Removed some unused files.

1 files changed, 0 insertions, 64 deletions

diff --git a/dynamics.hpp b/dynamics.hpp
index 21afd30..7d04b1a 100644
--- a/dynamics.hpp
+++ b/dynamics.hpp
@@ -4,45 +4,7 @@
 #include <eigen3/Eigen/LU>
 #include <random>
 
-#include <iostream>
-
 #include "p-spin.hpp"
-#include "stereographic.hpp"
-
-class gradientDescentStallException: public std::exception {
-  virtual const char* what() const throw() {
-    return "Gradient descent stalled.";
-  }
-};
-
-template <class Real, class Scalar, int p>
-std::tuple<Real, Vector<Scalar>> gradientDescent(const Tensor<Scalar, p>& J, const Vector<Scalar>& z0, Real ε, Real γ0 = 1, Real δγ = 2) {
-  Vector<Scalar> z = z0;
-  Real γ = γ0;
-
-  auto [W, dW] = WdW(J, z);
-
-  while (W > ε) {
-    Vector<Scalar> zNew = normalize(z - γ * dW.conjugate());
-
-    auto [WNew, dWNew] = WdW(J, zNew);
-
-    if (WNew < W) { // If the step lowered the objective, accept it!
-      z = zNew;
-      W = WNew;
-      dW = dWNew;
-      γ = γ0;
-    } else { // Otherwise, shrink the step and try again.
-      γ /= δγ;
-    }
-
-    if (γ < 1e-50) {
-      throw gradientDescentStallException();
-    }
-  }
-
-  return {W, z};
-}
 
 template <class Real, int p>
 Vector<Real> findMinimum(const Tensor<Real, p>& J, const Vector<Real>& z0, Real ε) {
@@ -98,8 +60,6 @@ Vector<Scalar> findSaddle(const Tensor<Scalar, p>& J, const Vector<Scalar>& z0,
 
     std::tie(std::ignore, dH, ddH) = hamGradHess(J, z);
 
-    std::cout << "error : " << g.norm() / z.size() << std::endl;
-
     zz = z.transpose() * z;
     g = dH - (z.transpose() * dH) * z / (Real)z.size() + z * (zz - (Real)z.size());
     M = ddH - (dH * z.transpose() + (z.transpose() * dH) * Matrix<Scalar>::Identity(z.size(), z.size()) + (ddH * z) * z.transpose()) / (Real)z.size()  + Matrix<Scalar>::Identity(z.size(), z.size()) * (zz - (Real)z.size()) + 2.0 * z * z.transpose();
@@ -119,30 +79,6 @@ Vector<Scalar> randomVector(unsigned N, Distribution d, Generator& r) {
   return z;
 }
 
-template <class Real, class Scalar, int p, class Distribution, class Generator>
-std::tuple<Real, Vector<Scalar>> metropolis(const Tensor<Scalar, p>& J, const Vector<Scalar>& z0,
-    std::function<Real(const Tensor<Scalar, p>&, const Vector<Scalar>&)>& energy,
-    Real T, Real γ, unsigned N, Distribution d, Generator& r) {
-  Vector<Scalar> z = z0;
-
-  Real E = energy(J, z);
-
-  std::uniform_real_distribution<Real> D(0, 1);
-
-  for (unsigned i = 0; i < N; i++) {
-    Vector<Scalar> zNew = normalize(z + γ * randomVector<Scalar>(z.size(), d, r));
-
-    Real ENew = energy(J, zNew);
-
-    if (E - ENew > T * log(D(r))) {
-      z = zNew;
-      E = ENew;
-    }
-  }
-
-  return {E, z};
-}
-
 template <class Real, int p, class Distribution, class Generator>
 Vector<Real> randomMinimum(const Tensor<Real, p>& J, Distribution d, Generator& r, Real ε) {
   Vector<Real> zSaddle;