VectorRepresentationStep: Vector Representation Step

VectorRepresentationStepR Documentation

Vector Representation Step

Description

Vector Representation Step

Vector Representation Step

Super classes

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

Methods

Public 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.

Author(s)

Mathieu Carrière


rgudhi documentation built on March 31, 2023, 11:38 p.m.