numpy.dtype.subdtype() function – Python

numpy.result_type() function – Python

Last Updated : 18 Jun, 2020

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 :

Python3

# 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 :

Python3

# 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

numpy.dtype.subdtype() function – Python

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