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POnditer: possible to manually handle dimensions with different lengths?
 

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  1. POnditer: possible to manually handle dimensions with different lengths?
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    <p>Using numpy's <a href="http://docs.scipy.org/doc/numpy/reference/generated/numpy.nditer.html" rel="nofollow">nditer</a>, is it possible to manually handle dimensions with different lengths?</p> <p>For example, lets say I had an array A[5, 100] and I wanted to sample every 10 along the second axis so I would end up with an array B[5,10]. Is it possible to do this with nditer, handling the iteration over the second axis manually of course (probably in cython)?</p> <p>Another way to ask this would be, is it possible to ask nditer to allow me to manually iterate over a set of dimensions I provide?</p> <p>I want to be able to do something like this (modified from this <a href="http://docs.scipy.org/doc/numpy/reference/arrays.nditer.html#putting-the-inner-loop-in-cython" rel="nofollow">example</a>)</p> <pre><code>@cython.boundscheck(False) def sum_squares_cy(arr): cdef np.ndarray[double] x cdef np.ndarray[double] y cdef int size cdef double value cdef int j axeslist = list(arr.shape) axeslist[1] = -1 out = zeros((arr.shape[0], 10)) it = np.nditer([arr, out], flags=['reduce_ok', 'external_loop', 'buffered', 'delay_bufalloc'], op_flags=[['readonly'], ['readwrite', 'no_broadcast']], op_axes=[None, axeslist], op_dtypes=['float64', 'float64']) it.operands[1][...] = 0 it.reset() for xarr, yarr in it: x = xarr y = yarr size = x.shape[0] j = 0 for i in range(size): #some magic here involving indexing into x[i] and y[j] return it.operands[1] </code></pre> <p>Does this make sense? Is it possible to do?</p>
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