bundles / numpy 2.4.3 / numpy / promote_types
built-in
numpy:promote_types
Signature
promote_types ( type1 , type2 , / ) Summary
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 considered "canonical", this mainly means that the promoted dtype will always be in native byte order.
Extended Summary
This function is symmetric, but rarely associative.
Parameters
type1: dtype or dtype specifierFirst data type.
type2: dtype or dtype specifierSecond data type.
Returns
out: dtypeThe promoted data type.
Notes
Please see numpy.result_type for additional information about promotion.
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.
NumPy now supports promotion for more structured dtypes. It will now remove unnecessary padding from a structure dtype and promote included fields individually.
Examples
import numpy as np np.promote_types('f4', 'f8')✓
np.promote_types('i8', 'f4')
✓np.promote_types('>i8', '<c8')
✓np.promote_types('i4', 'S8')
✓p = np.promote_types p('S', p('i1', 'u1')) p(p('S', 'i1'), 'u1')✓
See also
- can_cast
- dtype
- result_type
Aliases
-
numpy.promote_types