/usr/lib/python3/dist-packages/rasterio/mask.py is in python3-rasterio 0.36.0-2build5.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 | """Mask the area outside of the input shapes with no data."""
from __future__ import absolute_import
import warnings
import rasterio
from rasterio.features import geometry_mask
def mask(raster, shapes, nodata=None, crop=False, all_touched=False,
invert=False):
"""Mask the area outside of the input shapes with nodata.
For all regions in the input raster outside of the regions defined by
`shapes`, sets any data present to nodata.
Parameters
----------
raster: rasterio RasterReader object
Raster to which the mask will be applied.
shapes: list of polygons
Polygons are GeoJSON-like dicts specifying the boundaries of features
in the raster to be kept. All data outside of specified polygons
will be set to nodata.
nodata: int or float (opt)
Value representing nodata within each raster band. If not set,
defaults to the nodata value for the input raster. If there is no
set nodata value for the raster, it defaults to 0.
crop: bool (opt)
Whether to crop the raster to the extent of the data. Defaults to
False.
all_touched: bool (opt)
Use all pixels touched by features. If False (default), use only
pixels whose center is within the polygon or that are selected by
Bresenhams line algorithm.
invert: bool (opt)
If True, mask will be True for pixels that overlap shapes.
False by default.
Returns
-------
masked: numpy ndarray
Data contained in raster after applying the mask.
out_transform: affine object
Information for mapping pixel coordinates in `masked` to another
coordinate system.
"""
if crop and invert:
raise ValueError("crop and invert cannot both be True.")
if nodata is None:
if raster.nodata is not None:
nodata = raster.nodata
else:
nodata = 0
all_bounds = [rasterio.features.bounds(shape) for shape in shapes]
minxs, minys, maxxs, maxys = zip(*all_bounds)
mask_bounds = (min(minxs), min(minys), max(maxxs), max(maxys))
invert_y = raster.affine.e > 0
source_bounds = raster.bounds
if invert_y:
source_bounds = [source_bounds[0], source_bounds[3],
source_bounds[2], source_bounds[1]]
if rasterio.coords.disjoint_bounds(source_bounds, mask_bounds):
if crop:
raise ValueError("Input shapes do not overlap raster.")
else:
warnings.warn("GeoJSON outside bounds of existing output " +
"raster. Are they in different coordinate " +
"reference systems?")
if invert_y:
mask_bounds = [mask_bounds[0], mask_bounds[3],
mask_bounds[2], mask_bounds[1]]
if crop:
window = raster.window(*mask_bounds)
out_transform = raster.window_transform(window)
else:
window = None
out_transform = raster.affine
out_image = raster.read(window=window, masked=True)
out_shape = out_image.shape[1:]
shape_mask = geometry_mask(shapes, transform=out_transform, invert=invert,
out_shape=out_shape, all_touched=all_touched)
out_image.mask = out_image.mask | shape_mask
out_image.fill_value = nodata
for i in range(raster.count):
out_image[i] = out_image[i].filled(nodata)
return out_image, out_transform
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