Added getQualitiesFromXML and EventlistFromXML scripts and respective buttons
Changed Icons for both Button - only temporary versions at the moment
This commit is contained in:
79
pylot/core/io/getEventListFromXML.py
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79
pylot/core/io/getEventListFromXML.py
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#!/usr/bin/python
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# -*- coding: utf-8 -*-
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"""
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Script to get event parameters from PyLoT-xml file to write
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them into eventlist.
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LK, igem, 03/2021
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Edited for use in PyLoT
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JG, igem, 01/2022
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"""
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import pdb
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import os
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import argparse
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import numpy as np
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import matplotlib.pyplot as plt
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from obspy.core.event import read_events
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from pyproj import Proj
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import glob
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"""
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Creates an eventlist file summarizing all events found in a certain folder. Only called by pressing UI Button eventlis_xml_action
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:rtype:
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:param path: Path to root folder where single Event folder are to found
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"""
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def geteventlistfromxml(path, outpath):
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p = Proj(proj='utm', zone=32, ellps='WGS84')
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# open eventlist file and write header
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evlist = outpath + '/eventlist'
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evlistobj = open(evlist, 'w')
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evlistobj.write('EventID Date To Lat Lon EAST NORTH Dep Ml NoP NoS RMS errH errZ Gap \n')
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# data path
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dp = path + "/e*/*.xml"
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# list of all available xml-files
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xmlnames = glob.glob(dp)
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# read all onset weights
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for names in xmlnames:
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print("Getting location parameters from {}".format(names))
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cat = read_events(names)
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try:
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st = cat.events[0].origins[0].time
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Lat = cat.events[0].origins[0].latitude
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Lon = cat.events[0].origins[0].longitude
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EAST, NORTH = p(Lon, Lat)
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Dep = cat.events[0].origins[0].depth / 1000
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Ml = cat.events[0].magnitudes[1].mag
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NoP = []
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NoS = []
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except IndexError:
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print ('Insufficient data found for event (not localised): ' + names.split('/')[-1].split('_')[-1][:-4] + ' Skipping event for eventlist.' )
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continue
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for i in range(len(cat.events[0].origins[0].arrivals)):
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if cat.events[0].origins[0].arrivals[i].phase == 'P':
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NoP.append(cat.events[0].origins[0].arrivals[i].phase)
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elif cat.events[0].origins[0].arrivals[i].phase == 'S':
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NoS.append(cat.events[0].origins[0].arrivals[i].phase)
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#NoP = cat.events[0].origins[0].quality.used_station_count
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errH = cat.events[0].origins[0].origin_uncertainty.max_horizontal_uncertainty
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errZ = cat.events[0].origins[0].depth_errors.uncertainty
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Gap = cat.events[0].origins[0].quality.azimuthal_gap
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#evID = names.split('/')[6]
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evID = names.split('/')[-1].split('_')[-1][:-4]
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Date = str(st.year) + str('%02d' % st.month) + str('%02d' % st.day)
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To = str('%02d' % st.hour) + str('%02d' % st.minute) + str('%02d' % st.second) + \
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'.' + str('%06d' % st.microsecond)
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# write into eventlist
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evlistobj.write('%s %s %s %9.6f %9.6f %13.6f %13.6f %8.6f %3.1f %d %d NaN %d %d %d\n' %(evID, \
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Date, To, Lat, Lon, EAST, NORTH, Dep, Ml, len(NoP), len(NoS), errH, errZ, Gap))
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print ('Adding Event ' + names.split('/')[-1].split('_')[-1][:-4] + ' to eventlist')
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print('Eventlist created and saved in: ' + outpath)
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evlistobj.close()
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139
pylot/core/io/getQualitiesfromxml.py
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139
pylot/core/io/getQualitiesfromxml.py
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#!/usr/bin/python
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# -*- coding: utf-8 -*-
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"""
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Script to get onset uncertainties from Quakeml.xml files created by PyLoT.
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Uncertainties are tranformed into quality classes and visualized via histogram if desired.
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Ludger Küperkoch, BESTEC GmbH, 07/2017
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rev.: Ludger Küperkoch, igem, 10/2020
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Edited for usage in PyLoT: Jeldrik Gaal, igem, 01/2022
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"""
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import argparse
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import numpy as np
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import matplotlib.pyplot as plt
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from obspy.core.event import read_events
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import glob
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def getQualitiesfromxml(path):
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# uncertainties
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ErrorsP = [0.02, 0.04, 0.08, 0.16]
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ErrorsS = [0.04, 0.08, 0.16, 0.32]
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Pw0 = []
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Pw1 = []
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Pw2 = []
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Pw3 = []
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Pw4 = []
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Sw0 = []
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Sw1 = []
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Sw2 = []
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Sw3 = []
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Sw4 = []
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# data path
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dp = path + '/e*/*.xml'
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# list of all available xml-files
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xmlnames = glob.glob(dp)
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# read all onset weights
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for names in xmlnames:
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print("Getting onset weights from {}".format(names))
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cat = read_events(names)
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arrivals = cat.events[0].picks
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for Pick in arrivals:
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if Pick.phase_hint[0] == 'P':
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if Pick.time_errors.uncertainty <= ErrorsP[0]:
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Pw0.append(Pick.time_errors.uncertainty)
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elif Pick.time_errors.uncertainty > ErrorsP[0] and \
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Pick.time_errors.uncertainty <= ErrorsP[1]:
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Pw1.append(Pick.time_errors.uncertainty)
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elif Pick.time_errors.uncertainty > ErrorsP[1] and \
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Pick.time_errors.uncertainty <= ErrorsP[2]:
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Pw2.append(Pick.time_errors.uncertainty)
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elif Pick.time_errors.uncertainty > ErrorsP[2] and \
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Pick.time_errors.uncertainty <= ErrorsP[3]:
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Pw3.append(Pick.time_errors.uncertainty)
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elif Pick.time_errors.uncertainty > ErrorsP[3]:
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Pw4.append(Pick.time_errors.uncertainty)
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else:
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pass
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elif Pick.phase_hint[0] == 'S':
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if Pick.time_errors.uncertainty <= ErrorsS[0]:
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Sw0.append(Pick.time_errors.uncertainty)
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elif Pick.time_errors.uncertainty > ErrorsS[0] and \
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Pick.time_errors.uncertainty <= ErrorsS[1]:
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Sw1.append(Pick.time_errors.uncertainty)
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elif Pick.time_errors.uncertainty > ErrorsS[1] and \
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Pick.time_errors.uncertainty <= ErrorsS[2]:
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Sw2.append(Pick.time_errors.uncertainty)
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elif Pick.time_errors.uncertainty > ErrorsS[2] and \
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Pick.time_errors.uncertainty <= ErrorsS[3]:
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Sw3.append(Pick.time_errors.uncertainty)
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elif Pick.time_errors.uncertainty > ErrorsS[3]:
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Sw4.append(Pick.time_errors.uncertainty)
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else:
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pass
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else:
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print("Phase hint not defined for picking!")
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pass
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# get percentage of weights
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numPweights = np.sum([len(Pw0), len(Pw1), len(Pw2), len(Pw3), len(Pw4)])
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numSweights = np.sum([len(Sw0), len(Sw1), len(Sw2), len(Sw3), len(Sw4)])
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try:
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P0perc = 100.0 / numPweights * len(Pw0)
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except:
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P0perc = 0
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try:
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P1perc = 100.0 / numPweights * len(Pw1)
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except:
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P1perc = 0
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try:
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P2perc = 100.0 / numPweights * len(Pw2)
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except:
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P2perc = 0
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try:
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P3perc = 100.0 / numPweights * len(Pw3)
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except:
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P3perc = 0
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try:
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P4perc = 100.0 / numPweights * len(Pw4)
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except:
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P4perc = 0
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try:
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S0perc = 100.0 / numSweights * len(Sw0)
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except:
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Soperc = 0
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try:
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S1perc = 100.0 / numSweights * len(Sw1)
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except:
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S1perc = 0
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try:
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S2perc = 100.0 / numSweights * len(Sw2)
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except:
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S2perc = 0
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try:
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S3perc = 100.0 / numSweights * len(Sw3)
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except:
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S3perc = 0
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try:
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S4perc = 100.0 / numSweights * len(Sw4)
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except:
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S4perc = 0
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weights = ('0', '1', '2', '3', '4')
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y_pos = np.arange(len(weights))
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width = 0.34
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p1, = plt.bar(0 - width, P0perc, width, color='black')
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p2, = plt.bar(0, S0perc, width, color='red')
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plt.bar(y_pos - width, [P0perc, P1perc, P2perc, P3perc, P4perc], width, color='black')
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plt.bar(y_pos, [S0perc, S1perc, S2perc, S3perc, S4perc], width, color='red')
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plt.ylabel('%')
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plt.xticks(y_pos, weights)
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plt.xlim([-0.5, 4.5])
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plt.xlabel('Qualities')
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plt.title('{0} P-Qualities, {1} S-Qualities'.format(numPweights, numSweights))
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plt.legend([p1, p2], ['P-Weights', 'S-Weights'])
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plt.show()
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