numpy.result_type() function returns the type that results from applying the NumPy type promotion rules to the arguments.
NumPy type promotion by example :
Suppose calculating 3*arr, where arr is an array of 32-bit floats, intuitively should result in a 32-bit float output. If the 3 is a 32-bit integer, the NumPy rules indicate it can’t convert losslessly into a 32-bit float, so a 64-bit float should be the result type.
Syntax : numpy.result_type(arrays_and_dtypes)
Parameters :
arrays_and_dtypes : [list of arrays and dtypes] The operands of some operation whose result type is needed.
Return : [dtype] Return the result type.
Code #1 :
# Python program explaining # numpy.result_type() function # importing numpy as geek import numpy as geek gfg = geek.result_type('f4', 'i8') print (gfg) |
Output :
float64
Code #2 :
# Python program explaining # numpy.result_type() function # importing numpy as geek import numpy as geek gfg = geek.result_type(3, geek.arange(7, dtype = 'i1')) print (gfg) |
Output :
int8
