{"action":"created","issue":{"url":"https://api.github.com/repos/numpy/numpy/issues/6042","labels_url":"https://api.github.com/repos/numpy/numpy/issues/6042/labels{/name}","comments_url":"https://api.github.com/repos/numpy/numpy/issues/6042/comments","events_url":"https://api.github.com/repos/numpy/numpy/issues/6042/events","html_url":"https://github.com/numpy/numpy/pull/6042","id":92969399,"number":6042,"title":"files have been added by removing sub repository","user":{"login":"yiakwy","id":8510840,"avatar_url":"https://avatars.githubusercontent.com/u/8510840?v=3","gravatar_id":"","url":"https://api.github.com/users/yiakwy","html_url":"https://github.com/yiakwy","followers_url":"https://api.github.com/users/yiakwy/followers","following_url":"https://api.github.com/users/yiakwy/following{/other_user}","gists_url":"https://api.github.com/users/yiakwy/gists{/gist_id}","starred_url":"https://api.github.com/users/yiakwy/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/yiakwy/subscriptions","organizations_url":"https://api.github.com/users/yiakwy/orgs","repos_url":"https://api.github.com/users/yiakwy/repos","events_url":"https://api.github.com/users/yiakwy/events{/privacy}","received_events_url":"https://api.github.com/users/yiakwy/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"milestone":null,"comments":5,"created_at":"2015-07-04T04:17:18Z","updated_at":"2015-07-05T15:21:47Z","closed_at":null,"pull_request":{"url":"https://api.github.com/repos/numpy/numpy/pulls/6042","html_url":"https://github.com/numpy/numpy/pull/6042","diff_url":"https://github.com/numpy/numpy/pull/6042.diff","patch_url":"https://github.com/numpy/numpy/pull/6042.patch"},"body":"Hi I have added files PyMatrix filder. Please check it. I wrote a blog half a year ago www.yiak.co (a long time ago) for your reference. Now my question is , numpy is really fast! So how can I integrate my coding interface into numpy?"},"comment":{"url":"https://api.github.com/repos/numpy/numpy/issues/comments/118631938","html_url":"https://github.com/numpy/numpy/pull/6042#issuecomment-118631938","issue_url":"https://api.github.com/repos/numpy/numpy/issues/6042","id":118631938,"user":{"login":"yiakwy","id":8510840,"avatar_url":"https://avatars.githubusercontent.com/u/8510840?v=3","gravatar_id":"","url":"https://api.github.com/users/yiakwy","html_url":"https://github.com/yiakwy","followers_url":"https://api.github.com/users/yiakwy/followers","following_url":"https://api.github.com/users/yiakwy/following{/other_user}","gists_url":"https://api.github.com/users/yiakwy/gists{/gist_id}","starred_url":"https://api.github.com/users/yiakwy/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/yiakwy/subscriptions","organizations_url":"https://api.github.com/users/yiakwy/orgs","repos_url":"https://api.github.com/users/yiakwy/repos","events_url":"https://api.github.com/users/yiakwy/events{/privacy}","received_events_url":"https://api.github.com/users/yiakwy/received_events","type":"User","site_admin":false},"created_at":"2015-07-05T15:21:47Z","updated_at":"2015-07-05T15:21:47Z","body":"@rgommers Yes Numpy is good at its C implementation for numeric computation but does not support object container design philosophy initially (2013 I think, maybe I was wrong, and that is why pandas exists and numpy has ndtype module). Then I started implementation for universal matrix container with following principles: \r\n1. support n-demension matrix object container, **an uniform interface** for row vector(transpose of [...,0,0,0,0,1]) and col vector([1,0,0,0,...])\r\n2. matrix container supports storing object from scratch, and because it is a container or matrix tree\r\n3. matrix container can become **larger and smaller** in runtime by setting elements\r\n4. matrix container will return None if \"b[a,c,d,]\" is none not raising an error (I think raising an error is not a good practice for numeric application, try to believe me)\r\n5. matrix container is of dynamic dimension length, and \"b[a,c,d]  = e \"will set an element at position e even if it does not exist and filling gaps between. I also thinks that it is a good practice to do such a thing.\r\n6. If matrix support object from scratch, it will support R Dataframe immediately.\r\n7. Pandas interface is very ugly. That is main reason I don't want to use it.\r\n8. It could be a numeric container which support fast matrix iteration\r\n\r\nI know the philosophy and techniques used by numpy ndarray. All these good techniques I didn't touch will be really good for fast computation\r\n\r\n9. it uses \"gap\" for fast interacting\r\n10. it actually a one dimension array and compute index values to locate an element, while I used depth searching because the shape of matrix is runtime variable and **unpredictable**.\r\n11. Just In Time compiler group support\r\n\r\nSo my computation speed is very slow after testing, but have a good manipulation interface just like a matrix in matlab (and better, can set headers, indice, detect n-d row vector, n-d col vector, support sub matrix like d[[1,3], [1,3]] will retur 2-d matrix).\r\n\r\nI want numpy expert to give some ideas how these benefits can absorbed by numpy or how I can improve my codes to help numpy.\r\n\r\nI don't want create a wheel again. It is my fault to realize numpy support \"object\" now so want to join community to make contribution as far as I could. \r\n\r\nThanks for any ideas from numpy experts. I am able to do C Plugins\r\n\r\n\r\n "}}