In this article, we will see how to compute the negative value for all elements in a given NumPy array. So, The negative value is actually the number which when added to any number becomes 0.
Example:
If we take a number as 4 then -4 is its negative number because when we add -4 to 4 we get sum as 0. Now let us take another example, Suppose we take a number -6 Now when we add +6 to it then the sum becomes zero. hence +6 is the negative value of -6. Now suppose we have an array of numbers:
A = [1,2,3,-1,-2,-3,0] So, the negative value of A is A'=[-1,-2,-3,1,2,3,0].
So, for finding the numerical negative value of an element we have to use numpy.negative() function of NumPy library.
Syntax: numpy.negative(arr, /, out=None, *, where=True, casting=’same_kind’, order=’K’, dtype=None, subok=True[, signature, extobj], ufunc ‘negative’)
Return: [ndarray or scalar] Returned array or scalar = -(input arr or scalar )
Now, let’s see the examples:
Example 1:
Python3
# importing library import numpy as np # creating a array x = np.array([ - 1 , - 2 , - 3 , 1 , 2 , 3 , 0 ]) print ( "Printing the Original array:" , x) # converting array elements to # its corresponding negative value r1 = np.negative(x) print ( "Printing the negative value of the given array:" , r1) |
Output:
Printing the Original array: [-1 -2 -3 1 2 3 0] Printing the negative value of the given array: [ 1 2 3 -1 -2 -3 0]
Example 2:
Python3
# importing library import numpy as np # creating a numpy 2D array x = np.array([[ 1 , 2 ], [ 2 , 3 ]]) print ( "Printing the Original array Content:\n" , x) # converting array elements to # its corresponding negative value r1 = np.negative(x) print ( "Printing the negative value of the given array:\n" , r1) |
Output:
Printing the Original array Content: [[1 2] [2 3]] Printing the negative value of the given array: [[-1 -2] [-2 -3]]