FPCAPlot

class skfda.exploratory.visualization.FPCAPlot(mean, components, *, factor=1, multiple=None, chart=None, fig=None, axes=None, n_rows=None, n_cols=None)

FPCAPlot visualization.

Parameters:

• mean (FData) – The functional data object containing the mean function. If len(mean) > 1, the mean is computed.

• components (FData) – The principal components

• factor (float) – Multiple of the principal component curve to be added or subtracted.

• fig (Figure | None) – Figure over which the graph is plotted. If not specified it will be initialized

• axes (Axes | None) – Axes over where the graph is plotted. If None, see param fig.

• n_rows (int | None) – Designates the number of rows of the figure.

• n_cols (int | None) – Designates the number of columns of the figure.

• multiple (float | None) –

• chart (Figure | Axes | None) –

Methods

hover(event)	Activate the annotation when hovering a point.
plot()	Plot the object and its data.

hover(event)

Activate the annotation when hovering a point.

Callback method that activates the annotation when hovering a specific point in a graph. The annotation is a description of the point containing its coordinates.

Parameters:

event (MouseEvent) – event object containing the artist of the point hovered.

Return type:

None

plot()

Plot the object and its data.

Returns:

figure object in which the displays and

widgets will be plotted.

Return type:

Figure

Examples using skfda.exploratory.visualization.FPCAPlot

Functional Principal Component Analysis

Functional Principal Component Analysis

Meteorological data: data visualization, clustering, and functional PCA

Meteorological data: data visualization, clustering, and functional PCA