Merge remote-tracking branch 'origin/develop' into darius

this is probably just a workaround. Why was the program trying to access picks that were removed from the pick-dictionary?

.gitignore

@@ -0,0 +1,4 @@
+
+\.idea/
+
+*.pyc

QtPyLoT.py

@@ -64,7 +64,7 @@ from pylot.core.io.data import Data
 from pylot.core.io.inputs import FilterOptions, PylotParameter
 from autoPyLoT import autoPyLoT
 from pylot.core.pick.compare import Comparison
-from pylot.core.pick.utils import symmetrize_error, getQualityFromUncertainty
+from pylot.core.pick.utils import symmetrize_error, getQualityFromUncertainty, removePicksAbove
 from pylot.core.io.phases import picksdict_from_picks
 import pylot.core.loc.nll as nll
 from pylot.core.util.defaults import FILTERDEFAULTS, SetChannelComponents
@@ -74,7 +74,8 @@ from pylot.core.util.connection import checkurl
 from pylot.core.util.dataprocessing import read_metadata, restitute_data
 from pylot.core.util.utils import fnConstructor, getLogin, \
     full_range, readFilterInformation, trim_station_components, check4gaps, make_pen, pick_color_plt, \
-    pick_linestyle_plt, remove_underscores, check4doubled, identifyPhaseID, excludeQualityClasses, has_spe, check4rotated
+    pick_linestyle_plt, remove_underscores, check4doubled, identifyPhaseID, excludeQualityClasses, has_spe, \
+    check4rotated
 from pylot.core.util.event import Event
 from pylot.core.io.location import create_creation_info, create_event
 from pylot.core.util.widgets import FilterOptionsDialog, NewEventDlg, \
@@ -2051,6 +2052,7 @@ class MainWindow(QMainWindow):
     def finalizeAutoPick(self, result):
         self.apw.enable(True)
         if result:
+            result = removePicksAbove(result, 3)
             self.init_canvas_dict_wadatijack()
             for eventID in result.keys():
                 event = self.get_event_from_id(eventID)
@@ -2956,7 +2958,7 @@ class Project(object):
                 print(e, datetime, filename)
                 continue
             for event in self.eventlist:
-                if eventID in str(event.resource_id) or event.origins:
+                if eventID in str(event.resource_id) or eventID in event.origins:
                     if event.origins:
                         origin = event.origins[0]  # should have only one origin
                         if origin.time == datetime:

pylot/core/io/default_parameters.py

@@ -273,6 +273,26 @@ defaults = {'rootpath': {'type': str,
                       'value': 1.5,
                       'namestring': 'Noise factor S'},
 
+            'checkwindowP': {'type': float,
+                      'tooltip': 'time window before HOS/AR-maximum to check for smaller maxima [s]',
+                      'value': 10.0,
+                      'namestring': 'Check Window P'},
+
+            'minfactorP': {'type': float,
+                      'tooltip': 'Second maximum must be at least minfactor * first maximum [-]',
+                      'value': 0.7,
+                      'namestring': 'Minimum Factor P'},
+
+            'checkwindowS': {'type': float,
+                             'tooltip': 'time window before AR-maximum to check for smaller maxima [s]',
+                             'value': 10.0,
+                             'namestring': 'Check Window S'},
+
+            'minfactorS': {'type': float,
+                           'tooltip': 'Second maximum must be at least minfactor * first maximum [-]',
+                           'value': 0.7,
+                           'namestring': 'Minimum Factor S'},
+
             'minfmweight': {'type': int,
                             'tooltip': 'minimum required P weight for first-motion determination',
                             'value': 1,
@@ -455,7 +475,9 @@ settings_special_pick = {
         'aictsmooth',
         'tsmoothP',
         'ausP',
-        'nfacP'],
+        'nfacP',
+        'checkwindowP',
+        'minfactorP'],
     'h': [
         'algoS',
         'tdet1h',
@@ -469,7 +491,9 @@ settings_special_pick = {
         'aictsmoothS',
         'tsmoothS',
         'ausS',
-        'nfacS'],
+        'nfacS',
+        'checkwindowS',
+        'minfactorS'],
     'fm': [
         'minfmweight',
         'minFMSNR',

pylot/core/pick/autopick.py

@@ -177,6 +177,10 @@ def autopickstation(wfstream, pickparam, verbose=False,
     # parameter to check for spuriously picked S onset
     zfac = pickparam.get('zfac')
     # path to inventory-, dataless- or resp-files
+    checkwindowP = pickparam.get('checkwindowP')
+    minfactorP = pickparam.get('minfactorP')
+    checkwindowS = pickparam.get('checkwindowS')
+    minfactorS = pickparam.get('minfactorS')
 
     # initialize output
     Pweight = 4  # weight for P onset
@@ -324,7 +328,8 @@ def autopickstation(wfstream, pickparam, verbose=False,
             fig = fig_dict[key]
         else:
             fig = None
-        aicpick = AICPicker(aiccf, tsnrz, pickwinP, iplot, None, aictsmoothP, fig=fig)
+        aicpick = AICPicker(aiccf, tsnrz, pickwinP, checkwindow=checkwindowP, minfactor=minfactorP,
+                            iplot=iplot, Tsmooth=tsmoothP, fig=fig)
         # add pstart and pstop to aic plot
         if fig:
             for ax in fig.axes:
@@ -444,8 +449,8 @@ def autopickstation(wfstream, pickparam, verbose=False,
                 fig = fig_dict['refPpick']
             else:
                 fig = None
-            refPpick = PragPicker(cf2, tsnrz, pickwinP, iplot, ausP, tsmoothP,
-                                  aicpick.getpick(), fig)
+            refPpick = PragPicker(cf2, tsnrz, pickwinP, iplot=iplot, aus=ausP, Tsmooth=tsmoothP,
+                                  Pick1 = aicpick.getpick(), fig=fig)
             mpickP = refPpick.getpick()
             #############################################################
             if mpickP is not None:
@@ -626,8 +631,9 @@ def autopickstation(wfstream, pickparam, verbose=False,
             fig = fig_dict['aicARHfig']
         else:
             fig = None
-        aicarhpick = AICPicker(haiccf, tsnrh, pickwinS, iplot, None,
-                               aictsmoothS, fig=fig)
+        aicarhpick = AICPicker(haiccf, tsnrh, pickwinS, checkwindow=checkwindowS,
+                               minfactor=minfactorS, iplot=iplot, Tsmooth=aictsmoothS,
+                               fig=fig)
         ###############################################################
         # go on with processing if AIC onset passes quality control
         slope = aicarhpick.getSlope()
@@ -688,8 +694,8 @@ def autopickstation(wfstream, pickparam, verbose=False,
                 fig = fig_dict['refSpick']
             else:
                 fig = None
-            refSpick = PragPicker(arhcf2, tsnrh, pickwinS, iplot, ausS,
-                                  tsmoothS, aicarhpick.getpick(), fig)
+            refSpick = PragPicker(arhcf2, tsnrh, pickwinS, iplot=iplot, aus=ausS,
+                                  Tsmooth=tsmoothS, Pick1=aicarhpick.getpick(), fig=fig)
             mpickS = refSpick.getpick()
             #############################################################
             if mpickS is not None:

pylot/core/pick/picker.py

@@ -24,7 +24,7 @@ import warnings
 import matplotlib.pyplot as plt
 import numpy as np
 from pylot.core.pick.charfuns import CharacteristicFunction
-from pylot.core.pick.utils import getnoisewin, getsignalwin
+from pylot.core.pick.utils import getnoisewin, getsignalwin, get_maximum_index
 
 
 class AutoPicker(object):
@@ -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, checkwindow=None, minfactor=None, iplot=0, aus=None, Tsmooth=None, Pick1=None, fig=None):
         '''
         :param: cf, characteristic function, on which the picking algorithm is applied
         :type: `~pylot.core.pick.CharFuns.CharacteristicFunction` object
@@ -74,6 +74,8 @@ class AutoPicker(object):
         self.setTsmooth(Tsmooth)
         self.setpick1(Pick1)
         self.fig = fig
+        self.setCheckWindow(checkwindow)
+        self.minfactor = minfactor
         self.calcPick()
 
     def __str__(self):
@@ -89,6 +91,10 @@ class AutoPicker(object):
                    aus=self.getaus(),
                    Tsmooth=self.getTsmooth(),
                    Pick1=self.getpick1())
+    def setCheckWindow(self, checkwindow):
+        '''convert checkwindow to samples'''
+        if checkwindow:
+            self.checkwindow = int(checkwindow / self.Data[0].stats.delta)
 
     def getTSNR(self):
         return self.TSNR
@@ -187,8 +193,9 @@ class AICPicker(AutoPicker):
         offset = abs(min(aic) - min(aicsmooth))
         aicsmooth = aicsmooth - offset
         # get maximum of HOS/AR-CF as startimg point for searching
-        # minimum in AIC function 
-        icfmax = np.argmax(self.Data[0].data)
+        # minimum in AIC function
+        icfmax = get_maximum_index(self.Data[0].data, self.checkwindow, self.minfactor,
+                                   int(self.TSNR[1]/self.Data[0].stats.delta))
 
         # find minimum in AIC-CF front of maximum of HOS/AR-CF
         lpickwindow = int(round(self.PickWindow / self.dt))

pylot/core/pick/utils.py

@@ -13,6 +13,7 @@ import warnings
 import matplotlib.pyplot as plt
 import numpy as np
 from obspy.core import Stream, UTCDateTime
+from scipy.signal import argrelextrema
 
 
 def earllatepicker(X, nfac, TSNR, Pick1, iplot=0, verbosity=1, fig=None):
@@ -616,6 +617,7 @@ def wadaticheck(pickdic, dttolerance, iplot=0, fig_dict=None):
         checkedPpicks = []
         checkedSpicks = []
         checkedSPtimes = []
+        badstations = []
         # calculate deviations from Wadati regression
         ii = 0
         ibad = 0
@@ -629,6 +631,7 @@ def wadaticheck(pickdic, dttolerance, iplot=0, fig_dict=None):
                     # (not used anymore)
                     marker = 'badWadatiCheck'
                     pickdic[key]['S']['weight'] = 9
+                    badstations.append(key)
                     ibad += 1
                 else:
                     marker = 'goodWadatiCheck'
@@ -640,6 +643,8 @@ def wadaticheck(pickdic, dttolerance, iplot=0, fig_dict=None):
                     checkedSPtimes.append(checkedSPtime)
 
                 pickdic[key]['S']['marked'] = marker
+        print("wadaticheck: the following stations failed the check:")
+        print(badstations)
 
         if len(checkedPpicks) >= 3:
             # calculate new slope
@@ -862,6 +867,7 @@ def checkPonsets(pickdic, dttolerance, jackfactor=5, iplot=0, fig_dict=None):
     print("checkPonsets: %d pick(s) deviate too much from median!" % len(ibad))
     print("checkPonsets: Skipped %d P pick(s) out of %d" % (len(badstations) \
                                                             + len(badjkstations), len(stations)))
+    print(badstations)
 
     goodmarker = 'goodPonsetcheck'
     badmarker = 'badPonsetcheck'
@@ -935,8 +941,9 @@ def jackknife(X, phi, h):
     PHI_sub = None
 
     # determine number of subgroups
+    g = int(len(X) / h)
 
-    if len(X) % h:
+    if (len(X) / h) % 1 != 0:
         print("jackknife: Cannot divide quantity X in equal sized subgroups!")
         print("Choose another size for subgroups!")
         return PHI_jack, PHI_pseudo, PHI_sub
@@ -953,7 +960,7 @@ def jackknife(X, phi, h):
         # estimators of subgroups
         PHI_pseudo = []
         PHI_sub = []
-        for i in range(0, g - 1):
+        for i in range(0, g):
             # subgroup i, remove i-th sample
             xx = X[:]
             del xx[i]
@@ -1147,6 +1154,55 @@ def getQualityFromUncertainty(uncertainty, Errors):
 
     return quality
 
+def removePicksAbove(pickDic, minWeight):
+    '''remove picks from pick dicitonary with a weight > minweight'''
+    newdic = {}
+    for event in pickDic.keys():
+        newdic[event] = {}
+
+    for eventKey, eventDic in pickDic.items():
+        for station, phases in eventDic.items():
+            if phases['P']['weight'] < minWeight or phases['S']['weight'] < minWeight:
+                # dont append stations that will be empty to output dict
+                newdic[eventKey][station] = {}
+                if len(phases) > 2:
+                    # copy over other values beside P/S information
+                    additional_info = phases.copy()
+                    if 'P' in phases.keys():
+                        additional_info.pop('P')
+                    if 'S' in phases.keys():
+                        additional_info.pop('S')
+                    newdic[eventKey][station].update(additional_info)
+            for phasename, phaseinfo in phases.items():
+                if phasename in ('P', 'S') and phaseinfo['weight'] < minWeight:
+                    newdic[eventKey][station].update({phasename: phaseinfo})
+    return newdic
+
+
+def get_maximum_index(data, checkwindow, minfactor, safetygap):
+    '''get maximum of CF as starting point, then check for highest local maximum
+    in front of it.
+    return second maximum if its larger than first maximum * minfactor, else
+    return first maximum.
+    checkwindow and safetygap are given in samples'''
+    icfmax1 = np.argmax(data)
+    imax_local = argrelextrema(data[icfmax1 - checkwindow:icfmax1 - safetygap], np.greater)[0] # indices of local maxima
+    if imax_local.size > 0:
+        imax_local = imax_local + icfmax1 - checkwindow
+        local_maxima = (imax_local, data[imax_local])
+        largest_local_max = np.where(local_maxima[1] == max(local_maxima[1]))
+        icfmax2 = local_maxima[0][largest_local_max]
+        if data[icfmax2] > data[icfmax1] * minfactor:
+            print("Found valid local maximum in front of first maximum")
+            return icfmax2[0]
+        else:
+            print("First maximum is the largest: {}>{}".format(data[icfmax1],
+                                                               data[icfmax2]))
+            return icfmax1
+    else:
+        print("No local maxima found in check window")
+        return icfmax1
+
 if __name__ == '__main__':
     import doctest
 

pylot/core/util/widgets.py

@@ -377,7 +377,7 @@ class ComparisonWidget(QWidget):
                 axes_dict[phase]['std'].set_xlabel('standard deviation [s]')
 
             for ax in axes_dict['P'].values():
-                ax.set_ylabel('frequency [-]')
+                ax.set_ylabel('number of picks [-]')
 
             self.canvas.draw()
         else:
@@ -2442,7 +2442,7 @@ class TuneAutopicker(QWidget):
         self.setParent(parent)
         self.setWindowTitle('PyLoT - Tune Autopicker')
         self.parameter = parent._inputs
-        self.fig_dict = parent.fig_dict
+        self.set_fig_dict(parent.fig_dict)
         self.data = Data()
         self.init_main_layouts()
         self.init_eventlist()
@@ -2462,6 +2462,11 @@ class TuneAutopicker(QWidget):
             # self.setWindowModality(QtCore.Qt.WindowModality.ApplicationModal)
             # self.setWindowFlags(self.windowFlags() | QtCore.Qt.WindowStaysOnTopHint)
 
+    def set_fig_dict(self, fig_dict):
+        for key, value in fig_dict.items():
+            value._tight = True
+        self.fig_dict = fig_dict
+
     def init_main_layouts(self):
         self.main_layout = QtGui.QVBoxLayout()
         self.tune_layout = QtGui.QHBoxLayout()
@@ -2480,6 +2485,7 @@ class TuneAutopicker(QWidget):
 
     def init_stationlist(self):
         self.stationBox = QtGui.QComboBox()
+        self.stationBox.setMaxVisibleItems(42)
         self.trace_layout.addWidget(self.stationBox)
         self.fill_stationbox()
         self.figure_tabs.setCurrentIndex(0)
@@ -2568,7 +2574,10 @@ class TuneAutopicker(QWidget):
     def get_current_event_autopicks(self, station):
         event = self.get_current_event()
         if event.pylot_autopicks:
-            return event.pylot_autopicks[station]
+            if station in event.pylot_autopicks:
+                return event.pylot_autopicks[station]
+            else:
+                return
 
     def get_current_station(self):
         return str(self.stationBox.currentText()).split('.')[-1]