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NumAn_Op (stands for Numerical Analysis & Optimization) is a python package that contains some optimization algorithms.

Project description

Numerical_Analysis_Optimization_Package

Python package that contains some numerical analysis & optimization algorithms.

Following are the algorithms present in this package:

I. One dimensional function minimization algorithms:

  • Searching with elimination methods
    • Unrestricted search
    • Exhaustive search
    • Dichotomous search
    • Interval halving method
    • Fibonacci method
    • Golden section method
  • Searching with interpolation methods
    • Newton-Rapson method
    • Quasi-Newton method
    • Secant method

II. System of Equations & Decompositions:

  • The Elimination Of Gauss-Jordan
  • LU Decomposition Method
  • Cholesky Decomposition Method

III. Multi-dimensional function minimization algorithms:

  • Gradient methods
    • Gradient Descent method
    • Conjugate Gradient method
    • AdaGrad
  • Newton methods
    • Newton method
    • Quasi-Newton with DFP and armijo

Visualization of some the progress of some algorithms

Following are some plots visualizing the progress of some algorithms that the package contains. You can find all the scripts to make them in the Plotting_Scripts folder in this repository.

  1. One dimensional function minimization comparison:

    • Elimination methods comparison

      Function Optimization Comparison. (Elimination Methods)

    • Interpolation methods comparison

      Function Optimization Comparison. (Interpolation Methods)

  2. Mutli-Variable function minimization comparison:

    Multi-dimensional function minimization algorithms comparison

Note: You won't get the same progess path for the Adagrad method if you try to use the scripts in the Plotting_Scripts folder, and this is due to the fact that Adagrad is a variant of the stochastic gradient descent method, this means that it takes a random starting point each time.

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