{"action":"created","comment":{"url":"https://api.github.com/repos/numpy/numpy/pulls/comments/48677693","id":48677693,"diff_hunk":"@@ -574,6 +579,128 @@ def _shape_from_size(size, d):\n            shape = tuple(size) + (d,)\n     return shape\n \n+\n+# Set up dictionary of integer types and relevant functions.\n+#\n+# The dictionary is keyed by dtype(...).name and the values\n+# are a tuple (low, high, function), where low and high are\n+# the bounds of the largest half open interval `[low, high)`\n+# and the function is the relevant function to call for\n+# that precision.\n+\n+\n+def rand_int32(low, high, size, rngstate):\n+    \"\"\"\n+    random_int32(self, low, high=None, size=None, state)\n+","path":"numpy/random/mtrand/mtrand.pyx","position":36,"original_position":36,"commit_id":"5b5fcd23ca86e6e7bc17f0d77bb6cb260900afbe","original_commit_id":"5b5fcd23ca86e6e7bc17f0d77bb6cb260900afbe","user":{"login":"gfyoung","id":9273653,"avatar_url":"https://avatars.githubusercontent.com/u/9273653?v=3","gravatar_id":"","url":"https://api.github.com/users/gfyoung","html_url":"https://github.com/gfyoung","followers_url":"https://api.github.com/users/gfyoung/followers","following_url":"https://api.github.com/users/gfyoung/following{/other_user}","gists_url":"https://api.github.com/users/gfyoung/gists{/gist_id}","starred_url":"https://api.github.com/users/gfyoung/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/gfyoung/subscriptions","organizations_url":"https://api.github.com/users/gfyoung/orgs","repos_url":"https://api.github.com/users/gfyoung/repos","events_url":"https://api.github.com/users/gfyoung/events{/privacy}","received_events_url":"https://api.github.com/users/gfyoung/received_events","type":"User","site_admin":false},"body":"Function signature mismatch","created_at":"2016-01-01T13:03:57Z","updated_at":"2016-01-01T13:03:57Z","html_url":"https://github.com/numpy/numpy/pull/6910#discussion_r48677693","pull_request_url":"https://api.github.com/repos/numpy/numpy/pulls/6910","_links":{"self":{"href":"https://api.github.com/repos/numpy/numpy/pulls/comments/48677693"},"html":{"href":"https://github.com/numpy/numpy/pull/6910#discussion_r48677693"},"pull_request":{"href":"https://api.github.com/repos/numpy/numpy/pulls/6910"}}},"pull_request":{"url":"https://api.github.com/repos/numpy/numpy/pulls/6910","id":54832867,"html_url":"https://github.com/numpy/numpy/pull/6910","diff_url":"https://github.com/numpy/numpy/pull/6910.diff","patch_url":"https://github.com/numpy/numpy/pull/6910.patch","issue_url":"https://api.github.com/repos/numpy/numpy/issues/6910","number":6910,"state":"open","locked":false,"title":"Add 64  and 32 bit random integer functions.","user":{"login":"charris","id":77272,"avatar_url":"https://avatars.githubusercontent.com/u/77272?v=3","gravatar_id":"","url":"https://api.github.com/users/charris","html_url":"https://github.com/charris","followers_url":"https://api.github.com/users/charris/followers","following_url":"https://api.github.com/users/charris/following{/other_user}","gists_url":"https://api.github.com/users/charris/gists{/gist_id}","starred_url":"https://api.github.com/users/charris/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/charris/subscriptions","organizations_url":"https://api.github.com/users/charris/orgs","repos_url":"https://api.github.com/users/charris/repos","events_url":"https://api.github.com/users/charris/events{/privacy}","received_events_url":"https://api.github.com/users/charris/received_events","type":"User","site_admin":false},"body":"This is a WIP, in particular, the examples need fixing, tests need to be added, and a decision should be made whether to access these functions through a dtype argument in the current `random_integers` function. If the latter is chosen rk_functions for uint8, uint16, and maybe bool need to be added for efficiency, on the other hand, less new documentation needs to be written ;)\r\n\r\nI've reimplemented random_integers using the new functions but the random stream should be preserved. There is also an added random_intp function, which is used here to fix the mem_overlap tests failing in  #6812.\r\n\r\nAlternate PR's addressing this are #6824 and #6869, but I like this one as far as it goes.","created_at":"2015-12-30T21:58:17Z","updated_at":"2016-01-01T13:03:57Z","closed_at":null,"merged_at":null,"merge_commit_sha":"16751bdca48d95bd7f854c024e3e3a6f5db14b85","assignee":null,"milestone":{"url":"https://api.github.com/repos/numpy/numpy/milestones/36","html_url":"https://github.com/numpy/numpy/milestones/1.11.0%20release","labels_url":"https://api.github.com/repos/numpy/numpy/milestones/36/labels","id":1094191,"number":36,"title":"1.11.0 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