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.

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

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.

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

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/".

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

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

DTIC Science & Technology

2017-01-01

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

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

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

Simple proteomics data analysis in the object-oriented PowerShell.

PubMed

Mohammed, Yassene; Palmblad, Magnus

2013-01-01

Scripting languages such as Perl and Python are appreciated for solving simple, everyday tasks in bioinformatics. A more recent, object-oriented command shell and scripting language, Windows PowerShell, has many attractive features: an object-oriented interactive command line, fluent navigation and manipulation of XML files, ability to consume Web services from the command line, consistent syntax and grammar, rich regular expressions, and advanced output formatting. The key difference between classical command shells and scripting languages, such as bash, and object-oriented ones, such as PowerShell, is that in the latter the result of a command is a structured object with inherited properties and methods rather than a simple stream of characters. Conveniently, PowerShell is included in all new releases of Microsoft Windows and therefore already installed on most computers in classrooms and teaching labs. In this chapter we demonstrate how PowerShell in particular allows easy interaction with mass spectrometry data in XML formats, connection to Web services for tools such as BLAST, and presentation of results as formatted text or graphics. These features make PowerShell much more than "yet another scripting language."

PyCMSXiO: an external interface to script treatment plans for the Elekta® CMS XiO treatment planning system

NASA Astrophysics Data System (ADS)

Xing, Aitang; Arumugam, Sankar; Holloway, Lois; Goozee, Gary

2014-03-01

Scripting in radiotherapy treatment planning systems not only simplifies routine planning tasks but can also be used for clinical research. Treatment planning scripting can only be utilized in a system that has a built-in scripting interface. Among the commercially available treatment planning systems, Pinnacle (Philips) and Raystation (Raysearch Lab.) have inherent scripting functionality. CMS XiO (Elekta) is a widely used treatment planning system in radiotherapy centres around the world, but it does not have an interface that allows the user to script radiotherapy plans. In this study an external scripting interface, PyCMSXiO, was developed for XiO using the Python programming language. The interface was implemented as a python package/library using a modern object-oriented programming methodology. The package was organized as a hierarchy of different classes (objects). Each class (object) corresponds to a plan object such as the beam of a clinical radiotherapy plan. The interface of classes was implemented as object functions. Scripting in XiO using PyCMSXiO is comparable with Pinnacle scripting. This scripting package has been used in several research projects including commissioning of a beam model, independent three-dimensional dose verification for IMRT plans and a setup-uncertainty study. Ease of use and high-level functions provided in the package achieve a useful research tool. It was released as an open-source tool that may benefit the medical physics community.

Software Assurance Measurement -- State of the Practice

DTIC Science & Technology

2013-11-01

quality and productivity. 30+ languages, C/C++, Java , .NET, Oracle, PeopleSoft, SAP, Siebel, Spring, Struts, Hibernate , and all major databases. ChecKing...NET 39 ActionScript 39 Ada 40 C/C++ 40 Java 41 JavaScript 42 Objective-C 42 Opa 42 Packages 42 Perl 42 PHP 42 Python 42 Formal Methods...Suite—A tool for Ada, C, C++, C#, and Java code that comprises various analyses such as architecture checking, interface analyses, and clone detection

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.

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.

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

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.

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.

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.

Lessons learned: the switch from VMS to UNIX operations for the STScI's Science and Mission Scheduling Branch

NASA Astrophysics Data System (ADS)

Adler, David S.; Workman, William M., III; Chance, Don

2004-09-01

The Science and Mission Scheduling Branch (SMSB) of the Space Telescope Science Institute (STScI) historically operated exclusively under VMS. Due to diminished support for VMS-based platforms at STScI, SMSB recently transitioned to Unix operations. No additional resources were available to the group; the project was SMSB's to design, develop, and implement. Early decisions included the choice of Python as the primary scripting language; adoption of Object-Oriented Design in the development of base utilities; and the development of a Python utility to interact directly with the Sybase database. The project was completed in January 2004 with the implementation of a GUI to generate the Command Loads that are uplinked to HST. The current tool suite consists of 31 utilities and 271 tools comprising over 60,000 lines of code. In this paper, we summarize the decision-making process used to determine the primary scripting language, database interface, and code management library. We also describe the finished product and summarize lessons learned along the way to completing the project.

On the design of script languages for neural simulation.

PubMed

Brette, Romain

2012-01-01

In neural network simulators, models are specified according to a language, either specific or based on a general programming language (e.g. Python). There are also ongoing efforts to develop standardized languages, for example NeuroML. When designing these languages, efforts are often focused on expressivity, that is, on maximizing the number of model types than can be described and simulated. I argue that a complementary goal should be to minimize the cognitive effort required on the part of the user to use the language. I try to formalize this notion with the concept of "language entropy", and I propose a few practical guidelines to minimize the entropy of languages for neural simulation.

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

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.

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.

PyRosetta: a script-based interface for implementing molecular modeling algorithms using Rosetta.

PubMed

Chaudhury, Sidhartha; Lyskov, Sergey; Gray, Jeffrey J

2010-03-01

PyRosetta is a stand-alone Python-based implementation of the Rosetta molecular modeling package that allows users to write custom structure prediction and design algorithms using the major Rosetta sampling and scoring functions. PyRosetta contains Python bindings to libraries that define Rosetta functions including those for accessing and manipulating protein structure, calculating energies and running Monte Carlo-based simulations. PyRosetta can be used in two ways: (i) interactively, using iPython and (ii) script-based, using Python scripting. Interactive mode contains a number of help features and is ideal for beginners while script-mode is best suited for algorithm development. PyRosetta has similar computational performance to Rosetta, can be easily scaled up for cluster applications and has been implemented for algorithms demonstrating protein docking, protein folding, loop modeling and design. PyRosetta is a stand-alone package available at http://www.pyrosetta.org under the Rosetta license which is free for academic and non-profit users. A tutorial, user's manual and sample scripts demonstrating usage are also available on the web site.

PyRosetta: a script-based interface for implementing molecular modeling algorithms using Rosetta

PubMed Central

Chaudhury, Sidhartha; Lyskov, Sergey; Gray, Jeffrey J.

2010-01-01

Summary: PyRosetta is a stand-alone Python-based implementation of the Rosetta molecular modeling package that allows users to write custom structure prediction and design algorithms using the major Rosetta sampling and scoring functions. PyRosetta contains Python bindings to libraries that define Rosetta functions including those for accessing and manipulating protein structure, calculating energies and running Monte Carlo-based simulations. PyRosetta can be used in two ways: (i) interactively, using iPython and (ii) script-based, using Python scripting. Interactive mode contains a number of help features and is ideal for beginners while script-mode is best suited for algorithm development. PyRosetta has similar computational performance to Rosetta, can be easily scaled up for cluster applications and has been implemented for algorithms demonstrating protein docking, protein folding, loop modeling and design. Availability: PyRosetta is a stand-alone package available at http://www.pyrosetta.org under the Rosetta license which is free for academic and non-profit users. A tutorial, user's manual and sample scripts demonstrating usage are also available on the web site. Contact: pyrosetta@graylab.jhu.edu PMID:20061306

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.

Lightweight computational steering of very large scale molecular dynamics simulations

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

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

1996-09-01

We present a computational steering approach for controlling, analyzing, and visualizing very large scale molecular dynamics simulations involving tens to hundreds of millions of atoms. Our approach relies on extensible scripting languages and an easy to use tool for building extensions and modules. The system is extremely easy to modify, works with existing C code, is memory efficient, and can be used from inexpensive workstations and networks. We demonstrate how we have used this system to manipulate data from production MD simulations involving as many as 104 million atoms running on the CM-5 and Cray T3D. We also show howmore » this approach can be used to build systems that integrate common scripting languages (including Tcl/Tk, Perl, and Python), simulation code, user extensions, and commercial data analysis packages.« less

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.

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

TH-D-BRB-04: Pinnacle Scripting: Improving Efficiency While Maintaining Safety

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

Moore, J.

2016-06-15

Scripting capabilities and application programming interfaces (APIs) are becoming commonly available in modern treatment planning systems. These links to the treatment planning system (TPS) allow users to read data from the TPS, and in some cases use TPS functionality and write data back to the TPS. Such tools are powerful extensions, allowing automation of routine clinical tasks and supporting research, particularly research involving repetitive tasks on large patient populations. The data and functionality exposed by scripting/API capabilities is vendor dependent, as are the languages used by script/API engines, such as the Microsoft .NET framework or Python. Scripts deployed in amore » clinical environment must be commissioned and validated like any other software tool. This session will provide an overview of scripting applications and a discussion of best practices, followed by a practical introduction to the scripting capabilities of three commercial treatment planning systems. Learning Objectives: Understand the scripting capabilities available in several treatment planning systems Learn how to get started using scripting capabilities Understand the best practices for safe script deployment in a clinical environment R. Popple, Varian Medical Systems has provided research support unrelated to the topic of this session.R. Cardan, Varian Medical Systems for grant research, product evaluation, and teaching honorarium.« less

A Survey of Visualization Tools Assessed for Anomaly-Based Intrusion Detection Analysis

DTIC Science & Technology

2014-04-01

objective? • What vulnerabilities exist in the target system? • What damage or other consequences are likely? • What exploit scripts or other attack...languages C, R, and Python; no response capabilities. JUNG https://blogs.reucon.com/asterisk- java /tag/visualization/ Create custom layouts and can...annotate graphs, links, nodes with any Java data type. Must be familiar with coding in Java to call the routines; no monitoring or response

Visualization Software for VisIT Java Client

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

Billings, Jay Jay; Smith, Robert W

The VisIT Java Client (JVC) library is a lightweight thin client that is designed and written purely in the native language of Java (the Python & JavaScript versions of the library use the same concept) and communicates with any new unmodified standalone version of VisIT, a high performance computing parallel visualization toolkit, over traditional or web sockets and dynamically determines capabilities of the running VisIT instance whether local or remote.

A modeling paradigm for interdisciplinary water resources modeling: Simple Script Wrappers (SSW)

NASA Astrophysics Data System (ADS)

Steward, David R.; Bulatewicz, Tom; Aistrup, Joseph A.; Andresen, Daniel; Bernard, Eric A.; Kulcsar, Laszlo; Peterson, Jeffrey M.; Staggenborg, Scott A.; Welch, Stephen M.

2014-05-01

Holistic understanding of a water resources system requires tools capable of model integration. This team has developed an adaptation of the OpenMI (Open Modelling Interface) that allows easy interactions across the data passed between models. Capabilities have been developed to allow programs written in common languages such as matlab, python and scilab to share their data with other programs and accept other program's data. We call this interface the Simple Script Wrapper (SSW). An implementation of SSW is shown that integrates groundwater, economic, and agricultural models in the High Plains region of Kansas. Output from these models illustrates the interdisciplinary discovery facilitated through use of SSW implemented models. Reference: Bulatewicz, T., A. Allen, J.M. Peterson, S. Staggenborg, S.M. Welch, and D.R. Steward, The Simple Script Wrapper for OpenMI: Enabling interdisciplinary modeling studies, Environmental Modelling & Software, 39, 283-294, 2013. http://dx.doi.org/10.1016/j.envsoft.2012.07.006 http://code.google.com/p/simple-script-wrapper/

The Earth Data Analytic Services (EDAS) Framework

NASA Astrophysics Data System (ADS)

Maxwell, T. P.; Duffy, D.

2017-12-01

Faced with unprecedented growth in earth data volume and demand, NASA has developed the Earth Data Analytic Services (EDAS) framework, a high performance big data analytics framework built on Apache Spark. This framework enables scientists to execute data processing workflows combining common analysis operations close to the massive data stores at NASA. The data is accessed in standard (NetCDF, HDF, etc.) formats in a POSIX file system and processed using vetted earth data analysis tools (ESMF, CDAT, NCO, etc.). EDAS utilizes a dynamic caching architecture, a custom distributed array framework, and a streaming parallel in-memory workflow for efficiently processing huge datasets within limited memory spaces with interactive response times. EDAS services are accessed via a WPS API being developed in collaboration with the ESGF Compute Working Team to support server-side analytics for ESGF. The API can be accessed using direct web service calls, a Python script, a Unix-like shell client, or a JavaScript-based web application. New analytic operations can be developed in Python, Java, or Scala (with support for other languages planned). Client packages in Python, Java/Scala, or JavaScript contain everything needed to build and submit EDAS requests. The EDAS architecture brings together the tools, data storage, and high-performance computing required for timely analysis of large-scale data sets, where the data resides, to ultimately produce societal benefits. It is is currently deployed at NASA in support of the Collaborative REAnalysis Technical Environment (CREATE) project, which centralizes numerous global reanalysis datasets onto a single advanced data analytics platform. This service enables decision makers to compare multiple reanalysis datasets and investigate trends, variability, and anomalies in earth system dynamics around the globe.

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.

Early Market Site Identification Data

DOE Data Explorer

Levi Kilcher

2016-04-01

This data was compiled for the 'Early Market Opportunity Hot Spot Identification' project. The data and scripts included were used in the 'MHK Energy Site Identification and Ranking Methodology' Reports (Part I: Wave, NREL Report #66038; Part II: Tidal, NREL Report #66079). The Python scripts will generate a set of results--based on the Excel data files--some of which were described in the reports. The scripts depend on the 'score_site' package, and the score site package depends on a number of standard Python libraries (see the score_site install instructions).

The GBT Dynamic Scheduling System: Powered by the Web

NASA Astrophysics Data System (ADS)

Marganian, P.; Clark, M.; McCarty, M.; Sessoms, E.; Shelton, A.

2009-09-01

The web technologies utilized for the Robert C. Byrd Green Bank Telescope's (GBT) new Dynamic Scheduling System are discussed, focusing on languages, frameworks, and tools. We use a popular Python web framework, TurboGears, to take advantage of the extensive web services the system provides. TurboGears is a model-view-controller framework, which aggregates SQLAlchemy, Genshi, and CherryPy respectively. On top of this framework, Javascript (Prototype, script.aculo.us, and JQuery) and cascading style sheets (Blueprint) are used for desktop-quality web pages.

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.

New Python-based methods for data processing

PubMed Central

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

2013-01-01

Current pixel-array detectors produce diffraction images at extreme data rates (of up to 2 TB h−1) that make severe demands on computational resources. New multiprocessing frameworks are required to achieve rapid data analysis, as it is important to be able to inspect the data quickly in order to guide the experiment in real time. By utilizing readily available web-serving tools that interact with the Python scripting language, it was possible to implement a high-throughput Bragg-spot analyzer (cctbx.spotfinder) that is presently in use at numerous synchrotron-radiation beamlines. Similarly, Python interoperability enabled the production of a new data-reduction package (cctbx.xfel) for serial femto­second crystallography experiments at the Linac Coherent Light Source (LCLS). Future data-reduction efforts will need to focus on specialized problems such as the treatment of diffraction spots on interleaved lattices arising from multi-crystal specimens. In these challenging cases, accurate modeling of close-lying Bragg spots could benefit from the high-performance computing capabilities of graphics-processing units. PMID:23793153

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.

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.

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.

Automatically visualise and analyse data on pathways using PathVisioRPC from any programming environment.

PubMed

Bohler, Anwesha; Eijssen, Lars M T; van Iersel, Martijn P; Leemans, Christ; Willighagen, Egon L; Kutmon, Martina; Jaillard, Magali; Evelo, Chris T

2015-08-23

Biological pathways are descriptive diagrams of biological processes widely used for functional analysis of differentially expressed genes or proteins. Primary data analysis, such as quality control, normalisation, and statistical analysis, is often performed in scripting languages like R, Perl, and Python. Subsequent pathway analysis is usually performed using dedicated external applications. Workflows involving manual use of multiple environments are time consuming and error prone. Therefore, tools are needed that enable pathway analysis directly within the same scripting languages used for primary data analyses. Existing tools have limited capability in terms of available pathway content, pathway editing and visualisation options, and export file formats. Consequently, making the full-fledged pathway analysis tool PathVisio available from various scripting languages will benefit researchers. We developed PathVisioRPC, an XMLRPC interface for the pathway analysis software PathVisio. PathVisioRPC enables creating and editing biological pathways, visualising data on pathways, performing pathway statistics, and exporting results in several image formats in multiple programming environments. We demonstrate PathVisioRPC functionalities using examples in Python. Subsequently, we analyse a publicly available NCBI GEO gene expression dataset studying tumour bearing mice treated with cyclophosphamide in R. The R scripts demonstrate how calls to existing R packages for data processing and calls to PathVisioRPC can directly work together. To further support R users, we have created RPathVisio simplifying the use of PathVisioRPC in this environment. We have also created a pathway module for the microarray data analysis portal ArrayAnalysis.org that calls the PathVisioRPC interface to perform pathway analysis. This module allows users to use PathVisio functionality online without having to download and install the software and exemplifies how the PathVisioRPC interface can be used by data analysis pipelines for functional analysis of processed genomics data. PathVisioRPC enables data visualisation and pathway analysis directly from within various analytical environments used for preliminary analyses. It supports the use of existing pathways from WikiPathways or pathways created using the RPC itself. It also enables automation of tasks performed using PathVisio, making it useful to PathVisio users performing repeated visualisation and analysis tasks. PathVisioRPC is freely available for academic and commercial use at http://projects.bigcat.unimaas.nl/pathvisiorpc.

Proteomics to go: Proteomatic enables the user-friendly creation of versatile MS/MS data evaluation workflows.

PubMed

Specht, Michael; Kuhlgert, Sebastian; Fufezan, Christian; Hippler, Michael

2011-04-15

We present Proteomatic, an operating system independent and user-friendly platform that enables the construction and execution of MS/MS data evaluation pipelines using free and commercial software. Required external programs such as for peptide identification are downloaded automatically in the case of free software. Due to a strict separation of functionality and presentation, and support for multiple scripting languages, new processing steps can be added easily. Proteomatic is implemented in C++/Qt, scripts are implemented in Ruby, Python and PHP. All source code is released under the LGPL. Source code and installers for Windows, Mac OS X, and Linux are freely available at http://www.proteomatic.org. michael.specht@uni-muenster.de Supplementary data are available at Bioinformatics online.

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.

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

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.

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.

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

Rapid development of image analysis research tools: Bridging the gap between researcher and clinician with pyOsiriX.

PubMed

Blackledge, Matthew D; Collins, David J; Koh, Dow-Mu; Leach, Martin O

2016-02-01

We present pyOsiriX, a plugin built for the already popular dicom viewer OsiriX that provides users the ability to extend the functionality of OsiriX through simple Python scripts. This approach allows users to integrate the many cutting-edge scientific/image-processing libraries created for Python into a powerful DICOM visualisation package that is intuitive to use and already familiar to many clinical researchers. Using pyOsiriX we hope to bridge the apparent gap between basic imaging scientists and clinical practice in a research setting and thus accelerate the development of advanced clinical image processing. We provide arguments for the use of Python as a robust scripting language for incorporation into larger software solutions, outline the structure of pyOsiriX and how it may be used to extend the functionality of OsiriX, and we provide three case studies that exemplify its utility. For our first case study we use pyOsiriX to provide a tool for smooth histogram display of voxel values within a user-defined region of interest (ROI) in OsiriX. We used a kernel density estimation (KDE) method available in Python using the scikit-learn library, where the total number of lines of Python code required to generate this tool was 22. Our second example presents a scheme for segmentation of the skeleton from CT datasets. We have demonstrated that good segmentation can be achieved for two example CT studies by using a combination of Python libraries including scikit-learn, scikit-image, SimpleITK and matplotlib. Furthermore, this segmentation method was incorporated into an automatic analysis of quantitative PET-CT in a patient with bone metastases from primary prostate cancer. This enabled repeatable statistical evaluation of PET uptake values for each lesion, before and after treatment, providing estaimes maximum and median standardised uptake values (SUVmax and SUVmed respectively). Following treatment we observed a reduction in lesion volume, SUVmax and SUVmed for all lesions, in agreement with a reduction in concurrent measures of serum prostate-specific antigen (PSA). Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

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.

Turning a remotely controllable observatory into a fully autonomous system

NASA Astrophysics Data System (ADS)

Swindell, Scott; Johnson, Chris; Gabor, Paul; Zareba, Grzegorz; Kubánek, Petr; Prouza, Michael

2014-08-01

We describe a complex process needed to turn an existing, old, operational observatory - The Steward Observatory's 61" Kuiper Telescope - into a fully autonomous system, which observers without an observer. For this purpose, we employed RTS2,1 an open sourced, Linux based observatory control system, together with other open sourced programs and tools (GNU compilers, Python language for scripting, JQuery UI for Web user interface). This presentation provides a guide with time estimates needed for a newcomers to the field to handle such challenging tasks, as fully autonomous observatory operations.

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)

Python script for querying a list of web sites and their details from Splunk and dynamically creating tests for monitoring uptime. The data generated from this script is then sent back to Splunk for creating reports and alerts.

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 .

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.

TVB-EduPack—An Interactive Learning and Scripting Platform for The Virtual Brain

PubMed Central

Matzke, Henrik; Schirner, Michael; Vollbrecht, Daniel; Rothmeier, Simon; Llarena, Adalberto; Rojas, Raúl; Triebkorn, Paul; Domide, Lia; Mersmann, Jochen; Solodkin, Ana; Jirsa, Viktor K.; McIntosh, Anthony Randal; Ritter, Petra

2015-01-01

The Virtual Brain (TVB; thevirtualbrain.org) is a neuroinformatics platform for full brain network simulation based on individual anatomical connectivity data. The framework addresses clinical and neuroscientific questions by simulating multi-scale neural dynamics that range from local population activity to large-scale brain function and related macroscopic signals like electroencephalography and functional magnetic resonance imaging. TVB is equipped with a graphical and a command-line interface to create models that capture the characteristic biological variability to predict the brain activity of individual subjects. To enable researchers from various backgrounds a quick start into TVB and brain network modeling in general, we developed an educational module: TVB-EduPack. EduPack offers two educational functionalities that seamlessly integrate into TVB's graphical user interface (GUI): (i) interactive tutorials introduce GUI elements, guide through the basic mechanics of software usage and develop complex use-case scenarios; animations, videos and textual descriptions transport essential principles of computational neuroscience and brain modeling; (ii) an automatic script generator records model parameters and produces input files for TVB's Python programming interface; thereby, simulation configurations can be exported as scripts that allow flexible customization of the modeling process and self-defined batch- and post-processing applications while benefitting from the full power of the Python language and its toolboxes. This article covers the implementation of TVB-EduPack and its integration into TVB architecture. Like TVB, EduPack is an open source community project that lives from the participation and contribution of its users. TVB-EduPack can be obtained as part of TVB from thevirtualbrain.org. PMID:26635597

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.

ORBIT: A Code for Collective Beam Dynamics in High-Intensity Rings

NASA Astrophysics Data System (ADS)

Holmes, J. A.; Danilov, V.; Galambos, J.; Shishlo, A.; Cousineau, S.; Chou, W.; Michelotti, L.; Ostiguy, J.-F.; Wei, J.

2002-12-01

We are developing a computer code, ORBIT, specifically for beam dynamics calculations in high-intensity rings. Our approach allows detailed simulation of realistic accelerator problems. ORBIT is a particle-in-cell tracking code that transports bunches of interacting particles through a series of nodes representing elements, effects, or diagnostics that occur in the accelerator lattice. At present, ORBIT contains detailed models for strip-foil injection, including painting and foil scattering; rf focusing and acceleration; transport through various magnetic elements; longitudinal and transverse impedances; longitudinal, transverse, and three-dimensional space charge forces; collimation and limiting apertures; and the calculation of many useful diagnostic quantities. ORBIT is an object-oriented code, written in C++ and utilizing a scripting interface for the convenience of the user. Ongoing improvements include the addition of a library of accelerator maps, BEAMLINE/MXYZPTLK; the introduction of a treatment of magnet errors and fringe fields; the conversion of the scripting interface to the standard scripting language, Python; and the parallelization of the computations using MPI. The ORBIT code is an open source, powerful, and convenient tool for studying beam dynamics in high-intensity rings.

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

PubMed

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

2015-01-15

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

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

TESP combines existing domain simulators in the electric power grid, with new transactive agents, growth models and evaluation scripts. The existing domain simulators include GridLAB-D for the distribution grid and single-family residential buildings, MATPOWER for transmission and bulk generation, and EnergyPlus for large buildings. More are planned for subsequent versions of TESP. The new elements are: TEAgents - simulate market participants and transactive systems for market clearing. Some of this functionality was extracted from GridLAB-D and implemented in Python for customization by PNNL and others; Growth Model - a means for simulating system changes over a multiyear period, including bothmore » normal load growth and specific investment decisions. Customizable in Python code; and Evaluation Script - a means of evaluating different transactive systems through customizable post-processing in Python code. TESP provides a method for other researchers and vendors to design transactive systems, and test them in a virtual environment. It allows customization of the key components by modifying Python code.« less

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.

SBMLmod: a Python-based web application and web service for efficient data integration and model simulation.

PubMed

Schäuble, Sascha; Stavrum, Anne-Kristin; Bockwoldt, Mathias; Puntervoll, Pål; Heiland, Ines

2017-06-24

Systems Biology Markup Language (SBML) is the standard model representation and description language in systems biology. Enriching and analysing systems biology models by integrating the multitude of available data, increases the predictive power of these models. This may be a daunting task, which commonly requires bioinformatic competence and scripting. We present SBMLmod, a Python-based web application and service, that automates integration of high throughput data into SBML models. Subsequent steady state analysis is readily accessible via the web service COPASIWS. We illustrate the utility of SBMLmod by integrating gene expression data from different healthy tissues as well as from a cancer dataset into a previously published model of mammalian tryptophan metabolism. SBMLmod is a user-friendly platform for model modification and simulation. The web application is available at http://sbmlmod.uit.no , whereas the WSDL definition file for the web service is accessible via http://sbmlmod.uit.no/SBMLmod.wsdl . Furthermore, the entire package can be downloaded from https://github.com/MolecularBioinformatics/sbml-mod-ws . We envision that SBMLmod will make automated model modification and simulation available to a broader research community.

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.

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

McSpaden, Alexander Thomas

Two Python scripts have been written that process the output files of MCNP6 into a format that mimics the list-mode output of Los Alamos National Laboratory’s MC-15 and NPOD neutron detection systems. This report details the methods implemented in these scripts and instructions on their use.

Using OPeNDAP's Data-Services Framework to Lift Mash-Ups above Blind Dates

NASA Astrophysics Data System (ADS)

Gallagher, J. H. R.; Fulker, D. W.

2015-12-01

OPeNDAP's data-as-service framework (Hyrax) matches diverse sources with many end-user tools and contexts. Keys to its flexibility include: A data model embracing tabular data alongside n-dim arrays and other structures useful in geoinformatics. A REST-like protocol that supports—via suffix notation—a growing set of output forms (netCDF, XML, etc.) plus a query syntax for subsetting. Subsetting applies (via constraints on column values) to tabular data or (via constraints on indices or coordinates) to array-style data . A handler-style architecture that admits a growing set of input types. Community members may contribute handlers, making Hyrax effective as middleware, where N sources are mapped to M outputs with order N+M effort (not NxM). Hyrax offers virtual aggregations of source data, enabling granularity aimed at users, not data-collectors. OPeNDAP-access libraries exist in multiple languages, including Python, Java, and C++. Recent enhancements are increasing this framework's interoperability (i.e., its mash-up) potential. Extensions implemented as servlets—running adjacent to Hyrax—are enriching the forms of aggregation and enabling new protocols: User-specified aggregations, namely, applying a query to (huge) lists of source granules, and receiving one (large) table or zipped netCDF file. OGC (Open Geospatial Consortium) protocols, WMS and WCS. A Webification (W10n) protocol that returns JavaScript Object Notation (JSON). Extensions to OPeNDAP's query language are reducing transfer volumes and enabling new forms of inspection. Advances underway include: Functions that, for triangular-mesh sources, return sub-meshes spec'd via geospatial bounding boxes. Functions that, for data from multiple, satellite-borne sensors (with differing orbits), select observations based on coincidence. Calculations of means, histograms, etc. that greatly reduce output volumes.. Paths for communities to contribute new server functions (in Python, e.g.) that data providers may incorporate into Hyrax via installation parameters. One could say Hyrax itself is a mash-up, but we suggest it as an instrument for a mash-up artist's toolbox. This instrument can support mash-ups built on netCDF files, OGC protocols, JavaScript Web pages, and/or programs written in Python, Java, C or C++.

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/.

A new open-source Python-based Space Weather data access, visualization, and analysis toolkit

NASA Astrophysics Data System (ADS)

de Larquier, S.; Ribeiro, A.; Frissell, N. A.; Spaleta, J.; Kunduri, B.; Thomas, E. G.; Ruohoniemi, J.; Baker, J. B.

2013-12-01

Space weather research relies heavily on combining and comparing data from multiple observational platforms. Current frameworks exist to aggregate some of the data sources, most based on file downloads via web or ftp interfaces. Empirical models are mostly fortran based and lack interfaces with more useful scripting languages. In an effort to improve data and model access, the SuperDARN community has been developing a Python-based Space Science Data Visualization Toolkit (DaViTpy). At the center of this development was a redesign of how our data (from 30 years of SuperDARN radars) was made available. Several access solutions are now wrapped into one convenient Python interface which probes local directories, a new remote NoSQL database, and an FTP server to retrieve the requested data based on availability. Motivated by the efficiency of this interface and the inherent need for data from multiple instruments, we implemented similar modules for other space science datasets (POES, OMNI, Kp, AE...), and also included fundamental empirical models with Python interfaces to enhance data analysis (IRI, HWM, MSIS...). All these modules and more are gathered in a single convenient toolkit, which is collaboratively developed and distributed using Github and continues to grow. While still in its early stages, we expect this toolkit will facilitate multi-instrument space weather research and improve scientific productivity.

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.

TriBITS (Tribal Build, Integrate, and Test System)

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

2013-05-16

TriBITS is a configuration, build, test, and reporting system that uses the Kitware open-source CMake/CTest/CDash system. TriBITS contains a number of custom CMake/CTest scripts and python scripts that extend the functionality of the out-of-the-box CMake/CTest/CDash system.

PsychoPy--Psychophysics software in Python.

PubMed

Peirce, Jonathan W

2007-05-15

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

PsychoPy—Psychophysics software in Python

PubMed Central

Peirce, Jonathan W.

2007-01-01

The vast majority of studies into visual processing are conducted using computer display technology. The current paper describes a new free suite of software tools designed to make this task easier, using the latest advances in hardware and software. PsychoPy is a platform-independent experimental control system written in the Python interpreted language using entirely free libraries. PsychoPy scripts are designed to be extremely easy to read and write, while retaining complete power for the user to customize the stimuli and environment. Tools are provided within the package to allow everything from stimulus presentation and response collection (from a wide range of devices) to simple data analysis such as psychometric function fitting. Most importantly, PsychoPy is highly extensible and the whole system can evolve via user contributions. If a user wants to add support for a particular stimulus, analysis or hardware device they can look at the code for existing examples, modify them and submit the modifications back into the package so that the whole community benefits. PMID:17254636

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

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.

Extension Scripts to caffe for Running COWC Data

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

Mundhenk, T. Nathan; Konjevod, Goran; Sakla, Wesam A.

2016-07-14

These are scripts In python whlch extend the functlonallty of the open source software Caffe and allow 1t to scan an overhead scene of Images and detect or count cars from that scene. tt returns the number of cars or the location of cars as a marked scene lmase.

Generating Stimuli for Neuroscience Using PsychoPy.

PubMed

Peirce, Jonathan W

2008-01-01

PsychoPy is a software library written in Python, using OpenGL to generate very precise visual stimuli on standard personal computers. It is designed to allow the construction of as wide a variety of neuroscience experiments as possible, with the least effort. By writing scripts in standard Python syntax users can generate an enormous variety of visual and auditory stimuli and can interact with a wide range of external hardware (enabling its use in fMRI, EEG, MEG etc.). The structure of scripts is simple and intuitive. As a result, new experiments can be written very quickly, and trying to understand a previously written script is easy, even with minimal code comments. PsychoPy can also generate movies and image sequences to be used in demos or simulated neuroscience experiments. This paper describes the range of tools and stimuli that it provides and the environment in which experiments are conducted.

Modules based on the geochemical model PHREEQC for use in scripting and programming languages

USGS Publications Warehouse

Charlton, Scott R.; Parkhurst, David L.

2011-01-01

The geochemical model PHREEQC is capable of simulating a wide range of equilibrium reactions between water and minerals, ion exchangers, surface complexes, solid solutions, and gases. It also has a general kinetic formulation that allows modeling of nonequilibrium mineral dissolution and precipitation, microbial reactions, decomposition of organic compounds, and other kinetic reactions. To facilitate use of these reaction capabilities in scripting languages and other models, PHREEQC has been implemented in modules that easily interface with other software. A Microsoft COM (component object model) has been implemented, which allows PHREEQC to be used by any software that can interface with a COM server—for example, Excel®, Visual Basic®, Python, or MATLAB". PHREEQC has been converted to a C++ class, which can be included in programs written in C++. The class also has been compiled in libraries for Linux and Windows that allow PHREEQC to be called from C++, C, and Fortran. A limited set of methods implements the full reaction capabilities of PHREEQC for each module. Input methods use strings or files to define reaction calculations in exactly the same formats used by PHREEQC. Output methods provide a table of user-selected model results, such as concentrations, activities, saturation indices, and densities. The PHREEQC module can add geochemical reaction capabilities to surface-water, groundwater, and watershed transport models. It is possible to store and manipulate solution compositions and reaction information for many cells within the module. In addition, the object-oriented nature of the PHREEQC modules simplifies implementation of parallel processing for reactive-transport models. The PHREEQC COM module may be used in scripting languages to fit parameters; to plot PHREEQC results for field, laboratory, or theoretical investigations; or to develop new models that include simple or complex geochemical calculations.

Modules based on the geochemical model PHREEQC for use in scripting and programming languages

USGS Publications Warehouse

Charlton, S.R.; Parkhurst, D.L.

2011-01-01

The geochemical model PHREEQC is capable of simulating a wide range of equilibrium reactions between water and minerals, ion exchangers, surface complexes, solid solutions, and gases. It also has a general kinetic formulation that allows modeling of nonequilibrium mineral dissolution and precipitation, microbial reactions, decomposition of organic compounds, and other kinetic reactions. To facilitate use of these reaction capabilities in scripting languages and other models, PHREEQC has been implemented in modules that easily interface with other software. A Microsoft COM (component object model) has been implemented, which allows PHREEQC to be used by any software that can interface with a COM server-for example, Excel??, Visual Basic??, Python, or MATLAB??. PHREEQC has been converted to a C++ class, which can be included in programs written in C++. The class also has been compiled in libraries for Linux and Windows that allow PHREEQC to be called from C++, C, and Fortran. A limited set of methods implements the full reaction capabilities of PHREEQC for each module. Input methods use strings or files to define reaction calculations in exactly the same formats used by PHREEQC. Output methods provide a table of user-selected model results, such as concentrations, activities, saturation indices, and densities. The PHREEQC module can add geochemical reaction capabilities to surface-water, groundwater, and watershed transport models. It is possible to store and manipulate solution compositions and reaction information for many cells within the module. In addition, the object-oriented nature of the PHREEQC modules simplifies implementation of parallel processing for reactive-transport models. The PHREEQC COM module may be used in scripting languages to fit parameters; to plot PHREEQC results for field, laboratory, or theoretical investigations; or to develop new models that include simple or complex geochemical calculations. ?? 2011.

Python to learn programming

NASA Astrophysics Data System (ADS)

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

2013-04-01

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

HESS Opinions: Repeatable research: what hydrologistscan learn from the Duke cancer research scandal

USGS Publications Warehouse

Fienen, Michael; Bakker, Mark

2016-01-01

In the past decade, difficulties encountered in reproducing the results of a cancer study at Duke University resulted in a scandal and an investigation which concluded that tools used for data management, analysis, and modeling were inappropriate for the documentation of the study, let alone the reproduction of the results. New protocols were developed which require that data analysis and modeling be carried out with scripts that can be used to reproduce the results and are a record of all decisions and interpretations made during an analysis or a modeling effort. In the hydrological sciences, we face similar challenges and need to develop similar standards for transparency and repeatability of results. A promising route is to start making use of open-source languages (such as R and Python) to write scripts and to use collaborative coding environments (such as Git) to share our codes for inspection and use by the hydrological community. An important side-benefit to adopting such protocols is consistency and efficiency among collaborators.

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)).

ParaView visualization of Abaqus output on the mechanical deformation of complex microstructures

NASA Astrophysics Data System (ADS)

Liu, Qingbin; Li, Jiang; Liu, Jie

2017-02-01

Abaqus® is a popular software suite for finite element analysis. It delivers linear and nonlinear analyses of mechanical and fluid dynamics, includes multi-body system and multi-physics coupling. However, the visualization capability of Abaqus using its CAE module is limited. Models from microtomography have extremely complicated structures, and datasets of Abaqus output are huge, requiring a visualization tool more powerful than Abaqus/CAE. We convert Abaqus output into the XML-based VTK format by developing a Python script and then using ParaView to visualize the results. Such capabilities as volume rendering, tensor glyphs, superior animation and other filters allow ParaView to offer excellent visualizing manifestations. ParaView's parallel visualization makes it possible to visualize very big data. To support full parallel visualization, the Python script achieves data partitioning by reorganizing all nodes, elements and the corresponding results on those nodes and elements. The data partition scheme minimizes data redundancy and works efficiently. Given its good readability and extendibility, the script can be extended to the processing of more different problems in Abaqus. We share the script with Abaqus users on GitHub.

Data Provenance as a Tool for Debugging Hydrological Models based on Python

NASA Astrophysics Data System (ADS)

Wombacher, A.; Huq, M.; Wada, Y.; Van Beek, R.

2012-12-01

There is an increase in data volume used in hydrological modeling. The increasing data volume requires additional efforts in debugging models since a single output value is influenced by a multitude of input values. Thus, it is difficult to keep an overview among the data dependencies. Further, knowing these dependencies, it is a tedious job to infer all the relevant data values. The aforementioned data dependencies are also known as data provenance, i.e. the determination of how a particular value has been created and processed. The proposed tool infers the data provenance automatically from a python script and visualizes the dependencies as a graph without executing the script. To debug the model the user specifies the value of interest in space and time. The tool infers all related data values and displays them in the graph. The tool has been evaluated by hydrologists developing a model for estimating the global water demand [1]. The model uses multiple different data sources. The script we analysed has 120 lines of codes and used more than 3000 individual files, each of them representing a raster map of 360*720 cells. After importing the data of the files into a SQLite database, the data consumes around 40 GB of memory. Using the proposed tool a modeler is able to select individual values and infer which values have been used to calculate the value. Especially in cases of outliers or missing values it is a beneficial tool to provide the modeler with efficient information to investigate the unexpected behavior of the model. The proposed tool can be applied to many python scripts and has been tested with other scripts in different contexts. In case a python code contains an unknown function or class the tool requests additional information about the used function or class to enable the inference. This information has to be entered only once and can be shared with colleagues or in the community. Reference [1] Y. Wada, L. P. H. van Beek, D. Viviroli, H. H. Drr, R. Weingartner, and M. F. P. Bierkens, "Global monthly water stress: II. water demand and severity of water," Water Resources Research, vol. 47, 2011.

An Open-Source Automated Peptide Synthesizer Based on Arduino and Python.

PubMed

Gali, Hariprasad

2017-10-01

The development of the first open-source automated peptide synthesizer, PepSy, using Arduino UNO and readily available components is reported. PepSy was primarily designed to synthesize small peptides in a relatively small scale (<100 µmol). Scripts to operate PepSy in a fully automatic or manual mode were written in Python. Fully automatic script includes functions to carry out resin swelling, resin washing, single coupling, double coupling, Fmoc deprotection, ivDde deprotection, on-resin oxidation, end capping, and amino acid/reagent line cleaning. Several small peptides and peptide conjugates were successfully synthesized on PepSy with reasonably good yields and purity depending on the complexity of the peptide.

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.

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

GNU Data Language (GDL) - a free and open-source implementation of IDL

NASA Astrophysics Data System (ADS)

Arabas, Sylwester; Schellens, Marc; Coulais, Alain; Gales, Joel; Messmer, Peter

2010-05-01

GNU Data Language (GDL) is developed with the aim of providing an open-source drop-in replacement for the ITTVIS's Interactive Data Language (IDL). It is free software developed by an international team of volunteers led by Marc Schellens - the project's founder (a list of contributors is available on the project's website). The development is hosted on SourceForge where GDL continuously ranks in the 99th percentile of most active projects. GDL with its library routines is designed as a tool for numerical data analysis and visualisation. As its proprietary counterparts (IDL and PV-WAVE), GDL is used particularly in geosciences and astronomy. GDL is dynamically-typed, vectorized and has object-oriented programming capabilities. The library routines handle numerical calculations, data visualisation, signal/image processing, interaction with host OS and data input/output. GDL supports several data formats such as netCDF, HDF4, HDF5, GRIB, PNG, TIFF, DICOM, etc. Graphical output is handled by X11, PostScript, SVG or z-buffer terminals, the last one allowing output to be saved in a variety of raster graphics formats. GDL is an incremental compiler with integrated debugging facilities. It is written in C++ using the ANTLR language-recognition framework. Most of the library routines are implemented as interfaces to open-source packages such as GNU Scientific Library, PLPlot, FFTW, ImageMagick, and others. GDL features a Python bridge (Python code can be called from GDL; GDL can be compiled as a Python module). Extensions to GDL can be written in C++, GDL, and Python. A number of open software libraries written in IDL, such as the NASA Astronomy Library, MPFIT, CMSVLIB and TeXtoIDL are fully or partially functional under GDL. Packaged versions of GDL are available for several Linux distributions and Mac OS X. The source code compiles on some other UNIX systems, including BSD and OpenSolaris. The presentation will cover the current status of the project, the key accomplishments, and the weaknesses - areas where contributions and users' feedback are welcome! While still being in beta-stage of development, GDL proved to be a useful tool for classroom work on data analysis. Its usage for teaching meteorological-data processing at the University of Warsaw will serve as an example.

Youpi: A Web-based Astronomical Image Processing Pipeline

NASA Astrophysics Data System (ADS)

Monnerville, M.; Sémah, G.

2010-12-01

Youpi stands for “YOUpi is your processing PIpeline”. It is a portable, easy to use web application providing high level functionalities to perform data reduction on scientific FITS images. It is built on top of open source processing tools that are released to the community by Terapix, in order to organize your data on a computer cluster, to manage your processing jobs in real time and to facilitate teamwork by allowing fine-grain sharing of results and data. On the server side, Youpi is written in the Python programming language and uses the Django web framework. On the client side, Ajax techniques are used along with the Prototype and script.aculo.us Javascript librairies.

FELIX-1.0: A finite element solver for the time dependent generator coordinate method with the Gaussian overlap approximation

NASA Astrophysics Data System (ADS)

Regnier, D.; Verrière, M.; Dubray, N.; Schunck, N.

2016-03-01

We describe the software package FELIX that solves the equations of the time-dependent generator coordinate method (TDGCM) in N-dimensions (N ≥ 1) under the Gaussian overlap approximation. The numerical resolution is based on the Galerkin finite element discretization of the collective space and the Crank-Nicolson scheme for time integration. The TDGCM solver is implemented entirely in C++. Several additional tools written in C++, Python or bash scripting language are also included for convenience. In this paper, the solver is tested with a series of benchmarks calculations. We also demonstrate the ability of our code to handle a realistic calculation of fission dynamics.

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.

Python-based geometry preparation and simulation visualization toolkits for STEPS

PubMed Central

Chen, Weiliang; De Schutter, Erik

2014-01-01

STEPS is a stochastic reaction-diffusion simulation engine that implements a spatial extension of Gillespie's Stochastic Simulation Algorithm (SSA) in complex tetrahedral geometries. An extensive Python-based interface is provided to STEPS so that it can interact with the large number of scientific packages in Python. However, a gap existed between the interfaces of these packages and the STEPS user interface, where supporting toolkits could reduce the amount of scripting required for research projects. This paper introduces two new supporting toolkits that support geometry preparation and visualization for STEPS simulations. PMID:24782754

Python scripting in the nengo simulator.

PubMed

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

2009-01-01

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

Python Scripting in the Nengo Simulator

PubMed Central

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

2008-01-01

Nengo (http://nengo.ca) is an open-source neural simulator that has been greatly enhanced by the recent addition of a Python script interface. Nengo provides a wide range of features that are useful for physiological simulations, including unique features that facilitate development of population-coding models using the neural engineering framework (NEF). This framework uses information theory, signal processing, and control theory to formalize the development of large-scale neural circuit models. Notably, it can also be used to determine the synaptic weights that underlie observed network dynamics and transformations of represented variables. Nengo provides rich NEF support, and includes customizable models of spike generation, muscle dynamics, synaptic plasticity, and synaptic integration, as well as an intuitive graphical user interface. All aspects of Nengo models are accessible via the Python interface, allowing for programmatic creation of models, inspection and modification of neural parameters, and automation of model evaluation. Since Nengo combines Python and Java, it can also be integrated with any existing Java or 100% Python code libraries. Current work includes connecting neural models in Nengo with existing symbolic cognitive models, creating hybrid systems that combine detailed neural models of specific brain regions with higher-level models of remaining brain areas. Such hybrid models can provide (1) more realistic boundary conditions for the neural components, and (2) more realistic sub-components for the larger cognitive models. PMID:19352442

Towards a new Mercator Observatory Control System

NASA Astrophysics Data System (ADS)

Pessemier, W.; Raskin, G.; Prins, S.; Saey, P.; Merges, F.; Padilla, J. P.; Van Winckel, H.; Waelkens, C.

2010-07-01

A new control system is currently being developed for the 1.2-meter Mercator Telescope at the Roque de Los Muchachos Observatory (La Palma, Spain). Formerly based on transputers, the new Mercator Observatory Control System (MOCS) consists of a small network of Linux computers complemented by a central industrial controller and an industrial real-time data communication network. Python is chosen as the high-level language to develop flexible yet powerful supervisory control and data acquisition (SCADA) software for the Linux computers. Specialized applications such as detector control, auto-guiding and middleware management are also integrated in the same Python software package. The industrial controller, on the other hand, is connected to the majority of the field devices and is targeted to run various control loops, some of which are real-time critical. Independently of the Linux distributed control system (DCS), this controller makes sure that high priority tasks such as the telescope motion, mirror support and hydrostatic bearing control are carried out in a reliable and safe way. A comparison is made between different controller technologies including a LabVIEW embedded system, a PROFINET Programmable Logic Controller (PLC) and motion controller, and an EtherCAT embedded PC (soft-PLC). As the latter is chosen as the primary platform for the lower level control, a substantial part of the software is being ported to the IEC 61131-3 standard programming languages. Additionally, obsolete hardware is gradually being replaced by standard industrial alternatives with fast EtherCAT communication. The use of Python as a scripting language allows a smooth migration to the final MOCS: finished parts of the new control system can readily be commissioned to replace the corresponding transputer units of the old control system with minimal downtime. In this contribution, we give an overview of the systems design, implementation details and the current status of the project.

Nestly--a framework for running software with nested parameter choices and aggregating results.

PubMed

McCoy, Connor O; Gallagher, Aaron; Hoffman, Noah G; Matsen, Frederick A

2013-02-01

The execution of a software application or pipeline using various combinations of parameters and inputs is a common task in bioinformatics. In the absence of a specialized tool to organize, streamline and formalize this process, scientists must write frequently complex scripts to perform these tasks. We present nestly, a Python package to facilitate running tools with nested combinations of parameters and inputs. nestly provides three components. First, a module to build nested directory structures corresponding to choices of parameters. Second, the nestrun script to run a given command using each set of parameter choices. Third, the nestagg script to aggregate results of the individual runs into a CSV file, as well as support for more complex aggregation. We also include a module for easily specifying nested dependencies for the SCons build tool, enabling incremental builds. Source, documentation and tutorial examples are available at http://github.com/fhcrc/nestly. nestly can be installed from the Python Package Index via pip; it is open source (MIT license).

CyREST: Turbocharging Cytoscape Access for External Tools via a RESTful API.

PubMed

Ono, Keiichiro; Muetze, Tanja; Kolishovski, Georgi; Shannon, Paul; Demchak, Barry

2015-01-01

As bioinformatic workflows become increasingly complex and involve multiple specialized tools, so does the difficulty of reliably reproducing those workflows. Cytoscape is a critical workflow component for executing network visualization, analysis, and publishing tasks, but it can be operated only manually via a point-and-click user interface. Consequently, Cytoscape-oriented tasks are laborious and often error prone, especially with multistep protocols involving many networks. In this paper, we present the new cyREST Cytoscape app and accompanying harmonization libraries. Together, they improve workflow reproducibility and researcher productivity by enabling popular languages (e.g., Python and R, JavaScript, and C#) and tools (e.g., IPython/Jupyter Notebook and RStudio) to directly define and query networks, and perform network analysis, layouts and renderings. We describe cyREST's API and overall construction, and present Python- and R-based examples that illustrate how Cytoscape can be integrated into large scale data analysis pipelines. cyREST is available in the Cytoscape app store (http://apps.cytoscape.org) where it has been downloaded over 1900 times since its release in late 2014.

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.

CyREST: Turbocharging Cytoscape Access for External Tools via a RESTful API

PubMed Central

Ono, Keiichiro; Muetze, Tanja; Kolishovski, Georgi; Shannon, Paul; Demchak, Barry

2015-01-01

As bioinformatic workflows become increasingly complex and involve multiple specialized tools, so does the difficulty of reliably reproducing those workflows. Cytoscape is a critical workflow component for executing network visualization, analysis, and publishing tasks, but it can be operated only manually via a point-and-click user interface. Consequently, Cytoscape-oriented tasks are laborious and often error prone, especially with multistep protocols involving many networks. In this paper, we present the new cyREST Cytoscape app and accompanying harmonization libraries. Together, they improve workflow reproducibility and researcher productivity by enabling popular languages (e.g., Python and R, JavaScript, and C#) and tools (e.g., IPython/Jupyter Notebook and RStudio) to directly define and query networks, and perform network analysis, layouts and renderings. We describe cyREST’s API and overall construction, and present Python- and R-based examples that illustrate how Cytoscape can be integrated into large scale data analysis pipelines. cyREST is available in the Cytoscape app store (http://apps.cytoscape.org) where it has been downloaded over 1900 times since its release in late 2014. PMID:26672762

The Influence of Cross-Language Similarity on within- and between-Language Stroop Effects in Trilinguals

PubMed Central

van Heuven, Walter J. B.; Conklin, Kathy; Coderre, Emily L.; Guo, Taomei; Dijkstra, Ton

2011-01-01

This study investigated effects of cross-language similarity on within- and between-language Stroop interference and facilitation in three groups of trilinguals. Trilinguals were either proficient in three languages that use the same-script (alphabetic in German–English–Dutch trilinguals), two similar scripts and one different script (Chinese and alphabetic scripts in Chinese–English–Malay trilinguals), or three completely different scripts (Arabic, Chinese, and alphabetic in Uyghur–Chinese–English trilinguals). The results revealed a similar magnitude of within-language Stroop interference for the three groups, whereas between-language interference was modulated by cross-language similarity. For the same-script trilinguals, the within- and between-language interference was similar, whereas the between-language Stroop interference was reduced for trilinguals with languages written in different scripts. The magnitude of within-language Stroop facilitation was similar across the three groups of trilinguals, but smaller than within-language Stroop interference. Between-language Stroop facilitation was also modulated by cross-language similarity such that these effects became negative for trilinguals with languages written in different scripts. The overall pattern of Stroop interference and facilitation effects can be explained in terms of diverging and converging color and word information across languages. PMID:22180749

The Next Generation of Ground Operations Command and Control; Scripting in C Sharp and Visual Basic

NASA Technical Reports Server (NTRS)

Ritter, George; Pedoto, Ramon

2010-01-01

This slide presentation reviews the use of scripting languages in Ground Operations Command and Control. It describes the use of scripting languages in a historical context, the advantages and disadvantages of scripts. It describes the Enhanced and Redesigned Scripting (ERS) language, that was designed to combine the features of a scripting language and the graphical and IDE richness of a programming language with the utility of scripting languages. ERS uses the Microsoft Visual Studio programming environment and offers custom controls that enable an ERS developer to extend the Visual Basic and C sharp language interface with the Payload Operations Integration Center (POIC) telemetry and command system.

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

PubMed

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

2014-01-01

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

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

NASA Astrophysics Data System (ADS)

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

2013-12-01

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

FELIX-1.0: A finite element solver for the time dependent generator coordinate method with the Gaussian overlap approximation

DOE PAGES

Regnier, D.; Verriere, M.; Dubray, N.; ...

2015-11-30

In this study, we describe the software package FELIX that solves the equations of the time-dependent generator coordinate method (TDGCM) in NN-dimensions (N ≥ 1) under the Gaussian overlap approximation. The numerical resolution is based on the Galerkin finite element discretization of the collective space and the Crank–Nicolson scheme for time integration. The TDGCM solver is implemented entirely in C++. Several additional tools written in C++, Python or bash scripting language are also included for convenience. In this paper, the solver is tested with a series of benchmarks calculations. We also demonstrate the ability of our code to handle amore » realistic calculation of fission dynamics.« less

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.

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

NASA Astrophysics Data System (ADS)

Dias, B.; Milli, J.

2017-03-01

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

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.

A Dynamic Finite Element Method for Simulating the Physics of Faults Systems

NASA Astrophysics Data System (ADS)

Saez, E.; Mora, P.; Gross, L.; Weatherley, D.

2004-12-01

We introduce a dynamic Finite Element method using a novel high level scripting language to describe the physical equations, boundary conditions and time integration scheme. The library we use is the parallel Finley library: a finite element kernel library, designed for solving large-scale problems. It is incorporated as a differential equation solver into a more general library called escript, based on the scripting language Python. This library has been developed to facilitate the rapid development of 3D parallel codes, and is optimised for the Australian Computational Earth Systems Simulator Major National Research Facility (ACcESS MNRF) supercomputer, a 208 processor SGI Altix with a peak performance of 1.1 TFlops. Using the scripting approach we obtain a parallel FE code able to take advantage of the computational efficiency of the Altix 3700. We consider faults as material discontinuities (the displacement, velocity, and acceleration fields are discontinuous at the fault), with elastic behavior. The stress continuity at the fault is achieved naturally through the expression of the fault interactions in the weak formulation. The elasticity problem is solved explicitly in time, using the Saint Verlat scheme. Finally, we specify a suitable frictional constitutive relation and numerical scheme to simulate fault behaviour. Our model is based on previous work on modelling fault friction and multi-fault systems using lattice solid-like models. We adapt the 2D model for simulating the dynamics of parallel fault systems described to the Finite-Element method. The approach uses a frictional relation along faults that is slip and slip-rate dependent, and the numerical integration approach introduced by Mora and Place in the lattice solid model. In order to illustrate the new Finite Element model, single and multi-fault simulation examples are presented.

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

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.

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

On Parallel Software Engineering Education Using Python

ERIC Educational Resources Information Center

Marowka, Ami

2018-01-01

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

System for NIS Forecasting Based on Ensembles Analysis

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

2014-01-02

BMA-NIS is a package/library designed to be called by a script (e.g. Perl or Python). The software itself is written in the language of R. The software assists electric power delivery systems in planning resource availability and demand, based on historical data and current data variables. Net Interchange Schedule (NIS) is the algebraic sum of all energy scheduled to flow into or out of a balancing area during any interval. Accurate forecasts for NIS are important so that the Area Control Error (ACE) stays within an acceptable limit. To date, there are many approaches for forecasting NIS but all nonemore » of these are based on single models that can be sensitive to time of day and day of week effects.« less

Resistance is Futile: STScI's Science Planning and Scheduling Team Switches From VMS to Unix Operations

NASA Astrophysics Data System (ADS)

Adler, D. S.

2000-12-01

The Science Planning and Scheduling Team (SPST) of the Space Telescope Science Institute (STScI) has historically operated exclusively under VMS. Due to diminished support for VMS-based platforms at STScI, SPST is in the process of transitioning to Unix operations. In the summer of 1999, SPST selected Python as the primary scripting language for the operational tools and began translation of the VMS DCL code. As of October 2000, SPST has installed a utility library of 16 modules consisting of 8000 lines of code and 80 Python tools consisting of 13000 lines of code. All tasks related to calendar generation have been switched to Unix operations. Current work focuses on translating the tools used to generate the Science Mission Specifications (SMS). The software required to generate the Mission Schedule and Command Loads (PASS), maintained by another team at STScI, will take longer to translate than the rest of the SPST operational code. SPST is planning on creating tools to access PASS from Unix in the short term. We are on schedule to complete the work needed to fully transition SPST to Unix operations (while remotely accessing PASS on VMS) by the fall of 2001.

A multipurpose camera system for monitoring Kīlauea Volcano, Hawai'i

USGS Publications Warehouse

Patrick, Matthew R.; Orr, Tim R.; Lee, Lopaka; Moniz, Cyril J.

2015-01-01

We describe a low-cost, compact multipurpose camera system designed for field deployment at active volcanoes that can be used either as a webcam (transmitting images back to an observatory in real-time) or as a time-lapse camera system (storing images onto the camera system for periodic retrieval during field visits). The system also has the capability to acquire high-definition video. The camera system uses a Raspberry Pi single-board computer and a 5-megapixel low-light (near-infrared sensitive) camera, as well as a small Global Positioning System (GPS) module to ensure accurate time-stamping of images. Custom Python scripts control the webcam and GPS unit and handle data management. The inexpensive nature of the system allows it to be installed at hazardous sites where it might be lost. Another major advantage of this camera system is that it provides accurate internal timing (independent of network connection) and, because a full Linux operating system and the Python programming language are available on the camera system itself, it has the versatility to be configured for the specific needs of the user. We describe example deployments of the camera at Kīlauea Volcano, Hawai‘i, to monitor ongoing summit lava lake activity. 

Accurate Arabic Script Language/Dialect Classification

DTIC Science & Technology

2014-01-01

Army Research Laboratory Accurate Arabic Script Language/Dialect Classification by Stephen C. Tratz ARL-TR-6761 January 2014 Approved for public...1197 ARL-TR-6761 January 2014 Accurate Arabic Script Language/Dialect Classification Stephen C. Tratz Computational and Information Sciences...Include area code) Standard Form 298 (Rev. 8/98) Prescribed by ANSI Std. Z39.18 January 2014 Final Accurate Arabic Script Language/Dialect Classification

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.

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.

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

CoreFlow: a computational platform for integration, analysis and modeling of complex biological data.

PubMed

Pasculescu, Adrian; Schoof, Erwin M; Creixell, Pau; Zheng, Yong; Olhovsky, Marina; Tian, Ruijun; So, Jonathan; Vanderlaan, Rachel D; Pawson, Tony; Linding, Rune; Colwill, Karen

2014-04-04

A major challenge in mass spectrometry and other large-scale applications is how to handle, integrate, and model the data that is produced. Given the speed at which technology advances and the need to keep pace with biological experiments, we designed a computational platform, CoreFlow, which provides programmers with a framework to manage data in real-time. It allows users to upload data into a relational database (MySQL), and to create custom scripts in high-level languages such as R, Python, or Perl for processing, correcting and modeling this data. CoreFlow organizes these scripts into project-specific pipelines, tracks interdependencies between related tasks, and enables the generation of summary reports as well as publication-quality images. As a result, the gap between experimental and computational components of a typical large-scale biology project is reduced, decreasing the time between data generation, analysis and manuscript writing. CoreFlow is being released to the scientific community as an open-sourced software package complete with proteomics-specific examples, which include corrections for incomplete isotopic labeling of peptides (SILAC) or arginine-to-proline conversion, and modeling of multiple/selected reaction monitoring (MRM/SRM) results. CoreFlow was purposely designed as an environment for programmers to rapidly perform data analysis. These analyses are assembled into project-specific workflows that are readily shared with biologists to guide the next stages of experimentation. Its simple yet powerful interface provides a structure where scripts can be written and tested virtually simultaneously to shorten the life cycle of code development for a particular task. The scripts are exposed at every step so that a user can quickly see the relationships between the data, the assumptions that have been made, and the manipulations that have been performed. Since the scripts use commonly available programming languages, they can easily be transferred to and from other computational environments for debugging or faster processing. This focus on 'on the fly' analysis sets CoreFlow apart from other workflow applications that require wrapping of scripts into particular formats and development of specific user interfaces. Importantly, current and future releases of data analysis scripts in CoreFlow format will be of widespread benefit to the proteomics community, not only for uptake and use in individual labs, but to enable full scrutiny of all analysis steps, thus increasing experimental reproducibility and decreasing errors. This article is part of a Special Issue entitled: Can Proteomics Fill the Gap Between Genomics and Phenotypes? Copyright © 2014 Elsevier B.V. All rights reserved.

SciServer Compute brings Analysis to Big Data in the Cloud

NASA Astrophysics Data System (ADS)

Raddick, Jordan; Medvedev, Dmitry; Lemson, Gerard; Souter, Barbara

2016-06-01

SciServer Compute uses Jupyter Notebooks running within server-side Docker containers attached to big data collections to bring advanced analysis to big data "in the cloud." SciServer Compute is a component in the SciServer Big-Data ecosystem under development at JHU, which will provide a stable, reproducible, sharable virtual research environment.SciServer builds on the popular CasJobs and SkyServer systems that made the Sloan Digital Sky Survey (SDSS) archive one of the most-used astronomical instruments. SciServer extends those systems with server-side computational capabilities and very large scratch storage space, and further extends their functions to a range of other scientific disciplines.Although big datasets like SDSS have revolutionized astronomy research, for further analysis, users are still restricted to downloading the selected data sets locally - but increasing data sizes make this local approach impractical. Instead, researchers need online tools that are co-located with data in a virtual research environment, enabling them to bring their analysis to the data.SciServer supports this using the popular Jupyter notebooks, which allow users to write their own Python and R scripts and execute them on the server with the data (extensions to Matlab and other languages are planned). We have written special-purpose libraries that enable querying the databases and other persistent datasets. Intermediate results can be stored in large scratch space (hundreds of TBs) and analyzed directly from within Python or R with state-of-the-art visualization and machine learning libraries. Users can store science-ready results in their permanent allocation on SciDrive, a Dropbox-like system for sharing and publishing files. Communication between the various components of the SciServer system is managed through SciServer‘s new Single Sign-on Portal.We have created a number of demos to illustrate the capabilities of SciServer Compute, including Python and R scripts accessing a range of datasets and showing the data flow between storage and compute components.Demos, documentation, and more information can be found at www.sciserver.org.SciServer is funded by the National Science Foundation Award ACI-1261715.

Review of Software Platforms for Agent Based Models

DTIC Science & Technology

2008-04-01

EINSTein 4.3.2 Battlefield Python (optional, for batch runs) MANA 4.3.3 Battlefield N/A MASON 4.3.4 General Java NetLogo 4.3.5 General Logo-variant...through the use of relatively simple Python scripts. It also has built-in functions for parameter sweeps, and can plot the resulting fitness landscape ac...Nonetheless its ease of use, and support for automatic drawing of agents in 2D or 3D2 makes this a suitable platform for beginner programmers. 2Only in the

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

PubMed Central

2014-01-01

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

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.

A Software Engineering Paradigm for Quick-turnaround Earth Science Data Projects

NASA Astrophysics Data System (ADS)

Moore, K.

2016-12-01

As is generally the case with applied sciences professional and educational programs, the participants of such programs can come from a variety of technical backgrounds. In the NASA DEVELOP National Program, the participants constitute an interdisciplinary set of backgrounds, with varying levels of experience with computer programming. DEVELOP makes use of geographically explicit data sets, and it is necessary to use geographic information systems and geospatial image processing environments. As data sets cover longer time spans and include more complex sets of parameters, automation is becoming an increasingly prevalent feature. Though platforms such as ArcGIS, ERDAS Imagine, and ENVI facilitate the batch-processing of geospatial imagery, these environments are naturally constricting to the user in that they limit him or her to the tools that are available. Users must then turn to "homemade" scripting in more traditional programming languages such as Python, JavaScript, or R, to automate workflows. However, in the context of quick-turnaround projects like those in DEVELOP, the programming learning curve may be prohibitively steep. In this work, we consider how to best design a software development paradigm that addresses two major constants: an arbitrarily experienced programmer and quick-turnaround project timelines.

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

NASA Astrophysics Data System (ADS)

Mayorga, E.

2013-12-01

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

The Next Generation of Ground Operations Command and Control; Scripting in C no. and Visual Basic

NASA Technical Reports Server (NTRS)

Ritter, George; Pedoto, Ramon

2010-01-01

Scripting languages have become a common method for implementing command and control solutions in space ground operations. The Systems Test and Operations Language (STOL), the Huntsville Operations Support Center (HOSC) Scripting Language Processor (SLP), and the Spacecraft Control Language (SCL) offer script-commands that wrap tedious operations tasks into single calls. Since script-commands are interpreted, they also offer a certain amount of hands-on control that is highly valued in space ground operations. Although compiled programs seem to be unsuited for interactive user control and are more complex to develop, Marshall Space flight Center (MSFC) has developed a product called the Enhanced and Redesign Scripting (ERS) that makes use of the graphical and logical richness of a programming language while offering the hands-on and ease of control of a scripting language. ERS is currently used by the International Space Station (ISS) Payload Operations Integration Center (POIC) Cadre team members. ERS integrates spacecraft command mnemonics, telemetry measurements, and command and telemetry control procedures into a standard programming language, while making use of Microsoft's Visual Studio for developing Visual Basic (VB) or C# ground operations procedures. ERS also allows for script-style user control during procedure execution using a robust graphical user input and output feature. The availability of VB and C# programmers, and the richness of the languages and their development environment, has allowed ERS to lower our "script" development time and maintenance costs at the Marshall POIC.

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

NASA Astrophysics Data System (ADS)

Verkaik, J.

2013-12-01

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

Pairing Script and Dialogue: Combinations that Show Promise for Second or Foreign Language Learning.

ERIC Educational Resources Information Center

Holobow, N. E.; And Others

1984-01-01

Describes a study to determine if the initial advantage of listening to first language dialogs while reading second language scripts (i.e., reversed subtitling) would hold up over time and if a combination of coordinated dialogs and scripts both in the second language would gain effectiveness through usage. (SED)

Graph Mining Meets the Semantic Web

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

Lee, Sangkeun; Sukumar, Sreenivas R; Lim, Seung-Hwan

The Resource Description Framework (RDF) and SPARQL Protocol and RDF Query Language (SPARQL) were introduced about a decade ago to enable flexible schema-free data interchange on the Semantic Web. Today, data scientists use the framework as a scalable graph representation for integrating, querying, exploring and analyzing data sets hosted at different sources. With increasing adoption, the need for graph mining capabilities for the Semantic Web has emerged. We address that need through implementation of three popular iterative Graph Mining algorithms (Triangle count, Connected component analysis, and PageRank). We implement these algorithms as SPARQL queries, wrapped within Python scripts. We evaluatemore » the performance of our implementation on 6 real world data sets and show graph mining algorithms (that have a linear-algebra formulation) can indeed be unleashed on data represented as RDF graphs using the SPARQL query interface.« less

Echo

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

Harvey, Dustin Yewell

This document is a white paper marketing proposal for Echo™ is a data analysis platform designed for efficient, robust, and scalable creation and execution of complex workflows. Echo’s analysis management system refers to the ability to track, understand, and reproduce workflows used for arriving at results and decisions. Echo improves on traditional scripted data analysis in MATLAB, Python, R, and other languages to allow analysts to make better use of their time. Additionally, the Echo platform provides a powerful data management and curation solution allowing analysts to quickly find, access, and consume datasets. After two years of development and amore » first release in early 2016, Echo is now available for use with many data types in a wide range of application domains. Echo provides tools that allow users to focus on data analysis and decisions with confidence that results are reported accurately.« less

Just Google It: An Approach on Word Frequencies Based on Online Search Result.

PubMed

Moret-Tatay, Carmen; Gamermann, Daniel; Murphy, Michael; Kuzmičová, Anezka

2018-01-01

Word frequency is one of the most robust factors in the literature on word processing, based on the lexical corpus of a language. However, different sources might be used in order to determine the actual frequency of each word. Recent research has determined frequencies based on movie subtitles, Twitter, blog posts, or newspapers. In this paper, we examine a determination of these frequencies based on the World Wide Web. For this purpose, a Python script was developed to obtain frequencies of a word through online search results. These frequencies were employed to estimate lexical decision times in comparison to the traditional frequencies in a lexical decision task. It was found that the Google frequencies predict reaction times comparably to the traditional frequencies. Still, the explained variance was higher for the traditional database.

TmiRUSite and TmiROSite scripts: searching for mRNA fragments with miRNA binding sites with encoded amino acid residues.

PubMed

Berillo, Olga; Régnier, Mireille; Ivashchenko, Anatoly

2014-01-01

microRNAs are small RNA molecules that inhibit the translation of target genes. microRNA binding sites are located in the untranslated regions as well as in the coding domains. We describe TmiRUSite and TmiROSite scripts developed using python as tools for the extraction of nucleotide sequences for miRNA binding sites with their encoded amino acid residue sequences. The scripts allow for retrieving a set of additional sequences at left and at right from the binding site. The scripts presents all received data in table formats that are easy to analyse further. The predicted data finds utility in molecular and evolutionary biology studies. They find use in studying miRNA binding sites in animals and plants. TmiRUSite and TmiROSite scripts are available for free from authors upon request and at https: //sites.google.com/site/malaheenee/downloads for download.

FastScript3D - A Companion to Java 3D

NASA Technical Reports Server (NTRS)

Koenig, Patti

2005-01-01

FastScript3D is a computer program, written in the Java 3D(TM) programming language, that establishes an alternative language that helps users who lack expertise in Java 3D to use Java 3D for constructing three-dimensional (3D)-appearing graphics. The FastScript3D language provides a set of simple, intuitive, one-line text-string commands for creating, controlling, and animating 3D models. The first word in a string is the name of a command; the rest of the string contains the data arguments for the command. The commands can also be used as an aid to learning Java 3D. Developers can extend the language by adding custom text-string commands. The commands can define new 3D objects or load representations of 3D objects from files in formats compatible with such other software systems as X3D. The text strings can be easily integrated into other languages. FastScript3D facilitates communication between scripting languages [which enable programming of hyper-text markup language (HTML) documents to interact with users] and Java 3D. The FastScript3D language can be extended and customized on both the scripting side and the Java 3D side.

interPopula: a Python API to access the HapMap Project dataset

PubMed Central

2010-01-01

Background The HapMap project is a publicly available catalogue of common genetic variants that occur in humans, currently including several million SNPs across 1115 individuals spanning 11 different populations. This important database does not provide any programmatic access to the dataset, furthermore no standard relational database interface is provided. Results interPopula is a Python API to access the HapMap dataset. interPopula provides integration facilities with both the Python ecology of software (e.g. Biopython and matplotlib) and other relevant human population datasets (e.g. Ensembl gene annotation and UCSC Known Genes). A set of guidelines and code examples to address possible inconsistencies across heterogeneous data sources is also provided. Conclusions interPopula is a straightforward and flexible Python API that facilitates the construction of scripts and applications that require access to the HapMap dataset. PMID:21210977

Optimal Repair And Replacement Policy For A System With Multiple Components

DTIC Science & Technology

2016-06-17

Numerical Demonstration To implement the linear program, we use the Python Programming Language (PSF 2016) with the Pyomo optimization modeling language...opre.1040.0133. Hart, W.E., C. Laird, J. Watson, D.L. Woodruff. 2012. Pyomo–optimization modeling in python , vol. 67. Springer Science & Business...Media. Hart, W.E., J. Watson, D.L. Woodruff. 2011. Pyomo: modeling and solving mathematical programs in python . Mathematical Programming Computation 3(3

Facilitating the selection and creation of accurate interatomic potentials with robust tools and characterization

NASA Astrophysics Data System (ADS)

Trautt, Zachary T.; Tavazza, Francesca; Becker, Chandler A.

2015-10-01

The Materials Genome Initiative seeks to significantly decrease the cost and time of development and integration of new materials. Within the domain of atomistic simulations, several roadblocks stand in the way of reaching this goal. While the NIST Interatomic Potentials Repository hosts numerous interatomic potentials (force fields), researchers cannot immediately determine the best choice(s) for their use case. Researchers developing new potentials, specifically those in restricted environments, lack a comprehensive portfolio of efficient tools capable of calculating and archiving the properties of their potentials. This paper elucidates one solution to these problems, which uses Python-based scripts that are suitable for rapid property evaluation and human knowledge transfer. Calculation results are visible on the repository website, which reduces the time required to select an interatomic potential for a specific use case. Furthermore, property evaluation scripts are being integrated with modern platforms to improve discoverability and access of materials property data. To demonstrate these scripts and features, we will discuss the automation of stacking fault energy calculations and their application to additional elements. While the calculation methodology was developed previously, we are using it here as a case study in simulation automation and property calculations. We demonstrate how the use of Python scripts allows for rapid calculation in a more easily managed way where the calculations can be modified, and the results presented in user-friendly and concise ways. Additionally, the methods can be incorporated into other efforts, such as openKIM.

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.

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

Sauter, Nicholas K., E-mail: nksauter@lbl.gov; Hattne, Johan; Grosse-Kunstleve, Ralf W.

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

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

Entropic evidence for linguistic structure in the Indus script.

PubMed

Rao, Rajesh P N; Yadav, Nisha; Vahia, Mayank N; Joglekar, Hrishikesh; Adhikari, R; Mahadevan, Iravatham

2009-05-29

The script of the ancient Indus civilization remains undeciphered. The hypothesis that the script encodes language has recently been questioned. Here, we present evidence for the linguistic hypothesis by showing that the script's conditional entropy is closer to those of natural languages than various types of nonlinguistic systems.

GUI implementation of image encryption and decryption using Open CV-Python script on secured TFTP protocol

NASA Astrophysics Data System (ADS)

Reddy, K. Rasool; Rao, Ch. Madhava

2018-04-01

Currently safety is one of the primary concerns in the transmission of images due to increasing the use of images within the industrial applications. So it's necessary to secure the image facts from unauthorized individuals. There are various strategies are investigated to secure the facts. In that encryption is certainly one of maximum distinguished method. This paper gives a sophisticated Rijndael (AES) algorithm to shield the facts from unauthorized humans. Here Exponential Key Change (EKE) concept is also introduced to exchange the key between client and server. The things are exchange in a network among client and server through a simple protocol is known as Trivial File Transfer Protocol (TFTP). This protocol is used mainly in embedded servers to transfer the data and also provide protection to the data if protection capabilities are integrated. In this paper, implementing a GUI environment for image encryption and decryption. All these experiments carried out on Linux environment the usage of Open CV-Python script.

π Scope: python based scientific workbench with visualization tool for MDSplus data

NASA Astrophysics Data System (ADS)

Shiraiwa, S.

2014-10-01

π Scope is a python based scientific data analysis and visualization tool constructed on wxPython and Matplotlib. Although it is designed to be a generic tool, the primary motivation for developing the new software is 1) to provide an updated tool to browse MDSplus data, with functionalities beyond dwscope and jScope, and 2) to provide a universal foundation to construct interface tools to perform computer simulation and modeling for Alcator C-Mod. It provides many features to visualize MDSplus data during tokamak experiments including overplotting different signals and discharges, various plot types (line, contour, image, etc.), in-panel data analysis using python scripts, and publication quality graphics generation. Additionally, the logic to produce multi-panel plots is designed to be backward compatible with dwscope, enabling smooth migration for dwscope users. πScope uses multi-threading to reduce data transfer latency, and its object-oriented design makes it easy to modify and expand while the open source nature allows portability. A built-in tree data browser allows a user to approach the data structure both from a GUI and a script, enabling relatively complex data analysis workflow to be built quickly. As an example, an IDL-based interface to perform GENRAY/CQL3D simulations was ported on πScope, thus allowing LHCD simulation to be run between-shot using C-Mod experimental profiles. This workflow is being used to generate a large database to develop a LHCD actuator model for the plasma control system. Supported by USDoE Award DE-FC02-99ER54512.

A python tool for the implementation of domain-specific languages

NASA Astrophysics Data System (ADS)

Dejanović, Igor; Vaderna, Renata; Milosavljević, Gordana; Simić, Miloš; Vuković, Željko

2017-07-01

In this paper we describe textX, a meta-language and a tool for building Domain-Specific Languages. It is implemented in Python using Arpeggio PEG (Parsing Expression Grammar) parser library. From a single language description (grammar) textX will build a parser and a meta-model (a.k.a. abstract syntax) of the language. The parser is used to parse textual representations of models conforming to the meta-model. As a result of parsing, a Python object graph will be automatically created. The structure of the object graph will conform to the meta-model defined by the grammar. This approach frees a developer from the need to manually analyse a parse tree and transform it to other suitable representation. The textX library is independent of any integrated development environment and can be easily integrated in any Python project. The textX tool works as a grammar interpreter. The parser is configured at run-time using the grammar. The textX tool is a free and open-source project available at GitHub.

SoS Notebook: An Interactive Multi-Language Data Analysis Environment.

PubMed

Peng, Bo; Wang, Gao; Ma, Jun; Leong, Man Chong; Wakefield, Chris; Melott, James; Chiu, Yulun; Du, Di; Weinstein, John N

2018-05-22

Complex bioinformatic data analysis workflows involving multiple scripts in different languages can be difficult to consolidate, share, and reproduce. An environment that streamlines the entire processes of data collection, analysis, visualization and reporting of such multi-language analyses is currently lacking. We developed Script of Scripts (SoS) Notebook, a web-based notebook environment that allows the use of multiple scripting language in a single notebook, with data flowing freely within and across languages. SoS Notebook enables researchers to perform sophisticated bioinformatic analysis using the most suitable tools for different parts of the workflow, without the limitations of a particular language or complications of cross-language communications. SoS Notebook is hosted at http://vatlab.github.io/SoS/ and is distributed under a BSD license. bpeng@mdanderson.org.

Simplifying and enhancing the use of PyMOL with horizontal scripts

PubMed Central

2016-01-01

Abstract Scripts are used in PyMOL to exert precise control over the appearance of the output and to ease remaking similar images at a later time. We developed horizontal scripts to ease script development. A horizontal script makes a complete scene in PyMOL like a traditional vertical script. The commands in a horizontal script are separated by semicolons. These scripts are edited interactively on the command line with no need for an external text editor. This simpler workflow accelerates script development. In using PyMOL, the illustration of a molecular scene requires an 18‐element matrix of view port settings. The default format spans several lines and is laborious to manually reformat for one line. This default format prevents the fast assembly of horizontal scripts that can reproduce a molecular scene. We solved this problem by writing a function that displays the settings on one line in a compact format suitable for horizontal scripts. We also demonstrate the mapping of aliases to horizontal scripts. Many aliases can be defined in a single script file, which can be useful for applying costume molecular representations to any structure. We also redefined horizontal scripts as Python functions to enable the use of the help function to print documentation about an alias to the command history window. We discuss how these methods of using horizontal scripts both simplify and enhance the use of PyMOL in research and education. PMID:27488983

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.

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

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.

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

PubMed

Spielman, Stephanie J; Wilke, Claus O

2015-01-01

We introduce Pyvolve, a flexible Python module for simulating genetic data along a phylogeny using continuous-time Markov models of sequence evolution. Easily incorporated into Python bioinformatics pipelines, Pyvolve can simulate sequences according to most standard models of nucleotide, amino-acid, and codon sequence evolution. All model parameters are fully customizable. Users can additionally specify custom evolutionary models, with custom rate matrices and/or states to evolve. This flexibility makes Pyvolve a convenient framework not only for simulating sequences under a wide variety of conditions, but also for developing and testing new evolutionary models. Pyvolve is an open-source project under a FreeBSD license, and it is available for download, along with a detailed user-manual and example scripts, from http://github.com/sjspielman/pyvolve.

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.

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

EAGLE: 'EAGLE'Is an' Algorithmic Graph Library for Exploration

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

2015-01-16

The Resource Description Framework (RDF) and SPARQL Protocol and RDF Query Language (SPARQL) were introduced about a decade ago to enable flexible schema-free data interchange on the Semantic Web. Today data scientists use the framework as a scalable graph representation for integrating, querying, exploring and analyzing data sets hosted at different sources. With increasing adoption, the need for graph mining capabilities for the Semantic Web has emerged. Today there is no tools to conduct "graph mining" on RDF standard data sets. We address that need through implementation of popular iterative Graph Mining algorithms (Triangle count, Connected component analysis, degree distribution,more » diversity degree, PageRank, etc.). We implement these algorithms as SPARQL queries, wrapped within Python scripts and call our software tool as EAGLE. In RDF style, EAGLE stands for "EAGLE 'Is an' algorithmic graph library for exploration. EAGLE is like 'MATLAB' for 'Linked Data.'« less

HYDRA Hyperspectral Data Research Application Tom Rink and Tom Whittaker

NASA Astrophysics Data System (ADS)

Rink, T.; Whittaker, T.

2005-12-01

HYDRA is a freely available, easy to install tool for visualization and analysis of large local or remote hyper/multi-spectral datasets. HYDRA is implemented on top of the open source VisAD Java library via Jython - the Java implementation of the user friendly Python programming language. VisAD provides data integration, through its generalized data model, user-display interaction and display rendering. Jython has an easy to read, concise, scripting-like, syntax which eases software development. HYDRA allows data sharing of large datasets through its support of the OpenDAP and OpenADDE server-client protocols. The users can explore and interrogate data, and subset in physical and/or spectral space to isolate key areas of interest for further analysis without having to download an entire dataset. It also has an extensible data input architecture to recognize new instruments and understand different local file formats, currently NetCDF and HDF4 are supported.

Solving Equations of Multibody Dynamics

NASA Technical Reports Server (NTRS)

Jain, Abhinandan; Lim, Christopher

2007-01-01

Darts++ is a computer program for solving the equations of motion of a multibody system or of a multibody model of a dynamic system. It is intended especially for use in dynamical simulations performed in designing and analyzing, and developing software for the control of, complex mechanical systems. Darts++ is based on the Spatial-Operator- Algebra formulation for multibody dynamics. This software reads a description of a multibody system from a model data file, then constructs and implements an efficient algorithm that solves the dynamical equations of the system. The efficiency and, hence, the computational speed is sufficient to make Darts++ suitable for use in realtime closed-loop simulations. Darts++ features an object-oriented software architecture that enables reconfiguration of system topology at run time; in contrast, in related prior software, system topology is fixed during initialization. Darts++ provides an interface to scripting languages, including Tcl and Python, that enable the user to configure and interact with simulation objects at run time.

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

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

Stage by Stage: A Handbook for Using Drama in the Second Language Classroom.

ERIC Educational Resources Information Center

Burke, Ann F.; O'Sullivan, Julie C.

This book offers teachers the tools they need to incorporate drama into their language classes. It provides instructions on how to do the following: conduct a drama class; use acting and role-play exercises; select appropriate scripts for language learners; guide students to write their own scripts; and dramatize scripts for performance. Chapter…

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

Legacy model integration for enhancing hydrologic interdisciplinary research

NASA Astrophysics Data System (ADS)

Dozier, A.; Arabi, M.; David, O.

2013-12-01

Many challenges are introduced to interdisciplinary research in and around the hydrologic science community due to advances in computing technology and modeling capabilities in different programming languages, across different platforms and frameworks by researchers in a variety of fields with a variety of experience in computer programming. Many new hydrologic models as well as optimization, parameter estimation, and uncertainty characterization techniques are developed in scripting languages such as Matlab, R, Python, or in newer languages such as Java and the .Net languages, whereas many legacy models have been written in FORTRAN and C, which complicates inter-model communication for two-way feedbacks. However, most hydrologic researchers and industry personnel have little knowledge of the computing technologies that are available to address the model integration process. Therefore, the goal of this study is to address these new challenges by utilizing a novel approach based on a publish-subscribe-type system to enhance modeling capabilities of legacy socio-economic, hydrologic, and ecologic software. Enhancements include massive parallelization of executions and access to legacy model variables at any point during the simulation process by another program without having to compile all the models together into an inseparable 'super-model'. Thus, this study provides two-way feedback mechanisms between multiple different process models that can be written in various programming languages and can run on different machines and operating systems. Additionally, a level of abstraction is given to the model integration process that allows researchers and other technical personnel to perform more detailed and interactive modeling, visualization, optimization, calibration, and uncertainty analysis without requiring deep understanding of inter-process communication. To be compatible, a program must be written in a programming language with bindings to a common implementation of the message passing interface (MPI), which includes FORTRAN, C, Java, the .NET languages, Python, R, Matlab, and many others. The system is tested on a longstanding legacy hydrologic model, the Soil and Water Assessment Tool (SWAT), to observe and enhance speed-up capabilities for various optimization, parameter estimation, and model uncertainty characterization techniques, which is particularly important for computationally intensive hydrologic simulations. Initial results indicate that the legacy extension system significantly decreases developer time, computation time, and the cost of purchasing commercial parallel processing licenses, while enhancing interdisciplinary research by providing detailed two-way feedback mechanisms between various process models with minimal changes to legacy code.

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

NASA Astrophysics Data System (ADS)

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

2015-04-01

Most hydrologists are dealing with time series frequently. Reading in time series, transforming them and extracting specific periods for visualisation are part of the daily work. Spreadsheet software is used a lot for these operations, but has some major drawbacks. It is mostly not reproducible, it is prone to errors and not easy to automate, which results in repetitive work when dealing with large amounts of data. Scripting languages like R and Python on the other hand, provide flexibility, enable automation and reproducibility and, hence, increase efficiency. Python has gained popularity over the last years and currently, tools for many aspects of scientific computing are readily available in Python. An increased support in controlling and managing the dependencies between packages (e.g. the Anaconda environment) allows for a wide audience to use the huge variety of available packages. Pandas is a powerful Python package for data analysis and has a lot of functionalities related to time series. As such, the package is of special interest to hydrologists. Some other packages, focussing on hydrology (e.g. Hydroclimpy by Pierre Gerard-Marchant and Hydropy by Javier Rovegno Campos), stopped active development, mainly due to the superior implementation of Pandas. We present a (revised) version of the Hydropy package that is inspired by the aforementioned packages and builds on the power of Pandas. The main idea is to add hydrological domain knowledge to the already existing Pandas functionalities. Besides, the package attempts to make the time series handling intuitive and easy to perform, thus with a clear syntax. Some illustrative examples of the current implementation starting from a Pandas DataFrame named flowdata: Creating the object flow to work with: flow = HydroAnalysis(flowdata) Retrieve only the data during winter (across all years): flow.get_season('winter') Retrieve only the data during summer of 2010: flow.get_season('summer').get_year('2010') which is equivalent to flow.get_year('2010').get_season('summer') Retrieve only the data of July and get the peak values above the 95 percentile: flow.get_season('july').get_highpeaks(above_percentile=0.95) Retrieve only the data between two specified days and selecting only the rising limbs flow.get_date_range('01/10/2008', '15/2/2014').get_climbing() Calculate the annual sum and make a plot of it: flow.frequency_resample('A', 'sum').plot()

Interactive Light Stimulus Generation with High Performance Real-Time Image Processing and Simple Scripting.

PubMed

Szécsi, László; Kacsó, Ágota; Zeck, Günther; Hantz, Péter

2017-01-01

Light stimulation with precise and complex spatial and temporal modulation is demanded by a series of research fields like visual neuroscience, optogenetics, ophthalmology, and visual psychophysics. We developed a user-friendly and flexible stimulus generating framework (GEARS GPU-based Eye And Retina Stimulation Software), which offers access to GPU computing power, and allows interactive modification of stimulus parameters during experiments. Furthermore, it has built-in support for driving external equipment, as well as for synchronization tasks, via USB ports. The use of GEARS does not require elaborate programming skills. The necessary scripting is visually aided by an intuitive interface, while the details of the underlying software and hardware components remain hidden. Internally, the software is a C++/Python hybrid using OpenGL graphics. Computations are performed on the GPU, and are defined in the GLSL shading language. However, all GPU settings, including the GPU shader programs, are automatically generated by GEARS. This is configured through a method encountered in game programming, which allows high flexibility: stimuli are straightforwardly composed using a broad library of basic components. Stimulus rendering is implemented solely in C++, therefore intermediary libraries for interfacing could be omitted. This enables the program to perform computationally demanding tasks like en-masse random number generation or real-time image processing by local and global operations.

Arabic Script and the Rise of Arabic Calligraphy

ERIC Educational Resources Information Center

Alshahrani, Ali A.

2008-01-01

The aim of this paper is to present a concise coherent literature review of the Arabic Language script system as one of the oldest living Semitic languages in the world. The article discusses in depth firstly, Arabic script as a phonemic sound-based writing system of twenty eight, right to left cursive script where letterforms shaped by their…

GIS methodology for geothermal play fairway analysis: Example from the Snake River Plain volcanic province

USGS Publications Warehouse

DeAngelo, Jacob; Shervais, John W.; Glen, Jonathan; Nielson, Dennis L.; Garg, Sabodh; Dobson, Patrick; Gasperikova, Erika; Sonnenthal, Eric; Visser, Charles; Liberty, Lee M.; Siler, Drew; Evans, James P.; Santellanes, Sean

2016-01-01

Play fairway analysis in geothermal exploration derives from a systematic methodology originally developed within the petroleum industry and is based on a geologic and hydrologic framework of identified geothermal systems. We are tailoring this methodology to study the geothermal resource potential of the Snake River Plain and surrounding region. This project has contributed to the success of this approach by cataloging the critical elements controlling exploitable hydrothermal systems, establishing risk matrices that evaluate these elements in terms of both probability of success and level of knowledge, and building automated tools to process results. ArcGIS was used to compile a range of different data types, which we refer to as ‘elements’ (e.g., faults, vents, heatflow…), with distinct characteristics and confidence values. Raw data for each element were transformed into data layers with a common format. Because different data types have different uncertainties, each evidence layer had an accompanying confidence layer, which reflects spatial variations in these uncertainties. Risk maps represent the product of evidence and confidence layers, and are the basic building blocks used to construct Common Risk Segment (CRS) maps for heat, permeability, and seal. CRS maps quantify the variable risk associated with each of these critical components. In a final step, the three CRS maps were combined into a Composite Common Risk Segment (CCRS) map for analysis that reveals favorable areas for geothermal exploration. Python scripts were developed to automate data processing and to enhance the flexibility of the data analysis. Python scripting provided the structure that makes a custom workflow possible. Nearly every tool available in the ArcGIS ArcToolbox can be executed using commands in the Python programming language. This enabled the construction of a group of tools that could automate most of the processing for the project. Currently, our tools are repeatable, scalable, modifiable, and transferrable, allowing us to automate the task of data analysis and the production of CRS and CCRS maps. Our ultimate goal is to produce a toolkit that can be imported into ArcGIS and applied to any geothermal play type, with fully tunable parameters that will allow for the production of multiple versions of the CRS and CCRS maps in order to better test for sensitivity and to validate results.

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.

Vectorized algorithms for spiking neural network simulation.

PubMed

Brette, Romain; Goodman, Dan F M

2011-06-01

High-level languages (Matlab, Python) are popular in neuroscience because they are flexible and accelerate development. However, for simulating spiking neural networks, the cost of interpretation is a bottleneck. We describe a set of algorithms to simulate large spiking neural networks efficiently with high-level languages using vector-based operations. These algorithms constitute the core of Brian, a spiking neural network simulator written in the Python language. Vectorized simulation makes it possible to combine the flexibility of high-level languages with the computational efficiency usually associated with compiled languages.

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

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

NASA Astrophysics Data System (ADS)

Lin, J. W.-B.

2008-10-01

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

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

NASA Astrophysics Data System (ADS)

Lin, J. W.-B.

2009-02-01

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

An open source software tool to assign the material properties of bone for ABAQUS finite element simulations.

PubMed

Pegg, Elise C; Gill, Harinderjit S

2016-09-06

A new software tool to assign the material properties of bone to an ABAQUS finite element mesh was created and compared with Bonemat, a similar tool originally designed to work with Ansys finite element models. Our software tool (py_bonemat_abaqus) was written in Python, which is the chosen scripting language for ABAQUS. The purpose of this study was to compare the software packages in terms of the material assignment calculation and processing speed. Three element types were compared (linear hexahedral (C3D8), linear tetrahedral (C3D4) and quadratic tetrahedral elements (C3D10)), both individually and as part of a mesh. Comparisons were made using a CT scan of a hemi-pelvis as a test case. A small difference, of -0.05kPa on average, was found between Bonemat version 3.1 (the current version) and our Python package. Errors were found in the previous release of Bonemat (version 3.0 downloaded from www.biomedtown.org) during calculation of the quadratic tetrahedron Jacobian, and conversion of the apparent density to modulus when integrating over the Young׳s modulus field. These issues caused up to 2GPa error in the modulus assignment. For these reasons, we recommend users upgrade to the most recent release of Bonemat. Processing speeds were assessed for the three different element types. Our Python package took significantly longer (110s on average) to perform the calculations compared with the Bonemat software (10s). Nevertheless, the workflow advantages of the package and added functionality makes 'py_bonemat_abaqus' a useful tool for ABAQUS users. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

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

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

pynoddy 1.0: an experimental platform for automated 3-D kinematic and potential field modelling

NASA Astrophysics Data System (ADS)

Florian Wellmann, J.; Thiele, Sam T.; Lindsay, Mark D.; Jessell, Mark W.

2016-03-01

We present a novel methodology for performing experiments with subsurface structural models using a set of flexible and extensible Python modules. We utilize the ability of kinematic modelling techniques to describe major deformational, tectonic, and magmatic events at low computational cost to develop experiments testing the interactions between multiple kinematic events, effect of uncertainty regarding event timing, and kinematic properties. These tests are simple to implement and perform, as they are automated within the Python scripting language, allowing the encapsulation of entire kinematic experiments within high-level class definitions and fully reproducible results. In addition, we provide a link to geophysical potential-field simulations to evaluate the effect of parameter uncertainties on maps of gravity and magnetics. We provide relevant fundamental information on kinematic modelling and our implementation, and showcase the application of our novel methods to investigate the interaction of multiple tectonic events on a pre-defined stratigraphy, the effect of changing kinematic parameters on simulated geophysical potential fields, and the distribution of uncertain areas in a full 3-D kinematic model, based on estimated uncertainties in kinematic input parameters. Additional possibilities for linking kinematic modelling to subsequent process simulations are discussed, as well as additional aspects of future research. Our modules are freely available on github, including documentation and tutorial examples, and we encourage the contribution to this project.

pynoddy 1.0: an experimental platform for automated 3-D kinematic and potential field modelling

NASA Astrophysics Data System (ADS)

Wellmann, J. F.; Thiele, S. T.; Lindsay, M. D.; Jessell, M. W.

2015-11-01

We present a novel methodology for performing experiments with subsurface structural models using a set of flexible and extensible Python modules. We utilise the ability of kinematic modelling techniques to describe major deformational, tectonic, and magmatic events at low computational cost to develop experiments testing the interactions between multiple kinematic events, effect of uncertainty regarding event timing, and kinematic properties. These tests are simple to implement and perform, as they are automated within the Python scripting language, allowing the encapsulation of entire kinematic experiments within high-level class definitions and fully reproducible results. In addition, we provide a~link to geophysical potential-field simulations to evaluate the effect of parameter uncertainties on maps of gravity and magnetics. We provide relevant fundamental information on kinematic modelling and our implementation, and showcase the application of our novel methods to investigate the interaction of multiple tectonic events on a pre-defined stratigraphy, the effect of changing kinematic parameters on simulated geophysical potential-fields, and the distribution of uncertain areas in a full 3-D kinematic model, based on estimated uncertainties in kinematic input parameters. Additional possibilities for linking kinematic modelling to subsequent process simulations are discussed, as well as additional aspects of future research. Our modules are freely available on github, including documentation and tutorial examples, and we encourage the contribution to this project.

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

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…

Automated Spatio-Temporal Analysis of Remotely Sensed Imagery for Water Resources Management

NASA Astrophysics Data System (ADS)

Bahr, Thomas

2016-04-01

Since 2012, the state of California faces an extreme drought, which impacts water supply in many ways. Advanced remote sensing is an important technology to better assess water resources, monitor drought conditions and water supplies, plan for drought response and mitigation, and measure drought impacts. In the present case study latest time series analysis capabilities are used to examine surface water in reservoirs located along the western flank of the Sierra Nevada region of California. This case study was performed using the COTS software package ENVI 5.3. Integration of custom processes and automation is supported by IDL (Interactive Data Language). Thus, ENVI analytics is running via the object-oriented and IDL-based ENVITask API. A time series from Landsat images (L-5 TM, L-7 ETM+, L-8 OLI) of the AOI was obtained for 1999 to 2015 (October acquisitions). Downloaded from the USGS EarthExplorer web site, they already were georeferenced to a UTM Zone 10N (WGS-84) coordinate system. ENVITasks were used to pre-process the Landsat images as follows: • Triangulation based gap-filling for the SLC-off Landsat-7 ETM+ images. • Spatial subsetting to the same geographic extent. • Radiometric correction to top-of-atmosphere (TOA) reflectance. • Atmospheric correction using QUAC®, which determines atmospheric correction parameters directly from the observed pixel spectra in a scene, without ancillary information. Spatio-temporal analysis was executed with the following tasks: • Creation of Modified Normalized Difference Water Index images (MNDWI, Xu 2006) to enhance open water features while suppressing noise from built-up land, vegetation, and soil. • Threshold based classification of the water index images to extract the water features. • Classification aggregation as a post-classification cleanup process. • Export of the respective water classes to vector layers for further evaluation in a GIS. • Animation of the classification series and export to a common video format. • Plotting the time series of water surface area in square kilometers. The automated spatio-temporal analysis introduced here can be embedded in virtually any existing geospatial workflow for operational applications. Three integration options were implemented in this case study: • Integration within any ArcGIS environment whether deployed on the desktop, in the cloud, or online. Execution uses a customized ArcGIS script tool. A Python script file retrieves the parameters from the user interface and runs the precompiled IDL code. That IDL code is used to interface between the Python script and the relevant ENVITasks. • Publishing the spatio-temporal analysis tasks as services via the ENVI Services Engine (ESE). ESE is a cloud-based image analysis solution to publish and deploy advanced ENVI image and data analytics to existing enterprise infrastructures. For this purpose the entire IDL code can be capsuled in a single ENVITask. • Integration in an existing geospatial workflow using the Python-to-IDL Bridge. This mechanism allows calling IDL code within Python on a user-defined platform. The results of this case study verify the drastic decrease of the amount of surface water in the AOI, indicative of the major drought that is pervasive throughout California. Accordingly, the time series analysis was correlated successfully with the daily reservoir elevations of the Don Pedro reservoir (station DNP, operated by CDEC).

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.

BioC implementations in Go, Perl, Python and Ruby

PubMed Central

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

2014-01-01

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

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

O'Malley, Daniel; Vesselinov, Velimir V.

MADSpython (Model analysis and decision support tools in Python) is a code in Python that streamlines the process of using data and models for analysis and decision support using the code MADS. MADS is open-source code developed at LANL and written in C/C++ (MADS; http://mads.lanl.gov; LA-CC-11-035). MADS can work with external models of arbitrary complexity as well as built-in models of flow and transport in porous media. The Python scripts in MADSpython facilitate the generation of input and output file needed by MADS as wells as the external simulators which include FEHM and PFLOTRAN. MADSpython enables a number of data-more » and model-based analyses including model calibration, sensitivity analysis, uncertainty quantification, and decision analysis. MADSpython will be released under GPL V3 license. MADSpython will be distributed as a Git repo at gitlab.com and github.com. MADSpython manual and documentation will be posted at http://madspy.lanl.gov.« less

Non-Selective Lexical Access in Different-Script Bilinguals

ERIC Educational Resources Information Center

Moon, Jihye; Jiang, Nan

2012-01-01

Lexical access in bilinguals is known to be largely non-selective. However, most studies in this area have involved bilinguals whose two languages share the same script. This study aimed to examine bilingual lexical access among bilinguals whose two languages have distinct scripts. Korean-English bilinguals were tested in a phoneme monitoring task…

BigDataScript: a scripting language for data pipelines.

PubMed

Cingolani, Pablo; Sladek, Rob; Blanchette, Mathieu

2015-01-01

The analysis of large biological datasets often requires complex processing pipelines that run for a long time on large computational infrastructures. We designed and implemented a simple script-like programming language with a clean and minimalist syntax to develop and manage pipeline execution and provide robustness to various types of software and hardware failures as well as portability. We introduce the BigDataScript (BDS) programming language for data processing pipelines, which improves abstraction from hardware resources and assists with robustness. Hardware abstraction allows BDS pipelines to run without modification on a wide range of computer architectures, from a small laptop to multi-core servers, server farms, clusters and clouds. BDS achieves robustness by incorporating the concepts of absolute serialization and lazy processing, thus allowing pipelines to recover from errors. By abstracting pipeline concepts at programming language level, BDS simplifies implementation, execution and management of complex bioinformatics pipelines, resulting in reduced development and debugging cycles as well as cleaner code. BigDataScript is available under open-source license at http://pcingola.github.io/BigDataScript. © The Author 2014. Published by Oxford University Press.

BigDataScript: a scripting language for data pipelines

PubMed Central

Cingolani, Pablo; Sladek, Rob; Blanchette, Mathieu

2015-01-01

Motivation: The analysis of large biological datasets often requires complex processing pipelines that run for a long time on large computational infrastructures. We designed and implemented a simple script-like programming language with a clean and minimalist syntax to develop and manage pipeline execution and provide robustness to various types of software and hardware failures as well as portability. Results: We introduce the BigDataScript (BDS) programming language for data processing pipelines, which improves abstraction from hardware resources and assists with robustness. Hardware abstraction allows BDS pipelines to run without modification on a wide range of computer architectures, from a small laptop to multi-core servers, server farms, clusters and clouds. BDS achieves robustness by incorporating the concepts of absolute serialization and lazy processing, thus allowing pipelines to recover from errors. By abstracting pipeline concepts at programming language level, BDS simplifies implementation, execution and management of complex bioinformatics pipelines, resulting in reduced development and debugging cycles as well as cleaner code. Availability and implementation: BigDataScript is available under open-source license at http://pcingola.github.io/BigDataScript. Contact: pablo.e.cingolani@gmail.com PMID:25189778

Scriptwriting as a Tool for Learning Stylistic Variation

ERIC Educational Resources Information Center

Saugera, Valerie

2011-01-01

A film script is a useful tool for allowing students to experiment with language variation. Scripts of love stories comprise a range of language contexts, each triggering a different style on a formal-neutral-informal linguistic continuum: (1) technical cinematographic language in camera directions; (2) narrative language in exposition of scenes,…

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

Summary report for the Engineering Script Language (ESL)

NASA Technical Reports Server (NTRS)

1990-01-01

The following subject areas are covered: ESL methodology concept; ESL specification; user interface description; engineering scripting language command statements specification; and recommendations for further research and development.

Composable languages for bioinformatics: the NYoSh experiment

PubMed Central

Simi, Manuele

2014-01-01

Language WorkBenches (LWBs) are software engineering tools that help domain experts develop solutions to various classes of problems. Some of these tools focus on non-technical users and provide languages to help organize knowledge while other workbenches provide means to create new programming languages. A key advantage of language workbenches is that they support the seamless composition of independently developed languages. This capability is useful when developing programs that can benefit from different levels of abstraction. We reasoned that language workbenches could be useful to develop bioinformatics software solutions. In order to evaluate the potential of language workbenches in bioinformatics, we tested a prominent workbench by developing an alternative to shell scripting. To illustrate what LWBs and Language Composition can bring to bioinformatics, we report on our design and development of NYoSh (Not Your ordinary Shell). NYoSh was implemented as a collection of languages that can be composed to write programs as expressive and concise as shell scripts. This manuscript offers a concrete illustration of the advantages and current minor drawbacks of using the MPS LWB. For instance, we found that we could implement an environment-aware editor for NYoSh that can assist the programmers when developing scripts for specific execution environments. This editor further provides semantic error detection and can be compiled interactively with an automatic build and deployment system. In contrast to shell scripts, NYoSh scripts can be written in a modern development environment, supporting context dependent intentions and can be extended seamlessly by end-users with new abstractions and language constructs. We further illustrate language extension and composition with LWBs by presenting a tight integration of NYoSh scripts with the GobyWeb system. The NYoSh Workbench prototype, which implements a fully featured integrated development environment for NYoSh is distributed at http://nyosh.campagnelab.org. PMID:24482760

Composable languages for bioinformatics: the NYoSh experiment.

PubMed

Simi, Manuele; Campagne, Fabien

2014-01-01

Language WorkBenches (LWBs) are software engineering tools that help domain experts develop solutions to various classes of problems. Some of these tools focus on non-technical users and provide languages to help organize knowledge while other workbenches provide means to create new programming languages. A key advantage of language workbenches is that they support the seamless composition of independently developed languages. This capability is useful when developing programs that can benefit from different levels of abstraction. We reasoned that language workbenches could be useful to develop bioinformatics software solutions. In order to evaluate the potential of language workbenches in bioinformatics, we tested a prominent workbench by developing an alternative to shell scripting. To illustrate what LWBs and Language Composition can bring to bioinformatics, we report on our design and development of NYoSh (Not Your ordinary Shell). NYoSh was implemented as a collection of languages that can be composed to write programs as expressive and concise as shell scripts. This manuscript offers a concrete illustration of the advantages and current minor drawbacks of using the MPS LWB. For instance, we found that we could implement an environment-aware editor for NYoSh that can assist the programmers when developing scripts for specific execution environments. This editor further provides semantic error detection and can be compiled interactively with an automatic build and deployment system. In contrast to shell scripts, NYoSh scripts can be written in a modern development environment, supporting context dependent intentions and can be extended seamlessly by end-users with new abstractions and language constructs. We further illustrate language extension and composition with LWBs by presenting a tight integration of NYoSh scripts with the GobyWeb system. The NYoSh Workbench prototype, which implements a fully featured integrated development environment for NYoSh is distributed at http://nyosh.campagnelab.org.

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…

Interactive Light Stimulus Generation with High Performance Real-Time Image Processing and Simple Scripting

PubMed Central

Szécsi, László; Kacsó, Ágota; Zeck, Günther; Hantz, Péter

2017-01-01

Light stimulation with precise and complex spatial and temporal modulation is demanded by a series of research fields like visual neuroscience, optogenetics, ophthalmology, and visual psychophysics. We developed a user-friendly and flexible stimulus generating framework (GEARS GPU-based Eye And Retina Stimulation Software), which offers access to GPU computing power, and allows interactive modification of stimulus parameters during experiments. Furthermore, it has built-in support for driving external equipment, as well as for synchronization tasks, via USB ports. The use of GEARS does not require elaborate programming skills. The necessary scripting is visually aided by an intuitive interface, while the details of the underlying software and hardware components remain hidden. Internally, the software is a C++/Python hybrid using OpenGL graphics. Computations are performed on the GPU, and are defined in the GLSL shading language. However, all GPU settings, including the GPU shader programs, are automatically generated by GEARS. This is configured through a method encountered in game programming, which allows high flexibility: stimuli are straightforwardly composed using a broad library of basic components. Stimulus rendering is implemented solely in C++, therefore intermediary libraries for interfacing could be omitted. This enables the program to perform computationally demanding tasks like en-masse random number generation or real-time image processing by local and global operations. PMID:29326579

SERPent: Automated reduction and RFI-mitigation software for e-MERLIN

NASA Astrophysics Data System (ADS)

Peck, Luke W.; Fenech, Danielle M.

2013-08-01

The Scripted E-merlin Rfi-mitigation PipelinE for iNTerferometry (SERPent) is an automated reduction and RFI-mitigation procedure utilising the SumThreshold methodology (Offringa et al., 2010a), originally developed for the LOFAR pipeline. SERPent is written in the Parseltongue language enabling interaction with the Astronomical Image Processing Software (AIPS) program. Moreover, SERPent is a simple 'out of the box' Python script, which is easy to set up and is free of compilers. In addition to the flagging of RFI affected visibilities, the script also flags antenna zero-amplitude dropouts and Lovell telescope phase calibrator stationary scans inherent to the e-MERLIN system. Both the flagging and computational performances of SERPent are presented here, for e-MERLIN commissioning datasets for both L-band (1.3-1.8 GHz) and C-band (4-8 GHz) observations. RFI typically amounts to <20%-25% for the more problematic L-band observations and <5% for the generally RFI quieter C-band. The level of RFI detection and flagging is more accurate and delicate than visual manual flagging, with the output immediately ready for AIPS calibration. SERPent is fully parallelised and has been tested on a range of computing systems. The current flagging rate is at 110 GB day-1 on a 'high-end' computer (16 CPUs, 100 GB memory) which amounts to ˜6.9 GB CPU-1 day-1, with an expected increase in performance when e-MERLIN has completed its commissioning. The refining of automated reduction and calibration procedures is essential for the e-MERLIN legacy projects and future interferometers such as the SKA and the associated pathfinders (MeerKAT and ASKAP), where the vast data sizes (>TB) make traditional astronomer interactions unfeasible.

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)

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.

Knowledge-based engineering of a PLC controlled telescope

NASA Astrophysics Data System (ADS)

Pessemier, Wim; Raskin, Gert; Saey, Philippe; Van Winckel, Hans; Deconinck, Geert

2016-08-01

As the new control system of the Mercator Telescope is being finalized, we can review some technologies and design methodologies that are advantageous, despite their relative uncommonness in astronomical instrumentation. Particular for the Mercator Telescope is that it is controlled by a single high-end soft-PLC (Programmable Logic Controller). Using off-the-shelf components only, our distributed embedded system controls all subsystems of the telescope such as the pneumatic primary mirror support, the hydrostatic bearing, the telescope axes, the dome, the safety system, and so on. We show how real-time application logic can be written conveniently in typical PLC languages (IEC 61131-3) and in C++ (to implement the pointing kernel) using the commercial TwinCAT 3 programming environment. This software processes the inputs and outputs of the distributed system in real-time via an observatory-wide EtherCAT network, which is synchronized with high precision to an IEEE 1588 (PTP, Precision Time Protocol) time reference clock. Taking full advantage of the ability of soft-PLCs to run both real-time and non real-time software, the same device also hosts the most important user interfaces (HMIs or Human Machine Interfaces) and communication servers (OPC UA for process data, FTP for XML configuration data, and VNC for remote control). To manage the complexity of the system and to streamline the development process, we show how most of the software, electronics and systems engineering aspects of the control system have been modeled as a set of scripts written in a Domain Specific Language (DSL). When executed, these scripts populate a Knowledge Base (KB) which can be queried to retrieve specific information. By feeding the results of those queries to a template system, we were able to generate very detailed "browsable" web-based documentation about the system, but also PLC software code, Python client code, model verification reports, etc. The aim of this paper is to demonstrate the added value that technologies such as soft-PLCs and DSL-scripts and design methodologies such as knowledge-based engineering can bring to astronomical instrumentation.

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.

PyGOLD: a python based API for docking based virtual screening workflow generation.

PubMed

Patel, Hitesh; Brinkjost, Tobias; Koch, Oliver

2017-08-15

Molecular docking is one of the successful approaches in structure based discovery and development of bioactive molecules in chemical biology and medicinal chemistry. Due to the huge amount of computational time that is still required, docking is often the last step in a virtual screening approach. Such screenings are set as workflows spanned over many steps, each aiming at different filtering task. These workflows can be automatized in large parts using python based toolkits except for docking using the docking software GOLD. However, within an automated virtual screening workflow it is not feasible to use the GUI in between every step to change the GOLD configuration file. Thus, a python module called PyGOLD was developed, to parse, edit and write the GOLD configuration file and to automate docking based virtual screening workflows. The latest version of PyGOLD, its documentation and example scripts are available at: http://www.ccb.tu-dortmund.de/koch or http://www.agkoch.de. PyGOLD is implemented in Python and can be imported as a standard python module without any further dependencies. oliver.koch@agkoch.de, oliver.koch@tu-dortmund.de. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Production Management System for AMS Computing Centres

NASA Astrophysics Data System (ADS)

Choutko, V.; Demakov, O.; Egorov, A.; Eline, A.; Shan, B. S.; Shi, R.

2017-10-01

The Alpha Magnetic Spectrometer [1] (AMS) has collected over 95 billion cosmic ray events since it was installed on the International Space Station (ISS) on May 19, 2011. To cope with enormous flux of events, AMS uses 12 computing centers in Europe, Asia and North America, which have different hardware and software configurations. The centers are participating in data reconstruction, Monte-Carlo (MC) simulation [2]/Data and MC production/as well as in physics analysis. Data production management system has been developed to facilitate data and MC production tasks in AMS computing centers, including job acquiring, submitting, monitoring, transferring, and accounting. It was designed to be modularized, light-weighted, and easy-to-be-deployed. The system is based on Deterministic Finite Automaton [3] model, and implemented by script languages, Python and Perl, and the built-in sqlite3 database on Linux operating systems. Different batch management systems, file system storage, and transferring protocols are supported. The details of the integration with Open Science Grid are presented as well.

ATLAS tile calorimeter cesium calibration control and analysis software

NASA Astrophysics Data System (ADS)

Solovyanov, O.; Solodkov, A.; Starchenko, E.; Karyukhin, A.; Isaev, A.; Shalanda, N.

2008-07-01

An online control system to calibrate and monitor ATLAS Barrel hadronic calorimeter (TileCal) with a movable radioactive source, driven by liquid flow, is described. To read out and control the system an online software has been developed, using ATLAS TDAQ components like DVS (Diagnostic and Verification System) to verify the hardware before running, IS (Information Server) for data and status exchange between networked computers, and other components like DDC (DCS to DAQ Connection), to connect to PVSS-based slow control systems of Tile Calorimeter, high voltage and low voltage. A system of scripting facilities, based on Python language, is used to handle all the calibration and monitoring processes from hardware perspective to final data storage, including various abnormal situations. A QT based graphical user interface to display the status of the calibration system during the cesium source scan is described. The software for analysis of the detector response, using online data, is discussed. Performance of the system and first experience from the ATLAS pit are presented.

Conversion of the agent-oriented domain-specific language ALAS into JavaScript

NASA Astrophysics Data System (ADS)

Sredojević, Dejan; Vidaković, Milan; Okanović, Dušan; Mitrović, Dejan; Ivanović, Mirjana

2016-06-01

This paper shows generation of JavaScript code from code written in agent-oriented domain-specific language ALAS. ALAS is an agent-oriented domain-specific language for writing software agents that are executed within XJAF middleware. Since the agents can be executed on various platforms, they must be converted into a language of the target platform. We also try to utilize existing tools and technologies to make the whole conversion process as simple as possible, as well as faster and more efficient. We use the Xtext framework that is compatible with Java to implement ALAS infrastructure - editor and code generator. Since Xtext supports Java, generation of Java code from ALAS code is straightforward. To generate a JavaScript code that will be executed within the target JavaScript XJAF implementation, Google Web Toolkit (GWT) is used.

BioC implementations in Go, Perl, Python and Ruby.

PubMed

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

2014-01-01

As part of a communitywide effort for evaluating text mining and information extraction systems applied to the biomedical domain, BioC is focused on the goal of interoperability, currently a major barrier to wide-scale adoption of text mining tools. BioC is a simple XML format, specified by DTD, for exchanging data for biomedical natural language processing. With initial implementations in C++ and Java, BioC provides libraries of code for reading and writing BioC text documents and annotations. We extend BioC to Perl, Python, Go and Ruby. We used SWIG to extend the C++ implementation for Perl and one Python implementation. A second Python implementation and the Ruby implementation use native data structures and libraries. BioC is also implemented in the Google language Go. BioC modules are functional in all of these languages, which can facilitate text mining tasks. BioC implementations are freely available through the BioC site: http://bioc.sourceforge.net. Database URL: http://bioc.sourceforge.net/ Published by Oxford University Press 2014. This work is written by US Government employees and is in the public domain in the US.

Cognate Effects in Picture Naming: Does Cross-Language Activation Survive a Change of Script?

ERIC Educational Resources Information Center

Hoshino, Noriko; Kroll, Judith F.

2008-01-01

Bilinguals are faster to name a picture in one language when the picture's name is a cognate in the other language. We asked whether cognate facilitation in picture naming would be obtained for bilinguals whose two languages differ in script. Spanish-English and Japanese-English bilinguals named cognate and noncognate pictures in English, their…

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.

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.

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.

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.

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.

Simulation of Weld Mechanical Behavior to Include Welding-Induced Residual Stress and Distortion: Coupling of SYSWELD and Abaqus Codes

DTIC Science & Technology

2015-11-01

induced residual stresses and distortions from weld simulations in the SYSWELD software code in structural Finite Element Analysis ( FEA ) simulations...performed in the Abaqus FEA code is presented. The translation of these results is accomplished using a newly developed Python script. Full details of...Local Weld Model in Structural FEA ....................................................15 CONCLUSIONS

Maestro Workflow Conductor

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

Di Natale, Francesco

2017-06-01

MaestroWF is a Python tool and software package for loading YAML study specifications that represents a simulation campaign. The package is capable of parameterizing a study, pulling dependencies automatically, formatting output directories, and managing the flow and execution of the campaign. MaestroWF also provides a set of abstracted objects that can also be used to develop user specific scripts for launching simulation campaigns.

Graph Visualization for RDF Graphs with SPARQL-EndPoints

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

Sukumar, Sreenivas R; Bond, Nathaniel

2014-07-11

RDF graphs are hard to visualize as triples. This software module is a web interface that connects to a SPARQL endpoint and retrieves graph data that the user can explore interactively and seamlessly. The software written in python and JavaScript has been tested to work on screens as little as the smart phones to large screens such as EVEREST.

Factors Affecting Energy Absorption of a Plate during Shock Wave Impact Using a Damage Material Model

DTIC Science & Technology

2010-08-07

51 5.3.2 Abaqus VDLOAD Subroutine ............................................. 55 VI. INTERPRETATION OF RESULTS AND DISCUSSION...VDLOAD SUBROUTINE ........................................................... 91 C. PYTHON SCRIPT TO CONVERT ABAQUS INPUT FILE TO LS-DYNA INPUT FILE...all of the simulations, which are the pressures applied from the Abaqus /Explicit VDLOAD subroutine . The entire model 22 including the boundary

The effect of written text on comprehension of spoken English as a foreign language.

PubMed

Diao, Yali; Chandler, Paul; Sweller, John

2007-01-01

Based on cognitive load theory, this study investigated the effect of simultaneous written presentations on comprehension of spoken English as a foreign language. Learners' language comprehension was compared while they used 3 instructional formats: listening with auditory materials only, listening with a full, written script, and listening with simultaneous subtitled text. Listening with the presence of a script and subtitles led to better understanding of the scripted and subtitled passage but poorer performance on a subsequent auditory passage than listening with the auditory materials only. These findings indicated that where the intention was learning to listen, the use of a full script or subtitles had detrimental effects on the construction and automation of listening comprehension schemas.

Neuroanatomical affiliation visualization-interface system.

PubMed

Palombi, Olivier; Shin, Jae-Won; Watson, Charles; Paxinos, George

2006-01-01

A number of knowledge management systems have been developed to allow users to have access to large quantity of neuroanatomical data. The advent of three-dimensional (3D) visualization techniques allows users to interact with complex 3D object. In order to better understand the structural and functional organization of the brain, we present Neuroanatomical Affiliations Visualization-Interface System (NAVIS) as the original software to see brain structures and neuroanatomical affiliations in 3D. This version of NAVIS has made use of the fifth edition of "The Rat Brain in Stereotaxic coordinates" (Paxinos and Watson, 2005). The NAVIS development environment was based on the scripting language name Python, using visualization toolkit (VTK) as 3D-library and wxPython for the graphic user interface. The following manuscript is focused on the nucleus of the solitary tract (Sol) and the set of affiliated structures in the brain to illustrate the functionality of NAVIS. The nucleus of the Sol is the primary relay center of visceral and taste information, and consists of 14 distinct subnuclei that differ in cytoarchitecture, chemoarchitecture, connections, and function. In the present study, neuroanatomical projection data of the rat Sol were collected from selected literature in PubMed since 1975. Forty-nine identified projection data of Sol were inserted in NAVIS. The standard XML format used as an input for affiliation data allows NAVIS to update data online and/or allows users to manually change or update affiliation data. NAVIS can be extended to nuclei other than Sol.

CMS Configuration Editor: GUI based application for user analysis job

NASA Astrophysics Data System (ADS)

de Cosa, A.

2011-12-01

We present the user interface and the software architecture of the Configuration Editor for the CMS experiment. The analysis workflow is organized in a modular way integrated within the CMS framework that organizes in a flexible way user analysis code. The Python scripting language is adopted to define the job configuration that drives the analysis workflow. It could be a challenging task for users, especially for newcomers, to develop analysis jobs managing the configuration of many required modules. For this reason a graphical tool has been conceived in order to edit and inspect configuration files. A set of common analysis tools defined in the CMS Physics Analysis Toolkit (PAT) can be steered and configured using the Config Editor. A user-defined analysis workflow can be produced starting from a standard configuration file, applying and configuring PAT tools according to the specific user requirements. CMS users can adopt this tool, the Config Editor, to create their analysis visualizing in real time which are the effects of their actions. They can visualize the structure of their configuration, look at the modules included in the workflow, inspect the dependences existing among the modules and check the data flow. They can visualize at which values parameters are set and change them according to what is required by their analysis task. The integration of common tools in the GUI needed to adopt an object-oriented structure in the Python definition of the PAT tools and the definition of a layer of abstraction from which all PAT tools inherit.

An OpenMI Implementation of a Water Resources System using Simple Script Wrappers

NASA Astrophysics Data System (ADS)

Steward, D. R.; Aistrup, J. A.; Kulcsar, L.; Peterson, J. M.; Welch, S. M.; Andresen, D.; Bernard, E. A.; Staggenborg, S. A.; Bulatewicz, T.

2013-12-01

This team has developed an adaption of the Open Modelling Interface (OpenMI) that utilizes Simple Script Wrappers. Code is made OpenMI compliant through organization within three modules that initialize, perform time steps, and finalize results. A configuration file is prepared that specifies variables a model expects to receive as input and those it will make available as output. An example is presented for groundwater, economic, and agricultural production models in the High Plains Aquifer region of Kansas. Our models use the programming environments in Scilab and Matlab, along with legacy Fortran code, and our Simple Script Wrappers can also use Python. These models are collectively run within this interdisciplinary framework from initial conditions into the future. It will be shown that by applying model constraints to one model, the impact may be accessed on changes to the water resources system.

NanoPack: visualizing and processing long read sequencing data.

PubMed

De Coster, Wouter; D'Hert, Svenn; Schultz, Darrin T; Cruts, Marc; Van Broeckhoven, Christine

2018-03-14

Here we describe NanoPack, a set of tools developed for visualization and processing of long read sequencing data from Oxford Nanopore Technologies and Pacific Biosciences. The NanoPack tools are written in Python3 and released under the GNU GPL3.0 License. The source code can be found at https://github.com/wdecoster/nanopack, together with links to separate scripts and their documentation. The scripts are compatible with Linux, Mac OS and the MS Windows 10 subsystem for Linux and are available as a graphical user interface, a web service at http://nanoplot.bioinf.be and command line tools. wouter.decoster@molgen.vib-ua.be. Supplementary tables and figures are available at Bioinformatics online.

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

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

NASA Astrophysics Data System (ADS)

Merticariu, Vlad; Misev, Dimitar; Baumann, Peter

2017-04-01

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

Simulation for Dynamic Situation Awareness and Prediction III

DTIC Science & Technology

2010-03-01

source Java ™ library for capturing and sending network packets; 4) Groovy – an open source, Java -based scripting language (version 1.6 or newer). Open...DMOTH Analyzer application. Groovy is an open source dynamic scripting language for the Java Virtual Machine. It is consistent with Java syntax...between temperature, pressure, wind and relative humidity, and 3) a precipitation editing algorithm. The Editor can be used to prepare scripted changes

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.

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

ROSSTEP v1.3

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

Allevato, Adam

2016-07-21

ROSSTEP is a system for sequentially running roslaunch, rosnode, and bash scripts automatically, for use in Robot Operating System (ROS) applications. The system consists of YAML files which define actions and conditions. A python file parses the code and runs actions sequentially using the sys and subprocess python modules. Between actions, it uses various ROS-based code to check conditions required to proceed, and only moves on to the next action when all the necessary conditions have been met. Included is rosstep-creator, a QT application designed to create the YAML files required for ROSSTEP. It has a nearly one-to-one mapping frommore » interface elements to YAML output, and serves as a convenient GUI for working with the ROSSTEP system.« less

Tools for Integrating Data Access from the IRIS DMC into Research Workflows

NASA Astrophysics Data System (ADS)

Reyes, C. G.; Suleiman, Y. Y.; Trabant, C.; Karstens, R.; Weertman, B. R.

2012-12-01

Web service interfaces at the IRIS Data Management Center (DMC) provide access to a vast archive of seismological and related geophysical data. These interfaces are designed to easily incorporate data access into data processing workflows. Examples of data that may be accessed include: time series data, related metadata, and earthquake information. The DMC has developed command line scripts, MATLAB® interfaces and a Java library to support a wide variety of data access needs. Users of these interfaces do not need to concern themselves with web service details, networking, or even (in most cases) data conversion. Fetch scripts allow access to the DMC archive and are a comfortable fit for command line users. These scripts are written in Perl and are well suited for automation and integration into existing workflows on most operating systems. For metdata and event information, the Fetch scripts even parse the returned data into simple text summaries. The IRIS Java Web Services Library (IRIS-WS Library) allows Java developers the ability to create programs that access the DMC archives seamlessly. By returning the data and information as native Java objects the Library insulates the developer from data formats, network programming and web service details. The MATLAB interfaces leverage this library to allow users access to the DMC archive directly from within MATLAB (r2009b or newer), returning data into variables for immediate use. Data users and research groups are developing other toolkits that use the DMC's web services. Notably, the ObsPy framework developed at LMU Munich is a Python Toolbox that allows seamless access to data and information via the DMC services. Another example is the MATLAB-based GISMO and Waveform Suite developments that can now access data via web services. In summary, there now exist a host of ways that researchers can bring IRIS DMC data directly into their workflows. MATLAB users can use irisFetch.m, command line users can use the various Fetch scripts, Java users can use the IRIS-WS library, and Python users may request data through ObsPy. To learn more about any of these clients see http://www.iris.edu/ws/wsclients/.

HydroDesktop as a Community Designed and Developed Resource for Hydrologic Data Discovery and Analysis

NASA Astrophysics Data System (ADS)

Ames, D. P.

2013-12-01

As has been seen in other informatics fields, well-documented and appropriately licensed open source software tools have the potential to significantly increase both opportunities and motivation for inter-institutional science and technology collaboration. The CUAHSI HIS (and related HydroShare) projects have aimed to foster such activities in hydrology resulting in the development of many useful community software components including the HydroDesktop software application. HydroDesktop is an open source, GIS-based, scriptable software application for discovering data on the CUAHSI Hydrologic Information System and related resources. It includes a well-defined plugin architecture and interface to allow 3rd party developers to create extensions and add new functionality without requiring recompiling of the full source code. HydroDesktop is built in the C# programming language and uses the open source DotSpatial GIS engine for spatial data management. Capabilities include data search, discovery, download, visualization, and export. An extension that integrates the R programming language with HydroDesktop provides scripting and data automation capabilities and an OpenMI plugin provides the ability to link models. Current revision and updates to HydroDesktop include migration of core business logic to cross platform, scriptable Python code modules that can be executed in any operating system or linked into other software front-end applications.

META-X Design Flow Tools

DTIC Science & Technology

2013-04-01

Forces can be computed at specific angular positions, and geometrical parameters can be evaluated. Much higher resolution models are required, along...composition engines (C#, C++, Python, Java ) Desert operates on the CyPhy model, converting from a design space alternative structure to a set of design...consists of scripts to execute dymola, post-processing of results to create metrics, and general management of the job sequence. An earlier version created

autokonf - A Configuration Script Generator Implemented in Perl

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

Reus, J F

This paper discusses configuration scripts in general and the scripting language issues involved. A brief description of GNU autoconf is provided along with a contrasting overview of autokonf, a configuration script generator implemented in Perl, whose macros are implemented in Perl, generating a configuration script in Perl. It is very portable, easily extensible, and readily mastered.

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

PubMed

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

2018-03-19

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

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.

A Python Interface for the Dakota Iterative Systems Analysis Toolkit

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

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

Embracing Open Software Development in Solar Physics

NASA Astrophysics Data System (ADS)

Hughitt, V. K.; Ireland, J.; Christe, S.; Mueller, D.

2012-12-01

We discuss two ongoing software projects in solar physics that have adopted best practices of the open source software community. The first, the Helioviewer Project, is a powerful data visualization tool which includes online and Java interfaces inspired by Google Maps (tm). This effort allows users to find solar features and events of interest, and download the corresponding data. Having found data of interest, the user now has to analyze it. The dominant solar data analysis platform is an open-source library called SolarSoft (SSW). Although SSW itself is open-source, the programming language used is IDL, a proprietary language with licensing costs that are prohibative for many institutions and individuals. SSW is composed of a collection of related scripts written by missions and individuals for solar data processing and analysis, without any consistent data structures or common interfaces. Further, at the time when SSW was initially developed, many of the best software development processes of today (mirrored and distributed version control, unit testing, continuous integration, etc.) were not standard, and have not since been adopted. The challenges inherent in developing SolarSoft led to a second software project known as SunPy. SunPy is an open-source Python-based library which seeks to create a unified solar data analysis environment including a number of core datatypes such as Maps, Lightcurves, and Spectra which have consistent interfaces and behaviors. By taking advantage of the large and sophisticated body of scientific software already available in Python (e.g. SciPy, NumPy, Matplotlib), and by adopting many of the best practices refined in open-source software development, SunPy has been able to develop at a very rapid pace while still ensuring a high level of reliability. The Helioviewer Project and SunPy represent two pioneering technologies in solar physics - simple yet flexible data visualization and a powerful, new data analysis environment. We discuss the development of both these efforts and how they are beginning to influence the solar physics community.

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.

Moderate-resolution sea surface temperature data for the nearshore North Pacific

USGS Publications Warehouse

Payne, Meredith C.; Reusser, Deborah A.; Lee, Henry; Brown, Cheryl A.

2011-01-01

Coastal sea surface temperature (SST) is an important environmental characteristic in determining the suitability of habitat for nearshore marine and estuarine organisms. This publication describes and provides access to an easy-to-use coastal SST dataset for ecologists, biogeographers, oceanographers, and other scientists conducting research on nearshore marine habitats or processes. The data cover the Temperate Northern Pacific Ocean as defined by the 'Marine Ecosystems of the World' (MEOW) biogeographic schema developed by The Nature Conservancy. The spatial resolution of the SST data is 4-km grid cells within 20 km of the shore. The data span a 29-year period - from September 1981 to December 2009. These SST data were derived from Advanced Very High Resolution Radiometer (AVHRR) instrument measurements compiled into monthly means as part of the Pathfinder versions 5.0 and 5.1 (PFSST V50 and V51) Project. The processing methods used to transform the data from their native Hierarchical Data Format Scientific Data Set (HDF SDS) to georeferenced, spatial datasets capable of being read into geographic information systems (GIS) software are explained. In addition, links are provided to examples of scripts involved in the data processing steps. The scripts were written in the Python programming language, which is supported by ESRI's ArcGIS version 9 or later. The processed data files are also provided in text (.csv) and Access 2003 Database (.mdb) formats. All data except the raster files include attributes identifying realm, province, and ecoregion as defined by the MEOW classification schema.

MARATHI READER.

ERIC Educational Resources Information Center

APTE, MAHADEO L.

THE MARATHI LANGUAGE, SPOKEN IN BOMBAY STATE, INDIA, IS WRITTEN IN THE SCRIPT TRADITIONALLY KNOWN AS THE DEVANAGARI SCRIPT. THE SCRIPT IS SYLLABIC IN NATURE, EACH CHARACTER OR LETTER REPRESENTS A SYLLABLE RATHER THAN A CONSONANT OR A VOWEL ALONE. THE MARATHI ALPHABET IS THE ADOPTION OF THE DEVANAGARI SCRIPT WITH A FEW CHANGES AND INNOVATIONS. A…

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

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

Globalisation, Language Planning and Language Rights: The Recent Script Policy Measures Adopted by Japan and the People's Republic of China

ERIC Educational Resources Information Center

Premaratne, Dilhara D.

2015-01-01

In 2009, two significant script policy measures were adopted by Japan and the People's Republic of China (China hereafter), both as a response to national language needs triggered by globalisation. However, the measures chosen by the two countries were very different, Japan choosing to increase and China choosing to standardise the Chinese…

The Influence of Peer Models on the Play Scripts of Children with Specific Language Impairment.

ERIC Educational Resources Information Center

Robertson, Shari Brand; Weismer, Susan Ellis

1997-01-01

Two studies found positive effects of peer modeling upon the play scripts of preschool children with specific language impairment (SLI). The first study involved dyadic play sessions in which children with SLI were paired with a normal language peer model. The second study compared dyads of either two SLI children or one SLI child and one normal…

Development of a Web-Based Distributed Interactive Simulation (DIS) Environment Using JavaScript

DTIC Science & Technology

2014-09-01

scripting that let users change or interact with web content depending on user input, which is in contrast with server-side scripts such as PHP, Java and...transfer, DIS usually broadcasts or multicasts its PDUs based on UDP socket. 3. JavaScript JavaScript is the scripting language of the web, and all...IDE) for developing desktop, mobile and web applications with JAVA , C++, HTML5, JavaScript and more. b. Framework The DIS implementation of

Teaching CS1 with Python GUI Game Programming

NASA Astrophysics Data System (ADS)

Wang, Hong

2010-06-01

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

Wrapping Python around MODFLOW/MT3DMS based groundwater models

NASA Astrophysics Data System (ADS)

Post, V.

2008-12-01

Numerical models that simulate groundwater flow and solute transport require a great amount of input data that is often organized into different files. A large proportion of the input data consists of spatially-distributed model parameters. The model output consists of a variety data such as heads, fluxes and concentrations. Typically all files have different formats. Consequently, preparing input and managing output is a complex and error-prone task. Proprietary software tools are available that facilitate the preparation of input files and analysis of model outcomes. The use of such software may be limited if it does not support all the features of the groundwater model or when the costs of such tools are prohibitive. Therefore a Python library was developed that contains routines to generate input files and process output files of MODFLOW/MT3DMS based models. The library is freely available and has an open structure so that the routines can be customized and linked into other scripts and libraries. The current set of functions supports the generation of input files for MODFLOW and MT3DMS, including the capability to read spatially-distributed input parameters (e.g. hydraulic conductivity) from PNG files. Both ASCII and binary output files can be read efficiently allowing for visualization of, for example, solute concentration patterns in contour plots with superimposed flow vectors using matplotlib. Series of contour plots are then easily saved as an animation. The subroutines can also be used within scripts to calculate derived quantities such as the mass of a solute within a particular region of the model domain. Using Python as a wrapper around groundwater models provides an efficient and flexible way of processing input and output data, which is not constrained by limitations of third-party products.

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

PubMed Central

Hull, Michael J.; Willshaw, David J.

2014-01-01

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

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

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.

One-dimensional statistical parametric mapping in Python.

PubMed

Pataky, Todd C

2012-01-01

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

A Python Script for Aligning the STIS Echelle Blaze Function

NASA Astrophysics Data System (ADS)

Baer, Malinda; Proffitt, Charles R.; Lockwood, Sean A.

2018-01-01

Accurate flux calibration for the STIS echelle modes is heavily dependent on the proper alignment of the blaze function for each spectral order. However, due to changes in the instrument alignment over time and between exposures, the blaze function can shift in wavelength. This may result in flux calibration inconsistencies of up to 10%. We present the stisblazefix Python module as a tool for STIS users to correct their echelle spectra. The stisblazefix module assumes that the error in the blaze alignment is a linear function of spectral order, and finds the set of shifts that minimizes the flux inconsistencies in the overlap between spectral orders. We discuss the uses and limitations of this tool, and show that its use can provide significant improvements to the default pipeline flux calibration for many observations.

Visualization and processing of computed solid-state NMR parameters: MagresView and MagresPython.

PubMed

Sturniolo, Simone; Green, Timothy F G; Hanson, Robert M; Zilka, Miri; Refson, Keith; Hodgkinson, Paul; Brown, Steven P; Yates, Jonathan R

2016-09-01

We introduce two open source tools to aid the processing and visualisation of ab-initio computed solid-state NMR parameters. The Magres file format for computed NMR parameters (as implemented in CASTEP v8.0 and QuantumEspresso v5.0.0) is implemented. MagresView is built upon the widely used Jmol crystal viewer, and provides an intuitive environment to display computed NMR parameters. It can provide simple pictorial representation of one- and two-dimensional NMR spectra as well as output a selected spin-system for exact simulations with dedicated spin-dynamics software. MagresPython provides a simple scripting environment to manipulate large numbers of computed NMR parameters to search for structural correlations. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.

Formatting scripts with computers and Extended BASIC.

PubMed

Menning, C B

1984-02-01

A computer program, written in the language of Extended BASIC, is presented which enables scripts, for educational media, to be quickly written in a nearly unformatted style. From the resulting script file, stored on magnetic tape or disk, the computer program formats the script into either a storyboard , a presentation, or a narrator 's script. Script headings and page and paragraph numbers are automatic features in the word processing. Suggestions are given for making personal modifications to the computer program.

Snowflake: A Lightweight Portable Stencil DSL

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

Zhang, Nathan; Driscoll, Michael; Markley, Charles

Stencil computations are not well optimized by general-purpose production compilers and the increased use of multicore, manycore, and accelerator-based systems makes the optimization problem even more challenging. In this paper we present Snowflake, a Domain Specific Language (DSL) for stencils that uses a 'micro-compiler' approach, i.e., small, focused, domain-specific code generators. The approach is similar to that used in image processing stencils, but Snowflake handles the much more complex stencils that arise in scientific computing, including complex boundary conditions, higher-order operators (larger stencils), higher dimensions, variable coefficients, non-unit-stride iteration spaces, and multiple input or output meshes. Snowflake is embedded inmore » the Python language, allowing it to interoperate with popular scientific tools like SciPy and iPython; it also takes advantage of built-in Python libraries for powerful dependence analysis as part of a just-in-time compiler. We demonstrate the power of the Snowflake language and the micro-compiler approach with a complex scientific benchmark, HPGMG, that exercises the generality of stencil support in Snowflake. By generating OpenMP comparable to, and OpenCL within a factor of 2x of hand-optimized HPGMG, Snowflake demonstrates that a micro-compiler can support diverse processor architectures and is performance-competitive whilst preserving a high-level Python implementation.« less

Snowflake: A Lightweight Portable Stencil DSL

DOE PAGES

Zhang, Nathan; Driscoll, Michael; Markley, Charles; ...

2017-05-01

Stencil computations are not well optimized by general-purpose production compilers and the increased use of multicore, manycore, and accelerator-based systems makes the optimization problem even more challenging. In this paper we present Snowflake, a Domain Specific Language (DSL) for stencils that uses a 'micro-compiler' approach, i.e., small, focused, domain-specific code generators. The approach is similar to that used in image processing stencils, but Snowflake handles the much more complex stencils that arise in scientific computing, including complex boundary conditions, higher-order operators (larger stencils), higher dimensions, variable coefficients, non-unit-stride iteration spaces, and multiple input or output meshes. Snowflake is embedded inmore » the Python language, allowing it to interoperate with popular scientific tools like SciPy and iPython; it also takes advantage of built-in Python libraries for powerful dependence analysis as part of a just-in-time compiler. We demonstrate the power of the Snowflake language and the micro-compiler approach with a complex scientific benchmark, HPGMG, that exercises the generality of stencil support in Snowflake. By generating OpenMP comparable to, and OpenCL within a factor of 2x of hand-optimized HPGMG, Snowflake demonstrates that a micro-compiler can support diverse processor architectures and is performance-competitive whilst preserving a high-level Python implementation.« less

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.

PyNeb: a new tool for analyzing emission lines. I. Code description and validation of results

NASA Astrophysics Data System (ADS)

Luridiana, V.; Morisset, C.; Shaw, R. A.

2015-01-01

Analysis of emission lines in gaseous nebulae yields direct measures of physical conditions and chemical abundances and is the cornerstone of nebular astrophysics. Although the physical problem is conceptually simple, its practical complexity can be overwhelming since the amount of data to be analyzed steadily increases; furthermore, results depend crucially on the input atomic data, whose determination also improves each year. To address these challenges we created PyNeb, an innovative code for analyzing emission lines. PyNeb computes physical conditions and ionic and elemental abundances and produces both theoretical and observational diagnostic plots. It is designed to be portable, modular, and largely customizable in aspects such as the atomic data used, the format of the observational data to be analyzed, and the graphical output. It gives full access to the intermediate quantities of the calculation, making it possible to write scripts tailored to the specific type of analysis one wants to carry out. In the case of collisionally excited lines, PyNeb works by solving the equilibrium equations for an n-level atom; in the case of recombination lines, it works by interpolation in emissivity tables. The code offers a choice of extinction laws and ionization correction factors, which can be complemented by user-provided recipes. It is entirely written in the python programming language and uses standard python libraries. It is fully vectorized, making it apt for analyzing huge amounts of data. The code is stable and has been benchmarked against IRAF/NEBULAR. It is public, fully documented, and has already been satisfactorily used in a number of published papers.

SeqDepot: streamlined database of biological sequences and precomputed features.

PubMed

Ulrich, Luke E; Zhulin, Igor B

2014-01-15

Assembling and/or producing integrated knowledge of sequence features continues to be an onerous and redundant task despite a large number of existing resources. We have developed SeqDepot-a novel database that focuses solely on two primary goals: (i) assimilating known primary sequences with predicted feature data and (ii) providing the most simple and straightforward means to procure and readily use this information. Access to >28.5 million sequences and 300 million features is provided through a well-documented and flexible RESTful interface that supports fetching specific data subsets, bulk queries, visualization and searching by MD5 digests or external database identifiers. We have also developed an HTML5/JavaScript web application exemplifying how to interact with SeqDepot and Perl/Python scripts for use with local processing pipelines. Freely available on the web at http://seqdepot.net/. RESTaccess via http://seqdepot.net/api/v1. Database files and scripts maybe downloaded from http://seqdepot.net/download.

Point Cloud Based Change Detection - an Automated Approach for Cloud-based Services

NASA Astrophysics Data System (ADS)

Collins, Patrick; Bahr, Thomas

2016-04-01

The fusion of stereo photogrammetric point clouds with LiDAR data or terrain information derived from SAR interferometry has a significant potential for 3D topographic change detection. In the present case study latest point cloud generation and analysis capabilities are used to examine a landslide that occurred in the village of Malin in Maharashtra, India, on 30 July 2014, and affected an area of ca. 44.000 m2. It focuses on Pléiades high resolution satellite imagery and the Airbus DS WorldDEMTM as a product of the TanDEM-X mission. This case study was performed using the COTS software package ENVI 5.3. Integration of custom processes and automation is supported by IDL (Interactive Data Language). Thus, ENVI analytics is running via the object-oriented and IDL-based ENVITask API. The pre-event topography is represented by the WorldDEMTM product, delivered with a raster of 12 m x 12 m and based on the EGM2008 geoid (called pre-DEM). For the post-event situation a Pléiades 1B stereo image pair of the AOI affected was obtained. The ENVITask "GeneratePointCloudsByDenseImageMatching" was implemented to extract passive point clouds in LAS format from the panchromatic stereo datasets: • A dense image-matching algorithm is used to identify corresponding points in the two images. • A block adjustment is applied to refine the 3D coordinates that describe the scene geometry. • Additionally, the WorldDEMTM was input to constrain the range of heights in the matching area, and subsequently the length of the epipolar line. The "PointCloudFeatureExtraction" task was executed to generate the post-event digital surface model from the photogrammetric point clouds (called post-DEM). Post-processing consisted of the following steps: • Adding the geoid component (EGM 2008) to the post-DEM. • Pre-DEM reprojection to the UTM Zone 43N (WGS-84) coordinate system and resizing. • Subtraction of the pre-DEM from the post-DEM. • Filtering and threshold based classification of the DEM difference to analyze the surface changes in 3D. The automated point cloud generation and analysis introduced here can be embedded in virtually any existing geospatial workflow for operational applications. Three integration options were implemented in this case study: • Integration within any ArcGIS environment whether deployed on the desktop, in the cloud, or online. Execution uses a customized ArcGIS script tool. A Python script file retrieves the parameters from the user interface and runs the precompiled IDL code. That IDL code is used to interface between the Python script and the relevant ENVITasks. • Publishing the point cloud processing tasks as services via the ENVI Services Engine (ESE). ESE is a cloud-based image analysis solution to publish and deploy advanced ENVI image and data analytics to existing enterprise infrastructures. For this purpose the entire IDL code can be capsuled in a single ENVITask. • Integration in an existing geospatial workflow using the Python-to-IDL Bridge. This mechanism allows calling IDL code within Python on a user-defined platform. The results of this case study allow a 3D estimation of the topographic changes within the tectonically active and anthropogenically invaded Malin area after the landslide event. Accordingly, the point cloud analysis was correlated successfully with modelled displacement contours of the slope. Based on optical satellite imagery, such point clouds of high precision and density distribution can be obtained in a few minutes to support the operational monitoring of landslide processes.

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

NASA Astrophysics Data System (ADS)

Lin, J. W. B.

2015-12-01

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

Visualization of historical data for the ATLAS detector controls - DDV

NASA Astrophysics Data System (ADS)

Maciejewski, J.; Schlenker, S.

2017-10-01

The ATLAS experiment is one of four detectors located on the Large Hardon Collider (LHC) based at CERN. Its detector control system (DCS) stores the slow control data acquired within the back-end of distributed WinCC OA applications, which enables the data to be retrieved for future analysis, debugging and detector development in an Oracle relational database. The ATLAS DCS Data Viewer (DDV) is a client-server application providing access to the historical data outside of the experiment network. The server builds optimized SQL queries, retrieves the data from the database and serves it to the clients via HTTP connections. The server also implements protection methods to prevent malicious use of the database. The client is an AJAX-type web application based on the Vaadin (framework build around the Google Web Toolkit (GWT)) which gives users the possibility to access the data with ease. The DCS metadata can be selected using a column-tree navigation or a search engine supporting regular expressions. The data is visualized by a selection of output modules such as a java script value-over time plots or a lazy loading table widget. Additional plugins give the users the possibility to retrieve the data in ROOT format or as an ASCII file. Control system alarms can also be visualized in a dedicated table if necessary. Python mock-up scripts can be generated by the client, allowing the user to query the pythonic DDV server directly, such that the users can embed the scripts into more complex analysis programs. Users are also able to store searches and output configurations as XML on the server to share with others via URL or to embed in HTML.

Python Executable Script for Estimating Two Effective Parameters to Individualize Brain-Computer Interfaces: Individual Alpha Frequency and Neurophysiological Predictor.

PubMed

Alonso-Valerdi, Luz María

2016-01-01

A brain-computer interface (BCI) aims to establish communication between the human brain and a computing system so as to enable the interaction between an individual and his environment without using the brain output pathways. Individuals control a BCI system by modulating their brain signals through mental tasks (e.g., motor imagery or mental calculation) or sensory stimulation (e.g., auditory, visual, or tactile). As users modulate their brain signals at different frequencies and at different levels, the appropriate characterization of those signals is necessary. The modulation of brain signals through mental tasks is furthermore a skill that requires training. Unfortunately, not all the users acquire such skill. A practical solution to this problem is to assess the user probability of controlling a BCI system. Another possible solution is to set the bandwidth of the brain oscillations, which is highly sensitive to the users' age, sex and anatomy. With this in mind, NeuroIndex, a Python executable script, estimates a neurophysiological prediction index and the individual alpha frequency (IAF) of the user in question. These two parameters are useful to characterize the user EEG signals, and decide how to go through the complex process of adapting the human brain and the computing system on the basis of previously proposed methods. NeuroIndeX is not only the implementation of those methods, but it also complements the methods each other and provides an alternative way to obtain the prediction parameter. However, an important limitation of this application is its dependency on the IAF value, and some results should be interpreted with caution. The script along with some electroencephalographic datasets are available on a GitHub repository in order to corroborate the functionality and usability of this application.

Python Executable Script for Estimating Two Effective Parameters to Individualize Brain-Computer Interfaces: Individual Alpha Frequency and Neurophysiological Predictor

PubMed Central

Alonso-Valerdi, Luz María

2016-01-01

A brain-computer interface (BCI) aims to establish communication between the human brain and a computing system so as to enable the interaction between an individual and his environment without using the brain output pathways. Individuals control a BCI system by modulating their brain signals through mental tasks (e.g., motor imagery or mental calculation) or sensory stimulation (e.g., auditory, visual, or tactile). As users modulate their brain signals at different frequencies and at different levels, the appropriate characterization of those signals is necessary. The modulation of brain signals through mental tasks is furthermore a skill that requires training. Unfortunately, not all the users acquire such skill. A practical solution to this problem is to assess the user probability of controlling a BCI system. Another possible solution is to set the bandwidth of the brain oscillations, which is highly sensitive to the users' age, sex and anatomy. With this in mind, NeuroIndex, a Python executable script, estimates a neurophysiological prediction index and the individual alpha frequency (IAF) of the user in question. These two parameters are useful to characterize the user EEG signals, and decide how to go through the complex process of adapting the human brain and the computing system on the basis of previously proposed methods. NeuroIndeX is not only the implementation of those methods, but it also complements the methods each other and provides an alternative way to obtain the prediction parameter. However, an important limitation of this application is its dependency on the IAF value, and some results should be interpreted with caution. The script along with some electroencephalographic datasets are available on a GitHub repository in order to corroborate the functionality and usability of this application. PMID:27445783

EMAN2: an extensible image processing suite for electron microscopy.

PubMed

Tang, Guang; Peng, Liwei; Baldwin, Philip R; Mann, Deepinder S; Jiang, Wen; Rees, Ian; Ludtke, Steven J

2007-01-01

EMAN is a scientific image processing package with a particular focus on single particle reconstruction from transmission electron microscopy (TEM) images. It was first released in 1999, and new versions have been released typically 2-3 times each year since that time. EMAN2 has been under development for the last two years, with a completely refactored image processing library, and a wide range of features to make it much more flexible and extensible than EMAN1. The user-level programs are better documented, more straightforward to use, and written in the Python scripting language, so advanced users can modify the programs' behavior without any recompilation. A completely rewritten 3D transformation class simplifies translation between Euler angle standards and symmetry conventions. The core C++ library has over 500 functions for image processing and associated tasks, and it is modular with introspection capabilities, so programmers can add new algorithms with minimal effort and programs can incorporate new capabilities automatically. Finally, a flexible new parallelism system has been designed to address the shortcomings in the rigid system in EMAN1.

Universal electronics for miniature and automated chemical assays.

PubMed

Urban, Pawel L

2015-02-21

This minireview discusses universal electronic modules (generic programmable units) and their use by analytical chemists to construct inexpensive, miniature or automated devices. Recently, open-source platforms have gained considerable popularity among tech-savvy chemists because their implementation often does not require expert knowledge and investment of funds. Thus, chemistry students and researchers can easily start implementing them after a few hours of reading tutorials and trial-and-error. Single-board microcontrollers and micro-computers such as Arduino, Teensy, Raspberry Pi or BeagleBone enable collecting experimental data with high precision as well as efficient control of electric potentials and actuation of mechanical systems. They are readily programmed using high-level languages, such as C, C++, JavaScript or Python. They can also be coupled with mobile consumer electronics, including smartphones as well as teleinformatic networks. More demanding analytical tasks require fast signal processing. Field-programmable gate arrays enable efficient and inexpensive prototyping of high-performance analytical platforms, thus becoming increasingly popular among analytical chemists. This minireview discusses the advantages and drawbacks of universal electronic modules, considering their application in prototyping and manufacture of intelligent analytical instrumentation.

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 .

Generic Language Facilitates Children's Cross-Classification

ERIC Educational Resources Information Center

Nguyen, Simone P.; Gelman, A.

2012-01-01

Four studies examined the role of generic language in facilitating 4- and 5-year-old children's ability to cross-classify. Participants were asked to classify an item into a familiar (taxonomic or script) category, then cross-classify it into a novel (script or taxonomic) category with the help of a clue expressed in either generic or specific…

Manual Tape Scripts: German, Level 2. Curriculum Bulletin, 1969-70 Series, Number 19.

ERIC Educational Resources Information Center

Lipton, Gladys; And Others

This manual of tape scripts, together with a set of foreign language tapes for Level 2 German, was prepared to support the curriculum bulletin "New York City Foreign Language Program for Schools: German, Levels 1-4." Vocabulary, repetition, transformation, and recombination drills on specific grammatical features allow further development of…

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

PubMed Central

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

2017-01-01

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

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

PubMed

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

2017-01-01

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

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

The HST/WFC3 Quicklook Project: A User Interface to Hubble Space Telescope Wide Field Camera 3 Data

NASA Astrophysics Data System (ADS)

Bourque, Matthew; Bajaj, Varun; Bowers, Ariel; Dulude, Michael; Durbin, Meredith; Gosmeyer, Catherine; Gunning, Heather; Khandrika, Harish; Martlin, Catherine; Sunnquist, Ben; Viana, Alex

2017-06-01

The Hubble Space Telescope's Wide Field Camera 3 (WFC3) instrument, comprised of two detectors, UVIS (Ultraviolet-Visible) and IR (Infrared), has been acquiring ~ 50-100 images daily since its installation in 2009. The WFC3 Quicklook project provides a means for instrument analysts to store, calibrate, monitor, and interact with these data through the various Quicklook systems: (1) a ~ 175 TB filesystem, which stores the entire WFC3 archive on disk, (2) a MySQL database, which stores image header data, (3) a Python-based automation platform, which currently executes 22 unique calibration/monitoring scripts, (4) a Python-based code library, which provides system functionality such as logging, downloading tools, database connection objects, and filesystem management, and (5) a Python/Flask-based web interface to the Quicklook system. The Quicklook project has enabled large-scale WFC3 analyses and calibrations, such as the monitoring of the health and stability of the WFC3 instrument, the measurement of ~ 20 million WFC3/UVIS Point Spread Functions (PSFs), the creation of WFC3/IR persistence calibration products, and many others.

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.

Implementing a distributed intranet-based information system.

PubMed

O'Kane, K C; McColligan, E E; Davis, G A

1996-11-01

The article discusses Internet and intranet technologies and describes how to install an intranet-based information system using the Merle language facility and other readily available components. Merle is a script language designed to support decentralized medical record information retrieval applications on the World Wide Web. The goal of this work is to provide a script language tool to facilitate construction of efficient, fully functional, multipoint medical record information systems that can be accessed anywhere by low-cost Web browsers to search, retrieve, and analyze patient information. The language allows legacy MUMPS applications to function in a Web environment and to make use of the Web graphical, sound, and video presentation services. It also permits downloading of script applets for execution on client browsers, and it can be used in standalone mode with the Unix, Windows 95, Windows NT, and OS/2 operating systems.

RosettaScripts: a scripting language interface to the Rosetta macromolecular modeling suite.

PubMed

Fleishman, Sarel J; Leaver-Fay, Andrew; Corn, Jacob E; Strauch, Eva-Maria; Khare, Sagar D; Koga, Nobuyasu; Ashworth, Justin; Murphy, Paul; Richter, Florian; Lemmon, Gordon; Meiler, Jens; Baker, David

2011-01-01

Macromolecular modeling and design are increasingly useful in basic research, biotechnology, and teaching. However, the absence of a user-friendly modeling framework that provides access to a wide range of modeling capabilities is hampering the wider adoption of computational methods by non-experts. RosettaScripts is an XML-like language for specifying modeling tasks in the Rosetta framework. RosettaScripts provides access to protocol-level functionalities, such as rigid-body docking and sequence redesign, and allows fast testing and deployment of complex protocols without need for modifying or recompiling the underlying C++ code. We illustrate these capabilities with RosettaScripts protocols for the stabilization of proteins, the generation of computationally constrained libraries for experimental selection of higher-affinity binding proteins, loop remodeling, small-molecule ligand docking, design of ligand-binding proteins, and specificity redesign in DNA-binding proteins.

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.

OpenSesame: an open-source, graphical experiment builder for the social sciences.

PubMed

Mathôt, Sebastiaan; Schreij, Daniel; Theeuwes, Jan

2012-06-01

In the present article, we introduce OpenSesame, a graphical experiment builder for the social sciences. OpenSesame is free, open-source, and cross-platform. It features a comprehensive and intuitive graphical user interface and supports Python scripting for complex tasks. Additional functionality, such as support for eyetrackers, input devices, and video playback, is available through plug-ins. OpenSesame can be used in combination with existing software for creating experiments.

Does the reading of different orthographies produce distinct brain activity patterns? An ERP study.

PubMed

Bar-Kochva, Irit; Breznitz, Zvia

2012-01-01

Orthographies vary in the degree of transparency of spelling-sound correspondence. These range from shallow orthographies with transparent grapheme-phoneme relations, to deep orthographies, in which these relations are opaque. Only a few studies have examined whether orthographic depth is reflected in brain activity. In these studies a between-language design was applied, making it difficult to isolate the aspect of orthographic depth. In the present work this question was examined using a within-subject-and-language investigation. The participants were speakers of Hebrew, as they are skilled in reading two forms of script transcribing the same oral language. One form is the shallow pointed script (with diacritics), and the other is the deep unpointed script (without diacritics). Event-related potentials (ERPs) were recorded while skilled readers carried out a lexical decision task in the two forms of script. A visual non-orthographic task controlled for the visual difference between the scripts (resulting from the addition of diacritics to the pointed script only). At an early visual-perceptual stage of processing (~165 ms after target onset), the pointed script evoked larger amplitudes with longer latencies than the unpointed script at occipital-temporal sites. However, these effects were not restricted to orthographic processing, and may therefore have reflected, at least in part, the visual load imposed by the diacritics. Nevertheless, the results implied that distinct orthographic processing may have also contributed to these effects. At later stages (~340 ms after target onset) the unpointed script elicited larger amplitudes than the pointed one with earlier latencies. As this latency has been linked to orthographic-linguistic processing and to the classification of stimuli, it is suggested that these differences are associated with distinct lexical processing of a shallow and a deep orthography.

"Writing It in English": Script Choices among Young Multilingual Muslims in the UK

ERIC Educational Resources Information Center

Rosowsky, Andrey

2010-01-01

Much attention has been paid in the literature to matters of script choice vis-a-vis languages. This attention, however, has focused on script choice in a national and political context. By contrast, there has not been any significant attention paid to more local and idiosyncratic instances of script choice operating on an individual and community…

Addressing numerical challenges in introducing a reactive transport code into a land surface model: A biogeochemical modeling proof-of-concept with CLM-PFLOTRAN 1.0: Modeling Archive

DOE Data Explorer

Tang, G.; Andre, B.; Hoffman, F. M.; Painter, S. L.; Thornton, P. E.; Yuan, F.; Bisht, G.; Hammond, G. E.; Lichtner, P. C.; Kumar, J.; Mills, R. T.; Xu, X.

2016-04-19

This Modeling Archive is in support of an NGEE Arctic discussion paper under review and available at doi:10.5194/gmd-9-927-2016. The purpose is to document the simulations to allow verification, reproducibility, and follow-up studies. This dataset contains shell scripts to create the CLM-PFLOTRAN cases, specific input files for PFLOTRAN and CLM, outputs, and python scripts to make the figures using the outputs in the publication. Through these results, we demonstrate that CLM-PFLOTRAN can approximately reproduce CLM results in selected cases for the Arctic, temperate and tropic sites. In addition, the new framework facilitates mechanistic representations of soil biogeochemistry processes in the land surface model.

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.

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…

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

ERIC Educational Resources Information Center

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

2007-01-01

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

Using Unscripted Spoken Texts in the Teaching of Second Language Listening

ERIC Educational Resources Information Center

Wagner, Elvis

2014-01-01

Most spoken texts that are used in second language (L2) listening classroom activities are scripted texts, where the text is written, revised, polished, and then read aloud with artificially clear enunciation and slow rate of speech. This article explores the field's overreliance on these scripted texts, at the expense of including unscripted…

The Effects of Self-Explanation and Reading Questions and Answers on Learning Computer Programming Language

ERIC Educational Resources Information Center

Lee, Nancy

2013-01-01

The current study explored the differential effects of two learning strategies, self-explanation and reading questions and answers, on students' test performance in the computer programming language JavaScript. Students' perceptions toward the two strategies as to their effectiveness in learning JavaScript was also explored by examining students'…

Manual of Tape Scripts: Spanish, Level 2. Curriculum Bulletin, 1968-69 Series, Number 13.

ERIC Educational Resources Information Center

Lipton, Gladys; And Others

This second manual of tape scripts, together with a set of foreign language audio tapes for level 2 Spanish, was prepared to support the curriculum bulletin, New York City Foreign Language Program for Secondary Schools: Spanish, Levels 1-5. Vocabulary, repetition, transformation, and recombination drills on specific grammatical features allow…

Manual of Tape Scripts: German, Level 1. Curriculum Bulletin, 1968-69 Series, Number 11.

ERIC Educational Resources Information Center

Lipton, Gladys; And Others

This manual of tape scripts, together with a set of foreign language audio tapes for level 1 German, was prepared to support the curriculum bulletin, New York City Foreign Language Program for Secondary Schools: German, Levels 1-4. Vocabulary, repetition, transformation, and recombination drills on specific grammatical features allow further…

Manual of Tape Scripts: Italian, Level 1. Curriculum Bulletin, 1968-69 Series, Number 12.

ERIC Educational Resources Information Center

Lipton, Gladys; And Others

This manual of tape scripts, together with a set of foreign language audio tapes for level 1 Italian, was prepared to support the curriculum bulletin, New York City Foreign Language Program for Schools: Italian, Levels 1-4. Vocabulary, repetition, transformation, and recombination drills on specific grammatical features allow further development…

Manual of Tape Scripts: Russian, Levels 1 and 2. Curriculum Bulletin, 1969-70 Series, Number 18.

ERIC Educational Resources Information Center

Lipton, Gladys; And Others

This manual of tape scripts, together with a set of foreign language audio tapes for Levels 1 and 2 Russian, was prepared to support the curriculum bulletin, "New York City Foreign Language Program for Schools: Russian, Levels 1-4." Vocabulary, repetition, transformation, and recombination drills on specific grammatical features allow further…

Manual of Tape Scripts: French, Level 2. Curriculum Bulletin, 1968-69 Series, Number 10.

ERIC Educational Resources Information Center

Lipton, Gladys; And Others

This second manual of tape scripts, together with a set of foreign language audio tapes for level 2 French, was prepared to support the curriculum bulletin, New York City Foreign Language Program for Secondary Schools: French, Levels 1-5. Vocabulary, repetition, transformation, and recombination drills on specific grammatical features allow…

Manual of Tape Scripts: Italian, Level 2. Curriculum Bulletin, 1969-70 Series, Number 20.

ERIC Educational Resources Information Center

Lipton, Gladys; And Others

This manual of tape scripts, together with a set of foreign language audio tapes for Level 2 Italian, was prepared to support the curriculum bulletin, "New York City Foreign Language Program for Schools: Italian, Levels 1-4." Vocabulary, repetition, transformation, and recombination drills on specific grammatical features allow further development…

LEMS: a language for expressing complex biological models in concise and hierarchical form and its use in underpinning NeuroML 2.

PubMed

Cannon, Robert C; Gleeson, Padraig; Crook, Sharon; Ganapathy, Gautham; Marin, Boris; Piasini, Eugenio; Silver, R Angus

2014-01-01

Computational models are increasingly important for studying complex neurophysiological systems. As scientific tools, it is essential that such models can be reproduced and critically evaluated by a range of scientists. However, published models are currently implemented using a diverse set of modeling approaches, simulation tools, and computer languages making them inaccessible and difficult to reproduce. Models also typically contain concepts that are tightly linked to domain-specific simulators, or depend on knowledge that is described exclusively in text-based documentation. To address these issues we have developed a compact, hierarchical, XML-based language called LEMS (Low Entropy Model Specification), that can define the structure and dynamics of a wide range of biological models in a fully machine readable format. We describe how LEMS underpins the latest version of NeuroML and show that this framework can define models of ion channels, synapses, neurons and networks. Unit handling, often a source of error when reusing models, is built into the core of the language by specifying physical quantities in models in terms of the base dimensions. We show how LEMS, together with the open source Java and Python based libraries we have developed, facilitates the generation of scripts for multiple neuronal simulators and provides a route for simulator free code generation. We establish that LEMS can be used to define models from systems biology and map them to neuroscience-domain specific simulators, enabling models to be shared between these traditionally separate disciplines. LEMS and NeuroML 2 provide a new, comprehensive framework for defining computational models of neuronal and other biological systems in a machine readable format, making them more reproducible and increasing the transparency and accessibility of their underlying structure and properties.

LEMS: a language for expressing complex biological models in concise and hierarchical form and its use in underpinning NeuroML 2

PubMed Central

Cannon, Robert C.; Gleeson, Padraig; Crook, Sharon; Ganapathy, Gautham; Marin, Boris; Piasini, Eugenio; Silver, R. Angus

2014-01-01

Computational models are increasingly important for studying complex neurophysiological systems. As scientific tools, it is essential that such models can be reproduced and critically evaluated by a range of scientists. However, published models are currently implemented using a diverse set of modeling approaches, simulation tools, and computer languages making them inaccessible and difficult to reproduce. Models also typically contain concepts that are tightly linked to domain-specific simulators, or depend on knowledge that is described exclusively in text-based documentation. To address these issues we have developed a compact, hierarchical, XML-based language called LEMS (Low Entropy Model Specification), that can define the structure and dynamics of a wide range of biological models in a fully machine readable format. We describe how LEMS underpins the latest version of NeuroML and show that this framework can define models of ion channels, synapses, neurons and networks. Unit handling, often a source of error when reusing models, is built into the core of the language by specifying physical quantities in models in terms of the base dimensions. We show how LEMS, together with the open source Java and Python based libraries we have developed, facilitates the generation of scripts for multiple neuronal simulators and provides a route for simulator free code generation. We establish that LEMS can be used to define models from systems biology and map them to neuroscience-domain specific simulators, enabling models to be shared between these traditionally separate disciplines. LEMS and NeuroML 2 provide a new, comprehensive framework for defining computational models of neuronal and other biological systems in a machine readable format, making them more reproducible and increasing the transparency and accessibility of their underlying structure and properties. PMID:25309419

Pcetk: A pDynamo-based Toolkit for Protonation State Calculations in Proteins.

PubMed

Feliks, Mikolaj; Field, Martin J

2015-10-26

Pcetk (a pDynamo-based continuum electrostatic toolkit) is an open-source, object-oriented toolkit for the calculation of proton binding energetics in proteins. The toolkit is a module of the pDynamo software library, combining the versatility of the Python scripting language and the efficiency of the compiled languages, C and Cython. In the toolkit, we have connected pDynamo to the external Poisson-Boltzmann solver, extended-MEAD. Our goal was to provide a modern and extensible environment for the calculation of protonation states, electrostatic energies, titration curves, and other electrostatic-dependent properties of proteins. Pcetk is freely available under the CeCILL license, which is compatible with the GNU General Public License. The toolkit can be found on the Web at the address http://github.com/mfx9/pcetk. The calculation of protonation states in proteins requires a knowledge of pKa values of protonatable groups in aqueous solution. However, for some groups, such as protonatable ligands bound to protein, the pKa aq values are often difficult to obtain from experiment. As a complement to Pcetk, we revisit an earlier computational method for the estimation of pKa aq values that has an accuracy of ± 0.5 pKa-units or better. Finally, we verify the Pcetk module and the method for estimating pKa aq values with different model cases.

PyNN: A Common Interface for Neuronal Network Simulators.

PubMed

Davison, Andrew P; Brüderle, Daniel; Eppler, Jochen; Kremkow, Jens; Muller, Eilif; Pecevski, Dejan; Perrinet, Laurent; Yger, Pierre

2008-01-01

Computational neuroscience has produced a diversity of software for simulations of networks of spiking neurons, with both negative and positive consequences. On the one hand, each simulator uses its own programming or configuration language, leading to considerable difficulty in porting models from one simulator to another. This impedes communication between investigators and makes it harder to reproduce and build on the work of others. On the other hand, simulation results can be cross-checked between different simulators, giving greater confidence in their correctness, and each simulator has different optimizations, so the most appropriate simulator can be chosen for a given modelling task. A common programming interface to multiple simulators would reduce or eliminate the problems of simulator diversity while retaining the benefits. PyNN is such an interface, making it possible to write a simulation script once, using the Python programming language, and run it without modification on any supported simulator (currently NEURON, NEST, PCSIM, Brian and the Heidelberg VLSI neuromorphic hardware). PyNN increases the productivity of neuronal network modelling by providing high-level abstraction, by promoting code sharing and reuse, and by providing a foundation for simulator-agnostic analysis, visualization and data-management tools. PyNN increases the reliability of modelling studies by making it much easier to check results on multiple simulators. PyNN is open-source software and is available from http://neuralensemble.org/PyNN.

MyMolDB: a micromolecular database solution with open source and free components.

PubMed

Xia, Bing; Tai, Zheng-Fu; Gu, Yu-Cheng; Li, Bang-Jing; Ding, Li-Sheng; Zhou, Yan

2011-10-01

To manage chemical structures in small laboratories is one of the important daily tasks. Few solutions are available on the internet, and most of them are closed source applications. The open-source applications typically have limited capability and basic cheminformatics functionalities. In this article, we describe an open-source solution to manage chemicals in research groups based on open source and free components. It has a user-friendly interface with the functions of chemical handling and intensive searching. MyMolDB is a micromolecular database solution that supports exact, substructure, similarity, and combined searching. This solution is mainly implemented using scripting language Python with a web-based interface for compound management and searching. Almost all the searches are in essence done with pure SQL on the database by using the high performance of the database engine. Thus, impressive searching speed has been archived in large data sets for no external Central Processing Unit (CPU) consuming languages were involved in the key procedure of the searching. MyMolDB is an open-source software and can be modified and/or redistributed under GNU General Public License version 3 published by the Free Software Foundation (Free Software Foundation Inc. The GNU General Public License, Version 3, 2007. Available at: http://www.gnu.org/licenses/gpl.html). The software itself can be found at http://code.google.com/p/mymoldb/. Copyright © 2011 Wiley Periodicals, Inc.

PyNN: A Common Interface for Neuronal Network Simulators

PubMed Central

Davison, Andrew P.; Brüderle, Daniel; Eppler, Jochen; Kremkow, Jens; Muller, Eilif; Pecevski, Dejan; Perrinet, Laurent; Yger, Pierre

2008-01-01

Computational neuroscience has produced a diversity of software for simulations of networks of spiking neurons, with both negative and positive consequences. On the one hand, each simulator uses its own programming or configuration language, leading to considerable difficulty in porting models from one simulator to another. This impedes communication between investigators and makes it harder to reproduce and build on the work of others. On the other hand, simulation results can be cross-checked between different simulators, giving greater confidence in their correctness, and each simulator has different optimizations, so the most appropriate simulator can be chosen for a given modelling task. A common programming interface to multiple simulators would reduce or eliminate the problems of simulator diversity while retaining the benefits. PyNN is such an interface, making it possible to write a simulation script once, using the Python programming language, and run it without modification on any supported simulator (currently NEURON, NEST, PCSIM, Brian and the Heidelberg VLSI neuromorphic hardware). PyNN increases the productivity of neuronal network modelling by providing high-level abstraction, by promoting code sharing and reuse, and by providing a foundation for simulator-agnostic analysis, visualization and data-management tools. PyNN increases the reliability of modelling studies by making it much easier to check results on multiple simulators. PyNN is open-source software and is available from http://neuralensemble.org/PyNN. PMID:19194529

Change detection and characterization of volcanic activity using ground based low-light and near infrared cameras to monitor incandescence and thermal signatures

NASA Astrophysics Data System (ADS)

Harrild, M.; Webley, P.; Dehn, J.

2014-12-01

Knowledge and understanding of precursory events and thermal signatures are vital for monitoring volcanogenic processes, as activity can often range from low level lava effusion to large explosive eruptions, easily capable of ejecting ash up to aircraft cruise altitudes. Using ground based remote sensing techniques to monitor and detect this activity is essential, but often the required equipment and maintenance is expensive. Our investigation explores the use of low-light cameras to image volcanic activity in the visible to near infrared (NIR) portion of the electromagnetic spectrum. These cameras are ideal for monitoring as they are cheap, consume little power, are easily replaced and can provide near real-time data. We focus here on the early detection of volcanic activity, using automated scripts, that capture streaming online webcam imagery and evaluate image pixel brightness values to determine relative changes and flag increases in activity. The script is written in Python, an open source programming language, to reduce the overall cost to potential consumers and increase the application of these tools across the volcanological community. In addition, by performing laboratory tests to determine the spectral response of these cameras, a direct comparison of collocated low-light and thermal infrared cameras has allowed approximate eruption temperatures and effusion rates to be determined from pixel brightness. The results of a field campaign in June, 2013 to Stromboli volcano, Italy, are also presented here. Future field campaigns to Latin America will include collaborations with INSIVUMEH in Guatemala, to apply our techniques to Fuego and Santiaguito volcanoes.

Change detection and characterization of volcanic activity using ground based low-light and near infrared cameras to monitor incandescence and thermal signatures

NASA Astrophysics Data System (ADS)

Harrild, Martin; Webley, Peter; Dehn, Jonathan

2015-04-01

Knowledge and understanding of precursory events and thermal signatures are vital for monitoring volcanogenic processes, as activity can often range from low level lava effusion to large explosive eruptions, easily capable of ejecting ash up to aircraft cruise altitudes. Using ground based remote sensing techniques to monitor and detect this activity is essential, but often the required equipment and maintenance is expensive. Our investigation explores the use of low-light cameras to image volcanic activity in the visible to near infrared (NIR) portion of the electromagnetic spectrum. These cameras are ideal for monitoring as they are cheap, consume little power, are easily replaced and can provide near real-time data. We focus here on the early detection of volcanic activity, using automated scripts, that capture streaming online webcam imagery and evaluate image pixel brightness values to determine relative changes and flag increases in activity. The script is written in Python, an open source programming language, to reduce the overall cost to potential consumers and increase the application of these tools across the volcanological community. In addition, by performing laboratory tests to determine the spectral response of these cameras, a direct comparison of collocated low-light and thermal infrared cameras has allowed approximate eruption temperatures and effusion rates to be determined from pixel brightness. The results of a field campaign in June, 2013 to Stromboli volcano, Italy, are also presented here. Future field campaigns to Latin America will include collaborations with INSIVUMEH in Guatemala, to apply our techniques to Fuego and Santiaguito volcanoes.

PSTOOLS - FOUR PROGRAMS THAT INTERPRET/FORMAT POSTSCRIPT FILES

NASA Technical Reports Server (NTRS)

Choi, D.

1994-01-01

PSTOOLS is a package of four programs that operate on files written in the page description language, PostScript. The programs include a PostScript previewer for the IRIS workstation, a PostScript driver for the Matrix QCRZ film recorder, a PostScript driver for the Tektronix 4693D printer, and a PostScript code beautifier that formats PostScript files to be more legible. The three programs PSIRIS, PSMATRIX, and PSTEK are similar in that they all interpret the PostScript language and output the graphical results to a device, and they support color PostScript images. The common code which is shared by these three programs is included as a library of routines. PSPRETTY formats a PostScript file by appropriately indenting procedures and code delimited by "saves" and "restores." PSTOOLS does not use Adobe fonts. PSTOOLS is written in C-language for implementation on SGI IRIS 4D series workstations running IRIX 3.2 or later. A README file and UNIX man pages provide information regarding the installation and use of the PSTOOLS programs. A six-page manual which provides slightly more detailed information may be purchased separately. The standard distribution medium for this package is one .25 inch streaming magnetic tape cartridge in UNIX tar format. PSIRIS (the largest program) requires 1.2Mb of main memory. PSMATRIX requires the "gpib" board (IEEE 488) available from Silicon Graphics. Inc. The programs with graphical interfaces require that the IRIS have at least 24 bit planes. This package was developed in 1990 and updated in 1991. SGI, IRIS 4D, and IRIX are trademarks of Silicon Graphics, Inc. Matrix QCRZ is a registered trademark of the AGFA Group. Tektronix 4693D is a trademark of Tektronix, Inc. Adobe is a trademark of Adobe Systems Incorporated. PostScript is a registered trademark of Adobe Systems Incorporated. UNIX is a registered trademark of AT&T Bell Laboratories.

STSE: Spatio-Temporal Simulation Environment Dedicated to Biology.

PubMed

Stoma, Szymon; Fröhlich, Martina; Gerber, Susanne; Klipp, Edda

2011-04-28

Recently, the availability of high-resolution microscopy together with the advancements in the development of biomarkers as reporters of biomolecular interactions increased the importance of imaging methods in molecular cell biology. These techniques enable the investigation of cellular characteristics like volume, size and geometry as well as volume and geometry of intracellular compartments, and the amount of existing proteins in a spatially resolved manner. Such detailed investigations opened up many new areas of research in the study of spatial, complex and dynamic cellular systems. One of the crucial challenges for the study of such systems is the design of a well stuctured and optimized workflow to provide a systematic and efficient hypothesis verification. Computer Science can efficiently address this task by providing software that facilitates handling, analysis, and evaluation of biological data to the benefit of experimenters and modelers. The Spatio-Temporal Simulation Environment (STSE) is a set of open-source tools provided to conduct spatio-temporal simulations in discrete structures based on microscopy images. The framework contains modules to digitize, represent, analyze, and mathematically model spatial distributions of biochemical species. Graphical user interface (GUI) tools provided with the software enable meshing of the simulation space based on the Voronoi concept. In addition, it supports to automatically acquire spatial information to the mesh from the images based on pixel luminosity (e.g. corresponding to molecular levels from microscopy images). STSE is freely available either as a stand-alone version or included in the linux live distribution Systems Biology Operational Software (SB.OS) and can be downloaded from http://www.stse-software.org/. The Python source code as well as a comprehensive user manual and video tutorials are also offered to the research community. We discuss main concepts of the STSE design and workflow. We demonstrate it's usefulness using the example of a signaling cascade leading to formation of a morphological gradient of Fus3 within the cytoplasm of the mating yeast cell Saccharomyces cerevisiae. STSE is an efficient and powerful novel platform, designed for computational handling and evaluation of microscopic images. It allows for an uninterrupted workflow including digitization, representation, analysis, and mathematical modeling. By providing the means to relate the simulation to the image data it allows for systematic, image driven model validation or rejection. STSE can be scripted and extended using the Python language. STSE should be considered rather as an API together with workflow guidelines and a collection of GUI tools than a stand alone application. The priority of the project is to provide an easy and intuitive way of extending and customizing software using the Python language.

CIAO: CHANDRA/X-RAY DATA ANALYSIS FOR EVERYONE

NASA Astrophysics Data System (ADS)

McDowell, Jonathan; CIAO Team

2018-01-01

Eighteen years after the launch of Chandra, the archive is full of scientifically rich data and new observations continue. Improvements in recent years to the data analysis package CIAO (Chandra Interactive Analysis of Observations) and its extensive accompanying documentation make it easier for astronomers without a specialist background in high energy astrophysics to take advantage of this resource.The CXC supports hundreds of CIAO users around the world at all levels of training from high school and undergraduate students to the most experienced X-ray astronomers. In general, we strive to provide a software system which is easy for beginners, yet powerful for advanced users.Chandra data cover a range of instrument configurations and types of target (pointlike, extended and moving), requiring a flexible data analysis system. In addition to CIAO tools using the familiar FTOOLS/IRAF-style parameter interface, CIAO includes applications such as the Sherpa fitting engine which provide access to the data via Python scripting.In this poster we point prospective (and existing!) users to the high level Python scripts now provided to reprocess Chandra or other X-ray mission data, determine source fluxes and upper limits, and estimate backgrounds; and to the latest documentation including the CIAO Gallery, a new entry point featuring the system's different capabilities.This work has been supported by NASA under contract NAS 8-03060 to the Smithsonian Astrophysical Observatory for operation of the Chandra X-ray Center.

Tools for automating spacecraft ground systems: The Intelligent Command and Control (ICC) approach

NASA Technical Reports Server (NTRS)

Stoffel, A. William; Mclean, David

1996-01-01

The practical application of scripting languages and World Wide Web tools to the support of spacecraft ground system automation, is reported on. The mission activities and the automation tools used at the Goddard Space Flight Center (MD) are reviewed. The use of the Tool Command Language (TCL) and the Practical Extraction and Report Language (PERL) scripting tools for automating mission operations is discussed together with the application of different tools for the Compton Gamma Ray Observatory ground system.

Manipulation of Motivating Operations and Use of a Script-Fading Procedure to Teach Mands for Location to Children with Language Delays

ERIC Educational Resources Information Center

Howlett, Melissa A.; Sidener, Tina M.; Progar, Patrick R.; Sidener, David W.

2011-01-01

The effects of contriving motivating operations (MOs) and script fading on the acquisition of the mand "Where's [object]?" were evaluated in 2 boys with language delays. During each session, trials were alternated in which high-preference items were present (abolishing operation [AO] trials) or missing (establishing operation [EO] trials) from…

Creating a Culture that Acknowledges the Power of Words

ERIC Educational Resources Information Center

Murray, Carol Garboden

2012-01-01

The language used by adults in an early childhood setting is one of the most telling indicators of the values of a center. Each center has its own culture of language that consists of often heard phrases and scripts used when teaching and caring for young children. Listening closely to words, tones, and scripts--educators tune into what is unseen,…

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.

Advanced software development workstation. Engineering scripting language graphical editor: DRAFT design document

NASA Technical Reports Server (NTRS)

1991-01-01

The Engineering Scripting Language (ESL) is a language designed to allow nonprogramming users to write Higher Order Language (HOL) programs by drawing directed graphs to represent the program and having the system generate the corresponding program in HOL. The ESL system supports user generation of HOL programs through the manipulation of directed graphs. The components of this graphs (nodes, ports, and connectors) are objects each of which has its own properties and property values. The purpose of the ESL graphical editor is to allow the user to create or edit graph objects which represent programs.

Group Analysis in MNE-Python of Evoked Responses from a Tactile Stimulation Paradigm: A Pipeline for Reproducibility at Every Step of Processing, Going from Individual Sensor Space Representations to an across-Group Source Space Representation

PubMed Central

Andersen, Lau M.

2018-01-01

An important aim of an analysis pipeline for magnetoencephalographic data is that it allows for the researcher spending maximal effort on making the statistical comparisons that will answer the questions of the researcher, while in turn spending minimal effort on the intricacies and machinery of the pipeline. I here present a set of functions and scripts that allow for setting up a clear, reproducible structure for separating raw and processed data into folders and files such that minimal effort can be spend on: (1) double-checking that the right input goes into the right functions; (2) making sure that output and intermediate steps can be accessed meaningfully; (3) applying operations efficiently across groups of subjects; (4) re-processing data if changes to any intermediate step are desirable. Applying the scripts requires only general knowledge about the Python language. The data analyses are neural responses to tactile stimulations of the right index finger in a group of 20 healthy participants acquired from an Elekta Neuromag System. Two analyses are presented: going from individual sensor space representations to, respectively, an across-group sensor space representation and an across-group source space representation. The processing steps covered for the first analysis are filtering the raw data, finding events of interest in the data, epoching data, finding and removing independent components related to eye blinks and heart beats, calculating participants' individual evoked responses by averaging over epoched data and calculating a grand average sensor space representation over participants. The second analysis starts from the participants' individual evoked responses and covers: estimating noise covariance, creating a forward model, creating an inverse operator, estimating distributed source activity on the cortical surface using a minimum norm procedure, morphing those estimates onto a common cortical template and calculating the patterns of activity that are statistically different from baseline. To estimate source activity, processing of the anatomy of subjects based on magnetic resonance imaging is necessary. The necessary steps are covered here: importing magnetic resonance images, segmenting the brain, estimating boundaries between different tissue layers, making fine-resolution scalp surfaces for facilitating co-registration, creating source spaces and creating volume conductors for each subject. PMID:29403349

Group Analysis in MNE-Python of Evoked Responses from a Tactile Stimulation Paradigm: A Pipeline for Reproducibility at Every Step of Processing, Going from Individual Sensor Space Representations to an across-Group Source Space Representation.

PubMed

Andersen, Lau M

2018-01-01

An important aim of an analysis pipeline for magnetoencephalographic data is that it allows for the researcher spending maximal effort on making the statistical comparisons that will answer the questions of the researcher, while in turn spending minimal effort on the intricacies and machinery of the pipeline. I here present a set of functions and scripts that allow for setting up a clear, reproducible structure for separating raw and processed data into folders and files such that minimal effort can be spend on: (1) double-checking that the right input goes into the right functions; (2) making sure that output and intermediate steps can be accessed meaningfully; (3) applying operations efficiently across groups of subjects; (4) re-processing data if changes to any intermediate step are desirable. Applying the scripts requires only general knowledge about the Python language. The data analyses are neural responses to tactile stimulations of the right index finger in a group of 20 healthy participants acquired from an Elekta Neuromag System. Two analyses are presented: going from individual sensor space representations to, respectively, an across-group sensor space representation and an across-group source space representation. The processing steps covered for the first analysis are filtering the raw data, finding events of interest in the data, epoching data, finding and removing independent components related to eye blinks and heart beats, calculating participants' individual evoked responses by averaging over epoched data and calculating a grand average sensor space representation over participants. The second analysis starts from the participants' individual evoked responses and covers: estimating noise covariance, creating a forward model, creating an inverse operator, estimating distributed source activity on the cortical surface using a minimum norm procedure, morphing those estimates onto a common cortical template and calculating the patterns of activity that are statistically different from baseline. To estimate source activity, processing of the anatomy of subjects based on magnetic resonance imaging is necessary. The necessary steps are covered here: importing magnetic resonance images, segmenting the brain, estimating boundaries between different tissue layers, making fine-resolution scalp surfaces for facilitating co-registration, creating source spaces and creating volume conductors for each subject.

An Open-Source Approach for Catchment's Physiographic Characterization

NASA Astrophysics Data System (ADS)

Di Leo, M.; Di Stefano, M.

2013-12-01

A water catchment's hydrologic response is intimately linked to its morphological shape, which is a signature on the landscape of the particular climate conditions that generated the hydrographic basin over time. Furthermore, geomorphologic structures influence hydrologic regimes and land cover (vegetation). For these reasons, a basin's characterization is a fundamental element in hydrological studies. Physiographic descriptors have been extracted manually for long time, but currently Geographic Information System (GIS) tools ease such task by offering a powerful instrument for hydrologists to save time and improve accuracy of result. Here we present a program combining the flexibility of the Python programming language with the reliability of GRASS GIS, which automatically performing the catchment's physiographic characterization. GRASS (Geographic Resource Analysis Support System) is a Free and Open Source GIS, that today can look back on 30 years of successful development in geospatial data management and analysis, image processing, graphics and maps production, spatial modeling and visualization. The recent development of new hydrologic tools, coupled with the tremendous boost in the existing flow routing algorithms, reduced the computational time and made GRASS a complete toolset for hydrological analysis even for large datasets. The tool presented here is a module called r.basin, based on GRASS' traditional nomenclature, where the "r" stands for "raster", and it is available for GRASS version 6.x and more recently for GRASS 7. As input it uses a Digital Elevation Model and the coordinates of the outlet, and, powered by the recently developed r.stream.* hydrological tools, it performs the flow calculation, delimits the basin's boundaries and extracts the drainage network, returning the flow direction and accumulation, the distance to outlet and the hill slopes length maps. Based on those maps, it calculates hydrologically meaningful shape factors and morphological parameters such as topological diameter, drainage density, Horton's ratios, concentration time, and many more, beside producing statistics on main channel and elevation and geometric features such as centroid's coordinates, rectangle containing the basin, etc. Exploiting Python libraries, such as Numpy and Matplotlib, it produces graphics like the hypsographic and hypsometric curve and the Width Function. The results are exported as a spreadsheet in CSV format and graphics as pngs. The advantages offered by the implementation in Python and GRASS are manifold. Python is a powerful scripting language with huge potential for researchers due to its relative simplicity, high flexibility and thanks to a broad availability of scientific libraries. GRASS, and as a consequence, r.basin, is platform independent, so that it is available for GNU/Linux, MS Windows, Mac, etc. Furthermore, the module is constantly maintained and improved according to users' feedback with the precious help of expert developers. The code is available for review under the official GRASS add-ons repository, allowing hydrologists and researchers to knowingly use, inspect, modify, reuse, and even incorporate it in other projects, such as web services.

Writing Signed Languages: What For? What Form?

PubMed

Grushkin, Donald A

2017-01-01

Signed languages around the world have tended to maintain an "oral," unwritten status. Despite the advantages of possessing a written form of their language, signed language communities typically resist and reject attempts to create such written forms. The present article addresses many of the arguments against written forms of signed languages, and presents the potential advantages of writing signed languages. Following a history of the development of writing in spoken as well as signed language populations, the effects of orthographic types upon literacy and biliteracy are explored. Attempts at writing signed languages have followed two primary paths: "alphabetic" and "icono-graphic." It is argued that for greatest congruency and ease in developing biliteracy strategies in societies where an alphabetic script is used for the spoken language, signed language communities within these societies are best served by adoption of an alphabetic script for writing their signed language.

Increasing play-based commenting in children with autism spectrum disorder using a novel script-frame procedure.

PubMed

Groskreutz, Mark P; Peters, Amy; Groskreutz, Nicole C; Higbee, Thomas S

2015-01-01

Children with developmental disabilities may engage in less frequent and more repetitious language than peers with typical development. Scripts have been used to increase communication by teaching one or more specific statements and then fading the scripts. In the current study, preschoolers with developmental disabilities experienced a novel script-frame protocol and learned to make play-related comments about toys. After the script-frame protocol, commenting occurred in the absence of scripts, with untrained play activities, and included untrained comments. © Society for the Experimental Analysis of Behavior.

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.

The Power of Scripting: DGS Meets Programming

ERIC Educational Resources Information Center

Richter-Gebert, Jürgen; Kortenkamp, Ulrich

2010-01-01

In this article we demonstrate how the combination of a system for dynamic geometry with a freely programmable scripting environment can be advantageously used in teaching and research. We explain the reasons behind various design decisions that were made by us when designing the language "CindyScript" and give examples that proof how…

SCDU Testbed Automated In-Situ Alignment, Data Acquisition and Analysis

NASA Technical Reports Server (NTRS)

Werne, Thomas A.; Wehmeier, Udo J.; Wu, Janet P.; An, Xin; Goullioud, Renaud; Nemati, Bijan; Shao, Michael; Shen, Tsae-Pyng J.; Wang, Xu; Weilert, Mark A.;

A segmentation-free approach to Arabic and Urdu OCR

NASA Astrophysics Data System (ADS)

Sabbour, Nazly; Shafait, Faisal

2013-01-01

In this paper, we present a generic Optical Character Recognition system for Arabic script languages called Nabocr. Nabocr uses OCR approaches specific for Arabic script recognition. Performing recognition on Arabic script text is relatively more difficult than Latin text due to the nature of Arabic script, which is cursive and context sensitive. Moreover, Arabic script has different writing styles that vary in complexity. Nabocr is initially trained to recognize both Urdu Nastaleeq and Arabic Naskh fonts. However, it can be trained by users to be used for other Arabic script languages. We have evaluated our system's performance for both Urdu and Arabic. In order to evaluate Urdu recognition, we have generated a dataset of Urdu text called UPTI (Urdu Printed Text Image Database), which measures different aspects of a recognition system. The performance of our system for Urdu clean text is 91%. For Arabic clean text, the performance is 86%. Moreover, we have compared the performance of our system against Tesseract's newly released Arabic recognition, and the performance of both systems on clean images is almost the same.

Visualization of Octree Adaptive Mesh Refinement (AMR) in Astrophysical Simulations

NASA Astrophysics Data System (ADS)

Labadens, M.; Chapon, D.; Pomaréde, D.; Teyssier, R.

2012-09-01

Computer simulations are important in current cosmological research. Those simulations run in parallel on thousands of processors, and produce huge amount of data. Adaptive mesh refinement is used to reduce the computing cost while keeping good numerical accuracy in regions of interest. RAMSES is a cosmological code developed by the Commissariat à l'énergie atomique et aux énergies alternatives (English: Atomic Energy and Alternative Energies Commission) which uses Octree adaptive mesh refinement. Compared to grid based AMR, the Octree AMR has the advantage to fit very precisely the adaptive resolution of the grid to the local problem complexity. However, this specific octree data type need some specific software to be visualized, as generic visualization tools works on Cartesian grid data type. This is why the PYMSES software has been also developed by our team. It relies on the python scripting language to ensure a modular and easy access to explore those specific data. In order to take advantage of the High Performance Computer which runs the RAMSES simulation, it also uses MPI and multiprocessing to run some parallel code. We would like to present with more details our PYMSES software with some performance benchmarks. PYMSES has currently two visualization techniques which work directly on the AMR. The first one is a splatting technique, and the second one is a custom ray tracing technique. Both have their own advantages and drawbacks. We have also compared two parallel programming techniques with the python multiprocessing library versus the use of MPI run. The load balancing strategy has to be smartly defined in order to achieve a good speed up in our computation. Results obtained with this software are illustrated in the context of a massive, 9000-processor parallel simulation of a Milky Way-like galaxy.

Cross-Language Transfer of Word Reading Accuracy and Word Reading Fluency in Spanish-English and Chinese-English Bilinguals: Script-Universal and Script-Specific Processes

ERIC Educational Resources Information Center

Pasquarella, Adrian; Chen, Xi; Gottardo, Alexandra; Geva, Esther

2015-01-01

This study examined cross-language transfer of word reading accuracy and word reading fluency in Spanish-English and Chinese-English bilinguals. Participants included 51 Spanish-English and 64 Chinese-English bilinguals. Both groups of children completed parallel measures of phonological awareness, rapid automatized naming, word reading accuracy,…

PROVAT: a tool for Voronoi tessellation analysis of protein structures and complexes.

PubMed

Gore, Swanand P; Burke, David F; Blundell, Tom L

2005-08-01

Voronoi tessellation has proved to be a useful tool in protein structure analysis. We have developed PROVAT, a versatile public domain software that enables computation and visualization of Voronoi tessellations of proteins and protein complexes. It is a set of Python scripts that integrate freely available specialized software (Qhull, Pymol etc.) into a pipeline. The calculation component of the tool computes Voronoi tessellation of a given protein system in a way described by a user-supplied XML recipe and stores resulting neighbourhood information as text files with various styles. The Python pickle file generated in the process is used by the visualization component, a Pymol plug-in, that offers a GUI to explore the tessellation visually. PROVAT source code can be downloaded from http://raven.bioc.cam.ac.uk/~swanand/Provat1, which also provides a webserver for its calculation component, documentation and examples.

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

Dem Generation from Close-Range Photogrammetry Using Extended Python Photogrammetry Toolbox

NASA Astrophysics Data System (ADS)

Belmonte, A. A.; Biong, M. M. P.; Macatulad, E. G.

2017-10-01

Digital elevation models (DEMs) are widely used raster data for different applications concerning terrain, such as for flood modelling, viewshed analysis, mining, land development, engineering design projects, to name a few. DEMs can be obtained through various methods, including topographic survey, LiDAR or photogrammetry, and internet sources. Terrestrial close-range photogrammetry is one of the alternative methods to produce DEMs through the processing of images using photogrammetry software. There are already powerful photogrammetry software that are commercially-available and can produce high-accuracy DEMs. However, this entails corresponding cost. Although, some of these software have free or demo trials, these trials have limits in their usable features and usage time. One alternative is the use of free and open-source software (FOSS), such as the Python Photogrammetry Toolbox (PPT), which provides an interface for performing photogrammetric processes implemented through python script. For relatively small areas such as in mining or construction excavation, a relatively inexpensive, fast and accurate method would be advantageous. In this study, PPT was used to generate 3D point cloud data from images of an open pit excavation. The PPT was extended to add an algorithm converting the generated point cloud data into a usable DEM.

ChromaStarPy: A Stellar Atmosphere and Spectrum Modeling and Visualization Lab in Python

NASA Astrophysics Data System (ADS)

Short, C. Ian; Bayer, Jason H. T.; Burns, Lindsey M.

2018-02-01

We announce ChromaStarPy, an integrated general stellar atmospheric modeling and spectrum synthesis code written entirely in python V. 3. ChromaStarPy is a direct port of the ChromaStarServer (CSServ) Java modeling code described in earlier papers in this series, and many of the associated JavaScript (JS) post-processing procedures have been ported and incorporated into CSPy so that students have access to ready-made data products. A python integrated development environment (IDE) allows a student in a more advanced course to experiment with the code and to graphically visualize intermediate and final results, ad hoc, as they are running it. CSPy allows students and researchers to compare modeled to observed spectra in the same IDE in which they are processing observational data, while having complete control over the stellar parameters affecting the synthetic spectra. We also take the opportunity to describe improvements that have been made to the related codes, ChromaStar (CS), CSServ, and ChromaStarDB (CSDB), that, where relevant, have also been incorporated into CSPy. The application may be found at the home page of the OpenStars project: http://www.ap.smu.ca/OpenStars/.

ROOT.NET: Using ROOT from .NET languages like C# and F#

NASA Astrophysics Data System (ADS)

Watts, G.

2012-12-01

ROOT.NET provides an interface between Microsoft's Common Language Runtime (CLR) and .NET technology and the ubiquitous particle physics analysis tool, ROOT. ROOT.NET automatically generates a series of efficient wrappers around the ROOT API. Unlike pyROOT, these wrappers are statically typed and so are highly efficient as compared to the Python wrappers. The connection to .NET means that one gains access to the full series of languages developed for the CLR including functional languages like F# (based on OCaml). Many features that make ROOT objects work well in the .NET world are added (properties, IEnumerable interface, LINQ compatibility, etc.). Dynamic languages based on the CLR can be used as well, of course (Python, for example). Additionally it is now possible to access ROOT objects that are unknown to the translation tool. This poster will describe the techniques used to effect this translation, along with performance comparisons, and examples. All described source code is posted on the open source site CodePlex.

LK Scripting Language

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

The LK scripting language is a simple and fast computer programming language designed for easy integration with existing software to enable automation of tasks. The LK language is used by NREL’s System Advisor Model (SAM), the SAM Software Development Kit (SDK), and SolTrace products. LK is easy extensible and adaptable to new software due to its small footprint and is designed to be statically linked into other software. It is written in standard C++, is cross-platform (Windows, Linux, and OSX), and includes optional portions that enable direct integration with graphical user interfaces written in the open source C++ wxWidgets Versionmore » 3.0+ toolkit.« less

An approach to the language discrimination in different scripts using adjacent local binary pattern

NASA Astrophysics Data System (ADS)

Brodić, D.; Amelio, A.; Milivojević, Z. N.

2017-09-01

The paper proposes a language discrimination method of documents. First, each letter is encoded with the certain script type according to its status in baseline area. Such a cipher text is subjected to a feature extraction process. Accordingly, the local binary pattern as well as its expanded version called adjacent local binary pattern are extracted. Because of the difference in the language characteristics, the above analysis shows significant diversity. This type of diversity is a key aspect in the decision-making differentiation of the languages. Proposed method is tested on an example of documents. The experiments give encouraging results.

[The dynamic concision for three-dimensional reconstruction of human organ built with virtual reality modeling language (VRML)].

PubMed

Yu, Zhengyang; Zheng, Shusen; Chen, Huaiqing; Wang, Jianjun; Xiong, Qingwen; Jing, Wanjun; Zeng, Yu

2006-10-01

This research studies the process of dynamic concision and 3D reconstruction from medical body data using VRML and JavaScript language, focuses on how to realize the dynamic concision of 3D medical model built with VRML. The 2D medical digital images firstly are modified and manipulated by 2D image software. Then, based on these images, 3D mould is built with VRML and JavaScript language. After programming in JavaScript to control 3D model, the function of dynamic concision realized by Script node and sensor node in VRML. The 3D reconstruction and concision of body internal organs can be formed in high quality near to those got in traditional methods. By this way, with the function of dynamic concision, VRML browser can offer better windows of man-computer interaction in real time environment than before. 3D reconstruction and dynamic concision with VRML can be used to meet the requirement for the medical observation of 3D reconstruction and has a promising prospect in the fields of medical image.

Increasing Play-Based Commenting in Children with Autism Spectrum Disorder Using a Novel Script-Frame Procedure

ERIC Educational Resources Information Center

Groskreutz, Mark P.; Peters, Amy; Groskreutz, Nicole C.; Higbee, Thomas S.

2015-01-01

Children with developmental disabilities may engage in less frequent and more repetitious language than peers with typical development. Scripts have been used to increase communication by teaching one or more specific statements and then fading the scripts. In the current study, preschoolers with developmental disabilities experienced a novel…

Building Composite Characters on a Postscript Printer.

ERIC Educational Resources Information Center

Gothard, James E.

Procedures enabling the placement of diacritical markings over a character for printing in PostScript fonts on an Apple LaserWriter printer are described. The procedures involve some programming in the PostScript Language and manipulation of Adobe PostScript fonts. It is assumed that Microsoft Word will be used to create the text to be printed.…

The Use of Interactive Whiteboards in Teaching Non-Roman Scripts

ERIC Educational Resources Information Center

Tozcu, Anjel

2008-01-01

This study explores the use of the interactive whiteboards in teaching the non-Latin based orthographies of Hindi, Pashto, Dari, Persian (Farsi), and Hebrew. All these languages use non-roman scripts, and except for Hindi, they are cursive. Thus, letters within words are connected and for beginners the script may look quite complicated,…

Astronomical Simulations Using Visual Python

NASA Astrophysics Data System (ADS)

Cobb, Michael L.

2007-05-01

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

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

Open source tools for ATR development and performance evaluation

NASA Astrophysics Data System (ADS)

Baumann, James M.; Dilsavor, Ronald L.; Stubbles, James; Mossing, John C.

2002-07-01

Early in almost every engineering project, a decision must be made about tools; should I buy off-the-shelf tools or should I develop my own. Either choice can involve significant cost and risk. Off-the-shelf tools may be readily available, but they can be expensive to purchase and to maintain licenses, and may not be flexible enough to satisfy all project requirements. On the other hand, developing new tools permits great flexibility, but it can be time- (and budget-) consuming, and the end product still may not work as intended. Open source software has the advantages of both approaches without many of the pitfalls. This paper examines the concept of open source software, including its history, unique culture, and informal yet closely followed conventions. These characteristics influence the quality and quantity of software available, and ultimately its suitability for serious ATR development work. We give an example where Python, an open source scripting language, and OpenEV, a viewing and analysis tool for geospatial data, have been incorporated into ATR performance evaluation projects. While this case highlights the successful use of open source tools, we also offer important insight into risks associated with this approach.

Sirepo for Synchrotron Radiation Workshop

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

Nagler, Robert; Moeller, Paul; Rakitin, Maksim

Sirepo is an open source framework for cloud computing. The graphical user interface (GUI) for Sirepo, also known as the client, executes in any HTML5 compliant web browser on any computing platform, including tablets. The client is built in JavaScript, making use of the following open source libraries: Bootstrap, which is fundamental for cross-platform web applications; AngularJS, which provides a model–view–controller (MVC) architecture and GUI components; and D3.js, which provides interactive plots and data-driven transformations. The Sirepo server is built on the following Python technologies: Flask, which is a lightweight framework for web development; Jinja, which is a secure andmore » widely used templating language; and Werkzeug, a utility library that is compliant with the WSGI standard. We use Nginx as the HTTP server and proxy, which provides a scalable event-driven architecture. The physics codes supported by Sirepo execute inside a Docker container. One of the codes supported by Sirepo is the Synchrotron Radiation Workshop (SRW). SRW computes synchrotron radiation from relativistic electrons in arbitrary magnetic fields and propagates the radiation wavefronts through optical beamlines. SRW is open source and is primarily supported by Dr. Oleg Chubar of NSLS-II at Brookhaven National Laboratory.« less

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.

[Preliminary application of scripting in RayStation TPS system].

PubMed

Zhang, Jianying; Sun, Jing; Wang, Yun

2013-07-01

Discussing the basic application of scripting in RayStation TPS system. On the RayStation 3.0 Platform, the programming methods and the points should be considered during basic scripting application were explored with the help of utility scripts. The typical planning problems in the field of beam arrangement and plan outputting were used as examples by ironprthon language. The necessary properties and the functions of patient object for script writing can be extracted from RayStation system. With the help of NET controls, planning functions such as the interactive parameter input, treatment planning control and the extract of the plan have been realized by scripts. With the help of demo scripts, scripts can be developed in RayStation, as well as the system performance can be upgraded.

snpTree--a web-server to identify and construct SNP trees from whole genome sequence data.

PubMed

Leekitcharoenphon, Pimlapas; Kaas, Rolf S; Thomsen, Martin Christen Frølund; Friis, Carsten; Rasmussen, Simon; Aarestrup, Frank M

2012-01-01

The advances and decreasing economical cost of whole genome sequencing (WGS), will soon make this technology available for routine infectious disease epidemiology. In epidemiological studies, outbreak isolates have very little diversity and require extensive genomic analysis to differentiate and classify isolates. One of the successfully and broadly used methods is analysis of single nucletide polymorphisms (SNPs). Currently, there are different tools and methods to identify SNPs including various options and cut-off values. Furthermore, all current methods require bioinformatic skills. Thus, we lack a standard and simple automatic tool to determine SNPs and construct phylogenetic tree from WGS data. Here we introduce snpTree, a server for online-automatic SNPs analysis. This tool is composed of different SNPs analysis suites, perl and python scripts. snpTree can identify SNPs and construct phylogenetic trees from WGS as well as from assembled genomes or contigs. WGS data in fastq format are aligned to reference genomes by BWA while contigs in fasta format are processed by Nucmer. SNPs are concatenated based on position on reference genome and a tree is constructed from concatenated SNPs using FastTree and a perl script. The online server was implemented by HTML, Java and python script.The server was evaluated using four published bacterial WGS data sets (V. cholerae, S. aureus CC398, S. Typhimurium and M. tuberculosis). The evaluation results for the first three cases was consistent and concordant for both raw reads and assembled genomes. In the latter case the original publication involved extensive filtering of SNPs, which could not be repeated using snpTree. The snpTree server is an easy to use option for rapid standardised and automatic SNP analysis in epidemiological studies also for users with limited bioinformatic experience. The web server is freely accessible at http://www.cbs.dtu.dk/services/snpTree-1.0/.

Cultural neurolinguistics.

PubMed

Chen, Chuansheng; Xue, Gui; Mei, Leilei; Chen, Chunhui; Dong, Qi

2009-01-01

As the only species that evolved to possess a language faculty, humans have been surprisingly generative in creating a diverse array of language systems. These systems vary in phonology, morphology, syntax, and written forms. Before the advent of modern brain-imaging techniques, little was known about how differences across languages are reflected in the brain. This chapter aims to provide an overview of an emerging area of research - cultural neurolinguistics - that examines systematic cross-cultural/crosslinguistic variations in the neural networks of languages. We first briefly describe general brain networks for written and spoken languages. We then discuss language-specific brain regions by highlighting differences in neural bases of different scripts (logographic vs. alphabetic scripts), orthographies (transparent vs. nontransparent orthographies), and tonality (tonal vs. atonal languages). We also discuss neural basis of second language and the role of native language experience in second-language acquisition. In the last section, we outline a general model that integrates culture and neural bases of language and discuss future directions of research in this area.

Writing World-Wide Web CGI scripts in the REXX language

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

Cottrell, R.L.A.

This talk is aimed at people who have experience with REXX and are interested in using it to write WWW CGI scripts. As part of this, the author describes several functions that are available in a library of REXX functions that simplify writing WWW CGI scripts. This library is freely available at //www.slac.standard.edu/slac/www/tool/cgi-rexx/.

PSRPOPPy: an open-source package for pulsar population simulations

NASA Astrophysics Data System (ADS)

Bates, S. D.; Lorimer, D. R.; Rane, A.; Swiggum, J.

2014-04-01

We have produced a new software package for the simulation of pulsar populations, PSRPOPPY, based on the PSRPOP package. The codebase has been re-written in Python (save for some external libraries, which remain in their native Fortran), utilizing the object-oriented features of the language, and improving the modularity of the code. Pre-written scripts are provided for running the simulations in `standard' modes of operation, but the code is flexible enough to support the writing of personalised scripts. The modular structure also makes the addition of experimental features (such as new models for period or luminosity distributions) more straightforward than with the previous code. We also discuss potential additions to the modelling capabilities of the software. Finally, we demonstrate some potential applications of the code; first, using results of surveys at different observing frequencies, we find pulsar spectral indices are best fitted by a normal distribution with mean -1.4 and standard deviation 1.0. Secondly, we model pulsar spin evolution to calculate the best fit for a relationship between a pulsar's luminosity and spin parameters. We used the code to replicate the analysis of Faucher-Giguère & Kaspi, and have subsequently optimized their power-law dependence of radio luminosity, L, with period, P, and period derivative, Ṗ. We find that the underlying population is best described by L ∝ P-1.39±0.09 Ṗ0.48±0.04 and is very similar to that found for γ-ray pulsars by Perera et al. Using this relationship, we generate a model population and examine the age-luminosity relation for the entire pulsar population, which may be measurable after future large-scale surveys with the Square Kilometre Array.

Analysis of Ligand-Receptor Association and Intermediate Transfer Rates in Multienzyme Nanostructures with All-Atom Brownian Dynamics Simulations.

PubMed

Roberts, Christopher C; Chang, Chia-En A

2016-08-25

We present the second-generation GeomBD Brownian dynamics software for determining interenzyme intermediate transfer rates and substrate association rates in biomolecular complexes. Substrate and intermediate association rates for a series of enzymes or biomolecules can be compared between the freely diffusing disorganized configuration and various colocalized or complexed arrangements for kinetic investigation of enhanced intermediate transfer. In addition, enzyme engineering techniques, such as synthetic protein conjugation, can be computationally modeled and analyzed to better understand changes in substrate association relative to native enzymes. Tools are provided to determine nonspecific ligand-receptor association residence times, and to visualize common sites of nonspecific association of substrates on receptor surfaces. To demonstrate features of the software, interenzyme intermediate substrate transfer rate constants are calculated and compared for all-atom models of DNA origami scaffold-bound bienzyme systems of glucose oxidase and horseradish peroxidase. Also, a DNA conjugated horseradish peroxidase enzyme was analyzed for its propensity to increase substrate association rates and substrate local residence times relative to the unmodified enzyme. We also demonstrate the rapid determination and visualization of common sites of nonspecific ligand-receptor association by using HIV-1 protease and an inhibitor, XK263. GeomBD2 accelerates simulations by precomputing van der Waals potential energy grids and electrostatic potential grid maps, and has a flexible and extensible support for all-atom and coarse-grained force fields. Simulation software is written in C++ and utilizes modern parallelization techniques for potential grid preparation and Brownian dynamics simulation processes. Analysis scripts, written in the Python scripting language, are provided for quantitative simulation analysis. GeomBD2 is applicable to the fields of biophysics, bioengineering, and enzymology in both predictive and explanatory roles.

Querying Provenance Information: Basic Notions and an Example from Paleoclimate Reconstruction

NASA Astrophysics Data System (ADS)

Stodden, V.; Ludaescher, B.; Bocinsky, K.; Kintigh, K.; Kohler, T.; McPhillips, T.; Rush, J.

2016-12-01

Computational models are used to reconstruct and explain past environments and to predict likely future environments. For example, Bocinsky and Kohler have performed a 2,000-year reconstruction of the rain-fed maize agricultural niche in the US Southwest. The resulting academic publications not only contain traditional method descriptions, figures, etc. but also links to code and data for basic transparency and reproducibility. Examples include ResearchCompendia.org and the new project "Merging Science and Cyberinfrastructure Pathways: The Whole Tale." Provenance information provides a further critical element to understand a published study and to possibly extend or challenge the findings of the original authors. We present different notions and uses of provenance information using a computational archaeology example, e.g., the common use of "provenance for others" (for transparency and reproducibility), but also the more elusive but equally important use of "provenance for self". To this end, we distinguish prospective provenance (a.k.a. workflow) from retrospective provenance (a.k.a. data lineage) and show how combinations of both forms of provenance can be used to answer different kinds of important questions about a workflow and its execution. Since many workflows are developed using scripting or special purpose languages such as Python and R, we employ an approach and toolkit called YesWorkflow that brings provenance modeling, capture, and querying into the realm of scripting. YesWorkflow employs the basic W3C PROV standard, as well as the ProvONE extension for sharing and exchanging retrospective and prospective provenance information, respectively. Finally, we argue that the utility of provenance information should be maximized by developing different kinds provenance questions and queries during the early phases of computational workflow design and implementation.

STATISTICAL RELATIONAL LEARNING AND SCRIPT INDUCTION FOR TEXTUAL INFERENCE

DTIC Science & Technology

2017-12-01

E 23rd St Austin , TX 78712 8. PERFORMING ORGANIZATION REPORT NUMBER 9. SPONSORING/MONITORING AGENCY NAME(S) AND ADDRESS(ES) Air Force Research ...Processing (EMNLP), Austin , TX , 2016. 
 Pichotta, K. and Mooney, R.J., “Using Sentence-Level LSTM Language Models for Script Inference,” Proceedings of the...on Uphill Battles in Language Processing, Austin , TX , 2016. 
 Rajani, N., and Mooney, R. J., “Stacked Ensembles of Information Extractors for

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

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.

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.

Technical integration of hippocampus, Basal Ganglia and physical models for spatial navigation.

PubMed

Fox, Charles; Humphries, Mark; Mitchinson, Ben; Kiss, Tamas; Somogyvari, Zoltan; Prescott, Tony

2009-01-01

Computational neuroscience is increasingly moving beyond modeling individual neurons or neural systems to consider the integration of multiple models, often constructed by different research groups. We report on our preliminary technical integration of recent hippocampal formation, basal ganglia and physical environment models, together with visualisation tools, as a case study in the use of Python across the modelling tool-chain. We do not present new modeling results here. The architecture incorporates leaky-integrator and rate-coded neurons, a 3D environment with collision detection and tactile sensors, 3D graphics and 2D plots. We found Python to be a flexible platform, offering a significant reduction in development time, without a corresponding significant increase in execution time. We illustrate this by implementing a part of the model in various alternative languages and coding styles, and comparing their execution times. For very large-scale system integration, communication with other languages and parallel execution may be required, which we demonstrate using the BRAHMS framework's Python bindings.

MatLab Script and Functional Programming

NASA Technical Reports Server (NTRS)

Shaykhian, Gholam Ali

2007-01-01

MatLab Script and Functional Programming: MatLab is one of the most widely used very high level programming languages for scientific and engineering computations. It is very user-friendly and needs practically no formal programming knowledge. Presented here are MatLab programming aspects and not just the MatLab commands for scientists and engineers who do not have formal programming training and also have no significant time to spare for learning programming to solve their real world problems. Specifically provided are programs for visualization. The MatLab seminar covers the functional and script programming aspect of MatLab language. Specific expectations are: a) Recognize MatLab commands, script and function. b) Create, and run a MatLab function. c) Read, recognize, and describe MatLab syntax. d) Recognize decisions, loops and matrix operators. e) Evaluate scope among multiple files, and multiple functions within a file. f) Declare, define and use scalar variables, vectors and matrices.

Enabling Remote and Automated Operations at The Red Buttes Observatory

NASA Astrophysics Data System (ADS)

Ellis, Tyler G.; Jang-Condell, Hannah; Kasper, David; Yeigh, Rex R.

2016-01-01

The Red Buttes Observatory (RBO) is a 60 centimeter Cassegrain telescope located ten miles south of Laramie, Wyoming. The size and proximity of the telescope comfortably make the site ideal for remote and automated observations. This task required development of confidence in control systems for the dome, telescope, and camera. Python and WinSCP script routines were created for the management of science images and weather. These scripts control the observatory via the ASCOM standard libraries and allow autonomous operation after initiation.The automation tasks were completed primarily to rejuvenate an aging and underutilized observatory with hopes to contribute to an international exoplanet hunting team with other interests in potentially hazardous asteroid detection. RBO is owned and operated solely by the University of Wyoming. The updates and proprietor status have encouraged the development of an undergraduate astronomical methods course including hands-on experience with a research telescope, a rarity in bachelor programs for astrophysics.

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.

START: a system for flexible analysis of hundreds of genomic signal tracks in few lines of SQL-like queries.

PubMed

Zhu, Xinjie; Zhang, Qiang; Ho, Eric Dun; Yu, Ken Hung-On; Liu, Chris; Huang, Tim H; Cheng, Alfred Sze-Lok; Kao, Ben; Lo, Eric; Yip, Kevin Y

2017-09-22

A genomic signal track is a set of genomic intervals associated with values of various types, such as measurements from high-throughput experiments. Analysis of signal tracks requires complex computational methods, which often make the analysts focus too much on the detailed computational steps rather than on their biological questions. Here we propose Signal Track Query Language (STQL) for simple analysis of signal tracks. It is a Structured Query Language (SQL)-like declarative language, which means one only specifies what computations need to be done but not how these computations are to be carried out. STQL provides a rich set of constructs for manipulating genomic intervals and their values. To run STQL queries, we have developed the Signal Track Analytical Research Tool (START, http://yiplab.cse.cuhk.edu.hk/start/ ), a system that includes a Web-based user interface and a back-end execution system. The user interface helps users select data from our database of around 10,000 commonly-used public signal tracks, manage their own tracks, and construct, store and share STQL queries. The back-end system automatically translates STQL queries into optimized low-level programs and runs them on a computer cluster in parallel. We use STQL to perform 14 representative analytical tasks. By repeating these analyses using bedtools, Galaxy and custom Python scripts, we show that the STQL solution is usually the simplest, and the parallel execution achieves significant speed-up with large data files. Finally, we describe how a biologist with minimal formal training in computer programming self-learned STQL to analyze DNA methylation data we produced from 60 pairs of hepatocellular carcinoma (HCC) samples. Overall, STQL and START provide a generic way for analyzing a large number of genomic signal tracks in parallel easily.

A web access script language to support clinical application development.

PubMed

O'Kane, K C; McColligan, E E

1998-02-01

This paper describes the development of a script language to support the implementation of decentralized, clinical information applications on the World Wide Web (Web). The goal of this work is to facilitate construction of low overhead, fully functional clinical information systems that can be accessed anywhere by low cost Web browsers to search, retrieve and analyze stored patient data. The Web provides a model of network access to data bases on a global scale. Although it was originally conceived as a means to exchange scientific documents, Web browsers and servers currently support access to a wide variety of audio, video, graphical and text based data to a rapidly growing community. Access to these services is via inexpensive client software browsers that connect to servers by means of the open architecture of the Internet. In this paper, the design and implementation of a script language that supports the development of low cost, Web-based, distributed clinical information systems for both Inter- and Intra-Net use is presented. The language is based on the Mumps language and, consequently, supports many legacy applications with few modifications. Several enhancements, however, have been made to support modern programming practices and the Web interface. The interpreter for the language also supports standalone program execution on Unix, MS-Windows, OS/2 and other operating systems.

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.

[Radiology information system using HTML, JavaScript, and Web server].

PubMed

Sone, M; Sasaki, M; Oikawa, H; Yoshioka, K; Ehara, S; Tamakawa, Y

1997-12-01

We have developed a radiology information system using intranet techniques, including hypertext markup language, JavaScript, and Web server. JavaScript made it possible to develop an easy-to-use application, as well as to reduce network traffic and load on the server. The system we have developed is inexpensive and flexible, and its development and maintenance are much easier than with the previous system.

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

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.

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

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.

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.

Renaissance of the Web

NASA Astrophysics Data System (ADS)

McCarty, M.

2009-09-01

The renaissance of the web has driven development of many new technologies that have forever changed the way we write software. The resulting tools have been applied to both solve problems and creat new ones in a wide range of domains ranging from monitor and control user interfaces to information distribution. This discussion covers which of and how these technologies are being used in the astronomical computing community. Topics include JavaScript, Cascading Style Sheets, HTML, XML, JSON, RSS, iCalendar, Java, PHP, Python, Ruby on Rails, database technologies, and web frameworks/design patterns.

Dshell++: A Component Based, Reusable Space System Simulation Framework

NASA Technical Reports Server (NTRS)

Lim, Christopher S.; Jain, Abhinandan

2009-01-01

This paper describes the multi-mission Dshell++ simulation framework for high fidelity, physics-based simulation of spacecraft, robotic manipulation and mobility systems. Dshell++ is a C++/Python library which uses modern script driven object-oriented techniques to allow component reuse and a dynamic run-time interface for complex, high-fidelity simulation of spacecraft and robotic systems. The goal of the Dshell++ architecture is to manage the inherent complexity of physicsbased simulations while supporting component model reuse across missions. The framework provides several features that support a large degree of simulation configurability and usability.

Parallel File System I/O Performance Testing On LANL Clusters

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

Wiens, Isaac Christian; Green, Jennifer Kathleen

2016-08-18

These are slides from a presentation on parallel file system I/O performance testing on LANL clusters. I/O is a known bottleneck for HPC applications. Performance optimization of I/O is often required. This summer project entailed integrating IOR under Pavilion and automating the results analysis. The slides cover the following topics: scope of the work, tools utilized, IOR-Pavilion test workflow, build script, IOR parameters, how parameters are passed to IOR, *run_ior: functionality, Python IOR-Output Parser, Splunk data format, Splunk dashboard and features, and future work.

High-performance analysis of filtered semantic graphs

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

Buluc, Aydin; Fox, Armando; Gilbert, John R.

2012-01-01

High performance is a crucial consideration when executing a complex analytic query on a massive semantic graph. In a semantic graph, vertices and edges carry "attributes" of various types. Analytic queries on semantic graphs typically depend on the values of these attributes; thus, the computation must either view the graph through a filter that passes only those individual vertices and edges of interest, or else must first materialize a subgraph or subgraphs consisting of only the vertices and edges of interest. The filtered approach is superior due to its generality, ease of use, and memory efficiency, but may carry amore » performance cost. In the Knowledge Discovery Toolbox (KDT), a Python library for parallel graph computations, the user writes filters in a high-level language, but those filters result in relatively low performance due to the bottleneck of having to call into the Python interpreter for each edge. In this work, we use the Selective Embedded JIT Specialization (SEJITS) approach to automatically translate filters defined by programmers into a lower-level efficiency language, bypassing the upcall into Python. We evaluate our approach by comparing it with the high-performance C++ /MPI Combinatorial BLAS engine, and show that the productivity gained by using a high-level filtering language comes without sacrificing performance.« less

Context recognition for a hyperintensional inference machine

NASA Astrophysics Data System (ADS)

Duží, Marie; Fait, Michal; Menšík, Marek

2017-07-01

The goal of this paper is to introduce the algorithm of context recognition in the functional programming language TIL-Script, which is a necessary condition for the implementation of the TIL-Script inference machine. The TIL-Script language is an operationally isomorphic syntactic variant of Tichý's Transparent Intensional Logic (TIL). From the formal point of view, TIL is a hyperintensional, partial, typed λ-calculus with procedural semantics. Hyperintensional, because TIL λ-terms denote procedures (defined as TIL constructions) producing set-theoretic functions rather than the functions themselves; partial, because TIL is a logic of partial functions; and typed, because all the entities of TIL ontology, including constructions, receive a type within a ramified hierarchy of types. These features make it possible to distinguish three levels of abstraction at which TIL constructions operate. At the highest hyperintensional level the object to operate on is a construction (though a higher-order construction is needed to present this lower-order construction as an object of predication). At the middle intensional level the object to operate on is the function presented, or constructed, by a construction, while at the lowest extensional level the object to operate on is the value (if any) of the presented function. Thus a necessary condition for the development of an inference machine for the TIL-Script language is recognizing a context in which a construction occurs, namely extensional, intensional and hyperintensional context, in order to determine the type of an argument at which a given inference rule can be properly applied. As a result, our logic does not flout logical rules of extensional logic, which makes it possible to develop a hyperintensional inference machine for the TIL-Script language.

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…

A Pythonic Approach for Computational Geosciences and Geo-Data Processing

NASA Astrophysics Data System (ADS)

Morra, G.; Yuen, D. A.; Lee, S. M.

2016-12-01

Computational methods and data analysis play a constantly increasing role in Earth Sciences however students and professionals need to climb a steep learning curve before reaching a sufficient level that allows them to run effective models. Furthermore the recent arrival and new powerful machine learning tools such as Torch and Tensor Flow has opened new possibilities but also created a new realm of complications related to the completely different technology employed. We present here a series of examples entirely written in Python, a language that combines the simplicity of Matlab with the power and speed of compiled languages such as C, and apply them to a wide range of geological processes such as porous media flow, multiphase fluid-dynamics, creeping flow and many-faults interaction. We also explore ways in which machine learning can be employed in combination with numerical modelling. From immediately interpreting a large number of modeling results to optimizing a set of modeling parameters to obtain a desired optimal simulation. We show that by using Python undergraduate and graduate can learn advanced numerical technologies with a minimum dedicated effort, which in turn encourages them to develop more numerical tools and quickly progress in their computational abilities. We also show how Python allows combining modeling with machine learning as pieces of LEGO, therefore simplifying the transition towards a new kind of scientific geo-modelling. The conclusion is that Python is an ideal tool to create an infrastructure for geosciences that allows users to quickly develop tools, reuse techniques and encourage collaborative efforts to interpret and integrate geo-data in profound new ways.

Computers in Small Libraries: Learning Server-Side Scripting

ERIC Educational Resources Information Center

Roberts, Gary

2005-01-01

In this column, the author compares and contrasts the most popular scripting languages that are used to create truly dynamic service-oriented Web sites, building a conceptual framework that be can used as a starting point for specific server-side library projects.

Screening_mgmt: a Python module for managing screening data.

PubMed

Helfenstein, Andreas; Tammela, Päivi

2015-02-01

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

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.

Interfacing modeling suite Physics Of Eclipsing Binaries 2.0 with a Virtual Reality Platform

NASA Astrophysics Data System (ADS)

Harriett, Edward; Conroy, Kyle; Prša, Andrej; Klassner, Frank

2018-01-01

To explore alternate methods for modeling eclipsing binary stars, we extrapolate upon PHOEBE’s (PHysics Of Eclipsing BinariEs) capabilities in a virtual reality (VR) environment to create an immersive and interactive experience for users. The application used is Vizard, a python-scripted VR development platform for environments such as Cave Automatic Virtual Environment (CAVE) and other off-the-shelf VR headsets. Vizard allows the freedom for all modeling to be precompiled without compromising functionality or usage on its part. The system requires five arguments to be precomputed using PHOEBE’s python front-end: the effective temperature, flux, relative intensity, vertex coordinates, and orbits; the user can opt to implement other features from PHOEBE to be accessed within the simulation as well. Here we present the method for making the data observables accessible in real time. An Occulus Rift will be available for a live showcase of various cases of VR rendering of PHOEBE binary systems including detached and contact binary stars.

Fourier-Bessel Particle-In-Cell (FBPIC) v0.1.0

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

Lehe, Remi; Kirchen, Manuel; Jalas, Soeren

The Fourier-Bessel Particle-In-Cell code is a scientific simulation software for relativistic plasma physics. It is a Particle-In-Cell code whose distinctive feature is to use a spectral decomposition in cylindrical geometry. This decomposition allows to combine the advantages of spectral 3D Cartesian PIC codes (high accuracy and stability) and those of finite-difference cylindrical PIC codes with azimuthal decomposition (orders-of-magnitude speedup when compared to 3D simulations). The code is built on Python and can run both on CPU and GPU (the GPU runs being typically 1 or 2 orders of magnitude faster than the corresponding CPU runs.) The code has the exactmore » same output format as the open-source PIC codes Warp and PIConGPU (openPMD format: openpmd.org) and has a very similar input format as Warp (Python script with many similarities). There is therefore tight interoperability between Warp and FBPIC, and this interoperability will increase even more in the future.« less

Combining Open-Source Packages for Planetary Exploration

NASA Astrophysics Data System (ADS)

Schmidt, Albrecht; Grieger, Björn; Völk, Stefan

2015-04-01

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

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

Language and Literacy: The Case of India.

ERIC Educational Resources Information Center

Sridhar, Kamal K.

Language and literacy issues in India are reviewed in terms of background, steps taken to combat illiteracy, and some problems associated with literacy. The following facts are noted: India has 106 languages spoken by more than 685 million people, there are several minor script systems, a major language has different dialects, a language may use…

The World's Writing Systems.

ERIC Educational Resources Information Center

Daniels, Peter T., Ed.; Bright, William, Ed.

This survey of the world's written languages consists of a series of historical sketches of different languages, each including a table of signforms in their standard order and their variations, but focusing primarily on how the sounds of the language are represented in writing. A brief text in the language(s) the script is used for is also…

MTpy - Python Tools for Magnetotelluric Data Processing and Analysis

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

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.

The First Two R's.

ERIC Educational Resources Information Center

Tzeng, Ovid J. L.; Wang, William S. Y.

1983-01-01

Indicates that the way different languages reduce speech to script affects how visual information is processed in the brain, suggesting that the relation between script and speech underlying all types of writing systems plays an important part in reading behavior. Compares memory performance of native English/Chinese speakers. (JN)

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

[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.

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 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.

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

Adapting the iSNOBAL model for improved visualization in a GIS environment

NASA Astrophysics Data System (ADS)

Johansen, W. J.; Delparte, D.

2014-12-01

Snowmelt is a primary means of crucial water resources in much of the western United States. Researchers are developing models that estimate snowmelt to aid in water resource management. One such model is the image snowcover energy and mass balance (iSNOBAL) model. It uses input climate grids to simulate the development and melting of snowpack in mountainous regions. This study looks at applying this model to the Reynolds Creek Experimental Watershed in southwestern Idaho, utilizing novel approaches incorporating geographic information systems (GIS). To improve visualization of the iSNOBAL model, we have adapted it to run in a GIS environment. This type of environment is suited to both the input grid creation and the visualization of results. The data used for input grid creation can be stored locally or on a web-server. Kriging interpolation embedded within Python scripts are used to create air temperature, soil temperature, humidity, and precipitation grids, while built-in GIS and existing tools are used to create solar radiation and wind grids. Additional Python scripting is then used to perform model calculations. The final product is a user-friendly and accessible version of the iSNOBAL model, including the ability to easily visualize and interact with model results, all within a web- or desktop-based GIS environment. This environment allows for interactive manipulation of model parameters and visualization of the resulting input grids for the model calculations. Future work is moving towards adapting the model further for use in a 3D gaming engine for improved visualization and interaction.

A Tool for Conditions Tag Management in ATLAS

NASA Astrophysics Data System (ADS)

Sharmazanashvili, A.; Batiashvili, G.; Gvaberidze, G.; Shekriladze, L.; Formica, A.; Atlas Collaboration

2014-06-01

ATLAS Conditions data include about 2 TB in a relational database and 400 GB of files referenced from the database. Conditions data is entered and retrieved using COOL, the API for accessing data in the LCG Conditions Database infrastructure. It is managed using an ATLAS-customized python based tool set. Conditions data are required for every reconstruction and simulation job, so access to them is crucial for all aspects of ATLAS data taking and analysis, as well as by preceding tasks to derive optimal corrections to reconstruction. Optimized sets of conditions for processing are accomplished using strict version control on those conditions: a process which assigns COOL Tags to sets of conditions, and then unifies those conditions over data-taking intervals into a COOL Global Tag. This Global Tag identifies the set of conditions used to process data so that the underlying conditions can be uniquely identified with 100% reproducibility should the processing be executed again. Understanding shifts in the underlying conditions from one tag to another and ensuring interval completeness for all detectors for a set of runs to be processed is a complex task, requiring tools beyond the above mentioned python utilities. Therefore, a JavaScript /PHP based utility called the Conditions Tag Browser (CTB) has been developed. CTB gives detector and conditions experts the possibility to navigate through the different databases and COOL folders; explore the content of given tags and the differences between them, as well as their extent in time; visualize the content of channels associated with leaf tags. This report describes the structure and PHP/ JavaScript classes of functions of the CTB.

RGG: A general GUI Framework for R scripts

PubMed Central

Visne, Ilhami; Dilaveroglu, Erkan; Vierlinger, Klemens; Lauss, Martin; Yildiz, Ahmet; Weinhaeusel, Andreas; Noehammer, Christa; Leisch, Friedrich; Kriegner, Albert

2009-01-01

Background R is the leading open source statistics software with a vast number of biostatistical and bioinformatical analysis packages. To exploit the advantages of R, extensive scripting/programming skills are required. Results We have developed a software tool called R GUI Generator (RGG) which enables the easy generation of Graphical User Interfaces (GUIs) for the programming language R by adding a few Extensible Markup Language (XML) – tags. RGG consists of an XML-based GUI definition language and a Java-based GUI engine. GUIs are generated in runtime from defined GUI tags that are embedded into the R script. User-GUI input is returned to the R code and replaces the XML-tags. RGG files can be developed using any text editor. The current version of RGG is available as a stand-alone software (RGGRunner) and as a plug-in for JGR. Conclusion RGG is a general GUI framework for R that has the potential to introduce R statistics (R packages, built-in functions and scripts) to users with limited programming skills and helps to bridge the gap between R developers and GUI-dependent users. RGG aims to abstract the GUI development from individual GUI toolkits by using an XML-based GUI definition language. Thus RGG can be easily integrated in any software. The RGG project further includes the development of a web-based repository for RGG-GUIs. RGG is an open source project licensed under the Lesser General Public License (LGPL) and can be downloaded freely at PMID:19254356

Does processing a shallow and a deep orthography produce different brain activity patterns? An ERP study conducted in Hebrew.

PubMed

Bar-Kochva, Irit

2011-01-01

Orthographies range from shallow orthographies with transparent grapheme-phoneme relations, to deep orthographies, in which these relations are opaque. Two forms of script transcribe the Hebrew language: the shallow pointed script (with diacritics) and the deep unpointed script (without diacritics). This study was set out to examine whether the reading of these scripts evokes distinct brain activity. Preliminary results indicate distinct Event-related-potentials (ERPs). As an equivalent finding was absent when ERPs of non-orthographic stimuli with and without meaningless diacritics were compared, the results imply that print-specific aspects of processing account for the distinct activity elicited by the pointed and unpointed scripts.

A Markov model of the Indus script

PubMed Central

Rao, Rajesh P. N.; Yadav, Nisha; Vahia, Mayank N.; Joglekar, Hrishikesh; Adhikari, R.; Mahadevan, Iravatham

2009-01-01

Although no historical information exists about the Indus civilization (flourished ca. 2600–1900 B.C.), archaeologists have uncovered about 3,800 short samples of a script that was used throughout the civilization. The script remains undeciphered, despite a large number of attempts and claimed decipherments over the past 80 years. Here, we propose the use of probabilistic models to analyze the structure of the Indus script. The goal is to reveal, through probabilistic analysis, syntactic patterns that could point the way to eventual decipherment. We illustrate the approach using a simple Markov chain model to capture sequential dependencies between signs in the Indus script. The trained model allows new sample texts to be generated, revealing recurring patterns of signs that could potentially form functional subunits of a possible underlying language. The model also provides a quantitative way of testing whether a particular string belongs to the putative language as captured by the Markov model. Application of this test to Indus seals found in Mesopotamia and other sites in West Asia reveals that the script may have been used to express different content in these regions. Finally, we show how missing, ambiguous, or unreadable signs on damaged objects can be filled in with most likely predictions from the model. Taken together, our results indicate that the Indus script exhibits rich synactic structure and the ability to represent diverse content. both of which are suggestive of a linguistic writing system rather than a nonlinguistic symbol system. PMID:19666571

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

PubMed Central

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

2008-01-01

Neuropeptides and hormones are signaling molecules that support cell–cell communication in the central nervous system. Experimentally characterizing neuropeptides requires significant efforts because of the complex and variable processing of prohormone precursor proteins into neuropeptides and hormones. We demonstrate the power and flexibility of the Python language to develop components of an bioinformatic analytical pipeline to identify precursors from genomic data and to predict cleavage as these precursors are en route to the final bioactive peptides. We identified 75 precursors in the rhesus genome, predicted cleavage sites using support vector machines and compared the rhesus predictions to putative assignments based on homology to human sequences. The correct classification rate of cleavage using the support vector machines was over 97% for both human and rhesus data sets. The functionality of Python has been important to develop and maintain NeuroPred (http://neuroproteomics.scs.uiuc.edu/neuropred.html), a user-centered web application for the neuroscience community that provides cleavage site prediction from a wide range of models, precision and accuracy statistics, post-translational modifications, and the molecular mass of potential peptides. The combined results illustrate the suitability of the Python language to implement an all-inclusive bioinformatics approach to predict neuropeptides that encompasses a large number of interdependent steps, from scanning genomes for precursor genes to identification of potential bioactive neuropeptides. PMID:19169350

Statistical Analysis of the Indus Script Using n-Grams

PubMed Central

Yadav, Nisha; Joglekar, Hrishikesh; Rao, Rajesh P. N.; Vahia, Mayank N.; Adhikari, Ronojoy; Mahadevan, Iravatham

2010-01-01

The Indus script is one of the major undeciphered scripts of the ancient world. The small size of the corpus, the absence of bilingual texts, and the lack of definite knowledge of the underlying language has frustrated efforts at decipherment since the discovery of the remains of the Indus civilization. Building on previous statistical approaches, we apply the tools of statistical language processing, specifically n-gram Markov chains, to analyze the syntax of the Indus script. We find that unigrams follow a Zipf-Mandelbrot distribution. Text beginner and ender distributions are unequal, providing internal evidence for syntax. We see clear evidence of strong bigram correlations and extract significant pairs and triplets using a log-likelihood measure of association. Highly frequent pairs and triplets are not always highly significant. The model performance is evaluated using information-theoretic measures and cross-validation. The model can restore doubtfully read texts with an accuracy of about 75%. We find that a quadrigram Markov chain saturates information theoretic measures against a held-out corpus. Our work forms the basis for the development of a stochastic grammar which may be used to explore the syntax of the Indus script in greater detail. PMID:20333254

Sparks Will Fly: engineering creative script conflicts

NASA Astrophysics Data System (ADS)

Veale, Tony; Valitutti, Alessandro

2017-10-01

Scripts are often dismissed as the stuff of good movies and bad politics. They codify cultural experience so rigidly that they remove our freedom of choice and become the very antithesis of creativity. Yet, mental scripts have an important role to play in our understanding of creative behaviour, since a deliberate departure from an established script can produce results that are simultaneously novel and familiar, especially when others stick to the conventional script. Indeed, creative opportunities often arise at the overlapping boundaries of two scripts that antagonistically compete to mentally organise the same situation. This work explores the computational integration of competing scripts to generate creative friction in short texts that are surprising but meaningful. Our exploration considers conventional macro-scripts - ordered sequences of actions - and the less obvious micro-scripts that operate at even the lowest levels of language. For the former, we generate plots that squeeze two scripts into a single mini-narrative; for the latter, we generate ironic descriptions that use conflicting scripts to highlight the speaker's pragmatic insincerity. We show experimentally that verbal irony requires both kinds of scripts - macro and micro - to work together to reliably generate creative sparks from a speaker's subversive intent.

Culture, Ethics, Scripts, and Gifts.

ERIC Educational Resources Information Center

Messerschmitt, Dorothy; Hafernik, Johnnie Johnson; Vandrick, Stephanie

1997-01-01

Discusses gift-giving patterns in different cultures, particularly in relation to teacher-student interactions in English-as-a-Second-Language (ESL) instruction. Situations in which gift-giving can raise ethical questions and how to teach culturally diverse students about this issue are highlighted. Script theory provides a theoretical basis for…

Effects of peer-mediated implementation of visual scripts in middle school.

PubMed

Ganz, Jennifer B; Heath, Amy K; Lund, Emily M; Camargo, Siglia P H; Rispoli, Mandy J; Boles, Margot; Plaisance, Lauren

2012-05-01

Although research has investigated the impact of peer-mediated interventions and visual scripts on social and communication skills in children with autism spectrum disorders, no studies to date have investigated peer-mediated implementation of scripts. This study investigated the effects of peer-implemented scripts on a middle school student with autism, intellectual impairments, and speech-language impairment via a multiple baseline single-case research design across behaviors. The target student demonstrated improvements in three communicative behaviors when implemented by a trained peer; however, behaviors did not generalize to use with an untrained typically developing peer.

Towards a Software Framework to Support Deployment of Low Cost End-to-End Hydroclimatological Sensor Network

NASA Astrophysics Data System (ADS)

Celicourt, P.; Piasecki, M.

2015-12-01

Deployment of environmental sensors assemblies based on cheap platforms such as Raspberry Pi and Arduino have gained much attention over the past few years. While they are more attractive due to their ability to be controlled with a few programming language choices, the configuration task can become quite complex due to the need of having to learn several different proprietary data formats and protocols which constitute a bottleneck for the expansion of sensor network. In response to this rising complexity the Institute of Electrical and Electronics Engineers (IEEE) has sponsored the development of the IEEE 1451 standard in an attempt to introduce a common standard. The most innovative concept of the standard is the Transducer Electronic Data Sheet (TEDS) which enables transducers to self-identify, self-describe, self-calibrate, to exhibit plug-and-play functionality, etc. We used Python to develop an IEEE 1451.0 platform-independent graphical user interface to generate and provide sufficient information about almost ANY sensor and sensor platforms for sensor programming purposes, automatic calibration of sensors data, incorporation of back-end demands on data management in TEDS for automatic standard-based data storage, search and discovery purposes. These features are paramount to make data management much less onerous in large scale sensor network. Along with the TEDS Creator, we developed a tool namely HydroUnits for three specific purposes: encoding of physical units in the TEDS, dimensional analysis, and on-the-fly conversion of time series allowing users to retrieve data in a desired equivalent unit while accommodating unforeseen and user-defined units. In addition, our back-end data management comprises the Python/Django equivalent of the CUAHSI Observations Data Model (ODM) namely DjangODM that will be hosted by a MongoDB Database Server which offers more convenience for our application. We are also developing a data which will be paired with the data autoloading capability of Django and a TEDS processing script to populate the database with the incoming data. The Python WaterOneFlow Web Services developed by the Texas Water Development Board will be used to publish the data. The software suite is being tested on the Raspberry Pi as end node and a laptop PC as the base station in a wireless setting.

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.

Ada (Tradename) Compiler Validation Summary Report. International Business Machines Corporation. IBM Development System for the Ada Language for VM/CMS, Version 1.0. IBM 4381 (IBM System/370) under VM/CMS.

DTIC Science & Technology

1986-04-29

COMPILER VALIDATION SUMMARY REPORT: International Business Machines Corporation IBM Development System for the Ada Language for VM/CMS, Version 1.0 IBM 4381...tested using command scripts provided by International Business Machines Corporation. These scripts were reviewed by the validation team. Test.s were run...s): IBM 4381 (System/370) Operating System: VM/CMS, release 3.6 International Business Machines Corporation has made no deliberate extensions to the

An ESL Audio-Script Writing Workshop

ERIC Educational Resources Information Center

Miller, Carla

2012-01-01

The roles of dialogue, collaborative writing, and authentic communication have been explored as effective strategies in second language writing classrooms. In this article, the stages of an innovative, multi-skill writing method, which embeds students' personal voices into the writing process, are explored. A 10-step ESL Audio Script Writing Model…

Flexible Environments for Grand-Challenge Simulation in Climate Science

NASA Astrophysics Data System (ADS)

Pierrehumbert, R.; Tobis, M.; Lin, J.; Dieterich, C.; Caballero, R.

2004-12-01

Current climate models are monolithic codes, generally in Fortran, aimed at high-performance simulation of the modern climate. Though they adequately serve their designated purpose, they present major barriers to application in other problems. Tailoring them to paleoclimate of planetary simulations, for instance, takes months of work. Theoretical studies, where one may want to remove selected processes or break feedback loops, are similarly hindered. Further, current climate models are of little value in education, since the implementation of textbook concepts and equations in the code is obscured by technical detail. The Climate Systems Center at the University of Chicago seeks to overcome these limitations by bringing modern object-oriented design into the business of climate modeling. Our ultimate goal is to produce an end-to-end modeling environment capable of configuring anything from a simple single-column radiative-convective model to a full 3-D coupled climate model using a uniform, flexible interface. Technically, the modeling environment is implemented as a Python-based software component toolkit: key number-crunching procedures are implemented as discrete, compiled-language components 'glued' together and co-ordinated by Python, combining the high performance of compiled languages and the flexibility and extensibility of Python. We are incrementally working towards this final objective following a series of distinct, complementary lines. We will present an overview of these activities, including PyOM, a Python-based finite-difference ocean model allowing run-time selection of different Arakawa grids and physical parameterizations; CliMT, an atmospheric modeling toolkit providing a library of 'legacy' radiative, convective and dynamical modules which can be knitted into dynamical models, and PyCCSM, a version of NCAR's Community Climate System Model in which the coupler and run-control architecture are re-implemented in Python, augmenting its flexibility and adaptability.

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.

Mind the gap - do we need more geoscientific expertise for developing R?

NASA Astrophysics Data System (ADS)

Dietze, Michael; Kreutzer, Sebastian; Korup, Oliver

2017-04-01

R has reached a high level of acceptance and usage among geoscientists worldwide, including both users and developers. These two groups are not mutually exclusive but overlap strongly. This is a favourable situation to promote the implementation of new functionalities as packages and shared scripts. Despite this positive trend there is a series of missing functionalities. Likewise, other languages, such as Python, Matlab, C++ or FORTRAN, provide similar possibilities like R and have been used for addressing needs for such missing functionalities already long ago. R allows in principal to implement such lacking functionalities - but only if they have been identified and communicated amongst the community in a transparent way. Our session addresses this challenge. The PICO presentation gives a brief overview of the directions of R functionalities in the field of geosciences and identifies major gaps, from the viewpoint of us session conveners and most importantly based on the input of participating scientists. We invite all scientists to discuss and contribute knowledge to this topic based on their experiences and requirements. The suggestions will be broadcast as live updates during the PICO session and beyond. We intend to work towards building an active community of interacting developers and users to fill identified gaps to develop new powerful functionalities in the R environment.

Tools for open geospatial science

NASA Astrophysics Data System (ADS)

Petras, V.; Petrasova, A.; Mitasova, H.

2017-12-01

Open science uses open source to deal with reproducibility challenges in data and computational sciences. However, just using open source software or making the code public does not make the research reproducible. Moreover, the scientists face the challenge of learning new unfamiliar tools and workflows. In this contribution, we will look at a graduate-level course syllabus covering several software tools which make validation and reuse by a wider professional community possible. For the novices in the open science arena, we will look at how scripting languages such as Python and Bash help us reproduce research (starting with our own work). Jupyter Notebook will be introduced as a code editor, data exploration tool, and a lab notebook. We will see how Git helps us not to get lost in revisions and how Docker is used to wrap all the parts together using a single text file so that figures for a scientific paper or a technical report can be generated with a single command. We will look at examples of software and publications in the geospatial domain which use these tools and principles. Scientific contributions to GRASS GIS, a powerful open source desktop GIS and geoprocessing backend, will serve as an example of why and how to publish new algorithms and tools as part of a bigger open source project.

Sirepo - Warp

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

Nagler, Robert; Moeller, Paul

Sirepo is an open source framework for cloud computing. The graphical user interface (GUI) for Sirepo, also known as the client, executes in any HTML5 compliant web browser on any computing platform, including tablets. The client is built in JavaScript, making use of the following open source libraries: Bootstrap, which is fundamental for cross-platform web applications; AngularJS, which provides a model–view–controller (MVC) architecture and GUI components; and D3.js, which provides interactive plots and data-driven transformations. The Sirepo server is built on the following Python technologies: Flask, which is a lightweight framework for web development; Jin-ja, which is a secure andmore » widely used templating language; and Werkzeug, a utility library that is compliant with the WSGI standard. We use Nginx as the HTTP server and proxy, which provides a scalable event-driven architecture. The physics codes supported by Sirepo execute inside a Docker container. One of the codes supported by Sirepo is Warp. Warp is a particle-in-cell (PIC) code de-signed to simulate high-intensity charged particle beams and plasmas in both the electrostatic and electromagnetic regimes, with a wide variety of integrated physics models and diagnostics. At pre-sent, Sirepo supports a small subset of Warp’s capabilities. Warp is open source and is part of the Berkeley Lab Accelerator Simulation Toolkit.« less

System for Automated Geoscientific Analyses (SAGA) v. 2.1.4

NASA Astrophysics Data System (ADS)

Conrad, O.; Bechtel, B.; Bock, M.; Dietrich, H.; Fischer, E.; Gerlitz, L.; Wehberg, J.; Wichmann, V.; Böhner, J.

2015-02-01

The System for Automated Geoscientific Analyses (SAGA) is an open-source Geographic Information System (GIS), mainly licensed under the GNU General Public License. Since its first release in 2004, SAGA has rapidly developed from a specialized tool for digital terrain analysis to a comprehensive and globally established GIS platform for scientific analysis and modeling. SAGA is coded in C++ in an object oriented design and runs under several operating systems including Windows and Linux. Key functional features of the modular organized software architecture comprise an application programming interface for the development and implementation of new geoscientific methods, an easily approachable graphical user interface with many visualization options, a command line interpreter, and interfaces to scripting and low level programming languages like R and Python. The current version 2.1.4 offers more than 700 tools, which are implemented in dynamically loadable libraries or shared objects and represent the broad scopes of SAGA in numerous fields of geoscientific endeavor and beyond. In this paper, we inform about the system's architecture, functionality, and its current state of development and implementation. Further, we highlight the wide spectrum of scientific applications of SAGA in a review of published studies with special emphasis on the core application areas digital terrain analysis, geomorphology, soil science, climatology and meteorology, as well as remote sensing.

Configuration Tool for the Trusted Computing Exemplar Project

DTIC Science & Technology

2009-12-01

languages were examined: Microsoft .NET [8], Apple Cocoa (Objective-C) [9], wxPython [10], and Java [11]. Since every language has its pros and...languages using the criteria described above. Based on the developer’s limited experience and knowledge of Microsoft .NET and Apple Cocoa (Objective...became a tabbed panel within a separate window panel. Figure 9 depicts this evolution of the conceptual design. In Figure 9, the table column

The fast azimuthal integration Python library: pyFAI.

PubMed

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

2015-04-01

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

The Transition from VMS to Unix Operations for STScI's Science Planning and Scheduling Team

NASA Astrophysics Data System (ADS)

Adler, D. S.; Taylor, D. K.

The Science Planning and Scheduling Team of the Space Telescope Science Institute currently uses the VMS operating system. SPST began a transition to Unix-based operations in the summer of 1999. The main tasks for SPST to address in the Unix transition are: (1) converting the current SPST operational tools from DCL to Python; (2) converting our database report scripts from SQL; (3) adopting a Unix-based code management system; and (4) training the SPST staff. The goal is to fully transition the team to Unix operations by the end of 2001.

Automated delineation and characterization of watersheds for more than 3,000 surface-water-quality monitoring stations active in 2010 in Texas

USGS Publications Warehouse

Archuleta, Christy-Ann M.; Gonzales, Sophia L.; Maltby, David R.

2012-01-01

The U.S. Geological Survey (USGS), in cooperation with the Texas Commission on Environmental Quality, developed computer scripts and applications to automate the delineation of watershed boundaries and compute watershed characteristics for more than 3,000 surface-water-quality monitoring stations in Texas that were active during 2010. Microsoft Visual Basic applications were developed using ArcGIS ArcObjects to format the source input data required to delineate watershed boundaries. Several automated scripts and tools were developed or used to calculate watershed characteristics using Python, Microsoft Visual Basic, and the RivEX tool. Automated methods were augmented by the use of manual methods, including those done using ArcMap software. Watershed boundaries delineated for the monitoring stations are limited to the extent of the Subbasin boundaries in the USGS Watershed Boundary Dataset, which may not include the total watershed boundary from the monitoring station to the headwaters.

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

Barnette, Daniel W.

eCo-PylotDB, written completely in Python, provides a script that parses incoming emails and prepares extracted data for submission to a database table. The script extracts the database server, the database table, the server password, and the server username all from the email address to which the email is sent. The database table is specified on the Subject line. Any text in the body of the email is extracted as user comments for the database table. Attached files are extracted as data files with each file submitted to a specified table field but in separate rows of the targeted database table.more » Other information such as sender, date, time, and machine from which the email was sent is extracted and submitted to the database table as well. An email is sent back to the user specifying whether the data from the initial email was accepted or rejected by the database server. If rejected, the return email includes details as to why.« less

Software-defined Quantum Networking Ecosystem

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

Humble, Travis S.; Sadlier, Ronald

The software enables a user to perform modeling and simulation of software-defined quantum networks. The software addresses the problem of how to synchronize transmission of quantum and classical signals through multi-node networks and to demonstrate quantum information protocols such as quantum teleportation. The software approaches this problem by generating a graphical model of the underlying network and attributing properties to each node and link in the graph. The graphical model is then simulated using a combination of discrete-event simulators to calculate the expected state of each node and link in the graph at a future time. A user interacts withmore » the software by providing an initial network model and instantiating methods for the nodes to transmit information with each other. This includes writing application scripts in python that make use of the software library interfaces. A user then initiates the application scripts, which invokes the software simulation. The user then uses the built-in diagnostic tools to query the state of the simulation and to collect statistics on synchronization.« less

SciServer: An Online Collaborative Environment for Big Data in Research and Education

NASA Astrophysics Data System (ADS)

Raddick, Jordan; Souter, Barbara; Lemson, Gerard; Taghizadeh-Popp, Manuchehr

2017-01-01

For the past year, SciServer Compute (http://compute.sciserver.org) has offered access to big data resources running within server-side Docker containers. Compute has allowed thousands of researchers to bring advanced analysis to big datasets like the Sloan Digital Sky Survey and others, while keeping the analysis close to the data for better performance and easier read/write access. SciServer Compute is just one part of the SciServer system being developed at Johns Hopkins University, which provides an easy-to-use collaborative research environment for astronomy and many other sciences.SciServer enables these collaborative research strategies using Jupyter notebooks, in which users can write their own Python and R scripts and execute them on the same server as the data. We have written special-purpose libraries for querying, reading, and writing data. Intermediate results can be stored in large scratch space (hundreds of TBs) and analyzed directly from within Python or R with state-of-the-art visualization and machine learning libraries. Users can store science-ready results in their permanent allocation on SciDrive, a Dropbox-like system for sharing and publishing files.SciServer Compute’s virtual research environment has grown with the addition of task management and access control functions, allowing collaborators to share both data and analysis scripts securely across the world. These features also open up new possibilities for education, allowing instructors to share datasets with students and students to write analysis scripts to share with their instructors. We are leveraging these features into a new system called “SciServer Courseware,” which will allow instructors to share assignments with their students, allowing students to engage with big data in new ways.SciServer has also expanded to include more datasets beyond the Sloan Digital Sky Survey. A part of that growth has been the addition of the SkyQuery component, which allows for simple, fast cross-matching between very large astronomical datasets.Demos, documentation, and more information about all these resources can be found at www.sciserver.org.

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

Compilation of the ``Atlas of Gamma-rays from the Inelastic Scattering of Reactor Fast Neutrons'' (1978DE41) by A.M. Demidov, L.I. Govor, Yu. K. Cherepantsev, M.R. Ahmed, S. Al-Najjar, M.A. Al-Amili, N. Al-Assafi, and N. Rammo

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

Hurst, Aaron M.; Bernstein, Lee A.; Chong, Su-Ann

A Structured Query Language (SQL) relational database has been developed based on the original (n,n'gamma) work carried out by A.M. Demidov et al., at the Nuclear Research Institute in Baghdad, Iraq [``Atlas of Gamma-Ray Spectra from the Inelastic Scattering of Reactor Fast Neutrons'', Nuclear Research Institute, Baghdad, Iraq (Moscow, Atomizdat 1978)] for 105 independent measurements comprising 76 elemental samples of natural composition and 29 isotopically-enriched samples. The information from this ATLAS includes: gamma-ray energies and intensities; nuclide and level data corresponding to where the gamma-ray originated from; target (sample) experimental-measurement data. Taken together, this information allows for the extraction ofmore » the flux-weighted (n,n'gamma) cross sections for a given transition relative to a defined value. Currently, we are using the fast-neutron flux-weighted partial gamma-ray cross section from ENDF/B-VII.1 for the production of the 847-keV transition from the first excited 2+ state to the 0+ ground state in 56Fe, 468 mb. This value also takes into account contributions to the 847-keV transition following beta(-) decay of 56Mn formed in the 56Fe(n,p) reaction. However, this value can easily be adjusted to accommodate the user preference. The (n,n'gamma) data has been compiled into a series of ASCII comma separated value tables and a suite of Python scripts and C modules are provided to build the database. Upon building, the database can then be interacted with directly via the SQLite engine or accessed via the Jupyter Notebook Python-browser interface. Several examples exploiting these utilities are also provided with the complete software package.« less

Using the Landlab toolkit to evaluate and compare alternative geomorphic and hydrologic model formulations

NASA Astrophysics Data System (ADS)

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

2016-12-01

Developing a better understanding of catchment hydrology and geomorphology ideally involves quantitative hypothesis testing. Often one seeks to identify the simplest mathematical and/or computational model that accounts for the essential dynamics in the system of interest. Development of alternative hypotheses involves testing and comparing alternative formulations, but the process of comparison and evaluation is made challenging by the rigid nature of many computational models, which are often built around a single assumed set of equations. Here we review a software framework for two-dimensional computational modeling that facilitates the creation, testing, and comparison of surface-dynamics models. Landlab is essentially a Python-language software library. Its gridding module allows for easy generation of a structured (raster, hex) or unstructured (Voronoi-Delaunay) mesh, with the capability to attach data arrays to particular types of element. Landlab includes functions that implement common numerical operations, such as gradient calculation and summation of fluxes within grid cells. Landlab also includes a collection of process components, which are encapsulated pieces of software that implement a numerical calculation of a particular process. Examples include downslope flow routing over topography, shallow-water hydrodynamics, stream erosion, and sediment transport on hillslopes. Individual components share a common grid and data arrays, and they can be coupled through the use of a simple Python script. We illustrate Landlab's capabilities with a case study of Holocene landscape development in the northeastern US, in which we seek to identify a collection of model components that can account for the formation of a series of incised canyons that have that developed since the Laurentide ice sheet last retreated. We compare sets of model ingredients related to (1) catchment hydrologic response, (2) hillslope evolution, and (3) stream channel and gully incision. The case-study example demonstrates the value of exploring multiple working hypotheses, in the form of multiple alternative model components.

Photometric Calibration of the Gemini South Adaptive Optics Imager

NASA Astrophysics Data System (ADS)

Stevenson, Sarah Anne; Rodrigo Carrasco Damele, Eleazar; Thomas-Osip, Joanna

2017-01-01

The Gemini South Adaptive Optics Imager (GSAOI) is an instrument available on the Gemini South telescope at Cerro Pachon, Chile, utilizing the Gemini Multi-Conjugate Adaptive Optics System (GeMS). In order to allow users to easily perform photometry with this instrument and to monitor any changes in the instrument in the future, we seek to set up a process for performing photometric calibration with standard star observations taken across the time of the instrument’s operation. We construct a Python-based pipeline that includes IRAF wrappers for reduction and combines the AstroPy photutils package and original Python scripts with the IRAF apphot and photcal packages to carry out photometry and linear regression fitting. Using the pipeline, we examine standard star observations made with GSAOI on 68 nights between 2013 and 2015 in order to determine the nightly photometric zero points in the J, H, Kshort, and K bands. This work is based on observations obtained at the Gemini Observatory, processed using the Gemini IRAF and gemini_python packages, which is operated by the Association of Universities for Research in Astronomy, Inc., under a cooperative agreement with the NSF on behalf of the Gemini partnership: the National Science Foundation (United States), the National Research Council (Canada), CONICYT (Chile), Ministerio de Ciencia, Tecnología e Innovación Productiva (Argentina), and Ministério da Ciência, Tecnologia e Inovação (Brazil).

SWIFT MODELLER: a Java based GUI for molecular modeling.

PubMed

Mathur, Abhinav; Shankaracharya; Vidyarthi, Ambarish S

2011-10-01

MODELLER is command line argument based software which requires tedious formatting of inputs and writing of Python scripts which most people are not comfortable with. Also the visualization of output becomes cumbersome due to verbose files. This makes the whole software protocol very complex and requires extensive study of MODELLER manuals and tutorials. Here we describe SWIFT MODELLER, a GUI that automates formatting, scripting and data extraction processes and present it in an interactive way making MODELLER much easier to use than before. The screens in SWIFT MODELLER are designed keeping homology modeling in mind and their flow is a depiction of its steps. It eliminates the formatting of inputs, scripting processes and analysis of verbose output files through automation and makes pasting of the target sequence as the only prerequisite. Jmol (3D structure visualization tool) has been integrated into the GUI which opens and demonstrates the protein data bank files created by the MODELLER software. All files required and created by the software are saved in a folder named after the work instance's date and time of execution. SWIFT MODELLER lowers the skill level required for the software through automation of many of the steps in the original software protocol, thus saving an enormous amount of time per instance and making MODELLER very easy to work with.

Timeliner: Automating Procedures on the ISS

NASA Technical Reports Server (NTRS)

Brown, Robert; Braunstein, E.; Brunet, Rick; Grace, R.; Vu, T.; Zimpfer, Doug; Dwyer, William K.; Robinson, Emily

2002-01-01

Timeliner has been developed as a tool to automate procedural tasks. These tasks may be sequential tasks that would typically be performed by a human operator, or precisely ordered sequencing tasks that allow autonomous execution of a control process. The Timeliner system includes elements for compiling and executing sequences that are defined in the Timeliner language. The Timeliner language was specifically designed to allow easy definition of scripts that provide sequencing and control of complex systems. The execution environment provides real-time monitoring and control based on the commands and conditions defined in the Timeliner language. The Timeliner sequence control may be preprogrammed, compiled from Timeliner "scripts," or it may consist of real-time, interactive inputs from system operators. In general, the Timeliner system lowers the workload for mission or process control operations. In a mission environment, scripts can be used to automate spacecraft operations including autonomous or interactive vehicle control, performance of preflight and post-flight subsystem checkouts, or handling of failure detection and recovery. Timeliner may also be used for mission payload operations, such as stepping through pre-defined procedures of a scientific experiment.

SimPackJ/S: a web-oriented toolkit for discrete event simulation

NASA Astrophysics Data System (ADS)

Park, Minho; Fishwick, Paul A.

2002-07-01

SimPackJ/S is the JavaScript and Java version of SimPack, which means SimPackJ/S is a collection of JavaScript and Java libraries and executable programs for computer simulations. The main purpose of creating SimPackJ/S is that we allow existing SimPack users to expand simulation areas and provide future users with a freeware simulation toolkit to simulate and model a system in web environments. One of the goals for this paper is to introduce SimPackJ/S. The other goal is to propose translation rules for converting C to JavaScript and Java. Most parts demonstrate the translation rules with examples. In addition, we discuss a 3D dynamic system model and overview an approach to 3D dynamic systems using SimPackJ/S. We explain an interface between SimPackJ/S and the 3D language--Virtual Reality Modeling Language (VRML). This paper documents how to translate C to JavaScript and Java and how to utilize SimPackJ/S within a 3D web environment.

WegenerNet climate station network region Feldbach/Austria: From local measurements to weather and climate data products at 1 km-scale resolution

NASA Astrophysics Data System (ADS)

Kabas, T.; Leuprecht, A.; Bichler, C.; Kirchengast, G.

2010-12-01

South-eastern Austria is characteristic for experiencing a rich variety of weather and climate patterns. For this reason, the county of Feldbach was selected by the Wegener Center as a focus area for a pioneering observation experiment at very high resolution: The WegenerNet climate station network (in brief WegenerNet) comprises 151 meteorological stations within an area of about 20 km × 15 km (~ 1.4 km × 1.4 km station grid). All stations measure the main parameters temperature, humidity and precipitation with 5 minute sampling. Selected further stations include measurements of wind speed and direction completed by soil parameters as well as air pressure and net radiation. The collected data is integrated in an automatic processing system including data transfer, quality control, product generation, and visualization. Each station is equipped with an internet-attached data logger and the measurements are transferred as binary files via GPRS to the WegenerNet server in 1 hour intervals. The incoming raw data files of measured parameters as well as several operating values of the data logger are stored in a relational database (PostgreSQL). Next, the raw data pass the Quality Control System (QCS) in which the data are checked for its technical and physical plausibility (e.g., sensor specifications, temporal and spatial variability). In consideration of the data quality (quality flag), the Data Product Generator (DPG) results in weather and climate data products on various temporal scales (from 5 min to annual) for single stations and regular grids. Gridded data are derived by vertical scaling and squared inverse distance interpolation (1 km × 1 km and 0.01° × 0.01° grids). Both subsystems (QCS and DPG) are realized by the programming language Python. For application purposes the resulting data products are available via the bi-lingual (dt, en) WegenerNet data portal (www.wegenernet.org). At this time, the main interface is still online in a system in which MapServer is used to import spatial data by its database interface and to generate images of static geographic formats. However, a Java applet is additionally needed to display these images on the users local host. Furthermore, station data are visualized as time series by the scripting language PHP. Since February 2010, the visualization of gridded data products is a first step to a new data portal based on OpenLayers. In this GIS framework, all geographic information (e.g., OpenStreetMap) is displayed with MapServer. Furthermore, the visualization of all meteorological parameters are generated on the fly by a Python CGI script and transparently overlayed on the maps. Hence, station data and gridded data are visualized and further prepared for download in common data formats (csv, NetCDF). In conclusion, measured data and generated data products are provided with a data latency less than 1-2 hours in standard operation (near real time). Following an introduction of the processing system along the lines above, resulting data products are presented online at the WegenerNet data portal.

Chimenea and other tools: Automated imaging of multi-epoch radio-synthesis data with CASA

NASA Astrophysics Data System (ADS)

Staley, T. D.; Anderson, G. E.

2015-11-01

In preparing the way for the Square Kilometre Array and its pathfinders, there is a pressing need to begin probing the transient sky in a fully robotic fashion using the current generation of radio telescopes. Effective exploitation of such surveys requires a largely automated data-reduction process. This paper introduces an end-to-end automated reduction pipeline, AMIsurvey, used for calibrating and imaging data from the Arcminute Microkelvin Imager Large Array. AMIsurvey makes use of several component libraries which have been packaged separately for open-source release. The most scientifically significant of these is chimenea, which implements a telescope-agnostic algorithm for automated imaging of pre-calibrated multi-epoch radio-synthesis data, of the sort typically acquired for transient surveys or follow-up. The algorithm aims to improve upon standard imaging pipelines by utilizing iterative RMS-estimation and automated source-detection to avoid so called 'Clean-bias', and makes use of CASA subroutines for the underlying image-synthesis operations. At a lower level, AMIsurvey relies upon two libraries, drive-ami and drive-casa, built to allow use of mature radio-astronomy software packages from within Python scripts. While targeted at automated imaging, the drive-casa interface can also be used to automate interaction with any of the CASA subroutines from a generic Python process. Additionally, these packages may be of wider technical interest beyond radio-astronomy, since they demonstrate use of the Python library pexpect to emulate terminal interaction with an external process. This approach allows for rapid development of a Python interface to any legacy or externally-maintained pipeline which accepts command-line input, without requiring alterations to the original code.

Design Automation Using Script Languages. High-Level CAD Templates in Non-Parametric Programs

NASA Astrophysics Data System (ADS)

Moreno, R.; Bazán, A. M.

2017-10-01

The main purpose of this work is to study the advantages offered by the application of traditional techniques of technical drawing in processes for automation of the design, with non-parametric CAD programs, provided with scripting languages. Given that an example drawing can be solved with traditional step-by-step detailed procedures, is possible to do the same with CAD applications and to generalize it later, incorporating references. In today’s modern CAD applications, there are striking absences of solutions for building engineering: oblique projections (military and cavalier), 3D modelling of complex stairs, roofs, furniture, and so on. The use of geometric references (using variables in script languages) and their incorporation into high-level CAD templates allows the automation of processes. Instead of repeatedly creating similar designs or modifying their data, users should be able to use these templates to generate future variations of the same design. This paper presents the automation process of several complex drawing examples based on CAD script files aided with parametric geometry calculation tools. The proposed method allows us to solve complex geometry designs not currently incorporated in the current CAD applications and to subsequently create other new derivatives without user intervention. Automation in the generation of complex designs not only saves time but also increases the quality of the presentations and reduces the possibility of human errors.

Novel Technology for Treating Individuals with Aphasia and Concomitant Cognitive Deficits

PubMed Central

Cherney, Leora R.; Halper, Anita S.

2009-01-01

Purpose This article describes three individuals with aphasia and concomitant cognitive deficits who used state-of-the-art computer software for training conversational scripts. Method Participants were assessed before and after 9 weeks of a computer script training program. For each participant, three individualized scripts were developed, recorded on the software, and practiced sequentially at home. Weekly meetings with the speech-language pathologist occurred to monitor practice and assess progress. Baseline and posttreatment scripts were audiotaped, transcribed, and compared to the target scripts for content, grammatical productivity, and rate of production of script-related words. Interviews were conducted at the conclusion of treatment. Results There was great variability in improvements across scripts, with two participants improving on two of their three scripts in measures of content, grammatical productivity, and rate of production of script-related words. One participant gained more than 5 points on the Aphasia Quotient of the Western Aphasia Battery. Five positive themes were consistently identified from exit interviews: increased verbal communication, improvements in other modalities and situations, communication changes noticed by others, increased confidence, and satisfaction with the software. Conclusion Computer-based script training potentially may be an effective intervention for persons with chronic aphasia and concomitant cognitive deficits. PMID:19158062

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

NASA Astrophysics Data System (ADS)

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

2014-05-01

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

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.

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).

Configuration Tool Prototype for the Trusted Computing Exemplar Project

DTIC Science & Technology

2009-12-01

languages were examined: Microsoft .NET [8], Apple Cocoa (Objective-C) [9], wxPython [10], and Java [11]. Since every language has its pros and...languages using the criteria described above. Based on the developer’s limited experience and knowledge of Microsoft .NET and Apple Cocoa (Objective...a tabbed panel within a separate window panel. Figure 9 depicts this evolution of the conceptual design. In Figure 9, the table column headers are

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

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.

SU-E-J-114: Web-Browser Medical Physics Applications Using HTML5 and Javascript.

PubMed

Bakhtiari, M

2012-06-01

Since 2010, there has been a great attention about HTML5. Application developers and browser makers fully embrace and support the web of the future. Consumers have started to embrace HTML5, especially as more users understand the benefits and potential that HTML5 can mean for the future.Modern browsers such as Firefox, Google Chrome, and Safari are offering better and more robust support for HTML5, CSS3, and JavaScript. The idea is to introduce the HTML5 to medical physics community for open source software developments. The benefit of using HTML5 is developing portable software systems. The HTML5, CSS, and JavaScript programming languages were used to develop several applications for Quality Assurance in radiation therapy. The canvas element of HTML5 was used for handling and displaying the images, and JavaScript was used to manipulate the data. Sample application were developed to: 1. analyze the flatness and symmetry of the radiotherapy fields in a web browser, 2.analyze the Dynalog files from Varian machines, 3. visualize the animated Dynamic MLC files, 4. Simulation via Monte Carlo, and 5. interactive image manipulation. The programs showed great performance and speed in uploading the data and displaying the results. The flatness and symmetry program and Dynalog file analyzer ran in a fraction of second. The reason behind this performance is using JavaScript language which is a lower level programming language in comparison to the most of the scientific programming packages such as Matlab. The second reason is that JavaScript runs locally on client side computers not on the web-servers. HTML5 and JavaScript can be used to develop useful applications that can be run online or offline on different modern web-browsers. The programming platform can be also one of the modern web-browsers which are mostly open source (such as Firefox). © 2012 American Association of Physicists in Medicine.

Word Spotting for Indic Documents to Facilitate Retrieval

NASA Astrophysics Data System (ADS)

Bhardwaj, Anurag; Setlur, Srirangaraj; Govindaraju, Venu

With advances in the field of digitization of printed documents and several mass digitization projects underway, information retrieval and document search have emerged as key research areas. However, most of the current work in these areas is limited to English and a few oriental languages. The lack of efficient solutions for Indic scripts has hampered information extraction from a large body of documents of cultural and historical importance. This chapter presents two relevant topics in this area. First, we describe the use of a script-specific keyword spotting for Devanagari documents that makes use of domain knowledge of the script. Second, we address the needs of a digital library to provide access to a collection of documents from multiple scripts. This requires intelligent solutions which scale across different scripts. We present a script-independent keyword spotting approach for this purpose. Experimental results illustrate the efficacy of our methods.

Oral Reading in Bilingual Aphasia: Evidence from Mongolian and Chinese

ERIC Educational Resources Information Center

Weekes, Brendan Stuart; Su, I. Fan; Yin, Wengang; Zhang, Xihong

2007-01-01

Cognitive neuropsychological studies of bilingual patients with aphasia have contributed to our understanding of how the brain processes different languages. The question we asked is whether differences in script have any impact on language processing in bilingual aphasic patients who speak languages with different writing systems: Chinese and…

An introduction to scripting in Ruby for biologists.

PubMed

Aerts, Jan; Law, Andy

2009-07-16

The Ruby programming language has a lot to offer to any scientist with electronic data to process. Not only is the initial learning curve very shallow, but its reflection and meta-programming capabilities allow for the rapid creation of relatively complex applications while still keeping the code short and readable. This paper provides a gentle introduction to this scripting language for researchers without formal informatics training such as many wet-lab scientists. We hope this will provide such researchers an idea of how powerful a tool Ruby can be for their data management tasks and encourage them to learn more about it.

VizieR Online Data Catalog: SDSS DR7 voids and superclusters (Nadathur+, 2014)

NASA Astrophysics Data System (ADS)

Nadathur, S.; Hotchkiss, S.

2016-02-01

This is a public catalogue of voids and superclusters identified in the SDSS DR7 main galaxy and luminous red galaxy samples. This version is dated 04.11.2013. We make the catalogues available for general use. If you use them for your own work, we ask that you cite the original paper, Nadathur & Hotchkiss (2014MNRAS.440.1248N). The top-level directory cat_v11.11.13 contains an example python script called postproc.py, and two folders called comovcoords and redshiftcoords containing two versions of the catalogue in different coordinate systems. The comoving coordinate system is pretty self-explanatory, for a description of the other one please refer to the paper. Each of these directories is further divided into six folders containing the Type1 and Type2 void catalogues and the supercluster catalogue for each of the galaxy samples analysed here, and a folder called tools, which contains data useful for users wishing to apply their own selection criteria. The basic information provided includes the location of the barycentre of each structure, its volume, effective radius, average density and minimum or maximum density, its core galaxy and seed zone, the total number of galaxies in the seed zone, the number of zones merged to form the structure, the total number of particles in the structure, and its density ratio. These are split between two files for each structure type and each sample, named xxxinfo.txt and xxxlist.txt, where xxx refers to the structure type. It is also possible to extract lists of member galaxies of each structure and their magnitudes. An example python script, postproc.py, demonstrates how to access this information and how to build alternative catalogues using user-defined selection criteria. (27 data files).

Brian: a simulator for spiking neural networks in python.

PubMed

Goodman, Dan; Brette, Romain

2008-01-01

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

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.

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.

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

NASA Astrophysics Data System (ADS)

Wiebusch, Martin

2015-10-01

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

Characterizing and Quantifying Time Dependent Night Sky Brightness In and Around Tucson, Arizona

NASA Astrophysics Data System (ADS)

Nydegger, Rachel

2014-01-01

As part of a Research Experience for Undergraduates (REU) program with the National Optical Astronomy Observatory (NOAO), I (with mentor Dr. Constance Walker of NOAO) characterized light pollution in and near Tucson, Arizona using eight Sky Quality Meters (SQMs). In order to analyze the data in a consistent way for comparison, we created a standard procedure for reduction and analysis using python and MATLAB. The series of python scripts remove faulty data and examine specifically anthropogenic light pollution by excluding contributions made by the sun, moon, and the Milky Way. We then use MATLAB codes to illustrate how the light pollution changes in relation to time, distance from the city, and airglow. Data are then analyzed by a recently developed sky brightness model created by Dan Duriscoe of the National Park Service. To quantify the measurements taken by SQMs, we tested the wavelength sensitivity of the devices used for the data collection. The findings from the laboratory testing have prompted innovations for the SQMs as well as given a sense of how data gathered by these devices should be treated.

relaxGUI: a new software for fast and simple NMR relaxation data analysis and calculation of ps-ns and μs motion of proteins.

PubMed

Bieri, Michael; d'Auvergne, Edward J; Gooley, Paul R

2011-06-01

Investigation of protein dynamics on the ps-ns and μs-ms timeframes provides detailed insight into the mechanisms of enzymes and the binding properties of proteins. Nuclear magnetic resonance (NMR) is an excellent tool for studying protein dynamics at atomic resolution. Analysis of relaxation data using model-free analysis can be a tedious and time consuming process, which requires good knowledge of scripting procedures. The software relaxGUI was developed for fast and simple model-free analysis and is fully integrated into the software package relax. It is written in Python and uses wxPython to build the graphical user interface (GUI) for maximum performance and multi-platform use. This software allows the analysis of NMR relaxation data with ease and the generation of publication quality graphs as well as color coded images of molecular structures. The interface is designed for simple data analysis and management. The software was tested and validated against the command line version of relax.

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.

A Courseware to Script Animated Pedagogical Agents in Instructional Material for Elementary Students in English Education

ERIC Educational Resources Information Center

Hong, Zeng-Wei; Chen, Yen-Lin; Lan, Chien-Ho

2014-01-01

Animated agents are virtual characters who demonstrate facial expressions, gestures, movements, and speech to facilitate students' engagement in the learning environment. Our research developed a courseware that supports a XML-based markup language and an authoring tool for teachers to script animated pedagogical agents in teaching materials. The…

Silly Salamanders and Other Slightly Stupid Stuff for Readers Theatre.

ERIC Educational Resources Information Center

Fredericks, Anthony D.

This book contains more than two dozen reader's theater scripts to entertain and amuse those in the classroom or library. The scripts in the book--all are reproducible--can help nurture student language arts skills and the power of the imagination with their fractured "takes" on fairy tales and their twisted legends. Designed to…

TEACHING AND TRAINING WITH MOTION PICTURES (MAGNETIC SOUND).

ERIC Educational Resources Information Center

Bell and Howell Co., Lincolnwood, IL.

THE PREPARATION OF A MAGNETIC-SOUND TRACK FOR 16 MM. MOTION PICTURE FILMS IS DESCRIBED. IN SCRIPT PREPARATION, THE SCRIPT SHOULD BE WRITTEN IN NARRATIVE FORM TO INCLUDE ALL SHOTS NEEDED AND TO SUPPLEMENT AND GIVE INFORMATION NOT IN THE FILM. LANGUAGE SHOULD BE KEPT SIMPLE, AND UNAVOIDABLE TECHNICAL TERMS SHOULD BE EXPLAINED. IN REWRITING THE…

An Analysis of Some "Supra-grammatical" Aspects of Writing Done by Undergraduate Students.

ERIC Educational Resources Information Center

Das, Bikram K.

1978-01-01

Some of the "supra-grammatical" features of scripts written by undergraduate students in India are examined. The script writing was a test administered to assess the proficiency of students in the advanced cognitive and rhetorical skills involved in composition, both in their native language and English. The particular type of composition chosen…

The Wall Street Journal Report: Basis for a Model Program in Business English.

ERIC Educational Resources Information Center

Zuck, Joyce G.

One successful model for instruction in English as a second language (ESL) takes its core texts from a single recurring publication or broadcast. The use of one periodical maximizes the opportunity to become familiar with the format, topics, and common story genres or scripts. Script theory, which views texts as answers to predictable questions…

The Effect of Script on Poor Readers' Sensitivity to Dynamic Visual Stimuli

ERIC Educational Resources Information Center

Kim, Jeesun; Davis, Chris; Burnham, Denis; Luksaneeyanawin, Sudaporn

2004-01-01

The current research examined performance of good and poor readers of Thai on two tasks that assess sensitivity to dynamic visual displays. Readers of Thai, a complex alphabetic script that nonetheless has a regular orthography, were chosen in order to contrast patterns of performance with readers of Korean Hangul (a similarly regular language but…

First-Grade Teachers' Perception and Implementation of a Semi-Scripted Reading Curriculum

ERIC Educational Resources Information Center

Ainsworth, Mary Taylor; Ortlieb, Evan; Cheek, Earl H., Jr.; Pate, Roberta Simnacher; Fetters, Carol

2012-01-01

A teacher's role was dramatically changed from that of an educator to that of a facilitator with the adoption of semi-scripted curriculums. This case study explores teachers' perception and implementation of a state's English Language Arts curriculum in first-grade classrooms. Four first-grade teachers from a large urban school district were…

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.

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.

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.

Languages, Script and National Identity: Struggles over Linguistic Heterogeneity in Switzerland in the Nineteenth and Twentieth Centuries

ERIC Educational Resources Information Center

Boser, Lukas; Brühwiler, Ingrid

2017-01-01

For centuries, Switzerland has been a multilingual country (which currently has no less than four official languages.) Furthermore, one of those languages, German, is characterised by bigraphism (i.e. the coexistence of two different type styles). This article discusses the role played by language and writing systems in the great educational…

Novel technology for treating individuals with aphasia and concomitant cognitive deficits.

PubMed

Cherney, Leora R; Halper, Anita S

2008-01-01

This article describes three individuals with aphasia and concomitant cognitive deficits who used state-of-theart computer software for training conversational scripts. Participants were assessed before and after 9 weeks of a computer script training program. For each participant, three individualized scripts were developed, recorded on the software, and practiced sequentially at home. Weekly meetings with the speech-language pathologist occurred to monitor practice and assess progress. Baseline and posttreatment scripts were audiotaped, transcribed, and compared to the target scripts for content, grammatical productivity, and rate of production of script-related words. Interviews were conducted at the conclusion of treatment. There was great variability in improvements across scripts, with two participants improving on two of their three scripts in measures of content, grammatical productivity, and rate of production of scriptrelated words. One participant gained more than 5 points on the Aphasia Quotient of the Western Aphasia Battery. Five positive themes were consistently identified from exit interviews: increased verbal communication, improvements in other modalities and situations, communication changes noticed by others, increased confidence, and satisfaction with the software. Computer-based script training potentially may be an effective intervention for persons with chronic aphasia and concomitant cognitive deficits.

Design of 3D simulation engine for oilfield safety training

NASA Astrophysics Data System (ADS)

Li, Hua-Ming; Kang, Bao-Sheng

2015-03-01

Aiming at the demand for rapid custom development of 3D simulation system for oilfield safety training, this paper designs and implements a 3D simulation engine based on script-driven method, multi-layer structure, pre-defined entity objects and high-level tools such as scene editor, script editor, program loader. A scripting language been defined to control the system's progress, events and operating results. Training teacher can use this engine to edit 3D virtual scenes, set the properties of entity objects, define the logic script of task, and produce a 3D simulation training system without any skills of programming. Through expanding entity class, this engine can be quickly applied to other virtual training areas.

Tracking delays in report availability caused by incorrect exam status with Web-based issue tracking: a quality initiative.

PubMed

Awan, Omer Abdulrehman; van Wagenberg, Frans; Daly, Mark; Safdar, Nabile; Nagy, Paul

2011-04-01

Many radiology information systems (RIS) cannot accept a final report from a dictation reporting system before the exam has been completed in the RIS by a technologist. A radiologist can still render a report in a reporting system once images are available, but the RIS and ancillary systems may not get the results because of the study's uncompleted status. This delay in completing the study caused an alarming number of delayed reports and was undetected by conventional RIS reporting techniques. We developed a Web-based reporting tool to monitor uncompleted exams and automatically page section supervisors when a report was being delayed by its incomplete status in the RIS. Institutional Review Board exemption was obtained. At four imaging centers, a Python script was developed to poll the dictation system every 10 min for exams in five different modalities that were signed by the radiologist but could not be sent to the RIS. This script logged the exams into an existing Web-based tracking tool using PHP and a MySQL database. The script also text-paged the modality supervisor. The script logged the time at which the report was finally sent, and statistics were aggregated onto a separate Web-based reporting tool. Over a 1-year period, the average number of uncompleted exams per month and time to problem resolution decreased at every imaging center and in almost every imaging modality. Automated feedback provides a vital link in improving technologist performance and patient care without assigning a human resource to manage report queues.

Can we detect, monitor, and characterize volcanic activity using 'off the shelf' webcams and low-light cameras?

NASA Astrophysics Data System (ADS)

Harrild, M.; Webley, P. W.; Dehn, J.

2015-12-01

The ability to detect and monitor precursory events, thermal signatures, and ongoing volcanic activity in near-realtime is an invaluable tool. Volcanic hazards often range from low level lava effusion to large explosive eruptions, easily capable of ejecting ash to aircraft cruise altitudes. Using ground based remote sensing to detect and monitor this activity is essential, but the required equipment is often expensive and difficult to maintain, which increases the risk to public safety and the likelihood of financial impact. Our investigation explores the use of 'off the shelf' cameras, ranging from computer webcams to low-light security cameras, to monitor volcanic incandescent activity in near-realtime. These cameras are ideal as they operate in the visible and near-infrared (NIR) portions of the electromagnetic spectrum, are relatively cheap to purchase, consume little power, are easily replaced, and can provide telemetered, near-realtime data. We focus on the early detection of volcanic activity, using automated scripts that capture streaming online webcam imagery and evaluate each image according to pixel brightness, in order to automatically detect and identify increases in potentially hazardous activity. The cameras used here range in price from 0 to 1,000 and the script is written in Python, an open source programming language, to reduce the overall cost to potential users and increase the accessibility of these tools, particularly in developing nations. In addition, by performing laboratory tests to determine the spectral response of these cameras, a direct comparison of collocated low-light and thermal infrared cameras has allowed approximate eruption temperatures to be correlated to pixel brightness. Data collected from several volcanoes; (1) Stromboli, Italy (2) Shiveluch, Russia (3) Fuego, Guatemala (4) Popcatépetl, México, along with campaign data from Stromboli (June, 2013), and laboratory tests are presented here.

Portable Just-in-Time Specialization of Dynamically Typed Scripting Languages

NASA Astrophysics Data System (ADS)

Williams, Kevin; McCandless, Jason; Gregg, David

In this paper, we present a portable approach to JIT compilation for dynamically typed scripting languages. At runtime we generate ANSI C code and use the system's native C compiler to compile this code. The C compiler runs on a separate thread to the interpreter allowing program execution to continue during JIT compilation. Dynamic languages have variables which may change type at any point in execution. Our interpreter profiles variable types at both whole method and partial method granularity. When a frequently executed region of code is discovered, the compilation thread generates a specialized version of the region based on the profiled types. In this paper, we evaluate the level of instruction specialization achieved by our profiling scheme as well as the overall performance of our JIT.

"We Are All Beginners": Amazigh in Language Policy and Educational Practice in Morocco

ERIC Educational Resources Information Center

El Aissati, Abderrahman; Karsmakers, Suzanne; Kurvers, Jeanne

2011-01-01

In 2003, the Amazigh (Berber) language and the Tifinagh script were, for the first time in history, introduced as a subject for all students in public primary schools in Morocco. This study first investigates the language planning policy behind the introduction of the new Amazigh curriculum: selection, codification, standardization, curriculum…

Using Pipelined XNOR Logic to Reduce SEU Risks in State Machines

NASA Technical Reports Server (NTRS)

Le, Martin; Zheng, Xin; Katanyoutant, Sunant

2008-01-01

Single-event upsets (SEUs) pose great threats to avionic systems state machine control logic, which are frequently used to control sequence of events and to qualify protocols. The risks of SEUs manifest in two ways: (a) the state machine s state information is changed, causing the state machine to unexpectedly transition to another state; (b) due to the asynchronous nature of SEU, the state machine's state registers become metastable, consequently causing any combinational logic associated with the metastable registers to malfunction temporarily. Effect (a) can be mitigated with methods such as triplemodular redundancy (TMR). However, effect (b) cannot be eliminated and can degrade the effectiveness of any mitigation method of effect (a). Although there is no way to completely eliminate the risk of SEU-induced errors, the risk can be made very small by use of a combination of very fast state-machine logic and error-detection logic. Therefore, one goal of two main elements of the present method is to design the fastest state-machine logic circuitry by basing it on the fastest generic state-machine design, which is that of a one-hot state machine. The other of the two main design elements is to design fast error-detection logic circuitry and to optimize it for implementation in a field-programmable gate array (FPGA) architecture: In the resulting design, the one-hot state machine is fitted with a multiple-input XNOR gate for detection of illegal states. The XNOR gate is implemented with lookup tables and with pipelines for high speed. In this method, the task of designing all the logic must be performed manually because no currently available logic synthesis software tool can produce optimal solutions of design problems of this type. However, some assistance is provided by a script, written for this purpose in the Python language (an object-oriented interpretive computer language) to automatically generate hardware description language (HDL) code from state-transition rules.

NASA Armstrong's Approach to Store Separation Analysis

NASA Technical Reports Server (NTRS)

Acuff, Chris; Bui, Trong

2015-01-01

Presentation will an overview of NASA Armstrong's store separation capabilities and how they have been applied recently. Objective of the presentation is to brief Generation Orbit and other potential partners on NASA Armstrong's store separation capabilities. It will include discussions on the use of NAVSEP and Cart3D, as well as some Python scripting work to perform the analysis, and a short overview of this methodology applied to the Towed Glider Air Launch System. Collaboration with potential customers in this area could lead to funding for the further development of a store separation capability at NASA Armstrong, which would boost the portfolio of engineering expertise at the center.

Visualizing Astronomical Data with Blender

NASA Astrophysics Data System (ADS)

Kent, Brian R.

2014-01-01

We present methods for using the 3D graphics program Blender in the visualization of astronomical data. The software's forte for animating 3D data lends itself well to use in astronomy. The Blender graphical user interface and Python scripting capabilities can be utilized in the generation of models for data cubes, catalogs, simulations, and surface maps. We review methods for data import, 2D and 3D voxel texture applications, animations, camera movement, and composite renders. Rendering times can be improved by using graphic processing units (GPUs). A number of examples are shown using the software features most applicable to various kinds of data paradigms in astronomy.

The Stroop Effect in Kana and Kanji Scripts in Native Japanese Speakers: An fMRI Study

PubMed Central

Coderre, Emily L.; Filippi, Christopher G.; Newhouse, Paul A.; Dumas, Julie A.

2008-01-01

Prior research has shown that the two writing systems of the Japanese orthography are processed differently: kana (syllabic symbols) are processed like other phonetic languages such as English, while kanji (a logographic writing system) are processed like other logographic languages like Chinese. Previous work done with the Stroop task in Japanese has shown that these differences in processing strategies create differences in Stroop effects. This study investigated the Stroop effect in kanji and kana using functional magnetic resonance imaging (fMRI) to examine the similarities and differences in brain processing between logographic and phonetic languages. Nine native Japanese speakers performed the Stroop task both in kana and kanji scripts during fMRI. Both scripts individually produced significant Stroop effects as measured by the behavioral reaction time data. The imaging data for both scripts showed brain activation in the anterior cingulate gyrus, an area involved in inhibiting automatic processing. Though behavioral data showed no significant differences between the Stroop effects in kana and kanji, there were differential areas of activation in fMRI found for each writing system. In fMRI, the Stroop task activated an area in the left inferior parietal lobule during the kana task and the left inferior frontal gyrus during the kanji task. The results of the present study suggest that the Stroop task in Japanese kana and kanji elicits differential activation in brain regions involved in conflict detection and resolution for syllabic and logographic writing systems. PMID:18325582

Evidence for cross-script abstract identities in learners of Japanese kana.

PubMed

Schubert, Teresa; Gawthrop, Roderick; Kinoshita, Sachiko

2018-05-07

The presence of abstract letter identity representations in the Roman alphabet has been well documented. These representations are invariant to letter case (upper vs. lower) and visual appearance. For example, "a" and "A" are represented by the same abstract identity. Recent research has begun to consider whether the processing of non-Roman orthographies also involves abstract orthographic representations. In the present study, we sought evidence for abstract identities in Japanese kana, which consist of two scripts, hiragana and katakana. Abstract identities would be invariant to the script used as well as to the degree of visual similarity. We adapted the cross-case masked-priming letter match task used in previous research on Roman letters, by presenting cross-script kana pairs and testing adult beginning -to- intermediate Japanese second-language (L2) learners (first-language English readers). We found robust cross-script priming effects, which were equal in magnitude for visually similar (e.g., り/リ) and dissimilar (e.g., あ/ア) kana pairs. This pattern was found despite participants' imperfect explicit knowledge of the kana names, particularly for katakana. We also replicated prior findings from Roman abstract letter identities in the same participants. Ours is the first study reporting abstract kana identity priming (in adult L2 learners). Furthermore, these representations were acquired relatively early in our adult L2 learners.

Writing English Script: An Overlooked Skill.

ERIC Educational Resources Information Center

Ball, Wendy E.

1986-01-01

An important component of second language programs is the skill of understanding and using the graphic structure of language involved. Inadequate handwriting, poor layout, and difficulties in reading are primary symptoms of students with a weak grasp of the graphic structure. (CB)

Bad Breath - Multiple Languages

MedlinePlus

... List of All Topics All Bad Breath - Multiple Languages To use the sharing features on this page, please enable JavaScript. Chinese, Traditional ( ... Bethesda, MD 20894 U.S. Department of Health and Human Services National Institutes of Health Page last updated on 23 May 2018

Arthritis - Multiple Languages

MedlinePlus

... XYZ List of All Topics All Arthritis - Multiple Languages To use the sharing features on this page, please enable JavaScript. Chinese, Simplified ( ... Bethesda, MD 20894 U.S. Department of Health and Human Services National Institutes of Health Page last updated on 31 May 2018

Abortion - Multiple Languages

MedlinePlus

... XYZ List of All Topics All Abortion - Multiple Languages To use the sharing features on this page, please enable JavaScript. Chinese, Simplified ( ... Bethesda, MD 20894 U.S. Department of Health and Human Services National Institutes of Health Page last updated on 12 October 2017

Calcium - Multiple Languages

MedlinePlus

... XYZ List of All Topics All Calcium - Multiple Languages To use the sharing features on this page, please enable JavaScript. Chinese, Traditional ( ... Bethesda, MD 20894 U.S. Department of Health and Human Services National Institutes of Health Page last updated on 31 May 2018

Manipulation of motivating operations and use of a script-fading procedure to teach mands for location to children with language delays.

PubMed

Howlett, Melissa A; Sidener, Tina M; Progar, Patrick R; Sidener, David W

2011-01-01

The effects of contriving motivating operations (MOs) and script fading on the acquisition of the mand "Where's [object]?" were evaluated in 2 boys with language delays. During each session, trials were alternated in which high-preference items were present (abolishing operation [AO] trials) or missing (establishing operation [EO] trials) from their typical locations. Both participants learned to mand during EO trials and not to mand during AO trials during training. Generalization of manding was demonstrated across novel instructors, stimuli, and settings and maintained 3 to 4 weeks following the intervention.

An introduction to scripting in Ruby for biologists

PubMed Central

Aerts, Jan; Law, Andy

2009-01-01

The Ruby programming language has a lot to offer to any scientist with electronic data to process. Not only is the initial learning curve very shallow, but its reflection and meta-programming capabilities allow for the rapid creation of relatively complex applications while still keeping the code short and readable. This paper provides a gentle introduction to this scripting language for researchers without formal informatics training such as many wet-lab scientists. We hope this will provide such researchers an idea of how powerful a tool Ruby can be for their data management tasks and encourage them to learn more about it. PMID:19607723

Robust Optical Recognition of Cursive Pashto Script Using Scale, Rotation and Location Invariant Approach

PubMed Central

Ahmad, Riaz; Naz, Saeeda; Afzal, Muhammad Zeshan; Amin, Sayed Hassan; Breuel, Thomas

2015-01-01

The presence of a large number of unique shapes called ligatures in cursive languages, along with variations due to scaling, orientation and location provides one of the most challenging pattern recognition problems. Recognition of the large number of ligatures is often a complicated task in oriental languages such as Pashto, Urdu, Persian and Arabic. Research on cursive script recognition often ignores the fact that scaling, orientation, location and font variations are common in printed cursive text. Therefore, these variations are not included in image databases and in experimental evaluations. This research uncovers challenges faced by Arabic cursive script recognition in a holistic framework by considering Pashto as a test case, because Pashto language has larger alphabet set than Arabic, Persian and Urdu. A database containing 8000 images of 1000 unique ligatures having scaling, orientation and location variations is introduced. In this article, a feature space based on scale invariant feature transform (SIFT) along with a segmentation framework has been proposed for overcoming the above mentioned challenges. The experimental results show a significantly improved performance of proposed scheme over traditional feature extraction techniques such as principal component analysis (PCA). PMID:26368566

Distributed Hydrologic Modeling Apps for Decision Support in the Cloud

NASA Astrophysics Data System (ADS)

Swain, N. R.; Latu, K.; Christiensen, S.; Jones, N.; Nelson, J.

2013-12-01

Advances in computation resources and greater availability of water resources data represent an untapped resource for addressing hydrologic uncertainties in water resources decision-making. The current practice of water authorities relies on empirical, lumped hydrologic models to estimate watershed response. These models are not capable of taking advantage of many of the spatial datasets that are now available. Physically-based, distributed hydrologic models are capable of using these data resources and providing better predictions through stochastic analysis. However, there exists a digital divide that discourages many science-minded decision makers from using distributed models. This divide can be spanned using a combination of existing web technologies. The purpose of this presentation is to present a cloud-based environment that will offer hydrologic modeling tools or 'apps' for decision support and the web technologies that have been selected to aid in its implementation. Compared to the more commonly used lumped-parameter models, distributed models, while being more intuitive, are still data intensive, computationally expensive, and difficult to modify for scenario exploration. However, web technologies such as web GIS, web services, and cloud computing have made the data more accessible, provided an inexpensive means of high-performance computing, and created an environment for developing user-friendly apps for distributed modeling. Since many water authorities are primarily interested in the scenario exploration exercises with hydrologic models, we are creating a toolkit that facilitates the development of a series of apps for manipulating existing distributed models. There are a number of hurdles that cloud-based hydrologic modeling developers face. One of these is how to work with the geospatial data inherent with this class of models in a web environment. Supporting geospatial data in a website is beyond the capabilities of standard web frameworks and it requires the use of additional software. In particular, there are at least three elements that are needed: a geospatially enabled database, a map server, and geoprocessing toolbox. We recommend a software stack for geospatial web application development comprising: MapServer, PostGIS, and 52 North with Python as the scripting language to tie them together. Another hurdle that must be cleared is managing the cloud-computing load. We are using HTCondor as a solution to this end. Finally, we are creating a scripting environment wherein developers will be able to create apps that use existing hydrologic models in our system with minimal effort. This capability will be accomplished by creating a plugin for a Python content management system called CKAN. We are currently developing cyberinfrastructure that utilizes this stack and greatly lowers the investment required to deploy cloud-based modeling apps. This material is based upon work supported by the National Science Foundation under Grant No. 1135482

Representing Science through Historical Drama: "Lord Kelvin and the Age of the Earth Debate"

ERIC Educational Resources Information Center

Begoray, Deborah L.; Stinner, Arthur

2005-01-01

This paper presents a defense for the use of historical scripted conversations in science. We discuss drama's use of both expository and narrative text forms to expand the language forms available for a variety of learners, the use of scripted conversations as a defensible curriculum design to foster learning in general and science in particular,…

Narrative Development among Language-Minority Children: The Role of Bilingual versus Monolingual Preschool Education

ERIC Educational Resources Information Center

Schwartz, Mila; Shaul, Yehudit

2013-01-01

The development of script schema, as a source of narrative knowledge, is an essential stage in this knowledge construction. This study focused on the role of bilingual versus monolingual preschool education in the development of script schema knowledge in Russian (L1) and Hebrew (L2) among Russian/Hebrew-speaking children in Israel. The preschool…