pyvolve: A Flexible Python Module for Simulating Sequences along Phylogenies.
Spielman, Stephanie J; Wilke, Claus O
2015-01-01
We introduce Pyvolve, a flexible Python module for simulating genetic data along a phylogeny using continuous-time Markov models of sequence evolution. Easily incorporated into Python bioinformatics pipelines, Pyvolve can simulate sequences according to most standard models of nucleotide, amino-acid, and codon sequence evolution. All model parameters are fully customizable. Users can additionally specify custom evolutionary models, with custom rate matrices and/or states to evolve. This flexibility makes Pyvolve a convenient framework not only for simulating sequences under a wide variety of conditions, but also for developing and testing new evolutionary models. Pyvolve is an open-source project under a FreeBSD license, and it is available for download, along with a detailed user-manual and example scripts, from http://github.com/sjspielman/pyvolve.
Data management routines for reproducible research using the G-Node Python Client library.
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.
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.
Tusler, Charlotte A; Maggs, David J; Kass, Philip H; Paul-Murphy, Joanne R; Schwab, Ivan R; Murphy, Christopher J
2015-01-01
To describe using spectral domain optical coherence tomography (SD-OCT), digital slit-lamp biomicroscopy, and external photography, changes in the ophidian cuticle, spectacle, and cornea during ecdysis. Four normal royal pythons (Python regius). Snakes were assessed once daily throughout a complete shed cycle using nasal, axial, and temporal SD-OCT images, digital slit-lamp biomicroscopy, and external photography. Spectral domain optical coherence tomography (SD-OCT) images reliably showed the spectacular cuticle and stroma, subcuticular space (SCS), cornea, anterior chamber, iris, and Schlemm's canal. When visible, the subspectacular space (SSS) was more distended peripherally than axially. Ocular surface changes throughout ecdysis were relatively conserved among snakes at all three regions imaged. From baseline (7 days following completion of a full cycle), the spectacle gradually thickened before separating into superficial cuticular and deep, hyper-reflective stromal components, thereby creating the SCS. During spectacular separation, the stroma regained original reflectivity, and multiple hyper-reflective foci (likely fragments from the cuticular-stromal interface) were noted within the SCS. The cornea was relatively unchanged in character or thickness throughout all stages of ecdysis. Slit-lamp images did not permit observation of these changes. Spectral domain optical coherence tomography (SD-OCT) provided excellent high-resolution images of the snake anterior segment, and especially the cuticle, spectacle, and cornea of manually restrained normal snakes at all stages of ecdysis and warrants investigation in snakes with anterior segment disease. The peripheral spectacle may be the preferred entry point for diagnostic or therapeutic injections into the SSS and for initiating spectacular surgery. © 2014 American College of Veterinary Ophthalmologists.
Ibmdbpy-spatial : An Open-source implementation of in-database geospatial analytics in Python
NASA Astrophysics Data System (ADS)
Roy, Avipsa; Fouché, Edouard; Rodriguez Morales, Rafael; Moehler, Gregor
2017-04-01
As the amount of spatial data acquired from several geodetic sources has grown over the years and as data infrastructure has become more powerful, the need for adoption of in-database analytic technology within geosciences has grown rapidly. In-database analytics on spatial data stored in a traditional enterprise data warehouse enables much faster retrieval and analysis for making better predictions about risks and opportunities, identifying trends and spot anomalies. Although there are a number of open-source spatial analysis libraries like geopandas and shapely available today, most of them have been restricted to manipulation and analysis of geometric objects with a dependency on GEOS and similar libraries. We present an open-source software package, written in Python, to fill the gap between spatial analysis and in-database analytics. Ibmdbpy-spatial provides a geospatial extension to the ibmdbpy package, implemented in 2015. It provides an interface for spatial data manipulation and access to in-database algorithms in IBM dashDB, a data warehouse platform with a spatial extender that runs as a service on IBM's cloud platform called Bluemix. Working in-database reduces the network overload, as the complete data need not be replicated into the user's local system altogether and only a subset of the entire dataset can be fetched into memory in a single instance. Ibmdbpy-spatial accelerates Python analytics by seamlessly pushing operations written in Python into the underlying database for execution using the dashDB spatial extender, thereby benefiting from in-database performance-enhancing features, such as columnar storage and parallel processing. The package is currently supported on Python versions from 2.7 up to 3.4. The basic architecture of the package consists of three main components - 1) a connection to the dashDB represented by the instance IdaDataBase, which uses a middleware API namely - pypyodbc or jaydebeapi to establish the database connection via
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.
Assessing risks to humans from invasive Burmese pythons in Everglades National Park, Florida, USA
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.
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.
Pteros 2.0: Evolution of the fast parallel molecular analysis library for C++ and python.
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/. © 2015 Wiley Periodicals, Inc.
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
Analyzing microtomography data with Python and the scikit-image library.
Gouillart, Emmanuelle; Nunez-Iglesias, Juan; van der Walt, Stéfan
2017-01-01
The exploration and processing of images is a vital aspect of the scientific workflows of many X-ray imaging modalities. Users require tools that combine interactivity, versatility, and performance. scikit-image is an open-source image processing toolkit for the Python language that supports a large variety of file formats and is compatible with 2D and 3D images. The toolkit exposes a simple programming interface, with thematic modules grouping functions according to their purpose, such as image restoration, segmentation, and measurements. scikit-image users benefit from a rich scientific Python ecosystem that contains many powerful libraries for tasks such as visualization or machine learning. scikit-image combines a gentle learning curve, versatile image processing capabilities, and the scalable performance required for the high-throughput analysis of X-ray imaging data.
A pipeline for comprehensive and automated processing of electron diffraction data in IPLT.
Schenk, Andreas D; Philippsen, Ansgar; Engel, Andreas; Walz, Thomas
2013-05-01
Electron crystallography of two-dimensional crystals allows the structural study of membrane proteins in their native environment, the lipid bilayer. Determining the structure of a membrane protein at near-atomic resolution by electron crystallography remains, however, a very labor-intense and time-consuming task. To simplify and accelerate the data processing aspect of electron crystallography, we implemented a pipeline for the processing of electron diffraction data using the Image Processing Library and Toolbox (IPLT), which provides a modular, flexible, integrated, and extendable cross-platform, open-source framework for image processing. The diffraction data processing pipeline is organized as several independent modules implemented in Python. The modules can be accessed either from a graphical user interface or through a command line interface, thus meeting the needs of both novice and expert users. The low-level image processing algorithms are implemented in C++ to achieve optimal processing performance, and their interface is exported to Python using a wrapper. For enhanced performance, the Python processing modules are complemented with a central data managing facility that provides a caching infrastructure. The validity of our data processing algorithms was verified by processing a set of aquaporin-0 diffraction patterns with the IPLT pipeline and comparing the resulting merged data set with that obtained by processing the same diffraction patterns with the classical set of MRC programs. Copyright © 2013 Elsevier Inc. All rights reserved.
A pipeline for comprehensive and automated processing of electron diffraction data in IPLT
Schenk, Andreas D.; Philippsen, Ansgar; Engel, Andreas; Walz, Thomas
2013-01-01
Electron crystallography of two-dimensional crystals allows the structural study of membrane proteins in their native environment, the lipid bilayer. Determining the structure of a membrane protein at near-atomic resolution by electron crystallography remains, however, a very labor-intense and time-consuming task. To simplify and accelerate the data processing aspect of electron crystallography, we implemented a pipeline for the processing of electron diffraction data using the Image Processing Library & Toolbox (IPLT), which provides a modular, flexible, integrated, and extendable cross-platform, open-source framework for image processing. The diffraction data processing pipeline is organized as several independent modules implemented in Python. The modules can be accessed either from a graphical user interface or through a command line interface, thus meeting the needs of both novice and expert users. The low-level image processing algorithms are implemented in C++ to achieve optimal processing performance, and their interface is exported to Python using a wrapper. For enhanced performance, the Python processing modules are complemented with a central data managing facility that provides a caching infrastructure. The validity of our data processing algorithms was verified by processing a set of aquaporin-0 diffraction patterns with the IPLT pipeline and comparing the resulting merged data set with that obtained by processing the same diffraction patterns with the classical set of MRC programs. PMID:23500887
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. © 2016 Wiley Periodicals, Inc.
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
Data management routines for reproducible research using the G-Node Python Client library
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
Williams, Catherine J A; James, Lauren E; Bertelsen, Mads F; Wang, Tobias
2016-07-01
To quantify the effect of subcutaneous (SC) capsaicin injection on heart rate (HR) in ball pythons (Python regius) and to assess the efficacy of two opioids (morphine and butorphanol) in modifying this response. Prospective, randomized, unmatched study. Eleven mixed-sex, captive-bred ball pythons. Snakes were randomly assigned to three groups (n = 6) by intramuscular premedication: 1) control: saline (0.9 mL); 2) morphine (10 mg kg(-1) ); and 3) butorphanol (10 mg kg(-1) ). Three snakes were tested twice and another two were tested three times in different treatments administered 1 month apart. Under isoflurane anaesthesia, snakes were instrumented with SC electrocardiogram (ECG) electrodes and an SC catheter for remote stimulus delivery. After recovery from anaesthesia, all snakes, in visual and audial isolation from the experimenter, received a sham stimulus of saline (0.4 mL) via the SC catheter. A nociceptive stimulus of SC capsaicin (3 mg in 0.2 mL saline with 7% Tween 80) was then applied by catheter at 7 hours after premedication. In a subset (n = 3), two sham injections (saline 0.2 mL) preceded the capsaicin treatment. HR was recorded via ECG, and changes in HR (ΔHR) from baseline were calculated for all stimulations. Capsaicin injection was associated with a significant increase in HR [peak ΔHR: saline group: 8.8 ± 7.1 beats minute(-1) ; capsaicin group: 21.1 ± 5.8 beats minute(-1) (p = 0.0055)] and integrated ΔHR as a function of time. The administration of morphine or butorphanol 7 hours prior to nociception failed to significantly reduce the peak and integrated ΔHR. Butorphanol caused marked, long-lasting sedation as assessed by muscle tone. The HR response to an SC capsaicin injection can serve as a nociceptive model in P. regius. Morphine and butorphanol administration did not reduce HR response to capsaicin stimulation but produced significantly different effects on pre-stimulation HR and sedation. © 2015 Association
IRISpy: Analyzing IRIS Data in Python
NASA Astrophysics Data System (ADS)
Ryan, Daniel; Christe, Steven; Mumford, Stuart; Baruah, Ankit; Timothy, Shelbe; Pereira, Tiago; De Pontieu, Bart
2017-08-01
IRISpy is a new community-developed open-source software library for analysing IRIS level 2 data. It is written in Python, a free, cross-platform, general-purpose, high-level programming language. A wide array of scientific computing software packages have already been developed in Python, from numerical computation (NumPy, SciPy, etc.), to visualization and plotting (matplotlib), to solar-physics-specific data analysis (SunPy). IRISpy is currently under development as a SunPy-affiliated package which means it depends on the SunPy library, follows similar standards and conventions, and is developed with the support of of the SunPy development team. IRISpy’s has two primary data objects, one for analyzing slit-jaw imager data and another for analyzing spectrograph data. Both objects contain basic slicing, indexing, plotting, and animating functionality to allow users to easily inspect, reduce and analyze the data. As part of this functionality the objects can output SunPy Maps, TimeSeries, Spectra, etc. of relevant data slices for easier inspection and analysis. Work is also ongoing to provide additional data analysis functionality including derivation of systematic measurement errors (e.g. readout noise), exposure time correction, residual wavelength calibration, radiometric calibration, and fine scale pointing corrections. IRISpy’s code base is publicly available through github.com and can be contributed to by anyone. In this poster we demonstrate IRISpy’s functionality and future goals of the project. We also encourage interested users to become involved in further developing IRISpy.
NEVESIM: event-driven neural simulation framework with a Python interface.
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.
NEVESIM: event-driven neural simulation framework with a Python interface
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
Osteosarcoma in a woma python (Aspidites ramsayi).
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. © 2011 The Authors. Australian Veterinary Journal © 2011 Australian Veterinary Association.
BioServices: a common Python package to access biological Web Services programmatically.
Cokelaer, Thomas; Pultz, Dennis; Harder, Lea M; Serra-Musach, Jordi; Saez-Rodriguez, Julio
2013-12-15
Web interfaces provide access to numerous biological databases. Many can be accessed to in a programmatic way thanks to Web Services. Building applications that combine several of them would benefit from a single framework. BioServices is a comprehensive Python framework that provides programmatic access to major bioinformatics Web Services (e.g. KEGG, UniProt, BioModels, ChEMBLdb). Wrapping additional Web Services based either on Representational State Transfer or Simple Object Access Protocol/Web Services Description Language technologies is eased by the usage of object-oriented programming. BioServices releases and documentation are available at http://pypi.python.org/pypi/bioservices under a GPL-v3 license.
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. © The Author 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Using Python on the Peregrine System | High-Performance Computing | NREL
was not designed for use in a shared computing environment. The following example creates a new Python is run. For example an environment.yml file can be created on the developer's laptop and used on the
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.
Hart, Reece K; Rico, Rudolph; Hare, Emily; Garcia, John; Westbrook, Jody; Fusaro, Vincent A
2015-01-15
Biological sequence variants are commonly represented in scientific literature, clinical reports and databases of variation using the mutation nomenclature guidelines endorsed by the Human Genome Variation Society (HGVS). Despite the widespread use of the standard, no freely available and comprehensive programming libraries are available. Here we report an open-source and easy-to-use Python library that facilitates the parsing, manipulation, formatting and validation of variants according to the HGVS specification. The current implementation focuses on the subset of the HGVS recommendations that precisely describe sequence-level variation relevant to the application of high-throughput sequencing to clinical diagnostics. The package is released under the Apache 2.0 open-source license. Source code, documentation and issue tracking are available at http://bitbucket.org/hgvs/hgvs/. Python packages are available at PyPI (https://pypi.python.org/pypi/hgvs). Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.
Hart, Reece K.; Rico, Rudolph; Hare, Emily; Garcia, John; Westbrook, Jody; Fusaro, Vincent A.
2015-01-01
Summary: Biological sequence variants are commonly represented in scientific literature, clinical reports and databases of variation using the mutation nomenclature guidelines endorsed by the Human Genome Variation Society (HGVS). Despite the widespread use of the standard, no freely available and comprehensive programming libraries are available. Here we report an open-source and easy-to-use Python library that facilitates the parsing, manipulation, formatting and validation of variants according to the HGVS specification. The current implementation focuses on the subset of the HGVS recommendations that precisely describe sequence-level variation relevant to the application of high-throughput sequencing to clinical diagnostics. Availability and implementation: The package is released under the Apache 2.0 open-source license. Source code, documentation and issue tracking are available at http://bitbucket.org/hgvs/hgvs/. Python packages are available at PyPI (https://pypi.python.org/pypi/hgvs). Contact: reecehart@gmail.com Supplementary information: Supplementary data are available at Bioinformatics online. PMID:25273102
The Burmese python genome reveals the molecular basis for extreme adaptation in snakes
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
The Burmese python genome reveals the molecular basis for extreme adaptation in snakes.
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.
Programming biological models in Python using PySB.
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.
Programming biological models in Python using PySB
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
Tongue worm (Pentastomida) infection in ball pythons (Python regius) – a case report
Gałęcki, Remigiusz; Sokół, Rajmund; Dudek, Agnieszka
Tongue worms (Pentastomida) are endoparasites causing pentastomiasis, an invasive disease representing a threat to exotic animals and humans. Animals acquire infection via the alimentary tract. In reptiles, the parasite is present in the lungs, resulting in symptoms from the respiratory system. Pentastomiasis may be asymptomatic, but nonspecific symptoms may occur at high parasite concentrations. Due to the harmful effects of many antiparasitic substances, tongue worm invasion in reptiles remains not fully treatable. Although pentasomiasis is rarely diagnosed in Poland, pentastomids were diagnosed in two ball pythons, who were patients of the “Poliklinika Weterynaryjna” veterinary clinic. They demonstrated problems with the respiratory system and a significant deterioration of health. Fenbendazole at a dose of 100 mg/kg b.w., repeated after 7 days was shown to be effective.
An Object-Oriented Python Implementation of an Intermediate-Level Atmospheric Model
NASA Astrophysics Data System (ADS)
Lin, J. W.
2008-12-01
The Neelin-Zeng Quasi-equilibrium Tropical Circulation Model (QTCM1) is a Fortran-based intermediate-level atmospheric model that includes simplified treatments of several physical processes, including a GCM-like convective scheme and a land-surface scheme with representations of different surface types, evaporation, and soil moisture. This model has been used in studies of the Madden-Julian oscillation, ENSO, and vegetation-atmosphere interaction effects on climate. Through the assumption of convective quasi-equilibrium in the troposphere, the QTCM1 is able to include full nonlinearity, resolve baroclinic disturbances, and generate a reasonable climatology, all at low computational cost. One year of simulation on a PC at 5.625 × 3.75 degree longitude-latitude resolution takes under three minutes of wall-clock time. The Python package qtcm implements the QTCM1 in a mixed-language environment that retains the speed of compiled Fortran while providing the benefits of Python's object-oriented framework and robust suite of utilities and datatypes. We describe key programming constructs used to create this modeling environment: the decomposition of model runs into Python objects, providing methods so visualization tools are attached to model runs, and the use of Python's mutable datatypes (lists and dictionaries) to implement the "run list" entity, which enables total runtime control of subroutine execution order and content. The result is an interactive modeling environment where the traditional sequence of "hypothesis → modeling → visualization and analysis" is opened up and made nonlinear and flexible. In this environment, science tasks such as parameter-space exploration and testing alternative parameterizations can be easily automated, without the need for multiple versions of the model code interacting with a bevy of makefiles and shell scripts. The environment also simplifies interfacing of the atmospheric model to other models (e.g., hydrologic models
Astronomical Simulations Using Visual Python
NASA Astrophysics Data System (ADS)
Cobb, Michael L.
2007-05-01
The Physics and Engineering Physics Department at Southeast Missouri State University has adopted the “Matter and Interactions I Modern Mechanics” text by Chabay and Sherwood for our calculus based introductory physics course. We have fully integrated the use of modeling and simulations by using the Visual Python language also know as VPython. This powerful, high level, object orientated language with full three dimensional, stereo graphics has stimulated both my students and myself to find wider applications for our new found skills. We have successfully modeled gravitational resonances in planetary rings, galaxy collisions, and planetary orbits around binary star systems. This talk will provide a quick overview of VPython and demonstrate the various simulations.
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.
Light-weight Parallel Python Tools for Earth System Modeling Workflows
NASA Astrophysics Data System (ADS)
Mickelson, S. A.; Paul, K.; Xu, H.; Dennis, J.; Brown, D. I.
2015-12-01
With the growth in computing power over the last 30 years, earth system modeling codes have become increasingly data-intensive. As an example, it is expected that the data required for the next Intergovernmental Panel on Climate Change (IPCC) Assessment Report (AR6) will increase by more than 10x to an expected 25PB per climate model. Faced with this daunting challenge, developers of the Community Earth System Model (CESM) have chosen to change the format of their data for long-term storage from time-slice to time-series, in order to reduce the required download bandwidth needed for later analysis and post-processing by climate scientists. Hence, efficient tools are required to (1) perform the transformation of the data from time-slice to time-series format and to (2) compute climatology statistics, needed for many diagnostic computations, on the resulting time-series data. To address the first of these two challenges, we have developed a parallel Python tool for converting time-slice model output to time-series format. To address the second of these challenges, we have developed a parallel Python tool to perform fast time-averaging of time-series data. These tools are designed to be light-weight, be easy to install, have very few dependencies, and can be easily inserted into the Earth system modeling workflow with negligible disruption. In this work, we present the motivation, approach, and testing results of these two light-weight parallel Python tools, as well as our plans for future research and development.
Python and HPC for High Energy Physics Data Analyses
Sehrish, S.; Kowalkowski, J.; Paterno, M.; ...
2017-01-01
High level abstractions in Python that can utilize computing hardware well seem to be an attractive option for writing data reduction and analysis tasks. In this paper, we explore the features available in Python which are useful and efficient for end user analysis in High Energy Physics (HEP). A typical vertical slice of an HEP data analysis is somewhat fragmented: the state of the reduction/analysis process must be saved at certain stages to allow for selective reprocessing of only parts of a generally time-consuming workflow. Also, algorithms tend to to be modular because of the heterogeneous nature of most detectorsmore » and the need to analyze different parts of the detector separately before combining the information. This fragmentation causes difficulties for interactive data analysis, and as data sets increase in size and complexity (O10 TiB for a “small” neutrino experiment to the O10 PiB currently held by the CMS experiment at the LHC), data analysis methods traditional to the field must evolve to make optimum use of emerging HPC technologies and platforms. Mainstream big data tools, while suggesting a direction in terms of what can be done if an entire data set can be available across a system and analysed with high-level programming abstractions, are not designed with either scientific computing generally, or modern HPC platform features in particular, such as data caching levels, in mind. Our example HPC use case is a search for a new elementary particle which might explain the phenomenon known as “Dark Matter”. Here, using data from the CMS detector, we will use HDF5 as our input data format, and MPI with Python to implement our use case.« less
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.
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. © 2015 Wiley Periodicals, Inc.
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.
scikit-image: image processing in Python.
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.
scikit-image: image processing in Python
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
pyro: Python-based tutorial for computational methods for hydrodynamics
NASA Astrophysics Data System (ADS)
Zingale, Michael
2015-07-01
pyro is a simple python-based tutorial on computational methods for hydrodynamics. It includes 2-d solvers for advection, compressible, incompressible, and low Mach number hydrodynamics, diffusion, and multigrid. It is written with ease of understanding in mind. An extensive set of notes that is part of the Open Astrophysics Bookshelf project provides details of the algorithms.
QmeQ 1.0: An open-source Python package for calculations of transport through quantum dot devices
NASA Astrophysics Data System (ADS)
Kiršanskas, Gediminas; Pedersen, Jonas Nyvold; Karlström, Olov; Leijnse, Martin; Wacker, Andreas
2017-12-01
QmeQ is an open-source Python package for numerical modeling of transport through quantum dot devices with strong electron-electron interactions using various approximate master equation approaches. The package provides a framework for calculating stationary particle or energy currents driven by differences in chemical potentials or temperatures between the leads which are tunnel coupled to the quantum dots. The electronic structures of the quantum dots are described by their single-particle states and the Coulomb matrix elements between the states. When transport is treated perturbatively to lowest order in the tunneling couplings, the possible approaches are Pauli (classical), first-order Redfield, and first-order von Neumann master equations, and a particular form of the Lindblad equation. When all processes involving two-particle excitations in the leads are of interest, the second-order von Neumann approach can be applied. All these approaches are implemented in QmeQ. We here give an overview of the basic structure of the package, give examples of transport calculations, and outline the range of applicability of the different approximate approaches.
Python Source Code Plagiarism Attacks on Introductory Programming Course Assignments
ERIC Educational Resources Information Center
Karnalim, Oscar
2017-01-01
This paper empirically enlists Python plagiarism attacks that have been found on Introductory Programming course assignments for undergraduate students. According to our observation toward 400 plagiarism-suspected cases, there are 35 plagiarism attacks that have been conducted by students. It starts with comment & whitespace modification as…
Luminal and systemic signals trigger intestinal adaptation in the juvenile python.
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.
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.
Smelter, Andrey; Astra, Morgan; Moseley, Hunter N B
2017-03-17
The Biological Magnetic Resonance Data Bank (BMRB) is a public repository of Nuclear Magnetic Resonance (NMR) spectroscopic data of biological macromolecules. It is an important resource for many researchers using NMR to study structural, biophysical, and biochemical properties of biological macromolecules. It is primarily maintained and accessed in a flat file ASCII format known as NMR-STAR. While the format is human readable, the size of most BMRB entries makes computer readability and explicit representation a practical requirement for almost any rigorous systematic analysis. To aid in the use of this public resource, we have developed a package called nmrstarlib in the popular open-source programming language Python. The nmrstarlib's implementation is very efficient, both in design and execution. The library has facilities for reading and writing both NMR-STAR version 2.1 and 3.1 formatted files, parsing them into usable Python dictionary- and list-based data structures, making access and manipulation of the experimental data very natural within Python programs (i.e. "saveframe" and "loop" records represented as individual Python dictionary data structures). Another major advantage of this design is that data stored in original NMR-STAR can be easily converted into its equivalent JavaScript Object Notation (JSON) format, a lightweight data interchange format, facilitating data access and manipulation using Python and any other programming language that implements a JSON parser/generator (i.e., all popular programming languages). We have also developed tools to visualize assigned chemical shift values and to convert between NMR-STAR and JSONized NMR-STAR formatted files. Full API Reference Documentation, User Guide and Tutorial with code examples are also available. We have tested this new library on all current BMRB entries: 100% of all entries are parsed without any errors for both NMR-STAR version 2.1 and version 3.1 formatted files. We also compared our
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.
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.
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.
ScrumPy: metabolic modelling with Python.
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.
Overgaard, Johannes; Andersen, Johnnie B; Wang, Tobias
2002-01-01
The oxygen uptake of Python molurus increases enormously following feeding, and the elevated metabolism coincides with rapid growth of the gastrointestinal organs. There are opposing views regarding the energetic costs of the gastrointestinal hypertrophy, and this study concerns the metabolic response to feeding after fasting periods of different duration. Since mass and function of the gastrointestinal organs remain elevated for several days after feeding, the metabolic increment following a second meal given soon after the first can reveal whether the metabolic costs relate to the upregulation of gastrointestinal organs or merely the metabolic cost of processing a meal. Eight juvenile pythons were kept on a regular feeding regime for 6 mo after hatching. At the beginning of the metabolic measurements, they were fed mice (20% of body mass), and the metabolic response to similarly sized meals was determined following 3, 5, 7, 14, 21, 30, and 60 d of fasting. Our data show that the metabolic response following feeding was large, ranging from 21% to 35% of ingested energy (mean=27%), but the metabolic response seems independent of fasting duration. Hence, the extraordinarily large cost of digestion in P. molurus does not appear to correlate with increased function and growth of gastrointestinal organs but must be associated with other physiological processes.
SPICE-Based Python Packages for ESA Solar System Exploration Mission's Geometry Exploitation
NASA Astrophysics Data System (ADS)
Costa, M.; Grass, M.
2018-04-01
This contribution outlines three Python packages to provide an enhanced and extended usage of SPICE Toolkit APIS providing higher-level functions and data quick-look capabilities focused on European Space Agency solar system exploration missions.
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
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.
pyhector: A Python interface for the simple climate model Hector
DOE Office of Scientific and Technical Information (OSTI.GOV)
N Willner, Sven; Hartin, Corinne; Gieseke, Robert
2017-04-01
Pyhector is a Python interface for the simple climate model Hector (Hartin et al. 2015) developed in C++. Simple climate models like Hector can, for instance, be used in the analysis of scenarios within integrated assessment models like GCAM1, in the emulation of complex climate models, and in uncertainty analyses. Hector is an open-source, object oriented, simple global climate carbon cycle model. Its carbon cycle consists of a one pool atmosphere, three terrestrial pools which can be broken down into finer biomes or regions, and four carbon pools in the ocean component. The terrestrial carbon cycle includes primary production andmore » respiration fluxes. The ocean carbon cycle circulates carbon via a simplified thermohaline circulation, calculating air-sea fluxes as well as the marine carbonate system (Hartin et al. 2016). The model input is time series of greenhouse gas emissions; as example scenarios for these the Pyhector package contains the Representative Concentration Pathways (RCPs)2. These were developed to cover the range of baseline and mitigation emissions scenarios and are widely used in climate change research and model intercomparison projects. Using DataFrames from the Python library Pandas (McKinney 2010) as a data structure for the scenarios simplifies generating and adapting scenarios. Other parameters of the Hector model can easily be modified when running the model. Pyhector can be installed using pip from the Python Package Index.3 Source code and issue tracker are available in Pyhector's GitHub repository4. Documentation is provided through Readthedocs5. Usage examples are also contained in the repository as a Jupyter Notebook (Pérez and Granger 2007; Kluyver et al. 2016). Courtesy of the Mybinder project6, the example Notebook can also be executed and modified without installing Pyhector locally.« less
Reed, Robert N
2005-06-01
The growing international trade in live wildlife has the potential to result in continuing establishment of nonnative animal populations in the United States. Snakes may pose particularly high risks as potentially invasive species, as exemplified by the decimation of Guam's vertebrate fauna by the accidentally introduced brown tree snake. Herein, ecological and commercial predictors of the likelihood of establishment of invasive populations were used to model risk associated with legal commercial imports of 23 species of boas, pythons, and relatives into the United States during the period 1989-2000. Data on ecological variables were collected from multiple sources, while data on commercial variables were collated from import records maintained by the U.S. Fish and Wildlife Service. Results of the risk-assessment models indicate that species including boa constrictors (Boa constrictor), ball pythons (Python regius), and reticulated pythons (P. reticulatus) may pose particularly high risks as potentially invasive species. Recommendations for reducing risk of establishment of invasive populations of snakes and/or pathogens include temporary quarantine of imports to increase detection rates of nonnative pathogens, increasing research attention to reptile pathogens, reducing the risk that nonnative snakes will reach certain areas with high numbers of federally listed species (such as the Florida Keys), and attempting to better educate individuals purchasing reptiles.
Scoria: a Python module for manipulating 3D molecular data.
Ropp, Patrick; Friedman, Aaron; Durrant, Jacob D
2017-09-18
Third-party packages have transformed the Python programming language into a powerful computational-biology tool. Package installation is easy for experienced users, but novices sometimes struggle with dependencies and compilers. This presents a barrier that can hinder the otherwise broad adoption of new tools. We present Scoria, a Python package for manipulating three-dimensional molecular data. Unlike similar packages, Scoria requires no dependencies, compilation, or system-wide installation. One can incorporate the Scoria source code directly into their own programs. But Scoria is not designed to compete with other similar packages. Rather, it complements them. Our package leverages others (e.g. NumPy, SciPy), if present, to speed and extend its own functionality. To show its utility, we use Scoria to analyze a molecular dynamics trajectory. Our FootPrint script colors the atoms of one chain by the frequency of their contacts with a second chain. We are hopeful that Scoria will be a useful tool for the computational-biology community. A copy is available for download free of charge (Apache License 2.0) at http://durrantlab.com/scoria/ . Graphical abstract .
COBRApy: COnstraints-Based Reconstruction and Analysis for Python.
Ebrahim, Ali; Lerman, Joshua A; Palsson, Bernhard O; Hyduke, Daniel R
2013-08-08
COnstraint-Based Reconstruction and Analysis (COBRA) methods are widely used for genome-scale modeling of metabolic networks in both prokaryotes and eukaryotes. Due to the successes with metabolism, there is an increasing effort to apply COBRA methods to reconstruct and analyze integrated models of cellular processes. The COBRA Toolbox for MATLAB is a leading software package for genome-scale analysis of metabolism; however, it was not designed to elegantly capture the complexity inherent in integrated biological networks and lacks an integration framework for the multiomics data used in systems biology. The openCOBRA Project is a community effort to promote constraints-based research through the distribution of freely available software. Here, we describe COBRA for Python (COBRApy), a Python package that provides support for basic COBRA methods. COBRApy is designed in an object-oriented fashion that facilitates the representation of the complex biological processes of metabolism and gene expression. COBRApy does not require MATLAB to function; however, it includes an interface to the COBRA Toolbox for MATLAB to facilitate use of legacy codes. For improved performance, COBRApy includes parallel processing support for computationally intensive processes. COBRApy is an object-oriented framework designed to meet the computational challenges associated with the next generation of stoichiometric constraint-based models and high-density omics data sets. http://opencobra.sourceforge.net/
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
Irizarry, Kristopher J L; Bryden, Randall L
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.
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.
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
Automatic Parallelization of Numerical Python Applications using the Global Arrays Toolkit
DOE Office of Scientific and Technical Information (OSTI.GOV)
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 calledmore » 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.« less
Eddylicious: A Python package for turbulent inflow generation
NASA Astrophysics Data System (ADS)
Mukha, Timofey; Liefvendahl, Mattias
2018-01-01
A Python package for generating inflow for scale-resolving computer simulations of turbulent flow is presented. The purpose of the package is to unite existing inflow generation methods in a single code-base and make them accessible to users of various Computational Fluid Dynamics (CFD) solvers. The currently existing functionality consists of an accurate inflow generation method suitable for flows with a turbulent boundary layer inflow and input/output routines for coupling with the open-source CFD solver OpenFOAM.
SWMM5 Application Programming Interface and PySWMM: A Python Interfacing Wrapper
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). ...
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. Copyright © 2013 Elsevier Inc
Naval Observatory Vector Astrometry Software (NOVAS) Version 3.1:Fortran, C, and Python Editions
NASA Astrophysics Data System (ADS)
Kaplan, G. H.; Bangert, J. A.; Barron, E. G.; Bartlett, J. L.; Puatua, W.; Harris, W.; Barrett, P.
2012-08-01
The Naval Observatory Vector Astrometry Software (NOVAS) is a source - code library that provides common astrometric quantities and transformations to high precision. The library can supply, in one or two subroutine or function calls, the instantaneous celestial position of any star or planet in a variety of coordinate systems. NOVAS also provides access to all of the building blocks that go into such computations. NOVAS is used for a wide variety of applications, including the U.S. portions of The Astronomical Almanac and a number of telescope control systems. NOVAS uses IAU recommended models for Earth orientation, including the IAU 2006 precession theory, the IAU 2000A and 2000B nutation series, and diurnal rotation based on the celestial and terrestrial intermediate origins. Equinox - based quantities, such as sidereal time, are also supported. NOVAS Earth orientation calculations match those from SOFA at the sub - microarcsecond level for comparable transformations. NOVAS algorithms for aberration an d gravitational light deflection are equivalent, at the microarcsecond level, to those inherent in the current consensus VLBI delay algorithm. NOVAS can be easily connected to the JPL planetary/lunar ephemerides (e.g., DE405), and connections to IMCCE and IAA planetary ephemerides are planned. NOVAS Version 3.1 introduces a Python edition alongside the Fortran and C editions. The Python edition uses the computational code from the C edition and currently mimics the function calls of the C edition. Future versions will expand the functionality of the Python edition to exploit the object - oriented features of Python. In the Version 3.1 C edition, the ephemeris - access functions have been revised for use on 64 - bit systems and for improved performance in general. NOVAS source code, auxiliary files, and documentation are available from the USNO website (http://aa.usno.navy.mil/software/novas/novas_info.php).
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.
A Python Analytical Pipeline to Identify Prohormone Precursors and Predict Prohormone Cleavage Sites
Southey, Bruce R.; Sweedler, Jonathan V.; Rodriguez-Zas, Sandra L.
2008-01-01
Neuropeptides and hormones are signaling molecules that support cell–cell communication in the central nervous system. Experimentally characterizing neuropeptides requires significant efforts because of the complex and variable processing of prohormone precursor proteins into neuropeptides and hormones. We demonstrate the power and flexibility of the Python language to develop components of an bioinformatic analytical pipeline to identify precursors from genomic data and to predict cleavage as these precursors are en route to the final bioactive peptides. We identified 75 precursors in the rhesus genome, predicted cleavage sites using support vector machines and compared the rhesus predictions to putative assignments based on homology to human sequences. The correct classification rate of cleavage using the support vector machines was over 97% for both human and rhesus data sets. The functionality of Python has been important to develop and maintain NeuroPred (http://neuroproteomics.scs.uiuc.edu/neuropred.html), a user-centered web application for the neuroscience community that provides cleavage site prediction from a wide range of models, precision and accuracy statistics, post-translational modifications, and the molecular mass of potential peptides. The combined results illustrate the suitability of the Python language to implement an all-inclusive bioinformatics approach to predict neuropeptides that encompasses a large number of interdependent steps, from scanning genomes for precursor genes to identification of potential bioactive neuropeptides. PMID:19169350
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).
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
The fast azimuthal integration Python library: pyFAI.
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.
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.
Pediatric ocular injury secondary to a Burmese python bite.
Behrens, Alice W; Jones, Maria H; Lowery, R Scott
2018-03-22
We report the case of a 6-year-old girl with a penetrating ocular injury caused by a Burmese python. She received intravenous cefazolin before presenting and was treated thereafter with daily topical antibiotics and atropine. Six weeks after injury, she underwent cataract extraction and sulcus implantation of an intraocular lens and iris synechiolysis, with postoperative patching. Final visual outcome was excellent despite no globe repair was performed. Published by Elsevier Inc.
Planetary Geologic Mapping Python Toolbox: A Suite of Tools to Support Mapping Workflows
NASA Astrophysics Data System (ADS)
Hunter, M. A.; Skinner, J. A.; Hare, T. M.; Fortezzo, C. M.
2017-06-01
The collective focus of the Planetary Geologic Mapping Python Toolbox is to provide researchers with additional means to migrate legacy GIS data, assess the quality of data and analysis results, and simplify common mapping tasks.
π Scope: python based scientific workbench with visualization tool for MDSplus data
NASA Astrophysics Data System (ADS)
Shiraiwa, S.
2014-10-01
π Scope is a python based scientific data analysis and visualization tool constructed on wxPython and Matplotlib. Although it is designed to be a generic tool, the primary motivation for developing the new software is 1) to provide an updated tool to browse MDSplus data, with functionalities beyond dwscope and jScope, and 2) to provide a universal foundation to construct interface tools to perform computer simulation and modeling for Alcator C-Mod. It provides many features to visualize MDSplus data during tokamak experiments including overplotting different signals and discharges, various plot types (line, contour, image, etc.), in-panel data analysis using python scripts, and publication quality graphics generation. Additionally, the logic to produce multi-panel plots is designed to be backward compatible with dwscope, enabling smooth migration for dwscope users. πScope uses multi-threading to reduce data transfer latency, and its object-oriented design makes it easy to modify and expand while the open source nature allows portability. A built-in tree data browser allows a user to approach the data structure both from a GUI and a script, enabling relatively complex data analysis workflow to be built quickly. As an example, an IDL-based interface to perform GENRAY/CQL3D simulations was ported on πScope, thus allowing LHCD simulation to be run between-shot using C-Mod experimental profiles. This workflow is being used to generate a large database to develop a LHCD actuator model for the plasma control system. Supported by USDoE Award DE-FC02-99ER54512.
PYTHON for Variable Star Astronomy (Abstract)
NASA Astrophysics Data System (ADS)
Craig, M.
2018-06-01
(Abstract only) Open source PYTHON packages that are useful for data reduction, photometry, and other tasks relevant to variable star astronomy have been developed over the last three to four years as part of the Astropy project. Using this software, it is relatively straightforward to reduce images, automatically detect sources, and match them to catalogs. Over the last year browser-based tools for performing some of those tasks have been developed that minimize or eliminate the need to write any of your own code. After providing an overview of the current state of the software, an application that calculates transformation coefficients on a frame-by-frame basis by matching stars in an image to the APASS catalog will be described.
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
An object oriented Python interface for atomistic simulations
NASA Astrophysics Data System (ADS)
Hynninen, T.; Himanen, L.; Parkkinen, V.; Musso, T.; Corander, J.; Foster, A. S.
2016-01-01
Programmable simulation environments allow one to monitor and control calculations efficiently and automatically before, during, and after runtime. Environments directly accessible in a programming environment can be interfaced with powerful external analysis tools and extensions to enhance the functionality of the core program, and by incorporating a flexible object based structure, the environments make building and analysing computational setups intuitive. In this work, we present a classical atomistic force field with an interface written in Python language. The program is an extension for an existing object based atomistic simulation environment.
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.
Landlab: an Open-Source Python Library for Modeling Earth Surface Dynamics
NASA Astrophysics Data System (ADS)
Gasparini, N. M.; Adams, J. M.; Hobley, D. E. J.; Hutton, E.; Nudurupati, S. S.; Istanbulluoglu, E.; Tucker, G. E.
2016-12-01
Landlab is an open-source Python modeling library that enables users to easily build unique models to explore earth surface dynamics. The Landlab library provides a number of tools and functionalities that are common to many earth surface models, thus eliminating the need for a user to recode fundamental model elements each time she explores a new problem. For example, Landlab provides a gridding engine so that a user can build a uniform or nonuniform grid in one line of code. The library has tools for setting boundary conditions, adding data to a grid, and performing basic operations on the data, such as calculating gradients and curvature. The library also includes a number of process components, which are numerical implementations of physical processes. To create a model, a user creates a grid and couples together process components that act on grid variables. The current library has components for modeling a diverse range of processes, from overland flow generation to bedrock river incision, from soil wetting and drying to vegetation growth, succession and death. The code is freely available for download (https://github.com/landlab/landlab) or can be installed as a Python package. Landlab models can also be built and run on Hydroshare (www.hydroshare.org), an online collaborative environment for sharing hydrologic data, models, and code. Tutorials illustrating a wide range of Landlab capabilities such as building a grid, setting boundary conditions, reading in data, plotting, using components and building models are also available (https://github.com/landlab/tutorials). The code is also comprehensively documented both online and natively in Python. In this presentation, we illustrate the diverse capabilities of Landlab. We highlight existing functionality by illustrating outcomes from a range of models built with Landlab - including applications that explore landscape evolution and ecohydrology. Finally, we describe the range of resources available for new
Sarment: Python modules for HMM analysis and partitioning of sequences.
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.
Java vs. Python Coverage of Introductory Programming Concepts: A Textbook Analysis
ERIC Educational Resources Information Center
McMaster, Kirby; Sambasivam, Samuel; Rague, Brian; Wolthuis, Stuart
2017-01-01
In this research, we compare two languages, Java and Python, by performing a content analysis of words in textbooks that describe important programming concepts. Our goal is to determine which language has better textbook support for teaching introductory programming courses. We used the TextSTAT program to count how often our list of concept…
RdTools: An Open Source Python Library for PV Degradation Analysis
DOE Office of Scientific and Technical Information (OSTI.GOV)
Deceglie, Michael G; Jordan, Dirk; Nag, Ambarish
RdTools is a set of Python tools for analysis of photovoltaic data. In particular, PV production data is evaluated over several years to obtain rates of performance degradation over time. Rdtools can handle both high frequency (hourly or better) or low frequency (daily, weekly, etc.) datasets. Best results are obtained with higher frequency data.
PlasmaPy: initial development of a Python package for plasma physics
NASA Astrophysics Data System (ADS)
Murphy, Nicholas; Leonard, Andrew J.; Stańczak, Dominik; Haggerty, Colby C.; Parashar, Tulasi N.; Huang, Yu-Min; PlasmaPy Community
2017-10-01
We report on initial development of PlasmaPy: an open source community-driven Python package for plasma physics. PlasmaPy seeks to provide core functionality that is needed for the formation of a fully open source Python ecosystem for plasma physics. PlasmaPy prioritizes code readability, consistency, and maintainability while using best practices for scientific computing such as version control, continuous integration testing, embedding documentation in code, and code review. We discuss our current and planned capabilities, including features presently under development. The development roadmap includes features such as fluid and particle simulation capabilities, a Grad-Shafranov solver, a dispersion relation solver, atomic data retrieval methods, and tools to analyze simulations and experiments. We describe several ways to contribute to PlasmaPy. PlasmaPy has a code of conduct and is being developed under a BSD license, with a version 0.1 release planned for 2018. The success of PlasmaPy depends on active community involvement, so anyone interested in contributing to this project should contact the authors. This work was partially supported by the U.S. Department of Energy.
ObspyDMT: a Python toolbox for retrieving and processing large seismological data sets
NASA Astrophysics Data System (ADS)
Hosseini, Kasra; Sigloch, Karin
2017-10-01
We present obspyDMT, a free, open-source software toolbox for the query, retrieval, processing and management of seismological data sets, including very large, heterogeneous and/or dynamically growing ones. ObspyDMT simplifies and speeds up user interaction with data centers, in more versatile ways than existing tools. The user is shielded from the complexities of interacting with different data centers and data exchange protocols and is provided with powerful diagnostic and plotting tools to check the retrieved data and metadata. While primarily a productivity tool for research seismologists and observatories, easy-to-use syntax and plotting functionality also make obspyDMT an effective teaching aid. Written in the Python programming language, it can be used as a stand-alone command-line tool (requiring no knowledge of Python) or can be integrated as a module with other Python codes. It facilitates data archiving, preprocessing, instrument correction and quality control - routine but nontrivial tasks that can consume much user time. We describe obspyDMT's functionality, design and technical implementation, accompanied by an overview of its use cases. As an example of a typical problem encountered in seismogram preprocessing, we show how to check for inconsistencies in response files of two example stations. We also demonstrate the fully automated request, remote computation and retrieval of synthetic seismograms from the Synthetics Engine (Syngine) web service of the Data Management Center (DMC) at the Incorporated Research Institutions for Seismology (IRIS).
PLACE: an open-source python package for laboratory automation, control, and experimentation.
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. © 2014 Society for Laboratory Automation and Screening.
OpenSeesPy: Python library for the OpenSees finite element framework
NASA Astrophysics Data System (ADS)
Zhu, Minjie; McKenna, Frank; Scott, Michael H.
2018-01-01
OpenSees, an open source finite element software framework, has been used broadly in the earthquake engineering community for simulating the seismic response of structural and geotechnical systems. The framework allows users to perform finite element analysis with a scripting language and for developers to create both serial and parallel finite element computer applications as interpreters. For the last 15 years, Tcl has been the primary scripting language to which the model building and analysis modules of OpenSees are linked. To provide users with different scripting language options, particularly Python, the OpenSees interpreter interface was refactored to provide multi-interpreter capabilities. This refactoring, resulting in the creation of OpenSeesPy as a Python module, is accomplished through an abstract interface for interpreter calls with concrete implementations for different scripting languages. Through this approach, users are able to develop applications that utilize the unique features of several scripting languages while taking advantage of advanced finite element analysis models and algorithms.
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 &
SCoT: a Python toolbox for EEG source connectivity.
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.
SCoT: a Python toolbox for EEG source connectivity
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. PMID:24653694
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. Copyright © 2014 Elsevier Inc. All rights reserved.
A new open-source Python-based Space Weather data access, visualization, and analysis toolkit
NASA Astrophysics Data System (ADS)
de Larquier, S.; Ribeiro, A.; Frissell, N. A.; Spaleta, J.; Kunduri, B.; Thomas, E. G.; Ruohoniemi, J.; Baker, J. B.
2013-12-01
Space weather research relies heavily on combining and comparing data from multiple observational platforms. Current frameworks exist to aggregate some of the data sources, most based on file downloads via web or ftp interfaces. Empirical models are mostly fortran based and lack interfaces with more useful scripting languages. In an effort to improve data and model access, the SuperDARN community has been developing a Python-based Space Science Data Visualization Toolkit (DaViTpy). At the center of this development was a redesign of how our data (from 30 years of SuperDARN radars) was made available. Several access solutions are now wrapped into one convenient Python interface which probes local directories, a new remote NoSQL database, and an FTP server to retrieve the requested data based on availability. Motivated by the efficiency of this interface and the inherent need for data from multiple instruments, we implemented similar modules for other space science datasets (POES, OMNI, Kp, AE...), and also included fundamental empirical models with Python interfaces to enhance data analysis (IRI, HWM, MSIS...). All these modules and more are gathered in a single convenient toolkit, which is collaboratively developed and distributed using Github and continues to grow. While still in its early stages, we expect this toolkit will facilitate multi-instrument space weather research and improve scientific productivity.
PyEphem: Astronomical Ephemeris for Python
NASA Astrophysics Data System (ADS)
Rhodes, Brandon Craig
2011-12-01
PyEphem provides scientific-grade astronomical computations for the Python programming language. Given a date and location on the Earth’s surface, it can compute the positions of the Sun and Moon, of the planets and their moons, and of any asteroids, comets, or earth satellites whose orbital elements the user can provide. Additional functions are provided to compute the angular separation between two objects in the sky, to determine the constellation in which an object lies, and to find the times at which an object rises, transits, and sets on a particular day. The numerical routines that lie behind PyEphem are those from the wonderful XEphem astronomy application, whose author, Elwood Downey, generously gave permission for us to use them as the basis for PyEphem.
PyCOOL — A Cosmological Object-Oriented Lattice code written in Python
NASA Astrophysics Data System (ADS)
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/.
Identification of snake arenaviruses in live boas and pythons in a zoo in Germany.
Aqrawi, T; Stöhr, A C; Knauf-Witzens, T; Krengel, A; Heckers, K O; Marschang, R E
2015-01-01
Recent studies have described the detection and characterisation of new, snake specific arenaviruses in boas and pythons with inclusion body disease (IBD). The objective of this study was to detect arenaviral RNA in live snakes and to determine if these were associated with IBD in all cases. Samples for arenavirus detection in live animals were compared. Detected viruses were compared in order to understand their genetic variability. Esophageal swabs and whole blood was collected from a total of 28 boas and pythons. Samples were tested for arenaviral RNA by RT-PCR. Blood smears from all animals were examined for the presence of inclusion bodies. Internal tissues from animals that died or were euthanized during the study were examined for inclusions and via RT-PCR for arenaviral RNA. All PCR products were sequenced and the genomic sequences phylogenetically analysed. Nine live animals were found to be arenavirus-positive. Two additional snakes tested positive following necropsy. Five new arenaviruses were detected and identified. The detected viruses were named "Boa Arenavirus Deutschland (Boa Av DE) numbers 1-4" and one virus detected in a python (Morelia viridis) was named "Python Av DE1". Results from sequence analyses revealed considerable similarities to a portion of the glycoprotein genes of recently identified boid snake arenaviruses. Both oral swabs and whole blood can be used for the detection of arenaviruses in snakes. In most cases, but not in all, the presence of arenaviral RNA correlated with the presence of inclusions in the tissues of infected animals. There was evidence that some animals may be able to clear arenavirus infection without development of IBD. This is the first detection of arenaviruses in live snakes. The detection of arenaviruses in live snakes is of importance for both disease detection and prevention and for use in quarantine situations. The findings in this study support the theory that arenaviruses are the cause of IBD, but
SunPy 0.8 - Python for Solar Physics
NASA Astrophysics Data System (ADS)
Inglis, Andrew; Bobra, Monica; Christe, Steven; Hewett, Russell; Ireland, Jack; Mumford, Stuart; Martinez Oliveros, Juan Carlos; Perez-Suarez, David; Reardon, Kevin P.; Savage, Sabrina; Shih, Albert Y.; Ryan, Daniel; Sipocz, Brigitta; Freij, Nabil
2017-08-01
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. Python is one of the top ten most often used programming languages, as such it provides a wide array of software packages, such as numerical computation (NumPy, SciPy), machine learning (scikit-learn), signal processing (scikit-image, statsmodels) to visualization and plotting (matplotlib, mayavi). SunPy aims to provide the software for obtaining and analyzing solar and heliospheric data. This poster introduces a new major release of SunPy (0.8). This release includes two major new functionalities, as well as a number of bug fixes. It is based on 1120 contributions from 34 unique contributors. Fido is the new primary interface to download data. It provides a consistent and powerful search interface to all major data sources provides including VSO, JSOC, as well as individual data sources such as GOES XRS time series and and is fully pluggable to add new data sources, i.e. DKIST. In anticipation of Solar Orbiter and the Parker Solar Probe, SunPy now provides a powerful way of representing coordinates, allowing conversion between coordinate systems and viewpoints of different instruments, including preliminary reprojection capabilities. Other new features including new timeseries capabilities with better support for concatenation and metadata, updated documentation and example gallery. SunPy is distributed through pip and conda and all of its code is publicly available (sunpy.org).
PyCoTools: A Python Toolbox for COPASI.
Welsh, Ciaran M; Fullard, Nicola; Proctor, Carole J; Martinez-Guimera, Alvaro; Isfort, Robert J; Bascom, Charles C; Tasseff, Ryan; Przyborski, Stefan A; Shanley, Daryl P
2018-05-22
COPASI is an open source software package for constructing, simulating and analysing dynamic models of biochemical networks. COPASI is primarily intended to be used with a graphical user interface but often it is desirable to be able to access COPASI features programmatically, with a high level interface. PyCoTools is a Python package aimed at providing a high level interface to COPASI tasks with an emphasis on model calibration. PyCoTools enables the construction of COPASI models and the execution of a subset of COPASI tasks including time courses, parameter scans and parameter estimations. Additional 'composite' tasks which use COPASI tasks as building blocks are available for increasing parameter estimation throughput, performing identifiability analysis and performing model selection. PyCoTools supports exploratory data analysis on parameter estimation data to assist with troubleshooting model calibrations. We demonstrate PyCoTools by posing a model selection problem designed to show case PyCoTools within a realistic scenario. The aim of the model selection problem is to test the feasibility of three alternative hypotheses in explaining experimental data derived from neonatal dermal fibroblasts in response to TGF-β over time. PyCoTools is used to critically analyse the parameter estimations and propose strategies for model improvement. PyCoTools can be downloaded from the Python Package Index (PyPI) using the command 'pip install pycotools' or directly from GitHub (https://github.com/CiaranWelsh/pycotools). Documentation at http://pycotools.readthedocs.io. Supplementary data are available at Bioinformatics.
Naima: a Python package for inference of particle distribution properties from nonthermal spectra
NASA Astrophysics Data System (ADS)
Zabalza, V.
2015-07-01
The ultimate goal of the observation of nonthermal emission from astrophysical sources is to understand the underlying particle acceleration and evolution processes, and few tools are publicly available to infer the particle distribution properties from the observed photon spectra from X-ray to VHE gamma rays. Here I present naima, an open source Python package that provides models for nonthermal radiative emission from homogeneous distribution of relativistic electrons and protons. Contributions from synchrotron, inverse Compton, nonthermal bremsstrahlung, and neutral-pion decay can be computed for a series of functional shapes of the particle energy distributions, with the possibility of using user-defined particle distribution functions. In addition, naima provides a set of functions that allow to use these models to fit observed nonthermal spectra through an MCMC procedure, obtaining probability distribution functions for the particle distribution parameters. Here I present the models and methods available in naima and an example of their application to the understanding of a galactic nonthermal source. naima's documentation, including how to install the package, is available at http://naima.readthedocs.org.
A Python Calculator for Supernova Remnant Evolution
NASA Astrophysics Data System (ADS)
Leahy, D. A.; Williams, J. E.
2017-05-01
A freely available Python code for modeling supernova remnant (SNR) evolution has been created. This software is intended for two purposes: to understand SNR evolution and to use in modeling observations of SNR for obtaining good estimates of SNR properties. It includes all phases for the standard path of evolution for spherically symmetric SNRs. In addition, alternate evolutionary models are available, including evolution in a cloudy ISM, the fractional energy-loss model, and evolution in a hot low-density ISM. The graphical interface takes in various parameters and produces outputs such as shock radius and velocity versus time, as well as SNR surface brightness profile and spectrum. Some interesting properties of SNR evolution are demonstrated using the program.
Creating CAD designs and performing their subsequent analysis using opensource solutions in Python
NASA Astrophysics Data System (ADS)
Iakushkin, Oleg O.; Sedova, Olga S.
2018-01-01
The paper discusses the concept of a system that encapsulates the transition from geometry building to strength tests. The solution we propose views the engineer as a programmer who is capable of coding the procedure for working with the modeli.e., to outline the necessary transformations and create cases for boundary conditions. We propose a prototype of such system. In our work, we used: Python programming language to create the program; Jupyter framework to create a single workspace visualization; pythonOCC library to implement CAD; FeniCS library to implement FEM; GMSH and VTK utilities. The prototype is launched on a platform which is a dynamically expandable multi-tenant cloud service providing users with all computing resources on demand. However, the system may be deployed locally for prototyping or work that does not involve resource-intensive computing. To make it possible, we used containerization, isolating the system in a Docker container.
Simulation with Python on transverse modes of the symmetric confocal resonator
NASA Astrophysics Data System (ADS)
Wang, Qing Hua; Qi, Jing; Ji, Yun Jing; Song, Yang; Li, Zhenhua
2017-08-01
Python is a popular open-source programming language that can be used to simulate various optical phenomena. We have developed a suite of programs to help teach the course of laser principle. The complicated transverse modes of the symmetric confocal resonator can be visualized in personal computers, which is significant to help the students understand the pattern distribution of laser resonator.
A parvovirus isolated from royal python (Python regius) is a member of the genus Dependovirus.
Farkas, Szilvia L; Zádori, Zoltán; Benko, Mária; Essbauer, Sandra; Harrach, Balázs; Tijssen, Peter
2004-03-01
Parvoviruses were isolated from Python regius and Boa constrictor snakes and propagated in viper heart (VH-2) and iguana heart (IgH-2) cells. The full-length genome of a snake parvovirus was cloned and both strands were sequenced. The organization of the 4432-nt-long genome was found to be typical of parvoviruses. This genome was flanked by inverted terminal repeats (ITRs) of 154 nt, containing 122 nt terminal hairpins and contained two large open reading frames, encoding the non-structural and structural proteins. Genes of this new parvovirus were most similar to those from waterfowl parvoviruses and from adeno-associated viruses (AAVs), albeit to a relatively low degree and with some organizational differences. The structure of its ITRs also closely resembled those of AAVs. Based on these data, we propose to classify this virus, the first serpentine parvovirus to be identified, as serpentine adeno-associated virus (SAAV) in the genus Dependovirus.
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.
Teaching Beginning Chemistry Students Simple Lewis Dot Structures
ERIC Educational Resources Information Center
Nassiff, Peter; Czerwinski, Wendy A.
2015-01-01
Students beginning their initial study of chemistry often have a difficult time mastering simple Lewis dot structures. Textbooks show students how to manipulate Lewis structures by moving valence electron dots around the chemical structure so each atom has an octet or duet. However, an easier method of teaching Lewis structures for simple…
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.
ObsPy: A Python toolbox for seismology - Sustainability, New Features, and Applications
NASA Astrophysics Data System (ADS)
Krischer, L.; Megies, T.; Sales de Andrade, E.; Barsch, R.; MacCarthy, J.
2016-12-01
ObsPy (https://www.obspy.org) is a community-driven, open-source project dedicated to offer a bridge for seismology into the scientific Python ecosystem. Amongst other things, it provides Read and write support for essentially every commonly used data format in seismology with a unified interface. This includes waveform data as well as station and event meta information. A signal processing toolbox tuned to the specific needs of seismologists. Integrated access to the largest data centers, web services, and databases. Wrappers around third party codes like libmseed and evalresp. Using ObsPy enables users to take advantage of the vast scientific ecosystem that has developed around Python. In contrast to many other programming languages and tools, Python 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 must be translated to stable and production ready environments, especially in the age of big data. ObsPy has seen constant development for more than six years and enjoys a large rate of adoption in the seismological 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. We will present a short overview of the capabilities of ObsPy and point out several representative use cases and more specialized software built around ObsPy. Additionally we will discuss new and upcoming features, as well as the sustainability of open-source scientific software.
Optimizing python-based ROOT I/O with PyPy's tracing just-in-time compiler
NASA Astrophysics Data System (ADS)
Tlp Lavrijsen, Wim
2012-12-01
The Python programming language allows objects and classes to respond dynamically to the execution environment. Most of this, however, is made possible through language hooks which by definition can not be optimized and thus tend to be slow. The PyPy implementation of Python includes a tracing just in time compiler (JIT), which allows similar dynamic responses but at the interpreter-, rather than the application-level. Therefore, it is possible to fully remove the hooks, leaving only the dynamic response, in the optimization stage for hot loops, if the types of interest are opened up to the JIT. A general opening up of types to the JIT, based on reflection information, has already been developed (cppyy). The work described in this paper takes it one step further by customizing access to ROOT I/O to the JIT, allowing for fully automatic optimizations.
PyChimera: use UCSF Chimera modules in any Python 2.7 project.
Rodríguez-Guerra Pedregal, Jaime; Maréchal, Jean-Didier
2018-05-15
UCSF Chimera is a powerful visualization tool remarkably present in the computational chemistry and structural biology communities. Built on a C++ core wrapped under a Python 2.7 environment, one could expect to easily import UCSF Chimera's arsenal of resources in custom scripts or software projects. Nonetheless, this is not readily possible if the script is not executed within UCSF Chimera due to the isolation of the platform. UCSF ChimeraX, successor to the original Chimera, partially solves the problem but yet major upgrades need to be undergone so that this updated version can offer all UCSF Chimera features. PyChimera has been developed to overcome these limitations and provide access to the UCSF Chimera codebase from any Python 2.7 interpreter, including interactive programming with tools like IPython and Jupyter Notebooks, making it easier to use with additional third-party software. PyChimera is LGPL-licensed and available at https://github.com/insilichem/pychimera. jaime.rodriguezguerra@uab.cat or jeandidier.marechal@uab.cat. Supplementary data are available at Bioinformatics online.
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.
pyRMSD: a Python package for efficient pairwise RMSD matrix calculation and handling.
Gil, Víctor A; Guallar, Víctor
2013-09-15
We introduce pyRMSD, an open source standalone Python package that aims at offering an integrative and efficient way of performing Root Mean Square Deviation (RMSD)-related calculations of large sets of structures. It is specially tuned to do fast collective RMSD calculations, as pairwise RMSD matrices, implementing up to three well-known superposition algorithms. pyRMSD provides its own symmetric distance matrix class that, besides the fact that it can be used as a regular matrix, helps to save memory and increases memory access speed. This last feature can dramatically improve the overall performance of any Python algorithm using it. In addition, its extensibility, testing suites and documentation make it a good choice to those in need of a workbench for developing or testing new algorithms. The source code (under MIT license), installer, test suites and benchmarks can be found at https://pele.bsc.es/ under the tools section. victor.guallar@bsc.es Supplementary data are available at Bioinformatics online.
FRED 2: an immunoinformatics framework for Python
Schubert, Benjamin; Walzer, Mathias; Brachvogel, Hans-Philipp; Szolek, András; Mohr, Christopher; Kohlbacher, Oliver
2016-01-01
Summary: Immunoinformatics approaches are widely used in a variety of applications from basic immunological to applied biomedical research. Complex data integration is inevitable in immunological research and usually requires comprehensive pipelines including multiple tools and data sources. Non-standard input and output formats of immunoinformatics tools make the development of such applications difficult. Here we present FRED 2, an open-source immunoinformatics framework offering easy and unified access to methods for epitope prediction and other immunoinformatics applications. FRED 2 is implemented in Python and designed to be extendable and flexible to allow rapid prototyping of complex applications. Availability and implementation: FRED 2 is available at http://fred-2.github.io Contact: schubert@informatik.uni-tuebingen.de Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27153717
FRED 2: an immunoinformatics framework for Python.
Schubert, Benjamin; Walzer, Mathias; Brachvogel, Hans-Philipp; Szolek, András; Mohr, Christopher; Kohlbacher, Oliver
2016-07-01
Immunoinformatics approaches are widely used in a variety of applications from basic immunological to applied biomedical research. Complex data integration is inevitable in immunological research and usually requires comprehensive pipelines including multiple tools and data sources. Non-standard input and output formats of immunoinformatics tools make the development of such applications difficult. Here we present FRED 2, an open-source immunoinformatics framework offering easy and unified access to methods for epitope prediction and other immunoinformatics applications. FRED 2 is implemented in Python and designed to be extendable and flexible to allow rapid prototyping of complex applications. FRED 2 is available at http://fred-2.github.io schubert@informatik.uni-tuebingen.de Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.
PyORBIT: A Python Shell For ORBIT
DOE Office of Scientific and Technical Information (OSTI.GOV)
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. Wemore » also compare PyORBIT to ORBIT from the standpoint of features, performance and future expandability.« less
Drewes, Rich; Zou, Quan; Goodman, Philip H.
2008-01-01
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. PMID:19506707
qtcm 0.1.2: A Python Implementation of the Neelin-Zeng Quasi-Equilibrium Tropical Circulation model
NASA Astrophysics Data System (ADS)
Lin, J. W.-B.
2008-10-01
Historically, climate models have been developed incrementally and in compiled languages like Fortran. While the use of legacy compiled languages results in fast, time-tested code, the resulting model is limited in its modularity and cannot take advantage of functionality available with modern computer languages. Here we describe an effort at using the open-source, object-oriented language Python to 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.
qtcm 0.1.2: a Python implementation of the Neelin-Zeng Quasi-Equilibrium Tropical Circulation Model
NASA Astrophysics Data System (ADS)
Lin, J. W.-B.
2009-02-01
Historically, climate models have been developed incrementally and in compiled languages like Fortran. While the use of legacy compiled languages results in fast, time-tested code, the resulting model is limited in its modularity and cannot take advantage of functionality available with modern computer languages. Here we describe an effort at using the open-source, object-oriented language Python to 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.
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. Copyright © 2012 Wiley Periodicals, Inc.
Introducing Python tools for magnetotellurics: MTpy
NASA Astrophysics Data System (ADS)
Krieger, L.; Peacock, J.; Inverarity, K.; Thiel, S.; Robertson, K.
2013-12-01
Within the framework of geophysical exploration techniques, the magnetotelluric method (MT) is relatively immature: It is still not as widely spread as other geophysical methods like seismology, and its processing schemes and data formats are not thoroughly standardized. As a result, the file handling and processing software within the academic community is mainly based on a loose collection of codes, which are sometimes highly adapted to the respective local specifications. Although tools for the estimation of the frequency dependent MT transfer function, as well as inversion and modelling codes, are available, the standards and software for handling MT data are generally not unified throughout the community. To overcome problems that arise from missing standards, and to simplify the general handling of MT data, we have developed the software package "MTpy", which allows the handling, processing, and imaging of magnetotelluric data sets. It is written in Python and the code is open-source. The setup of this package follows the modular approach of successful software packages like GMT or Obspy. It contains sub-packages and modules for various tasks within the standard MT data processing and handling scheme. Besides pure Python classes and functions, MTpy provides wrappers and convenience scripts to call external software, e.g. modelling and inversion codes. Even though still under development, MTpy already contains ca. 250 functions that work on raw and preprocessed data. However, as our aim is not to produce a static collection of software, we rather introduce MTpy as a flexible framework, which will be dynamically extended in the future. It then has the potential to help standardise processing procedures and at same time be a versatile supplement for existing algorithms. We introduce the concept and structure of MTpy, and we illustrate the workflow of MT data processing utilising MTpy on an example data set collected over a geothermal exploration site in South
celerite: Scalable 1D Gaussian Processes in C++, Python, and Julia
NASA Astrophysics Data System (ADS)
Foreman-Mackey, Daniel; Agol, Eric; Ambikasaran, Sivaram; Angus, Ruth
2017-09-01
celerite provides fast and scalable Gaussian Process (GP) Regression in one dimension and is implemented in C++, Python, and Julia. The celerite API is designed to be familiar to users of george and, like george, celerite is designed to efficiently evaluate the marginalized likelihood of a dataset under a GP model. This is then be used alongside a non-linear optimization or posterior inference library for the best results.
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…
Dem Generation from Close-Range Photogrammetry Using Extended Python Photogrammetry Toolbox
NASA Astrophysics Data System (ADS)
Belmonte, A. A.; Biong, M. M. P.; Macatulad, E. G.
2017-10-01
Digital elevation models (DEMs) are widely used raster data for different applications concerning terrain, such as for flood modelling, viewshed analysis, mining, land development, engineering design projects, to name a few. DEMs can be obtained through various methods, including topographic survey, LiDAR or photogrammetry, and internet sources. Terrestrial close-range photogrammetry is one of the alternative methods to produce DEMs through the processing of images using photogrammetry software. There are already powerful photogrammetry software that are commercially-available and can produce high-accuracy DEMs. However, this entails corresponding cost. Although, some of these software have free or demo trials, these trials have limits in their usable features and usage time. One alternative is the use of free and open-source software (FOSS), such as the Python Photogrammetry Toolbox (PPT), which provides an interface for performing photogrammetric processes implemented through python script. For relatively small areas such as in mining or construction excavation, a relatively inexpensive, fast and accurate method would be advantageous. In this study, PPT was used to generate 3D point cloud data from images of an open pit excavation. The PPT was extended to add an algorithm converting the generated point cloud data into a usable DEM.
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.
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.
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.
Interfacing of high temperature Z-meter setup using python
NASA Astrophysics Data System (ADS)
Patel, Ashutosh; Sisodia, Shashank; Pandey, Sudhir K.
2017-05-01
In this work, we interface high temperature Z-meter setup to automize the whole measurement process. A program is built on open source programming language `Python' which convert the manual measurement process into fully automated process without any cost addition. Using this program, simultaneous measurement of Seebeck coefficient (α), thermal conductivity (κ) and electrical resistivity (ρ), are performed and using all three, figure-of-merit (ZT) is calculated. Developed program is verified by performing measurement over p-type Bi0.36Sb1.45Te3 sample and the data obtained are found to be in good agreement with the reported data.
Effects of temperature on the metabolic response to feeding in Python molurus.
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.
PylotDB - A Database Management, Graphing, and Analysis Tool Written in Python
DOE Office of Scientific and Technical Information (OSTI.GOV)
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;more » 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.« less
Functional morphology and patterns of blood flow in the heart of Python regius.
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
NASA Astrophysics Data System (ADS)
Braun, N.; Hauth, T.; Pulvermacher, C.; Ritter, M.
2017-10-01
Today’s analyses for high-energy physics (HEP) experiments involve processing a large amount of data with highly specialized algorithms. The contemporary workflow from recorded data to final results is based on the execution of small scripts - often written in Python or ROOT macros which call complex compiled algorithms in the background - to perform fitting procedures and generate plots. During recent years interactive programming environments, such as Jupyter, became popular. Jupyter allows to develop Python-based applications, so-called notebooks, which bundle code, documentation and results, e.g. plots. Advantages over classical script-based approaches is the feature to recompute only parts of the analysis code, which allows for fast and iterative development, and a web-based user frontend, which can be hosted centrally and only requires a browser on the user side. In our novel approach, Python and Jupyter are tightly integrated into the Belle II Analysis Software Framework (basf2), currently being developed for the Belle II experiment in Japan. This allows to develop code in Jupyter notebooks for every aspect of the event simulation, reconstruction and analysis chain. These interactive notebooks can be hosted as a centralized web service via jupyterhub with docker and used by all scientists of the Belle II Collaboration. Because of its generality and encapsulation, the setup can easily be scaled to large installations.
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.
Efficient and Flexible Climate Analysis with Python in a Cloud-Based Distributed Computing Framework
NASA Astrophysics Data System (ADS)
Gannon, C.
2017-12-01
As climate models become progressively more advanced, and spatial resolution further improved through various downscaling projects, climate projections at a local level are increasingly insightful and valuable. However, the raw size of climate datasets presents numerous hurdles for analysts wishing to develop customized climate risk metrics or perform site-specific statistical analysis. Four Twenty Seven, a climate risk consultancy, has implemented a Python-based distributed framework to analyze large climate datasets in the cloud. With the freedom afforded by efficiently processing these datasets, we are able to customize and continually develop new climate risk metrics using the most up-to-date data. Here we outline our process for using Python packages such as XArray and Dask to evaluate netCDF files in a distributed framework, StarCluster to operate in a cluster-computing environment, cloud computing services to access publicly hosted datasets, and how this setup is particularly valuable for generating climate change indicators and performing localized statistical analysis.
Neuroimaging, Genetics, and Clinical Data Sharing in Python Using the CubicWeb Framework
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
Neuroimaging, Genetics, and Clinical Data Sharing in Python Using the CubicWeb Framework.
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.
Esquerré, Damien; Sherratt, Emma; Keogh, J Scott
2017-12-01
Ontogenetic allometry, how species change with size through their lives, and heterochony, a decoupling between shape, size, and age, are major contributors to biological diversity. However, macroevolutionary allometric and heterochronic trends remain poorly understood because previous studies have focused on small groups of closely related species. Here, we focus on testing hypotheses about the evolution of allometry and how allometry and heterochrony drive morphological diversification at the level of an entire species-rich and diverse clade. Pythons are a useful system due to their remarkably diverse and well-adapted phenotypes and extreme size disparity. We collected detailed phenotype data on 40 of the 44 species of python from 1191 specimens. We used a suite of analyses to test for shifts in allometric trajectories that modify morphological diversity. Heterochrony is the main driver of initial divergence within python clades, and shifts in the slopes of allometric trajectories make exploration of novel phenotypes possible later in divergence history. We found that allometric coefficients are highly evolvable and there is an association between ontogenetic allometry and ecology, suggesting that allometry is both labile and adaptive rather than a constraint on possible phenotypes. © 2017 The Author(s). Evolution © 2017 The Society for the Study of Evolution.
ODTbrain: a Python library for full-view, dense diffraction tomography.
Müller, Paul; Schürmann, Mirjam; Guck, Jochen
2015-11-04
Analyzing the three-dimensional (3D) refractive index distribution of a single cell makes it possible to describe and characterize its inner structure in a marker-free manner. A dense, full-view tomographic data set is a set of images of a cell acquired for multiple rotational positions, densely distributed from 0 to 360 degrees. The reconstruction is commonly realized by projection tomography, which is based on the inversion of the Radon transform. The reconstruction quality of projection tomography is greatly improved when first order scattering, which becomes relevant when the imaging wavelength is comparable to the characteristic object size, is taken into account. This advanced reconstruction technique is called diffraction tomography. While many implementations of projection tomography are available today, there is no publicly available implementation of diffraction tomography so far. We present a Python library that implements the backpropagation algorithm for diffraction tomography in 3D. By establishing benchmarks based on finite-difference time-domain (FDTD) simulations, we showcase the superiority of the backpropagation algorithm over the backprojection algorithm. Furthermore, we discuss how measurment parameters influence the reconstructed refractive index distribution and we also give insights into the applicability of diffraction tomography to biological cells. The present software library contains a robust implementation of the backpropagation algorithm. The algorithm is ideally suited for the application to biological cells. Furthermore, the implementation is a drop-in replacement for the classical backprojection algorithm and is made available to the large user community of the Python programming language.
Temporal and spatial complexity of maternal thermoregulation in tropical pythons.
Stahlschmidt, Zachary Ross; Shine, Richard; Denardo, Dale F
2012-01-01
Parental care is a widespread adaptation that evolved independently in a broad range of taxa. Although the dynamics by which two parents meet the developmental needs of offspring are well studied in birds, we lack understanding about the temporal and spatial complexity of parental care in taxa exhibiting female-only care, the predominant mode of parental care. Thus, we examined the behavioral and physiological mechanisms by which female water pythons Liasis fuscus meet a widespread developmental need (thermoregulation) in a natural setting. Although female L. fuscus were not facultatively thermogenic, they did use behaviors on multiple spatial scales (e.g., shifts in egg-brooding postures and surface activity patterns) to balance the thermal needs of their offspring throughout reproduction (gravidity and egg brooding). Maternal behaviors in L. fuscus varied by stage within reproduction and were mediated by interindividual variation in body size and fecundity. Female pythons with relatively larger clutch sizes were cooler during egg brooding, suggesting a trade-off between reproductive quantity (size of clutch) and quality (developmental temperature). In nature, caregiving parents of all taxa must navigate both extrinsic factors (temporal and spatial complexity) and intrinsic factors (body size and fecundity) to meet the needs of their offspring. Our study used a comprehensive approach that can be used as a general template for future research examining the dynamics by which parents meet other developmental needs (e.g., predation risk or energy balance).
Dual-polarization phase shift processing with the Python ARM Radar Toolkit
NASA Astrophysics Data System (ADS)
Collis, S. M.; Lang, T. J.; Mühlbauer, K.; Helmus, J.; North, K.
2016-12-01
Weather radars that measure backscatter returns at two orthogonal polarizations can give unique insight into storm macro and microphysics. Phase shift between the two polarizations caused by anisotropy in the liquid water path can be used as a constraint in rainfall rate and drop size distribution retrievals, and has the added benefit of being robust to attenuation and radar calibration. The measurement is complicated, however, by the impact of phase shift on backscatter in the presence of large drops and when the pulse volume is not filled uniformly by scatterers (known as partial beam filling). This has led to a signal processing challenge of separating the underlying desired signal from the transient signal, a challenge that has attracted many diverse solutions. To this end, the Python-ARM Radar Toolkit (Py-ART) [1] becomes increasingly important. By providing an open architecture for implementation of retrieval techniques, Py-ART has attracted three very different approaches to the phase processing problem: a fully variational technique, a finite impulse response filter technique [2], and a technique based on a linear programming [3]. These either exist within the toolkit or in another open source package that uses the Py-ART architecture. This presentation will provide an overview of differential phase and specific differential phase observed at C- and S-band frequencies, the signal processing behind the three aforementioned techniques, and some examples of their application. The goal of this presentation is to highlight the importance of open source architectures such as Py-ART for geophysical retrievals. [1] Helmus, J.J. & Collis, S.M., (2016). The Python ARM Radar Toolkit (Py-ART), a Library for Working with Weather Radar Data in the Python Programming Language. JORS. 4(1), p.e25. DOI: http://doi.org/10.5334/jors.119[2] Timothy J. Lang, David A. Ahijevych, Stephen W. Nesbitt, Richard E. Carbone, Steven A. Rutledge, and Robert Cifelli, 2007: Radar
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.
Modeling Quantum Teleportation with Quantum Tools in Python (QuTiP)
2017-12-01
FORM TO THE ABOVE ADDRESS. 1. REPORT DATE (DD-MM-YYYY) December 2017 2. REPORT TYPE Technical Report 3. DATES COVERED (From - To) June 1, 2017... technical report we evaluate one in particular, the Quantum Tools in Python (QuTiP) package, to determine its suitability for use in the simulation of...found that QuTiP is technically sound in that it is able to reproduce several published findings, and that it saves significant program design time due
Kim, Dayeong; Soundrarajan, Nagasundarapandian; Lee, Juyeon; Cho, Hye-Sun; Choi, Minkyeung; Cha, Se-Yeoun; Ahn, Byeongyong; Jeon, Hyoim; Le, Minh Thong; Song, Hyuk; Kim, Jin-Hoi; Park, Chankyu
2017-09-01
In this study, we sought to identify novel antimicrobial peptides (AMPs) in Python bivittatus through bioinformatic analyses of publicly available genome information and experimental validation. In our analysis of the python genome, we identified 29 AMP-related candidate sequences. Of these, we selected five cathelicidin-like sequences and subjected them to further in silico analyses. The results showed that these sequences likely have antimicrobial activity. The sequences were named Pb-CATH1 to Pb-CATH5 according to their sequence similarity to previously reported snake cathelicidins. We predicted their molecular structure and then chemically synthesized the mature peptide for three putative cathelicidins and subjected them to biological activity tests. Interestingly, all three peptides showed potent antimicrobial effects against Gram-negative bacteria but very weak activity against Gram-positive bacteria. Remarkably, ΔPb-CATH4 showed potent activity against antibiotic-resistant clinical isolates and also was observed to possess very low hemolytic activity and cytotoxicity. ΔPb-CATH4 also showed considerable serum stability. Electron microscopic analysis indicated that ΔPb-CATH4 exerts its effects via toroidal pore preformation. Structural comparison of the cathelicidins identified in this study to previously reported ones revealed that these Pb-CATHs are representatives of a new group of reptilian cathelicidins lacking the acidic connecting domain. Furthermore, Pb-CATH4 possesses a completely different mature peptide sequence from those of previously described reptilian cathelicidins. These new AMPs may be candidates for the development of alternatives to or complements of antibiotics to control multidrug-resistant pathogens. Copyright © 2017 American Society for Microbiology.
Kim, Dayeong; Soundrarajan, Nagasundarapandian; Lee, Juyeon; Cho, Hye-sun; Choi, Minkyeung; Cha, Se-Yeoun; Ahn, Byeongyong; Jeon, Hyoim; Le, Minh Thong; Song, Hyuk; Kim, Jin-Hoi
2017-01-01
ABSTRACT In this study, we sought to identify novel antimicrobial peptides (AMPs) in Python bivittatus through bioinformatic analyses of publicly available genome information and experimental validation. In our analysis of the python genome, we identified 29 AMP-related candidate sequences. Of these, we selected five cathelicidin-like sequences and subjected them to further in silico analyses. The results showed that these sequences likely have antimicrobial activity. The sequences were named Pb-CATH1 to Pb-CATH5 according to their sequence similarity to previously reported snake cathelicidins. We predicted their molecular structure and then chemically synthesized the mature peptide for three putative cathelicidins and subjected them to biological activity tests. Interestingly, all three peptides showed potent antimicrobial effects against Gram-negative bacteria but very weak activity against Gram-positive bacteria. Remarkably, ΔPb-CATH4 showed potent activity against antibiotic-resistant clinical isolates and also was observed to possess very low hemolytic activity and cytotoxicity. ΔPb-CATH4 also showed considerable serum stability. Electron microscopic analysis indicated that ΔPb-CATH4 exerts its effects via toroidal pore preformation. Structural comparison of the cathelicidins identified in this study to previously reported ones revealed that these Pb-CATHs are representatives of a new group of reptilian cathelicidins lacking the acidic connecting domain. Furthermore, Pb-CATH4 possesses a completely different mature peptide sequence from those of previously described reptilian cathelicidins. These new AMPs may be candidates for the development of alternatives to or complements of antibiotics to control multidrug-resistant pathogens. PMID:28630199
COSMOS: Python library for massively parallel workflows
Gafni, Erik; Luquette, Lovelace J.; Lancaster, Alex K.; Hawkins, Jared B.; Jung, Jae-Yoon; Souilmi, Yassine; Wall, Dennis P.; Tonellato, Peter J.
2014-01-01
Summary: Efficient workflows to shepherd clinically generated genomic data through the multiple stages of a next-generation sequencing pipeline are of critical importance in translational biomedical science. Here we present COSMOS, a Python library for workflow management that allows formal description of pipelines and partitioning of jobs. In addition, it includes a user interface for tracking the progress of jobs, abstraction of the queuing system and fine-grained control over the workflow. Workflows can be created on traditional computing clusters as well as cloud-based services. Availability and implementation: Source code is available for academic non-commercial research purposes. Links to code and documentation are provided at http://lpm.hms.harvard.edu and http://wall-lab.stanford.edu. Contact: dpwall@stanford.edu or peter_tonellato@hms.harvard.edu. Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24982428
One-dimensional statistical parametric mapping in Python.
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/.
COSMOS: Python library for massively parallel workflows.
Gafni, Erik; Luquette, Lovelace J; Lancaster, Alex K; Hawkins, Jared B; Jung, Jae-Yoon; Souilmi, Yassine; Wall, Dennis P; Tonellato, Peter J
2014-10-15
Efficient workflows to shepherd clinically generated genomic data through the multiple stages of a next-generation sequencing pipeline are of critical importance in translational biomedical science. Here we present COSMOS, a Python library for workflow management that allows formal description of pipelines and partitioning of jobs. In addition, it includes a user interface for tracking the progress of jobs, abstraction of the queuing system and fine-grained control over the workflow. Workflows can be created on traditional computing clusters as well as cloud-based services. Source code is available for academic non-commercial research purposes. Links to code and documentation are provided at http://lpm.hms.harvard.edu and http://wall-lab.stanford.edu. dpwall@stanford.edu or peter_tonellato@hms.harvard.edu. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.
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
CIF2Cell: Generating geometries for electronic structure programs
NASA Astrophysics Data System (ADS)
Björkman, Torbjörn
2011-05-01
The CIF2Cell program generates the geometrical setup for a number of electronic structure programs based on the crystallographic information in a Crystallographic Information Framework (CIF) file. The program will retrieve the space group number, Wyckoff positions and crystallographic parameters, make a sensible choice for Bravais lattice vectors (primitive or principal cell) and generate all atomic positions. Supercells can be generated and alloys are handled gracefully. The code currently has output interfaces to the electronic structure programs ABINIT, CASTEP, CPMD, Crystal, Elk, Exciting, EMTO, Fleur, RSPt, Siesta and VASP. Program summaryProgram title: CIF2Cell Catalogue identifier: AEIM_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEIM_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU GPL version 3 No. of lines in distributed program, including test data, etc.: 12 691 No. of bytes in distributed program, including test data, etc.: 74 933 Distribution format: tar.gz Programming language: Python (versions 2.4-2.7) Computer: Any computer that can run Python (versions 2.4-2.7) Operating system: Any operating system that can run Python (versions 2.4-2.7) Classification: 7.3, 7.8, 8 External routines: PyCIFRW [1] Nature of problem: Generate the geometrical setup of a crystallographic cell for a variety of electronic structure programs from data contained in a CIF file. Solution method: The CIF file is parsed using routines contained in the library PyCIFRW [1], and crystallographic as well as bibliographic information is extracted. The program then generates the principal cell from symmetry information, crystal parameters, space group number and Wyckoff sites. Reduction to a primitive cell is then performed, and the resulting cell is output to suitably named files along with documentation of the information source generated from any bibliographic information contained in the CIF
Beginning Teacher Induction: A Report on Beginning Teacher Effectiveness and Retention.
ERIC Educational Resources Information Center
Serpell, Zewelanji; Bozeman, Leslie A.
National statistics show a rise in the number of beginning teachers undergoing formal induction in their first year of teaching. This report discusses the effectiveness of induction programs and resulting outcomes for beginning teacher retention, beginning teacher effectiveness, and mentor participation. The various components of induction…
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
DOE Office of Scientific and Technical Information (OSTI.GOV)
Zahariev, Federico; De Silva, Nuwan; Gordon, Mark S.
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
Andrew, Audra L; Perry, Blair W; Card, Daren C; Schield, Drew R; Ruggiero, Robert P; McGaugh, Suzanne E; Choudhary, Amit; Secor, Stephen M; Castoe, Todd A
2017-05-02
Previous studies examining post-feeding organ regeneration in the Burmese python (Python molurus bivittatus) have identified thousands of genes that are significantly differentially regulated during this process. However, substantial gaps remain in our understanding of coherent mechanisms and specific growth pathways that underlie these rapid and extensive shifts in organ form and function. Here we addressed these gaps by comparing gene expression in the Burmese python heart, liver, kidney, and small intestine across pre- and post-feeding time points (fasted, one day post-feeding, and four days post-feeding), and by conducting detailed analyses of molecular pathways and predictions of upstream regulatory molecules across these organ systems. Identified enriched canonical pathways and upstream regulators indicate that while downstream transcriptional responses are fairly tissue specific, a suite of core pathways and upstream regulator molecules are shared among responsive tissues. Pathways such as mTOR signaling, PPAR/LXR/RXR signaling, and NRF2-mediated oxidative stress response are significantly differentially regulated in multiple tissues, indicative of cell growth and proliferation along with coordinated cell-protective stress responses. Upstream regulatory molecule analyses identify multiple growth factors, kinase receptors, and transmembrane receptors, both within individual organs and across separate tissues. Downstream transcription factors MYC and SREBF are induced in all tissues. These results suggest that largely divergent patterns of post-feeding gene regulation across tissues are mediated by a core set of higher-level signaling molecules. Consistent enrichment of the NRF2-mediated oxidative stress response indicates this pathway may be particularly important in mediating cellular stress during such extreme regenerative growth.
NASA Astrophysics Data System (ADS)
Smith, M. J.; Vardaro, M.; Crowley, M. F.; Glenn, S. M.; Schofield, O.; Belabbassi, L.; Garzio, L. M.; Knuth, F.; Fram, J. P.; Kerfoot, J.
2016-02-01
The Ocean Observatories Initiative (OOI), funded by the National Science Foundation, provides users with access to long-term datasets from a variety of oceanographic sensors. The Endurance Array in the Pacific Ocean consists of two separate lines off the coasts of Oregon and Washington. The Oregon line consists of 7 moorings, two cabled benthic experiment packages and 6 underwater gliders. The Washington line comprises 6 moorings and 6 gliders. Each mooring is outfitted with a variety of instrument packages. The raw data from these instruments are sent to shore via satellite communication and in some cases, via fiber optic cable. Raw data is then sent to the cyberinfrastructure (CI) group at Rutgers where it is aggregated, parsed into thousands of different data streams, and integrated into a software package called uFrame. The OOI CI delivers the data to the general public via a web interface that outputs data into commonly used scientific data file formats such as JSON, netCDF, and CSV. The Rutgers data management team has developed a series of command-line Python tools that streamline data acquisition in order to facilitate the QA/QC review process. The first step in the process is querying the uFrame database for a list of all available platforms. From this list, a user can choose a specific platform and automatically download all available datasets from the specified platform. The downloaded dataset is plotted using a generalized Python netcdf plotting routine that utilizes a data visualization toolbox called matplotlib. This routine loads each netCDF file separately and outputs plots by each available parameter. These Python tools have been uploaded to a Github repository that is openly available to help facilitate OOI data access and visualization.
PyBoolNet: a python package for the generation, analysis and visualization of boolean networks.
Klarner, Hannes; Streck, Adam; Siebert, Heike
2017-03-01
The goal of this project is to provide a simple interface to working with Boolean networks. Emphasis is put on easy access to a large number of common tasks including the generation and manipulation of networks, attractor and basin computation, model checking and trap space computation, execution of established graph algorithms as well as graph drawing and layouts. P y B ool N et is a Python package for working with Boolean networks that supports simple access to model checking via N u SMV, standard graph algorithms via N etwork X and visualization via dot . In addition, state of the art attractor computation exploiting P otassco ASP is implemented. The package is function-based and uses only native Python and N etwork X data types. https://github.com/hklarner/PyBoolNet. hannes.klarner@fu-berlin.de. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com
Nmrglue: an open source Python package for the analysis of multidimensional NMR data.
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.
Nmrglue: An Open Source Python Package for the Analysis of Multidimensional NMR Data
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
Beginning to manage drug discovery and development knowledge.
Sumner-Smith, M
2001-05-01
Knowledge management approaches and technologies are beginning to be implemented by the pharmaceutical industry in support of new drug discovery and development processes aimed at greater efficiencies and effectiveness. This trend coincides with moves to reduce paper, coordinate larger teams with more diverse skills that are distributed around the globe, and to comply with regulatory requirements for electronic submissions and the associated maintenance of electronic records. Concurrently, the available technologies have implemented web-based architectures with a greater range of collaborative tools and personalization through portal approaches. However, successful application of knowledge management methods depends on effective cultural change management, as well as proper architectural design to match the organizational and work processes within a company.
NASA Astrophysics Data System (ADS)
Anderson, R. B.; Finch, N.; Clegg, S.; Graff, T.; Morris, R. V.; Laura, J.
2017-06-01
We present a Python-based library and graphical interface for the analysis of point spectra. The tool is being developed with a focus on methods used for ChemCam data, but is flexible enough to handle spectra from other instruments.
User interfaces for computational science: A domain specific language for OOMMF embedded in Python
NASA Astrophysics Data System (ADS)
Beg, Marijan; Pepper, Ryan A.; Fangohr, Hans
2017-05-01
Computer simulations are used widely across the engineering and science disciplines, including in the research and development of magnetic devices using computational micromagnetics. In this work, we identify and review different approaches to configuring simulation runs: (i) the re-compilation of source code, (ii) the use of configuration files, (iii) the graphical user interface, and (iv) embedding the simulation specification in an existing programming language to express the computational problem. We identify the advantages and disadvantages of different approaches and discuss their implications on effectiveness and reproducibility of computational studies and results. Following on from this, we design and describe a domain specific language for micromagnetics that is embedded in the Python language, and allows users to define the micromagnetic simulations they want to carry out in a flexible way. We have implemented this micromagnetic simulation description language together with a computational backend that executes the simulation task using the Object Oriented MicroMagnetic Framework (OOMMF). We illustrate the use of this Python interface for OOMMF by solving the micromagnetic standard problem 4. All the code is publicly available and is open source.
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.
PsychoPy--Psychophysics software in Python.
Peirce, Jonathan W
2007-05-15
The vast majority of studies into visual processing are conducted using computer display technology. The current paper describes a new free suite of software tools designed to make this task easier, using the latest advances in hardware and software. PsychoPy is a platform-independent experimental control system written in the Python interpreted language using entirely free libraries. PsychoPy scripts are designed to be extremely easy to read and write, while retaining complete power for the user to customize the stimuli and environment. Tools are provided within the package to allow everything from stimulus presentation and response collection (from a wide range of devices) to simple data analysis such as psychometric function fitting. Most importantly, PsychoPy is highly extensible and the whole system can evolve via user contributions. If a user wants to add support for a particular stimulus, analysis or hardware device they can look at the code for existing examples, modify them and submit the modifications back into the package so that the whole community benefits.
PsychoPy—Psychophysics software in Python
Peirce, Jonathan W.
2007-01-01
The vast majority of studies into visual processing are conducted using computer display technology. The current paper describes a new free suite of software tools designed to make this task easier, using the latest advances in hardware and software. PsychoPy is a platform-independent experimental control system written in the Python interpreted language using entirely free libraries. PsychoPy scripts are designed to be extremely easy to read and write, while retaining complete power for the user to customize the stimuli and environment. Tools are provided within the package to allow everything from stimulus presentation and response collection (from a wide range of devices) to simple data analysis such as psychometric function fitting. Most importantly, PsychoPy is highly extensible and the whole system can evolve via user contributions. If a user wants to add support for a particular stimulus, analysis or hardware device they can look at the code for existing examples, modify them and submit the modifications back into the package so that the whole community benefits. PMID:17254636
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.
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.
PREdator: a python based GUI for data analysis, evaluation and fitting
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.
Biopython: freely available Python tools for computational molecular biology and bioinformatics.
Cock, Peter J A; Antao, Tiago; Chang, Jeffrey T; Chapman, Brad A; Cox, Cymon J; Dalke, Andrew; Friedberg, Iddo; Hamelryck, Thomas; Kauff, Frank; Wilczynski, Bartek; de Hoon, Michiel J L
2009-06-01
The Biopython project is a mature open source international collaboration of volunteer developers, providing Python libraries for a wide range of bioinformatics problems. Biopython includes modules for reading and writing different sequence file formats and multiple sequence alignments, dealing with 3D macro molecular structures, interacting with common tools such as BLAST, ClustalW and EMBOSS, accessing key online databases, as well as providing numerical methods for statistical learning. Biopython is freely available, with documentation and source code at (www.biopython.org) under the Biopython license.
Update 0.2 to "pysimm: A python package for simulation of molecular systems"
NASA Astrophysics Data System (ADS)
Demidov, Alexander G.; Fortunato, Michael E.; Colina, Coray M.
2018-01-01
An update to the pysimm Python molecular simulation API is presented. A major part of the update is the implementation of a new interface with CASSANDRA - a modern, versatile Monte Carlo molecular simulation program. Several significant improvements in the LAMMPS communication module that allow better and more versatile simulation setup are reported as well. An example of an application implementing iterative CASSANDRA-LAMMPS interaction is illustrated.
NASA Astrophysics Data System (ADS)
Yu, Haoyu S.; Fiedler, Lucas J.; Alecu, I. M.; Truhlar, Donald G.
2017-01-01
We present a Python program, FREQ, for calculating the optimal scale factors for calculating harmonic vibrational frequencies, fundamental vibrational frequencies, and zero-point vibrational energies from electronic structure calculations. The program utilizes a previously published scale factor optimization model (Alecu et al., 2010) to efficiently obtain all three scale factors from a set of computed vibrational harmonic frequencies. In order to obtain the three scale factors, the user only needs to provide zero-point energies of 15 or 6 selected molecules. If the user has access to the Gaussian 09 or Gaussian 03 program, we provide the option for the user to run the program by entering the keywords for a certain method and basis set in the Gaussian 09 or Gaussian 03 program. Four other Python programs, input.py, input6, pbs.py, and pbs6.py, are also provided for generating Gaussian 09 or Gaussian 03 input and PBS files. The program can also be used with data from any other electronic structure package. A manual of how to use this program is included in the code package.
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.
Multiple papillomas in a diamond python, Morelia spilota spilota.
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.
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
Low cost of gastric acid secretion during digestion in ball pythons.
Nørgaard, Simon; Andreassen, Kim; Malte, Christian Lind; Enok, Sanne; Wang, Tobias
2016-04-01
Due to their large metabolic responses to digestion (specific dynamic action, SDA), snakes represent an interesting animal group to identify the underlying mechanisms for the postprandial rise in metabolism. The SDA response results from the energetic costs of many different processes ranging over prey handling, secretions by the digestive system, synthesis of enzymes, plasticity of most visceral organs, as well as protein synthesis and nitrogen excretion. The contribution of the individual mechanisms, however, remains elusive. Gastric acid secretion has been proposed to account for more than half of the SDA response, while other studies report much lower contributions of the gastric processes. To investigate the energetic cost of gastric acid secretion, ball pythons (Python regius) were fed meals with added amounts of bone meal (up to 25 g bone meal kg(-1) snake) to achieve a five-fold rise in the buffer capacity of the meals. Direct measurements within the stomach lumen showed similar reduction in gastric pH when buffer capacity was increased, but we found no effects on the rise in oxygen consumption over the first three days of digestion. There was, however, a slower return of oxygen consumption to resting baseline. We conclude that gastric acid secretion only contributes modestly to the SDA response and propose that post-absorptive processes, such as increased protein synthesis, are likely to underlie the SDA response. Copyright © 2016 Elsevier Inc. All rights reserved.
HiCAT Software Infrastructure: Safe hardware control with object oriented Python
NASA Astrophysics Data System (ADS)
Moriarty, Christopher; Brooks, Keira; Soummer, Remi
2018-01-01
High contrast imaging for Complex Aperture Telescopes (HiCAT) is a testbed designed to demonstrate coronagraphy and wavefront control for segmented on-axis space telescopes such as envisioned for LUVOIR. To limit the air movements in the testbed room, software interfaces for several different hardware components were developed to completely automate operations. When developing software interfaces for many different pieces of hardware, unhandled errors are commonplace and can prevent the software from properly closing a hardware resource. Some fragile components (e.g. deformable mirrors) can be permanently damaged because of this. We present an object oriented Python-based infrastructure to safely automate hardware control and optical experiments. Specifically, conducting high-contrast imaging experiments while monitoring humidity and power status along with graceful shutdown processes even for unexpected errors. Python contains a construct called a “context manager” that allows you define code to run when a resource is opened or closed. Context managers ensure that a resource is properly closed, even when unhandled errors occur. Harnessing the context manager design, we also use Python’s multiprocessing library to monitor humidity and power status without interrupting the experiment. Upon detecting a safety problem, the master process sends an event to the child process that triggers the context managers to gracefully close any open resources. This infrastructure allows us to queue up several experiments and safely operate the testbed without a human in the loop.
Iplt--image processing library and toolkit for the electron microscopy community.
Philippsen, Ansgar; Schenk, Andreas D; Stahlberg, Henning; Engel, Andreas
2003-01-01
We present the foundation for establishing a modular, collaborative, integrated, open-source architecture for image processing of electron microscopy images, named iplt. It is designed around object oriented paradigms and implemented using the programming languages C++ and Python. In many aspects it deviates from classical image processing approaches. This paper intends to motivate developers within the community to participate in this on-going project. The iplt homepage can be found at http://www.iplt.org.
Bednar, James A.
2008-01-01
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. PMID:19352443
MatchingTools: A Python library for symbolic effective field theory calculations
NASA Astrophysics Data System (ADS)
Criado, Juan C.
2018-06-01
MatchingTools is a Python library for doing symbolic calculations in effective field theory. It provides the tools to construct general models by defining their field content and their interaction Lagrangian. Once a model is given, the heavy particles can be integrated out at the tree level to obtain an effective Lagrangian in which only the light particles appear. After integration, some of the terms of the resulting Lagrangian might not be independent. MatchingTools contains functions for transforming these terms to rewrite them in terms of any chosen set of operators.
Ecoupling server: A tool to compute and analyze electronic couplings.
Cabeza de Vaca, Israel; Acebes, Sandra; Guallar, Victor
2016-07-05
Electron transfer processes are often studied through the evaluation and analysis of the electronic coupling (EC). Since most standard QM codes do not provide readily such a measure, additional, and user-friendly tools to compute and analyze electronic coupling from external wave functions will be of high value. The first server to provide a friendly interface for evaluation and analysis of electronic couplings under two different approximations (FDC and GMH) is presented in this communication. Ecoupling server accepts inputs from common QM and QM/MM software and provides useful plots to understand and analyze the results easily. The web server has been implemented in CGI-python using Apache and it is accessible at http://ecouplingserver.bsc.es. Ecoupling server is free and open to all users without login. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.
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 ).
Shah, Abhik; Woolf, Peter
2009-01-01
Summary In this paper, we introduce pebl, a Python library and application for learning Bayesian network structure from data and prior knowledge that provides features unmatched by alternative software packages: the ability to use interventional data, flexible specification of structural priors, modeling with hidden variables and exploitation of parallel processing. PMID:20161541
Pyff - a pythonic framework for feedback applications and stimulus presentation in neuroscience.
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.
An Introduction to Programming for Bioscientists: A Python-Based Primer
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
An Introduction to Programming for Bioscientists: A Python-Based Primer.
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.
Mushu, a free- and open source BCI signal acquisition, written in Python.
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.
Powerlaw: a Python package for analysis of heavy-tailed distributions.
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.
PyMVPA: A python toolbox for multivariate pattern analysis of fMRI data.
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.
PyMVPA: A Python toolbox for multivariate pattern analysis of fMRI data
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. PMID:19184561
Oral flora of Python regius kept as pets.
Dipineto, L; Russo, T P; Calabria, M; De Rosa, L; Capasso, M; Menna, L F; Borrelli, L; Fioretti, A
2014-05-01
This study was aimed at evaluating the oral bacterial flora of 60 Python regius kept as pets by culture and biochemical methods. All isolates were also submitted to antimicrobial susceptibility testing using the disc diffusion method. The oral cavity of snakes sampled harboured a wide range of Gram-negative bacteria mainly constituted by Pseudomonas spp., Morganella morganii, Acinetobacter calcoaceticus, Aeromonas hydrophila, but also by Salmonella spp. Staphylococcus spp. was the commonest Gram-positive isolates, and various anaerobic Clostridium species were also found. The most effective antimicrobial agents were enrofloxacin and ciprofloxacin, followed by doxycycline and gentamicin. The oral cavity of snakes sampled harboured a wide range of bacteria. Our results suggest that people who come in contact with snakes could be at risk of infection and should follow proper hygiene practices when handling these reptiles. © 2014 The Society for Applied Microbiology.
NASA Astrophysics Data System (ADS)
Machalek, P.; Kim, S. M.; Berry, R. D.; Liang, A.; Small, T.; Brevdo, E.; Kuznetsova, A.
2012-12-01
We describe how the Climate Corporation uses Python and Clojure, a language impleneted on top of Java, to generate climatological forecasts for precipitation based on the Advanced Hydrologic Prediction Service (AHPS) radar based daily precipitation measurements. A 2-year-long forecasts is generated on each of the ~650,000 CONUS land based 4-km AHPS grids by constructing 10,000 ensembles sampled from a 30-year reconstructed AHPS history for each grid. The spatial and temporal correlations between neighboring AHPS grids and the sampling of the analogues are handled by Python. The parallelization for all the 650,000 CONUS stations is further achieved by utilizing the MAP-REDUCE framework (http://code.google.com/edu/parallel/mapreduce-tutorial.html). Each full scale computational run requires hundreds of nodes with up to 8 processors each on the Amazon Elastic MapReduce (http://aws.amazon.com/elasticmapreduce/) distributed computing service resulting in 3 terabyte datasets. We further describe how we have productionalized a monthly run of the simulations process at full scale of the 4km AHPS grids and how the resultant terabyte sized datasets are handled.
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.
ChromaStarPy: A Stellar Atmosphere and Spectrum Modeling and Visualization Lab in Python
NASA Astrophysics Data System (ADS)
Short, C. Ian; Bayer, Jason H. T.; Burns, Lindsey M.
2018-02-01
We announce ChromaStarPy, an integrated general stellar atmospheric modeling and spectrum synthesis code written entirely in python V. 3. ChromaStarPy is a direct port of the ChromaStarServer (CSServ) Java modeling code described in earlier papers in this series, and many of the associated JavaScript (JS) post-processing procedures have been ported and incorporated into CSPy so that students have access to ready-made data products. A python integrated development environment (IDE) allows a student in a more advanced course to experiment with the code and to graphically visualize intermediate and final results, ad hoc, as they are running it. CSPy allows students and researchers to compare modeled to observed spectra in the same IDE in which they are processing observational data, while having complete control over the stellar parameters affecting the synthetic spectra. We also take the opportunity to describe improvements that have been made to the related codes, ChromaStar (CS), CSServ, and ChromaStarDB (CSDB), that, where relevant, have also been incorporated into CSPy. The application may be found at the home page of the OpenStars project: http://www.ap.smu.ca/OpenStars/.
PDB file parser and structure class implemented in Python.
Hamelryck, Thomas; Manderick, Bernard
2003-11-22
The biopython project provides a set of bioinformatics tools implemented in Python. Recently, biopython was extended with a set of modules that deal with macromolecular structure. Biopython now contains a parser for PDB files that makes the atomic information available in an easy-to-use but powerful data structure. The parser and data structure deal with features that are often left out or handled inadequately by other packages, e.g. atom and residue disorder (if point mutants are present in the crystal), anisotropic B factors, multiple models and insertion codes. In addition, the parser performs some sanity checking to detect obvious errors. The Biopython distribution (including source code and documentation) is freely available (under the Biopython license) from http://www.biopython.org
pyBSM: A Python package for modeling imaging systems
NASA Astrophysics Data System (ADS)
LeMaster, Daniel A.; Eismann, Michael T.
2017-05-01
There are components that are common to all electro-optical and infrared imaging system performance models. The purpose of the Python Based Sensor Model (pyBSM) is to provide open source access to these functions for other researchers to build upon. Specifically, pyBSM implements much of the capability found in the ERIM Image Based Sensor Model (IBSM) V2.0 along with some improvements. The paper also includes two use-case examples. First, performance of an airborne imaging system is modeled using the General Image Quality Equation (GIQE). The results are then decomposed into factors affecting noise and resolution. Second, pyBSM is paired with openCV to evaluate performance of an algorithm used to detect objects in an image.
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)
Federal Register 2010, 2011, 2012, 2013, 2014
2010-03-12
... DeSchauensee's anaconda-- were shown to pose a medium risk. None of the large constrictors that were assessed... Brazilian island of Marajo, nearby areas around the mouth of the Amazon River, and several drainages in... risk of establishment ranged from medium (reticulated python, DeSchauensee's anaconda, green anaconda...
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/.
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.
The Programming Language Python In Earth System Simulations
NASA Astrophysics Data System (ADS)
Gross, L.; Imranullah, A.; Mora, P.; Saez, E.; Smillie, J.; Wang, C.
2004-12-01
Mathematical models in earth sciences base on the solution of systems of coupled, non-linear, time-dependent partial differential equations (PDEs). The spatial and time-scale vary from a planetary scale and million years for convection problems to 100km and 10 years for fault systems simulations. Various techniques are in use to deal with the time dependency (e.g. Crank-Nicholson), with the non-linearity (e.g. Newton-Raphson) and weakly coupled equations (e.g. non-linear Gauss-Seidel). Besides these high-level solution algorithms discretization methods (e.g. finite element method (FEM), boundary element method (BEM)) are used to deal with spatial derivatives. Typically, large-scale, three dimensional meshes are required to resolve geometrical complexity (e.g. in the case of fault systems) or features in the solution (e.g. in mantel convection simulations). The modelling environment escript allows the rapid implementation of new physics as required for the development of simulation codes in earth sciences. Its main object is to provide a programming language, where the user can define new models and rapidly develop high-level solution algorithms. The current implementation is linked with the finite element package finley as a PDE solver. However, the design is open and other discretization technologies such as finite differences and boundary element methods could be included. escript is implemented as an extension of the interactive programming environment python (see www.python.org). Key concepts introduced are Data objects, which are holding values on nodes or elements of the finite element mesh, and linearPDE objects, which are defining linear partial differential equations to be solved by the underlying discretization technology. In this paper we will show the basic concepts of escript and will show how escript is used to implement a simulation code for interacting fault systems. We will show some results of large-scale, parallel simulations on an SGI Altix
Wrapping Python around MODFLOW/MT3DMS based groundwater models
NASA Astrophysics Data System (ADS)
Post, V.
2008-12-01
Numerical models that simulate groundwater flow and solute transport require a great amount of input data that is often organized into different files. A large proportion of the input data consists of spatially-distributed model parameters. The model output consists of a variety data such as heads, fluxes and concentrations. Typically all files have different formats. Consequently, preparing input and managing output is a complex and error-prone task. Proprietary software tools are available that facilitate the preparation of input files and analysis of model outcomes. The use of such software may be limited if it does not support all the features of the groundwater model or when the costs of such tools are prohibitive. Therefore a Python library was developed that contains routines to generate input files and process output files of MODFLOW/MT3DMS based models. The library is freely available and has an open structure so that the routines can be customized and linked into other scripts and libraries. The current set of functions supports the generation of input files for MODFLOW and MT3DMS, including the capability to read spatially-distributed input parameters (e.g. hydraulic conductivity) from PNG files. Both ASCII and binary output files can be read efficiently allowing for visualization of, for example, solute concentration patterns in contour plots with superimposed flow vectors using matplotlib. Series of contour plots are then easily saved as an animation. The subroutines can also be used within scripts to calculate derived quantities such as the mass of a solute within a particular region of the model domain. Using Python as a wrapper around groundwater models provides an efficient and flexible way of processing input and output data, which is not constrained by limitations of third-party products.
A Python Interface for the Dakota Iterative Systems Analysis Toolkit
NASA Astrophysics Data System (ADS)
Piper, M.; Hutton, E.; Syvitski, J. P.
2016-12-01
Uncertainty quantification is required to improve the accuracy, reliability, and accountability of Earth science models. Dakota is a software toolkit, developed at Sandia National Laboratories, that provides an interface between models and a library of analysis methods, including support for sensitivity analysis, uncertainty quantification, optimization, and calibration techniques. Dakota is a powerful tool, but its learning curve is steep: the user not only must understand the structure and syntax of the Dakota input file, but also must develop intermediate code, called an analysis driver, that allows Dakota to run a model. The CSDMS Dakota interface (CDI) is a Python package that wraps and extends Dakota's user interface. It simplifies the process of configuring and running a Dakota experiment. A user can program to the CDI, allowing a Dakota experiment to be scripted. The CDI creates Dakota input files and provides a generic analysis driver. Any model written in Python that exposes a Basic Model Interface (BMI), as well as any model componentized in the CSDMS modeling framework, automatically works with the CDI. The CDI has a plugin architecture, so models written in other languages, or those that don't expose a BMI, can be accessed by the CDI by programmatically extending a template; an example is provided in the CDI distribution. Currently, six Dakota analysis methods have been implemented for examples from the much larger Dakota library. To demonstrate the CDI, we performed an uncertainty quantification experiment with the HydroTrend hydrological water balance and transport model. In the experiment, we evaluated the response of long-term suspended sediment load at the river mouth (Qs) to uncertainty in two input parameters, annual mean temperature (T) and precipitation (P), over a series of 100-year runs, using the polynomial chaos method. Through Dakota, we calculated moments, local and global (Sobol') sensitivity indices, and probability density and
PyCDT: A Python toolkit for modeling point defects in semiconductors and insulators
Broberg, Danny; Medasani, Bharat; Zimmermann, Nils E. R.; ...
2018-02-13
Point defects have a strong impact on the performance of semiconductor and insulator materials used in technological applications, spanning microelectronics to energy conversion and storage. The nature of the dominant defect types, how they vary with processing conditions, and their impact on materials properties are central aspects that determine the performance of a material in a certain application. This information is, however, difficult to access directly from experimental measurements. Consequently, computational methods, based on electronic density functional theory (DFT), have found widespread use in the calculation of point-defect properties. Here we have developed the Python Charged Defect Toolkit (PyCDT) tomore » expedite the setup and post-processing of defect calculations with widely used DFT software. PyCDT has a user-friendly command-line interface and provides a direct interface with the Materials Project database. This allows for setting up many charged defect calculations for any material of interest, as well as post-processing and applying state-of-the-art electrostatic correction terms. Our paper serves as a documentation for PyCDT, and demonstrates its use in an application to the well-studied GaAs compound semiconductor. As a result, we anticipate that the PyCDT code will be useful as a framework for undertaking readily reproducible calculations of charged point-defect properties, and that it will provide a foundation for automated, high-throughput calculations.« less
PyCDT: A Python toolkit for modeling point defects in semiconductors and insulators
NASA Astrophysics Data System (ADS)
Broberg, Danny; Medasani, Bharat; Zimmermann, Nils E. R.; Yu, Guodong; Canning, Andrew; Haranczyk, Maciej; Asta, Mark; Hautier, Geoffroy
2018-05-01
Point defects have a strong impact on the performance of semiconductor and insulator materials used in technological applications, spanning microelectronics to energy conversion and storage. The nature of the dominant defect types, how they vary with processing conditions, and their impact on materials properties are central aspects that determine the performance of a material in a certain application. This information is, however, difficult to access directly from experimental measurements. Consequently, computational methods, based on electronic density functional theory (DFT), have found widespread use in the calculation of point-defect properties. Here we have developed the Python Charged Defect Toolkit (PyCDT) to expedite the setup and post-processing of defect calculations with widely used DFT software. PyCDT has a user-friendly command-line interface and provides a direct interface with the Materials Project database. This allows for setting up many charged defect calculations for any material of interest, as well as post-processing and applying state-of-the-art electrostatic correction terms. Our paper serves as a documentation for PyCDT, and demonstrates its use in an application to the well-studied GaAs compound semiconductor. We anticipate that the PyCDT code will be useful as a framework for undertaking readily reproducible calculations of charged point-defect properties, and that it will provide a foundation for automated, high-throughput calculations.
PyCDT: A Python toolkit for modeling point defects in semiconductors and insulators
DOE Office of Scientific and Technical Information (OSTI.GOV)
Broberg, Danny; Medasani, Bharat; Zimmermann, Nils E. R.
Point defects have a strong impact on the performance of semiconductor and insulator materials used in technological applications, spanning microelectronics to energy conversion and storage. The nature of the dominant defect types, how they vary with processing conditions, and their impact on materials properties are central aspects that determine the performance of a material in a certain application. This information is, however, difficult to access directly from experimental measurements. Consequently, computational methods, based on electronic density functional theory DFT), have found widespread use in the calculation of point defect properties. Here we have developed the Python Charged Defect Toolkit (PyCDT)more » to expedite the setup and post-processing of defect calculations with widely used DFT software. PyCDT has a user-friendly command-line interface and provides a direct interface with the Materials Project database. This allows for setting up many charged defect calculations for any material of interest, as well as post-processing and applying state-of-the-art electrostatic correction terms. Our paper serves as a documentation for PyCDT, and demonstrates its use in an application to the well-studied GaAs compound semiconductor. We anticipate that the PyCDT code will be useful as a framework for undertaking readily reproducible calculations of charged point-defect properties, and that it will provide a foundation for automated, high-throughput calculations.« less
PyCDT: A Python toolkit for modeling point defects in semiconductors and insulators
DOE Office of Scientific and Technical Information (OSTI.GOV)
Broberg, Danny; Medasani, Bharat; Zimmermann, Nils E. R.
Point defects have a strong impact on the performance of semiconductor and insulator materials used in technological applications, spanning microelectronics to energy conversion and storage. The nature of the dominant defect types, how they vary with processing conditions, and their impact on materials properties are central aspects that determine the performance of a material in a certain application. This information is, however, difficult to access directly from experimental measurements. Consequently, computational methods, based on electronic density functional theory (DFT), have found widespread use in the calculation of point-defect properties. Here we have developed the Python Charged Defect Toolkit (PyCDT) tomore » expedite the setup and post-processing of defect calculations with widely used DFT software. PyCDT has a user-friendly command-line interface and provides a direct interface with the Materials Project database. This allows for setting up many charged defect calculations for any material of interest, as well as post-processing and applying state-of-the-art electrostatic correction terms. Our paper serves as a documentation for PyCDT, and demonstrates its use in an application to the well-studied GaAs compound semiconductor. As a result, we anticipate that the PyCDT code will be useful as a framework for undertaking readily reproducible calculations of charged point-defect properties, and that it will provide a foundation for automated, high-throughput calculations.« less
ObsPy - A Python Toolbox for Seismology - and Applications
NASA Astrophysics Data System (ADS)
Krischer, L.; Megies, T.; Barsch, R.; MacCarthy, J.; Lecocq, T.; Koymans, M. R.; Carothers, L.; Eulenfeld, T.; Reyes, C. G.; Falco, N.; Sales de Andrade, E.
2017-12-01
Recent years witnessed the evolution of Python's ecosystem into one of the most powerful and productive scientific environments across disciplines. ObsPy (https://www.obspy.org) is a fully community driven, open-source project dedicated to provide a bridge for seismology into that ecosystem. It is a Python toolbox offering: Read and write support for essentially every commonly used data format in seismology with a unified interface and automatic format detection. This includes waveform data (MiniSEED, SAC, SEG-Y, Reftek, …) as well as station (SEED, StationXML, SC3ML, …) and event meta information (QuakeML, ZMAP, …). Integrated access to the largest data centers, web services, and real-time data streams (FDSNWS, ArcLink, SeedLink, ...). A powerful signal processing toolbox tuned to the specific needs of seismologists. Utility functionality like travel time calculations with the TauP method, geodetic functions, and data visualizations. ObsPy has been in constant development for more than eight years and is developed and used by scientists around the world with successful applications in all branches of seismology. Additionally it nowadays serves as the foundation for a large number of more specialized packages. Newest features include: Full interoperability of SEED and StationXML/Inventory objects Access to the Nominal Response Library (NRL) for easy and quick creation of station metadata from scratch Support for the IRIS Federated Catalog Service Improved performance of the EarthWorm client Several improvements to MiniSEED read/write module Improved plotting capabilities for PPSD (spectrograms, PSD of discrete frequencies over time, ..) Support for.. Reading ArcLink Inventory XML Reading Reftek data format Writing SeisComp3 ML (SC3ML) Writing StationTXT format This presentation will give a short overview of the capabilities of ObsPy and point out several representative or new use cases and show-case some projects that are based on ObsPy, e.g.: seismo
Anisotropy in the Microwave Sky at 90 GHz: Results from Python III
NASA Astrophysics Data System (ADS)
Platt, S. R.; Kovac, J.; Dragovan, M.; Peterson, J. B.; Ruhl, J. E.
1997-01-01
The third year of observations with the Python microwave background experiment densely samples a 5.5d × 22° region of sky that includes the fields measured during the first 2 years of observations with this instrument. The sky is sampled in two multipole bands centered at l ~ 87 and l ~ 170. These two data sets are analyzed to place limits on fluctuations in the microwave sky at 90 GHz. Interpreting the observed fluctuations as anisotropy in the cosmic microwave background, we find flat-band power estimates of δTl ≡ [l(l + 1)Cl/(2π)]1/2 = 60+15-13 μK at l = 87+18-38 and δTl = 66+17-16 μK at l = 170+69-50. Combining the entire 3 year set of Python observations, we find that the angular power spectrum of fluctuations has a spectral index m = 0.16+.20-.18 and an amplitude δTle = 63+15-14 μK at le = 139+99-34 for the functional form δTl = δTle(l/le)m. The stated uncertainties in the amplitudes and spectral index represent 1 σ confidence intervals in the likelihood added in quadrature with a 20% calibration uncertainty and an estimate of the effects of a +/-0.05d uncertainty in the measured beamwidths. The limits of l are determined from the half-maximum points of the window functions.
Pydna: a simulation and documentation tool for DNA assembly strategies using python.
Pereira, Filipa; Azevedo, Flávio; Carvalho, Ângela; Ribeiro, Gabriela F; Budde, Mark W; Johansson, Björn
2015-05-02
Recent advances in synthetic biology have provided tools to efficiently construct complex DNA molecules which are an important part of many molecular biology and biotechnology projects. The planning of such constructs has traditionally been done manually using a DNA sequence editor which becomes error-prone as scale and complexity of the construction increase. A human-readable formal description of cloning and assembly strategies, which also allows for automatic computer simulation and verification, would therefore be a valuable tool. We have developed pydna, an extensible, free and open source Python library for simulating basic molecular biology DNA unit operations such as restriction digestion, ligation, PCR, primer design, Gibson assembly and homologous recombination. A cloning strategy expressed as a pydna script provides a description that is complete, unambiguous and stable. Execution of the script automatically yields the sequence of the final molecule(s) and that of any intermediate constructs. Pydna has been designed to be understandable for biologists with limited programming skills by providing interfaces that are semantically similar to the description of molecular biology unit operations found in literature. Pydna simplifies both the planning and sharing of cloning strategies and is especially useful for complex or combinatorial DNA molecule construction. An important difference compared to existing tools with similar goals is the use of Python instead of a specifically constructed language, providing a simulation environment that is more flexible and extensible by the user.
MEvoLib v1.0: the first molecular evolution library for Python.
Álvarez-Jarreta, Jorge; Ruiz-Pesini, Eduardo
2016-10-28
Molecular evolution studies involve many different hard computational problems solved, in most cases, with heuristic algorithms that provide a nearly optimal solution. Hence, diverse software tools exist for the different stages involved in a molecular evolution workflow. We present MEvoLib, the first molecular evolution library for Python, providing a framework to work with different tools and methods involved in the common tasks of molecular evolution workflows. In contrast with already existing bioinformatics libraries, MEvoLib is focused on the stages involved in molecular evolution studies, enclosing the set of tools with a common purpose in a single high-level interface with fast access to their frequent parameterizations. The gene clustering from partial or complete sequences has been improved with a new method that integrates accessible external information (e.g. GenBank's features data). Moreover, MEvoLib adjusts the fetching process from NCBI databases to optimize the download bandwidth usage. In addition, it has been implemented using parallelization techniques to cope with even large-case scenarios. MEvoLib is the first library for Python designed to facilitate molecular evolution researches both for expert and novel users. Its unique interface for each common task comprises several tools with their most used parameterizations. It has also included a method to take advantage of biological knowledge to improve the gene partition of sequence datasets. Additionally, its implementation incorporates parallelization techniques to enhance computational costs when handling very large input datasets.
Developing Basic Electronics Aptitudes.
ERIC Educational Resources Information Center
Lakeshore Technical Coll., Cleveland, WI.
This curriculum guide provides materials for basic training in electrical and electronic theory to enable participants to analyze circuits and use test equipment to verify electrical operations and to succeed in the beginning electrical and electronic courses in the Lakeshore Technical College (Wisconsin) electronics programs. The course includes…
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.
Improved cardiac filling facilitates the postprandial elevation of stroke volume in Python regius.
Enok, Sanne; Leite, Gabriella S P C; Leite, Cléo A C; Gesser, Hans; Hedrick, Michael S; Wang, Tobias
2016-10-01
To accommodate the pronounced metabolic response to digestion, pythons increase heart rate and elevate stroke volume, where the latter has been ascribed to a massive and fast cardiac hypertrophy. However, numerous recent studies show that heart mass rarely increases, even upon ingestion of large meals, and we therefore explored the possibility that a rise in mean circulatory filling pressure (MCFP) serves to elevate venous pressure and cardiac filling during digestion. To this end, we measured blood flows and pressures in anaesthetized Python regius The anaesthetized snakes exhibited the archetypal tachycardia as well as a rise in both venous pressure and MCFP that fully account for the approximate doubling of stroke volume. There was no rise in blood volume and the elevated MCFP must therefore stem from increased vascular tone, possibly by means of increased sympathetic tone on the veins. Furthermore, although both venous pressure and MCFP increased during volume loading, there was no evidence that postprandial hearts were endowed with an additional capacity to elevate stroke volume. In vitro measurements of force development of paced ventricular strips also failed to reveal signs of increased contractility, but the postprandial hearts had higher activities of cytochrome oxidase and pyruvate kinase, which probably serves to sustain the rise in cardiac work during digestion. © 2016. Published by The Company of Biologists Ltd.
Pyff – A Pythonic Framework for Feedback Applications and Stimulus Presentation in Neuroscience
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
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
ERIC Educational Resources Information Center
Wildman, Terry M.; And Others
Intended for beginning teachers in Virginia, this handbook is designed to serve as a guide for negotiating the first few years of teaching. The concept of teacher as problem solver is promoted throughout the manual. The handbook is organized around the idea that the beginning teacher's main tasks are to: (1) discover how to learn from their own…
ERIC Educational Resources Information Center
Koonce, Glenn L.; Hoskins, Joan J.; Goldman, Katie D.
2012-01-01
This study illustrates the development, usability, and advantages of an electronic exhibit for the TEAC (Teacher Education Accreditation Council) academic audit from the perspective of program education faculty. The examination of the successful utilization of electronic exhibits for teacher licensure and educational leadership program IBs…
pytc: Open-Source Python Software for Global Analyses of Isothermal Titration Calorimetry Data.
Duvvuri, Hiranmayi; Wheeler, Lucas C; Harms, Michael J
2018-05-08
Here we describe pytc, an open-source Python package for global fits of thermodynamic models to multiple isothermal titration calorimetry experiments. Key features include simplicity, the ability to implement new thermodynamic models, a robust maximum likelihood fitter, a fast Bayesian Markov-Chain Monte Carlo sampler, rigorous implementation, extensive documentation, and full cross-platform compatibility. pytc fitting can be done using an application program interface or via a graphical user interface. It is available for download at https://github.com/harmslab/pytc .
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.
Bioinformatic pipelines in Python with Leaf
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
SunPy: Python for Solar Physics
NASA Astrophysics Data System (ADS)
Bobra, M.; Inglis, A. R.; Mumford, S.; Christe, S.; Freij, N.; Hewett, R.; Ireland, J.; Martinez Oliveros, J. C.; Reardon, K.; Savage, S. L.; Shih, A. Y.; Pérez-Suárez, D.
2017-12-01
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. SunPy aims to provide the software for obtaining and analyzing solar and heliospheric data. This poster introduces a new major release, SunPy version 0.8. The first major new feature introduced is Fido, the new primary interface to download data. It provides a consistent and powerful search interface to all major data providers including the VSO and the JSOC, as well as individual data sources such as GOES XRS time series. It is also easy to add new data sources as they become available, i.e. DKIST. The second major new feature is the SunPy coordinate framework. This provides a powerful way of representing coordinates, allowing simple and intuitive conversion between coordinate systems and viewpoints of different instruments (i.e., Solar Orbiter and the Parker Solar Probe), including transformation to astrophysical frames like ICRS. Other new features including new timeseries capabilities with better support for concatenation and metadata, updated documentation and example gallery. SunPy is distributed through pip and conda and all of its code is publicly available (sunpy.org).
Python-Based Tool for Universal Nuclear Data Extraction
NASA Astrophysics Data System (ADS)
McDonald, William; Blair, Hayden; Consalvi, Peter; Garbiso, Markus; Grover, Hannah; Harget, Alex; Martin, Matthew; Natzke, Connor; Leach, Kyle
2017-09-01
Over the past 70 years, nuclear physics experiments have provided a vast wealth of experimental data on both ground and excited state properties across the nuclear chart. In many cases, searching for and parsing the relevant nuclear structure data from previous work can be tedious and difficult. Although the compilation, evaluation, and digitization of this data by multiple groups around the world over the past several decades has helped dramatically in this respect, the process of performing systematic studies using this data can still be cumbersome and limited. We are in the process of creating a python-based program to extract, sort, and manipulate nuclear and atomic data efficiently. In its current state, the program is able to extract all atomic-shell ionization energies, excited- and ground-state nuclear properties, and all beta-decay rates and ratios. As a part of this ongoing project, we plan to use this tool to examine beta-decay rates in extreme astrophysical environments.
A python framework for environmental model uncertainty analysis
White, Jeremy; Fienen, Michael N.; 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.
A cross-validation package driving Netica with python
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).