nan length coordinates

[chrisroat]

Is your feature request related to a problem? Please describe.

When using arrays with a nan shape, I'd like to provide a coordinate specification from a delayed object, which is my responsibility to make sure has the right chunks and length.

Describe the solution you'd like

Below are three examples that I think should work, where I give a coordinate via a dask array, a dask series, and a dask index. Currently, all three examples error out by computing the coordinate length (triggering an unwanted dask computation!), and then indicating that its different than the array's corresponding length, which is nan.

import dask
import dask.array as da
import dask.dataframe as dd
import numpy as np
import pandas as pd
import xarray as xr

def foo():
    return np.arange(4)

arr = da.from_delayed(dask.delayed(foo)(), shape=(np.nan,), dtype=int)

idx = da.from_delayed(dask.delayed(foo)(), shape=(np.nan,), dtype=int)

ddf = dd.from_pandas(pd.DataFrame({'y': np.arange(4)}), npartitions=1)

arr0 = xr.DataArray(arr, coords=[('z', idx)])
arr1 = xr.DataArray(arr, coords=[('z', ddf['y'])])
arr2 = xr.DataArray(arr, coords=[('z', ddf.index)])

Error:

ValueError: conflicting sizes for dimension 'z': length nan on the data but length 4 on coordinate 'z'

Describe alternatives you've considered

After computations to complete add the missing coordinate. This requires carrying around the delayed index with the delayed array.

[mathause]

dask or lazy coordinates are currently not allowed in xarrays data model, so unfortunately this cannot work - even a standard dask.array.array is turned into a numpy array:

xr.DataArray([1, 2, 3], coords=[('z', da.array([1, 2, 3]))]).z.data

[dcherian]

Thanks for the nice examples @chrisroat . Closing as duplicate of #2801

EDIT: Oops meant to close the other one.