weighted polyfit with NaNs appears broken

What happened?

polyfit can't seem to handle weights still (despite https://github.com/pydata/xarray/pull/5933). nans are involved.

What did you expect to happen?

No response

Minimal Complete Verifiable Example

np.random.seed(10)
y = np.random.rand(10)
x = np.arange(len(y))
y[3] = np.nan
y[5] = np.nan
w = y/10

msk = ~np.isnan(y)
x = x[msk]
y = y[msk]
w = w[msk]

da_test = xr.DataArray(y, dims='time', coords={'time': x})
da_test.polyfit('time', 1, w=w)

# np.polyfit(x, y, 1)#, w=w) # <-- should match this

MVCE confirmation

• Minimal example — the example is as focused as reasonably possible to demonstrate the underlying issue in xarray.
• Complete example — the example is self-contained, including all data and the text of any traceback.
• Verifiable example — the example copy & pastes into an IPython prompt or Binder notebook, returning the result.
• New issue — a search of GitHub Issues suggests this is not a duplicate.
• Recent environment — the issue occurs with the latest version of xarray and its dependencies.

Relevant log output

No response

Anything else we need to know?

not inserting the nans and/or converting the weights to a data array didn't matter

Environment

Start at the DataArray.polyfit entry point and run the provided minimal example with the shown weighted, NaN-filtered arrays. Compare its result with numpy.polyfit using the same x, y, and w inputs, then add or update coverage so weighted fitting produces the expected matching result.