def plot_tf(data, delta):
"""
Plots a time frequency representation of any time series.
"""
npts = len(data)
plotTfr(data, dt=delta, fmin=1.0 / (npts * delta),
fmax=1.0 / (2.0 * delta))
def test_plot_tfr(self):
n = 295
t, dt = np.linspace(0., 20 * np.pi, n, retstep=True)
sig = np.sin(t)
with ImageComparison(self.path, 'time_frequency_representation.png') \
as ic:
plotTfr(sig, dt=dt, show=False)
plt.savefig(ic.name)
def test_plot_tfr(self):
n = 295
t, dt = np.linspace(0., 20 * np.pi, n, retstep=True)
sig = np.sin(t)
with ImageComparison(self.path, 'time_frequency_representation.png') \
as ic:
plotTfr(sig, dt=dt, show=False)
plt.savefig(ic.name)
def plot_tf(data, delta):
"""
Plots a time frequency representation of any time series.
"""
npts = len(data)
plotTfr(data,
dt=delta,
fmin=1.0 / (npts * delta),
fmax=1.0 / (2.0 * delta))
def plot_tf(data, delta, freqmin=None, freqmax=None):
"""
Plots a time frequency representation of any time series. Right now it is
basically limited to plotting source time functions.
"""
npts = len(data)
fig = plotTfr(data, dt=delta, fmin=1.0 / (npts * delta),
fmax=1.0 / (2.0 * delta), show=False)
# Get the different axes...use some kind of logic to determine which is
# which. This is super flaky as dependent on the ObsPy version and what
# not.
axes = {}
for ax in fig.axes:
xlim = ax.get_xlim()
ylim = ax.get_ylim()
# Colorbar.
if xlim == ylim:
continue
# Spectral axis.
elif xlim[0] > xlim[1]:
axes["spec"] = ax
elif ylim[0] < 0:
axes["time"] = ax
else:
axes["tf"] = ax
fig.suptitle("Source Time Function")
if len(axes) != 3:
msg = "Could not plot frequency limits!"
print msg
plt.gcf().patch.set_alpha(0.0)
plt.show()
return
axes["spec"].grid()
axes["time"].grid()
axes["tf"].grid()
axes["spec"].xaxis.tick_top()
axes["spec"].set_ylabel("Frequency [Hz]")
axes["time"].set_xlabel("Time [s]")
axes["time"].set_ylabel("Velocity [m/s]")
if freqmin is not None and freqmax is not None:
xmin, xmax = axes["tf"].get_xlim()
axes["tf"].hlines(freqmin, xmin, xmax, color="green", lw=2)
axes["tf"].hlines(freqmax, xmin, xmax, color="red", lw=2)
axes["tf"].text(xmax - (0.02 * (xmax - xmin)),
freqmin,
"%.1f s" % (1.0 / freqmin),
color="green",
horizontalalignment="right", verticalalignment="top")
axes["tf"].text(xmax - (0.02 * (xmax - xmin)),
freqmax,
"%.1f s" % (1.0 / freqmax),
color="red",
horizontalalignment="right",
verticalalignment="bottom")
xmin, xmax = axes["spec"].get_xlim()
axes["spec"].hlines(freqmin, xmin, xmax, color="green", lw=2)
axes["spec"].hlines(freqmax, xmin, xmax, color="red", lw=2)
plt.gcf().patch.set_alpha(0.0)
plt.show()
def plot_tf(data, delta, freqmin=None, freqmax=None):
"""
Plots a time frequency representation of any time series. Right now it is
basically limited to plotting source time functions.
"""
npts = len(data)
fig = plotTfr(data,
dt=delta,
fmin=1.0 / (npts * delta),
fmax=1.0 / (2.0 * delta),
show=False)
# Get the different axes...use some kind of logic to determine which is
# which. This is super flaky as dependent on the ObsPy version and what
# not.
axes = {}
for ax in fig.axes:
xlim = ax.get_xlim()
ylim = ax.get_ylim()
# Colorbar.
if xlim == ylim:
continue
# Spectral axis.
elif xlim[0] > xlim[1]:
axes["spec"] = ax
elif ylim[0] < 0:
axes["time"] = ax
else:
axes["tf"] = ax
fig.suptitle("Source Time Function")
if len(axes) != 3:
msg = "Could not plot frequency limits!"
print msg
plt.gcf().patch.set_alpha(0.0)
plt.show()
return
axes["spec"].grid()
axes["time"].grid()
axes["tf"].grid()
axes["spec"].xaxis.tick_top()
axes["spec"].set_ylabel("Frequency [Hz]")
axes["time"].set_xlabel("Time [s]")
axes["time"].set_ylabel("Velocity [m/s]")
if freqmin is not None and freqmax is not None:
xmin, xmax = axes["tf"].get_xlim()
axes["tf"].hlines(freqmin, xmin, xmax, color="green", lw=2)
axes["tf"].hlines(freqmax, xmin, xmax, color="red", lw=2)
axes["tf"].text(xmax - (0.02 * (xmax - xmin)),
freqmin,
"%.1f s" % (1.0 / freqmin),
color="green",
horizontalalignment="right",
verticalalignment="top")
axes["tf"].text(xmax - (0.02 * (xmax - xmin)),
freqmax,
"%.1f s" % (1.0 / freqmax),
color="red",
horizontalalignment="right",
verticalalignment="bottom")
xmin, xmax = axes["spec"].get_xlim()
axes["spec"].hlines(freqmin, xmin, xmax, color="green", lw=2)
axes["spec"].hlines(freqmax, xmin, xmax, color="red", lw=2)
plt.gcf().patch.set_alpha(0.0)
plt.show()
import numpy as np
from obspy.signal.tf_misfit import plotTfr
# general constants
tmax = 6.
dt = 0.01
npts = int(tmax / dt + 1)
t = np.linspace(0., tmax, npts)
fmin = .5
fmax = 10
# constants for the signal
A1 = 4.
t1 = 2.
f1 = 2.
phi1 = 0.
# generate the signal
H1 = (np.sign(t - t1) + 1) / 2
st1 = A1 * (t - t1) * np.exp(-2 * (t - t1)) * \
np.cos(2. * np.pi * f1 * (t - t1) + phi1 * np.pi) * H1
plotTfr(st1, dt=dt, fmin=fmin, fmax=fmax)
