Title: BUG: shared log axes lose _minpos and revert to default · Issue #7587 · matplotlib/matplotlib · GitHub
Open Graph Title: BUG: shared log axes lose _minpos and revert to default · Issue #7587 · matplotlib/matplotlib
X Title: BUG: shared log axes lose _minpos and revert to default · Issue #7587 · matplotlib/matplotlib
Description: This example showcases two instances where the view limits in 1.5.3 are not the same as when using 2.0.0rc1 with the classic style. from distutils.version import LooseVersion import numpy as np import matplotlib as mpl import matplotlib....
Open Graph Description: This example showcases two instances where the view limits in 1.5.3 are not the same as when using 2.0.0rc1 with the classic style. from distutils.version import LooseVersion import numpy as np imp...
X Description: This example showcases two instances where the view limits in 1.5.3 are not the same as when using 2.0.0rc1 with the classic style. from distutils.version import LooseVersion import numpy as np imp...
Opengraph URL: https://github.com/matplotlib/matplotlib/issues/7587
X: @github
Domain: github.com
{"@context":"https://schema.org","@type":"DiscussionForumPosting","headline":"BUG: shared log axes lose _minpos and revert to default","articleBody":"This example showcases two instances where the view limits in 1.5.3 are not the same as when using 2.0.0rc1 with the classic style.\r\n\r\n```python\r\nfrom distutils.version import LooseVersion\r\n\r\nimport numpy as np\r\nimport matplotlib as mpl\r\nimport matplotlib.pyplot as plt\r\n\r\n\r\nif LooseVersion(mpl.__version__) \u003e= LooseVersion('2.0.0'):\r\n plt.style.use('classic')\r\n\r\n\r\ncc_t = np.arange(-100, 101, 5) / 1000\r\ncc_concave = np.ones_like(cc_t)\r\n\r\nfig, ax = plt.subplots()\r\nax.plot(cc_t, cc_concave, ls=\"\", marker=\".\", color=\"0.7\",\r\n label=\"xcorr (concave)\")\r\nax.set_title(mpl.__version__)\r\n\r\n\r\nnp.random.seed(0)\r\nfreq = np.arange(0.0, 100.0, 0.001)\r\nresp = np.random.rand(*freq.shape) + 1j * np.random.rand(*freq.shape)\r\n\r\nfig, (ax1, ax2) = plt.subplots(2, 1, sharex=True)\r\nax1.loglog(freq, abs(resp), lw=1.5)\r\nax1.set_title(mpl.__version__)\r\nax2.semilogx(freq, np.angle(resp), lw=1.5)\r\nax2.set_title(mpl.__version__)\r\n\r\nplt.show()\r\n```\r\n\r\nFor the first plot, with 1.5.3, the resulting image, with view limits (-0.1, 0.15), is:\r\n\r\n\r\n\r\nbut with 2.0.0rc1 in classic style, its view limits are (-0.1, 0.1):\r\n\r\n\r\n\r\nFor the second plot, with 1.5.3, the result image, with view limits (10^-3, 10^2), is:\r\n\r\n\r\nbut with 2.0.0rc1 in classic style, its view limits are (10^-7, 10^2):\r\n\r\n\r\nThe interesting thing is that this view limit is only triggered if something is plotted in both axes.","author":{"url":"https://github.com/QuLogic","@type":"Person","name":"QuLogic"},"datePublished":"2016-12-08T01:28:28.000Z","interactionStatistic":{"@type":"InteractionCounter","interactionType":"https://schema.org/CommentAction","userInteractionCount":5},"url":"https://github.com/7587/matplotlib/issues/7587"}
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