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/1371#issuecomment-473387146,https://api.github.com/repos/pydata/xarray/issues/1371,473387146,MDEyOklzc3VlQ29tbWVudDQ3MzM4NzE0Ng==,5572303,2019-03-15T18:01:31Z,2019-03-15T18:01:31Z,CONTRIBUTOR,"My personal hope is to keep this thread open just for the record. But given the non-activity on the numpy end, I honestly can't promise any resolution to this issue in the near future. Thanks!
PS I persist because some people do seem to appreciate that PR and have forked it for their own use :)","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,221366244
https://github.com/pydata/xarray/issues/1371#issuecomment-473033854,https://api.github.com/repos/pydata/xarray/issues/1371,473033854,MDEyOklzc3VlQ29tbWVudDQ3MzAzMzg1NA==,5572303,2019-03-14T19:52:33Z,2019-03-14T19:52:33Z,CONTRIBUTOR,"So, as per suggestion by Stephan, I submitted the PR to numpy instead: https://github.com/numpy/numpy/pull/9211
Despite having possibly the highest number of comments of all active numpy PRs and passing all the tests, it's been sitting in limbo for the last few months. There seems to be quite some uncertainty about what to do with it, and the discussion has gone off tangent a bit to more upstream issues.
My hope is still to have it eventually merged into numpy, so that it could be easily ported to xarray.
It's proven to be quite useful to my coworkers, as well as some of the numpy users. I believe it'll also serve xarray well. Thank you all for your patience.","{""total_count"": 1, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 1}",,221366244
https://github.com/pydata/xarray/issues/1420#issuecomment-303255121,https://api.github.com/repos/pydata/xarray/issues/1420,303255121,MDEyOklzc3VlQ29tbWVudDMwMzI1NTEyMQ==,5572303,2017-05-23T00:21:29Z,2017-05-23T00:21:29Z,CONTRIBUTOR,"This is getting close to the fundamental paradigm of xarray. Would it entail some massive code migration (and user protests) if we change how we express `da.coords['x']`(by removing point coordinates)?
I'm thinking of a new API that compares only the values and indexing coordinates between two objects, but struggle to come up with a simple, descriptive name........","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,230529125
https://github.com/pydata/xarray/issues/1420#issuecomment-303244294,https://api.github.com/repos/pydata/xarray/issues/1420,303244294,MDEyOklzc3VlQ29tbWVudDMwMzI0NDI5NA==,5572303,2017-05-22T23:09:39Z,2017-05-22T23:09:39Z,CONTRIBUTOR,"I'm just having a hard time wrapping my head around the definitions here. `da['some_attr'] = 0` sets a point coordinate, and this point coordinate shows up in `da.coords`, but not `da.dims`, because `da.dims` only pertains to indexing coordinates. Why is this point coordinate attached to every other coordinate then? In other words, why would `da.coords['x']` contain `some_attr` as well?
Somehow it just doesn't feel right intuitively for some point dimension to mess up my comparison between two 1-D coordinates, but I might be missing some important use cases here.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,230529125
https://github.com/pydata/xarray/pull/1389#issuecomment-301135310,https://api.github.com/repos/pydata/xarray/issues/1389,301135310,MDEyOklzc3VlQ29tbWVudDMwMTEzNTMxMA==,5572303,2017-05-12T17:18:49Z,2017-05-12T17:18:49Z,CONTRIBUTOR,"Thank you very much for your patience!
BTW, I think I messed up my co-worker's name in `whats-new.rst`. The spelling is right (Kyle Heuton), but the extra indentation shouldn't be there. As a result his name appears a bit out of place. Would be very much obliged if you could fix that in your next push to master. Gracias.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,225222227
https://github.com/pydata/xarray/pull/1389#issuecomment-300947995,https://api.github.com/repos/pydata/xarray/issues/1389,300947995,MDEyOklzc3VlQ29tbWVudDMwMDk0Nzk5NQ==,5572303,2017-05-11T23:59:29Z,2017-05-11T23:59:29Z,CONTRIBUTOR,`api.rst` should've been a checklist item :),"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,225222227
https://github.com/pydata/xarray/pull/1389#issuecomment-300850103,https://api.github.com/repos/pydata/xarray/issues/1389,300850103,MDEyOklzc3VlQ29tbWVudDMwMDg1MDEwMw==,5572303,2017-05-11T16:51:34Z,2017-05-11T16:51:34Z,CONTRIBUTOR,"If that's the case then I have nothing more to add. I've run flake8 on the individual files I touched I as well, such as `flake8 xarray/core/dataset.py`, and none of my changes are flagged.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,225222227
https://github.com/pydata/xarray/pull/1389#issuecomment-300675689,https://api.github.com/repos/pydata/xarray/issues/1389,300675689,MDEyOklzc3VlQ29tbWVudDMwMDY3NTY4OQ==,5572303,2017-05-11T03:55:58Z,2017-05-11T03:55:58Z,CONTRIBUTOR,"` git diff upstream/master | flake8 --diff` only complains about a bunch of lines in `whats-new.rst` and `reshaping.rst`. But these complaints don't make any sense to me. Some examples:
```
doc/reshaping.rst:195:1: E112 expected an indented block
doc/reshaping.rst:203:1: E101 indentation contains mixed spaces and tabs
doc/reshaping.rst:203:1: W191 indentation contains tabs
doc/reshaping.rst:203:2: E113 unexpected indentation
```
I've played around with it a bit but not seen any changes to the complaints. What is going on? Should I even worry about the `.rst` files?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,225222227
https://github.com/pydata/xarray/pull/1389#issuecomment-300600778,https://api.github.com/repos/pydata/xarray/issues/1389,300600778,MDEyOklzc3VlQ29tbWVudDMwMDYwMDc3OA==,5572303,2017-05-10T20:20:12Z,2017-05-10T20:20:12Z,CONTRIBUTOR,"Haha, brilliant.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,225222227
https://github.com/pydata/xarray/pull/1389#issuecomment-300566860,https://api.github.com/repos/pydata/xarray/issues/1389,300566860,MDEyOklzc3VlQ29tbWVudDMwMDU2Njg2MA==,5572303,2017-05-10T18:08:33Z,2017-05-10T18:08:33Z,CONTRIBUTOR,"I just made some futile attempts to find that checklist, to no avail. Mind helping me with a link? :)","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,225222227
https://github.com/pydata/xarray/pull/1389#issuecomment-300555321,https://api.github.com/repos/pydata/xarray/issues/1389,300555321,MDEyOklzc3VlQ29tbWVudDMwMDU1NTMyMQ==,5572303,2017-05-10T17:30:32Z,2017-05-10T17:30:32Z,CONTRIBUTOR,"Today is the first time I've heard of flake8. Is this how you guys standardize quality checks? If so, do you run once for python 3.5 and once for 2.7?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,225222227
https://github.com/pydata/xarray/pull/1389#issuecomment-300534562,https://api.github.com/repos/pydata/xarray/issues/1389,300534562,MDEyOklzc3VlQ29tbWVudDMwMDUzNDU2Mg==,5572303,2017-05-10T16:16:28Z,2017-05-10T16:16:28Z,CONTRIBUTOR,Looks ready now.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,225222227
https://github.com/pydata/xarray/pull/1389#issuecomment-300306624,https://api.github.com/repos/pydata/xarray/issues/1389,300306624,MDEyOklzc3VlQ29tbWVudDMwMDMwNjYyNA==,5572303,2017-05-09T21:27:06Z,2017-05-09T21:27:06Z,CONTRIBUTOR,Think I just copied something over from `variable.py` and changed the message a little bit...,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,225222227
https://github.com/pydata/xarray/pull/1389#issuecomment-300289437,https://api.github.com/repos/pydata/xarray/issues/1389,300289437,MDEyOklzc3VlQ29tbWVudDMwMDI4OTQzNw==,5572303,2017-05-09T20:20:44Z,2017-05-09T20:20:44Z,CONTRIBUTOR," From numpy 1.11.0 release notes:
```
np.lexsort now supports arrays with object data-type
The function now internally calls the generic npy_amergesort when the type does not implement a merge-sort kind of argsort method.
```","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,225222227
https://github.com/pydata/xarray/pull/1389#issuecomment-300283451,https://api.github.com/repos/pydata/xarray/issues/1389,300283451,MDEyOklzc3VlQ29tbWVudDMwMDI4MzQ1MQ==,5572303,2017-05-09T19:57:39Z,2017-05-09T19:57:39Z,CONTRIBUTOR,"1.10.4 failed with the merge sort error. 1.11.0 failed with some error that had nothing to do with merge sort (` Reason: image not found. Make sure your test modules/packages have valid Python names.`) Starting from 1.11.1 it works fine.
What's the best course of action now?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,225222227
https://github.com/pydata/xarray/pull/1389#issuecomment-300267772,https://api.github.com/repos/pydata/xarray/issues/1389,300267772,MDEyOklzc3VlQ29tbWVudDMwMDI2Nzc3Mg==,5572303,2017-05-09T18:57:51Z,2017-05-09T18:57:51Z,CONTRIBUTOR,"If I downgrade to numpy 1.10, I get that error. Once upgraded to 1.12, it goes away......
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,225222227
https://github.com/pydata/xarray/pull/1389#issuecomment-300029141,https://api.github.com/repos/pydata/xarray/issues/1389,300029141,MDEyOklzc3VlQ29tbWVudDMwMDAyOTE0MQ==,5572303,2017-05-09T00:39:44Z,2017-05-09T00:39:44Z,CONTRIBUTOR,Perhaps it's finally ready for prime time?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,225222227
https://github.com/pydata/xarray/pull/1389#issuecomment-299645639,https://api.github.com/repos/pydata/xarray/issues/1389,299645639,MDEyOklzc3VlQ29tbWVudDI5OTY0NTYzOQ==,5572303,2017-05-06T15:04:31Z,2017-05-06T15:04:31Z,CONTRIBUTOR,I've added a tiny bit of extra docstring just to ease my discomfort about the NaN sort. If you feel it's redundant I can remove it.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,225222227
https://github.com/pydata/xarray/pull/1389#issuecomment-299230655,https://api.github.com/repos/pydata/xarray/issues/1389,299230655,MDEyOklzc3VlQ29tbWVudDI5OTIzMDY1NQ==,5572303,2017-05-04T16:01:45Z,2017-05-04T16:01:45Z,CONTRIBUTOR,Almost time to merge this baby in? :),"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,225222227
https://github.com/pydata/xarray/issues/1374#issuecomment-298802941,https://api.github.com/repos/pydata/xarray/issues/1374,298802941,MDEyOklzc3VlQ29tbWVudDI5ODgwMjk0MQ==,5572303,2017-05-03T01:14:12Z,2017-05-03T01:14:12Z,CONTRIBUTOR,This has impacted our workflow as well. Please let us know if we can help.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,221855729
https://github.com/pydata/xarray/pull/1389#issuecomment-298365438,https://api.github.com/repos/pydata/xarray/issues/1389,298365438,MDEyOklzc3VlQ29tbWVudDI5ODM2NTQzOA==,5572303,2017-05-01T16:18:55Z,2017-05-01T16:18:55Z,CONTRIBUTOR,"Weird. Travis seems to fail in places unrelated to my changes.
I'm rather agnostic to `sortby` vs. `sort_by`.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,225222227
https://github.com/pydata/xarray/issues/967#issuecomment-298109506,https://api.github.com/repos/pydata/xarray/issues/967,298109506,MDEyOklzc3VlQ29tbWVudDI5ODEwOTUwNg==,5572303,2017-04-28T21:20:57Z,2017-04-28T21:20:57Z,CONTRIBUTOR,"Sounds good. As I'm writing the type-checking code I run into this question: Why would I have a `xarray.core.dataset.DataVariables` object as input? A DataVariables object could contain multiple DataArrays, which makes the interpretation a bit unclear. In my mind it should only be 1.) name(s) of existing index coords, or 2.) 1D DataArray(s) with dim in `self.dims`","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,171077425
https://github.com/pydata/xarray/issues/1113#issuecomment-298054041,https://api.github.com/repos/pydata/xarray/issues/1113,298054041,MDEyOklzc3VlQ29tbWVudDI5ODA1NDA0MQ==,5572303,2017-04-28T17:09:09Z,2017-04-28T17:09:09Z,CONTRIBUTOR,Just did. Got it to work. Muchas Gracias.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,188869101
https://github.com/pydata/xarray/issues/967#issuecomment-297875052,https://api.github.com/repos/pydata/xarray/issues/967,297875052,MDEyOklzc3VlQ29tbWVudDI5Nzg3NTA1Mg==,5572303,2017-04-28T00:27:46Z,2017-04-28T00:27:46Z,CONTRIBUTOR,"What would the signature of `sortby()` be then? On our end we just want a more intuitive way to sort by dimension labels, so now I have `sort_index(self, dims, ascending=True)`. `sortby()`, based on your description, seems like a separate method. Or any suggestion on how we can marry the two into something coherent?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,171077425
https://github.com/pydata/xarray/issues/967#issuecomment-297868909,https://api.github.com/repos/pydata/xarray/issues/967,297868909,MDEyOklzc3VlQ29tbWVudDI5Nzg2ODkwOQ==,5572303,2017-04-27T23:43:12Z,2017-04-27T23:43:12Z,CONTRIBUTOR,"A couple of things:
1.) Upon a little thinking I believe `sort_values()` doesn't make much sense, so I'm only working on `sort_index()'.
2.) the way I handle the `inplace` kwarg is by
```
if inplace:
self = self.isel(**{d: self.indexes[d].argsort()
if ascending
else self.indexes[d].argsort()[::-1]
for d in dimensions})
else:
return self.isel(**{d: self.indexes[d].argsort()
if ascending
else self.indexes[d].argsort()[::-1]
for d in dimensions})
```
But when I run
```
ds.sort_index(dims=['x', 'y'], inplace=True)
```
nothing changes. If I put a `pdb.set_trace()` right below the self = self*** I can evaluate self and see that it's what I want it to be. But somehow that assignment is not realized to the higher level. Any quick pointer?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,171077425
https://github.com/pydata/xarray/issues/1113#issuecomment-297835073,https://api.github.com/repos/pydata/xarray/issues/1113,297835073,MDEyOklzc3VlQ29tbWVudDI5NzgzNTA3Mw==,5572303,2017-04-27T20:48:44Z,2017-04-27T20:48:44Z,CONTRIBUTOR,"When I do `conda install netcdf4`, it ends up downgrading my numpy from 1.12.0 to 1.11.3, which triggers other dependency-related problems in my code. Is there a different solution to this problem?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,188869101
https://github.com/pydata/xarray/issues/967#issuecomment-296394094,https://api.github.com/repos/pydata/xarray/issues/967,296394094,MDEyOklzc3VlQ29tbWVudDI5NjM5NDA5NA==,5572303,2017-04-22T18:57:07Z,2017-04-22T18:57:07Z,CONTRIBUTOR,"On our end, we currently do the following when we need to sort by axis label (lat/lon in this case):
```
da.reindex(indexers={'lat':sorted(da.coords['lat'].values), 'lon':sorted(da.coords['lon'].values)})
```
Upon first glance of the source code I think our approach goes down different code path than your `.isel()` approach. The most obvious difference, from a user's stand point, is probably that `.reindex()` returns a new object, whereas `.isel()` returns a view (typically). In Pandas, both `sort_index()` and `sort_values()` seem to return new objects.
We'd be happy to contribute to an xarray version of `sort_index()` and `sort_values()`. The first question is, which one would be the more robust and computationally efficient code path to take?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,171077425
https://github.com/pydata/xarray/issues/1371#issuecomment-293730368,https://api.github.com/repos/pydata/xarray/issues/1371,293730368,MDEyOklzc3VlQ29tbWVudDI5MzczMDM2OA==,5572303,2017-04-12T22:56:42Z,2017-04-12T22:56:42Z,CONTRIBUTOR,"Cool, let me toss it out on the numpy board and see what they think.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,221366244
https://github.com/pydata/xarray/pull/924#issuecomment-287904381,https://api.github.com/repos/pydata/xarray/issues/924,287904381,MDEyOklzc3VlQ29tbWVudDI4NzkwNDM4MQ==,5572303,2017-03-20T21:30:32Z,2017-03-20T21:30:32Z,CONTRIBUTOR,This functionality is quite important to us as well. How might we help? Should I simply fork `groupby-multiple-args`?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,168272291
https://github.com/pydata/xarray/pull/1204#issuecomment-274641832,https://api.github.com/repos/pydata/xarray/issues/1204,274641832,MDEyOklzc3VlQ29tbWVudDI3NDY0MTgzMg==,5572303,2017-01-23T22:43:32Z,2017-01-23T22:43:32Z,CONTRIBUTOR,tears in my eyes.......,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,200478981
https://github.com/pydata/xarray/pull/1204#issuecomment-274574880,https://api.github.com/repos/pydata/xarray/issues/1204,274574880,MDEyOklzc3VlQ29tbWVudDI3NDU3NDg4MA==,5572303,2017-01-23T18:30:14Z,2017-01-23T18:30:14Z,CONTRIBUTOR,checking in on this PR...,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,200478981
https://github.com/pydata/xarray/pull/1204#issuecomment-274195788,https://api.github.com/repos/pydata/xarray/issues/1204,274195788,MDEyOklzc3VlQ29tbWVudDI3NDE5NTc4OA==,5572303,2017-01-20T22:22:01Z,2017-01-20T22:22:01Z,CONTRIBUTOR,time to merge this guy?,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,200478981
https://github.com/pydata/xarray/pull/1204#issuecomment-273676997,https://api.github.com/repos/pydata/xarray/issues/1204,273676997,MDEyOklzc3VlQ29tbWVudDI3MzY3Njk5Nw==,5572303,2017-01-19T04:06:45Z,2017-01-19T04:06:45Z,CONTRIBUTOR,I'm not sure why continuous integration check is taking forever.....,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,200478981
https://github.com/pydata/xarray/pull/1204#issuecomment-272582190,https://api.github.com/repos/pydata/xarray/issues/1204,272582190,MDEyOklzc3VlQ29tbWVudDI3MjU4MjE5MA==,5572303,2017-01-14T00:14:17Z,2017-01-14T00:14:17Z,CONTRIBUTOR,"So I addressed some of the comments, but not all. Please let me know what you think.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,200478981
https://github.com/pydata/xarray/issues/1072#issuecomment-271461749,https://api.github.com/repos/pydata/xarray/issues/1072,271461749,MDEyOklzc3VlQ29tbWVudDI3MTQ2MTc0OQ==,5572303,2017-01-10T01:37:22Z,2017-01-10T01:37:22Z,CONTRIBUTOR,"I'm curious, if you put a `from .computation import apply_ufunc` inside `ops.py`, would you not get some circular ImportError? Seems difficult to get out of this circle......","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,186680248
https://github.com/pydata/xarray/issues/1072#issuecomment-270810132,https://api.github.com/repos/pydata/xarray/issues/1072,270810132,MDEyOklzc3VlQ29tbWVudDI3MDgxMDEzMg==,5572303,2017-01-06T01:47:20Z,2017-01-06T01:47:20Z,CONTRIBUTOR,Ok I'll give it a shot. Will touch base when I run into roadblocks.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,186680248
https://github.com/pydata/xarray/issues/1072#issuecomment-270797694,https://api.github.com/repos/pydata/xarray/issues/1072,270797694,MDEyOklzc3VlQ29tbWVudDI3MDc5NzY5NA==,5572303,2017-01-06T00:25:54Z,2017-01-06T00:25:54Z,CONTRIBUTOR,"So I took at quick look at the commits in #964. It's not entirely clear to me how one can easily add a `join` argument to `fillna`. Should I keep my current commits, and just submit a PR to master once #964 is merged in, and then we could see how it goes from there?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,186680248
https://github.com/pydata/xarray/issues/1072#issuecomment-260716231,https://api.github.com/repos/pydata/xarray/issues/1072,260716231,MDEyOklzc3VlQ29tbWVudDI2MDcxNjIzMQ==,5572303,2016-11-15T17:57:19Z,2016-11-15T17:57:19Z,CONTRIBUTOR,"Checking in on how to move forward from here...I feel it's pretty close to a PR...
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,186680248
https://github.com/pydata/xarray/issues/1072#issuecomment-260431105,https://api.github.com/repos/pydata/xarray/issues/1072,260431105,MDEyOklzc3VlQ29tbWVudDI2MDQzMTEwNQ==,5572303,2016-11-14T19:11:55Z,2016-11-14T19:11:55Z,CONTRIBUTOR,"Currently, `ds0.combine_first(ds1)` gives exactly the same result as `xr.merge([ds0, ds1])`. But for data arrays it still offers something new.
Either
1.) my `combine_first` should be doing something different with datasets, or
2.) we don't need a `combine_first` for datasets, or
3.) change `xr.merge` so that when applied to data arrays, it creates a new data array with outer-join and fillna (by chaining `combine_first` down the list of data arrays).
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,186680248
https://github.com/pydata/xarray/issues/1072#issuecomment-260411626,https://api.github.com/repos/pydata/xarray/issues/1072,260411626,MDEyOklzc3VlQ29tbWVudDI2MDQxMTYyNg==,5572303,2016-11-14T18:02:47Z,2016-11-14T18:02:47Z,CONTRIBUTOR,"I suppose I can save one line by getting rid of the duplicate `f = _func_slash_method_wrapper(fillna)`, but besides that I'm not sure what's the best way to refactor this.
If the behaviors check out, then this branch might be ready for a PR.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,186680248
https://github.com/pydata/xarray/issues/1072#issuecomment-260166034,https://api.github.com/repos/pydata/xarray/issues/1072,260166034,MDEyOklzc3VlQ29tbWVudDI2MDE2NjAzNA==,5572303,2016-11-13T04:14:38Z,2016-11-13T04:14:38Z,CONTRIBUTOR,"So these are my `_fillna` and `_combine_first` in `ops.inject_binary_ops`:
```
f = _func_slash_method_wrapper(fillna)
method = cls._binary_op(f, join='left', fillna=True)
setattr(cls, '_fillna', method)
f = _func_slash_method_wrapper(fillna)
method = cls._binary_op(f, join='outer', fillna=True)
setattr(cls, '_combine_first', method)
```
Within dataarray.py and dataset.py, `combine_first(self, other)` simply returns `self._combine_first(other)`. This code path renders the test results you saw earlier.
Given this construct, I'm not sure how to do the refactor like you mentioned. Perhaps a few more pointers to the right direction? :)
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,186680248
https://github.com/pydata/xarray/issues/1072#issuecomment-260137121,https://api.github.com/repos/pydata/xarray/issues/1072,260137121,MDEyOklzc3VlQ29tbWVudDI2MDEzNzEyMQ==,5572303,2016-11-12T17:48:08Z,2016-11-12T17:48:08Z,CONTRIBUTOR,"hmm, so what would be an expected behavior of `ds.combine_first`?
If I have
```
>>> ds0
Dimensions: (x: 2, y: 2)
Coordinates:
* x (x) |S1 'a' 'b'
* y (y) int64 -1 0
Data variables:
ds0 (x, y) int64 0 0 0 0
>>> ds1
Dimensions: (x: 2, y: 2)
Coordinates:
* x (x) |S1 'b' 'c'
* y (y) int64 0 1
Data variables:
ds1 (x, y) int64 1 1 1 1
```
I get
```
>>> ds0.combine_first(ds1)
Dimensions: (x: 3, y: 3)
Coordinates:
* x (x) object 'a' 'b' 'c'
* y (y) int64 -1 0 1
Data variables:
ds0 (x, y) float64 0.0 0.0 nan 0.0 0.0 nan nan nan nan
ds1 (x, y) float64 nan nan nan nan 1.0 1.0 nan 1.0 1.0
```
and changing the order to `ds1.combine_first(ds0)` just flips the order of the data_vars, but the cell values of the data_vars remain the same.
This is done essentially by adding a `_combine_first` to `ops.py` that mimics `_fillna`, except `join='outer'`.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,186680248
https://github.com/pydata/xarray/pull/1065#issuecomment-260100010,https://api.github.com/repos/pydata/xarray/issues/1065,260100010,MDEyOklzc3VlQ29tbWVudDI2MDEwMDAxMA==,5572303,2016-11-12T04:00:10Z,2016-11-12T04:00:10Z,CONTRIBUTOR,"woohoo!
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,185794232
https://github.com/pydata/xarray/issues/1072#issuecomment-259842225,https://api.github.com/repos/pydata/xarray/issues/1072,259842225,MDEyOklzc3VlQ29tbWVudDI1OTg0MjIyNQ==,5572303,2016-11-10T23:49:07Z,2016-11-10T23:49:07Z,CONTRIBUTOR,"Any suggestion on improvement?
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,186680248
https://github.com/pydata/xarray/pull/1065#issuecomment-259842050,https://api.github.com/repos/pydata/xarray/issues/1065,259842050,MDEyOklzc3VlQ29tbWVudDI1OTg0MjA1MA==,5572303,2016-11-10T23:48:11Z,2016-11-10T23:48:11Z,CONTRIBUTOR,"Alright, if that's desired, I'd just change code in `apply_over_both()` of `dataset._calculate_binary_op` to react to different kwarg values, and adding a method in `test_dataset.py`. Should be able to push before the weekend is over.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,185794232
https://github.com/pydata/xarray/pull/1065#issuecomment-259750146,https://api.github.com/repos/pydata/xarray/issues/1065,259750146,MDEyOklzc3VlQ29tbWVudDI1OTc1MDE0Ng==,5572303,2016-11-10T17:15:29Z,2016-11-10T17:15:29Z,CONTRIBUTOR,"Just checking in. Is there something else that needs to be added to this PR before merge?
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,185794232
https://github.com/pydata/xarray/issues/1072#issuecomment-259272844,https://api.github.com/repos/pydata/xarray/issues/1072,259272844,MDEyOklzc3VlQ29tbWVudDI1OTI3Mjg0NA==,5572303,2016-11-08T21:59:06Z,2016-11-08T22:10:54Z,CONTRIBUTOR,"So I spent some time looking at `dataset._calculate_binary_op` but couldn't quite come up with what I wanted. After banging my head against the wall a bit this is what I have:
```
def combine_first(left, right):
la, ra = xr.align(left, right, join='outer', copy=False) # should copy=True?
la, ra = la.where(ra.isnull() | ra.notnull()), ra.where(la.isnull() | la.notnull())
ra.values[la.notnull().values] = la.values[la.notnull().values]
return ra
```
And it seems to work. My test cases are
```
>>> l_2d
array([[1, 1],
[1, 1]])
Coordinates:
* x (x) |S1 'a' 'b'
* y (y) int64 -2 0
>>> r_2d
array([[0, 0],
[0, 0]])
Coordinates:
* x (x) |S1 'b' 'c'
* y (y) int64 0 2
>>> ar_1d
array([4, 5, 6])
Coordinates:
* x (x) |S1 'a' 'b' 'd'
```
and here are the results:
```
>>> combine_first(l_2d, r_2d)
array([[ 1., 1., nan],
[ 1., 1., 0.],
[ nan, 0., 0.]])
Coordinates:
* x (x) object 'a' 'b' 'c'
* y (y) int64 -2 0 2
>>> combine_first(r_2d, l_2d)
array([[ 1., 1., nan],
[ 1., 0., 0.],
[ nan, 0., 0.]])
Coordinates:
* x (x) object 'a' 'b' 'c'
* y (y) int64 -2 0 2
>>> combine_first(l_2d, ar_1d)
array([[ 1., 1.],
[ 1., 1.],
[ 6., 6.]])
Coordinates:
* x (x) object 'a' 'b' 'd'
* y (y) int64 -2 0
>>> combine_first(ar_1d, l_2d)
array([[ 4., 4.],
[ 5., 5.],
[ 6., 6.]])
Coordinates:
* x (x) object 'a' 'b' 'd'
* y (y) int64 -2 0
```
I don't like the fact that I have to access `.values`, and the use of `.where` is slightly wonky. But this is definitely the cleanest working solution I have thus far. Any suggestion to improve is welcome.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,186680248
https://github.com/pydata/xarray/issues/1072#issuecomment-258718234,https://api.github.com/repos/pydata/xarray/issues/1072,258718234,MDEyOklzc3VlQ29tbWVudDI1ODcxODIzNA==,5572303,2016-11-06T23:02:01Z,2016-11-06T23:15:30Z,CONTRIBUTOR,"Thanks for the reply. Would it make things easier if `c, d = xr.align(a, b, join=""outer"")` explicitly broadcasts missing dimensions in all returned values? Currently, if `b` is missing a dimension, then `d` would also miss a dimension:
```
>>> a
array([[1, 1],
[1, 1]])
Coordinates:
* x (x) |S1 'a' 'b'
* y (y) int64 -2 0
>>> b
array([4, 5, 6])
Coordinates:
* x (x) |S1 'a' 'b' 'd'
>>> c, d = xr.align(a, b, join=""outer"")
>>> c
array([[ 1., 1.],
[ 1., 1.],
[ nan, nan]])
Coordinates:
* x (x) object 'a' 'b' 'd'
* y (y) int64 -2 0
>>> d
array([4, 5, 6])
Coordinates:
* x (x) object 'a' 'b' 'd'
```
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,186680248
https://github.com/pydata/xarray/issues/1072#issuecomment-258567735,https://api.github.com/repos/pydata/xarray/issues/1072,258567735,MDEyOklzc3VlQ29tbWVudDI1ODU2NzczNQ==,5572303,2016-11-04T22:58:24Z,2016-11-04T22:58:24Z,CONTRIBUTOR,"Another test:
```
>>> left
array([[1, 1],
[1, 1]])
Coordinates:
* x (x) |S1 'a' 'b'
* y (y) int64 -2 0
>>> right
array([[0, 0],
[0, 0]])
Coordinates:
* x (x) |S1 'b' 'c'
* y (y) int64 0 2
>>> combine_first(left, right)
array([[ 1., 1., nan],
[ 1., 1., 0.],
[ nan, 0., 0.]])
Coordinates:
* x (x) object 'a' 'b' 'c'
* y (y) int64 -2 0 2
>>> combine_first(right, left)
array([[ 1., 1., nan],
[ 1., 0., 0.],
[ nan, 0., 0.]])
Coordinates:
* x (x) object 'a' 'b' 'c'
* y (y) int64 -2 0 2
```
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,186680248
https://github.com/pydata/xarray/issues/1072#issuecomment-258294667,https://api.github.com/repos/pydata/xarray/issues/1072,258294667,MDEyOklzc3VlQ29tbWVudDI1ODI5NDY2Nw==,5572303,2016-11-03T22:35:47Z,2016-11-03T22:35:47Z,CONTRIBUTOR,"Here's my somewhat hacky stab at it, not optimized for speed/efficiency:
```
def combine_first(left, right):
""""""
Takes 2 data arrays, performs an outer-concat, using values from the right array to
fill in for missing coordinates in the left array.
""""""
l_aligned, r_aligned = xr.align(left, right, join=""outer"")
temp = l_aligned + r_aligned # hack
temp.values[temp.notnull().values] = np.nan # now template is all nan
# insert non-nan values from right array first
temp.values[r_aligned.notnull().values] = r_aligned.values[r_aligned.notnull().values]
# insert values from left array, overwriting those from right array
temp.values[l_aligned.notnull().values] = l_aligned.values[l_aligned.notnull().values]
return temp
```
And the result:
```
>>> ar1 = xr.DataArray([4,5,6],[('x',[1,2,3])])
>>> ar2 = xr.DataArray([[7,8,9],[10,11,12],[13,14,15]],[('x',[1,12,13]),('y',[0,5,6])])
>>> ar1
array([4, 5, 6])
Coordinates:
* x (x) int64 1 2 3
>>> ar2
array([[ 7, 8, 9],
[10, 11, 12],
[13, 14, 15]])
Coordinates:
* x (x) int64 1 12 13
* y (y) int64 0 5 6
>>> temp = combine_first(ar1, ar2)
>>> temp
array([[ 4., 5., 6.],
[ 4., 5., 6.],
[ 4., 5., 6.],
[ 10., 11., 12.],
[ 13., 14., 15.]])
Coordinates:
* x (x) int64 1 2 3 12 13
* y (y) int64 0 5 6
>>> temp = combine_first(ar2, ar1)
>>> temp
array([[ 7., 8., 9.],
[ 4., 5., 6.],
[ 4., 5., 6.],
[ 10., 11., 12.],
[ 13., 14., 15.]])
Coordinates:
* x (x) int64 1 2 3 12 13
* y (y) int64 0 5 6
```
Would this be the behavior we want from xarray's `combine_first`? Not entirely analogous to the Pandas function. Maybe rename it?
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,186680248
https://github.com/pydata/xarray/issues/1072#issuecomment-258234611,https://api.github.com/repos/pydata/xarray/issues/1072,258234611,MDEyOklzc3VlQ29tbWVudDI1ODIzNDYxMQ==,5572303,2016-11-03T18:35:13Z,2016-11-03T20:25:12Z,CONTRIBUTOR,"So I fooled around with Pandas' `combine_first`:
```
>>> df1 = pd.DataFrame({'x':[1,2,3],'z':[4,5,6]}).set_index('x')
>>> df1
z
x
1 4
2 5
3 6
>>> df2 = pd.DataFrame({'x':[1,12,13],'y':[0,5,6],'z':[7,8,9]}).set_index(['x','y'])
>>> df2
z
x y
1 0 7
12 5 8
13 6 9
>>> df1.combine_first(df2)
z
x y
1 0 4.0
12 5 8.0
13 6 9.0
```
and was surprised that the indexes were not ""outer-joined"". Is this the behavior xarray wants to emulate?
As a mockup for `xr.combine_first(arr1, arr2)`, I was thinking about using `align([arr1, arr2], join=""outer"")` to set up the template, and then go into the template to set the values right. Is that a sound approach? Muchas gracias.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,186680248
https://github.com/pydata/xarray/issues/1072#issuecomment-258025537,https://api.github.com/repos/pydata/xarray/issues/1072,258025537,MDEyOklzc3VlQ29tbWVudDI1ODAyNTUzNw==,5572303,2016-11-02T23:02:03Z,2016-11-02T23:02:03Z,CONTRIBUTOR,"Is combine_first already implemented? I can't find it in the source code, neither could I find ops.choose.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,186680248
https://github.com/pydata/xarray/pull/1065#issuecomment-257001251,https://api.github.com/repos/pydata/xarray/issues/1065,257001251,MDEyOklzc3VlQ29tbWVudDI1NzAwMTI1MQ==,5572303,2016-10-28T18:58:42Z,2016-10-28T18:58:42Z,CONTRIBUTOR,"Out of curiosity, how do I test inner-join vs. outer-join using only 1-D arrays? I can certainly simplify the current tests to be 2D + 1D.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,185794232
https://github.com/pydata/xarray/issues/1059#issuecomment-256784086,https://api.github.com/repos/pydata/xarray/issues/1059,256784086,MDEyOklzc3VlQ29tbWVudDI1Njc4NDA4Ng==,5572303,2016-10-27T22:08:35Z,2016-10-27T22:08:35Z,CONTRIBUTOR,"Yup, did that. Thank you. Will request to have you as a reviewer. Much obliged.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,185017914
https://github.com/pydata/xarray/issues/1059#issuecomment-256766382,https://api.github.com/repos/pydata/xarray/issues/1059,256766382,MDEyOklzc3VlQ29tbWVudDI1Njc2NjM4Mg==,5572303,2016-10-27T20:55:30Z,2016-10-27T20:55:30Z,CONTRIBUTOR,"Thanks. I will soon submit a pull request from my fork. Which branch should it go to? It seems that many people submit pull requests to master here.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,185017914
https://github.com/pydata/xarray/issues/1046#issuecomment-255246621,https://api.github.com/repos/pydata/xarray/issues/1046,255246621,MDEyOklzc3VlQ29tbWVudDI1NTI0NjYyMQ==,5572303,2016-10-20T22:32:23Z,2016-10-20T22:32:23Z,CONTRIBUTOR,"Let me exhaust a few other ideas first. I'll definitely share my thoughts here first before making any commit. Thanks.
","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,182667672
https://github.com/pydata/xarray/issues/1046#issuecomment-253681067,https://api.github.com/repos/pydata/xarray/issues/1046,253681067,MDEyOklzc3VlQ29tbWVudDI1MzY4MTA2Nw==,5572303,2016-10-14T00:53:54Z,2016-10-14T00:53:54Z,CONTRIBUTOR,"My opinion is that the nan has got to go. If we want to (1) maintain pandas-consistency and (2) use bottleneck without mucking it up, then I think we need to add some logic in either rolling.reduce() or rolling._center_result().
So here's my failed attempt:
```
def reverse_and_roll_1d(data, window_size, min_periods=1):
""""""
Implements a concept to fix the end-of-array problem with
xarray.core.rolling._center_shift(),
by
1.) take slice of the back-end of the array
2.) flip it
3.) compute centered-window arithmetic
4.) flip it again
5.) replace back-end of default result with (4)
:param DataArray data: 1-D data array, with dim name 'x'.
:param int window_size: size of window.
""""""
# first the default way to computing centered window
r = data.rolling(x=window_size, center=True, min_periods=min_periods)
avg = r.mean()
# now we need to fix the back-end of the array
rev_start = len(data.x) # an index
rev_end = len(data.x) - window_size - 1 \
if len(data.data) > window_size \
else None # another index
tail_slice = slice(rev_start, rev_end, -1) # back end of array, flipped
r2 = data[dict(x=tail_slice)].\
rolling(x=window_size, center=True, min_periods=min_periods)
avg[dict(x=slice(-window_size+1, None))] = \
r2.mean()[dict(x=slice(window_size-2, None, -1))] # replacement
return avg
```
This algorithm is consistently 8 times slower than pd.DataFrame.rolling(), for various 1d array sizes.
I'm open to ideas as well :)
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