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java.lang.Objectorg.apache.commons.math3.analysis.function.Gaussian.Parametric
public static class Gaussian.Parametric
Parametric function where the input array contains the parameters of the Gaussian, ordered as follows:
Constructor Summary | |
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Gaussian.Parametric()
|
Method Summary | |
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double[] |
gradient(double x,
double... param)
Computes the value of the gradient at x . |
private void |
validateParameters(double[] param)
Validates parameters to ensure they are appropriate for the evaluation of the value(double,double[]) and gradient(double,double[])
methods. |
double |
value(double x,
double... param)
Computes the value of the Gaussian at x . |
Methods inherited from class java.lang.Object |
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clone, equals, finalize, getClass, hashCode, notify, notifyAll, toString, wait, wait, wait |
Constructor Detail |
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public Gaussian.Parametric()
Method Detail |
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public double value(double x, double... param) throws NullArgumentException, DimensionMismatchException, NotStrictlyPositiveException
x
.
value
in interface ParametricUnivariateFunction
x
- Value for which the function must be computed.param
- Values of norm, mean and standard deviation.
NullArgumentException
- if param
is null
.
DimensionMismatchException
- if the size of param
is
not 3.
NotStrictlyPositiveException
- if param[2]
is negative.public double[] gradient(double x, double... param) throws NullArgumentException, DimensionMismatchException, NotStrictlyPositiveException
x
.
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).
gradient
in interface ParametricUnivariateFunction
x
- Value at which the gradient must be computed.param
- Values of norm, mean and standard deviation.
x
.
NullArgumentException
- if param
is null
.
DimensionMismatchException
- if the size of param
is
not 3.
NotStrictlyPositiveException
- if param[2]
is negative.private void validateParameters(double[] param) throws NullArgumentException, DimensionMismatchException, NotStrictlyPositiveException
value(double,double[])
and gradient(double,double[])
methods.
param
- Values of norm, mean and standard deviation.
NullArgumentException
- if param
is null
.
DimensionMismatchException
- if the size of param
is
not 3.
NotStrictlyPositiveException
- if param[2]
is negative.
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