{"action":"created","issue":{"url":"https://api.github.com/repos/matplotlib/matplotlib/issues/6915","repository_url":"https://api.github.com/repos/matplotlib/matplotlib","labels_url":"https://api.github.com/repos/matplotlib/matplotlib/issues/6915/labels{/name}","comments_url":"https://api.github.com/repos/matplotlib/matplotlib/issues/6915/comments","events_url":"https://api.github.com/repos/matplotlib/matplotlib/issues/6915/events","html_url":"https://github.com/matplotlib/matplotlib/issues/6915","id":169778592,"number":6915,"title":"plt.yscale('log') after plt.scatter() behaves unpredictably in this example.","user":{"login":"davidmikolas","id":17236804,"avatar_url":"https://avatars.githubusercontent.com/u/17236804?v=3","gravatar_id":"","url":"https://api.github.com/users/davidmikolas","html_url":"https://github.com/davidmikolas","followers_url":"https://api.github.com/users/davidmikolas/followers","following_url":"https://api.github.com/users/davidmikolas/following{/other_user}","gists_url":"https://api.github.com/users/davidmikolas/gists{/gist_id}","starred_url":"https://api.github.com/users/davidmikolas/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/davidmikolas/subscriptions","organizations_url":"https://api.github.com/users/davidmikolas/orgs","repos_url":"https://api.github.com/users/davidmikolas/repos","events_url":"https://api.github.com/users/davidmikolas/events{/privacy}","received_events_url":"https://api.github.com/users/davidmikolas/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":{"login":"efiring","id":85125,"avatar_url":"https://avatars.githubusercontent.com/u/85125?v=3","gravatar_id":"","url":"https://api.github.com/users/efiring","html_url":"https://github.com/efiring","followers_url":"https://api.github.com/users/efiring/followers","following_url":"https://api.github.com/users/efiring/following{/other_user}","gists_url":"https://api.github.com/users/efiring/gists{/gist_id}","starred_url":"https://api.github.com/users/efiring/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/efiring/subscriptions","organizations_url":"https://api.github.com/users/efiring/orgs","repos_url":"https://api.github.com/users/efiring/repos","events_url":"https://api.github.com/users/efiring/events{/privacy}","received_events_url":"https://api.github.com/users/efiring/received_events","type":"User","site_admin":false},"assignees":[{"login":"efiring","id":85125,"avatar_url":"https://avatars.githubusercontent.com/u/85125?v=3","gravatar_id":"","url":"https://api.github.com/users/efiring","html_url":"https://github.com/efiring","followers_url":"https://api.github.com/users/efiring/followers","following_url":"https://api.github.com/users/efiring/following{/other_user}","gists_url":"https://api.github.com/users/efiring/gists{/gist_id}","starred_url":"https://api.github.com/users/efiring/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/efiring/subscriptions","organizations_url":"https://api.github.com/users/efiring/orgs","repos_url":"https://api.github.com/users/efiring/repos","events_url":"https://api.github.com/users/efiring/events{/privacy}","received_events_url":"https://api.github.com/users/efiring/received_events","type":"User","site_admin":false}],"milestone":{"url":"https://api.github.com/repos/matplotlib/matplotlib/milestones/14","html_url":"https://github.com/matplotlib/matplotlib/milestones/2.0%20(style%20change%20major%20release)","labels_url":"https://api.github.com/repos/matplotlib/matplotlib/milestones/14/labels","id":662004,"number":14,"title":"2.0 (style change major release)","description":"Style changes only","creator":{"login":"tacaswell","id":199813,"avatar_url":"https://avatars.githubusercontent.com/u/199813?v=3","gravatar_id":"","url":"https://api.github.com/users/tacaswell","html_url":"https://github.com/tacaswell","followers_url":"https://api.github.com/users/tacaswell/followers","following_url":"https://api.github.com/users/tacaswell/following{/other_user}","gists_url":"https://api.github.com/users/tacaswell/gists{/gist_id}","starred_url":"https://api.github.com/users/tacaswell/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/tacaswell/subscriptions","organizations_url":"https://api.github.com/users/tacaswell/orgs","repos_url":"https://api.github.com/users/tacaswell/repos","events_url":"https://api.github.com/users/tacaswell/events{/privacy}","received_events_url":"https://api.github.com/users/tacaswell/received_events","type":"User","site_admin":false},"open_issues":48,"closed_issues":576,"state":"open","created_at":"2014-05-17T14:28:22Z","updated_at":"2016-09-18T06:12:27Z","due_on":null,"closed_at":null},"comments":14,"created_at":"2016-08-07T03:58:38Z","updated_at":"2016-09-18T08:19:22Z","closed_at":null,"body":"As mentioned [in this SE question](http://stackoverflow.com/q/38800189/3904031) a scatter plot is not autoscaling to include all of the data if `plt.yscale('log')` is used after `plt.scatter()`. This happens for the y-axis but not the x-axis in the example, and does not happen for `plt.plot()`.\r\n\r\nIn an [earlier answer](http://stackoverflow.com/a/18774741/3904031) by a developer, `ax.set_yscale('log')` is shown following `ax.scatter()`, so I am wondering if this may be a bug.\r\n\r\nUsing matplotlib version 1.5.1 and python 2.7.11\r\n\r\n![image](https://cloud.githubusercontent.com/assets/17236804/17460373/045f64e4-5c96-11e6-8477-9702baec4939.png)\r\n\r\n    import matplotlib.pyplot as plt\r\n\r\n    X = [0.997, 2.643, 0.354, 0.075, 1.0, 0.03, 2.39, 0.364, 0.221, 0.437]\r\n    Y = [15.487507, 2.320735, 0.085742, 0.303032, 1.0, 0.025435, 4.436435,\r\n         0.025435, 0.000503, 2.320735]\r\n\r\n    plt.figure()\r\n\r\n    plt.subplot(2,2,1)\r\n    plt.scatter(X, Y)\r\n    plt.xscale('log')\r\n    plt.yscale('log')\r\n    plt.title('scatter - scale last')   \r\n\r\n    plt.subplot(2,2,2)\r\n    plt.plot(X, Y)\r\n    plt.xscale('log')\r\n    plt.yscale('log')\r\n    plt.title('plot - scale last')   \r\n\r\n    plt.subplot(2,2,3)\r\n    plt.xscale('log')\r\n    plt.yscale('log')\r\n    plt.scatter(X, Y)\r\n    plt.title('scatter - scale first')   \r\n\r\n    plt.subplot(2,2,4)\r\n    plt.xscale('log')\r\n    plt.yscale('log')\r\n    plt.plot(X, Y)\r\n    plt.title('plot - scale first')   \r\n\r\n    plt.show()\r\n"},"comment":{"url":"https://api.github.com/repos/matplotlib/matplotlib/issues/comments/247833828","html_url":"https://github.com/matplotlib/matplotlib/issues/6915#issuecomment-247833828","issue_url":"https://api.github.com/repos/matplotlib/matplotlib/issues/6915","id":247833828,"user":{"login":"davidmikolas","id":17236804,"avatar_url":"https://avatars.githubusercontent.com/u/17236804?v=3","gravatar_id":"","url":"https://api.github.com/users/davidmikolas","html_url":"https://github.com/davidmikolas","followers_url":"https://api.github.com/users/davidmikolas/followers","following_url":"https://api.github.com/users/davidmikolas/following{/other_user}","gists_url":"https://api.github.com/users/davidmikolas/gists{/gist_id}","starred_url":"https://api.github.com/users/davidmikolas/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/davidmikolas/subscriptions","organizations_url":"https://api.github.com/users/davidmikolas/orgs","repos_url":"https://api.github.com/users/davidmikolas/repos","events_url":"https://api.github.com/users/davidmikolas/events{/privacy}","received_events_url":"https://api.github.com/users/davidmikolas/received_events","type":"User","site_admin":false},"created_at":"2016-09-18T08:19:22Z","updated_at":"2016-09-18T08:19:22Z","body":"As far as I know natural logarithms or exp() are not likely to appear in plotting routines - most things should be base 10. However, there is that artifact at 10** -2.3466, or ~0.0045 which looks like natural logs were used. Is it possible to to a quick text search for `np.exp(` or `math.exp(` or `np.log(` or `math.log(` just to rule it out?"}}
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