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

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26110%2F12%3APU100042" target="_blank" >RIV/00216305:26110/12:PU100042 - isvavai.cz</a>

Výsledek na webu

—

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

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

Popis výsledku v původním jazyce

This paper examines the feasibility of high-level Python based utilities for numerically intensive applications via an example of a multidimensional integration for the evaluation of the statistical characteristics of a random variable. We discuss the approaches to the implementation of mathematically formulated incremental expressions using high-level scripting code and low-level compiled code. Due to the dynamic typing of the Python language, components of the algorithm can be easily coded in a generic way as algorithmic templates. Using the Enthought Development Suite they can be effectively assembled into a flexible computational framework that can be configured to execute the code for arbitrary combinations of integration schemes and versions of instantiated code. The paper describes the development cycle using a simple running example involving averaging of a random two-parametric function that includes discontinuity. This example is also used to compare the performance of the av

Název v anglickém jazyce

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

Popis výsledku anglicky

This paper examines the feasibility of high-level Python based utilities for numerically intensive applications via an example of a multidimensional integration for the evaluation of the statistical characteristics of a random variable. We discuss the approaches to the implementation of mathematically formulated incremental expressions using high-level scripting code and low-level compiled code. Due to the dynamic typing of the Python language, components of the algorithm can be easily coded in a generic way as algorithmic templates. Using the Enthought Development Suite they can be effectively assembled into a flexible computational framework that can be configured to execute the code for arbitrary combinations of integration schemes and versions of instantiated code. The paper describes the development cycle using a simple running example involving averaging of a random two-parametric function that includes discontinuity. This example is also used to compare the performance of the av

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

JM - Inženýrské stavitelství

OECD FORD obor

—

Projekt

<a href="/cs/project/GAP105%2F11%2F1551" target="_blank" >GAP105/11/1551: Energetické a napjatostní aspekty kvazikřehkého lomu ? důsledky pro určování lomově-mechanických parametrů silikátových kompozitů</a><br>

Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2012

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

COMPUTER PHYSICS COMMUNICATIONS

ISSN

0010-4655

e-ISSN

—

Svazek periodika

184

Číslo periodika v rámci svazku

2

Stát vydavatele periodika

NL - Nizozemsko

Počet stran výsledku

14

Strana od-do

414-427

Kód UT WoS článku

—

EID výsledku v databázi Scopus

—