def shape_multiply(arr, scale, oddOnly=False, adjustFunction=None):
'''Works like tile except that it keeps all like elements clumped
Essentially a non-interpolating, multi-dimensional image up-scaler
Similar to scipy.ndimage.zoom but without interpolation'''
arr = np.asanyarray(arr)
scale = coerce_to_target_length(scale, arr.ndim)
if oddOnly:
assert all([i%2 == 1 for i in scale]), \
'All elements of scale must be odd integers greater than 0!'
t = np.tile(arr, scale)
t.shape = zipflat(scale, arr.shape)
t = _transpose_interleaved(t)
if adjustFunction != None:
t = adjustFunction(t, arr, scale)
new_shape = [sh * sc for sh, sc in zip(arr.shape, scale)]
return t.reshape(new_shape)
def _transpose_interleaved(arr):
'''Helper function for shape_multiply and shape_divide
Transposes an array so that all odd axes are first, i.e.:
[1, 3, 5, 7, ..., 0, 2, 4, ...]'''
return arr.transpose(*zipflat(range(1, arr.ndim, 2),
range(0, arr.ndim, 2)))
