Source code for openquake.hmtk.plotting.seismicity.occurrence.recurrence_plot

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

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# D. Monelli.
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Simple plots for the recurrence model

import numpy as np
import matplotlib.pyplot as plt
from openquake.hmtk.plotting.seismicity.catalogue_plots import _save_image
from openquake.hmtk.seismicity.occurrence.utils import get_completeness_counts
from openquake.hazardlib.mfd.truncated_gr import TruncatedGRMFD
from openquake.hazardlib.mfd.evenly_discretized import EvenlyDiscretizedMFD
from openquake.hazardlib.mfd.youngs_coppersmith_1985 import\

def _get_recurrence_model(input_model):
    Returns the annual and cumulative recurrence rates predicted by the
    recurrence model
    if not isinstance(input_model, (TruncatedGRMFD,
        raise ValueError('Recurrence model not recognised')
    # Get model annual occurrence rates
    annual_rates = input_model.get_annual_occurrence_rates()
    annual_rates = np.array([[val[0], val[1]] for val in annual_rates])
    # Get cumulative rates
    cumulative_rates = np.array([np.sum(annual_rates[iloc:, 1])
                                 for iloc in range(0, len(annual_rates), 1)])
    return annual_rates, cumulative_rates

def _check_completeness_table(completeness, catalogue):
    Generates the completeness table according to different instances
    if isinstance(completeness, np.ndarray) and np.shape(completeness)[1] == 2:
        return completeness
    elif isinstance(completeness, float):
        return np.array([[float(np.min(['year'])),
    elif completeness is None:
        return np.array([[float(np.min(['year'])),
        raise ValueError('Completeness representation not recognised')

[docs]def plot_recurrence_model( input_model, catalogue, completeness, dmag=0.1, filename=None, figure_size=(8, 6), filetype='png', dpi=300, ax=None): """ Plot a calculated recurrence model over an observed catalogue, adjusted for time-varying completeness """ annual_rates, cumulative_rates = _get_recurrence_model(input_model) # Get observed annual recurrence if not catalogue.end_year: catalogue.update_end_year() cent_mag, t_per, n_obs = get_completeness_counts(catalogue, completeness, dmag) obs_rates = n_obs / t_per cum_obs_rates = np.array([np.sum(obs_rates[i:]) for i in range(len(obs_rates))]) if ax is None: fig, ax = plt.subplots(figsize=figure_size) else: fig = ax.get_figure() ax.semilogy(cent_mag, obs_rates, 'bo') ax.semilogy(annual_rates[:, 0], annual_rates[:, 1], 'b-') ax.semilogy(cent_mag, cum_obs_rates, 'rs') ax.semilogy(annual_rates[:, 0], cumulative_rates, 'r-') ax.grid(which='both') ax.set_xlabel('Magnitude') ax.set_ylabel('Annual Rate') ax.legend(['Observed Incremental Rate', 'Model Incremental Rate', 'Observed Cumulative Rate', 'Model Cumulative Rate']) ax.tick_params(labelsize=12) _save_image(fig, filename, filetype, dpi)
[docs]def plot_trunc_gr_model( aval, bval, min_mag, max_mag, dmag, catalogue=None, completeness=None, filename=None, figure_size=(8, 6), filetype='png', dpi=300, ax=None): """ Plots a Gutenberg-Richter model """ input_model = TruncatedGRMFD(min_mag, max_mag, dmag, aval, bval) if not catalogue: # Plot only the modelled recurrence annual_rates, cumulative_rates = _get_recurrence_model(input_model) if ax is None: fig, ax = plt.subplots(figsize=figure_size) else: fig = ax.get_figure() ax.semilogy(annual_rates[:, 0], annual_rates[:, 1], 'b-') ax.semilogy(annual_rates[:, 0], cumulative_rates, 'r-') ax.xlabel('Magnitude') ax.set_ylabel('Annual Rate') ax.set_legend(['Incremental Rate', 'Cumulative Rate']) _save_image(fig, filename, filetype, dpi) else: completeness = _check_completeness_table(completeness, catalogue) plot_recurrence_model( input_model, catalogue, completeness, dmag, filename=filename, figure_size=figure_size, filetype=filetype, dpi=dpi, ax=ax)