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[reformat] code reformatting with PyCharm

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Marcel Paffrath 2017-08-03 09:41:54 +02:00
parent 4107f0249d
commit 20b31a1c5c
49 changed files with 3255 additions and 3194 deletions
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31
QtPyLoT.py
View File

@ -23,10 +23,11 @@ https://www.iconfinder.com/iconsets/flavour
(http://www.gnu.org/copyleft/lesser.html) (http://www.gnu.org/copyleft/lesser.html)
""" """
import os
import sys
import platform
import argparse import argparse
import os
import platform
import sys
import matplotlib import matplotlib
matplotlib.use('Qt4Agg') matplotlib.use('Qt4Agg')
@ -66,10 +67,10 @@ from pylot.core.pick.compare import Comparison
from pylot.core.pick.utils import symmetrize_error from pylot.core.pick.utils import symmetrize_error
from pylot.core.io.phases import picksdict_from_picks from pylot.core.io.phases import picksdict_from_picks
import pylot.core.loc.nll as nll import pylot.core.loc.nll as nll
from pylot.core.util.defaults import FILTERDEFAULTS, OUTPUTFORMATS, SetChannelComponents, \ from pylot.core.util.defaults import FILTERDEFAULTS, SetChannelComponents, \
readFilterInformation readFilterInformation
from pylot.core.util.errors import FormatError, DatastructureError, \ from pylot.core.util.errors import FormatError, DatastructureError, \
OverwriteError, ProcessingError OverwriteError
from pylot.core.util.connection import checkurl from pylot.core.util.connection import checkurl
from pylot.core.util.dataprocessing import read_metadata, restitute_data from pylot.core.util.dataprocessing import read_metadata, restitute_data
from pylot.core.util.utils import fnConstructor, getLogin, \ from pylot.core.util.utils import fnConstructor, getLogin, \
@ -81,7 +82,7 @@ from pylot.core.util.widgets import FilterOptionsDialog, NewEventDlg, \
getDataType, ComparisonDialog, TuneAutopicker, PylotParaBox getDataType, ComparisonDialog, TuneAutopicker, PylotParaBox
from pylot.core.util.map_projection import map_projection from pylot.core.util.map_projection import map_projection
from pylot.core.util.structure import DATASTRUCTURE from pylot.core.util.structure import DATASTRUCTURE
from pylot.core.util.thread import AutoPickThread, Thread, Worker from pylot.core.util.thread import Thread, Worker
from pylot.core.util.version import get_git_version as _getVersionString from pylot.core.util.version import get_git_version as _getVersionString
if sys.version_info.major == 3: if sys.version_info.major == 3:
@ -270,7 +271,7 @@ class MainWindow(QMainWindow):
quitIcon = self.style().standardIcon(QStyle.SP_MediaStop) quitIcon = self.style().standardIcon(QStyle.SP_MediaStop)
helpIcon = self.style().standardIcon(QStyle.SP_DialogHelpButton) helpIcon = self.style().standardIcon(QStyle.SP_DialogHelpButton)
newFolderIcon = self.style().standardIcon(QStyle.SP_FileDialogNewFolder) newFolderIcon = self.style().standardIcon(QStyle.SP_FileDialogNewFolder)
# create resource icons # create resource icons
newIcon = QIcon() newIcon = QIcon()
newIcon.addPixmap(QPixmap(':/icons/newfile.png')) newIcon.addPixmap(QPixmap(':/icons/newfile.png'))
@ -1149,8 +1150,8 @@ class MainWindow(QMainWindow):
# return False # return False
# export to given path # export to given path
#self.get_data().exportEvent(fbasename, exform, upperErrors=[uppererrorP[3], uppererrorS[3]]) # self.get_data().exportEvent(fbasename, exform, upperErrors=[uppererrorP[3], uppererrorS[3]])
#try: # try:
self.get_data().exportEvent(fbasename, exform[0], fcheck=fcheck, self.get_data().exportEvent(fbasename, exform[0], fcheck=fcheck,
upperErrors=[uppererrorP[3], uppererrorS[3]]) upperErrors=[uppererrorP[3], uppererrorS[3]])
self.get_data().exportEvent(fbasename, exform[1], fcheck=fcheck, self.get_data().exportEvent(fbasename, exform[1], fcheck=fcheck,
@ -1159,7 +1160,7 @@ class MainWindow(QMainWindow):
# QMessageBox.warning(self, "PyLoT Warning", # QMessageBox.warning(self, "PyLoT Warning",
# "Could not save event: {}".format(e)) # "Could not save event: {}".format(e))
# return # return
#self.get_data().exportEvent(fbasename, exform[2], upperErrors=[uppererrorP[3], uppererrorS[3]]) # self.get_data().exportEvent(fbasename, exform[2], upperErrors=[uppererrorP[3], uppererrorS[3]])
# all files save (ui clean) # all files save (ui clean)
self.update_status('Picks saved as %s, %s, and %s' % (fbasename + exform[0], fbasename + exform[1], self.update_status('Picks saved as %s, %s, and %s' % (fbasename + exform[0], fbasename + exform[1],
fbasename + exform[2])) fbasename + exform[2]))
@ -1322,7 +1323,7 @@ class MainWindow(QMainWindow):
if self.tabs.currentIndex() == 2: if self.tabs.currentIndex() == 2:
self.init_event_table() self.init_event_table()
self.refreshRefTestButtons() self.refreshRefTestButtons()
# only refresh first/second tab when an event was changed. # only refresh first/second tab when an event was changed.
if self._eventChanged[0] or self._eventChanged[1]: if self._eventChanged[0] or self._eventChanged[1]:
event = self.get_current_event() event = self.get_current_event()
@ -1888,7 +1889,7 @@ class MainWindow(QMainWindow):
args = {'parameter': self._inputs, args = {'parameter': self._inputs,
'station': 'all', 'station': 'all',
'fnames': 'None', 'fnames': 'None',
'eventid': self.get_current_event_path (), 'eventid': self.get_current_event_path(),
'iplot': 0, 'iplot': 0,
'fig_dict': None, 'fig_dict': None,
'locflag': 0} 'locflag': 0}
@ -1900,7 +1901,7 @@ class MainWindow(QMainWindow):
self.addListItem(str(self._inputs)) self.addListItem(str(self._inputs))
self.mp_worker.signals.message.connect(self.addListItem) self.mp_worker.signals.message.connect(self.addListItem)
#self.mp_thread.finished.connect(self.finalizeAutoPick) # self.mp_thread.finished.connect(self.finalizeAutoPick)
def finalizeAutoPick(self): def finalizeAutoPick(self):
self.drawPicks(picktype='auto') self.drawPicks(picktype='auto')
@ -2348,7 +2349,7 @@ class MainWindow(QMainWindow):
if type(item) == QtGui.QTableWidgetItem: if type(item) == QtGui.QTableWidgetItem:
self.event_table.setItem(r_index, c_index, item) self.event_table.setItem(r_index, c_index, item)
elif type(item) in [QtGui.QWidget, QtGui.QPushButton]: elif type(item) in [QtGui.QWidget, QtGui.QPushButton]:
self.event_table.setCellWidget(r_index, c_index, item) self.event_table.setCellWidget(r_index, c_index, item)
header = self.event_table.horizontalHeader() header = self.event_table.horizontalHeader()
header.setResizeMode(QtGui.QHeaderView.ResizeToContents) header.setResizeMode(QtGui.QHeaderView.ResizeToContents)
@ -2674,7 +2675,7 @@ class Project(object):
if eventID in str(event.resource_id): if eventID in str(event.resource_id):
self.remove_event(event) self.remove_event(event)
break break
def read_eventfile_info(self, filename, separator=','): def read_eventfile_info(self, filename, separator=','):
''' '''
Try to read event information from file (:param:filename) comparing specific event datetimes. Try to read event information from file (:param:filename) comparing specific event datetimes.

65
autoPyLoT.py
View File

@ -4,35 +4,37 @@
from __future__ import print_function from __future__ import print_function
import argparse import argparse
import datetime
import glob import glob
import os import os
import datetime
from obspy import read_events
from obspy.core.event import ResourceIdentifier
import pylot.core.loc.hyposat as hyposat
import pylot.core.loc.hypo71 as hypo71
import pylot.core.loc.velest as velest
import pylot.core.loc.hypodd as hypodd
import pylot.core.loc.focmec as focmec import pylot.core.loc.focmec as focmec
import pylot.core.loc.hash as hash import pylot.core.loc.hash as hash
import pylot.core.loc.hypo71 as hypo71
import pylot.core.loc.hypodd as hypodd
import pylot.core.loc.hyposat as hyposat
import pylot.core.loc.nll as nll import pylot.core.loc.nll as nll
#from PySide.QtGui import QWidget, QInputDialog import pylot.core.loc.velest as velest
from obspy import read_events
from obspy.core.event import ResourceIdentifier
# from PySide.QtGui import QWidget, QInputDialog
from pylot.core.analysis.magnitude import MomentMagnitude, LocalMagnitude from pylot.core.analysis.magnitude import MomentMagnitude, LocalMagnitude
from pylot.core.io.data import Data from pylot.core.io.data import Data
from pylot.core.io.inputs import PylotParameter from pylot.core.io.inputs import PylotParameter
from pylot.core.pick.autopick import autopickevent, iteratepicker from pylot.core.pick.autopick import autopickevent, iteratepicker
from pylot.core.util.dataprocessing import restitute_data, read_metadata, \ from pylot.core.util.dataprocessing import restitute_data, read_metadata, \
remove_underscores remove_underscores
from pylot.core.util.structure import DATASTRUCTURE
from pylot.core.util.version import get_git_version as _getVersionString
from pylot.core.util.event import Event
from pylot.core.util.utils import real_None
from pylot.core.util.defaults import SEPARATOR from pylot.core.util.defaults import SEPARATOR
from pylot.core.util.event import Event
from pylot.core.util.structure import DATASTRUCTURE
from pylot.core.util.utils import real_None
from pylot.core.util.version import get_git_version as _getVersionString
__version__ = _getVersionString() __version__ = _getVersionString()
def autoPyLoT(input_dict=None, parameter=None, inputfile=None, fnames=None, eventid=None, savepath=None, station='all', iplot=0): def autoPyLoT(input_dict=None, parameter=None, inputfile=None, fnames=None, eventid=None, savepath=None, station='all',
iplot=0):
""" """
Determine phase onsets automatically utilizing the automatic picking Determine phase onsets automatically utilizing the automatic picking
algorithms by Kueperkoch et al. 2010/2012. algorithms by Kueperkoch et al. 2010/2012.
@ -108,7 +110,7 @@ def autoPyLoT(input_dict=None, parameter=None, inputfile=None, fnames=None, even
'dbase': parameter.get('database')} 'dbase': parameter.get('database')}
exf = ['root', 'dpath', 'dbase'] exf = ['root', 'dpath', 'dbase']
if parameter['eventID'] is not '*' and fnames == 'None': if parameter['eventID'] is not '*' and fnames == 'None':
dsfields['eventID'] = parameter['eventID'] dsfields['eventID'] = parameter['eventID']
exf.append('eventID') exf.append('eventID')
@ -176,7 +178,7 @@ def autoPyLoT(input_dict=None, parameter=None, inputfile=None, fnames=None, even
events[index] = event events[index] = event
for event in events: for event in events:
pylot_event = Event(event) #event should be path to event directory pylot_event = Event(event) # event should be path to event directory
data.setEvtData(pylot_event) data.setEvtData(pylot_event)
if fnames == 'None': if fnames == 'None':
data.setWFData(glob.glob(os.path.join(datapath, event, '*'))) data.setWFData(glob.glob(os.path.join(datapath, event, '*')))
@ -196,10 +198,10 @@ def autoPyLoT(input_dict=None, parameter=None, inputfile=None, fnames=None, even
parameter.setParam(eventID=eventID) parameter.setParam(eventID=eventID)
else: else:
data.setWFData(fnames) data.setWFData(fnames)
event = events[0] event = events[0]
#now = datetime.datetime.now() # now = datetime.datetime.now()
#evID = '%d%02d%02d%02d%02d' % (now.year, # evID = '%d%02d%02d%02d%02d' % (now.year,
# now.month, # now.month,
# now.day, # now.day,
# now.hour, # now.hour,
@ -210,13 +212,13 @@ def autoPyLoT(input_dict=None, parameter=None, inputfile=None, fnames=None, even
wfdat = wfdat.select(station=station) wfdat = wfdat.select(station=station)
if not wfdat: if not wfdat:
print('Could not find station {}. STOP!'.format(station)) print('Could not find station {}. STOP!'.format(station))
return return
wfdat = remove_underscores(wfdat) wfdat = remove_underscores(wfdat)
metadata = read_metadata(parameter.get('invdir')) metadata = read_metadata(parameter.get('invdir'))
print("Restitute data ...") print("Restitute data ...")
corr_dat = restitute_data(wfdat.copy(), *metadata) corr_dat = restitute_data(wfdat.copy(), *metadata)
if not corr_dat and locflag: if not corr_dat and locflag:
locflag = 2 locflag = 2
print('Working on event %s. Stations: %s' % (event, station)) print('Working on event %s. Stations: %s' % (event, station))
print(wfdat) print(wfdat)
########################################################## ##########################################################
@ -277,12 +279,12 @@ def autoPyLoT(input_dict=None, parameter=None, inputfile=None, fnames=None, even
WAscaling = parameter.get('WAscaling') WAscaling = parameter.get('WAscaling')
magscaling = parameter.get('magscaling') magscaling = parameter.get('magscaling')
local_mag = LocalMagnitude(corr_dat, evt, local_mag = LocalMagnitude(corr_dat, evt,
parameter.get('sstop'), parameter.get('sstop'),
WAscaling, True, iplot) WAscaling, True, iplot)
for station, amplitude in local_mag.amplitudes.items(): for station, amplitude in local_mag.amplitudes.items():
picks[station]['S']['Ao'] = amplitude.generic_amplitude picks[station]['S']['Ao'] = amplitude.generic_amplitude
print("Local station magnitudes scaled with:") print("Local station magnitudes scaled with:")
print("log(Ao) + %f * log(r) + %f * r + %f" % (WAscaling[0], print("log(Ao) + %f * log(r) + %f * r + %f" % (WAscaling[0],
WAscaling[1], WAscaling[1],
WAscaling[2])) WAscaling[2]))
evt = local_mag.updated_event(magscaling) evt = local_mag.updated_event(magscaling)
@ -310,7 +312,8 @@ def autoPyLoT(input_dict=None, parameter=None, inputfile=None, fnames=None, even
if input_dict: if input_dict:
if 'fig_dict' in input_dict: if 'fig_dict' in input_dict:
fig_dict = input_dict['fig_dict'] fig_dict = input_dict['fig_dict']
picks = iteratepicker(wfdat, nllocfile, picks, badpicks, parameter, fig_dict=fig_dict) picks = iteratepicker(wfdat, nllocfile, picks, badpicks, parameter,
fig_dict=fig_dict)
else: else:
picks = iteratepicker(wfdat, nllocfile, picks, badpicks, parameter) picks = iteratepicker(wfdat, nllocfile, picks, badpicks, parameter)
# write phases to NLLoc-phase file # write phases to NLLoc-phase file
@ -349,12 +352,12 @@ def autoPyLoT(input_dict=None, parameter=None, inputfile=None, fnames=None, even
WAscaling = parameter.get('WAscaling') WAscaling = parameter.get('WAscaling')
magscaling = parameter.get('magscaling') magscaling = parameter.get('magscaling')
local_mag = LocalMagnitude(corr_dat, evt, local_mag = LocalMagnitude(corr_dat, evt,
parameter.get('sstop'), parameter.get('sstop'),
WAscaling, True, iplot) WAscaling, True, iplot)
for station, amplitude in local_mag.amplitudes.items(): for station, amplitude in local_mag.amplitudes.items():
picks[station]['S']['Ao'] = amplitude.generic_amplitude picks[station]['S']['Ao'] = amplitude.generic_amplitude
print("Local station magnitudes scaled with:") print("Local station magnitudes scaled with:")
print("log(Ao) + %f * log(r) + %f * r + %f" % (WAscaling[0], print("log(Ao) + %f * log(r) + %f * r + %f" % (WAscaling[0],
WAscaling[1], WAscaling[1],
WAscaling[2])) WAscaling[2]))
evt = local_mag.updated_event(magscaling) evt = local_mag.updated_event(magscaling)
@ -420,16 +423,16 @@ if __name__ == "__main__":
autoregressive prediction and AIC followed by locating the seismic events using autoregressive prediction and AIC followed by locating the seismic events using
NLLoc''') NLLoc''')
#parser.add_argument('-d', '-D', '--input_dict', type=str, # parser.add_argument('-d', '-D', '--input_dict', type=str,
# action='store', # action='store',
# help='''optional, dictionary containing processing parameters''') # help='''optional, dictionary containing processing parameters''')
#parser.add_argument('-p', '-P', '--parameter', type=str, # parser.add_argument('-p', '-P', '--parameter', type=str,
# action='store', # action='store',
# help='''parameter file, default=None''') # help='''parameter file, default=None''')
parser.add_argument('-i', '-I', '--inputfile', type=str, parser.add_argument('-i', '-I', '--inputfile', type=str,
action='store', action='store',
help='''full path to the file containing the input help='''full path to the file containing the input
parameters for autoPyLoT''') parameters for autoPyLoT''')
parser.add_argument('-f', '-F', '--fnames', type=str, parser.add_argument('-f', '-F', '--fnames', type=str,
action='store', action='store',
help='''optional, list of data file names''') help='''optional, list of data file names''')
@ -439,11 +442,11 @@ if __name__ == "__main__":
parser.add_argument('-s', '-S', '--spath', type=str, parser.add_argument('-s', '-S', '--spath', type=str,
action='store', action='store',
help='''optional, save path for autoPyLoT output''') help='''optional, save path for autoPyLoT output''')
#parser.add_argument('-v', '-V', '--version', action='version', # parser.add_argument('-v', '-V', '--version', action='version',
# version='autoPyLoT ' + __version__, # version='autoPyLoT ' + __version__,
# help='show version information and exit') # help='show version information and exit')
cla = parser.parse_args() cla = parser.parse_args()
picks = autoPyLoT(inputfile=str(cla.inputfile), fnames=str(cla.fnames), picks = autoPyLoT(inputfile=str(cla.inputfile), fnames=str(cla.fnames),
eventid=str(cla.eventid), savepath=str(cla.spath)) eventid=str(cla.eventid), savepath=str(cla.spath))

24
help/index.html
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@ -1,17 +1,19 @@
<html><head><title>PyLoT - the Python picking and Localisation Tool</title></head> <html>
<head><title>PyLoT - the Python picking and Localisation Tool</title></head>
<body> <body>
<p><b>PyLoT</b> is a program which is capable of picking seismic phases, <p><b>PyLoT</b> is a program which is capable of picking seismic phases,
exporting these as numerous standard phase format and localize the corresponding exporting these as numerous standard phase format and localize the corresponding
seismic event with external software as, e.g.:</p> seismic event with external software as, e.g.:</p>
<ul type="circle"> <ul type="circle">
<li><a href="http://alomax.free.fr/nlloc/index.html">NonLinLoc</a></li> <li><a href="http://alomax.free.fr/nlloc/index.html">NonLinLoc</a></li>
<li>HypoInvers</li> <li>HypoInvers</li>
<li>HypoSat</li> <li>HypoSat</li>
<li>whatever you want ...</li> <li>whatever you want ...</li>
</ul> </ul>
<p>Read more on the <p>Read more on the
<a href="https://ariadne.geophysik.rub.de/trac/PyLoT/wiki/">PyLoT WikiPage</a>.</p> <a href="https://ariadne.geophysik.rub.de/trac/PyLoT/wiki/">PyLoT WikiPage</a>.</p>
<p>Bug reports are very much appreciated and can also be delivered on our <p>Bug reports are very much appreciated and can also be delivered on our
<a href="https://ariadne.geophysik.rub.de/trac/PyLoT">PyLoT TracPage</a> after <a href="https://ariadne.geophysik.rub.de/trac/PyLoT">PyLoT TracPage</a> after
successful registration.</p> successful registration.</p>
</body></html> </body>
</html>

12
makePyLoT.py
View File

@ -158,12 +158,12 @@ def buildPyLoT(verbosity=None):
def installPyLoT(verbosity=None): def installPyLoT(verbosity=None):
files_to_copy = {'autoPyLoT_local.in':['~', '.pylot'], files_to_copy = {'autoPyLoT_local.in': ['~', '.pylot'],
'autoPyLoT_regional.in':['~', '.pylot']} 'autoPyLoT_regional.in': ['~', '.pylot']}
if verbosity > 0: if verbosity > 0:
print ('starting installation of PyLoT ...') print('starting installation of PyLoT ...')
if verbosity > 1: if verbosity > 1:
print ('copying input files into destination folder ...') print('copying input files into destination folder ...')
ans = input('please specify scope of interest ' ans = input('please specify scope of interest '
'([0]=local, 1=regional) :') or 0 '([0]=local, 1=regional) :') or 0
if not isinstance(ans, int): if not isinstance(ans, int):
@ -182,7 +182,7 @@ def installPyLoT(verbosity=None):
assert not os.path.isabs(srcfile), 'source files seem to be ' \ assert not os.path.isabs(srcfile), 'source files seem to be ' \
'corrupted ...' 'corrupted ...'
if verbosity > 1: if verbosity > 1:
print ('copying file {file} to folder {dest}'.format(file=file, dest=destination)) print('copying file {file} to folder {dest}'.format(file=file, dest=destination))
shutil.copyfile(srcfile, destination) shutil.copyfile(srcfile, destination)
if link_file: if link_file:
if verbosity: if verbosity:
@ -190,8 +190,6 @@ def installPyLoT(verbosity=None):
os.symlink(destination, link_dest) os.symlink(destination, link_dest)
def cleanUp(verbosity=None): def cleanUp(verbosity=None):
if verbosity >= 1: if verbosity >= 1:
print('cleaning up build files...') print('cleaning up build files...')

99
pylot/core/analysis/magnitude.py
View File

@ -6,27 +6,27 @@ Revised/extended summer 2017.
:author: Ludger Küperkoch / MAGS2 EP3 working group :author: Ludger Küperkoch / MAGS2 EP3 working group
""" """
import os
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
import numpy as np import numpy as np
import obspy.core.event as ope import obspy.core.event as ope
from obspy.geodetics import degrees2kilometers from obspy.geodetics import degrees2kilometers
from scipy import integrate, signal
from scipy.optimize import curve_fit
from pylot.core.pick.utils import getsignalwin, crossings_nonzero_all, \ from pylot.core.pick.utils import getsignalwin, crossings_nonzero_all, \
select_for_phase select_for_phase
from pylot.core.util.utils import common_range, fit_curve from pylot.core.util.utils import common_range, fit_curve
from scipy import integrate, signal
from scipy.optimize import curve_fit
def richter_magnitude_scaling(delta): def richter_magnitude_scaling(delta):
distance = np.array([0, 10, 20, 25, 30, 35,40, 45, 50, 60, 70, 75, 85, 90, 100, 110, distance = np.array([0, 10, 20, 25, 30, 35, 40, 45, 50, 60, 70, 75, 85, 90, 100, 110,
120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 230, 240, 250, 120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 230, 240, 250,
260, 270, 280, 290, 300, 310, 320, 330, 340, 350, 360, 370, 380, 260, 270, 280, 290, 300, 310, 320, 330, 340, 350, 360, 370, 380,
390, 400, 430, 470, 510, 560, 600, 700, 800, 900, 1000]) 390, 400, 430, 470, 510, 560, 600, 700, 800, 900, 1000])
richter_scaling = np.array([1.4, 1.5, 1.7, 1.9, 2.1, 2.3, 2.4, 2.5, 2.6, 2.8, 2.8, 2.9, richter_scaling = np.array([1.4, 1.5, 1.7, 1.9, 2.1, 2.3, 2.4, 2.5, 2.6, 2.8, 2.8, 2.9,
2.9, 3.0, 3.1, 3.1, 3.2, 3.2, 3.3, 3.3, 3.4, 3.4, 3.5, 3.5, 2.9, 3.0, 3.1, 3.1, 3.2, 3.2, 3.3, 3.3, 3.4, 3.4, 3.5, 3.5,
3.6, 3.7, 3.7, 3.8, 3.8, 3.9, 3.9, 4.0, 4.0, 4.1, 4.2, 4.2, 3.6, 3.7, 3.7, 3.8, 3.8, 3.9, 3.9, 4.0, 4.0, 4.1, 4.2, 4.2,
4.2, 4.2, 4.3, 4.3, 4.3, 4.4, 4.4, 4.5, 4.6, 4.7, 4.8, 4.9, 4.2, 4.2, 4.3, 4.3, 4.3, 4.4, 4.4, 4.5, 4.6, 4.7, 4.8, 4.9,
5.1, 5.2, 5.4, 5.5, 5.7]) 5.1, 5.2, 5.4, 5.5, 5.7])
# prepare spline interpolation to calculate return value # prepare spline interpolation to calculate return value
func, params = fit_curve(distance, richter_scaling) func, params = fit_curve(distance, richter_scaling)
return func(delta, params) return func(delta, params)
@ -47,7 +47,7 @@ class Magnitude(object):
def __str__(self): def __str__(self):
print( print(
'number of stations used: {0}\n'.format(len(self.magnitudes.values()))) 'number of stations used: {0}\n'.format(len(self.magnitudes.values())))
print('\tstation\tmagnitude') print('\tstation\tmagnitude')
for s, m in self.magnitudes.items(): print('\t{0}\t{1}'.format(s, m)) for s, m in self.magnitudes.items(): print('\t{0}\t{1}'.format(s, m))
@ -126,8 +126,8 @@ class Magnitude(object):
# scaling necessary # scaling necessary
print("Scaling network magnitude ...") print("Scaling network magnitude ...")
mag = ope.Magnitude( mag = ope.Magnitude(
mag=np.median([M.mag for M in self.magnitudes.values()]) *\ mag=np.median([M.mag for M in self.magnitudes.values()]) * \
magscaling[0] + magscaling[1], magscaling[0] + magscaling[1],
magnitude_type=self.type, magnitude_type=self.type,
origin_id=self.origin_id, origin_id=self.origin_id,
station_count=len(self.magnitudes), station_count=len(self.magnitudes),
@ -215,7 +215,7 @@ class LocalMagnitude(Magnitude):
th = np.arange(0, len(sqH) * dt, dt) th = np.arange(0, len(sqH) * dt, dt)
# get maximum peak within pick window # get maximum peak within pick window
iwin = getsignalwin(th, t0 - stime, self.calc_win) iwin = getsignalwin(th, t0 - stime, self.calc_win)
ii = min([iwin[len(iwin)-1], len(th)]) ii = min([iwin[len(iwin) - 1], len(th)])
iwin = iwin[0:ii] iwin = iwin[0:ii]
wapp = np.max(sqH[iwin]) wapp = np.max(sqH[iwin])
if self.verbose: if self.verbose:
@ -250,8 +250,8 @@ class LocalMagnitude(Magnitude):
if not wf: if not wf:
if self.verbose: if self.verbose:
print( print(
'WARNING: no waveform data found for station {0}'.format( 'WARNING: no waveform data found for station {0}'.format(
station)) station))
continue continue
delta = degrees2kilometers(a.distance) delta = degrees2kilometers(a.distance)
onset = pick.time onset = pick.time
@ -270,13 +270,14 @@ class LocalMagnitude(Magnitude):
if str(self.wascaling) == '[0.0, 0.0, 0.0]': if str(self.wascaling) == '[0.0, 0.0, 0.0]':
print("Calculating original Richter magnitude ...") print("Calculating original Richter magnitude ...")
magnitude = ope.StationMagnitude(mag=np.log10(a0) \ magnitude = ope.StationMagnitude(mag=np.log10(a0) \
+ richter_magnitude_scaling(delta)) + richter_magnitude_scaling(delta))
else: else:
print("Calculating scaled local magnitude ...") print("Calculating scaled local magnitude ...")
a0 = a0 * 1e03 # mm to nm (see Havskov & Ottemöller, 2010) a0 = a0 * 1e03 # mm to nm (see Havskov & Ottemöller, 2010)
magnitude = ope.StationMagnitude(mag=np.log10(a0) \ magnitude = ope.StationMagnitude(mag=np.log10(a0) \
+ self.wascaling[0] * np.log10(delta) + self.wascaling[1] + self.wascaling[0] * np.log10(delta) + self.wascaling[1]
* delta + self.wascaling[2]) * delta + self.wascaling[
2])
magnitude.origin_id = self.origin_id magnitude.origin_id = self.origin_id
magnitude.waveform_id = pick.waveform_id magnitude.waveform_id = pick.waveform_id
magnitude.amplitude_id = amplitude.resource_id magnitude.amplitude_id = amplitude.resource_id
@ -397,8 +398,8 @@ def calcMoMw(wfstream, w0, rho, vp, delta, verbosity=False):
if verbosity: if verbosity:
print( print(
"calcMoMw: Calculating seismic moment Mo and moment magnitude Mw for station {0} ...".format( "calcMoMw: Calculating seismic moment Mo and moment magnitude Mw for station {0} ...".format(
tr.stats.station)) tr.stats.station))
# additional common parameters for calculating Mo # additional common parameters for calculating Mo
rP = 2 / np.sqrt( rP = 2 / np.sqrt(
@ -412,8 +413,8 @@ def calcMoMw(wfstream, w0, rho, vp, delta, verbosity=False):
if verbosity: if verbosity:
print( print(
"calcMoMw: Calculated seismic moment Mo = {0} Nm => Mw = {1:3.1f} ".format( "calcMoMw: Calculated seismic moment Mo = {0} Nm => Mw = {1:3.1f} ".format(
Mo, Mw)) Mo, Mw))
return Mo, Mw return Mo, Mw
@ -452,7 +453,7 @@ def calcsourcespec(wfstream, onset, vp, delta, azimuth, incidence,
:type: integer :type: integer
''' '''
if verbosity: if verbosity:
print ("Calculating source spectrum for station %s ...." % wfstream[0].stats.station) print("Calculating source spectrum for station %s ...." % wfstream[0].stats.station)
# get Q value # get Q value
Q, A = qp Q, A = qp
@ -509,9 +510,9 @@ def calcsourcespec(wfstream, onset, vp, delta, azimuth, incidence,
zc = crossings_nonzero_all(wfzc) zc = crossings_nonzero_all(wfzc)
if np.size(zc) == 0 or len(zc) <= 3: if np.size(zc) == 0 or len(zc) <= 3:
if verbosity: if verbosity:
print ("calcsourcespec: Something is wrong with the waveform, " print("calcsourcespec: Something is wrong with the waveform, "
"no zero crossings derived!\n") "no zero crossings derived!\n")
print ("No calculation of source spectrum possible!") print("No calculation of source spectrum possible!")
plotflag = 0 plotflag = 0
else: else:
plotflag = 1 plotflag = 1
@ -558,22 +559,22 @@ def calcsourcespec(wfstream, onset, vp, delta, azimuth, incidence,
[optspecfit, _] = curve_fit(synthsourcespec, F, YYcor, [w0in, Fcin]) [optspecfit, _] = curve_fit(synthsourcespec, F, YYcor, [w0in, Fcin])
w0 = optspecfit[0] w0 = optspecfit[0]
fc = optspecfit[1] fc = optspecfit[1]
#w01 = optspecfit[0] # w01 = optspecfit[0]
#fc1 = optspecfit[1] # fc1 = optspecfit[1]
if verbosity: if verbosity:
print ("calcsourcespec: Determined w0-value: %e m/Hz, \n" print("calcsourcespec: Determined w0-value: %e m/Hz, \n"
"calcsourcespec: Determined corner frequency: %f Hz" % (w0, fc)) "calcsourcespec: Determined corner frequency: %f Hz" % (w0, fc))
# use of conventional fitting # use of conventional fitting
# [w02, fc2] = fitSourceModel(F, YYcor, Fcin, iplot, verbosity) # [w02, fc2] = fitSourceModel(F, YYcor, Fcin, iplot, verbosity)
# get w0 and fc as median of both # get w0 and fc as median of both
# source spectrum fits # source spectrum fits
#w0 = np.median([w01, w02]) # w0 = np.median([w01, w02])
#fc = np.median([fc1, fc2]) # fc = np.median([fc1, fc2])
#if verbosity: # if verbosity:
# print("calcsourcespec: Using w0-value = %e m/Hz and fc = %f Hz" % ( # print("calcsourcespec: Using w0-value = %e m/Hz and fc = %f Hz" % (
# w0, fc)) # w0, fc))
if iplot > 1: if iplot > 1:
f1 = plt.figure() f1 = plt.figure()
@ -659,9 +660,9 @@ def fitSourceModel(f, S, fc0, iplot, verbosity=False):
# left side of initial corner frequency # left side of initial corner frequency
fcstopl = max(f[0], fc0 - max(1, fc0 / 2)) fcstopl = max(f[0], fc0 - max(1, fc0 / 2))
il = np.where(f <= fcstopl) il = np.where(f <= fcstopl)
il = il[0][np.size(il) - 1] il = il[0][np.size(il) - 1]
# right side of initial corner frequency # right side of initial corner frequency
fcstopr = min(fc0 + (fc0 / 2), f[len(f) - 1]) fcstopr = min(fc0 + (fc0 / 2), f[len(f) - 1])
ir = np.where(f >= fcstopr) ir = np.where(f >= fcstopr)
# check, if fcstopr is available # check, if fcstopr is available
if np.size(ir) == 0: if np.size(ir) == 0:
@ -672,16 +673,16 @@ def fitSourceModel(f, S, fc0, iplot, verbosity=False):
# vary corner frequency around initial point # vary corner frequency around initial point
print("fitSourceModel: Varying corner frequency " print("fitSourceModel: Varying corner frequency "
"around initial corner frequency ...") "around initial corner frequency ...")
# check difference of il and ir in order to # check difference of il and ir in order to
# keep calculation time acceptable # keep calculation time acceptable
idiff = ir - il idiff = ir - il
if idiff > 10000: if idiff > 10000:
increment = 100 increment = 100
elif idiff <= 20: elif idiff <= 20:
increment = 1 increment = 1
else: else:
increment = 10 increment = 10
for i in range(il, ir, increment): for i in range(il, ir, increment):
FC = f[i] FC = f[i]
@ -707,10 +708,10 @@ def fitSourceModel(f, S, fc0, iplot, verbosity=False):
w0 = max(S) w0 = max(S)
if verbosity: if verbosity:
print( print(
"fitSourceModel: best fc: {0} Hz, best w0: {1} m/Hz".format(fc, w0)) "fitSourceModel: best fc: {0} Hz, best w0: {1} m/Hz".format(fc, w0))
if iplot > 1: if iplot > 1:
plt.figure()#iplot) plt.figure() # iplot)
plt.loglog(f, S, 'k') plt.loglog(f, S, 'k')
plt.loglog([f[0], fc], [w0, w0], 'g') plt.loglog([f[0], fc], [w0, w0], 'g')
plt.loglog([fc, fc], [w0 / 100, w0], 'g') plt.loglog([fc, fc], [w0 / 100, w0], 'g')
@ -719,7 +720,7 @@ def fitSourceModel(f, S, fc0, iplot, verbosity=False):
plt.xlabel('Frequency [Hz]') plt.xlabel('Frequency [Hz]')
plt.ylabel('Amplitude [m/Hz]') plt.ylabel('Amplitude [m/Hz]')
plt.grid() plt.grid()
plt.figure()#iplot + 1) plt.figure() # iplot + 1)
plt.subplot(311) plt.subplot(311)
plt.plot(f[il:ir], STD, '*') plt.plot(f[il:ir], STD, '*')
plt.title('Common Standard Deviations') plt.title('Common Standard Deviations')

46
pylot/core/analysis/magnitude.py.orig
View File

@ -12,6 +12,7 @@ from obspy.core import Stream
from pylot.core.pick.utils import getsignalwin from pylot.core.pick.utils import getsignalwin
from scipy.optimize import curve_fit from scipy.optimize import curve_fit
class Magnitude(object): class Magnitude(object):
''' '''
Superclass for calculating Wood-Anderson peak-to-peak Superclass for calculating Wood-Anderson peak-to-peak
@ -45,7 +46,6 @@ class Magnitude(object):
self.calcwapp() self.calcwapp()
self.calcsourcespec() self.calcsourcespec()
def getwfstream(self): def getwfstream(self):
return self.wfstream return self.wfstream
@ -85,6 +85,7 @@ class Magnitude(object):
def calcsourcespec(self): def calcsourcespec(self):
self.sourcespek = None self.sourcespek = None
class WApp(Magnitude): class WApp(Magnitude):
''' '''
Method to derive peak-to-peak amplitude as seen on a Wood-Anderson- Method to derive peak-to-peak amplitude as seen on a Wood-Anderson-
@ -92,8 +93,8 @@ class WApp(Magnitude):
''' '''
def calcwapp(self): def calcwapp(self):
print ("Getting Wood-Anderson peak-to-peak amplitude ...") print("Getting Wood-Anderson peak-to-peak amplitude ...")
print ("Simulating Wood-Anderson seismograph ...") print("Simulating Wood-Anderson seismograph ...")
self.wapp = None self.wapp = None
stream = self.getwfstream() stream = self.getwfstream()
@ -118,7 +119,7 @@ class WApp(Magnitude):
# get maximum peak within pick window # get maximum peak within pick window
iwin = getsignalwin(th, self.getTo(), self.getpwin()) iwin = getsignalwin(th, self.getTo(), self.getpwin())
self.wapp = np.max(sqH[iwin]) self.wapp = np.max(sqH[iwin])
print ("Determined Wood-Anderson peak-to-peak amplitude: %f mm") % self.wapp print("Determined Wood-Anderson peak-to-peak amplitude: %f mm") % self.wapp
if self.getiplot() > 1: if self.getiplot() > 1:
stream.plot() stream.plot()
@ -143,10 +144,10 @@ class DCfc(Magnitude):
''' '''
def calcsourcespec(self): def calcsourcespec(self):
print ("Calculating source spectrum ....") print("Calculating source spectrum ....")
self.w0 = None # DC-value self.w0 = None # DC-value
self.fc = None # corner frequency self.fc = None # corner frequency
stream = self.getwfstream() stream = self.getwfstream()
tr = stream[0] tr = stream[0]
@ -159,14 +160,14 @@ class DCfc(Magnitude):
# fft # fft
fny = tr.stats.sampling_rate / 2 fny = tr.stats.sampling_rate / 2
l = len(xdat) / tr.stats.sampling_rate l = len(xdat) / tr.stats.sampling_rate
n = tr.stats.sampling_rate * l # number of fft bins after Bath n = tr.stats.sampling_rate * l # number of fft bins after Bath
# find next power of 2 of data length # find next power of 2 of data length
m = pow(2, np.ceil(np.log(len(xdat)) / np.log(2))) m = pow(2, np.ceil(np.log(len(xdat)) / np.log(2)))
N = int(np.power(m, 2)) N = int(np.power(m, 2))
y = tr.stats.delta * np.fft.fft(xdat, N) y = tr.stats.delta * np.fft.fft(xdat, N)
Y = abs(y[: N/2]) Y = abs(y[: N / 2])
L = (N - 1) / tr.stats.sampling_rate L = (N - 1) / tr.stats.sampling_rate
f = np.arange(0, fny, 1/L) f = np.arange(0, fny, 1 / L)
# remove zero-frequency and frequencies above # remove zero-frequency and frequencies above
# corner frequency of seismometer (assumed # corner frequency of seismometer (assumed
@ -185,20 +186,18 @@ class DCfc(Magnitude):
[optspecfit, pcov] = curve_fit(synthsourcespec, F, YY.real, [DCin, Fcin]) [optspecfit, pcov] = curve_fit(synthsourcespec, F, YY.real, [DCin, Fcin])
self.w0 = optspecfit[0] self.w0 = optspecfit[0]
self.fc = optspecfit[1] self.fc = optspecfit[1]
print ("DCfc: Determined DC-value: %e m/Hz, \n" \ print("DCfc: Determined DC-value: %e m/Hz, \n" \
"Determined corner frequency: %f Hz" % (self.w0, self.fc)) "Determined corner frequency: %f Hz" % (self.w0, self.fc))
#if self.getiplot() > 1:
iplot=2
if iplot > 1:
print ("DCfc: Determined DC-value: %e m/Hz, \n"
"Determined corner frequency: %f Hz" % (self.w0, self.fc))
# if self.getiplot() > 1:
iplot = 2
if iplot > 1:
print("DCfc: Determined DC-value: %e m/Hz, \n"
"Determined corner frequency: %f Hz" % (self.w0, self.fc))
if self.getiplot() > 1: if self.getiplot() > 1:
f1 = plt.figure() f1 = plt.figure()
plt.subplot(2,1,1) plt.subplot(2, 1, 1)
# show displacement in mm # show displacement in mm
plt.plot(t, np.multiply(tr, 1000), 'k') plt.plot(t, np.multiply(tr, 1000), 'k')
plt.plot(t[iwin], np.multiply(xdat, 1000), 'g') plt.plot(t[iwin], np.multiply(xdat, 1000), 'g')
@ -206,12 +205,12 @@ class DCfc(Magnitude):
plt.xlabel('Time since %s' % tr.stats.starttime) plt.xlabel('Time since %s' % tr.stats.starttime)
plt.ylabel('Displacement [mm]') plt.ylabel('Displacement [mm]')
plt.subplot(2,1,2) plt.subplot(2, 1, 2)
plt.loglog(f, Y.real, 'k') plt.loglog(f, Y.real, 'k')
plt.loglog(F, YY.real) plt.loglog(F, YY.real)
plt.loglog(F, fit, 'g') plt.loglog(F, fit, 'g')
plt.title('Source Spectrum from P Pulse, DC=%e m/Hz, fc=%4.1f Hz' \ plt.title('Source Spectrum from P Pulse, DC=%e m/Hz, fc=%4.1f Hz' \
% (self.w0, self.fc)) % (self.w0, self.fc))
plt.xlabel('Frequency [Hz]') plt.xlabel('Frequency [Hz]')
plt.ylabel('Amplitude [m/Hz]') plt.ylabel('Amplitude [m/Hz]')
plt.grid() plt.grid()
@ -235,8 +234,7 @@ def synthsourcespec(f, omega0, fcorner):
:type: float :type: float
''' '''
#ssp = omega0 / (pow(2, (1 + f / fcorner))) # ssp = omega0 / (pow(2, (1 + f / fcorner)))
ssp = omega0 / (1 + pow(2, (f / fcorner))) ssp = omega0 / (1 + pow(2, (f / fcorner)))
return ssp return ssp

162
pylot/core/io/data.py
View File

@ -3,15 +3,17 @@
import copy import copy
import os import os
from obspy import read_events from obspy import read_events
from obspy.core import read, Stream, UTCDateTime from obspy.core import read, Stream, UTCDateTime
from obspy.io.sac import SacIOError
from obspy.core.event import Event as ObsPyEvent from obspy.core.event import Event as ObsPyEvent
from obspy.io.sac import SacIOError
from pylot.core.io.phases import readPILOTEvent, picks_from_picksdict, \ from pylot.core.io.phases import readPILOTEvent, picks_from_picksdict, \
picksdict_from_pilot, merge_picks picksdict_from_pilot, merge_picks
from pylot.core.util.errors import FormatError, OverwriteError from pylot.core.util.errors import FormatError, OverwriteError
from pylot.core.util.utils import fnConstructor, full_range
from pylot.core.util.event import Event from pylot.core.util.event import Event
from pylot.core.util.utils import fnConstructor, full_range
class Data(object): class Data(object):
""" """
@ -75,7 +77,7 @@ class Data(object):
def __add__(self, other): def __add__(self, other):
assert isinstance(other, Data), "operands must be of same type 'Data'" assert isinstance(other, Data), "operands must be of same type 'Data'"
rs_id = self.get_evt_data().get('resource_id') rs_id = self.get_evt_data().get('resource_id')
rs_id_other = other.get_evt_data().get('resource_id') rs_id_other = other.get_evt_data().get('resource_id')
if other.isNew() and not self.isNew(): if other.isNew() and not self.isNew():
picks_to_add = other.get_evt_data().picks picks_to_add = other.get_evt_data().picks
old_picks = self.get_evt_data().picks old_picks = self.get_evt_data().picks
@ -156,23 +158,23 @@ class Data(object):
self.replacePicks(event, 'auto') self.replacePicks(event, 'auto')
if 'manual' in fcheck: if 'manual' in fcheck:
self.replacePicks(event, 'manual') self.replacePicks(event, 'manual')
def replaceOrigin(self, event, forceOverwrite=False): def replaceOrigin(self, event, forceOverwrite=False):
if self.get_evt_data().origins or forceOverwrite: if self.get_evt_data().origins or forceOverwrite:
if event.origins: if event.origins:
print("Found origin, replace it by new origin." ) print("Found origin, replace it by new origin.")
event.origins = self.get_evt_data().origins event.origins = self.get_evt_data().origins
def replaceMagnitude(self, event, forceOverwrite=False): def replaceMagnitude(self, event, forceOverwrite=False):
if self.get_evt_data().magnitudes or forceOverwrite: if self.get_evt_data().magnitudes or forceOverwrite:
if event.magnitudes: if event.magnitudes:
print("Found magnitude, replace it by new magnitude") print("Found magnitude, replace it by new magnitude")
event.magnitudes = self.get_evt_data().magnitudes event.magnitudes = self.get_evt_data().magnitudes
def replacePicks(self, event, picktype): def replacePicks(self, event, picktype):
checkflag = 0 checkflag = 0
picks = event.picks picks = event.picks
#remove existing picks # remove existing picks
for j, pick in reversed(list(enumerate(picks))): for j, pick in reversed(list(enumerate(picks))):
if picktype in str(pick.method_id.id): if picktype in str(pick.method_id.id):
picks.pop(j) picks.pop(j)
@ -180,7 +182,7 @@ class Data(object):
if checkflag: if checkflag:
print("Found %s pick(s), remove them and append new picks to catalog." % picktype) print("Found %s pick(s), remove them and append new picks to catalog." % picktype)
#append new picks # append new picks
for pick in self.get_evt_data().picks: for pick in self.get_evt_data().picks:
if picktype in str(pick.method_id.id): if picktype in str(pick.method_id.id):
picks.append(pick) picks.append(pick)
@ -195,8 +197,8 @@ class Data(object):
""" """
from pylot.core.util.defaults import OUTPUTFORMATS from pylot.core.util.defaults import OUTPUTFORMATS
if not type(fcheck)==list: if not type(fcheck) == list:
fcheck=[fcheck] fcheck = [fcheck]
try: try:
evtformat = OUTPUTFORMATS[fnext] evtformat = OUTPUTFORMATS[fnext]
@ -204,7 +206,7 @@ class Data(object):
errmsg = '{0}; selected file extension {1} not ' \ errmsg = '{0}; selected file extension {1} not ' \
'supported'.format(e, fnext) 'supported'.format(e, fnext)
raise FormatError(errmsg) raise FormatError(errmsg)
# check for already existing xml-file # check for already existing xml-file
if fnext == '.xml': if fnext == '.xml':
if os.path.isfile(fnout + fnext): if os.path.isfile(fnout + fnext):
@ -231,73 +233,71 @@ class Data(object):
# Prefer manual picks! # Prefer manual picks!
for i in range(len(evtdata_org.picks)): for i in range(len(evtdata_org.picks)):
if evtdata_org.picks[i].method_id == 'manual': if evtdata_org.picks[i].method_id == 'manual':
mstation = evtdata_org.picks[i].waveform_id.station_code mstation = evtdata_org.picks[i].waveform_id.station_code
mstation_ext = mstation + '_' mstation_ext = mstation + '_'
for k in range(len(evtdata_copy.picks)): for k in range(len(evtdata_copy.picks)):
if ((evtdata_copy.picks[k].waveform_id.station_code == mstation) or \ if ((evtdata_copy.picks[k].waveform_id.station_code == mstation) or \
(evtdata_copy.picks[k].waveform_id.station_code == mstation_ext)) and \ (evtdata_copy.picks[k].waveform_id.station_code == mstation_ext)) and \
(evtdata_copy.picks[k].method_id == 'auto'): (evtdata_copy.picks[k].method_id == 'auto'):
del evtdata_copy.picks[k] del evtdata_copy.picks[k]
break break
lendiff = len(evtdata_org.picks) - len(evtdata_copy.picks) lendiff = len(evtdata_org.picks) - len(evtdata_copy.picks)
if lendiff is not 0: if lendiff is not 0:
print("Manual as well as automatic picks available. Prefered the {} manual ones!".format(lendiff)) print("Manual as well as automatic picks available. Prefered the {} manual ones!".format(lendiff))
if upperErrors: if upperErrors:
# check for pick uncertainties exceeding adjusted upper errors # check for pick uncertainties exceeding adjusted upper errors
# Picks with larger uncertainties will not be saved in output file! # Picks with larger uncertainties will not be saved in output file!
for j in range(len(evtdata_org.picks)): for j in range(len(evtdata_org.picks)):
for i in range(len(evtdata_copy.picks)): for i in range(len(evtdata_copy.picks)):
if evtdata_copy.picks[i].phase_hint[0] == 'P': if evtdata_copy.picks[i].phase_hint[0] == 'P':
if (evtdata_copy.picks[i].time_errors['upper_uncertainty'] >= upperErrors[0]) or \ if (evtdata_copy.picks[i].time_errors['upper_uncertainty'] >= upperErrors[0]) or \
(evtdata_copy.picks[i].time_errors['uncertainty'] == None): (evtdata_copy.picks[i].time_errors['uncertainty'] == None):
print("Uncertainty exceeds or equal adjusted upper time error!") print("Uncertainty exceeds or equal adjusted upper time error!")
print("Adjusted uncertainty: {}".format(upperErrors[0])) print("Adjusted uncertainty: {}".format(upperErrors[0]))
print("Pick uncertainty: {}".format(evtdata_copy.picks[i].time_errors['uncertainty'])) print("Pick uncertainty: {}".format(evtdata_copy.picks[i].time_errors['uncertainty']))
print("{1} P-Pick of station {0} will not be saved in outputfile".format( print("{1} P-Pick of station {0} will not be saved in outputfile".format(
evtdata_copy.picks[i].waveform_id.station_code, evtdata_copy.picks[i].waveform_id.station_code,
evtdata_copy.picks[i].method_id)) evtdata_copy.picks[i].method_id))
print("#") print("#")
del evtdata_copy.picks[i] del evtdata_copy.picks[i]
break break
if evtdata_copy.picks[i].phase_hint[0] == 'S': if evtdata_copy.picks[i].phase_hint[0] == 'S':
if (evtdata_copy.picks[i].time_errors['upper_uncertainty'] >= upperErrors[1]) or \ if (evtdata_copy.picks[i].time_errors['upper_uncertainty'] >= upperErrors[1]) or \
(evtdata_copy.picks[i].time_errors['uncertainty'] == None): (evtdata_copy.picks[i].time_errors['uncertainty'] == None):
print("Uncertainty exceeds or equal adjusted upper time error!") print("Uncertainty exceeds or equal adjusted upper time error!")
print("Adjusted uncertainty: {}".format(upperErrors[1])) print("Adjusted uncertainty: {}".format(upperErrors[1]))
print("Pick uncertainty: {}".format(evtdata_copy.picks[i].time_errors['uncertainty'])) print("Pick uncertainty: {}".format(evtdata_copy.picks[i].time_errors['uncertainty']))
print("{1} S-Pick of station {0} will not be saved in outputfile".format( print("{1} S-Pick of station {0} will not be saved in outputfile".format(
evtdata_copy.picks[i].waveform_id.station_code, evtdata_copy.picks[i].waveform_id.station_code,
evtdata_copy.picks[i].method_id)) evtdata_copy.picks[i].method_id))
print("#") print("#")
del evtdata_copy.picks[i] del evtdata_copy.picks[i]
break break
if fnext == '.obs': if fnext == '.obs':
try: try:
evtdata_copy.write(fnout + fnext, format=evtformat) evtdata_copy.write(fnout + fnext, format=evtformat)
# write header afterwards # write header afterwards
evid = str(evtdata_org.resource_id).split('/')[1] evid = str(evtdata_org.resource_id).split('/')[1]
header = '# EQEVENT: Label: EQ%s Loc: X 0.00 Y 0.00 Z 10.00 OT 0.00 \n' % evid header = '# EQEVENT: Label: EQ%s Loc: X 0.00 Y 0.00 Z 10.00 OT 0.00 \n' % evid
nllocfile = open(fnout + fnext) nllocfile = open(fnout + fnext)
l = nllocfile.readlines() l = nllocfile.readlines()
nllocfile.close() nllocfile.close()
l.insert(0, header) l.insert(0, header)
nllocfile = open(fnout + fnext, 'w') nllocfile = open(fnout + fnext, 'w')
nllocfile.write("".join(l)) nllocfile.write("".join(l))
nllocfile.close() nllocfile.close()
except KeyError as e: except KeyError as e:
raise KeyError('''{0} export format raise KeyError('''{0} export format
not implemented: {1}'''.format(evtformat, e)) not implemented: {1}'''.format(evtformat, e))
if fnext == '.cnv': if fnext == '.cnv':
try: try:
evtdata_org.write(fnout + fnext, format=evtformat) evtdata_org.write(fnout + fnext, format=evtformat)
except KeyError as e: except KeyError as e:
raise KeyError('''{0} export format raise KeyError('''{0} export format
not implemented: {1}'''.format(evtformat, e)) not implemented: {1}'''.format(evtformat, e))
def getComp(self): def getComp(self):
""" """
@ -362,7 +362,7 @@ class Data(object):
except Exception as e: except Exception as e:
warnmsg += '{0}\n{1}\n'.format(fname, e) warnmsg += '{0}\n{1}\n'.format(fname, e)
except SacIOError as se: except SacIOError as se:
warnmsg += '{0}\n{1}\n'.format(fname, se) warnmsg += '{0}\n{1}\n'.format(fname, se)
if warnmsg: if warnmsg:
warnmsg = 'WARNING: unable to read\n' + warnmsg warnmsg = 'WARNING: unable to read\n' + warnmsg
print(warnmsg) print(warnmsg)
@ -427,21 +427,21 @@ class Data(object):
:raise OverwriteError: raises an OverwriteError if the picks list is :raise OverwriteError: raises an OverwriteError if the picks list is
not empty. The GUI will then ask for a decision. not empty. The GUI will then ask for a decision.
""" """
#firstonset = find_firstonset(picks) # firstonset = find_firstonset(picks)
# check for automatic picks # check for automatic picks
print("Writing phases to ObsPy-quakeml file") print("Writing phases to ObsPy-quakeml file")
for key in picks: for key in picks:
if picks[key]['P']['picker'] == 'auto': if picks[key]['P']['picker'] == 'auto':
print("Existing picks will be overwritten!") print("Existing picks will be overwritten!")
picks = picks_from_picksdict(picks) picks = picks_from_picksdict(picks)
break break
else: else:
if self.get_evt_data().picks: if self.get_evt_data().picks:
raise OverwriteError('Existing picks would be overwritten!') raise OverwriteError('Existing picks would be overwritten!')
break break
else: else:
picks = picks_from_picksdict(picks) picks = picks_from_picksdict(picks)
break break
self.get_evt_data().picks = picks self.get_evt_data().picks = picks
# if 'smi:local' in self.getID() and firstonset: # if 'smi:local' in self.getID() and firstonset:
# fonset_str = firstonset.strftime('%Y_%m_%d_%H_%M_%S') # fonset_str = firstonset.strftime('%Y_%m_%d_%H_%M_%S')
@ -449,7 +449,6 @@ class Data(object):
# ID.convertIDToQuakeMLURI(authority_id=authority_id) # ID.convertIDToQuakeMLURI(authority_id=authority_id)
# self.get_evt_data().resource_id = ID # self.get_evt_data().resource_id = ID
def applyEvent(event): def applyEvent(event):
""" """
takes an `obspy.core.event.Event` object and applies all new takes an `obspy.core.event.Event` object and applies all new
@ -476,7 +475,6 @@ class Data(object):
applydata[typ](data) applydata[typ](data)
self._new = False self._new = False
class GenericDataStructure(object): class GenericDataStructure(object):

176
pylot/core/io/default_parameters.py
View File

@ -5,347 +5,347 @@ defaults = {'rootpath': {'type': str,
'tooltip': 'project path', 'tooltip': 'project path',
'value': '', 'value': '',
'namestring': 'Root path'}, 'namestring': 'Root path'},
'datapath': {'type': str, 'datapath': {'type': str,
'tooltip': 'data path', 'tooltip': 'data path',
'value': '', 'value': '',
'namestring': 'Data path'}, 'namestring': 'Data path'},
'database': {'type': str, 'database': {'type': str,
'tooltip': 'name of data base', 'tooltip': 'name of data base',
'value': '', 'value': '',
'namestring': 'Database path'}, 'namestring': 'Database path'},
'eventID': {'type': str, 'eventID': {'type': str,
'tooltip': 'event ID for single event processing (* for all events found in database)', 'tooltip': 'event ID for single event processing (* for all events found in database)',
'value': '', 'value': '',
'namestring': 'Event ID'}, 'namestring': 'Event ID'},
'extent': {'type': str, 'extent': {'type': str,
'tooltip': 'extent of array ("local", "regional" or "global")', 'tooltip': 'extent of array ("local", "regional" or "global")',
'value': 'local', 'value': 'local',
'namestring': 'Array extent'}, 'namestring': 'Array extent'},
'invdir': {'type': str, 'invdir': {'type': str,
'tooltip': 'full path to inventory or dataless-seed file', 'tooltip': 'full path to inventory or dataless-seed file',
'value': '', 'value': '',
'namestring': 'Inversion dir'}, 'namestring': 'Inversion dir'},
'datastructure': {'type': str, 'datastructure': {'type': str,
'tooltip': 'choose data structure', 'tooltip': 'choose data structure',
'value': 'PILOT', 'value': 'PILOT',
'namestring': 'Datastructure'}, 'namestring': 'Datastructure'},
'apverbose': {'type': bool, 'apverbose': {'type': bool,
'tooltip': "choose 'True' or 'False' for terminal output", 'tooltip': "choose 'True' or 'False' for terminal output",
'value': True, 'value': True,
'namestring': 'App. verbosity'}, 'namestring': 'App. verbosity'},
'nllocbin': {'type': str, 'nllocbin': {'type': str,
'tooltip': 'path to NLLoc executable', 'tooltip': 'path to NLLoc executable',
'value': '', 'value': '',
'namestring': 'NLLoc bin path'}, 'namestring': 'NLLoc bin path'},
'nllocroot': {'type': str, 'nllocroot': {'type': str,
'tooltip': 'root of NLLoc-processing directory', 'tooltip': 'root of NLLoc-processing directory',
'value': '', 'value': '',
'namestring': 'NLLoc root path'}, 'namestring': 'NLLoc root path'},
'phasefile': {'type': str, 'phasefile': {'type': str,
'tooltip': 'name of autoPyLoT-output phase file for NLLoc', 'tooltip': 'name of autoPyLoT-output phase file for NLLoc',
'value': 'AUTOPHASES.obs', 'value': 'AUTOPHASES.obs',
'namestring': 'Phase filename'}, 'namestring': 'Phase filename'},
'ctrfile': {'type': str, 'ctrfile': {'type': str,
'tooltip': 'name of autoPyLoT-output control file for NLLoc', 'tooltip': 'name of autoPyLoT-output control file for NLLoc',
'value': 'Insheim_min1d2015_auto.in', 'value': 'Insheim_min1d2015_auto.in',
'namestring': 'Control filename'}, 'namestring': 'Control filename'},
'ttpatter': {'type': str, 'ttpatter': {'type': str,
'tooltip': 'pattern of NLLoc ttimes from grid', 'tooltip': 'pattern of NLLoc ttimes from grid',
'value': 'ttime', 'value': 'ttime',
'namestring': 'Traveltime pattern'}, 'namestring': 'Traveltime pattern'},
'outpatter': {'type': str, 'outpatter': {'type': str,
'tooltip': 'pattern of NLLoc-output file', 'tooltip': 'pattern of NLLoc-output file',
'value': 'AUTOLOC_nlloc', 'value': 'AUTOLOC_nlloc',
'namestring': 'NLLoc output pattern'}, 'namestring': 'NLLoc output pattern'},
'vp': {'type': float, 'vp': {'type': float,
'tooltip': 'average P-wave velocity', 'tooltip': 'average P-wave velocity',
'value': 3530., 'value': 3530.,
'namestring': 'P-velocity'}, 'namestring': 'P-velocity'},
'rho': {'type': float, 'rho': {'type': float,
'tooltip': 'average rock density [kg/m^3]', 'tooltip': 'average rock density [kg/m^3]',
'value': 2500., 'value': 2500.,
'namestring': 'Density'}, 'namestring': 'Density'},
'Qp': {'type': (float, float), 'Qp': {'type': (float, float),
'tooltip': 'quality factor for P waves (Qp*f^a); list(Qp, a)', 'tooltip': 'quality factor for P waves (Qp*f^a); list(Qp, a)',
'value': (300., 0.8), 'value': (300., 0.8),
'namestring': ('Quality factor', 'Qp1', 'Qp2')}, 'namestring': ('Quality factor', 'Qp1', 'Qp2')},
'pstart': {'type': float, 'pstart': {'type': float,
'tooltip': 'start time [s] for calculating CF for P-picking', 'tooltip': 'start time [s] for calculating CF for P-picking',
'value': 15.0, 'value': 15.0,
'namestring': 'P start'}, 'namestring': 'P start'},
'pstop': {'type': float, 'pstop': {'type': float,
'tooltip': 'end time [s] for calculating CF for P-picking', 'tooltip': 'end time [s] for calculating CF for P-picking',
'value': 60.0, 'value': 60.0,
'namestring': 'P stop'}, 'namestring': 'P stop'},
'sstart': {'type': float, 'sstart': {'type': float,
'tooltip': 'start time [s] relative to P-onset for calculating CF for S-picking', 'tooltip': 'start time [s] relative to P-onset for calculating CF for S-picking',
'value': -1.0, 'value': -1.0,
'namestring': 'S start'}, 'namestring': 'S start'},
'sstop': {'type': float, 'sstop': {'type': float,
'tooltip': 'end time [s] after P-onset for calculating CF for S-picking', 'tooltip': 'end time [s] after P-onset for calculating CF for S-picking',
'value': 10.0, 'value': 10.0,
'namestring': 'S stop'}, 'namestring': 'S stop'},
'bpz1': {'type': (float, float), 'bpz1': {'type': (float, float),
'tooltip': 'lower/upper corner freq. of first band pass filter Z-comp. [Hz]', 'tooltip': 'lower/upper corner freq. of first band pass filter Z-comp. [Hz]',
'value': (2, 20), 'value': (2, 20),
'namestring': ('Z-bandpass 1', 'Lower', 'Upper')}, 'namestring': ('Z-bandpass 1', 'Lower', 'Upper')},
'bpz2': {'type': (float, float), 'bpz2': {'type': (float, float),
'tooltip': 'lower/upper corner freq. of second band pass filter Z-comp. [Hz]', 'tooltip': 'lower/upper corner freq. of second band pass filter Z-comp. [Hz]',
'value': (2, 30), 'value': (2, 30),
'namestring': ('Z-bandpass 2', 'Lower', 'Upper')}, 'namestring': ('Z-bandpass 2', 'Lower', 'Upper')},
'bph1': {'type': (float, float), 'bph1': {'type': (float, float),
'tooltip': 'lower/upper corner freq. of first band pass filter H-comp. [Hz]', 'tooltip': 'lower/upper corner freq. of first band pass filter H-comp. [Hz]',
'value': (2, 15), 'value': (2, 15),
'namestring': ('H-bandpass 1', 'Lower', 'Upper')}, 'namestring': ('H-bandpass 1', 'Lower', 'Upper')},
'bph2': {'type': (float, float), 'bph2': {'type': (float, float),
'tooltip': 'lower/upper corner freq. of second band pass filter z-comp. [Hz]', 'tooltip': 'lower/upper corner freq. of second band pass filter z-comp. [Hz]',
'value': (2, 20), 'value': (2, 20),
'namestring': ('H-bandpass 2', 'Lower', 'Upper')}, 'namestring': ('H-bandpass 2', 'Lower', 'Upper')},
'algoP': {'type': str, 'algoP': {'type': str,
'tooltip': 'choose algorithm for P-onset determination (HOS, ARZ, or AR3)', 'tooltip': 'choose algorithm for P-onset determination (HOS, ARZ, or AR3)',
'value': 'HOS', 'value': 'HOS',
'namestring': 'P algorithm'}, 'namestring': 'P algorithm'},
'tlta': {'type': float, 'tlta': {'type': float,
'tooltip': 'for HOS-/AR-AIC-picker, length of LTA window [s]', 'tooltip': 'for HOS-/AR-AIC-picker, length of LTA window [s]',
'value': 7.0, 'value': 7.0,
'namestring': 'LTA window'}, 'namestring': 'LTA window'},
'hosorder': {'type': int, 'hosorder': {'type': int,
'tooltip': 'for HOS-picker, order of Higher Order Statistics', 'tooltip': 'for HOS-picker, order of Higher Order Statistics',
'value': 4, 'value': 4,
'namestring': 'HOS order'}, 'namestring': 'HOS order'},
'Parorder': {'type': int, 'Parorder': {'type': int,
'tooltip': 'for AR-picker, order of AR process of Z-component', 'tooltip': 'for AR-picker, order of AR process of Z-component',
'value': 2, 'value': 2,
'namestring': 'AR order P'}, 'namestring': 'AR order P'},
'tdet1z': {'type': float, 'tdet1z': {'type': float,
'tooltip': 'for AR-picker, length of AR determination window [s] for Z-component, 1st pick', 'tooltip': 'for AR-picker, length of AR determination window [s] for Z-component, 1st pick',
'value': 1.2, 'value': 1.2,
'namestring': 'AR det. window Z 1'}, 'namestring': 'AR det. window Z 1'},
'tpred1z': {'type': float, 'tpred1z': {'type': float,
'tooltip': 'for AR-picker, length of AR prediction window [s] for Z-component, 1st pick', 'tooltip': 'for AR-picker, length of AR prediction window [s] for Z-component, 1st pick',
'value': 0.4, 'value': 0.4,
'namestring': 'AR pred. window Z 1'}, 'namestring': 'AR pred. window Z 1'},
'tdet2z': {'type': float, 'tdet2z': {'type': float,
'tooltip': 'for AR-picker, length of AR determination window [s] for Z-component, 2nd pick', 'tooltip': 'for AR-picker, length of AR determination window [s] for Z-component, 2nd pick',
'value': 0.6, 'value': 0.6,
'namestring': 'AR det. window Z 2'}, 'namestring': 'AR det. window Z 2'},
'tpred2z': {'type': float, 'tpred2z': {'type': float,
'tooltip': 'for AR-picker, length of AR prediction window [s] for Z-component, 2nd pick', 'tooltip': 'for AR-picker, length of AR prediction window [s] for Z-component, 2nd pick',
'value': 0.2, 'value': 0.2,
'namestring': 'AR pred. window Z 2'}, 'namestring': 'AR pred. window Z 2'},
'addnoise': {'type': float, 'addnoise': {'type': float,
'tooltip': 'add noise to seismogram for stable AR prediction', 'tooltip': 'add noise to seismogram for stable AR prediction',
'value': 0.001, 'value': 0.001,
'namestring': 'Add noise'}, 'namestring': 'Add noise'},
'tsnrz': {'type': (float, float, float, float), 'tsnrz': {'type': (float, float, float, float),
'tooltip': 'for HOS/AR, window lengths for SNR-and slope estimation [tnoise, tsafetey, tsignal, tslope] [s]', 'tooltip': 'for HOS/AR, window lengths for SNR-and slope estimation [tnoise, tsafetey, tsignal, tslope] [s]',
'value': (3, 0.1, 0.5, 1.0), 'value': (3, 0.1, 0.5, 1.0),
'namestring': ('SNR windows P', 'Noise', 'Safety', 'Signal', 'Slope')}, 'namestring': ('SNR windows P', 'Noise', 'Safety', 'Signal', 'Slope')},
'pickwinP': {'type': float, 'pickwinP': {'type': float,
'tooltip': 'for initial AIC pick, length of P-pick window [s]', 'tooltip': 'for initial AIC pick, length of P-pick window [s]',
'value': 3.0, 'value': 3.0,
'namestring': 'AIC window P'}, 'namestring': 'AIC window P'},
'Precalcwin': {'type': float, 'Precalcwin': {'type': float,
'tooltip': 'for HOS/AR, window length [s] for recalculation of CF (relative to 1st pick)', 'tooltip': 'for HOS/AR, window length [s] for recalculation of CF (relative to 1st pick)',
'value': 6.0, 'value': 6.0,
'namestring': 'Recal. window P'}, 'namestring': 'Recal. window P'},
'aictsmooth': {'type': float, 'aictsmooth': {'type': float,
'tooltip': 'for HOS/AR, take average of samples for smoothing of AIC-function [s]', 'tooltip': 'for HOS/AR, take average of samples for smoothing of AIC-function [s]',
'value': 0.2, 'value': 0.2,
'namestring': 'AIC smooth P'}, 'namestring': 'AIC smooth P'},
'tsmoothP': {'type': float, 'tsmoothP': {'type': float,
'tooltip': 'for HOS/AR, take average of samples for smoothing CF [s]', 'tooltip': 'for HOS/AR, take average of samples for smoothing CF [s]',
'value': 0.1, 'value': 0.1,
'namestring': 'CF smooth P'}, 'namestring': 'CF smooth P'},
'ausP': {'type': float, 'ausP': {'type': float,
'tooltip': 'for HOS/AR, artificial uplift of samples (aus) of CF (P)', 'tooltip': 'for HOS/AR, artificial uplift of samples (aus) of CF (P)',
'value': 0.001, 'value': 0.001,
'namestring': 'Artificial uplift P'}, 'namestring': 'Artificial uplift P'},
'nfacP': {'type': float, 'nfacP': {'type': float,
'tooltip': 'for HOS/AR, noise factor for noise level determination (P)', 'tooltip': 'for HOS/AR, noise factor for noise level determination (P)',
'value': 1.3, 'value': 1.3,
'namestring': 'Noise factor P'}, 'namestring': 'Noise factor P'},
'algoS': {'type': str, 'algoS': {'type': str,
'tooltip': 'choose algorithm for S-onset determination (ARH or AR3)', 'tooltip': 'choose algorithm for S-onset determination (ARH or AR3)',
'value': 'ARH', 'value': 'ARH',
'namestring': 'S algorithm'}, 'namestring': 'S algorithm'},
'tdet1h': {'type': float, 'tdet1h': {'type': float,
'tooltip': 'for HOS/AR, length of AR-determination window [s], H-components, 1st pick', 'tooltip': 'for HOS/AR, length of AR-determination window [s], H-components, 1st pick',
'value': 0.8, 'value': 0.8,
'namestring': 'AR det. window H 1'}, 'namestring': 'AR det. window H 1'},
'tpred1h': {'type': float, 'tpred1h': {'type': float,
'tooltip': 'for HOS/AR, length of AR-prediction window [s], H-components, 1st pick', 'tooltip': 'for HOS/AR, length of AR-prediction window [s], H-components, 1st pick',
'value': 0.4, 'value': 0.4,
'namestring': 'AR pred. window H 1'}, 'namestring': 'AR pred. window H 1'},
'tdet2h': {'type': float, 'tdet2h': {'type': float,
'tooltip': 'for HOS/AR, length of AR-determinaton window [s], H-components, 2nd pick', 'tooltip': 'for HOS/AR, length of AR-determinaton window [s], H-components, 2nd pick',
'value': 0.6, 'value': 0.6,
'namestring': 'AR det. window H 2'}, 'namestring': 'AR det. window H 2'},
'tpred2h': {'type': float, 'tpred2h': {'type': float,
'tooltip': 'for HOS/AR, length of AR-prediction window [s], H-components, 2nd pick', 'tooltip': 'for HOS/AR, length of AR-prediction window [s], H-components, 2nd pick',
'value': 0.3, 'value': 0.3,
'namestring': 'AR pred. window H 2'}, 'namestring': 'AR pred. window H 2'},
'Sarorder': {'type': int, 'Sarorder': {'type': int,
'tooltip': 'for AR-picker, order of AR process of H-components', 'tooltip': 'for AR-picker, order of AR process of H-components',
'value': 4, 'value': 4,
'namestring': 'AR order S'}, 'namestring': 'AR order S'},
'Srecalcwin': {'type': float, 'Srecalcwin': {'type': float,
'tooltip': 'for AR-picker, window length [s] for recalculation of CF (2nd pick) (H)', 'tooltip': 'for AR-picker, window length [s] for recalculation of CF (2nd pick) (H)',
'value': 5.0, 'value': 5.0,
'namestring': 'Recal. window S'}, 'namestring': 'Recal. window S'},
'pickwinS': {'type': float, 'pickwinS': {'type': float,
'tooltip': 'for initial AIC pick, length of S-pick window [s]', 'tooltip': 'for initial AIC pick, length of S-pick window [s]',
'value': 3.0, 'value': 3.0,
'namestring': 'AIC window S'}, 'namestring': 'AIC window S'},
'tsnrh': {'type': (float, float, float, float), 'tsnrh': {'type': (float, float, float, float),
'tooltip': 'for ARH/AR3, window lengths for SNR-and slope estimation [tnoise, tsafetey, tsignal, tslope] [s]', 'tooltip': 'for ARH/AR3, window lengths for SNR-and slope estimation [tnoise, tsafetey, tsignal, tslope] [s]',
'value': (2, 0.2, 1.5, 0.5), 'value': (2, 0.2, 1.5, 0.5),
'namestring': ('SNR windows S', 'Noise', 'Safety', 'Signal', 'Slope')}, 'namestring': ('SNR windows S', 'Noise', 'Safety', 'Signal', 'Slope')},
'aictsmoothS': {'type': float, 'aictsmoothS': {'type': float,
'tooltip': 'for AIC-picker, take average of samples for smoothing of AIC-function [s]', 'tooltip': 'for AIC-picker, take average of samples for smoothing of AIC-function [s]',
'value': 0.5, 'value': 0.5,
'namestring': 'AIC smooth S'}, 'namestring': 'AIC smooth S'},
'tsmoothS': {'type': float, 'tsmoothS': {'type': float,
'tooltip': 'for AR-picker, take average of samples for smoothing CF [s] (S)', 'tooltip': 'for AR-picker, take average of samples for smoothing CF [s] (S)',
'value': 0.7, 'value': 0.7,
'namestring': 'CF smooth S'}, 'namestring': 'CF smooth S'},
'ausS': {'type': float, 'ausS': {'type': float,
'tooltip': 'for HOS/AR, artificial uplift of samples (aus) of CF (S)', 'tooltip': 'for HOS/AR, artificial uplift of samples (aus) of CF (S)',
'value': 0.9, 'value': 0.9,
'namestring': 'Artificial uplift S'}, 'namestring': 'Artificial uplift S'},
'nfacS': {'type': float, 'nfacS': {'type': float,
'tooltip': 'for AR-picker, noise factor for noise level determination (S)', 'tooltip': 'for AR-picker, noise factor for noise level determination (S)',
'value': 1.5, 'value': 1.5,
'namestring': 'Noise factor S'}, 'namestring': 'Noise factor S'},
'minfmweight': {'type': int, 'minfmweight': {'type': int,
'tooltip': 'minimum required P weight for first-motion determination', 'tooltip': 'minimum required P weight for first-motion determination',
'value': 1, 'value': 1,
'namestring': 'Min. P weight'}, 'namestring': 'Min. P weight'},
'minFMSNR': {'type': float, 'minFMSNR': {'type': float,
'tooltip': 'miniumum required SNR for first-motion determination', 'tooltip': 'miniumum required SNR for first-motion determination',
'value': 2., 'value': 2.,
'namestring': 'Min SNR'}, 'namestring': 'Min SNR'},
'fmpickwin': {'type': float, 'fmpickwin': {'type': float,
'tooltip': 'pick window around P onset for calculating zero crossings', 'tooltip': 'pick window around P onset for calculating zero crossings',
'value': 0.2, 'value': 0.2,
'namestring': 'Zero crossings window'}, 'namestring': 'Zero crossings window'},
'timeerrorsP': {'type': (float, float, float, float), 'timeerrorsP': {'type': (float, float, float, float),
'tooltip': 'discrete time errors [s] corresponding to picking weights [0 1 2 3] for P', 'tooltip': 'discrete time errors [s] corresponding to picking weights [0 1 2 3] for P',
'value': (0.01, 0.02, 0.04, 0.08), 'value': (0.01, 0.02, 0.04, 0.08),
'namestring': ('Time errors P', '0', '1', '2', '3')}, 'namestring': ('Time errors P', '0', '1', '2', '3')},
'timeerrorsS': {'type': (float, float, float, float), 'timeerrorsS': {'type': (float, float, float, float),
'tooltip': 'discrete time errors [s] corresponding to picking weights [0 1 2 3] for S', 'tooltip': 'discrete time errors [s] corresponding to picking weights [0 1 2 3] for S',
'value': (0.04, 0.08, 0.16, 0.32), 'value': (0.04, 0.08, 0.16, 0.32),
'namestring': ('Time errors S', '0', '1', '2', '3')}, 'namestring': ('Time errors S', '0', '1', '2', '3')},
'minAICPslope': {'type': float, 'minAICPslope': {'type': float,
'tooltip': 'below this slope [counts/s] the initial P pick is rejected', 'tooltip': 'below this slope [counts/s] the initial P pick is rejected',
'value': 0.8, 'value': 0.8,
'namestring': 'Min. slope P'}, 'namestring': 'Min. slope P'},
'minAICPSNR': {'type': float, 'minAICPSNR': {'type': float,
'tooltip': 'below this SNR the initial P pick is rejected', 'tooltip': 'below this SNR the initial P pick is rejected',
'value': 1.1, 'value': 1.1,
'namestring': 'Min. SNR P'}, 'namestring': 'Min. SNR P'},
'minAICSslope': {'type': float, 'minAICSslope': {'type': float,
'tooltip': 'below this slope [counts/s] the initial S pick is rejected', 'tooltip': 'below this slope [counts/s] the initial S pick is rejected',
'value': 1., 'value': 1.,
'namestring': 'Min. slope S'}, 'namestring': 'Min. slope S'},
'minAICSSNR': {'type': float, 'minAICSSNR': {'type': float,
'tooltip': 'below this SNR the initial S pick is rejected', 'tooltip': 'below this SNR the initial S pick is rejected',
'value': 1.5, 'value': 1.5,
'namestring': 'Min. SNR S'}, 'namestring': 'Min. SNR S'},
'minsiglength': {'type': float, 'minsiglength': {'type': float,
'tooltip': 'length of signal part for which amplitudes must exceed noiselevel [s]', 'tooltip': 'length of signal part for which amplitudes must exceed noiselevel [s]',
'value': 1., 'value': 1.,
'namestring': 'Min. signal length'}, 'namestring': 'Min. signal length'},
'noisefactor': {'type': float, 'noisefactor': {'type': float,
'tooltip': 'noiselevel*noisefactor=threshold', 'tooltip': 'noiselevel*noisefactor=threshold',
'value': 1.0, 'value': 1.0,
'namestring': 'Noise factor'}, 'namestring': 'Noise factor'},
'minpercent': {'type': float, 'minpercent': {'type': float,
'tooltip': 'required percentage of amplitudes exceeding threshold', 'tooltip': 'required percentage of amplitudes exceeding threshold',
'value': 10., 'value': 10.,
'namestring': 'Min amplitude [%]'}, 'namestring': 'Min amplitude [%]'},
'zfac': {'type': float, 'zfac': {'type': float,
'tooltip': 'P-amplitude must exceed at least zfac times RMS-S amplitude', 'tooltip': 'P-amplitude must exceed at least zfac times RMS-S amplitude',
'value': 1.5, 'value': 1.5,
'namestring': 'Z factor'}, 'namestring': 'Z factor'},
'mdttolerance': {'type': float, 'mdttolerance': {'type': float,
'tooltip': 'maximum allowed deviation of P picks from median [s]', 'tooltip': 'maximum allowed deviation of P picks from median [s]',
'value': 6.0, 'value': 6.0,
'namestring': 'Median tolerance'}, 'namestring': 'Median tolerance'},
'wdttolerance': {'type': float, 'wdttolerance': {'type': float,
'tooltip': 'maximum allowed deviation from Wadati-diagram', 'tooltip': 'maximum allowed deviation from Wadati-diagram',
'value': 1.0, 'value': 1.0,
'namestring': 'Wadati tolerance'}, 'namestring': 'Wadati tolerance'},
'WAscaling': {'type': (float, float, float), 'WAscaling': {'type': (float, float, float),
'tooltip': 'Scaling relation (log(Ao)+Alog(r)+Br+C) of Wood-Anderson amplitude Ao [nm] \ 'tooltip': 'Scaling relation (log(Ao)+Alog(r)+Br+C) of Wood-Anderson amplitude Ao [nm] \
If zeros are set, original Richter magnitude is calculated!', If zeros are set, original Richter magnitude is calculated!',
@ -357,30 +357,30 @@ defaults = {'rootpath': {'type': str,
If zeros are set, no scaling of network magnitude is applied!', If zeros are set, no scaling of network magnitude is applied!',
'value': (0., 0.), 'value': (0., 0.),
'namestring': ('Local mag. scaling', '', '')}, 'namestring': ('Local mag. scaling', '', '')},
'minfreq': {'type': (float, float), 'minfreq': {'type': (float, float),
'tooltip': 'Lower filter frequency [P, S]', 'tooltip': 'Lower filter frequency [P, S]',
'value': (1.0, 1.0), 'value': (1.0, 1.0),
'namestring': ('Lower freq.', 'P', 'S')}, 'namestring': ('Lower freq.', 'P', 'S')},
'maxfreq': {'type': (float, float), 'maxfreq': {'type': (float, float),
'tooltip': 'Upper filter frequency [P, S]', 'tooltip': 'Upper filter frequency [P, S]',
'value': (10.0, 10.0), 'value': (10.0, 10.0),
'namestring': ('Upper freq.', 'P', 'S')}, 'namestring': ('Upper freq.', 'P', 'S')},
'filter_order': {'type': (int, int), 'filter_order': {'type': (int, int),
'tooltip': 'filter order [P, S]', 'tooltip': 'filter order [P, S]',
'value': (2, 2), 'value': (2, 2),
'namestring': ('Order', 'P', 'S')}, 'namestring': ('Order', 'P', 'S')},
'filter_type': {'type': (str, str), 'filter_type': {'type': (str, str),
'tooltip': 'filter type (bandpass, bandstop, lowpass, highpass) [P, S]', 'tooltip': 'filter type (bandpass, bandstop, lowpass, highpass) [P, S]',
'value': ('bandpass' , 'bandpass'), 'value': ('bandpass', 'bandpass'),
'namestring': ('Type', 'P', 'S')} 'namestring': ('Type', 'P', 'S')}
} }
settings_main={ settings_main = {
'dirs':[ 'dirs': [
'rootpath', 'rootpath',
'datapath', 'datapath',
'database', 'database',
@ -388,26 +388,26 @@ settings_main={
'invdir', 'invdir',
'datastructure', 'datastructure',
'apverbose'], 'apverbose'],
'nlloc':[ 'nlloc': [
'nllocbin', 'nllocbin',
'nllocroot', 'nllocroot',
'phasefile', 'phasefile',
'ctrfile', 'ctrfile',
'ttpatter', 'ttpatter',
'outpatter'], 'outpatter'],
'smoment':[ 'smoment': [
'vp', 'vp',
'rho', 'rho',
'Qp'], 'Qp'],
'localmag':[ 'localmag': [
'WAscaling', 'WAscaling',
'magscaling'], 'magscaling'],
'filter':[ 'filter': [
'minfreq', 'minfreq',
'maxfreq', 'maxfreq',
'filter_order', 'filter_order',
'filter_type'], 'filter_type'],
'pick':[ 'pick': [
'extent', 'extent',
'pstart', 'pstart',
'pstop', 'pstop',
@ -419,8 +419,8 @@ settings_main={
'bph2'] 'bph2']
} }
settings_special_pick={ settings_special_pick = {
'z':[ 'z': [
'algoP', 'algoP',
'tlta', 'tlta',
'hosorder', 'hosorder',
@ -437,7 +437,7 @@ settings_special_pick={
'tsmoothP', 'tsmoothP',
'ausP', 'ausP',
'nfacP'], 'nfacP'],
'h':[ 'h': [
'algoS', 'algoS',
'tdet1h', 'tdet1h',
'tpred1h', 'tpred1h',
@ -451,11 +451,11 @@ settings_special_pick={
'tsmoothS', 'tsmoothS',
'ausS', 'ausS',
'nfacS'], 'nfacS'],
'fm':[ 'fm': [
'minfmweight', 'minfmweight',
'minFMSNR', 'minFMSNR',
'fmpickwin'], 'fmpickwin'],
'quality':[ 'quality': [
'timeerrorsP', 'timeerrorsP',
'timeerrorsS', 'timeerrorsS',
'minAICPslope', 'minAICPslope',

35
pylot/core/io/inputs.py
View File

@ -1,8 +1,9 @@
#!/usr/bin/env python #!/usr/bin/env python
# -*- coding: utf-8 -*- # -*- coding: utf-8 -*-
from pylot.core.util.errors import ParameterError
from pylot.core.io import default_parameters from pylot.core.io import default_parameters
from pylot.core.util.errors import ParameterError
class PylotParameter(object): class PylotParameter(object):
''' '''
@ -69,13 +70,13 @@ class PylotParameter(object):
# Set default values of parameter names # Set default values of parameter names
def __init_default_paras(self): def __init_default_paras(self):
parameters=default_parameters.defaults parameters = default_parameters.defaults
self.__defaults = parameters self.__defaults = parameters
def __init_subsettings(self): def __init_subsettings(self):
self._settings_main=default_parameters.settings_main self._settings_main = default_parameters.settings_main
self._settings_special_pick=default_parameters.settings_special_pick self._settings_special_pick = default_parameters.settings_special_pick
# String representation of the object # String representation of the object
def __repr__(self): def __repr__(self):
return "PylotParameter('%s')" % self.__filename return "PylotParameter('%s')" % self.__filename
@ -136,13 +137,13 @@ class PylotParameter(object):
return self._settings_special_pick return self._settings_special_pick
def get_all_para_names(self): def get_all_para_names(self):
all_names=[] all_names = []
all_names += self.get_main_para_names()['dirs'] all_names += self.get_main_para_names()['dirs']
all_names += self.get_main_para_names()['nlloc'] all_names += self.get_main_para_names()['nlloc']
all_names += self.get_main_para_names()['smoment'] all_names += self.get_main_para_names()['smoment']
all_names += self.get_main_para_names()['localmag'] all_names += self.get_main_para_names()['localmag']
all_names += self.get_main_para_names()['pick'] all_names += self.get_main_para_names()['pick']
all_names += self.get_main_para_names()['filter'] all_names += self.get_main_para_names()['filter']
all_names += self.get_special_para_names()['z'] all_names += self.get_special_para_names()['z']
all_names += self.get_special_para_names()['h'] all_names += self.get_special_para_names()['h']
all_names += self.get_special_para_names()['fm'] all_names += self.get_special_para_names()['fm']
@ -156,14 +157,14 @@ class PylotParameter(object):
message = 'Type check failed for param: {}, is type: {}, expected type:{}' message = 'Type check failed for param: {}, is type: {}, expected type:{}'
message = message.format(param, is_type, expect_type) message = message.format(param, is_type, expect_type)
print(Warning(message)) print(Warning(message))
def setParamKV(self, param, value): def setParamKV(self, param, value):
self.__setitem__(param, value) self.__setitem__(param, value)
def setParam(self, **kwargs): def setParam(self, **kwargs):
for key in kwargs: for key in kwargs:
self.__setitem__(key, kwargs[key]) self.__setitem__(key, kwargs[key])
@staticmethod @staticmethod
def _printParameterError(errmsg): def _printParameterError(errmsg):
print('ParameterError:\n non-existent parameter %s' % errmsg) print('ParameterError:\n non-existent parameter %s' % errmsg)
@ -172,7 +173,7 @@ class PylotParameter(object):
defaults = self.get_defaults() defaults = self.get_defaults()
for param in defaults: for param in defaults:
self.setParamKV(param, defaults[param]['value']) self.setParamKV(param, defaults[param]['value'])
def from_file(self, fnin=None): def from_file(self, fnin=None):
if not fnin: if not fnin:
if self.__filename is not None: if self.__filename is not None:
@ -225,9 +226,9 @@ class PylotParameter(object):
# for key, value in self.iteritems(): # for key, value in self.iteritems():
# lines.append('{key}\t{value}\n'.format(key=key, value=value)) # lines.append('{key}\t{value}\n'.format(key=key, value=value))
# fid_out.writelines(lines) # fid_out.writelines(lines)
header = ('%This is a parameter input file for PyLoT/autoPyLoT.\n'+ header = ('%This is a parameter input file for PyLoT/autoPyLoT.\n' +
'%All main and special settings regarding data handling\n'+ '%All main and special settings regarding data handling\n' +
'%and picking are to be set here!\n'+ '%and picking are to be set here!\n' +
'%Parameters are optimized for %{} data sets!\n'.format(self.get_main_para_names()['pick'][0])) '%Parameters are optimized for %{} data sets!\n'.format(self.get_main_para_names()['pick'][0]))
separator = '%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n' separator = '%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%\n'
@ -244,14 +245,14 @@ class PylotParameter(object):
'filter settings', separator) 'filter settings', separator)
self.write_section(fid_out, self.get_main_para_names()['pick'], self.write_section(fid_out, self.get_main_para_names()['pick'],
'common settings picker', separator) 'common settings picker', separator)
fid_out.write(('#special settings for calculating CF#\n'+ fid_out.write(('#special settings for calculating CF#\n' +
'%!!Edit the following only if you know what you are doing!!%\n')) '%!!Edit the following only if you know what you are doing!!%\n'))
self.write_section(fid_out, self.get_special_para_names()['z'], self.write_section(fid_out, self.get_special_para_names()['z'],
'Z-component', None) 'Z-component', None)
self.write_section(fid_out, self.get_special_para_names()['h'], self.write_section(fid_out, self.get_special_para_names()['h'],
'H-components', None) 'H-components', None)
self.write_section(fid_out, self.get_special_para_names()['fm'], self.write_section(fid_out, self.get_special_para_names()['fm'],
'first-motion picker', None) 'first-motion picker', None)
self.write_section(fid_out, self.get_special_para_names()['quality'], self.write_section(fid_out, self.get_special_para_names()['quality'],
'quality assessment', None) 'quality assessment', None)
@ -267,7 +268,7 @@ class PylotParameter(object):
if type(value) == list or type(value) == tuple: if type(value) == list or type(value) == tuple:
value_tmp = '' value_tmp = ''
for vl in value: for vl in value:
value_tmp+= '{} '.format(vl) value_tmp += '{} '.format(vl)
value = value_tmp value = value_tmp
tooltip = self.get_defaults()[name]['tooltip'] tooltip = self.get_defaults()[name]['tooltip']
if not len(str(value)) > l_val: if not len(str(value)) > l_val:
@ -283,7 +284,7 @@ class PylotParameter(object):
ttip = '%{:<{}}\n'.format(tooltip, l_ttip) ttip = '%{:<{}}\n'.format(tooltip, l_ttip)
else: else:
ttip = '%{}\n'.format(tooltip) ttip = '%{}\n'.format(tooltip)
line = value+name+ttip line = value + name + ttip
fid.write(line) fid.write(line)

351
pylot/core/io/phases.py
View File

@ -2,22 +2,23 @@
# -*- coding: utf-8 -*- # -*- coding: utf-8 -*-
import glob import glob
import obspy.core.event as ope
from obspy.core.event import read_events
import os import os
import scipy.io as sio import warnings
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
import numpy as np import numpy as np
import warnings import obspy.core.event as ope
import scipy.io as sio
from obspy.core import UTCDateTime from obspy.core import UTCDateTime
from obspy.core.event import read_events
from obspy.core.util import AttribDict from obspy.core.util import AttribDict
from pylot.core.io.inputs import PylotParameter from pylot.core.io.inputs import PylotParameter
from pylot.core.io.location import create_arrival, create_event, \ from pylot.core.io.location import create_event, \
create_magnitude, create_origin, create_pick create_magnitude
from pylot.core.pick.utils import select_for_phase from pylot.core.pick.utils import select_for_phase
from pylot.core.util.utils import getOwner, full_range, four_digits from pylot.core.util.utils import getOwner, full_range, four_digits
def add_amplitudes(event, amplitudes): def add_amplitudes(event, amplitudes):
amplitude_list = [] amplitude_list = []
for pick in event.picks: for pick in event.picks:
@ -36,6 +37,7 @@ def add_amplitudes(event, amplitudes):
event.amplitudes = amplitude_list event.amplitudes = amplitude_list
return event return event
def readPILOTEvent(phasfn=None, locfn=None, authority_id='RUB', **kwargs): def readPILOTEvent(phasfn=None, locfn=None, authority_id='RUB', **kwargs):
""" """
readPILOTEvent - function readPILOTEvent - function
@ -203,7 +205,7 @@ def picksdict_from_picks(evt):
try: try:
onsets = picks[station] onsets = picks[station]
except KeyError as e: except KeyError as e:
#print(e) # print(e)
onsets = {} onsets = {}
mpp = pick.time mpp = pick.time
spe = pick.time_errors.uncertainty spe = pick.time_errors.uncertainty
@ -233,6 +235,7 @@ def picksdict_from_picks(evt):
picks[station] = onsets.copy() picks[station] = onsets.copy()
return picks return picks
def picks_from_picksdict(picks, creation_info=None): def picks_from_picksdict(picks, creation_info=None):
picks_list = list() picks_list = list()
for station, onsets in picks.items(): for station, onsets in picks.items():
@ -266,8 +269,8 @@ def picks_from_picksdict(picks, creation_info=None):
pick.phase_hint = label pick.phase_hint = label
pick.method_id = ope.ResourceIdentifier(id=picker) pick.method_id = ope.ResourceIdentifier(id=picker)
pick.waveform_id = ope.WaveformStreamID(station_code=station, pick.waveform_id = ope.WaveformStreamID(station_code=station,
channel_code=ccode, channel_code=ccode,
network_code=ncode) network_code=ncode)
try: try:
polarity = phase['fm'] polarity = phase['fm']
if polarity == 'U' or '+': if polarity == 'U' or '+':
@ -277,7 +280,7 @@ def picks_from_picksdict(picks, creation_info=None):
else: else:
pick.polarity = 'undecidable' pick.polarity = 'undecidable'
except KeyError as e: except KeyError as e:
if 'fm' in str(e): # no polarity information found for this phase if 'fm' in str(e): # no polarity information found for this phase
pass pass
else: else:
raise e raise e
@ -289,7 +292,7 @@ def reassess_pilot_db(root_dir, db_dir, out_dir=None, fn_param=None, verbosity=0
import glob import glob
db_root = os.path.join(root_dir, db_dir) db_root = os.path.join(root_dir, db_dir)
evt_list = glob.glob1(db_root,'e????.???.??') evt_list = glob.glob1(db_root, 'e????.???.??')
for evt in evt_list: for evt in evt_list:
if verbosity > 0: if verbosity > 0:
@ -297,7 +300,6 @@ def reassess_pilot_db(root_dir, db_dir, out_dir=None, fn_param=None, verbosity=0
reassess_pilot_event(root_dir, db_dir, evt, out_dir, fn_param, verbosity) reassess_pilot_event(root_dir, db_dir, evt, out_dir, fn_param, verbosity)
def reassess_pilot_event(root_dir, db_dir, event_id, out_dir=None, fn_param=None, verbosity=0): def reassess_pilot_event(root_dir, db_dir, event_id, out_dir=None, fn_param=None, verbosity=0):
from obspy import read from obspy import read
@ -305,7 +307,6 @@ def reassess_pilot_event(root_dir, db_dir, event_id, out_dir=None, fn_param=None
from pylot.core.pick.utils import earllatepicker from pylot.core.pick.utils import earllatepicker
if fn_param is None: if fn_param is None:
import pylot.core.util.defaults as defaults
fn_param = defaults.AUTOMATIC_DEFAULTS fn_param = defaults.AUTOMATIC_DEFAULTS
default = PylotParameter(fn_param, verbosity) default = PylotParameter(fn_param, verbosity)
@ -339,7 +340,8 @@ def reassess_pilot_event(root_dir, db_dir, event_id, out_dir=None, fn_param=None
except Exception as e: except Exception as e:
if 'No file matching file pattern:' in e.message: if 'No file matching file pattern:' in e.message:
if verbosity > 0: if verbosity > 0:
warnings.warn('no waveform data found for station {station}'.format(station=station), RuntimeWarning) warnings.warn('no waveform data found for station {station}'.format(station=station),
RuntimeWarning)
datacheck.append(fn_pattern + ' (no data)\n') datacheck.append(fn_pattern + ' (no data)\n')
continue continue
else: else:
@ -395,7 +397,7 @@ def reassess_pilot_event(root_dir, db_dir, event_id, out_dir=None, fn_param=None
os.makedirs(out_dir) os.makedirs(out_dir)
fnout_prefix = os.path.join(out_dir, 'PyLoT_{0}.'.format(event_id)) fnout_prefix = os.path.join(out_dir, 'PyLoT_{0}.'.format(event_id))
evt.write(fnout_prefix + 'xml', format='QUAKEML') evt.write(fnout_prefix + 'xml', format='QUAKEML')
#evt.write(fnout_prefix + 'cnv', format='VELEST') # evt.write(fnout_prefix + 'cnv', format='VELEST')
def writephases(arrivals, fformat, filename, parameter, eventinfo=None): def writephases(arrivals, fformat, filename, parameter, eventinfo=None):
@ -424,10 +426,10 @@ def writephases(arrivals, fformat, filename, parameter, eventinfo=None):
:param: eventinfo, optional, needed for VELEST-cnv file :param: eventinfo, optional, needed for VELEST-cnv file
and FOCMEC- and HASH-input files and FOCMEC- and HASH-input files
:type: `obspy.core.event.Event` object :type: `obspy.core.event.Event` object
""" """
if fformat == 'NLLoc': if fformat == 'NLLoc':
print ("Writing phases to %s for NLLoc" % filename) print("Writing phases to %s for NLLoc" % filename)
fid = open("%s" % filename, 'w') fid = open("%s" % filename, 'w')
# write header # write header
fid.write('# EQEVENT: %s Label: EQ%s Loc: X 0.00 Y 0.00 Z 10.00 OT 0.00 \n' % fid.write('# EQEVENT: %s Label: EQ%s Loc: X 0.00 Y 0.00 Z 10.00 OT 0.00 \n' %
@ -451,7 +453,7 @@ def writephases(arrivals, fformat, filename, parameter, eventinfo=None):
ss = onset.second ss = onset.second
ms = onset.microsecond ms = onset.microsecond
ss_ms = ss + ms / 1000000.0 ss_ms = ss + ms / 1000000.0
pweight = 1 # use pick pweight = 1 # use pick
try: try:
if arrivals[key]['P']['weight'] >= 4: if arrivals[key]['P']['weight'] >= 4:
pweight = 0 # do not use pick pweight = 0 # do not use pick
@ -478,7 +480,7 @@ def writephases(arrivals, fformat, filename, parameter, eventinfo=None):
ss = onset.second ss = onset.second
ms = onset.microsecond ms = onset.microsecond
ss_ms = ss + ms / 1000000.0 ss_ms = ss + ms / 1000000.0
sweight = 1 # use pick sweight = 1 # use pick
try: try:
if arrivals[key]['S']['weight'] >= 4: if arrivals[key]['S']['weight'] >= 4:
sweight = 0 # do not use pick sweight = 0 # do not use pick
@ -496,15 +498,15 @@ def writephases(arrivals, fformat, filename, parameter, eventinfo=None):
fid.close() fid.close()
elif fformat == 'HYPO71': elif fformat == 'HYPO71':
print ("Writing phases to %s for HYPO71" % filename) print("Writing phases to %s for HYPO71" % filename)
fid = open("%s" % filename, 'w') fid = open("%s" % filename, 'w')
# write header # write header
fid.write(' %s\n' % fid.write(' %s\n' %
parameter.get('eventID')) parameter.get('eventID'))
for key in arrivals: for key in arrivals:
if arrivals[key]['P']['weight'] < 4: if arrivals[key]['P']['weight'] < 4:
stat = key stat = key
if len(stat) > 4: # HYPO71 handles only 4-string station IDs if len(stat) > 4: # HYPO71 handles only 4-string station IDs
stat = stat[1:5] stat = stat[1:5]
Ponset = arrivals[key]['P']['mpp'] Ponset = arrivals[key]['P']['mpp']
Sonset = arrivals[key]['S']['mpp'] Sonset = arrivals[key]['S']['mpp']
@ -544,36 +546,36 @@ def writephases(arrivals, fformat, filename, parameter, eventinfo=None):
elif sweight >= 2: elif sweight >= 2:
sstr = 'E' sstr = 'E'
fid.write('%-4s%sP%s%d %02d%02d%02d%02d%02d%5.2f %s%sS %d %s\n' % (stat, fid.write('%-4s%sP%s%d %02d%02d%02d%02d%02d%5.2f %s%sS %d %s\n' % (stat,
pstr, pstr,
fm, fm,
pweight, pweight,
year, year,
month, month,
day, day,
hh, hh,
mm, mm,
ss_ms, ss_ms,
Sss_ms, Sss_ms,
sstr, sstr,
sweight, sweight,
Ao)) Ao))
else: else:
fid.write('%-4s%sP%s%d %02d%02d%02d%02d%02d%5.2f %s\n' % (stat, fid.write('%-4s%sP%s%d %02d%02d%02d%02d%02d%5.2f %s\n' % (stat,
pstr, pstr,
fm, fm,
pweight, pweight,
year, year,
month, month,
day, day,
hh, hh,
mm, mm,
ss_ms, ss_ms,
Ao)) Ao))
fid.close() fid.close()
elif fformat == 'HYPOSAT': elif fformat == 'HYPOSAT':
print ("Writing phases to %s for HYPOSAT" % filename) print("Writing phases to %s for HYPOSAT" % filename)
fid = open("%s" % filename, 'w') fid = open("%s" % filename, 'w')
# write header # write header
fid.write('%s, event %s \n' % (parameter.get('database'), parameter.get('eventID'))) fid.write('%s, event %s \n' % (parameter.get('database'), parameter.get('eventID')))
@ -595,7 +597,7 @@ def writephases(arrivals, fformat, filename, parameter, eventinfo=None):
# use symmetrized picking error as std # use symmetrized picking error as std
# (read the HYPOSAT manual) # (read the HYPOSAT manual)
pstd = arrivals[key]['P']['spe'] pstd = arrivals[key]['P']['spe']
fid.write('%-5s P1 %4.0f %02d %02d %02d %02d %05.02f %5.3f -999. 0.00 -999. 0.00\n' fid.write('%-5s P1 %4.0f %02d %02d %02d %02d %05.02f %5.3f -999. 0.00 -999. 0.00\n'
% (key, pyear, pmonth, pday, phh, pmm, Pss, pstd)) % (key, pyear, pmonth, pday, phh, pmm, Pss, pstd))
# S onsets # S onsets
if arrivals[key].has_key('S') and arrivals[key]['S']: if arrivals[key].has_key('S') and arrivals[key]['S']:
@ -610,12 +612,12 @@ def writephases(arrivals, fformat, filename, parameter, eventinfo=None):
sms = Sonset.microsecond sms = Sonset.microsecond
Sss = sss + sms / 1000000.0 Sss = sss + sms / 1000000.0
sstd = arrivals[key]['S']['spe'] sstd = arrivals[key]['S']['spe']
fid.write('%-5s S1 %4.0f %02d %02d %02d %02d %05.02f %5.3f -999. 0.00 -999. 0.00\n' fid.write('%-5s S1 %4.0f %02d %02d %02d %02d %05.02f %5.3f -999. 0.00 -999. 0.00\n'
% (key, syear, smonth, sday, shh, smm, Sss, sstd)) % (key, syear, smonth, sday, shh, smm, Sss, sstd))
fid.close() fid.close()
elif fformat == 'VELEST': elif fformat == 'VELEST':
print ("Writing phases to %s for VELEST" % filename) print("Writing phases to %s for VELEST" % filename)
fid = open("%s" % filename, 'w') fid = open("%s" % filename, 'w')
# get informations needed in cnv-file # get informations needed in cnv-file
# check, whether latitude is N or S and longitude is E or W # check, whether latitude is N or S and longitude is E or W
@ -631,14 +633,14 @@ def writephases(arrivals, fformat, filename, parameter, eventinfo=None):
# get last two integers of origin year # get last two integers of origin year
stime = eventsource['time'] stime = eventsource['time']
if stime.year - 2000 >= 0: if stime.year - 2000 >= 0:
syear = stime.year - 2000 syear = stime.year - 2000
else: else:
syear = stime.year - 1900 syear = stime.year - 1900
ifx = 0 # default value, see VELEST manual, pp. 22-23 ifx = 0 # default value, see VELEST manual, pp. 22-23
# write header # write header
fid.write('%s%02d%02d %02d%02d %05.2f %7.4f%c %8.4f%c %7.2f %6.2f %02.0f 0.0 0.03 1.0 1.0\n' % ( fid.write('%s%02d%02d %02d%02d %05.2f %7.4f%c %8.4f%c %7.2f %6.2f %02.0f 0.0 0.03 1.0 1.0\n' % (
syear, stime.month, stime.day, stime.hour, stime.minute, stime.second, eventsource['latitude'], syear, stime.month, stime.day, stime.hour, stime.minute, stime.second, eventsource['latitude'],
cns, eventsource['longitude'], cew, eventsource['depth'],eventinfo.magnitudes[0]['mag'], ifx)) cns, eventsource['longitude'], cew, eventsource['depth'], eventinfo.magnitudes[0]['mag'], ifx))
n = 0 n = 0
for key in arrivals: for key in arrivals:
# P onsets # P onsets
@ -646,33 +648,33 @@ def writephases(arrivals, fformat, filename, parameter, eventinfo=None):
if arrivals[key]['P']['weight'] < 4: if arrivals[key]['P']['weight'] < 4:
n += 1 n += 1
stat = key stat = key
if len(stat) > 4: # VELEST handles only 4-string station IDs if len(stat) > 4: # VELEST handles only 4-string station IDs
stat = stat[1:5] stat = stat[1:5]
Ponset = arrivals[key]['P']['mpp'] Ponset = arrivals[key]['P']['mpp']
Pweight = arrivals[key]['P']['weight'] Pweight = arrivals[key]['P']['weight']
Prt = Ponset - stime # onset time relative to source time Prt = Ponset - stime # onset time relative to source time
if n % 6 is not 0: if n % 6 is not 0:
fid.write('%-4sP%d%6.2f' % (stat, Pweight, Prt)) fid.write('%-4sP%d%6.2f' % (stat, Pweight, Prt))
else: else:
fid.write('%-4sP%d%6.2f\n' % (stat, Pweight, Prt)) fid.write('%-4sP%d%6.2f\n' % (stat, Pweight, Prt))
# S onsets # S onsets
if arrivals[key].has_key('S'): if arrivals[key].has_key('S'):
if arrivals[key]['S']['weight'] < 4: if arrivals[key]['S']['weight'] < 4:
n += 1 n += 1
stat = key stat = key
if len(stat) > 4: # VELEST handles only 4-string station IDs if len(stat) > 4: # VELEST handles only 4-string station IDs
stat = stat[1:5] stat = stat[1:5]
Sonset = arrivals[key]['S']['mpp'] Sonset = arrivals[key]['S']['mpp']
Sweight = arrivals[key]['S']['weight'] Sweight = arrivals[key]['S']['weight']
Srt = Ponset - stime # onset time relative to source time Srt = Ponset - stime # onset time relative to source time
if n % 6 is not 0: if n % 6 is not 0:
fid.write('%-4sS%d%6.2f' % (stat, Sweight, Srt)) fid.write('%-4sS%d%6.2f' % (stat, Sweight, Srt))
else: else:
fid.write('%-4sS%d%6.2f\n' % (stat, Sweight, Srt)) fid.write('%-4sS%d%6.2f\n' % (stat, Sweight, Srt))
fid.close() fid.close()
elif fformat == 'hypoDD': elif fformat == 'hypoDD':
print ("Writing phases to %s for hypoDD" % filename) print("Writing phases to %s for hypoDD" % filename)
fid = open("%s" % filename, 'w') fid = open("%s" % filename, 'w')
# get event information needed for hypoDD-phase file # get event information needed for hypoDD-phase file
eventsource = eventinfo.origins[0] eventsource = eventinfo.origins[0]
@ -681,59 +683,62 @@ def writephases(arrivals, fformat, filename, parameter, eventinfo=None):
hddID = event.split('.')[0][1:5] hddID = event.split('.')[0][1:5]
# write header # write header
fid.write('# %d %d %d %d %d %5.2f %7.4f +%6.4f %7.4f %4.2f 0.1 0.5 %4.2f %s\n' % ( fid.write('# %d %d %d %d %d %5.2f %7.4f +%6.4f %7.4f %4.2f 0.1 0.5 %4.2f %s\n' % (
stime.year, stime.month, stime.day, stime.hour, stime.minute, stime.second, stime.year, stime.month, stime.day, stime.hour, stime.minute, stime.second,
eventsource['latitude'], eventsource['longitude'], eventsource['depth'] / 1000, eventsource['latitude'], eventsource['longitude'], eventsource['depth'] / 1000,
eventinfo.magnitudes[0]['mag'], eventsource['quality']['standard_error'], hddID)) eventinfo.magnitudes[0]['mag'], eventsource['quality']['standard_error'], hddID))
for key in arrivals: for key in arrivals:
if arrivals[key].has_key('P'): if arrivals[key].has_key('P'):
# P onsets # P onsets
if arrivals[key]['P']['weight'] < 4: if arrivals[key]['P']['weight'] < 4:
Ponset = arrivals[key]['P']['mpp'] Ponset = arrivals[key]['P']['mpp']
Prt = Ponset - stime # onset time relative to source time Prt = Ponset - stime # onset time relative to source time
fid.write('%s %6.3f 1 P\n' % (key, Prt)) fid.write('%s %6.3f 1 P\n' % (key, Prt))
# S onsets # S onsets
if arrivals[key]['S']['weight'] < 4: if arrivals[key]['S']['weight'] < 4:
Sonset = arrivals[key]['S']['mpp'] Sonset = arrivals[key]['S']['mpp']
Srt = Sonset - stime # onset time relative to source time Srt = Sonset - stime # onset time relative to source time
fid.write('%-5s %6.3f 1 S\n' % (key, Srt)) fid.write('%-5s %6.3f 1 S\n' % (key, Srt))
fid.close() fid.close()
elif fformat == 'FOCMEC': elif fformat == 'FOCMEC':
print ("Writing phases to %s for FOCMEC" % filename) print("Writing phases to %s for FOCMEC" % filename)
fid = open("%s" % filename, 'w') fid = open("%s" % filename, 'w')
# get event information needed for FOCMEC-input file # get event information needed for FOCMEC-input file
eventsource = eventinfo.origins[0] eventsource = eventinfo.origins[0]
stime = eventsource['time'] stime = eventsource['time']
# write header line including event information # write header line including event information
fid.write('%s %d%02d%02d%02d%02d%02.0f %7.4f %6.4f %3.1f %3.1f\n' % (parameter.get('eventID'), fid.write('%s %d%02d%02d%02d%02d%02.0f %7.4f %6.4f %3.1f %3.1f\n' % (parameter.get('eventID'),
stime.year, stime.month, stime.day, stime.hour, stime.minute, stime.second, stime.year, stime.month, stime.day,
eventsource['latitude'], eventsource['longitude'], eventsource['depth'] / 1000, stime.hour, stime.minute, stime.second,
eventinfo.magnitudes[0]['mag'])) eventsource['latitude'],
eventsource['longitude'],
eventsource['depth'] / 1000,
eventinfo.magnitudes[0]['mag']))
picks = eventinfo.picks picks = eventinfo.picks
for key in arrivals: for key in arrivals:
if arrivals[key].has_key('P'): if arrivals[key].has_key('P'):
if arrivals[key]['P']['weight'] < 4 and arrivals[key]['P']['fm'] is not None: if arrivals[key]['P']['weight'] < 4 and arrivals[key]['P']['fm'] is not None:
stat = key stat = key
for i in range(len(picks)): for i in range(len(picks)):
station = picks[i].waveform_id.station_code station = picks[i].waveform_id.station_code
if station == stat: if station == stat:
# get resource ID # get resource ID
resid_picks = picks[i].get('resource_id') resid_picks = picks[i].get('resource_id')
# find same ID in eventinfo # find same ID in eventinfo
# there it is the pick_id!! # there it is the pick_id!!
for j in range(len(eventinfo.origins[0].arrivals)): for j in range(len(eventinfo.origins[0].arrivals)):
resid_eventinfo = eventinfo.origins[0].arrivals[j].get('pick_id') resid_eventinfo = eventinfo.origins[0].arrivals[j].get('pick_id')
if resid_eventinfo == resid_picks and eventinfo.origins[0].arrivals[j].phase == 'P': if resid_eventinfo == resid_picks and eventinfo.origins[0].arrivals[j].phase == 'P':
if len(stat) > 4: # FOCMEC handles only 4-string station IDs if len(stat) > 4: # FOCMEC handles only 4-string station IDs
stat = stat[1:5] stat = stat[1:5]
az = eventinfo.origins[0].arrivals[j].get('azimuth') az = eventinfo.origins[0].arrivals[j].get('azimuth')
inz = eventinfo.origins[0].arrivals[j].get('takeoff_angle') inz = eventinfo.origins[0].arrivals[j].get('takeoff_angle')
fid.write('%-4s %6.2f %6.2f%s \n' % (stat, fid.write('%-4s %6.2f %6.2f%s \n' % (stat,
az, az,
inz, inz,
arrivals[key]['P']['fm'])) arrivals[key]['P']['fm']))
break break
fid.close() fid.close()
@ -742,9 +747,9 @@ def writephases(arrivals, fformat, filename, parameter, eventinfo=None):
# HASH-driver 1 and 2 (see HASH manual!) # HASH-driver 1 and 2 (see HASH manual!)
filename1 = filename + 'drv1' + '.phase' filename1 = filename + 'drv1' + '.phase'
filename2 = filename + 'drv2' + '.phase' filename2 = filename + 'drv2' + '.phase'
print ("Writing phases to %s for HASH for HASH-driver 1" % filename1) print("Writing phases to %s for HASH for HASH-driver 1" % filename1)
fid1 = open("%s" % filename1, 'w') fid1 = open("%s" % filename1, 'w')
print ("Writing phases to %s for HASH for HASH-driver 2" % filename2) print("Writing phases to %s for HASH for HASH-driver 2" % filename2)
fid2 = open("%s" % filename2, 'w') fid2 = open("%s" % filename2, 'w')
# get event information needed for HASH-input file # get event information needed for HASH-input file
eventsource = eventinfo.origins[0] eventsource = eventinfo.origins[0]
@ -759,26 +764,32 @@ def writephases(arrivals, fformat, filename, parameter, eventinfo=None):
erz = eventsource.depth_errors['uncertainty'] erz = eventsource.depth_errors['uncertainty']
stime = eventsource['time'] stime = eventsource['time']
if stime.year - 2000 >= 0: if stime.year - 2000 >= 0:
syear = stime.year - 2000 syear = stime.year - 2000
else: else:
syear = stime.year - 1900 syear = stime.year - 1900
picks = eventinfo.picks picks = eventinfo.picks
# write header line including event information # write header line including event information
# for HASH-driver 1 # for HASH-driver 1
fid1.write('%s%02d%02d%02d%02d%5.2f%2dN%5.2f%3dE%5.2f%6.3f%4.2f%5.2f%5.2f%s\n' % (syear, fid1.write('%s%02d%02d%02d%02d%5.2f%2dN%5.2f%3dE%5.2f%6.3f%4.2f%5.2f%5.2f%s\n' % (syear,
stime.month, stime.day, stime.hour, stime.minute, stime.second, stime.month, stime.day,
latdeg, latmin, londeg, lonmin, eventsource['depth'], stime.hour, stime.minute,
eventinfo.magnitudes[0]['mag'], erh, erz, stime.second,
hashID)) latdeg, latmin, londeg,
lonmin, eventsource['depth'],
eventinfo.magnitudes[0][
'mag'], erh, erz,
hashID))
# write header line including event information # write header line including event information
# for HASH-driver 2 # for HASH-driver 2
fid2.write('%d%02d%02d%02d%02d%5.2f%dN%5.2f%3dE%6.2f%5.2f %d %5.2f %5.2f %4.2f %s \n' % (syear, stime.month, stime.day, fid2.write(
stime.hour, stime.minute, stime.second, '%d%02d%02d%02d%02d%5.2f%dN%5.2f%3dE%6.2f%5.2f %d %5.2f %5.2f %4.2f %s \n' % (
latdeg,latmin,londeg, lonmin, syear, stime.month, stime.day,
eventsource['depth'], stime.hour, stime.minute, stime.second,
eventsource['quality']['used_phase_count'], latdeg, latmin, londeg, lonmin,
erh, erz, eventinfo.magnitudes[0]['mag'], eventsource['depth'],
hashID)) eventsource['quality']['used_phase_count'],
erh, erz, eventinfo.magnitudes[0]['mag'],
hashID))
# write phase lines # write phase lines
for key in arrivals: for key in arrivals:
@ -789,36 +800,38 @@ def writephases(arrivals, fformat, filename, parameter, eventinfo=None):
ncode = arrivals[key]['P']['network'] ncode = arrivals[key]['P']['network']
if arrivals[key]['P']['weight'] < 2: if arrivals[key]['P']['weight'] < 2:
Pqual='I' Pqual = 'I'
else: else:
Pqual='E' Pqual = 'E'
for i in range(len(picks)): for i in range(len(picks)):
station = picks[i].waveform_id.station_code station = picks[i].waveform_id.station_code
if station == stat: if station == stat:
# get resource ID # get resource ID
resid_picks = picks[i].get('resource_id') resid_picks = picks[i].get('resource_id')
# find same ID in eventinfo # find same ID in eventinfo
# there it is the pick_id!! # there it is the pick_id!!
for j in range(len(eventinfo.origins[0].arrivals)): for j in range(len(eventinfo.origins[0].arrivals)):
resid_eventinfo = eventinfo.origins[0].arrivals[j].get('pick_id') resid_eventinfo = eventinfo.origins[0].arrivals[j].get('pick_id')
if resid_eventinfo == resid_picks and eventinfo.origins[0].arrivals[j].phase == 'P': if resid_eventinfo == resid_picks and eventinfo.origins[0].arrivals[j].phase == 'P':
if len(stat) > 4: # HASH handles only 4-string station IDs if len(stat) > 4: # HASH handles only 4-string station IDs
stat = stat[1:5] stat = stat[1:5]
az = eventinfo.origins[0].arrivals[j].get('azimuth') az = eventinfo.origins[0].arrivals[j].get('azimuth')
inz = eventinfo.origins[0].arrivals[j].get('takeoff_angle') inz = eventinfo.origins[0].arrivals[j].get('takeoff_angle')
dist = eventinfo.origins[0].arrivals[j].get('distance') dist = eventinfo.origins[0].arrivals[j].get('distance')
# write phase line for HASH-driver 1 # write phase line for HASH-driver 1
fid1.write('%-4s%sP%s%d 0 %3.1f %03d %03d 2 1 %s\n' % (stat, Pqual, arrivals[key]['P']['fm'], arrivals[key]['P']['weight'], fid1.write(
dist, inz, az, ccode)) '%-4s%sP%s%d 0 %3.1f %03d %03d 2 1 %s\n' % (
# write phase line for HASH-driver 2 stat, Pqual, arrivals[key]['P']['fm'], arrivals[key]['P']['weight'],
fid2.write('%-4s %s %s %s %s \n' % ( dist, inz, az, ccode))
stat, # write phase line for HASH-driver 2
ncode, fid2.write('%-4s %s %s %s %s \n' % (
ccode, stat,
Pqual, ncode,
arrivals[key]['P']['fm'])) ccode,
break Pqual,
arrivals[key]['P']['fm']))
break
fid1.write(' %s' % hashID) fid1.write(' %s' % hashID)
fid1.close() fid1.close()
@ -849,6 +862,7 @@ def merge_picks(event, picks):
del time, err, phase, station, network, method del time, err, phase, station, network, method
return event return event
def getQualitiesfromxml(xmlnames, ErrorsP, ErrorsS, plotflag=1): def getQualitiesfromxml(xmlnames, ErrorsP, ErrorsS, plotflag=1):
""" """
Script to get onset uncertainties from Quakeml.xml files created by PyLoT. Script to get onset uncertainties from Quakeml.xml files created by PyLoT.
@ -867,7 +881,7 @@ def getQualitiesfromxml(xmlnames, ErrorsP, ErrorsS, plotflag=1):
Sw2 = [] Sw2 = []
Sw3 = [] Sw3 = []
Sw4 = [] Sw4 = []
for names in xmlnames: for names in xmlnames:
print("Getting onset weights from {}".format(names)) print("Getting onset weights from {}".format(names))
cat = read_events(names) cat = read_events(names)
cat_copy = cat.copy() cat_copy = cat.copy()
@ -881,53 +895,53 @@ def getQualitiesfromxml(xmlnames, ErrorsP, ErrorsS, plotflag=1):
for mpick in arrivals_copy: for mpick in arrivals_copy:
if mpick.phase_hint[0] == 'P': if mpick.phase_hint[0] == 'P':
if ((mpick.waveform_id.station_code == mstation) or \ if ((mpick.waveform_id.station_code == mstation) or \
(mpick.waveform_id.station_code == mstation_ext)) and \ (mpick.waveform_id.station_code == mstation_ext)) and \
((mpick.method_id).split('/')[1] == 'auto') and \ ((mpick.method_id).split('/')[1] == 'auto') and \
(mpick.time_errors['uncertainty'] <= ErrorsP[3]): (mpick.time_errors['uncertainty'] <= ErrorsP[3]):
del mpick del mpick
break break
elif mpick.phase_hint[0] == 'S': elif mpick.phase_hint[0] == 'S':
if ((mpick.waveform_id.station_code == mstation) or \ if ((mpick.waveform_id.station_code == mstation) or \
(mpick.waveform_id.station_code == mstation_ext)) and \ (mpick.waveform_id.station_code == mstation_ext)) and \
((mpick.method_id).split('/')[1] == 'auto') and \ ((mpick.method_id).split('/')[1] == 'auto') and \
(mpick.time_errors['uncertainty'] <= ErrorsS[3]): (mpick.time_errors['uncertainty'] <= ErrorsS[3]):
del mpick del mpick
break break
lendiff = len(arrivals) - len(arrivals_copy) lendiff = len(arrivals) - len(arrivals_copy)
if lendiff is not 0: if lendiff is not 0:
print("Found manual as well as automatic picks, prefered the {} manual ones!".format(lendiff)) print("Found manual as well as automatic picks, prefered the {} manual ones!".format(lendiff))
for Pick in arrivals_copy: for Pick in arrivals_copy:
if Pick.phase_hint[0] == 'P': if Pick.phase_hint[0] == 'P':
if Pick.time_errors.uncertainty <= ErrorsP[0]: if Pick.time_errors.uncertainty <= ErrorsP[0]:
Pw0.append(Pick.time_errors.uncertainty) Pw0.append(Pick.time_errors.uncertainty)
elif (Pick.time_errors.uncertainty > ErrorsP[0]) and \ elif (Pick.time_errors.uncertainty > ErrorsP[0]) and \
(Pick.time_errors.uncertainty <= ErrorsP[1]): (Pick.time_errors.uncertainty <= ErrorsP[1]):
Pw1.append(Pick.time_errors.uncertainty) Pw1.append(Pick.time_errors.uncertainty)
elif (Pick.time_errors.uncertainty > ErrorsP[1]) and \ elif (Pick.time_errors.uncertainty > ErrorsP[1]) and \
(Pick.time_errors.uncertainty <= ErrorsP[2]): (Pick.time_errors.uncertainty <= ErrorsP[2]):
Pw2.append(Pick.time_errors.uncertainty) Pw2.append(Pick.time_errors.uncertainty)
elif (Pick.time_errors.uncertainty > ErrorsP[2]) and \ elif (Pick.time_errors.uncertainty > ErrorsP[2]) and \
(Pick.time_errors.uncertainty <= ErrorsP[3]): (Pick.time_errors.uncertainty <= ErrorsP[3]):
Pw3.append(Pick.time_errors.uncertainty) Pw3.append(Pick.time_errors.uncertainty)
elif Pick.time_errors.uncertainty > ErrorsP[3]: elif Pick.time_errors.uncertainty > ErrorsP[3]:
Pw4.append(Pick.time_errors.uncertainty) Pw4.append(Pick.time_errors.uncertainty)
else: else:
pass pass
elif Pick.phase_hint[0] == 'S': elif Pick.phase_hint[0] == 'S':
if Pick.time_errors.uncertainty <= ErrorsS[0]: if Pick.time_errors.uncertainty <= ErrorsS[0]:
Sw0.append(Pick.time_errors.uncertainty) Sw0.append(Pick.time_errors.uncertainty)
elif (Pick.time_errors.uncertainty > ErrorsS[0]) and \ elif (Pick.time_errors.uncertainty > ErrorsS[0]) and \
(Pick.time_errors.uncertainty <= ErrorsS[1]): (Pick.time_errors.uncertainty <= ErrorsS[1]):
Sw1.append(Pick.time_errors.uncertainty) Sw1.append(Pick.time_errors.uncertainty)
elif (Pick.time_errors.uncertainty > ErrorsS[1]) and \ elif (Pick.time_errors.uncertainty > ErrorsS[1]) and \
(Pick.time_errors.uncertainty <= ErrorsS[2]): (Pick.time_errors.uncertainty <= ErrorsS[2]):
Sw2.append(Pick.time_errors.uncertainty) Sw2.append(Pick.time_errors.uncertainty)
elif (Pick.time_errors.uncertainty > ErrorsS[2]) and \ elif (Pick.time_errors.uncertainty > ErrorsS[2]) and \
(Pick.time_errors.uncertainty <= ErrorsS[3]): (Pick.time_errors.uncertainty <= ErrorsS[3]):
Sw3.append(Pick.time_errors.uncertainty) Sw3.append(Pick.time_errors.uncertainty)
elif Pick.time_errors.uncertainty > ErrorsS[3]: elif Pick.time_errors.uncertainty > ErrorsS[3]:
Sw4.append(Pick.time_errors.uncertainty) Sw4.append(Pick.time_errors.uncertainty)
else: else:
pass pass
else: else:
@ -992,6 +1006,5 @@ def getQualitiesfromxml(xmlnames, ErrorsP, ErrorsS, plotflag=1):
plt.xticks(y_pos, weights) plt.xticks(y_pos, weights)
plt.xlim([-0.5, 4.5]) plt.xlim([-0.5, 4.5])
plt.xlabel('Qualities') plt.xlabel('Qualities')
plt.title('{0} P-Qualities, {1} S-Qualities'.format(numPweights, numSweights)) plt.title('{0} P-Qualities, {1} S-Qualities'.format(numPweights, numSweights))
plt.show() plt.show()

1
pylot/core/loc/focmec.py
View File

@ -6,6 +6,7 @@ from pylot.core.util.version import get_git_version as _getVersionString
__version__ = _getVersionString() __version__ = _getVersionString()
def export(picks, fnout, parameter, eventinfo): def export(picks, fnout, parameter, eventinfo):
''' '''
Take <picks> dictionary and exports picking data to a focmec Take <picks> dictionary and exports picking data to a focmec

1
pylot/core/loc/hash.py
View File

@ -6,6 +6,7 @@ from pylot.core.util.version import get_git_version as _getVersionString
__version__ = _getVersionString() __version__ = _getVersionString()
def export(picks, fnout, parameter, eventinfo): def export(picks, fnout, parameter, eventinfo):
''' '''
Take <picks> dictionary and exports picking data to a HASH Take <picks> dictionary and exports picking data to a HASH

1
pylot/core/loc/hypo71.py
View File

@ -6,6 +6,7 @@ from pylot.core.util.version import get_git_version as _getVersionString
__version__ = _getVersionString() __version__ = _getVersionString()
def export(picks, fnout, parameter): def export(picks, fnout, parameter):
''' '''
Take <picks> dictionary and exports picking data to a HYPO71 Take <picks> dictionary and exports picking data to a HYPO71

1
pylot/core/loc/hypodd.py
View File

@ -6,6 +6,7 @@ from pylot.core.util.version import get_git_version as _getVersionString
__version__ = _getVersionString() __version__ = _getVersionString()
def export(picks, fnout, parameter, eventinfo): def export(picks, fnout, parameter, eventinfo):
''' '''
Take <picks> dictionary and exports picking data to a hypoDD Take <picks> dictionary and exports picking data to a hypoDD

1
pylot/core/loc/hyposat.py
View File

@ -6,6 +6,7 @@ from pylot.core.util.version import get_git_version as _getVersionString
__version__ = _getVersionString() __version__ = _getVersionString()
def export(picks, fnout, parameter): def export(picks, fnout, parameter):
''' '''
Take <picks> dictionary and exports picking data to a HYPOSAT Take <picks> dictionary and exports picking data to a HYPOSAT

11
pylot/core/loc/nll.py
View File

@ -1,9 +1,10 @@
#!/usr/bin/env python #!/usr/bin/env python
# -*- coding: utf-8 -*- # -*- coding: utf-8 -*-
import subprocess
import os
import glob import glob
import os
import subprocess
from obspy import read_events from obspy import read_events
from pylot.core.io.phases import writephases from pylot.core.io.phases import writephases
from pylot.core.util.utils import getPatternLine, runProgram, which from pylot.core.util.utils import getPatternLine, runProgram, which
@ -11,9 +12,11 @@ from pylot.core.util.version import get_git_version as _getVersionString
__version__ = _getVersionString() __version__ = _getVersionString()
class NLLocError(EnvironmentError): class NLLocError(EnvironmentError):
pass pass
def export(picks, fnout, parameter): def export(picks, fnout, parameter):
''' '''
Take <picks> dictionary and exports picking data to a NLLOC-obs Take <picks> dictionary and exports picking data to a NLLOC-obs
@ -58,7 +61,7 @@ def modify_inputs(ctrfn, root, nllocoutn, phasefn, tttn):
locfiles = 'LOCFILES %s NLLOC_OBS %s %s 0\n' % (phasefile, tttable, nllocout) locfiles = 'LOCFILES %s NLLOC_OBS %s %s 0\n' % (phasefile, tttable, nllocout)
# modification of NLLoc-control file # modification of NLLoc-control file
print ("Modifying NLLoc-control file %s ..." % ctrfile) print("Modifying NLLoc-control file %s ..." % ctrfile)
curlocfiles = getPatternLine(ctrfile, 'LOCFILES') curlocfiles = getPatternLine(ctrfile, 'LOCFILES')
nllfile = open(ctrfile, 'r') nllfile = open(ctrfile, 'r')
filedata = nllfile.read() filedata = nllfile.read()
@ -94,7 +97,7 @@ def locate(fnin, infile=None):
def read_location(fn): def read_location(fn):
path, file = os.path.split(fn) path, file = os.path.split(fn)
file = glob.glob1(path, file + '.[0-9]*.grid0.loc.hyp') file = glob.glob1(path, file + '.[0-9]*.grid0.loc.hyp')
if len(file) > 1: if len(file) > 1:
raise IOError('ambiguous location name {0}'.format(file)) raise IOError('ambiguous location name {0}'.format(file))
fn = os.path.join(path, file[0]) fn = os.path.join(path, file[0])

1
pylot/core/loc/velest.py
View File

@ -6,6 +6,7 @@ from pylot.core.util.version import get_git_version as _getVersionString
__version__ = _getVersionString() __version__ = _getVersionString()
def export(picks, fnout, parameter, eventinfo): def export(picks, fnout, parameter, eventinfo):
''' '''
Take <picks> dictionary and exports picking data to a VELEST-cnv Take <picks> dictionary and exports picking data to a VELEST-cnv

58
pylot/core/pick/autopick.py
View File

@ -11,14 +11,14 @@ function conglomerate utils.
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
import numpy as np import numpy as np
from pylot.core.io.data import Data
from pylot.core.io.inputs import PylotParameter from pylot.core.io.inputs import PylotParameter
from pylot.core.pick.picker import AICPicker, PragPicker
from pylot.core.pick.charfuns import CharacteristicFunction from pylot.core.pick.charfuns import CharacteristicFunction
from pylot.core.pick.charfuns import HOScf, AICcf, ARZcf, ARHcf, AR3Ccf from pylot.core.pick.charfuns import HOScf, AICcf, ARZcf, ARHcf, AR3Ccf
from pylot.core.pick.picker import AICPicker, PragPicker
from pylot.core.pick.utils import checksignallength, checkZ4S, earllatepicker, \ from pylot.core.pick.utils import checksignallength, checkZ4S, earllatepicker, \
getSNR, fmpicker, checkPonsets, wadaticheck getSNR, fmpicker, checkPonsets, wadaticheck
from pylot.core.util.utils import getPatternLine, gen_Pool from pylot.core.util.utils import getPatternLine, gen_Pool
from pylot.core.io.data import Data
def autopickevent(data, param, iplot=0, fig_dict=None): def autopickevent(data, param, iplot=0, fig_dict=None):
@ -43,10 +43,10 @@ def autopickevent(data, param, iplot=0, fig_dict=None):
if not iplot: if not iplot:
input_tuples.append((topick, param, apverbose)) input_tuples.append((topick, param, apverbose))
if iplot>0: if iplot > 0:
all_onsets[station] = autopickstation(topick, param, verbose=apverbose, iplot=iplot, fig_dict=fig_dict) all_onsets[station] = autopickstation(topick, param, verbose=apverbose, iplot=iplot, fig_dict=fig_dict)
if iplot>0: if iplot > 0:
print('iPlot Flag active: NO MULTIPROCESSING possible.') print('iPlot Flag active: NO MULTIPROCESSING possible.')
return all_onsets return all_onsets
@ -70,7 +70,7 @@ def autopickevent(data, param, iplot=0, fig_dict=None):
def call_autopickstation(input_tuple): def call_autopickstation(input_tuple):
wfstream, pickparam, verbose = input_tuple wfstream, pickparam, verbose = input_tuple
#multiprocessing not possible with interactive plotting # multiprocessing not possible with interactive plotting
return autopickstation(wfstream, pickparam, verbose, iplot=0) return autopickstation(wfstream, pickparam, verbose, iplot=0)
@ -92,7 +92,7 @@ def autopickstation(wfstream, pickparam, verbose=False, iplot=0, fig_dict=None):
# special parameters for P picking # special parameters for P picking
iplot = iplot iplot = iplot
algoP = pickparam.get('algoP') algoP = pickparam.get('algoP')
pstart = pickparam.get('pstart') pstart = pickparam.get('pstart')
pstop = pickparam.get('pstop') pstop = pickparam.get('pstop')
@ -291,7 +291,7 @@ def autopickstation(wfstream, pickparam, verbose=False, iplot=0, fig_dict=None):
'Skipping control function checkZ4S.' 'Skipping control function checkZ4S.'
if verbose: print(msg) if verbose: print(msg)
else: else:
if iplot>1: if iplot > 1:
if fig_dict: if fig_dict:
fig = fig_dict['checkZ4s'] fig = fig_dict['checkZ4s']
else: else:
@ -364,7 +364,7 @@ def autopickstation(wfstream, pickparam, verbose=False, iplot=0, fig_dict=None):
mpickP, iplot, fig=fig) mpickP, iplot, fig=fig)
else: else:
epickP, lpickP, Perror = earllatepicker(z_copy, nfacP, tsnrz, epickP, lpickP, Perror = earllatepicker(z_copy, nfacP, tsnrz,
mpickP, iplot) mpickP, iplot)
# get SNR # get SNR
[SNRP, SNRPdB, Pnoiselevel] = getSNR(z_copy, tsnrz, mpickP) [SNRP, SNRPdB, Pnoiselevel] = getSNR(z_copy, tsnrz, mpickP)
@ -392,7 +392,7 @@ def autopickstation(wfstream, pickparam, verbose=False, iplot=0, fig_dict=None):
fig = None fig = None
FM = fmpicker(zdat, z_copy, fmpickwin, mpickP, iplot, fig) FM = fmpicker(zdat, z_copy, fmpickwin, mpickP, iplot, fig)
else: else:
FM = fmpicker(zdat, z_copy, fmpickwin, mpickP, iplot) FM = fmpicker(zdat, z_copy, fmpickwin, mpickP, iplot)
else: else:
FM = 'N' FM = 'N'
@ -567,15 +567,15 @@ def autopickstation(wfstream, pickparam, verbose=False, iplot=0, fig_dict=None):
fig = fig_dict['el_S1pick'] fig = fig_dict['el_S1pick']
else: else:
fig = None fig = None
epickS1, lpickS1, Serror1 = earllatepicker(h_copy, nfacS, epickS1, lpickS1, Serror1 = earllatepicker(h_copy, nfacS,
tsnrh, tsnrh,
mpickS, iplot, mpickS, iplot,
fig=fig) fig=fig)
else: else:
epickS1, lpickS1, Serror1 = earllatepicker(h_copy, nfacS, epickS1, lpickS1, Serror1 = earllatepicker(h_copy, nfacS,
tsnrh, tsnrh,
mpickS, iplot) mpickS, iplot)
h_copy[0].data = trH2_filt.data h_copy[0].data = trH2_filt.data
if iplot: if iplot:
if fig_dict: if fig_dict:
@ -706,7 +706,7 @@ def autopickstation(wfstream, pickparam, verbose=False, iplot=0, fig_dict=None):
ax1.plot([aicpick.getpick() - 0.5, aicpick.getpick() + 0.5], ax1.plot([aicpick.getpick() - 0.5, aicpick.getpick() + 0.5],
[-1, -1], 'r') [-1, -1], 'r')
ax1.plot([refPpick.getpick(), refPpick.getpick()], ax1.plot([refPpick.getpick(), refPpick.getpick()],
[-1.3, 1.3], 'r', linewidth=2, label='Final P Pick') [-1.3, 1.3], 'r', linewidth=2, label='Final P Pick')
ax1.plot([refPpick.getpick() - 0.5, refPpick.getpick() + 0.5], ax1.plot([refPpick.getpick() - 0.5, refPpick.getpick() + 0.5],
[1.3, 1.3], 'r', linewidth=2) [1.3, 1.3], 'r', linewidth=2)
ax1.plot([refPpick.getpick() - 0.5, refPpick.getpick() + 0.5], ax1.plot([refPpick.getpick() - 0.5, refPpick.getpick() + 0.5],
@ -714,28 +714,28 @@ def autopickstation(wfstream, pickparam, verbose=False, iplot=0, fig_dict=None):
ax1.plot([lpickP, lpickP], [-1.1, 1.1], 'r--', label='lpp') ax1.plot([lpickP, lpickP], [-1.1, 1.1], 'r--', label='lpp')
ax1.plot([epickP, epickP], [-1.1, 1.1], 'r--', label='epp') ax1.plot([epickP, epickP], [-1.1, 1.1], 'r--', label='epp')
ax1.set_title('%s, %s, P Weight=%d, SNR=%7.2f, SNR[dB]=%7.2f ' ax1.set_title('%s, %s, P Weight=%d, SNR=%7.2f, SNR[dB]=%7.2f '
'Polarity: %s' % (tr_filt.stats.station, 'Polarity: %s' % (tr_filt.stats.station,
tr_filt.stats.channel, tr_filt.stats.channel,
Pweight, Pweight,
SNRP, SNRP,
SNRPdB, SNRPdB,
FM)) FM))
else: else:
ax1.set_title('%s, P Weight=%d, SNR=None, ' ax1.set_title('%s, P Weight=%d, SNR=None, '
'SNRdB=None' % (tr_filt.stats.channel, Pweight)) 'SNRdB=None' % (tr_filt.stats.channel, Pweight))
else: else:
ax1.set_title('%s, %s, P Weight=%d' % (tr_filt.stats.station, ax1.set_title('%s, %s, P Weight=%d' % (tr_filt.stats.station,
tr_filt.stats.channel, tr_filt.stats.channel,
Pweight)) Pweight))
ax1.legend() ax1.legend()
ax1.set_yticks([]) ax1.set_yticks([])
ax1.set_ylim([-1.5, 1.5]) ax1.set_ylim([-1.5, 1.5])
ax1.set_ylabel('Normalized Counts') ax1.set_ylabel('Normalized Counts')
#fig.suptitle(tr_filt.stats.starttime) # fig.suptitle(tr_filt.stats.starttime)
if len(edat[0]) > 1 and len(ndat[0]) > 1 and Sflag == 1: if len(edat[0]) > 1 and len(ndat[0]) > 1 and Sflag == 1:
# plot horizontal traces # plot horizontal traces
ax2 = fig.add_subplot(3,1,2,sharex=ax1) ax2 = fig.add_subplot(3, 1, 2, sharex=ax1)
th1data = np.arange(0, th1data = np.arange(0,
trH1_filt.stats.npts / trH1_filt.stats.npts /
trH1_filt.stats.sampling_rate, trH1_filt.stats.sampling_rate,
@ -750,7 +750,7 @@ def autopickstation(wfstream, pickparam, verbose=False, iplot=0, fig_dict=None):
arhcf1.getCF() / max(arhcf1.getCF()), 'b', label='CF1') arhcf1.getCF() / max(arhcf1.getCF()), 'b', label='CF1')
if aicSflag == 1: if aicSflag == 1:
ax2.plot(arhcf2.getTimeArray(), ax2.plot(arhcf2.getTimeArray(),
arhcf2.getCF() / max(arhcf2.getCF()), 'm', label='CF2') arhcf2.getCF() / max(arhcf2.getCF()), 'm', label='CF2')
ax2.plot( ax2.plot(
[aicarhpick.getpick(), aicarhpick.getpick()], [aicarhpick.getpick(), aicarhpick.getpick()],
[-1, 1], 'g', label='Initial S Onset') [-1, 1], 'g', label='Initial S Onset')
@ -782,9 +782,9 @@ def autopickstation(wfstream, pickparam, verbose=False, iplot=0, fig_dict=None):
ax2.set_yticks([]) ax2.set_yticks([])
ax2.set_ylim([-1.5, 1.5]) ax2.set_ylim([-1.5, 1.5])
ax2.set_ylabel('Normalized Counts') ax2.set_ylabel('Normalized Counts')
#fig.suptitle(trH1_filt.stats.starttime) # fig.suptitle(trH1_filt.stats.starttime)
ax3 = fig.add_subplot(3,1,3, sharex=ax1) ax3 = fig.add_subplot(3, 1, 3, sharex=ax1)
th2data = np.arange(0, th2data = np.arange(0,
trH2_filt.stats.npts / trH2_filt.stats.npts /
trH2_filt.stats.sampling_rate, trH2_filt.stats.sampling_rate,

5
pylot/core/pick/charfuns.py
View File

@ -17,7 +17,6 @@ autoregressive prediction: application ot local and regional distances, Geophys.
:author: MAGS2 EP3 working group :author: MAGS2 EP3 working group
""" """
import matplotlib.pyplot as plt
import numpy as np import numpy as np
from obspy.core import Stream from obspy.core import Stream
@ -466,7 +465,7 @@ class ARHcf(CharacteristicFunction):
# prediction error = CF # prediction error = CF
cf[i + lpred] = np.sqrt(np.sum(np.power(self.xpred[0][i:i + lpred] - xnp[0][i:i + lpred], 2) \ cf[i + lpred] = np.sqrt(np.sum(np.power(self.xpred[0][i:i + lpred] - xnp[0][i:i + lpred], 2) \
+ np.power(self.xpred[1][i:i + lpred] - xnp[1][i:i + lpred], 2)) / ( + np.power(self.xpred[1][i:i + lpred] - xnp[1][i:i + lpred], 2)) / (
2 * lpred)) 2 * lpred))
nn = np.isnan(cf) nn = np.isnan(cf)
if len(nn) > 1: if len(nn) > 1:
cf[nn] = 0 cf[nn] = 0
@ -608,7 +607,7 @@ class AR3Ccf(CharacteristicFunction):
cf[i + lpred] = np.sqrt(np.sum(np.power(self.xpred[0][i:i + lpred] - xnp[0][i:i + lpred], 2) \ cf[i + lpred] = np.sqrt(np.sum(np.power(self.xpred[0][i:i + lpred] - xnp[0][i:i + lpred], 2) \
+ np.power(self.xpred[1][i:i + lpred] - xnp[1][i:i + lpred], 2) \ + np.power(self.xpred[1][i:i + lpred] - xnp[1][i:i + lpred], 2) \
+ np.power(self.xpred[2][i:i + lpred] - xnp[2][i:i + lpred], 2)) / ( + np.power(self.xpred[2][i:i + lpred] - xnp[2][i:i + lpred], 2)) / (
3 * lpred)) 3 * lpred))
nn = np.isnan(cf) nn = np.isnan(cf)
if len(nn) > 1: if len(nn) > 1:
cf[nn] = 0 cf[nn] = 0

18
pylot/core/pick/compare.py
View File

@ -4,11 +4,10 @@
import copy import copy
import operator import operator
import os import os
import numpy as np
import glob
import matplotlib.pyplot as plt
from obspy import read_events
import matplotlib.pyplot as plt
import numpy as np
from obspy import read_events
from pylot.core.io.phases import picksdict_from_picks from pylot.core.io.phases import picksdict_from_picks
from pylot.core.util.pdf import ProbabilityDensityFunction from pylot.core.util.pdf import ProbabilityDensityFunction
from pylot.core.util.utils import find_in_list from pylot.core.util.utils import find_in_list
@ -334,7 +333,7 @@ class PDFDictionary(object):
axarr[l].set_title(phase) axarr[l].set_title(phase)
if l is 0: if l is 0:
axann = axarr[l].annotate(station, xy=(.05, .5), axann = axarr[l].annotate(station, xy=(.05, .5),
xycoords='axes fraction') xycoords='axes fraction')
bbox_props = dict(boxstyle='round', facecolor='lightgrey', bbox_props = dict(boxstyle='round', facecolor='lightgrey',
alpha=.7) alpha=.7)
axann.set_bbox(bbox_props) axann.set_bbox(bbox_props)
@ -352,7 +351,6 @@ class PDFstatistics(object):
Takes a path as argument. Takes a path as argument.
""" """
def __init__(self, directory): def __init__(self, directory):
"""Initiates some values needed when dealing with pdfs later""" """Initiates some values needed when dealing with pdfs later"""
self._rootdir = directory self._rootdir = directory
@ -449,7 +447,7 @@ class PDFstatistics(object):
else: else:
raise ValueError("for call to method {0} value has to be " raise ValueError("for call to method {0} value has to be "
"defined but is 'None' ".format(method_options[ "defined but is 'None' ".format(method_options[
property.upper()])) property.upper()]))
for pdf_dict in self: for pdf_dict in self:
# create worklist # create worklist
@ -459,7 +457,7 @@ class PDFstatistics(object):
return rlist return rlist
def writeThetaToFile(self,array,out_dir): def writeThetaToFile(self, array, out_dir):
""" """
Method to write array like data to file. Useful since acquiring can take Method to write array like data to file. Useful since acquiring can take
serious amount of time when dealing with large databases. serious amount of time when dealing with large databases.
@ -471,12 +469,12 @@ class PDFstatistics(object):
""" """
fid = open(os.path.join(out_dir), 'w') fid = open(os.path.join(out_dir), 'w')
for val in array: for val in array:
fid.write(str(val)+'\n') fid.write(str(val) + '\n')
fid.close() fid.close()
def main(): def main():
root_dir ='/home/sebastianp/Codetesting/xmls/' root_dir = '/home/sebastianp/Codetesting/xmls/'
Insheim = PDFstatistics(root_dir) Insheim = PDFstatistics(root_dir)
Insheim.curphase = 'p' Insheim.curphase = 'p'
qdlist = Insheim.get('qdf', 0.2) qdlist = Insheim.get('qdf', 0.2)

55
pylot/core/pick/picker.py
View File

@ -19,12 +19,13 @@ calculated after Diehl & Kissling (2009).
:author: MAGS2 EP3 working group / Ludger Kueperkoch :author: MAGS2 EP3 working group / Ludger Kueperkoch
""" """
import numpy as np
import matplotlib.pyplot as plt
from pylot.core.pick.utils import getnoisewin, getsignalwin
from pylot.core.pick.charfuns import CharacteristicFunction
import warnings import warnings
import matplotlib.pyplot as plt
import numpy as np
from pylot.core.pick.charfuns import CharacteristicFunction
from pylot.core.pick.utils import getnoisewin, getsignalwin
class AutoPicker(object): class AutoPicker(object):
''' '''
@ -212,14 +213,14 @@ class AICPicker(AutoPicker):
self.Data[0].data = self.Data[0].data * 1000000 self.Data[0].data = self.Data[0].data * 1000000
# get signal window # get signal window
isignal = getsignalwin(self.Tcf, self.Pick, self.TSNR[2]) isignal = getsignalwin(self.Tcf, self.Pick, self.TSNR[2])
ii = min([isignal[len(isignal)-1], len(self.Tcf)]) ii = min([isignal[len(isignal) - 1], len(self.Tcf)])
isignal = isignal[0:ii] isignal = isignal[0:ii]
try: try:
aic[isignal] aic[isignal]
except IndexError as e: except IndexError as e:
msg = "Time series out of bounds! {}".format(e) msg = "Time series out of bounds! {}".format(e)
print(msg) print(msg)
return return
# calculate SNR from CF # calculate SNR from CF
self.SNR = max(abs(aic[isignal] - np.mean(aic[isignal]))) / \ self.SNR = max(abs(aic[isignal] - np.mean(aic[isignal]))) / \
max(abs(aic[inoise] - np.mean(aic[inoise]))) max(abs(aic[inoise] - np.mean(aic[inoise])))
@ -242,7 +243,7 @@ class AICPicker(AutoPicker):
print("Choose longer slope determination window!") print("Choose longer slope determination window!")
if self.iplot > 1: if self.iplot > 1:
if not self.fig: if not self.fig:
fig = plt.figure() #self.iplot) ### WHY? MP MP fig = plt.figure() # self.iplot) ### WHY? MP MP
else: else:
fig = self.fig fig = self.fig
ax = fig.add_subplot(111) ax = fig.add_subplot(111)
@ -271,7 +272,7 @@ class AICPicker(AutoPicker):
if self.iplot > 1: if self.iplot > 1:
if not self.fig: if not self.fig:
fig = plt.figure()#self.iplot) fig = plt.figure() # self.iplot)
else: else:
fig = self.fig fig = self.fig
ax1 = fig.add_subplot(211) ax1 = fig.add_subplot(211)
@ -283,21 +284,25 @@ class AICPicker(AutoPicker):
ax1.set_xlabel('Time [s] since %s' % self.Data[0].stats.starttime) ax1.set_xlabel('Time [s] since %s' % self.Data[0].stats.starttime)
ax1.set_yticks([]) ax1.set_yticks([])
ax1.legend() ax1.legend()
if self.Pick is not None: if self.Pick is not None:
ax2 = fig.add_subplot(2,1,2, sharex=ax1) ax2 = fig.add_subplot(2, 1, 2, sharex=ax1)
ax2.plot(self.Tcf, x, 'k', label='Data') ax2.plot(self.Tcf, x, 'k', label='Data')
ax1.axvspan(self.Tcf[inoise[0]],self.Tcf[inoise[-1]], color='y', alpha=0.2, lw=0, label='Noise Window') ax1.axvspan(self.Tcf[inoise[0]], self.Tcf[inoise[-1]], color='y', alpha=0.2, lw=0, label='Noise Window')
ax1.axvspan(self.Tcf[isignal[0]],self.Tcf[isignal[-1]], color='b', alpha=0.2, lw=0, label='Signal Window') ax1.axvspan(self.Tcf[isignal[0]], self.Tcf[isignal[-1]], color='b', alpha=0.2, lw=0,
ax1.axvspan(self.Tcf[iislope[0]],self.Tcf[iislope[-1]], color='g', alpha=0.2, lw=0, label='Slope Window') label='Signal Window')
ax1.axvspan(self.Tcf[iislope[0]], self.Tcf[iislope[-1]], color='g', alpha=0.2, lw=0,
ax2.axvspan(self.Tcf[inoise[0]],self.Tcf[inoise[-1]], color='y', alpha=0.2, lw=0, label='Noise Window') label='Slope Window')
ax2.axvspan(self.Tcf[isignal[0]],self.Tcf[isignal[-1]], color='b', alpha=0.2, lw=0, label='Signal Window')
ax2.axvspan(self.Tcf[iislope[0]],self.Tcf[iislope[-1]], color='g', alpha=0.2, lw=0, label='Slope Window') ax2.axvspan(self.Tcf[inoise[0]], self.Tcf[inoise[-1]], color='y', alpha=0.2, lw=0, label='Noise Window')
ax2.axvspan(self.Tcf[isignal[0]], self.Tcf[isignal[-1]], color='b', alpha=0.2, lw=0,
label='Signal Window')
ax2.axvspan(self.Tcf[iislope[0]], self.Tcf[iislope[-1]], color='g', alpha=0.2, lw=0,
label='Slope Window')
ax2.plot(self.Tcf[iislope], datafit, 'g', linewidth=2, label='Slope') ax2.plot(self.Tcf[iislope], datafit, 'g', linewidth=2, label='Slope')
ax1.set_title('Station %s, SNR=%7.2f, Slope= %12.2f counts/s' % (self.Data[0].stats.station, ax1.set_title('Station %s, SNR=%7.2f, Slope= %12.2f counts/s' % (self.Data[0].stats.station,
self.SNR, self.slope)) self.SNR, self.slope))
ax2.set_xlabel('Time [s] since %s' % self.Data[0].stats.starttime) ax2.set_xlabel('Time [s] since %s' % self.Data[0].stats.starttime)
ax2.set_ylabel('Counts') ax2.set_ylabel('Counts')
ax2.set_yticks([]) ax2.set_yticks([])
@ -307,7 +312,7 @@ class AICPicker(AutoPicker):
if self.Pick == None: if self.Pick == None:
print('AICPicker: Could not find minimum, picking window too short?') print('AICPicker: Could not find minimum, picking window too short?')
return return
@ -317,7 +322,7 @@ class PragPicker(AutoPicker):
''' '''
def calcPick(self): def calcPick(self):
if self.getpick1() is not None: if self.getpick1() is not None:
print('PragPicker: Get most likely pick from HOS- or AR-CF using pragmatic picking algorithm ...') print('PragPicker: Get most likely pick from HOS- or AR-CF using pragmatic picking algorithm ...')
@ -402,7 +407,7 @@ class PragPicker(AutoPicker):
if self.getiplot() > 1: if self.getiplot() > 1:
if not self.fig: if not self.fig:
fig = plt.figure()#self.getiplot()) fig = plt.figure() # self.getiplot())
else: else:
fig = self.fig fig = self.fig
ax = fig.add_subplot(111) ax = fig.add_subplot(111)

155
pylot/core/pick/utils.py
View File

@ -9,6 +9,7 @@
""" """
import warnings import warnings
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
import numpy as np import numpy as np
from obspy.core import Stream, UTCDateTime from obspy.core import Stream, UTCDateTime
@ -41,11 +42,11 @@ def earllatepicker(X, nfac, TSNR, Pick1, iplot=0, verbosity=1, fig=None):
assert isinstance(X, Stream), "%s is not a stream object" % str(X) assert isinstance(X, Stream), "%s is not a stream object" % str(X)
if verbosity == 2: if verbosity == 2:
print('earllatepicker:') print('earllatepicker:')
print('nfac:', nfac) print('nfac:', nfac)
print('Init pick:', Pick1) print('Init pick:', Pick1)
print('TSNR (T_noise, T_gap, T_signal):', TSNR) print('TSNR (T_noise, T_gap, T_signal):', TSNR)
LPick = None LPick = None
EPick = None EPick = None
PickError = None PickError = None
@ -69,14 +70,14 @@ def earllatepicker(X, nfac, TSNR, Pick1, iplot=0, verbosity=1, fig=None):
print('x_inoise:', x[inoise]) print('x_inoise:', x[inoise])
print('x_isignal:', x[isignal]) print('x_isignal:', x[isignal])
print('nlevel:', nlevel) print('nlevel:', nlevel)
# get time where signal exceeds nlevel # get time where signal exceeds nlevel
ilup, = np.where(x[isignal] > nlevel) ilup, = np.where(x[isignal] > nlevel)
ildown, = np.where(x[isignal] < -nlevel) ildown, = np.where(x[isignal] < -nlevel)
if not ilup.size and not ildown.size: if not ilup.size and not ildown.size:
if verbosity: if verbosity:
print ("earllatepicker: Signal lower than noise level!\n" print("earllatepicker: Signal lower than noise level!\n"
"Skip this trace!") "Skip this trace!")
return LPick, EPick, PickError return LPick, EPick, PickError
il = min(np.min(ilup) if ilup.size else float('inf'), il = min(np.min(ilup) if ilup.size else float('inf'),
np.min(ildown) if ildown.size else float('inf')) np.min(ildown) if ildown.size else float('inf'))
@ -118,7 +119,7 @@ def earllatepicker(X, nfac, TSNR, Pick1, iplot=0, verbosity=1, fig=None):
if iplot > 1: if iplot > 1:
if not fig: if not fig:
fig = plt.figure()#iplot) fig = plt.figure() # iplot)
ax = fig.add_subplot(111) ax = fig.add_subplot(111)
ax.plot(t, x, 'k', label='Data') ax.plot(t, x, 'k', label='Data')
ax.axvspan(t[inoise[0]], t[inoise[-1]], color='y', alpha=0.2, lw=0, label='Noise Window') ax.axvspan(t[inoise[0]], t[inoise[-1]], color='y', alpha=0.2, lw=0, label='Noise Window')
@ -131,9 +132,9 @@ def earllatepicker(X, nfac, TSNR, Pick1, iplot=0, verbosity=1, fig=None):
ax.plot([LPick, LPick], [max(x) / 2, -max(x) / 2], '--k', label='lpp') ax.plot([LPick, LPick], [max(x) / 2, -max(x) / 2], '--k', label='lpp')
ax.plot([EPick, EPick], [max(x) / 2, -max(x) / 2], '--k', label='epp') ax.plot([EPick, EPick], [max(x) / 2, -max(x) / 2], '--k', label='epp')
ax.plot([Pick1 + PickError, Pick1 + PickError], ax.plot([Pick1 + PickError, Pick1 + PickError],
[max(x) / 2, -max(x) / 2], 'r--', label='spe') [max(x) / 2, -max(x) / 2], 'r--', label='spe')
ax.plot([Pick1 - PickError, Pick1 - PickError], ax.plot([Pick1 - PickError, Pick1 - PickError],
[max(x) / 2, -max(x) / 2], 'r--') [max(x) / 2, -max(x) / 2], 'r--')
ax.set_xlabel('Time [s] since %s' % X[0].stats.starttime) ax.set_xlabel('Time [s] since %s' % X[0].stats.starttime)
ax.set_yticks([]) ax.set_yticks([])
ax.set_title( ax.set_title(
@ -173,7 +174,7 @@ def fmpicker(Xraw, Xfilt, pickwin, Pick, iplot=0, fig=None):
FM = None FM = None
if Pick is not None: if Pick is not None:
print ("fmpicker: Get first motion (polarity) of onset using unfiltered seismogram...") print("fmpicker: Get first motion (polarity) of onset using unfiltered seismogram...")
xraw = Xraw[0].data xraw = Xraw[0].data
xfilt = Xfilt[0].data xfilt = Xfilt[0].data
@ -212,15 +213,15 @@ def fmpicker(Xraw, Xfilt, pickwin, Pick, iplot=0, fig=None):
else: else:
li1 = index1[0] li1 = index1[0]
if np.size(xraw[ipick[0][1]:ipick[0][li1]]) == 0: if np.size(xraw[ipick[0][1]:ipick[0][li1]]) == 0:
print ("fmpicker: Onset on unfiltered trace too emergent for first motion determination!") print("fmpicker: Onset on unfiltered trace too emergent for first motion determination!")
P1 = None P1 = None
else: else:
imax1 = np.argmax(abs(xraw[ipick[0][1]:ipick[0][li1]])) imax1 = np.argmax(abs(xraw[ipick[0][1]:ipick[0][li1]]))
if imax1 == 0: if imax1 == 0:
imax1 = np.argmax(abs(xraw[ipick[0][1]:ipick[0][index1[1]]])) imax1 = np.argmax(abs(xraw[ipick[0][1]:ipick[0][index1[1]]]))
if imax1 == 0: if imax1 == 0:
print ("fmpicker: Zero crossings too close!") print("fmpicker: Zero crossings too close!")
print ("Skip first motion determination!") print("Skip first motion determination!")
return FM return FM
islope1 = np.where((t >= Pick) & (t <= Pick + t[imax1])) islope1 = np.where((t >= Pick) & (t <= Pick + t[imax1]))
@ -254,15 +255,15 @@ def fmpicker(Xraw, Xfilt, pickwin, Pick, iplot=0, fig=None):
else: else:
li2 = index2[0] li2 = index2[0]
if np.size(xfilt[ipick[0][1]:ipick[0][li2]]) == 0: if np.size(xfilt[ipick[0][1]:ipick[0][li2]]) == 0:
print ("fmpicker: Onset on filtered trace too emergent for first motion determination!") print("fmpicker: Onset on filtered trace too emergent for first motion determination!")
P2 = None P2 = None
else: else:
imax2 = np.argmax(abs(xfilt[ipick[0][1]:ipick[0][li2]])) imax2 = np.argmax(abs(xfilt[ipick[0][1]:ipick[0][li2]]))
if imax2 == 0: if imax2 == 0:
imax2 = np.argmax(abs(xfilt[ipick[0][1]:ipick[0][index2[1]]])) imax2 = np.argmax(abs(xfilt[ipick[0][1]:ipick[0][index2[1]]]))
if imax2 == 0: if imax2 == 0:
print ("fmpicker: Zero crossings too close!") print("fmpicker: Zero crossings too close!")
print ("Skip first motion determination!") print("Skip first motion determination!")
return FM return FM
islope2 = np.where((t >= Pick) & (t <= Pick + t[imax2])) islope2 = np.where((t >= Pick) & (t <= Pick + t[imax2]))
@ -286,11 +287,11 @@ def fmpicker(Xraw, Xfilt, pickwin, Pick, iplot=0, fig=None):
elif P1[0] > 0 >= P2[0]: elif P1[0] > 0 >= P2[0]:
FM = '+' FM = '+'
print ("fmpicker: Found polarity %s" % FM) print("fmpicker: Found polarity %s" % FM)
if iplot > 1: if iplot > 1:
if not fig: if not fig:
fig = plt.figure()#iplot) fig = plt.figure() # iplot)
ax1 = fig.add_subplot(211) ax1 = fig.add_subplot(211)
ax1.plot(t, xraw, 'k') ax1.plot(t, xraw, 'k')
ax1.plot([Pick, Pick], [max(xraw), -max(xraw)], 'b', linewidth=2, label='Pick') ax1.plot([Pick, Pick], [max(xraw), -max(xraw)], 'b', linewidth=2, label='Pick')
@ -304,11 +305,11 @@ def fmpicker(Xraw, Xfilt, pickwin, Pick, iplot=0, fig=None):
ax1.set_title('First-Motion Determination, %s, Unfiltered Data' % Xraw[ ax1.set_title('First-Motion Determination, %s, Unfiltered Data' % Xraw[
0].stats.station) 0].stats.station)
ax2=fig.add_subplot(2,1,2, sharex=ax1) ax2 = fig.add_subplot(2, 1, 2, sharex=ax1)
ax2.set_title('First-Motion Determination, Filtered Data') ax2.set_title('First-Motion Determination, Filtered Data')
ax2.plot(t, xfilt, 'k') ax2.plot(t, xfilt, 'k')
ax2.plot([Pick, Pick], [max(xfilt), -max(xfilt)], 'b', ax2.plot([Pick, Pick], [max(xfilt), -max(xfilt)], 'b',
linewidth=2) linewidth=2)
if P2 is not None: if P2 is not None:
ax2.plot(t[islope2], xfilt[islope2]) ax2.plot(t[islope2], xfilt[islope2])
ax2.plot(zc2, np.zeros(len(zc2)), '*g', markersize=14) ax2.plot(zc2, np.zeros(len(zc2)), '*g', markersize=14)
@ -359,7 +360,7 @@ def getSNR(X, TSNR, t1, tracenum=0):
SNR = None SNR = None
SNRdB = None SNRdB = None
noiselevel = None noiselevel = None
x = X[tracenum].data x = X[tracenum].data
npts = X[tracenum].stats.npts npts = X[tracenum].stats.npts
sr = X[tracenum].stats.sampling_rate sr = X[tracenum].stats.sampling_rate
@ -372,7 +373,7 @@ def getSNR(X, TSNR, t1, tracenum=0):
# get signal window # get signal window
isignal = getsignalwin(t, t1, TSNR[2]) isignal = getsignalwin(t, t1, TSNR[2])
if np.size(inoise) < 1: if np.size(inoise) < 1:
print ("getSNR: Empty array inoise, check noise window!") print("getSNR: Empty array inoise, check noise window!")
return SNR, SNRdB, noiselevel return SNR, SNRdB, noiselevel
# demean over entire waveform # demean over entire waveform
@ -380,13 +381,13 @@ def getSNR(X, TSNR, t1, tracenum=0):
# calculate ratios # calculate ratios
noiselevel = np.sqrt(np.mean(np.square(x[inoise]))) noiselevel = np.sqrt(np.mean(np.square(x[inoise])))
#signallevel = np.sqrt(np.mean(np.square(x[isignal]))) # signallevel = np.sqrt(np.mean(np.square(x[isignal])))
if np.size(isignal) < 1: if np.size(isignal) < 1:
print ("getSNR: Empty array isignal, check signal window!") print("getSNR: Empty array isignal, check signal window!")
return SNR, SNRdB, noiselevel return SNR, SNRdB, noiselevel
#noiselevel = np.abs(x[inoise]).max() # noiselevel = np.abs(x[inoise]).max()
signallevel = np.abs(x[isignal]).max() signallevel = np.abs(x[isignal]).max()
SNR = signallevel / noiselevel SNR = signallevel / noiselevel
@ -418,9 +419,9 @@ def getnoisewin(t, t1, tnoise, tgap):
inoise, = np.where((t <= max([t1 - tgap, 0])) \ inoise, = np.where((t <= max([t1 - tgap, 0])) \
& (t >= max([t1 - tnoise - tgap, 0]))) & (t >= max([t1 - tnoise - tgap, 0])))
if np.size(inoise) < 1: if np.size(inoise) < 1:
inoise, = np.where((t>=t[0]) & (t<=t1)) inoise, = np.where((t >= t[0]) & (t <= t1))
if np.size(inoise) < 1: if np.size(inoise) < 1:
print ("getnoisewin: Empty array inoise, check noise window!") print("getnoisewin: Empty array inoise, check noise window!")
return inoise return inoise
@ -444,7 +445,7 @@ def getsignalwin(t, t1, tsignal):
isignal, = np.where((t <= min([t1 + tsignal, len(t)])) \ isignal, = np.where((t <= min([t1 + tsignal, len(t)])) \
& (t >= t1)) & (t >= t1))
if np.size(isignal) < 1: if np.size(isignal) < 1:
print ("getsignalwin: Empty array isignal, check signal window!") print("getsignalwin: Empty array isignal, check signal window!")
return isignal return isignal
@ -473,7 +474,7 @@ def getResolutionWindow(snr, extent):
>>> getResolutionWindow(2) >>> getResolutionWindow(2)
2.5 2.5
""" """
res_wins = { res_wins = {
'regional': {'HRW': 2., 'MRW': 5., 'LRW': 10., 'VLRW': 15.}, 'regional': {'HRW': 2., 'MRW': 5., 'LRW': 10., 'VLRW': 15.},
'local': {'HRW': 2., 'MRW': 5., 'LRW': 10., 'VLRW': 15.}, 'local': {'HRW': 2., 'MRW': 5., 'LRW': 10., 'VLRW': 15.},
@ -487,11 +488,11 @@ def getResolutionWindow(snr, extent):
time_resolution = res_wins[extent]['LRW'] time_resolution = res_wins[extent]['LRW']
elif snr < 3.: elif snr < 3.:
time_resolution = res_wins[extent]['MRW'] time_resolution = res_wins[extent]['MRW']
elif snr >3.: elif snr > 3.:
time_resolution = res_wins[extent]['HRW'] time_resolution = res_wins[extent]['HRW']
else: else:
time_resolution = res_wins[extent]['VLRW'] time_resolution = res_wins[extent]['VLRW']
return time_resolution / 2 return time_resolution / 2
@ -573,8 +574,8 @@ def wadaticheck(pickdic, dttolerance, iplot):
# calculate vp/vs ratio before check # calculate vp/vs ratio before check
vpvsr = p1[0] + 1 vpvsr = p1[0] + 1
print ("###############################################") print("###############################################")
print ("wadaticheck: Average Vp/Vs ratio before check: %f" % vpvsr) print("wadaticheck: Average Vp/Vs ratio before check: %f" % vpvsr)
checkedPpicks = [] checkedPpicks = []
checkedSpicks = [] checkedSpicks = []
@ -611,23 +612,23 @@ def wadaticheck(pickdic, dttolerance, iplot):
# calculate vp/vs ratio after check # calculate vp/vs ratio after check
cvpvsr = p2[0] + 1 cvpvsr = p2[0] + 1
print ("wadaticheck: Average Vp/Vs ratio after check: %f" % cvpvsr) print("wadaticheck: Average Vp/Vs ratio after check: %f" % cvpvsr)
print ("wadatacheck: Skipped %d S pick(s)" % ibad) print("wadatacheck: Skipped %d S pick(s)" % ibad)
else: else:
print ("###############################################") print("###############################################")
print ("wadatacheck: Not enough checked S-P times available!") print("wadatacheck: Not enough checked S-P times available!")
print ("Skip Wadati check!") print("Skip Wadati check!")
checkedonsets = pickdic checkedonsets = pickdic
else: else:
print ("wadaticheck: Not enough S-P times available for reliable regression!") print("wadaticheck: Not enough S-P times available for reliable regression!")
print ("Skip wadati check!") print("Skip wadati check!")
wfitflag = 1 wfitflag = 1
# plot results # plot results
if iplot > 0: if iplot > 0:
plt.figure()#iplot) plt.figure() # iplot)
f1, = plt.plot(Ppicks, SPtimes, 'ro') f1, = plt.plot(Ppicks, SPtimes, 'ro')
if wfitflag == 0: if wfitflag == 0:
f2, = plt.plot(Ppicks, wdfit, 'k') f2, = plt.plot(Ppicks, wdfit, 'k')
@ -645,12 +646,14 @@ def wadaticheck(pickdic, dttolerance, iplot):
return checkedonsets return checkedonsets
def RMS(X): def RMS(X):
''' '''
Function returns root mean square of a given array X Function returns root mean square of a given array X
''' '''
return np.sqrt(np.sum(np.power(X, 2))/len(X)) return np.sqrt(np.sum(np.power(X, 2)) / len(X))
def checksignallength(X, pick, TSNR, minsiglength, nfac, minpercent, iplot=0, fig=None): def checksignallength(X, pick, TSNR, minsiglength, nfac, minpercent, iplot=0, fig=None):
''' '''
Function to detect spuriously picked noise peaks. Function to detect spuriously picked noise peaks.
@ -684,7 +687,7 @@ def checksignallength(X, pick, TSNR, minsiglength, nfac, minpercent, iplot=0, fi
assert isinstance(X, Stream), "%s is not a stream object" % str(X) assert isinstance(X, Stream), "%s is not a stream object" % str(X)
print ("Checking signal length ...") print("Checking signal length ...")
if len(X) > 1: if len(X) > 1:
# all three components available # all three components available
@ -714,21 +717,21 @@ def checksignallength(X, pick, TSNR, minsiglength, nfac, minpercent, iplot=0, fi
numoverthr = len(np.where(rms[isignal] >= minsiglevel)[0]) numoverthr = len(np.where(rms[isignal] >= minsiglevel)[0])
if numoverthr >= minnum: if numoverthr >= minnum:
print ("checksignallength: Signal reached required length.") print("checksignallength: Signal reached required length.")
returnflag = 1 returnflag = 1
else: else:
print ("checksignallength: Signal shorter than required minimum signal length!") print("checksignallength: Signal shorter than required minimum signal length!")
print ("Presumably picked noise peak, pick is rejected!") print("Presumably picked noise peak, pick is rejected!")
print ("(min. signal length required: %s s)" % minsiglength) print("(min. signal length required: %s s)" % minsiglength)
returnflag = 0 returnflag = 0
if iplot == 2: if iplot == 2:
if not fig: if not fig:
fig = plt.figure()#iplot) fig = plt.figure() # iplot)
ax = fig.add_subplot(111) ax = fig.add_subplot(111)
ax.plot(t, rms, 'k', label='RMS Data') ax.plot(t, rms, 'k', label='RMS Data')
ax.axvspan(t[inoise[0]], t[inoise[-1]], color='y', alpha=0.2, lw=0, label='Noise Window') ax.axvspan(t[inoise[0]], t[inoise[-1]], color='y', alpha=0.2, lw=0, label='Noise Window')
ax.axvspan(t[isignal[0]], t[isignal[-1]], color='b', alpha=0.2, lw=0, label='Signal Window') ax.axvspan(t[isignal[0]], t[isignal[-1]], color='b', alpha=0.2, lw=0, label='Signal Window')
ax.plot([t[isignal[0]], t[isignal[len(isignal) - 1]]], ax.plot([t[isignal[0]], t[isignal[len(isignal) - 1]]],
[minsiglevel, minsiglevel], 'g', linewidth=2, label='Minimum Signal Level') [minsiglevel, minsiglevel], 'g', linewidth=2, label='Minimum Signal Level')
ax.plot([pick, pick], [min(rms), max(rms)], 'b', linewidth=2, label='Onset') ax.plot([pick, pick], [min(rms), max(rms)], 'b', linewidth=2, label='Onset')
@ -771,8 +774,8 @@ def checkPonsets(pickdic, dttolerance, iplot):
stations.append(key) stations.append(key)
# apply jackknife bootstrapping on variance of P onsets # apply jackknife bootstrapping on variance of P onsets
print ("###############################################") print("###############################################")
print ("checkPonsets: Apply jackknife bootstrapping on P-onset times ...") print("checkPonsets: Apply jackknife bootstrapping on P-onset times ...")
[xjack, PHI_pseudo, PHI_sub] = jackknife(Ppicks, 'VAR', 1) [xjack, PHI_pseudo, PHI_sub] = jackknife(Ppicks, 'VAR', 1)
# get pseudo variances smaller than average variances # get pseudo variances smaller than average variances
# (times safety factor), these picks passed jackknife test # (times safety factor), these picks passed jackknife test
@ -780,7 +783,7 @@ def checkPonsets(pickdic, dttolerance, iplot):
# these picks did not pass jackknife test # these picks did not pass jackknife test
badjk = np.where(PHI_pseudo > 5 * xjack) badjk = np.where(PHI_pseudo > 5 * xjack)
badjkstations = np.array(stations)[badjk] badjkstations = np.array(stations)[badjk]
print ("checkPonsets: %d pick(s) did not pass jackknife test!" % len(badjkstations)) print("checkPonsets: %d pick(s) did not pass jackknife test!" % len(badjkstations))
print(badjkstations) print(badjkstations)
# calculate median from these picks # calculate median from these picks
@ -793,9 +796,9 @@ def checkPonsets(pickdic, dttolerance, iplot):
goodstations = np.array(stations)[igood] goodstations = np.array(stations)[igood]
badstations = np.array(stations)[ibad] badstations = np.array(stations)[ibad]
print ("checkPonsets: %d pick(s) deviate too much from median!" % len(ibad)) print("checkPonsets: %d pick(s) deviate too much from median!" % len(ibad))
print ("checkPonsets: Skipped %d P pick(s) out of %d" % (len(badstations) \ print("checkPonsets: Skipped %d P pick(s) out of %d" % (len(badstations) \
+ len(badjkstations), len(stations))) + len(badjkstations), len(stations)))
goodmarker = 'goodPonsetcheck' goodmarker = 'goodPonsetcheck'
badmarker = 'badPonsetcheck' badmarker = 'badPonsetcheck'
@ -863,8 +866,8 @@ def jackknife(X, phi, h):
g = len(X) / h g = len(X) / h
if type(g) is not int: if type(g) is not int:
print ("jackknife: Cannot divide quantity X in equal sized subgroups!") print("jackknife: Cannot divide quantity X in equal sized subgroups!")
print ("Choose another size for subgroups!") print("Choose another size for subgroups!")
return PHI_jack, PHI_pseudo, PHI_sub return PHI_jack, PHI_pseudo, PHI_sub
else: else:
# estimator of undisturbed spot check # estimator of undisturbed spot check
@ -932,7 +935,7 @@ def checkZ4S(X, pick, zfac, checkwin, iplot, fig=None):
assert isinstance(X, Stream), "%s is not a stream object" % str(X) assert isinstance(X, Stream), "%s is not a stream object" % str(X)
print ("Check for spuriously picked S onset instead of P onset ...") print("Check for spuriously picked S onset instead of P onset ...")
returnflag = 0 returnflag = 0
@ -949,7 +952,7 @@ def checkZ4S(X, pick, zfac, checkwin, iplot, fig=None):
# get earliest time of all 3 traces # get earliest time of all 3 traces
min_t = min(zdat[0].stats.starttime, edat[0].stats.starttime, ndat[0].stats.starttime) min_t = min(zdat[0].stats.starttime, edat[0].stats.starttime, ndat[0].stats.starttime)
# generate time arrays for all 3 traces # generate time arrays for all 3 traces
tz = np.arange(0, zdat[0].stats.npts / zdat[0].stats.sampling_rate, tz = np.arange(0, zdat[0].stats.npts / zdat[0].stats.sampling_rate,
zdat[0].stats.delta) zdat[0].stats.delta)
@ -961,11 +964,11 @@ def checkZ4S(X, pick, zfac, checkwin, iplot, fig=None):
zdiff = (zdat[0].stats.starttime - min_t) zdiff = (zdat[0].stats.starttime - min_t)
ndiff = (ndat[0].stats.starttime - min_t) ndiff = (ndat[0].stats.starttime - min_t)
ediff = (edat[0].stats.starttime - min_t) ediff = (edat[0].stats.starttime - min_t)
# get signal windows # get signal windows
isignalz = getsignalwin(tz, pick-zdiff, checkwin) isignalz = getsignalwin(tz, pick - zdiff, checkwin)
isignaln = getsignalwin(tn, pick-ndiff, checkwin) isignaln = getsignalwin(tn, pick - ndiff, checkwin)
isignale = getsignalwin(te, pick-ediff, checkwin) isignale = getsignalwin(te, pick - ediff, checkwin)
# calculate RMS of traces # calculate RMS of traces
rmsz = RMS(zdat[0].data[isignalz]) rmsz = RMS(zdat[0].data[isignalz])
@ -978,9 +981,9 @@ def checkZ4S(X, pick, zfac, checkwin, iplot, fig=None):
# vertical P-coda level must exceed horizontal P-coda level # vertical P-coda level must exceed horizontal P-coda level
# zfac times encodalevel # zfac times encodalevel
if rmsz < minsiglevel: if rmsz < minsiglevel:
print ("checkZ4S: Maybe S onset? Skip this P pick!") print("checkZ4S: Maybe S onset? Skip this P pick!")
else: else:
print ("checkZ4S: P onset passes checkZ4S test!") print("checkZ4S: P onset passes checkZ4S test!")
returnflag = 1 returnflag = 1
if iplot > 1: if iplot > 1:
@ -996,28 +999,28 @@ def checkZ4S(X, pick, zfac, checkwin, iplot, fig=None):
'N': ndiff, 'N': ndiff,
'E': ediff} 'E': ediff}
signal_dict = {'Z': isignalz, signal_dict = {'Z': isignalz,
'N': isignaln, 'N': isignaln,
'E': isignale} 'E': isignale}
for i, key in enumerate(['Z', 'N', 'E']): for i, key in enumerate(['Z', 'N', 'E']):
rms = rms_dict[key] rms = rms_dict[key]
trace = traces_dict[key] trace = traces_dict[key]
t = np.arange(diff_dict[key], trace.stats.npts / trace.stats.sampling_rate+diff_dict[key], t = np.arange(diff_dict[key], trace.stats.npts / trace.stats.sampling_rate + diff_dict[key],
trace.stats.delta) trace.stats.delta)
if i == 0: if i == 0:
ax1 = fig.add_subplot(3, 1, i+1) ax1 = fig.add_subplot(3, 1, i + 1)
ax = ax1 ax = ax1
ax.set_title('CheckZ4S, Station %s' % zdat[0].stats.station) ax.set_title('CheckZ4S, Station %s' % zdat[0].stats.station)
else: else:
ax = fig.add_subplot(3,1,i+1, sharex=ax1) ax = fig.add_subplot(3, 1, i + 1, sharex=ax1)
ax.plot(t, abs(trace.data), color='b', label='abs') ax.plot(t, abs(trace.data), color='b', label='abs')
ax.plot(t, trace.data, color='k') ax.plot(t, trace.data, color='k')
name = str(trace.stats.channel) + ': {}'.format(rms) name = str(trace.stats.channel) + ': {}'.format(rms)
ax.plot([pick, pick+checkwin], [rms, rms], 'r', label='RMS {}'.format(name)) ax.plot([pick, pick + checkwin], [rms, rms], 'r', label='RMS {}'.format(name))
ax.plot([pick, pick], ax.get_ylim(), 'm', label='Pick') ax.plot([pick, pick], ax.get_ylim(), 'm', label='Pick')
ax.set_ylabel('Normalized Counts') ax.set_ylabel('Normalized Counts')
ax.axvspan(pick, pick+checkwin, color='c', alpha=0.2, ax.axvspan(pick, pick + checkwin, color='c', alpha=0.2,
lw=0) lw=0)
ax.legend() ax.legend()
ax.set_xlabel('Time [s] since %s' % zdat[0].stats.starttime) ax.set_xlabel('Time [s] since %s' % zdat[0].stats.starttime)

174
pylot/core/pick/utils.py.orig
View File

@ -8,14 +8,14 @@
:author: Ludger Kueperkoch / MAGS2 EP3 working group :author: Ludger Kueperkoch / MAGS2 EP3 working group
""" """
import pdb
import numpy as np
import matplotlib.pyplot as plt
from obspy.core import Stream, UTCDateTime
import warnings import warnings
import matplotlib.pyplot as plt
import numpy as np
from obspy.core import Stream, UTCDateTime
def earllatepicker(X, nfac, TSNR, Pick1, iplot=0, stealthMode = False):
def earllatepicker(X, nfac, TSNR, Pick1, iplot=0, stealthMode=False):
''' '''
Function to derive earliest and latest possible pick after Diehl & Kissling (2009) Function to derive earliest and latest possible pick after Diehl & Kissling (2009)
as reasonable uncertainties. Latest possible pick is based on noise level, as reasonable uncertainties. Latest possible pick is based on noise level,
@ -45,7 +45,8 @@ def earllatepicker(X, nfac, TSNR, Pick1, iplot=0, stealthMode = False):
EPick = None EPick = None
PickError = None PickError = None
if stealthMode is False: if stealthMode is False:
print 'earllatepicker: Get earliest and latest possible pick relative to most likely pick ...' print
'earllatepicker: Get earliest and latest possible pick relative to most likely pick ...'
x = X[0].data x = X[0].data
t = np.arange(0, X[0].stats.npts / X[0].stats.sampling_rate, t = np.arange(0, X[0].stats.npts / X[0].stats.sampling_rate,
@ -61,8 +62,8 @@ def earllatepicker(X, nfac, TSNR, Pick1, iplot=0, stealthMode = False):
ilup, = np.where(x[isignal] > nlevel) ilup, = np.where(x[isignal] > nlevel)
ildown, = np.where(x[isignal] < -nlevel) ildown, = np.where(x[isignal] < -nlevel)
if not ilup.size and not ildown.size: if not ilup.size and not ildown.size:
print ("earllatepicker: Signal lower than noise level!") print("earllatepicker: Signal lower than noise level!")
print ("Skip this trace!") print("Skip this trace!")
return LPick, EPick, PickError return LPick, EPick, PickError
il = min(np.min(ilup) if ilup.size else float('inf'), il = min(np.min(ilup) if ilup.size else float('inf'),
np.min(ildown) if ildown.size else float('inf')) np.min(ildown) if ildown.size else float('inf'))
@ -70,20 +71,21 @@ def earllatepicker(X, nfac, TSNR, Pick1, iplot=0, stealthMode = False):
# get earliest possible pick # get earliest possible pick
EPick = np.nan; count = 0 EPick = np.nan;
count = 0
pis = isignal pis = isignal
# if EPick stays NaN the signal window size will be doubled # if EPick stays NaN the signal window size will be doubled
while np.isnan(EPick): while np.isnan(EPick):
if count > 0: if count > 0:
print("earllatepicker: Doubled signal window size %s time(s) " print("earllatepicker: Doubled signal window size %s time(s) "
"because of NaN for earliest pick." %count) "because of NaN for earliest pick." % count)
if stealthMode is False: if stealthMode is False:
print("\nearllatepicker: Doubled signal window size %s time(s) " print("\nearllatepicker: Doubled signal window size %s time(s) "
"because of NaN for earliest pick." %count) "because of NaN for earliest pick." % count)
isigDoubleWinStart = pis[-1] + 1 isigDoubleWinStart = pis[-1] + 1
isignalDoubleWin = np.arange(isigDoubleWinStart, isignalDoubleWin = np.arange(isigDoubleWinStart,
isigDoubleWinStart + len(pis)) isigDoubleWinStart + len(pis))
if (isigDoubleWinStart + len(pis)) < X[0].data.size: if (isigDoubleWinStart + len(pis)) < X[0].data.size:
pis = np.concatenate((pis, isignalDoubleWin)) pis = np.concatenate((pis, isignalDoubleWin))
else: else:
@ -97,7 +99,6 @@ def earllatepicker(X, nfac, TSNR, Pick1, iplot=0, stealthMode = False):
# T0/4 is assumed as time difference between most likely and earliest possible pick! # T0/4 is assumed as time difference between most likely and earliest possible pick!
EPick = Pick1 - T0 / 2 EPick = Pick1 - T0 / 2
# get symmetric pick error as mean from earliest and latest possible pick # get symmetric pick error as mean from earliest and latest possible pick
# by weighting latest possible pick two times earliest possible pick # by weighting latest possible pick two times earliest possible pick
diffti_tl = LPick - Pick1 diffti_tl = LPick - Pick1
@ -165,7 +166,7 @@ def fmpicker(Xraw, Xfilt, pickwin, Pick, iplot=0):
FM = None FM = None
if Pick is not None: if Pick is not None:
print ("fmpicker: Get first motion (polarity) of onset using unfiltered seismogram...") print("fmpicker: Get first motion (polarity) of onset using unfiltered seismogram...")
xraw = Xraw[0].data xraw = Xraw[0].data
xfilt = Xfilt[0].data xfilt = Xfilt[0].data
@ -204,15 +205,15 @@ def fmpicker(Xraw, Xfilt, pickwin, Pick, iplot=0):
else: else:
li1 = index1[0] li1 = index1[0]
if np.size(xraw[ipick[0][1]:ipick[0][li1]]) == 0: if np.size(xraw[ipick[0][1]:ipick[0][li1]]) == 0:
print ("fmpicker: Onset on unfiltered trace too emergent for first motion determination!") print("fmpicker: Onset on unfiltered trace too emergent for first motion determination!")
P1 = None P1 = None
else: else:
imax1 = np.argmax(abs(xraw[ipick[0][1]:ipick[0][li1]])) imax1 = np.argmax(abs(xraw[ipick[0][1]:ipick[0][li1]]))
if imax1 == 0: if imax1 == 0:
imax1 = np.argmax(abs(xraw[ipick[0][1]:ipick[0][index1[1]]])) imax1 = np.argmax(abs(xraw[ipick[0][1]:ipick[0][index1[1]]]))
if imax1 == 0: if imax1 == 0:
print ("fmpicker: Zero crossings too close!") print("fmpicker: Zero crossings too close!")
print ("Skip first motion determination!") print("Skip first motion determination!")
return FM return FM
islope1 = np.where((t >= Pick) & (t <= Pick + t[imax1])) islope1 = np.where((t >= Pick) & (t <= Pick + t[imax1]))
@ -246,15 +247,15 @@ def fmpicker(Xraw, Xfilt, pickwin, Pick, iplot=0):
else: else:
li2 = index2[0] li2 = index2[0]
if np.size(xfilt[ipick[0][1]:ipick[0][li2]]) == 0: if np.size(xfilt[ipick[0][1]:ipick[0][li2]]) == 0:
print ("fmpicker: Onset on filtered trace too emergent for first motion determination!") print("fmpicker: Onset on filtered trace too emergent for first motion determination!")
P2 = None P2 = None
else: else:
imax2 = np.argmax(abs(xfilt[ipick[0][1]:ipick[0][li2]])) imax2 = np.argmax(abs(xfilt[ipick[0][1]:ipick[0][li2]]))
if imax2 == 0: if imax2 == 0:
imax2 = np.argmax(abs(xfilt[ipick[0][1]:ipick[0][index2[1]]])) imax2 = np.argmax(abs(xfilt[ipick[0][1]:ipick[0][index2[1]]]))
if imax2 == 0: if imax2 == 0:
print ("fmpicker: Zero crossings too close!") print("fmpicker: Zero crossings too close!")
print ("Skip first motion determination!") print("Skip first motion determination!")
return FM return FM
islope2 = np.where((t >= Pick) & (t <= Pick + t[imax2])) islope2 = np.where((t >= Pick) & (t <= Pick + t[imax2]))
@ -278,7 +279,7 @@ def fmpicker(Xraw, Xfilt, pickwin, Pick, iplot=0):
elif P1[0] > 0 >= P2[0]: elif P1[0] > 0 >= P2[0]:
FM = '+' FM = '+'
print ("fmpicker: Found polarity %s" % FM) print("fmpicker: Found polarity %s" % FM)
if iplot > 1: if iplot > 1:
plt.figure(iplot) plt.figure(iplot)
@ -353,10 +354,10 @@ def getSNR(X, TSNR, t1):
# get signal window # get signal window
isignal = getsignalwin(t, t1, TSNR[2]) isignal = getsignalwin(t, t1, TSNR[2])
if np.size(inoise) < 1: if np.size(inoise) < 1:
print ("getSNR: Empty array inoise, check noise window!") print("getSNR: Empty array inoise, check noise window!")
return return
elif np.size(isignal) < 1: elif np.size(isignal) < 1:
print ("getSNR: Empty array isignal, check signal window!") print("getSNR: Empty array isignal, check signal window!")
return return
# demean over entire waveform # demean over entire waveform
@ -392,9 +393,9 @@ def getnoisewin(t, t1, tnoise, tgap):
# get noise window # get noise window
inoise, = np.where((t <= max([t1 - tgap, 0])) \ inoise, = np.where((t <= max([t1 - tgap, 0])) \
& (t >= max([t1 - tnoise - tgap, 0]))) & (t >= max([t1 - tnoise - tgap, 0])))
if np.size(inoise) < 1: if np.size(inoise) < 1:
print ("getnoisewin: Empty array inoise, check noise window!") print("getnoisewin: Empty array inoise, check noise window!")
return inoise return inoise
@ -416,9 +417,9 @@ def getsignalwin(t, t1, tsignal):
# get signal window # get signal window
isignal, = np.where((t <= min([t1 + tsignal, len(t)])) \ isignal, = np.where((t <= min([t1 + tsignal, len(t)])) \
& (t >= t1)) & (t >= t1))
if np.size(isignal) < 1: if np.size(isignal) < 1:
print ("getsignalwin: Empty array isignal, check signal window!") print("getsignalwin: Empty array isignal, check signal window!")
return isignal return isignal
@ -457,7 +458,7 @@ def getResolutionWindow(snr):
else: else:
time_resolution = res_wins['HRW'] time_resolution = res_wins['HRW']
return time_resolution/2 return time_resolution / 2
def wadaticheck(pickdic, dttolerance, iplot): def wadaticheck(pickdic, dttolerance, iplot):
@ -485,17 +486,16 @@ def wadaticheck(pickdic, dttolerance, iplot):
SPtimes = [] SPtimes = []
for key in pickdic: for key in pickdic:
if pickdic[key]['P']['weight'] < 4 and pickdic[key]['S']['weight'] < 4: if pickdic[key]['P']['weight'] < 4 and pickdic[key]['S']['weight'] < 4:
# calculate S-P time # calculate S-P time
spt = pickdic[key]['S']['mpp'] - pickdic[key]['P']['mpp'] spt = pickdic[key]['S']['mpp'] - pickdic[key]['P']['mpp']
# add S-P time to dictionary # add S-P time to dictionary
pickdic[key]['SPt'] = spt pickdic[key]['SPt'] = spt
# add P onsets and corresponding S-P times to list # add P onsets and corresponding S-P times to list
UTCPpick = UTCDateTime(pickdic[key]['P']['mpp']) UTCPpick = UTCDateTime(pickdic[key]['P']['mpp'])
UTCSpick = UTCDateTime(pickdic[key]['S']['mpp']) UTCSpick = UTCDateTime(pickdic[key]['S']['mpp'])
Ppicks.append(UTCPpick.timestamp) Ppicks.append(UTCPpick.timestamp)
Spicks.append(UTCSpick.timestamp) Spicks.append(UTCSpick.timestamp)
SPtimes.append(spt) SPtimes.append(spt)
if len(SPtimes) >= 3: if len(SPtimes) >= 3:
# calculate slope # calculate slope
@ -505,8 +505,8 @@ def wadaticheck(pickdic, dttolerance, iplot):
# calculate vp/vs ratio before check # calculate vp/vs ratio before check
vpvsr = p1[0] + 1 vpvsr = p1[0] + 1
print ("###############################################") print("###############################################")
print ("wadaticheck: Average Vp/Vs ratio before check: %f" % vpvsr) print("wadaticheck: Average Vp/Vs ratio before check: %f" % vpvsr)
checkedPpicks = [] checkedPpicks = []
checkedSpicks = [] checkedSpicks = []
@ -527,7 +527,7 @@ def wadaticheck(pickdic, dttolerance, iplot):
ibad += 1 ibad += 1
else: else:
marker = 'goodWadatiCheck' marker = 'goodWadatiCheck'
checkedPpick = UTCDateTime(pickdic[key]['P']['mpp']) checkedPpick = UTCDateTime(pickdic[key]['P']['mpp'])
checkedPpicks.append(checkedPpick.timestamp) checkedPpicks.append(checkedPpick.timestamp)
checkedSpick = UTCDateTime(pickdic[key]['S']['mpp']) checkedSpick = UTCDateTime(pickdic[key]['S']['mpp'])
checkedSpicks.append(checkedSpick.timestamp) checkedSpicks.append(checkedSpick.timestamp)
@ -543,18 +543,18 @@ def wadaticheck(pickdic, dttolerance, iplot):
# calculate vp/vs ratio after check # calculate vp/vs ratio after check
cvpvsr = p2[0] + 1 cvpvsr = p2[0] + 1
print ("wadaticheck: Average Vp/Vs ratio after check: %f" % cvpvsr) print("wadaticheck: Average Vp/Vs ratio after check: %f" % cvpvsr)
print ("wadatacheck: Skipped %d S pick(s)" % ibad) print("wadatacheck: Skipped %d S pick(s)" % ibad)
else: else:
print ("###############################################") print("###############################################")
print ("wadatacheck: Not enough checked S-P times available!") print("wadatacheck: Not enough checked S-P times available!")
print ("Skip Wadati check!") print("Skip Wadati check!")
checkedonsets = pickdic checkedonsets = pickdic
else: else:
print ("wadaticheck: Not enough S-P times available for reliable regression!") print("wadaticheck: Not enough S-P times available for reliable regression!")
print ("Skip wadati check!") print("Skip wadati check!")
wfitflag = 1 wfitflag = 1
# plot results # plot results
@ -614,7 +614,7 @@ def checksignallength(X, pick, TSNR, minsiglength, nfac, minpercent, iplot):
assert isinstance(X, Stream), "%s is not a stream object" % str(X) assert isinstance(X, Stream), "%s is not a stream object" % str(X)
print ("Checking signal length ...") print("Checking signal length ...")
if len(X) > 1: if len(X) > 1:
# all three components available # all three components available
@ -639,25 +639,25 @@ def checksignallength(X, pick, TSNR, minsiglength, nfac, minpercent, iplot):
# calculate minimum adjusted signal level # calculate minimum adjusted signal level
minsiglevel = max(rms[inoise]) * nfac minsiglevel = max(rms[inoise]) * nfac
# minimum adjusted number of samples over minimum signal level # minimum adjusted number of samples over minimum signal level
minnum = len(isignal) * minpercent/100 minnum = len(isignal) * minpercent / 100
# get number of samples above minimum adjusted signal level # get number of samples above minimum adjusted signal level
numoverthr = len(np.where(rms[isignal] >= minsiglevel)[0]) numoverthr = len(np.where(rms[isignal] >= minsiglevel)[0])
if numoverthr >= minnum: if numoverthr >= minnum:
print ("checksignallength: Signal reached required length.") print("checksignallength: Signal reached required length.")
returnflag = 1 returnflag = 1
else: else:
print ("checksignallength: Signal shorter than required minimum signal length!") print("checksignallength: Signal shorter than required minimum signal length!")
print ("Presumably picked noise peak, pick is rejected!") print("Presumably picked noise peak, pick is rejected!")
print ("(min. signal length required: %s s)" % minsiglength) print("(min. signal length required: %s s)" % minsiglength)
returnflag = 0 returnflag = 0
if iplot == 2: if iplot == 2:
plt.figure(iplot) plt.figure(iplot)
p1, = plt.plot(t,rms, 'k') p1, = plt.plot(t, rms, 'k')
p2, = plt.plot(t[inoise], rms[inoise], 'c') p2, = plt.plot(t[inoise], rms[inoise], 'c')
p3, = plt.plot(t[isignal],rms[isignal], 'r') p3, = plt.plot(t[isignal], rms[isignal], 'r')
p4, = plt.plot([t[isignal[0]], t[isignal[len(isignal)-1]]], p4, = plt.plot([t[isignal[0]], t[isignal[len(isignal) - 1]]],
[minsiglevel, minsiglevel], 'g', linewidth=2) [minsiglevel, minsiglevel], 'g', linewidth=2)
p5, = plt.plot([pick, pick], [min(rms), max(rms)], 'b', linewidth=2) p5, = plt.plot([pick, pick], [min(rms), max(rms)], 'b', linewidth=2)
plt.legend([p1, p2, p3, p4, p5], ['RMS Data', 'RMS Noise Window', plt.legend([p1, p2, p3, p4, p5], ['RMS Data', 'RMS Noise Window',
@ -698,22 +698,22 @@ def checkPonsets(pickdic, dttolerance, iplot):
stations = [] stations = []
for key in pickdic: for key in pickdic:
if pickdic[key]['P']['weight'] < 4: if pickdic[key]['P']['weight'] < 4:
# add P onsets to list # add P onsets to list
UTCPpick = UTCDateTime(pickdic[key]['P']['mpp']) UTCPpick = UTCDateTime(pickdic[key]['P']['mpp'])
Ppicks.append(UTCPpick.timestamp) Ppicks.append(UTCPpick.timestamp)
stations.append(key) stations.append(key)
# apply jackknife bootstrapping on variance of P onsets # apply jackknife bootstrapping on variance of P onsets
print ("###############################################") print("###############################################")
print ("checkPonsets: Apply jackknife bootstrapping on P-onset times ...") print("checkPonsets: Apply jackknife bootstrapping on P-onset times ...")
[xjack,PHI_pseudo,PHI_sub] = jackknife(Ppicks, 'VAR', 1) [xjack, PHI_pseudo, PHI_sub] = jackknife(Ppicks, 'VAR', 1)
# get pseudo variances smaller than average variances # get pseudo variances smaller than average variances
# (times safety factor), these picks passed jackknife test # (times safety factor), these picks passed jackknife test
ij = np.where(PHI_pseudo <= 2 * xjack) ij = np.where(PHI_pseudo <= 2 * xjack)
# these picks did not pass jackknife test # these picks did not pass jackknife test
badjk = np.where(PHI_pseudo > 2 * xjack) badjk = np.where(PHI_pseudo > 2 * xjack)
badjkstations = np.array(stations)[badjk] badjkstations = np.array(stations)[badjk]
print ("checkPonsets: %d pick(s) did not pass jackknife test!" % len(badjkstations)) print("checkPonsets: %d pick(s) did not pass jackknife test!" % len(badjkstations))
# calculate median from these picks # calculate median from these picks
pmedian = np.median(np.array(Ppicks)[ij]) pmedian = np.median(np.array(Ppicks)[ij])
@ -725,9 +725,9 @@ def checkPonsets(pickdic, dttolerance, iplot):
goodstations = np.array(stations)[igood] goodstations = np.array(stations)[igood]
badstations = np.array(stations)[ibad] badstations = np.array(stations)[ibad]
print ("checkPonsets: %d pick(s) deviate too much from median!" % len(ibad)) print("checkPonsets: %d pick(s) deviate too much from median!" % len(ibad))
print ("checkPonsets: Skipped %d P pick(s) out of %d" % (len(badstations) \ print("checkPonsets: Skipped %d P pick(s) out of %d" % (len(badstations) \
+ len(badjkstations), len(stations))) + len(badjkstations), len(stations)))
goodmarker = 'goodPonsetcheck' goodmarker = 'goodPonsetcheck'
badmarker = 'badPonsetcheck' badmarker = 'badPonsetcheck'
@ -794,8 +794,8 @@ def jackknife(X, phi, h):
g = len(X) / h g = len(X) / h
if type(g) is not int: if type(g) is not int:
print ("jackknife: Cannot divide quantity X in equal sized subgroups!") print("jackknife: Cannot divide quantity X in equal sized subgroups!")
print ("Choose another size for subgroups!") print("Choose another size for subgroups!")
return PHI_jack, PHI_pseudo, PHI_sub return PHI_jack, PHI_pseudo, PHI_sub
else: else:
# estimator of undisturbed spot check # estimator of undisturbed spot check
@ -863,7 +863,7 @@ def checkZ4S(X, pick, zfac, checkwin, iplot):
assert isinstance(X, Stream), "%s is not a stream object" % str(X) assert isinstance(X, Stream), "%s is not a stream object" % str(X)
print ("Check for spuriously picked S onset instead of P onset ...") print("Check for spuriously picked S onset instead of P onset ...")
returnflag = 0 returnflag = 0
@ -876,10 +876,9 @@ def checkZ4S(X, pick, zfac, checkwin, iplot):
if len(ndat) == 0: # check for other components if len(ndat) == 0: # check for other components
ndat = X.select(component="1") ndat = X.select(component="1")
z = zdat[0].data z = zdat[0].data
tz = np.arange(0, zdat[0].stats.npts / zdat[0].stats.sampling_rate, tz = np.arange(0, zdat[0].stats.npts / zdat[0].stats.sampling_rate,
zdat[0].stats.delta) zdat[0].stats.delta)
# calculate RMS trace from vertical component # calculate RMS trace from vertical component
absz = np.sqrt(np.power(z, 2)) absz = np.sqrt(np.power(z, 2))
@ -904,16 +903,16 @@ def checkZ4S(X, pick, zfac, checkwin, iplot):
# vertical P-coda level must exceed horizontal P-coda level # vertical P-coda level must exceed horizontal P-coda level
# zfac times encodalevel # zfac times encodalevel
if zcodalevel < minsiglevel: if zcodalevel < minsiglevel:
print ("checkZ4S: Maybe S onset? Skip this P pick!") print("checkZ4S: Maybe S onset? Skip this P pick!")
else: else:
print ("checkZ4S: P onset passes checkZ4S test!") print("checkZ4S: P onset passes checkZ4S test!")
returnflag = 1 returnflag = 1
if iplot > 1: if iplot > 1:
te = np.arange(0, edat[0].stats.npts / edat[0].stats.sampling_rate, te = np.arange(0, edat[0].stats.npts / edat[0].stats.sampling_rate,
edat[0].stats.delta) edat[0].stats.delta)
tn = np.arange(0, ndat[0].stats.npts / ndat[0].stats.sampling_rate, tn = np.arange(0, ndat[0].stats.npts / ndat[0].stats.sampling_rate,
ndat[0].stats.delta) ndat[0].stats.delta)
plt.plot(tz, z / max(z), 'k') plt.plot(tz, z / max(z), 'k')
plt.plot(tz[isignal], z[isignal] / max(z), 'r') plt.plot(tz[isignal], z[isignal] / max(z), 'r')
plt.plot(te, edat[0].data / max(edat[0].data) + 1, 'k') plt.plot(te, edat[0].data / max(edat[0].data) + 1, 'k')
@ -955,9 +954,8 @@ def writephases(arrivals, fformat, filename):
:type: string :type: string
''' '''
if fformat == 'NLLoc': if fformat == 'NLLoc':
print ("Writing phases to %s for NLLoc" % filename) print("Writing phases to %s for NLLoc" % filename)
fid = open("%s" % filename, 'w') fid = open("%s" % filename, 'w')
# write header # write header
fid.write('# EQEVENT: Label: EQ001 Loc: X 0.00 Y 0.00 Z 10.00 OT 0.00 \n') fid.write('# EQEVENT: Label: EQ001 Loc: X 0.00 Y 0.00 Z 10.00 OT 0.00 \n')
@ -969,34 +967,32 @@ def writephases(arrivals, fformat, filename):
onset = arrivals[key]['P']['mpp'] onset = arrivals[key]['P']['mpp']
year = onset.year year = onset.year
month = onset.month month = onset.month
day =onset.day day = onset.day
hh = onset.hour hh = onset.hour
mm = onset.minute mm = onset.minute
ss = onset.second ss = onset.second
ms = onset.microsecond ms = onset.microsecond
ss_ms = ss + (ms / 1E06) ss_ms = ss + (ms / 1E06)
fid.write('%s ? ? ? P %s %d%02d%02d %02d%02d %7.4f GAU 0 0 0 0 1 \n' \ fid.write('%s ? ? ? P %s %d%02d%02d %02d%02d %7.4f GAU 0 0 0 0 1 \n' \
% (key, fm, year, month, day, hh, mm, ss_ms)) % (key, fm, year, month, day, hh, mm, ss_ms))
if arrivals[key]['S']['weight'] < 4: if arrivals[key]['S']['weight'] < 4:
fm = '?' fm = '?'
onset = arrivals[key]['S']['mpp'] onset = arrivals[key]['S']['mpp']
year = onset.year year = onset.year
month = onset.month month = onset.month
day =onset.day day = onset.day
hh = onset.hour hh = onset.hour
mm = onset.minute mm = onset.minute
ss = onset.second ss = onset.second
ms = onset.microsecond ms = onset.microsecond
ss_ms = ss + (ms / 1E06) ss_ms = ss + (ms / 1E06)
fid.write('%s ? ? ? S %s %d%02d%02d %02d%02d %7.4f GAU 0 0 0 0 1 \n' \ fid.write('%s ? ? ? S %s %d%02d%02d %02d%02d %7.4f GAU 0 0 0 0 1 \n' \
% (key, fm, year, month, day, hh, mm, ss_ms)) % (key, fm, year, month, day, hh, mm, ss_ms))
fid.close() fid.close()
if __name__ == '__main__': if __name__ == '__main__':
import doctest import doctest
doctest.testmod() doctest.testmod()

27
pylot/core/util/dataprocessing.py
View File

@ -1,12 +1,11 @@
#!/usr/bin/env python #!/usr/bin/env python
# -*- coding: utf-8 -*- # -*- coding: utf-8 -*-
import os
import glob import glob
import os
import sys import sys
import numpy as np import numpy as np
from obspy import UTCDateTime, read_inventory, read from obspy import UTCDateTime, read_inventory, read
from obspy.io.xseed import Parser from obspy.io.xseed import Parser
from pylot.core.util.utils import key_for_set_value, find_in_list, \ from pylot.core.util.utils import key_for_set_value, find_in_list, \
@ -116,7 +115,7 @@ def make_time_line(line, datetime):
return newline return newline
def evt_head_check(root_dir, out_dir = None): def evt_head_check(root_dir, out_dir=None):
""" """
A function to make sure that an arbitrary number of .gse files have correct values in their header. A function to make sure that an arbitrary number of .gse files have correct values in their header.
:param root_dir: a directory leading to the .gse files. :param root_dir: a directory leading to the .gse files.
@ -183,7 +182,7 @@ def read_metadata(path_to_inventory):
print("Neither dataless-SEED file, inventory-xml file nor " print("Neither dataless-SEED file, inventory-xml file nor "
"RESP-file found!") "RESP-file found!")
print("!!WRONG CALCULATION OF SOURCE PARAMETERS!!") print("!!WRONG CALCULATION OF SOURCE PARAMETERS!!")
robj = None, robj = None,
elif invtype == 'dless': # prevent multiple read of large dlsv elif invtype == 'dless': # prevent multiple read of large dlsv
print("Reading metadata information from dataless-SEED file ...") print("Reading metadata information from dataless-SEED file ...")
if len(inv[invtype]) == 1: if len(inv[invtype]) == 1:
@ -201,7 +200,7 @@ def restitute_trace(input_tuple):
tr, invtype, inobj, unit, force = input_tuple tr, invtype, inobj, unit, force = input_tuple
remove_trace = False remove_trace = False
seed_id = tr.get_id() seed_id = tr.get_id()
# check, whether this trace has already been corrected # check, whether this trace has already been corrected
if 'processing' in tr.stats.keys() \ if 'processing' in tr.stats.keys() \
@ -244,14 +243,14 @@ def restitute_trace(input_tuple):
remove_trace = True remove_trace = True
# apply restitution to data # apply restitution to data
print("Correcting instrument at station %s, channel %s" \ print("Correcting instrument at station %s, channel %s" \
% (tr.stats.station, tr.stats.channel)) % (tr.stats.station, tr.stats.channel))
try: try:
if invtype in ['resp', 'dless']: if invtype in ['resp', 'dless']:
try: try:
tr.simulate(**kwargs) tr.simulate(**kwargs)
except ValueError as e: except ValueError as e:
vmsg = '{0}'.format(e) vmsg = '{0}'.format(e)
print(vmsg) print(vmsg)
else: else:
tr.attach_response(inventory) tr.attach_response(inventory)
@ -293,15 +292,15 @@ def restitute_data(data, invtype, inobj, unit='VEL', force=False):
for tr in data: for tr in data:
input_tuples.append((tr, invtype, inobj, unit, force)) input_tuples.append((tr, invtype, inobj, unit, force))
data.remove(tr) data.remove(tr)
pool = gen_Pool() pool = gen_Pool()
result = pool.map(restitute_trace, input_tuples) result = pool.map(restitute_trace, input_tuples)
pool.close() pool.close()
for tr, remove_trace in result: for tr, remove_trace in result:
if not remove_trace: if not remove_trace:
data.traces.append(tr) data.traces.append(tr)
# check if ALL traces could be restituted, take care of large datasets # check if ALL traces could be restituted, take care of large datasets
# better try restitution for smaller subsets of data (e.g. station by # better try restitution for smaller subsets of data (e.g. station by
# station) # station)
@ -343,8 +342,8 @@ def get_prefilt(trace, tlow=(0.5, 0.9), thi=(5., 2.), verbosity=0):
trace.stats.station, trace.stats.channel)) trace.stats.station, trace.stats.channel))
# get corner frequencies for pre-filtering # get corner frequencies for pre-filtering
fny = trace.stats.sampling_rate / 2 fny = trace.stats.sampling_rate / 2
fc21 = fny - (fny * thi[0]/100.) fc21 = fny - (fny * thi[0] / 100.)
fc22 = fny - (fny * thi[1]/100.) fc22 = fny - (fny * thi[1] / 100.)
return (tlow[0], tlow[1], fc21, fc22) return (tlow[0], tlow[1], fc21, fc22)

24
pylot/core/util/defaults.py
View File

@ -9,17 +9,19 @@ Created on Wed Feb 26 12:31:25 2014
import os import os
import platform import platform
from pylot.core.loc import nll from pylot.core.io.inputs import PylotParameter
from pylot.core.loc import hyposat
from pylot.core.loc import hypo71 from pylot.core.loc import hypo71
from pylot.core.loc import hypodd from pylot.core.loc import hypodd
from pylot.core.loc import hyposat
from pylot.core.loc import nll
from pylot.core.loc import velest from pylot.core.loc import velest
from pylot.core.io.inputs import PylotParameter
def readDefaultFilterInformation(fname): def readDefaultFilterInformation(fname):
pparam = PylotParameter(fname) pparam = PylotParameter(fname)
return readFilterInformation(pparam) return readFilterInformation(pparam)
def readFilterInformation(pylot_parameter): def readFilterInformation(pylot_parameter):
p_filter = {'filtertype': pylot_parameter['filter_type'][0], p_filter = {'filtertype': pylot_parameter['filter_type'][0],
'freq': [pylot_parameter['minfreq'][0], pylot_parameter['maxfreq'][0]], 'freq': [pylot_parameter['minfreq'][0], pylot_parameter['maxfreq'][0]],
@ -31,6 +33,7 @@ def readFilterInformation(pylot_parameter):
'S': s_filter} 'S': s_filter}
return filter_information return filter_information
# determine system dependent path separator # determine system dependent path separator
system_name = platform.system() system_name = platform.system()
if system_name in ["Linux", "Darwin"]: if system_name in ["Linux", "Darwin"]:
@ -59,14 +62,14 @@ LOCTOOLS = dict(nll=nll, hyposat=hyposat, velest=velest, hypo71=hypo71, hypodd=h
class SetChannelComponents(object): class SetChannelComponents(object):
def __init__(self): def __init__(self):
self.setDefaultCompPosition() self.setDefaultCompPosition()
def setDefaultCompPosition(self): def setDefaultCompPosition(self):
# default component order # default component order
self.compPosition_Map = dict(Z=2, N=1, E=0) self.compPosition_Map = dict(Z=2, N=1, E=0)
self.compName_Map = {'3': 'Z', self.compName_Map = {'3': 'Z',
'1': 'N', '1': 'N',
'2': 'E'} '2': 'E'}
def _getCurrentPosition(self, component): def _getCurrentPosition(self, component):
for key, value in self.compName_Map.items(): for key, value in self.compName_Map.items():
if value == component: if value == component:
@ -85,10 +88,10 @@ class SetChannelComponents(object):
def setCompPosition(self, component_alter, component, switch=True): def setCompPosition(self, component_alter, component, switch=True):
component_alter = str(component_alter) component_alter = str(component_alter)
if not component_alter in self.compName_Map.keys(): if not component_alter in self.compName_Map.keys():
errMsg='setCompPosition: Unrecognized alternative component {}. Expecting one of {}.' errMsg = 'setCompPosition: Unrecognized alternative component {}. Expecting one of {}.'
raise ValueError(errMsg.format(component_alter, self.compName_Map.keys())) raise ValueError(errMsg.format(component_alter, self.compName_Map.keys()))
if not component in self.compPosition_Map.keys(): if not component in self.compPosition_Map.keys():
errMsg='setCompPosition: Unrecognized target component {}. Expecting one of {}.' errMsg = 'setCompPosition: Unrecognized target component {}. Expecting one of {}.'
raise ValueError(errMsg.format(component, self.compPosition_Map.keys())) raise ValueError(errMsg.format(component, self.compPosition_Map.keys()))
print('setCompPosition: set component {} to {}'.format(component_alter, component)) print('setCompPosition: set component {} to {}'.format(component_alter, component))
if switch: if switch:
@ -97,7 +100,7 @@ class SetChannelComponents(object):
def getCompPosition(self, component): def getCompPosition(self, component):
return self._getCurrentPosition(component)[0] return self._getCurrentPosition(component)[0]
def getPlotPosition(self, component): def getPlotPosition(self, component):
component = str(component) component = str(component)
if component in self.compPosition_Map.keys(): if component in self.compPosition_Map.keys():
@ -105,6 +108,5 @@ class SetChannelComponents(object):
elif component in self.compName_Map.keys(): elif component in self.compName_Map.keys():
return self.compPosition_Map[self.compName_Map[component]] return self.compPosition_Map[self.compName_Map[component]]
else: else:
errMsg='getCompPosition: Unrecognized component {}. Expecting one of {} or {}.' errMsg = 'getCompPosition: Unrecognized component {}. Expecting one of {} or {}.'
raise ValueError(errMsg.format(component, self.compPosition_Map.keys(), self.compName_Map.keys())) raise ValueError(errMsg.format(component, self.compPosition_Map.keys(), self.compName_Map.keys()))

1
pylot/core/util/errors.py
View File

@ -25,5 +25,6 @@ class OverwriteError(IOError):
class ParameterError(Exception): class ParameterError(Exception):
pass pass
class ProcessingError(RuntimeError): class ProcessingError(RuntimeError):
pass pass

20
pylot/core/util/event.py
View File

@ -6,7 +6,6 @@ import os
from obspy import UTCDateTime from obspy import UTCDateTime
from obspy.core.event import Event as ObsPyEvent from obspy.core.event import Event as ObsPyEvent
from obspy.core.event import Origin, ResourceIdentifier from obspy.core.event import Origin, ResourceIdentifier
from pylot.core.io.phases import picks_from_picksdict from pylot.core.io.phases import picks_from_picksdict
@ -14,10 +13,11 @@ class Event(ObsPyEvent):
''' '''
Pickable class derived from ~obspy.core.event.Event containing information on a single event. Pickable class derived from ~obspy.core.event.Event containing information on a single event.
''' '''
def __init__(self, path): def __init__(self, path):
self.pylot_id = path.split('/')[-1] self.pylot_id = path.split('/')[-1]
# initialize super class # initialize super class
super(Event, self).__init__(resource_id=ResourceIdentifier('smi:local/'+self.pylot_id)) super(Event, self).__init__(resource_id=ResourceIdentifier('smi:local/' + self.pylot_id))
self.path = path self.path = path
self.database = path.split('/')[-2] self.database = path.split('/')[-2]
self.datapath = path.split('/')[-3] self.datapath = path.split('/')[-3]
@ -32,13 +32,13 @@ class Event(ObsPyEvent):
def get_notes_path(self): def get_notes_path(self):
notesfile = os.path.join(self.path, 'notes.txt') notesfile = os.path.join(self.path, 'notes.txt')
return notesfile return notesfile
def get_notes(self): def get_notes(self):
notesfile = self.get_notes_path() notesfile = self.get_notes_path()
if os.path.isfile(notesfile): if os.path.isfile(notesfile):
with open(notesfile) as infile: with open(notesfile) as infile:
path = str(infile.readlines()[0].split('\n')[0]) path = str(infile.readlines()[0].split('\n')[0])
text = '[eventInfo: '+path+']' text = '[eventInfo: ' + path + ']'
self.addNotes(text) self.addNotes(text)
try: try:
datetime = UTCDateTime(path.split('/')[-1]) datetime = UTCDateTime(path.split('/')[-1])
@ -73,13 +73,13 @@ class Event(ObsPyEvent):
''' '''
for station in picks: for station in picks:
self.pylot_picks[station] = picks[station] self.pylot_picks[station] = picks[station]
#add ObsPy picks # add ObsPy picks
self.picks = picks_from_picksdict(self.pylot_picks) self.picks = picks_from_picksdict(self.pylot_picks)
def addAutopicks(self, autopicks): def addAutopicks(self, autopicks):
for station in autopicks: for station in autopicks:
self.pylot_autopicks[station] = autopicks[station] self.pylot_autopicks[station] = autopicks[station]
def setPick(self, station, pick): def setPick(self, station, pick):
if pick: if pick:
self.pylot_picks[station] = pick self.pylot_picks[station] = pick
@ -89,14 +89,14 @@ class Event(ObsPyEvent):
except Exception as e: except Exception as e:
print('Could not remove pick {} from station {}: {}'.format(pick, station, e)) print('Could not remove pick {} from station {}: {}'.format(pick, station, e))
self.picks = picks_from_picksdict(self.pylot_picks) self.picks = picks_from_picksdict(self.pylot_picks)
def setPicks(self, picks): def setPicks(self, picks):
''' '''
set pylot picks and delete and overwrite all existing set pylot picks and delete and overwrite all existing
''' '''
self.pylot_picks = picks self.pylot_picks = picks
self.picks = picks_from_picksdict(self.pylot_picks) self.picks = picks_from_picksdict(self.pylot_picks)
def getPick(self, station): def getPick(self, station):
if station in self.pylot_picks.keys(): if station in self.pylot_picks.keys():
return self.pylot_picks[station] return self.pylot_picks[station]
@ -110,7 +110,7 @@ class Event(ObsPyEvent):
def setAutopicks(self, autopicks): def setAutopicks(self, autopicks):
self.pylot_autopicks = autopicks self.pylot_autopicks = autopicks
def getAutopick(self, station): def getAutopick(self, station):
if station in self.pylot_autopicks.keys(): if station in self.pylot_autopicks.keys():
return self.pylot_autopicks[station] return self.pylot_autopicks[station]

123
pylot/core/util/map_projection.py
View File

@ -1,16 +1,15 @@
from mpl_toolkits.basemap import Basemap
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
import numpy as np import numpy as np
import obspy import obspy
from matplotlib import cm from PySide import QtGui
from scipy.interpolate import griddata
from matplotlib.backends.backend_qt4agg import NavigationToolbar2QT as NavigationToolbar from matplotlib.backends.backend_qt4agg import NavigationToolbar2QT as NavigationToolbar
from PySide import QtCore, QtGui from mpl_toolkits.basemap import Basemap
from pylot.core.util.widgets import PickDlg from pylot.core.util.widgets import PickDlg
from scipy.interpolate import griddata
plt.interactive(False) plt.interactive(False)
class map_projection(QtGui.QWidget): class map_projection(QtGui.QWidget):
def __init__(self, parent, figure=None): def __init__(self, parent, figure=None):
''' '''
@ -29,7 +28,7 @@ class map_projection(QtGui.QWidget):
self.init_stations() self.init_stations()
self.init_basemap(resolution='l') self.init_basemap(resolution='l')
self.init_map() self.init_map()
#self.show() # self.show()
def init_map(self): def init_map(self):
self.init_lat_lon_dimensions() self.init_lat_lon_dimensions()
@ -37,7 +36,7 @@ class map_projection(QtGui.QWidget):
self.init_x_y_dimensions() self.init_x_y_dimensions()
self.connectSignals() self.connectSignals()
self.draw_everything() self.draw_everything()
def onpick(self, event): def onpick(self, event):
ind = event.ind ind = event.ind
button = event.mouseevent.button button = event.mouseevent.button
@ -45,7 +44,7 @@ class map_projection(QtGui.QWidget):
return return
data = self._parent.get_data().getWFData() data = self._parent.get_data().getWFData()
for index in ind: for index in ind:
station=str(self.station_names[index].split('.')[-1]) station = str(self.station_names[index].split('.')[-1])
try: try:
pickDlg = PickDlg(self, parameter=self._parent._inputs, pickDlg = PickDlg(self, parameter=self._parent._inputs,
data=data.select(station=station), data=data.select(station=station),
@ -90,7 +89,7 @@ class map_projection(QtGui.QWidget):
else: else:
self.figure = self._parent.am_figure self.figure = self._parent.am_figure
self.toolbar = self._parent.am_toolbar self.toolbar = self._parent.am_toolbar
self.main_ax = self.figure.add_subplot(111) self.main_ax = self.figure.add_subplot(111)
self.canvas = self.figure.canvas self.canvas = self.figure.canvas
@ -106,29 +105,29 @@ class map_projection(QtGui.QWidget):
self.comboBox_am = QtGui.QComboBox() self.comboBox_am = QtGui.QComboBox()
self.comboBox_am.insertItem(0, 'auto') self.comboBox_am.insertItem(0, 'auto')
self.comboBox_am.insertItem(1, 'manual') self.comboBox_am.insertItem(1, 'manual')
self.top_row.addWidget(QtGui.QLabel('Select a phase: ')) self.top_row.addWidget(QtGui.QLabel('Select a phase: '))
self.top_row.addWidget(self.comboBox_phase) self.top_row.addWidget(self.comboBox_phase)
self.top_row.setStretch(1,1) #set stretch of item 1 to 1 self.top_row.setStretch(1, 1) # set stretch of item 1 to 1
self.main_box.addWidget(self.canvas) self.main_box.addWidget(self.canvas)
self.main_box.addWidget(self.toolbar) self.main_box.addWidget(self.toolbar)
def init_stations(self): def init_stations(self):
def get_station_names_lat_lon(parser): def get_station_names_lat_lon(parser):
station_names=[] station_names = []
lat=[] lat = []
lon=[] lon = []
for station in parser.stations: for station in parser.stations:
station_name=station[0].station_call_letters station_name = station[0].station_call_letters
network=station[0].network_code network = station[0].network_code
if not station_name in station_names: if not station_name in station_names:
station_names.append(network+'.'+station_name) station_names.append(network + '.' + station_name)
lat.append(station[0].latitude) lat.append(station[0].latitude)
lon.append(station[0].longitude) lon.append(station[0].longitude)
return station_names, lat, lon return station_names, lat, lon
station_names, lat, lon = get_station_names_lat_lon(self.parser) station_names, lat, lon = get_station_names_lat_lon(self.parser)
self.station_names = station_names self.station_names = station_names
self.lat = lat self.lat = lat
@ -136,52 +135,53 @@ class map_projection(QtGui.QWidget):
def init_picks(self): def init_picks(self):
phase = self.comboBox_phase.currentText() phase = self.comboBox_phase.currentText()
def get_picks(station_names): def get_picks(station_names):
picks=[] picks = []
for station in station_names: for station in station_names:
try: try:
station=station.split('.')[-1] station = station.split('.')[-1]
picks.append(self.picks_dict[station][phase]['mpp']) picks.append(self.picks_dict[station][phase]['mpp'])
except: except:
picks.append(np.nan) picks.append(np.nan)
return picks return picks
def get_picks_rel(picks): def get_picks_rel(picks):
picks_rel=[] picks_rel = []
picks_utc = [] picks_utc = []
for pick in picks: for pick in picks:
if type(pick) is obspy.core.utcdatetime.UTCDateTime: if type(pick) is obspy.core.utcdatetime.UTCDateTime:
picks_utc.append(pick) picks_utc.append(pick)
minp = min(picks_utc) minp = min(picks_utc)
for pick in picks: for pick in picks:
if type(pick) is obspy.core.utcdatetime.UTCDateTime: if type(pick) is obspy.core.utcdatetime.UTCDateTime:
pick -= minp pick -= minp
picks_rel.append(pick) picks_rel.append(pick)
return picks_rel return picks_rel
self.picks = get_picks(self.station_names) self.picks = get_picks(self.station_names)
self.picks_rel = get_picks_rel(self.picks) self.picks_rel = get_picks_rel(self.picks)
def init_picks_active(self): def init_picks_active(self):
def remove_nan_picks(picks): def remove_nan_picks(picks):
picks_no_nan=[] picks_no_nan = []
for pick in picks: for pick in picks:
if not np.isnan(pick): if not np.isnan(pick):
picks_no_nan.append(pick) picks_no_nan.append(pick)
return picks_no_nan return picks_no_nan
self.picks_no_nan = remove_nan_picks(self.picks_rel) self.picks_no_nan = remove_nan_picks(self.picks_rel)
def init_stations_active(self): def init_stations_active(self):
def remove_nan_lat_lon(picks, lat, lon): def remove_nan_lat_lon(picks, lat, lon):
lat_no_nan=[] lat_no_nan = []
lon_no_nan=[] lon_no_nan = []
for index, pick in enumerate(picks): for index, pick in enumerate(picks):
if not np.isnan(pick): if not np.isnan(pick):
lat_no_nan.append(lat[index]) lat_no_nan.append(lat[index])
lon_no_nan.append(lon[index]) lon_no_nan.append(lon[index])
return lat_no_nan, lon_no_nan return lat_no_nan, lon_no_nan
self.lat_no_nan, self.lon_no_nan = remove_nan_lat_lon(self.picks_rel, self.lat, self.lon) self.lat_no_nan, self.lon_no_nan = remove_nan_lat_lon(self.picks_rel, self.lat, self.lon)
def init_lat_lon_dimensions(self): def init_lat_lon_dimensions(self):
@ -189,7 +189,7 @@ class map_projection(QtGui.QWidget):
londim = max(lon) - min(lon) londim = max(lon) - min(lon)
latdim = max(lat) - min(lat) latdim = max(lat) - min(lat)
return londim, latdim return londim, latdim
self.londim, self.latdim = get_lon_lat_dim(self.lon, self.lat) self.londim, self.latdim = get_lon_lat_dim(self.lon, self.lat)
def init_x_y_dimensions(self): def init_x_y_dimensions(self):
@ -197,30 +197,30 @@ class map_projection(QtGui.QWidget):
xdim = max(x) - min(x) xdim = max(x) - min(x)
ydim = max(y) - min(y) ydim = max(y) - min(y)
return xdim, ydim return xdim, ydim
self.x, self.y = self.basemap(self.lon, self.lat) self.x, self.y = self.basemap(self.lon, self.lat)
self.xdim, self.ydim = get_x_y_dim(self.x, self.y) self.xdim, self.ydim = get_x_y_dim(self.x, self.y)
def init_basemap(self, resolution='l'): def init_basemap(self, resolution='l'):
#basemap = Basemap(projection=projection, resolution = resolution, ax=self.main_ax) # basemap = Basemap(projection=projection, resolution = resolution, ax=self.main_ax)
basemap = Basemap(projection='lcc', resolution = resolution, ax=self.main_ax, basemap = Basemap(projection='lcc', resolution=resolution, ax=self.main_ax,
width=5e6, height=2e6, width=5e6, height=2e6,
lat_0=(min(self.lat)+max(self.lat))/2., lat_0=(min(self.lat) + max(self.lat)) / 2.,
lon_0=(min(self.lon)+max(self.lon))/2.) lon_0=(min(self.lon) + max(self.lon)) / 2.)
#basemap.fillcontinents(color=None, lake_color='aqua',zorder=1) # basemap.fillcontinents(color=None, lake_color='aqua',zorder=1)
basemap.drawmapboundary(zorder=2)#fill_color='darkblue') basemap.drawmapboundary(zorder=2) # fill_color='darkblue')
basemap.shadedrelief(zorder=3) basemap.shadedrelief(zorder=3)
basemap.drawcountries(zorder=4) basemap.drawcountries(zorder=4)
basemap.drawstates(zorder=5) basemap.drawstates(zorder=5)
basemap.drawcoastlines(zorder=6) basemap.drawcoastlines(zorder=6)
self.basemap = basemap self.basemap = basemap
self.figure.tight_layout() self.figure.tight_layout()
def init_lat_lon_grid(self): def init_lat_lon_grid(self):
def get_lat_lon_axis(lat, lon): def get_lat_lon_axis(lat, lon):
steplat = (max(lat)-min(lat))/250 steplat = (max(lat) - min(lat)) / 250
steplon = (max(lon)-min(lon))/250 steplon = (max(lon) - min(lon)) / 250
lataxis = np.arange(min(lat), max(lat), steplat) lataxis = np.arange(min(lat), max(lat), steplat)
lonaxis = np.arange(min(lon), max(lon), steplon) lonaxis = np.arange(min(lon), max(lon), steplon)
@ -235,7 +235,8 @@ class map_projection(QtGui.QWidget):
def init_picksgrid(self): def init_picksgrid(self):
self.picksgrid_no_nan = griddata((self.lat_no_nan, self.lon_no_nan), self.picksgrid_no_nan = griddata((self.lat_no_nan, self.lon_no_nan),
self.picks_no_nan, (self.latgrid, self.longrid), method='linear') ################## self.picks_no_nan, (self.latgrid, self.longrid),
method='linear') ##################
def draw_contour_filled(self, nlevel='50'): def draw_contour_filled(self, nlevel='50'):
levels = np.linspace(min(self.picks_no_nan), max(self.picks_no_nan), nlevel) levels = np.linspace(min(self.picks_no_nan), max(self.picks_no_nan), nlevel)
@ -244,7 +245,7 @@ class map_projection(QtGui.QWidget):
def scatter_all_stations(self): def scatter_all_stations(self):
self.sc = self.basemap.scatter(self.lon, self.lat, s=50, facecolor='none', latlon=True, self.sc = self.basemap.scatter(self.lon, self.lat, s=50, facecolor='none', latlon=True,
zorder=10, picker=True, edgecolor='m', label='Not Picked') zorder=10, picker=True, edgecolor='m', label='Not Picked')
self.cid = self.canvas.mpl_connect('pick_event', self.onpick) self.cid = self.canvas.mpl_connect('pick_event', self.onpick)
if self.eventLoc: if self.eventLoc:
lat, lon = self.eventLoc lat, lon = self.eventLoc
@ -255,11 +256,11 @@ class map_projection(QtGui.QWidget):
lon = self.lon_no_nan lon = self.lon_no_nan
lat = self.lat_no_nan lat = self.lat_no_nan
#workaround because of an issue with latlon transformation of arrays with len <3 # workaround because of an issue with latlon transformation of arrays with len <3
if len(lon) <= 2 and len(lat) <= 2: if len(lon) <= 2 and len(lat) <= 2:
self.sc_picked = self.basemap.scatter(lon[0], lat[0], s=50, facecolor='white', self.sc_picked = self.basemap.scatter(lon[0], lat[0], s=50, facecolor='white',
c=self.picks_no_nan[0], latlon=True, zorder=11, label='Picked') c=self.picks_no_nan[0], latlon=True, zorder=11, label='Picked')
if len(lon) == 2 and len(lat) == 2: if len(lon) == 2 and len(lat) == 2:
self.sc_picked = self.basemap.scatter(lon[1], lat[1], s=50, facecolor='white', self.sc_picked = self.basemap.scatter(lon[1], lat[1], s=50, facecolor='white',
c=self.picks_no_nan[1], latlon=True, zorder=11) c=self.picks_no_nan[1], latlon=True, zorder=11)
else: else:
@ -267,11 +268,11 @@ class map_projection(QtGui.QWidget):
c=self.picks_no_nan, latlon=True, zorder=11, label='Picked') c=self.picks_no_nan, latlon=True, zorder=11, label='Picked')
def annotate_ax(self): def annotate_ax(self):
self.annotations=[] self.annotations = []
for index, name in enumerate(self.station_names): for index, name in enumerate(self.station_names):
self.annotations.append(self.main_ax.annotate(' %s' % name, xy=(self.x[index], self.y[index]), self.annotations.append(self.main_ax.annotate(' %s' % name, xy=(self.x[index], self.y[index]),
fontsize='x-small', color='white', zorder=12)) fontsize='x-small', color='white', zorder=12))
self.legend=self.main_ax.legend() self.legend = self.main_ax.legend()
def add_cbar(self, label): def add_cbar(self, label):
cbar = self.main_ax.figure.colorbar(self.sc_picked, fraction=0.025) cbar = self.main_ax.figure.colorbar(self.sc_picked, fraction=0.025)
@ -307,19 +308,19 @@ class map_projection(QtGui.QWidget):
def remove_drawings(self): def remove_drawings(self):
if hasattr(self, 'sc_picked'): if hasattr(self, 'sc_picked'):
self.sc_picked.remove() self.sc_picked.remove()
del(self.sc_picked) del (self.sc_picked)
if hasattr(self, 'sc_event'): if hasattr(self, 'sc_event'):
self.sc_event.remove() self.sc_event.remove()
del(self.sc_event) del (self.sc_event)
if hasattr(self, 'cbar'): if hasattr(self, 'cbar'):
self.cbar.remove() self.cbar.remove()
del(self.cbar) del (self.cbar)
if hasattr(self, 'contourf'): if hasattr(self, 'contourf'):
self.remove_contourf() self.remove_contourf()
del(self.contourf) del (self.contourf)
if hasattr(self, 'cid'): if hasattr(self, 'cid'):
self.canvas.mpl_disconnect(self.cid) self.canvas.mpl_disconnect(self.cid)
del(self.cid) del (self.cid)
try: try:
self.sc.remove() self.sc.remove()
except Exception as e: except Exception as e:
@ -343,18 +344,18 @@ class map_projection(QtGui.QWidget):
xlim = map.ax.get_xlim() xlim = map.ax.get_xlim()
ylim = map.ax.get_ylim() ylim = map.ax.get_ylim()
x, y = event.xdata, event.ydata x, y = event.xdata, event.ydata
zoom = {'up': 1./2., zoom = {'up': 1. / 2.,
'down': 2.} 'down': 2.}
if not event.xdata or not event.ydata: if not event.xdata or not event.ydata:
return return
if event.button in zoom: if event.button in zoom:
factor = zoom[event.button] factor = zoom[event.button]
xdiff = (xlim[1]-xlim[0])*factor xdiff = (xlim[1] - xlim[0]) * factor
xl = x - 0.5 * xdiff xl = x - 0.5 * xdiff
xr = x + 0.5 * xdiff xr = x + 0.5 * xdiff
ydiff = (ylim[1]-ylim[0])*factor ydiff = (ylim[1] - ylim[0]) * factor
yb = y - 0.5 * ydiff yb = y - 0.5 * ydiff
yt = y + 0.5 * ydiff yt = y + 0.5 * ydiff
@ -364,10 +365,8 @@ class map_projection(QtGui.QWidget):
map.ax.set_xlim(xl, xr) map.ax.set_xlim(xl, xr)
map.ax.set_ylim(yb, yt) map.ax.set_ylim(yb, yt)
map.ax.figure.canvas.draw() map.ax.figure.canvas.draw()
def _warn(self, message): def _warn(self, message):
self.qmb = QtGui.QMessageBox(QtGui.QMessageBox.Icon.Warning, self.qmb = QtGui.QMessageBox(QtGui.QMessageBox.Icon.Warning,
'Warning', message) 'Warning', message)
self.qmb.show() self.qmb.show()

24
pylot/core/util/pdf.py
View File

@ -2,20 +2,23 @@
# -*- coding: utf-8 -*- # -*- coding: utf-8 -*-
import warnings import warnings
import numpy as np import numpy as np
from obspy import UTCDateTime from obspy import UTCDateTime
from pylot.core.util.utils import fit_curve, find_nearest, clims from pylot.core.util.utils import fit_curve, clims
from pylot.core.util.version import get_git_version as _getVersionString from pylot.core.util.version import get_git_version as _getVersionString
__version__ = _getVersionString() __version__ = _getVersionString()
__author__ = 'sebastianw' __author__ = 'sebastianw'
def create_axis(x0, incr, npts): def create_axis(x0, incr, npts):
ax = np.zeros(npts) ax = np.zeros(npts)
for i in range(npts): for i in range(npts):
ax[i] = x0 + incr * i ax[i] = x0 + incr * i
return ax return ax
def gauss_parameter(te, tm, tl, eta): def gauss_parameter(te, tm, tl, eta):
''' '''
takes three onset times and returns the parameters sig1, sig2, a1 and a2 takes three onset times and returns the parameters sig1, sig2, a1 and a2
@ -79,9 +82,9 @@ def gauss_branches(k, param_tuple):
:returns fun_vals: list with function values along axes x :returns fun_vals: list with function values along axes x
''' '''
#python 3 workaround # python 3 workaround
mu, sig1, sig2, a1, a2 = param_tuple mu, sig1, sig2, a1, a2 = param_tuple
def _func(k, mu, sig1, sig2, a1, a2): def _func(k, mu, sig1, sig2, a1, a2):
if k < mu: if k < mu:
rval = a1 * 1 / (np.sqrt(2 * np.pi) * sig1) * np.exp(-((k - mu) / sig1) ** 2 / 2) rval = a1 * 1 / (np.sqrt(2 * np.pi) * sig1) * np.exp(-((k - mu) / sig1) ** 2 / 2)
@ -110,9 +113,9 @@ def exp_branches(k, param_tuple):
:returns fun_vals: list with function values along axes x: :returns fun_vals: list with function values along axes x:
''' '''
#python 3 workaround # python 3 workaround
mu, sig1, sig2, a = param_tuple mu, sig1, sig2, a = param_tuple
def _func(k, mu, sig1, sig2, a): def _func(k, mu, sig1, sig2, a):
mu = float(mu) mu = float(mu)
if k < mu: if k < mu:
@ -313,14 +316,14 @@ class ProbabilityDensityFunction(object):
:return float: rval :return float: rval
''' '''
#rval = 0 # rval = 0
#for x in self.axis: # for x in self.axis:
# rval += x * self.data(x) # rval += x * self.data(x)
rval = self.mu rval = self.mu
# Not sure about this! That might not be the barycentre. # Not sure about this! That might not be the barycentre.
# However, for std calculation (next function) # However, for std calculation (next function)
# self.mu is also used!! (LK, 02/2017) # self.mu is also used!! (LK, 02/2017)
return rval return rval
def standard_deviation(self): def standard_deviation(self):
mu = self.mu mu = self.mu
@ -394,7 +397,6 @@ class ProbabilityDensityFunction(object):
qu = self.quantile(1 - prob_value) qu = self.quantile(1 - prob_value)
return qu - ql return qu - ql
def quantile_dist_frac(self, x): def quantile_dist_frac(self, x):
""" """
takes a probability value and returns the fraction of two takes a probability value and returns the fraction of two
@ -411,8 +413,7 @@ class ProbabilityDensityFunction(object):
""" """
if x <= 0 or x >= 0.25: if x <= 0 or x >= 0.25:
raise ValueError('Value out of range.') raise ValueError('Value out of range.')
return self.quantile_distance(0.5-x)/self.quantile_distance(x) return self.quantile_distance(0.5 - x) / self.quantile_distance(x)
def plot(self, label=None): def plot(self, label=None):
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
@ -486,4 +487,3 @@ class ProbabilityDensityFunction(object):
x0, npts = self.commonlimits(incr, other) x0, npts = self.commonlimits(incr, other)
return x0, incr, npts return x0, incr, npts

3
pylot/core/util/plotting.py
View File

@ -3,6 +3,7 @@
import matplotlib.pyplot as plt import matplotlib.pyplot as plt
def create_bin_list(l_boundary, u_boundary, nbins=100): def create_bin_list(l_boundary, u_boundary, nbins=100):
""" """
takes two boundaries and a number of bins and creates a list of bins for takes two boundaries and a number of bins and creates a list of bins for
@ -54,4 +55,4 @@ def histplot(array, binlist, xlab='Values',
if fnout: if fnout:
plt.savefig(fnout) plt.savefig(fnout)
else: else:
plt.show() plt.show()

32
pylot/core/util/thread.py
View File

@ -1,6 +1,9 @@
# -*- coding: utf-8 -*- # -*- coding: utf-8 -*-
import sys, os, traceback
import multiprocessing import multiprocessing
import os
import sys
import traceback
from PySide.QtCore import QThread, Signal, Qt, Slot, QRunnable, QObject from PySide.QtCore import QThread, Signal, Qt, Slot, QRunnable, QObject
from PySide.QtGui import QDialog, QProgressBar, QLabel, QHBoxLayout, QPushButton from PySide.QtGui import QDialog, QProgressBar, QLabel, QHBoxLayout, QPushButton
@ -42,7 +45,7 @@ class AutoPickThread(QThread):
class Thread(QThread): class Thread(QThread):
message = Signal(str) message = Signal(str)
def __init__(self, parent, func, arg=None, progressText=None, pb_widget=None, redirect_stdout=False): def __init__(self, parent, func, arg=None, progressText=None, pb_widget=None, redirect_stdout=False):
QThread.__init__(self, parent) QThread.__init__(self, parent)
self.func = func self.func = func
@ -55,7 +58,7 @@ class Thread(QThread):
def run(self): def run(self):
if self.redirect_stdout: if self.redirect_stdout:
sys.stdout = self sys.stdout = self
try: try:
if self.arg: if self.arg:
self.data = self.func(self.arg) self.data = self.func(self.arg)
@ -68,7 +71,7 @@ class Thread(QThread):
exc_type, exc_obj, exc_tb = sys.exc_info() exc_type, exc_obj, exc_tb = sys.exc_info()
fname = os.path.split(exc_tb.tb_frame.f_code.co_filename)[1] fname = os.path.split(exc_tb.tb_frame.f_code.co_filename)[1]
print('Exception: {}, file: {}, line: {}'.format(exc_type, fname, exc_tb.tb_lineno)) print('Exception: {}, file: {}, line: {}'.format(exc_type, fname, exc_tb.tb_lineno))
sys.stdout = sys.__stdout__ sys.stdout = sys.__stdout__
def __del__(self): def __del__(self):
self.wait() self.wait()
@ -79,7 +82,7 @@ class Thread(QThread):
# generate widget if not given in init # generate widget if not given in init
if not self.pb_widget: if not self.pb_widget:
self.pb_widget = QDialog(self.parent()) self.pb_widget = QDialog(self.parent())
self.pb_widget.setWindowFlags(Qt.SplashScreen) self.pb_widget.setWindowFlags(Qt.SplashScreen)
self.pb_widget.setModal(True) self.pb_widget.setModal(True)
# add button # add button
@ -109,6 +112,7 @@ class Worker(QRunnable):
''' '''
''' '''
def __init__(self, fun, args, def __init__(self, fun, args,
progressText=None, progressText=None,
pb_widget=None, pb_widget=None,
@ -116,7 +120,7 @@ class Worker(QRunnable):
super(Worker, self).__init__() super(Worker, self).__init__()
self.fun = fun self.fun = fun
self.args = args self.args = args
#self.kwargs = kwargs # self.kwargs = kwargs
self.signals = WorkerSignals() self.signals = WorkerSignals()
self.progressText = progressText self.progressText = progressText
self.pb_widget = pb_widget self.pb_widget = pb_widget
@ -131,9 +135,9 @@ class Worker(QRunnable):
result = self.fun(self.args) result = self.fun(self.args)
except: except:
traceback.print_exc() traceback.print_exc()
exctype, value = sys.exc_info ()[:2] exctype, value = sys.exc_info()[:2]
print(exctype, value, traceback.format_exc()) print(exctype, value, traceback.format_exc())
#self.signals.error.emit ((exctype, value, traceback.format_exc ())) # self.signals.error.emit ((exctype, value, traceback.format_exc ()))
else: else:
self.signals.result.emit(result) self.signals.result.emit(result)
finally: finally:
@ -157,7 +161,7 @@ class WorkerSignals(QObject):
class MultiThread(QThread): class MultiThread(QThread):
finished = Signal(str) finished = Signal(str)
message = Signal(str) message = Signal(str)
def __init__(self, parent, func, args, ncores=1, def __init__(self, parent, func, args, ncores=1,
progressText=None, pb_widget=None, redirect_stdout=False): progressText=None, pb_widget=None, redirect_stdout=False):
@ -170,16 +174,16 @@ class MultiThread(QThread):
self.redirect_stdout = redirect_stdout self.redirect_stdout = redirect_stdout
self.finished.connect(self.hideProgressbar) self.finished.connect(self.hideProgressbar)
self.showProgressbar() self.showProgressbar()
def run(self): def run(self):
if self.redirect_stdout: if self.redirect_stdout:
sys.stdout = self sys.stdout = self
try: try:
if not self.ncores: if not self.ncores:
self.ncores = multiprocessing.cpu_count() self.ncores = multiprocessing.cpu_count()
pool = multiprocessing.Pool(self.ncores) pool = multiprocessing.Pool(self.ncores)
self.data = pool.map_async(self.func, self.args, callback=self.emitDone) self.data = pool.map_async(self.func, self.args, callback=self.emitDone)
#self.data = pool.apply_async(self.func, self.shotlist, callback=self.emitDone) #emit each time returned # self.data = pool.apply_async(self.func, self.shotlist, callback=self.emitDone) #emit each time returned
pool.close() pool.close()
self._executed = True self._executed = True
except Exception as e: except Exception as e:
@ -188,7 +192,7 @@ class MultiThread(QThread):
exc_type, exc_obj, exc_tb = sys.exc_info() exc_type, exc_obj, exc_tb = sys.exc_info()
fname = os.path.split(exc_tb.tb_frame.f_code.co_filename)[1] fname = os.path.split(exc_tb.tb_frame.f_code.co_filename)[1]
print('Exception: {}, file: {}, line: {}'.format(exc_type, fname, exc_tb.tb_lineno)) print('Exception: {}, file: {}, line: {}'.format(exc_type, fname, exc_tb.tb_lineno))
sys.stdout = sys.__stdout__ sys.stdout = sys.__stdout__
def __del__(self): def __del__(self):
self.wait() self.wait()
@ -197,7 +201,7 @@ class MultiThread(QThread):
if self.progressText: if self.progressText:
if not self.pb_widget: if not self.pb_widget:
self.pb_widget = QDialog(self.parent()) self.pb_widget = QDialog(self.parent())
self.pb_widget.setWindowFlags(Qt.SplashScreen) self.pb_widget.setWindowFlags(Qt.SplashScreen)
self.pb_widget.setModal(True) self.pb_widget.setModal(True)
hl = QHBoxLayout() hl = QHBoxLayout()
pb = QProgressBar() pb = QProgressBar()

25
pylot/core/util/utils.py
View File

@ -2,26 +2,28 @@
# -*- coding: utf-8 -*- # -*- coding: utf-8 -*-
import hashlib import hashlib
import numpy as np
from scipy.interpolate import splrep, splev
import os import os
import platform import platform
import re import re
import warnings
import subprocess import subprocess
import numpy as np
from obspy import UTCDateTime, read from obspy import UTCDateTime, read
from pylot.core.io.inputs import PylotParameter from pylot.core.io.inputs import PylotParameter
from scipy.interpolate import splrep, splev
def _pickle_method(m): def _pickle_method(m):
if m.im_self is None: if m.im_self is None:
return getattr, (m.im_class, m.im_func.func_name) return getattr, (m.im_class, m.im_func.func_name)
else: else:
return getattr, (m.im_self, m.im_func.func_name) return getattr, (m.im_self, m.im_func.func_name)
def fit_curve(x, y): def fit_curve(x, y):
return splev, splrep(x, y) return splev, splrep(x, y)
def getindexbounds(f, eta): def getindexbounds(f, eta):
mi = f.argmax() mi = f.argmax()
m = max(f) m = max(f)
@ -34,9 +36,9 @@ def getindexbounds(f, eta):
def gen_Pool(ncores='max'): def gen_Pool(ncores='max'):
import multiprocessing import multiprocessing
if ncores=='max': if ncores == 'max':
ncores=multiprocessing.cpu_count() ncores = multiprocessing.cpu_count()
pool = multiprocessing.Pool(ncores) pool = multiprocessing.Pool(ncores)
return pool return pool
@ -106,6 +108,7 @@ def findComboBoxIndex(combo_box, val):
""" """
return combo_box.findText(val) if combo_box.findText(val) is not -1 else 0 return combo_box.findText(val) if combo_box.findText(val) is not -1 else 0
def find_in_list(list, str): def find_in_list(list, str):
""" """
takes a list of strings and a string and returns the first list item takes a list of strings and a string and returns the first list item
@ -135,6 +138,7 @@ def find_in_list(list, str):
return rlist[0] return rlist[0]
return None return None
def find_nearest(array, value): def find_nearest(array, value):
''' '''
function find_nearest takes an array and a value and returns the function find_nearest takes an array and a value and returns the
@ -181,12 +185,14 @@ def fnConstructor(s):
fn = '_' + fn fn = '_' + fn
return fn return fn
def real_None(value): def real_None(value):
if value == 'None': if value == 'None':
return None return None
else: else:
return value return value
def four_digits(year): def four_digits(year):
""" """
takes a two digit year integer and returns the correct four digit equivalent takes a two digit year integer and returns the correct four digit equivalent
@ -307,6 +313,7 @@ def getPatternLine(fn, pattern):
return None return None
def is_executable(fn): def is_executable(fn):
""" """
takes a filename and returns True if the file is executable on the system takes a filename and returns True if the file is executable on the system
@ -492,6 +499,7 @@ def runProgram(cmd, parameter=None):
subprocess.check_output('{} | tee /dev/stderr'.format(cmd), shell=True) subprocess.check_output('{} | tee /dev/stderr'.format(cmd), shell=True)
def which(program, infile=None): def which(program, infile=None):
""" """
takes a program name and returns the full path to the executable or None takes a program name and returns the full path to the executable or None
@ -510,7 +518,7 @@ def which(program, infile=None):
bpath = os.path.join(os.path.expanduser('~'), '.pylot', 'pylot.in') bpath = os.path.join(os.path.expanduser('~'), '.pylot', 'pylot.in')
else: else:
bpath = os.path.join(os.path.expanduser('~'), '.pylot', infile) bpath = os.path.join(os.path.expanduser('~'), '.pylot', infile)
if os.path.exists(bpath): if os.path.exists(bpath):
nllocpath = ":" + PylotParameter(bpath).get('nllocbin') nllocpath = ":" + PylotParameter(bpath).get('nllocbin')
os.environ['PATH'] += nllocpath os.environ['PATH'] += nllocpath
@ -538,6 +546,7 @@ def which(program, infile=None):
return None return None
if __name__ == "__main__": if __name__ == "__main__":
import doctest import doctest

3561
pylot/core/util/widgets.py
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3
pylot/testing/testHelpForm.py
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@ -1,7 +1,8 @@
#!/usr/bin/env python #!/usr/bin/env python
# -*- coding: utf-8 -*- # -*- coding: utf-8 -*-
import sys, time import sys
from PySide.QtGui import QApplication from PySide.QtGui import QApplication
from pylot.core.util.widgets import HelpForm from pylot.core.util.widgets import HelpForm

2
pylot/testing/testPickDlg.py
View File

@ -2,6 +2,7 @@
# -*- coding: utf-8 -*- # -*- coding: utf-8 -*-
import sys import sys
import matplotlib import matplotlib
matplotlib.use('Qt4Agg') matplotlib.use('Qt4Agg')
@ -10,7 +11,6 @@ matplotlib.rcParams['backend.qt4'] = 'PySide'
from PySide.QtGui import QApplication from PySide.QtGui import QApplication
from obspy.core import read from obspy.core import read
from pylot.core.util.widgets import PickDlg from pylot.core.util.widgets import PickDlg
import icons_rc
app = QApplication(sys.argv) app = QApplication(sys.argv)

3
pylot/testing/testPropDlg.py
View File

@ -1,7 +1,8 @@
#!/usr/bin/env python #!/usr/bin/env python
# -*- coding: utf-8 -*- # -*- coding: utf-8 -*-
import sys, time import sys
from PySide.QtGui import QApplication from PySide.QtGui import QApplication
from pylot.core.util.widgets import PropertiesDlg from pylot.core.util.widgets import PropertiesDlg

4
pylot/testing/testUIcomponents.py
View File

@ -2,7 +2,9 @@
# -*- coding: utf-8 -*- # -*- coding: utf-8 -*-
import sys, time import sys
import time
from PySide.QtGui import QApplication from PySide.QtGui import QApplication
from pylot.core.util.widgets import FilterOptionsDialog, PropertiesDlg, HelpForm from pylot.core.util.widgets import FilterOptionsDialog, PropertiesDlg, HelpForm

6
pylot/testing/testUtils.py
View File

@ -8,20 +8,16 @@ import unittest
class Test(unittest.TestCase): class Test(unittest.TestCase):
def setUp(self): def setUp(self):
pass pass
def tearDown(self): def tearDown(self):
pass pass
def testName(self): def testName(self):
pass pass
if __name__ == "__main__": if __name__ == "__main__":
#import sys;sys.argv = ['', 'Test.testName'] # import sys;sys.argv = ['', 'Test.testName']
unittest.main() unittest.main()

4
pylot/testing/testWidgets.py
View File

@ -8,12 +8,10 @@ import unittest
class Test(unittest.TestCase): class Test(unittest.TestCase):
def testName(self): def testName(self):
pass pass
if __name__ == "__main__": if __name__ == "__main__":
#import sys;sys.argv = ['', 'Test.testName'] # import sys;sys.argv = ['', 'Test.testName']
unittest.main() unittest.main()

532
pylot/testing/test_autopick.py
View File

@ -6,40 +6,40 @@
Only for test purposes! Only for test purposes!
""" """
import argparse
import glob
from obspy.core import read from obspy.core import read
import matplotlib.pyplot as plt
import numpy as np
from pylot.core.pick.charfuns import * from pylot.core.pick.charfuns import *
from pylot.core.pick.picker import * from pylot.core.pick.picker import *
import glob
import argparse
def run_makeCF(project, database, event, iplot, station=None): def run_makeCF(project, database, event, iplot, station=None):
#parameters for CF calculation # parameters for CF calculation
t2 = 7 #length of moving window for HOS calculation [sec] t2 = 7 # length of moving window for HOS calculation [sec]
p = 4 #order of HOS p = 4 # order of HOS
cuttimes = [10, 50] #start and end time for CF calculation cuttimes = [10, 50] # start and end time for CF calculation
bpz = [2, 30] #corner frequencies of bandpass filter, vertical component bpz = [2, 30] # corner frequencies of bandpass filter, vertical component
bph = [2, 15] #corner frequencies of bandpass filter, horizontal components bph = [2, 15] # corner frequencies of bandpass filter, horizontal components
tdetz= 1.2 #length of AR-determination window [sec], vertical component tdetz = 1.2 # length of AR-determination window [sec], vertical component
tdeth= 0.8 #length of AR-determination window [sec], horizontal components tdeth = 0.8 # length of AR-determination window [sec], horizontal components
tpredz = 0.4 #length of AR-prediction window [sec], vertical component tpredz = 0.4 # length of AR-prediction window [sec], vertical component
tpredh = 0.4 #length of AR-prediction window [sec], horizontal components tpredh = 0.4 # length of AR-prediction window [sec], horizontal components
addnoise = 0.001 #add noise to seismogram for stable AR prediction addnoise = 0.001 # add noise to seismogram for stable AR prediction
arzorder = 2 #chosen order of AR process, vertical component arzorder = 2 # chosen order of AR process, vertical component
arhorder = 4 #chosen order of AR process, horizontal components arhorder = 4 # chosen order of AR process, horizontal components
TSNRhos = [5, 0.5, 1, 0.1] #window lengths [s] for calculating SNR for earliest/latest pick and quality assessment TSNRhos = [5, 0.5, 1, 0.1] # window lengths [s] for calculating SNR for earliest/latest pick and quality assessment
#from HOS-CF [noise window, safety gap, signal window, slope determination window] # from HOS-CF [noise window, safety gap, signal window, slope determination window]
TSNRarz = [5, 0.5, 1, 0.5] #window lengths [s] for calculating SNR for earliest/lates pick and quality assessment TSNRarz = [5, 0.5, 1, 0.5] # window lengths [s] for calculating SNR for earliest/lates pick and quality assessment
#from ARZ-CF # from ARZ-CF
#get waveform data # get waveform data
if station: if station:
dpz = '/data/%s/EVENT_DATA/LOCAL/%s/%s/%s*HZ.msd' % (project, database, event, station) dpz = '/data/%s/EVENT_DATA/LOCAL/%s/%s/%s*HZ.msd' % (project, database, event, station)
dpe = '/data/%s/EVENT_DATA/LOCAL/%s/%s/%s*HE.msd' % (project, database, event, station) dpe = '/data/%s/EVENT_DATA/LOCAL/%s/%s/%s*HE.msd' % (project, database, event, station)
dpn = '/data/%s/EVENT_DATA/LOCAL/%s/%s/%s*HN.msd' % (project, database, event, station) dpn = '/data/%s/EVENT_DATA/LOCAL/%s/%s/%s*HN.msd' % (project, database, event, station)
#dpz = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*_z.gse' % (project, database, event, station) # dpz = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*_z.gse' % (project, database, event, station)
#dpe = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*_e.gse' % (project, database, event, station) # dpe = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*_e.gse' % (project, database, event, station)
#dpn = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*_n.gse' % (project, database, event, station) # dpn = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*_n.gse' % (project, database, event, station)
else: else:
# dpz = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/*_z.gse' % (project, database, event) # dpz = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/*_z.gse' % (project, database, event)
# dpe = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/*_e.gse' % (project, database, event) # dpe = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/*_e.gse' % (project, database, event)
@ -51,245 +51,253 @@ def run_makeCF(project, database, event, iplot, station=None):
wfefiles = glob.glob(dpe) wfefiles = glob.glob(dpe)
wfnfiles = glob.glob(dpn) wfnfiles = glob.glob(dpn)
if wfzfiles: if wfzfiles:
for i in range(len(wfzfiles)): for i in range(len(wfzfiles)):
print 'Vertical component data found ...' print
print wfzfiles[i] 'Vertical component data found ...'
st = read('%s' % wfzfiles[i]) print
st_copy = st.copy() wfzfiles[i]
#filter and taper data st = read('%s' % wfzfiles[i])
tr_filt = st[0].copy() st_copy = st.copy()
tr_filt.filter('bandpass', freqmin=bpz[0], freqmax=bpz[1], zerophase=False) # filter and taper data
tr_filt.taper(max_percentage=0.05, type='hann') tr_filt = st[0].copy()
st_copy[0].data = tr_filt.data tr_filt.filter('bandpass', freqmin=bpz[0], freqmax=bpz[1], zerophase=False)
############################################################## tr_filt.taper(max_percentage=0.05, type='hann')
#calculate HOS-CF using subclass HOScf of class CharacteristicFunction st_copy[0].data = tr_filt.data
hoscf = HOScf(st_copy, cuttimes, t2, p) #instance of HOScf ##############################################################
############################################################## # calculate HOS-CF using subclass HOScf of class CharacteristicFunction
#calculate AIC-HOS-CF using subclass AICcf of class CharacteristicFunction hoscf = HOScf(st_copy, cuttimes, t2, p) # instance of HOScf
#class needs stream object => build it ##############################################################
tr_aic = tr_filt.copy() # calculate AIC-HOS-CF using subclass AICcf of class CharacteristicFunction
tr_aic.data = hoscf.getCF() # class needs stream object => build it
st_copy[0].data = tr_aic.data tr_aic = tr_filt.copy()
aiccf = AICcf(st_copy, cuttimes) #instance of AICcf tr_aic.data = hoscf.getCF()
############################################################## st_copy[0].data = tr_aic.data
#get prelimenary onset time from AIC-HOS-CF using subclass AICPicker of class AutoPicking aiccf = AICcf(st_copy, cuttimes) # instance of AICcf
aicpick = AICPicker(aiccf, None, TSNRhos, 3, 10, None, 0.1) ##############################################################
############################################################## # get prelimenary onset time from AIC-HOS-CF using subclass AICPicker of class AutoPicking
#get refined onset time from HOS-CF using class Picker aicpick = AICPicker(aiccf, None, TSNRhos, 3, 10, None, 0.1)
hospick = PragPicker(hoscf, None, TSNRhos, 2, 10, 0.001, 0.2, aicpick.getpick()) ##############################################################
#get earliest and latest possible picks # get refined onset time from HOS-CF using class Picker
hosELpick = EarlLatePicker(hoscf, 1.5, TSNRhos, None, 10, None, None, hospick.getpick()) hospick = PragPicker(hoscf, None, TSNRhos, 2, 10, 0.001, 0.2, aicpick.getpick())
############################################################## # get earliest and latest possible picks
#calculate ARZ-CF using subclass ARZcf of class CharcteristicFunction hosELpick = EarlLatePicker(hoscf, 1.5, TSNRhos, None, 10, None, None, hospick.getpick())
#get stream object of filtered data ##############################################################
st_copy[0].data = tr_filt.data # calculate ARZ-CF using subclass ARZcf of class CharcteristicFunction
arzcf = ARZcf(st_copy, cuttimes, tpredz, arzorder, tdetz, addnoise) #instance of ARZcf # get stream object of filtered data
############################################################## st_copy[0].data = tr_filt.data
#calculate AIC-ARZ-CF using subclass AICcf of class CharacteristicFunction arzcf = ARZcf(st_copy, cuttimes, tpredz, arzorder, tdetz, addnoise) # instance of ARZcf
#class needs stream object => build it ##############################################################
tr_arzaic = tr_filt.copy() # calculate AIC-ARZ-CF using subclass AICcf of class CharacteristicFunction
tr_arzaic.data = arzcf.getCF() # class needs stream object => build it
st_copy[0].data = tr_arzaic.data tr_arzaic = tr_filt.copy()
araiccf = AICcf(st_copy, cuttimes, tpredz, 0, tdetz) #instance of AICcf tr_arzaic.data = arzcf.getCF()
############################################################## st_copy[0].data = tr_arzaic.data
#get onset time from AIC-ARZ-CF using subclass AICPicker of class AutoPicking araiccf = AICcf(st_copy, cuttimes, tpredz, 0, tdetz) # instance of AICcf
aicarzpick = AICPicker(araiccf, 1.5, TSNRarz, 2, 10, None, 0.1) ##############################################################
############################################################## # get onset time from AIC-ARZ-CF using subclass AICPicker of class AutoPicking
#get refined onset time from ARZ-CF using class Picker aicarzpick = AICPicker(araiccf, 1.5, TSNRarz, 2, 10, None, 0.1)
arzpick = PragPicker(arzcf, 1.5, TSNRarz, 2.0, 10, 0.1, 0.05, aicarzpick.getpick()) ##############################################################
#get earliest and latest possible picks # get refined onset time from ARZ-CF using class Picker
arzELpick = EarlLatePicker(arzcf, 1.5, TSNRarz, None, 10, None, None, arzpick.getpick()) arzpick = PragPicker(arzcf, 1.5, TSNRarz, 2.0, 10, 0.1, 0.05, aicarzpick.getpick())
# get earliest and latest possible picks
arzELpick = EarlLatePicker(arzcf, 1.5, TSNRarz, None, 10, None, None, arzpick.getpick())
elif not wfzfiles: elif not wfzfiles:
print 'No vertical component data found!' print
'No vertical component data found!'
if wfefiles and wfnfiles: if wfefiles and wfnfiles:
for i in range(len(wfefiles)): for i in range(len(wfefiles)):
print 'Horizontal component data found ...' print
print wfefiles[i] 'Horizontal component data found ...'
print wfnfiles[i] print
#merge streams wfefiles[i]
H = read('%s' % wfefiles[i]) print
H += read('%s' % wfnfiles[i]) wfnfiles[i]
H_copy = H.copy() # merge streams
#filter and taper data H = read('%s' % wfefiles[i])
trH1_filt = H[0].copy() H += read('%s' % wfnfiles[i])
trH2_filt = H[1].copy() H_copy = H.copy()
trH1_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False) # filter and taper data
trH2_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False) trH1_filt = H[0].copy()
trH1_filt.taper(max_percentage=0.05, type='hann') trH2_filt = H[1].copy()
trH2_filt.taper(max_percentage=0.05, type='hann') trH1_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False)
H_copy[0].data = trH1_filt.data trH2_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False)
H_copy[1].data = trH2_filt.data trH1_filt.taper(max_percentage=0.05, type='hann')
trH2_filt.taper(max_percentage=0.05, type='hann')
H_copy[0].data = trH1_filt.data
H_copy[1].data = trH2_filt.data
############################################################## ##############################################################
#calculate ARH-CF using subclass ARHcf of class CharcteristicFunction # calculate ARH-CF using subclass ARHcf of class CharcteristicFunction
arhcf = ARHcf(H_copy, cuttimes, tpredh, arhorder, tdeth, addnoise) #instance of ARHcf arhcf = ARHcf(H_copy, cuttimes, tpredh, arhorder, tdeth, addnoise) # instance of ARHcf
############################################################## ##############################################################
#calculate AIC-ARH-CF using subclass AICcf of class CharacteristicFunction # calculate AIC-ARH-CF using subclass AICcf of class CharacteristicFunction
#class needs stream object => build it # class needs stream object => build it
tr_arhaic = trH1_filt.copy() tr_arhaic = trH1_filt.copy()
tr_arhaic.data = arhcf.getCF() tr_arhaic.data = arhcf.getCF()
H_copy[0].data = tr_arhaic.data H_copy[0].data = tr_arhaic.data
#calculate ARH-AIC-CF # calculate ARH-AIC-CF
arhaiccf = AICcf(H_copy, cuttimes, tpredh, 0, tdeth) #instance of AICcf arhaiccf = AICcf(H_copy, cuttimes, tpredh, 0, tdeth) # instance of AICcf
############################################################## ##############################################################
#get onset time from AIC-ARH-CF using subclass AICPicker of class AutoPicking # get onset time from AIC-ARH-CF using subclass AICPicker of class AutoPicking
aicarhpick = AICPicker(arhaiccf, 1.5, TSNRarz, 4, 10, None, 0.1) aicarhpick = AICPicker(arhaiccf, 1.5, TSNRarz, 4, 10, None, 0.1)
############################################################### ###############################################################
#get refined onset time from ARH-CF using class Picker # get refined onset time from ARH-CF using class Picker
arhpick = PragPicker(arhcf, 1.5, TSNRarz, 2.5, 10, 0.1, 0.05, aicarhpick.getpick()) arhpick = PragPicker(arhcf, 1.5, TSNRarz, 2.5, 10, 0.1, 0.05, aicarhpick.getpick())
#get earliest and latest possible picks # get earliest and latest possible picks
arhELpick = EarlLatePicker(arhcf, 1.5, TSNRarz, None, 10, None, None, arhpick.getpick()) arhELpick = EarlLatePicker(arhcf, 1.5, TSNRarz, None, 10, None, None, arhpick.getpick())
# create stream with 3 traces
# merge streams
AllC = read('%s' % wfefiles[i])
AllC += read('%s' % wfnfiles[i])
AllC += read('%s' % wfzfiles[i])
# filter and taper data
All1_filt = AllC[0].copy()
All2_filt = AllC[1].copy()
All3_filt = AllC[2].copy()
All1_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False)
All2_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False)
All3_filt.filter('bandpass', freqmin=bpz[0], freqmax=bpz[1], zerophase=False)
All1_filt.taper(max_percentage=0.05, type='hann')
All2_filt.taper(max_percentage=0.05, type='hann')
All3_filt.taper(max_percentage=0.05, type='hann')
AllC[0].data = All1_filt.data
AllC[1].data = All2_filt.data
AllC[2].data = All3_filt.data
# calculate AR3C-CF using subclass AR3Ccf of class CharacteristicFunction
ar3ccf = AR3Ccf(AllC, cuttimes, tpredz, arhorder, tdetz, addnoise) # instance of AR3Ccf
# get earliest and latest possible pick from initial ARH-pick
ar3cELpick = EarlLatePicker(ar3ccf, 1.5, TSNRarz, None, 10, None, None, arhpick.getpick())
##############################################################
if iplot:
# plot vertical trace
plt.figure()
tr = st[0]
tdata = np.arange(0, tr.stats.npts / tr.stats.sampling_rate, tr.stats.delta)
p1, = plt.plot(tdata, tr_filt.data / max(tr_filt.data), 'k')
p2, = plt.plot(hoscf.getTimeArray(), hoscf.getCF() / max(hoscf.getCF()), 'r')
p3, = plt.plot(aiccf.getTimeArray(), aiccf.getCF() / max(aiccf.getCF()), 'b')
p4, = plt.plot(arzcf.getTimeArray(), arzcf.getCF() / max(arzcf.getCF()), 'g')
p5, = plt.plot(araiccf.getTimeArray(), araiccf.getCF() / max(araiccf.getCF()), 'y')
plt.plot([aicpick.getpick(), aicpick.getpick()], [-1, 1], 'b--')
plt.plot([aicpick.getpick() - 0.5, aicpick.getpick() + 0.5], [1, 1], 'b')
plt.plot([aicpick.getpick() - 0.5, aicpick.getpick() + 0.5], [-1, -1], 'b')
plt.plot([hospick.getpick(), hospick.getpick()], [-1.3, 1.3], 'r', linewidth=2)
plt.plot([hospick.getpick() - 0.5, hospick.getpick() + 0.5], [1.3, 1.3], 'r')
plt.plot([hospick.getpick() - 0.5, hospick.getpick() + 0.5], [-1.3, -1.3], 'r')
plt.plot([hosELpick.getLpick(), hosELpick.getLpick()], [-1.1, 1.1], 'r--')
plt.plot([hosELpick.getEpick(), hosELpick.getEpick()], [-1.1, 1.1], 'r--')
plt.plot([aicarzpick.getpick(), aicarzpick.getpick()], [-1.2, 1.2], 'y', linewidth=2)
plt.plot([aicarzpick.getpick() - 0.5, aicarzpick.getpick() + 0.5], [1.2, 1.2], 'y')
plt.plot([aicarzpick.getpick() - 0.5, aicarzpick.getpick() + 0.5], [-1.2, -1.2], 'y')
plt.plot([arzpick.getpick(), arzpick.getpick()], [-1.4, 1.4], 'g', linewidth=2)
plt.plot([arzpick.getpick() - 0.5, arzpick.getpick() + 0.5], [1.4, 1.4], 'g')
plt.plot([arzpick.getpick() - 0.5, arzpick.getpick() + 0.5], [-1.4, -1.4], 'g')
plt.plot([arzELpick.getLpick(), arzELpick.getLpick()], [-1.2, 1.2], 'g--')
plt.plot([arzELpick.getEpick(), arzELpick.getEpick()], [-1.2, 1.2], 'g--')
plt.yticks([])
plt.ylim([-1.5, 1.5])
plt.xlabel('Time [s]')
plt.ylabel('Normalized Counts')
plt.title('%s, %s, CF-SNR=%7.2f, CF-Slope=%12.2f' % (tr.stats.station, \
tr.stats.channel, aicpick.getSNR(),
aicpick.getSlope()))
plt.suptitle(tr.stats.starttime)
plt.legend([p1, p2, p3, p4, p5], ['Data', 'HOS-CF', 'HOSAIC-CF', 'ARZ-CF', 'ARZAIC-CF'])
# plot horizontal traces
plt.figure(2)
plt.subplot(2, 1, 1)
tsteph = tpredh / 4
th1data = np.arange(0, trH1_filt.stats.npts / trH1_filt.stats.sampling_rate, trH1_filt.stats.delta)
th2data = np.arange(0, trH2_filt.stats.npts / trH2_filt.stats.sampling_rate, trH2_filt.stats.delta)
tarhcf = np.arange(0, len(arhcf.getCF()) * tsteph, tsteph) + cuttimes[0] + tdeth + tpredh
p21, = plt.plot(th1data, trH1_filt.data / max(trH1_filt.data), 'k')
p22, = plt.plot(arhcf.getTimeArray(), arhcf.getCF() / max(arhcf.getCF()), 'r')
p23, = plt.plot(arhaiccf.getTimeArray(), arhaiccf.getCF() / max(arhaiccf.getCF()))
plt.plot([aicarhpick.getpick(), aicarhpick.getpick()], [-1, 1], 'b')
plt.plot([aicarhpick.getpick() - 0.5, aicarhpick.getpick() + 0.5], [1, 1], 'b')
plt.plot([aicarhpick.getpick() - 0.5, aicarhpick.getpick() + 0.5], [-1, -1], 'b')
plt.plot([arhpick.getpick(), arhpick.getpick()], [-1, 1], 'r')
plt.plot([arhpick.getpick() - 0.5, arhpick.getpick() + 0.5], [1, 1], 'r')
plt.plot([arhpick.getpick() - 0.5, arhpick.getpick() + 0.5], [-1, -1], 'r')
plt.plot([arhELpick.getLpick(), arhELpick.getLpick()], [-0.8, 0.8], 'r--')
plt.plot([arhELpick.getEpick(), arhELpick.getEpick()], [-0.8, 0.8], 'r--')
plt.plot([arhpick.getpick() + arhELpick.getPickError(), arhpick.getpick() + arhELpick.getPickError()], \
[-0.2, 0.2], 'r--')
plt.plot([arhpick.getpick() - arhELpick.getPickError(), arhpick.getpick() - arhELpick.getPickError()], \
[-0.2, 0.2], 'r--')
plt.yticks([])
plt.ylim([-1.5, 1.5])
plt.ylabel('Normalized Counts')
plt.title([trH1_filt.stats.station, trH1_filt.stats.channel])
plt.suptitle(trH1_filt.stats.starttime)
plt.legend([p21, p22, p23], ['Data', 'ARH-CF', 'ARHAIC-CF'])
plt.subplot(2, 1, 2)
plt.plot(th2data, trH2_filt.data / max(trH2_filt.data), 'k')
plt.plot(arhcf.getTimeArray(), arhcf.getCF() / max(arhcf.getCF()), 'r')
plt.plot(arhaiccf.getTimeArray(), arhaiccf.getCF() / max(arhaiccf.getCF()))
plt.plot([aicarhpick.getpick(), aicarhpick.getpick()], [-1, 1], 'b')
plt.plot([aicarhpick.getpick() - 0.5, aicarhpick.getpick() + 0.5], [1, 1], 'b')
plt.plot([aicarhpick.getpick() - 0.5, aicarhpick.getpick() + 0.5], [-1, -1], 'b')
plt.plot([arhpick.getpick(), arhpick.getpick()], [-1, 1], 'r')
plt.plot([arhpick.getpick() - 0.5, arhpick.getpick() + 0.5], [1, 1], 'r')
plt.plot([arhpick.getpick() - 0.5, arhpick.getpick() + 0.5], [-1, -1], 'r')
plt.plot([arhELpick.getLpick(), arhELpick.getLpick()], [-0.8, 0.8], 'r--')
plt.plot([arhELpick.getEpick(), arhELpick.getEpick()], [-0.8, 0.8], 'r--')
plt.plot([arhpick.getpick() + arhELpick.getPickError(), arhpick.getpick() + arhELpick.getPickError()], \
[-0.2, 0.2], 'r--')
plt.plot([arhpick.getpick() - arhELpick.getPickError(), arhpick.getpick() - arhELpick.getPickError()], \
[-0.2, 0.2], 'r--')
plt.title([trH2_filt.stats.station, trH2_filt.stats.channel])
plt.yticks([])
plt.ylim([-1.5, 1.5])
plt.xlabel('Time [s]')
plt.ylabel('Normalized Counts')
# plot 3-component window
plt.figure(3)
plt.subplot(3, 1, 1)
p31, = plt.plot(tdata, tr_filt.data / max(tr_filt.data), 'k')
p32, = plt.plot(ar3ccf.getTimeArray(), ar3ccf.getCF() / max(ar3ccf.getCF()), 'r')
plt.plot([arhpick.getpick(), arhpick.getpick()], [-1, 1], 'b')
plt.plot([arhpick.getpick() - 0.5, arhpick.getpick() + 0.5], [-1, -1], 'b')
plt.plot([arhpick.getpick() - 0.5, arhpick.getpick() + 0.5], [1, 1], 'b')
plt.plot([ar3cELpick.getLpick(), ar3cELpick.getLpick()], [-0.8, 0.8], 'b--')
plt.plot([ar3cELpick.getEpick(), ar3cELpick.getEpick()], [-0.8, 0.8], 'b--')
plt.yticks([])
plt.xticks([])
plt.ylabel('Normalized Counts')
plt.title([tr.stats.station, tr.stats.channel])
plt.suptitle(trH1_filt.stats.starttime)
plt.legend([p31, p32], ['Data', 'AR3C-CF'])
plt.subplot(3, 1, 2)
plt.plot(th1data, trH1_filt.data / max(trH1_filt.data), 'k')
plt.plot(ar3ccf.getTimeArray(), ar3ccf.getCF() / max(ar3ccf.getCF()), 'r')
plt.plot([arhpick.getpick(), arhpick.getpick()], [-1, 1], 'b')
plt.plot([arhpick.getpick() - 0.5, arhpick.getpick() + 0.5], [-1, -1], 'b')
plt.plot([arhpick.getpick() - 0.5, arhpick.getpick() + 0.5], [1, 1], 'b')
plt.plot([ar3cELpick.getLpick(), ar3cELpick.getLpick()], [-0.8, 0.8], 'b--')
plt.plot([ar3cELpick.getEpick(), ar3cELpick.getEpick()], [-0.8, 0.8], 'b--')
plt.yticks([])
plt.xticks([])
plt.ylabel('Normalized Counts')
plt.title([trH1_filt.stats.station, trH1_filt.stats.channel])
plt.subplot(3, 1, 3)
plt.plot(th2data, trH2_filt.data / max(trH2_filt.data), 'k')
plt.plot(ar3ccf.getTimeArray(), ar3ccf.getCF() / max(ar3ccf.getCF()), 'r')
plt.plot([arhpick.getpick(), arhpick.getpick()], [-1, 1], 'b')
plt.plot([arhpick.getpick() - 0.5, arhpick.getpick() + 0.5], [-1, -1], 'b')
plt.plot([arhpick.getpick() - 0.5, arhpick.getpick() + 0.5], [1, 1], 'b')
plt.plot([ar3cELpick.getLpick(), ar3cELpick.getLpick()], [-0.8, 0.8], 'b--')
plt.plot([ar3cELpick.getEpick(), ar3cELpick.getEpick()], [-0.8, 0.8], 'b--')
plt.yticks([])
plt.ylabel('Normalized Counts')
plt.title([trH2_filt.stats.station, trH2_filt.stats.channel])
plt.xlabel('Time [s]')
plt.show()
raw_input()
plt.close()
#create stream with 3 traces
#merge streams
AllC = read('%s' % wfefiles[i])
AllC += read('%s' % wfnfiles[i])
AllC += read('%s' % wfzfiles[i])
#filter and taper data
All1_filt = AllC[0].copy()
All2_filt = AllC[1].copy()
All3_filt = AllC[2].copy()
All1_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False)
All2_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False)
All3_filt.filter('bandpass', freqmin=bpz[0], freqmax=bpz[1], zerophase=False)
All1_filt.taper(max_percentage=0.05, type='hann')
All2_filt.taper(max_percentage=0.05, type='hann')
All3_filt.taper(max_percentage=0.05, type='hann')
AllC[0].data = All1_filt.data
AllC[1].data = All2_filt.data
AllC[2].data = All3_filt.data
#calculate AR3C-CF using subclass AR3Ccf of class CharacteristicFunction
ar3ccf = AR3Ccf(AllC, cuttimes, tpredz, arhorder, tdetz, addnoise) #instance of AR3Ccf
#get earliest and latest possible pick from initial ARH-pick
ar3cELpick = EarlLatePicker(ar3ccf, 1.5, TSNRarz, None, 10, None, None, arhpick.getpick())
##############################################################
if iplot:
#plot vertical trace
plt.figure()
tr = st[0]
tdata = np.arange(0, tr.stats.npts / tr.stats.sampling_rate, tr.stats.delta)
p1, = plt.plot(tdata, tr_filt.data/max(tr_filt.data), 'k')
p2, = plt.plot(hoscf.getTimeArray(), hoscf.getCF() / max(hoscf.getCF()), 'r')
p3, = plt.plot(aiccf.getTimeArray(), aiccf.getCF()/max(aiccf.getCF()), 'b')
p4, = plt.plot(arzcf.getTimeArray(), arzcf.getCF()/max(arzcf.getCF()), 'g')
p5, = plt.plot(araiccf.getTimeArray(), araiccf.getCF()/max(araiccf.getCF()), 'y')
plt.plot([aicpick.getpick(), aicpick.getpick()], [-1, 1], 'b--')
plt.plot([aicpick.getpick()-0.5, aicpick.getpick()+0.5], [1, 1], 'b')
plt.plot([aicpick.getpick()-0.5, aicpick.getpick()+0.5], [-1, -1], 'b')
plt.plot([hospick.getpick(), hospick.getpick()], [-1.3, 1.3], 'r', linewidth=2)
plt.plot([hospick.getpick()-0.5, hospick.getpick()+0.5], [1.3, 1.3], 'r')
plt.plot([hospick.getpick()-0.5, hospick.getpick()+0.5], [-1.3, -1.3], 'r')
plt.plot([hosELpick.getLpick(), hosELpick.getLpick()], [-1.1, 1.1], 'r--')
plt.plot([hosELpick.getEpick(), hosELpick.getEpick()], [-1.1, 1.1], 'r--')
plt.plot([aicarzpick.getpick(), aicarzpick.getpick()], [-1.2, 1.2], 'y', linewidth=2)
plt.plot([aicarzpick.getpick()-0.5, aicarzpick.getpick()+0.5], [1.2, 1.2], 'y')
plt.plot([aicarzpick.getpick()-0.5, aicarzpick.getpick()+0.5], [-1.2, -1.2], 'y')
plt.plot([arzpick.getpick(), arzpick.getpick()], [-1.4, 1.4], 'g', linewidth=2)
plt.plot([arzpick.getpick()-0.5, arzpick.getpick()+0.5], [1.4, 1.4], 'g')
plt.plot([arzpick.getpick()-0.5, arzpick.getpick()+0.5], [-1.4, -1.4], 'g')
plt.plot([arzELpick.getLpick(), arzELpick.getLpick()], [-1.2, 1.2], 'g--')
plt.plot([arzELpick.getEpick(), arzELpick.getEpick()], [-1.2, 1.2], 'g--')
plt.yticks([])
plt.ylim([-1.5, 1.5])
plt.xlabel('Time [s]')
plt.ylabel('Normalized Counts')
plt.title('%s, %s, CF-SNR=%7.2f, CF-Slope=%12.2f' % (tr.stats.station, \
tr.stats.channel, aicpick.getSNR(), aicpick.getSlope()))
plt.suptitle(tr.stats.starttime)
plt.legend([p1, p2, p3, p4, p5], ['Data', 'HOS-CF', 'HOSAIC-CF', 'ARZ-CF', 'ARZAIC-CF'])
#plot horizontal traces
plt.figure(2)
plt.subplot(2,1,1)
tsteph = tpredh / 4
th1data = np.arange(0, trH1_filt.stats.npts / trH1_filt.stats.sampling_rate, trH1_filt.stats.delta)
th2data = np.arange(0, trH2_filt.stats.npts / trH2_filt.stats.sampling_rate, trH2_filt.stats.delta)
tarhcf = np.arange(0, len(arhcf.getCF()) * tsteph, tsteph) + cuttimes[0] + tdeth +tpredh
p21, = plt.plot(th1data, trH1_filt.data/max(trH1_filt.data), 'k')
p22, = plt.plot(arhcf.getTimeArray(), arhcf.getCF()/max(arhcf.getCF()), 'r')
p23, = plt.plot(arhaiccf.getTimeArray(), arhaiccf.getCF()/max(arhaiccf.getCF()))
plt.plot([aicarhpick.getpick(), aicarhpick.getpick()], [-1, 1], 'b')
plt.plot([aicarhpick.getpick()-0.5, aicarhpick.getpick()+0.5], [1, 1], 'b')
plt.plot([aicarhpick.getpick()-0.5, aicarhpick.getpick()+0.5], [-1, -1], 'b')
plt.plot([arhpick.getpick(), arhpick.getpick()], [-1, 1], 'r')
plt.plot([arhpick.getpick()-0.5, arhpick.getpick()+0.5], [1, 1], 'r')
plt.plot([arhpick.getpick()-0.5, arhpick.getpick()+0.5], [-1, -1], 'r')
plt.plot([arhELpick.getLpick(), arhELpick.getLpick()], [-0.8, 0.8], 'r--')
plt.plot([arhELpick.getEpick(), arhELpick.getEpick()], [-0.8, 0.8], 'r--')
plt.plot([arhpick.getpick() + arhELpick.getPickError(), arhpick.getpick() + arhELpick.getPickError()], \
[-0.2, 0.2], 'r--')
plt.plot([arhpick.getpick() - arhELpick.getPickError(), arhpick.getpick() - arhELpick.getPickError()], \
[-0.2, 0.2], 'r--')
plt.yticks([])
plt.ylim([-1.5, 1.5])
plt.ylabel('Normalized Counts')
plt.title([trH1_filt.stats.station, trH1_filt.stats.channel])
plt.suptitle(trH1_filt.stats.starttime)
plt.legend([p21, p22, p23], ['Data', 'ARH-CF', 'ARHAIC-CF'])
plt.subplot(2,1,2)
plt.plot(th2data, trH2_filt.data/max(trH2_filt.data), 'k')
plt.plot(arhcf.getTimeArray(), arhcf.getCF()/max(arhcf.getCF()), 'r')
plt.plot(arhaiccf.getTimeArray(), arhaiccf.getCF()/max(arhaiccf.getCF()))
plt.plot([aicarhpick.getpick(), aicarhpick.getpick()], [-1, 1], 'b')
plt.plot([aicarhpick.getpick()-0.5, aicarhpick.getpick()+0.5], [1, 1], 'b')
plt.plot([aicarhpick.getpick()-0.5, aicarhpick.getpick()+0.5], [-1, -1], 'b')
plt.plot([arhpick.getpick(), arhpick.getpick()], [-1, 1], 'r')
plt.plot([arhpick.getpick()-0.5, arhpick.getpick()+0.5], [1, 1], 'r')
plt.plot([arhpick.getpick()-0.5, arhpick.getpick()+0.5], [-1, -1], 'r')
plt.plot([arhELpick.getLpick(), arhELpick.getLpick()], [-0.8, 0.8], 'r--')
plt.plot([arhELpick.getEpick(), arhELpick.getEpick()], [-0.8, 0.8], 'r--')
plt.plot([arhpick.getpick() + arhELpick.getPickError(), arhpick.getpick() + arhELpick.getPickError()], \
[-0.2, 0.2], 'r--')
plt.plot([arhpick.getpick() - arhELpick.getPickError(), arhpick.getpick() - arhELpick.getPickError()], \
[-0.2, 0.2], 'r--')
plt.title([trH2_filt.stats.station, trH2_filt.stats.channel])
plt.yticks([])
plt.ylim([-1.5, 1.5])
plt.xlabel('Time [s]')
plt.ylabel('Normalized Counts')
#plot 3-component window
plt.figure(3)
plt.subplot(3,1,1)
p31, = plt.plot(tdata, tr_filt.data/max(tr_filt.data), 'k')
p32, = plt.plot(ar3ccf.getTimeArray(), ar3ccf.getCF()/max(ar3ccf.getCF()), 'r')
plt.plot([arhpick.getpick(), arhpick.getpick()], [-1, 1], 'b')
plt.plot([arhpick.getpick()-0.5, arhpick.getpick()+0.5], [-1, -1], 'b')
plt.plot([arhpick.getpick()-0.5, arhpick.getpick()+0.5], [1, 1], 'b')
plt.plot([ar3cELpick.getLpick(), ar3cELpick.getLpick()], [-0.8, 0.8], 'b--')
plt.plot([ar3cELpick.getEpick(), ar3cELpick.getEpick()], [-0.8, 0.8], 'b--')
plt.yticks([])
plt.xticks([])
plt.ylabel('Normalized Counts')
plt.title([tr.stats.station, tr.stats.channel])
plt.suptitle(trH1_filt.stats.starttime)
plt.legend([p31, p32], ['Data', 'AR3C-CF'])
plt.subplot(3,1,2)
plt.plot(th1data, trH1_filt.data/max(trH1_filt.data), 'k')
plt.plot(ar3ccf.getTimeArray(), ar3ccf.getCF()/max(ar3ccf.getCF()), 'r')
plt.plot([arhpick.getpick(), arhpick.getpick()], [-1, 1], 'b')
plt.plot([arhpick.getpick()-0.5, arhpick.getpick()+0.5], [-1, -1], 'b')
plt.plot([arhpick.getpick()-0.5, arhpick.getpick()+0.5], [1, 1], 'b')
plt.plot([ar3cELpick.getLpick(), ar3cELpick.getLpick()], [-0.8, 0.8], 'b--')
plt.plot([ar3cELpick.getEpick(), ar3cELpick.getEpick()], [-0.8, 0.8], 'b--')
plt.yticks([])
plt.xticks([])
plt.ylabel('Normalized Counts')
plt.title([trH1_filt.stats.station, trH1_filt.stats.channel])
plt.subplot(3,1,3)
plt.plot(th2data, trH2_filt.data/max(trH2_filt.data), 'k')
plt.plot(ar3ccf.getTimeArray(), ar3ccf.getCF()/max(ar3ccf.getCF()), 'r')
plt.plot([arhpick.getpick(), arhpick.getpick()], [-1, 1], 'b')
plt.plot([arhpick.getpick()-0.5, arhpick.getpick()+0.5], [-1, -1], 'b')
plt.plot([arhpick.getpick()-0.5, arhpick.getpick()+0.5], [1, 1], 'b')
plt.plot([ar3cELpick.getLpick(), ar3cELpick.getLpick()], [-0.8, 0.8], 'b--')
plt.plot([ar3cELpick.getEpick(), ar3cELpick.getEpick()], [-0.8, 0.8], 'b--')
plt.yticks([])
plt.ylabel('Normalized Counts')
plt.title([trH2_filt.stats.station, trH2_filt.stats.channel])
plt.xlabel('Time [s]')
plt.show()
raw_input()
plt.close()
if __name__ == '__main__': if __name__ == '__main__':
parser = argparse.ArgumentParser() parser = argparse.ArgumentParser()

3
pylot/testing/test_pdf.py
View File

@ -2,6 +2,7 @@
# -*- coding: utf-8 -*- # -*- coding: utf-8 -*-
from pylot.core.util.pdf import ProbabilityDensityFunction from pylot.core.util.pdf import ProbabilityDensityFunction
pdf = ProbabilityDensityFunction.from_pick(0.34, 0.5, 0.54, type='exp') pdf = ProbabilityDensityFunction.from_pick(0.34, 0.5, 0.54, type='exp')
pdf2 = ProbabilityDensityFunction.from_pick(0.34, 0.5, 0.54, type='exp') pdf2 = ProbabilityDensityFunction.from_pick(0.34, 0.5, 0.54, type='exp')
diff = pdf - pdf2 diff = pdf - pdf2

1
scripts/pylot-noisewindow.py
View File

@ -2,6 +2,7 @@
# -*- coding: utf-8 -*- # -*- coding: utf-8 -*-
import argparse import argparse
import numpy import numpy
from pylot.core.pick.utils import getnoisewin from pylot.core.pick.utils import getnoisewin

1
scripts/pylot-pick-earliest-latest.py
View File

@ -11,6 +11,7 @@
""" """
import argparse import argparse
import obspy import obspy
from pylot.core.pick.utils import earllatepicker from pylot.core.pick.utils import earllatepicker

1
scripts/pylot-pick-firstmotion.py
View File

@ -8,6 +8,7 @@
""" """
import argparse import argparse
import obspy import obspy
from pylot.core.pick.utils import fmpicker from pylot.core.pick.utils import fmpicker

2
scripts/pylot-reasses-pilot-db.py
View File

@ -3,8 +3,8 @@
import argparse import argparse
from pylot.core.util.version import get_git_version as _getVersionString
from pylot.core.io.phases import reassess_pilot_db from pylot.core.io.phases import reassess_pilot_db
from pylot.core.util.version import get_git_version as _getVersionString
__version__ = _getVersionString() __version__ = _getVersionString()
__author__ = 'S. Wehling-Benatelli' __author__ = 'S. Wehling-Benatelli'

2
scripts/pylot-reasses-pilot-event.py
View File

@ -3,8 +3,8 @@
import argparse import argparse
from pylot.core.util.version import get_git_version as _getVersionString
from pylot.core.io.phases import reassess_pilot_event from pylot.core.io.phases import reassess_pilot_event
from pylot.core.util.version import get_git_version as _getVersionString
__version__ = _getVersionString() __version__ = _getVersionString()
__author__ = 'S. Wehling-Benatelli' __author__ = 'S. Wehling-Benatelli'

1
scripts/pylot-signalwindow.py
View File

@ -2,6 +2,7 @@
# -*- coding: utf-8 -*- # -*- coding: utf-8 -*-
import argparse import argparse
import numpy import numpy
from pylot.core.pick.utils import getsignalwin from pylot.core.pick.utils import getsignalwin

4
scripts/pylot-snr.py
View File

@ -9,6 +9,7 @@
""" """
import argparse import argparse
import obspy import obspy
from pylot.core.pick.utils import getSNR from pylot.core.pick.utils import getSNR
@ -27,4 +28,5 @@ if __name__ == "__main__":
'are calculated', 'are calculated',
dest='time') dest='time')
args = parser.parse_args() args = parser.parse_args()
print getSNR(args.data, args.tsnr, args.time) print
getSNR(args.data, args.tsnr, args.time)

557
scripts/run_makeCF.py
View File

@ -6,295 +6,302 @@
Only for test purposes! Only for test purposes!
""" """
from obspy.core import read
import matplotlib.pyplot as plt
import numpy as np
from pylot.core.pick.charfuns import CharacteristicFunction
from pylot.core.pick.picker import AutoPicker
from pylot.core.pick.utils import *
import glob
import argparse import argparse
import glob
from obspy.core import read
from pylot.core.pick.utils import *
def run_makeCF(project, database, event, iplot, station=None): def run_makeCF(project, database, event, iplot, station=None):
#parameters for CF calculation # parameters for CF calculation
t2 = 7 #length of moving window for HOS calculation [sec] t2 = 7 # length of moving window for HOS calculation [sec]
p = 4 #order of HOS p = 4 # order of HOS
cuttimes = [10, 50] #start and end time for CF calculation cuttimes = [10, 50] # start and end time for CF calculation
bpz = [2, 30] #corner frequencies of bandpass filter, vertical component bpz = [2, 30] # corner frequencies of bandpass filter, vertical component
bph = [2, 15] #corner frequencies of bandpass filter, horizontal components bph = [2, 15] # corner frequencies of bandpass filter, horizontal components
tdetz= 1.2 #length of AR-determination window [sec], vertical component tdetz = 1.2 # length of AR-determination window [sec], vertical component
tdeth= 0.8 #length of AR-determination window [sec], horizontal components tdeth = 0.8 # length of AR-determination window [sec], horizontal components
tpredz = 0.4 #length of AR-prediction window [sec], vertical component tpredz = 0.4 # length of AR-prediction window [sec], vertical component
tpredh = 0.4 #length of AR-prediction window [sec], horizontal components tpredh = 0.4 # length of AR-prediction window [sec], horizontal components
addnoise = 0.001 #add noise to seismogram for stable AR prediction addnoise = 0.001 # add noise to seismogram for stable AR prediction
arzorder = 2 #chosen order of AR process, vertical component arzorder = 2 # chosen order of AR process, vertical component
arhorder = 4 #chosen order of AR process, horizontal components arhorder = 4 # chosen order of AR process, horizontal components
TSNRhos = [5, 0.5, 1, .6] #window lengths [s] for calculating SNR for earliest/latest pick and quality assessment TSNRhos = [5, 0.5, 1, .6] # window lengths [s] for calculating SNR for earliest/latest pick and quality assessment
#from HOS-CF [noise window, safety gap, signal window, slope determination window] # from HOS-CF [noise window, safety gap, signal window, slope determination window]
TSNRarz = [5, 0.5, 1, 1.0] #window lengths [s] for calculating SNR for earliest/lates pick and quality assessment TSNRarz = [5, 0.5, 1, 1.0] # window lengths [s] for calculating SNR for earliest/lates pick and quality assessment
#from ARZ-CF # from ARZ-CF
#get waveform data # get waveform data
if station: if station:
dpz = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*HZ.msd' % (project, database, event, station) dpz = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*HZ.msd' % (project, database, event, station)
dpe = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*HE.msd' % (project, database, event, station) dpe = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*HE.msd' % (project, database, event, station)
dpn = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*HN.msd' % (project, database, event, station) dpn = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*HN.msd' % (project, database, event, station)
#dpz = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*_z.gse' % (project, database, event, station) # dpz = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*_z.gse' % (project, database, event, station)
#dpe = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*_e.gse' % (project, database, event, station) # dpe = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*_e.gse' % (project, database, event, station)
#dpn = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*_n.gse' % (project, database, event, station) # dpn = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/%s*_n.gse' % (project, database, event, station)
else: else:
dpz = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/*HZ.msd' % (project, database, event) dpz = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/*HZ.msd' % (project, database, event)
dpe = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/*HE.msd' % (project, database, event) dpe = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/*HE.msd' % (project, database, event)
dpn = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/*HN.msd' % (project, database, event) dpn = '/DATA/%s/EVENT_DATA/LOCAL/%s/%s/*HN.msd' % (project, database, event)
wfzfiles = glob.glob(dpz) wfzfiles = glob.glob(dpz)
wfefiles = glob.glob(dpe) wfefiles = glob.glob(dpe)
wfnfiles = glob.glob(dpn) wfnfiles = glob.glob(dpn)
if wfzfiles: if wfzfiles:
for i in range(len(wfzfiles)): for i in range(len(wfzfiles)):
print 'Vertical component data found ...' print
print wfzfiles[i] 'Vertical component data found ...'
st = read('%s' % wfzfiles[i]) print
st_copy = st.copy() wfzfiles[i]
#filter and taper data st = read('%s' % wfzfiles[i])
tr_filt = st[0].copy() st_copy = st.copy()
tr_filt.filter('bandpass', freqmin=bpz[0], freqmax=bpz[1], zerophase=False) # filter and taper data
tr_filt.taper(max_percentage=0.05, type='hann') tr_filt = st[0].copy()
st_copy[0].data = tr_filt.data tr_filt.filter('bandpass', freqmin=bpz[0], freqmax=bpz[1], zerophase=False)
############################################################## tr_filt.taper(max_percentage=0.05, type='hann')
#calculate HOS-CF using subclass HOScf of class CharacteristicFunction st_copy[0].data = tr_filt.data
hoscf = HOScf(st_copy, cuttimes, t2, p) #instance of HOScf ##############################################################
############################################################## # calculate HOS-CF using subclass HOScf of class CharacteristicFunction
#calculate AIC-HOS-CF using subclass AICcf of class CharacteristicFunction hoscf = HOScf(st_copy, cuttimes, t2, p) # instance of HOScf
#class needs stream object => build it ##############################################################
tr_aic = tr_filt.copy() # calculate AIC-HOS-CF using subclass AICcf of class CharacteristicFunction
tr_aic.data = hoscf.getCF() # class needs stream object => build it
st_copy[0].data = tr_aic.data tr_aic = tr_filt.copy()
aiccf = AICcf(st_copy, cuttimes) #instance of AICcf tr_aic.data = hoscf.getCF()
############################################################## st_copy[0].data = tr_aic.data
#get prelimenary onset time from AIC-HOS-CF using subclass AICPicker of class AutoPicking aiccf = AICcf(st_copy, cuttimes) # instance of AICcf
aicpick = AICPicker(aiccf, TSNRhos, 3, 10, None, 0.1) ##############################################################
############################################################## # get prelimenary onset time from AIC-HOS-CF using subclass AICPicker of class AutoPicking
#get refined onset time from HOS-CF using class Picker aicpick = AICPicker(aiccf, TSNRhos, 3, 10, None, 0.1)
hospick = PragPicker(hoscf, TSNRhos, 2, 10, 0.001, 0.2, aicpick.getpick()) ##############################################################
############################################################# # get refined onset time from HOS-CF using class Picker
#get earliest and latest possible picks hospick = PragPicker(hoscf, TSNRhos, 2, 10, 0.001, 0.2, aicpick.getpick())
st_copy[0].data = tr_filt.data #############################################################
[lpickhos, epickhos, pickerrhos] = earllatepicker(st_copy, 1.5, TSNRhos, hospick.getpick(), 10) # get earliest and latest possible picks
############################################################# st_copy[0].data = tr_filt.data
#get SNR [lpickhos, epickhos, pickerrhos] = earllatepicker(st_copy, 1.5, TSNRhos, hospick.getpick(), 10)
[SNR, SNRdB] = getSNR(st_copy, TSNRhos, hospick.getpick()) #############################################################
print 'SNR:', SNR, 'SNR[dB]:', SNRdB # get SNR
########################################################## [SNR, SNRdB] = getSNR(st_copy, TSNRhos, hospick.getpick())
#get first motion of onset print
hosfm = fmpicker(st, st_copy, 0.2, hospick.getpick(), 11) 'SNR:', SNR, 'SNR[dB]:', SNRdB
############################################################## ##########################################################
#calculate ARZ-CF using subclass ARZcf of class CharcteristicFunction # get first motion of onset
arzcf = ARZcf(st, cuttimes, tpredz, arzorder, tdetz, addnoise) #instance of ARZcf hosfm = fmpicker(st, st_copy, 0.2, hospick.getpick(), 11)
############################################################## ##############################################################
#calculate AIC-ARZ-CF using subclass AICcf of class CharacteristicFunction # calculate ARZ-CF using subclass ARZcf of class CharcteristicFunction
#class needs stream object => build it arzcf = ARZcf(st, cuttimes, tpredz, arzorder, tdetz, addnoise) # instance of ARZcf
tr_arzaic = tr_filt.copy() ##############################################################
tr_arzaic.data = arzcf.getCF() # calculate AIC-ARZ-CF using subclass AICcf of class CharacteristicFunction
st_copy[0].data = tr_arzaic.data # class needs stream object => build it
araiccf = AICcf(st_copy, cuttimes, tpredz, 0, tdetz) #instance of AICcf tr_arzaic = tr_filt.copy()
############################################################## tr_arzaic.data = arzcf.getCF()
#get onset time from AIC-ARZ-CF using subclass AICPicker of class AutoPicking st_copy[0].data = tr_arzaic.data
aicarzpick = AICPicker(araiccf, TSNRarz, 2, 10, None, 0.1) araiccf = AICcf(st_copy, cuttimes, tpredz, 0, tdetz) # instance of AICcf
############################################################## ##############################################################
#get refined onset time from ARZ-CF using class Picker # get onset time from AIC-ARZ-CF using subclass AICPicker of class AutoPicking
arzpick = PragPicker(arzcf, TSNRarz, 2.0, 10, 0.1, 0.05, aicarzpick.getpick()) aicarzpick = AICPicker(araiccf, TSNRarz, 2, 10, None, 0.1)
#get earliest and latest possible picks ##############################################################
st_copy[0].data = tr_filt.data # get refined onset time from ARZ-CF using class Picker
[lpickarz, epickarz, pickerrarz] = earllatepicker(st_copy, 1.5, TSNRarz, arzpick.getpick(), 10) arzpick = PragPicker(arzcf, TSNRarz, 2.0, 10, 0.1, 0.05, aicarzpick.getpick())
# get earliest and latest possible picks
st_copy[0].data = tr_filt.data
[lpickarz, epickarz, pickerrarz] = earllatepicker(st_copy, 1.5, TSNRarz, arzpick.getpick(), 10)
elif not wfzfiles: elif not wfzfiles:
print 'No vertical component data found!' print
'No vertical component data found!'
if wfefiles and wfnfiles: if wfefiles and wfnfiles:
for i in range(len(wfefiles)): for i in range(len(wfefiles)):
print 'Horizontal component data found ...' print
print wfefiles[i] 'Horizontal component data found ...'
print wfnfiles[i] print
#merge streams wfefiles[i]
H = read('%s' % wfefiles[i]) print
H += read('%s' % wfnfiles[i]) wfnfiles[i]
H_copy = H.copy() # merge streams
#filter and taper data H = read('%s' % wfefiles[i])
trH1_filt = H[0].copy() H += read('%s' % wfnfiles[i])
trH2_filt = H[1].copy() H_copy = H.copy()
trH1_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False) # filter and taper data
trH2_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False) trH1_filt = H[0].copy()
trH1_filt.taper(max_percentage=0.05, type='hann') trH2_filt = H[1].copy()
trH2_filt.taper(max_percentage=0.05, type='hann') trH1_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False)
H_copy[0].data = trH1_filt.data trH2_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False)
H_copy[1].data = trH2_filt.data trH1_filt.taper(max_percentage=0.05, type='hann')
trH2_filt.taper(max_percentage=0.05, type='hann')
H_copy[0].data = trH1_filt.data
H_copy[1].data = trH2_filt.data
############################################################## ##############################################################
#calculate ARH-CF using subclass ARHcf of class CharcteristicFunction # calculate ARH-CF using subclass ARHcf of class CharcteristicFunction
arhcf = ARHcf(H_copy, cuttimes, tpredh, arhorder, tdeth, addnoise) #instance of ARHcf arhcf = ARHcf(H_copy, cuttimes, tpredh, arhorder, tdeth, addnoise) # instance of ARHcf
############################################################## ##############################################################
#calculate AIC-ARH-CF using subclass AICcf of class CharacteristicFunction # calculate AIC-ARH-CF using subclass AICcf of class CharacteristicFunction
#class needs stream object => build it # class needs stream object => build it
tr_arhaic = trH1_filt.copy() tr_arhaic = trH1_filt.copy()
tr_arhaic.data = arhcf.getCF() tr_arhaic.data = arhcf.getCF()
H_copy[0].data = tr_arhaic.data H_copy[0].data = tr_arhaic.data
#calculate ARH-AIC-CF # calculate ARH-AIC-CF
arhaiccf = AICcf(H_copy, cuttimes, tpredh, 0, tdeth) #instance of AICcf arhaiccf = AICcf(H_copy, cuttimes, tpredh, 0, tdeth) # instance of AICcf
############################################################## ##############################################################
#get onset time from AIC-ARH-CF using subclass AICPicker of class AutoPicking # get onset time from AIC-ARH-CF using subclass AICPicker of class AutoPicking
aicarhpick = AICPicker(arhaiccf, TSNRarz, 4, 10, None, 0.1) aicarhpick = AICPicker(arhaiccf, TSNRarz, 4, 10, None, 0.1)
############################################################### ###############################################################
#get refined onset time from ARH-CF using class Picker # get refined onset time from ARH-CF using class Picker
arhpick = PragPicker(arhcf, TSNRarz, 2.5, 10, 0.1, 0.05, aicarhpick.getpick()) arhpick = PragPicker(arhcf, TSNRarz, 2.5, 10, 0.1, 0.05, aicarhpick.getpick())
#get earliest and latest possible picks # get earliest and latest possible picks
H_copy[0].data = trH1_filt.data H_copy[0].data = trH1_filt.data
[lpickarh1, epickarh1, pickerrarh1] = earllatepicker(H_copy, 1.5, TSNRarz, arhpick.getpick(), 10) [lpickarh1, epickarh1, pickerrarh1] = earllatepicker(H_copy, 1.5, TSNRarz, arhpick.getpick(), 10)
H_copy[0].data = trH2_filt.data H_copy[0].data = trH2_filt.data
[lpickarh2, epickarh2, pickerrarh2] = earllatepicker(H_copy, 1.5, TSNRarz, arhpick.getpick(), 10) [lpickarh2, epickarh2, pickerrarh2] = earllatepicker(H_copy, 1.5, TSNRarz, arhpick.getpick(), 10)
#get earliest pick of both earliest possible picks # get earliest pick of both earliest possible picks
epick = [epickarh1, epickarh2] epick = [epickarh1, epickarh2]
lpick = [lpickarh1, lpickarh2] lpick = [lpickarh1, lpickarh2]
pickerr = [pickerrarh1, pickerrarh2] pickerr = [pickerrarh1, pickerrarh2]
ipick =np.argmin([epickarh1, epickarh2]) ipick = np.argmin([epickarh1, epickarh2])
epickarh = epick[ipick] epickarh = epick[ipick]
lpickarh = lpick[ipick] lpickarh = lpick[ipick]
pickerrarh = pickerr[ipick] pickerrarh = pickerr[ipick]
# create stream with 3 traces
# merge streams
AllC = read('%s' % wfefiles[i])
AllC += read('%s' % wfnfiles[i])
AllC += read('%s' % wfzfiles[i])
# filter and taper data
All1_filt = AllC[0].copy()
All2_filt = AllC[1].copy()
All3_filt = AllC[2].copy()
All1_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False)
All2_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False)
All3_filt.filter('bandpass', freqmin=bpz[0], freqmax=bpz[1], zerophase=False)
All1_filt.taper(max_percentage=0.05, type='hann')
All2_filt.taper(max_percentage=0.05, type='hann')
All3_filt.taper(max_percentage=0.05, type='hann')
AllC[0].data = All1_filt.data
AllC[1].data = All2_filt.data
AllC[2].data = All3_filt.data
# calculate AR3C-CF using subclass AR3Ccf of class CharacteristicFunction
ar3ccf = AR3Ccf(AllC, cuttimes, tpredz, arhorder, tdetz, addnoise) # instance of AR3Ccf
##############################################################
if iplot:
# plot vertical trace
plt.figure()
tr = st[0]
tdata = np.arange(0, tr.stats.npts / tr.stats.sampling_rate, tr.stats.delta)
p1, = plt.plot(tdata, tr_filt.data / max(tr_filt.data), 'k')
p2, = plt.plot(hoscf.getTimeArray(), hoscf.getCF() / max(hoscf.getCF()), 'r')
p3, = plt.plot(aiccf.getTimeArray(), aiccf.getCF() / max(aiccf.getCF()), 'b')
p4, = plt.plot(arzcf.getTimeArray(), arzcf.getCF() / max(arzcf.getCF()), 'g')
p5, = plt.plot(araiccf.getTimeArray(), araiccf.getCF() / max(araiccf.getCF()), 'y')
plt.plot([aicpick.getpick(), aicpick.getpick()], [-1, 1], 'b--')
plt.plot([aicpick.getpick() - 0.5, aicpick.getpick() + 0.5], [1, 1], 'b')
plt.plot([aicpick.getpick() - 0.5, aicpick.getpick() + 0.5], [-1, -1], 'b')
plt.plot([hospick.getpick(), hospick.getpick()], [-1.3, 1.3], 'r', linewidth=2)
plt.plot([hospick.getpick() - 0.5, hospick.getpick() + 0.5], [1.3, 1.3], 'r')
plt.plot([hospick.getpick() - 0.5, hospick.getpick() + 0.5], [-1.3, -1.3], 'r')
plt.plot([lpickhos, lpickhos], [-1.1, 1.1], 'r--')
plt.plot([epickhos, epickhos], [-1.1, 1.1], 'r--')
plt.plot([aicarzpick.getpick(), aicarzpick.getpick()], [-1.2, 1.2], 'y', linewidth=2)
plt.plot([aicarzpick.getpick() - 0.5, aicarzpick.getpick() + 0.5], [1.2, 1.2], 'y')
plt.plot([aicarzpick.getpick() - 0.5, aicarzpick.getpick() + 0.5], [-1.2, -1.2], 'y')
plt.plot([arzpick.getpick(), arzpick.getpick()], [-1.4, 1.4], 'g', linewidth=2)
plt.plot([arzpick.getpick() - 0.5, arzpick.getpick() + 0.5], [1.4, 1.4], 'g')
plt.plot([arzpick.getpick() - 0.5, arzpick.getpick() + 0.5], [-1.4, -1.4], 'g')
plt.plot([lpickarz, lpickarz], [-1.2, 1.2], 'g--')
plt.plot([epickarz, epickarz], [-1.2, 1.2], 'g--')
plt.yticks([])
plt.ylim([-1.5, 1.5])
plt.xlabel('Time [s]')
plt.ylabel('Normalized Counts')
plt.title('%s, %s, CF-SNR=%7.2f, CF-Slope=%12.2f' % (tr.stats.station,
tr.stats.channel, aicpick.getSNR(),
aicpick.getSlope()))
plt.suptitle(tr.stats.starttime)
plt.legend([p1, p2, p3, p4, p5], ['Data', 'HOS-CF', 'HOSAIC-CF', 'ARZ-CF', 'ARZAIC-CF'])
# plot horizontal traces
plt.figure(2)
plt.subplot(2, 1, 1)
tsteph = tpredh / 4
th1data = np.arange(0, trH1_filt.stats.npts / trH1_filt.stats.sampling_rate, trH1_filt.stats.delta)
th2data = np.arange(0, trH2_filt.stats.npts / trH2_filt.stats.sampling_rate, trH2_filt.stats.delta)
tarhcf = np.arange(0, len(arhcf.getCF()) * tsteph, tsteph) + cuttimes[0] + tdeth + tpredh
p21, = plt.plot(th1data, trH1_filt.data / max(trH1_filt.data), 'k')
p22, = plt.plot(arhcf.getTimeArray(), arhcf.getCF() / max(arhcf.getCF()), 'r')
p23, = plt.plot(arhaiccf.getTimeArray(), arhaiccf.getCF() / max(arhaiccf.getCF()))
plt.plot([aicarhpick.getpick(), aicarhpick.getpick()], [-1, 1], 'b')
plt.plot([aicarhpick.getpick() - 0.5, aicarhpick.getpick() + 0.5], [1, 1], 'b')
plt.plot([aicarhpick.getpick() - 0.5, aicarhpick.getpick() + 0.5], [-1, -1], 'b')
plt.plot([arhpick.getpick(), arhpick.getpick()], [-1, 1], 'r')
plt.plot([arhpick.getpick() - 0.5, arhpick.getpick() + 0.5], [1, 1], 'r')
plt.plot([arhpick.getpick() - 0.5, arhpick.getpick() + 0.5], [-1, -1], 'r')
plt.plot([lpickarh, lpickarh], [-0.8, 0.8], 'r--')
plt.plot([epickarh, epickarh], [-0.8, 0.8], 'r--')
plt.plot([arhpick.getpick() + pickerrarh, arhpick.getpick() + pickerrarh], [-0.2, 0.2], 'r--')
plt.plot([arhpick.getpick() - pickerrarh, arhpick.getpick() - pickerrarh], [-0.2, 0.2], 'r--')
plt.yticks([])
plt.ylim([-1.5, 1.5])
plt.ylabel('Normalized Counts')
plt.title([trH1_filt.stats.station, trH1_filt.stats.channel])
plt.suptitle(trH1_filt.stats.starttime)
plt.legend([p21, p22, p23], ['Data', 'ARH-CF', 'ARHAIC-CF'])
plt.subplot(2, 1, 2)
plt.plot(th2data, trH2_filt.data / max(trH2_filt.data), 'k')
plt.plot(arhcf.getTimeArray(), arhcf.getCF() / max(arhcf.getCF()), 'r')
plt.plot(arhaiccf.getTimeArray(), arhaiccf.getCF() / max(arhaiccf.getCF()))
plt.plot([aicarhpick.getpick(), aicarhpick.getpick()], [-1, 1], 'b')
plt.plot([aicarhpick.getpick() - 0.5, aicarhpick.getpick() + 0.5], [1, 1], 'b')
plt.plot([aicarhpick.getpick() - 0.5, aicarhpick.getpick() + 0.5], [-1, -1], 'b')
plt.plot([arhpick.getpick(), arhpick.getpick()], [-1, 1], 'r')
plt.plot([arhpick.getpick() - 0.5, arhpick.getpick() + 0.5], [1, 1], 'r')
plt.plot([arhpick.getpick() - 0.5, arhpick.getpick() + 0.5], [-1, -1], 'r')
plt.plot([lpickarh, lpickarh], [-0.8, 0.8], 'r--')
plt.plot([epickarh, epickarh], [-0.8, 0.8], 'r--')
plt.plot([arhpick.getpick() + pickerrarh, arhpick.getpick() + pickerrarh], [-0.2, 0.2], 'r--')
plt.plot([arhpick.getpick() - pickerrarh, arhpick.getpick() - pickerrarh], [-0.2, 0.2], 'r--')
plt.title([trH2_filt.stats.station, trH2_filt.stats.channel])
plt.yticks([])
plt.ylim([-1.5, 1.5])
plt.xlabel('Time [s]')
plt.ylabel('Normalized Counts')
# plot 3-component window
plt.figure(3)
plt.subplot(3, 1, 1)
p31, = plt.plot(tdata, tr_filt.data / max(tr_filt.data), 'k')
p32, = plt.plot(ar3ccf.getTimeArray(), ar3ccf.getCF() / max(ar3ccf.getCF()), 'r')
plt.plot([arhpick.getpick(), arhpick.getpick()], [-1, 1], 'b')
plt.plot([arhpick.getpick() - 0.5, arhpick.getpick() + 0.5], [-1, -1], 'b')
plt.plot([arhpick.getpick() - 0.5, arhpick.getpick() + 0.5], [1, 1], 'b')
plt.yticks([])
plt.xticks([])
plt.ylabel('Normalized Counts')
plt.title([tr.stats.station, tr.stats.channel])
plt.suptitle(trH1_filt.stats.starttime)
plt.legend([p31, p32], ['Data', 'AR3C-CF'])
plt.subplot(3, 1, 2)
plt.plot(th1data, trH1_filt.data / max(trH1_filt.data), 'k')
plt.plot(ar3ccf.getTimeArray(), ar3ccf.getCF() / max(ar3ccf.getCF()), 'r')
plt.plot([arhpick.getpick(), arhpick.getpick()], [-1, 1], 'b')
plt.plot([arhpick.getpick() - 0.5, arhpick.getpick() + 0.5], [-1, -1], 'b')
plt.plot([arhpick.getpick() - 0.5, arhpick.getpick() + 0.5], [1, 1], 'b')
plt.yticks([])
plt.xticks([])
plt.ylabel('Normalized Counts')
plt.title([trH1_filt.stats.station, trH1_filt.stats.channel])
plt.subplot(3, 1, 3)
plt.plot(th2data, trH2_filt.data / max(trH2_filt.data), 'k')
plt.plot(ar3ccf.getTimeArray(), ar3ccf.getCF() / max(ar3ccf.getCF()), 'r')
plt.plot([arhpick.getpick(), arhpick.getpick()], [-1, 1], 'b')
plt.plot([arhpick.getpick() - 0.5, arhpick.getpick() + 0.5], [-1, -1], 'b')
plt.plot([arhpick.getpick() - 0.5, arhpick.getpick() + 0.5], [1, 1], 'b')
plt.yticks([])
plt.ylabel('Normalized Counts')
plt.title([trH2_filt.stats.station, trH2_filt.stats.channel])
plt.xlabel('Time [s]')
plt.show()
raw_input()
plt.close()
#create stream with 3 traces
#merge streams
AllC = read('%s' % wfefiles[i])
AllC += read('%s' % wfnfiles[i])
AllC += read('%s' % wfzfiles[i])
#filter and taper data
All1_filt = AllC[0].copy()
All2_filt = AllC[1].copy()
All3_filt = AllC[2].copy()
All1_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False)
All2_filt.filter('bandpass', freqmin=bph[0], freqmax=bph[1], zerophase=False)
All3_filt.filter('bandpass', freqmin=bpz[0], freqmax=bpz[1], zerophase=False)
All1_filt.taper(max_percentage=0.05, type='hann')
All2_filt.taper(max_percentage=0.05, type='hann')
All3_filt.taper(max_percentage=0.05, type='hann')
AllC[0].data = All1_filt.data
AllC[1].data = All2_filt.data
AllC[2].data = All3_filt.data
#calculate AR3C-CF using subclass AR3Ccf of class CharacteristicFunction
ar3ccf = AR3Ccf(AllC, cuttimes, tpredz, arhorder, tdetz, addnoise) #instance of AR3Ccf
##############################################################
if iplot:
#plot vertical trace
plt.figure()
tr = st[0]
tdata = np.arange(0, tr.stats.npts / tr.stats.sampling_rate, tr.stats.delta)
p1, = plt.plot(tdata, tr_filt.data/max(tr_filt.data), 'k')
p2, = plt.plot(hoscf.getTimeArray(), hoscf.getCF() / max(hoscf.getCF()), 'r')
p3, = plt.plot(aiccf.getTimeArray(), aiccf.getCF()/max(aiccf.getCF()), 'b')
p4, = plt.plot(arzcf.getTimeArray(), arzcf.getCF()/max(arzcf.getCF()), 'g')
p5, = plt.plot(araiccf.getTimeArray(), araiccf.getCF()/max(araiccf.getCF()), 'y')
plt.plot([aicpick.getpick(), aicpick.getpick()], [-1, 1], 'b--')
plt.plot([aicpick.getpick()-0.5, aicpick.getpick()+0.5], [1, 1], 'b')
plt.plot([aicpick.getpick()-0.5, aicpick.getpick()+0.5], [-1, -1], 'b')
plt.plot([hospick.getpick(), hospick.getpick()], [-1.3, 1.3], 'r', linewidth=2)
plt.plot([hospick.getpick()-0.5, hospick.getpick()+0.5], [1.3, 1.3], 'r')
plt.plot([hospick.getpick()-0.5, hospick.getpick()+0.5], [-1.3, -1.3], 'r')
plt.plot([lpickhos, lpickhos], [-1.1, 1.1], 'r--')
plt.plot([epickhos, epickhos], [-1.1, 1.1], 'r--')
plt.plot([aicarzpick.getpick(), aicarzpick.getpick()], [-1.2, 1.2], 'y', linewidth=2)
plt.plot([aicarzpick.getpick()-0.5, aicarzpick.getpick()+0.5], [1.2, 1.2], 'y')
plt.plot([aicarzpick.getpick()-0.5, aicarzpick.getpick()+0.5], [-1.2, -1.2], 'y')
plt.plot([arzpick.getpick(), arzpick.getpick()], [-1.4, 1.4], 'g', linewidth=2)
plt.plot([arzpick.getpick()-0.5, arzpick.getpick()+0.5], [1.4, 1.4], 'g')
plt.plot([arzpick.getpick()-0.5, arzpick.getpick()+0.5], [-1.4, -1.4], 'g')
plt.plot([lpickarz, lpickarz], [-1.2, 1.2], 'g--')
plt.plot([epickarz, epickarz], [-1.2, 1.2], 'g--')
plt.yticks([])
plt.ylim([-1.5, 1.5])
plt.xlabel('Time [s]')
plt.ylabel('Normalized Counts')
plt.title('%s, %s, CF-SNR=%7.2f, CF-Slope=%12.2f' % (tr.stats.station,
tr.stats.channel, aicpick.getSNR(), aicpick.getSlope()))
plt.suptitle(tr.stats.starttime)
plt.legend([p1, p2, p3, p4, p5], ['Data', 'HOS-CF', 'HOSAIC-CF', 'ARZ-CF', 'ARZAIC-CF'])
#plot horizontal traces
plt.figure(2)
plt.subplot(2,1,1)
tsteph = tpredh / 4
th1data = np.arange(0, trH1_filt.stats.npts / trH1_filt.stats.sampling_rate, trH1_filt.stats.delta)
th2data = np.arange(0, trH2_filt.stats.npts / trH2_filt.stats.sampling_rate, trH2_filt.stats.delta)
tarhcf = np.arange(0, len(arhcf.getCF()) * tsteph, tsteph) + cuttimes[0] + tdeth +tpredh
p21, = plt.plot(th1data, trH1_filt.data/max(trH1_filt.data), 'k')
p22, = plt.plot(arhcf.getTimeArray(), arhcf.getCF()/max(arhcf.getCF()), 'r')
p23, = plt.plot(arhaiccf.getTimeArray(), arhaiccf.getCF()/max(arhaiccf.getCF()))
plt.plot([aicarhpick.getpick(), aicarhpick.getpick()], [-1, 1], 'b')
plt.plot([aicarhpick.getpick()-0.5, aicarhpick.getpick()+0.5], [1, 1], 'b')
plt.plot([aicarhpick.getpick()-0.5, aicarhpick.getpick()+0.5], [-1, -1], 'b')
plt.plot([arhpick.getpick(), arhpick.getpick()], [-1, 1], 'r')
plt.plot([arhpick.getpick()-0.5, arhpick.getpick()+0.5], [1, 1], 'r')
plt.plot([arhpick.getpick()-0.5, arhpick.getpick()+0.5], [-1, -1], 'r')
plt.plot([lpickarh, lpickarh], [-0.8, 0.8], 'r--')
plt.plot([epickarh, epickarh], [-0.8, 0.8], 'r--')
plt.plot([arhpick.getpick() + pickerrarh, arhpick.getpick() + pickerrarh], [-0.2, 0.2], 'r--')
plt.plot([arhpick.getpick() - pickerrarh, arhpick.getpick() - pickerrarh], [-0.2, 0.2], 'r--')
plt.yticks([])
plt.ylim([-1.5, 1.5])
plt.ylabel('Normalized Counts')
plt.title([trH1_filt.stats.station, trH1_filt.stats.channel])
plt.suptitle(trH1_filt.stats.starttime)
plt.legend([p21, p22, p23], ['Data', 'ARH-CF', 'ARHAIC-CF'])
plt.subplot(2,1,2)
plt.plot(th2data, trH2_filt.data/max(trH2_filt.data), 'k')
plt.plot(arhcf.getTimeArray(), arhcf.getCF()/max(arhcf.getCF()), 'r')
plt.plot(arhaiccf.getTimeArray(), arhaiccf.getCF()/max(arhaiccf.getCF()))
plt.plot([aicarhpick.getpick(), aicarhpick.getpick()], [-1, 1], 'b')
plt.plot([aicarhpick.getpick()-0.5, aicarhpick.getpick()+0.5], [1, 1], 'b')
plt.plot([aicarhpick.getpick()-0.5, aicarhpick.getpick()+0.5], [-1, -1], 'b')
plt.plot([arhpick.getpick(), arhpick.getpick()], [-1, 1], 'r')
plt.plot([arhpick.getpick()-0.5, arhpick.getpick()+0.5], [1, 1], 'r')
plt.plot([arhpick.getpick()-0.5, arhpick.getpick()+0.5], [-1, -1], 'r')
plt.plot([lpickarh, lpickarh], [-0.8, 0.8], 'r--')
plt.plot([epickarh, epickarh], [-0.8, 0.8], 'r--')
plt.plot([arhpick.getpick() + pickerrarh, arhpick.getpick() + pickerrarh], [-0.2, 0.2], 'r--')
plt.plot([arhpick.getpick() - pickerrarh, arhpick.getpick() - pickerrarh], [-0.2, 0.2], 'r--')
plt.title([trH2_filt.stats.station, trH2_filt.stats.channel])
plt.yticks([])
plt.ylim([-1.5, 1.5])
plt.xlabel('Time [s]')
plt.ylabel('Normalized Counts')
#plot 3-component window
plt.figure(3)
plt.subplot(3,1,1)
p31, = plt.plot(tdata, tr_filt.data/max(tr_filt.data), 'k')
p32, = plt.plot(ar3ccf.getTimeArray(), ar3ccf.getCF()/max(ar3ccf.getCF()), 'r')
plt.plot([arhpick.getpick(), arhpick.getpick()], [-1, 1], 'b')
plt.plot([arhpick.getpick()-0.5, arhpick.getpick()+0.5], [-1, -1], 'b')
plt.plot([arhpick.getpick()-0.5, arhpick.getpick()+0.5], [1, 1], 'b')
plt.yticks([])
plt.xticks([])
plt.ylabel('Normalized Counts')
plt.title([tr.stats.station, tr.stats.channel])
plt.suptitle(trH1_filt.stats.starttime)
plt.legend([p31, p32], ['Data', 'AR3C-CF'])
plt.subplot(3,1,2)
plt.plot(th1data, trH1_filt.data/max(trH1_filt.data), 'k')
plt.plot(ar3ccf.getTimeArray(), ar3ccf.getCF()/max(ar3ccf.getCF()), 'r')
plt.plot([arhpick.getpick(), arhpick.getpick()], [-1, 1], 'b')
plt.plot([arhpick.getpick()-0.5, arhpick.getpick()+0.5], [-1, -1], 'b')
plt.plot([arhpick.getpick()-0.5, arhpick.getpick()+0.5], [1, 1], 'b')
plt.yticks([])
plt.xticks([])
plt.ylabel('Normalized Counts')
plt.title([trH1_filt.stats.station, trH1_filt.stats.channel])
plt.subplot(3,1,3)
plt.plot(th2data, trH2_filt.data/max(trH2_filt.data), 'k')
plt.plot(ar3ccf.getTimeArray(), ar3ccf.getCF()/max(ar3ccf.getCF()), 'r')
plt.plot([arhpick.getpick(), arhpick.getpick()], [-1, 1], 'b')
plt.plot([arhpick.getpick()-0.5, arhpick.getpick()+0.5], [-1, -1], 'b')
plt.plot([arhpick.getpick()-0.5, arhpick.getpick()+0.5], [1, 1], 'b')
plt.yticks([])
plt.ylabel('Normalized Counts')
plt.title([trH2_filt.stats.station, trH2_filt.stats.channel])
plt.xlabel('Time [s]')
plt.show()
raw_input()
plt.close()
parser = argparse.ArgumentParser() parser = argparse.ArgumentParser()
parser.add_argument('--project', type=str, help='project name (e.g. Insheim)') parser.add_argument('--project', type=str, help='project name (e.g. Insheim)')