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{"@context":"https://schema.org","@type":"DiscussionForumPosting","headline":"Adding cyclic point feature","articleBody":"I will address the same issue as for **Cartopy** (https://github.com/SciTools/cartopy/issues/1402). I would find extremely useful to have an automatic behavior of adding a **cyclic point** when needed, or at least add an option when doing a plot. \r\n\r\nHere is an example of what I mean (data: [ens_avg_snow.zip](https://github.com/lukelbd/proplot/files/3922831/ens_avg_snow.zip)):\r\n```python\r\nimport xarray as xr\r\nimport proplot as plot\r\n\r\nens_avg_snow = xr.open_dataarray('ens_avg_snow.nc')\r\n\r\nf, axs = plot.subplots(proj='cyl', width=8)\r\nm = axs[0].contourf(ens_avg_snow, cmap='BuRd')\r\nf.colorbar(m)\r\naxs.format(\r\n    geogridlinewidth=0.5, geogridcolor='gray8', geogridalpha=0.5, labels=True, \r\n    coast=True, ocean=True, oceancolor='gray3', latlim=(20,90),\r\n)\r\n```\r\n![proplot_cyclic_point](https://user-images.githubusercontent.com/20254164/70159609-7c655d00-16b9-11ea-8775-196183f02eb7.jpg)\r\n\r\nAs you can see, there is a white line at 0° of longitude. I usually use the `add_cyclic_point` function of `cartopy.utils` but it is not straightforward for DataArrays because it doesn't keep the coordinates and attributes. I recently found some very useful code here: https://github.com/darothen/plot-all-in-ncfile/blob/master/plot_util.py that allows to do it easily with the function `cyclic_dataarray` and there is also a `check_cyclic` that could be used for automatically checking it.\r\n\r\nHere is the function that allows adding a cyclic point (from the link above):\r\n```python\r\nfrom cartopy.util import add_cyclic_point\r\n\r\n# https://github.com/darothen/plot-all-in-ncfile/blob/master/plot_util.py\r\ndef cyclic_dataarray(da, coord='lon'):\r\n    \"\"\" Add a cyclic coordinate point to a DataArray along a specified\r\n    named coordinate dimension.\r\n    \"\"\"\r\n    assert isinstance(da, xr.DataArray)\r\n\r\n    lon_idx = da.dims.index(coord)\r\n    cyclic_data, cyclic_coord = add_cyclic_point(da.values,\r\n                                                 coord=da.coords[coord],\r\n                                                 axis=lon_idx)\r\n\r\n    # Copy and add the cyclic coordinate and data\r\n    new_coords = dict(da.coords)\r\n    new_coords[coord] = cyclic_coord\r\n    new_values = cyclic_data\r\n\r\n    new_da = xr.DataArray(new_values, dims=da.dims, coords=new_coords)\r\n\r\n    # Copy the attributes for the re-constructed data and coords\r\n    for att, val in da.attrs.items():\r\n        new_da.attrs[att] = val\r\n    for c in da.coords:\r\n        for att in da.coords[c].attrs:\r\n            new_da.coords[c].attrs[att] = da.coords[c].attrs[att]\r\n\r\n    return new_da\r\n```\r\nThus `ens_avg_snow_cyclic = cyclic_dataarray(ens_avg_snow)` allows to make back the previous plot without the white line. Incorporating this directly into **ProPlot** would be nice so that we can just add an option like for example `add_cyclic=True` (just need to be careful about the dimension to do the cyclic or have another way to pass it). \r\n\r\n\r\n","author":{"url":"https://github.com/mickaellalande","@type":"Person","name":"mickaellalande"},"datePublished":"2019-12-04T16:27:00.000Z","interactionStatistic":{"@type":"InteractionCounter","interactionType":"https://schema.org/CommentAction","userInteractionCount":13},"url":"https://github.com/82/proplot/issues/82"}