NumPy参考 >例行程序 >Data type routines > 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, but rarely associative.
First data type.
Second data type.
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')
An example of a non-associative case:
>>> p = np.promote_types
>>> p('S', p('i1', 'u1'))
dtype('S6')
>>> p(p('S', 'i1'), 'u1')
dtype('S4')