ENH: Create the ability for fused operations (fused ufuncs or `map_reduce`) style

It would be nice to have something in NumPy, which would give the largest value by magnitude. IOW abs(a).max(). However it would be better if it didn’t result in creating a second copy of the data as abs(a) would do.

[eric-wieser]

I don’t like that idea of adding ufuncs for a small subset of op, reduction. If this is a common enough case, perhaps we should support something like np.map_reduce, used as:

max_abs   = np.ufunc.map_reduce(np.abs, np.maximum)
all_equal = np.ufunc.map_reduce(np.equal, np.logical_and)

max_abs(a)       # np.maximum.reduce(np.abs(a)), but more efficient
all_equal(a, b)  # np.logical_and.reduce(np.equal(a, b)), but more efficient

could possibly be maintained in its own package!

That seems reasonable to me - anyone is free to create their own gufunc that does these things

[charris]

How does scikit-learn handle signed integers?