In this article, let’s discuss how to get the floor, ceiling, and truncated values of the elements of a Numpy array. First, we need to import the NumPy library to use all the functions available in it. This can be done with this import statement:
import numpy as np
Getting the floor value
The greatest integer that is less than or equal to x where x is the array element is known as floor value. It can found using the function numpy.floor()
Syntax:
numpy.floor(x[, out]) = ufunc ‘floor’)
Example 1:
Python
# Import the numpy libraryimport numpy as np # Initialize numpy arraya = np.array([1.2]) # Get floor valuea = np.floor(a)print(a) |
Output:
[1.]
Example 2:
Python
import numpy as np a = np.array([-1.8, -1.6, -0.5, 0.5, 1.6, 1.8, 3.0]) a = np.floor(a)print(a) |
OutPut:
[-2., -2., -1., 0., 1., 1., 3.]
Getting the ceil value
The least integer that is greater than or equal to x where x is the array element is known as ceil value. It can be found using the numpy.ceil() method.
Syntax:
numpy.ceil(x[, out]) = ufunc ‘ceil’)
Example 1:
Python
# Import the numpy libraryimport numpy as np # Initialize numpy arraya = np.array([1.2]) # Get ceil valuea = np.ceil(a)print(a) |
Output:
[2.]
Example 2:
Python
import numpy as np a = np.array([-1.8, -1.6, -0.5, 0.5, 1.6, 1.8, 3.0]) a = np.ceil(a)print(a) |
Output:
[-1., -1., -0., 1., 2., 2., 3.]
Getting the Truncate value
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. It can be found using the numpy.trunc() method.
Syntax:
numpy.trunc(x[, out]) = ufunc ‘trunc’)
Example 1:
Python
# Import the numpy libraryimport numpy as np # Initialize numpy arraya = np.array([1.2]) # Get truncate valuea = np.trunc(a)print(a) |
Output:
[1.]
Example 2:
Python
import numpy as np a = np.array([-1.8, -1.6, -0.5, 0.5, 1.6, 1.8, 3.0]) a = np.trunc(a)print(a) |
Output:
[-1., -1., -0., 0., 1., 1., 3.]
Example to get floor, ceil, trunc values of the elements of a numpy array
Python
import numpy as np input_arr = np.array([-1.8, -1.6, -0.5, 0.5, 1.6, 1.8, 3.0])print(input_arr) floor_values = np.floor(input_arr)print("\nFloor values : \n", floor_values) ceil_values = np.ceil(input_arr)print("\nCeil values : \n", ceil_values) trunc_values = np.trunc(input_arr)print("\nTruncated values : \n", trunc_values) |
Output:
[-1.8 -1.6 -0.5 0.5 1.6 1.8 3. ] Floor values : [-2. -2. -1. 0. 1. 1. 3.] Ceil values : [-1. -1. -0. 1. 2. 2. 3.] Truncated values : [-1. -1. -0. 0. 1. 1. 3.]
Attention geek! Strengthen your foundations with the Python Programming Foundation Course and learn the basics.
To begin with, your interview preparations Enhance your Data Structures concepts with the Python DS Course.
