A large collection of equations for Python 2 curve fitting and surface fitting that can output source code in several computing languages, and run a genetic algorithm for initial parameter estimation. Comes with cluster, parallel, IPython, GUI, NodeJS, and web-based graphical examples. Includes orthogonal distance and relative error regressions.

Examples and demos showing how to call functions from the nAG Library for Python

A Modern Fortran translation of the FITPACK package for curve and surface fitting

A large collection of equations for Python 3 curve fitting and surface fitting that can output source code in several computing languages, and run a genetic algorithm for initial parameter estimation. Comes with cluster, parallel, IPython, GUI, NodeJS, and web-based graphical examples. Includes orthogonal distance and relative error regressions.

Python 3 tkinter graphical curve fitting and surface fitting application, saves results to PDF.

A Django site in Python 3 for curve fitting 2D and 3D data that can output source code in several computing languages and run a genetic algorithm for initial parameter estimation. Includes orthogonal distance and relative error regressions. Generates PDF files and surface animations. Based on code from zunzun.com.

Python 3 Flask graphical curve fitting and surface fitting web application

Neural nets for high accuracy multivariable nonlinear regression.

Python 3 wxPython graphical curve fitting and surface fitting application, saves results to PDF.

C++ implementation of joint skeleton-surfaceShape EM-ICP

A Django site in Python 2 for curve fitting 2D and 3D data that can output source code in several computing languages and run a genetic algorithm for initial parameter estimation. Includes orthogonal distance and relative error regressions. Generates PDF files and surface animations. Based on code from zunzun.com.

Matlab toolbox for creating 3D cave models from sparse survey

Python 3 pyQt5 graphical curve fitting and surface fitting application, saves results to PDF

Given are two csv files, pc1.csv and pc2.csv, which contain noisy LIDAR point cloud data in the form of (x, y, z) coordinates of the ground plane. Find best surface fit

Estimating Ground Surface Normals and Fitting Surfaces to Noisy LIDAR Point Cloud Data

Python 3 CherryPy graphical curve fitting and surface fitting web application

Python 3 Bottle graphical curve fitting and surface fitting web application