How to get the floor, ceiling and truncated values of the elements of a numpy array?
Last Updated :
29 Aug, 2020
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 numpy as np
a = np.array([ 1.2 ])
a = 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 numpy as np
a = np.array([ 1.2 ])
a = 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 numpy as np
a = np.array([ 1.2 ])
a = 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.]
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