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numpy.rint() in Python
  • Last Updated : 04 Dec, 2020

The numpy.rint() is a mathematical function that rounds elements of the array to the nearest integer.

Syntax : numpy.rint(x[, out]) = ufunc ‘rint’)
Parameters :
array : [array_like] Input array.

Return : An array with all array elements being rounded off, having same type and shape as input.

 
Code #1 : Working




# Python program explaining
# rint() function
import numpy as np
  
in_array = [.5, 1.5, 2.5, 3.5, 4.5, 10.1]
print ("Input array : \n", in_array)
  
rintoff_values = np.rint(in_array)
print ("\nRounded values : \n", rintoff_values)
  
  
in_array = [.53, 1.54, .71]
print ("\nInput array : \n", in_array)
  
rintoff_values = np.rint(in_array)
print ("\nRounded values : \n", rintoff_values)
  
in_array = [.5538, 1.33354, .71445]
print ("\nInput array : \n", in_array)
  
rintoff_values = np.rint(in_array)
print ("\nRounded values : \n", rintoff_values)


Output:



Input array : 
 [0.5, 1.5, 2.5, 3.5, 4.5, 10.1]

Rounded values : 
 [  0.   2.   2.   4.   4.  10.]

Input array : 
 [0.53, 1.54, 0.71]

Rounded values : 
 [ 1.  2.  1.]

Input array : 
 [0.5538, 1.33354, 0.71445]

Rounded values : 
 [ 1.  1.  1.]

 

Code #2 : Working




# Python program explaining
# rint() function
import numpy as np
  
in_array = [1 ,4, 7, 9, 12]
print ("Input array : \n", in_array)
  
rintoff_values = np.rint(in_array)
print ("\nRounded values : \n", rintoff_values)
  
in_array = [133 ,344, 437, 449, 12]
print ("\nInput array : \n", in_array)
  
rintoff_values = np.rint(in_array)
print ("\nRounded values upto 2: \n", rintoff_values)
  
in_array = [133 ,344, 437, 449, 12]
print ("\nInput array : \n", in_array)
  
rintoff_values = np.rint(in_array)
print ("\nRounded values upto 3: \n", rintoff_values)


Output:

Input array : 
 [1, 4, 7, 9, 12]

Rounded values : 
 [  1.   4.   7.   9.  12.]

Input array : 
 [133, 344, 437, 449, 12]

Rounded values upto 2: 
 [ 133.  344.  437.  449.   12.]

Input array : 
 [133, 344, 437, 449, 12]

Rounded values upto 3: 
 [ 133.  344.  437.  449.   12.]

 
References : https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.rint.html#numpy.rint
.

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