5.1.2.1.2. etfba.io.results

Difine classes of analysis results.

5.1.2.1.2.1. Classes

PrettyDict

dict() -> new empty dictionary

FBAResults

TFBAResults

EFBAResults

ETFBAResults

VariabilityResults

FVAResults

TVAResults

EVAResults

5.1.2.1.2.2. Module Contents

class etfba.io.results.PrettyDict(*args, ndigits=3, **kwargs)[source]

Bases: dict

dict() -> new empty dictionary dict(mapping) -> new dictionary initialized from a mapping object’s

(key, value) pairs

dict(iterable) -> new dictionary initialized as if via:

d = {} for k, v in iterable:

d[k] = v

dict(**kwargs) -> new dictionary initialized with the name=value pairs

in the keyword argument list. For example: dict(one=1, two=2)

ndigits[source]
save(file, exp_transform=False)[source]
Parameters:
  • file (str) – File ending with .xlsx, .tsv, or .bin format.

  • log_transform (bool) – Determines whether to apply natural exponential transformation.

__repr__()[source]

Return repr(self).

class etfba.io.results.FBAResults(opt_obj, opt_fluxes, opt_success, stoy_mat)[source]
opt_objective[source]

Optimal objective value achieved during optimization.

Type:

float

opt_fluxes[source]

Dictionary mapping reaction ID to its optimal flux value.

Type:

dict

optimization_successful[source]

Indicates whether the optimization process was successful.

Type:

bool

_opt_obj[source]
_opt_fluxes[source]
_opt_success[source]
_stoy_mat[source]
property opt_objective[source]
property opt_fluxes[source]
property optimization_successful[source]
statement(metabid)[source]
Parameters:

metabid (str) – Metabolite ID.

class etfba.io.results.TFBAResults(opt_obj, opt_fluxes, opt_lnconcs, opt_dgps, opt_success, stoy_mat, **kwargs)[source]

Bases: FBAResults

...
opt_concentrations[source]

Dictionary mapping metabolite ID to its optimal concentration.

Type:

dict

opt_directions[source]

Dictionary mapping reaction ID to its direction (“f” for forward, “b” for backward).

Type:

dict

opt_gibbs_energy[source]

Dictionary mapping reaction ID to its optimal deltaGprime value.

Type:

dict

_opt_lnconcs[source]
_opt_concs[source]
_opt_dgps[source]
property opt_concentrations[source]
property opt_directions[source]
property opt_gibbs_energy[source]
class etfba.io.results.EFBAResults(opt_obj, opt_fluxes, opt_total_epc, opt_epcs, opt_success, stoy_mat, **kwargs)[source]

Bases: FBAResults

...
opt_total_enzyme_cost[source]

Optimal total enzyme protein cost achieved.

Type:

float

opt_enzyme_costs[source]

Dictionary mapping reaction ID to its optimal enzyme protein abundance.

Type:

dict

_opt_total_epc[source]
_opt_epcs[source]
property opt_total_enzyme_cost[source]
property opt_enzyme_costs[source]
class etfba.io.results.ETFBAResults(opt_obj, opt_fluxes, opt_lnconcs, opt_dgps, opt_total_epc, opt_epcs, opt_success, stoy_mat)[source]

Bases: TFBAResults, EFBAResults

...
class etfba.io.results.VariabilityResults(obj_value, gamma, ranges)[source]
objective_value[source]

Objective value obtained from TFBA, EFBA, or ETFBA analysis.

Type:

float

gamma[source]

Control parameter for the objective value.

Type:

float

_obj_value[source]
_gamma[source]
_ranges[source]
property objective_value[source]
property gamma[source]
class etfba.io.results.FVAResults(obj_value, gamma, ranges)[source]

Bases: VariabilityResults

...
flux_ranges[source]

Dictionary containing reaction IDs mapped to their corresponding net flux ranges [lb, ub].

Type:

dict

property flux_ranges[source]
class etfba.io.results.TVAResults(obj_value, gamma, ranges)[source]

Bases: VariabilityResults

...
gibbs_energy_ranges[source]

Dictionary containing reaction IDs mapped to their corresponding ranges of deltaGprime [lb, ub].

Type:

dict

property gibbs_energy_ranges[source]
class etfba.io.results.EVAResults(obj_value, gamma, ranges)[source]

Bases: VariabilityResults

...
protein_cost_ranges[source]

Dictionary mapping reaction IDs to their respective ranges of protein cost [lb, ub].

Type:

dict

property protein_cost_ranges[source]