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Resolves #1830

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This commit is contained in:
Sean Gillies 2020-03-20 13:41:48 -06:00
parent 6c9816cb10
commit 07b25aac52
1 changed files with 5 additions and 8 deletions
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13
docs/topics/reproject.rst
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@ -27,7 +27,7 @@ transform.
# degrees N, each pixel covering 15".
rows, cols = src_shape = (512, 512)
d = 1.0/240 # decimal degrees per pixel
# The following is equivalent to
# The following is equivalent to
# A(d, 0, -cols*d/2, 0, -d, rows*d/2).
src_transform = A.translation(-cols*d/2, rows*d/2) * A.scale(d, -d)
src_crs = {'init': 'EPSG:4326'}
@ -36,13 +36,13 @@ transform.
# Destination: a 1024 x 1024 dataset in Web Mercator (EPSG:3857)
# with origin at 0.0, 0.0.
dst_shape = (1024, 1024)
dst_transform = [-237481.5, 425.0, 0.0, 237536.4, 0.0, -425.0]
dst_transform = A.translation(-237481.5, 237536.4) * A.scale(425.0, -425.0)
dst_crs = {'init': 'EPSG:3857'}
destination = np.zeros(dst_shape, np.uint8)
reproject(
source,
destination,
source,
destination,
src_transform=src_transform,
src_crs=src_crs,
dst_transform=dst_transform,
@ -64,7 +64,7 @@ Estimating optimal output shape
Rasterio provides a :func:`rasterio.warp.calculate_default_transform()` function to
determine the optimal resolution and transform for the destination raster.
Given a source dataset in a known coordinate reference system, this
Given a source dataset in a known coordinate reference system, this
function will return a ``transform, width, height`` tuple which is calculated
by libgdal.
@ -120,8 +120,6 @@ See ``rasterio/rio/warp.py`` for more complex examples of reprojection based on
new bounds, dimensions, and resolution (as well as a command-line interface
described :ref:`here <warp>`).
It is also possible to use :func:`~rasterio.warp.reproject()` to create an output dataset zoomed
out by a factor of 2. Methods of the :class:`rasterio.Affine` class help us generate
the output dataset's transform matrix and, thereby, its spatial extent.
@ -170,4 +168,3 @@ References
----------
.. [1] https://docs.scipy.org/doc/scipy/reference/generated/scipy.ndimage.geometric_transform.html#scipy.ndimage.geometric_transform