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Sample records for zachary wasserman python

  1. Alligator and Python Struggle

    USGS Multimedia Gallery

    An American alligator and a Burmese python locked in a struggle to prevail in Everglades National Park. This python appears to be losing, but snakes in similar situations have apparently escaped unharmed, and in other situations pythons have eaten alligators....

  2. Python for Ecology

    EPA Science Inventory

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

  3. Python to learn programming

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

  4. Python in Astronomy 2016

    NASA Astrophysics Data System (ADS)

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

    2016-04-01

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

  5. 75 FR 38069 - Injurious Wildlife Species; Listing the Boa Constrictor, Four Python Species, and Four Anaconda...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-07-01

    ...), Southern African python (Python natalensis), boa constrictor (Boa constrictor), yellow anaconda (Eunectes... proposed rule (75 FR 11808) to list the Indian python (Python molurus, including Burmese python Python... python (Python sebae), Southern African python (Python natalensis), boa constrictor (Boa...

  6. Python Data Visualization

    SciTech Connect

    2011-08-15

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

  7. Repast for Python Scripting.

    SciTech Connect

    Collier, N.; North, M. J.; Decision and Information Sciences

    2005-01-01

    Repast for Python Scripting (RepastPy) is a rapid application development (RAD) tool for producing simulations from the Repast agent simulation framework. Using a point-and-click component based interface, users can easily construct a simulation and then use a special subset of the Python programming language to define agent behaviors. RepastPy is the next generation of Repast visual development tools superceding the older SimBuilder tool and incorporating a streamlined user interface, improved Python language support, and the latest improvements to Repast. RepastPy now provides the ability to export RepastPy models to Java, allowing users to then work in the traditional Repast for Java environment.

  8. Python Data Visualization

    Energy Science and Technology Software Center (ESTSC)

    2011-08-15

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

  9. Biologists Remove Python from Everglades

    USGS Multimedia Gallery

    This 16 1/2-foot python, being removed from the wild by USGS and NPS personnel, was captured in a thicket in Everglades National Park in May 2012. The python was equipped with a radio-transmitter and an accelerometer as part of one of the Burmese python projects led by USGS to learn more about the b...

  10. Python and computer vision

    SciTech Connect

    Doak, J. E.; Prasad, Lakshman

    2002-01-01

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

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

    USGS Publications Warehouse

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

    2011-01-01

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

  12. Notes on clotting in a Burmese python (Python molurus bivittatus).

    PubMed

    Ratnoff, O D; Rosenberg, M J; Everson, B; Emanuelson, M; Tulodziecki, N

    1990-05-01

    Studies of the clotting mechanisms in the plasma of a Burmese python (Python molurus bivittatus) confirm earlier information that both extrinsic and intrinsic pathways of thrombin formation participate in reptilian hemostasis. Plasma fibrinogen was present at a concentration comparable to that in human plasma. Other assays were hampered by the need to use nonreptilian reagents. The activated partial thromboplastin time was shorter than was that of human plasma, thus implying the presence of prothrombin in python plasma; however, this protein could be demonstrated only in trace amounts. Similarly, only small amounts of Hageman factor (factor XII) and antihemophilic factor (factor VIII) were detected, and none of plasma prekallikrein, high-molecular-weight kininogen, and Christmas factor (factor IX). The prothrombin time was slower than that of human plasma. Factor VII was not detected, but both proaccelerin (factor V) and Stuart factor (factor X) were present. Python plasma inhibited bovine thrombin and human plasmin, but it was deficient in fibrinolytic capacity. PMID:2341766

  13. Pynamic: the Python Dynamic Benchmark

    SciTech Connect

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

    2007-07-10

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

  14. Extension Modules for the Python Interpretive language

    Energy Science and Technology Software Center (ESTSC)

    2006-12-29

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

  15. 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.

  16. Accessing the VO with Python

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  17. Anatomy of the python heart.

    PubMed

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

    2010-12-01

    The hearts of all snakes and lizards consist of two atria and a single incompletely divided ventricle. In general, the squamate ventricle is subdivided into three chambers: cavum arteriosum (left), cavum venosum (medial) and cavum pulmonale (right). Although a similar division also applies to the heart of pythons, this family of snakes is unique amongst snakes in having intracardiac pressure separation. Here we provide a detailed anatomical description of the cardiac structures that confer this functional division. We measured the masses and volumes of the ventricular chambers, and we describe the gross morphology based on dissections of the heart from 13 ball pythons (Python regius) and one Burmese python (P. molurus). The cavum venosum is much reduced in pythons and constitutes approximately 10% of the cavum arteriosum. We suggest that shunts will always be less than 20%, while other studies conclude up to 50%. The high-pressure cavum arteriosum accounted for approximately 75% of the total ventricular mass, and was twice as dense as the low-pressure cavum pulmonale. The reptile ventricle has a core of spongious myocardium, but the three ventricular septa that separate the pulmonary and systemic chambers--the muscular ridge, the bulbuslamelle and the vertical septum--all had layers of compact myocardium. Pythons, however, have unique pads of connective tissue on the site of pressure separation. Because the hearts of varanid lizards, which also are endowed with pressure separation, share many of these morphological specializations, we propose that intraventricular compact myocardium is an indicator of high-pressure systems and possibly pressure separation. PMID:20376590

  18. Python-ARM Radar Toolkit

    SciTech Connect

    2013-03-17

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

  19. Python in the Cling World

    NASA Astrophysics Data System (ADS)

    Lavrijsen, W.

    2015-12-01

    The language improvements in C++11/14 greatly reduce the amount of boilerplate code required and allow resource ownership to be clarified in interfaces. On top, the Cling C++ interpreter brings a truly interactive experience and real dynamic behavior to the language. Taken together, these developments bring C++ much closer to Python in ability, allowing the combination of PyROOT/cppyy and Cling to integrate the two languages on a new level. This paper describes the current state of the art, including cross-language callbacks, automatic template instantiations, and the ability to use Python from Cling.

  20. MontePython: Implementing Quantum Monte Carlo using Python

    NASA Astrophysics Data System (ADS)

    Nilsen, Jon Kristian

    2007-11-01

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

  1. Advanced Python Scripting Using Sherpa

    NASA Astrophysics Data System (ADS)

    Refsdal, R.; Doe, S.; Nguyen, D.; Siemiginowska, A.; Burke, D.; Evans, J.; Evans, I.

    2011-07-01

    Sherpa is a general purpose modeling and fitting application written in Python. The dynamism of Python allows Sherpa to be a powerful and extensible software package ready for the modern challenges of data analysis. Primarily developed for the Chandra Interactive Analysis of Observations (CIAO) package, it provides a flexible environment for resolving spectral and image properties, analyzing time series, and modeling generic types of data. Complex model expressions are supported using Sherpa's general purpose definition syntax. Sherpa's parameterized data modeling is achieved using robust optimization methods implementing the forward fitting technique. Sherpa includes functions to calculate goodness-of-fit and parameter confidence limits. CPU intensive routines are written in C++/FORTRAN. But since all other data structures are contained in Python modules, users can easily add their own data structures, models, statistics or optimization methods to Sherpa. We will introduce a scripted example that highlights Sherpa's ability to estimate energy and photon flux errors using simulations. The draws from these simulations, accessible as NumPy ndarrays, can be sampled from uni-variate and multi-variate normal distributions and can be binned and visualized with simple high level functions. We will demonstrate how Sherpa can be extended with user-defined model and statistic classes written in Python. Sherpa's open design even allows users to incorporate prior statistics derived from the source model.

  2. Pybus -- A Python Software Bus

    SciTech Connect

    Lavrijsen, Wim T.L.P.

    2004-10-14

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

  3. 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.

  4. Pyomo : Python Optimization Modeling Objects.

    SciTech Connect

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

    2010-11-01

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

  5. Steering object-oriented computations with Python

    SciTech Connect

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

    1996-10-01

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

  6. A Burmese Python and an Alligator Encounter in South Florida

    USGS Multimedia Gallery

    A Burmese python (Python molurus) peeks over the head of an alligator that holds the python's body in its mouth in Everglades National Park. Photo courtesy of Lori Oberhofer, National Park Service....

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

    PubMed

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

    2001-09-01

    Neoplastic diseases associated with retroviruses were diagnosed in four Burmese pythons (Python molurus bivattatus) from a single collection. Snake No. 1 was a 7-year-old female with recurrent undifferentiated mesenchymal round cell tumor (lymphosarcoma) of the oral cavity. At necropsy, similar neoplastic masses were evident in the uterus and ovary, and there was diffuse involvement of the spleen. Snake No. 2 was a 4.5-year-old female that was euthanatized because of complications following resection of a segmental colonic adenocarcinoma. Snake No. 3 was a 5-year-old female that was euthanatized because of a large transitional cell carcinoma of the right kidney. Snake No. 4 was a 19-year-old female that was euthanatized following recurrence of an intermandibular fibrosarcoma. Ultrastructural examination revealed few to numerous extracellular and intracellular (intravacuolar) type C-like retroviral particles in all tumors. Tumors were about 90-95 nm in diameter, with an electron-dense core and bilaminar external membrane. The relationship of the intraneoplastic viral particles to the etiology of the tumors is uncertain. PMID:11572567

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

    USGS Publications Warehouse

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

    2011-01-01

    Context. Invasive Burmese pythons (Python molurus bivittatus) are established over thousands of square kilometres of southern Florida, USA, and consume a wide range of native vertebrates. Few tools are available to control the python population, and none of the available tools have been validated in the field to assess capture success as a proportion of pythons available to be captured. Aims. Our primary aim was to conduct a trap trial for capturing invasive pythons in an area east of Everglades National Park, where many pythons had been captured in previous years, to assess the efficacy of traps for population control.Wealso aimed to compare results of visual surveys with trap capture rates, to determine capture rates of non-target species, and to assess capture rates as a proportion of resident pythons in the study area. Methods.Weconducted a medium-scale (6053 trap nights) experiment using two types of attractant traps baited with live rats in the Frog Pond area east of Everglades National Park.Wealso conducted standardised and opportunistic visual surveys in the trapping area. Following the trap trial, the area was disc harrowed to expose pythons and allow calculation of an index of the number of resident pythons. Key results. We captured three pythons and 69 individuals of various rodent, amphibian, and reptile species in traps. Eleven pythons were discovered during disc harrowing operations, as were large numbers of rodents. Conclusions. The trap trial captured a relatively small proportion of the pythons that appeared to be present in the study area, although previous research suggests that trap capture rates improve with additional testing of alternative trap designs. Potential negative impacts to non-target species were minimal. Low python capture rates may have been associated with extremely high local prey abundances during the trap experiment. Implications. Results of this trial illustrate many of the challenges in implementing and interpreting results from tests of control tools for large cryptic predators such as Burmese pythons. ?? CSIRO 2011.

  9. Parallel, Distributed Scripting with Python

    SciTech Connect

    Miller, P J

    2002-05-24

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

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

    PubMed

    Leal, Francisca; Cohn, Martin J

    2015-01-01

    Within amniotes, external copulatory organs have undergone extensive morphological diversification. One of the most extreme examples is squamate (lizards and snakes) hemipenes, which are paired copulatory organs that extend from the lateral margins of the cloaca. Here, we describe the development of hemipenes in a basal snake, the ball python (Python regius). Snake hemipenes arise as a pair of lateral swellings on either side of the caudal part of the cloaca, and these paired outgrowths persist to form the left and right hemipenes. In non-squamate amniotes, external genitalia form from paired swellings that arise on the anterior side of the cloaca, which then fuse medially to form a single genital tubercle, the anlagen of the penis or clitoris. Whereas in non-squamate amniotes, Sonic hedgehog (Shh)-expressing cells of the cloacal endoderm form the urethral or sulcus epithelium and are required for phallus outgrowth, the hemipenes of squamates lack an endodermal contribution, and the sulcus does not express Shh. Thus, snake hemipenes differ from the genital tubercles of non-squamate amniotes both in their embryonic origins and in at least part of patterning mechanisms, which raises the possibility that hemipenes may not be direct homologs of the unpaired amniote penis. Nonetheless, we find that some developmental genes show similar expression patterns in snake hemipenes buds and non-squamate genital tubercles, suggesting that homologous developmental mechanisms are involved in aspects of external genital development across amniotes, even when these structures may have different developmental origins and may have arisen independently during evolution. PMID:24970309

  11. Reflection-Based Python-C++ Bindings

    SciTech Connect

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

    2004-10-14

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

  12. Python fiber-optic seal

    SciTech Connect

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

    1993-12-31

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

  13. Python Scripting for CIAO Data Analysis

    NASA Astrophysics Data System (ADS)

    Galle, E. C.; Anderson, C. S.; Bonaventura, N. R.; Burke, D. J.; Fruscione, A.; Lee, N. P.; McDowell, J. C.

    2011-07-01

    The Chandra X-ray Center has adopted Python as the primary scripting language in the Chandra Interactive Analysis of Observations software package (CIAO). Python is a dynamic object-oriented programming language that offers strong support for integration with other languages and tools and comes with extensive standard libraries. Integrating Python into CIAO allows us to develop powerful new scripts for data analysis, as well as rewrite and improve upon popular CIAO contributed scripts. We discuss the coding guidelines that we have developed during this process, using specific CIAO contributed scripts — available for download online — as examples.

  14. Python based high-level synthesis compiler

    NASA Astrophysics Data System (ADS)

    Cieszewski, Rados?aw; 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.

  15. 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 python wrapper invokes the underlying FORTRAN layer to compute transient groundwater elevations and processes this information to create time-series and 2D plots.

  16. ParselTongue: AIPS Python Interface

    NASA Astrophysics Data System (ADS)

    Kettenis, Mark; Sipior, Mike

    2012-08-01

    ParselTongue is a Python interface to classic AIPS, Obit and possibly other task-based data reduction packages. It serves as the software infrastructure for some of the ALBUS implementation. It allows you to run AIPS tasks, and access AIPS headers and extension tables from Python. There is also support for running Obit tasks and accessing data in FITS files. Full access to the visibilities in AIPS UV data is also available.

  17. 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.

  18. Identification and characterization of two closely related unclassifiable endogenous retroviruses in pythons (Python molurus and Python curtus).

    PubMed

    Huder, Jon B; Böni, Jürg; Hatt, Jean-Michel; Soldati, Guido; Lutz, Hans; Schüpbach, Jörg

    2002-08-01

    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

  19. Identification and Characterization of Two Closely Related Unclassifiable Endogenous Retroviruses in Pythons (Python molurus and Python curtus)

    PubMed Central

    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

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

    PubMed Central

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

    2015-01-01

    This study aimed to analyze the agreement between measurements of unloaded oxygen uptake and peak oxygen uptake based on equations proposed by Wasserman and on real measurements directly obtained with the ergospirometry system. We performed an incremental cardiopulmonary exercise test (CPET), which was applied to two groups of sedentary male subjects: one apparently healthy group (HG, n=12) and the other had stable coronary artery disease (n=16). The mean age in the HG was 474 years and that in the coronary artery disease group (CG) was 578 years. Both groups performed CPET on a cycle ergometer with a ramp-type protocol at an intensity that was calculated according to the Wasserman equation. In the HG, there was no significant difference between measurements predicted by the formula and real measurements obtained in CPET in the unloaded condition. However, at peak effort, a significant difference was observed between oxygen uptake (V?O2)peak(predicted)and V?O2peak(real)(nonparametric Wilcoxon test). In the CG, there was a significant difference of 116.26 mL/min between the predicted values by the formula and the real values obtained in the unloaded condition. A significant difference in peak effort was found, where V?O2peak(real)was 40% lower than V?O2peak(predicted)(nonparametric Wilcoxon test). There was no agreement between the real and predicted measurements as analyzed by Lins coefficient or the Bland and Altman model. The Wasserman formula does not appear to be appropriate for prediction of functional capacity of volunteers. Therefore, this formula cannot precisely predict the increase in power in incremental CPET on a cycle ergometer. PMID:26397972

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

    PubMed

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

    2015-12-01

    This study aimed to analyze the agreement between measurements of unloaded oxygen uptake and peak oxygen uptake based on equations proposed by Wasserman and on real measurements directly obtained with the ergospirometry system. We performed an incremental cardiopulmonary exercise test (CPET), which was applied to two groups of sedentary male subjects: one apparently healthy group (HG, n=12) and the other had stable coronary artery disease (n=16). The mean age in the HG was 474 years and that in the coronary artery disease group (CG) was 578 years. Both groups performed CPET on a cycle ergometer with a ramp-type protocol at an intensity that was calculated according to the Wasserman equation. In the HG, there was no significant difference between measurements predicted by the formula and real measurements obtained in CPET in the unloaded condition. However, at peak effort, a significant difference was observed between oxygen uptake (V?O2)peak(predicted)and V?O2peak(real)(nonparametric Wilcoxon test). In the CG, there was a significant difference of 116.26 mL/min between the predicted values by the formula and the real values obtained in the unloaded condition. A significant difference in peak effort was found, where V?O2peak(real)was 40% lower than V?O2peak(predicted)(nonparametric Wilcoxon test). There was no agreement between the real and predicted measurements as analyzed by Lin's coefficient or the Bland and Altman model. The Wasserman formula does not appear to be appropriate for prediction of functional capacity of volunteers. Therefore, this formula cannot precisely predict the increase in power in incremental CPET on a cycle ergometer. PMID:26397972

  2. SunPy—Python for solar physics

    NASA Astrophysics Data System (ADS)

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

    2015-01-01

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

  3. The Python Interface to Antelope and Applications

    NASA Astrophysics Data System (ADS)

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

    2008-12-01

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

  4. Gist: A scientific graphics package for Python

    SciTech Connect

    Busby, L.E.

    1996-05-08

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

  5. Measuring the Length of a Captured Burmese Python

    USGS Multimedia Gallery

    Skip Snow (National Park Service) measures the length of a captured Burmese python (Python molurus) at the South Florida Research Center, Everglades National Park. Photo courtesy of Lori Oberhofer, NPS. ...

  6. 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.

  7. Python for Large-Scale Electrophysiology

    PubMed Central

    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

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

    SciTech Connect

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

    1996-04-16

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

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

    USGS Publications Warehouse

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

    2011-01-01

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

  10. THE PYTHON SHELL FOR THE ORBIT CODE

    SciTech Connect

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

    2009-01-01

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

  11. Physiology: postprandial cardiac hypertrophy in pythons.

    PubMed

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

    2005-03-01

    Oxygen consumption by carnivorous reptiles increases enormously after they have eaten a large meal in order to meet metabolic demands, and this places an extra load on the cardiovascular system. Here we show that there is an extraordinarily rapid 40% increase in ventricular muscle mass in Burmese pythons (Python molurus) a mere 48 hours after feeding, which results from increased gene expression of muscle-contractile proteins. As this fully reversible hypertrophy occurs naturally, it could provide a useful model for investigating the mechanisms that lead to cardiac growth in other animals. PMID:15744290

  12. Implanting a Radio Transmitter in a Burmese Python

    USGS Multimedia Gallery

    Researchers implant a radio transmitter in a 16-foot, 155-pound female Burmese python (Python molurus) at the South Florida Research Center, Everglades National Park. Radio-tracking builds understanding of where pythons spend their time and therefore where they can be controlled in practice. Photo c...

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

    USGS Publications Warehouse

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

    2012-01-01

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

  14. Retained caseous yolk sac in a Burmese python (Python molurus bivittatus).

    PubMed

    Bodri, M S; Hendrick, M J; O'Brien, R T; Sadanaga, K K

    1990-10-01

    Retained yolk sacs are common in the domestic chicken and account for considerable morbidity and mortality during late embryonic development and within the first 10 days of life. What is believed to be the first recorded instance of a retained caseous yolk sac and its successful surgical removal from a Burmese python (Python molurus bivittatus) is reported. The snake experienced no post-operative complications and continues to be well 16 mo following surgery. PMID:2250338

  15. A Record-Breaking Invasive Burmese Python

    USGS Multimedia Gallery

    This female Burmese python broke the records for her length - 17 feet, 7 inches -and the number of eggs she contained: 87. She was first captured in Everglades National Park by USGS researchers in the spring of 2012, when they followed a

  16. Burmese Python Caught in the Everglades

    USGS Multimedia Gallery

    This large Burmese python, weighing 162 pounds and more than 15 feet long at the time of its capture in 2009, was caught alive in the Everglades and was found to have eaten an American alligator that measured about 6 feet in length. University of Florida researchers in the photo: Michael Rochford is...

  17. A Record-Breaking Invasive Burmese Python

    USGS Multimedia Gallery

    This female Burmese python broke the records for her length - 17 feet, 7 inches - and the number of eggs she contained: 87. She was first captured in Everglades National Park by USGS researchers in the spring of 2012, when they followed a

  18. Python Scripting in the Nengo Simulator

    PubMed Central

    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

  19. A Record-Breaking Invasive Burmese Python

    USGS Multimedia Gallery

    This female Burmese python broke the records for her length - 17 feet, 7 inches - and the number of eggs she contained: 87. She was first captured in Everglades National Park by USGS researchers in the spring of 2012, when they followed a

  20. A Record-Breaking Invasive Burmese Python

    USGS Multimedia Gallery

    This female Burmese python broke the records for her length -- 17 feet, 7 inches – and the number of eggs she contained: 87. She was first captured in Everglades National Park by USGS researchers in the spring of 2012, when they followed a

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

    NASA Astrophysics Data System (ADS)

    Poore, Geoffrey M.

    2015-01-01

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

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

    PubMed Central

    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. PMID:26623196

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

    PubMed

    Falk, Bryan G; Reed, Robert N

    2015-01-01

    Molecular approaches to prey identification are increasingly useful in elucidating predator-prey relationships, and we aimed to investigate the feasibility of these methods to document the species identities of prey consumed by invasive Burmese pythons in Florida. We were particularly interested in the diet of young snakes, because visual identification of prey from this size class has proven difficult. We successfully extracted DNA from the gastrointestinal contents of 43 young pythons, as well as from several control samples, and attempted amplification of DNA mini-barcodes, a 130-bp region of COX1. Using a PNA clamp to exclude python DNA, we found that prey DNA was not present in sufficient quality for amplification of this locus in 86% of our samples. All samples from the GI tracts of young pythons contained only hair, and the six samples we were able to identify to species were hispid cotton rats. This suggests that young Burmese pythons prey predominantly on small mammals and that prey diversity among snakes of this size class is low. We discuss prolonged gastrointestinal transit times and extreme gastric breakdown as possible causes of DNA degradation that limit the success of a molecular approach to prey identification in Burmese pythons. PMID:26623196

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

    USGS Publications Warehouse

    Falk, Bryan; Reed, Robert N.

    2015-01-01

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

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

    PubMed Central

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

    2014-01-01

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

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

    USGS Publications Warehouse

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

    2012-01-01

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

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

    USGS Publications Warehouse

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

    2012-01-01

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

  8. Ventilatory and cardiovascular responses of a python (Python molurus) to exercise and digestion.

    PubMed

    Secor, S M; Hicks, J W; Bennett, A F

    2000-08-01

    To investigate the potential limiting steps of peak metabolic rates, we examined gas exchange rates ( vdot (O2), vdot (CO2)), respiratory exchange ratio (RER), breathing frequency, tidal volume, minute ventilation volume (V.e) as well as the heart rate, systemic blood flow and stroke volume of Burmese pythons (Python molurus) while fasting at rest, exercising, digesting and exercising while digesting. All measured variables increased significantly during exercise (crawling at 0.4 km h(-)(1) and at vdot (O2max)), highlighted by a 17-fold increase in vdot (CO2) and a 24-fold increase in V.e. During the digestion of a meal equivalent to 25 % of the snake's body mass, pythons responded with increases in vdot (O2) and heart rate similar to those experienced during exercise, along with a 4.5-fold increase in systemic blood flow. Interestingly, pythons hyperventilated while exercising, whereas they hypoventilated during digestion. The combined demands of exercise and digestion resulted in significantly higher vdot (O2), vdot (CO2), breathing frequency and heart rate than during either exercise or digestion alone. Evidently, the capacities of the ventilatory and cardiovascular systems to transport oxygen to locomotor muscles are not a limiting factor in the attainment of peak metabolic rates during exercise in pythons PMID:10903159

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

    PubMed

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

    2001-06-01

    Burmese pythons (Python molurus) regulate digestive performance and metabolism with the ingestion of each meal. To explore the python's postprandial responses, we monitored the concentrations of blood micronutrients and homocysteine during fasting and for 15 days after feeding. Plasma folate concentrations peaked with a 270% increase over fasting levels 3 days after feeding, whereas plasma B-12 peaked with a 66% increase within 1 day. Erythrocyte folate concentrations were highest 15 days after feeding with a 44% increase. The major plasma folate was 5-methyltetrahydrofolate during fasting and was non-5-methyltetrahydrofolate during digestion, whereas erythrocytes contained polyglutamyl forms of non-5-methyltetrahydrofolate. Plasma homocysteine concentrations peaked with a 56% increase 3 days after feeding, and were markedly greater than those of mammals. Plasma zinc and copper did not change significantly. Plasma zinc concentrations were 20 times greater than plasma copper and approximately 30 times higher than those of mammals. Pythons showed a significant postprandial decline of 25% in hematocrit. Plasma pyridoxal 5'-phosphate (coenzyme form of vitamin B-6) was not detected probably due to its tight protein binding. Most micronutrient concentrations appear to plateau 3 days after feeding, suggesting that pythons have relatively rapid homeostasis of micronutrients despite the ingestion of large meals. PMID:11423336

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

    PubMed

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

    2006-05-01

    Oleoylethanolamide (OEA) is an endogenous lipid mediator that inhibits feeding in rats and mice by activating the nuclear receptor peroxisome proliferator-activated receptor-alpha (PPAR-alpha). In rodents, intestinal OEA levels increase about threefold upon refeeding, a response that may contribute to the induction of between-meal satiety. Here, we examined whether feeding-induced OEA mobilization also occurs in Burmese pythons (Python molurus), a species of ambush-hunting snakes that consume huge meals after months of fasting and undergo massive feeding-dependent changes in gastrointestinal hormonal release and gut morphology. Using liquid chromatography/mass spectrometry (LC/MS), we measured OEA levels in the gastrointestinal tract of fasted (28 days) and fed (48 h after feeding) pythons. We observed a nearly 300-fold increase in OEA levels in the small intestine of fed compared with fasted animals (322 +/- 121 vs. 1 +/- 1 pmol/mg protein, n = 3-4). In situ OEA biosynthesis was suggested by the concomitant increase of N-acyl phosphatidylethanolamine species that serve as potential biosynthetic precursors for OEA. Furthermore, we observed a concomitant increase in saturated, mono- and diunsaturated, but not polyunsaturated fatty-acid ethanolamides (FAE) in the small intestine of fed pythons. The identification of OEA and other FAEs in the gastrointestinal tract of Python molurus suggests that this class of lipid messengers may be widespread among vertebrate groups and may represent an evolutionarily ancient means of regulating energy intake. PMID:16373434

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

    PubMed

    Cox, Christian L; Secor, Stephen M

    2008-04-01

    In Burmese pythons fasting and feeding cause dramatic regulation of gastric acid production and intestinal nutrient uptake. Predictably, other components of their gastrointestinal tract are similarly regulated with each meal. We therefore assessed the matched regulation of gastrointestinal performance by comparing the postprandial activities and capacities of gastric (pepsin), pancreatic (amylase and trypsin) and intestinal (aminopeptidase-N and maltase) enzymes, and intestinal nutrient uptake. Tissue samples were collected from pythons fasted and at 0.25, 0.5, 1, 2, 3, 4, 6, 10 and 15 days following their consumption of rodent meals equaling 25% of snake body mass. With feeding, pythons experience no significant change in stomach mass, whereas both the pancreas and small intestine doubled in mass. Feeding also triggered a depletion of gastric mucosal pepsinogen, a respective 5.7- and 20-fold increase in the peak activities of pancreatic trypsin and amylase, and a respective 2.3- and 5.5-fold increase in the peak activities of intestinal maltase and aminopeptidase-N. Enzyme activities peaked between 2 and 4 days postfeeding and returned to fasting levels by day 10. Independent of digestive stage, python intestine exhibited a proximal to distal decline in enzyme activity. For both sugars and proteins, intestinal capacities for enzyme activity were significantly correlated with nutrient uptake capacities. The concomitant postprandial upregulation of tissue morphology, intestinal nutrient transport rates and enzyme activities illustrate, for the python, the matched regulation of their gastrointestinal performance with each meal. PMID:18344488

  12. Stimfit: quantifying electrophysiological data with Python

    PubMed Central

    Guzman, Segundo J.; Schlgl, 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

  13. 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.

  14. Writing analytic element programs in Python.

    PubMed

    Bakker, Mark; Kelson, Victor A

    2009-01-01

    The analytic element method is a mesh-free approach for modeling ground water flow at both the local and the regional scale. With the advent of the Python object-oriented programming language, it has become relatively easy to write analytic element programs. In this article, an introduction is given of the basic principles of the analytic element method and of the Python programming language. A simple, yet flexible, object-oriented design is presented for analytic element codes using multiple inheritance. New types of analytic elements may be added without the need for any changes in the existing part of the code. The presented code may be used to model flow to wells (with either a specified discharge or drawdown) and streams (with a specified head). The code may be extended by any hydrogeologist with a healthy appetite for writing computer code to solve more complicated ground water flow problems. PMID:19473273

  15. 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.

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

    PubMed

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

    2011-12-01

    Osteosarcoma of the axial skeleton in an 18-month-old woma python (Aspidites ramsayi) is described. A subcutaneous mass overlying the costal arches enlarged progressively over a period of 5 months and, in that time, became ulcerated and more invasive of surrounding tissues. A punch biopsy of the lesion under general anaesthesia provided tissue for histopathology and diagnosis of low-grade osteosarcoma. PMID:22103954

  17. Py4Syn: Python for synchrotrons.

    PubMed

    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. PMID:26289269

  18. POPPY: Physical Optics Propagation in PYthon

    NASA Astrophysics Data System (ADS)

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

    2016-02-01

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

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

    PubMed

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

    2015-01-01

    Large pythons and boas comprise a group of animals whose anatomy and physiology are very different from traditional mammalian, avian and other reptilian models typically used in operant conditioning. In the current study, investigators used a modified shaping procedure involving successive approximations to train wild Burmese pythons (Python molurus bivitattus) to approach and depress an illuminated push button in order to gain access to a food reward. Results show that these large, wild snakes can be trained to accept extremely small food items, associate a stimulus with such rewards via operant conditioning and perform a contingent operant response to gain access to a food reward. The shaping procedure produced robust responses and provides a mechanism for investigating complex behavioral phenomena in massive snakes that are rarely studied in learning research. PMID:25139000

  20. Feeding a large-scale physics application to Python

    SciTech Connect

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

    1997-10-01

    The authors describe their experiences using Python with the SPaSM molecular dynamics code at Los Alamos National Laboratory. Originally developed as a large monolithic application for massive parallel processing systems, they have used Python to transform their application into a flexible, highly modular, and extremely powerful system for performing simulation, data analysis, and visualization. In addition, they describe how Python has solved a number of important problems related to the development, debugging, deployment, and maintenance of scientific software.

  1. The Virtual Observatory for the Python Programmer

    NASA Astrophysics Data System (ADS)

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

    2014-01-01

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

  2. Extensible message passing application development and debugging with Python

    SciTech Connect

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

    1996-09-19

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

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

    SciTech Connect

    Gezahegne, A; Love, N S

    2007-12-10

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

  4. 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.

  5. Improvement of AMGA Python Client Library for Belle II Experiment

    NASA Astrophysics Data System (ADS)

    Kwak, Jae-Hyuck; Park, Geunchul; Huh, Taesang; Hwang, Soonwook

    2015-12-01

    This paper describes the recent improvement of the AMGA (ARDA Metadata Grid Application) python client library for the Belle II Experiment. We were drawn to the action items related to library improvement after in-depth discussions with the developer of the Belle II distributed computing system. The improvement includes client-side metadata federation support in python, DIRAC SSL library support as well as API refinement for synchronous operation. Some of the improvements have already been applied to the AMGA python client library as bundled with the Belle II distributed computing software. The recent mass Monte- Carlo (MC) production campaign shows that the AMGA python client library is reliably stable.

  6. scikit-image: image processing in Python

    PubMed Central

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

    2014-01-01

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

  7. Gastric function and its contribution to the postprandial metabolic response of the Burmese python Python molurus.

    PubMed

    Secor, Stephen M

    2003-05-01

    The large intact prey ingested by Burmese pythons require considerable processing by the stomach before passage into the small intestine. To investigate the function and cost of gastric digestion and its contribution to postprandial metabolic response for the Burmese python, I examined the rate of gastric digestion, the postprandial profile of gastric pH and the effects of decreasing gastric workload on the metabolic cost of digestion, referred to as specific dynamic action (SDA). Ingested meal mass (equivalent to 25% of snake body mass) was reduced by 18% within 1 day postfeeding, by which time intragastric pH had decreased from 7.5 to 2. Gastric pH was maintained at 1.5 for the next 5-7 days, after which it returned to 7.5. The SDA generated by digesting an intact rat meal was reduced by 9.1%, 26.0%, 56.5% and 66.8%, respectively, when pythons were fed steak, ground rat, liquid diet or ground rat directly infused into the small intestine. The production of HCl and enzymes and other gastric functions represent an estimated 55% of the python's SDA generated from the digestion of an intact rodent meal. Additional contributors to SDA include protein synthesis (estimated 26%), gastrointestinal upregulation (estimated 5%) and the activities of the pancreas, gallbladder, liver, kidneys and intestines during digestion (estimated 14%). Operating on a 'pay before pumping' principle, pythons must expend endogenous energy in order to initiate acid production and other digestive processes before ingested nutrients can be absorbed and channeled into metabolic pathways. PMID:12682094

  8. SunPy: Solar Physics in Python

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  9. Python Program to Select HII Region Models

    NASA Astrophysics Data System (ADS)

    Miller, Clare; Lamarche, Cody; Vishwas, Amit; Stacey, Gordon J.

    2016-01-01

    HII regions are areas of singly ionized Hydrogen formed by the ionizing radiaiton of upper main sequence stars. The infrared fine-structure line emissions, particularly Oxygen, Nitrogen, and Neon, can give important information about HII regions including gas temperature and density, elemental abundances, and the effective temperature of the stars that form them. The processes involved in calculating this information from observational data are complex. Models, such as those provided in Rubin 1984 and those produced by Cloudy (Ferland et al, 2013) enable one to extract physical parameters from observational data. However, the multitude of search parameters can make sifting through models tedious. I digitized Rubin's models and wrote a Python program that is able to take observed line ratios and their uncertainties and find the Rubin or Cloudy model that best matches the observational data. By creating a Python script that is user friendly and able to quickly sort through models with a high level of accuracy, this work increases efficiency and reduces human error in matching HII region models to observational data.

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

    PubMed

    Tsuji, Yamato; Prayitno, Bambang; Suryobroto, Bambang

    2016-04-01

    We observed an encounter between a reticulated python (Python reticulatus) and a group of wild Javan lutungs (Trachypithecus auratus mauritius) at the Pangandaran Nature Reserve, West Java, Indonesia. A python (about 2 m in length) moved toward a group of lutungs in the trees. Upon seeing the python, an adult male and several adult female lutungs began to emit alarm calls. As the python approached, two adult and one sub-adult female jumped onto a branch near the python and began mobbing the python by shaking the branch. During the mobbing, other individuals in the group (including an adult lutung male) remained nearby but did not participate. The python then rolled into a ball-like shape and stopped moving, at which point the lutungs moved away. The total duration of the encounter was about 40 min, during which time the lutungs stopped feeding and grooming. Group cohesiveness during and after the encounter was greater than that before the encounter, indicating that lutungs adjust their daily activity in response to potential predation risk. PMID:26910233

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

    PubMed

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

    2007-11-01

    Osteitis deformans (Paget's disease of bone) is a chronic focal disorder of bone remodelling characterized by an initial increase in osteoclast-mediated bone resorption, with subsequent compensatory increase in new bone formation, resulting in a disorganized mosaic of woven and lamellar bone. In the Burmese python (Python molurus bivittatus) of this report, multifocal gross swellings involving the proximal third of the vertebral spine were observed and associated with anorexia, a relative inability to move or to fully extend the body, and to strike at prey. Serum biochemistry revealed elevated alkaline-phosphatase activity. Radiographic changes (irregular bone proliferation along the vertebral margins), computed tomography scan results (abnormal mineral density), and histopathological features (generalized thickening of the bony trabeculae at the expense of the intertrabecular spaces and irregular patches of lamellar bone with a characteristic "mosaic" pattern) indicated osteitis deformans. PMID:17222574

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

    PubMed

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

    2010-12-01

    An 11-yr-old Burmese python (Python molurus bivittatus) was presented with a history of respiratory symptoms. Computed tomography and an endoscopic examination of the left lung were performed and revealed severe pneumonia. Microbiologic examination of a tracheal wash sample and an endoscopy-guided sample from the lung confirmed infection with Salmonella enterica ssp. IV, Enterobacter cloacae, and Klebsiella pneumoniae. Computed tomographic examination demonstrated a hyperattenuated structure within the heart. Echocardiographic examination revealed a hyperechoic mass at the pulmonic valve as well as a dilated truncus pulmonalis. As therapy for pneumonia was ineffective, the snake was euthanized. Postmortem examination confirmed pneumonia and infective endocarditis of the pulmonic valve caused by septicemia with Salmonella enterica ssp. IV. Focal arteriosclerosis of the pulmonary trunk was also diagnosed. The case presented here demonstrates the possible connection between respiratory and cardiovascular diseases in snakes. PMID:21370657

  13. An Extensible Python User Environment for Subsurface Modeling

    NASA Astrophysics Data System (ADS)

    Daily, J. A.

    2008-12-01

    We use the Python programming language to collect, organize, and present the multitude of data and provenance associated with running scientific application codes. Without a user environment, the inputs, outputs, analyses, and executables are muddled by arcane directory hierarchies, file names, and symbolic links. Our user environment emulates the ad hoc ways of the scientific application user while hiding the addling details of where files should go, which machines can run which application codes, and what steps it took to create their application study. We use the wxPython GUI toolkit to create a cross-platform GUI application that focuses on the task-oriented analysis process using a richly interactive graph as its main interface. Navigating the graph, users setup and launch their registered scientific applications and watch as the graph reacts in real-time to users' input and the output of their running processes. These processes reflect steps a user regularly takes and uses the tools and programs they are familiar with thanks to Python and wxPython's auto-discovery of system tools for file types, the extensibility of our registry for new or platform-dependent file types and installed tools, and the expressiveness and readability of the python language and the wxPython GUI toolkit. It is our interactive process graph and the seamless integration of user-familiar tools that makes our environment a novel example of Python for furthering and easing the use of scientific application codes.

  14. DMTCP: bringing interactive checkpoint-restart to Python

    NASA Astrophysics Data System (ADS)

    Arya, Kapil; Cooperman, Gene

    2015-01-01

    DMTCP (Distributed MultiThreaded CheckPointing) is a mature checkpoint-restart package. It operates in user space without kernel privilege, and adapts to application-specific requirements through plugins. While DMTCP has been able to checkpoint Python and IPython ‘from the outside’ for many years, a Python module has recently been created to support DMTCP. IPython support is included through a new DMTCP plugin. A checkpoint can be requested interactively within a Python session or under the control of a specific Python program. Further, the Python program can execute specific Python code prior to checkpoint, upon resuming (within the original process) and upon restarting (from a checkpoint image). Applications of DMTCP are demonstrated for: (i) Python-based graphics using virtual network client, (ii) a fast/slow technique to use multiple hosts or cores to check one (Cython Behnel S et al 2011 Comput. Sci. Eng. 13 31-39) computation in parallel, and (iii) a reversible debugger, FReD, with a novel reverse-expression watchpoint feature for locating the cause of a bug.

  15. PyMOOSE: Interoperable Scripting in Python for MOOSE

    PubMed Central

    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

  16. Responses of python gastrointestinal regulatory peptides to feeding.

    PubMed

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

    2001-11-20

    In the Burmese python (Python molurus), the rapid up-regulation of gastrointestinal (GI) function and morphology after feeding, and subsequent down-regulation on completing digestion, are expected to be mediated by GI hormones and neuropeptides. Hence, we examined postfeeding changes in plasma and tissue concentrations of 11 GI hormones and neuropeptides in the python. Circulating levels of cholecystokinin (CCK), glucose-dependent insulinotropic peptide (GIP), glucagon, and neurotensin increase by respective factors of 25-, 6-, 6-, and 3.3-fold within 24 h after feeding. In digesting pythons, the regulatory peptides neurotensin, somatostatin, motilin, and vasoactive intestinal peptide occur largely in the stomach, GIP and glucagon in the pancreas, and CCK and substance P in the small intestine. Tissue concentrations of CCK, GIP, and neurotensin decline with feeding. Tissue distributions and molecular forms (as determined by gel-permeation chromatography) of many python GI peptides are similar or identical to those of their mammalian counterparts. The postfeeding release of GI peptides from tissues, and their concurrent rise in plasma concentrations, suggests that they play a role in regulating python-digestive responses. These large postfeeding responses, and similarities of peptide structure with mammals, make pythons an attractive model for studying GI peptides. PMID:11707600

  17. Facultative thermogenesis during brooding is not the norm among pythons.

    PubMed

    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 (31.5C) and a sub-optimal temperature (25.5C)-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. PMID:26113382

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

    PubMed

    Lignot, Jean-Herv; Helmstetter, Ccile; Secor, Stephen M

    2005-07-01

    The postprandial morphological changes of the intestinal epithelium of Burmese pythons were examined using fasting pythons and at eight time points after feeding. In fasting pythons, tightly packed enterocytes possess very short microvilli and are arranged in a pseudostratified fashion. Enterocyte width increases by 23% within 24 h postfeeding, inducing significant increases in villus length and intestinal mass. By 6 days postfeeding, enterocyte volume had peaked, following as much as an 80% increase. Contributing to enterocyte hypertrophy is the cellular accumulation of lipid droplets at the tips and edges of the villi of the proximal and middle small intestine, but which were absent in the distal small intestine. At 3 days postfeeding, conventional and environmental scanning electron microscopy revealed cracks and lipid extrusion along the narrow edges of the villi and at the villus tips. Transmission electron microscopy demonstrated the rapid postprandial lengthening of enterocyte microvilli, increasing 4.8-fold in length within 24 h, and the maintaining of that length through digestion. Beginning at 24 h postfeeding, spherical particles were found embedded apically within enterocytes of the proximal and middle small intestine. These particles possessed an annular-like construction and were stained with the calcium-stain Alizarine red S suggesting that they were bone in origin. Following the completion of digestion, many of the postprandial responses were reversed, as observed by the atrophy of enterocytes, the shortening of villi, and the retraction of the microvilli. Further exploration of the python intestine will reveal the underlying mechanisms of these trophic responses and the origin and fate of the engulfed particles. PMID:16002308

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

    PubMed

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

    2014-05-15

    Physiological cardiac hypertrophy is characterized by reversible enlargement of cardiomyocytes and changes in chamber architecture, which increase stroke volume and via augmented convective oxygen transport. Cardiac hypertrophy is known to occur in response to repeated elevations of O2 demand and/or reduced O2 supply in several species of vertebrate ectotherms, including postprandial Burmese pythons (Python bivittatus). Recent data suggest postprandial cardiac hypertrophy in P. bivittatus is a facultative rather than obligatory response to digestion, though the triggers of this response are unknown. Here, we hypothesized that an O2 supply-demand mismatch stimulates postprandial cardiac enlargement in Burmese pythons. To test this hypothesis, we rendered animals anemic prior to feeding, essentially halving blood oxygen content during the postprandial period. Fed anemic animals had heart rates 126% higher than those of fasted controls, which, coupled with a 71% increase in mean arterial pressure, suggests fed anemic animals were experiencing significantly elevated cardiac work. We found significant cardiac hypertrophy in fed anemic animals, which exhibited ventricles 39% larger than those of fasted controls and 28% larger than in fed controls. These findings support our hypothesis that those animals with a greater magnitude of O2 supply-demand mismatch exhibit the largest hearts. The 'low O2 signal' stimulating postprandial cardiac hypertrophy is likely mediated by elevated ventricular wall stress associated with postprandial hemodynamics. PMID:24311803

  20. Using Python for Climate Model Intercomparison

    NASA Astrophysics Data System (ADS)

    Caldwell, P.

    2012-12-01

    With the success of CMIP3, model intercomparison projects have become a core methodology for climate research. The nature of these projects requires users to sort through and download massive datasets, to work with arrays too large to fit into memory, and to handle a profusion of grids and other model-specific information in a flexible way. In this talk I will provide a climate scientist's perspective on using python to overcome these problems. I will share my experiences with server-side data reduction, automating data downloads, minimizing memory usage, parallel data processing, comparing and plotting data on differing (and perhaps irregular) grids, and using compiled (fortran) code to remove bottlenecks. Where possible, solution approaches will be illustrated with simple example code. Prepared by LLNL under Contract DE-AC52-07NA27344.

  1. 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.

  2. drive-casa: Python interface for CASA scripting

    NASA Astrophysics Data System (ADS)

    Staley, Tim D.

    2015-04-01

    drive-casa provides a Python interface for scripting of CASA (ascl.net/1107.013) subroutines from a separate Python process, allowing for utilization alongside other Python packages which may not easily be installed into the CASA environment. This is particularly useful for embedding use of CASA subroutines within a larger pipeline. drive-casa runs plain-text casapy scripts directly; alternatively, the package includes a set of convenience routines which try to adhere to a consistent style and make it easy to chain together successive CASA reduction commands to generate a command-script programmatically.

  3. galpy: A python Library for Galactic Dynamics

    NASA Astrophysics Data System (ADS)

    Bovy, Jo

    2015-02-01

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

  4. galpy: A python LIBRARY FOR GALACTIC DYNAMICS

    SciTech Connect

    Bovy, Jo

    2015-02-01

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

  5. Neutron Scattering Experiment Automation with Python

    SciTech Connect

    Zolnierczuk, Piotr A; Riedel, Richard A

    2010-01-01

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

  6. PyMC: Bayesian Stochastic Modelling in Python

    PubMed Central

    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

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

    NASA Astrophysics Data System (ADS)

    Sanchez, David; Deil, Christoph

    2015-01-01

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

  8. Rapid Development of Interferometric Software Using MIRIAD and Python

    NASA Astrophysics Data System (ADS)

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

    2012-06-01

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

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

    PubMed

    Gramfort, Alexandre; Luessi, Martin; Larson, Eric; Engemann, Denis A; Strohmeier, Daniel; Brodbeck, Christian; Goj, Roman; Jas, Mainak; Brooks, Teon; Parkkonen, Lauri; Hmlinen, 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. PMID:24431986

  10. MEG and EEG data analysis with MNE-Python

    PubMed Central

    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

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

    PubMed

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

    2012-09-01

    An invasive population of Burmese pythons (Python molurus bivittatus) is established across several thousand square kilometers of southern Florida and appears to have caused precipitous population declines among several species of native mammals. Why has this giant snake had such great success as an invasive species when many established reptiles have failed to spread? We scored the Burmese python for each of 15 literature-based attributes relative to predefined comparison groups from a diverse range of taxa and provide a review of the natural history and ecology of Burmese pythons relevant to each attribute. We focused on attributes linked to spread and magnitude of impacts rather than establishment success. Our results suggest that attributes related to body size and generalism appeared to be particularly applicable to the Burmese python's success in Florida. The attributes with the highest scores were: high reproductive potential, low vulnerability to predation, large adult body size, large offspring size and high dietary breadth. However, attributes of ectotherms in general and pythons in particular (including predatory mode, energetic efficiency and social interactions) might have also contributed to invasion success. Although establishment risk assessments are an important initial step in prevention of new establishments, evaluating species in terms of their potential for spreading widely and negatively impacting ecosystems might become part of the means by which resource managers prioritize control efforts in environments with large numbers of introduced species. PMID:22938523

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

    USGS Publications Warehouse

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

    2012-01-01

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

  13. 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 Australia. Workflow of MT data processing. Within the structural diagram, the MTpy sub-packages are shown in red (time series data processing), green (handling of EDI files and impedance tensor data), yellow (connection to modelling/inversion algorithms), black (impedance tensor interpretation, e.g. by Phase Tensor calculations), and blue (generation of visual representations, e.g pseudo sections or resistivity models).

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

    PubMed

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

    2009-09-01

    The morphology of the digestive system in fasting and refed Burmese pythons was determined, as well as the localization of the proton (H(+), K(+)-ATPase) and sodium (Na(+), K(+)-ATPase) pumps. In fasting pythons, oxyntopeptic cells located within the fundic glands are typically non-active, with a thick apical tubulovesicular system and numerous zymogen granules. They become active Immediately after feeding but return to a non-active state 3 days after the Ingestion of the prey. The proton pump, expressed throughout the different fasting/feeding states, is either sequestered in the tubulovesicular system in non-active cells or located along the apical digitations extending within the crypt lumen in active cells. The sodium pump is rapidly upregulated in fed animals and is classically located along the baso-lateral membranes of the gastric oxyntopeptic cells. In the Intestine, it is only expressed along the lateral membranes of the enterocytes, i.e., above the lateral spaces and not along the basal side of the cells. Thus, solute transport within the Intestinal lining is mainly achieved through the apical part of the cells and across the lateral spaces while absorbed fat massively crosses the entire height of the cells and flows into the Intercellular spaces. Therefore, in the Burmese python, the gastrointestinal cellular system quickly upregulates after feeding, due to Inexpensive cellular changes, passive mechanisms, and the progressive activation and synthesis of key enzymes such as the sodium pump. This cell plasticity also allows anticipation of the next fasting and feeding periods. PMID:19799514

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

    PubMed

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

    2015-10-01

    Burmese pythons are sit-and-wait predators that are well adapted to go long periods without food, yet subsequently consume and digest single meals that can exceed their body weight. These large feeding events result in a dramatic alkaline tide that is compensated by a hypoventilatory response that normalizes plasma pH; however, little is known regarding how plasma HCO3(-) is lowered in the days post-feeding. The current study demonstrated that Burmese pythons contain the cellular machinery for renal acid-base compensation and actively remodel the kidney to limit HCO3(-) reabsorption in the post-feeding period. After being fed a 25% body weight meal plasma total CO2 was elevated by 1.5-fold after 1 day, but returned to control concentrations by 4 days post-feeding (d pf). Gene expression analysis was used to verify the presence of carbonic anhydrase (CA) II, IV and XIII, Na(+) H(+) exchanger 3 (NHE3), the Na(+) HCO3(-) co-transporter (NBC) and V-type ATPase. CA IV expression was significantly down-regulated at 3 dpf versus fasted controls. This was supported by activity analysis that showed a significant decrease in the amount of GPI-linked CA activity in isolated kidney membranes at 3 dpf versus fasted controls. In addition, V-type ATPase activity was significantly up-regulated at 3 dpf; no change in gene expression was observed. Both CA II and NHE3 expression was up-regulated at 3 dpf, which may be related to post-prandial ion balance. These results suggest that Burmese pythons actively remodel their kidney after feeding, which would in part benefit renal HCO3(-) clearance. PMID:26123779

  16. Intracardiac flow separation in an in situ perfused heart from Burmese python Python molurus.

    PubMed

    Wang, Tobias; Altimiras, Jordi; Axelsson, Michael

    2002-09-01

    The heart of non-crocodilian reptiles has two separate atria that receive blood from the systemic and pulmonary circulations. The ventricle is not fully divided, but is compartmentalised into two chambers (cavum dorsale and cavum pulmonale) by a muscular ridge that runs from the apex to the base of the ventricle. The muscular ridge is small in turtles, but is well developed in varanid lizards and many species of snakes. These anatomical differences correlate with an effective blood flow separation in varanid lizards, whereas turtles can exhibit very large cardiac shunts. Very little is known about the cardiac shunt patterns in other groups of reptiles. Here we characterise cardiac performance and flow dynamics in the Burmese python (Python molurus) using an in situ perfused heart preparation. The pericardium remained intact and the two atria were perfused separately (Ringer solution), and the two systemic and the pulmonary outflows were independently cannulated. Right and left atrial filling pressures and ventricular outflow pressures of the pulmonary and systemic vessels could be manipulated independently, permitting the establishment of large experimental intraventricular pressure gradients across the muscular ridge. The maximal power output generated by the systemic side of the ventricle exceeded the maximal power output that was generated by the cavum pulmonale that perfuse the pulmonary circulation. Furthermore, systemic flow could be generated against a higher outflow pressure than pulmonary flow. Perfusate entering the right atrium was preferentially distributed into the pulmonary circulation, whereas perfusate into the left atrium was distributed to the systemic circulation. Our study indicates that the well-developed muscular ridge can separate the cavum systemic and pulmonary sides of the heart to prevent mixing of systemic and pulmonary flows. Therefore, the heart of Python appears to exhibit a large degree of ventricular flow separation as previously described for varanid lizards. We speculate that the ventricular separation has evolved in response to the need of maintaining high oxygen delivery while protecting the pulmonary circulation from oedema as result of high vascular pressures. PMID:12151377

  17. 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 equivalent to flow.get_year('2010').get_season('summer') Retrieve only the data of July and get the peak values above the 95 percentile: flow.get_season('july').get_highpeaks(above_percentile=0.95) Retrieve only the data between two specified days and selecting only the rising limbs flow.get_date_range('01/10/2008', '15/2/2014').get_climbing() Calculate the annual sum and make a plot of it: flow.frequency_resample('A', 'sum').plot()

  18. Tachykinins (substance P, neurokinin A and neuropeptide gamma) and neurotensin from the intestine of the Burmese python, Python molurus.

    PubMed

    Conlon, J M; Adrian, T E; Secor, S M

    1997-01-01

    Peptides with substance P-like immunoreactivity, neurokinin A-like immunoreactivity and neurotensin-like immunoreactivity were isolated in pure form from an extract of the intestine of the Burmese python (Python molurus). The primary structure of python substance P (Arg-Pro-Arg-Pro-Gln-Gln-Phe-Tyr-Gly-Leu- Met-NH2) shows one amino acid substitution (Phe8-->Tyr) compared with chicken/alligator substance P and an additional substitution (Lys3-->Arg) as compared with mammalian substance P. The neurokinin A-like immunoreactivity was separated into two components. Python neuropeptide gamma (Asp-Ala-Gly-Tyr- Ser-Pro-Leu-Ser-His-Lys-Arg-His-Lys-Thr-Asp-Ser-Phe-Val-Gly-Leu-Met-NH2 shows three substitutions (Gly5-->Ser, Gln6-->Pro and Ile7-->Leu) compared with alligator neuropeptide gamma and an additional substitution (His4-->Tyr) compared with mammalian neuropeptide gamma. Python neurokinin A (His-Lys-Thr-Asp-Ser-Phe-Val-Gly- Leu-Met.NH2) is identical to human/chicken/alligator neurokinin A. Python neurotensin (pGlu-Leu-Val-His-Asn-Lys-Ala-Arg-Pro-Tyr-Ile-Leu) is identical to chicken/alligator neurotensin. The data are indicative of differential evolutionary pressure to conserve the amino acid sequences of reptilian gastrointestinal peptides. PMID:9437709

  19. Python algorithms in particle tracking microrheology

    PubMed Central

    2012-01-01

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

  20. AJAC: Atomic data calculation tool in Python

    NASA Astrophysics Data System (ADS)

    Amani, Tahat; Jordi, Marti; Kaher, Tahat; Ali, Khwaldeh

    2013-04-01

    In this work, new features and extensions of a currently used online atomic database management system are reported. A multiplatform flexible computation package is added to the present system, to allow the calculation of various atomic radiative and collisional processes, based on simplifying the use of some existing atomic codes adopted from the literature. The interaction between users and data is facilitated by a rather extensive Python graphical user interface working online and could be installed in personal computers of different classes. In particular, this study gives an overview of the use of one model of the package models (i.e., electron impact collisional excitation model). The accuracy of computing capability of the electron impact collisional excitation in the adopted model, which follows the distorted wave approximation approach, is enhanced by implementing the Dirac R-matrix approximation approach. The validity and utility of this approach are presented through a comparison of the current computed results with earlier available theoretical and experimental results. Finally, the source code is made available under the general public license and being distributed freely in the hope that it will be useful to a wide community of laboratory and astrophysical plasma diagnostics.

  1. Bioinformatic pipelines in Python with Leaf

    PubMed Central

    2013-01-01

    Background An incremental, loosely planned development approach is often used in bioinformatic studies when dealing with custom data analysis in a rapidly changing environment. Unfortunately, the lack of a rigorous software structuring can undermine the maintainability, communicability and replicability of the process. To ameliorate this problem we propose the Leaf system, the aim of which is to seamlessly introduce the pipeline formality on top of a dynamical development process with minimum overhead for the programmer, thus providing a simple layer of software structuring. Results Leaf includes a formal language for the definition of pipelines with code that can be transparently inserted into the users 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

  2. MTpy: A Python toolbox for magnetotellurics

    NASA Astrophysics Data System (ADS)

    Krieger, Lars; Peacock, Jared R.

    2014-11-01

    We present the software package MTpy that allows handling, processing, and imaging of magnetotelluric (MT) data sets. Written in Python, the code is open source, containing sub-packages and modules for various tasks within the standard MT data processing and handling scheme. Besides the independent definition of classes and functions, MTpy provides wrappers and convenience scripts to call standard external data processing and modelling software. In its current state, modules and functions of MTpy work on raw and pre-processed MT data. However, opposite to providing a static compilation of software, we prefer to introduce MTpy as a flexible software toolbox, whose contents can be combined and utilised according to the respective needs of the user. Just as the overall functionality of a mechanical toolbox can be extended by adding new tools, MTpy is a flexible framework, which will be dynamically extended in the future. Furthermore, it can help to unify and extend existing codes and algorithms within the (academic) MT community. In this paper, we introduce the structure and concept of MTpy. Additionally, we show some examples from an everyday work-flow of MT data processing: the generation of standard EDI data files from raw electric (E-) and magnetic flux density (B-) field time series as input, the conversion into MiniSEED data format, as well as the generation of a graphical data representation in the form of a Phase Tensor pseudosection.

  3. PsychoPyPsychophysics software in Python

    PubMed Central

    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

  4. 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.

  5. Septicaemia secondary to infection by Corynebacterium macginleyi in an Indian python (Python molurus).

    PubMed

    Martnez, Jorge; Segura, Pablo; Garca, David; Aduriz, Gorka; Ibabe, Jos 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. PMID:15996494

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

    PubMed

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

    2005-01-01

    We quantified the specific dynamic action (SDA) resulting from the ingestion of various meal types in Burmese pythons (Python molurus) at 30 degrees C. Each snake was fed a series of experimental meals consisting of amino acid mixtures, simple proteins, simple or complex carbohydrates, or lipids as well as meals of whole animal tissue (chicken breast, beef suet, and mouse). Rates of oxygen consumption were measured for approximately 4 d after feeding, and the increment above standard metabolic rate was determined and compared to energy content of the meals. While food type (protein, carbohydrate, and lipid) had a general influence, SDA was highly dependent on meal composition (i.e., amino acid composition and carbohydrate structure). For chicken breast and simple carbohydrates, the SDA coefficient was approximately one-third the energetic content of the meal. Lard, suet, cellulose, and starch were not digested and did not produce measurable SDA. We conclude that the cost of de novo protein synthesis is an important component of SDA after ingestion of protein meals because (1) simple proteins, such as gelatin and collagen, did not stimulate levels of SDA attained after consumption of complete protein, (2) incomplete mixtures of amino acids failed to elicit the SDA of a complete mixture, and (3) the inhibition of de novo protein synthesis with the drug cycloheximide caused a more than 70% decrease in SDA. Stomach distension and mechanical digestion of intact prey did not cause measurable SDA. PMID:15778938

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

    PubMed

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

    1997-08-29

    Insulin was purified from an extract of the pancreas of the Burmese python, Python molurus (Squamata:Serpentes) and its primary structure established as: A Chain: Gly-Ile-Val-Glu-Gln-Cys-Cys-Glu-Asn-Thr10-Cys-Ser-Leu-Tyr-Glu-Leu- Glu-Asn-Tyr-Cys20-Asn. B-Chain: Ala-Pro-Asn-Gln-His-Leu-Cys-Gly-Ser-His10-Leu-Val-Glu-Ala-Leu-Tyr- Leu-Val-Cys-Gly20-Asp-Arg-Gly-Phe-Tyr-Tyr-Ser-Pro-Arg-Ser30. With the exception of the conservative substitution Phe --> Tyr at position B25, those residues in human insulin that comprise the receptor-binding and those residues involved in dimer and hexamer formation are fully conserved in python insulin. Python insulin was slightly more potent (1.8-fold) than human insulin in inhibiting the binding of [125I-Tyr-A14] insulin to the soluble full-length recombinant human insulin receptor but was slightly less potent (1.5-fold) than human insulin for inhibiting binding to the secreted extracellular domain of the receptor. The primary structure of python glucagon contains only one amino acid substitution (Ser28 --> Asn) compared with turtle/duck glucagon and python somatostatin is identical to that of mammalian somatostatin-14. In contrast, python pancreatic polypeptide (Arg-Ile-Ala-Pro-Val-Phe-Pro-Gly-Lys-Asp10-Glu-Leu-Ala-Lys-Phe- Tyr20-Thr-Glu-Leu-Gln-Gln-Tyr-Leu-Asn-Ser-Ile30-Asn-Arg-Pro-Arg -Phe.NH2) contains only 35 instead of the customary 36 residues and the amino acid sequence of this peptide has been poorly conserved between reptiles and birds (18 substitutions compared with alligator and 20 substitutions compared with chicken). PMID:9350978

  8. Synthetic seismogram web service and Python tools

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

  9. A Python interface with Narcisse graphics

    SciTech Connect

    Motteler, Z.C.

    1996-04-15

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

  10. pyam: Python Implementation of YaM

    NASA Technical Reports Server (NTRS)

    Myint, Steven; Jain, Abhinandan

    2012-01-01

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

  11. Effects of meal size, clutch, and metabolism on the energy efficiencies of juvenile Burmese pythons, Python molurus.

    PubMed

    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. PMID:17913527

  12. Adaptive regulation of digestive performance in the genus Python.

    PubMed

    Ott, Brian D; Secor, Stephen M

    2007-01-01

    The adaptive interplay between feeding habits and digestive physiology is demonstrated by the Burmese python, which in response to feeding infrequently has evolved the capacity to widely regulate gastrointestinal performance with feeding and fasting. To explore the generality of this physiological trait among pythons, we compared the postprandial responses of metabolism and both intestinal morphology and function among five members of the genus Python: P. brongersmai, P. molurus, P. regius, P. reticulatus and P. sebae. These infrequently feeding pythons inhabit Africa, southeast Asia and Indonesia and vary in body shape from short and stout (P. brongersmai) to long and slender (P. reticulatus). Following the consumption of rodent meals equaling 25% of snake body mass, metabolic rates of pythons peaked at 1.5 days at levels 9.9- to 14.5-fold of standard metabolic rates before returning to prefeeding rates by day 6-8. Specific dynamic action of these meals (317-347 kJ) did not differ among species and equaled 23-27% of the ingested energy. For each species, feeding triggered significant upregulation of intestinal nutrient transport and aminopeptidase-N activity. Concurrently, intestinal mass doubled on average for the five species, in part due to an 85% increase in mucosal thickness, itself a product of 27-59% increases in enterocyte volume. The integrative response of intestinal functional upregulation and tissue hypertrophy enables each of these five python species, regardless of body shape, to modulate intestinal performance to meet the demands of their large infrequent meals. PMID:17210969

  13. A parvovirus isolated from royal python (Python regius) is a member of the genus Dependovirus.

    PubMed

    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. PMID:14993638

  14. Determinants of the postfeeding metabolic response of Burmese pythons, Python molurus.

    PubMed

    Secor, S M; Diamond, J

    1997-01-01

    The relatively large meal sizes consumed by sit-and-wait-foraging snake species make them favorable for investigating specific dynamic action, the rise in metabolic rate associated with digestion. Hence, we measured O2 consumption rates (VO2) before and up to 20 d after Burmese pythons (Python molurus) either had only constricted and killed rodent meals or had also been allowed to consume meals ranging in size from 5% to 111% of their body mass. Postprandial VO2 peaked within 2 d at a value that increased with meal size, up to 44 times standard metabolic rate for the largest meals. In addition to being the largest known magnitude of postprandial metabolic response, this also exceeds the factorial increase in VO2 during peak physical activity for all studied animals except perhaps racehorses. Specific dynamic action, calculated from the extra VO2 above standard metabolic rate over the duration of digestion, increased with meal size and equaled 32% of ingested meal energy. The allometric exponent for body mass was 0.68 for standard metabolic rate, 0.90 for peak postprandial VO2, and 1.01 for specific dynamic action. Specific dynamic action is higher, and standard metabolic rate is lower, in sit-and-wait-foraging snake species than in actively foraging snake species. This suggests that sit-and-wait-foraging snakes, which consume large meals at long and unpredictable intervals, reduce standard metabolic rate by allowing the energetically expensive small intestine and other associated organs to atrophy between meals but thereby incur a large specific dynamic action while rebuilding those organs upon feeding. PMID:9231393

  15. Effects of meal size on postprandial responses in juvenile Burmese pythons (Python molurus).

    PubMed

    Secor, S M; Diamond, J

    1997-03-01

    Pythons were reported previously to exhibit large changes in intestinal mass and transporter activities on consuming meals equal to 25% of the snake's body mass. This paper examines how those and other adaptive responses to feeding vary with meal size (5, 25, or 65% of body mass). Larger meals took longer to pass through the stomach and small intestine. After ingestion of a meal, O2 consumption rates rose to up to 32 times fasting levels and remained significantly elevated for up to 13 days. This specific dynamic action equaled 29-36% of ingested energy. After 25 and 65% size meals, plasma Cl- significantly dropped, whereas plasma CO2, glucose, creatinine, and urea nitrogen increased as much as a factor of 2.3-4.2. Within 1 day the intestinal mucosal mass more than doubled, and masses of the intestinal serosa, liver, stomach, pancreas, and kidneys also increased. Intestinal uptake rates of amino acids and of D-glucose increased by up to 43 times fasting levels, whereas uptake capacities increased by up to 59 times fasting levels. Magnitudes of many of these responses (O2 consumption rate, kidney hypertrophy, and D-glucose and L-lysine uptake) increased with meal size up to the largest meals studied; other responses (Na+-independent L-leucine uptake, plasma Cl-, and organ masses) plateaued at meals equal to 25% of the snake's body mass; and still other responses (nutrient uptake at day 1, passive glucose uptake, and plasma protein and alkaline phosphatase) were all-or-nothing, being independent of meal size between 5 and 65% of body mass. Pythons undergo a wide array of postprandial responses, many of which differ in their sensitivity to meal size. PMID:9087654

  16. A Python-Based IRAF Regression Testing System

    NASA Astrophysics Data System (ADS)

    Bushouse, H.; Simon, B.; Shukla, H.; Wyckoff, E.

    We have developed a Python-based regression testing system for tasks that run within the IRAF environment. The system uses XML format configuration files to control test instances for each task. The configuration file specifies the task to be tested, the IRAF parameter file to use with the task, as well as the names and types of output files to be compared upon task completion. Python methods are used to perform the file comparisons, including comparisons of ASCII, binary, and FITS files. Tasks can be tested individually or an entire directory tree can be traversed, running tests for all configuration files that are found.

  17. Exomerge user's manual : a lightweight Python interface for manipulating Exodus files.

    SciTech Connect

    Kostka, Timothy D.

    2013-01-01

    Exomerge is a lightweight Python module for reading, manipulating and writing data within ExodusII files. It is built upon a Python wrapper around the ExodusII API functions. This module, the Python wrapper, and the ExodusII libraries are available as part of the standard SIERRA installation.

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

    PubMed

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

    2015-11-01

    Snakes are important predators that have radiated throughout many ecosystems, and constriction was important in their radiation. Constrictors immobilize and kill prey by using body loops to exert pressure on their prey. Despite its importance, little is known about constriction performance or its full effects on prey. We studied the scaling of constriction performance in two species of giant pythons (Python reticulatus and Python molurus bivittatus) and propose a new mechanism of prey death by constriction. In both species, peak constriction pressure increased significantly with snake diameter. These and other constrictors can exert pressures dramatically higher than their prey's blood pressure, suggesting that constriction can stop circulatory function and perhaps kill prey rapidly by over-pressurizing the brain and disrupting neural function. We propose the latter 'red-out effect' as another possible mechanism of prey death from constriction. These effects may be important to recognize and treat properly in rare cases when constrictors injure humans. PMID:26347553

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

    USGS Publications Warehouse

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

    2012-01-01

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

  20. A novel Mycoplasma sp. associated with proliferative tracheitis and pneumonia in a Burmese python (Python molurus bivittatus).

    PubMed

    Penner, J D; Jacobson, E R; Brown, D R; Adams, H P; Besch-Williford, C L

    1997-10-01

    Proliferative lymphocytic tracheitis and pneumonia were observed histologically in the respiratory tract of a captive Burmese python (Python molurus bivittatus). A mycoplasma species was isolated from the respiratory tissue. Polymerase chain reaction analysis of the 16S rRNA gene sequence of the isolate showed 0.90 similarity to Mycoplasma agassizii, an organism previously shown to cause respiratory disease in reptiles. Based on these findings, a novel Mycoplasma species was suspected to be the causative agent of respiratory disease in this snake. PMID:9447490

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

    PubMed

    Schilliger, Lionel; Trhiou-Sechi, Emilie; Petit, Amandine M P; Misbach, Charlotte; Chetboul, Valrie

    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. PMID:21370663

  2. PyKrige: Development of a Kriging Toolkit for Python

    NASA Astrophysics Data System (ADS)

    Murphy, B. S.

    2014-12-01

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

  3. 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.

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

    NASA Astrophysics Data System (ADS)

    Altay, G.; Wise, J. H.

    2015-04-01

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

  5. PyTrilinos : a parallel python interface to Trilinos.

    SciTech Connect

    Spotz, William F.

    2006-02-01

    PyTrilinos provides python access to selected Trilinos packages: emerging from early stages, portability, completeness; parallelism; rapid prototyping; application development; unit testing; and numeric compatibility (migrating to NumPy). PyTrilinos complements and supplements the SciPy package.

  6. 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.

  7. pyGadgetReader: GADGET snapshot reader for python

    NASA Astrophysics Data System (ADS)

    Thompson, Robert

    2014-11-01

    pyGadgetReader is a universal GADGET snapshot reader for python that supports type-1, type-2, HDF5, and TIPSY (ascl:1111.015) binary formats. It additionally supports reading binary outputs from FoF_Special, P-StarGroupFinder, Rockstar (ascl:1210.008), and Rockstar-Galaxies.

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

    PubMed

    Jurica, Peter; van Leeuwen, Cees

    2009-01-01

    Free access to scientific information facilitates scientific progress. Open-access scientific journals are a first step in this direction; a further step is to make auxiliary and supplementary materials that accompany scientific publications, such as methodological procedures and data-analysis tools, open and accessible to the scientific community. To this purpose it is instrumental to establish a software base, which will grow toward a comprehensive free and open-source language of technical and scientific computing. Endeavors in this direction are met with an important obstacle. MATLAB((R)), the predominant computation tool in many fields of research, is a closed-source commercial product. To facilitate the transition to an open computation platform, we propose Open-source MATLAB((R))-to-Python Compiler (OMPC), a platform that uses syntax adaptation and emulation to allow transparent import of existing MATLAB((R)) functions into Python programs. The imported MATLAB((R)) modules will run independently of MATLAB((R)), relying on Python's numerical and scientific libraries. Python offers a stable and mature open source platform that, in many respects, surpasses commonly used, expensive commercial closed source packages. The proposed software will therefore facilitate the transparent transition towards a free and general open-source lingua franca for scientific computation, while enabling access to the existing methods and algorithms of technical computing already available in MATLAB((R)). OMPC is available at http://ompc.juricap.com. PMID:19225577

  9. SunPy: Python for Solar Physics Data Analysis

    NASA Astrophysics Data System (ADS)

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

    2012-05-01

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

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

    PubMed

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

    2015-10-01

    In the last years Python has gained more and more traction in the scientific community. Projects like NumPy, SciPy, and Matplotlib have created a strong foundation for scientific computing in Python and machine learning packages like scikit-learn or packages for data analysis like Pandas are building on top of it. In this paper we present Wyrm ( https://github.com/bbci/wyrm ), an open source BCI toolbox in Python. Wyrm is applicable to a broad range of neuroscientific problems. It can be used as a toolbox for analysis and visualization of neurophysiological data and in real-time settings, like an online BCI application. In order to prevent software defects, Wyrm makes extensive use of unit testing. We will explain the key aspects of Wyrm's software architecture and design decisions for its data structure, and demonstrate and validate the use of our toolbox by presenting our approach to the classification tasks of two different data sets from the BCI Competition III. Furthermore, we will give a brief analysis of the data sets using our toolbox, and demonstrate how we implemented an online experiment using Wyrm. With Wyrm we add the final piece to our ongoing effort to provide a complete, free and open source BCI system in Python. PMID:26001643

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

    USGS Publications Warehouse

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

    2011-01-01

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

  12. 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 illustrate this approach with several case studies in groundwater hydrology and geochemistry and provide links to several python libraries that facilitate pre- and post-processing operations.

  13. 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

  14. Postprandial remodeling of the gut microbiota in Burmese pythons

    PubMed Central

    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

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

    PubMed

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

    2010-11-01

    The vertebrate gut microbiota evolved in an environment typified by periodic fluctuations in nutrient availability, yet little is known about its responses to host feeding and fasting. As many model species (for example, mice) are adapted to lifestyles of frequent small meals, we turned to the Burmese python, a sit-and-wait foraging snake that consumes large prey at long intervals (>1 month), to examine the effects of a dynamic nutrient milieu on the gut microbiota. We used multiplexed 16S rRNA gene pyrosequencing to characterize bacterial communities harvested from the intestines of fasted and digesting snakes, and from their rodent meal. In this unprecedented survey of a reptilian host, we found that Bacteroidetes and Firmicutes numerically dominated the python gut. In the large intestine, fasting was associated with increased abundances of the genera Bacteroides, Rikenella, Synergistes and Akkermansia, and with reduced overall diversity. A marked postprandial shift in bacterial community configuration occurred. Between 12?h and 3 days after feeding, Firmicutes, including the taxa Clostridium, Lactobacillus and Peptostreptococcaceae, gradually outnumbered the fasting-dominant Bacteroidetes, and overall 'species'-level diversity increased significantly. Most lineages seemed to be indigenous to the python rather than ingested with the meal, but a dietary source of Lactobacillus could not be ruled out. Thus, the observed large-scale alterations of the gut microbiota that accompany the Burmese python's own dramatic physiological and morphological changes during feeding and fasting emphasize the need to consider both microbial and host cellular responses to nutrient flux. The Burmese python may provide a unique model for dissecting these interrelationships. PMID:20520652

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

    PubMed

    Hunter, Margaret E; Hart, Kristen M

    2013-01-01

    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

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

    USGS Publications Warehouse

    Hunter, Margaret E.; Hart, Kristen M.

    2013-01-01

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

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

    PubMed

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

    2011-01-01

    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. PMID:21801464

  19. Molecular genetic evidence for parthenogenesis in the Burmese python, Python molurus bivittatus.

    PubMed

    Groot, T V M; Bruins, E; Breeuwer, J A J

    2003-02-01

    Parthenogenesis among reptiles is rare. Only a few species have the ability to reproduce asexually. Most of these are obligate parthenogenetic species that consist (almost) entirely of females, which can reproduce solely through parthenogenesis. Rarer are sexual species that only sporadically reproduce through parthenogenesis. A female Python molurus bivittatus (Reptilia, Boidae) from the Artis Zoo, Amsterdam, produced eggs in five consecutive years that contained embryos while she was isolated from males. These eggs might be fertilized with stored sperm, or might be the product of parthenogenesis. Parthenogenesis has not been shown for the Boidae family before. We performed parentship analyses on the snake and seven of her embryos using microsatellites and AFLP. Four microsatellite loci developed for this species combined with three loci developed previously for different snake species revealed too little variation to discriminate between sperm retention and parthenogenesis. With AFLP we were able to confirm that the Artis Zoo female reproduced parthenogenetically. Because the offspring are genetically identical to their mother, whereas in previous studies on sporadic parthenogenesis in snakes a loss of genetic information was reported, we conclude that the meiotic pathways that produce the diploid egg cells are different. PMID:12634818

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

    PubMed

    Adkesson, Michael J; Fernandez-Varon, Emilio; Cox, Sherry; Martn-Jimnez, Toms

    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. PMID:22950317

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

    PubMed

    Krause, Florian; Lindemann, Oliver

    2014-06-01

    Expyriment is an open-source and platform-independent lightweight Python library for designing and conducting timing-critical behavioral and neuroimaging experiments. The major goal is to provide a well-structured Python library for script-based experiment development, with a high priority being the readability of the resulting program code. Expyriment has been tested extensively under Linux and Windows and is an all-in-one solution, as it handles stimulus presentation, the recording of input/output events, communication with other devices, and the collection and preprocessing of data. Furthermore, it offers a hierarchical design structure, which allows for an intuitive transition from the experimental design to a running program. It is therefore also suited for students, as well as for experimental psychologists and neuroscientists with little programming experience. PMID:24142834

  2. Pyvolve: A Flexible Python Module for Simulating Sequences along Phylogenies.

    PubMed

    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. PMID:26397960

  3. Pyvolve: A Flexible Python Module for Simulating Sequences along Phylogenies

    PubMed Central

    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. PMID:26397960

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

    PubMed

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

    2015-09-01

    Carbonic anhydrase (CA) is one of the most abundant proteins found in vertebrate erythrocytes with the majority of species expressing a low activity CA I and high activity CA II. However, several phylogenetic gaps remain in our understanding of the expansion of cytoplasmic CA in vertebrate erythrocytes. In particular, very little is known about isoforms from reptiles. The current study sought to characterize the erythrocyte isoforms from two squamate species, Python molurus and Nerodia rhombifer, which was combined with information from recent genome projects to address this important phylogenetic gap. Obtained sequences grouped closely with CA XIII in phylogenetic analyses. CA II mRNA transcripts were also found in erythrocytes, but found at less than half the levels of CA XIII. Structural analysis suggested similar biochemical activity as the respective mammalian isoforms, with CA XIII being a low activity isoform. Biochemical characterization verified that the majority of CA activity in the erythrocytes was due to a high activity CA II-like isoform; however, titration with copper supported the presence of two CA pools. The CA II-like pool accounted for 90 % of the total activity. To assess potential disparate roles of these isoforms a feeding stress was used to up-regulate CO2 excretion pathways. Significant up-regulation of CA II and the anion exchanger was observed; CA XIII was strongly down-regulated. While these results do not provide insight into the role of CA XIII in the erythrocytes, they do suggest that the presence of two isoforms is not simply a case of physiological redundancy. PMID:26005204

  5. AstroAsciiData: ASCII table Python module

    NASA Astrophysics Data System (ADS)

    Kümmel, Martin; Haase, Jonas

    2013-11-01

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

  6. Python as a Federation Tool for GENESIS 3.0

    PubMed Central

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

    2012-01-01

    The GENESIS simulation platform was one of the first broad-scale modeling systems in computational biology to encourage modelers to develop and share model features and components. Supported by a large developer community, it participated in innovative simulator technologies such as benchmarking, parallelization, and declarative model specification and was the first neural simulator to define bindings for the Python scripting language. An important feature of the latest version of GENESIS is that it decomposes into self-contained software components complying with the Computational Biology Initiative federated software architecture. This architecture allows separate scripting bindings to be defined for different necessary components of the simulator, e.g., the mathematical solvers and graphical user interface. Python is a scripting language that provides rich sets of freely available open source libraries. With clean dynamic object-oriented designs, they produce highly readable code and are widely employed in specialized areas of software component integration. We employ a simplified wrapper and interface generator to examine an application programming interface and make it available to a given scripting language. This allows independent software components to be ‘glued’ together and connected to external libraries and applications from user-defined Python or Perl scripts. We illustrate our approach with three examples of Python scripting. (1) Generate and run a simple single-compartment model neuron connected to a stand-alone mathematical solver. (2) Interface a mathematical solver with GENESIS 3.0 to explore a neuron morphology from either an interactive command-line or graphical user interface. (3) Apply scripting bindings to connect the GENESIS 3.0 simulator to external graphical libraries and an open source three dimensional content creation suite that supports visualization of models based on electron microscopy and their conversion to computational models. Employed in this way, the stand-alone software components of the GENESIS 3.0 simulator provide a framework for progressive federated software development in computational neuroscience. PMID:22276101

  7. 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.

  8. COOPR: A COmmon Optimization Python Repository v. 1.0

    Energy Science and Technology Software Center (ESTSC)

    2008-08-14

    Coopr integrates Python packages for defining optimizers, modeling optimization applications, and managing computational experiments. A major driver for Coopr development is the Pyomo package that can be used to define abstract problems, create concrete problem instances, and solve these instances with standard solvers. Other Coopr packages include EXACT, a framework for managing computational experiments, SUCASA, a tool for customizing integer programming solvers, and OPT, a generic optimization interface.

  9. Python as a federation tool for GENESIS 3.0.

    PubMed

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

    2012-01-01

    The GENESIS simulation platform was one of the first broad-scale modeling systems in computational biology to encourage modelers to develop and share model features and components. Supported by a large developer community, it participated in innovative simulator technologies such as benchmarking, parallelization, and declarative model specification and was the first neural simulator to define bindings for the Python scripting language. An important feature of the latest version of GENESIS is that it decomposes into self-contained software components complying with the Computational Biology Initiative federated software architecture. This architecture allows separate scripting bindings to be defined for different necessary components of the simulator, e.g., the mathematical solvers and graphical user interface. Python is a scripting language that provides rich sets of freely available open source libraries. With clean dynamic object-oriented designs, they produce highly readable code and are widely employed in specialized areas of software component integration. We employ a simplified wrapper and interface generator to examine an application programming interface and make it available to a given scripting language. This allows independent software components to be 'glued' together and connected to external libraries and applications from user-defined Python or Perl scripts. We illustrate our approach with three examples of Python scripting. (1) Generate and run a simple single-compartment model neuron connected to a stand-alone mathematical solver. (2) Interface a mathematical solver with GENESIS 3.0 to explore a neuron morphology from either an interactive command-line or graphical user interface. (3) Apply scripting bindings to connect the GENESIS 3.0 simulator to external graphical libraries and an open source three dimensional content creation suite that supports visualization of models based on electron microscopy and their conversion to computational models. Employed in this way, the stand-alone software components of the GENESIS 3.0 simulator provide a framework for progressive federated software development in computational neuroscience. PMID:22276101

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

    NASA Astrophysics Data System (ADS)

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

    2013-07-01

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

  11. PyRAT - python radiography analysis tool (u)

    SciTech Connect

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

    2011-01-14

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

  12. Python for Information Theoretic Analysis of Neural Data

    PubMed Central

    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

  13. ELLIPT2D: A Flexible Finite Element Code Written Python

    SciTech Connect

    Pletzer, A.; Mollis, J.C.

    2001-03-22

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

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

    PubMed Central

    Liu, Wanli; Islamaj Do?an, 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

  15. User-friendly parallelization of GAUDI applications with Python

    NASA Astrophysics Data System (ADS)

    Mato, Pere; Smith, Eoin

    2010-04-01

    GAUDI is a software framework in C++ used to build event data processing applications using a set of standard components with well-defined interfaces. Simulation, high-level trigger, reconstruction, and analysis programs used by several experiments are developed using GAUDI. These applications can be configured and driven by simple Python scripts. Given the fact that a considerable amount of existing software has been developed using serial methodology, and has existed in some cases for many years, implementation of parallelisation techniques at the framework level may offer a way of exploiting current multi-core technologies to maximize performance and reduce latencies without re-writing thousands/millions of lines of code. In the solution we have developed, the parallelization techniques are introduced to the high level Python scripts which configure and drive the applications, such that the core C++ application code requires no modification, and that end users need make only minimal changes to their scripts. The developed solution leverages from existing generic Python modules that support parallel processing. Naturally, the parallel version of a given program should produce results consistent with its serial execution. The evaluation of several prototypes incorporating various parallelization techniques are presented and discussed.

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

    PubMed

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

    2014-01-01

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

  17. VPython: Python plus Animations in Stereo 3D

    NASA Astrophysics Data System (ADS)

    Sherwood, Bruce

    2004-03-01

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

  18. GAiN: Distributed Array Computation with Python

    SciTech Connect

    Daily, Jeffrey A.

    2009-04-24

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

  19. Disposition of enrofloxacin and its metabolite ciprofloxacin after intramuscular injection in juvenile Burmese pythons (Python molurus bivittatus).

    PubMed

    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. PMID:9226619

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

    PubMed

    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. PMID:25788598

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

    USGS Publications Warehouse

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

    2015-01-01

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

  2. 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.

  3. The fast azimuthal integration Python library: pyFAI

    PubMed Central

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

    2015-01-01

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

  4. PyVO: Python access to the Virtual Observatory

    NASA Astrophysics Data System (ADS)

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

    2014-02-01

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

  5. 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.

  6. LASER STRIPPING COMPUTING WITH THE PYTHON ORBIT CODE

    SciTech Connect

    Gorlov, Timofey V; Shishlo, Andrei P

    2009-01-01

    The laser assisted hydrogen stripping becomes a widely discussed alternative for the existing stripping foil approach. The simulation tool for this new approach is presented. The created application is implemented in form of extension module to the Python ORBIT parallel code that is under development at the SNS. The physical model of the application deals with quantum theory and allows calculating evolution and ionization of hydrogen atoms and ions affected by superposition of electromagnetic and laser fields. The algorithm, structure, benchmark cases, and results of simulations for several future and existing accelerators are discussed.

  7. Climate Map for Northern African Python: Areas Potentially Suitable for Invasion

    USGS Multimedia Gallery

    The Northern African Python ( Python sebae ) occurs naturally in a diverse collection of localities in central Africa. The climate-matched portions of the U.S. include peninsular Florida, extreme south Texas, Puerto Rico (right inset), Hawaii (left inset), and the other island territories (not shown...

  8. Fatty Acids Identified in the Burmese Python Promote Beneficial Cardiac Growth

    PubMed Central

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

    2012-01-01

    Burmese pythons display a dramatic 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 PI3K/Akt/mTor signaling 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 the cardioprotective enzyme, superoxide dismutase. Finally, we identified a combination of fatty acids in python plasma that promotes physiological heart growth when injected into either pythons or mice. PMID:22034436

  9. Pyteomics—a Python Framework for Exploratory Data Analysis and Rapid Software Prototyping in Proteomics

    NASA Astrophysics Data System (ADS)

    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

  10. Pyteomics--a Python framework for exploratory data analysis and rapid software prototyping in proteomics.

    PubMed

    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. PMID:23292976

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

    PubMed

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

    2011-10-28

    Burmese pythons display a marked increase in heart mass after a large meal. We investigated the molecular mechanisms of this physiological heart growth with the goal of applying this knowledge to the mammalian heart. We found that heart growth in pythons is characterized by myocyte hypertrophy in the absence of cell proliferation and by activation of physiological signal transduction pathways. Despite high levels of circulating lipids, the postprandial python heart does not accumulate triglycerides or fatty acids. Instead, there is robust activation of pathways of fatty acid transport and oxidation combined with increased expression and activity of superoxide dismutase, a cardioprotective enzyme. We also identified a combination of fatty acids in python plasma that promotes physiological heart growth when injected into either pythons or mice. PMID:22034436

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

    SciTech Connect

    Grant, Robert

    2015-11-23

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

  13. 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.

  14. CMCpy: Genetic Code-Message Coevolution Models in Python.

    PubMed

    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

  15. Novel divergent nidovirus in a python with pneumonia.

    PubMed

    Bodewes, Rogier; Lempp, Charlotte; Schrch, Anita C; Habierski, Andre; Hahn, Kerstin; Lamers, Mart; von Drnberg, Katja; Wohlsein, Peter; Drexler, Jan Felix; Haagmans, Bart L; Smits, Saskia L; Baumgrtner, 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. PMID:25063552

  16. Adaptive responses to feeding in Burmese pythons: pay before pumping.

    PubMed

    Secor, S M; Diamond, J

    1995-06-01

    Burmese pythons normally consume large meals after long intervals. We measured gut contents, O2 consumption rates, small intestinal brush-border uptake rates of amino acids and glucose, organ masses and blood chemistry in pythons during the 30 days following ingestion of meals equivalent to 25% of their body mass. Within 1-3 days after ingestion, O2 consumption rates, intestinal nutrient uptake rates and uptake capacities peaked at 17, 6-26 and 11-24 times fasting levels, respectively. Small intestinal mass doubled, and other organs also increased in mass. Changes in blood chemistry included a 78% decline in PO2 and a large 'alkaline tide' associated with gastric acid section (i.e. a rise in blood pH and HCO3- concentrations and a fall in Cl- concentration). All of these values returned to fasting levels by the time of defecation at 8-14 days. The response of O2 consumption (referred to as specific dynamic action, SDA) is the largest, and the upregulation of intestinal nutrient transporters the second largest, response reported for any vertebrate upon feeding. The SDA is a large as the factorial rise in O2 consumption measured in mammalian sprinters and is sustained for much longer. The extra energy expended for digestion is equivalent to 32% of the meal's energy yield, with much of it being measured before the prey energy was absorbed. PMID:7782719

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

    PubMed

    Rossant, Cyrille; Harris, Kenneth D

    2013-01-01

    Large datasets are becoming more and more common in science, particularly in neuroscience where experimental techniques are rapidly evolving. Obtaining interpretable results from raw data can sometimes be done automatically; however, there are numerous situations where there is a need, at all processing stages, to visualize the data in an interactive way. This enables the scientist to gain intuition, discover unexpected patterns, and find guidance about subsequent analysis steps. Existing visualization tools mostly focus on static publication-quality figures and do not support interactive visualization of large datasets. While working on Python software for visualization of neurophysiological data, we developed techniques to leverage the computational power of modern graphics cards for high-performance interactive data visualization. We were able to achieve very high performance despite the interpreted and dynamic nature of Python, by using state-of-the-art, fast libraries such as NumPy, PyOpenGL, and PyTables. We present applications of these methods to visualization of neurophysiological data. We believe our tools will be useful in a broad range of domains, in neuroscience and beyond, where there is an increasing need for scalable and fast interactive visualization. PMID:24391582

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

    PubMed Central

    Rossant, Cyrille; Harris, Kenneth D.

    2013-01-01

    Large datasets are becoming more and more common in science, particularly in neuroscience where experimental techniques are rapidly evolving. Obtaining interpretable results from raw data can sometimes be done automatically; however, there are numerous situations where there is a need, at all processing stages, to visualize the data in an interactive way. This enables the scientist to gain intuition, discover unexpected patterns, and find guidance about subsequent analysis steps. Existing visualization tools mostly focus on static publication-quality figures and do not support interactive visualization of large datasets. While working on Python software for visualization of neurophysiological data, we developed techniques to leverage the computational power of modern graphics cards for high-performance interactive data visualization. We were able to achieve very high performance despite the interpreted and dynamic nature of Python, by using state-of-the-art, fast libraries such as NumPy, PyOpenGL, and PyTables. We present applications of these methods to visualization of neurophysiological data. We believe our tools will be useful in a broad range of domains, in neuroscience and beyond, where there is an increasing need for scalable and fast interactive visualization. PMID:24391582

  19. New Python-based methods for data processing

    PubMed Central

    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

  20. Programming biological models in Python using PySB

    PubMed Central

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

    2013-01-01

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

  1. Conservative constraints on early cosmology with MONTE PYTHON

    SciTech Connect

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

    2013-02-01

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

  2. New Python-based methods for data processing

    SciTech Connect

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

    2013-07-01

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

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

    SciTech Connect

    Hart, William Eugene

    2010-11-01

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

  4. First identification of a ranavirus from green pythons (Chondropython viridis).

    PubMed

    Hyatt, A D; Williamson, M; Coupar, B E H; Middleton, D; Hengstberger, S G; Gould, A R; Selleck, P; Wise, T G; Kattenbelt, J; Cunningham, A A; Lee, J

    2002-04-01

    Ten juvenile green pythons (Chondropython viridis) died or were euthanized shortly after having been illegally imported into Australia from Indonesia in 1998. Histologic examination of two of the three snakes that died revealed moderately severe chronic ulceration of the nasal mucosa and focal or periacinar degeneration and necrosis of the liver. In addition there was severe necrotizing inflammation of the pharyngeal submucosa accompanied by numerous macrophages, heterophils, and edema. An iridovirus was isolated in culture from several tissues and characterized by immunohistochemistry, electron microscopy, enzyme-linked immunosorbent Assay, polyacrylamide gel electrophoresis, polymerase chain reaction and sequence analysis, restriction endonuclease digestion, and DNA hybridization. This is the first report of a systemic ranavirus infection in any species of snake and is a new member of the genus, Ranavirus. PMID:12038121

  5. PyORBIT: A Python Shell For ORBIT

    SciTech Connect

    Jean-Francois Ostiguy; Jeffrey Holmes

    2003-07-01

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

  6. PYTRANSIT: fast and easy exoplanet transit modelling in PYTHON

    NASA Astrophysics Data System (ADS)

    Parviainen, Hannu

    2015-07-01

    We present a fast and user friendly exoplanet transit light-curve modelling package PYTRANSIT, implementing optimized versions of the Gimnez and Mandel & Agol transit models. The package offers an object-oriented PYTHON interface to access the two models implemented natively in FORTRAN with OpenMP parallelization. A partial OpenCL version of the quadratic Mandel-Agol model is also included for GPU-accelerated computations. The aim of PYTRANSIT is to facilitate the analysis of photometric time series of exoplanet transits consisting of hundreds of thousands of data points, and of multipassband transit light curves from spectrophotometric observations, as a part of a researcher's programming toolkit for building complex, problem-specific analyses.

  7. A cross-validation package driving Netica with python

    USGS Publications Warehouse

    Fienen, Michael N.; Plant, Nathaniel G.

    2014-01-01

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

  8. Python package for model STructure ANalysis (pySTAN)

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

    The selection and identification of a suitable hydrological model structure is more than fitting parameters of a model structure to reproduce a measured hydrograph. The procedure is highly dependent on various criteria, i.e. the modelling objective, the characteristics and the scale of the system under investigation as well as the available data. Rigorous analysis of the candidate model structures is needed to support and objectify the selection of the most appropriate structure for a specific case (or eventually justify the use of a proposed ensemble of structures). This holds both in the situation of choosing between a limited set of different structures as well as in the framework of flexible model structures with interchangeable components. Many different methods to evaluate and analyse model structures exist. This leads to a sprawl of available methods, all characterized by different assumptions, changing conditions of application and various code implementations. Methods typically focus on optimization, sensitivity analysis or uncertainty analysis, with backgrounds from optimization, machine-learning or statistics amongst others. These methods also need an evaluation metric (objective function) to compare the model outcome with some observed data. However, for current methods described in literature, implementations are not always transparent and reproducible (if available at all). No standard procedures exist to share code and the popularity (and amount of applications) of the methods is sometimes more dependent on the availability than the merits of the method. Moreover, new implementations of existing methods are difficult to verify and the different theoretical backgrounds make it difficult for environmental scientists to decide about the usefulness of a specific method. A common and open framework with a large set of methods can support users in deciding about the most appropriate method. Hence, it enables to simultaneously apply and compare different methods on a fair basis. We developed and present pySTAN (python framework for STructure Analysis), a python package containing a set of functions for model structure evaluation to provide the analysis of (hydrological) model structures. A selected set of algorithms for optimization, uncertainty and sensitivity analysis is currently available, together with a set of evaluation (objective) functions and input distributions to sample from. The methods are implemented model-independent and the python language provides the wrapper functions to apply administer external model codes. Different objective functions can be considered simultaneously with both statistical metrics and more hydrology specific metrics. By using so-called reStructuredText (sphinx documentation generator) and Python documentation strings (docstrings), the generation of manual pages is semi-automated and a specific environment is available to enhance both the readability and transparency of the code. It thereby enables a larger group of users to apply and compare these methods and to extend the functionalities.

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

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

  10. PyRAT (python radiography analysis tool): overview

    SciTech Connect

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

    2011-01-14

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

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

    PubMed

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

    2014-07-01

    Interspecific allometric analyses indicate that mean arterial blood pressure (MAP) increases with body mass of snakes and mammals. In snakes, MAP increases in proportion to the increased distance between the heart and the head, when the heart-head vertical distance is expressed as ?gh (where ? is the density of blood, G: is acceleration due to gravity and h is the vertical distance above the heart), and the rise in MAP is associated with a larger heart to normalize wall stress in the ventricular wall. Based on measurements of MAP in Burmese pythons ranging from 0.9 to 3.7 m in length (0.20-27 kg), we demonstrate that although MAP increases with body mass, the rise in MAP is merely half of that predicted by heart-head distance. Scaling relationships within individual species, therefore, may not be accurately predicted by existing interspecific analyses. PMID:24737752

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

    PubMed

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

    2013-01-01

    Myiases are caused by the presence of maggots in vertebrate tissues and organs. Myiases have been studied widely in humans, farm animals, and pets, whereas reports of myiasis in reptiles are scarce. We describe a case of myiasis caused by the Megaselia scalaris (Loew) in an Indian python (Python molurus bivittatus, Kuhl) (Ophida: Boidae). The python, 15 yr old, born and reared in a terrarium in the mainland of Venice (Italy), was affected by diffuse, purulent pneumonia caused by Burkholderia cepacia. The severe infestation of maggots found in the lungs during an autopsy indicated at a myiasis. PMID:23427672

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

    PubMed Central

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

    2014-01-01

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

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

    PubMed

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

    2014-03-01

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

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

    USGS Publications Warehouse

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

    2014-01-01

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

  16. Environmental DNA (eDNA) sampling improves occurrence and detection estimates of invasive burmese pythons.

    PubMed

    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. Generic sampling design and terminology are proposed to standardize and clarify interpretations of eDNA-based occupancy models. PMID:25874630

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

    PubMed Central

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

    2015-01-01

    Environmental DNA (eDNA) methods are used to detect DNA that is shed into the aquatic environment by cryptic or low density species. Applied in eDNA studies, occupancy models can be used to estimate occurrence and detection probabilities and thereby account for imperfect detection. However, occupancy terminology has been applied inconsistently in eDNA studies, and many have calculated occurrence probabilities while not considering the effects of imperfect detection. Low detection of invasive giant constrictors using visual surveys and traps has hampered the estimation of occupancy and detection estimates needed for population management in southern Florida, USA. Giant constrictor snakes pose a threat to native species and the ecological restoration of the Florida Everglades. To assist with detection, we developed species-specific eDNA assays using quantitative PCR (qPCR) for the Burmese python (Python molurus bivittatus), Northern African python (P. sebae), boa constrictor (Boa constrictor), and the green (Eunectes murinus) and yellow anaconda (E. notaeus). Burmese pythons, Northern African pythons, and boa constrictors are established and reproducing, while the green and yellow anaconda have the potential to become established. We validated the python and boa constrictor assays using laboratory trials and tested all species in 21 field locations distributed in eight southern Florida regions. Burmese python eDNA was detected in 37 of 63 field sampling events; however, the other species were not detected. Although eDNA was heterogeneously distributed in the environment, occupancy models were able to provide the first estimates of detection probabilities, which were greater than 91%. Burmese python eDNA was detected along the leading northern edge of the known population boundary. The development of informative detection tools and eDNA occupancy models can improve conservation efforts in southern Florida and support more extensive studies of invasive constrictors. Generic sampling design and terminology are proposed to standardize and clarify interpretations of eDNA-based occupancy models. PMID:25874630

  18. Obtaining and processing Daymet data using Python and ArcGIS

    USGS Publications Warehouse

    Bohms, Stefanie

    2013-01-01

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

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

    USGS Publications Warehouse

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

    2015-01-01

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

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

    PubMed Central

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

    2012-01-01

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

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

    PubMed

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

    2012-02-14

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

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

    PubMed

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

    2015-05-01

    Python snake species are often encountered in illegal activities and the question of species identity can be pertinent to such criminal investigations. Morphological identification of species of pythons can be confounded by many issues and molecular examination by DNA analysis can provide an alternative and objective means of identification. Our paper reports on the development and validation of a PCR primer pair that amplifies a segment of the mitochondrial cytochrome b gene that has been suggested previously as a good candidate locus for differentiating python species. We used this DNA region to perform species identification of pythons, even when the template DNA was of poor quality, as might be the case with forensic evidentiary items. Validation tests are presented to demonstrate the characteristics of the assay. Tests involved the cross-species amplification of this marker in non-target species, minimum amount of DNA template required, effects of degradation on product amplification and a blind trial to simulate a casework scenario that provided 100% correct identity. Our results demonstrate that this assay performs reliably and robustly on pythons and can be applied directly to forensic investigations where the presence of a species of python is in question. PMID:25541013

  3. 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.

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

    USGS Publications Warehouse

    Dorcas, Michael E.; Wilson, John D.; Reed, Robert N.; Snow, Ray W.; Rochford, Michael R.; Miller, Melissa A.; Meshaka, Walter E., Jr.; 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.

  5. Python framework for kinetic modeling of electronically excited reaction pathways

    NASA Astrophysics Data System (ADS)

    Verboncoeur, John; Parsey, Guy; Guclu, Yaman; Christlieb, Andrew

    2012-10-01

    The use of plasma energy to enhance and control the chemical reactions during combustion, a technology referred to as ``plasma assisted combustion'' (PAC), can result in a variety of beneficial effects: e.g. stable lean operation, pollution reduction, and wider range of p-T operating conditions. While experimental evidence abounds, theoretical understanding of PAC is at best incomplete, and numerical tools still lack in reliable predictive capabilities. In the context of a joint experimental-numerical effort at Michigan State University, we present here an open-source modular Python framework dedicated to the dynamic optimization of non-equilibrium PAC systems. Multiple sources of experimental reaction data, e.g. reaction rates, cross-sections and oscillator strengths, are used in order to quantify the effect of data uncertainty and limiting assumptions. A collisional-radiative model (CRM) is implemented to organize reactions by importance and as a potential means of measuring a non-Maxwellian electron energy distribution function (EEDF), when coupled to optical emission spectroscopy data. Finally, we explore scaling laws in PAC parameter space using a kinetic global model (KGM) accelerated with CRM optimized reaction sequences and sparse stiff integrators.

  6. SIMA: Python software for analysis of dynamic fluorescence imaging data

    PubMed Central

    Kaifosh, Patrick; Zaremba, Jeffrey D.; Danielson, Nathan B.; Losonczy, Attila

    2014-01-01

    Fluorescence imaging is a powerful method for monitoring dynamic signals in the nervous system. However, analysis of dynamic fluorescence imaging data remains burdensome, in part due to the shortage of available software tools. To address this need, we have developed SIMA, an open source Python package that facilitates common analysis tasks related to fluorescence imaging. Functionality of this package includes correction of motion artifacts occurring during in vivo imaging with laser-scanning microscopy, segmentation of imaged fields into regions of interest (ROIs), and extraction of signals from the segmented ROIs. We have also developed a graphical user interface (GUI) for manual editing of the automatically segmented ROIs and automated registration of ROIs across multiple imaging datasets. This software has been designed with flexibility in mind to allow for future extension with different analysis methods and potential integration with other packages. Software, documentation, and source code for the SIMA package and ROI Buddy GUI are freely available at http://www.losonczylab.org/sima/. PMID:25295002

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

    PubMed

    Helfenstein, Andreas; Tammela, Pivi

    2015-02-01

    High-throughput screening is an established technique in drug discovery and, as such, has also found its way into academia. High-throughput screening generates a considerable amount of data, which is why specific software is used for its analysis and management. The commercially available software packages are often beyond the financial limits of small-scale academic laboratories and, furthermore, lack the flexibility to fulfill certain user-specific requirements. We have developed a Python module, screening_mgmt, which is a lightweight tool for flexible data retrieval, analysis, and storage for different screening assays in one central database. The module reads custom-made analysis scripts and plotting instructions, and it offers a graphical user interface to import, modify, and display the data in a uniform manner. During the test phase, we used this module for the management of 10,000 data points of various origins. It has provided a practical, user-friendly tool for sharing and exchanging information between researchers. PMID:25381290

  8. Hyperopt: a Python library for model selection and hyperparameter optimization

    NASA Astrophysics Data System (ADS)

    Bergstra, James; Komer, Brent; Eliasmith, Chris; Yamins, Dan; Cox, David D.

    2015-01-01

    Sequential model-based optimization (also known as Bayesian optimization) is one of the most efficient methods (per function evaluation) of function minimization. This efficiency makes it appropriate for optimizing the hyperparameters of machine learning algorithms that are slow to train. The Hyperopt library provides algorithms and parallelization infrastructure for performing hyperparameter optimization (model selection) in Python. This paper presents an introductory tutorial on the usage of the Hyperopt library, including the description of search spaces, minimization (in serial and parallel), and the analysis of the results collected in the course of minimization. This paper also gives an overview of Hyperopt-Sklearn, a software project that provides automatic algorithm configuration of the Scikit-learn machine learning library. Following Auto-Weka, we take the view that the choice of classifier and even the choice of preprocessing module can be taken together to represent a single large hyperparameter optimization problem. We use Hyperopt to define a search space that encompasses many standard components (e.g. SVM, RF, KNN, PCA, TFIDF) and common patterns of composing them together. We demonstrate, using search algorithms in Hyperopt and standard benchmarking data sets (MNIST, 20-newsgroups, convex shapes), that searching this space is practical and effective. In particular, we improve on best-known scores for the model space for both MNIST and convex shapes. The paper closes with some discussion of ongoing and future work.

  9. AstroML: Python-powered Machine Learning for Astronomy

    NASA Astrophysics Data System (ADS)

    Vander Plas, Jake; Connolly, A. J.; Ivezic, Z.

    2014-01-01

    As astronomical data sets grow in size and complexity, automated machine learning and data mining methods are becoming an increasingly fundamental component of research in the field. The astroML project (http://astroML.org) provides a common repository for practical examples of the data mining and machine learning tools used and developed by astronomical researchers, written in Python. The astroML module contains a host of general-purpose data analysis and machine learning routines, loaders for openly-available astronomical datasets, and fast implementations of specific computational methods often used in astronomy and astrophysics. The associated website features hundreds of examples of these routines being used for analysis of real astronomical datasets, while the associated textbook provides a curriculum resource for graduate-level courses focusing on practical statistics, machine learning, and data mining approaches within Astronomical research. This poster will highlight several of the more powerful and unique examples of analysis performed with astroML, all of which can be reproduced in their entirety on any computer with the proper packages installed.

  10. batman: BAsic Transit Model cAlculatioN in Python

    NASA Astrophysics Data System (ADS)

    Kreidberg, Laura

    2015-11-01

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

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

    Secor, Stephen M; White, Scott E

    2010-01-01

    Individually, the metabolic demands of digestion or movement can be fully supported by elevations in cardiovascular performance, but when occurring simultaneously, vascular perfusion may have to be prioritized to either the gut or skeletal muscles. Burmese pythons (Python molurus) experience similar increases in metabolic rate during the digestion of a meal as they do while crawling, hence each would have an equal demand for vascular supply when these two actions are combined. To determine, for the Burmese python, whether blood flow is prioritized when snakes are digesting and moving, we examined changes in cardiac performance and blood flow in response to digestion, movement, and the combination of digestion and movement. We used perivascular blood flow probes to measure blood flow through the left carotid artery, dorsal aorta, superior mesenteric artery and hepatic portal vein, and to calculate cardiac output, heart rate and stroke volume. Fasted pythons while crawling experienced a 2.7- and 3.3-fold increase, respectively, in heart rate and cardiac output, and a 66% decrease in superior mesenteric flow. During the digestion of a rodent meal equaling in mass to 24.7% of the snake's body mass, heart rate and cardiac output increased by 3.3- and 4.4-fold, respectively. Digestion also resulted in respective 11.6- and 14.1-fold increases in superior mesenteric and hepatic portal flow. When crawling while digesting, cardiac output and dorsal aorta flow increased by only 21% and 9%, respectively, a modest increase compared with that when they start to crawl on an empty stomach. Crawling did triggered a significant reduction in blood flow to the digesting gut, decreasing superior mesenteric and hepatic portal flow by 81% and 47%, respectively. When faced with the dual demands of digestion and crawling, Burmese pythons prioritize blood flow, apparently diverting visceral supply to the axial muscles. PMID:20008365

  13. SunPy - Python for Solar Physics, Version 0.4

    NASA Astrophysics Data System (ADS)

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

    2014-06-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2015-01-01

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

  15. 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.

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

    PubMed

    Yesylevskyy, Semen O

    2015-07-15

    Pteros is the high-performance open-source library for molecular modeling and analysis of molecular dynamics trajectories. Starting from version 2.0 Pteros is available for C++ and Python programming languages with very similar interfaces. This makes it suitable for writing complex reusable programs in C++ and simple interactive scripts in Python alike. New version improves the facilities for asynchronous trajectory reading and parallel execution of analysis tasks by introducing analysis plugins which could be written in either C++ or Python in completely uniform way. The high level of abstraction provided by analysis plugins greatly simplifies prototyping and implementation of complex analysis algorithms. Pteros is available for free under Artistic License from http://sourceforge.net/projects/pteros/. PMID:25974373

  17. The mechanical properties of the systemic and pulmonary arteries of python regius correlate with blood pressures.

    PubMed

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

    2015-12-01

    Pythons are unique amongst snakes in having different pressures in the aortas and pulmonary arteries because of intraventricular pressure separation. In this study, we investigate whether this correlates with different blood vessel strength in the ball python Python regius. We excised segments from the left, right, and dorsal aortas, and from the two pulmonary arteries. These were subjected to tensile testing. We show that the aortic vessel wall is significantly stronger than the pulmonary artery wall in P. regius. Gross morphological characteristics (vessel wall thickness and correlated absolute amount of collagen content) are likely the most influential factors. Collagen fiber thickness and orientation are likely to have an effect, though the effect of collagen fiber type and cross-links between fibers will need further study. J. Morphol. 276:1412-1421, 2015. © 2015 Wiley Periodicals, Inc. PMID:26780263

  18. 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 helps researchers to ensure the robustness of the algorithm, correctness of the results in edge cases as well as the detection of changes in results due to new development. For all modules GRASS GIS automatically creates standardized command line and graphical user interfaces and documentation. Finally, we will show how GRASS GIS can be used together with powerful Python tools such as the NumPy package and the IPython Notebook. References: Gebbert, S., Pebesma, E., 2014. A temporal GIS for field based environmental modeling. Environmental Modelling & Software 53, 1-12. Neteler, M., Bowman, M.H., Landa, M. and Metz, M., 2012. GRASS GIS: a multi-purpose Open Source GIS. Environmental Modelling & Software 31: 124-130. Petras, V., Gebbert, S., 2014. Testing framework for GRASS GIS: ensuring reproducibility of scientific geospatial computing. Poster presented at: AGU Fall Meeting, December 15-19, 2014, San Francisco, USA. Zambelli, P., Gebbert, S., Ciolli, M., 2013. Pygrass: An Object Oriented Python Application Programming Interface (API) for Geographic Resources Analysis Support System (GRASS) Geographic Information System (GIS). ISPRS International Journal of Geo-Information 2, 201-219.

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

    PubMed

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

    2012-09-01

    A well-established population of Burmese pythons resides in the Everglades of southern Florida. Prompted in part by a report that identified much of southern USA as suitable habitat for expansion or establishment of the Burmese python, we examined the plausibility of this snake to survive winters at sites north of the Everglades. We integrated daily low and high temperatures recorded from October to February from 2005-2011 at Homestead, Orlando and Gainesville, Florida; and Aiken, South Carolina, with minimum temperatures projected for python digestion (16 °C), activity (5 °C) and survival (0 °C). Mean low and high temperatures decreased northward from Homestead to Aiken and the number of days of freezing temperatures increased northward. Digestion was impaired or inhibited for 2 months in the Everglades and up to at least 5 months in Aiken, and activity was increasingly limited northward during these months. Reports of overwinter survivorship document that a single bout of low and freezing temperatures results in python death. The capacity for Burmese pythons to successfully overwinter in more temperate regions of the USA is seemingly prohibited because they lack the behaviors to seek refuge from, and the physiology to tolerate, cold temperatures. As tropical Southeast Asia is the source of the Everglades Burmese pythons, we predict it is unlikely that they will be able to successfully expand to or colonize more temperate areas of Florida and adjoining states due to their lack of behavioral and physiological traits to seek refuge from cold temperatures. PMID:22938524

  20. 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

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

    PubMed Central

    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

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

    NASA Astrophysics Data System (ADS)

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

    2015-09-01

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

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

    NASA Astrophysics Data System (ADS)

    Houska, Tobias; Kraft, Philipp; Breuer, Lutz

    2015-04-01

    The selection and parameterization of reliable process descriptions in ecological modelling is driven by several uncertainties. The procedure is highly dependent on various criteria, like the used algorithm, the likelihood function selected and the definition of the prior parameter distributions. A wide variety of tools have been developed in the past decades to optimize parameters. Some of the tools are closed source. Due to this, the choice for a specific parameter estimation method is sometimes more dependent on its availability than the performance. A toolbox with a large set of methods can support users in deciding about the most suitable method. Further, it enables to test and compare different methods. We developed the SPOT (Statistical Parameter Optimization Tool), an open source python package containing a comprehensive set of modules, to analyze and optimize parameters of (environmental) models. SPOT comes along with a selected set of algorithms for parameter optimization and uncertainty analyses (Monte Carlo, MC; Latin Hypercube Sampling, LHS; Maximum Likelihood, MLE; Markov Chain Monte Carlo, MCMC; Scuffled Complex Evolution, SCE-UA; Differential Evolution Markov Chain, DE-MCZ), together with several likelihood functions (Bias, (log-) Nash-Sutcliff model efficiency, Correlation Coefficient, Coefficient of Determination, Covariance, (Decomposed-, Relative-, Root-) Mean Squared Error, Mean Absolute Error, Agreement Index) and prior distributions (Binomial, Chi-Square, Dirichlet, Exponential, Laplace, (log-, multivariate-) Normal, Pareto, Poisson, Cauchy, Uniform, Weibull) to sample from. The model-independent structure makes it suitable to analyze a wide range of applications. We apply all algorithms of the SPOT package in three different case studies. Firstly, we investigate the response of the Rosenbrock function, where the MLE algorithm shows its strengths. Secondly, we study the Griewank function, which has a challenging response surface for optimization methods. Here we see simple algorithms like the MCMC struggling to find the global optimum of the function, while algorithms like SCE-UA and DE-MCZ show their strengths. Thirdly, we apply an uncertainty analysis of a one-dimensional physically based hydrological model build with the Catchment Modelling Framework (CMF). The model is driven by meteorological and groundwater data from a Free Air Carbon Enrichment (FACE) experiment in Linden (Hesse, Germany). Simulation results are evaluated with measured soil moisture data. We search for optimal parameter sets of the van Genuchten-Mualem function and find different equally optimal solutions with some of the algorithms. The case studies reveal that the implemented SPOT methods work sufficiently well. They further show the benefit of having one tool at hand that includes a number of parameter search methods, likelihood functions and a priori parameter distributions within one platform independent package.

  4. 77 FR 3329 - Injurious Wildlife Species; Listing Three Python Species and One Anaconda Species as Injurious...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-01-23

    ... inquiry in the Federal Register (73 FR 5784; January 31, 2008) soliciting available biological, economic..., 2010, we published a proposed rule in the Federal Register (75 FR 11808) to list Python molurus (which... (75 FR 38069; July 1, 2010). For the injurious wildlife evaluation in this final rule, in addition...

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

    ERIC Educational Resources Information Center

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

    2007-01-01

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

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

    Energy Science and Technology Software Center (ESTSC)

    2014-01-30

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

  7. Close-Up of a Radio Transmitter on an Invasive Burmese Python

    USGS Multimedia Gallery

    This close-up is of the radio-transmitter on a 16 1/2-foot python. The snake, being removed from the wild by USGS and NPS personnel, was re-captured in a thicket in Everglades National Park in April 2012. After its first capture, the snake was equipped with a radio-transmitter and an accelerometer a...

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

    SciTech Connect

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

    2010-11-29

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

  9. PCSIM: A Parallel Simulation Environment for Neural Circuits Fully Integrated with Python

    PubMed Central

    Pecevski, Dejan; Natschlger, 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

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

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

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

    ERIC Educational Resources Information Center

    Murrell, Elizabeth

    1998-01-01

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

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

    USGS Publications Warehouse

    Reed, Robert N.; Snow, Ray W.

    2014-01-01

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

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

    ERIC Educational Resources Information Center

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

    2007-01-01

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

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

    SciTech Connect

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

    2011-01-01

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

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

    SciTech Connect

    2014-01-30

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

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

    PubMed

    Secor, Stephen M

    2008-12-01

    As an apparent adaptation to predictably long episodes of fasting, the sit-and-wait foraging Burmese python experiences unprecedented regulation of gastrointestinal and cardiovascular performance with feeding and fasting. The ingestion of a meal signals the quiescent gut tissues to start secreting digestive acid and enzymes, to upregulate intestinal brush-border enzymes and nutrient transporters, and to grow. An integrated phenomenon, digestion is also characterized by increases in the mass, and presumably the function, of the heart, pancreas, liver and kidneys. Once digestion is complete, the python's stomach and small intestine rapidly downregulate performance. Much of the modulation of intestinal function can be explained by the 5-fold increase in microvillus length and apical surface area with feeding, and the subsequent shortening of the microvilli after digestion has finished. Digestion for the Burmese python is a relatively expensive endeavor, evident by the as much as a 44-fold increase in metabolic rate and equivalent in cost to as much as 37% of the meal's energy. Their large metabolic response is supported by substantial increases in ventilation and cardiac output and the apparent catabolism of glucose and lipids. Unmatched in the magnitude of its numerous physiological responses to feeding, the Burmese python is a very attractive model for examining the capacities and regulatory mechanisms of physiological performance. PMID:19043049

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

    PubMed

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

    2015-01-01

    Snake venom gene evolution has been studied intensively over the past several decades, yet most previous studies have lacked the context of complete snake genomes and the full context of gene expression across diverse snake tissues. We took a novel approach to studying snake venom evolution by leveraging the complete genome of the Burmese python, including information from tissue-specific patterns of gene expression. We identified the orthologs of snake venom genes in the python genome, and conducted detailed analysis of gene expression of these venom homologs to identify patterns that differ between snake venom gene families and all other genes. We found that venom gene homologs in the python are expressed in many different tissues outside of oral glands, which illustrates the pitfalls of using transcriptomic data alone to define "venom toxins." We hypothesize that the python may represent an ancestral state prior to major venom development, which is supported by our finding that the expansion of venom gene families is largely restricted to highly venomous caenophidian snakes. Therefore, the python provides insight into biases in which genes were recruited for snake venom systems. Python venom homologs are generally expressed at lower levels, have higher variance among tissues, and are expressed in fewer organs compared with all other python genes. We propose a model for the evolution of snake venoms in which venom genes are recruited preferentially from genes with particular expression profile characteristics, which facilitate a nearly neutral transition toward specialized venom system expression. PMID:25338510

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

    PubMed

    Starck, J M; Weimer, I; Aupperle, H; Mller, 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 reduction does not result in clinical signs and disease can progress unrecognized for an extended period. PMID:26410400

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

    PubMed

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

    2015-12-01

    Highly repetitive DNA sequences of the centromeric heterochromatin provide valuable molecular cytogenetic markers for the investigation of genomic compartmentalization in the macrochromosomes and microchromosomes of sauropsids. Here, the relationship between centromeric heterochromatin and karyotype evolution was examined using cloned repetitive DNA sequences from two snake species, the habu snake (Protobothrops flavoviridis, Crotalinae, Viperidae) and Burmese python (Python bivittatus, Pythonidae). Three satellite DNA (stDNA) families were isolated from the heterochromatin of these snakes: 168-bp PFL-MspI from P. flavoviridis and 196-bp PBI-DdeI and 174-bp PBI-MspI from P. bivittatus. The PFL-MspI and PBI-DdeI sequences were localized to the centromeric regions of most chromosomes in the respective species, suggesting that the two sequences were the major components of the centromeric heterochromatin in these organisms. The PBI-MspI sequence was localized to the pericentromeric region of four chromosome pairs. The PFL-MspI and the PBI-DdeI sequences were conserved only in the genome of closely related species, Gloydius blomhoffii (Crotalinae) and Python molurus, respectively, although their locations on the chromosomes were slightly different. In contrast, the PBI-MspI sequence was also in the genomes of P. molurus and Boa constrictor (Boidae), and additionally localized to the centromeric regions of eight chromosome pairs in B. constrictor, suggesting that this sequence originated in the genome of a common ancestor of Pythonidae and Boidae, approximately 86 million years ago. The three stDNA sequences showed no genomic compartmentalization between the macrochromosomes and microchromosomes, suggesting that homogenization of the centromeric and/or pericentromeric stDNA sequences occurred in the macrochromosomes and microchromosomes of these snakes. PMID:26205503

  20. GMES: A Python package for solving Maxwells 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 Maxwells 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, Queens 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 project homepage [7]. Running time: Problem dependent (a simulation with real valued electromagnetic field takes typically about 0.16 ?s per Yee cell per time-step.) SWIG, http://www.swig.org. Cython, http://www.cython.org. NumPy, http://numpy.scipy.org. SciPy, http://www.scipy.org. matplotlib, http://matplotlib.sourceforge.net. MPI for Python, http://mpi4py.scipy.org. GMES, http://sourceforge.net/projects/gmes.

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

    PubMed

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

    2012-01-01

    Snakes exhibit an apparent dichotomy in the regulation of gastrointestinal (GI) performance with feeding and fasting; frequently feeding species modestly regulate intestinal function whereas infrequently feeding species rapidly upregulate and downregulate intestinal function with the start and completion of each meal, respectively. The downregulatory response with fasting for infrequently feeding snakes is hypothesized to be a selective attribute that reduces energy expenditure between meals. To ascertain the links between feeding habit, whole-animal metabolism, and GI function and metabolism, we measured preprandial and postprandial metabolic rates and gastric and intestinal acid-base secretion, epithelial conductance and oxygen consumption for the frequently feeding diamondback water snake (Nerodia rhombifer) and the infrequently feeding Burmese python (Python molurus). Independent of body mass, Burmese pythons possess a significantly lower standard metabolic rate and respond to feeding with a much larger metabolic response compared with water snakes. While fasting, pythons cease gastric acid and intestinal base secretion, both of which are stimulated with feeding. In contrast, fasted water snakes secreted gastric acid and intestinal base at rates similar to those of digesting snakes. We observed no difference between fasted and fed individuals for either species in gastric or intestinal transepithelial potential and conductance, with the exception of a significantly greater gastric transepithelial potential for fed pythons at the start of titration. Water snakes experienced no significant change in gastric or intestinal metabolism with feeding. Fed pythons, in contrast, experienced a near-doubling of gastric metabolism and a tripling of intestinal metabolic rate. For fasted individuals, the metabolic rate of the stomach and small intestine was significantly lower for pythons than for water snakes. The fasting downregulation of digestive function for pythons is manifested in a depressed gastric and intestinal metabolism, which selectively serves to reduce basal metabolism and hence promote survival between infrequent meals. By maintaining elevated GI performance between meals, fasted water snakes incur the additional cost of tissue activity, which is expressed in a higher standard metabolic rate. PMID:22162867

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

    PubMed

    Johnson, Jami L; Tom Wrden, 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. PMID:25304874

  3. BioServices: a common Python package to access biological Web Services programmatically

    PubMed Central

    Cokelaer, Thomas; Pultz, Dennis; Harder, Lea M.; Serra-Musach, Jordi; Saez-Rodriguez, Julio

    2013-01-01

    Motivation: 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. Results: 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. Availability and implementation: BioServices releases and documentation are available at http://pypi.python.org/pypi/bioservices under a GPL-v3 license. Contact: cokelaer@ebi.ac.uk or bioservices@googlegroups.com Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24064416

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

    NASA Astrophysics Data System (ADS)

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

    2013-10-01

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

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

    NASA Technical Reports Server (NTRS)

    Lang, Timothy J.

    2015-01-01

    At NASA Marshall Space Flight Center (MSFC), Python is used several different ways to analyze and visualize precipitating weather systems. A number of different Python-based software packages have been developed, which are available to the larger scientific community. The approach in all these packages is to utilize pre-existing Python modules as well as to be object-oriented and scalable. The first package that will be described and demonstrated is the Python Advanced Microwave Precipitation Radiometer (AMPR) Data Toolkit, or PyAMPR for short. PyAMPR reads geolocated brightness temperature data from any flight of the AMPR airborne instrument over its 25-year history into a common data structure suitable for user-defined analyses. It features rapid, simplified (i.e., one line of code) production of quick-look imagery, including Google Earth overlays, swath plots of individual channels, and strip charts showing multiple channels at once. These plotting routines are also capable of significant customization for detailed, publication-ready figures. Deconvolution of the polarization-varying channels to static horizontally and vertically polarized scenes is also available. Examples will be given of PyAMPR's contribution toward real-time AMPR data display during the Integrated Precipitation and Hydrology Experiment (IPHEx), which took place in the Carolinas during May-June 2014. The second software package is the Marshall Multi-Radar/Multi-Sensor (MRMS) Mosaic Python Toolkit, or MMM-Py for short. MMM-Py was designed to read, analyze, and display three-dimensional national mosaicked reflectivity data produced by the NOAA National Severe Storms Laboratory (NSSL). MMM-Py can read MRMS mosaics from either their unique binary format or their converted NetCDF format. It can also read and properly interpret the current mosaic design (4 regional tiles) as well as mosaics produced prior to late July 2013 (8 tiles). MMM-Py can easily stitch multiple tiles together to provide a larger regional or national picture of precipitating weather systems. Composites, horizontal and vertical crosssections, and combinations thereof are easily displayed using as little as one line of code. MMM-Py can also write to the native MRMS binary format, and sub-sectioning of tiles (or multiple stitched tiles) is anticipated to be in place by the time of this meeting. Thus, MMM-Py also can be used to power the creation of custom mosaics for targeted regional studies. Overlays of other data (e.g., lightning observations) are easily accomplished. Demonstrations of MMM-Py, including the creation of animations, will be shown. Finally, Marshall has done significant work to interface Python-based analysis routines with the U.S. Department of Energy's Py-ART software package for radar data ingest, processing, and analysis. One example of this is the Python Turbulence Detection Algorithm (PyTDA), an MSFC-based implementation of the National Center for Atmospheric Research (NCAR) Turbulence Detection Algorithm (NTDA) for the purposes of convective-scale analysis, situational awareness, and forensic meteorology. PyTDA exploits Py-ART's radar data ingest routines and data model to rapidly produce aviation-relevant turbulence estimates from Doppler radar data. Work toward processing speed optimization and better integration within the Py-ART framework will be highlighted. Python-based analysis within the Py-ART framework is also being done for new research related to intercomparison of ground-based radar data with satellite estimates of ocean winds, as well as research on the electrification of pyrocumulus clouds.

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

    PubMed

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

    1999-01-01

    Two-dimensional echocardiography was performed on Burmese pythons (Python molurus bivittatus) to determine an optimal echocardiographic imaging technique for snakes and to describe the echocardiographic anatomy of the snake heart. Five snakes immobilized with tiletamine/zolazepam and maintained on isoflurane in oxygen were imaged in dorsal recumbency. The portion of the snake's body containing the heart was submerged in warm water to reduce the artifact created by air trapped between and under the scales. Imaging in sagittal planes demonstrated the caudal vena cava, sinus venous valve, right atrium, various portions of the ventricle, horizontal septum, the left aortic arch, and pulmonary artery. Transverse imaging depicted the spatial relationship of the left and right aortic arches and pulmonary artery and the horizontal septum. Basic knowledge of cardiac blood flow in the reptile was necessary to understand the echocardiographic anatomy. PMID:10023997

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

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

    PubMed Central

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

    2013-01-01

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

  9. 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/.

  10. ObsPy: A Python Toolbox for Seismologists, Seismological Observatories and Data Centers

    NASA Astrophysics Data System (ADS)

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

    2012-04-01

    Python combines the possibilities of a full-blown programming language with the flexibility of an interactive scripting language. Its extensive standard library and many freely available high quality scientific modules cover most needs in developing scientific processing workflows. ObsPy extends Python's capabilities to fit the specific needs that arise when working with seismological data. It a) comes with a continuously growing signal processing toolbox that covers the most common tasks in seismological analysis, b) provides read and write support for many common waveform and metadata file formats and c) enables access to various data centers, webservices and databases to retrieve waveform data and station/event metadata. In combination with widely used, free Python packages like NumPy, SciPy, Matplotlib, IPython and PyQt, ObsPy makes it possible to develop complete workflows in Python, ranging from reading locally stored data or requesting data from one or more different data centers via signal analysis and data processing to visualization in GUI applications, output of modified/derived data and creating publication-quality figures. All functionality is extensively documented and the ObsPy Gallery/Tutorial give a good impression of the wide range of use cases. ObsPy is tested and running on Linux, MacOSX and Windows XP/Vista/7 and comes with installation routines for these systems. ObsPy is developed in a test-driven approach and is available under the GPL/LGPLv3 licences. Users are welcome to request help, report bugs or propose enhancements via the user mailing list or the Trac ticket system.

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

    PubMed

    Castoe, Todd A; de Koning, A P Jason; Hall, Kathryn T; Card, Daren C; Schield, Drew R; Fujita, Matthew K; Ruggiero, Robert P; Degner, Jack F; Daza, Juan M; Gu, Wanjun; Reyes-Velasco, Jacobo; Shaney, Kyle J; Castoe, Jill M; Fox, Samuel E; Poole, Alex W; Polanco, Daniel; Dobry, Jason; Vandewege, Michael W; Li, Qing; Schott, Ryan K; Kapusta, Aurlie; Minx, Patrick; Feschotte, Cdric; 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. PMID:24297902

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

    PubMed

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

    2009-01-01

    Thirty-nine healthy boid snakes representing six different species (Python regius, Boa constrictor, Python reticulatus, Morelia viridis, Epicrates cenchria, and Morelia spilota) were examined using computed tomography (CT) to characterize the normal appearance of the respiratory tissue. Assessment was done subjectively and densitometry was performed using a defined protocol. The length of the right lung was calculated to be 11.1% of the body length, without a significant difference between species. The length of the left lung in proportion to the right was dependent on the species examined. The most developed left lung was in P. regius (81.2%), whereas in B. constrictor, the left lung was vestigial or absent (24.7%). A median attenuation of -814.6 HU and a variability of 45.9 HU were calculated for all species with no significant difference between species. Within the species, a significantly higher attenuation was found for P. regius in the dorsal and cranial aspect of the lung compared with the ventral and caudal part. In B. constrictor, the reduced left lung was significantly hyperattenuating compared with the right lung. Results of this study emphasize the value of CT and provide basic reference data for assessment of the snake lung in these species. Veterinary Radiology & PMID:19788032

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

    PubMed Central

    Pecevski, Dejan; Kappel, David; Jonke, Zeno

    2014-01-01

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

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

    PubMed

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

    2016-03-01

    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,1-3 it is only recently that unified approaches are emerging;4,5 however, workflows that, for example, aim to optimize search parameters or that employ cascaded style searches6 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,7 OMSSA,8 MS-GF+,9 Myrimatch,10 MS Amanda11), statistical postprocessing algorithms (qvality,12 Percolator13), and one algorithm that combines statistically postprocessed outputs from multiple search engines ("combined FDR"14) 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",14 PeptideShaker,2 and Bayes' theorem. PMID:26709623

  15. 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.

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

    PubMed

    Pecevski, Dejan; Kappel, David; Jonke, Zeno

    2014-01-01

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

  17. A python analytical pipeline to identify prohormone precursors and predict prohormone cleavage sites.

    PubMed

    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

  18. A Python package for parsing, validating, mapping and formatting sequence variants using HGVS nomenclature

    PubMed Central

    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

  19. A Python Analytical Pipeline to Identify Prohormone Precursors and Predict Prohormone Cleavage Sites

    PubMed Central

    Southey, Bruce R.; Sweedler, Jonathan V.; Rodriguez-Zas, Sandra L.

    2008-01-01

    Neuropeptides and hormones are signaling molecules that support cellcell 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

  20. Structural flexibility of the intestine of Burmese python in response to feeding.

    PubMed

    Starck, J M; Beese, K

    2001-01-01

    The small intestine of Burmese pythons, Python molurus bivittatus, undergoes a remarkable size increase shortly after feeding. We studied the dynamics, reversibility and repeatability of organ size changes using noninvasive imaging techniques. We employed light and electron microscopy, flow cytometry and immunohistology to study the cytological mechanisms that drive the size changes of the small intestine. Within 2 days of feeding, the size of the small intestine increased to up to three times the fasting value. The size changes were fully reversible and could be elicited repeatedly by feeding. These enormous size changes were possible because the mucosal epithelium of the small intestine is a transitional epithelium that allows for considerable size changes without cell proliferation. Histological evidence suggested that a fluid pressure-pump system (lymphatic, blood pressure) was the driving force that inflated the intestinal villi. The rates of cell proliferation were not elevated immediately after feeding but peaked 1 week later when small intestine size was already declining. In contrast to the current paradigm, we suggest that the small intestine is not part of the previously proposed 'pay-before-pumping' model. Instead, the size of the python's small intestine may be upregulated without major metabolic investment. It can occur even if the individual is energetically exhausted. An evolutionary perspective of the transitional epithelium mechanism suggests superior functionality compared with the pay-before-pumping model because it allows for long periods of fasting and depletion of energy reserves, while still enabling the snake to digest prey and absorb nutrients. PMID:11136618

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

    PubMed

    Rst, Hannes L; Schmitt, Uwe; Aebersold, Ruedi; Malmstrm, 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). PMID:24420968

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

    NASA Astrophysics Data System (ADS)

    Starn, J. J.

    2013-12-01

    Particle tracking often is used to generate particle-age distributions that are used as impulse-response functions in convolution. A typical application is to produce groundwater solute breakthrough curves (BTC) at endpoint receptors such as pumping wells or streams. The commonly used semi-analytical particle-tracking algorithm based on the assumption of linear velocity gradients between opposing cell faces is computationally very fast when used in combination with finite-difference models. However, large gradients near pumping wells in regional-scale groundwater-flow models often are not well represented because of cell-size limitations. This leads to inaccurate velocity fields, especially at weak sinks. Accurate analytical solutions for velocity near a pumping well are available, and various boundary conditions can be imposed using image-well theory. Python can be used to embed these solutions into existing semi-analytical particle-tracking codes, thereby maintaining the integrity and quality-assurance of the existing code. Python (and associated scientific computational packages NumPy, SciPy, and Matplotlib) is an effective tool because of its wide ranging capability. Python text processing allows complex and database-like manipulation of model input and output files, including binary and HDF5 files. High-level functions in the language include ODE solvers to solve first-order particle-location ODEs, Gaussian kernel density estimation to compute smooth particle-age distributions, and convolution. The highly vectorized nature of NumPy arrays and functions minimizes the need for computationally expensive loops. A modular Python code base has been developed to compute BTCs using embedded analytical solutions at pumping wells based on an existing well-documented finite-difference groundwater-flow simulation code (MODFLOW) and a semi-analytical particle-tracking code (MODPATH). The Python code base is tested by comparing BTCs with highly discretized synthetic steady-flow finite-difference transport simulations (MT3DMS). Results show more accurate simulation of pumping-well BTCs for a given grid cell size when using analytical solutions. The code base is extended to transient flow and BTCs are compared to results from MT3DMS simulations. Results show the particle-based solutions can resolve transient behavior using coarser model grids with far less computational effort than MT3DMS. The effect of simulation accuracy on parameter estimates (porosity) also is investigated. Porosity estimated using more accurate analytical solutions are less biased than in synthetic finite-difference transport simulations, which tend to be biased by coarseness of the grid. Eliminating the bias by using a finer grid comes at the expense of much larger computational effort. Finally, the code base was applied to an actual groundwater-flow model of Salt Lake Valley, Utah. Particle simulations using the Python code base compare well with finite-difference simulations, but with less computational effort, and have the added advantage of delineating flow paths, thus explicitly connecting solute source areas with receptors, and producing complete particle-age distributions. Knowledge of source areas and age distribution greatly enhances the analysis of dissolved solids data in Salt Lake Valley.

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

    SciTech Connect

    Sainio, J.

    2012-04-01

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

  4. 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.

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

    NASA Astrophysics Data System (ADS)

    Hughes, J. D.; White, J.

    2013-12-01

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

  6. 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.

  7. 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.

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

    NASA Astrophysics Data System (ADS)

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

    2009-12-01

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

  9. 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/.

  10. 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.

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

    PubMed

    Starck, J Matthias

    2009-06-01

    Brightness-modulated ultrasonography, continuous-wave Doppler, and pulsed-wave Doppler-echocardiography were used to analyze the functional morphology of the undisturbed heart of ball pythons. In particular, the action of the muscular ridge and the atrio-ventricular valves are key features to understand how patterns of blood flow emerge from structures directing blood into the various chambers of the heart. A step-by-step image analysis of echocardiographs shows that during ventricular diastole, the atrio-ventricular valves block the interventricular canals so that blood from the right atrium first fills the cavum venosum, and blood from the left atrium fills the cavum arteriosum. During diastole, blood from the cavum venosum crosses the muscular ridge into the cavum pulmonale. During middle to late systole the muscular ridge closes, thus prohibiting further blood flow into the cavum pulmonale. At the same time, the atrio-ventricular valves open the interventricular canal and allow blood from the cavum arteriosum to flow into the cavum venosum. In the late phase of ventricular systole, all blood from the cavum pulmonale is pressed into the pulmonary trunk; all blood from the cavum venosum is pressed into both aortas. Quantitative measures of blood flow volume showed that resting snakes bypass the pulmonary circulation and shunt about twice the blood volume into the systemic circulation as into the pulmonary circulation. When digesting, the oxygen demand of snakes increased tremendously. This is associated with shunting more blood into the pulmonary circulation. The results of this study allow the presentation of a detailed functional model of the python heart. They are also the basis for a functional hypothesis of how shunting is achieved. Further, it was shown that shunting is an active regulation process in response to changing demands of the organism (here, oxygen demand). Finally, the results of this study support earlier reports about a dual pressure circulation in Python regius. PMID:19097161

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

    PubMed Central

    Alstott, Jeff; Bullmore, Ed; Plenz, Dietmar

    2014-01-01

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

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

    PubMed Central

    2014-01-01

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

  14. 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, Queens 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 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. Restrictions: Problems must meet the criteria for using the master equation in Lindblad, Floquet-Markov, or Bloch-Redfield form. Running time: A few seconds up to several tens of hours, depending on size of the underlying Hilbert space.

  15. Digesting pythons quickly oxidize the proteins in their meals and save the lipids for later.

    PubMed

    McCue, Marshall D; Guzman, R Marena; Passement, Celeste A

    2015-07-01

    Pythons digesting rodent meals exhibit up to 10-fold increases in their resting metabolic rate (RMR); this increase in RMR is termed specific dynamic action (SDA). Studies have shown that SDA is partially fueled by oxidizing dietary nutrients, yet it remains unclear whether the proteins and the lipids in their meals contribute equally to this energy demand. We raised two populations of mice on diets labeled with either [(13)C]leucine or [(13)C]palmitic acid to intrinsically enrich the proteins and lipids in their bodies, respectively. Ball pythons (Python regius) were fed whole mice (and pureed mice 3weeks later), after which we measured their metabolic rates and the ?(13)C in the breath. The ?(13)C values in the whole bodies of the protein- and lipid-labeled mice were generally similar (i.e. 5.74.7 and 2.85.4, respectively) but the oxidative kinetics of these two macronutrient pools were quite different. We found that the snakes oxidized 5% of the protein and only 0.24% of the lipids in their meals within 14?days. Oxidation of the dietary proteins peaked 24?h after ingestion, at which point these proteins provided ?90% of the metabolic requirement of the snakes, and by 14?days the oxidation of these proteins decreased to nearly zero. The oxidation of the dietary lipids peaked 1day later, at which point these lipids supplied ?25% of the energy demand. Fourteen days after ingestion, these lipids were still being oxidized and continued to account for ?25% of the metabolic rate. Pureeing the mice reduced the cost of gastric digestion and decreased SDA by 24%. Pureeing also reduced the oxidation of dietary proteins by 43%, but it had no effect on the rates of dietary lipid oxidation. Collectively, these results demonstrate that pythons are able to effectively partition the two primary metabolic fuels in their meals. This approach of uniquely labeling the different components of the diet will allow researchers to examine new questions about how and when animals use the nutrients in their meals. PMID:25987734

  16. 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, Queens 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 coordinates from the Python interface, and to return the forces and energy that are used to integrate the equations of motion. Restrictions: This code only deals with distinguishable particles. It does not include fermonic or bosonic exchanges between equivalent nuclei, which can become important at very low temperatures. Running time: Depends dramatically on the nature of the simulation being performed. A few minutes for short tests with empirical force fields, up to several weeks for production calculations with ab initio forces. The examples provided with the code run in less than an hour.

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

    NASA Astrophysics Data System (ADS)

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

    2014-01-01

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

  18. Python-based framework for coupled MC-TH reactor calculations

    NASA Astrophysics Data System (ADS)

    Travleev, Anton A.; Molitor, Richard; Sanchez, Victor

    2014-06-01

    We develop a set of Python packages to provide a modern programming interface to codes used for analysis of nuclear reactors. Currently implemented interfaces to the Monte Carlo (MC) neutronics code MCNP and thermo-hydraulic (TH) code SCF allow efficient description of calculation models and provide a framework for coupled calculations. In this paper we illustrate how these interfaces can be used to describe a pin model, and report results of coupled MCNP-SCF calculations performed for a PWR fuel assembly, organized by means of the interfaces.

  19. A Python-based GUI Software to Calculate Times of Maximum and Minimum: Xtrema

    NASA Astrophysics Data System (ADS)

    Bahar, E.; enavc?, H. V.; Ba?trk, .

    2015-07-01

    We develop a python-based GUI code, Xtrema, that can be used for calculating the times of minimum for eclipsing binary systems as well as the maxima of pulsating stars. Xtrema performs minimum/maximum time determination from multi-cycle light curves (i.e., 1000) such as from Kepler/CoRoT data, using different methods, and also provides error estimates. Despite the coarse sampling rate of the long cadence Kepler data, Xtrema can be used to determine reliable times of minimum/maximum by combining successive minimum/maximum profiles as defined by the user.

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

    PubMed Central

    Wiseman, Richard; Watt, Caroline

    2015-01-01

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

  1. 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.

  2. TelluSim: A Python Plug-in Based Computational Framework for Spatially Distributed Environmental and Earth Sciences Modelling

    NASA Astrophysics Data System (ADS)

    Willgoose, G. R.

    2008-12-01

    TelluSim is a python-based computational framework for integrating and manipulating modules written in a variety of computer languages. TelluSim consists of a main program that dynamically, at run time, assembles a series of modules. These modules can be written in any language that can be accessed by Python. Currently we have modules in Fortran and Python, with C to be supported soon. New modules are incorporated as plug-ins like done for a browser or Photoshop, simply by copying the module binary into a plug-in directory. TelluSim automatically generates a GUI for parameter and state I/O, and automatically creates the intermodule communication mechanisms needed for the computations. A decision to use Python was arrived at after detailed trials using other languages including C, Tcl/Tk and Fortran. An important aspect of the design of TelluSim was to minimise the overhead in interfacing the modules with TelluSim, and minimise any requirement for recoding of existing software, so eliminating a major disadvantage of more complex frameworks (e.g. JAMS, openMI). Several significant Fortran codes developed by the author have been incorporated as part of the design process and as proof of concept. In particular the SIBERIA landform evolution code (a high performance F90 code, including parallel capability) has been broken up into a series of TelluSim modules, so that the SIBERIA now consists of a Python script of 20 lines. These 20 lines assemble and run the underlying modules (about 50,000 lines of Fortran code). The presentation will discuss in more detail the design of TelluSim, and our experiences of the advantages and disadvantages of using Python relative to other approaches.

  3. cloudPEST - A python module for cloud-computing deployment of PEST, a program for parameter estimation

    USGS Publications Warehouse

    Fienen, Michael N.; Kunicki, Thomas C.; Kester, Daniel E.

    2011-01-01

    This report documents cloudPEST-a Python module with functions to facilitate deployment of the model-independent parameter estimation code PEST on a cloud-computing environment. cloudPEST makes use of low-level, freely available command-line tools that interface with the Amazon Elastic Compute Cloud (EC2(TradeMark)) that are unlikely to change dramatically. This report describes the preliminary setup for both Python and EC2 tools and subsequently describes the functions themselves. The code and guidelines have been tested primarily on the Windows(Registered) operating system but are extensible to Linux(Registered).

  4. Pyff – A Pythonic Framework for Feedback Applications and Stimulus Presentation in Neuroscience

    PubMed Central

    Venthur, Bastian; Scholler, Simon; Williamson, John; Dähne, Sven; Treder, Matthias S.; Kramarek, Maria T.; Müller, Klaus-Robert; Blankertz, Benjamin

    2010-01-01

    This paper introduces Pyff, the Pythonic feedback framework for feedback applications and stimulus presentation. Pyff provides a platform-independent framework that allows users to develop and run neuroscientific experiments in the programming language Python. Existing solutions have mostly been implemented in C++, which makes for a rather tedious programming task for non-computer-scientists, or in Matlab, which is not well suited for more advanced visual or auditory applications. Pyff was designed to make experimental paradigms (i.e., feedback and stimulus applications) easily programmable. It includes base classes for various types of common feedbacks and stimuli as well as useful libraries for external hardware such as eyetrackers. Pyff is also equipped with a steadily growing set of ready-to-use feedbacks and stimuli. It can be used as a standalone application, for instance providing stimulus presentation in psychophysics experiments, or within a closed loop such as in biofeedback or brain–computer interfacing experiments. Pyff communicates with other systems via a standardized communication protocol and is therefore suitable to be used with any system that may be adapted to send its data in the specified format. Having such a general, open-source framework will help foster a fruitful exchange of experimental paradigms between research groups. In particular, it will decrease the need of reprogramming standard paradigms, ease the reproducibility of published results, and naturally entail some standardization of stimulus presentation. PMID:21160550

  5. PylotDB - A Database Management, Graphing, and Analysis Tool Written in Python

    Energy Science and Technology Software Center (ESTSC)

    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 acrossmore » different databases as well as across different servers; extract information from any field to create new fields; generate, edit, and delete databases, tables, and fields; generate or read into a table CSV data; and similar operations. Since much of the database information is brought under control of the Python computer language, PylotDB is not intended for huge databases for which MySQL and Oracle, for example, are better suited. PylotDB is better suited for smaller databases that might be typically needed in a small research group situation. PylotDB can also be used as a learning tool for database applications in general.« less

  6. PylotDB - A Database Management, Graphing, and Analysis Tool Written in Python

    SciTech Connect

    2012-01-04

    PylotDB, written completely in Python, provides a user interface (UI) with which to interact with, analyze, graph data from, and manage open source databases such as MySQL. The UI mitigates the user having to know in-depth knowledge of the database application programming interface (API). PylotDB allows the user to generate various kinds of plots from user-selected data; generate statistical information on text as well as numerical fields; backup and restore databases; compare database tables across different databases as well as across different servers; extract information from any field to create new fields; generate, edit, and delete databases, tables, and fields; generate or read into a table CSV data; and similar operations. Since much of the database information is brought under control of the Python computer language, PylotDB is not intended for huge databases for which MySQL and Oracle, for example, are better suited. PylotDB is better suited for smaller databases that might be typically needed in a small research group situation. PylotDB can also be used as a learning tool for database applications in general.

  7. PyMVPA: A Python toolbox for multivariate pattern analysis of fMRI data

    PubMed Central

    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

  8. Pyemu: A Python-Based Framework for Linear-Based Model Uncertainty Analysis

    NASA Astrophysics Data System (ADS)

    White, J.

    2014-12-01

    pyEMU is an open-source python-based framework for model-independent linear-based parameter and predictive uncertainty analysis. The framework is designed to support the analysis of high-dimensional inverse problems that have thousands of parameters and hundreds of thousands of observations. The code is compatible with the PEST and PEST++ software suite, and implements several forms of linear analysis equations, such as Schur's complement for conditional uncertainty propagation and subspace error variance, including a form of error variance analysis of model structural error. These linear analysis equations are the most common and also the most applicable to large-scale environmental models. Several native python operators (such as multiplication, subtraction, addition, exponentiation) have been overloaded to make equation building more concise as well as to achieve speedup with operations involving diagonal matrices. To help ensure pyEMU is intuitive and easy to use, emphasis was placed on flexibility and concise object instantiation. As a result, several types of arguments can be handled elegantly.

  9. A multi-model Python wrapper for operational oil spill transport forecasts

    NASA Astrophysics Data System (ADS)

    Hou, X.; Hodges, B. R.; Negusse, S.; Barker, C.

    2015-01-01

    The Hydrodynamic and oil spill modeling system for Python (HyosPy) is presented as an example of a multi-model wrapper that ties together existing models, web access to forecast data and visualization techniques as part of an adaptable operational forecast system. The system is designed to automatically run a continual sequence of hindcast/forecast hydrodynamic models so that multiple predictions of the time-and-space-varying velocity fields are already available when a spill is reported. Once the user provides the estimated spill parameters, the system runs multiple oil spill prediction models using the output from the hydrodynamic models. As new wind and tide data become available, they are downloaded from the web, used as forcing conditions for a new instance of the hydrodynamic model and then applied to a new instance of the oil spill model. The predicted spill trajectories from multiple oil spill models are visualized through Python methods invoking Google MapTM and Google EarthTM functions. HyosPy is designed in modules that allow easy future adaptation to new models, new data sources or new visualization tools.

  10. Using Python to generate AHPS-based precipitation simulations over CONUS using Amazon distributed computing

    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.

  11. PyMVPA: A python toolbox for multivariate pattern analysis of fMRI data.

    PubMed

    Hanke, Michael; Halchenko, Yaroslav O; Sederberg, Per B; Hanson, Stephen José; Haxby, James V; Pollmann, Stefan

    2009-01-01

    Decoding patterns of neural activity onto cognitive states is one of the central goals of functional brain imaging. Standard univariate fMRI analysis methods, which correlate cognitive and perceptual function with the blood oxygenation-level dependent (BOLD) signal, have proven successful in identifying anatomical regions based on signal increases during cognitive and perceptual tasks. Recently, researchers have begun to explore new multivariate techniques that have proven to be more flexible, more reliable, and more sensitive than standard univariate analysis. Drawing on the field of statistical learning theory, these new classifier-based analysis techniques possess explanatory power that could provide new insights into the functional properties of the brain. However, unlike the wealth of software packages for univariate analyses, there are few packages that facilitate multivariate pattern classification analyses of fMRI data. Here we introduce a Python-based, cross-platform, and open-source software toolbox, called PyMVPA, for the application of classifier-based analysis techniques to fMRI datasets. PyMVPA makes use of Python's ability to access libraries written in a large variety of programming languages and computing environments to interface with the wealth of existing machine learning packages. We present the framework in this paper and provide illustrative examples on its usage, features, and programmability. PMID:19184561

  12. Pyff - a pythonic framework for feedback applications and stimulus presentation in neuroscience.

    PubMed

    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

  13. Species identification of protected carpet pythons suitable for degraded forensic samples.

    PubMed

    Ciavaglia, Sherryn; Donnellan, Stephen; Henry, Julianne; Linacre, Adrian

    2014-09-01

    In this paper we report on the identification of a section of mitochondrial DNA that can be used to identify the species of protected and illegally traded pythons of the genus Morelia. Successful enforcement of wildlife laws requires forensic tests that can identify the species nominated in the relevant legislation. The potentially degraded state of evidentiary samples requires that forensic investigation using molecular genetic species identification is optimized to interrogate small fragments of DNA. DNA was isolated from 35 samples of Morelia spilota from which the complete cytochrome b was sequenced. The ND6 gene was also sequenced in 32 of these samples. Additional DNA sequences were generated from 9 additional species of Morelia. The sequences were aligned by Geneious and imported into MEGA to create phylogenetic trees based on the entire complex of approximately 1,706 base pairs (bp). To mimic degraded DNA, which is usually found in forensic cases, short sub-sections of the full alignment were used to generate phylogenetic trees. The sub-sections that had the greatest DNA sequence information were in parts of the cytochrome b gene. Our results highlight that legislation is presently informed by inadequate taxonomy. We demonstrated that a 278 bp region of the cytochrome b gene recovered the topology of the phylogenetic tree found with the entire gene sequence and correctly identified species of Morelia with a high degree of confidence. The locus described in this report will assist in the successful prosecution of alleged illegal trade in python species. PMID:24915762

  14. Low cost of gastric acid secretion during digestion in ball pythons.

    PubMed

    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 25gbonemealkg(-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. PMID:26802791

  15. Automatic Parallelization of Numerical Python Applications using the Global Arrays Toolkit

    SciTech Connect

    Daily, Jeffrey A.; Lewis, Robert R.

    2011-11-30

    Global Arrays is a software system from Pacific Northwest National Laboratory that enables an efficient, portable, and parallel shared-memory programming interface to manipulate distributed dense arrays. The NumPy module is the de facto standard for numerical calculation in the Python programming language, a language whose use is growing rapidly in the scientific and engineering communities. NumPy provides a powerful N-dimensional array class as well as other scientific computing capabilities. However, like the majority of the core Python modules, NumPy is inherently serial. Using a combination of Global Arrays and NumPy, we have reimplemented NumPy as a distributed drop-in replacement called Global Arrays in NumPy (GAiN). Serial NumPy applications can become parallel, scalable GAiN applications with only minor source code changes. Scalability studies of several different GAiN applications will be presented showing the utility of developing serial NumPy codes which can later run on more capable clusters or supercomputers.

  16. Python for Development of OpenMP and CUDA Kernels for Multidimensional Data

    SciTech Connect

    Bell, Zane W; Davidson, Gregory G; D'Azevedo, Ed F; Evans, Thomas M; Joubert, Wayne; Munro Jr, John K; Patlolla, Dilip Reddy; Vacaliuc, Bogdan

    2011-01-01

    Design of data structures for high performance computing (HPC) is one of the principal challenges facing researchers looking to utilize heterogeneous computing machinery. Heterogeneous systems derive cost, power, and speed efficiency by being composed of the appropriate hardware for the task. Yet, each type of processor requires a specific organization of the application state in order to achieve peak performance. Discovering this and refactoring the code can be a challenging and time-consuming task for the researcher, as the data structures and the computational model must be co-designed. We present a methodology that uses Python as the environment for which to explore tradeoffs in both the data structure design as well as the code executing on the computation accelerator. Our method enables multi-dimensional arrays to be used effectively in any target environment. We have chosen to focus on OpenMP and CUDA environments, thus exploring the development of optimized kernels for the two most common classes of computing hardware available today: multi-core CPU and GPU. Python s large palette of file and network access routines, its associative indexing syntax and support for common HPC environments makes it relevant for diverse hardware ranging from laptops through computing clusters to the highest performance supercomputers. Our work enables researchers to accelerate the development of their codes on the computing hardware of their choice.

  17. Effects of temperature on the metabolic response to feeding in Python molurus.

    PubMed

    Wang, Tobias; Zaar, Morten; Arvedsen, Sine; Vedel-Smith, Christina; Overgaard, Johannes

    2002-11-01

    As ectothermic vertebrates, reptiles undergo diurnal and seasonal changes in body temperature, which affect many biological functions. In conjunction with a general review regarding the effects of temperature on digestion in reptiles, we describe the effects of various temperatures (20-35 degrees C) on the metabolic response to digestion in the Burmese python (Python molurus). The snakes were fed mice amounting to 20% of their body weight and gas exchange (oxygen uptake and CO(2) production) were measured until digestion had ended and gas exchange returned to fasting levels. Elevated temperature was associated with a faster and larger metabolic increase after ingestion, and the time required to return to fasting levels was markedly longer at low temperature. The factorial increase between fasting oxygen consumption (VO(2)) and maximal VO(2) during digestion was, however, similar at all temperatures studied. Furthermore, the integrated SDA response was not affected by temperature suggesting the costs associated with digestion are temperature-independent. Other studies on reptiles show that digestive efficiency is only marginally affected by temperature and we conclude that selection of higher body temperatures during digestion (postprandial thermophilic response) primarily reduces the time required for digestion. PMID:12443910

  18. An ecological risk assessment of nonnative boas and pythons as potentially invasive species in the United States.

    PubMed

    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. PMID:16022706

  19. Whole transcriptome analysis of the fasting and fed Burmese python heart: insights into extreme physiological cardiac adaptation

    PubMed Central

    Wall, Christopher E.; Cozza, Steven; Riquelme, Cecilia A.; McCombie, W. Richard; Heimiller, Joseph K.; Marr, Thomas G.

    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. PMID:21045117

  20. SUPPRESSION OF BLOOD FEEDING BY OCHLEROTATUS DORSALIS AND OCHLEROTATUS MELANIMON (DIPTERA: CULICIDAE) ON CATTLE TREATED WITH PYTHON EAR TAGS

    Technology Transfer Automated Retrieval System (TEKTRAN)

    Adult mosquitoes were collected by drop traps to compare blood feeding rates between cattle treated with 2 Python ear tags (10% zeta cypermethrin and 20% piperonyl butoxide) per animal and animals that were untreated. Mosquitoes were collected both 2 and 4 weeks after application of the ear tags. ...

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

    PubMed Central

    Hunter, Margaret E.; Hart, Kristen M.

    2013-01-01

    Invasive species represent an increasing threat to native ecosystems, harming indigenous taxa through predation, habitat modification, cross-species hybridization and alteration of ecosystem processes. Additionally, high economic costs are associated with environmental damage, restoration and control measures. The Burmese python, Python molurus bivittatus, is one of the most notable invasive species in the US, due to the threat it poses to imperiled species and the Greater Everglades ecosystem. To address population structure and relatedness, next generation sequencing was used to rapidly produce species-specific microsatellite loci. The Roche 454 GS-FLX Titanium platform provided 6616 di-, tri- and tetra-nucleotide repeats in 117,516 sequences. Using stringent criteria, 24 of 26 selected tri- and tetra-nucleotide loci were polymerase chain reaction (PCR) amplified and 18 were polymorphic. An additional six cross-species loci were amplified, and the resulting 24 loci were incorporated into eight PCR multiplexes. Multi-locus genotypes yielded an average of 61% (39%–77%) heterozygosity and 3.7 (2–6) alleles per locus. Population-level studies using the developed microsatellites will track the invasion front and monitor population-suppression dynamics. Additionally, cross-species amplification was detected in the invasive Ball, P. regius, and Northern African python, P. sebae. These markers can be used to address the hybridization potential of Burmese pythons and the larger, more aggressive P. sebae. PMID:23449030

  2. Whole transcriptome analysis of the fasting and fed Burmese python heart: insights into extreme physiological cardiac adaptation.

    PubMed

    Wall, Christopher E; Cozza, Steven; Riquelme, Cecilia A; McCombie, W Richard; Heimiller, Joseph K; Marr, Thomas G; Leinwand, Leslie A

    2011-01-01

    The infrequently feeding Burmese python (Python molurus) experiences significant and rapid postprandial cardiac hypertrophy followed by regression as digestion is completed. To begin to explore the molecular mechanisms of this response, we have sequenced and assembled the fasted and postfed Burmese python heart transcriptomes with Illumina technology using the chicken (Gallus gallus) genome as a reference. In addition, we have used RNA-seq analysis to identify differences in the expression of biological processes and signaling pathways between fasted, 1 day postfed (DPF), and 3 DPF hearts. Out of a combined transcriptome of ?2,800 mRNAs, 464 genes were differentially expressed. Genes showing differential expression at 1 DPF compared with fasted were enriched for biological processes involved in metabolism and energetics, while genes showing differential expression at 3 DPF compared with fasted were enriched for processes involved in biogenesis, structural remodeling, and organization. Moreover, we present evidence for the activation of physiological and not pathological signaling pathways in this rapid, novel model of cardiac growth in pythons. Together, our data provide the first comprehensive gene expression profile for a reptile heart. PMID:21045117

  3. SpacePy - a Python-based library of tools for the space sciences

    SciTech Connect

    Morley, Steven K; Welling, Daniel T; Koller, Josef; Larsen, Brian A; Henderson, Michael G

    2010-01-01

    Space science deals with the bodies within the solar system and the interplanetary medium; the primary focus is on atmospheres and above - at Earth the short timescale variation in the the geomagnetic field, the Van Allen radiation belts and the deposition of energy into the upper atmosphere are key areas of investigation. SpacePy is a package for Python, targeted at the space sciences, that aims to make basic data analysis, modeling and visualization easier. It builds on the capabilities of the well-known NumPy and MatPlotLib packages. Publication quality output direct from analyses is emphasized. The SpacePy project seeks to promote accurate and open research standards by providing an open environment for code development. In the space physics community there has long been a significant reliance on proprietary languages that restrict free transfer of data and reproducibility of results. By providing a comprehensive, open-source library of widely used analysis and visualization tools in a free, modern and intuitive language, we hope that this reliance will be diminished. SpacePy includes implementations of widely used empirical models, statistical techniques used frequently in space science (e.g. superposed epoch analysis), and interfaces to advanced tools such as electron drift shell calculations for radiation belt studies. SpacePy also provides analysis and visualization tools for components of the Space Weather Modeling Framework - currently this only includes the BATS-R-US 3-D magnetohydrodynamic model and the RAM ring current model - including streamline tracing in vector fields. Further development is currently underway. External libraries, which include well-known magnetic field models, high-precision time conversions and coordinate transformations are wrapped for access from Python using SWIG and f2py. The rest of the tools have been implemented directly in Python. The provision of open-source tools to perform common tasks will provide openness in the analysis methods employed in scientific studies and will give access to advanced tools to all space scientists regardless of affiliation or circumstance.

  4. 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. Weingartner, and M. F. P. Bierkens, "Global monthly water stress: II. water demand and severity of water," Water Resources Research, vol. 47, 2011.

  5. Escript: Open Source Environment For Solving Large-Scale Geophysical Joint Inversion Problems in Python

    NASA Astrophysics Data System (ADS)

    Gross, Lutz; Altinay, Cihan; Fenwick, Joel; Smith, Troy

    2014-05-01

    The program package escript has been designed for solving mathematical modeling problems using python, see Gross et al. (2013). Its development and maintenance has been funded by the Australian Commonwealth to provide open source software infrastructure for the Australian Earth Science community (recent funding by the Australian Geophysical Observing System EIF (AGOS) and the AuScope Collaborative Research Infrastructure Scheme (CRIS)). The key concepts of escript are based on the terminology of spatial functions and partial differential equations (PDEs) - an approach providing abstraction from the underlying spatial discretization method (i.e. the finite element method (FEM)). This feature presents a programming environment to the user which is easy to use even for complex models. Due to the fact that implementations are independent from data structures simulations are easily portable across desktop computers and scalable compute clusters without modifications to the program code. escript has been successfully applied in a variety of applications including modeling mantel convection, melting processes, volcanic flow, earthquakes, faulting, multi-phase flow, block caving and mineralization (see Poulet et al. 2013). The recent escript release (see Gross et al. (2013)) provides an open framework for solving joint inversion problems for geophysical data sets (potential field, seismic and electro-magnetic). The strategy bases on the idea to formulate the inversion problem as an optimization problem with PDE constraints where the cost function is defined by the data defect and the regularization term for the rock properties, see Gross & Kemp (2013). This approach of first-optimize-then-discretize avoids the assemblage of the - in general- dense sensitivity matrix as used in conventional approaches where discrete programming techniques are applied to the discretized problem (first-discretize-then-optimize). In this paper we will discuss the mathematical framework for inversion and appropriate solution schemes in escript. We will also give a brief introduction into escript's open framework for defining and solving geophysical inversion problems. Finally we will show some benchmark results to demonstrate the computational scalability of the inversion method across a large number of cores and compute nodes in a parallel computing environment. References: - L. Gross et al. (2013): Escript Solving Partial Differential Equations in Python Version 3.4, The University of Queensland, https://launchpad.net/escript-finley - L. Gross and C. Kemp (2013) Large Scale Joint Inversion of Geophysical Data using the Finite Element Method in escript. ASEG Extended Abstracts 2013, http://dx.doi.org/10.1071/ASEG2013ab306 - T. Poulet, L. Gross, D. Georgiev, J. Cleverley (2012): escript-RT: Reactive transport simulation in Python using escript, Computers & Geosciences, Volume 45, 168-176. http://dx.doi.org/10.1016/j.cageo.2011.11.005.

  6. libNeuroML and PyLEMS: using Python to combine procedural and declarative modeling approaches in computational neuroscience

    PubMed Central

    Vella, Michael; Cannon, Robert C.; Crook, Sharon; Davison, Andrew P.; Ganapathy, Gautham; Robinson, Hugh P. C.; Silver, R. Angus; Gleeson, Padraig

    2014-01-01

    NeuroML is an XML-based model description language, which provides a powerful common data format for defining and exchanging models of neurons and neuronal networks. In the latest version of NeuroML, the structure and behavior of ion channel, synapse, cell, and network model descriptions are based on underlying definitions provided in LEMS, a domain-independent language for expressing hierarchical mathematical models of physical entities. While declarative approaches for describing models have led to greater exchange of model elements among software tools in computational neuroscience, a frequent criticism of XML-based languages is that they are difficult to work with directly. Here we describe two Application Programming Interfaces (APIs) written in Python (http://www.python.org), which simplify the process of developing and modifying models expressed in NeuroML and LEMS. The libNeuroML API provides a Python object model with a direct mapping to all NeuroML concepts defined by the NeuroML Schema, which facilitates reading and writing the XML equivalents. In addition, it offers a memory-efficient, array-based internal representation, which is useful for handling large-scale connectomics data. The libNeuroML API also includes support for performing common operations that are required when working with NeuroML documents. Access to the LEMS data model is provided by the PyLEMS API, which provides a Python implementation of the LEMS language, including the ability to simulate most models expressed in LEMS. Together, libNeuroML and PyLEMS provide a comprehensive solution for interacting with NeuroML models in a Python environment. PMID:24795618

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

    SciTech Connect

    Barker, Z D

    2008-08-14

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

  8. FragBuilder: an efficient Python library to setup quantum chemistry calculations on peptides models

    PubMed Central

    Hamelryck, Thomas; Jensen, Jan H.

    2014-01-01

    We present a powerful Python library to quickly and efficiently generate realistic peptide model structures. The library makes it possible to quickly set up quantum mechanical calculations on model peptide structures. It is possible to manually specify a specific conformation of the peptide. Additionally the library also offers sampling of backbone conformations and side chain rotamer conformations from continuous distributions. The generated peptides can then be geometry optimized by the MMFF94 molecular mechanics force field via convenient functions inside the library. Finally, it is possible to output the resulting structures directly to files in a variety of useful formats, such as XYZ or PDB formats, or directly as input files for a quantum chemistry program. FragBuilder is freely available at https://github.com/jensengroup/fragbuilder/ under the terms of the BSD open source license. PMID:24688855

  9. The adaptive significance of ontogenetic colour change in a tropical python.

    PubMed

    Wilson, David; Heinsohn, Robert; Endler, John A

    2007-02-22

    Ontogenetic colour change is typically associated with changes in size, vulnerability or habitat, but assessment of its functional significance requires quantification of the colour signals from the receivers' perspective. The tropical python, Morelia viridis, is an ideal species to establish the functional significance of ontogenetic colour change. Neonates hatch either yellow or red and both the morphs change to green with age. Here, we show that colour change from red or yellow to green provides camouflage from visually oriented avian predators in the different habitats used by juveniles and adults. This reflects changes in foraging behaviour and vulnerability as individuals mature and provides a rare demonstration of the adaptive value of ontogenetic colour change. PMID:17443961

  10. 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.

  11. uPy: a ubiquitous computer graphics Python API with Biological Modeling Applications

    PubMed Central

    Autin, L.; Johnson, G.; Hake, J.; Olson, A.; Sanner, M.

    2015-01-01

    In this paper we describe uPy, an extension module for the Python programming language that provides a uniform abstraction of the APIs of several 3D computer graphics programs called hosts, including: Blender, Maya, Cinema4D, and DejaVu. A plugin written with uPy is a unique piece of code that will run in all uPy-supported hosts. We demonstrate the creation of complex plug-ins for molecular/cellular modeling and visualization and discuss how uPy can more generally simplify programming for many types of projects (not solely science applications) intended for multi-host distribution. uPy is available at http://upy.scripps.edu PMID:24806987

  12. TEMPy: a Python library for assessment of three-dimensional electron microscopy density fits

    PubMed Central

    Farabella, Irene; Vasishtan, Daven; Joseph, Agnel Praveen; Pandurangan, Arun Prasad; Sahota, Harpal; Topf, Maya

    2015-01-01

    Three-dimensional electron microscopy is currently one of the most promising techniques used to study macromolecular assemblies. Rigid and flexible fitting of atomic models into density maps is often essential to gain further insights into the assemblies they represent. Currently, tools that facilitate the assessment of fitted atomic models and maps are needed. TEMPy (template and electron microscopy comparison using Python) is a toolkit designed for this purpose. The library includes a set of methods to assess density fits in intermediate-to-low resolution maps, both globally and locally. It also provides procedures for single-fit assessment, ensemble generation of fits, clustering, and multiple and consensus scoring, as well as plots and output files for visualization purposes to help the user in analysing rigid and flexible fits. The modular nature of TEMPy helps the integration of scoring and assessment of fits into large pipelines, making it a tool suitable for both novice and expert structural biologists. PMID:26306092

  13. PySLHA: a Pythonic interface to SUSY Les Houches Accord data

    NASA Astrophysics Data System (ADS)

    Buckley, Andy

    2015-10-01

    This paper describes the PySLHA package, a Python language module and program collection for reading, writing and visualising SUSY model data in the SLHA format. PySLHA can read and write SLHA data in a very general way, including the official SLHA2 extension and user customisations, and with arbitrarily deep indexing of data block entries and a dedicated, intuitive interface for particle data and decay information. The draft SLHA3 XSECTION feature is also fully supported. PySLHA can additionally read and write the legacy ISAWIG model format, and provides format conversion scripts. A publication-quality mass spectrum and decay chain plotting tool, slhaplot, is included in the package.

  14. Modular Toolkit for Data Processing (MDP): A Python Data Processing Framework.

    PubMed

    Zito, Tiziano; Wilbert, Niko; Wiskott, Laurenz; Berkes, Pietro

    2008-01-01

    Modular toolkit for Data Processing (MDP) is a data processing framework written in Python. From the user's perspective, MDP is a collection of supervised and unsupervised learning algorithms and other data processing units that can be combined into data processing sequences and more complex feed-forward network architectures. Computations are performed efficiently in terms of speed and memory requirements. From the scientific developer's perspective, MDP is a modular framework, which can easily be expanded. The implementation of new algorithms is easy and intuitive. The new implemented units are then automatically integrated with the rest of the library. MDP has been written in the context of theoretical research in neuroscience, but it has been designed to be helpful in any context where trainable data processing algorithms are used. Its simplicity on the user's side, the variety of readily available algorithms, and the reusability of the implemented units make it also a useful educational tool. PMID:19169361

  15. uPy: a ubiquitous CG Python API with biological-modeling applications.

    PubMed

    Autin, Ludovic; Johnson, Graham; Hake, Johan; Olson, Arthur; Sanner, Michel

    2012-01-01

    The uPy Python extension module provides a uniform abstraction of the APIs of several 3D computer graphics programs (called hosts), including Blender, Maya, Cinema 4D, and DejaVu. A plug-in written with uPy can run in all uPy-supported hosts. Using uPy, researchers have created complex plug-ins for molecular and cellular modeling and visualization. uPy can simplify programming for many types of projects (not solely science applications) intended for multihost distribution. It's available at http://upy.scripps.edu. The first featured Web extra is a video that shows interactive analysis of a calcium dynamics simulation. YouTube URL: http://youtu.be/wvs-nWE6ypo. The second featured Web extra is a video that shows rotation of the HIV virus. YouTube URL: http://youtu.be/vEOybMaRoKc. PMID:24806987

  16. Radio Astronomy Tools in Python: Spectral-cube, pvextractor, and more

    NASA Astrophysics Data System (ADS)

    Ginsburg, A.; Robitaille, T.; Beaumont, C.; Rosolowsky, E.; Leroy, A.; Brogan, C.; Hunter, T.; Teuben, P.; Brisbin, D.

    2015-12-01

    The radio-astro-tools organization has been established to facilitate development of radio and millimeter analysis tools by the scientific community. The first packages developed under its umbrella are: • The spectral-cube package, for reading, writing, and analyzing spectral data cubes • The pvextractor package for extracting position-velocity slices from position-position-velocity cubes along aribitrary paths • The radio-beam package to handle gaussian beams in the context of the astropy quantity and unit framework • casa-python to enable installation of these packages - and any other - into users' CASA environments without conflicting with the underlying CASA package. Community input in the form of code contributions, suggestions, questions and commments is welcome on all of these tools. They can all be found at http://radio-astro-tools.github.io.

  17. Heavy Analysis and Light Virtualization of Water Use Data with Python

    NASA Astrophysics Data System (ADS)

    Kim, H.; Bijoor, N.; Famiglietti, J. S.

    2014-12-01

    Water utilities possess a large amount of water data that could be used to inform urban ecohydrology, management decisions, and conservation policies, but such data are rarely analyzed owing to difficulty in analyzation, visualization, and interpretion. We have developed a high performance computing resource for this purpose. We partnered with 6 water agencies in Orange County who provided 10 years of parcel-level monthly water use billing data for a pilot study. The first challenge that we overcame was to refine all human errors and unify the many different formats of data over all agencies. Second, we tested and applied experimental approaches to the data, including complex calculations, with high efficiency. Third, we developed a method to refine the data so it can be browsed along a time series index and/or geo-spatial queries with high efficiency, no matter how large the data. Python scientific libraries were the best match to handle arbitrary data sets in our environment. Further milestones include agency entry, sets of formulae, and maintaining 15M rows X 70 columns of data with high performance of cpu-bound processes. To deal with billions of rows, we performed an analysis virtualization stack by leveraging iPython parallel computing. With this architecture, one agency could be considered one computing node or virtual machine that maintains its own data sets respectively. For example, a big agency could use a large node, and a small agency could use a micro node. Under the minimum required raw data specs, more agencies could be analyzed. The program developed in this study simplifies data analysis, visualization, and interpretation of large water datasets, and can be used to analyze large data volumes from water agencies nationally or worldwide.

  18. 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.

  19. morphforge: a toolbox for simulating small networks of biologically detailed neurons in Python.

    PubMed

    Hull, Michael J; Willshaw, David J

    2013-01-01

    The broad structure of a modeling study can often be explained over a cup of coffee, but converting this high-level conceptual idea into graphs of the final simulation results may require many weeks of sitting at a computer. Although models themselves can be complex, often many mental resources are wasted working around complexities of the software ecosystem such as fighting to manage files, interfacing between tools and data formats, finding mistakes in code or working out the units of variables. morphforge is a high-level, Python toolbox for building and managing simulations of small populations of multicompartmental biophysical model neurons. An entire in silico experiment, including the definition of neuronal morphologies, channel descriptions, stimuli, visualization and analysis of results can be written within a single short Python script using high-level objects. Multiple independent simulations can be created and run from a single script, allowing parameter spaces to be investigated. Consideration has been given to the reuse of both algorithmic and parameterizable components to allow both specific and stochastic parameter variations. Some other features of the toolbox include: the automatic generation of human-readable documentation (e.g., PDF files) about a simulation; the transparent handling of different biophysical units; a novel mechanism for plotting simulation results based on a system of tags; and an architecture that supports both the use of established formats for defining channels and synapses (e.g., MODL files), and the possibility to support other libraries and standards easily. We hope that this toolbox will allow scientists to quickly build simulations of multicompartmental model neurons for research and serve as a platform for further tool development. PMID:24478690

  20. PySP : modeling and solving stochastic mixed-integer programs in Python.

    SciTech Connect

    Woodruff, David L.; Watson, Jean-Paul

    2010-08-01

    Although stochastic programming is a powerful tool for modeling decision-making under uncertainty, various impediments have historically prevented its widespread use. One key factor involves the ability of non-specialists to easily express stochastic programming problems as extensions of deterministic models, which are often formulated first. A second key factor relates to the difficulty of solving stochastic programming models, particularly the general mixed-integer, multi-stage case. Intricate, configurable, and parallel decomposition strategies are frequently required to achieve tractable run-times. We simultaneously address both of these factors in our PySP software package, which is part of the COIN-OR Coopr open-source Python project for optimization. To formulate a stochastic program in PySP, the user specifies both the deterministic base model and the scenario tree with associated uncertain parameters in the Pyomo open-source algebraic modeling language. Given these two models, PySP provides two paths for solution of the corresponding stochastic program. The first alternative involves writing the extensive form and invoking a standard deterministic (mixed-integer) solver. For more complex stochastic programs, we provide an implementation of Rockafellar and Wets Progressive Hedging algorithm. Our particular focus is on the use of Progressive Hedging as an effective heuristic for approximating general multi-stage, mixed-integer stochastic programs. By leveraging the combination of a high-level programming language (Python) and the embedding of the base deterministic model in that language (Pyomo), we are able to provide completely generic and highly configurable solver implementations. PySP has been used by a number of research groups, including our own, to rapidly prototype and solve difficult stochastic programming problems.

  1. A new species of Hepatozoon (Apicomplexa: Adeleorina) from Python regius (Serpentes: Pythonidae) and its experimental transmission by a mosquito vector.

    PubMed

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

    2007-10-01

    Hepatozoon ayorgbor n. sp. is described from specimens of Python regius imported from Ghana. Gametocytes were found in the peripheral blood of 43 of 55 snakes examined. Localization of gametocytes was mainly inside the erythrocytes; free gametocytes were found in 15 (34.9%) positive specimens. Infections of laboratory-reared Culex quinquefasciatus feeding on infected snakes, as well as experimental infection of juvenile Python regius by ingestion of infected mosquitoes, were performed to complete the life cycle. Similarly, transmission to different snake species (Boa constrictor and Lamprophis fuliginosus) and lizards (Lepidodactylus lugubris) was performed to assess the host specificity. Isolates were compared with Hepatozoon species from sub-Saharan reptiles and described as a new species based on the morphology, phylogenetic analysis, and a complete life cycle. PMID:18163356

  2. VarPy: A python library for volcanology and rock physics data analysis

    NASA Astrophysics Data System (ADS)

    Filgueira, Rosa; Atkinson, Malcom; Bell, Andrew; Snelling, Brawen; Main, Ian

    2014-05-01

    The increasing prevalence of digital instrumentation in volcanology and rock physics is leading to a wealth of data, which in turn is increasing the need for computational analyses and models. Today, these are largely developed by each individual or researcher. The introduction of a shared library that can be used for this purpose has several benefits: 1. when an existing function in the library meets a need recognised by a researcher it is usually much less effort than developing ones own code; 2. once functions are established and multiply used they become better tested, more reliable and eventually trusted by the community; 3. use of the same functions by different researchers makes it easier to compare results and to compare the skill of rival analysis and modelling methods; and 4. in the longer term the cost of maintaining these functions is shared over a wide community and they therefore have greater duration. Python is a high-level interpreted programming language, with capabilities for object-oriented programming. Often scientists choose this language to program their programs because of the increased productivity it provides. Although, there are many software tools available for interactive data analysis and development, there are not libraries designed specifically for volcanology and rock physics data. Therefore, we propose a new Python open-source toolbox called "VarPy" to facilitate rapid application development for rock physicists and volcanologists, which allow users to define their own workflows to develop models, analyses and visualisations. This proposal is triggered by our work on data assimilation in the NERC EFFORT (Earthquake and Failure Forecasting in Real Time) project, using data provided by the NERC CREEP 2 experimental project and volcanic experiments from INVG observatory Etna and IGN observatory Hierro as a test cases. In EFFORT project we are developing a scientist gateway which offers services for collecting and sharing volcanology and rock physics data with the intent of stimulating sharing, collaboration and comparison of methods among the practitioners in the two fields. As such, it offers facilities for running analyses and models either under a researcher's control or periodically as part of an experiment and to compare the skills of predictive methods. The gateway therefore runs code on behalf of volcanology and rock physics researchers. Varpy library is intended to make it much easier for those researchers to set up the code they need to run. The library also makes it easier to arrange that code is in a form suitable for running in the EFFORT computational services. Care has been taken to ensure that the library can also be used outside of EFFORT systems, e.g., on a researcher's own laptop, providing two variants of the library: the gateway version and developer's version, with many of the functions completely identical. The library must fulfill two purposes simultaneously: • by providing a full repertoire of commonly required actions it must make it easy for volcanologist and rock physicists to write the python scripts they need to accomplish their work, and • by wrapping operations it must enable the EFFORT gateway to maintain the integrity of its data. Notice that proposal of VarPy library does not attempt to replace the functions provided by other libraries, such as NumpY and ScipY. VarPy is complementary to them.

  3. Python Processing and Version Control using VisTrails for the Netherlands Hydrological Instrument (Invited)

    NASA Astrophysics Data System (ADS)

    Verkaik, J.

    2013-12-01

    The Netherlands Hydrological Instrument (NHI) model predicts water demands in periods of drought, supporting the Dutch decision makers in taking operational as well as long-term decisions with respect to the water supply. Other applications of NHI are predicting fresh-salt interaction, nutrient loadings, and agriculture change. The NHI model consists of several coupled models: a saturated groundwater model (MODFLOW), an unsaturated groundwater model (MetaSWAP), a sub-catchment surface water model (MOZART), and a distribution network of surface waters model (DM/SOBEK). Each of these models requires specific, usually large, input data that may be the result of sophisticated schematization workflows. Input data can also be dependent on each other, for example, the precipitation data is input for the unsaturated zone model (cells) as well as for the surface water models (polygons). For efficient data management, we developed several Python tools such that the modeler or stakeholder can use the model in a user-friendly manner, and data is managed in a consistent, transparent and reproducible way. Two open source Python tools are presented here: the data version control module for the workflow manager VisTrails called FileSync, and the NHI model control script that uses FileSync. VisTrails is an open-source scientific workflow and provenance management system that provides support for simulations, data exploration and visualization. Since VisTrails does not directly support version control we developed a version control module called FileSync. With this generic module, the user can synchronize data from and to his workflow through a dialog window. The FileSync dialog calls the FileSync script that is command-line based and performs the actual data synchronization. This script allows the user to easily create a model repository, upload and download data, create releases and define scenarios. The data synchronization approach applied here differs from systems as Subversion or Git, since these systems do not perform well for large (binary) model data files. For this reason, a new concept of parameterization and data splitting has been implemented. Each file, or set of files, is uniquely labeled as a parameter, and for this parameter metadata is maintained by Subversion. The metadata data contains file hashes to identify data content and the location where the actual bulk data are stored that can be reached by FTP. The NHI model control script is a command-line driven Python script for pre-processing, running, and post-processing the NHI model and uses one single configuration file for all computational kernels. This configuration file is an easy-to-use, keyword-driven, Windows INI-file, having separate sections for all the kernels. It also includes a FileSync data section where the user can specify version controlled model data to be used as input. The NHI control script keeps all the data consistent during the pre-processing. Furthermore, this script is able to do model state handling when the NHI model is used for ensemble forecasting.

  4. Distribution of dopamine immunoreactivity in the forebrain and midbrain of the snake Python regius: a study with antibodies against dopamine.

    PubMed

    Smeets, W J

    1988-05-01

    The distribution of dopamine (DA) immunoreactivity in the forebrain and midbrain of the ball python, Python regius, was studied by using recently developed antibodies against DA. In order to determine general and species-specific features of the DA system in reptiles, we have selected the ball python as a representative of a reptilian radiation that hitherto has not been the subject of (immuno)histochemical studies. Dopamine-containing cell bodies were found around the glomeruli and in the external plexiform layer of both the main and accessory olfactory bulb, but not in the telencephalon proper. In the diencephalon, DA cells were observed in several parts of the periventricular hypothalamic nucleus, in the periventricular organ, the ependymal wall of the infundibular recess, the lateral hypothalamic area, the magnocellular ventrolateral thalamic nucleus, and the pretectal posterodorsal nucleus. In the midbrain, DA cells were found in the ventral tegmental area, the substantia nigra, and the presumed reptilian homologue of the mammalian A8 cell group. Dopaminergic fibers and varicosities were observed throughout the whole brain, particularly in the telencephalon and diencephalon. The nucleus accumbens, striatum, olfactory tubercle, and nucleus of the accessory olfactory tract appear to have the most dense innervation, but the lateral septal nucleus, the dorsal ventricular ridge, and the nucleus sphericus also show numerous DA-containing fibers and varicosities. Except for the lateral cortex, cortical areas are not densely innervated by DA fibers. The DA system of the snake Python regius shares many features with that of lizards and turtles as determined with the same antibodies. The taxonomically close relationship between lizards and snakes, which together constitute the Squamata, is reflected in a similar distribution of DA fibers and varicosities to the dorsal ventricular ridge and the lateral cortex, and in the limited number of CSF-contacting DA neurons in the hypothalamus. PMID:3385007

  5. Large-scale automated image analysis for computational profiling of brain tissue surrounding implanted neuroprosthetic devices using Python

    PubMed Central

    Rey-Villamizar, Nicolas; Somasundar, Vinay; Megjhani, Murad; Xu, Yan; Lu, Yanbin; Padmanabhan, Raghav; Trett, Kristen; Shain, William; Roysam, Badri

    2014-01-01

    In this article, we describe the use of Python for large-scale automated server-based bio-image analysis in FARSIGHT, a free and open-source toolkit of image analysis methods for quantitative studies of complex and dynamic tissue microenvironments imaged by modern optical microscopes, including confocal, multi-spectral, multi-photon, and time-lapse systems. The core FARSIGHT modules for image segmentation, feature extraction, tracking, and machine learning are written in C++, leveraging widely used libraries including ITK, VTK, Boost, and Qt. For solving complex image analysis tasks, these modules must be combined into scripts using Python. As a concrete example, we consider the problem of analyzing 3-D multi-spectral images of brain tissue surrounding implanted neuroprosthetic devices, acquired using high-throughput multi-spectral spinning disk step-and-repeat confocal microscopy. The resulting images typically contain 5 fluorescent channels. Each channel consists of 6000 10,000 500 voxels with 16 bits/voxel, implying image sizes exceeding 250 GB. These images must be mosaicked, pre-processed to overcome imaging artifacts, and segmented to enable cellular-scale feature extraction. The features are used to identify cell types, and perform large-scale analysis for identifying spatial distributions of specific cell types relative to the device. Python was used to build a server-based script (Dell 910 PowerEdge servers with 4 sockets/server with 10 cores each, 2 threads per core and 1TB of RAM running on Red Hat Enterprise Linux linked to a RAID 5 SAN) capable of routinely handling image datasets at this scale and performing all these processing steps in a collaborative multi-user multi-platform environment. Our Python script enables efficient data storage and movement between computers and storage servers, logs all the processing steps, and performs full multi-threaded execution of all codes, including open and closed-source third party libraries. PMID:24808857

  6. What parts of the US mainland are climatically suitable for invasive alien pythons spreading from Everglades National Park?

    USGS Publications Warehouse

    Rodda, G.H.; Jarnevich, C.S.; Reed, R.N.

    2009-01-01

    The Burmese Python (Python molurus bivittatus) is now well established in southern Florida and spreading northward. The factors likely to limit this spread are unknown, but presumably include climate or are correlated with climate. We compiled monthly rainfall and temperature statistics from 149 stations located near the edge of the python's native range in Asia (Pakistan east to China and south to Indonesia). The southern and eastern native range limits extend to saltwater, leaving unresolved the species' climatic tolerances in those areas. The northern and western limits are associated with cold and aridity respectively. We plotted mean monthly rainfall against mean monthly temperature for the 149 native range weather stations to identify the climate conditions inhabited by pythons in their native range, and mapped areas of the coterminous United States with the same climate today and projected for the year 2100. We accounted for both dry-season aestivation and winter hibernation (under two scenarios of hibernation duration). The potential distribution was relatively insensitive to choice of scenario for hibernation duration. US areas climatically matched at present ranged up the coasts and across the south from Delaware to Oregon, and included most of California, Texas, Oklahoma, Arkansas, Louisiana, Mississippi, Alabama, Florida, Georgia, and South and North Carolina. By the year 2100, projected areas of potential suitable climate extend northward beyond the current limit to include parts of the states of Washington, Colorado, Illinois, Indiana, Ohio, West Virginia, Pennsylvania, New Jersey, and New York. Thus a substantial portion of the mainland US is potentially vulnerable to this ostensibly tropical invader. ?? 2008 Springer Science+Business Media B.V.

  7. Large-scale automated image analysis for computational profiling of brain tissue surrounding implanted neuroprosthetic devices using Python.

    PubMed

    Rey-Villamizar, Nicolas; Somasundar, Vinay; Megjhani, Murad; Xu, Yan; Lu, Yanbin; Padmanabhan, Raghav; Trett, Kristen; Shain, William; Roysam, Badri

    2014-01-01

    In this article, we describe the use of Python for large-scale automated server-based bio-image analysis in FARSIGHT, a free and open-source toolkit of image analysis methods for quantitative studies of complex and dynamic tissue microenvironments imaged by modern optical microscopes, including confocal, multi-spectral, multi-photon, and time-lapse systems. The core FARSIGHT modules for image segmentation, feature extraction, tracking, and machine learning are written in C++, leveraging widely used libraries including ITK, VTK, Boost, and Qt. For solving complex image analysis tasks, these modules must be combined into scripts using Python. As a concrete example, we consider the problem of analyzing 3-D multi-spectral images of brain tissue surrounding implanted neuroprosthetic devices, acquired using high-throughput multi-spectral spinning disk step-and-repeat confocal microscopy. The resulting images typically contain 5 fluorescent channels. Each channel consists of 6000 × 10,000 × 500 voxels with 16 bits/voxel, implying image sizes exceeding 250 GB. These images must be mosaicked, pre-processed to overcome imaging artifacts, and segmented to enable cellular-scale feature extraction. The features are used to identify cell types, and perform large-scale analysis for identifying spatial distributions of specific cell types relative to the device. Python was used to build a server-based script (Dell 910 PowerEdge servers with 4 sockets/server with 10 cores each, 2 threads per core and 1TB of RAM running on Red Hat Enterprise Linux linked to a RAID 5 SAN) capable of routinely handling image datasets at this scale and performing all these processing steps in a collaborative multi-user multi-platform environment. Our Python script enables efficient data storage and movement between computers and storage servers, logs all the processing steps, and performs full multi-threaded execution of all codes, including open and closed-source third party libraries. PMID:24808857

  8. Uncertainty quantification of surface-water/groundwater exchange estimates in large wetland systems using Python

    NASA Astrophysics Data System (ADS)

    Hughes, J. D.; Metz, P. A.

    2014-12-01

    Most watershed studies include observation-based water budget analyses to develop first-order estimates of significant flow terms. Surface-water/groundwater (SWGW) exchange is typically assumed to be equal to the residual of the sum of inflows and outflows in a watershed. These estimates of SWGW exchange, however, are highly uncertain as a result of the propagation of uncertainty inherent in the calculation or processing of the other terms of the water budget, such as stage-area-volume relations, and uncertainties associated with land-cover based evapotranspiration (ET) rate estimates. Furthermore, the uncertainty of estimated SWGW exchanges can be magnified in large wetland systems that transition from dry to wet during wet periods. Although it is well understood that observation-based estimates of SWGW exchange are uncertain it is uncommon for the uncertainty of these estimates to be directly quantified. High-level programming languages like Python can greatly reduce the effort required to (1) quantify the uncertainty of estimated SWGW exchange in large wetland systems and (2) evaluate how different approaches for partitioning land-cover data in a watershed may affect the water-budget uncertainty. We have used Python with the Numpy, Scipy.stats, and pyDOE packages to implement an unconstrained Monte Carlo approach with Latin Hypercube sampling to quantify the uncertainty of monthly estimates of SWGW exchange in the Floral City watershed of the Tsala Apopka wetland system in west-central Florida, USA. Possible sources of uncertainty in the water budget analysis include rainfall, ET, canal discharge, and land/bathymetric surface elevations. Each of these input variables was assigned a probability distribution based on observation error or spanning the range of probable values. The Monte Carlo integration process exposes the uncertainties in land-cover based ET rate estimates as the dominant contributor to the uncertainty in SWGW exchange estimates. We will discuss the uncertainty of SWGW exchange estimates using an ET model that partitions the watershed into open water and wetland land-cover types. We will also discuss the uncertainty of SWGW exchange estimates calculated using ET models partitioned into additional land-cover types.

  9. FMC: a one-liner Python program to manage, classify and plot focal mechanisms

    NASA Astrophysics Data System (ADS)

    lvarez-Gmez, Jos A.

    2014-05-01

    The analysis of earthquake focal mechanisms (or Seismic Moment Tensor, SMT) is a key tool on seismotectonics research. Each focal mechanism is characterized by several location parameters of the earthquake hypocenter, the earthquake size (magnitude and scalar moment tensor) and some geometrical characteristics of the rupture (nodal planes orientations, SMT components and/or SMT main axes orientations). The aim of FMC is to provide a simple but powerful tool to manage focal mechanism data. The data should be input to the program formatted as one of two of the focal mechanisms formatting options of the GMT (Generic Mapping Tools) package (Wessel and Smith, 1998): the Harvard CMT convention and the single nodal plane Aki and Richards (1980) convention. The former is a SMT format that can be downloaded directly from the Global CMT site (http://www.globalcmt.org/), while the later is the simplest way to describe earthquake rupture data. FMC is programmed in Python language, which is distributed as Open Source GPL-compatible, and therefore can be used to develop Free Software. Python runs on almost any machine, and has a wide support and presence in any operative system. The program has been conceived with the modularity and versatility of the classical UNIX-like tools. Is called from the command line and can be easily integrated into shell scripts (*NIX systems) or batch files (DOS/Windows systems). The program input and outputs can be done by means of ASCII files or using standard input (or redirection "<"), standard output (screen or redirection ">") and pipes ("|"). By default FMC will read the input and write the output as a Harvard CMT (psmeca formatted) ASCII file, although other formats can be used. Optionally FMC will produce a classification diagram representing the rupture type of the focal mechanisms processed. In order to count with a detailed classification of the focal mechanisms I decided to classify the focal mechanism in a series of fields that include the oblique slip regimes. This approximation is similar to the Johnston et al. (1994) classification; with 7 classes of earthquakes: 1) Normal; 2) Normal - Strike-slip; 3) Strike-slip - Normal; 4) Strike-slip; 5) Strike-slip - Reverse; 6) Reverse - strike-slip and 7) Reverse. FMC uses by default this classification in the resulting diagram, based on the Kaverina et al. (1996) projection, which improves the Frohlich and Apperson (1992) ternary diagram.

  10. Python tools for rapid development, calibration, and analysis of generalized groundwater-flow models

    NASA Astrophysics Data System (ADS)

    Starn, J. J.; Belitz, K.

    2014-12-01

    National-scale water-quality data sets for the United States have been available for several decades; however, groundwater models to interpret these data are available for only a small percentage of the country. Generalized models may be adequate to explain and project groundwater-quality trends at the national scale by using regional scale models (defined as watersheds at or between the HUC-6 and HUC-8 levels). Coast-to-coast data such as the National Hydrologic Dataset Plus (NHD+) make it possible to extract the basic building blocks for a model anywhere in the country. IPython notebooks have been developed to automate the creation of generalized groundwater-flow models from the NHD+. The notebook format allows rapid testing of methods for model creation, calibration, and analysis. Capabilities within the Python ecosystem greatly speed up the development and testing of algorithms. GeoPandas is used for very efficient geospatial processing. Raster processing includes the Geospatial Data Abstraction Library and image processing tools. Model creation is made possible through Flopy, a versatile input and output writer for several MODFLOW-based flow and transport model codes. Interpolation, integration, and map plotting included in the standard Python tool stack also are used, making the notebook a comprehensive platform within on to build and evaluate general models. Models with alternative boundary conditions, number of layers, and cell spacing can be tested against one another and evaluated by using water-quality data. Novel calibration criteria were developed by comparing modeled heads to land-surface and surface-water elevations. Information, such as predicted age distributions, can be extracted from general models and tested for its ability to explain water-quality trends. Groundwater ages then can be correlated with horizontal and vertical hydrologic position, a relation that can be used for statistical assessment of likely groundwater-quality conditions. Convolution with age distributions can be used to quickly ascertain likely future water-quality conditions. Although these models are admittedly very general and are still being tested, the hope is that they will be useful for answering questions related to water quality at the regional scale.

  11. Increased blood oxygen affinity during digestion in the snake Python molurus.

    PubMed

    Overgaard, Johannes; Wang, Tobias

    2002-11-01

    Many snakes exhibit large increases in metabolic rate during digestion that place extensive demands on efficient oxygen transport. In the present study, we describe blood oxygen affinity following three weeks of fasting and 48 h after feeding in the Burmese python (Python molurus). We also report simultaneous measurements of arterial blood gases and haematological parameters. Arterial blood was obtained from chronically implanted catheters, and blood oxygen-dissociation curves were constructed from oxygen content measurements at known oxygen partial pressure (P(O(2))) values at 2% and 5% CO(2). Arterial pH remained constant at approximately 7.6 after feeding, but digestion was associated with an approximately 6 mmol l(-1) increase in [HCO(3)(-)], while CO(2) partial pressure (P(CO(2))) increased from 2.21+/-0.13 kPa in fasted animals to 2.89+/-0.17 kPa at 48 h after feeding. Blood oxygen affinity in vivo was predicted on the basis of pH in vivo and the blood oxygen-dissociation curves obtained in vitro. The blood oxygen affinity in vivo increased during digestion, with P(50) values decreasing from 4.58+/-0.11 kPa to 3.53+/-0.24 kPa. This increase was associated with a significant decrease in the red blood cell [NTP]/[Hb(4)] ratio (relationship between the concentrations of organic phosphates and total haemoglobin) and a significant decrease in mean cellular haemoglobin content, which is indicative of swelling of the red blood cells. Our data for blood oxygen affinity and arterial oxygen levels, together with previously published values of oxygen uptake and blood flows, allow for a quantitative evaluation of oxygen transport during digestion. This analysis shows that a large part of the increased metabolism during digestion is supported by an increased venous extraction, while arterial P(O(2)) (Pa(O(2))) and haemoglobin saturation do not vary with digestive status. Thus, we predict that venous P(O(2)) (Pv(O(2))) is reduced from a fasting value of 5.2 kPa to 1.6 kPa during digestion. PMID:12324542

  12. Using the Python language and the CMOR2 library to create PMIPn-CMIPn compliant model output

    NASA Astrophysics Data System (ADS)

    Peterschmitt, Jean-Yves; Doutriaux, Charles

    2015-04-01

    The Paleoclimate Modelling Intercomparison Project (PMIP) is a long standing initiative that has provided an efficient mechanism for coordinating paleoclimate modelling activities that provide valuable information on the mechanisms of climate change, the identification of key feedbacks operating in the climate system and, through model evaluation, the capability of climate models to reproduce climates different from today. The third phase of PMIP (aka PMIP 3) started in 2009 (the fourth phase is about to start) and followed the requirements specified by CMIP5 (Coupled Model Intercomparison Project). Generating data files following strict Model Intercomparison Projects (MIPs) standards (NetCDF format, file and variable names, file structure, metadata information, directory hierarchy, etc…) has been a key to the success of many recent Model Intercomparison Projects. It is unfortunately not always easy to convert proprietary model output format to the required standards, and this has prevented some smaller modelling groups from sharing their data. We will present how the Python version of the CMOR2 (Climate Model Output Rewriter) library bundled with the UV-CDAT Python distribution (Ultrascale Visualization Climate Data Analysis Tools) can be used to easily convert raw model output to the appropriate MIP shareable format. References: http://pmip3.lsce.ipsl.fr/ http://cmip-pcmdi.llnl.gov/cmip5/output_req.html http://www2-pcmdi.llnl.gov/cmor http://uvcdat.llnl.gov/ https://www.python.org/

  13. Open-Source Python Modules to Estimate Level Ice Thickness from Ice Charts

    NASA Astrophysics Data System (ADS)

    Geiger, C. A.; Deliberty, T. L.; Bernstein, E. R.; Helfrich, S.

    2012-12-01

    A collaborative research effort between the University of Delaware (UD) and National Ice Center (NIC) addresses the task of providing open-source translations of sea ice stage-of-development into level ice thickness estimates on a 4km grid for the Interactive Multisensor Snow and Ice Mapping System (IMS). The characteristics for stage-of-development are quantified from remote sensing imagery with estimates of level ice thickness categories originating from World Meteorological Organization (WMO) egg coded ice charts codified since the 1970s. Conversions utilize Python scripting modules which transform electronic ice charts with WMO egg code characteristics into five level ice thickness categories, in centimeters, (0-10, 10-30, 30-70, 70-120, >120cm) and five ice types (open water, first year pack ice, fast ice, multiyear ice, and glacial ice with a reserve slot for deformed ice fractions). Both level ice thickness categories and ice concentration fractions are reported with uncertainties propagated based on WMO ice stage ranges which serve as proxy estimates for standard deviation. These products are in preparation for use by NCEP, CMC, and NAVO by 2014 based on their modeling requirements for daily products in near-real time. In addition to development, continuing research tests the value of these estimated products against in situ observations to improve both value and uncertainty estimates.

  14. NIFTY - Numerical Information Field Theory. A versatile PYTHON library for signal inference

    NASA Astrophysics Data System (ADS)

    Selig, M.; Bell, M. R.; Junklewitz, H.; Oppermann, N.; Reinecke, M.; Greiner, M.; Pachajoa, C.; Enlin, T. A.

    2013-06-01

    NIFTy (Numerical Information Field Theory) is a software package designed to enable the development of signal inference algorithms that operate regardless of the underlying spatial grid and its resolution. Its object-oriented framework is written in Python, although it accesses libraries written in Cython, C++, and C for efficiency. NIFTy offers a toolkit that abstracts discretized representations of continuous spaces, fields in these spaces, and operators acting on fields into classes. Thereby, the correct normalization of operations on fields is taken care of automatically without concerning the user. This allows for an abstract formulation and programming of inference algorithms, including those derived within information field theory. Thus, NIFTy permits its user to rapidly prototype algorithms in 1D, and then apply the developed code in higher-dimensional settings of real world problems. The set of spaces on which NIFTy operates comprises point sets, n-dimensional regular grids, spherical spaces, their harmonic counterparts, and product spaces constructed as combinations of those. The functionality and diversity of the package is demonstrated by a Wiener filter code example that successfully runs without modification regardless of the space on which the inference problem is defined. NIFTy homepage http://www.mpa-garching.mpg.de/ift/nifty/; Excerpts of this paper are part of the NIFTy source code and documentation.

  15. MSNoise: a Python Package for Monitoring Seismic Velocity Changes using Ambient Seismic Noise

    NASA Astrophysics Data System (ADS)

    Lecocq, T.; Caudron, C.; Brenguier, F.

    2013-12-01

    Earthquakes occur every day all around the world and are recorded by thousands of seismic stations. In between earthquakes, stations are recording "noise". In the last 10 years, the understanding of this noise and its potential usage have been increasing rapidly. The method, called "seismic interferometry", uses the principle that seismic waves travel between two recorders and are multiple-scattered in the medium. By cross-correlating the two records, one gets an information on the medium below/between the stations. The cross-correlation function (CCF) is a proxy to the Green Function of the medium. Recent developments of the technique have shown those CCF can be used to image the earth at depth (3D seismic tomography) or study the medium changes with time. We present MSNoise, a complete software suite to compute relative seismic velocity changes under a seismic network, using ambient seismic noise. The whole is written in Python, from the monitoring of data archives, to the production of high quality figures. All steps have been optimized to only compute the necessary steps and to use 'job'-based processing. We present a validation of the software on a dataset acquired during the UnderVolc[1] project on the Piton de la Fournaise Volcano, La Réunion Island, France, for which precursory relative changes of seismic velocity are visible for three eruptions betwee 2009 and 2011.

  16. Phylogeographic analysis of the green python, Morelia viridis, reveals cryptic diversity.

    PubMed

    Rawlings, Lesley H; Donnellan, Stephen C

    2003-04-01

    Green pythons, which are regionally variable in colour patterns, are found throughout the lowland rainforest of New Guinea and adjacent far northeastern Australia. The species is popular in commercial trade and management of this trade and its impacts on natural populations could be assisted by molecular identification tools. We used mitochondrial nucleotide sequences and a limited allozyme data to test whether significantly differentiated populations occur within the species range. Phylogenetic analysis of mtDNA sequences revealed hierarchal phylogeographic structure both within New Guinea and between New Guinea and Australia. Strongly supported reciprocally monophyletic mitochondrial lineages, northern and southern, were found either side of the central mountain range that runs nearly the length of New Guinea. Limited allozyme data suggest that population differentiation is reflected in the nuclear as well as the mitochondrial genome. A previous morphological analysis did not find any phenotypic concordance with the pattern of differentiation observed in the molecular data. The southern mitochondrial lineage includes all of the Australian haplotypes, which form a single lineage, nested among the southern New Guinean haplotypes. PMID:12679069

  17. pyAudioAnalysis: An Open-Source Python Library for Audio Signal Analysis.

    PubMed

    Giannakopoulos, Theodoros

    2015-01-01

    Audio information plays a rather important role in the increasing digital content that is available today, resulting in a need for methodologies that automatically analyze such content: audio event recognition for home automations and surveillance systems, speech recognition, music information retrieval, multimodal analysis (e.g. audio-visual analysis of online videos for content-based recommendation), etc. This paper presents pyAudioAnalysis, an open-source Python library that provides a wide range of audio analysis procedures including: feature extraction, classification of audio signals, supervised and unsupervised segmentation and content visualization. pyAudioAnalysis is licensed under the Apache License and is available at GitHub (https://github.com/tyiannak/pyAudioAnalysis/). Here we present the theoretical background behind the wide range of the implemented methodologies, along with evaluation metrics for some of the methods. pyAudioAnalysis has been already used in several audio analysis research applications: smart-home functionalities through audio event detection, speech emotion recognition, depression classification based on audio-visual features, music segmentation, multimodal content-based movie recommendation and health applications (e.g. monitoring eating habits). The feedback provided from all these particular audio applications has led to practical enhancement of the library. PMID:26656189

  18. Publishing Earth Science Data with Python: A Case Study with Regional Climate Model Output

    NASA Astrophysics Data System (ADS)

    Green, G. M.; Tedesco, M.; Alexander, P. M.; Fettweis, X.; Datta, R.

    2014-12-01

    As datasets become larger, with the increasing spatial and temporal resolution of both observed and modeled data, the need to provide a service that makes them more accessible to the scientific community is increasing. At the same time, open-source tools are making more options available, but it can be difficult to determine what the viable alternatives are. In this presentation, we discuss a software architecture and data distribution model that was adopted to distribute the outputs of the regional climate model Modle Atmosphrique Rgional (MAR). This involved summarizing a large static dataset for ad-hoc query and data download in a web-based application called "MAR Explorer", and making the application available using a cloud-based Amazon server. The application was built using open-source Python tools, and is available at cryocity.org. We discuss the web application development tools and data processing methods used to distribute the above mentioned dataset, with the goal of making these methods more easily accessible to others needing to distribute similar data.

  19. Nengo: a Python tool for building large-scale functional brain models.

    PubMed

    Bekolay, Trevor; Bergstra, James; Hunsberger, Eric; Dewolf, Travis; Stewart, Terrence C; Rasmussen, Daniel; Choo, Xuan; Voelker, Aaron Russell; Eliasmith, Chris

    2014-01-01

    Neuroscience currently lacks a comprehensive theory of how cognitive processes can be implemented in a biological substrate. The Neural Engineering Framework (NEF) proposes one such theory, but has not yet gathered significant empirical support, partly due to the technical challenge of building and simulating large-scale models with the NEF. Nengo is a software tool that can be used to build and simulate large-scale models based on the NEF; currently, it is the primary resource for both teaching how the NEF is used, and for doing research that generates specific NEF models to explain experimental data. Nengo 1.4, which was implemented in Java, was used to create Spaun, the world's largest functional brain model (Eliasmith et al., 2012). Simulating Spaun highlighted limitations in Nengo 1.4's ability to support model construction with simple syntax, to simulate large models quickly, and to collect large amounts of data for subsequent analysis. This paper describes Nengo 2.0, which is implemented in Python and overcomes these limitations. It uses simple and extendable syntax, simulates a benchmark model on the scale of Spaun 50 times faster than Nengo 1.4, and has a flexible mechanism for collecting simulation results. PMID:24431999

  20. pyAudioAnalysis: An Open-Source Python Library for Audio Signal Analysis

    PubMed Central

    Giannakopoulos, Theodoros

    2015-01-01

    Audio information plays a rather important role in the increasing digital content that is available today, resulting in a need for methodologies that automatically analyze such content: audio event recognition for home automations and surveillance systems, speech recognition, music information retrieval, multimodal analysis (e.g. audio-visual analysis of online videos for content-based recommendation), etc. This paper presents pyAudioAnalysis, an open-source Python library that provides a wide range of audio analysis procedures including: feature extraction, classification of audio signals, supervised and unsupervised segmentation and content visualization. pyAudioAnalysis is licensed under the Apache License and is available at GitHub (https://github.com/tyiannak/pyAudioAnalysis/). Here we present the theoretical background behind the wide range of the implemented methodologies, along with evaluation metrics for some of the methods. pyAudioAnalysis has been already used in several audio analysis research applications: smart-home functionalities through audio event detection, speech emotion recognition, depression classification based on audio-visual features, music segmentation, multimodal content-based movie recommendation and health applications (e.g. monitoring eating habits). The feedback provided from all these particular audio applications has led to practical enhancement of the library. PMID:26656189

  1. A python-based docking program utilizing a receptor bound ligand shape: PythDock.

    PubMed

    Chung, Jae Yoon; Cho, Seung Joo; Hah, Jung-Mi

    2011-09-01

    PythDock is a heuristic docking program that uses Python programming language with a simple scoring function and a population based search engine. The scoring function considers electrostatic and dispersion/repulsion terms. The search engine utilizes a particle swarm optimization algorithm. A grid potential map is generated using the shape information of a bound ligand within the active site. Therefore, the searching area is more relevant to the ligand binding. To evaluate the docking performance of PythDock, two well-known docking programs (AutoDock and DOCK) were also used with the same data. The accuracy of docked results were measured by the difference of the ligand structure between x-ray structure, and docked pose, i.e., average root mean squared deviation values of the bound ligand were compared for fourteen protein-ligand complexes. Since the number of ligands' rotational flexibility is an important factor affecting the accuracy of a docking, the data set was chosen to have various degrees of flexibility. Although PythDock has a scoring function simpler than those of other programs (AutoDock and DOCK), our results showed that PythDock predicted more accurate poses than both AutoDock4.2 and DOCK6.2. This indicates that PythDock could be a useful tool to study ligand-receptor interactions and could also be beneficial in structure based drug design. PMID:21975806

  2. Nengo: a Python tool for building large-scale functional brain models

    PubMed Central

    Bekolay, Trevor; Bergstra, James; Hunsberger, Eric; DeWolf, Travis; Stewart, Terrence C.; Rasmussen, Daniel; Choo, Xuan; Voelker, Aaron Russell; Eliasmith, Chris

    2014-01-01

    Neuroscience currently lacks a comprehensive theory of how cognitive processes can be implemented in a biological substrate. The Neural Engineering Framework (NEF) proposes one such theory, but has not yet gathered significant empirical support, partly due to the technical challenge of building and simulating large-scale models with the NEF. Nengo is a software tool that can be used to build and simulate large-scale models based on the NEF; currently, it is the primary resource for both teaching how the NEF is used, and for doing research that generates specific NEF models to explain experimental data. Nengo 1.4, which was implemented in Java, was used to create Spaun, the world's largest functional brain model (Eliasmith et al., 2012). Simulating Spaun highlighted limitations in Nengo 1.4's ability to support model construction with simple syntax, to simulate large models quickly, and to collect large amounts of data for subsequent analysis. This paper describes Nengo 2.0, which is implemented in Python and overcomes these limitations. It uses simple and extendable syntax, simulates a benchmark model on the scale of Spaun 50 times faster than Nengo 1.4, and has a flexible mechanism for collecting simulation results. PMID:24431999

  3. The Integrated Plasma Simulator: A Flexible Python Framework for Coupled Multiphysics Simulation

    SciTech Connect

    Foley, Samantha S; Elwasif, Wael R; Bernholdt, David E

    2011-11-01

    High-fidelity coupled multiphysics simulations are an increasingly important aspect of computational science. In many domains, however, there has been very limited experience with simulations of this sort, therefore research in coupled multiphysics often requires computational frameworks with significant flexibility to respond to the changing directions of the physics and mathematics. This paper presents the Integrated Plasma Simulator (IPS), a framework designed for loosely coupled simulations of fusion plasmas. The IPS provides users with a simple component architecture into which a wide range of existing plasma physics codes can be inserted as components. Simulations can take advantage of multiple levels of parallelism supported in the IPS, and can be controlled by a high-level ``driver'' component, or by other coordination mechanisms, such as an asynchronous event service. We describe the requirements and design of the framework, and how they were implemented in the Python language. We also illustrate the flexibility of the framework by providing examples of different types of simulations that utilize various features of the IPS.

  4. Analysis and Visualization of Multi-Scale Astrophysical Simulations using Python and NumPy

    SciTech Connect

    Turk, M.; /KIPAC, Menlo Park

    2008-09-30

    The study the origins of cosmic structure requires large-scale computer simulations beginning with well-constrained, observationally-determined, initial conditions. We use Adaptive Mesh Refinement to conduct multi-resolution simulations spanning twelve orders of magnitude in spatial dimensions and over twenty orders of magnitude in density. These simulations must be analyzed and visualized in a manner that is fast, accurate, and reproducible. I present 'yt,' a cross-platform analysis toolkit written in Python. 'yt' consists of a data-management layer for transporting and tracking simulation outputs, a plotting layer, a parallel analysis layer for handling mesh-based and particle-based data, as well as several interfaces. I demonstrate how the origins of cosmic structure--from the scale of clusters of galaxies down to the formation of individual stars--can be analyzed and visualized using a NumPy-based toolkit. Additionally, I discuss efforts to port this analysis code to other adaptive mesh refinement data formats, enabling direct comparison of data between research groups using different methods to simulate the same objects.

  5. Magnetic resonance imaging volumetry for noninvasive measures of phenotypic flexibility during digestion in Burmese pythons.

    PubMed

    Hansen, Kasper; Pedersen, Pil Birkefeldt Mller; Pedersen, Michael; Wang, Tobias

    2013-01-01

    Pythons are renowned for the profound phenotypical flexibility of their visceral organs in response to ingestion of large meals following prolonged fasting. Traditionally, the phenotypic changes are studied by determining organ mass of snakes killed at different times during digestion. Here we evaluate the use of magnetic resonance imaging (MRI) for in vivo measurements of the visceral organs in fasting and digesting snakes. Twelve snakes were MRI scanned immediately before the organs were removed and weighed to provide direct comparison of the two methods. Both methods provided similar estimates for the mass of liver, gallbladder, and pancreas, whereas MRI overestimated the size of the heart and small intestine, probably because blood and digesta contributed to the volume determined by MRI. The correlations were used to derive wet organ mass from MRI-based volumes to evaluate the mass development through repeated MRI scans of five digesting snakes. MRI was performed at fasting and 24, 48, 72, 132, and 500 h after eating a meal corresponding to 25% of body mass. This observation period revealed a reversible volume upregulation of the visceral organs, supporting the view that successive MRI facilitates in vivo investigations of structural changes accompanied by digestion. PMID:23303329

  6. Dispel4py: An Open-Source Python library for Data-Intensive Seismology

    NASA Astrophysics Data System (ADS)

    Filgueira, Rosa; Krause, Amrey; Spinuso, Alessandro; Klampanos, Iraklis; Danecek, Peter; Atkinson, Malcolm

    2015-04-01

    Scientific workflows are a necessary tool for many scientific communities as they enable easy composition and execution of applications on computing resources while scientists can focus on their research without being distracted by the computation management. Nowadays, scientific communities (e.g. Seismology) have access to a large variety of computing resources and their computational problems are best addressed using parallel computing technology. However, successful use of these technologies requires a lot of additional machinery whose use is not straightforward for non-experts: different parallel frameworks (MPI, Storm, multiprocessing, etc.) must be used depending on the computing resources (local machines, grids, clouds, clusters) where applications are run. This implies that for achieving the best applications' performance, users usually have to change their codes depending on the features of the platform selected for running them. This work presents dispel4py, a new open-source Python library for describing abstract stream-based workflows for distributed data-intensive applications. Special care has been taken to provide dispel4py with the ability to map abstract workflows to different platforms dynamically at run-time. Currently dispel4py has four mappings: Apache Storm, MPI, multi-threading and sequential. The main goal of dispel4py is to provide an easy-to-use tool to develop and test workflows in local resources by using the sequential mode with a small dataset. Later, once a workflow is ready for long runs, it can be automatically executed on different parallel resources. dispel4py takes care of the underlying mappings by performing an efficient parallelisation. Processing Elements (PE) represent the basic computational activities of any dispel4Py workflow, which can be a seismologic algorithm, or a data transformation process. For creating a dispel4py workflow, users only have to write very few lines of code to describe their PEs and how they are connected by using Python, which is widely supported on many platforms and is popular in many scientific domains, such as in geosciences. Once, a dispel4py workflow is written, a user only has to select which mapping they would like to use, and everything else (parallelisation, distribution of data) is carried on by dispel4py without any cost to the user. Among all dispel4py features we would like to highlight the following: * The PEs are connected by streams and not by writing to and reading from intermediate files, avoiding many IO operations. * The PEs can be stored into a registry. Therefore, different users can recombine PEs in many different workflows. * dispel4py has been enriched with a provenance mechanism to support runtime provenance analysis. We have adopted the W3C-PROV data model, which is accessible via a prototypal browser-based user interface and a web API. It supports the users with the visualisation of graphical products and offers combined operations to access and download the data, which may be selectively stored at runtime, into dedicated data archives. dispel4py has been already used by seismologists in the VERCE project to develop different seismic workflows. One of them is the Seismic Ambient Noise Cross-Correlation workflow, which preprocesses and cross-correlates traces from several stations. First, this workflow was tested on a local machine by using a small number of stations as input data. Later, it was executed on different parallel platforms (SuperMUC cluster, and Terracorrelator machine), automatically scaling up by using MPI and multiprocessing mappings and up to 1000 stations as input data. The results show that the dispel4py achieves scalable performance in both mappings tested on different parallel platforms.

  7. pyLIDEM: A Python-Based Tool to Delineate Coastal Watersheds Using LIDAR Data

    NASA Astrophysics Data System (ADS)

    O'Banion, R.; Alameddine, I.; Gronewold, A.; Reckhow, K.

    2008-12-01

    Accurately identifying the boundary of a watershed is one of the most fundamental and important steps in any hydrological assessment. Representative applications include defining a study area, predicting overland flow, estimating groundwater infiltration, modeling pollutant accumulation and wash-off rates, and evaluating effectiveness of pollutant mitigation measures. The United States Environmental Protection Agency (USEPA) Total Maximum Daily Load (TMDL) program, the most comprehensive water quality management program in the United States (US), is just one example of an application in which accurate and efficient watershed delineation tools play a critical role. For example, many impaired water bodies currently being addressed through the TMDL program drain small coastal watersheds with relatively flat terrain, making watershed delineation particularly challenging. Most of these TMDL studies use 30-meter digital elevation models (DEMs) that rarely capture all of the small elevation changes in coastal watersheds, leading to errors not only in watershed boundary delineation, but in subsequent model predictions (such as watershed runoff flow and pollutant deposition rate predictions) for which watershed attributes are key inputs. Manually delineating these low-relief coastal watersheds through the use of expert knowledge of local water flow patterns, often produces relatively accurate (and often more accurate) watershed boundaries as compared to the boundaries generated by the 30-meter DEMs. Yet, manual delineation is a costly and time consuming procedure that is often not opted for. There is a growing need, therefore, particularly to address the ongoing needs of the TMDL program (and similar environmental management programs), for software tools which can utilize high resolution topography data to more accurately delineate coastal watersheds. Here, we address this need by developing pyLIDEM (python LIdar DEM), a python-based tool which processes bare earth high-resolution Light Detection and Ranging (LIDAR) data, generates fine scale DEMs, and delineates watershed boundaries for a given pour point. Because LIDAR data are typically distributed in large sets of predefined tiles, our tool is capable of combining only the minimum number of bare earth LIDAR tiles required to delineate a watershed of interest. Our tool then processes the LIDAR data into Triangulated Irregular Networks, generates DEMs at user- specified cell sizes, and creates the required files needed to delineate watersheds within ArcGIS. To make pyLIDEM more accessible to the modeling community, we have bundled it within an ArcGIS toolbox, which also allows users to run it directly from an ArcGIS platform. We assess pyLIDEM functionality and accuracy by delineating several impaired small coastal watersheds in the Newport River Estuary in Eastern North Carolina using LIDAR data collected for the North Carolina Flood Mapping Program. We then compare the pyLIDAR-based watershed boundaries with those generated manually and with those generated using the 30-meter DEMs, and find that the pyLIDAR-based boundaries are more accurate than the 30-meter DEMs, and provide a significant time savings compared to manual delineation, particularly in cases where multiple watersheds need to be delineated for a single project.

  8. Nipype: a flexible, lightweight and extensible neuroimaging data processing framework in python.

    PubMed

    Gorgolewski, Krzysztof; Burns, Christopher D; Madison, Cindee; Clark, Dav; Halchenko, Yaroslav O; Waskom, Michael L; Ghosh, Satrajit S

    2011-01-01

    Current neuroimaging software offer users an incredible opportunity to analyze their data in different ways, with different underlying assumptions. Several sophisticated software packages (e.g., AFNI, BrainVoyager, FSL, FreeSurfer, Nipy, R, SPM) are used to process and analyze large and often diverse (highly multi-dimensional) data. However, this heterogeneous collection of specialized applications creates several issues that hinder replicable, efficient, and optimal use of neuroimaging analysis approaches: (1) No uniform access to neuroimaging analysis software and usage information; (2) No framework for comparative algorithm development and dissemination; (3) Personnel turnover in laboratories often limits methodological continuity and training new personnel takes time; (4) Neuroimaging software packages do not address computational efficiency; and (5) Methods sections in journal articles are inadequate for reproducing results. To address these issues, we present Nipype (Neuroimaging in Python: Pipelines and Interfaces; http://nipy.org/nipype), an open-source, community-developed, software package, and scriptable library. Nipype solves the issues by providing Interfaces to existing neuroimaging software with uniform usage semantics and by facilitating interaction between these packages using Workflows. Nipype provides an environment that encourages interactive exploration of algorithms, eases the design of Workflows within and between packages, allows rapid comparative development of algorithms and reduces the learning curve necessary to use different packages. Nipype supports both local and remote execution on multi-core machines and clusters, without additional scripting. Nipype is Berkeley Software Distribution licensed, allowing anyone unrestricted usage. An open, community-driven development philosophy allows the software to quickly adapt and address the varied needs of the evolving neuroimaging community, especially in the context of increasing demand for reproducible research. PMID:21897815

  9. Functional site of endogenous phospholipase A2 inhibitor from python serum.

    PubMed

    Thwin, Maung-Maung; Satish, Ramapatna L; Chan, Steven T F; Gopalakrishnakone, Ponnampalam

    2002-01-01

    The functional site of 'phospholipase A2 inhibitor from python' (PIP) was predicted based on the hypothesis of proline brackets. Using different sources of secretory phospholipase A2 (sPLA2s) as enzyme, and [3H]arachidonate-labelled Escherichia coli as substrate, short synthetic peptides representing the proposed site were examined for their secretory phospholipase A2 (sPLA2) inhibitory activity. A decapeptide P-PB.III proved to be the most potent of the tested peptides in inhibiting sPLA2 enzymatic activity in vitro, and exhibited striking anti-inflammatory effects in vivo in a mouse paw oedema model. P-PB.III inhibited the enzymatic activity of class I, II and III PLA2s, including that of human synovial fluid from arthritis patients. When tested by ELISA, biotinylated P-PB.III interacted positively with various PLA2s, suggesting that the specific region of PIP corresponding to P-PB.III, is likely to be involved in the PLA2-PLI interaction. The effect of P-PB.III on the peritoneal inflammatory response after surgical trauma in rats was also examined. P-PB.III effectively reduced the extent of postsurgical peritoneal adhesions as compared to controls. sPLA2 levels at seventh postoperative day in the peritoneal tissue of P-PB.III-treated rats were also significantly reduced (P < 0.05) in comparison to those of the untreated controls. The present results shed additional insight on the essential structural elements for PLA2 binding, and may be useful as a basis for the design of novel therapeutic agents. PMID:11856333

  10. Annotated checklist of the recent and extinct pythons (Serpentes, Pythonidae), with notes on nomenclature, taxonomy, and distribution

    PubMed Central

    Schleip, Wulf D.; O’Shea, Mark

    2010-01-01

    Abstract McDiarmid et al. (1999) published the first part of their planned taxonomic catalog of the snakes of the world. Since then, several new python taxa have been described in both the scientific literature and non-peer-reviewed publications. This checklist evaluates the nomenclatural status of the names and discusses the taxonomic status of the new taxa, and aims to continue the work of McDiarmid et al. (1999) for the family Pythonidae, covering the period 1999 to 2010. Numerous new taxa are listed, and where appropriate recent synonymies are included and annotations are made. A checklist and a taxonomic identification key of valid taxa are provided. PMID:21594030

  11. Combustion-chamber Performance Characteristics of a Python Turbine-propeller Engine Investigated in Altitude Wind Tunnel

    NASA Technical Reports Server (NTRS)

    Campbell, Carl E

    1951-01-01

    Combustion-chamber performance characteristics of a Python turbine-propeller engine were determined from investigation of a complete engine over a range of engine speeds and shaft horsepowers at simulated altitudes. Results indicated the effect of engine operating conditions and altitude on combustion efficiency and combustion-chamber total pressure losses. Performance of this vaporizing type combustion chamber was also compared with several atomizing type combustion chambers. Over the range of test conditions investigated, combustion efficiency varied from approximately 0.95 to 0.99.

  12. Weighing empirical and hypothetical evidence for assessing potential invasive species range limits: a review of the case of Burmese pythons in the USA.

    PubMed

    Engeman, Richard; Avery, Michael L; Jacobson, Elliott

    2014-10-01

    Range expansion potential is an important consideration for prioritizing management actions against an invasive species. Understanding the potential for range expansion by invasive reptiles such as the Burmese python can be challenging, because the lack of knowledge on fundamental physiological and behavioral constraints initially forces reliance on modeling to predict hypothetical invasive range potential. Hypothetical predictions for Burmese python range limits in the USA have been highly divergent, from only extreme South Florida and the extreme southern Gulf edge of Texas to a broad swath over the southern third of the continental USA. Empirical observations on python thermal tolerances and behavioral abilities to cope with more temperate temperatures became evident during a cold spell in December 2009-January 2010. We review and highlight important considerations for improving invasive range estimation methodology, deciding between competing range predictions, and the importance of having, and applying, empirical data to aid in decision making. PMID:24943887

  13. Giant Constrictors: Biological and Management Profiles and an Establishment Risk Assessment for Nine Large Species of Pythons, Anacondas, and the Boa Constrictor

    USGS Publications Warehouse

    Reed, Robert N.; Rodda, Gordon H.

    2009-01-01

    Giant Constrictors: Biological and Management Profiles and an Establishment Risk Assessment for Nine Large Species of Pythons, Anacondas, and the Boa Constrictor, estimates the ecological risks associated with colonization of the United States by nine large constrictors. The nine include the world's four largest snake species (Green Anaconda, Eunectes murinus; Indian or Burmese Python, Python molurus; Northern African Python, Python sebae; and Reticulated Python, Broghammerus reticulatus), the Boa Constrictor (Boa constrictor), and four species that are ecologically or visually similar to one of the above (Southern African Python, Python natalensis; Yellow Anaconda, Eunectes notaeus; DeSchauensee's Anaconda, Eunectes deschauenseei; and Beni Anaconda, Eunectes beniensis). At present, the only probable pathway by which these species would become established in the United States is the pet trade. Although importation for the pet trade involves some risk that these animals could become established as exotic or invasive species, it does not guarantee such establishment. Federal regulators have the task of appraising the importation risks and balancing those risks against economic, social, and ecological benefits associated with the importation. The risk assessment quantifies only the ecological risks, recognizing that ecosystem processes are complex and only poorly understood. The risk assessment enumerates the types of economic impacts that may be experienced, but leaves quantification of economic costs to subsequent studies. Primary factors considered in judging the risk of establishment were: (1) history of establishment in other countries, (2) number of each species in commerce, (3) suitability of U.S. climates for each species, and (4) natural history traits, such as reproductive rate and dispersal ability, that influence the probability of establishment, spread, and impact. In addition, the risk assessment reviews all management tools for control of invasive giant constrictor populations. There is great uncertainty about many aspects of the risk assessment; the level of uncertainty is estimated separately for each risk component. Overall risk was judged to be high for five of the giant constrictors studied, and medium for the other four species. Because all nine species shared a large number of natural history traits that promote invasiveness or impede population control, none of the species was judged to be of low risk.

  14. Novel phospholipase A2 inhibitors from python serum are potent peptide antibiotics.

    PubMed

    Samy, Ramar Perumal; Thwin, Maung Maung; Stiles, Brad G; Satyanarayana-Jois, Seetharama; Chinnathambi, Arunachalam; Zayed, M E; Alharbi, Sulaiman Ali; Siveen, Kodappully Sivaraman; Sikka, Sakshi; Kumar, Alan Prem; Sethi, Gautam; Lim, Lina Hsiu Kim

    2015-04-01

    Antimicrobial peptides (AMPs) play a vital role in defense against resistant bacteria. In this study, eight different AMPs synthesized from Python reticulatus serum protein were tested for bactericidal activity against various Gram-positive and Gram-negative bacteria (Staphylococcus aureus, Burkholderia pseudomallei (KHW and TES strains), and Proteus vulgaris) using a disc-diffusion method (20 μg/disc). Among the tested peptides, phospholipase A2 inhibitory peptide (PIP)-18[59-76], β-Asp65-PIP[59-67], D-Ala66-PNT.II, and D60,65E-PIP[59-67] displayed the most potent bactericidal activity against all tested pathogens in a dose-dependent manner (100-6.8 μg/ml), with a remarkable activity noted against S. aureus at 6.8 μg/ml dose within 6 h of incubation. Determination of minimum inhibitory concentrations (MICs) by a micro-broth dilution method at 100-3.125 μg/ml revealed that PIP-18[59-76], β-Asp65-PIP[59-67] and D-Ala66-PNT.II peptides exerted a potent inhibitory effect against S. aureus and B. pseudomallei (KHW) (MICs 3.125 μg/ml), while a much less inhibitory potency (MICs 12.5 μg/ml) was noted for β-Asp65-PIP[59-67] and D-Ala66-PNT.II peptides against B. pseudomallei (TES). Higher doses of peptides had no effect on the other two strains (i.e., Klebsiella pneumoniae and Streptococcus pneumoniae). Overall, PIP-18[59-76] possessed higher antimicrobial activity than that of chloramphenicol (CHL), ceftazidime (CF) and streptomycin (ST) (30 μg/disc). When the two most active peptides, PIP-18[59-76] and β-Asp65-PIP[59-67], were applied topically at a 150 mg/kg dose for testing wound healing activity in a mouse model of S. aureus infection, the former accelerates faster wound healing than the latter peptide at 14 days post-treatment. The western blot data suggest that the topical application of peptides (PIP-18[59-67] and β-Asp65-PIP[59-67]) modulates NF-kB mediated wound repair in mice with relatively little haemolytic (100-1.56 μg/ml) and cytotoxic (1000-3.125 μg/ml) effects evident on human cells in vitro. PMID:25583073

  15. A Python Plug-in Based Computational Framework for Spatially Distributed Environmental and Earth Sciences Modelling

    NASA Astrophysics Data System (ADS)

    Willgoose, G. R.

    2009-12-01

    One of the pioneering landform evolution models, SIBERIA, while developed in the 1980s is still widely used in the science community and is a key component of engineering software used to assess the long-term stability of man-made landforms such as rehabilitated mine sites and nuclear waste repositories. While SIBERIA is very reliable, computationally fast and well tested (both its underlying science and the computer code) the range of emerging applications have challenged the ability of the author to maintain and extend the underlying computer code. Moreover, the architecture of the SIBERIA code is not well suited to collaborative extension of its capabilities without often triggering forking of the code base. This paper describes a new modelling framework designed to supersede SIBERIA (as well as other earth sciences codes by the author) called TelluSim. The design is such that it is potentially more than simply a new landform evolution model, but TelluSim is a more general dynamical system modelling framework using time evolving GIS data as its spatial discretisation. TelluSim is designed as an open modular framework facilitating open-sourcing of the code, while addressing compromises made in the original design of SIBERIA in the 1980s. An important aspect of the design of TelluSim was to minimise the overhead in interfacing the modules with TelluSim, and minimise any requirement for recoding of existing software, so eliminating a major disadvantage of more complex frameworks. The presentation will discuss in more detail the reasoning behind the design of TelluSim, and experiences of the advantages and disadvantages of using Python relative to other approaches (e.g. Matlab, R). The paper will discuss examples of how TelluSim has facilitated the incorporation and testing of new algorithms, and environmental processes, and the support for novel science and data testing methodologies. It will also discuss plans to link TelluSim with other open source geoscience modelling frameworks such as CSDMS.

  16. CellLab-CTS 2015: a Python library for continuous-time stochastic cellular automaton modeling using Landlab

    NASA Astrophysics Data System (ADS)

    Tucker, G. E.; Hobley, D. E. J.; Hutton, E.; Gasparini, N. M.; Istanbulluoglu, E.; Adams, J. M.; Nudurupati, S. S.

    2015-11-01

    CellLab-CTS 2015 is a Python-language software library for creating two-dimensional, continuous-time stochastic (CTS) cellular automaton models. The model domain consists of a set of grid nodes, with each node assigned an integer state-code that represents its condition or composition. Adjacent pairs of nodes may undergo transitions to different states, according to a user-defined average transition rate. A model is created by writing a Python code that defines the possible states, the transitions, and the rates of those transitions. The code instantiates, initializes, and runs one of four object classes that represent different types of CTS model. CellLab-CTS provides the option of using either square or hexagonal grid cells. The software provides the ability to treat particular grid-node states as moving particles, and to track their position over time. Grid nodes may also be assigned user-defined properties, which the user can update after each transition through the use of a callback function. As a component of the Landlab modeling framework, CellLab-CTS models take advantage of a suite of Landlab's tools and capabilities, such as support for standardized input and output.

  17. Rapid changes in gene expression direct rapid shifts in intestinal form and function in the Burmese python after feeding.

    PubMed

    Andrew, Audra L; Card, Daren C; Ruggiero, Robert P; Schield, Drew R; Adams, Richard H; Pollock, David D; Secor, Stephen M; Castoe, Todd A

    2015-05-01

    Snakes provide a unique and valuable model system for studying the extremes of physiological remodeling because of the ability of some species to rapidly upregulate organ form and function upon feeding. The predominant model species used to study such extreme responses has been the Burmese python because of the extreme nature of postfeeding response in this species. We analyzed the Burmese python intestine across a time series, before, during, and after feeding to understand the patterns and timing of changes in gene expression and their relationship to changes in intestinal form and function upon feeding. Our results indicate that >2,000 genes show significant changes in expression in the small intestine following feeding, including genes involved in intestinal morphology and function (e.g., hydrolases, microvillus proteins, trafficking and transport proteins), as well as genes involved in cell division and apoptosis. Extensive changes in gene expression occur surprisingly rapidly, within the first 6 h of feeding, coincide with changes in intestinal morphology, and effectively return to prefeeding levels within 10 days. Collectively, our results provide an unprecedented portrait of parallel changes in gene expression and intestinal morphology and physiology on a scale that is extreme both in the magnitude of changes, as well as in the incredibly short time frame of these changes, with up- and downregulation of expression and function occurring in the span of 10 days. Our results also identify conserved vertebrate signaling pathways that modulate these responses, which may suggest pathways for therapeutic modulation of intestinal function in humans. PMID:25670730

  18. Graph-based active learning of agglomeration (GALA): a Python library to segment 2D and 3D neuroimages.

    PubMed

    Nunez-Iglesias, Juan; Kennedy, Ryan; Plaza, Stephen M; Chakraborty, Anirban; Katz, William T

    2014-01-01

    The aim in high-resolution connectomics is to reconstruct complete neuronal connectivity in a tissue. Currently, the only technology capable of resolving the smallest neuronal processes is electron microscopy (EM). Thus, a common approach to network reconstruction is to perform (error-prone) automatic segmentation of EM images, followed by manual proofreading by experts to fix errors. We have developed an algorithm and software library to not only improve the accuracy of the initial automatic segmentation, but also point out the image coordinates where it is likely to have made errors. Our software, called gala (graph-based active learning of agglomeration), improves the state of the art in agglomerative image segmentation. It is implemented in Python and makes extensive use of the scientific Python stack (numpy, scipy, networkx, scikit-learn, scikit-image, and others). We present here the software architecture of the gala library, and discuss several designs that we consider would be generally useful for other segmentation packages. We also discuss the current limitations of the gala library and how we intend to address them. PMID:24772079

  19. The Social Tunnel Versus the Python: A New Way to Understand the Impact of Baby Booms and Baby Busts on a Society.

    ERIC Educational Resources Information Center

    McFalls, Joseph A.; And Others

    1986-01-01

    Maintains that the "python analogy," often used to help students understand the negative societal impact of unusually small or large age cohorts, is better replaced by the social tunnel analogy, which is diagramed and illustrated with reference to the educational problems experienced in the United States as a result of the World War II baby boom.

  20. The Social Tunnel Versus the Python: A New Way to Understand the Impact of Baby Booms and Baby Busts on a Society.

    ERIC Educational Resources Information Center

    McFalls, Joseph A.; And Others

    1986-01-01

    Maintains that the "python analogy," often used to help students understand the negative societal impact of unusually small or large age cohorts, is better replaced by the social tunnel analogy, which is diagramed and illustrated with reference to the educational problems experienced in the United States as a result of the World War II baby boom.…

  1. Development of a 3D Potential Field Forward Modelling System in Python

    NASA Astrophysics Data System (ADS)

    Cole, P.

    2012-12-01

    The collection of potential field data has long been a standard part of geophysical exploration. Specifically, airborne magnetic data is collected routinely in any brown-fields area, because of the low cost and fast acquisition rate compared to other geophysical techniques. However, the interpretation of such data can be a daunting task, especially when 3D models are becoming more necessary. The current trend in modelling software is to follow either the modelling of individual profiles, which are then "joined" up into 3D sections, or to model in a full 3D using polygonal based models (Singh and Guptasarma, 2001). Unfortunately, both techniques have disadvantages. When modelling in 2.5D the impact of other profiles is not truly available on your current profile being modelled, and vice versa. The problem is not present in 3D, but 3D polygonal models, while being easy to construct the initial model, are not as easy to make fast changes to. In some cases, the entire model must be recreated from scratch. The ability to easily change a model is the very basis of forward modelling. With this is mind, the objective of the project was to: 1) Develop software which was truly modelling in 3D 2) Create a system which would allow the rapid changing of the 3D model, without the need to recreate the model. The solution was to adopt a voxel based approach, rather than a polygonal approach. The solution for a cube (Blakely 1996) was used to calculate potential field for each voxel. The voxels are then summed over the entire volume. The language used was python, because of its huge capacity for scientific development. It enables full 3D visualisation as well as complex mathematical routines. Some properties worth noting are: 1) Although 200 rows by 200 columns by 200 layers would imply 8 million calculations, in reality, since the calculation for adjacent voxels produces the same result, only 200 calculations are necessary. 2) Changes to susceptibility and density do not affect the field shape, merely the amplitude of the anomaly. Therefore, it is not necessary to recalculate the entire field if one of these parameters is changed. The interface to the program works similar to a paint program. The model is simply drawn into the side views or top views of the volume of interest. Relevant voxels are either activated or deactivated in this way. The software has proved to be extremely successful. It has enabled faster modelling of anomalies in a non-complex manner - implying little or no training to prospective users. References Blakely, R.J., Potential Theory in Gravity and Magnetic Applications (1996), pp 200 - 201 Singh, B., Guptasarma, D., (2001). New method for fast computation of gravity and magnetic anomalies from arbitrary polyhedral, Geophysics, 66, pp. 521 - 526

  2. Using Python for scientific computing: Efficient and flexible evaluation of the statistical characteristics of functions with multivariate random inputs

    NASA Astrophysics Data System (ADS)

    Chudoba, R.; Sadlek, V.; Rypl, R.; Vo?echovsk, M.

    2013-02-01

    This paper examines the feasibility of high-level Python based utilities for numerically intensive applications via an example of a multidimensional integration for the evaluation of the statistical characteristics of a random variable. We discuss the approaches to the implementation of mathematically formulated incremental expressions using high-level scripting code and low-level compiled code. Due to the dynamic typing of the Python language, components of the algorithm can be easily coded in a generic way as algorithmic templates. Using the Enthought Development Suite they can be effectively assembled into a flexible computational framework that can be configured to execute the code for arbitrary combinations of integration schemes and versions of instantiated code. The paper describes the development cycle using a simple running example involving averaging of a random two-parametric function that includes discontinuity. This example is also used to compare the performance of the available algorithmic and executional features. The implemented package including further examples and the results of performance studies have been made available via the free repository [1] and CPCP library. Program summaryProgram title: spirrid Catalogue identifier: AENL_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AENL_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Special licence provided by the author No. of lines in distributed program, including test data, etc.: 10722 No. of bytes in distributed program, including test data, etc.: 157099 Distribution format: tar.gz Programming language: Python and C. Computer: PC. Operating system: LINUX, UNIX, Windows. Classification: 4.13, 6.2. External routines: NumPy (http://numpy.scipy.org/), SciPy (http://www.scipy.com) Nature of problem: Evaluation of the statistical moments of a function of random variables. Solution method: Direct multidimensional integration. Running time: Depending on the number of random variables the time needed for the numerical estimation of the mean value of a function with a sufficiently low level of numerical error varies. For orientation, the time needed for two included examples: examples/fiber_tt_2p/fiber_tt_2p.py with 2 random variables: few milliseconds examples/fiber_po_8p/fiber_po_8p.py with 8 random variables: few seconds

  3. LANL12-RS-107J PYTHON Radiography Analysis Tool (PyRAT). Mid-Year Deliverable Report for FY15

    SciTech Connect

    Temple, Brian Allen; Armstrong, Jerawan Chudoung

    2015-04-14

    This document is a mid-year report on a deliverable for the PYTHON Radiography Analysis Tool (PyRAT) for project LANL12-RS-107J in FY15. The deliverable is deliverable number 2 in the work package and is titled “Add the ability to read in more types of image file formats in PyRAT”. Right now PyRAT can only read in uncompressed TIF files (tiff files). It is planned to expand the file formats that can be read by PyRAT, making it easier to use in more situations. A summary of the file formats added include jpeg, jpg, png and formatted ASCII files.

  4. QuTiP: An open-source Python framework for the dynamics of open quantum systems

    NASA Astrophysics Data System (ADS)

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

    2012-08-01

    We present an object-oriented open-source framework for solving the dynamics of open quantum systems written in Python. Arbitrary Hamiltonians, including time-dependent systems, may be built up from operators and states defined by a quantum object class, and then passed on to a choice of master equation or Monte Carlo solvers. We give an overview of the basic structure for the framework before detailing the numerical simulation of open system dynamics. Several examples are given to illustrate the build up to a complete calculation. Finally, we measure the performance of our library against that of current implementations. The framework described here is particularly well suited to the fields of quantum optics, superconducting circuit devices, nanomechanics, and trapped ions, while also being ideal for use in classroom instruction. Catalogue identifier: AEMB_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEMB_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU General Public License, version 3 No. of lines in distributed program, including test data, etc.: 16 482 No. of bytes in distributed program, including test data, etc.: 213 438 Distribution format: tar.gz Programming language: Python Computer: i386, x86-64 Operating system: Linux, Mac OSX, Windows RAM: 2+ Gigabytes Classification: 7 External routines: NumPy (http://numpy.scipy.org/), SciPy (http://www.scipy.org/), Matplotlib (http://matplotlib.sourceforge.net/) Nature of problem: Dynamics of open quantum systems. Solution method: Numerical solutions to Lindblad master equation or Monte Carlo wave function method. Restrictions: Problems must meet the criteria for using the master equation in Lindblad form. Running time: A few seconds up to several tens of minutes, depending on size of underlying Hilbert space.

  5. Wilber 3: A Python-Django Web Application For Acquiring Large-scale Event-oriented Seismic Data

    NASA Astrophysics Data System (ADS)

    Newman, R. L.; Clark, A.; Trabant, C. M.; Karstens, R.; Hutko, A. R.; Casey, R. E.; Ahern, T. K.

    2013-12-01

    Since 2001, the IRIS Data Management Center (DMC) WILBER II system has provided a convenient web-based interface for locating seismic data related to a particular event, and requesting a subset of that data for download. Since its launch, both the scale of available data and the technology of web-based applications have developed significantly. Wilber 3 is a ground-up redesign that leverages a number of public and open-source projects to provide an event-oriented data request interface with a high level of interactivity and scalability for multiple data types. Wilber 3 uses the IRIS/Federation of Digital Seismic Networks (FDSN) web services for event data, metadata, and time-series data. Combining a carefully optimized Google Map with the highly scalable SlickGrid data API, the Wilber 3 client-side interface can load tens of thousands of events or networks/stations in a single request, and provide instantly responsive browsing, sorting, and filtering of event and meta data in the web browser, without further reliance on the data service. The server-side of Wilber 3 is a Python-Django application, one of over a dozen developed in the last year at IRIS, whose common framework, components, and administrative overhead represent a massive savings in developer resources. Requests for assembled datasets, which may include thousands of data channels and gigabytes of data, are queued and executed using the Celery distributed Python task scheduler, giving Wilber 3 the ability to operate in parallel across a large number of nodes.

  6. Processing of terabytes of data for seismic noise analysis with the Python codes of the Whisper Suite. (Invited)

    NASA Astrophysics Data System (ADS)

    Briand, X.; Campillo, M.; Brenguier, F.; Boue, P.; Poli, P.; Roux, P.; Takeda, T.

    2013-12-01

    The Whisper Suite, as part of the ERC project Whisper (whisper.obs.ujf-grenoble.fr), is developed with the high-level programming language Python and uses intensively the scientific libraries Scipy and Obspy, which is dedicated to the seismological community (www.obspy.org). The Whisper Suite consists of several tools. It provides a flexible way to specify a pipeline of seismogram processing. The user can define his own sequence of treatments, can use the Python libraries he needs and eventually, can add his processing procedure to the Whisper Suite. Another package is dedicated to the computation of correlations. When dealing with large data set, computational time becomes a major difficulty and we devoted a lot of efforts to make possible the fast processing of the large data sets produced by the present day dense seismic networks. With the Whisper Suite, we manage currently more than 150TB of data for ambient noise analysis. For the computations of 68 millions correlations (daily, 5Hz, correlation window 3600s) on a 50 core cluster, with a dedicated disk array, the required time is 4 days. With a distributed storage (Irods) and a grid of clusters (mode best effort), both provided by the University of Grenoble, we compute currently one year of 4-hours correlations for 550 3C stations of the Hi-Net Japanese Network in one day (about 350 millions individual correlations) . Note that the quadratic space complexity can be critical. We developed also codes for the analysis of the correlations. The Whisper Suite is used to make challenging observations using cross-correlation techniques at various scales in the Earth. We present some examples of applications. Using a global data set of available broadband stations, we discuss the emergence of the complete teleseismic body wave wave field, including the deep phases used for imaging of the mantle and the core. The giant 2011 Tohoku-oki earthquake and the records of the dense Hi-Net array offer an opportunity to analyze what are the changes in the elastic properties of the crust at large scale, including the co-seismic non linear response of the shallow layers and the signatures of the different processes affecting the crust at depth, such as postseismic slip and viscoelastic relaxation.

  7. C++QEDv2 Milestone 10: A C++/Python application-programming framework for simulating open quantum dynamics

    NASA Astrophysics Data System (ADS)

    Sandner, Raimar; Vukics, Andrs

    2014-09-01

    The v2 Milestone 10 release of C++QED is primarily a feature release, which also corrects some problems of the previous release, especially as regards the build system. The adoption of C++11 features has led to many simplifications in the codebase. A full doxygen-based API manual [1] is now provided together with updated user guides. A largely automated, versatile new testsuite directed both towards computational and physics features allows for quickly spotting arising errors. The states of trajectories are now savable and recoverable with full binary precision, allowing for trajectory continuation regardless of evolution method (single/ensemble Monte Carlo wave-function or Master equation trajectory). As the main new feature, the framework now presents Python bindings to the highest-level programming interface, so that actual simulations for given composite quantum systems can now be performed from Python. Catalogue identifier: AELU_v2_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AELU_v2_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: yes No. of lines in distributed program, including test data, etc.: 492422 No. of bytes in distributed program, including test data, etc.: 8070987 Distribution format: tar.gz Programming language: C++/Python. Computer: i386-i686, x86 64. Operating system: In principle cross-platform, as yet tested only on UNIX-like systems (including Mac OS X). RAM: The framework itself takes about 60MB, which is fully shared. The additional memory taken by the program which defines the actual physical system (script) is typically less than 1MB. The memory storing the actual data scales with the system dimension for state-vector manipulations, and the square of the dimension for density-operator manipulations. This might easily be GBs, and often the memory of the machine limits the size of the simulated system. Classification: 4.3, 4.13, 6.2. External routines: Boost C++ libraries, GNU Scientific Library, Blitz++, FLENS, NumPy, SciPy Catalogue identifier of previous version: AELU_v1_0 Journal reference of previous version: Comput. Phys. Comm. 183 (2012) 1381 Does the new version supersede the previous version?: Yes Nature of problem: Definition of (open) composite quantum systems out of elementary building blocks [2,3]. Manipulation of such systems, with emphasis on dynamical simulations such as Master-equation evolution [4] and Monte Carlo wave-function simulation [5]. Solution method: Master equation, Monte Carlo wave-function method Reasons for new version: The new version is mainly a feature release, but it does correct some problems of the previous version, especially as regards the build system. Summary of revisions: We give an example for a typical Python script implementing the ring-cavity system presented in Sec. 3.3 of Ref. [2]: Restrictions: Total dimensionality of the system. Master equation-few thousands. Monte Carlo wave-function trajectory-several millions. Unusual features: Because of the heavy use of compile-time algorithms, compilation of programs written in the framework may take a long time and much memory (up to several GBs). Additional comments: The framework is not a program, but provides and implements an application-programming interface for developing simulations in the indicated problem domain. We use several C++11 features which limits the range of supported compilers (g++ 4.7, clang++ 3.1) Documentation, http://cppqed.sourceforge.net/ Running time: Depending on the magnitude of the problem, can vary from a few seconds to weeks. References: [1] Entry point: http://cppqed.sf.net [2] A. Vukics, C++QEDv2: The multi-array concept and compile-time algorithms in the definition of composite quantum systems, Comp. Phys. Comm. 183(2012)1381. [3] A. Vukics, H. Ritsch, C++QED: an object-oriented framework for wave-function simulations of cavity QED systems, Eur. Phys. J. D 44 (2007) 585. [4] H. J. Carmichael, An Open Systems Approach to Quantum Optics, Springer, 1993. [5] J. Dalibard, Y. Castin, K. Molmer, Wave-function approach to dissipative processes in quantum optics, Phys. Rev. Lett. 68 (1992) 580.

  8. Molecular identification of Sarcocystis spp. helped to define the origin of green pythons (Morelia viridis) confiscated in Germany.

    PubMed

    Moré, Gastón; Pantchev, Nikola; Herrmann, Daland C; Vrhovec, Majda Globokar; Öfner, Sabine; Conraths, Franz J; Schares, Gereon

    2014-04-01

    Sarcocystis spp. represent apicomplexan parasites. They usually have a heteroxenous life cycle. Around 200 species have been described, affecting a wide range of animals worldwide, including reptiles. In recent years, large numbers of reptiles have been imported into Europe as pets and, as a consequence, animal welfare and species protection issues emerged. A sample of pooled feces from four confiscated green pythons (Morelia viridis) containing Sarcocystis spp. sporocysts was investigated. These snakes were imported for the pet trade and declared as being captive-bred. Full length 18S rRNA genes were amplified, cloned into plasmids and sequenced. Two different Sarcocystis spp. sequences were identified and registered as Sarcocystis sp. from M. viridis in GenBank. Both showed a 95-97% sequence identity with the 18S rRNA gene of Sarcocystis singaporensis. Phylogenetic analysis positioned these sequences together with other Sarcocystis spp. from snakes and rodents as definitive and intermediate hosts (IH), respectively. Sequence data and also the results of clinical and parasitological examinations suggest that the snakes were definitive hosts for Sarcocystis spp. that circulate in wild IH. Thus, it seems unlikely that the infected snakes had been legally bred. Our research shows that information on the infection of snakes with Sarcocystis spp. may be used to assess compliance with regulations on the trade with wildlife species. PMID:24476633

  9. NMRbot: Python scripts enable high-throughput data collection on current Bruker BioSpin NMR spectrometers.

    PubMed

    Clos, Lawrence J; Jofre, M Fransisca; Ellinger, James J; Westler, William M; Markley, John L

    2013-06-01

    To facilitate the high-throughput acquisition of nuclear magnetic resonance (NMR) experimental data on large sets of samples, we have developed a simple and straightforward automated methodology that capitalizes on recent advances in Bruker BioSpin NMR spectrometer hardware and software. Given the daunting challenge for non-NMR experts to collect quality spectra, our goal was to increase user accessibility, provide customized functionality, and improve the consistency and reliability of resultant data. This methodology, NMRbot, is encoded in a set of scripts written in the Python programming language accessible within the Bruker BioSpin TopSpin™ software. NMRbot improves automated data acquisition and offers novel tools for use in optimizing experimental parameters on the fly. This automated procedure has been successfully implemented for investigations in metabolomics, small-molecule library profiling, and protein-ligand titrations on four Bruker BioSpin NMR spectrometers at the National Magnetic Resonance Facility at Madison. The investigators reported benefits from ease of setup, improved spectral quality, convenient customizations, and overall time savings. PMID:23678341

  10. CSSSCL: a python package that uses combined sequence similarity scores for accurate taxonomic classification of long and short sequence reads

    PubMed Central

    Borozan, Ivan; Ferretti, Vincent

    2016-01-01

    Summary: Sequence comparison of genetic material between known and unknown organisms plays a crucial role in genomics, metagenomics and phylogenetic analysis. The emerging long-read sequencing technologies can now produce reads of tens of kilobases in length that promise a more accurate assessment of their origin. To facilitate the classification of long and short DNA sequences, we have developed a Python package that implements a new sequence classification model that we have demonstrated to improve the classification accuracy when compared with other state of the art classification methods. For the purpose of validation, and to demonstrate its usefulness, we test the combined sequence similarity score classifier (CSSSCL) using three different datasets, including a metagenomic dataset composed of short reads. Availability and implementation: Packages source code and test datasets are available under the GPLv3 license at https://github.com/oicr-ibc/cssscl. Contact: ivan.borozan@oicr.on.ca Supplementary information: Supplementary data are available at Bioinformatics online. PMID:26454281

  11. Application of python-based Abaqus preprocess and postprocess technique in analysis of gearbox vibration and noise reduction

    NASA Astrophysics Data System (ADS)

    Yi, Guilian; Sui, Yunkang; Du, Jiazheng

    2011-06-01

    To reduce vibration and noise, a damping layer and constraint layer are usually pasted on the inner surface of a gearbox thin shell, and their thicknesses are the main parameters in the vibration and noise reduction design. The normal acceleration of the point on the gearbox surface is the main index that can reflect the vibration and noise of that point, and the normal accelerations of different points can reflect the degree of the vibration and noise of the whole structure. The K-S function is adopted to process many points' normal accelerations as the comprehensive index of the vibration characteristics of the whole structure, and the vibration acceleration level is adopted to measure the degree of the vibration and noise. Secondary development of the Abaqus preprocess and postprocess on the basis of the Python scripting programming automatically modifies the model parameters, submits the job, and restarts the analysis totally, which avoids the tedious work of returning to the Abaqus/CAE for modifying and resubmitting and improves the speed of the preprocess and postprocess and the computational efficiency.

  12. Tribological analysis of the ventral scale structure in a Python regius in relation to laser textured surfaces

    NASA Astrophysics Data System (ADS)

    Abdel-Aal, H. A.; El Mansori, M.

    2013-09-01

    Laser texturing is one of the leading technologies applied to modify surface topography. To date, however, a standardized procedure to generate deterministic textures is virtually non-existent. In nature, especially in squamata, there are many examples of deterministic structured textures that allow species to control friction and condition their tribological response for efficient function. In this work, we draw a comparison between industrial surfaces and reptilian surfaces. We chose the Python regius species as a bio-analogue with a deterministic surface. We first study the structural make up of the ventral scales of the snake (both construction and metrology). We further compare the metrological features of the ventral scales to experimentally recommended performance indicators of industrial surfaces extracted from open literature. The results indicate the feasibility of engineering a laser textured surface based on the reptilian ornamentation constructs. It is shown that the metrological features, key to efficient function of a rubbing deterministic surface, are already optimized in the reptile. We further show that optimization in reptilian surfaces is based on synchronizing surface form, textures and aspects to condition the frictional response. Mimicking reptilian surfaces, we argue, may form a design methodology potentially capable of generating advanced deterministic surface constructs capable of efficient tribological function.

  13. A biomolecular electrostatics solver using Python, GPUs and boundary elements that can handle solvent-filled cavities and Stern layers.

    PubMed

    Cooper, Christopher D; Bardhan, Jaydeep P; Barba, L A

    2014-03-01

    The continuum theory applied to biomolecular electrostatics leads to an implicit-solvent model governed by the Poisson-Boltzmann equation. Solvers relying on a boundary integral representation typically do not consider features like solvent-filled cavities or ion-exclusion (Stern) layers, due to the added difficulty of treating multiple boundary surfaces. This has hindered meaningful comparisons with volume-based methods, and the effects on accuracy of including these features has remained unknown. This work presents a solver called PyGBe that uses a boundary-element formulation and can handle multiple interacting surfaces. It was used to study the effects of solvent-filled cavities and Stern layers on the accuracy of calculating solvation energy and binding energy of proteins, using the well-known apbs finite-difference code for comparison. The results suggest that if required accuracy for an application allows errors larger than about 2% in solvation energy, then the simpler, single-surface model can be used. When calculating binding energies, the need for a multi-surface model is problem-dependent, becoming more critical when ligand and receptor are of comparable size. Comparing with the apbs solver, the boundary-element solver is faster when the accuracy requirements are higher. The cross-over point for the PyGBe code is in the order of 1-2% error, when running on one gpu card (nvidia Tesla C2075), compared with apbs running on six Intel Xeon cpu cores. PyGBe achieves algorithmic acceleration of the boundary element method using a treecode, and hardware acceleration using gpus via PyCuda from a user-visible code that is all Python. The code is open-source under MIT license. PMID:25284826

  14. A biomolecular electrostatics solver using Python, GPUs and boundary elements that can handle solvent-filled cavities and Stern layers

    PubMed Central

    Cooper, Christopher D.; Bardhan, Jaydeep P.; Barba, L. A.

    2014-01-01

    The continuum theory applied to biomolecular electrostatics leads to an implicit-solvent model governed by the Poisson-Boltzmann equation. Solvers relying on a boundary integral representation typically do not consider features like solvent-filled cavities or ion-exclusion (Stern) layers, due to the added difficulty of treating multiple boundary surfaces. This has hindered meaningful comparisons with volume-based methods, and the effects on accuracy of including these features has remained unknown. This work presents a solver called PyGBe that uses a boundary-element formulation and can handle multiple interacting surfaces. It was used to study the effects of solvent-filled cavities and Stern layers on the accuracy of calculating solvation energy and binding energy of proteins, using the well-known apbs finite-difference code for comparison. The results suggest that if required accuracy for an application allows errors larger than about 2% in solvation energy, then the simpler, single-surface model can be used. When calculating binding energies, the need for a multi-surface model is problem-dependent, becoming more critical when ligand and receptor are of comparable size. Comparing with the apbs solver, the boundary-element solver is faster when the accuracy requirements are higher. The cross-over point for the PyGBe code is in the order of 12% error, when running on one gpu card (nvidia Tesla C2075), compared with apbs running on six Intel Xeon cpu cores. PyGBe achieves algorithmic acceleration of the boundary element method using a treecode, and hardware acceleration using gpus via PyCuda from a user-visible code that is all Python. The code is open-source under MIT license. PMID:25284826

  15. On the tradeoffs of programming language choice for numerical modelling in geoscience. A case study comparing modern Fortran, C++/Blitz++ and Python/NumPy.

    NASA Astrophysics Data System (ADS)

    Jarecka, D.; Arabas, S.; Fijalkowski, M.; Gaynor, A.

    2012-04-01

    The language of choice for numerical modelling in geoscience has long been Fortran. A choice of a particular language and coding paradigm comes with different set of tradeoffs such as that between performance, ease of use (and ease of abuse), code clarity, maintainability and reusability, availability of open source compilers, debugging tools, adequate external libraries and parallelisation mechanisms. The availability of trained personnel and the scale and activeness of the developer community is of importance as well. We present a short comparison study aimed at identification and quantification of these tradeoffs for a particular example of an object oriented implementation of a parallel 2D-advection-equation solver in Python/NumPy, C++/Blitz++ and modern Fortran. The main angles of comparison will be complexity of implementation, performance of various compilers or interpreters and characterisation of the "added value" gained by a particular choice of the language. The choice of the numerical problem is dictated by the aim to make the comparison useful and meaningful to geoscientists. Python is chosen as a language that traditionally is associated with ease of use, elegant syntax but limited performance. C++ is chosen for its traditional association with high performance but even higher complexity and syntax obscurity. Fortran is included in the comparison for its widespread use in geoscience often attributed to its performance. We confront the validity of these traditional views. We point out how the usability of a particular language in geoscience depends on the characteristics of the language itself and the availability of pre-existing software libraries (e.g. NumPy, SciPy, PyNGL, PyNIO, MPI4Py for Python and Blitz++, Boost.Units, Boost.MPI for C++). Having in mind the limited complexity of the considered numerical problem, we present a tentative comparison of performance of the three implementations with different open source compilers including CPython and PyPy, Clang++ and GNU g++, and GNU gfortran.

  16. Molecular evolution of peptide tyrosine--tyrosine: primary structure of PYY from the lampreys Geotria australis and Lampetra fluviatilis, bichir, python and desert tortoise.

    PubMed

    Wang, Y; Nielsen, P F; Youson, J H; Potter, I C; Lance, V A; Conlon, J M

    1999-02-01

    Peptide tyrosine-tyrosine (PYY) has been isolated from the intestines of two species of reptile, the desert tortoise Gopherus agassizii (Testudines) and the Burmese python Python molurus (Squamata), from the primitive Actinopterygian fish, the bichir Polypterus senegalis (Polypteriformes) and from two agnathans, the Southern-hemisphere lamprey Geotria australis (Geotriidae) and the holarctic lamprey Lampetra fluviatilis (Petromyzontidae). The primary structure of bichir PYY is identical to the proposed ancestral sequence of gnathostome PYY (YPPKPENPGE10/DAPPEELAKY20/YSALR HYINL30/ITRQRY). Tortoise and python PYY differ by six and seven residues, respectively, from the ancestral sequence consistent with the traditional view that the Testudines represent an earlier divergence from the primitive reptilian stock than the Squamates. The current views of agnathan phylogeny favor the hypothesis that the Southern-hemisphere lampreys and the holarctic lampreys arose from a common ancestral stock but their divergence is of a relatively ancient (pre-Tertiary) origin. The Geotria PYY-related peptide shows only two amino acid substitutions (Pro10-->Gln and Leu22-->Ser) compared with PYY from the holarctic lamprey Petromyzon marinus. This result was unexpected as Petromyzon PYY differs from Lampetra PYY deduced from the nucleotide sequence of a cDNA (Sderberg et al. J. Neurosci. Res. 1994;37:633-640) by 10 residues. However, a re-examination of an extract of Lampetra intestine revealed the presence of a PYY that differed in primary structure from Petromyzon PYY by only one amino acid residue (Pro10-->Ser). This result suggests that the structure of PYY has been strongly conserved during the evolution of Agnatha and that at least two genes encoding PYY-related peptides are expressed in Lampetra tissues. PMID:10100922

  17. 3-D Numerical Simulation and Analysis of Complex Fiber Geometry RaFC Materials with High Volume Fraction and High Aspect Ratio based on ABAQUS PYTHON

    NASA Astrophysics Data System (ADS)

    Jin, BoCheng

    2011-12-01

    Organic and inorganic fiber reinforced composites with innumerable fiber orientation distributions and fiber geometries are abundantly available in several natural and synthetic structures. Inorganic glass fiber composites have been introduced to numerous applications due to their economical fabrication and tailored structural properties. Numerical characterization of such composite material systems is necessitated due to their intrinsic statistical nature, which renders extensive experimentation prohibitively time consuming and costly. To predict various mechanical behavior and characterizations of Uni-Directional Fiber Composites (UDFC) and Random Fiber Composites (RaFC), we numerically developed Representative Volume Elements (RVE) with high accuracy and efficiency and with complex fiber geometric representations encountered in uni-directional and random fiber networks. In this thesis, the numerical simulations of unidirectional RaFC fiber strand RVE models (VF>70%) are first presented by programming in ABAQUS PYTHON. Secondly, when the cross sectional aspect ratios (AR) of the second phase fiber inclusions are not necessarily one, various types of RVE models with different cross sectional shape fibers are simulated and discussed. A modified random sequential absorption algorithm is applied to enhance the volume fraction number (VF) of the RVE, which the mechanical properties represents the composite material. Thirdly, based on a Spatial Segment Shortest Distance (SSSD) algorithm, a 3-Dimentional RaFC material RVE model is simulated in ABAQUS PYTHON with randomly oriented and distributed straight fibers of high fiber aspect ratio (AR=100:1) and volume fraction (VF=31.8%). Fourthly, the piecewise multi-segments fiber geometry is obtained in MATLAB environment by a modified SSSD algorithm. Finally, numerical methods including the polynomial curve fitting and piecewise quadratic and cubic B-spline interpolation are applied to optimize the RaFC fiber geometries. Based on the multi-segments fiber geometries and aforementioned techniques, smooth curved fiber geometries depicted by cubic B-spline polynomial interpolation are obtained and different types of RaFC RVEs with high fiber filament aspect ratio (AR>3000:1) and high RVE volume fraction (VF>40.29%) are simulated by ABAQUS scripting language PYTHON programming.

  18. Performance and Operational Characteristics of a Python Turbine-propeller Engine at Simulated Altitude Conditions / Carl L. Meyer and Lavern A. Johnson

    NASA Technical Reports Server (NTRS)

    Meyer, Carl L; Johnson, Lavern A

    1952-01-01

    The performance and operational characteristics of a Python turbine-propeller engine were investigated at simulated altitude conditions in the NACA Lewis altitude wind tunnel. In the performance phase, data were obtained over a range of engine speeds and exhaust nozzle areas at altitudes from 10,000 to 40,000 feet at a single cowl-inlet ram pressure ratio; independent control of engine speed and fuel flow was used to obtain a range of powers at each engine speed. Engine performance data obtained at a given altitude could not be used to predict performance accurately at other altitudes by use of the standard air pressure and temperature generalizing factors. At a given engine speed and turbine-inlet total temperature, a greater portion of the total available energy was converted to propulsive power as the altitude increased.

  19. Detecting an elusive invasive species: a diagnostic PCR to detect Burmese python in Florida waters and an assessment of persistence of environmental DNA.

    PubMed

    Piaggio, Antoinette J; Engeman, Richard M; Hopken, Matthew W; Humphrey, John S; Keacher, Kandy L; Bruce, William E; Avery, Michael L

    2014-03-01

    Recent studies have demonstrated that detection of environmental DNA (eDNA) from aquatic vertebrates in water bodies is possible. The Burmese python, Python bivittatus, is a semi-aquatic, invasive species in Florida where its elusive nature and cryptic coloration make its detection difficult. Our goal was to develop a diagnostic PCR to detect P. bivittatus from water-borne eDNA, which could assist managers in monitoring this invasive species. First, we used captive P. bivittatus to determine whether reptilian DNA could be isolated and amplified from water samples. We also evaluated the efficacy of two DNA isolation methods and two DNA extraction kits commonly used in eDNA preparation. A fragment of the mitochondrial cytochrome b gene from P. bivittatus was detected in all water samples isolated with the sodium acetate precipitate and the QIAamp DNA Micro Kit. Next, we designed P. bivittatus-specific primers and assessed the degradation rate of eDNA in water. Our primers did not amplify DNA from closely related species, and we found that P. bivittatus DNA was consistently detectable up to 96 h. Finally, we sampled water from six field sites in south Florida. Samples from five sites, where P. bivittatus has been observed, tested positive for eDNA. The final site was negative and had no prior documented evidence of P. bivittatus. This study shows P. bivittatus eDNA can be isolated from water samples; thus, this method is a new and promising technique for the management of invasive reptiles. PMID:24119154

  20. Pipe dream? Envisioning a grassroots Python ecosystem of open, common software tools and data access in support of river and coastal biogeochemical research (Invited)

    NASA Astrophysics Data System (ADS)

    Mayorga, E.

    2013-12-01

    Practical, problem oriented software developed by scientists and graduate students in domains lacking a strong software development tradition is often balkanized into the scripting environments provided by dominant, typically proprietary tools. In environmental fields, these tools include ArcGIS, Matlab, SAS, Excel and others, and are often constrained to specific operating systems. While this situation is the outcome of rational choices, it limits the dissemination of useful tools and their integration into loosely coupled frameworks that can meet wider needs and be developed organically by groups addressing their own needs. Open-source dynamic languages offer the advantages of an accessible programming syntax, a wealth of pre-existing libraries, multi-platform access, linkage to community libraries developed in lower level languages such as C or FORTRAN, and access to web service infrastructure. Python in particular has seen a large and increasing uptake in scientific communities, as evidenced by the continued growth of the annual SciPy conference. Ecosystems with distinctive physical structures and organization, and mechanistic processes that are well characterized, are both factors that have often led to the grass-roots development of useful code meeting the needs of a range of communities. In aquatic applications, examples include river and watershed analysis tools (River Tools, Taudem, etc), and geochemical modules such as CO2SYS, PHREEQ and LOADEST. I will review the state of affairs and explore the potential offered by a Python tool ecosystem in supporting aquatic biogeochemistry and water quality research. This potential is multi-faceted and broadly involves accessibility to lone grad students, access to a wide community of programmers and problem solvers via online resources such as StackExchange, and opportunities to leverage broader cyberinfrastructure efforts and tools, including those from widely different domains. Collaborative development of such tools can provide the additional advantage of enhancing cohesion and communication across specific research areas, and reducing research obstacles in a range of disciplines.

  1. Darwin and evolutionary tales in leukemia. The Ham-Wasserman Lecture.

    PubMed

    Greaves, Mel

    2009-01-01

    All cancers evolve by a process of genetic diversification and "natural selection" akin to the process first described by Charles Darwin for species evolution. The evolutionary, natural history of childhood acute lymphoblastic leukemia (ALL) is almost entirely covert, clinically silent and well advanced by the point of diagnosis. It has, however, been possible to backtrack this process by molecular scrutiny of appropriate clinical samples: (i) leukemic clones in monozygotic twins that are either concordant or discordant for ALL; (ii) archived neonatal blood spots or Guthrie cards from individuals who later developed leukemia; and (iii) stored, viable cord blood cells. These studies indicate prenatal initiation of leukemia by chromosome translocation and gene fusion (or hyperdiploidy) and the post-natal acquisition of multiple, gene copy number alterations (CNAs), mostly deletions. The prenatal or first "hit" occurs very commonly, exceeding the clinical rate of ALL by some 100x and indicating a low rate of penetrance or evolutionary progression. The acquisition of the critical, secondary CNAs requires some Darwinian selective advantage to expand numbers of cells at risk, and the cytokine TGF beta is able to exercise this function. The clonal architecture of ALL has been investigated by single cell analysis with multicolor probes to mutant genes. The data reveal not a linear sequence of mutation acquisition with clonal succession but rather considerable complexity with a tree-like or branching structure of genetically distinct subclones very reminiscent of Darwin's original 1837 evolutionary divergence diagram. This evolutionary pattern has important implications for stem cells in ALL, for the origins of relapse and for therapeutic targeting. PMID:20008176

  2. Documentation and Instructions for Running Two Python Scripts that Aid in Setting up 3D Measurements using the Polytec 3D Scanning Laser Doppler Vibrometer.

    SciTech Connect

    Rohe, Daniel Peter

    2015-08-24

    Sandia National Laboratories has recently purchased a Polytec 3D Scanning Laser Doppler Vibrometer for vibration measurement. This device has proven to be a very nice tool for making vibration measurements, and has a number of advantages over traditional sensors such as accelerometers. The non-contact nature of the laser vibrometer means there is no mass loading due to measuring the response. Additionally, the laser scanning heads can position the laser spot much more quickly and accurately than placing an accelerometer or performing a roving hammer impact. The disadvantage of the system is that a significant amount of time must be invested to align the lasers with each other and the part so that the laser spots can be accurately positioned. The Polytec software includes a number of nice tools to aid in this procedure; however, certain portions are still tedious. Luckily, the Polytec software is readily extensible by programming macros for the system, so tedious portions of the procedure can be made easier by automating the process. The Polytec Software includes a WinWrap (similar to Visual Basic) editor and interface to run macros written in that programming language. The author, however, is much more proficient in Python, and the latter also has a much larger set of libraries that can be used to create very complex macros, while taking advantage of Python’s inherent readability and maintainability.

  3. Data for giant constrictors - Biological management profiles and an establishment risk assessment for nine large species of pythons, anacondas, and the boa constrictor

    USGS Publications Warehouse

    Jarnevich, C.S.; Rodda, G.H.; Reed, R.N.

    2011-01-01

    Giant Constrictors' Climate Space The giant constrictors' climate space data set represents the information needed to recreate the climate space and climate matching analyses in Reed and Rodda (2009). A detailed methodology and results are included in that report. The data include locations for nine species of large constrictors including Python molurus, Broghammerus reticulatus, P. sebae, P. natalensis, Boa constrictor, Eunectes notaeus, E. deschauenseei, E. beniensis, and E. murinus. The locations are from published sources. Climate data are included for monthly precipitation and average monthly temperature along with the species locations. The individual spreadsheets of location data match the figures in the Reed and Rodda (2009) report, illustrating areas of the mainland United States that match the climate envelope of the native range. The precipitation and temperature data at each location were used to determine the climate space for each species. Graphs of climate space formed the basis for the algorithms in the data set, and more details can be found in Reed and Rodda (2009). These algorithms were used in ArcGIS to generate maps of areas in the United States that matched the climate space of locations of the snakes in their native range. We discovered a rounding error in ArcGIS in the implementation of the algorithms, which has been corrected here. Therefore the shapefiles are slightly different than those appearing in the risk assessment figures illustrating areas of the United States that match the climate envelope of the species in their native ranges. However, the suitable localities are not different at the scale of intended use for these maps, although there are more noticeable differences between areas classified as 'too cold' and 'too hot'.

  4. Creative Computing with Landlab: Open-Source Python Software for Building and Exploring 2D Models of Earth-Surface Dynamics

    NASA Astrophysics Data System (ADS)

    Tucker, G. E.; Hobley, D. E.; Gasparini, N. M.; Hutton, E.; Istanbulluoglu, E.; Nudurupati, S.; Adams, J. M.

    2013-12-01

    Computer models help us explore the consequences of scientific hypotheses at a level of precision and quantification that is impossible for our unaided minds. The process of writing and debugging the necessary code is often time-consuming, however, and this cost can inhibit progress. The code-development barrier can be especially problematic when a field is rapidly unearthing new data and new ideas, as is presently the case in surface dynamics. To help meet the need for rapid, flexible model development, we have written a prototype software framework for two-dimensional numerical modeling of planetary surface processes. The Landlab software can be used to develop new models from scratch, to create models from existing components, or a combination of the two. Landlab provides a gridding module that allows you to create and configure a model grid in just a few lines of code. Grids can be regular or unstructured, and can readily be used to implement staggered-grid numerical solutions to equations for various types of geophysical flow. The gridding module provides built-in functions for common numerical operations, such as calculating gradients and integrating fluxes around the perimeter of cells. Landlab is written in Python, a high-level language that enables rapid code development and takes advantage of a wealth of libraries for scientific computing and graphical output. Landlab also provides a framework for assembling new models from combinations of pre-built components. This capability is illustrated with several examples, including flood inundation, long-term landscape evolution, impact cratering, post-wildfire erosion, and ecohydrology. Interoperability with the Community Surface Dynamics Modeling System (CSDMS) Model-Coupling Framework allows models created in Landlab to be combined with other CSDMS models, which helps to bring frontier problems in landscape and seascape dynamics within closer theoretical reach.

  5. PyBetVH: A Python tool for probabilistic volcanic hazard assessment and for generation of Bayesian hazard curves and maps

    NASA Astrophysics Data System (ADS)

    Tonini, Roberto; Sandri, Laura; Anne Thompson, Mary

    2015-06-01

    PyBetVH is a completely new, free, open-source and cross-platform software implementation of the Bayesian Event Tree for Volcanic Hazard (BET_VH), a tool for estimating the probability of any magmatic hazardous phenomenon occurring in a selected time frame, accounting for all the uncertainties. New capabilities of this implementation include the ability to calculate hazard curves which describe the distribution of the exceedance probability as a function of intensity (e.g., tephra load) on a grid of points covering the target area. The computed hazard curves are (i) absolute (accounting for the probability of eruption in a given time frame, and for all the possible vent locations and eruptive sizes) and (ii) Bayesian (computed at different percentiles, in order to quantify the epistemic uncertainty). Such curves allow representation of the full information contained in the probabilistic volcanic hazard assessment (PVHA) and are well suited to become a main input to quantitative risk analyses. PyBetVH allows for interactive visualization of both the computed hazard curves, and the corresponding Bayesian hazard/probability maps. PyBetVH is designed to minimize the efforts of end users, making PVHA results accessible to people who may be less experienced in probabilistic methodologies, e.g. decision makers. The broad compatibility of Python language has also allowed PyBetVH to be installed on the VHub cyber-infrastructure, where it can be run online or downloaded at no cost. PyBetVH can be used to assess any type of magmatic hazard from any volcano. Here we illustrate how to perform a PVHA through PyBetVH using the example of analyzing tephra fallout from the Okataina Volcanic Centre (OVC), New Zealand, and highlight the range of outputs that the tool can generate.

  6. PyMS: a Python toolkit for processing of gas chromatography-mass spectrometry (GC-MS) data. Application and comparative study of selected tools

    PubMed Central

    2012-01-01

    Background Gas chromatographymass spectrometry (GC-MS) is a technique frequently used in targeted and non-targeted measurements of metabolites. Most existing software tools for processing of raw instrument GC-MS data tightly integrate data processing methods with graphical user interface facilitating interactive data processing. While interactive processing remains critically important in GC-MS applications, high-throughput studies increasingly dictate the need for command line tools, suitable for scripting of high-throughput, customized processing pipelines. Results PyMS comprises a library of functions for processing of instrument GC-MS data developed in Python. PyMS currently provides a complete set of GC-MS processing functions, including reading of standard data formats (ANDI- MS/NetCDF and JCAMP-DX), noise smoothing, baseline correction, peak detection, peak deconvolution, peak integration, and peak alignment by dynamic programming. A novel common ion single quantitation algorithm allows automated, accurate quantitation of GC-MS electron impact (EI) fragmentation spectra when a large number of experiments are being analyzed. PyMS implements parallel processing for by-row and by-column data processing tasks based on Message Passing Interface (MPI), allowing processing to scale on multiple CPUs in distributed computing environments. A set of specifically designed experiments was performed in-house and used to comparatively evaluate the performance of PyMS and three widely used software packages for GC-MS data processing (AMDIS, AnalyzerPro, and XCMS). Conclusions PyMS is a novel software package for the processing of raw GC-MS data, particularly suitable for scripting of customized processing pipelines and for data processing in batch mode. PyMS provides limited graphical capabilities and can be used both for routine data processing and interactive/exploratory data analysis. In real-life GC-MS data processing scenarios PyMS performs as well or better than leading software packages. We demonstrate data processing scenarios simple to implement in PyMS, yet difficult to achieve with many conventional GC-MS data processing software. Automated sample processing and quantitation with PyMS can provide substantial time savings compared to more traditional interactive software systems that tightly integrate data processing with the graphical user interface. PMID:22647087

  7. Using Python for Pedigree Analysis

    Technology Transfer Automated Retrieval System (TEKTRAN)

    A pedigree is a way of describing a population of people or animals in terms of genetic relationships among individuals. Pedigrees are of interest to many people, including scientists, animal and plant breeders, and genealogists. They are used to assess the diversity of populations, in combination ...

  8. ArcNEMO, a spatially distributed nutrient emission model developed in Python to quantify losses of nitrogen and phosphorous from agriculture to surface waters

    NASA Astrophysics Data System (ADS)

    Van Opstal, Mattias; Tits, Mia; Beckers, Veronique; Batelaan, Okke; Van Orshoven, Jos; Elsen, Annemie; Diels, Jan; D'heygere, Tom; Van Hoof, Kor

    2014-05-01

    Pollution of surface water bodies with nitrogen (N) and phosphorous (P) from agricultural sources is a major problem in areas with intensive agriculture in Europe. The Flemish Environment Agency requires information on how spatially explicit policy measures on manure and fertilizer use, and changes in land use and soil management affect the N and P concentration in the surface waters in the region of Flanders, Belgium. To assist in this, a new spatially distributed, mechanistic nutrient emission model was developed in the open-source language Python. The model is called ArcNEMO (Nutrient Emission MOdel). The model is fully integrated in ArcGIS, but could be easily adapted to work with open-source GIS software. In Flanders, detailed information is available each year on the delineation of each agricultural parcel and the crops grown on them. Parcels are linked to farms, and for each farm yearly manure and fertilizer use is available. To take full advantage of this information and to be able to simulate nutrient losses to the high-density surface water network, the model makes use of grid cells of 50 by 50m. A fertilizer allocation model was developed to calculate from the yearly parcel and farm data the fertilizer and manure input per grid cell for further use in the ArcNEMO-model. The model architecture was chosen such that the model can be used to simulate spatially explicit monthly discharge and losses of N and P to the surface water for the whole of Flanders (13,500 km²) over periods of 10-20 years. The extended time period is necessary because residence times in groundwater and the rates of organic matter turnover imply that water quality reacts slowly to changes of land use and fertilization practices. Vertical water flow and nutrient transport in the unsaturated zone are described per grid cell using a cascading bucket-type model with daily time steps. Groundwater flow is described by solving the 2D-groundwater flow equation using an explicit numerical solution with daily time steps. Solute transport is described using a mixing cell concept in the unsaturated zone, and by numerically solving the 2D solute transport equation in the groundwater. Denitrification in soil and groundwater is described as a first order process. Mineralisation of organic N and P in the top soil of every grid cell is modelled according to the principles of the RothC model and by assigning C:N and C:P ratios to organic matter pools. As mineralization is a slow process, it is modelled with monthly rather than daily time steps. Soil erosion and N and P transport with sediment flow is modelled in line with the WaTEM/SEDEM spatially distributed soil erosion and sediment delivery model, also with monthly time steps. The performance of the model was evaluated with discharge and water quality time series from small catchments in Flanders.

  9. Introduction of the Python script STRinNGS for analysis of STR regions in FASTQ or BAM files and expansion of the Danish STR sequence database to 11 STRs.

    PubMed

    Friis, Susanne L; Buchard, Anders; Rockenbauer, Eszter; Børsting, Claus; Morling, Niels

    2016-03-01

    This work introduces the in-house developed Python application STRinNGS for analysis of STR sequence elements in BAM or FASTQ files. STRinNGS identifies sequence reads with STR loci by their flanking sequences, it analyses the STR sequence and the flanking regions, and generates a report with the assigned SNP-STR alleles. The main output file from STRinNGS contains all sequences with read counts above 1% of the total number of reads per locus. STR sequences are automatically named according to the nomenclature used previously and according to the repeat unit definitions in STRBase (http://www.cstl.nist.gov/strbase/). The sequences are named with (1) the locus name, (2) the length of the repeat region divided by the length of the repeat unit, (3) the sequence(s) of the repeat unit(s) followed by the number of repeats and (4) variations in the flanking regions. Lower case letters in the main output file are used to flag sequences with previously unknown variations in the STRs. SNPs in the flanking regions are named by their "rs" numbers and the nucleotides in the SNP position. Data from 207 Danes sequenced with the Ion Torrent™ HID STR 10-plex that amplified nine STRs (CSF1PO, D3S1358, D5S818, D7S820, D8S1179, D16S539, TH01, TPOX, vWA), and Amelogenin was analysed with STRinNGS. Sequencing uncovered five common SNPs near four STRs and revealed 20 new alleles in the 207 Danes. Three short homopolymers in the D8S1179 flanking regions caused frequent sequencing errors. In 29 of 3726 allele calls (0.8%), sequences with homopolymer errors were falsely assigned as true alleles. An in-house developed script in R compensated for these errors by compiling sequence reads that had identical STR sequences and identical nucleotides in the five common SNPs. In the output file from the R script, all SNP-STR haplotype calls were correct. The 207 samples and six additional samples were sequenced for D3S1358, D12S391, and D21S11 using the 454 GS Junior platform in this and a previous work. Overall, next generation sequencing (NGS) of the 11 STRs lowered the mean match probability 386 times and increased the typical paternity indexes (i.e. the geometric mean) for trios and duos 47 and 23 times, respectively, compared to the traditional PCR-CE typing of the same population. PMID:26722765

  10. MTpy: A Python toolbox for magnetotellurics

    USGS Publications Warehouse

    Krieger, Lars; Peacock, Jared R.

    2014-01-01

    In this paper, we introduce the structure and concept of MTpy  . Additionally, we show some examples from an everyday work-flow of MT data processing: the generation of standard EDI data files from raw electric (E-) and magnetic flux density (B-) field time series as input, the conversion into MiniSEED data format, as well as the generation of a graphical data representation in the form of a Phase Tensor pseudosection.

  11. PyCS : Python Curve Shifting

    NASA Astrophysics Data System (ADS)

    Tewes, Malte

    2015-09-01

    PyCS is a software toolbox to estimate time delays between multiple images of strongly lensed quasars, from resolved light curves such as obtained by the COSMOGRAIL monitoring program. The pycs package defines a collection of classes and high level functions, that you can script in a flexible way. PyCS makes it easy to compare different point estimators (including your own) without much code integration. The package heavily depends on numpy, scipy, and matplotlib.

  12. Python Engine Installed in Altitude Wind Tunnel

    NASA Technical Reports Server (NTRS)

    1949-01-01

    An engine mechanic checks instrumentation prior to an investigation of engine operating characteristics and thrust control of a large turboprop engine with counter-rotating propellers under high-altitude flight conditions in the 20-foot-dianieter test section of the Altitude Wind Tunnel at the Lewis Flight Propulsion Laboratory of the National Advisory Committee for Aeronautics, Cleveland, Ohio, now known as the John H. Glenn Research Center at Lewis Field.

  13. Medieval Romances: "Perceval" to "Monty Python."

    ERIC Educational Resources Information Center

    Jehle, Dorothy M.

    A selection of romances from medieval literature can be used successfully in undergraduate literature classes to trace the appearance and relevance of medieval themes, motifs, and characters in works of modern poetry, fiction, and film. New scholarly editions, historiographies, translations, and modernizations give both teachers and students more…

  14. Zachary-Fort Lauderdale pipeline construction and conversion project: final supplement to final environmental impact statement. Docket No. CP74-192

    SciTech Connect

    1980-05-01

    This Final Supplement to the Final Environmental Impact Statement (Final Supplement) evaluates the economic, engineering, and environmental aspects of newly developed alternatives to an abandonment/conversion project proposed by Florida Gas Transmission Company (Florida Gas). It also updates the staff's previous FEIS and studies revisions to the original proposal. Wherever possible, the staff has adopted portions of its previous FEIS in lieu of reprinting portions of that analysis which require no change. 60 references, 8 figures, 35 tables.

  15. The role of structural ledges at phase boundaries; 2: F. c. c. -b. c. c. interfaces in Nishiyama-Wasserman orientation

    SciTech Connect

    Shiflet, G.J.; Merwe, J.H. van der . Dept. of Physics)

    1994-04-01

    The ledge mode of misfit accommodation was first postulated for boundaries between b.c.c. and f.c.c metal phases; the interfaces being [111] f.c.c.-[110] b.c.c. planes and relative orientations varying from Nishiyama-Wassermann (NW) to Kurdjumov-Sachs (KS). Here the geometrical quantities are uniquely related by the misfit ratio r of atomic diameters. They consider the so-called NW-x configuration in which the orientation is imposed by close matching along the <[bar 2]11> f.c.c. and <[bar 1]10> b.c.c. (taken as x-) directions. From the fact that no net shear pattern displacements are present with x-ledges (ledges normal to the x-direction) it is concluded that they are energetically preferable to y-ledges and justifies the approach of an energetic comparison between stepped interfaces with x-ledges and a planar interface containing conventional misfit dislocations (MDs). The NW-x stepped configuration is at first subjected to a rigid model analysis, i.e. a model with rigid crystals and periodic (truncated Fourier representation) interfacial interaction. This analysis provides (1) energetic justification for a relation between terrace periodicity and misfit cancellation, (2) values of upper and lower average energy bounds, (3) a method for estimating interfacial shear moduli, and (4) a motivation for the suggestion that a relative rigid translation of the crystals is needed for energy minimization.

  16. The Funeral of Froggy the Frog: The Child as Dramatist, Designer, and Realist

    ERIC Educational Resources Information Center

    Cummins, Lauren

    2004-01-01

    One sunny afternoon, six-year-old Zachary and his friend John Michael, four and a half, discovered a dead frog in a bag of clay in the garage. Zachary proposed, "Let's have a funeral for the frog." This is how the funeral drama of Froggy the Frog began. This article describes the play experiences of Zachary and John Michael as designers,

  17. The Funeral of Froggy the Frog: The Child as Dramatist, Designer, and Realist

    ERIC Educational Resources Information Center

    Cummins, Lauren

    2004-01-01

    One sunny afternoon, six-year-old Zachary and his friend John Michael, four and a half, discovered a dead frog in a bag of clay in the garage. Zachary proposed, "Let's have a funeral for the frog." This is how the funeral drama of Froggy the Frog began. This article describes the play experiences of Zachary and John Michael as designers,…

  18. Crates and Transform: Python Interfaces for Data Analysis

    NASA Astrophysics Data System (ADS)

    Lyn, J.; Cresitello-Dittmar, M.; Evans, I.; Evans, J. D.

    2014-05-01

    With its flexible design and ease-of-use, Crates and Transform have been incorporated into the Chandra X-Ray Center's (CXC) data visualization and fitting tools and data processing scripts to facilitate a wide variety of tasks. Chandra's fitting and modeling application, called Sherpa, uses Crates as an underlying data access module, taking advantage of its ability to interpret standard Flexible Image Transport System (FITS) files, such as Redistribution Matrix Files (RMF), Auxiliary Response Files(ARF), and both types of Pulse Height Analysis (PHA) files. The Chandra Imaging and Plotting System (ChIPS) tool utilizes the associated Transform module for visualizing data in different World Coordinate Systems (WCS). By using the CXC DataModel (DM) as a backend, Crates can perform advanced filtering and binning techniques on data. This capability, combined with its simple Application Programming Interface, make it ideal for incorporation into our data analysis scripts, aiding with operations from simple keyword manipulation to creating and writing multiple Header Definition Unit (HDU) files. Crates and Transform are available respectively as the pycrates and pytransform modules within the Chandra Interactive Analysis of Observations (CIAO) environment to assist users with their own analysis threads. In this paper, we will illustrate the capabilities of the Crates and Transform modules and how they are being used within the CXC for analysis.

  19. Pablo Python Looks at Animals. [Multimedia Educational Kit].

    ERIC Educational Resources Information Center

    Sullivan, Rick; Green, David

    Teachers and students can view the world of animals together through an exploration of how-and-why questions about animals in this curriculum unit. The problem-solving and critical thinking skills of students are improved through interactive activities involving oral and written communication, mathematics, creative arts, music, dance, and creative

  20. rely.py, a python script to detect reliable clades.

    PubMed

    Li, Blaise; Dettai, Agns; Lecointre, Guillaume

    2010-01-01

    rely.py is a program implementing the method to detect independently repeated clades by comparing phylogenies as described in Li and Lecointre (2009) and adapted to incompletely overlapping datasets in Li et al. (2009). The comparison can be performed on trees obtained by any inference method (maximum parsimony, Bayesian inference, maximum likelihood). The program computes repetition indices, provides greedy summary trees for each validity domain and a nexus matrix representation of the clades weighted by their repetition indices. The additional script concatnexus.py assists the user in preparing the primary analyses, but it can also be used separately to concatenate nexus datasets. PMID:19800976

  1. DiffPy-CMI-Python libraries for Complex Modeling Initiative

    SciTech Connect

    2014-02-01

    Software to manipulate and describe crystal and molecular structures and set up structural refinements from multiple experimental inputs. Calculation and simulation of structure derived physical quantities. Library for creating customized refinements of atomic structures from available experimental and theoretical inputs.

  2. Pablo Python Looks at Animals. [Multimedia Educational Kit].

    ERIC Educational Resources Information Center

    Sullivan, Rick; Green, David

    Teachers and students can view the world of animals together through an exploration of how-and-why questions about animals in this curriculum unit. The problem-solving and critical thinking skills of students are improved through interactive activities involving oral and written communication, mathematics, creative arts, music, dance, and creative…

  3. Gully measurement strategies in a pixel using python

    NASA Astrophysics Data System (ADS)

    Wells, Robert; Momm, Henrique; Bennett, Sean; Dabney, Seth

    2015-04-01

    Gullies are often the single largest sediment sources within the landscape; however, measurement and process description of these channels presents challenges that have limited complete understanding. A strategy currently being employed in the field and laboratory to measure topography of gullies utilizes inexpensive, off-the-shelf cameras and software. Photogrammetry may be entering an enlightened period, as users have numerous choices (cameras, lenses, and software) and many are utilizing the technology to define their surroundings; however, the key for those seeking answers will be what happens once topography is represented as a three-dimensional digital surface model. Perhaps the model can be compared with another model to visualize change, either in topography or in vegetation cover, or both. With these models of our landscape, prediction technology should be rejuvenated and/or reinvented. Over the past several decades, researchers have endeavored to capture the erosion process and transfer these observations through oral and written word. Several have hypothesized a fundamental system for gully expression in the landscape; however, this understanding has not transferred well into our prediction technology. Unlike many materials, soils often times do not behave in a predictable fashion. Which soil physical properties lend themselves to erosion process description? In most cases, several disciplines are required to visualize the erosion process and its impact on our landscape. With a small camera, the landscape becomes more accessible and this accessibility will lead to a deeper understanding and development of uncompromised erosion theory. Why? Conservation of our soil resources is inherently linked to a complete understanding of soil wasting.

  4. Tabizi Pythons and Clendro Hawks: Using Imaginary Animals to Achieve Real Knowledge about Ecosystems

    ERIC Educational Resources Information Center

    Rockow, Michael

    2007-01-01

    The author describes how he used to teach a unit on food webs and ecosystems using actual food webs as models. However, the models used by the author tend to be either too simplistic or too complicated for his students. A few years ago, he solved these problems by making up his own food web, complete with invented plants and animals. The model has

  5. A Python tool to set up relative free energy calculations in GROMACS.

    PubMed

    Klimovich, Pavel V; Mobley, David L

    2015-11-01

    Free energy calculations based on molecular dynamics (MD) simulations have seen a tremendous growth in the last decade. However, it is still difficult and tedious to set them up in an automated manner, as the majority of the present-day MD simulation packages lack that functionality. Relative free energy calculations are a particular challenge for several reasons, including the problem of finding a common substructure and mapping the transformation to be applied. Here we present a tool, alchemical-setup.py, that automatically generates all the input files needed to perform relative solvation and binding free energy calculations with the MD package GROMACS. When combined with Lead Optimization Mapper (LOMAP;Liu et al. in J Comput Aided Mol Des 27(9):755-770, 2013), recently developed in our group, alchemical-setup.py allows fully automated setup of relative free energy calculations in GROMACS. Taking a graph of the planned calculations and a mapping, both computed by LOMAP, our tool generates the topology and coordinate files needed to perform relative free energy calculations for a given set of molecules, and provides a set of simulation input parameters. The tool was validated by performing relative hydration free energy calculations for a handful of molecules from the SAMPL4 challenge (Mobley et al. in J Comput Aided Mol Des 28(4):135-150, 2014). Good agreement with previously published results and the straightforward way in which free energy calculations can be conducted make alchemical-setup.py a promising tool for automated setup of relative solvation and binding free energy calculations. PMID:26487189

  6. The Python Project: A Unique Model for Extending Research Opportunities to Undergraduate Students

    ERIC Educational Resources Information Center

    Harvey, Pamela A.; Wall, Christopher; Luckey, Stephen W.; Langer, Stephen; Leinwand, Leslie A.

    2014-01-01

    Undergraduate science education curricula are traditionally composed of didactic instruction with a small number of laboratory courses that provide introductory training in research techniques. Research on learning methodologies suggests this model is relatively ineffective, whereas participation in independent research projects promotes enhanced

  7. Pyro: A Python-Based Versatile Programming Environment for Teaching Robotics

    ERIC Educational Resources Information Center

    Blank, Douglas; Kumar, Deepak; Meeden, Lisa; Yanco, Holly

    2004-01-01

    In this article we describe a programming framework called Pyro, which provides a set of abstractions that allows students to write platform-independent robot programs. This project is unique because of its focus on the pedagogical implications of teaching mobile robotics via a top-down approach. We describe the background of the project, its

  8. pySPACEa signal processing and classification environment in Python

    PubMed Central

    Krell, Mario M.; Straube, Sirko; Seeland, Anett; Whrle, Hendrik; Teiwes, Johannes; Metzen, Jan H.; Kirchner, Elsa A.; Kirchner, Frank

    2013-01-01

    In neuroscience large amounts of data are recorded to provide insights into cerebral information processing and function. The successful extraction of the relevant signals becomes more and more challenging due to increasing complexities in acquisition techniques and questions addressed. Here, automated signal processing and machine learning tools can help to process the data, e.g., to separate signal and noise. With the presented software pySPACE (http://pyspace.github.io/pyspace), signal processing algorithms can be compared and applied automatically on time series data, either with the aim of finding a suitable preprocessing, or of training supervised algorithms to classify the data. pySPACE originally has been built to process multi-sensor windowed time series data, like event-related potentials from the electroencephalogram (EEG). The software provides automated data handling, distributed processing, modular build-up of signal processing chains and tools for visualization and performance evaluation. Included in the software are various algorithms like temporal and spatial filters, feature generation and selection, classification algorithms, and evaluation schemes. Further, interfaces to other signal processing tools are provided and, since pySPACE is a modular framework, it can be extended with new algorithms according to individual needs. In the presented work, the structural hierarchies are described. It is illustrated how users and developers can interface the software and execute offline and online modes. Configuration of pySPACE is realized with the YAML format, so that programming skills are not mandatory for usage. The concept of pySPACE is to have one comprehensive tool that can be used to perform complete signal processing and classification tasks. It further allows to define own algorithms, or to integrate and use already existing libraries. PMID:24399965

  9. pySPACE-a signal processing and classification environment in Python.

    PubMed

    Krell, Mario M; Straube, Sirko; Seeland, Anett; Wöhrle, Hendrik; Teiwes, Johannes; Metzen, Jan H; Kirchner, Elsa A; Kirchner, Frank

    2013-01-01

    In neuroscience large amounts of data are recorded to provide insights into cerebral information processing and function. The successful extraction of the relevant signals becomes more and more challenging due to increasing complexities in acquisition techniques and questions addressed. Here, automated signal processing and machine learning tools can help to process the data, e.g., to separate signal and noise. With the presented software pySPACE (http://pyspace.github.io/pyspace), signal processing algorithms can be compared and applied automatically on time series data, either with the aim of finding a suitable preprocessing, or of training supervised algorithms to classify the data. pySPACE originally has been built to process multi-sensor windowed time series data, like event-related potentials from the electroencephalogram (EEG). The software provides automated data handling, distributed processing, modular build-up of signal processing chains and tools for visualization and performance evaluation. Included in the software are various algorithms like temporal and spatial filters, feature generation and selection, classification algorithms, and evaluation schemes. Further, interfaces to other signal processing tools are provided and, since pySPACE is a modular framework, it can be extended with new algorithms according to individual needs. In the presented work, the structural hierarchies are described. It is illustrated how users and developers can interface the software and execute offline and online modes. Configuration of pySPACE is realized with the YAML format, so that programming skills are not mandatory for usage. The concept of pySPACE is to have one comprehensive tool that can be used to perform complete signal processing and classification tasks. It further allows to define own algorithms, or to integrate and use already existing libraries. PMID:24399965

  10. SkData: data sets and algorithm evaluation protocols in Python

    NASA Astrophysics Data System (ADS)

    Bergstra, James; Pinto, Nicolas; Cox, David D.

    2015-01-01

    Machine learning benchmark data sets come in all shapes and sizes, whereas classification algorithms assume sanitized input, such as (x, y) pairs with vector-valued input x and integer class label y. Researchers and practitioners know all too well how tedious it can be to get from the URL of a new data set to a NumPy ndarray suitable for e.g. pandas or sklearn. The SkData library handles that work for a growing number of benchmark data sets (small and large) so that one-off in-house scripts for downloading and parsing data sets can be replaced with library code that is reliable, community-tested, and documented. The SkData library also introduces an open-ended formalization of training and testing protocols that facilitates direct comparison with published research. This paper describes the usage and architecture of the SkData library.

  11. A standard python environment for software applications at the Robert C. Byrd Green Bank Telescope (GBT)

    NASA Astrophysics Data System (ADS)

    Radziwill, Nicole M.; Shelton, Amy L.

    2006-06-01

    Since 2003, the monitor and control software systems for the Robert C. Byrd Green Bank Telescope (GBT) have been substantially redesigned to make the telescope easier to use. The result is the release of the Astronomer's Integrated Desktop (Astrid), an observation management platform used to create and submit scheduling blocks, monitor their progress on the telescope, and provide a real time, quick look data display. Using Astrid, the astronomer launches one application and has access to all of the software, documentation, and feedback facilities that are required to conduct an interactive observing session. These systems together provide a common look and feel for GBT software applications, enable offline observation preparation, and facilitate dynamic scheduling and remote observing.

  12. Phenix - a comprehensive python-based system for macromolecular structure solution

    SciTech Connect

    Terwilliger, Thomas C; Hung, Li - Wei; Adams, Paul D; Afonine, Pavel V; Bunkoczi, Gabor; Chen, Vincent B; Davis, Ian; Echols, Nathaniel; Headd, Jeffrey J; Grosse Kunstleve, Ralf W; Mccoy, Airlie J; Moriarty, Nigel W; Oeffner, Robert; Read, Randy J; Richardson, David C; Richardson, Jane S; Zwarta, Peter H

    2009-01-01

    Macromolecular X-ray crystallography is routinely applied to understand biological processes at a molecular level. However, significant time and effort are still required to solve and complete many of these structures because of the need for manual interpretation of complex numerical data using many software packages, and the repeated use of interactive three-dimensional graphics. Phenix has been developed to provide a comprehensive system for crystallographic structure solution with an emphasis on automation of all procedures. This has relied on the development of algorithms that minimize or eliminate subjective input, the development of algorithms that automate procedures that are traditionally performed by hand, and finally the development of a framework that allows a tight integration between the algorithms.

  13. The Python Project: A Unique Model for Extending Research Opportunities to Undergraduate Students

    ERIC Educational Resources Information Center

    Harvey, Pamela A.; Wall, Christopher; Luckey, Stephen W.; Langer, Stephen; Leinwand, Leslie A.

    2014-01-01

    Undergraduate science education curricula are traditionally composed of didactic instruction with a small number of laboratory courses that provide introductory training in research techniques. Research on learning methodologies suggests this model is relatively ineffective, whereas participation in independent research projects promotes enhanced…

  14. A Rapid Python-Based Methodology for Target-Focused Combinatorial Library Design.

    PubMed

    Li, Shiliang; Song, Yuwei; Liu, Xiaofeng; Li, Honglin

    2016-01-01

    The chemical space is so vast that only a small portion of it has been examined. As a complementary approach to systematically probe the chemical space, virtual combinatorial library design has extended enormous impacts on generating novel and diverse structures for drug discovery. Despite the favorable contributions, high attrition rates in drug development that mainly resulted from lack of efficacy and side effects make it increasingly challenging to discover good chemical starting points. In most cases, focused libraries, which are restricted to particular regions of the chemical space, are deftly exploited to maximize hit rate and improve efficiency at the beginning of the drug discovery and drug development pipeline. This paper presented a valid methodology for fast target-focused combinatorial library design in both reaction-based and production-based ways with the library creating rates of approximately 70,000 molecules per second. Simple, quick and convenient operating procedures are the specific features of the method. SHAFTS, a hybrid 3D similarity calculation software, was embedded to help refine the size of the libraries and improve hit rates. Two target-focused (p38-focused and COX2-focused) libraries were constructed efficiently in this study. This rapid library enumeration method is portable and applicable to any other targets for good chemical starting points identification collaborated with either structure-based or ligand-based virtual screening. PMID:26522993

  15. Pyro: A Python-Based Versatile Programming Environment for Teaching Robotics

    ERIC Educational Resources Information Center

    Blank, Douglas; Kumar, Deepak; Meeden, Lisa; Yanco, Holly

    2004-01-01

    In this article we describe a programming framework called Pyro, which provides a set of abstractions that allows students to write platform-independent robot programs. This project is unique because of its focus on the pedagogical implications of teaching mobile robotics via a top-down approach. We describe the background of the project, its…

  16. From Monty Python to Total Recall: A Feature Film Activity for the Cognitive Psychology Course.

    ERIC Educational Resources Information Center

    Conner, David B.

    1996-01-01

    Describes a college psychology course activity designed to help students define the parameters of cognitive psychology. Students selected a feature film and a journal article that represented some aspect of cognitive psychology. They then wrote a paper discussing the theoretical and empirical connections between the sources and the topic. (MJP)

  17. Tabizi Pythons and Clendro Hawks: Using Imaginary Animals to Achieve Real Knowledge about Ecosystems

    ERIC Educational Resources Information Center

    Rockow, Michael

    2007-01-01

    The author describes how he used to teach a unit on food webs and ecosystems using actual food webs as models. However, the models used by the author tend to be either too simplistic or too complicated for his students. A few years ago, he solved these problems by making up his own food web, complete with invented plants and animals. The model has…

  18. The Python Project: A Unique Model for Extending Research Opportunities to Undergraduate Students

    PubMed Central

    Harvey, Pamela A.; Wall, Christopher; Luckey, Stephen W.; Langer, Stephen

    2014-01-01

    Undergraduate science education curricula are traditionally composed of didactic instruction with a small number of laboratory courses that provide introductory training in research techniques. Research on learning methodologies suggests this model is relatively ineffective, whereas participation in independent research projects promotes enhanced knowledge acquisition and improves retention of students in science. However, availability of faculty mentors and limited departmental budgets prevent the majority of students from participating in research. A need therefore exists for this important component in undergraduate education in both small and large university settings. A course was designed to provide students with the opportunity to engage in a research project in a classroom setting. Importantly, the course collaborates with a sponsor's laboratory, producing a symbiotic relationship between the classroom and the laboratory and an evolving course curriculum. Students conduct a novel gene expression study, with their collective data being relevant to the ongoing research project in the sponsor's lab. The success of this course was assessed based on the quality of the data produced by the students, student perception data, student learning gains, and on whether the course promoted interest in and preparation for careers in science. In this paper, we describe the strategies and outcomes of this course, which represents a model for efficiently providing research opportunities to undergraduates. PMID:25452492

  19. 75 FR 11808 - Injurious Wildlife Species; Listing the Boa Constrictor, Four Python Species, and Four Anaconda...

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-03-12

    ... South Florida. The Service published a notice of inquiry in the Federal Register (73 FR 5784; January 31... they hatch, but nevertheless are independent from birth, grow rapidly, and mature in a few years... captive, female green anaconda that was 5 years old in 1976 and that had no access to males gave birth...

  20. Weatherizing America

    SciTech Connect

    Stewart, Zachary; Bergeron, T.J.; Barth, Dale; Qualis, Xavier; Sewall, Travis; Fransen, Richard; Gill, Tony

    2009-01-01

    As Recovery Act money arrives to expand home weatherization programs across the country, Zachary Stewart of Phoenix, Ariz., and others have found an exciting opportunity not only to start working again, but also to find a calling.

  1. Weatherizing America

    ScienceCinema

    Stewart, Zachary; Bergeron, T.J.; Barth, Dale; Qualis, Xavier; Sewall, Travis; Fransen, Richard; Gill, Tony;

    2013-05-29

    As Recovery Act money arrives to expand home weatherization programs across the country, Zachary Stewart of Phoenix, Ariz., and others have found an exciting opportunity not only to start working again, but also to find a calling.

  2. PORT HUDSON NATIONAL CEMETERY PLAQUE, FORMERLY MOUNTED AT BASE OF ...

    Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

    PORT HUDSON NATIONAL CEMETERY PLAQUE, FORMERLY MOUNTED AT BASE OF FLAGPOLE, PRESENTLY STORED IN SERVICE BUILDING. VIEW TO WEST. - Port Hudson National Cemetery, 20978 Port Hickey Road, Zachary, East Baton Rouge Parish, LA

  3. 78 FR 66367 - National Institute of General Medical Sciences; Notice of Closed Meetings

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-11-05

    ..., MD 20815. Contact Person: John J. Laffan, Ph.D., Scientific Review Officer, Office of Scientific... L. Zachary, Ph.D., Scientific Review Officer, Office of Scientific Review, National Institute...

  4. SAE2.py : a python script to automate parameter studies using SCREAMER with application to magnetic switching on Z.

    SciTech Connect

    Orndorff-Plunkett, Franklin

    2011-05-01

    The SCREAMER simulation code is widely used at Sandia National Laboratories for designing and simulating pulsed power accelerator experiments on super power accelerators. A preliminary parameter study of Z with a magnetic switching retrofit illustrates the utility of the automating script for optimizing pulsed power designs. SCREAMER is a circuit based code commonly used in pulsed-power design and requires numerous iterations to find optimal configurations. System optimization using simulations like SCREAMER is by nature inefficient and incomplete when done manually. This is especially the case when the system has many interactive elements whose emergent effects may be unforeseeable and complicated. For increased completeness, efficiency and robustness, investigators should probe a suitably confined parameter space using deterministic, genetic, cultural, ant-colony algorithms or other computational intelligence methods. I have developed SAE2 - a user-friendly, deterministic script that automates the search for optima of pulsed-power designs with SCREAMER. This manual demonstrates how to make input decks for SAE2 and optimize any pulsed-power design that can be modeled using SCREAMER. Application of SAE2 to magnetic switching on model of a potential Z refurbishment illustrates the power of SAE2. With respect to the manual optimization, the automated optimization resulted in 5% greater peak current (10% greater energy) and a 25% increase in safety factor for the most highly stressed element.

  5. The Unlock Project: A Python-based framework for practical brain-computer interface communication app development

    PubMed Central

    Brumberg, Jonathan S.; Lorenz, Sean D.; Galbraith, Byron V.; Guenther, Frank H.

    2013-01-01

    In this paper we present a framework for reducing the development time needed for creating applications for use in non-invasive brain-computer interfaces (BCI). Our framework is primarily focused on facilitating rapid software app development akin to current efforts in consumer portable computing (e.g. smart phones and tablets). This is accomplished by handling intermodule communication without direct user or developer implementation, instead relying on a core subsystem for communication of standard, internal data formats. We also provide a library of hardware interfaces for common mobile EEG platforms for immediate use in BCI applications. A use-case example is described in which a user with amyotrophic lateral sclerosis participated in an electroencephalography-based BCI protocol developed using the proposed framework. We show that our software environment is capable of running in real-time with updates occurring 5060 times per second with limited computational overhead (5 ms system lag) while providing accurate data acquisition and signal analysis. PMID:23366434

  6. Efficient multi-objective calibration of a computationally intensive hydrologic model with parallel computing software in Python

    Technology Transfer Automated Retrieval System (TEKTRAN)

    With enhanced data availability, distributed watershed models for large areas with high spatial and temporal resolution are increasingly used to understand water budgets and examine effects of human activities and climate change/variability on water resources. Developing parallel computing software...

  7. Modeling Multiphase Coastal and Hydraulic Processes in an Interactive Python Environment with the Open Source Proteus Toolkit

    NASA Astrophysics Data System (ADS)

    Kees, C. E.; Farthing, M. W.; Ahmadia, A. J.; Bakhtyar, R.; Miller, C. T.

    2014-12-01

    Hydrology is dominated by multiphase flow processes, due to the importance of capturing water's interaction with soil and air phases. Unfortunately, many different mathematical model formulations are required to model particular processes and scales of interest, and each formulation often requires specialized numerical methods. The Proteus toolkit is a software package for research on models for coastal and hydraulic processes and improvements in numerics, particularly 3D multiphase processes and parallel numerics. The models considered include multiphase flow, shallow water flow, turbulent free surface flow, and various flow-driven processes. We will discuss the objectives of Proteus and recent evolution of the toolkit's design as well as present examples of how it has been used used to construct computational models of multiphase flows for the US Army Corps of Engineers. Proteus is also an open source toolkit authored primarily within the US Army Corps of Engineers, and used, developed, and maintained by a small community of researchers in both theoretical modeling and computational methods research. We will discuss how open source and community development practices have played a role in the creation of Proteus.

  8. PyLDTk: Python toolkit for calculating stellar limb darkening profiles and model-specific coefficients for arbitrary filters

    NASA Astrophysics Data System (ADS)

    Parviainen, Hannu

    2015-10-01

    PyLDTk automates the calculation of custom stellar limb darkening (LD) profiles and model-specific limb darkening coefficients (LDC) using the library of PHOENIX-generated specific intensity spectra by Husser et al. (2013). It facilitates exoplanet transit light curve modeling, especially transmission spectroscopy where the modeling is carried out for custom narrow passbands. PyLDTk construct model-specific priors on the limb darkening coefficients prior to the transit light curve modeling. It can also be directly integrated into the log posterior computation of any pre-existing transit modeling code with minimal modifications to constrain the LD model parameter space directly by the LD profile, allowing for the marginalization over the whole parameter space that can explain the profile without the need to approximate this constraint by a prior distribution. This is useful when using a high-order limb darkening model where the coefficients are often correlated, and the priors estimated from the tabulated values usually fail to include these correlations.

  9. The Unlock Project: a Python-based framework for practical brain-computer interface communication "app" development.

    PubMed

    Brumberg, Jonathan S; Lorenz, Sean D; Galbraith, Byron V; Guenther, Frank H

    2012-01-01

    In this paper we present a framework for reducing the development time needed for creating applications for use in non-invasive brain-computer interfaces (BCI). Our framework is primarily focused on facilitating rapid software "app" development akin to current efforts in consumer portable computing (e.g. smart phones and tablets). This is accomplished by handling intermodule communication without direct user or developer implementation, instead relying on a core subsystem for communication of standard, internal data formats. We also provide a library of hardware interfaces for common mobile EEG platforms for immediate use in BCI applications. A use-case example is described in which a user with amyotrophic lateral sclerosis participated in an electroencephalography-based BCI protocol developed using the proposed framework. We show that our software environment is capable of running in real-time with updates occurring 50-60 times per second with limited computational overhead (5 ms system lag) while providing accurate data acquisition and signal analysis. PMID:23366434

  10. Opening the Black Box of Social Cognitive Mapping

    ERIC Educational Resources Information Center

    Neal, Zachary P.; Neal, Jennifer Watling

    2013-01-01

    This article provides Zachary P. Neal and Jennifer Watling Neal's response to Thomas W. Farmer and Hongling Xie's commentary on Neal and Neal's "Multiple Meanings of Peer Groups in Social Cognitive Mapping." Neal and Neal assert that many of Farmer and Xie's comments highlight the motivation behind their original…

  11. Opening the Black Box of Social Cognitive Mapping

    ERIC Educational Resources Information Center

    Neal, Zachary P.; Neal, Jennifer Watling

    2013-01-01

    This article provides Zachary P. Neal and Jennifer Watling Neal's response to Thomas W. Farmer and Hongling Xie's commentary on Neal and Neal's "Multiple Meanings of Peer Groups in Social Cognitive Mapping." Neal and Neal assert that many of Farmer and Xie's comments highlight the motivation behind their original

  12. Peer Mentoring and Action Learning

    ERIC Educational Resources Information Center

    O'Neil, Judy; Marsick, Victoria J.

    2009-01-01

    Mentoring has been defined in many different ways. Traditionally, mentoring is seen as a relationship between an older, more experienced mentor and a younger, less experienced protege for the purpose of helping and developing the protege's career. Zachary's (2005) description best fits the process discussed in this article: "Mentoring is best

  13. 77 FR 26968 - Final Flood Elevation Determinations

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-05-08

    ... Executive Order 12866 of September 30, 1993, Regulatory Planning and Review, 58 FR 51735. Executive Order....C. 4001 et seq.; Reorganization Plan No. 3 of 1978, 3 CFR, ] 1978 Comp., p. 329; E.O. 12127, 44 FR... upstream of Albert Drive. Redwood Creek Approximately 900 feet +92 City of Zachary, downstream of...

  14. Arapahos on the Great Plains. Student Workbook.

    ERIC Educational Resources Information Center

    Spoonhunter, Bob; Woodenlegs, Martha

    The student workbook is derived from "An Ethnological Report on Cheyenne and Arapaho: Aboriginal Occupation," by Zachary Gussow and "Northern Snows to Southern Summers--An Arapaho Odyssey," by Bob Spoonhunter. The first section discusses the Arapaho origins by recounting many different legends that explain how they arrived on the Great Plains. The

  15. "Creating Unity from Diversity: Finding Our Commonalities, Respecting Our Differences." Presenter Abstracts of the Annual National Conference of the National Multicultural Institute (9th, Washington, D.C., May 19-22, 1994).

    ERIC Educational Resources Information Center

    National Multicultural Inst., Washington, DC.

    This is primarily a collection of abstracts for training workshops for professionals in the field of multicultural education. The abstracts are: (1) "An Exploration of the Unspoken: A Group Relations Approach to Multicultural Dialogue" (Zachary G. Green); (2) "Exploring Our Cultural Assumptions" (Daniel Rivera); (3) "Challenging Homophobia:

  16. Some Fast Food for Thought!

    ERIC Educational Resources Information Center

    Instructor, 1978

    1978-01-01

    An interview with Professor Zacharie Clements focuses on the educational bureaucracy, issues related to the back-to-basics movement, and cutbacks in school funding. Professor Clements advocates pep rallies for teachers who do a good job despite the drawbacks of the teaching profession. (CM)

  17. Proceedings of the Annual Meeting of the Association for Education in Journalism and Mass Communication (85th, Miami, Florida, August 5-8, 2002). Commission on the Status of Women Division.

    ERIC Educational Resources Information Center

    2002

    The Commission on the Status of Women Division of the proceedings contains the following 6 papers: "Relationship Content in Four Men's and Women's Magazines" (Alexis Zachary and Bryan Denham); "Mind the Gender Gap: Gender Differences in Motivation to Contribute Online Content" (Cindy Royal); "Peering through the Glass Ceiling of the Boys' Club:…

  18. Strategies for Change in Information Programs.

    ERIC Educational Resources Information Center

    Hug, William E., Ed.

    Part 1 of this two-part book examines "the subtle and ubiquitous nature of change." The purpose of the first group of readings is twofold. First, the works of Wasserman, Meadow, McAnally and Downs, Pettinger and Zapol, and Steere comment and report on needs, obstructions, and futures of many aspects of library-media-information programs and

  19. Keats: A Collection of Critical Essays. Twentieth Century Views Series.

    ERIC Educational Resources Information Center

    Bate, Walter Jackson, Ed.

    One of a series of works aimed at presenting contemporary critical opinion on major authors, this collection includes essays by Walter Jackson Bate, T. S. Eliot, Douglas Bush, Richard H. Fogle, Jack Stillinger, Harold Bloom, David Perkins, Earl Wasserman, and D. G. James--all dealing with the biography and literary work of John Keats. Designed for…

  20. Dryden: A Collection of Critical Essays. Twentieth Century Views Series.

    ERIC Educational Resources Information Center

    Schilling, Bernard N., Ed.

    One of a series of works aimed at presenting contemporary critical opinion on major authors, this collection includes essays by Bernard Schilling, T. S. Eliot, Louis I. Bredvold, James M. Osborn, Reuben A. Brower, Edwin Morgan, Earl Wasserman, R. J. Kaufmann, Moody E. Prior, Earl W. Miner, Edward N. Hooker, E. M. W. Tillyard, John Hollander,…

  1. 78 FR 54255 - HRSA's Bureau of Health Professions Advanced Education Nursing Traineeship Program

    Federal Register 2010, 2011, 2012, 2013, 2014

    2013-09-03

    ... Education Nursing Traineeship Program AGENCY: Health Resources and Services Administration (HRSA), HHS... Education Nursing Traineeship (AENT) program. Effective fiscal year (FY) 2014, AENT support for part-time... practitioners and nurse midwives. FOR FURTHER INFORMATION CONTACT: Joan Wasserman, DrPH, RN, Advanced...

  2. Corrigendum.

    PubMed

    2016-01-01

    Zuckerman SL, Kerr ZY, Yengo-Kahn A, Wasserman E, Covassin T, Solomon GS. Epidemiology of sports-related concussion in NCAA athletes from 2009-2010 to 2013-2014: incidence, recurrence, and mechanisms. Am J Sports Med. 2015;43(11):2654-2662. (Original DOI: 10.1177/0363546515599634). PMID:26729730

  3. Effects of Stimulus Duration and Choice Delay on Visual Categorization in Pigeons

    ERIC Educational Resources Information Center

    Lazareva, Olga F.; Wasserman, Edward A.

    2009-01-01

    We [Lazareva, O. F., Freiburger, K. L., & Wasserman, E. A. (2004). "Pigeons concurrently categorize photographs at both basic and superordinate levels." "Psychonomic Bulletin and Review," 11, 1111-1117] previously trained four pigeons to classify color photographs into their basic-level categories (cars, chairs, flowers, or people) or into their

  4. Pupil Dilation and Object Permanence in Infants

    ERIC Educational Resources Information Center

    Sirois, Sylvain; Jackson, Iain R.

    2012-01-01

    This paper examines the relative merits of looking time and pupil diameter measures in the study of early cognitive abilities of infants. Ten-month-old infants took part in a modified version of the classic drawbridge experiment used to study object permanence (Baillargeon, Spelke, & Wasserman, 1985). The study involved a factorial design where

  5. Effects of Stimulus Duration and Choice Delay on Visual Categorization in Pigeons

    ERIC Educational Resources Information Center

    Lazareva, Olga F.; Wasserman, Edward A.

    2009-01-01

    We [Lazareva, O. F., Freiburger, K. L., & Wasserman, E. A. (2004). "Pigeons concurrently categorize photographs at both basic and superordinate levels." "Psychonomic Bulletin and Review," 11, 1111-1117] previously trained four pigeons to classify color photographs into their basic-level categories (cars, chairs, flowers, or people) or into their…

  6. Stata Hybrids: Updates and Ideas

    NASA Technical Reports Server (NTRS)

    Fieldler, James

    2014-01-01

    At last year's Stata conference I presented two projects for using Python with Stata: a plugin that embeds the Python programming language within Stata and code for using Stata data sets in Python. In this talk I will describe some small improvements being made to these projects, and I will present other ideas for combining tools with Stata. Some of these ideas use Python, some use JavaScript and a web browser.

  7. 76 FR 40082 - Semiannual Regulatory Agenda

    Federal Register 2010, 2011, 2012, 2013, 2014

    2011-07-07

    .... 225 Injurious Wildlife 1018-AV68 Evaluation; Constrictor Species From Python, Boa, and Eunectes Genera.... Timetable: Action Date FR Cite NPRM 12/00/11 Regulatory Flexibility Analysis Required: Yes. Agency Contact..., Northern African python, Southern African python, boa constrictor, yellow anaconda, DeSchauensee's...

  8. PyUtilib: A Pythos Utility Library v. 1.0

    Energy Science and Technology Software Center (ESTSC)

    2010-01-07

    PyUtilib is a collection of Python utilities that are used by Python packages developed at Sandia National Laboratories, including the Coopr and FAST Python packages. PyUtilib includes facilities for managing factories, subprocess management, interfacing with Excel, and applying numerical techniques.

  9. MISR Toolkit

    Atmospheric Science Data Center

    2014-05-07

    ... x64). Its core interface is C. There are also bindings for Python and IDL. It is available as source and Windows binaries (zip or installer). The python and IDL binary modules require Python 2.7 and IDL 8.2 respectively. ...

  10. Orbital stability in combined uniform axial and three-dimensional wiggler magnetic fields for free-electron lasers

    NASA Technical Reports Server (NTRS)

    Johnston, S.

    1984-01-01

    Zachary Phys. Rev. A 29 (6), 3224 (1984) recently analyzed the instability of relativistic-electron helical trajectories in combined uniform axial and helical wiggler magnetic fields when the radial variation of the wiggler field is taken into account. It is shown here that the type 2 instability comprised of secular terms growing linearly in time, identified by Zachary and earlier by Diament Phys. Rev. A 23 (5), 2537 (1981), is an artifact of simple perturbation theory. A multiple-time-scale perturbation analysis reveals a nonsecular evolution on a slower time scale which accommodates an arbitrary initial perturbation. It is shown that, in the absence of exponential instability, the electron seeks a modified helical orbit more appropriate to its perturbed state and oscillates stably about it. Thus, the perturbed motion is oscillatory but nonsecular, and hence the helical orbits are stable.

  11. Factors Mediating Alcohol Craving and Relapse: Stress, Compulsivity, and Genetics

    PubMed Central

    Rodd, Zachary A.; Anstrom, Kristin K; Knapp, Darin J.; Racz, Ildiko; Zimmer, Andreas; Serra, Salvatore; Bell, Richard L.; Woodward, Donald J.; Breese, George R.; Colombo, Giancarlo

    2010-01-01

    This article represents the proceedings of a symposium at the 2004 annual meeting of the International Society for Biomedical Research on Alcoholism in Heidelberg, Germany. The symposium was organized by Zachary A. Rodd and Giancarlo Colombo. The presentations were (1) Pharmacological reversal of cycled withdrawal-sensitized or stress-sensitized withdrawal anxiety and enhanced ethanol drinking, by Darin J. Knapp and George R. Breese, (2) Alcohol craving and relapse in rats genetically selected for high alcohol preference, by Zachary A. Rodd and Richard L. Bell, (3) Exposure to stress increases dopaminergic burst firing in awake rats, by Kristin Anstrom and Donald J. Woodward, (4) Involvement of cannabinoid CB1 and GABAB receptors in the control of relapse-like drinking in alcohol-preferring Sardinian alcohol-preferring rats by Giancarlo Colombo and Salvatore Serra, and (5) Stress-induced ethanol drinking in CB1?/?, POMC, and PENK knockout mice, by Idiko Racz and Andreas Zimmer. PMID:16088996

  12. Developing operational algorithms using linear and non-linear squares estimation in Python for the identification of Culex pipiens and Culex restuans in a mosquito abatement district (Cook County, Illinois, USA).

    PubMed

    Jacob, Benjamin J; Gu, Weidong; Caamano, Erik X; Novak, Robert J

    2009-05-01

    In this research, community level spatial models were developed for determining mosquito abundance and environmental factors that could aid in the risk prediction of West Nile virus (WNv) outbreaks. Adult Culex pipiens and Culex restuan mosquitoes and multiple habitat covariates were collected from nine sites within Cook County, Illinois, USA, to provide spatio-temporal information on the abundance of WNv vectors from 2002 to 2005. Regression analyses of the sampled covariates revealed that the adult Culex population was positively associated with temperature throughout the sampling frame. The model output also indicated that precipitation was negatively associated to mosquito abundance in 2002, 2003 and 2005 (P <0.05), but positively associated in 2004 (P <0.05). A land use land cover classification, based on QuickBird visible and near infra-red data, acquired at 0.61 m resolution, was used to investigate possible associations between geographical features and the abundance of sampled Culex oviposition surveillance sites. A maximum likelihood unsupervised classification in ArcInfo 9.2(R) revealed that the highest overall mosquito abundance was found in sites having a low-to-moderate range of built environment (40%) and high forest composition. A set of propagation equations were then designed to model the calibration uncertainties, which revealed that normalized difference vegetation index (NDVI), and two NDVI variants, were informative markers for the sampled mosquito data. Spatial dependence of the covariates of Cx. restuans and Cx. pipiens oviposition sites were indexed using semivariograms, which suggested that all main effects of the explanatory variables were statistically significant in the model. Additionally, a multispectral classification and digital elevation model-based geographical information system method were able to evaluate stream flow direction and accumulation for identification of terrain covariates associated with the sampled habitat data. These results demonstrate that remotely sensed operational indices can be used to identify parameters associated with field-sampled Cx. pipiens and Cx. restuans aquatic habitats. PMID:19440960

  13. Surface Structure Determination of Hematite Using Low-Energy X-Ray Photoelectron Diffraction

    NASA Astrophysics Data System (ADS)

    Thevuthasan, S.; Kim, Y. J.; Chambers, S. A.; Morais, J.; Denecke, R.; Fadley, C. S.; Liu, P.; Kendelewicz, T.; Brown, D. E.

    1998-03-01

    The structure and composition of oxide surfaces strongly influence their chemical and mechanical properities. As such, there is a growing interest of determining the nature of surface termination, reconstruction and relaxation on these surfaces. Recent theoretical work by Wasserman et. al [1] have shown that hematite(? - Fe_2O_3(0001)) surface has a single Fe layer termination with relaxations in the first four planes of -49%, -3%, -41%, and 21% respectively. Recently, we performed low-energy x-ray photoelectron diffraction measurements at Advanced Light Source on a clean epitaxially grown hematite(0001) surface and preliminary analysis confirms some of the findings from the theoretical work. We will discuss these results along with theoretical simulations. ([1] Wasserman et. al, Surf. Sci. 383 (1997)) (Work supported by the U.S. DOE - Environmental Management Science Program)

  14. Chaotic self-similar wave maps coupled to gravity

    NASA Astrophysics Data System (ADS)

    Szybka, Sebastian J.

    2004-04-01

    It was shown recently that the SU(2) sigma model coupled to gravity has periodic spherically symmetric self-similar solutions for small values of the coupling constant. In this article we extend the analysis of Bizo?, Szybka, and Wasserman to larger values of the coupling constant (??0.426) and present numerical evidence for the chaotic solution and the fractal threshold behavior. We explain this phenomenon in terms of horseshoelike dynamics and heteroclinic intersections.

  15. Optical Transmission: Enhanced Optical Transmission through MacEtch-Fabricated Buried Metal Gratings (Adv. Mater. 7/2016).

    PubMed

    Liu, Runyu; Zhao, Xiang; Roberts, Christopher; Yu, Lan; Mohseni, Parsian K; Li, Xiuling; Podolskiy, Viktor; Wasserman, Daniel

    2016-02-01

    On page 1441, D. Wasserman and co-workers demonstrate a nanostructured thin film formed by engraving a thin, patterned metal layer into a semiconductor substrate via the MacEtch technique. The patterned film allows for enhanced electrical contact and simultaneously transmits more light than a smooth air-semiconductor interface. The demonstrated approach has the potential for integration with a wide range of optoelectronic devices. PMID:26866622

  16. Heider balance in human networks

    NASA Astrophysics Data System (ADS)

    Gawro?ski, P.; Ku?akowski, K.

    2005-07-01

    Recently, a continuous dynamics was proposed to simulate dynamics of interpersonal relations in a society represented by a fully connected graph. The final state of such a society was found to be identical with the so-called Heider balance (HB), where the society is divided into two mutually hostile groups. In the continuous model, a polarization of opinions was found in HB. Here we demonstrate that the polarization occurs also in Barabsi-Albert networks, where the Heider balance is not necessarily present. In the second part of this work we demonstrate the results of our formalism, when applied to reference examples: the Southern women and the Zachary club.

  17. Weighting dissimilarities to detect communities in networks.

    PubMed

    Alvarez, Alejandro J; Sanz-Rodrguez, Carlos E; Cabrera, Juan Luis

    2015-12-13

    Many complex systems can be described as networks exhibiting inner organization as communities of nodes. The identification of communities is a key factor to understand community-based functionality. We propose a family of measures based on the weighted sum of two dissimilarity quantifiers that facilitates efficient classification of communities by tuning the quantifiers' relative weight to the network's particularities. Additionally, two new dissimilarities are introduced and incorporated in our analysis. The effectiveness of our approach is tested by examining the Zachary's Karate Club Network and the Caenorhabditis elegans reactions network. The analysis reveals the method's classification power as confirmed by the efficient detection of intrapathway metabolic functions in C. elegans. PMID:26527808

  18. 77 FR 7968 - Semiannual Regulatory Agenda

    Federal Register 2010, 2011, 2012, 2013, 2014

    2012-02-13

    .... 391 Injurious Wildlife 1018-AV68 Evaluation; Constrictor Species From Python, Boa, and Eunectes Genera... federally owned or controlled lands and/or waters. Timetable: Action Date FR Cite NPRM 07/00/12 Regulatory... (FWS) Final Rule Stage 391. Injurious Wildlife Evaluation; Constrictor Species From Python, Boa,...

  19. Pyomo

    Energy Science and Technology Software Center (ESTSC)

    2007-08-30

    Pyomo is a Python package that can be used to define abstract problems, create concrete problem instances, and solve these instances with standard solvers. Pyomo provides a capability that is commonly associated with algebraic modeling languages like AMPL and GAMS. However, Pyomo can leverage Python's programming environment to support the development of complex models and optimization solvers in the same modeling environment.

  20. PyTrilinos Rapid Prototyping Package

    Energy Science and Technology Software Center (ESTSC)

    2005-03-01

    PyTrilinos provides access to selected Trilinos packages from the python scripting language. This allows interactive and dynamic creation of Trilinos objects, rapid prototyping that does not require compilation, and "gluing" Trilinos scripts to other python modules, such as plotting, etc. The currently supported packages are Epetra, EpetraExt, and NOX.

  1. PyTrilinos

    Energy Science and Technology Software Center (ESTSC)

    2015-10-19

    PyTrilinos is a Python interface to selected Trilinos packages. This makes Trilinos linear algebra classes, linear solvers, preconditioners, nonlinear solvers, eigensolvers, and tools available to Python programmers. This broadens the user base of Trilinos, and facilitates rapid prototyping of scientific codes and interactive manipulation of large, distributed data sets.

  2. Martensite Formation in Hydrogen-Containing Metastable Austenitic Stainless Steel During Micro-Tension Testing

    NASA Astrophysics Data System (ADS)

    Mine, Yoji; Hirashita, Koichi; Matsuda, Mitsuhiro; Takashima, Kazuki

    2011-12-01

    Deformation-induced martensite in type 304 stainless steel during micro-tension testing was characterized. The stress-strain behavior of uncharged and hydrogen-charged specimens revealed that hydrogen hastened the onset of hardening but decreased the strain-hardening rate, leading to premature plastic instability. In both specimens, a set of twin-related ?'-martensite variants with Kurdjumov-Sachs relationships was prevalent. The Nishiyama-Wasserman relationship variant was also formed, but it was suppressed by hydrogen. This may be attributed to differences in the underlying deformation microstructure.

  3. Polar Oxide Interface Stabilization by Formation of Metallic Nanocrystals

    SciTech Connect

    Lazarov, Vlado; Chambers, Scott A.; Gajdardziska-Josifovska, Marija

    2003-06-13

    In-situ X ray photo-electron spectroscopy and ex-situ transmission electron microscopy and diffraction studies of a model Fe3O4(111)/MgO(111) polar oxide interface exclude stabilization by interface faceting, and uncover stabilization by dominant formation of metallic Fe(110) nanocrystals. The iron nanocrystals nucleate both at the interface and with in the magnetite film and grow in a Nishiyama-Wasserman orientation relationship with a bimodal size distribution related to twinning. Minority magnetite nanocrystals were also observed, growing in the less polar (100) orientation than the magnetite (111) film.

  4. Pizza.py Toolkit

    SciTech Connect

    2006-01-01

    Pizza.py is a loosely integrated collection of tools, many of which provide support for the LAMMPS molecular dynamics and ChemCell cell modeling packages. There are tools to create input files. convert between file formats, process log and dump files, create plots, and visualize and animate simulation snapshots. Software packages that are wrapped by Pizza.py. so they can invoked from within Python, include GnuPlot, MatLab, Raster3d. and RasMol. Pizza.py is written in Python and runs on any platform that supports Python. Pizza.py enhances the standard Python interpreter in a few simple ways. Its tools are Python modules which can be invoked interactively, from scripts, or from GUIs when appropriate. Some of the tools require additional Python packages to be installed as part of the users Python. Others are wrappers on software packages (as listed above) which must be available on the users system. It is easy to modify or extend Pizza.py with new functionality or new tools, which need not have anything to do with LAMMPS or ChemCell.

  5. Pizza.py Toolkit

    Energy Science and Technology Software Center (ESTSC)

    2006-01-01

    Pizza.py is a loosely integrated collection of tools, many of which provide support for the LAMMPS molecular dynamics and ChemCell cell modeling packages. There are tools to create input files. convert between file formats, process log and dump files, create plots, and visualize and animate simulation snapshots. Software packages that are wrapped by Pizza.py. so they can invoked from within Python, include GnuPlot, MatLab, Raster3d. and RasMol. Pizza.py is written in Python and runs onmore »any platform that supports Python. Pizza.py enhances the standard Python interpreter in a few simple ways. Its tools are Python modules which can be invoked interactively, from scripts, or from GUIs when appropriate. Some of the tools require additional Python packages to be installed as part of the users Python. Others are wrappers on software packages (as listed above) which must be available on the users system. It is easy to modify or extend Pizza.py with new functionality or new tools, which need not have anything to do with LAMMPS or ChemCell.« less

  6. CyNEST: a maintainable Cython-based interface for the NEST simulator

    PubMed Central

    Zaytsev, Yury V.; Morrison, Abigail

    2014-01-01

    NEST is a simulator for large-scale networks of spiking point neuron models (Gewaltig and Diesmann, 2007). Originally, simulations were controlled via the Simulation Language Interpreter (SLI), a built-in scripting facility implementing a language derived from PostScript (Adobe Systems, Inc., 1999). The introduction of PyNEST (Eppler et al., 2008), the Python interface for NEST, enabled users to control simulations using Python. As the majority of NEST users found PyNEST easier to use and to combine with other applications, it immediately displaced SLI as the default NEST interface. However, developing and maintaining PyNEST has become increasingly difficult over time. This is partly because adding new features requires writing low-level C++ code intermixed with calls to the Python/C API, which is unrewarding. Moreover, the Python/C API evolves with each new version of Python, which results in a proliferation of version-dependent code branches. In this contribution we present the re-implementation of PyNEST in the Cython language, a superset of Python that additionally supports the declaration of C/C++ types for variables and class attributes, and provides a convenient foreign function interface (FFI) for invoking C/C++ routines (Behnel et al., 2011). Code generation via Cython allows the production of smaller and more maintainable bindings, including increased compatibility with all supported Python releases without additional burden for NEST developers. Furthermore, this novel approach opens up the possibility to support alternative implementations of the Python language at no cost given a functional Cython back-end for the corresponding implementation, and also enables cross-compilation of Python bindings for embedded systems and supercomputers alike. PMID:24672470

  7. CyNEST: a maintainable Cython-based interface for the NEST simulator.

    PubMed

    Zaytsev, Yury V; Morrison, Abigail

    2014-01-01

    NEST is a simulator for large-scale networks of spiking point neuron models (Gewaltig and Diesmann, 2007). Originally, simulations were controlled via the Simulation Language Interpreter (SLI), a built-in scripting facility implementing a language derived from PostScript (Adobe Systems, Inc., 1999). The introduction of PyNEST (Eppler et al., 2008), the Python interface for NEST, enabled users to control simulations using Python. As the majority of NEST users found PyNEST easier to use and to combine with other applications, it immediately displaced SLI as the default NEST interface. However, developing and maintaining PyNEST has become increasingly difficult over time. This is partly because adding new features requires writing low-level C++ code intermixed with calls to the Python/C API, which is unrewarding. Moreover, the Python/C API evolves with each new version of Python, which results in a proliferation of version-dependent code branches. In this contribution we present the re-implementation of PyNEST in the Cython language, a superset of Python that additionally supports the declaration of C/C++ types for variables and class attributes, and provides a convenient foreign function interface (FFI) for invoking C/C++ routines (Behnel et al., 2011). Code generation via Cython allows the production of smaller and more maintainable bindings, including increased compatibility with all supported Python releases without additional burden for NEST developers. Furthermore, this novel approach opens up the possibility to support alternative implementations of the Python language at no cost given a functional Cython back-end for the corresponding implementation, and also enables cross-compilation of Python bindings for embedded systems and supercomputers alike. PMID:24672470

  8. Model Analysis ToolKit

    Energy Science and Technology Software Center (ESTSC)

    2015-05-15

    MATK provides basic functionality to facilitate model analysis within the Python computational environment. Model analysis setup within MATK includes: - define parameters - define observations - define model (python function) - define samplesets (sets of parameter combinations) Currently supported functionality includes: - forward model runs - Latin-Hypercube sampling of parameters - multi-dimensional parameter studies - parallel execution of parameter samples - model calibration using internal Levenberg-Marquardt algorithm - model calibration using lmfit package - modelmore » calibration using levmar package - Markov Chain Monte Carlo using pymc package MATK facilitates model analysis using: - scipy - calibration (scipy.optimize) - rpy2 - Python interface to R« less

  9. Model Analysis ToolKit

    SciTech Connect

    2015-05-15

    MATK provides basic functionality to facilitate model analysis within the Python computational environment. Model analysis setup within MATK includes: - define parameters - define observations - define model (python function) - define samplesets (sets of parameter combinations) Currently supported functionality includes: - forward model runs - Latin-Hypercube sampling of parameters - multi-dimensional parameter studies - parallel execution of parameter samples - model calibration using internal Levenberg-Marquardt algorithm - model calibration using lmfit package - model calibration using levmar package - Markov Chain Monte Carlo using pymc package MATK facilitates model analysis using: - scipy - calibration (scipy.optimize) - rpy2 - Python interface to R

  10. The morphology, crystallography, and chemistry of phases in as-cast nickel-aluminum bronze

    NASA Astrophysics Data System (ADS)

    Hasan, F.; Jahanafrooz, A.; Lorimer, G. W.; Ridley, N.

    1982-08-01

    The morphology, crystallography, and composition of the phases present in as-cast nickel-aluminum bronze of nominal composition copper-10 wt pct aluminum-5 wt pct nickel-5 wt pct iron have been investigated using optical, electron optical, and microprobe analysis techniques. The as-cast microstructure consists of copper-rich α, martensitic β, and κ-phases based on Fe3Al and NiAl. The κz precipitates have a dendritic morphology and are cored; the composition ranges from iron-rich solid solution to Fe3Al. The κII and κiv precipitates have, respectively, a dendritic and an equiaxed/dendritic morphology, and are based on Fe3Al, while κIII is a eutectoidal decomposition product of lamellar or globular morphology based on NiAl. The κI, κII, and κIII precipitates have the Kurdjumov-Sachs orientation relationship with α matrix. Small κIV precipitates exhibit the Nishiyama-Wasserman orientation relationship with the α matrix, while large κiv precipitates have an orientation relationship which lies between Kurdjumov-Sachs and Nishiyama-Wasserman.

  11. Relational Learning in a Context of Transposition: A Review

    PubMed Central

    Lazareva, Olga F

    2012-01-01

    In a typical transposition task, an animal is presented with a single pair of stimuli (for example, S3+ S4?, where plus and minus denote reward and nonreward and digits denote stimulus location on a sensory dimension such as size). Subsequently, an animal is presented with a testing pair that contains a previously reinforced or nonreinforced stimulus and a novel stimulus (for example, S2S3 and S4S5). Does the choice of a novel S2 instead of previously reinforced S3 in a testing pair S2S3 indicate that the animal has learned a relation (i.e., select smaller)? This review of empirical evidence and theoretical accounts shows that an organism's behavior in a transposition task is undoubtedly influenced by prior reinforcement history of the training stimuli (Spence, 1937). However, it is also affected by two other factors that are relational in naturea similarity of two testing stimuli to each other and an overall similarity of the testing pair as a whole to the training pair as a whole. The influence of the two latter factors is especially evident in studies that use multiple pairs of training stimuli and a wide range of testing pairs comprising nonadjacent stimuli (Lazareva, Miner, Young, & Wasserman, 2008; Lazareva, Wasserman, & Young, 2005). In sum, the evidence suggests that both prior reinforcement history and relational information affect an animal's behavior in a typical transposition task. PMID:22389528

  12. Mole Pi: Using New Technology to Teach the Magnitude of a Mole

    ERIC Educational Resources Information Center

    Geyer, Michael J.

    2014-01-01

    A modified technique for demonstrating the magnitude of Avogadro's number using a new Raspberry Pi computer and the Python language is described. The technique also provides students the opportunity to review dimensional analysis.

  13. VESPA: False positive probabilities calculator

    NASA Astrophysics Data System (ADS)

    Morton, Timothy D.

    2015-03-01

    Validation of Exoplanet Signals using a Probabilistic Algorithm (VESPA) calculates false positive probabilities and statistically validates transiting exoplanets. Written in Python, it uses isochrones [ascl:1503.010] and the package simpledist.

  14. George: Gaussian Process regression

    NASA Astrophysics Data System (ADS)

    Foreman-Mackey, Dan

    2015-11-01

    George is a fast and flexible library, implemented in C++ with Python bindings, for Gaussian Process regression useful for accounting for correlated noise in astronomical datasets, including those for transiting exoplanet discovery and characterization and stellar population modeling.

  15. SNL cxxtest v. 1.0

    Energy Science and Technology Software Center (ESTSC)

    2010-04-28

    SNL cxxtest is a set of Python routines that support software testing for C++ codes. This software augments the open-source cxxtest project to provide a more comprehensive capability for software testing.

  16. ctools: Cherenkov Telescope Science Analysis Software

    NASA Astrophysics Data System (ADS)

    Knödlseder, Jürgen; Mayer, Michael; Deil, Christoph; Buehler, Rolf; Bregeon, Johan; Martin, Pierrick

    2016-01-01

    ctools provides tools for the scientific analysis of Cherenkov Telescope Array (CTA) data. Analysis of data from existing Imaging Air Cherenkov Telescopes (such as H.E.S.S., MAGIC or VERITAS) is also supported, provided that the data and response functions are available in the format defined for CTA. ctools comprises a set of ftools-like binary executables with a command-line interface allowing for interactive step-wise data analysis. A Python module allows control of all executables, and the creation of shell or Python scripts and pipelines is supported. ctools provides cscripts, which are Python scripts complementing the binary executables. Extensions of the ctools package by user defined binary executables or Python scripts is supported. ctools are based on GammaLib (ascl:1110.007).

  17. Web service performance script

    Energy Science and Technology Software Center (ESTSC)

    2009-08-01

    This python script, available from ESRI and modified here, checks a server at specified intervals to ensure that web services remain up and running. If any are found to be off, they are automatically turned back on.

  18. AstroML: Machine learning and data mining in astronomy

    NASA Astrophysics Data System (ADS)

    VanderPlas, Jacob; Fouesneau, Morgan; Taylor, Julia

    2014-07-01

    Written in Python, AstroML is a library of statistical and machine learning routines for analyzing astronomical data in python, loaders for several open astronomical datasets, and a large suite of examples of analyzing and visualizing astronomical datasets. An optional companion library, astroML_addons, is available; it requires a C compiler and contains faster and more efficient implementations of certain algorithms in compiled code.

  19. k2photometry: Read, reduce and detrend K2 photometry

    NASA Astrophysics Data System (ADS)

    Van Eylen, Vincent; Nowak, Grzegorz; Albrecht, Simon; Palle, Enric; Ribas, Ignasi; Bruntt, Hans; Perger, Manuel; Gandolfi, Davide; Hirano, Teriyuki; Sanchis-Ojeda, Roberto; Kiilerich, Amanda; Arranz, Jorge P.; Badenas, Mariona; Dai, Fei; Deeg, Hans J.; Guenther, Eike W.; Montanes-Rodriguez, Pilar; Narita, Norio; Rogers, Leslie A.; Bejar, Victor J. S.; Shrotriya, Tushar S.; Winn, Joshua N.; Sebastian, Daniel

    2016-02-01

    k2photometry reads, reduces and detrends K2 photometry and searches for transiting planets. MAST database pixel files are used as input; the output includes raw lightcurves, detrended lightcurves and a transit search can be performed as well. Stellar variability is not typically well-preserved but parameters can be tweaked to change that. The BLS algorithm used to detect periodic events is a Python implementation by Ruth Angus and Dan Foreman-Mackey (https://github.com/dfm/python-bls).

  20. Death in the White House: President William Henry Harrison's Atypical Pneumonia.

    PubMed

    McHugh, Jane; Mackowiak, Philip A

    2014-10-01

    Historians have long maintained that pneumonia killed William Henry Harrison (1773-1841) just 1 month after he became the ninth president of the United States. For more than a century and a half, it has been alleged that the aged Harrison caught a fatal chill the day he was sworn into office while delivering an overly long inaugural address in wet, freezing weather without a hat, overcoat, and gloves. However, a careful review of the detailed case summary written by his personal physician suggests that enteric fever, not pneumonia per se, was the disorder that carried off "Old Tippecanoe." Two other presidents of that era, James Knox Polk and Zachary Taylor, also developed severe gastroenteritis while in office. Taylor's illness, like Harrison's, proved fatal. In all 3 cases, the illnesses were likely a consequence of the unsanitary conditions that existed in the nation's capital during most of the nineteenth century. PMID:24962997