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41c9183be3
...
ae6c4966a9
2
PyLoT.py
2
PyLoT.py
@ -2196,7 +2196,6 @@ class MainWindow(QMainWindow):
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if event.pylot_autopicks:
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self.drawPicks(picktype='auto')
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if event.pylot_picks or event.pylot_autopicks:
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if not self._inputs.get('extent') == 'global':
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self.locateEventAction.setEnabled(True)
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self.qualities_action.setEnabled(True)
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self.eventlist_xml_action.setEnabled(True)
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@ -2632,6 +2631,7 @@ class MainWindow(QMainWindow):
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picks=self.getPicksOnStation(station, 'manual'),
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autopicks=self.getPicksOnStation(station, 'auto'),
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metadata=self.metadata, event=event,
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model=self.inputs.get('taup_model'),
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filteroptions=self.filteroptions, wftype=wftype,
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show_comp_data=self.dataPlot.comp_checkbox.isChecked())
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if self.filterActionP.isChecked():
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@ -9,7 +9,7 @@ PyLoT - the Python picking and Localization Tool
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This python library contains a graphical user interfaces for picking
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seismic phases. This software needs ObsPy (http://github.com/obspy/obspy/wiki)
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and the Qt libraries to be installed first.
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and the Qt4 libraries to be installed first.
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PILOT has been developed in Mathworks' MatLab. In order to distribute
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PILOT without facing portability problems, it has been decided to re-
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@ -501,7 +501,7 @@ defaults = {'datapath': {'type': str,
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'taup_model': {'type': str,
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'tooltip': 'Define TauPy model for traveltime estimation. Possible values: 1066a, 1066b, ak135, ak135f, herrin, iasp91, jb, prem, pwdk, sp6',
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'value': 'iasp91',
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'value': None,
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'namestring': 'TauPy model'},
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'taup_phases': {'type': str,
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@ -21,7 +21,6 @@ try:
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from scipy.signal import tukey
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except ImportError:
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from scipy.signal.windows import tukey
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from obspy.core import Stream
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from pylot.core.pick.utils import PickingFailedException
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@ -521,6 +521,7 @@ class Array_map(QtWidgets.QWidget):
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picks=self._parent.get_current_event().getPick(station),
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autopicks=self._parent.get_current_event().getAutopick(station),
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filteroptions=self._parent.filteroptions, metadata=self.metadata,
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model=self.parameter.get('taup_model'),
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event=pyl_mw.get_current_event())
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except Exception as e:
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message = 'Could not generate Plot for station {st}.\n {er}'.format(st=station, er=e)
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@ -1871,14 +1871,13 @@ class PickDlg(QDialog):
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def __init__(self, parent=None, data=None, data_compare=None, station=None, network=None, location=None, picks=None,
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autopicks=None, rotate=False, parameter=None, embedded=False, metadata=None, show_comp_data=False,
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event=None, filteroptions=None, wftype=None):
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event=None, filteroptions=None, model=None, wftype=None):
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super(PickDlg, self).__init__(parent, Qt.Window)
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self.orig_parent = parent
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self.setAttribute(Qt.WA_DeleteOnClose)
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# initialize attributes
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self.parameter = parameter
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model = self.parameter.get('taup_model')
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self._embedded = embedded
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self.showCompData = show_comp_data
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self.station = station
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@ -2271,8 +2270,8 @@ class PickDlg(QDialog):
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arrivals = func[plot](source_origin.depth,
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source_origin.latitude,
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source_origin.longitude,
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station_coords.get('latitude'),
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station_coords.get('longitude'),
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station_coords['latitude'],
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station_coords['longitude'],
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phases)
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self.arrivals = arrivals
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@ -1,2 +0,0 @@
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# -*- coding: utf-8 -*-
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#
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@ -1,90 +0,0 @@
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############################# correlation parameters #####################################
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# min_corr_stacking: minimum correlation coefficient for building beam trace
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# min_corr_export: minimum correlation coefficient for pick export
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# min_stack: minimum number of stations for building beam trace
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# t_before: correlation window before pick
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# t_after: correlation window after pick#
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# cc_maxlag: maximum shift for initial correlation
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# cc_maxlag2: maximum shift for second (final) correlation (also for calculating pick uncertainty)
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# initial_pick_outlier_threshold: (hopefully) threshold for excluding large outliers of initial (AIC) picks
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# export_threshold: automatically exclude all onsets which deviate more than this threshold from corrected taup onsets
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# min_picks_export: minimum number of correlated picks for export
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# min_picks_autopylot: minimum number of reference autopicks picks to continue with event
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# check_RMS: do RMS check to search for restitution errors (very experimental)
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# use_taupy_onsets: use taupy onsets as reference picks instead of external picks
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# station_list: use the following stations as reference for stacking
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# use_stacked_trace: use existing stacked trace if found (spare re-computation)
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# data_dir: obspyDMT data subdirectory (e.g. 'raw', 'processed')
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# pickfile_extension: use quakeML files (PyLoT output) with the following extension, e.g. '_autopylot' for pickfiles
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# such as 'PyLoT_20170501_141822_autopylot.xml'
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logging: info
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pick_phases: ['P', 'S']
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# P-phase
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P:
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min_corr_stacking: 0.8
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min_corr_export: 0.6
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min_stack: 20
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t_before: 30.
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t_after: 50.
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cc_maxlag: 50.
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cc_maxlag2: 5.
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initial_pick_outlier_threshold: 30.
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export_threshold: 2.5
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min_picks_export: 100
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min_picks_autopylot: 50
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check_RMS: True
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use_taupy_onsets: False
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station_list: ['HU.MORH', 'HU.TIH', 'OX.FUSE', 'OX.BAD']
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use_stacked_trace: False
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data_dir: 'processed'
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pickfile_extension: '_autopylot'
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dt_stacking: [250, 250]
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# filter for first correlation (rough)
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filter_options:
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freqmax: 0.5
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freqmin: 0.03
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# filter for second correlation (fine)
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filter_options_final:
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freqmax: 0.5
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freqmin: 0.03
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filter_type: bandpass
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sampfreq: 20.0
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# S-phase
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S:
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min_corr_stacking: 0.7
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min_corr_export: 0.6
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min_stack: 20
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t_before: 60.
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t_after: 60.
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cc_maxlag: 100.
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cc_maxlag2: 25.
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initial_pick_outlier_threshold: 30.
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export_threshold: 5.0
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min_picks_export: 200
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min_picks_autopylot: 50
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check_RMS: True
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use_taupy_onsets: False
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station_list: ['HU.MORH','HU.TIH', 'OX.FUSE', 'OX.BAD']
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use_stacked_trace: False
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data_dir: 'processed'
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pickfile_extension: '_autopylot'
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dt_stacking: [250, 250]
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# filter for first correlation (rough)
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filter_options:
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freqmax: 0.1
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freqmin: 0.01
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# filter for second correlation (fine)
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filter_options_final:
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freqmax: 0.2
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freqmin: 0.01
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filter_type: bandpass
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sampfreq: 20.0
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File diff suppressed because it is too large
Load Diff
@ -1,40 +0,0 @@
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#!/bin/bash
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#ulimit -s 8192
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#ulimit -v $(ulimit -v | awk '{printf("%d",$1*0.95)}')
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#ulimit -v
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#655360
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source /opt/anaconda3/etc/profile.d/conda.sh
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conda activate pylot_311
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NSLOTS=20
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#qsub -l low -cwd -l "os=*stretch" -pe smp 40 submit_pick_corr_correction.sh
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#$ -l low
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#$ -l h_vmem=6G
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#$ -cwd
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#$ -pe smp 20
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#$ -N corr_pick
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export PYTHONPATH="$PYTHONPATH:/home/marcel/git/pylot_tools/"
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export PYTHONPATH="$PYTHONPATH:/home/marcel/git/"
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export PYTHONPATH="$PYTHONPATH:/home/marcel/git/pylot/"
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#export MKL_NUM_THREADS=${NSLOTS:=1}
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#export NUMEXPR_NUM_THREADS=${NSLOTS:=1}
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#export OMP_NUM_THREADS=${NSLOTS:=1}
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#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
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#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
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#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
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#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
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#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
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pylot_infile='/home/marcel/.pylot/pylot_alparray_syn_fwi_mk6_it3.in'
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#pylot_infile='/home/marcel/.pylot/pylot_adriaarray_corr_P_and_S.in'
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# THIS SCRIPT SHOLD BE CALLED BY "submit_to_grid_engine.py" using the following line:
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python pick_correlation_correction.py $1 $pylot_infile -pd -n ${NSLOTS:=1} -istart $2 --params 'parameters_fwi_mk6_it3.yaml'
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#--event_blacklist eventlist.txt
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@ -1,23 +0,0 @@
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#!/usr/bin/env python
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import subprocess
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fnames = [
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('/data/AlpArray_Data/dmt_database_synth_model_mk6_it3_no_rotation', 0),
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]
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#fnames = [('/data/AlpArray_Data/dmt_database_mantle_0.01-0.2_SKS-phase', 0),
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# ('/data/AlpArray_Data/dmt_database_mantle_0.01-0.2_S-phase', 0),]
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####
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script_location = '/home/marcel/VersionCtrl/git/code_base/correlation_picker/submit_pick_corr_correction.sh'
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####
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for fnin, istart in fnames:
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input_cmds = f'qsub -q low.q@minos15,low.q@minos14,low.q@minos13,low.q@minos12,low.q@minos11 {script_location} {fnin} {istart}'
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print(input_cmds)
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print(subprocess.check_output(input_cmds.split()))
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@ -1,61 +0,0 @@
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#!/usr/bin/env python
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# -*- coding: utf-8 -*-
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import os
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import glob
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import json
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from obspy import read_events
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from pylot.core.util.dataprocessing import Metadata
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from pylot.core.util.obspyDMT_interface import qml_from_obspyDMT
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def get_event_obspy_dmt(eventdir):
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event_pkl_file = os.path.join(eventdir, 'info', 'event.pkl')
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if not os.path.exists(event_pkl_file):
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raise IOError('Could not find event path for event: {}'.format(eventdir))
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event = qml_from_obspyDMT(event_pkl_file)
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return event
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def get_event_pylot(eventdir, extension=''):
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event_id = get_event_id(eventdir)
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filename = os.path.join(eventdir, 'PyLoT_{}{}.xml'.format(event_id, extension))
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if not os.path.isfile(filename):
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return
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cat = read_events(filename)
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return cat[0]
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def get_event_id(eventdir):
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event_id = os.path.split(eventdir)[-1]
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return event_id
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def get_picks(eventdir, extension=''):
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event_id = get_event_id(eventdir)
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filename = 'PyLoT_{}{}.xml'
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filename = filename.format(event_id, extension)
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fpath = os.path.join(eventdir, filename)
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fpaths = glob.glob(fpath)
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if len(fpaths) == 1:
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cat = read_events(fpaths[0])
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picks = cat[0].picks
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return picks
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elif len(fpaths) == 0:
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print('get_picks: File not found: {}'.format(fpath))
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return
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print(f'WARNING: Ambiguous pick file specification. Found the following pick files {fpaths}\nFilemask: {fpath}')
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return
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def write_json(object, fname):
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with open(fname, 'w') as outfile:
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json.dump(object, outfile, sort_keys=True, indent=4)
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def get_metadata(eventdir):
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metadata_path = os.path.join(eventdir, 'resp')
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metadata = Metadata(inventory=metadata_path, verbosity=0)
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return metadata
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@ -1,76 +0,0 @@
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import pytest
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from obspy import read, Trace, UTCDateTime
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from pylot.correlation.pick_correlation_correction import XCorrPickCorrection
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class TestXCorrPickCorrection():
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def setup(self):
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self.make_test_traces()
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self.make_test_picks()
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self.t_before = 2.
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self.t_after = 2.
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self.cc_maxlag = 0.5
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def make_test_traces(self):
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# take first trace of test Stream from obspy
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tr1 = read()[0]
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# filter trace
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tr1.filter('bandpass', freqmin=1, freqmax=20)
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# make a copy and shift the copy by 0.1 s
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tr2 = tr1.copy()
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tr2.stats.starttime += 0.1
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self.trace1 = tr1
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self.trace2 = tr2
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def make_test_picks(self):
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# create an artificial reference pick on reference trace (trace1) and another one on the 0.1 s shifted trace
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self.tpick1 = UTCDateTime('2009-08-24T00:20:07.7')
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# shift the second pick by 0.2 s, the correction should be around 0.1 s now
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self.tpick2 = self.tpick1 + 0.2
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def test_slice_trace_okay(self):
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self.setup()
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xcpc = XCorrPickCorrection(UTCDateTime(), Trace(), UTCDateTime(), Trace(),
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t_before=self.t_before, t_after=self.t_after, cc_maxlag=self.cc_maxlag)
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test_trace = self.trace1
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pick_time = self.tpick2
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sliced_trace = xcpc.slice_trace(test_trace, pick_time)
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assert ((sliced_trace.stats.starttime == pick_time - self.t_before - self.cc_maxlag / 2)
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and (sliced_trace.stats.endtime == pick_time + self.t_after + self.cc_maxlag / 2))
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def test_slice_trace_fails(self):
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self.setup()
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test_trace = self.trace1
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pick_time = self.tpick1
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with pytest.raises(ValueError):
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xcpc = XCorrPickCorrection(UTCDateTime(), Trace(), UTCDateTime(), Trace(),
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t_before=self.t_before + 20, t_after=self.t_after, cc_maxlag=self.cc_maxlag)
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xcpc.slice_trace(test_trace, pick_time)
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with pytest.raises(ValueError):
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xcpc = XCorrPickCorrection(UTCDateTime(), Trace(), UTCDateTime(), Trace(),
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t_before=self.t_before, t_after=self.t_after + 50, cc_maxlag=self.cc_maxlag)
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xcpc.slice_trace(test_trace, pick_time)
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def test_cross_correlation(self):
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self.setup()
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# create XCorrPickCorrection object
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xcpc = XCorrPickCorrection(self.tpick1, self.trace1, self.tpick2, self.trace2, t_before=self.t_before,
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t_after=self.t_after, cc_maxlag=self.cc_maxlag)
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# execute correlation
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correction, cc_max, uncert, fwfm = xcpc.cross_correlation(False, '', '')
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# define awaited test result
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test_result = (-0.09983091718314982, 0.9578431835689154, 0.0015285160561610929, 0.03625786256084631)
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# check results
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assert pytest.approx(test_result, rel=1e-6) == (correction, cc_max, uncert, fwfm)
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