[edit] restructuring autopicking module

renamed several function and classes, moved script files to scripts

pylot/core/pick/autopick.py

@@ -12,8 +12,8 @@ function conglomerate utils.
 import matplotlib.pyplot as plt
 import numpy as np
 from scipy import integrate
-from pylot.core.pick.Picker import AICPicker, PragPicker
-from pylot.core.pick.CharFuns import HOScf, AICcf, ARZcf, ARHcf, AR3Ccf
+from pylot.core.pick.picker import AICPicker, PragPicker
+from pylot.core.pick.charfuns import HOScf, AICcf, ARZcf, ARHcf, AR3Ccf
 from pylot.core.pick.utils import checksignallength, checkZ4S, earllatepicker,\
     getSNR, fmpicker, checkPonsets, wadaticheck
 from pylot.core.util.utils import getPatternLine

pylot/core/pick/earllatepicker.py

@@ -1,27 +0,0 @@
-#!/usr/bin/python
-# -*- coding: utf-8 -*-
-"""
-   Created Mar 2015
-   Transcription of the rezipe of Diehl et al. (2009) for consistent phase
-   picking. For a given inital (the most likely) pick, the corresponding earliest
-   and latest possible pick is calculated based on noise measurements in front of
-   the most likely pick and signal wavelength derived from zero crossings.
-
-   :author: Ludger Kueperkoch / MAGS2 EP3 working group
-"""
-
-import argparse
-import obspy
-from pylot.core.pick.utils import earllatepicker
-
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser()
-    parser.add_argument('--X', type=~obspy.core.stream.Stream, help='time series (seismogram) read with obspy module read')
-    parser.add_argument('--nfac', type=int, help='(noise factor), nfac times noise level to calculate latest possible pick')
-    parser.add_argument('--TSNR', type=tuple, help='length of time windows around pick used to determine SNR \
-                        [s] (Tnoise, Tgap, Tsignal)')
-    parser.add_argument('--Pick1', type=float, help='Onset time of most likely pick')
-    parser.add_argument('--iplot', type=int, help='if set, figure no. iplot occurs')
-    args = parser.parse_args()
-    earllatepicker(args.X, args.nfac, args.TSNR, args.Pick1, args.iplot)

pylot/core/pick/fmpicker.py

@@ -1,23 +0,0 @@
-#!/usr/bin/python
-# -*- coding: utf-8 -*-
-"""
-   Created Mar 2015
-   Function to derive first motion (polarity) for given phase onset based on zero crossings.
-
-   :author: MAGS2 EP3 working group / Ludger Kueperkoch
-"""
-
-import argparse
-import obspy
-from pylot.core.pick.utils import fmpicker
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser()
-    parser.add_argument('--Xraw', type=~obspy.core.stream.Stream, help='unfiltered time series (seismogram) read with obspy module read')
-    parser.add_argument('--Xfilt', type=~obspy.core.stream.Stream, help='filtered time series (seismogram) read with obspy module read')
-    parser.add_argument('--pickwin', type=float, help='length of pick window [s] for first motion determination')
-    parser.add_argument('--Pick', type=float, help='Onset time of most likely pick')
-    parser.add_argument('--iplot', type=int, help='if set, figure no. iplot occurs')
-    args = parser.parse_args()
-    fmpicker(args.Xraw, args.Xfilt, args.pickwin, args.Pick, args.iplot)
-

pylot/core/pick/getSNR.py

@@ -1,30 +0,0 @@
-#!/usr/bin/python
-# -*- coding: utf-8 -*-
-"""
-   Created Mar/Apr 2015
-   Function to calculate SNR of certain part of seismogram relative
-   to given time. Returns SNR and SNR [dB].
-
-   :author: Ludger Kueperkoch /MAGS EP3 working group
-"""
-
-import argparse
-import obspy
-from pylot.core.pick.utils import getSNR
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser()
-    parser.add_argument('--data', '-d', type=~obspy.core.stream.Stream,
-                        help='time series (seismogram) read with obspy module '
-                             'read',
-                        dest='data')
-    parser.add_argument('--tsnr', '-s', type=tuple,
-                        help='length of time windows around pick used to '
-                             'determine SNR [s] (Tnoise, Tgap, Tsignal)',
-                        dest='tsnr')
-    parser.add_argument('--time', '-t', type=float,
-                        help='initial time from which noise and signal windows '
-                             'are calculated',
-                        dest='time')
-    args = parser.parse_args()
-    print getSNR(args.data, args.tsnr, args.time)

pylot/core/pick/getnoisewin.py

@@ -1,15 +0,0 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-
-import argparse
-import numpy
-from pylot.core.pick.utils import getnoisewin
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser()
-    parser.add_argument('--t', type=~numpy.array, help='numpy array of time stamps')
-    parser.add_argument('--t1', type=float, help='time from which relativ to it noise window is extracted')
-    parser.add_argument('--tnoise', type=float, help='length of time window [s] for noise part extraction')
-    parser.add_argument('--tgap', type=float, help='safety gap between signal (t1=onset) and noise')
-    args = parser.parse_args()
-    getnoisewin(args.t, args.t1, args.tnoise, args.tgap)

pylot/core/pick/getsignalwin.py

@@ -1,14 +0,0 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-
-import argparse
-import numpy
-from pylot.core.pick.utils import getsignalwin
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser()
-    parser.add_argument('--t', type=~numpy.array, help='numpy array of time stamps')
-    parser.add_argument('--t1', type=float, help='time from which relativ to it signal window is extracted')
-    parser.add_argument('--tsignal', type=float, help='length of time window [s] for signal part extraction')
-    args = parser.parse_args()
-    getsignalwin(args.t, args.t1, args.tsignal)

pylot/core/pick/picker.py

@@ -22,10 +22,10 @@ calculated after Diehl & Kissling (2009).
 import numpy as np
 import matplotlib.pyplot as plt
 from pylot.core.pick.utils import getnoisewin, getsignalwin
-from pylot.core.pick.CharFuns import CharacteristicFunction
+from pylot.core.pick.charfuns import CharacteristicFunction
 import warnings
 
-class AutoPicking(object):
+class AutoPicker(object):
     '''
     Superclass of different, automated picking algorithms applied on a CF determined
     using AIC, HOS, or AR prediction.
@@ -137,7 +137,7 @@ class AutoPicking(object):
         self.Pick = None
 
 
-class AICPicker(AutoPicking):
+class AICPicker(AutoPicker):
     '''
     Method to derive the onset time of an arriving phase based on CF
     derived from AIC. In order to get an impression of the quality of this inital pick,
@@ -289,7 +289,7 @@ class AICPicker(AutoPicking):
             print('AICPicker: Could not find minimum, picking window too short?')
 
 
-class PragPicker(AutoPicking):
+class PragPicker(AutoPicker):
     '''
     Method of pragmatic picking exploiting information given by CF.
     '''

pylot/core/pick/run_makeCF.py

@@ -9,8 +9,8 @@
 from obspy.core import read
 import matplotlib.pyplot as plt
 import numpy as np
-from pylot.core.pick.CharFuns import CharacteristicFunction
-from pylot.core.pick.Picker import AutoPicking
+from pylot.core.pick.charfuns import CharacteristicFunction
+from pylot.core.pick.picker import AutoPicker
 from pylot.core.pick.utils import *
 import glob
 import argparse