def get_live_timeseries():
ts = TimeSeries()
ts.set_live()
ts.dt = 1 / sampling_rate
ts.npts = ts_size
# ts.put('net', 'IU')
ts.put("npts", ts_size)
ts.put("sampling_rate", sampling_rate)
ts.tref = TimeReferenceType.UTC
ts.t0 = datetime.utcnow().timestamp()
ts["delta"] = 0.1
ts["calib"] = 0.1
ts["site_id"] = bson.objectid.ObjectId()
ts["channel_id"] = bson.objectid.ObjectId()
ts["source_id"] = bson.objectid.ObjectId()
ts.set_as_origin("test", "0", "0", AtomicType.TIMESERIES)
ts.data = DoubleVector(np.random.rand(ts_size))
return ts
def get_live_timeseries():
ts = TimeSeries()
ts.set_live()
ts.dt = 1 / sampling_rate
ts.npts = ts_size
# ts.put('net', 'IU')
ts.put('npts', ts_size)
ts.put('sampling_rate', sampling_rate)
ts.tref = TimeReferenceType.UTC
ts.t0 = datetime.utcnow().timestamp()
ts['delta'] = 0.1
ts['calib'] = 0.1
ts['site_id'] = bson.objectid.ObjectId()
ts['channel_id'] = bson.objectid.ObjectId()
ts['source_id'] = bson.objectid.ObjectId()
ts.set_as_origin('test', '0', '0', AtomicType.TIMESERIES)
ts.data = DoubleVector(np.random.rand(ts_size))
return ts
def make_wavelet_noise_data(nscale=0.1,
ns=2048,
padlength=512,
dt=0.05,
npoles=3,
corners=[0.08, 0.8]):
wn = TimeSeries(ns)
wn.t0 = 0.0
wn.dt = dt
wn.tref = TimeReferenceType.Relative
wn.live = True
nd = ns + 2 * padlength
y = nscale * randn(nd)
sos = signal.butter(npoles,
corners,
btype='bandpass',
output='sos',
fs=1.0 / dt)
y = signal.sosfilt(sos, y)
for i in range(ns):
wn.data[i] = y[i + padlength]
return (wn)
def test_TimeSeries():
ts = TimeSeries()
ts.npts = 100
ts.t0 = 0.0
ts.dt = 0.001
ts.live = 1
ts.tref = TimeReferenceType.Relative
ts.data.append(1.0)
ts.data.append(2.0)
ts.data.append(3.0)
ts.data.append(4.0)
ts.sync_npts()
assert ts.npts == 104
assert ts.npts == ts["npts"]
ts += ts
for i in range(4):
ts.data[i] = i * 0.5
ts_copy = pickle.loads(pickle.dumps(ts))
assert ts.data == ts_copy.data
assert ts.data[3] == 1.5
assert ts.data[103] == 8
assert ts.time(100) == 0.1
assert ts.sample_number(0.0998) == 100
def test_operators():
d = _CoreTimeSeries(10)
d1 = make_constant_data_ts(d, nsamp=10)
dsave = _CoreTimeSeries(d1)
d = _CoreTimeSeries(6)
d2 = make_constant_data_ts(d, t0=-0.2, nsamp=6, val=2.0)
dsave = _CoreTimeSeries(d1)
d1 += d2
assert np.allclose(d1.data, [3, 3, 3, 3, 1, 1, 1, 1, 1, 1])
d1 = _CoreTimeSeries(dsave)
d = d1 + d2
assert np.allclose(d.data, [3, 3, 3, 3, 1, 1, 1, 1, 1, 1])
d1 = _CoreTimeSeries(dsave)
d1 *= 2.5
assert np.allclose(d1.data,
[2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5])
d3 = TimeSeries(10)
d4 = TimeSeries(6)
d3 = make_constant_data_ts(d3, nsamp=10)
d4 = make_constant_data_ts(d4, t0=-0.2, nsamp=6, val=2.0)
dsave = _CoreTimeSeries(d3)
d3 = TimeSeries(dsave)
d3 += d4
assert np.allclose(d3.data, [3, 3, 3, 3, 1, 1, 1, 1, 1, 1])
d3 = TimeSeries(dsave)
d = d3 + d4
assert np.allclose(d.data, [3, 3, 3, 3, 1, 1, 1, 1, 1, 1])
d1 = _CoreTimeSeries(dsave)
d3 = TimeSeries(dsave)
d3 *= 2.5
assert np.allclose(d3.data,
[2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5])
x = np.linspace(-0.7, 1.2, 20)
for t in x:
d3 = TimeSeries(dsave)
d4.t0 = t
d3 += d4
# These are selected asserts of the incremental test above
# visually d4 moves through d3 as the t0 value advance. Assert
# tests end member: skewed left, inside, and skewed right
d3 = TimeSeries(dsave)
d4.t0 = -0.7 # no overlap test
d3 += d4
assert np.allclose(d3.data, [1, 1, 1, 1, 1, 1, 1, 1, 1, 1])
d3 = TimeSeries(dsave)
d4.t0 = -0.3 # overlap left
d3 += d4
assert np.allclose(d3.data, [3, 3, 3, 1, 1, 1, 1, 1, 1, 1])
d3 = TimeSeries(dsave)
d4.t0 = 0.3 # d4 inside d3 test
d3 += d4
assert np.allclose(d3.data, [1, 1, 1, 3, 3, 3, 3, 3, 3, 1])
d3 = TimeSeries(dsave)
d4.t0 = 0.7 # partial overlap right
d3 += d4
assert np.allclose(d3.data, [1, 1, 1, 1, 1, 1, 1, 3, 3, 3])
d3 = TimeSeries(dsave)
d4.t0 = 1.0 # no overlap test right
d3 += d4
assert np.allclose(d3.data, [1, 1, 1, 1, 1, 1, 1, 1, 1, 1])
# Repeat the same test for Seismogram objects
# This section is edited cut-paste of above
# Intentionally do not test _CoreSeismogram directly because
# currently if it works for Seismogram it will for _CoreSeismogram
d = _CoreSeismogram(10)
d1 = make_constant_data_seis(d, nsamp=10)
dsave = _CoreSeismogram(d1)
d = _CoreSeismogram(6)
d2 = make_constant_data_seis(d, t0=-0.2, nsamp=6, val=2.0)
dsave = _CoreSeismogram(d1)
d1 += d2
assert np.allclose(
d1.data,
np.array([
[3.0, 3.0, 3.0, 3.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
[3.0, 3.0, 3.0, 3.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
[3.0, 3.0, 3.0, 3.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
]),
)
d1 = _CoreSeismogram(dsave)
d = d1 + d2
assert np.allclose(
d.data,
np.array([
[3.0, 3.0, 3.0, 3.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
[3.0, 3.0, 3.0, 3.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
[3.0, 3.0, 3.0, 3.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
]),
)
d1 = _CoreSeismogram(dsave)
d1 *= 2.5
assert np.allclose(
d1.data,
np.array([
[2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5],
[2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5],
[2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5],
]),
)
d3 = Seismogram(10)
d4 = Seismogram(6)
d3 = make_constant_data_seis(d3, nsamp=10)
d4 = make_constant_data_seis(d4, t0=-0.2, nsamp=6, val=2.0)
dsave = Seismogram(d3)
d3 += d4
assert np.allclose(
d3.data,
np.array([
[3.0, 3.0, 3.0, 3.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
[3.0, 3.0, 3.0, 3.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
[3.0, 3.0, 3.0, 3.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
]),
)
d3 = Seismogram(dsave)
d = d3 + d4
assert np.allclose(
d.data,
np.array([
[3.0, 3.0, 3.0, 3.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
[3.0, 3.0, 3.0, 3.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
[3.0, 3.0, 3.0, 3.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
]),
)
d3 = Seismogram(dsave)
d3 *= 2.5
assert np.allclose(
d1.data,
np.array([
[2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5],
[2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5],
[2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5, 2.5],
]),
)
x = np.linspace(-0.7, 1.2, 20)
for t in x:
d3 = Seismogram(dsave)
d4.t0 = t
d3 += d4
# These are selected asserts of the incremental test above
# visually d4 moves through d3 as the t0 value advance. Assert
# tests end member: skewed left, inside, and skewed right
d3 = Seismogram(dsave)
d4.t0 = -0.7 # no overlap test
d3 += d4
assert np.allclose(
d3.data,
np.array([
[1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
[1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
[1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
]),
)
d3 = Seismogram(dsave)
d4.t0 = -0.3 # overlap left
d3 += d4
assert np.allclose(
d3.data,
np.array([
[3, 3, 3, 1, 1, 1, 1, 1, 1, 1],
[3, 3, 3, 1, 1, 1, 1, 1, 1, 1],
[3, 3, 3, 1, 1, 1, 1, 1, 1, 1],
]),
)
d3 = Seismogram(dsave)
d4.t0 = 0.3 # d4 inside d3 test
d3 += d4
assert np.allclose(
d3.data,
np.array([
[1, 1, 1, 3, 3, 3, 3, 3, 3, 1],
[1, 1, 1, 3, 3, 3, 3, 3, 3, 1],
[1, 1, 1, 3, 3, 3, 3, 3, 3, 1],
]),
)
d3 = Seismogram(dsave)
d4.t0 = 0.7 # partial overlap right
d3 += d4
assert np.allclose(
d3.data,
np.array([
[1, 1, 1, 1, 1, 1, 1, 3, 3, 3],
[1, 1, 1, 1, 1, 1, 1, 3, 3, 3],
[1, 1, 1, 1, 1, 1, 1, 3, 3, 3],
]),
)
d3 = Seismogram(dsave)
d4.t0 = 1.0 # no overlap test right
d3 += d4
assert np.allclose(
d3.data,
np.array([
[1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
[1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
[1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
]),
)
# Repeat exactly for - test but different numeric results
# just omit *= tests
d = _CoreTimeSeries(10)
d1 = make_constant_data_ts(d, nsamp=10)
dsave = _CoreTimeSeries(d1)
d = _CoreTimeSeries(6)
d2 = make_constant_data_ts(d, t0=-0.2, nsamp=6, val=2.0)
dsave = _CoreTimeSeries(d1)
d1 -= d2
assert np.allclose(d1.data, [-1, -1, -1, -1, 1, 1, 1, 1, 1, 1])
d1 = _CoreTimeSeries(dsave)
d = d1 - d2
assert np.allclose(d.data, [-1, -1, -1, -1, 1, 1, 1, 1, 1, 1])
d3 = TimeSeries(10)
d4 = TimeSeries(6)
d3 = make_constant_data_ts(d3, nsamp=10)
d4 = make_constant_data_ts(d4, t0=-0.2, nsamp=6, val=2.0)
dsave = _CoreTimeSeries(d3)
d3 = TimeSeries(dsave)
d3 -= d4
assert np.allclose(d3.data, [-1, -1, -1, -1, 1, 1, 1, 1, 1, 1])
d3 = TimeSeries(dsave)
d = d3 - d4
assert np.allclose(d.data, [-1, -1, -1, -1, 1, 1, 1, 1, 1, 1])
x = np.linspace(-0.7, 1.2, 20)
for t in x:
d3 = TimeSeries(dsave)
d4.t0 = t
d3 -= d4
# These are selected asserts of the incremental test above
# visually d4 moves through d3 as the t0 value advance. Assert
# tests end member: skewed left, inside, and skewed right
d3 = TimeSeries(dsave)
d4.t0 = -0.7 # no overlap test
d3 -= d4
assert np.allclose(d3.data, [1, 1, 1, 1, 1, 1, 1, 1, 1, 1])
d3 = TimeSeries(dsave)
d4.t0 = -0.3 # overlap left
d3 -= d4
assert np.allclose(d3.data, [-1, -1, -1, 1, 1, 1, 1, 1, 1, 1])
d3 = TimeSeries(dsave)
d4.t0 = 0.3 # d4 inside d3 test
d3 -= d4
assert np.allclose(d3.data, [1, 1, 1, -1, -1, -1, -1, -1, -1, 1])
d3 = TimeSeries(dsave)
d4.t0 = 0.7 # partial overlap right
d3 -= d4
assert np.allclose(d3.data, [1, 1, 1, 1, 1, 1, 1, -1, -1, -1])
d3 = TimeSeries(dsave)
d4.t0 = 1.0 # no overlap test right
d3 -= d4
assert np.allclose(d3.data, [1, 1, 1, 1, 1, 1, 1, 1, 1, 1])
# Repeat the same test for Seismogram objects
# This section is edited cut-paste of above
# Intentionally do not test _CoreSeismogram directly because
# currently if it works for Seismogram it will for _CoreSeismogram
d = _CoreSeismogram(10)
d1 = make_constant_data_seis(d, nsamp=10)
dsave = _CoreSeismogram(d1)
d = _CoreSeismogram(6)
d2 = make_constant_data_seis(d, t0=-0.2, nsamp=6, val=2.0)
dsave = _CoreSeismogram(d1)
d1 -= d2
assert np.allclose(
d1.data,
np.array([
[-1.0, -1.0, -1.0, -1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
[-1.0, -1.0, -1.0, -1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
[-1.0, -1.0, -1.0, -1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
]),
)
d1 = _CoreSeismogram(dsave)
d = d1 - d2
assert np.allclose(
d.data,
np.array([
[-1.0, -1.0, -1.0, -1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
[-1.0, -1.0, -1.0, -1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
[-1.0, -1.0, -1.0, -1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
]),
)
d3 = Seismogram(10)
d4 = Seismogram(6)
d3 = make_constant_data_seis(d3, nsamp=10)
d4 = make_constant_data_seis(d4, t0=-0.2, nsamp=6, val=2.0)
dsave = Seismogram(d3)
d3 -= d4
assert np.allclose(
d3.data,
np.array([
[-1.0, -1.0, -1.0, -1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
[-1.0, -1.0, -1.0, -1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
[-1.0, -1.0, -1.0, -1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
]),
)
d3 = Seismogram(dsave)
d = d3 - d4
assert np.allclose(
d.data,
np.array([
[-1.0, -1.0, -1.0, -1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
[-1.0, -1.0, -1.0, -1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
[-1.0, -1.0, -1.0, -1.0, 1.0, 1.0, 1.0, 1.0, 1.0, 1.0],
]),
)
x = np.linspace(-0.7, 1.2, 20)
for t in x:
d3 = Seismogram(dsave)
d4.t0 = t
d3 -= d4
# These are selected asserts of the incremental test above
# visually d4 moves through d3 as the t0 value advance. Assert
# tests end member: skewed left, inside, and skewed right
d3 = Seismogram(dsave)
d4.t0 = -0.7 # no overlap test
d3 -= d4
assert np.allclose(
d3.data,
np.array([
[1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
[1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
[1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
]),
)
d3 = Seismogram(dsave)
d4.t0 = -0.3 # overlap left
d3 -= d4
assert np.allclose(
d3.data,
np.array([
[-1, -1, -1, 1, 1, 1, 1, 1, 1, 1],
[-1, -1, -1, 1, 1, 1, 1, 1, 1, 1],
[-1, -1, -1, 1, 1, 1, 1, 1, 1, 1],
]),
)
d3 = Seismogram(dsave)
d4.t0 = 0.3 # d4 inside d3 test
d3 -= d4
assert np.allclose(
d3.data,
np.array([
[1, 1, 1, -1, -1, -1, -1, -1, -1, 1],
[1, 1, 1, -1, -1, -1, -1, -1, -1, 1],
[1, 1, 1, -1, -1, -1, -1, -1, -1, 1],
]),
)
d3 = Seismogram(dsave)
d4.t0 = 0.7 # partial overlap right
d3 -= d4
assert np.allclose(
d3.data,
np.array([
[1, 1, 1, 1, 1, 1, 1, -1, -1, -1],
[1, 1, 1, 1, 1, 1, 1, -1, -1, -1],
[1, 1, 1, 1, 1, 1, 1, -1, -1, -1],
]),
)
d3 = Seismogram(dsave)
d4.t0 = 1.0 # no overlap test right
d3 -= d4
assert np.allclose(
d3.data,
np.array([
[1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
[1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
[1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
]),
)