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
102177256,MDU6SXNzdWUxMDIxNzcyNTY=,542,issue with xray.open_mfdataset and binary operations,1177508,closed,0,,,5,2015-08-20T16:28:12Z,2015-09-03T08:41:00Z,2015-09-01T22:05:02Z,NONE,,,,"example:

``` python
with xray.open_mfdataset(...) as ds:
    a = ds['x'] * ds['y']
```

gives:

`NotImplementedError: Dask.array operations only work on dask arrays, not numpy arrays.` If I do `ds.load()` first then all is good... I guess this is an `xray` issue, not `dask`.
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/542/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue
91184107,MDU6SXNzdWU5MTE4NDEwNw==,444,segmentation fault with `open_mfdataset`,1177508,closed,0,,,26,2015-06-26T07:57:58Z,2015-07-16T21:40:22Z,2015-07-16T21:40:22Z,NONE,,,,"This is super strange. Does anyone have any idea why a segmentation fault might be happening here?

```
Python 3.4.3 (default, Jun 26 2015, 00:02:21) 
[GCC 4.3.4 [gcc-4_3-branch revision 152973]] on linux
Type ""help"", ""copyright"", ""credits"" or ""license"" for more information.
>>> import xray
>>> xray.open_mfdataset('2*.nc', concat_dim='time')
Traceback (most recent call last):
  File ""<stdin>"", line 1, in <module>
  File ""/ichec/home/users/razvan/.local/lib/python3.4/site-packages/xray/backends/api.py"", line 205, in open_mfdataset
Segmentation fault (core dumped)
```

I stay it's strange because I ended up tracking down the bug to `xray.core.ops.array_equiv`. I have no idea what's going on, but by mistake I found out that if I introduce `isnull(arr1 & arr2)` just before the `return` statement then I don't get the error any more... So my `xray.core.ops.array_equiv` is now:

```
def array_equiv(arr1, arr2):
    """"""Like np.array_equal, but also allows values to be NaN in both arrays
    """"""
    arr1, arr2 = as_like_arrays(arr1, arr2)
    if arr1.shape != arr2.shape:
        return False
    # segmentation fault if we don't call this here...
    isnull(arr1 & arr2)
    return bool(((arr1 == arr2) | (isnull(arr1) & isnull(arr2))).all())
```

Thanks...
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/444/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue
94030797,MDU6SXNzdWU5NDAzMDc5Nw==,458,groupby / apply and dask (`open_mfdataset`),1177508,closed,0,,,2,2015-07-09T12:10:04Z,2015-07-15T00:02:40Z,2015-07-15T00:02:34Z,NONE,,,,"It seems that, when working with `open_mfdataset`, things are not consistent. Trying the following:

``` python
import numpy as np
import xray
a = xray.open_mfdataset('*.nc', concat_dim='time', preprocess=lambda x: x.assign_coords(agl=('mean_height_agl', range(x.dims['mean_height_agl']))).swap_dims({'mean_height_agl': 'agl'}).squeeze('time'))
a.groupby('time').apply(np.sum)
```

gives an error with a huge traceback that ends with:

``` python
IndexError:  Exception in remote process

tuple index out of range

Traceback:
  File ""/home/razvan/.local/lib/python3.4/site-packages/dask/async.py"", line 260, in execute_task
    result = _execute_task(task, data)
  File ""/home/razvan/.local/lib/python3.4/site-packages/dask/async.py"", line 243, in _execute_task
    return func(*args2)
  File ""/home/razvan/.local/lib/python3.4/site-packages/toolz/functoolz.py"", line 378, in __call__
    ret = fns[0](*args, **kwargs)
  File ""/home/razvan/.local/lib/python3.4/site-packages/dask/array/core.py"", line 377, in _concatenate2
```

but if I do:

``` python
a.load()
a.groupby('time').apply(np.sum)
```

there's no error. The files I'm using for this are at [this dropbox place](https://www.dropbox.com/sh/wnyana6rgefevmg/AAAzmm37L34A7xKTFbyiy3Aoa?dl=0).
","{""url"": ""https://api.github.com/repos/pydata/xarray/issues/458/reactions"", ""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,completed,13221727,issue
91109966,MDU6SXNzdWU5MTEwOTk2Ng==,443,multiple files - variable X not equal across datasets,1177508,closed,0,,,9,2015-06-26T00:18:21Z,2015-06-29T18:06:54Z,2015-06-29T18:06:54Z,NONE,,,,"The other day I was playing with `xray.open_mfdataset` and I noticed you can get this error, when opening multiple files at the same time. I think there is a pretty easy solution to this:

``` python
import glob as g
from toolz.curried import curry, map, pipe
import xray

def get_ds(glob):
    def _get_ds(file_path):
        dim = 'mean_height_agl'
        dim_new = 'agl'
        with xray.open_dataset(file_path) as _ds:
            _ds.load()
            return (_ds.assign_coords(**{dim_new:
                                         (dim, range(_ds.coords[dim].size))})
                    .swap_dims({dim: dim_new}))

    return pipe(g.glob(glob),
                sorted,
                map(_get_ds),
                curry(xray.concat)(dim='time'))
```

Of course, this is for a particular variable I was having trouble with, but the idea is to swap dimensions, that is create a dummy dimension with the same length as the troublesome variable and then swap the two. This can be done for any number of troublesome variables. I don't know how feasible this is though. Just thought to share my idea...
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