{"action":"created","comment":{"url":"https://api.github.com/repos/astropy/astropy/pulls/comments/78246294","id":78246294,"diff_hunk":"@@ -152,23 +192,23 @@ class ZScaleInterval(BaseInterval):\n     image : array_like\n         Input array.\n     nsamples : int, optional\n-        Number of points in array to sample for determining scaling factors.\n-        Default to 1000.\n+        Number of points in array to sample for determining scaling\n+        factors.  Default to 1000.\n     contrast : float, optional\n-        Scaling factor (between 0 and 1) for determining min and max. Larger\n-        values increase the difference between min and max values used for\n-        display. Default to 0.25.\n+        Scaling factor (between 0 and 1) for determining min and max.\n+        Larger values increase the difference between min and max values\n+        used for display. 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classes","user":{"login":"larrybradley","id":4992897,"avatar_url":"https://avatars.githubusercontent.com/u/4992897?v=3","gravatar_id":"","url":"https://api.github.com/users/larrybradley","html_url":"https://github.com/larrybradley","followers_url":"https://api.github.com/users/larrybradley/followers","following_url":"https://api.github.com/users/larrybradley/following{/other_user}","gists_url":"https://api.github.com/users/larrybradley/gists{/gist_id}","starred_url":"https://api.github.com/users/larrybradley/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/larrybradley/subscriptions","organizations_url":"https://api.github.com/users/larrybradley/orgs","repos_url":"https://api.github.com/users/larrybradley/repos","events_url":"https://api.github.com/users/larrybradley/events{/privacy}","received_events_url":"https://api.github.com/users/larrybradley/received_events","type":"User","site_admin":false},"body":"This PR contains the following changes to the `visualization` subpackage:\r\n\r\n* ~~Adds a `Norm` class to generate a `matplotlib.colors.Normalize` object from an interval and a stretch instance.~~\r\n* ~~Adds a convenience `ImgNorm` class for quick interactive analysis (and used by the `fits2bitmap` command-line script).  `ImgNorm` replaces the `scale_image` function.~~\r\n* Deprecates the `scale_image` function (in favor of the `ImgNorm` class).\r\n* Adds a default stretch for the existing `Normalization` class.\r\n* Adds default `vmin/vmax` for the `ManualInterval` class.\r\n* Adds missing API docs for existing interval and stretch classes.\r\n* Adds addition tests for the visualization subpackage.\r\n* Augments and updates the visualization narrative docs.\r\n\r\nExamples\r\n----------\r\n\r\nWith the existing `ImageNormalize` class one needs to input the `vmin/vmax` values, which is a bit cumbersome, e.g.:\r\n\r\n```\r\ninterval = MinMaxInterval()\r\nvmin, vmax = interval.get_limits(image)\r\nnorm = ImageNormalize(vmin=vmin, vmax=vmax, stretch=SqrtStretch())\r\n```\r\n\r\nWith the new ~~`Norm` class~~ inputs, one can simply do, e.g.:\r\n\r\n```\r\nnorm = ImageNormalize(image, MinMaxInterval(), SqrtStretch())\r\n```\r\n\r\nAnd then the image is displayed with:\r\n```\r\nax.imshow(image, origin='lower', norm=norm)\r\n```\r\n\r\ncc: @astrofrog 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