# -*- coding: utf-8 -*-
# vim: tabstop=4 shiftwidth=4 softtabstop=4
#
# LICENSE
#
# Copyright (C) 2010-2023 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.
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# You should have received a copy of the GNU Affero General Public License
# along with OpenQuake. If not, see <http://www.gnu.org/licenses/>
#
# DISCLAIMER
#
# 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
# (https://www.globalquakemodel.org/tools-products) 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.
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# Feedback and contribution to the software is welcome, and can be
# directed to the hazard scientific staff of the GEM Model Facility
# (hazard@globalquakemodel.org).
#
# 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
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"""
Module :mod: 'openquake.hmtk.plotting.seismicity.completeness.plot_stepp_1971'
creates plot to illustrate outcome of Stepp (1972) method for completeness
analysis
"""
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] > 0.0
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="lower left", 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)
