def plot_trunc_gr_model(aval, bval, min_mag, max_mag, dmag, catalogue=None, completeness=None, figure_size=None, filename=None, filetype='png', dpi=300): """ 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) plt.semilogy(annual_rates[:, 0], annual_rates[:, 1], 'b-') plt.semilogy(annual_rates[:, 0], cumulative_rates, 'r-') plt.xlabel('Magnitude', fontsize='large') plt.ylabel('Annual Rate', fontsize='large') plt.legend(['Incremental Rate', 'Cumulative Rate']) _save_image(filename, filetype, dpi) else: completeness = _check_completeness_table(completeness, catalogue) plot_recurrence_model(input_model, catalogue, completeness, input_model.bin_width, figure_size, filename, filetype, dpi)
def plot_recurrence_model(input_model, catalogue, completeness, dmag, figure_size=(10, 8), filename=None, filetype='png', dpi=300): """ Plot a calculated recurrence model over an observed catalogue, adjusted for time-varying completeness """ if figure_size is None: figure_size=(10, 8) if dmag is None: dmag = 0.1 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))]) # Create plot plt.figure(figsize=figure_size) plt.semilogy(cent_mag, obs_rates, 'bo') plt.semilogy(annual_rates[:, 0], annual_rates[:, 1], 'b-') plt.semilogy(cent_mag, cum_obs_rates, 'rs') plt.semilogy(annual_rates[:, 0], cumulative_rates, 'r-') plt.grid(which='both') plt.xlabel('Magnitude', fontsize='16') plt.ylabel('Annual Rate', fontsize='16') plt.legend(['Observed Incremental Rate', 'Model Incremental Rate', 'Observed Cumulative Rate', 'Model Cumulative Rate'], fontsize=14) plt.tick_params(labelsize=12) _save_image(filename, filetype, dpi)
def plot_recurrence_models(configs, area, slip, msr, rake, shear_modulus=30.0, disp_length_ratio=1.25E-5, msr_sigma=0., filename=None, filetype='png', dpi=300): """ Plots a set of recurrence models :param list configs: List of configuration dictionaries """ plt.figure(figsize=DEFAULT_SIZE) for config in configs: model = RecurrenceBranch(area, slip, msr, rake, shear_modulus, disp_length_ratio, msr_sigma, weight=1.0) model.get_recurrence(config) occurrence = model.recurrence.occur_rates cumulative = np.array([np.sum(occurrence[iloc:]) for iloc in range(0, len(occurrence))]) if 'AndersonLuco' in config['Model_Name']: flt_label = config['Model_Name'] + ' - ' + config['Model_Type'] +\ ' Type' else: flt_label = config['Model_Name'] flt_color=np.random.uniform(0.1, 1.0, 3) plt.semilogy(model.magnitudes, cumulative, '-', label=flt_label, color=flt_color, linewidth=2.) plt.semilogy(model.magnitudes, model.recurrence.occur_rates, '--', color=flt_color, linewidth=2.) plt.xlabel('Magnitude', fontsize=14) plt.ylabel('Annual Rate', fontsize=14) plt.legend(bbox_to_anchor=(1.1, 1.0)) _save_image(filename, filetype, dpi)
def plot_recurrence_model(input_model, catalogue, completeness, dmag, filename=None, filetype='png', dpi=300): """ 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() obs_rates = get_completeness_adjusted_table(catalogue, completeness, input_model.bin_width, catalogue.end_year) # Create plot plt.semilogy(obs_rates[:, 0] + dmag / 2., obs_rates[:, 1], 'bo') plt.semilogy(annual_rates[:, 0], annual_rates[:, 1], 'b-') plt.semilogy(obs_rates[:, 0] + dmag / 2., obs_rates[:, 2], 'rs') plt.semilogy(annual_rates[:, 0], cumulative_rates, 'r-') plt.xlabel('Magnitude', fontsize='large') plt.ylabel('Annual Rate', fontsize='large') plt.legend(['Observed Incremental Rate', 'Model Incremental Rate', 'Observed Cumulative Rate', 'Model Cumulative Rate']) _save_image(filename, filetype, dpi)
def plot_recurrence_models(configs, area, slip, msr, rake, shear_modulus=30.0, disp_length_ratio=1.25E-5, msr_sigma=0., filename=None, filetype='png', dpi=300): """ Plots a set of recurrence models :param list configs: List of configuration dictionaries """ plt.figure(figsize=DEFAULT_SIZE) for config in configs: model = RecurrenceBranch(area, slip, msr, rake, shear_modulus, disp_length_ratio, msr_sigma, weight=1.0) model.get_recurrence(config) occurrence = model.recurrence.occur_rates cumulative = np.array( [np.sum(occurrence[iloc:]) for iloc in range(0, len(occurrence))]) if 'AndersonLuco' in config['Model_Name']: flt_label = config['Model_Name'] + ' - ' + config['Model_Type'] +\ ' Type' else: flt_label = config['Model_Name'] flt_color = np.random.uniform(0.1, 1.0, 3) plt.semilogy(model.magnitudes, cumulative, '-', label=flt_label, color=flt_color, linewidth=2.) plt.semilogy(model.magnitudes, model.recurrence.occur_rates, '--', color=flt_color, linewidth=2.) plt.xlabel('Magnitude', fontsize=14) plt.ylabel('Annual Rate', fontsize=14) plt.legend(bbox_to_anchor=(1.1, 1.0)) _save_image(filename, filetype, dpi)