Source code for openquake.hmtk.plotting.seismicity.completeness.plot_stepp_1972

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

# Copyright (C) 2010-2022 GEM Foundation, G. Weatherill, M. Pagani,
# D. Monelli.
# The Hazard Modeller's Toolkit is free software: you can redistribute
# it and/or modify it under the terms of the GNU Affero General Public
# License as published by the Free Software Foundation, either version
# 3 of the License, or (at your option) any later version.
# You should have received a copy of the GNU Affero General Public License
# along with OpenQuake. If not, see <>
# The software Hazard Modeller's Toolkit (openquake.hmtk) provided herein
# is released as a prototype implementation on behalf of
# scientists and engineers working within the GEM Foundation (Global
# Earthquake Model).
# It is distributed for the purpose of open collaboration and in the
# hope that it will be useful to the scientific, engineering, disaster
# risk and software design communities.
# The software is NOT distributed as part of GEM’s OpenQuake suite
# ( and must be considered as a
# separate entity. The software provided herein is designed and implemented
# by scientific staff. It is not developed to the design standards, nor
# subject to same level of critical review by professional software
# developers, as GEM’s OpenQuake software suite.
# Feedback and contribution to the software is welcome, and can be
# directed to the hazard scientific staff of the GEM Model Facility
# (
# The Hazard Modeller's Toolkit (openquake.hmtk) is therefore distributed
# WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or
# FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License
# for more details.
# The GEM Foundation, and the authors of the software, assume no
# liability for use of the software.

Module :mod: 'openquake.hmtk.plotting.seismicity.completeness.plot_stepp_1971'
creates plot to illustrate outcome of Stepp (1972) method for completeness
import os.path
import itertools

import numpy as np
import matplotlib.pyplot as plt

# markers which can be filled or empty
VALID_MARKERS = ['s', 'o', '^', 'D', 'p', 'h', '8',
                 '*', 'd', 'v', '<', '>', 'H']

[docs]def create_stepp_plot(model, figure_size=(8, 6), filename=None, filetype='png', dpi=300, ax=None): ''' Creates the classic Stepp (1972) plots for a completed Stepp analysis, and exports the figure to a file. :param model: Completed Stepp (1972) analysis as instance of :class: `openquake.hmtk.seismicity.completeness.comp_stepp_1971.Stepp1971` :param string filename: Name of output file :param string filetype: Type of file (from list supported by matplotlib) :param int dpi: Resolution (dots per inch) of output file ''' if ax is None: fig, ax = plt.subplots(figsize=figure_size) else: fig = ax.get_figure() if filename and os.path.exists(filename): raise IOError('File already exists!') # get colours from current axes: thus user can set up before calling prop_cycler = ax._get_lines.prop_cycler prop_cyclers = itertools.tee(itertools.cycle(prop_cycler), 3) marker_cyclers = itertools.tee(itertools.cycle(VALID_MARKERS), 3) # plot observed Sigma lambda for i, (min_mag, max_mag) in enumerate(zip(model.magnitude_bin[:-1], model.magnitude_bin[1:])): label = '(%g, %g]: %d' % (min_mag, max_mag, model.completeness_table[i, 0]) colour = next(prop_cyclers[0])['color'] ax.loglog(model.time_values, model.sigma[:, i], linestyle='none', marker=next(marker_cyclers[0]), markersize=3, markerfacecolor=colour, markeredgecolor=colour, label=label) # plot expected Poisson rate for i in range(0, len(model.magnitude_bin) - 1): ax.loglog(model.time_values, model.model_line[:, i], color=next(prop_cyclers[1])['color'], linewidth=0.5) # mark breaks from expected rate for i in range(0, len(model.magnitude_bin) - 1): colour = next(prop_cyclers[2])['color'] if np.any(np.isnan(model.model_line[:, i])): continue xmarker = model.end_year - model.completeness_table[i, 0] knee = model.model_line[:, i] > 0. ymarker = 10.0 ** np.interp(np.log10(xmarker), np.log10(model.time_values[knee]), np.log10(model.model_line[knee, i])) ax.loglog(xmarker, ymarker, marker=next(marker_cyclers[2]), markerfacecolor='white', markeredgecolor=colour) ax.legend(loc='center left', bbox_to_anchor=(1, 0.5), frameon=False, fontsize='small') ax.set_xlabel('Time (years)') ax.set_ylabel("$\\sigma_{\\lambda} = \\sqrt{\\lambda} / \\sqrt{T}$") ax.autoscale(enable=True, axis='both', tight=True) # save figure to file if filename is not None: fig.savefig(filename, dpi=dpi, format=filetype)