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autoPyLoT: figure beautification

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also added nav toolbar to TuneAutopicker
This commit is contained in:
Marcel Paffrath
2017-05-15 11:20:40 +02:00
parent 77b076d560
commit 4d9c7b02cf
6 changed files with 45 additions and 33 deletions
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4
pylot/core/pick/autopick.py
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@@ -700,7 +700,7 @@ def autopickstation(wfstream, pickparam, verbose=False, iplot=0, fig_dict=None):
if len(edat[0]) > 1 and len(ndat[0]) > 1 and Sflag == 1:
# plot horizontal traces
ax2 = fig.add_subplot(312)
ax2 = fig.add_subplot(3,1,2,sharex=ax1)
th1data = np.arange(0,
trH1_filt.stats.npts /
trH1_filt.stats.sampling_rate,
@@ -749,7 +749,7 @@ def autopickstation(wfstream, pickparam, verbose=False, iplot=0, fig_dict=None):
ax2.set_ylabel('Normalized Counts')
#fig.suptitle(trH1_filt.stats.starttime)
ax3 = fig.add_subplot(313)
ax3 = fig.add_subplot(3,1,3, sharex=ax1)
th2data = np.arange(0,
trH2_filt.stats.npts /
trH2_filt.stats.sampling_rate,

18
pylot/core/pick/picker.py
View File

@@ -268,22 +268,28 @@ class AICPicker(AutoPicker):
ax1.plot([self.Pick, self.Pick], [-0.1, 0.5], 'b', linewidth=2, label='AIC-Pick')
ax1.set_xlabel('Time [s] since %s' % self.Data[0].stats.starttime)
ax1.set_yticks([])
ax1.set_title(self.Data[0].stats.station)
ax1.legend()
if self.Pick is not None:
ax2 = fig.add_subplot(212)
ax2 = fig.add_subplot(2,1,2, sharex=ax1)
ax2.plot(self.Tcf, x, 'k', label='Data')
ax2.plot(self.Tcf[inoise], self.Data[0].data[inoise], label='Noise Window')
ax2.plot(self.Tcf[isignal], self.Data[0].data[isignal], 'r', label='Signal Window')
ax2.plot(self.Tcf[islope], dataslope, 'g--', label='Slope Window')
ax1.axvspan(self.Tcf[inoise[0]],self.Tcf[inoise[-1]], color='y', alpha=0.2, lw=0, label='Noise Window')
ax1.axvspan(self.Tcf[isignal[0]],self.Tcf[isignal[-1]], color='b', alpha=0.2, lw=0, label='Signal Window')
ax1.axvspan(self.Tcf[islope[0]],self.Tcf[islope[-1]], color='g', alpha=0.2, lw=0, label='Slope Window')
ax2.axvspan(self.Tcf[inoise[0]],self.Tcf[inoise[-1]], color='y', alpha=0.2, lw=0, label='Noise Window')
ax2.axvspan(self.Tcf[isignal[0]],self.Tcf[isignal[-1]], color='b', alpha=0.2, lw=0, label='Signal Window')
ax2.axvspan(self.Tcf[islope[0]],self.Tcf[islope[-1]], color='g', alpha=0.2, lw=0, label='Slope Window')
ax2.plot(self.Tcf[islope], datafit, 'g', linewidth=2, label='Slope')
ax2.set_title('Station %s, SNR=%7.2f, Slope= %12.2f counts/s' % (self.Data[0].stats.station,
ax1.set_title('Station %s, SNR=%7.2f, Slope= %12.2f counts/s' % (self.Data[0].stats.station,
self.SNR, self.slope))
ax2.set_xlabel('Time [s] since %s' % self.Data[0].stats.starttime)
ax2.set_ylabel('Counts')
ax2.set_yticks([])
ax2.legend()
else:
ax1.set_title(self.Data[0].stats.station)
if self.Pick == None:
print('AICPicker: Could not find minimum, picking window too short?')

16
pylot/core/pick/utils.py
View File

@@ -105,12 +105,11 @@ def earllatepicker(X, nfac, TSNR, Pick1, iplot=None, stealth_mode=False, fig=Non
if iplot > 1:
if not fig:
print('New Figure.........................')
fig = plt.figure()#iplot)
ax = fig.add_subplot(111)
ax.plot(t, x, 'k', label='Data')
ax.plot(t[inoise], x[inoise], label='Noise Window')
ax.plot(t[isignal], x[isignal], 'r', label='Signal Window')
ax.axvspan(t[inoise[0]], t[inoise[-1]], color='y', alpha=0.2, lw=0, label='Noise Window')
ax.axvspan(t[isignal[0]], t[isignal[-1]], color='b', alpha=0.2, lw=0, label='Signal Window')
ax.plot([t[0], t[int(len(t)) - 1]], [nlevel, nlevel], '--k', label='Noise Level')
ax.plot(t[isignal[zc]], np.zeros(len(zc)), '*g',
markersize=14, label='Zero Crossings')
@@ -292,7 +291,7 @@ def fmpicker(Xraw, Xfilt, pickwin, Pick, iplot=None, fig=None):
ax1.set_title('First-Motion Determination, %s, Unfiltered Data' % Xraw[
0].stats.station)
ax2=fig.add_subplot(212)
ax2=fig.add_subplot(2,1,2, sharex=ax1)
ax2.set_title('First-Motion Determination, Filtered Data')
ax2.plot(t, xfilt, 'k')
ax2.plot([Pick, Pick], [max(xfilt), -max(xfilt)], 'b',
@@ -693,8 +692,8 @@ def checksignallength(X, pick, TSNR, minsiglength, nfac, minpercent, iplot=0, fi
fig = plt.figure()#iplot)
ax = fig.add_subplot(111)
ax.plot(t, rms, 'k', label='RMS Data')
ax.plot(t[inoise], rms[inoise], 'c', label='RMS Noise Window')
ax.plot(t[isignal], rms[isignal], 'r', label='RMS Signal Window')
ax.axvspan(t[inoise[0]], t[inoise[-1]], color='y', alpha=0.2, lw=0, label='Noise Window')
ax.axvspan(t[isignal[0]], t[isignal[-1]], color='b', alpha=0.2, lw=0, label='Signal Window')
ax.plot([t[isignal[0]], t[isignal[len(isignal) - 1]]],
[minsiglevel, minsiglevel], 'g', linewidth=2, label='Minimum Signal Level')
ax.plot([pick, pick], [min(rms), max(rms)], 'b', linewidth=2, label='Onset')
@@ -964,11 +963,10 @@ def checkZ4S(X, pick, zfac, checkwin, iplot, fig=None):
fig = plt.figure()
ax = fig.add_subplot(111)
ax.plot(tz, z / max(z), 'k')
ax.plot(tz[isignal], z[isignal] / max(z), 'r')
ax.axvspan(tz[isignal[0]], tz[isignal[-1]], color='b', alpha=0.2,
lw=0, label='Signal Window')
ax.plot(te, edat[0].data / max(edat[0].data) + 1, 'k')
ax.plot(te[isignal], edat[0].data[isignal] / max(edat[0].data) + 1, 'r')
ax.plot(tn, ndat[0].data / max(ndat[0].data) + 2, 'k')
ax.plot(tn[isignal], ndat[0].data[isignal] / max(ndat[0].data) + 2, 'r')
ax.plot([tz[isignal[0]], tz[isignal[len(isignal) - 1]]],
[minsiglevel / max(z), minsiglevel / max(z)], 'g',
linewidth=2, label='Minimum Signal Level')