pyenzyme.enzymeml.models.kineticmodel module#
- pydantic model pyenzyme.enzymeml.models.kineticmodel.KineticModel[source]#
Bases:
EnzymeMLBase
Show JSON schema
{ "title": "KineticModel", "type": "object", "properties": { "name": { "title": "Name", "description": "Name of the kinetic law.", "type": "string" }, "equation": { "title": "Equation", "description": "Equation for the kinetic law.", "type": "string" }, "parameters": { "title": "Parameters", "description": "List of estimated parameters.", "type": "array", "items": { "$ref": "#/definitions/KineticParameter" } }, "ontology": { "description": "Type of the estimated parameter.", "allOf": [ { "$ref": "#/definitions/SBOTerm" } ] } }, "required": [ "name", "equation" ], "definitions": { "SBOTerm": { "title": "SBOTerm", "description": "String enumeration used to assign ontologies derived from SBOTerms.", "enum": [ "SBO:0000176", "SBO:0000208", "SBO:0000181", "SBO:0000182", "SBO:0000179", "SBO:0000180", "SBO:0000209", "SBO:0000377", "SBO:0000177", "SBO:0000200", "SBO:0000672", "SBO:0000252", "SBO:0000251", "SBO:0000247", "SBO:0000327", "SBO:0000328", "SBO:0000336", "SBO:0000015", "SBO:0000011", "SBO:0000013", "SBO:0000020", "SBO:0000461", "SBO:0000462", "SBO:0000021", "SBO:0000296", "SBO:0000297", "SBO:0000607", "SBO:0000028", "SBO:0000025", "SBO:0000027", "SBO:0000186" ], "type": "string" }, "KineticParameter": { "title": "KineticParameter", "type": "object", "properties": { "name": { "title": "Name", "description": "Name of the estimated parameter.", "type": "string" }, "value": { "title": "Value", "description": "Numerical value of the estimated parameter.", "type": "number" }, "unit": { "title": "Unit", "description": "Unit of the estimated parameter.", "type": "string" }, "initial_value": { "title": "Initial Value", "description": "Initial value that was used for the parameter estimation.", "type": "number" }, "upper": { "title": "Upper", "description": "Upper bound of the estimated parameter.", "type": "number" }, "lower": { "title": "Lower", "description": "Lower bound of the estimated parameter.", "type": "number" }, "is_global": { "title": "Is Global", "description": "Specifies if this parameter is a global parameter.", "default": false, "type": "boolean" }, "stdev": { "title": "Stdev", "description": "Standard deviation of the estimated parameter.", "type": "number" }, "constant": { "title": "Constant", "description": "Specifies if this parameter is constant", "default": false, "type": "boolean" }, "ontology": { "description": "Type of the estimated parameter.", "allOf": [ { "$ref": "#/definitions/SBOTerm" } ] } }, "required": [ "name" ] } } }
- Config
validate_all: bool = True
validate_assignment: bool = True
- Fields
- field equation: str [Required]#
Equation for the kinetic law.
- field name: str [Required]#
Name of the kinetic law.
- field parameters: List[KineticParameter] [Optional]#
List of estimated parameters.
- addParameter(name: str, value: Optional[float] = None, unit: Optional[str] = None, initial_value: Optional[float] = None, upper: Optional[float] = None, lower: Optional[float] = None, is_global: bool = False, stdev: Optional[float] = None, constant: bool = False, ontology: Optional[SBOTerm] = None)[source]#
Adds a parameter to the KineticModel object
- Parameters
name (str) – Name of the estimated parameter.
value (Optional[float], optional) – Numerical value of the estimated parameter.. Defaults to None.
unit (Optional[str], optional) – Unit of the estimated parameter.. Defaults to None.
initial_value (Optional[float], optional) – Initial value that was used for the parameter estimation. Defaults to None.
upper (Optional[float], optional) – Upper bound of the estimated parameter.. Defaults to None.
lower (Optional[float], optional) – Lower bound of the estimated parameter.. Defaults to None.
is_global (bool, optional) – Specifies if this parameter is a global parameter.. Defaults to False.
stdev (Optional[float], optional) – Standard deviation of the estimated parameter.. Defaults to None.
constant (bool, optional) – Specifies if this parameter is constant. Defaults to False.
ontology (Optional[SBOTerm], optional) – Type of the estimated parameter.. Defaults to None.
- static createGenerator(name: str, equation: str, **parameters)[source]#
Creates an abstract model generator to generated specific models.
- Parameters
name (str) – Name of the model.
equation (str) – Equation
- Returns
[description]
- Return type
[type]
- evaluate(**kwargs)[source]#
Calculates the the reaction velocity given the internal parameters and variable concentrations handed as keyword arguments.
Examples
model = KineticModel(…) <- Lets assume this is a Menten Model with already estimated parameters print(model.evaluate(protein=10.0, substrate=1.0))
>> 1.002 <- This is the resulting velocity
- Returns
Corresponding reaction velocity given the internal parameters and variables.
- Return type
float
- classmethod fromEquation(name: str, equation: str, enzmldoc: Optional[Any] = None)[source]#
Creates a Kinetic Model instance from an equation
- Parameters
equation (str) – Mathematical equation decribing the model.
- Returns
Resulting kinetic model
- Return type
- getParameter(name: str) KineticParameter [source]#
Returns a parameter of choice from the model.
- Parameters
name (str) – Name of the parameter.
- Raises
KeyError – If the parameter does not exist.
- Returns
The desired parameter.
- Return type
- pydantic model pyenzyme.enzymeml.models.kineticmodel.KineticParameter[source]#
Bases:
EnzymeMLBase
Show JSON schema
{ "title": "KineticParameter", "type": "object", "properties": { "name": { "title": "Name", "description": "Name of the estimated parameter.", "type": "string" }, "value": { "title": "Value", "description": "Numerical value of the estimated parameter.", "type": "number" }, "unit": { "title": "Unit", "description": "Unit of the estimated parameter.", "type": "string" }, "initial_value": { "title": "Initial Value", "description": "Initial value that was used for the parameter estimation.", "type": "number" }, "upper": { "title": "Upper", "description": "Upper bound of the estimated parameter.", "type": "number" }, "lower": { "title": "Lower", "description": "Lower bound of the estimated parameter.", "type": "number" }, "is_global": { "title": "Is Global", "description": "Specifies if this parameter is a global parameter.", "default": false, "type": "boolean" }, "stdev": { "title": "Stdev", "description": "Standard deviation of the estimated parameter.", "type": "number" }, "constant": { "title": "Constant", "description": "Specifies if this parameter is constant", "default": false, "type": "boolean" }, "ontology": { "description": "Type of the estimated parameter.", "allOf": [ { "$ref": "#/definitions/SBOTerm" } ] } }, "required": [ "name" ], "definitions": { "SBOTerm": { "title": "SBOTerm", "description": "String enumeration used to assign ontologies derived from SBOTerms.", "enum": [ "SBO:0000176", "SBO:0000208", "SBO:0000181", "SBO:0000182", "SBO:0000179", "SBO:0000180", "SBO:0000209", "SBO:0000377", "SBO:0000177", "SBO:0000200", "SBO:0000672", "SBO:0000252", "SBO:0000251", "SBO:0000247", "SBO:0000327", "SBO:0000328", "SBO:0000336", "SBO:0000015", "SBO:0000011", "SBO:0000013", "SBO:0000020", "SBO:0000461", "SBO:0000462", "SBO:0000021", "SBO:0000296", "SBO:0000297", "SBO:0000607", "SBO:0000028", "SBO:0000025", "SBO:0000027", "SBO:0000186" ], "type": "string" } } }
- Config
validate_all: bool = True
validate_assignment: bool = True
- Fields
- field constant: bool = False#
Specifies if this parameter is constant
- field initial_value: Optional[float] = None#
Initial value that was used for the parameter estimation.
- field is_global: bool = False#
Specifies if this parameter is a global parameter.
- field lower: Optional[float] = None#
Lower bound of the estimated parameter.
- field name: str [Required]#
Name of the estimated parameter.
- field stdev: Optional[float] = None#
Standard deviation of the estimated parameter.
- field unit: Optional[str] = None#
Unit of the estimated parameter.
- field upper: Optional[float] = None#
Upper bound of the estimated parameter.
- field value: Optional[float] = None#
Numerical value of the estimated parameter.