The numpy.trunc() is a mathematical function that returns the truncated value of the elements of array. The trunc of the scalar x is the nearest integer i which, closer to zero than x. This simply means that, the fractional part of the signed number x is discarded by this function.
Syntax : numpy.trunc(x[, out]) = ufunc ‘trunc’)
Parameters :a : [array_like] Input array
Return :
The truncated of each element, with float data-type
Code #1 : Working
# Python program explaining # trunc() function import numpy as np in_array = [. 5 , 1.5 , 2.5 , 3.5 , 4.5 , 10.1 ] print ( "Input array : \n" , in_array) truncoff_values = np.trunc(in_array) print ( "\nRounded values : \n" , truncoff_values) in_array = [. 53 , 1.54 , . 71 ] print ( "\nInput array : \n" , in_array) truncoff_values = np.trunc(in_array) print ( "\nRounded values : \n" , truncoff_values) in_array = [. 5538 , 1.33354 , . 71445 ] print ( "\nInput array : \n" , in_array) truncoff_values = np.trunc(in_array) print ( "\nRounded values : \n" , truncoff_values) |
Output :
Input array : [0.5, 1.5, 2.5, 3.5, 4.5, 10.1] Rounded values : [ 0. 1. 2. 3. 4. 10.] Input array : [0.53, 1.54, 0.71] Rounded values : [ 0. 1. 0.] Input array : [0.5538, 1.33354, 0.71445] Rounded values : [ 0. 1. 0.]
Code 2 : Working
# Python program explaining # trunc() function import numpy as np in_array = [ 1.67 , 4.5 , 7 , 9 , 12 ] print ( "Input array : \n" , in_array) truncoff_values = np.trunc(in_array) print ( "\nRounded values : \n" , truncoff_values) in_array = [ 133.000 , 344.54 , 437.56 , 44.9 , 1.2 ] print ( "\nInput array : \n" , in_array) truncoff_values = np.trunc(in_array) print ( "\nRounded values upto 2: \n" , truncoff_values) |
Output :
Input array : [1.67, 4.5, 7, 9, 12] Rounded values : [ 1. 4. 7. 9. 12.] Input array : [133.0, 344.54, 437.56, 44.9, 1.2] Rounded values upto 2: [ 133. 344. 437. 44. 1.]
References : https://docs.scipy.org/doc/numpy-dev/reference/generated/numpy.trunc.html#numpy.trunc
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