Enabled plotting of figures when called from terminal.
This commit is contained in:
Ludger Küperkoch
parent
ab410b790c
commit
811f52c95c
14
autoPyLoT.py
14
autoPyLoT.py
@ -450,16 +450,13 @@ if __name__ == "__main__":
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autoregressive prediction and AIC followed by locating the seismic events using
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NLLoc''')
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# parser.add_argument('-d', '-D', '--input_dict', type=str,
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# action='store',
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# help='''optional, dictionary containing processing parameters''')
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# parser.add_argument('-p', '-P', '--parameter', type=str,
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# action='store',
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# help='''parameter file, default=None''')
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parser.add_argument('-i', '-I', '--inputfile', type=str,
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action='store',
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help='''full path to the file containing the input
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parameters for autoPyLoT''')
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parser.add_argument('-p', '-P', '--iplot', type=int,
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action='store',
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help='''Boolean flag for plotting: 0=none, 1=partial, 2=all''')
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parser.add_argument('-f', '-F', '--fnames', type=str,
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action='store',
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help='''optional, list of data file names''')
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@ -472,12 +469,9 @@ if __name__ == "__main__":
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parser.add_argument('-c', '-C', '--ncores', type=int,
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action='store', default=0,
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help='''optional, number of CPU cores used for parallel processing (default: all available)''')
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# parser.add_argument('-v', '-V', '--version', action='version',
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# version='autoPyLoT ' + __version__,
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# help='show version information and exit')
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cla = parser.parse_args()
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picks = autoPyLoT(inputfile=str(cla.inputfile), fnames=str(cla.fnames),
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eventid=str(cla.eventid), savepath=str(cla.spath),
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ncores=cla.ncores)
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ncores=cla.ncores, iplot=str(cla.iplot))
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@ -44,27 +44,27 @@ def autopickevent(data, param, iplot=0, fig_dict=None, ncores=0, metadata=None,
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for station in stations:
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topick = data.select(station=station)
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if not iplot:
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input_tuples.append((topick, param, apverbose, metadata, origin))
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if iplot > 0:
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#if not iplot:
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# input_tuples.append((topick, param, apverbose, metadata, origin))
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#if iplot > 0:
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all_onsets[station] = autopickstation(topick, param, verbose=apverbose,
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iplot=iplot, fig_dict=fig_dict,
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metadata=metadata, origin=origin)
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if iplot > 0:
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print('iPlot Flag active: NO MULTIPROCESSING possible.')
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return all_onsets
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#if iplot > 0:
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# print('iPlot Flag active: NO MULTIPROCESSING possible.')
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# return all_onsets
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pool = gen_Pool(ncores)
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result = pool.map(call_autopickstation, input_tuples)
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pool.close()
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#pool = gen_Pool(ncores)
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#result = pool.map(call_autopickstation, input_tuples)
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#pool.close()
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for pick in result:
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station = pick['station']
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pick.pop('station')
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all_onsets[station] = pick
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#for pick in result:
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# station = pick['station']
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# pick.pop('station')
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# all_onsets[station] = pick
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return all_onsets
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#return all_onsets
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# quality control
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# median check and jackknife on P-onset times
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@ -95,10 +95,9 @@ def autopickstation(wfstream, pickparam, verbose=False,
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# declaring pickparam variables (only for convenience)
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# read your autoPyLoT.in for details!
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plt_flag = 0
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# special parameters for P picking
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iplot = iplot
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algoP = pickparam.get('algoP')
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pstart = pickparam.get('pstart')
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pstop = pickparam.get('pstop')
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@ -761,6 +760,7 @@ def autopickstation(wfstream, pickparam, verbose=False,
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# plot vertical trace
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if not fig_dict:
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fig = plt.figure()
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plt_flag = 1
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else:
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fig = fig_dict['mainFig']
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ax1 = fig.add_subplot(311)
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@ -905,6 +905,10 @@ def autopickstation(wfstream, pickparam, verbose=False,
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ax3.set_xlabel('Time [s] after %s' % tr_filt.stats.starttime)
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ax3.set_ylabel('Normalized Counts')
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ax3.set_title(trH2_filt.stats.channel)
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if plt_flag == 1:
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fig.show()
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raw_input()
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plt.close(fig)
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##########################################################################
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# calculate "real" onset times
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if lpickP is not None and lpickP == mpickP:
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@ -154,6 +154,7 @@ class AICPicker(AutoPicker):
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self.Pick = None
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self.slope = None
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self.SNR = None
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plt_flag = 0
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# find NaN's
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nn = np.isnan(self.cf)
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if len(nn) > 1:
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@ -244,6 +245,7 @@ class AICPicker(AutoPicker):
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if self.iplot > 1:
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if not self.fig:
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fig = plt.figure() # self.iplot) ### WHY? MP MP
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plt_flag = 1
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else:
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fig = self.fig
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ax = fig.add_subplot(111)
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@ -254,6 +256,10 @@ class AICPicker(AutoPicker):
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ax.set_xlabel('Time [s] since %s' % self.Data[0].stats.starttime)
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ax.set_yticks([])
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ax.set_title(self.Data[0].stats.station)
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if plt_flag == 1:
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fig.show()
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raw_input()
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plt.close(fig)
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return
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iislope = islope[0][0:imax]
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dataslope = self.Data[0].data[iislope]
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@ -273,6 +279,7 @@ class AICPicker(AutoPicker):
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if self.iplot > 1:
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if not self.fig:
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fig = plt.figure() # self.iplot)
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plt_flag = 1
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else:
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fig = self.fig
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ax1 = fig.add_subplot(211)
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@ -307,8 +314,16 @@ class AICPicker(AutoPicker):
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ax2.set_ylabel('Counts')
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ax2.set_yticks([])
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ax2.legend()
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if plt_flag == 1:
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fig.show()
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raw_input()
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plt.close(fig)
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else:
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ax1.set_title(self.Data[0].stats.station)
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if plt_flag == 1:
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fig.show()
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raw_input()
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plt.close(fig)
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if self.Pick == None:
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print('AICPicker: Could not find minimum, picking window too short?')
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@ -330,6 +345,7 @@ class PragPicker(AutoPicker):
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self.SNR = None
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self.slope = None
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pickflag = 0
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plt_flag = 0
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# smooth CF
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ismooth = int(round(self.Tsmooth / self.dt))
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cfsmooth = np.zeros(len(self.cf))
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@ -408,6 +424,7 @@ class PragPicker(AutoPicker):
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if self.getiplot() > 1:
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if not self.fig:
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fig = plt.figure() # self.getiplot())
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plt_flag = 1
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else:
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fig = self.fig
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ax = fig.add_subplot(111)
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@ -419,6 +436,10 @@ class PragPicker(AutoPicker):
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ax.set_yticks([])
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ax.set_title(self.Data[0].stats.station)
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ax.legend()
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if plt_flag == 1:
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fig.show()
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raw_input()
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plt.close(fig)
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return
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else:
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@ -50,6 +50,7 @@ def earllatepicker(X, nfac, TSNR, Pick1, iplot=0, verbosity=1, fig=None):
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LPick = None
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EPick = None
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PickError = None
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plt_flag = 0
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if verbosity:
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print('earllatepicker: Get earliest and latest possible pick'
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' relative to most likely pick ...')
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@ -120,6 +121,7 @@ def earllatepicker(X, nfac, TSNR, Pick1, iplot=0, verbosity=1, fig=None):
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if iplot > 1:
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if not fig:
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fig = plt.figure() # iplot)
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plt_flag = 1
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ax = fig.add_subplot(111)
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ax.plot(t, x, 'k', label='Data')
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ax.axvspan(t[inoise[0]], t[inoise[-1]], color='y', alpha=0.2, lw=0, label='Noise Window')
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@ -141,6 +143,10 @@ def earllatepicker(X, nfac, TSNR, Pick1, iplot=0, verbosity=1, fig=None):
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'Earliest-/Latest Possible/Most Likely Pick & Symmetric Pick Error, %s' %
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X[0].stats.station)
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ax.legend()
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if plt_flag == 1:
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fig.show()
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raw_input()
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plt.close(fig)
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return EPick, LPick, PickError
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@ -167,6 +173,7 @@ def fmpicker(Xraw, Xfilt, pickwin, Pick, iplot=0, fig=None):
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:type: int
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'''
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plt_flag = 0
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warnings.simplefilter('ignore', np.RankWarning)
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assert isinstance(Xraw, Stream), "%s is not a stream object" % str(Xraw)
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@ -292,6 +299,7 @@ def fmpicker(Xraw, Xfilt, pickwin, Pick, iplot=0, fig=None):
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if iplot > 1:
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if not fig:
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fig = plt.figure() # iplot)
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plt_flag = 1
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ax1 = fig.add_subplot(211)
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ax1.plot(t, xraw, 'k')
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ax1.plot([Pick, Pick], [max(xraw), -max(xraw)], 'b', linewidth=2, label='Pick')
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@ -317,6 +325,10 @@ def fmpicker(Xraw, Xfilt, pickwin, Pick, iplot=0, fig=None):
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ax2.text(Pick + 0.02, max(xraw) / 2, '%s' % FM, fontsize=14)
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ax2.set_xlabel('Time [s] since %s' % Xraw[0].stats.starttime)
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ax2.set_yticks([])
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if plt_flag == 1:
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fig.show()
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raw_input()
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plt.close(fig)
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return FM
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@ -685,6 +697,7 @@ def checksignallength(X, pick, TSNR, minsiglength, nfac, minpercent, iplot=0, fi
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: type: int
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'''
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plt_flag = 0
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assert isinstance(X, Stream), "%s is not a stream object" % str(X)
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print("Checking signal length ...")
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@ -729,6 +742,7 @@ def checksignallength(X, pick, TSNR, minsiglength, nfac, minpercent, iplot=0, fi
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if iplot == 2:
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if not fig:
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fig = plt.figure() # iplot)
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plt_flag = 1
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ax = fig.add_subplot(111)
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ax.plot(t, rms, 'k', label='RMS Data')
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ax.axvspan(t[inoise[0]], t[inoise[-1]], color='y', alpha=0.2, lw=0, label='Noise Window')
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@ -741,6 +755,10 @@ def checksignallength(X, pick, TSNR, minsiglength, nfac, minpercent, iplot=0, fi
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ax.set_ylabel('Counts')
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ax.set_title('Check for Signal Length, Station %s' % X[0].stats.station)
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ax.set_yticks([])
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if plt_flag == 1:
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fig.show()
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raw_input()
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plt.close(fig)
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return returnflag
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