numpy.find_common_type¶

numpy.find_common_type(array_types, scalar_types)[source]¶

Determine common type following standard coercion rules.

Parameters

array_typessequence: A list of dtypes or dtype convertible objects representing arrays.
scalar_typessequence: A list of dtypes or dtype convertible objects representing scalars.

Returns

datatypedtype: The common data type, which is the maximum of array_types ignoring scalar_types, unless the maximum of scalar_types is of a different kind (dtype.kind). If the kind is not understood, then None is returned.

See also

dtype, common_type, can_cast, mintypecode

Examples

>>> np.find_common_type([], [np.int64, np.float32, complex])
dtype('complex128')
>>> np.find_common_type([np.int64, np.float32], [])
dtype('float64')

The standard casting rules ensure that a scalar cannot up-cast an array unless the scalar is of a fundamentally different kind of data (i.e. under a different hierarchy in the data type hierarchy) then the array:

>>> np.find_common_type([np.float32], [np.int64, np.float64])
dtype('float32')

Complex is of a different type, so it up-casts the float in the array_types argument:

>>> np.find_common_type([np.float32], [complex])
dtype('complex128')

Type specifier strings are convertible to dtypes and can therefore be used instead of dtypes:

>>> np.find_common_type(['f4', 'f4', 'i4'], ['c8'])
dtype('complex128')

numpy.issubclass_

numpy.typename