Head First Programming A learner's guide to programming using the Python language

CERN Document Server

Griffiths, David

2009-01-01

Looking for a reliable way to learn how to program on your own, without being overwhelmed by confusing concepts? Head First Programming introduces the core concepts of writing computer programs -- variables, decisions, loops, functions, and objects -- which apply regardless of the programming language. This book offers concrete examples and exercises in the dynamic and versatile Python language to demonstrate and reinforce these concepts. Learn the basic tools to start writing the programs that interest you, and get a better understanding of what software can (and cannot) do. When you're fi

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

Science.gov (United States)

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.

A student's guide to Python for physical modeling

CERN Document Server

Kinder, Jesse M

2015-01-01

Python is a computer programming language that is rapidly gaining popularity throughout the sciences. A Student’s Guide to Python for Physical Modeling aims to help you, the student, teach yourself enough of the Python programming language to get started with physical modeling. You will learn how to install an open-source Python programming environment and use it to accomplish many common scientific computing tasks: importing, exporting, and visualizing data; numerical analysis; and simulation. No prior programming experience is assumed. This tutorial focuses on fundamentals and introduces a wide range of useful techniques, including: Basic Python programming and scripting Numerical arrays Two- and three-dimensional graphics Monte Carlo simulations Numerical methods, including solving ordinary differential equations Image processing Animation Numerous code samples and exercises—with solutions—illustrate new ideas as they are introduced. A website that accompanies this guide provides additional resourc...

Python essential reference

CERN Document Server

Beazley, David M

2009-01-01

Python Essential Reference is the definitive reference guide to the Python programming language — the one authoritative handbook that reliably untangles and explains both the core Python language and the most essential parts of the Python library. Designed for the professional programmer, the book is concise, to the point, and highly accessible. It also includes detailed information on the Python library and many advanced subjects that is not available in either the official Python documentation or any other single reference source. Thoroughly updated to reflect the significant new programming language features and library modules that have been introduced in Python 2.6 and Python 3, the fourth edition of Python Essential Reference is the definitive guide for programmers who need to modernize existing Python code or who are planning an eventual migration to Python 3. Programmers starting a new Python project will find detailed coverage of contemporary Python programming idioms.

Implementing Python for DrRacket

OpenAIRE

Ramos, Pedro Palma; Leitão, António Menezes

2014-01-01

The Python programming language is becoming increasingly popular in a variety of areas, most notably among novice programmers. On the other hand, Racket and other Scheme dialects are considered excellent vehicles for introducing Computer Science concepts. This paper presents an implementation of Python for Racket and the DrRacket IDE. This allows Python programmers to use Racket libraries and vice versa, as well as using DrRacket's pedagogic features. In particular, it allows architects and d...

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

Science.gov (United States)

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.

Learning Python

National Research Council Canada - National Science Library

Lutz, Mark; Ascher, David

1999-01-01

... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xv Part I. Getting Started 1. A Python Q&A Session Why Do People Use Python? Is Python a Scripting Language? Okay, But What's the Downside? Who Uses Python Today...

Learning Python

National Research Council Canada - National Science Library

Lutz, Mark; Ascher, David

2004-01-01

... . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . xv Part I. Getting Started 1. A Python Q&A Session Why Do People Use Python? Is Python a Scripting Language? Okay, But What's the Downside? Who Uses Python Today...

Implementation of Private Cloud Computing Using Integration of JavaScript and Python

Directory of Open Access Journals (Sweden)

2010-09-01

Full Text Available

This paper deals with the design and deployment of a novel library class in Python, enabling the use of JavaScript functionalities in Application Programming and the leveraging of this Library into development for third generation technologies such as Private Cloud Computing. The integration of these two prevalent languages provides us with a new level of compliance which helps in developing an understanding between Web Programming and Application Programming. An inter-browser functionality wrapping, which would enable users to have a JavaScript experience in Python interfaces directly, without having to depend on external programs, has been developed. The functionality of this concept is prevalent in the fact that Applications written in JavaScript and accessed on the browser now have the capability of interacting with each other on a common platform with the help of a Python wrapper. The idea is demonstrated by the integrating with the now ubiquitous Cloud Computing concept. With the help of examples, we have showcased the same and explained how the Library XOCOM can be a stepping stone to flexible cloud computing environment.

Python : the holy grail of programming

CERN Multimedia

2006-01-01

From 3 to 5 July, CERN hosted the fifth EuroPython Conference bringing together 300 users of Python, an open source programming language, which is more and more appreciated, especially at CERN. The local organisation of Euopython 2006 was managed by a small team from the PH/SFT group. Above, David Quarrie presenting the use of Python in Atlas analyses. If you visited Building 40 at the beginning of July, you may have come across a long orange and yellow snake. This had no relation with the Football World Championship! It was just the mascot of the fifth EuroPython Conference that saw almost 300 software developers, designers and business people gathering at CERN for the annual meeting of the European Python community. Python is an open source programming language actively used in industry and academia for a wide variety of purposes. As CERN decided to host this conference, it is perhaps not surprising to learn that Python is increasingly used in our Laboratory in both computing and physics application domai...

CVXPY: A Python-Embedded Modeling Language for Convex Optimization

OpenAIRE

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.

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

Science.gov (United States)

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.

Two-Language, Two-Paradigm Introductory Computing Curriculum Model and its Implementation

OpenAIRE

Zanev, Vladimir; Radenski, Atanas

2011-01-01

This paper analyzes difficulties with the introduction of object-oriented concepts in introductory computing education and then proposes a two-language, two-paradigm curriculum model that alleviates such difficulties. Our two-language, two-paradigm curriculum model begins with teaching imperative programming using Python programming language, continues with teaching object-oriented computing using Java, and concludes with teaching object-oriented data structures with Java.

The Python ARM Radar Toolkit (Py-ART), a Library for Working with Weather Radar Data in the Python Programming Language

OpenAIRE

Helmus, Jonathan J; Collis, Scott M

2016-01-01

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 Cy...

X Python reference manual

NARCIS (Netherlands)

K.S. Mullender (Sjoerd)

1995-01-01

textabstractThis document describes the built-in types, exceptions, and functions of the X windows extension to Python. It assumes basic knowledge about the Python language and access to the X windows documentation. For an informal introduction to the language, see the Python Tutorial. The Python

Python Introduction and Installation

Directory of Open Access Journals (Sweden)

William J. Turkel

2012-07-01

Full Text Available This first lesson in our section on dealing with Online Sources is designed to get you and your computer set up to start programming. We will focus on installing the relevant software – all free and reputable – and finally we will help you to get your toes wet with some simple programming that provides immediate results. In this opening module you will install the Python programming language, the Beautiful Soup HTML/XML parser, and a text editor. Screencaps provided here come from Komodo Edit, but you can use any text editor capable of working with Python. Here’s a list of other options: Python Editors. Once everything is installed, you will write your first programs, “Hello World” in Python and HTML.

Python and computer vision

Energy Technology Data Exchange (ETDEWEB)

Doak, J. E. (Justin E.); Prasad, Lakshman

2002-01-01

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

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

Science.gov (United States)

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 imperative and declarative modelling approaches in computational neuroscience

Directory of Open Access Journals (Sweden)

Michael eVella

2014-04-01

Full Text Available 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 APIs (Application Programming Interfaces 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.

Python 3 text processing with NLTK 3 cookbook

CERN Document Server

Perkins, Jacob

2014-01-01

This book is intended for Python programmers interested in learning how to do natural language processing. Maybe you've learned the limits of regular expressions the hard way, or you've realized that human language cannot be deterministically parsed like a computer language. Perhaps you have more text than you know what to do with, and need automated ways to analyze and structure that text. This Cookbook will show you how to train and use statistical language models to process text in ways that are practically impossible with standard programming tools. A basic knowledge of Python and the basi

Programming Python

CERN Document Server

Lutz, Mark

2011-01-01

If you've mastered Python's fundamentals, you're ready to start using it to get real work done. Programming Python will show you how, with in-depth tutorials on the language's primary application domains: system administration, GUIs, and the Web. You'll also explore how Python is used in databases, networking, front-end scripting layers, text processing, and more. This book focuses on commonly used tools and libraries to give you a comprehensive understanding of Python's many roles in practical, real-world programming. You'll learn language syntax and programming techniques in a clear and co

Learning Python

CERN Document Server

Lutz, Mark

2009-01-01

Google and YouTube use Python because it's highly adaptable, easy to maintain, and allows for rapid development. If you want to write high-quality, efficient code that's easily integrated with other languages and tools, this hands-on book will help you be productive with Python quickly -- whether you're new to programming or just new to Python. It's an easy-to-follow self-paced tutorial, based on author and Python expert Mark Lutz's popular training course. Each chapter contains a stand-alone lesson on a key component of the language, and includes a unique Test Your Knowledge section with p

Python to learn programming

Science.gov (United States)

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.

Head First Python

CERN Document Server

Barry, Paul

2010-01-01

Ever wished you could learn Python from a book? Head First Python is a complete learning experience for Python that helps you learn the language through a unique method that goes beyond syntax and how-to manuals, helping you understand how to be a great Python programmer. You'll quickly learn the language's fundamentals, then move onto persistence, exception handling, web development, SQLite, data wrangling, and Google App Engine. You'll also learn how to write mobile apps for Android, all thanks to the power that Python gives you. We think your time is too valuable to waste struggling with

PyCSP - Communicating Sequential Processes for Python

DEFF Research Database (Denmark)

Vinter, Brian; Bjørndalen, John Markus; Anshus, Otto Johan

CSP presently supports the core CSP abstractions. We introduce the PyCSP library, its implementation, a few performance benchmarks, and show example code using PyCSP. An early prototype of PyCSP has been used in this year's Extreme Multiprogramming Class at the CS department, university of Copenhagen......The Python programming language is effective for rapidly specifying programs and experimenting with them. It is increasingly being used in computational sciences, and in teaching computer science. CSP is effective for describing concurrency. It has become especially relevant with the emergence...... of commodity multi-core architectures. We are interested in exploring how a combination of Python and CSP can benefit both the computational sciences and the hands-on teaching of distributed and parallel computing in computer science. To make this possible, we have developed PyCSP, a CSP library for Python. Py...

Beginning Python using Python 2.6 and Python 3.1

CERN Document Server

Payne, James

2010-01-01

Beginning Python: Using Python 2.6 and Python 3.1 introduces this open source, portable, interpreted, object-oriented programming language that combines remarkable power with clear syntax. This book enables you to quickly create robust, reliable, and reusable Python applications by teaching the basics so you can quickly develop Web and scientific applications, incorporate databases, and master systems tasks on various operating systems, including Linux, MAC OS, and Windows. You’ll get a comprehensive tutorial that guides you from writing simple, basic Python scripts all the way through complex concepts, and also features a reference of the standard modules with examples illustrating how to implement features in the various modules. Plus, the book covers using Python in specific program development domains, such as XML, databases, scientific applications, network programming, and Web development

pyPaSWAS: Python-based multi-core CPU and GPU sequence alignment.

Science.gov (United States)

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.

SymPy: symbolic computing in Python

Directory of Open Access Journals (Sweden)

Aaron Meurer

2017-01-01

Full Text Available SymPy is an open source computer algebra system written in pure Python. It is built with a focus on extensibility and ease of use, through both interactive and programmatic applications. These characteristics have led SymPy to become a popular symbolic library for the scientific Python ecosystem. This paper presents the architecture of SymPy, a description of its features, and a discussion of select submodules. The supplementary material provide additional examples and further outline details of the architecture and features of SymPy.

Towards Python-based Domain-specific Languages for Self-reconfigurable Modular Robotics Research

DEFF Research Database (Denmark)

Moghadam, Mikael; Johan Christensen, David; Brandt, David

2013-01-01

This paper explores the role of operating system and high-level languages in the development of software and domain-specific languages (DSLs) for self-reconfigurable robotics. We review some of the current trends in self-reconfigurable robotics and describe the development of a software system...... for ATRON II which utilizes Linux and Python to significantly improve software abstraction and portability while providing some basic features which could prove useful when using Python, either stand-alone or via a DSL, on a self-reconfigurable robot system. These features include transparent socket...... communication, module identification, easy software transfer and reliable module-to-module communication. The end result is a software platform for modular robots that where appropriate builds on existing work in operating systems, virtual machines, middleware and high-level languages....

Python library reference

NARCIS (Netherlands)

G. van Rossum (Guido)

1995-01-01

textabstractPython is an extensible, interpreted, object-oriented programming language. It supports a wide range of applications, from simple text processing scripts to interactive WWW browsers. While the Python Reference Manual describes the exact syntax and semantics of the language, it does not

p3d--Python module for structural bioinformatics.

Science.gov (United States)

Fufezan, Christian; Specht, Michael

2009-08-21

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

Simplifying the parallelization of scientific codes by a function-centric approach in Python

International Nuclear Information System (INIS)

Nilsen, Jon K; Cai Xing; Langtangen, Hans Petter; Hoeyland, Bjoern

2010-01-01

The purpose of this paper is to show how existing scientific software can be parallelized using a separate thin layer of Python code where all parallelization-specific tasks are implemented. We provide specific examples of such a Python code layer, which can act as templates for parallelizing a wide set of serial scientific codes. The use of Python for parallelization is motivated by the fact that the language is well suited for reusing existing serial codes programmed in other languages. The extreme flexibility of Python with regard to handling functions makes it very easy to wrap up decomposed computational tasks of a serial scientific application as Python functions. Many parallelization-specific components can be implemented as generic Python functions, which may take as input those wrapped functions that perform concrete computational tasks. The overall programming effort needed by this parallelization approach is limited, and the resulting parallel Python scripts have a compact and clean structure. The usefulness of the parallelization approach is exemplified by three different classes of application in natural and social sciences.

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

Science.gov (United States)

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.

MDSplus objects-Python implementation

Energy Technology Data Exchange (ETDEWEB)

Fredian, T., E-mail: twf@psfc.mit.ed [Massachusetts Institute of Technology, Plasma Science and Fusion Center, NW17-268, 175 Albany Street, Cambridge, MA 02139 (United States); Stillerman, J. [Massachusetts Institute of Technology, Plasma Science and Fusion Center, NW17-268, 175 Albany Street, Cambridge, MA 02139 (United States); Manduchi, G. [Consorzio RFX, Euratom-ENEA Association, Corso Stati Uniti 4, Padova 35127 (Italy)

2010-07-15

MDSplus is a data acquisition and analysis software package used widely throughout the international fusion research community. During the past year, an important set of enhancements were designed under the project name of 'MDSobjects' which would provide a common, powerful application programming interface (API) to MDSplus in programming languages with object-oriented capabilities. This paper will discuss the Python language implementation of this API and some of the capabilities that this implementation provides for data storage and retrieval using the MDSplus system. We have implemented a new MDSplus Python module which exposes the MDSplus objects features to the language. The internal MDSplus programming language, TDI, has also been enhanced to be able to invoke Python commands from the TDI language. Now that Python is aware of the complex data structures in MDSplus such as Signals, the language becomes a very good candidate for applications ranging from data acquisition device support to analysis and visualization.

MDSplus objects-Python implementation

International Nuclear Information System (INIS)

Fredian, T.; Stillerman, J.; Manduchi, G.

2010-01-01

MDSplus is a data acquisition and analysis software package used widely throughout the international fusion research community. During the past year, an important set of enhancements were designed under the project name of 'MDSobjects' which would provide a common, powerful application programming interface (API) to MDSplus in programming languages with object-oriented capabilities. This paper will discuss the Python language implementation of this API and some of the capabilities that this implementation provides for data storage and retrieval using the MDSplus system. We have implemented a new MDSplus Python module which exposes the MDSplus objects features to the language. The internal MDSplus programming language, TDI, has also been enhanced to be able to invoke Python commands from the TDI language. Now that Python is aware of the complex data structures in MDSplus such as Signals, the language becomes a very good candidate for applications ranging from data acquisition device support to analysis and visualization.

Python and AWS Cookbook

CERN Document Server

Garnaat, Mitch

2011-01-01

If you intend to use Amazon Web Services (AWS) for remote computing and storage, Python is an ideal programming language for developing applications and controlling your cloud-based infrastructure. This cookbook gets you started with more than two dozen recipes for using Python with AWS, based on the author's boto library. You'll find detailed recipes for working with the S3 storage service as well as EC2, the service that lets you design and build cloud applications. Each recipe includes a code solution you can use immediately, along with a discussion of why and how the recipe works. You al

Python Switch Statement

Directory of Open Access Journals (Sweden)

2008-06-01

Full Text Available The Python programming language does not have a built in switch/case control structure as found in many other high level programming languages. It is thought by some that this is a deficiency in the language, and the control structure should be added. This paper demonstrates that not only is the control structure not needed, but that the methods available in Python are more expressive than built in case statements in other high level languages.

Python Integration with a Functional DBMS

OpenAIRE

Zou, Hanzheng

2009-01-01

Python is an Object Oriented programming language and widely used nowadays. This report describes how to extend a functional database system Amos II for integration with Python. Several possibilities are analyzed to combine the Amos II C external interfaces with those of Python. Based on these discussions, new functionality has been added to the Python language by implementing a Python C external module. A basic API called PyAmos, interfacing Python and Amos II, is proposed and implemented in...

DendroPy: a Python library for phylogenetic computing.

Science.gov (United States)

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).

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

OpenAIRE

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 ...

Python high performance programming

CERN Document Server

Lanaro, Gabriele

2013-01-01

An exciting, easy-to-follow guide illustrating the techniques to boost the performance of Python code, and their applications with plenty of hands-on examples.If you are a programmer who likes the power and simplicity of Python and would like to use this language for performance-critical applications, this book is ideal for you. All that is required is a basic knowledge of the Python programming language. The book will cover basic and advanced topics so will be great for you whether you are a new or a seasoned Python developer.

p3d – Python module for structural bioinformatics

Directory of Open Access Journals (Sweden)

Fufezan Christian

2009-08-01

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

Introduction into bi-partite networks in python

OpenAIRE

Kasberger, Stefan

2016-01-01

This essay and the related computation delivers a comprehensive introduction into the concept of bipartite networks, a class of networks whose nodes are divided into two sets and only the connection between two nodes in different sets is allowed (Easley and Kleinberg, 2010). The analysis and visualization is done in the programming language Python and offers easy to understand first steps in both fields, network analyses and python programming. As data a collaboration network of github users ...

Programming for computations Python : a gentle introduction to numerical simulations with Python

CERN Document Server

Linge, Svein

2016-01-01

This book presents computer programming as a key method for solving mathematical problems. There are two versions of the book, one for MATLAB and one for Python. The book was inspired by the Springer book TCSE 6: A Primer on Scientific Programming with Python (by Langtangen), but the style is more accessible and concise, in keeping with the needs of engineering students. The book outlines the shortest possible path from no previous experience with programming to a set of skills that allows the students to write simple programs for solving common mathematical problems with numerical methods in engineering and science courses. The emphasis is on generic algorithms, clean design of programs, use of functions, and automatic tests for verification.

Leveraging Python Interoperability Tools to Improve Sapphire's Usability

Energy Technology Data Exchange (ETDEWEB)

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.

Computational physics problem solving with Python

CERN Document Server

Landau, Rubin H; Bordeianu, Cristian C

2015-01-01

The use of computation and simulation has become an essential part of the scientific process. Being able to transform a theory into an algorithm requires significant theoretical insight, detailed physical and mathematical understanding, and a working level of competency in programming. This upper-division text provides an unusually broad survey of the topics of modern computational physics from a multidisciplinary, computational science point of view. Its philosophy is rooted in learning by doing (assisted by many model programs), with new scientific materials as well as with the Python progr

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

International Nuclear Information System (INIS)

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

2010-01-01

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

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

Science.gov (United States)

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

2015-01-01

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

Reflection-Based Python-C++ Bindings

International Nuclear Information System (INIS)

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

2004-01-01

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

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

Science.gov (United States)

Machalek, P.; Kim, S. M.; Berry, R. D.; Liang, A.; Small, T.; Brevdo, E.; Kuznetsova, A.

2012-12-01

We describe how the Climate Corporation uses Python and Clojure, a language impleneted on top of Java, to generate climatological forecasts for precipitation based on the Advanced Hydrologic Prediction Service (AHPS) radar based daily precipitation measurements. A 2-year-long forecasts is generated on each of the ~650,000 CONUS land based 4-km AHPS grids by constructing 10,000 ensembles sampled from a 30-year reconstructed AHPS history for each grid. The spatial and temporal correlations between neighboring AHPS grids and the sampling of the analogues are handled by Python. The parallelization for all the 650,000 CONUS stations is further achieved by utilizing the MAP-REDUCE framework (http://code.google.com/edu/parallel/mapreduce-tutorial.html). Each full scale computational run requires hundreds of nodes with up to 8 processors each on the Amazon Elastic MapReduce (http://aws.amazon.com/elasticmapreduce/) distributed computing service resulting in 3 terabyte datasets. We further describe how we have productionalized a monthly run of the simulations process at full scale of the 4km AHPS grids and how the resultant terabyte sized datasets are handled.

Dive Into Python 3

CERN Document Server

Pilgrim, Mark

2009-01-01

Mark Pilgrim's Dive Into Python 3 is a hands-on guide to Python 3 (the latest version of the Python language) and its differences from Python 2. As in the original book, Dive Into Python, each chapter starts with a real, complete code sample, proceeds to pick it apart and explain the pieces, and then puts it all back together in a summary at the end. This book includes: * Example programs completely rewritten to illustrate powerful new concepts now available in Python 3: sets, iterators, generators, closures, comprehensions, and much more* A detailed case study of porting a major library from

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

Science.gov (United States)

Hedley, Joanna; Eatwell, Kevin; Schwarz, Tobias

2014-01-01

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

Algorithmic synthesis using Python compiler

Science.gov (United States)

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.

Using Python as a first programming environment for computational physics in developing countries

Science.gov (United States)

Akpojotor, Godfrey; Ehwerhemuepha, Louis; Echenim, Myron; Akpojotor, Famous

2011-03-01

Python unique features such its interpretative, multiplatform and object oriented nature as well as being a free and open source software creates the possibility that any user connected to the internet can download the entire package into any platform, install it and immediately begin to use it. Thus Python is gaining reputation as a preferred environment for introducing students and new beginners to programming. Therefore in Africa, the Python African Tour project has been launched and we are coordinating its use in computational science. We examine here the challenges and prospects of using Python for computational physics (CP) education in developing countries (DC). Then we present our project on using Python to simulate and aid the learning of laboratory experiments illustrated here by modeling of the simple pendulum and also to visualize phenomena in physics illustrated here by demonstrating the wave motion of a particle in a varying potential. This project which is to train both the teachers and our students on CP using Python can easily be adopted in other DC.

Python 3 for Absolute Beginners

CERN Document Server

Hall, Tim

2009-01-01

There are many more people who want to study programming other than aspiring computer scientists with a passing grade in advanced calculus. This guide appeals to your intelligence and ability to solve practical problems, while gently teaching the most recent revision of the programming language Python. You can learn solid software design skills and accomplish practical programming tasks, like extending applications and automating everyday processes, even if you have no programming experience at all. Authors Tim Hall and J-P Stacey use everyday language to decode programming jargon and teach Py

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

Science.gov (United States)

Jurica, Peter; van Leeuwen, Cees

2009-01-01

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

Beginning programming with Python for dummies

CERN Document Server

Mueller, John Paul

2014-01-01

Learn Python-the fun and easy way-and get in the programming game today! Python is one of the fastest growing programming languages, and no wonder. It requires three to five times less time than developing in Java, is a great building block for learning both procedural and object-oriented programming concepts, and is an ideal language for data analysis. Beginning Programming with Python For Dummies is the perfect guide to this dynamic and powerful programming language-even if you''ve never coded before! Author John Paul Mueller draws on his vast programming knowledge and experience to guide yo

ParselTongue: AIPS Talking Python

Science.gov (United States)

Kettenis, M.; van Langevelde, H. J.; Reynolds, C.; Cotton, B.

2006-07-01

After more than 20 years of service, classic AIPS still is the data reduction package of choice for many radio-interferometry projects, especially for VLBI. Its age shows, most prominently in the limited scripting capabilities of its user interface: POPS. ParselTongue is an attempt to make the trusted AIPS algorithms and AIPS data structures available in a modern dynamic programming language: Python. It also provides an environment to do distributed computing to take advantage of modern computing clusters. This makes it suitable for use as a scripting interface for doing complicated data reduction on large data sets. It is also used as a coding platform for the new calibration algorithms that are being developed for the European VLBI Network as part of the ALBUS project. Here we hope to take advantage of Python's extensive support for web-based technologies to automate things like collecting calibration data.

Python as a federation tool for GENESIS 3.0.

Directory of Open Access Journals (Sweden)

Hugo Cornelis

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

Python as a federation tool for GENESIS 3.0.

Science.gov (United States)

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

2012-01-01

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

Wyrm: A Brain-Computer Interface Toolbox in Python.

Science.gov (United States)

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

2015-10-01

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

Python for Scientific Computing Education: Modeling of Queueing Systems

Directory of Open Access Journals (Sweden)

Vladimiras Dolgopolovas

2014-01-01

Full Text Available In this paper, we present the methodology for the introduction to scientific computing based on model-centered learning. We propose multiphase queueing systems as a basis for learning objects. We use Python and parallel programming for implementing the models and present the computer code and results of stochastic simulations.

Python tutorial

NARCIS (Netherlands)

G. van Rossum (Guido)

1995-01-01

textabstractPython is a simple, yet powerful programming language that bridges the gap between C and shell programming, and is thus ideally suited for ``throw-away programming'' and rapid prototyping. Its syntax is put together from constructs borrowed from a variety of other languages; most

The Julia programming language: the future of scientific computing

Science.gov (United States)

Gibson, John

2017-11-01

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

Python pocket reference

CERN Document Server

Lutz, Mark

2010-01-01

This is the book to reach for when you're coding on the fly and need an answer now. It's an easy-to-use reference to the core language, with descriptions of commonly used modules and toolkits, and a guide to recent changes, new features, and upgraded built-ins -- all updated to cover Python 3.X as well as version 2.6. You'll also quickly find exactly what you need with the handy index. Written by Mark Lutz -- widely recognized as the world's leading Python trainer -- Python Pocket Reference, Fourth Edition, is the perfect companion to O'Reilly's classic Python tutorials, also written by Mark

Python data analysis

CERN Document Server

Idris, Ivan

2014-01-01

This book is for programmers, scientists, and engineers who have knowledge of the Python language and know the basics of data science. It is for those who wish to learn different data analysis methods using Python and its libraries. This book contains all the basic ingredients you need to become an expert data analyst.

Probabilistic programming in Python using PyMC3

Directory of Open Access Journals (Sweden)

John Salvatier

2016-04-01

Full Text Available Probabilistic programming allows for automatic Bayesian inference on user-defined probabilistic models. Recent advances in Markov chain Monte Carlo (MCMC sampling allow inference on increasingly complex models. This class of MCMC, known as Hamiltonian Monte Carlo, requires gradient information which is often not readily available. PyMC3 is a new open source probabilistic programming framework written in Python that uses Theano to compute gradients via automatic differentiation as well as compile probabilistic programs on-the-fly to C for increased speed. Contrary to other probabilistic programming languages, PyMC3 allows model specification directly in Python code. The lack of a domain specific language allows for great flexibility and direct interaction with the model. This paper is a tutorial-style introduction to this software package.

Julia and Python in Astronomy: Better Together

OpenAIRE

Barbary, Kyle

2016-01-01

Astronomers love Python because it is open source, easy to learn, and has a tremendous ecosystem for scientific computing. The Julia programming language has many of those same characteristics. In this talk, I discuss Julia, its use in astronomy and the growing ecosystem of astronomy packages, particularly those managed by the JuliaAstro organization (http://JuliaAstro.github.io).

Writing analytic element programs in Python.

Science.gov (United States)

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.

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

Science.gov (United States)

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

2018-01-01

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

Emerge - A Python environment for the modeling of subsurface transfers

Science.gov (United States)

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…

Beginning Python from novice to professional

CERN Document Server

Hetland, Magnus Lie

2005-01-01

""Beginning Python: From Novice to Professional"" is the most comprehensive book on the Python ever written. Based on ""Practical Python,"" this newly revised book is both an introduction and practical reference for a swath of Python-related programming topics, including addressing language internals, database integration, network programming, and web services. Advanced topics, such as extending Python and packaging/distributing Python applications, are also covered. Ten different projects illustrate the concepts introduced in the book. You will learn how to create a P2P file-sharing applicati

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

Science.gov (United States)

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

2013-04-15

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

Game Development in Python with Pygame - 2D Platformgame for Raspberry Pi 3 driven arcademachine

OpenAIRE

Bryndum, Leonora; Hastrup, Jakob Scheunemann; Holm, Kevin Martin Lindemark; Kjær, Alberte Jeberg

2017-01-01

The purpose of this study, is to explore how to develop a 2D-arcade platform game for a Raspberry Pi 3 computer. This will be done with the programming language Python 3 and the game development framework Pygame. To do this, we investigate and learn about the Python 3 language and how this is structured. We investigate what an arcade game usually contains in the terms of programmatic content, and choose the focus points: Game Loop, Collisions, Physics, Animation, Level Design, Camera, Heads U...

Python Introduction and Installation

OpenAIRE

William J. Turkel; Adam Crymble

2012-01-01

This first lesson in our section on dealing with Online Sources is designed to get you and your computer set up to start programming. We will focus on installing the relevant software – all free and reputable – and finally we will help you to get your toes wet with some simple programming that provides immediate results. In this opening module you will install the Python programming language, the Beautiful Soup HTML/XML parser, and a text editor. Screencaps provided here come from Komodo ...

Specifying the Behaviour of Python Programs: Language and Basic Examples

Directory of Open Access Journals (Sweden)

2010-04-01

Full Text Available This manuscript describe BeSSY, a function-centric language for formal behavioural specification that requires no more than high-school mathematics on arithmetic, functions, Boolean algebra and sets theory. An object can be modelled as a union of data sets and functions whereas inherited object can be modelled as a union of supersets and a set of object-specific functions. Python list and dictionary operations will be specified in BeSSY for illustration.

Python reference manual

NARCIS (Netherlands)

G. van Rossum (Guido)

1995-01-01

textabstractPython is a simple, yet powerful, interpreted programming language that bridges the gap between C and shell programming, and is thus ideally suited for ``throw-away programming'' and rapid prototyping. Its syntax is put together from constructs borrowed from a variety of other languages;

Learning Python with Raspberry Pi

CERN Document Server

Bradbury, Alex

2014-01-01

The must-have companion guide to the Raspberry Pi User Guide! Raspberry Pi chose Python as its teaching language of choice to encourage a new generation of programmers to learn how to program. This approachable book serves as an ideal resource for anyone wanting to use Raspberry Pi to learn to program and helps you get started with the Python programming language. Aimed at first-time developers with no prior programming language assumed, this beginner book gets you up and running.Covers variables, loops, and functionsAddresses 3D graphics programmingWalks you through programming MinecraftZero

On Parallel Software Engineering Education Using Python

Science.gov (United States)

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…

Schopnosti překladačů programovacího jazyka Python

OpenAIRE

Pala, Ondřej

2015-01-01

PALA, Ondřej. Ability of compilers programming language Python. Brno, 2015. Diploma thesis. Mendel university in Brno. Diploma thesis rate ability of selected compilers programming language Python. First path of thesis is focused to programming language Python and principle of working compilers. Second path is focused to creating testing tasks, defining eva-luation criterias of compilers and testing compilers without testing tasks.

SunPy—Python for solar physics

International Nuclear Information System (INIS)

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

2015-01-01

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

OpenSeesPy: Python library for the OpenSees finite element framework

Science.gov (United States)

Zhu, Minjie; McKenna, Frank; Scott, Michael H.

2018-01-01

OpenSees, an open source finite element software framework, has been used broadly in the earthquake engineering community for simulating the seismic response of structural and geotechnical systems. The framework allows users to perform finite element analysis with a scripting language and for developers to create both serial and parallel finite element computer applications as interpreters. For the last 15 years, Tcl has been the primary scripting language to which the model building and analysis modules of OpenSees are linked. To provide users with different scripting language options, particularly Python, the OpenSees interpreter interface was refactored to provide multi-interpreter capabilities. This refactoring, resulting in the creation of OpenSeesPy as a Python module, is accomplished through an abstract interface for interpreter calls with concrete implementations for different scripting languages. Through this approach, users are able to develop applications that utilize the unique features of several scripting languages while taking advantage of advanced finite element analysis models and algorithms.

Mahotas: Open source software for scriptable computer vision

Directory of Open Access Journals (Sweden)

Luis Pedro Coelho

2013-07-01

Full Text Available Mahotas is a computer vision library for Python. It contains traditional image processing functionality such as filtering and morphological operations as well as more modern computer vision functions for feature computation, including interest point detection and local descriptors. The interface is in Python, a dynamic programming language, which is appropriate for fast development, but the algorithms are implemented in C++ and are tuned for speed. The library is designed to fit in with the scientific software ecosystem in this language and can leverage the existing infrastructure developed in that language. Mahotas is released under a liberal open source license (MIT License and is available from http://github.com/luispedro/mahotas and from the Python Package Index (http://pypi.python.org/pypi/mahotas. Tutorials and full API documentation are available online at http://mahotas.readthedocs.org/.

PaCAL: A Python Package for Arithmetic Computations with Random Variables

Directory of Open Access Journals (Sweden)

Marcin Korze?

2014-05-01

Full Text Available In this paper we present PaCAL, a Python package for arithmetical computations on random variables. The package is capable of performing the four arithmetic operations: addition, subtraction, multiplication and division, as well as computing many standard functions of random variables. Summary statistics, random number generation, plots, and histograms of the resulting distributions can easily be obtained and distribution parameter ?tting is also available. The operations are performed numerically and their results interpolated allowing for arbitrary arithmetic operations on random variables following practically any probability distribution encountered in practice. The package is easy to use, as operations on random variables are performed just as they are on standard Python variables. Independence of random variables is, by default, assumed on each step but some computations on dependent random variables are also possible. We demonstrate on several examples that the results are very accurate, often close to machine precision. Practical applications include statistics, physical measurements or estimation of error distributions in scienti?c computations.

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

Directory of Open Access Journals (Sweden)

Berk Ekmekci

2016-06-01

Full Text Available 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.

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

Science.gov (United States)

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.

Pybus - A Python Software Bus

International Nuclear Information System (INIS)

Lavrijsen, Wim T.L.P.

2004-01-01

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

Imagining a Stata / Python Combination

Science.gov (United States)

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.

An introduction to statistics with Python with applications in the life sciences

CERN Document Server

Haslwanter, Thomas

2016-01-01

This textbook provides an introduction to the free software Python and its use for statistical data analysis. It covers common statistical tests for continuous, discrete and categorical data, as well as linear regression analysis and topics from survival analysis and Bayesian statistics. Working code and data for Python solutions for each test, together with easy-to-follow Python examples, can be reproduced by the reader and reinforce their immediate understanding of the topic. With recent advances in the Python ecosystem, Python has become a popular language for scientific computing, offering a powerful environment for statistical data analysis and an interesting alternative to R. The book is intended for master and PhD students, mainly from the life and medical sciences, with a basic knowledge of statistics. As it also provides some statistics background, the book can be used by anyone who wants to perform a statistical data analysis. .

A Python interface to Diffpack-based classes and solvers

OpenAIRE

Munthe-Kaas, Heidi Vikki

2013-01-01

Python is a programming language that has gained a lot of popularity during the last 15 years, and as a very easy-to-learn and flexible scripting language it is very well suited for computa- tional science, both in mathematics and in physics. Diffpack is a PDE library written in C++, made for easier implementation of both smaller PDE solvers and for larger libraries of simu- lators. It contains large class hierarchies for different solvers, grids, arrays, parallel computing and almost everyth...

Introduction to Python for CMF Authority Users

Energy Technology Data Exchange (ETDEWEB)

Pritchett-Sheats, Lori A. [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

2017-03-14

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

EPICS V4 in Python

International Nuclear Information System (INIS)

Guobao Shen; Kraimer, M.; Davidsaver, M.

2012-01-01

At NSLS-II, Python has been selected as the primary development language for physics applications. Interest in Python as a rapid application development environment continues to grow. Many large experimental scientific facilities have adopted Python for beam commissioning and the operation. The EPICS control system framework has become the de facto standard for the control of large experimental facilities, where it is in use in over 100 facilities. The next version of EPICS (EPICS V4), under active development will extend the support for physics applications, data acquisition, and data analysis. Python support for EPICS V4 will provide an effective framework to address these requirements. This paper presents design, development and status of activities focused on EPICS V4 in Python

Aura: A Multi-Featured Programming Framework in Python

Directory of Open Access Journals (Sweden)

2010-09-01

Full Text Available This paper puts forward the design, programming and application of innovative educational software, ‘Aura’ made using Python and PyQt Python bindings. The research paper presents a new concept of using a single tool to relate between syntaxes of various programming languages and algorithms. It radically increases their understanding and retaining capacity, since they can correlate between many programming languages. The software is a totally unorthodox attempt towards helping students who have their first tryst with programming languages. The application is designed to help students understand how algorithms work and thus, help them in learning multiple programming languages on a single platform using an interactive graphical user interface. This paper elucidates how using Python and PyQt bindings, a comprehensive feature rich application, that implements an interactive algorithm building technique, a web browser, multiple programming language framework, a code generator and a real time code sharing hub be embedded into a single interface. And also explains, that using Python as building tool, it requires much less coding than conventional feature rich applications coded in other programming languages, and at the same time does not compromise on stability, inter-operability and robustness of the application.

Pro Python System Administration

CERN Document Server

Sileika, R

2010-01-01

As time goes on, system administrators are presented with increasingly complicated challenges. In the early days, a team of engineers might have had to look after one or two systems. These days, one engineer can administer hundreds or thousands of systems. System administrators are gradually replacing their tools with more advanced and flexible ones. One of the choices is Python. Structurally, Python is a modern, high-level language with a very clean syntax. Python comes with many built-in libraries that can make automation tasks easier. It also has extensive set of third-party libraries and a

PyXNAT: XNAT in Python

Directory of Open Access Journals (Sweden)

Yannick eSchwartz

2012-05-01

Full Text Available 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 programatic 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 backend library to build XNAT clients and as an alternative frontend from the command line.

PyXNAT: XNAT in Python.

Science.gov (United States)

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.

Extending and embedding the Python interpreter

NARCIS (Netherlands)

G. van Rossum (Guido)

1995-01-01

textabstractPython is an interpreted, object-oriented programming language. This document describes how to write modules in C or C++ to extend the Python interpreter with new modules. Those modules can define new functions but also new object types and their methods. The document also describes

Programming ArcGIS with Python cookbook

CERN Document Server

Pimpler, Eric

2015-01-01

Programming ArcGIS with Python Cookbook, Second Edition, is written for GIS professionals who wish to revolutionize their ArcGIS workflow with Python. Whether you are new to ArcGIS or a seasoned professional, you almost certainly spend time each day performing various geoprocessing tasks. This book will teach you how to use the Python programming language to automate these geoprocessing tasks and make you a more efficient and effective GIS professional.

Parallel programming with Python

CERN Document Server

Palach, Jan

2014-01-01

A fast, easy-to-follow and clear tutorial to help you develop Parallel computing systems using Python. Along with explaining the fundamentals, the book will also introduce you to slightly advanced concepts and will help you in implementing these techniques in the real world. If you are an experienced Python programmer and are willing to utilize the available computing resources by parallelizing applications in a simple way, then this book is for you. You are required to have a basic knowledge of Python development to get the most of this book.

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

Science.gov (United States)

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.

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

DEFF Research Database (Denmark)

Enkovaara, Jussi; Romero, Nichols A.; Shende, Sameer

2011-01-01

of the productivity enhancing features together with a good numerical performance. We have used this approach in implementing an electronic structure simulation software GPAW using the combination of Python and C programming languages. While the chosen approach works well in standard workstations and Unix...... 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...... 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...

A 3d game in python

OpenAIRE

Xu, Minghui

2014-01-01

3D game has widely been accepted and loved by many game players. More and more different kinds of 3D games were developed to feed people’s needs. The most common programming language for development of 3D game is C++ nowadays. Python is a high-level scripting language. It is simple and clear. The concise syntax could speed up the development cycle. This project was to develop a 3D game using only Python. The game is about how a cat lives in the street. In order to live, the player need...

Feasibility of Python in teaching programming

Directory of Open Access Journals (Sweden)

Rafael Martínez Estévez

2014-03-01

Full Text Available Given the diversity of the objectives of the programming courses in the Cuban educational system and the training of teachers, it is not easy to decide the language to be used in each case. The intention of this article is to bring to debate to our context a trend that has been growing in the last decade: Python as a first programming language. The aim of this study is to compile some inter national experiences in the use of Python in introductory programming courses, also analyzing their advantages and disadvantages.

Re-imagining a Stata/Python Combination

Science.gov (United States)

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.

Python GUI Scripting Interface for Running Atomic Physics Applications

OpenAIRE

Tahat, Amani; Tahat, Mofleh

2011-01-01

We create a Python GUI scripting interface working under Windows in addition to (UNIX/Linux). The GUI has been built around the Python open-source programming language. We use the Python's GUI library that so called Python Mega Widgets (PMW) and based on Tkinter Python module (http://www.freenetpages.co.uk/hp/alan.gauld/tutgui.htm). The new GUI was motivated primarily by the desire of more updated operations, more flexibility incorporating future and current improvements in producing atomic d...

Pro Android Python with SL4A Writing Android Native Apps Using Python, Lua, and Beanshell

CERN Document Server

Ferrill, Paul

2011-01-01

Pro Android Python with SL4A is for programmers and hobbyists who want to write apps for Android devices without having to learn Java first. Paul Ferrill leads you from installing the Scripting Layer for Android (SL4A) to writing small scripts, to more complicated and interesting projects, and finally to uploading and packaging your programs to an Android device. Android runs scripts in many scripting languages, but Python, Lua, and Beanshell are particularly popular. Most programmers know more than one programming language, so that they have the best tool for whatever task they want to accomp

WekaPyScript: Classification, Regression, and Filter Schemes for WEKA Implemented in Python

Directory of Open Access Journals (Sweden)

Christopher Beckham

2016-08-01

Full Text Available WekaPyScript is a package for the machine learning software WEKA that allows learning algorithms and preprocessing methods for classification and regression to be written in Python, as opposed to WEKA’s implementation language, Java. This opens up WEKA to its machine learning and scientific computing ecosystem. Furthermore, due to Python’s minimalist syntax, learning algorithms and preprocessing methods can be prototyped easily and utilised from within WEKA. WekaPyScript works by running a local Python server using the host’s installation of Python; as a result, any libraries installed in the host installation can be leveraged when writing a script for WekaPyScript. Three example scripts (two learning algorithms and one preprocessing method are presented.

PRACTICAL APPROACH FOR HYPERSPECTRAL IMAGE PROCESSING IN PYTHON

OpenAIRE

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

2018-01-01

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 ...

A python based interface for the tandem-linac control system

International Nuclear Information System (INIS)

Ajith Kumar, B.P.

2011-01-01

The control system for the Tandem-LINAC accelerator system at IUAC is a client-server design running on a network of PCs under the GNU/Linux operating system. The computers connected to the devices in the accelerator run a server program. The computers providing the user interface runs different kinds of client programs that communicates to the servers over a TCT/IP network to control/monitor the accelerator parameters. Both the programs were written in C language and some programming expertise was required to write the client programs. The addition of a Python language interface has enabled the users to write programs for specific tasks like data logging and partial automation of the operation with minimal effort. (author)

PNet: A Python Library for Petri Net Modeling and Simulation

OpenAIRE

Zhu En Chay; Bing Feng Goh; Maurice HT Ling

2016-01-01

Petri Net is a formalism to describe changes between 2 or more states across discrete time and has been used to model many systems. We present PNet – a pure Python library for Petri Net modeling and simulation in Python programming language. The design of PNet focuses on reducing the learning curve needed to define a Petri Net by using a text-based language rather than programming constructs to define transition rules. Complex transition rules can be refined as regular Python functions. To de...

Python for Unix and Linux system administration

CERN Document Server

Gift, Noah

2007-01-01

Python is an ideal language for solving problems, especially in Linux and Unix networks. With this pragmatic book, administrators can review various tasks that often occur in the management of these systems, and learn how Python can provide a more efficient and less painful way to handle them. Each chapter in Python for Unix and Linux System Administration presents a particular administrative issue, such as concurrency or data backup, and presents Python solutions through hands-on examples. Once you finish this book, you'll be able to develop your own set of command-line utilities with Pytho

Interactive game programming with Python (CodeSkulptor)

OpenAIRE

Ajayi, Richard Olugbenga

2014-01-01

Over the years, several types of gaming platforms have been created to encourage a more organised and friendly atmosphere for game lovers in various works of life, culture, and environment. This thesis focuses on the concept of interactive programming using Python. It encourages the use of Python to create simple interactive games applications based on basic human concept and ideas. CodeSkulptor is a browser-based IDE programming environment and uses the Python programming language. O...

Simulation with Python on transverse modes of the symmetric confocal resonator

Science.gov (United States)

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.

Mastering object-oriented Python

CERN Document Server

Lott, Steven F

2014-01-01

This book follows a standard tutorial approach with approximately 750 code samples spread through the 19 chapters. This amounts to over 5,900 lines of code that illustrate each concept.This book is aimed at programmers who have already learned the basics of object-oriented Python and need to write more sophisticated, flexible code that integrates seamlessly with the rest of Python. This book assumes a computer science background, with experience of common Python design patterns.

DAL Algorithms and Python

CERN Document Server

Aydemir, Bahar

2017-01-01

The Trigger and Data Acquisition (TDAQ) system of the ATLAS detector at the Large Hadron Collider (LHC) at CERN is composed of a large number of distributed hardware and software components. TDAQ system consists of about 3000 computers and more than 25000 applications which, in a coordinated manner, provide the data-taking functionality of the overall system. There is a number of online services required to configure, monitor and control the ATLAS data taking. In particular, the configuration service is used to provide configuration of above components. The configuration of the ATLAS data acquisition system is stored in XML-based object database named OKS. DAL (Data Access Library) allowing to access it's information by C++, Java and Python clients in a distributed environment. Some information has quite complicated structure, so it's extraction requires writing special algorithms. Algorithms available on C++ programming language and partially reimplemented on Java programming language. The goal of the projec...

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

Science.gov (United States)

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

2011-01-01

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

Brian: a simulator for spiking neural networks in Python

Directory of Open Access Journals (Sweden)

Dan F M Goodman

2008-11-01

Full Text Available 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.

Brian: a simulator for spiking neural networks in python.

Science.gov (United States)

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.

Pynamic: the Python Dynamic Benchmark

Energy Technology Data Exchange (ETDEWEB)

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

2007-07-10

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

Python pocket reference, version 2.4

CERN Document Server

Lutz, Mark

2005-01-01

Python is optimized for quality, productivity, portability, and integration. Hundreds of thousands of Python developers around the world rely on Python for general-purpose tasks, Internet scripting, systems programming, user interfaces, and product customization. Available on all major computing platforms, including commercial versions of Unix, Linux, Windows, and Mac OS X, Python is portable, powerful and remarkable easy to use. With its convenient, quick-reference format, Python Pocket Reference, 3rd Edition is the perfect on-the-job reference. More importantly, it's now been refreshed

Python for secret agents

CERN Document Server

Lott, Steven F

2014-01-01

If you are a Python beginner who is looking to learn the language through interesting projects, this book is for you. A basic knowledge of programming and statistics is beneficial to get the most out of the book.

A New Python Library for Spectroscopic Analysis with MIDAS Style

Science.gov (United States)

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

2013-10-01

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

Python for scientists

CERN Document Server

Stewart, John M

2017-01-01

Scientific Python is a significant public domain alternative to expensive proprietary software packages. This book teaches from scratch everything the working scientist needs to know using copious, downloadable, useful and adaptable code snippets. Readers will discover how easy it is to implement and test non-trivial mathematical algorithms and will be guided through the many freely available add-on modules. A range of examples, relevant to many different fields, illustrate the language's capabilities. The author also shows how to use pre-existing legacy code (usually in Fortran77) within the Python environment, thus avoiding the need to master the original code. In this new edition, several chapters have been re-written to reflect the IPython notebook style. With an extended index, an entirely new chapter discussing SymPy and a substantial increase in the number of code snippets, researchers and research students will be able to quickly acquire all the skills needed for using Python effectively.

Pybel: a Python wrapper for the OpenBabel cheminformatics toolkit

Directory of Open Access Journals (Sweden)

Morley Chris

2008-03-01

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

Pyception: Teaching Python with a Serious Game

OpenAIRE

Laskemoen, Kristian

2013-01-01

This thesis set out to study how an online serious game could affect users? motivation on learning Python. One of the projects core goals is to find out whether learning Python is more motivating when having an effortless start through a web based game. A second goal is to find out if Python as a programming language are well suited for a serious game.After the development and implementation of the game, it was performed a user experiment in order to receive feedback. Data from this user expe...

ELLIPT2D: A Flexible Finite Element Code Written Python

International Nuclear Information System (INIS)

Pletzer, A.; Mollis, J.C.

2001-01-01

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

Výuka algoritmizace a programování se zaměřením na programovací jazyk Python

OpenAIRE

Kotek, Lukáš

2013-01-01

The thesis researches the ability of use of Python programming language in the field of high school education and uses qualitative and quantitative methods of research and finds Python suitable. The thesis also brings theoretical analysis of the Python language, including practical exams in the form of sample programs. It researchs even other programming languages used in education and their suitability for this purpose and compares them with Python programming language. It also finds two mos...

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

Science.gov (United States)

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

CS Circles: An In-Browser Python Course for Beginners

OpenAIRE

Pritchard, David; Vasiga, Troy

2012-01-01

Computer Science Circles is a free programming website for beginners that is designed to be fun, easy to use, and accessible to the broadest possible audience. We teach Python since it is simple yet powerful, and the course content is well-structured but written in plain language. The website has over one hundred exercises in thirty lesson pages, plus special features to help teachers support their students. It is available in both English and French. We discuss the philosophy behind the cour...

PyMOOSE: interoperable scripting in Python for MOOSE

Directory of Open Access Journals (Sweden)

Subhasis Ray

2008-12-01

Full Text Available Python is emerging as a common scripting language for simulators. This opens up many possibilities for interoperability in the form of analysis, interfaces, and communications between simulators. We report the integration of Python scripting with the Multi-scale Object Oriented Simulation Environment (MOOSE. MOOSE is a general-purpose simulation system for compartmental neuronal models and for models of signaling pathways based on chemical kinetics. We show how the Python-scripting version of MOOSE, PyMOOSE, combines the power of a compiled simulator with the versatility and ease of use of Python. We illustrate this by using Python numerical libraries to analyze MOOSE output online, and by developing a GUI in Python/Qt for a MOOSE simulation. Finally, we build and run a composite neuronal/signaling model that uses both the NEURON and MOOSE numerical engines, and Python as a bridge between the two. Thus PyMOOSE has a high degree of interoperability with analysis routines, with graphical toolkits, and with other simulators.

Practical Approach for Hyperspectral Image Processing in Python

Science.gov (United States)

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.

An object oriented Python interface for atomistic simulations

Science.gov (United States)

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.

OpenVX-based Python Framework for real-time cross platform acceleration of embedded computer vision applications

Directory of Open Access Journals (Sweden)

Ori Heimlich

2016-11-01

Full Text Available Embedded real-time vision applications are being rapidly deployed in a large realm of consumer electronics, ranging from automotive safety to surveillance systems. However, the relatively limited computational power of embedded platforms is considered as a bottleneck for many vision applications, necessitating optimization. OpenVX is a standardized interface, released in late 2014, in an attempt to provide both system and kernel level optimization to vision applications. With OpenVX, Vision processing are modeled with coarse-grained data flow graphs, which can be optimized and accelerated by the platform implementer. Current full implementations of OpenVX are given in the programming language C, which does not support advanced programming paradigms such as object-oriented, imperative and functional programming, nor does it have runtime or type-checking. Here we present a python-based full Implementation of OpenVX, which eliminates much of the discrepancies between the object-oriented paradigm used by many modern applications and the native C implementations. Our open-source implementation can be used for rapid development of OpenVX applications in embedded platforms. Demonstration includes static and real-time image acquisition and processing using a Raspberry Pi and a GoPro camera. Code is given as supplementary information. Code project and linked deployable virtual machine are located on GitHub: https://github.com/NBEL-lab/PythonOpenVX.

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

Science.gov (United States)

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.

New Python-based methods for data processing

International Nuclear Information System (INIS)

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

2013-01-01

The Computational Crystallography Toolbox (cctbx) is a flexible software platform that has been used to develop high-throughput crystal-screening tools for both synchrotron sources and X-ray free-electron lasers. Plans for data-processing and visualization applications are discussed, and the benefits and limitations of using graphics-processing units are evaluated. Current pixel-array detectors produce diffraction images at extreme data rates (of up to 2 TB h −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

New Python-based methods for data processing

Energy Technology Data Exchange (ETDEWEB)

Sauter, Nicholas K., E-mail: nksauter@lbl.gov; Hattne, Johan; Grosse-Kunstleve, Ralf W.; Echols, Nathaniel [Lawrence Berkeley National Laboratory, 1 Cyclotron Road, Berkeley, CA 94720 (United States)

2013-07-01

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

Integrating the Media Computation API with Pythy, an Online IDE for Novice Python Programmers

OpenAIRE

Athri, Ashima

2015-01-01

Improvements in both software and curricula have helped introductory computer science courses attract and retain more students. Pythy is one such online learning environment that aims to reduce software setup related barriers to learning Python while providing facilities like course management and grading to instructors. To further enable its goals of being beginner-centric, we want to integrate full support for media-computation-style programming activities. The media computation curriculum ...

Machine Learning: developing an image recognition program : with Python, Scikit Learn and OpenCV

OpenAIRE

Nguyen, Minh

2016-01-01

Machine Learning is one of the most debated topic in computer world these days, especially after the first Computer Go program has beaten human Go world champion. Among endless application of Machine Learning, image recognition, which problem is processing enormous amount of data from dynamic input. This thesis will present the basic concept of Machine Learning, Machine Learning algorithms, Python programming language and Scikit Learn – a simple and efficient tool for data analysis in P...

PRACTICAL APPROACH FOR HYPERSPECTRAL IMAGE PROCESSING IN PYTHON

Directory of Open Access Journals (Sweden)

L. Annala

2018-04-01

Full Text Available 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.

a performance analysis for evaluation of programming languages ...

African Journals Online (AJOL)

Mohammed et al.

PROGRAMMING LANGUAGES BASED ON MOBILE COMPUTING. FOR NIGERIA ... Finally, Vb.net is suitable for data Transfer using upload scheme. Keywords: ... INTRODUCTION .... java, Julia, python, matlab, mathematica and Ruby by.

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

Science.gov (United States)

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 .

Obtaining and processing Daymet data using Python and ArcGIS

Science.gov (United States)

Bohms, Stefanie

2013-01-01

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

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

Science.gov (United States)

Iakushkin, Oleg O.; Sedova, Olga S.

2018-01-01

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

Accessing the VO with Python

Science.gov (United States)

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

2014-05-01

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

Learning scientific programming with Python

CERN Document Server

Hill, Christian

2015-01-01

Learn to master basic programming tasks from scratch with real-life scientifically relevant examples and solutions drawn from both science and engineering. Students and researchers at all levels are increasingly turning to the powerful Python programming language as an alternative to commercial packages and this fast-paced introduction moves from the basics to advanced concepts in one complete volume, enabling readers to quickly gain proficiency. Beginning with general programming concepts such as loops and functions within the core Python 3 language, and moving onto the NumPy, SciPy and Matplotlib libraries for numerical programming and data visualisation, this textbook also discusses the use of IPython notebooks to build rich-media, shareable documents for scientific analysis. Including a final chapter introducing challenging topics such as floating-point precision and algorithm stability, and with extensive online resources to support advanced study, this textbook represents a targeted package for students...

A primer on scientific programming with Python

CERN Document Server

Langtangen, Hans Petter

2014-01-01

The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology and finance. The book teaches "Matlab-style" and procedural programming as well as object-oriented programming. High school mathematics is a required background and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science. From the reviews: Langtangen … does an excellent job of introducing programming as a set of skills in problem solving. ...

A primer on scientific programming with Python

CERN Document Server

Langtangen, Hans Petter

2016-01-01

The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology and finance. The book teaches "Matlab-style" and procedural programming as well as object-oriented programming. High school mathematics is a required background and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science. From the reviews: Langtangen … does an excellent job of introducing programming as a set of skills in problem solving. ...

Visualization of the CMS python configuration system

International Nuclear Information System (INIS)

Erdmann, M; Fischer, R; Klimkovich, T; Mueller, G; Steggemann, J; Hegner, B; Hinzmann, A

2010-01-01

The job configuration system of the CMS experiment is based on the Python programming language. Software modules and their order of execution are both represented by Python objects. In order to investigate and verify configuration parameters and dependencies naturally appearing in modular software, CMS employs a graphical tool. This tool visualizes the configuration objects, their dependencies, and the information flow. Furthermore it can be used for documentation purposes. The underlying software concepts as well as the visualization are presented.

Visualization of the CMS python configuration system

Energy Technology Data Exchange (ETDEWEB)

Erdmann, M; Fischer, R; Klimkovich, T; Mueller, G; Steggemann, J [RWTH Aachen University, Physikalisches Institut 3A, 52062 Aachen (Germany); Hegner, B [CERN, CH-1211 Geneva 23 (Switzerland); Hinzmann, A, E-mail: andreas.hinzmann@cern.c

2010-04-01

The job configuration system of the CMS experiment is based on the Python programming language. Software modules and their order of execution are both represented by Python objects. In order to investigate and verify configuration parameters and dependencies naturally appearing in modular software, CMS employs a graphical tool. This tool visualizes the configuration objects, their dependencies, and the information flow. Furthermore it can be used for documentation purposes. The underlying software concepts as well as the visualization are presented.

A modern Python interface for the Generic Mapping Tools

Science.gov (United States)

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

Using Scripting Languages to Teach Programming

OpenAIRE

Syropoulos, Apostolos; Stavrianos, Athanasios

2014-01-01

Nowadays, scripting programming languages like Python, Perl and Ruby are widely used in system programming, scientific computing, etc. Although solving a particular problem in these languages requires less time, less programming effort, and less concepts to be taught to achieve the desired goal, still they are not used as teaching tools. Therefore, the use of scripting languages as a teaching vehicle for programming course is very promising. On the other hand, GUI programming, when performed ...

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

Science.gov (United States)

Gannon, C.

2017-12-01

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

A facility for creating Python extensions in C++

International Nuclear Information System (INIS)

Dubois, P F

1998-01-01

Python extensions are usually created by writing the glue that connects Python to the desired new functionality in the C language. While simple extensions do not require much effort, to do the job correctly with full error checking is tedious and prone to errors in reference counting and to memory leaks, especially when errors occur. The resulting program is difficult to read and maintain. By designing suitable C++ classes to wrap the Python C API, we are able to produce extensions that are correct and which clean up after themselves correctly when errors occur. This facility also integrates the C++ and Python exception facilities. This paper briefly describes our package for this purpose, named CXX. The emphasis is on our design choices and the way these contribute to the construction of accurate Python extensions. We also briefly relate the way CXX's facilities for sequence classes allow use of C++'s Standard Template Library (STL) algorithms on C++ sequences

Implementation of quantum game theory simulations using Python

Science.gov (United States)

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.

IRISpy: Analyzing IRIS Data in Python

Science.gov (United States)

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

2017-08-01

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

VPython: Python plus Animations in Stereo 3D

Science.gov (United States)

Sherwood, Bruce

2004-03-01

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

Python Materials Genomics (pymatgen): A robust, open-source python library for materials analysis

OpenAIRE

Ong, Shyue Ping; Richards, William Davidson; Jain, Anubhav; Hautier, Geoffroy; Kocher, Michael; Cholia, Shreyas; Gunter, Dan; Chevrier, Vincent L.; Persson, Kristin A.; Ceder, Gerbrand

2012-01-01

We present the Python Materials Genomics (pymatgen) library, a robust, open-source Python library for materials analysis. A key enabler in high-throughput computational materials science efforts is a robust set of software tools to perform initial setup for the calculations (e.g., generation of structures and necessary input files) and post-calculation analysis to derive useful material properties from raw calculated data. The pymatgen library aims to meet these needs by (1) defining core Pyt...

PyBus -- A Python Software Bus

OpenAIRE

Lavrijsen, W

2005-01-01

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...

ObsPy: A Python Toolbox for Seismology - Recent Developments and Applications

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Proposal of a Python interface to OpenMI, as the base for open source hydrological framework

Directory of Open Access Journals (Sweden)

Robert Szczepanek

2012-03-01

Full Text Available Hydrologists need simple, yet powerful, open source framework for developing and testing mathematical models. Such framework should ensure long-term interoperability and high scalability. This can be done by implementation of the existing, already tested standards. At the moment two interesting options exist: Open Modelling Interface (OpenMI and Object Modeling System (OMS. OpenMI was developed within the Fifth European Framework Programme for integrated watershed management, described in the Water Framework Directive. OpenMI interfaces are available for the C# and Java programming languages. OpenMI Association is now in the process of agreement with Open Geospatial Consortium (OGC, so the spatial standards existing in OpenMI 2.0 should be better implemented in the future. The OMS project is pure Java, object-oriented modeling framework coordinated by the U.S. Department of Agriculture. Big advantage of OMS compared to OpenMI is its simplicity of implementation. On the other hand, OpenMI seems to be more powerful and better suited for hydrological models. Finally, OpenMI model was selected as the base interface for the proposed open source hydrological framework.  The existing hydrological libraries and models focus usually on just one GIS package (HydroFOSS – GRASS or one operating system (HydroDesktop – Microsoft Windows. The new hydrological framework should break those limitations. To make hydrological models’ implementation as easy as possible, the framework should be based on a simple, high-level computer language. Low and mid-level languages, like Java (SEXTANTE or C (GRASS, SAGA were excluded, as too complicated for regular hydrologist. From popular, high-level languages, Python seems to be a good choice. Leading GIS desktop applications – GRASS and QGIS – use Python as second native language, providing well documented API. This way, a Python-based hydrological library could be easily integrated with any GIS package supporting

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

Science.gov (United States)

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

Flexible Environmental Modeling with Python and Open - GIS

Science.gov (United States)

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

A pythonic integrated solution for virtual prototyping of cyclotrons

International Nuclear Information System (INIS)

Qin Bin; Yang Jun; Xiong Yongqian; Chen Dezhi; Yu Tiaoqin; Dong Tianlin; Zhang Tianjue; Fan Mingwu

2007-01-01

Virtual prototyping (VP) is a novel technique in engineering, which is desired to be applied to cyclotron design and development. Some sub-prototyping components, including beam dynamics, magnet, RF system and control system of cyclotrons, have been developed separately, but an integrated platform which encapsulates these different components is required for global system optimization. Considering that the VP integrated platform is a large-scale software and has numerous loose-coupled components, this paper describes the pythonic approach to implement this platform. By mixing the high-level interpreted Python language and the compiled languages like Fortran/C/C++ in an effective method, this approach can achieve a combination of code efficiency, flexibility and compactness

My Journey from Python to R

OpenAIRE

Lorgat, Mohamed Wasim

2018-01-01

A lightning talk of my personal experiences in programming, from childhood with languages including Game Maker and DarkBASIC, to now with Python and R. I highlight the underlying principle which, I argue, separates the R community from others.See the reference for further reading material along this line.

Using Python to Construct a Scalable Parallel Nonlinear Wave Solver

KAUST Repository

Mandli, Kyle

2011-01-01

Computational scientists seek to provide efficient, easy-to-use tools and frameworks that enable application scientists within a specific discipline to build and/or apply numerical models with up-to-date computing technologies that can be executed on all available computing systems. Although many tools could be useful for groups beyond a specific application, it is often difficult and time consuming to combine existing software, or to adapt it for a more general purpose. Python enables a high-level approach where a general framework can be supplemented with tools written for different fields and in different languages. This is particularly important when a large number of tools are necessary, as is the case for high performance scientific codes. This motivated our development of PetClaw, a scalable distributed-memory solver for time-dependent nonlinear wave propagation, as a case-study for how Python can be used as a highlevel framework leveraging a multitude of codes, efficient both in the reuse of code and programmer productivity. We present scaling results for computations on up to four racks of Shaheen, an IBM BlueGene/P supercomputer at King Abdullah University of Science and Technology. One particularly important issue that PetClaw has faced is the overhead associated with dynamic loading leading to catastrophic scaling. We use the walla library to solve the issue which does so by supplanting high-cost filesystem calls with MPI operations at a low enough level that developers may avoid any changes to their codes.

Quantum Computers and Quantum Computer Languages: Quantum Assembly Language and Quantum C Language

OpenAIRE

Blaha, Stephen

2002-01-01

We show a representation of Quantum Computers defines Quantum Turing Machines with associated Quantum Grammars. We then create examples of Quantum Grammars. Lastly we develop an algebraic approach to high level Quantum Languages using Quantum Assembly language and Quantum C language as examples.

Python in the NERSC Exascale Science Applications Program for Data

Energy Technology Data Exchange (ETDEWEB)

Ronaghi, Zahra; Thomas, Rollin; Deslippe, Jack; Bailey, Stephen; Gursoy, Doga; Kisner, Theodore; Keskitalo, Reijo; Borrill, Julian

2017-11-12

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

High-level language computer architecture

CERN Document Server

Chu, Yaohan

1975-01-01

High-Level Language Computer Architecture offers a tutorial on high-level language computer architecture, including von Neumann architecture and syntax-oriented architecture as well as direct and indirect execution architecture. Design concepts of Japanese-language data processing systems are discussed, along with the architecture of stack machines and the SYMBOL computer system. The conceptual design of a direct high-level language processor is also described.Comprised of seven chapters, this book first presents a classification of high-level language computer architecture according to the pr

Scripting MODFLOW model development using Python and FloPy

Science.gov (United States)

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

2016-01-01

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

Python for data analysis data wrangling with Pandas, NumPy, and IPython

CERN Document Server

McKinney, Wes

2017-01-01

Get complete instructions for manipulating, processing, cleaning, and crunching datasets in Python. Updated for Python 3.6, the second edition of this hands-on guide is packed with practical case studies that show you how to solve a broad set of data analysis problems effectively. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. It’s ideal for analysts new to Python and for Python programmers new to data science and scientific computing. Data files and related material are available on GitHub. Use the IPython shell and Jupyter notebook for exploratory computing Learn basic and advanced features in NumPy (Numerical Python) Get started with data analysis tools in the pandas library Use flexible tools to load, clean, transform, merge, and reshape data Create informative visualizations with matplotlib ...

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

Science.gov (United States)

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

2018-04-01

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

Numeric computation and statistical data analysis on the Java platform

CERN Document Server

Chekanov, Sergei V

2016-01-01

Numerical computation, knowledge discovery and statistical data analysis integrated with powerful 2D and 3D graphics for visualization are the key topics of this book. The Python code examples powered by the Java platform can easily be transformed to other programming languages, such as Java, Groovy, Ruby and BeanShell. This book equips the reader with a computational platform which, unlike other statistical programs, is not limited by a single programming language. The author focuses on practical programming aspects and covers a broad range of topics, from basic introduction to the Python language on the Java platform (Jython), to descriptive statistics, symbolic calculations, neural networks, non-linear regression analysis and many other data-mining topics. He discusses how to find regularities in real-world data, how to classify data, and how to process data for knowledge discoveries. The code snippets are so short that they easily fit into single pages. Numeric Computation and Statistical Data Analysis ...

pypk - A Python extension module to handle chemical kinetics in plasma physics modeling

Directory of Open Access Journals (Sweden)

2008-06-01

Full Text Available PLASMAKIN is a package to handle physical and chemical data used in plasma physics modeling and to compute gas-phase and gas-surface kinetics data: particle production and loss rates, photon emission spectra and energy exchange rates. A large number of species properties and reaction types are supported, namely: gas or electron temperature dependent collision rate coefficients, vibrational and cascade levels, evaluation of branching ratios, superelastic and other reverse processes, three-body collisions, radiation imprisonment and photoelectric emission. Support of non-standard rate coefficient functions can be handled by a user-supplied shared library.

The main block of the PLASMAKIN package is a Fortran module that can be included in an user's program or compiled as a shared library, libpk. pypk is a new addition to the package and provides access to libpk from Python programs. It is build on top of the ctypes foreign function library module and is prepared to work with several Fortran compilers. However pypk is more than a wrapper and provides its own classes and functions taking advantage of Python language characteristics. Integration with Python tools allows substantial productivity gains on program development and insight on plasma physics problems.

Computer Assisted Language Learning. Routledge Studies in Computer Assisted Language Learning

Science.gov (United States)

Pennington, Martha

2011-01-01

Computer-assisted language learning (CALL) is an approach to language teaching and learning in which computer technology is used as an aid to the presentation, reinforcement and assessment of material to be learned, usually including a substantial interactive element. This books provides an up-to date and comprehensive overview of…

CLIMLAB: a Python-based software toolkit for interactive, process-oriented climate modeling

Science.gov (United States)

Rose, B. E. J.

2015-12-01

Global climate is a complex emergent property of the rich interactions between simpler components of the climate system. We build scientific understanding of this system by breaking it down into component process models (e.g. radiation, large-scale dynamics, boundary layer turbulence), understanding each components, and putting them back together. Hands-on experience and freedom to tinker with climate models (whether simple or complex) is invaluable for building physical understanding. CLIMLAB is an open-ended software engine for interactive, process-oriented climate modeling. With CLIMLAB you can interactively mix and match model components, or combine simpler process models together into a more comprehensive model. It was created primarily to support classroom activities, using hands-on modeling to teach fundamentals of climate science at both undergraduate and graduate levels. CLIMLAB is written in Python and ties in with the rich ecosystem of open-source scientific Python tools for numerics and graphics. The IPython notebook format provides an elegant medium for distributing interactive example code. I will give an overview of the current capabilities of CLIMLAB, the curriculum we have developed thus far, and plans for the future. Using CLIMLAB requires some basic Python coding skills. We consider this an educational asset, as we are targeting upper-level undergraduates and Python is an increasingly important language in STEM fields. However CLIMLAB is well suited to be deployed as a computational back-end for a graphical gaming environment based on earth-system modeling.

Developers@CERN Forum | Python at CERN | 30 – 31 May

CERN Multimedia

2016-01-01

The Developers@CERN Forum is an event by developers for developers aimed at promoting knowledge- and experience-sharing (see here). The second forum will take place in the IT auditorium in the afternoons of 30 and 31 May.   With the topic “Python at CERN”, it will consist of a series of talks regarding the Python language, frameworks and tools used at CERN. Are you a Python guru or would you like to learn? Come and share your Python experiences with other developers! Submissions for presentations and workshops are open until 9 May at http://cern.ch/dev-forum. If you would like to stay informed about this or future events, please subscribe to the announcement e-group (just a few e-mails per year) here. 

DeepPy: Pythonic deep learning

DEFF Research Database (Denmark)

Larsen, Anders Boesen Lindbo

This technical report introduces DeepPy – a deep learning framework built on top of NumPy with GPU acceleration. DeepPy bridges the gap between highperformance neural networks and the ease of development from Python/NumPy. Users with a background in scientific computing in Python will quickly...... be able to understand and change the DeepPy codebase as it is mainly implemented using high-level NumPy primitives. Moreover, DeepPy supports complex network architectures by letting the user compose mathematical expressions as directed graphs. The latest version is available at http...

Status of parallel Python-based implementation of UEDGE

Science.gov (United States)

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.

Transliterating non-ASCII characters with Python

Directory of Open Access Journals (Sweden)

Seth Bernstein

2013-10-01

Full Text Available This lesson shows how to use Python to transliterate automatically a list of words from a language with a non-Latin alphabet to a standardized format using the American Standard Code for Information Interchange (ASCII characters. It builds on readers’ understanding of Python from the lessons “Viewing HTML Files,” “Working with Web Pages,” “From HTML to List of Words (part 1” and “Intro to Beautiful Soup.” At the end of the lesson, we will use the transliteration dictionary to convert the names from a database of the Russian organization Memorial from Cyrillic into Latin characters. Although the example uses Cyrillic characters, the technique can be reproduced with other alphabets using Unicode.

Ascaridosis in captive reticulated python( Python reticulatus ) | Taiwo ...

African Journals Online (AJOL)

Two captive reticulated pythons, Python reticulatus, in the Zoological Gardens, University of Ibadan, Ibadan, Nigeria died and were submitted for necropsy at the Diagnostic Laboratory of the Department of Veterinary Pathology, University of Ibadan. Both pythons had been infected with Ascaridia galli for a long period of time ...

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

Science.gov (United States)

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

2011-01-01

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

Building and documenting workflows with python-based snakemake

NARCIS (Netherlands)

J. Köster (Johannes); S. Rahmann (Sven)

2012-01-01

textabstractSnakemake is a novel workflow engine with a simple Python-derived workflow definition language and an optimizing execution environment. It is the first system that supports multiple named wildcards (or variables) in input and output filenames of each rule definition. It also allows to

Teaching CS1 with Python GUI Game Programming

Science.gov (United States)

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.

Pro Python

CERN Document Server

Alchin, Marty

2010-01-01

You've learned the basics of Python, but how do you take your skills to the next stage? Even if you know enough to be productive, there are a number of features that can take you to the next level in Python. Pro Python explores concepts and features normally left to experimentation, allowing you to be even more productive and creative. In addition to pure code concerns, Pro Python will develop your programming techniques and approaches, which will help make you a better Python programmer. Not only will this book help your code, it will also help you understand and interact with the many establ

Computability, complexity, and languages fundamentals of theoretical computer science

CERN Document Server

Davis, Martin D; Rheinboldt, Werner

1983-01-01

Computability, Complexity, and Languages: Fundamentals of Theoretical Computer Science provides an introduction to the various aspects of theoretical computer science. Theoretical computer science is the mathematical study of models of computation. This text is composed of five parts encompassing 17 chapters, and begins with an introduction to the use of proofs in mathematics and the development of computability theory in the context of an extremely simple abstract programming language. The succeeding parts demonstrate the performance of abstract programming language using a macro expa

Language evolution and human-computer interaction

Science.gov (United States)

Grudin, Jonathan; Norman, Donald A.

1991-01-01

Many of the issues that confront designers of interactive computer systems also appear in natural language evolution. Natural languages and human-computer interfaces share as their primary mission the support of extended 'dialogues' between responsive entities. Because in each case one participant is a human being, some of the pressures operating on natural languages, causing them to evolve in order to better support such dialogue, also operate on human-computer 'languages' or interfaces. This does not necessarily push interfaces in the direction of natural language - since one entity in this dialogue is not a human, this is not to be expected. Nonetheless, by discerning where the pressures that guide natural language evolution also appear in human-computer interaction, we can contribute to the design of computer systems and obtain a new perspective on natural languages.

A Python extension to the ATLAS online software for the thin gap chamber trigger system

CERN Document Server

Maeno, Tadashi; Komatsu, Satoru; Nakayoshi, Kazuo; Yasu, Yoshiji

2004-01-01

A Python extension module for A Toroidal LHC Apparatus (ATLAS) Online Software has been developed for the Thin Gap Chamber (TGC) trigger system. Python is an interactive scripting language including built- in high-level libraries, and provides an easy way to build Web applications. These features are not included in the Online Software, and are important in developing test software for the TGC trigger system. The Python extension module is designed and implemented using a C++ library, "Boost.Python." We have developed a Web application using the extension module and Zope (a Python-based Web application server), which allows one to monitor the TGC trigger system from anywhere in the world. The functionalities of the Python extension module and its application for the TGC trigger system are presented. 7 Refs.

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

Directory of Open Access Journals (Sweden)

Bastian Venthur

2010-12-01

Full Text Available This paper introduces Pyff, the Pythonic Feedback Framework for feedbackapplications and stimulus presentation. Pyff provides a platform independentframework that allows users to develop and run neuroscientific experiments inthe programming language Python. Existing solutions have mostly beenimplemented in C++, which makes for a rather tedious programming task fornon-computer-scientists, or in Matlab, which is not well suited for moreadvanced visual or auditory applications. Pyff was designed to makeexperimental paradigms (i.e. feedback and stimulus applications easilyprogrammable. It includes base classes for various types of common feedbacksand stimuli as well as useful libraries for external hardware such aseyetrackers. Pyff is also equipped with a steadily growing set of ready-to-usefeedbacks and stimuli. It can be used as a standalone application, for instanceproviding stimulus presentation in psychophysics experiments, or within aclosed loop such as in biofeedback or brain-computer interfacing experiments.Pyff communicates with other systems via a standardized communication protocoland is therefore suitable to be used with any system that may be adapted tosend its data in the specified format. Having such a general, open sourceframework will help foster a fruitful exchange of experimental paradigmsbetween research groups. In particular, it will decrease the need ofreprogramming standard paradigms, ease the reproducibility of publishedresults, and naturally entail some standardization of stimulus presentation.

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

Science.gov (United States)

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

2010-12-01

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

Quantum Computers and Quantum Computer Languages: Quantum Assembly Language and Quantum C

OpenAIRE

Blaha, Stephen

2002-01-01

We show a representation of Quantum Computers defines Quantum Turing Machines with associated Quantum Grammars. We then create examples of Quantum Grammars. Lastly we develop an algebraic approach to high level Quantum Languages using Quantum Assembly language and Quantum C language as examples.

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

Science.gov (United States)

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…

Trends in programming languages for neuroscience simulations.

Science.gov (United States)

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

2009-01-01

Neuroscience simulators allow scientists to express models in terms of biological concepts, without having to concern themselves with low-level computational details of their implementation. The expressiveness, power and ease-of-use of the simulator interface is critical in efficiently and accurately translating ideas into a working simulation. We review long-term trends in the development of programmable simulator interfaces, and examine the benefits of moving from proprietary, domain-specific languages to modern dynamic general-purpose languages, in particular Python, which provide neuroscientists with an interactive and expressive simulation development environment and easy access to state-of-the-art general-purpose tools for scientific computing.

Trends in Programming Languages for Neuroscience Simulations

Science.gov (United States)

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

2009-01-01

Neuroscience simulators allow scientists to express models in terms of biological concepts, without having to concern themselves with low-level computational details of their implementation. The expressiveness, power and ease-of-use of the simulator interface is critical in efficiently and accurately translating ideas into a working simulation. We review long-term trends in the development of programmable simulator interfaces, and examine the benefits of moving from proprietary, domain-specific languages to modern dynamic general-purpose languages, in particular Python, which provide neuroscientists with an interactive and expressive simulation development environment and easy access to state-of-the-art general-purpose tools for scientific computing. PMID:20198154

Trends in programming languages for neuroscience simulations

Directory of Open Access Journals (Sweden)

Andrew P Davison

2009-12-01

Full Text Available Neuroscience simulators allow scientists to express models in terms of biological concepts, without having to concern themselves with low-level computational details of their implementation. The expressiveness, power and ease-of-use of the simulator interface is critical in efficiently and accurately translating ideas into a working simulation. We review long-term trends in the development of programmable simulator interfaces, and examine the benefits of moving from proprietary, domain-specific languages to modern dynamic general-purpose languages, in particular Python, which provide neuroscientists with an interactive and expressive simulation development environment and easy access to state-of-the-art general-purpose tools for scientific computing.

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

Science.gov (United States)

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

2012-05-15

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

Contracting for Computer Software in Standardized Computer Languages

Science.gov (United States)

Brannigan, Vincent M.; Dayhoff, Ruth E.

1982-01-01

The interaction between standardized computer languages and contracts for programs which use these languages is important to the buyer or seller of software. The rationale for standardization, the problems in standardizing computer languages, and the difficulties of determining whether the product conforms to the standard are issues which must be understood. The contract law processes of delivery, acceptance testing, acceptance, rejection, and revocation of acceptance are applicable to the contracting process for standard language software. Appropriate contract language is suggested for requiring strict compliance with a standard, and an overview of remedies is given for failure to comply.

Analysis of computer programming languages

International Nuclear Information System (INIS)

Risset, Claude Alain

1967-01-01

This research thesis aims at trying to identify some methods of syntax analysis which can be used for computer programming languages while putting aside computer devices which influence the choice of the programming language and methods of analysis and compilation. In a first part, the author proposes attempts of formalization of Chomsky grammar languages. In a second part, he studies analytical grammars, and then studies a compiler or analytic grammar for the Fortran language

IPython: components for interactive and parallel computing across disciplines. (Invited)

Science.gov (United States)

Perez, F.; Bussonnier, M.; Frederic, J. D.; Froehle, B. M.; Granger, B. E.; Ivanov, P.; Kluyver, T.; Patterson, E.; Ragan-Kelley, B.; Sailer, Z.

2013-12-01

Scientific computing is an inherently exploratory activity that requires constantly cycling between code, data and results, each time adjusting the computations as new insights and questions arise. To support such a workflow, good interactive environments are critical. The IPython project (http://ipython.org) provides a rich architecture for interactive computing with: 1. Terminal-based and graphical interactive consoles. 2. A web-based Notebook system with support for code, text, mathematical expressions, inline plots and other rich media. 3. Easy to use, high performance tools for parallel computing. Despite its roots in Python, the IPython architecture is designed in a language-agnostic way to facilitate interactive computing in any language. This allows users to mix Python with Julia, R, Octave, Ruby, Perl, Bash and more, as well as to develop native clients in other languages that reuse the IPython clients. In this talk, I will show how IPython supports all stages in the lifecycle of a scientific idea: 1. Individual exploration. 2. Collaborative development. 3. Production runs with parallel resources. 4. Publication. 5. Education. In particular, the IPython Notebook provides an environment for "literate computing" with a tight integration of narrative and computation (including parallel computing). These Notebooks are stored in a JSON-based document format that provides an "executable paper": notebooks can be version controlled, exported to HTML or PDF for publication, and used for teaching.

graphkernels: R and Python packages for graph comparison.

Science.gov (United States)

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

2018-02-01

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

Contracting for Computer Software in Standardized Computer Languages

OpenAIRE

Brannigan, Vincent M.; Dayhoff, Ruth E.

1982-01-01

The interaction between standardized computer languages and contracts for programs which use these languages is important to the buyer or seller of software. The rationale for standardization, the problems in standardizing computer languages, and the difficulties of determining whether the product conforms to the standard are issues which must be understood. The contract law processes of delivery, acceptance testing, acceptance, rejection, and revocation of acceptance are applicable to the co...

Internationalization and Localization in Python

CERN Multimedia

CERN. Geneva

2016-01-01

Internationalization and Localization are increasingly important in an interconnected world. Regardless of that, developers tend to treat them as secondary issues, very often choosing to address them properly when it's already too late. The fact that most programming language standard libraries choose to ignore the matter doesn't help either. In this talk we will present some useful Python libraries and tools that can help you internationalize and localize your code with minimal effort. We will also describe some common pitfalls and problems.

Pythran: enabling static optimization of scientific Python programs

Science.gov (United States)

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.

Exploring HPCS languages in scientific computing

International Nuclear Information System (INIS)

Barrett, R F; Alam, S R; Almeida, V F d; Bernholdt, D E; Elwasif, W R; Kuehn, J A; Poole, S W; Shet, A G

2008-01-01

As computers scale up dramatically to tens and hundreds of thousands of cores, develop deeper computational and memory hierarchies, and increased heterogeneity, developers of scientific software are increasingly challenged to express complex parallel simulations effectively and efficiently. In this paper, we explore the three languages developed under the DARPA High-Productivity Computing Systems (HPCS) program to help address these concerns: Chapel, Fortress, and X10. These languages provide a variety of features not found in currently popular HPC programming environments and make it easier to express powerful computational constructs, leading to new ways of thinking about parallel programming. Though the languages and their implementations are not yet mature enough for a comprehensive evaluation, we discuss some of the important features, and provide examples of how they can be used in scientific computing. We believe that these characteristics will be important to the future of high-performance scientific computing, whether the ultimate language of choice is one of the HPCS languages or something else

Exploring HPCS languages in scientific computing

Science.gov (United States)

Barrett, R. F.; Alam, S. R.; Almeida, V. F. d.; Bernholdt, D. E.; Elwasif, W. R.; Kuehn, J. A.; Poole, S. W.; Shet, A. G.

2008-07-01

As computers scale up dramatically to tens and hundreds of thousands of cores, develop deeper computational and memory hierarchies, and increased heterogeneity, developers of scientific software are increasingly challenged to express complex parallel simulations effectively and efficiently. In this paper, we explore the three languages developed under the DARPA High-Productivity Computing Systems (HPCS) program to help address these concerns: Chapel, Fortress, and X10. These languages provide a variety of features not found in currently popular HPC programming environments and make it easier to express powerful computational constructs, leading to new ways of thinking about parallel programming. Though the languages and their implementations are not yet mature enough for a comprehensive evaluation, we discuss some of the important features, and provide examples of how they can be used in scientific computing. We believe that these characteristics will be important to the future of high-performance scientific computing, whether the ultimate language of choice is one of the HPCS languages or something else.

Text Mining in Python through the HTRC Feature Reader

Directory of Open Access Journals (Sweden)

Peter Organisciak

2016-11-01

Full Text Available We introduce a toolkit for working with the 13.6 million volume Extracted Features Dataset from the HathiTrust Research Center. You will learn how to peer at the words and trends of any book in the collection, while developing broadly useful Python data analysis skills. The HathiTrust holds nearly 15 million digitized volumes from libraries around the world. In addition to their individual value, these works in aggregate are extremely valuable for historians. Spanning many centuries and genres, they offer a way to learn about large-scale trends in history and culture, as well as evidence for changes in language or even the structure of the book. To simplify access to this collection the HathiTrust Research Center (HTRC has released the Extracted Features dataset (Capitanu et al. 2015: a dataset that provides quantitative information describing every page of every volume in the collection. In this lesson, we introduce the HTRC Feature Reader, a library for working with the HTRC Extracted Features dataset using the Python programming language. The HTRC Feature Reader is structured to support work using popular data science libraries, particularly Pandas. Pandas provides simple structures for holding data and powerful ways to interact with it. The HTRC Feature Reader uses these data structures, so learning how to use it will also cover general data analysis skills in Python.

Fixing the Sorting Algorithm for Android, Java and Python

NARCIS (Netherlands)

C.P.T. de Gouw (Stijn); F.S. de Boer (Frank)

2015-01-01

htmlabstractTim Peters developed the Timsort hybrid sorting algorithm in 2002. TimSort was first developed for Python, a popular programming language, but later ported to Java (where it appears as java.util.Collections.sort and java.util.Arrays.sort). TimSort is today used as the default sorting

Computer Language For Optimization Of Design

Science.gov (United States)

Scotti, Stephen J.; Lucas, Stephen H.

1991-01-01

SOL is computer language geared to solution of design problems. Includes mathematical modeling and logical capabilities of computer language like FORTRAN; also includes additional power of nonlinear mathematical programming methods at language level. SOL compiler takes SOL-language statements and generates equivalent FORTRAN code and system calls. Provides syntactic and semantic checking for recovery from errors and provides detailed reports containing cross-references to show where each variable used. Implemented on VAX/VMS computer systems. Requires VAX FORTRAN compiler to produce executable program.

Teaching natural language to computers

OpenAIRE

Corneli, Joseph; Corneli, Miriam

2016-01-01

"Natural Language," whether spoken and attended to by humans, or processed and generated by computers, requires networked structures that reflect creative processes in semantic, syntactic, phonetic, linguistic, social, emotional, and cultural modules. Being able to produce novel and useful behavior following repeated practice gets to the root of both artificial intelligence and human language. This paper investigates the modalities involved in language-like applications that computers -- and ...

Scikit-learn: Machine Learning in Python

OpenAIRE

Pedregosa, Fabian; Varoquaux, Gaël; Gramfort, Alexandre; Michel, Vincent; Thirion, Bertrand; Grisel, Olivier; Blondel, Mathieu; Prettenhofer, Peter; Weiss, Ron; Dubourg, Vincent; Vanderplas, Jake; Passos, Alexandre; Cournapeau, David; Brucher, Matthieu; Perrot, Matthieu

2011-01-01

International audience; Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems. This package focuses on bringing machine learning to non-specialists using a general-purpose high-level language. Emphasis is put on ease of use, performance, documentation, and API consistency. It has minimal dependencies and is distributed under the simplified BSD license, encouraging its use in both academic ...

Scikit-learn: Machine Learning in Python

OpenAIRE

Pedregosa, Fabian; Varoquaux, Gaël; Gramfort, Alexandre; Michel, Vincent; Thirion, Bertrand; Grisel, Olivier; Blondel, Mathieu; Louppe, Gilles; Prettenhofer, Peter; Weiss, Ron; Dubourg, Vincent; Vanderplas, Jake; Passos, Alexandre; Cournapeau, David; Brucher, Matthieu

2012-01-01

Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems. This package focuses on bringing machine learning to non-specialists using a general-purpose high-level language. Emphasis is put on ease of use, performance, documentation, and API consistency. It has minimal dependencies and is distributed under the simplified BSD license, encouraging its use in both academic and commercial settings....

pyGeno: A Python package for precision medicine and proteogenomics.

Science.gov (United States)

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.

AutoWIG: automatic generation of python bindings for C++ libraries

Directory of Open Access Journals (Sweden)

Pierre Fernique

2018-04-01

Full Text Available Most of Python and R scientific packages incorporate compiled scientific libraries to speed up the code and reuse legacy libraries. While several semi-automatic solutions exist to wrap these compiled libraries, the process of wrapping a large library is cumbersome and time consuming. In this paper, we introduce AutoWIG, a Python package that wraps automatically compiled libraries into high-level languages using LLVM/Clang technologies and the Mako templating engine. Our approach is automatic, extensible, and applies to complex C++ libraries, composed of thousands of classes or incorporating modern meta-programming constructs.

Computers and languages theory and practice

CERN Document Server

Nijholt, A

1988-01-01

A global introduction to language technology and the areas of computer science where language technology plays a role. Surveyed in this volume are issues related to the parsing problem in the fields of natural languages, programming languages, and formal languages.Throughout the book attention is paid to the social forces which influenced the development of the various topics. Also illustrated are the development of the theory of language analysis, its role in compiler construction, and its role in computer applications with a natural language interface between men and machine. Parts of the ma

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

Science.gov (United States)

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

2010-01-01

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

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Pascal-SC a computer language for scientific computation

CERN Document Server

Bohlender, Gerd; von Gudenberg, Jürgen Wolff; Rheinboldt, Werner; Siewiorek, Daniel

1987-01-01

Perspectives in Computing, Vol. 17: Pascal-SC: A Computer Language for Scientific Computation focuses on the application of Pascal-SC, a programming language developed as an extension of standard Pascal, in scientific computation. The publication first elaborates on the introduction to Pascal-SC, a review of standard Pascal, and real floating-point arithmetic. Discussions focus on optimal scalar product, standard functions, real expressions, program structure, simple extensions, real floating-point arithmetic, vector and matrix arithmetic, and dynamic arrays. The text then examines functions a

[Lecture Games] Python programming game

OpenAIRE

Johnsen, Andreas Lyngstad; Ushakov, Georgy

2011-01-01

Pythia is a programming game that allows the player to change pieces of theirenvironment through use of the programming language Python. The idea is that thegame could be used as a part of teaching simple programming to first year universitystudents. The game should be fun enough for the students to keep playing, teachenough for it to earn a place as a teaching tool, and it should be usable by allstudents. It should also be possible for a teacher to create their own content for theg...

Endocardial fibrosarcoma in a reticulated python (Python reticularis).

Science.gov (United States)

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

2010-11-01

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

Python for signal processing featuring IPython notebooks

CERN Document Server

Unpingco, José

2013-01-01

This book covers the fundamental concepts in signal processing illustrated with Python code and made available via IPython Notebooks, which are live, interactive, browser-based documents that allow one to change parameters, redraw plots, and tinker with the ideas presented in the text. Everything in the text is computable in this format and thereby invites readers to ""experiment and learn"" as they read. The book focuses on the core, fundamental principles of signal processing. The code corresponding to this book uses the core functionality of the scientific Python toolchain that should remai

ACPYPE - AnteChamber PYthon Parser interfacE.

Science.gov (United States)

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.

The spectacle of the ball python (Python regius)

DEFF Research Database (Denmark)

Da Silva, Mari-Ann Otkjær; Heegaard, Steffen; Wang, Tobias

2014-01-01

A detailed morphological description of the spectacle of the ball python (Python regius) is provided. The eyes of 21 snakes were examined by light microscopy and/or transmission electron microscopy. Additionally, eyes of nine live snakes were examined using optical coherence tomography (OCT...

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

Science.gov (United States)

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

2011-03-01

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

Computational physics

CERN Document Server

Newman, Mark

2013-01-01

A complete introduction to the field of computational physics, with examples and exercises in the Python programming language. Computers play a central role in virtually every major physics discovery today, from astrophysics and particle physics to biophysics and condensed matter. This book explains the fundamentals of computational physics and describes in simple terms the techniques that every physicist should know, such as finite difference methods, numerical quadrature, and the fast Fourier transform. The book offers a complete introduction to the topic at the undergraduate level, and is also suitable for the advanced student or researcher who wants to learn the foundational elements of this important field.

SMMP v. 3.0—Simulating proteins and protein interactions in Python and Fortran

Science.gov (United States)

Meinke, Jan H.; Mohanty, Sandipan; Eisenmenger, Frank; Hansmann, Ulrich H. E.

2008-03-01

We describe a revised and updated version of the program package SMMP. SMMP is an open-source FORTRAN package for molecular simulation of proteins within the standard geometry model. It is designed as a simple and inexpensive tool for researchers and students to become familiar with protein simulation techniques. SMMP 3.0 sports a revised API increasing its flexibility, an implementation of the Lund force field, multi-molecule simulations, a parallel implementation of the energy function, Python bindings, and more. Program summaryTitle of program:SMMP Catalogue identifier:ADOJ_v3_0 Program summary URL:http://cpc.cs.qub.ac.uk/summaries/ADOJ_v3_0.html Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Licensing provisions:Standard CPC licence, http://cpc.cs.qub.ac.uk/licence/licence.html Programming language used:FORTRAN, Python No. of lines in distributed program, including test data, etc.:52 105 No. of bytes in distributed program, including test data, etc.:599 150 Distribution format:tar.gz Computer:Platform independent Operating system:OS independent RAM:2 Mbytes Classification:3 Does the new version supersede the previous version?:Yes Nature of problem:Molecular mechanics computations and Monte Carlo simulation of proteins. Solution method:Utilizes ECEPP2/3, FLEX, and Lund potentials. Includes Monte Carlo simulation algorithms for canonical, as well as for generalized ensembles. Reasons for new version:API changes and increased functionality. Summary of revisions:Added Lund potential; parameters used in subroutines are now passed as arguments; multi-molecule simulations; parallelized energy calculation for ECEPP; Python bindings. Restrictions:The consumed CPU time increases with the size of protein molecule. Running time:Depends on the size of the simulated molecule.

Rapid web development using AJAX and Python

Energy Technology Data Exchange (ETDEWEB)

Dolgert, A; Gibbons, L; Kuznetsov, V [Cornell University, Ithaca, NY 14853 (United States)], E-mail: vkuznet@gmail.com

2008-07-15

We discuss the rapid development of a large scale data discovery service for the CMS experiment using modern AJAX techniques and the Python language. To implement a flexible interface capable of accommodating several different versions of the DBS database, we used a 'stack' approach. Asynchronous JavaScript and XML (AJAX) together with an SQL abstraction layer, template engine, code generation tool and dynamic queries provide powerful tools for constructing interactive interfaces to large amounts of data. We show how the use of these tools, with rapid development in a modern scripting language, improved the scalability and usability of the the search interface for different user communities.

Rapid web development using AJAX and Python

International Nuclear Information System (INIS)

Dolgert, A; Gibbons, L; Kuznetsov, V

2008-01-01

We discuss the rapid development of a large scale data discovery service for the CMS experiment using modern AJAX techniques and the Python language. To implement a flexible interface capable of accommodating several different versions of the DBS database, we used a 'stack' approach. Asynchronous JavaScript and XML (AJAX) together with an SQL abstraction layer, template engine, code generation tool and dynamic queries provide powerful tools for constructing interactive interfaces to large amounts of data. We show how the use of these tools, with rapid development in a modern scripting language, improved the scalability and usability of the the search interface for different user communities

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

Science.gov (United States)

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

2009-01-01

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

Proceedings of the 7th Python in Science conference

OpenAIRE

Varoquaux , Gaël; Vaught , Travis; Millman , Jarrod

2008-01-01

International audience; The SciPy conference provides a unique opportunity to learn and affect what is happening in the realm of scientific computing with Python. Attendees have the opportunity to review the available tools and how they apply to specific problems. By providing a forum for developers to share their Python expertise with the wider commercial, academic, and research communities, this conference fosters collaboration and facilitates the sharing of software components, techniques ...

Proceedings of the 8th Python in Science conference

OpenAIRE

Varoquaux , Gaël; Van Der Walt , Stefan; Millman , Jarrod

2009-01-01

International audience; The SciPy conference provides a unique opportunity to learn and affect what is happening in the realm of scientific computing with Python. Attendees have the opportunity to review the available tools and how they apply to specific problems. By providing a forum for developers to share their Python expertise with the wider commercial, academic, and research communities, this conference fosters collaboration and facilitates the sharing of software components, techniques ...

Optimizing Python-based ROOT I/O with PyPy's Tracing JIT

CERN Multimedia

CERN. Geneva

2012-01-01

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 automatic selective reading, judicious caching, and buffer tuning.

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

Science.gov (United States)

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

2016-09-01

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

Adventures in Python

CERN Document Server

Richardson, Craig

2015-01-01

The complete beginner's guide to Python, for young people whowant to start today Adventures in Python is designed for 11-to 15-year oldswho want to teach themselves Python programming, but don't knowwhere to start. Even if you have no programming experience at all,this easy to follow format and clear, simple instruction will getyou up and running quickly. The book walks you through nineprojects that teach you the fundamentals of programming in general,and Python in particular, gradually building your skills until youhave the confidence and ability to tackle your own projects. Videoclips accom

Programming biological models in Python using PySB.

Science.gov (United States)

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.

Approaching the largest ‘API’: extracting information from the Internet with Python

Directory of Open Access Journals (Sweden)

Jonathan E. Germann

2018-02-01

Full Text Available This article explores the need for libraries to algorithmically access and manipulate the world’s largest API: the Internet. The billions of pages on the ‘Internet API’ (HTTP, HTML, CSS, XPath, DOM, etc. are easily accessible and manipulable. Libraries can assist in creating meaning through the datafication of information on the world wide web. Because most information is created for human consumption, some programming is required for automated extraction. Python is an easy-to-learn programming language with extensive packages and community support for web page automation. Four packages (Urllib, Selenium, BeautifulSoup, Scrapy in Python can automate almost any web page for all sized projects. An example warrant data project is explained to illustrate how well Python packages can manipulate web pages to create meaning through assembling custom datasets.

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

Directory of Open Access Journals (Sweden)

K. Hosseini

2017-10-01

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

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

Science.gov (United States)

Hosseini, Kasra; Sigloch, Karin

2017-10-01

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

Computer Language Settings and Canadian Spellings

Science.gov (United States)

Shuttleworth, Roger

2011-01-01

The language settings used on personal computers interact with the spell-checker in Microsoft Word, which directly affects the flagging of spellings that are deemed incorrect. This study examined the language settings of personal computers owned by a group of Canadian university students. Of 21 computers examined, only eight had their Windows…

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

Science.gov (United States)

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

Python profiling 101

CERN Multimedia

CERN. Geneva

2014-01-01

Python code is much easier to write than C, yet much less efficient. It's often assumed that Python is not performance-oriented and therefore making effort to optimize it doesn't pay off. While in many cases it's true, at a certain moment of a development, especially right before reaching production-ready state, it might turn out that a Python code runs slowly and one needs to find a culprit. In this talk I'll not tell how to make your program faster. Instead, I'll show different techniques to look for the bottlenecks in the code. The presentation will be built around a live demo using real-life Python code.

ACPYPE - AnteChamber PYthon Parser interfacE

Directory of Open Access Journals (Sweden)

Sousa da Silva Alan W

2012-07-01

Full Text Available Abstract Background 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. Findings 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. Conclusions 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.

Learning Python network programming

CERN Document Server

Sarker, M O Faruque

2015-01-01

If you're a Python developer or a system administrator with Python experience and you're looking to take your first steps in network programming, then this book is for you. Basic knowledge of Python is assumed.

An Overview of Computer-Based Natural Language Processing.

Science.gov (United States)

Gevarter, William B.

Computer-based Natural Language Processing (NLP) is the key to enabling humans and their computer-based creations to interact with machines using natural languages (English, Japanese, German, etc.) rather than formal computer languages. NLP is a major research area in the fields of artificial intelligence and computational linguistics. Commercial…

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

Science.gov (United States)

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.

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

Directory of Open Access Journals (Sweden)

Nicolas eRey-Villamizar

2014-04-01

Full Text Available In this article, we describe 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 task, these modules must be combined into scripts using Python. As a concrete example, we consider the problem of analyzing 3-D multi-spectral brain tissue images 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, 6,000$times$10,000$times$500 voxels with 16 bits/voxel, implying image sizes exceeding 250GB. 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 analytics 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 consisting. Our Python script enables efficient data storage and movement between compute and storage servers, logging all processing steps, and performs full multi-threaded execution of all codes, including open and closed-source third party libraries.

Computers and Languages: Theory and Practice

NARCIS (Netherlands)

Nijholt, Antinus

A global introduction to language technology and the areas of computer science where language technology plays a role. Surveyed in this volume are issueas related to the parsing problem in the fields of natural languages, programming languages, and formal languages. Throughout the book attention is

Computer Programming Languages for Health Care

Science.gov (United States)

O'Neill, Joseph T.

1979-01-01

This paper advocates the use of standard high level programming languages for medical computing. It recommends that U.S. Government agencies having health care missions implement coordinated policies that encourage the use of existing standard languages and the development of new ones, thereby enabling them and the medical computing community at large to share state-of-the-art application programs. Examples are based on a model that characterizes language and language translator influence upon the specification, development, test, evaluation, and transfer of application programs.

Developers@CERN Forums: Python

CERN Multimedia

CERN. Geneva

2016-01-01

The Developers@CERN Forums second edition took place at the end of May on the topic of Python. How do developers at CERN interact with Python? Which cutting-edge projects are using Python? What were the highlights of this most recent forum?

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

Science.gov (United States)

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

“Computer Assisted Language Learning” (CALL

Directory of Open Access Journals (Sweden)

Nazlı Gündüz

2005-10-01

Full Text Available This article will provide an overview of computers; an overview of the history of CALL, itspros and cons, the internet, World Wide Web, Multimedia, and research related to the uses of computers in the language classroom. Also, it also aims to provide some background for the beginnerson using the Internet in language classes today. It discusses some of the common types of Internetactivities that are being used today, what the minimum requirements are for using the Internet forlanguage learning, and some easy activities you can adapt for your classes. Some special terminology related to computers will also be used in this paper. For example, computer assisted language learning(CALL refers to the sets of instructions which need to be loaded into the computer for it to be able to work in the language classroom. It should be borne in mind that CALL does not refer to the use of acomputer by a teacher to type out a worksheet or a class list or preparing his/her own teaching alone.Hardware refers to any computer equipment used, including the computer itself, the keyboard, screen (or the monitor, the disc-drive, and the printer. Software (computer programs refers to the sets of instructions which need to be loaded into the computer for it to be able to work.

Lua(Jit) for computing accelerator beam physics

CERN Multimedia

CERN. Geneva

2016-01-01

As mentioned in the 2nd developers meeting, I would like to open the debate with a special presentation on another language - Lua, and a tremendous technology - LuaJit. Lua is much less known at CERN, but it is very simple, much smaller than Python and its JIT is extremely performant. The language is a dynamic scripting language easy to learn and easy to embedded in applications. I will show how we use it in HPC for accelerator beam physics as a replacement for C, C++, Fortran and Python, with some benchmarks versus Python, PyPy4 and C/C++.

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

Science.gov (United States)

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

2010-09-01

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

Some issues of creation of belarusian language computer resources

OpenAIRE

Rubashko, N.; Nevmerjitskaia, G.

2003-01-01

The main reason for creation of computer resources of natural language is the necessity to bring into accord the ways of language normalization with the form of its existence - the computer form of language usage should correspond to the computer form of language standards fixation. This paper discusses various aspects of the creation of Belarusian language computer resources. It also briefly gives an overview of the objectives of the project involved.

Gala: A Python package for galactic dynamics

Science.gov (United States)

Price-Whelan, Adrian M.

2017-10-01

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

‘ShruthLaikh’: Employing Python to Develop Vocabulary Enhancing Application

Directory of Open Access Journals (Sweden)

2010-09-01

Full Text Available This paper presents how the power of Python, its various modules and Artificial Intelligence techniques can be integrated into a very useful and effective English spelling-correcting and vocabulary-enhancing application. The objective is to use the Python interface for various functionalities like text to speech, graphical user interface and sqlite3 database to integrate them into a single useful tool. The application is named as “ShruthLaikh”, which is a Hindi word for dictations. It has been demonstrated how this simple yet intelligent tool can help users to absorb word spellings in a very effective manner at the same time enhancing their retaining power. It also proves how Python as a programming language can be utilized effectively for the creation of powerful and user-friendly applications that can assist in more ways than one in revolutionizing the educational scene in nations across the world and the role that Python can play in imparting education in an innovative way.

Use of EPICS and Python technology for the development of a computational toolkit for high heat flux testing of plasma facing components

Energy Technology Data Exchange (ETDEWEB)

Sugandhi, Ritesh, E-mail: ritesh@ipr.res.in; Swamy, Rajamannar, E-mail: rajamannar@ipr.res.in; Khirwadkar, Samir, E-mail: sameer@ipr.res.in

2016-11-15

Highlights: • An integrated approach to software development for computational processing and experimental control. • Use of open source, cross platform, robust and advanced tools for computational code development. • Prediction of optimized process parameters for critical heat flux model. • Virtual experimentation for high heat flux testing of plasma facing components. - Abstract: The high heat flux testing and characterization of the divertor and first wall components are a challenging engineering problem of a tokamak. These components are subject to steady state and transient heat load of high magnitude. Therefore, the accurate prediction and control of the cooling parameters is crucial to prevent burnout. The prediction of the cooling parameters is based on the numerical solution of the critical heat flux (CHF) model. In a test facility for high heat flux testing of plasma facing components (PFC), the integration of computations and experimental control is an essential requirement. Experimental physics and industrial control system (EPICS) provides powerful tools for steering controls, data simulation, hardware interfacing and wider usability. Python provides an open source alternative for numerical computations and scripting. We have integrated these two open source technologies to develop a graphical software for a typical high heat flux experiment. The implementation uses EPICS based tools namely IOC (I/O controller) server, control system studio (CSS) and Python based tools namely Numpy, Scipy, Matplotlib and NOSE. EPICS and Python are integrated using PyEpics library. This toolkit is currently under operation at high heat flux test facility at Institute for Plasma Research (IPR) and is also useful for the experimental labs working in the similar research areas. The paper reports the software architectural design, implementation tools and rationale for their selection, test and validation.

Use of EPICS and Python technology for the development of a computational toolkit for high heat flux testing of plasma facing components

International Nuclear Information System (INIS)

Sugandhi, Ritesh; Swamy, Rajamannar; Khirwadkar, Samir

2016-01-01

Highlights: • An integrated approach to software development for computational processing and experimental control. • Use of open source, cross platform, robust and advanced tools for computational code development. • Prediction of optimized process parameters for critical heat flux model. • Virtual experimentation for high heat flux testing of plasma facing components. - Abstract: The high heat flux testing and characterization of the divertor and first wall components are a challenging engineering problem of a tokamak. These components are subject to steady state and transient heat load of high magnitude. Therefore, the accurate prediction and control of the cooling parameters is crucial to prevent burnout. The prediction of the cooling parameters is based on the numerical solution of the critical heat flux (CHF) model. In a test facility for high heat flux testing of plasma facing components (PFC), the integration of computations and experimental control is an essential requirement. Experimental physics and industrial control system (EPICS) provides powerful tools for steering controls, data simulation, hardware interfacing and wider usability. Python provides an open source alternative for numerical computations and scripting. We have integrated these two open source technologies to develop a graphical software for a typical high heat flux experiment. The implementation uses EPICS based tools namely IOC (I/O controller) server, control system studio (CSS) and Python based tools namely Numpy, Scipy, Matplotlib and NOSE. EPICS and Python are integrated using PyEpics library. This toolkit is currently under operation at high heat flux test facility at Institute for Plasma Research (IPR) and is also useful for the experimental labs working in the similar research areas. The paper reports the software architectural design, implementation tools and rationale for their selection, test and validation.

Learning Python testing

CERN Document Server

Arbuckle, Daniel

2014-01-01

This book is ideal if you want to learn about the testing disciplines and automated testing tools from a hands-on, conversational guide. You should already know Python and be comfortable with Python 3.

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

Science.gov (United States)

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

2013-04-01

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

NEURON and Python.

Science.gov (United States)

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

2009-01-01

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

Building and documenting workflows with python-based snakemake

OpenAIRE

Köster, Johannes; Rahmann, Sven

2012-01-01

textabstractSnakemake is a novel workflow engine with a simple Python-derived workflow definition language and an optimizing execution environment. It is the first system that supports multiple named wildcards (or variables) in input and output filenames of each rule definition. It also allows to write human-readable workflows that document themselves. We have found Snakemake especially useful for building high-throughput sequencing data analysis pipelines and present examples from this area....

Semantic computing and language knowledge bases

Science.gov (United States)

Wang, Lei; Wang, Houfeng; Yu, Shiwen

2017-09-01

As the proposition of the next-generation Web - semantic Web, semantic computing has been drawing more and more attention within the circle and the industries. A lot of research has been conducted on the theory and methodology of the subject, and potential applications have also been investigated and proposed in many fields. The progress of semantic computing made so far cannot be detached from its supporting pivot - language resources, for instance, language knowledge bases. This paper proposes three perspectives of semantic computing from a macro view and describes the current status of affairs about the construction of language knowledge bases and the related research and applications that have been carried out on the basis of these resources via a case study in the Institute of Computational Linguistics at Peking University.

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

Science.gov (United States)

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

2012-08-01

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

Functional Python programming

CERN Document Server

Lott, Steven

2015-01-01

This book is for developers who want to use Python to write programs that lean heavily on functional programming design patterns. You should be comfortable with Python programming, but no knowledge of functional programming paradigms is needed.

PyORBIT: A Python Shell For ORBIT

Energy Technology Data Exchange (ETDEWEB)

Jean-Francois Ostiguy; Jeffrey Holmes

2003-07-01

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

PyORBIT: A Python Shell For ORBIT

International Nuclear Information System (INIS)

Jean-Francois Ostiguy; Jeffrey Holmes

2003-01-01

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

Python data visualization cookbook

CERN Document Server

Milovanovic, Igor

2013-01-01

This book is written in a Cookbook style targeted towards an advanced audience. It covers the advanced topics of data visualization in Python.Python Data Visualization Cookbook is for developers that already know about Python programming in general. If you have heard about data visualization but you don't know where to start, then this book will guide you from the start and help you understand data, data formats, data visualization, and how to use Python to visualize data.You will need to know some general programming concepts, and any kind of programming experience will be helpful, but the co

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

International Nuclear Information System (INIS)

Sainio, J.

2012-01-01

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

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

Energy Technology Data Exchange (ETDEWEB)

Sainio, J., E-mail: jani.sainio@utu.fi [Turku School of Economics, University of Turku, Rehtorinpellonkatu 3, FI-20500 Turku (Finland); Department of Physics and Astronomy, University of Turku, FI-20014 Turku (Finland)

2012-04-01

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

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

Science.gov (United States)

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

2011-01-01

Context: Invasive Burmese pythons (Python molurus bivittatus) are established over thousands of square kilometres of southern Florida, USA, and consume a wide range of native vertebrates. Few tools are available to control the python population, and none of the available tools have been validated in the field to assess capture success as a proportion of pythons available to be captured. Aims: Our primary aim was to conduct a trap trial for capturing invasive pythons in an area east of Everglades National Park, where many pythons had been captured in previous years, to assess the efficacy of traps for population control. We also aimed to compare results of visual surveys with trap capture rates, to determine capture rates of non-target species, and to assess capture rates as a proportion of resident pythons in the study area. Methods: We conducted a medium-scale (6053 trap nights) experiment using two types of attractant traps baited with live rats in the Frog Pond area east of Everglades National Park. We also conducted standardised and opportunistic visual surveys in the trapping area. Following the trap trial, the area was disc harrowed to expose pythons and allow calculation of an index of the number of resident pythons. Key results: We captured three pythons and 69 individuals of various rodent, amphibian, and reptile species in traps. Eleven pythons were discovered during disc harrowing operations, as were large numbers of rodents.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

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

International Nuclear Information System (INIS)

Lavrijsen, Wim TLP

2012-01-01

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.

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

Science.gov (United States)

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.

Computer methods in physics 250 problems with guided solutions

CERN Document Server

Landau, Rubin H

2018-01-01

Our future scientists and professionals must be conversant in computational techniques. In order to facilitate integration of computer methods into existing physics courses, this textbook offers a large number of worked examples and problems with fully guided solutions in Python as well as other languages (Mathematica, Java, C, Fortran, and Maple). It’s also intended as a self-study guide for learning how to use computer methods in physics. The authors include an introductory chapter on numerical tools and indication of computational and physics difficulty level for each problem.

Python requests essentials

CERN Document Server

Chandra, Rakesh Vidya

2015-01-01

If you are a Python administrator or developer interested in interacting with web APIs and have a passion for creating your own web applications, this is the book for you. Basic knowledge of Python programming, APIs, and web services will be an advantage.

Development of the Tensoral Computer Language

Science.gov (United States)

Ferziger, Joel; Dresselhaus, Eliot

1996-01-01

The research scientist or engineer wishing to perform large scale simulations or to extract useful information from existing databases is required to have expertise in the details of the particular database, the numerical methods and the computer architecture to be used. This poses a significant practical barrier to the use of simulation data. The goal of this research was to develop a high-level computer language called Tensoral, designed to remove this barrier. The Tensoral language provides a framework in which efficient generic data manipulations can be easily coded and implemented. First of all, Tensoral is general. The fundamental objects in Tensoral represent tensor fields and the operators that act on them. The numerical implementation of these tensors and operators is completely and flexibly programmable. New mathematical constructs and operators can be easily added to the Tensoral system. Tensoral is compatible with existing languages. Tensoral tensor operations co-exist in a natural way with a host language, which may be any sufficiently powerful computer language such as Fortran, C, or Vectoral. Tensoral is very-high-level. Tensor operations in Tensoral typically act on entire databases (i.e., arrays) at one time and may, therefore, correspond to many lines of code in a conventional language. Tensoral is efficient. Tensoral is a compiled language. Database manipulations are simplified optimized and scheduled by the compiler eventually resulting in efficient machine code to implement them.

Python geospatial development essentials

CERN Document Server

Bahgat, Karim

2015-01-01

This book is ideal for Python programmers who are tasked with or wish to make a special-purpose GIS application. Analysts, political scientists, geographers, and GIS specialists seeking a creative platform to experiment with cutting-edge spatial analysis, but who are still only beginners in Python, will also find this book beneficial. Familiarity with Tkinter application development in Python is preferable but not mandatory.

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

Science.gov (United States)

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

2009-01-01

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

Elementary mechanics using Python a modern course combining analytical and numerical techniques

CERN Document Server

Malthe-Sørenssen, Anders

2015-01-01

This book – specifically developed as a novel textbook on elementary classical mechanics – shows how analytical and numerical methods can be seamlessly integrated to solve physics problems. This approach allows students to solve more advanced and applied problems at an earlier stage and equips them to deal with real-world examples well beyond the typical special cases treated in standard textbooks. Another advantage of this approach is that students are brought closer to the way physics is actually discovered and applied, as they are introduced right from the start to a more exploratory way of understanding phenomena and of developing their physical concepts. While not a requirement, it is advantageous for the reader to have some prior knowledge of scientific programming with a scripting-type language. This edition of the book uses Python, and a chapter devoted to the basics of scientific programming with Python is included. A parallel edition using Matlab instead of Python is also available. Last but not...

Python geospatial development

CERN Document Server

Westra, Erik

2013-01-01

This is a tutorial style book that will teach usage of Python tools for GIS using simple practical examples and then show you how to build a complete mapping application from scratch. The book assumes basic knowledge of Python. No knowledge of Open Source GIS is required.Experienced Python developers who want to learn about geospatial concepts, work with geospatial data, solve spatial problems, and build mapbased applications.This book will be useful those who want to get up to speed with Open Source GIS in order to build GIS applications or integrate GeoSpatial features into their existing ap

scikit-image: image processing in Python.

Science.gov (United States)

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

2014-01-01

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

scikit-image: image processing in Python

Directory of Open Access Journals (Sweden)

Stéfan van der Walt

2014-06-01

Full Text Available 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.

Practical Maya programming with Python

CERN Document Server

Galanakis, Robert

2014-01-01

""Practical Maya Programming with Python"" is a practical tutorial packed with plenty of examples and sample projects which guides you through building reusable, independent modules and handling unexpected errors. If you are a developer looking to build a powerful system using Python and Maya's capabilities, then this book is for you. Practical Maya Programming with Python is perfect for intermediate users with basic experience in Python and Maya who want to better their knowledge and skills.

Enhanced OpenModelica Python Interface

OpenAIRE

Bajracharya, Sudeep

2016-01-01

OMPython is a Python library for OpenModelica, which provides a Python interface to OpenModelica. This thesis significantly improves OMPython by an enhanced, more powerful and easier to use API. It presents how a user can use the Python interface to simulate and access Modelica models using Python objects. The enhanced OMPython includes the list of functions that have been implemented such as getXXXNames(), getXXXValues(), setXXXValues(), getXXXOptions(), setXXXOptions(), and simulate(), etc....

Computer language evaluation for MFTF SCDS

International Nuclear Information System (INIS)

Anderson, R.E.; McGoldrick, P.R.; Wyman, R.H.

1979-01-01

The computer languages available for the systems and application implementation on the Supervisory Control and Diagnostics System (SCDS) for the Mirror Fusion Test Facility (MFTF) were surveyed and evaluated. Four language processors, CAL (Common Assembly Language), Extended FORTRAN, CORAL 66, and Sequential Pascal (SPASCAL, a subset of Concurrent Pascal [CPASCAL]) are commercially available for the Interdata 7/32 and 8/32 computers that constitute the SCDS. Of these, the Sequential Pascal available from Kansas State University appears best for the job in terms of minimizing the implementation time, debugging time, and maintenance time. This improvement in programming productivity is due to the availability of a high-level, block-structured language that includes many compile-time and run-time checks to detect errors. In addition, the advanced data-types in language allow easy description of the program variables. 1 table

Python penetration testing essentials

CERN Document Server

Mohit

2015-01-01

If you are a Python programmer or a security researcher who has basic knowledge of Python programming and want to learn about penetration testing with the help of Python, this book is ideal for you. Even if you are new to the field of ethical hacking, this book can help you find the vulnerabilities in your system so that you are ready to tackle any kind of attack or intrusion.

Using Python to Program LEGO MINDSTORMS® Robots: The PyNXC Project

Directory of Open Access Journals (Sweden)

2010-04-01

Full Text Available

 

The definitive guide to Jython Python for the Java platform

CERN Document Server

Juneau, Josh; Ng, Victor; Soto, Leo; Wierzbicki, Frank

2010-01-01

Jython is an open source implementation of the high-level, dynamic, object-oriented scripting language Python seamlessly integrated with the Java platform. The predecessor to Jython, JPython, is certified as 100% Pure Java. Jython is freely available for both commercial and noncommercial use and is distributed with source code. Jython is complementary to Java. The Definitive Guide to Jython, written by the official Jython team leads, covers the latest Jython 2.5 (or 2.5.x) from the basics to the advanced features. This book begins with a brief introduction to the language and then journeys thr

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

Science.gov (United States)

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.

Mitigating Spreadsheet Model Risk with Python Open Source Infrastructure

OpenAIRE

Beavers, Oliver

2018-01-01

Across an aggregation of EuSpRIG presentation papers, two maxims hold true: spreadsheets models are akin to software, yet spreadsheet developers are not software engineers. As such, the lack of traditional software engineering tools and protocols invites a higher rate of error in the end result. This paper lays ground work for spreadsheet modelling professionals to develop reproducible audit tools using freely available, open source packages built with the Python programming language, enablin...

An overview of computer-based natural language processing

Science.gov (United States)

Gevarter, W. B.

1983-01-01

Computer based Natural Language Processing (NLP) is the key to enabling humans and their computer based creations to interact with machines in natural language (like English, Japanese, German, etc., in contrast to formal computer languages). The doors that such an achievement can open have made this a major research area in Artificial Intelligence and Computational Linguistics. Commercial natural language interfaces to computers have recently entered the market and future looks bright for other applications as well. This report reviews the basic approaches to such systems, the techniques utilized, applications, the state of the art of the technology, issues and research requirements, the major participants and finally, future trends and expectations. It is anticipated that this report will prove useful to engineering and research managers, potential users, and others who will be affected by this field as it unfolds.

Optlang: An algebraic modeling language for mathematical optimization

DEFF Research Database (Denmark)

Jensen, Kristian; Cardoso, Joao; Sonnenschein, Nikolaus

2016-01-01

Optlang is a Python package implementing a modeling language for solving mathematical optimization problems, i.e., maximizing or minimizing an objective function over a set of variables subject to a number of constraints. It provides a common native Python interface to a series of optimization...

Computers in Language Testing: Present Research and Some Future Directions.

Science.gov (United States)

Brown, James Dean

1997-01-01

Explores recent developments in the use of computers in language testing in four areas: (1) item banking; (2) computer-assisted language testing; (3) computerized-adaptive language testing; and (4) research on the effectiveness of computers in language testing. Examines educational measurement literature in an attempt to forecast the directions…

Learning Python design patterns

CERN Document Server

Zlobin, Gennadiy

2013-01-01

This book takes a tutorial-based and user-friendly approach to covering Python design patterns. Its concise presentation means that in a short space of time, you will get a good introduction to various design patterns.If you are an intermediate level Python user, this book is for you. Prior knowledge of Python programming is essential. Some knowledge of UML is also required to understand the UML diagrams which are used to describe some design patterns.

Programming an offline-analyzer of motor imagery signals via python language.

Science.gov (United States)

Alonso-Valerdi, Luz María; Sepulveda, Francisco

2011-01-01

Brain Computer Interface (BCI) systems control the user's environment via his/her brain signals. Brain signals related to motor imagery (MI) have become a widespread method employed by the BCI community. Despite the large number of references describing the MI signal treatment, there is not enough information related to the available programming languages that could be suitable to develop a specific-purpose MI-based BCI. The present paper describes the development of an offline-analysis system based on MI-EEG signals via open-source programming languages, and the assessment of the system using electrical activity recorded from three subjects. The analyzer recognized at least 63% of the MI signals corresponding to three classes. The results of the offline analysis showed a promising performance considering that the subjects have never undergone MI trainings.

Beta-shifts, their languages and computability

DEFF Research Database (Denmark)

Simonsen, Jakob Grue

2011-01-01

they give into the dynamics of the underlying system. We prove that the language of the ß-shift is recursive iff ß is a computable real number. That fact yields a precise characterization of the reals: The real numbers ß for which we can compute arbitrarily good approximations—hence in particular......For every real number ß >1, the ß-shift is a dynamical system describing iterations of the map x ¿ ßx mod 1 and is studied intensively in number theory. Each ß-shift has an associated language of finite strings of characters; properties of this language are studied for the additional insight...

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

DEFF Research Database (Denmark)

Astarita, Giuseppe; Rourke, Bryan C; Andersen, Johnnie Bremholm

2006-01-01

to the induction of between-meal satiety. Here we examined whether feeding-induced OEA mobilization also occurs in Burmese pythons (Python molurus), a species of ambush-hunting snakes that consumes huge meals after months of fasting and undergoes massive feeding-dependent changes in gastrointestinal hormonal...... release and gut morphology. Using liquid-chromatography/mass-spectrometry (LC/MS), we measured OEA levels in the gastrointestinal tract of fasted (28 days) and fed (48h after feeding) pythons. We observed a nearly 300-fold increase in OEA levels in the small intestine of fed compared to fasted animals......-unsaturated, but not polyunsaturated fatty-acid ethanolamides (FAE) in the small intestine of fed pythons. The identification of OEA and other FAEs in the gastrointestinal tract of Python molurus suggests that this class of lipid messengers may be widespread among vertebrate groups and may represent an evolutionarily ancient means...

Amebiasis in four ball pythons, Python reginus.

Science.gov (United States)

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

2001-12-01

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

Multi-language Struct Support in Babel

Energy Technology Data Exchange (ETDEWEB)

Ebner, D; Prantl, A; Epperly, T W

2011-03-22

Babel is an open-source language interoperability framework tailored to the needs of high-performance scientific computing. As an integral element of the Common Component Architecture (CCA) it is used in a wide range of research projects. In this paper we describe how we extended Babel to support interoperable tuple data types (structs). Structs are a common idiom in scientific APIs; they are an efficient way to pass tuples of nonuniform data between functions, and are supported natively by most programming languages. Using our extended version of Babel, developers of scientific code can now pass structs as arguments between functions implemented in any of the supported languages. In C, C++ and Fortran 2003, structs can be passed without the overhead of data marshaling or copying, providing language interoperability at minimal cost. Other supported languages are Fortran 77, Fortran 90, Java and Python. We will show how we designed a struct implementation that is interoperable with all of the supported languages and present benchmark data compare the performance of all language bindings, highlighting the differences between languages that offer native struct support and an object-oriented interface with getter/setter methods.

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

Energy Technology Data Exchange (ETDEWEB)

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

2011-11-01

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

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

Science.gov (United States)

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…

The fast azimuthal integration Python library: pyFAI.

Science.gov (United States)

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.

75 FR 23327 - Asset-Backed Securities

Science.gov (United States)

2010-05-03

... code in Python, a commonly used open source interpretive programming language. We are proposing new... code in Python, a commonly used computer programming language that is open source and interpretive. The... Program and Python (e) Hardship Exemptions 2. Presentation of the Narrative Description of the Waterfall C...

New Computer Terms in Bloggers’ Language

Directory of Open Access Journals (Sweden)

Vilija Celiešienė

2012-06-01

Full Text Available The article presents an analysis of new words in computer terminology that make their way to blogs and analyzes how the official neologisms and computer terms, especially the equivalents to barbarisms, are employed in everyday use. The article also discusses the ways of including the new computer terms into texts. The blogs on topics of information technology are the objects of the research. The analysis of the aforementioned blogs allowed highlighting certain trends in the use of new computer terms. An observation was made that even though the authors of the blogs could freely choose their writing style, they were not bound by the standards of literary language. Thus, their language was full of non-standard vocabulary; however, self-control regarding the language used could still be noticed. An interest in novelties of computer terminology and the tendency to accept some of the suggested new Lithuanian and loaned computer terms were noticed. When using the new words the bloggers frequently employed specific graphical elements and (or comments. The graphical elements were often chosen by bloggers to express their feelings of doubt regarding the suitability of the use of the suggested loanword. Attempting to explain the meaning of the new word to the readers the bloggers tended to post comments about the new computer terms.

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

Science.gov (United States)

Jensen, Bjarke; Wang, Tobias

2009-12-01

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

Unilateral microphthalmia or anophthalmia in eight pythons (Pythonidae)

DEFF Research Database (Denmark)

Da Silva, Mari-Ann Otkjær; Berthelsen, MF; Wang, T

2015-01-01

OBJECTIVE: To provide morphological descriptions of microphthalmia or anophthalmia in eight pythons using microcomputerized tomography (μCT), magnetic resonance imaging (MRI), and histopathology. ANIMALS STUDIED: Seven Burmese pythons (Python bivittatus) and one ball python (P. regius) with clini......OBJECTIVE: To provide morphological descriptions of microphthalmia or anophthalmia in eight pythons using microcomputerized tomography (μCT), magnetic resonance imaging (MRI), and histopathology. ANIMALS STUDIED: Seven Burmese pythons (Python bivittatus) and one ball python (P. regius...... macroscopic anomalies. CONCLUSIONS: Eight pythons with unilateral left-sided microphthalmia or anophthalmia had one normal eye and a left orbit with malformed or incompletely developed ocular structures along with remnants of fetal structures. These cases lend further information to a condition that is often...

pycalphad: CALPHAD-based Computational Thermodynamics in Python

Directory of Open Access Journals (Sweden)

Richard Otis

2017-01-01

Full Text Available The pycalphad software package is a free and open-source Python library for designing thermodynamic models, calculating phase diagrams and investigating phase equilibria using the CALPHAD method. It provides routines for reading thermodynamic databases and solving the multi-component, multi-phase Gibbs energy minimization problem. The pycalphad software project advances the state of thermodynamic modeling by providing a flexible yet powerful interface for manipulating CALPHAD data and models. The key feature of the software is that the thermodynamic models of individual phases and their associated databases can be programmatically manipulated and overridden at run-time without modifying any internal solver or calculation code. Because the models are internally decoupled from the equilibrium solver and the models themselves are represented symbolically, pycalphad is an ideal tool for CALPHAD database development and model prototyping.

A Python Engine for Teaching Artificial Intelligence in Games

OpenAIRE

Riedl, Mark O.

2015-01-01

Computer games play an important role in our society and motivate people to learn computer science. Since artificial intelligence is integral to most games, they can also be used to teach artificial intelligence. We introduce the Game AI Game Engine (GAIGE), a Python game engine specifically designed to teach about how AI is used in computer games. A progression of seven assignments builds toward a complete, working Multi-User Battle Arena (MOBA) game. We describe the engine, the assignments,...

The InSAR Scientific Computing Environment (ISCE): A Python Framework for Earth Science

Science.gov (United States)

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

2015-12-01

The InSAR Scientific Computing Environment (ISCE, funded by NASA ESTO) provides a modern computing framework for geodetic image processing of InSAR data from a diverse array of radar satellites and aircraft. ISCE is both a modular, flexible, and extensible framework for building software components and applications as well as a toolbox of applications for processing raw or focused InSAR and Polarimetric InSAR data. The ISCE framework contains object-oriented Python components layered to construct Python InSAR components that manage legacy Fortran/C InSAR programs. Components are independently configurable in a layered manner to provide maximum control. Polymorphism is used to define a workflow in terms of abstract facilities for each processing step that are realized by specific components at run-time. This enables a single workflow to work on either raw or focused data from all sensors. ISCE can serve as the core of a production center to process Level-0 radar data to Level-3 products, but is amenable to interactive processing approaches that allow scientists to experiment with data to explore new ways of doing science with InSAR data. The NASA-ISRO SAR (NISAR) Mission will deliver data of unprecedented quantity and quality, making possible global-scale studies in climate research, natural hazards, and Earth's ecosystems. ISCE is planned as the foundational element in processing NISAR data, enabling a new class of analyses that take greater advantage of the long time and large spatial scales of these new data. NISAR will be but one mission in a constellation of radar satellites in the future delivering such data. ISCE currently supports all publicly available strip map mode space-borne SAR data since ERS and is expected to include support for upcoming missions. ISCE has been incorporated into two prototype cloud-based systems that have demonstrated its elasticity in addressing larger data processing problems in a "production" context and its ability to be

pypet: A Python Toolkit for Data Management of Parameter Explorations

Directory of Open Access Journals (Sweden)

Robert Meyer

2016-08-01

Full Text Available 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.

MGtoolkit: A python package for implementing metagraphs

Science.gov (United States)

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

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

MGtoolkit: A python package for implementing metagraphs

Directory of Open Access Journals (Sweden)

D. Ranathunga

2017-01-01

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

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

Science.gov (United States)

Tsuji, Yamato; Prayitno, Bambang; Suryobroto, Bambang

2016-04-01

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

Generation of Test Questions from RDF Files Using PYTHON and SPARQL

Science.gov (United States)

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.

Natural language computing an English generative grammar in Prolog

CERN Document Server

Dougherty, Ray C

2013-01-01

This book's main goal is to show readers how to use the linguistic theory of Noam Chomsky, called Universal Grammar, to represent English, French, and German on a computer using the Prolog computer language. In so doing, it presents a follow-the-dots approach to natural language processing, linguistic theory, artificial intelligence, and expert systems. The basic idea is to introduce meaningful answers to significant problems involved in representing human language data on a computer. The book offers a hands-on approach to anyone who wishes to gain a perspective on natural language

Computer Assisted Language Learning (CALL): Using Internet for Effective Language Learning

NARCIS (Netherlands)

Kremenska, Anelly

2006-01-01

Please, cite this publication as: Kremenska, A. (2006). Computer Assisted Language Learning (CALL): Using Internet for Effective Language Learning. Proceedings of International Workshop in Learning Networks for Lifelong Competence Development, TENCompetence Conference. March 30th-31st, Sofia,

Installing Python Modules with pip

OpenAIRE

Fred Gibbs

2013-01-01

This lesson shows you how to download and install Python modules. There are many ways to install external modules, but for the purposes of this lesson, we’re going to use a program called pip. As of Python 2.7.9 and newer, pip is installed by default. This tutorial will be helpful for anyone using older versions of Python (which are still quite common).

Computer-Assisted Language Learning: Current Programs and Projects. ERIC Digest.

Science.gov (United States)

Higgins, Chris

For many years, foreign language teachers have used the computer to provide supplemental exercises in the instruction of foreign languages. In recent years, advances in computer technology have motivated teachers to reassess the computer and consider it a valuable part of daily foreign language learning. Innovative software programs, authoring…

Psyplot: Visualizing rectangular and triangular Climate Model Data with Python

Science.gov (United States)

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.

HAL/SM language specification. [programming languages and computer programming for space shuttles

Science.gov (United States)

Williams, G. P. W., Jr.; Ross, C.

1975-01-01

A programming language is presented for the flight software of the NASA Space Shuttle program. It is intended to satisfy virtually all of the flight software requirements of the space shuttle. To achieve this, it incorporates a wide range of features, including applications-oriented data types and organizations, real time control mechanisms, and constructs for systems programming tasks. It is a higher order language designed to allow programmers, analysts, and engineers to communicate with the computer in a form approximating natural mathematical expression. Parts of the English language are combined with standard notation to provide a tool that readily encourages programming without demanding computer hardware expertise. Block diagrams and flow charts are included. The semantics of the language is discussed.

Computer Assisted Language Learning (CALL) Software: Evaluation ...

African Journals Online (AJOL)

Evaluating the nature and extent of the influence of Computer Assisted Language Learning (CALL) on the quality of language learning is highly problematic. This is owing to the number and complexity of interacting variables involved in setting the items for teaching and learning languages. This paper identified and ...

Learning theories in computer-assisted foreign language acquisition

OpenAIRE

Baeva, D.

2013-01-01

This paper reviews the learning theories, focusing to the strong interest in technology use for language learning. It is important to look at how technology has been used in the field thus far. The goals of this review are to understand how computers have been used in the past years to support foreign language learning, and to explore any research evidence with regards to how computer technology can enhance language skills acquisition

Re-imagining a Stata/Python combination

OpenAIRE

James Fiedler

2013-01-01

At last year’s Stata Conference, I presented some ideas for combining Stata and Python within a single interface. Two methods were presented; in one, Python was used to automate Stata, and 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 talk I will demonstrate a method for achieving interaction between Stata and Python which does ...

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

Science.gov (United States)

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.

Eddylicious: A Python package for turbulent inflow generation

Science.gov (United States)

Mukha, Timofey; Liefvendahl, Mattias

2018-01-01

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

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

Science.gov (United States)

Falk, Bryan; Reed, Robert N.

2015-01-01

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

Session Types Go Dynamic or How to Verify Your Python Conversations

Directory of Open Access Journals (Sweden)

Rumyana Neykova

2013-12-01

Full Text Available This paper presents the first implementation of session types in a dynamically-typed language - Python. Communication safety of the whole system is guaranteed at runtime by monitors that check the execution traces comply with an associated protocol. Protocols are written in Scribble, a choreography description language based on multiparty session types, with addition of logic formulas for more precise behaviour properties. The presented framework overcomes the limitations of previous works on the session types where all endpoints should be statically typed so that they do not permit interoperability with untyped participants. The advantages, expressiveness and performance of dynamic protocol checking are demonstrated through use case and benchmarks.

PySSM: A Python Module for Bayesian Inference of Linear Gaussian State Space Models

Directory of Open Access Journals (Sweden)

Christopher Strickland

2014-04-01

Full Text Available PySSM is a Python package that has been developed for the analysis of time series using linear Gaussian state space models. PySSM is easy to use; models can be set up quickly and efficiently and a variety of different settings are available to the user. It also takes advantage of scientific libraries NumPy and SciPy and other high level features of the Python language. PySSM is also used as a platform for interfacing between optimized and parallelized Fortran routines. These Fortran routines heavily utilize basic linear algebra and linear algebra Package functions for maximum performance. PySSM contains classes for filtering, classical smoothing as well as simulation smoothing.

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

Science.gov (United States)

Smelter, Andrey; Moseley, Hunter N B

2018-01-01

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

Computer-Assisted Language Learning : proceedings of the seventh Twente Workshop on Language Technology

NARCIS (Netherlands)

Appelo, L.; de Jong, Franciska M.G.

1994-01-01

TWLT is an acronym of Twente Workshop(s) on Language Technology. These workshops on natural language theory and technology are organised bij Project Parlevink (sometimes with the help of others) a language theory and technology project conducted at the Department of Computer Science of the

The Zoonotic Implications of Pentastomiasis in the Royal Python (Python Regius)

OpenAIRE

Ayinmode, AB; Adedokun, AO; Aina, A; Taiwo, V

2010-01-01

Pentastomes are worm-like endoparasites of the phylum Pentastomida found principally in the respiratory tract of reptiles, birds, and mammals. They cause a zoonotic disease known as pentastomiasis in humans and other mammals. The autopsy of a Nigerian royal python (Python regius) revealed two yellowish-white parasites in the lungs, tissue necrosis and inflammatory lesions. The parasite was confirmed to be Armillifer spp (Pentastomid); this is the first recorded case of pentastomiasis in the r...

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

Science.gov (United States)

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

2012-05-01

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

ProjectQ: An Open Source Software Framework for Quantum Computing

OpenAIRE

Steiger, Damian S.; Häner, Thomas; Troyer, Matthias

2016-01-01

We introduce ProjectQ, an open source software effort for quantum computing. The first release features a compiler framework capable of targeting various types of hardware, a high-performance simulator with emulation capabilities, and compiler plug-ins for circuit drawing and resource estimation. We introduce our Python-embedded domain-specific language, present the features, and provide example implementations for quantum algorithms. The framework allows testing of quantum algorithms through...

Scraping EDGAR with Python

Science.gov (United States)

Ashraf, Rasha

2017-01-01

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

The use of Computer Assisted Language Learning (CALL) Devices ...

African Journals Online (AJOL)

Despite the numerous advantages that can be made of the computer in language teaching, many ... be made of the computer in English Language teaching by low technologically exposed teachers. ... http://dx.doi.org/10.4314/ict.v2i1.31950.

Collocational Relations in Japanese Language Textbooks and Computer-Assisted Language Learning Resources

Directory of Open Access Journals (Sweden)

Irena SRDANOVIĆ

2011-05-01

Full Text Available In this paper, we explore presence of collocational relations in the computer-assisted language learning systems and other language resources for the Japanese language, on one side, and, in the Japanese language learning textbooks and wordlists, on the other side. After introducing how important it is to learn collocational relations in a foreign language, we examine their coverage in the various learners’ resources for the Japanese language. We particularly concentrate on a few collocations at the beginner’s level, where we demonstrate their treatment across various resources. A special attention is paid to what is referred to as unpredictable collocations, which have a bigger foreign language learning-burden than the predictable ones.

Can Computers Be Used for Whole Language Approaches to Reading and Language Arts?

Science.gov (United States)

Balajthy, Ernest

Holistic approaches to the teaching of reading and writing, most notably the Whole Language movement, reject the philosophy that language skills can be taught. Instead, holistic teachers emphasize process, and they structure the students' classroom activities to be rich in language experience. Computers can be used as tools for whole language…

The Advantages and Disadvantages of Computer Technology in Second Language Acquisition

Science.gov (United States)

Lai, Cheng-Chieh; Kritsonis, William Allan

2006-01-01

The purpose of this article is to discuss the advantages and disadvantages of computer technology and Computer Assisted Language Learning (CALL) programs for current second language learning. According to the National Clearinghouse for English Language Acquisition & Language Instruction Educational Programs' report (2002), more than nine million…

PetClaw: Parallelization and Performance Optimization of a Python-Based Nonlinear Wave Propagation Solver Using PETSc

KAUST Repository

Alghamdi, Amal Mohammed

2012-04-01

Clawpack, a conservation laws package implemented in Fortran, and its Python-based version, PyClaw, are existing tools providing nonlinear wave propagation solvers that use state of the art finite volume methods. Simulations using those tools can have extensive computational requirements to provide accurate results. Therefore, a number of tools, such as BearClaw and MPIClaw, have been developed based on Clawpack to achieve significant speedup by exploiting parallel architectures. However, none of them has been shown to scale on a large number of cores. Furthermore, these tools, implemented in Fortran, achieve parallelization by inserting parallelization logic and MPI standard routines throughout the serial code in a non modular manner. Our contribution in this thesis research is three-fold. First, we demonstrate an advantageous use case of Python in implementing easy-to-use modular extensible scalable scientific software tools by developing an implementation of a parallelization framework, PetClaw, for PyClaw using the well-known Portable Extensible Toolkit for Scientific Computation, PETSc, through its Python wrapper petsc4py. Second, we demonstrate the possibility of getting acceptable Python code performance when compared to Fortran performance after introducing a number of serial optimizations to the Python code including integrating Clawpack Fortran kernels into PyClaw for low-level computationally intensive parts of the code. As a result of those optimizations, the Python overhead in PetClaw for a shallow water application is only 12 percent when compared to the corresponding Fortran Clawpack application. Third, we provide a demonstration of PetClaw scalability on up to the entirety of Shaheen; a 16-rack Blue Gene/P IBM supercomputer that comprises 65,536 cores and located at King Abdullah University of Science and Technology (KAUST). The PetClaw solver achieved above 0.98 weak scaling efficiency for an Euler application on the whole machine excluding the

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

Science.gov (United States)

Penning, David A; Dartez, Schuyler F

2016-03-01

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

Errors and Intelligence in Computer-Assisted Language Learning: Parsers and Pedagogues. Routledge Studies in Computer Assisted Language Learning

Science.gov (United States)

Heift, Trude; Schulze, Mathias

2012-01-01

This book provides the first comprehensive overview of theoretical issues, historical developments and current trends in ICALL (Intelligent Computer-Assisted Language Learning). It assumes a basic familiarity with Second Language Acquisition (SLA) theory and teaching, CALL and linguistics. It is of interest to upper undergraduate and/or graduate…

Anatomy of the python heart.

Science.gov (United States)

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

2010-12-01

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

Unilateral microphthalmia or anophthalmia in eight pythons (Pythonidae).

Science.gov (United States)

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

2015-01-01

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

Building machine learning systems with Python

CERN Document Server

Coelho, Luis Pedro

2015-01-01

This book primarily targets Python developers who want to learn and use Python's machine learning capabilities and gain valuable insights from data to develop effective solutions for business problems.

Cameo: A Python Library for Computer Aided Metabolic Engineering and Optimization of Cell Factories.

Science.gov (United States)

Cardoso, João G R; Jensen, Kristian; Lieven, Christian; Lærke Hansen, Anne Sofie; Galkina, Svetlana; Beber, Moritz; Özdemir, Emre; Herrgård, Markus J; Redestig, Henning; Sonnenschein, Nikolaus

2018-04-20

Computational systems biology methods enable rational design of cell factories on a genome-scale and thus accelerate the engineering of cells for the production of valuable chemicals and proteins. Unfortunately, the majority of these methods' implementations are either not published, rely on proprietary software, or do not provide documented interfaces, which has precluded their mainstream adoption in the field. In this work we present cameo, a platform-independent software that enables in silico design of cell factories and targets both experienced modelers as well as users new to the field. It is written in Python and implements state-of-the-art methods for enumerating and prioritizing knockout, knock-in, overexpression, and down-regulation strategies and combinations thereof. Cameo is an open source software project and is freely available under the Apache License 2.0. A dedicated Web site including documentation, examples, and installation instructions can be found at http://cameo.bio . Users can also give cameo a try at http://try.cameo.bio .

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

Science.gov (United States)

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.

The Potential of Incorporating Computer Games in Foreign Language Curricula

Directory of Open Access Journals (Sweden)

Jayakaran Mukundan

2014-04-01

Full Text Available There is ample evidence that technology-enhanced instruction could result in students’ learning. With the advancement and ever-increasing growth of technology, the use of educational electronic games or computer games in education has appealed to both educators and students. Because of their potential to enhance students’ interest, motivation and creativity, computer games can be used to teach various skills and strategies to different types of students, particularly schoolchildren. These games have also made inroads into language learning classrooms as they provide language learners with a rich learning context to engage in authentic and meaningful learning experiences. This paper reviews the potential of integrating computer games into second/foreign language syllabi and curricula by offering a synopsis of the assumptions, prior studies and theoretical background in support of these games in language education. At the end, the paper touches upon the role of teachers and the likely inhibiting factors affecting the integration of computer games into English language programs.

Detection of nidoviruses in live pythons and boas.

Science.gov (United States)

Marschang, Rachel E; Kolesnik, Ekaterina

2017-02-09

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

Programming ArcGIS 10.1 with Python cookbook

CERN Document Server

Pimpler, Eric

2013-01-01

This book is written in a helpful, practical style with numerous hands-on recipes and chapters to help you save time and effort by using Python to power ArcGIS to create shortcuts, scripts, tools, and customizations.""Programming ArcGIS 10.1 with Python Cookbook"" is written for GIS professionals who wish to revolutionize their ArcGIS workflow with Python. Basic Python or programming knowledge is essential(?).

Manipulating Strings in Python

Directory of Open Access Journals (Sweden)

William J. Turkel

2012-07-01

Full Text Available This lesson is a brief introduction to string manipulation techniques in Python. Knowing how to manipulate strings plays a crucial role in most text processing tasks. If you’d like to experiment with the following lessons, you can write and execute short programs as we’ve been doing, or you can open up a Python shell / Terminal to try them out on the command line.

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

Science.gov (United States)

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

2016-12-01

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

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

Science.gov (United States)

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

2012-01-01

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

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

Science.gov (United States)

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.

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

Science.gov (United States)

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

2009-08-01

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

Computer modelling as a tool for understanding language evolution

NARCIS (Netherlands)

de Boer, Bart; Gontier, N; VanBendegem, JP; Aerts, D

2006-01-01

This paper describes the uses of computer models in studying the evolution of language. Language is a complex dynamic system that can be studied at the level of the individual and at the level of the population. Much of the dynamics of language evolution and language change occur because of the

Conversation Analysis in Computer-Assisted Language Learning

Science.gov (United States)

González-Lloret, Marta

2015-01-01

The use of Conversation Analysis (CA) in the study of technology-mediated interactions is a recent methodological addition to qualitative research in the field of Computer-assisted Language Learning (CALL). The expansion of CA in Second Language Acquisition research, coupled with the need for qualitative techniques to explore how people interact…

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

Science.gov (United States)

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.

Computer-Assisted Language Learning: Diversity in Research and Practice

Science.gov (United States)

Stockwell, Glenn, Ed.

2012-01-01

Computer-assisted language learning (CALL) is an approach to teaching and learning languages that uses computers and other technologies to present, reinforce, and assess material to be learned, or to create environments where teachers and learners can interact with one another and the outside world. This book provides a much-needed overview of the…

Students' Motivation toward Computer-Based Language Learning

Science.gov (United States)

Genc, Gulten; Aydin, Selami

2011-01-01

The present article examined some factors affecting the motivation level of the preparatory school students in using a web-based computer-assisted language-learning course. The sample group of the study consisted of 126 English-as-a-foreign-language learners at a preparatory school of a state university. After performing statistical analyses…

Building an application for computing the resource requests such as disk, CPU, and tape and studying the time evolution of computing model

CERN Document Server

Noormandipour, Mohammad Reza

2017-01-01

The goal of this project was building an application to calculate the computing resources needed by the LHCb experiment for data processing and analysis, and to predict their evolution in future years. The source code was developed in the Python programming language and the application built and developed in CERN GitLab. This application will facilitate the calculation of resources required by LHCb in both qualitative and quantitative aspects. The granularity of computations is improved to a weekly basis, in contrast with the yearly basis used so far. The LHCb computing model will benefit from the new possibilities and options added, as the new predictions and calculations are aimed at giving more realistic and accurate estimates.

ALOHA: Automatic libraries of helicity amplitudes for Feynman diagram computations

Science.gov (United States)

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

2012-10-01

We present an application that automatically writes the HELAS (HELicity Amplitude Subroutines) library corresponding to the Feynman rules of any quantum field theory Lagrangian. The code is written in Python and takes the Universal FeynRules Output (UFO) as an input. From this input it produces the complete set of routines, wave-functions and amplitudes, that are needed for the computation of Feynman diagrams at leading as well as at higher orders. The representation is language independent and currently it can output routines in Fortran, C++, and Python. A few sample applications implemented in the MADGRAPH 5 framework are presented. Program summary Program title: ALOHA Catalogue identifier: AEMS_v1_0 Program summary URL: http://cpc.cs.qub.ac.uk/summaries/AEMS_v1_0.html Program obtainable from: CPC Program Library, Queen's University, Belfast, N. Ireland Licensing provisions: http://www.opensource.org/licenses/UoI-NCSA.php No. of lines in distributed program, including test data, etc.: 6094320 No. of bytes in distributed program, including test data, etc.: 7479819 Distribution format: tar.gz Programming language: Python2.6 Computer: 32/64 bit Operating system: Linux/Mac/Windows RAM: 512 Mbytes Classification: 4.4, 11.6 Nature of problem: An effcient numerical evaluation of a squared matrix element can be done with the help of the helicity routines implemented in the HELAS library [1]. This static library contains a limited number of helicity functions and is therefore not always able to provide the needed routine in the presence of an arbitrary interaction. This program provides a way to automatically create the corresponding routines for any given model. Solution method: ALOHA takes the Feynman rules associated to the vertex obtained from the model information (in the UFO format [2]), and multiplies it by the different wavefunctions or propagators. As a result the analytical expression of the helicity routines is obtained. Subsequently, this expression is

PyMidas: Interface from Python to Midas

Science.gov (United States)

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.

xarray: N-D labeled Arrays and Datasets in Python

Directory of Open Access Journals (Sweden)

Stephan Hoyer

2017-04-01

Full Text Available xarray is an open source project and Python package that provides a toolkit and data structures for N-dimensional labeled arrays. Our approach combines an application programing interface (API inspired by pandas with the Common Data Model for self-described scientific data. Key features of the xarray package include label-based indexing and arithmetic, interoperability with the core scientific Python packages (e.g., pandas, NumPy, Matplotlib, out-of-core computation on datasets that don’t fit into memory, a wide range of serialization and input/output (I/O options, and advanced multi-dimensional data manipulation tools such as group-by and resampling. xarray, as a data model and analytics toolkit, has been widely adopted in the geoscience community but is also used more broadly for multi-dimensional data analysis in physics, machine learning and finance.

pyGeno: A Python package for precision medicine and proteogenomics [version 2; referees: 1 approved, 2 approved with reservations

Directory of Open Access Journals (Sweden)

Tariq Daouda

2016-05-01

Full Text Available 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.

Python for Development of OpenMP and CUDA Kernels for Multidimensional Data

International Nuclear Information System (INIS)

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

2011-01-01

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

Interactive computing in BASIC an introduction to interactive computing and a practical course in the BASIC language

CERN Document Server

Sanderson, Peter C

1973-01-01

Interactive Computing in BASIC: An Introduction to Interactive Computing and a Practical Course in the BASIC Language provides a general introduction to the principles of interactive computing and a comprehensive practical guide to the programming language Beginners All-purpose Symbolic Instruction Code (BASIC). The book starts by providing an introduction to computers and discussing the aspects of terminal usage, programming languages, and the stages in writing and testing a program. The text then discusses BASIC with regard to methods in writing simple arithmetical programs, control stateme

Structured Design Language for Computer Programs

Science.gov (United States)

Pace, Walter H., Jr.

1986-01-01

Box language used at all stages of program development. Developed to provide improved productivity in designing, coding, and maintaining computer programs. BOX system written in FORTRAN 77 for batch execution.

Python tools for Visual Studio

CERN Document Server

Wang, Cathy

2014-01-01

This is a hands-on guide that provides exemplary coverage of all the features and concepts related to PTVS.The book is intended for developers who are aiming to enhance their productivity in Python projects with automation tools that Visual Studio provides for the .Net community. Some basic knowledge of Python programming is essential.

Static Analysis of Dynamic Languages

DEFF Research Database (Denmark)

Madsen, Magnus

Dynamic programming languages are highly popular and widely used. Java- Script is often called the lingua franca of the web and it is the de facto standard for client-side web programming. On the server-side the PHP, Python and Ruby languages are prevalent. What these languages have in common...... with static type systems, such as Java and C# , but the same features are rarely available for dynamic languages such as JavaScript. The aim of this thesis is to investigate techniques for improving the tool- support for dynamic programming languages without imposing any artificial restrictions...... of new dataflow analysis techniques to tackle the nature of dynamic programming languages....

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

Science.gov (United States)

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

2009-12-01

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

seismo-live: Training in Computational Seismology using Jupyter Notebooks

Science.gov (United States)

Igel, H.; Krischer, L.; van Driel, M.; Tape, C.

2016-12-01

Practical training in computational methodologies is still underrepresented in Earth science curriculae despite the increasing use of sometimes highly sophisticated simulation technologies in research projects. At the same time well-engineered community codes make it easy to return simulation-based results yet with the danger that the inherent traps of numerical solutions are not well understood. It is our belief that training with highly simplified numerical solutions (here to the equations describing elastic wave propagation) with carefully chosen elementary ingredients of simulation technologies (e.g., finite-differencing, function interpolation, spectral derivatives, numerical integration) could substantially improve this situation. For this purpose we have initiated a community platform (www.seismo-live.org) where Python-based Jupyter notebooks can be accessed and run without and necessary downloads or local software installations. The increasingly popular Jupyter notebooks allow combining markup language, graphics, equations with interactive, executable python codes. We demonstrate the potential with training notebooks for the finite-difference method, pseudospectral methods, finite/spectral element methods, the finite-volume and the discontinuous Galerkin method. The platform already includes general Python training, introduction to the ObsPy library for seismology as well as seismic data processing and noise analysis. Submission of Jupyter notebooks for general seismology are encouraged. The platform can be used for complementary teaching in Earth Science courses on compute-intensive research areas.

CMCpy: Genetic Code-Message Coevolution Models in Python

Science.gov (United States)

Becich, Peter J.; Stark, Brian P.; Bhat, Harish S.; Ardell, David H.

2013-01-01

Code-message coevolution (CMC) models represent coevolution of a genetic code and a population of protein-coding genes (“messages”). Formally, CMC models are sets of quasispecies coupled together for fitness through a shared genetic code. Although CMC models display plausible explanations for the origin of multiple genetic code traits by natural selection, useful modern implementations of CMC models are not currently available. To meet this need we present CMCpy, an object-oriented Python API and command-line executable front-end that can reproduce all published results of CMC models. CMCpy implements multiple solvers for leading eigenpairs of quasispecies models. We also present novel analytical results that extend and generalize applications of perturbation theory to quasispecies models and pioneer the application of a homotopy method for quasispecies with non-unique maximally fit genotypes. Our results therefore facilitate the computational and analytical study of a variety of evolutionary systems. CMCpy is free open-source software available from http://pypi.python.org/pypi/CMCpy/. PMID:23532367

ssbio: a Python framework for structural systems biology.

Science.gov (United States)

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

2018-06-15

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

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

Science.gov (United States)

England, Joseph R; Colletti, Patrick M

2018-06-01

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

Pylogeny: an open-source Python framework for phylogenetic tree reconstruction and search space heuristics

Directory of Open Access Journals (Sweden)

Alexander Safatli

2015-06-01

Full Text Available Summary. Pylogeny is a cross-platform library for the Python programming language that provides an object-oriented application programming interface for phylogenetic heuristic searches. Its primary function is to permit both heuristic search and analysis of the phylogenetic tree search space, as well as to enable the design of novel algorithms to search this space. To this end, the framework supports the structural manipulation of phylogenetic trees, in particular using rearrangement operators such as NNI, SPR, and TBR, the scoring of trees using parsimony and likelihood methods, the construction of a tree search space graph, and the programmatic execution of a few existing heuristic programs. The library supports a range of common phylogenetic file formats and can be used for both nucleotide and protein data. Furthermore, it is also capable of supporting GPU likelihood calculation on nucleotide character data through the BEAGLE library.Availability. Existing development and source code is available for contribution and for download by the public from GitHub (http://github.com/AlexSafatli/Pylogeny. A stable release of this framework is available for download through PyPi (Python Package Index at http://pypi.python.org/pypi/pylogeny.

MEG and EEG data analysis with MNE-Python

Directory of Open Access Journals (Sweden)

Alexandre eGramfort

2013-12-01

Full Text Available Magnetoencephalography and electroencephalography (M/EEG measure the weakelectromagnetic signals generated by neuronal activity in the brain. Using thesesignals to characterize and locate neural activation in the brain is achallenge that requires expertise in physics, signalprocessing, statistics, and numerical methods. As part of the MNE softwaresuite, MNE-Python is an open-sourcesoftware package that addresses this challenge by providingstate-of-the-art algorithms implemented in Python that cover multiple methods of data preprocessing, source localization, statistical analysis, and estimation offunctional 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 analysispipelines by writing Python scripts.Moreover, MNE-Python is tightly integrated with the core Python libraries for scientificcomptutation (Numpy, Scipy and visualization (matplotlib and Mayavi, as wellas the greater neuroimaging ecosystem in Python via the Nibabel package. The code is provided under the new BSD licenseallowing code reuse, even in commercial products. Although MNE-Python has onlybeen under heavy development for a couple of years, it has rapidly evolved withexpanded 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 ofmethods by other researchers. Full documentation, including dozens ofexamples, is available at http://martinos.org/mne.

Biopython: freely available Python tools for computational molecular biology and bioinformatics

DEFF Research Database (Denmark)

Cock, Peter J A; Antao, Tiago; Chang, Jeffrey T

2009-01-01

SUMMARY: The Biopython project is a mature open source international collaboration of volunteer developers, providing Python libraries for a wide range of bioinformatics problems. Biopython includes modules for reading and writing different sequence file formats and multiple sequence alignments......, dealing with 3D macro molecular structures, interacting with common tools such as BLAST, ClustalW and EMBOSS, accessing key online databases, as well as providing numerical methods for statistical learning. AVAILABILITY: Biopython is freely available, with documentation and source code at (www...

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

Science.gov (United States)

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

2014-09-09

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

Author Languages, Authoring Systems, and Their Relation to the Changing Focus of Computer-Aided Language Learning.

Science.gov (United States)

Sussex, Roland

1991-01-01

Considers how the effectiveness of computer-assisted language learning (CALL) has been hampered by language teachers who lack programing and software engineering expertise, and explores the limitations and potential contributions of author languages, programs, and environments in increasing the range of options for language teachers who are not…

Python for finance

CERN Document Server

Yan, Yuxing

2014-01-01

Python is a free and powerful tool which can be used to build a financial calculator and price options, and can also explain many trading strategies and test various hypotheses. In addition to that, real-world data can be used to run CAPM (Capital Asset Pricing Model), the Fama-French 3-factor model, estimate VaR (Value at Risk), and estimate spread, illiquidity, and liquidity. This book explores the basics of programming in Python. It is a step-by-step tutorial that will teach you, with the help of concise, practical programs, how to run various statistic tests. With this book, you will learn

On the Relationship between a Computational Natural Logic and Natural Language

DEFF Research Database (Denmark)

Andreasen, Troels; Bulskov, Henrik; Nilsson, Jørgen Fischer

2016-01-01

This paper makes a case for adopting appropriate forms of natural logic as target language for computational reasoning with descriptive natural language. Natural logics are stylized fragments of natural language where reasoning can be conducted directly by natural reasoning rules reflecting intui...... intuitive reasoning in natural language. The approach taken in this paper is to extend natural logic stepwise with a view to covering successively larger parts of natural language. We envisage applications for computational querying and reasoning, in particular within the life-sciences....

Brainlab: a Python toolkit to aid in the design, simulation, and analysis of spiking neural networks with the NeoCortical Simulator

Directory of Open Access Journals (Sweden)

Richard P Drewes

2009-05-01

Full Text Available 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 programmatictasks. 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 environment in particular. Brainlab is an integrated model building, experimentation, and data analysis environment for the powerful parallel spiking neural network simulator system NCS (the NeoCortical Simulator.

Creating and Viewing HTML Files with Python

OpenAIRE

William J. Turkel; Adam Crymble

2012-01-01

This lesson uses Python to create and view an HTML file. If you write programs that output HTML, you can use any browser to look at your results. This is especially convenient if your program is automatically creating hyperlinks or graphic entities like charts and diagrams. Here you will learn how to create HTML files with Python scripts, and how to use Python to automatically open an HTML file in Firefox.

A comparison of common programming languages used in bioinformatics.

Science.gov (United States)

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.

Thai Language Sentence Similarity Computation Based on Syntactic Structure and Semantic Vector

Science.gov (United States)

Wang, Hongbin; Feng, Yinhan; Cheng, Liang

2018-03-01

Sentence similarity computation plays an increasingly important role in text mining, Web page retrieval, machine translation, speech recognition and question answering systems. Thai language as a kind of resources scarce language, it is not like Chinese language with HowNet and CiLin resources. So the Thai sentence similarity research faces some challenges. In order to solve this problem of the Thai language sentence similarity computation. This paper proposes a novel method to compute the similarity of Thai language sentence based on syntactic structure and semantic vector. This method firstly uses the Part-of-Speech (POS) dependency to calculate two sentences syntactic structure similarity, and then through the word vector to calculate two sentences semantic similarity. Finally, we combine the two methods to calculate two Thai language sentences similarity. The proposed method not only considers semantic, but also considers the sentence syntactic structure. The experiment result shows that this method in Thai language sentence similarity computation is feasible.

From Computer Assisted Language Learning (CALL) to Mobile Assisted Language Use (MALU)

Science.gov (United States)

Jarvis, Huw; Achilleos, Marianna

2013-01-01

This article begins by critiquing the long-established acronym CALL (Computer Assisted Language Learning). We then go on to report on a small-scale study which examines how student non-native speakers of English use a range of digital devices beyond the classroom in both their first (L1) and second (L2) languages. We look also at the extent to…

BiEntropy for Python v. 1.0

Energy Technology Data Exchange (ETDEWEB)

2018-03-15

This Python package provides high-performance implementations of the functions and examples presented in "BiEntropy - The Approximate Entropy of a Finite Binary String" by Grenville J. Croll, presented at ANPA 34 in 2013. https://arxiv.org/abs/1305.0954 According to the paper, BiEntropy is "a simple algorithm which computes the approximate entropy of a finite binary string of arbitrary length" using "a weighted average of the Shannon Entropies of the string and all but the last binary derivative of the string."

Computational Nonlinear Morphology with Emphasis on Semitic Languages. Studies in Natural Language Processing.

Science.gov (United States)

Kiraz, George Anton

This book presents a tractable computational model that can cope with complex morphological operations, especially in Semitic languages, and less complex morphological systems present in Western languages. It outlines a new generalized regular rewrite rule system that uses multiple finite-state automata to cater to root-and-pattern morphology,…

MEG and EEG data analysis with MNE-Python.

Science.gov (United States)

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.

Computational Investigations of Multiword Chunks in Language Learning.

Science.gov (United States)

McCauley, Stewart M; Christiansen, Morten H

2017-07-01

Second-language learners rarely arrive at native proficiency in a number of linguistic domains, including morphological and syntactic processing. Previous approaches to understanding the different outcomes of first- versus second-language learning have focused on cognitive and neural factors. In contrast, we explore the possibility that children and adults may rely on different linguistic units throughout the course of language learning, with specific focus on the granularity of those units. Following recent psycholinguistic evidence for the role of multiword chunks in online language processing, we explore the hypothesis that children rely more heavily on multiword units in language learning than do adults learning a second language. To this end, we take an initial step toward using large-scale, corpus-based computational modeling as a tool for exploring the granularity of speakers' linguistic units. Employing a computational model of language learning, the Chunk-Based Learner, we compare the usefulness of chunk-based knowledge in accounting for the speech of second-language learners versus children and adults speaking their first language. Our findings suggest that while multiword units are likely to play a role in second-language learning, adults may learn less useful chunks, rely on them to a lesser extent, and arrive at them through different means than children learning a first language. Copyright © 2017 Cognitive Science Society, Inc.

Creating and Viewing HTML Files with Python

Directory of Open Access Journals (Sweden)

William J. Turkel

2012-07-01

Full Text Available This lesson uses Python to create and view an HTML file. If you write programs that output HTML, you can use any browser to look at your results. This is especially convenient if your program is automatically creating hyperlinks or graphic entities like charts and diagrams. Here you will learn how to create HTML files with Python scripts, and how to use Python to automatically open an HTML file in Firefox.

Building probabilistic graphical models with Python

CERN Document Server

Karkera, Kiran R

2014-01-01

This is a short, practical guide that allows data scientists to understand the concepts of Graphical models and enables them to try them out using small Python code snippets, without being too mathematically complicated. If you are a data scientist who knows about machine learning and want to enhance your knowledge of graphical models, such as Bayes network, in order to use them to solve real-world problems using Python libraries, this book is for you. This book is intended for those who have some Python and machine learning experience, or are exploring the machine learning field.

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

Science.gov (United States)

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.

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

Science.gov (United States)

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.

Experience in programming Assembly language of CDC CYBER 170/750 computer

International Nuclear Information System (INIS)

Caldeira, A.D.

1987-10-01

Aiming to optimize processing time of BCG computer code in the CDC CYBER 170/750 computer, the FORTRAN-V language of INTERP subroutine was converted to Assembly language. The BCG code was developed for solving neutron transport equation by iterative method, and the INTERP subroutine is innermost loop of the code carrying out 5 interpolation types. The central processor unit Assembly language of the CDC CYBER 170/750 computer and its application in implementing the interpolation subroutine of BCG code are described. (M.C.K.)

PyROOT: Seamless Melting of C++ and Python

CERN Multimedia

CERN. Geneva

2016-01-01

With ROOT it's possible to use any C++ library from Python without writing any bindings nor dictionaries: loading the library and injecting the relevant headers in the ROOT C++ interpreter is enough to guarantee interactive usage from within Python. Just in time (JIT) compilation of C++ code and immediate utilisation of C++ entities from within Python is also supported. Thanks to the ROOT type system and C++ interpreter and JIT compiler, complete Python/C++ interoperability is achieved. In this contribution we explain how this mechanism is general enough to make any library written in C or C++ usable from within Python and how concepts such as template metaprogramming are mapped in Python. We review the basics of the JIT compilation capabilities provided by the Clang based ROOT interpreter, Cling, and the way in which some of the information of the Abstract Syntax Tree (AST) built by Clang is stored by the ROOT type system. The way in which ROOT manages the automatic loading of libraries and parsing of neces...

Second-Language Composition Instruction, Computers and First-Language Pedagogy: A Descriptive Survey.

Science.gov (United States)

Harvey, T. Edward

1987-01-01

A national survey of full-time instructional faculty (N=208) at universities, 2-year colleges, and high schools regarding attitudes toward using computers in second-language composition instruction revealed a predomination of Apple and IBM-PC computers used, a major frustration in lack of foreign character support, and mixed opinions about real…

A high level language for a high performance computer

Science.gov (United States)

Perrott, R. H.

1978-01-01

The proposed computational aerodynamic facility will join the ranks of the supercomputers due to its architecture and increased execution speed. At present, the languages used to program these supercomputers have been modifications of programming languages which were designed many years ago for sequential machines. A new programming language should be developed based on the techniques which have proved valuable for sequential programming languages and incorporating the algorithmic techniques required for these supercomputers. The design objectives for such a language are outlined.

Design and Delivery of Multiple Server-Side Computer Languages Course

Science.gov (United States)

Wang, Shouhong; Wang, Hai

2011-01-01

Given the emergence of service-oriented architecture, IS students need to be knowledgeable of multiple server-side computer programming languages to be able to meet the needs of the job market. This paper outlines the pedagogy of an innovative course of multiple server-side computer languages for the undergraduate IS majors. The paper discusses…

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

Science.gov (United States)

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

2015-01-01

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

Python based high-level synthesis compiler

Science.gov (United States)

Cieszewski, Radosław; Pozniak, Krzysztof; Romaniuk, Ryszard

2014-11-01

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

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

Science.gov (United States)

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

2009-03-01

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

Linguistics, Computers, and the Language Teacher. A Communicative Approach.

Science.gov (United States)

Underwood, John H.

This analysis of the state of the art of computer programs and programming for language teaching has two parts. In the first part, an overview of the theory and practice of language teaching, Noam Chomsky's view of language, and the implications and problems of generative theory are presented. The theory behind the input model of language…

Computer-Aided Transformation of PDE Models: Languages, Representations, and a Calculus of Operations

Science.gov (United States)

2016-01-05

Computer-aided transformation of PDE models: languages, representations, and a calculus of operations A domain-specific embedded language called...languages, representations, and a calculus of operations Report Title A domain-specific embedded language called ibvp was developed to model initial...Computer-aided transformation of PDE models: languages, representations, and a calculus of operations 1 Vision and background Physical and engineered systems

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

Science.gov (United States)

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

Artificial intelligence, expert systems, computer vision, and natural language processing

Science.gov (United States)

Gevarter, W. B.

1984-01-01

An overview of artificial intelligence (AI), its core ingredients, and its applications is presented. The knowledge representation, logic, problem solving approaches, languages, and computers pertaining to AI are examined, and the state of the art in AI is reviewed. The use of AI in expert systems, computer vision, natural language processing, speech recognition and understanding, speech synthesis, problem solving, and planning is examined. Basic AI topics, including automation, search-oriented problem solving, knowledge representation, and computational logic, are discussed.

Cameo: A Python Library for Computer Aided Metabolic Engineering and Optimization of Cell Factories

DEFF Research Database (Denmark)

Cardoso, Joao G.R.; Jensen, Kristian; Lieven, Christian

2018-01-01

. It is written in Python and implements state-of-the-art methods for enumerating and prioritizing knock-out, knock-in, over-expression, and down-regulation strategies and combinations thereof. Cameo is an open source software project and is freely available under the Apache License 2.0. A dedicated website...

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

International Nuclear Information System (INIS)

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

2010-01-01

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

PetClaw: A scalable parallel nonlinear wave propagation solver for Python

KAUST Repository

Alghamdi, Amal; Ahmadia, Aron; Ketcheson, David I.; Knepley, Matthew; Mandli, Kyle; Dalcin, Lisandro

2011-01-01

We present PetClaw, a scalable distributed-memory solver for time-dependent nonlinear wave propagation. PetClaw unifies two well-known scientific computing packages, Clawpack and PETSc, using Python interfaces into both. We rely on Clawpack to provide the infrastructure and kernels for time-dependent nonlinear wave propagation. Similarly, we rely on PETSc to manage distributed data arrays and the communication between them.We describe both the implementation and performance of PetClaw as well as our challenges and accomplishments in scaling a Python-based code to tens of thousands of cores on the BlueGene/P architecture. The capabilities of PetClaw are demonstrated through application to a novel problem involving elastic waves in a heterogeneous medium. Very finely resolved simulations are used to demonstrate the suppression of shock formation in this system.

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

Science.gov (United States)

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

2016-01-01

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

Cross-language Babel structs—making scientific interfaces more efficient

International Nuclear Information System (INIS)

Prantl, Adrian; Epperly, Thomas G W; Ebner, Dietmar

2013-01-01

Babel is an open-source language interoperability framework tailored to the needs of high-performance scientific computing. As an integral element of the Common Component Architecture, it is employed in a wide range of scientific applications where it is used to connect components written in different programming languages. In this paper we describe how we extended Babel to support interoperable tuple data types (structs). Structs are a common idiom in (mono-lingual) scientific application programming interfaces (APIs); they are an efficient way to pass tuples of nonuniform data between functions, and are supported natively by most programming languages. Using our extended version of Babel, developers of scientific codes can now pass structs as arguments between functions implemented in any of the supported languages. In C, C++, Fortran 2003/2008 and Chapel, structs can be passed without the overhead of data marshaling or copying, providing language interoperability at minimal cost. Other supported languages are Fortran 77, Fortran 90/95, Java and Python. We will show how we designed a struct implementation that is interoperable with all of the supported languages and present benchmark data to compare the performance of all language bindings, highlighting the differences between languages that offer native struct support and an object-oriented interface with getter/setter methods. A case study shows how structs can help simplify the interfaces of scientific codes significantly. (paper)

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

DEFF Research Database (Denmark)

Christensen, Christian Bech; Christensen-Dalsgaard, Jakob; Brandt, Christian

2012-01-01

are sensitive to sound pressure and (2) snakes are sensitive to vibrations, but cannot hear the sound pressure per se. Vibration and sound-pressure sensitivities were quantified by measuring brainstem evoked potentials in 11 royal pythons, Python regius. Vibrograms and audiograms showed greatest sensitivity...... at low frequencies of 80-160 Hz, with sensitivities of -54 dB re. 1 m s(-2) and 78 dB re. 20 μPa, respectively. To investigate whether pythons detect sound pressure or sound-induced head vibrations, we measured the sound-induced head vibrations in three dimensions when snakes were exposed to sound...... pressure at threshold levels. In general, head vibrations induced by threshold-level sound pressure were equal to or greater than those induced by threshold-level vibrations, and therefore sound-pressure sensitivity can be explained by sound-induced head vibration. From this we conclude that pythons...

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

Science.gov (United States)

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

2011-09-01

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

Python-Assisted MODFLOW Application and Code Development

Science.gov (United States)

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.

Pygrass: An Object Oriented Python Application Programming Interface (API for Geographic Resources Analysis Support System (GRASS Geographic Information System (GIS

Directory of Open Access Journals (Sweden)

Marco Ciolli

2013-03-01

Full Text Available PyGRASS is an object-oriented Python Application Programming Interface (API for Geographic Resources Analysis Support System (GRASS Geographic Information System (GIS, a powerful open source GIS widely used in academia, commercial settings and governmental agencies. We present the architecture of the PyGRASS library, covering interfaces to GRASS modules, vector and raster data, with a focus on the new capabilities that it provides to GRASS users and developers. Our design concept of the module interface allows the direct linking of inputs and outputs of GRASS modules to create process chains, including compatibility checks, process control and error handling. The module interface was designed to be easily extended to work with remote processing services (Web Processing Service (WPS, Web Service Definition Language (WSDL/Simple Object Access Protocol (SOAP. The new object-oriented Python programming API introduces an abstract layer that opens the possibility to use and access transparently the efficient raster and vector functions of GRASS that are implemented in C. The design goal was to provide an easy to use, but powerful, Python interface for users and developers who are not familiar with the programming language C and with the GRASS C-API. We demonstrate the capabilities, scalability and performance of PyGRASS with several dedicated tests and benchmarks. We compare and discuss the results of the benchmarks with dedicated C implementations.

Python for probability, statistics, and machine learning

CERN Document Server

Unpingco, José

2016-01-01

This book covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules in these areas. The entire text, including all the figures and numerical results, is reproducible using the Python codes and their associated Jupyter/IPython notebooks, which are provided as supplementary downloads. The author develops key intuitions in machine learning by working meaningful examples using multiple analytical methods and Python codes, thereby connecting theoretical concepts to concrete implementations. Modern Python modules like Pandas, Sympy, and Scikit-learn are applied to simulate and visualize important machine learning concepts like the bias/variance trade-off, cross-validation, and regularization. Many abstract mathematical ideas, such as convergence in probability theory, are developed and illustrated with numerical examples. This book is suitable for anyone with an undergraduate-level exposure to probability, statistics, or machine learning and with rudimentary knowl...

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

Directory of Open Access Journals (Sweden)

Kristopher J. L. Irizarry

2016-01-01

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

A postmortem experience of Indian rock python (Python molurus molurus that swallowed a whole barking deer

Directory of Open Access Journals (Sweden)

Amam Zonaed Siddiki

2013-06-01

Full Text Available The object of this study was to report a post mortem findings of a female Indian Rock Python with a length of 406 cm (13.32 feet and approximate weight of 60 kg (including a whole deer that was swallowed by the python, that was brought to the Teaching Veterinary Hospital, Chittagong Veterinary and Animal Sciences University (CVASU by the Forest Department of Kumira Range Office, Chittagong. The local inhabitants accidently found the python at the forest area of Kumira and they frightenedly injured and killed the snake eventually. The postmortem (PM examination was performed according to standard protocols. Gross examination revealed bloody discharge was come out through mouth and a couple of skin lacerations observed on the right dorso-lateral part of the abdominal region. The whole barrel-shaped body cavity was opened and whole deer (partially decomposed was recovered from the stomach. Furthermore, three fractured ribs were found on right thorax. The PM examination team believes that the possible cause of python death was traumatic injury inflicted by the local people. [Vet World 2013; 6(3.000: 163-165

Foreign Language Teaching and the Computer.

Science.gov (United States)

Garrett, Nina, Ed.; Hart, Robert S., Ed.

1986-01-01

"Juegos comunicativos," a software program designed for use with the Apple IIe, IIc, or II+, emphasizes "communicative" computer-assisted Spanish language learning through five educational games. The program uses Spanish vocabulary and structures to solve "problems" rather than the standard drill-and-practice format.…

Integrating Computer-Assisted Language Learning in Saudi Schools: A Change Model

Science.gov (United States)

Alresheed, Saleh; Leask, Marilyn; Raiker, Andrea

2015-01-01

Computer-assisted language learning (CALL) technology and pedagogy have gained recognition globally for their success in supporting second language acquisition (SLA). In Saudi Arabia, the government aims to provide most educational institutions with computers and networking for integrating CALL into classrooms. However, the recognition of CALL's…

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

Science.gov (United States)

Ryerson, William G; Tan, Weimin

2017-08-01

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

When technology became language: the origins of the linguistic conception of computer programming, 1950-1960.

Science.gov (United States)

Nofre, David; Priestley, Mark; Alberts, Gerard

2014-01-01

Language is one of the central metaphors around which the discipline of computer science has been built. The language metaphor entered modern computing as part of a cybernetic discourse, but during the second half of the 1950s acquired a more abstract meaning, closely related to the formal languages of logic and linguistics. The article argues that this transformation was related to the appearance of the commercial computer in the mid-1950s. Managers of computing installations and specialists on computer programming in academic computer centers, confronted with an increasing variety of machines, called for the creation of "common" or "universal languages" to enable the migration of computer code from machine to machine. Finally, the article shows how the idea of a universal language was a decisive step in the emergence of programming languages, in the recognition of computer programming as a proper field of knowledge, and eventually in the way we think of the computer.

SYNCOM: A general syntax conversion language and computer program

International Nuclear Information System (INIS)

Bindon, D.C.

1972-09-01

The problems of syntax conversion are discussed and the reasons given for the choice of the Interpretive method. A full description is given of the SYNCON language and computer program together with brief details of some programs written in the language. (author)

Machine learning in Python essential techniques for predictive analysis

CERN Document Server

Bowles, Michael

2015-01-01

Learn a simpler and more effective way to analyze data and predict outcomes with Python Machine Learning in Python shows you how to successfully analyze data using only two core machine learning algorithms, and how to apply them using Python. By focusing on two algorithm families that effectively predict outcomes, this book is able to provide full descriptions of the mechanisms at work, and the examples that illustrate the machinery with specific, hackable code. The algorithms are explained in simple terms with no complex math and applied using Python, with guidance on algorithm selection, d

Neurolinguistics and psycholinguistics as a basis for computer acquisition of natural language

Energy Technology Data Exchange (ETDEWEB)

Powers, D.M.W.

1983-04-01

Research into natural language understanding systems for computers has concentrated on implementing particular grammars and grammatical models of the language concerned. This paper presents a rationale for research into natural language understanding systems based on neurological and psychological principles. Important features of the approach are that it seeks to place the onus of learning the language on the computer, and that it seeks to make use of the vast wealth of relevant psycholinguistic and neurolinguistic theory. 22 references.