def __init__(self,
cofactor_id_swaps=NADH_NADPH,
candidate_reactions=None,
skip_reactions=None,
*args,
**kwargs):
super(CofactorSwapOptimization, self).__init__(*args, **kwargs)
self._target_type = SWAP_TYPE
swap_pairs = ([
self.model.metabolites.get_by_id(m) for m in cofactor_id_swaps[0]
], [self.model.metabolites.get_by_id(m) for m in cofactor_id_swaps[1]])
self.metadata['swap_pairs'] = swap_pairs
self.representation = candidate_reactions or self.find_swappable_reactions(
self.model, swap_pairs)
if skip_reactions:
self.representation -= skip_reactions
self._decoder = decoders.ReactionSetDecoder(self.representation,
self.model)
self._evaluator = evaluators.SwapEvaluator(
model=self.model,
decoder=self._decoder,
objective_function=self.objective_function,
simulation_method=self._simulation_method,
simulation_kwargs=self._simulation_kwargs,
swap_pair=swap_pairs)
def __init__(self,
reactions=None,
essential_reactions=None,
use_nullspace_simplification=True,
*args,
**kwargs):
super(ReactionKnockoutOptimization, self).__init__(*args, **kwargs)
if reactions is None:
self.reactions = set([r.id for r in self.model.reactions])
else:
self.reactions = reactions
logger.debug("Computing essential reactions...")
if essential_reactions is None:
self.essential_reactions = set(
r.id
for r in find_essential_reactions(self.model, processes=1))
else:
self.essential_reactions = set([
r.id for r in find_essential_reactions(self.model, processes=1)
])
self.essential_reactions.update(essential_reactions)
if use_nullspace_simplification:
ns = nullspace(create_stoichiometric_array(self.model))
dead_ends = set(find_blocked_reactions_nullspace(self.model,
ns=ns))
exchanges = set(self.model.boundary)
reactions = [
r for r in self.model.reactions
if (r not in exchanges) and (r not in dead_ends) and (
r.id not in self.essential_reactions)
]
groups = find_coupled_reactions_nullspace(self.model, ns=ns)
groups_keys = [
set(group) for group in groups
if any(r.id in reactions for r in group)
]
reduced_set = reduce_reaction_set(reactions, groups_keys)
to_keep = [r.id for r in reduced_set]
else:
groups = None
to_keep = set(r.id for r in self.model.reactions)
to_keep.difference_update(r.id for r in self.model.boundary)
to_keep.difference_update(self.essential_reactions)
to_keep = list(to_keep)
self.representation = to_keep
self._target_type = REACTION_KNOCKOUT_TYPE
self._decoder = decoders.ReactionSetDecoder(self.representation,
self.model,
groups=groups)
self._evaluator = evaluators.KnockoutEvaluator(
model=self.model,
decoder=self._decoder,
objective_function=self.objective_function,
simulation_method=self._simulation_method,
simulation_kwargs=self._simulation_kwargs)
def __init__(self, reactions=None, essential_reactions=None, *args, **kwargs):
super(ReactionKnockoutOptimization, self).__init__(*args, **kwargs)
if reactions is None:
self.reactions = set([r.id for r in self.model.reactions])
else:
self.reactions = reactions
logger.debug("Computing essential reactions...")
if essential_reactions is None:
self.essential_reactions = set([r.id for r in self.model.essential_reactions()])
else:
self.essential_reactions = set([r.id for r in self.model.essential_reactions()] + essential_reactions)
exchange_reactions = set([r.id for r in self.model.exchanges])
self.representation = list(self.reactions.difference(self.essential_reactions).difference(exchange_reactions))
self._target_type = REACTION_KNOCKOUT_TYPE
self._decoder = decoders.ReactionSetDecoder(self.representation, self.model)
self._evaluator = evaluators.KnockoutEvaluator(model=self.model,
decoder=self._decoder,
objective_function=self.objective_function,
simulation_method=self._simulation_method,
simulation_kwargs=self._simulation_kwargs)