rsatoolbox.vis.timecourse module

Lineplot of dissimilarity over time

See demo_meg_mne for an example.

rsatoolbox.vis.timecourse.plot_timecourse(rdms_data: RDMs, descriptor: str, n_t_display: int = 20, fig_width: int | None = None, timecourse_plot_rel_height: int | None = None, time_formatted: List[str] | None = None, colored_conditions: list | None = None, plot_individual_dissimilarities: bool | None = None) → Tuple[Figure, List[Axes]][source]

plots the RDM movie for a given descriptor

Parameters:

  • rdms_data (rsatoolbox.rdm.RDMs) – rdm movie

  • descriptor (str) – name of the descriptor that created the rdm movie

  • n_t_display (int, optional) – number of RDM time points to display. Defaults to 20.

  • fig_width (int, optional) – width of the figure (in inches). Defaults to None.

  • timecourse_plot_rel_height (int, optional) – height of the timecourse plot (relative to the rdm movie row).

  • time_formatted (List[str], optional) – time points formatted as strings. Defaults to None (i.e., rdms_data.time_descriptors[‘time’] is considered to be in seconds)

  • colored_condiitons (list, optional) – vector of pattern condition names to dissimilarities

  • None. (according to a categorical model on colored_conditions Defaults to) –

  • plot_individual_dissimilarities (bool, optional) – whether to plot the individual dissimilarities. Defaults to None (i.e., False if colored_conditions is not None, True otherwise).

Returns:

Tuple of

  • Handle to created figure

  • Subplot axis handles from plt.subplots.

Return type:

Tuple[matplotlib.figure.Figure, npt.ArrayLike, collections.defaultdict]

rsatoolbox.vis.timecourse.unsquareform(a: NDArray) → NDArray[source]

Helper function; convert squareform to vector