#SaxQuantizer

A time/space optimized implementation of Symbolic Aggregate approXimation (SAX), with numerosity reduction and scaling. This is based on ``A Symbolic Representation of Time Series, with Implications for Streaming Algorithms,'' by Jessica Len et al.

---

Dependencies

• C++ compiler with C++11 support
• Boost Math

---

Usage

Simply include saxquantizer.hpp in your project, and use the provided functions from the SaxQuantizer namespace.

See docs for detailed description.

---

Example:

#include <vector>
#include <string>
#include <iostream>
#include "saxquantizer.hpp"

using namespace std;

int main(int argc, char **argv) {
  SaxQuantizer::Sax sax(6, 1, 5);
  vector<double> input = { 1, 1, 1, 1, 2, 2, 10, 10, 100 };
  vector<int> output;
  sax.quantize(input, &output, false); // true for reduction

  cout << "input:";
  for (const auto & x : input) cout << " " << x;
  cout << endl;

  cout << "output:";
  for (const auto & x : output) cout << " " << x;
  cout << endl;
}