Skip to content

Baunt/ABC-SMC

Repository files navigation

Approximate Bayesian Calculation - Sequential Monte Carlo Algorithm

Installation

  1. Required python in the system at least the 3 version. If you install python do not miss to adding into the environment variables. Also required to install matplotlib: pip install matplotlib
  2. Use x64 architecture if you build C++

Documentation

Simplest C++ plotting library --> matplotlib-cpp

##Tips and Tricks

Measure execution time with high precision

Computational complexity of mathematical operations

Complexity
Addition O(n)
Subtraction O(n)
Multiplication O(n^2)
Division O(n^2)
  • Combine constants where we can
  • Instead of use simple math expression like from math library for example pow(x,2) use x*x. Integer quotient use like x*x*x*x. Not cute but effective.
  • Instead of dividing use the inverse of denominator like vector[i] / constant --> vector[i] * constatn2 where constant2 = 1.0 / constatnt1

img.png

TODO

Check this library. Maybe it is faster than Eigen or vanilla C++ NumPy to NumCpp

Extended Doxygen: Standardese

Random number generator: PCG

Mermaid: https://mermaid-js.github.io/mermaid/#/

About

ABC_SMC algorithm implementation

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published

Languages