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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Helmus, Jonathan J.; Collis, Scott M.

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

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.

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

Python-Based Applications for Hydrogeological Modeling

NASA Astrophysics Data System (ADS)

Khambhammettu, P.

2013-12-01

Python is a general-purpose, high-level programming language whose design philosophy emphasizes code readability. Add-on packages supporting fast array computation (numpy), plotting (matplotlib), scientific /mathematical Functions (scipy), have resulted in a powerful ecosystem for scientists interested in exploratory data analysis, high-performance computing and data visualization. Three examples are provided to demonstrate the applicability of the Python environment in hydrogeological applications. Python programs were used to model an aquifer test and estimate aquifer parameters at a Superfund site. The aquifer test conducted at a Groundwater Circulation Well was modeled with the Python/FORTRAN-based TTIM Analytic Element Code. The aquifer parameters were estimated with PEST such that a good match was produced between the simulated and observed drawdowns. Python scripts were written to interface with PEST and visualize the results. A convolution-based approach was used to estimate source concentration histories based on observed concentrations at receptor locations. Unit Response Functions (URFs) that relate the receptor concentrations to a unit release at the source were derived with the ATRANS code. The impact of any releases at the source could then be estimated by convolving the source release history with the URFs. Python scripts were written to compute and visualize receptor concentrations for user-specified source histories. The framework provided a simple and elegant way to test various hypotheses about the site. A Python/FORTRAN-based program TYPECURVEGRID-Py was developed to compute and visualize groundwater elevations and drawdown through time in response to a regional uniform hydraulic gradient and the influence of pumping wells using either the Theis solution for a fully-confined aquifer or the Hantush-Jacob solution for a leaky confined aquifer. The program supports an arbitrary number of wells that can operate according to arbitrary schedules. The python wrapper invokes the underlying FORTRAN layer to compute transient groundwater elevations and processes this information to create time-series and 2D plots.

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.

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.

Java vs. Python Coverage of Introductory Programming Concepts: A Textbook Analysis

ERIC Educational Resources Information Center

McMaster, Kirby; Sambasivam, Samuel; Rague, Brian; Wolthuis, Stuart

2017-01-01

In this research, we compare two languages, Java and Python, by performing a content analysis of words in textbooks that describe important programming concepts. Our goal is to determine which language has better textbook support for teaching introductory programming courses. We used the TextSTAT program to count how often our list of concept…

Introduction to Python for CMF Authority Users

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pritchett-Sheats, Lori A.

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

Stata Hybrids: Updates and Ideas

NASA Technical Reports Server (NTRS)

Fieldler, James

2014-01-01

At last year's Stata conference I presented two projects for using Python with Stata: a plugin that embeds the Python programming language within Stata and code for using Stata data sets in Python. In this talk I will describe some small improvements being made to these projects, and I will present other ideas for combining tools with Stata. Some of these ideas use Python, some use JavaScript and a web browser.

Scientific Computing for Chemists: An Undergraduate Course in Simulations, Data Processing, and Visualization

ERIC Educational Resources Information Center

Weiss, Charles J.

2017-01-01

The Scientific Computing for Chemists course taught at Wabash College teaches chemistry students to use the Python programming language, Jupyter notebooks, and a number of common Python scientific libraries to process, analyze, and visualize data. Assuming no prior programming experience, the course introduces students to basic programming and…

Syphilis and psychiatry at the Mysore Government Mental Hospital (NIMHANS) in the early 20th century

PubMed Central

Ghani, Sarah; Murthy, Pratima; Jain, Sanjeev; Sarin, Alok

2018-01-01

Prior to the advent of the Wasserman Test as a diagnostic tool for Syphilis, the identification rate for Syphilis at the Mysore Government Mental Hospital in Southern India was 1%. With the introduction of the test, there was a dramatic increase in the diagnosis of Syphilis, with 17% of the patients testing positive. This paper throws light on the early notions of Syphilis and GPI, societal responses to the disease, early misdiagnosis, the advent of the Wasserman test and treatment management as reflected in the records of the early 20th century at the Mysore Government Mental Hospital (currently known as NIMHANS). PMID:29527060

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.

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

SWMM5 Application Programming Interface and PySWMM: A Python Interfacing Wrapper

EPA Science Inventory

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

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.

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.

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.

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…

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.

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

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.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ayer, Vidya M.; Miguez, Sheila; Toby, Brian H.

Scientists have been central to the historical development of the computer industry, but the importance of software only continues to grow for all areas of scientific research and in particular for powder diffraction. Knowing how to program a computer is a basic and useful skill for scientists. The article introduces the three types of programming languages and why scripting languages are now preferred for scientists. Of them, the authors assert Python is the most useful and easiest to learn. Python is introduced. Also presented is an overview to a few of the many add-on packages available to extend the capabilitiesmore » of Python, for example, for numerical computations, scientific graphics and graphical user interface programming.« less

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

PubMed

Yesylevskyy, Semen O

2015-07-15

Pteros is the high-performance open-source library for molecular modeling and analysis of molecular dynamics trajectories. Starting from version 2.0 Pteros is available for C++ and Python programming languages with very similar interfaces. This makes it suitable for writing complex reusable programs in C++ and simple interactive scripts in Python alike. New version improves the facilities for asynchronous trajectory reading and parallel execution of analysis tasks by introducing analysis plugins which could be written in either C++ or Python in completely uniform way. The high level of abstraction provided by analysis plugins greatly simplifies prototyping and implementation of complex analysis algorithms. Pteros is available for free under Artistic License from http://sourceforge.net/projects/pteros/. © 2015 Wiley Periodicals, Inc.

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.

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

SSR_pipeline--computer software for the identification of microsatellite sequences from paired-end Illumina high-throughput DNA sequence data

USGS Publications Warehouse

Miller, Mark P.; Knaus, Brian J.; Mullins, Thomas D.; Haig, Susan M.

2013-01-01

SSR_pipeline is a flexible set of programs designed to efficiently identify simple sequence repeats (SSRs; for example, microsatellites) from paired-end high-throughput Illumina DNA sequencing data. The program suite contains three analysis modules along with a fourth control module that can be used to automate analyses of large volumes of data. The modules are used to (1) identify the subset of paired-end sequences that pass quality standards, (2) align paired-end reads into a single composite DNA sequence, and (3) identify sequences that possess microsatellites conforming to user specified parameters. Each of the three separate analysis modules also can be used independently to provide greater flexibility or to work with FASTQ or FASTA files generated from other sequencing platforms (Roche 454, Ion Torrent, etc). All modules are implemented in the Python programming language and can therefore be used from nearly any computer operating system (Linux, Macintosh, Windows). The program suite relies on a compiled Python extension module to perform paired-end alignments. Instructions for compiling the extension from source code are provided in the documentation. Users who do not have Python installed on their computers or who do not have the ability to compile software also may choose to download packaged executable files. These files include all Python scripts, a copy of the compiled extension module, and a minimal installation of Python in a single binary executable. See program documentation for more information.

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.

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

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 for developing new high-level interfaces, which can help make GMT more accessible to beginners and more intuitive for Python users. GMT/Python is an open-source project hosted on Github (github.com/GenericMappingTools/gmt-python) and is in early stages of development. A first release will accompany the release of GMT 6, which is expected for early 2018.

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.

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

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.

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

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.

Dr.LiTHO: a development and research lithography simulator

NASA Astrophysics Data System (ADS)

Fühner, Tim; Schnattinger, Thomas; Ardelean, Gheorghe; Erdmann, Andreas

2007-03-01

This paper introduces Dr.LiTHO, a research and development oriented lithography simulation environment developed at Fraunhofer IISB to flexibly integrate our simulation models into one coherent platform. We propose a light-weight approach to a lithography simulation environment: The use of a scripting (batch) language as an integration platform. Out of the great variety of different scripting languages, Python proved superior in many ways: It exhibits a good-natured learning-curve, it is efficient, available on virtually any platform, and provides sophisticated integration mechanisms for existing programs. In this paper, we will describe the steps, required to provide Python bindings for existing programs and to finally generate an integrated simulation environment. In addition, we will give a short introduction into selected software design demands associated with the development of such a framework. We will especially focus on testing and (both technical and user-oriented) documentation issues. Dr.LiTHO Python files contain not only all simulation parameter settings but also the simulation flow, providing maximum flexibility. In addition to relatively simple batch jobs, repetitive tasks can be pooled in libraries. And as Python is a full-blown programming language, users can add virtually any functionality, which is especially useful in the scope of simulation studies or optimization tasks, that often require masses of evaluations. Furthermore, we will give a short overview of the numerous existing Python packages. Several examples demonstrate the feasibility and productiveness of integrating Python packages into custom Dr.LiTHO scripts.

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.

Traffic Pattern Detection Using the Hough Transformation for Anomaly Detection to Improve Maritime Domain Awareness

DTIC Science & Technology

2013-12-01

Programming code in the Python language used in AIS data preprocessing is contained in Appendix A. The MATLAB programming code used to apply the Hough...described in Chapter III is applied to archived AIS data in this chapter. The implementation of the method, including programming techniques used, is...is contained in the second. To provide a proof of concept for the algorithm described in Chapter III, the PYTHON programming language was used for

A general spectral method for the numerical simulation of one-dimensional interacting fermions

NASA Astrophysics Data System (ADS)

Clason, Christian; von Winckel, Gregory

2012-08-01

This software implements a general framework for the direct numerical simulation of systems of interacting fermions in one spatial dimension. The approach is based on a specially adapted nodal spectral Galerkin method, where the basis functions are constructed to obey the antisymmetry relations of fermionic wave functions. An efficient Matlab program for the assembly of the stiffness and potential matrices is presented, which exploits the combinatorial structure of the sparsity pattern arising from this discretization to achieve optimal run-time complexity. This program allows the accurate discretization of systems with multiple fermions subject to arbitrary potentials, e.g., for verifying the accuracy of multi-particle approximations such as Hartree-Fock in the few-particle limit. It can be used for eigenvalue computations or numerical solutions of the time-dependent Schrödinger equation. The new version includes a Python implementation of the presented approach. New version program summaryProgram title: assembleFermiMatrix Catalogue identifier: AEKO_v1_1 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEKO_v1_1.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 332 No. of bytes in distributed program, including test data, etc.: 5418 Distribution format: tar.gz Programming language: MATLAB/GNU Octave, Python Computer: Any architecture supported by MATLAB, GNU Octave or Python Operating system: Any supported by MATLAB, GNU Octave or Python RAM: Depends on the data Classification: 4.3, 2.2. External routines: Python 2.7+, NumPy 1.3+, SciPy 0.10+ Catalogue identifier of previous version: AEKO_v1_0 Journal reference of previous version: Comput. Phys. Commun. 183 (2012) 405 Does the new version supersede the previous version?: Yes Nature of problem: The direct numerical solution of the multi-particle one-dimensional Schrödinger equation in a quantum well is challenging due to the exponential growth in the number of degrees of freedom with increasing particles. Solution method: A nodal spectral Galerkin scheme is used where the basis functions are constructed to obey the antisymmetry relations of the fermionic wave function. The assembly of these matrices is performed efficiently by exploiting the combinatorial structure of the sparsity patterns. Reasons for new version: A Python implementation is now included. Summary of revisions: Added a Python implementation; small documentation fixes in Matlab implementation. No change in features of the package. Restrictions: Only one-dimensional computational domains with homogeneous Dirichlet or periodic boundary conditions are supported. Running time: Seconds to minutes.

[Not Available].

PubMed

Pecevski, Dejan; Natschläger, Thomas; Schuch, Klaus

2009-01-01

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.

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.

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

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.

Psi4NumPy: An Interactive Quantum Chemistry Programming Environment for Reference Implementations and Rapid Development.

PubMed

Smith, Daniel G A; Burns, Lori A; Sirianni, Dominic A; Nascimento, Daniel R; Kumar, Ashutosh; James, Andrew M; Schriber, Jeffrey B; Zhang, Tianyuan; Zhang, Boyi; Abbott, Adam S; Berquist, Eric J; Lechner, Marvin H; Cunha, Leonardo A; Heide, Alexander G; Waldrop, Jonathan M; Takeshita, Tyler Y; Alenaizan, Asem; Neuhauser, Daniel; King, Rollin A; Simmonett, Andrew C; Turney, Justin M; Schaefer, Henry F; Evangelista, Francesco A; DePrince, A Eugene; Crawford, T Daniel; Patkowski, Konrad; Sherrill, C David

2018-06-11

Psi4NumPy demonstrates the use of efficient computational kernels from the open-source Psi4 program through the popular NumPy library for linear algebra in Python to facilitate the rapid development of clear, understandable Python computer code for new quantum chemical methods, while maintaining a relatively low execution time. Using these tools, reference implementations have been created for a number of methods, including self-consistent field (SCF), SCF response, many-body perturbation theory, coupled-cluster theory, configuration interaction, and symmetry-adapted perturbation theory. Furthermore, several reference codes have been integrated into Jupyter notebooks, allowing background, underlying theory, and formula information to be associated with the implementation. Psi4NumPy tools and associated reference implementations can lower the barrier for future development of quantum chemistry methods. These implementations also demonstrate the power of the hybrid C++/Python programming approach employed by the Psi4 program.

C3I and Modelling and Simulation (M&S) Interoperability

DTIC Science & Technology

2004-03-01

customised Open Source products. The technical implementation is based on the use of the eXtendend Markup Language (XML) and Python . XML is developed...to structure, store and send information. The language is focus on the description of data. Python is a portable, interpreted, object-oriented...programming language. A huge variety of usable Open Source Projects were issued by the Python Community. 3.1 Phase 1: Feasibility Studies Phase 1 was

Simulation with Python on transverse modes of the symmetric confocal resonator

NASA Astrophysics Data System (ADS)

Wang, Qing Hua; Qi, Jing; Ji, Yun Jing; Song, Yang; Li, Zhenhua

2017-08-01

Python is a popular open-source programming language that can be used to simulate various optical phenomena. We have developed a suite of programs to help teach the course of laser principle. The complicated transverse modes of the symmetric confocal resonator can be visualized in personal computers, which is significant to help the students understand the pattern distribution of laser resonator.

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

NASA Astrophysics Data System (ADS)

Sainio, J.

2012-04-01

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

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.

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.

Generation of Test Questions from RDF Files Using PYTHON and SPARQL

NASA Astrophysics Data System (ADS)

Omarbekova, Assel; Sharipbay, Altynbek; Barlybaev, Alibek

2017-02-01

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

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

GRASS GIS 7 is a free and open source GIS software developed and used by many scientists (Neteler et al., 2012). While some users of GRASS GIS prefer its graphical user interface, significant part of the scientific community takes advantage of various scripting and programing interfaces offered by GRASS GIS to develop new models and algorithms. Here we will present different interfaces added to GRASS GIS 7 and available in Python, a popular programming language and environment in geosciences. These Python interfaces are designed to satisfy the needs of scientists and programmers under various circumstances. PyGRASS (Zambelli et al., 2013) is a new object-oriented interface to GRASS GIS modules and libraries. The GRASS GIS libraries are implemented in C to ensure maximum performance and the PyGRASS interface provides an intuitive, pythonic access to their functionality. GRASS GIS Python scripting library is another way of accessing GRASS GIS modules. It combines the simplicity of Bash and the efficiency of the Python syntax. When full access to all low-level and advanced functions and structures from GRASS GIS library is required, Python programmers can use an interface based on the Python ctypes package. Ctypes interface provides complete, direct access to all functionality as it would be available to C programmers. GRASS GIS provides specialized Python library for managing and analyzing spatio-temporal data (Gebbert and Pebesma, 2014). The temporal library introduces space time datasets representing time series of raster, 3D raster or vector maps and allows users to combine various spatio-temporal operations including queries, aggregation, sampling or the analysis of spatio-temporal topology. We will also discuss the advantages of implementing scientific algorithm as a GRASS GIS module and we will show how to write such module in Python. To facilitate the development of the module, GRASS GIS provides a Python library for testing (Petras and Gebbert, 2014) which helps researchers to ensure the robustness of the algorithm, correctness of the results in edge cases as well as the detection of changes in results due to new development. For all modules GRASS GIS automatically creates standardized command line and graphical user interfaces and documentation. Finally, we will show how GRASS GIS can be used together with powerful Python tools such as the NumPy package and the IPython Notebook. References: Gebbert, S., Pebesma, E., 2014. A temporal GIS for field based environmental modeling. Environmental Modelling & Software 53, 1-12. Neteler, M., Bowman, M.H., Landa, M. and Metz, M., 2012. GRASS GIS: a multi-purpose Open Source GIS. Environmental Modelling & Software 31: 124-130. Petras, V., Gebbert, S., 2014. Testing framework for GRASS GIS: ensuring reproducibility of scientific geospatial computing. Poster presented at: AGU Fall Meeting, December 15-19, 2014, San Francisco, USA. Zambelli, P., Gebbert, S., Ciolli, M., 2013. Pygrass: An Object Oriented Python Application Programming Interface (API) for Geographic Resources Analysis Support System (GRASS) Geographic Information System (GIS). ISPRS International Journal of Geo-Information 2, 201-219.

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.

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.

Automating tasks in protein structure determination with the clipper python module

PubMed Central

McNicholas, Stuart; Croll, Tristan; Burnley, Tom; Palmer, Colin M.; Hoh, Soon Wen; Jenkins, Huw T.; Dodson, Eleanor

2017-01-01

Abstract Scripting programming languages provide the fastest means of prototyping complex functionality. Those with a syntax and grammar resembling human language also greatly enhance the maintainability of the produced source code. Furthermore, the combination of a powerful, machine‐independent scripting language with binary libraries tailored for each computer architecture allows programs to break free from the tight boundaries of efficiency traditionally associated with scripts. In the present work, we describe how an efficient C++ crystallographic library such as Clipper can be wrapped, adapted and generalized for use in both crystallographic and electron cryo‐microscopy applications, scripted with the Python language. We shall also place an emphasis on best practices in automation, illustrating how this can be achieved with this new Python module. PMID:28901669

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.

ParFit: A Python-Based Object-Oriented Program for Fitting Molecular Mechanics Parameters to ab Initio Data.

PubMed

Zahariev, Federico; De Silva, Nuwan; Gordon, Mark S; Windus, Theresa L; Dick-Perez, Marilu

2017-03-27

A newly created object-oriented program for automating the process of fitting molecular-mechanics parameters to ab initio data, termed ParFit, is presented. ParFit uses a hybrid of deterministic and stochastic genetic algorithms. ParFit can simultaneously handle several molecular-mechanics parameters in multiple molecules and can also apply symmetric and antisymmetric constraints on the optimized parameters. The simultaneous handling of several molecules enhances the transferability of the fitted parameters. ParFit is written in Python, uses a rich set of standard and nonstandard Python libraries, and can be run in parallel on multicore computer systems. As an example, a series of phosphine oxides, important for metal extraction chemistry, are parametrized using ParFit. ParFit is in an open source program available for free on GitHub ( https://github.com/fzahari/ParFit ).

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.

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 software to three currently available Python libraries for parsing NMR-STAR formatted files: PyStarLib, NMRPyStar, and PyNMRSTAR. The nmrstarlib package is a simple, fast, and efficient library for accessing data from the BMRB. The library provides an intuitive dictionary-based interface with which Python programs can read, edit, and write NMR-STAR formatted files and their equivalent JSONized NMR-STAR files. The nmrstarlib package can be used as a library for accessing and manipulating data stored in NMR-STAR files and as a command-line tool to convert from NMR-STAR file format into its equivalent JSON file format and vice versa, and to visualize chemical shift values. Furthermore, the nmrstarlib implementation provides a guide for effectively JSONizing other older scientific formats, improving the FAIRness of data in these formats.

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.

Pynamic: the Python Dynamic Benchmark

DOE Office of Scientific and Technical Information (OSTI.GOV)

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

2007-07-10

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

Pybus -- A Python Software Bus

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lavrijsen, Wim T.L.P.

2004-10-14

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

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 .

Software Engineering Education Directory

DTIC Science & Technology

1990-04-01

and Engineering (CMSC 735) Codes: GPEV2 * Textiooks: IEEE Tutoria on Models and Metrics for Software Management and Engameeing by Basi, Victor R...Software Engineering (Comp 227) Codes: GPRY5 Textbooks: IEEE Tutoria on Software Design Techniques by Freeman, Peter and Wasserman, Anthony 1. Software

Pycellerator: an arrow-based reaction-like modelling language for biological simulations.

PubMed

Shapiro, Bruce E; Mjolsness, Eric

2016-02-15

We introduce Pycellerator, a Python library for reading Cellerator arrow notation from standard text files, conversion to differential equations, generating stand-alone Python solvers, and optionally running and plotting the solutions. All of the original Cellerator arrows, which represent reactions ranging from mass action, Michales-Menten-Henri (MMH) and Gene-Regulation (GRN) to Monod-Wyman-Changeaux (MWC), user defined reactions and enzymatic expansions (KMech), were previously represented with the Mathematica extended character set. These are now typed as reaction-like commands in ASCII text files that are read by Pycellerator, which includes a Python command line interface (CLI), a Python application programming interface (API) and an iPython notebook interface. Cellerator reaction arrows are now input in text files. The arrows are parsed by Pycellerator and translated into differential equations in Python, and Python code is automatically generated to solve the system. Time courses are produced by executing the auto-generated Python code. Users have full freedom to modify the solver and utilize the complete set of standard Python tools. The new libraries are completely independent of the old Cellerator software and do not require Mathematica. All software is available (GPL) from the github repository at https://github.com/biomathman/pycellerator/releases. Details, including installation instructions and a glossary of acronyms and terms, are given in the Supplementary information. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

ParFit: A Python-Based Object-Oriented Program for Fitting Molecular Mechanics Parameters to ab Initio Data

DOE PAGES

Zahariev, Federico; De Silva, Nuwan; Gordon, Mark S.; ...

2017-02-23

Here, a newly created object-oriented program for automating the process of fitting molecular-mechanics parameters to ab initio data, termed ParFit, is presented. ParFit uses a hybrid of deterministic and stochastic genetic algorithms. ParFit can simultaneously handle several molecular-mechanics parameters in multiple molecules and can also apply symmetric and antisymmetric constraints on the optimized parameters. The simultaneous handling of several molecules enhances the transferability of the fitted parameters. ParFit is written in Python, uses a rich set of standard and nonstandard Python libraries, and can be run in parallel on multicore computer systems. As an example, a series of phosphine oxides,more » important for metal extraction chemistry, are parametrized using ParFit.« less

ParFit: A Python-Based Object-Oriented Program for Fitting Molecular Mechanics Parameters to ab Initio Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Zahariev, Federico; De Silva, Nuwan; Gordon, Mark S.

Here, a newly created object-oriented program for automating the process of fitting molecular-mechanics parameters to ab initio data, termed ParFit, is presented. ParFit uses a hybrid of deterministic and stochastic genetic algorithms. ParFit can simultaneously handle several molecular-mechanics parameters in multiple molecules and can also apply symmetric and antisymmetric constraints on the optimized parameters. The simultaneous handling of several molecules enhances the transferability of the fitted parameters. ParFit is written in Python, uses a rich set of standard and nonstandard Python libraries, and can be run in parallel on multicore computer systems. As an example, a series of phosphine oxides,more » important for metal extraction chemistry, are parametrized using ParFit.« less

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.

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.

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

Flexible Environmental Modeling with Python and Open - GIS

NASA Astrophysics Data System (ADS)

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

2015-04-01

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

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.

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

Open source clustering software.

PubMed

de Hoon, M J L; Imoto, S; Nolan, J; Miyano, S

2004-06-12

We have implemented k-means clustering, hierarchical clustering and self-organizing maps in a single multipurpose open-source library of C routines, callable from other C and C++ programs. Using this library, we have created an improved version of Michael Eisen's well-known Cluster program for Windows, Mac OS X and Linux/Unix. In addition, we generated a Python and a Perl interface to the C Clustering Library, thereby combining the flexibility of a scripting language with the speed of C. The C Clustering Library and the corresponding Python C extension module Pycluster were released under the Python License, while the Perl module Algorithm::Cluster was released under the Artistic License. The GUI code Cluster 3.0 for Windows, Macintosh and Linux/Unix, as well as the corresponding command-line program, were released under the same license as the original Cluster code. The complete source code is available at http://bonsai.ims.u-tokyo.ac.jp/mdehoon/software/cluster. Alternatively, Algorithm::Cluster can be downloaded from CPAN, while Pycluster is also available as part of the Biopython distribution.

Automating tasks in protein structure determination with the clipper python module.

PubMed

McNicholas, Stuart; Croll, Tristan; Burnley, Tom; Palmer, Colin M; Hoh, Soon Wen; Jenkins, Huw T; Dodson, Eleanor; Cowtan, Kevin; Agirre, Jon

2018-01-01

Scripting programming languages provide the fastest means of prototyping complex functionality. Those with a syntax and grammar resembling human language also greatly enhance the maintainability of the produced source code. Furthermore, the combination of a powerful, machine-independent scripting language with binary libraries tailored for each computer architecture allows programs to break free from the tight boundaries of efficiency traditionally associated with scripts. In the present work, we describe how an efficient C++ crystallographic library such as Clipper can be wrapped, adapted and generalized for use in both crystallographic and electron cryo-microscopy applications, scripted with the Python language. We shall also place an emphasis on best practices in automation, illustrating how this can be achieved with this new Python module. © 2017 The Authors Protein Science published by Wiley Periodicals, Inc. on behalf of The Protein Society.

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.

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.

Correction to: Assessment of Local Adverse Reactions to Subcutaneous Immunoglobulin (SCIG) in Clinical Trials.

PubMed

Ballow, Mark; Wasserman, Richard L; Jolles, Stephen; Chapel, Helen; Berger, Mel; Misbah, Siraj A

2018-04-27

The article Assessment of Local Adverse Reactions to Subcutaneous Immunoglobulin (SCIG) in Clinical Trials, written by Mark Ballow, Richard L. Wasserman, Stephen Jolles, Helen Chapel, Mel Berger, Siraj A. Misbah, was originally published Online First without open access.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

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

2010-11-29

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

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

USGS Publications Warehouse

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

2011-01-01

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

PyR@TE. Renormalization group equations for general gauge theories

NASA Astrophysics Data System (ADS)

Lyonnet, F.; Schienbein, I.; Staub, F.; Wingerter, A.

2014-03-01

Although the two-loop renormalization group equations for a general gauge field theory have been known for quite some time, deriving them for specific models has often been difficult in practice. This is mainly due to the fact that, albeit straightforward, the involved calculations are quite long, tedious and prone to error. The present work is an attempt to facilitate the practical use of the renormalization group equations in model building. To that end, we have developed two completely independent sets of programs written in Python and Mathematica, respectively. The Mathematica scripts will be part of an upcoming release of SARAH 4. The present article describes the collection of Python routines that we dubbed PyR@TE which is an acronym for “Python Renormalization group equations At Two-loop for Everyone”. In PyR@TE, once the user specifies the gauge group and the particle content of the model, the routines automatically generate the full two-loop renormalization group equations for all (dimensionless and dimensionful) parameters. The results can optionally be exported to LaTeX and Mathematica, or stored in a Python data structure for further processing by other programs. For ease of use, we have implemented an interactive mode for PyR@TE in form of an IPython Notebook. As a first application, we have generated with PyR@TE the renormalization group equations for several non-supersymmetric extensions of the Standard Model and found some discrepancies with the existing literature. Catalogue identifier: AERV_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AERV_v1_0.html Program obtainable from: CPC Program Library, Queen’s University, Belfast, N. Ireland Licensing provisions: Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html No. of lines in distributed program, including test data, etc.: 924959 No. of bytes in distributed program, including test data, etc.: 495197 Distribution format: tar.gz Programming language: Python. Computer: Personal computer. Operating system: Tested on Fedora 15, MacOS 10 and 11, Ubuntu 12. Classification: 11.1. External routines: SymPy, PyYAML, NumPy, IPython, SciPy Nature of problem: Deriving the renormalization group equations for a general quantum field theory. Solution method: Group theory, tensor algebra Running time: Tens of seconds per model (one-loop), tens of minutes (two-loop)

Working with HITRAN Database Using Hapi: HITRAN Application Programming Interface

NASA Astrophysics Data System (ADS)

Kochanov, Roman V.; Hill, Christian; Wcislo, Piotr; Gordon, Iouli E.; Rothman, Laurence S.; Wilzewski, Jonas

2015-06-01

A HITRAN Application Programing Interface (HAPI) has been developed to allow users on their local machines much more flexibility and power. HAPI is a programming interface for the main data-searching capabilities of the new "HITRANonline" web service (http://www.hitran.org). It provides the possibility to query spectroscopic data from the HITRAN database in a flexible manner using either functions or query language. Some of the prominent current features of HAPI are: a) Downloading line-by-line data from the HITRANonline site to a local machine b) Filtering and processing the data in SQL-like fashion c) Conventional Python structures (lists, tuples, and dictionaries) for representing spectroscopic data d) Possibility to use a large set of third-party Python libraries to work with the data e) Python implementation of the HT lineshape which can be reduced to a number of conventional line profiles f) Python implementation of total internal partition sums (TIPS-2011) for spectra simulations g) High-resolution spectra calculation accounting for pressure, temperature and optical path length h) Providing instrumental functions to simulate experimental spectra i) Possibility to extend HAPI's functionality by custom line profiles, partitions sums and instrumental functions Currently the API is a module written in Python and uses Numpy library providing fast array operations. The API is designed to deal with data in multiple formats such as ASCII, CSV, HDF5 and XSAMS. This work has been supported by NASA Aura Science Team Grant NNX14AI55G and NASA Planetary Atmospheres Grant NNX13AI59G. L.S. Rothman et al. JQSRT, Volume 130, 2013, Pages 4-50 N.H. Ngo et al. JQSRT, Volume 129, November 2013, Pages 89-100 A. L. Laraia at al. Icarus, Volume 215, Issue 1, September 2011, Pages 391-400

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.

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.

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

Creating CAD designs and performing their subsequent analysis using opensource solutions in Python

NASA Astrophysics Data System (ADS)

Iakushkin, Oleg O.; Sedova, Olga S.

2018-01-01

The paper discusses the concept of a system that encapsulates the transition from geometry building to strength tests. The solution we propose views the engineer as a programmer who is capable of coding the procedure for working with the modeli.e., to outline the necessary transformations and create cases for boundary conditions. We propose a prototype of such system. In our work, we used: Python programming language to create the program; Jupyter framework to create a single workspace visualization; pythonOCC library to implement CAD; FeniCS library to implement FEM; GMSH and VTK utilities. The prototype is launched on a platform which is a dynamically expandable multi-tenant cloud service providing users with all computing resources on demand. However, the system may be deployed locally for prototyping or work that does not involve resource-intensive computing. To make it possible, we used containerization, isolating the system in a Docker container.

The Simulation of a Major Automated Information System (AIS) on a Microcomputer

DTIC Science & Technology

1984-03-01

The AIS would be selected from a public zec cor application. Rationale for this choice are: a. Many public sector organizations have a far richer...19. Boehm, Barry W. and others, Characteristics of Software Quality, North-Holland, 1978. 20. Freeman, Peter and Wasserman, Anthony I., Tutorial on

A high level interface to SCOP and ASTRAL implemented in python.

PubMed

Casbon, James A; Crooks, Gavin E; Saqi, Mansoor A S

2006-01-10

Benchmarking algorithms in structural bioinformatics often involves the construction of datasets of proteins with given sequence and structural properties. The SCOP database is a manually curated structural classification which groups together proteins on the basis of structural similarity. The ASTRAL compendium provides non redundant subsets of SCOP domains on the basis of sequence similarity such that no two domains in a given subset share more than a defined degree of sequence similarity. Taken together these two resources provide a 'ground truth' for assessing structural bioinformatics algorithms. We present a small and easy to use API written in python to enable construction of datasets from these resources. We have designed a set of python modules to provide an abstraction of the SCOP and ASTRAL databases. The modules are designed to work as part of the Biopython distribution. Python users can now manipulate and use the SCOP hierarchy from within python programs, and use ASTRAL to return sequences of domains in SCOP, as well as clustered representations of SCOP from ASTRAL. The modules make the analysis and generation of datasets for use in structural genomics easier and more principled.

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.

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.

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

PubMed Central

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

2015-01-01

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

COMP Superscalar, an interoperable programming framework

NASA Astrophysics Data System (ADS)

Badia, Rosa M.; Conejero, Javier; Diaz, Carlos; Ejarque, Jorge; Lezzi, Daniele; Lordan, Francesc; Ramon-Cortes, Cristian; Sirvent, Raul

2015-12-01

COMPSs is a programming framework that aims to facilitate the parallelization of existing applications written in Java, C/C++ and Python scripts. For that purpose, it offers a simple programming model based on sequential development in which the user is mainly responsible for (i) identifying the functions to be executed as asynchronous parallel tasks and (ii) annotating them with annotations or standard Python decorators. A runtime system is in charge of exploiting the inherent concurrency of the code, automatically detecting and enforcing the data dependencies between tasks and spawning these tasks to the available resources, which can be nodes in a cluster, clouds or grids. In cloud environments, COMPSs provides scalability and elasticity features allowing the dynamic provision of resources.

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

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).

A new Python library to analyse skeleton images confirms malaria parasite remodelling of the red blood cell membrane skeleton.

PubMed

Nunez-Iglesias, Juan; Blanch, Adam J; Looker, Oliver; Dixon, Matthew W; Tilley, Leann

2018-01-01

We present Skan (Skeleton analysis), a Python library for the analysis of the skeleton structures of objects. It was inspired by the "analyse skeletons" plugin for the Fiji image analysis software, but its extensive Application Programming Interface (API) allows users to examine and manipulate any intermediate data structures produced during the analysis. Further, its use of common Python data structures such as SciPy sparse matrices and pandas data frames opens the results to analysis within the extensive ecosystem of scientific libraries available in Python. We demonstrate the validity of Skan's measurements by comparing its output to the established Analyze Skeletons Fiji plugin, and, with a new scanning electron microscopy (SEM)-based method, we confirm that the malaria parasite Plasmodium falciparum remodels the host red blood cell cytoskeleton, increasing the average distance between spectrin-actin junctions.

A Python-based interface to examine motions in time series of solar images

NASA Astrophysics Data System (ADS)

Campos-Rozo, J. I.; Vargas Domínguez, S.

2017-10-01

Python is considered to be a mature programming language, besides of being widely accepted as an engaging option for scientific analysis in multiple areas, as will be presented in this work for the particular case of solar physics research. SunPy is an open-source library based on Python that has been recently developed to furnish software tools to solar data analysis and visualization. In this work we present a graphical user interface (GUI) based on Python and Qt to effectively compute proper motions for the analysis of time series of solar data. This user-friendly computing interface, that is intended to be incorporated to the Sunpy library, uses a local correlation tracking technique and some extra tools that allows the selection of different parameters to calculate, vizualize and analyze vector velocity fields of solar data, i.e. time series of solar filtergrams and magnetograms.

A new Python library to analyse skeleton images confirms malaria parasite remodelling of the red blood cell membrane skeleton

PubMed Central

Looker, Oliver; Dixon, Matthew W.; Tilley, Leann

2018-01-01

We present Skan (Skeleton analysis), a Python library for the analysis of the skeleton structures of objects. It was inspired by the “analyse skeletons” plugin for the Fiji image analysis software, but its extensive Application Programming Interface (API) allows users to examine and manipulate any intermediate data structures produced during the analysis. Further, its use of common Python data structures such as SciPy sparse matrices and pandas data frames opens the results to analysis within the extensive ecosystem of scientific libraries available in Python. We demonstrate the validity of Skan’s measurements by comparing its output to the established Analyze Skeletons Fiji plugin, and, with a new scanning electron microscopy (SEM)-based method, we confirm that the malaria parasite Plasmodium falciparum remodels the host red blood cell cytoskeleton, increasing the average distance between spectrin-actin junctions. PMID:29472997

KMCLib: A general framework for lattice kinetic Monte Carlo (KMC) simulations

NASA Astrophysics Data System (ADS)

Leetmaa, Mikael; Skorodumova, Natalia V.

2014-09-01

KMCLib is a general framework for lattice kinetic Monte Carlo (KMC) simulations. The program can handle simulations of the diffusion and reaction of millions of particles in one, two, or three dimensions, and is designed to be easily extended and customized by the user to allow for the development of complex custom KMC models for specific systems without having to modify the core functionality of the program. Analysis modules and on-the-fly elementary step diffusion rate calculations can be implemented as plugins following a well-defined API. The plugin modules are loosely coupled to the core KMCLib program via the Python scripting language. KMCLib is written as a Python module with a backend C++ library. After initial compilation of the backend library KMCLib is used as a Python module; input to the program is given as a Python script executed using a standard Python interpreter. We give a detailed description of the features and implementation of the code and demonstrate its scaling behavior and parallel performance with a simple one-dimensional A-B-C lattice KMC model and a more complex three-dimensional lattice KMC model of oxygen-vacancy diffusion in a fluorite structured metal oxide. KMCLib can keep track of individual particle movements and includes tools for mean square displacement analysis, and is therefore particularly well suited for studying diffusion processes at surfaces and in solids. Catalogue identifier: AESZ_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AESZ_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.: 49 064 No. of bytes in distributed program, including test data, etc.: 1 575 172 Distribution format: tar.gz Programming language: Python and C++. Computer: Any computer that can run a C++ compiler and a Python interpreter. Operating system: Tested on Ubuntu 12.4 LTS, CentOS release 5.9, Mac OSX 10.5.8 and Mac OSX 10.8.2, but should run on any system that can have a C++ compiler, MPI and a Python interpreter. Has the code been vectorized or parallelized?: Yes. From one to hundreds of processors depending on the type of input and simulation. RAM: From a few megabytes to several gigabytes depending on input parameters and the size of the system to simulate. Classification: 4.13, 16.13. External routines: KMCLib uses an external Mersenne Twister pseudo random number generator that is included in the code. A Python 2.7 interpreter and a standard C++ runtime library are needed to run the serial version of the code. For running the parallel version an MPI implementation is needed, such as e.g. MPICH from http://www.mpich.org or Open-MPI from http://www.open-mpi.org. SWIG (obtainable from http://www.swig.org/) and CMake (obtainable from http://www.cmake.org/) are needed for building the backend module, Sphinx (obtainable from http://sphinx-doc.org) for building the documentation and CPPUNIT (obtainable from http://sourceforge.net/projects/cppunit/) for building the C++ unit tests. Nature of problem: Atomic scale simulation of slowly evolving dynamics is a great challenge in many areas of computational materials science and catalysis. When the rare-events dynamics of interest is orders of magnitude slower than the typical atomic vibrational frequencies a straight-forward propagation of the equations of motions for the particles in the simulation cannot reach time scales of relevance for modeling the slow dynamics. Solution method: KMCLib provides an implementation of the kinetic Monte Carlo (KMC) method that solves the slow dynamics problem by utilizing the separation of time scales between fast vibrational motion and the slowly evolving rare-events dynamics. Only the latter is treated explicitly and the system is simulated as jumping between fully equilibrated local energy minima on the slow-dynamics potential energy surface. Restrictions: KMCLib implements the lattice KMC method and is as such restricted to geometries that can be expressed on a grid in space. Unusual features: KMCLib has been designed to be easily customized, to allow for user-defined functionality and integration with other codes. The user can define her own on-the-fly rate calculator via a Python API, so that site-specific elementary process rates, or rates depending on long-range interactions or complex geometrical features can easily be included. KMCLib also allows for on-the-fly analysis with user-defined analysis modules. KMCLib can keep track of individual particle movements and includes tools for mean square displacement analysis, and is therefore particularly well suited for studying diffusion processes at surfaces and in solids. Additional comments: The full documentation of the program is distributed with the code and can also be found at http://www.github.com/leetmaa/KMCLib/manual Running time: rom a few seconds to several days depending on the type of simulation and input parameters.

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 the Application Programming Interface (API) for improved functionality and consistency within the package, as well as increased compatibility with existing conventions used in other scientific software packages for Python. The most significant new features include efficient solvers for arbitrary time-dependent Hamiltonians and collapse operators, support for the Floquet formalism, and new solvers for Bloch-Redfield and Floquet-Markov master equations. Restrictions: Problems must meet the criteria for using the master equation in Lindblad, Floquet-Markov, or Bloch-Redfield form. Running time: A few seconds up to several tens of hours, depending on size of the underlying Hilbert space.

An Evaluation of the Automated Cost Estimating Integrated Tools (ACEIT) System

DTIC Science & Technology

1989-09-01

residual and it is described as the residual divided by its standard deviation (13:App A,17). Neter, Wasserman, and Kutner, in Applied Linear Regression Models...others. Applied Linear Regression Models. Homewood IL: Irwin, 1983. 19. Raduchel, William J. "A Professional’s Perspective on User-Friendliness," Byte

Pupil Dilation and Object Permanence in Infants

ERIC Educational Resources Information Center

Sirois, Sylvain; Jackson, Iain R.

2012-01-01

This paper examines the relative merits of looking time and pupil diameter measures in the study of early cognitive abilities of infants. Ten-month-old infants took part in a modified version of the classic drawbridge experiment used to study object permanence (Baillargeon, Spelke, & Wasserman, 1985). The study involved a factorial design where…

Effects of Stimulus Duration and Choice Delay on Visual Categorization in Pigeons

ERIC Educational Resources Information Center

Lazareva, Olga F.; Wasserman, Edward A.

2009-01-01

We [Lazareva, O. F., Freiburger, K. L., & Wasserman, E. A. (2004). "Pigeons concurrently categorize photographs at both basic and superordinate levels." "Psychonomic Bulletin and Review," 11, 1111-1117] previously trained four pigeons to classify color photographs into their basic-level categories (cars, chairs, flowers, or people) or into their…

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.

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.

The Profile Envision and Splicing Tool (PRESTO): Developing an Atmospheric Wind Analysis Tool for Space Launch Vehicles Using Python

NASA Technical Reports Server (NTRS)

Orcutt, John M.; Barbre, Robert E., Jr.; Brenton, James C.; Decker, Ryan K.

2017-01-01

Launch vehicle programs require vertically complete atmospheric profiles. Many systems at the ER to make the necessary measurements, but all have different EVR, vertical coverage, and temporal coverage. MSFC Natural Environments Branch developed a tool to create a vertically complete profile from multiple inputs using Python. Forward work: Finish Formal Testing Acceptance Testing, End-to-End Testing. Formal Release

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.

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

PubMed Central

Wils, Stefan; Schutter, Erik De

2008-01-01

We describe how the use of the Python language improved the user interface of the program STEPS. STEPS is a simulation platform for modeling and stochastic simulation of coupled reaction-diffusion systems with complex 3-dimensional boundary conditions. Setting up such models is a complicated process that consists of many phases. Initial versions of STEPS relied on a static input format that did not cleanly separate these phases, limiting modelers in how they could control the simulation and becoming increasingly complex as new features and new simulation algorithms were added. We solved all of these problems by tightly integrating STEPS with Python, using SWIG to expose our existing simulation code. PMID:19623245

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

PubMed

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

2016-03-04

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sainio, J., E-mail: jani.sainio@utu.fi; Department of Physics and Astronomy, University of Turku, FI-20014 Turku

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

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

Automatic Parallelization of Numerical Python Applications using the Global Arrays Toolkit

DOE Office of Scientific and Technical Information (OSTI.GOV)

Daily, Jeffrey A.; Lewis, Robert R.

2011-11-30

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

PyNEST: A Convenient Interface to the NEST Simulator.

PubMed

Eppler, Jochen Martin; Helias, Moritz; Muller, Eilif; Diesmann, Markus; Gewaltig, Marc-Oliver

2008-01-01

The neural simulation tool NEST (http://www.nest-initiative.org) is a simulator for heterogeneous networks of point neurons or neurons with a small number of compartments. It aims at simulations of large neural systems with more than 10(4) neurons and 10(7) to 10(9) synapses. NEST is implemented in C++ and can be used on a large range of architectures from single-core laptops over multi-core desktop computers to super-computers with thousands of processor cores. Python (http://www.python.org) is a modern programming language that has recently received considerable attention in Computational Neuroscience. Python is easy to learn and has many extension modules for scientific computing (e.g. http://www.scipy.org). In this contribution we describe PyNEST, the new user interface to NEST. PyNEST combines NEST's efficient simulation kernel with the simplicity and flexibility of Python. Compared to NEST's native simulation language SLI, PyNEST makes it easier to set up simulations, generate stimuli, and analyze simulation results. We describe how PyNEST connects NEST and Python and how it is implemented. With a number of examples, we illustrate how it is used.

PyNEST: A Convenient Interface to the NEST Simulator

PubMed Central

Eppler, Jochen Martin; Helias, Moritz; Muller, Eilif; Diesmann, Markus; Gewaltig, Marc-Oliver

2008-01-01

The neural simulation tool NEST (http://www.nest-initiative.org) is a simulator for heterogeneous networks of point neurons or neurons with a small number of compartments. It aims at simulations of large neural systems with more than 104 neurons and 107 to 109 synapses. NEST is implemented in C++ and can be used on a large range of architectures from single-core laptops over multi-core desktop computers to super-computers with thousands of processor cores. Python (http://www.python.org) is a modern programming language that has recently received considerable attention in Computational Neuroscience. Python is easy to learn and has many extension modules for scientific computing (e.g. http://www.scipy.org). In this contribution we describe PyNEST, the new user interface to NEST. PyNEST combines NEST's efficient simulation kernel with the simplicity and flexibility of Python. Compared to NEST's native simulation language SLI, PyNEST makes it easier to set up simulations, generate stimuli, and analyze simulation results. We describe how PyNEST connects NEST and Python and how it is implemented. With a number of examples, we illustrate how it is used. PMID:19198667

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

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

2011-01-01

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

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.

SWMM5 Application Programming Interface and PySWMM: A ...

EPA Pesticide Factsheets

In support of the OpenWaterAnalytics open source initiative, the PySWMM project encompasses the development of a Python interfacing wrapper to SWMM5 with parallel ongoing development of the USEPA Stormwater Management Model (SWMM5) application programming interface (API). ... The purpose of this work is to increase the utility of the SWMM dll by creating a Toolkit API for accessing its functionality. The utility of the Toolkit is further enhanced with a wrapper to allow access from the Python scripting language. This work is being prosecuted as part of an Open Source development strategy and is being performed by volunteer software developers.

Comparison of Selection Procedures and Validation of Criterion Used in Selection of Significant Control Variates of a Simulation Model

DTIC Science & Technology

1990-03-01

and M.H. Knuter. Applied Linear Regression Models. Homewood IL: Richard D. Erwin Inc., 1983. Pritsker, A. Alan B. Introduction to Simulation and SLAM...Control Variates in Simulation," European Journal of Operational Research, 42: (1989). Neter, J., W. Wasserman, and M.H. Xnuter. Applied Linear Regression Models

Dryden: A Collection of Critical Essays. Twentieth Century Views Series.

ERIC Educational Resources Information Center

Schilling, Bernard N., Ed.

One of a series of works aimed at presenting contemporary critical opinion on major authors, this collection includes essays by Bernard Schilling, T. S. Eliot, Louis I. Bredvold, James M. Osborn, Reuben A. Brower, Edwin Morgan, Earl Wasserman, R. J. Kaufmann, Moody E. Prior, Earl W. Miner, Edward N. Hooker, E. M. W. Tillyard, John Hollander,…

Network Simulation Models

DTIC Science & Technology

2008-12-01

1979; Wasserman and Faust, 1994). SNA thus relies heavily on graph theory to make predictions about network structure and thus social behavior...becomes a tool for increasing the specificity of theory , thinking through the theoretical implications, and generating testable predictions. In...to summarize Construct and its roots in constructural sociological theory . We discover that the (LPM) provides a mathematical bridge between

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.

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

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.

PyMCT: A Very High Level Language Coupling Tool For Climate System Models

NASA Astrophysics Data System (ADS)

Tobis, M.; Pierrehumbert, R. T.; Steder, M.; Jacob, R. L.

2006-12-01

At the Climate Systems Center of the University of Chicago, we have been examining strategies for applying agile programming techniques to complex high-performance modeling experiments. While the "agile" development methodology differs from a conventional requirements process and its associated milestones, the process remain a formal one. It is distinguished by continuous improvement in functionality, large numbers of small releases, extensive and ongoing testing strategies, and a strong reliance on very high level languages (VHLL). Here we report on PyMCT, which we intend as a core element in a model ensemble control superstructure. PyMCT is a set of Python bindings for MCT, the Fortran-90 based Model Coupling Toolkit, which forms the infrastructure for the inter-component communication in the Community Climate System Model (CCSM). MCT provides a scalable model communication infrastructure. In order to take maximum advantage of agile software development methodologies, we exposed MCT functionality to Python, a prominent VHLL. We describe how the scalable architecture of MCT allows us to overcome the relatively weak runtime performance of Python, so that the performance of the combined system is not severely impacted. To demonstrate these advantages, we reimplemented the CCSM coupler in Python. While this alone offers no new functionality, it does provide a rigorous test of PyMCT functionality and performance. We reimplemented the CPL6 library, presenting an interesting case study of the comparison between conventional Fortran-90 programming and the higher abstraction level provided by a VHLL. The powerful abstractions provided by Python will allow much more complex experimental paradigms. In particular, we hope to build on the scriptability of our coupling strategy to enable systematic sensitivity tests. Our most ambitious objective is to combine our efforts with Bayesian inverse modeling techniques toward objective tuning at the highest level, across model architectures.

Automated Alerting for Black Hole Routing

DTIC Science & Technology

2007-09-01

Beginners or Learning Bro). Reply: Just the documentation that comes with it and is available from the wiki. Question 4: Is Bro compatible with...other scripts written in Python , Java, or Perl? Reply: It can call arbitrary programs but doesn’t link directly into other interpreters. Question 5...need to write that daemon? (C) What kind of scripts does Spunk support…and are Python and C part of them or not? 88 Reply: Puri, the answers to all

Extraction of Vertical Profiles of Atmospheric Variables from Gridded Binary, Edition 2 (GRIB2) Model Output Files

DTIC Science & Technology

2018-01-18

processing. Specifically, the method described herein uses wgrib2 commands along with a Python script or program to produce tabular text files that in...It makes use of software that is readily available and can be implemented on many computer systems combined with relatively modest additional...example), extracts appropriate information, and lists the extracted information in a readable tabular form. The Python script used here is described in

PyEPL: a cross-platform experiment-programming library.

PubMed

Geller, Aaron S; Schlefer, Ian K; Sederberg, Per B; Jacobs, Joshua; Kahana, Michael J

2007-11-01

PyEPL (the Python Experiment-Programming Library) is a Python library which allows cross-platform and object-oriented coding of behavioral experiments. It provides functions for displaying text and images onscreen, as well as playing and recording sound, and is capable of rendering 3-D virtual environments forspatial-navigation tasks. It is currently tested for Mac OS X and Linux. It interfaces with Activewire USB cards (on Mac OS X) and the parallel port (on Linux) for synchronization of experimental events with physiological recordings. In this article, we first present two sample programs which illustrate core PyEPL features. The examples demonstrate visual stimulus presentation, keyboard input, and simulation and exploration of a simple 3-D environment. We then describe the components and strategies used in implementing PyEPL.

PyEPL: A cross-platform experiment-programming library

PubMed Central

Geller, Aaron S.; Schleifer, Ian K.; Sederberg, Per B.; Jacobs, Joshua; Kahana, Michael J.

2009-01-01

PyEPL (the Python Experiment-Programming Library) is a Python library which allows cross-platform and object-oriented coding of behavioral experiments. It provides functions for displaying text and images onscreen, as well as playing and recording sound, and is capable of rendering 3-D virtual environments for spatial-navigation tasks. It is currently tested for Mac OS X and Linux. It interfaces with Activewire USB cards (on Mac OS X) and the parallel port (on Linux) for synchronization of experimental events with physiological recordings. In this article, we first present two sample programs which illustrate core PyEPL features. The examples demonstrate visual stimulus presentation, keyboard input, and simulation and exploration of a simple 3-D environment. We then describe the components and strategies used in implementing PyEPL. PMID:18183912

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.

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...

Pulseq-Graphical Programming Interface: Open source visual environment for prototyping pulse sequences and integrated magnetic resonance imaging algorithm development.

PubMed

Ravi, Keerthi Sravan; Potdar, Sneha; Poojar, Pavan; Reddy, Ashok Kumar; Kroboth, Stefan; Nielsen, Jon-Fredrik; Zaitsev, Maxim; Venkatesan, Ramesh; Geethanath, Sairam

2018-03-11

To provide a single open-source platform for comprehensive MR algorithm development inclusive of simulations, pulse sequence design and deployment, reconstruction, and image analysis. We integrated the "Pulseq" platform for vendor-independent pulse programming with Graphical Programming Interface (GPI), a scientific development environment based on Python. Our integrated platform, Pulseq-GPI, permits sequences to be defined visually and exported to the Pulseq file format for execution on an MR scanner. For comparison, Pulseq files using either MATLAB only ("MATLAB-Pulseq") or Python only ("Python-Pulseq") were generated. We demonstrated three fundamental sequences on a 1.5 T scanner. Execution times of the three variants of implementation were compared on two operating systems. In vitro phantom images indicate equivalence with the vendor supplied implementations and MATLAB-Pulseq. The examples demonstrated in this work illustrate the unifying capability of Pulseq-GPI. The execution times of all the three implementations were fast (a few seconds). The software is capable of user-interface based development and/or command line programming. The tool demonstrated here, Pulseq-GPI, integrates the open-source simulation, reconstruction and analysis capabilities of GPI Lab with the pulse sequence design and deployment features of Pulseq. Current and future work includes providing an ISMRMRD interface and incorporating Specific Absorption Ratio and Peripheral Nerve Stimulation computations. Copyright © 2018 Elsevier Inc. All rights reserved.

MADANALYSIS 5, a user-friendly framework for collider phenomenology

NASA Astrophysics Data System (ADS)

Conte, Eric; Fuks, Benjamin; Serret, Guillaume

2013-01-01

We present MADANALYSIS 5, a new framework for phenomenological investigations at particle colliders. Based on a C++ kernel, this program allows us to efficiently perform, in a straightforward and user-friendly fashion, sophisticated physics analyses of event files such as those generated by a large class of Monte Carlo event generators. MADANALYSIS 5 comes with two modes of running. The first one, easier to handle, uses the strengths of a powerful PYTHON interface in order to implement physics analyses by means of a set of intuitive commands. The second one requires one to implement the analyses in the C++ programming language, directly within the core of the analysis framework. This opens unlimited possibilities concerning the level of complexity which can be reached, being only limited by the programming skills and the originality of the user. Program summaryProgram title: MadAnalysis 5 Catalogue identifier: AENO_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AENO_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: Permission to use, copy, modify and distribute this program is granted under the terms of the GNU General Public License. No. of lines in distributed program, including test data, etc.: 31087 No. of bytes in distributed program, including test data, etc.: 399105 Distribution format: tar.gz Programming language: PYTHON, C++. Computer: All platforms on which Python version 2.7, Root version 5.27 and the g++ compiler are available. Compatibility with newer versions of these programs is also ensured. However, the Python version must be below version 3.0. Operating system: Unix, Linux and Mac OS operating systems on which the above-mentioned versions of Python and Root, as well as g++, are available. Classification: 11.1. External routines: ROOT (http://root.cern.ch/drupal/) Nature of problem: Implementing sophisticated phenomenological analyses in high-energy physics through a flexible, efficient and straightforward fashion, starting from event files such as those produced by Monte Carlo event generators. The event files can have been matched or not to parton-showering and can have been processed or not by a (fast) simulation of a detector. According to the sophistication level of the event files (parton-level, hadron-level, reconstructed-level), one must note that several input formats are possible. Solution method: We implement an interface allowing the production of predefined as well as user-defined histograms for a large class of kinematical distributions after applying a set of event selection cuts specified by the user. This therefore allows us to devise robust and novel search strategies for collider experiments, such as those currently running at the Large Hadron Collider at CERN, in a very efficient way. Restrictions: Unsupported event file format. Unusual features: The code is fully based on object representations for events, particles, reconstructed objects and cuts, which facilitates the implementation of an analysis. Running time: It depends on the purposes of the user and on the number of events to process. It varies from a few seconds to the order of the minute for several millions of events.

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.

Problem Solving and Emotional Distress Among Brain and Breast Cancer Survivors

DTIC Science & Technology

2007-03-30

Whittle, 1994; Hochberg & Slotnick, 1980 ; Imperato, Paleologos, & Vick, 1990; Lieberman et al., 1982; Salander, Karlsson, Bergenheim, & Henriksson, 1995...1981; Mulhern, Wasserman, & Friedman, 1996; Shanfield, 1980 ; Zebrack, Zeltzer, & Whitton, 2002). Hobbie et al. (2000) administered questionnaires and...e.g., Broeckl, 2000; Hobbie et al., 2000; Koocher & O’Malley, 1981; Mulhern et al., 1996; Shanfield, 1980 ; 86 Zebrack et al., 2002) that

Polar Coding with CRC-Aided List Decoding

DTIC Science & Technology

2015-08-01

TECHNICAL REPORT 2087 August 2015 Polar Coding with CRC-Aided List Decoding David Wasserman Approved...list decoding . RESULTS Our simulation results show that polar coding can produce results very similar to the FEC used in the Digital Video...standard. RECOMMENDATIONS In any application for which the DVB-S2 FEC is considered, polar coding with CRC-aided list decod - ing with N = 65536

Owlready: Ontology-oriented programming in Python with automatic classification and high level constructs for biomedical ontologies.

PubMed

Lamy, Jean-Baptiste

2017-07-01

Ontologies are widely used in the biomedical domain. While many tools exist for the edition, alignment or evaluation of ontologies, few solutions have been proposed for ontology programming interface, i.e. for accessing and modifying an ontology within a programming language. Existing query languages (such as SPARQL) and APIs (such as OWLAPI) are not as easy-to-use as object programming languages are. Moreover, they provide few solutions to difficulties encountered with biomedical ontologies. Our objective was to design a tool for accessing easily the entities of an OWL ontology, with high-level constructs helping with biomedical ontologies. From our experience on medical ontologies, we identified two difficulties: (1) many entities are represented by classes (rather than individuals), but the existing tools do not permit manipulating classes as easily as individuals, (2) ontologies rely on the open-world assumption, whereas the medical reasoning must consider only evidence-based medical knowledge as true. We designed a Python module for ontology-oriented programming. It allows access to the entities of an OWL ontology as if they were objects in the programming language. We propose a simple high-level syntax for managing classes and the associated "role-filler" constraints. We also propose an algorithm for performing local closed world reasoning in simple situations. We developed Owlready, a Python module for a high-level access to OWL ontologies. The paper describes the architecture and the syntax of the module version 2. It details how we integrated the OWL ontology model with the Python object model. The paper provides examples based on Gene Ontology (GO). We also demonstrate the interest of Owlready in a use case focused on the automatic comparison of the contraindications of several drugs. This use case illustrates the use of the specific syntax proposed for manipulating classes and for performing local closed world reasoning. Owlready has been successfully used in a medical research project. It has been published as Open-Source software and then used by many other researchers. Future developments will focus on the support of vagueness and additional non-monotonic reasoning feature, and automatic dialog box generation. Copyright © 2017 Elsevier B.V. All rights reserved.

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

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 .

Analyzing microtomography data with Python and the scikit-image library.

PubMed

Gouillart, Emmanuelle; Nunez-Iglesias, Juan; van der Walt, Stéfan

2017-01-01

The exploration and processing of images is a vital aspect of the scientific workflows of many X-ray imaging modalities. Users require tools that combine interactivity, versatility, and performance. scikit-image is an open-source image processing toolkit for the Python language that supports a large variety of file formats and is compatible with 2D and 3D images. The toolkit exposes a simple programming interface, with thematic modules grouping functions according to their purpose, such as image restoration, segmentation, and measurements. scikit-image users benefit from a rich scientific Python ecosystem that contains many powerful libraries for tasks such as visualization or machine learning. scikit-image combines a gentle learning curve, versatile image processing capabilities, and the scalable performance required for the high-throughput analysis of X-ray imaging data.

A 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 variety of compressed binary file formats. The 'mwtab' package is an easy-to-use Python package that provides FAIRer utilization of the Metabolomics Workbench Data Repository. The source code is freely available on GitHub and via the Python Package Index. Documentation includes a 'User Guide', 'Tutorial', and 'API Reference'. The GitHub repository also provides 'mwtab' package unit-tests via a continuous integration service.

REDItools: high-throughput RNA editing detection made easy.

PubMed

Picardi, Ernesto; Pesole, Graziano

2013-07-15

The reliable detection of RNA editing sites from massive sequencing data remains challenging and, although several methodologies have been proposed, no computational tools have been released to date. Here, we introduce REDItools a suite of python scripts to perform high-throughput investigation of RNA editing using next-generation sequencing data. REDItools are in python programming language and freely available at http://code.google.com/p/reditools/. ernesto.picardi@uniba.it or graziano.pesole@uniba.it Supplementary data are available at Bioinformatics online.

SimulatorToFMU v0.1

DOE Office of Scientific and Technical Information (OSTI.GOV)

Nouidui, Thierry; Wetter, Michael

SimulatorToFMU is a software package written in Python which allows users to export a memoryless Python-driven simulation program or script as a Functional Mock-up Unit (FMU) for model exchange or co-simulation.In CyDER (Cyber Physical Co-simulation Platform for Distributed Energy Resources in Smart Grids), SimulatorToFMU will allow exporting OPAL-RT as an FMU. This will enable OPAL-RT to be linked to CYMDIST and GridDyn FMUs through a standardized open source interface.

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 .

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

Testing Deceptive Honeypots

DTIC Science & Technology

2014-09-01

get install python2.7 python- openssl python-gevent libevent-dev python2.7-dev build-essential make liblapack-dev libmysqlclient-dev python-chardet...apt-get install python-dev openssl python- openssl python-pyasn1 python-twisted • apt-get install subversion • apt-get install authbind 4

Computational thermochemistry: Automated generation of scale factors for vibrational frequencies calculated by electronic structure model chemistries

NASA Astrophysics Data System (ADS)

Yu, Haoyu S.; Fiedler, Lucas J.; Alecu, I. M.; Truhlar, Donald G.

2017-01-01

We present a Python program, FREQ, for calculating the optimal scale factors for calculating harmonic vibrational frequencies, fundamental vibrational frequencies, and zero-point vibrational energies from electronic structure calculations. The program utilizes a previously published scale factor optimization model (Alecu et al., 2010) to efficiently obtain all three scale factors from a set of computed vibrational harmonic frequencies. In order to obtain the three scale factors, the user only needs to provide zero-point energies of 15 or 6 selected molecules. If the user has access to the Gaussian 09 or Gaussian 03 program, we provide the option for the user to run the program by entering the keywords for a certain method and basis set in the Gaussian 09 or Gaussian 03 program. Four other Python programs, input.py, input6, pbs.py, and pbs6.py, are also provided for generating Gaussian 09 or Gaussian 03 input and PBS files. The program can also be used with data from any other electronic structure package. A manual of how to use this program is included in the code package.

PyGaze: an open-source, cross-platform toolbox for minimal-effort programming of eyetracking experiments.

PubMed

Dalmaijer, Edwin S; Mathôt, Sebastiaan; Van der Stigchel, Stefan

2014-12-01

The PyGaze toolbox is an open-source software package for Python, a high-level programming language. It is designed for creating eyetracking experiments in Python syntax with the least possible effort, and it offers programming ease and script readability without constraining functionality and flexibility. PyGaze can be used for visual and auditory stimulus presentation; for response collection via keyboard, mouse, joystick, and other external hardware; and for the online detection of eye movements using a custom algorithm. A wide range of eyetrackers of different brands (EyeLink, SMI, and Tobii systems) are supported. The novelty of PyGaze lies in providing an easy-to-use layer on top of the many different software libraries that are required for implementing eyetracking experiments. Essentially, PyGaze is a software bridge for eyetracking research.

Using POGIL to Help Students Learn to Program

ERIC Educational Resources Information Center

Hu, Helen H.; Shepherd, Tricia D.

2013-01-01

POGIL has been successfully implemented in a scientific computing course to teach science students how to program in Python. Following POGIL guidelines, the authors have developed guided inquiry activities that lead student teams to discover and understand programming concepts. With each iteration of the scientific computing course, the authors…

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.

A Coupled Simulation Architecture for Agent-Based/Geohydrological Modelling

NASA Astrophysics Data System (ADS)

Jaxa-Rozen, M.

2016-12-01

The quantitative modelling of social-ecological systems can provide useful insights into the interplay between social and environmental processes, and their impact on emergent system dynamics. However, such models should acknowledge the complexity and uncertainty of both of the underlying subsystems. For instance, the agent-based models which are increasingly popular for groundwater management studies can be made more useful by directly accounting for the hydrological processes which drive environmental outcomes. Conversely, conventional environmental models can benefit from an agent-based depiction of the feedbacks and heuristics which influence the decisions of groundwater users. From this perspective, this work describes a Python-based software architecture which couples the popular NetLogo agent-based platform with the MODFLOW/SEAWAT geohydrological modelling environment. This approach enables users to implement agent-based models in NetLogo's user-friendly platform, while benefiting from the full capabilities of MODFLOW/SEAWAT packages or reusing existing geohydrological models. The software architecture is based on the pyNetLogo connector, which provides an interface between the NetLogo agent-based modelling software and the Python programming language. This functionality is then extended and combined with Python's object-oriented features, to design a simulation architecture which couples NetLogo with MODFLOW/SEAWAT through the FloPy library (Bakker et al., 2016). The Python programming language also provides access to a range of external packages which can be used for testing and analysing the coupled models, which is illustrated for an application of Aquifer Thermal Energy Storage (ATES).

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

PubMed

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

2014-01-01

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

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

PubMed Central

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

2014-01-01

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

Papers and Proceedings of the Combined Annual Meetings of the Midwest History of Education Society and the History of Education Society (Chicago, Illinois, October 27-29, 1978).

ERIC Educational Resources Information Center

Rutkowski, Edward, Ed.

1979-01-01

The selected papers presented in this document include topics on normal schools in Wisconsin and Minnesota, George S. Counts, and segregated schooling in Kansas. "Wisconsin Normal Schools and the Educational Hierarchy, 1860-1890" (J. Wasserman) describes the struggle of normal schools to be perceived as teacher training institutions…

Novel Interventions for Heat/Exercise Induced Sudden Death and Fatigue

DTIC Science & Technology

2011-10-01

292(1): p. E331-E339. 26. Wasserman, K., Beaver, W.L. and Whipp, B.J. , Gas exchange theory and the lactic acidosis ( anaerobic ) threshold ...the anaerobic threshold . J Sports Sci Med, 2005. 4: p. 29-36. 28. McBride, A., Ghilagaber, S., Nikolaev, A., and Hardie, D.G., The glycogen- binding...Induced Sudden Death and Fatigue PRINCIPAL INVESTIGATOR: Susan L. Hamilton, Ph.D

A specific prediction equation is necessary to estimate peak oxygen uptake in obese patients with metabolic syndrome.

PubMed

Debeaumont, D; Tardif, C; Folope, V; Castres, I; Lemaitre, F; Tourny, C; Dechelotte, P; Thill, C; Darmon, A; Coquart, J B

2016-06-01

The aims were to: (1) compare peak oxygen uptake ([Formula: see text]peak) predicted from four standard equations to actual [Formula: see text]peak measured from a cardiopulmonary exercise test (CPET) in obese patients with metabolic syndrome (MetS), and (2) develop a new equation to accurately estimate [Formula: see text]peak in obese women with MetS. Seventy-five obese patients with MetS performed a CPET. Anthropometric data were also collected for each participant. [Formula: see text]peak was predicted from four prediction equations (from Riddle et al., Hansen et al., Wasserman et al. or Gläser et al.) and then compared with the actual [Formula: see text]peak measured during the CPET. The accuracy of the predictions was determined with the Bland-Altman method. When accuracy was low, a new prediction equation including anthropometric variables was proposed. [Formula: see text]peak predicted from the equation of Wasserman et al. was not significantly different from actual [Formula: see text]peak in women. Moreover, a significant correlation was found between the predicted and actual values (p < 0.001, r = 0.69). In men, no significant difference was noted between actual [Formula: see text]peak and [Formula: see text]peak predicted from the prediction equation of Gläser et al., and these two values were also correlated (p = 0.03, r = 0.44). However, the LoA95% was wide, whatever the prediction equation or gender. Regression analysis suggested a new prediction equation derived from age and height for obese women with MetS. The methods of Wasserman et al. and Gläser et al. are valid to predict [Formula: see text]peak in obese women and men with MetS, respectively. However, the accuracy of the predictions was low for both methods. Consequently, a new prediction equation including age and height was developed for obese women with MetS. However, new prediction equation remains to develop in obese men with MetS.

A Multidisciplinary Tool for Systems Analysis of Planetary Entry, Descent, and Landing (SAPE)

NASA Technical Reports Server (NTRS)

Samareh, Jamshid A.

2009-01-01

SAPE is a Python-based multidisciplinary analysis tool for systems analysis of planetary entry, descent, and landing (EDL) for Venus, Earth, Mars, Jupiter, Saturn, Uranus, Neptune, and Titan. The purpose of SAPE is to provide a variable-fidelity capability for conceptual and preliminary analysis within the same framework. SAPE includes the following analysis modules: geometry, trajectory, aerodynamics, aerothermal, thermal protection system, and structural sizing. SAPE uses the Python language-a platform-independent open-source software for integration and for the user interface. The development has relied heavily on the object-oriented programming capabilities that are available in Python. Modules are provided to interface with commercial and government off-the-shelf software components (e.g., thermal protection systems and finite-element analysis). SAPE runs on Microsoft Windows and Apple Mac OS X and has been partially tested on Linux.

Teaching Introductory GIS Programming to Geographers Using an Open Source Python Approach

ERIC Educational Resources Information Center

Etherington, Thomas R.

2016-01-01

Computer programming is not commonly taught to geographers as a part of geographic information system (GIS) courses, but the advent of NeoGeography, big data and open GIS means that programming skills are becoming more important. To encourage the teaching of programming to geographers, this paper outlines a course based around a series of…

T-Reg Comparator: an analysis tool for the comparison of position weight matrices

PubMed Central

Roepcke, Stefan; Grossmann, Steffen; Rahmann, Sven; Vingron, Martin

2005-01-01

T-Reg Comparator is a novel software tool designed to support research into transcriptional regulation. Sequence motifs representing transcription factor binding sites are usually encoded as position weight matrices. The user inputs a set of such weight matrices or binding site sequences and our program matches them against the T-Reg database, which is presently built on data from the Transfac [E. Wingender (2004) In Silico Biol., 4, 55–61] and Jaspar [A. Sandelin, W. Alkema, P. Engstrom, W. W. Wasserman and B. Lenhard (2004) Nucleic Acids Res., 32, D91–D94]. Our tool delivers a detailed report on similarities between user-supplied motifs and motifs in the database. Apart from simple one-to-one relationships, T-Reg Comparator is also able to detect similarities between submatrices. In addition, we provide a user interface to a program for sequence scanning with weight matrices. Typical areas of application for T-Reg Comparator are motif and regulatory module finding and annotation of regulatory genomic regions. T-Reg Comparator is available at . PMID:15980506

T-Reg Comparator: an analysis tool for the comparison of position weight matrices.

PubMed

Roepcke, Stefan; Grossmann, Steffen; Rahmann, Sven; Vingron, Martin

2005-07-01

T-Reg Comparator is a novel software tool designed to support research into transcriptional regulation. Sequence motifs representing transcription factor binding sites are usually encoded as position weight matrices. The user inputs a set of such weight matrices or binding site sequences and our program matches them against the T-Reg database, which is presently built on data from the Transfac [E. Wingender (2004) In Silico Biol., 4, 55-61] and Jaspar [A. Sandelin, W. Alkema, P. Engstrom, W. W. Wasserman and B. Lenhard (2004) Nucleic Acids Res., 32, D91-D94]. Our tool delivers a detailed report on similarities between user-supplied motifs and motifs in the database. Apart from simple one-to-one relationships, T-Reg Comparator is also able to detect similarities between submatrices. In addition, we provide a user interface to a program for sequence scanning with weight matrices. Typical areas of application for T-Reg Comparator are motif and regulatory module finding and annotation of regulatory genomic regions. T-Reg Comparator is available at http://treg.molgen.mpg.de.

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.

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

NASA Astrophysics Data System (ADS)

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

2012-08-01

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

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.

Arc4nix: A cross-platform geospatial analytical library for cluster and cloud computing

NASA Astrophysics Data System (ADS)

Tang, Jingyin; Matyas, Corene J.

2018-02-01

Big Data in geospatial technology is a grand challenge for processing capacity. The ability to use a GIS for geospatial analysis on Cloud Computing and High Performance Computing (HPC) clusters has emerged as a new approach to provide feasible solutions. However, users lack the ability to migrate existing research tools to a Cloud Computing or HPC-based environment because of the incompatibility of the market-dominating ArcGIS software stack and Linux operating system. This manuscript details a cross-platform geospatial library "arc4nix" to bridge this gap. Arc4nix provides an application programming interface compatible with ArcGIS and its Python library "arcpy". Arc4nix uses a decoupled client-server architecture that permits geospatial analytical functions to run on the remote server and other functions to run on the native Python environment. It uses functional programming and meta-programming language to dynamically construct Python codes containing actual geospatial calculations, send them to a server and retrieve results. Arc4nix allows users to employ their arcpy-based script in a Cloud Computing and HPC environment with minimal or no modification. It also supports parallelizing tasks using multiple CPU cores and nodes for large-scale analyses. A case study of geospatial processing of a numerical weather model's output shows that arcpy scales linearly in a distributed environment. Arc4nix is open-source software.

Programming for physicians: A free online course.

PubMed

Kubben, Pieter L

2016-01-01

This article is an introduction for clinical readers into programming and computational thinking using the programming language Python. Exercises can be done completely online without any need for installation of software. Participants will be taught the fundamentals of programming, which are necessarily independent of the sort of application (stand-alone, web, mobile, engineering, and statistical/machine learning) that is to be developed afterward.

Harnessing Full Value from the DoD Serum Repository and the Defense Medical Surveillance System

DTIC Science & Technology

2010-01-01

Munger KL, Rubertone MV, Peck CA, Lennette ET, Spiegelman D, Ascherio A. Temporal relationship between elevation of epstein - barr virus antibody titers...Rubertone MV, Peck CA, Lennette ET, Spiegelman D, Ascherio A. Multiple sclerosis and Epstein - Barr virus . JAMA. 2003; 289:1533–6. 44. Wasserman GM... vaccine development against diseases that threaten military personnel, prophylactic and treatment drugs for infectious diseases, techniques for

Statistical Machine Learning for Structured and High Dimensional Data

DTIC Science & Technology

2014-09-17

AFRL-OSR-VA-TR-2014-0234 STATISTICAL MACHINE LEARNING FOR STRUCTURED AND HIGH DIMENSIONAL DATA Larry Wasserman CARNEGIE MELLON UNIVERSITY Final...Re . 8-98) v Prescribed by ANSI Std. Z39.18 14-06-2014 Final Dec 2009 - Aug 2014 Statistical Machine Learning for Structured and High Dimensional...area of resource-constrained statistical estimation. machine learning , high-dimensional statistics U U U UU John Lafferty 773-702-3813 > Research under

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.

Optimizing python-based ROOT I/O with PyPy's tracing just-in-time compiler

NASA Astrophysics Data System (ADS)

Tlp Lavrijsen, Wim

2012-12-01

The Python programming language allows objects and classes to respond dynamically to the execution environment. Most of this, however, is made possible through language hooks which by definition can not be optimized and thus tend to be slow. The PyPy implementation of Python includes a tracing just in time compiler (JIT), which allows similar dynamic responses but at the interpreter-, rather than the application-level. Therefore, it is possible to fully remove the hooks, leaving only the dynamic response, in the optimization stage for hot loops, if the types of interest are opened up to the JIT. A general opening up of types to the JIT, based on reflection information, has already been developed (cppyy). The work described in this paper takes it one step further by customizing access to ROOT I/O to the JIT, allowing for fully automatic optimizations.

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…

EggLib: processing, analysis and simulation tools for population genetics and genomics

PubMed Central

2012-01-01

Background With the considerable growth of available nucleotide sequence data over the last decade, integrated and flexible analytical tools have become a necessity. In particular, in the field of population genetics, there is a strong need for automated and reliable procedures to conduct repeatable and rapid polymorphism analyses, coalescent simulations, data manipulation and estimation of demographic parameters under a variety of scenarios. Results In this context, we present EggLib (Evolutionary Genetics and Genomics Library), a flexible and powerful C++/Python software package providing efficient and easy to use computational tools for sequence data management and extensive population genetic analyses on nucleotide sequence data. EggLib is a multifaceted project involving several integrated modules: an underlying computationally efficient C++ library (which can be used independently in pure C++ applications); two C++ programs; a Python package providing, among other features, a high level Python interface to the C++ library; and the egglib script which provides direct access to pre-programmed Python applications. Conclusions EggLib has been designed aiming to be both efficient and easy to use. A wide array of methods are implemented, including file format conversion, sequence alignment edition, coalescent simulations, neutrality tests and estimation of demographic parameters by Approximate Bayesian Computation (ABC). Classes implementing different demographic scenarios for ABC analyses can easily be developed by the user and included to the package. EggLib source code is distributed freely under the GNU General Public License (GPL) from its website http://egglib.sourceforge.net/ where a full documentation and a manual can also be found and downloaded. PMID:22494792

EggLib: processing, analysis and simulation tools for population genetics and genomics.

PubMed

De Mita, Stéphane; Siol, Mathieu

2012-04-11

With the considerable growth of available nucleotide sequence data over the last decade, integrated and flexible analytical tools have become a necessity. In particular, in the field of population genetics, there is a strong need for automated and reliable procedures to conduct repeatable and rapid polymorphism analyses, coalescent simulations, data manipulation and estimation of demographic parameters under a variety of scenarios. In this context, we present EggLib (Evolutionary Genetics and Genomics Library), a flexible and powerful C++/Python software package providing efficient and easy to use computational tools for sequence data management and extensive population genetic analyses on nucleotide sequence data. EggLib is a multifaceted project involving several integrated modules: an underlying computationally efficient C++ library (which can be used independently in pure C++ applications); two C++ programs; a Python package providing, among other features, a high level Python interface to the C++ library; and the egglib script which provides direct access to pre-programmed Python applications. EggLib has been designed aiming to be both efficient and easy to use. A wide array of methods are implemented, including file format conversion, sequence alignment edition, coalescent simulations, neutrality tests and estimation of demographic parameters by Approximate Bayesian Computation (ABC). Classes implementing different demographic scenarios for ABC analyses can easily be developed by the user and included to the package. EggLib source code is distributed freely under the GNU General Public License (GPL) from its website http://egglib.sourceforge.net/ where a full documentation and a manual can also be found and downloaded.

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.

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.

Pyro: A Python-Based Versatile Programming Environment for Teaching Robotics

ERIC Educational Resources Information Center

Blank, Douglas; Kumar, Deepak; Meeden, Lisa; Yanco, Holly

2004-01-01

In this article we describe a programming framework called Pyro, which provides a set of abstractions that allows students to write platform-independent robot programs. This project is unique because of its focus on the pedagogical implications of teaching mobile robotics via a top-down approach. We describe the background of the project, its…

A comparison of common programming languages used in bioinformatics.

PubMed

Fourment, Mathieu; Gillings, Michael R

2008-02-05

The performance of different programming languages has previously been benchmarked using abstract mathematical algorithms, but not using standard bioinformatics algorithms. We compared the memory usage and speed of execution for three standard bioinformatics methods, implemented in programs using one of six different programming languages. Programs for the Sellers algorithm, the Neighbor-Joining tree construction algorithm and an algorithm for parsing BLAST file outputs were implemented in C, C++, C#, Java, Perl and Python. Implementations in C and C++ were fastest and used the least memory. Programs in these languages generally contained more lines of code. Java and C# appeared to be a compromise between the flexibility of Perl and Python and the fast performance of C and C++. The relative performance of the tested languages did not change from Windows to Linux and no clear evidence of a faster operating system was found. Source code and additional information are available from http://www.bioinformatics.org/benchmark/. This benchmark provides a comparison of six commonly used programming languages under two different operating systems. The overall comparison shows that a developer should choose an appropriate language carefully, taking into account the performance expected and the library availability for each language.

A comparison of common programming languages used in bioinformatics

PubMed Central

Fourment, Mathieu; Gillings, Michael R

2008-01-01

Background The performance of different programming languages has previously been benchmarked using abstract mathematical algorithms, but not using standard bioinformatics algorithms. We compared the memory usage and speed of execution for three standard bioinformatics methods, implemented in programs using one of six different programming languages. Programs for the Sellers algorithm, the Neighbor-Joining tree construction algorithm and an algorithm for parsing BLAST file outputs were implemented in C, C++, C#, Java, Perl and Python. Results Implementations in C and C++ were fastest and used the least memory. Programs in these languages generally contained more lines of code. Java and C# appeared to be a compromise between the flexibility of Perl and Python and the fast performance of C and C++. The relative performance of the tested languages did not change from Windows to Linux and no clear evidence of a faster operating system was found. Source code and additional information are available from Conclusion This benchmark provides a comparison of six commonly used programming languages under two different operating systems. The overall comparison shows that a developer should choose an appropriate language carefully, taking into account the performance expected and the library availability for each language. PMID:18251993

76 FR 40082 - Semiannual Regulatory Agenda

Federal Register 2010, 2011, 2012, 2013, 2014

2011-07-07

...; Constrictor Species From Python, Boa, and Eunectes Genera. Bureau of Ocean Energy Management, Regulation, and... Wildlife Evaluation; Constrictor Species from Python, Boa, and Eunectes Genera Legal Authority: 18 U.S.C... are: Indian python (including Burmese python), reticulated python, Northern African python, Southern...

An Introduction to Programming for Bioscientists: A Python-Based Primer

PubMed Central

Mura, Cameron

2016-01-01

Computing has revolutionized the biological sciences over the past several decades, such that virtually all contemporary research in molecular biology, biochemistry, and other biosciences utilizes computer programs. The computational advances have come on many fronts, spurred by fundamental developments in hardware, software, and algorithms. These advances have influenced, and even engendered, a phenomenal array of bioscience fields, including molecular evolution and bioinformatics; genome-, proteome-, transcriptome- and metabolome-wide experimental studies; structural genomics; and atomistic simulations of cellular-scale molecular assemblies as large as ribosomes and intact viruses. In short, much of post-genomic biology is increasingly becoming a form of computational biology. The ability to design and write computer programs is among the most indispensable skills that a modern researcher can cultivate. Python has become a popular programming language in the biosciences, largely because (i) its straightforward semantics and clean syntax make it a readily accessible first language; (ii) it is expressive and well-suited to object-oriented programming, as well as other modern paradigms; and (iii) the many available libraries and third-party toolkits extend the functionality of the core language into virtually every biological domain (sequence and structure analyses, phylogenomics, workflow management systems, etc.). This primer offers a basic introduction to coding, via Python, and it includes concrete examples and exercises to illustrate the language’s usage and capabilities; the main text culminates with a final project in structural bioinformatics. A suite of Supplemental Chapters is also provided. Starting with basic concepts, such as that of a “variable,” the Chapters methodically advance the reader to the point of writing a graphical user interface to compute the Hamming distance between two DNA sequences. PMID:27271528

An Introduction to Programming for Bioscientists: A Python-Based Primer.

PubMed

Ekmekci, Berk; McAnany, Charles E; Mura, Cameron

2016-06-01

Computing has revolutionized the biological sciences over the past several decades, such that virtually all contemporary research in molecular biology, biochemistry, and other biosciences utilizes computer programs. The computational advances have come on many fronts, spurred by fundamental developments in hardware, software, and algorithms. These advances have influenced, and even engendered, a phenomenal array of bioscience fields, including molecular evolution and bioinformatics; genome-, proteome-, transcriptome- and metabolome-wide experimental studies; structural genomics; and atomistic simulations of cellular-scale molecular assemblies as large as ribosomes and intact viruses. In short, much of post-genomic biology is increasingly becoming a form of computational biology. The ability to design and write computer programs is among the most indispensable skills that a modern researcher can cultivate. Python has become a popular programming language in the biosciences, largely because (i) its straightforward semantics and clean syntax make it a readily accessible first language; (ii) it is expressive and well-suited to object-oriented programming, as well as other modern paradigms; and (iii) the many available libraries and third-party toolkits extend the functionality of the core language into virtually every biological domain (sequence and structure analyses, phylogenomics, workflow management systems, etc.). This primer offers a basic introduction to coding, via Python, and it includes concrete examples and exercises to illustrate the language's usage and capabilities; the main text culminates with a final project in structural bioinformatics. A suite of Supplemental Chapters is also provided. Starting with basic concepts, such as that of a "variable," the Chapters methodically advance the reader to the point of writing a graphical user interface to compute the Hamming distance between two DNA sequences.

A Flexible Method for Producing F.E.M. Analysis of Bone Using Open-Source Software

NASA Technical Reports Server (NTRS)

Boppana, Abhishektha; Sefcik, Ryan; Meyers, Jerry G.; Lewandowski, Beth E.

2016-01-01

This project, performed in support of the NASA GRC Space Academy summer program, sought to develop an open-source workflow methodology that segmented medical image data, created a 3D model from the segmented data, and prepared the model for finite-element analysis. In an initial step, a technological survey evaluated the performance of various existing open-source software that claim to perform these tasks. However, the survey concluded that no single software exhibited the wide array of functionality required for the potential NASA application in the area of bone, muscle and bio fluidic studies. As a result, development of a series of Python scripts provided the bridging mechanism to address the shortcomings of the available open source tools. The implementation of the VTK library provided the most quick and effective means of segmenting regions of interest from the medical images; it allowed for the export of a 3D model by using the marching cubes algorithm to build a surface mesh. To facilitate the development of the model domain from this extracted information required a surface mesh to be processed in the open-source software packages Blender and Gmsh. The Preview program of the FEBio suite proved to be sufficient for volume filling the model with an unstructured mesh and preparing boundaries specifications for finite element analysis. To fully allow FEM modeling, an in house developed Python script allowed assignment of material properties on an element by element basis by performing a weighted interpolation of voxel intensity of the parent medical image correlated to published information of image intensity to material properties, such as ash density. A graphical user interface combined the Python scripts and other software into a user friendly interface. The work using Python scripts provides a potential alternative to expensive commercial software and inadequate, limited open-source freeware programs for the creation of 3D computational models. More work will be needed to validate this approach in creating finite-element models.

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.

Programming for physicians: A free online course

PubMed Central

Kubben, Pieter L.

2016-01-01

This article is an introduction for clinical readers into programming and computational thinking using the programming language Python. Exercises can be done completely online without any need for installation of software. Participants will be taught the fundamentals of programming, which are necessarily independent of the sort of application (stand-alone, web, mobile, engineering, and statistical/machine learning) that is to be developed afterward. PMID:27127694

PyMICE: APython library for analysis of IntelliCage data.

PubMed

Dzik, Jakub M; Puścian, Alicja; Mijakowska, Zofia; Radwanska, Kasia; Łęski, Szymon

2018-04-01

IntelliCage is an automated system for recording the behavior of a group of mice housed together. It produces rich, detailed behavioral data calling for new methods and software for their analysis. Here we present PyMICE, a free and open-source library for analysis of IntelliCage data in the Python programming language. We describe the design and demonstrate the use of the library through a series of examples. PyMICE provides easy and intuitive access to IntelliCage data, and thus facilitates the possibility of using numerous other Python scientific libraries to form a complete data analysis workflow.

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.

A New Effort for Atmospherical Forecast: Meteorological Image Processing Software (MIPS) for Astronomical Observations

NASA Astrophysics Data System (ADS)

Shameoni Niaei, M.; Kilic, Y.; Yildiran, B. E.; Yüzlükoglu, F.; Yesilyaprak, C.

2016-12-01

We have described a new software (MIPS) about the analysis and image processing of the meteorological satellite (Meteosat) data for an astronomical observatory. This software will be able to help to make some atmospherical forecast (cloud, humidity, rain) using meteosat data for robotic telescopes. MIPS uses a python library for Eumetsat data that aims to be completely open-source and licenced under GNU/General Public Licence (GPL). MIPS is a platform independent and uses h5py, numpy, and PIL with the general-purpose and high-level programming language Python and the QT framework.

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

What about a Simple Language? Analyzing the Difficulties in Learning to Program

ERIC Educational Resources Information Center

Mannila, Linda; Peltomaki, Mia; Salakoski, Tapio

2006-01-01

In this paper, we present the results from a two-part study. We analyze 60 programs written by novice programmers aged 16-19 after their first programming course, in either Java or Python. The aim is to find difficulties independent of the language used, and such originating from the language. Second, we analyze the transition from a…

PyPele Rewritten To Use MPI

NASA Technical Reports Server (NTRS)

Hockney, George; Lee, Seungwon

2008-01-01

A computer program known as PyPele, originally written as a Pythonlanguage extension module of a C++ language program, has been rewritten in pure Python language. The original version of PyPele dispatches and coordinates parallel-processing tasks on cluster computers and provides a conceptual framework for spacecraft-mission- design and -analysis software tools to run in an embarrassingly parallel mode. The original version of PyPele uses SSH (Secure Shell a set of standards and an associated network protocol for establishing a secure channel between a local and a remote computer) to coordinate parallel processing. Instead of SSH, the present Python version of PyPele uses Message Passing Interface (MPI) [an unofficial de-facto standard language-independent application programming interface for message- passing on a parallel computer] while keeping the same user interface. The use of MPI instead of SSH and the preservation of the original PyPele user interface make it possible for parallel application programs written previously for the original version of PyPele to run on MPI-based cluster computers. As a result, engineers using the previously written application programs can take advantage of embarrassing parallelism without need to rewrite those programs.

Visual Basic VPython Interface: Charged Particle in a Magnetic Field

NASA Astrophysics Data System (ADS)

Prayaga, Chandra

2006-12-01

A simple Visual Basic (VB) to VPython interface is described and illustrated with the example of a charged particle in a magnetic field. This interface allows data to be passed to Python through a text file read by Python. The first component of the interface is a user-friendly data entry screen designed in VB, in which the user can input values of the charge, mass, initial position and initial velocity of the particle, and the magnetic field. Next, a command button is coded to write these values to a text file. Another command button starts the VPython program, which reads the data from the text file, numerically solves the equation of motion, and provides the 3d graphics animation. Students can use the interface to run the program several times with different data and observe changes in the motion.

Software Development for Asteroid and Variable Star Research

NASA Astrophysics Data System (ADS)

Sweckard, Teaghen; Clason, Timothy; Kenney, Jessica; Wuerker, Wolfgang; Palser, Sage; Giles, Tucker; Linder, Tyler; Sanchez, Richard

2018-01-01

The process of collecting and analyzing light curves from variable stars and asteroids is almost identical. In 2016 a collaboration was created to develop a simple fundamental way to study both asteroids and variable stars using methods that would allow the process to be repeated by middle school and high school students.Using robotic telescopes at Cerro Tololo (Chile), Yerkes Observatory (US), and Stone Edge Observatory (US) data were collected on RV Del and three asteroids. It was discovered that the only available software program which could be easily installed on lab computers was MPO Canopus. However, after six months it was determined that MPO Canopus was not an acceptable option because of the steep learning curve, lack of documentation and technical support.Therefore, the project decided that the best option was to design our own python based software. Using python and python libraries we developed code that can be used for photometry and can be easily changed to the user's needs. We accomplished this by meeting with our mentor astronomer, Tyler Linder, and in the beginning wrote two different programs, one for asteroids and one for variable stars. In the end, though, we chose to combine codes so that the program would be capable of performing photometry for both moving and static objects.The software performs differential photometry by comparing the magnitude of known reference stars to the object being studied. For asteroids, the image timestamps are used to obtain ephemeris of the asteroid from JPL Horizons automatically.

ALOHA: Automatic libraries of helicity amplitudes for Feynman diagram computations

NASA Astrophysics Data System (ADS)

de Aquino, Priscila; Link, William; Maltoni, Fabio; Mattelaer, Olivier; Stelzer, Tim

2012-10-01

We present an application that automatically writes the HELAS (HELicity Amplitude Subroutines) library corresponding to the Feynman rules of any quantum field theory Lagrangian. The code is written in Python and takes the Universal FeynRules Output (UFO) as an input. From this input it produces the complete set of routines, wave-functions and amplitudes, that are needed for the computation of Feynman diagrams at leading as well as at higher orders. The representation is language independent and currently it can output routines in Fortran, C++, and Python. A few sample applications implemented in the MADGRAPH 5 framework are presented. Program summary Program title: ALOHA Catalogue identifier: AEMS_v1_0 Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AEMS_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: http://www.opensource.org/licenses/UoI-NCSA.php No. of lines in distributed program, including test data, etc.: 6094320 No. of bytes in distributed program, including test data, etc.: 7479819 Distribution format: tar.gz Programming language: Python2.6 Computer: 32/64 bit Operating system: Linux/Mac/Windows RAM: 512 Mbytes Classification: 4.4, 11.6 Nature of problem: An effcient numerical evaluation of a squared matrix element can be done with the help of the helicity routines implemented in the HELAS library [1]. This static library contains a limited number of helicity functions and is therefore not always able to provide the needed routine in the presence of an arbitrary interaction. This program provides a way to automatically create the corresponding routines for any given model. Solution method: ALOHA takes the Feynman rules associated to the vertex obtained from the model information (in the UFO format [2]), and multiplies it by the different wavefunctions or propagators. As a result the analytical expression of the helicity routines is obtained. Subsequently, this expression is automatically written in the requested language (Python, Fortran or C++) Restrictions: The allowed fields are currently spin 0, 1/2, 1 and 2, and the propagators of these particles are canonical. Running time: A few seconds for the SM and the MSSM, and up to a few minutes for models with spin 2 particles. References: [1] Murayama, H. and Watanabe, I. and Hagiwara, K., HELAS: HELicity Amplitude Subroutines for Feynman diagram evaluations, KEK-91-11, (1992) http://www-lib.kek.jp/cgi-bin/img_index?199124011 [2] C. Degrande, C. Duhr, B. Fuks, D. Grellscheid, O. Mattelaer, et al., UFO— The Universal FeynRules Output, Comput. Phys. Commun. 183 (2012) 1201-1214. arXiv:1108.2040, doi:10.1016/j.cpc.2012.01.022.

THRESH—Software for tracking rainfall thresholds for landslide and debris-flow occurrence, user manual

USGS Publications Warehouse

Baum, Rex L.; Fischer, Sarah J.; Vigil, Jacob C.

2018-02-28

Precipitation thresholds are used in many areas to provide early warning of precipitation-induced landslides and debris flows, and the software distribution THRESH is designed for automated tracking of precipitation, including precipitation forecasts, relative to thresholds for landslide occurrence. This software is also useful for analyzing multiyear precipitation records to compare timing of threshold exceedance with dates and times of historical landslides. This distribution includes the main program THRESH for comparing precipitation to several kinds of thresholds, two utility programs, and a small collection of Python and shell scripts to aid the automated collection and formatting of input data and the graphing and further analysis of output results. The software programs can be deployed on computing platforms that support Fortran 95, Python 2, and certain Unix commands. The software handles rainfall intensity-duration thresholds, cumulative recent-antecedent precipitation thresholds, and peak intensity thresholds as well as various measures of antecedent precipitation. Users should have predefined rainfall thresholds before running THRESH.

Data-Driven Hint Generation in Vast Solution Spaces: A Self-Improving Python Programming Tutor

ERIC Educational Resources Information Center

Rivers, Kelly; Koedinger, Kenneth R.

2017-01-01

To provide personalized help to students who are working on code-writing problems, we introduce a data-driven tutoring system, ITAP (Intelligent Teaching Assistant for Programming). ITAP uses state abstraction, path construction, and state reification to automatically generate personalized hints for students, even when given states that have not…

Automating an integrated spatial data-mining model for landfill site selection

NASA Astrophysics Data System (ADS)

Abujayyab, Sohaib K. M.; Ahamad, Mohd Sanusi S.; Yahya, Ahmad Shukri; Ahmad, Siti Zubaidah; Aziz, Hamidi Abdul

2017-10-01

An integrated programming environment represents a robust approach to building a valid model for landfill site selection. One of the main challenges in the integrated model is the complicated processing and modelling due to the programming stages and several limitations. An automation process helps avoid the limitations and improve the interoperability between integrated programming environments. This work targets the automation of a spatial data-mining model for landfill site selection by integrating between spatial programming environment (Python-ArcGIS) and non-spatial environment (MATLAB). The model was constructed using neural networks and is divided into nine stages distributed between Matlab and Python-ArcGIS. A case study was taken from the north part of Peninsular Malaysia. 22 criteria were selected to utilise as input data and to build the training and testing datasets. The outcomes show a high-performance accuracy percentage of 98.2% in the testing dataset using 10-fold cross validation. The automated spatial data mining model provides a solid platform for decision makers to performing landfill site selection and planning operations on a regional scale.

Efficient Algorithms for Bayesian Network Parameter Learning from Incomplete Data

DTIC Science & Technology

2015-07-01

Efficient Algorithms for Bayesian Network Parameter Learning from Incomplete Data Guy Van den Broeck∗ and Karthika Mohan∗ and Arthur Choi and Adnan ...notwithstanding any other provision of law , no person shall be subject to a penalty for failing to comply with a collection of information if it does...Wasserman, L. (2011). All of Statistics. Springer Science & Business Media. Yaramakala, S., & Margaritis, D. (2005). Speculative markov blanket discovery for optimal feature selection. In Proceedings of ICDM.

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.

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.

Task switching in rhesus macaques (Macaca mulatta) and tufted capuchin monkeys (Cebus apella) during computerized categorization tasks.

PubMed

Smith, Travis R; Beran, Michael J

2018-05-31

The present experiments extended to monkeys a previously used abstract categorization procedure (Castro & Wasserman, 2016) where pigeons had categorized arrays of clipart icons based upon two task rules: the number of clipart objects in the array or the variability of objects in the array. Experiment 1 replicated Castro and Wasserman by using capuchin monkeys and rhesus monkeys and reported that monkeys' performances were similar to pigeons' in terms of acquisition, pattern of errors, and the absence of switch costs. Furthermore, monkeys' insensitivity to the added irrelevant information suggested that an associative (rather than rule-based) categorization mechanism was dominant. Experiment 2 was conducted to include categorization cue reversals to determine (a) whether the monkeys would quickly adapt to the reversals and inhibit interference from a prereversal task rule (consistent with a rule-based mechanism) and (b) whether the latency to make a response prior to a correct or incorrect outcome was informative about the presence of a cognitive mechanism. The cue reassignment produced profound and long-lasting performance deficits, and a long reacquisition phase suggested the involvement of associative learning processes; however, monkeys also displayed longer latencies to choose prior to correct responses on challenging trials, suggesting the involvement of nonassociative processes. Together these performances suggest a mix of associative and cognitive-control processes governing monkey categorization judgments. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

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.

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.

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.

77 FR 7968 - Semiannual Regulatory Agenda

Federal Register 2010, 2011, 2012, 2013, 2014

2012-02-13

...; Constrictor Species From Python, Boa, and Eunectes Genera. National Park Service--Proposed Rule Stage... Evaluation; Constrictor Species From Python, Boa, and Eunectes Genera Legal Authority: 18 U.S.C. 42 Abstract... wildlife under the Lacey Act: Indian python (including Burmese python), reticulated python, Northern...

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.

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.

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.

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

USGS Publications Warehouse

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

2011-01-01

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

Compare Gene Calls

DOE Office of Scientific and Technical Information (OSTI.GOV)

Ecale Zhou, Carol L.

2016-07-05

Compare Gene Calls (CGC) is a Python code used for combining and comparing gene calls from any number of gene callers. A gene caller is a computer program that predicts the extends of open reading frames within genomes of biological organisms.

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

PubMed

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

2012-01-01

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

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.

Stan: A Probabilistic Programming Language for Bayesian Inference and Optimization

ERIC Educational Resources Information Center

Gelman, Andrew; Lee, Daniel; Guo, Jiqiang

2015-01-01

Stan is a free and open-source C++ program that performs Bayesian inference or optimization for arbitrary user-specified models and can be called from the command line, R, Python, Matlab, or Julia and has great promise for fitting large and complex statistical models in many areas of application. We discuss Stan from users' and developers'…

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.

Evaluation of methods to reduce background using the Python-based ELISA_QC program.

PubMed

Webster, Rose P; Cohen, Cinder F; Saeed, Fatima O; Wetzel, Hanna N; Ball, William J; Kirley, Terence L; Norman, Andrew B

2018-05-01

Almost all immunological approaches [immunohistochemistry, enzyme-linked immunosorbent assay (ELISA), Western blot], that are used to quantitate specific proteins have had to address high backgrounds due to non-specific reactivity. We report here for the first time a quantitative comparison of methods for reduction of the background of commercial biotinylated antibodies using the Python-based ELISA_QC program. This is demonstrated using a recombinant humanized anti-cocaine monoclonal antibody. Several approaches, such as adjustment of the incubation time and the concentration of blocking agent, as well as the dilution of secondary antibodies, have been explored to address this issue. In this report, systematic comparisons of two different methods, contrasted with other more traditional methods to address this problem are provided. Addition of heparin (HP) at 1 μg/ml to the wash buffer prior to addition of the secondary biotinylated antibody reduced the elevated background absorbance values (from a mean of 0.313 ± 0.015 to 0.137 ± 0.002). A novel immunodepletion (ID) method also reduced the background (from a mean of 0.331 ± 0.010 to 0.146 ± 0.013). Overall, the ID method generated more similar results at each concentration of the ELISA standard curve to that using the standard lot 1 than the HP method, as analyzed by the Python-based ELISA_QC program. We conclude that the ID method, while more laborious, provides the best solution to resolve the high background seen with specific lots of biotinylated secondary antibody. Copyright © 2018. Published by Elsevier B.V.

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.

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.

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

In silico FRET from simulated dye dynamics

NASA Astrophysics Data System (ADS)

Hoefling, Martin; Grubmüller, Helmut

2013-03-01

Single molecule fluorescence resonance energy transfer (smFRET) experiments probe molecular distances on the nanometer scale. In such experiments, distances are recorded from FRET transfer efficiencies via the Förster formula, E=1/(1+(). The energy transfer however also depends on the mutual orientation of the two dyes used as distance reporter. Since this information is typically inaccessible in FRET experiments, one has to rely on approximations, which reduce the accuracy of these distance measurements. A common approximation is an isotropic and uncorrelated dye orientation distribution. To assess the impact of such approximations, we present the algorithms and implementation of a computational toolkit for the simulation of smFRET on the basis of molecular dynamics (MD) trajectory ensembles. In this study, the dye orientation dynamics, which are used to determine dynamic FRET efficiencies, are extracted from MD simulations. In a subsequent step, photons and bursts are generated using a Monte Carlo algorithm. The application of the developed toolkit on a poly-proline system demonstrated good agreement between smFRET simulations and experimental results and therefore confirms our computational method. Furthermore, it enabled the identification of the structural basis of measured heterogeneity. The presented computational toolkit is written in Python, available as open-source, applicable to arbitrary systems and can easily be extended and adapted to further problems. Catalogue identifier: AENV_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AENV_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GPLv3, the bundled SIMD friendly Mersenne twister implementation [1] is provided under the SFMT-License. No. of lines in distributed program, including test data, etc.: 317880 No. of bytes in distributed program, including test data, etc.: 54774217 Distribution format: tar.gz Programming language: Python, Cython, C (ANSI C99). Computer: Any (see memory requirements). Operating system: Any OS with CPython distribution (e.g. Linux, MacOSX, Windows). Has the code been vectorised or parallelized?: Yes, in Ref. [2], 4 CPU cores were used. RAM: About 700MB per process for the simulation setup in Ref. [2]. Classification: 16.1, 16.7, 23. External routines: Calculation of Rκ2-trajectories from GROMACS [3] MD trajectories requires the GromPy Python module described in Ref. [4] or a GROMACS 4.6 installation. The md2fret program uses a standard Python interpreter (CPython) v2.6+ and < v3.0 as well as the NumPy module. The analysis examples require the Matplotlib Python module. Nature of problem: Simulation and interpretation of single molecule FRET experiments. Solution method: Combination of force-field based molecular dynamics (MD) simulating the dye dynamics and Monte Carlo sampling to obtain photon statistics of FRET kinetics. Additional comments: !!!!! The distribution file for this program is over 50 Mbytes and therefore is not delivered directly when download or Email is requested. Instead a html file giving details of how the program can be obtained is sent. !!!!! Running time: A single run in Ref. [2] takes about 10 min on a Quad Core Intel Xeon CPU W3520 2.67GHz with 6GB physical RAM References: [1] M. Saito, M. Matsumoto, SIMD-oriented fast Mersenne twister: a 128-bit pseudorandom number generator, in: A. Keller, S. Heinrich, H. Niederreiter (Eds.), Monte Carlo and Quasi-Monte Carlo Methods 2006, Springer; Berlin, Heidelberg, 2008, pp. 607-622. [2] M. Hoefling, N. Lima, D. Hänni, B. Schuler, C. A. M. Seidel, H. Grubmüller, Structural heterogeneity and quantitative FRET efficiency distributions of polyprolines through a hybrid atomistic simulation and Monte Carlo approach, PLoS ONE 6 (5) (2011) e19791. [3] D. V. D. Spoel, E. Lindahl, B. Hess, G. Groenhof, A. E. Mark, H. J. C. Berendsen, GROMACS: fast, flexible, and free., J Comput Chem 26 (16) (2005) 1701-1718. [4] R. Pool, A. Feenstra, M. Hoefling, R. Schulz, J. C. Smith, J. Heringa, Enabling grand-canonical Monte Carlo: Extending the flexibility of gromacs through the GromPy Python interface module, Journal of Chemical Theory and Computation 33 (12) (2012) 1207-1214.

Medical Surveillance Monthly Report (MSMR). Volume 23, Number 2, February 2016

DTIC Science & Technology

2016-05-06

the past 20 years.3 Th e expansion of the cur- rent epidemic that began in the early 2000s was primarily attributable to increased cases among men...disease screening. In the early 20th century, it was estimated that 5% of Army enlistees had evidence of some type of venereal disease.11 Wasserman...conjunction with early screening dur- ing World War II, led to near eradica- tion of syphilis among active duty Army soldiers.11 Screening for syphilis in

The Center for Advanced Food Technology: Food Related Studies.

DTIC Science & Technology

1992-11-16

Glucan (Callose) Synthase from Beta Vulgaris L. by Product-Entrapment," Entrapment Mechanisms and Polypeptide Characterization. Elant MU g. 97:684...Na3HGe7O16 xH20, xaO 0-6. 1," Chemiatr of Materials, 4:388. FRost, D.L, Drake, R.R., and B.P. Wasserman (1992) ’(1,3)-- glucan Synthase from Saccbaro...Wu, A., and R.W. Harriman (1992) "Probing the Molecular Architecture of (1,3-- Glucan (Callose) Synthase: Polypeptide Depletion Studies," Biochemical

Influence of Fiber Type Composition and Capillary Density on Onset of Blood Lactate Accumulation,

DTIC Science & Technology

1981-03-25

changes referred to as aerobic and anaerobic thresholds as suggested by e.g. Skinner and McLellan (32). To assess the "breaking point", which re- presents...in man. Acta Physiol Scand Suppl 443, 1976. 37 Wasserman K., Whipp B., Koyal S., Beaver t’. : Anaerobic threshold and respiratory gas exchange during...onset of a net accumulation of lactate in blood, has been proposed to represent a metabolic shift from aerobic to revalent anaerobic energy contribution

An Investigation of Expert Systems Usage for Software Requirements Development in the Strategic Defense Initiative Environment.

DTIC Science & Technology

1986-06-10

the solution of the base could be the solution of the target. If expert systems are to mimic humans , then they should inherently utilize analogy. In the...expert systems environment, the theory of frames for representing knowledge developed partly because humans usually solve problems by first seeing if...Goals," Computer, May 1975, p. 17. 8. A.I. Wasserman, "Some Principles of User Software Engineering for Information Systems ," Digest of Papers, COMPCON

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

PubMed

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

2010-01-01

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

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

PubMed Central

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

2010-01-01

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

Earth Experiments in a Virtual World: Introducing Climate & Coding to High School Girls

NASA Astrophysics Data System (ADS)

Singh, H. A.; Twedt, J. R.

2017-12-01

In our increasingly technologically-driven and information-saturated world, literacy in STEM fields can be crucial for career advancement. Nevertheless, both systemic and interpersonal barriers can prevent individuals, particularly members of under-represented groups, from engaging in these fields. Here, we present a high school-level workshop developed to foster basic understanding of climate science while exposing students to the Python programming language. For the past four years, the workshop has been a part of the annual Expanding Your Horizons conference for high school girls, whose mission is to spark interest in STEM fields. Moving through current events in the realm of global climate policy, the fundamentals of climate, and the mathematical representation of planetary energy balance, the workshop culminates in an under-the-hood exploration of a basic climate model coded in the Python programming language. Students interact directly with the underlying code to run `virtual world' experiments that explore the impact of solar insolation, planetary albedo, the greenhouse effect, and meridional energy transport on global temperatures. Engagement with Python is through the Jupyter Notebook interface, which permits direct interaction with the code but is more user-friendly for beginners than a command-line approach. We conclude with further ideas for providing online access to workshop materials for educators, and additional venues for presenting such workshops to under-represented groups in STEM.

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.

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.

Ultrasound imaging of the anterior section of the eye of five different snake species.

PubMed

Lauridsen, Henrik; Da Silva, Mari-Ann O; Hansen, Kasper; Jensen, Heidi M; Warming, Mads; Wang, Tobias; Pedersen, Michael

2014-12-30

Nineteen clinically normal snakes: six ball pythons (Python regius), six Burmese pythons (Python bivittatus), one Children's python (Antaresia childreni), four Amazon tree boas (Corallus hortulanus), and two Malagasy ground boas (Acrantophis madagascariensis) were subjected to ultrasound imaging with 21 MHz (ball python) and 50 MHz (ball python, Burmese python, Children's python, Amazon tree boa, Malagasy ground boa) transducers in order to measure the different structures of the anterior segment in clinically normal snake eyes with the aim to review baseline values for clinically important ophthalmic structures. The ultrasonographic measurements included horizontal spectacle diameter, spectacle thickness, depth of sub-spectacular space and corneal thickness. For comparative purposes, a formalin-fixed head of a Burmese python was subjected to micro computed tomography. In all snakes, the spectacle was thinner than the cornea. There was significant difference in spectacle diameter, and spectacle and corneal thickness between the Amazon tree boa and the Burmese and ball pythons. There was no difference in the depth of the sub-spectacular space. The results obtained in the Burmese python with the 50 MHz transducer were similar to the results obtained with micro computed tomography. Images acquired with the 21 MHz transducer included artifacts which may be misinterpreted as ocular structures. Our measurements of the structures in the anterior segment of the eye can serve as orientative values for snakes examined for ocular diseases. In addition, we demonstrated that using a high frequency transducer minimizes the risk of misinterpreting artifacts as ocular structures.

An Interactive and Comprehensive Working Environment for High-Energy Physics Software with Python and Jupyter Notebooks

NASA Astrophysics Data System (ADS)

Braun, N.; Hauth, T.; Pulvermacher, C.; Ritter, M.

2017-10-01

Today’s analyses for high-energy physics (HEP) experiments involve processing a large amount of data with highly specialized algorithms. The contemporary workflow from recorded data to final results is based on the execution of small scripts - often written in Python or ROOT macros which call complex compiled algorithms in the background - to perform fitting procedures and generate plots. During recent years interactive programming environments, such as Jupyter, became popular. Jupyter allows to develop Python-based applications, so-called notebooks, which bundle code, documentation and results, e.g. plots. Advantages over classical script-based approaches is the feature to recompute only parts of the analysis code, which allows for fast and iterative development, and a web-based user frontend, which can be hosted centrally and only requires a browser on the user side. In our novel approach, Python and Jupyter are tightly integrated into the Belle II Analysis Software Framework (basf2), currently being developed for the Belle II experiment in Japan. This allows to develop code in Jupyter notebooks for every aspect of the event simulation, reconstruction and analysis chain. These interactive notebooks can be hosted as a centralized web service via jupyterhub with docker and used by all scientists of the Belle II Collaboration. Because of its generality and encapsulation, the setup can easily be scaled to large installations.

CIF2Cell: Generating geometries for electronic structure programs

NASA Astrophysics Data System (ADS)

Björkman, Torbjörn

2011-05-01

The CIF2Cell program generates the geometrical setup for a number of electronic structure programs based on the crystallographic information in a Crystallographic Information Framework (CIF) file. The program will retrieve the space group number, Wyckoff positions and crystallographic parameters, make a sensible choice for Bravais lattice vectors (primitive or principal cell) and generate all atomic positions. Supercells can be generated and alloys are handled gracefully. The code currently has output interfaces to the electronic structure programs ABINIT, CASTEP, CPMD, Crystal, Elk, Exciting, EMTO, Fleur, RSPt, Siesta and VASP. Program summaryProgram title: CIF2Cell Catalogue identifier: AEIM_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEIM_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU GPL version 3 No. of lines in distributed program, including test data, etc.: 12 691 No. of bytes in distributed program, including test data, etc.: 74 933 Distribution format: tar.gz Programming language: Python (versions 2.4-2.7) Computer: Any computer that can run Python (versions 2.4-2.7) Operating system: Any operating system that can run Python (versions 2.4-2.7) Classification: 7.3, 7.8, 8 External routines: PyCIFRW [1] Nature of problem: Generate the geometrical setup of a crystallographic cell for a variety of electronic structure programs from data contained in a CIF file. Solution method: The CIF file is parsed using routines contained in the library PyCIFRW [1], and crystallographic as well as bibliographic information is extracted. The program then generates the principal cell from symmetry information, crystal parameters, space group number and Wyckoff sites. Reduction to a primitive cell is then performed, and the resulting cell is output to suitably named files along with documentation of the information source generated from any bibliographic information contained in the CIF file. If the space group symmetries is not present in the CIF file the program will fall back on internal tables, so only the minimal input of space group, crystal parameters and Wyckoff positions are required. Additional key features are handling of alloys and supercell generation. Additional comments: Currently implements support for the following general purpose electronic structure programs: ABINIT [2,3], CASTEP [4], CPMD [5], Crystal [6], Elk [7], exciting [8], EMTO [9], Fleur [10], RSPt [11], Siesta [12] and VASP [13-16]. Running time: The examples provided in the distribution take only seconds to run.

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.

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.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Wahanani, Nursinta Adi, E-mail: sintaadi@batan.go.id; Natsir, Khairina, E-mail: sintaadi@batan.go.id; Hartini, Entin, E-mail: sintaadi@batan.go.id

Data processing software packages such as VSOP and MCNPX are softwares that has been scientifically proven and complete. The result of VSOP and MCNPX are huge and complex text files. In the analyze process, user need additional processing like Microsoft Excel to show informative result. This research develop an user interface software for output of VSOP and MCNPX. VSOP program output is used to support neutronic analysis and MCNPX program output is used to support burn-up analysis. Software development using iterative development methods which allow for revision and addition of features according to user needs. Processing time with this softwaremore » 500 times faster than with conventional methods using Microsoft Excel. PYTHON is used as a programming language, because Python is available for all major operating systems: Windows, Linux/Unix, OS/2, Mac, Amiga, among others. Values that support neutronic analysis are k-eff, burn-up and mass Pu{sup 239} and Pu{sup 241}. Burn-up analysis used the mass inventory values of actinide (Thorium, Plutonium, Neptunium and Uranium). Values are visualized in graphical shape to support analysis.« less

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.

A geometric approach to identify cavities in particle systems

NASA Astrophysics Data System (ADS)

Voyiatzis, Evangelos; Böhm, Michael C.; Müller-Plathe, Florian

2015-11-01

The implementation of a geometric algorithm to identify cavities in particle systems in an open-source python program is presented. The algorithm makes use of the Delaunay space tessellation. The present python software is based on platform-independent tools, leading to a portable program. Its successful execution provides information concerning the accessible volume fraction of the system, the size and shape of the cavities and the group of atoms forming each of them. The program can be easily incorporated into the LAMMPS software. An advantage of the present algorithm is that no a priori assumption on the cavity shape has to be made. As an example, the cavity size and shape distributions in a polyethylene melt system are presented for three spherical probe particles. This paper serves also as an introductory manual to the script. It summarizes the algorithm, its implementation, the required user-defined parameters as well as the format of the input and output files. Additionally, we demonstrate possible applications of our approach and compare its capability with the ones of well documented cavity size estimators.

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.

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.

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.

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.

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.

PyChimera: use UCSF Chimera modules in any Python 2.7 project.

PubMed

Rodríguez-Guerra Pedregal, Jaime; Maréchal, Jean-Didier

2018-05-15

UCSF Chimera is a powerful visualization tool remarkably present in the computational chemistry and structural biology communities. Built on a C++ core wrapped under a Python 2.7 environment, one could expect to easily import UCSF Chimera's arsenal of resources in custom scripts or software projects. Nonetheless, this is not readily possible if the script is not executed within UCSF Chimera due to the isolation of the platform. UCSF ChimeraX, successor to the original Chimera, partially solves the problem but yet major upgrades need to be undergone so that this updated version can offer all UCSF Chimera features. PyChimera has been developed to overcome these limitations and provide access to the UCSF Chimera codebase from any Python 2.7 interpreter, including interactive programming with tools like IPython and Jupyter Notebooks, making it easier to use with additional third-party software. PyChimera is LGPL-licensed and available at https://github.com/insilichem/pychimera. jaime.rodriguezguerra@uab.cat or jeandidier.marechal@uab.cat. Supplementary data are available at Bioinformatics online.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Singleton, Jr., Robert; Israel, Daniel M.; Doebling, Scott William

For code verification, one compares the code output against known exact solutions. There are many standard test problems used in this capacity, such as the Noh and Sedov problems. ExactPack is a utility that integrates many of these exact solution codes into a common API (application program interface), and can be used as a stand-alone code or as a python package. ExactPack consists of python driver scripts that access a library of exact solutions written in Fortran or Python. The spatial profiles of the relevant physical quantities, such as the density, fluid velocity, sound speed, or internal energy, are returnedmore » at a time specified by the user. The solution profiles can be viewed and examined by a command line interface or a graphical user interface, and a number of analysis tools and unit tests are also provided. We have documented the physics of each problem in the solution library, and provided complete documentation on how to extend the library to include additional exact solutions. ExactPack’s code architecture makes it easy to extend the solution-code library to include additional exact solutions in a robust, reliable, and maintainable manner.« less

User interfaces for computational science: A domain specific language for OOMMF embedded in Python

NASA Astrophysics Data System (ADS)

Beg, Marijan; Pepper, Ryan A.; Fangohr, Hans

2017-05-01

Computer simulations are used widely across the engineering and science disciplines, including in the research and development of magnetic devices using computational micromagnetics. In this work, we identify and review different approaches to configuring simulation runs: (i) the re-compilation of source code, (ii) the use of configuration files, (iii) the graphical user interface, and (iv) embedding the simulation specification in an existing programming language to express the computational problem. We identify the advantages and disadvantages of different approaches and discuss their implications on effectiveness and reproducibility of computational studies and results. Following on from this, we design and describe a domain specific language for micromagnetics that is embedded in the Python language, and allows users to define the micromagnetic simulations they want to carry out in a flexible way. We have implemented this micromagnetic simulation description language together with a computational backend that executes the simulation task using the Object Oriented MicroMagnetic Framework (OOMMF). We illustrate the use of this Python interface for OOMMF by solving the micromagnetic standard problem 4. All the code is publicly available and is open source.

DOE Office of Scientific and Technical Information (OSTI.GOV)

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

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.

ALGORITHMS AND PROGRAMS FOR STRONG GRAVITATIONAL LENSING IN KERR SPACE-TIME INCLUDING POLARIZATION

DOE Office of Scientific and Technical Information (OSTI.GOV)

Chen, Bin; Maddumage, Prasad; Kantowski, Ronald

2015-05-15

Active galactic nuclei (AGNs) and quasars are important astrophysical objects to understand. Recently, microlensing observations have constrained the size of the quasar X-ray emission region to be of the order of 10 gravitational radii of the central supermassive black hole. For distances within a few gravitational radii, light paths are strongly bent by the strong gravity field of the central black hole. If the central black hole has nonzero angular momentum (spin), then a photon’s polarization plane will be rotated by the gravitational Faraday effect. The observed X-ray flux and polarization will then be influenced significantly by the strong gravitymore » field near the source. Consequently, linear gravitational lensing theory is inadequate for such extreme circumstances. We present simple algorithms computing the strong lensing effects of Kerr black holes, including the effects on polarization. Our algorithms are realized in a program “KERTAP” in two versions: MATLAB and Python. The key ingredients of KERTAP are a graphic user interface, a backward ray-tracing algorithm, a polarization propagator dealing with gravitational Faraday rotation, and algorithms computing observables such as flux magnification and polarization angles. Our algorithms can be easily realized in other programming languages such as FORTRAN, C, and C++. The MATLAB version of KERTAP is parallelized using the MATLAB Parallel Computing Toolbox and the Distributed Computing Server. The Python code was sped up using Cython and supports full implementation of MPI using the “mpi4py” package. As an example, we investigate the inclination angle dependence of the observed polarization and the strong lensing magnification of AGN X-ray emission. We conclude that it is possible to perform complex numerical-relativity related computations using interpreted languages such as MATLAB and Python.« less

Algorithms and Programs for Strong Gravitational Lensing In Kerr Space-time Including Polarization

NASA Astrophysics Data System (ADS)

Chen, Bin; Kantowski, Ronald; Dai, Xinyu; Baron, Eddie; Maddumage, Prasad

2015-05-01

Active galactic nuclei (AGNs) and quasars are important astrophysical objects to understand. Recently, microlensing observations have constrained the size of the quasar X-ray emission region to be of the order of 10 gravitational radii of the central supermassive black hole. For distances within a few gravitational radii, light paths are strongly bent by the strong gravity field of the central black hole. If the central black hole has nonzero angular momentum (spin), then a photon’s polarization plane will be rotated by the gravitational Faraday effect. The observed X-ray flux and polarization will then be influenced significantly by the strong gravity field near the source. Consequently, linear gravitational lensing theory is inadequate for such extreme circumstances. We present simple algorithms computing the strong lensing effects of Kerr black holes, including the effects on polarization. Our algorithms are realized in a program “KERTAP” in two versions: MATLAB and Python. The key ingredients of KERTAP are a graphic user interface, a backward ray-tracing algorithm, a polarization propagator dealing with gravitational Faraday rotation, and algorithms computing observables such as flux magnification and polarization angles. Our algorithms can be easily realized in other programming languages such as FORTRAN, C, and C++. The MATLAB version of KERTAP is parallelized using the MATLAB Parallel Computing Toolbox and the Distributed Computing Server. The Python code was sped up using Cython and supports full implementation of MPI using the “mpi4py” package. As an example, we investigate the inclination angle dependence of the observed polarization and the strong lensing magnification of AGN X-ray emission. We conclude that it is possible to perform complex numerical-relativity related computations using interpreted languages such as MATLAB and Python.

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

Stonix, Version 0.x

DOE Office of Scientific and Technical Information (OSTI.GOV)

2015-05-13

STONIX is a program for configuring UNIX and Linux computer operating systems. It applies configurations based on the guidance from publicly accessible resources such as: NSA Guides, DISA STIGs, the Center for Internet Security (CIS), USGCB and vendor security documentation. STONIX is written in the Python programming language using the QT4 and PyQT4 libraries to provide a GUI. The code is designed to be easily extensible and customizable.

Evaluating GPS biologging technology for studying spatial ecology of large constricting snakes

USGS Publications Warehouse

Smith, Brian; Hart, Kristen M.; Mazzotti, Frank J.; Basille, Mathieu; Romagosa, Christina M.

2018-01-01

Background: GPS telemetry has revolutionized the study of animal spatial ecology in the last two decades. Until recently, it has mainly been deployed on large mammals and birds, but the technology is rapidly becoming miniaturized, and applications in diverse taxa are becoming possible. Large constricting snakes are top predators in their ecosystems, and accordingly they are often a management priority, whether their populations are threatened or invasive. Fine-scale GPS tracking datasets could greatly improve our ability to understand and manage these snakes, but the ability of this new technology to deliver high-quality data in this system is unproven. In order to evaluate GPS technology in large constrictors, we GPS-tagged 13 Burmese pythons (Python bivittatus) in Everglades National Park and deployed an additional 7 GPS tags on stationary platforms to evaluate habitat-driven biases in GPS locations. Both python and test platform GPS tags were programmed to attempt a GPS fix every 90 min.Results: While overall fix rates for the tagged pythons were low (18.1%), we were still able to obtain an average of 14.5 locations/animal/week, a large improvement over once-weekly VHF tracking. We found overall accuracy and precision to be very good (mean accuracy = 7.3 m, mean precision = 12.9 m), but a very few imprecise locations were still recorded (0.2% of locations with precision > 1.0 km). We found that dense vegetation did decrease fix rate, but we concluded that the low observed fix rate was also due to python microhabitat selection underground or underwater. Half of our recovered pythons were either missing their tag or the tag had malfunctioned, resulting in no data being recovered.Conclusions: GPS biologging technology is a promising tool for obtaining frequent, accurate, and precise locations of large constricting snakes. We recommend future studies couple GPS telemetry with frequent VHF locations in order to reduce bias and limit the impact of catastrophic failures on data collection, and we recommend improvements to GPS tag design to lessen the frequency of these failures.

The Julia programming language: the future of scientific computing

NASA Astrophysics Data System (ADS)

Gibson, John

2017-11-01

Julia is an innovative new open-source programming language for high-level, high-performance numerical computing. Julia combines the general-purpose breadth and extensibility of Python, the ease-of-use and numeric focus of Matlab, the speed of C and Fortran, and the metaprogramming power of Lisp. Julia uses type inference and just-in-time compilation to compile high-level user code to machine code on the fly. A rich set of numeric types and extensive numerical libraries are built-in. As a result, Julia is competitive with Matlab for interactive graphical exploration and with C and Fortran for high-performance computing. This talk interactively demonstrates Julia's numerical features and benchmarks Julia against C, C++, Fortran, Matlab, and Python on a spectral time-stepping algorithm for a 1d nonlinear partial differential equation. The Julia code is nearly as compact as Matlab and nearly as fast as Fortran. This material is based upon work supported by the National Science Foundation under Grant No. 1554149.

PyORBIT: A Python Shell For ORBIT

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jean-Francois Ostiguy; Jeffrey Holmes

2003-07-01

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

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.

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.

ObspyDMT: a Python toolbox for retrieving and processing large seismological data sets

NASA Astrophysics Data System (ADS)

Hosseini, Kasra; Sigloch, Karin

2017-10-01

We present obspyDMT, a free, open-source software toolbox for the query, retrieval, processing and management of seismological data sets, including very large, heterogeneous and/or dynamically growing ones. ObspyDMT simplifies and speeds up user interaction with data centers, in more versatile ways than existing tools. The user is shielded from the complexities of interacting with different data centers and data exchange protocols and is provided with powerful diagnostic and plotting tools to check the retrieved data and metadata. While primarily a productivity tool for research seismologists and observatories, easy-to-use syntax and plotting functionality also make obspyDMT an effective teaching aid. Written in the Python programming language, it can be used as a stand-alone command-line tool (requiring no knowledge of Python) or can be integrated as a module with other Python codes. It facilitates data archiving, preprocessing, instrument correction and quality control - routine but nontrivial tasks that can consume much user time. We describe obspyDMT's functionality, design and technical implementation, accompanied by an overview of its use cases. As an example of a typical problem encountered in seismogram preprocessing, we show how to check for inconsistencies in response files of two example stations. We also demonstrate the fully automated request, remote computation and retrieval of synthetic seismograms from the Synthetics Engine (Syngine) web service of the Data Management Center (DMC) at the Incorporated Research Institutions for Seismology (IRIS).

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

Bulletin of the American Astronomical Society. Volume 36, Number 1, 2004

DTIC Science & Technology

2004-01-01

A. S., Van Malderen, R., Uytterhoeven, K., Davignon, G., Dunham, E. W., Olkin , C. B., Taylor, B. W., Wasserman, L. H., Clancy, K., Person, M. J...Leggett, S. K., Levine, S. E., Moon, D.-S., Olkin , C. B., Osip, D. J., Pasachoff, J. M., Penprase, B. E., Person, M. J., Qu, S., Rayner, J. T., Rob...Moon, D.-S., Buie, M. W., Dunham, E. W., Olkin , C. B., Taylor, B., Kern, S. D., Qu, S., Salyk, C. V., Leggett, S. K., Levine, S. E., and Stone, R. C

DOE Office of Scientific and Technical Information (OSTI.GOV)

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

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.

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.

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/.

Tidal analysis and Arrival Process Mining Using Automatic Identification System (AIS) Data

DTIC Science & Technology

2017-01-01

files, organized by location. The data were processed using the Python programming language (van Rossum and Drake 2001), the Pandas data analysis...ER D C/ CH L TR -1 7- 2 Coastal Inlets Research Program Tidal Analysis and Arrival Process Mining Using Automatic Identification System...17-2 January 2017 Tidal Analysis and Arrival Process Mining Using Automatic Identification System (AIS) Data Brandan M. Scully Coastal and

ORBKIT: A modular python toolbox for cross-platform postprocessing of quantum chemical wavefunction data.

PubMed

Hermann, Gunter; Pohl, Vincent; Tremblay, Jean Christophe; Paulus, Beate; Hege, Hans-Christian; Schild, Axel

2016-06-15

ORBKIT is a toolbox for postprocessing electronic structure calculations based on a highly modular and portable Python architecture. The program allows computing a multitude of electronic properties of molecular systems on arbitrary spatial grids from the basis set representation of its electronic wavefunction, as well as several grid-independent properties. The required data can be extracted directly from the standard output of a large number of quantum chemistry programs. ORBKIT can be used as a standalone program to determine standard quantities, for example, the electron density, molecular orbitals, and derivatives thereof. The cornerstone of ORBKIT is its modular structure. The existing basic functions can be arranged in an individual way and can be easily extended by user-written modules to determine any other derived quantity. ORBKIT offers multiple output formats that can be processed by common visualization tools (VMD, Molden, etc.). Additionally, ORBKIT possesses routines to order molecular orbitals computed at different nuclear configurations according to their electronic character and to interpolate the wavefunction between these configurations. The program is open-source under GNU-LGPLv3 license and freely available at https://github.com/orbkit/orbkit/. This article provides an overview of ORBKIT with particular focus on its capabilities and applicability, and includes several example calculations. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

A comparative study of programming languages for next-generation astrodynamics systems

NASA Astrophysics Data System (ADS)

Eichhorn, Helge; Cano, Juan Luis; McLean, Frazer; Anderl, Reiner

2018-03-01

Due to the computationally intensive nature of astrodynamics tasks, astrodynamicists have relied on compiled programming languages such as Fortran for the development of astrodynamics software. Interpreted languages such as Python, on the other hand, offer higher flexibility and development speed thereby increasing the productivity of the programmer. While interpreted languages are generally slower than compiled languages, recent developments such as just-in-time (JIT) compilers or transpilers have been able to close this speed gap significantly. Another important factor for the usefulness of a programming language is its wider ecosystem which consists of the available open-source packages and development tools such as integrated development environments or debuggers. This study compares three compiled languages and three interpreted languages, which were selected based on their popularity within the scientific programming community and technical merit. The three compiled candidate languages are Fortran, C++, and Java. Python, Matlab, and Julia were selected as the interpreted candidate languages. All six languages are assessed and compared to each other based on their features, performance, and ease-of-use through the implementation of idiomatic solutions to classical astrodynamics problems. We show that compiled languages still provide the best performance for astrodynamics applications, but JIT-compiled dynamic languages have reached a competitive level of speed and offer an attractive compromise between numerical performance and programmer productivity.

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

NASA Astrophysics Data System (ADS)

Sandner, Raimar; Vukics, András

2014-09-01

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

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-Observed Characteristics of Precipitating Systems during NAME 2004. J. Climate, 20, 1713-1733. doi: http://dx.doi.org/10.1175/JCLI4082.1[3] Scott E. Giangrande, Robert McGraw, and Lei Lei, 2013: An Application of Linear Programming to Polarimetric Radar Differential Phase Processing. JTECH. 30, 1716-1729, doi: 10.1175/JTECH-D-12-00147.1.

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.

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.

Leveraging Python Interoperability Tools to Improve Sapphire's Usability

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gezahegne, A; Love, N S

2007-12-10

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

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.

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.

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.

Simulating the Physical World

NASA Astrophysics Data System (ADS)

Berendsen, Herman J. C.

2004-06-01

The simulation of physical systems requires a simplified, hierarchical approach which models each level from the atomistic to the macroscopic scale. From quantum mechanics to fluid dynamics, this book systematically treats the broad scope of computer modeling and simulations, describing the fundamental theory behind each level of approximation. Berendsen evaluates each stage in relation to its applications giving the reader insight into the possibilities and limitations of the models. Practical guidance for applications and sample programs in Python are provided. With a strong emphasis on molecular models in chemistry and biochemistry, this book will be suitable for advanced undergraduate and graduate courses on molecular modeling and simulation within physics, biophysics, physical chemistry and materials science. It will also be a useful reference to all those working in the field. Additional resources for this title including solutions for instructors and programs are available online at www.cambridge.org/9780521835275. The first book to cover the wide range of modeling and simulations, from atomistic to the macroscopic scale, in a systematic fashion Providing a wealth of background material, it does not assume advanced knowledge and is eminently suitable for course use Contains practical examples and sample programs in Python

A hybrid numerical fluid dynamics code for resistive magnetohydrodynamics

DOE Office of Scientific and Technical Information (OSTI.GOV)

Johnson, Jeffrey

2006-04-01

Spasmos is a computational fluid dynamics code that uses two numerical methods to solve the equations of resistive magnetohydrodynamic (MHD) flows in compressible, inviscid, conducting media[1]. The code is implemented as a set of libraries for the Python programming language[2]. It represents conducting and non-conducting gases and materials with uncomplicated (analytic) equations of state. It supports calculations in 1D, 2D, and 3D geometry, though only the 1D configuation has received significant testing to date. Because it uses the Python interpreter as a front end, users can easily write test programs to model systems with a variety of different numerical andmore » physical parameters. Currently, the code includes 1D test programs for hydrodynamics (linear acoustic waves, the Sod weak shock[3], the Noh strong shock[4], the Sedov explosion[5], magnetic diffusion (decay of a magnetic pulse[6], a driven oscillatory "wine-cellar" problem[7], magnetic equilibrium), and magnetohydrodynamics (an advected magnetic pulse[8], linear MHD waves, a magnetized shock tube[9]). Spasmos current runs only in a serial configuration. In the future, it will use MPI for parallel computation.« less

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

PubMed

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

2011-09-01

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

Python as a federation tool for GENESIS 3.0.

PubMed

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

2012-01-01

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

Python as a Federation Tool for GENESIS 3.0

PubMed Central

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

2012-01-01

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

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, statistical models) and analysis tools. The tools developed for this package can be adapted to create similar environments for hydrologic models.

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

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.

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

DOE Office of Scientific and Technical Information (OSTI.GOV)

Barnette, Daniel W.

2012-01-04

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

PyFLOWGO: An open-source platform for simulation of channelized lava thermo-rheological properties

NASA Astrophysics Data System (ADS)

Chevrel, Magdalena Oryaëlle; Labroquère, Jérémie; Harris, Andrew J. L.; Rowland, Scott K.

2018-02-01

Lava flow advance can be modeled through tracking the evolution of the thermo-rheological properties of a control volume of lava as it cools and crystallizes. An example of such a model was conceived by Harris and Rowland (2001) who developed a 1-D model, FLOWGO, in which the velocity of a control volume flowing down a channel depends on rheological properties computed following the thermal path estimated via a heat balance box model. We provide here an updated version of FLOWGO written in Python that is an open-source, modern and flexible language. Our software, named PyFLOWGO, allows selection of heat fluxes and rheological models of the user's choice to simulate the thermo-rheological evolution of the lava control volume. We describe its architecture which offers more flexibility while reducing the risk of making error when changing models in comparison to the previous FLOWGO version. Three cases are tested using actual data from channel-fed lava flow systems and results are discussed in terms of model validation and convergence. PyFLOWGO is open-source and packaged in a Python library to be imported and reused in any Python program (https://github.com/pyflowgo/pyflowgo)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hagberg, Aric; Swart, Pieter; S Chult, Daniel

NetworkX is a Python language package for exploration and analysis of networks and network algorithms. The core package provides data structures for representing many types of networks, or graphs, including simple graphs, directed graphs, and graphs with parallel edges and self loops. The nodes in NetworkX graphs can be any (hashable) Python object and edges can contain arbitrary data; this flexibility mades NetworkX ideal for representing networks found in many different scientific fields. In addition to the basic data structures many graph algorithms are implemented for calculating network properties and structure measures: shortest paths, betweenness centrality, clustering, and degree distributionmore » and many more. NetworkX can read and write various graph formats for eash exchange with existing data, and provides generators for many classic graphs and popular graph models, such as the Erdoes-Renyi, Small World, and Barabasi-Albert models, are included. The ease-of-use and flexibility of the Python programming language together with connection to the SciPy tools make NetworkX a powerful tool for scientific computations. We discuss some of our recent work studying synchronization of coupled oscillators to demonstrate how NetworkX enables research in the field of computational networks.« less

Conceptual thresholds for same and different in old-(Macaca mulatta) and new-world (Cebus apella) monkeys

PubMed Central

Flemming, Timothy M.

2011-01-01

Learning of the relational same/different (S/D) concept has been demonstrated to be largely dependent upon stimulus sets containing more than two items for pigeons and old-world monkeys. Stimulus arrays containing several images for use in same/different discrimination procures (e.g. 16 identical images vs. 16 nonidentical images) have been shown to facilitate and even be necessary for learning of relational concepts (Flemming, Beran & Washburn, 2007; Wasserman, Young & Fagot, 2001; Young, Wasserman & Garner, 1997). In the present study, we investigate the threshold at which a new world primate, the capuchin (Cebus apella) may be able to make such a discrimination. Utilizing a method of increasing entropy, rather than conventional procedures of decreasing entropy, we demonstrate unique evidence that capuchin monkeys are readily capable of making 2-item relational S/D conditional discriminations. In another experiment, we examine the supposed level of difficulty in making S/D discriminations by rhesus monkeys (Macaca mulatta). Whereas pigeons (Columba livia) and baboons (Papio papio) have shown marked difficulty simultaneously discriminating same from different arrays at all when composed of fewer than 8 items each, rhesus monkeys seem to understand that pairs of stimuli connote sameness and difference just the same (Flemming et al., 2007). With sustained accurate performance of 2-item S/D discriminations, both experienced and task-naïve rhesus monkeys appear quite certain in their conceptual knowledge of same and different. We conclude that learning of the same/different relational concept may be less dependent upon high levels of entropy contrast than originally hypothesized for nonhuman primates. PMID:21238555

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.

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.

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.

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

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.

MONTE: the next generation of mission design and navigation software

NASA Astrophysics Data System (ADS)

Evans, Scott; Taber, William; Drain, Theodore; Smith, Jonathon; Wu, Hsi-Cheng; Guevara, Michelle; Sunseri, Richard; Evans, James

2018-03-01

The Mission analysis, Operations and Navigation Toolkit Environment (MONTE) (Sunseri et al. in NASA Tech Briefs 36(9), 2012) is an astrodynamic toolkit produced by the Mission Design and Navigation Software Group at the Jet Propulsion Laboratory. It provides a single integrated environment for all phases of deep space and Earth orbiting missions. Capabilities include: trajectory optimization and analysis, operational orbit determination, flight path control, and 2D/3D visualization. MONTE is presented to the user as an importable Python language module. This allows a simple but powerful user interface via CLUI or script. In addition, the Python interface allows MONTE to be used seamlessly with other canonical scientific programming tools such as SciPy, NumPy, and Matplotlib. MONTE is the prime operational orbit determination software for all JPL navigated missions.

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.

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.

A novel Python program for implementation of quality control in the ELISA.

PubMed

Wetzel, Hanna N; Cohen, Cinder; Norman, Andrew B; Webster, Rose P

2017-09-01

The use of semi-quantitative assays such as the enzyme-linked immunosorbent assay (ELISA) requires stringent quality control of the data. However, such quality control is often lacking in academic settings due to unavailability of software and knowledge. Therefore, our aim was to develop methods to easily implement Levey-Jennings quality control methods. For this purpose, we created a program written in Python (a programming language with an open-source license) and tested it using a training set of ELISA standard curves quantifying the Fab fragment of an anti-cocaine monoclonal antibody in mouse blood. A colorimetric ELISA was developed using a goat anti-human anti-Fab capture method. Mouse blood samples spiked with the Fab fragment were tested against a standard curve of known concentrations of Fab fragment in buffer over a period of 133days stored at 4°C to assess stability of the Fab fragment and to generate a test dataset to assess the program. All standard curves were analyzed using our program to batch process the data and to generate Levey-Jennings control charts and statistics regarding the datasets. The program was able to identify values outside of two standard deviations, and this identification of outliers was consistent with the results of a two-way ANOVA. This program is freely available, which will help laboratories implement quality control methods, thus improving reproducibility within and between labs. We report here successful testing of the program with our training set and development of a method for quantification of the Fab fragment in mouse blood. Copyright © 2017 Elsevier B.V. All rights reserved.

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).

New implementation of OGC Web Processing Service in Python programming language. PyWPS-4 and issues we are facing with processing of large raster data using OGC WPS

NASA Astrophysics Data System (ADS)

Čepický, Jáchym; Moreira de Sousa, Luís

2016-06-01

The OGC® Web Processing Service (WPS) Interface Standard provides rules for standardizing inputs and outputs (requests and responses) for geospatial processing services, such as polygon overlay. The standard also defines how a client can request the execution of a process, and how the output from the process is handled. It defines an interface that facilitates publishing of geospatial processes and client discovery of processes and and binding to those processes into workflows. Data required by a WPS can be delivered across a network or they can be available at a server. PyWPS was one of the first implementations of OGC WPS on the server side. It is written in the Python programming language and it tries to connect to all existing tools for geospatial data analysis, available on the Python platform. During the last two years, the PyWPS development team has written a new version (called PyWPS-4) completely from scratch. The analysis of large raster datasets poses several technical issues in implementing the WPS standard. The data format has to be defined and validated on the server side and binary data have to be encoded using some numeric representation. Pulling raster data from remote servers introduces security risks, in addition, running several processes in parallel has to be possible, so that system resources are used efficiently while preserving security. Here we discuss these topics and illustrate some of the solutions adopted within the PyWPS implementation.

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.

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.

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

ERDC MSRC Resource. High Performance Computing for the Warfighter. Fall 2006

DTIC Science & Technology

2006-01-01

to as Aggregated Combat Modeling, putting us at the campaign level).” Incorporating UIT within DAC The DAC system is written in Python and uses...API calls with two Python classes, UITConnectionFactory and UITConnection. UITConnectionFactory supports Kerberos authentication and establishes a...API calls within these Python classes, we insulated the DAC code from the Python SOAP interface requirements and details of the ERDC MSRC Resource

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.

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.

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

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.

Pizza.py Toolkit

DOE Office of Scientific and Technical Information (OSTI.GOV)

Plimpton, Steve; Jones, Matt; Crozier, Paul

2006-01-01

Pizza.py is a loosely integrated collection of tools, many of which provide support for the LAMMPS molecular dynamics and ChemCell cell modeling packages. There are tools to create input files. convert between file formats, process log and dump files, create plots, and visualize and animate simulation snapshots. Software packages that are wrapped by Pizza.py. so they can invoked from within Python, include GnuPlot, MatLab, Raster3d. and RasMol. Pizza.py is written in Python and runs on any platform that supports Python. Pizza.py enhances the standard Python interpreter in a few simple ways. Its tools are Python modules which can be invokedmore » interactively, from scripts, or from GUIs when appropriate. Some of the tools require additional Python packages to be installed as part of the users Python. Others are wrappers on software packages (as listed above) which must be available on the users system. It is easy to modify or extend Pizza.py with new functionality or new tools, which need not have anything to do with LAMMPS or ChemCell.« less

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hart, William Eugene

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

The Affective Experience of Novice Computer Programmers

ERIC Educational Resources Information Center

Bosch, Nigel; D'Mello, Sidney

2017-01-01

Novice students (N = 99) participated in a lab study in which they learned the fundamentals of computer programming in Python using a self-paced computerized learning environment involving a 25-min scaffolded learning phase and a 10-min unscaffolded fadeout phase. Students provided affect judgments at approximately 100 points (every 15 s) over the…

ISMRM Raw Data Format: A Proposed Standard for MRI Raw Datasets

PubMed Central

Inati, Souheil J.; Naegele, Joseph D.; Zwart, Nicholas R.; Roopchansingh, Vinai; Lizak, Martin J.; Hansen, David C.; Liu, Chia-Ying; Atkinson, David; Kellman, Peter; Kozerke, Sebastian; Xue, Hui; Campbell-Washburn, Adrienne E.; Sørensen, Thomas S.; Hansen, Michael S.

2015-01-01

Purpose This work proposes the ISMRM Raw Data (ISMRMRD) format as a common MR raw data format, which promotes algorithm and data sharing. Methods A file format consisting of a flexible header and tagged frames of k-space data was designed. Application Programming Interfaces were implemented in C/C++, MATLAB, and Python. Converters for Bruker, General Electric, Philips, and Siemens proprietary file formats were implemented in C++. Raw data were collected using MRI scanners from four vendors, converted to ISMRMRD format, and reconstructed using software implemented in three programming languages (C++, MATLAB, Python). Results Images were obtained by reconstructing the raw data from all vendors. The source code, raw data, and images comprising this work are shared online, serving as an example of an image reconstruction project following a paradigm of reproducible research. Conclusion The proposed raw data format solves a practical problem for the MRI community. It may serve as a foundation for reproducible research and collaborations. The ISMRMRD format is a completely open and community-driven format, and the scientific community is invited (including commercial vendors) to participate either as users or developers. PMID:26822475

Services for domain specific developments in the Cloud

NASA Astrophysics Data System (ADS)

Schwichtenberg, Horst; Gemuend, André

2015-04-01

We will discuss and demonstrate the possibilities of new Cloud Services where the complete development of code is in the Cloud. We will discuss the possibilities of such services where the complete development cycle from programing to testing is in the cloud. This can be also combined with dedicated research domain specific services and hide the burden of accessing available infrastructures. As an example, we will show a service that is intended to complement the services of the VERCE projects infrastructure, a service that utilizes Cloud resources to offer simplified execution of data pre- and post-processing scripts. It offers users access to the ObsPy seismological toolbox for processing data with the Python programming language, executed on virtual Cloud resources in a secured sandbox. The solution encompasses a frontend with a modern graphical user interface, a messaging infrastructure as well as Python worker nodes for background processing. All components are deployable in the Cloud and have been tested on different environments based on OpenStack and OpenNebula. Deployments on commercial, public Clouds will be tested in the future.

Object-oriented numerics with FOSS: comparing PyPy &amp; NumPy, GCC/Clang &amp; Bitz++ and Gfortran

NASA Astrophysics Data System (ADS)

Jarecka, Dorota; Arabas, Sylwester; Fijalkowski, Maciej; Jaruga, Anna; Del Vento, Davide

2013-04-01

Employment of object-oriented programming (OOP) techniques may help to improve code readability, and hence its auditability and maintainability - both being arguably crucial for scientific software. OOP offers, in particular, the possibility to reproduce in the program code the mathematical "blackboard abstractions" used in the literature. There exist a number of free and open-source tools allowing to obtain this goal without sacrificing performance. An OOP implementation of the MPDATA advection algorithm used as a core of weather, ocean and climate modelling systems will serve as an example for briefly highlighting some relevant recent FOSS developments including: - NumPy support in the PyPy just-in-time compiler of Python. - the Blitz++ library coupled with the C++11 support in GCC and Clang; - support for OOP constructs from Fortran 2003/2008 in GFortran; A brief overview of other performance-related packages for Python like Numba and Cython will be also given. This poster will describe and extends key findings presented in http://arxiv.org/abs/1301.1334

Simulating Responses of Gravitational-Wave Instrumentation

NASA Technical Reports Server (NTRS)

Armstrong, John; Edlund, Jeffrey; Vallisneri. Michele

2006-01-01

Synthetic LISA is a computer program for simulating the responses of the instrumentation of the NASA/ESA Laser Interferometer Space Antenna (LISA) mission, the purpose of which is to detect and study gravitational waves. Synthetic LISA generates synthetic time series of the LISA fundamental noises, as filtered through all the time-delay-interferometry (TDI) observables. (TDI is a method of canceling phase noise in temporally varying unequal-arm interferometers.) Synthetic LISA provides a streamlined module to compute the TDI responses to gravitational waves, according to a full model of TDI (including the motion of the LISA array and the temporal and directional dependence of the arm lengths). Synthetic LISA is written in the C++ programming language as a modular package that accommodates the addition of code for specific gravitational wave sources or for new noise models. In addition, time series for waves and noises can be easily loaded from disk storage or electronic memory. The package includes a Python-language interface for easy, interactive steering and scripting. Through Python, Synthetic LISA can read and write data files in Flexible Image Transport System (FITS), which is a commonly used astronomical data format.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Hart, David; Klise, Katherine A.

The PyEPANET package is a set of commands for the Python programming language that are built to wrap the EPANET toolkit library commands, without requiring the end user to program using the ctypes package. This package does not contain the EPANET code, nor does it implement the functions within the EPANET software, and it requires the separately downloaded or compiled EPANET2 toolkit dynamic library (epanet.dll, libepanent.so, or epanet.dylib) and/or the EPANET-MSX dynamic library in order to function.

Test-driven programming

NASA Astrophysics Data System (ADS)

Georgiev, Bozhidar; Georgieva, Adriana

2013-12-01

In this paper, are presented some possibilities concerning the implementation of a test-driven development as a programming method. Here is offered a different point of view for creation of advanced programming techniques (build tests before programming source with all necessary software tools and modules respectively). Therefore, this nontraditional approach for easier programmer's work through building tests at first is preferable way of software development. This approach allows comparatively simple programming (applied with different object-oriented programming languages as for example JAVA, XML, PYTHON etc.). It is predictable way to develop software tools and to provide help about creating better software that is also easier to maintain. Test-driven programming is able to replace more complicated casual paradigms, used by many programmers.

GLINT: a user-friendly toolset for the analysis of high-throughput DNA-methylation array data.

PubMed

Rahmani, Elior; Yedidim, Reut; Shenhav, Liat; Schweiger, Regev; Weissbrod, Omer; Zaitlen, Noah; Halperin, Eran

2017-06-15

GLINT is a user-friendly command-line toolset for fast analysis of genome-wide DNA methylation data generated using the Illumina human methylation arrays. GLINT, which does not require any programming proficiency, allows an easy execution of Epigenome-Wide Association Study analysis pipeline under different models while accounting for known confounders in methylation data. GLINT is a command-line software, freely available at https://github.com/cozygene/glint/releases . It requires Python 2.7 and several freely available Python packages. Further information and documentation as well as a quick start tutorial are available at http://glint-epigenetics.readthedocs.io . elior.rahmani@gmail.com or ehalperin@cs.ucla.edu. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

Soapy: an adaptive optics simulation written purely in Python for rapid concept development

NASA Astrophysics Data System (ADS)

Reeves, Andrew

2016-07-01

Soapy is a newly developed Adaptive Optics (AO) simulation which aims be a flexible and fast to use tool-kit for many applications in the field of AO. It is written purely in the Python language, adding to and taking advantage of the already rich ecosystem of scientific libraries and programs. The simulation has been designed to be extremely modular, such that each component can be used stand-alone for projects which do not require a full end-to-end simulation. Ease of use, modularity and code clarity have been prioritised at the expense of computational performance. Though this means the code is not yet suitable for large studies of Extremely Large Telescope AO systems, it is well suited to education, exploration of new AO concepts and investigations of current generation telescopes.

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

Gsolve, a Python computer program with a graphical user interface to transform relative gravity survey measurements to absolute gravity values and gravity anomalies

NASA Astrophysics Data System (ADS)

McCubbine, Jack; Tontini, Fabio Caratori; Stagpoole, Vaughan; Smith, Euan; O'Brien, Grant

2018-01-01

A Python program (Gsolve) with a graphical user interface has been developed to assist with routine data processing of relative gravity measurements. Gsolve calculates the gravity at each measurement site of a relative gravity survey, which is referenced to at least one known gravity value. The tidal effects of the sun and moon, gravimeter drift and tares in the data are all accounted for during the processing of the survey measurements. The calculation is based on a least squares formulation where the difference between the absolute gravity at each surveyed location and parameters relating to the dynamics of the gravimeter are minimized with respect to the relative gravity observations, and some supplied gravity reference site values. The program additionally allows the user to compute free air gravity anomalies, with respect to the GRS80 and GRS67 reference ellipsoids, from the determined gravity values and calculate terrain corrections at each of the surveyed sites using a prism formula and a user supplied digital elevation model. This paper reviews the mathematical framework used to reduce relative gravimeter survey observations to gravity values. It then goes on to detail how the processing steps can be implemented using the software.

Urbanization may limit impacts of an invasive predator on native mammal diversity

USGS Publications Warehouse

Reichert, Brian E.; Sovie, Adia R.; Udell, Brad J.; Hart, Kristen M.; Borkhataria, Rena R.; Bonneau, Mathieu; Reed, Robert; McCleery, Robert A.

2017-01-01

AimOur understanding of the effects of invasive species on faunal diversity is limited in part because invasions often occur in modified landscapes where other drivers of community diversity can exacerbate or reduce the net impacts of an invader. Furthermore, rigorous assessments of the effects of invasive species on native communities that account for variation in sampling, species-specific detection and occurrence of rare species are lacking. Invasive Burmese pythons (Python molurus bivittatus) may be causing declines in medium- to large-sized mammals throughout the Greater Everglades Ecosystem (GEE); however, other factors such as urbanization, habitat changes and drastic alteration in water flow may also be influential in structuring mammal communities. The aim of this study was to gain an understanding of how mammal communities simultaneously facing invasive predators and intensively human-altered landscapes are influenced by these drivers and their interactions.LocationFlorida, USA.MethodsWe used data from trail cameras and scat searches with a hierarchical community model that accounts for undetected species to determine the relative influence of introduced Burmese pythons, urbanization, local hydrology, habitat types and interactive effects between pythons and urbanization on mammal species occurrence, site-level species richness, and turnover.ResultsPython density had significant negative effects on all species except coyotes. Despite these negative effects, occurrence of some generalist species increased significantly near urban areas. At the community level, pythons had the greatest impact on species richness, while turnover was greatest along the urbanization gradient where communities were increasingly similar as distance to urbanization decreased.Main conclusionsWe found evidence for an antagonistic interaction between pythons and urbanization where the impacts of pythons were reduced near urban development. Python-induced changes to mammal communities may be mediated near urban development, but elsewhere in the GEE, pythons are likely causing a fundamental restructuring of the food web, declines in ecosystem function, and creating complex and unpredictable cascading effects.

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

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.

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.

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.

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

The Jupyter/IPython architecture: a unified view of computational research, from interactive exploration to communication and publication.

NASA Astrophysics Data System (ADS)

Ragan-Kelley, M.; Perez, F.; Granger, B.; Kluyver, T.; Ivanov, P.; Frederic, J.; Bussonnier, M.

2014-12-01

IPython has provided terminal-based tools for interactive computing in Python since 2001. The notebook document format and multi-process architecture introduced in 2011 have expanded the applicable scope of IPython into teaching, presenting, and sharing computational work, in addition to interactive exploration. The new architecture also allows users to work in any language, with implementations in Python, R, Julia, Haskell, and several other languages. The language agnostic parts of IPython have been renamed to Jupyter, to better capture the notion that a cross-language design can encapsulate commonalities present in computational research regardless of the programming language being used. This architecture offers components like the web-based Notebook interface, that supports rich documents that combine code and computational results with text narratives, mathematics, images, video and any media that a modern browser can display. This interface can be used not only in research, but also for publication and education, as notebooks can be converted to a variety of output formats, including HTML and PDF. Recent developments in the Jupyter project include a multi-user environment for hosting notebooks for a class or research group, a live collaboration notebook via Google Docs, and better support for languages other than Python.

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.

Neo: an object model for handling electrophysiology data in multiple formats

PubMed Central

Garcia, Samuel; Guarino, Domenico; Jaillet, Florent; Jennings, Todd; Pröpper, Robert; Rautenberg, Philipp L.; Rodgers, Chris C.; Sobolev, Andrey; Wachtler, Thomas; Yger, Pierre; Davison, Andrew P.

2014-01-01

Neuroscientists use many different software tools to acquire, analyze and visualize electrophysiological signals. However, incompatible data models and file formats make it difficult to exchange data between these tools. This reduces scientific productivity, renders potentially useful analysis methods inaccessible and impedes collaboration between labs. A common representation of the core data would improve interoperability and facilitate data-sharing. To that end, we propose here a language-independent object model, named “Neo,” suitable for representing data acquired from electroencephalographic, intracellular, or extracellular recordings, or generated from simulations. As a concrete instantiation of this object model we have developed an open source implementation in the Python programming language. In addition to representing electrophysiology data in memory for the purposes of analysis and visualization, the Python implementation provides a set of input/output (IO) modules for reading/writing the data from/to a variety of commonly used file formats. Support is included for formats produced by most of the major manufacturers of electrophysiology recording equipment and also for more generic formats such as MATLAB. Data representation and data analysis are conceptually separate: it is easier to write robust analysis code if it is focused on analysis and relies on an underlying package to handle data representation. For that reason, and also to be as lightweight as possible, the Neo object model and the associated Python package are deliberately limited to representation of data, with no functions for data analysis or visualization. Software for neurophysiology data analysis and visualization built on top of Neo automatically gains the benefits of interoperability, easier data sharing and automatic format conversion; there is already a burgeoning ecosystem of such tools. We intend that Neo should become the standard basis for Python tools in neurophysiology. PMID:24600386

Neo: an object model for handling electrophysiology data in multiple formats.

PubMed

Garcia, Samuel; Guarino, Domenico; Jaillet, Florent; Jennings, Todd; Pröpper, Robert; Rautenberg, Philipp L; Rodgers, Chris C; Sobolev, Andrey; Wachtler, Thomas; Yger, Pierre; Davison, Andrew P

2014-01-01

Neuroscientists use many different software tools to acquire, analyze and visualize electrophysiological signals. However, incompatible data models and file formats make it difficult to exchange data between these tools. This reduces scientific productivity, renders potentially useful analysis methods inaccessible and impedes collaboration between labs. A common representation of the core data would improve interoperability and facilitate data-sharing. To that end, we propose here a language-independent object model, named "Neo," suitable for representing data acquired from electroencephalographic, intracellular, or extracellular recordings, or generated from simulations. As a concrete instantiation of this object model we have developed an open source implementation in the Python programming language. In addition to representing electrophysiology data in memory for the purposes of analysis and visualization, the Python implementation provides a set of input/output (IO) modules for reading/writing the data from/to a variety of commonly used file formats. Support is included for formats produced by most of the major manufacturers of electrophysiology recording equipment and also for more generic formats such as MATLAB. Data representation and data analysis are conceptually separate: it is easier to write robust analysis code if it is focused on analysis and relies on an underlying package to handle data representation. For that reason, and also to be as lightweight as possible, the Neo object model and the associated Python package are deliberately limited to representation of data, with no functions for data analysis or visualization. Software for neurophysiology data analysis and visualization built on top of Neo automatically gains the benefits of interoperability, easier data sharing and automatic format conversion; there is already a burgeoning ecosystem of such tools. We intend that Neo should become the standard basis for Python tools in neurophysiology.

DataViewer3D: An Open-Source, Cross-Platform Multi-Modal Neuroimaging Data Visualization Tool

PubMed Central

Gouws, André; Woods, Will; Millman, Rebecca; Morland, Antony; Green, Gary

2008-01-01

Integration and display of results from multiple neuroimaging modalities [e.g. magnetic resonance imaging (MRI), magnetoencephalography, EEG] relies on display of a diverse range of data within a common, defined coordinate frame. DataViewer3D (DV3D) is a multi-modal imaging data visualization tool offering a cross-platform, open-source solution to simultaneous data overlay visualization requirements of imaging studies. While DV3D is primarily a visualization tool, the package allows an analysis approach where results from one imaging modality can guide comparative analysis of another modality in a single coordinate space. DV3D is built on Python, a dynamic object-oriented programming language with support for integration of modular toolkits, and development of cross-platform software for neuroimaging. DV3D harnesses the power of the Visualization Toolkit (VTK) for two-dimensional (2D) and 3D rendering, calling VTK's low level C++ functions from Python. Users interact with data via an intuitive interface that uses Python to bind wxWidgets, which in turn calls the user's operating system dialogs and graphical user interface tools. DV3D currently supports NIfTI-1, ANALYZE™ and DICOM formats for MRI data display (including statistical data overlay). Formats for other data types are supported. The modularity of DV3D and ease of use of Python allows rapid integration of additional format support and user development. DV3D has been tested on Mac OSX, RedHat Linux and Microsoft Windows XP. DV3D is offered for free download with an extensive set of tutorial resources and example data. PMID:19352444

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

CyNEST: a maintainable Cython-based interface for the NEST simulator

PubMed Central

Zaytsev, Yury V.; Morrison, Abigail

2014-01-01

NEST is a simulator for large-scale networks of spiking point neuron models (Gewaltig and Diesmann, 2007). Originally, simulations were controlled via the Simulation Language Interpreter (SLI), a built-in scripting facility implementing a language derived from PostScript (Adobe Systems, Inc., 1999). The introduction of PyNEST (Eppler et al., 2008), the Python interface for NEST, enabled users to control simulations using Python. As the majority of NEST users found PyNEST easier to use and to combine with other applications, it immediately displaced SLI as the default NEST interface. However, developing and maintaining PyNEST has become increasingly difficult over time. This is partly because adding new features requires writing low-level C++ code intermixed with calls to the Python/C API, which is unrewarding. Moreover, the Python/C API evolves with each new version of Python, which results in a proliferation of version-dependent code branches. In this contribution we present the re-implementation of PyNEST in the Cython language, a superset of Python that additionally supports the declaration of C/C++ types for variables and class attributes, and provides a convenient foreign function interface (FFI) for invoking C/C++ routines (Behnel et al., 2011). Code generation via Cython allows the production of smaller and more maintainable bindings, including increased compatibility with all supported Python releases without additional burden for NEST developers. Furthermore, this novel approach opens up the possibility to support alternative implementations of the Python language at no cost given a functional Cython back-end for the corresponding implementation, and also enables cross-compilation of Python bindings for embedded systems and supercomputers alike. PMID:24672470

Transire, a Program for Generating Solid-State Interface Structures

DTIC Science & Technology

2017-09-14

function-based electron transport property calculator. Three test cases are presented to demonstrate the usage of Transire: the misorientation of the...graphene bilayer, the interface energy as a function of misorientation of copper grain boundaries, and electron transport transmission across the...gallium nitride/silicon carbide interface. 15. SUBJECT TERMS crystalline interface, electron transport, python, computational chemistry, grain boundary

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.

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.

Image Classification Workflow Using Machine Learning Methods

NASA Astrophysics Data System (ADS)

Christoffersen, M. S.; Roser, M.; Valadez-Vergara, R.; Fernández-Vega, J. A.; Pierce, S. A.; Arora, R.

2016-12-01

Recent increases in the availability and quality of remote sensing datasets have fueled an increasing number of scientifically significant discoveries based on land use classification and land use change analysis. However, much of the software made to work with remote sensing data products, specifically multispectral images, is commercial and often prohibitively expensive. The free to use solutions that are currently available come bundled up as small parts of much larger programs that are very susceptible to bugs and difficult to install and configure. What is needed is a compact, easy to use set of tools to perform land use analysis on multispectral images. To address this need, we have developed software using the Python programming language with the sole function of land use classification and land use change analysis. We chose Python to develop our software because it is relatively readable, has a large body of relevant third party libraries such as GDAL and Spectral Python, and is free to install and use on Windows, Linux, and Macintosh operating systems. In order to test our classification software, we performed a K-means unsupervised classification, Gaussian Maximum Likelihood supervised classification, and a Mahalanobis Distance based supervised classification. The images used for testing were three Landsat rasters of Austin, Texas with a spatial resolution of 60 meters for the years of 1984 and 1999, and 30 meters for the year 2015. The testing dataset was easily downloaded using the Earth Explorer application produced by the USGS. The software should be able to perform classification based on any set of multispectral rasters with little to no modification. Our software makes the ease of land use classification using commercial software available without an expensive license.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Tanny, S; Bogue, J; Parsai, E

Purpose: Potential collisions between the gantry head and the patient or table assembly are difficult to detect in most treatment planning systems. We have developed and implemented a novel software package for the representation of potential gantry collisions with the couch assembly at the time of treatment planning. Methods: Physical dimensions of the Varian Edge linear accelerator treatment head were measured and reproduced using the Visual Python display package. A script was developed for the Pinnacle treatment planning system to generate a file with the relevant couch, gantry, and isocenter positions for each beam in a planning trial. A pythonmore » program was developed to parse the information from the TPS and produce a representative model of the couch/gantry system. Using the model and the Visual Python libraries, a rendering window is generated for each beam that allows the planner to evaluate the possibility of a collision. Results: Comparison against heuristic methods and direct verification on the machine validated the collision model generated by the software. Encounters of <1 cm between the gantry treatment head and table were visualized as collisions in our virtual model. Visual windows were created depicting the angle of collision for each beam, including the anticipated table coordinates. Visual rendering of a 6 arc trial with multiple couch positions was completed in under 1 minute, with network bandwidth being the primary bottleneck. Conclusion: The developed software allows for quick examination of possible collisions during the treatment planning process and helps to prevent major collisions prior to plan approval. The software can easily be implemented on future planning systems due to the versatility and platform independence of the Python programming language. Further integration of the software with the treatment planning system will allow the possibility of patient-gantry collision detection for a range of treatment machines.« less

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.

Personalization of structural PDB files.

PubMed

Woźniak, Tomasz; Adamiak, Ryszard W

2013-01-01

PDB format is most commonly applied by various programs to define three-dimensional structure of biomolecules. However, the programs often use different versions of the format. Thus far, no comprehensive solution for unifying the PDB formats has been developed. Here we present an open-source, Python-based tool called PDBinout for processing and conversion of various versions of PDB file format for biostructural applications. Moreover, PDBinout allows to create one's own PDB versions. PDBinout is freely available under the LGPL licence at http://pdbinout.ibch.poznan.pl.

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.

OpenStereo: Open Source, Cross-Platform Software for Structural Geology Analysis

NASA Astrophysics Data System (ADS)

Grohmann, C. H.; Campanha, G. A.

2010-12-01

Free and open source software (FOSS) are increasingly seen as synonyms of innovation and progress. Freedom to run, copy, distribute, study, change and improve the software (through access to the source code) assure a high level of positive feedback between users and developers, which results in stable, secure and constantly updated systems. Several software packages for structural geology analysis are available to the user, with commercial licenses or that can be downloaded at no cost from the Internet. Some provide basic tools of stereographic projections such as plotting poles, great circles, density contouring, eigenvector analysis, data rotation etc, while others perform more specific tasks, such as paleostress or geotechnical/rock stability analysis. This variety also means a wide range of data formating for input, Graphical User Interface (GUI) design and graphic export format. The majority of packages is built for MS-Windows and even though there are packages for the UNIX-based MacOS, there aren't native packages for *nix (UNIX, Linux, BSD etc) Operating Systems (OS), forcing the users to run these programs with emulators or virtual machines. Those limitations lead us to develop OpenStereo, an open source, cross-platform software for stereographic projections and structural geology. The software is written in Python, a high-level, cross-platform programming language and the GUI is designed with wxPython, which provide a consistent look regardless the OS. Numeric operations (like matrix and linear algebra) are performed with the Numpy module and all graphic capabilities are provided by the Matplolib library, including on-screen plotting and graphic exporting to common desktop formats (emf, eps, ps, pdf, png, svg). Data input is done with simple ASCII text files, with values of dip direction and dip/plunge separated by spaces, tabs or commas. The user can open multiple file at the same time (or the same file more than once), and overlay different elements of each dataset (poles, great circles etc). The GUI shows the opened files in a tree structure, similar to “layers” of many illustration software, where the vertical order of the files in the tree reflects the drawing order of the selected elements. At this stage, the software performs plotting operations of poles to planes, lineations, great circles, density contours and rose diagrams. A set of statistics is calculated for each file and its eigenvalues and eigenvectors are used to suggest if the data is clustered about a mean value or distributed along a girdle. Modified Flinn, Triangular and histograms plots are also available. Next step of development will focus on tools as merging and rotation of datasets, possibility to save 'projects' and paleostress analysis. In its current state, OpenStereo requires Python, wxPython, Numpy and Matplotlib installed in the system. We recommend installing PythonXY or the Enthought Python Distribution on MS-Windows and MacOS machines, since all dependencies are provided. Most Linux distributions provide an easy way to install all dependencies through software repositories. OpenStereo is released under the GNU General Public License. Programmers willing to contribute are encouraged to contact the authors directly. FAPESP Grant #09/17675-5

78 FR 44275 - Semiannual Regulatory Agenda

Federal Register 2010, 2011, 2012, 2013, 2014

2013-07-23

... 1018-AV68 Evaluation; Constrictor Species From Python, Boa, and Eunectes Genera. National Park Service... Species From Python, Boa, and Eunectes Genera Legal Authority: 18 U.S.C. 42 Abstract: We are making a... Lacey Act: Reticulated python, DeSchauensee's anaconda, green anaconda, and Beni anaconda. The boa...

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 the oblique slip regimes. This approximation is similar to the Johnston et al. (1994) classification; with 7 classes of earthquakes: 1) Normal; 2) Normal - Strike-slip; 3) Strike-slip - Normal; 4) Strike-slip; 5) Strike-slip - Reverse; 6) Reverse - strike-slip and 7) Reverse. FMC uses by default this classification in the resulting diagram, based on the Kaverina et al. (1996) projection, which improves the Frohlich and Apperson (1992) ternary diagram.

Book Review:

NASA Astrophysics Data System (ADS)

Dray, T.

2005-10-01

I have had a love/hate relationship with this book ever since it first came out. On the one hand, this is an excellent introduction for mathematicians to the differential geometry underlying general relativity. On the other hand, this is definitely a book for mathematicians. The book's greatest strength is its clear, precise presentation of the basic ideas in differential geometry, combined with equally clear and precise applications to theoretical physics, notably general relativity. But the book's precision is also its greatest weakness; this is not an easy book to read for non-mathematicians, who may not appreciate the notational complexity, some of which is nonstandard. The present edition is very similar to the original, published in 1992. In addition to minor revisions and clarifications of the material, there is now a brief introduction to fibre bundles, and a (very) brief discussion of the gauge theory description of fundamental particles. The index to the symbols used is also a more complete than in the past, but without the descriptive material present in the previous edition. The bulk of the book consists of a careful introduction to tensors and their properties. Tensors are introduced first as linear maps on vector spaces, and only later generalized to tensor fields on manifolds. The differentiation and integration of differential forms is discussed in detail, including Stokes' theorem, Lie differentiation and Hodge duality, and connections, curvature and torsion. To this point, Wasserman's text can be viewed as an expanded version of Bishop and Goldberg's classic text [1], one major difference being Wasserman's inclusion of the pseudo-Riemannian case from the beginning (in particular, when discussing Hodge duality). Whether one prefers Wasserman's approach to Bishop and Goldberg's is largely a matter of taste: Wasserman's treatment is both more complete and more precise, making it easier to check calculations in detail, but occasionally more difficult to remember what one is calculating. An instructor using this text would be well advised to think carefully about which topics to cover, rather than trying to do everything. The remainder of the book contains applications to mechanics, relativity and gauge theory. In each case, better treatments exist elsewhere. However, each such treatment typically introduces its own notation; it is not without some truth that differential geometry is often described as the study of objects under changes of notation. Having several short treatments of these different topics in one place makes it easy for the instructor to choose those he or she wishes to emphasize, while providing a clear transition to more advanced treatments. The presentation does have some idiosyncrasies. The key concept of a derivation is not clearly defined. Some subtleties are referred to in cryptic comments ('This space is too large') which are never explained. The occasionally nonstandard notation is not always easy to follow, although this is a common criticism of introductory texts in differential geometry, which must balance precision with understanding. And appropriate cross references are not always given in sentences of the form 'Recall that ...', which on occasion contained (correct) results which I did not find obvious, and which I could not quickly find explicitly stated in earlier sections. I also have one minor gripe about the publishing format, namely that the outside margins are too small, at only 1 cm; I found this extremely distracting. But all of these criticisms are minor. Wasserman's book would unquestionably be an excellent introduction to tensor analysis for mathematicians, especially those who are interested in the physics applications. The readers of Classical and Quantum Gravity will want to know whether the book is equally suitable as a text for an introductory course in general relativity. At first glance, this text appears to fill a niche in mathematical sophistication between, say, the undergraduate texts by Schutz [2] or d'Inverno [3], which do not require prior background in differential geometry, and the graduate text by Sachs [4], which does. Nonetheless, the answer, unfortunately, is no. I teach a course in general relativity primarily aimed at advanced undergraduate mathematics majors, which is, however, taken by both undergraduate and graduate students in both mathematics and physics; it is the only course in general relativity taught at my university. Each time I teach the course, I struggle to choose an appropriate text. Wasserman's book has frequently been one of the finalists, but I have never quite been willing to inflict it on my physics students, choosing instead to list it as an optional text. (I have been equally unwilling to inflict Hartle's marvellous book [5] on my mathematics students.) My main objection to this book as a relativity text is not, however, due to concern that the mathematical sophistication is too much for undergraduate physics students. Rather, as a mathematical text in relativity, it does not go far enough. The standard applications are here, but just barely. There is a good discussion of the Schwarzschild solution, including applications to solar system tests and its interpretation as a black hole. However, the Kerr solution is barely mentioned, and the Reissner-Nordström solution is conspicuously absent. Similarly, the cosmological implications of the Friedmann-Robertson-Walker solutions are discussed only briefly. And that's it - no further cosmology, no mention of gravitational waves, etc. Fair enough for a mathematics text in tensor analysis, but not enough to permit this book to be used as a standalone relativity text. This is, ultimately, why I have never used this book as a primary text: I want to spend more time doing relativity and less time proving theorems. For a course for mathematicians (only), however, or as a supplementary text filling in some of the missing mathematical details, this book would be an excellent choice. References [1] Bishop R L and Goldberg S I 1980 Tensor Analysis on Manifolds (New York: Dover) [2] Schutz B F 1985 A First Course in General Relativity (Cambridge: Cambridge University Press) [3] d'Inverno R 1991 Introducing Einstein's Relativity (Oxford: Oxford University Press) [4] Sachs R K 1977 General Relativity for Mathematicians (New York: Springer) [5] Hartle J B 2003 Gravity: An Introduction to Einstein's General Relativity (San Francisco: Addison Wesley)

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.

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.”

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.

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

In Silico Analysis of Gene Expression Network Components Underlying Pigmentation Phenotypes in the Python Identified Evolutionarily Conserved Clusters of Transcription Factor Binding Sites

PubMed Central

2016-01-01

Color variation provides the opportunity to investigate the genetic basis of evolution and selection. Reptiles are less studied than mammals. Comparative genomics approaches allow for knowledge gained in one species to be leveraged for use in another species. We describe a comparative vertebrate analysis of conserved regulatory modules in pythons aimed at assessing bioinformatics evidence that transcription factors important in mammalian pigmentation phenotypes may also be important in python pigmentation phenotypes. We identified 23 python orthologs of mammalian genes associated with variation in coat color phenotypes for which we assessed the extent of pairwise protein sequence identity between pythons and mouse, dog, horse, cow, chicken, anole lizard, and garter snake. We next identified a set of melanocyte/pigment associated transcription factors (CREB, FOXD3, LEF-1, MITF, POU3F2, and USF-1) that exhibit relatively conserved sequence similarity within their DNA binding regions across species based on orthologous alignments across multiple species. Finally, we identified 27 evolutionarily conserved clusters of transcription factor binding sites within ~200-nucleotide intervals of the 1500-nucleotide upstream regions of AIM1, DCT, MC1R, MITF, MLANA, OA1, PMEL, RAB27A, and TYR from Python bivittatus. Our results provide insight into pigment phenotypes in pythons. PMID:27698666

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.

In Silico Analysis of Gene Expression Network Components Underlying Pigmentation Phenotypes in the Python Identified Evolutionarily Conserved Clusters of Transcription Factor Binding Sites.

PubMed

Irizarry, Kristopher J L; Bryden, Randall L

2016-01-01

Color variation provides the opportunity to investigate the genetic basis of evolution and selection. Reptiles are less studied than mammals. Comparative genomics approaches allow for knowledge gained in one species to be leveraged for use in another species. We describe a comparative vertebrate analysis of conserved regulatory modules in pythons aimed at assessing bioinformatics evidence that transcription factors important in mammalian pigmentation phenotypes may also be important in python pigmentation phenotypes. We identified 23 python orthologs of mammalian genes associated with variation in coat color phenotypes for which we assessed the extent of pairwise protein sequence identity between pythons and mouse, dog, horse, cow, chicken, anole lizard, and garter snake. We next identified a set of melanocyte/pigment associated transcription factors (CREB, FOXD3, LEF-1, MITF, POU3F2, and USF-1) that exhibit relatively conserved sequence similarity within their DNA binding regions across species based on orthologous alignments across multiple species. Finally, we identified 27 evolutionarily conserved clusters of transcription factor binding sites within ~200-nucleotide intervals of the 1500-nucleotide upstream regions of AIM1, DCT, MC1R, MITF, MLANA, OA1, PMEL, RAB27A, and TYR from Python bivittatus . Our results provide insight into pigment phenotypes in pythons.

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.

Sailfish: A flexible multi-GPU implementation of the lattice Boltzmann method

NASA Astrophysics Data System (ADS)

Januszewski, M.; Kostur, M.

2014-09-01

We present Sailfish, an open source fluid simulation package implementing the lattice Boltzmann method (LBM) on modern Graphics Processing Units (GPUs) using CUDA/OpenCL. We take a novel approach to GPU code implementation and use run-time code generation techniques and a high level programming language (Python) to achieve state of the art performance, while allowing easy experimentation with different LBM models and tuning for various types of hardware. We discuss the general design principles of the code, scaling to multiple GPUs in a distributed environment, as well as the GPU implementation and optimization of many different LBM models, both single component (BGK, MRT, ELBM) and multicomponent (Shan-Chen, free energy). The paper also presents results of performance benchmarks spanning the last three NVIDIA GPU generations (Tesla, Fermi, Kepler), which we hope will be useful for researchers working with this type of hardware and similar codes. Catalogue identifier: AETA_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AETA_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU Lesser General Public License, version 3 No. of lines in distributed program, including test data, etc.: 225864 No. of bytes in distributed program, including test data, etc.: 46861049 Distribution format: tar.gz Programming language: Python, CUDA C, OpenCL. Computer: Any with an OpenCL or CUDA-compliant GPU. Operating system: No limits (tested on Linux and Mac OS X). RAM: Hundreds of megabytes to tens of gigabytes for typical cases. Classification: 12, 6.5. External routines: PyCUDA/PyOpenCL, Numpy, Mako, ZeroMQ (for multi-GPU simulations), scipy, sympy Nature of problem: GPU-accelerated simulation of single- and multi-component fluid flows. Solution method: A wide range of relaxation models (LBGK, MRT, regularized LB, ELBM, Shan-Chen, free energy, free surface) and boundary conditions within the lattice Boltzmann method framework. Simulations can be run in single or double precision using one or more GPUs. Restrictions: The lattice Boltzmann method works for low Mach number flows only. Unusual features: The actual numerical calculations run exclusively on GPUs. The numerical code is built dynamically at run-time in CUDA C or OpenCL, using templates and symbolic formulas. The high-level control of the simulation is maintained by a Python process. Additional comments: !!!!! The distribution file for this program is over 45 Mbytes and therefore is not delivered directly when Download or Email is requested. Instead a html file giving details of how the program can be obtained is sent. !!!!! Running time: Problem-dependent, typically minutes (for small cases or short simulations) to hours (large cases or long simulations).

A Reward-Based Behavioral Platform to Measure Neural Activity during Head-Fixed Behavior.

PubMed

Micallef, Andrew H; Takahashi, Naoya; Larkum, Matthew E; Palmer, Lucy M

2017-01-01

Understanding the neural computations that contribute to behavior requires recording from neurons while an animal is behaving. This is not an easy task as most subcellular recording techniques require absolute head stability. The Go/No-Go sensory task is a powerful decision-driven task that enables an animal to report a binary decision during head-fixation. Here we discuss how to set up an Ardunio and Python based platform system to control a Go/No-Go sensory behavior paradigm. Using an Arduino micro-controller and Python-based custom written program, a reward can be delivered to the animal depending on the decision reported. We discuss the various components required to build the behavioral apparatus that can control and report such a sensory stimulus paradigm. This system enables the end user to control the behavioral testing in real-time and therefore it provides a strong custom-made platform for probing the neural basis of behavior.

Using the Maxent program for species distribution modelling to assess invasion risk

USGS Publications Warehouse

Jarnevich, Catherine S.; Young, Nicholas E.; Venette, R.C

2015-01-01

MAXENT is a software package used to relate known species occurrences to information describing the environment, such as climate, topography, anthropogenic features or soil data, and forecast the presence or absence of a species at unsampled locations. This particular method is one of the most popular species distribution modelling techniques because of its consistent strong predictive performance and its ease to implement. This chapter discusses the decisions and techniques needed to prepare a correlative climate matching model for the native range of an invasive alien species and use this model to predict the potential distribution of this species in a potentially invaded range (i.e. a novel environment) by using MAXENT for the Burmese python (Python molurus bivittatus) as a case study. The chapter discusses and demonstrates the challenges that are associated with this approach and examines the inherent limitations that come with using MAXENT to forecast distributions of invasive alien species.

EasyModeller: A graphical interface to MODELLER

PubMed Central

2010-01-01

Background MODELLER is a program for automated protein Homology Modeling. It is one of the most widely used tool for homology or comparative modeling of protein three-dimensional structures, but most users find it a bit difficult to start with MODELLER as it is command line based and requires knowledge of basic Python scripting to use it efficiently. Findings The study was designed with an aim to develop of "EasyModeller" tool as a frontend graphical interface to MODELLER using Perl/Tk, which can be used as a standalone tool in windows platform with MODELLER and Python preinstalled. It helps inexperienced users to perform modeling, assessment, visualization, and optimization of protein models in a simple and straightforward way. Conclusion EasyModeller provides a graphical straight forward interface and functions as a stand-alone tool which can be used in a standard personal computer with Microsoft Windows as the operating system. PMID:20712861

Computational Workbench for Multibody Dynamics

NASA Technical Reports Server (NTRS)

Edmonds, Karina

2007-01-01

PyCraft is a computer program that provides an interactive, workbenchlike computing environment for developing and testing algorithms for multibody dynamics. Examples of multibody dynamic systems amenable to analysis with the help of PyCraft include land vehicles, spacecraft, robots, and molecular models. PyCraft is based on the Spatial-Operator- Algebra (SOA) formulation for multibody dynamics. The SOA operators enable construction of simple and compact representations of complex multibody dynamical equations. Within the Py-Craft computational workbench, users can, essentially, use the high-level SOA operator notation to represent the variety of dynamical quantities and algorithms and to perform computations interactively. PyCraft provides a Python-language interface to underlying C++ code. Working with SOA concepts, a user can create and manipulate Python-level operator classes in order to implement and evaluate new dynamical quantities and algorithms. During use of PyCraft, virtually all SOA-based algorithms are available for computational experiments.

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

Algorithm Building and Learning Programming Languages Using a New Educational Paradigm

NASA Astrophysics Data System (ADS)

Jain, Anshul K.; Singhal, Manik; Gupta, Manu Sheel

2011-08-01

This research paper presents a new concept of using a single tool to associate syntax of various programming languages, algorithms and basic coding techniques. A simple framework has been programmed in Python that helps students learn skills to develop algorithms, and implement them in various programming languages. The tool provides an innovative and a unified graphical user interface for development of multimedia objects, educational games and applications. It also aids collaborative learning amongst students and teachers through an integrated mechanism based on Remote Procedure Calls. The paper also elucidates an innovative method for code generation to enable students to learn the basics of programming languages using drag-n-drop methods for image objects.

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.

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

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.

A new algorithm to reduce noise in microscopy images implemented with a simple program in python.

PubMed

Papini, Alessio

2012-03-01

All microscopical images contain noise, increasing when (e.g., transmission electron microscope or light microscope) approaching the resolution limit. Many methods are available to reduce noise. One of the most commonly used is image averaging. We propose here to use the mode of pixel values. Simple Python programs process a given number of images, recorded consecutively from the same subject. The programs calculate the mode of the pixel values in a given position (a, b). The result is a new image containing in (a, b) the mode of the values. Therefore, the final pixel value corresponds to that read in at least two of the pixels in position (a, b). The application of the program on a set of images obtained by applying salt and pepper noise and GIMP hurl noise with 10-90% standard deviation showed that the mode performs better than averaging with three-eight images. The data suggest that the mode would be more efficient (in the sense of a lower number of recorded images to process to reduce noise below a given limit) for lower number of total noisy pixels and high standard deviation (as impulse noise and salt and pepper noise), while averaging would be more efficient when the number of varying pixels is high, and the standard deviation is low, as in many cases of Gaussian noise affected images. The two methods may be used serially. Copyright © 2011 Wiley Periodicals, Inc.

Satiety and eating patterns in two species of constricting snakes.

PubMed

Nielsen, Torben P; Jacobsen, Magnus W; Wang, Tobias

2011-01-10

Satiety has been studied extensively in mammals, birds and fish but very little information exists on reptiles. Here we investigate time-dependent satiation in two species of constricting snakes, ball pythons (Python regius) and yellow anacondas (Eunectes notaeus). Satiation was shown to depend on both fasting time and prey size. In the ball pythons fed with mice of a relative prey mass RPM (mass of the prey/mass of the snake×100) of 15%, we observed a satiety response that developed between 6 and 12h after feeding, but after 24h pythons regained their appetite. With an RPM of 10% the pythons kept eating throughout the experiment. The anacondas showed a non-significant tendency for satiety to develop between 6 and 12h after ingesting a prey of 20% RPM. Unlike pythons, anacondas remained satiated after 24h. Handling time (from strike until prey swallowed) increased with RPM. We also found a significant decrease in handling time between the first and the second prey and a positive correlation between handling time and the mass of the snake. 2010 Elsevier Inc. All rights reserved.

The Biological Observation Matrix (BIOM) format or: how I learned to stop worrying and love the ome-ome.

PubMed

McDonald, Daniel; Clemente, Jose C; Kuczynski, Justin; Rideout, Jai Ram; Stombaugh, Jesse; Wendel, Doug; Wilke, Andreas; Huse, Susan; Hufnagle, John; Meyer, Folker; Knight, Rob; Caporaso, J Gregory

2012-07-12

We present the Biological Observation Matrix (BIOM, pronounced "biome") format: a JSON-based file format for representing arbitrary observation by sample contingency tables with associated sample and observation metadata. As the number of categories of comparative omics data types (collectively, the "ome-ome") grows rapidly, a general format to represent and archive this data will facilitate the interoperability of existing bioinformatics tools and future meta-analyses. The BIOM file format is supported by an independent open-source software project (the biom-format project), which initially contains Python objects that support the use and manipulation of BIOM data in Python programs, and is intended to be an open development effort where developers can submit implementations of these objects in other programming languages. The BIOM file format and the biom-format project are steps toward reducing the "bioinformatics bottleneck" that is currently being experienced in diverse areas of biological sciences, and will help us move toward the next phase of comparative omics where basic science is translated into clinical and environmental applications. The BIOM file format is currently recognized as an Earth Microbiome Project Standard, and as a Candidate Standard by the Genomic Standards Consortium.

New Version of SeismicHandler (SHX) based on ObsPy

NASA Astrophysics Data System (ADS)

Stammler, Klaus; Walther, Marcus

2016-04-01

The command line version of SeismicHandler (SH), a scientific analysis tool for seismic waveform data developed around 1990, has been redesigned in the recent years, based on a project funded by the Deutsche Forschungsgemeinschaft (DFG). The aim was to address new data access techniques, simplified metadata handling and a modularized software design. As a result the program was rewritten in Python in its main parts, taking advantage of simplicity of this script language and its variety of well developed software libraries, including ObsPy. SHX provides an easy access to waveforms and metadata via arclink and FDSN webservice protocols, also access to event catalogs is implemented. With single commands whole networks or stations within a certain area may be read in, the metadata are retrieved from the servers and stored in a local database. For data processing the large set of SH commands is available, as well as the SH scripting language. Via this SH language scripts or additional Python modules the command set of SHX is easily extendable. The program is open source, tested on Linux operating systems, documentation and download is found at URL "https://www.seismic-handler.org/".

Sensor Placement Optimization using Chama

DOE Office of Scientific and Technical Information (OSTI.GOV)

Klise, Katherine A.; Nicholson, Bethany L.; Laird, Carl Damon

Continuous or regularly scheduled monitoring has the potential to quickly identify changes in the environment. However, even with low - cost sensors, only a limited number of sensors can be deployed. The physical placement of these sensors, along with the sensor technology and operating conditions, can have a large impact on the performance of a monitoring strategy. Chama is an open source Python package which includes mixed - integer, stochastic programming formulations to determine sensor locations and technology that maximize monitoring effectiveness. The methods in Chama are general and can be applied to a wide range of applications. Chama ismore » currently being used to design sensor networks to monitor airborne pollutants and to monitor water quality in water distribution systems. The following documentation includes installation instructions and examples, description of software features, and software license. The software is intended to be used by regulatory agencies, industry, and the research community. It is assumed that the reader is familiar with the Python Programming Language. References are included for addit ional background on software components. Online documentation, hosted at http://chama.readthedocs.io/, will be updated as new features are added. The online version includes API documentation .« less

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

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.

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.

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

PubMed Central

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

2015-01-01

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

Isolation and identification of bacterial populations of zoonotic importance from captive non-venomous snakes in Malaysia.

PubMed

Abba, Yusuf; Ilyasu, Yusuf Maina; Noordin, Mustapha Mohamed

2017-07-01

Captivity of non-venomous snakes such as python and boa are common in zoos, aquariums and as pets in households. Poor captivity conditions expose these reptiles to numerous pathogens which may result in disease conditions. The purpose of this study was to investigate the common bacteria isolated from necropsied captive snakes in Malaysia over a five year period. A total of 27 snake carcasses presented for necropsy at the Universiti Putra Malaysia (UPM) were used in this survey. Samples were aseptically obtained at necropsy from different organs/tissues (lung, liver, heart, kindey, oesophagus, lymph node, stomach, spinal cord, spleen, intestine) and cultured onto 5% blood and McConkey agar, respectively. Gram staining, morphological evaluation and biochemical test such as oxidase, catalase and coagulase were used to tentatively identify the presumptive bacterial isolates. Pythons had the highest number of cases (81.3%) followed by anaconda (14.8%) and boa (3.7%). Mixed infection accounted for 81.5% in all snakes and was highest in pythons (63%). However, single infection was only observed in pythons (18.5%). A total of 82.7%, 95.4% and 100% of the bacterial isolates from python, anaconda and boa, respectively were gram negative. Aeromonas spp was the most frequently isolated bacteria in pythons and anaconda with incidences of 25 (18%) and 8 (36.6%) with no difference (p > 0.05) in incidence, respectively, while Salmonella spp was the most frequently isolated in boa and significantly higher (p < 0.05) than in python and anaconda. Bacteria species were most frequently isolated from the kidney of pythons 35 (25.2%), intestines of anacondas 11 (50%) and stomach of boa 3 (30%). This study showed that captive pythons harbored more bacterial species than anaconda or boa. Most of the bacterial species isolated from these snakes have public health importance and have been incriminated in human infections worldwide. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

PubMed

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

2012-01-01

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

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

USGS Publications Warehouse

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

2015-01-01

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

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

PubMed

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

2015-01-01

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

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.

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.

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.

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.

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.

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.

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.

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.

Pydna: a simulation and documentation tool for DNA assembly strategies using python.

PubMed

Pereira, Filipa; Azevedo, Flávio; Carvalho, Ângela; Ribeiro, Gabriela F; Budde, Mark W; Johansson, Björn

2015-05-02

Recent advances in synthetic biology have provided tools to efficiently construct complex DNA molecules which are an important part of many molecular biology and biotechnology projects. The planning of such constructs has traditionally been done manually using a DNA sequence editor which becomes error-prone as scale and complexity of the construction increase. A human-readable formal description of cloning and assembly strategies, which also allows for automatic computer simulation and verification, would therefore be a valuable tool. We have developed pydna, an extensible, free and open source Python library for simulating basic molecular biology DNA unit operations such as restriction digestion, ligation, PCR, primer design, Gibson assembly and homologous recombination. A cloning strategy expressed as a pydna script provides a description that is complete, unambiguous and stable. Execution of the script automatically yields the sequence of the final molecule(s) and that of any intermediate constructs. Pydna has been designed to be understandable for biologists with limited programming skills by providing interfaces that are semantically similar to the description of molecular biology unit operations found in literature. Pydna simplifies both the planning and sharing of cloning strategies and is especially useful for complex or combinatorial DNA molecule construction. An important difference compared to existing tools with similar goals is the use of Python instead of a specifically constructed language, providing a simulation environment that is more flexible and extensible by the user.

Continued Development of Python-Based Thomson Data Analysis and Associated Visualization Tool for NSTX-U

NASA Astrophysics Data System (ADS)

Wallace, William; Miller, Jared; Diallo, Ahmed

2015-11-01

MultiPoint Thomson Scattering (MPTS) is an established, accurate method of finding the temperature, density, and pressure of a magnetically confined plasma. Two Nd:YAG (1064 nm) lasers are fired into the plasma with a effective frequency of 60 Hz, and the light is Doppler shifted by Thomson scattering. Polychromators on the NSTX-U midplane collect the scattered photons at various radii/scattering angles, and the avalanche photodiode voltages are saved to an MDSplus tree for later analysis. IDL code is then used to determine plasma temperature, pressure, and density from the captured polychromator measurements via Selden formulas. [1] Previous work [2] converted the single-processor IDL code into Python code, and prepared a new architecture for multiprocessing MPTS in parallel. However, that work was not completed to the generation of output data and curve fits that match with the previous IDL. This project refactored the Python code into a object-oriented architecture, and created a software test suite for the new architecture which allowed identification of the code which generated the difference in output. Another effort currently underway is to display the Thomson data in an intuitive, interactive format. This work was supported in part by the U.S. Department of Energy, Office of Science, Office of Workforce Development for Teachers and Scientists (WDTS) under the Community College Internship (CCI) program.

Jupyter Notebooks for Earth Sciences: An Interactive Training Platform for Seismology

NASA Astrophysics Data System (ADS)

Igel, H.; Chow, B.; Donner, S.; Krischer, L.; van Driel, M.; Tape, C.

2017-12-01

We have initiated a community platform (http://www.seismo-live.org) where Python-based Jupyter notebooks (https://jupyter.org) can be accessed and run without necessary downloads or local software installations. The increasingly popular Jupyter notebooks allow the combination of markup language, graphics, and equations with interactive, executable Python code examples. Jupyter notebooks are a powerful and easy-to-grasp tool for students to develop entire projects, scientists to collaborate and efficiently interchange evolving workflows, and trainers to develop efficient practical material. Utilizing the tmpnb project (https://github.com/jupyter/tmpnb), we link the power of Jupyter notebooks with an underlying server, such that notebooks can be run from anywhere, even on smart phones. We demonstrate the potential with notebooks for 1) learning the programming language Python, 2) basic signal processing, 3) an introduction to the ObsPy library (https://obspy.org) for seismology, 4) seismic noise analysis, 5) an entire suite of notebooks for computational seismology (the finite-difference method, pseudospectral methods, finite/spectral element methods, the finite-volume and the discontinuous Galerkin methods, Instaseis), 6) rotational seismology, 7) making results in papers fully reproducible, 8) a rate-and-state friction toolkit, 9) glacial seismology. The platform is run as a community project using Github. Submission of complementary Jupyter notebooks is encouraged. Extension in the near future include linear(-ized) and nonlinear inverse problems.

Jungle Giants: Assessing Sustainable Harvesting in a Difficult-to-Survey Species (Python reticulatus).

PubMed

Natusch, Daniel J D; Lyons, Jessica A; Mumpuni; Riyanto, Awal; Shine, Richard

2016-01-01

Sustainability of wildlife harvests is critical but difficult to assess. Evaluations of sustainability typically combine modelling with the measurement of underlying abundances. For many taxa harvested in developing countries, however, abundances are near-impossible to survey and a lack of detailed ecological information impedes the reliability of models. In such cases, repeated surveys of the attributes of harvested individuals may provide more robust information on sustainability. If the numbers, sizes and other demographic attributes of animals taken for the commercial trade do not change over biologically significant time intervals (decades), there is a prima facie case that the harvest is indeed sustainable. Here, we report the results of examinations of > 4,200 reticulated pythons (Python reticulatus) taken for the commercial leather industry in northern and southern Sumatra, Indonesia. The numbers, mean body sizes, clutch sizes, sizes at maturity and proportion of giant specimens have not decreased between our first surveys (1995) and repeat surveys (2015). Thus, despite assumptions to the contrary, the harvest appears to be sustainable. We use our data to inform the design of future monitoring programs for this species. Our study underpins the need for robust science to inform wildlife trade policy and decision-making, and urges wildlife managers to assess sustainability of difficult-to-survey terrestrial wildlife by drawing inferences directly from the harvest itself.

Jungle Giants: Assessing Sustainable Harvesting in a Difficult-to-Survey Species (Python reticulatus)

PubMed Central

Natusch, Daniel J. D.; Lyons, Jessica A.; Mumpuni; Riyanto, Awal; Shine, Richard

2016-01-01

Sustainability of wildlife harvests is critical but difficult to assess. Evaluations of sustainability typically combine modelling with the measurement of underlying abundances. For many taxa harvested in developing countries, however, abundances are near-impossible to survey and a lack of detailed ecological information impedes the reliability of models. In such cases, repeated surveys of the attributes of harvested individuals may provide more robust information on sustainability. If the numbers, sizes and other demographic attributes of animals taken for the commercial trade do not change over biologically significant time intervals (decades), there is a prima facie case that the harvest is indeed sustainable. Here, we report the results of examinations of > 4,200 reticulated pythons (Python reticulatus) taken for the commercial leather industry in northern and southern Sumatra, Indonesia. The numbers, mean body sizes, clutch sizes, sizes at maturity and proportion of giant specimens have not decreased between our first surveys (1995) and repeat surveys (2015). Thus, despite assumptions to the contrary, the harvest appears to be sustainable. We use our data to inform the design of future monitoring programs for this species. Our study underpins the need for robust science to inform wildlife trade policy and decision-making, and urges wildlife managers to assess sustainability of difficult-to-survey terrestrial wildlife by drawing inferences directly from the harvest itself. PMID:27391138

Parallel, Distributed Scripting with Python

DOE Office of Scientific and Technical Information (OSTI.GOV)

Miller, P J

2002-05-24

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

A pipeline for comprehensive and automated processing of electron diffraction data in IPLT.

PubMed

Schenk, Andreas D; Philippsen, Ansgar; Engel, Andreas; Walz, Thomas

2013-05-01

Electron crystallography of two-dimensional crystals allows the structural study of membrane proteins in their native environment, the lipid bilayer. Determining the structure of a membrane protein at near-atomic resolution by electron crystallography remains, however, a very labor-intense and time-consuming task. To simplify and accelerate the data processing aspect of electron crystallography, we implemented a pipeline for the processing of electron diffraction data using the Image Processing Library and Toolbox (IPLT), which provides a modular, flexible, integrated, and extendable cross-platform, open-source framework for image processing. The diffraction data processing pipeline is organized as several independent modules implemented in Python. The modules can be accessed either from a graphical user interface or through a command line interface, thus meeting the needs of both novice and expert users. The low-level image processing algorithms are implemented in C++ to achieve optimal processing performance, and their interface is exported to Python using a wrapper. For enhanced performance, the Python processing modules are complemented with a central data managing facility that provides a caching infrastructure. The validity of our data processing algorithms was verified by processing a set of aquaporin-0 diffraction patterns with the IPLT pipeline and comparing the resulting merged data set with that obtained by processing the same diffraction patterns with the classical set of MRC programs. Copyright © 2013 Elsevier Inc. All rights reserved.

A pipeline for comprehensive and automated processing of electron diffraction data in IPLT

PubMed Central

Schenk, Andreas D.; Philippsen, Ansgar; Engel, Andreas; Walz, Thomas

2013-01-01

Electron crystallography of two-dimensional crystals allows the structural study of membrane proteins in their native environment, the lipid bilayer. Determining the structure of a membrane protein at near-atomic resolution by electron crystallography remains, however, a very labor-intense and time-consuming task. To simplify and accelerate the data processing aspect of electron crystallography, we implemented a pipeline for the processing of electron diffraction data using the Image Processing Library & Toolbox (IPLT), which provides a modular, flexible, integrated, and extendable cross-platform, open-source framework for image processing. The diffraction data processing pipeline is organized as several independent modules implemented in Python. The modules can be accessed either from a graphical user interface or through a command line interface, thus meeting the needs of both novice and expert users. The low-level image processing algorithms are implemented in C++ to achieve optimal processing performance, and their interface is exported to Python using a wrapper. For enhanced performance, the Python processing modules are complemented with a central data managing facility that provides a caching infrastructure. The validity of our data processing algorithms was verified by processing a set of aquaporin-0 diffraction patterns with the IPLT pipeline and comparing the resulting merged data set with that obtained by processing the same diffraction patterns with the classical set of MRC programs. PMID:23500887

MR-Tandem: parallel X!Tandem using Hadoop MapReduce on Amazon Web Services.

PubMed

Pratt, Brian; Howbert, J Jeffry; Tasman, Natalie I; Nilsson, Erik J

2012-01-01

MR-Tandem adapts the popular X!Tandem peptide search engine to work with Hadoop MapReduce for reliable parallel execution of large searches. MR-Tandem runs on any Hadoop cluster but offers special support for Amazon Web Services for creating inexpensive on-demand Hadoop clusters, enabling search volumes that might not otherwise be feasible with the compute resources a researcher has at hand. MR-Tandem is designed to drop in wherever X!Tandem is already in use and requires no modification to existing X!Tandem parameter files, and only minimal modification to X!Tandem-based workflows. MR-Tandem is implemented as a lightly modified X!Tandem C++ executable and a Python script that drives Hadoop clusters including Amazon Web Services (AWS) Elastic Map Reduce (EMR), using the modified X!Tandem program as a Hadoop Streaming mapper and reducer. The modified X!Tandem C++ source code is Artistic licensed, supports pluggable scoring, and is available as part of the Sashimi project at http://sashimi.svn.sourceforge.net/viewvc/sashimi/trunk/trans_proteomic_pipeline/extern/xtandem/. The MR-Tandem Python script is Apache licensed and available as part of the Insilicos Cloud Army project at http://ica.svn.sourceforge.net/viewvc/ica/trunk/mr-tandem/. Full documentation and a windows installer that configures MR-Tandem, Python and all necessary packages are available at this same URL. brian.pratt@insilicos.com

Short telomeres in hatchling snakes: erythrocyte telomere dynamics and longevity in tropical pythons.

PubMed

Ujvari, Beata; Madsen, Thomas

2009-10-16

Telomere length (TL) has been found to be associated with life span in birds and humans. However, other studies have demonstrated that TL does not affect survival among old humans. Furthermore, replicative senescence has been shown to be induced by changes in the protected status of the telomeres rather than the loss of TL. In the present study we explore whether age- and sex-specific telomere dynamics affect life span in a long-lived snake, the water python (Liasis fuscus). Erythrocyte TL was measured using the Telo TAGGG TL Assay Kit (Roche). In contrast to other vertebrates, TL of hatchling pythons was significantly shorter than that of older snakes. However, during their first year of life hatchling TL increased substantially. While TL of older snakes decreased with age, we did not observe any correlation between TL and age in cross-sectional sampling. In older snakes, female TL was longer than that of males. When using recapture as a proxy for survival, our results do not support that longer telomeres resulted in an increased water python survival/longevity. In fish high telomerase activity has been observed in somatic cells exhibiting high proliferation rates. Hatchling pythons show similar high somatic cell proliferation rates. Thus, the increase in TL of this group may have been caused by increased telomerase activity. In older humans female TL is longer than that of males. This has been suggested to be caused by high estrogen levels that stimulate increased telomerase activity. Thus, high estrogen levels may also have caused the longer telomeres in female pythons. The lack of correlation between TL and age among old snakes and the fact that longer telomeres did not appear to affect python survival do not support that erythrocyte telomere dynamics has a major impact on water python longevity.

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

PubMed

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

2015-01-01

Snake venom gene evolution has been studied intensively over the past several decades, yet most previous studies have lacked the context of complete snake genomes and the full context of gene expression across diverse snake tissues. We took a novel approach to studying snake venom evolution by leveraging the complete genome of the Burmese python, including information from tissue-specific patterns of gene expression. We identified the orthologs of snake venom genes in the python genome, and conducted detailed analysis of gene expression of these venom homologs to identify patterns that differ between snake venom gene families and all other genes. We found that venom gene homologs in the python are expressed in many different tissues outside of oral glands, which illustrates the pitfalls of using transcriptomic data alone to define "venom toxins." We hypothesize that the python may represent an ancestral state prior to major venom development, which is supported by our finding that the expansion of venom gene families is largely restricted to highly venomous caenophidian snakes. Therefore, the python provides insight into biases in which genes were recruited for snake venom systems. Python venom homologs are generally expressed at lower levels, have higher variance among tissues, and are expressed in fewer organs compared with all other python genes. We propose a model for the evolution of snake venoms in which venom genes are recruited preferentially from genes with particular expression profile characteristics, which facilitate a nearly neutral transition toward specialized venom system expression. © The Author 2014. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Unified EDGE

DOE Office of Scientific and Technical Information (OSTI.GOV)

2007-06-18

UEDGE is an interactive suite of physics packages using the Python or BASIS scripting systems. The plasma is described by time-dependent 2D plasma fluid equations that include equations for density, velocity, ion temperature, electron temperature, electrostatic potential, and gas density in the edge region of a magnetic fusion energy confinement device. Slab, cylindrical, and toroidal geometries are allowed, and closed and open magnetic field-line regions are included. Classical transport is assumed along magnetic field lines, and anomalous transport is assumed across field lines. Multi-charge state impurities can be included with the corresponding line-radiation energy loss. Although UEDGE is written inmore » Fortran, for efficient execution and analysis of results, it utilizes either Python or BASIS scripting shells. Python is easily available for many platforms (http://www.Python.org/). The features and availability of BASIS are described in "Basis Manual Set" by P.F. Dubois, Z.C. Motteler, et al., Lawrence Livermore National Laboratory report UCRL-MA-1 18541, June, 2002 and http://basis.llnl.gov. BASIS has been reviewed and released by LLNL for unlimited distribution. The Python version utilizes PYBASIS scripts developed by D.P. Grote, LLNL. The Python version also uses MPPL code and MAC Perl script, available from the public-domain BASIS source above. The Forthon version of UEDGE uses the same source files, but utilizes Forthon to produce a Python-compatible source. Forthon has been developed by D.P. Grote at LBL (see http://hifweb.lbl.gov/Forthon/ and Grote et al. in the references below), and it is freely available. The graphics can be performed by any package importable to Python, such as PYGIST.« less

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.

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.

Polyglot Programming in Applications Used for Genetic Data Analysis

PubMed Central

Nowak, Robert M.

2014-01-01

Applications used for the analysis of genetic data process large volumes of data with complex algorithms. High performance, flexibility, and a user interface with a web browser are required by these solutions, which can be achieved by using multiple programming languages. In this study, I developed a freely available framework for building software to analyze genetic data, which uses C++, Python, JavaScript, and several libraries. This system was used to build a number of genetic data processing applications and it reduced the time and costs of development. PMID:25197633

Polyglot programming in applications used for genetic data analysis.

PubMed

Nowak, Robert M

2014-01-01

Applications used for the analysis of genetic data process large volumes of data with complex algorithms. High performance, flexibility, and a user interface with a web browser are required by these solutions, which can be achieved by using multiple programming languages. In this study, I developed a freely available framework for building software to analyze genetic data, which uses C++, Python, JavaScript, and several libraries. This system was used to build a number of genetic data processing applications and it reduced the time and costs of development.

Shwirl: Meaningful coloring of spectral cube data with volume rendering

NASA Astrophysics Data System (ADS)

Vohl, Dany

2017-04-01

Shwirl visualizes spectral data cubes with meaningful coloring methods. The program has been developed to investigate transfer functions, which combines volumetric elements (or voxels) to set the color, and graphics shaders, functions used to compute several properties of the final image such as color, depth, and/or transparency, as enablers for scientific visualization of astronomical data. The program uses Astropy (ascl:1304.002) to handle FITS files and World Coordinate System, Qt (and PyQt) for the user interface, and VisPy, an object-oriented Python visualization library binding onto OpenGL.

XAFSmass: a program for calculating the optimal mass of XAFS samples

NASA Astrophysics Data System (ADS)

Klementiev, K.; Chernikov, R.

2016-05-01

We present a new implementation of the XAFSmass program that calculates the optimal mass of XAFS samples. It has several improvements as compared to the old Windows based program XAFSmass: 1) it is truly platform independent, as provided by Python language, 2) it has an improved parser of chemical formulas that enables parentheses and nested inclusion-to-matrix weight percentages. The program calculates the absorption edge height given the total optical thickness, operates with differently determined sample amounts (mass, pressure, density or sample area) depending on the aggregate state of the sample and solves the inverse problem of finding the elemental composition given the experimental absorption edge jump and the chemical formula.

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.

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.

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

PubMed

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

2014-01-01

pyOpenMS is an open-source, Python-based interface to the C++ OpenMS library, providing facile access to a feature-rich, open-source algorithm library for MS-based proteomics analysis. It contains Python bindings that allow raw access to the data structures and algorithms implemented in OpenMS, specifically those for file access (mzXML, mzML, TraML, mzIdentML among others), basic signal processing (smoothing, filtering, de-isotoping, and peak-picking) and complex data analysis (including label-free, SILAC, iTRAQ, and SWATH analysis tools). pyOpenMS thus allows fast prototyping and efficient workflow development in a fully interactive manner (using the interactive Python interpreter) and is also ideally suited for researchers not proficient in C++. In addition, our code to wrap a complex C++ library is completely open-source, allowing other projects to create similar bindings with ease. The pyOpenMS framework is freely available at https://pypi.python.org/pypi/pyopenms while the autowrap tool to create Cython code automatically is available at https://pypi.python.org/pypi/autowrap (both released under the 3-clause BSD licence). © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Fragment Impact Toolkit (FIT)

DOE Office of Scientific and Technical Information (OSTI.GOV)

Shevitz, Daniel Wolf; Key, Brian P.; Garcia, Daniel B.

2017-09-05

The Fragment Impact Toolkit (FIT) is a software package used for probabilistic consequence evaluation of fragmenting sources. The typical use case for FIT is to simulate an exploding shell and evaluate the consequence on nearby objects. FIT is written in the programming language Python and is designed as a collection of interacting software modules. Each module has a function that interacts with the other modules to produce desired results.

"Remember to Hand out Medals": Peer Rating and Expertise in a Question-and-Answer Study Group

ERIC Educational Resources Information Center

Ponti, Marisa

2015-01-01

This article reports on an exploratory study of giving medals as part of a peer rating system in a question-and-answer (Q&A) study group on Python, a programming language. There are no professional teachers tutoring learners. The study aimed to understand whether and how medals, awarded to responses in a peer-based learning environment, can…

A Python Program for Solving Schro¨dinger's Equation in Undergraduate Physical Chemistry

ERIC Educational Resources Information Center

Srnec, Matthew N.; Upadhyay, Shiv; Madura, Jeffry D.

2017-01-01

In undergraduate physical chemistry, Schrödinger's equation is solved for a variety of cases. In doing so, the energies and wave functions of the system can be interpreted to provide connections with the physical system being studied. Solving this equation by hand for a one-dimensional system is a manageable task, but it becomes time-consuming…

DOE Office of Scientific and Technical Information (OSTI.GOV)

Piot, P.; Halavanau, A.

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

Pyomo v5.0

DOE Office of Scientific and Technical Information (OSTI.GOV)

Woodruff, David; Hackebeil, Gabe; Laird, Carl Damon

Pyomo supports the formulation and analysis of mathematical models for complex optimization applications. This capability is commonly associated with algebraic modeling languages (AMLs), which support the description and analysis of mathematical models with a high-level language. Although most AMLs are implemented in custom modeling languages, Pyomo's modeling objects are embedded within Python, a full- featured high-level programming language that contains a rich set of supporting libraries.

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 system. Acknowledgements: Project work is supported by Australian Commonwealth Government through the Australian Computational Earth Systems Simulator Major National Research Facility, Queensland State Government Smart State Research Facility Fund, The University of Queensland and SGI.

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.

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.

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.

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.

Large reptiles and cold temperatures: Do extreme cold spells set distributional limits for tropical reptiles in Florida?

USGS Publications Warehouse

Mazzotti, Frank J.; Cherkiss, Michael S.; Parry, Mark; Beauchamp, Jeff; Rochford, Mike; Smith, Brian J.; Hart, Kristen M.; Brandt, Laura A.

2016-01-01

Distributional limits of many tropical species in Florida are ultimately determined by tolerance to low temperature. An unprecedented cold spell during 2–11 January 2010, in South Florida provided an opportunity to compare the responses of tropical American crocodiles with warm-temperate American alligators and to compare the responses of nonnative Burmese pythons with native warm-temperate snakes exposed to prolonged cold temperatures. After the January 2010 cold spell, a record number of American crocodiles (n = 151) and Burmese pythons (n = 36) were found dead. In contrast, no American alligators and no native snakes were found dead. American alligators and American crocodiles behaved differently during the cold spell. American alligators stopped basking and retreated to warmer water. American crocodiles apparently continued to bask during extreme cold temperatures resulting in lethal body temperatures. The mortality of Burmese pythons compared to the absence of mortality for native snakes suggests that the current population of Burmese pythons in the Everglades is less tolerant of cold temperatures than native snakes. Burmese pythons introduced from other parts of their native range may be more tolerant of cold temperatures. We documented the direct effects of cold temperatures on crocodiles and pythons; however, evidence of long-term effects of cold temperature on their populations within their established ranges remains lacking. Mortality of crocodiles and pythons outside of their current established range may be more important in setting distributional limits.

Automated Reporting of DXA Studies Using a Custom-Built Computer Program.

PubMed

England, Joseph R; Colletti, Patrick M

2018-06-01

Dual-energy x-ray absorptiometry (DXA) scans are a critical population health tool and relatively simple to interpret but can be time consuming to report, often requiring manual transfer of bone mineral density and associated statistics into commercially available dictation systems. We describe here a custom-built computer program for automated reporting of DXA scans using Pydicom, an open-source package built in the Python computer language, and regular expressions to mine DICOM tags for patient information and bone mineral density statistics. This program, easy to emulate by any novice computer programmer, has doubled our efficiency at reporting DXA scans and has eliminated dictation errors.

Developing a Conceptual Architecture for a Generalized Agent-based Modeling Environment (GAME)

DTIC Science & Technology

2008-03-01

4. REPAST (Java, Python , C#, Open Source) ........28 5. MASON: Multi-Agent Modeling Language (Swarm Extension... Python , C#, Open Source) Repast (Recursive Porous Agent Simulation Toolkit) was designed for building agent-based models and simulations in the...Repast makes it easy for inexperienced users to build models by including a built-in simple model and provide interfaces through which menus and Python

XMDS2: Fast, scalable simulation of coupled stochastic partial differential equations

NASA Astrophysics Data System (ADS)

Dennis, Graham R.; Hope, Joseph J.; Johnsson, Mattias T.

2013-01-01

XMDS2 is a cross-platform, GPL-licensed, open source package for numerically integrating initial value problems that range from a single ordinary differential equation up to systems of coupled stochastic partial differential equations. The equations are described in a high-level XML-based script, and the package generates low-level optionally parallelised C++ code for the efficient solution of those equations. It combines the advantages of high-level simulations, namely fast and low-error development, with the speed, portability and scalability of hand-written code. XMDS2 is a complete redesign of the XMDS package, and features support for a much wider problem space while also producing faster code. Program summaryProgram title: XMDS2 Catalogue identifier: AENK_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AENK_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GNU General Public License, version 2 No. of lines in distributed program, including test data, etc.: 872490 No. of bytes in distributed program, including test data, etc.: 45522370 Distribution format: tar.gz Programming language: Python and C++. Computer: Any computer with a Unix-like system, a C++ compiler and Python. Operating system: Any Unix-like system; developed under Mac OS X and GNU/Linux. RAM: Problem dependent (roughly 50 bytes per grid point) Classification: 4.3, 6.5. External routines: The external libraries required are problem-dependent. Uses FFTW3 Fourier transforms (used only for FFT-based spectral methods), dSFMT random number generation (used only for stochastic problems), MPI message-passing interface (used only for distributed problems), HDF5, GNU Scientific Library (used only for Bessel-based spectral methods) and a BLAS implementation (used only for non-FFT-based spectral methods). Nature of problem: General coupled initial-value stochastic partial differential equations. Solution method: Spectral method with method-of-lines integration Running time: Determined by the size of the problem

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.

Open-Source Python Tools for Deploying Interactive GIS Dashboards for a Billion Datapoints on a Laptop

NASA Astrophysics Data System (ADS)

Steinberg, P. D.; Bednar, J. A.; Rudiger, P.; Stevens, J. L. R.; Ball, C. E.; Christensen, S. D.; Pothina, D.

2017-12-01

The rich variety of software libraries available in the Python scientific ecosystem provides a flexible and powerful alternative to traditional integrated GIS (geographic information system) programs. Each such library focuses on doing a certain set of general-purpose tasks well, and Python makes it relatively simple to glue the libraries together to solve a wide range of complex, open-ended problems in Earth science. However, choosing an appropriate set of libraries can be challenging, and it is difficult to predict how much "glue code" will be needed for any particular combination of libraries and tasks. Here we present a set of libraries that have been designed to work well together to build interactive analyses and visualizations of large geographic datasets, in standard web browsers. The resulting workflows run on ordinary laptops even for billions of data points, and easily scale up to larger compute clusters when available. The declarative top-level interface used in these libraries means that even complex, fully interactive applications can be built and deployed as web services using only a few dozen lines of code, making it simple to create and share custom interactive applications even for datasets too large for most traditional GIS systems. The libraries we will cover include GeoViews (HoloViews extended for geographic applications) for declaring visualizable/plottable objects, Bokeh for building visual web applications from GeoViews objects, Datashader for rendering arbitrarily large datasets faithfully as fixed-size images, Param for specifying user-modifiable parameters that model your domain, Xarray for computing with n-dimensional array data, Dask for flexibly dispatching computational tasks across processors, and Numba for compiling array-based Python code down to fast machine code. We will show how to use the resulting workflow with static datasets and with simulators such as GSSHA or AdH, allowing you to deploy flexible, high-performance web-based dashboards for your GIS data or simulations without needing major investments in code development or maintenance.

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.

An End-to-End System to Enable Quick, Easy and Inexpensive Deployment of Hydrometeorological Stations

NASA Astrophysics Data System (ADS)

Celicourt, P.; Piasecki, M.

2014-12-01

The high cost of hydro-meteorological data acquisition, communication and publication systems along with limited qualified human resources is considered as the main reason why hydro-meteorological data collection remains a challenge especially in developing countries. Despite significant advances in sensor network technologies which gave birth to open hardware and software, low-cost (less than $50) and low-power (in the order of a few miliWatts) sensor platforms in the last two decades, sensors and sensor network deployment remains a labor-intensive, time consuming, cumbersome, and thus expensive task. These factors give rise for the need to develop a affordable, simple to deploy, scalable and self-organizing end-to-end (from sensor to publication) system suitable for deployment in such countries. The design of the envisioned system will consist of a few Sensed-And-Programmed Arduino-based sensor nodes with low-cost sensors measuring parameters relevant to hydrological processes and a Raspberry Pi micro-computer hosting the in-the-field back-end data management. This latter comprises the Python/Django model of the CUAHSI Observations Data Model (ODM) namely DjangODM backed by a PostgreSQL Database Server. We are also developing a Python-based data processing script which will be paired with the data autoloading capability of Django to populate the DjangODM database with the incoming data. To publish the data, the WOFpy (WaterOneFlow Web Services in Python) developed by the Texas Water Development Board for 'Water Data for Texas' which can produce WaterML web services from a variety of back-end database installations such as SQLite, MySQL, and PostgreSQL will be used. A step further would be the development of an appealing online visualization tool using Python statistics and analytics tools (Scipy, Numpy, Pandas) showing the spatial distribution of variables across an entire watershed as a time variant layer on top of a basemap.

The InSAR Scientific Computing Environment (ISCE): An Earth Science SAR Processing Framework, Toolbox, and Foundry

NASA Astrophysics Data System (ADS)

Agram, P. S.; Gurrola, E. M.; Lavalle, M.; Sacco, G. F.; Rosen, P. A.

2016-12-01

The InSAR Scientific Computing Environment (ISCE) provides both a modular, flexible, and extensible framework for building software components and applications that work together seamlessly as well as a toolbox for processing InSAR data into higher level geodetic image products from a diverse array of radar satellites and aircraft. ISCE easily scales to serve as the SAR processing engine at the core of the NASA JPL Advanced Rapid Imaging and Analysis (ARIA) Center for Natural Hazards as well as a software toolbox for individual scientists working with SAR data. ISCE is planned as the foundational element in processing NISAR data, enabling a new class of analyses that take greater advantage of the long time and large spatial scales of these data. ISCE in ARIA is also a SAR Foundry for development of new processing components and workflows to meet the needs of both large processing centers and individual users. The ISCE framework contains object-oriented Python components layered to construct Python InSAR components that manage legacy Fortran/C InSAR programs. The Python user interface enables both command-line deployment of workflows as well as an interactive "sand box" (the Python interpreter) where scientists can "play" with the data. Recent developments in ISCE include the addition of components to ingest Sentinel-1A SAR data (both stripmap and TOPS-mode) and a new workflow for processing the TOPS-mode data. New components are being developed to exploit polarimetric-SAR data to provide the ecosystem and land-cover/land-use change communities with rigorous and efficient tools to perform multi-temporal, polarimetric and tomographic analyses in order to generate calibrated, geocoded and mosaicked Level-2 and Level-3 products (e.g., maps of above-ground biomass or forest disturbance). ISCE has been downloaded by over 200 users by a license for WinSAR members through the Unavco.org website. Others may apply directly to JPL for a license at download.jpl.nasa.gov.

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

NASA Astrophysics Data System (ADS)

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

2012-04-01

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

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

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.

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.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Veseli, S.

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

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.

Methods to Secure Databases Against Vulnerabilities

DTIC Science & Technology

2015-12-01

for several languages such as C, C++, PHP, Java and Python [16]. MySQL will work well with very large databases. The documentation references...using Eclipse and connected to each database management system using Python and Java drivers provided by MySQL , MongoDB, and Datastax (for Cassandra...tiers in Python and Java . Problem MySQL MongoDB Cassandra 1. Injection a. Tautologies Vulnerable Vulnerable Not Vulnerable b. Illegal query

Prevalence of Amblyomma gervaisi ticks on captive snakes in Tamil Nadu.

PubMed

Catherine, B R; Jayathangaraj, M G; Soundararajan, C; Bala Guru, C; Yogaraj, D

2017-12-01

Ticks are the important ectoparasites that occur on snakes and transmit rickettsiosis, anaplasmosis and ehrlichiosis. A total of 62 snakes (Reticulated python, Indian Rock Python, Rat snakes and Spectacled cobra) were examined for tick infestation at Chennai Snake Park Trust (Guindy), Arignar Anna Zoological Park (Vandalur) and Rescue centre (Velachery) in Tamil Nadu from September, 2015 to June, 2016. Ticks from infested snakes were collected and were identified as Amblyomma gervaisi (previously known as Aponomma gervaisi ). Overall occurrence of tick infestation on snakes was 66.13%. Highest prevalence of tick infestation was observed more on Reticulated Python ( Python reticulatus , 90.91%) followed by Indian Rock Python ( Python molurus , 88.89%), Spectacled cobra ( Naja naja, 33.33%) and Rat snake ( Ptyas mucosa, 21.05%). Highest prevalence of ticks were observed on snakes reared at Chennai Snake Park Trust, Guindy (83.33%), followed by Arignar Anna Zoological Park, Vandalur (60.00%) and low level prevalence of 37.50% on snakes at Rescue centre, Velachery. Among the system of management, the prevalence of ticks were more on captive snakes (70.37%) than the free ranging snakes (37.5%). The presences of ticks were more on the first quarter when compared to other three quarters and were highly significant ( P  ≤ 0.01).

Gist: A scientific graphics package for Python

DOE Office of Scientific and Technical Information (OSTI.GOV)

Busby, L.E.

1996-05-08

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

EMPIRE and pyenda: Two ensemble-based data assimilation systems written in Fortran and Python

NASA Astrophysics Data System (ADS)

Geppert, Gernot; Browne, Phil; van Leeuwen, Peter Jan; Merker, Claire

2017-04-01

We present and compare the features of two ensemble-based data assimilation frameworks, EMPIRE and pyenda. Both frameworks allow to couple models to the assimilation codes using the Message Passing Interface (MPI), leading to extremely efficient and fast coupling between models and the data-assimilation codes. The Fortran-based system EMPIRE (Employing Message Passing Interface for Researching Ensembles) is optimized for parallel, high-performance computing. It currently includes a suite of data assimilation algorithms including variants of the ensemble Kalman and several the particle filters. EMPIRE is targeted at models of all kinds of complexity and has been coupled to several geoscience models, eg. the Lorenz-63 model, a barotropic vorticity model, the general circulation model HadCM3, the ocean model NEMO, and the land-surface model JULES. The Python-based system pyenda (Python Ensemble Data Assimilation) allows Fortran- and Python-based models to be used for data assimilation. Models can be coupled either using MPI or by using a Python interface. Using Python allows quick prototyping and pyenda is aimed at small to medium scale models. pyenda currently includes variants of the ensemble Kalman filter and has been coupled to the Lorenz-63 model, an advection-based precipitation nowcasting scheme, and the dynamic global vegetation model JSBACH.

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

Chained nuclei and python pattern in skeletal muscle cells as histological markers for electrical injury.

PubMed

Tanaka, Hiroki; Okuda, Katsuhiro; Ohtani, Seiji; Asari, Masaru; Horioka, Kie; Isozaki, Shotaro; Hayakawa, Akira; Ogawa, Katsuhiro; Hiroshi, Shiono; Shimizu, Keiko

2018-05-01

Electrical injury is damage caused by an electrical current passing through the body. We have previously reported that irregular stripes crossing skeletal muscle fibers (python pattern) and multiple small nuclei arranged in the longitudinal direction of the muscle fibers (chained nuclear change) are uniquely observed by histopathological analysis in the skeletal muscle tissues of patients with electrical injury. However, it remains unclear whether these phenomena are caused by the electrical current itself or by the joule heat generated by the electric current passing through the body. To clarify the causes underlying these changes, we applied electric and heat injury to the exteriorized rat soleus muscle in situ. Although both the python pattern and chained nuclear change were induced by electric injury, only the python pattern was induced by heat injury. Furthermore, a chained nuclear change was induced in the soleus muscle cells by electric current flow in physiological saline at 40 °C ex vivo, but a python pattern was not observed. When the skeletal muscle was exposed to electrical injury in cardiac-arrested rats, a python pattern was induced within 5 h after cardiac arrest, but no chained nuclear change was observed. Therefore, a chained nuclear change is induced by an electrical current alone in tissues in vital condition, whereas a python pattern is caused by joule heat, which may occur shortly after death. The degree and distribution of these skeletal muscle changes may be useful histological markers for analyzing cases of electrical injury in forensic medicine. Copyright © 2017 Elsevier B.V. All rights reserved.

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 models of different domains and grid types.

Automation of Educational Tasks for Academic Radiology.

PubMed

Lamar, David L; Richardson, Michael L; Carlson, Blake

2016-07-01

The process of education involves a variety of repetitious tasks. We believe that appropriate computer tools can automate many of these chores, and allow both educators and their students to devote a lot more of their time to actual teaching and learning. This paper details tools that we have used to automate a broad range of academic radiology-specific tasks on Mac OS X, iOS, and Windows platforms. Some of the tools we describe here require little expertise or time to use; others require some basic knowledge of computer programming. We used TextExpander (Mac, iOS) and AutoHotKey (Win) for automated generation of text files, such as resident performance reviews and radiology interpretations. Custom statistical calculations were performed using TextExpander and the Python programming language. A workflow for automated note-taking was developed using Evernote (Mac, iOS, Win) and Hazel (Mac). Automated resident procedure logging was accomplished using Editorial (iOS) and Python. We created three variants of a teaching session logger using Drafts (iOS) and Pythonista (iOS). Editorial and Drafts were used to create flashcards for knowledge review. We developed a mobile reference management system for iOS using Editorial. We used the Workflow app (iOS) to automatically generate a text message reminder for daily conferences. Finally, we developed two separate automated workflows-one with Evernote (Mac, iOS, Win) and one with Python (Mac, Win)-that generate simple automated teaching file collections. We have beta-tested these workflows, techniques, and scripts on several of our fellow radiologists. All of them expressed enthusiasm for these tools and were able to use one or more of them to automate their own educational activities. Appropriate computer tools can automate many educational tasks, and thereby allow both educators and their students to devote a lot more of their time to actual teaching and learning. Copyright © 2016 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

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 contribute with new functionality and point out room for improvements. Because of that, Pymicra is a candidate to be a community-developed code in the future and to centralize part of the data processing aimed at micrometeorology.

Psi4 1.1: An Open-Source Electronic Structure Program Emphasizing Automation, Advanced Libraries, and Interoperability.

PubMed

Parrish, Robert M; Burns, Lori A; Smith, Daniel G A; Simmonett, Andrew C; DePrince, A Eugene; Hohenstein, Edward G; Bozkaya, Uğur; Sokolov, Alexander Yu; Di Remigio, Roberto; Richard, Ryan M; Gonthier, Jérôme F; James, Andrew M; McAlexander, Harley R; Kumar, Ashutosh; Saitow, Masaaki; Wang, Xiao; Pritchard, Benjamin P; Verma, Prakash; Schaefer, Henry F; Patkowski, Konrad; King, Rollin A; Valeev, Edward F; Evangelista, Francesco A; Turney, Justin M; Crawford, T Daniel; Sherrill, C David

2017-07-11

Psi4 is an ab initio electronic structure program providing methods such as Hartree-Fock, density functional theory, configuration interaction, and coupled-cluster theory. The 1.1 release represents a major update meant to automate complex tasks, such as geometry optimization using complete-basis-set extrapolation or focal-point methods. Conversion of the top-level code to a Python module means that Psi4 can now be used in complex workflows alongside other Python tools. Several new features have been added with the aid of libraries providing easy access to techniques such as density fitting, Cholesky decomposition, and Laplace denominators. The build system has been completely rewritten to simplify interoperability with independent, reusable software components for quantum chemistry. Finally, a wide range of new theoretical methods and analyses have been added to the code base, including functional-group and open-shell symmetry adapted perturbation theory, density-fitted coupled cluster with frozen natural orbitals, orbital-optimized perturbation and coupled-cluster methods (e.g., OO-MP2 and OO-LCCD), density-fitted multiconfigurational self-consistent field, density cumulant functional theory, algebraic-diagrammatic construction excited states, improvements to the geometry optimizer, and the "X2C" approach to relativistic corrections, among many other improvements.

ISMRM Raw data format: A proposed standard for MRI raw datasets.

PubMed

Inati, Souheil J; Naegele, Joseph D; Zwart, Nicholas R; Roopchansingh, Vinai; Lizak, Martin J; Hansen, David C; Liu, Chia-Ying; Atkinson, David; Kellman, Peter; Kozerke, Sebastian; Xue, Hui; Campbell-Washburn, Adrienne E; Sørensen, Thomas S; Hansen, Michael S

2017-01-01

This work proposes the ISMRM Raw Data format as a common MR raw data format, which promotes algorithm and data sharing. A file format consisting of a flexible header and tagged frames of k-space data was designed. Application Programming Interfaces were implemented in C/C++, MATLAB, and Python. Converters for Bruker, General Electric, Philips, and Siemens proprietary file formats were implemented in C++. Raw data were collected using magnetic resonance imaging scanners from four vendors, converted to ISMRM Raw Data format, and reconstructed using software implemented in three programming languages (C++, MATLAB, Python). Images were obtained by reconstructing the raw data from all vendors. The source code, raw data, and images comprising this work are shared online, serving as an example of an image reconstruction project following a paradigm of reproducible research. The proposed raw data format solves a practical problem for the magnetic resonance imaging community. It may serve as a foundation for reproducible research and collaborations. The ISMRM Raw Data format is a completely open and community-driven format, and the scientific community is invited (including commercial vendors) to participate either as users or developers. Magn Reson Med 77:411-421, 2017. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

The Biological Observation Matrix (BIOM) format or: how I learned to stop worrying and love the ome-ome

PubMed Central

2012-01-01

Background We present the Biological Observation Matrix (BIOM, pronounced “biome”) format: a JSON-based file format for representing arbitrary observation by sample contingency tables with associated sample and observation metadata. As the number of categories of comparative omics data types (collectively, the “ome-ome”) grows rapidly, a general format to represent and archive this data will facilitate the interoperability of existing bioinformatics tools and future meta-analyses. Findings The BIOM file format is supported by an independent open-source software project (the biom-format project), which initially contains Python objects that support the use and manipulation of BIOM data in Python programs, and is intended to be an open development effort where developers can submit implementations of these objects in other programming languages. Conclusions The BIOM file format and the biom-format project are steps toward reducing the “bioinformatics bottleneck” that is currently being experienced in diverse areas of biological sciences, and will help us move toward the next phase of comparative omics where basic science is translated into clinical and environmental applications. The BIOM file format is currently recognized as an Earth Microbiome Project Standard, and as a Candidate Standard by the Genomic Standards Consortium. PMID:23587224

Extracting Spatiotemporal Objects from Raster Data to Represent Physical Features and Analyze Related Processes

NASA Astrophysics Data System (ADS)

Zollweg, J. A.

2017-10-01

Numerous ground-based, airborne, and orbiting platforms provide remotely-sensed data of remarkable spatial resolution at short time intervals. However, this spatiotemporal data is most valuable if it can be processed into information, thereby creating meaning. We live in a world of objects: cars, buildings, farms, etc. On a stormy day, we don't see millions of cubes of atmosphere; we see a thunderstorm `object'. Temporally, we don't see the properties of those individual cubes changing, we see the thunderstorm as a whole evolving and moving. There is a need to represent the bulky, raw spatiotemporal data from remote sensors as a small number of relevant spatiotemporal objects, thereby matching the human brain's perception of the world. This presentation reveals an efficient algorithm and system to extract the objects/features from raster-formatted remotely-sensed data. The system makes use of the Python object-oriented programming language, SciPy/NumPy for matrix manipulation and scientific computation, and export/import to the GeoJSON standard geographic object data format. The example presented will show how thunderstorms can be identified and characterized in a spatiotemporal continuum using a Python program to process raster data from NOAA's High-Resolution Rapid Refresh v2 (HRRRv2) data stream.

A Reward-Based Behavioral Platform to Measure Neural Activity during Head-Fixed Behavior

PubMed Central

Micallef, Andrew H.; Takahashi, Naoya; Larkum, Matthew E.; Palmer, Lucy M.

2017-01-01

Understanding the neural computations that contribute to behavior requires recording from neurons while an animal is behaving. This is not an easy task as most subcellular recording techniques require absolute head stability. The Go/No-Go sensory task is a powerful decision-driven task that enables an animal to report a binary decision during head-fixation. Here we discuss how to set up an Ardunio and Python based platform system to control a Go/No-Go sensory behavior paradigm. Using an Arduino micro-controller and Python-based custom written program, a reward can be delivered to the animal depending on the decision reported. We discuss the various components required to build the behavioral apparatus that can control and report such a sensory stimulus paradigm. This system enables the end user to control the behavioral testing in real-time and therefore it provides a strong custom-made platform for probing the neural basis of behavior. PMID:28620282

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

PubMed

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

2013-06-01

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

The Lake Tahoe Basin Land Use Simulation Model

USGS Publications Warehouse

Forney, William M.; Oldham, I. Benson

2011-01-01

This U.S. Geological Survey Open-File Report describes the final modeling product for the Tahoe Decision Support System project for the Lake Tahoe Basin funded by the Southern Nevada Public Land Management Act and the U.S. Geological Survey's Geographic Analysis and Monitoring Program. This research was conducted by the U.S. Geological Survey Western Geographic Science Center. The purpose of this report is to describe the basic elements of the novel Lake Tahoe Basin Land Use Simulation Model, publish samples of the data inputs, basic outputs of the model, and the details of the Python code. The results of this report include a basic description of the Land Use Simulation Model, descriptions and summary statistics of model inputs, two figures showing the graphical user interface from the web-based tool, samples of the two input files, seven tables of basic output results from the web-based tool and descriptions of their parameters, and the fully functional Python code.

Online characterization of planetary surfaces: PlanetServer, an open-source analysis and visualization tool

NASA Astrophysics Data System (ADS)

Marco Figuera, R.; Pham Huu, B.; Rossi, A. P.; Minin, M.; Flahaut, J.; Halder, A.

2018-01-01

The lack of open-source tools for hyperspectral data visualization and analysis creates a demand for new tools. In this paper we present the new PlanetServer, a set of tools comprising a web Geographic Information System (GIS) and a recently developed Python Application Programming Interface (API) capable of visualizing and analyzing a wide variety of hyperspectral data from different planetary bodies. Current WebGIS open-source tools are evaluated in order to give an overview and contextualize how PlanetServer can help in this matters. The web client is thoroughly described as well as the datasets available in PlanetServer. Also, the Python API is described and exposed the reason of its development. Two different examples of mineral characterization of different hydrosilicates such as chlorites, prehnites and kaolinites in the Nili Fossae area on Mars are presented. As the obtained results show positive outcome in hyperspectral analysis and visualization compared to previous literature, we suggest using the PlanetServer approach for such investigations.

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.

Weather forecasting with open source software

NASA Astrophysics Data System (ADS)

Rautenhaus, Marc; Dörnbrack, Andreas

2013-04-01

To forecast the weather situation during aircraft-based atmospheric field campaigns, we employ a tool chain of existing and self-developed open source software tools and open standards. Of particular value are the Python programming language with its extension libraries NumPy, SciPy, PyQt4, Matplotlib and the basemap toolkit, the NetCDF standard with the Climate and Forecast (CF) Metadata conventions, and the Open Geospatial Consortium Web Map Service standard. These open source libraries and open standards helped to implement the "Mission Support System", a Web Map Service based tool to support weather forecasting and flight planning during field campaigns. The tool has been implemented in Python and has also been released as open source (Rautenhaus et al., Geosci. Model Dev., 5, 55-71, 2012). In this presentation we discuss the usage of free and open source software for weather forecasting in the context of research flight planning, and highlight how the field campaign work benefits from using open source tools and open standards.

Modelling and Simulation of the Knee Joint with a Depth Sensor Camera for Prosthetics and Movement Rehabilitation

NASA Astrophysics Data System (ADS)

Risto, S.; Kallergi, M.

2015-09-01

The purpose of this project was to model and simulate the knee joint. A computer model of the knee joint was first created, which was controlled by Microsoft's Kinect for Windows. Kinect created a depth map of the knee and lower leg motion independent of lighting conditions through an infrared sensor. A combination of open source software such as Blender, Python, Kinect SDK and NI_Mate were implemented for the creation and control of the simulated knee based on movements of a live physical model. A physical size model of the knee and lower leg was also created, the movement of which was controlled remotely by the computer model and Kinect. The real time communication of the model and the robotic knee was achieved through programming in Python and Arduino language. The result of this study showed that Kinect in the modelling of human kinematics and can play a significant role in the development of prosthetics and other assistive technologies.

WeBIAS: a web server for publishing bioinformatics applications.

PubMed

Daniluk, Paweł; Wilczyński, Bartek; Lesyng, Bogdan

2015-11-02

One of the requirements for a successful scientific tool is its availability. Developing a functional web service, however, is usually considered a mundane and ungratifying task, and quite often neglected. When publishing bioinformatic applications, such attitude puts additional burden on the reviewers who have to cope with poorly designed interfaces in order to assess quality of presented methods, as well as impairs actual usefulness to the scientific community at large. In this note we present WeBIAS-a simple, self-contained solution to make command-line programs accessible through web forms. It comprises a web portal capable of serving several applications and backend schedulers which carry out computations. The server handles user registration and authentication, stores queries and results, and provides a convenient administrator interface. WeBIAS is implemented in Python and available under GNU Affero General Public License. It has been developed and tested on GNU/Linux compatible platforms covering a vast majority of operational WWW servers. Since it is written in pure Python, it should be easy to deploy also on all other platforms supporting Python (e.g. Windows, Mac OS X). Documentation and source code, as well as a demonstration site are available at http://bioinfo.imdik.pan.pl/webias . WeBIAS has been designed specifically with ease of installation and deployment of services in mind. Setting up a simple application requires minimal effort, yet it is possible to create visually appealing, feature-rich interfaces for query submission and presentation of results.

ODTbrain: a Python library for full-view, dense diffraction tomography.

PubMed

Müller, Paul; Schürmann, Mirjam; Guck, Jochen

2015-11-04

Analyzing the three-dimensional (3D) refractive index distribution of a single cell makes it possible to describe and characterize its inner structure in a marker-free manner. A dense, full-view tomographic data set is a set of images of a cell acquired for multiple rotational positions, densely distributed from 0 to 360 degrees. The reconstruction is commonly realized by projection tomography, which is based on the inversion of the Radon transform. The reconstruction quality of projection tomography is greatly improved when first order scattering, which becomes relevant when the imaging wavelength is comparable to the characteristic object size, is taken into account. This advanced reconstruction technique is called diffraction tomography. While many implementations of projection tomography are available today, there is no publicly available implementation of diffraction tomography so far. We present a Python library that implements the backpropagation algorithm for diffraction tomography in 3D. By establishing benchmarks based on finite-difference time-domain (FDTD) simulations, we showcase the superiority of the backpropagation algorithm over the backprojection algorithm. Furthermore, we discuss how measurment parameters influence the reconstructed refractive index distribution and we also give insights into the applicability of diffraction tomography to biological cells. The present software library contains a robust implementation of the backpropagation algorithm. The algorithm is ideally suited for the application to biological cells. Furthermore, the implementation is a drop-in replacement for the classical backprojection algorithm and is made available to the large user community of the Python programming language.

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.

MR-Tandem: parallel X!Tandem using Hadoop MapReduce on Amazon Web Services

PubMed Central

Pratt, Brian; Howbert, J. Jeffry; Tasman, Natalie I.; Nilsson, Erik J.

2012-01-01

Summary: MR-Tandem adapts the popular X!Tandem peptide search engine to work with Hadoop MapReduce for reliable parallel execution of large searches. MR-Tandem runs on any Hadoop cluster but offers special support for Amazon Web Services for creating inexpensive on-demand Hadoop clusters, enabling search volumes that might not otherwise be feasible with the compute resources a researcher has at hand. MR-Tandem is designed to drop in wherever X!Tandem is already in use and requires no modification to existing X!Tandem parameter files, and only minimal modification to X!Tandem-based workflows. Availability and implementation: MR-Tandem is implemented as a lightly modified X!Tandem C++ executable and a Python script that drives Hadoop clusters including Amazon Web Services (AWS) Elastic Map Reduce (EMR), using the modified X!Tandem program as a Hadoop Streaming mapper and reducer. The modified X!Tandem C++ source code is Artistic licensed, supports pluggable scoring, and is available as part of the Sashimi project at http://sashimi.svn.sourceforge.net/viewvc/sashimi/trunk/trans_proteomic_pipeline/extern/xtandem/. The MR-Tandem Python script is Apache licensed and available as part of the Insilicos Cloud Army project at http://ica.svn.sourceforge.net/viewvc/ica/trunk/mr-tandem/. Full documentation and a windows installer that configures MR-Tandem, Python and all necessary packages are available at this same URL. Contact: brian.pratt@insilicos.com PMID:22072385

PyMVPA: A Unifying Approach to the Analysis of Neuroscientific Data

PubMed Central

Hanke, Michael; Halchenko, Yaroslav O.; Sederberg, Per B.; Olivetti, Emanuele; Fründ, Ingo; Rieger, Jochem W.; Herrmann, Christoph S.; Haxby, James V.; Hanson, Stephen José; Pollmann, Stefan

2008-01-01

The Python programming language is steadily increasing in popularity as the language of choice for scientific computing. The ability of this scripting environment to access a huge code base in various languages, combined with its syntactical simplicity, make it the ideal tool for implementing and sharing ideas among scientists from numerous fields and with heterogeneous methodological backgrounds. The recent rise of reciprocal interest between the machine learning (ML) and neuroscience communities is an example of the desire for an inter-disciplinary transfer of computational methods that can benefit from a Python-based framework. For many years, a large fraction of both research communities have addressed, almost independently, very high-dimensional problems with almost completely non-overlapping methods. However, a number of recently published studies that applied ML methods to neuroscience research questions attracted a lot of attention from researchers from both fields, as well as the general public, and showed that this approach can provide novel and fruitful insights into the functioning of the brain. In this article we show how PyMVPA, a specialized Python framework for machine learning based data analysis, can help to facilitate this inter-disciplinary technology transfer by providing a single interface to a wide array of machine learning libraries and neural data-processing methods. We demonstrate the general applicability and power of PyMVPA via analyses of a number of neural data modalities, including fMRI, EEG, MEG, and extracellular recordings. PMID:19212459

A JavaScript API for the Ice Sheet System Model (ISSM) 4.11: towards an online interactive model for the cryosphere community

NASA Astrophysics Data System (ADS)

Larour, Eric; Cheng, Daniel; Perez, Gilberto; Quinn, Justin; Morlighem, Mathieu; Duong, Bao; Nguyen, Lan; Petrie, Kit; Harounian, Silva; Halkides, Daria; Hayes, Wayne

2017-12-01

Earth system models (ESMs) are becoming increasingly complex, requiring extensive knowledge and experience to deploy and use in an efficient manner. They run on high-performance architectures that are significantly different from the everyday environments that scientists use to pre- and post-process results (i.e., MATLAB, Python). This results in models that are hard to use for non-specialists and are increasingly specific in their application. It also makes them relatively inaccessible to the wider science community, not to mention to the general public. Here, we present a new software/model paradigm that attempts to bridge the gap between the science community and the complexity of ESMs by developing a new JavaScript application program interface (API) for the Ice Sheet System Model (ISSM). The aforementioned API allows cryosphere scientists to run ISSM on the client side of a web page within the JavaScript environment. When combined with a web server running ISSM (using a Python API), it enables the serving of ISSM computations in an easy and straightforward way. The deep integration and similarities between all the APIs in ISSM (MATLAB, Python, and now JavaScript) significantly shortens and simplifies the turnaround of state-of-the-art science runs and their use by the larger community. We demonstrate our approach via a new Virtual Earth System Laboratory (VESL) website (http://vesl.jpl.nasa.gov, VESL(2017)).

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

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.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Spotz, William F.

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

Results from the 2010 Feb 14 and July 4 Pluto Occultations

NASA Astrophysics Data System (ADS)

Young, Leslie; Sicardy, B.; Widemann, T.; Brucker, M. J.; Buie, M. W.; Fraser, B.; Van Heerden, H.; Howell, R. R.; Lonergan, K.; Olkin, C. B.; Reitsema, H. J.; Richter, A.; Sepersky, T.; Wasserman, L. H.; Young, E. F.

2010-10-01

The Portable High-speed Occultation Telescope (PHOT) group observed two occultations by Pluto in 2010. The first, of a I=9.3 magnitudue star on 2010 Feb 14, was organized by the Meudon occultation group, with the PHOT group as collaborators. For this bright but low-elevation event, we deployed to three sites in Europe: Obs. Haute Provence, France (0.8-m; L. Young, H. Reitsema), Leopold Figl, Austria (1.5-m; E. Young), and Apline Astrovillage, Lu, Switzerland (0.36-m; C. Olkin, L. Wasserman). We obtained a lightcurve at Lu under clear conditions, which will be combined with two other lightcurves from the Meudon group, from Sisteron and Pic du Midi, France. We observed the second Pluto occultation, of a I=13.2 star on 2010 July 4 UT, from four sites in South Africa: with our portable telescope near Upington (0.36-m; M. Buie, L. Wasserman), the Boyden telescope in Bloemfontein (1.5-m; L. Young, M. Brucker), the Innes telescope in Johannesburg (0.67-m; T. Sepersky, B. Fraser), and the telescope at Aloe Ridge north of Johannesburg (0.62-m; R. Howell, K. Lonergan, A. Richter). Upington was cloudy, Boyden had heavy scattered clouds, and Innes suffered from haze and telescope mechanical problems. A lightcurve was obtained from Aloe Ridge under clear conditions. Data was also obtained by Karl-Ludwig Bath & Thomas Sauer at Hakos, Namibia and by Berto Monard of ASSA near Pretoria, South Africa. The length of the Aloe Ridge chord suggests it is nearly central. These observations give us four contiguous years in which we observed one or more Pluto occultations, providing constraints on the seasonal evolution of Pluto's atmosphere. Thanks are due to Marcelo Assafin and Jim Elliot for sharing predictions prior to the July event. This work was supported, in part, by NASA PAST NNX08A062G.

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

USGS Publications Warehouse

Reed, Robert N.; Rodda, Gordon H.

2009-01-01

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

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

PubMed

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

2010-01-01

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

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.

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

PubMed

Siuda, Krzysztof; Nowak, Magdalena; Kedryna, Mariusz

2004-01-01

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

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.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Grote, D. P.

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

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.

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.

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.

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

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.

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.

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

PubMed

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

2011-01-01

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

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.

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

Automated generation of lattice QCD Feynman rules

NASA Astrophysics Data System (ADS)

Hart, A.; von Hippel, G. M.; Horgan, R. R.; Müller, E. H.

2009-12-01

The derivation of the Feynman rules for lattice perturbation theory from actions and operators is complicated, especially for highly improved actions such as HISQ. This task is, however, both important and particularly suitable for automation. We describe a suite of software to generate and evaluate Feynman rules for a wide range of lattice field theories with gluons and (relativistic and/or heavy) quarks. Our programs are capable of dealing with actions as complicated as (m)NRQCD and HISQ. Automated differentiation methods are used to calculate also the derivatives of Feynman diagrams. Program summaryProgram title: HiPPY, HPsrc Catalogue identifier: AEDX_v1_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/AEDX_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: GPLv2 (see Additional comments below) No. of lines in distributed program, including test data, etc.: 513 426 No. of bytes in distributed program, including test data, etc.: 4 893 707 Distribution format: tar.gz Programming language: Python, Fortran95 Computer: HiPPy: Single-processor workstations. HPsrc: Single-processor workstations and MPI-enabled multi-processor systems Operating system: HiPPy: Any for which Python v2.5.x is available. HPsrc: Any for which a standards-compliant Fortran95 compiler is available Has the code been vectorised or parallelised?: Yes RAM: Problem specific, typically less than 1 GB for either code Classification: 4.4, 11.5 Nature of problem: Derivation and use of perturbative Feynman rules for complicated lattice QCD actions. Solution method: An automated expansion method implemented in Python (HiPPy) and code to use expansions to generate Feynman rules in Fortran95 (HPsrc). Restrictions: No general restrictions. Specific restrictions are discussed in the text. Additional comments: The HiPPy and HPsrc codes are released under the second version of the GNU General Public Licence (GPL v2). Therefore anyone is free to use or modify the code for their own calculations. As part of the licensing, we ask that any publications including results from the use of this code or of modifications of it cite Refs. [1,2] as well as this paper. Finally, we also ask that details of these publications, as well as of any bugs or required or useful improvements of this core code, would be communicated to us. Running time: Very problem specific, depending on the complexity of the Feynman rules and the number of integration points. Typically between a few minutes and several weeks. The installation tests provided with the program code take only a few seconds to run. References:A. Hart, G.M. von Hippel, R.R. Horgan, L.C. Storoni, Automatically generating Feynman rules for improved lattice eld theories, J. Comput. Phys. 209 (2005) 340-353, doi:10.1016/j.jcp.2005.03.010, arXiv:hep-lat/0411026. M. Lüscher, P. Weisz, Efficient Numerical Techniques for Perturbative Lattice Gauge Theory Computations, Nucl. Phys. B 266 (1986) 309, doi:10.1016/0550-3213(86)90094-5.

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

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.

PyCCF: Python Cross Correlation Function for reverberation mapping studies

NASA Astrophysics Data System (ADS)

Sun, Mouyuan; Grier, C. J.; Peterson, B. M.

2018-05-01

PyCCF emulates a Fortran program written by B. Peterson for use with reverberation mapping. The code cross correlates two light curves that are unevenly sampled using linear interpolation and measures the peak and centroid of the cross-correlation function. In addition, it is possible to run Monto Carlo iterations using flux randomization and random subset selection (RSS) to produce cross-correlation centroid distributions to estimate the uncertainties in the cross correlation results.

A Case Study of Human-in-the-loop for Telescope Operation

DTIC Science & Technology

2014-08-22

comply with a collection of information if it does not display a currently valid OMB control number. 1. REPORT DATE (DD-MM-YY) 2. REPORT TYPE 3...preferred commercial camera control software; required for autofocus and advanced mount model configuration) • Dome control – custom Python program...his overnight telescope shifts. He was essentially self-taught using his personally owned telescope that was a different model from the AFIT

MYRaf: A new Approach with IRAF for Astronomical Photometric Reduction

NASA Astrophysics Data System (ADS)

Kilic, Y.; Shameoni Niaei, M.; Özeren, F. F.; Yesilyaprak, C.

2016-12-01

In this study, the design and some developments of MYRaf software for astronomical photometric reduction are presented. MYRaf software is an easy to use, reliable, and has a fast IRAF aperture photometry GUI tools. MYRaf software is an important step for the automated software process of robotic telescopes, and uses IRAF, PyRAF, matplotlib, ginga, alipy, and Sextractor with the general-purpose and high-level programming language Python and uses the QT framework.

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

Guided Tour of Pythonian Museum

NASA Technical Reports Server (NTRS)

Lee, H. Joe

2017-01-01

At http:hdfeos.orgzoo, we have a large collection of Python examples of dealing with NASA HDF (Hierarchical Data Format) products. During this hands-on Python tutorial session, we'll present a few common hacks to access and visualize local NASA HDF data. We'll also cover how to access remote data served by OPeNDAP (Open-source Project for a Network Data Access Protocol). As a glue language, we will demonstrate how you can use Python for your data workflow - from searching data to analyzing data with machine learning.

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.

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

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

Graphical programming interface: A development environment for MRI methods.

PubMed

Zwart, Nicholas R; Pipe, James G

2015-11-01

To introduce a multiplatform, Python language-based, development environment called graphical programming interface for prototyping MRI techniques. The interface allows developers to interact with their scientific algorithm prototypes visually in an event-driven environment making tasks such as parameterization, algorithm testing, data manipulation, and visualization an integrated part of the work-flow. Algorithm developers extend the built-in functionality through simple code interfaces designed to facilitate rapid implementation. This article shows several examples of algorithms developed in graphical programming interface including the non-Cartesian MR reconstruction algorithms for PROPELLER and spiral as well as spin simulation and trajectory visualization of a FLORET example. The graphical programming interface framework is shown to be a versatile prototyping environment for developing numeric algorithms used in the latest MR techniques. © 2014 Wiley Periodicals, Inc.

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

PubMed

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

2015-12-01

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

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.