def test_acceleration():
datafiles, _ = read_data_dir("geonet", "us1000778i", "20161113_110259_WTMC_20.V2A")
acc_file = datafiles[0]
acc = read_data(acc_file)[0]
target_g = acc[0].data * GAL_TO_PCTG
target_m = acc[0].data / 100
target_cm = acc[0].data
acc_g = get_acceleration(acc, units="%%g")
assert acc_g[0].stats["units"] == "%%g"
np.testing.assert_allclose(acc_g[0], target_g)
acc_m = get_acceleration(acc, units="m/s/s")
assert acc_m[0].stats["units"] == "m/s/s"
np.testing.assert_allclose(acc_m[0], target_m)
acc_cm = get_acceleration(acc, units="cm/s/s")
assert acc_cm[0].stats["units"] == "cm/s/s"
np.testing.assert_allclose(acc_cm[0], target_cm)
def test_acceleration():
datafiles, _ = read_data_dir('geonet', 'us1000778i',
'20161113_110259_WTMC_20.V2A')
acc_file = datafiles[0]
acc = read_data(acc_file)[0]
target_g = acc[0].data * GAL_TO_PCTG
target_m = acc[0].data / 100
target_cm = acc[0].data
acc_g = get_acceleration(acc, units='%%g')
assert acc_g[0].stats['units'] == '%%g'
np.testing.assert_allclose(acc_g[0], target_g)
acc_m = get_acceleration(acc, units='m/s/s')
assert acc_m[0].stats['units'] == 'm/s/s'
np.testing.assert_allclose(acc_m[0], target_m)
acc_cm = get_acceleration(acc, units='cm/s/s')
assert acc_cm[0].stats['units'] == 'cm/s/s'
np.testing.assert_allclose(acc_cm[0], target_cm)
def test_acceleration():
datafiles, _ = read_data_dir(
'geonet', 'us1000778i', '20161113_110259_WTMC_20.V2A')
acc_file = datafiles[0]
acc = read_data(acc_file)[0]
target_g = acc[0].data * GAL_TO_PCTG
target_m = acc[0].data / 100
target_cm = acc[0].data
acc_g = get_acceleration(acc, units='%%g')
assert acc_g[0].stats['units'] == '%%g'
np.testing.assert_allclose(acc_g[0], target_g)
acc_m = get_acceleration(acc, units='m/s/s')
assert acc_m[0].stats['units'] == 'm/s/s'
np.testing.assert_allclose(acc_m[0], target_m)
acc_cm = get_acceleration(acc, units='cm/s/s')
assert acc_cm[0].stats['units'] == 'cm/s/s'
np.testing.assert_allclose(acc_cm[0], target_cm)
def generate_oscillators(self,
imts,
sa_periods,
fas_periods,
rotate=False):
"""
Create dictionary of requested imt and its coinciding oscillators.
Args:
imts (list): List of imts.
sa_periods (list): List of periods. Used to generate the SA
oscillators.
fas_periods (list): List of periods. Used to generate the FAS
oscillators.
rotate (bool): Whether to rotate the sa oscillators for the ROTD
component.
Returns:
dictionary: dictionary of oscillators for each imt.
Notes:
Damping value must be set.
"""
if self.stream is None:
raise Exception('StationSummary.stream is not set.')
oscillator_dict = OrderedDict()
for imt in imts:
stream = self.stream.copy()
if imt.upper() == 'PGA':
oscillator = get_acceleration(stream)
oscillator_dict['PGA'] = oscillator
elif imt.upper() == 'PGV':
oscillator = get_velocity(stream)
oscillator_dict['PGV'] = oscillator
elif imt.upper() == 'FAS':
oscillator = get_acceleration(stream, 'cm/s/s')
oscillator_dict['FAS'] = oscillator
elif imt.upper().startswith('SA'):
for period in sa_periods:
tag = 'SA(' + str(period) + ')'
oscillator = get_spectral(period,
stream,
damping=self.damping)
oscillator_dict[tag] = oscillator
if rotate:
oscillator = get_spectral(period,
stream,
damping=self.damping,
rotation='nongm')
oscillator_dict[tag + '_ROT'] = oscillator
elif imt.upper() == 'ARIAS':
oscillator = get_acceleration(stream, units='m/s/s')
oscillator_dict['ARIAS'] = oscillator
else:
fmt = "Invalid imt: %r. Skipping..."
logging.warning(fmt % (imt))
imts = []
for key in oscillator_dict:
if key == 'FAS':
for period in fas_periods:
imts += ['FAS(' + str(period) + ')']
elif key.find('ROT') < 0:
imts += [key]
self.imts = imts
self.oscillators = oscillator_dict
def plot_arias(stream,
axes=None,
axis_index=None,
figsize=None,
file=None,
minfontsize=14,
show=False,
show_maximum=True,
title=None,
xlabel=None,
ylabel=None):
"""
Create plots of arias intensity.
Args:
stream (obspy.core.stream.Stream):
Set of acceleration data with units of gal (cm/s/s).
axes (ndarray):
Array of subplots. Default is None.
axis_index (int):
First index of axes array to plot the traces. Default is None.
Required if axes is not None.
figsize (tuple):
Tuple of height and width. Default is None.
file (str):
File where the image will be saved. Default is None.
minfontsize (int):
Minimum font size. Default is 14.
show (bool):
Plot the figure. Default is False.
show_maximum (bool):
Show the maximum value.
title (str):
Title for plot. Default is None.
xlabel (str):
Label for x axis. Default is None.
ylabel (str):
Label for y axis. Default is None.
Returns:
numpy.ndarray: Array of matplotlib.axes._subplots.AxesSubplot.
"""
if len(stream) < 1:
raise Exception('No traces contained within the provided stream.')
stream = get_acceleration(stream, units='m/s/s')
Ia = calculate_arias(stream, ['channels'], True)[0]
starttime = stream[0].stats.starttime
if title is None:
title = ('Event on ' + str(starttime.month) + '/' +
str(starttime.day) + '/' + str(starttime.year))
if xlabel is None:
xlabel = 'Time (s)'
if ylabel is None:
ylabel = 'Ia (m/s)'
if figsize is None:
figsize = (6.5, 7.5)
if axes is None:
fig, axs = plt.subplots(len(Ia), 1, figsize=figsize)
axis_numbers = np.linspace(0, len(Ia) - 1, len(Ia))
elif axis_index is not None:
axs = axes
axis_numbers = np.linspace(axis_index, axis_index + len(Ia) - 1,
len(Ia))
for idx, trace in zip(axis_numbers.astype(int), Ia):
ax = axs[idx]
dt = trace.stats['delta']
npts = len(trace.data)
t = np.linspace(0, (npts - 1) * dt, num=npts)
network = trace.stats['network']
station = trace.stats['station']
channel = trace.stats['channel']
trace_label = network + '.' + station + '.' + channel
ax.set_title(trace_label, fontsize=minfontsize)
ax.plot(t, trace.data)
if show_maximum:
abs_arr = np.abs(trace.data.copy())
idx = np.argmax(abs_arr)
max_value = abs_arr[idx]
ax.plot([t[idx]], [trace.data[idx]], marker='o', color="red")
ax.annotate('%.2E' % max_value, (t[idx], trace.data[idx]),
xycoords='data',
xytext=(.85, 0.25),
textcoords='axes fraction',
arrowprops=dict(facecolor='black',
shrink=0.05,
width=1,
headwidth=4),
horizontalalignment='right',
verticalalignment='top')
ax.set_xlabel(xlabel, fontsize=minfontsize)
ax.set_ylabel(ylabel, fontsize=minfontsize)
ax.xaxis.set_tick_params(labelsize=minfontsize - 2)
ax.yaxis.set_tick_params(labelsize=minfontsize - 2)
plt.suptitle(title, y=1.01, fontsize=minfontsize + 4)
plt.tight_layout()
if show and axes is None:
plt.show()
if file is not None and axes is None:
fig.savefig(file, format='png')
return axs
def plot_durations(stream,
durations,
axes=None,
axis_index=None,
figsize=None,
file=None,
minfontsize=14,
show=False,
title=None,
xlabel=None,
ylabel=None):
"""
Create plots of durations.
Args:
stream (obspy.core.stream.Stream):
Set of acceleration data with units of gal (cm/s/s).
durations (list):
List of percentage minimum and maximums (tuple).
axes (ndarray):
Array of subplots. Default is None.
axis_index (int):
First index of axes array to plot the traces. Default is None.
Required if axes is not None.
figsize (tuple):
Tuple of height and width. Default is None.
file (str):
File where the image will be saved. Default is None.
show (bool):
Plot the figure. Default is False.
title (str):
Title for plot. Default is None.
xlabel (str):
Label for x axis. Default is None.
ylabel (str):
Label for y axis. Default is None.
Returns:
numpy.ndarray: Array of matplotlib.axes._subplots.AxesSubplot.
"""
if len(stream) < 1:
raise Exception('No traces contained within the provided stream.')
stream = get_acceleration(stream, units='m/s/s')
NIa = calculate_arias(stream, ['channels'], True)[1]
starttime = stream[0].stats.starttime
if title is None:
title = ('Event on ' + str(starttime.month) + '/' +
str(starttime.day) + '/' + str(starttime.year))
if xlabel is None:
xlabel = 'Time (s)'
if ylabel is None:
ylabel = 'NIa (m/s)'
if figsize is None:
figsize = (6.5, 7.5)
if axes is None:
fig, axs = plt.subplots(len(NIa), 1, figsize=figsize)
axis_numbers = np.linspace(0, len(NIa) - 1, len(NIa))
elif axis_index is not None:
axs = axes
axis_numbers = np.linspace(axis_index, axis_index + len(NIa) - 1,
len(NIa))
for idx, trace in zip(axis_numbers.astype(int), NIa):
ax = axs[idx]
dt = trace.stats['delta']
npts = len(trace.data)
t = np.linspace(0, (npts - 1) * dt, num=npts)
network = trace.stats['network']
station = trace.stats['station']
channel = trace.stats['channel']
trace_label = network + '.' + station + '.' + channel
ax.set_title(trace_label, fontsize=minfontsize)
ax.plot(t, trace.data)
if xlabel:
ax.set_xlabel(xlabel)
if xlabel:
ax.set_ylabel(ylabel)
for i, duration in enumerate(durations):
first_percentile = duration[0]
second_percentile = duration[1]
t1 = get_time_from_percent(trace.data, first_percentile, dt)
t2 = get_time_from_percent(trace.data, second_percentile, dt)
height = (1 / (len(durations) + 1) * i) + 1 / (len(durations) + 1)
ax.plot(t1, first_percentile, 'ok')
ax.plot(t2, second_percentile, 'ok')
ax.annotate('',
xy=(t1, height),
xytext=(t2, height),
arrowprops=dict(arrowstyle='<->'))
label = '$D_{%i{-}%i}$' % (100 * duration[0], 100 * duration[1])
ax.text(t2,
height,
label,
style='italic',
horizontalalignment='left',
verticalalignment='center')
ax.set_xlabel(xlabel, fontsize=minfontsize)
ax.set_ylabel(ylabel, fontsize=minfontsize)
ax.xaxis.set_tick_params(labelsize=minfontsize - 2)
ax.yaxis.set_tick_params(labelsize=minfontsize - 2)
plt.suptitle(title, y=1.01, fontsize=minfontsize + 4)
plt.tight_layout()
if show and axes is None:
plt.show()
if file is not None and axes is None:
if not file.endswith(".png"):
file += ".png"
fig.savefig(file)
return axs