def test1_sum_one_moving_block(self):
"""
"""
vol = np.asarray( [1, 3, 4] )
one_block = Block([ slice(0, 2) ])
block_set = spanning_blocks(array_shape=vol.shape,
block_shape=one_block.shape, step=1)
R, lags = sum_one_moving_block(vol, one_block, block_set)
R_real = (2.0, 1.0)
lags_real = ([0], [1])
self.assertEqual(R, R_real)
self.assertEqual(lags, lags_real)
def test2_sum_one_moving_block(self):
"""
"""
vol = np.asarray( [[1, 2, 3],
[4, 5, 6],
[7, 8, 9]] )
one_block = Block([slice(0,2), slice(0, 2)])
block_set = spanning_blocks(array_shape=vol.shape,
block_shape=one_block.shape, step=1)
R, lags = sum_one_moving_block(vol, one_block, block_set)
R_real = (10.0, 10.0, 10.0, 10.0)
lags_real = ([0, 0], [0, 1], [1, 0], [1, 1])
self.assertEqual(R, R_real)
self.assertEqual(lags, lags_real)
def sum_one_moving_block(vol, center_block, block_set=None):
"""Find correlation between one block and all other spanning blocks
for the array
"""
# set params for summation
array_shape = vol.shape
ndim = len(vol.shape)
block_shape = center_block.shape
step = 1
# Find spanning blocks if necessary
if not block_set:
block_set = spanning_blocks(array_shape=array_shape,
block_shape=block_shape, step=1)
# find correlation value and lag values for each
R, lags = zip(*map(_sum_two_blocks, block_set, repeat(center_block,
len(block_set)), repeat(vol, len(block_set))))
return R, lags
