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#!/usr/bin/env python
##
## \file addingEvidenceCodes_1.py
## \brief adds controlled vocabulary terms to a reaction in a model
## \author Sarah Keating
##
## <!--------------------------------------------------------------------------
## This sample program is distributed under a different license than the rest
## of libSBML. This program uses the open-source MIT license, as follows:
##
## Copyright (c) 2013-2014 by the California Institute of Technology
## (California, USA), the European Bioinformatics Institute (EMBL-EBI, UK)
## and the University of Heidelberg (Germany), with support from the National
## Institutes of Health (USA) under grant R01GM070923. All rights reserved.
##
## Permission is hereby granted, free of charge, to any person obtaining a
## copy of this software and associated documentation files (the "Software"),
## to deal in the Software without restriction, including without limitation
## the rights to use, copy, modify, merge, publish, distribute, sublicense,
## and/or sell copies of the Software, and to permit persons to whom the
## Software is furnished to do so, subject to the following conditions:
##
## The above copyright notice and this permission notice shall be included in
## all copies or substantial portions of the Software.
##
## THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
## IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
## FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL
## THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
## LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
## FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER
## DEALINGS IN THE SOFTWARE.
##
## Neither the name of the California Institute of Technology (Caltech), nor
## of the European Bioinformatics Institute (EMBL-EBI), nor of the University
## of Heidelberg, nor the names of any contributors, may be used to endorse
## or promote products derived from this software without specific prior
## written permission.
## ------------------------------------------------------------------------ -->
import sys
import os.path
from libsbml import *
def main (args):
"""usage: addingEvidenceCodes_1 <input-filename> <output-filename>
Adds controlled vocabulary term to a reaction
"""
if len(args) != 3:
print(main.__doc__)
sys.exit(2)
d = readSBML(args[1]);
errors = d.getNumErrors();
if (errors > 0):
print("Read Error(s):\n");
d.printErrors();
print("Correct the above and re-run.\n");
else:
n = d.getModel().getNumReactions();
if (n <= 0):
print("Model has no reactions.\n Cannot add CV terms\n");
else:
r = d.getModel().getReaction(0);
# check that the reaction has a metaid
# no CVTerms will be added if there is no metaid to reference
#
if ( not r.isSetMetaId()):
r.setMetaId("metaid_0000052");
cv1 = CVTerm(BIOLOGICAL_QUALIFIER);
cv1.setBiologicalQualifierType(BQB_IS_DESCRIBED_BY);
cv1.addResource("urn:miriam:obo.eco:ECO%3A0000183");
r.addCVTerm(cv1);
cv2 = CVTerm(BIOLOGICAL_QUALIFIER);
cv2.setBiologicalQualifierType(BQB_IS);
cv2.addResource("urn:miriam:kegg.reaction:R00756");
cv2.addResource("urn:miriam:reactome:REACT_736");
r.addCVTerm(cv2);
writeSBML(d, args[2]);
return errors;
if __name__ == '__main__':
main(sys.argv)
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