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1d43837d15
For root mean square / quadratic mean. Added in GDAL 3.3 per https://github.com/OSGeo/gdal/pull/3210
111 lines
4.1 KiB
Python
111 lines
4.1 KiB
Python
"""
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Rasterio exposes GDAL's resampling/decimation on I/O. These are the tests
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that it does this correctly.
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"""
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import numpy as np
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import pytest
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import rasterio
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from rasterio.enums import Resampling
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from rasterio.errors import ResamplingAlgorithmError
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from rasterio.windows import Window
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from .conftest import requires_gdal2, requires_gdal33
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# Rasterio's test dataset is 718 rows by 791 columns.
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def test_read_out_shape_resample_down():
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with rasterio.open('tests/data/RGB.byte.tif') as s:
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out = np.zeros((8, 8), dtype=rasterio.ubyte)
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data = s.read(1, out=out)
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expected = np.array([
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[ 0, 0, 20, 15, 0, 0, 0, 0],
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[ 0, 6, 193, 9, 255, 127, 23, 39],
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[ 0, 7, 27, 255, 193, 14, 28, 34],
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[ 0, 31, 29, 44, 14, 22, 43, 0],
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[ 0, 9, 69, 49, 17, 22, 255, 0],
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[ 11, 7, 13, 25, 13, 29, 33, 0],
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[ 8, 10, 88, 27, 20, 33, 25, 0],
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[ 0, 0, 0, 0, 98, 23, 0, 0]], dtype=np.uint8)
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assert (data == expected).all() # all True.
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def test_read_out_shape_resample_up():
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# Instead of testing array items, test statistics. Upsampling by an even
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# constant factor shouldn't change the mean.
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with rasterio.open('tests/data/RGB.byte.tif') as s:
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out = np.zeros((7180, 7910), dtype=rasterio.ubyte)
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data = s.read(1, out=out, masked=True)
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assert data.shape == (7180, 7910)
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assert data.mean() == s.read(1, masked=True).mean()
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# TODO: justify or remove this test.
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def test_read_downsample_alpha():
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with rasterio.Env(GTIFF_IMPLICIT_JPEG_OVR=False):
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with rasterio.open('tests/data/alpha.tif') as src:
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out = np.zeros((100, 100), dtype=rasterio.ubyte)
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assert src.width == 1223
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assert src.height == 1223
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assert src.count == 4
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assert src.read(1, out=out, masked=False).shape == out.shape
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# attempt decimated read of alpha band
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src.read(4, out=out, masked=False)
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@requires_gdal2
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def test_resample_alg_effect_1():
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"""default (nearest) and cubic produce different results"""
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with rasterio.open('tests/data/RGB.byte.tif') as s:
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# Existence of overviews can upset our expectations, so we
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# guard against that here.
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assert not any([s.overviews(bidx) for bidx in s.indexes])
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out_shape = (s.height // 2, s.width // 2)
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nearest = s.read(1, out_shape=out_shape)
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cubic = s.read(1, out_shape=out_shape, resampling=Resampling.cubic)
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assert np.any(nearest != cubic)
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@requires_gdal2
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def test_resample_alg_effect_2():
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"""Average and bilinear produce different results"""
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with rasterio.open('tests/data/RGB.byte.tif') as s:
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# Existence of overviews can upset our expectations, so we
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# guard against that here.
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assert not any([s.overviews(bidx) for bidx in s.indexes])
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out_shape = (s.height // 2, s.width // 2)
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avg = s.read(1, out_shape=out_shape, resampling=Resampling.average)
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bilin = s.read(1, out_shape=out_shape, resampling=Resampling.bilinear)
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assert np.any(avg != bilin)
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@requires_gdal2
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def test_float_window():
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"""floating point windows work"""
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with rasterio.open('tests/data/RGB.byte.tif') as s:
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out_shape = (401, 401)
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window = Window(300.5, 300.5, 200.5, 200.5)
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s.read(1, window=window, out_shape=out_shape)
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@requires_gdal2
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def test_resampling_alg_error():
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"""Get an exception instead of a crash when using warp-only algs for read or write, see issue #1930"""
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with pytest.raises(ResamplingAlgorithmError):
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with rasterio.open("tests/data/RGB.byte.tif") as src:
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src.read(1, out_shape=(1, 10, 10), resampling=Resampling.max)
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@requires_gdal33
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def test_resampling_rms():
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"""Test Resampling.rms method"""
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with rasterio.open('tests/data/float.tif') as s:
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out_shape = (2, 2)
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rms = s.read(1, out_shape=out_shape, resampling=Resampling.rms)
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expected = np.array([
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[1.35266399, 0.95388681],
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[0.29308701, 1.54074657]], dtype=np.float32)
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assert (rms == expected).all() # all True.
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