def test_rechunk_blockshape():
 (new_shape, new_chunks) = ((10, 10), (4, 3))
 new_blockdims = normalize_chunks(new_chunks, new_shape)
 old_chunks = ((4, 4, 2), (3, 3, 3, 1))
 a = np.random.uniform(0, 1, 100).reshape((10, 10))
 x = da.from_array(a, chunks=old_chunks)
 check1 = rechunk(x, chunks=new_chunks)
 assert (check1.chunks == new_blockdims)
 assert np.all((check1.compute() == a))

def test_rechunk_blockshape ( ) : ( new_shape , new_chunks ) = ( ( 10 , 10 ) , ( 4 , 3 ) ) new_blockdims = normalize_chunks ( new_chunks , new_shape ) old_chunks = ( ( 4 , 4 , 2 ) , ( 3 , 3 , 3 , 1 ) ) a = np . random . uniform ( 0 , 1 , 100 ) . reshape ( ( 10 , 10 ) ) x = da . from_array ( a , chunks = old_chunks ) check1 = rechunk ( x , chunks = new_chunks ) assert ( check1 . chunks == new_blockdims ) assert np . all ( ( check1 . compute ( ) == a ) )
test that blockshape can be used .