Least Squares Ellipse Fitting Algorithm Implementation

This example demonstrates the implementation of least squares ellipse fitting using the function fit_ellipse(x, y, axis_handle). The algorithm employs a general conic equation approach (Ax² + Bxy + Cy² + Dx + Ey + F = 0) and utilizes constrained least squares optimization to ensure proper ellipse formation. Through matrix operations and eigenvalue decomposition, the function transforms scattered coordinate points into an optimal elliptical representation, significantly reducing fitting errors and enhancing computational accuracy. The axis_handle parameter enables direct visualization of results on specified plot axes. When dealing with elliptical data pattern analysis, this least squares ellipse fitting implementation serves as an essential tool for precise geometric modeling and data interpretation. The method's mathematical foundation ensures reliable performance across various datasets while maintaining computational efficiency through linear algebra optimizations.