def __prepareProblem(self, lp):
"""Prepares the lp construct for analysis
Transposes the stoichiometric matrix S_ij -> S^T
Columns(Reactions) become rows and rows(Metabolites) become columns
Previous column, now row bounds are set to 0
Previous row, now column bounds are set to > 0
"""
oldProb = Metabolism(lp)
biomR = [r for r in oldProb.getColumnIDs() if re.search(".*.*", r, re.IGNORECASE)][0]
print biomR
oldProb.deleteReactionsFromStoich([biomR])
oldProb.eraseHistory()
newProb = Metabolism(glp_create_prob())
for elem in range(1, oldProb.getNumCols() + 1):
columnsDict = dict()
identifier = glp_get_col_name(oldProb.lp, elem)
colCoefList = oldProb.getColumnCoef(elem)
columnsDict[identifier] = (0, 0, colCoefList)
newProb.addRows(columnsDict)
for elem in range(1, oldProb.getNumRows() + 1):
rowsDict = dict()
identifier = glp_get_row_name(oldProb.lp, elem)
rowCoefList = oldProb.getRowCoef(elem)
rowsDict[identifier] = (0, 10000, rowCoefList)
newProb.addColumns(rowsDict)
newProb.eraseHistory()
return newProb.lp
Copyright (c) 2010 . All rights reserved.
"""
import sys
import os
if __name__ == '__main__':
from ifba.GlpkWrap.metabolism import Metabolism
from ifba.GlpkWrap.util import ImportCplex, WriteCplex
from ifba.fluxVariability.fluxVariability import Variability
import random
import pickle
lp = Metabolism(ImportCplex('../../ifba/models/iAF1260template_minimalMed_noCarb.lp'))
print len(lp.getColumnIDs())
lp.modifyColumnBounds({'R("MglcDb_Transp")':(0, 20), 'R("Mo2b_Transp")':(-20, 20)})
lp.modifyColumnBounds({'R("R_Ec_biomass_iAF1260_core_59p81M")': (1., 100.)})
lp.eraseHistory()
if os.path.exists('blocked.pcl'):
blocked = pickle.load(open('blocked.pcl'))
else:
# blocked = Variability(lp).getBlocked(['R("R_Ec_biomass_iAF1260_core_59p81M")', 'R("R_AGPR")'])
blocked = Variability(lp).getBlocked()
sys.exit()
pickle.dump(blocked, open('blocked.pcl', 'w'))
print blocked
print len(blocked)
lp.deleteReactionsFromStoich(blocked)
lp.eraseHistory()
ids = list(set(lp.getColumnIDs()) - set(lp.getTransporters()))
