dpnp.common_type

dpnp.common_type(*arrays)[source]

Return a scalar type which is common to the input arrays.

The return type will always be an inexact (i.e. floating point) scalar type, even if all the arrays are integer arrays. If one of the inputs is an integer array, the minimum precision type that is returned is a 64-bit floating point dtype.

For full documentation refer to numpy.common_type

Parameters:

array1 ({dpnp.ndarray, usm_ndarray}) -- Input arrays.
array2 ({dpnp.ndarray, usm_ndarray}) -- Input arrays.
... ({dpnp.ndarray, usm_ndarray}) -- Input arrays.

Returns:

out -- Data type code.

Return type:

data type code

Examples

>>> import dpnp as np
>>> np.common_type(np.arange(2, dtype=np.float32))
<class 'numpy.float32'>
>>> np.common_type(np.arange(2, dtype=np.float32), np.arange(2))
<class 'numpy.float64'>
>>> np.common_type(np.arange(4), np.array([45, 6.j]), np.array([45.0]))
<class 'numpy.complex128'>