prepare.py
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	# -- coding: utf-8 --
	"""
	.. module:: skimpy
	:platform: Unix, Windows
	:synopsis: Simple Kinetic Models in Python

	.. moduleauthor:: SKiMPy team

	[---------]

	Copyright 2017 Laboratory of Computational Systems Biotechnology (LCSB),
	Ecole Polytechnique Federale de Lausanne (EPFL), Switzerland

	Licensed under the Apache License, Version 2.0 (the "License");
	you may not use this file except in compliance with the License.
	You may obtain a copy of the License at

	http://www.apache.org/licenses/LICENSE-2.0

	Unless required by applicable law or agreed to in writing, software
	distributed under the License is distributed on an "AS IS" BASIS,
	WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
	See the License for the specific language governing permissions and
	limitations under the License.

	"""
	from .utils import get_reduced_stoichiometry
	from skimpy.utils.tabdict import TabDict


	def prepare_mca(kinetic_model, **kwargs):

	# Better since this is implemented now
	all_variables = TabDict([(k,v.symbol) for k,v in kinetic_model.reactants.items()])

	#Get depedent variables (i.e. concentrations)
	reduced_stoichiometry, dependent_weights, independent_ix, dependent_ix = \
	get_reduced_stoichiometry(kinetic_model, all_variables)


	return reduced_stoichiometry,\
	dependent_weights,\
	independent_ix,\
	dependent_ix