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author | Jaron Kent-Dobias <jaron@kent-dobias.com> | 2019-12-03 12:32:18 -0500 |
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committer | Jaron Kent-Dobias <jaron@kent-dobias.com> | 2019-12-03 12:32:18 -0500 |
commit | e5ce48512f5a80933c696811d2fda70f0f9a2141 (patch) | |
tree | 3d5790246782bc2c6564c125fb49b5329bfd9ee1 | |
parent | 0801c4565346eb441aaea0a2a263ce7aae20298a (diff) | |
download | space_wolff-e5ce48512f5a80933c696811d2fda70f0f9a2141.tar.gz space_wolff-e5ce48512f5a80933c696811d2fda70f0f9a2141.tar.bz2 space_wolff-e5ce48512f5a80933c696811d2fda70f0f9a2141.zip |
ran clang-format
-rw-r--r-- | space_wolff.hpp | 123 |
1 files changed, 79 insertions, 44 deletions
diff --git a/space_wolff.hpp b/space_wolff.hpp index 81ff776..a78116d 100644 --- a/space_wolff.hpp +++ b/space_wolff.hpp @@ -1,5 +1,4 @@ -#include "randutils/randutils.hpp" #include <cmath> #include <eigen3/Eigen/Dense> #include <fstream> @@ -11,6 +10,8 @@ #include <set> #include <vector> +#include "randutils/randutils.hpp" + const std::array<std::array<unsigned, 16>, 16> smiley = { {{{0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0}}, {{0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0}}, @@ -29,13 +30,16 @@ const std::array<std::array<unsigned, 16>, 16> smiley = { {{0, 0, 1, 1, 1, 0, 0, 0, 0, 0, 0, 1, 1, 1, 0, 0}}, {{0, 0, 0, 0, 1, 1, 1, 1, 1, 1, 1, 1, 0, 0, 0, 0}}}}; -template <class T, int D> using Vector = Eigen::Matrix<T, D, 1>; +template <class T, int D> +using Vector = Eigen::Matrix<T, D, 1>; -template <class T, int D> using Matrix = Eigen::Matrix<T, D, D>; +template <class T, int D> +using Matrix = Eigen::Matrix<T, D, D>; /** brief diff - periodic subtraction of vectors */ -template <class T, int D> Vector<T, D> diff(T L, Vector<T, D> v1, Vector<T, D> v2) { +template <class T, int D> +Vector<T, D> diff(T L, Vector<T, D> v1, Vector<T, D> v2) { Vector<T, D> v; for (unsigned i = 0; i < D; i++) { @@ -48,17 +52,19 @@ template <class T, int D> Vector<T, D> diff(T L, Vector<T, D> v1, Vector<T, D> v return v; } -template <class T, int D, class S> class Spin { -public: +template <class T, int D, class S> +class Spin { + public: Vector<T, D> x; S s; }; -template <class T, int D> class Euclidean { -private: +template <class T, int D> +class Euclidean { + private: T L; -public: + public: Vector<T, D> t; Matrix<T, D> r; @@ -79,7 +85,8 @@ public: r = r0; } - template <class S> Spin<T, D, S> act(const Spin<T, D, S>& s) const { + template <class S> + Spin<T, D, S> act(const Spin<T, D, S>& s) const { Spin<T, D, S> s_new; s_new.x = t + r * s.x; @@ -115,13 +122,14 @@ public: } }; -template <class T, int D, class S> class Octree { -private: +template <class T, int D, class S> +class Octree { + private: T L; unsigned N; std::vector<std::set<Spin<T, D, S>*>> data; -public: + public: Octree(T L, unsigned depth) : L(L), N(pow(2, depth)), data(pow(N, D)){}; unsigned ind(Vector<T, D> x) const { @@ -140,14 +148,16 @@ public: void remove(Spin<T, D, S>* s) { data[ind(s->x)].erase(s); }; - std::set<Spin<T, D, S>*> neighbors(const Vector<T, D>& x, unsigned depth) const { + std::set<Spin<T, D, S>*> neighbors(const Vector<T, D>& x, + unsigned depth) const { std::set<Spin<T, D, S>*> ns; std::set<unsigned> seen; nearest_neighbors_of(ind(x), depth, ns, seen); return ns; }; - void nearest_neighbors_of(unsigned ind, unsigned depth, std::set<Spin<T, D, S>*>& ns, + void nearest_neighbors_of(unsigned ind, unsigned depth, + std::set<Spin<T, D, S>*>& ns, std::set<unsigned>& seen) const { ns.insert(data[ind].begin(), data[ind].end()); seen.insert(ind); @@ -155,8 +165,9 @@ public: if (depth > 0) { for (unsigned i = 0; i < D; i++) { for (signed j : {-1, 1}) { - unsigned nind = pow(N, i + 1) * (ind / ((unsigned)pow(N, i + 1))) + - fmod(pow(N, i + 1) + ind + j * pow(N, i), pow(N, i + 1)); + unsigned nind = + pow(N, i + 1) * (ind / ((unsigned)pow(N, i + 1))) + + fmod(pow(N, i + 1) + ind + j * pow(N, i), pow(N, i + 1)); if (!seen.contains(nind)) { seen.insert(nind); @@ -169,13 +180,13 @@ public: }; class quantity { -private: + private: double total; double total2; std::vector<double> C; unsigned wait; -public: + public: unsigned n; std::list<double> hist; @@ -235,7 +246,8 @@ public: } double σ() const { - return 2.0 / (n - wait) * this->τ()[0] * (C[0] / (n - wait) - pow(this->avg(), 2)); + return 2.0 / (n - wait) * this->τ()[0] * + (C[0] / (n - wait) - pow(this->avg(), 2)); } double serr() const { return sqrt(this->σ()); } @@ -243,23 +255,32 @@ public: unsigned num_added() const { return n - wait; } }; -template <class U, int D, class S> class Model; - template <class U, int D, class S> - class measurement { - public: - virtual void pre_cluster(const Model<U, D, S>&, unsigned, const Euclidean<U, D>&) {}; - virtual void plain_bond_visited(const Model<U, D, S>&, const Spin<U, D, S>*, const Spin<U, D, S>*, const Spin<U, D, S>& , double) {}; - virtual void plain_site_transformed(const Model<U, D, S>&, const Spin<U, D, S>*, const Spin<U, D, S>&) {}; - - virtual void ghost_bond_visited(const Model<U, D, S>&, const Spin<U, D, S>&, const Spin<U, D, S>&, double) {}; - virtual void ghost_site_transformed(const Model<U, D, S>&, const Euclidean<U, D>&) {}; +class Model; - virtual void post_cluster(const Model<U, D, S>&) {}; - }; +template <class U, int D, class S> +class measurement { + public: + virtual void pre_cluster(const Model<U, D, S>&, unsigned, + const Euclidean<U, D>&){}; + virtual void plain_bond_visited(const Model<U, D, S>&, const Spin<U, D, S>*, + const Spin<U, D, S>*, const Spin<U, D, S>&, + double){}; + virtual void plain_site_transformed(const Model<U, D, S>&, + const Spin<U, D, S>*, + const Spin<U, D, S>&){}; + + virtual void ghost_bond_visited(const Model<U, D, S>&, const Spin<U, D, S>&, + const Spin<U, D, S>&, double){}; + virtual void ghost_site_transformed(const Model<U, D, S>&, + const Euclidean<U, D>&){}; + + virtual void post_cluster(const Model<U, D, S>&){}; +}; -template <class U, int D, class S> class Model { -public: +template <class U, int D, class S> +class Model { + public: U L; Euclidean<U, D> s0; std::vector<Spin<U, D, S>> s; @@ -271,9 +292,10 @@ public: std::vector<Matrix<U, D>> mats; std::vector<Vector<U, D>> steps; double E; - measurement<U, D, S> &A; + measurement<U, D, S>& A; - void one_sequences(std::list<std::array<double, D>>& sequences, unsigned level) { + void one_sequences(std::list<std::array<double, D>>& sequences, + unsigned level) { if (level > 0) { unsigned new_level = level - 1; unsigned old_length = sequences.size(); @@ -286,9 +308,18 @@ public: } } - Model(U L, std::function<double(const Spin<U, D, S>&, const Spin<U, D, S>&)> Z, - std::function<double(const Spin<U, D, S>&)> B, unsigned dDepth, unsigned nDepth, measurement<U, D, S>& A) - : L(L), s0(L), dict(L, dDepth), Z(Z), B(B), dDepth(dDepth), nDepth(nDepth), A(A) { + Model(U L, + std::function<double(const Spin<U, D, S>&, const Spin<U, D, S>&)> Z, + std::function<double(const Spin<U, D, S>&)> B, unsigned dDepth, + unsigned nDepth, measurement<U, D, S>& A) + : L(L), + s0(L), + dict(L, dDepth), + Z(Z), + B(B), + dDepth(dDepth), + nDepth(nDepth), + A(A) { std::array<double, D> ini_sequence; ini_sequence.fill(1); std::list<std::array<double, D>> sequences; @@ -296,7 +327,7 @@ public: one_sequences(sequences, D); - sequences.pop_front(); // don't want the identity matrix! + sequences.pop_front(); // don't want the identity matrix! for (std::array<double, D> sequence : sequences) { Matrix<U, D> m; @@ -390,10 +421,13 @@ public: } else { Spin<U, D, S> si_new = r.act(*si); std::set<Spin<U, D, S>*> all_neighbors; - std::set<Spin<U, D, S>*> current_neighbors = dict.neighbors(si->x, nDepth); - std::set<Spin<U, D, S>*> new_neighbors = dict.neighbors(si_new.x, nDepth); + std::set<Spin<U, D, S>*> current_neighbors = + dict.neighbors(si->x, nDepth); + std::set<Spin<U, D, S>*> new_neighbors = + dict.neighbors(si_new.x, nDepth); - all_neighbors.insert(current_neighbors.begin(), current_neighbors.end()); + all_neighbors.insert(current_neighbors.begin(), + current_neighbors.end()); all_neighbors.insert(new_neighbors.begin(), new_neighbors.end()); all_neighbors.insert(NULL); for (Spin<U, D, S>* sj : all_neighbors) { @@ -427,7 +461,8 @@ public: std::uniform_real_distribution<double> t_dist(0, L); std::uniform_int_distribution<unsigned> r_dist(0, D - 1); std::uniform_int_distribution<unsigned> ind_dist(0, s.size() - 1); - std::uniform_int_distribution<unsigned> coin(0, mats.size() + steps.size() - 1); + std::uniform_int_distribution<unsigned> coin( + 0, mats.size() + steps.size() - 1); for (unsigned i = 0; i < N; i++) { Vector<U, D> t; |