Overview

Calculators for spline and polynomial interpolation

Inspired by the lectures of Prof. Dr. Achim Kehrein on Numerical Mathematics.

🔧 Current Features

• Cubic spline interpolation from a set of data points (either clamped or natural, just change the flag variable)
• Polynomial interpolation from a set of data points (using Newton’s Approach)
• Plots of both interpolations on the same axes for comparison
• Polynomial interpolation of 3 points (using Lagrange’s Approach) in Python

“Example with 9 Data Points”

📦 Requirements

• MATLAB R2018b or later
• Python (only for Lagrange Interpolater)

🚧 Future Work

• Implementing cubic spline and newton interpolaters in Python and generalising the lagrange interpolater.

📚 References

KEHREIN, Achim. A Primer On Numerical Mathetmatics For Scientists and Engineers. (unreleased, TBA)