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Sample records for python mixture package

  1. MGtoolkit: A python package for implementing metagraphs

    NASA Astrophysics Data System (ADS)

    Ranathunga, D.; Nguyen, H.; Roughan, M.

    In this paper we present MGtoolkit: an open-source Python package for implementing metagraphs - a first of its kind. Metagraphs are commonly used to specify and analyse business and computer-network policies alike. MGtoolkit can help verify such policies and promotes learning and experimentation with metagraphs. The package currently provides purely textual output for visualising metagraphs and their analysis results.

  2. Gala: A Python package for galactic dynamics

    NASA Astrophysics Data System (ADS)

    Price-Whelan, Adrian M.

    2017-10-01

    Gala is an Astropy-affiliated Python package for galactic dynamics. Python enables wrapping low-level languages (e.g., C) for speed without losing flexibility or ease-of-use in the user-interface. The API for Gala was designed to provide a class-based and user-friendly interface to fast (C or Cython-optimized) implementations of common operations such as gravitational potential and force evaluation, orbit integration, dynamical transformations, and chaos indicators for nonlinear dynamics. Gala also relies heavily on and interfaces well with the implementations of physical units and astronomical coordinate systems in the Astropy package (astropy.units and astropy.coordinates). Gala was designed to be used by both astronomical researchers and by students in courses on gravitational dynamics or astronomy. It has already been used in a number of scientific publications and has also been used in graduate courses on Galactic dynamics to, e.g., provide interactive visualizations of textbook material.

  3. 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 ismore » therefore fast and able to handle large datasets. The Gist module includes an X Windows event dispatcher which can be dynamically added (e.g., via importing a dynamically loaded module) to the Python interpreter after a simple two-line modification to the Python core. This makes fast mouse-controlled zoom, pan, and other graphic operations available to the researcher while maintaining the usual Python command-line interface. Munro`s Gist library is already freely available. The Python Gist module is currently under review and is also expected to qualify for unlimited release.« less

  4. pysimm: A Python Package for Simulation of Molecular Systems

    NASA Astrophysics Data System (ADS)

    Fortunato, Michael; Colina, Coray

    pysimm, short for python simulation interface for molecular modeling, is a python package designed to facilitate the structure generation and simulation of molecular systems through convenient and programmatic access to object-oriented representations of molecular system data. This poster presents core features of pysimm and design philosophies that highlight a generalized methodology for incorporation of third-party software packages through API interfaces. The integration with the LAMMPS simulation package is explained to demonstrate this methodology. pysimm began as a back-end python library that powered a cloud-based application on nanohub.org for amorphous polymer simulation. The extension from a specific application library to general purpose simulation interface is explained. Additionally, this poster highlights the rapid development of new applications to construct polymer chains capable of controlling chain morphology such as molecular weight distribution and monomer composition.

  5. PYCHEM: a multivariate analysis package for python.

    PubMed

    Jarvis, Roger M; Broadhurst, David; Johnson, Helen; O'Boyle, Noel M; Goodacre, Royston

    2006-10-15

    We have implemented a multivariate statistical analysis toolbox, with an optional standalone graphical user interface (GUI), using the Python scripting language. This is a free and open source project that addresses the need for a multivariate analysis toolbox in Python. Although the functionality provided does not cover the full range of multivariate tools that are available, it has a broad complement of methods that are widely used in the biological sciences. In contrast to tools like MATLAB, PyChem 2.0.0 is easily accessible and free, allows for rapid extension using a range of Python modules and is part of the growing amount of complementary and interoperable scientific software in Python based upon SciPy. One of the attractions of PyChem is that it is an open source project and so there is an opportunity, through collaboration, to increase the scope of the software and to continually evolve a user-friendly platform that has applicability across a wide range of analytical and post-genomic disciplines. http://sourceforge.net/projects/pychem

  6. 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

  7. graphkernels: R and Python packages for graph comparison

    PubMed Central

    Ghisu, M Elisabetta; Llinares-López, Felipe; Borgwardt, Karsten

    2018-01-01

    Abstract Summary Measuring the similarity of graphs is a fundamental step in the analysis of graph-structured data, which is omnipresent in computational biology. Graph kernels have been proposed as a powerful and efficient approach to this problem of graph comparison. Here we provide graphkernels, the first R and Python graph kernel libraries including baseline kernels such as label histogram based kernels, classic graph kernels such as random walk based kernels, and the state-of-the-art Weisfeiler-Lehman graph kernel. The core of all graph kernels is implemented in C ++ for efficiency. Using the kernel matrices computed by the package, we can easily perform tasks such as classification, regression and clustering on graph-structured samples. Availability and implementation The R and Python packages including source code are available at https://CRAN.R-project.org/package=graphkernels and https://pypi.python.org/pypi/graphkernels. Contact mahito@nii.ac.jp or elisabetta.ghisu@bsse.ethz.ch Supplementary information Supplementary data are available online at Bioinformatics. PMID:29028902

  8. graphkernels: R and Python packages for graph comparison.

    PubMed

    Sugiyama, Mahito; Ghisu, M Elisabetta; Llinares-López, Felipe; Borgwardt, Karsten

    2018-02-01

    Measuring the similarity of graphs is a fundamental step in the analysis of graph-structured data, which is omnipresent in computational biology. Graph kernels have been proposed as a powerful and efficient approach to this problem of graph comparison. Here we provide graphkernels, the first R and Python graph kernel libraries including baseline kernels such as label histogram based kernels, classic graph kernels such as random walk based kernels, and the state-of-the-art Weisfeiler-Lehman graph kernel. The core of all graph kernels is implemented in C ++ for efficiency. Using the kernel matrices computed by the package, we can easily perform tasks such as classification, regression and clustering on graph-structured samples. The R and Python packages including source code are available at https://CRAN.R-project.org/package=graphkernels and https://pypi.python.org/pypi/graphkernels. mahito@nii.ac.jp or elisabetta.ghisu@bsse.ethz.ch. Supplementary data are available online at Bioinformatics. © The Author(s) 2017. Published by Oxford University Press.

  9. Eddylicious: A Python package for turbulent inflow generation

    NASA Astrophysics Data System (ADS)

    Mukha, Timofey; Liefvendahl, Mattias

    2018-01-01

    A Python package for generating inflow for scale-resolving computer simulations of turbulent flow is presented. The purpose of the package is to unite existing inflow generation methods in a single code-base and make them accessible to users of various Computational Fluid Dynamics (CFD) solvers. The currently existing functionality consists of an accurate inflow generation method suitable for flows with a turbulent boundary layer inflow and input/output routines for coupling with the open-source CFD solver OpenFOAM.

  10. DREAMTools: a Python package for scoring collaborative challenges

    PubMed Central

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

    2016-01-01

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

  11. Analysis of counting data: Development of the SATLAS Python package

    NASA Astrophysics Data System (ADS)

    Gins, W.; de Groote, R. P.; Bissell, M. L.; Granados Buitrago, C.; Ferrer, R.; Lynch, K. M.; Neyens, G.; Sels, S.

    2018-01-01

    For the analysis of low-statistics counting experiments, a traditional nonlinear least squares minimization routine may not always provide correct parameter and uncertainty estimates due to the assumptions inherent in the algorithm(s). In response to this, a user-friendly Python package (SATLAS) was written to provide an easy interface between the data and a variety of minimization algorithms which are suited for analyzinglow, as well as high, statistics data. The advantage of this package is that it allows the user to define their own model function and then compare different minimization routines to determine the optimal parameter values and their respective (correlated) errors. Experimental validation of the different approaches in the package is done through analysis of hyperfine structure data of 203Fr gathered by the CRIS experiment at ISOLDE, CERN.

  12. A cross-validation package driving Netica with python

    USGS Publications Warehouse

    Fienen, Michael N.; Plant, Nathaniel G.

    2014-01-01

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

  13. astroplan: An Open Source Observation Planning Package in Python

    NASA Astrophysics Data System (ADS)

    Morris, Brett M.; Tollerud, Erik; Sipőcz, Brigitta; Deil, Christoph; Douglas, Stephanie T.; Berlanga Medina, Jazmin; Vyhmeister, Karl; Smith, Toby R.; Littlefair, Stuart; Price-Whelan, Adrian M.; Gee, Wilfred T.; Jeschke, Eric

    2018-03-01

    We present astroplan—an open source, open development, Astropy affiliated package for ground-based observation planning and scheduling in Python. astroplan is designed to provide efficient access to common observational quantities such as celestial rise, set, and meridian transit times and simple transformations from sky coordinates to altitude-azimuth coordinates without requiring a detailed understanding of astropy’s implementation of coordinate systems. astroplan provides convenience functions to generate common observational plots such as airmass and parallactic angle as a function of time, along with basic sky (finder) charts. Users can determine whether or not a target is observable given a variety of observing constraints, such as airmass limits, time ranges, Moon illumination/separation ranges, and more. A selection of observation schedulers are included that divide observing time among a list of targets, given observing constraints on those targets. Contributions to the source code from the community are welcome.

  14. Quantiprot - a Python package for quantitative analysis of protein sequences.

    PubMed

    Konopka, Bogumił M; Marciniak, Marta; Dyrka, Witold

    2017-07-17

    The field of protein sequence analysis is dominated by tools rooted in substitution matrices and alignments. A complementary approach is provided by methods of quantitative characterization. A major advantage of the approach is that quantitative properties defines a multidimensional solution space, where sequences can be related to each other and differences can be meaningfully interpreted. Quantiprot is a software package in Python, which provides a simple and consistent interface to multiple methods for quantitative characterization of protein sequences. The package can be used to calculate dozens of characteristics directly from sequences or using physico-chemical properties of amino acids. Besides basic measures, Quantiprot performs quantitative analysis of recurrence and determinism in the sequence, calculates distribution of n-grams and computes the Zipf's law coefficient. We propose three main fields of application of the Quantiprot package. First, quantitative characteristics can be used in alignment-free similarity searches, and in clustering of large and/or divergent sequence sets. Second, a feature space defined by quantitative properties can be used in comparative studies of protein families and organisms. Third, the feature space can be used for evaluating generative models, where large number of sequences generated by the model can be compared to actually observed sequences.

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

    PubMed

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

    2015-01-01

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

  16. 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

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

    NASA Astrophysics Data System (ADS)

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

    2017-04-01

    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.

  18. Python package for model STructure ANalysis (pySTAN)

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

  19. SPICE-Based Python Packages for ESA Solar System Exploration Mission's Geometry Exploitation

    NASA Astrophysics Data System (ADS)

    Costa, M.; Grass, M.

    2018-04-01

    This contribution outlines three Python packages to provide an enhanced and extended usage of SPICE Toolkit APIS providing higher-level functions and data quick-look capabilities focused on European Space Agency solar system exploration missions.

  20. GillesPy: A Python Package for Stochastic Model Building and Simulation.

    PubMed

    Abel, John H; Drawert, Brian; Hellander, Andreas; Petzold, Linda R

    2016-09-01

    GillesPy is an open-source Python package for model construction and simulation of stochastic biochemical systems. GillesPy consists of a Python framework for model building and an interface to the StochKit2 suite of efficient simulation algorithms based on the Gillespie stochastic simulation algorithms (SSA). To enable intuitive model construction and seamless integration into the scientific Python stack, we present an easy to understand, action-oriented programming interface. Here, we describe the components of this package and provide a detailed example relevant to the computational biology community.

  1. GillesPy: A Python Package for Stochastic Model Building and Simulation

    PubMed Central

    Abel, John H.; Drawert, Brian; Hellander, Andreas; Petzold, Linda R.

    2017-01-01

    GillesPy is an open-source Python package for model construction and simulation of stochastic biochemical systems. GillesPy consists of a Python framework for model building and an interface to the StochKit2 suite of efficient simulation algorithms based on the Gillespie stochastic simulation algorithms (SSA). To enable intuitive model construction and seamless integration into the scientific Python stack, we present an easy to understand, action-oriented programming interface. Here, we describe the components of this package and provide a detailed example relevant to the computational biology community. PMID:28630888

  2. 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

  3. GenomeDiagram: a python package for the visualization of large-scale genomic data.

    PubMed

    Pritchard, Leighton; White, Jennifer A; Birch, Paul R J; Toth, Ian K

    2006-03-01

    We present GenomeDiagram, a flexible, open-source Python module for the visualization of large-scale genomic, comparative genomic and other data with reference to a single chromosome or other biological sequence. GenomeDiagram may be used to generate publication-quality vector graphics, rastered images and in-line streamed graphics for webpages. The package integrates with datatypes from the BioPython project, and is available for Windows, Linux and Mac OS X systems. GenomeDiagram is freely available as source code (under GNU Public License) at http://bioinf.scri.ac.uk/lp/programs.html, and requires Python 2.3 or higher, and recent versions of the ReportLab and BioPython packages. A user manual, example code and images are available at http://bioinf.scri.ac.uk/lp/programs.html.

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

    PubMed

    Hart, Reece K; Rico, Rudolph; Hare, Emily; Garcia, John; Westbrook, Jody; Fusaro, Vincent A

    2015-01-15

    Biological sequence variants are commonly represented in scientific literature, clinical reports and databases of variation using the mutation nomenclature guidelines endorsed by the Human Genome Variation Society (HGVS). Despite the widespread use of the standard, no freely available and comprehensive programming libraries are available. Here we report an open-source and easy-to-use Python library that facilitates the parsing, manipulation, formatting and validation of variants according to the HGVS specification. The current implementation focuses on the subset of the HGVS recommendations that precisely describe sequence-level variation relevant to the application of high-throughput sequencing to clinical diagnostics. The package is released under the Apache 2.0 open-source license. Source code, documentation and issue tracking are available at http://bitbucket.org/hgvs/hgvs/. Python packages are available at PyPI (https://pypi.python.org/pypi/hgvs). Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.

  5. HyDe: a Python Package for Genome-Scale Hybridization Detection.

    PubMed

    Blischak, Paul D; Chifman, Julia; Wolfe, Andrea D; Kubatko, Laura S

    2018-03-19

    The analysis of hybridization and gene flow among closely related taxa is a common goal for researchers studying speciation and phylogeography. Many methods for hybridization detection use simple site pattern frequencies from observed genomic data and compare them to null models that predict an absence of gene flow. The theory underlying the detection of hybridization using these site pattern probabilities exploits the relationship between the coalescent process for gene trees within population trees and the process of mutation along the branches of the gene trees. For certain models, site patterns are predicted to occur in equal frequency (i.e., their difference is 0), producing a set of functions called phylogenetic invariants. In this paper we introduce HyDe, a software package for detecting hybridization using phylogenetic invariants arising under the coalescent model with hybridization. HyDe is written in Python, and can be used interactively or through the command line using pre-packaged scripts. We demonstrate the use of HyDe on simulated data, as well as on two empirical data sets from the literature. We focus in particular on identifying individual hybrids within population samples and on distinguishing between hybrid speciation and gene flow. HyDe is freely available as an open source Python package under the GNU GPL v3 on both GitHub (https://github.com/pblischak/HyDe) and the Python Package Index (PyPI: https://pypi.python.org/pypi/phyde).

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

    PubMed

    Daouda, Tariq; Perreault, Claude; Lemieux, Sébastien

    2016-01-01

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

  7. PyPanda: a Python package for gene regulatory network reconstruction

    PubMed Central

    van IJzendoorn, David G.P.; Glass, Kimberly; Quackenbush, John; Kuijjer, Marieke L.

    2016-01-01

    Summary: PANDA (Passing Attributes between Networks for Data Assimilation) is a gene regulatory network inference method that uses message-passing to integrate multiple sources of ‘omics data. PANDA was originally coded in C ++. In this application note we describe PyPanda, the Python version of PANDA. PyPanda runs considerably faster than the C ++ version and includes additional features for network analysis. Availability and implementation: The open source PyPanda Python package is freely available at http://github.com/davidvi/pypanda. Contact: mkuijjer@jimmy.harvard.edu or d.g.p.van_ijzendoorn@lumc.nl PMID:27402905

  8. PyPanda: a Python package for gene regulatory network reconstruction.

    PubMed

    van IJzendoorn, David G P; Glass, Kimberly; Quackenbush, John; Kuijjer, Marieke L

    2016-11-01

    PANDA (Passing Attributes between Networks for Data Assimilation) is a gene regulatory network inference method that uses message-passing to integrate multiple sources of 'omics data. PANDA was originally coded in C ++. In this application note we describe PyPanda, the Python version of PANDA. PyPanda runs considerably faster than the C ++ version and includes additional features for network analysis. The open source PyPanda Python package is freely available at http://github.com/davidvi/pypanda CONTACT: mkuijjer@jimmy.harvard.edu or d.g.p.van_ijzendoorn@lumc.nl. © The Author 2016. Published by Oxford University Press.

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

    PubMed Central

    Daouda, Tariq; Perreault, Claude; Lemieux, Sébastien

    2016-01-01

    pyGeno is a Python package mainly intended for precision medicine applications that revolve around genomics and proteomics. It integrates reference sequences and annotations from Ensembl, genomic polymorphisms from the dbSNP database and data from next-gen sequencing into an easy to use, memory-efficient and fast framework, therefore allowing the user to easily explore subject-specific genomes and proteomes. Compared to a standalone program, pyGeno gives the user access to the complete expressivity of Python, a general programming language. Its range of application therefore encompasses both short scripts and large scale genome-wide studies. PMID:27785359

  10. pyBSM: A Python package for modeling imaging systems

    NASA Astrophysics Data System (ADS)

    LeMaster, Daniel A.; Eismann, Michael T.

    2017-05-01

    There are components that are common to all electro-optical and infrared imaging system performance models. The purpose of the Python Based Sensor Model (pyBSM) is to provide open source access to these functions for other researchers to build upon. Specifically, pyBSM implements much of the capability found in the ERIM Image Based Sensor Model (IBSM) V2.0 along with some improvements. The paper also includes two use-case examples. First, performance of an airborne imaging system is modeled using the General Image Quality Equation (GIQE). The results are then decomposed into factors affecting noise and resolution. Second, pyBSM is paired with openCV to evaluate performance of an algorithm used to detect objects in an image.

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

    NASA Astrophysics Data System (ADS)

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

    2016-10-01

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

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

    PubMed

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

    2015-02-01

    In modern laboratories, software can drive the full experimental process from data acquisition to storage, processing, and analysis. The automation of laboratory data acquisition is an important consideration for every laboratory. When implementing a laboratory automation scheme, important parameters include its reliability, time to implement, adaptability, and compatibility with software used at other stages of experimentation. In this article, we present an open-source, flexible, and extensible Python package for Laboratory Automation, Control, and Experimentation (PLACE). The package uses modular organization and clear design principles; therefore, it can be easily customized or expanded to meet the needs of diverse laboratories. We discuss the organization of PLACE, data-handling considerations, and then present an example using PLACE for laser-ultrasound experiments. Finally, we demonstrate the seamless transition to post-processing and analysis with Python through the development of an analysis module for data produced by PLACE automation. © 2014 Society for Laboratory Automation and Screening.

  13. PyBoolNet: a python package for the generation, analysis and visualization of boolean networks.

    PubMed

    Klarner, Hannes; Streck, Adam; Siebert, Heike

    2017-03-01

    The goal of this project is to provide a simple interface to working with Boolean networks. Emphasis is put on easy access to a large number of common tasks including the generation and manipulation of networks, attractor and basin computation, model checking and trap space computation, execution of established graph algorithms as well as graph drawing and layouts. P y B ool N et is a Python package for working with Boolean networks that supports simple access to model checking via N u SMV, standard graph algorithms via N etwork X and visualization via dot . In addition, state of the art attractor computation exploiting P otassco ASP is implemented. The package is function-based and uses only native Python and N etwork X data types. https://github.com/hklarner/PyBoolNet. hannes.klarner@fu-berlin.de. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

  14. PyPathway: Python Package for Biological Network Analysis and Visualization.

    PubMed

    Xu, Yang; Luo, Xiao-Chun

    2018-05-01

    Life science studies represent one of the biggest generators of large data sets, mainly because of rapid sequencing technological advances. Biological networks including interactive networks and human curated pathways are essential to understand these high-throughput data sets. Biological network analysis offers a method to explore systematically not only the molecular complexity of a particular disease but also the molecular relationships among apparently distinct phenotypes. Currently, several packages for Python community have been developed, such as BioPython and Goatools. However, tools to perform comprehensive network analysis and visualization are still needed. Here, we have developed PyPathway, an extensible free and open source Python package for functional enrichment analysis, network modeling, and network visualization. The network process module supports various interaction network and pathway databases such as Reactome, WikiPathway, STRING, and BioGRID. The network analysis module implements overrepresentation analysis, gene set enrichment analysis, network-based enrichment, and de novo network modeling. Finally, the visualization and data publishing modules enable users to share their analysis by using an easy web application. For package availability, see the first Reference.

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

    PubMed

    Alstott, Jeff; Bullmore, Ed; Plenz, Dietmar

    2014-01-01

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

  16. 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

  17. ChemoPy: freely available python package for computational biology and chemoinformatics.

    PubMed

    Cao, Dong-Sheng; Xu, Qing-Song; Hu, Qian-Nan; Liang, Yi-Zeng

    2013-04-15

    Molecular representation for small molecules has been routinely used in QSAR/SAR, virtual screening, database search, ranking, drug ADME/T prediction and other drug discovery processes. To facilitate extensive studies of drug molecules, we developed a freely available, open-source python package called chemoinformatics in python (ChemoPy) for calculating the commonly used structural and physicochemical features. It computes 16 drug feature groups composed of 19 descriptors that include 1135 descriptor values. In addition, it provides seven types of molecular fingerprint systems for drug molecules, including topological fingerprints, electro-topological state (E-state) fingerprints, MACCS keys, FP4 keys, atom pairs fingerprints, topological torsion fingerprints and Morgan/circular fingerprints. By applying a semi-empirical quantum chemistry program MOPAC, ChemoPy can also compute a large number of 3D molecular descriptors conveniently. The python package, ChemoPy, is freely available via http://code.google.com/p/pychem/downloads/list, and it runs on Linux and MS-Windows. Supplementary data are available at Bioinformatics online.

  18. Nmrglue: an open source Python package for the analysis of multidimensional NMR data.

    PubMed

    Helmus, Jonathan J; Jaroniec, Christopher P

    2013-04-01

    Nmrglue, an open source Python package for working with multidimensional NMR data, is described. When used in combination with other Python scientific libraries, nmrglue provides a highly flexible and robust environment for spectral processing, analysis and visualization and includes a number of common utilities such as linear prediction, peak picking and lineshape fitting. The package also enables existing NMR software programs to be readily tied together, currently facilitating the reading, writing and conversion of data stored in Bruker, Agilent/Varian, NMRPipe, Sparky, SIMPSON, and Rowland NMR Toolkit file formats. In addition to standard applications, the versatility offered by nmrglue makes the package particularly suitable for tasks that include manipulating raw spectrometer data files, automated quantitative analysis of multidimensional NMR spectra with irregular lineshapes such as those frequently encountered in the context of biomacromolecular solid-state NMR, and rapid implementation and development of unconventional data processing methods such as covariance NMR and other non-Fourier approaches. Detailed documentation, install files and source code for nmrglue are freely available at http://nmrglue.com. The source code can be redistributed and modified under the New BSD license.

  19. Nmrglue: An Open Source Python Package for the Analysis of Multidimensional NMR Data

    PubMed Central

    Helmus, Jonathan J.; Jaroniec, Christopher P.

    2013-01-01

    Nmrglue, an open source Python package for working with multidimensional NMR data, is described. When used in combination with other Python scientific libraries, nmrglue provides a highly flexible and robust environment for spectral processing, analysis and visualization and includes a number of common utilities such as linear prediction, peak picking and lineshape fitting. The package also enables existing NMR software programs to be readily tied together, currently facilitating the reading, writing and conversion of data stored in Bruker, Agilent/Varian, NMRPipe, Sparky, SIMPSON, and Rowland NMR Toolkit file formats. In addition to standard applications, the versatility offered by nmrglue makes the package particularly suitable for tasks that include manipulating raw spectrometer data files, automated quantitative analysis of multidimensional NMR spectra with irregular lineshapes such as those frequently encountered in the context of biomacromolecular solid-state NMR, and rapid implementation and development of unconventional data processing methods such as covariance NMR and other non-Fourier approaches. Detailed documentation, install files and source code for nmrglue are freely available at http://nmrglue.com. The source code can be redistributed and modified under the New BSD license. PMID:23456039

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

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

    NASA Astrophysics Data System (ADS)

    Varley, Ryan

    2016-10-01

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

  2. Manipulating Environmental Time Series in Python/Numpy: the Scikits.Timeseries Package and its Applications.

    NASA Astrophysics Data System (ADS)

    Gerard-Marchant, P. G.

    2008-12-01

    Numpy is a free, open source C/Python interface designed for the fast and convenient manipulation of multidimensional numerical arrays. The base object, ndarray, can also be easily be extended to define new objects meeting specific needs. Thanks to its simplicity, efficiency and modularity, numpy and its companion library Scipy have become increasingly popular in the scientific community over the last few years, with application ranging from astronomy and engineering to finances and statistics. Its capacity to handle missing values is particularly appealing when analyzing environmental time series, where irregular data sampling might be an issue. After reviewing the main characteristics of numpy objects and the mechanism of subclassing, we will present the scikits.timeseries package, developed to manipulate single- and multi-variable arrays indexed in time. We will illustrate some typical applications of this package by introducing climpy, a set of extensions designed to help analyzing the impacts of climate variability on environmental data such as precipitations or streamflows.

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

    PubMed

    Khramtsova, Ekaterina A; Stranger, Barbara E

    2017-02-01

    Over the last decade, genome-wide association studies (GWAS) have generated vast amounts of analysis results, requiring development of novel tools for data visualization. Quantile–quantile (QQ) plots and Manhattan plots are classical tools which have been utilized to visually summarize GWAS results and identify genetic variants significantly associated with traits of interest. However, static visualizations are limiting in the information that can be shown. Here, we present Assocplots, a Python package for viewing and exploring GWAS results not only using classic static Manhattan and QQ plots, but also through a dynamic extension which allows to interactively visualize the relationships between GWAS results from multiple cohorts or studies. The Assocplots package is open source and distributed under the MIT license via GitHub (https://github.com/khramts/assocplots) along with examples, documentation and installation instructions. ekhramts@medicine.bsd.uchicago.edu or bstranger@medicine.bsd.uchicago.edu

  4. Mocking the weak lensing universe: The LensTools Python computing package

    NASA Astrophysics Data System (ADS)

    Petri, A.

    2016-10-01

    We present a newly developed software package which implements a wide range of routines frequently used in Weak Gravitational Lensing (WL). With the continuously increasing size of the WL scientific community we feel that easy to use Application Program Interfaces (APIs) for common calculations are a necessity to ensure efficiency and coordination across different working groups. Coupled with existing open source codes, such as CAMB (Lewis et al., 2000) and Gadget2 (Springel, 2005), LensTools brings together a cosmic shear simulation pipeline which, complemented with a variety of WL feature measurement tools and parameter sampling routines, provides easy access to the numerics for theoretical studies of WL as well as for experiment forecasts. Being implemented in PYTHON (Rossum, 1995), LensTools takes full advantage of a range of state-of-the art techniques developed by the large and growing open-source software community (Jones et al., 2001; McKinney, 2010; Astrophy Collaboration, 2013; Pedregosa et al., 2011; Foreman-Mackey et al., 2013). We made the LensTools code available on the Python Package Index and published its documentation on http://lenstools.readthedocs.io.

  5. PhasePApy: A robust pure Python package for automatic identification of seismic phases

    USGS Publications Warehouse

    Chen, Chen; Holland, Austin

    2016-01-01

    We developed a Python phase identification package: the PhasePApy for earthquake data processing and near‐real‐time monitoring. The package takes advantage of the growing number of Python libraries including Obspy. All the data formats supported by Obspy can be supported within the PhasePApy. The PhasePApy has two subpackages: the PhasePicker and the Associator, aiming to identify phase arrival onsets and associate them to phase types, respectively. The PhasePicker and the Associator can work jointly or separately. Three autopickers are implemented in the PhasePicker subpackage: the frequency‐band picker, the Akaike information criteria function derivative picker, and the kurtosis picker. All three autopickers identify picks with the same processing methods but different characteristic functions. The PhasePicker triggers the pick with a dynamic threshold and can declare a pick with false‐pick filtering. Also, the PhasePicker identifies a pick polarity and uncertainty for further seismological analysis, such as focal mechanism determination. Two associators are included in the Associator subpackage: the 1D Associator and 3D Associator, which assign phase types to picks that can best fit potential earthquakes by minimizing root mean square (rms) residuals of the misfits in distance and time, respectively. The Associator processes multiple picks from all channels at a seismic station and aggregates them to increase computational efficiencies. Both associators use travel‐time look up tables to determine the best estimation of the earthquake location and evaluate the phase type for picks. The PhasePApy package has been used extensively for local and regional earthquakes and can work for active source experiments as well.

  6. pyRMSD: a Python package for efficient pairwise RMSD matrix calculation and handling.

    PubMed

    Gil, Víctor A; Guallar, Víctor

    2013-09-15

    We introduce pyRMSD, an open source standalone Python package that aims at offering an integrative and efficient way of performing Root Mean Square Deviation (RMSD)-related calculations of large sets of structures. It is specially tuned to do fast collective RMSD calculations, as pairwise RMSD matrices, implementing up to three well-known superposition algorithms. pyRMSD provides its own symmetric distance matrix class that, besides the fact that it can be used as a regular matrix, helps to save memory and increases memory access speed. This last feature can dramatically improve the overall performance of any Python algorithm using it. In addition, its extensibility, testing suites and documentation make it a good choice to those in need of a workbench for developing or testing new algorithms. The source code (under MIT license), installer, test suites and benchmarks can be found at https://pele.bsc.es/ under the tools section. victor.guallar@bsc.es Supplementary data are available at Bioinformatics online.

  7. PlasmaPy: initial development of a Python package for plasma physics

    NASA Astrophysics Data System (ADS)

    Murphy, Nicholas; Leonard, Andrew J.; Stańczak, Dominik; Haggerty, Colby C.; Parashar, Tulasi N.; Huang, Yu-Min; PlasmaPy Community

    2017-10-01

    We report on initial development of PlasmaPy: an open source community-driven Python package for plasma physics. PlasmaPy seeks to provide core functionality that is needed for the formation of a fully open source Python ecosystem for plasma physics. PlasmaPy prioritizes code readability, consistency, and maintainability while using best practices for scientific computing such as version control, continuous integration testing, embedding documentation in code, and code review. We discuss our current and planned capabilities, including features presently under development. The development roadmap includes features such as fluid and particle simulation capabilities, a Grad-Shafranov solver, a dispersion relation solver, atomic data retrieval methods, and tools to analyze simulations and experiments. We describe several ways to contribute to PlasmaPy. PlasmaPy has a code of conduct and is being developed under a BSD license, with a version 0.1 release planned for 2018. The success of PlasmaPy depends on active community involvement, so anyone interested in contributing to this project should contact the authors. This work was partially supported by the U.S. Department of Energy.

  8. Cluster-lensing: A Python Package for Galaxy Clusters and Miscentering

    NASA Astrophysics Data System (ADS)

    Ford, Jes; VanderPlas, Jake

    2016-12-01

    We describe a new open source package for calculating properties of galaxy clusters, including Navarro, Frenk, and White halo profiles with and without the effects of cluster miscentering. This pure-Python package, cluster-lensing, provides well-documented and easy-to-use classes and functions for calculating cluster scaling relations, including mass-richness and mass-concentration relations from the literature, as well as the surface mass density {{Σ }}(R) and differential surface mass density {{Δ }}{{Σ }}(R) profiles, probed by weak lensing magnification and shear. Galaxy cluster miscentering is especially a concern for stacked weak lensing shear studies of galaxy clusters, where offsets between the assumed and the true underlying matter distribution can lead to a significant bias in the mass estimates if not accounted for. This software has been developed and released in a public GitHub repository, and is licensed under the permissive MIT license. The cluster-lensing package is archived on Zenodo. Full documentation, source code, and installation instructions are available at http://jesford.github.io/cluster-lensing/.

  9. ExGUtils: A Python Package for Statistical Analysis With the ex-Gaussian Probability Density.

    PubMed

    Moret-Tatay, Carmen; Gamermann, Daniel; Navarro-Pardo, Esperanza; Fernández de Córdoba Castellá, Pedro

    2018-01-01

    The study of reaction times and their underlying cognitive processes is an important field in Psychology. Reaction times are often modeled through the ex-Gaussian distribution, because it provides a good fit to multiple empirical data. The complexity of this distribution makes the use of computational tools an essential element. Therefore, there is a strong need for efficient and versatile computational tools for the research in this area. In this manuscript we discuss some mathematical details of the ex-Gaussian distribution and apply the ExGUtils package, a set of functions and numerical tools, programmed for python, developed for numerical analysis of data involving the ex-Gaussian probability density. In order to validate the package, we present an extensive analysis of fits obtained with it, discuss advantages and differences between the least squares and maximum likelihood methods and quantitatively evaluate the goodness of the obtained fits (which is usually an overlooked point in most literature in the area). The analysis done allows one to identify outliers in the empirical datasets and criteriously determine if there is a need for data trimming and at which points it should be done.

  10. PyXRF: Python-based X-ray fluorescence analysis package

    NASA Astrophysics Data System (ADS)

    Li, Li; Yan, Hanfei; Xu, Wei; Yu, Dantong; Heroux, Annie; Lee, Wah-Keat; Campbell, Stuart I.; Chu, Yong S.

    2017-09-01

    We developed a python-based fluorescence analysis package (PyXRF) at the National Synchrotron Light Source II (NSLS-II) for the X-ray fluorescence-microscopy beamlines, including Hard X-ray Nanoprobe (HXN), and Submicron Resolution X-ray Spectroscopy (SRX). This package contains a high-level fitting engine, a comprehensive commandline/ GUI design, rigorous physics calculations, and a visualization interface. PyXRF offers a method of automatically finding elements, so that users do not need to spend extra time selecting elements manually. Moreover, PyXRF provides a convenient and interactive way of adjusting fitting parameters with physical constraints. This will help us perform quantitative analysis, and find an appropriate initial guess for fitting. Furthermore, we also create an advanced mode for expert users to construct their own fitting strategies with a full control of each fitting parameter. PyXRF runs single-pixel fitting at a fast speed, which opens up the possibilities of viewing the results of fitting in real time during experiments. A convenient I/O interface was designed to obtain data directly from NSLS-II's experimental database. PyXRF is under open-source development and designed to be an integral part of NSLS-II's scientific computation library.

  11. ExGUtils: A Python Package for Statistical Analysis With the ex-Gaussian Probability Density

    PubMed Central

    Moret-Tatay, Carmen; Gamermann, Daniel; Navarro-Pardo, Esperanza; Fernández de Córdoba Castellá, Pedro

    2018-01-01

    The study of reaction times and their underlying cognitive processes is an important field in Psychology. Reaction times are often modeled through the ex-Gaussian distribution, because it provides a good fit to multiple empirical data. The complexity of this distribution makes the use of computational tools an essential element. Therefore, there is a strong need for efficient and versatile computational tools for the research in this area. In this manuscript we discuss some mathematical details of the ex-Gaussian distribution and apply the ExGUtils package, a set of functions and numerical tools, programmed for python, developed for numerical analysis of data involving the ex-Gaussian probability density. In order to validate the package, we present an extensive analysis of fits obtained with it, discuss advantages and differences between the least squares and maximum likelihood methods and quantitatively evaluate the goodness of the obtained fits (which is usually an overlooked point in most literature in the area). The analysis done allows one to identify outliers in the empirical datasets and criteriously determine if there is a need for data trimming and at which points it should be done. PMID:29765345

  12. Naima: a Python package for inference of particle distribution properties from nonthermal spectra

    NASA Astrophysics Data System (ADS)

    Zabalza, V.

    2015-07-01

    The ultimate goal of the observation of nonthermal emission from astrophysical sources is to understand the underlying particle acceleration and evolution processes, and few tools are publicly available to infer the particle distribution properties from the observed photon spectra from X-ray to VHE gamma rays. Here I present naima, an open source Python package that provides models for nonthermal radiative emission from homogeneous distribution of relativistic electrons and protons. Contributions from synchrotron, inverse Compton, nonthermal bremsstrahlung, and neutral-pion decay can be computed for a series of functional shapes of the particle energy distributions, with the possibility of using user-defined particle distribution functions. In addition, naima provides a set of functions that allow to use these models to fit observed nonthermal spectra through an MCMC procedure, obtaining probability distribution functions for the particle distribution parameters. Here I present the models and methods available in naima and an example of their application to the understanding of a galactic nonthermal source. naima's documentation, including how to install the package, is available at http://naima.readthedocs.org.

  13. PyMT: A Python package for model-coupling in the Earth sciences

    NASA Astrophysics Data System (ADS)

    Hutton, E.

    2016-12-01

    The current landscape of Earth-system models is not only broad in scientific scope, but also broad in type. On the one hand, the large variety of models is exciting, as it provides fertile ground for extending or linking models together in novel ways to answer new scientific questions. However, the heterogeneity in model type acts to inhibit model coupling, model development, or even model use. Existing models are written in a variety of programming languages, operate on different grids, use their own file formats (both for input and output), have different user interfaces, have their own time steps, etc. Each of these factors become obstructions to scientists wanting to couple, extend - or simply run - existing models. For scientists whose main focus may not be computer science these barriers become even larger and become significant logistical hurdles. And this is all before the scientific difficulties of coupling or running models are addressed. The CSDMS Python Modeling Toolkit (PyMT) was developed to help non-computer scientists deal with these sorts of modeling logistics. PyMT is the fundamental package the Community Surface Dynamics Modeling System uses for the coupling of models that expose the Basic Modeling Interface (BMI). It contains: Tools necessary for coupling models of disparate time and space scales (including grid mappers) Time-steppers that coordinate the sequencing of coupled models Exchange of data between BMI-enabled models Wrappers that automatically load BMI-enabled models into the PyMT framework Utilities that support open-source interfaces (UGRID, SGRID,CSDMS Standard Names, etc.) A collection of community-submitted models, written in a variety of programminglanguages, from a variety of process domains - but all usable from within the Python programming language A plug-in framework for adding additional BMI-enabled models to the framework In this presentation we intoduce the basics of the PyMT as well as provide an example of coupling

  14. PySeqLab: an open source Python package for sequence labeling and segmentation.

    PubMed

    Allam, Ahmed; Krauthammer, Michael

    2017-11-01

    Text and genomic data are composed of sequential tokens, such as words and nucleotides that give rise to higher order syntactic constructs. In this work, we aim at providing a comprehensive Python library implementing conditional random fields (CRFs), a class of probabilistic graphical models, for robust prediction of these constructs from sequential data. Python Sequence Labeling (PySeqLab) is an open source package for performing supervised learning in structured prediction tasks. It implements CRFs models, that is discriminative models from (i) first-order to higher-order linear-chain CRFs, and from (ii) first-order to higher-order semi-Markov CRFs (semi-CRFs). Moreover, it provides multiple learning algorithms for estimating model parameters such as (i) stochastic gradient descent (SGD) and its multiple variations, (ii) structured perceptron with multiple averaging schemes supporting exact and inexact search using 'violation-fixing' framework, (iii) search-based probabilistic online learning algorithm (SAPO) and (iv) an interface for Broyden-Fletcher-Goldfarb-Shanno (BFGS) and the limited-memory BFGS algorithms. Viterbi and Viterbi A* are used for inference and decoding of sequences. Using PySeqLab, we built models (classifiers) and evaluated their performance in three different domains: (i) biomedical Natural language processing (NLP), (ii) predictive DNA sequence analysis and (iii) Human activity recognition (HAR). State-of-the-art performance comparable to machine-learning based systems was achieved in the three domains without feature engineering or the use of knowledge sources. PySeqLab is available through https://bitbucket.org/A_2/pyseqlab with tutorials and documentation. ahmed.allam@yale.edu or michael.krauthammer@yale.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

  15. ProtPOS: a python package for the prediction of protein preferred orientation on a surface

    PubMed Central

    Ngai, Jimmy C. F.; Mak, Pui-In; Siu, Shirley W. I.

    2016-01-01

    Summary: Atomistic molecular dynamics simulation is a promising technique to investigate the energetics and dynamics in the protein–surface adsorption process which is of high relevance to modern biotechnological applications. To increase the chance of success in simulating the adsorption process, favorable orientations of the protein at the surface must be determined. Here, we present ProtPOS which is a lightweight and easy-to-use python package that can predict low-energy protein orientations on a surface of interest. It combines a fast conformational sampling algorithm with the energy calculation of GROMACS. The advantage of ProtPOS is it allows users to select any force fields suitable for the system at hand and provide structural output readily available for further simulation studies. Availability and Implementation: ProtPOS is freely available for academic and non-profit uses at http://cbbio.cis.umac.mo/software/protpos Supplementary information: Supplementary data are available at Bioinformatics online. Contact: shirleysiu@umac.mo PMID:27153619

  16. ProtPOS: a python package for the prediction of protein preferred orientation on a surface.

    PubMed

    Ngai, Jimmy C F; Mak, Pui-In; Siu, Shirley W I

    2016-08-15

    Atomistic molecular dynamics simulation is a promising technique to investigate the energetics and dynamics in the protein-surface adsorption process which is of high relevance to modern biotechnological applications. To increase the chance of success in simulating the adsorption process, favorable orientations of the protein at the surface must be determined. Here, we present ProtPOS which is a lightweight and easy-to-use python package that can predict low-energy protein orientations on a surface of interest. It combines a fast conformational sampling algorithm with the energy calculation of GROMACS. The advantage of ProtPOS is it allows users to select any force fields suitable for the system at hand and provide structural output readily available for further simulation studies. ProtPOS is freely available for academic and non-profit uses at http://cbbio.cis.umac.mo/software/protpos Supplementary data are available at Bioinformatics online. shirleysiu@umac.mo. © The Author 2016. Published by Oxford University Press.

  17. scraps: An open-source Python-based analysis package for analyzing and plotting superconducting resonator data

    DOE PAGES

    Carter, Faustin Wirkus; Khaire, Trupti S.; Novosad, Valentyn; ...

    2016-11-07

    We present "scraps" (SuperConducting Analysis and Plotting Software), a Python package designed to aid in the analysis and visualization of large amounts of superconducting resonator data, specifically complex transmission as a function of frequency, acquired at many different temperatures and driving powers. The package includes a least-squares fitting engine as well as a Monte-Carlo Markov Chain sampler for sampling the posterior distribution given priors, marginalizing over nuisance parameters, and estimating covariances. A set of plotting tools for generating publication-quality figures is also provided in the package. Lastly, we discuss the functionality of the software and provide some examples of itsmore » utility on data collected from a niobium-nitride coplanar waveguide resonator fabricated at Argonne National Laboratory.« less

  18. Python Open source Waveform ExtractoR (POWER): an open source, Python package to monitor and post-process numerical relativity simulations

    NASA Astrophysics Data System (ADS)

    Johnson, Daniel; Huerta, E. A.; Haas, Roland

    2018-01-01

    Numerical simulations of Einstein’s field equations provide unique insights into the physics of compact objects moving at relativistic speeds, and which are driven by strong gravitational interactions. Numerical relativity has played a key role to firmly establish gravitational wave astrophysics as a new field of research, and it is now paving the way to establish whether gravitational wave radiation emitted from compact binary mergers is accompanied by electromagnetic and astro-particle counterparts. As numerical relativity continues to blend in with routine gravitational wave data analyses to validate the discovery of gravitational wave events, it is essential to develop open source tools to streamline these studies. Motivated by our own experience as users and developers of the open source, community software, the Einstein Toolkit, we present an open source, Python package that is ideally suited to monitor and post-process the data products of numerical relativity simulations, and compute the gravitational wave strain at future null infinity in high performance environments. We showcase the application of this new package to post-process a large numerical relativity catalog and extract higher-order waveform modes from numerical relativity simulations of eccentric binary black hole mergers and neutron star mergers. This new software fills a critical void in the arsenal of tools provided by the Einstein Toolkit consortium to the numerical relativity community.

  19. ImagePy: an open-source, Python-based and platform-independent software package for boimage analysis.

    PubMed

    Wang, Anliang; Yan, Xiaolong; Wei, Zhijun

    2018-04-27

    This note presents the design of a scalable software package named ImagePy for analysing biological images. Our contribution is concentrated on facilitating extensibility and interoperability of the software through decoupling the data model from the user interface. Especially with assistance from the Python ecosystem, this software framework makes modern computer algorithms easier to be applied in bioimage analysis. ImagePy is free and open source software, with documentation and code available at https://github.com/Image-Py/imagepy under the BSD license. It has been tested on the Windows, Mac and Linux operating systems. wzjdlut@dlut.edu.cn or yxdragon@imagepy.org.

  20. A clustering package for nucleotide sequences using Laplacian Eigenmaps and Gaussian Mixture Model.

    PubMed

    Bruneau, Marine; Mottet, Thierry; Moulin, Serge; Kerbiriou, Maël; Chouly, Franz; Chretien, Stéphane; Guyeux, Christophe

    2018-02-01

    In this article, a new Python package for nucleotide sequences clustering is proposed. This package, freely available on-line, implements a Laplacian eigenmap embedding and a Gaussian Mixture Model for DNA clustering. It takes nucleotide sequences as input, and produces the optimal number of clusters along with a relevant visualization. Despite the fact that we did not optimise the computational speed, our method still performs reasonably well in practice. Our focus was mainly on data analytics and accuracy and as a result, our approach outperforms the state of the art, even in the case of divergent sequences. Furthermore, an a priori knowledge on the number of clusters is not required here. For the sake of illustration, this method is applied on a set of 100 DNA sequences taken from the mitochondrially encoded NADH dehydrogenase 3 (ND3) gene, extracted from a collection of Platyhelminthes and Nematoda species. The resulting clusters are tightly consistent with the phylogenetic tree computed using a maximum likelihood approach on gene alignment. They are coherent too with the NCBI taxonomy. Further test results based on synthesized data are then provided, showing that the proposed approach is better able to recover the clusters than the most widely used software, namely Cd-hit-est and BLASTClust. Copyright © 2017 Elsevier Ltd. All rights reserved.

  1. 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.

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

    PubMed

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

    2013-12-15

    Web interfaces provide access to numerous biological databases. Many can be accessed to in a programmatic way thanks to Web Services. Building applications that combine several of them would benefit from a single framework. BioServices is a comprehensive Python framework that provides programmatic access to major bioinformatics Web Services (e.g. KEGG, UniProt, BioModels, ChEMBLdb). Wrapping additional Web Services based either on Representational State Transfer or Simple Object Access Protocol/Web Services Description Language technologies is eased by the usage of object-oriented programming. BioServices releases and documentation are available at http://pypi.python.org/pypi/bioservices under a GPL-v3 license.

  3. Update 0.2 to "pysimm: A python package for simulation of molecular systems"

    NASA Astrophysics Data System (ADS)

    Demidov, Alexander G.; Fortunato, Michael E.; Colina, Coray M.

    2018-01-01

    An update to the pysimm Python molecular simulation API is presented. A major part of the update is the implementation of a new interface with CASSANDRA - a modern, versatile Monte Carlo molecular simulation program. Several significant improvements in the LAMMPS communication module that allow better and more versatile simulation setup are reported as well. An example of an application implementing iterative CASSANDRA-LAMMPS interaction is illustrated.

  4. QmeQ 1.0: An open-source Python package for calculations of transport through quantum dot devices

    NASA Astrophysics Data System (ADS)

    Kiršanskas, Gediminas; Pedersen, Jonas Nyvold; Karlström, Olov; Leijnse, Martin; Wacker, Andreas

    2017-12-01

    QmeQ is an open-source Python package for numerical modeling of transport through quantum dot devices with strong electron-electron interactions using various approximate master equation approaches. The package provides a framework for calculating stationary particle or energy currents driven by differences in chemical potentials or temperatures between the leads which are tunnel coupled to the quantum dots. The electronic structures of the quantum dots are described by their single-particle states and the Coulomb matrix elements between the states. When transport is treated perturbatively to lowest order in the tunneling couplings, the possible approaches are Pauli (classical), first-order Redfield, and first-order von Neumann master equations, and a particular form of the Lindblad equation. When all processes involving two-particle excitations in the leads are of interest, the second-order von Neumann approach can be applied. All these approaches are implemented in QmeQ. We here give an overview of the basic structure of the package, give examples of transport calculations, and outline the range of applicability of the different approximate approaches.

  5. Tethys – A Python Package for Spatial and Temporal Downscaling of Global Water Withdrawals

    SciTech Connect

    Li, Xinya; Vernon, Chris R.; Hejazi, Mohamad I.

    Downscaling of water withdrawals from regional/national to local scale is a fundamental step and also a common problem when integrating large scale economic and integrated assessment models with high-resolution detailed sectoral models. Tethys, an open-access software written in Python, is developed with statistical downscaling algorithms, to spatially and temporally downscale water withdrawal data to a finer scale. The spatial resolution will be downscaled from region/basin scale to grid (0.5 geographic degree) scale and the temporal resolution will be downscaled from year to month. Tethys is used to produce monthly global gridded water withdrawal products based on estimates from the Globalmore » Change Assessment Model (GCAM).« less

  6. Tethys – A Python Package for Spatial and Temporal Downscaling of Global Water Withdrawals

    DOE PAGES

    Li, Xinya; Vernon, Chris R.; Hejazi, Mohamad I.; ...

    2018-02-09

    Downscaling of water withdrawals from regional/national to local scale is a fundamental step and also a common problem when integrating large scale economic and integrated assessment models with high-resolution detailed sectoral models. Tethys, an open-access software written in Python, is developed with statistical downscaling algorithms, to spatially and temporally downscale water withdrawal data to a finer scale. The spatial resolution will be downscaled from region/basin scale to grid (0.5 geographic degree) scale and the temporal resolution will be downscaled from year to month. Tethys is used to produce monthly global gridded water withdrawal products based on estimates from the Globalmore » Change Assessment Model (GCAM).« less

  7. Pse-Analysis: a python package for DNA/RNA and protein/ peptide sequence analysis based on pseudo components and kernel methods.

    PubMed

    Liu, Bin; Wu, Hao; Zhang, Deyuan; Wang, Xiaolong; Chou, Kuo-Chen

    2017-02-21

    To expedite the pace in conducting genome/proteome analysis, we have developed a Python package called Pse-Analysis. The powerful package can automatically complete the following five procedures: (1) sample feature extraction, (2) optimal parameter selection, (3) model training, (4) cross validation, and (5) evaluating prediction quality. All the work a user needs to do is to input a benchmark dataset along with the query biological sequences concerned. Based on the benchmark dataset, Pse-Analysis will automatically construct an ideal predictor, followed by yielding the predicted results for the submitted query samples. All the aforementioned tedious jobs can be automatically done by the computer. Moreover, the multiprocessing technique was adopted to enhance computational speed by about 6 folds. The Pse-Analysis Python package is freely accessible to the public at http://bioinformatics.hitsz.edu.cn/Pse-Analysis/, and can be directly run on Windows, Linux, and Unix.

  8. 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.

  9. MEANS: python package for Moment Expansion Approximation, iNference and Simulation

    PubMed Central

    Fan, Sisi; Geissmann, Quentin; Lakatos, Eszter; Lukauskas, Saulius; Ale, Angelique; Babtie, Ann C.; Kirk, Paul D. W.; Stumpf, Michael P. H.

    2016-01-01

    Motivation: Many biochemical systems require stochastic descriptions. Unfortunately these can only be solved for the simplest cases and their direct simulation can become prohibitively expensive, precluding thorough analysis. As an alternative, moment closure approximation methods generate equations for the time-evolution of the system’s moments and apply a closure ansatz to obtain a closed set of differential equations; that can become the basis for the deterministic analysis of the moments of the outputs of stochastic systems. Results: We present a free, user-friendly tool implementing an efficient moment expansion approximation with parametric closures that integrates well with the IPython interactive environment. Our package enables the analysis of complex stochastic systems without any constraints on the number of species and moments studied and the type of rate laws in the system. In addition to the approximation method our package provides numerous tools to help non-expert users in stochastic analysis. Availability and implementation: https://github.com/theosysbio/means Contacts: m.stumpf@imperial.ac.uk or e.lakatos13@imperial.ac.uk Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27153663

  10. MEANS: python package for Moment Expansion Approximation, iNference and Simulation.

    PubMed

    Fan, Sisi; Geissmann, Quentin; Lakatos, Eszter; Lukauskas, Saulius; Ale, Angelique; Babtie, Ann C; Kirk, Paul D W; Stumpf, Michael P H

    2016-09-15

    Many biochemical systems require stochastic descriptions. Unfortunately these can only be solved for the simplest cases and their direct simulation can become prohibitively expensive, precluding thorough analysis. As an alternative, moment closure approximation methods generate equations for the time-evolution of the system's moments and apply a closure ansatz to obtain a closed set of differential equations; that can become the basis for the deterministic analysis of the moments of the outputs of stochastic systems. We present a free, user-friendly tool implementing an efficient moment expansion approximation with parametric closures that integrates well with the IPython interactive environment. Our package enables the analysis of complex stochastic systems without any constraints on the number of species and moments studied and the type of rate laws in the system. In addition to the approximation method our package provides numerous tools to help non-expert users in stochastic analysis. https://github.com/theosysbio/means m.stumpf@imperial.ac.uk or e.lakatos13@imperial.ac.uk Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

  11. 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.

  12. Constraint Network Analysis (CNA): a Python software package for efficiently linking biomacromolecular structure, flexibility, (thermo-)stability, and function.

    PubMed

    Pfleger, Christopher; Rathi, Prakash Chandra; Klein, Doris L; Radestock, Sebastian; Gohlke, Holger

    2013-04-22

    For deriving maximal advantage from information on biomacromolecular flexibility and rigidity, results from rigidity analyses must be linked to biologically relevant characteristics of a structure. Here, we describe the Python-based software package Constraint Network Analysis (CNA) developed for this task. CNA functions as a front- and backend to the graph-based rigidity analysis software FIRST. CNA goes beyond the mere identification of flexible and rigid regions in a biomacromolecule in that it (I) provides a refined modeling of thermal unfolding simulations that also considers the temperature-dependence of hydrophobic tethers, (II) allows performing rigidity analyses on ensembles of network topologies, either generated from structural ensembles or by using the concept of fuzzy noncovalent constraints, and (III) computes a set of global and local indices for quantifying biomacromolecular stability. This leads to more robust results from rigidity analyses and extends the application domain of rigidity analyses in that phase transition points ("melting points") and unfolding nuclei ("structural weak spots") are determined automatically. Furthermore, CNA robustly handles small-molecule ligands in general. Such advancements are important for applying rigidity analysis to data-driven protein engineering and for estimating the influence of ligand molecules on biomacromolecular stability. CNA maintains the efficiency of FIRST such that the analysis of a single protein structure takes a few seconds for systems of several hundred residues on a single core. These features make CNA an interesting tool for linking biomacromolecular structure, flexibility, (thermo-)stability, and function. CNA is available from http://cpclab.uni-duesseldorf.de/software for nonprofit organizations.

  13. Polarbrdf: A General Purpose Python Package for Visualization Quantitative Analysis of Multi-Angular Remote Sensing Measurements

    NASA Technical Reports Server (NTRS)

    Singh, Manoj K.; Gautam, Ritesh; Gatebe, Charles K.; Poudyal, Rajesh

    2016-01-01

    The Bidirectional Reflectance Distribution Function (BRDF) is a fundamental concept for characterizing the reflectance property of a surface, and helps in the analysis of remote sensing data from satellite, airborne and surface platforms. Multi-angular remote sensing measurements are required for the development and evaluation of BRDF models for improved characterization of surface properties. However, multi-angular data and the associated BRDF models are typically multidimensional involving multi-angular and multi-wavelength information. Effective visualization of such complex multidimensional measurements for different wavelength combinations is presently somewhat lacking in the literature, and could serve as a potentially useful research and teaching tool in aiding both interpretation and analysis of BRDF measurements. This article describes a newly developed software package in Python (PolarBRDF) to help visualize and analyze multi-angular data in polar and False Color Composite (FCC) forms. PolarBRDF also includes functionalities for computing important multi-angular reflectance/albedo parameters including spectral albedo, principal plane reflectance and spectral reflectance slope. Application of PolarBRDF is demonstrated using various case studies obtained from airborne multi-angular remote sensing measurements using NASA's Cloud Absorption Radiometer (CAR). Our visualization program also provides functionalities for untangling complex surface/atmosphere features embedded in pixel-based remote sensing measurements, such as the FCC imagery generation of BRDF measurements of grasslands in the presence of wild fire smoke and clouds. Furthermore, PolarBRDF also provides quantitative information of the angular distribution of scattered surface/atmosphere radiation, in the form of relevant BRDF variables such as sunglint, hotspot and scattering statistics.

  14. PolarBRDF: A general purpose Python package for visualization and quantitative analysis of multi-angular remote sensing measurements

    NASA Astrophysics Data System (ADS)

    Singh, Manoj K.; Gautam, Ritesh; Gatebe, Charles K.; Poudyal, Rajesh

    2016-11-01

    The Bidirectional Reflectance Distribution Function (BRDF) is a fundamental concept for characterizing the reflectance property of a surface, and helps in the analysis of remote sensing data from satellite, airborne and surface platforms. Multi-angular remote sensing measurements are required for the development and evaluation of BRDF models for improved characterization of surface properties. However, multi-angular data and the associated BRDF models are typically multidimensional involving multi-angular and multi-wavelength information. Effective visualization of such complex multidimensional measurements for different wavelength combinations is presently somewhat lacking in the literature, and could serve as a potentially useful research and teaching tool in aiding both interpretation and analysis of BRDF measurements. This article describes a newly developed software package in Python (PolarBRDF) to help visualize and analyze multi-angular data in polar and False Color Composite (FCC) forms. PolarBRDF also includes functionalities for computing important multi-angular reflectance/albedo parameters including spectral albedo, principal plane reflectance and spectral reflectance slope. Application of PolarBRDF is demonstrated using various case studies obtained from airborne multi-angular remote sensing measurements using NASA's Cloud Absorption Radiometer (CAR). Our visualization program also provides functionalities for untangling complex surface/atmosphere features embedded in pixel-based remote sensing measurements, such as the FCC imagery generation of BRDF measurements of grasslands in the presence of wildfire smoke and clouds. Furthermore, PolarBRDF also provides quantitative information of the angular distribution of scattered surface/atmosphere radiation, in the form of relevant BRDF variables such as sunglint, hotspot and scattering statistics.

  15. PolarBRDF: A general purpose Python package for visualization and quantitative analysis of multi-angular remote sensing measurements

    NASA Astrophysics Data System (ADS)

    Poudyal, R.; Singh, M.; Gautam, R.; Gatebe, C. K.

    2016-12-01

    The Bidirectional Reflectance Distribution Function (BRDF) is a fundamental concept for characterizing the reflectance property of a surface, and helps in the analysis of remote sensing data from satellite, airborne and surface platforms. Multi-angular remote sensing measurements are required for the development and evaluation of BRDF models for improved characterization of surface properties. However, multi-angular data and the associated BRDF models are typically multidimensional involving multi-angular and multi-wavelength information. Effective visualization of such complex multidimensional measurements for different wavelength combinations is presently somewhat lacking in the literature, and could serve as a potentially useful research and teaching tool in aiding both interpretation and analysis of BRDF measurements. This article describes a newly developed software package in Python (PolarBRDF) to help visualize and analyze multi-angular data in polar and False Color Composite (FCC) forms. PolarBRDF also includes functionalities for computing important multi-angular reflectance/albedo parameters including spectral albedo, principal plane reflectance and spectral reflectance slope. Application of PolarBRDF is demonstrated using various case studies obtained from airborne multi-angular remote sensing measurements using NASA's Cloud Absorption Radiometer (CAR)- http://car.gsfc.nasa.gov/. Our visualization program also provides functionalities for untangling complex surface/atmosphere features embedded in pixel-based remote sensing measurements, such as the FCC imagery generation of BRDF measurements of grasslands in the presence of wildfire smoke and clouds. Furthermore, PolarBRDF also provides quantitative information of the angular distribution of scattered surface/atmosphere radiation, in the form of relevant BRDF variables such as sunglint, hotspot and scattering statistics.

  16. repDNA: a Python package to generate various modes of feature vectors for DNA sequences by incorporating user-defined physicochemical properties and sequence-order effects.

    PubMed

    Liu, Bin; Liu, Fule; Fang, Longyun; Wang, Xiaolong; Chou, Kuo-Chen

    2015-04-15

    In order to develop powerful computational predictors for identifying the biological features or attributes of DNAs, one of the most challenging problems is to find a suitable approach to effectively represent the DNA sequences. To facilitate the studies of DNAs and nucleotides, we developed a Python package called representations of DNAs (repDNA) for generating the widely used features reflecting the physicochemical properties and sequence-order effects of DNAs and nucleotides. There are three feature groups composed of 15 features. The first group calculates three nucleic acid composition features describing the local sequence information by means of kmers; the second group calculates six autocorrelation features describing the level of correlation between two oligonucleotides along a DNA sequence in terms of their specific physicochemical properties; the third group calculates six pseudo nucleotide composition features, which can be used to represent a DNA sequence with a discrete model or vector yet still keep considerable sequence-order information via the physicochemical properties of its constituent oligonucleotides. In addition, these features can be easily calculated based on both the built-in and user-defined properties via using repDNA. The repDNA Python package is freely accessible to the public at http://bioinformatics.hitsz.edu.cn/repDNA/. bliu@insun.hit.edu.cn or kcchou@gordonlifescience.org Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  17. pySAPC, a python package for sparse affinity propagation clustering: Application to odontogenesis whole genome time series gene-expression data.

    PubMed

    Cao, Huojun; Amendt, Brad A

    2016-11-01

    Developmental dental anomalies are common forms of congenital defects. The molecular mechanisms of dental anomalies are poorly understood. Systematic approaches such as clustering genes based on similar expression patterns could identify novel genes involved in dental anomalies and provide a framework for understanding molecular regulatory mechanisms of these genes during tooth development (odontogenesis). A python package (pySAPC) of sparse affinity propagation clustering algorithm for large datasets was developed. Whole genome pair-wise similarity was calculated based on expression pattern similarity based on 45 microarrays of several stages during odontogenesis. pySAPC identified 743 gene clusters based on expression pattern similarity during mouse tooth development. Three clusters are significantly enriched for genes associated with dental anomalies (with FDR <0.1). The three clusters of genes have distinct expression patterns during odontogenesis. Clustering genes based on similar expression profiles recovered several known regulatory relationships for genes involved in odontogenesis, as well as many novel genes that may be involved with the same genetic pathways as genes that have already been shown to contribute to dental defects. By using sparse similarity matrix, pySAPC use much less memory and CPU time compared with the original affinity propagation program that uses a full similarity matrix. This python package will be useful for many applications where dataset(s) are too large to use full similarity matrix. This article is part of a Special Issue entitled "System Genetics" Guest Editor: Dr. Yudong Cai and Dr. Tao Huang. Copyright © 2016. Published by Elsevier B.V.

  18. The effect on turkey meat shelf life of modified-atmosphere packaging with an argon mixture.

    PubMed

    Fraqueza, M J; Barreto, A S

    2009-09-01

    There is a lack of knowledge related to the action of Ar on microbial development and prevention of oxidation when applied to raw meat under modified-atmosphere package (MAP). The aim of this study was to evaluate the effect of an anaerobic gas mixture with Ar on spoilage flora growth, color, and lipid oxidation stability of turkey meat under MAP stored at 0 degrees C. Breast muscles samples were collected on different working days from turkey carcasses (BUT9 and BIG6), fast-cooled in a tunnel (-2 degrees C, 2 m.s(-1), 90% RH) for 2 h and selected to be deboned according current practices in industrial slaughterhouses. The breasts were cut into slices that were individually packaged under aerobiosis (P0) and in 4 different modified atmospheres containing different gas mixtures as (P1) 100% N2, (P2) 50% Ar-50% N2, (P3) 50% Ar-50% CO2, and (P4) 50% N2-50% CO2. All samples were stored at 0+/-1 degrees C in the dark for between 12 and 25 d. Meat samples packaged in P0 were analyzed for their microbial and physicochemical characteristics on d 0, 5, and 12 of storage and then extended to 19 and 25 d when samples were under MAP. The microbial shelf life period extension of MAP sliced turkey meat compared with aerobic packaging (5-d shelf life) is 1 wk more for P1 and P2 mixtures, 2 wk for P4, and 3 wk for P3. The Ar-CO2 mixture was more efficient in delaying flora development than CO2-N2 with 1 log difference on the 25th day of storage, for total psychrotrophic counts, total anaerobic counts, and Brochothrix thermosphacta. The presence of Ar on gas mixtures did not seem to have any additional protective effect on lipid turkey meat oxidation.

  19. iFeature: a python package and web server for features extraction and selection from protein and peptide sequences.

    PubMed

    Chen, Zhen; Zhao, Pei; Li, Fuyi; Leier, André; Marquez-Lago, Tatiana T; Wang, Yanan; Webb, Geoffrey I; Smith, A Ian; Daly, Roger J; Chou, Kuo-Chen; Song, Jiangning

    2018-03-08

    Structural and physiochemical descriptors extracted from sequence data have been widely used to represent sequences and predict structural, functional, expression and interaction profiles of proteins and peptides as well as DNAs/RNAs. Here, we present iFeature, a versatile Python-based toolkit for generating various numerical feature representation schemes for both protein and peptide sequences. iFeature is capable of calculating and extracting a comprehensive spectrum of 18 major sequence encoding schemes that encompass 53 different types of feature descriptors. It also allows users to extract specific amino acid properties from the AAindex database. Furthermore, iFeature integrates 12 different types of commonly used feature clustering, selection, and dimensionality reduction algorithms, greatly facilitating training, analysis, and benchmarking of machine-learning models. The functionality of iFeature is made freely available via an online web server and a stand-alone toolkit. http://iFeature.erc.monash.edu/; https://github.com/Superzchen/iFeature/. jiangning.song@monash.edu; kcchou@gordonlifescience.org; roger.daly@monash.edu. Supplementary data are available at Bioinformatics online.

  20. piscope - A Python based software package for the analysis of volcanic SO2 emissions using UV SO2 cameras

    NASA Astrophysics Data System (ADS)

    Gliss, Jonas; Stebel, Kerstin; Kylling, Arve; Solvejg Dinger, Anna; Sihler, Holger; Sudbø, Aasmund

    2017-04-01

    UV SO2 cameras have become a common method for monitoring SO2 emission rates from volcanoes. Scattered solar UV radiation is measured in two wavelength windows, typically around 310 nm and 330 nm (distinct / weak SO2 absorption) using interference filters. The data analysis comprises the retrieval of plume background intensities (to calculate plume optical densities), the camera calibration (to convert optical densities into SO2 column densities) and the retrieval of gas velocities within the plume as well as the retrieval of plume distances. SO2 emission rates are then typically retrieved along a projected plume cross section, for instance a straight line perpendicular to the plume propagation direction. Today, for most of the required analysis steps, several alternatives exist due to ongoing developments and improvements related to the measurement technique. We present piscope, a cross platform, open source software toolbox for the analysis of UV SO2 camera data. The code is written in the Python programming language and emerged from the idea of a common analysis platform incorporating a selection of the most prevalent methods found in literature. piscope includes several routines for plume background retrievals, routines for cell and DOAS based camera calibration including two individual methods to identify the DOAS field of view (shape and position) within the camera images. Gas velocities can be retrieved either based on an optical flow analysis or using signal cross correlation. A correction for signal dilution (due to atmospheric scattering) can be performed based on topographic features in the images. The latter requires distance retrievals to the topographic features used for the correction. These distances can be retrieved automatically on a pixel base using intersections of individual pixel viewing directions with the local topography. The main features of piscope are presented based on dataset recorded at Mt. Etna, Italy in September 2015.

  1. modlAMP: Python for antimicrobial peptides.

    PubMed

    Müller, Alex T; Gabernet, Gisela; Hiss, Jan A; Schneider, Gisbert

    2017-09-01

    We have implemented the lecular esign aboratory's nti icrobial eptides package ( ), a Python-based software package for the design, classification and visual representation of peptide data. modlAMP offers functions for molecular descriptor calculation and the retrieval of amino acid sequences from public or local sequence databases, and provides instant access to precompiled datasets for machine learning. The package also contains methods for the analysis and representation of circular dichroism spectra. The modlAMP Python package is available under the BSD license from URL http://doi.org/10.5905/ethz-1007-72 or via pip from the Python Package Index (PyPI). gisbert.schneider@pharma.ethz.ch. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  2. metaseq: a Python package for integrative genome-wide analysis reveals relationships between chromatin insulators and associated nuclear mRNA.

    PubMed

    Dale, Ryan K; Matzat, Leah H; Lei, Elissa P

    2014-08-01

    Here we introduce metaseq, a software library written in Python, which enables loading multiple genomic data formats into standard Python data structures and allows flexible, customized manipulation and visualization of data from high-throughput sequencing studies. We demonstrate its practical use by analyzing multiple datasets related to chromatin insulators, which are DNA-protein complexes proposed to organize the genome into distinct transcriptional domains. Recent studies in Drosophila and mammals have implicated RNA in the regulation of chromatin insulator activities. Moreover, the Drosophila RNA-binding protein Shep has been shown to antagonize gypsy insulator activity in a tissue-specific manner, but the precise role of RNA in this process remains unclear. Better understanding of chromatin insulator regulation requires integration of multiple datasets, including those from chromatin-binding, RNA-binding, and gene expression experiments. We use metaseq to integrate RIP- and ChIP-seq data for Shep and the core gypsy insulator protein Su(Hw) in two different cell types, along with publicly available ChIP-chip and RNA-seq data. Based on the metaseq-enabled analysis presented here, we propose a model where Shep associates with chromatin cotranscriptionally, then is recruited to insulator complexes in trans where it plays a negative role in insulator activity. Published by Oxford University Press on behalf of Nucleic Acids Research 2014. This work is written by (a) US Government employee(s) and is in the public domain in the US.

  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. CSB: a Python framework for structural bioinformatics.

    PubMed

    Kalev, Ivan; Mechelke, Martin; Kopec, Klaus O; Holder, Thomas; Carstens, Simeon; Habeck, Michael

    2012-11-15

    Computational Structural Biology Toolbox (CSB) is a cross-platform Python class library for reading, storing and analyzing biomolecular structures with rich support for statistical analyses. CSB is designed for reusability and extensibility and comes with a clean, well-documented API following good object-oriented engineering practice. Stable release packages are available for download from the Python Package Index (PyPI) as well as from the project's website http://csb.codeplex.com. ivan.kalev@gmail.com or michael.habeck@tuebingen.mpg.de

  5. 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

  6. Recovery of PET from packaging plastics mixtures by wet shaking table.

    PubMed

    Carvalho, M T; Agante, E; Durão, F

    2007-01-01

    Recycling requires the separation of materials appearing in a mass of wastes of heterogeneous composition and characteristics, into single, almost pure, component/material flows. The separation of materials (e.g., some types of plastics) with similar physical properties (e.g., specific gravity) is often accomplished by human sorting. This is the case of the separation of packaging plastics in municipal solid wastes (MSW). The low cost of virgin plastics and low value of recycled plastics necessitate the utilization of low cost techniques and processes in the recycling of packaging plastics. An experimental study was conducted to evaluate the feasibility of production of a PET product, cleaned from PVC and PS, using a wet shaking table. The wet shaking table is an environmentally friendly process, widely used to separate minerals, which has low capital and operational costs. Some operational variables of the equipment, as well as different feed characteristics, were considered. The results show that the separation of these plastics is feasible although, similarly to the mineral field, in somewhat complex flow sheets.

  7. 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

  8. Scraping EDGAR with Python

    ERIC Educational Resources Information Center

    Ashraf, Rasha

    2017-01-01

    This article presents Python codes that can be used to extract data from Securities and Exchange Commission (SEC) filings. The Python program web crawls to obtain URL paths for company filings of required reports, such as Form 10-K. The program then performs a textual analysis and counts the number of occurrences of words in the filing that…

  9. 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)....

  10. 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.

  11. Amebiasis in four ball pythons, Python reginus.

    PubMed

    Kojimoto, A; Uchida, K; Horii, Y; Okumura, S; Yamaguch, R; Tateyama, S

    2001-12-01

    Between September 13th and November 18th in 1999, four ball pythons, Python reginus kept in the same display, showed anorexia and died one after another. At necropsy, all four snakes had severe hemorrhagic colitis. Microscopically, all snakes had severe necrotizing hemorrhagic colitis, in association with ameba-like protozoa. Some of the protozoa had macrophage-like morphology and others formed protozoal cysts with thickened walls. These protozoa were distributed throughout the wall in the large intestine. Based on the pathological findings, these snakes were infested with a member of Entamoeba sp., presumably with infection by Entamoeba invadens, the most prevalent type of reptilian amoebae.

  12. NEURON and Python.

    PubMed

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

    2009-01-01

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

  13. NEURON and Python

    PubMed Central

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

    2008-01-01

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

  14. Optics simulations: a Python workshop

    NASA Astrophysics Data System (ADS)

    Ghalila, H.; Ammar, A.; Varadharajan, S.; Majdi, Y.; Zghal, M.; Lahmar, S.; Lakshminarayanan, V.

    2017-08-01

    Numerical simulations allow teachers and students to indirectly perform sophisticated experiments that cannot be realizable otherwise due to cost and other constraints. During the past few decades there has been an explosion in the development of numerical tools concurrently with open source environments such as Python software. This availability of open source software offers an incredible opportunity for advancing teaching methodologies as well as in research. More specifically it is possible to correlate theoretical knowledge with experimental measurements using "virtual" experiments. We have been working on the development of numerical simulation tools using the Python program package and we have concentrated on geometric and physical optics simulations. The advantage of doing hands-on numerical experiments is that it allows the student learner to be an active participant in the pedagogical/learning process rather than playing a passive role as in the traditional lecture format. Even in laboratory classes because of constraints of space, lack of equipment and often-large numbers of students, many students play a passive role since they work in groups of 3 or more students. Furthermore these new tools help students get a handle on numerical methods as well simulations and impart a "feel" for the physics under investigation.

  15. Scripting MODFLOW Model Development Using Python and FloPy.

    PubMed

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

    2016-09-01

    Graphical user interfaces (GUIs) are commonly used to construct and postprocess numerical groundwater flow and transport models. Scripting model development with the programming language Python is presented here as an alternative approach. One advantage of Python is that there are many packages available to facilitate the model development process, including packages for plotting, array manipulation, optimization, and data analysis. For MODFLOW-based models, the FloPy package was developed by the authors to construct model input files, run the model, and read and plot simulation results. Use of Python with the available scientific packages and FloPy facilitates data exploration, alternative model evaluations, and model analyses that can be difficult to perform with GUIs. Furthermore, Python scripts are a complete, transparent, and repeatable record of the modeling process. The approach is introduced with a simple FloPy example to create and postprocess a MODFLOW model. A more complicated capture-fraction analysis with a real-world model is presented to demonstrate the types of analyses that can be performed using Python and FloPy. © 2016, National Ground Water Association.

  16. Scripting MODFLOW model development using Python and FloPy

    USGS Publications Warehouse

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

    2016-01-01

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

  17. Python Scripts for Automation of Current-Voltage Testing of Semiconductor Devices (FY17)

    DTIC Science & Technology

    2017-01-01

    ARL-TR-7923 ● JAN 2017 US Army Research Laboratory Python Scripts for Automation of Current- Voltage Testing of Semiconductor...manual device-testing procedures is reduced or eliminated through automation. This technical report includes scripts written in Python , version 2.7, used ...nothing. 3.1.9 Exit Program The script exits the entire program. Line 505, sys.exit(), uses the sys package that comes with Python to exit system

  18. PyXNAT: XNAT in Python.

    PubMed

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

    2012-01-01

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

  19. PyXNAT: XNAT in Python

    PubMed Central

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

    2012-01-01

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

  20. 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.

  1. An intuitive Python interface for Bioconductor libraries demonstrates the utility of language translators.

    PubMed

    Gautier, Laurent

    2010-12-21

    Computer languages can be domain-related, and in the case of multidisciplinary projects, knowledge of several languages will be needed in order to quickly implements ideas. Moreover, each computer language has relative strong points, making some languages better suited than others for a given task to be implemented. The Bioconductor project, based on the R language, has become a reference for the numerical processing and statistical analysis of data coming from high-throughput biological assays, providing a rich selection of methods and algorithms to the research community. At the same time, Python has matured as a rich and reliable language for the agile development of prototypes or final implementations, as well as for handling large data sets. The data structures and functions from Bioconductor can be exposed to Python as a regular library. This allows a fully transparent and native use of Bioconductor from Python, without one having to know the R language and with only a small community of translators required to know both. To demonstrate this, we have implemented such Python representations for key infrastructure packages in Bioconductor, letting a Python programmer handle annotation data, microarray data, and next-generation sequencing data. Bioconductor is now not solely reserved to R users. Building a Python application using Bioconductor functionality can be done just like if Bioconductor was a Python package. Moreover, similar principles can be applied to other languages and libraries. Our Python package is available at: http://pypi.python.org/pypi/rpy2-bioconductor-extensions/.

  2. PAINeT: An object-oriented software package for simulations of flow-field, transport coefficients and flux terms in non-equilibrium gas mixture flows

    NASA Astrophysics Data System (ADS)

    Istomin, V. A.

    2018-05-01

    The software package Planet Atmosphere Investigator of Non-equilibrium Thermodynamics (PAINeT) has been devel-oped for studying the non-equilibrium effects associated with electronic excitation, chemical reactions and ionization. These studies are necessary for modeling process in shock tubes, in high enthalpy flows, in nozzles or jet engines, in combustion and explosion processes, in modern plasma-chemical and laser technologies. The advantages and possibilities of the package implementation are stated. Within the framework of the package implementation, based on kinetic theory approximations (one-temperature and state-to-state approaches), calculations are carried out, and the limits of applicability of a simplified description of shock-heated air flows and any other mixtures chosen by the user are given. Using kinetic theory algorithms, a numerical calculation of the heat fluxes and relaxation terms can be performed, which is necessary for further comparison of engineering simulation with experi-mental data. The influence of state-to-state distributions over electronic energy levels on the coefficients of thermal conductivity, diffusion, heat fluxes and diffusion velocities of the components of various gas mixtures behind shock waves is studied. Using the software package the accuracy of different approximations of the kinetic theory of gases is estimated. As an example state-resolved atomic ionized mixture of N/N+/O/O+/e- is considered. It is shown that state-resolved diffusion coefficients of neutral and ionized species vary from level to level. Comparing results of engineering applications with those given by PAINeT, recommendations for adequate models selection are proposed.

  3. Practical Approach for Hyperspectral Image Processing in Python

    NASA Astrophysics Data System (ADS)

    Annala, L.; Eskelinen, M. A.; Hämäläinen, J.; Riihinen, A.; Pölönen, I.

    2018-04-01

    Python is a very popular programming language among data scientists around the world. Python can also be used in hyperspectral data analysis. There are some toolboxes designed for spectral imaging, such as Spectral Python and HyperSpy, but there is a need for analysis pipeline, which is easy to use and agile for different solutions. We propose a Python pipeline which is built on packages xarray, Holoviews and scikit-learn. We have developed some of own tools, MaskAccessor, VisualisorAccessor and a spectral index library. They also fulfill our goal of easy and agile data processing. In this paper we will present our processing pipeline and demonstrate it in practice.

  4. 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

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

    PubMed

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

    2013-12-26

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

  6. Stimfit: quantifying electrophysiological data with Python

    PubMed Central

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

    2013-01-01

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

  7. 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.

  8. 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, andmore » (3) gluing together all components of the project including existing C and C++ modules. For (l), we provide a schema definition and discuss how the various tables interact to represent objects in the database as tree structures. (2) focuses on an algorithm to create a hierarchical representation of an object, given its string representation, and an algorithm to match unknown objects against objects in a database. And finally, (3) discusses the use of Boost Python to interact with the pre-existing C and C++ code that creates the CDTs and CATS, performs shape feature extraction and syntactic characterization, and normalizes object strings. The paper concludes with a vision of the future use of Python for the CV project.« less

  9. Python/Lua Benchmarks

    SciTech Connect

    Busby, L.

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

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

    Federal Register 2010, 2011, 2012, 2013, 2014

    2010-07-01

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

  11. 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.

  12. 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.

  13. A Python library for FAIRer access and deposition to the Metabolomics Workbench Data Repository.

    PubMed

    Smelter, Andrey; Moseley, Hunter N B

    2018-01-01

    The Metabolomics Workbench Data Repository is a public repository of mass spectrometry and nuclear magnetic resonance data and metadata derived from a wide variety of metabolomics studies. The data and metadata for each study is deposited, stored, and accessed via files in the domain-specific 'mwTab' flat file format. In order to improve the accessibility, reusability, and interoperability of the data and metadata stored in 'mwTab' formatted files, we implemented a Python library and package. This Python package, named 'mwtab', is a parser for the domain-specific 'mwTab' flat file format, which provides facilities for reading, accessing, and writing 'mwTab' formatted files. Furthermore, the package provides facilities to validate both the format and required metadata elements of a given 'mwTab' formatted file. In order to develop the 'mwtab' package we used the official 'mwTab' format specification. We used Git version control along with Python unit-testing framework as well as continuous integration service to run those tests on multiple versions of Python. Package documentation was developed using sphinx documentation generator. The 'mwtab' package provides both Python programmatic library interfaces and command-line interfaces for reading, writing, and validating 'mwTab' formatted files. Data and associated metadata are stored within Python dictionary- and list-based data structures, enabling straightforward, 'pythonic' access and manipulation of data and metadata. Also, the package provides facilities to convert 'mwTab' files into a JSON formatted equivalent, enabling easy reusability of the data by all modern programming languages that implement JSON parsers. The 'mwtab' package implements its metadata validation functionality based on a pre-defined JSON schema that can be easily specialized for specific types of metabolomics studies. The library also provides a command-line interface for interconversion between 'mwTab' and JSONized formats in raw text and a

  14. Xarray: multi-dimensional data analysis in Python

    NASA Astrophysics Data System (ADS)

    Hoyer, Stephan; Hamman, Joe; Maussion, Fabien

    2017-04-01

    xarray (http://xarray.pydata.org) is an open source project and Python package that provides a toolkit and data structures for N-dimensional labeled arrays, which are the bread and butter of modern geoscientific data analysis. Key features of the package include label-based indexing and arithmetic, interoperability with the core scientific Python packages (e.g., pandas, NumPy, Matplotlib, Cartopy), out-of-core computation on datasets that don't fit into memory, a wide range of input/output options, and advanced multi-dimensional data manipulation tools such as group-by and resampling. In this contribution we will present the key features of the library and demonstrate its great potential for a wide range of applications, from (big-)data processing on super computers to data exploration in front of a classroom.

  15. 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.

  16. Fluorinated alkyl substances and technical mixtures used in food paper-packaging exhibit endocrine-related activity in vitro.

    PubMed

    Rosenmai, A K; Taxvig, C; Svingen, T; Trier, X; van Vugt-Lussenburg, B M A; Pedersen, M; Lesné, L; Jégou, B; Vinggaard, A M

    2016-07-01

    Migration of chemicals from packaging materials to foods may lead to human exposure. Polyfluoroalkyl substances (PFAS) can be used in technical mixtures (TMs) for use in food packaging of paper and board, and PFAS have been detected in human serum and umbilical cord blood. The specific structures of the PFAS in TMs are often unknown, but polyfluorinated alkyl phosphate esters (PAPs) have been characterized in TMs, food packaging, and in food. PAPs can be metabolized into fluorotelomer alcohols (FTOHs) and perfluoroalkyl carboxylic acids (PFCAs). Some PFAS have endocrine activities, highlighting the need to investigate these effects. Herein, we studied the endocrine activity of less characterized PFAS, including short-chain PFCAs and FTOHs, PAPs, and TMs of unknown chemical composition. Long-chain PFCAs were also included. We applied seven assays covering effects on estrogen, glucocorticoid, androgen, and peroxisome proliferator-activated receptor (PPAR) activity, as well as steroidogenesis in vitro and ex vivo. In general, PAPs, FTOHs, TMs, and long-chain PFCAs showed estrogenic activity through receptor activation and/or increasing 17β-estradiol levels. Furthermore, short- and long-chain PFCAs activated PPARα and PPARγ. Collectively, this means that (i) PAPs, FTOHs, and PFCAs exhibit endocrine activity through distinct and sometimes different mechanisms, (ii) two out of three tested TMs exhibited estrogenic activity, and (iii) short-chain FTOHs showed estrogenic activity and short-chain PFCAs generally activate both PPARα and PPARγ with similar potency and efficacy as long-chain PFCAs. In conclusion, several new and divergent toxicological targets were identified for different groups of PFAS. © 2016 American Society of Andrology and European Academy of Andrology.

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

    NASA Astrophysics Data System (ADS)

    Sommer, Philipp

    2016-04-01

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

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

    PubMed

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

    2010-11-01

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

  19. 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.

  20. An intuitive Python interface for Bioconductor libraries demonstrates the utility of language translators

    PubMed Central

    2010-01-01

    Background Computer languages can be domain-related, and in the case of multidisciplinary projects, knowledge of several languages will be needed in order to quickly implements ideas. Moreover, each computer language has relative strong points, making some languages better suited than others for a given task to be implemented. The Bioconductor project, based on the R language, has become a reference for the numerical processing and statistical analysis of data coming from high-throughput biological assays, providing a rich selection of methods and algorithms to the research community. At the same time, Python has matured as a rich and reliable language for the agile development of prototypes or final implementations, as well as for handling large data sets. Results The data structures and functions from Bioconductor can be exposed to Python as a regular library. This allows a fully transparent and native use of Bioconductor from Python, without one having to know the R language and with only a small community of translators required to know both. To demonstrate this, we have implemented such Python representations for key infrastructure packages in Bioconductor, letting a Python programmer handle annotation data, microarray data, and next-generation sequencing data. Conclusions Bioconductor is now not solely reserved to R users. Building a Python application using Bioconductor functionality can be done just like if Bioconductor was a Python package. Moreover, similar principles can be applied to other languages and libraries. Our Python package is available at: http://pypi.python.org/pypi/rpy2-bioconductor-extensions/ PMID:21210978

  1. Acariasis on pet Burmese python, Python molurus bivittatus in Malaysia.

    PubMed

    Mariana, A; Vellayan, S; Halimaton, I; Ho, T M

    2011-03-01

    To identify the acari present on pet Burmese pythons in Malaysia and to determine whether there is any potential public health risk related to handling of the snakes. Two sub-adult Burmese pythons kept as pets for a period of about 6 to 7 months by different owners, were brought to an exotic animal practice for treatment. On a complete medical examination, some ticks and mites (acari) were detected beneath the dorsal and ventral scales along body length of the snakes. Ticks were directly identified and mites were mounted prior to identification. A total of 12 ticks represented by 3 males, 2 females and 7 nymphal stages of Rhipicephalus sanguineus (R. sanguineus) were extracted from the first python while the other one was with 25 female Ophionyssus natricis (O. natricis) mesostigmatid mites. Only adult female mites were found. These mites are common ectoparasites of Burmese pythons. Both the acarine species found on the Burmese pythons are known vectors of pathogens. This is the first record that R. sanguineus has been reported from a pet Burmese python in Malaysia. Copyright © 2011 Hainan Medical College. Published by Elsevier B.V. All rights reserved.

  2. cyvcf2: fast, flexible variant analysis with Python.

    PubMed

    Pedersen, Brent S; Quinlan, Aaron R

    2017-06-15

    Variant call format (VCF) files document the genetic variation observed after DNA sequencing, alignment and variant calling of a sample cohort. Given the complexity of the VCF format as well as the diverse variant annotations and genotype metadata, there is a need for fast, flexible methods enabling intuitive analysis of the variant data within VCF and BCF files. We introduce cyvcf2 , a Python library and software package for fast parsing and querying of VCF and BCF files and illustrate its speed, simplicity and utility. bpederse@gmail.com or aaronquinlan@gmail.com. cyvcf2 is available from https://github.com/brentp/cyvcf2 under the MIT license and from common python package managers. Detailed documentation is available at http://brentp.github.io/cyvcf2/. © The Author 2017. Published by Oxford University Press.

  3. Scoria: a Python module for manipulating 3D molecular data.

    PubMed

    Ropp, Patrick; Friedman, Aaron; Durrant, Jacob D

    2017-09-18

    Third-party packages have transformed the Python programming language into a powerful computational-biology tool. Package installation is easy for experienced users, but novices sometimes struggle with dependencies and compilers. This presents a barrier that can hinder the otherwise broad adoption of new tools. We present Scoria, a Python package for manipulating three-dimensional molecular data. Unlike similar packages, Scoria requires no dependencies, compilation, or system-wide installation. One can incorporate the Scoria source code directly into their own programs. But Scoria is not designed to compete with other similar packages. Rather, it complements them. Our package leverages others (e.g. NumPy, SciPy), if present, to speed and extend its own functionality. To show its utility, we use Scoria to analyze a molecular dynamics trajectory. Our FootPrint script colors the atoms of one chain by the frequency of their contacts with a second chain. We are hopeful that Scoria will be a useful tool for the computational-biology community. A copy is available for download free of charge (Apache License 2.0) at http://durrantlab.com/scoria/ . Graphical abstract .

  4. 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.

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

    PubMed

    Guéguen, Laurent

    2005-08-15

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

  6. Pynamic: the Python Dynamic Benchmark

    SciTech Connect

    Lee, G L; Ahn, D H; de Supinksi, B R

    2007-07-10

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

  7. 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

  8. ScrumPy: metabolic modelling with Python.

    PubMed

    Poolman, M G

    2006-09-01

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

  9. PYTHON for Variable Star Astronomy (Abstract)

    NASA Astrophysics Data System (ADS)

    Craig, M.

    2018-06-01

    (Abstract only) Open source PYTHON packages that are useful for data reduction, photometry, and other tasks relevant to variable star astronomy have been developed over the last three to four years as part of the Astropy project. Using this software, it is relatively straightforward to reduce images, automatically detect sources, and match them to catalogs. Over the last year browser-based tools for performing some of those tasks have been developed that minimize or eliminate the need to write any of your own code. After providing an overview of the current state of the software, an application that calculates transformation coefficients on a frame-by-frame basis by matching stars in an image to the APASS catalog will be described.

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

    PubMed

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

    2012-05-15

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

  11. Respiratory disease in ball pythons (Python regius) experimentally infected with ball python nidovirus.

    PubMed

    Hoon-Hanks, Laura L; Layton, Marylee L; Ossiboff, Robert J; Parker, John S L; Dubovi, Edward J; Stenglein, Mark D

    2018-04-01

    Circumstantial evidence has linked a new group of nidoviruses with respiratory disease in pythons, lizards, and cattle. We conducted experimental infections in ball pythons (Python regius) to test the hypothesis that ball python nidovirus (BPNV) infection results in respiratory disease. Three ball pythons were inoculated orally and intratracheally with cell culture isolated BPNV and two were sham inoculated. Antemortem choanal, oroesophageal, and cloacal swabs and postmortem tissues of infected snakes were positive for viral RNA, protein, and infectious virus by qRT-PCR, immunohistochemistry, western blot and virus isolation. Clinical signs included oral mucosal reddening, abundant mucus secretions, open-mouthed breathing, and anorexia. Histologic lesions included chronic-active mucinous rhinitis, stomatitis, tracheitis, esophagitis and proliferative interstitial pneumonia. Control snakes remained negative and free of clinical signs throughout the experiment. Our findings establish a causal relationship between nidovirus infection and respiratory disease in ball pythons and shed light on disease progression and transmission. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

  12. IRISpy: Analyzing IRIS Data in Python

    NASA Astrophysics Data System (ADS)

    Ryan, Daniel; Christe, Steven; Mumford, Stuart; Baruah, Ankit; Timothy, Shelbe; Pereira, Tiago; De Pontieu, Bart

    2017-08-01

    IRISpy is a new community-developed open-source software library for analysing IRIS level 2 data. It is written in Python, a free, cross-platform, general-purpose, high-level programming language. A wide array of scientific computing software packages have already been developed in Python, from numerical computation (NumPy, SciPy, etc.), to visualization and plotting (matplotlib), to solar-physics-specific data analysis (SunPy). IRISpy is currently under development as a SunPy-affiliated package which means it depends on the SunPy library, follows similar standards and conventions, and is developed with the support of of the SunPy development team. IRISpy’s has two primary data objects, one for analyzing slit-jaw imager data and another for analyzing spectrograph data. Both objects contain basic slicing, indexing, plotting, and animating functionality to allow users to easily inspect, reduce and analyze the data. As part of this functionality the objects can output SunPy Maps, TimeSeries, Spectra, etc. of relevant data slices for easier inspection and analysis. Work is also ongoing to provide additional data analysis functionality including derivation of systematic measurement errors (e.g. readout noise), exposure time correction, residual wavelength calibration, radiometric calibration, and fine scale pointing corrections. IRISpy’s code base is publicly available through github.com and can be contributed to by anyone. In this poster we demonstrate IRISpy’s functionality and future goals of the project. We also encourage interested users to become involved in further developing IRISpy.

  13. OMPC: an Open-Source MATLAB®-to-Python Compiler

    PubMed Central

    Jurica, Peter; van Leeuwen, Cees

    2008-01-01

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

  14. Status of parallel Python-based implementation of UEDGE

    NASA Astrophysics Data System (ADS)

    Umansky, M. V.; Pankin, A. Y.; Rognlien, T. D.; Dimits, A. M.; Friedman, A.; Joseph, I.

    2017-10-01

    The tokamak edge transport code UEDGE has long used the code-development and run-time framework Basis. However, with the support for Basis expected to terminate in the coming years, and with the advent of the modern numerical language Python, it has become desirable to move UEDGE to Python, to ensure its long-term viability. Our new Python-based UEDGE implementation takes advantage of the portable build system developed for FACETS. The new implementation gives access to Python's graphical libraries and numerical packages for pre- and post-processing, and support of HDF5 simplifies exchanging data. The older serial version of UEDGE has used for time-stepping the Newton-Krylov solver NKSOL. The renovated implementation uses backward Euler discretization with nonlinear solvers from PETSc, which has the promise to significantly improve the UEDGE parallel performance. We will report on assessment of some of the extended UEDGE capabilities emerging in the new implementation, and will discuss the future directions. Work performed for U.S. DOE by LLNL under contract DE-AC52-07NA27344.

  15. 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.

  16. 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

  17. 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.

  18. 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.

  19. 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.

  20. PsychoPy—Psychophysics 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

  1. TRIPPy: Trailed Image Photometry in Python

    NASA Astrophysics Data System (ADS)

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

    2016-06-01

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

  2. PsychoPy--Psychophysics software in Python.

    PubMed

    Peirce, Jonathan W

    2007-05-15

    The vast majority of studies into visual processing are conducted using computer display technology. The current paper describes a new free suite of software tools designed to make this task easier, using the latest advances in hardware and software. PsychoPy is a platform-independent experimental control system written in the Python interpreted language using entirely free libraries. PsychoPy scripts are designed to be extremely easy to read and write, while retaining complete power for the user to customize the stimuli and environment. Tools are provided within the package to allow everything from stimulus presentation and response collection (from a wide range of devices) to simple data analysis such as psychometric function fitting. Most importantly, PsychoPy is highly extensible and the whole system can evolve via user contributions. If a user wants to add support for a particular stimulus, analysis or hardware device they can look at the code for existing examples, modify them and submit the modifications back into the package so that the whole community benefits.

  3. 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…

  4. ConKit: a python interface to contact predictions.

    PubMed

    Simkovic, Felix; Thomas, Jens M H; Rigden, Daniel J

    2017-07-15

    Recent advances in protein residue contact prediction algorithms have led to the emergence of many new methods and a variety of file formats. We present ConKit , an open source, modular and extensible Python interface which allows facile conversion between formats and provides an interface to analyses of sequence alignments and sets of contact predictions. ConKit is available via the Python Package Index. The documentation can be found at http://www.conkit.org . ConKit is licensed under the BSD 3-Clause. hlfsimko@liverpool.ac.uk or drigden@liverpool.ac.uk. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

  5. Python in Astronomy 2016 Unproceedings

    NASA Astrophysics Data System (ADS)

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

    2016-03-01

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

  6. 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 conceptmore » of a ''software bus'' can be realized in Python. It demonstrates, within the context of the ATLAS software framework Athena, how PyBus can be used for the installation and (run-time) configuration of software, not necessarily Python modules, from a Python application in a way that is transparent to the end-user.« less

  7. A streamlined Python framework for AT-TPC data analysis

    NASA Astrophysics Data System (ADS)

    Taylor, J. Z.; Bradt, J.; Bazin, D.; Kuchera, M. P.

    2017-09-01

    User-friendly data analysis software has been developed for the Active-Target Time Projection Chamber (AT-TPC) experiment at the National Superconducting Cyclotron Laboratory at Michigan State University. The AT-TPC, commissioned in 2014, is a gas-filled detector that acts as both the detector and target for high-efficiency detection of low-intensity, exotic nuclear reactions. The pytpc framework is a Python package for analyzing AT-TPC data. The package was developed for the analysis of 46Ar(p, p) data. The existing software was used to analyze data produced by the 40Ar(p, p) experiment that ran in August, 2015. Usage of the package was documented in an analysis manual both to improve analysis steps and aid in the work of future AT-TPC users. Software features and analysis methods in the pytpc framework will be presented along with the 40Ar results.

  8. The Effect of Modified Atmosphere Packaging and Addition of Rosemary Extract, Sodium Acetate and Calcium Lactate Mixture on the Quality of Pre-cooked Hamburger Patties during Refrigerated Storage

    PubMed Central

    Muhlisin; Kang, Sun Moon; Choi, Won Hee; Lee, Keun Taik; Cheong, Sung Hee; Lee, Sung Ki

    2013-01-01

    The effect of modified atmosphere packaging (MAP; 30% CO2+70% N2 or 100% N2) and an additive mixture (500 ppm rosemary extract, 3,000 ppm sodium acetate and 1,500 ppm calcium lactate) on the quality of pre-cooked hamburger patties during storage at 5°C for 14 d was evaluated. The addition of the additive mixture reduced aerobic and anaerobic bacteria counts in both 30% CO2-MAP (30% CO2+70% N2) and 100% N2-MAP (p<0.05). The 30% CO2-MAP was more effective to suppress the microbial growth than 100% N2-MAP, moreover the 30% CO2-MAP combined with additive mixture resulted in the lowest bacterial counts. The hamburger patties with additive mixture showed lower CIE L* and CIE a*, and higher CIE b* than those with no additive mixture. The 30% CO2-MAP tended to decrease the TBARS during storage regardless of the addition of additives. The use of 30% CO2-MAP in combination with additives mixture was effective for maintaining the quality and extending the shelf-life of pre-cooked hamburger patties. PMID:25049716

  9. Strike kinematics and performance in juvenile ball pythons (Python regius).

    PubMed

    Ryerson, William G; Tan, Weimin

    2017-08-01

    The rapid strike of snakes has interested researchers for decades. Although most work has focused on the strike performance of vipers, recent work has shown that other snakes outside of the Viperidae can strike with the same velocities and accelerations. However, to date all of these examples focus on performance in adult snakes. Here, we use high-speed video to measure the strike kinematics and performance of 10 juvenile (<6 months of age) ball pythons, Python regius. We find that juvenile P. regius strike at levels comparable to larger snakes, but with shorter durations and over shorter distances. We conclude that the juvenile P. regius maintain performance likely through manipulation of the axial musculature and accompanying elastic tissues, and that this is a first step to understanding ontogenetic changes in behavior and a potential avenue for understanding how captivity may also impact behavior. © 2017 Wiley Periodicals, Inc.

  10. Python Environment for Bayesian Learning: Inferring the Structure of Bayesian Networks from Knowledge and Data

    PubMed Central

    Shah, Abhik; Woolf, Peter

    2009-01-01

    Summary In this paper, we introduce pebl, a Python library and application for learning Bayesian network structure from data and prior knowledge that provides features unmatched by alternative software packages: the ability to use interventional data, flexible specification of structural priors, modeling with hidden variables and exploitation of parallel processing. PMID:20161541

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

    NASA Astrophysics Data System (ADS)

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

    2014-05-01

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

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

    SciTech Connect

    Helmus, Jonathan J.; Collis, Scott M.

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

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

    DOE PAGES

    Helmus, Jonathan J.; Collis, Scott M.

    2016-07-18

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

  14. 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.

  15. The fast azimuthal integration Python library: pyFAI.

    PubMed

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

    2015-04-01

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

  16. DendroPy: a Python library for phylogenetic computing.

    PubMed

    Sukumaran, Jeet; Holder, Mark T

    2010-06-15

    DendroPy is a cross-platform library for the Python programming language that provides for object-oriented reading, writing, simulation and manipulation of phylogenetic data, with an emphasis on phylogenetic tree operations. DendroPy uses a splits-hash mapping to perform rapid calculations of tree distances, similarities and shape under various metrics. It contains rich simulation routines to generate trees under a number of different phylogenetic and coalescent models. DendroPy's data simulation and manipulation facilities, in conjunction with its support of a broad range of phylogenetic data formats (NEXUS, Newick, PHYLIP, FASTA, NeXML, etc.), allow it to serve a useful role in various phyloinformatics and phylogeographic pipelines. The stable release of the library is available for download and automated installation through the Python Package Index site (http://pypi.python.org/pypi/DendroPy), while the active development source code repository is available to the public from GitHub (http://github.com/jeetsukumaran/DendroPy).

  17. BoF - Python in Astronomy

    NASA Astrophysics Data System (ADS)

    Barrett, P. E.

    This BoF will be chaired by Paul Barrett and will begin with an introduction to Python in astronomy, be followed by reports of current Python projects, and conclude with a discussion about the current state of Python in astronomy. The introduction will give a brief overview of the language, highlighting modules, resources, and aspects of the language that are important to scientific programming and astronomical data analysis. The closing discussion will provide an opportunity for questions and comments.

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

    PubMed

    Hedley, Joanna; Eatwell, Kevin; Schwarz, Tobias

    2014-01-01

    Anesthesia and tube restraint methods are often required for computed tomography (CT) of snakes due to their natural tendency to curl up. However, these restraint methods may cause animal stress. The aim of this study was to determine whether the CT appearance of the lungs differs for ball pythons in a curled position vs. tube restraint. Whole body CT was performed on ten clinically healthy ball pythons, first in curled and then in straight positions restrained in a tube. Curved multiplanar reformatted (MPR) lung images from curled position scans were compared with standard MPR lung images from straight position scans. Lung attenuation and thickness were measured at three locations for each scan. Time for positioning and scanning was 12 ± 5 min shorter for curled snakes compared to tube restraint. Lung parenchyma thickness and attenuation declined from cranial to caudal on both straight and curled position images. Mean lung parenchyma thickness was greater in curled images at locations 1 (P = 0.048) and 3 (P = 0.044). Mean lung parenchyma thickness decreased between location 1 and 2 by 86-87% (straight: curled) and between location 1 and 3 by 51-50% (straight: curled). Mean lung attenuation at location 1 was significantly greater on curled position images than tube restraint images (P = 0.043). Findings indicated that CT evaluation of the lungs is feasible for ball pythons positioned in curled recumbency if curved MPR is available. However, lung parenchyma thickness and attenuation in some locations may vary from those acquired using tube restraint. © 2014 American College of Veterinary Radiology.

  19. 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.

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

    PubMed

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

    2016-06-01

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

  1. pyhector: A Python interface for the simple climate model Hector

    SciTech Connect

    N Willner, Sven; Hartin, Corinne; Gieseke, Robert

    2017-04-01

    Pyhector is a Python interface for the simple climate model Hector (Hartin et al. 2015) developed in C++. Simple climate models like Hector can, for instance, be used in the analysis of scenarios within integrated assessment models like GCAM1, in the emulation of complex climate models, and in uncertainty analyses. Hector is an open-source, object oriented, simple global climate carbon cycle model. Its carbon cycle consists of a one pool atmosphere, three terrestrial pools which can be broken down into finer biomes or regions, and four carbon pools in the ocean component. The terrestrial carbon cycle includes primary production andmore » respiration fluxes. The ocean carbon cycle circulates carbon via a simplified thermohaline circulation, calculating air-sea fluxes as well as the marine carbonate system (Hartin et al. 2016). The model input is time series of greenhouse gas emissions; as example scenarios for these the Pyhector package contains the Representative Concentration Pathways (RCPs)2. These were developed to cover the range of baseline and mitigation emissions scenarios and are widely used in climate change research and model intercomparison projects. Using DataFrames from the Python library Pandas (McKinney 2010) as a data structure for the scenarios simplifies generating and adapting scenarios. Other parameters of the Hector model can easily be modified when running the model. Pyhector can be installed using pip from the Python Package Index.3 Source code and issue tracker are available in Pyhector's GitHub repository4. Documentation is provided through Readthedocs5. Usage examples are also contained in the repository as a Jupyter Notebook (Pérez and Granger 2007; Kluyver et al. 2016). Courtesy of the Mybinder project6, the example Notebook can also be executed and modified without installing Pyhector locally.« less

  2. COBRApy: COnstraints-Based Reconstruction and Analysis for Python.

    PubMed

    Ebrahim, Ali; Lerman, Joshua A; Palsson, Bernhard O; Hyduke, Daniel R

    2013-08-08

    COnstraint-Based Reconstruction and Analysis (COBRA) methods are widely used for genome-scale modeling of metabolic networks in both prokaryotes and eukaryotes. Due to the successes with metabolism, there is an increasing effort to apply COBRA methods to reconstruct and analyze integrated models of cellular processes. The COBRA Toolbox for MATLAB is a leading software package for genome-scale analysis of metabolism; however, it was not designed to elegantly capture the complexity inherent in integrated biological networks and lacks an integration framework for the multiomics data used in systems biology. The openCOBRA Project is a community effort to promote constraints-based research through the distribution of freely available software. Here, we describe COBRA for Python (COBRApy), a Python package that provides support for basic COBRA methods. COBRApy is designed in an object-oriented fashion that facilitates the representation of the complex biological processes of metabolism and gene expression. COBRApy does not require MATLAB to function; however, it includes an interface to the COBRA Toolbox for MATLAB to facilitate use of legacy codes. For improved performance, COBRApy includes parallel processing support for computationally intensive processes. COBRApy is an object-oriented framework designed to meet the computational challenges associated with the next generation of stoichiometric constraint-based models and high-density omics data sets. http://opencobra.sourceforge.net/

  3. ssbio: a Python framework for structural systems biology.

    PubMed

    Mih, Nathan; Brunk, Elizabeth; Chen, Ke; Catoiu, Edward; Sastry, Anand; Kavvas, Erol; Monk, Jonathan M; Zhang, Zhen; Palsson, Bernhard O

    2018-06-15

    Working with protein structures at the genome-scale has been challenging in a variety of ways. Here, we present ssbio, a Python package that provides a framework to easily work with structural information in the context of genome-scale network reconstructions, which can contain thousands of individual proteins. The ssbio package provides an automated pipeline to construct high quality genome-scale models with protein structures (GEM-PROs), wrappers to popular third-party programs to compute associated protein properties, and methods to visualize and annotate structures directly in Jupyter notebooks, thus lowering the barrier of linking 3D structural data with established systems workflows. ssbio is implemented in Python and available to download under the MIT license at http://github.com/SBRG/ssbio. Documentation and Jupyter notebook tutorials are available at http://ssbio.readthedocs.io/en/latest/. Interactive notebooks can be launched using Binder at https://mybinder.org/v2/gh/SBRG/ssbio/master?filepath=Binder.ipynb. Supplementary data are available at Bioinformatics online.

  4. On Parallel Software Engineering Education Using Python

    ERIC Educational Resources Information Center

    Marowka, Ami

    2018-01-01

    Python is gaining popularity in academia as the preferred language to teach novices serial programming. The syntax of Python is clean, easy, and simple to understand. At the same time, it is a high-level programming language that supports multi programming paradigms such as imperative, functional, and object-oriented. Therefore, by default, it is…

  5. pyMOOGi - python wrapper for MOOG

    NASA Astrophysics Data System (ADS)

    Adamow, Monika M.

    2017-06-01

    pyMOOGi is a python wrapper for MOOG. It allows to use MOOG in a classical, interactive way, but with all graphics handled by python libraries. Some MOOG features have been redesigned, like plotting with abfind driver. Also, new funtions have been added, like automatic rescaling of stellar spectrum for synth driver. pyMOOGi is an open source project.

  6. The atomic simulation environment-a Python library for working with atoms.

    PubMed

    Hjorth Larsen, Ask; Jørgen Mortensen, Jens; Blomqvist, Jakob; Castelli, Ivano E; Christensen, Rune; Dułak, Marcin; Friis, Jesper; Groves, Michael N; Hammer, Bjørk; Hargus, Cory; Hermes, Eric D; Jennings, Paul C; Bjerre Jensen, Peter; Kermode, James; Kitchin, John R; Leonhard Kolsbjerg, Esben; Kubal, Joseph; Kaasbjerg, Kristen; Lysgaard, Steen; Bergmann Maronsson, Jón; Maxson, Tristan; Olsen, Thomas; Pastewka, Lars; Peterson, Andrew; Rostgaard, Carsten; Schiøtz, Jakob; Schütt, Ole; Strange, Mikkel; Thygesen, Kristian S; Vegge, Tejs; Vilhelmsen, Lasse; Walter, Michael; Zeng, Zhenhua; Jacobsen, Karsten W

    2017-07-12

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

  7. The atomic simulation environment—a Python library for working with atoms

    NASA Astrophysics Data System (ADS)

    Hjorth Larsen, Ask; Jørgen Mortensen, Jens; Blomqvist, Jakob; Castelli, Ivano E.; Christensen, Rune; Dułak, Marcin; Friis, Jesper; Groves, Michael N.; Hammer, Bjørk; Hargus, Cory; Hermes, Eric D.; Jennings, Paul C.; Bjerre Jensen, Peter; Kermode, James; Kitchin, John R.; Leonhard Kolsbjerg, Esben; Kubal, Joseph; Kaasbjerg, Kristen; Lysgaard, Steen; Bergmann Maronsson, Jón; Maxson, Tristan; Olsen, Thomas; Pastewka, Lars; Peterson, Andrew; Rostgaard, Carsten; Schiøtz, Jakob; Schütt, Ole; Strange, Mikkel; Thygesen, Kristian S.; Vegge, Tejs; Vilhelmsen, Lasse; Walter, Michael; Zeng, Zhenhua; Jacobsen, Karsten W.

    2017-07-01

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

  8. 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.

  9. 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

  10. 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 librarymore » gives access to data distribution routines in C, C++, and FORTRAN. But we need more than that. Many reasonable and common tasks are best done in (or as extensions to) scripting languages. Consider sysadm tools such as password crackers, file purgers, etc ... These are simple to write in a scripting language such as Python (an open source, portable, and freely available interpreter). But these tasks beg to be done in parallel. Consider the a password checker that checks an encrypted password against a 25,000 word dictionary. This can take around 10 seconds in Python (6 seconds in C). It is trivial to parallelize if you can distribute the information and co-ordinate the work.« less

  11. 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.

  12. Naval Observatory Vector Astrometry Software (NOVAS) Version 3.1, Introducing a Python Edition

    NASA Astrophysics Data System (ADS)

    Barron, Eric G.; Kaplan, G. H.; Bangert, J.; Bartlett, J. L.; Puatua, W.; Harris, W.; Barrett, P.

    2011-01-01

    The Naval Observatory Vector Astrometry Software (NOVAS) is a source-code library that provides common astrometric quantities and transformations. NOVAS calculations are accurate at the sub-milliarcsecond level. The library can supply, in one or two subroutine or function calls, the instantaneous celestial position of any star or planet in a variety of coordinate systems. NOVAS also provides access to all of the building blocks that go into such computations. NOVAS Version 3.1 introduces a Python edition alongside the Fortran and C editions. The Python edition uses the computational code from the C edition and, currently, mimics the function calls of the C edition. Future versions will expand the functionality of the Python edition to harness the object-oriented nature of the Python language, and will implement the ability to handle large quantities of objects or observers using the array functionality in NumPy (a third-party scientific package for Python). NOVAS 3.1 also adds a module to transform GCRS vectors to the ITRS; the ITRS to GCRS transformation was already provided in NOVAS 3.0. The module that corrects an ITRS vector for polar motion has been modified to undo that correction upon demand. In the C edition, the ephemeris-access functions have been revised for use on 64-bit systems and for improved performance in general. NOVAS, including documentation, is available from the USNO website (http://www.usno.navy.mil/USNO/astronomical-applications/software-products/novas).

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

    PubMed Central

    Pecevski, Dejan; Natschläger, Thomas; Schuch, Klaus

    2008-01-01

    The Parallel Circuit SIMulator (PCSIM) is a software package for simulation of neural circuits. It is primarily designed for distributed simulation of large scale networks of spiking point neurons. Although its computational core is written in C++, PCSIM's primary interface is implemented in the Python programming language, which is a powerful programming environment and allows the user to easily integrate the neural circuit simulator with data analysis and visualization tools to manage the full neural modeling life cycle. The main focus of this paper is to describe PCSIM's full integration into Python and the benefits thereof. In particular we will investigate how the automatically generated bidirectional interface and PCSIM's object-oriented modular framework enable the user to adopt a hybrid modeling approach: using and extending PCSIM's functionality either employing pure Python or C++ and thus combining the advantages of both worlds. Furthermore, we describe several supplementary PCSIM packages written in pure Python and tailored towards setting up and analyzing neural simulations. PMID:19543450

  14. Astronomical Simulations Using Visual Python

    NASA Astrophysics Data System (ADS)

    Cobb, Michael L.

    2007-05-01

    The Physics and Engineering Physics Department at Southeast Missouri State University has adopted the “Matter and Interactions I Modern Mechanics” text by Chabay and Sherwood for our calculus based introductory physics course. We have fully integrated the use of modeling and simulations by using the Visual Python language also know as VPython. This powerful, high level, object orientated language with full three dimensional, stereo graphics has stimulated both my students and myself to find wider applications for our new found skills. We have successfully modeled gravitational resonances in planetary rings, galaxy collisions, and planetary orbits around binary star systems. This talk will provide a quick overview of VPython and demonstrate the various simulations.

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

    PubMed

    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/.

  16. PyCoTools: A Python Toolbox for COPASI.

    PubMed

    Welsh, Ciaran M; Fullard, Nicola; Proctor, Carole J; Martinez-Guimera, Alvaro; Isfort, Robert J; Bascom, Charles C; Tasseff, Ryan; Przyborski, Stefan A; Shanley, Daryl P

    2018-05-22

    COPASI is an open source software package for constructing, simulating and analysing dynamic models of biochemical networks. COPASI is primarily intended to be used with a graphical user interface but often it is desirable to be able to access COPASI features programmatically, with a high level interface. PyCoTools is a Python package aimed at providing a high level interface to COPASI tasks with an emphasis on model calibration. PyCoTools enables the construction of COPASI models and the execution of a subset of COPASI tasks including time courses, parameter scans and parameter estimations. Additional 'composite' tasks which use COPASI tasks as building blocks are available for increasing parameter estimation throughput, performing identifiability analysis and performing model selection. PyCoTools supports exploratory data analysis on parameter estimation data to assist with troubleshooting model calibrations. We demonstrate PyCoTools by posing a model selection problem designed to show case PyCoTools within a realistic scenario. The aim of the model selection problem is to test the feasibility of three alternative hypotheses in explaining experimental data derived from neonatal dermal fibroblasts in response to TGF-β over time. PyCoTools is used to critically analyse the parameter estimations and propose strategies for model improvement. PyCoTools can be downloaded from the Python Package Index (PyPI) using the command 'pip install pycotools' or directly from GitHub (https://github.com/CiaranWelsh/pycotools). Documentation at http://pycotools.readthedocs.io. Supplementary data are available at Bioinformatics.

  17. Python based high-level synthesis compiler

    NASA Astrophysics Data System (ADS)

    Cieszewski, Radosław; Pozniak, Krzysztof; Romaniuk, Ryszard

    2014-11-01

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

  18. Modeling Quantum Teleportation with Quantum Tools in Python (QuTiP)

    DTIC Science & Technology

    2017-12-01

    FORM TO THE ABOVE ADDRESS. 1. REPORT DATE (DD-MM-YYYY) December 2017 2. REPORT TYPE Technical Report 3. DATES COVERED (From - To) June 1, 2017... technical report we evaluate one in particular, the Quantum Tools in Python (QuTiP) package, to determine its suitability for use in the simulation of...found that QuTiP is technically sound in that it is able to reproduce several published findings, and that it saves significant program design time due

  19. 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/.

  20. Packaging Software Assets for Reuse

    NASA Astrophysics Data System (ADS)

    Mattmann, C. A.; Marshall, J. J.; Downs, R. R.

    2010-12-01

    The reuse of existing software assets such as code, architecture, libraries, and modules in current software and systems development projects can provide many benefits, including reduced costs, in time and effort, and increased reliability. Many reusable assets are currently available in various online catalogs and repositories, usually broken down by disciplines such as programming language (Ibiblio for Maven/Java developers, PyPI for Python developers, CPAN for Perl developers, etc.). The way these assets are packaged for distribution can play a role in their reuse - an asset that is packaged simply and logically is typically easier to understand, install, and use, thereby increasing its reusability. A well-packaged asset has advantages in being more reusable and thus more likely to provide benefits through its reuse. This presentation will discuss various aspects of software asset packaging and how they can affect the reusability of the assets. The characteristics of well-packaged software will be described. A software packaging domain model will be introduced, and some existing packaging approaches examined. An example case study of a Reuse Enablement System (RES), currently being created by near-term Earth science decadal survey missions, will provide information about the use of the domain model. Awareness of these factors will help software developers package their reusable assets so that they can provide the most benefits for software reuse.

  1. Introduction to Python for CMF Authority Users

    SciTech Connect

    Pritchett-Sheats, Lori A.

    This talk is a very broad over view of Python that highlights key features in the language used in the Common Model Framework (CMF). I assume that the audience has some programming experience in a shell scripting language (C shell, Bash, PERL) or other high level language (C/C++/ Fortran). The talk will cover Python data types, classes (objects) and basic programming constructs. The talk concludes with slides describing how I developed the basic classes for a TITANS homework assignment.

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

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

    PubMed

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

    2014-01-01

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

  4. 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

  5. SCoT: a Python toolbox for EEG source connectivity

    PubMed Central

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

    2014-01-01

    Analysis of brain connectivity has become an important research tool in neuroscience. Connectivity can be estimated between cortical sources reconstructed from the electroencephalogram (EEG). Such analysis often relies on trial averaging to obtain reliable results. However, some applications such as brain-computer interfaces (BCIs) require single-trial estimation methods. In this paper, we present SCoT—a source connectivity toolbox for Python. This toolbox implements routines for blind source decomposition and connectivity estimation with the MVARICA approach. Additionally, a novel extension called CSPVARICA is available for labeled data. SCoT estimates connectivity from various spectral measures relying on vector autoregressive (VAR) models. Optionally, these VAR models can be regularized to facilitate ill posed applications such as single-trial fitting. We demonstrate basic usage of SCoT on motor imagery (MI) data. Furthermore, we show simulation results of utilizing SCoT for feature extraction in a BCI application. These results indicate that CSPVARICA and correct regularization can significantly improve MI classification. While SCoT was mainly designed for application in BCIs, it contains useful tools for other areas of neuroscience. SCoT is a software package that (1) brings combined source decomposition and connectivtiy estimation to the open Python platform, and (2) offers tools for single-trial connectivity estimation. The source code is released under the MIT license and is available online at github.com/SCoT-dev/SCoT. PMID:24653694

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

    NASA Astrophysics Data System (ADS)

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

    2015-04-01

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

  7. A Python Geospatial Language Toolkit

    NASA Astrophysics Data System (ADS)

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

    2012-12-01

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

  8. One-dimensional statistical parametric mapping in Python.

    PubMed

    Pataky, Todd C

    2012-01-01

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

  9. PDB file parser and structure class implemented in Python.

    PubMed

    Hamelryck, Thomas; Manderick, Bernard

    2003-11-22

    The biopython project provides a set of bioinformatics tools implemented in Python. Recently, biopython was extended with a set of modules that deal with macromolecular structure. Biopython now contains a parser for PDB files that makes the atomic information available in an easy-to-use but powerful data structure. The parser and data structure deal with features that are often left out or handled inadequately by other packages, e.g. atom and residue disorder (if point mutants are present in the crystal), anisotropic B factors, multiple models and insertion codes. In addition, the parser performs some sanity checking to detect obvious errors. The Biopython distribution (including source code and documentation) is freely available (under the Biopython license) from http://www.biopython.org

  10. pyhector: A Python interface for the simple climate model Hector

    DOE PAGES

    Willner, Sven N.; Hartin, Corinne; Gieseke, Robert

    2017-04-01

    Here, pyhector is a Python interface for the simple climate model Hector (Hartin et al. 2015) developed in C++. Simple climate models like Hector can, for instance, be used in the analysis of scenarios within integrated assessment models like GCAM1, in the emulation of complex climate models, and in uncertainty analyses. Hector is an open-source, object oriented, simple global climate carbon cycle model. Its carbon cycle consists of a one pool atmosphere, three terrestrial pools which can be broken down into finer biomes or regions, and four carbon pools in the ocean component. The terrestrial carbon cycle includes primary productionmore » and respiration fluxes. The ocean carbon cycle circulates carbon via a simplified thermohaline circulation, calculating air-sea fluxes as well as the marine carbonate system. The model input is time series of greenhouse gas emissions; as example scenarios for these the Pyhector package contains the Representative Concentration Pathways (RCPs)2.« less

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

    NASA Astrophysics Data System (ADS)

    Mulansky, Mario; Kreuz, Thomas

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

  12. batman: BAsic Transit Model cAlculatioN in Python

    NASA Astrophysics Data System (ADS)

    Kreidberg, Laura

    2015-11-01

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

  13. 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

  14. Ultrasonographic anatomy of the coelomic organs of boid snakes (Boa constrictor imperator, Python regius, Python molurus molurus, and Python curtus).

    PubMed

    Banzato, Tommaso; Russo, Elisa; Finotti, Luca; Milan, Maria C; Gianesella, Matteo; Zotti, Alessandro

    2012-05-01

    To determine the ultrasonographic features of the coelomic organs of healthy snakes belonging to the Boidae and Pythonidae families. 16 ball pythons (Python regius; 7 males, 8 females, and 1 sexually immature), 10 Indian rock pythons (Python molurus molurus; 5 males, 4 females, and 1 sexually immature), 12 Python curtus (5 males and 7 females), and 8 boa constrictors (Boa constrictor imperator; 4 males and 4 females). All snakes underwent complete ultrasonographic evaluation of the coelomic cavity; chemical restraint was not necessary. A dorsolateral approach to probe placement was chosen to increase image quality and to avoid injury to the snakes and operators. Qualitative and quantitative observations were recorded. The liver, stomach, gallbladder, pancreas, small and large intestines, kidneys, cloaca, and scent glands were identified in all snakes. The hemipenes were identified in 10 of the 21 (48%) male snakes. The spleen was identified in 5 of the 46 (11%) snakes, and ureters were identified in 6 (13%). In 2 sexually immature snakes, the gonads were not visible. One (2%) snake was gravid, and 7 (15%) had small amounts of free fluid in the coelomic cavity. A significant positive correlation was identified between several measurements (diameter and thickness of scent glands, gastric and pyloric walls, and colonic wall) and body length (snout to vent) and body weight. The study findings can be used as an atlas of the ultrasonographic anatomy of the coelomic cavity in healthy boid snakes. Ultrasonography was reasonably fast to perform and was well tolerated in conscious snakes.

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

    SciTech Connect

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

    2011-01-01

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

  16. PyPDB: a Python API for the Protein Data Bank.

    PubMed

    Gilpin, William

    2016-01-01

    We have created a Python programming interface for the RCSB Protein Data Bank (PDB) that allows search and data retrieval for a wide range of result types, including BLAST and sequence motif queries. The API relies on the existing XML-based API and operates by creating custom XML requests from native Python types, allowing extensibility and straightforward modification. The package has the ability to perform many types of advanced search of the PDB that are otherwise only available through the PDB website. PyPDB is implemented exclusively in Python 3 using standard libraries for maximal compatibility. The most up-to-date version, including iPython notebooks containing usage tutorials, is available free-of-charge under an open-source MIT license via GitHub at https://github.com/williamgilpin/pypdb, and the full API reference is at http://williamgilpin.github.io/pypdb_docs/html/. The latest stable release is also available on PyPI. wgilpin@stanford.edu. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  17. 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

  18. 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

  19. Python for large-scale electrophysiology.

    PubMed

    Spacek, Martin; Blanche, Tim; Swindale, Nicholas

    2008-01-01

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

  20. 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.

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

    PubMed

    Jensen, Bjarke; Wang, Tobias

    2009-12-01

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

  3. 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.

  4. Information-Theoretical Analysis of EEG Microstate Sequences in Python.

    PubMed

    von Wegner, Frederic; Laufs, Helmut

    2018-01-01

    We present an open-source Python package to compute information-theoretical quantities for electroencephalographic data. Electroencephalography (EEG) measures the electrical potential generated by the cerebral cortex and the set of spatial patterns projected by the brain's electrical potential on the scalp surface can be clustered into a set of representative maps called EEG microstates. Microstate time series are obtained by competitively fitting the microstate maps back into the EEG data set, i.e., by substituting the EEG data at a given time with the label of the microstate that has the highest similarity with the actual EEG topography. As microstate sequences consist of non-metric random variables, e.g., the letters A-D, we recently introduced information-theoretical measures to quantify these time series. In wakeful resting state EEG recordings, we found new characteristics of microstate sequences such as periodicities related to EEG frequency bands. The algorithms used are here provided as an open-source package and their use is explained in a tutorial style. The package is self-contained and the programming style is procedural, focusing on code intelligibility and easy portability. Using a sample EEG file, we demonstrate how to perform EEG microstate segmentation using the modified K-means approach, and how to compute and visualize the recently introduced information-theoretical tests and quantities. The time-lagged mutual information function is derived as a discrete symbolic alternative to the autocorrelation function for metric time series and confidence intervals are computed from Markov chain surrogate data. The software package provides an open-source extension to the existing implementations of the microstate transform and is specifically designed to analyze resting state EEG recordings.

  5. 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.

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

    PubMed

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

    2010-09-01

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

  7. Ibmdbpy-spatial : An Open-source implementation of in-database geospatial analytics in Python

    NASA Astrophysics Data System (ADS)

    Roy, Avipsa; Fouché, Edouard; Rodriguez Morales, Rafael; Moehler, Gregor

    2017-04-01

    As the amount of spatial data acquired from several geodetic sources has grown over the years and as data infrastructure has become more powerful, the need for adoption of in-database analytic technology within geosciences has grown rapidly. In-database analytics on spatial data stored in a traditional enterprise data warehouse enables much faster retrieval and analysis for making better predictions about risks and opportunities, identifying trends and spot anomalies. Although there are a number of open-source spatial analysis libraries like geopandas and shapely available today, most of them have been restricted to manipulation and analysis of geometric objects with a dependency on GEOS and similar libraries. We present an open-source software package, written in Python, to fill the gap between spatial analysis and in-database analytics. Ibmdbpy-spatial provides a geospatial extension to the ibmdbpy package, implemented in 2015. It provides an interface for spatial data manipulation and access to in-database algorithms in IBM dashDB, a data warehouse platform with a spatial extender that runs as a service on IBM's cloud platform called Bluemix. Working in-database reduces the network overload, as the complete data need not be replicated into the user's local system altogether and only a subset of the entire dataset can be fetched into memory in a single instance. Ibmdbpy-spatial accelerates Python analytics by seamlessly pushing operations written in Python into the underlying database for execution using the dashDB spatial extender, thereby benefiting from in-database performance-enhancing features, such as columnar storage and parallel processing. The package is currently supported on Python versions from 2.7 up to 3.4. The basic architecture of the package consists of three main components - 1) a connection to the dashDB represented by the instance IdaDataBase, which uses a middleware API namely - pypyodbc or jaydebeapi to establish the database connection via

  8. A Gene Ontology Tutorial in Python.

    PubMed

    Vesztrocy, Alex Warwick; Dessimoz, Christophe

    2017-01-01

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

  9. 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

  10. Python scripting in the nengo simulator.

    PubMed

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

    2009-01-01

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

  11. SymPy: Symbolic computing in python

    DOE PAGES

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

    2017-01-02

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

  12. An Object-Oriented Python Implementation of an Intermediate-Level Atmospheric Model

    NASA Astrophysics Data System (ADS)

    Lin, J. W.

    2008-12-01

    The Neelin-Zeng Quasi-equilibrium Tropical Circulation Model (QTCM1) is a Fortran-based intermediate-level atmospheric model that includes simplified treatments of several physical processes, including a GCM-like convective scheme and a land-surface scheme with representations of different surface types, evaporation, and soil moisture. This model has been used in studies of the Madden-Julian oscillation, ENSO, and vegetation-atmosphere interaction effects on climate. Through the assumption of convective quasi-equilibrium in the troposphere, the QTCM1 is able to include full nonlinearity, resolve baroclinic disturbances, and generate a reasonable climatology, all at low computational cost. One year of simulation on a PC at 5.625 × 3.75 degree longitude-latitude resolution takes under three minutes of wall-clock time. The Python package qtcm implements the QTCM1 in a mixed-language environment that retains the speed of compiled Fortran while providing the benefits of Python's object-oriented framework and robust suite of utilities and datatypes. We describe key programming constructs used to create this modeling environment: the decomposition of model runs into Python objects, providing methods so visualization tools are attached to model runs, and the use of Python's mutable datatypes (lists and dictionaries) to implement the "run list" entity, which enables total runtime control of subroutine execution order and content. The result is an interactive modeling environment where the traditional sequence of "hypothesis → modeling → visualization and analysis" is opened up and made nonlinear and flexible. In this environment, science tasks such as parameter-space exploration and testing alternative parameterizations can be easily automated, without the need for multiple versions of the model code interacting with a bevy of makefiles and shell scripts. The environment also simplifies interfacing of the atmospheric model to other models (e.g., hydrologic models

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

    PubMed

    Penning, David A; Dartez, Schuyler F

    2016-03-01

    Constriction is a prey-immobilization technique used by many snakes and is hypothesized to have been important to the evolution and diversification of snakes. However, very few studies have examined the factors that affect constriction performance. We investigated constriction performance in ball pythons (Python regius) by evaluating how peak constriction pressure is affected by snake size, sex, and experience. In one experiment, we tested the ontogenetic scaling of constriction performance and found that snake diameter was the only significant factor determining peak constriction pressure. The number of loops applied in a coil and its interaction with snake diameter did not significantly affect constriction performance. Constriction performance in ball pythons scaled differently than in other snakes that have been studied, and medium to large ball pythons are capable of exerting significantly higher pressures than those shown to cause circulatory arrest in prey. In a second experiment, we tested the effects of experience on constriction performance in hatchling ball pythons over 10 feeding events. By allowing snakes in one test group to gain constriction experience, and manually feeding snakes under sedation in another test group, we showed that experience did not affect constriction performance. During their final (10th) feedings, all pythons constricted similarly and with sufficiently high pressures to kill prey rapidly. At the end of the 10 feeding trials, snakes that were allowed to constrict were significantly smaller than their non-constricting counterparts. © 2016 Wiley Periodicals, Inc.

  14. 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

  15. A New Python Library for Spectroscopic Analysis with MIDAS Style

    NASA Astrophysics Data System (ADS)

    Song, Y.; Luo, A.; Zhao, Y.

    2013-10-01

    The ESO MIDAS is a system for astronomers to analyze data which many astronomers are using. Python is a high level script language and there are many applications for astronomical data process. We are releasing a new Python library which realizes some MIDAS commands in Python. People can use it to write a MIDAS style Python code. We call it PydasLib. It is a Python library based on ESO MIDAS functions, which is easily used by astronomers who are familiar with the usage of MIDAS.

  16. SunPy 0.8 - Python for Solar Physics

    NASA Astrophysics Data System (ADS)

    Inglis, Andrew; Bobra, Monica; Christe, Steven; Hewett, Russell; Ireland, Jack; Mumford, Stuart; Martinez Oliveros, Juan Carlos; Perez-Suarez, David; Reardon, Kevin P.; Savage, Sabrina; Shih, Albert Y.; Ryan, Daniel; Sipocz, Brigitta; Freij, Nabil

    2017-08-01

    SunPy is a community-developed open-source software library for solar physics. It is written in Python, a free, cross-platform, general-purpose, high-level programming language which is being increasingly adopted throughout the scientific community. Python is one of the top ten most often used programming languages, as such it provides a wide array of software packages, such as numerical computation (NumPy, SciPy), machine learning (scikit-learn), signal processing (scikit-image, statsmodels) to visualization and plotting (matplotlib, mayavi). SunPy aims to provide the software for obtaining and analyzing solar and heliospheric data. This poster introduces a new major release of SunPy (0.8). This release includes two major new functionalities, as well as a number of bug fixes. It is based on 1120 contributions from 34 unique contributors. Fido is the new primary interface to download data. It provides a consistent and powerful search interface to all major data sources provides including VSO, JSOC, as well as individual data sources such as GOES XRS time series and and is fully pluggable to add new data sources, i.e. DKIST. In anticipation of Solar Orbiter and the Parker Solar Probe, SunPy now provides a powerful way of representing coordinates, allowing conversion between coordinate systems and viewpoints of different instruments, including preliminary reprojection capabilities. Other new features including new timeseries capabilities with better support for concatenation and metadata, updated documentation and example gallery. SunPy is distributed through pip and conda and all of its code is publicly available (sunpy.org).

  17. A Python Interface for the Dakota Iterative Systems Analysis Toolkit

    NASA Astrophysics Data System (ADS)

    Piper, M.; Hutton, E.; Syvitski, J. P.

    2016-12-01

    Uncertainty quantification is required to improve the accuracy, reliability, and accountability of Earth science models. Dakota is a software toolkit, developed at Sandia National Laboratories, that provides an interface between models and a library of analysis methods, including support for sensitivity analysis, uncertainty quantification, optimization, and calibration techniques. Dakota is a powerful tool, but its learning curve is steep: the user not only must understand the structure and syntax of the Dakota input file, but also must develop intermediate code, called an analysis driver, that allows Dakota to run a model. The CSDMS Dakota interface (CDI) is a Python package that wraps and extends Dakota's user interface. It simplifies the process of configuring and running a Dakota experiment. A user can program to the CDI, allowing a Dakota experiment to be scripted. The CDI creates Dakota input files and provides a generic analysis driver. Any model written in Python that exposes a Basic Model Interface (BMI), as well as any model componentized in the CSDMS modeling framework, automatically works with the CDI. The CDI has a plugin architecture, so models written in other languages, or those that don't expose a BMI, can be accessed by the CDI by programmatically extending a template; an example is provided in the CDI distribution. Currently, six Dakota analysis methods have been implemented for examples from the much larger Dakota library. To demonstrate the CDI, we performed an uncertainty quantification experiment with the HydroTrend hydrological water balance and transport model. In the experiment, we evaluated the response of long-term suspended sediment load at the river mouth (Qs) to uncertainty in two input parameters, annual mean temperature (T) and precipitation (P), over a series of 100-year runs, using the polynomial chaos method. Through Dakota, we calculated moments, local and global (Sobol') sensitivity indices, and probability density and

  18. 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.

  19. 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

  20. The Ocean Observatories Initiative: Data Acquisition Functions and Its Built-In Automated Python Modules

    NASA Astrophysics Data System (ADS)

    Smith, M. J.; Vardaro, M.; Crowley, M. F.; Glenn, S. M.; Schofield, O.; Belabbassi, L.; Garzio, L. M.; Knuth, F.; Fram, J. P.; Kerfoot, J.

    2016-02-01

    The Ocean Observatories Initiative (OOI), funded by the National Science Foundation, provides users with access to long-term datasets from a variety of oceanographic sensors. The Endurance Array in the Pacific Ocean consists of two separate lines off the coasts of Oregon and Washington. The Oregon line consists of 7 moorings, two cabled benthic experiment packages and 6 underwater gliders. The Washington line comprises 6 moorings and 6 gliders. Each mooring is outfitted with a variety of instrument packages. The raw data from these instruments are sent to shore via satellite communication and in some cases, via fiber optic cable. Raw data is then sent to the cyberinfrastructure (CI) group at Rutgers where it is aggregated, parsed into thousands of different data streams, and integrated into a software package called uFrame. The OOI CI delivers the data to the general public via a web interface that outputs data into commonly used scientific data file formats such as JSON, netCDF, and CSV. The Rutgers data management team has developed a series of command-line Python tools that streamline data acquisition in order to facilitate the QA/QC review process. The first step in the process is querying the uFrame database for a list of all available platforms. From this list, a user can choose a specific platform and automatically download all available datasets from the specified platform. The downloaded dataset is plotted using a generalized Python netcdf plotting routine that utilizes a data visualization toolbox called matplotlib. This routine loads each netCDF file separately and outputs plots by each available parameter. These Python tools have been uploaded to a Github repository that is openly available to help facilitate OOI data access and visualization.

  1. Unilateral microphthalmia or anophthalmia in eight pythons (Pythonidae).

    PubMed

    Da Silva, Mari-Ann O; Bertelsen, Mads F; Wang, Tobias; Pedersen, Michael; Lauridsen, Henrik; Heegaard, Steffen

    2015-01-01

    To provide morphological descriptions of microphthalmia or anophthalmia in eight pythons using microcomputerized tomography (μCT), magnetic resonance imaging (MRI), and histopathology. Seven Burmese pythons (Python bivittatus) and one ball python (P. regius) with clinically normal right eyes and an abnormal or missing left eye. At the time of euthanasia, four of the eight snakes underwent necropsy. Hereafter, the heads of two Burmese pythons and one ball python were examined using μCT, and another Burmese python was subjected to MRI. Following these procedures, the heads of these four pythons along with the heads of an additional three Burmese pythons were prepared for histology. All eight snakes had left ocular openings seen as dermal invaginations between 0.2 and 2.0 mm in diameter. They also had varying degrees of malformations of the orbital bones and a limited presence of nervous, glandular, and muscle tissue in the posterior orbit. Two individuals had small but identifiable eyes. Furthermore, remnants of the pigmented embryonic framework of the hyaloid vessels were found in the anophthalmic snakes. Necropsies revealed no other macroscopic anomalies. Eight pythons with unilateral left-sided microphthalmia or anophthalmia had one normal eye and a left orbit with malformed or incompletely developed ocular structures along with remnants of fetal structures. These cases lend further information to a condition that is often seen in snakes, but infrequently described. © 2014 American College of Veterinary Ophthalmologists.

  2. Detection of nidoviruses in live pythons and boas.

    PubMed

    Marschang, Rachel E; Kolesnik, Ekaterina

    2017-02-09

    Nidoviruses have recently been described as a putative cause of severe respiratory disease in pythons in the USA and Europe. The objective of this study was to establish the use of a conventional PCR for the detection of nidoviruses in samples from live animals and to extend the list of susceptible species. A PCR targeting a portion of ORF1a of python nidoviruses was used to detect nidoviruses in diagnostic samples from live boas and pythons. A total of 95 pythons, 84 boas and 22 snakes of unknown species were included in the study. Samples tested included oral swabs and whole blood. Nidoviruses were detected in 27.4% of the pythons and 2.4% of the boas tested. They were most commonly detected in ball pythons (Python [P.] regius) and Indian rock pythons (P. molurus), but were also detected for the first time in other python species, including Morelia spp. and Boa constrictor. Oral swabs were most commonly tested positive. The PCR described here can be used for the detection of nidoviruses in oral swabs from live snakes. These viruses appear to be relatively common among snakes in captivity in Europe and screening for these viruses should be considered in the clinical work-up. Nidoviruses are believed to be an important cause of respiratory disease in pythons, but can also infect boas. Detection of these viruses in live animals is now possible and can be of interest both in diseased animals as well as in quarantine situations.

  3. 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.

  4. 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

  5. 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.

  6. 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.

  7. 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. © 2011 The Authors. Australian Veterinary Journal © 2011 Australian Veterinary Association.

  8. 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.

  9. qtcm 0.1.2: A Python Implementation of the Neelin-Zeng Quasi-Equilibrium Tropical Circulation model

    NASA Astrophysics Data System (ADS)

    Lin, J. W.-B.

    2008-10-01

    Historically, climate models have been developed incrementally and in compiled languages like Fortran. While the use of legacy compiled languages results in fast, time-tested code, the resulting model is limited in its modularity and cannot take advantage of functionality available with modern computer languages. Here we describe an effort at using the open-source, object-oriented language Python to create more flexible climate models: the package qtcm, a Python implementation of the intermediate-level Neelin-Zeng Quasi-Equilibrium Tropical Circulation model (QTCM1) of the atmosphere. The qtcm package retains the core numerics of QTCM1, written in Fortran to optimize model performance, but uses Python structures and utilities to wrap the QTCM1 Fortran routines and manage model execution. The resulting "mixed language" modeling package allows order and choice of subroutine execution to be altered at run time, and model analysis and visualization to be integrated in interactively with model execution at run time. This flexibility facilitates more complex scientific analysis using less complex code than would be possible using traditional languages alone, and provides tools to transform the traditional "formulate hypothesis → write and test code → run model → analyze results" sequence into a feedback loop that can be executed automatically by the computer.

  10. qtcm 0.1.2: a Python implementation of the Neelin-Zeng Quasi-Equilibrium Tropical Circulation Model

    NASA Astrophysics Data System (ADS)

    Lin, J. W.-B.

    2009-02-01

    Historically, climate models have been developed incrementally and in compiled languages like Fortran. While the use of legacy compiled languages results in fast, time-tested code, the resulting model is limited in its modularity and cannot take advantage of functionality available with modern computer languages. Here we describe an effort at using the open-source, object-oriented language Python to create more flexible climate models: the package qtcm, a Python implementation of the intermediate-level Neelin-Zeng Quasi-Equilibrium Tropical Circulation model (QTCM1) of the atmosphere. The qtcm package retains the core numerics of QTCM1, written in Fortran to optimize model performance, but uses Python structures and utilities to wrap the QTCM1 Fortran routines and manage model execution. The resulting "mixed language" modeling package allows order and choice of subroutine execution to be altered at run time, and model analysis and visualization to be integrated in interactively with model execution at run time. This flexibility facilitates more complex scientific analysis using less complex code than would be possible using traditional languages alone, and provides tools to transform the traditional "formulate hypothesis → write and test code → run model → analyze results" sequence into a feedback loop that can be executed automatically by the computer.

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

    NASA Astrophysics Data System (ADS)

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

    2013-04-01

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

  12. pytc: Open-Source Python Software for Global Analyses of Isothermal Titration Calorimetry Data.

    PubMed

    Duvvuri, Hiranmayi; Wheeler, Lucas C; Harms, Michael J

    2018-05-08

    Here we describe pytc, an open-source Python package for global fits of thermodynamic models to multiple isothermal titration calorimetry experiments. Key features include simplicity, the ability to implement new thermodynamic models, a robust maximum likelihood fitter, a fast Bayesian Markov-Chain Monte Carlo sampler, rigorous implementation, extensive documentation, and full cross-platform compatibility. pytc fitting can be done using an application program interface or via a graphical user interface. It is available for download at https://github.com/harmslab/pytc .

  13. pyNBS: A Python implementation for network-based stratification of tumor mutations.

    PubMed

    Huang, Justin K; Jia, Tongqiu; Carlin, Daniel E; Ideker, Trey

    2018-03-28

    We present pyNBS: a modularized Python 2.7 implementation of the network-based stratification (NBS) algorithm for stratifying tumor somatic mutation profiles into molecularly and clinically relevant subtypes. In addition to release of the software, we benchmark its key parameters and provide a compact cancer reference network that increases the significance of tumor stratification using the NBS algorithm. The structure of the code exposes key steps of the algorithm to foster further collaborative development. The package, along with examples and data, can be downloaded and installed from the URL http://www.github.com/huangger/pyNBS/. jkh013@ucsd.edu.

  14. 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.

  15. HTSeq--a Python framework to work with high-throughput sequencing data.

    PubMed

    Anders, Simon; Pyl, Paul Theodor; Huber, Wolfgang

    2015-01-15

    A large choice of tools exists for many standard tasks in the analysis of high-throughput sequencing (HTS) data. However, once a project deviates from standard workflows, custom scripts are needed. We present HTSeq, a Python library to facilitate the rapid development of such scripts. HTSeq offers parsers for many common data formats in HTS projects, as well as classes to represent data, such as genomic coordinates, sequences, sequencing reads, alignments, gene model information and variant calls, and provides data structures that allow for querying via genomic coordinates. We also present htseq-count, a tool developed with HTSeq that preprocesses RNA-Seq data for differential expression analysis by counting the overlap of reads with genes. HTSeq is released as an open-source software under the GNU General Public Licence and available from http://www-huber.embl.de/HTSeq or from the Python Package Index at https://pypi.python.org/pypi/HTSeq. © The Author 2014. Published by Oxford University Press.

  16. 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

  17. 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.

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

    PubMed

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

    2009-03-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2014-11-01

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

  20. Accelerating wave propagation modeling in the frequency domain using Python

    NASA Astrophysics Data System (ADS)

    Jo, Sang Hoon; Park, Min Jun; Ha, Wan Soo

    2017-04-01

    Python is a dynamic programming language adopted in many science and engineering areas. We used Python to simulate wave propagation in the frequency domain. We used the Pardiso matrix solver to solve the impedance matrix of the wave equation. Numerical examples shows that Python with numpy consumes longer time to construct the impedance matrix using the finite element method when compared with Fortran; however we could reduce the time significantly to be comparable to that of Fortran using a simple Numba decorator.

  1. PyMidas: Interface from Python to Midas

    NASA Astrophysics Data System (ADS)

    Maisala, Sami; Oittinen, Tero

    2014-01-01

    PyMidas is an interface between Python and MIDAS, the major ESO legacy general purpose data processing system. PyMidas allows a user to exploit both the rich legacy of MIDAS software and the power of Python scripting in a unified interactive environment. PyMidas also allows the usage of other Python-based astronomical analysis systems such as PyRAF.

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

    PubMed

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

    2015-01-01

    Subspectacular nematodiasis was diagnosed in three captive-bred juvenile ball pythons (Python regius) from two unrelated facilities within a 6-month period. The snakes were presented with similar lesions, including swelling of facial, periocular and oral tissues. Bilaterally, the subspectacular spaces were distended and filled with an opaque fluid, which contained nematodes and eggs. Histopathology showed nematodes throughout the periocular tissue, subspectacular space and subcutaneous tissue of the head. The nematodes from both facilities were morphologically indistinguishable and most closely resembled Serpentirhabdias species. Morphological characterization and genetic sequencing indicate this is a previously undescribed rhabdiasid nematode. Copyright © 2014 Elsevier Ltd. All rights reserved.

  3. A fast and efficient python library for interfacing with the Biological Magnetic Resonance Data Bank.

    PubMed

    Smelter, Andrey; Astra, Morgan; Moseley, Hunter N B

    2017-03-17

    The Biological Magnetic Resonance Data Bank (BMRB) is a public repository of Nuclear Magnetic Resonance (NMR) spectroscopic data of biological macromolecules. It is an important resource for many researchers using NMR to study structural, biophysical, and biochemical properties of biological macromolecules. It is primarily maintained and accessed in a flat file ASCII format known as NMR-STAR. While the format is human readable, the size of most BMRB entries makes computer readability and explicit representation a practical requirement for almost any rigorous systematic analysis. To aid in the use of this public resource, we have developed a package called nmrstarlib in the popular open-source programming language Python. The nmrstarlib's implementation is very efficient, both in design and execution. The library has facilities for reading and writing both NMR-STAR version 2.1 and 3.1 formatted files, parsing them into usable Python dictionary- and list-based data structures, making access and manipulation of the experimental data very natural within Python programs (i.e. "saveframe" and "loop" records represented as individual Python dictionary data structures). Another major advantage of this design is that data stored in original NMR-STAR can be easily converted into its equivalent JavaScript Object Notation (JSON) format, a lightweight data interchange format, facilitating data access and manipulation using Python and any other programming language that implements a JSON parser/generator (i.e., all popular programming languages). We have also developed tools to visualize assigned chemical shift values and to convert between NMR-STAR and JSONized NMR-STAR formatted files. Full API Reference Documentation, User Guide and Tutorial with code examples are also available. We have tested this new library on all current BMRB entries: 100% of all entries are parsed without any errors for both NMR-STAR version 2.1 and version 3.1 formatted files. We also compared our

  4. MCPB.py: A Python Based Metal Center Parameter Builder.

    PubMed

    Li, Pengfei; Merz, Kenneth M

    2016-04-25

    MCPB.py, a python based metal center parameter builder, has been developed to build force fields for the simulation of metal complexes employing the bonded model approach. It has an optimized code structure, with far fewer required steps than the previous developed MCPB program. It supports various AMBER force fields and more than 80 metal ions. A series of parametrization schemes to derive force constants and charge parameters are available within the program. We give two examples (one metalloprotein example and one organometallic compound example), indicating the program's ability to build reliable force fields for different metal ion containing complexes. The original version was released with AmberTools15. It is provided via the GNU General Public License v3.0 (GNU_GPL_v3) agreement and is free to download and distribute. MCPB.py provides a bridge between quantum mechanical calculations and molecular dynamics simulation software packages thereby enabling the modeling of metal ion centers. It offers an entry into simulating metal ions in a number of situations by providing an efficient way for researchers to handle the vagaries and difficulties associated with metal ion modeling.

  5. photPARTY: Python Automated Square-Aperture Photometry

    NASA Astrophysics Data System (ADS)

    Symons, Teresa A.

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

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

    PubMed

    Helfenstein, Andreas; Tammela, Päivi

    2015-02-01

    High-throughput screening is an established technique in drug discovery and, as such, has also found its way into academia. High-throughput screening generates a considerable amount of data, which is why specific software is used for its analysis and management. The commercially available software packages are often beyond the financial limits of small-scale academic laboratories and, furthermore, lack the flexibility to fulfill certain user-specific requirements. We have developed a Python module, screening_mgmt, which is a lightweight tool for flexible data retrieval, analysis, and storage for different screening assays in one central database. The module reads custom-made analysis scripts and plotting instructions, and it offers a graphical user interface to import, modify, and display the data in a uniform manner. During the test phase, we used this module for the management of 10,000 data points of various origins. It has provided a practical, user-friendly tool for sharing and exchanging information between researchers. © 2014 Society for Laboratory Automation and Screening.

  7. 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.

  8. ObsPy: A Python Toolbox for Seismology

    NASA Astrophysics Data System (ADS)

    Krischer, Lion; Megies, Tobias; Sales de Andrade, Elliott; Barsch, Robert; MacCarthy, Jonathan

    2017-04-01

    In recent years the Python ecosystem evolved into one of the most powerful and productive scientific environments across disciplines. ObsPy (https://www.obspy.org) is a fully community-driven, open-source project dedicated to providing a bridge for seismology into that ecosystem. It does so by offering Read and write support for essentially every commonly used data format in seismology with a unified interface and automatic format detection. This includes waveform data (MiniSEED, SAC, SEG-Y, Reftek, …) as well as station (SEED, StationXML, …) and event meta information (QuakeML, ZMAP, …). Integrated access to the largest data centers, web services, and real-time data streams (FDSNWS, ArcLink, SeedLink, ...). A powerful signal processing toolbox tuned to the specific needs of seismologists. Utility functionality like travel time calculations with the TauP method, geodetic functions, and data visualizations. ObsPy has been in constant development for more than seven years and is developed and used by scientists around the world with successful applications in all branches of seismology. Additionally it nowadays serves as the foundation for a large number of more specialized packages. This presentation will give a short overview of the capabilities of ObsPy and point out several representative or new use cases. Additionally we will discuss the road ahead as well as the long-term sustainability of open-source scientific software.

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

    SciTech Connect

    Gezahegne, A; Love, N S

    2007-12-10

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

  10. Re-imagining a Stata/Python Combination

    NASA Technical Reports Server (NTRS)

    Fiedler, James

    2013-01-01

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

  11. Scoring Package

    National Institute of Standards and Technology Data Gateway

    NIST Scoring Package (PC database for purchase)   The NIST Scoring Package (Special Database 1) is a reference implementation of the draft Standard Method for Evaluating the Performance of Systems Intended to Recognize Hand-printed Characters from Image Data Scanned from Forms.

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

    PubMed

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

    2009-08-01

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

  13. Ball python nidovirus: a candidate etiologic agent for severe respiratory disease in Python regius.

    PubMed

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

    2014-09-09

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

  14. GfaPy: a flexible and extensible software library for handling sequence graphs in Python.

    PubMed

    Gonnella, Giorgio; Kurtz, Stefan

    2017-10-01

    GFA 1 and GFA 2 are recently defined formats for representing sequence graphs, such as assembly, variation or splicing graphs. The formats are adopted by several software tools. Here, we present GfaPy, a software package for creating, parsing and editing GFA graphs using the programming language Python. GfaPy supports GFA 1 and GFA 2, using the same interface and allows for interconversion between both formats. The software package provides a simple interface for custom record types, which is an important new feature of GFA 2 (compared to GFA 1). This enables new applications of the format. GfaPy is available open source at https://github.com/ggonnella/gfapy and installable via pip. gonnella@zbh.uni-hamburg.de. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  15. Python-based dynamic scheduling assistant for atmospheric measurements by Bruker instruments using OPUS.

    PubMed

    Geddes, Alexander; Robinson, John; Smale, Dan

    2018-02-01

    Atmospheric remote sensing by instruments such as spectrometers and interferometers often requires scheduling that is dependent on external factors, for example; time and solar (or lunar) zenith angle. Such instruments manufactured by Bruker often use the software package OPUS, which, while useful, is not flexible enough for automatic, repeated, atmospheric measurements of this nature. In this brief paper, we describe ASAP, a Python tool developed to run our network of Fourier transform interferometers in New Zealand and Antarctica. It allows the automated scheduling of measurements by time, lunar, or solar zenith angle while accounting for weather or other external parameters. There is a wide range of useful functions, all packaged in a simple graphical user interface; it is available on request.

  16. 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.

  17. scikit-image: image processing in Python.

    PubMed

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

    2014-01-01

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

  18. TRIPPy: Python-based Trailed Source Photometry

    NASA Astrophysics Data System (ADS)

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

    2016-05-01

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

  19. 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

  20. The Programming Language Python In Earth System Simulations

    NASA Astrophysics Data System (ADS)

    Gross, L.; Imranullah, A.; Mora, P.; Saez, E.; Smillie, J.; Wang, C.

    2004-12-01

    Mathematical models in earth sciences base on the solution of systems of coupled, non-linear, time-dependent partial differential equations (PDEs). The spatial and time-scale vary from a planetary scale and million years for convection problems to 100km and 10 years for fault systems simulations. Various techniques are in use to deal with the time dependency (e.g. Crank-Nicholson), with the non-linearity (e.g. Newton-Raphson) and weakly coupled equations (e.g. non-linear Gauss-Seidel). Besides these high-level solution algorithms discretization methods (e.g. finite element method (FEM), boundary element method (BEM)) are used to deal with spatial derivatives. Typically, large-scale, three dimensional meshes are required to resolve geometrical complexity (e.g. in the case of fault systems) or features in the solution (e.g. in mantel convection simulations). The modelling environment escript allows the rapid implementation of new physics as required for the development of simulation codes in earth sciences. Its main object is to provide a programming language, where the user can define new models and rapidly develop high-level solution algorithms. The current implementation is linked with the finite element package finley as a PDE solver. However, the design is open and other discretization technologies such as finite differences and boundary element methods could be included. escript is implemented as an extension of the interactive programming environment python (see www.python.org). Key concepts introduced are Data objects, which are holding values on nodes or elements of the finite element mesh, and linearPDE objects, which are defining linear partial differential equations to be solved by the underlying discretization technology. In this paper we will show the basic concepts of escript and will show how escript is used to implement a simulation code for interacting fault systems. We will show some results of large-scale, parallel simulations on an SGI Altix

  1. ObsPy - A Python Toolbox for Seismology - and Applications

    NASA Astrophysics Data System (ADS)

    Krischer, L.; Megies, T.; Barsch, R.; MacCarthy, J.; Lecocq, T.; Koymans, M. R.; Carothers, L.; Eulenfeld, T.; Reyes, C. G.; Falco, N.; Sales de Andrade, E.

    2017-12-01

    Recent years witnessed the evolution of Python's ecosystem into one of the most powerful and productive scientific environments across disciplines. ObsPy (https://www.obspy.org) is a fully community driven, open-source project dedicated to provide a bridge for seismology into that ecosystem. It is a Python toolbox offering: Read and write support for essentially every commonly used data format in seismology with a unified interface and automatic format detection. This includes waveform data (MiniSEED, SAC, SEG-Y, Reftek, …) as well as station (SEED, StationXML, SC3ML, …) and event meta information (QuakeML, ZMAP, …). Integrated access to the largest data centers, web services, and real-time data streams (FDSNWS, ArcLink, SeedLink, ...). A powerful signal processing toolbox tuned to the specific needs of seismologists. Utility functionality like travel time calculations with the TauP method, geodetic functions, and data visualizations. ObsPy has been in constant development for more than eight years and is developed and used by scientists around the world with successful applications in all branches of seismology. Additionally it nowadays serves as the foundation for a large number of more specialized packages. Newest features include: Full interoperability of SEED and StationXML/Inventory objects Access to the Nominal Response Library (NRL) for easy and quick creation of station metadata from scratch Support for the IRIS Federated Catalog Service Improved performance of the EarthWorm client Several improvements to MiniSEED read/write module Improved plotting capabilities for PPSD (spectrograms, PSD of discrete frequencies over time, ..) Support for.. Reading ArcLink Inventory XML Reading Reftek data format Writing SeisComp3 ML (SC3ML) Writing StationTXT format This presentation will give a short overview of the capabilities of ObsPy and point out several representative or new use cases and show-case some projects that are based on ObsPy, e.g.: seismo

  2. Data processing with Pymicra, the Python tool for Micrometeorological Analyses

    NASA Astrophysics Data System (ADS)

    Chor, T. L.; Dias, N. L.

    2017-12-01

    With the ever-increasing capability of instrumentation of collecting high-frequency turbulence data, micrometeorological experiments are now generating significant amounts of data. Clearly, data processing -- and not data collection anymore -- has become the limiting factor for those very large data sets. The ability of extracting useful scientific information from those experiments, therefore, hinges on tools that (i) are able to process those data effectively and accurately, (ii) are flexible enough to be adapted to the specific requirements of each investigation, and (iii) are robust enough to make data analysis easily reproducible over different sets of large data sets. We have developed a framework for micrometeorological data analysis called Pymicra which does deliver such capabilities while maintaining proximity of the investigator with the data. It is fully written in an open-source, very high level language, Python, which has been gaining widespread acceptance as a scientific tool. It follows the philosophy of "not reinventing the wheel" and, as a result, relies on existing well-established open-source Python packages such as Numpy and Pandas. Thus, minimum effort is needed to program statistics, array processing, Fourier analysis, etc. Among the things that Pymicra does are reading and organizing data from virtually any format, applying common quality control procedures, extracting fluctuations in a number of ways, correcting for sensor drift, automatic calculation of fluid properties (such as air and dry air density), handling of units, calculation of cross-spectra, calculation of turbulent fluxes and scales, and all other features already provided by Pandas (interpolation, statistical tests, handling of missing data, etc.). Pymicra is freely available on Github and the fact that it makes heavy use of high-level programming makes adding and modifying code considerably easy for any scientific programmer, making it straightforward for other scientists to

  3. SpiceyPy, a Python Wrapper for SPICE

    NASA Astrophysics Data System (ADS)

    Annex, A.

    2017-06-01

    SpiceyPy is an open source Python wrapper for the NAIF SPICE toolkit. It is available for macOS, Linux, and Windows platforms and for Python versions 2.7.x and 3.x as well as Anaconda. SpiceyPy can be installed by running: “pip install spiceypy.”

  4. Brainlab: A Python Toolkit to Aid in the Design, Simulation, and Analysis of Spiking Neural Networks with the NeoCortical Simulator.

    PubMed

    Drewes, Rich; Zou, Quan; Goodman, Philip H

    2009-01-01

    Neuroscience modeling experiments often involve multiple complex neural network and cell model variants, complex input stimuli and input protocols, followed by complex data analysis. Coordinating all this complexity becomes a central difficulty for the experimenter. The Python programming language, along with its extensive library packages, has emerged as a leading "glue" tool for managing all sorts of complex programmatic tasks. This paper describes a toolkit called Brainlab, written in Python, that leverages Python's strengths for the task of managing the general complexity of neuroscience modeling experiments. Brainlab was also designed to overcome the major difficulties of working with the NCS (NeoCortical Simulator) environment in particular. Brainlab is an integrated model-building, experimentation, and data analysis environment for the powerful parallel spiking neural network simulator system NCS.

  5. Brainlab: A Python Toolkit to Aid in the Design, Simulation, and Analysis of Spiking Neural Networks with the NeoCortical Simulator

    PubMed Central

    Drewes, Rich; Zou, Quan; Goodman, Philip H.

    2008-01-01

    Neuroscience modeling experiments often involve multiple complex neural network and cell model variants, complex input stimuli and input protocols, followed by complex data analysis. Coordinating all this complexity becomes a central difficulty for the experimenter. The Python programming language, along with its extensive library packages, has emerged as a leading “glue” tool for managing all sorts of complex programmatic tasks. This paper describes a toolkit called Brainlab, written in Python, that leverages Python's strengths for the task of managing the general complexity of neuroscience modeling experiments. Brainlab was also designed to overcome the major difficulties of working with the NCS (NeoCortical Simulator) environment in particular. Brainlab is an integrated model-building, experimentation, and data analysis environment for the powerful parallel spiking neural network simulator system NCS. PMID:19506707

  6. 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. Copyright © 2009 The Author(s). Journal Compilation © 2009 National Ground Water Association.

  7. 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.

  8. A modern Python interface for the Generic Mapping Tools

    NASA Astrophysics Data System (ADS)

    Uieda, L.; Wessel, P.

    2017-12-01

    Figures generated by The Generic Mapping Tools (GMT) are present in countless publications across the Earth sciences. The command-line interface of GMT lends the tool its flexibility but also creates a barrier to entry for begginers. Meanwhile, adoption of the Python programming language has grown across the scientific community. This growth is largely due to the simplicity and low barrier to entry of the language and its ecosystem of tools. Thus, it is not surprising that there have been at least three attempts to create Python interfaces for GMT: gmtpy (github.com/emolch/gmtpy), pygmt (github.com/ian-r-rose/pygmt), and PyGMT (github.com/glimmer-cism/PyGMT). None of these projects are currently active and, with the exception of pygmt, they do not use the GMT Application Programming Interface (API) introduced in GMT 5. The two main Python libraries for plotting data on maps are the matplotlib Basemap toolkit (matplotlib.org/basemap) and Cartopy (scitools.org.uk/cartopy), both of which rely on matplotlib (matplotlib.org) as the backend for generating the figures. Basemap is known to have limitations and is being discontinued. Cartopy is an improvement over Basemap but is still bound by the speed and memory constraints of matplotlib. We present a new Python interface for GMT (GMT/Python) that makes use of the GMT API and of new features being developed for the upcoming GMT 6 release. The GMT/Python library is designed according to the norms and styles of the Python community. The library integrates with the scientific Python ecosystem by using the "virtual files" from the GMT API to implement input and output of Python data types (numpy "ndarray" for tabular data and xarray "Dataset" for grids). Other features include an object-oriented interface for creating figures, the ability to display figures in the Jupyter notebook, and descriptive aliases for GMT arguments (e.g., "region" instead of "R" and "projection" instead of "J"). GMT/Python can also serve as a backend

  9. 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.

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

    PubMed

    Meyer, W; Luz, S; Schnapper, A

    2009-08-01

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

  11. Python in the NERSC Exascale Science Applications Program for Data

    SciTech Connect

    Ronaghi, Zahra; Thomas, Rollin; Deslippe, Jack

    We describe a new effort at the National Energy Re- search Scientific Computing Center (NERSC) in performance analysis and optimization of scientific Python applications targeting the Intel Xeon Phi (Knights Landing, KNL) many- core architecture. The Python-centered work outlined here is part of a larger effort called the NERSC Exascale Science Applications Program (NESAP) for Data. NESAP for Data focuses on applications that process and analyze high-volume, high-velocity data sets from experimental/observational science (EOS) facilities supported by the US Department of Energy Office of Science. We present three case study applications from NESAP for Data that use Python. These codesmore » vary in terms of “Python purity” from applications developed in pure Python to ones that use Python mainly as a convenience layer for scientists without expertise in lower level programming lan- guages like C, C++ or Fortran. The science case, requirements, constraints, algorithms, and initial performance optimizations for each code are discussed. Our goal with this paper is to contribute to the larger conversation around the role of Python in high-performance computing today and tomorrow, highlighting areas for future work and emerging best practices« less

  12. 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 (31.5 °C) and a sub-optimal temperature (25.5 °C)-in six species of pythons, including members of two major phylogenetic branches currently devoid of data on the subject. We found no evidence of facultative thermogenesis in five species: Aspidites melanocephalus, A. ramsayi, Morelia viridis, M. spilota cheynei, and Python regius. However, we found that Bothrochilus boa had a thermal metabolic sensitivity indicative of facultative thermogenesis (i.e., a higher metabolic rate at the lower temperature). However, its metabolic rate was quite low and technical challenges prevented us from measuring temperature differential to make conclusions about facultative endothermy in this species. Regardless, our data combined with existing literature demonstrate that facultative thermogenesis is not as widespread among pythons as previously thought.

  13. 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

  14. Responses of python gastrointestinal regulatory peptides to feeding

    PubMed Central

    Secor, Stephen M.; Fehsenfeld, Drew; Diamond, Jared; Adrian, Thomas E.

    2001-01-01

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

  15. Advanced functional network analysis in the geosciences: The pyunicorn package

    NASA Astrophysics Data System (ADS)

    Donges, Jonathan F.; Heitzig, Jobst; Runge, Jakob; Schultz, Hanna C. H.; Wiedermann, Marc; Zech, Alraune; Feldhoff, Jan; Rheinwalt, Aljoscha; Kutza, Hannes; Radebach, Alexander; Marwan, Norbert; Kurths, Jürgen

    2013-04-01

    Functional networks are a powerful tool for analyzing large geoscientific datasets such as global fields of climate time series originating from observations or model simulations. pyunicorn (pythonic unified complex network and recurrence analysis toolbox) is an open-source, fully object-oriented and easily parallelizable package written in the language Python. It allows for constructing functional networks (aka climate networks) representing the structure of statistical interrelationships in large datasets and, subsequently, investigating this structure using advanced methods of complex network theory such as measures for networks of interacting networks, node-weighted statistics or network surrogates. Additionally, pyunicorn allows to study the complex dynamics of geoscientific systems as recorded by time series by means of recurrence networks and visibility graphs. The range of possible applications of the package is outlined drawing on several examples from climatology.

  16. 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. © 2014. Published by The Company of Biologists Ltd.

  17. Effect of laser treatment on first-intention incisional wound healing in ball pythons (Python regius).

    PubMed

    Cole, Grayson L; Lux, Cassie N; Schumacher, Juergen P; Seibert, Rachel L; Sadler, Ryan A; Henderson, Andrea L; Odoi, Agricola; Newkirk, Kim M

    2015-10-01

    To evaluate effects of laser treatment on incisional wound healing in ball pythons (Python regius). 6 healthy adult ball pythons. Snakes were sedated, a skin biopsy specimen was collected for histologic examination, and eight 2-cm skin incisions were made in each snake; each incision was closed with staples (day 0). Gross evaluation of all incision sites was performed daily for 30 days, and a wound score was assigned. Four incisions of each snake were treated (5 J/cm(2) and a wavelength of 980 nm on a continuous wave sequence) by use of a class 4 laser once daily for 7 consecutive days; the other 4 incisions were not treated. Two excisional skin biopsy specimens (1 control and 1 treatment) were collected from each snake on days 2, 7, 14, and 30 and evaluated microscopically. Scores were assigned for total inflammation, degree of fibrosis, and collagen maturity. Generalized linear models were used to investigate the effect of treatment on each variable. Wound scores for laser-treated incisions were significantly better than scores for control incisions on day 2 but not at other time points. There were no significant differences in necrosis, fibroplasia, inflammation, granuloma formation, or bacterial contamination between control and treatment groups. Collagen maturity was significantly better for the laser-treated incisions on day 14. Laser treatment resulted in a significant increase in collagen maturity at day 14 but did not otherwise significantly improve healing of skin incisions.

  18. COSMOS: Python library for massively parallel workflows.

    PubMed

    Gafni, Erik; Luquette, Lovelace J; Lancaster, Alex K; Hawkins, Jared B; Jung, Jae-Yoon; Souilmi, Yassine; Wall, Dennis P; Tonellato, Peter J

    2014-10-15

    Efficient workflows to shepherd clinically generated genomic data through the multiple stages of a next-generation sequencing pipeline are of critical importance in translational biomedical science. Here we present COSMOS, a Python library for workflow management that allows formal description of pipelines and partitioning of jobs. In addition, it includes a user interface for tracking the progress of jobs, abstraction of the queuing system and fine-grained control over the workflow. Workflows can be created on traditional computing clusters as well as cloud-based services. Source code is available for academic non-commercial research purposes. Links to code and documentation are provided at http://lpm.hms.harvard.edu and http://wall-lab.stanford.edu. dpwall@stanford.edu or peter_tonellato@hms.harvard.edu. Supplementary data are available at Bioinformatics online. © The Author 2014. Published by Oxford University Press.

  19. COSMOS: Python library for massively parallel workflows

    PubMed Central

    Gafni, Erik; Luquette, Lovelace J.; Lancaster, Alex K.; Hawkins, Jared B.; Jung, Jae-Yoon; Souilmi, Yassine; Wall, Dennis P.; Tonellato, Peter J.

    2014-01-01

    Summary: Efficient workflows to shepherd clinically generated genomic data through the multiple stages of a next-generation sequencing pipeline are of critical importance in translational biomedical science. Here we present COSMOS, a Python library for workflow management that allows formal description of pipelines and partitioning of jobs. In addition, it includes a user interface for tracking the progress of jobs, abstraction of the queuing system and fine-grained control over the workflow. Workflows can be created on traditional computing clusters as well as cloud-based services. Availability and implementation: Source code is available for academic non-commercial research purposes. Links to code and documentation are provided at http://lpm.hms.harvard.edu and http://wall-lab.stanford.edu. Contact: dpwall@stanford.edu or peter_tonellato@hms.harvard.edu. Supplementary information: Supplementary data are available at Bioinformatics online. PMID:24982428

  20. FRED 2: an immunoinformatics framework for Python

    PubMed Central

    Schubert, Benjamin; Walzer, Mathias; Brachvogel, Hans-Philipp; Szolek, András; Mohr, Christopher; Kohlbacher, Oliver

    2016-01-01

    Summary: Immunoinformatics approaches are widely used in a variety of applications from basic immunological to applied biomedical research. Complex data integration is inevitable in immunological research and usually requires comprehensive pipelines including multiple tools and data sources. Non-standard input and output formats of immunoinformatics tools make the development of such applications difficult. Here we present FRED 2, an open-source immunoinformatics framework offering easy and unified access to methods for epitope prediction and other immunoinformatics applications. FRED 2 is implemented in Python and designed to be extendable and flexible to allow rapid prototyping of complex applications. Availability and implementation: FRED 2 is available at http://fred-2.github.io Contact: schubert@informatik.uni-tuebingen.de Supplementary information: Supplementary data are available at Bioinformatics online. PMID:27153717

  1. A Python Calculator for Supernova Remnant Evolution

    NASA Astrophysics Data System (ADS)

    Leahy, D. A.; Williams, J. E.

    2017-05-01

    A freely available Python code for modeling supernova remnant (SNR) evolution has been created. This software is intended for two purposes: to understand SNR evolution and to use in modeling observations of SNR for obtaining good estimates of SNR properties. It includes all phases for the standard path of evolution for spherically symmetric SNRs. In addition, alternate evolutionary models are available, including evolution in a cloudy ISM, the fractional energy-loss model, and evolution in a hot low-density ISM. The graphical interface takes in various parameters and produces outputs such as shock radius and velocity versus time, as well as SNR surface brightness profile and spectrum. Some interesting properties of SNR evolution are demonstrated using the program.

  2. FRED 2: an immunoinformatics framework for Python.

    PubMed

    Schubert, Benjamin; Walzer, Mathias; Brachvogel, Hans-Philipp; Szolek, András; Mohr, Christopher; Kohlbacher, Oliver

    2016-07-01

    Immunoinformatics approaches are widely used in a variety of applications from basic immunological to applied biomedical research. Complex data integration is inevitable in immunological research and usually requires comprehensive pipelines including multiple tools and data sources. Non-standard input and output formats of immunoinformatics tools make the development of such applications difficult. Here we present FRED 2, an open-source immunoinformatics framework offering easy and unified access to methods for epitope prediction and other immunoinformatics applications. FRED 2 is implemented in Python and designed to be extendable and flexible to allow rapid prototyping of complex applications. FRED 2 is available at http://fred-2.github.io schubert@informatik.uni-tuebingen.de Supplementary data are available at Bioinformatics online. © The Author 2016. Published by Oxford University Press.

  3. PyEphem: Astronomical Ephemeris for Python

    NASA Astrophysics Data System (ADS)

    Rhodes, Brandon Craig

    2011-12-01

    PyEphem provides scientific-grade astronomical computations for the Python programming language. Given a date and location on the Earth’s surface, it can compute the positions of the Sun and Moon, of the planets and their moons, and of any asteroids, comets, or earth satellites whose orbital elements the user can provide. Additional functions are provided to compute the angular separation between two objects in the sky, to determine the constellation in which an object lies, and to find the times at which an object rises, transits, and sets on a particular day. The numerical routines that lie behind PyEphem are those from the wonderful XEphem astronomy application, whose author, Elwood Downey, generously gave permission for us to use them as the basis for PyEphem.

  4. 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.

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

    NASA Astrophysics Data System (ADS)

    Dias, B.; Milli, J.

    2017-03-01

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

  6. Prevalence Incidence Mixture Models

    Cancer.gov

    The R package and webtool fits Prevalence Incidence Mixture models to left-censored and irregularly interval-censored time to event data that is commonly found in screening cohorts assembled from electronic health records. Absolute and relative risk can be estimated for simple random sampling, and stratified sampling (the two approaches of superpopulation and a finite population are supported for target populations). Non-parametric (absolute risks only), semi-parametric, weakly-parametric (using B-splines), and some fully parametric (such as the logistic-Weibull) models are supported.

  7. ObsPy: A Python toolbox for seismology - Sustainability, New Features, and Applications

    NASA Astrophysics Data System (ADS)

    Krischer, L.; Megies, T.; Sales de Andrade, E.; Barsch, R.; MacCarthy, J.

    2016-12-01

    ObsPy (https://www.obspy.org) is a community-driven, open-source project dedicated to offer a bridge for seismology into the scientific Python ecosystem. Amongst other things, it provides Read and write support for essentially every commonly used data format in seismology with a unified interface. This includes waveform data as well as station and event meta information. A signal processing toolbox tuned to the specific needs of seismologists. Integrated access to the largest data centers, web services, and databases. Wrappers around third party codes like libmseed and evalresp. Using ObsPy enables users to take advantage of the vast scientific ecosystem that has developed around Python. In contrast to many other programming languages and tools, Python is simple enough to enable an exploratory and interactive coding style desired by many scientists. At the same time it is a full-fledged programming language usable by software engineers to build complex and large programs. This combination makes it very suitable for use in seismology where research code often must be translated to stable and production ready environments, especially in the age of big data. ObsPy has seen constant development for more than six years and enjoys a large rate of adoption in the seismological community with thousands of users. Successful applications include time-dependent and rotational seismology, big data processing, event relocations, and synthetic studies about attenuation kernels and full-waveform inversions to name a few examples. Additionally it sparked the development of several more specialized packages slowly building a modern seismological ecosystem around it. We will present a short overview of the capabilities of ObsPy and point out several representative use cases and more specialized software built around ObsPy. Additionally we will discuss new and upcoming features, as well as the sustainability of open-source scientific software.

  8. 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.

  9. 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.

  10. Landlab: an Open-Source Python Library for Modeling Earth Surface Dynamics

    NASA Astrophysics Data System (ADS)

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

    2016-12-01

    Landlab is an open-source Python modeling library that enables users to easily build unique models to explore earth surface dynamics. The Landlab library provides a number of tools and functionalities that are common to many earth surface models, thus eliminating the need for a user to recode fundamental model elements each time she explores a new problem. For example, Landlab provides a gridding engine so that a user can build a uniform or nonuniform grid in one line of code. The library has tools for setting boundary conditions, adding data to a grid, and performing basic operations on the data, such as calculating gradients and curvature. The library also includes a number of process components, which are numerical implementations of physical processes. To create a model, a user creates a grid and couples together process components that act on grid variables. The current library has components for modeling a diverse range of processes, from overland flow generation to bedrock river incision, from soil wetting and drying to vegetation growth, succession and death. The code is freely available for download (https://github.com/landlab/landlab) or can be installed as a Python package. Landlab models can also be built and run on Hydroshare (www.hydroshare.org), an online collaborative environment for sharing hydrologic data, models, and code. Tutorials illustrating a wide range of Landlab capabilities such as building a grid, setting boundary conditions, reading in data, plotting, using components and building models are also available (https://github.com/landlab/tutorials). The code is also comprehensively documented both online and natively in Python. In this presentation, we illustrate the diverse capabilities of Landlab. We highlight existing functionality by illustrating outcomes from a range of models built with Landlab - including applications that explore landscape evolution and ecohydrology. Finally, we describe the range of resources available for new

  11. 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

  12. Nipype: A Flexible, Lightweight and Extensible Neuroimaging Data Processing Framework in Python

    PubMed Central

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

    2011-01-01

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

  13. A Python Implementation of an Intermediate-Level Tropical Circulation Model and Implications for How Modeling Science is Done

    NASA Astrophysics Data System (ADS)

    Lin, J. W. B.

    2015-12-01

    Historically, climate models have been developed incrementally and in compiled languages like Fortran. While the use of legacy compiledlanguages results in fast, time-tested code, the resulting model is limited in its modularity and cannot take advantage of functionalityavailable with modern computer languages. Here we describe an effort at using the open-source, object-oriented language Pythonto create more flexible climate models: the package qtcm, a Python implementation of the intermediate-level Neelin-Zeng Quasi-Equilibrium Tropical Circulation model (QTCM1) of the atmosphere. The qtcm package retains the core numerics of QTCM1, written in Fortran, to optimize model performance but uses Python structures and utilities to wrap the QTCM1 Fortran routines and manage model execution. The resulting "mixed language" modeling package allows order and choice of subroutine execution to be altered at run time, and model analysis and visualization to be integrated in interactively with model execution at run time. This flexibility facilitates more complex scientific analysis using less complex code than would be possible using traditional languages alone and provides tools to transform the traditional "formulate hypothesis → write and test code → run model → analyze results" sequence into a feedback loop that can be executed automatically by the computer.

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

    PubMed

    Diamond, Steven; Boyd, Stephen

    2016-04-01

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

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

    PubMed Central

    Diamond, Steven; Boyd, Stephen

    2016-01-01

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

  16. Packaged Food

    NASA Technical Reports Server (NTRS)

    1976-01-01

    After studies found that many elderly persons don't eat adequately because they can't afford to, they have limited mobility, or they just don't bother, Innovated Foods, Inc. and JSC developed shelf-stable foods processed and packaged for home preparation with minimum effort. Various food-processing techniques and delivery systems are under study and freeze dried foods originally used for space flight are being marketed. (See 77N76140)

  17. Seafood Packaging

    NASA Technical Reports Server (NTRS)

    1996-01-01

    NASA's Technology Transfer Office at Stennis Space Center worked with a New Orleans seafood packaging company to develop a container to improve the shipping longevity of seafood, primarily frozen and fresh fish, while preserving the taste. A NASA engineer developed metalized heat resistant polybags with thermal foam liners using an enhanced version of the metalized mylar commonly known as 'space blanket material,' which was produced during the Apollo era.

  18. 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. © 2012 Wiley Publishing Asia Pty Ltd, ISZS and IOZ/CAS.

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

    PubMed Central

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

    2004-01-01

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

  20. 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.

  1. Neuroimaging, Genetics, and Clinical Data Sharing in Python Using the CubicWeb Framework

    PubMed Central

    Grigis, Antoine; Goyard, David; Cherbonnier, Robin; Gareau, Thomas; Papadopoulos Orfanos, Dimitri; Chauvat, Nicolas; Di Mascio, Adrien; Schumann, Gunter; Spooren, Will; Murphy, Declan; Frouin, Vincent

    2017-01-01

    In neurosciences or psychiatry, the emergence of large multi-center population imaging studies raises numerous technological challenges. From distributed data collection, across different institutions and countries, to final data publication service, one must handle the massive, heterogeneous, and complex data from genetics, imaging, demographics, or clinical scores. These data must be both efficiently obtained and downloadable. We present a Python solution, based on the CubicWeb open-source semantic framework, aimed at building population imaging study repositories. In addition, we focus on the tools developed around this framework to overcome the challenges associated with data sharing and collaborative requirements. We describe a set of three highly adaptive web services that transform the CubicWeb framework into a (1) multi-center upload platform, (2) collaborative quality assessment platform, and (3) publication platform endowed with massive-download capabilities. Two major European projects, IMAGEN and EU-AIMS, are currently supported by the described framework. We also present a Python package that enables end users to remotely query neuroimaging, genetics, and clinical data from scripts. PMID:28360851

  2. Efficient and Flexible Climate Analysis with Python in a Cloud-Based Distributed Computing Framework

    NASA Astrophysics Data System (ADS)

    Gannon, C.

    2017-12-01

    As climate models become progressively more advanced, and spatial resolution further improved through various downscaling projects, climate projections at a local level are increasingly insightful and valuable. However, the raw size of climate datasets presents numerous hurdles for analysts wishing to develop customized climate risk metrics or perform site-specific statistical analysis. Four Twenty Seven, a climate risk consultancy, has implemented a Python-based distributed framework to analyze large climate datasets in the cloud. With the freedom afforded by efficiently processing these datasets, we are able to customize and continually develop new climate risk metrics using the most up-to-date data. Here we outline our process for using Python packages such as XArray and Dask to evaluate netCDF files in a distributed framework, StarCluster to operate in a cluster-computing environment, cloud computing services to access publicly hosted datasets, and how this setup is particularly valuable for generating climate change indicators and performing localized statistical analysis.

  3. Neuroimaging, Genetics, and Clinical Data Sharing in Python Using the CubicWeb Framework.

    PubMed

    Grigis, Antoine; Goyard, David; Cherbonnier, Robin; Gareau, Thomas; Papadopoulos Orfanos, Dimitri; Chauvat, Nicolas; Di Mascio, Adrien; Schumann, Gunter; Spooren, Will; Murphy, Declan; Frouin, Vincent

    2017-01-01

    In neurosciences or psychiatry, the emergence of large multi-center population imaging studies raises numerous technological challenges. From distributed data collection, across different institutions and countries, to final data publication service, one must handle the massive, heterogeneous, and complex data from genetics, imaging, demographics, or clinical scores. These data must be both efficiently obtained and downloadable. We present a Python solution, based on the CubicWeb open-source semantic framework, aimed at building population imaging study repositories. In addition, we focus on the tools developed around this framework to overcome the challenges associated with data sharing and collaborative requirements. We describe a set of three highly adaptive web services that transform the CubicWeb framework into a (1) multi-center upload platform, (2) collaborative quality assessment platform, and (3) publication platform endowed with massive-download capabilities. Two major European projects, IMAGEN and EU-AIMS, are currently supported by the described framework. We also present a Python package that enables end users to remotely query neuroimaging, genetics, and clinical data from scripts.

  4. Pyviko: an automated Python tool to design gene knockouts in complex viruses with overlapping genes.

    PubMed

    Taylor, Louis J; Strebel, Klaus

    2017-01-07

    Gene knockouts are a common tool used to study gene function in various organisms. However, designing gene knockouts is complicated in viruses, which frequently contain sequences that code for multiple overlapping genes. Designing mutants that can be traced by the creation of new or elimination of existing restriction sites further compounds the difficulty in experimental design of knockouts of overlapping genes. While software is available to rapidly identify restriction sites in a given nucleotide sequence, no existing software addresses experimental design of mutations involving multiple overlapping amino acid sequences in generating gene knockouts. Pyviko performed well on a test set of over 240,000 gene pairs collected from viral genomes deposited in the National Center for Biotechnology Information Nucleotide database, identifying a point mutation which added a premature stop codon within the first 20 codons of the target gene in 93.2% of all tested gene-overprinted gene pairs. This shows that Pyviko can be used successfully in a wide variety of contexts to facilitate the molecular cloning and study of viral overprinted genes. Pyviko is an extensible and intuitive Python tool for designing knockouts of overlapping genes. Freely available as both a Python package and a web-based interface ( http://louiejtaylor.github.io/pyViKO/ ), Pyviko simplifies the experimental design of gene knockouts in complex viruses with overlapping genes.

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

    PubMed

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

    2011-07-28

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

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

    PubMed

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

    2016-05-01

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

  7. 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. Copyright © 2015 Elsevier Inc. All rights reserved.

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

    PubMed

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

    2003-04-01

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

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

    PubMed

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

    2012-08-01

    This study aims at a functional and morphological characterization of the lung of a boid snake. In particular, we were interested to see if the python's lungs are designed with excess capacity as compared to resting and working oxygen demands. Therefore, the morphological respiratory diffusion capacity of ball pythons (Python regius) was examined following a stereological, hierarchically nested approach. The volume of the respiratory exchange tissue was determined using computed tomography. Tissue compartments were quantified using stereological methods on light microscopic images. The tissue diffusion barrier for oxygen transport was characterized and measured using transmission electron micrographs. We found a significant negative correlation between body mass and the volume of respiratory tissue; the lungs of larger snakes had relatively less respiratory tissue. Therefore, mass-specific respiratory tissue was calculated to exclude effects of body mass. The volume of the lung that contains parenchyma was 11.9±5.0mm(3)g(-1). The volume fraction, i.e., the actual pulmonary exchange tissue per lung parenchyma, was 63.22±7.3%; the total respiratory surface was, on average, 0.214±0.129m(2); it was significantly negatively correlated to body mass, with larger snakes having proportionally smaller respiratory surfaces. For the air-blood barrier, a harmonic mean of 0.78±0.05μm was found, with the epithelial layer representing the thickest part of the barrier. Based on these findings, a median diffusion capacity of the tissue barrier ( [Formula: see text] ) of 0.69±0.38ml O(2)min(-1)mmHg(-1) was calculated. Based on published values for blood oxygen concentration, a total oxygen uptake capacity of 61.16mlO(2)min(-1)kg(-1) can be assumed. This value exceeds the maximum demand for oxygen in ball pythons by a factor of 12. We conclude that healthy individuals of P. regius possess a considerable spare capacity for tissue oxygen exchange. Copyright © 2012 Elsevier Gmb

  10. Enabling grand-canonical Monte Carlo: extending the flexibility of GROMACS through the GromPy python interface module.

    PubMed

    Pool, René; Heringa, Jaap; Hoefling, Martin; Schulz, Roland; Smith, Jeremy C; Feenstra, K Anton

    2012-05-05

    We report on a python interface to the GROMACS molecular simulation package, GromPy (available at https://github.com/GromPy). This application programming interface (API) uses the ctypes python module that allows function calls to shared libraries, for example, written in C. To the best of our knowledge, this is the first reported interface to the GROMACS library that uses direct library calls. GromPy can be used for extending the current GROMACS simulation and analysis modes. In this work, we demonstrate that the interface enables hybrid Monte-Carlo/molecular dynamics (MD) simulations in the grand-canonical ensemble, a simulation mode that is currently not implemented in GROMACS. For this application, the interplay between GromPy and GROMACS requires only minor modifications of the GROMACS source code, not affecting the operation, efficiency, and performance of the GROMACS applications. We validate the grand-canonical application against MD in the canonical ensemble by comparison of equations of state. The results of the grand-canonical simulations are in complete agreement with MD in the canonical ensemble. The python overhead of the grand-canonical scheme is only minimal. Copyright © 2012 Wiley Periodicals, Inc.

  11. Bioinformatic pipelines in Python with Leaf

    PubMed Central

    2013-01-01

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

  12. SunPy: Python for Solar Physics

    NASA Astrophysics Data System (ADS)

    Bobra, M.; Inglis, A. R.; Mumford, S.; Christe, S.; Freij, N.; Hewett, R.; Ireland, J.; Martinez Oliveros, J. C.; Reardon, K.; Savage, S. L.; Shih, A. Y.; Pérez-Suárez, D.

    2017-12-01

    SunPy is a community-developed open-source software library for solar physics. It is written in Python, a free, cross-platform, general-purpose, high-level programming language which is being increasingly adopted throughout the scientific community. SunPy aims to provide the software for obtaining and analyzing solar and heliospheric data. This poster introduces a new major release, SunPy version 0.8. The first major new feature introduced is Fido, the new primary interface to download data. It provides a consistent and powerful search interface to all major data providers including the VSO and the JSOC, as well as individual data sources such as GOES XRS time series. It is also easy to add new data sources as they become available, i.e. DKIST. The second major new feature is the SunPy coordinate framework. This provides a powerful way of representing coordinates, allowing simple and intuitive conversion between coordinate systems and viewpoints of different instruments (i.e., Solar Orbiter and the Parker Solar Probe), including transformation to astrophysical frames like ICRS. Other new features including new timeseries capabilities with better support for concatenation and metadata, updated documentation and example gallery. SunPy is distributed through pip and conda and all of its code is publicly available (sunpy.org).

  13. Matriarch: A Python Library for Materials Architecture.

    PubMed

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

    2015-10-12

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

  14. pyres: a Python wrapper for electrical resistivity modeling with R2

    NASA Astrophysics Data System (ADS)

    Befus, Kevin M.

    2018-04-01

    A Python package, pyres, was written to handle common as well as specialized input and output tasks for the R2 electrical resistivity (ER) modeling program. Input steps including handling field data, creating quadrilateral or triangular meshes, and data filtering allow repeatable and flexible ER modeling within a programming environment. pyres includes non-trivial routines and functions for locating and constraining specific known or separately-parameterized regions in both quadrilateral and triangular meshes. Three basic examples of how to run forward and inverse models with pyres are provided. The importance of testing mesh convergence and model sensitivity are also addressed with higher-level examples that show how pyres can facilitate future research-grade ER analyses.

  15. D3GB: An Interactive Genome Browser for R, Python, and WordPress.

    PubMed

    Barrios, David; Prieto, Carlos

    2017-05-01

    Genome browsers are useful not only for showing final results but also for improving analysis protocols, testing data quality, and generating result drafts. Its integration in analysis pipelines allows the optimization of parameters, which leads to better results. New developments that facilitate the creation and utilization of genome browsers could contribute to improving analysis results and supporting the quick visualization of genomic data. D3 Genome Browser is an interactive genome browser that can be easily integrated in analysis protocols and shared on the Web. It is distributed as an R package, a Python module, and a WordPress plugin to facilitate its integration in pipelines and the utilization of platform capabilities. It is compatible with popular data formats such as GenBank, GFF, BED, FASTA, and VCF, and enables the exploration of genomic data with a Web browser.

  16. Pyrcca: Regularized Kernel Canonical Correlation Analysis in Python and Its Applications to Neuroimaging.

    PubMed

    Bilenko, Natalia Y; Gallant, Jack L

    2016-01-01

    In this article we introduce Pyrcca, an open-source Python package for performing canonical correlation analysis (CCA). CCA is a multivariate analysis method for identifying relationships between sets of variables. Pyrcca supports CCA with or without regularization, and with or without linear, polynomial, or Gaussian kernelization. We first use an abstract example to describe Pyrcca functionality. We then demonstrate how Pyrcca can be used to analyze neuroimaging data. Specifically, we use Pyrcca to implement cross-subject comparison in a natural movie functional magnetic resonance imaging (fMRI) experiment by finding a data-driven set of functional response patterns that are similar across individuals. We validate this cross-subject comparison method in Pyrcca by predicting responses to novel natural movies across subjects. Finally, we show how Pyrcca can reveal retinotopic organization in brain responses to natural movies without the need for an explicit model.

  17. PyRETIS: A well-done, medium-sized python library for rare events.

    PubMed

    Lervik, Anders; Riccardi, Enrico; van Erp, Titus S

    2017-10-30

    Transition path sampling techniques are becoming common approaches in the study of rare events at the molecular scale. More efficient methods, such as transition interface sampling (TIS) and replica exchange transition interface sampling (RETIS), allow the investigation of rare events, for example, chemical reactions and structural/morphological transitions, in a reasonable computational time. Here, we present PyRETIS, a Python library for performing TIS and RETIS simulations. PyRETIS directs molecular dynamics (MD) simulations in order to sample rare events with unbiased dynamics. PyRETIS is designed to be easily interfaced with any molecular simulation package and in the present release, it has been interfaced with GROMACS and CP2K, for classical and ab initio MD simulations, respectively. © 2017 Wiley Periodicals, Inc. © 2017 Wiley Periodicals, Inc.

  18. Pyrcca: Regularized Kernel Canonical Correlation Analysis in Python and Its Applications to Neuroimaging

    PubMed Central

    Bilenko, Natalia Y.; Gallant, Jack L.

    2016-01-01

    In this article we introduce Pyrcca, an open-source Python package for performing canonical correlation analysis (CCA). CCA is a multivariate analysis method for identifying relationships between sets of variables. Pyrcca supports CCA with or without regularization, and with or without linear, polynomial, or Gaussian kernelization. We first use an abstract example to describe Pyrcca functionality. We then demonstrate how Pyrcca can be used to analyze neuroimaging data. Specifically, we use Pyrcca to implement cross-subject comparison in a natural movie functional magnetic resonance imaging (fMRI) experiment by finding a data-driven set of functional response patterns that are similar across individuals. We validate this cross-subject comparison method in Pyrcca by predicting responses to novel natural movies across subjects. Finally, we show how Pyrcca can reveal retinotopic organization in brain responses to natural movies without the need for an explicit model. PMID:27920675

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

    NASA Astrophysics Data System (ADS)

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

    2014-03-01

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

  20. Reflective Packaging

    NASA Technical Reports Server (NTRS)

    1994-01-01

    The aluminized polymer film used in spacecraft as a radiation barrier to protect both astronauts and delicate instruments has led to a number of spinoff applications. Among them are aluminized shipping bags, food cart covers and medical bags. Radiant Technologies purchases component materials and assembles a barrier made of layers of aluminized foil. The packaging reflects outside heat away from the product inside the container. The company is developing new aluminized lines, express mailers, large shipping bags, gel packs and insulated panels for the building industry.

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

    PubMed

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

    2014-05-01

    A detailed morphological description of the spectacle of the ball python (Python regius) is provided. The eyes of 21 snakes were examined by light microscopy and/or transmission electron microscopy. Additionally, eyes of nine live snakes were examined using optical coherence tomography (OCT) and Scheimpflug scanning (Pentacam). The spectacle consists of three layers: outer epithelium, stroma and inner epithelium. The outer epithelium is made up of flat basal cells overlaid by keratin, the stroma consists of organized layers of collagen fibrils with interweaving nerve fibers and blood vessels, and the inner epithelium holds squamous cells containing vesicles and microvilli. At the rim of the spectacle, there is a transition zone, where the spectacle merges with the epidermis and dermis of the periocular scales. This zone is characterized by a greater height of the basal cells of the outer epithelium and a less orderly organization of the stroma compared with the spectacle proper. The thickness of the spectacle was uniform throughout. It averaged 96 ± 10 µm in histological specimens and 108 ± 13 µm using OCT. The subspectacular space was extremely narrow in the live snakes; however, the space was visible at the periphery of the spectacle with OCT. Copyright © 2013 Wiley Periodicals, Inc.

  2. Predicting size limit of wild blood python (python brongersmai stull, 1938) harvesting in north sumatera

    NASA Astrophysics Data System (ADS)

    Mangantar Pardamean Sianturi, Markus; Jumilawaty, Erni; Delvian; Hartanto, Adrian

    2018-03-01

    Blood python (Python brongersmai Stull, 1938) is one of heavily exploited wildlife in Indonesia. The high demands on its skin trade have made its harvesting regulated under quota-based setting by the government to prevent over-harvesting. To gain understanding on the sustainability of P. brongersmai in the wild, biological characters of wild-caught specimens were studied. Samples were collected from two slaughterhouses from Rantau Prapat and Langkat. Parameters measured were morphological (Snout-vent length (SVL), body mass, abdomen width) and anatomical characters (Fat classes). Total samples of P. brongersmai in this research were 541 with 269 male and 272 female snakes. Female snakes had the highest proportion of individuals with the best quality of abdominal fat reserves (Class 3). Linear models are built and tested for its significance in relation between fat classes as anatomical characters and morphological characters. All tested morphological characters were significant in female snakes. By using linear equation models, we generate size limit to prioritize harvesting in the future. We suggest the use of SVL and stomach width ranging between 139,7 – 141,5 cm and 24,72 – 25,71 cm respectively to achieve sustainability of P. brongersmai in the wild.

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

    PubMed

    Martínez, Jorge; Segura, Pablo; García, David; Aduriz, Gorka; Ibabe, José C; Peris, Bernardo; Corpa, Juan M

    2006-09-01

    A seven-year-old female Indian python (Python molurus) weighing about 35kg was euthanased after several clinical episodes of stomatitis, pneumonia, ophthalmitis and dystocia over a period of four years. The animal had been maintained in a terrarium in a circus truck at an adequate temperature. During shows, however, the snake was considered to be exposed to stressful conditions for several hours at a time at low temperatures and with noise and bright lights. A post-mortem examination indicated ulcerative stomatitis, osteomyelitis, severe pneumonia and numerous granulomata and multifocal necrosis in stomach and spleen. Corynebacterium macginleyi was isolated in pure culture from the ulcerative stomatitis, and mixed with Stenotrophomonas maltophilia from the lungs and spleen. The findings indicated that the snake had died from a septicaemic process caused by C. macginleyi, probably originating from the stomatitis. The role of S. maltophilia as a secondary agent is discussed. The stress of the circus show and poor husbandry may have predisposed the animal to infection and septicaemia. This is the first report of C. macginleyi causing disease in a snake.

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

    SciTech Connect

    Morley, Steven K; Welling, Daniel T; Koller, Josef

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

  5. ETE: a python Environment for Tree Exploration.

    PubMed

    Huerta-Cepas, Jaime; Dopazo, Joaquín; Gabaldón, Toni

    2010-01-13

    Many bioinformatics analyses, ranging from gene clustering to phylogenetics, produce hierarchical trees as their main result. These are used to represent the relationships among different biological entities, thus facilitating their analysis and interpretation. A number of standalone programs are available that focus on tree visualization or that perform specific analyses on them. However, such applications are rarely suitable for large-scale surveys, in which a higher level of automation is required. Currently, many genome-wide analyses rely on tree-like data representation and hence there is a growing need for scalable tools to handle tree structures at large scale. Here we present the Environment for Tree Exploration (ETE), a python programming toolkit that assists in the automated manipulation, analysis and visualization of hierarchical trees. ETE libraries provide a broad set of tree handling options as well as specific methods to analyze phylogenetic and clustering trees. Among other features, ETE allows for the independent analysis of tree partitions, has support for the extended newick format, provides an integrated node annotation system and permits to link trees to external data such as multiple sequence alignments or numerical arrays. In addition, ETE implements a number of built-in analytical tools, including phylogeny-based orthology prediction and cluster validation techniques. Finally, ETE's programmable tree drawing engine can be used to automate the graphical rendering of trees with customized node-specific visualizations. ETE provides a complete set of methods to manipulate tree data structures that extends current functionality in other bioinformatic toolkits of a more general purpose. ETE is free software and can be downloaded from http://ete.cgenomics.org.

  6. ETE: a python Environment for Tree Exploration

    PubMed Central

    2010-01-01

    Background Many bioinformatics analyses, ranging from gene clustering to phylogenetics, produce hierarchical trees as their main result. These are used to represent the relationships among different biological entities, thus facilitating their analysis and interpretation. A number of standalone programs are available that focus on tree visualization or that perform specific analyses on them. However, such applications are rarely suitable for large-scale surveys, in which a higher level of automation is required. Currently, many genome-wide analyses rely on tree-like data representation and hence there is a growing need for scalable tools to handle tree structures at large scale. Results Here we present the Environment for Tree Exploration (ETE), a python programming toolkit that assists in the automated manipulation, analysis and visualization of hierarchical trees. ETE libraries provide a broad set of tree handling options as well as specific methods to analyze phylogenetic and clustering trees. Among other features, ETE allows for the independent analysis of tree partitions, has support for the extended newick format, provides an integrated node annotation system and permits to link trees to external data such as multiple sequence alignments or numerical arrays. In addition, ETE implements a number of built-in analytical tools, including phylogeny-based orthology prediction and cluster validation techniques. Finally, ETE's programmable tree drawing engine can be used to automate the graphical rendering of trees with customized node-specific visualizations. Conclusions ETE provides a complete set of methods to manipulate tree data structures that extends current functionality in other bioinformatic toolkits of a more general purpose. ETE is free software and can be downloaded from http://ete.cgenomics.org. PMID:20070885

  7. Cosmic Microwave Background Anisotropy Measurement from Python V

    NASA Astrophysics Data System (ADS)

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

    2003-02-01

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

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

    PubMed

    Hedley, J; Eatwell, K

    2013-10-12

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

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

    PubMed Central

    Rutllant, Josep

    2016-01-01

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

  10. 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.

  11. Development of a technique for contrast radiographic examination of the gastrointestinal tract in ball pythons (Python regius).

    PubMed

    Banzato, Tommaso; Russo, Elisa; Finotti, Luca; Zotti, Alessandro

    2012-07-01

    To develop a technique for radiographic evaluation of the gastrointestinal tract in ball pythons (Python regius). 10 ball python cadavers (5 males and 5 females) and 18 healthy adult ball pythons (10 males and 8 females). Live snakes were allocated to 3 groups (A, B, and C). A dose (25 mL/kg) of barium sulfate suspension at 3 concentrations (25%, 35%, and 45% [wt/vol]) was administered through an esophageal probe to snakes in groups A, B, and C, respectively. Each evaluation ended when all the contrast medium had reached the large intestine. Transit times through the esophagus, stomach, and small intestine were recorded. Imaging quality was evaluated by 3 investigators who assigned a grading score on the basis of predetermined criteria. Statistical analysis was conducted to evaluate differences in quality among the study groups. The esophagus and stomach had a consistent distribution pattern of contrast medium, whereas 3 distribution patterns of contrast medium were identified in the small intestine, regardless of barium concentration. Significant differences in imaging quality were detected among the 3 groups. Radiographic procedures were tolerated well by all snakes. The 35% concentration of contrast medium yielded the best imaging quality. Use of contrast medium for evaluation of the cranial portion of the gastrointestinal tract could be a reliable technique for the diagnosis of gastrointestinal diseases in ball pythons. However, results of this study may not translate to other snake species because of variables identified in this group of snakes.

  12. Clinical and histologic effects of intracardiac administration of propofol for induction of anesthesia in ball pythons (Python regius).

    PubMed

    McFadden, Michael S; Bennett, R Avery; Reavill, Drury R; Ragetly, Guillaume R; Clark-Price, Stuart C

    2011-09-15

    To assess the clinical differences between induction of anesthesia in ball pythons with intracardiac administration of propofol and induction with isoflurane in oxygen and to assess the histologic findings over time in hearts following intracardiac administration of propofol. Prospective randomized study. 30 hatchling ball pythons (Python regius). Anesthesia was induced with intracardiac administration of propofol (10 mg/kg [4.5 mg/lb]) in 18 ball pythons and with 5% isoflurane in oxygen in 12 ball pythons. Induction time, time of anesthesia, and recovery time were recorded. Hearts from snakes receiving intracardiac administration of propofol were evaluated histologically 3, 7, 14, 30, and 60 days following propofol administration. Induction time with intracardiac administration of propofol was significantly shorter than induction time with 5% isoflurane in oxygen. No significant differences were found in total anesthesia time. Recovery following intracardiac administration of propofol was significantly longer than recovery following induction of anesthesia with isoflurane in oxygen. Heart tissue evaluated histologically at 3, 7, and 14 days following intracardiac administration of propofol had mild inflammatory changes, and no histopathologic lesions were seen 30 and 60 days following propofol administration. Intracardiac injection of propofol in snakes is safe and provides a rapid induction of anesthesia but leads to prolonged recovery, compared with that following induction with isoflurane. Histopathologic lesions in heart tissues following intracardiac injection of propofol were mild and resolved after 14 days.

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

    PubMed

    Irizarry, Kristopher J L; Rutllant, Josep

    2016-01-01

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

  14. Food consumption increases cell proliferation in the python brain.

    PubMed

    Habroun, Stacy S; Schaffner, Andrew A; Taylor, Emily N; Strand, Christine R

    2018-04-06

    Pythons are model organisms for investigating physiological responses to food intake. While systemic growth in response to food consumption is well documented, what occurs in the brain is currently unexplored. In this study, male ball pythons ( Python regius ) were used to test the hypothesis that food consumption stimulates cell proliferation in the brain. We used 5-bromo-12'-deoxyuridine (BrdU) as a cell-birth marker to quantify and compare cell proliferation in the brain of fasted snakes and those at 2 and 6 days after a meal. Throughout the telencephalon, cell proliferation was significantly increased in the 6 day group, with no difference between the 2 day group and controls. Systemic postprandial plasticity occurs quickly after a meal is ingested, during the period of active digestion; however, the brain displays a surge of cell proliferation after most digestion and absorption is complete. © 2018. Published by The Company of Biologists Ltd.

  15. Tongue worm (Pentastomida) infection in ball pythons (Python regius) – a case report

    PubMed

    Gałęcki, Remigiusz; Sokół, Rajmund; Dudek, Agnieszka

    Tongue worms (Pentastomida) are endoparasites causing pentastomiasis, an invasive disease representing a threat to exotic animals and humans. Animals acquire infection via the alimentary tract. In reptiles, the parasite is present in the lungs, resulting in symptoms from the respiratory system. Pentastomiasis may be asymptomatic, but nonspecific symptoms may occur at high parasite concentrations. Due to the harmful effects of many antiparasitic substances, tongue worm invasion in reptiles remains not fully treatable. Although pentasomiasis is rarely diagnosed in Poland, pentastomids were diagnosed in two ball pythons, who were patients of the “Poliklinika Weterynaryjna” veterinary clinic. They demonstrated problems with the respiratory system and a significant deterioration of health. Fenbendazole at a dose of 100 mg/kg b.w., repeated after 7 days was shown to be effective.

  16. 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.

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

    PubMed

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

    2017-05-01

    Mechanical ventilation is widely recommended for reptiles during anesthesia, and while it is well-known that their low ectothermic metabolism requires much lower ventilation than in mammals, very little is known about the influence of ventilation protocol on the recovery from anesthesia. Here, 15 ball pythons (Python regius) were induced and maintained with isoflurane for 60min at one of three ventilation protocols (30, 125, or 250mlmin -1 kg -1 body mass) while an arterial catheter was inserted, and ventilation was then continued on 100% oxygen at the specified rate until voluntary extubation. Mean arterial blood pressure and heart rate (HR) were measured, and arterial blood samples collected at 60, 80, 180min and 12 and 24h after intubation. In all three groups, there was evidence of a metabolic acidosis, and snakes maintained at 30mlmin -1 kg -1 experienced an additional respiratory acidosis, while the two other ventilation protocols resulted in normal or low arterial PCO 2 . In general, normal acid-base status was restored within 12h in all three protocols. HR increased by 143±64% during anesthesia with high mechanical ventilation (250mlmin -1 kg -1 ) in comparison with recovered values. Recovery times after mechanical ventilation at 30, 125, or 250mlmin -1 kg -1 were 289±70, 126±16, and 68±7min, respectively. Mild overventilation may result in a faster recovery, and the associated lowering of arterial PCO 2 normalised arterial pH in the face of metabolic acidosis. Copyright © 2017 Elsevier Inc. All rights reserved.

  18. Spectral domain optical coherence tomography imaging of spectacular ecdysis in the royal python (Python regius).

    PubMed

    Tusler, Charlotte A; Maggs, David J; Kass, Philip H; Paul-Murphy, Joanne R; Schwab, Ivan R; Murphy, Christopher J

    2015-01-01

    To describe using spectral domain optical coherence tomography (SD-OCT), digital slit-lamp biomicroscopy, and external photography, changes in the ophidian cuticle, spectacle, and cornea during ecdysis. Four normal royal pythons (Python regius). Snakes were assessed once daily throughout a complete shed cycle using nasal, axial, and temporal SD-OCT images, digital slit-lamp biomicroscopy, and external photography. Spectral domain optical coherence tomography (SD-OCT) images reliably showed the spectacular cuticle and stroma, subcuticular space (SCS), cornea, anterior chamber, iris, and Schlemm's canal. When visible, the subspectacular space (SSS) was more distended peripherally than axially. Ocular surface changes throughout ecdysis were relatively conserved among snakes at all three regions imaged. From baseline (7 days following completion of a full cycle), the spectacle gradually thickened before separating into superficial cuticular and deep, hyper-reflective stromal components, thereby creating the SCS. During spectacular separation, the stroma regained original reflectivity, and multiple hyper-reflective foci (likely fragments from the cuticular-stromal interface) were noted within the SCS. The cornea was relatively unchanged in character or thickness throughout all stages of ecdysis. Slit-lamp images did not permit observation of these changes. Spectral domain optical coherence tomography (SD-OCT) provided excellent high-resolution images of the snake anterior segment, and especially the cuticle, spectacle, and cornea of manually restrained normal snakes at all stages of ecdysis and warrants investigation in snakes with anterior segment disease. The peripheral spectacle may be the preferred entry point for diagnostic or therapeutic injections into the SSS and for initiating spectacular surgery. © 2014 American College of Veterinary Ophthalmologists.

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

    NASA Astrophysics Data System (ADS)

    Mortensen, Mikael; Langtangen, Hans Petter

    2016-06-01

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

  20. Packaging Your Training Materials

    ERIC Educational Resources Information Center

    Espeland, Pamela

    1977-01-01

    The types of packaging and packaging materials to use for training materials should be determined during the planning of the training programs, according to the packaging market. Five steps to follow in shopping for packaging are presented, along with a list of packaging manufacturers. (MF)

  1. MontePython 3: Parameter inference code for cosmology

    NASA Astrophysics Data System (ADS)

    Brinckmann, Thejs; Lesgourgues, Julien; Audren, Benjamin; Benabed, Karim; Prunet, Simon

    2018-05-01

    MontePython 3 provides numerous ways to explore parameter space using Monte Carlo Markov Chain (MCMC) sampling, including Metropolis-Hastings, Nested Sampling, Cosmo Hammer, and a Fisher sampling method. This improved version of the Monte Python (ascl:1307.002) parameter inference code for cosmology offers new ingredients that improve the performance of Metropolis-Hastings sampling, speeding up convergence and offering significant time improvement in difficult runs. Additional likelihoods and plotting options are available, as are post-processing algorithms such as Importance Sampling and Adding Derived Parameter.

  2. Fatal Purpureocillium lilacinum pneumonia in a green tree python.

    PubMed

    Meyer, Jean; Loncaric, Igor; Richter, Barbara; Spergser, Joachim

    2018-03-01

    A 10-y-old female green tree python ( Morelia viridis) died of fungal pneumonia caused by Purpureocillium lilacinum, which was confirmed histologically and by PCR and subsequent DNA sequencing. The same fungal species was cultivated from a swab taken from the terrarium in which the snake was housed. Clinical and environmental P. lilacinum isolates were indistinguishable by the typing method applied, strongly suggesting clonal relatedness of both isolates. Because no other underlying predisposing respiratory infection could be detected by virus-specific PCR or histopathology, P. lilacinum was considered a primary pulmonary pathogen in this tree python.

  3. Identification of a novel nidovirus in an outbreak of fatal respiratory disease in ball pythons (Python regius).

    PubMed

    Uccellini, Lorenzo; Ossiboff, Robert J; de Matos, Ricardo E C; Morrisey, James K; Petrosov, Alexandra; Navarrete-Macias, Isamara; Jain, Komal; Hicks, Allison L; Buckles, Elizabeth L; Tokarz, Rafal; McAloose, Denise; Lipkin, Walter Ian

    2014-08-08

    Respiratory infections are important causes of morbidity and mortality in reptiles; however, the causative agents are only infrequently identified. Pneumonia, tracheitis and esophagitis were reported in a collection of ball pythons (Python regius). Eight of 12 snakes had evidence of bacterial pneumonia. High-throughput sequencing of total extracted nucleic acids from lung, esophagus and spleen revealed a novel nidovirus. PCR indicated the presence of viral RNA in lung, trachea, esophagus, liver, and spleen. In situ hybridization confirmed the presence of intracellular, intracytoplasmic viral nucleic acids in the lungs of infected snakes. Phylogenetic analysis based on a 1,136 amino acid segment of the polyprotein suggests that this virus may represent a new species in the subfamily Torovirinae. This report of a novel nidovirus in ball pythons may provide insight into the pathogenesis of respiratory disease in this species and enhances our knowledge of the diversity of nidoviruses.

  4. 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.

  5. Science packages

    NASA Astrophysics Data System (ADS)

    1997-01-01

    Primary science teachers in Scotland have a new updating method at their disposal with the launch of a package of CDi (Compact Discs Interactive) materials developed by the BBC and the Scottish Office. These were a response to the claim that many primary teachers felt they had been inadequately trained in science and lacked the confidence to teach it properly. Consequently they felt the need for more in-service training to equip them with the personal understanding required. The pack contains five disks and a printed user's guide divided up as follows: disk 1 Investigations; disk 2 Developing understanding; disks 3,4,5 Primary Science staff development videos. It was produced by the Scottish Interactive Technology Centre (Moray House Institute) and is available from BBC Education at £149.99 including VAT. Free Internet distribution of science education materials has also begun as part of the Global Schoolhouse (GSH) scheme. The US National Science Teachers' Association (NSTA) and Microsoft Corporation are making available field-tested comprehensive curriculum material including 'Micro-units' on more than 80 topics in biology, chemistry, earth and space science and physics. The latter are the work of the Scope, Sequence and Coordination of High School Science project, which can be found at http://www.gsh.org/NSTA_SSandC/. More information on NSTA can be obtained from its Web site at http://www.nsta.org.

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

    PubMed

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

    2009-12-01

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

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

    PubMed

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

    2010-12-01

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

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

    NASA Astrophysics Data System (ADS)

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

    2013-06-01

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

  9. DMPy: a Python package for automated mathematical model construction of large-scale metabolic systems.

    PubMed

    Smith, Robert W; van Rosmalen, Rik P; Martins Dos Santos, Vitor A P; Fleck, Christian

    2018-06-19

    Models of metabolism are often used in biotechnology and pharmaceutical research to identify drug targets or increase the direct production of valuable compounds. Due to the complexity of large metabolic systems, a number of conclusions have been drawn using mathematical methods with simplifying assumptions. For example, constraint-based models describe changes of internal concentrations that occur much quicker than alterations in cell physiology. Thus, metabolite concentrations and reaction fluxes are fixed to constant values. This greatly reduces the mathematical complexity, while providing a reasonably good description of the system in steady state. However, without a large number of constraints, many different flux sets can describe the optimal model and we obtain no information on how metabolite levels dynamically change. Thus, to accurately determine what is taking place within the cell, finer quality data and more detailed models need to be constructed. In this paper we present a computational framework, DMPy, that uses a network scheme as input to automatically search for kinetic rates and produce a mathematical model that describes temporal changes of metabolite fluxes. The parameter search utilises several online databases to find measured reaction parameters. From this, we take advantage of previous modelling efforts, such as Parameter Balancing, to produce an initial mathematical model of a metabolic pathway. We analyse the effect of parameter uncertainty on model dynamics and test how recent flux-based model reduction techniques alter system properties. To our knowledge this is the first time such analysis has been performed on large models of metabolism. Our results highlight that good estimates of at least 80% of the reaction rates are required to accurately model metabolic systems. Furthermore, reducing the size of the model by grouping reactions together based on fluxes alters the resulting system dynamics. The presented pipeline automates the modelling process for large metabolic networks. From this, users can simulate their pathway of interest and obtain a better understanding of how altering conditions influences cellular dynamics. By testing the effects of different parameterisations we are also able to provide suggestions to help construct more accurate models of complete metabolic systems in the future.

  10. Mass decomposition of galaxies using DECA software package

    NASA Astrophysics Data System (ADS)

    Mosenkov, A. V.

    2014-01-01

    The new DECA software package, which is designed to perform photometric analysis of the images of disk and elliptical galaxies having a regular structure, is presented. DECA is written in Python interpreted language and combines the capabilities of several widely used packages for astronomical data processing such as IRAF, SExtractor, and the GALFIT code used to perform two-dimensional decomposition of galaxy images into several photometric components (bulge+disk). DECA has the advantage that it can be applied to large samples of galaxies with different orientations with respect to the line of sight (including edge-on galaxies) and requires minimum human intervention. Examples of using the package to study a sample of simulated galaxy images and a sample of real objects are shown to demonstrate that DECA can be a reliable tool for the study of the structure of galaxies.

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

    PubMed Central

    Meyer, Robert; Obermayer, Klaus

    2016-01-01

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

  12. p3d--Python module for structural bioinformatics.

    PubMed

    Fufezan, Christian; Specht, Michael

    2009-08-21

    High-throughput bioinformatic analysis tools are needed to mine the large amount of structural data via knowledge based approaches. The development of such tools requires a robust interface to access the structural data in an easy way. For this the Python scripting language is the optimal choice since its philosophy is to write an understandable source code. p3d is an object oriented Python module that adds a simple yet powerful interface to the Python interpreter to process and analyse three dimensional protein structure files (PDB files). p3d's strength arises from the combination of a) very fast spatial access to the structural data due to the implementation of a binary space partitioning (BSP) tree, b) set theory and c) functions that allow to combine a and b and that use human readable language in the search queries rather than complex computer language. All these factors combined facilitate the rapid development of bioinformatic tools that can perform quick and complex analyses of protein structures. p3d is the perfect tool to quickly develop tools for structural bioinformatics using the Python scripting language.

  13. Teaching CS1 with Python GUI Game Programming

    NASA Astrophysics Data System (ADS)

    Wang, Hong

    2010-06-01

    Python is becoming a popular programming language in teaching freshman programming courses. The author designed a sequence of game programming labs using Pygame to further help engage students and to improve their programming skills. The class survey showed that the adoption of Pygame is successful.

  14. Python Source Code Plagiarism Attacks on Introductory Programming Course Assignments

    ERIC Educational Resources Information Center

    Karnalim, Oscar

    2017-01-01

    This paper empirically enlists Python plagiarism attacks that have been found on Introductory Programming course assignments for undergraduate students. According to our observation toward 400 plagiarism-suspected cases, there are 35 plagiarism attacks that have been conducted by students. It starts with comment & whitespace modification as…

  15. 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.

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

    PubMed

    Meyer, Robert; Obermayer, Klaus

    2016-01-01

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

  17. ObsPy: A Python toolbox for seismology - Current state, applications, and ecosystem around it

    NASA Astrophysics Data System (ADS)

    Lecocq, Thomas; Megies, Tobias; Krischer, Lion; Sales de Andrade, Elliott; Barsch, Robert; Beyreuther, Moritz

    2016-04-01

    ObsPy (http://www.obspy.org) is a community-driven, open-source project offering a bridge for seismology into the scientific Python ecosystem. It provides * read and write support for essentially all commonly used waveform, station, and event metadata formats with a unified interface, * a comprehensive signal processing toolbox tuned to the needs of seismologists, * integrated access to all large data centers, web services and databases, and * convenient wrappers to third party codes like libmseed and evalresp. Python, in contrast to many other languages and tools, is simple enough to enable an exploratory and interactive coding style desired by many scientists. At the same time it is a full-fledged programming language usable by software engineers to build complex and large programs. This combination makes it very suitable for use in seismology where research code often has to be translated to stable and production ready environments. It furthermore offers many freely available high quality scientific modules covering most needs in developing scientific software. ObsPy has been in constant development for more than 5 years and nowadays enjoys a large rate of adoption in the community with thousands of users. Successful applications include time-dependent and rotational seismology, big data processing, event relocations, and synthetic studies about attenuation kernels and full-waveform inversions to name a few examples. Additionally it sparked the development of several more specialized packages slowly building a modern seismological ecosystem around it. This contribution will give a short introduction and overview of ObsPy and highlight a number of use cases and software built around it. We will furthermore discuss the issue of sustainability of scientific software.

  18. ObsPy: A Python toolbox for seismology - Current state, applications, and ecosystem around it

    NASA Astrophysics Data System (ADS)

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

    2015-12-01

    ObsPy (http://www.obspy.org) is a community-driven, open-source project offering a bridge for seismology into the scientific Python ecosystem. It provides read and write support for essentially all commonly used waveform, station, and event metadata formats with a unified interface, a comprehensive signal processing toolbox tuned to the needs of seismologists, integrated access to all large data centers, web services and databases, and convenient wrappers to third party codes like libmseed and evalresp. Python, in contrast to many other languages and tools, is simple enough to enable an exploratory and interactive coding style desired by many scientists. At the same time it is a full-fledged programming language usable by software engineers to build complex and large programs. This combination makes it very suitable for use in seismology where research code often has to be translated to stable and production ready environments. It furthermore offers many freely available high quality scientific modules covering most needs in developing scientific software.ObsPy has been in constant development for more than 5 years and nowadays enjoys a large rate of adoption in the community with thousands of users. Successful applications include time-dependent and rotational seismology, big data processing, event relocations, and synthetic studies about attenuation kernels and full-waveform inversions to name a few examples. Additionally it sparked the development of several more specialized packages slowly building a modern seismological ecosystem around it.This contribution will give a short introduction and overview of ObsPy and highlight a number of us cases and software built around it. We will furthermore discuss the issue of sustainability of scientific software.

  19. 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

  20. Dual-polarization phase shift processing with the Python ARM Radar Toolkit

    NASA Astrophysics Data System (ADS)

    Collis, S. M.; Lang, T. J.; Mühlbauer, K.; Helmus, J.; North, K.

    2016-12-01

    Weather radars that measure backscatter returns at two orthogonal polarizations can give unique insight into storm macro and microphysics. Phase shift between the two polarizations caused by anisotropy in the liquid water path can be used as a constraint in rainfall rate and drop size distribution retrievals, and has the added benefit of being robust to attenuation and radar calibration. The measurement is complicated, however, by the impact of phase shift on backscatter in the presence of large drops and when the pulse volume is not filled uniformly by scatterers (known as partial beam filling). This has led to a signal processing challenge of separating the underlying desired signal from the transient signal, a challenge that has attracted many diverse solutions. To this end, the Python-ARM Radar Toolkit (Py-ART) [1] becomes increasingly important. By providing an open architecture for implementation of retrieval techniques, Py-ART has attracted three very different approaches to the phase processing problem: a fully variational technique, a finite impulse response filter technique [2], and a technique based on a linear programming [3]. These either exist within the toolkit or in another open source package that uses the Py-ART architecture. This presentation will provide an overview of differential phase and specific differential phase observed at C- and S-band frequencies, the signal processing behind the three aforementioned techniques, and some examples of their application. The goal of this presentation is to highlight the importance of open source architectures such as Py-ART for geophysical retrievals. [1] Helmus, J.J. & Collis, S.M., (2016). The Python ARM Radar Toolkit (Py-ART), a Library for Working with Weather Radar Data in the Python Programming Language. JORS. 4(1), p.e25. DOI: http://doi.org/10.5334/jors.119[2] Timothy J. Lang, David A. Ahijevych, Stephen W. Nesbitt, Richard E. Carbone, Steven A. Rutledge, and Robert Cifelli, 2007: Radar

  1. 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

  2. Comparison of cyclic correlation algorithm implemented in matlab and python

    NASA Astrophysics Data System (ADS)

    Carr, Richard; Whitney, James

    Simulation is a necessary step for all engineering projects. Simulation gives the engineers an approximation of how their devices will perform under different circumstances, without hav-ing to build, or before building a physical prototype. This is especially true for space bound devices, i.e., space communication systems, where the impact of system malfunction or failure is several orders of magnitude over that of terrestrial applications. Therefore having a reliable simulation tool is key in developing these devices and systems. Math Works Matrix Laboratory (MATLAB) is a matrix based software used by scientists and engineers to solve problems and perform complex simulations. MATLAB has a number of applications in a wide variety of fields which include communications, signal processing, image processing, mathematics, eco-nomics and physics. Because of its many uses MATLAB has become the preferred software for many engineers; it is also very expensive, especially for students and startups. One alternative to MATLAB is Python. The Python is a powerful, easy to use, open source programming environment that can be used to perform many of the same functions as MATLAB. Python programming environment has been steadily gaining popularity in niche programming circles. While there are not as many function included in the software as MATLAB, there are many open source functions that have been developed that are available to be downloaded for free. This paper illustrates how Python can implement the cyclic correlation algorithm and com-pares the results to the cyclic correlation algorithm implemented in the MATLAB environment. Some of the characteristics to be compared are the accuracy and precision of the results, and the length of the programs. The paper will demonstrate that Python is capable of performing simulations of complex algorithms such cyclic correlation.

  3. 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

  4. 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 radio-telemetered pythons appeared to exhibit maladaptive behavior during the cold spell, including attempting to bask instead of retreating to sheltered refugia. We discuss implications of our findings for persistence and spread of introduced Burmese pythons in the United States and for maximizing their rate of removal.

  5. 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.

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

    PubMed

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

    2011-09-01

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

  7. ESMPy and OpenClimateGIS: Python Interfaces for High Performance Grid Remapping and Geospatial Dataset Manipulation

    NASA Astrophysics Data System (ADS)

    O'Kuinghttons, Ryan; Koziol, Benjamin; Oehmke, Robert; DeLuca, Cecelia; Theurich, Gerhard; Li, Peggy; Jacob, Joseph

    2016-04-01

    The Earth System Modeling Framework (ESMF) Python interface (ESMPy) supports analysis and visualization in Earth system modeling codes by providing access to a variety of tools for data manipulation. ESMPy started as a Python interface to the ESMF grid remapping package, which provides mature and robust high-performance and scalable grid remapping between 2D and 3D logically rectangular and unstructured grids and sets of unconnected data. ESMPy now also interfaces with OpenClimateGIS (OCGIS), a package that performs subsetting, reformatting, and computational operations on climate datasets. ESMPy exposes a subset of ESMF grid remapping utilities. This includes bilinear, finite element patch recovery, first-order conservative, and nearest neighbor grid remapping methods. There are also options to ignore unmapped destination points, mask points on source and destination grids, and provide grid structure in the polar regions. Grid remapping on the sphere takes place in 3D Cartesian space, so the pole problem is not an issue as it can be with other grid remapping software. Remapping can be done between any combination of 2D and 3D logically rectangular and unstructured grids with overlapping domains. Grid pairs where one side of the regridding is represented by an appropriate set of unconnected data points, as is commonly found with observational data streams, is also supported. There is a developing interoperability layer between ESMPy and OpenClimateGIS (OCGIS). OCGIS is a pure Python, open source package designed for geospatial manipulation, subsetting, and computation on climate datasets stored in local NetCDF files or accessible remotely via the OPeNDAP protocol. Interfacing with OCGIS has brought GIS-like functionality to ESMPy (i.e. subsetting, coordinate transformations) as well as additional file output formats (i.e. CSV, ESRI Shapefile). ESMPy is distinguished by its strong emphasis on open source, community governance, and distributed development. The user

  8. HEPMath 1.4: A mathematica package for semi-automatic computations in high energy physics

    NASA Astrophysics Data System (ADS)

    Wiebusch, Martin

    2015-10-01

    This article introduces the Mathematica package HEPMath which provides a number of utilities and algorithms for High Energy Physics computations in Mathematica. Its functionality is similar to packages like FormCalc or FeynCalc, but it takes a more complete and extensible approach to implementing common High Energy Physics notations in the Mathematica language, in particular those related to tensors and index contractions. It also provides a more flexible method for the generation of numerical code which is based on new features for C code generation in Mathematica. In particular it can automatically generate Python extension modules which make the compiled functions callable from Python, thus eliminating the need to write any code in a low-level language like C or Fortran. It also contains seamless interfaces to LHAPDF, FeynArts, and LoopTools.

  9. 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. Copyright © 2015. Published by Elsevier Inc.

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

    USGS Publications Warehouse

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

    2016-01-01

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

  11. Brian: a simulator for spiking neural networks in python.

    PubMed

    Goodman, Dan; Brette, Romain

    2008-01-01

    "Brian" is a new simulator for spiking neural networks, written in Python (http://brian. di.ens.fr). It is an intuitive and highly flexible tool for rapidly developing new models, especially networks of single-compartment neurons. In addition to using standard types of neuron models, users can define models by writing arbitrary differential equations in ordinary mathematical notation. Python scientific libraries can also be used for defining models and analysing data. Vectorisation techniques allow efficient simulations despite the overheads of an interpreted language. Brian will be especially valuable for working on non-standard neuron models not easily covered by existing software, and as an alternative to using Matlab or C for simulations. With its easy and intuitive syntax, Brian is also very well suited for teaching computational neuroscience.

  12. 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.

  13. 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.

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

    PubMed Central

    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

  15. Transcriptome analysis of the response of Burmese python to digestion

    PubMed Central

    Sanggaard, Kristian Wejse; Schauser, Leif; Lauridsen, Sanne Enok; Enghild, Jan J.

    2017-01-01

    Abstract Exceptional and extreme feeding behaviour makes the Burmese python (Python bivittatus) an interesting model to study physiological remodelling and metabolic adaptation in response to refeeding after prolonged starvation. In this study, we used transcriptome sequencing of 5 visceral organs during fasting as well as 24 hours and 48 hours after ingestion of a large meal to unravel the postprandial changes in Burmese pythons. We first used the pooled data to perform a de novo assembly of the transcriptome and supplemented this with a proteomic survey of enzymes in the plasma and gastric fluid. We constructed a high-quality transcriptome with 34 423 transcripts, of which 19 713 (57%) were annotated. Among highly expressed genes (fragments per kilo base per million sequenced reads > 100 in 1 tissue), we found that the transition from fasting to digestion was associated with differential expression of 43 genes in the heart, 206 genes in the liver, 114 genes in the stomach, 89 genes in the pancreas, and 158 genes in the intestine. We interrogated the function of these genes to test previous hypotheses on the response to feeding. We also used the transcriptome to identify 314 secreted proteins in the gastric fluid of the python. Digestion was associated with an upregulation of genes related to metabolic processes, and translational changes therefore appear to support the postprandial rise in metabolism. We identify stomach-related proteins from a digesting individual and demonstrate that the sensitivity of modern liquid chromatography/tandem mass spectrometry equipment allows the identification of gastric juice proteins that are present during digestion. PMID:28873961

  16. Transcriptome analysis of the response of Burmese python to digestion.

    PubMed

    Duan, Jinjie; Sanggaard, Kristian Wejse; Schauser, Leif; Lauridsen, Sanne Enok; Enghild, Jan J; Schierup, Mikkel Heide; Wang, Tobias

    2017-08-01

    Exceptional and extreme feeding behaviour makes the Burmese python (Python bivittatus) an interesting model to study physiological remodelling and metabolic adaptation in response to refeeding after prolonged starvation. In this study, we used transcriptome sequencing of 5 visceral organs during fasting as well as 24 hours and 48 hours after ingestion of a large meal to unravel the postprandial changes in Burmese pythons. We first used the pooled data to perform a de novo assembly of the transcriptome and supplemented this with a proteomic survey of enzymes in the plasma and gastric fluid. We constructed a high-quality transcriptome with 34 423 transcripts, of which 19 713 (57%) were annotated. Among highly expressed genes (fragments per kilo base per million sequenced reads > 100 in 1 tissue), we found that the transition from fasting to digestion was associated with differential expression of 43 genes in the heart, 206 genes in the liver, 114 genes in the stomach, 89 genes in the pancreas, and 158 genes in the intestine. We interrogated the function of these genes to test previous hypotheses on the response to feeding. We also used the transcriptome to identify 314 secreted proteins in the gastric fluid of the python. Digestion was associated with an upregulation of genes related to metabolic processes, and translational changes therefore appear to support the postprandial rise in metabolism. We identify stomach-related proteins from a digesting individual and demonstrate that the sensitivity of modern liquid chromatography/tandem mass spectrometry equipment allows the identification of gastric juice proteins that are present during digestion. © The Authors 2017. Published by Oxford University Press.

  17. 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

  18. Pediatric ocular injury secondary to a Burmese python bite.

    PubMed

    Behrens, Alice W; Jones, Maria H; Lowery, R Scott

    2018-03-22

    We report the case of a 6-year-old girl with a penetrating ocular injury caused by a Burmese python. She received intravenous cefazolin before presenting and was treated thereafter with daily topical antibiotics and atropine. Six weeks after injury, she underwent cataract extraction and sulcus implantation of an intraocular lens and iris synechiolysis, with postoperative patching. Final visual outcome was excellent despite no globe repair was performed. Published by Elsevier Inc.

  19. 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

  20. 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/ Published by Oxford University Press 2014. This work is written by US Government employees and is in the public domain in the US.

  1. ACPYPE - AnteChamber PYthon Parser interfacE.

    PubMed

    Sousa da Silva, Alan W; Vranken, Wim F

    2012-07-23

    ACPYPE (or AnteChamber PYthon Parser interfacE) is a wrapper script around the ANTECHAMBER software that simplifies the generation of small molecule topologies and parameters for a variety of molecular dynamics programmes like GROMACS, CHARMM and CNS. It is written in the Python programming language and was developed as a tool for interfacing with other Python based applications such as the CCPN software suite (for NMR data analysis) and ARIA (for structure calculations from NMR data). ACPYPE is open source code, under GNU GPL v3, and is available as a stand-alone application at http://www.ccpn.ac.uk/acpype and as a web portal application at http://webapps.ccpn.ac.uk/acpype. We verified the topologies generated by ACPYPE in three ways: by comparing with default AMBER topologies for standard amino acids; by generating and verifying topologies for a large set of ligands from the PDB; and by recalculating the structures for 5 protein-ligand complexes from the PDB. ACPYPE is a tool that simplifies the automatic generation of topology and parameters in different formats for different molecular mechanics programmes, including calculation of partial charges, while being object oriented for integration with other applications.

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

    PubMed Central

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

    2014-01-01

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

  3. 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

  4. A Python Script to Compute Isochrones for MODFLOW.

    PubMed

    Feo, Alessandra; Zanini, Andrea; Petrella, Emma; Celico, Fulvio

    2018-03-01

    MODFLOW constitutes today the most popular modeling tool in the study of water flow in aquifers and in modeling aquifers. To simplify the interface to MODFLOW various GUI have been developed for the creation of model definition files and for the visualization and interpretation of results. Recently Bakker et al. (2016) developed the FloPy interface to MODFLOW that allows to import and use the produced simulation data using Python. This allows to construct model input files, run the models, read and plot simulations results through Python scripts. In this note, we present a Python program (that uses FloPy) interface that allows us to generate time-related capture zones (isochrones) for confined 2D steady-state groundwater flow in unbounded domains, with one or more wells. As an application, we show a validation of the approach and the results of four basic test cases: a homogenous aquifer with one well, a heterogeneous aquifer with one well, an aquifer with four wells located both longitudinal and perpendicular to the flow direction. © 2017, National Ground Water Association.

  5. Packaging for Food Service

    NASA Technical Reports Server (NTRS)

    Stilwell, E. J.

    1985-01-01

    Most of the key areas of concern in packaging the three principle food forms for the space station were covered. It can be generally concluded that there are no significant voids in packaging materials availability or in current packaging technology. However, it must also be concluded that the process by which packaging decisions are made for the space station feeding program will be very synergistic. Packaging selection will depend heavily on the preparation mechanics, the preferred presentation and the achievable disposal systems. It will be important that packaging be considered as an integral part of each decision as these systems are developed.

  6. Combining Open-Source Packages for Planetary Exploration

    NASA Astrophysics Data System (ADS)

    Schmidt, Albrecht; Grieger, Björn; Völk, Stefan

    2015-04-01

    The science planning of the ESA Rosetta mission has presented challenges which were addressed with combining various open-source software packages, such as the SPICE toolkit, the Python language and the Web graphics library three.js. The challenge was to compute certain parameters from a pool of trajectories and (possible) attitudes to describe the behaviour of the spacecraft. To be able to do this declaratively and efficiently, a C library was implemented that allows to interface the SPICE toolkit for geometrical computations from the Python language and process as much data as possible during one subroutine call. To minimise the lines of code one has to write special care was taken to ensure that the bindings were idiomatic and thus integrate well into the Python language and ecosystem. When done well, this very much simplifies the structure of the code and facilitates the testing for correctness by automatic test suites and visual inspections. For rapid visualisation and confirmation of correctness of results, the geometries were visualised with the three.js library, a popular Javascript library for displaying three-dimensional graphics in a Web browser. Programmatically, this was achieved by generating data files from SPICE sources that were included into templated HTML and displayed by a browser, thus made easily accessible to interested parties at large. As feedback came and new ideas were to be explored, the authors benefited greatly from the design of the Python-to-SPICE library which allowed the expression of algorithms to be concise and easier to communicate. In summary, by combining several well-established open-source tools, we were able to put together a flexible computation and visualisation environment that helped communicate and build confidence in planning ideas.

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

    PubMed

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

    2012-01-15

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

  8. Python Winding Itself Around Datacubes: How to Access Massive Multi-Dimensional Arrays in a Pythonic Way

    NASA Astrophysics Data System (ADS)

    Merticariu, Vlad; Misev, Dimitar; Baumann, Peter

    2017-04-01

    While python has developed into the lingua franca in Data Science there is often a paradigm break when accessing specialized tools. In particular for one of the core data categories in science and engineering, massive multi-dimensional arrays, out-of-memory solutions typically employ their own, different models. We discuss this situation on the example of the scalable open-source array engine, rasdaman ("raster data manager") which offers access to and processing of Petascale multi-dimensional arrays through an SQL-style array query language, rasql. Such queries are executed in the server on a storage engine utilizing adaptive array partitioning and based on a processing engine implementing a "tile streaming" paradigm to allow processing of arrays massively larger than server RAM. The rasdaman QL has acted as blueprint for forthcoming ISO Array SQL and the Open Geospatial Consortium (OGC) geo analytics language, Web Coverage Processing Service, adopted in 2008. Not surprisingly, rasdaman is OGC and INSPIRE Reference Implementation for their "Big Earth Data" standards suite. Recently, rasdaman has been augmented with a python interface which allows to transparently interact with the database (credits go to Siddharth Shukla's Master Thesis at Jacobs University). Programmers do not need to know the rasdaman query language, as the operators are silently transformed, through lazy evaluation, into queries. Arrays delivered are likewise automatically transformed into their python representation. In the talk, the rasdaman concept will be illustrated with the help of large-scale real-life examples of operational satellite image and weather data services, and sample python code.

  9. 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.

  10. Anaesthetic induction with alfaxalone in the ball python (Python regius): dose response and effect of injection site.

    PubMed

    James, Lauren E; Williams, Catherine Ja; Bertelsen, Mads F; Wang, Tobias

    2018-05-01

    To characterise the minimum dose of intramuscular alfaxalone required to facilitate intubation for mechanical ventilation, and to investigate the impact of cranial versus caudal injection on anaesthetic depth. Randomised crossover study. Six healthy juvenile ball pythons (Python regius). Three dosages (10, 20 and 30 mg kg -1 ) of alfaxalone were administered to each python in a caudal location with a minimum 2 weeks washout. Induction and recovery were monitored by assessing muscle tone, righting reflex, response to a noxious stimulus and the ability to intubate. A subsequent experiment assessed the influence of injection site by comparing administration of 20 mg kg -1 alfaxalone in a cranial location (1 cm cranial to the heart) with the caudal site. Respiration rate was monitored throughout, and when intubation was possible, snakes were mechanically ventilated. Regardless of dose and injection site, maximum effect was reached within 10.0 ± 2.7 minutes. When administered at the caudal injection site, intubation was only successful after a dosage of 30 mg kg- 1 , which is higher than in previous reports for other reptiles. However, intubation was possible in all cases after 7.2 ± 1.6 minutes upon cranial administration of 20 mg kg -1 , and anaesthetic duration was significantly lengthened (p < 0.001). Both 30 mg kg -1 at the caudal site and 20 mg kg -1 at the cranial site led to apnoea approximately 10 minutes post-injection, at which time the snakes were intubated and mechanically ventilated. Alfaxalone provided rapid, smooth induction when administered intramuscularly to pythons, and may serve as a useful induction agent prior to provision of volatile anaesthetics. The same dosage injected in the cranial site led to deeper anaesthesia than when injected caudally, suggesting that shunting to the liver and first-pass metabolism of alfaxalone occur when injected caudally, via the renal portal system. Copyright © 2018 Association of Veterinary Anaesthetists and

  11. Bituminous Mixtures Lab

    DOT National Transportation Integrated Search

    2002-07-25

    The Bituminous Mixtures Laboratory (BML) specializes in the research of asphalt pavement mixtures. This lab supports FHWA's efforts to develop, evaluate and improve materials, mixture design technology and performance-based tests for asphalt paving m...

  12. 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. © 2015. Published by The Company of Biologists Ltd.

  13. OzPythonPlex: An optimised forensic STR multiplex assay set for the Australasian carpet python (Morelia spilota).

    PubMed

    Ciavaglia, Sherryn; Linacre, Adrian

    2018-05-01

    Reptile species, and in particular snakes, are protected by national and international agreements yet are commonly handled illegally. To aid in the enforcement of such legislation, we report on the development of three 11-plex assays from the genome of the carpet python to type 24 loci of tetra-nucleotide and penta-nucleotide repeat motifs (pure, compound and complex included). The loci range in size between 70 and 550 bp. Seventeen of the loci are newly characterised with the inclusion of seven previously developed loci to facilitate cross-comparison with previous carpet python genotyping studies. Assays were optimised in accordance with human forensic profiling kits using one nanogram template DNA. Three loci are included in all three of the multiplex reactions as quality assurance markers, to ensure sample identity and genotyping accuracy is maintained across the three profiling assays. Allelic ladders have been developed for the three assays to ensure consistent and precise allele designation. A DNA reference database of allele frequencies is presented based on 249 samples collected from throughout the species native range. A small number of validation tests are conducted to demonstrate the utility of these multiplex assays. We suggest further appropriate validation tests that should be conducted prior to the application of the multiplex assays in criminal investigations involving carpet pythons. Copyright © 2018 Elsevier B.V. All rights reserved.

  14. Comparative Packaging Study

    NASA Technical Reports Server (NTRS)

    Perchonok, Michele; Antonini, David

    2008-01-01

    This viewgraph presentation describes a comparative packaging study for use on long duration space missions. The topics include: 1) Purpose; 2) Deliverables; 3) Food Sample Selection; 4) Experimental Design Matrix; 5) Permeation Rate Comparison; and 6) Packaging Material Information.

  15. Creative Thinking Package

    ERIC Educational Resources Information Center

    Jones, Clive

    1972-01-01

    A look at the latest package from a British managment training organization, which explains and demonstrates creative thinking techniques, including brainstorming. The package, designed for groups of twelve or more, consists of tapes, visuals, and associated exercises. (Editor/JB)

  16. Automating Disk Forensic Processing with SleuthKit, XML and Python

    DTIC Science & Technology

    2009-05-01

    1 Automating Disk Forensic Processing with SleuthKit, XML and Python Simson L. Garfinkel Abstract We have developed a program called fiwalk which...files themselves. We show how it is relatively simple to create automated disk forensic applications using a Python module we have written that reads...software that the portable device may contain. Keywords: Computer Forensics; XML; Sleuth Kit; Python I. INTRODUCTION In recent years we have found many

  17. Modular avionics packaging standardization

    NASA Astrophysics Data System (ADS)

    Austin, M.; McNichols, J. K.

    The Modular Avionics Packaging (MAP) Program for packaging future military avionics systems with the objective of improving reliability, maintainability, and supportability, and reducing equipment life cycle costs is addressed. The basic MAP packaging concepts called the Standard Avionics Module, the Standard Enclosure, and the Integrated Rack are summarized, and the benefits of modular avionics packaging, including low risk design, technology independence with common functions, improved maintainability and life cycle costs are discussed. Progress made in MAP is briefly reviewed.

  18. Bifrost: a Modular Python/C++ Framework for Development of High-Throughput Data Analysis Pipelines

    NASA Astrophysics Data System (ADS)

    Cranmer, Miles; Barsdell, Benjamin R.; Price, Danny C.; Garsden, Hugh; Taylor, Gregory B.; Dowell, Jayce; Schinzel, Frank; Costa, Timothy; Greenhill, Lincoln J.

    2017-01-01

    Large radio interferometers have data rates that render long-term storage of raw correlator data infeasible, thus motivating development of real-time processing software. For high-throughput applications, processing pipelines are challenging to design and implement. Motivated by science efforts with the Long Wavelength Array, we have developed Bifrost, a novel Python/C++ framework that eases the development of high-throughput data analysis software by packaging algorithms as black box processes in a directed graph. This strategy to modularize code allows astronomers to create parallelism without code adjustment. Bifrost uses CPU/GPU ’circular memory’ data buffers that enable ready introduction of arbitrary functions into the processing path for ’streams’ of data, and allow pipelines to automatically reconfigure in response to astrophysical transient detection or input of new observing settings. We have deployed and tested Bifrost at the latest Long Wavelength Array station, in Sevilleta National Wildlife Refuge, NM, where it handles throughput exceeding 10 Gbps per CPU core.

  19. Sleep: An Open-Source Python Software for Visualization, Analysis, and Staging of Sleep Data.

    PubMed

    Combrisson, Etienne; Vallat, Raphael; Eichenlaub, Jean-Baptiste; O'Reilly, Christian; Lajnef, Tarek; Guillot, Aymeric; Ruby, Perrine M; Jerbi, Karim

    2017-01-01

    We introduce Sleep, a new Python open-source graphical user interface (GUI) dedicated to visualization, scoring and analyses of sleep data. Among its most prominent features are: (1) Dynamic display of polysomnographic data, spectrogram, hypnogram and topographic maps with several customizable parameters, (2) Implementation of several automatic detection of sleep features such as spindles, K-complexes, slow waves, and rapid eye movements (REM), (3) Implementation of practical signal processing tools such as re-referencing or filtering, and (4) Display of main descriptive statistics including publication-ready tables and figures. The software package supports loading and reading raw EEG data from standard file formats such as European Data Format, in addition to a range of commercial data formats. Most importantly, Sleep is built on top of the VisPy library, which provides GPU-based fast and high-level visualization. As a result, it is capable of efficiently handling and displaying large sleep datasets. Sleep is freely available (http://visbrain.org/sleep) and comes with sample datasets and an extensive documentation. Novel functionalities will continue to be added and open-science community efforts are expected to enhance the capacities of this module.

  20. microMS: A Python Platform for Image-Guided Mass Spectrometry Profiling

    NASA Astrophysics Data System (ADS)

    Comi, Troy J.; Neumann, Elizabeth K.; Do, Thanh D.; Sweedler, Jonathan V.

    2017-09-01

    Image-guided mass spectrometry (MS) profiling provides a facile framework for analyzing samples ranging from single cells to tissue sections. The fundamental workflow utilizes a whole-slide microscopy image to select targets of interest, determine their spatial locations, and subsequently perform MS analysis at those locations. Improving upon prior reported methodology, a software package was developed for working with microscopy images. microMS, for microscopy-guided mass spectrometry, allows the user to select and profile diverse samples using a variety of target patterns and mass analyzers. Written in Python, the program provides an intuitive graphical user interface to simplify image-guided MS for novice users. The class hierarchy of instrument interactions permits integration of new MS systems while retaining the feature-rich image analysis framework. microMS is a versatile platform for performing targeted profiling experiments using a series of mass spectrometers. The flexibility in mass analyzers greatly simplifies serial analyses of the same targets by different instruments. The current capabilities of microMS are presented, and its application for off-line analysis of single cells on three distinct instruments is demonstrated. The software has been made freely available for research purposes. [Figure not available: see fulltext.

  1. microMS: A Python Platform for Image-Guided Mass Spectrometry Profiling.

    PubMed

    Comi, Troy J; Neumann, Elizabeth K; Do, Thanh D; Sweedler, Jonathan V

    2017-09-01

    Image-guided mass spectrometry (MS) profiling provides a facile framework for analyzing samples ranging from single cells to tissue sections. The fundamental workflow utilizes a whole-slide microscopy image to select targets of interest, determine their spatial locations, and subsequently perform MS analysis at those locations. Improving upon prior reported methodology, a software package was developed for working with microscopy images. microMS, for microscopy-guided mass spectrometry, allows the user to select and profile diverse samples using a variety of target patterns and mass analyzers. Written in Python, the program provides an intuitive graphical user interface to simplify image-guided MS for novice users. The class hierarchy of instrument interactions permits integration of new MS systems while retaining the feature-rich image analysis framework. microMS is a versatile platform for performing targeted profiling experiments using a series of mass spectrometers. The flexibility in mass analyzers greatly simplifies serial analyses of the same targets by different instruments. The current capabilities of microMS are presented, and its application for off-line analysis of single cells on three distinct instruments is demonstrated. The software has been made freely available for research purposes. Graphical Abstract ᅟ.

  2. Sleep: An Open-Source Python Software for Visualization, Analysis, and Staging of Sleep Data

    PubMed Central

    Combrisson, Etienne; Vallat, Raphael; Eichenlaub, Jean-Baptiste; O'Reilly, Christian; Lajnef, Tarek; Guillot, Aymeric; Ruby, Perrine M.; Jerbi, Karim

    2017-01-01

    We introduce Sleep, a new Python open-source graphical user interface (GUI) dedicated to visualization, scoring and analyses of sleep data. Among its most prominent features are: (1) Dynamic display of polysomnographic data, spectrogram, hypnogram and topographic maps with several customizable parameters, (2) Implementation of several automatic detection of sleep features such as spindles, K-complexes, slow waves, and rapid eye movements (REM), (3) Implementation of practical signal processing tools such as re-referencing or filtering, and (4) Display of main descriptive statistics including publication-ready tables and figures. The software package supports loading and reading raw EEG data from standard file formats such as European Data Format, in addition to a range of commercial data formats. Most importantly, Sleep is built on top of the VisPy library, which provides GPU-based fast and high-level visualization. As a result, it is capable of efficiently handling and displaying large sleep datasets. Sleep is freely available (http://visbrain.org/sleep) and comes with sample datasets and an extensive documentation. Novel functionalities will continue to be added and open-science community efforts are expected to enhance the capacities of this module. PMID:28983246

  3. IB2d: a Python and MATLAB implementation of the immersed boundary method.

    PubMed

    Battista, Nicholas A; Strickland, W Christopher; Miller, Laura A

    2017-03-29

    The development of fluid-structure interaction (FSI) software involves trade-offs between ease of use, generality, performance, and cost. Typically there are large learning curves when using low-level software to model the interaction of an elastic structure immersed in a uniform density fluid. Many existing codes are not publicly available, and the commercial software that exists usually requires expensive licenses and may not be as robust or allow the necessary flexibility that in house codes can provide. We present an open source immersed boundary software package, IB2d, with full implementations in both MATLAB and Python, that is capable of running a vast range of biomechanics models and is accessible to scientists who have experience in high-level programming environments. IB2d contains multiple options for constructing material properties of the fiber structure, as well as the advection-diffusion of a chemical gradient, muscle mechanics models, and artificial forcing to drive boundaries with a preferred motion.

  4. LIVVkit: An extensible, python-based, land ice verification and validation toolkit for ice sheet models

    SciTech Connect

    Kennedy, Joseph H.; Bennett, Andrew R.; Evans, Katherine J.

    To address the pressing need to better understand the behavior and complex interaction of ice sheets within the global Earth system, significant development of continental-scale, dynamical ice sheet models is underway. Concurrent to the development of the Community Ice Sheet Model (CISM), the corresponding verification and validation (V&V) process is being coordinated through a new, robust, Python-based extensible software package, the Land Ice Verification and Validation toolkit (LIVVkit). Incorporated into the typical ice sheet model development cycle, it provides robust and automated numerical verification, software verification, performance validation, and physical validation analyses on a variety of platforms, from personal laptopsmore » to the largest supercomputers. LIVVkit operates on sets of regression test and reference data sets, and provides comparisons for a suite of community prioritized tests, including configuration and parameter variations, bit-for-bit evaluation, and plots of model variables to indicate where differences occur. LIVVkit also provides an easily extensible framework to incorporate and analyze results of new intercomparison projects, new observation data, and new computing platforms. LIVVkit is designed for quick adaptation to additional ice sheet models via abstraction of model specific code, functions, and configurations into an ice sheet model description bundle outside the main LIVVkit structure. Furthermore, through shareable and accessible analysis output, LIVVkit is intended to help developers build confidence in their models and enhance the credibility of ice sheet models overall.« less

  5. LIVVkit: An extensible, python-based, land ice verification and validation toolkit for ice sheet models

    DOE PAGES

    Kennedy, Joseph H.; Bennett, Andrew R.; Evans, Katherine J.; ...

    2017-03-23

    To address the pressing need to better understand the behavior and complex interaction of ice sheets within the global Earth system, significant development of continental-scale, dynamical ice sheet models is underway. Concurrent to the development of the Community Ice Sheet Model (CISM), the corresponding verification and validation (V&V) process is being coordinated through a new, robust, Python-based extensible software package, the Land Ice Verification and Validation toolkit (LIVVkit). Incorporated into the typical ice sheet model development cycle, it provides robust and automated numerical verification, software verification, performance validation, and physical validation analyses on a variety of platforms, from personal laptopsmore » to the largest supercomputers. LIVVkit operates on sets of regression test and reference data sets, and provides comparisons for a suite of community prioritized tests, including configuration and parameter variations, bit-for-bit evaluation, and plots of model variables to indicate where differences occur. LIVVkit also provides an easily extensible framework to incorporate and analyze results of new intercomparison projects, new observation data, and new computing platforms. LIVVkit is designed for quick adaptation to additional ice sheet models via abstraction of model specific code, functions, and configurations into an ice sheet model description bundle outside the main LIVVkit structure. Furthermore, through shareable and accessible analysis output, LIVVkit is intended to help developers build confidence in their models and enhance the credibility of ice sheet models overall.« less

  6. LIVVkit: An extensible, python-based, land ice verification and validation toolkit for ice sheet models

    NASA Astrophysics Data System (ADS)

    Kennedy, Joseph H.; Bennett, Andrew R.; Evans, Katherine J.; Price, Stephen; Hoffman, Matthew; Lipscomb, William H.; Fyke, Jeremy; Vargo, Lauren; Boghozian, Adrianna; Norman, Matthew; Worley, Patrick H.

    2017-06-01

    To address the pressing need to better understand the behavior and complex interaction of ice sheets within the global Earth system, significant development of continental-scale, dynamical ice sheet models is underway. Concurrent to the development of the Community Ice Sheet Model (CISM), the corresponding verification and validation (V&V) process is being coordinated through a new, robust, Python-based extensible software package, the Land Ice Verification and Validation toolkit (LIVVkit). Incorporated into the typical ice sheet model development cycle, it provides robust and automated numerical verification, software verification, performance validation, and physical validation analyses on a variety of platforms, from personal laptops to the largest supercomputers. LIVVkit operates on sets of regression test and reference data sets, and provides comparisons for a suite of community prioritized tests, including configuration and parameter variations, bit-for-bit evaluation, and plots of model variables to indicate where differences occur. LIVVkit also provides an easily extensible framework to incorporate and analyze results of new intercomparison projects, new observation data, and new computing platforms. LIVVkit is designed for quick adaptation to additional ice sheet models via abstraction of model specific code, functions, and configurations into an ice sheet model description bundle outside the main LIVVkit structure. Ultimately, through shareable and accessible analysis output, LIVVkit is intended to help developers build confidence in their models and enhance the credibility of ice sheet models overall.

  7. Trends in Food Packaging.

    ERIC Educational Resources Information Center

    Ott, Dana B.

    1988-01-01

    This article discusses developments in food packaging, processing, and preservation techniques in terms of packaging materials, technologies, consumer benefits, and current and potential food product applications. Covers implications due to consumer life-style changes, cost-effectiveness of packaging materials, and the ecological impact of…

  8. Packaging of electronic modules

    NASA Technical Reports Server (NTRS)

    Katzin, L.

    1966-01-01

    Study of design approaches that are taken toward optimizing the packaging of electronic modules with respect to size, shape, component orientation, interconnections, and structural support. The study does not present a solution to specific packaging problems, but rather the factors to be considered to achieve optimum packaging designs.

  9. 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. © 2015 The Author(s) Published by the Royal Society. All rights reserved.

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

    PubMed Central

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

    2015-01-01

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

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

    PubMed

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

    2011-01-01

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

  12. 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.

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

    USGS Publications Warehouse

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

    2016-01-01

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

  14. PyEEG: An Open Source Python Module for EEG/MEG Feature Extraction

    PubMed Central

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

    2011-01-01

    Computer-aided diagnosis of neural diseases from EEG signals (or other physiological signals that can be treated as time series, e.g., MEG) is an emerging field that has gained much attention in past years. Extracting features is a key component in the analysis of EEG signals. In our previous works, we have implemented many EEG feature extraction functions in the Python programming language. As Python is gaining more ground in scientific computing, an open source Python module for extracting EEG features has the potential to save much time for computational neuroscientists. In this paper, we introduce PyEEG, an open source Python module for EEG feature extraction. PMID:21512582

  15. Facilitating hydrological data analysis workflows in R: the RHydro package

    NASA Astrophysics Data System (ADS)

    Buytaert, Wouter; Moulds, Simon; Skoien, Jon; Pebesma, Edzer; Reusser, Dominik

    2015-04-01

    The advent of new technologies such as web-services and big data analytics holds great promise for hydrological data analysis and simulation. Driven by the need for better water management tools, it allows for the construction of much more complex workflows, that integrate more and potentially more heterogeneous data sources with longer tool chains of algorithms and models. With the scientific challenge of designing the most adequate processing workflow comes the technical challenge of implementing the workflow with a minimal risk for errors. A wide variety of new workbench technologies and other data handling systems are being developed. At the same time, the functionality of available data processing languages such as R and Python is increasing at an accelerating pace. Because of the large diversity of scientific questions and simulation needs in hydrology, it is unlikely that one single optimal method for constructing hydrological data analysis workflows will emerge. Nevertheless, languages such as R and Python are quickly gaining popularity because they combine a wide array of functionality with high flexibility and versatility. The object-oriented nature of high-level data processing languages makes them particularly suited for the handling of complex and potentially large datasets. In this paper, we explore how handling and processing of hydrological data in R can be facilitated further by designing and implementing a set of relevant classes and methods in the experimental R package RHydro. We build upon existing efforts such as the sp and raster packages for spatial data and the spacetime package for spatiotemporal data to define classes for hydrological data (HydroST). In order to handle simulation data from hydrological models conveniently, a HM class is defined. Relevant methods are implemented to allow for an optimal integration of the HM class with existing model fitting and simulation functionality in R. Lastly, we discuss some of the design challenges

  16. Advancements in meat packaging.

    PubMed

    McMillin, Kenneth W

    2017-10-01

    Packaging of meat provides the same or similar benefits for raw chilled and processed meats as other types of food packaging. Although air-permeable packaging is most prevalent for raw chilled red meat, vacuum and modified atmosphere packaging offer longer shelf life. The major advancements in meat packaging have been in the widely used plastic polymers while biobased materials and their integration into composite packaging are receiving much attention for functionality and sustainability. At this time, active and intelligent packaging are not widely used for antioxidant, antimicrobial, and other functions to stabilize and enhance meat properties although many options are being developed and investigated. The advances being made in nanotechnology will be incorporated into food packaging and presumably into meat packaging when appropriate and useful. Intelligent packaging using sensors for transmission of desired information and prompting of subsequent changes in packaging materials, environments or the products to maintain safety and quality are still in developmental stages. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. Edible packaging materials.

    PubMed

    Janjarasskul, Theeranun; Krochta, John M

    2010-01-01

    Research groups and the food and pharmaceutical industries recognize edible packaging as a useful alternative or addition to conventional packaging to reduce waste and to create novel applications for improving product stability, quality, safety, variety, and convenience for consumers. Recent studies have explored the ability of biopolymer-based food packaging materials to carry and control-release active compounds. As diverse edible packaging materials derived from various by-products or waste from food industry are being developed, the dry thermoplastic process is advancing rapidly as a feasible commercial edible packaging manufacturing process. The employment of nanocomposite concepts to edible packaging materials promises to improve barrier and mechanical properties and facilitate effective incorporation of bioactive ingredients and other designed functions. In addition to the need for a more fundamental understanding to enable design to desired specifications, edible packaging has to overcome challenges such as regulatory requirements, consumer acceptance, and scaling-up research concepts to commercial applications.

  18. [Packaging: the guarantee of medicinal quality].

    PubMed

    Chaumeil, J-C

    2003-01-01

    Primary packaging guarantees the pharmaceutical quality of the medicinal preparation received by the patient. Glass bottles containing parenteral solutions for example ensure that sterility, quality and optimal stability are preserved until administration. Recent innovations in materials research has lead to improvements in parenteral infusions. Multicompartmental bags, allowing extemporaneous mixtures without opening the container, constitute an extremely beneficial advance for the patient, allowing administration of mixtures with solutions and emulsions which would be unstable if stored. Metered dose pressurized inhalers are an excellent example of drug administration devices designed specifically to ensure quality and bioavailability. These examples illustrate the important role of primary packaging and demonstrate the usefulness of research and development in this area.

  19. Python and HPC for High Energy Physics Data Analyses

    DOE PAGES

    Sehrish, S.; Kowalkowski, J.; Paterno, M.; ...

    2017-01-01

    High level abstractions in Python that can utilize computing hardware well seem to be an attractive option for writing data reduction and analysis tasks. In this paper, we explore the features available in Python which are useful and efficient for end user analysis in High Energy Physics (HEP). A typical vertical slice of an HEP data analysis is somewhat fragmented: the state of the reduction/analysis process must be saved at certain stages to allow for selective reprocessing of only parts of a generally time-consuming workflow. Also, algorithms tend to to be modular because of the heterogeneous nature of most detectorsmore » and the need to analyze different parts of the detector separately before combining the information. This fragmentation causes difficulties for interactive data analysis, and as data sets increase in size and complexity (O10 TiB for a “small” neutrino experiment to the O10 PiB currently held by the CMS experiment at the LHC), data analysis methods traditional to the field must evolve to make optimum use of emerging HPC technologies and platforms. Mainstream big data tools, while suggesting a direction in terms of what can be done if an entire data set can be available across a system and analysed with high-level programming abstractions, are not designed with either scientific computing generally, or modern HPC platform features in particular, such as data caching levels, in mind. Our example HPC use case is a search for a new elementary particle which might explain the phenomenon known as “Dark Matter”. Here, using data from the CMS detector, we will use HDF5 as our input data format, and MPI with Python to implement our use case.« less

  20. 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.

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

    NASA Astrophysics Data System (ADS)

    Kent, Brian R.

    2016-06-01

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

  2. Interfacing of high temperature Z-meter setup using python

    NASA Astrophysics Data System (ADS)

    Patel, Ashutosh; Sisodia, Shashank; Pandey, Sudhir K.

    2017-05-01

    In this work, we interface high temperature Z-meter setup to automize the whole measurement process. A program is built on open source programming language `Python' which convert the manual measurement process into fully automated process without any cost addition. Using this program, simultaneous measurement of Seebeck coefficient (α), thermal conductivity (κ) and electrical resistivity (ρ), are performed and using all three, figure-of-merit (ZT) is calculated. Developed program is verified by performing measurement over p-type Bi0.36Sb1.45Te3 sample and the data obtained are found to be in good agreement with the reported data.

  3. 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.

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

    NASA Astrophysics Data System (ADS)

    Álvarez-Gómez, José A.

    2014-05-01

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

  5. 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

  6. Interactions between the invasive Burmese python, Python bivittatus Kuhl, and the local mosquito community in Florida, USA.

    PubMed

    Reeves, Lawrence E; Krysko, Kenneth L; Avery, Michael L; Gillett-Kaufman, Jennifer L; Kawahara, Akito Y; Connelly, C Roxanne; Kaufman, Phillip E

    2018-01-01

    The Burmese python, Python bivittatus Kuhl, is a well-established invasive species in the greater Everglades ecosystem of southern Florida, USA. Most research on its ecological impacts focuses on its role as a predator and its trophic interactions with native vertebrate species, particularly mammals. Beyond predation, there is little known about the ecological interactions between P. bivittatus and native faunal communities. It is likely that established populations of P. bivittatus in southern Florida serve as hosts for native mosquito communities. To test this concept, we used mitochondrial cytochrome c oxidase subunit I DNA barcoding to determine the hosts of blood fed mosquitoes collected at a research facility in northern Florida where captive P. bivittatus and Argentine black and white tegu, Salvator merianae (Duméril and Bibron), are maintained in outdoor enclosures, accessible to local mosquitoes. We recovered python DNA from the blood meals of three species of Culex mosquitoes: Culex erraticus (Dyar and Knab), Culex quinquefasciatus Say, and Culex pilosus (Dyar and Knab). Culex erraticus conclusively (P = 0.001; Fisher's Exact Test) took more blood meals from P. bivittatus than from any other available host. While the majority of mosquito blood meals in our sample were derived from P. bivittatus, only one was derived from S. merianae. These results demonstrate that local mosquitoes will feed on invasive P. bivittatus, a recently introduced host. If these interactions also occur in southern Florida, P. bivittatus may be involved in the transmission networks of mosquito-vectored pathogens. Our results also illustrate the potential of detecting the presence of P. bivittatus in the field through screening mosquito blood meals for their DNA.

  7. Interactions between the invasive Burmese python, Python bivittatus Kuhl, and the local mosquito community in Florida, USA

    PubMed Central

    Krysko, Kenneth L.; Gillett-Kaufman, Jennifer L.; Kawahara, Akito Y.; Connelly, C. Roxanne

    2018-01-01

    The Burmese python, Python bivittatus Kuhl, is a well-established invasive species in the greater Everglades ecosystem of southern Florida, USA. Most research on its ecological impacts focuses on its role as a predator and its trophic interactions with native vertebrate species, particularly mammals. Beyond predation, there is little known about the ecological interactions between P. bivittatus and native faunal communities. It is likely that established populations of P. bivittatus in southern Florida serve as hosts for native mosquito communities. To test this concept, we used mitochondrial cytochrome c oxidase subunit I DNA barcoding to determine the hosts of blood fed mosquitoes collected at a research facility in northern Florida where captive P. bivittatus and Argentine black and white tegu, Salvator merianae (Duméril and Bibron), are maintained in outdoor enclosures, accessible to local mosquitoes. We recovered python DNA from the blood meals of three species of Culex mosquitoes: Culex erraticus (Dyar and Knab), Culex quinquefasciatus Say, and Culex pilosus (Dyar and Knab). Culex erraticus conclusively (P = 0.001; Fisher’s Exact Test) took more blood meals from P. bivittatus than from any other available host. While the majority of mosquito blood meals in our sample were derived from P. bivittatus, only one was derived from S. merianae. These results demonstrate that local mosquitoes will feed on invasive P. bivittatus, a recently introduced host. If these interactions also occur in southern Florida, P. bivittatus may be involved in the transmission networks of mosquito-vectored pathogens. Our results also illustrate the potential of detecting the presence of P. bivittatus in the field through screening mosquito blood meals for their DNA. PMID:29342169

  8. Packaged die heater

    DOEpatents

    Spielberger, Richard; Ohme, Bruce Walker; Jensen, Ronald J.

    2011-06-21

    A heater for heating packaged die for burn-in and heat testing is described. The heater may be a ceramic-type heater with a metal filament. The heater may be incorporated into the integrated circuit package as an additional ceramic layer of the package, or may be an external heater placed in contact with the package to heat the die. Many different types of integrated circuit packages may be accommodated. The method provides increased energy efficiency for heating the die while reducing temperature stresses on testing equipment. The method allows the use of multiple heaters to heat die to different temperatures. Faulty die may be heated to weaken die attach material to facilitate removal of the die. The heater filament or a separate temperature thermistor located in the package may be used to accurately measure die temperature.

  9. Programming biological models in Python using PySB.

    PubMed

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

    2013-01-01

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

  10. Novel divergent nidovirus in a python with pneumonia.

    PubMed

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

    2014-11-01

    The order Nidovirales contains large, enveloped viruses with a non-segmented positive-stranded RNA genome. Nidoviruses have been detected in man and various animal species, but, to date, there have been no reports of nidovirus in reptiles. In the present study, we describe the detection, characterization, phylogenetic analyses and disease association of a novel divergent nidovirus in the lung of an Indian python (Python molurus) with necrotizing pneumonia. Characterization of the partial genome (>33 000 nt) of this virus revealed several genetic features that are distinct from other nidoviruses, including a very large polyprotein 1a, a putative ribosomal frameshift signal that was identical to the frameshift signal of astroviruses and retroviruses and an accessory ORF that showed some similarity with the haemagglutinin-neuraminidase of paramyxoviruses. Analysis of genome organization and phylogenetic analysis of polyprotein 1ab suggests that this virus belongs to the subfamily Torovirinae. Results of this study provide novel insights into the genetic diversity within the order Nidovirales. © 2014 The Authors.

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

    PubMed Central

    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

  12. 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

  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. Temporal and spatial complexity of maternal thermoregulation in tropical pythons.

    PubMed

    Stahlschmidt, Zachary Ross; Shine, Richard; Denardo, Dale F

    2012-01-01

    Parental care is a widespread adaptation that evolved independently in a broad range of taxa. Although the dynamics by which two parents meet the developmental needs of offspring are well studied in birds, we lack understanding about the temporal and spatial complexity of parental care in taxa exhibiting female-only care, the predominant mode of parental care. Thus, we examined the behavioral and physiological mechanisms by which female water pythons Liasis fuscus meet a widespread developmental need (thermoregulation) in a natural setting. Although female L. fuscus were not facultatively thermogenic, they did use behaviors on multiple spatial scales (e.g., shifts in egg-brooding postures and surface activity patterns) to balance the thermal needs of their offspring throughout reproduction (gravidity and egg brooding). Maternal behaviors in L. fuscus varied by stage within reproduction and were mediated by interindividual variation in body size and fecundity. Female pythons with relatively larger clutch sizes were cooler during egg brooding, suggesting a trade-off between reproductive quantity (size of clutch) and quality (developmental temperature). In nature, caregiving parents of all taxa must navigate both extrinsic factors (temporal and spatial complexity) and intrinsic factors (body size and fecundity) to meet the needs of their offspring. Our study used a comprehensive approach that can be used as a general template for future research examining the dynamics by which parents meet other developmental needs (e.g., predation risk or energy balance).

  15. Pybel: a Python wrapper for the OpenBabel cheminformatics toolkit.

    PubMed

    O'Boyle, Noel M; Morley, Chris; Hutchison, Geoffrey R

    2008-03-09

    Scripting languages such as Python are ideally suited to common programming tasks in cheminformatics such as data analysis and parsing information from files. However, for reasons of efficiency, cheminformatics toolkits such as the OpenBabel toolkit are often implemented in compiled languages such as C++. We describe Pybel, a Python module that provides access to the OpenBabel toolkit. Pybel wraps the direct toolkit bindings to simplify common tasks such as reading and writing molecular files and calculating fingerprints. Extensive use is made of Python iterators to simplify loops such as that over all the molecules in a file. A Pybel Molecule can be easily interconverted to an OpenBabel OBMol to access those methods or attributes not wrapped by Pybel. Pybel allows cheminformaticians to rapidly develop Python scripts that manipulate chemical information. It is open source, available cross-platform, and offers the power of the OpenBabel toolkit to Python programmers.

  16. 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.

  17. Pybel: a Python wrapper for the OpenBabel cheminformatics toolkit

    PubMed Central

    O'Boyle, Noel M; Morley, Chris; Hutchison, Geoffrey R

    2008-01-01

    Background Scripting languages such as Python are ideally suited to common programming tasks in cheminformatics such as data analysis and parsing information from files. However, for reasons of efficiency, cheminformatics toolkits such as the OpenBabel toolkit are often implemented in compiled languages such as C++. We describe Pybel, a Python module that provides access to the OpenBabel toolkit. Results Pybel wraps the direct toolkit bindings to simplify common tasks such as reading and writing molecular files and calculating fingerprints. Extensive use is made of Python iterators to simplify loops such as that over all the molecules in a file. A Pybel Molecule can be easily interconverted to an OpenBabel OBMol to access those methods or attributes not wrapped by Pybel. Conclusion Pybel allows cheminformaticians to rapidly develop Python scripts that manipulate chemical information. It is open source, available cross-platform, and offers the power of the OpenBabel toolkit to Python programmers. PMID:18328109

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

    USGS Publications Warehouse

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

    2016-01-01

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

  19. GENERAL PURPOSE ADA PACKAGES

    NASA Technical Reports Server (NTRS)

    Klumpp, A. R.

    1994-01-01

    Ten families of subprograms are bundled together for the General-Purpose Ada Packages. The families bring to Ada many features from HAL/S, PL/I, FORTRAN, and other languages. These families are: string subprograms (INDEX, TRIM, LOAD, etc.); scalar subprograms (MAX, MIN, REM, etc.); array subprograms (MAX, MIN, PROD, SUM, GET, and PUT); numerical subprograms (EXP, CUBIC, etc.); service subprograms (DATE_TIME function, etc.); Linear Algebra II; Runge-Kutta integrators; and three text I/O families of packages. In two cases, a family consists of a single non-generic package. In all other cases, a family comprises a generic package and its instances for a selected group of scalar types. All generic packages are designed to be easily instantiated for the types declared in the user facility. The linear algebra package is LINRAG2. This package includes subprograms supplementing those in NPO-17985, An Ada Linear Algebra Package Modeled After HAL/S (LINRAG). Please note that LINRAG2 cannot be compiled without LINRAG. Most packages have widespread applicability, although some are oriented for avionics applications. All are designed to facilitate writing new software in Ada. Several of the packages use conventions introduced by other programming languages. A package of string subprograms is based on HAL/S (a language designed for the avionics software in the Space Shuttle) and PL/I. Packages of scalar and array subprograms are taken from HAL/S or generalized current Ada subprograms. A package of Runge-Kutta integrators is patterned after a built-in MAC (MIT Algebraic Compiler) integrator. Those packages modeled after HAL/S make it easy to translate existing HAL/S software to Ada. The General-Purpose Ada Packages program source code is available on two 360K 5.25" MS-DOS format diskettes. The software was developed using VAX Ada v1.5 under DEC VMS v4.5. It should be portable to any validated Ada compiler and it should execute either interactively or in batch. The largest package

  20. Paperless Work Package Application

    SciTech Connect

    Kilgore, Jr., William R.; Morrell, Jr., Otto K.; Morrison, Dan

    2014-07-31

    Paperless Work Package (PWP) System is a computer program process that takes information from Asset Suite, provides a platform for other electronic inputs, Processes the inputs into an electronic package that can be downloaded onto an electronic work tablet or laptop computer, provides a platform for electronic inputs into the work tablet, and then transposes those inputs back into Asset Suite and to permanent SRS records. The PWP System will basically eliminate paper requirements from the maintenance work control system. The program electronically relays the instructions given by the planner to work on a piece of equipment which is currentlymore » relayed via a printed work package. The program does not control/approve what is done. The planner will continue to plan the work package, the package will continue to be routed, approved, and scheduled. The supervisor reviews and approves the work to be performed and assigns work to individuals or to a work group. (The supervisor conducts pre job briefings with the workers involved in the job) The Operations Manager (Work Controlling Entity) approves the work package electronically for the work that will be done in his facility prior to work starting. The PWP System will provide the package in an electronic form. All the reviews, approvals, and safety measures taken by people outside the electronic package does not change from the paper driven work packages.« less

  1. FluxPyt: a Python-based free and open-source software for 13C-metabolic flux analyses.

    PubMed

    Desai, Trunil S; Srivastava, Shireesh

    2018-01-01

    13 C-Metabolic flux analysis (MFA) is a powerful approach to estimate intracellular reaction rates which could be used in strain analysis and design. Processing and analysis of labeling data for calculation of fluxes and associated statistics is an essential part of MFA. However, various software currently available for data analysis employ proprietary platforms and thus limit accessibility. We developed FluxPyt, a Python-based truly open-source software package for conducting stationary 13 C-MFA data analysis. The software is based on the efficient elementary metabolite unit framework. The standard deviations in the calculated fluxes are estimated using the Monte-Carlo analysis. FluxPyt also automatically creates flux maps based on a template for visualization of the MFA results. The flux distributions calculated by FluxPyt for two separate models: a small tricarboxylic acid cycle model and a larger Corynebacterium glutamicum model, were found to be in good agreement with those calculated by a previously published software. FluxPyt was tested in Microsoft™ Windows 7 and 10, as well as in Linux Mint 18.2. The availability of a free and open 13 C-MFA software that works in various operating systems will enable more researchers to perform 13 C-MFA and to further modify and develop the package.

  2. FluxPyt: a Python-based free and open-source software for 13C-metabolic flux analyses

    PubMed Central

    Desai, Trunil S.

    2018-01-01

    13C-Metabolic flux analysis (MFA) is a powerful approach to estimate intracellular reaction rates which could be used in strain analysis and design. Processing and analysis of labeling data for calculation of fluxes and associated statistics is an essential part of MFA. However, various software currently available for data analysis employ proprietary platforms and thus limit accessibility. We developed FluxPyt, a Python-based truly open-source software package for conducting stationary 13C-MFA data analysis. The software is based on the efficient elementary metabolite unit framework. The standard deviations in the calculated fluxes are estimated using the Monte-Carlo analysis. FluxPyt also automatically creates flux maps based on a template for visualization of the MFA results. The flux distributions calculated by FluxPyt for two separate models: a small tricarboxylic acid cycle model and a larger Corynebacterium glutamicum model, were found to be in good agreement with those calculated by a previously published software. FluxPyt was tested in Microsoft™ Windows 7 and 10, as well as in Linux Mint 18.2. The availability of a free and open 13C-MFA software that works in various operating systems will enable more researchers to perform 13C-MFA and to further modify and develop the package. PMID:29736347

  3. Himawari Support In The CSPP-GEO Direct Broadcast Package

    NASA Astrophysics Data System (ADS)

    Cureton, G. P.; Martin, G.

    2016-12-01

    The Cooperative Institute for Meteorological Satellite Studies (CIMSS) has a long history of supporting the Direct Broadcast (DB) community for various sensors, recently with the International MODIS/AIRS Processing Package (IMAPP) for the NASA EOS polar orbiters Terra and Aqua, and the Community Satellite Processing Package (CSPP) for the NOAA polar orbiter Suomi-NPP. CSPP has been significant in encouraging the early usage of Suomi-NPP data by US and international weather agencies, and it is hoped that a new package, CSPP-GEO, will similarly encourage usage of DB data from GOES-R, Himawari, and other geostationary satellites. The support of Himawari-8 provides several challenges for the CSPP-GEO-Geocat package, which generally revolve around the greatly increased data rate associated with the subsatellite point footprint approaching 1km. CSPP-GEO-Geocat takes advantage of python shared-memory multiprocessor support to divide Himawari data into managable pieces, which are then farmed out to indvidual cores for processing by the underlying geocat code. The resulting product segments are then stitched together to make the final product NetCDF4 files. CSPP-GEO-Geocat will support high-data-rate HRIT input, as well as the reduced resolution HimwariCast direct broadcast data stream. Products supported by CSPP-GEO-Geocat include the level-1 reflective and emissive bands, as well as level-2 products like cloud mask, cloud type, optical depth and particle size, cloud top temperature and pressure.

  4. ARM Data-Oriented Metrics and Diagnostics Package for Climate Model Evaluation Value-Added Product

    SciTech Connect

    Zhang, Chengzhu; Xie, Shaocheng

    A Python-based metrics and diagnostics package is currently being developed by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Infrastructure Team at Lawrence Livermore National Laboratory (LLNL) to facilitate the use of long-term, high-frequency measurements from the ARM Facility in evaluating the regional climate simulation of clouds, radiation, and precipitation. This metrics and diagnostics package computes climatological means of targeted climate model simulation and generates tables and plots for comparing the model simulation with ARM observational data. The Coupled Model Intercomparison Project (CMIP) model data sets are also included in the package to enable model intercomparison as demonstratedmore » in Zhang et al. (2017). The mean of the CMIP model can serve as a reference for individual models. Basic performance metrics are computed to measure the accuracy of mean state and variability of climate models. The evaluated physical quantities include cloud fraction, temperature, relative humidity, cloud liquid water path, total column water vapor, precipitation, sensible and latent heat fluxes, and radiative fluxes, with plan to extend to more fields, such as aerosol and microphysics properties. Process-oriented diagnostics focusing on individual cloud- and precipitation-related phenomena are also being developed for the evaluation and development of specific model physical parameterizations. The version 1.0 package is designed based on data collected at ARM’s Southern Great Plains (SGP) Research Facility, with the plan to extend to other ARM sites. The metrics and diagnostics package is currently built upon standard Python libraries and additional Python packages developed by DOE (such as CDMS and CDAT). The ARM metrics and diagnostic package is available publicly with the hope that it can serve as an easy entry point for climate modelers to compare their models with ARM data. In this report, we first present the input data

  5. Nutrition. Learning Activity Package.

    ERIC Educational Resources Information Center

    Lee, Carolyn

    This learning activity package on nutrition is one of a series of 12 titles developed for use in health occupations education programs. Materials in the package include objectives, a list of materials needed, a list of definitions, information sheets, reviews (self evaluations) of portions of the content, and answers to reviews. These topics are…

  6. Packaging and Transportation Safety

    DOT National Transportation Integrated Search

    1997-01-31

    This Guide supplements the Department of Energy (DOE) Order, DOE O 460.1A, PACKAGING AND TRANSPORTATION SAFETY, 10-2-96, by providing clarifying material for the implementation of packaging and transportation safety of hazardous materials. DOE O 460....

  7. Grooming. Learning Activity Package.

    ERIC Educational Resources Information Center

    Stark, Pamela

    This learning activity package on grooming for health workers is one of a series of 12 titles developed for use in health occupations education programs. Materials in the package include objectives, a list of materials needed, information sheets, reviews (self evaluations) of portions of the content, and answers to reviews. These topics are…

  8. Modular electronics packaging system

    NASA Technical Reports Server (NTRS)

    Hunter, Don J. (Inventor)

    2001-01-01

    A modular electronics packaging system includes multiple packaging slices that are mounted horizontally to a base structure. The slices interlock to provide added structural support. Each packaging slice includes a rigid and thermally conductive housing having four side walls that together form a cavity to house an electronic circuit. The chamber is enclosed on one end by an end wall, or web, that isolates the electronic circuit from a circuit in an adjacent packaging slice. The web also provides a thermal path between the electronic circuit and the base structure. Each slice also includes a mounting bracket that connects the packaging slice to the base structure. Four guide pins protrude from the slice into four corresponding receptacles in an adjacent slice. A locking element, such as a set screw, protrudes into each receptacle and interlocks with the corresponding guide pin. A conduit is formed in the slice to allow electrical connection to the electronic circuit.

  9. New Finsler package

    NASA Astrophysics Data System (ADS)

    Youssef, Nabil L.; Elgendi, S. G.

    2014-03-01

    The book “Handbook of Finsler geometry” has been included with a CD containing an elegant Maple package, FINSLER, for calculations in Finsler geometry. Using this package, an example concerning a Finsler generalization of Einstein’s vacuum field equations was treated. In this example, the calculation of the components of the hv-curvature of Cartan connection leads to wrong expressions. On the other hand, the FINSLER package works only in dimension four. We introduce a new Finsler package in which we fix the two problems and solve them. Moreover, we extend this package to compute not only the geometric objects associated with Cartan connection but also those associated with Berwald, Chern and Hashiguchi connections in any dimension. These improvements have been illustrated by a concrete example. Furthermore, the problem of simplifying tensor expressions is treated. This paper is intended to make calculations in Finsler geometry more easier and simpler.

  10. Bayesian mixture analysis for metagenomic community profiling.

    PubMed

    Morfopoulou, Sofia; Plagnol, Vincent

    2015-09-15

    Deep sequencing of clinical samples is now an established tool for the detection of infectious pathogens, with direct medical applications. The large amount of data generated produces an opportunity to detect species even at very low levels, provided that computational tools can effectively profile the relevant metagenomic communities. Data interpretation is complicated by the fact that short sequencing reads can match multiple organisms and by the lack of completeness of existing databases, in particular for viral pathogens. Here we present metaMix, a Bayesian mixture model framework for resolving complex metagenomic mixtures. We show that the use of parallel Monte Carlo Markov chains for the exploration of the species space enables the identification of the set of species most likely to contribute to the mixture. We demonstrate the greater accuracy of metaMix compared with relevant methods, particularly for profiling complex communities consisting of several related species. We designed metaMix specifically for the analysis of deep transcriptome sequencing datasets, with a focus on viral pathogen detection; however, the principles are generally applicable to all types of metagenomic mixtures. metaMix is implemented as a user friendly R package, freely available on CRAN: http://cran.r-project.org/web/packages/metaMix sofia.morfopoulou.10@ucl.ac.uk Supplementary data are available at Bionformatics online. © The Author 2015. Published by Oxford University Press.

  11. The Discovery of XY Sex Chromosomes in a Boa and Python.

    PubMed

    Gamble, Tony; Castoe, Todd A; Nielsen, Stuart V; Banks, Jaison L; Card, Daren C; Schield, Drew R; Schuett, Gordon W; Booth, Warren

    2017-07-24

    For over 50 years, biologists have accepted that all extant snakes share the same ZW sex chromosomes derived from a common ancestor [1-3], with different species exhibiting sex chromosomes at varying stages of differentiation. Accordingly, snakes have been a well-studied model for sex chromosome evolution in animals [1, 4]. A review of the literature, however, reveals no compelling support that boas and pythons possess ZW sex chromosomes [2, 5]. Furthermore, phylogenetic patterns of facultative parthenogenesis in snakes and a sex-linked color mutation in the ball python (Python regius) are best explained by boas and pythons possessing an XY sex chromosome system [6, 7]. Here we demonstrate that a boa (Boa imperator) and python (Python bivittatus) indeed possess XY sex chromosomes, based on the discovery of male-specific genetic markers in both species. We use these markers, along with transcriptomic and genomic data, to identify distinct sex chromosomes in boas and pythons, demonstrating that XY systems evolved independently in each lineage. This discovery highlights the dynamic evolution of vertebrate sex chromosomes and further enhances the value of snakes as a model for studying sex chromosome evolution. Copyright © 2017 Elsevier Ltd. All rights reserved.

  12. 49 CFR 173.193 - Bromoacetone, methyl bromide, chloropicrin and methyl bromide or methyl chloride mixtures, etc.

    Code of Federal Regulations, 2012 CFR

    2012-10-01

    ... packaged as follows in wooden boxes (4C1, 4C2, 4D or 4F) with inner glass receptacles or tubes in... material. Total amount of liquid in the outer box must not exceed 11 kg (24 pounds). Packagings must... bromide mixtures containing up to 2% chloropicrin must be packaged in 4G fiberboard boxes with inside...

  13. 49 CFR 173.193 - Bromoacetone, methyl bromide, chloropicrin and methyl bromide or methyl chloride mixtures, etc.

    Code of Federal Regulations, 2011 CFR

    2011-10-01

    ... packaged as follows in wooden boxes (4C1, 4C2, 4D or 4F) with inner glass receptacles or tubes in... material. Total amount of liquid in the outer box must not exceed 11 kg (24 pounds). Packagings must... bromide mixtures containing up to 2% chloropicrin must be packaged in 4G fiberboard boxes with inside...

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

    PubMed

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

    2014-07-01

    Interspecific allometric analyses indicate that mean arterial blood pressure (MAP) increases with body mass of snakes and mammals. In snakes, MAP increases in proportion to the increased distance between the heart and the head, when the heart-head vertical distance is expressed as ρgh (where ρ is the density of blood, G: is acceleration due to gravity and h is the vertical distance above the heart), and the rise in MAP is associated with a larger heart to normalize wall stress in the ventricular wall. Based on measurements of MAP in Burmese pythons ranging from 0.9 to 3.7 m in length (0.20-27 kg), we demonstrate that although MAP increases with body mass, the rise in MAP is merely half of that predicted by heart-head distance. Scaling relationships within individual species, therefore, may not be accurately predicted by existing interspecific analyses. © 2014. Published by The Company of Biologists Ltd.

  15. Oral flora of Python regius kept as pets.

    PubMed

    Dipineto, L; Russo, T P; Calabria, M; De Rosa, L; Capasso, M; Menna, L F; Borrelli, L; Fioretti, A

    2014-05-01

    This study was aimed at evaluating the oral bacterial flora of 60 Python regius kept as pets by culture and biochemical methods. All isolates were also submitted to antimicrobial susceptibility testing using the disc diffusion method. The oral cavity of snakes sampled harboured a wide range of Gram-negative bacteria mainly constituted by Pseudomonas spp., Morganella morganii, Acinetobacter calcoaceticus, Aeromonas hydrophila, but also by Salmonella spp. Staphylococcus spp. was the commonest Gram-positive isolates, and various anaerobic Clostridium species were also found. The most effective antimicrobial agents were enrofloxacin and ciprofloxacin, followed by doxycycline and gentamicin. The oral cavity of snakes sampled harboured a wide range of bacteria. Our results suggest that people who come in contact with snakes could be at risk of infection and should follow proper hygiene practices when handling these reptiles. © 2014 The Society for Applied Microbiology.

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

    PubMed

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

    2012-12-01

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

  17. 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. Wemore » also compare PyORBIT to ORBIT from the standpoint of features, performance and future expandability.« less

  18. A Python Script for Aligning the STIS Echelle Blaze Function

    NASA Astrophysics Data System (ADS)

    Baer, Malinda; Proffitt, Charles R.; Lockwood, Sean A.

    2018-01-01

    Accurate flux calibration for the STIS echelle modes is heavily dependent on the proper alignment of the blaze function for each spectral order. However, due to changes in the instrument alignment over time and between exposures, the blaze function can shift in wavelength. This may result in flux calibration inconsistencies of up to 10%. We present the stisblazefix Python module as a tool for STIS users to correct their echelle spectra. The stisblazefix module assumes that the error in the blaze alignment is a linear function of spectral order, and finds the set of shifts that minimizes the flux inconsistencies in the overlap between spectral orders. We discuss the uses and limitations of this tool, and show that its use can provide significant improvements to the default pipeline flux calibration for many observations.

  19. htsint: a Python library for sequencing pipelines that combines data through gene set generation.

    PubMed

    Richards, Adam J; Herrel, Anthony; Bonneaud, Camille

    2015-09-24

    Sequencing technologies provide a wealth of details in terms of genes, expression, splice variants, polymorphisms, and other features. A standard for sequencing analysis pipelines is to put genomic or transcriptomic features into a context of known functional information, but the relationships between ontology terms are often ignored. For RNA-Seq, considering genes and their genetic variants at the group level enables a convenient way to both integrate annotation data and detect small coordinated changes between experimental conditions, a known caveat of gene level analyses. We introduce the high throughput data integration tool, htsint, as an extension to the commonly used gene set enrichment frameworks. The central aim of htsint is to compile annotation information from one or more taxa in order to calculate functional distances among all genes in a specified gene space. Spectral clustering is then used to partition the genes, thereby generating functional modules. The gene space can range from a targeted list of genes, like a specific pathway, all the way to an ensemble of genomes. Given a collection of gene sets and a count matrix of transcriptomic features (e.g. expression, polymorphisms), the gene sets produced by htsint can be tested for 'enrichment' or conditional differences using one of a number of commonly available packages. The database and bundled tools to generate functional modules were designed with sequencing pipelines in mind, but the toolkit nature of htsint allows it to also be used in other areas of genomics. The software is freely available as a Python library through GitHub at https://github.com/ajrichards/htsint.

  20. MagPy: A Python toolbox for controlling Magstim transcranial magnetic stimulators.

    PubMed

    McNair, Nicolas A

    2017-01-30

    To date, transcranial magnetic stimulation (TMS) studies manipulating stimulation parameters have largely used blocked paradigms. However, altering these parameters on a trial-by-trial basis in Magstim stimulators is complicated by the need to send regular (1Hz) commands to the stimulator. Additionally, effecting such control interferes with the ability to send TMS pulses or simultaneously present stimuli with high-temporal precision. This manuscript presents the MagPy toolbox, a Python software package that provides full control over Magstim stimulators via the serial port. It is able to maintain this control with no impact on concurrent processing, such as stimulus delivery. In addition, a specially-designed "QuickFire" serial cable is specified that allows MagPy to trigger TMS pulses with very low-latency. In a series of experimental simulations, MagPy was able to maintain uninterrupted remote control over the connected Magstim stimulator across all testing sessions. In addition, having MagPy enabled had no effect on stimulus timing - all stimuli were presented for precisely the duration specified. Finally, using the QuickFire cable, MagPy was able to elicit TMS pulses with sub-millisecond latencies. The MagPy toolbox allows for experiments that require manipulating stimulation parameters from trial to trial. Furthermore, it can achieve this in contexts that require tight control over timing, such as those seeking to combine TMS with fMRI or EEG. Together, the MagPy toolbox and QuickFire serial cable provide an effective means for controlling Magstim stimulators during experiments while ensuring high-precision timing. Copyright © 2016 Elsevier B.V. All rights reserved.

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

    PubMed

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

    2011-12-01

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

  2. Tachycardia in response to remote capsaicin injection as a model for nociception in the ball python (Python regius).

    PubMed

    Williams, Catherine J A; James, Lauren E; Bertelsen, Mads F; Wang, Tobias

    2016-07-01

    To quantify the effect of subcutaneous (SC) capsaicin injection on heart rate (HR) in ball pythons (Python regius) and to assess the efficacy of two opioids (morphine and butorphanol) in modifying this response. Prospective, randomized, unmatched study. Eleven mixed-sex, captive-bred ball pythons. Snakes were randomly assigned to three groups (n = 6) by intramuscular premedication: 1) control: saline (0.9 mL); 2) morphine (10 mg kg(-1) ); and 3) butorphanol (10 mg kg(-1) ). Three snakes were tested twice and another two were tested three times in different treatments administered 1 month apart. Under isoflurane anaesthesia, snakes were instrumented with SC electrocardiogram (ECG) electrodes and an SC catheter for remote stimulus delivery. After recovery from anaesthesia, all snakes, in visual and audial isolation from the experimenter, received a sham stimulus of saline (0.4 mL) via the SC catheter. A nociceptive stimulus of SC capsaicin (3 mg in 0.2 mL saline with 7% Tween 80) was then applied by catheter at 7 hours after premedication. In a subset (n = 3), two sham injections (saline 0.2 mL) preceded the capsaicin treatment. HR was recorded via ECG, and changes in HR (ΔHR) from baseline were calculated for all stimulations. Capsaicin injection was associated with a significant increase in HR [peak ΔHR: saline group: 8.8 ± 7.1 beats minute(-1) ; capsaicin group: 21.1 ± 5.8 beats minute(-1) (p = 0.0055)] and integrated ΔHR as a function of time. The administration of morphine or butorphanol 7 hours prior to nociception failed to significantly reduce the peak and integrated ΔHR. Butorphanol caused marked, long-lasting sedation as assessed by muscle tone. The HR response to an SC capsaicin injection can serve as a nociceptive model in P. regius. Morphine and butorphanol administration did not reduce HR response to capsaicin stimulation but produced significantly different effects on pre-stimulation HR and sedation. © 2015 Association

  3. pymzML--Python module for high-throughput bioinformatics on mass spectrometry data.

    PubMed

    Bald, Till; Barth, Johannes; Niehues, Anna; Specht, Michael; Hippler, Michael; Fufezan, Christian

    2012-04-01

    pymzML is an extension to Python that offers (i) an easy access to mass spectrometry (MS) data that allows the rapid development of tools, (ii) a very fast parser for mzML data, the standard data format in MS and (iii) a set of functions to compare or handle spectra. pymzML requires Python2.6.5+ and is fully compatible with Python3. The module is freely available on http://pymzml.github.com or pypi, is published under LGPL license and requires no additional modules to be installed. christian@fufezan.net.

  4. 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.

  5. Packaging Concerns/Techniques for Large Devices

    NASA Technical Reports Server (NTRS)

    Sampson, Michael J.

    2009-01-01

    This slide presentation reviews packaging challenges and options for electronic parts. The presentation includes information about non-hermetic packages, space challenges for packaging and complex package variations.

  6. ViSAPy: a Python tool for biophysics-based generation of virtual spiking activity for evaluation of spike-sorting algorithms.

    PubMed

    Hagen, Espen; Ness, Torbjørn V; Khosrowshahi, Amir; Sørensen, Christina; Fyhn, Marianne; Hafting, Torkel; Franke, Felix; Einevoll, Gaute T

    2015-04-30

    New, silicon-based multielectrodes comprising hundreds or more electrode contacts offer the possibility to record spike trains from thousands of neurons simultaneously. This potential cannot be realized unless accurate, reliable automated methods for spike sorting are developed, in turn requiring benchmarking data sets with known ground-truth spike times. We here present a general simulation tool for computing benchmarking data for evaluation of spike-sorting algorithms entitled ViSAPy (Virtual Spiking Activity in Python). The tool is based on a well-established biophysical forward-modeling scheme and is implemented as a Python package built on top of the neuronal simulator NEURON and the Python tool LFPy. ViSAPy allows for arbitrary combinations of multicompartmental neuron models and geometries of recording multielectrodes. Three example benchmarking data sets are generated, i.e., tetrode and polytrode data mimicking in vivo cortical recordings and microelectrode array (MEA) recordings of in vitro activity in salamander retinas. The synthesized example benchmarking data mimics salient features of typical experimental recordings, for example, spike waveforms depending on interspike interval. ViSAPy goes beyond existing methods as it includes biologically realistic model noise, synaptic activation by recurrent spiking networks, finite-sized electrode contacts, and allows for inhomogeneous electrical conductivities. ViSAPy is optimized to allow for generation of long time series of benchmarking data, spanning minutes of biological time, by parallel execution on multi-core computers. ViSAPy is an open-ended tool as it can be generalized to produce benchmarking data or arbitrary recording-electrode geometries and with various levels of complexity. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

  7. Packaging for Posterity.

    ERIC Educational Resources Information Center

    Sias, Jim

    1990-01-01

    A project in which students designed environmentally responsible food packaging is described. The problem definition; research on topics such as waste paper, plastic, metal, glass, incineration, recycling, and consumer preferences; and the presentation design are provided. (KR)

  8. Battery packaging - Technology review

    SciTech Connect

    Maiser, Eric

    2014-06-16

    This paper gives a brief overview of battery packaging concepts, their specific advantages and drawbacks, as well as the importance of packaging for performance and cost. Production processes, scaling and automation are discussed in detail to reveal opportunities for cost reduction. Module standardization as an additional path to drive down cost is introduced. A comparison to electronics and photovoltaics production shows 'lessons learned' in those related industries and how they can accelerate learning curves in battery production.

  9. The ENSDF Java Package

    SciTech Connect

    Sonzogni, A.A.

    2005-05-24

    A package of computer codes has been developed to process and display nuclear structure and decay data stored in the ENSDF (Evaluated Nuclear Structure Data File) library. The codes were written in an object-oriented fashion using the java language. This allows for an easy implementation across multiple platforms as well as deployment on web pages. The structure of the different java classes that make up the package is discussed as well as several different implementations.

  10. 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

  11. 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.

  12. Planetary Geologic Mapping Python Toolbox: A Suite of Tools to Support Mapping Workflows

    NASA Astrophysics Data System (ADS)

    Hunter, M. A.; Skinner, J. A.; Hare, T. M.; Fortezzo, C. M.

    2017-06-01

    The collective focus of the Planetary Geologic Mapping Python Toolbox is to provide researchers with additional means to migrate legacy GIS data, assess the quality of data and analysis results, and simplify common mapping tasks.

  13. Comparative Packaging Study

    NASA Technical Reports Server (NTRS)

    Perchonok, Michele H.; Oziomek, Thomas V.

    2009-01-01

    Future long duration manned space flights beyond low earth orbit will require the food system to remain safe, acceptable and nutritious. Development of high barrier food packaging will enable this requirement by preventing the ingress and egress of gases and moisture. New high barrier food packaging materials have been identified through a trade study. Practical application of this packaging material within a shelf life test will allow for better determination of whether this material will allow the food system to meet given requirements after the package has undergone processing. The reason to conduct shelf life testing, using a variety of packaging materials, stems from the need to preserve food used for mission durations of several years. Chemical reactions that take place during longer durations may decrease food quality to a point where crew physical or psychological well-being is compromised. This can result in a reduction or loss of mission success. The rate of chemical reactions, including oxidative rancidity and staling, can be controlled by limiting the reactants, reducing the amount of energy available to drive the reaction, and minimizing the amount of water available. Water not only acts as a media for microbial growth, but also as a reactant and means by which two reactants may come into contact with each other. The objective of this study is to evaluate three packaging materials for potential use in long duration space exploration missions.

  14. Solvation Structure and Thermodynamic Mapping (SSTMap): An Open-Source, Flexible Package for the Analysis of Water in Molecular Dynamics Trajectories.

    PubMed

    Haider, Kamran; Cruz, Anthony; Ramsey, Steven; Gilson, Michael K; Kurtzman, Tom

    2018-01-09

    We have developed SSTMap, a software package for mapping structural and thermodynamic water properties in molecular dynamics trajectories. The package introduces automated analysis and mapping of local measures of frustration and enhancement of water structure. The thermodynamic calculations are based on Inhomogeneous Fluid Solvation Theory (IST), which is implemented using both site-based and grid-based approaches. The package also extends the applicability of solvation analysis calculations to multiple molecular dynamics (MD) simulation programs by using existing cross-platform tools for parsing MD parameter and trajectory files. SSTMap is implemented in Python and contains both command-line tools and a Python module to facilitate flexibility in setting up calculations and for automated generation of large data sets involving analysis of multiple solutes. Output is generated in formats compatible with popular Python data science packages. This tool will be used by the molecular modeling community for computational analysis of water in problems of biophysical interest such as ligand binding and protein function.

  15. 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

  16. Sharma's Python Sign: A New Tubal Sign in Female Genital Tuberculosis

    PubMed Central

    Sharma, Jai Bhagwan

    2016-01-01

    Female genital tuberculosis (FGTB) is an important cause of infertility in developing countries. Various type of TB salpingitis can be endosalpingitis, exosalpingitis, interstitial TB salpingitis, and salpingitis isthmica nodosa. The fallopian tubes are thickened enlarged and tortuous. Unilateral or bilateral hydrosalpinx or pyosalpinx may be formed. A new sign python sign is presented in which fallopian tube looks like a blue python on dye testing in FGTB. PMID:27365923

  17. Sharma's Python Sign: A New Tubal Sign in Female Genital Tuberculosis.

    PubMed

    Sharma, Jai Bhagwan

    2016-01-01

    Female genital tuberculosis (FGTB) is an important cause of infertility in developing countries. Various type of TB salpingitis can be endosalpingitis, exosalpingitis, interstitial TB salpingitis, and salpingitis isthmica nodosa. The fallopian tubes are thickened enlarged and tortuous. Unilateral or bilateral hydrosalpinx or pyosalpinx may be formed. A new sign python sign is presented in which fallopian tube looks like a blue python on dye testing in FGTB.

  18. 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

  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

  20. 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.

  1. Lenstronomy: Multi-purpose gravitational lens modeling software package

    NASA Astrophysics Data System (ADS)

    Birrer, Simon; Amara, Adam

    2018-04-01

    Lenstronomy is a multi-purpose open-source gravitational lens modeling python package. Lenstronomy reconstructs the lens mass and surface brightness distributions of strong lensing systems using forward modelling and supports a wide range of analytic lens and light models in arbitrary combination. The software is also able to reconstruct complex extended sources as well as point sources. Lenstronomy is flexible and numerically accurate, with a clear user interface that could be deployed across different platforms. Lenstronomy has been used to derive constraints on dark matter properties in strong lenses, measure the expansion history of the universe with time-delay cosmography, measure cosmic shear with Einstein rings, and decompose quasar and host galaxy light.

  2. RH Packaging Program Guidance

    SciTech Connect

    Washington TRU Solutions LLC

    The purpose of this program guidance document is to provide the technical requirements for use, operation, inspection, and maintenance of the RH-TRU 72-B Waste Shipping Package (also known as the "RH-TRU 72-B cask") and directly related components. This document complies with the requirements as specified in the RH-TRU 72-B Safety Analysis Report for Packaging (SARP), and Nuclear Regulatory Commission (NRC) Certificate of Compliance (C of C) 9212. If there is a conflict between this document and the SARP and/or C of C, the C of C shall govern. The C of C states: "...each package must be prepared for shipmentmore » and operated in accordance with the procedures described in Chapter 7.0, Operating Procedures, of the application." It further states: "...each package must be tested and maintained in accordance with the procedures described in Chapter 8.0, Acceptance Tests and Maintenance Program of the Application." Chapter 9.0 of the SARP tasks the Waste Isolation Pilot Plant (WIPP) Management and Operating (M&O) Contractor with assuring the packaging is used in accordance with the requirements of the C of C. Because the packaging is NRC-approved, users need to be familiar with Title 10 Code of Federal Regulations (CFR) §71.8, "Deliberate Misconduct." Any time a user suspects or has indications that the conditions of approval in the C of C were not met, the U.S. Department of Energy (DOE) Carlsbad Field Office (CBFO) shall be notified immediately. The CBFO will evaluate the issue and notify the NRC if required.In accordance with 10 CFR Part 71, "Packaging and Transportation of Radioactive Material," certificate holders, packaging users, and contractors or subcontractors who use, design, fabricate, test, maintain, or modify the packaging shall post copies of (1) 10 CFR Part 21, "Reporting of Defects and Noncompliance," regulations, (2) Section 206 of the Energy Reorganization Act of 1974, and (3) NRC Form 3, Notice to Employees. These documents must be posted in a

  3. RH Packaging Program Guidance

    SciTech Connect

    Washington TRU Solutions LLC

    The purpose of this program guidance document is to provide the technical requirements for use, operation, inspection, and maintenance of the RH-TRU 72-B Waste Shipping Package and directly related components. This document complies with the requirements as specified in the RH-TRU 72-B Safety Analysis Report for Packaging (SARP), and Nuclear Regulatory Commission (NRC) Certificate of Compliance (C of C) 9212. If there is a conflict between this document and the SARP and/or C of C, the C of C shall govern. The C of C states: "...each package must be prepared for shipment and operated in accordance with the proceduresmore » described in Chapter 7.0, Operating Procedures, of the application." It further states: "...each package must be tested and maintained in accordance with the procedures described in Chapter 8.0, Acceptance Tests and Maintenance Program of the Application." Chapter 9.0 of the SARP tasks the Waste Isolation Pilot Plant (WIPP) Management and Operating (M&O) Contractor with assuring the packaging is used in accordance with the requirements of the C of C. Because the packaging is NRC-approved, users need to be familiar with 10 Code of Federal Regulations (CFR) §71.8, "Deliberate Misconduct." Any time a user suspects or has indications that the conditions of approval in the C of C were not met, the U.S. Department of Energy (DOE) Carlsbad Field Office (CBFO) shall be notified immediately. CBFO will evaluate the issue and notify the NRC if required. In accordance with 10 CFR Part 71, "Packaging and Transportation of Radioactive Material," certificate holders, packaging users, and contractors or subcontractors who use, design, fabricate, test, maintain, or modify the packaging shall post copies of (1) 10 CFR Part 21, "Reporting of Defects and Noncompliance," regulations, (2) Section 206 of the Energy Reorganization Act of 1974, and (3) NRC Form 3, Notice to Employees. These documents must be posted in a conspicuous location where the activities subject

  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.; 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. 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. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

  6. pyPaSWAS: Python-based multi-core CPU and GPU sequence alignment.

    PubMed

    Warris, Sven; Timal, N Roshan N; Kempenaar, Marcel; Poortinga, Arne M; van de Geest, Henri; Varbanescu, Ana L; Nap, Jan-Peter

    2018-01-01

    Our previously published CUDA-only application PaSWAS for Smith-Waterman (SW) sequence alignment of any type of sequence on NVIDIA-based GPUs is platform-specific and therefore adopted less than could be. The OpenCL language is supported more widely and allows use on a variety of hardware platforms. Moreover, there is a need to promote the adoption of parallel computing in bioinformatics by making its use and extension more simple through more and better application of high-level languages commonly used in bioinformatics, such as Python. The novel application pyPaSWAS presents the parallel SW sequence alignment code fully packed in Python. It is a generic SW implementation running on several hardware platforms with multi-core systems and/or GPUs that provides accurate sequence alignments that also can be inspected for alignment details. Additionally, pyPaSWAS support the affine gap penalty. Python libraries are used for automated system configuration, I/O and logging. This way, the Python environment will stimulate further extension and use of pyPaSWAS. pyPaSWAS presents an easy Python-based environment for accurate and retrievable parallel SW sequence alignments on GPUs and multi-core systems. The strategy of integrating Python with high-performance parallel compute languages to create a developer- and user-friendly environment should be considered for other computationally intensive bioinformatics algorithms.

  7. Application of GA package in functional packaging

    NASA Astrophysics Data System (ADS)

    Belousova, D. A.; Noskova, E. E.; Kapulin, D. V.

    2018-05-01

    The approach to application program for the task of configuration of the elements of the commutation circuit for design of the radio-electronic equipment on the basis of the genetic algorithm is offered. The efficiency of the used approach for commutation circuits with different characteristics for computer-aided design on radio-electronic manufacturing is shown. The prototype of the computer-aided design subsystem on the basis of a package GA for R with a set of the general functions for optimization of multivariate models is programmed.

  8. Food Packaging Materials

    NASA Technical Reports Server (NTRS)

    1978-01-01

    The photos show a few of the food products packaged in Alure, a metallized plastic material developed and manufactured by St. Regis Paper Company's Flexible Packaging Division, Dallas, Texas. The material incorporates a metallized film originally developed for space applications. Among the suppliers of the film to St. Regis is King-Seeley Thermos Company, Winchester, Ma'ssachusetts. Initially used by NASA as a signal-bouncing reflective coating for the Echo 1 communications satellite, the film was developed by a company later absorbed by King-Seeley. The metallized film was also used as insulating material for components of a number of other spacecraft. St. Regis developed Alure to meet a multiple packaging material need: good eye appeal, product protection for long periods and the ability to be used successfully on a wide variety of food packaging equipment. When the cost of aluminum foil skyrocketed, packagers sought substitute metallized materials but experiments with a number of them uncovered problems; some were too expensive, some did not adequately protect the product, some were difficult for the machinery to handle. Alure offers a solution. St. Regis created Alure by sandwiching the metallized film between layers of plastics. The resulting laminated metallized material has the superior eye appeal of foil but is less expensive and more easily machined. Alure effectively blocks out light, moisture and oxygen and therefore gives the packaged food long shelf life. A major packaging firm conducted its own tests of the material and confirmed the advantages of machinability and shelf life, adding that it runs faster on machines than materials used in the past and it decreases product waste; the net effect is increased productivity.

  9. Food packages for Space Shuttle

    NASA Technical Reports Server (NTRS)

    Fohey, M. F.; Sauer, R. L.; Westover, J. B.; Rockafeller, E. F.

    1978-01-01

    The paper reviews food packaging techniques used in space flight missions and describes the system developed for the Space Shuttle. Attention is directed to bite-size food cubes used in Gemini, Gemini rehydratable food packages, Apollo spoon-bowl rehydratable packages, thermostabilized flex pouch for Apollo, tear-top commercial food cans used in Skylab, polyethylene beverage containers, Skylab rehydratable food package, Space Shuttle food package configuration, duck-bill septum rehydration device, and a drinking/dispensing nozzle for Space Shuttle liquids. Constraints and testing of packaging is considered, a comparison of food package materials is presented, and typical Shuttle foods and beverages are listed.

  10. Detecting small holes in packages

    DOEpatents

    Kronberg, James W.; Cadieux, James R.

    1996-01-01

    A package containing a tracer gas, and a method for determining the presence of a hole in the package by sensing the presence of the gas outside the package. The preferred tracer gas, especially for food packaging, is sulfur hexafluoride. A quantity of the gas is added to the package and the package is closed. The concentration of the gas in the atmosphere outside the package is measured and compared to a predetermined value of the concentration of the gas in the absence of the package. A measured concentration greater than the predetermined value indicates the presence of a hole in the package. Measuring may be done in a chamber having a lower pressure than that in the package.

  11. Detecting small holes in packages

    DOEpatents

    Kronberg, J.W.; Cadieux, J.R.

    1996-03-19

    A package containing a tracer gas, and a method for determining the presence of a hole in the package by sensing the presence of the gas outside the package are disclosed. The preferred tracer gas, especially for food packaging, is sulfur hexafluoride. A quantity of the gas is added to the package and the package is closed. The concentration of the gas in the atmosphere outside the package is measured and compared to a predetermined value of the concentration of the gas in the absence of the package. A measured concentration greater than the predetermined value indicates the presence of a hole in the package. Measuring may be done in a chamber having a lower pressure than that in the package. 3 figs.

  12. GOGrapher: A Python library for GO graph representation and analysis

    PubMed Central

    Muller, Brian; Richards, Adam J; Jin, Bo; Lu, Xinghua

    2009-01-01

    Background The Gene Ontology is the most commonly used controlled vocabulary for annotating proteins. The concepts in the ontology are organized as a directed acyclic graph, in which a node corresponds to a biological concept and a directed edge denotes the parent-child semantic relationship between a pair of terms. A large number of protein annotations further create links between proteins and their functional annotations, reflecting the contemporary knowledge about proteins and their functional relationships. This leads to a complex graph consisting of interleaved biological concepts and their associated proteins. What is needed is a simple, open source library that provides tools to not only create and view the Gene Ontology graph, but to analyze and manipulate it as well. Here we describe the development and use of GOGrapher, a Python library that can be used for the creation, analysis, manipulation, and visualization of Gene Ontology related graphs. Findings An object-oriented approach was adopted to organize the hierarchy of the graphs types and associated classes. An Application Programming Interface is provided through which different types of graphs can be pragmatically created, manipulated, and visualized. GOGrapher has been successfully utilized in multiple research projects, e.g., a graph-based multi-label text classifier for protein annotation. Conclusion The GOGrapher project provides a reusable programming library designed for the manipulation and analysis of Gene Ontology graphs. The library is freely available for the scientific community to use and improve. PMID:19583843

  13. GOGrapher: A Python library for GO graph representation and analysis.

    PubMed

    Muller, Brian; Richards, Adam J; Jin, Bo; Lu, Xinghua

    2009-07-07

    The Gene Ontology is the most commonly used controlled vocabulary for annotating proteins. The concepts in the ontology are organized as a directed acyclic graph, in which a node corresponds to a biological concept and a directed edge denotes the parent-child semantic relationship between a pair of terms. A large number of protein annotations further create links between proteins and their functional annotations, reflecting the contemporary knowledge about proteins and their functional relationships. This leads to a complex graph consisting of interleaved biological concepts and their associated proteins. What is needed is a simple, open source library that provides tools to not only create and view the Gene Ontology graph, but to analyze and manipulate it as well. Here we describe the development and use of GOGrapher, a Python library that can be used for the creation, analysis, manipulation, and visualization of Gene Ontology related graphs. An object-oriented approach was adopted to organize the hierarchy of the graphs types and associated classes. An Application Programming Interface is provided through which different types of graphs can be pragmatically created, manipulated, and visualized. GOGrapher has been successfully utilized in multiple research projects, e.g., a graph-based multi-label text classifier for protein annotation. The GOGrapher project provides a reusable programming library designed for the manipulation and analysis of Gene Ontology graphs. The library is freely available for the scientific community to use and improve.

  14. Gastric adenocarcinoma in a diamond python (Morelia spilota spilota).

    PubMed

    Baron, H R; Allavena, R; Melville, L M; Doneley, R J T

    2014-10-01

    A 5-year-old captive male diamond python (Morelia spilota spilota) was presented with a 1-month history of regurgitation and anorexia and discrete coelomic distention. Physical examination revealed a firm, immobile mass at approximately two-thirds of the snout-vent length from the front of the head. Ultrasound-guided fine needle aspirate biopsy of the mass in the region of the stomach showed necrosis with bacterial infiltration and possibly neoplastic changes. A gastroscopy was conducted, but showed grossly normal gastric mucosa, confirmed by biopsy. On exploratory coeliotomy, it was confirmed the mass involved most of the stomach wall and occluded the gastric lumen. The mass was completely excised and based on histopathology, a diagnosis of gastric adenocarcinoma was made. The snake was found dead 12 h postoperatively, but no specific cause of death was found on postmortem examination. Most cases of adenocarcinoma in snakes go undiagnosed. This case report illustrates that the architecture of gastric masses may lead to false-negative gastric biopsy results in snakes with neoplasia. © 2014 Australian Veterinary Association.

  15. Programming PHREEQC calculations with C++ and Python a comparative study

    USGS Publications Warehouse

    Charlton, Scott R.; Parkhurst, David L.; Muller, Mike

    2011-01-01

    The new IPhreeqc module provides an application programming interface (API) to facilitate coupling of other codes with the U.S. Geological Survey geochemical model PHREEQC. Traditionally, loose coupling of PHREEQC with other applications required methods to create PHREEQC input files, start external PHREEQC processes, and process PHREEQC output files. IPhreeqc eliminates most of this effort by providing direct access to PHREEQC capabilities through a component object model (COM), a library, or a dynamically linked library (DLL). Input and calculations can be specified through internally programmed strings, and all data exchange between an application and the module can occur in computer memory. This study compares simulations programmed in C++ and Python that are tightly coupled with IPhreeqc modules to the traditional simulations that are loosely coupled to PHREEQC. The study compares performance, quantifies effort, and evaluates lines of code and the complexity of the design. The comparisons show that IPhreeqc offers a more powerful and simpler approach for incorporating PHREEQC calculations into transport models and other applications that need to perform PHREEQC calculations. The IPhreeqc module facilitates the design of coupled applications and significantly reduces run times. Even a moderate knowledge of one of the supported programming languages allows more efficient use of PHREEQC than the traditional loosely coupled approach.

  16. A python framework for environmental model uncertainty analysis

    USGS Publications Warehouse

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

    2016-01-01

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

  17. AESOP: A Python Library for Investigating Electrostatics in Protein Interactions.

    PubMed

    Harrison, Reed E S; Mohan, Rohith R; Gorham, Ronald D; Kieslich, Chris A; Morikis, Dimitrios

    2017-05-09

    Electric fields often play a role in guiding the association of protein complexes. Such interactions can be further engineered to accelerate complex association, resulting in protein systems with increased productivity. This is especially true for enzymes where reaction rates are typically diffusion limited. To facilitate quantitative comparisons of electrostatics in protein families and to describe electrostatic contributions of individual amino acids, we previously developed a computational framework called AESOP. We now implement this computational tool in Python with increased usability and the capability of performing calculations in parallel. AESOP utilizes PDB2PQR and Adaptive Poisson-Boltzmann Solver to generate grid-based electrostatic potential files for protein structures provided by the end user. There are methods within AESOP for quantitatively comparing sets of grid-based electrostatic potentials in terms of similarity or generating ensembles of electrostatic potential files for a library of mutants to quantify the effects of perturbations in protein structure and protein-protein association. Copyright © 2017 Biophysical Society. Published by Elsevier Inc. All rights reserved.

  18. Python-Based Tool for Universal Nuclear Data Extraction

    NASA Astrophysics Data System (ADS)

    McDonald, William; Blair, Hayden; Consalvi, Peter; Garbiso, Markus; Grover, Hannah; Harget, Alex; Martin, Matthew; Natzke, Connor; Leach, Kyle

    2017-09-01

    Over the past 70 years, nuclear physics experiments have provided a vast wealth of experimental data on both ground and excited state properties across the nuclear chart. In many cases, searching for and parsing the relevant nuclear structure data from previous work can be tedious and difficult. Although the compilation, evaluation, and digitization of this data by multiple groups around the world over the past several decades has helped dramatically in this respect, the process of performing systematic studies using this data can still be cumbersome and limited. We are in the process of creating a python-based program to extract, sort, and manipulate nuclear and atomic data efficiently. In its current state, the program is able to extract all atomic-shell ionization energies, excited- and ground-state nuclear properties, and all beta-decay rates and ratios. As a part of this ongoing project, we plan to use this tool to examine beta-decay rates in extreme astrophysical environments.

  19. 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.

  20. Near azeotropic mixture substitute

    NASA Technical Reports Server (NTRS)

    Jones, Jack A. (Inventor)

    1996-01-01

    The present invention comprises a refrigerant mixture consisting of a first mole fraction of 1,1,1,2-tetrafluoroethane (R134a) and a second mole fraction of a component selected from the group consisting of a mixture of CHClFCF.sub.3 (R124) and CH.sub.3 CClF.sub.2 (R142b); a mixture of CHF.sub.2 CH.sub.3 (R152a) and CHClFCF.sub.3 (R124); a mixture of CHF.sub.2 CH.sub.3 (R152a) and CH.sub.3 CClF.sub.2 (R142b); and a mixture of CHClFCF.sub.3 (R124), CH.sub.3 CClF.sub.2 (R142b) and CHF.sub.2 CH.sub.3 (R152a).