def test_has_mask():
"""Should return True."""
with rasterio.open(S3_MASK_PATH) as src_dst:
assert utils.has_mask_band(src_dst)
with rasterio.open(COG_DST) as src_dst:
assert not utils.has_mask_band(src_dst)
def test_has_alpha():
"""Check if rasters have alpha bands."""
with rasterio.open(S3_ALPHA_PATH) as src_dst:
assert utils.has_alpha_band(src_dst)
assert not utils.has_mask_band(src_dst)
with rasterio.open(COG_DST) as src_dst:
assert not utils.has_alpha_band(src_dst)
def _get_info(asset: str) -> Tuple:
with rasterio.open(asset) as src_dst:
description = [
src_dst.descriptions[b - 1] for i, b in enumerate(src_dst.indexes)
]
indexes = non_alpha_indexes(src_dst)
mask = has_mask_band(src_dst)
return (
src_dst.count,
src_dst.dtypes[0],
description,
src_dst.tags(),
src_dst.nodata,
mask,
indexes,
)
def info(address: str) -> Dict:
"""
Return simple metadata about the file.
Attributes
----------
address : str or PathLike object
A dataset path or URL. Will be opened in "r" mode.
Returns
-------
out : dict.
"""
with rasterio.open(address) as src_dst:
minzoom, maxzoom = get_zooms(src_dst)
bounds = transform_bounds(src_dst.crs,
constants.WGS84_CRS,
*src_dst.bounds,
densify_pts=21)
center = [(bounds[0] + bounds[2]) / 2, (bounds[1] + bounds[3]) / 2,
minzoom]
def _get_descr(ix):
"""Return band description."""
name = src_dst.descriptions[ix - 1]
if not name:
name = "band{}".format(ix)
return name
band_descriptions = [(ix, _get_descr(ix)) for ix in src_dst.indexes]
tags = [(ix, src_dst.tags(ix)) for ix in src_dst.indexes]
other_meta = dict()
if src_dst.scales[0] and src_dst.offsets[0]:
other_meta.update(dict(scale=src_dst.scales[0]))
other_meta.update(dict(offset=src_dst.offsets[0]))
if has_alpha_band(src_dst):
nodata_type = "Alpha"
elif has_mask_band(src_dst):
nodata_type = "Mask"
elif src_dst.nodata is not None:
nodata_type = "Nodata"
else:
nodata_type = "None"
try:
cmap = src_dst.colormap(1)
other_meta.update(dict(colormap=cmap))
except ValueError:
pass
return dict(
address=address,
bounds=bounds,
center=center,
minzoom=minzoom,
maxzoom=maxzoom,
band_metadata=tags,
band_descriptions=band_descriptions,
dtype=src_dst.meta["dtype"],
colorinterp=[
src_dst.colorinterp[ix - 1].name for ix in src_dst.indexes
],
nodata_type=nodata_type,
**other_meta,
)
def metadata(
src_dst: Union[DatasetReader, DatasetWriter, WarpedVRT],
bounds: Optional[Tuple[float, float, float, float]] = None,
indexes: Optional[Union[Sequence[int], int]] = None,
max_size: int = 1024,
bounds_crs: CRS = constants.WGS84_CRS,
percentiles: Tuple[float, float] = (2.0, 98.0),
hist_options: Dict = {},
**kwargs: Any,
) -> Dict:
"""
Retrieve metadata and statistics from an image.
Attributes
----------
src_dst : rasterio.io.DatasetReader
rasterio.io.DatasetReader object
bounds : tuple, optional
Bounding box coordinates from which to calculate image statistics.
max_size : int
`max_size` of the longest dimension, respecting
bounds X/Y aspect ratio.
indexes : list of ints or a single int, optional
Band indexes.
bounds_crs: CRS or str, optional
Specify bounds coordinate reference system, default WGS84/EPSG4326.
percentiles: tuple, optional
Tuple of Min/Max percentiles to compute. Default is (2, 98).
hist_options : dict, optional
Options to forward to numpy.histogram function.
kwargs : Any, optional
Additional options to forward to part or preview
Returns
-------
dict
"""
if isinstance(indexes, int):
indexes = (indexes, )
if indexes is None:
indexes = non_alpha_indexes(src_dst)
if indexes != src_dst.indexes:
warnings.warn("Alpha band was removed from the output data array",
AlphaBandWarning)
if bounds:
data, mask = part(
src_dst,
bounds,
max_size=max_size,
indexes=indexes,
bounds_crs=bounds_crs,
**kwargs,
)
bounds = transform_bounds(bounds_crs,
constants.WGS84_CRS,
*bounds,
densify_pts=21)
else:
data, mask = preview(src_dst,
max_size=max_size,
indexes=indexes,
**kwargs)
bounds = transform_bounds(src_dst.crs,
constants.WGS84_CRS,
*src_dst.bounds,
densify_pts=21)
data = numpy.ma.array(data)
data.mask = mask == 0
statistics = {
indexes[b]: raster_stats(data[b],
percentiles=percentiles,
**hist_options)
for b in range(data.shape[0])
}
def _get_descr(ix):
"""Return band description."""
name = src_dst.descriptions[ix - 1]
if not name:
name = "band{}".format(ix)
return name
band_descriptions = [(ix, _get_descr(ix)) for ix in indexes]
tags = [(ix, src_dst.tags(ix)) for ix in indexes]
other_meta = dict()
if src_dst.scales[0] and src_dst.offsets[0]:
other_meta.update(dict(scale=src_dst.scales[0]))
other_meta.update(dict(offset=src_dst.offsets[0]))
if has_alpha_band(src_dst):
nodata_type = "Alpha"
elif has_mask_band(src_dst):
nodata_type = "Mask"
elif src_dst.nodata is not None:
nodata_type = "Nodata"
else:
nodata_type = "None"
try:
cmap = src_dst.colormap(1)
other_meta.update(dict(colormap=cmap))
except ValueError:
pass
return dict(
bounds=bounds,
statistics=statistics,
band_metadata=tags,
band_descriptions=band_descriptions,
dtype=src_dst.meta["dtype"],
colorinterp=[src_dst.colorinterp[ix - 1].name for ix in indexes],
nodata_type=nodata_type,
**other_meta,
)
