numpy.reciprocal () in Python



numpy.reciprocal (x, /, out = None, *, where = True): this math function is used to calculate the reciprocal of all elements of the input array.

Parameters:

x [array_like] : Input array or object whose elements needed to test.

out [ndarray, optional] : A location into which the result is stored.
  – & gt ; If provided, it must have a shape that the inputs broadcast to.
  – & gt; If not provided or None, a freshly-allocated array is returned.

** kwargs: Allows to pass keyword variable length of argument to a function. Used when we want to handle named argument in a function.

where [array_like, optional]: True value means to calculate the universal functions (ufunc) at that position, False value means to leave the value in the output alone.

Return:
y: ndarray. This is a scalar if x is a scalar.

Note: For integer arguments with an absolute value greater than 1, the result is always zero due to the way Python handles integer division. For integer zero, the result is an overflow.

Code # 1:

# Python3 code demonstrates the responserocal function ()

 
# numpy import

import numpy as np

 

in_num = 2.0

print ( "Input number:" , in_num)

 

out_num = np.reciprocal (in_num)

print ( "Output number:" , out_num)

Output:

 Input number: 2.0 Output number: 0.5 

Code # 2:

# Python3 code demonstrates the responserocal () function

 
# numpy import

import numpy as np

 

in_arr = [ 2. , 3. , 8.

print ( " Input array: " , in_arr) 

 

out_arr = np.reciprocal (in_arr) 

print ( " Output array: " , out_arr) 

Output:

 Input array: [2.0, 3.0, 8.0] Output array: [0.5 0.33333333 0.125] 

Code # 3: Exception in reciprocity () function. The result is always zero.

# Python3 code demonstrates an exception in the recrocal () function

 
# numpy import

import numpy as np

  

in_arr = [ 2 , 3 , 8

print ( "Input array:" , in_arr) 

 

out_arr = np.reciprocal (in_arr) 

print ( "Output array:" , out_arr) 

Output:

 Input array: [2, 3, 8] Output array: [0 0 0]