def comp_ppsd(sta, debug=True):
net = "IU"
for chan in chans:
print('On:' + sta + ' ' + chan)
stime = UTCDateTime('2016-280T00:00:00')
etime = UTCDateTime('2019-280T00:00:00')
ctime = stime
if sta == 'QSPA':
sen = 3.43 * 10**9
else:
sen = 41.943
paz = {'gain': 1., 'poles': [], 'zeros': [], 'sensitivity': sen}
while ctime < etime:
if debug:
print(ctime)
try:
#if True:
st = Stream()
nctime = ctime
for addday in range(5):
nctime = ctime + addday * 24 * 60 * 60
st += read('/msd/' + net + '_' + sta + '/' +
str(nctime.year) + '/' +
str(nctime.julday).zfill(3) + '/*' + chan + '*')
if debug:
print(st)
except:
ctime += 5 * 24 * 60 * 60
continue
st.merge(fill_value=0)
if 'ppsd' not in vars():
ppsd = PPSD(st[0].stats,
paz,
db_bins=(-100, 100, 1.),
ppsd_length=2**14,
period_smoothing_width_octaves=0.50,
special_handling="ringlaser")
ppsd.add(st)
ctime += 5 * 24 * 60 * 60
ppsd.save_npz('PDF_DATA_' + net + '_' + sta + '_' + chan + ".npz")
ppsd.plot(filename='PPSD_' + net + '_' + sta + '_' + chan + '.PNG',
show_noise_models=False,
period_lim=(2., 1000.))
del ppsd
return
def test_ppsd_add_npz(self):
"""
Test PPSD.add_npz().
"""
# set up a bogus PPSD, with fixed random psds but with real start times
# of psd pieces, to facilitate testing the stack selection.
ppsd = PPSD(stats=Stats(dict(sampling_rate=150)),
metadata=None,
db_bins=(-200, -50, 20.),
period_step_octaves=1.4)
_times_processed = np.load(
os.path.join(self.path, "ppsd_times_processed.npy")).tolist()
# change data to nowadays used nanoseconds POSIX timestamp
_times_processed = [UTCDateTime(t)._ns for t in _times_processed]
np.random.seed(1234)
_binned_psds = [
arr for arr in np.random.uniform(-200, -50, (
len(_times_processed), len(ppsd.period_bin_centers)))
]
with NamedTemporaryFile(suffix=".npz") as tf1, \
NamedTemporaryFile(suffix=".npz") as tf2, \
NamedTemporaryFile(suffix=".npz") as tf3:
# save data split up over three separate temporary files
ppsd._times_processed = _times_processed[:200]
ppsd._binned_psds = _binned_psds[:200]
ppsd.save_npz(tf1.name)
ppsd._times_processed = _times_processed[200:400]
ppsd._binned_psds = _binned_psds[200:400]
ppsd.save_npz(tf2.name)
ppsd._times_processed = _times_processed[400:]
ppsd._binned_psds = _binned_psds[400:]
ppsd.matplotlib_version = "X.X.X"
ppsd.save_npz(tf3.name)
# now load these saved npz files and check if all data is present
ppsd = PPSD.load_npz(tf1.name, metadata=None)
ppsd.add_npz(tf2.name)
# we changed a version number so this should emit a warning
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
ppsd.add_npz(tf3.name)
self.assertEqual(len(w), 1)
np.testing.assert_array_equal(_binned_psds, ppsd._binned_psds)
np.testing.assert_array_equal(_times_processed,
ppsd._times_processed)
# adding data already present should also emit a warning and the
# PPSD should not be changed
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
ppsd.add_npz(tf2.name)
self.assertEqual(len(w), 1)
np.testing.assert_array_equal(_binned_psds, ppsd._binned_psds)
np.testing.assert_array_equal(_times_processed,
ppsd._times_processed)
def test_ppsd_add_npz(self):
"""
Test PPSD.add_npz().
"""
# set up a bogus PPSD, with fixed random psds but with real start times
# of psd pieces, to facilitate testing the stack selection.
ppsd = PPSD(stats=Stats(dict(sampling_rate=150)), metadata=None,
db_bins=(-200, -50, 20.), period_step_octaves=1.4)
_times_processed = np.load(
os.path.join(self.path, "ppsd_times_processed.npy")).tolist()
# change data to nowadays used nanoseconds POSIX timestamp
_times_processed = [UTCDateTime(t)._ns for t in _times_processed]
np.random.seed(1234)
_binned_psds = [
arr for arr in np.random.uniform(
-200, -50,
(len(_times_processed), len(ppsd.period_bin_centers)))]
with NamedTemporaryFile(suffix=".npz") as tf1, \
NamedTemporaryFile(suffix=".npz") as tf2, \
NamedTemporaryFile(suffix=".npz") as tf3:
# save data split up over three separate temporary files
ppsd._times_processed = _times_processed[:200]
ppsd._binned_psds = _binned_psds[:200]
ppsd.save_npz(tf1.name)
ppsd._times_processed = _times_processed[200:400]
ppsd._binned_psds = _binned_psds[200:400]
ppsd.save_npz(tf2.name)
ppsd._times_processed = _times_processed[400:]
ppsd._binned_psds = _binned_psds[400:]
ppsd.matplotlib_version = "X.X.X"
ppsd.save_npz(tf3.name)
# now load these saved npz files and check if all data is present
ppsd = PPSD.load_npz(tf1.name, metadata=None)
ppsd.add_npz(tf2.name)
# we changed a version number so this should emit a warning
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
ppsd.add_npz(tf3.name)
self.assertEqual(len(w), 1)
np.testing.assert_array_equal(_binned_psds, ppsd._binned_psds)
np.testing.assert_array_equal(_times_processed,
ppsd._times_processed)
# adding data already present should also emit a warning and the
# PPSD should not be changed
with warnings.catch_warnings(record=True) as w:
warnings.simplefilter('always')
ppsd.add_npz(tf2.name)
self.assertEqual(len(w), 1)
np.testing.assert_array_equal(_binned_psds, ppsd._binned_psds)
np.testing.assert_array_equal(_times_processed,
ppsd._times_processed)
#st= read(curfile)
#if idx == 0:
#ppsd = PPSD(st[0].stats, paz)
#ppsd.add(st)
#ppsd.save_npz(st[0].id + 'PDF.npz')
debug = True
string = 'newdata/output_raw/2017/XX/FF'
pazNEW = corn_freq_2_paz(4.9, .96)
pazNEW['sensitivity'] = 75900.
chans = ['HHZ', 'HHE', 'HHN']
for idx, chan in enumerate(chans):
st = Stream()
for s in range(1, 9):
if debug:
print('On ' + str(s) + ' ' + chan)
st += read(string + str(s) + '/' + chan + '.D/XX*')
stime = UTCDateTime('2017-05-03T01:10:00.0')
etime = UTCDateTime('2017-05-04T01:10:00.0')
st.trim(starttime=stime, endtime=etime)
st.decimate(4)
st.decimate(2)
print(st)
ppsd = PPSD(st[0].stats, pazNEW)
ppsd.add(st)
ppsd.save_npz(st[0].id + 'PDF.npz')
