[major, refs #200] major change for the magnitude estimation from GUI
restitution of waveform data has been moved to dataprocessing; the routines have been cleaned up and work in changed order now: new function restitute_data is a wrapper function in order to restitute seismic data with the most popular kinds of station metadata
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@ -568,7 +568,7 @@ def autopickstation(wfstream, pickparam, verbose=False):
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[cordat, restflag] = restitute_data(h_copy, invdir)
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# calculate WA-peak-to-peak amplitude
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# using subclass WApp of superclass Magnitude
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if restflag == 1:
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if restflag:
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if Sweight < 4:
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wapp = WApp(cordat, mpickS, mpickP + sstop, iplot)
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else:
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@ -578,6 +578,9 @@ def autopickstation(wfstream, pickparam, verbose=False):
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(0.5 * (mpickP + sstop)), iplot)
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Ao = wapp.getwapp()
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else:
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print("Go on processing data without source parameter "
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"determination!")
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else:
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msg = 'Bad initial (AIC) S-pick, skipping this onset!\n' \
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@ -3,9 +3,14 @@
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import os
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import glob
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from obspy import UTCDateTime, read_inventory
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import sys
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import numpy as np
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from obspy import UTCDateTime, read_inventory, read
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from obspy.io.xseed import Parser
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from pylot.core.util.utils import key_for_set_value, find_in_list, \
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remove_underscores
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def time_from_header(header):
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@ -150,140 +155,129 @@ def evt_head_check(root_dir, out_dir = None):
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print(nfiles)
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def restitute_data(data, invdlpath):
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def restitute_data(data, path_to_inventory, unit='VEL', force=False):
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"""
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takes a data stream and a path_to_inventory and returns the corrected
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waveform data stream
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:param data: seismic data stream
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:param path_to_inventory: path to inventory folder or file
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:param unit: unit to correct for (default: 'VEL')
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:param force: force restitution for already corrected traces (default:
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False)
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:return: corrected data stream
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"""
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:param invdlpath:
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:param data:
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:return:
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"""
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restflag = list()
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restflag = False
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data = remove_underscores(data)
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for tr in data:
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# remove underscores
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if len(tr.stats.station) > 3 and tr.stats.station[3] == '_':
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tr.stats.station = tr.stats.station[0:3]
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dlfile = list()
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invfile = list()
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respfile = list()
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inv = dict(dless=dlfile, xml=invfile, resp=respfile)
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if os.path.isfile(invdlpath):
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ext = os.path.splitext(invdlpath)[1].split('.')[1]
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inv[ext] += [invdlpath]
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if os.path.isfile(path_to_inventory):
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ext = os.path.splitext(path_to_inventory)[1].split('.')[1]
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inv[ext] += [path_to_inventory]
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else:
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for ext in inv.keys():
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inv[ext] += glob.glob1(invdlpath,'*.{}'.format(ext))
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inv[ext] += glob.glob1(path_to_inventory, '*.{0}'.format(ext))
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# check for dataless-SEED file
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# TODO ineffective loop -> better concatenate inventory entries and
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# loop over traces
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if len(dlfile) >= 1:
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print("Found dataless-SEED file(s)!")
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print("Reading meta data information ...")
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for j in range(len(dlfile)):
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print("Found dataless-SEED file %s" % dlfile[j])
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parser = Parser('%s' % dlfile[j])
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for i in range(len(data)):
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# check, whether this trace has already been corrected
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try:
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data[i].stats.processing
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except:
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try:
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print(
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"Correcting %s, %s for instrument response "
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"..." % (data[i].stats.station,
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data[i].stats.channel))
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# get corner frequencies for pre-filtering
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fny = data[i].stats.sampling_rate / 2
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fc21 = fny - (fny * 0.05)
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fc22 = fny - (fny * 0.02)
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prefilt = [0.5, 0.9, fc21, fc22]
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# instrument correction
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data[i].simulate(pre_filt=prefilt,
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seedresp={'filename': parser,
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'date': data[
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i].stats.starttime,
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'units': "VEL"})
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restflag = True
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except ValueError as e:
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vmsg = '{0}'.format(e)
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print(vmsg)
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else:
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print("Trace has already been corrected!")
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# check for inventory-xml file
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if len(invfile) >= 1:
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print("Found inventory-xml file(s)!")
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print("Reading meta data information ...")
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for j in range(len(invfile)):
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print("Found inventory-xml file %s" % invfile[j])
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inv = read_inventory(invfile[j], format="STATIONXML")
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for i in range(len(data)):
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# check, whether this trace has already been corrected
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try:
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data[i].stats.processing
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except:
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try:
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print("Correcting %s, %s for instrument response "
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"..." % (data[i].stats.station,
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data[i].stats.channel))
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# get corner frequencies for pre-filtering
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fny = data[i].stats.sampling_rate / 2
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fc21 = fny - (fny * 0.05)
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fc22 = fny - (fny * 0.02)
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prefilt = [0.5, 0.9, fc21, fc22]
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# instrument correction
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data[i].attach_response(inv)
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data[i].remove_response(output='VEL',
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pre_filt=prefilt)
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restflag = True
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except ValueError as e:
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vmsg = '{0}'.format(e)
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print(vmsg)
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else:
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print("Trace has already been corrected!")
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# check for RESP-file
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if len(respfile) >= 1:
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print("Found response file(s)!")
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print("Reading meta data information ...")
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for j in range(len(respfile)):
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print("Found RESP-file %s" % respfile[j])
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for i in range(len(data)):
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# check, whether this trace has already been corrected
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try:
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data[i].stats.processing
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except:
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try:
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print("Correcting %s, %s for instrument response "
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"..." % (data[i].stats.station,
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data[i].stats.channel))
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# get corner frequencies for pre-filtering
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fny = data[i].stats.sampling_rate / 2
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fc21 = fny - (fny * 0.05)
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fc22 = fny - (fny * 0.02)
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prefilt = [0.5, 0.9, fc21, fc22]
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# instrument correction
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seedresp = {'filename': respfile[0],
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'date': data[0].stats.starttime,
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'units': "VEL"}
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data[i].simulate(paz_remove=None, pre_filt=prefilt,
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seedresp=seedresp)
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restflag = True
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except ValueError as e:
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vmsg = '{0}'.format(e)
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print(vmsg)
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else:
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print("Trace has already been corrected!")
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invtype = key_for_set_value(inv)
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if len(respfile) < 1 and len(invfile) < 1 and len(dlfile) < 1:
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print("No dataless-SEED file,inventory-xml file nor RESP-file "
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if invtype is None:
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print("Neither dataless-SEED file,inventory-xml file nor RESP-file "
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"found!")
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print("Go on processing data without source parameter "
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"determination!")
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return data, False
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# loop over traces
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for tr in data:
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seed_id = tr.get_id()
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# check, whether this trace has already been corrected
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if 'processing' in tr.stats.keys() and not force:
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print("Trace {0} has already been corrected!".format(seed_id))
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continue
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stime = tr.stats.starttime
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seedresp = None
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prefilt = get_prefilt(tr)
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if invtype == 'resp':
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fresp = find_in_list(inv[invtype], seed_id)
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if not fresp:
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raise IOError('no response file found '
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'for trace {0}'.format(seed_id))
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fname = fresp
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seedresp = dict(filename=fname,
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date=stime,
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units=unit)
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kwargs = dict(paz_remove=None, pre_filt=prefilt, seedresp=seedresp)
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elif invtype == 'dless':
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if len(inv[invtype]) > 1:
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fname = Parser(find_in_list(inv[invtype], seed_id))
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else:
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fname = Parser(inv[invtype][0])
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seedresp = dict(filename=fname,
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date=stime,
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units=unit)
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kwargs = dict(pre_filt=prefilt, seedresp=seedresp)
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elif invtype == 'xml':
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invlist = inv[invtype]
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if len(invlist) > 1:
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finv = find_in_list(invlist, seed_id)
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else:
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finv = invlist[0]
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inventory = read_inventory(finv, format='STATIONXML')
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# apply restitution to data
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if invtype in ['resp', 'dless']:
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tr.simulate(**kwargs)
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else:
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tr.attach_response(inventory)
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tr.remove_response(output=unit,
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pre_filt=prefilt)
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restflag.append(True)
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# check if ALL traces could be restituted, take care of large datasets
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# better try restitution for smaller subsets of data (e.g. station by
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# station)
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if len(restflag) > 0:
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restflag = np.all(restflag)
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else:
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restflag = False
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return data, restflag
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def get_prefilt(trace, tlow=(0.5, 0.9), thi=(5., 2.), verbosity=0):
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"""
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takes a `obspy.core.stream.Trace` object, taper parameters tlow and thi and
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returns the pre-filtering corner frequencies for the cosine taper for
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further processing
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:param trace: seismic data trace
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:type trace: `obspy.core.stream.Trace`
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:param tlow: tuple or list containing the desired lower corner
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frequenices for a cosine taper
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:type tlow: tuple or list
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:param thi: tuple or list containing the percentage values of the
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Nyquist frequency for the desired upper corner frequencies of the cosine
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taper
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:type thi: tuple or list
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:param verbosity: verbosity level
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:type verbosity: int
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:return: pre-filt cosine taper corner frequencies
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:rtype: tuple
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..example::
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>>> st = read()
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>>> get_prefilt(st[0])
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(0.5, 0.9, 47.5, 49.0)
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"""
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if verbosity:
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print("Calculating pre-filter values for %s, %s ..." % (
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trace.stats.station, trace.stats.channel))
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# get corner frequencies for pre-filtering
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fny = trace.stats.sampling_rate / 2
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fc21 = fny - (fny * thi[0]/100.)
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fc22 = fny - (fny * thi[1]/100.)
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return (tlow[0], tlow[1], fc21, fc22)
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if __name__ == "__main__":
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import doctest
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@ -328,6 +328,23 @@ def isIterable(obj):
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return False
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return True
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def key_for_set_value(d):
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"""
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takes a dictionary and returns the first key for which's value the
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boolean is True
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:param d: dictionary containing values
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:type d: dict
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:return: key to the first non-False value found; None if no value's
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boolean equals True
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"""
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r = None
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for k, v in d.items():
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if v:
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return k
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return r
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def prepTimeAxis(stime, trace):
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'''
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takes a starttime and a trace object and returns a valid time axis for
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@ -354,6 +371,20 @@ def prepTimeAxis(stime, trace):
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return time_ax
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def remove_underscores(data):
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"""
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takes a `obspy.core.stream.Stream` object and removes all underscores
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from stationnames
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:param data: stream of seismic data
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:type data: `obspy.core.stream.Stream`
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:return: data stream
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"""
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for tr in data:
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# remove underscores
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tr.stats.station = tr.stats.station.strip('_')
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return data
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def scaleWFData(data, factor=None, components='all'):
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"""
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produce scaled waveforms from given waveform data and a scaling factor,
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