Class Gaussian.Parametric
java.lang.Object
org.apache.commons.math3.analysis.function.Gaussian.Parametric
- All Implemented Interfaces:
ParametricUnivariateFunction
- Enclosing class:
Gaussian
Parametric function where the input array contains the parameters of
the Gaussian, ordered as follows:
- Norm
- Mean
- Standard deviation
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Constructor Summary
Constructors -
Method Summary
Modifier and TypeMethodDescriptiondouble[]
gradient
(double x, double... param) Computes the value of the gradient atx
.private void
validateParameters
(double[] param) Validates parameters to ensure they are appropriate for the evaluation of thevalue(double,double[])
andgradient(double,double[])
methods.double
value
(double x, double... param) Computes the value of the Gaussian atx
.
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Constructor Details
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Parametric
public Parametric()
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Method Details
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value
public double value(double x, double... param) throws NullArgumentException, DimensionMismatchException, NotStrictlyPositiveException Computes the value of the Gaussian atx
.- Specified by:
value
in interfaceParametricUnivariateFunction
- Parameters:
x
- Value for which the function must be computed.param
- Values of norm, mean and standard deviation.- Returns:
- the value of the function.
- Throws:
NullArgumentException
- ifparam
isnull
.DimensionMismatchException
- if the size ofparam
is not 3.NotStrictlyPositiveException
- ifparam[2]
is negative.
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gradient
public double[] gradient(double x, double... param) throws NullArgumentException, DimensionMismatchException, NotStrictlyPositiveException Computes the value of the gradient atx
. The components of the gradient vector are the partial derivatives of the function with respect to each of the parameters (norm, mean and standard deviation).- Specified by:
gradient
in interfaceParametricUnivariateFunction
- Parameters:
x
- Value at which the gradient must be computed.param
- Values of norm, mean and standard deviation.- Returns:
- the gradient vector at
x
. - Throws:
NullArgumentException
- ifparam
isnull
.DimensionMismatchException
- if the size ofparam
is not 3.NotStrictlyPositiveException
- ifparam[2]
is negative.
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validateParameters
private void validateParameters(double[] param) throws NullArgumentException, DimensionMismatchException, NotStrictlyPositiveException Validates parameters to ensure they are appropriate for the evaluation of thevalue(double,double[])
andgradient(double,double[])
methods.- Parameters:
param
- Values of norm, mean and standard deviation.- Throws:
NullArgumentException
- ifparam
isnull
.DimensionMismatchException
- if the size ofparam
is not 3.NotStrictlyPositiveException
- ifparam[2]
is negative.
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