numpy.sqrt() in Python

numpy.sign() in Python

Last Updated : 03 Oct, 2019

numpy.sign(array [, out]) function is used to indicate the sign of a number element-wise. For integer inputs, if array value is greater than 0 it returns 1, if array value is less than 0 it returns -1, and if array value 0 it returns 0.

Syntax: numpy.sign() Parameters : array : [array_like] Input values. out : [ndarray, optional] Output array placed with result. Return : [ndarray] Returns the sign of array. If an array is scalar then the sign of array will be scalar.

Code 1 :

Python3

# Python Program illustrating
# numpy.sign() method

# importing numpy
import numpy as geek  

# input arrays    
array1 = [1, 0, -13]
array2 =  [-1, 0, 15]

# print the input arrays  
print ("input array1 : ", array1)
print ("input array2 : ", array2)

# determine the sign of integer numbers in an array  
print ("\nCheck sign of array1 : ", geek.sign(array1))
print ("\nCheck sign of array2 : ", geek.sign(array2))

Output :

array1 :  [1, 0, -13]
array2 :  [-1, 0, 15]

Check sign of array1 :  [ 1  0 -1]

Check sign of array2 :  [-1  0  1]

Code 2 :

Python3

# Python Program illustrating
# numpy.sign() method

# importing numpy  
import numpy as geek 

# determine the sign of complex number
print ("\n Check sign of complex input1 : ", geek.sign(7-3j))
print ("\n Check sign of complex input2 : ", geek.sign(-7 + 3j))

Output :

 Check sign of complex input1 :  (1+0j)

 Check sign of complex input2 :  (-1+0j)

numpy.sqrt() in Python

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