core.recurrence_matrix.RecurrenceMatrix

core.recurrence_matrix.RecurrenceMatrix(
    matrix,
    time,
    epsilon,
    m,
    tau,
    series=None,
    value_name=None,
    value_unit=None,
    time_name=None,
    time_unit=None,
    label=None,
)

Recurrence matrix object. Used for Recurrence Quantification Analysis (RQA).

Methods

Name	Description
laplacian_eigenmaps	Function to run regime change detection workflow
plot	Plotting function for recurrence matrices

laplacian_eigenmaps

core.recurrence_matrix.RecurrenceMatrix.laplacian_eigenmaps(w_size, w_incre)

Function to run regime change detection workflow

Parameters

w_size : int

Window size for the fisher information

w_incre : int

Window increment for the fisher information

Returns

FI_series : ammonyte.RQARes

RQARes object containing the Fisher Information time series derived from the Laplacian eigenmaps of the recurrence matrix.

plot

core.recurrence_matrix.RecurrenceMatrix.plot(
    figsize=(8, 8),
    xlabel=None,
    ylabel=None,
    title=None,
    imshow_kwargs=None,
)

Plotting function for recurrence matrices

Parameters

figsize : tuple = (8, 8)

Size of figure

xlabel : str = None

Label on x axis (if time name and units are present they will be used)

ylabel : str = None

Label on y axis (if time name and units are present they will be used)

title : str = None

Title of the plot

imshow_kwargs : dict = None

Dictionary of key word arguments for the imshow method from matplotlib.axes.Axes.imshow

Returns

fig : matplotlib.figure.Figure

The figure object from matplotlib. See matplotlib.pyplot.figure <https://matplotlib.org/stable/api/figure_api.html>_ for details.

ax : matplotlib.axes.Axes

The axis object from matplotlib. See matplotlib.axes <https://matplotlib.org/stable/api/axes_api.html>_ for details.

See Also

matplotlib.axes.Axes.imshow