pkpd.models.pd_models module¶

PD models

class pkpd.models.pd_models.PDGenericModel[source]¶: Bases: pkpd.models.pd_models.PDModel

class pkpd.models.pd_models.PDGompertz[source]¶

Bases: pkpd.models.pd_models.PDGenericModel

areParametersSignificant(lowerBound, upperBound)[source]¶

Parameters: upperBound (lowerBound and) – a numpy array of parameters
Returns: a list of string with “True”, “False”, “NA”, “Suspicious”

areParametersValid(p)[source]¶

calculateParameterUnits(sample)[source]¶

forwardModel(parameters, x=None)[source]¶

getDescription()[source]¶

getEquation()[source]¶

getModelEquation()[source]¶

getParameterDescriptions()[source]¶

getParameterNames()[source]¶

prepare()[source]¶

printSetup()[source]¶

class pkpd.models.pd_models.PDHill[source]¶

Bases: pkpd.models.pd_models.PDGenericModel

areParametersSignificant(lowerBound, upperBound)[source]¶

Parameters: upperBound (lowerBound and) – a numpy array of parameters
Returns: a list of string with “True”, “False”, “NA”, “Suspicious”

areParametersValid(p)[source]¶

calculateParameterUnits(sample)[source]¶

forwardModel(parameters, x=None)[source]¶

getDescription()[source]¶

getEquation()[source]¶

getModelEquation()[source]¶

getParameterDescriptions()[source]¶

getParameterNames()[source]¶

prepare()[source]¶

printSetup()[source]¶

class pkpd.models.pd_models.PDLogLinear[source]¶

Bases: pkpd.models.pd_models.PDGenericModel

areParametersSignificant(lowerBound, upperBound)[source]¶

Parameters: upperBound (lowerBound and) – a numpy array of parameters
Returns: a list of string with “True”, “False”, “NA”, “Suspicious”

areParametersValid(p)[source]¶

calculateParameterUnits(sample)[source]¶

forwardModel(parameters, x=None)[source]¶

getDescription()[source]¶

getEquation()[source]¶

getModelEquation()[source]¶

getParameterDescriptions()[source]¶

getParameterNames()[source]¶

prepare()[source]¶

printSetup()[source]¶

class pkpd.models.pd_models.PDLogistic1[source]¶

Bases: pkpd.models.pd_models.PDGenericModel

areParametersSignificant(lowerBound, upperBound)[source]¶

Parameters: upperBound (lowerBound and) – a numpy array of parameters
Returns: a list of string with “True”, “False”, “NA”, “Suspicious”

areParametersValid(p)[source]¶

calculateParameterUnits(sample)[source]¶

forwardModel(parameters, x=None)[source]¶

getDescription()[source]¶

getEquation()[source]¶

getModelEquation()[source]¶

getParameterDescriptions()[source]¶

getParameterNames()[source]¶

prepare()[source]¶

printSetup()[source]¶

class pkpd.models.pd_models.PDLogistic2[source]¶

Bases: pkpd.models.pd_models.PDGenericModel

areParametersSignificant(lowerBound, upperBound)[source]¶

Parameters: upperBound (lowerBound and) – a numpy array of parameters
Returns: a list of string with “True”, “False”, “NA”, “Suspicious”

areParametersValid(p)[source]¶

calculateParameterUnits(sample)[source]¶

forwardModel(parameters, x=None)[source]¶

getDescription()[source]¶

getEquation()[source]¶

getModelEquation()[source]¶

getParameterDescriptions()[source]¶

getParameterNames()[source]¶

prepare()[source]¶

printSetup()[source]¶

class pkpd.models.pd_models.PDLogistic3[source]¶

Bases: pkpd.models.pd_models.PDGenericModel

areParametersSignificant(lowerBound, upperBound)[source]¶

Parameters: upperBound (lowerBound and) – a numpy array of parameters
Returns: a list of string with “True”, “False”, “NA”, “Suspicious”

areParametersValid(p)[source]¶

calculateParameterUnits(sample)[source]¶

forwardModel(parameters, x=None)[source]¶

getDescription()[source]¶

getEquation()[source]¶

getModelEquation()[source]¶

getParameterDescriptions()[source]¶

getParameterNames()[source]¶

prepare()[source]¶

printSetup()[source]¶

class pkpd.models.pd_models.PDLogistic4[source]¶

Bases: pkpd.models.pd_models.PDGenericModel

areParametersSignificant(lowerBound, upperBound)[source]¶

Parameters: upperBound (lowerBound and) – a numpy array of parameters
Returns: a list of string with “True”, “False”, “NA”, “Suspicious”

areParametersValid(p)[source]¶

calculateParameterUnits(sample)[source]¶

forwardModel(parameters, x=None)[source]¶

getDescription()[source]¶

getEquation()[source]¶

getModelEquation()[source]¶

getParameterDescriptions()[source]¶

getParameterNames()[source]¶

prepare()[source]¶

printSetup()[source]¶

class pkpd.models.pd_models.PDModel[source]¶: Bases: pkpd.objects.PKPDModel

class pkpd.models.pd_models.PDMorgan[source]¶

Bases: pkpd.models.pd_models.PDGenericModel

areParametersSignificant(lowerBound, upperBound)[source]¶

Parameters: upperBound (lowerBound and) – a numpy array of parameters
Returns: a list of string with “True”, “False”, “NA”, “Suspicious”

areParametersValid(p)[source]¶

calculateParameterUnits(sample)[source]¶

forwardModel(parameters, x=None)[source]¶

getDescription()[source]¶

getEquation()[source]¶

getModelEquation()[source]¶

getParameterDescriptions()[source]¶

getParameterNames()[source]¶

prepare()[source]¶

printSetup()[source]¶

class pkpd.models.pd_models.PDOQuigley0[source]¶

Bases: pkpd.models.pd_models.PDGenericModel

areParametersSignificant(lowerBound, upperBound)[source]¶

Parameters: upperBound (lowerBound and) – a numpy array of parameters
Returns: a list of string with “True”, “False”, “NA”, “Suspicious”

areParametersValid(p)[source]¶

calculateParameterUnits(sample)[source]¶

forwardModel(parameters, x=None)[source]¶

getDescription()[source]¶

getEquation()[source]¶

getModelEquation()[source]¶

getParameterDescriptions()[source]¶

getParameterNames()[source]¶

prepare()[source]¶

printSetup()[source]¶

class pkpd.models.pd_models.PDOQuigley1[source]¶

Bases: pkpd.models.pd_models.PDGenericModel

areParametersSignificant(lowerBound, upperBound)[source]¶

Parameters: upperBound (lowerBound and) – a numpy array of parameters
Returns: a list of string with “True”, “False”, “NA”, “Suspicious”

areParametersValid(p)[source]¶

calculateParameterUnits(sample)[source]¶

forwardModel(parameters, x=None)[source]¶

getDescription()[source]¶

getEquation()[source]¶

getModelEquation()[source]¶

getParameterDescriptions()[source]¶

getParameterNames()[source]¶

prepare()[source]¶

printSetup()[source]¶

class pkpd.models.pd_models.PDOQuigley2[source]¶

Bases: pkpd.models.pd_models.PDGenericModel

areParametersSignificant(lowerBound, upperBound)[source]¶

Parameters: upperBound (lowerBound and) – a numpy array of parameters
Returns: a list of string with “True”, “False”, “NA”, “Suspicious”

areParametersValid(p)[source]¶

calculateParameterUnits(sample)[source]¶

forwardModel(parameters, x=None)[source]¶

getDescription()[source]¶

getEquation()[source]¶

getModelEquation()[source]¶

getParameterDescriptions()[source]¶

getParameterNames()[source]¶

prepare()[source]¶

printSetup()[source]¶

class pkpd.models.pd_models.PDPolynomial[source]¶

Bases: pkpd.models.pd_models.PDGenericModel

areParametersSignificant(lowerBound, upperBound)[source]¶

Parameters: upperBound (lowerBound and) – a numpy array of parameters
Returns: a list of string with “True”, “False”, “NA”, “Suspicious”

areParametersValid(p)[source]¶

calculateParameterUnits(sample)[source]¶

forwardModel(parameters, x=None)[source]¶

getDescription()[source]¶

getEquation(p=None)[source]¶

getModelEquation()[source]¶

getParameterDescriptions()[source]¶

getParameterNames()[source]¶

prepare()[source]¶

printSetup()[source]¶

class pkpd.models.pd_models.PDPolynomial1[source]¶: Bases: pkpd.models.pd_models.PDPolynomial

class pkpd.models.pd_models.PDPolynomial2[source]¶: Bases: pkpd.models.pd_models.PDPolynomial

class pkpd.models.pd_models.PDPolynomial3[source]¶: Bases: pkpd.models.pd_models.PDPolynomial

class pkpd.models.pd_models.PDPolynomial4[source]¶: Bases: pkpd.models.pd_models.PDPolynomial

class pkpd.models.pd_models.PDPolynomial5[source]¶: Bases: pkpd.models.pd_models.PDPolynomial

class pkpd.models.pd_models.PDPolynomial6[source]¶: Bases: pkpd.models.pd_models.PDPolynomial

class pkpd.models.pd_models.PDPolynomial7[source]¶: Bases: pkpd.models.pd_models.PDPolynomial

class pkpd.models.pd_models.PDPolynomial8[source]¶: Bases: pkpd.models.pd_models.PDPolynomial

class pkpd.models.pd_models.PDPolynomial9[source]¶: Bases: pkpd.models.pd_models.PDPolynomial

class pkpd.models.pd_models.PDRichards[source]¶

Bases: pkpd.models.pd_models.PDGenericModel

areParametersSignificant(lowerBound, upperBound)[source]¶

Parameters: upperBound (lowerBound and) – a numpy array of parameters
Returns: a list of string with “True”, “False”, “NA”, “Suspicious”

areParametersValid(p)[source]¶

calculateParameterUnits(sample)[source]¶

forwardModel(parameters, x=None)[source]¶

getDescription()[source]¶

getEquation()[source]¶

getModelEquation()[source]¶

getParameterDescriptions()[source]¶

getParameterNames()[source]¶

prepare()[source]¶

printSetup()[source]¶

class pkpd.models.pd_models.PDSaturated[source]¶

Bases: pkpd.models.pd_models.PDGenericModel

areParametersSignificant(lowerBound, upperBound)[source]¶

Parameters: upperBound (lowerBound and) – a numpy array of parameters
Returns: a list of string with “True”, “False”, “NA”, “Suspicious”

areParametersValid(p)[source]¶

calculateParameterUnits(sample)[source]¶

forwardModel(parameters, x=None)[source]¶

getDescription()[source]¶

getEquation()[source]¶

getModelEquation()[source]¶

getParameterDescriptions()[source]¶

getParameterNames()[source]¶

prepare()[source]¶

printSetup()[source]¶

class pkpd.models.pd_models.PDSigmoid[source]¶

Bases: pkpd.models.pd_models.PDGenericModel

areParametersSignificant(lowerBound, upperBound)[source]¶

Parameters: upperBound (lowerBound and) – a numpy array of parameters
Returns: a list of string with “True”, “False”, “NA”, “Suspicious”

areParametersValid(p)[source]¶

calculateParameterUnits(sample)[source]¶

forwardModel(parameters, x=None)[source]¶

getDescription()[source]¶

getEquation()[source]¶

getModelEquation()[source]¶

getParameterDescriptions()[source]¶

getParameterNames()[source]¶

prepare()[source]¶

printSetup()[source]¶

class pkpd.models.pd_models.PDWeibull[source]¶

Bases: pkpd.models.pd_models.PDGenericModel

areParametersSignificant(lowerBound, upperBound)[source]¶

Parameters: upperBound (lowerBound and) – a numpy array of parameters
Returns: a list of string with “True”, “False”, “NA”, “Suspicious”

areParametersValid(p)[source]¶

calculateParameterUnits(sample)[source]¶

forwardModel(parameters, x=None)[source]¶

getDescription()[source]¶

getEquation()[source]¶

getModelEquation()[source]¶

getParameterDescriptions()[source]¶

getParameterNames()[source]¶

prepare()[source]¶

printSetup()[source]¶