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Vector Representation Step

Vector Representation Step

Author

Mathieu Carrière

Super classes

rgudhi::PythonClass -> rgudhi::SKLearnClass -> VectorRepresentationStep

Methods

Inherited methods


Method apply()

Applies the class on a single persistence diagram and outputs the result.

Usage

VectorRepresentationStep$apply(diag)

Arguments

diag

A 2-column tibble::tibble specifying a persistence diagram.

Returns

A tibble::tibble storing the requested vector representation of the persistence diagram in a table suitable for visualization.


Method fit()

Fits the class on a sample of persistence diagrams.

Usage

VectorRepresentationStep$fit(X, y = NULL)

Arguments

X

A list of 2-column tibble::tibbles specifying a sample of persistence diagrams.

y

An integer vector specifying persistence diagram labels (unused for now).

Returns

The class itself invisibly.


Method transform()

Applies the class on a sample of persistence diagrams.

Usage

VectorRepresentationStep$transform(X)

Arguments

X

A list of 2-column tibble::tibbles specifying a sample of persistence diagrams.

Returns

A list of tibble::tibbles storing the requested vector representations of the persistence diagrams in a table suitable for visualization.


Method fit_transform()

Applies sequentially the $fit() and $transform() methods on a sample of persistence diagrams in a more efficient way than calling them directly.

Usage

VectorRepresentationStep$fit_transform(X, y = NULL)

Arguments

X

A list of 2-column tibble::tibbles specifying a sample of persistence diagrams.

y

An integer vector specifying persistence diagram labels (unused for now).

Returns

A list of tibble::tibbles storing the requested vector representations of the persistence diagrams in a table suitable for visualization.


Method clone()

The objects of this class are cloneable with this method.

Usage

VectorRepresentationStep$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.