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			210 lines
		
	
	
		
			7.8 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
			
		
		
	
	
			210 lines
		
	
	
		
			7.8 KiB
		
	
	
	
		
			Python
		
	
	
	
	
	
from __future__ import print_function
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import sys
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from helper import unittest, PillowTestCase, hopper
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from PIL import Image
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try:
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    import site
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    import numpy
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    assert site  # silence warning
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    assert numpy  # silence warning
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except ImportError:
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    # Skip via setUp()
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    pass
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TEST_IMAGE_SIZE = (10, 10)
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# Numpy on pypy as of pypy 5.3.1 is corrupting the numpy.array(Image)
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# call such that it's returning a object of type numpy.ndarray, but
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# the repr is that of a PIL.Image. Size and shape are 1 and (), not the
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# size and shape of the array. This causes failures in several tests.
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SKIP_NUMPY_ON_PYPY = hasattr(sys, 'pypy_version_info') and (
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    sys.pypy_version_info <= (5, 3, 1, 'final', 0))
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class TestNumpy(PillowTestCase):
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    def setUp(self):
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        try:
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            import site
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            import numpy
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            assert site  # silence warning
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            assert numpy  # silence warning
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        except ImportError:
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            self.skipTest("ImportError")
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    def test_numpy_to_image(self):
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        def to_image(dtype, bands=1, boolean=0):
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            if bands == 1:
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                if boolean:
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                    data = [0, 1] * 50
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                else:
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                    data = list(range(100))
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                a = numpy.array(data, dtype=dtype)
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                a.shape = TEST_IMAGE_SIZE
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                i = Image.fromarray(a)
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                if list(i.getdata()) != data:
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                    print("data mismatch for", dtype)
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            else:
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                data = list(range(100))
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                a = numpy.array([[x]*bands for x in data], dtype=dtype)
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                a.shape = TEST_IMAGE_SIZE[0], TEST_IMAGE_SIZE[1], bands
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                i = Image.fromarray(a)
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                if list(i.split()[0].getdata()) != list(range(100)):
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                    print("data mismatch for", dtype)
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            # print(dtype, list(i.getdata()))
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            return i
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        # Check supported 1-bit integer formats
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        self.assertRaises(TypeError, lambda: to_image(numpy.bool))
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        self.assertRaises(TypeError, lambda: to_image(numpy.bool8))
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        # Check supported 8-bit integer formats
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        self.assert_image(to_image(numpy.uint8), "L", TEST_IMAGE_SIZE)
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        self.assert_image(to_image(numpy.uint8, 3), "RGB", TEST_IMAGE_SIZE)
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        self.assert_image(to_image(numpy.uint8, 4), "RGBA", TEST_IMAGE_SIZE)
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        self.assert_image(to_image(numpy.int8), "I", TEST_IMAGE_SIZE)
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        # Check non-fixed-size integer types
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        # These may fail, depending on the platform, since we have no native
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        # 64 bit int image types.
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        # self.assert_image(to_image(numpy.uint), "I", TEST_IMAGE_SIZE)
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        # self.assert_image(to_image(numpy.int), "I", TEST_IMAGE_SIZE)
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        # Check 16-bit integer formats
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        if Image._ENDIAN == '<':
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            self.assert_image(to_image(numpy.uint16), "I;16", TEST_IMAGE_SIZE)
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        else:
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            self.assert_image(to_image(numpy.uint16), "I;16B", TEST_IMAGE_SIZE)
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        self.assert_image(to_image(numpy.int16), "I", TEST_IMAGE_SIZE)
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        # Check 32-bit integer formats
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        self.assert_image(to_image(numpy.uint32), "I", TEST_IMAGE_SIZE)
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        self.assert_image(to_image(numpy.int32), "I", TEST_IMAGE_SIZE)
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        # Check 64-bit integer formats
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        self.assertRaises(TypeError, lambda: to_image(numpy.uint64))
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        self.assertRaises(TypeError, lambda: to_image(numpy.int64))
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        # Check floating-point formats
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        self.assert_image(to_image(numpy.float), "F", TEST_IMAGE_SIZE)
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        self.assertRaises(TypeError, lambda: to_image(numpy.float16))
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        self.assert_image(to_image(numpy.float32), "F", TEST_IMAGE_SIZE)
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        self.assert_image(to_image(numpy.float64), "F", TEST_IMAGE_SIZE)
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        self.assert_image(to_image(numpy.uint8, 2), "LA", (10, 10))
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        self.assert_image(to_image(numpy.uint8, 3), "RGB", (10, 10))
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        self.assert_image(to_image(numpy.uint8, 4), "RGBA", (10, 10))
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    # based on an erring example at
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    # https://stackoverflow.com/questions/10854903/what-is-causing-dimension-dependent-attributeerror-in-pil-fromarray-function
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    def test_3d_array(self):
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        size = (5, TEST_IMAGE_SIZE[0], TEST_IMAGE_SIZE[1])
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        a = numpy.ones(size, dtype=numpy.uint8)
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        self.assert_image(Image.fromarray(a[1, :, :]), "L", TEST_IMAGE_SIZE)
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        size = (TEST_IMAGE_SIZE[0], 5, TEST_IMAGE_SIZE[1])
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        a = numpy.ones(size, dtype=numpy.uint8)
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        self.assert_image(Image.fromarray(a[:, 1, :]), "L", TEST_IMAGE_SIZE)
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        size = (TEST_IMAGE_SIZE[0], TEST_IMAGE_SIZE[1], 5)
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        a = numpy.ones(size, dtype=numpy.uint8)
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        self.assert_image(Image.fromarray(a[:, :, 1]), "L", TEST_IMAGE_SIZE)
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    def _test_img_equals_nparray(self, img, np):
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        self.assertGreaterEqual(len(np.shape), 2)
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        np_size = np.shape[1], np.shape[0]
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        self.assertEqual(img.size, np_size)
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        px = img.load()
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        for x in range(0, img.size[0], int(img.size[0]/10)):
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            for y in range(0, img.size[1], int(img.size[1]/10)):
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                self.assert_deep_equal(px[x, y], np[y, x])
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    @unittest.skipIf(SKIP_NUMPY_ON_PYPY, "numpy.array(Image) is flaky on PyPy")
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    def test_16bit(self):
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        img = Image.open('Tests/images/16bit.cropped.tif')
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        np_img = numpy.array(img)
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        self._test_img_equals_nparray(img, np_img)
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        self.assertEqual(np_img.dtype, numpy.dtype('<u2'))
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    def test_1bit(self):
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        # Test that 1-bit arrays convert to numpy and back
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        # See: https://github.com/python-pillow/Pillow/issues/350
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        arr = numpy.array([[1, 0, 0, 1, 0], [0, 1, 0, 0, 0]], 'u1')
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        img = Image.fromarray(arr * 255).convert('1')
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        self.assertEqual(img.mode, '1')
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        arr_back = numpy.array(img)
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        # numpy 1.8 and earlier return this as a boolean. (trusty/precise)
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        if arr_back.dtype == numpy.bool:
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            arr_bool = numpy.array([[1, 0, 0, 1, 0], [0, 1, 0, 0, 0]], 'bool')
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            numpy.testing.assert_array_equal(arr_bool, arr_back)
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        else:
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            numpy.testing.assert_array_equal(arr, arr_back)
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    def test_save_tiff_uint16(self):
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        # Tests that we're getting the pixel value in the right byte order.
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        pixel_value = 0x1234
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        a = numpy.array([pixel_value] * TEST_IMAGE_SIZE[0] * TEST_IMAGE_SIZE[1], dtype=numpy.uint16)
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        a.shape = TEST_IMAGE_SIZE
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        img = Image.fromarray(a)
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        img_px = img.load()
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        self.assertEqual(img_px[0, 0], pixel_value)
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    @unittest.skipIf(SKIP_NUMPY_ON_PYPY, "numpy.array(Image) is flaky on PyPy")
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    def test_to_array(self):
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        def _to_array(mode, dtype):
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            img = hopper(mode)
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            # Resize to non-square
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            img = img.crop((3, 0, 124, 127))
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            self.assertEqual(img.size, (121, 127))
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            np_img = numpy.array(img)
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            self._test_img_equals_nparray(img, np_img)
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            self.assertEqual(np_img.dtype, numpy.dtype(dtype))
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        modes = [("L", 'uint8'),
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                 ("I", 'int32'),
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                 ("F", 'float32'),
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                 ("LA", 'uint8'),
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                 ("RGB", 'uint8'),
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                 ("RGBA", 'uint8'),
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                 ("RGBX", 'uint8'),
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                 ("CMYK", 'uint8'),
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                 ("YCbCr", 'uint8'),
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                 ("I;16", '<u2'),
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                 ("I;16B", '>u2'),
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                 ("I;16L", '<u2'),
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                 ("HSV", 'uint8'),
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                 ]
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        for mode in modes:
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            _to_array(*mode)
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    def test_point_lut(self):
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        # see https://github.com/python-pillow/Pillow/issues/439
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        data = list(range(256))*3
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        lut = numpy.array(data, dtype='uint8')
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        im = hopper()
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        im.point(lut)
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    def test_putdata(self):
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        # shouldn't segfault
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        # see https://github.com/python-pillow/Pillow/issues/1008
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        im = Image.new('F', (150, 100))
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        arr = numpy.zeros((15000,), numpy.float32)
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        im.putdata(arr)
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        self.assertEqual(len(im.getdata()), len(arr))
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if __name__ == '__main__':
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    unittest.main()
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