def test_window():
lon_min = Data.SmallTestData().window()["lon_min"]
lon_max = Data.SmallTestData().window()["lon_max"]
lon_min_ref = 2.5
lon_max_ref = 15.0
isequal = np.allclose(lon_min, lon_min_ref) and \
np.allclose(lon_max, lon_max_ref)
assert isequal
def test_normalize_time_series_array():
ts = np.arange(16).reshape(4, 4).astype("float")
Data.normalize_time_series_array(ts)
mean = ts.mean(axis=0)
std = ts.std(axis=0)
ts = ts[:, 0]
mean_ref = np.array([0., 0., 0., 0.])
std_ref = np.array([1., 1., 1., 1.])
ts_ref = np.array([-1.34164079, -0.4472136, 0.4472136, 1.34164079])
isequal = np.allclose(mean, mean_ref) and np.allclose(std, std_ref) and \
np.allclose(ts, ts_ref)
assert isequal
def test_observable():
obs = Data.SmallTestData().observable()
obs_ref = np.array([[0.00000000e+00, 1.00000000e+00, 1.22464680e-16,
-1.00000000e+00, -2.44929360e-16, 1.00000000e+00],
[3.09016994e-01, 9.51056516e-01, -3.09016994e-01,
-9.51056516e-01, 3.09016994e-01, 9.51056516e-01],
[5.87785252e-01, 8.09016994e-01, -5.87785252e-01,
-8.09016994e-01, 5.87785252e-01, 8.09016994e-01],
[8.09016994e-01, 5.87785252e-01, -8.09016994e-01,
-5.87785252e-01, 8.09016994e-01, 5.87785252e-01],
[9.51056516e-01, 3.09016994e-01, -9.51056516e-01,
-3.09016994e-01, 9.51056516e-01, 3.09016994e-01],
[1.00000000e+00, 1.22464680e-16, -1.00000000e+00,
-2.44929360e-16, 1.00000000e+00, 3.67394040e-16],
[9.51056516e-01, -3.09016994e-01, -9.51056516e-01,
3.09016994e-01, 9.51056516e-01, -3.09016994e-01],
[8.09016994e-01, -5.87785252e-01, -8.09016994e-01,
5.87785252e-01, 8.09016994e-01, -5.87785252e-01],
[5.87785252e-01, -8.09016994e-01, -5.87785252e-01,
8.09016994e-01, 5.87785252e-01, -8.09016994e-01],
[3.09016994e-01, -9.51056516e-01, -3.09016994e-01,
9.51056516e-01, 3.09016994e-01, -9.51056516e-01]])
isequal = np.allclose(obs, obs_ref)
assert isequal
def create_test_data():
# Create test time series
tdata = Data.SmallTestData().observable()
n_index, n_times = tdata.shape
# subtract means form the input data
tdata -= np.mean(tdata, axis=1)[:, None]
# normalize the data
tdata /= np.sqrt(np.sum(tdata * tdata, axis=1))[:, None]
return tdata
def test_cos_window():
ts = np.arange(24).reshape(12, 2)
cw = Data.cos_window(data=ts, gamma=0.75)
cw_ref = np.array([[0., 0.], [0.14644661, 0.14644661], [0.5, 0.5],
[0.85355339, 0.85355339], [1., 1.], [1., 1.], [1., 1.],
[1., 1.], [0.85355339, 0.85355339], [0.5, 0.5],
[0.14644661, 0.14644661], [0., 0.]])
isequal = np.allclose(cw, cw_ref)
assert isequal
def test_zero_pad_data():
ts = np.arange(20).reshape(5, 4)
zpd = Data.zero_pad_data(ts)
zpd_ref = np.array([[0., 0., 0., 0.], [0., 1., 2., 3.], [4., 5., 6., 7.],
[8., 9., 10., 11.], [12., 13., 14., 15.],
[16., 17., 18., 19.], [0., 0., 0., 0.],
[0., 0., 0., 0.]])
isequal = np.allclose(zpd, zpd_ref)
assert isequal
def test_SmallTestData():
res = Data.SmallTestData().observable()
exp = np.array([[0., 1., 0., -1., -0., 1.],
[0.309, 0.9511, -0.309, -0.9511, 0.309, 0.9511],
[0.5878, 0.809, -0.5878, -0.809, 0.5878, 0.809],
[0.809, 0.5878, -0.809, -0.5878, 0.809, 0.5878],
[0.9511, 0.309, -0.9511, -0.309, 0.9511, 0.309],
[1., 0., -1., -0., 1., 0.],
[0.9511, -0.309, -0.9511, 0.309, 0.9511, -0.309],
[0.809, -0.5878, -0.809, 0.5878, 0.809, -0.5878],
[0.5878, -0.809, -0.5878, 0.809, 0.5878, -0.809],
[0.309, -0.9511, -0.309, 0.9511, 0.309, -0.9511]])
assert np.allclose(res, exp, atol=1e-04)
def test_set_window():
data = Data.SmallTestData()
data.set_window(window={"time_min": 0., "time_max": 4., "lat_min": 10.,
"lat_max": 20., "lon_min": 5., "lon_max": 10.})
obs = data.observable()
obs_ref = np.array([[1.22464680e-16, -1.00000000e+00],
[-3.09016994e-01, -9.51056516e-01],
[-5.87785252e-01, -8.09016994e-01],
[-8.09016994e-01, -5.87785252e-01],
[-9.51056516e-01, -3.09016994e-01]])
isequal = np.allclose(obs, obs_ref)
assert isequal
def test_set_global_window():
data = Data.SmallTestData()
data.set_window(window={"time_min": 0., "time_max": 4.,
"lat_min": 10., "lat_max": 20., "lon_min": 5.,
"lon_max": 10.})
lat1 = data.grid.grid()["lat"]
data.set_global_window()
lat2 = data.grid.grid()["lat"]
lat1_ref = np.array([10., 15.], dtype=np.float32)
lat2_ref = np.array([0., 5., 10., 15., 20., 25.], dtype=np.float32)
isequal = np.allclose(lat1, lat1_ref) and np.allclose(lat2, lat2_ref)
assert isequal
def test_next_power_2():
isequal = np.allclose(Data.next_power_2(253), 256)
assert isequal
