iqm.error_reduction_tools.readout_characterization.visualization.plot_covariance_heatmaps

iqm.error_reduction_tools.readout_characterization.visualization.plot_covariance_heatmaps#

iqm.error_reduction_tools.readout_characterization.visualization.plot_covariance_heatmaps(covariance_data, vmax=None, show_plot=True)#

Generate heatmap visualizations for all correlation matrices.

Creates one heatmap per error category from covariance analysis. Provides a matrix view complementary to topology-based visualization. Designed to accept direct outputs from compute_*_covariance functions.

Parameters:

  • covariance_data (SingleCovarianceData | StateCovarianceData) – Obtained from the compute_*_covariance functions.

  • vmax (float | None) – Colormap saturation value. If None, uses max absolute covariance per matrix.

  • show_plot (bool) – If True, displays all heatmaps. If False, returns Figure list.

Returns:

Matplotlib figures if show_plot=False, otherwise None.

Return type:

list[Figure] | None

Example

>>> result = compute_state_dependent_covariance(data)
>>> plot_covariance_heatmaps(result, vmax=0.01)
# Displays 12 heatmaps (one per error pair combination)
Contents