# -*- coding: utf-8 -*-
"""Helpers to interface with Matlab models."""
from __future__ import absolute_import
import re
from collections import OrderedDict
from uuid import uuid4
from warnings import warn
from numpy import array, inf, isinf
from numpy import object as np_object
from cobra.core import Metabolite, Model, Reaction
from cobra.util import create_stoichiometric_matrix
from cobra.util.solver import set_objective
try:
from scipy import io as scipy_io
from scipy import sparse as scipy_sparse
except ImportError:
scipy_io = None
# precompiled regular expressions
[docs]_bracket_re = re.compile(r"\[(?P<compartment>[a-z]+)\]$")
[docs]_underscore_re = re.compile(r"_(?P<compartment>[a-z]+)$")
[docs]def _get_id_compartment(id):
"""Extract the compartment from the id string."""
bracket_search = _bracket_re.search(id)
if bracket_search:
return bracket_search.group("compartment")
underscore_search = _underscore_re.search(id)
if underscore_search:
return underscore_search.group("compartment")
return None
[docs]def _cell(x):
"""Translate an array x into a MATLAB cell array."""
x_no_none = [i if i is not None else "" for i in x]
return array(x_no_none, dtype=np_object)
[docs]def load_matlab_model(infile_path, variable_name=None, inf=inf):
"""Load a cobra model stored as a .mat file.
Parameters
----------
infile_path: str
path to the file to to read
variable_name: str, optional
The variable name of the model in the .mat file. If this is not
specified, then the first MATLAB variable which looks like a COBRA
model will be used
inf: value
The value to use for infinite bounds. Some solvers do not handle
infinite values so for using those, set this to a high numeric value.
Returns
-------
cobra.core.Model.Model:
The resulting cobra model
"""
if not scipy_io:
raise ImportError("load_matlab_model requires scipy")
data = scipy_io.loadmat(infile_path)
possible_names = []
if variable_name is None:
# skip meta variables
meta_vars = {"__globals__", "__header__", "__version__"}
possible_names = sorted(i for i in data if i not in meta_vars)
if len(possible_names) == 1:
variable_name = possible_names[0]
if variable_name is not None:
return from_mat_struct(data[variable_name], model_id=variable_name, inf=inf)
for possible_name in possible_names:
try:
return from_mat_struct(data[possible_name], model_id=possible_name, inf=inf)
except ValueError:
pass
# If code here is executed, then no model was found.
raise IOError("no COBRA model found")
[docs]def save_matlab_model(model, file_name, varname=None):
"""Save the cobra model as a .mat file.
This .mat file can be used directly in the MATLAB version of COBRA.
Parameters
----------
model : cobra.core.Model.Model object
The model to save
file_name : str or file-like object
The file to save to
varname : string
The name of the variable within the workspace
"""
if not scipy_io:
raise ImportError("load_matlab_model requires scipy")
if varname is None:
varname = (
str(model.id)
if model.id is not None and len(model.id) > 0
else "exported_model"
)
mat = create_mat_dict(model)
scipy_io.savemat(file_name, {varname: mat}, appendmat=True, oned_as="column")
[docs]def create_mat_dict(model):
"""Create a dict mapping model attributes to arrays."""
rxns = model.reactions
mets = model.metabolites
mat = OrderedDict()
mat["mets"] = _cell([met_id for met_id in create_mat_metabolite_id(model)])
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")) * 1.0
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
rxn_gene = scipy_sparse.dok_matrix((len(model.reactions), len(model.genes)))
if min(rxn_gene.shape) > 0:
for i, reaction in enumerate(model.reactions):
for gene in reaction.genes:
rxn_gene[i, model.genes.index(gene)] = 1
mat["rxnGeneMat"] = rxn_gene
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"))
stoich_mat = create_stoichiometric_matrix(model)
mat["S"] = stoich_mat if stoich_mat 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")) * 1.0
mat["ub"] = array(rxns.list_attr("upper_bound")) * 1.0
mat["b"] = array(mets.list_attr("_bound")) * 1.0
mat["c"] = array(rxns.list_attr("objective_coefficient")) * 1.0
mat["rev"] = array(rxns.list_attr("reversibility")) * 1
mat["description"] = str(model.id)
return mat
[docs]def from_mat_struct(mat_struct, model_id=None, inf=inf):
"""Create a model from the COBRA toolbox struct.
The struct will be a dict read in by scipy.io.loadmat
"""
m = mat_struct
if m.dtype.names is None:
raise ValueError("not a valid mat struct")
if not {"rxns", "mets", "S", "lb", "ub"} <= set(m.dtype.names):
raise ValueError("not a valid mat struct")
if "c" in m.dtype.names:
c_vec = m["c"][0, 0]
else:
c_vec = None
warn("objective vector 'c' not found")
model = Model()
if model_id is not None:
model.id = model_id
elif "description" in m.dtype.names:
description = m["description"][0, 0][0]
if not isinstance(description, str) and len(description) > 1:
model.id = description[0]
warn("Several IDs detected, only using the first.")
else:
model.id = description
else:
model.id = "imported_model"
for i, name in enumerate(m["mets"][0, 0]):
new_metabolite = Metabolite()
new_metabolite.id = str(name[0][0])
if all(var in m.dtype.names for var in ["metComps", "comps", "compNames"]):
comp_index = m["metComps"][0, 0][i][0] - 1
new_metabolite.compartment = m["comps"][0, 0][comp_index][0][0]
if new_metabolite.compartment not in model.compartments:
comp_name = m["compNames"][0, 0][comp_index][0][0]
model.compartments[new_metabolite.compartment] = comp_name
else:
new_metabolite.compartment = _get_id_compartment(new_metabolite.id)
if new_metabolite.compartment not in model.compartments:
model.compartments[
new_metabolite.compartment
] = new_metabolite.compartment
try:
new_metabolite.name = str(m["metNames"][0, 0][i][0][0])
except (IndexError, ValueError):
pass
try:
new_metabolite.formula = str(m["metFormulas"][0][0][i][0][0])
except (IndexError, ValueError):
pass
try:
new_metabolite.charge = float(m["metCharge"][0, 0][i][0])
int_charge = int(new_metabolite.charge)
if new_metabolite.charge == int_charge:
new_metabolite.charge = int_charge
except (IndexError, ValueError):
pass
model.add_metabolites([new_metabolite])
new_reactions = []
coefficients = {}
for i, name in enumerate(m["rxns"][0, 0]):
new_reaction = Reaction()
new_reaction.id = str(name[0][0])
new_reaction.lower_bound = float(m["lb"][0, 0][i][0])
new_reaction.upper_bound = float(m["ub"][0, 0][i][0])
if isinf(new_reaction.lower_bound) and new_reaction.lower_bound < 0:
new_reaction.lower_bound = -inf
if isinf(new_reaction.upper_bound) and new_reaction.upper_bound > 0:
new_reaction.upper_bound = inf
if c_vec is not None:
coefficients[new_reaction] = float(c_vec[i][0])
try:
new_reaction.gene_reaction_rule = str(m["grRules"][0, 0][i][0][0])
except (IndexError, ValueError):
pass
try:
new_reaction.name = str(m["rxnNames"][0, 0][i][0][0])
except (IndexError, ValueError):
pass
try:
new_reaction.subsystem = str(m["subSystems"][0, 0][i][0][0])
except (IndexError, ValueError):
pass
new_reactions.append(new_reaction)
model.add_reactions(new_reactions)
set_objective(model, coefficients)
coo = scipy_sparse.coo_matrix(m["S"][0, 0])
for i, j, v in zip(coo.row, coo.col, coo.data):
model.reactions[j].add_metabolites({model.metabolites[i]: v})
return model
[docs]def _check(result):
"""Ensure success of a pymatbridge operation."""
if result["success"] is not True:
raise RuntimeError(result["content"]["stdout"])
[docs]def model_to_pymatbridge(model, variable_name="model", matlab=None):
"""Send the model to a MATLAB workspace through pymatbridge.
This model can then be manipulated through the COBRA toolbox
Parameters
----------
variable_name : str
The variable name to which the model will be assigned in the
MATLAB workspace
matlab : None or pymatbridge.Matlab instance
The MATLAB workspace to which the variable will be sent. If
this is None, then this will be sent to the same environment
used in IPython magics.
"""
if scipy_sparse is None:
raise ImportError("`model_to_pymatbridge` requires scipy!")
if matlab is None: # assumed to be running an IPython magic
from IPython import get_ipython
matlab = get_ipython().magics_manager.registry["MatlabMagics"].Matlab
model_info = create_mat_dict(model)
S = scipy_sparse.dok_matrix(model_info["S"])
model_info["S"] = 0
temp_S_name = "cobra_pymatbridge_temp_" + uuid4().hex
_check(matlab.set_variable(variable_name, model_info))
_check(matlab.set_variable(temp_S_name, S))
_check(matlab.run_code("%s.S = %s;" % (variable_name, temp_S_name)))
# all vectors need to be transposed
for i in model_info.keys():
if i == "S":
continue
_check(matlab.run_code("{0}.{1} = {0}.{1}';".format(variable_name, i)))
_check(matlab.run_code("clear %s;" % temp_S_name))