def assert_same_read_results(source, dst_shape, dst_dtype, dst_transform,
dst_nodata, dst_projection, resampling):
expected = np.empty(dst_shape, dtype=dst_dtype)
with source.open() as src:
rasterio.warp.reproject(src.data,
expected,
src_transform=src.transform,
src_crs=str(src.crs),
src_nodata=src.nodata,
dst_transform=dst_transform,
dst_crs=str(dst_projection),
dst_nodata=dst_nodata,
resampling=resampling)
result = np.full(dst_shape, dst_nodata, dtype=dst_dtype)
H, W = dst_shape
dst_gbox = GeoBox(W, H, dst_transform, dst_projection)
with datacube.set_options(reproject_threads=1):
with source.open() as rdr:
read_time_slice(rdr,
result,
dst_gbox,
dst_nodata=dst_nodata,
resampling=resampling)
assert np.isclose(result, expected, atol=0, rtol=0.05,
equal_nan=True).all()
return result
def _read_from_source(source, dest, dst_transform, dst_nodata, dst_projection, resampling):
"""
Adapt old signature to new function, so that we can keep old tests at least for now
"""
H, W = dest.shape
gbox = GeoBox(W, H, dst_transform, dst_projection)
dest[:] = dst_nodata # new code assumes pre-populated image
with source.open() as rdr:
read_time_slice(rdr, dest, gbox, resampling=resampling, dst_nodata=dst_nodata)
def reproject_and_fuse(datasources: List[DataSource],
destination: np.ndarray,
dst_gbox: GeoBox,
dst_nodata: Optional[Union[int, float]],
resampling: str = 'nearest',
fuse_func: Optional[FuserFunction] = None,
skip_broken_datasets: bool = False):
"""
Reproject and fuse `sources` into a 2D numpy array `destination`.
:param datasources: Data sources to open and read from
:param destination: ndarray of appropriate size to read data into
:param dst_gbox: GeoBox defining destination region
:param skip_broken_datasets: Carry on in the face of adversity and failing reads.
"""
# pylint: disable=too-many-locals
assert len(destination.shape) == 2
def copyto_fuser(dest: np.ndarray, src: np.ndarray) -> None:
where_nodata = (
dest == dst_nodata) if not np.isnan(dst_nodata) else np.isnan(dest)
np.copyto(dest, src, where=where_nodata)
fuse_func = fuse_func or copyto_fuser
destination.fill(dst_nodata)
if len(datasources) == 0:
return destination
elif len(datasources) == 1:
with ignore_exceptions_if(skip_broken_datasets):
with datasources[0].open() as rdr:
read_time_slice(rdr, destination, dst_gbox, resampling,
dst_nodata)
return destination
else:
# Multiple sources, we need to fuse them together into a single array
buffer_ = np.full(destination.shape,
dst_nodata,
dtype=destination.dtype)
for source in datasources:
with ignore_exceptions_if(skip_broken_datasets):
with source.open() as rdr:
roi = read_time_slice(rdr, buffer_, dst_gbox, resampling,
dst_nodata)
if not roi_is_empty(roi):
fuse_func(destination[roi], buffer_[roi])
buffer_[roi] = dst_nodata # clean up for next read
return destination
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
