def test_numpy_equals_dask():
attrs = {'res': (10.0, 10.0)}
small_numpy_based_data_array = xr.DataArray(elevation, attrs=attrs)
dask_data = da.from_array(elevation, chunks=(3, 3))
small_das_based_data_array = xr.DataArray(dask_data, attrs=attrs)
numpy_result = hillshade(small_numpy_based_data_array, name='numpy')
dask_result = hillshade(small_das_based_data_array, name='dask')
dask_result.data = dask_result.data.compute()
assert np.isclose(numpy_result, dask_result, equal_nan=True).all()
def test_hillshade_gpu_equals_cpu():
import cupy
small_da = xr.DataArray(elevation, attrs={'res': (10.0, 10.0)})
cpu = hillshade(small_da, name='numpy_result')
small_da_cupy = xr.DataArray(cupy.asarray(elevation),
attrs={'res': (10.0, 10.0)})
gpu = hillshade(small_da_cupy, name='cupy_result')
general_output_checks(small_da_cupy, gpu)
assert np.isclose(cpu.data, gpu.data.get(), equal_nan=True).all()
def test_hillshade_gpu_equals_cpu():
import cupy
small_da = xr.DataArray(elevation, attrs={'res': (10.0, 10.0)})
cpu = hillshade(small_da, name='numpy_result')
small_da_cupy = xr.DataArray(cupy.asarray(elevation), attrs={'res': (10.0, 10.0)})
gpu = hillshade(small_da_cupy, name='cupy_result')
assert isinstance(gpu.data, cupy.ndarray)
assert np.isclose(cpu, gpu, equal_nan=True).all()
def test_hillshade_cpu():
attrs = {'res': (10.0, 10.0)}
small_numpy_based_data_array = xr.DataArray(elevation, attrs=attrs)
numpy_result = hillshade(small_numpy_based_data_array, name='numpy')
dask_data = da.from_array(elevation, chunks=(3, 3))
small_das_based_data_array = xr.DataArray(dask_data, attrs=attrs)
dask_result = hillshade(small_das_based_data_array, name='dask')
general_output_checks(small_das_based_data_array, dask_result)
np.testing.assert_allclose(numpy_result.data,
dask_result.data.compute(),
equal_nan=True)
def create_map2():
global cvs
global terrain
global water
global trees
img = stack(shade(terrain, cmap=['black', 'white'], how='linear'))
yield img.to_pil()
img = stack(shade(terrain, cmap=Elevation, how='linear'))
yield img.to_pil()
img = stack(
shade(terrain, cmap=Elevation, how='linear'),
shade(hillshade(terrain, azimuth=210),
cmap=['black', 'white'],
how='linear',
alpha=128),
)
yield img.to_pil()
img = stack(
shade(terrain, cmap=Elevation, how='linear'),
shade(water, cmap=['aqua', 'white']),
shade(hillshade(terrain, azimuth=210),
cmap=['black', 'white'],
how='linear',
alpha=128),
)
yield img.to_pil()
img = stack(
shade(terrain, cmap=Elevation, how='linear'),
shade(water, cmap=['aqua', 'white']),
shade(hillshade(terrain + trees, azimuth=210),
cmap=['black', 'white'],
how='linear',
alpha=128), shade(tree_colorize, cmap='limegreen', how='linear'))
yield img.to_pil()
yield img.to_pil()
yield img.to_pil()
yield img.to_pil()
def test_hillshade():
"""
Assert Simple Hillshade transfer function
"""
da_gaussian = xr.DataArray(data_gaussian)
da_gaussian_shade = hillshade(da_gaussian, name='hillshade_agg')
general_output_checks(da_gaussian, da_gaussian_shade)
assert da_gaussian_shade.name == 'hillshade_agg'
assert da_gaussian_shade.mean() > 0
assert da_gaussian_shade[60, 60] > 0
def test_hillshade():
"""
Assert Simple Hillshade transfer function
"""
da_gaussian = xr.DataArray(data_gaussian)
da_gaussian_shade = hillshade(da_gaussian)
assert da_gaussian_shade.dims == da_gaussian.dims
assert da_gaussian_shade.coords == da_gaussian.coords
assert da_gaussian_shade.attrs == da_gaussian.attrs
assert da_gaussian_shade.mean() > 0
assert da_gaussian_shade[60, 60] > 0
def test_hillshade():
"""
Assert Simple Hillshade transfer function
"""
da_gaussian = xr.DataArray(data_gaussian)
da_gaussian_shade = hillshade(da_gaussian, name='hillshade_agg')
assert da_gaussian_shade.dims == da_gaussian.dims
assert da_gaussian_shade.attrs == da_gaussian.attrs
assert da_gaussian_shade.name == 'hillshade_agg'
for coord in da_gaussian.coords:
assert np.all(da_gaussian_shade[coord] == da_gaussian[coord])
assert da_gaussian_shade.mean() > 0
assert da_gaussian_shade[60, 60] > 0
def test_hillshade_rtx_with_shadows(data_gaussian):
import cupy
tall_gaussian = 400 * data_gaussian
cpu = hillshade(xr.DataArray(tall_gaussian))
tall_gaussian = cupy.asarray(tall_gaussian)
rtx = hillshade(xr.DataArray(tall_gaussian))
rtx.data = cupy.asnumpy(rtx.data)
assert cpu.shape == rtx.shape
nhalf = cpu.shape[0] // 2
# Quadrant nearest sun direction should be almost identical.
quad_cpu = cpu.data[nhalf::, ::nhalf]
quad_rtx = cpu.data[nhalf::, ::nhalf]
assert_allclose(quad_cpu, quad_rtx, atol=0.03)
# Opposite diagonal should be in shadow.
diag_cpu = np.diagonal(cpu.data[::-1])[nhalf:]
diag_rtx = np.diagonal(rtx.data[::-1])[nhalf:]
assert_array_less(diag_rtx, diag_cpu + 1e-3)
def hillshade(ds, groupby=None, elev_var='topography__elevation', **kwargs):
elev = ds[elev_var]
if groupby is not None:
# TODO: use shortcut=True
# https://github.com/holoviz/datashader/issues/871
hshade = elev.groupby(groupby).apply(xrspatial.hillshade,
shortcut=False,
**kwargs)
else:
hshade = xrspatial.hillshade(elev, **kwargs)
return hshade
def test_numpy_equals_dask():
# input data
data = np.asarray(
[[1432.6542, 1432.4764, 1432.4764, 1432.1207, 1431.9429, np.nan],
[1432.6542, 1432.6542, 1432.4764, 1432.2986, 1432.1207, np.nan],
[1432.832, 1432.6542, 1432.4764, 1432.2986, 1432.1207, np.nan],
[1432.832, 1432.6542, 1432.4764, 1432.4764, 1432.1207, np.nan],
[1432.832, 1432.6542, 1432.6542, 1432.4764, 1432.2986, np.nan],
[1432.832, 1432.6542, 1432.6542, 1432.4764, 1432.2986, np.nan],
[1432.832, 1432.832, 1432.6542, 1432.4764, 1432.4764, np.nan]],
dtype=np.float32)
attrs = {'res': (10.0, 10.0)}
small_numpy_based_data_array = xr.DataArray(data, attrs=attrs)
dask_data = da.from_array(data, chunks=(3, 3))
small_das_based_data_array = xr.DataArray(dask_data, attrs=attrs)
numpy_result = hillshade(small_numpy_based_data_array, name='numpy')
dask_result = hillshade(small_das_based_data_array, name='dask')
dask_result.data = dask_result.data.compute()
assert np.isclose(numpy_result, dask_result, equal_nan=True).all()
def create_map(azimuth):
global cvs
global terrain
global water
global trees
img = stack(
shade(terrain, cmap=Elevation, how='linear'),
shade(water, cmap=['aqua', 'white']),
shade(hillshade(terrain + trees, azimuth=azimuth),
cmap=['black', 'white'],
how='linear',
alpha=128), shade(tree_colorize, cmap='limegreen', how='linear'))
print('image created')
return img.to_pil()
def test_hillshade():
"""
Assert Simple Hillshade transfer function
"""
da_gaussian = xr.DataArray(data_gaussian)
# add crs for tests
da_gaussian = _add_EPSG4326_crs_to_da(da_gaussian)
da_gaussian_shade = hillshade(da_gaussian, name='hillshade_agg')
# test preservation of attrs and coords, including crs
assert da_gaussian_shade.dims == da_gaussian.dims
assert da_gaussian_shade.attrs == da_gaussian.attrs
assert da_gaussian_shade.name == 'hillshade_agg'
for coord in da_gaussian.coords:
assert np.all(da_gaussian_shade[coord] == da_gaussian[coord])
assert da_gaussian_shade.mean() > 0
assert da_gaussian_shade[60, 60] > 0
def time_hillshade(self, nx, type):
shadows = (type == "rtxpy")
hillshade(self.xr, shadows=shadows)
