def test_detrend_1D(
array_dims,
array_shape,
detrend_dim,
chunks,
detrend_type,
trend_amplitude,
linear_error,
):
da_original = noise(array_dims, array_shape)
da_trend = da_original + trend_amplitude * da_original[detrend_dim]
if chunks:
da_trend = da_trend.chunk(chunks)
# bail out if we are expecting an error
if detrend_type == "linear" and linear_error:
with pytest.raises(linear_error):
detrend(da_trend, detrend_dim, detrend_type=detrend_type)
return
detrended = detrend(da_trend, detrend_dim, detrend_type=detrend_type)
assert detrended.chunks == da_trend.chunks
if detrend_type is None:
xrt.assert_equal(detrended, da_trend)
elif detrend_type == "constant":
xrt.assert_allclose(detrended, da_trend - da_trend.mean(dim=detrend_dim))
elif detrend_type == "linear":
xrt.assert_allclose(detrended, da_original)
def test_dim_format(dim, detrend_type):
""" Check that detrend can deal with dim in various formats"""
data = xr.DataArray(
np.random.random([10]),
dims=[dim],
coords={dim: range(10)},
)
dt = detrend(data, dim=dim, detrend_type=detrend_type)
dt = detrend(data, dim=[dim], detrend_type=detrend_type)
def test_detrend_2D(array_dims, array_shape, chunks, detrend_type,
trend_amplitude):
da_original = noise(array_dims, array_shape)
da_trend = (da_original + trend_amplitude["x"] * da_original["x"] +
trend_amplitude["y"] * da_original["y"])
if chunks:
da_trend = da_trend.chunk(chunks)
detrend_dim = ["y", "x"]
detrended = detrend(da_trend, detrend_dim, detrend_type=detrend_type)
assert detrended.chunks == da_trend.chunks
if detrend_type is None:
xrt.assert_equal(detrended, da_trend)
elif detrend_type == "constant":
xrt.assert_allclose(detrended,
da_trend - da_trend.mean(dim=detrend_dim))
elif detrend_type == "linear":
xrt.assert_allclose(detrended, da_original)