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{"@context":"https://schema.org","@type":"DiscussionForumPosting","headline":"Numpy Interoperability Issues with certain datatypes","articleBody":"There appears to be some issue regarding the interoperability between numpy and arrayfire-python regarding certain data types.\nI did the conversion using the methods:\n\n``` python\n# numpy to arrayfire\naf.interop.np_to_af_array\n\n# arrayfire to numpy\naf.Array.__array__()\n```\n\nThe only two data types which appear to work as intended are `float` and `double` (`f32` and `f64` in Arrayfire, `np.float32` and `np.float64` in numpy).\n\n64 bit integer values (signed and unsigned) and bool appear to be not supported (KeyError when trying to convert), but the data types `u8`, `u32` and `s32` are not converted correctly.\n\nAn example:\n\n```\nnparr = np.array([5, 10, 15, 20, 25, 30], np.int)\nprint(nparr)\n# Output: [ 5 10 15 20 25 30]\n\nafarr = af.interop.np_to_af_array(nparr)\nprint(afarr)\n# Output:\n# arrayfire.Array()\n# Type: long int\n# [6 1 1 1]\n#42949672965 \n#85899345935 \n#128849018905 \n# -7780732514909268839 \n#0\n#0\n\nafarr += 10\nprint(afarr.__array__())\n# Output: [25 10 35 20 45 30] instead of [25, 30, 35, 40, 45, 50]\n# Ten was only added to every second value!\n```\n\n[I tried these conversions with all of the aforementioned datatypes](https://gist.github.com/lukasbindreiter/249abd48b2e77665a41282fb2ffed5d7)\n\nI am using ArrayFire v3.3.2 (build f65dd97) with Python 3.5.2 on 64bit Windows\n","author":{"url":"https://github.com/lukasbindreiter","@type":"Person","name":"lukasbindreiter"},"datePublished":"2016-09-06T13:46:21.000Z","interactionStatistic":{"@type":"InteractionCounter","interactionType":"https://schema.org/CommentAction","userInteractionCount":2},"url":"https://github.com/92/arrayfire-python/issues/92"}