biocrnpyler.core.HillPositive

class biocrnpyler.core.HillPositive(k: float, s1: Species, K: float, n: float)[source]

Bases: Hill

Positive Hill function propensity (activation).

Implements an activating Hill function with sigmoidal dose-response curve. As s1 increases, the rate approaches \(k\).

Parameters:

k (float or ParameterEntry) – Maximum rate constant. Must be positive.
s1 (Species) – Input species that activates the reaction.
K (float or ParameterEntry) – Half-saturation constant (concentration at half-maximal rate). Must be positive.
n (float or ParameterEntry) – Hill coefficient (cooperativity). Must be positive. Values > 1 indicate ultrasensitivity.

Attributes:

name (str) – Set to ‘hillpositive’ for this propensity type.

See also

HillNegative: Repressive Hill function.
ProportionalHillPositive: Proportional positive Hill.

Notes

The following formula is implemented:

\[p(s_1; k, K, n) = \frac{k s_1^n}{K^n + s_1^n}, \]

leading to the following behaviors:

When \(s_1 = 0\): rate ≈ 0
When \(s_1 = K\): rate = \(k\)/2
When \(s1 \gg K\): rate \(\rightarrow\) \(k\)
Larger \(n\) gives sharper (more switch-like) response

Examples

Create a Hill activation propensity:

>>> X = bcp.Species('X')
>>> prop = bcp.HillPositive(k=10.0, s1=X, K=50.0, n=2.0)

Use with parameter objects:

>>> kmax = bcp.ParameterEntry('kmax', 10.0)
>>> Kd = bcp.ParameterEntry('Kd', 50.0)
>>> hill_n = bcp.ParameterEntry('n', 2.0)
>>> prop = bcp.HillPositive(k=kmax, s1=X, K=Kd, n=hill_n)

Methods

`create_kinetic_law`	Create SBML kinetic law for Hill propensity.
`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`	Generate human-readable rate formula string.

property K

Half-saturation (dissociation) constant value.

Type:: float

__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, stochastic, **kwargs)[source]

Create SBML kinetic law for Hill propensity.

This method is shared by all Hill subclasses.

Parameters:

model (libsbml.Model) – SBML model object.
sbml_reaction (libsbml.Reaction) – SBML reaction to add kinetic law to.
stochastic (bool) – If True, uses stochastic formulation (same as deterministic for Hill functions).
**kwargs – Additional arguments. ‘reverse_reaction’ is not supported.

Returns:

Created SBML kinetic law object.

Return type:

libsbml.KineticLaw

Raises:

ValueError – If reverse_reaction=True (Hill propensities cannot be reversible) or if rate formula is invalid.

property d

Proportional species (None if not proportional).

Type:: Species

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

Maximum rate constant value.

Type:: float

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

property n

Hill coefficient (cooperativity) value.

Type:: float

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

Generate human-readable rate formula string.

Returns:: Formatted Hill positive formula.
Return type:: str

property s1

Input species driving the Hill function.

Type:: Species

property species: List

All species used in the propensity function.

Type:: List of Species