You might check numpy it is really powerful tool for working with multi
dimensional arrays:
ex.
>>> a = arange(81).reshape(3,3,3,3)
>>> a
array([[[[ 0, 1, 2],
[ 3, 4, 5],
[ 6, 7, 8]],
[[ 9, 10, 11],
[12, 13, 14],
[15, 16, 17]],
[[18, 19, 20],
[21, 22, 23],
[24, 25, 26]]],
[[[27, 28, 29],
[30, 31, 32],
[33, 34, 35]],
[[36, 37, 38],
[39, 40, 41],
[42, 43, 44]],
[[45, 46, 47],
[48, 49, 50],
[51, 52, 53]]],
[[[54, 55, 56],
[57, 58, 59],
[60, 61, 62]],
[[63, 64, 65],
[66, 67, 68],
[69, 70, 71]],
[[72, 73, 74],
[75, 76, 77],
[78, 79, 80]]]])
>>> f = a.flat
>>> for i in f:
... print(i)
0
1
2
..
98
99
cheers
Wojciech
On 05/08/14 21:06, Frank Miles wrote:
I need to evaluate a complicated function over a multidimensional space
as part of an optimization problem. This is a somewhat general problem
in which the number of dimensions and the function being evaluated can
vary from problem to problem.
I've got a working version (with loads of conditionals, and it only works
to #dimensions <= 10), but I'd like something simpler and clearer and
less hard-coded.
I've web-searched for some plausible method, but haven't found anything
"nice". Any recommendations where I should look, or what technique should
be used?
TIA!
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