running diff on carray returns short arrays

[btel]

When calculating array derivative (diff) carray shortens the array:

import carray as ca
import numpy as np

carr = ca.arange(1000000)
diff_arr = ca.eval("np.diff(carr)", vm="python")
nd_arr = np.diff(carr)

print "Number of elements in c:", len(carr)
print "Number of elements in diff_arr:", len(diff_arr)
print "Number of elements in nd_arr:", len(np_arr)

This returns on my computer:

Number of elements in carr: 1000000
Number of elements in diff_arr: 999877
Number of elements in nd_arr: 999999

Derivatives calculated with ndarray and carray have different lengths.

[FrancescAlted]

This is because np.diff is not keeping the length of the output the same than operands. This is not easily supported by a blocking technique, and should be implemented as 'toplevel' function.

Anyway, meanwhile this should raise a NotImplementedError at very least.

[FrancescAlted]

A possible implementation of np.diff for carray could be:

l = len(carr)-1 diff_arr = ca.fromiter((carr[i+1] - carr[i] for i in xrange(l)), 'f8', l)

which is about a 30% faster than np.diff on my machine (but the above only supports unidimensional arrays).