def test_ExtractComponent():
seis = Seismogram()
seis.live = 1
seis.data = dmatrix(np.random.rand(3, 6))
seis.npts = 6
ts = []
for i in range(3):
ts.append(ExtractComponent(seis, i))
for i in range(3):
assert (ts[i].data == seis.data[i]).all()
def get_live_seismogram(ts_size=255, sampling_rate=20.0):
seis = Seismogram()
seis.set_live()
seis.set_as_origin("test", "0", "0", AtomicType.SEISMOGRAM)
seis.dt = 1 / sampling_rate
seis.npts = ts_size
# seis.put('net', 'IU')
seis.put("npts", ts_size)
seis.put("sampling_rate", sampling_rate)
seis.tref = TimeReferenceType.UTC
seis.t0 = 0
seis["delta"] = 0.1
seis["calib"] = 0.1
seis["site_id"] = bson.objectid.ObjectId()
seis["source_id"] = bson.objectid.ObjectId()
seis.data = dmatrix(3, ts_size)
for i in range(3):
for j in range(ts_size):
seis.data[i, j] = np.random.rand()
return seis
def get_live_seismogram():
seis = Seismogram()
seis.set_live()
seis.set_as_origin('test', '0', '0', AtomicType.SEISMOGRAM)
seis.dt = 1 / sampling_rate
seis.npts = ts_size
# seis.put('net', 'IU')
seis.put('npts', ts_size)
seis.put('sampling_rate', sampling_rate)
seis.tref = TimeReferenceType.UTC
seis.t0 = 0
seis['delta'] = 0.1
seis['calib'] = 0.1
seis['site_id'] = bson.objectid.ObjectId()
seis['channel_id'] = [bson.objectid.ObjectId()]
seis['source_id'] = bson.objectid.ObjectId()
seis.data = dmatrix(3, ts_size)
for i in range(3):
for j in range(ts_size):
seis.data[i, j] = np.random.rand()
return seis
def test_Seismogram():
seis = Seismogram()
seis.npts = 100
assert seis.data.rows() == 3
assert seis.data.columns() == 100
seis.t0 = 0.0
seis.dt = 0.001
seis.live = 1
seis.tref = TimeReferenceType.Relative
seis.data = dmatrix(np.random.rand(3, 6))
assert seis.npts != 6
seis.sync_npts()
assert seis.npts == 6
assert seis.npts == seis["npts"]
seis.npts = 4
assert seis.data.columns() == 4
seis.npts = 10
assert (seis.data[0:3, 4:10] == 0).all()
seis.data = dmatrix(np.random.rand(3, 100))
seis.sync_npts()
seis_copy = pickle.loads(pickle.dumps(seis))
assert seis_copy.t0 == seis.t0
assert seis_copy.dt == seis.dt
assert seis_copy.live == seis.live
assert seis_copy.tref == seis.tref
assert (seis_copy.data[:] == seis.data[:]).all()
# test the += operator
seis1 = Seismogram(seis)
seis2 = Seismogram(seis)
seis1 += seis2
assert (np.isclose(seis1.data[:], seis.data + seis.data)).all()
seis.npts = 0
assert seis.data.rows() == 0
seis.npts = 100
for i in range(3):
for j in range(100):
if i == 0:
seis.data[i, j] = 1.0
else:
seis.data[i, j] = 0.0
seis.data[0, 1] = 1.0
seis.data[0, 2] = 1.0
seis.data[0, 3] = 0.0
seis.data[1, 1] = 1.0
seis.data[1, 2] = 1.0
seis.data[1, 3] = 0.0
seis.data[2, 1] = 1.0
seis.data[2, 2] = 0.0
seis.data[2, 3] = 1.0
sc = SphericalCoordinate()
sc.phi = 0.0
sc.theta = np.pi / 4
seis.rotate(sc)
assert all(np.isclose(seis.data[:, 3], [0, -0.707107, 0.707107]))
seis.rotate_to_standard()
assert all(seis.data[:, 3] == [0, 0, 1])
sc.phi = -np.pi / 4
seis.data[:, 3] = sc.unit_vector
seis.rotate(sc)
assert all(seis.data[:, 3] == [0, 0, 1])
seis.rotate_to_standard()
assert all(np.isclose(seis.data[:, 3], [0.5, -0.5, 0.707107]))
seis.data[:, 3] = [0, 0, 1]
nu = [np.sqrt(3.0) / 3.0, np.sqrt(3.0) / 3.0, np.sqrt(3.0) / 3.0]
seis.rotate(nu)
assert (np.isclose(
seis.tmatrix,
np.array([
[0.70710678, -0.70710678, 0.0],
[0.40824829, 0.40824829, -0.81649658],
[0.57735027, 0.57735027, 0.57735027],
]),
)).all()
assert all(np.isclose(seis.data[:, 0], [0.707107, 0.408248, 0.57735]))
assert all(np.isclose(seis.data[:, 1], [0, 0, 1.73205]))
seis.rotate_to_standard()
assert all(np.isclose(seis.data[:, 0], [1, 0, 0]))
assert all(np.isclose(seis.data[:, 1], [1, 1, 1]))
nu = [np.sqrt(3.0) / 3.0, np.sqrt(3.0) / 3.0, np.sqrt(3.0) / 3.0]
seis.rotate(SphericalCoordinate(nu))
assert (np.isclose(
seis.tmatrix,
np.array([
[0.70710678, -0.70710678, 0.0],
[0.40824829, 0.40824829, -0.81649658],
[0.57735027, 0.57735027, 0.57735027],
]),
)).all()
assert all(np.isclose(seis.data[:, 0], [0.707107, 0.408248, 0.57735]))
assert all(np.isclose(seis.data[:, 1], [0, 0, 1.73205]))
seis.rotate_to_standard()
assert all(np.isclose(seis.data[:, 0], [1, 0, 0]))
assert all(np.isclose(seis.data[:, 1], [1, 1, 1]))
sc.phi = np.pi / 4
sc.theta = 0.0
seis.rotate(sc)
assert (np.isclose(
seis.tmatrix,
np.array([
[0.70710678, -0.70710678, 0.0],
[0.70710678, 0.70710678, 0.0],
[0.0, 0.0, 1.0],
]),
)).all()
assert all(np.isclose(seis.data[:, 0], [0.707107, 0.707107, 0]))
assert all(np.isclose(seis.data[:, 1], [0, 1.41421, 1]))
assert all(np.isclose(seis.data[:, 2], [0, 1.41421, 0]))
assert all(np.isclose(seis.data[:, 3], [0, 0, 1]))
seis.rotate_to_standard()
# test for serialization of SphericalCoordinate
sc_copy = pickle.loads(pickle.dumps(sc))
assert sc_copy.radius == sc.radius
assert sc_copy.theta == sc.theta
assert sc_copy.phi == sc.phi
a = np.zeros((3, 3))
a[0][0] = 1.0
a[0][1] = 1.0
a[0][2] = 1.0
a[1][0] = -1.0
a[1][1] = 1.0
a[1][2] = 1.0
a[2][0] = 0.0
a[2][1] = -1.0
a[2][2] = 0.0
seis.transform(a)
assert all(np.isclose(seis.data[:, 0], [1, -1, 0]))
assert all(np.isclose(seis.data[:, 1], [3, 1, -1]))
assert all(np.isclose(seis.data[:, 2], [2, 0, -1]))
assert all(np.isclose(seis.data[:, 3], [1, 1, 0]))
seis_copy = pickle.loads(pickle.dumps(seis))
seis_copy.rotate_to_standard()
assert all(np.isclose(seis_copy.data[:, 0], [1, 0, 0]))
assert all(np.isclose(seis_copy.data[:, 1], [1, 1, 1]))
assert all(np.isclose(seis_copy.data[:, 2], [1, 1, 0]))
assert all(np.isclose(seis_copy.data[:, 3], [0, 0, 1]))
seis.rotate_to_standard()
seis.rotate(np.pi / 4)
seis.transform(a)
assert (np.isclose(
seis.tmatrix,
np.array([[1.41421, 0.0, 1], [0.0, 1.41421, 1],
[-0.707107, -0.707107, 0]]),
)).all()
assert all(np.isclose(seis.data[:, 0], [1.41421, 0, -0.707107]))
assert all(np.isclose(seis.data[:, 1], [2.41421, 2.41421, -1.41421]))
assert all(np.isclose(seis.data[:, 2], [1.41421, 1.41421, -1.41421]))
assert all(np.isclose(seis.data[:, 3], [1, 1, 0]))
seis.rotate_to_standard()
assert all(np.isclose(seis.data[:, 0], [1, 0, 0]))
assert all(np.isclose(seis.data[:, 1], [1, 1, 1]))
assert all(np.isclose(seis.data[:, 2], [1, 1, 0]))
assert all(np.isclose(seis.data[:, 3], [0, 0, 1]))
uvec = SlownessVector()
uvec.ux = 0.17085 # cos(-20deg)/5.5
uvec.uy = -0.062185 # sin(-20deg)/5.5
seis.free_surface_transformation(uvec, 5.0, 3.5)
assert (np.isclose(
seis.tmatrix,
np.array([
[-0.171012, -0.469846, 0],
[0.115793, -0.0421458, 0.445447],
[-0.597975, 0.217647, 0.228152],
]),
)).all()
seis.tmatrix = a
assert (seis.tmatrix == a).all()
# test for serialization of SlownessVector
uvec_copy = pickle.loads(pickle.dumps(uvec))
assert uvec_copy.ux == uvec.ux
assert uvec_copy.uy == uvec.uy
assert uvec_copy.azimuth() == uvec.azimuth()
def test_CoreSeismogram():
md = Metadata()
md["delta"] = 0.01
md["starttime"] = 0.0
md["npts"] = 100
# test metadata constructor
md["tmatrix"] = np.random.rand(3, 3)
cseis = _CoreSeismogram(md, False)
assert (cseis.tmatrix == md["tmatrix"]).all()
md["tmatrix"] = dmatrix(np.random.rand(3, 3))
cseis = _CoreSeismogram(md, False)
assert (cseis.tmatrix == md["tmatrix"]).all()
md["tmatrix"] = np.random.rand(9)
cseis = _CoreSeismogram(md, False)
assert (cseis.tmatrix == md["tmatrix"].reshape(3, 3)).all()
md["tmatrix"] = np.random.rand(1, 9)
cseis = _CoreSeismogram(md, False)
assert (cseis.tmatrix == md["tmatrix"].reshape(3, 3)).all()
md["tmatrix"] = np.random.rand(9, 1)
cseis = _CoreSeismogram(md, False)
assert (cseis.tmatrix == md["tmatrix"].reshape(3, 3)).all()
md["tmatrix"] = np.random.rand(3, 3).tolist()
cseis = _CoreSeismogram(md, False)
assert np.isclose(cseis.tmatrix,
np.array(md["tmatrix"]).reshape(3, 3)).all()
md["tmatrix"] = np.random.rand(9).tolist()
cseis = _CoreSeismogram(md, False)
assert np.isclose(cseis.tmatrix,
np.array(md["tmatrix"]).reshape(3, 3)).all()
# test whether the setter of tmatrix updates metadata correctly
tm = np.random.rand(1, 9)
cseis.tmatrix = tm
assert (cseis.tmatrix == tm.reshape(3, 3)).all()
assert np.isclose(cseis.tmatrix,
np.array(cseis["tmatrix"]).reshape(3, 3)).all()
tm = np.random.rand(9).tolist()
cseis.tmatrix = tm
assert np.isclose(cseis.tmatrix, np.array(tm).reshape(3, 3)).all()
assert np.isclose(cseis.tmatrix,
np.array(cseis["tmatrix"]).reshape(3, 3)).all()
# test exceptions
md["tmatrix"] = np.random.rand(4, 2)
with pytest.raises(MsPASSError, match="should be a 3x3 matrix"):
_CoreSeismogram(md, False)
md["tmatrix"] = dmatrix(np.random.rand(2, 4))
with pytest.raises(MsPASSError, match="should be a 3x3 matrix"):
_CoreSeismogram(md, False)
md["tmatrix"] = 42
with pytest.raises(MsPASSError, match="not recognized"):
_CoreSeismogram(md, False)
md.erase("tmatrix")
# tmatrix not defined is taken to default to tmatrix being an identity
# matrix. We test that condition here
cseis = _CoreSeismogram(md, False)
assert np.isclose(cseis.tmatrix, np.eye(3)).all()
md["tmatrix"] = {4: 2}
with pytest.raises(MsPASSError, match="type is not recognized"):
_CoreSeismogram(md, False)
md["tmatrix"] = np.random.rand(9).tolist()
md["tmatrix"][3] = "str"
with pytest.raises(MsPASSError, match="should be float"):
_CoreSeismogram(md, False)
md["tmatrix"] = np.random.rand(3, 4).tolist()
with pytest.raises(MsPASSError, match="should be a 3x3 list of list"):
_CoreSeismogram(md, False)
md["tmatrix"] = [1, 2, 3]
with pytest.raises(MsPASSError, match="should be a 3x3 list of list"):
_CoreSeismogram(md, False)
md["tmatrix"] = np.random.rand(2, 2).tolist()
with pytest.raises(
MsPASSError,
match="should be a list of 9 floats or a 3x3 list of list"):
_CoreSeismogram(md, False)
md["tmatrix"] = np.random.rand(3, 3).tolist()
md["tmatrix"][1][1] = "str"
with pytest.raises(MsPASSError, match="should be float"):
_CoreSeismogram(md, False)
def test_dmatrix():
dm = dmatrix()
assert dm.rows() == 0
dm = dmatrix(9, 4)
assert dm.rows() == 9
assert dm.columns() == 4
assert dm.size == 4 * 9
assert len(dm) == 9
assert dm.shape == (9, 4)
md = [array.array("l", (0 for _ in range(5))) for _ in range(3)]
for i in range(3):
for j in range(5):
md[i][j] = i * 5 + j
dm = dmatrix(md)
assert np.equal(dm, md).all()
dm_c = dmatrix(dm)
assert (dm_c[:] == dm).all()
dm_c.zero()
assert not dm_c[:].any()
md = np.zeros((7, 4), dtype=np.double, order="F")
for i in range(7):
for j in range(4):
md[i][j] = i * 4 + j
dm = dmatrix(md)
assert (dm == md).all()
assert (dm.transpose() == md.transpose()).all()
assert (dm * 3.14 == md * 3.14).all()
assert (2.17 * dm == 2.17 * md).all()
assert (dm * dm.transpose() == np.matmul(md, md.transpose())).all()
with pytest.raises(MsPASSError, match="size mismatch"):
dm * dm
dm_c = dmatrix(dm)
dm += dm_c
assert (dm == md + md).all()
dm += md
assert (dm == md + md + md).all()
assert type(dm) == dmatrix
dm -= dm_c
dm -= dm_c
dm -= md
assert not dm[:].any()
assert type(dm) == dmatrix
dm_c = dmatrix(dm)
md = np.zeros((7, 4), dtype=np.single, order="C")
for i in range(7):
for j in range(4):
md[i][j] = i * 4 + j
dm = dmatrix(md)
assert (dm == md).all()
md = np.zeros((7, 4), dtype=np.int, order="F")
for i in range(7):
for j in range(4):
md[i][j] = i * 4 + j
dm = dmatrix(md)
assert (dm == md).all()
md = np.zeros((7, 4), dtype=np.unicode_, order="C")
for i in range(7):
for j in range(4):
md[i][j] = i * 4 + j
dm = dmatrix(md)
assert (dm == np.float_(md)).all()
md = np.zeros((53, 37), dtype=np.double, order="C")
for i in range(53):
for j in range(37):
md[i][j] = i * 37 + j
dm = dmatrix(md)
assert dm[17, 23] == md[17, 23]
assert (dm[17] == md[17]).all()
assert (dm[::] == md[::]).all()
assert (dm[3::] == md[3::]).all()
assert (dm[:5:] == md[:5:]).all()
assert (dm[::7] == md[::7]).all()
assert (dm[-3::] == md[-3::]).all()
assert (dm[:-5:] == md[:-5:]).all()
assert (dm[::-7] == md[::-7]).all()
assert (dm[11:41:7] == md[11:41:7]).all()
assert (dm[-11:-41:-7] == md[-11:-41:-7]).all()
assert (dm[3::, 13] == md[3::, 13]).all()
assert (dm[19, :5:] == md[19, :5:]).all()
assert (dm[::-7, ::-11] == md[::-7, ::-11]).all()
with pytest.raises(IndexError, match="out of bounds for axis 1"):
dummy = dm[3, 50]
with pytest.raises(IndexError, match="out of bounds for axis 0"):
dummy = dm[80]
with pytest.raises(IndexError, match="out of bounds for axis 1"):
dm[3, 50] = 1.0
with pytest.raises(IndexError, match="out of bounds for axis 0"):
dm[60, 50] = 1
dm[7, 17] = 3.14
assert dm[7, 17] == 3.14
dm[7, 17] = "6.28"
assert dm[7, 17] == 6.28
dm[7] = 10
assert (dm[7] == 10).all()
dm[::] = md
assert (dm == md).all()
dm[:, -7] = 3.14
assert (dm[:, -7] == 3.14).all()
dm[17, :] = 3.14
assert (dm[17, :] == 3.14).all()
dm[3:7, -19:-12] = 3.14
assert (dm[3:7, -19:-12] == 3.14).all()
def setup_function(function):
ts_size = 255
sampling_rate = 20.0
function.dict1 = {
"network": "IU",
"station": "ANMO",
"starttime": obspy.UTCDateTime(2019, 12, 31, 23, 59, 59, 915000),
"npts": ts_size,
"sampling_rate": sampling_rate,
"channel": "BHE",
"live": True,
"_id": bson.objectid.ObjectId(),
"jdate": obspy.UTCDateTime(2019, 12, 31, 23, 59, 59, 915000),
"date_str": obspy.UTCDateTime(2019, 12, 31, 23, 59, 59, 915000),
"not_defined_date": obspy.UTCDateTime(2019, 12, 31, 23, 59, 59,
915000),
}
function.dict2 = {
"network": "IU",
"station": "ANMO",
"starttime": obspy.UTCDateTime(2019, 12, 31, 23, 59, 59, 915000),
"npts": ts_size,
"sampling_rate": sampling_rate,
"channel": "BHN",
}
function.dict3 = {
"network": "IU",
"station": "ANMO",
"starttime": obspy.UTCDateTime(2019, 12, 31, 23, 59, 59, 915000),
"npts": ts_size,
"sampling_rate": sampling_rate,
"channel": "BHZ",
}
function.tr1 = obspy.Trace(data=np.random.randint(0, 1000, ts_size),
header=function.dict1)
function.tr2 = obspy.Trace(data=np.random.randint(0, 1000, ts_size),
header=function.dict2)
function.tr3 = obspy.Trace(data=np.random.randint(0, 1000, ts_size),
header=function.dict3)
function.stream = obspy.Stream(
traces=[function.tr1, function.tr2, function.tr3])
function.md1 = Metadata()
function.md1.put("network", "IU")
function.md1.put("npts", ts_size)
function.md1.put("sampling_rate", sampling_rate)
function.md1.put("live", True)
function.ts1 = TimeSeries()
function.ts1.data = DoubleVector(np.random.rand(ts_size))
function.ts1.live = True
function.ts1.dt = 1 / sampling_rate
function.ts1.t0 = 0
function.ts1.npts = ts_size
# TODO: need to bind the constructor that can do TimeSeries(md1)
function.ts1.put("net", "IU")
function.ts1.put("npts", ts_size)
function.ts1.put("sampling_rate", sampling_rate)
function.seismogram = Seismogram()
# TODO: the default of seismogram.tref is UTC which is inconsistent with the default
# for TimeSeries()
# TODO: It would be nice to have dmatrix support numpy.ndarray as input
function.seismogram.data = dmatrix(3, ts_size)
for i in range(3):
for j in range(ts_size):
function.seismogram.data[i, j] = np.random.rand()
function.seismogram.live = True
function.seismogram.dt = 1 / sampling_rate
function.seismogram.t0 = 0
function.seismogram.npts = ts_size
# FIXME: if the following key is network, the Seismogram2Stream will error out
# when calling TimeSeries2Trace internally due to the issue when mdef.is_defined(k)
# returns True but k is an alias, the mdef.type(k) will error out.
function.seismogram.put("net", "IU")
function.seismogram.put("npts", ts_size)
function.seismogram.put("sampling_rate", sampling_rate)
def test_CoreSeismogram():
md = Metadata()
md['delta'] = 0.01
md['starttime'] = 0.0
md['npts'] = 100
# test metadata constructor
md['tmatrix'] = np.random.rand(3, 3)
cseis = _CoreSeismogram(md, False)
assert (cseis.transformation_matrix == md['tmatrix']).all()
md['tmatrix'] = dmatrix(np.random.rand(3, 3))
cseis = _CoreSeismogram(md, False)
assert (cseis.transformation_matrix == md['tmatrix']).all()
md['tmatrix'] = np.random.rand(9)
cseis = _CoreSeismogram(md, False)
assert (cseis.transformation_matrix == md['tmatrix'].reshape(3, 3)).all()
md['tmatrix'] = np.random.rand(1, 9)
cseis = _CoreSeismogram(md, False)
assert (cseis.transformation_matrix == md['tmatrix'].reshape(3, 3)).all()
md['tmatrix'] = np.random.rand(9, 1)
cseis = _CoreSeismogram(md, False)
assert (cseis.transformation_matrix == md['tmatrix'].reshape(3, 3)).all()
md['tmatrix'] = np.random.rand(3, 3).tolist()
cseis = _CoreSeismogram(md, False)
assert np.isclose(cseis.transformation_matrix,
np.array(md['tmatrix']).reshape(3, 3)).all()
md['tmatrix'] = np.random.rand(9).tolist()
cseis = _CoreSeismogram(md, False)
assert np.isclose(cseis.transformation_matrix,
np.array(md['tmatrix']).reshape(3, 3)).all()
# test whether the setter of transformation_matrix updates metadata correctly
tm = np.random.rand(1, 9)
cseis.transformation_matrix = tm
assert (cseis.transformation_matrix == tm.reshape(3, 3)).all()
assert np.isclose(cseis.transformation_matrix,
np.array(cseis['tmatrix']).reshape(3, 3)).all()
tm = np.random.rand(9).tolist()
cseis.transformation_matrix = tm
assert np.isclose(cseis.transformation_matrix,
np.array(tm).reshape(3, 3)).all()
assert np.isclose(cseis.transformation_matrix,
np.array(cseis['tmatrix']).reshape(3, 3)).all()
# test exceptions
md['tmatrix'] = np.random.rand(4, 2)
with pytest.raises(MsPASSError, match="should be a 3x3 matrix"):
_CoreSeismogram(md, False)
md['tmatrix'] = dmatrix(np.random.rand(2, 4))
with pytest.raises(MsPASSError, match="should be a 3x3 matrix"):
_CoreSeismogram(md, False)
md['tmatrix'] = 42
with pytest.raises(MsPASSError, match="not recognized"):
_CoreSeismogram(md, False)
md.erase('tmatrix')
with pytest.raises(MsPASSError, match="Error trying to extract"):
_CoreSeismogram(md, False)
md['tmatrix'] = {4: 2}
with pytest.raises(MsPASSError, match="type is not recognized"):
_CoreSeismogram(md, False)
md['tmatrix'] = np.random.rand(9).tolist()
md['tmatrix'][3] = 'str'
with pytest.raises(MsPASSError, match="should be float"):
_CoreSeismogram(md, False)
md['tmatrix'] = np.random.rand(3, 4).tolist()
with pytest.raises(MsPASSError, match="should be a 3x3 list of list"):
_CoreSeismogram(md, False)
md['tmatrix'] = [1, 2, 3]
with pytest.raises(MsPASSError, match="should be a 3x3 list of list"):
_CoreSeismogram(md, False)
md['tmatrix'] = np.random.rand(2, 2).tolist()
with pytest.raises(
MsPASSError,
match="should be a list of 9 floats or a 3x3 list of list"):
_CoreSeismogram(md, False)
md['tmatrix'] = np.random.rand(3, 3).tolist()
md['tmatrix'][1][1] = 'str'
with pytest.raises(MsPASSError, match="should be float"):
_CoreSeismogram(md, False)
