Numpy is the best Python library for manipulating an array in any dimension efficiently. In fact, you often use NumPy array for demonstration purposes like a random sample, plotting e.t.c. Numpy Conjugate is one of the methods in NumPy. It allows you to calculate the conjugate gradient in machine learning which is very helpful in making a good predictive model. In this entire article, you will know how to calculate numpy conjugate for both one and two-dimensional arrays.
But before going to the demonstration part lets learn the syntax of the NumPy conjugate
numpy.conjugate(x, /, out=None, *, where=True, casting='same_kind', order='K', dtype=None, subok=True[, signature, extobj])
The explanation of the Most used parameters is below.
x: Your input NumPy array with complex elements.
out: Use it if you want to store the output in another array.
where: This condition is broadcast over the input. It used with the combination of the out parameter.
To know more about the other parameters you can go to the Numpy Conjugate Offical Documentation.
Steps to implement Numpy Conjugate in python
In this section, you will know all the steps to create a NumPy array with each element as a complex number. Then after you will find its conjugate using the conjugate() method.
Step 1: Import necessary modules
In my example, I am using only the NumPy array. Therefore let’s import it using the import statement.
import numpy as np
Step2: Create an Array of Complex Numbers
The second step is to create a complex number. For our coding demonstration, I am using both the 1D and 2D NumPy array. You can create a NumPy array using the numpy.array() method. Let’s create them.
1D Complex Numpy Array
con_array_1d = np.array([1+2j,5-4j,10+9j])
2D Complex Numpy array
con_array_2d = np.eye(3)+1j
Step 3: Find the conjugate of the NumPy array
After implementing step 2, now let’s calculate the conjugate of the complex number. To do so you have to just pass the array as an argument to the np. conjugate() method. Use the following lines of code to find the conjugate.
Conjugate for 1D Array
import numpy as np con_array_1d = np.array([1+2j,5-4j,10+9j]) print(np.conjugate(con_array_1d))
Conjugate for 2D Array
import numpy as np con_array_2d = np.eye(3)+1j print(np.conjugate(con_array_2d))
That’s all for now. Conjugate of a complex number is very helpful in solving the linear equations in algebra. These are examples of the implementation of the conjugate method. Hope you have properly learned it. In case you have any doubt then you can contact us for more information.
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