csep.plots.plot_magnitude_histogram

csep.plots.plot_magnitude_histogram(forecast, observation=None, magnitude_bins=None, percentile=95, log_scale=True, normalize=True, cumulative=False, intervals=True, ax=None, show=False, **kwargs)[source]

Generates a semi-log magnitude histogram comparing a catalog-based forecast with observed data. The forecast’s mean and uncertainty intervals are displayed along with the observed event counts.

Usage Tutorials

Parameters:

  • forecast (CatalogForecast or list of CSEPCatalog or GriddedForecast) – A forecast or a list of observed catalogs.

  • observation (CSEPCatalog) – The observed catalog for comparison.

  • magnitude_bins (list of float or numpy.ndarray, optional) – The bins for magnitude histograms. If None, defaults to the region magnitudes or standard CSEP bins. Defaults to None.

  • percentile (int, optional) – The percentile used for uncertainty intervals. Defaults to 95.

  • log_scale (bool, optional) – Whether to plot the y-axis in logarithmic scale. Defaults to True.

  • normalize (bool, optional) – Whether to normalize the forecast for the total number in the observation catalog.

  • cumulative (bool, optional) – Whether to plot cumulative counts N(M >= m). Defaults to False.

  • intervals (bool, optional) – Whether to display forecast uncertainty intervals. Defaults to True.

  • ax (matplotlib.axes.Axes, optional) – The axes object to draw the plot on. If None, a new figure and axes are created. Defaults to None.

  • show (bool, optional) – Whether to display the plot immediately. Defaults to False.

  • **kwargs (optional) –

    Additional keyword arguments to customize the plot:

    • figsize (tuple): The size of the figure.

    • color (str): Color for the observed histogram points.

    • markersize (int): Size of the markers in the plot. Defaults to 6.

    • capsize (float): Size of the error bar caps. Defaults to 4.

    • linewidth (float): Width of the error bar lines. Defaults to 1.5.

    • xlim (tuple): Limits for the X-axis.

    • xlabel (str): Label for the X-axis. Defaults to ‘Magnitude’.

    • xlabel_fontsize (int): Font size for the X-axis label.

    • ylabel (str): Label for the Y-axis. Defaults to ‘Event count’.

    • ylabel_fontsize (int): Font size for the Y-axis label.

    • title (str): Title of the plot. Defaults to ‘Magnitude Histogram’.

    • title_fontsize (int): Font size for the plot title.

    • grid (bool): Whether to show grid lines. Defaults to True.

    • legend_loc (str): Location of the legend. Defaults to ‘best’.

    • legend_fontsize (int): Font size of the legend text.

    • tight_layout (bool): Whether to use tight layout for the figure. Defaults to True.

Returns:

The axes object containing the plot.

Return type:

matplotlib.axes.Axes

Changed in version 0.8.0: It now accepts a CatalogForecast or a GriddedForecast. An obervation CSEPCatalog is now optional. Added magnitude_bins, percentile and log_scale to fine-tune the plot. Added parameters to customize coloring, formatting and sizing of the plot elements. The plot_args dictionary is only partially supported and will be removed in v1.0.0