This is documentation for an old release of NumPy (version 1.10.1). Read this page in the documentation of the latest stable release (version > 1.17).
numpy.promote_types¶
- numpy.promote_types(type1, type2)¶
Returns the data type with the smallest size and smallest scalar kind to which both type1 and type2 may be safely cast. The returned data type is always in native byte order.
This function is symmetric and associative.
Parameters: type1 : dtype or dtype specifier
First data type.
type2 : dtype or dtype specifier
Second data type.
Returns: out : dtype
The promoted data type.
See also
Notes
New in version 1.6.0.
Starting in NumPy 1.9, promote_types function now returns a valid string length when given an integer or float dtype as one argument and a string dtype as another argument. Previously it always returned the input string dtype, even if it wasn’t long enough to store the max integer/float value converted to a string.
Examples
>>> np.promote_types('f4', 'f8') dtype('float64')
>>> np.promote_types('i8', 'f4') dtype('float64')
>>> np.promote_types('>i8', '<c8') dtype('complex128')
>>> np.promote_types('i4', 'S8') dtype('S11')