numpy.negative() in Python

Syntax : numpy.negative(arr, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj], ufunc 'negative') Parameters : arr : [array_like or scalar] Input array. dtype : The type of the returned array. By default, the dtype of arr is used. out : [ndarray, optional] A location into which the result is stored.   -> If provided, it must have a shape that the inputs broadcast to.   -> If not provided or None, a freshly-allocated array is returned. where : [array_like, optional] Values of True indicate to calculate the ufunc at that position, values of False indicate to leave the value in the output alone. **kwargs : Allows to pass keyword variable length of argument to a function. Used when we want to handle named argument in a function. Return : [ndarray or scalar] Returned array or scalar = -(input arr or scalar )

# Python program explaining
# numpy.negative() function

import numpy as geek
in_num = 10

print ("Input  number : ", in_num)
  
out_num = geek.negative(in_num) 
print ("negative of input number : ", out_num) 

Input  number :  10
negative of input number :  -10

# Python program explaining
# numpy.negative function

import numpy as geek

in_arr = geek.array([[2, -7, 5], [-6, 2, 0]])
 
print ("Input array : ", in_arr) 
  
out_arr = geek.negative(in_arr) 
print ("negative of array elements: ", out_arr) 

Input array :  [[  2.   2.   2.]
 [  2.   2.  nan]]
product of array elements:  32.0Input array :  [[ 2 -7  5]
 [-6  2  0]]
negative of array elements:  [[-2  7 -5]
 [ 6 -2  0]]