8.1.1.1.1.2. skimpy.analysis.mca

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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

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8.1.1.1.1.2.1. Submodules

8.1.1.1.1.2.2. Package Contents

8.1.1.1.1.2.2.1. Classes

JacobianFunction

Tensor

ConcentrationControlFunction

Tensor

FluxControlFunction

8.1.1.1.1.2.2.2. Functions

get_reversible_fluxes(net_fluxes, displacements, reactions)

param net_fluxes

dict of net-fluxes

8.1.1.1.1.2.2.3. Attributes

SPLIT

Item types

NET

SPLIT

Item types

NET

class skimpy.JacobianFunction(reduced_stoichometry, independent_elasticity_function, dependent_elasticity_function, volume_ratio_function, conservation_relation, independent_variable_ix, dependent_variable_ix)
__call__(self, fluxes, concentrations, parameters, flux_jacobian=False)
Parameters

  • fluxes – Dict or pd.Series of reference flux vector

  • concentrations – Dict or pd.Series of reference concentration vector

  • parameters – Dict or pd.Series of reference parameters vector

class skimpy.Tensor(data, indexes, *args, **kwargs)

Bases: object

build_index_dict(self, index_names)
slice_by(self, slicer, value)

Returns a slice of the tensor along a value on a specific index

Parameters

  • slicer (str or pandas.Index) –

  • value –

Returns

get_slice_index(self, slicer)

Utility function for getting the integer number of the index (0,1, or 2)

Parameters

slicer –

Returns

mean(self, slicer, *args, **kwargs)

Flatten using the mean along an index

Parameters

  • slicer –

  • args –

  • kwargs –

Returns

std(self, slicer, *args, **kwargs)

Flatten using the standard deviation along an index :param slicer: :param args: :param kwargs: :return:

quantile(self, slicer, quantile, *args, **kwargs)

Flatten using the standard deviation along an index :param slicer: :param args: :param kwargs: :return:

make_df(self, data, index1, index2)
skimpy.SPLIT = split

Item types

skimpy.NET = net
skimpy.get_reversible_fluxes(net_fluxes, displacements, reactions)
Parameters

  • net_fluxes – dict of net-fluxes

  • displacements – dict of displacements for reversible reactions

  • reactions – list of reaction names

Returns

class skimpy.ConcentrationControlFunction(model, reduced_stoichometry, independent_elasticity_function, dependent_elasticity_function, parameter_elasticity_function, volume_ratio_function, conservation_relation, independent_variable_ix, dependent_variable_ix, mca_type=NET, displacement_function=None)
__call__(self, flux_dict, concentration_dict, parameter_population)
class skimpy.Tensor(data, indexes, *args, **kwargs)

Bases: object

build_index_dict(self, index_names)
slice_by(self, slicer, value)

Returns a slice of the tensor along a value on a specific index

Parameters

  • slicer (str or pandas.Index) –

  • value –

Returns

get_slice_index(self, slicer)

Utility function for getting the integer number of the index (0,1, or 2)

Parameters

slicer –

Returns

mean(self, slicer, *args, **kwargs)

Flatten using the mean along an index

Parameters

  • slicer –

  • args –

  • kwargs –

Returns

std(self, slicer, *args, **kwargs)

Flatten using the standard deviation along an index :param slicer: :param args: :param kwargs: :return:

quantile(self, slicer, quantile, *args, **kwargs)

Flatten using the standard deviation along an index :param slicer: :param args: :param kwargs: :return:

make_df(self, data, index1, index2)
skimpy.SPLIT = split

Item types

skimpy.NET = net
class skimpy.FluxControlFunction(model, reduced_stoichometry, independent_elasticity_function, dependent_elasticity_function, parameter_elasticity_function, conservation_relation, independent_variable_ix, dependent_variable_ix, concentration_control_fun, mca_type=NET)
__call__(self, flux_dict, concentration_dict, parameter_population)