Python Complex to Float

Complex numbers have two parts one that is a regular number (real) and another that is like a special extra part (imaginary). Floats, on the flip side, are straightforward numbers with decimals. So, complex numbers are a bit fancy with both real and imaginary bits, while float are just regular numbers with dots.

Python Complex to Float

Below are some ways and examples by which we can convert complex numbers to float in Python:

Convert Real Part to Float in Python

In this example, a complex number (3 + 4j) is assigned to the variable "complex_number." The real part of the complex number is then converted to a float.

complex_number = 3 + 4j

real_part_float = float(complex_number.real)

print("Complex Number:", complex_number)
print("Real Part as Float:", real_part_float)

Complex Number: (3+4j)
Real Part as Float: 3.0

Converting Imaginary Part to Float in Python

In this example, a complex number (3 + 4j) is assigned to the variable "complex_number." The imaginary part of the complex number is then converted to a float.

complex_number = 3 + 4j

imag_part_float = float(complex_number.imag)

print("Complex Number:", complex_number)
print("Imaginary Part as Float:", imag_part_float)

Complex Number: (3+4j)
Imaginary Part as Float: 4.0

Python Complex Matrix Multiplication with Float Output

In this example, two complex matrices, "matrix_a" and "matrix_b," are multiplied using NumPy dot product function. The resulting complex matrix is stored in "result_matrix," and its real part is extracted and converted to a float. The original matrices, the result matrix, and the real part as a float are then printed.

import numpy as np

matrix_a = np.array([[2 + 3j, 1 - 2j], [0.5 + 1j, -2]])
matrix_b = np.array([[1 - 1j, 2 + 2j], [3j, 4]])

result_matrix = np.dot(matrix_a, matrix_b)

real_part = float(result_matrix.real)

print("Matrix A:\n", matrix_a)
print("Matrix B:\n", matrix_b)
print("Result Matrix (Real Part as Float):\n", result_matrix)
print("Real Part as Float:", real_part)