def test_crop(self):
dims = (2, 2, 4)
sz = reduce(lambda x, y: x*y, dims)
origAry = arange(sz, dtype='int16').reshape(dims)
imageData = ImagesLoader(self.sc).fromArrays([origAry])
croppedData = imageData.crop((0, 0, 0), (2, 2, 2))
crop = croppedData.collect()[0][1]
expected = squeeze(origAry[slice(0, 2), slice(0, 2), slice(0, 2)])
assert_true(array_equal(expected, crop))
assert_equals(tuple(expected.shape), croppedData._dims.count)
assert_equals(str(expected.dtype), croppedData._dtype)
def _run_tst_crop(self, minBounds, maxBounds):
dims = (2, 2, 4)
sz = reduce(lambda x, y: x * y, dims)
origAry = arange(sz, dtype=dtypeFunc('int16')).reshape(dims)
imageData = ImagesLoader(self.sc).fromArrays([origAry])
croppedData = imageData.crop(minBounds, maxBounds)
crop = croppedData.collect()[0][1]
slices = []
for minb, maxb in zip(minBounds, maxBounds):
# skip the bounds-checking that we do in actual function; assume minb is <= maxb
if minb < maxb:
slices.append(slice(minb, maxb))
else:
slices.append(minb)
expected = squeeze(origAry[slices])
assert_true(array_equal(expected, crop))
assert_equals(tuple(expected.shape), croppedData._dims.count)
assert_equals(str(expected.dtype), croppedData._dtype)
def _run_tst_crop(self, minBounds, maxBounds):
dims = (2, 2, 4)
sz = reduce(lambda x, y: x * y, dims)
origAry = arange(sz, dtype=dtypeFunc("int16")).reshape(dims)
imageData = ImagesLoader(self.sc).fromArrays([origAry])
croppedData = imageData.crop(minBounds, maxBounds)
crop = croppedData.collect()[0][1]
slices = []
for minb, maxb in zip(minBounds, maxBounds):
# skip the bounds-checking that we do in actual function; assume minb is <= maxb
if minb < maxb:
slices.append(slice(minb, maxb))
else:
slices.append(minb)
expected = squeeze(origAry[slices])
assert_true(array_equal(expected, crop))
assert_equals(tuple(expected.shape), croppedData._dims.count)
assert_equals(str(expected.dtype), croppedData._dtype)
