amici.pysb_import¶
PySB Import¶
This module provides all necessary functionality to import a model specified
in the pysb.core.Model
format.
Functions Summary
|
Constructs a list of monomer names contained in complex patterns. |
|
Wrapper to interface |
|
Creates an |
|
Generate AMICI C++ files for the provided model. |
|
Load a pysb model module and return the |
Functions
-
amici.pysb_import.
extract_monomers
(complex_patterns)[source]¶ Constructs a list of monomer names contained in complex patterns. Multiplicity of names corresponds to the stoichiometry in the complex.
- Parameters
complex_patterns (
typing.Union
[pysb.core.ComplexPattern
,typing.List
[pysb.core.ComplexPattern
]]) – (list of) complex pattern(s)- Return type
- Returns
list of monomer names
-
amici.pysb_import.
has_fixed_parameter_ic
(specie, pysb_model, ode_model)[source]¶ Wrapper to interface
ode_export.ODEModel.state_has_fixed_parameter_initial_condition()
from a pysb specie/model arguments- Parameters
specie (
pysb.core.ComplexPattern
) – pysb speciespysb_model (
pysb.core.Model
) – pysb modelode_model (
amici.ode_export.ODEModel
) – ODE model
- Return type
- Returns
False
if the species does not have an initial condition at all. Otherwise the return value ofode_export.ODEModel.state_has_fixed_parameter_initial_condition()
-
amici.pysb_import.
ode_model_from_pysb_importer
(model, constant_parameters=None, observables=None, sigmas=None, noise_distributions=None, compute_conservation_laws=True, simplify=<function powsimp>, verbose=False)[source]¶ Creates an
amici.ODEModel
instance from apysb.Model
instance.- Parameters
model (
pysb.core.Model
) – seeamici.pysb_import.pysb2amici()
constant_parameters (
typing.Optional
[typing.List
[str
]]) – seeamici.pysb_import.pysb2amici()
observables (
typing.Optional
[typing.List
[str
]]) – seeamici.pysb_import.pysb2amici()
sigmas (
typing.Optional
[typing.Dict
[str
,str
]]) – dict with names of observable Expressions as keys and names of sigma Expressions as value sigmanoise_distributions (
typing.Optional
[typing.Dict
[str
,typing.Union
[str
,typing.Callable
]]]) – seeamici.pysb_import.pysb2amici()
compute_conservation_laws (
bool
) – seeamici.pysb_import.pysb2amici()
simplify (
typing.Callable
) – seeamici.ODEModel._simplify
verbose (
typing.Union
[int
,bool
]) – verbosity level for logging, True/False default tologging.DEBUG
/logging.ERROR
- Return type
- Returns
New ODEModel instance according to pysbModel
-
amici.pysb_import.
pysb2amici
(model, output_dir=None, observables=None, constant_parameters=None, sigmas=None, noise_distributions=None, verbose=False, assume_pow_positivity=False, compiler=None, compute_conservation_laws=True, compile=True, simplify=<function <lambda>>)[source]¶ Generate AMICI C++ files for the provided model.
- Parameters
model (
pysb.core.Model
) – pysb model,pysb.Model.name
will determine the name of the generated moduleoutput_dir (
typing.Optional
[str
]) – seeamici.ode_export.ODEExporter.set_paths()
observables (
typing.Optional
[typing.List
[str
]]) – list ofpysb.core.Expression
orpysb.core.Observable
names in the provided model that should be mapped to observablessigmas (
typing.Optional
[typing.Dict
[str
,str
]]) – dict ofpysb.core.Expression
names that should be mapped to sigmasnoise_distributions (
typing.Optional
[typing.Dict
[str
,typing.Union
[str
,typing.Callable
]]]) – dict with names of observable Expressions as keys and a noise type identifier, or a callable generating a custom noise formula string (seeamici.import_utils.noise_distribution_to_cost_function()
). If nothing is passed for some observable id, a normal model is assumed as default.constant_parameters (
typing.Optional
[typing.List
[str
]]) – list ofpysb.core.Parameter
names that should be mapped as fixed parametersverbose (
typing.Union
[int
,bool
]) – verbosity level for logging, True/False default tologging.DEBUG
/logging.ERROR
assume_pow_positivity (
bool
) – if set totrue
, a special pow function is used to avoid problems with state variables that may become negative due to numerical errorscompiler (
typing.Optional
[str
]) – distutils/setuptools compiler selection to build the python extensioncompute_conservation_laws (
bool
) – if set totrue
, conservation laws are automatically computed and applied such that the state-jacobian of the ODE right-hand-side has full rank. This option should be set totrue
when using the Newton algorithm to compute steadystatescompile (
bool
) – Iftrue
, build the python module for the generated model. If false, just generate the source code.simplify (
typing.Callable
) – seeamici.ODEModel._simplify