def benchmark_sinc(self):
n = 10000000
i_control = num.array([0., n - 1], dtype=num.int64)
t_control = num.array([0., n - 1], dtype=num.float)
s_in = num.zeros(n, dtype=num.float)
s_out = num.zeros(n, dtype=num.float)
tmin = 0.
deltat = 1.0
from pyrocko import signal_ext
t1 = time.time()
signal_ext.antidrift(i_control, t_control, s_in, tmin, deltat, s_out)
t2 = time.time()
print(t2 - t1)
def benchmark_sinc(self):
n = 10000000
i_control = num.array([0., n-1], dtype=num.int64)
t_control = num.array([0., n-1], dtype=num.float)
s_in = num.zeros(n, dtype=num.float)
s_out = num.zeros(n, dtype=num.float)
tmin = 0.
deltat = 1.0
from pyrocko import signal_ext
t1 = time.time()
signal_ext.antidrift(i_control, t_control, s_in, tmin, deltat, s_out)
t2 = time.time()
print t2 - t1
def iload(fn, load_data=True, interpolation='sinc'):
from pyrocko import datacube_ext
from pyrocko import signal_ext
if interpolation not in ('sinc', 'off'):
raise NotImplemented(
'no such interpolation method: %s' % interpolation)
with open(fn, 'rb') as f:
if load_data:
loadflag = 2
else:
if interpolation == 'off':
loadflag = 0
else:
# must get correct nsamples if interpolation is off
loadflag = 1
try:
header, data_arrays, gps_tags, nsamples, _ = datacube_ext.load(
f.fileno(), loadflag, 0, -1, None)
except datacube_ext.DataCubeError as e:
e = DataCubeError(str(e))
e.set_context('filename', fn)
raise e
header = dict(header)
deltat = 1.0 / int(header['S_RATE'])
nchannels = int(header['CH_NUM'])
ipos, t, fix, nsvs, header_, offset_, nsamples_ = \
get_extended_timing_context(fn)
tmin, tmax, icontrol, tcontrol = analyse_gps_tags(
header_, (ipos, t, fix, nsvs), offset_, nsamples_)
tmin_ip = round(tmin / deltat) * deltat
if interpolation != 'off':
tmax_ip = round(tmax / deltat) * deltat
else:
tmax_ip = tmin_ip + (nsamples-1) * deltat
nsamples_ip = int(round((tmax_ip - tmin_ip)/deltat)) + 1
# to prevent problems with rounding errors:
tmax_ip = tmin_ip + (nsamples_ip-1) * deltat
leaps = num.array(
[x[0] + util.gps_utc_offset(x[0]) for x in util.read_leap_seconds2()],
dtype=num.float)
for i in range(nchannels):
if load_data:
arr = data_arrays[i]
assert arr.size == nsamples
if interpolation == 'sinc' and icontrol is not None:
ydata = num.empty(nsamples_ip, dtype=num.float)
signal_ext.antidrift(
icontrol, tcontrol,
arr.astype(num.float), tmin_ip, deltat, ydata)
ydata = num.round(ydata).astype(arr.dtype)
else:
ydata = arr
tr_tmin = tmin_ip
tr_tmax = None
else:
ydata = None
tr_tmin = tmin_ip
tr_tmax = tmax_ip
tr = trace.Trace('', header['DEV_NO'], '', 'p%i' % i, deltat=deltat,
ydata=ydata, tmin=tr_tmin, tmax=tr_tmax, meta=header)
bleaps = num.logical_and(tmin_ip <= leaps, leaps < tmax_ip)
if num.any(bleaps):
assert num.sum(bleaps) == 1
tcut = leaps[bleaps][0]
for tmin_cut, tmax_cut in [
(tr.tmin, tcut), (tcut, tr.tmax+tr.deltat)]:
try:
tr_cut = tr.chop(tmin_cut, tmax_cut, inplace=False)
tr_cut.shift(
util.utc_gps_offset(0.5*(tr_cut.tmin+tr_cut.tmax)))
yield tr_cut
except trace.NoData:
pass
else:
tr.shift(util.utc_gps_offset(0.5*(tr.tmin+tr.tmax)))
yield tr
def iload(fn, load_data=True, interpolation='sinc'):
from pyrocko import datacube_ext
from pyrocko import signal_ext
if interpolation not in ('sinc', 'off'):
raise NotImplementedError(
'no such interpolation method: %s' % interpolation)
with open(fn, 'rb') as f:
if load_data:
loadflag = 2
else:
loadflag = 1
try:
header, data_arrays, gps_tags, nsamples, _ = datacube_ext.load(
f.fileno(), loadflag, 0, -1, None)
except datacube_ext.DataCubeError as e:
e = DataCubeError(str(e))
e.set_context('filename', fn)
raise e
header = dict(header)
deltat = 1.0 / int(header['S_RATE'])
nchannels = int(header['CH_NUM'])
ipos, t, fix, nsvs, header_, offset_, nsamples_ = \
get_extended_timing_context(fn)
tmin, tmax, icontrol, tcontrol, _ = analyse_gps_tags(
header_, (ipos, t, fix, nsvs), offset_, nsamples_)
if icontrol is None:
logger.warn(
'No usable GPS timestamps found. Using datacube header '
'information to guess time. (file: "%s")' % fn)
tmin_ip = round(tmin / deltat) * deltat
if interpolation != 'off':
tmax_ip = round(tmax / deltat) * deltat
else:
tmax_ip = tmin_ip + (nsamples-1) * deltat
nsamples_ip = int(round((tmax_ip - tmin_ip)/deltat)) + 1
# to prevent problems with rounding errors:
tmax_ip = tmin_ip + (nsamples_ip-1) * deltat
leaps = num.array(
[x[0] + util.gps_utc_offset(x[0]) for x in util.read_leap_seconds2()],
dtype=num.float)
if load_data and icontrol is not None:
ncontrol_this = num.sum(
num.logical_and(0 <= icontrol, icontrol < nsamples))
if ncontrol_this <= 1:
logger.warn(
'Extrapolating GPS time information from directory context '
'(insufficient number of GPS timestamps in file: "%s").' % fn)
for i in range(nchannels):
if load_data:
arr = data_arrays[i]
assert arr.size == nsamples
if interpolation == 'sinc' and icontrol is not None:
ydata = num.empty(nsamples_ip, dtype=num.float)
try:
signal_ext.antidrift(
icontrol, tcontrol,
arr.astype(num.float), tmin_ip, deltat, ydata)
except signal_ext.Error as e:
e = DataCubeError(str(e))
e.set_context('filename', fn)
e.set_context('n_control_points', icontrol.size)
e.set_context('n_samples_raw', arr.size)
e.set_context('n_samples_ip', ydata.size)
e.set_context('tmin_ip', util.time_to_str(tmin_ip))
raise e
ydata = num.round(ydata).astype(arr.dtype)
else:
ydata = arr
tr_tmin = tmin_ip
tr_tmax = None
else:
ydata = None
tr_tmin = tmin_ip
tr_tmax = tmax_ip
tr = trace.Trace('', header['DEV_NO'], '', 'p%i' % i, deltat=deltat,
ydata=ydata, tmin=tr_tmin, tmax=tr_tmax, meta=header)
bleaps = num.logical_and(tmin_ip <= leaps, leaps < tmax_ip)
if num.any(bleaps):
assert num.sum(bleaps) == 1
tcut = leaps[bleaps][0]
for tmin_cut, tmax_cut in [
(tr.tmin, tcut), (tcut, tr.tmax+tr.deltat)]:
try:
tr_cut = tr.chop(tmin_cut, tmax_cut, inplace=False)
tr_cut.shift(
util.utc_gps_offset(0.5*(tr_cut.tmin+tr_cut.tmax)))
yield tr_cut
except trace.NoData:
pass
else:
tr.shift(util.utc_gps_offset(0.5*(tr.tmin+tr.tmax)))
yield tr
def iload(fn, load_data=True, interpolation='sinc'):
from pyrocko import datacube_ext
from pyrocko import signal_ext
if interpolation not in ('sinc', 'off'):
raise NotImplemented('no such interpolation method: %s' %
interpolation)
with open(fn, 'rb') as f:
if load_data:
loadflag = 2
else:
if interpolation == 'off':
loadflag = 0
else:
# must get correct nsamples if interpolation is off
loadflag = 1
try:
header, data_arrays, gps_tags, nsamples, _ = datacube_ext.load(
f.fileno(), loadflag, 0, -1, None)
except datacube_ext.DataCubeError as e:
e = DataCubeError(str(e))
e.set_context('filename', fn)
raise e
header = dict(header)
deltat = 1.0 / int(header['S_RATE'])
nchannels = int(header['CH_NUM'])
ipos, t, fix, nsvs, header_, offset_, nsamples_ = \
get_extended_timing_context(fn)
tmin, tmax, icontrol, tcontrol = analyse_gps_tags(header_,
(ipos, t, fix, nsvs),
offset_, nsamples_)
tmin_ip = round(tmin / deltat) * deltat
if interpolation != 'off':
tmax_ip = round(tmax / deltat) * deltat
else:
tmax_ip = tmin_ip + (nsamples - 1) * deltat
nsamples_ip = int(round((tmax_ip - tmin_ip) / deltat)) + 1
# to prevent problems with rounding errors:
tmax_ip = tmin_ip + (nsamples_ip - 1) * deltat
leaps = num.array(
[x[0] + util.gps_utc_offset(x[0]) for x in util.read_leap_seconds2()],
dtype=num.float)
for i in range(nchannels):
if load_data:
arr = data_arrays[i]
assert arr.size == nsamples
if interpolation == 'sinc' and icontrol is not None:
ydata = num.empty(nsamples_ip, dtype=num.float)
signal_ext.antidrift(icontrol, tcontrol, arr.astype(num.float),
tmin_ip, deltat, ydata)
ydata = num.round(ydata).astype(arr.dtype)
else:
ydata = arr
tr_tmin = tmin_ip
tr_tmax = None
else:
ydata = None
tr_tmin = tmin_ip
tr_tmax = tmax_ip
tr = trace.Trace('',
header['DEV_NO'],
'',
'p%i' % i,
deltat=deltat,
ydata=ydata,
tmin=tr_tmin,
tmax=tr_tmax,
meta=header)
bleaps = num.logical_and(tmin_ip <= leaps, leaps < tmax_ip)
if num.any(bleaps):
assert num.sum(bleaps) == 1
tcut = leaps[bleaps][0]
for tmin_cut, tmax_cut in [(tr.tmin, tcut),
(tcut, tr.tmax + tr.deltat)]:
try:
tr_cut = tr.chop(tmin_cut, tmax_cut, inplace=False)
tr_cut.shift(
util.utc_gps_offset(0.5 * (tr_cut.tmin + tr_cut.tmax)))
yield tr_cut
except trace.NoData:
pass
else:
tr.shift(util.utc_gps_offset(0.5 * (tr.tmin + tr.tmax)))
yield tr
def iload(fn, load_data=True, interpolation='sinc'):
from pyrocko import datacube_ext
from pyrocko import signal_ext
if interpolation not in ('sinc', 'off'):
raise NotImplemented(
'no such interpolation method: %s' % interpolation)
with open(fn, 'r') as f:
if load_data:
loadflag = 2
else:
if interpolation == 'off':
loadflag = 0
else:
# must get correct nsamples if interpolation is off
loadflag = 1
header, data_arrays, gps_tags, nsamples, _ = datacube_ext.load(
f.fileno(), loadflag, 0, -1, None)
header = dict(header)
deltat = 1.0 / int(header['S_RATE'])
nchannels = int(header['CH_NUM'])
tmin, tmax, icontrol, tcontrol = analyse_gps_tags(
header, gps_tags, nsamples)
tmin_ip = round(tmin / deltat) * deltat
if interpolation != 'off':
tmax_ip = round(tmax / deltat) * deltat
else:
tmax_ip = tmin_ip + (nsamples-1) * deltat
nsamples_ip = int(round((tmax_ip - tmin_ip)/deltat)) + 1
# to prevent problems with rounding errors:
tmax_ip = tmin_ip + (nsamples_ip-1) * deltat
for i in range(nchannels):
if load_data:
arr = data_arrays[i]
assert arr.size == nsamples
if interpolation == 'sinc' and icontrol is not None:
ydata = num.empty(nsamples_ip, dtype=num.float)
signal_ext.antidrift(
icontrol, tcontrol,
arr.astype(num.float), tmin_ip, deltat, ydata)
ydata = num.round(ydata).astype(arr.dtype)
else:
ydata = arr
tr_tmin = tmin_ip
tr_tmax = None
else:
ydata = None
tr_tmin = tmin_ip
tr_tmax = tmax_ip
toff = util.gps_utc_offset(tmin_ip)
tr_tmin -= toff
if tr_tmax is not None:
tr_tmax -= toff
tr = trace.Trace('', header['DEV_NO'], '', 'p%i' % i, deltat=deltat,
ydata=ydata, tmin=tr_tmin, tmax=tr_tmax, meta=header)
yield tr