PyLoT.py

@@ -89,7 +89,7 @@ from pylot.core.util.structure import DATASTRUCTURE
 from pylot.core.util.thread import Thread, Worker
 from pylot.core.util.version import get_git_version as _getVersionString
 from pylot.core.io.getEventListFromXML import geteventlistfromxml
-from pylot.core.io.getQualitiesfromxml import getQualitiesfromxml
+from pylot.core.io.phases import getQualitiesfromxml
 
 from pylot.styles import style_settings
 
@@ -1669,8 +1669,8 @@ class MainWindow(QMainWindow):
         self.cmpw.show()
 
     def pickQualities(self):
-        path = self._inputs['rootpath'] + '/' + self._inputs['datapath'] + '/' + self._inputs['database']
-        getQualitiesfromxml(path)
+        path = self.get_current_event_path()
+        getQualitiesfromxml(path, self._inputs.get('timeerrorsP'), self._inputs.get('timeerrorsS'), plotflag=1)
         return
 
     def eventlistXml(self):

pylot/core/io/getQualitiesfromxml.py

@@ -1,138 +0,0 @@
-#!/usr/bin/python
-# -*- coding: utf-8 -*-
-
-"""
-   Script to get onset uncertainties from Quakeml.xml files created by PyLoT.
-   Uncertainties are tranformed into quality classes and visualized via histogram if desired.
-   Ludger Küperkoch, BESTEC GmbH, 07/2017
-   rev.: Ludger Küperkoch, igem, 10/2020
-   Edited for usage in PyLoT: Jeldrik Gaal, igem, 01/2022
-"""
-
-import glob
-
-import matplotlib.pyplot as plt
-import numpy as np
-from obspy.core.event import read_events
-
-
-def getQualitiesfromxml(path):
-    # uncertainties
-    ErrorsP = [0.02, 0.04, 0.08, 0.16]
-    ErrorsS = [0.04, 0.08, 0.16, 0.32]
-
-    Pw0 = []
-    Pw1 = []
-    Pw2 = []
-    Pw3 = []
-    Pw4 = []
-    Sw0 = []
-    Sw1 = []
-    Sw2 = []
-    Sw3 = []
-    Sw4 = []
-
-    # data path
-    dp = path + '/e*/*.xml'
-    # list of all available xml-files
-    xmlnames = glob.glob(dp)
-
-    # read all onset weights
-    for names in xmlnames:
-        print("Getting onset weights from {}".format(names))
-        cat = read_events(names)
-        arrivals = cat.events[0].picks
-        for Pick in arrivals:
-            if Pick.phase_hint[0] == 'P':
-                if Pick.time_errors.uncertainty <= ErrorsP[0]:
-                    Pw0.append(Pick.time_errors.uncertainty)
-                elif Pick.time_errors.uncertainty > ErrorsP[0] and \
-                        Pick.time_errors.uncertainty <= ErrorsP[1]:
-                    Pw1.append(Pick.time_errors.uncertainty)
-                elif Pick.time_errors.uncertainty > ErrorsP[1] and \
-                        Pick.time_errors.uncertainty <= ErrorsP[2]:
-                    Pw2.append(Pick.time_errors.uncertainty)
-                elif Pick.time_errors.uncertainty > ErrorsP[2] and \
-                        Pick.time_errors.uncertainty <= ErrorsP[3]:
-                    Pw3.append(Pick.time_errors.uncertainty)
-                elif Pick.time_errors.uncertainty > ErrorsP[3]:
-                    Pw4.append(Pick.time_errors.uncertainty)
-                else:
-                    pass
-            elif Pick.phase_hint[0] == 'S':
-                if Pick.time_errors.uncertainty <= ErrorsS[0]:
-                    Sw0.append(Pick.time_errors.uncertainty)
-                elif Pick.time_errors.uncertainty > ErrorsS[0] and \
-                        Pick.time_errors.uncertainty <= ErrorsS[1]:
-                    Sw1.append(Pick.time_errors.uncertainty)
-                elif Pick.time_errors.uncertainty > ErrorsS[1] and \
-                        Pick.time_errors.uncertainty <= ErrorsS[2]:
-                    Sw2.append(Pick.time_errors.uncertainty)
-                elif Pick.time_errors.uncertainty > ErrorsS[2] and \
-                        Pick.time_errors.uncertainty <= ErrorsS[3]:
-                    Sw3.append(Pick.time_errors.uncertainty)
-                elif Pick.time_errors.uncertainty > ErrorsS[3]:
-                    Sw4.append(Pick.time_errors.uncertainty)
-                else:
-                    pass
-            else:
-                print("Phase hint not defined for picking!")
-                pass
-    # get percentage of weights
-    numPweights = np.sum([len(Pw0), len(Pw1), len(Pw2), len(Pw3), len(Pw4)])
-    numSweights = np.sum([len(Sw0), len(Sw1), len(Sw2), len(Sw3), len(Sw4)])
-    try:
-        P0perc = 100.0 / numPweights * len(Pw0)
-    except:
-        P0perc = 0
-    try:
-        P1perc = 100.0 / numPweights * len(Pw1)
-    except:
-        P1perc = 0
-    try:
-        P2perc = 100.0 / numPweights * len(Pw2)
-    except:
-        P2perc = 0
-    try:
-        P3perc = 100.0 / numPweights * len(Pw3)
-    except:
-        P3perc = 0
-    try:
-        P4perc = 100.0 / numPweights * len(Pw4)
-    except:
-        P4perc = 0
-    try:
-        S0perc = 100.0 / numSweights * len(Sw0)
-    except:
-        Soperc = 0
-    try:
-        S1perc = 100.0 / numSweights * len(Sw1)
-    except:
-        S1perc = 0
-    try:
-        S2perc = 100.0 / numSweights * len(Sw2)
-    except:
-        S2perc = 0
-    try:
-        S3perc = 100.0 / numSweights * len(Sw3)
-    except:
-        S3perc = 0
-    try:
-        S4perc = 100.0 / numSweights * len(Sw4)
-    except:
-        S4perc = 0
-
-    weights = ('0', '1', '2', '3', '4')
-    y_pos = np.arange(len(weights))
-    width = 0.34
-    p1, = plt.bar(0 - width, P0perc, width, color='black')
-    p2, = plt.bar(0, S0perc, width, color='red')
-    plt.bar(y_pos - width, [P0perc, P1perc, P2perc, P3perc, P4perc], width, color='black')
-    plt.bar(y_pos, [S0perc, S1perc, S2perc, S3perc, S4perc], width, color='red')
-    plt.ylabel('%')
-    plt.xticks(y_pos, weights)
-    plt.xlim([-0.5, 4.5])
-    plt.xlabel('Qualities')
-    plt.title('{0} P-Qualities, {1} S-Qualities'.format(numPweights, numSweights))
-    plt.legend([p1, p2], ['P-Weights', 'S-Weights'])
-    plt.show()

pylot/core/io/phases.py

@@ -17,7 +17,7 @@ from pylot.core.io.location import create_event, \
     create_magnitude
 from pylot.core.pick.utils import select_for_phase, get_quality_class
 from pylot.core.util.utils import getOwner, full_range, four_digits, transformFilterString4Export, \
-    backtransformFilterString
+    backtransformFilterString, loopIdentifyPhase, identifyPhase
 
 
 def add_amplitudes(event, amplitudes):
@@ -375,7 +375,6 @@ def picks_from_picksdict(picks, creation_info=None):
 
 
 def reassess_pilot_db(root_dir, db_dir, out_dir=None, fn_param=None, verbosity=0):
-    import glob
     # TODO: change root to datapath
     db_root = os.path.join(root_dir, db_dir)
     evt_list = glob.glob1(db_root, 'e????.???.??')
@@ -1056,37 +1055,60 @@ def merge_picks(event, picks):
     return event
 
 
-def getQualitiesfromxml(xmlnames, ErrorsP, ErrorsS, plotflag=1):
+def getQualitiesfromxml(path, errorsP, errorsS, plotflag=1, figure=None, verbosity=0):
     """
     Script to get onset uncertainties from Quakeml.xml files created by PyLoT.
     Uncertainties are tranformed into quality classes and visualized via histogram if desired.
     Ludger Küperkoch, BESTEC GmbH, 07/2017
-    :param xmlnames: list of xml obspy event files containing picks
-    :type xmlnames: list
-    :param ErrorsP: time errors of P waves for the four discrete quality classes
-    :type ErrorsP:
-    :param ErrorsS: time errors of S waves for the four discrete quality classes
-    :type ErrorsS:
+    :param path: path containing xml files
+    :type path: str
+    :param errorsP: time errors of P waves for the four discrete quality classes
+    :type errorsP:
+    :param errorsS: time errors of S waves for the four discrete quality classes
+    :type errorsS:
     :param plotflag:
     :type plotflag:
     :return:
     :rtype:
     """
 
-    from pylot.core.pick.utils import get_quality_class
-    from pylot.core.util.utils import loopIdentifyPhase, identifyPhase
+    def calc_perc(uncertainties, ntotal):
+        if len(uncertainties) == 0:
+            return 0
+        else:
+            return 100 / ntotal * len(uncertainties)
+
+    def calc_weight_perc(psweights, weight_ids):
+        # count total number of list items for this phase
+        numWeights = np.sum([len(weight) for weight in psweights.values()])
+
+        # iterate over all available weights to return a list with percentages for plotting
+        plot_list = []
+        for weight_id in weight_ids:
+            plot_list.append(calc_perc(psweights[weight_id], numWeights))
+
+        return plot_list, numWeights
+
+    xmlnames = glob.glob(os.path.join(path, '*.xml'))
+    if len(xmlnames) == 0:
+        print(f'No files found in path {path}.')
+        return False
+
+    # first define possible phases here
+    phases = ['P', 'S']
+
+    # define possible weights (0-4)
+    weight_ids = list(range(5))
+
+    # put both error lists in a dictionary with P/S key so that amount of code can be halfed by simply using P/S as key
+    errors = dict(P=errorsP, S=errorsS)
+
+    # create dictionaries for each phase (P/S) with a dictionary of empty list for each weight defined in weights
+    # tuple above
+    weights = {}
+    for phase in phases:
+        weights[phase] = {weight_id: [] for weight_id in weight_ids}
 
-    # read all onset weights
-    Pw0 = []
-    Pw1 = []
-    Pw2 = []
-    Pw3 = []
-    Pw4 = []
-    Sw0 = []
-    Sw1 = []
-    Sw2 = []
-    Sw3 = []
-    Sw4 = []
     for names in xmlnames:
         print("Getting onset weights from {}".format(names))
         cat = read_events(names)
@@ -1094,119 +1116,60 @@ def getQualitiesfromxml(xmlnames, ErrorsP, ErrorsS, plotflag=1):
         arrivals = cat.events[0].picks
         arrivals_copy = cat_copy.events[0].picks
         # Prefere manual picks if qualities are sufficient!
-        for Pick in arrivals:
-            if Pick.method_id.id.split('/')[1] == 'manual':
-                mstation = Pick.waveform_id.station_code
+        for pick in arrivals:
+            if pick.method_id.id.split('/')[1] == 'manual':
+                mstation = pick.waveform_id.station_code
                 mstation_ext = mstation + '_'
                 for mpick in arrivals_copy:
-                    phase = identifyPhase(loopIdentifyPhase(Pick.phase_hint))
-                    if phase == 'P':
-                        if ((mpick.waveform_id.station_code == mstation) or
-                            (mpick.waveform_id.station_code == mstation_ext)) and \
-                                (mpick.method_id.id.split('/')[1] == 'auto') and \
-                                (mpick.time_errors['uncertainty'] <= ErrorsP[3]):
-                            del mpick
-                            break
-                    elif phase == 'S':
-                        if ((mpick.waveform_id.station_code == mstation) or
-                            (mpick.waveform_id.station_code == mstation_ext)) and \
-                                (mpick.method_id.id.split('/')[1] == 'auto') and \
-                                (mpick.time_errors['uncertainty'] <= ErrorsS[3]):
-                            del mpick
-                            break
+                    phase = identifyPhase(loopIdentifyPhase(pick.phase_hint)) # MP MP catch if this fails?
+                    if ((mpick.waveform_id.station_code == mstation) or
+                        (mpick.waveform_id.station_code == mstation_ext)) and \
+                            (mpick.method_id.id.split('/')[1] == 'auto') and \
+                            (mpick.time_errors['uncertainty'] <= errors[phase][3]):
+                        del mpick
+                        break
         lendiff = len(arrivals) - len(arrivals_copy)
         if lendiff != 0:
             print("Found manual as well as automatic picks, prefered the {} manual ones!".format(lendiff))
 
-        for Pick in arrivals_copy:
-            phase = identifyPhase(loopIdentifyPhase(Pick.phase_hint))
-            if phase == 'P':
-                Pqual = get_quality_class(Pick.time_errors.uncertainty, ErrorsP)
-                if Pqual == 0:
-                    Pw0.append(Pick.time_errors.uncertainty)
-                elif Pqual == 1:
-                    Pw1.append(Pick.time_errors.uncertainty)
-                elif Pqual == 2:
-                    Pw2.append(Pick.time_errors.uncertainty)
-                elif Pqual == 3:
-                    Pw3.append(Pick.time_errors.uncertainty)
-                elif Pqual == 4:
-                    Pw4.append(Pick.time_errors.uncertainty)
-            elif phase == 'S':
-                Squal = get_quality_class(Pick.time_errors.uncertainty, ErrorsS)
-                if Squal == 0:
-                    Sw0.append(Pick.time_errors.uncertainty)
-                elif Squal == 1:
-                    Sw1.append(Pick.time_errors.uncertainty)
-                elif Squal == 2:
-                    Sw2.append(Pick.time_errors.uncertainty)
-                elif Squal == 3:
-                    Sw3.append(Pick.time_errors.uncertainty)
-                elif Squal == 4:
-                    Sw4.append(Pick.time_errors.uncertainty)
-            else:
+        for pick in arrivals_copy:
+            phase = identifyPhase(loopIdentifyPhase(pick.phase_hint))
+            uncertainty = pick.time_errors.uncertainty
+            if not uncertainty:
+                if verbosity > 0:
+                    print('No uncertainty, pick {} invalid!'.format(pick.method_id.id))
+                continue
+            # check P/S phase
+            if phase not in phases:
                 print("Phase hint not defined for picking!")
-                pass
+                continue
+
+            qual = get_quality_class(uncertainty, errors[phase])
+            weights[phase][qual].append(uncertainty)
 
     if plotflag == 0:
-        Punc = [Pw0, Pw1, Pw2, Pw3, Pw4]
-        Sunc = [Sw0, Sw1, Sw2, Sw3, Sw4]
-        return Punc, Sunc
+        p_unc = [weights['P'][weight_id] for weight_id in weight_ids]
+        s_unc = [weights['S'][weight_id] for weight_id in weight_ids]
+        return p_unc, s_unc
     else:
+        if not figure:
+            fig = plt.figure()
+        ax = fig.add_subplot(111)
         # get percentage of weights
-        numPweights = np.sum([len(Pw0), len(Pw1), len(Pw2), len(Pw3), len(Pw4)])
-        numSweights = np.sum([len(Sw0), len(Sw1), len(Sw2), len(Sw3), len(Sw4)])
-        if len(Pw0) > 0:
-            P0perc = 100 / numPweights * len(Pw0)
-        else:
-            P0perc = 0
-        if len(Pw1) > 0:
-            P1perc = 100 / numPweights * len(Pw1)
-        else:
-            P1perc = 0
-        if len(Pw2) > 0:
-            P2perc = 100 / numPweights * len(Pw2)
-        else:
-            P2perc = 0
-        if len(Pw3) > 0:
-            P3perc = 100 / numPweights * len(Pw3)
-        else:
-            P3perc = 0
-        if len(Pw4) > 0:
-            P4perc = 100 / numPweights * len(Pw4)
-        else:
-            P4perc = 0
-        if len(Sw0) > 0:
-            S0perc = 100 / numSweights * len(Sw0)
-        else:
-            S0perc = 0
-        if len(Sw1) > 0:
-            S1perc = 100 / numSweights * len(Sw1)
-        else:
-            S1perc = 0
-        if len(Sw2) > 0:
-            S2perc = 100 / numSweights * len(Sw2)
-        else:
-            S2perc = 0
-        if len(Sw3) > 0:
-            S3perc = 100 / numSweights * len(Sw3)
-        else:
-            S3perc = 0
-        if len(Sw4) > 0:
-            S4perc = 100 / numSweights * len(Sw4)
-        else:
-            S4perc = 0
+        listP, numPweights = calc_weight_perc(weights['P'], weight_ids)
+        listS, numSweights = calc_weight_perc(weights['S'], weight_ids)
 
-        weights = ('0', '1', '2', '3', '4')
-        y_pos = np.arange(len(weights))
+        y_pos = np.arange(len(weight_ids))
         width = 0.34
-        plt.bar(y_pos - width, [P0perc, P1perc, P2perc, P3perc, P4perc], width, color='black')
-        plt.bar(y_pos, [S0perc, S1perc, S2perc, S3perc, S4perc], width, color='red')
-        plt.ylabel('%')
-        plt.xticks(y_pos, weights)
-        plt.xlim([-0.5, 4.5])
-        plt.xlabel('Qualities')
-        plt.title('{0} P-Qualities, {1} S-Qualities'.format(numPweights, numSweights))
-        plt.show()
+        ax.bar(y_pos - width, listP, width, color='black')
+        ax.bar(y_pos, listS, width, color='red')
+        ax.set_ylabel('%')
+        ax.set_xticks(y_pos, weight_ids)
+        ax.set_xlim([-0.5, 4.5])
+        ax.set_xlabel('Qualities')
+        ax.set_title('{0} P-Qualities, {1} S-Qualities'.format(numPweights, numSweights))
 
-        return [P0perc, P1perc, P2perc, P3perc, P4perc], [S0perc, S1perc, S2perc, S3perc, S4perc]
+        if not figure:
+            fig.show()
+
+        return listP, listS

pylot/core/pick/utils.py

@@ -1320,7 +1320,7 @@ def get_quality_class(uncertainty, weight_classes):
     :return: quality of pick (0-4)
     :rtype: int
     """
-    if not uncertainty: return max(weight_classes)
+    if not uncertainty: return len(weight_classes)
     try:
         # create generator expression containing all indices of values in weight classes that are >= than uncertainty.
         # call next on it once to receive first value

tests/test_get_qualities_from_xml.py

@@ -5,7 +5,7 @@ from pylot.core.io.phases import getQualitiesfromxml
 
 class TestQualityFromXML(unittest.TestCase):
     def setUp(self):
-        self.xmlpaths = ['PyLoT_e0019.048.13.xml']
+        self.path = '.'
         self.ErrorsP = [0.02, 0.04, 0.08, 0.16]
         self.ErrorsS = [0.04, 0.08, 0.16, 0.32]
         self.test0_result = [[0.0136956521739, 0.0126, 0.0101612903226, 0.00734848484849, 0.0135069444444,
@@ -23,10 +23,10 @@ class TestQualityFromXML(unittest.TestCase):
                             [92.0, 4.0, 4.0, 0, 0]
 
     def test_result_plotflag0(self):
-        self.assertEqual(getQualitiesfromxml(self.xmlpaths, self.ErrorsP, self.ErrorsS, 0), self.test0_result)
+        self.assertEqual(getQualitiesfromxml(self.path, self.ErrorsP, self.ErrorsS, 0), self.test0_result)
 
     def test_result_plotflag1(self):
-        self.assertEqual(getQualitiesfromxml(self.xmlpaths, self.ErrorsP, self.ErrorsS, 1), self.test1_result)
+        self.assertEqual(getQualitiesfromxml(self.path, self.ErrorsP, self.ErrorsS, 1), self.test1_result)
 
 
 if __name__ == '__main__':