Merge branch 'refs/heads/correlation_picker' into develop

This commit is contained in:
Marcel Paffrath 2024-09-12 16:24:50 +02:00
commit 41c9183be3
13 changed files with 2288 additions and 8 deletions

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@ -2196,7 +2196,8 @@ class MainWindow(QMainWindow):
if event.pylot_autopicks:
self.drawPicks(picktype='auto')
if event.pylot_picks or event.pylot_autopicks:
self.locateEventAction.setEnabled(True)
if not self._inputs.get('extent') == 'global':
self.locateEventAction.setEnabled(True)
self.qualities_action.setEnabled(True)
self.eventlist_xml_action.setEnabled(True)
@ -2631,7 +2632,6 @@ class MainWindow(QMainWindow):
picks=self.getPicksOnStation(station, 'manual'),
autopicks=self.getPicksOnStation(station, 'auto'),
metadata=self.metadata, event=event,
model=self.inputs.get('taup_model'),
filteroptions=self.filteroptions, wftype=wftype,
show_comp_data=self.dataPlot.comp_checkbox.isChecked())
if self.filterActionP.isChecked():

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@ -9,7 +9,7 @@ PyLoT - the Python picking and Localization Tool
This python library contains a graphical user interfaces for picking
seismic phases. This software needs ObsPy (http://github.com/obspy/obspy/wiki)
and the Qt4 libraries to be installed first.
and the Qt libraries to be installed first.
PILOT has been developed in Mathworks' MatLab. In order to distribute
PILOT without facing portability problems, it has been decided to re-

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@ -501,7 +501,7 @@ defaults = {'datapath': {'type': str,
'taup_model': {'type': str,
'tooltip': 'Define TauPy model for traveltime estimation. Possible values: 1066a, 1066b, ak135, ak135f, herrin, iasp91, jb, prem, pwdk, sp6',
'value': None,
'value': 'iasp91',
'namestring': 'TauPy model'},
'taup_phases': {'type': str,

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@ -21,6 +21,7 @@ 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

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@ -521,7 +521,6 @@ class Array_map(QtWidgets.QWidget):
picks=self._parent.get_current_event().getPick(station),
autopicks=self._parent.get_current_event().getAutopick(station),
filteroptions=self._parent.filteroptions, metadata=self.metadata,
model=self.parameter.get('taup_model'),
event=pyl_mw.get_current_event())
except Exception as e:
message = 'Could not generate Plot for station {st}.\n {er}'.format(st=station, er=e)

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@ -1871,13 +1871,14 @@ class PickDlg(QDialog):
def __init__(self, parent=None, data=None, data_compare=None, station=None, network=None, location=None, picks=None,
autopicks=None, rotate=False, parameter=None, embedded=False, metadata=None, show_comp_data=False,
event=None, filteroptions=None, model=None, wftype=None):
event=None, filteroptions=None, wftype=None):
super(PickDlg, self).__init__(parent, Qt.Window)
self.orig_parent = parent
self.setAttribute(Qt.WA_DeleteOnClose)
# initialize attributes
self.parameter = parameter
model = self.parameter.get('taup_model')
self._embedded = embedded
self.showCompData = show_comp_data
self.station = station
@ -2270,8 +2271,8 @@ class PickDlg(QDialog):
arrivals = func[plot](source_origin.depth,
source_origin.latitude,
source_origin.longitude,
station_coords['latitude'],
station_coords['longitude'],
station_coords.get('latitude'),
station_coords.get('longitude'),
phases)
self.arrivals = arrivals

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@ -0,0 +1,2 @@
# -*- coding: utf-8 -*-
#

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@ -0,0 +1,90 @@
############################# correlation parameters #####################################
# min_corr_stacking: minimum correlation coefficient for building beam trace
# min_corr_export: minimum correlation coefficient for pick export
# min_stack: minimum number of stations for building beam trace
# t_before: correlation window before pick
# t_after: correlation window after pick#
# cc_maxlag: maximum shift for initial correlation
# cc_maxlag2: maximum shift for second (final) correlation (also for calculating pick uncertainty)
# initial_pick_outlier_threshold: (hopefully) threshold for excluding large outliers of initial (AIC) picks
# export_threshold: automatically exclude all onsets which deviate more than this threshold from corrected taup onsets
# min_picks_export: minimum number of correlated picks for export
# min_picks_autopylot: minimum number of reference autopicks picks to continue with event
# check_RMS: do RMS check to search for restitution errors (very experimental)
# use_taupy_onsets: use taupy onsets as reference picks instead of external picks
# station_list: use the following stations as reference for stacking
# use_stacked_trace: use existing stacked trace if found (spare re-computation)
# data_dir: obspyDMT data subdirectory (e.g. 'raw', 'processed')
# pickfile_extension: use quakeML files (PyLoT output) with the following extension, e.g. '_autopylot' for pickfiles
# such as 'PyLoT_20170501_141822_autopylot.xml'
logging: info
pick_phases: ['P', 'S']
# P-phase
P:
min_corr_stacking: 0.8
min_corr_export: 0.6
min_stack: 20
t_before: 30.
t_after: 50.
cc_maxlag: 50.
cc_maxlag2: 5.
initial_pick_outlier_threshold: 30.
export_threshold: 2.5
min_picks_export: 100
min_picks_autopylot: 50
check_RMS: True
use_taupy_onsets: False
station_list: ['HU.MORH', 'HU.TIH', 'OX.FUSE', 'OX.BAD']
use_stacked_trace: False
data_dir: 'processed'
pickfile_extension: '_autopylot'
dt_stacking: [250, 250]
# filter for first correlation (rough)
filter_options:
freqmax: 0.5
freqmin: 0.03
# filter for second correlation (fine)
filter_options_final:
freqmax: 0.5
freqmin: 0.03
filter_type: bandpass
sampfreq: 20.0
# S-phase
S:
min_corr_stacking: 0.7
min_corr_export: 0.6
min_stack: 20
t_before: 60.
t_after: 60.
cc_maxlag: 100.
cc_maxlag2: 25.
initial_pick_outlier_threshold: 30.
export_threshold: 5.0
min_picks_export: 200
min_picks_autopylot: 50
check_RMS: True
use_taupy_onsets: False
station_list: ['HU.MORH','HU.TIH', 'OX.FUSE', 'OX.BAD']
use_stacked_trace: False
data_dir: 'processed'
pickfile_extension: '_autopylot'
dt_stacking: [250, 250]
# filter for first correlation (rough)
filter_options:
freqmax: 0.1
freqmin: 0.01
# filter for second correlation (fine)
filter_options_final:
freqmax: 0.2
freqmin: 0.01
filter_type: bandpass
sampfreq: 20.0

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@ -0,0 +1,40 @@
#!/bin/bash
#ulimit -s 8192
#ulimit -v $(ulimit -v | awk '{printf("%d",$1*0.95)}')
#ulimit -v
#655360
source /opt/anaconda3/etc/profile.d/conda.sh
conda activate pylot_311
NSLOTS=20
#qsub -l low -cwd -l "os=*stretch" -pe smp 40 submit_pick_corr_correction.sh
#$ -l low
#$ -l h_vmem=6G
#$ -cwd
#$ -pe smp 20
#$ -N corr_pick
export PYTHONPATH="$PYTHONPATH:/home/marcel/git/pylot_tools/"
export PYTHONPATH="$PYTHONPATH:/home/marcel/git/"
export PYTHONPATH="$PYTHONPATH:/home/marcel/git/pylot/"
#export MKL_NUM_THREADS=${NSLOTS:=1}
#export NUMEXPR_NUM_THREADS=${NSLOTS:=1}
#export OMP_NUM_THREADS=${NSLOTS:=1}
#python pick_correlation_correction.py '/data/AlpArray_Data/dmt_database_mantle_M5.8-6.0' '/home/marcel/.pylot/pylot_alparray_mantle_corr_stack_0.03-0.5.in' -pd -n ${NSLOTS:=1} -istart 0 -istop 100
#python pick_correlation_correction.py '/data/AlpArray_Data/dmt_database_mantle_M5.8-6.0' '/home/marcel/.pylot/pylot_alparray_mantle_corr_stack_0.03-0.5.in' -pd -n ${NSLOTS:=1} -istart 100 -istop 200
#python pick_correlation_correction.py '/data/AlpArray_Data/dmt_database_mantle_M6.0-6.5' '/home/marcel/.pylot/pylot_alparray_mantle_corr_stack_0.03-0.5.in' -pd -n ${NSLOTS:=1} -istart 0 -istop 100
#python pick_correlation_correction.py '/data/AlpArray_Data/dmt_database_mantle_M5.8-6.0' '/home/marcel/.pylot/pylot_alparray_mantle_corr_stack_0.03-0.5.in' -pd -n ${NSLOTS:=1} -istart 100 -istop 200
#python pick_correlation_correction.py 'H:\sciebo\dmt_database' 'H:\Sciebo\dmt_database\pylot_alparray_mantle_corr_S_0.01-0.2.in' -pd -n 4 -t
pylot_infile='/home/marcel/.pylot/pylot_alparray_syn_fwi_mk6_it3.in'
#pylot_infile='/home/marcel/.pylot/pylot_adriaarray_corr_P_and_S.in'
# THIS SCRIPT SHOLD BE CALLED BY "submit_to_grid_engine.py" using the following line:
python pick_correlation_correction.py $1 $pylot_infile -pd -n ${NSLOTS:=1} -istart $2 --params 'parameters_fwi_mk6_it3.yaml'
#--event_blacklist eventlist.txt

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@ -0,0 +1,23 @@
#!/usr/bin/env python
import subprocess
fnames = [
('/data/AlpArray_Data/dmt_database_synth_model_mk6_it3_no_rotation', 0),
]
#fnames = [('/data/AlpArray_Data/dmt_database_mantle_0.01-0.2_SKS-phase', 0),
# ('/data/AlpArray_Data/dmt_database_mantle_0.01-0.2_S-phase', 0),]
####
script_location = '/home/marcel/VersionCtrl/git/code_base/correlation_picker/submit_pick_corr_correction.sh'
####
for fnin, istart in fnames:
input_cmds = f'qsub -q low.q@minos15,low.q@minos14,low.q@minos13,low.q@minos12,low.q@minos11 {script_location} {fnin} {istart}'
print(input_cmds)
print(subprocess.check_output(input_cmds.split()))

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@ -0,0 +1,61 @@
#!/usr/bin/env python
# -*- coding: utf-8 -*-
import os
import glob
import json
from obspy import read_events
from pylot.core.util.dataprocessing import Metadata
from pylot.core.util.obspyDMT_interface import qml_from_obspyDMT
def get_event_obspy_dmt(eventdir):
event_pkl_file = os.path.join(eventdir, 'info', 'event.pkl')
if not os.path.exists(event_pkl_file):
raise IOError('Could not find event path for event: {}'.format(eventdir))
event = qml_from_obspyDMT(event_pkl_file)
return event
def get_event_pylot(eventdir, extension=''):
event_id = get_event_id(eventdir)
filename = os.path.join(eventdir, 'PyLoT_{}{}.xml'.format(event_id, extension))
if not os.path.isfile(filename):
return
cat = read_events(filename)
return cat[0]
def get_event_id(eventdir):
event_id = os.path.split(eventdir)[-1]
return event_id
def get_picks(eventdir, extension=''):
event_id = get_event_id(eventdir)
filename = 'PyLoT_{}{}.xml'
filename = filename.format(event_id, extension)
fpath = os.path.join(eventdir, filename)
fpaths = glob.glob(fpath)
if len(fpaths) == 1:
cat = read_events(fpaths[0])
picks = cat[0].picks
return picks
elif len(fpaths) == 0:
print('get_picks: File not found: {}'.format(fpath))
return
print(f'WARNING: Ambiguous pick file specification. Found the following pick files {fpaths}\nFilemask: {fpath}')
return
def write_json(object, fname):
with open(fname, 'w') as outfile:
json.dump(object, outfile, sort_keys=True, indent=4)
def get_metadata(eventdir):
metadata_path = os.path.join(eventdir, 'resp')
metadata = Metadata(inventory=metadata_path, verbosity=0)
return metadata

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@ -0,0 +1,76 @@
import pytest
from obspy import read, Trace, UTCDateTime
from pylot.correlation.pick_correlation_correction import XCorrPickCorrection
class TestXCorrPickCorrection():
def setup(self):
self.make_test_traces()
self.make_test_picks()
self.t_before = 2.
self.t_after = 2.
self.cc_maxlag = 0.5
def make_test_traces(self):
# take first trace of test Stream from obspy
tr1 = read()[0]
# filter trace
tr1.filter('bandpass', freqmin=1, freqmax=20)
# make a copy and shift the copy by 0.1 s
tr2 = tr1.copy()
tr2.stats.starttime += 0.1
self.trace1 = tr1
self.trace2 = tr2
def make_test_picks(self):
# create an artificial reference pick on reference trace (trace1) and another one on the 0.1 s shifted trace
self.tpick1 = UTCDateTime('2009-08-24T00:20:07.7')
# shift the second pick by 0.2 s, the correction should be around 0.1 s now
self.tpick2 = self.tpick1 + 0.2
def test_slice_trace_okay(self):
self.setup()
xcpc = XCorrPickCorrection(UTCDateTime(), Trace(), UTCDateTime(), Trace(),
t_before=self.t_before, t_after=self.t_after, cc_maxlag=self.cc_maxlag)
test_trace = self.trace1
pick_time = self.tpick2
sliced_trace = xcpc.slice_trace(test_trace, pick_time)
assert ((sliced_trace.stats.starttime == pick_time - self.t_before - self.cc_maxlag / 2)
and (sliced_trace.stats.endtime == pick_time + self.t_after + self.cc_maxlag / 2))
def test_slice_trace_fails(self):
self.setup()
test_trace = self.trace1
pick_time = self.tpick1
with pytest.raises(ValueError):
xcpc = XCorrPickCorrection(UTCDateTime(), Trace(), UTCDateTime(), Trace(),
t_before=self.t_before + 20, t_after=self.t_after, cc_maxlag=self.cc_maxlag)
xcpc.slice_trace(test_trace, pick_time)
with pytest.raises(ValueError):
xcpc = XCorrPickCorrection(UTCDateTime(), Trace(), UTCDateTime(), Trace(),
t_before=self.t_before, t_after=self.t_after + 50, cc_maxlag=self.cc_maxlag)
xcpc.slice_trace(test_trace, pick_time)
def test_cross_correlation(self):
self.setup()
# create XCorrPickCorrection object
xcpc = XCorrPickCorrection(self.tpick1, self.trace1, self.tpick2, self.trace2, t_before=self.t_before,
t_after=self.t_after, cc_maxlag=self.cc_maxlag)
# execute correlation
correction, cc_max, uncert, fwfm = xcpc.cross_correlation(False, '', '')
# define awaited test result
test_result = (-0.09983091718314982, 0.9578431835689154, 0.0015285160561610929, 0.03625786256084631)
# check results
assert pytest.approx(test_result, rel=1e-6) == (correction, cc_max, uncert, fwfm)