release version: 0.1a

release notes:
==============
Features
- consistent manual phase picking through predefined SNR dependant zoom level
- uniform uncertainty estimation from waveform's properties for automatic and manual picks
- pdf representation and comparison of picks taking the uncertainty intrinsically into account
- Richter and moment magnitude estimation
- location determination with external installation of [NonLinLoc](http://alomax.free.fr/nlloc/index.html)
Known issues
- Magnitude estimation from manual PyLoT takes some time (instrument correction)

.gitignore

@@ -1,4 +0,0 @@
-*.pyc
-*~
-.idea
-pylot/RELEASE-VERSION

README.md

@@ -1,111 +1,92 @@
-# PyLoT
+# PyLoT
-
+
-version: 0.3
+version: 0.1a
-
+
-The Python picking and Localisation Tool
+The Python picking and Localisation Tool
-
+
-This python library contains a graphical user interfaces for picking seismic phases. This software needs [ObsPy][ObsPy]
+This python library contains a graphical user interfaces for picking
-and the PySide2 Qt5 bindings for python to be installed first.
+seismic phases. This software needs [ObsPy][ObsPy]
-
+and the PySide Qt4 bindings for python to be installed first.
-PILOT has originally been developed in Mathworks' MatLab. In order to distribute PILOT without facing portability
+
-problems, it has been decided to redevelop the software package in Python. The great work of the ObsPy group allows easy
+PILOT has originally been developed in Mathworks' MatLab. In order to
-handling of a bunch of seismic data and PyLoT will benefit a lot compared to the former MatLab version.
+distribute PILOT without facing portability problems, it has been decided
-
+to redevelop the software package in Python. The great work of the ObsPy
-The development of PyLoT is part of the joint research project MAGS2 and AlpArray.
+group allows easy handling of a bunch of seismic data and PyLoT will
-
+benefit a lot compared to the former MatLab version.
-## Installation
+
-
+The development of PyLoT is part of the joint research project MAGS2.
-At the moment there is no automatic installation procedure available for PyLoT. Best way to install is to clone the
+
-repository and add the path to your Python path.
+##Installation
-
+
-It is highly recommended to use Anaconda for a simple creation of a Python installation using either the *pylot.yml* or the *requirements.txt* file found in the PyLoT root directory. First make sure that the *conda-forge* channel is available in your Anaconda installation:
+At the moment there is no automatic installation procedure available for PyLoT.
-
+Best way to install is to clone the repository and add the path to your Python path.
-    conda config --add channels conda-forge
+
-
+####prerequisites:
-Afterwards run (from the PyLoT main directory where the files *requirements.txt* and *pylot.yml* are located)
+
-
+In order to run PyLoT you need to install:
-    conda env create -f pylot.yml
+
-or
+- python
-    
+- scipy
-    conda create --name pylot_38 --file requirements.txt
+- numpy
-
+- matplotlib
-to create a new Anaconda environment called "pylot_38".
+- obspy
-
+- pyside
-Afterwards activate the environment by typing
+
-
+####some handwork
-    conda activate pylot_38
+
-
+PyLoT needs a properties folder on your system to work. It should be situated in your home directory:
-#### Prerequisites:
+
-
+    mkdir ~/.pylot
-In order to run PyLoT you need to install:
+
-
+In the next step you have to copy some files to this directory:
-- Python 3
+
-- obspy
+    cp path-to-pylot/inputs/pylot.in ~/.pylot/
-- pyside2
+
-- pyqtgraph
+for local distance seismicity
-- cartopy
+
-
+    cp path-to-pylot/inputs/autoPyLoT_local.in ~/.pylot/autoPyLoT.in
-(the following are already dependencies of the above packages):
+
-- scipy
+for regional distance seismicity
-- numpy
+
-- matplotlib <= 3.3.x
+    cp path-to-pylot/inputs/autoPyLoT_regional.in ~/.pylot/autoPyLoT.in
-
+
-#### Some handwork:
+and some extra information on filtering, error estimates (just needed for reading old PILOT data) and the Richter magnitude scaling relation
-
+
-PyLoT needs a properties folder on your system to work. It should be situated in your home directory
+    cp path-to-pylot/inputs/filter.in path-to-pylot/inputs/PILOT_TimeErrors.in path-to-pylot/inputs/richter_scaling.data ~/.pylot/
-(on Windows usually C:/Users/*username*):
+
-
+You may need to do some modifications to these files. Especially folder names should be reviewed.
-    mkdir ~/.pylot
+
-
+PyLoT has been tested on Mac OSX (10.11) and Debian Linux 8.
-In the next step you have to copy some files to this directory:
+
-
+
-*for local distance seismicity*
+##release notes:
-
+==============
-    cp path-to-pylot/inputs/pylot_local.in ~/.pylot/pylot.in
+
-
+#### Features
-*for regional distance seismicity*
+
-
+- consistent manual phase picking through predefined SNR dependant zoom level
-    cp path-to-pylot/inputs/pylot_regional.in ~/.pylot/pylot.in
+- uniform uncertainty estimation from waveform's properties for automatic and manual picks
-
+- pdf representation and comparison of picks taking the uncertainty intrinsically into account 
-*for global distance seismicity*
+- Richter and moment magnitude estimation
-
+- location determination with external installation of [NonLinLoc](http://alomax.free.fr/nlloc/index.html)
-    cp path-to-pylot/inputs/pylot_global.in ~/.pylot/pylot.in
+
-
+#### Known issues
-and some extra information on error estimates (just needed for reading old PILOT data) and the Richter magnitude scaling
+
-relation
+- Magnitude estimation from manual PyLoT takes some time (instrument correction)
-
+
-    cp path-to-pylot/inputs/PILOT_TimeErrors.in path-to-pylot/inputs/richter_scaling.data ~/.pylot/
+We hope to solve these with the next release.
-
+
-You may need to do some modifications to these files. Especially folder names should be reviewed.
+####staff:
-
+======
-PyLoT has been tested on Mac OSX (10.11), Debian Linux 8 and on Windows 10.
+
-
+original author(s): L. Kueperkoch, S. Wehling-Benatelli, M. Bischoff (PILOT)
-## Release notes
+
-
+developer(s): S. Wehling-Benatelli, L. Kueperkoch, K. Olbert, M. Bischoff,
-#### Features:
+              C. Wollin, M. Rische, M. Paffrath
-
+
-- event organisation in project files and waveform visualisation
+others: A. Bruestle, T. Meier, W. Friederich
-- consistent manual phase picking through predefined SNR dependant zoom level
+
-- consistent automatic phase picking routines using Higher Order Statistics, AIC and Autoregression
+
-- interactive tuning of auto-pick parameters
+[ObsPy]: http://github.com/obspy/obspy/wiki
-- uniform uncertainty estimation from waveform's properties for automatic and manual picks
+
-- pdf representation and comparison of picks taking the uncertainty intrinsically into account
+October 2016
-- Richter and moment magnitude estimation
-- location determination with external installation of [NonLinLoc](http://alomax.free.fr/nlloc/index.html)
-
-#### Known issues:
-
-We hope to solve these with the next release.
-
-## Staff
-
-Original author(s): M. Rische, S. Wehling-Benatelli, L. Kueperkoch, M. Bischoff (PILOT)
-
-Developer(s): S. Wehling-Benatelli, M. Paffrath, L. Kueperkoch, K. Olbert, M. Bischoff, C. Wollin, M. Rische, D. Arnold, K. Cökerim, S. Zimmermann
-
-Others: A. Bruestle, T. Meier, W. Friederich
-
-
-[ObsPy]: http://github.com/obspy/obspy/wiki
-
-April 2022

autoPyLoT.py

@@ -4,137 +4,61 @@
 from __future__ import print_function
 
 import argparse
-import datetime
 import glob
 import os
-import traceback
 
 from obspy import read_events
-from obspy.core.event import ResourceIdentifier
 
-import pylot.core.loc.focmec as focmec
+import pylot.core.loc.hsat as hsat
-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.velest as velest
+from pylot.core.analysis.magnitude import MomentMagnitude, RichterMagnitude
-# from PySide.QtGui import QWidget, QInputDialog
-from pylot.core.analysis.magnitude import MomentMagnitude, LocalMagnitude
 from pylot.core.io.data import Data
-from pylot.core.io.inputs import PylotParameter
+from pylot.core.io.inputs import AutoPickParameter
 from pylot.core.pick.autopick import autopickevent, iteratepicker
-from pylot.core.util.dataprocessing import restitute_data, Metadata
+from pylot.core.util.dataprocessing import restitute_data, read_metadata, \
-from pylot.core.util.defaults import SEPARATOR
+    remove_underscores
-from pylot.core.util.event import Event
 from pylot.core.util.structure import DATASTRUCTURE
-from pylot.core.util.utils import get_none, trim_station_components, check4gapsAndRemove, check4doubled, \
-    check4rotated
 from pylot.core.util.version import get_git_version as _getVersionString
 
 __version__ = _getVersionString()
 
 
-def autoPyLoT(input_dict=None, parameter=None, inputfile=None, fnames=None, eventid=None, savepath=None,
+def autoPyLoT(inputfile):
-              savexml=True, station='all', iplot=0, ncores=0, obspyDMT_wfpath=False):
     """
     Determine phase onsets automatically utilizing the automatic picking
     algorithms by Kueperkoch et al. 2010/2012.
-    :param obspyDMT_wfpath: if obspyDMT is used, name of data directory ("raw" or "processed")
+
-    :param input_dict:
+    :param inputfile: path to the input file containing all parameter
-    :type input_dict:
+    information for automatic picking (for formatting details, see.
-    :param parameter: PylotParameter object containing parameters used for automatic picking
+    `~pylot.core.io.inputs.AutoPickParameter`
-    :type parameter: pylot.core.io.inputs.PylotParameter
-    :param inputfile: path to the input file containing all parameter information for automatic picking
-    (for formatting details, see. `~pylot.core.io.inputs.PylotParameter`
     :type inputfile: str
-    :param fnames: list of data file names or None when called from GUI
+    :return:
-    :type fnames: str
+
-    :param eventid: event path incl. event ID (path to waveform files)
+    .. rubric:: Example
-    :type eventid: str
+
-    :param savepath: save path for autoPyLoT output, if None/"None" output will be saved in event folder
-    :type savepath: str
-    :param savexml: export results in XML file if True
-    :type savexml: bool
-    :param station: choose specific station name or 'all' to pick all stations
-    :type station: str
-    :param iplot: logical variable for plotting: 0=none, 1=partial, 2=all
-    :type iplot: int
-    :param ncores: number of cores used for parallel processing. Default (0) uses all available cores
-    :type ncores: int
-    :return: dictionary containing picks
-    :rtype: dict
     """
-
-    if ncores == 1:
-        sp_info = 'autoPyLoT is running serial on 1 cores.'
-    else:
-        if ncores == 0:
-            ncores_readable = 'all available'
-        else:
-            ncores_readable = ncores
-        sp_info = 'autoPyLoT is running in parallel on {} cores.'.format(ncores_readable)
-
     splash = '''************************************\n
                 *********autoPyLoT starting*********\n
                 The Python picking and Location Tool\n
-                Version {version} 2017\n
+                Version {version} 2015\n
                 \n
                 Authors:\n
-                L. Kueperkoch (BESTEC GmbH, Landau i. d. Pfalz, \n
+                S. Wehling-Benatelli (Ruhr-Universität Bochum)\n
-                   now at igem GmbH, Mainz)
+                L. Küperkoch (BESTEC GmbH, Landau i. d. Pfalz)\n
-                M. Paffrath (Ruhr-Universitaet Bochum)\n
+                K. Olbert (Christian-Albrechts Universität zu Kiel)\n
-                S. Wehling-Benatelli (Ruhr-Universitaet Bochum)\n
+                ***********************************'''.format(version=_getVersionString())
-                
-                {sp}
-                ***********************************'''.format(version=_getVersionString(),
-                                                              sp=sp_info)
     print(splash)
 
-    parameter = get_none(parameter)
+    # reading parameter file
-    inputfile = get_none(inputfile)
-    eventid = get_none(eventid)
 
-    fig_dict = None
+    parameter = AutoPickParameter(inputfile)
-    fig_dict_wadatijack = None
 
-    if input_dict and isinstance(input_dict, dict):
+    data = Data()
-        if 'parameter' in input_dict:
-            parameter = input_dict['parameter']
-        if 'fig_dict' in input_dict:
-            fig_dict = input_dict['fig_dict']
-        if 'fig_dict_wadatijack' in input_dict:
-            fig_dict_wadatijack = input_dict['fig_dict_wadatijack']
-        if 'station' in input_dict:
-            station = input_dict['station']
-        if 'fnames' in input_dict:
-            fnames = input_dict['fnames']
-        if 'eventid' in input_dict:
-            eventid = input_dict['eventid']
-        if 'iplot' in input_dict:
-            iplot = input_dict['iplot']
-        if 'savexml' in input_dict:
-            savexml = input_dict['savexml']
-        if 'obspyDMT_wfpath' in input_dict:
-            obspyDMT_wfpath = input_dict['obspyDMT_wfpath']
-
-    if not parameter:
-        if not inputfile:
-            print('Using default input parameter')
-        parameter = PylotParameter(inputfile)
-    else:
-        if not type(parameter) == PylotParameter:
-            print('Wrong input type for parameter: {}'.format(type(parameter)))
-            return
-        if inputfile:
-            print('Parameters set and input file given. Choose either of both.')
-            return
 
     evt = None
+    # getting information on data structure
 
-    # reading parameter file
     if parameter.hasParam('datastructure'):
-        # getting information on data structure
         datastructure = DATASTRUCTURE[parameter.get('datastructure')]()
         dsfields = {'root': parameter.get('rootpath'),
                     'dpath': parameter.get('datapath'),
@@ -142,15 +66,15 @@ def autoPyLoT(input_dict=None, parameter=None, inputfile=None, fnames=None, even
 
         exf = ['root', 'dpath', 'dbase']
 
-        if parameter['eventID'] != '*' and fnames == 'None':
+        if parameter.hasParam('eventID'):
-            dsfields['eventID'] = parameter['eventID']
+            dsfields['eventID'] = parameter.get('eventID')
             exf.append('eventID')
 
         datastructure.modifyFields(**dsfields)
         datastructure.setExpandFields(exf)
 
-        # check if default location routine NLLoc is available and all stations are used
+        # check if default location routine NLLoc is available
-        if get_none(parameter['nllocbin']) and station == 'all':
+        if parameter.hasParam('nllocbin'):
             locflag = 1
             # get NLLoc-root path
             nllocroot = parameter.get('nllocroot')
@@ -167,7 +91,7 @@ def autoPyLoT(input_dict=None, parameter=None, inputfile=None, fnames=None, even
             ttpat = parameter.get('ttpatter')
             # pattern of NLLoc-output file
             nllocoutpatter = parameter.get('outpatter')
-            maxnumit = 2  # maximum number of iterations for re-picking
+            maxnumit = 3  # maximum number of iterations for re-picking
         else:
             locflag = 0
             print("                 !!!              ")
@@ -175,142 +99,31 @@ def autoPyLoT(input_dict=None, parameter=None, inputfile=None, fnames=None, even
             print("!!No source parameter estimation possible!!")
             print("                 !!!              ")
 
-        wfpath_extension = ''
+        datapath = datastructure.expandDataPath()
-        if obspyDMT_wfpath not in [None, False, 'False', '']:
+        if not parameter.hasParam('eventID'):
-            wfpath_extension = obspyDMT_wfpath
+            # multiple event processing
-            print('Using obspyDMT structure. There will be no restitution, as pre-processed data are expected.')
+            # read each event in database
-            if wfpath_extension != 'processed':
+            events = [events for events in glob.glob(os.path.join(datapath, '*')) if os.path.isdir(events)]
-                print('WARNING: Expecting wfpath_extension to be "processed" for'
-                      ' pre-processed data but received "{}" instead!!!'.format(wfpath_extension))
-
-        if not input_dict:
-            # started in production mode
-            datapath = datastructure.expandDataPath()
-            if fnames == 'None' and parameter['eventID'] == '*':
-                # multiple event processing
-                # read each event in database
-                events = [event for event in glob.glob(os.path.join(datapath, '*')) if
-                          (os.path.isdir(event) and not event.endswith('EVENTS-INFO'))]
-            elif fnames == 'None' and parameter['eventID'] != '*' and not type(parameter['eventID']) == list:
-                # single event processing
-                events = glob.glob(os.path.join(datapath, parameter['eventID']))
-            elif fnames == 'None' and type(parameter['eventID']) == list:
-                # multiple event processing
-                events = []
-                for eventID in parameter['eventID']:
-                    events.append(os.path.join(datapath, eventID))
-            else:
-                # autoPyLoT was initialized from GUI
-                events = [eventid]
-                evID = os.path.split(eventid)[-1]
-                locflag = 2
         else:
-            # started in tune or interactive mode
+            # single event processing
-            datapath = os.path.join(parameter['rootpath'],
+            events = glob.glob(os.path.join(datapath, parameter.get('eventID')))
-                                    parameter['datapath'])
+        for event in events:
-            events = []
+            data.setWFData(glob.glob(os.path.join(datapath, event, '*')))
-            for eventID in eventid:
+            evID = os.path.split(event)[-1]
-                events.append(os.path.join(datapath,
+            print('Working on event %s' % event)
-                                           parameter['database'],
+            print(data)
-                                           eventID))
+            wfdat = data.getWFData()  # all available streams
-
+            wfdat = remove_underscores(wfdat)
-        if not events:
+            metadata =  read_metadata(parameter.get('invdir'))
-            print('autoPyLoT: No events given. Return!')
+            corr_dat, rest_flag = restitute_data(wfdat.copy(), *metadata)
-            return
-
-        # transform system path separator to '/'
-        for index, eventpath in enumerate(events):
-            eventpath = eventpath.replace(SEPARATOR, '/')
-            events[index] = eventpath
-
-        allpicks = {}
-        glocflag = locflag
-
-        nEvents = len(events)
-        for index, eventpath in enumerate(events):
-            print('Working on: {} ({}/{})'.format(eventpath, index + 1, nEvents))
-            evID = os.path.split(eventpath)[-1]
-            event_datapath = os.path.join(eventpath, wfpath_extension)
-            fext = '.xml'
-            filename = os.path.join(eventpath, 'PyLoT_' + evID + fext)
-            try:
-                data = Data(evtdata=filename)
-                data.get_evt_data().path = eventpath
-                print('Reading event data from filename {}...'.format(filename))
-            except Exception as e:
-                print('Could not read event from file {}: {}'.format(filename, e))
-                data = Data()
-                pylot_event = Event(eventpath)  # event should be path to event directory
-                data.setEvtData(pylot_event)
-            if fnames == 'None':
-                data.set_wf_data(glob.glob(os.path.join(datapath, event_datapath, '*')))
-                # the following is necessary because within
-                # multiple event processing no event ID is provided
-                # in autopylot.in
-                try:
-                    parameter.get('eventID')
-                except Exception:
-                    now = datetime.datetime.now()
-                    eventID = '%d%02d%02d%02d%02d' % (now.year,
-                                                      now.month,
-                                                      now.day,
-                                                      now.hour,
-                                                      now.minute)
-                    parameter.setParam(eventID=eventID)
-            else:
-                data.set_wf_data(fnames)
-
-                eventpath = events[0]
-                # now = datetime.datetime.now()
-                # evID = '%d%02d%02d%02d%02d' % (now.year,
-                #                               now.month,
-                #                               now.day,
-                #                               now.hour,
-                #                               now.minute)
-                parameter.setParam(eventID=eventid)
-            wfdat = data.get_wf_data()  # all available streams
-            if not station == 'all':
-                wfdat = wfdat.select(station=station)
-                if not wfdat:
-                    print('Could not find station {}. STOP!'.format(station))
-                    return
-            # wfdat = remove_underscores(wfdat)
-            # trim components for each station to avoid problems with different trace starttimes for one station
-            wfdat = check4gapsAndRemove(wfdat)
-            wfdat = check4doubled(wfdat)
-            wfdat = trim_station_components(wfdat, trim_start=True, trim_end=False)
-            if not wfpath_extension:
-                metadata = Metadata(parameter.get('invdir'))
-            else:
-                metadata = Metadata(os.path.join(eventpath, 'resp'))
-            corr_dat = None
-            if metadata:
-                # rotate stations to ZNE
-                try:
-                    wfdat = check4rotated(wfdat, metadata)
-                except Exception as e:
-                    print('Could not rotate station {} to ZNE:\n{}'.format(wfdat[0].stats.station,
-                                                                           traceback.format_exc()))
-                if locflag:
-                    print("Restitute data ...")
-                    corr_dat = restitute_data(wfdat.copy(), metadata, ncores=ncores)
-            if not corr_dat and locflag:
-                locflag = 2
-            print('Stations: %s' % (station))
-            print(wfdat)
             ##########################################################
             # !automated picking starts here!
-            fdwj = None
+            picks = autopickevent(wfdat, parameter)
-            if fig_dict_wadatijack:
-                fdwj = fig_dict_wadatijack[evID]
-            picks = autopickevent(wfdat, parameter, iplot=iplot, fig_dict=fig_dict,
-                                  fig_dict_wadatijack=fdwj,
-                                  ncores=ncores, metadata=metadata, origin=data.get_evt_data().origins)
             ##########################################################
             # locating
-            if locflag > 0:
+            if locflag == 1:
                 # write phases to NLLoc-phase file
-                nll.export(picks, phasefile, parameter)
+                nll.export(picks, phasefile)
 
                 # For locating the event the NLLoc-control file has to be modified!
                 nllocout = '%s_%s' % (evID, nllocoutpatter)
@@ -319,7 +132,7 @@ def autoPyLoT(input_dict=None, parameter=None, inputfile=None, fnames=None, even
                                   ttpat)
 
                 # locate the event
-                nll.locate(ctrfile, parameter)
+                nll.locate(ctrfile)
 
                 # !iterative picking if traces remained unpicked or occupied with bad picks!
                 # get theoretical onset times for picks with weights >= 4
@@ -341,48 +154,22 @@ def autoPyLoT(input_dict=None, parameter=None, inputfile=None, fnames=None, even
                         # get latest NLLoc-location file if several are available
                         nllocfile = max(glob.glob(locsearch), key=os.path.getctime)
                         evt = read_events(nllocfile)[0]
-                        # calculate seismic moment Mo and moment magnitude Mw
+                        # calculating seismic moment Mo and moment magnitude Mw
                         moment_mag = MomentMagnitude(corr_dat, evt, parameter.get('vp'),
                                                      parameter.get('Qp'),
-                                                     parameter.get('rho'), True,
+                                                     parameter.get('rho'), True, 0)
-                                                     iplot)
                         # update pick with moment property values (w0, fc, Mo)
-                        for stats, props in moment_mag.moment_props.items():
+                        for station, props in moment_mag.moment_props.items():
-                            picks[stats]['P'].update(props)
+                            picks[station]['P'].update(props)
                         evt = moment_mag.updated_event()
-                        net_mw = moment_mag.net_magnitude()
+                        local_mag = RichterMagnitude(corr_dat, evt,
-                        if net_mw is not None:
+                                                     parameter.get('sstop'), True, 0)
-                            print("Network moment magnitude: %4.1f" % net_mw.mag)
+                        for station, amplitude in local_mag.amplitudes.items():
-                        # calculate local (Richter) magntiude
+                            picks[station]['S']['Ao'] = amplitude.generic_amplitude
-                        WAscaling = parameter.get('WAscaling')
+                        evt = local_mag.updated_event()
-                        magscaling = parameter.get('magscaling')
-                        local_mag = LocalMagnitude(corr_dat, evt,
-                                                   parameter.get('sstop'),
-                                                   WAscaling, True, iplot)
-                        # update pick with local magnitude property values
-                        for stats, amplitude in local_mag.amplitudes.items():
-                            picks[stats]['S']['Ao'] = amplitude.generic_amplitude
-                        print("Local station magnitudes scaled with:")
-                        print("log(Ao) + %f * log(r) + %f * r + %f" % (WAscaling[0],
-                                                                       WAscaling[1],
-                                                                       WAscaling[2]))
-                        evt = local_mag.updated_event(magscaling)
-                        net_ml = local_mag.net_magnitude(magscaling)
-                        if net_ml:
-                            print("Network local magnitude: %4.1f" % net_ml.mag)
-                        if magscaling is None:
-                            scaling = False
-                        elif magscaling[0] != 0 and magscaling[1] != 0:
-                            scaling = False
-                        else:
-                            scaling = True
-                        if scaling:
-                            print("Network local magnitude scaled with:")
-                            print("%f * Ml + %f" % (magscaling[0], magscaling[1]))
                     else:
                         print("autoPyLoT: No NLLoc-location file available!")
                         print("No source parameter estimation possible!")
-                        locflag = 9
                 else:
                     # get theoretical P-onset times from NLLoc-location file
                     locsearch = '%s/loc/%s.????????.??????.grid?.loc.hyp' % (nllocroot, nllocout)
@@ -396,19 +183,13 @@ def autoPyLoT(input_dict=None, parameter=None, inputfile=None, fnames=None, even
                                 print("autoPyLoT: Number of maximum iterations reached, stop iterative picking!")
                                 break
                             print("autoPyLoT: Starting with iteration No. %d ..." % nlloccounter)
-                            if input_dict:
+                            picks = iteratepicker(wfdat, nllocfile, picks, badpicks, parameter)
-                                if 'fig_dict' in input_dict:
-                                    fig_dict = input_dict['fig_dict']
-                                    picks = iteratepicker(wfdat, nllocfile, picks, badpicks, parameter,
-                                                          fig_dict=fig_dict)
-                            else:
-                                picks = iteratepicker(wfdat, nllocfile, picks, badpicks, parameter)
                             # write phases to NLLoc-phase file
-                            nll.export(picks, phasefile, parameter)
+                            nll.export(picks, phasefile)
                             # remove actual NLLoc-location file to keep only the last
                             os.remove(nllocfile)
                             # locate the event
-                            nll.locate(ctrfile, parameter)
+                            nll.locate(ctrfile)
                             print("autoPyLoT: Iteration No. %d finished." % nlloccounter)
                             # get updated NLLoc-location file
                             nllocfile = max(glob.glob(locsearch), key=os.path.getctime)
@@ -417,145 +198,73 @@ def autoPyLoT(input_dict=None, parameter=None, inputfile=None, fnames=None, even
                             for key in picks:
                                 if picks[key]['P']['weight'] >= 4 or picks[key]['S']['weight'] >= 4:
                                     badpicks.append([key, picks[key]['P']['mpp']])
-                            print("autoPyLoT: After iteration No. %d: %d bad onsets found ..." % (nlloccounter,
+                            print("autoPyLoT: After iteration No. %d: %d bad onsets found ..." % (nlloccounter, \
                                                                                                   len(badpicks)))
                             if len(badpicks) == 0:
                                 print("autoPyLoT: No more bad onsets found, stop iterative picking!")
                                 nlloccounter = maxnumit
                         evt = read_events(nllocfile)[0]
-                        if locflag < 2:
+                        # calculating seismic moment Mo and moment magnitude Mw
-                            # calculate seismic moment Mo and moment magnitude Mw
+                        moment_mag = MomentMagnitude(corr_dat, evt, parameter.get('vp'),
-                            moment_mag = MomentMagnitude(corr_dat, evt, parameter.get('vp'),
+                                                     parameter.get('Qp'),
-                                                         parameter.get('Qp'),
+                                                     parameter.get('rho'), True, 0)
-                                                         parameter.get('rho'), True,
+                        # update pick with moment property values (w0, fc, Mo)
-                                                         iplot)
+                        for station, props in moment_mag.moment_props.items():
-                            # update pick with moment property values (w0, fc, Mo)
+                            picks[station]['P'].update(props)
-                            for stats, props in moment_mag.moment_props.items():
+                        evt = moment_mag.updated_event()
-                                if stats in picks:
+                        local_mag = RichterMagnitude(corr_dat, evt,
-                                    picks[stats]['P'].update(props)
+                                                     parameter.get('sstop'), True, 0)
-                            evt = moment_mag.updated_event()
+                        for station, amplitude in local_mag.amplitudes.items():
-                            net_mw = moment_mag.net_magnitude()
+                            picks[station]['S']['Ao'] = amplitude.generic_amplitude
-                            if net_mw is not None:
+                        evt = local_mag.updated_event()
-                                print("Network moment magnitude: %4.1f" % net_mw.mag)
+                        net_mw = moment_mag.net_magnitude()
-                            # calculate local (Richter) magntiude
+                        print("Network moment magnitude: %4.1f" % net_mw.mag)
-                            WAscaling = parameter.get('WAscaling')
-                            magscaling = parameter.get('magscaling')
-                            local_mag = LocalMagnitude(corr_dat, evt,
-                                                       parameter.get('sstop'),
-                                                       WAscaling, True, iplot)
-                            # update pick with local magnitude property values
-                            for stats, amplitude in local_mag.amplitudes.items():
-                                if stats in picks:
-                                    picks[stats]['S']['Ao'] = amplitude.generic_amplitude
-                            print("Local station magnitudes scaled with:")
-                            print("log(Ao) + %f * log(r) + %f * r + %f" % (WAscaling[0],
-                                                                           WAscaling[1],
-                                                                           WAscaling[2]))
-                            evt = local_mag.updated_event(magscaling)
-                            net_ml = local_mag.net_magnitude(magscaling)
-                            if net_ml:
-                                print("Network local magnitude: %4.1f" % net_ml.mag)
-                            if magscaling is None:
-                                scaling = False
-                            elif magscaling[0] != 0 and magscaling[1] != 0:
-                                scaling = False
-                            else:
-                                scaling = True
-                            if scaling:
-                                print("Network local magnitude scaled with:")
-                                print("%f * Ml + %f" % (magscaling[0], magscaling[1]))
                     else:
                         print("autoPyLoT: No NLLoc-location file available! Stop iteration!")
-                        locflag = 9
             ##########################################################
-            # write phase files for various location 
+            # write phase files for various location routines
-            # and fault mechanism calculation routines
+            # HYPO71
-            # ObsPy event object
+            hypo71file = '%s/autoPyLoT_HYPO71.pha' % event
-            if evt is not None:
+            hsat.export(picks, hypo71file)
-                event_id = eventpath.split('/')[-1]
-                evt.resource_id = ResourceIdentifier('smi:local/' + event_id)
-                data.applyEVTData(evt, 'event')
             data.applyEVTData(picks)
-            if savexml:
+            if evt is not None:
-                if savepath == 'None' or savepath is None:
+                data.applyEVTData(evt, 'event')
-                    saveEvtPath = eventpath
+            fnqml = '%s/autoPyLoT' % event
-                else:
+            data.exportEvent(fnqml)
-                    saveEvtPath = savepath
-                fnqml = '%s/PyLoT_%s_autopylot' % (saveEvtPath, evID)
-                data.exportEvent(fnqml, fnext='.xml', fcheck=['auto', 'magnitude', 'origin'])
-            if locflag == 1:
-                # HYPO71
-                hypo71file = '%s/PyLoT_%s_HYPO71_phases' % (eventpath, evID)
-                hypo71.export(picks, hypo71file, parameter)
-                # HYPOSAT
-                hyposatfile = '%s/PyLoT_%s_HYPOSAT_phases' % (eventpath, evID)
-                hyposat.export(picks, hyposatfile, parameter)
-                # VELEST
-                velestfile = '%s/PyLoT_%s_VELEST_phases.cnv' % (eventpath, evID)
-                velest.export(picks, velestfile, evt, parameter)
-                # hypoDD
-                hypoddfile = '%s/PyLoT_%s_hypoDD_phases.pha' % (eventpath, evID)
-                hypodd.export(picks, hypoddfile, parameter, evt)
-                # FOCMEC
-                focmecfile = '%s/PyLoT_%s_FOCMEC.in' % (eventpath, evID)
-                focmec.export(picks, focmecfile, parameter, evt)
-                # HASH
-                hashfile = '%s/PyLoT_%s_HASH' % (eventpath, evID)
-                hash.export(picks, hashfile, parameter, evt)
 
             endsplash = '''------------------------------------------\n'
                            -----Finished event %s!-----\n'
                            ------------------------------------------'''.format \
                             (version=_getVersionString()) % evID
             print(endsplash)
-            locflag = glocflag
             if locflag == 0:
                 print("autoPyLoT was running in non-location mode!")
 
-            # save picks for current event ID to dictionary with ALL picks
-            allpicks[evID] = picks
-
     endsp = '''####################################\n
                ************************************\n
                *********autoPyLoT terminates*******\n
                The Python picking and Location Tool\n
                ************************************'''.format(version=_getVersionString())
     print(endsp)
-    return allpicks
 
 
 if __name__ == "__main__":
+    from pylot.core.util.defaults import AUTOMATIC_DEFAULTS
     # parse arguments
     parser = argparse.ArgumentParser(
         description='''autoPyLoT automatically picks phase onset times using higher order statistics,
-                       autoregressive prediction and AIC followed by locating the seismic events using 
+                       autoregressive prediction and AIC''')
-                       NLLoc''')
 
     parser.add_argument('-i', '-I', '--inputfile', type=str,
                         action='store',
                         help='''full path to the file containing the input
-                        parameters for autoPyLoT''')
+                        parameters for autoPyLoT''',
-    parser.add_argument('-p', '-P', '--iplot', type=int,
+                        default=AUTOMATIC_DEFAULTS
-                        action='store', default=0,
+                        )
-                        help='''optional, logical variable for plotting: 0=none, 1=partial, 2=all''')
+    parser.add_argument('-v', '-V', '--version', action='version',
-    parser.add_argument('-f', '-F', '--fnames', type=str,
+                        version='autoPyLoT ' + __version__,
-                        action='store',
+                        help='show version information and exit')
-                        help='''optional, list of data file names''')
-    parser.add_argument('-e', '--eventid', type=str,
-                        action='store',
-                        help='''optional, event path incl. event ID''')
-    parser.add_argument('-s', '-S', '--spath', type=str,
-                        action='store',
-                        help='''optional, save path for autoPyLoT output''')
-    parser.add_argument('-c', '-C', '--ncores', type=int,
-                        action='store', default=0,
-                        help='''optional, number of CPU cores used for parallel processing (default: all available(=0))''')
-    parser.add_argument('-dmt', '-DMT', '--obspy_dmt_wfpath', type=str,
-                        action='store', default=False,
-                        help='''optional, wftype (raw, processed) used for obspyDMT database structure''')
 
     cla = parser.parse_args()
 
-    picks = autoPyLoT(inputfile=str(cla.inputfile), fnames=str(cla.fnames),
+    autoPyLoT(str(cla.inputfile))
-                      eventid=str(cla.eventid), savepath=str(cla.spath),
-                      ncores=cla.ncores, iplot=int(cla.iplot), obspyDMT_wfpath=str(cla.obspy_dmt_wfpath))

autopylot.sh

@@ -1,12 +0,0 @@
-#!/bin/bash
-
-#$ -l low
-#$ -cwd
-#$ -pe smp 40
-##$ -l mem=3G
-#$ -l h_vmem=6G
-#$ -l os=*stretch
-
-conda activate pylot_311
-
-python ./autoPyLoT.py -i /home/marcel/.pylot/pylot_adriaarray.in -c 20 -dmt processed

docs/gui.md

@@ -1,474 +0,0 @@
-# PyLoT Documentation
-
-- [PyLoT Documentation](#pylot-documentation)
-- [PyLoT GUI](#pylot-gui)
-    - [First start](#first-start)
-    - [Main Screen](#main-screen)
-        - [Waveform Plot](#waveform-plot)
-            - [Mouse view controls](#mouse-view-controls)
-            - [Buttons](#buttons)
-        - [Array Map](#array-map)
-        - [Eventlist](#eventlist)
-    - [Usage](#usage)
-        - [Projects and Events](#projects-and-events)
-        - [Event folder structure](#event-folder-structure)
-        - [Loading event information from CSV file](#loading-event-information-from-csv-file)
-        - [Adding events to project](#adding-events-to-project)
-        - [Saving projects](#saving-projects)
-        - [Adding metadata](#adding-metadata)
-- [Picking](#picking)
-    - [Manual Picking](#manual-picking)
-        - [Picking window](#picking-window)
-            - [Picking Window Settings](#picking-window-settings)
-        - [Filtering](#filtering)
-        - [Export and Import of manual picks](#export-and-import-of-manual-picks)
-            - [Export](#export)
-            - [Import](#import)
-    - [Automatic Picking](#automatic-picking)
-        - [Tuning](#tuning)
-        - [Production run of the autopicker](#production-run-of-the-autopicker)
-        - [Evaluation of automatic picks](#evaluation-of-automatic-picks)
-            - [1. Jackknife check](#1-jackknife-check)
-            - [2. Wadati check](#2-wadati-check)
-        - [Comparison between automatic and manual picks](#comparison-between-automatic-and-manual-picks)
-        - [Export and Import of automatic picks](#export-and-import-of-automatic-picks)
-- [Location determination](#location-determination)
-- [FAQ](#faq)
-
-# PyLoT GUI
-
-This section describes how to use PyLoT graphically to view waveforms and create manual or automatic picks.
-
-## First start
-
-After opening PyLoT for the first time, the setup routine asks for the following information:
-
-Questions:
-
-1. Full Name
-2. Authority: Enter authority/institution name
-3. Format: Enter output format (*.xml, *.cnv, *.obs)
-
-[//]: <> (TODO: explain what these things mean, where they are used)
-
-## Main Screen
-
-After entering the [information](#first-start), PyLoTs main window is shown. It defaults to a view of
-the [Waveform Plot](#waveform-plot), which starts empty.
-
-<img src=images/gui/pylot-main-screen.png alt="Tune autopicks button" title="Tune autopicks button">
-
-Add trace data by [loading a project](#projects-and-events) or by [adding event data](#adding-events-to-project).
-
-### Waveform Plot
-
-The waveform plot shows a trace list of all stations of an event.   
-Click on any trace to open the stations [picking window](#picking-window), where you can review automatic and manual
-picks.
-
-<img src=images/gui/pylot-waveform-plot.png alt="A Waveform Plot showing traces of one event">
-
-Above the traces the currently displayed event can be selected. In the bottom bar information about the trace under the
-mouse cursor is shown. This information includes the station name (station), the absolute UTC time (T) of the point
-under the mouse cursor and the relative time since the first trace start in seconds (t) as well as a trace count.
-
-#### Mouse view controls
-
-Hold left mouse button and drag to pan view.
-
-Hold right mouse button and Direction | Result --- | --- Move the mouse up | Increase amplitude scale Move the mouse
-down | Decrease amplitude scale Move the mouse right | Increase time scale Move the mouse left | Decrease time scale
-
-Press right mouse button and click "View All" from the context menu to reset the view.
-
-#### Buttons
-
-[//]: <> (Hack: We need these invisible spaces to add space to the first column, otherwise )
-
-| Icon &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp;&nbsp; &nbsp; &nbsp; &nbsp; &nbsp; &nbsp; | Description                                                                                                                                                                                                                                                                                                                                                                                                |
-|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
-| <img src="../icons/newfile.png" alt="Create new project" width="64" height="64">                                                                                                   | Create a new project, for more information about projects see [Projects and Events](#projects-and-events).                                                                                                                                                                                                                                                                                                 |
-| <img src="../icons/openproject.png" alt="Open project" width="64" height="64">                                                                                                     | Load a project file from disk.                                                                                                                                                                                                                                                                                                                                                                             |
-| <img src="../icons/saveproject.png" alt="Save Project" width="64" height="64">                                                                                                     | Save all current events into an associated project file on disk. If there is no project file currently associated, you will be asked to create a new one.                                                                                                                                                                                                                                                  |
-| <img src="../icons/saveprojectas.png" alt="Save Project as" width="64" height="64">                                                                                                | Save all current events into a new project file on disk. See [Saving projects](#saving-projects).                                                                                                                                                                                                                                                                                                          |
-| <img src="../icons/add.png" alt="Add event data" width="64" height="64">                                                                                                           | Add event data by selecting directories containing waveforms. For more information see [Event folder structure](#event-folder-structure).                                                                                                                                                                                                                                                                  |
-| <img src="../icons/openpick.png" alt="Load event information" width="64" height="64">                                                                                              | Load picks/origins from disk into the currently displayed event. If a pick already exists for a station, the one from file will overwrite the existing one.                                                                                                                                                                                                                                                |
-| <img src="../icons/openpicks.png" alt="Load information for all events" width="64" height="64">                                                                                    | Load picks/origins for all events of the current project. PyLoT searches for files within the directory of the event and tries to load them for that event. For this function to work, the files containing picks/origins have to be named as described in [Event folder   structure](#event-folder-structure). If a pick already exists for a station, the one from file will overwrite the existing one. |
-| <img src="../icons/savepicks.png" alt="Save picks" width="64" height="64">                                                                                                         | Save event information such as picks and origin to file. You will be asked to select a directory in which this information should be saved.                                                                                                                                                                                                                                                                |
-| <img src="../icons/openloc.png" alt="Load location information" width="64" height="64">                                                                                            | Load location information from disk,                                                                                                                                                                                                                                                                                                                                                                       |
-| <img src="../icons/Matlab_PILOT_icon.png" alt="Load legacy information" width="64" height="64">                                                                                    | Load event information from a previous, MatLab based PILOT version.                                                                                                                                                                                                                                                                                                                                        |
-| <img src="../icons/key_Z.png" alt="Display Z" width="64" height="64">                                                                                                              | Display Z component of streams in waveform plot.                                                                                                                                                                                                                                                                                                                                                           |
-| <img src="../icons/key_N.png" alt="Display N" width="64" height="64">                                                                                                              | Display N component of streams in waveform plot.                                                                                                                                                                                                                                                                                                                                                           |
-| <img src="../icons/key_E.png" alt="Display E" width="64" height="64">                                                                                                              | Display E component of streams in waveform plot.                                                                                                                                                                                                                                                                                                                                                           |
-| <img src="../icons/tune.png" alt="Tune Autopicker" width="64" height="64">                                                                                                         | Open the [Tune Autopicker window](#tuning).                                                                                                                                                                                                                                                                                                                                                                |
-| <img src="../icons/autopylot_button.png" alt="" width="64" height="64">                                                                                                            | Opens a window that allows starting the autopicker for all events ([Production run of the AutoPicker](#production-run-of-the-autopicker)).                                                                                                                                                                                                                                                                 |
-| <img src="../icons/compare_button.png" alt="Comparison" width="64" height="64">                                                                                                    | Compare automatic and manual picks, only available if automatic and manual picks for an event exist. See [Comparison between automatic and manual picks](#comparison-between-automatic-and-manual-picks).                                                                                                                                                                                                  |
-| <img src="../icons/locate_button.png" alt="Locate event" width="64" height="64">                                                                                                   | Run a location routine (NonLinLoc) as configured in the settings on the picks. See [Location determination](#location-determination).                                                                                                                                                                                                                                                                      |
-
-### Array Map
-
-The array map will display a color diagram to allow a visual check of the consistency of picks across multiple stations.
-This works by calculating the time difference of every onset to the earliest onset. Then isolines are drawn between
-stations with the same time difference and the areas between isolines are colored.  
-The result should resemble a color gradient as the wavefront rolls over the network area. Stations where picks are
-earlier/later than their neighbours can be reviewed by clicking on them, which opens
-the [picking window](#picking-window).
-
-Above the Array Map the picks that are used to create the map can be customized. The phase of picks that should be used
-can be selected, which allows checking the consistency of the P- and S-phase separately. Additionally the pick type can
-be set to manual, automatic or hybrid, meaning display only manual picks, automatic picks or only display automatic
-picks for stations where there are no manual ones.
-
-![Array Map](images/gui/arraymap-example.png "Array Map")  
-*Array Map for an event at the Northern Mid Atlantic Ridge, between North Africa and Mexico (Lat. 22.58, Lon. -45.11).
-The wavefront moved from west to east over the network area (Alps and Balcan region), with the earliest onsets in blue
-in the west.*
-
-To be able to display an array map PyLoT needs to load an inventory file, where the metadata of seismic stations is
-kept. For more information see [Metadata](#adding-metadata). Additionally automatic or manual picks need to exist for
-the current event.
-
-### Eventlist
-
-The eventlist displays event parameters. The displayed parameters are saved in the .xml file in the event folder. Events
-can be deleted from the project by pressing the red X in the leftmost column of the corresponding event.
-
-<img src="images/gui/eventlist.png" alt="Eventlist">
-
-| Column     | Description                                                                                                        |
-|------------|--------------------------------------------------------------------------------------------------------------------|
-| Event      | Full path to the events folder.                                                                                    |
-| Time       | Time of event.                                                                                                     |
-| Lat        | Latitude in degrees of event location.                                                                             |
-| Lon        | Longitude in degrees of event location.                                                                            |
-| Depth      | Depth in km of event.                                                                                              |
-| Mag        | Magnitude of event.                                                                                                |
-| [N] MP     | Number of manual picks.                                                                                            |
-| [N] AP     | Number of automatic picks.                                                                                         |
-| Tuning Set | Select whether this event is a Tuning event. See [Automatic Picking](#automatic-picking).                          |
-| Test Set   | Select whether this event is a Test event. See [Automatic Picking](#automatic-picking).                            |
-| Notes      | Free form text field for notes regarding this event. Text will be saved in the notes.txt file in the event folder. |
-
-## Usage
-
-### Projects and Events
-
-PyLoT uses projects to categorize different seismic data. A project consists of one or multiple events. Events contain
-seismic traces from one or multiple stations. An event also contains further information, e.g. origin time, source
-parameters and automatic as well as manual picks. Projects are used to group events which should be analysed together. A
-project could contain all events from a specific region within a timeframe of interest or all recorded events of a
-seismological experiment.
-
-### Event folder structure
-
-PyLoT expects the following folder structure for seismic data:
-
-* Every event should be in it's own folder with the following naming scheme for the folders:
-  ``e[id].[doy].[yy]``, where ``[id]`` is a four-digit numerical id increasing from 0001, ``[doy]`` the three digit day
-  of year and ``[yy]`` the last two digits of the year of the event. This structure has to be created by the user of
-  PyLoT manually.
-* These folders should contain the seismic data for their event as ``.mseed`` or other supported filetype
-* All automatic and manual picks should be in an ``.xml`` file in their event folder. PyLoT saves picks in this file.
-  This file does not have to be added manually unless there are picks to be imported. The format used to save picks is
-  QUAKEML.   
-  Picks are saved in a file with the same filename as the event folder with ``PyLoT_`` prepended.
-* The file ``notes.txt`` is used for saving analysts comments. Everything saved here will be displayed in the 'Notes'
-  column of the eventlist.
-
-### Loading event information from CSV file
-
-Event information can be saved in a ``.csv`` file located in the rootpath. The file is made from one header line, which
-is followed by one or multiple data lines. Values are separated by comma, while a dot is used as a decimal separator.   
-This information is then shown in the table in the [Eventlist tab](#Eventlist).
-
-One example header and data line is shown below.
-```event,Date,Time,Magnitude,Lat,Long,Depth,Region,Basis Lat,Basis Long,Distance [km],Distance [rad],Distance [deg]```   
-```e0001.024.16,24/01/16,10:30:30,7.1,59.66,-153.45,128,Southern Alaska,46.62,10.26,8104.65,1.27,72.89,7.1```
-
-The meaning of the header entries is:
-
-| Header               | description                                                                                    |
-|----------------------|------------------------------------------------------------------------------------------------|
-| event                | Event id, has to be the same as the folder name in which waveform data for this event is kept. |
-| Data                 | Origin date of the event, format DD/MM/YY or DD/MM/YYYY.                                       |
-| Time                 | Origin time of the event. Format HH:MM:SS.                                                     |
-| Lat, Long            | Origin latitude and longitude in decimal degrees.                                              |
-| Region               | Flinn-Engdahl region name.                                                                     |
-| Basis Lat, Basis Lon | Latitude and longitude of the basis of the station network in decimal degrees.                 |
-| Distance [km]        | Distance from origin coordinates to basis coordinates in km.                                   |
-| Distance [rad]       | Distance from origin coordinates to basis coordinates in rad.                                  |
-
-### Adding events to project
-
-PyLoT GUI starts with an empty project. To add events, use the add event data button. Select one or multiple folders
-containing events.
-
-[//]: <> (TODO: explain _Directories: Root path, Data path, Database path_)
-
-### Saving projects
-
-Save the current project from the menu with File->Save project or File->Save project as. PyLoT uses ``.plp`` files to
-save project information. This file format is not interchangeable between different versions of Python interpreters.
-Saved projects contain the automatic and manual picks. Seismic trace data is not included into the ``.plp`` file, but
-read from its location used when saving the file.
-
-### Adding metadata
-
-[//]: <> (TODO: Add picture of metadata "manager" when it is done)
-
-PyLoT can handle ``.dless``, ``.xml``, ``.resp`` and ``.dseed`` file formats for Metadata. Metadata files stored on disk
-can be added to a project by clicking *Edit*->*Manage Inventories*. This opens up a window where the folders which
-contain metadata files can be selected. PyLoT will then search these files for the station names when it needs the
-information.
-
-# Picking
-
-PyLoTs automatic and manual pick determination works as following:
-
-* Using certain parameters, a first initial/coarse pick is determined. The first manual pick is determined by visual
-  review of the whole waveform and selection of the most likely onset by the analyst. The first automatic pick is
-  determined by calculation of a characteristic function (CF) for the seismic trace. When a wave arrives, the CFs
-  properties change, which is determined as the signals onset.
-* Afterwards, a refined set of parameters is applied to a small part of the waveform around the initial onset. For
-  manual picks this means a closer view of the trace, for automatic picks this is done by a recalculated CF with
-  different parameters.
-* This second picking phase results in the precise pick, which is treated as the onset time.
-
-## Manual Picking
-
-To create manual picks, you will need to open or create a project that contains seismic trace data (
-see [Adding events to projects](#adding-events-to-project)). Click on a trace to open
-the [Picking window](#picking-window).
-
-### Picking window
-
-Open the picking window of a station by leftclicking on any trace in the waveform plot. Here you can create manual picks
-for the selected station.
-
-<img src="images/gui/picking/pickwindow.png" alt="Picking window">
-
-*Picking window of a station.*
-
-#### Picking Window Settings
-
-| Icon                                                                             | Shortcut       | Menu Alternative            | Description                                                                                                                                                                                                         |
-|----------------------------------------------------------------------------------|----------------|-----------------------------|---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
-| <img src="../icons/filter_p.png" alt="Filter P" width="64" height="64">          | p              | Filter->Apply P Filter      | Filter all channels according to the options specified in Filter parameter, P Filter section.                                                                                                                       |
-| <img src="../icons/filter_s.png" alt="Filter S" width="64" height="64">          | s              | Filter->Apply S Filter      | Filter all channels according to the options specified in Filter parameter, S Filter section.                                                                                                                       |
-| <img src="../icons/key_A.png" alt="Filter Automatically" width="64" height="64"> | Ctrl + a       | Filter->Automatic Filtering | If enabled, automatically select the correct filter option (P, S) depending on the selected phase to be picked.                                                                                                     |
-| ![desc](images/gui/picking/phase_selection.png "Phase selection")                | 1 (P) or 5 (S) | Picks->P or S               | Select phase to pick. If Automatic Filtering is enabled, this will apply the appropriate filter depending on the phase.                                                                                             |
-| ![Zoom into](../icons/zoom_in.png "Zoom into waveform")                          | -              | -                           | Zoom into waveform.                                                                                                                                                                                                 |
-| ![Reset zoom](../icons/zoom_0.png "Reset zoom")                                  | -              | -                           | Reset zoom to default view.                                                                                                                                                                                         |
-| ![Delete picks](../icons/delete.png "Delete picks")                              | -              | -                           | Delete all manual picks on this station.                                                                                                                                                                            |
-| ![Rename a phase](../icons/sync.png "Rename a phase")                            | -              | -                           | Click this button and then the picked phase to rename it.                                                                                                                                                           |
-| ![Continue](images/gui/picking/continue.png "Continue with next station")        | -              | -                           | If checked, after accepting the manual picks for this station with 'OK', the picking window for the next station will be opened. This option is useful for fast manual picking of a complete event.                 |
-| Estimated onsets                                                                 | -              | -                           | Show the theoretical onsets for this station. Needs metadata and origin information.                                                                                                                                |
-| Compare to channel                                                               | -              | -                           | Select a data channel to compare against. The selected channel will be displayed in the picking window behind every channel allowing the analyst to visually compare signal correlation between different channels. |
-| Scaling                                                                          | -              | -                           | Individual means every channel is scaled to its own maximum. If a channel is selected here, all channels will be scaled relatively to this channel.                                                                 |
-
-| Menu Command              | Shortcut | Description                                                                                                                                                                                                                                                                 |
-|---------------------------|----------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
-| P Channels and S Channels | -        | Select which channels should be treated as P or S channels during picking. When picking a phase, only the corresponding channels will be shown during the precise pick. Normally, the Z channel should be selected for the P phase and the N and E channel for the S phase. |
-
-### Filtering
-
-Access the Filter options by pressing Ctrl+f on the Waveform plot or by the menu under *Edit*->*Filter Parameter*.
-
-<img src=images/gui/pylot-filter-options.png>
-
-Here you are able to select filter type, order and frequencies for the P and S pick separately. These settings are used
-in the GUI for displaying the filtered waveform data and during manual picking. The values used by PyLoT for automatic
-picking are displayed next to the manual values. They can be changed in the [Tune Autopicker dialog](#tuning).  
-A green value automatic value means the automatic and manual filter parameter is configured the same, red means they are
-configured differently. By toggling the "Overwrite filteroptions" checkmark you can set whether the manual
-precise/second pick uses the filter settings for the automatic picker (unchecked) or whether it uses the filter options
-in this dialog (checked). To guarantee consistent picking results between automatic and manual picking it is recommended
-to use the same filter settings for the determination of automatic and manual picks.
-
-### Export and Import of manual picks
-
-#### Export
-
-After the creation of manual picks they can either be saved in the project file (
-see [Saving projects](#saving-projects)). Alternatively the picks can be exported by pressing
-the <img src="../icons/savepicks.png" alt="Save event information button" title="Save picks button" height=24 width=24>
-button above the waveform plot or in the menu File->Save event information (shortcut Ctrl+p). Select the event directory
-in which to save the file. The filename will be ``PyLoT_[event_folder_name].[filetype selected during first startup]``
-.     
-You can rename and copy this file, but PyLoT will then no longer be able to automatically recognize the correct picks
-for an event and the file will have to be manually selected when loading.
-
-#### Import
-
-To import previously saved picks press
-the <img src="../icons/openpick.png" alt="Load event information button" width="24" height="24"> button and select the
-file to load. You will be asked to save the current state of your project if you have not done so before. You can
-continue without saving by pressing "Discard". This does not delete any information from your project, it just means
-that no project file is saved before the changes of importing picks are applied. PyLoT will automatically load files
-named after the scheme it uses when saving picks, described in the paragraph above. If it can't find any matching files,
-a file dialogue will open and you can select the file you wish to load.
-
-If you see a warning "Mismatch in event identifiers" and are asked whether to continue loading the picks, this means
-that PyLoT doesn't recognize the picks in the file as belonging to this specific event. They could have either been
-saved under a different installation of PyLoT but with the same waveform data, which means they are still compatible and
-you can continue loading them. Or they could be picks from a different event, in which case loading them is not
-recommended.
-
-## Automatic Picking
-
-The general workflow for automatic picking is as following:
-
-- After setting up the project by loading waveforms and optionally metadata, the right parameters for the autopicker
-  have to be determined
-- This [tuning](#tuning) is done for single stations with immediate graphical feedback of all picking results
-- Afterwards the autopicker can be run for all or a subset of events from the project
-
-For automatic picking PyLoT discerns between tune and test events, which the user has to set as such. Tune events are
-used to calibrate the autopicking algorithm, test events are then used to test the calibration. The purpose of that is
-controlling whether the parameters found during tuning are able to reliably pick the "unknown" test events.  
-If this behaviour is not desired and all events should be handled the same, dont mark any events. Since this is just a
-way to group events to compare the picking results, nothing else will change.
-
-### Tuning
-
-Tuning describes the process of adjusting the autopicker settings to the characteristics of your data set. To do this in
-PyLoT, use the <img src=../icons/tune.png height=24 alt="Tune autopicks button" title="Tune autopicks button"> button to
-open the Tune Autopicker.
-
-<img src=images/gui/tuning/tune_autopicker.png>
-
-View of a station in the Tune Autopicker window.
-
-1. Select the event to be displayed and processed.
-2. Select the station from the event.
-3. To pick the currently displayed trace, click
-   the <img src=images/gui/tuning/autopick_trace_button.png alt="Pick trace button" title="Autopick trace button" height=16>
-   button.
-4. These tabs are used to select the current view. __Traces Plot__ contains a plot of the stations traces, where manual
-   picks can be created/edited. __Overview__ contains graphical results of the automatic picking process. The __P and S
-   tabs__ contain the automatic picking results of the P and S phase, while __log__ contains a useful text output of
-   automatic picking.
-5. These buttons are used to load/save/reset settings for automatic picking. The parameters can be saved in PyLoT input
-   files, which have the file ending *.in*. They are human readable text files, which can also be edited by hand. Saving
-   the parameters allows you to load them again later, even on different machines.
-6. These menus control the behaviour of the creation of manual picks from the Tune Autopicker window. Picks allows to
-   select the phase for which a manual pick should be created, Filter allows to filter waveforms and edit the filter
-   parameters. P-Channels and S-Channels allow to select the channels that should be displayed when creating a manual P
-   or S pick.
-7. This menu is the same as in the [Picking Window](#picking-window-settings), with the exception of the __Manual
-   Onsets__ options. The __Manual Onsets__ buttons accepts or reject the manual picks created in the Tune Autopicker
-   window, pressing accept adds them to the manual picks for the event, while reject removes them.
-8. The traces plot in the centre allows creating manual picks and viewing the waveforms.
-9. The parameters which influence the autopicking result are in the Main settings and Advanced settings tabs on the left
-   side. For a description of all the parameters see the [tuning documentation](tuning.md).
-
-### Production run of the autopicker
-
-After the settings used during tuning give the desired results, the autopicker can be used on the complete dataset. To
-invoke the autopicker on the whole set of events, click
-the <img src=../icons/autopylot_button.png alt="Autopick" title="Autopick" height=32> button.
-
-### Evaluation of automatic picks
-
-PyLoT has two internal consistency checks for automatic picks that were determined for an event:
-
-1. Jackknife check
-2. Wadati check
-
-#### 1. Jackknife check
-
-The jackknife test in PyLoT checks the consistency of automatically determined P-picks by checking the statistical
-variance of the picks. The variance of all P-picks is calculated and compared to the variance of subsets, in which one
-pick is removed.   
-The idea is, that picks that are close together in time should not influence the estimation of the variance much, while
-picks whose positions deviates from the norm influence the variance to a greater extent. If the estimated variance of a
-subset with a pick removed differs to much from the estimated variance of all picks, the pick that was removed from the
-subset will be marked as invalid.   
-The factor by which picks are allowed to skew from the estimation of variance can be configured, it is called *
-jackfactor*, see [here](tuning.md#Pick-quality-control).
-
-Additionally, the deviation of picks from the median is checked. For that, the median of all P-picks that passed the
-Jackknife test is calculated. Picks whose onset times deviate from the mean onset time by more than the *mdttolerance*
-are marked as invalid.
-
-<img src=images/gui/jackknife_plot.png title="Jackknife/Median test diagram">
-
-*The result of both tests (Jackknife and Median) is shown in a diagram afterwards. The onset time is plotted against a
-running number of stations. Picks that failed either the Jackknife or the median test are colored red. The median is
-plotted as a green line.*
-
-The Jackknife and median check are suitable to check for picks that are outside of the expected time window, for
-example, when a wrong phase was picked. It won't recognize picks that are in close proximity to the right onset which
-are just slightly to late/early.
-
-#### 2. Wadati check
-
-The Wadati check checks the consistency of S picks. For this the SP-time, the time difference between S and P onset is
-plotted against the P onset time. A line is fitted to the points, which minimizes the error. Then the deviation of
-single picks to this line is checked. If the deviation in seconds is above the *wdttolerance*
-parameter ([see here](tuning.md#Pick-quality-control)), the pick is marked as invalid.
-
-<img src=images/gui/wadati_plot.png title="Output diagram of Wadati check">
-
-*The Wadati plot in PyLoT shows the SP onset time difference over the P onset time. A first line is fitted (black). All
-picks which deviate to much from this line are marked invalid (red). Then a second line is fitted which excludes the
-invalid picks. From this lines slope, the ratio of P and S wave velocity is determined.*
-
-### Comparison between automatic and manual picks
-
-Every pick in PyLoT consists of an earliest possible, latest possible and most likely onset time. The earliest and
-latest possible onset time characterize the uncertainty of a pick. This approach is described in Diel, Kissling and
-Bormann (2012) - Tutorial for consistent phase picking at local to regional distances. These times are represented as a
-Probability Density Function (PDF) for every pick. The PDF is implemented as two exponential distributions around the
-most likely onset as the expected value.
-
-To compare two single picks, their PDFs are cross correlated to create a new PDF. This corresponds to the subtraction of
-the automatic pick from the manual pick.
-
- <img src=images/gui/comparison/comparison_pdf.png title="Comparison between automatic and manual pick">
-
-*Comparison between an automatic and a manual pick for a station in PyLoT by comparing their PDFs.*  
-*The upper plot shows the difference between the two single picks that are shown in the lower plot.*
-*The difference is implemented as a cross correlation between the two PDFs. and results in a new PDF, the comparison
-PDF.*
-*The expected value of the comparison PDF corresponds to the time distance between the automatic and manual picks most
-likely onset.*
-*The standard deviation corresponds to the combined uncertainty.*
-
-To compare the automatic and manual picks between multiple stations of an event, the properties of all the comparison
-PDFs are shown in a histogram.
-
-<img src=images/gui/comparison/compare_widget.png title="Comparison between picks of an event">
-
-*Comparison between the automatic and manual picks for an event in PyLoT.*   
-*The top left plot shows the standard deviation of the comparison PDFs for P picks.*
-*The bottom left plot shows the expected values of the comparison PDFs for P picks.*
-*The top right plot shows the standard deviation of the comparison PDFs for S picks.*
-*The bottom right plot shows the expected values of the comparison PDFs for S picks.*   
-*The standard deviation plots show that most P picks have an uncertainty between 1 and 2 seconds, while S pick
-uncertainties have a much larger spread between 1 to 15 seconds.*
-*This means P picks have higher quality classes on average than S picks.*
-*The expected values are largely negative, meaning that the algorithm tends to pick earlier than the analyst with the
-applied settings (Manual - Automatic).*
-*The number of samples mentioned in the plots legends is the amount of stations that have an automatic and a manual P
-pick.*
-
-### Export and Import of automatic picks
-
-Picks can be saved in *.xml* format.
-
-# Location determination
-
-To be added.
-
-# FAQ
-
-Q: During manual picking the error "No channel to plot for phase ..." is displayed, and I am unable to create a pick.  
-A: Select a channel that should be used for the corresponding phase in the Pickwindow. For further information
-read [Picking Window settings](#picking-window-settings).
-
-Q: I see a warning "Mismatch in event identifiers" when loading picks from a file.  
-A: This means that PyLoT doesn't recognize the picks in the file as belonging to this specific event. They could have
-been saved under a different installation of PyLoT but with the same waveform data, which means they are still
-compatible and you can continue loading them or they could be the picks of a different event, in which case loading them
-is not recommended.

docs/tuning.md

@@ -1,150 +0,0 @@
-# AutoPyLoT Tuning
-
-A description of the parameters used for determining automatic picks.
-
-## Filter parameters and cut times
-
-Parameters applied to the traces before picking algorithm starts.
-
-| Name                | Description                                                                                                                                                                                                             |
-|---------------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
-| *P Start*, *P
-Stop* | Define time interval relative to trace start time for CF calculation on vertical trace. Value is relative to theoretical onset time if 'Use TauPy' option is enabled in main settings of 'Tune Autopicker' dialogue.    |
-| *S Start*, *S
-Stop* | Define time interval relative to trace start time for CF calculation on horizontal traces. Value is relative to theoretical onset time if 'Use TauPy' option is enabled in main settings of 'Tune Autopicker' dialogue. |
-| *Bandpass
-Z1*       | Filter settings for Butterworth bandpass applied to vertical trace for calculation of initial P pick.                                                                                                                   |
-| *Bandpass
-Z2*       | Filter settings for Butterworth bandpass applied to vertical trace for calculation of precise P pick.                                                                                                                   |
-| *Bandpass
-H1*       | Filter settings for Butterworth bandpass applied to horizontal traces for calculation of initial S pick.                                                                                                                |
-| *Bandpass
-H2*       | Filter settings for Butterworth bandpass applied to horizontal traces for calculation of precise S pick.                                                                                                                |
-
-## Inital P pick
-
-Parameters used for determination of initial P pick.
-
-| Name         | Description                                                                                                                  |
-|--------------|------------------------------------------------------------------------------------------------------------------------------|
-| *
-tLTA*       | Size of gliding LTA window in seconds used for calculation of HOS-CF.                                                        |
-| *pickwin
-P*  | Size of time window in seconds in which the minimum of the AIC-CF in front of the maximum of the HOS-CF is determined.       |
-| *
-AICtsmooth* | Average of samples in this time window will be used for smoothing of the AIC-CF.                                             |
-| *
-checkwinP*  | Time in front of the global maximum of the HOS-CF in which to search for a second local extrema.                             |
-| *minfactorP* | Used with *
-checkwinP*. If a second local maximum is found, it has to be at least as big as the first maximum * *minfactorP*. |
-| *
-tsignal*    | Time window in seconds after the initial P pick used for determining signal amplitude.                                       |
-| *
-tnoise*     | Time window in seconds in front of initial P pick used for determining noise amplitude.                                      |
-| *tsafetey*   | Time in seconds between *tsignal* and *
-tnoise*.                                                                              |
-| *
-tslope*     | Time window in seconds after initial P pick in which the slope of the onset is calculated.                                   |
-
-## Inital S pick
-
-Parameters used for determination of initial S pick
-
-| Name          | Description                                                                                                                  |
-|---------------|------------------------------------------------------------------------------------------------------------------------------|
-| *
-tdet1h*      | Length of time window in seconds in which AR params of the waveform are determined.                                          |
-| *
-tpred1h*     | Length of time window in seconds in which the waveform is predicted using the AR model.                                      |
-| *
-AICtsmoothS* | Average of samples in this time window is used for smoothing the AIC-CF.                                                     |
-| *
-pickwinS*    | Time window in which the minimum in the AIC-CF in front of the maximum in the ARH-CF is determined.                          |
-| *
-checkwinS*   | Time in front of the global maximum of the ARH-CF in which to search for a second local extrema.                             |
-| *minfactorP*  | Used with *
-checkwinS*. If a second local maximum is found, it has to be at least as big as the first maximum * *minfactorS*. |
-| *
-tsignal*     | Time window in seconds after the initial P pick used for determining signal amplitude.                                       |
-| *
-tnoise*      | Time window in seconds in front of initial P pick used for determining noise amplitude.                                      |
-| *tsafetey*    | Time in seconds between *tsignal* and *
-tnoise*.                                                                              |
-| *
-tslope*      | Time window in seconds after initial P pick in which the slope of the onset is calculated.                                   |
-
-## Precise P pick
-
-Parameters used for determination of precise P pick.
-
-| Name         | Description                                                                                                                                                                                                             |
-|--------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
-| *Precalcwin* | Time window in seconds for recalculation of the HOS-CF. The new CF will be two times the size of *
-Precalcwin*, since it will be calculated from the initial pick to +/- *Precalcwin*.                                   |
-| *
-tsmoothP*   | Average of samples in this time window will be used for smoothing the second HOS-CF.                                                                                                                                    |
-| *
-ausP*       | Controls artificial uplift of samples during precise picking. A common local minimum of the smoothed and unsmoothed HOS-CF is found when the previous sample is larger or equal to the current sample times (1+*
-ausP*). |
-
-## Precise S pick
-
-Parameters used for determination of precise S pick.
-
-| Name         | Description                                                                                                                                                                                                             |
-|--------------|-------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
-| *
-tdet2h*     | Time window for determination of AR coefficients.                                                                                                                                                                       |
-| *
-tpred2h*    | Time window in which the waveform is predicted using the determined AR parameters.                                                                                                                                      |
-| *Srecalcwin* | Time window for recalculation of ARH-CF. New CF will be calculated from initial pick +/- *
-Srecalcwin*.                                                                                                                  |
-| *
-tsmoothS*   | Average of samples in this time window will be used for smoothing the second ARH-CF.                                                                                                                                    |
-| *
-ausS*       | Controls artificial uplift of samples during precise picking. A common local minimum of the smoothed and unsmoothed ARH-CF is found when the previous sample is larger or equal to the current sample times (1+*
-ausS*). |
-| *
-pickwinS*   | Time window around initial pick in which to look for a precise pick.                                                                                                                                                    |
-
-## Pick quality control
-
-Parameters used for checking quality and integrity of automatic picks.
-
-| Name                                       | Description                                                                                                                                                                                                                                                                    |
-|--------------------------------------------|--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
-| *
-minAICPslope*                             | Initial P picks with a slope lower than this value will be discared.                                                                                                                                                                                                           |
-| *
-minAICPSNR*                               | Initial P picks with a SNR below this value will be discarded.                                                                                                                                                                                                                 |
-| *
-minAICSslope*                             | Initial S picks with a slope lower than this value will be discarded.                                                                                                                                                                                                          |
-| *
-minAICSSNR*                               | Initial S picks with a SNR below this value will be discarded.                                                                                                                                                                                                                 |
-| *minsiglength*, *noisefacor*. *minpercent* | Parameters for checking signal length. In the time window of size *
-minsiglength* after the initial P pick *
-minpercent* of samples have to be larger than the RMS value.                                                                                                        |
-| *
-zfac*                                     | To recognize misattributed S picks, the RMS amplitude of vertical and horizontal traces are compared. The RMS amplitude of the vertical traces has to be at least *
-zfac* higher than the RMS amplitude on the horizontal traces for the pick to be accepted as a valid P pick. |
-| *
-jackfactor*                               | A P pick is removed if the jackknife pseudo value of the variance of his subgroup is larger than the variance of all picks multiplied with the *
-jackfactor*.                                                                                                                   |
-| *
-mdttolerance*                             | Maximum allowed deviation of P onset times from the median. Value in seconds.                                                                                                                                                                                                  |
-| *
-wdttolerance*                             | Maximum allowed deviation of S onset times from the line during the Wadati test. Value in seconds.                                                                                                                                                                             |
-
-## Pick quality determination
-
-Parameters for discrete quality classes.
-
-| Name             | Description                                                                                                                                                                                                           |
-|------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|
-| *
-timeerrorsP*    | Width of the time windows in seconds between earliest and latest possible pick which represent the quality classes 0, 1, 2, 3 for P onsets.                                                                           |
-| *
-timeerrorsS*    | Width of the time windows in seconds between earliest and latest possible pick which represent the quality classes 0, 1, 2, 3 for S onsets.                                                                           |
-| *nfacP*, *nfacS* | For determination of latest possible onset time. The time when the signal reaches an amplitude of *
-nfac* * mean value of the RMS amplitude in the time window *tnoise* corresponds to the latest possible onset time. |
-

help/index.html

@@ -1,19 +1,17 @@
-<html>
+<html><head><title>PyLoT - the Python picking and Localisation Tool</title></head>
-<head><title>PyLoT - the Python picking and Localisation Tool</title></head>
 <body>
 <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">
-    <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>
 <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
-    <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>
+</body></html>
-</html>

icons.qrc

@@ -2,40 +2,10 @@
     <qresource>
         <file>icons/pylot.ico</file>
         <file>icons/pylot.png</file>
-        <file>icons/back.png</file>
+        <file>icons/locate.png</file>
-        <file>icons/home.png</file>
-        <file>icons/newfile.png</file>
-        <file>icons/open.png</file>
-        <file>icons/openproject.png</file>
-        <file>icons/add.png</file>
-        <file>icons/save.png</file>
-        <file>icons/saveas.png</file>
-        <file>icons/saveproject.png</file>
-        <file>icons/saveprojectas.png</file>
-        <file>icons/manupicksicon_small.png</file>
-        <file>icons/autopicksicon_small.png</file>
-        <file>icons/tune.png</file>
-        <file>icons/autopylot_button.png</file>
-        <file>icons/pick.png</file>
-        <file>icons/waveform.png</file>
-        <file>icons/openpick.png</file>
-        <file>icons/openpicks.png</file>
-        <file>icons/openpick.png</file>
-        <file>icons/openpicks.png</file>
-        <file>icons/savepicks.png</file>
-        <file>icons/preferences.png</file>
-        <file>icons/parameter.png</file>
-        <file>icons/inventory.png</file>
-        <file>icons/map.png</file>
-        <file>icons/openloc.png</file>
-        <file>icons/compare_button.png</file>
-        <file>icons/pick_qualities_button.png</file>
-        <file>icons/eventlist_xml_button.png</file>
-        <file>icons/locate_button.png</file>
-        <file>icons/Matlab_PILOT_icon.png</file>
         <file>icons/printer.png</file>
         <file>icons/delete.png</file>
-        <file>icons/key_A.png</file>
+        <file>icons/compare.png</file>
         <file>icons/key_E.png</file>
         <file>icons/key_N.png</file>
         <file>icons/key_P.png</file>
@@ -48,8 +18,6 @@
         <file>icons/key_W.png</file>
         <file>icons/key_Z.png</file>
         <file>icons/filter.png</file>
-        <file>icons/filter_p.png</file>
-        <file>icons/filter_s.png</file>
         <file>icons/sync.png</file>
         <file>icons/zoom_0.png</file>
         <file>icons/zoom_in.png</file>

inputs/autoPyLoT.in

@@ -0,0 +1,100 @@
+%This is a parameter input file for autoPyLoT.
+%All main and special settings regarding data handling
+%and picking are to be set here!
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+#main settings#
+/DATA/Insheim                       #rootpath#     %project path
+EVENT_DATA/LOCAL		    #datapath#     %data path
+2013.02_Insheim                     #database#     %name of data base
+e0019.048.13                        #eventID#      %certain evnt ID for processing
+True                                #apverbose#
+PILOT				    #datastructure#  %choose data structure
+0                                   #iplot#        %flag for plotting: 0 none, 1, partly, >1 everything
+AUTOPHASES_AIC_HOS4_ARH             #phasefile#    %name of autoPILOT output phase file 
+AUTOLOC_AIC_HOS4_ARH                #locfile#      %name of autoPILOT output location file 
+AUTOFOCMEC_AIC_HOS4_ARH.in          #focmecin#     %name of focmec input file containing polarities
+HYPOSAT                             #locrt#        %location routine used ("HYPOINVERSE" or "HYPOSAT")
+6                                   #pmin#         %minimum required P picks for location
+4                                   #p0min#        %minimum required P picks for location if at least
+                                                   %3 excellent P picks are found
+2                                   #smin#         %minimum required S picks for location
+/home/ludger/bin/run_HYPOSAT4autoPILOT.csh #cshellp# %path and name of c-shell script to run location routine
+7.6 8.5                             #blon#         %longitude bounding for location map
+49 49.4                             #blat#         %lattitude bounding for location map
+#parameters for moment magnitude estimation#
+5000                                #vp#           %average P-wave velocity
+2800                                #vs#           %average S-wave velocity
+2200                                #rho#          %rock density [kg/m^3]
+300                                 #Qp#           %quality factor for P waves
+100                                 #Qs#           %quality factor for S waves
+#common settings picker#
+15                                  #pstart#       %start time [s] for calculating CF for P-picking
+40                                  #pstop#        %end time [s] for calculating CF for P-picking
+-1.0                                #sstart#       %start time [s] after or before(-) P-onset for calculating CF for S-picking
+7                                   #sstop#        %end time [s] after P-onset for calculating CF for S-picking
+2 20                                #bpz1#         %lower/upper corner freq. of first band pass filter Z-comp. [Hz]
+2 30                                #bpz2#         %lower/upper corner freq. of second band pass filter Z-comp. [Hz]
+2 15                                #bph1#         %lower/upper corner freq. of first band pass filter H-comp. [Hz]
+2 20                                #bph2#         %lower/upper corner freq. of second band pass filter z-comp. [Hz]
+#special settings for calculating CF#
+%!!Be careful when editing the following!!
+#Z-component#
+HOS                                 #algoP#        %choose algorithm for P-onset determination (HOS, ARZ, or AR3)
+7                                   #tlta#         %for HOS-/AR-AIC-picker, length of LTA window [s] 
+4                                   #hosorder#     %for HOS-picker, order of Higher Order Statistics
+2                                   #Parorder#     %for AR-picker, order of AR process of Z-component
+1.2                                 #tdet1z#       %for AR-picker, length of AR determination window [s] for Z-component, 1st pick
+0.4                                 #tpred1z#      %for AR-picker, length of AR prediction window [s] for Z-component, 1st pick
+0.6                                 #tdet2z#       %for AR-picker, length of AR determination window [s] for Z-component, 2nd pick
+0.2                                 #tpred2z#      %for AR-picker, length of AR prediction window [s] for Z-component, 2nd pick
+0.001                               #addnoise#     %add noise to seismogram for stable AR prediction
+3 0.1 0.5 0.1                       #tsnrz#        %for HOS/AR, window lengths for SNR-and slope estimation [tnoise,tsafetey,tsignal,tslope] [s]
+3                                   #pickwinP#     %for initial AIC pick, length of P-pick window [s]
+8                                   #Precalcwin#   %for HOS/AR, window length [s] for recalculation of CF (relative to 1st pick)
+0                                   #peps4aic#     %for HOS/AR, artificial uplift of samples of AIC-function (P)
+0.2                                 #aictsmooth#   %for HOS/AR, take average of samples for smoothing of AIC-function [s]
+0.1                                 #tsmoothP#     %for HOS/AR, take average of samples for smoothing CF [s]
+0.001                               #ausP#         %for HOS/AR, artificial uplift of samples (aus) of CF (P)
+1.3                                 #nfacP#        %for HOS/AR, noise factor for noise level determination (P)
+#H-components#
+ARH                                 #algoS#        %choose algorithm for S-onset determination (ARH or AR3)
+0.8                                 #tdet1h#       %for HOS/AR, length of AR-determination window [s], H-components, 1st pick
+0.4                                 #tpred1h#      %for HOS/AR, length of AR-prediction window [s], H-components, 1st pick
+0.6                                 #tdet2h#       %for HOS/AR, length of AR-determinaton window [s], H-components, 2nd pick
+0.3                                 #tpred2h#      %for HOS/AR, length of AR-prediction window [s], H-components, 2nd pick
+4                                   #Sarorder#     %for AR-picker, order of AR process of H-components
+6                                   #Srecalcwin#   %for AR-picker, window length [s] for recalculation of CF (2nd pick) (H)
+3                                   #pickwinS#     %for initial AIC pick, length of S-pick window [s]
+2 0.2 1.5 0.5                       #tsnrh#        %for ARH/AR3, window lengths for SNR-and slope estimation [tnoise,tsafetey,tsignal,tslope] [s]
+0.05                                #aictsmoothS#  %for AIC-picker, take average of samples for smoothing of AIC-function [s]
+0.02                                #tsmoothS#     %for AR-picker, take average of samples for smoothing CF [s] (S)
+0.2                                 #pepsS#        %for AR-picker, artificial uplift of samples of CF (S) 
+0.4                                 #ausS#         %for HOS/AR, artificial uplift of samples (aus) of CF (S)
+1.5                                 #nfacS#        %for AR-picker, noise factor for noise level determination (S)
+%first-motion picker%
+1                                   #minfmweight#  %minimum required p weight for first-motion determination
+2                                   #minFMSNR#     %miniumum required SNR for first-motion determination
+0.2                                 #fmpickwin#    %pick window around P onset for calculating zero crossings
+%quality assessment%
+#inital AIC onset#
+0.01 0.02 0.04 0.08                 #timeerrorsP#   %discrete time errors [s] corresponding to picking weights [0 1 2 3] for P
+0.04 0.08 0.16 0.32                 #timeerrorsS#   %discrete time errors [s] corresponding to picking weights [0 1 2 3] for S
+80                                  #minAICPslope#  %below this slope [counts/s] the initial P pick is rejected
+1.2                                 #minAICPSNR#    %below this SNR the initial P pick is rejected
+50                                  #minAICSslope#  %below this slope [counts/s] the initial S pick is rejected
+1.5                                 #minAICSSNR#    %below this SNR the initial S pick is rejected
+#check duration of signal using envelope function#
+1.5                                 #prepickwin#   %pre-signal window length [s] for noise level estimation 
+0.7                                 #minsiglength# %minimum required length of signal [s]
+0.2                                 #sgap#         %safety gap between noise and signal window [s]
+2                                   #noisefactor#  %noiselevel*noisefactor=threshold
+60                                  #minpercent#   %per cent of samples required higher than threshold
+#check for spuriously picked S-onsets#
+3.0                                 #zfac#         %P-amplitude must exceed zfac times RMS-S amplitude 
+#jackknife-processing for P-picks#
+3                                   #thresholdweight#%minimum required weight of picks
+3                                   #dttolerance#  %maximum allowed deviation of P picks from median [s]
+4                                   #minstats#     %minimum number of stations with reliable P picks
+3                                   #Sdttolerance# %maximum allowed deviation from Wadati-diagram
+

inputs/autoPyLoT_local.in

@@ -0,0 +1,99 @@
+%This is a parameter input file for autoPyLoT.
+%All main and special settings regarding data handling
+%and picking are to be set here!
+%Parameters are optimized for local data sets!
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+#main settings#
+/DATA/Insheim                       #rootpath#     %project path
+EVENT_DATA/LOCAL		    #datapath#     %data path
+2016.08_Insheim                     #database#     %name of data base
+e0007.224.16                        #eventID#      %event ID for single event processing
+/DATA/Insheim/STAT_INFO             #invdir#       %full path to inventory or dataless-seed file
+PILOT				    #datastructure#%choose data structure
+0                                   #iplot#        %flag for plotting: 0 none, 1 partly, >1 everything
+True                                #apverbose#    %choose 'True' or 'False' for terminal output
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+#NLLoc settings#
+/home/ludger/NLLOC                  #nllocbin#     %path to NLLoc executable
+/home/ludger/NLLOC/Insheim          #nllocroot#    %root of NLLoc-processing directory
+AUTOPHASES.obs                      #phasefile#    %name of autoPyLoT-output phase file for NLLoc
+                                                   %(in nllocroot/obs)
+Insheim_min1d032016_auto.in         #ctrfile#      %name of autoPyLoT-output control file for NLLoc
+                                                   %(in nllocroot/run)
+ttime                               #ttpatter#     %pattern of NLLoc ttimes from grid
+                                                   %(in nllocroot/times)
+AUTOLOC_nlloc                       #outpatter#    %pattern of NLLoc-output file
+                                                   %(returns 'eventID_outpatter')
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+#parameters for seismic moment estimation#
+3530                                #vp#           %average P-wave velocity
+2500                                #rho#          %average rock density [kg/m^3]
+300 0.8                             #Qp#           %quality factor for P waves ([Qp, ap], Qp*f^a)
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+AUTOFOCMEC_AIC_HOS4_ARH.in          #focmecin#     %name of focmec input file containing derived polarities
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+#common settings picker#
+15.0                                #pstart#       %start time [s] for calculating CF for P-picking
+60.0                                #pstop#        %end time [s] for calculating CF for P-picking
+-1.0                                #sstart#       %start time [s] relative to P-onset for calculating CF for S-picking
+10.0                                #sstop#        %end time [s] after P-onset for calculating CF for S-picking
+2 20                                #bpz1#         %lower/upper corner freq. of first band pass filter Z-comp. [Hz]
+2 30                                #bpz2#         %lower/upper corner freq. of second band pass filter Z-comp. [Hz]
+2 15                                #bph1#         %lower/upper corner freq. of first band pass filter H-comp. [Hz]
+2 20                                #bph2#         %lower/upper corner freq. of second band pass filter z-comp. [Hz]
+#special settings for calculating CF#
+%!!Edit the following only if you know what you are doing!!%
+#Z-component#
+HOS                                 #algoP#        %choose algorithm for P-onset determination (HOS, ARZ, or AR3)
+7.0                                 #tlta#         %for HOS-/AR-AIC-picker, length of LTA window [s] 
+4                                   #hosorder#     %for HOS-picker, order of Higher Order Statistics
+2                                   #Parorder#     %for AR-picker, order of AR process of Z-component
+1.2                                 #tdet1z#       %for AR-picker, length of AR determination window [s] for Z-component, 1st pick
+0.4                                 #tpred1z#      %for AR-picker, length of AR prediction window [s] for Z-component, 1st pick
+0.6                                 #tdet2z#       %for AR-picker, length of AR determination window [s] for Z-component, 2nd pick
+0.2                                 #tpred2z#      %for AR-picker, length of AR prediction window [s] for Z-component, 2nd pick
+0.001                               #addnoise#     %add noise to seismogram for stable AR prediction
+3 0.1 0.5 0.5                       #tsnrz#        %for HOS/AR, window lengths for SNR-and slope estimation [tnoise,tsafetey,tsignal,tslope] [s]
+3.0                                 #pickwinP#     %for initial AIC pick, length of P-pick window [s]
+6.0                                 #Precalcwin#   %for HOS/AR, window length [s] for recalculation of CF (relative to 1st pick)
+0.2                                 #aictsmooth#   %for HOS/AR, take average of samples for smoothing of AIC-function [s]
+0.1                                 #tsmoothP#     %for HOS/AR, take average of samples for smoothing CF [s]
+0.001                               #ausP#         %for HOS/AR, artificial uplift of samples (aus) of CF (P)
+1.3                                 #nfacP#        %for HOS/AR, noise factor for noise level determination (P)
+#H-components#
+ARH                                 #algoS#        %choose algorithm for S-onset determination (ARH or AR3)
+0.8                                 #tdet1h#       %for HOS/AR, length of AR-determination window [s], H-components, 1st pick
+0.4                                 #tpred1h#      %for HOS/AR, length of AR-prediction window [s], H-components, 1st pick
+0.6                                 #tdet2h#       %for HOS/AR, length of AR-determinaton window [s], H-components, 2nd pick
+0.3                                 #tpred2h#      %for HOS/AR, length of AR-prediction window [s], H-components, 2nd pick
+4                                   #Sarorder#     %for AR-picker, order of AR process of H-components
+5.0                                 #Srecalcwin#   %for AR-picker, window length [s] for recalculation of CF (2nd pick) (H)
+3.0                                 #pickwinS#     %for initial AIC pick, length of S-pick window [s]
+2 0.2 1.5 0.5                       #tsnrh#        %for ARH/AR3, window lengths for SNR-and slope estimation [tnoise,tsafetey,tsignal,tslope] [s]
+0.5                                 #aictsmoothS#  %for AIC-picker, take average of samples for smoothing of AIC-function [s]
+0.7                                 #tsmoothS#     %for AR-picker, take average of samples for smoothing CF [s] (S)
+0.9                                 #ausS#         %for HOS/AR, artificial uplift of samples (aus) of CF (S)
+1.5                                 #nfacS#        %for AR-picker, noise factor for noise level determination (S)
+%first-motion picker%
+1                                   #minfmweight#  %minimum required P weight for first-motion determination
+2                                   #minFMSNR#     %miniumum required SNR for first-motion determination
+0.2                                 #fmpickwin#    %pick window around P onset for calculating zero crossings
+%quality assessment%
+#inital AIC onset#
+0.01 0.02 0.04 0.08                 #timeerrorsP#   %discrete time errors [s] corresponding to picking weights [0 1 2 3] for P
+0.04 0.08 0.16 0.32                 #timeerrorsS#   %discrete time errors [s] corresponding to picking weights [0 1 2 3] for S
+4                                   #minAICPslope#  %below this slope [counts/s] the initial P pick is rejected
+1.2                                 #minAICPSNR#    %below this SNR the initial P pick is rejected
+2                                   #minAICSslope#  %below this slope [counts/s] the initial S pick is rejected
+1.5                                 #minAICSSNR#    %below this SNR the initial S pick is rejected
+#check duration of signal using envelope function#
+3                                   #minsiglength# %minimum required length of signal [s]
+1.0                                 #noisefactor#  %noiselevel*noisefactor=threshold
+40                                  #minpercent#   %required percentage of samples higher than threshold
+#check for spuriously picked S-onsets#
+2.0                                 #zfac#         %P-amplitude must exceed at least zfac times RMS-S amplitude 
+#check statistics of P onsets#
+2.5                                 #mdttolerance#  %maximum allowed deviation of P picks from median [s]
+#wadati check#
+1.0                                 #wdttolerance# %maximum allowed deviation from Wadati-diagram
+

inputs/autoPyLoT_regional.in

@@ -0,0 +1,100 @@
+%This is a parameter input file for autoPyLoT.
+%All main and special settings regarding data handling
+%and picking are to be set here!
+%Parameters are optimized for regional data sets!
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+
+#main settings#
+/DATA/Egelados                      #rootpath#     %project path
+EVENT_DATA/LOCAL		    #datapath#     %data path
+2006.01_Nisyros                     #database#     %name of data base
+e1412.008.06                        #eventID#      %event ID for single event processing
+/DATA/Egelados/STAT_INFO            #invdir#       %full path to inventory or dataless-seed file
+PILOT				    #datastructure#  %choose data structure
+0                                   #iplot#        %flag for plotting: 0 none, 1, partly, >1 everything
+True                                #apverbose#    %choose 'True' or 'False' for terminal output
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+#NLLoc settings#
+/home/ludger/NLLOC                  #nllocbin#     %path to NLLoc executable
+/home/ludger/NLLOC/Insheim          #nllocroot#    %root of NLLoc-processing directory
+AUTOPHASES.obs                      #phasefile#    %name of autoPyLoT-output phase file for NLLoc
+                                                   %(in nllocroot/obs)
+Insheim_min1d2015_auto.in           #ctrfile#      %name of autoPyLoT-output control file for NLLoc
+                                                   %(in nllocroot/run)
+ttime                               #ttpatter#     %pattern of NLLoc ttimes from grid
+                                                   %(in nllocroot/times)
+AUTOLOC_nlloc                       #outpatter#    %pattern of NLLoc-output file
+                                                   %(returns 'eventID_outpatter')
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+#parameters for seismic moment estimation#
+3530                                #vp#           %average P-wave velocity
+2700                                #rho#          %average rock density [kg/m^3]
+1000f**0.8                          #Qp#           %quality factor for P waves (Qp*f^a)
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+AUTOFOCMEC_AIC_HOS4_ARH.in          #focmecin#     %name of focmec input file containing derived polarities
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+#common settings picker#
+20                                  #pstart#       %start time [s] for calculating CF for P-picking
+100                                 #pstop#        %end time [s] for calculating CF for P-picking
+1.0                                 #sstart#       %start time [s] after or before(-) P-onset for calculating CF for S-picking
+100                                 #sstop#        %end time [s] after P-onset for calculating CF for S-picking
+3 10                                #bpz1#         %lower/upper corner freq. of first band pass filter Z-comp. [Hz]
+3 12                                #bpz2#         %lower/upper corner freq. of second band pass filter Z-comp. [Hz]
+3 8                                 #bph1#         %lower/upper corner freq. of first band pass filter H-comp. [Hz]
+3 6                                 #bph2#         %lower/upper corner freq. of second band pass filter H-comp. [Hz]
+#special settings for calculating CF#
+%!!Be careful when editing the following!!
+#Z-component#
+HOS                                 #algoP#        %choose algorithm for P-onset determination (HOS, ARZ, or AR3)
+7                                   #tlta#         %for HOS-/AR-AIC-picker, length of LTA window [s] 
+4                                   #hosorder#     %for HOS-picker, order of Higher Order Statistics
+2                                   #Parorder#     %for AR-picker, order of AR process of Z-component
+1.2                                 #tdet1z#       %for AR-picker, length of AR determination window [s] for Z-component, 1st pick
+0.4                                 #tpred1z#      %for AR-picker, length of AR prediction window [s] for Z-component, 1st pick
+0.6                                 #tdet2z#       %for AR-picker, length of AR determination window [s] for Z-component, 2nd pick
+0.2                                 #tpred2z#      %for AR-picker, length of AR prediction window [s] for Z-component, 2nd pick
+0.001                               #addnoise#     %add noise to seismogram for stable AR prediction
+5 0.2 3.0 1.5                       #tsnrz#        %for HOS/AR, window lengths for SNR-and slope estimation [tnoise,tsafetey,tsignal,tslope] [s]
+3                                   #pickwinP#     %for initial AIC and refined pick, length of P-pick window [s]
+8                                   #Precalcwin#   %for HOS/AR, window length [s] for recalculation of CF (relative to 1st pick)
+1.0                                 #aictsmooth#   %for HOS/AR, take average of samples for smoothing of AIC-function [s]
+0.3                                 #tsmoothP#     %for HOS/AR, take average of samples for smoothing CF [s]
+0.3                                 #ausP#         %for HOS/AR, artificial uplift of samples (aus) of CF (P)
+1.3                                 #nfacP#        %for HOS/AR, noise factor for noise level determination (P)
+#H-components#
+ARH                                 #algoS#        %choose algorithm for S-onset determination (ARH or AR3)
+0.8                                 #tdet1h#       %for HOS/AR, length of AR-determination window [s], H-components, 1st pick
+0.4                                 #tpred1h#      %for HOS/AR, length of AR-prediction window [s], H-components, 1st pick
+0.6                                 #tdet2h#       %for HOS/AR, length of AR-determinaton window [s], H-components, 2nd pick
+0.3                                 #tpred2h#      %for HOS/AR, length of AR-prediction window [s], H-components, 2nd pick
+4                                   #Sarorder#     %for AR-picker, order of AR process of H-components
+10                                  #Srecalcwin#   %for AR-picker, window length [s] for recalculation of CF (2nd pick) (H)
+25                                  #pickwinS#     %for initial AIC and refined pick, length of S-pick window [s]
+5 0.2 3.0 3.0                       #tsnrh#        %for ARH/AR3, window lengths for SNR-and slope estimation [tnoise,tsafetey,tsignal,tslope] [s]
+3.5                                 #aictsmoothS#  %for AIC-picker, take average of samples for smoothing of AIC-function [s]
+1.0                                 #tsmoothS#     %for AR-picker, take average of samples for smoothing CF [s] (S)
+0.2                                 #ausS#         %for HOS/AR, artificial uplift of samples (aus) of CF (S)
+1.5                                 #nfacS#        %for AR-picker, noise factor for noise level determination (S)
+%first-motion picker%
+1                                   #minfmweight#  %minimum required p weight for first-motion determination
+2                                   #minFMSNR#     %miniumum required SNR for first-motion determination
+6.0                                 #fmpickwin#    %pick window around P onset for calculating zero crossings
+%quality assessment%
+#inital AIC onset#
+0.04 0.08 0.16 0.32                 #timeerrorsP#   %discrete time errors [s] corresponding to picking weights [0 1 2 3] for P
+0.04 0.08 0.16 0.32                 #timeerrorsS#   %discrete time errors [s] corresponding to picking weights [0 1 2 3] for S
+3                                   #minAICPslope#  %below this slope [counts/s] the initial P pick is rejected
+1.2                                 #minAICPSNR#    %below this SNR the initial P pick is rejected
+5                                   #minAICSslope#  %below this slope [counts/s] the initial S pick is rejected
+2.5                                 #minAICSSNR#    %below this SNR the initial S pick is rejected
+#check duration of signal using envelope function#
+30                                  #minsiglength# %minimum required length of signal [s]
+2.5                                 #noisefactor#  %noiselevel*noisefactor=threshold
+60                                  #minpercent#   %required percentage of samples higher than threshold
+#check for spuriously picked S-onsets#
+0.5                                 #zfac#         %P-amplitude must exceed at least zfac times RMS-S amplitude 
+#check statistics of P onsets#
+45                                  #mdttolerance#  %maximum allowed deviation of P picks from median [s]
+#wadati check#
+3.0                                 #wdttolerance# %maximum allowed deviation from Wadati-diagram
+

inputs/filter.in

@@ -0,0 +1,2 @@
+P bandpass 4 2.0 20.0
+S bandpass 4 2.0 15.0

inputs/pylot.in

@@ -0,0 +1,98 @@
+%This is a example parameter input file for PyLoT.
+%All main and special settings regarding data handling
+%and picking are to be set here!
+%Parameters shown here are optimized for local data sets!
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+#main settings#
+/data/Geothermie/Insheim            #rootpath#      %project path
+EVENT_DATA/LOCAL                    #datapath#      %data path
+2013.02_Insheim                     #database#      %name of data base
+e0019.048.13                        #eventID#       %event ID for single event processing
+/data/Geothermie/Insheim/STAT_INFO  #invdir#        %full path to  inventory or dataless-seed file
+PILOT                               #datastructure# %choose data structure
+0                                   #iplot#         %flag for plotting: 0 none, 1 partly, >1 everything
+True                                #apverbose#     %choose 'True' or 'False' for terminal output
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+#NLLoc settings#
+/progs/bin                          #nllocbin#      %path to NLLoc executable
+/data/Geothermie/Insheim/LOCALISATION/NLLoc          #nllocroot#     %root of NLLoc-processing directory
+AUTOPHASES.obs                      #phasefile#     %name of autoPyLoT-output phase file for NLLoc
+                                                    %(in nllocroot/obs)
+Insheim_min1d2015.in           #ctrfile#       %name of PyLoT-output control file for NLLoc
+                                                    %(in nllocroot/run)
+ttime                               #ttpatter#      %pattern of NLLoc ttimes from grid
+                                                    %(in nllocroot/times)
+AUTOLOC_nlloc                       #outpatter#     %pattern of NLLoc-output file
+                                                    %(returns 'eventID_outpatter')
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+#parameters for seismic moment estimation#
+3530                                #vp#            %average P-wave velocity
+2500                                #rho#           %average rock density [kg/m^3]
+300 0.8                           #Qp#            %quality factor for P waves (Qp*f^a); list(Qp, a)
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+AUTOFOCMEC_AIC_HOS4_ARH.in          #focmecin#      %name of focmec input file containing derived polarities
+%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
+#common settings picker#
+15.0                                #pstart#        %start time [s] for calculating CF for P-picking
+60.0                                #pstop#         %end time [s] for calculating CF for P-picking
+-1.0                                #sstart#        %start time [s] relative to P-onset for calculating CF for S-picking
+10.0                                #sstop#         %end time [s] after P-onset for calculating CF for S-picking
+2 20                                #bpz1#          %lower/upper corner freq. of first band pass filter Z-comp. [Hz]
+2 30                                #bpz2#          %lower/upper corner freq. of second band pass filter Z-comp. [Hz]
+2 15                                #bph1#          %lower/upper corner freq. of first band pass filter H-comp. [Hz]
+2 20                                #bph2#          %lower/upper corner freq. of second band pass filter z-comp. [Hz]
+#special settings for calculating CF#
+%!!Edit the following only if you know what you are doing!!%
+#Z-component#
+HOS                                 #algoP#         %choose algorithm for P-onset determination (HOS, ARZ, or AR3)
+7.0                                 #tlta#          %for HOS-/AR-AIC-picker, length of LTA window [s]
+4                                   #hosorder#      %for HOS-picker, order of Higher Order Statistics
+2                                   #Parorder#      %for AR-picker, order of AR process of Z-component
+1.2                                 #tdet1z#        %for AR-picker, length of AR determination window [s] for Z-component, 1st pick
+0.4                                 #tpred1z#       %for AR-picker, length of AR prediction window [s] for Z-component, 1st pick
+0.6                                 #tdet2z#        %for AR-picker, length of AR determination window [s] for Z-component, 2nd pick
+0.2                                 #tpred2z#       %for AR-picker, length of AR prediction window [s] for Z-component, 2nd pick
+0.001                               #addnoise#      %add noise to seismogram for stable AR prediction
+3 0.1 0.5 0.5                       #tsnrz#         %for HOS/AR, window lengths for SNR-and slope estimation [tnoise,tsafetey,tsignal,tslope] [s]
+3.0                                 #pickwinP#      %for initial AIC pick, length of P-pick window [s]
+6.0                                 #Precalcwin#    %for HOS/AR, window length [s] for recalculation of CF (relative to 1st pick)
+0.2                                 #aictsmooth#    %for HOS/AR, take average of samples for smoothing of AIC-function [s]
+0.1                                 #tsmoothP#      %for HOS/AR, take average of samples for smoothing CF [s]
+0.001                               #ausP#          %for HOS/AR, artificial uplift of samples (aus) of CF (P)
+1.3                                 #nfacP#         %for HOS/AR, noise factor for noise level determination (P)
+#H-components#
+ARH                                 #algoS#         %choose algorithm for S-onset determination (ARH or AR3)
+0.8                                 #tdet1h#        %for HOS/AR, length of AR-determination window [s], H-components, 1st pick
+0.4                                 #tpred1h#       %for HOS/AR, length of AR-prediction window [s], H-components, 1st pick
+0.6                                 #tdet2h#        %for HOS/AR, length of AR-determinaton window [s], H-components, 2nd pick
+0.3                                 #tpred2h#       %for HOS/AR, length of AR-prediction window [s], H-components, 2nd pick
+4                                   #Sarorder#      %for AR-picker, order of AR process of H-components
+5.0                                 #Srecalcwin#    %for AR-picker, window length [s] for recalculation of CF (2nd pick) (H)
+3.0                                 #pickwinS#      %for initial AIC pick, length of S-pick window [s]
+2 0.2 1.5 0.5                       #tsnrh#         %for ARH/AR3, window lengths for SNR-and slope estimation [tnoise,tsafetey,tsignal,tslope] [s]
+0.5                                 #aictsmoothS#   %for AIC-picker, take average of samples for smoothing of AIC-function [s]
+0.7                                 #tsmoothS#      %for AR-picker, take average of samples for smoothing CF [s] (S)
+0.9                                 #ausS#          %for HOS/AR, artificial uplift of samples (aus) of CF (S)
+1.5                                 #nfacS#         %for AR-picker, noise factor for noise level determination (S)
+%first-motion picker%
+1                                   #minfmweight#   %minimum required P weight for first-motion determination
+2                                   #minFMSNR#      %miniumum required SNR for first-motion determination
+0.2                                 #fmpickwin#     %pick window around P onset for calculating zero crossings
+%quality assessment%
+#inital AIC onset#
+0.01 0.02 0.04 0.08                 #timeerrorsP#   %discrete time errors [s] corresponding to picking weights [0 1 2 3] for P
+0.04 0.08 0.16 0.32                 #timeerrorsS#   %discrete time errors [s] corresponding to picking weights [0 1 2 3] for S
+4                                   #minAICPslope#  %below this slope [counts/s] the initial P pick is rejected
+1.2                                 #minAICPSNR#    %below this SNR the initial P pick is rejected
+2                                   #minAICSslope#  %below this slope [counts/s] the initial S pick is rejected
+1.5                                 #minAICSSNR#    %below this SNR the initial S pick is rejected
+#check duration of signal using envelope function#
+3                                   #minsiglength#  %minimum required length of signal [s]
+1.0                                 #noisefactor#   %noiselevel*noisefactor=threshold
+40                                  #minpercent#    %required percentage of samples higher than threshold
+#check for spuriously picked S-onsets#
+2.0                                 #zfac#          %P-amplitude must exceed at least zfac times RMS-S amplitude
+#check statistics of P onsets#
+2.5                                 #mdttolerance#  %maximum allowed deviation of P picks from median [s]
+#wadati check#
+1.0                                 #wdttolerance#  %maximum allowed deviation from Wadati-diagram

inputs/pylot_global.in

@@ -1,100 +0,0 @@
-%This is a parameter input file for PyLoT/autoPyLoT.
-%All main and special settings regarding data handling
-%and picking are to be set here!
-%Parameters are optimized for %extent data sets!
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-#main settings#
-                                                   #rootpath#       %project path                                                                                        
-                                                   #datapath#       %data path                                                                                           
-                                                   #database#       %name of data base                                                                                   
-                                                   #eventID#        %event ID for single event processing (* for all events found in database)                           
-                                                   #invdir#         %full path to  inventory or dataless-seed file                                                       
-PILOT                                              #datastructure#  %choose data structure                                                                               
-True                                               #apverbose#      %choose 'True' or 'False' for terminal output                                                        
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-#NLLoc settings#
-None                                               #nllocbin#       %path to NLLoc executable                                                                            
-None                                               #nllocroot#      %root of NLLoc-processing directory                                                                  
-None                                               #phasefile#      %name of autoPyLoT-output phase file for NLLoc                                                       
-None                                               #ctrfile#        %name of autoPyLoT-output control file for NLLoc                                                     
-ttime                                              #ttpatter#       %pattern of NLLoc ttimes from grid                                                                   
-AUTOLOC_nlloc                                      #outpatter#      %pattern of NLLoc-output file                                                                        
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-#parameters for seismic moment estimation#
-3530.0                                             #vp#             %average P-wave velocity                                                                             
-2500.0                                             #rho#            %average rock density [kg/m^3]                                                                       
-300.0 0.8                                          #Qp#             %quality factor for P waves (Qp*f^a); list(Qp, a)                                                    
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-#settings local magnitude#
-1.0 1.0 1.0                                        #WAscaling#      %Scaling relation (log(Ao)+Alog(r)+Br+C) of Wood-Anderson amplitude Ao [nm]                           If zeros are set, original Richter magnitude is calculated!
-1.0 1.0                                            #magscaling#     %Scaling relation for derived local magnitude [a*Ml+b].                            If zeros are set, no scaling of network magnitude is applied!
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-#filter settings#
-0.01 0.01                                          #minfreq#        %Lower filter frequency [P, S]                                                                       
-0.3 0.3                                            #maxfreq#        %Upper filter frequency [P, S]                                                                       
-3 3                                                #filter_order#   %filter order [P, S]                                                                                 
-bandpass bandpass                                  #filter_type#    %filter type (bandpass, bandstop, lowpass, highpass) [P, S]                                          
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-#common settings picker#
-global                                             #extent#         %extent of array ("local", "regional" or "global")                                                   
--150.0                                             #pstart#         %start time [s] for calculating CF for P-picking (if TauPy: seconds relative to estimated onset)     
-600.0                                              #pstop#          %end time [s] for calculating CF for P-picking (if TauPy: seconds relative to estimated onset)       
-200.0                                              #sstart#         %start time [s] relative to P-onset for calculating CF for S-picking                                 
-1150.0                                             #sstop#          %end time [s] after P-onset for calculating CF for S-picking                                         
-True                                               #use_taup#       %use estimated traveltimes from TauPy for calculating windows for CF                                 
-iasp91                                             #taup_model#     %define TauPy model for traveltime estimation. Possible values: 1066a, 1066b, ak135, ak135f, herrin, iasp91, jb, prem, pwdk, sp6
-0.05 0.5                                           #bpz1#           %lower/upper corner freq. of first band pass filter Z-comp. [Hz]                                     
-0.001 0.5                                          #bpz2#           %lower/upper corner freq. of second band pass filter Z-comp. [Hz]                                    
-0.05 0.5                                           #bph1#           %lower/upper corner freq. of first band pass filter H-comp. [Hz]                                     
-0.001 0.5                                          #bph2#           %lower/upper corner freq. of second band pass filter z-comp. [Hz]                                    
-#special settings for calculating CF#
-%!!Edit the following only if you know what you are doing!!%
-#Z-component#
-HOS                                                #algoP#          %choose algorithm for P-onset determination (HOS, ARZ, or AR3)                                       
-150.0                                              #tlta#           %for HOS-/AR-AIC-picker, length of LTA window [s]                                                    
-4                                                  #hosorder#       %for HOS-picker, order of Higher Order Statistics                                                    
-2                                                  #Parorder#       %for AR-picker, order of AR process of Z-component                                                   
-16.0                                               #tdet1z#         %for AR-picker, length of AR determination window [s] for Z-component, 1st pick                      
-10.0                                               #tpred1z#        %for AR-picker, length of AR prediction window [s] for Z-component, 1st pick                         
-12.0                                               #tdet2z#         %for AR-picker, length of AR determination window [s] for Z-component, 2nd pick                      
-6.0                                                #tpred2z#        %for AR-picker, length of AR prediction window [s] for Z-component, 2nd pick                         
-0.001                                              #addnoise#       %add noise to seismogram for stable AR prediction                                                    
-60.0 10.0 40.0 10.0                                #tsnrz#          %for HOS/AR, window lengths for SNR-and slope estimation [tnoise, tsafetey, tsignal, tslope] [s]     
-150.0                                              #pickwinP#       %for initial AIC pick, length of P-pick window [s]                                                   
-35.0                                               #Precalcwin#     %for HOS/AR, window length [s] for recalculation of CF (relative to 1st pick)                        
-6.0                                                #aictsmooth#     %for HOS/AR, take average of samples for smoothing of AIC-function [s]                               
-4.0                                                #tsmoothP#       %for HOS/AR, take average of samples for smoothing CF [s]                                            
-0.001                                              #ausP#           %for HOS/AR, artificial uplift of samples (aus) of CF (P)                                            
-1.1                                                #nfacP#          %for HOS/AR, noise factor for noise level determination (P)                                          
-#H-components#
-ARH                                                #algoS#          %choose algorithm for S-onset determination (ARH or AR3)                                             
-12.0                                               #tdet1h#         %for HOS/AR, length of AR-determination window [s], H-components, 1st pick                           
-6.0                                                #tpred1h#        %for HOS/AR, length of AR-prediction window [s], H-components, 1st pick                              
-8.0                                                #tdet2h#         %for HOS/AR, length of AR-determinaton window [s], H-components, 2nd pick                            
-4.0                                                #tpred2h#        %for HOS/AR, length of AR-prediction window [s], H-components, 2nd pick                              
-4                                                  #Sarorder#       %for AR-picker, order of AR process of H-components                                                  
-30.0                                               #Srecalcwin#     %for AR-picker, window length [s] for recalculation of CF (2nd pick) (H)                             
-195.0                                              #pickwinS#       %for initial AIC pick, length of S-pick window [s]                                                   
-100.0 10.0 45.0 10.0                               #tsnrh#          %for ARH/AR3, window lengths for SNR-and slope estimation [tnoise, tsafetey, tsignal, tslope] [s]    
-22.0                                               #aictsmoothS#    %for AIC-picker, take average of samples for smoothing of AIC-function [s]                           
-10.0                                               #tsmoothS#       %for AR-picker, take average of samples for smoothing CF [s] (S)                                     
-0.001                                              #ausS#           %for HOS/AR, artificial uplift of samples (aus) of CF (S)                                            
-1.2                                                #nfacS#          %for AR-picker, noise factor for noise level determination (S)                                       
-#first-motion picker#
-1                                                  #minfmweight#    %minimum required P weight for first-motion determination                                            
-3.0                                                #minFMSNR#       %miniumum required SNR for first-motion determination                                                
-10.0                                               #fmpickwin#      %pick window around P onset for calculating zero crossings                                           
-#quality assessment#
-1.0 2.0 4.0 8.0                                    #timeerrorsP#    %discrete time errors [s] corresponding to picking weights [0 1 2 3] for P                           
-4.0 8.0 16.0 32.0                                  #timeerrorsS#    %discrete time errors [s] corresponding to picking weights [0 1 2 3] for S                           
-0.5                                                #minAICPslope#   %below this slope [counts/s] the initial P pick is rejected                                          
-1.1                                                #minAICPSNR#     %below this SNR the initial P pick is rejected                                                       
-1.0                                                #minAICSslope#   %below this slope [counts/s] the initial S pick is rejected                                          
-1.3                                                #minAICSSNR#     %below this SNR the initial S pick is rejected                                                       
-5.0                                                #minsiglength#   %length of signal part for which amplitudes must exceed noiselevel [s]                               
-1.0                                                #noisefactor#    %noiselevel*noisefactor=threshold                                                                    
-10.0                                               #minpercent#     %required percentage of amplitudes exceeding threshold                                               
-1.2                                                #zfac#           %P-amplitude must exceed at least zfac times RMS-S amplitude                                         
-25.0                                               #mdttolerance#   %maximum allowed deviation of P picks from median [s]                                                
-50.0                                               #wdttolerance#   %maximum allowed deviation from Wadati-diagram                                                       
-5.0                                                #jackfactor#     %pick is removed if the variance of the subgroup with the pick removed is larger than the mean variance of all subgroups times safety factor

inputs/pylot_local.in

@@ -1,100 +0,0 @@
-%This is a parameter input file for PyLoT/autoPyLoT.
-%All main and special settings regarding data handling
-%and picking are to be set here!
-%Parameters are optimized for %extent data sets!
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-#main settings#
-/DATA/Insheim                                      #rootpath#       %project path                                                                                        
-EVENT_DATA/LOCAL                                   #datapath#       %data path                                                                                           
-2018.02_Insheim                                    #database#       %name of data base                                                                                   
-e0006.038.18                                       #eventID#        %event ID for single event processing (* for all events found in database)                           
-/DATA/Insheim/STAT_INFO                            #invdir#         %full path to  inventory or dataless-seed file                                                       
-PILOT                                              #datastructure#  %choose data structure                                                                               
-True                                               #apverbose#      %choose 'True' or 'False' for terminal output                                                        
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-#NLLoc settings#
-/home/ludger/NLLOC                                 #nllocbin#       %path to NLLoc executable                                                                            
-/home/ludger/NLLOC/Insheim                         #nllocroot#      %root of NLLoc-processing directory                                                                  
-AUTOPHASES.obs                                     #phasefile#      %name of autoPyLoT-output phase file for NLLoc                                                       
-Insheim_min1d032016_auto.in                        #ctrfile#        %name of autoPyLoT-output control file for NLLoc                                                     
-ttime                                              #ttpatter#       %pattern of NLLoc ttimes from grid                                                                   
-AUTOLOC_nlloc                                      #outpatter#      %pattern of NLLoc-output file                                                                        
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-#parameters for seismic moment estimation#
-3530.0                                             #vp#             %average P-wave velocity                                                                             
-2500.0                                             #rho#            %average rock density [kg/m^3]                                                                       
-300.0 0.8                                          #Qp#             %quality factor for P waves (Qp*f^a); list(Qp, a)                                                    
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-#settings local magnitude#
-1.11 0.0009 -2.0                                   #WAscaling#      %Scaling relation (log(Ao)+Alog(r)+Br+C) of Wood-Anderson amplitude Ao [nm]                           If zeros are set, original Richter magnitude is calculated!
-0.0 0.0                                            #magscaling#     %Scaling relation for derived local magnitude [a*Ml+b].                            If zeros are set, no scaling of network magnitude is applied!
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-#filter settings#
-2.0 2.0                                            #minfreq#        %Lower filter frequency [P, S]                                                                       
-30.0 15.0                                          #maxfreq#        %Upper filter frequency [P, S]                                                                       
-3 3                                                #filter_order#   %filter order [P, S]                                                                                 
-bandpass bandpass                                  #filter_type#    %filter type (bandpass, bandstop, lowpass, highpass) [P, S]                                          
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-#common settings picker#
-local                                              #extent#         %extent of array ("local", "regional" or "global")                                                   
-7.0                                                #pstart#         %start time [s] for calculating CF for P-picking                                                     
-16.0                                               #pstop#          %end time [s] for calculating CF for P-picking                                                       
--0.5                                               #sstart#         %start time [s] relative to P-onset for calculating CF for S-picking                                 
-10.0                                               #sstop#          %end time [s] after P-onset for calculating CF for S-picking                                         
-False                                              #use_taup#       %use estimated traveltimes from TauPy for calculating windows for CF                                 
-iasp91                                             #taup_model#     %define TauPy model for traveltime estimation                                                        
-2.0 20.0                                           #bpz1#           %lower/upper corner freq. of first band pass filter Z-comp. [Hz]                                     
-2.0 30.0                                           #bpz2#           %lower/upper corner freq. of second band pass filter Z-comp. [Hz]                                    
-2.0 10.0                                           #bph1#           %lower/upper corner freq. of first band pass filter H-comp. [Hz]                                     
-2.0 15.0                                           #bph2#           %lower/upper corner freq. of second band pass filter z-comp. [Hz]                                    
-#special settings for calculating CF#
-%!!Edit the following only if you know what you are doing!!%
-#Z-component#
-HOS                                                #algoP#          %choose algorithm for P-onset determination (HOS, ARZ, or AR3)                                       
-4.0                                                #tlta#           %for HOS-/AR-AIC-picker, length of LTA window [s]                                                    
-4                                                  #hosorder#       %for HOS-picker, order of Higher Order Statistics                                                    
-2                                                  #Parorder#       %for AR-picker, order of AR process of Z-component                                                   
-1.2                                                #tdet1z#         %for AR-picker, length of AR determination window [s] for Z-component, 1st pick                      
-0.4                                                #tpred1z#        %for AR-picker, length of AR prediction window [s] for Z-component, 1st pick                         
-0.6                                                #tdet2z#         %for AR-picker, length of AR determination window [s] for Z-component, 2nd pick                      
-0.2                                                #tpred2z#        %for AR-picker, length of AR prediction window [s] for Z-component, 2nd pick                         
-0.001                                              #addnoise#       %add noise to seismogram for stable AR prediction                                                    
-3.0 0.0 1.0 0.5                                    #tsnrz#          %for HOS/AR, window lengths for SNR-and slope estimation [tnoise, tsafetey, tsignal, tslope] [s]     
-3.0                                                #pickwinP#       %for initial AIC pick, length of P-pick window [s]                                                   
-6.0                                                #Precalcwin#     %for HOS/AR, window length [s] for recalculation of CF (relative to 1st pick)                        
-0.4                                                #aictsmooth#     %for HOS/AR, take average of samples for smoothing of AIC-function [s]                               
-0.1                                                #tsmoothP#       %for HOS/AR, take average of samples for smoothing CF [s]                                            
-0.4                                                #ausP#           %for HOS/AR, artificial uplift of samples (aus) of CF (P)                                            
-1.3                                                #nfacP#          %for HOS/AR, noise factor for noise level determination (P)                                          
-#H-components#
-ARH                                                #algoS#          %choose algorithm for S-onset determination (ARH or AR3)                                             
-0.8                                                #tdet1h#         %for HOS/AR, length of AR-determination window [s], H-components, 1st pick                           
-0.4                                                #tpred1h#        %for HOS/AR, length of AR-prediction window [s], H-components, 1st pick                              
-0.6                                                #tdet2h#         %for HOS/AR, length of AR-determinaton window [s], H-components, 2nd pick                            
-0.3                                                #tpred2h#        %for HOS/AR, length of AR-prediction window [s], H-components, 2nd pick                              
-4                                                  #Sarorder#       %for AR-picker, order of AR process of H-components                                                  
-5.0                                                #Srecalcwin#     %for AR-picker, window length [s] for recalculation of CF (2nd pick) (H)                             
-4.0                                                #pickwinS#       %for initial AIC pick, length of S-pick window [s]                                                   
-2.0 0.2 1.5 1.0                                    #tsnrh#          %for ARH/AR3, window lengths for SNR-and slope estimation [tnoise, tsafetey, tsignal, tslope] [s]    
-1.0                                                #aictsmoothS#    %for AIC-picker, take average of samples for smoothing of AIC-function [s]                           
-0.7                                                #tsmoothS#       %for AR-picker, take average of samples for smoothing CF [s] (S)                                     
-0.9                                                #ausS#           %for HOS/AR, artificial uplift of samples (aus) of CF (S)                                            
-1.5                                                #nfacS#          %for AR-picker, noise factor for noise level determination (S)                                       
-#first-motion picker#
-1                                                  #minfmweight#    %minimum required P weight for first-motion determination                                            
-2.0                                                #minFMSNR#       %miniumum required SNR for first-motion determination                                                
-0.2                                                #fmpickwin#      %pick window around P onset for calculating zero crossings                                           
-#quality assessment#
-0.04 0.08 0.16 0.32                                #timeerrorsP#    %discrete time errors [s] corresponding to picking weights [0 1 2 3] for P                           
-0.05 0.10 0.20 0.40                                #timeerrorsS#    %discrete time errors [s] corresponding to picking weights [0 1 2 3] for S                           
-0.8                                                #minAICPslope#   %below this slope [counts/s] the initial P pick is rejected                                          
-1.1                                                #minAICPSNR#     %below this SNR the initial P pick is rejected                                                       
-1.0                                                #minAICSslope#   %below this slope [counts/s] the initial S pick is rejected                                          
-1.5                                                #minAICSSNR#     %below this SNR the initial S pick is rejected                                                       
-1.0                                                #minsiglength#   %length of signal part for which amplitudes must exceed noiselevel [s]                               
-1.1                                                #noisefactor#    %noiselevel*noisefactor=threshold                                                                    
-50.0                                               #minpercent#     %required percentage of amplitudes exceeding threshold                                               
-1.1                                                #zfac#           %P-amplitude must exceed at least zfac times RMS-S amplitude                                         
-5.0                                                #mdttolerance#   %maximum allowed deviation of P picks from median [s]                                                
-1.0                                                #wdttolerance#   %maximum allowed deviation from Wadati-diagram                                                       
-2.0                                                #jackfactor#     %pick is removed if the variance of the subgroup with the pick removed is larger than the mean variance of all subgroups times safety factor

inputs/pylot_regional.in

@@ -1,100 +0,0 @@
-%This is a parameter input file for PyLoT/autoPyLoT.
-%All main and special settings regarding data handling
-%and picking are to be set here!
-%Parameters are optimized for %extent data sets!
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-#main settings#
-                                                   #rootpath#       %project path                                                                                        
-                                                   #datapath#       %data path                                                                                           
-                                                   #database#       %name of data base                                                                                   
-                                                   #eventID#        %event ID for single event processing (* for all events found in database)                           
-                                                   #invdir#         %full path to  inventory or dataless-seed file                                                       
-PILOT                                              #datastructure#  %choose data structure                                                                               
-True                                               #apverbose#      %choose 'True' or 'False' for terminal output                                                        
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-#NLLoc settings#
-None                                               #nllocbin#       %path to NLLoc executable                                                                            
-None                                               #nllocroot#      %root of NLLoc-processing directory                                                                  
-None                                               #phasefile#      %name of autoPyLoT-output phase file for NLLoc                                                       
-None                                               #ctrfile#        %name of autoPyLoT-output control file for NLLoc                                                     
-ttime                                              #ttpatter#       %pattern of NLLoc ttimes from grid                                                                   
-AUTOLOC_nlloc                                      #outpatter#      %pattern of NLLoc-output file                                                                        
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-#parameters for seismic moment estimation#
-3530.0                                             #vp#             %average P-wave velocity                                                                             
-2500.0                                             #rho#            %average rock density [kg/m^3]                                                                       
-300.0 0.8                                          #Qp#             %quality factor for P waves (Qp*f^a); list(Qp, a)                                                    
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-#settings local magnitude#
-1.11 0.0009 -2.0                                   #WAscaling#      %Scaling relation (log(Ao)+Alog(r)+Br+C) of Wood-Anderson amplitude Ao [nm]                           If zeros are set, original Richter magnitude is calculated!
-1.0382 -0.447                                      #magscaling#     %Scaling relation for derived local magnitude [a*Ml+b].                            If zeros are set, no scaling of network magnitude is applied!
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-#filter settings#
-1.0 1.0                                            #minfreq#        %Lower filter frequency [P, S]                                                                       
-10.0 10.0                                          #maxfreq#        %Upper filter frequency [P, S]                                                                       
-2 2                                                #filter_order#   %filter order [P, S]                                                                                 
-bandpass bandpass                                  #filter_type#    %filter type (bandpass, bandstop, lowpass, highpass) [P, S]                                          
-%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
-#common settings picker#
-local                                              #extent#         %extent of array ("local", "regional" or "global")                                                   
-15.0                                               #pstart#         %start time [s] for calculating CF for P-picking                                                     
-60.0                                               #pstop#          %end time [s] for calculating CF for P-picking                                                       
--1.0                                               #sstart#         %start time [s] relative to P-onset for calculating CF for S-picking                                 
-10.0                                               #sstop#          %end time [s] after P-onset for calculating CF for S-picking                                         
-True                                               #use_taup#       %use estimated traveltimes from TauPy for calculating windows for CF                                 
-iasp91                                             #taup_model#     %define TauPy model for traveltime estimation                                                        
-2.0 10.0                                           #bpz1#           %lower/upper corner freq. of first band pass filter Z-comp. [Hz]                                     
-2.0 12.0                                           #bpz2#           %lower/upper corner freq. of second band pass filter Z-comp. [Hz]                                    
-2.0 8.0                                            #bph1#           %lower/upper corner freq. of first band pass filter H-comp. [Hz]                                     
-2.0 10.0                                           #bph2#           %lower/upper corner freq. of second band pass filter z-comp. [Hz]                                    
-#special settings for calculating CF#
-%!!Edit the following only if you know what you are doing!!%
-#Z-component#
-HOS                                                #algoP#          %choose algorithm for P-onset determination (HOS, ARZ, or AR3)                                       
-7.0                                                #tlta#           %for HOS-/AR-AIC-picker, length of LTA window [s]                                                    
-4                                                  #hosorder#       %for HOS-picker, order of Higher Order Statistics                                                    
-2                                                  #Parorder#       %for AR-picker, order of AR process of Z-component                                                   
-1.2                                                #tdet1z#         %for AR-picker, length of AR determination window [s] for Z-component, 1st pick                      
-0.4                                                #tpred1z#        %for AR-picker, length of AR prediction window [s] for Z-component, 1st pick                         
-0.6                                                #tdet2z#         %for AR-picker, length of AR determination window [s] for Z-component, 2nd pick                      
-0.2                                                #tpred2z#        %for AR-picker, length of AR prediction window [s] for Z-component, 2nd pick                         
-0.001                                              #addnoise#       %add noise to seismogram for stable AR prediction                                                    
-3.0 0.1 0.5 1.0                                    #tsnrz#          %for HOS/AR, window lengths for SNR-and slope estimation [tnoise, tsafetey, tsignal, tslope] [s]     
-3.0                                                #pickwinP#       %for initial AIC pick, length of P-pick window [s]                                                   
-6.0                                                #Precalcwin#     %for HOS/AR, window length [s] for recalculation of CF (relative to 1st pick)                        
-0.2                                                #aictsmooth#     %for HOS/AR, take average of samples for smoothing of AIC-function [s]                               
-0.1                                                #tsmoothP#       %for HOS/AR, take average of samples for smoothing CF [s]                                            
-0.001                                              #ausP#           %for HOS/AR, artificial uplift of samples (aus) of CF (P)                                            
-1.3                                                #nfacP#          %for HOS/AR, noise factor for noise level determination (P)                                          
-#H-components#
-ARH                                                #algoS#          %choose algorithm for S-onset determination (ARH or AR3)                                             
-0.8                                                #tdet1h#         %for HOS/AR, length of AR-determination window [s], H-components, 1st pick                           
-0.4                                                #tpred1h#        %for HOS/AR, length of AR-prediction window [s], H-components, 1st pick                              
-0.6                                                #tdet2h#         %for HOS/AR, length of AR-determinaton window [s], H-components, 2nd pick                            
-0.3                                                #tpred2h#        %for HOS/AR, length of AR-prediction window [s], H-components, 2nd pick                              
-4                                                  #Sarorder#       %for AR-picker, order of AR process of H-components                                                  
-5.0                                                #Srecalcwin#     %for AR-picker, window length [s] for recalculation of CF (2nd pick) (H)                             
-4.0                                                #pickwinS#       %for initial AIC pick, length of S-pick window [s]                                                   
-2.0 0.3 1.5 1.0                                    #tsnrh#          %for ARH/AR3, window lengths for SNR-and slope estimation [tnoise, tsafetey, tsignal, tslope] [s]    
-1.0                                                #aictsmoothS#    %for AIC-picker, take average of samples for smoothing of AIC-function [s]                           
-0.7                                                #tsmoothS#       %for AR-picker, take average of samples for smoothing CF [s] (S)                                     
-0.9                                                #ausS#           %for HOS/AR, artificial uplift of samples (aus) of CF (S)                                            
-1.5                                                #nfacS#          %for AR-picker, noise factor for noise level determination (S)                                       
-#first-motion picker#
-1                                                  #minfmweight#    %minimum required P weight for first-motion determination                                            
-2.0                                                #minFMSNR#       %miniumum required SNR for first-motion determination                                                
-0.2                                                #fmpickwin#      %pick window around P onset for calculating zero crossings                                           
-#quality assessment#
-0.02 0.04 0.08 0.16                                #timeerrorsP#    %discrete time errors [s] corresponding to picking weights [0 1 2 3] for P                           
-0.04 0.08 0.16 0.32                                #timeerrorsS#    %discrete time errors [s] corresponding to picking weights [0 1 2 3] for S                           
-0.8                                                #minAICPslope#   %below this slope [counts/s] the initial P pick is rejected                                          
-1.1                                                #minAICPSNR#     %below this SNR the initial P pick is rejected                                                       
-1.0                                                #minAICSslope#   %below this slope [counts/s] the initial S pick is rejected                                          
-1.5                                                #minAICSSNR#     %below this SNR the initial S pick is rejected                                                       
-1.0                                                #minsiglength#   %length of signal part for which amplitudes must exceed noiselevel [s]                               
-1.0                                                #noisefactor#    %noiselevel*noisefactor=threshold                                                                    
-10.0                                               #minpercent#     %required percentage of amplitudes exceeding threshold                                               
-1.5                                                #zfac#           %P-amplitude must exceed at least zfac times RMS-S amplitude                                         
-6.0                                                #mdttolerance#   %maximum allowed deviation of P picks from median [s]                                                
-1.0                                                #wdttolerance#   %maximum allowed deviation from Wadati-diagram                                                       
-5.0                                                #jackfactor#     %pick is removed if the variance of the subgroup with the pick removed is larger than the mean variance of all subgroups times safety factor

makePyLoT.py

@@ -158,31 +158,24 @@ def buildPyLoT(verbosity=None):
 
 
 def installPyLoT(verbosity=None):
-    files_to_copy = {'pylot_local.in': ['~', '.pylot'],
+    files_to_copy = {'autoPyLoT_local.in':['~', '.pylot'],
-                     'pylot_regional.in': ['~', '.pylot'],
+                     'autoPyLoT_regional.in':['~', '.pylot'],
-                     'pylot_global.in': ['~', '.pylot']}
+                     'filter.in':['~', '.pylot']}
     if verbosity > 0:
-        print('starting installation of PyLoT ...')
+        print ('starting installation of PyLoT ...')
     if verbosity > 1:
-        print('copying input files into destination folder ...')
+        print ('copying input files into destination folder ...')
     ans = input('please specify scope of interest '
-                '([0]=local, 1=regional, 2=global, 3=active) :') or 0
+                '([0]=local, 1=regional) :') or 0
     if not isinstance(ans, int):
         ans = int(ans)
-    if ans == 0:
+    ans = 'local' if ans is 0 else 'regional'
-        ans = 'local'
-    elif ans == 1:
-        ans = 'regional'
-    elif ans == 2:
-        ans = 'global'
-    elif ans == 3:
-        ans = 'active'
     link_dest = []
     for file, destination in files_to_copy.items():
         link_file = ans in file
         if link_file:
             link_dest = copy.deepcopy(destination)
-            link_dest.append('pylot.in')
+            link_dest.append('autoPyLoT.in')
             link_dest = os.path.join(*link_dest)
         destination.append(file)
         destination = os.path.join(*destination)
@@ -190,7 +183,7 @@ def installPyLoT(verbosity=None):
         assert not os.path.isabs(srcfile), 'source files seem to be ' \
                                            'corrupted ...'
         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)
         if link_file:
             if verbosity:
@@ -198,6 +191,8 @@ def installPyLoT(verbosity=None):
             os.symlink(destination, link_dest)
 
 
+
+
 def cleanUp(verbosity=None):
     if verbosity >= 1:
         print('cleaning up build files...')

pylot.yml

@@ -1,14 +0,0 @@
-name: pylot_38
-channels:
-  - conda-forge
-  - defaults
-dependencies:
-  - cartopy=0.20.2
-  - matplotlib-base=3.3.4
-  - numpy=1.22.3
-  - obspy=1.3.0
-  - pyqtgraph=0.12.4
-  - pyside2>=5.13.2
-  - python=3.8.12
-  - qt>=5.12.9
-  - scipy=1.8.0

pylot/RELEASE-VERSION

@@ -0,0 +1 @@
+0.1a

pylot/core/analysis/magnitude.py

@@ -2,10 +2,10 @@
 # -*- coding: utf-8 -*-
 """
 Created autumn/winter 2015.
-Revised/extended summer 2017.
 
 :author: Ludger Küperkoch / MAGS2 EP3 working group
 """
+import os
 
 import matplotlib.pyplot as plt
 import numpy as np
@@ -20,17 +20,10 @@ from pylot.core.util.utils import common_range, fit_curve
 
 
 def richter_magnitude_scaling(delta):
-    distance = np.array([0, 10, 20, 25, 30, 35, 40, 45, 50, 60, 70, 75, 85, 90, 100, 110,
+    relation = np.loadtxt(os.path.join(os.path.expanduser('~'),
-                         120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 230, 240, 250,
+                                       '.pylot', 'richter_scaling.data'))
-                         260, 270, 280, 290, 300, 310, 320, 330, 340, 350, 360, 370, 380,
-                         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,
-                                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,
-                                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])
     # prepare spline interpolation to calculate return value
-    func, params = fit_curve(distance, richter_scaling)
+    func, params = fit_curve(relation[:, 0], relation[:, 1])
     return func(delta, params)
 
 
@@ -41,15 +34,15 @@ class Magnitude(object):
 
     def __init__(self, stream, event, verbosity=False, iplot=0):
         self._type = "M"
-        self._stream = stream
         self._plot_flag = iplot
         self._verbosity = verbosity
         self._event = event
+        self._stream = stream
         self._magnitudes = dict()
 
     def __str__(self):
         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')
         for s, m in self.magnitudes.items(): print('\t{0}\t{1}'.format(s, m))
 
@@ -118,46 +111,28 @@ class Magnitude(object):
     def calc(self):
         pass
 
-    def updated_event(self, magscaling=None):
+    def updated_event(self):
-        net_ml = self.net_magnitude(magscaling)
+        self.event.magnitudes.append(self.net_magnitude())
-        if net_ml:
-            self.event.magnitudes.append(net_ml)
         return self.event
 
-    def net_magnitude(self, magscaling=None):
+    def net_magnitude(self):
         if self:
-            if magscaling is None:
+            # TODO if an average Magnitude instead of the median is calculated
-                scaling = False
+            # StationMagnitudeContributions should be added to the returned
-            elif magscaling[0] == 0.0 and magscaling[1] == 0.0:
+            # Magnitude object
-                scaling = False
+            # mag_error => weights (magnitude error estimate from peak_to_peak, calcsourcespec?)
-            else:
+            # weights => StationMagnitdeContribution
-                scaling = True
+            mag = ope.Magnitude(
-            if scaling == True:
+                mag=np.median([M.mag for M in self.magnitudes.values()]),
-                # scaling necessary
+                magnitude_type=self.type,
-                print("Scaling network magnitude ...")
+                origin_id=self.origin_id,
-                mag = ope.Magnitude(
+                station_count=len(self.magnitudes),
-                    mag=np.median([M.mag for M in self.magnitudes.values()]) * \
+                azimuthal_gap=self.origin_id.get_referred_object().quality.azimuthal_gap)
-                        magscaling[0] + magscaling[1],
-                    magnitude_type=self.type,
-                    origin_id=self.origin_id,
-                    station_count=len(self.magnitudes),
-                    azimuthal_gap=self.origin_id.get_referred_object().quality.azimuthal_gap)
-            else:
-                # no scaling necessary
-                # Temporary fix needs rework
-                if (len(self.magnitudes.keys()) == 0):
-                    print("Error in local magnitude calculation ")
-                    return None
-                mag = ope.Magnitude(
-                    mag=np.median([M.mag for M in self.magnitudes.values()]),
-                    magnitude_type=self.type,
-                    origin_id=self.origin_id,
-                    station_count=len(self.magnitudes),
-                    azimuthal_gap=self.origin_id.get_referred_object().quality.azimuthal_gap)
             return mag
+        return None
 
 
-class LocalMagnitude(Magnitude):
+class RichterMagnitude(Magnitude):
     """
     Method to derive peak-to-peak amplitude as seen on a Wood-Anderson-
     seismograph. Has to be derived from instrument corrected traces!
@@ -174,11 +149,10 @@ class LocalMagnitude(Magnitude):
 
     _amplitudes = dict()
 
-    def __init__(self, stream, event, calc_win, wascaling, verbosity=False, iplot=0):
+    def __init__(self, stream, event, calc_win, verbosity=False, iplot=0):
-        super(LocalMagnitude, self).__init__(stream, event, verbosity, iplot)
+        super(RichterMagnitude, self).__init__(stream, event, verbosity, iplot)
 
         self._calc_win = calc_win
-        self._wascaling = wascaling
         self._type = 'ML'
         self.calc()
 
@@ -190,10 +164,6 @@ class LocalMagnitude(Magnitude):
     def calc_win(self, value):
         self._calc_win = value
 
-    @property
-    def wascaling(self):
-        return self._wascaling
-
     @property
     def amplitudes(self):
         return self._amplitudes
@@ -205,14 +175,6 @@ class LocalMagnitude(Magnitude):
 
     def peak_to_peak(self, st, t0):
 
-        try:
-            iplot = int(self.plot_flag)
-        except:
-            if self.plot_flag == True or self.plot_flag == 'True':
-                iplot = 2
-            else:
-                iplot = 0
-
         # simulate Wood-Anderson response
         st.simulate(paz_remove=None, paz_simulate=self._paz)
 
@@ -225,62 +187,39 @@ class LocalMagnitude(Magnitude):
 
         power = [np.power(tr.data, 2) for tr in st if tr.stats.channel[-1] not
                  in 'Z3']
-        # checking horizontal count and calculating power_sum accordingly
+        if len(power) != 2:
-        if len(power) == 1:
+            raise ValueError('Wood-Anderson amplitude defintion only valid for '
-            print('WARNING: Only one horizontal found for station {0}.'.format(st[0].stats.station))
+                             'two horizontals: {0} given'.format(len(power)))
-            power_sum = power[0]
+        power_sum = power[0] + power[1]
-        elif len(power) == 2:
+        #
-            power_sum = power[0] + power[1]
-        else:
-            raise ValueError('Wood-Anderson aomplitude defintion only valid for'
-                             ' up to two horizontals: {0} given'.format(len(power)))
-
         sqH = np.sqrt(power_sum)
 
         # get time array
-        th = np.arange(0, st[0].stats.npts / st[0].stats.sampling_rate, dt)
+        th = np.arange(0, len(sqH) * dt, dt)
         # get maximum peak within pick window
         iwin = getsignalwin(th, t0 - stime, self.calc_win)
-        ii = min([iwin[len(iwin) - 1], len(th)])
-        iwin = iwin[0:ii]
         wapp = np.max(sqH[iwin])
         if self.verbose:
-            print("Determined Wood-Anderson peak-to-peak amplitude for station {0}: {1} "
+            print("Determined Wood-Anderson peak-to-peak amplitude: {0} "
-                  "mm".format(st[0].stats.station, wapp))
+                  "mm".format(wapp))
 
         # check for plot flag (for debugging only)
-        fig = None
+        if self.plot_flag > 1:
-        if iplot > 1:
+            st.plot()
-            fig = plt.figure()
+            f = plt.figure(2)
-            ax = fig.add_subplot(211)
+            plt.plot(th, sqH)
-            ax.plot(th, st[0].data, 'k')
+            plt.plot(th[iwin], sqH[iwin], 'g')
-            ax.plot(th, sqH)
+            plt.plot([t0, t0], [0, max(sqH)], 'r', linewidth=2)
-            ax.plot(th[iwin], sqH[iwin], 'g')
+            plt.title(
-            ax.plot([t0 - stime, t0 - stime], [0, max(sqH)], 'r', linewidth=2)
+                'Station %s, RMS Horizontal Traces, WA-peak-to-peak=%4.1f mm' \
-            ax.set_title('Station %s, Channel %s, RMS Horizontal Trace, '
+                % (st[0].stats.station, wapp))
-                         'WA-peak-to-peak=%6.3f mm' % (st[0].stats.station,
+            plt.xlabel('Time [s]')
-                                                       st[0].stats.channel,
+            plt.ylabel('Displacement [mm]')
-                                                       wapp))
+            plt.show()
-            ax.set_xlabel('Time [s]')
+            raw_input()
-            ax.set_ylabel('Displacement [mm]')
+            plt.close(f)
-            ax = fig.add_subplot(212)
-            ax.plot(th, st[1].data, 'k')
-            ax.plot(th, sqH)
-            ax.plot(th[iwin], sqH[iwin], 'g')
-            ax.plot([t0 - stime, t0 - stime], [0, max(sqH)], 'r', linewidth=2)
-            ax.set_title('Channel %s, RMS Horizontal Trace, '
-                         'WA-peak-to-peak=%6.3f mm' % (st[1].stats.channel,
-                                                       wapp))
-            ax.set_xlabel('Time [s]')
-            ax.set_ylabel('Displacement [mm]')
-            fig.show()
-            try:
-                input()
-            except SyntaxError:
-                pass
-            plt.close(fig)
 
-        return wapp, fig
+        return wapp
 
     def calc(self):
         for a in self.arrivals:
@@ -288,22 +227,17 @@ class LocalMagnitude(Magnitude):
                 continue
             pick = a.pick_id.get_referred_object()
             station = pick.waveform_id.station_code
-            # make sure calculating Ml only from reliable onsets
-            # NLLoc: time_weight = 0 => do not use onset!
-            if a.time_weight == 0:
-                print("Uncertain pick at Station {}, do not use it!".format(station))
-                continue
             wf = select_for_phase(self.stream.select(
                 station=station), a.phase)
             if not wf:
                 if self.verbose:
                     print(
-                        'WARNING: no waveform data found for station {0}'.format(
+                    'WARNING: no waveform data found for station {0}'.format(
-                            station))
+                        station))
                 continue
             delta = degrees2kilometers(a.distance)
             onset = pick.time
-            a0, self.p2p_fig = self.peak_to_peak(wf, onset)
+            a0 = self.peak_to_peak(wf, onset)
             amplitude = ope.Amplitude(generic_amplitude=a0 * 1e-3)
             amplitude.unit = 'm'
             amplitude.category = 'point'
@@ -314,22 +248,10 @@ class LocalMagnitude(Magnitude):
             self.event.amplitudes.append(amplitude)
             self.amplitudes = (station, amplitude)
             # using standard Gutenberg-Richter relation
-            # or scale WA amplitude with given scaling relation
+            # TODO make the ML calculation more flexible by allowing
-            if str(self.wascaling) == '[0.0, 0.0, 0.0]':
+            # use of custom relation functions
-                print("Calculating original Richter magnitude ...")
+            magnitude = ope.StationMagnitude(
-                magnitude = ope.StationMagnitude(mag=np.log10(a0) \
+                mag=np.log10(a0) + richter_magnitude_scaling(delta))
-                                                     + richter_magnitude_scaling(delta))
-            else:
-                print("Calculating scaled local magnitude ...")
-                a0 = a0 * 1e03  # mm to nm (see Havskov & Ottemöller, 2010)
-                magnitude = ope.StationMagnitude(mag=np.log10(a0) \
-                                                     + self.wascaling[0] * np.log10(delta) + self.wascaling[1]
-                                                     * delta + self.wascaling[
-                                                         2])
-            if self.verbose:
-                print(
-                    "Local Magnitude for station {0}: ML = {1:3.1f}".format(
-                        station, magnitude.mag))
             magnitude.origin_id = self.origin_id
             magnitude.waveform_id = pick.waveform_id
             magnitude.amplitude_id = amplitude.resource_id
@@ -393,44 +315,26 @@ class MomentMagnitude(Magnitude):
         for a in self.arrivals:
             if a.phase not in 'pP':
                 continue
-            # make sure calculating Mo only from reliable onsets
-            # NLLoc: time_weight = 0 => do not use onset!
-            if a.time_weight == 0:
-                continue
             pick = a.pick_id.get_referred_object()
             station = pick.waveform_id.station_code
-            if len(self.stream) <= 2:
+            wf = select_for_phase(self.stream.select(
-                print("Station:" '{0}'.format(station))
+                station=station), a.phase)
-                print("WARNING: No instrument corrected data available,"
-                      " no magnitude calculation possible! Go on.")
-                continue
-            wf = self.stream.select(station=station)
             if not wf:
                 continue
-            try:
-                scopy = wf.copy()
-            except AssertionError:
-                print("WARNING: Something's wrong with the data,"
-                      "station {},"
-                      "no calculation of moment magnitude possible! Go on.".format(station))
-                continue
             onset = pick.time
             distance = degrees2kilometers(a.distance)
             azimuth = a.azimuth
             incidence = a.takeoff_angle
-            if not 0. <= incidence <= 360.:
+            w0, fc = calcsourcespec(wf, onset, self.p_velocity, distance,
-                if self.verbose:
+                                    azimuth,
-                    print(f'WARNING: Incidence angle outside bounds - {incidence}')
+                                    incidence, self.p_attenuation,
-                return
-            w0, fc = calcsourcespec(scopy, onset, self.p_velocity, distance,
-                                    azimuth, incidence, self.p_attenuation,
                                     self.plot_flag, self.verbose)
             if w0 is None or fc is None:
                 if self.verbose:
                     print("WARNING: insufficient frequency information")
                 continue
-            WF = select_for_phase(scopy, "P")
+            wf = select_for_phase(wf, "P")
-            m0, mw = calcMoMw(WF, w0, self.rock_density, self.p_velocity,
+            m0, mw = calcMoMw(wf, w0, self.rock_density, self.p_velocity,
                               distance, self.verbose)
             self.moment_props = (station, dict(w0=w0, fc=fc, Mo=m0))
             magnitude = ope.StationMagnitude(mag=mw)
@@ -440,40 +344,6 @@ class MomentMagnitude(Magnitude):
             self.event.station_magnitudes.append(magnitude)
             self.magnitudes = (station, magnitude)
 
-    # WIP JG
-    def getSourceSpec(self):
-        for a in self.arrivals:
-            if a.phase not in 'pP':
-                continue
-            # make sure calculating Mo only from reliable onsets
-            # NLLoc: time_weight = 0 => do not use onset!
-            if a.time_weight == 0:
-                continue
-            pick = a.pick_id.get_referred_object()
-            station = pick.waveform_id.station_code
-            if len(self.stream) <= 2:
-                print("Station:" '{0}'.format(station))
-                print("WARNING: No instrument corrected data available,"
-                      " no magnitude calculation possible! Go on.")
-                continue
-            wf = self.stream.select(station=station)
-            if not wf:
-                continue
-            try:
-                scopy = wf.copy()
-            except AssertionError:
-                print("WARNING: Something's wrong with the data,"
-                      "station {},"
-                      "no calculation of moment magnitude possible! Go on.".format(station))
-                continue
-            onset = pick.time
-            distance = degrees2kilometers(a.distance)
-            azimuth = a.azimuth
-            incidence = a.takeoff_angle
-            w0, fc, plt = calcsourcespec(scopy, onset, self.p_velocity, distance,
-                                    azimuth, incidence, self.p_attenuation,
-                                    3, self.verbose)
-            return w0, fc, plt
 
 def calcMoMw(wfstream, w0, rho, vp, delta, verbosity=False):
     '''
@@ -501,24 +371,23 @@ def calcMoMw(wfstream, w0, rho, vp, delta, verbosity=False):
 
     if verbosity:
         print(
-            "calcMoMw: Calculating seismic moment Mo and moment magnitude Mw \
+        "calcMoMw: Calculating seismic moment Mo and moment magnitude Mw for station {0} ...".format(
-                for station {0} ...".format(tr.stats.station))
+            tr.stats.station))
 
     # additional common parameters for calculating Mo
-    # average radiation pattern of P waves (Aki & Richards, 1980)
+    rP = 2 / np.sqrt(
-    rP = 2 / np.sqrt(15)
+        15)  # average radiation pattern of P waves (Aki & Richards, 1980)
     freesurf = 2.0  # free surface correction, assuming vertical incidence
 
     Mo = w0 * 4 * np.pi * rho * np.power(vp, 3) * delta / (rP * freesurf)
 
-    # Mw = np.log10(Mo * 1e07) * 2 / 3 - 10.7 # after Hanks & Kanamori (1979),
+    # Mw = np.log10(Mo * 1e07) * 2 / 3 - 10.7 # after Hanks & Kanamori (1979), defined for [dyn*cm]!
-    # defined for [dyn*cm]!
     Mw = np.log10(Mo) * 2 / 3 - 6.7  # for metric units
 
     if verbosity:
         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
 
@@ -557,29 +426,17 @@ def calcsourcespec(wfstream, onset, vp, delta, azimuth, incidence,
     :type:  integer
     '''
     if verbosity:
-        print("Calculating source spectrum for station %s ...." % wfstream[0].stats.station)
+        print ("Calculating source spectrum ....")
-
-    try:
-        iplot = int(iplot)
-    except:
-        if iplot == True or iplot == 'True':
-            iplot = 2
-        else:
-            iplot = 0
 
     # get Q value
     Q, A = qp
 
     dist = delta * 1000  # hypocentral distance in [m]
 
-    Fc = None
+    fc = None
     w0 = None
-    zdat = select_for_phase(wfstream, "P")
 
-    if len(zdat) == 0:
+    zdat = select_for_phase(wfstream, "P")
-        print("No vertical component found in stream:\n{}".format(wfstream))
-        print("No calculation of source spectrum possible!")
-        return w0, Fc
 
     dt = zdat[0].stats.delta
 
@@ -588,6 +445,7 @@ def calcsourcespec(wfstream, onset, vp, delta, azimuth, incidence,
     # trim traces to common range (for rotation)
     trstart, trend = common_range(wfstream)
     wfstream.trim(trstart, trend)
+
     # rotate into LQT (ray-coordindate-) system using Obspy's rotate
     # L: P-wave direction
     # Q: SV-wave direction
@@ -595,21 +453,18 @@ def calcsourcespec(wfstream, onset, vp, delta, azimuth, incidence,
     LQT = wfstream.rotate('ZNE->LQT', azimuth, incidence)
     ldat = LQT.select(component="L")
     if len(ldat) == 0:
-        # if horizontal channels are 1 and 2
+        # if horizontal channels are 2 and 3
         # no azimuth information is available and thus no
         # rotation is possible!
         if verbosity:
             print("calcsourcespec: Azimuth information is missing, "
                   "no rotation of components possible!")
-        # instead, use component 3
+        ldat = LQT.select(component="Z")
-        ldat = LQT.select(component="3")
-        if len(ldat) == 0:
-            # maybe component z available
-            ldat = LQT.select(component="Z")
 
     # integrate to displacement
     # unrotated vertical component (for comparison)
     inttrz = signal.detrend(integrate.cumtrapz(zdat[0].data, None, dt))
+
     # rotated component Z => L
     Ldat = signal.detrend(integrate.cumtrapz(ldat[0].data, None, dt))
 
@@ -625,10 +480,12 @@ def calcsourcespec(wfstream, onset, vp, delta, azimuth, incidence,
     zc = crossings_nonzero_all(wfzc)
     if np.size(zc) == 0 or len(zc) <= 3:
         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
     else:
+        plotflag = 1
         index = min([3, len(zc) - 1])
         calcwin = (zc[index] - zc[0]) * dt
         iwin = getsignalwin(t, rel_onset, calcwin)
@@ -636,15 +493,14 @@ def calcsourcespec(wfstream, onset, vp, delta, azimuth, incidence,
 
         # fft
         fny = freq / 2
-        # l = len(xdat) / freq
+        l = len(xdat) / freq
         # number of fft bins after Bath
-        # n = freq * l
+        n = freq * l
         # find next power of 2 of data length
         m = pow(2, np.ceil(np.log(len(xdat)) / np.log(2)))
-        N = min(int(np.power(m, 2)), 16384)
+        N = int(np.power(m, 2))
-        # N = int(np.power(m, 2))
         y = dt * np.fft.fft(xdat, N)
-        Y = abs(y[: int(N / 2)])
+        Y = abs(y[: N / 2])
         L = (N - 1) / freq
         f = np.arange(0, fny, 1 / L)
 
@@ -674,8 +530,8 @@ def calcsourcespec(wfstream, onset, vp, delta, azimuth, incidence,
         w01 = optspecfit[0]
         fc1 = optspecfit[1]
         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" % (w01, fc1))
+                   "Determined corner frequency: %f Hz" % (w01, fc1))
 
         # use of conventional fitting
         [w02, fc2] = fitSourceModel(F, YYcor, Fcin, iplot, verbosity)
@@ -683,11 +539,12 @@ def calcsourcespec(wfstream, onset, vp, delta, azimuth, incidence,
         # get w0 and fc as median of both
         # source spectrum fits
         w0 = np.median([w01, w02])
-        Fc = np.median([fc1, fc2])
+        fc = np.median([fc1, fc2])
         if verbosity:
             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()
         tLdat = np.arange(0, len(Ldat) * dt, dt)
         plt.subplot(2, 1, 1)
@@ -695,7 +552,7 @@ def calcsourcespec(wfstream, onset, vp, delta, azimuth, incidence,
         p1, = plt.plot(t, np.multiply(inttrz, 1000), 'k')
         p2, = plt.plot(tLdat, np.multiply(Ldat, 1000))
         plt.legend([p1, p2], ['Displacement', 'Rotated Displacement'])
-        if iplot == 1:
+        if plotflag == 1:
             plt.plot(t[iwin], np.multiply(xdat, 1000), 'g')
             plt.title('Seismogram and P Pulse, Station %s-%s' \
                       % (zdat[0].stats.station, zdat[0].stats.channel))
@@ -705,32 +562,27 @@ def calcsourcespec(wfstream, onset, vp, delta, azimuth, incidence,
         plt.xlabel('Time since %s' % zdat[0].stats.starttime)
         plt.ylabel('Displacement [mm]')
 
-        if iplot > 1:
+        if plotflag == 1:
             plt.subplot(2, 1, 2)
             p1, = plt.loglog(f, Y.real, 'k')
             p2, = plt.loglog(F, YY.real)
             p3, = plt.loglog(F, YYcor, 'r')
             p4, = plt.loglog(F, fit, 'g')
-            plt.loglog([Fc, Fc], [w0 / 100, w0], 'g')
+            plt.loglog([fc, fc], [w0 / 100, w0], 'g')
-            plt.legend([p1, p2, p3, p4], ['Raw Spectrum',
+            plt.legend([p1, p2, p3, p4], ['Raw Spectrum', \
-                                          'Used Raw Spectrum',
+                                          'Used Raw Spectrum', \
-                                          'Q-Corrected Spectrum',
+                                          'Q-Corrected Spectrum', \
                                           'Fit to Spectrum'])
             plt.title('Source Spectrum from P Pulse, w0=%e m/Hz, fc=%6.2f Hz' \
-                      % (w0, Fc))
+                      % (w0, fc))
             plt.xlabel('Frequency [Hz]')
             plt.ylabel('Amplitude [m/Hz]')
             plt.grid()
-            if iplot == 3:
+        plt.show()
-                return w0, Fc, plt
+        raw_input()
-            plt.show()
+        plt.close(f1)
-            try:
-                input()
-            except SyntaxError:
-                pass
-            plt.close(f1)
 
-    return w0, Fc
+    return w0, fc
 
 
 def synthsourcespec(f, omega0, fcorner):
@@ -770,49 +622,23 @@ def fitSourceModel(f, S, fc0, iplot, verbosity=False):
     :type:   float
     '''
 
-    try:
-        iplot = int(iplot)
-    except:
-        if iplot == True or iplot == 'True':
-            iplot = 2
-        else:
-            iplot = 0
-
     w0 = []
     stdw0 = []
     fc = []
     stdfc = []
     STD = []
+
     # get window around initial corner frequency for trials
-    # left side of initial corner frequency
+    fcstopl = fc0 - max(1, len(f) / 10)
-    fcstopl = max(f[0], fc0 - max(1, fc0 / 2))
+    il = np.argmin(abs(f - fcstopl))
-    il = np.where(f <= fcstopl)
+    fcstopl = f[il]
-    il = il[0][np.size(il) - 1]
+    fcstopr = fc0 + min(len(f), len(f) / 10)
-    # right side of initial corner frequency
+    ir = np.argmin(abs(f - fcstopr))
-    fcstopr = min(fc0 + (fc0 / 2), f[len(f) - 1])
+    fcstopr = f[ir]
-    ir = np.where(f >= fcstopr)
+    iF = np.where((f >= fcstopl) & (f <= fcstopr))
-    # check, if fcstopr is available
-    if np.size(ir) == 0:
-        fcstopr = fc0
-        ir = len(f) - 1
-    else:
-        ir = ir[0][0]
 
     # vary corner frequency around initial point
-    print("fitSourceModel: Varying corner frequency "
+    for i in range(il, ir):
-          "around initial corner frequency ...")
-    # check difference of il and ir in order to
-    # keep calculation time acceptable
-    idiff = ir - il
-    if idiff > 100000:
-        increment = 1000
-    elif idiff <= 100000 and idiff > 10000:
-        increment = 100
-    elif idiff <= 20:
-        increment = 1
-    else:
-        increment = 10
-    for i in range(il, ir, increment):
         FC = f[i]
         indexdc = np.where((f > 0) & (f <= FC))
         dc = np.mean(S[indexdc])
@@ -829,43 +655,40 @@ def fitSourceModel(f, S, fc0, iplot, verbosity=False):
 
     # get best found w0 anf fc from minimum
     if len(STD) > 0:
-        Fc = fc[np.argmin(STD)]
+        fc = fc[np.argmin(STD)]
         w0 = w0[np.argmin(STD)]
     elif len(STD) == 0:
-        Fc = fc0
+        fc = fc0
         w0 = max(S)
     if verbosity:
         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:
+
-        plt.figure()  # iplot)
+    if iplot > 1:
+        plt.figure(iplot)
         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')
         plt.title('Calculated Source Spectrum, Omega0=%e m/Hz, fc=%6.2f Hz' \
-                  % (w0, Fc))
+                  % (w0, fc))
         plt.xlabel('Frequency [Hz]')
         plt.ylabel('Amplitude [m/Hz]')
         plt.grid()
-        if iplot == 2:
+        plt.figure(iplot + 1)
-            plt.figure()  # iplot + 1)
+        plt.subplot(311)
-            plt.subplot(311)
+        plt.plot(f[il:ir], STD, '*')
-            plt.plot(fc, STD, '*')
+        plt.title('Common Standard Deviations')
-            plt.title('Common Standard Deviations')
+        plt.xticks([])
-            plt.xticks([])
+        plt.subplot(312)
-            plt.subplot(312)
+        plt.plot(f[il:ir], stdw0, '*')
-            plt.plot(fc, stdw0, '*')
+        plt.title('Standard Deviations of w0-Values')
-            plt.title('Standard Deviations of w0-Values')
+        plt.xticks([])
-            plt.xticks([])
+        plt.subplot(313)
-            plt.subplot(313)
+        plt.plot(f[il:ir], stdfc, '*')
-            plt.plot(fc, stdfc, '*')
+        plt.title('Standard Deviations of Corner Frequencies')
-            plt.title('Standard Deviations of Corner Frequencies')
+        plt.xlabel('Corner Frequencies [Hz]')
-            plt.xlabel('Corner Frequencies [Hz]')
+        plt.show()
-            plt.show()
+        raw_input()
-        try:
-            input()
-        except SyntaxError:
-            pass
         plt.close()
 
-    return w0, Fc
+    return w0, fc

pylot/core/io/data.py

@@ -1,69 +1,334 @@
 #!/usr/bin/env python
 # -*- coding: utf-8 -*-
 
+import copy
 import os
-from dataclasses import dataclass, field
+from obspy import read_events
-from typing import List, Union
+from obspy.core import read, Stream, UTCDateTime
+from obspy.core.event import Event
 
-from obspy import UTCDateTime
+from pylot.core.io.phases import readPILOTEvent, picks_from_picksdict, \
+    picksdict_from_pilot, merge_picks
+from pylot.core.util.errors import FormatError, OverwriteError
+from pylot.core.util.utils import fnConstructor, full_range
 
-from pylot.core.io.event import EventData
-from pylot.core.io.waveformdata import WaveformData
-from pylot.core.util.dataprocessing import Metadata
 
-@dataclass
+class Data(object):
-class Data:
+    """
-    event_data: EventData = field(default_factory=EventData)
+    Data container with attributes wfdata holding ~obspy.core.stream.
-    waveform_data: WaveformData = field(default_factory=WaveformData)
+
-    metadata: Metadata = field(default_factory=Metadata)
+    :type parent: PySide.QtGui.QWidget object, optional
-    _parent: Union[None, 'QtWidgets.QWidget'] = None
+    :param parent: A PySide.QtGui.QWidget object utilized when
+    called by a GUI to display a PySide.QtGui.QMessageBox instead of printing
+    to standard out.
+    :type evtdata: ~obspy.core.event.Event object, optional
+    :param evtdata ~obspy.core.event.Event object containing all derived or
+    loaded event. Container object holding, e.g. phase arrivals, etc.
+    """
 
     def __init__(self, parent=None, evtdata=None):
         self._parent = parent
-        self.event_data = EventData(evtdata)
+        if self.getParent():
-        self.waveform_data = WaveformData()
+            self.comp = parent.getComponent()
+        else:
+            self.comp = 'Z'
+            self.wfdata = Stream()
+        self._new = False
+        if isinstance(evtdata, Event):
+            pass
+        elif isinstance(evtdata, dict):
+            evt = readPILOTEvent(**evtdata)
+            evtdata = evt
+        elif isinstance(evtdata, basestring):
+            try:
+                cat = read_events(evtdata)
+                if len(cat) is not 1:
+                    raise ValueError('ambiguous event information for file: '
+                                     '{file}'.format(file=evtdata))
+                evtdata = cat[0]
+            except TypeError as e:
+                if 'Unknown format for file' in e.message:
+                    if 'PHASES' in evtdata:
+                        picks = picksdict_from_pilot(evtdata)
+                        evtdata = Event()
+                        evtdata.picks = picks_from_picksdict(picks)
+                    elif 'LOC' in evtdata:
+                        raise NotImplementedError('PILOT location information '
+                                                  'read support not yet '
+                                                  'implemeted.')
+                    else:
+                        raise e
+                else:
+                    raise e
+        else:  # create an empty Event object
+            self.setNew()
+            evtdata = Event()
+            evtdata.picks = []
+        self.evtdata = evtdata
+        self.wforiginal = None
+        self.cuttimes = None
+        self.dirty = False
 
     def __str__(self):
-        return str(self.waveform_data.wfdata)
+        return str(self.wfdata)
 
     def __add__(self, other):
-        if not isinstance(other, Data):
+        assert isinstance(other, Data), "operands must be of same type 'Data'"
-            raise TypeError("Operands must be of type 'Data'")
+        if other.isNew() and not self.isNew():
-        if self.event_data.is_new() and other.event_data.is_new():
+            picks_to_add = other.get_evt_data().picks
+            old_picks = self.get_evt_data().picks
+            for pick in picks_to_add:
+                if pick not in old_picks:
+                    old_picks.append(pick)
+        elif not other.isNew() and self.isNew():
+            new = other + self
+            self.evtdata = new.get_evt_data()
+        elif self.isNew() and other.isNew():
             pass
-        elif other.event_data.is_new():
+        elif self.get_evt_data().get('id') == other.get_evt_data().get('id'):
-            new_picks = other.event_data.evtdata.picks
+            other.setNew()
-            old_picks = self.event_data.evtdata.picks
-            old_picks.extend([pick for pick in new_picks if pick not in old_picks])
-        elif self.event_data.is_new():
-            return other + self
-        elif self.event_data.get_id() == other.event_data.get_id():
-            other.event_data.set_new()
             return self + other
         else:
-            raise ValueError("Both Data objects have differing unique Event identifiers")
+            raise ValueError("both Data objects have differing "
+                             "unique Event identifiers")
         return self
 
-    def get_parent(self):
+    def getPicksStr(self):
+        picks_str = ''
+        for pick in self.get_evt_data().picks:
+            picks_str += str(pick) + '\n'
+        return picks_str
+
+    def getParent(self):
+        """
+
+
+        :return:
+        """
         return self._parent
 
-    def filter_wf_data(self, **kwargs):
+    def isNew(self):
-        self.waveform_data.wfdata.detrend('linear')
+        """
-        self.waveform_data.wfdata.taper(0.02, type='cosine')
-        self.waveform_data.wfdata.filter(**kwargs)
-        self.waveform_data.dirty = True
 
-    def set_wf_data(self, fnames: List[str], fnames_alt: List[str] = None, check_rotated=False, metadata=None, tstart=0, tstop=0):
-        return self.waveform_data.load_waveforms(fnames, fnames_alt, check_rotated, metadata, tstart, tstop)
 
-    def reset_wf_data(self):
+        :return:
-        self.waveform_data.reset()
+        """
+        return self._new
 
-    def get_wf_data(self):
+    def setNew(self):
-        return self.waveform_data.wfdata
+        self._new = True
 
-    def rotate_wf_data(self):
+    def getCutTimes(self):
-        self.waveform_data.rotate_zne(self.metadata)
+        """
+
+
+        :return:
+        """
+        if self.cuttimes is None:
+            self.updateCutTimes()
+        return self.cuttimes
+
+    def updateCutTimes(self):
+        """
+
+
+        """
+        self.cuttimes = full_range(self.getWFData())
+
+    def getEventFileName(self):
+        """
+
+
+        :return:
+        """
+        ID = self.getID()
+        # handle forbidden filenames especially on windows systems
+        return fnConstructor(str(ID))
+
+    def exportEvent(self, fnout, fnext='.xml'):
+
+        """
+
+        :param fnout:
+        :param fnext:
+        :raise KeyError:
+        """
+        from pylot.core.util.defaults import OUTPUTFORMATS
+
+        try:
+            evtformat = OUTPUTFORMATS[fnext]
+        except KeyError as e:
+            errmsg = '{0}; selected file extension {1} not ' \
+                     'supported'.format(e, fnext)
+            raise FormatError(errmsg)
+
+        # try exporting event via ObsPy
+        try:
+            self.get_evt_data().write(fnout + fnext, format=evtformat)
+        except KeyError as e:
+            raise KeyError('''{0} export format
+                              not implemented: {1}'''.format(evtformat, e))
+
+    def getComp(self):
+        """
+
+
+        :return:
+        """
+        return self.comp
+
+    def getID(self):
+        """
+
+
+        :return:
+        """
+        try:
+            return self.evtdata.get('resource_id').id
+        except:
+            return None
+
+    def filterWFData(self, kwargs):
+        """
+
+        :param kwargs:
+        """
+        self.getWFData().filter(**kwargs)
+        self.dirty = True
+
+    def setWFData(self, fnames):
+        """
+
+        :param fnames:
+        """
+        self.wfdata = Stream()
+        self.wforiginal = None
+        if fnames is not None:
+            self.appendWFData(fnames)
+        else:
+            return False
+        self.wforiginal = self.getWFData().copy()
+        self.dirty = False
+        return True
+
+    def appendWFData(self, fnames):
+        """
+
+        :param fnames:
+        """
+        assert isinstance(fnames, list), "input parameter 'fnames' is " \
+                                         "supposed to be of type 'list' " \
+                                         "but is actually" \
+                                         " {0}".format(type(fnames))
+        if self.dirty:
+            self.resetWFData()
+
+        warnmsg = ''
+        for fname in fnames:
+            try:
+                self.wfdata += read(fname)
+            except TypeError:
+                try:
+                    self.wfdata += read(fname, format='GSE2')
+                except Exception as e:
+                    warnmsg += '{0}\n{1}\n'.format(fname, e)
+        if warnmsg:
+            warnmsg = 'WARNING: unable to read\n' + warnmsg
+            print(warnmsg)
+
+    def getWFData(self):
+        """
+
+
+        :return:
+        """
+        return self.wfdata
+
+    def getOriginalWFData(self):
+        """
+
+
+        :return:
+        """
+        return self.wforiginal
+
+    def resetWFData(self):
+        """
+
+
+        """
+        self.wfdata = self.getOriginalWFData().copy()
+        self.dirty = False
+
+    def resetPicks(self):
+        """
+
+
+        """
+        self.get_evt_data().picks = []
+
+    def get_evt_data(self):
+        """
+
+
+        :return:
+        """
+        return self.evtdata
+
+    def setEvtData(self, event):
+        self.evtdata = event
+
+    def applyEVTData(self, data, type='pick', authority_id='rub'):
+
+        """
+
+        :param data:
+        :param type:
+        :param authority_id:
+        :raise OverwriteError:
+        """
+
+        def applyPicks(picks):
+            """
+            Creates ObsPy pick objects and append it to the picks list from the
+            PyLoT dictionary contain all picks.
+            :param picks:
+            :raise OverwriteError: raises an OverwriteError if the picks list is
+             not empty. The GUI will then ask for a decision.
+            """
+
+            #firstonset = find_firstonset(picks)
+            if self.get_evt_data().picks:
+                raise OverwriteError('Actual picks would be overwritten!')
+            else:
+                picks = picks_from_picksdict(picks)
+            self.get_evt_data().picks = picks
+            # if 'smi:local' in self.getID() and firstonset:
+            #     fonset_str = firstonset.strftime('%Y_%m_%d_%H_%M_%S')
+            #     ID = ResourceIdentifier('event/' + fonset_str)
+            #     ID.convertIDToQuakeMLURI(authority_id=authority_id)
+            #     self.get_evt_data().resource_id = ID
+
+
+        def applyEvent(event):
+            """
+            takes an `obspy.core.event.Event` object and applies all new
+            information on the event to the actual data
+            :param event:
+            """
+            if not self.isNew():
+                self.setEvtData(event)
+            else:
+                # prevent overwriting original pick information
+                picks =  copy.deepcopy(self.get_evt_data().picks)
+                event = merge_picks(event, picks)
+                # apply event information from location
+                self.get_evt_data().update(event)
+
+        applydata = {'pick': applyPicks,
+                     'event': applyEvent}
+
+        applydata[type](data)
 
 
 class GenericDataStructure(object):
@@ -240,8 +505,8 @@ class PilotDataStructure(GenericDataStructure):
 
     def __init__(self, **fields):
         if not fields:
-            fields = {'database': '',
+            fields = {'database': '2006.01',
-                      'root': ''}
+                      'root': '/data/Egelados/EVENT_DATA/LOCAL'}
 
         GenericDataStructure.__init__(self, **fields)