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Fixed #31713 -- Added SpatialReference support to GDALRaster.transform().

This commit is contained in:
rico-ci 2020-06-18 14:52:02 +02:00 committed by Mariusz Felisiak
parent 7af8f41273
commit cb0da637a6
4 changed files with 86 additions and 68 deletions
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19
django/contrib/gis/gdal/raster/source.py
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@ -425,17 +425,24 @@ class GDALRaster(GDALRasterBase):
return target
def transform(self, srid, driver=None, name=None, resampling='NearestNeighbour',
def transform(self, srs, driver=None, name=None, resampling='NearestNeighbour',
max_error=0.0):
"""
Return a copy of this raster reprojected into the given SRID.
Return a copy of this raster reprojected into the given spatial
reference system.
"""
# Convert the resampling algorithm name into an algorithm id
algorithm = GDAL_RESAMPLE_ALGORITHMS[resampling]
# Instantiate target spatial reference system
target_srs = SpatialReference(srid)
if isinstance(srs, SpatialReference):
target_srs = srs
elif isinstance(srs, (int, str)):
target_srs = SpatialReference(srs)
else:
raise TypeError(
'Transform only accepts SpatialReference, string, and integer '
'objects.'
)
# Create warped virtual dataset in the target reference system
target = capi.auto_create_warped_vrt(
self._ptr, self.srs.wkt.encode(), target_srs.wkt.encode(),
@ -445,7 +452,7 @@ class GDALRaster(GDALRasterBase):
# Construct the target warp dictionary from the virtual raster
data = {
'srid': srid,
'srid': target_srs.srid,
'width': target.width,
'height': target.height,
'origin': [target.origin.x, target.origin.y],

21
docs/ref/contrib/gis/gdal.txt
View File

@ -1368,14 +1368,16 @@ blue.
[ 19., 21., 23.],
[ 31., 33., 35.]], dtype=float32)
.. method:: transform(srid, driver=None, name=None, resampling='NearestNeighbour', max_error=0.0)
.. method:: transform(srs, driver=None, name=None, resampling='NearestNeighbour', max_error=0.0)
Returns a transformed version of this raster with the specified SRID.
Transforms this raster to a different spatial reference system
(``srs``), which may be a :class:`SpatialReference` object, or any
other input accepted by :class:`SpatialReference` (including spatial
reference WKT and PROJ strings, or an integer SRID).
This function transforms the current raster into a new spatial reference
system that can be specified with an ``srid``. It calculates the bounds
and scale of the current raster in the new spatial reference system and
warps the raster using the :attr:`~GDALRaster.warp` function.
It calculates the bounds and scale of the current raster in the new
spatial reference system and warps the raster using the
:attr:`~GDALRaster.warp` function.
By default, the driver of the source raster is used and the name of the
raster is the original name appended with
@ -1394,10 +1396,15 @@ blue.
... "scale": [100, -100],
... "bands": [{"data": range(36), "nodata_value": 99}]
... })
>>> target = rst.transform(4326)
>>> target_srs = SpatialReference(4326)
>>> target = rst.transform(target_srs)
>>> target.origin
[-82.98492744885776, 27.601924753080144]
.. versionchanged:: 3.2
Support for :class:`SpatialReference` ``srs`` was added
.. attribute:: info
Returns a string with a summary of the raster. This is equivalent to

3
docs/releases/3.2.txt
View File

@ -68,7 +68,8 @@ Minor features
:mod:`django.contrib.gis`
~~~~~~~~~~~~~~~~~~~~~~~~~
* ...
* The :meth:`.GDALRaster.transform` method now supports
:class:`~django.contrib.gis.gdal.SpatialReference`.
:mod:`django.contrib.messages`
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

111
tests/gis_tests/gdal_tests/test_raster.py
View File

@ -3,7 +3,7 @@ import shutil
import struct
import tempfile
from django.contrib.gis.gdal import GDAL_VERSION, GDALRaster
from django.contrib.gis.gdal import GDAL_VERSION, GDALRaster, SpatialReference
from django.contrib.gis.gdal.error import GDALException
from django.contrib.gis.gdal.raster.band import GDALBand
from django.contrib.gis.shortcuts import numpy
@ -471,62 +471,65 @@ class GDALRasterTests(SimpleTestCase):
self.assertEqual(result, [23] * 16)
def test_raster_transform(self):
# Prepare tempfile and nodata value
rstfile = tempfile.NamedTemporaryFile(suffix='.tif')
ndv = 99
tests = [
3086,
'3086',
SpatialReference(3086),
]
for srs in tests:
with self.subTest(srs=srs):
# Prepare tempfile and nodata value.
rstfile = tempfile.NamedTemporaryFile(suffix='.tif')
ndv = 99
# Create in file based raster.
source = GDALRaster({
'datatype': 1,
'driver': 'tif',
'name': rstfile.name,
'width': 5,
'height': 5,
'nr_of_bands': 1,
'srid': 4326,
'origin': (-5, 5),
'scale': (2, -2),
'skew': (0, 0),
'bands': [{
'data': range(25),
'nodata_value': ndv,
}],
})
# Create in file based raster
source = GDALRaster({
'datatype': 1,
'driver': 'tif',
'name': rstfile.name,
'width': 5,
'height': 5,
'nr_of_bands': 1,
'srid': 4326,
'origin': (-5, 5),
'scale': (2, -2),
'skew': (0, 0),
'bands': [{
'data': range(25),
'nodata_value': ndv,
}],
})
target = source.transform(srs)
# Transform raster into srid 4326.
target = source.transform(3086)
# Reload data from disk.
target = GDALRaster(target.name)
self.assertEqual(target.srs.srid, 3086)
self.assertEqual(target.width, 7)
self.assertEqual(target.height, 7)
self.assertEqual(target.bands[0].datatype(), source.bands[0].datatype())
self.assertAlmostEqual(target.origin[0], 9124842.791079799, 3)
self.assertAlmostEqual(target.origin[1], 1589911.6476407414, 3)
self.assertAlmostEqual(target.scale[0], 223824.82664250192, 3)
self.assertAlmostEqual(target.scale[1], -223824.82664250192, 3)
self.assertEqual(target.skew, [0, 0])
# Reload data from disk
target = GDALRaster(target.name)
self.assertEqual(target.srs.srid, 3086)
self.assertEqual(target.width, 7)
self.assertEqual(target.height, 7)
self.assertEqual(target.bands[0].datatype(), source.bands[0].datatype())
self.assertAlmostEqual(target.origin[0], 9124842.791079799, 3)
self.assertAlmostEqual(target.origin[1], 1589911.6476407414, 3)
self.assertAlmostEqual(target.scale[0], 223824.82664250192, 3)
self.assertAlmostEqual(target.scale[1], -223824.82664250192, 3)
self.assertEqual(target.skew, [0, 0])
result = target.bands[0].data()
if numpy:
result = result.flatten().tolist()
# The reprojection of a raster that spans over a large area
# skews the data matrix and might introduce nodata values.
self.assertEqual(
result,
[
ndv, ndv, ndv, ndv, 4, ndv, ndv,
ndv, ndv, 2, 3, 9, ndv, ndv,
ndv, 1, 2, 8, 13, 19, ndv,
0, 6, 6, 12, 18, 18, 24,
ndv, 10, 11, 16, 22, 23, ndv,
ndv, ndv, 15, 21, 22, ndv, ndv,
ndv, ndv, 20, ndv, ndv, ndv, ndv,
]
)
result = target.bands[0].data()
if numpy:
result = result.flatten().tolist()
# The reprojection of a raster that spans over a large area
# skews the data matrix and might introduce nodata values.
self.assertEqual(
result,
[
ndv, ndv, ndv, ndv, 4, ndv, ndv,
ndv, ndv, 2, 3, 9, ndv, ndv,
ndv, 1, 2, 8, 13, 19, ndv,
0, 6, 6, 12, 18, 18, 24,
ndv, 10, 11, 16, 22, 23, ndv,
ndv, ndv, 15, 21, 22, ndv, ndv,
ndv, ndv, 20, ndv, ndv, ndv, ndv,
],
)
class GDALBandTests(SimpleTestCase):