def generate_test_dataarray(
dims=OrderedDict([('y', 20), ('x', 20), ('time', 10)]),
name='variable',
mean=0, sigma=1,
extent=(-10.0, 50.0, 0.0, 60.0),
random_seed=42,
crs='epsg:4326'):
np.random.seed(random_seed)
coords = OrderedDict()
if 'y' in dims:
coords['y'] = np.linspace(extent[3], extent[1], dims['y'])
if 'x' in dims:
coords['x'] = np.linspace(extent[0], extent[2], dims['x'])
if 'time' in dims:
coords['time'] = pd.date_range('2017-01-01', '2018-01-01',
periods=dims['time'])
meta = {'attr1': 1, 'attr2': 2, 'attr3': 3}
if 'x' in dims and 'y' in dims:
transform = rasterio.transform.from_bounds(
*extent, width=dims['x']-1, height=dims['y']-1)
meta['crs'] = _parse_crs(crs).to_string()
meta['transform'] = transform[:6]
data = np.random.normal(mean, sigma, tuple(dims.values()))
da = xr.DataArray(data, coords=coords, dims=list(dims.keys()),
name=name, attrs=meta)
return da
def test_reproject_with_extra_dims(dims):
crs1 = warp._parse_crs('epsg:4326')
crs2 = warp._parse_crs('epsg:3395')
ds = generate_test_dataset(
dims=dims, crs=crs1
)
proj = warp.Reprojection(crs=crs2)
reprojected = proj.apply(ds)
# Check that a reprojected slice of the dataset is the same as
# the slice of the reprojection of the entire dataset.
slices = [
{'band': 3},
{'time': slice(1, 3)}
]
for s in slices:
xr_assert_equal(
proj.apply(ds.isel(**s)),
reprojected.isel(**s)
)
def generate_test_dataset(
dims=OrderedDict([('y', 20), ('x', 20), ('time', 10)]),
var=['C11', 'C12__im', 'C12__re', 'C22'],
mean=0, sigma=1,
extent=(-10.0, 50.0, 0.0, 60.0),
random_seed=42,
crs='epsg:4326'):
np.random.seed(random_seed)
coords = OrderedDict()
for name, size in dims.items():
if name == 'y':
coords[name] = np.linspace(extent[3], extent[1], size)
elif name == 'x':
coords[name] = np.linspace(extent[0], extent[2], size)
elif name == 'time':
coords[name] = pd.date_range('2017-01-01', '2018-01-01',
periods=size)
else:
coords[name] = np.arange(size)
meta = {'attr1': 1, 'attr2': 2, 'attr3': 3}
ds = xr.Dataset(coords=coords, attrs=meta)
if 'x' in dims and 'y' in dims:
transform = rasterio.transform.from_bounds(
*extent, width=dims['x']-1, height=dims['y']-1)
ds.attrs['crs'] = _parse_crs(crs).to_string()
ds.attrs['transform'] = transform[:6]
ds.attrs['res'] = (abs(transform.a), abs(transform.e))
ds.attrs['bounds'] = extent
if isinstance(mean, (int, float)):
mean = [mean] * len(var)
for v, m in zip(var, mean):
ds[v] = (tuple(dims.keys()),
np.random.normal(m, sigma, tuple(dims.values())))
return ds
def test_reprojection(name, kwargs):
ds = generate_test_dataset(**kwargs)
crs = warp._parse_crs('epsg:4326')
proj = warp.Reprojection(crs=crs)
reprojected = proj.apply(ds)
assert_equal_crs(crs, warp.get_crs(reprojected))
def test_parse_crs_fails(invalidcrs):
with assert_raises(CRSError):
warp._parse_crs(invalidcrs)
def test_parse_crs(crs):
assert_equal_crs(crs, warp._parse_crs(crs))
assert_equal_crs(crs, warp._parse_crs(crs.to_string()))
assert_equal_crs(crs, warp._parse_crs(crs.to_dict()))
assert_equal_crs(crs, warp._parse_crs(crs.wkt))
assert_equal_crs(crs, warp._parse_crs(crs.to_epsg()))