8.1.1.1.1.5. skimpy.analysis.oracle

[———]

Copyright 2018 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.

8.1.1.1.1.5.1. Submodules

8.1.1.1.1.5.2. Attributes

BIGM

BIGM_THERMO

BIGM_DG

BIGM_P

EPSILON

MAX_STOICH

BIGM

BIGM_THERMO

BIGM_DG

BIGM_P

EPSILON

MIN_C

MAX_C

BIGM

EPSILON

LOG

LIN

8.1.1.1.1.5.3. Classes

MinFLuxVariable

Class to represent a negative slack variable for relaxation problems

MinFLux

Class to represent thermodynamics constraints.

ParameterValues

Parameters set for kinetic models wich can be indexed with symbols or

BinUseVariable

BinVariable

FluxRatioCons

Class to represent thermodynamics constraints.

8.1.1.1.1.5.4. Functions

add_min_log_displacement(tmodel, min_log_displacement)

add_undefined_delta_g(_tmodel, solution[, ...])

add_dummy_delta_g(tmodel, rxn[, delta_g_std, ...])

add_min_flux_requirements(tmodel, flux[, inplace, exclude])

relax_min_flux(tmodel[, reactions_to_ignore, solver, ...])

fix_directionality(tmodel, solution[, inplace])

Takes a flux solution and transfers its reaction directionality as

sanitize_cobra_vars(met_name)

deltag0_to_keq(deltag0, temp[, unit, gas_constant])

load_fluxes(solution_raw, tmodel, kmodel[, density, ...])

load_concentrations(solution_raw, tmodel, kmodel[, ...])

load_equilibrium_constants(solution_raw, tmodel, kmodel)

impose_turnover_concentation_ratios(tmodel, ...[, ...])

add_ratio_constraints(model, lc, fwd, bwd, ratio[, ...])

8.1.1.1.1.5.5. Package Contents

skimpy.add_min_log_displacement(tmodel, min_log_displacement, tva_fluxes=None, inplace=True)
skimpy.BIGM
skimpy.BIGM_THERMO
skimpy.BIGM_DG
skimpy.BIGM_P
skimpy.EPSILON
skimpy.MAX_STOICH = 10
skimpy.add_undefined_delta_g(_tmodel, solution, delta_g_std=-10, delta_g_std_err=2, add_displacement=True, inplace=True, exclude_reactions=[])
skimpy.add_dummy_delta_g(tmodel, rxn, delta_g_std=-100, delta_g_std_err=2, add_displacement=True)
skimpy.BIGM
skimpy.BIGM_THERMO
skimpy.BIGM_DG
skimpy.BIGM_P
skimpy.EPSILON
class skimpy.MinFLuxVariable(reaction, **kwargs)

Bases: pytfa.optim.variables.ReactionVariable

Class to represent a negative slack variable for relaxation problems

prefix = 'MinFluxVar_'
class skimpy.MinFLux(reaction, expr, **kwargs)

Bases: pytfa.optim.constraints.ReactionConstraint

Class to represent thermodynamics constraints. G: Flux_FW + Fluw_BW > min_flux

prefix = 'MF_'
skimpy.add_min_flux_requirements(tmodel, flux, inplace=True, exclude=[])
skimpy.relax_min_flux(tmodel, reactions_to_ignore=(), solver=None, in_place=False)
Parameters:

  • t_tmodel (pytfa.thermo.ThermoModel:)

  • reactions_to_ignore – Iterable of reactions that should not be relaxed

  • solver – solver to use (e.g. ‘optlang-glpk’, ‘optlang-cplex’, ‘optlang-gurobi’

Returns:

a cobra_model with relaxed bounds on standard Gibbs free energy

skimpy.fix_directionality(tmodel, solution, inplace=True)

Takes a flux solution and transfers its reaction directionality as constraints for the cobra_model :param inplace: :param tmodel: :param solution: :return:

skimpy.sanitize_cobra_vars(met_name)
skimpy.deltag0_to_keq(deltag0, temp, unit=KCAL, gas_constant=None)
class skimpy.ParameterValues(parameter_values, kmodel=None)

Bases: object

Parameters set for kinetic models wich can be indexed with symbols or

_parameter_values
_sym_to_str
__getitem__(item)
__setitem__(item, value)
items()
keys()
values()
skimpy.load_fluxes(solution_raw, tmodel, kmodel, density=None, ratio_gdw_gww=None, concentration_scaling=None, time_scaling=None, xmol_in_flux=0.001)
skimpy.load_concentrations(solution_raw, tmodel, kmodel, concentration_scaling=None)
skimpy.load_equilibrium_constants(solution_raw, tmodel, kmodel, concentration_scaling=None, in_place=False)
skimpy.MIN_C = 1e-10
skimpy.MAX_C = 0.1
skimpy.BIGM
skimpy.EPSILON
skimpy.LOG = 'log'
skimpy.LIN = 'lin'
class skimpy.BinUseVariable(model, id_, **kwargs)

Bases: pytfa.optim.variables.ModelVariable, pytfa.optim.variables.BinaryVariable

prefix = 'BinUseVariable_'
class skimpy.BinVariable(model, id_, **kwargs)

Bases: pytfa.optim.variables.ModelVariable

prefix = 'BinVariable_'
class skimpy.FluxRatioCons(model, expr, id_, **kwargs)

Bases: pytfa.optim.constraints.ModelConstraint

Class to represent thermodynamics constraints. G: Flux_FW + Fluw_BW > min_flux

prefix = 'FluxRatioCons_'
skimpy.impose_turnover_concentation_ratios(tmodel, metabolites, tva, ratio, in_place=False, discretization=LOG, N=11)
skimpy.add_ratio_constraints(model, lc, fwd, bwd, ratio, concentration_range=(MIN_C, MAX_C), discretization=LOG, N=11)