psamm.fastcore
– Fastcore (approximate consistent subset)¶
Fastcore module implementing the fastcore algorithm
This is an implementation of the algorithms described in [Vlassis14].
Use the functions fastcore()
and fastcc()
to easily apply
these algorithms to a MetabolicModel
.

exception
psamm.fastcore.
FastcoreError
¶ Indicates an error while running Fastcore

class
psamm.fastcore.
FastcoreProblem
(*args, **kwargs)¶ Represents a FastCore extension of a flux balance problem.
Accepts the same arguments as
FluxBalanceProblem
, and an additionalepsilon
keyword argument.Parameters:  model –
MetabolicModel
to solve.  solver – LP solver instance to use.
 epsilon – Flux threshold value.

find_sparse_mode
(core, additional, scaling, weights={})¶ Find a sparse mode containing reactions of the core subset.
Return an iterator of the support of a sparse mode that contains as many reactions from core as possible, and as few reactions from additional as possible (approximately). A dictionary of weights can be supplied which gives further penalties for including specific additional reactions.

flip
(reactions)¶ Flip the specified reactions.

is_flipped
(reaction)¶ Return true if reaction is flipped.

lp10
(subset_k, subset_p, weights={})¶ Force reactions in K above epsilon while minimizing support of P.
This program forces reactions in subset K to attain flux > epsilon while minimizing the sum of absolute flux values for reactions in subset P (L1regularization).

lp7
(reaction_subset)¶ Approximately maximize the number of reaction with flux.
This is similar to FBA but approximately maximizing the number of reactions in subset with flux > epsilon, instead of just maximizing the flux of one particular reaction. LP7 prefers “flux splitting” over “flux concentrating”.
 model –

psamm.fastcore.
fastcc
(model, epsilon, solver)¶ Check consistency of model reactions.
Yield all reactions in the model that are not part of the consistent subset.
Parameters:  model –
MetabolicModel
to solve.  epsilon – Flux threshold value.
 solver – LP solver instance to use.
 model –

psamm.fastcore.
fastcc_consistent_subset
(model, epsilon, solver)¶ Return consistent subset of model.
The largest consistent subset is returned as a set of reaction names.
Parameters:  model –
MetabolicModel
to solve.  epsilon – Flux threshold value.
 solver – LP solver instance to use.
Returns: Set of reaction IDs in the consistent reaction subset.
 model –

psamm.fastcore.
fastcc_is_consistent
(model, epsilon, solver)¶ Quickly check whether model is consistent
Return true if the model is consistent. If it is only necessary to know whether a model is consistent, this function is fast as it will return the result as soon as it finds a single inconsistent reaction.
Parameters:  model –
MetabolicModel
to solve.  epsilon – Flux threshold value.
 solver – LP solver instance to use.
 model –

psamm.fastcore.
fastcore
(model, core, epsilon, solver, scaling=100000.0, weights={})¶ Find a flux consistent subnetwork containing the core subset.
The result will contain the core subset and as few of the additional reactions as possible.
Parameters:  model –
MetabolicModel
to solve.  core – Set of core reaction IDs.
 epsilon – Flux threshold value.
 solver – LP solver instance to use.
 scaling – Scaling value to apply (see [Vlassis14] for more information on this parameter).
 weights – Dictionary with reaction IDs as keys and values as weights. Weights specify the cost of adding a reaction to the consistent subnetwork. Default value is 1.
Returns: Set of reaction IDs in the consistent reaction subset.
 model –