I should have said "discrete lazily evaluated form (which we support through dask)". I think we already have what you want in principle (caveats at the end).

Here's an example: ``` python import dask import numpy as np import xarray as xr

xr.set_options(display_style="html")

def arbitrary_function(dataset): return dataset["a"] * dataset["wavelength"] * dataset.attrs["wcs_param"]

ds = xr.Dataset()

construct a dask array.

In practice this could represent an on-disk dataset,

with data reads only occurring when necessary

ds["a"] = xr.DataArray(dask.array.ones((10,)), dims=["wavelength"], coords={"wavelength": np.arange(10)})

some coordinate system parameter

ds.attrs["wcs_param"] = 1.0

complicated pixel to world function

no compute happens since we are working with dask arrays

so this is quite cheap.

ds.coords["azimuth"] = arbitrary_function(ds) ds ```

So you can carry around your coordinate system parameters in the .attrs dictionary and the non-dimensional coordinate azimuth is only evaluated when needed e.g. when plotting ``` python

Both 'a' and 'azimuth' are computed now, since actual values are required to plot

ds.a.plot(x="azimuth") ```

In practice, there are a few limitations. @djhoese and @snowman2 may have useful perspective here.

1. xarray tends to compute "non-dimensional coordinates" more than necessary. The more egregious examples have been fixed (#3068, #3311, #3454, #3453) but there may still be some places where fixes are needed (#3588).
2. there's some discussion about carrying around Earth-specific coordinate system parameters here: https://github.com/pydata/xarray/issues/2288; https://github.com/pydata/xarray/issues/2996.

Additional info: 1. https://docs.dask.org/en/latest/array.html 2. https://xarray.pydata.org/en/stable/dask.html 3. https://blog.dask.org/2019/06/20/load-image-data

PS: If it helps, I'd be happy to chat over skype for a half hour getting you oriented with how we do things.