Source code for openquake.hmtk.plotting.seismicity.completeness.cumulative_rate_analysis

# -*- coding: utf-8 -*-
# vim: tabstop=4 shiftwidth=4 softtabstop=4

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# D. Monelli.
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Module openquake.hmtk.plotting.seismicity.completeness.simple_completeness is a graphical
function for estimating the completeness period of magnitude intervals
by plotting the cumulative rate of events with time in each interval

import numpy as np
import pylab
import matplotlib.pyplot as plt
from openquake.hmtk.seismicity.completeness.base import (

[docs]class SimpleCumulativeRate(BaseCatalogueCompleteness): ''' Class to define the temporal variation in completess using simple changes in cumulative rates in individual completeness bins '''
[docs] def completeness(self, catalogue, config, saveplot=False, filetype='png', timeout=120): ''' :param catalogue: Earthquake catalogue as instance of :class:`openquake.hmtk.seismicity.catalogue.Catalogue` :param dict config: Configuration parameters of the algorithm, containing the following information: 'magnitude_bin' Size of magnitude bin (non-negative float) 'time_bin' Size (in dec. years) of the time window (non-negative float) 'increment_lock' Boolean to indicate whether to ensure completeness magnitudes always decrease with more recent bins :returns: 2-column table indicating year of completeness and corresponding magnitude numpy.ndarray ''' if saveplot and not isinstance(saveplot, str): raise ValueError('To save the figures enter a filename: ') # Get magntitude bins magnitude_bins = self._get_magnitudes_from_spacing(['magnitude'], config['magnitude_bin']) dec_time = catalogue.get_decimal_time() completeness_table = np.zeros([len(magnitude_bins) - 1, 2], dtype=float) min_year = float(np.min(['year'])) max_year = float(np.max(['year'])) + 1.0 has_completeness = np.zeros(len(magnitude_bins) - 1, dtype=bool) for iloc in range(0, len(magnitude_bins) - 1): lower_mag = magnitude_bins[iloc] upper_mag = magnitude_bins[iloc + 1] idx = np.logical_and(['magnitude'] >= lower_mag,['magnitude'] < upper_mag) cumvals = np.cumsum(np.ones(np.sum(idx))) plt.plot(dec_time[idx], cumvals, '.') plt.xlim(min_year, max_year + 5) title_string = 'Magnitude %5.2f to %5.2f' % (lower_mag, upper_mag) plt.title(title_string) pts = pylab.ginput(1, timeout=timeout)[0] if pts[0] <= max_year: # Magnitude bin has no completeness! has_completeness[iloc] = True completeness_table[iloc, 0] = np.floor(pts[0]) completeness_table[iloc, 1] = magnitude_bins[iloc] print(completeness_table[iloc, :], has_completeness[iloc]) if config['increment_lock'] and (iloc > 0) and \ (completeness_table[iloc, 0] > completeness_table[iloc - 1, 0]): completeness_table[iloc, 0] = \ completeness_table[iloc - 1, 0] # Add marker line to indicate completeness point marker_line = np.array([ [0., completeness_table[iloc, 0]], [cumvals[-1], completeness_table[iloc, 0]]]) plt.plot(marker_line[:, 0], marker_line[:, 1], 'r-') if saveplot: filename = saveplot + '_' + ('%5.2f' % lower_mag) + ( '%5.2f' % upper_mag) + '.' + filetype plt.savefig(filename, format=filetype) plt.close() return completeness_table[has_completeness, :]
def _get_magnitudes_from_spacing(self, magnitudes, delta_m): '''If a single magnitude spacing is input then create the bins :param numpy.ndarray magnitudes: Vector of earthquake magnitudes :param float delta_m: Magnitude bin width :returns: Vector of magnitude bin edges (numpy.ndarray) ''' min_mag = np.min(magnitudes) max_mag = np.max(magnitudes) if (max_mag - min_mag) < delta_m: raise ValueError('Bin width greater than magnitude range!') mag_bins = np.arange(np.floor(min_mag), np.ceil(max_mag), delta_m) # Check to see if there are magnitudes in lower and upper bins is_mag = np.logical_and(mag_bins - max_mag < delta_m, min_mag - mag_bins < delta_m) mag_bins = mag_bins[is_mag] return mag_bins