Ran clang-format.

3 files changed, 30 insertions, 21 deletions

diff --git a/langevin.cpp b/langevin.cpp
index dcf8c68..d704266 100644
--- a/langevin.cpp
+++ b/langevin.cpp
@@ -1,8 +1,8 @@
-#include <getopt.h>
-#include <cstdlib>
-#include <random>
 #include <complex>
+#include <cstdlib>
 #include <functional>
+#include <getopt.h>
+#include <random>
 
 #include <eigen3/Eigen/Core>
 #include <eigen3/unsupported/Eigen/CXX11/Tensor>
@@ -60,7 +60,8 @@ std::tuple<double, Vector> WdW(const Tensor& J, const Vector& z) {
   return {W, dW};
 }
 
-Vector langevin(const Tensor& J, const Vector& z0, double T, double γ0, std::function<bool(double, unsigned)> quit, Rng& r) {
+Vector langevin(const Tensor& J, const Vector& z0, double T, double γ0,
+                std::function<bool(double, unsigned)> quit, Rng& r) {
   Vector z = z0;
 
   double W;
@@ -97,13 +98,13 @@ Vector langevin(const Tensor& J, const Vector& z0, double T, double γ0, std::fu
 int main(int argc, char* argv[]) {
   // model parameters
   unsigned N = 10; // number of spins
-  double T = 1; // temperature
-  double Rκ = 1; // real part of distribution parameter
-  double Iκ = 0; // imaginary part of distribution parameter
+  double T = 1;    // temperature
+  double Rκ = 1;   // real part of distribution parameter
+  double Iκ = 0;   // imaginary part of distribution parameter
 
   // simulation parameters
-  double δ = 1e-2; // threshold for determining saddle
-  double γ = 1e-2; // step size
+  double δ = 1e-2;   // threshold for determining saddle
+  double γ = 1e-2;   // step size
   unsigned t = 1000; // number of Langevin steps
 
   int opt;
diff --git a/stereographic.hpp b/stereographic.hpp
index 7a6b411..7dd871c 100644
--- a/stereographic.hpp
+++ b/stereographic.hpp
@@ -17,7 +17,7 @@ Vector stereographicToEuclidean(const Vector& ζ) {
 Vector euclideanToStereographic(const Vector& z) {
   unsigned N = z.size();
   Vector ζ(N - 1);
-  
+
   for (unsigned i = 0; i < N - 1; i++) {
     ζ(i) = z(i) / (sqrt(N) - z(N - 1));
   }
@@ -33,7 +33,7 @@ Matrix stereographicJacobian(const Vector& ζ) {
 
   for (unsigned i = 0; i < N - 1; i++) {
     for (unsigned j = 0; j < N - 1; j++) {
-      J(i, j) = - 4.0 * ζ(i) * ζ(j);
+      J(i, j) = -4.0 * ζ(i) * ζ(j);
       if (i == j) {
         J(i, j) += 2.0 * (1.0 + b);
       }
@@ -55,7 +55,8 @@ Matrix stereographicMetric(const Vector& ζ) {
 
   for (unsigned i = 0; i < N; i++) {
     for (unsigned j = 0; j < N; j++) {
-      g(i, j) = 16.0 * (std::conj(ζ(i)) * ζ(j) * (1.0 + a) - std::real(std::conj(ζ(i) * ζ(j)) * (1.0 + b)));
+      g(i, j) = 16.0 * (std::conj(ζ(i)) * ζ(j) * (1.0 + a) -
+                        std::real(std::conj(ζ(i) * ζ(j)) * (1.0 + b)));
       if (i == j) {
         g(i, j) += 4.0 * std::abs(1.0 + b);
       }
@@ -66,7 +67,8 @@ Matrix stereographicMetric(const Vector& ζ) {
   return g;
 }
 
-std::tuple<std::complex<double>, Vector, Matrix> stereographicHamGradHess(const Tensor3& J, const Vector& ζ) {
+std::tuple<std::complex<double>, Vector, Matrix> stereographicHamGradHess(const Tensor3& J,
+                                                                          const Vector& ζ) {
   Vector grad;
   Matrix hess;
 
diff --git a/tensor.hpp b/tensor.hpp
index 8345d83..9e860d9 100644
--- a/tensor.hpp
+++ b/tensor.hpp
@@ -2,13 +2,14 @@
 
 #include <algorithm>
 #include <array>
-#include <utility>
 #include <eigen3/unsupported/Eigen/CXX11/Tensor>
+#include <utility>
 
 #include "factorial.hpp"
 
 template <class Scalar, unsigned p, std::size_t... Indices>
-void setJ(Scalar z, Eigen::Tensor<Scalar, p>& J, const std::array<unsigned, p>& is, std::index_sequence<Indices...>) {
+void setJ(Scalar z, Eigen::Tensor<Scalar, p>& J, const std::array<unsigned, p>& is,
+          std::index_sequence<Indices...>) {
   J(std::get<Indices>(is)...) = z;
 }
 
@@ -20,7 +21,8 @@ Eigen::Tensor<Scalar, p> initializeJ(unsigned N, std::index_sequence<Indices...>
 }
 
 template <class Scalar, unsigned p, class Distribution, class Generator>
-void populateCouplings(Eigen::Tensor<Scalar, p>& J, unsigned N, unsigned l, std::array<unsigned, p> is, Distribution d, Generator& r) {
+void populateCouplings(Eigen::Tensor<Scalar, p>& J, unsigned N, unsigned l,
+                       std::array<unsigned, p> is, Distribution d, Generator& r) {
   if (l == 0) {
     Scalar z = d(r);
     do {
@@ -52,14 +54,18 @@ Eigen::Tensor<Scalar, p> generateCouplings(unsigned N, Distribution d, Generator
 }
 
 template <class Scalar>
-Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic> contractDown(const Eigen::Tensor<Scalar, 2>& J, const Eigen::Matrix<Scalar, Eigen::Dynamic, 1>& z) {
-  return Eigen::Map<const Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic>>(J.data(), z.size(), z.size());
+Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic>
+contractDown(const Eigen::Tensor<Scalar, 2>& J, const Eigen::Matrix<Scalar, Eigen::Dynamic, 1>& z) {
+  return Eigen::Map<const Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic>>(J.data(), z.size(),
+                                                                                 z.size());
 }
 
 template <class Scalar, int r>
-Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic> contractDown(const Eigen::Tensor<Scalar, r>& J, const Eigen::Matrix<Scalar, Eigen::Dynamic, 1>& z) {
-  Eigen::Tensor<Scalar, 1> zT = Eigen::TensorMap<Eigen::Tensor<const Scalar, 1>>(z.data(), {z.size()});
-  std::array<Eigen::IndexPair<int>, 1> ip = {Eigen::IndexPair<int>(0,0)};
+Eigen::Matrix<Scalar, Eigen::Dynamic, Eigen::Dynamic>
+contractDown(const Eigen::Tensor<Scalar, r>& J, const Eigen::Matrix<Scalar, Eigen::Dynamic, 1>& z) {
+  Eigen::Tensor<Scalar, 1> zT =
+      Eigen::TensorMap<Eigen::Tensor<const Scalar, 1>>(z.data(), {z.size()});
+  std::array<Eigen::IndexPair<int>, 1> ip = {Eigen::IndexPair<int>(0, 0)};
   Eigen::Tensor<Scalar, r - 1> Jz = J.contract(zT, ip);
   return contractDown(Jz, z);
 }