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4 rows where repo = 13221727, type = "issue" and user = 2062210 sorted by updated_at descending

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  • xarray · 4 ✖
id node_id number title user state locked assignee milestone comments created_at updated_at ▲ closed_at author_association active_lock_reason draft pull_request body reactions performed_via_github_app state_reason repo type
110890919 MDU6SXNzdWUxMTA4OTA5MTk= 621 An iris cube converter? DamienIrving 2062210 closed 0     1 2015-10-12T00:11:40Z 2017-12-20T15:14:17Z 2017-12-20T15:14:17Z NONE      

Would it be possible to include a function to convert from an xray.DataArray to an iris.cube?

For weather/climate/ocean science, xray is by far the best library for general data processing, while iris and cartopy are the best for geospatial plotting. At the moment I usually write the results of my xray data processing out to a netCDF file, then read that file in with iris for plotting. I'm assuming many other people do the same, so a .to_cube() function might allow people to skip that extra input/output step.

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  completed xarray 13221727 issue
51518779 MDU6SXNzdWU1MTUxODc3OQ== 290 Journal of Open Research Software DamienIrving 2062210 closed 0     2 2014-12-10T04:58:59Z 2016-08-04T21:17:53Z 2016-08-04T21:17:53Z NONE      

I'm envisaging that people (including myself in the future) might like to cite xray in their journal papers (along with the other software packages and libraries that they used). I was therefore wondering if you have thought about writing a paper about xray for the Journal of Open Research Software? This would be a great way for you to get academic credit for the hard work you've put into it, and would also make it very easy for authors to cite.

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  completed xarray 13221727 issue
91665446 MDU6SXNzdWU5MTY2NTQ0Ng== 447 Add rolling mean function DamienIrving 2062210 closed 0     2 2015-06-29T01:37:23Z 2015-06-29T03:17:53Z 2015-06-29T03:17:53Z NONE      

A nice addition to the time-series functionality that is built into xray would be the ability to calculate a rolling mean (e.g. for those cases where you've got daily data but you want to work on the 10-day running mean or something).

As far as I'm aware (apologies if I'm wrong), to do a rolling mean at the moment you have to convert to a pandas DataFrame, used the pandas rolling_mean() function and then convert back to an xray data array. This is fine for one dimensional data, but not so nice when you want to do it over a large (time, lat, lon) array.

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  completed xarray 13221727 issue
32763132 MDU6SXNzdWUzMjc2MzEzMg== 112 Why not CDAT? DamienIrving 2062210 closed 0     3 2014-05-04T07:03:45Z 2014-09-27T01:20:43Z 2014-09-02T03:41:41Z NONE      

In your main README file you ask the questions "Why not Pandas?" and "Why not Iris?" Another question you might want to ask is "Why not CDAT?" It was written quite a long time ago now but is still used extensively by UV-CDAT and thus by the ESGF. In particular, the cdms2, cdutil, genutil and MV2 libraries within CDAT do some of what xray does.

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  completed xarray 13221727 issue

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