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issue 1
- 'levels' tick labels for discrete colormaps · 2 ✖
| id | html_url | issue_url | node_id | user | created_at | updated_at ▲ | author_association | body | reactions | performed_via_github_app | issue |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 367115118 | https://github.com/pydata/xarray/issues/1015#issuecomment-367115118 | https://api.github.com/repos/pydata/xarray/issues/1015 | MDEyOklzc3VlQ29tbWVudDM2NzExNTExOA== | fmaussion 10050469 | 2018-02-20T20:52:15Z | 2018-02-20T20:52:15Z | MEMBER | I think a doc example would be enough. For example in the gallery? http://xarray.pydata.org/en/latest/auto_gallery/index.html |
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'levels' tick labels for discrete colormaps 178501065 | |
| 248847812 | https://github.com/pydata/xarray/issues/1015#issuecomment-248847812 | https://api.github.com/repos/pydata/xarray/issues/1015 | MDEyOklzc3VlQ29tbWVudDI0ODg0NzgxMg== | fmaussion 10050469 | 2016-09-22T09:00:56Z | 2016-09-22T09:00:56Z | MEMBER | Note that currently the colorbar labelling logic is handed over entirely to matplotlib, so its mpl which decides upon this. With the ``` python from matplotlib import pyplot as plt import xarray as xr data = xr.DataArray(np.arange(12).reshape((3, 4))10 + 10) levels = np.append(np.arange(10)10 + 10, 115) f, (ax1, ax2, ax3) = plt.subplots(1, 3, figsize=(14, 4)) data.plot(ax=ax1, levels=levels) data.plot(ax=ax2, levels=levels, cbar_kwargs={'ticks':levels}) data.plot(ax=ax3, levels=levels, cbar_kwargs={'ticks':levels, 'spacing':'proportional'}) plt.tight_layout() ```
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'levels' tick labels for discrete colormaps 178501065 |
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