biocrnpyler.core.GeneralPropensity

class biocrnpyler.core.GeneralPropensity(propensity_function: str, propensity_species: List[Species], propensity_parameters: List[ParameterEntry])[source]

Bases: Propensity

Propensity with user-defined formula string.

A GeneralPropensity allows specification of arbitrary kinetic rate laws using a formula string. The formula can reference species and parameters that are validated and tracked.

Parameters:

propensity_function (str) – Valid mathematical formula as a string (e.g., ‘k*S1*S2’). Must contain all referenced species and parameters.
propensity_species (list of Species) – List of Species objects used in the formula. Each species must appear in the propensity_function string.
propensity_parameters (list of ParameterEntry) – List of ParameterEntry objects used in the formula. Each parameter name must appear in the propensity_function string.

Attributes:

propensity_function (str) – The mathematical formula defining the rate law.
name (str) – Set to ‘general’ for this propensity type.

Raises:

TypeError – If propensity_species or propensity_parameters contain invalid types.
ValueError – If species or parameters in lists do not appear in the formula.

See also

MassAction: Mass action kinetics propensity.
Hill: Hill-type propensities.

Notes

The propensity_function string must be a valid mathematical expression that can be parsed by libsbml.parseL3Formula(). It can include:

Arithmetic operators: +, -, *, /, ^
Mathematical functions: exp, log, sin, cos, etc.
Species names (as strings matching their representation)
Parameter names (matching ParameterEntry.parameter_name)

Examples

Create a custom Michaelis-Menten propensity:

>>> S = bcp.Species('S')
>>> E = bcp.Species('E')
>>> kcat = bcp.ParameterEntry('kcat', 0.1)
>>> Km = bcp.ParameterEntry('Km', 10.0)
>>> prop = bcp.GeneralPropensity(
...     propensity_function='kcat*E*S/(Km + S)',
...     propensity_species=[S, E],
...     propensity_parameters=[kcat, Km]
... )

Create a custom regulatory function:

>>> X = bcp.Species('X')
>>> Y = bcp.Species('Y')
>>> k1 = bcp.ParameterEntry('k1', 1.0)
>>> k2 = bcp.ParameterEntry('k2', 0.5)
>>> prop = bcp.GeneralPropensity(
...     propensity_function='k1*X + k2*Y^2',
...     propensity_species=[X, Y],
...     propensity_parameters=[k1, k2]
... )

Methods

`create_kinetic_law`	Create SBML kinetic law using the propensity_function string.
`from_dict`	Create a propensity from a dictionary.
`get_available_propensities`	Get all available propensity subclasses.
`is_valid_propensity`	Check if an object is a valid Propensity subclass instance.
`pretty_print`	Generate human-readable string representation of propensity.
`pretty_print_parameters`	Generate formatted string of all propensity parameters.
`pretty_print_rate`	Return the propensity function formula string.

__eq__(other)[source]

Test equality between propensities.

Parameters:: other (Propensity) – Other propensity to compare with.
Returns:: True if propensities have the same class and propensity_dict.
Return type:: bool

create_kinetic_law(model, sbml_reaction, **kwargs)[source]

Create SBML kinetic law using the propensity_function string.

Translates species and parameter names to SBML identifiers and creates the kinetic law from the formula string.

Parameters:

model (libsbml.Model) – SBML model object.
sbml_reaction (libsbml.Reaction) – SBML reaction to add kinetic law to.
**kwargs – Additional keyword arguments (unused for GeneralPropensity).

Returns:

Created SBML kinetic law object.

Return type:

libsbml.KineticLaw

Raises:

ValueError – If the propensity_function cannot be parsed as valid SBML formula.

classmethod from_dict(propensity_dict)[source]

Create a propensity from a dictionary.

Parameters:: propensity_dict (dict) – Dictionary with ‘parameters’ and ‘species’ keys containing parameter and species values.
Returns:: New instance of the propensity class.
Return type:: Propensity

static get_available_propensities() → Set[source]

Get all available propensity subclasses.

Returns:: Set of all Propensity subclass types available in BioCRNpyler.
Return type:: set

Examples

>>> propensities = bcp.Propensity.get_available_propensities()
>>> bcp.MassAction in propensities
True

property is_reversible

Whether the propensity represents a reversible reaction.

Default is False. Subclasses override this for reversible kinetics.

Type:: bool

static is_valid_propensity(propensity_type) → bool[source]

Check if an object is a valid Propensity subclass instance.

Recursively checks all subclasses of Propensity to determine if the given object is a valid propensity type.

Parameters:: propensity_type (object) – Object to check for Propensity validity.
Returns:: True if propensity_type is an instance of Propensity or any of its subclasses, False otherwise.
Return type:: bool

Examples

>>> prop = bcp.MassAction(k_forward=100.0)
>>> bcp.Propensity.is_valid_propensity(prop)
True
>>> bcp.Propensity.is_valid_propensity("not a propensity")
False

property k_forward

Forward rate constant.

Raises:: NotImplementedError – Must be implemented by subclasses that use rate constants.
Type:: Float

property k_reverse

Reverse rate constant for reversible reactions.

Raises:: NotImplementedError – Must be implemented by subclasses that use rate constants.
Type:: Float or None

pretty_print(show_parameters=True, **kwargs)[source]

Generate human-readable string representation of propensity.

Parameters:

show_parameters (bool, default True) – If True, includes parameter values in output.
**kwargs – Additional keyword arguments passed to formatting methods.

Returns:

Formatted string showing rate formula and optionally parameters.

Return type:

str

pretty_print_parameters(show_keys=True, **kwargs)[source]

Generate formatted string of all propensity parameters.

Parameters:

show_keys (bool, default True) – If True, shows search and found keys for ModelParameter objects (useful for debugging parameter lookup).
**kwargs – Additional formatting keyword arguments.

Returns:

Formatted string listing all parameters and their values.

Return type:

str

pretty_print_rate(**kwargs)[source]

Return the propensity function formula string.

Returns:: The propensity_function formula.
Return type:: str

property species: List

All species used in the propensity function.

Type:: List of Species