VectorRepresentationStep | R Documentation |
Vector Representation Step
Vector Representation Step
rgudhi::PythonClass
-> rgudhi::SKLearnClass
-> VectorRepresentationStep
apply()
Applies the class on a single persistence diagram and outputs the result.
VectorRepresentationStep$apply(diag)
diag
A 2-column tibble::tibble specifying a persistence diagram.
A tibble::tibble storing the requested vector representation of the persistence diagram in a table suitable for visualization.
fit()
Fits the class on a sample of persistence diagrams.
VectorRepresentationStep$fit(X, y = NULL)
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).
The class itself invisibly.
transform()
Applies the class on a sample of persistence diagrams.
VectorRepresentationStep$transform(X)
X
A list of 2-column tibble::tibbles specifying a sample of persistence diagrams.
A list of tibble::tibbles storing the requested vector representations of the persistence diagrams in a table suitable for visualization.
fit_transform()
Applies sequentially the $fit()
and $transform()
methods
on a sample of persistence diagrams in a more efficient way than
calling them directly.
VectorRepresentationStep$fit_transform(X, y = NULL)
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).
A list of tibble::tibbles storing the requested vector representations of the persistence diagrams in a table suitable for visualization.
clone()
The objects of this class are cloneable with this method.
VectorRepresentationStep$clone(deep = FALSE)
deep
Whether to make a deep clone.
Mathieu Carrière
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