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
