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| -rw-r--r-- | doc/neps/nep-0050-scalar-promotion.rst | 20 |
1 files changed, 20 insertions, 0 deletions
diff --git a/doc/neps/nep-0050-scalar-promotion.rst b/doc/neps/nep-0050-scalar-promotion.rst index b39f8b6b5..63cf8f4be 100644 --- a/doc/neps/nep-0050-scalar-promotion.rst +++ b/doc/neps/nep-0050-scalar-promotion.rst @@ -555,6 +555,26 @@ passed out as a result from a function, rather than used only very localized. or a pattern of calling ``np.result_type()`` before ``np.asarray()``. +Keep using value-based logic for Python scalars +----------------------------------------------- + +Some of the main issues with the current logic arise, because we apply it +to NumPy scalars and 0-D arrays, rather than the application to Python scalars. +We could thus consider to keep inspecting the value for Python scalars. + +We reject this idea on the grounds that it will not remove the surprises +given earlier:: + + np.uint8(100) + 1000 == np.uint16(1100) + np.uint8(100) + 200 == np.uint8(44) + +And adapting the precision based on the result value rather than the input +value might be possible for scalar operations, but is not feasible for array +operations. +This is because array operations need to allocate the result array before +performing the calculation. + + Discussion ========== |