Transfer plotting of results in GUI after picking

This commit is contained in:
Darius Arnold 2018-07-03 13:55:04 +02:00
parent 86419220e2
commit 80835bc56e

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@ -195,6 +195,12 @@ class PickingResults(dict):
self.fc = None
self.Mw = None
# flags for plotting
self.aicPflag = 0
self.aicSflag = 0
self.Pflag = 0
self.Sflag = 0
def __setattr__(self, key, value):
self[key] = value
@ -430,6 +436,7 @@ class AutopickStation(object):
print(pfe)
self.finish_picking()
self.plot_pick_results()
return {'P': self.p_results, 'S':self.s_results, 'station':self.ztrace.stats.station} #TODO method to format picking results as a dict correctly
def finish_picking(self):
@ -502,6 +509,130 @@ class AutopickStation(object):
self.s_results.picker='auto'
self.s_results.Ao = None
def plot_pick_results(self):
if self.iplot > 0:
# plot vertical trace
if self.fig_dict is None:
fig = plt.figure()
plt_flag = 1
linecolor = 'k'
else:
fig = self.fig_dict['mainFig']
linecolor = self.fig_dict['plot_style']['linecolor']['rgba_mpl']
plt_flag = 0
fig._tight = True
ax1 = fig.add_subplot(311)
tdata = np.linspace(start=0, stop=self.ztrace.stats.npts*self.ztrace.stats.delta, num=self.ztrace.stats.npts)
# plot tapered trace filtered with bpz2 filter settings
ax1.plot(tdata, self.tr_filt_z_bpz2.data/max(self.tr_filt_z_bpz2.data), color=linecolor, linewidth=0.7, label='Data')
if self.p_results.Pweight < 4:
# plot CF of initial onset (HOScf or ARZcf)
ax1.plot(self.cf1.getTimeArray(), self.cf1.getCF()/max(self.cf1.getCF()), 'b', label='CF1')
if self.p_results.aicPflag == 1:
aicpick = self.p_results.aicpick
refPpick = self.p_results.refPpick
# plot CF of precise pick (HOScf or ARZcf)
ax1.plot(self.cf2.getTimeArray(), self.cf2.getCF() / max(self.cf2.getCF()), 'm', label='CF2')
# plot inital P pick
ax1.plot([aicpick.getpick(), aicpick.getpick()], [-1, 1], 'r', label='Initial P Onset')
ax1.plot([aicpick.getpick() - 0.5, aicpick.getpick() + 0.5], [1, 1], 'r')
ax1.plot([aicpick.getpick() - 0.5, aicpick.getpick() + 0.5], [-1, -1], 'r')
# plot precise P pick
ax1.plot([refPpick.getpick(), refPpick.getpick()], [-1.3, 1.3], 'r', linewidth=2, label='Final P Pick')
ax1.plot([refPpick.getpick() - 0.5, refPpick.getpick() + 0.5], [1.3, 1.3], 'r', linewidth=2)
ax1.plot([refPpick.getpick() - 0.5, refPpick.getpick() + 0.5], [-1.3, -1.3], 'r', linewidth=2)
# plot latest possible P pick
ax1.plot([self.p_results.lpickP, self.p_results.lpickP], [-1.1, 1.1], 'r--', label='lpp')
# plot earliest possible P pick
ax1.plot([self.p_results.epickP, self.p_results.epickP], [-1.1, 1.1], 'r--', label='epp')
# add title to plot
title = '{station}, {channel}, P weight={pweight:d}, SNR={snr:7.2}, SNR[dB]={snrdb:7.2}, Polarity: {polarity}'
ax1.set_title(title.format(station=self.ztrace.stats.station,
channel=self.ztrace.stats.channel,
pweight=self.p_results.Pweight,
snr=self.p_results.SNRP,
snrdb=self.p_results.SNRPdB,
polarity=self.p_results.FM))
else:
title = '{channel}, P weight={pweight}, SNR=None, SNR[dB]=None'
ax1.set_title(title.format(channel=self.ztrace.stats.channel, pweight=self.p_results.Pweight))
ax1.legend(loc=1)
ax1.set_yticks([])
ax1.set_ylim([-1.5, 1.5])
ax1.set_ylabel('Normalized Counts')
if self.s_results.Sflag == 1:
# plot E trace
ax2 = fig.add_subplot(3, 1, 2, sharex=ax1)
th1data = np.linspace(0, self.etrace.stats.npts*self.etrace.stats.delta, self.etrace.stats.npts)
# plot filtered and tapered waveform
ax2.plot(th1data, self.etrace.data / max(self.etrace.data), color=linecolor, linewidth=0.7, label='Data')
if self.p_results.Pweight < 4:
# plot initial CF (ARHcf or AR3Ccf)
ax2.plot(self.arhcf1.getTimeArray(), self.arhcf1.getCF() / max(self.arhcf1.getCF()), 'b', label='CF1')
if self.s_results.aicSflag == 1 and self.s_results.Sweight <= 4:
aicarhpick = self.aicarhpick
refSpick = self.refSpick
# plot second cf, used for determing precise onset (ARHcf or AR3Ccf)
ax2.plot(self.arhcf2.getTimeArray(), self.arhcf2.getCF() / max(self.arhcf2.getCF()), 'm', label='CF2')
# plot preliminary onset time, calculated from CF1
ax2.plot([aicarhpick.getpick(), aicarhpick.getpick()], [-1, 1], 'g', label='Initial S Onset')
ax2.plot([aicarhpick.getpick() - 0.5, aicarhpick.getpick() + 0.5], [1, 1], 'g')
ax2.plot([aicarhpick.getpick() - 0.5, aicarhpick.getpick() + 0.5], [-1, -1], 'g')
# plot precise onset time, calculated from CF2
ax2.plot([refSpick.getpick(), refSpick.getpick()], [-1.3, 1.3], 'g', linewidth=2, label='Final S Pick')
ax2.plot([refSpick.getpick() - 0.5, refSpick.getpick() + 0.5], [1.3, 1.3], 'g', linewidth=2)
ax2.plot([refSpick.getpick() - 0.5, refSpick.getpick() + 0.5], [-1.3, -1.3], 'g', linewidth=2)
ax2.plot([self.s_results.lpickS, self.s_results.lpickS], [-1.1, 1.1], 'g--', label='lpp')
ax2.plot([self.s_results.epickS, self.s_results.epickS], [-1.1, 1.1], 'g--', label='epp')
title = '{channel}, S weight={sweight}, SNR={snr:7.2}, SNR[dB]={snrdb:7.2}'
ax2.set_title(title.format(channel=self.etrace.stats.channel,
sweight=self.s_results.Sweight,
snr=self.s_results.SNRS,
snrdb=self.s_results.SNRSdB))
else:
title = '{channel}, S weight={sweight}, SNR=None, SNR[dB]=None'
ax2.set_title(title.format(channel=self.etrace.stats.channel, sweight=self.s_results.Sweight))
ax2.legend(loc=1)
ax2.set_yticks([])
ax2.set_ylim([-1.5, 1.5])
ax2.set_ylabel('Normalized Counts')
# plot N trace
ax3 = fig.add_subplot(3, 1, 3, sharex=ax1)
th2data= np.linspace(0, self.ntrace.stats.npts*self.ntrace.stats.delta, self.ntrace.stats.npts)
# plot trace
ax3.plot(th2data, self.ntrace.data / max(self.ntrace.data), color=linecolor, linewidth=0.7, label='Data')
if self.p_results.Pweight < 4:
p22, = ax3.plot(self.arhcf1.getTimeArray(), self.arhcf1.getCF() / max(self.arhcf1.getCF()), 'b', label='CF1')
if self.s_results.aicSflag == 1:
aicarhpick = self.aicarhpick
refSpick = self.refSpick
ax3.plot(self.arhcf2.getTimeArray(), self.arhcf2.getCF() / max(self.arhcf2.getCF()), 'm', label='CF2')
ax3.plot([aicarhpick.getpick(), aicarhpick.getpick()], [-1, 1], 'g', label='Initial S Onset')
ax3.plot([aicarhpick.getpick() - 0.5, aicarhpick.getpick() + 0.5], [1, 1], 'g')
ax3.plot([aicarhpick.getpick() - 0.5, aicarhpick.getpick() + 0.5], [-1, -1], 'g')
ax3.plot([refSpick.getpick(), refSpick.getpick()], [-1.3, 1.3], 'g', linewidth=2,
label='Final S Pick')
ax3.plot([refSpick.getpick() - 0.5, refSpick.getpick() + 0.5], [1.3, 1.3], 'g', linewidth=2)
ax3.plot([refSpick.getpick() - 0.5, refSpick.getpick() + 0.5], [-1.3, -1.3], 'g', linewidth=2)
ax3.plot([self.s_results.lpickS, self.s_results.lpickS], [-1.1, 1.1], 'g--', label='lpp')
ax3.plot([self.s_results.epickS, self.s_results.epickS], [-1.1, 1.1], 'g--', label='epp')
ax3.legend(loc=1)
ax3.set_yticks([])
ax3.set_ylim([-1.5, 1.5])
ax3.set_xlabel('Time [s] after %s' % self.ntrace.stats.starttime)
ax3.set_ylabel('Normalized Counts')
ax3.set_title(self.ntrace.stats.channel)
if plt_flag == 1:
fig.show()
try:
input()
except SyntaxError:
pass
plt.close(fig)
def pick_p_qc1(self, aicpick, z_copy, tr_filt):
"""
Quality control of first pick using minseglength and checkZ4S.
@ -579,7 +710,7 @@ class AutopickStation(object):
tr_filt, z_copy = self.prepare_wfstream(self.zstream, self.p_params.bpz1[0], self.p_params.bpz1[1])
# save filtered trace in instance for later plotting
self.tr_filt_z = tr_filt
self.tr_filt_z_bpz2 = tr_filt
try:
# modify pstart, pstop to be around theoretical onset if taupy should be used, else does nothing
self.modify_starttimes_taupy()
@ -622,7 +753,7 @@ class AutopickStation(object):
slope = aicpick.getSlope()
if not slope: slope = 0
if slope >= self.p_params.minAICPslope and aicpick.getSNR() >= self.p_params.minAICPSNR and Pflag == 1:
aicPflag = 1
self.p_results.aicPflag = 1
msg = 'AIC P-pick passes quality control: Slope: {0} counts/s, ' \
'SNR: {1}\nGo on with refined picking ...\n' \
'autopickstation: re-filtering vertical trace ' \
@ -630,6 +761,8 @@ class AutopickStation(object):
self.vprint(msg)
# refilter waveform with larger bandpass
tr_filt, z_copy = self.prepare_wfstream(self.zstream, freqmin=self.p_params.bpz2[0], freqmax=self.p_params.bpz2[1])
# save filtered trace in instance for later plotting
self.tr_filt_z_bpz2 = tr_filt
cuttimes2 = [round(max([aicpick.getpick() - self.p_params.Precalcwin, 0])),
round(min([len(self.ztrace.data) * self.ztrace.stats.delta,
aicpick.getpick() + self.p_params.Precalcwin]))]
@ -648,6 +781,8 @@ class AutopickStation(object):
fig, linecolor = get_fig_from_figdict(self.fig_dict, 'refPpick')
refPpick = PragPicker(cf2, self.p_params.tsnrz, self.p_params.pickwinP, self.iplot, self.p_params.ausP,
self.p_params.tsmoothP, aicpick.getpick(), fig, linecolor)
# save PragPicker result for plotting
self.p_results.refPpick = refPpick
self.p_results.mpickP = refPpick.getpick()
if self.p_results.mpickP is not None:
# quality assessment, get earliest/latest pick and symmetrized uncertainty
@ -669,7 +804,7 @@ class AutopickStation(object):
print(msg)
msg = 'autopickstation: Refined P-Pick: {} s | P-Error: {} s'.format(self.p_results.mpickP, self.p_results.Perror)
print(msg)
Sflag = 1
self.s_results.Sflag = 1
self.p_results.aicpick = aicpick
else:
@ -679,10 +814,10 @@ class AutopickStation(object):
'min. AIC-Slope={3}counts/s)'.format(aicpick.getSNR(), aicpick.getSlope(),
self.p_params.minAICPSNR, self.p_params.minAICPslope)
self.vprint(msg)
Sflag = 0
self.s_results.Sflag = 0
else:
#todo add why did picking fail, which should be saved in the pick dictionary
raise PickingFailedException("Why did it fail")
#todo why did picking fail should be saved in the pick dictionary
raise PickingFailedException('AIC P onset did not pass quality control')
def pick_s_phase(self):
@ -748,6 +883,8 @@ class AutopickStation(object):
arhcf1 = ARHcf(h_copy, cuttimesh, self.s_params.tpred1h, self.s_params.Sarorder, self.s_params.tdet1h, self.p_params.addnoise)
elif self.s_params.algoS == 'AR3':
arhcf1 = AR3Ccf(h_copy, cuttimesh, self.s_params.tpred1h, self.s_params.Sarorder, self.s_params.tdet1h, self.p_params.addnoise)
# save cf for later plotting
self.arhcf1 = arhcf1
tr_arhaic = trH1_filt.copy()
tr_arhaic.data = arhcf1.getCF()
@ -759,6 +896,8 @@ class AutopickStation(object):
# get preliminary onset time from AIC cf
fig, linecolor = get_fig_from_figdict(self.fig_dict, 'aicARHfig')
aicarhpick = AICPicker(haiccf, self.s_params.tsnrh, self.s_params.pickwinS, self.iplot, Tsmooth=self.s_params.aictsmoothS, fig=fig, linecolor=linecolor)
# save pick for later plotting
self.aicarhpick = aicarhpick
# go on with processing if AIC onset passes quality control
slope = aicarhpick.getSlope()
@ -767,7 +906,7 @@ class AutopickStation(object):
slope = 0
if slope >= self.s_params.minAICSslope and aicarhpick.getSNR() >= self.s_params.minAICSSNR and aicarhpick.getpick() is not None:
aicSflag = 1
self.s_results.aicSflag = 1
msg = 'AIC S-pick passes quality control: Slope: {0} counts/s, ' \
'SNR: {1}\nGo on with refined picking ...\n' \
'autopickstation: re-filtering horizontal traces ' \
@ -787,23 +926,31 @@ class AutopickStation(object):
h_copy[0].data = trH1_filt.data
h_copy[1].data = trH2_filt.data
elif self.s_params.algoS == 'AR3':
trH1_filt, _ = self.prepare_wfstream(self.zstream, freqmin=self.s_params.bph2[0], freqmax=self.s_params.bph2[1])
trH2_filt, _ = self.prepare_wfstream(self.estream, freqmin=self.s_params.bph2[0], freqmax=self.s_params.bph2[1])
trH3_filt, _ = self.prepare_wfstream(self.nstream, freqmin=self.s_params.bph2[0], freqmax=self.s_params.bph2[1])
trH3_filt, _ = self.prepare_wfstream(self.zstream, freqmin=self.s_params.bph2[0], freqmax=self.s_params.bph2[1])
trH1_filt, _ = self.prepare_wfstream(self.estream, freqmin=self.s_params.bph2[0], freqmax=self.s_params.bph2[1])
trH2_filt, _ = self.prepare_wfstream(self.nstream, freqmin=self.s_params.bph2[0], freqmax=self.s_params.bph2[1])
h_copy = hdat.copy()
h_copy[0].data = trH1_filt.data
h_copy[1].data = trH2_filt.data
h_copy[2].data = trH3_filt.data
h_copy[0].data = trH3_filt.data
h_copy[1].data = trH1_filt.data
h_copy[2].data = trH2_filt.data
# calculate second cd
# save filtered traces for plotting
self.estream_bph2 = trH1_filt
self.nstream_bph2 = trH2_filt
# calculate second cf
if self.s_params.algoS == 'ARH':
arhcf2 = ARHcf(h_copy, cuttimesh2, self.s_params.tpred2h, self.s_params.Sarorder, self.s_params.tdet2h, self.p_params.addnoise)
elif self.s_params.algoS == 'AR3':
arhcf2 = AR3Ccf(h_copy, cuttimesh2, self.s_params.tpred2h, self.s_params.Sarorder, self.s_params.tdet2h, self.p_params.addnoise)
# save cf for later plotting
self.arhcf2 = arhcf2
# get refined onset time from CF2
fig, linecolor = get_fig_from_figdict(self.fig_dict, 'refSpick')
refSpick = PragPicker(arhcf2, self.s_params.tsnrh, self.s_params.pickwinS, self.iplot, self.s_params.ausS, self.s_params.tsmoothS, aicarhpick.getpick(), fig, linecolor)
# save refSpick for later plotitng
self.refSpick = refSpick
self.s_results.mpickS = refSpick.getpick()
if self.s_results.mpickS is not None:
@ -861,30 +1008,6 @@ class AutopickStation(object):
print('autopickstation: No horizontal component data available or '
'bad P onset, skipping S picking!')
### plotting ###
# TODO finish converting the plotting code
if self.iplot > 0:
# plot vertical trace
if self.fig_dict is None:
fig = plt.figure()
plt_flag = 1
linecolor = 'k'
else:
fig, linecolor = get_fig_from_figdict(self.fig_dict, 'mainFig')
fig._tight = True
ax1 = fig.add_subplot(311)
# create time axis
tdata = np.linspace(start=0., stop=self.ztrace.stats.npts*self.tr_filt_z.stats.delta, num=self.tr_filt_z.stats.npts)
# plot filtered waveform of z trace
ax1.plot(tdata, self.tr_filt_z.data / max(self.tr_filt_z.data), color=linecolor, linewidth=0.7, label='Data')
if self.p_results.Pweight < 4:
# plot first HOS/ARZ cf of z trace
ax1.plot(self.cf1.getTimeArray(), self.cf1.getCF / max(self.cf1.getCF()), color='b', label='CF1')
if self.p_results.aicPflag == 1:
ax1.plot(self.cf2.getTimeArray(), self.cf2.getCF() / max(self.cf2.getCF()), color='m', label='CF2')
ax1.plot([self.p_results.aicpick.getpick(), self.p_results.aicpick.getpick()], [-1, 1], 'r', label='Initial P Onset')
def get_fig_from_figdict(figdict, figkey):
"""
Helper method to extract a figure by name from dictionary