def test_read_with_rasterfiledatasource(self, make_sample_geotiff, dst_nodata):
sample_geotiff_path, geobox, written_data = make_sample_geotiff(dst_nodata)
source = RasterFileDataSource(str(sample_geotiff_path), 1)
dest = np.zeros_like(written_data)
dst_transform = geobox.transform
dst_projection = epsg3577
dst_resampling = Resampling.nearest
# Read exactly the hunk of data that we wrote
_read_from_source(source, dest, dst_transform, dst_nodata, dst_projection, dst_resampling)
assert np.all(written_data == dest)
# Try reading from partially outside of our area
xoff = 50
offset_transform = dst_transform * Affine.translation(xoff, 0)
dest = np.zeros_like(written_data)
_read_from_source(source, dest, offset_transform, dst_nodata, dst_projection, dst_resampling)
assert np.all(written_data[:, xoff:] == dest[:, :xoff])
# Try reading from complete outside of our area, should return nodata
xoff = 300
offset_transform = dst_transform * Affine.translation(xoff, 0)
dest = np.zeros_like(written_data)
_read_from_source(source, dest, offset_transform, dst_nodata, dst_projection, dst_resampling)
if np.isnan(dst_nodata):
assert np.all(np.isnan(dest))
else:
assert np.all(dst_nodata == dest)
def _read(gbox,
resampling='nearest',
fallback_nodata=None,
dst_nodata=-999):
with RasterFileDataSource(mm.path, 1, nodata=fallback_nodata).open() as rdr:
yy = np.full(gbox.shape, dst_nodata, dtype=rdr.dtype)
roi = read_time_slice(rdr, yy, gbox, resampling, dst_nodata)
return yy, roi
def _read(gbox, resampling='nearest',
fallback_nodata=-999,
dst_nodata=-999,
check_paste=False):
with RasterFileDataSource(mm.path, 1, nodata=fallback_nodata).open() as rdr:
if check_paste:
# check that we are using paste
paste_ok, reason = can_paste(compute_reproject_roi(rdr_geobox(rdr), gbox))
assert paste_ok is True, reason
yy = np.full(gbox.shape, dst_nodata, dtype=rdr.dtype)
roi = read_time_slice(rdr, yy, gbox, resampling, dst_nodata)
return yy, roi
def test_read_data_from_outside_file_region(self, make_sample_netcdf, dst_transform):
sample_nc, geobox, written_data = make_sample_netcdf
source = RasterFileDataSource(sample_nc, 1)
dest = np.zeros((200, 1000))
dst_nodata = -999
dst_projection = epsg3577
dst_resampling = Resampling.nearest
# Read exactly the hunk of data that we wrote
_read_from_source(source, dest, dst_transform, dst_nodata, dst_projection, dst_resampling)
assert np.all(dest == -999)
def test_read_from_file_with_missing_crs(self, no_crs_gdal_path):
"""
We need to be able to read from data files even when GDAL can't automatically gather all the metdata.
The :class:`RasterFileDataSource` is able to override the nodata, CRS and transform attributes if necessary.
"""
crs = epsg4326
nodata = -999
transform = Affine(0.01, 0.0, 111.975,
0.0, 0.01, -9.975)
data_source = RasterFileDataSource(no_crs_gdal_path, bandnumber=1, nodata=nodata, crs=crs, transform=transform)
with pytest.warns(DeprecationWarning):
with data_source.open() as src:
dest1 = src.read()
assert dest1.shape == (10, 10)
def xtest_failed_data_read(self, make_sample_geotiff, dst_nodata):
sample_geotiff_path, geobox, written_data = make_sample_geotiff(dst_nodata)
src_transform = Affine(25.0, 0.0, 1200000.0,
0.0, -25.0, -4200000.0)
source = RasterFileDataSource(sample_geotiff_path, 1, transform=src_transform)
dest = np.zeros((20, 100))
dst_nodata = -999
dst_projection = epsg3577
dst_resampling = Resampling.nearest
# Read exactly the hunk of data that we wrote
dst_transform = Affine(25.0, 0.0, 127327.0,
0.0, -25.0, -417232.0)
_read_from_source(source, dest, dst_transform, dst_nodata, dst_projection, dst_resampling)
assert np.all(written_data == dest)