def get_coordinates(self):
"""{get_coordinates}
The default implementation tries to find the lat/lon coordinates based on dataset.affine.
It cannot determine the alt or time dimensions, so child classes may
have to overload this method.
"""
# check to see if the coordinates are rotated used affine
affine = self.dataset.transform
if self.crs is not None:
crs = self.crs
elif isinstance(self.dataset.crs,
rasterio.crs.CRS) and "init" in self.dataset.crs:
crs = self.dataset.crs["init"].upper()
elif isinstance(self.dataset.crs, dict) and "init" in self.dataset.crs:
crs = self.dataset.crs["init"].upper()
else:
try:
crs = pyproj.CRS(self.dataset.crs).to_wkt()
except pyproj.exceptions.CRSError:
raise RuntimeError("Unexpected rasterio crs '%s'" %
self.dataset.crs)
return Coordinates.from_geotransform(affine.to_gdal(),
self.dataset.shape, crs)
def get_data_overviews(self, coordinates, coordinates_index):
# Figure out how much coarser the request is than the actual data
reduction_factor = np.inf
for c in ["lat", "lon"]:
crd = coordinates[c]
if crd.size == 1:
reduction_factor = 0
break
if isinstance(crd, UniformCoordinates1d):
min_delta = crd.step
elif isinstance(crd, ArrayCoordinates1d) and crd.is_monotonic:
min_delta = crd.deltas.min()
else:
raise NotImplementedError(
"The Rasterio node with prefer_overviews=True currently does not support request coordinates type {}"
.format(coordinates))
reduction_factor = min(
reduction_factor,
np.abs(min_delta / self.coordinates[c].step
) # self.coordinates is always uniform
)
# Find the overview that's closest to this reduction factor
if (reduction_factor < 2) or (len(
self.overviews) == 0): # Then we shouldn't use an overview
overview = 1
overview_level = None
else:
diffs = reduction_factor - np.array(self.overviews)
if self.prefer_overviews_closest:
diffs = np.abs(diffs)
else:
diffs[diffs < 0] = np.inf
overview_level = np.argmin(diffs)
overview = self.overviews[np.argmin(diffs)]
# Now read the data
inds = coordinates_index
if overview_level is None:
dataset = self.dataset
else:
dataset = self.open_dataset(self.source, overview_level)
try:
# read data within coordinates_index window at the resolution of the overview
# Rasterio will then automatically pull from the overview
window = (
((inds[0].min() // overview),
int(np.ceil(inds[0].max() / overview) + 1)),
((inds[1].min() // overview),
int(np.ceil(inds[1].max() / overview) + 1)),
)
slc = (slice(window[0][0], window[0][1],
1), slice(window[1][0], window[1][1], 1))
new_coords = Coordinates.from_geotransform(
dataset.transform.to_gdal(),
dataset.shape,
crs=self.coordinates.crs)
new_coords = new_coords[slc]
missing_coords = self.coordinates.drop(["lat", "lon"])
new_coords = merge_dims([new_coords, missing_coords])
new_coords = new_coords.transpose(*self.coordinates.dims)
coordinates_shape = new_coords.shape[:2]
# The following lines are *nearly* copied/pasted from get_data
if self.outputs is not None: # read all the bands
raster_data = dataset.read(out_shape=(len(self.outputs), ) +
coordinates_shape,
window=window)
raster_data = np.moveaxis(raster_data, 0, 2)
else: # read the requested band
raster_data = dataset.read(self.band,
out_shape=coordinates_shape,
window=window)
# set raster data to output array
data = self.create_output_array(new_coords)
data.data.ravel()[:] = raster_data.ravel()
except Exception as e:
_logger.error(
"Error occurred when reading overview with Rasterio: {}".
format(e))
if overview_level is not None:
dataset.close()
return data