numpy.sqrt() in Python

numpy.sqrt(array[, out]) function is used to determine the positive square-root of an array, element-wise.

Syntax: numpy.sqrt()

Parameters:
array : [array_like] Input values whose square-roots have to be determined.
out : [ndarray, optional] Alternate array object in which to put the result; if provided, it must have the same shape as arr.

Returns : [ndarray] Returns the square root of the number in an array.

Code #1 :



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# Python program explaining
# numpy.sqrt() method 
  
# importing numpy
import numpy as geek 
  
# applying sqrt() method on integer numbers 
arr1 = geek.sqrt([1, 4, 9, 16])
arr2 = geek.sqrt([6, 10, 18])
  
print("square-root of an array1  : ", arr1)
print("square-root of an array2  : ", arr2)

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Output:

square-root of an array1  :  [ 1.  2.  3.  4.]
square-root of an array2  :  [ 2.44948974  3.16227766  4.24264069]

 
Code #2 :

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# Python program explaining
# numpy.sqrt() method 
  
# importing numpy
import numpy as geek 
  
# applying sqrt() method on complex numbers
arr = geek.sqrt([4, -1, -5 + 9J])
  
print("square-root of an array  : ", arr)

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Output:

square-root of an array  :  [ 2.00000000+0.j  0.00000000+1.j  1.62721083+2.76546833j]

 
Code #3 :

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# Python program explaining
# numpy.sqrt() method 
  
# importing numpy
import numpy as geek 
  
# applying sqrt() method on negative element of real numbers 
arr = geek.sqrt([-4, 5, -6])
  
print("square-root of an array  : ", arr)

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Output:

RuntimeWarning: invalid value encountered in sqrt
square-root of an array  :  [ nan  2.23606798  nan]

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