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[update] add linecolor settings to autoPyLoT figs

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This commit is contained in:
Marcel Paffrath 2017-09-08 17:01:36 +02:00
parent 7ef784f2d2
commit 104a8dda64
5 changed files with 86 additions and 45 deletions
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14
QtPyLoT.py
View File

@ -1991,26 +1991,35 @@ class MainWindow(QMainWindow):
'el_S1pick',
'el_S2pick',
'refSpick',
'aicARHfig'
'aicARHfig',
'plot_style'
]
for key in self.fig_keys:
if key == 'plot_style':
fig = self._style
else:
fig = Figure()
self.fig_dict[key] = fig
def init_canvas_dict(self):
self.canvas_dict = {}
for key in self.fig_keys:
if not key == 'plot_style':
self.canvas_dict[key] = PylotCanvas(self.fig_dict[key], parent=self)
def init_fig_dict_wadatijack(self, eventIDs):
self.fig_dict_wadatijack = {}
self.fig_keys_wadatijack = [
'jackknife',
'wadati'
'wadati',
'plot_style'
]
for eventID in eventIDs:
self.fig_dict_wadatijack[eventID] = {}
for key in self.fig_keys_wadatijack:
if key == 'plot_style':
fig = self._style
else:
fig = Figure()
self.fig_dict_wadatijack[eventID][key] = fig
@ -2019,6 +2028,7 @@ class MainWindow(QMainWindow):
for eventID in self.fig_dict_wadatijack.keys():
self.canvas_dict_wadatijack[eventID] = {}
for key in self.fig_keys_wadatijack:
if not key == 'plot_style':
self.canvas_dict_wadatijack[eventID][key] = PylotCanvas(self.fig_dict_wadatijack[eventID][key],
parent=self)

54
pylot/core/pick/autopick.py
View File

@ -322,9 +322,11 @@ def autopickstation(wfstream, pickparam, verbose=False,
key = 'aicFig'
if fig_dict:
fig = fig_dict[key]
linecolor = fig_dict['plot_style']['linecolor']['rgba_mpl']
else:
fig = None
aicpick = AICPicker(aiccf, tsnrz, pickwinP, iplot, None, aictsmoothP, fig=fig)
linecolor = 'k'
aicpick = AICPicker(aiccf, tsnrz, pickwinP, iplot, None, aictsmoothP, fig=fig, linecolor=linecolor)
# add pstart and pstop to aic plot
if fig:
for ax in fig.axes:
@ -347,12 +349,14 @@ def autopickstation(wfstream, pickparam, verbose=False,
key = 'slength'
if fig_dict:
fig = fig_dict[key]
linecolor = fig_dict['plot_style']['linecolor']['rgba_mpl']
else:
fig = None
linecolor = 'k'
Pflag = checksignallength(zne, aicpick.getpick(), tsnrz,
minsiglength / 2,
nfacsl, minpercent, iplot,
fig)
fig, linecolor)
else:
# filter and taper horizontal traces
trH1_filt = edat.copy()
@ -369,12 +373,14 @@ def autopickstation(wfstream, pickparam, verbose=False,
zne += trH2_filt
if fig_dict:
fig = fig_dict['slength']
linecolor = fig_dict['plot_style']['linecolor']['rgba_mpl']
else:
fig = None
linecolor = 'k'
Pflag = checksignallength(zne, aicpick.getpick(), tsnrz,
minsiglength,
nfacsl, minpercent, iplot,
fig)
fig, linecolor)
if Pflag == 1:
# check for spuriously picked S onset
@ -387,10 +393,12 @@ def autopickstation(wfstream, pickparam, verbose=False,
if iplot > 1:
if fig_dict:
fig = fig_dict['checkZ4s']
linecolor = fig_dict['plot_style']['linecolor']['rgba_mpl']
else:
fig = None
linecolor = 'k'
Pflag = checkZ4S(zne, aicpick.getpick(), zfac,
tsnrz[2], iplot, fig)
tsnrz[2], iplot, fig, linecolor)
if Pflag == 0:
Pmarker = 'SinsteadP'
Pweight = 9
@ -442,10 +450,12 @@ def autopickstation(wfstream, pickparam, verbose=False,
algoP=algoP)
if fig_dict:
fig = fig_dict['refPpick']
linecolor = fig_dict['plot_style']['linecolor']['rgba_mpl']
else:
fig = None
linecolor = 'k'
refPpick = PragPicker(cf2, tsnrz, pickwinP, iplot, ausP, tsmoothP,
aicpick.getpick(), fig)
aicpick.getpick(), fig, linecolor)
mpickP = refPpick.getpick()
#############################################################
if mpickP is not None:
@ -454,10 +464,13 @@ def autopickstation(wfstream, pickparam, verbose=False,
if iplot:
if fig_dict:
fig = fig_dict['el_Ppick']
linecolor = fig_dict['plot_style']['linecolor']['rgba_mpl']
else:
fig = None
linecolor = 'k'
epickP, lpickP, Perror = earllatepicker(z_copy, nfacP, tsnrz,
mpickP, iplot, fig=fig)
mpickP, iplot, fig=fig,
linecolor=linecolor)
else:
epickP, lpickP, Perror = earllatepicker(z_copy, nfacP, tsnrz,
mpickP, iplot)
@ -487,9 +500,10 @@ def autopickstation(wfstream, pickparam, verbose=False,
if iplot:
if fig_dict:
fig = fig_dict['fm_picker']
linecolor = fig_dict['plot_style']['linecolor']['rgba_mpl']
else:
fig = None
FM = fmpicker(zdat, z_copy, fmpickwin, mpickP, iplot, fig)
FM = fmpicker(zdat, z_copy, fmpickwin, mpickP, iplot, fig, linecolor)
else:
FM = fmpicker(zdat, z_copy, fmpickwin, mpickP, iplot)
else:
@ -624,10 +638,12 @@ def autopickstation(wfstream, pickparam, verbose=False,
# of class AutoPicking
if fig_dict:
fig = fig_dict['aicARHfig']
linecolor = fig_dict['plot_style']['linecolor']['rgba_mpl']
else:
fig = None
linecolor = 'k'
aicarhpick = AICPicker(haiccf, tsnrh, pickwinS, iplot, None,
aictsmoothS, fig=fig)
aictsmoothS, fig=fig, linecolor=linecolor)
###############################################################
# go on with processing if AIC onset passes quality control
slope = aicarhpick.getSlope()
@ -686,10 +702,12 @@ def autopickstation(wfstream, pickparam, verbose=False,
# get refined onset time from CF2 using class Picker
if fig_dict:
fig = fig_dict['refSpick']
linecolor = fig_dict['plot_style']['linecolor']['rgba_mpl']
else:
fig = None
linecolor = 'k'
refSpick = PragPicker(arhcf2, tsnrh, pickwinS, iplot, ausS,
tsmoothS, aicarhpick.getpick(), fig)
tsmoothS, aicarhpick.getpick(), fig, linecolor)
mpickS = refSpick.getpick()
#############################################################
if mpickS is not None:
@ -699,12 +717,15 @@ def autopickstation(wfstream, pickparam, verbose=False,
if iplot:
if fig_dict:
fig = fig_dict['el_S1pick']
linecolor = fig_dict['plot_style']['linecolor']['rgba_mpl']
else:
fig = None
linecolor = 'k'
epickS1, lpickS1, Serror1 = earllatepicker(h_copy, nfacS,
tsnrh,
mpickS, iplot,
fig=fig)
fig=fig,
linecolor=linecolor)
else:
epickS1, lpickS1, Serror1 = earllatepicker(h_copy, nfacS,
tsnrh,
@ -714,12 +735,15 @@ def autopickstation(wfstream, pickparam, verbose=False,
if iplot:
if fig_dict:
fig = fig_dict['el_S2pick']
linecolor = fig_dict['plot_style']['linecolor']['rgba_mpl']
else:
fig = None
linecolor = ''
epickS2, lpickS2, Serror2 = earllatepicker(h_copy, nfacS,
tsnrh,
mpickS, iplot,
fig=fig)
fig=fig,
linecolor=linecolor)
else:
epickS2, lpickS2, Serror2 = earllatepicker(h_copy, nfacS,
tsnrh,
@ -828,8 +852,10 @@ def autopickstation(wfstream, pickparam, verbose=False,
if fig_dict == None or fig_dict == 'None':
fig = plt.figure()
plt_flag = 1
linecolor = 'k'
else:
fig = fig_dict['mainFig']
linecolor = fig_dict['plot_style']['linecolor']['rgba_mpl']
ax1 = fig.add_subplot(311)
tdata = np.arange(0, zdat[0].stats.npts / tr_filt.stats.sampling_rate,
tr_filt.stats.delta)
@ -837,7 +863,7 @@ def autopickstation(wfstream, pickparam, verbose=False,
wfldiff = len(tr_filt.data) - len(tdata)
if wfldiff < 0:
tdata = tdata[0:len(tdata) - abs(wfldiff)]
ax1.plot(tdata, tr_filt.data / max(tr_filt.data), 'k', label='Data')
ax1.plot(tdata, tr_filt.data / max(tr_filt.data), color=linecolor, linewidth=0.7, label='Data')
if Pweight < 4:
ax1.plot(cf1.getTimeArray(), cf1.getCF() / max(cf1.getCF()),
'b', label='CF1')
@ -896,7 +922,7 @@ def autopickstation(wfstream, pickparam, verbose=False,
wfldiff = len(trH1_filt.data) - len(th1data)
if wfldiff < 0:
th1data = th1data[0:len(th1data) - abs(wfldiff)]
ax2.plot(th1data, trH1_filt.data / max(trH1_filt.data), 'k', label='Data')
ax2.plot(th1data, trH1_filt.data / max(trH1_filt.data), color=linecolor, linewidth=0.7, label='Data')
if Pweight < 4:
ax2.plot(arhcf1.getTimeArray(),
arhcf1.getCF() / max(arhcf1.getCF()), 'b', label='CF1')
@ -945,7 +971,7 @@ def autopickstation(wfstream, pickparam, verbose=False,
wfldiff = len(trH2_filt.data) - len(th2data)
if wfldiff < 0:
th2data = th2data[0:len(th2data) - abs(wfldiff)]
ax3.plot(th2data, trH2_filt.data / max(trH2_filt.data), 'k', label='Data')
ax3.plot(th2data, trH2_filt.data / max(trH2_filt.data), color=linecolor, linewidth=0.7, label='Data')
if Pweight < 4:
p22, = ax3.plot(arhcf1.getTimeArray(),
arhcf1.getCF() / max(arhcf1.getCF()), 'b', label='CF1')

17
pylot/core/pick/picker.py
View File

@ -35,7 +35,7 @@ class AutoPicker(object):
warnings.simplefilter('ignore')
def __init__(self, cf, TSNR, PickWindow, iplot=0, aus=None, Tsmooth=None, Pick1=None, fig=None):
def __init__(self, cf, TSNR, PickWindow, iplot=0, aus=None, Tsmooth=None, Pick1=None, fig=None, linecolor='k'):
'''
:param: cf, characteristic function, on which the picking algorithm is applied
:type: `~pylot.core.pick.CharFuns.CharacteristicFunction` object
@ -62,7 +62,8 @@ class AutoPicker(object):
'''
assert isinstance(cf, CharacteristicFunction), "%s is not a CharacteristicFunction object" % str(cf)
self._linecolor = linecolor
self._pickcolor_p = 'b'
self.cf = cf.getCF()
self.Tcf = cf.getTimeArray()
self.Data = cf.getXCF()
@ -264,13 +265,13 @@ class AICPicker(AutoPicker):
print("Choose longer slope determination window!")
if self.iplot > 1:
if self.fig == None or self.fig == 'None':
fig = plt.figure() # self.iplot) ### WHY? MP MP
fig = plt.figure()
plt_flag = 1
else:
fig = self.fig
ax = fig.add_subplot(111)
x = self.Data[0].data
ax.plot(self.Tcf, x / max(x), 'k', label='(HOS-/AR-) Data')
ax.plot(self.Tcf, x / max(x), color=self._linecolor, linewidth=0.7, label='(HOS-/AR-) Data')
ax.plot(self.Tcf, aicsmooth / max(aicsmooth), 'r', label='Smoothed AIC-CF')
ax.legend(loc=1)
ax.set_xlabel('Time [s] since %s' % self.Data[0].stats.starttime)
@ -307,7 +308,7 @@ class AICPicker(AutoPicker):
x = self.Data[0].data
if len(self.Tcf) > len(self.Data[0].data): # why? LK
self.Tcf = self.Tcf[0:len(self.Tcf)-1]
ax1.plot(self.Tcf, x / max(x), 'k', label='(HOS-/AR-) Data')
ax1.plot(self.Tcf, x / max(x), color=self._linecolor, linewidth=0.7, label='(HOS-/AR-) Data')
ax1.plot(self.Tcf, aicsmooth / max(aicsmooth), 'r', label='Smoothed AIC-CF')
if self.Pick is not None:
ax1.plot([self.Pick, self.Pick], [-0.1, 0.5], 'b', linewidth=2, label='AIC-Pick')
@ -317,7 +318,7 @@ class AICPicker(AutoPicker):
if self.Pick is not None:
ax2 = fig.add_subplot(2, 1, 2, sharex=ax1)
ax2.plot(self.Tcf, x, 'k', label='Data')
ax2.plot(self.Tcf, x, color=self._linecolor, linewidth=0.7, label='Data')
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')
@ -473,10 +474,10 @@ class PragPicker(AutoPicker):
else:
fig = self.fig
ax = fig.add_subplot(111)
ax.plot(Tcfpick, cfipick, 'k', label='CF')
ax.plot(Tcfpick, cfipick, color=self._linecolor, linewidth=0.7, label='CF')
ax.plot(Tcfpick, cfsmoothipick, 'r', label='Smoothed CF')
if pickflag > 0:
ax.plot([self.Pick, self.Pick], [min(cfipick), max(cfipick)], 'b', linewidth=2, label='Pick')
ax.plot([self.Pick, self.Pick], [min(cfipick), max(cfipick)], self._pickcolor_p, linewidth=2, label='Pick')
ax.set_xlabel('Time [s] since %s' % self.Data[0].stats.starttime)
ax.set_yticks([])
ax.set_title(self.Data[0].stats.station)

33
pylot/core/pick/utils.py
View File

@ -15,7 +15,7 @@ import numpy as np
from obspy.core import Stream, UTCDateTime
def earllatepicker(X, nfac, TSNR, Pick1, iplot=0, verbosity=1, fig=None):
def earllatepicker(X, nfac, TSNR, Pick1, iplot=0, verbosity=1, fig=None, linecolor='k'):
'''
Function to derive earliest and latest possible pick after Diehl & Kissling (2009)
as reasonable uncertainties. Latest possible pick is based on noise level,
@ -131,16 +131,16 @@ def earllatepicker(X, nfac, TSNR, Pick1, iplot=0, verbosity=1, fig=None):
fig = plt.figure() # iplot)
plt_flag = 1
ax = fig.add_subplot(111)
ax.plot(t, x, 'k', label='Data')
ax.plot(t, x, color=linecolor, linewidth=0.7, label='Data')
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[0], t[int(len(t)) - 1]], [nlevel, nlevel], color=linecolor, linewidth=0.7, linestyle='dashed', label='Noise Level')
ax.plot(t[pis[zc]], np.zeros(len(zc)), '*g',
markersize=14, label='Zero Crossings')
ax.plot([t[0], t[int(len(t)) - 1]], [-nlevel, -nlevel], '--k')
ax.plot([t[0], t[int(len(t)) - 1]], [-nlevel, -nlevel], color=linecolor, linewidth=0.7, linestyle='dashed')
ax.plot([Pick1, Pick1], [max(x), -max(x)], 'b', linewidth=2, label='mpp')
ax.plot([LPick, LPick], [max(x) / 2, -max(x) / 2], '--k', label='lpp')
ax.plot([EPick, EPick], [max(x) / 2, -max(x) / 2], '--k', label='epp')
ax.plot([LPick, LPick], [max(x) / 2, -max(x) / 2], color=linecolor, linewidth=0.7, linestyle='dashed', label='lpp')
ax.plot([EPick, EPick], [max(x) / 2, -max(x) / 2], color=linecolor, linewidth=0.7, linestyle='dashed', label='epp')
ax.plot([Pick1 + PickError, Pick1 + PickError],
[max(x) / 2, -max(x) / 2], 'r--', label='spe')
ax.plot([Pick1 - PickError, Pick1 - PickError],
@ -160,7 +160,7 @@ def earllatepicker(X, nfac, TSNR, Pick1, iplot=0, verbosity=1, fig=None):
return EPick, LPick, PickError
def fmpicker(Xraw, Xfilt, pickwin, Pick, iplot=0, fig=None):
def fmpicker(Xraw, Xfilt, pickwin, Pick, iplot=0, fig=None, linecolor='k'):
'''
Function to derive first motion (polarity) of given phase onset Pick.
Calculation is based on zero crossings determined within time window pickwin
@ -324,7 +324,7 @@ def fmpicker(Xraw, Xfilt, pickwin, Pick, iplot=0, fig=None):
fig = plt.figure() # iplot)
plt_flag = 1
ax1 = fig.add_subplot(211)
ax1.plot(t, xraw, 'k')
ax1.plot(t, xraw, color=linecolor, linewidth=0.7)
ax1.plot([Pick, Pick], [max(xraw), -max(xraw)], 'b', linewidth=2, label='Pick')
if P1 is not None:
ax1.plot(t[islope1], xraw[islope1], label='Slope Window')
@ -338,7 +338,7 @@ def fmpicker(Xraw, Xfilt, pickwin, Pick, iplot=0, fig=None):
ax2 = fig.add_subplot(2, 1, 2, sharex=ax1)
ax2.set_title('First-Motion Determination, Filtered Data')
ax2.plot(t, xfilt, 'k')
ax2.plot(t, xfilt, color=linecolor, linewidth=0.7)
ax2.plot([Pick, Pick], [max(xfilt), -max(xfilt)], 'b',
linewidth=2)
if P2 is not None:
@ -668,15 +668,18 @@ def wadaticheck(pickdic, dttolerance, iplot=0, fig_dict=None):
if iplot > 0:
if fig_dict:
fig = fig_dict['wadati']
linecolor = fig_dict['plot_style']['linecolor']['rgba_mpl']
plt_flag = 0
else:
fig = plt.figure()
linecolor = 'k'
plt_flag = 1
ax = fig.add_subplot(111)
ax.plot(Ppicks, SPtimes, 'ro', label='Skipped S-Picks')
if wfitflag == 0:
ax.plot(Ppicks, wdfit, 'k', label='Wadati 1')
ax.plot(checkedPpicks, checkedSPtimes, 'ko', label='Reliable S-Picks')
ax.plot(Ppicks, wdfit, color=linecolor, linewidth=0.7, label='Wadati 1')
ax.plot(checkedPpicks, checkedSPtimes, color=linecolor,
linewidth=0, marker='o', label='Reliable S-Picks')
ax.plot(checkedPpicks, wdfit2, 'g', label='Wadati 2')
ax.set_title('Wadati-Diagram, %d S-P Times, Vp/Vs(raw)=%5.2f,' \
'Vp/Vs(checked)=%5.2f' % (len(SPtimes), vpvsr, cvpvsr))
@ -699,7 +702,7 @@ def RMS(X):
return np.sqrt(np.sum(np.power(X, 2)) / len(X))
def checksignallength(X, pick, TSNR, minsiglength, nfac, minpercent, iplot=0, fig=None):
def checksignallength(X, pick, TSNR, minsiglength, nfac, minpercent, iplot=0, fig=None, linecolor='k'):
'''
Function to detect spuriously picked noise peaks.
Uses RMS trace of all 3 components (if available) to determine,
@ -785,7 +788,7 @@ def checksignallength(X, pick, TSNR, minsiglength, nfac, minpercent, iplot=0, fi
fig = plt.figure() # iplot)
plt_flag = 1
ax = fig.add_subplot(111)
ax.plot(t, rms, 'k', label='RMS Data')
ax.plot(t, rms, color=linecolor, linewidth=0.7, label='RMS Data')
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]]],
@ -975,7 +978,7 @@ def jackknife(X, phi, h):
return PHI_jack, PHI_pseudo, PHI_sub
def checkZ4S(X, pick, zfac, checkwin, iplot, fig=None):
def checkZ4S(X, pick, zfac, checkwin, iplot, fig=None, linecolor='k'):
'''
Function to compare energy content of vertical trace with
energy content of horizontal traces to detect spuriously
@ -1103,7 +1106,7 @@ def checkZ4S(X, pick, zfac, checkwin, iplot, fig=None):
plt_flag = 1
ax = fig.add_subplot(3, 1, i + 1, sharex=ax1)
ax.plot(t, abs(trace.data), color='b', label='abs')
ax.plot(t, trace.data, color='k')
ax.plot(t, trace.data, color=linecolor, linewidth=0.7)
name = str(trace.stats.channel) + ': {}'.format(rms)
ax.plot([pick, pick + checkwin], [rms, rms], 'r', label='RMS {}'.format(name))
ax.plot([pick, pick], ax.get_ylim(), 'm', label='Pick')

1
pylot/core/util/widgets.py
View File

@ -2766,6 +2766,7 @@ class TuneAutopicker(QWidget):
'locflag': 0,
'savexml': False}
for key in self.fig_dict.keys():
if not key == 'plot_style':
self.fig_dict[key].clear()
self.ap_thread = Thread(self, autoPyLoT, arg=args,
progressText='Picking trace...',