payload: {"action":"closed","issue":{"url":"https://api.github.com/repos/numpy/numpy/issues/14047","repository_url":"https://api.github.com/repos/numpy/numpy","labels_url":"https://api.github.com/repos/numpy/numpy/issues/14047/labels{/name}","comments_url":"https://api.github.com/repos/numpy/numpy/issues/14047/comments","events_url":"https://api.github.com/repos/numpy/numpy/issues/14047/events","html_url":"https://github.com/numpy/numpy/issues/14047","id":469429661,"node_id":"MDU6SXNzdWU0Njk0Mjk2NjE=","number":14047,"title":"Bug report in np.linalg.matrix_rank","user":{"login":"youkaichao","id":23236638,"node_id":"MDQ6VXNlcjIzMjM2NjM4","avatar_url":"https://avatars0.githubusercontent.com/u/23236638?v=4","gravatar_id":"","url":"https://api.github.com/users/youkaichao","html_url":"https://github.com/youkaichao","followers_url":"https://api.github.com/users/youkaichao/followers","following_url":"https://api.github.com/users/youkaichao/following{/other_user}","gists_url":"https://api.github.com/users/youkaichao/gists{/gist_id}","starred_url":"https://api.github.com/users/youkaichao/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/youkaichao/subscriptions","organizations_url":"https://api.github.com/users/youkaichao/orgs","repos_url":"https://api.github.com/users/youkaichao/repos","events_url":"https://api.github.com/users/youkaichao/events{/privacy}","received_events_url":"https://api.github.com/users/youkaichao/received_events","type":"User","site_admin":false},"labels":[{"id":81818822,"node_id":"MDU6TGFiZWw4MTgxODgyMg==","url":"https://api.github.com/repos/numpy/numpy/labels/57%20-%20Close?","name":"57 - Close?","color":"207de5","default":false}],"state":"closed","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":2,"created_at":"2019-07-17T20:30:54Z","updated_at":"2019-07-18T02:53:18Z","closed_at":"2019-07-18T02:53:18Z","author_association":"NONE","body":"Somehow I find [this](https://drive.google.com/open?id=1jZHjnOyAxK--4TD0bgppKtFGtfiNn0N8) magic matrix that fails the `np.linalg.matrix_rank` function.\r\n\r\n### Reproducing code example:\r\n\r\n```python\r\nimport numpy as np\r\n\r\ndata = np.load('tmp.npy')\r\n\r\ndata.shape # (810000, 9)\r\n\r\nnp.linalg.matrix_rank(data) # 7\r\n\r\nnp.linalg.matrix_rank(data[190:300]) # 9\r\n```\r\n\r\n### Numpy/Python version information:\r\n\r\n1.16.2 3.6.1 |Anaconda custom (64-bit)| (default, May 11 2017, 13:09:58) \r\n[GCC 4.4.7 20120313 (Red Hat 4.4.7-1)]\r\n\r\n"}}
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