Catalog#

class bruces.Catalog(origin_times, latitudes=None, longitudes=None, eastings=None, northings=None, depths=None, magnitudes=None)[source]#

Earthquake catalog.

Parameters:

  • origin_times (sequence of scalar or sequence of datetime_like) – Origin times (in years if scalar).

  • latitudes (array_like or None, optional, default None) – Latitudes (in degree).

  • longitudes (array_like or None, optional, default None) – Longitudes (in degree).

  • eastings (array_like or None, optional, default None) – Easting coordinates (in km). Ignored if latitudes and longitudes are set.

  • northings (array_like or None, optional, default None) – Northing coordinates (in km). Ignored if latitudes and longitudes are set.

  • depths (array_like or None, optional, default None) – Depths (in km).

  • magnitudes (array_like or None, optional, default None) – Magnitudes.

decluster(algorithm='nearest-neighbor', return_indices=False, **kwargs)[source]#

Decluster earthquake catalog.

Parameters:

  • algorithm (str, optional, default 'nearest-neighbor') –

    Declustering algorithm:

    • ’gardner-knopoff’: Gardner-Knopoff’s method (after Gardner and Knopoff, 1974)

    • ’nearest-neighbor’: nearest-neighbor algorithm (after Zaliapin and Ben-Zion, 2008)

    • ’reasenberg’: Reasenberg’s method (after Reasenberg, 1985)

  • return_indices (bool, optional, default False) – If True, return indices of background events instead of declustered catalog.

  • window (str {'default', 'gruenthal', 'uhrhammer'}, optional, default 'default') –

    Only if algorithm = "gardner-knopoff". Distance and time windows:

    • ’default’: Gardner and Knopoff (1974)

    • ’gruenthal’: personnal communication (see van Stiphout et al., 2012)

    • ’uhrhammer’: Uhrhammer (1986)

  • method (str, optional, default 'gaussian-mixture') –

    Only if algorithm = "nearest-neighbor". Declustering method:

    • ’gaussian-mixture’: use a Gaussian Mixture classifier

    • ’thinning’: random thinning (after Zaliapin and Ben-Zion, 2020)

  • d (scalar, optional, default 1.6) – Only if algorithm = "nearest-neighbor". Fractal dimension of epicenter/hypocenter.

  • w (scalar, optional, default 1.0) – Only if algorithm = "nearest-neighbor". Magnitude weighting factor (usually b-value).

  • use_depth (bool, optional, default False) – Only if algorithm = "nearest-neighbor". If True, consider depth in interevent distance calculation.

  • eta_0 (scalar or None, optional, default None) – Only if algorithm = "nearest-neighbor" and method = "thinning". Initial cutoff threshold. If None, invoke bruces.Catalog.fit_cutoff_threshold().

  • alpha_0 (scalar, optional, default 1.5) – Only if algorithm = "nearest-neighbor" and method = "thinning". Cluster threshold.

  • M (int, optional, default 16) – Only if algorithm = "nearest-neighbor" and method = "thinning". Number of reshufflings.

  • seed (int or None, optional, default None) – Only if algorithm = "nearest-neighbor". Seed for random number generator.

  • rfact (int, optional, default 10) – Only if algorithm = "reasenberg". Number of crack radii surrounding each earthquake within which to consider linking a new event into a cluster.

  • xmeff (scalar or None, optional, default None) – Only if algorithm = "reasenberg". “Effective” lower magnitude cutoff for catalog. If None, use minimum magnitude in catalog.

  • xk (scalar, optional, default 0.5) – Only if algorithm = "reasenberg". Factor by which xmeff is raised during clusters.

  • tau_min (scalar, timedelta_like or None, optional, default None) – Only if algorithm = "reasenberg". Look ahead time for non-clustered events (in days if scalar). Default is 1 day.

  • tau_max (scalar, timedelta_like or None, optional, default None) – Only if algorithm = "reasenberg". Maximum look ahead time for clustered events (in days if scalar). Default is 10 days.

  • p (scalar, optional, default 0.95) – Only if algorithm = "reasenberg". Confidence of observing the next event in the sequence.

Returns:

Declustered earthquake catalog or indices of background events.

Return type:

bruces.Catalog or array_like

property depths#

Return depths.

property eastings#

Return easting coordinates.

fit_cutoff_threshold(d=1.6, w=1.0, use_depth=False)[source]#

Estimate the optimal cutoff threshold for nearest-neighbor.

Parameters:

  • use_depth (bool, optional, default False) – If True, consider depth in interevent distance calculation.

  • d (scalar, optional, default 1.6) – Fractal dimension of epicenter/hypocenter.

  • w (scalar, optional, default 1.0) – Magnitude weighting factor (usually b-value).

Returns:

Optimal initial cutoff threshold.

Return type:

float

Note

This function assumes that the catalog is clustered.

property latitudes#

Return latitudes.

property longitudes#

Return longitudes.

property magnitudes#

Return magnitudes.

property northings#

Return northing coordinates.

property origin_times#

Return origin times.

plot_time_space_distances(d=1.6, w=1.0, use_depth=False, eta_0=None, eta_0_diag=None, kde=True, bins=50, hist_args=None, line_args=None, text_args=None, ax=None)[source]#

Plot rescaled time vs space distances.

Parameters:

  • d (scalar, optional, default 1.6) – Fractal dimension of epicenter/hypocenter.

  • w (scalar, optional, default 1.0) – Magnitude weighting factor (usually b-value).

  • use_depth (bool, optional, default False) – If True, consider depth in interevent distance calculation.

  • eta_0 (scalar, 'auto', array_like or None, optional, default None) – Initial cutoff threshold values for which to draw a constant line. If eta_0 = “auto”, invoke bruces.Catalog.fit_cutoff_threshold().

  • eta_0_diag (scalar or None, optional, default None) – If not None, plot will be centered around eta_0_diag. This option is automatically enabled if eta_0 = “auto”.

  • kde (bool, optional, default True) – If True, use Gaussian Kernel Density Estimator.

  • bins (int, optional, default 50) – Number of bins for both axes.

  • hist_args (dict or None, optional, default None) – Plot arguments passed to matplotlib.pyplot.contourf() or matplotlib.pyplot.pcolormesh().

  • line_args (dict or None, optional, default None) – Plot arguments passed to matplotlib.pyplot.plot().

  • text_args (dict or None, optional, default None) – Plot arguments passed to matplotlib.pyplot.text().

  • ax (matplotlib.pyplot.Axes or None, optional, default None) – Matplotlib axes.

Returns:

Matplotlib axes.

Return type:

matplotlib.pyplot.Axes

seismicity_rate(tbins, return_cumulative=False)[source]#

Get seismicity rate.

Parameters:

  • tbins (timedelta_like or sequence of datetime_like) – If tbins is a timedelta_like, it defines the width of each bin. If tbins is a sequence of datetime_like, it defines a monotonically increasing list of bin edges.

  • return_cumulative (bool, optional, default False) – If True, return cumulative number of events instead of seismicity rate.

Returns:

  • array_like – Seismicity rate (in events/year) or cumulative seismicity (number of events).

  • sequence of datetime_like – Dates.

time_space_distances(d=1.6, w=1.0, use_depth=False, return_logs=True, prune_nans=False)[source]#

Get rescaled time and space distances for each earthquake in the catalog.

Parameters:

  • d (scalar, optional, default 1.6) – Fractal dimension of epicenter/hypocenter.

  • w (scalar, optional, default 1.0) – Magnitude weighting factor (usually b-value).

  • use_depth (bool, optional, default False) – If True, consider depth in interevent distance calculation.

  • return_logs (bool, optional, default True) – If True, return distance as log10.

  • prune_nans (bool, optional, default False) – If True, remove NaN values from output.

Returns:

  • array_like – Rescaled time distances.

  • array_like – Rescaled space distances.

write(filename, file_format=None, **kwargs)[source]#

Write catalog to CSV file.

Parameters:

  • filename (str, pathlike or buffer) – Output file name or buffer.

  • file_format (str ('csv') or None, optional, default None) – Output file format.

property years#

Return origin times in decimal years.