Python NumPy absolute() function is used to return the element-wise absolute values of the input array. In other words, this mathematical function helps the user to calculate the absolute value element in the given array. An absolute value is a positive value of a given negative value, so it just removes the negative sign from the input value.
The NumPy absolute() function takes four parameters arr, out, where, and dtype, and returns a new array with an argument value as the absolute of the source array elements. In this article, I will explain how to use numpy.absolute() function on single, multi-dimension arrays of float elements, and complex numbers.
1. Quick Examples of Python NumPy Absolute Value
If you are in a hurry, below are some quick examples of how to use Python NumPy absolute value.
# Below are the quick examples
# Example 1: Use numpy.absolute() to get the absolute value
arr = np.array([-46])
arr2 = np.absolute(arr)
# Example 2: get the absolute values of multiple elements of 1-d array
arr = [4, -9, 14, -23, 32, -56]
arr2 = np.absolute(arr)
# Example 3: Use numpy.absolute() function to get
# the absolute values of floating point
arr = [-15.7, 8.6, -7.1, 8.7, -19.2, 43.8]
arr2 = np.absolute(arr)
# Example 4: Use numpy.absolute() get the absolute values
# of 2-D array elements
arr = np.array([[-12, 8, -23, 32], [49, -74, -92, 106]])
arr2 = np.absolute(arr)
# Example 5: Use numpy.absolute() function with complex numbers
arr = [4+7j, -5-9j, 16+13j, -8+17j]
arr2 = np.absolute(arr)
# Example 6: Use np.absolute function to graphical representation
arr = np.linspace(start = -18, stop = 13, num = 12, endpoint = True)
arr2 = np.absolute(arr)
print(arr2)
plt.plot(arr, np.absolute(arr))
plt.plot(arr, arr, color = 'orange')
plt.show()
2. Syntax of NumPy absolute()
Following is the syntax of the numpy.absolute() function.
# Syntax of numpy.absolute()
numpy.absolute(arr, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None)
2.1 Parameters of absolute()
The absolute() function allows the following parameters.
arr -Input array.out– It is ndarray, None, or tuple of ndarray and None, optional. Out will be the location where the result is to be stored. If provided, it must have a shape that the inputs broadcast to. If not provided or None, a freshly-allocated array is returned.where– This condition is broadcast over the input.dtype– It is an optional parameter that specifies the type of the returned array.
2.2 Return Value of absolute()
It returns an array with the absolute value for each element of an array.
3. Usage of NumPy absolute() Function
This mathematical Python NumPy in-built function absolute() takes the input array as param and returns the absolute value of each element in the input array. An absolute value is a positive value of a given negative value, so it just removes the negative sign from the input value. For positive value, it just returns the same value.
3.1 Get the Absolute Value of Single Element
Use numpy.absolute() function to get the absolute value of a single element of an input NumPy array.
import numpy as np
arr = np.array([-46])
# Use numpy.absolute() to get the absolute value
arr2 = np.absolute(arr)
print(arr2)
# Output
# 46
3.2 Get the Absolute Values of Multiple Elements of 1-D Array
Let’s create a one-dimensional NumPy array using numpy.array() and use this function to calculate the absolute value for each element in the NumPy array.
import numpy as np
# Create an 1D input array
arr = [4, -9, 14, -23, 32, -56]
# get the absolute values of multiple elements of 1-d array
arr2 = np.absolute(arr)
print(arr2)
# Output
[ 4 9 14 23 32 56]
4. Get the absolute Values of Float Elements of 1-D NumPy Array
Similaly, lets calculate the absolute value of the float elements of an array by using the numpy.absolute() function. For float values, the absolute returns the positive float value.
import numpy as np
# creating an 1D input array
arr = [-15.7, 8.6, -7.1, 8.7, -19.2, 43.8]
# Use numpy.absolute() function to get
# the absolute values of floating point
arr2 = np.absolute(arr)
print(arr2)
# Output
# [15.7 8.6 7.1 8.7 19.2 43.8]
5. Get the Absolute Values of 2-D NumPy Array Elements
To get absolute values of Two- Dimensional array elements, just pass the two dimensional array tot he absolute() function. It returns the array in same shape as input.
import numpy as np
# creating an 2D input array
arr = np.array([[-12, 8, -23, 32], [49, -74, -92, 106]])
# Use numpy.absolute() get the absolute values
# of 2-D array elements
arr2 = np.absolute(arr)
print(arr2)
# Output
# [[ 12 8 23 32]
# [ 49 74 92 106]]
6. Get the Absolute Values of Complex Numbers
We can also get the absolute value of complex elements of an array. For example
import numpy as np
# Create an array with complex values
arr = [4+7j, -5-9j, 16+13j, -8+17j]
# Use numpy.absolute() function with complex numbers
arr2 = np.absolute(arr)
print(arr2)
# Output
# [ 8.06225775 10.29563014 20.61552813 18.78829423]
7. Get the Absolute Values on Graphical Representation
By using the matplotlib.pyplot, we can represent the absolute values in a graphical representation.
import numpy as np
import matplotlib.pyplot as plt
# Use np.absolute function to graphical representation
arr = np.linspace(start = -18, stop = 13,
num = 12, endpoint = True)
arr2 = np.absolute(arr)
print(arr2)
plt.plot(arr, np.absolute(arr))
plt.plot(arr, arr, color = 'orange')
plt.show()
# Output
# [18. 15.18181818 12.36363636 9.54545455 6.72727273 3.90909091
# 1.09090909 1.72727273 4.54545455 7.36363636 10.18181818 13. ]
Yields below output.
You can see the Parabolic graph of the absolute() method in Numpy.
8. Conclusion
In this article, I have explained how to use Python numpy.absolute() function and how to calculate the absolute value of every element in the given array with examples.
Happy Learning!!
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