[update] added test for AutoPyLoT, added test files for correlation picker as well

.gitignore

@@ -2,3 +2,4 @@
 *~
 .idea
 pylot/RELEASE-VERSION
+/tests/test_autopicker/dmt_database_test/

PyLoT.py

@@ -1031,22 +1031,23 @@ class MainWindow(QMainWindow):
                 if not fname:
                     return
 
-        qmb = QMessageBox(self, icon=QMessageBox.Question,
-                          text='Do you want to overwrite this data?',)
-        overwrite_button = qmb.addButton('Overwrite', QMessageBox.YesRole)
-        merge_button = qmb.addButton('Merge', QMessageBox.NoRole)
-
-        qmb.exec_()
-
-        if qmb.clickedButton() == overwrite_button:
-            merge_strategy = 'Overwrite'
-        elif qmb.clickedButton() == merge_button:
-            merge_strategy = 'Merge'
-        else:
-            return
-
         if not event:
             event = self.get_current_event()
+
+        if event.picks:
+            qmb = QMessageBox(self, icon=QMessageBox.Question,
+                              text='Do you want to overwrite the data?',)
+            overwrite_button = qmb.addButton('Overwrite', QMessageBox.YesRole)
+            merge_button = qmb.addButton('Merge', QMessageBox.NoRole)
+            qmb.exec_()
+
+            if qmb.clickedButton() == overwrite_button:
+                merge_strategy = 'Overwrite'
+            elif qmb.clickedButton() == merge_button:
+                merge_strategy = 'Merge'
+            else:
+                return
+
         data = Data(self, event)
         try:
             data_new = Data(self, evtdata=str(fname))

autoPyLoT.py

@@ -184,15 +184,15 @@ def autoPyLoT(input_dict=None, parameter=None, inputfile=None, fnames=None, even
         if not input_dict:
             # started in production mode
             datapath = datastructure.expandDataPath()
-            if fnames == 'None' and parameter['eventID'] == '*':
+            if fnames in [None, 'None'] and parameter['eventID'] == '*':
                 # multiple event processing
                 # read each event in database
                 events = [event for event in glob.glob(os.path.join(datapath, '*')) if
                           (os.path.isdir(event) and not event.endswith('EVENTS-INFO'))]
-            elif fnames == 'None' and parameter['eventID'] != '*' and not type(parameter['eventID']) == list:
+            elif fnames in [None, 'None'] and parameter['eventID'] != '*' and not type(parameter['eventID']) == list:
                 # single event processing
                 events = glob.glob(os.path.join(datapath, parameter['eventID']))
-            elif fnames == 'None' and type(parameter['eventID']) == list:
+            elif fnames in [None, 'None'] and type(parameter['eventID']) == list:
                 # multiple event processing
                 events = []
                 for eventID in parameter['eventID']:
@@ -234,12 +234,15 @@ def autoPyLoT(input_dict=None, parameter=None, inputfile=None, fnames=None, even
                 data.get_evt_data().path = eventpath
                 print('Reading event data from filename {}...'.format(filename))
             except Exception as e:
-                print('Could not read event from file {}: {}'.format(filename, e))
+                if type(e) == FileNotFoundError:
+                    print('Creating new event file.')
+                else:
+                    print('Could not read event from file {}: {}'.format(filename, e))
                 data = Data()
                 pylot_event = Event(eventpath)  # event should be path to event directory
                 data.setEvtData(pylot_event)
-            if fnames == 'None':
-                data.setWFData(glob.glob(os.path.join(datapath, event_datapath, '*')))
+            if fnames in [None, 'None']:
+                data.setWFData(glob.glob(os.path.join(event_datapath, '*')))
                 # the following is necessary because within
                 # multiple event processing no event ID is provided
                 # in autopylot.in

pylot/core/pick/charfuns.py

@@ -17,7 +17,10 @@ autoregressive prediction: application ot local and regional distances, Geophys.
 :author: MAGS2 EP3 working group
 """
 import numpy as np
-from scipy import signal
+try:
+    from scipy.signal import tukey
+except ImportError:
+    from scipy.signal.windows import tukey
 from obspy.core import Stream
 
 from pylot.core.pick.utils import PickingFailedException
@@ -227,7 +230,7 @@ class AICcf(CharacteristicFunction):
         ind = np.where(~np.isnan(xnp))[0]
         if ind.size:
             xnp[:ind[0]] = xnp[ind[0]]
-        xnp = signal.tukey(len(xnp), alpha=0.05) * xnp
+        xnp = tukey(len(xnp), alpha=0.05) * xnp
         xnp = xnp - np.mean(xnp)
         datlen = len(xnp)
         k = np.arange(1, datlen)

pylot/core/util/dataprocessing.py

@@ -27,6 +27,10 @@ class Metadata(object):
         # saves which metadata files are from obspy dmt
         self.obspy_dmt_invs = []
         if inventory:
+            # make sure that no accidental backslashes mess up the path
+            if isinstance(inventory, str):
+                inventory = inventory.replace('\\', '/')
+                inventory = os.path.abspath(inventory)
             if os.path.isdir(inventory):
                 self.add_inventory(inventory)
             if os.path.isfile(inventory):

tests/test_autopicker/pylot_alparray_mantle_corr_stack_0.03-0.5.in

@@ -0,0 +1,99 @@
+%This is a parameter input file for PyLoT/autoPyLoT.
+%All main and special settings regarding data handling
+%and picking are to be set here!
+%Parameters are optimized for %extent data sets!
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+#main settings#
+dmt_database_test                                  #datapath#       %data path
+20171010_063224.a                                  #eventID#        %event ID for single event processing (* for all events found in database)
+                                                   #invdir#         %full path to  inventory or dataless-seed file                                                       
+PILOT                                              #datastructure#  %choose data structure                                                                               
+True                                               #apverbose#      %choose 'True' or 'False' for terminal output                                                        
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+#NLLoc settings#
+None                                               #nllocbin#       %path to NLLoc executable                                                                            
+None                                               #nllocroot#      %root of NLLoc-processing directory                                                                  
+None                                               #phasefile#      %name of autoPyLoT-output phase file for NLLoc                                                       
+None                                               #ctrfile#        %name of autoPyLoT-output control file for NLLoc                                                     
+ttime                                              #ttpatter#       %pattern of NLLoc ttimes from grid                                                                   
+AUTOLOC_nlloc                                      #outpatter#      %pattern of NLLoc-output file                                                                        
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+#parameters for seismic moment estimation#
+3530.0                                             #vp#             %average P-wave velocity                                                                             
+2500.0                                             #rho#            %average rock density [kg/m^3]                                                                       
+300.0 0.8                                          #Qp#             %quality factor for P waves (Qp*f^a); list(Qp, a)                                                    
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+#settings local magnitude#
+1.0 1.0 1.0                                        #WAscaling#      %Scaling relation (log(Ao)+Alog(r)+Br+C) of Wood-Anderson amplitude Ao [nm]                           If zeros are set, original Richter magnitude is calculated!
+1.0 1.0                                            #magscaling#     %Scaling relation for derived local magnitude [a*Ml+b].                            If zeros are set, no scaling of network magnitude is applied!
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+#filter settings#
+0.03 0.03                                          #minfreq#        %Lower filter frequency [P, S]                                                                       
+0.5 0.5                                            #maxfreq#        %Upper filter frequency [P, S]                                                                       
+4 4                                                #filter_order#   %filter order [P, S]                                                                                 
+bandpass bandpass                                  #filter_type#    %filter type (bandpass, bandstop, lowpass, highpass) [P, S]                                          
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+#common settings picker#
+global                                             #extent#         %extent of array ("local", "regional" or "global")                                                   
+-100.0                                             #pstart#         %start time [s] for calculating CF for P-picking (if TauPy: seconds relative to estimated onset)     
+50.0                                               #pstop#          %end time [s] for calculating CF for P-picking (if TauPy: seconds relative to estimated onset)       
+-50.0                                              #sstart#         %start time [s] relative to P-onset for calculating CF for S-picking                                 
+50.0                                               #sstop#          %end time [s] after P-onset for calculating CF for S-picking                                         
+True                                               #use_taup#       %use estimated traveltimes from TauPy for calculating windows for CF                                 
+ak135                                              #taup_model#     %Define TauPy model for traveltime estimation. Possible values: 1066a, 1066b, ak135, ak135f, herrin, iasp91, jb, prem, pwdk, sp6
+P,Pdiff,S,SKS                                      #taup_phases#    %Specify possible phases for TauPy (comma separated). See Obspy TauPy documentation for possible values.
+0.03 0.5                                           #bpz1#           %lower/upper corner freq. of first band pass filter Z-comp. [Hz]                                     
+0.01 0.5                                           #bpz2#           %lower/upper corner freq. of second band pass filter Z-comp. [Hz]                                    
+0.03 0.5                                           #bph1#           %lower/upper corner freq. of first band pass filter H-comp. [Hz]                                     
+0.01 0.5                                           #bph2#           %lower/upper corner freq. of second band pass filter z-comp. [Hz]                                    
+#special settings for calculating CF#
+%!!Edit the following only if you know what you are doing!!%
+#Z-component#
+HOS                                                #algoP#          %choose algorithm for P-onset determination (HOS, ARZ, or AR3)                                       
+300.0                                              #tlta#           %for HOS-/AR-AIC-picker, length of LTA window [s]                                                    
+4                                                  #hosorder#       %for HOS-picker, order of Higher Order Statistics                                                    
+2                                                  #Parorder#       %for AR-picker, order of AR process of Z-component                                                   
+16.0                                               #tdet1z#         %for AR-picker, length of AR determination window [s] for Z-component, 1st pick                      
+10.0                                               #tpred1z#        %for AR-picker, length of AR prediction window [s] for Z-component, 1st pick                         
+12.0                                               #tdet2z#         %for AR-picker, length of AR determination window [s] for Z-component, 2nd pick                      
+6.0                                                #tpred2z#        %for AR-picker, length of AR prediction window [s] for Z-component, 2nd pick                         
+0.001                                              #addnoise#       %add noise to seismogram for stable AR prediction                                                    
+60.0 5.0 20.0 12.0                                 #tsnrz#          %for HOS/AR, window lengths for SNR-and slope estimation [tnoise, tsafetey, tsignal, tslope] [s]     
+50.0                                               #pickwinP#       %for initial AIC pick, length of P-pick window [s]                                                   
+30.0                                               #Precalcwin#     %for HOS/AR, window length [s] for recalculation of CF (relative to 1st pick)                        
+2.0                                                #aictsmooth#     %for HOS/AR, take average of samples for smoothing of AIC-function [s]                               
+2.0                                                #tsmoothP#       %for HOS/AR, take average of samples in this time window for smoothing CF [s]                        
+0.006                                              #ausP#           %for HOS/AR, artificial uplift of samples (aus) of CF (P)                                            
+2.0                                                #nfacP#          %for HOS/AR, noise factor for noise level determination (P)                                          
+#H-components#
+ARH                                                #algoS#          %choose algorithm for S-onset determination (ARH or AR3)                                             
+12.0                                               #tdet1h#         %for HOS/AR, length of AR-determination window [s], H-components, 1st pick                           
+6.0                                                #tpred1h#        %for HOS/AR, length of AR-prediction window [s], H-components, 1st pick                              
+8.0                                                #tdet2h#         %for HOS/AR, length of AR-determinaton window [s], H-components, 2nd pick                            
+4.0                                                #tpred2h#        %for HOS/AR, length of AR-prediction window [s], H-components, 2nd pick                              
+4                                                  #Sarorder#       %for AR-picker, order of AR process of H-components                                                  
+100.0                                              #Srecalcwin#     %for AR-picker, window length [s] for recalculation of CF (2nd pick) (H)                             
+195.0                                              #pickwinS#       %for initial AIC pick, length of S-pick window [s]                                                   
+60.0 10.0 30.0 12.0                                #tsnrh#          %for ARH/AR3, window lengths for SNR-and slope estimation [tnoise, tsafetey, tsignal, tslope] [s]    
+22.0                                               #aictsmoothS#    %for AIC-picker, take average of samples in this time window for smoothing of AIC-function [s]       
+20.0                                               #tsmoothS#       %for AR-picker, take average of samples for smoothing CF [s] (S)                                     
+0.001                                              #ausS#           %for HOS/AR, artificial uplift of samples (aus) of CF (S)                                            
+2.0                                                #nfacS#          %for AR-picker, noise factor for noise level determination (S)                                       
+#first-motion picker#
+1                                                  #minfmweight#    %minimum required P weight for first-motion determination                                            
+3.0                                                #minFMSNR#       %miniumum required SNR for first-motion determination                                                
+10.0                                               #fmpickwin#      %pick window [s] around P onset for calculating zero crossings                                       
+#quality assessment#
+0.1 0.2 0.4 0.8                                    #timeerrorsP#    %discrete time errors [s] corresponding to picking weights [0 1 2 3] for P                           
+4.0 8.0 16.0 32.0                                  #timeerrorsS#    %discrete time errors [s] corresponding to picking weights [0 1 2 3] for S                           
+0.005                                              #minAICPslope#   %below this slope [counts/s] the initial P pick is rejected                                          
+1.1                                                #minAICPSNR#     %below this SNR the initial P pick is rejected                                                       
+0.002                                              #minAICSslope#   %below this slope [counts/s] the initial S pick is rejected                                          
+1.3                                                #minAICSSNR#     %below this SNR the initial S pick is rejected                                                       
+20.0                                               #minsiglength#   %length of signal part for which amplitudes must exceed noiselevel [s]                               
+1.0                                                #noisefactor#    %noiselevel*noisefactor=threshold                                                                    
+10.0                                               #minpercent#     %required percentage of amplitudes exceeding threshold                                               
+0.1                                                #zfac#           %P-amplitude must exceed at least zfac times RMS-S amplitude                                         
+100.0                                              #mdttolerance#   %maximum allowed deviation of P picks from median [s]                                                
+50.0                                               #wdttolerance#   %maximum allowed deviation from Wadati-diagram                                                       
+25.0                                               #jackfactor#     %pick is removed if the variance of the subgroup with the pick removed is larger than the mean variance of all subgroups times safety factor

tests/test_autopicker/test_autopylot.py

@@ -0,0 +1,67 @@
+import os
+import pytest
+
+from obspy import read_events
+
+from autoPyLoT import autoPyLoT
+
+
+class TestAutopickerGlobal():
+    def init(self):
+        self.params_infile = 'pylot_alparray_mantle_corr_stack_0.03-0.5.in'
+        self.test_event_dir = 'dmt_database_test'
+        self.fname_outfile_xml = os.path.join(
+            self.test_event_dir, '20171010_063224.a', 'PyLoT_20171010_063224.a_autopylot.xml'
+        )
+
+        # check if the input files exist
+        if not os.path.isfile(self.params_infile):
+            print(f'Test input file {os.path.abspath(self.params_infile)} not found.')
+            return False
+
+        if not os.path.exists(self.test_event_dir):
+            print(
+                f'Test event directory not found at location "{os.path.abspath(self.test_event_dir)}". '
+                f'Make sure to load it from the website first.'
+            )
+            return False
+
+        return True
+
+    def test_autopicker(self):
+        assert self.init(), 'Initialization failed due to missing input files.'
+        # check for output file in test directory and remove it if necessary
+        if os.path.isfile(self.fname_outfile_xml):
+            os.remove(self.fname_outfile_xml)
+        autoPyLoT(inputfile=self.params_infile, eventid='20171010_063224.a', obspyDMT_wfpath='processed')
+
+        # test for different known output files if they are identical or not
+        compare_pickfiles(self.fname_outfile_xml, 'PyLoT_20171010_063224.a_autopylot.xml', True)
+        compare_pickfiles(self.fname_outfile_xml, 'PyLoT_20171010_063224.a_saved_from_GUI.xml', True)
+        compare_pickfiles(self.fname_outfile_xml, 'PyLoT_20171010_063224.a_corrected_taup_times_0.03-0.5_P.xml', False)
+
+
+def compare_pickfiles(pickfile1: str, pickfile2: str, samefile: bool = True) -> None:
+    """
+    Compare the pick times and errors from two pick files.
+
+    Parameters:
+        pickfile1 (str): The path to the first pick file.
+        pickfile2 (str): The path to the second pick file.
+        samefile (bool): A flag indicating whether the two files are expected to be the same. Defaults to True.
+
+    Returns:
+        None
+    """
+    cat1 = read_events(pickfile1)
+    cat2 = read_events(pickfile2)
+    picks1 = sorted(cat1[0].picks, key=lambda pick: str(pick.waveform_id))
+    picks2 = sorted(cat2[0].picks, key=lambda pick: str(pick.waveform_id))
+    pick_times1 = [pick.time for pick in picks1]
+    pick_times2 = [pick.time for pick in picks2]
+    pick_terrs1 = [pick.time_errors for pick in picks1]
+    pick_terrs2 = [pick.time_errors for pick in picks2]
+
+    # check if times and errors are identical or not depending on the samefile flag
+    assert (pick_times1 == pick_times2) is samefile, 'Pick times error'
+    assert (pick_terrs1 == pick_terrs2) is samefile, 'Pick time errors errors'