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Title: Model Analysis ToolKit

Abstract

MATK provides basic functionality to facilitate model analysis within the Python computational environment. Model analysis setup within MATK includes: - define parameters - define observations - define model (python function) - define samplesets (sets of parameter combinations) Currently supported functionality includes: - forward model runs - Latin-Hypercube sampling of parameters - multi-dimensional parameter studies - parallel execution of parameter samples - model calibration using internal Levenberg-Marquardt algorithm - model calibration using lmfit package - model calibration using levmar package - Markov Chain Monte Carlo using pymc package MATK facilitates model analysis using: - scipy - calibration (scipy.optimize) - rpy2 - Python interface to R

Authors:
Publication Date:
Research Org.:
Los Alamos National Laboratory
Sponsoring Org.:
USDOE
OSTI Identifier:
1232133
Report Number(s):
MATK; 003429MLTPL00
C14023; LA-CC-13-132
DOE Contract Number:  
AC52-06NA25396
Resource Type:
Software
Software Revision:
00
Software Package Number:
003429
Software Package Contents:
Open Source Software package available from Los Alamos National Laboratory at the following URL: https://github.com/dharp/MATK
Software CPU:
MLTPL
Open Source:
Yes
Source Code Available:
Yes
Country of Publication:
United States

Citation Formats

Harp, Dylan R. Model Analysis ToolKit. Computer software. https://www.osti.gov//servlets/purl/1232133. Vers. 00. USDOE. 15 May. 2015. Web.
Harp, Dylan R. (2015, May 15). Model Analysis ToolKit (Version 00) [Computer software]. https://www.osti.gov//servlets/purl/1232133.
Harp, Dylan R. Model Analysis ToolKit. Computer software. Version 00. May 15, 2015. https://www.osti.gov//servlets/purl/1232133.
@misc{osti_1232133,
title = {Model Analysis ToolKit, Version 00},
author = {Harp, Dylan R.},
abstractNote = {MATK provides basic functionality to facilitate model analysis within the Python computational environment. Model analysis setup within MATK includes: - define parameters - define observations - define model (python function) - define samplesets (sets of parameter combinations) Currently supported functionality includes: - forward model runs - Latin-Hypercube sampling of parameters - multi-dimensional parameter studies - parallel execution of parameter samples - model calibration using internal Levenberg-Marquardt algorithm - model calibration using lmfit package - model calibration using levmar package - Markov Chain Monte Carlo using pymc package MATK facilitates model analysis using: - scipy - calibration (scipy.optimize) - rpy2 - Python interface to R},
url = {https://www.osti.gov//servlets/purl/1232133},
doi = {},
year = {2015},
month = {5},
note =
}