def plot_spectrum(self, ax=None, tickfmt=None, ntraces=10, fontsize=10):
"""
Plot a power spectrum.
w is window length for smoothing filter
"""
if ax is None:
fig = plt.figure(figsize=(12,6))
ax = fig.add_subplot(111)
trace_indices = utils.get_trace_indices(self.data.shape[0],
ntraces,
random=True)
fs = 1 / self.dt
specs, peaks, mis, mas = [], [], [], []
for ti in trace_indices:
trace = self.data[ti, :]
if sum(trace) == 0: continue
f, amp, fmi, fma = self.spectrum(trace, fs)
peak = f[np.argmax(amp)]
specs.append(amp)
peaks.append(peak)
mis.append(fmi)
mas.append(fma)
spec = np.mean(np.dstack(specs), axis=-1)
spec = np.squeeze(spec)
db = 20 * np.log10(amp)
db = db - np.amax(db)
f_peak = np.mean(peaks)
f_min = np.amin(mis)
f_max = np.amax(mas)
statstring = "\nMin: {:.2f} Hz\nPeak: {:.2f} Hz\nMax: {:.2f}"
stats = statstring.format(f_min, f_peak, f_max)
ax.plot(f, db, lw=0) # Plot invisible line to get the min
y_min = ax.get_yticks()[0]
ax.fill_between(f, y_min, db, lw=0, facecolor='k', alpha=0.5)
ax.set_xlabel('frequency [Hz]', fontsize=fontsize - 4)
ax.xaxis.set_label_coords(0.5, -0.12)
ax.set_xlim([0, np.amax(f)])
ax.set_xticklabels(ax.get_xticks(), fontsize=fontsize - 4)
ax.set_yticklabels(ax.get_yticks(), fontsize=fontsize - 4)
ax.set_ylabel('power [dB]', fontsize=fontsize - 4)
ax.text(.98, .95, 'AMPLITUDE SPECTRUM'+stats,
horizontalalignment='right',
verticalalignment='top',
transform=ax.transAxes, fontsize=fontsize - 3)
ax.yaxis.set_major_formatter(tickfmt)
ax.xaxis.set_major_formatter(tickfmt)
ax.grid('on')
return ax
def plot_spectrum(spec_ax, data, dt, tickfmt, ntraces=10, fontsize=10):
"""
Plot a power spectrum.
w is window length for smoothing filter
"""
trace_indices = utils.get_trace_indices(data.shape[1],
ntraces,
random=True)
fs = 1/(dt/10**6)
specs, peaks, mis, mas = [], [], [], []
for ti in trace_indices:
trace = data[:, ti]
f, amp, fmi, fma = get_spectrum(trace, fs)
peak = f[np.argmax(amp)]
specs.append(amp)
peaks.append(peak)
mis.append(fmi)
mas.append(fma)
spec = np.mean(np.dstack(specs), axis=-1)
spec = np.squeeze(spec)
db = 20 * np.log10(amp)
db = db - np.amax(db)
f_peak = np.mean(peaks)
f_min = np.amin(mis)
f_max = np.amax(mas)
statstring = "\nMin: {:.2f} Hz\nPeak: {:.2f} Hz\nMax: {:.2f}"
stats = statstring.format(f_min, f_peak, f_max)
spec_ax.plot(f, db, lw=0) # Plot invisible line to get the min
y_min = spec_ax.get_yticks()[0]
spec_ax.fill_between(f, y_min, db, lw=0, facecolor='k', alpha=0.5)
spec_ax.set_xlabel('frequency [Hz]', fontsize=fontsize - 4)
spec_ax.xaxis.set_label_coords(0.5, -0.12)
spec_ax.set_xlim([0, np.amax(f)])
spec_ax.set_xticklabels(spec_ax.get_xticks(), fontsize=fontsize - 4)
spec_ax.set_yticklabels(spec_ax.get_yticks(), fontsize=fontsize - 4)
spec_ax.set_ylabel('power [dB]', fontsize=fontsize - 4)
spec_ax.text(.98, .95, 'AMPLITUDE SPECTRUM'+stats,
horizontalalignment='right',
verticalalignment='top',
transform=spec_ax.transAxes, fontsize=fontsize - 3)
spec_ax.yaxis.set_major_formatter(tickfmt)
spec_ax.xaxis.set_major_formatter(tickfmt)
spec_ax.grid('on')
return spec_ax
def plot_spectrum(self,
ax=None,
tickfmt=None,
ntraces=20,
fontsize=10,
colour='k'):
"""
Plot a power spectrum.
w is window length for smoothing filter
"""
if tickfmt is None:
# Set the tickformat.
tickfmt = mtick.FormatStrFormatter('%.0f')
if ax is None:
fig = plt.figure(figsize=(12, 6))
ax = fig.add_subplot(111)
trace_indices = utils.get_trace_indices(self.data.shape[:-1],
ntraces,
random=True)
fs = 1 / self.dt
specs, peaks, mis, mas = [], [], [], []
for ti in trace_indices:
try:
# 3D
trace = self.data[ti[0], ti[1], :]
except IndexError:
# 2D
trace = self.data[ti, :]
if sum(trace) == 0:
continue
f, amp, fmi, fma = self.spectrum(trace, fs)
peak = f[np.argmax(amp)]
specs.append(amp)
peaks.append(peak)
mis.append(fmi)
mas.append(fma)
spec = np.nanmean(np.dstack(specs), axis=-1)
spec = np.squeeze(spec)
db = 20 * np.log10(spec)
db = db - np.amax(db)
f_peak = np.mean(peaks)
f_min = np.amin(mis)
f_max = np.amax(mas)
dt = 1000 // fs
f_nyquist = fs // 2
statstring = "\nMin: {:.1f} Hz\nPeak: {:.1f} Hz\nMax: {:.1f} Hz\nNyquist ({} ms): {} Hz"
stats = statstring.format(f_min, f_peak, f_max, dt, f_nyquist)
ax.plot(f, db, lw=0) # Plot invisible line to get the min
y_min = ax.get_yticks()[0]
ax.fill_between(f, y_min, db, lw=0, facecolor=colour, alpha=0.6)
ax.set_xlabel('frequency [Hz]', fontsize=fontsize - 4)
ax.xaxis.set_label_coords(0.5, -0.12)
ax.set_xlim([0, np.amax(f)])
ax.set_xticklabels(ax.get_xticks(), fontsize=fontsize - 4)
ax.set_yticklabels(ax.get_yticks(), fontsize=fontsize - 4)
ax.set_ylabel('power [dB]', fontsize=fontsize - 4)
ax.text(.98, .95, 'AMPLITUDE SPECTRUM',
horizontalalignment='right',
verticalalignment='top',
fontweight='bold',
color=colour,
transform=ax.transAxes, fontsize=fontsize - 3)
ax.text(.98, .95, stats,
horizontalalignment='right',
verticalalignment='top',
transform=ax.transAxes, fontsize=fontsize - 3)
ax.yaxis.set_major_formatter(tickfmt)
ax.xaxis.set_major_formatter(tickfmt)
ax.grid()
gridlines = ax.get_xgridlines() + ax.get_ygridlines()
for line in gridlines:
line.set_linestyle('-')
line.set_alpha(0.2)
return ax
