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Fix quantified/units-on-attribute mixtures in tests and derivative calculations for xarray 0.16.0 #1431

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dopplershift merged 2 commits into from
Jul 28, 2020
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Fix quantified/units-on-attribute mixtures in tests and derivative calculations for xarray 0.16.0 #1431

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bd71853
Fix quantified/units-on-attribute mixtures for xarray 0.16.0
jthielen Jul 28, 2020
3b6c01c
MNT:(deps): Bump xarray from 0.15.1 to 0.16.0 in /ci
dependabot[bot] Jul 27, 2020
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2 changes: 1 addition & 1 deletion ci/Current.txt
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Original file line number Diff line number Diff line change
Expand Up @@ -2,7 +2,7 @@ matplotlib==3.2.1
numpy==1.19.1
scipy==1.5.2
pint==0.14
xarray==0.15.1
xarray==0.16.0
traitlets==4.3.3
pooch==1.1.1
pandas==1.0.5
11 changes: 2 additions & 9 deletions src/metpy/calc/tools.py
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Expand Up @@ -928,10 +928,7 @@ def wrapper(f, **kwargs):

# Calculate and return result as a DataArray
result = func(f.metpy.unit_array, **new_kwargs)
return xr.DataArray(result.magnitude,
coords=f.coords,
dims=f.dims,
attrs={'units': str(result.units)})
return xr.DataArray(result, coords=f.coords, dims=f.dims)
else:
# Error
raise ValueError('Must specify either "x" or "delta" for value positions when "f" '
Expand Down Expand Up @@ -1218,11 +1215,7 @@ def laplacian(f, **kwargs):
pos_kwarg, positions, axes = _process_gradient_args(f, kwargs)
derivs = [second_derivative(f, axis=axis, **{pos_kwarg: positions[ind]})
for ind, axis in enumerate(axes)]
laplac = sum(derivs)
if isinstance(derivs[0], xr.DataArray):
# Patch in the units that are dropped
laplac.attrs['units'] = derivs[0].attrs['units']
return laplac
return sum(derivs)


def _broadcast_to_axis(arr, axis, ndim):
Expand Down
6 changes: 3 additions & 3 deletions tests/calc/test_basic.py
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Expand Up @@ -696,10 +696,10 @@ def test_smooth_window_1d_dataarray():
smoothed = smooth_window(temperature, window=np.ones(3) / 3, normalize_weights=False)
truth = xr.DataArray(
[37., 34.33333333, 31.66666667, 30.33333333, 27., 26., 24.66666667,
25.66666667, 27., 30.],
25.66666667, 27., 30.] * units.degF,
dims=('time',),
coords={'time': pd.date_range('2020-01-01', periods=10, freq='H')},
attrs={'units': 'degF'})
coords={'time': pd.date_range('2020-01-01', periods=10, freq='H')}
)
xr.testing.assert_allclose(smoothed, truth)


Expand Down
20 changes: 10 additions & 10 deletions tests/calc/test_calc_tools.py
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Expand Up @@ -1087,7 +1087,7 @@ def test_first_derivative_xarray_lonlat(test_da_lonlat):
_, truth = xr.broadcast(test_da_lonlat, partial)
truth.coords['crs'] = test_da_lonlat['crs']
truth.attrs['units'] = 'kelvin / meter'
truth.metpy.quantify()
truth = truth.metpy.quantify()

# Assert result matches expectation
xr.testing.assert_allclose(deriv, truth)
Expand All @@ -1103,7 +1103,7 @@ def test_first_derivative_xarray_time_and_default_axis(test_da_xy):
deriv = first_derivative(test_da_xy)
truth = xr.full_like(test_da_xy, -0.000777000777)
truth.attrs['units'] = 'kelvin / second'
truth.metpy.quantify()
truth = truth.metpy.quantify()

xr.testing.assert_allclose(deriv, truth)
assert deriv.metpy.units == truth.metpy.units
Expand All @@ -1123,7 +1123,7 @@ def test_first_derivative_xarray_time_subsecond_precision():

truth = xr.full_like(test_da, 5.)
truth.attrs['units'] = 'kelvin / second'
truth.metpy.quantify()
truth = truth.metpy.quantify()

xr.testing.assert_allclose(deriv, truth)
assert deriv.metpy.units == truth.metpy.units
Expand All @@ -1141,7 +1141,7 @@ def test_second_derivative_xarray_lonlat(test_da_lonlat):
_, truth = xr.broadcast(test_da_lonlat, partial)
truth.coords['crs'] = test_da_lonlat['crs']
truth.attrs['units'] = 'kelvin / meter^2'
truth.metpy.quantify()
truth = truth.metpy.quantify()

xr.testing.assert_allclose(deriv, truth)
assert deriv.metpy.units == truth.metpy.units
Expand All @@ -1156,11 +1156,11 @@ def test_gradient_xarray(test_da_xy):

truth_x = xr.full_like(test_da_xy, -6.993007e-07)
truth_x.attrs['units'] = 'kelvin / meter'
truth_x.metpy.quantify()
truth_x = truth_x.metpy.quantify()

truth_y = xr.full_like(test_da_xy, -2.797203e-06)
truth_y.attrs['units'] = 'kelvin / meter'
truth_y.metpy.quantify()
truth_y = truth_y.metpy.quantify()

partial = xr.DataArray(
np.array([0.04129204, 0.03330003, 0.02264402]),
Expand All @@ -1169,7 +1169,7 @@ def test_gradient_xarray(test_da_xy):
_, truth_p = xr.broadcast(test_da_xy, partial)
truth_p.coords['crs'] = test_da_xy['crs']
truth_p.attrs['units'] = 'kelvin / hectopascal'
truth_p.metpy.quantify()
truth_p = truth_p.metpy.quantify()

# Assert results match expectations
xr.testing.assert_allclose(deriv_x, truth_x)
Expand All @@ -1195,11 +1195,11 @@ def test_gradient_xarray_implicit_axes(test_da_xy):

truth_x = xr.full_like(data, -6.993007e-07)
truth_x.attrs['units'] = 'kelvin / meter'
truth_x.metpy.quantify()
truth_x = truth_x.metpy.quantify()

truth_y = xr.full_like(data, -2.797203e-06)
truth_y.attrs['units'] = 'kelvin / meter'
truth_y.metpy.quantify()
truth_y = truth_y.metpy.quantify()

xr.testing.assert_allclose(deriv_x, truth_x)
assert deriv_x.metpy.units == truth_x.metpy.units
Expand Down Expand Up @@ -1253,7 +1253,7 @@ def test_laplacian_xarray_lonlat(test_da_lonlat):
_, truth = xr.broadcast(test_da_lonlat, partial)
truth.coords['crs'] = test_da_lonlat['crs']
truth.attrs['units'] = 'kelvin / meter^2'
truth.metpy.quantify()
truth = truth.metpy.quantify()

xr.testing.assert_allclose(laplac, truth)
assert laplac.metpy.units == truth.metpy.units
Expand Down
4 changes: 2 additions & 2 deletions tests/interpolate/test_slices.py
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Expand Up @@ -197,8 +197,8 @@ def test_cross_section_dataset_and_nearest_interp(test_ds_lonlat):
data_cross = cross_section(test_ds_lonlat, start, end, steps=7, interp_type='nearest')
nearest_values = test_ds_lonlat.isel(lat=xr.DataArray([0, 1, 2, 3, 3, 4, 5], dims='index'),
lon=xr.DataArray(range(7), dims='index'))
truth_temp = nearest_values['temperature'].values
truth_rh = nearest_values['relative_humidity'].values
truth_temp = nearest_values['temperature'].metpy.unit_array
truth_rh = nearest_values['relative_humidity'].metpy.unit_array
truth_values_lon = np.array([255.5, 258.20305939, 261.06299342, 264.10041516,
267.3372208, 270.7961498, 274.5])
truth_values_lat = np.array([30.5, 33.02800969, 35.49306226, 37.88512911, 40.19271688,
Expand Down