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convertQuesoMFileToTxt.py
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convertQuesoMFileToTxt.py
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"""
-----------------------------------------------------------------------bl-
--------------------------------------------------------------------------
QUESO - a library to support the Quantification of Uncertainty
for Estimation, Simulation and Optimization
Copyright (C) 2008,2009,2010,2011,2012,2013 The PECOS Development Team
This library is free software; you can redistribute it and/or
modify it under the terms of the Version 2.1 GNU Lesser General
Public License as published by the Free Software Foundation.
This library is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
Lesser General Public License for more details.
You should have received a copy of the GNU Lesser General Public
License along with this library; if not, write to the Free Software
Foundation, Inc. 51 Franklin Street, Fifth Floor,
Boston, MA 02110-1301 USA
-----------------------------------------------------------------------el-
This module contains a utility funtion, convertMFile, for converting m-files
generated by QUESO into regular text. See the convertMFile help string for more
specific information on usage and output. Conversion can also be accomplished
by invoking convertQuesoMFileToTxt.py on the command line. In this case,
the script will parse a list of input m-files and create text file output
for each m-file. The script separates the chain data, likelihood data, and
target data into separate output files. For more information on the command
version, run: python convertQuesoMFileToTxt.py --help
"""
import re
import sys
def convertMFile(mFileName, getChain=True, getLike=True,
getTarget=True, chainIdent='[cC]hain',
likeIdent='[lL]ikelihood', targetIdent='[tT]arget'):
"""
This function parses chain, likelihood, and target data from a single m-file.
mFileName specifies the name of m-file to parse. The get{Chain,Like,Target}
optional inputs take boolean values indicating if the function should parse
that particular item from the file. The {chain,like,target}Ident optional
inputs allow the user to specify a regular expression that identifies that
particular item in the m-file. This function returns a dictionary
containing keys, 'chain', 'logLikelihood', and 'logTarget'. The value
associated with a particular key is the data for that item in character
string format. If the data for an item cannot be found in the file, the
key for that item will not be present in the dictionary.
"""
# tokens delimiting the data
dataEncloseTokens = ('[', ']')
# Read file into string buffer
fIn = open(mFileName,'r')
fileBuf = fIn.read()
fIn.close()
outputMap = dict()
parseMap = {'chain': (getChain, chainIdent), 'logLikelihood': (getLike, likeIdent),
'logTarget': (getTarget, targetIdent)}
# iterate over wanted items and parse them from the buffer
for item in parseMap:
if parseMap[item][0] == False:
continue
# Find tag for current item via search with regex: identString\w*\s*=\s*(?=\[)
parseTagRegEx = parseMap[item][1] + r'\w*\s*=\s*' + '(?=' + re.escape(dataEncloseTokens[0]) + ')'
match = re.search(parseTagRegEx, fileBuf)
tag = ''
if match:
tag = match.group(0) + re.escape(dataEncloseTokens[0])
else:
print 'Error: Could not find identifier {0} in {1}. Regex string: {2}'.format(item, mFileName, parseTagRegEx)
return outputMap
# Extract current item data between [ ] via search with regex: (?<=tag)[^\]]+
parseDataRegEx = '(?<=' + tag + ')[^' + re.escape(dataEncloseTokens[1]) + ']+'
match = re.search(parseDataRegEx, fileBuf)
if match:
outputMap[item] = match.group(0)
else:
print 'Error: Could not find {0} data in {1}. Regex string: {2}'.format(item, mFileName, parseDataRegEx)
return outputMap
return outputMap
if __name__ == "__main__":
import argparse
parser = argparse.ArgumentParser(description='Convert a list of m-files generated by QUESO into text files.')
parser.add_argument('-c', '--chain', type=str, choices=['yes','no'], default='yes',
help='Parse chain data from m-file (default: yes)')
parser.add_argument('-l', '--likelihood', type=str, choices=['yes','no'], default='yes',
help='Parse likelihood data from m-file (default: yes)')
parser.add_argument('-t', '--target', type=str, choices=['yes','no'], default='yes',
help='Parse target data from m-file (default: yes)')
parser.add_argument('-ci', '--chain_identifier', type=str, default='[cC]hain',
help='RegEx string identifying chain entry in the m-file (default: [cC]hain)')
parser.add_argument('-li', '--likelihood_identifier', type=str, default='[lL]ikelihood',
help='RegEx string identifying likelihood entry in the m-file (default: [lL]ikelihood)')
parser.add_argument('-ti', '--target_identifier', type=str, default='[tT]arget',
help='RegEx string identifying target entry in the m-file (default: [tT]arget)')
parser.add_argument('mFileList', nargs='+', help='List of m-files to convert')
args = parser.parse_args()
if args.chain == 'yes':
getChainOpt = True
else:
getChainOpt = False
if args.likelihood == 'yes':
getLikeOpt = True
else:
getLikeOpt = False
if args.target == 'yes':
getTargetOpt = True
else:
getTargetOpt = False
# process files one-by-one
for mFileName in args.mFileList:
outputMap = convertMFile(mFileName, getChain=getChainOpt, getLike=getLikeOpt, getTarget=getTargetOpt, \
chainIdent=args.chain_identifier, likeIdent=args.likelihood_identifier, \
targetIdent=args.target_identifier)
# Write the data out to text files
mFileNameBase = mFileName.rstrip('.m')
for item in outputMap:
outFileName = mFileNameBase + '_' + item + '.txt'
fOut = open(outFileName, 'w')
fOut.write(outputMap[item])
fOut.close()
print 'Created file {0}...'.format(outFileName)