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_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)
