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/4079#issuecomment-1435715372,https://api.github.com/repos/pydata/xarray/issues/4079,1435715372,IC_kwDOAMm_X85Vk0cs,14808389,2023-02-18T16:51:14Z,2023-02-18T16:51:14Z,MEMBER,"> hmm... would `np.nan` work?

not sure about alignment, but at least `obj.sizes` would break with multiple dims: while it does not compare as equal, the `hash()` of `np.nan` stays constant (same with any other object, I guess).","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,621078539
https://github.com/pydata/xarray/issues/4079#issuecomment-1434959378,https://api.github.com/repos/pydata/xarray/issues/4079,1434959378,IC_kwDOAMm_X85Vh74S,2448579,2023-02-17T17:16:14Z,2023-02-17T17:16:22Z,MEMBER,"This reminds me of the issue with `nan` shaped dimensions. Where again we want to avoid automatic alignment (well in that case you can't align).

For this particular issue could we define a `xr.UNNAMED` that doesn't equal itself (hmm... would `np.nan` work?). Would that skip alignment checks?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,621078539
https://github.com/pydata/xarray/issues/4079#issuecomment-1434932769,https://api.github.com/repos/pydata/xarray/issues/4079,1434932769,IC_kwDOAMm_X85Vh1Yh,1217238,2023-02-17T17:03:52Z,2023-02-17T17:03:52Z,MEMBER,"I agree, automatic dimension only ever really made sense for interactive usecases, where a user could see and fix the default names.

It's a little late to change the default now to raising an error instead, but maybe we could add a warning?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,621078539
https://github.com/pydata/xarray/issues/4079#issuecomment-1434805981,https://api.github.com/repos/pydata/xarray/issues/4079,1434805981,IC_kwDOAMm_X85VhWbd,14808389,2023-02-17T15:28:07Z,2023-02-17T15:28:07Z,MEMBER,"I'd probably use `itertools.count()` or the `uuid` module to generate globally unique dimension names... something like
```python
class _UnnamedDimensions:
    def __init__(self):
        self.dimension_names = (f""unnamed_dim_{number}"" for number in itertools.count())

    def __call__(self, n):
        return list(itertools.islice(dimension_names, None, n))

unnamed_dimensions = _UnnamedDimensions()
```
or using `uuid` (probably overkill):
```python
def unnamed_dimensions(n):
    return [uuid.uuid4() for _ in range(n)]
```
you'd use it like this:
```python
d1 = xr.DataArray(data=[1, 2], dims=unnamed_dimensions(1))
d2 = xr.DataArray(data=[[1, 2]], dims=unnamed_dimensions(2))
```
which would make ""unnamed"" a bit more explicit.

Edit: that's probably not so different from what you meant with `d1_i`","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,621078539
https://github.com/pydata/xarray/issues/4079#issuecomment-630936142,https://api.github.com/repos/pydata/xarray/issues/4079,630936142,MDEyOklzc3VlQ29tbWVudDYzMDkzNjE0Mg==,1217238,2020-05-19T16:33:49Z,2020-05-19T16:33:49Z,MEMBER,"In the specific example from your notebook, where do the dimensions lengths `__variants/BaseCounts_dim1`, `__variants/MLEAC_dim1` and `__variants/MLEAF_dim1` come from?

`BaseCounts_dim1` is length 4, so maybe that corresponds to DNA bases ATGC?","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,621078539
https://github.com/pydata/xarray/issues/4079#issuecomment-630916682,https://api.github.com/repos/pydata/xarray/issues/4079,630916682,MDEyOklzc3VlQ29tbWVudDYzMDkxNjY4Mg==,1217238,2020-05-19T16:00:34Z,2020-05-19T16:00:34Z,MEMBER,"The main problem is that unnamed dimensions (in NumPy, at least) have different semantics than named dimensions, particular for how dimensions are matched up in broadcasting. For that reason, we really want all dimensions to always be named.

We could possibly add support for unnamed dimensions in the Dataset constructor, but on the other hand it also provides a gentle nudge to chose names.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,621078539
https://github.com/pydata/xarray/issues/4079#issuecomment-630906095,https://api.github.com/repos/pydata/xarray/issues/4079,630906095,MDEyOklzc3VlQ29tbWVudDYzMDkwNjA5NQ==,1197350,2020-05-19T15:42:07Z,2020-05-19T15:42:07Z,MEMBER,"> Is there a way to create arrays and datasets with unnamed dimensions?

No. Xarray's data model requires all dimensions to have a name.

Xarray allows you to create DataArrays without specifying dimensions:

```python
import xarray as xr
import numpy as np
da = xr.DataArray(np.zeros((4, 5)))
```

Xarray will choose dimension names in this case (`dim_0`, `dim_1`, etc.)

This doesn't work with creating Datasets, because you *have* to specify all variables' dimensions in the Dataset constructor.

I imagine that unnamed dimensions would break lots of internal Xarray logic.","{""total_count"": 0, ""+1"": 0, ""-1"": 0, ""laugh"": 0, ""hooray"": 0, ""confused"": 0, ""heart"": 0, ""rocket"": 0, ""eyes"": 0}",,621078539