Fixes #31087.

nanmin/nanmax misbehave with the initial argument in the slow path (non-ndarray input like lists). Two issues:

1. nanmax([1.0], initial=nan) returns nan because the slow path uses np.amax which propagates NaN from initial, unlike np.fmax.reduce used in the fast path. Fixed by stripping NaN initial before passing to amax/amin, since nanmax/nanmin should ignore NaN in initial the same way they ignore NaN in array elements.

2. nanmax([], initial=1.0) returns nan because the all-NaN check (np.all(mask)) returns True on an empty mask and unconditionally overwrites the result with NaN. Fixed by using initial as the result for all-NaN slices when it's a valid (non-NaN) value.