def create_smatrix(cpids, rctnids, stm, obfunc):
"""Create the stiochiomatrix with the fba module"""
# Use stoichiometric Dictionary to create S matrix
# Preallocate size of array
st_mat = [[0.0] * len(rctnids) for i in cpids]
if verbose:
print(f"Number of total compounds: {len(cpids)}")
print(f"Number of total reactions: {len(rctnids)}")
print(
f"Stiochiomatrix dimensions before fill: {len(st_mat)} x {len(st_mat[0])}"
)
# Fill in S matrix
for cidx, c in enumerate(cpids):
for ridx, r in enumerate(rctnids):
try:
val = stm[c][r]
except KeyError:
val = 0.0
st_mat[cidx][ridx] = val
if verbose:
print(
f"Stiochiomatrix dimensions after fill: fill: {len(st_mat)} x {len(st_mat[0])}"
)
# Load the data
lp.load(st_mat, cpids, rctnids)
# Objective function
lp.objective_coefficients(obfunc)
return cpids, rctnids
def createSMatrix(cpdIds, rxnIds, sm, objFunc):
"""Create the SMatrix with the fba module"""
# Use stoichiometric Dictionary to create S matrix
# Preallocate size of array
SMat = [[0.0] * len(rxnIds) for i in cpdIds]
if verbose:
print "Number of total compounds: %d" % len(cpdIds)
print "Number of total reactions: %d" % len(rxnIds)
print "SMat dimensions before fill: %d x %d" % (len(SMat), len(
SMat[0]))
# Fill in S matrix
for cIdx, c in enumerate(cpdIds):
for rIdx, r in enumerate(rxnIds):
try:
val = sm[c][r]
except KeyError:
val = 0.0
SMat[cIdx][rIdx] = val
if verbose:
print "SMat dimensions after fill: %d x %d" % (len(SMat), len(SMat[0]))
# Load the data
lp.load(SMat, cpdIds, rxnIds)
# Objective function
lp.objective_coefficients(objFunc)
return cpdIds, rxnIds
def createSMatrix(cpdIds, rxnIds, sm, objFunc):
"""Create the SMatrix with the fba module"""
# Use stoichiometric Dictionary to create S matrix
# Preallocate size of array
SMat = [[0.0] * len(rxnIds) for i in cpdIds]
if verbose:
print "Number of total compounds: %d" % len(cpdIds)
print "Number of total reactions: %d" % len(rxnIds)
print "SMat dimensions before fill: %d x %d" % (len(SMat),
len(SMat[0]))
# Fill in S matrix
for cIdx, c in enumerate(cpdIds):
for rIdx, r in enumerate(rxnIds):
try:
val = sm[c][r]
except KeyError:
val = 0.0
SMat[cIdx][rIdx] = val
if verbose:
print "SMat dimensions after fill: %d x %d" % (len(SMat), len(SMat[0]))
# Load the data
lp.load(SMat, cpdIds, rxnIds)
# Objective function
lp.objective_coefficients(objFunc)
return cpdIds, rxnIds
def test_matrix(self):
"""Just initialize with a simple matrix"""
mat = [
[1, 2, 3, 4],
[5, 6, 7, 8],
[9, 10, 11, 12]
]
lp.load(mat)
def test_objective_coeff(self):
"""Test adding the objective coefficients. Note that there
should be as many coefficients as columns in the matrix."""
mat = [
[ 1.0, 1.0, 1.0],
[10.0, 4.0, 5.0],
[ 2.0, 2.0, 6.0],
[ 2.0, 2.0, 6.0],
]
lp.load(mat)
lp.objective_coefficients([ 10.0, 6.0, 4.0 ])
def test_solve(self):
"""Test the complete linear programing solution, using the
example from the documentation"""
mat = [
[ 1.0, 1.0, 1.0],
[10.0, 4.0, 5.0],
[ 2.0, 2.0, 6.0],
]
lp.load(mat)
lp.objective_coefficients([ 10.0, 6.0, 4.0 ])
lp.row_bounds([(None, 100.0), (None, 600.0), (None, 300.0)])
lp.col_bounds([(0, None), (0, None), (0, None)])
status, result = lp.solve()
r = "%0.3f" % result
self.assertEqual(r, "733.333")
self.assertEqual(status, 'opt')
def test_bound_cols(self):
"""Test adding tuples of boundary conditions for columns"""
mat = [
[1, 2, 3, 4],
[5, 6, 7, 8],
[9, 10, 11, 12]
]
lp.load(mat)
boundsc = []
# test that we don't have enough values
self.assertRaises(ValueError, lp.col_bounds, boundsc)
# a boundary of None should be infiniity!
boundsc = [(None, 1000), (1000, None), (1000, 1000), (None, None)]
lp.col_bounds(boundsc)
def test_primals(self):
"""Test getting the primals back as a list"""
mat = [
[ 1.0, 1.0, 1.0],
[10.0, 4.0, 5.0],
[ 2.0, 2.0, 6.0],
]
rh = ['a', 'b', 'c']
ch = ['x', 'y', 'z']
lp.load(mat, rh, ch)
lp.objective_coefficients([ 10.0, 6.0, 4.0 ])
lp.row_bounds([(None, 100.0), (None, 600.0), (None, 300.0)])
lp.col_bounds([(0, None), (0, None), (0, None)])
status, result = lp.solve()
col_pri = [33.333333333333336, 66.66666666666666, 0.0]
col_res = lp.col_primals()
self.assertEqual(col_pri, col_res)
def test_col_bounds(self):
'''Testing the assertion of column bounds'''
# define an FBA matrix of the right size
newfba = lp.load([[1, 2, 3, 4, 5, 6], [1, 2, 3, 4, 5, 6], [1, 2, 3, 4, 5, 6]])
ca = PyFBA.metabolism.Compound("A", "e")
cb = PyFBA.metabolism.Compound("B", "c")
cc = PyFBA.metabolism.Compound("C", "h")
compounds = {ca, cb, cc}
col_bounds = PyFBA.fba.compound_bounds(compounds)
self.assertEqual(col_bounds[ca], (0, 0))
self.assertEqual(col_bounds[cb], (0, 0))
self.assertEqual(col_bounds[cc], (0, 0))
def test_headers(self):
"""Test adding headers to the rows and columns"""
mat = [
[1, 2, 3, 4],
[5, 6, 7, 8],
[9, 10, 11, 12]
]
rh = ['a', 'b', 'c']
ch = ['w', 'x', 'y', 'z']
lp.load(mat, rh, ch)
rh.append('should fail')
self.assertRaises(ValueError, lp.load, mat, rh, ch)
rh = ['a', 'b', 'c']
lp.load(mat, rh, ch)
ch.append("also should fail")
self.assertRaises(ValueError, lp.load, mat, rh, ch)
def test_row_bounds(self):
'''Testing the assertion of row bounds and the logic'''
# define a media compound
media_compound = PyFBA.metabolism.CompoundWithLocation(
"m0011", 'Media', 'e')
media = {media_compound}
# define an FBA matrix of the right size
newfba = lp.load([[1, 2, 3, 4, 5, 6]])
# make up some reactions
ra = PyFBA.metabolism.Reaction('rA', 'reaction A')
ra.direction = '>'
rb = PyFBA.metabolism.Reaction('rB', 'reaction B')
rb.direction = '<'
rc = PyFBA.metabolism.Reaction('rC', 'reaction C')
rc.direction = '='
rd = PyFBA.metabolism.Reaction('rUS', 'reaction US')
rd.direction = '='
rd.is_uptake_secretion = True
re = PyFBA.metabolism.Reaction('biomass_equation', 'biomass_equation')
re.direction = '>'
rf = PyFBA.metabolism.Reaction('rUSM', 'reaction US Media')
rf.direction = '='
rf.is_uptake_secretion = True
rf.add_left_compounds({media_compound})
# test our reactions
all_reactions = {ra: ra, rb: rb, rc: rc, rd: rd, re: re, rf: rf}
reactions2run = set(all_reactions.keys())
rbvals = PyFBA.fba.reaction_bounds(all_reactions, reactions2run, media)
self.assertEqual(rbvals[ra], (0, 1000))
self.assertEqual(rbvals[rb], (-1000, 1000))
self.assertEqual(rbvals[rc], (-1000, 1000))
self.assertEqual(rbvals[rd], (0, 1000))
self.assertEqual(rbvals[re], (0, 1000))
self.assertEqual(rbvals[rf], (-1000, 1000))
def test_row_bounds(self):
'''Testing the assertion of row bounds and the logic'''
# define a media compound
media_compound = PyFBA.metabolism.Compound('Media', 'e')
media = {media_compound}
# define an FBA matrix of the right size
newfba = lp.load([[1,2,3,4,5,6]])
# make up some reactions
ra = PyFBA.metabolism.Reaction('reaction A')
ra.direction = '>'
rb = PyFBA.metabolism.Reaction('reaction B')
rb.direction = '<'
rc = PyFBA.metabolism.Reaction('reaction C')
rc.direction = '='
rd = PyFBA.metabolism.Reaction('reaction US')
rd.direction = '='
rd.is_uptake_secretion = True
re = PyFBA.metabolism.Reaction('biomass_equation')
re.direction = '>'
rf = PyFBA.metabolism.Reaction('reaction US Media')
rf.direction = '='
rf.is_uptake_secretion = True
rf.add_left_compounds({media_compound})
# test our reactions
all_reactions = {ra: ra, rb: rb, rc: rc, rd: rd, re: re, rf: rf}
reactions2run = set(all_reactions.keys())
rbvals = PyFBA.fba.reaction_bounds(all_reactions, reactions2run, media)
self.assertEqual(rbvals[ra], (0, 1000))
self.assertEqual(rbvals[rb], (-1000, 1000))
self.assertEqual(rbvals[rc], (-1000, 1000))
self.assertEqual(rbvals[rd], (0, 1000))
self.assertEqual(rbvals[re], (0, 1000))
self.assertEqual(rbvals[rf], (-1000, 1000))
