ae151484780b389b5c7b4530c9ac1ef4bb659e23,scipy/special/_basic.py,,factorial,#Any#Any#,2277

Before Change

                    out[n == current] = val
            return out
    else:
        if np.ndim(n) == 0:
            return 0 if n < 0 else gamma(n + 1)

        n = asarray(n)
        vals = gamma(n + 1)
        return where(n >= 0, vals, 0)

After Change

            un = np.unique(n).astype(object)

            // Convert to object array of long ints if np.int can"t handle size
            if np.isnan(n).any():
                dt = float
            elif un[-1] > 20:
                dt = object
            elif un[-1] > 12:
                dt = np.int64
            else:
                dt = np.int

            out = np.empty_like(n, dtype=dt)

            // Handle invalid/trivial values
            // Ignore runtime warning when less operator used w/np.nan

Instances