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.')
arias = Arias(stream)
Ia = arias.arias_stream
NIa = Ia.normalize(False)
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
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.')
arias = Arias(stream)
Ia = arias.arias_stream
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
