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/1553#issuecomment-748491929,https://api.github.com/repos/pydata/xarray/issues/1553,748491929,MDEyOklzc3VlQ29tbWVudDc0ODQ5MTkyOQ==,18488,2020-12-19T16:00:00Z,2020-12-19T16:00:00Z,NONE,"For the case of a simple vectorized `reindex` you can work around the lack of a multi-dimensional `DataArray.reindex` by falling back on `isel` as follows:

```
def reindex_vectorized(da, indexers, method=None, tolerance=None, dim=None, fill_value=None):
    # Reindex does not presently support vectorized lookups: https://github.com/pydata/xarray/issues/1553
    # Sel does (e.g. https://github.com/pydata/xarray/issues/4630) but can't handle missing keys
    
    if dim is None:
        dim = 'dim_0'

    if fill_value is None:
        fill_value = {'i': np.nan, 'f': np.nan}[da.dtype.kind]
    dtype = np.result_type(fill_value, da.dtype)
    
    if method is None:
        method = {}
    elif not isinstance(method, dict):
        method = {dim: method for dim in da.dims}
        
    if tolerance is None:
        tolerance = {}
    elif not isinstance(tolerance, dict):
        tolerance = {dim: tolerance for dim in da.dims}
    
    ixs = {}
    masks = []
    any_empty = False
    for index_dim, index in indexers.items():
        ix = da.indexes[index_dim].get_indexer(index, method=method.get(index_dim), tolerance=tolerance.get(index_dim))
        ixs[index_dim] = xr.DataArray(np.fmax(0, ix), dims=[dim])
        masks.append(ix >= 0)
        any_empty = any_empty or (len(da.indexes[index_dim]) == 0)
    
    mask = functools.reduce(lambda x, y: x & y, masks)
    
    if any_empty and len(mask):
        # Unfortunately can't just isel with `ixs` in this special case, because we'll go out of bounds accessing index 0
        new_coords = {
            name: coord
            for name, coord in da.coords.items()
            # XXX: to match the other case we should really include coords with name in ixs too, but it's fiddly
            if name not in ixs
        }
        new_dims = [name for name in da.dims if name not in ixs] + [dim]
        result = xr.DataArray(
            data=np.broadcast_to(
                fill_value,
                tuple(n for name, n in da.sizes.items() if name not in ixs) + (len(mask),)
            ),
            coords=new_coords, dims=new_dims,
            name=da.name, attrs=da.attrs
        )
    else:
        result = da[ixs]

        if not mask.all():
            result = result.astype(dtype, copy=False)
            result[{dim: ~mask}] = fill_value
    
    return result
```

Example:

```
sensor_data = xr.DataArray(np.arange(6).reshape((3, 2)), coords=[
    ('time', [0, 2, 3]),
    ('sensor', ['A', 'C']),
])

reindex_vectorized(sensor_data, {
    'sensor': ['A', 'A', 'A', 'B', 'C'],
    'time': [0, 1, 2, 0, 0],
}, method={'time': 'ffill'})
# [0, 0, 2, nan, 1]

reindex_vectorized(xr.DataArray(coords=[
    ('sensor', []),
    ('time', [0, 2])
]), {
    'sensor': ['A', 'A', 'A', 'B', 'C'],
    'time': [0, 1, 2, 0, 0],
}, method={'time': 'ffill'})
# [nan, nan, nan, nan, nan]
```","{""total_count"": 1, ""+1"": 1, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,254927382
https://github.com/pydata/xarray/issues/4714#issuecomment-748486801,https://api.github.com/repos/pydata/xarray/issues/4714,748486801,MDEyOklzc3VlQ29tbWVudDc0ODQ4NjgwMQ==,18488,2020-12-19T15:13:36Z,2020-12-19T15:14:59Z,NONE,"Thanks for the response. I think `reindex` would need to be changed as well because this code:

```python
sensor_data.reindex({
    'time': [1],
    'sensor': ['A', 'B']
}, method='ffill')
```

Is not equivalent to this code:
```python
sensor_data.reindex({
    'time': [1],
    'sensor': ['A', 'B']
}).ffill(dim='time').ffill(dim='sensor')
```

So if I understand your `to_dataset` idea correctly, you are proposing:

```python
ds = sensor_data.to_dataset(dim='sensor')
xr.concat([
    ds[sensor].sel({'time': time}, method='ffill', drop=True)
    for sensor, time in zip(['A', 'A', 'A', 'B', 'C'], [0, 1, 2, 0, 0])
], dim='sample')
```

I guess this works but it's a bit cumbersome and unlikely to be fast. I think there must be something I'm not understanding here - I'm not familiar with all the nuances of the `xarray` api.

Your idea of `reindex` followed by `sel` is an interesting one, but it does do something slightly different than what I was asking for: it does not fail if one of the sensors in the query list is missing, but rather inserts a NaN. I suppose you could fix this by doing an extra check afterwards, assuming that your original pre-reindex data contained no NaNs.

In general `min(S*N,T*N)` could be much larger than `S*T`, so for big queries it's quite possible that you wouldn't have enough space to allocate the intermediate even if you could fit 100s of copies of the original `S*T` matrix. Using a dask cluster would make this situation less likely of course, but it seems like it would be better to avoid all this copying (even on a beefy cluster) even if just for performance reasons.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,771382653
https://github.com/pydata/xarray/issues/4714#issuecomment-748479287,https://api.github.com/repos/pydata/xarray/issues/4714,748479287,MDEyOklzc3VlQ29tbWVudDc0ODQ3OTI4Nw==,18488,2020-12-19T14:06:36Z,2020-12-19T14:06:36Z,NONE,"Thanks for the suggestion. One issue with this alternative is it creates a potentially large intermediate object.

If you have T times and S sensors, and want to sample them at N (time, sensor) pairs, then the intermediate object with your approach has size `T*N` (if you index sensors first) or `S*N` (if you index time first). If you can index both dimensions in one `sel` call then we should only need to allocate memory for the result of size `N`, which is considerably better.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,771382653
https://github.com/pydata/xarray/issues/4714#issuecomment-748477889,https://api.github.com/repos/pydata/xarray/issues/4714,748477889,MDEyOklzc3VlQ29tbWVudDc0ODQ3Nzg4OQ==,18488,2020-12-19T13:53:53Z,2020-12-19T13:53:53Z,NONE,I guess it would also make sense to have this in `reindex` if you did decide to add it.,"{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,771382653