Method _promote_scalar

numpy/array_api/_array_object.py:172–220

Returns a promoted version of a Python scalar appropriate for use with operations on self. This may raise an OverflowError in cases where the scalar is an integer that is too large to fit in a NumPy integer dtype, or TypeError when the scalar type is incompa

(self, scalar)

    # Helper function to match the type promotion rules in the spec
    def _promote_scalar(self, scalar):
        """
        Returns a promoted version of a Python scalar appropriate for use with
        operations on self.

        This may raise an OverflowError in cases where the scalar is an
        integer that is too large to fit in a NumPy integer dtype, or
        TypeError when the scalar type is incompatible with the dtype of self.
        """
        # Note: Only Python scalar types that match the array dtype are
        # allowed.
        if isinstance(scalar, bool):
            if self.dtype not in _boolean_dtypes:
                raise TypeError(
                    "Python bool scalars can only be promoted with bool arrays"
                )
        elif isinstance(scalar, int):
            if self.dtype in _boolean_dtypes:
                raise TypeError(
                    "Python int scalars cannot be promoted with bool arrays"
                )
            if self.dtype in _integer_dtypes:
                info = np.iinfo(self.dtype)
                if not (info.min <= scalar <= info.max):
                    raise OverflowError(
                        "Python int scalars must be within the bounds of the dtype for integer arrays"
                    )
            # int + array(floating) is allowed
        elif isinstance(scalar, float):
            if self.dtype not in _floating_dtypes:
                raise TypeError(
                    "Python float scalars can only be promoted with floating-point arrays."
                )
        elif isinstance(scalar, complex):
            if self.dtype not in _complex_floating_dtypes:
                raise TypeError(
                    "Python complex scalars can only be promoted with complex floating-point arrays."
                )
        else:
            raise TypeError("'scalar' must be a Python scalar")

        # Note: scalars are unconditionally cast to the same dtype as the
        # array.

        # Note: the spec only specifies integer-dtype/int promotion
        # behavior for integers within the bounds of the integer dtype.
        # Outside of those bounds we use the default NumPy behavior (either
        # cast or raise OverflowError).
        return Array._new(np.array(scalar, self.dtype))

    @staticmethod
    def _normalize_two_args(x1, x2) -> Tuple[Array, Array]: