def create_mat_dict(model):
"""create a dict mapping model attributes to arrays"""
model = model.to_array_based_model()
rxns = model.reactions
mets = model.metabolites
mat = dicttype()
mat["mets"] = _cell(mets.list_attr("id"))
mat["metNames"] = _cell(mets.list_attr("name"))
mat["metFormulas"] = _cell([str(m.formula) for m in mets])
mat["genes"] = _cell(model.genes.list_attr("id"))
mat["grRules"] = _cell(rxns.list_attr("gene_reaction_rule"))
mat["rxns"] = _cell(rxns.list_attr("id"))
mat["rxnNames"] = _cell(rxns.list_attr("name"))
mat["subSystems"] = _cell(rxns.list_attr("subsystem"))
mat["csense"] = "".join(model._constraint_sense)
mat["S"] = model.S
# multiply by 1 to convert to float, working around scipy bug
# https://github.com/scipy/scipy/issues/4537
mat["lb"] = array(rxns.list_attr("lower_bound")) * 1.
mat["ub"] = array(rxns.list_attr("upper_bound")) * 1.
mat["b"] = array(mets.list_attr("_bound")) * 1.
mat["c"] = array(rxns.list_attr("objective_coefficient")) * 1.
mat["rev"] = array(rxns.list_attr("reversibility")) * 1
mat["description"] = str(model.description)
return mat
def create_mat_dict(model):
"""create a dict mapping model attributes to arrays"""
model = model.to_array_based_model()
rxns = model.reactions
mets = model.metabolites
mat = dicttype()
mat["mets"] = _cell(mets.list_attr("id"))
mat["metNames"] = _cell(mets.list_attr("name"))
mat["metFormulas"] = _cell([str(m.formula) for m in mets])
mat["genes"] = _cell(model.genes.list_attr("id"))
mat["grRules"] = _cell(rxns.list_attr("gene_reaction_rule"))
mat["rxns"] = _cell(rxns.list_attr("id"))
mat["rxnNames"] = _cell(rxns.list_attr("name"))
mat["subSystems"] = _cell(rxns.list_attr("subsystem"))
mat["csense"] = "".join(model._constraint_sense)
mat["S"] = model.S
# multiply by 1 to convert to float, working around scipy bug
# https://github.com/scipy/scipy/issues/4537
mat["lb"] = array(rxns.list_attr("lower_bound")) * 1.
mat["ub"] = array(rxns.list_attr("upper_bound")) * 1.
mat["b"] = array(mets.list_attr("_bound")) * 1.
mat["c"] = array(rxns.list_attr("objective_coefficient")) * 1.
mat["rev"] = array(rxns.list_attr("reversibility")) * 1
mat["description"] = str(model.description)
return mat
def save_matlab_model(model, file_name):
"""Save the cobra model as a .mat file.
This .mat file can be used directly in the MATLAB version of COBRA.
model : :class:`~cobra.core.Model.Model` object
file_name : str or file-like object
"""
model = model.to_array_based_model()
rxns = model.reactions
mets = model.metabolites
mat = dicttype()
csense = ""
for m in mets:
csense += m._constraint_sense
mat["mets"] = _cell(mets.list_attr("id"))
mat["metNames"] = _cell(mets.list_attr("name"))
mat["metFormulas"] = _cell([str(m.formula) for m in mets])
mat["genes"] = _cell(model.genes.list_attr("id"))
mat["grRules"] = _cell(rxns.list_attr("gene_reaction_rule"))
mat["rxns"] = _cell(rxns.list_attr("id"))
mat["rxnNames"] = _cell(rxns.list_attr("name"))
mat["subSystems"] = _cell(rxns.list_attr("subsystem"))
mat["csense"] = csense
mat["S"] = model.S
mat["lb"] = array(rxns.list_attr("lower_bound"))
mat["ub"] = array(rxns.list_attr("upper_bound"))
mat["b"] = array(mets.list_attr("_bound"))
mat["c"] = array(rxns.list_attr("objective_coefficient"))
mat["rev"] = array(rxns.list_attr("reversibility"))
mat["description"] = str(model.description)
savemat(file_name, {str(model.description): mat},
appendmat=True, oned_as="column")
def create_mat_dict(model):
"""create a dict mapping model attributes to arrays"""
model = model.to_array_based_model()
rxns = model.reactions
mets = model.metabolites
mat = dicttype()
mat["mets"] = _cell(mets.list_attr("id"))
mat["metNames"] = _cell(mets.list_attr("name"))
mat["metFormulas"] = _cell([str(m.formula) for m in mets])
try:
mat["metCharge"] = array(mets.list_attr("charge")) * 1.
except TypeError:
# can't have any None entries for charge, or this will fail
pass
mat["genes"] = _cell(model.genes.list_attr("id"))
# make a matrix for rxnGeneMat
# reactions are rows, genes are columns
rxnGene = dok_matrix((len(model.reactions), len(model.genes)))
if min(rxnGene.shape) > 0:
for i, reaction in enumerate(model.reactions):
for gene in reaction.genes:
rxnGene[i, model.genes.index(gene)] = 1
mat["rxnGeneMat"] = rxnGene
mat["grRules"] = _cell(rxns.list_attr("gene_reaction_rule"))
mat["rxns"] = _cell(rxns.list_attr("id"))
mat["rxnNames"] = _cell(rxns.list_attr("name"))
mat["subSystems"] = _cell(rxns.list_attr("subsystem"))
mat["csense"] = "".join(model._constraint_sense)
mat["S"] = model.S if model.S is not None else [[]]
# multiply by 1 to convert to float, working around scipy bug
# https://github.com/scipy/scipy/issues/4537
mat["lb"] = array(rxns.list_attr("lower_bound")) * 1.
mat["ub"] = array(rxns.list_attr("upper_bound")) * 1.
mat["b"] = array(mets.list_attr("_bound")) * 1.
mat["c"] = array(rxns.list_attr("objective_coefficient")) * 1.
mat["rev"] = array(rxns.list_attr("reversibility")) * 1
mat["description"] = str(model.id)
return mat
def save_matlab_model(model, file_name):
"""Save the cobra model as a .mat file.
This .mat file can be used directly in the MATLAB version of COBRA.
.. note:: This function works best with scipy 0.11b1 or later
Parameters
----------
model : cobra.Model
file_name : str or file-like object
"""
model = model.to_array_based_model()
rxns = model.reactions
mets = model.metabolites
mat = dicttype()
csense = ""
for m in mets:
csense += m._constraint_sense
mat["mets"] = _cell(mets.list_attr("id"))
mat["metNames"] = _cell(mets.list_attr("name"))
mat["metFormulas"] = _cell([str(m.formula) for m in mets])
mat["genes"] = _cell(model.genes.list_attr("id"))
mat["grRules"] = _cell(rxns.list_attr("gene_reaction_rule"))
mat["rxns"] = _cell(rxns.list_attr("id"))
mat["rxnNames"] = _cell(rxns.list_attr("name"))
mat["subSystems"] = _cell(rxns.list_attr("subsystem"))
mat["csense"] = csense
mat["S"] = model.S
mat["lb"] = array(rxns.list_attr("lower_bound"))
mat["ub"] = array(rxns.list_attr("upper_bound"))
mat["b"] = array(mets.list_attr("_bound"))
mat["c"] = array(rxns.list_attr("objective_coefficient"))
mat["rev"] = array(rxns.list_attr("reversibility"))
mat["description"] = str(model.description)
savemat(file_name, {str(model.description): mat},
appendmat=True, oned_as="column")
