issue_comments: 904403621

I included the proposed changes, thanks for the help.

However the new test I implemented does not go through and I fail to understand why. Would you be able to check ? The idea of the test is to ensure that lazy computations give the same results than normal ones. I tracked down the problem to line 1377 of computation.py: python demeaned_da_a = da_a - da_a.mean(dim=dim) # <-- this one returns nan upon computation (.compute()) demeaned_da_b = da_b - da_b.mean(dim=dim) # <-- this one returns the correct value although the input is masked with nans in the same way

The values before the mean call are: da_a.compute() = <xarray.DataArray <this-array> (x: 2, time: 2)> array([[ 1., 2.], [ 2., nan]]) da_b.compute() = <xarray.DataArray <this-array> (x: 2, time: 2)> array([[ 1., 2.], [ 1., nan]])

And for the means (dim is None): da_a.mean(dim=dim).compute()=<xarray.DataArray <this-array> ()> array(nan) da_b.mean(dim=dim).compute()=<xarray.DataArray <this-array> ()> array(1.33333333)

For non lazy computations everything seems fine.