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) |
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) |
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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