def test_single_execution(self):
# stations 21, & 22
# 3 windows say
#
anxcor = Anxcor()
anxcor.set_window_length(120.0)
times = anxcor.get_starttimes(starttime_stamp, endtime_stamp, 0.5)
bank = WavebankWrapper(source_dir)
anxcor.add_dataset(bank, 'nodals')
result = anxcor.process(times)
pairs = list(result.coords['rec'].values) + list(
result.coords['src'].values)
anxcor.align_station_pairs(result)
assert len(pairs) == 6
def test_rotation(self):
# stations 21, & 22
# 3 windows say
#
anxcor = Anxcor(3600)
bank = WavebankWrapper(source_dir)
anxcor.add_dataset(bank, 'nodals')
anxcor.set_task_kwargs('crosscorrelate', dict(dummy_task=True))
result = anxcor.process([starttime_stamp])
rotated_result = anxcor.align_station_pairs(result)
streams = anxcor.xarray_to_obspy(result)
assert len(streams) == 9, 'not enough traces retained!'
def test_dask_align(self):
from distributed import Client, LocalCluster
cluster = LocalCluster(n_workers=1, threads_per_worker=1)
c = Client(cluster)
anxcor = Anxcor()
anxcor.set_window_length(120.0)
times = anxcor.get_starttimes(starttime_stamp, endtime_stamp, 0.5)
bank = WavebankWrapper(source_dir)
anxcor.add_dataset(bank, 'nodals')
result = anxcor.process(times)
pairs = list(result.coords['rec'].values) + list(
result.coords['src'].values)
result = anxcor.align_station_pairs(result, dask_client=c)
c.close()
cluster.close()
assert result is not None
def test_align_algo_z_invariant(self):
se_one_trace = np.asarray([5, 1e-15, 1e-15]).T
nw_one_trace = np.asarray([5, 1e-15, 1e-15])
zne_matrix = np.outer(se_one_trace, nw_one_trace)
result = np.stack([zne_matrix] * 100, axis=2)
result = np.reshape(result, (3, 3, 100, 1, 1))
anxcor = Anxcor()
dataarray = xr.DataArray(
result,
coords={
'rec': ['test_rec'],
'src': ['test_src'],
'src_chan': ['Z', 'N', 'E'],
'rec_chan': ['Z', 'N', 'E'],
'time': np.arange(0, 100)
},
dims=['src_chan', 'rec_chan', 'time', 'rec', 'src'],
name='test_array')
data = dataarray.data
dataset = dataarray.to_dataset()
df = pd.DataFrame([{
'src': 'test_src',
'rec': 'test_rec',
'src_latitude': 0,
'src_longitude': 0,
'rec_latitude': -1 / 200,
'rec_longitude': np.sqrt(3) / 200
}])
dataset.attrs['df'] = df
aligned_result = anxcor.align_station_pairs(dataset)
aligned_array = aligned_result[list(aligned_result.data_vars)[0]]
data = aligned_array.data
assert np.sum(data[0, 0, :, 0, 0]) == 25.0 * 100, 'zz was rotated!!'
assert np.sum(data[0, 0, :, 1,
0]) < 1e-10, 'rotation failed with off diagonal nz'
assert np.sum(data[0, 0, :, 0,
1]) < 1e-10, 'rotation failed with off diagonal zn'
assert np.sum(data[0, 0, :, 2,
0]) < 1e-10, 'rotation failed with off diagonal ez'
assert np.sum(data[0, 0, :, 1,
1]) < 1e-10, 'rotation failed with off diagonal nn'
assert np.sum(data[0, 0, :, 2,
2]) < 1e-10, 'rotation failed with off diagonal ee'
assert np.sum(data[0, 0, :, 0,
2]) < 1e-10, 'rotation failed with off diagonal ze'
def test_align_algo_90_deg_angle_invariant(self):
result = np.ones((3, 3, 100)) * 1e-15
result[1, 1, :] = 2
result[2, 2, :] = 3
result = np.reshape(result, (3, 3, 100, 1, 1))
anxcor = Anxcor()
dataarray = xr.DataArray(
result,
coords={
'rec': ['test_rec'],
'src': ['test_src'],
'src_chan': ['Z', 'N', 'E'],
'rec_chan': ['Z', 'N', 'E'],
'time': np.arange(0, 100)
},
dims=['src_chan', 'rec_chan', 'time', 'rec', 'src'],
name='test_array')
data = dataarray.data
dataset = dataarray.to_dataset()
df = pd.DataFrame([{
'src': 'test_src',
'rec': 'test_rec',
'src_latitude': 0,
'src_longitude': 0,
'rec_latitude': 0,
'rec_longitude': 1
}])
dataset.attrs['df'] = df
aligned_result = anxcor.align_station_pairs(dataset)
aligned_array = aligned_result[list(aligned_result.data_vars)[0]]
data = aligned_array.data
assert np.sum(
data[0, 0, :, 1, 1]
) == 300, 'radial failed to rotate properly under 90 degree rotation'
assert np.sum(
data[0, 0, :, 2, 2]
) == 200, 'transverse failed to rotate properly under 90 degree rotation'
assert np.sum(
data[0, 0, :, 0, 0]
) < 1e-10, 'z component introduced rotation under 90 degree transform'
