html_url,issue_url,id,node_id,user,created_at,updated_at,author_association,body,reactions,performed_via_github_app,issue
https://github.com/pydata/xarray/issues/486#issuecomment-291953242,https://api.github.com/repos/pydata/xarray/issues/486,291953242,MDEyOklzc3VlQ29tbWVudDI5MTk1MzI0Mg==,3169620,2017-04-05T18:29:33Z,2017-04-05T18:29:53Z,CONTRIBUTOR,"@jhamman @godfrey4000 - I'm not sure of the status of this, but I'm the lead developer on a package called [CIS](https://github.com/cedadev/cis) which might be useful/relevant. 

It was designed as a command line tool to allow easy collocation (resampling) between different model and observation datasets, but is now also a Python library. We spent a fair amount of time thinking about the various permutations and you can see some of the details in our paper [here](http://www.geosci-model-dev.net/9/3093/2016/). Internally we currently use [Iris](https://github.com/scitools/iris) Cube-like objects but it would be pretty easy to operate on xarray Datasets since they share a similar design.

The basic syntax is: 
```
from CIS import read_data
X = read_data('some_obs_data.nc')
Y = read_data('some_other_data.nc')
X.sampled_from(Y)
# or...
Y.collocated_onto(X)
```
Happy to discuss further here, or in `xmap`.","{""total_count"": 5, ""+1"": 5, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,96211612