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/3245#issuecomment-873480044,https://api.github.com/repos/pydata/xarray/issues/3245,873480044,MDEyOklzc3VlQ29tbWVudDg3MzQ4MDA0NA==,35968931,2021-07-03T22:41:39Z,2021-07-03T22:41:39Z,MEMBER,"Also I can add a `.to_pint()` method, but I don't really understand what the purpose would be? To be any use to users it would need to accept a `units` argument, but then it's basically just a less powerful version of `pint_xarray`'s `.quantify()` accessor method. Can you see any reason to add it @keewis ?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,484240082
https://github.com/pydata/xarray/issues/3245#issuecomment-873222015,https://api.github.com/repos/pydata/xarray/issues/3245,873222015,MDEyOklzc3VlQ29tbWVudDg3MzIyMjAxNQ==,35968931,2021-07-02T19:43:04Z,2021-07-02T20:18:11Z,MEMBER,"I'm trying to implement this (I wanted pint-aware plotting to work) in #5568, but not 100% sure if I'm doing it right.

~~1) Do we want these `as_*`, `to_*` methods to live in `Variable` or `DataArray`?~~

2) What about multiply-wrapped arrays? At the moment I have essentially

```python
def as_numpy(self) -> T_DataArray:
    """"""
    Coerces wrapped data into a numpy array, and returns it wrapped in
    a DataArray.
    """"""
    data = self.data
    if isinstance(data, dask_array_type):
        return self.load()
    elif isinstance(data, cupy_array_type):
        return self.copy(data=data.get())
    elif isinstance(data, pint_array_type):
        return self.copy(data=data.magnitude)
    elif isinstance(data, sparse_array_type):
        return self.copy(data=data.to_dense())
    else:
        return self.copy(data=np.array(data))
```
but do I actually want multiple passes, like
```python
    data = self.data
    if isinstance(data, dask_array_type):
        data = self.load().data
    if isinstance(data, cupy_array_type):
        data = data.get()
    if isinstance(data, pint_array_type):
        data = data.magnitude
    if isinstance(data, sparse_array_type):
        data = data.to_dense()

    return self.copy(data=np.array(data))
```

3) @jacobtomlinson currently `.values` will extract the values of a cupy array by special-casing it, but based on the above discussion do we actually want to break that in favour of getting them via `.to_numpy()` instead?

4) There are `_as_sparse` and `_to_dense` methods already, but they are private and only present on `Variable`. Should I expose them?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,484240082