issue_comments: 283062107

Having an xarray wrapper on trapz or cumtrapz would definitely be useful for many users. I weakly prefer not to use the name integrate and instead keep the standard scipy names because they make clear the numerical algorithm that is being applied. The issue is that certain types of gridded data (such as output from numerical models) should actually not be integrated with the trapezoidal rule but rather should use the native finite volume discretization for their computational grid. The goal of our hypothetical pangeo vector calculus package is to implement integrals and derivatives in such a context. A built-in xarray integration function would apply in cases where the data is assumed to be continuous, and where no auxiliary information about the grid (beyond the coordinates) is available.

I will also make the same comment I always make when such feature requests are raised: yes, it always seems desirable to add new features to xarray on a function-by-function basis. But where does it end? Why not implement the rest of the scipy.ode module? And why stop there? As a community we need to develop a roadmap that clearly defines the scope of xarray. Once apply is stable, it might not be that hard to wrap a large fraction of the scipy library. But maybe that should live in a separate package.