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[reformat] code reformatting with PyCharm

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Marcel Paffrath
2017-08-03 09:41:54 +02:00
parent 4107f0249d
commit 20b31a1c5c
49 changed files with 3255 additions and 3194 deletions
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pylot/core/analysis/magnitude.py
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@@ -6,27 +6,27 @@ Revised/extended summer 2017.
:author: Ludger Küperkoch / MAGS2 EP3 working group
"""
import os
import matplotlib.pyplot as plt
import numpy as np
import obspy.core.event as ope
from obspy.geodetics import degrees2kilometers
from scipy import integrate, signal
from scipy.optimize import curve_fit
from pylot.core.pick.utils import getsignalwin, crossings_nonzero_all, \
select_for_phase
from pylot.core.util.utils import common_range, fit_curve
from scipy import integrate, signal
from scipy.optimize import curve_fit
def richter_magnitude_scaling(delta):
distance = np.array([0, 10, 20, 25, 30, 35,40, 45, 50, 60, 70, 75, 85, 90, 100, 110,
distance = np.array([0, 10, 20, 25, 30, 35, 40, 45, 50, 60, 70, 75, 85, 90, 100, 110,
120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 230, 240, 250,
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])
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)
return func(delta, params)
@@ -47,7 +47,7 @@ class Magnitude(object):
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))
@@ -126,8 +126,8 @@ class Magnitude(object):
# scaling necessary
print("Scaling network magnitude ...")
mag = ope.Magnitude(
mag=np.median([M.mag for M in self.magnitudes.values()]) *\
magscaling[0] + magscaling[1],
mag=np.median([M.mag for M in self.magnitudes.values()]) * \
magscaling[0] + magscaling[1],
magnitude_type=self.type,
origin_id=self.origin_id,
station_count=len(self.magnitudes),
@@ -215,7 +215,7 @@ class LocalMagnitude(Magnitude):
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)])
ii = min([iwin[len(iwin) - 1], len(th)])
iwin = iwin[0:ii]
wapp = np.max(sqH[iwin])
if self.verbose:
@@ -250,8 +250,8 @@ class LocalMagnitude(Magnitude):
if not wf:
if self.verbose:
print(
'WARNING: no waveform data found for station {0}'.format(
station))
'WARNING: no waveform data found for station {0}'.format(
station))
continue
delta = degrees2kilometers(a.distance)
onset = pick.time
@@ -270,13 +270,14 @@ class LocalMagnitude(Magnitude):
if str(self.wascaling) == '[0.0, 0.0, 0.0]':
print("Calculating original Richter magnitude ...")
magnitude = ope.StationMagnitude(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)
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])
+ self.wascaling[0] * np.log10(delta) + self.wascaling[1]
* delta + self.wascaling[
2])
magnitude.origin_id = self.origin_id
magnitude.waveform_id = pick.waveform_id
magnitude.amplitude_id = amplitude.resource_id
@@ -397,8 +398,8 @@ def calcMoMw(wfstream, w0, rho, vp, delta, verbosity=False):
if verbosity:
print(
"calcMoMw: Calculating seismic moment Mo and moment magnitude Mw for station {0} ...".format(
tr.stats.station))
"calcMoMw: Calculating seismic moment Mo and moment magnitude Mw for station {0} ...".format(
tr.stats.station))
# additional common parameters for calculating Mo
rP = 2 / np.sqrt(
@@ -412,8 +413,8 @@ def calcMoMw(wfstream, w0, rho, vp, delta, verbosity=False):
if verbosity:
print(
"calcMoMw: Calculated seismic moment Mo = {0} Nm => Mw = {1:3.1f} ".format(
Mo, Mw))
"calcMoMw: Calculated seismic moment Mo = {0} Nm => Mw = {1:3.1f} ".format(
Mo, Mw))
return Mo, Mw
@@ -452,7 +453,7 @@ 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 for station %s ...." % wfstream[0].stats.station)
# get Q value
Q, A = qp
@@ -509,9 +510,9 @@ 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, "
"no zero crossings derived!\n")
print ("No calculation of source spectrum possible!")
print("calcsourcespec: Something is wrong with the waveform, "
"no zero crossings derived!\n")
print("No calculation of source spectrum possible!")
plotflag = 0
else:
plotflag = 1
@@ -558,22 +559,22 @@ def calcsourcespec(wfstream, onset, vp, delta, azimuth, incidence,
[optspecfit, _] = curve_fit(synthsourcespec, F, YYcor, [w0in, Fcin])
w0 = optspecfit[0]
fc = optspecfit[1]
#w01 = optspecfit[0]
#fc1 = optspecfit[1]
# w01 = optspecfit[0]
# fc1 = optspecfit[1]
if verbosity:
print ("calcsourcespec: Determined w0-value: %e m/Hz, \n"
"calcsourcespec: Determined corner frequency: %f Hz" % (w0, fc))
print("calcsourcespec: Determined w0-value: %e m/Hz, \n"
"calcsourcespec: Determined corner frequency: %f Hz" % (w0, fc))
# use of conventional fitting
# [w02, fc2] = fitSourceModel(F, YYcor, Fcin, iplot, verbosity)
# use of conventional fitting
# [w02, fc2] = fitSourceModel(F, YYcor, Fcin, iplot, verbosity)
# get w0 and fc as median of both
# source spectrum fits
#w0 = np.median([w01, w02])
#fc = np.median([fc1, fc2])
#if verbosity:
# print("calcsourcespec: Using w0-value = %e m/Hz and fc = %f Hz" % (
# w0, fc))
# get w0 and fc as median of both
# source spectrum fits
# w0 = np.median([w01, w02])
# fc = np.median([fc1, fc2])
# if verbosity:
# print("calcsourcespec: Using w0-value = %e m/Hz and fc = %f Hz" % (
# w0, fc))
if iplot > 1:
f1 = plt.figure()
@@ -659,9 +660,9 @@ def fitSourceModel(f, S, fc0, iplot, verbosity=False):
# left side of initial corner frequency
fcstopl = max(f[0], fc0 - max(1, fc0 / 2))
il = np.where(f <= fcstopl)
il = il[0][np.size(il) - 1]
il = il[0][np.size(il) - 1]
# right side of initial corner frequency
fcstopr = min(fc0 + (fc0 / 2), f[len(f) - 1])
fcstopr = min(fc0 + (fc0 / 2), f[len(f) - 1])
ir = np.where(f >= fcstopr)
# check, if fcstopr is available
if np.size(ir) == 0:
@@ -672,16 +673,16 @@ def fitSourceModel(f, S, fc0, iplot, verbosity=False):
# vary corner frequency around initial point
print("fitSourceModel: Varying corner frequency "
"around initial corner frequency ...")
"around initial corner frequency ...")
# check difference of il and ir in order to
# keep calculation time acceptable
idiff = ir - il
if idiff > 10000:
increment = 100
increment = 100
elif idiff <= 20:
increment = 1
increment = 1
else:
increment = 10
increment = 10
for i in range(il, ir, increment):
FC = f[i]
@@ -707,10 +708,10 @@ def fitSourceModel(f, S, fc0, iplot, verbosity=False):
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)
plt.figure() # iplot)
plt.loglog(f, S, 'k')
plt.loglog([f[0], fc], [w0, w0], 'g')
plt.loglog([fc, fc], [w0 / 100, w0], 'g')
@@ -719,7 +720,7 @@ def fitSourceModel(f, S, fc0, iplot, verbosity=False):
plt.xlabel('Frequency [Hz]')
plt.ylabel('Amplitude [m/Hz]')
plt.grid()
plt.figure()#iplot + 1)
plt.figure() # iplot + 1)
plt.subplot(311)
plt.plot(f[il:ir], STD, '*')
plt.title('Common Standard Deviations')