From 07a5acbdf79153bb505771708202a9a5fc6f98f0 Mon Sep 17 00:00:00 2001
From: Jaron Kent-Dobias <jaron@kent-dobias.com>
Date: Sun, 1 Nov 2020 17:09:15 +0100
Subject: Added correlation code.

---
 hadamard_mcmc.hpp   | 11 +++++++
 hmm_correlation.cpp | 94 +++++++++++++++++++++++++++++++++++++++++++++++++++++
 quantity.hpp        | 39 +++++++++++++---------
 3 files changed, 129 insertions(+), 15 deletions(-)
 create mode 100644 hmm_correlation.cpp

diff --git a/hadamard_mcmc.hpp b/hadamard_mcmc.hpp
index 107622a..634b822 100644
--- a/hadamard_mcmc.hpp
+++ b/hadamard_mcmc.hpp
@@ -68,6 +68,17 @@ public:
       }
     }
   }
+
+  double operator*(const Orthogonal& o2) const {
+    const Orthogonal& o1 = *this;
+    double total = 0;
+    for (unsigned i = 0; i < this->size(); i++) {
+      for (unsigned j = 0; j < this->size(); j++) {
+        total += o1(i, j) * o2(i, j);
+      }
+    }
+    return total;
+  }
 };
 
 class Givens {
diff --git a/hmm_correlation.cpp b/hmm_correlation.cpp
new file mode 100644
index 0000000..80a6927
--- /dev/null
+++ b/hmm_correlation.cpp
@@ -0,0 +1,94 @@
+
+#include "hadamard_mcmc.hpp"
+#include "quantity.hpp"
+#include "matrices.hpp"
+
+#include <chrono>
+#include <fstream>
+#include <iostream>
+
+std::string getFilename(unsigned n, double β, double θ₀, unsigned lag, unsigned skip) {
+  return "correlation_" + std::to_string(n) + "_" + std::to_string(β) + "_" +
+    std::to_string(θ₀) + "_" + std::to_string(lag) + "_" + std::to_string(skip)
+    + ".dat";
+}
+
+class MeasureCorrelation : public Measurement {
+public:
+  Quantity<Orthogonal> Q;
+
+  MeasureCorrelation(unsigned lag, unsigned skip) : Q(lag, skip) {}
+
+  void after_sweep(double, double E, const Orthogonal& M) override {
+    Q.add(M);
+  }
+};
+
+int main(int argc, char* argv[]) {
+  // model parameters
+  unsigned n = 2; // matrix size over four
+
+  // simulation settings
+  double β = 1; // temperature
+  unsigned m = 1e4; // number of relaxation sweeps
+  unsigned N = 1e4; // number of measurement sweeps
+  double θ₀ = 0.05; // standard deviation of step size
+
+  // measurement settings
+  unsigned l = 1e3; // lag in autocorrelation function
+  unsigned s = 1; // skip in autocorrelation function
+
+  bool loadDataFromFile = false;
+
+  int opt;
+
+  while ((opt = getopt(argc, argv, "n:b:m:N:l:t:i:Ls:")) != -1) {
+    switch (opt) {
+    case 'n':
+      n = atoi(optarg);
+      break;
+    case 'b':
+      β = atof(optarg);
+      break;
+    case 'm':
+      m = (unsigned)atof(optarg);
+      break;
+    case 'N':
+      N = (unsigned)atof(optarg);
+      break;
+    case 'l':
+      l = (unsigned)atof(optarg);
+      break;
+    case 's':
+      s = (unsigned)atof(optarg);
+      break;
+    case 't':
+      θ₀ = atof(optarg);
+      break;
+    case 'L':
+      loadDataFromFile = true;
+      break;
+    default:
+      exit(1);
+    }
+  }
+
+  MeasureCorrelation Q(l, s);
+  MCMC simulation(n, β, Q, θ₀);
+
+  if (loadDataFromFile) {
+    Q.Q.read(getFilename(n, β, θ₀, l, s));
+    std::cout << "Imported data from file, number of steps " << Q.Q.num_added() << "." << std::endl;
+  }
+
+  simulation.run(m, true);
+  std::cout << "Finished initial relaxation at " << β << "." << std::endl;
+  simulation.run(N);
+
+  std::cout << "Finished simulation of " << β << ", writing output file." << std::endl;
+  std::string filename = getFilename(n, β, θ₀, l, s);
+  Q.Q.write(filename);
+
+  return 0;
+}
+
diff --git a/quantity.hpp b/quantity.hpp
index 296a6e8..400a0dd 100644
--- a/quantity.hpp
+++ b/quantity.hpp
@@ -8,16 +8,21 @@
 #include <fstream>
 #include <iomanip>
 
+template <class T>
 class Quantity {
 private:
-  unsigned n;
-  std::list<double> hist;
+  uint64_t N;
+  uint64_t n;
+  unsigned skip;
+  std::list<T> hist;
   double total;
   double total2;
   std::vector<double> C;
 
 public:
-  Quantity(unsigned lag) : C(lag) {
+  Quantity(unsigned lag, unsigned s = 1) : C(lag) {
+    skip = s;
+    N = 0;
     n = 0;
     total = 0;
     total2 = 0;
@@ -52,19 +57,23 @@ public:
     hist = {};
   }
 
-  void add(double x) {
-    hist.push_front(x);
-    if (hist.size() > C.size()) {
-      hist.pop_back();
-      unsigned t = 0;
-      for (double a : hist) {
-        C[t] += a * x;
-        t++;
+  void add(const T& x) {
+    if (N % skip == 0) {
+      hist.push_front(x);
+      if (hist.size() > C.size()) {
+        hist.pop_back();
+        unsigned t = 0;
+        for (T a : hist) {
+          C[t] += a * x;
+          t++;
+        }
+        double norm = x * x;
+        total += sqrt(norm);
+        total2 += norm;
+        n++;
       }
-      total += x;
-      total2 += pow(x, 2);
-      n++;
     }
+    N++;
   }
 
   double avg() const { return total / n; }
@@ -96,7 +105,7 @@ public:
       M++;
     }
 
-    return {τtmp, 2.0 * (2.0 * M + 1) * pow(τtmp, 2) / n};
+    return {skip * τtmp, skip * 2.0 * (2.0 * M + 1) * pow(τtmp, 2) / n};
   }
 
   double σ() const {
-- 
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