33 Commits

Author SHA1 Message Date
9333ebf7f3 [update] deactivate Spectrogram tab features in main branch 2024-09-12 16:58:27 +02:00
8c46b1ed18 [update] README.md 2024-09-12 16:54:39 +02:00
c743813446 Merge branch 'refs/heads/develop'
# Conflicts:
#	PyLoT.py
#	README.md
#	pylot/core/util/widgets.py
2024-09-12 16:32:15 +02:00
41c9183be3 Merge branch 'refs/heads/correlation_picker' into develop 2024-09-12 16:24:50 +02:00
28f75cedcb Merge branch 'refs/heads/develop' into correlation_picker 2024-09-11 10:31:50 +02:00
424d42aa1c Merge branch 'refs/heads/develop' into correlation_picker
# Conflicts:
#	pylot/core/pick/charfuns.py
#	tests/test_autopicker/pylot_alparray_mantle_corr_stack_0.03-0.5.in
#	tests/test_autopicker/test_autopylot.py
2024-08-29 16:37:15 +02:00
2cea10088d [update] added test for AutoPyLoT, added test files for correlation picker as well 2024-08-29 16:35:04 +02:00
466f19eb2e [bugfix] fixed import for tukey in newer scipy versions 2024-08-28 18:01:03 +02:00
5d90904838 Merge branch 'develop' into correlation_picker 2024-08-27 17:46:21 +02:00
29107ee40c [update] WIP: adding tests for autopylot (global) 2024-08-26 17:18:41 +02:00
db11e125c0 [todos] add todos 2024-08-09 16:53:21 +02:00
b59232d77b [bugfix] function name accidentally overwritten on parameter renaming 2024-08-09 16:52:57 +02:00
176e93d833 [refactor] finished annotations (type hints) 2024-08-09 16:52:32 +02:00
759e7bb848 [bugfix] partially reverted signature of an inner function with shadowed variable name
[refactor] minor
2024-08-09 16:24:40 +02:00
61c3f40063 Merge branch 'develop' into correlation_picker 2024-08-09 15:50:46 +02:00
67f34cc871 Merge branch 'develop' into correlation_picker
# Conflicts:
#	pylot.yml
#	requirements.txt
2024-08-09 15:05:30 +02:00
f4f48a930f [refactor] moved unittest to existing test folder 2024-08-09 15:03:55 +02:00
a068bb8457 [update] refactoring, added type hints 2024-08-08 16:49:15 +02:00
452f2a2e18 [bugfix] test raised different Exception than planned 2024-08-08 14:41:16 +02:00
c3a2ef5022 [minor] changed test to be approximately equal to test result on different machine 2024-08-08 11:28:10 +02:00
8e7bd87711 [new] added some unit tests for correlation picker (WIP) 2024-08-07 17:11:27 +02:00
d5817adc46 [merge] changes to correlation picker from different machines that were not committed 2024-08-07 10:17:35 +02:00
14f01ec46d Merge branch 'correlation_picker' of git.geophysik.ruhr-uni-bochum.de:marcel/pylot into correlation_picker 2024-08-07 10:08:57 +02:00
1b074d14ff [update] WIP: Adding type hints, docstrings etc. 2024-08-06 16:03:50 +02:00
ce71c549ca [bugfix] removed parameter that was re-introduced accidentally from manual merge 2024-08-06 16:03:16 +02:00
c4220b389e Merge branch 'correlation_picker' of git.geophysik.ruhr-uni-bochum.de:marcel/pylot into correlation_picker 2024-07-25 15:36:06 +02:00
0f29d0e20d [minor] small modifications (naming conventions) 2024-07-25 14:50:40 +02:00
cdcd226c87 [initial] adding files from correlation picker 2024-07-24 14:07:13 +02:00
710ea57503 Merge branch 'github-master' 2017-09-25 15:50:38 +02:00
8aaad643ec release version 0.2
release notes:
==============
Features:
- centralize all functionalities of PyLoT and control them from within the main GUI
- handling multiple events inside GUI with project files (save and load work progress)
- GUI based adjustments of pick parameters and I/O
- interactive tuning of parameters from within the GUI
- call automatic picking algorithm from within the GUI
- comparison of automatic with manual picks for multiple events using clear differentiation of manual picks into 'tune' and 'test-set' (beta)
- manual picking of different (user defined) phase types
- phase onset estimation with ObsPy TauPy

- interactive zoom/scale functionalities in all plots (mousewheel, pan, pan-zoom)
- array map to visualize stations and control onsets (beta feature, switch to manual picks not implemented)

Platform support:
- python 3 support
- Windows support

Performance:
- multiprocessing for automatic picking and restitution of multiple stations
- use pyqtgraph library for better performance on main waveform plot

Visualization:
- pick uncertainty (quality classes) visualization with gradients
- pick color unification for all plots
- new icons and stylesheets

Known Issues:
2017-09-25 14:24:52 +02:00
bc808b66c2 [update] README.md 2017-09-25 10:17:58 +02:00
472e5b3b9e Merge branch 'develop' 2017-09-21 16:18:53 +02:00
Marc S. Boxberg
503ea419c4 release version: 0.1a
release notes:
==============
Features
- consistent manual phase picking through predefined SNR dependant zoom level
- uniform uncertainty estimation from waveform's properties for automatic and manual picks
- pdf representation and comparison of picks taking the uncertainty intrinsically into account
- Richter and moment magnitude estimation
- location determination with external installation of [NonLinLoc](http://alomax.free.fr/nlloc/index.html)
Known issues
- Magnitude estimation from manual PyLoT takes some time (instrument correction)
2016-10-04 09:38:05 +02:00
14 changed files with 2295 additions and 33 deletions

8
PyLoT.py Executable file → Normal file
View File

@@ -716,14 +716,14 @@ class MainWindow(QMainWindow):
self.tabs.addTab(wf_tab, 'Waveform Plot')
self.tabs.addTab(array_tab, 'Array Map')
self.tabs.addTab(events_tab, 'Eventlist')
self.tabs.addTab(spectro_tab, 'Spectro')
#self.tabs.addTab(spectro_tab, 'Spectro')
self.wf_layout.addWidget(self.no_data_label)
self.wf_layout.addWidget(self.wf_scroll_area)
self.wf_scroll_area.setWidgetResizable(True)
self.init_array_tab()
self.init_event_table()
self.init_spectro_tab()
#self.init_spectro_tab()
self.tabs.setCurrentIndex(0)
self.eventLabel = QLabel()
@@ -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():

View File

@@ -54,33 +54,14 @@ In order to run PyLoT you need to install:
#### Some handwork:
PyLoT needs a properties folder on your system to work. It should be situated in your home directory
(on Windows usually C:/Users/*username*):
mkdir ~/.pylot
In the next step you have to copy some files to this directory:
*for local distance seismicity*
cp path-to-pylot/inputs/pylot_local.in ~/.pylot/pylot.in
*for regional distance seismicity*
cp path-to-pylot/inputs/pylot_regional.in ~/.pylot/pylot.in
*for global distance seismicity*
cp path-to-pylot/inputs/pylot_global.in ~/.pylot/pylot.in
and some extra information on error estimates (just needed for reading old PILOT data) and the Richter magnitude scaling
Some extra information on error estimates (just needed for reading old PILOT data) and the Richter magnitude scaling
relation
cp path-to-pylot/inputs/PILOT_TimeErrors.in path-to-pylot/inputs/richter_scaling.data ~/.pylot/
You may need to do some modifications to these files. Especially folder names should be reviewed.
PyLoT has been tested on Mac OSX (10.11), Debian Linux 8 and on Windows 10.
PyLoT has been tested on Mac OSX (10.11), Debian Linux 8 and on Windows 10/11.
## Release notes
@@ -89,6 +70,7 @@ PyLoT has been tested on Mac OSX (10.11), Debian Linux 8 and on Windows 10.
- event organisation in project files and waveform visualisation
- consistent manual phase picking through predefined SNR dependant zoom level
- consistent automatic phase picking routines using Higher Order Statistics, AIC and Autoregression
- pick correlation correction for teleseismic waveforms
- interactive tuning of auto-pick parameters
- uniform uncertainty estimation from waveform's properties for automatic and manual picks
- pdf representation and comparison of picks taking the uncertainty intrinsically into account
@@ -97,7 +79,7 @@ PyLoT has been tested on Mac OSX (10.11), Debian Linux 8 and on Windows 10.
#### Known issues:
We hope to solve these with the next release.
Current release is still in development progress and has several issues. We are currently lacking manpower, but hope to assess many of the issues in the near future.
## Staff
@@ -110,4 +92,4 @@ Others: A. Bruestle, T. Meier, W. Friederich
[ObsPy]: http://github.com/obspy/obspy/wiki
August 2024
September 2024

View File

@@ -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-

View File

@@ -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,

View File

@@ -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

View File

@@ -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)

View File

@@ -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

File diff suppressed because it is too large Load Diff

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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)