HSICEstimator¶
- class HSICEstimator(*args)¶
Base class of HSIC estimators.
See also
Notes
HSIC-based analyses must be performed by using the derived classes:
HSICEstimatorConditionalSensitivity
,HSICEstimatorGlobalSensitivity
andHSICEstimatorTargetSensitivity
.The
ResourceMap
key HSICEstimator-InputCovarianceMatrixCacheSizeMb allows one to limit the total size (in mega bytes) of the input matrix cached.Methods
Draw the HSIC indices.
Draw the p-values obtained with an asymptotic formula.
Draw the p-values obtained by permutation.
Draw the R2-HSIC indices.
Accessor to the object's name.
Get the list of all covariance models used.
Get the dimension of the input sample.
Get the estimator used for computations.
Get the HSIC indices.
getId
()Accessor to the object's id.
Accessor to the underlying implementation.
Get the input sample.
getName
()Accessor to the object's name.
Get the output sample.
Get the p-values obtained with an asymptotic formula.
Get the p-value estimated through permutations.
Get the number of permutations.
Get the R2-HSIC indices.
getSize
()Get the size of the input sample.
run
()Compute all values at once.
Set the covariance models.
setInputSample
(inputSample)Set the input sample.
setName
(name)Accessor to the object's name.
setOutputSample
(outputSample)Set the output sample.
Set the number of permutations to be used for p-value estimate.
- __init__(*args)¶
- drawHSICIndices()¶
Draw the HSIC indices.
- Returns:
- graph
Graph
The graph of all HSIC indices according to components.
- graph
- drawPValuesAsymptotic()¶
Draw the p-values obtained with an asymptotic formula.
- Returns:
- graph
Graph
The graph of all p-values estimated with an asymptotic formula.
- graph
- drawPValuesPermutation()¶
Draw the p-values obtained by permutation.
- Returns:
- graph
Graph
The graph of all p-values by permutation according to components.
- graph
- drawR2HSICIndices()¶
Draw the R2-HSIC indices.
- Returns:
- graph
Graph
The graph of all R2-HSIC indices according to components.
- graph
- getClassName()¶
Accessor to the object’s name.
- Returns:
- class_namestr
The object class name (object.__class__.__name__).
- getCovarianceModelCollection()¶
Get the list of all covariance models used.
- Returns:
- collCovarianceModelCollection
The list of all covariance models used. The last one is the output covariance model.
- getDimension()¶
Get the dimension of the input sample.
- Returns:
- dimint
The dimension of the input sample.
- getEstimator()¶
Get the estimator used for computations.
- Returns:
- estimator
HSICStat
The estimator used for internal computations.
- estimator
- getHSICIndices()¶
Get the HSIC indices.
- Returns:
- hsicIndices
Point
The HSIC indices of all components.
- hsicIndices
- getId()¶
Accessor to the object’s id.
- Returns:
- idint
Internal unique identifier.
- getImplementation()¶
Accessor to the underlying implementation.
- Returns:
- implImplementation
A copy of the underlying implementation object.
- getName()¶
Accessor to the object’s name.
- Returns:
- namestr
The name of the object.
- getOutputSample()¶
Get the output sample.
- Returns:
- outSample
Sample
The output sample used for analysis.
- outSample
- getPValuesAsymptotic()¶
Get the p-values obtained with an asymptotic formula.
- Returns:
- pvalsequence of float
The p-values for all components.
- getPValuesPermutation()¶
Get the p-value estimated through permutations.
- Returns:
- pval
Point
The p-values of all components estimated with permutations of the data.
- pval
- getPermutationSize()¶
Get the number of permutations.
- Returns:
- permutationSizeint
The number of permutations.
- getR2HSICIndices()¶
Get the R2-HSIC indices.
- Returns:
- r2hsicIndices
Point
The R2-HSIC indices of all components.
- r2hsicIndices
- getSize()¶
Get the size of the input sample.
- Returns:
- sizeint
The size of the input sample.
- run()¶
Compute all values at once.
- setCovarianceModelCollection(coll)¶
Set the covariance models.
- Parameters:
- collCovarianceModelCollection
The list of all covariance models.
- setInputSample(inputSample)¶
Set the input sample.
- Parameters:
- inputSample2-d sequence of float
The input sample to be used.
- setName(name)¶
Accessor to the object’s name.
- Parameters:
- namestr
The name of the object.
- setOutputSample(outputSample)¶
Set the output sample.
- Parameters:
- outputSample2-d sequence of float
The output sample to be used.
- setPermutationSize(B)¶
Set the number of permutations to be used for p-value estimate.
- Parameters:
- Bint
The number of permutation used for p-value estimates.