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{"@context":"https://schema.org","@type":"DiscussionForumPosting","headline":"canvas.draw() does not render tick labels with pdf backend","articleBody":"### Bug report\r\n\r\n**Bug summary**\r\n\r\nMy issue is closely related to the [one here](https://github.com/matplotlib/matplotlib/issues/6103).\r\nI need to access the ticklabels before writing my plot to a file, but when being non interactive there appears to be no way of forcing the generation of ticklabels, or is there?  Both `fig.canvas.draw()` and `matplotlib.pyplot.draw()` have no effect.\r\n\r\nOf course I could generate my own ticklabels, using `ax.set_xticklabels(ax.get_xticks())` but I very much like the default formatting of ticks so I would like to rely on matplotlib here. \r\n\r\nIn the code below method 0 is what I would label the clean solution whereas all other implementations are workarounds, necessary to compensate for the difference of the behaviors of interactive vs non interactive backends. I find the dependence on the interactiveness of the backend problematic. This is because what I often do is to develop a plotting code using an interactive backend and when it's ready I apply it to big data on a HPC were I'm not always provided interactive backends. \r\n\r\n**Code for reproduction**\r\n\r\n```python\r\n#!/usr/bin/env python3\r\n\r\nimport matplotlib\r\nmatplotlib.use('pdf')\r\nimport matplotlib.pyplot as plt\r\nimport matplotlib.ticker as ticker\r\nimport numpy as np\r\n\r\nprint('backend:',matplotlib.get_backend())\r\n\r\nx = np.linspace(0,3,100)\r\ny = np.sin(x)**2\r\n\r\nmethod = 0\r\nwhile True:\r\n    fig, ax = plt.subplots()\r\n    ax.plot(x,y)\r\n    if method == 0:\r\n        fig.canvas.draw()\r\n        plt.draw()\r\n    elif method == 1:\r\n        ax.xaxis.set_major_locator(ticker.AutoLocator())\r\n        ax.xaxis.set_major_formatter(ticker.ScalarFormatter())\r\n    elif method == 2:\r\n        ax.set_xticklabels(ax.get_xticks())\r\n    elif method == 3:\r\n        ax.set_xticklabels([ ticker.ScalarFormatter().format_data(tick) for tick in ax.get_xticks() ])\r\n    elif method == 4:\r\n        ax.set_xticklabels([ '{:g}'.format(tick) for tick in ax.get_xticks() ])\r\n    else:\r\n        break\r\n    \r\n    print('method {:d} :'.format(method), end='')\r\n    print([ label.get_text() for label in ax.get_xticklabels() ] )\r\n    method += 1\r\n```\r\n\r\n**Actual outcome**\r\n\r\n```\r\nbackend: pdf\r\nmethod 0 :['', '', '', '', '', '', '', '', '']\r\nmethod 1 :['', '', '', '', '', '', '', '', '']\r\nmethod 2 :['-0.5', '0.0', '0.5', '1.0', '1.5', '2.0', '2.5', '3.0', '3.5']\r\nmethod 3 :['−5e−1', '0', '5e−1', '1', '1.5', '2', '2.5', '3', '3.5']\r\nmethod 4 :['-0.5', '0', '0.5', '1', '1.5', '2', '2.5', '3', '3.5']\r\n```\r\n\r\n**Expected outcome**\r\n\r\n```\r\nbackend: pdf\r\nmethod 0 :['−0.5', '0.0', '0.5', '1.0', '1.5', '2.0', '2.5', '3.0', '3.5']\r\nmethod 1 :['', '', '', '', '', '', '', '', '']\r\nmethod 2 :['-0.5', '0.0', '0.5', '1.0', '1.5', '2.0', '2.5', '3.0', '3.5']\r\nmethod 3 :['−5e−1', '0', '5e−1', '1', '1.5', '2', '2.5', '3', '3.5']\r\nmethod 4 :['-0.5', '0', '0.5', '1', '1.5', '2', '2.5', '3', '3.5']\r\n```\r\nWhich (apart from the first line of course) is obtained when using an interactive backend.\r\n\r\n**Matplotlib version**\r\n  * Operating system: Ubuntu 16.04.5 LTS 64-bit\r\n  * Matplotlib version: 3.0.2 (conda, build: py36_1002, channel: conda-forge)\r\n  * Matplotlib backend (`print(matplotlib.get_backend())`): pdf\r\n  * Python version: 3.6.8 (conda, build: h0371630_0)\r\n\r\n","author":{"url":"https://github.com/baloe","@type":"Person","name":"baloe"},"datePublished":"2019-02-25T12:14:51.000Z","interactionStatistic":{"@type":"InteractionCounter","interactionType":"https://schema.org/CommentAction","userInteractionCount":7},"url":"https://github.com/13513/matplotlib/issues/13513"}