def test_read_from_broken_source():
crs = geometry.CRS('EPSG:4326')
shape = (2, 2)
no_data = -1
source1 = FakeDatasetSource(value=[[1, 1], [no_data, no_data]],
crs=crs,
band_source_class=BrokenBandDataSource)
source2 = FakeDatasetSource(value=[[2, 2], [2, 2]], crs=crs)
sources = [source1, source2]
output_data = np.full(shape, fill_value=no_data, dtype='int16')
# Check exception is raised
with pytest.raises(OSError):
reproject_and_fuse(sources,
output_data,
dst_transform=identity,
dst_projection=crs,
dst_nodata=no_data)
# Check can ignore errors
reproject_and_fuse(sources,
output_data,
dst_transform=identity,
dst_projection=crs,
dst_nodata=no_data,
skip_broken_datasets=True)
assert (output_data == [[2, 2], [2, 2]]).all()
def test_read_from_broken_source():
crs = mock.MagicMock()
shape = (2, 2)
no_data = -1
source1 = _mock_datasetsource([[1, 1], [no_data, no_data]],
crs=crs,
shape=shape)
source2 = _mock_datasetsource([[2, 2], [2, 2]], crs=crs, shape=shape)
sources = [source1, source2]
rio_reader = source1.open.return_value.__enter__.return_value
rio_reader.read.side_effect = OSError('Read or write failed')
output_data = numpy.full(shape, fill_value=no_data, dtype='int16')
# Check exception is raised
with pytest.raises(OSError):
reproject_and_fuse(sources,
output_data,
dst_transform=identity,
dst_projection=crs,
dst_nodata=no_data)
# Check can ignore errors
reproject_and_fuse(sources,
output_data,
dst_transform=identity,
dst_projection=crs,
dst_nodata=no_data,
skip_broken_datasets=True)
assert (output_data == [[2, 2], [2, 2]]).all()
def _fuse_measurement(dest, datasets, geobox, measurement,
skip_broken_datasets=False,
fuse_func=None):
reproject_and_fuse([new_datasource(dataset, measurement['name']) for dataset in datasets],
dest,
geobox.affine,
geobox.crs,
dest.dtype.type(measurement['nodata']),
resampling=measurement.get('resampling_method', 'nearest'),
fuse_func=fuse_func,
skip_broken_datasets=skip_broken_datasets)
def test_mixed_result_when_first_source_partially_empty():
crs = mock.MagicMock()
shape = (2, 2)
no_data = -1
source1 = _mock_datasetsource([[1, 1], [no_data, no_data]], crs=crs, shape=shape)
source2 = _mock_datasetsource([[2, 2], [2, 2]], crs=crs, shape=shape)
sources = [source1, source2]
output_data = np.full(shape, fill_value=no_data, dtype='int16')
reproject_and_fuse(sources, output_data, dst_transform=identity, dst_projection=crs, dst_nodata=no_data)
assert (output_data == [[1, 1], [2, 2]]).all()
def test_second_source_used_when_first_is_empty():
crs = mock.MagicMock()
shape = (2, 2)
no_data = -1
source1 = _mock_datasetsource([[-1, -1], [-1, -1]], crs=crs, shape=shape)
source2 = _mock_datasetsource([[2, 2], [2, 2]], crs=crs, shape=shape)
sources = [source1, source2]
output_data = np.full(shape, fill_value=no_data, dtype='int16')
reproject_and_fuse(sources, output_data, dst_transform=identity, dst_projection=crs, dst_nodata=no_data)
assert (output_data == 2).all()
def test_first_source_is_priority_in_reproject_and_fuse():
crs = geometry.CRS('EPSG:4326')
shape = (2, 2)
no_data = -1
source1 = FakeDatasetSource([[1, 1], [1, 1]], crs=crs, shape=shape)
source2 = FakeDatasetSource([[2, 2], [2, 2]], crs=crs, shape=shape)
sources = [source1, source2]
output_data = np.full(shape, fill_value=no_data, dtype='int16')
reproject_and_fuse(sources, output_data, dst_transform=identity, dst_projection=crs, dst_nodata=no_data)
assert (output_data == 1).all()
def test_mixed_result_when_first_source_partially_empty_with_nan_nodata():
crs = geometry.CRS('EPSG:4326')
shape = (2, 2)
no_data = np.nan
source1 = FakeDatasetSource([[1, 1], [no_data, no_data]], crs=crs)
source2 = FakeDatasetSource([[2, 2], [2, 2]], crs=crs)
sources = [source1, source2]
output_data = np.full(shape, fill_value=no_data, dtype='float64')
reproject_and_fuse(sources, output_data, dst_transform=identity, dst_projection=crs, dst_nodata=no_data)
assert (output_data == [[1, 1], [2, 2]]).all()
def test_first_source_is_priority_in_reproject_and_fuse():
crs = mock.MagicMock()
shape = (2, 2)
no_data = -1
source1 = _mock_datasetsource([[1, 1], [1, 1]], crs=crs, shape=shape)
source2 = _mock_datasetsource([[2, 2], [2, 2]], crs=crs, shape=shape)
sources = [source1, source2]
output_data = numpy.full(shape, fill_value=no_data, dtype='int16')
reproject_and_fuse(sources,
output_data,
dst_transform=identity,
dst_projection=crs,
dst_nodata=no_data)
assert (output_data == 1).all()
