@@ -188,7 +188,17 @@ Running scripts
Batch system
For the phase_transition_mpi program, there are scripts in the **./slurm_scripts** directory that come along with it. This is to be able to run it on a batch system using Slurm if you have access to one. The only program that should be executed by the user is the **./slurm_scripts/execute.script** script. You can see how to use this script by doing:
./slurm_scripts/execute.script --help
-
This is the recommended way to use this program as it takes approximately 90 minutes to complete when using 8 processes where each process has 10 threads.
+This is the recommended way of using the program. Here is a table using different parameters on the Fox cluster:
+
+
+| Lattice size | Samples | Processes | threads | Time (seconds) |
+
+| 20 | 1e7 | 10 | 10 | 133.735 |
+
+| 40 | 1e7 | 10 | 10 | 814.126 |
+
+| 60 | 1e7 | 10 | 10 | 2575.33 |
+
If you happen to have such a system available to you, then you should clone this repo on that system, then compile the MPI program like this:
make bin/phase_transition_mpi
After compiling, you can schedule it by using the **./slurm_scripts/execute.script**:
diff --git a/docs/main_8cpp.html b/docs/main_8cpp.html
index a5e86df..6ac48da 100644
--- a/docs/main_8cpp.html
+++ b/docs/main_8cpp.html
@@ -119,7 +119,7 @@ Functions
| | Create the data for the burn-in time for temperatures 1.0 and 2.4 for both unordered and ordered initial states.
|
| |
| void | create_pd_estimate_data () |
-| | Create the data used to estimate the probability distribution for tempratures 1.0 anbd 2.4.
|
+| | Create the data used to estimate the probability distribution for tempratures 1.0 and 2.4.
|
| |
| void | test_burn_in_time () |
| | Create data using the same parameters except one uses burn-in time, while the other doesn't.
|
@@ -183,7 +183,7 @@ Janita Ovidie Sandtrøen Willumsen (janitaws)
-
Create the data used to estimate the probability distribution for tempratures 1.0 anbd 2.4.
+
Create the data used to estimate the probability distribution for tempratures 1.0 and 2.4.
Definition at line 37 of file main.cpp.
diff --git a/docs/main_8cpp_source.html b/docs/main_8cpp_source.html
index 727245f..5ee72db 100644
--- a/docs/main_8cpp_source.html
+++ b/docs/main_8cpp_source.html
@@ -125,25 +125,25 @@ $(document).ready(function(){initNavTree('main_8cpp_source.html',''); initResiza
24 montecarlo::progression(1.0, 20, 20000,
-
25 "../output/burn_in_time/unordered_1_0.txt");
+
25 "./data/hp/burn_in_time/unordered_1_0.txt");
26 montecarlo::progression(1.0, 20, 20000, 1,
-
27 "../output/burn_in_time/ordered_1_0.txt");
+
27 "./data/hp/burn_in_time/ordered_1_0.txt");
28 montecarlo::progression(2.4, 20, 20000,
-
29 "../output/burn_in_time/unordered_2_4.txt");
+
29 "./data/hp/burn_in_time/unordered_2_4.txt");
30 montecarlo::progression(2.4, 20, 20000, 1,
-
31 "../output/burn_in_time/ordered_2_4.txt");
+
31 "./data/hp/burn_in_time/ordered_2_4.txt");
-
35
+
35
36
-
41 "../output/pd_estimate/estimate_1_0.txt");
+
41 "./data/hp/pd_estimate/estimate_1_0.txt");
-
43 "../output/pd_estimate/estimate_2_4.txt");
+
43 "./data/hp/pd_estimate/estimate_2_4.txt");
@@ -153,10 +153,10 @@ $(document).ready(function(){initNavTree('main_8cpp_source.html',''); initResiza
-
53 "../output/test_burn_in_time/burn_in.txt", 5000);
+
53 "./data/hp/test_burn_in_time/burn_in.txt", 5000);
-
56 "../output/test_burn_in_time/no_burn_in.txt", 0);
+
56 "./data/hp/test_burn_in_time/no_burn_in.txt", 0);
@@ -191,19 +191,19 @@ $(document).ready(function(){initNavTree('main_8cpp_source.html',''); initResiza
-
91 "../output/phase_transition/size_20.txt");
+
91 "./data/hp/phase_transition/size_20.txt");
-
94 "../output/phase_transition/size_40.txt");
+
94 "./data/hp/phase_transition/size_40.txt");
-
97 "../output/phase_transition/size_60.txt");
+
97 "./data/hp/phase_transition/size_60.txt");
-
100 "../output/phase_transition/size_80.txt");
+
100 "./data/hp/phase_transition/size_80.txt");
-
103 "../output/phase_transition/size_100.txt");
+
103 "./data/hp/phase_transition/size_100.txt");
104 t1 = omp_get_wtime();
106 std::cout <<
"Time: " << t1 - t0 << std::endl;
@@ -281,15 +281,15 @@ $(document).ready(function(){initNavTree('main_8cpp_source.html',''); initResiza
Type to use with the IsingModel class and montecarlo module.
void test_parallel_speedup()
Test how much Openmp speeds up.
int main(int argc, char **argv)
The main function.
-
void create_pd_estimate_data()
Create the data used to estimate the probability distribution for tempratures 1.0 anbd 2....
+
void create_pd_estimate_data()
Create the data used to estimate the probability distribution for tempratures 1.0 and 2....
void create_burn_in_time_data()
Create the data for the burn-in time for temperatures 1.0 and 2.4 for both unordered and ordered init...
void test_burn_in_time()
Create data using the same parameters except one uses burn-in time, while the other doesn't.
void create_phase_transition_data()
Create data for studying phase transition.
void usage(std::string filename)
A function that displays how to use the program and quits.
-
void phase_transition(int L, double start_T, double end_T, int points_T, int cycles, std::function< data_t(int, double, int, int)> monte_carlo, std::string outfile, int burn_in_time=BURN_IN_TIME)
Perform the MCMC algorithm using a range of temperatures.
-
data_t mcmc_parallel(int L, double T, int cycles, int burn_in_time=BURN_IN_TIME)
Execute the Metropolis algorithm for a certain amount of Monte Carlo cycles in parallel.
-
data_t mcmc_serial(int L, double T, int cycles, int burn_in_time=BURN_IN_TIME)
Execute the Metropolis algorithm for a certain amount of Monte Carlo cycles.
-
void pd_estimate(double T, int L, int cycles, const std::string filename, int burn_in_time=BURN_IN_TIME)
Estimate the probability distribution for the energy.
+
void phase_transition(int L, double start_T, double end_T, int points_T, int cycles, std::function< data_t(int, double, int, int)> monte_carlo, std::string outfile, int burn_in_time=BURN_IN_TIME)
Perform the MCMC algorithm using a range of temperatures.
+
data_t mcmc_parallel(int L, double T, int cycles, int burn_in_time=BURN_IN_TIME)
Execute the Metropolis algorithm for a certain amount of Monte Carlo cycles in parallel.
+
data_t mcmc_serial(int L, double T, int cycles, int burn_in_time=BURN_IN_TIME)
Execute the Metropolis algorithm for a certain amount of Monte Carlo cycles.
+
void pd_estimate(double T, int L, int cycles, const std::string filename, int burn_in_time=BURN_IN_TIME)
Estimate the probability distribution for the energy.
5
6
7
- 8
+ 8
9
10
11
@@ -135,52 +135,67 @@ $(document).ready(function(){initNavTree('mcmc__progression_8cpp_source.html',''
32int main(
int argc,
char **argv)
- 35 struct option long_options[] = {{
"help", 0, 0, 0}, {NULL, 0, NULL, 0}};
-
- 37 int option_index = -1;
-
-
-
- 41 c = getopt_long(argc, argv,
"h", long_options, &option_index);
-
-
-
-
-
-
- 48 switch (option_index) {
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
-
- 69 double temp = atoi(argv[1]);
- 70 int L = atoi(argv[2]), cycles = atoi(argv[3]), burn_in_time = atoi(argv[4]);
- 71 std::string outfile = argv[5];
-
- 73 montecarlo::progression(temp, L, cycles, outfile, burn_in_time);
+ 35 struct option long_options[] = {
+ 36 {
"help", 0, 0, 0}, {NULL, 0, NULL, 0}};
+
+ 38 int option_index = -1;
+
+
+
+ 42 c = getopt_long(argc, argv,
"h", long_options, &option_index);
+
+
+
+
+
+
+ 49 switch (option_index) {
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
+
-
-
- 77 std::cout <<
"Time: " << t1 - t0 <<
" seconds\n";
-
+
+ 76 double temp = atoi(argv[1]);
+ 77 int L = atoi(argv[2]), cycles = atoi(argv[3]), burn_in_time = atoi(argv[4]);
+ 78 std::string outfile = argv[5];
+
+
+
+
+
+
+ 85 montecarlo::progression(temp, L, cycles, outfile, burn_in_time);
+
+
+
+
+ 90 std::cout <<
"Time: " << t1 - t0 <<
" seconds\n";
+
int main(int argc, char **argv)
The main function.
void usage(std::string filename)
A function that displays how to use the program and quits.
void progression(double T, int L, int cycles, int value, const std::string filename, int burn_in_time=BURN_IN_TIME)
Write the expected values for each Monte Carlo cycles to file.
#define DEBUG(msg)
Writes a debug message.
- Returns
- data_t
-Definition at line 141 of file monte_carlo.cpp.
+Definition at line 127 of file monte_carlo.cpp.
@@ -245,7 +245,7 @@ Janita Ovidie Sandtrøen Willumsen (janitaws)
- Returns
- data_t
-Definition at line 122 of file monte_carlo.cpp.
+Definition at line 108 of file monte_carlo.cpp.
@@ -305,7 +305,7 @@ Janita Ovidie Sandtrøen Willumsen (janitaws)
-Definition at line 91 of file monte_carlo.cpp.
+Definition at line 77 of file monte_carlo.cpp.
@@ -385,7 +385,7 @@ Janita Ovidie Sandtrøen Willumsen (janitaws)
-Definition at line 169 of file monte_carlo.cpp.
+Definition at line 155 of file monte_carlo.cpp.
@@ -512,7 +512,7 @@ Janita Ovidie Sandtrøen Willumsen (janitaws)
-Definition at line 53 of file monte_carlo.cpp.
+Definition at line 46 of file monte_carlo.cpp.
diff --git a/docs/monte__carlo_8cpp_source.html b/docs/monte__carlo_8cpp_source.html
index cf453d5..d035ff8 100644
--- a/docs/monte__carlo_8cpp_source.html
+++ b/docs/monte__carlo_8cpp_source.html
@@ -126,180 +126,166 @@ $(document).ready(function(){initNavTree('monte__carlo_8cpp_source.html',''); in
-
- 27 std::random_device rd;
- 28 uint32_t rd_sample = rd();
- 29 std::mt19937 engine(rd_sample);
-
- 31 std::cout <<
"Seed: " << rd_sample << std::endl;
-
-
-
-
-
-
-
- 39 for (size_t i = 0; i < burn_in_time; i++) {
-
-
-
-
- 44 for (size_t i = 1; i <= cycles; i++) {
-
- 46 tmp = data / (i * n_spins);
- 47 ofile << i <<
',' << tmp
.E <<
',' << tmp
.E2 <<
',' << tmp
.M <<
','
-
-
-
-
+
+
+
+
+
+
+ 32 for (size_t i = 0; i < burn_in_time; i++) {
+
+
+
+
+ 37 for (size_t i = 1; i <= cycles; i++) {
+
+ 39 tmp = data / (i * n_spins);
+ 40 ofile << i <<
',' << tmp
.E <<
',' << tmp
.E2 <<
',' << tmp
.M <<
','
+
+
+
+
+
+
+ 47 const std::string filename,
int burn_in_time)
+
+
+
+
-
- 54 const std::string filename,
int burn_in_time)
-
-
-
-
-
-
-
-
-
-
- 65 std::random_device rd;
- 66 uint32_t rd_sample = rd();
- 67 std::mt19937 engine(rd());
-
- 69 std::cout <<
"Seed: " << rd_sample << std::endl;
-
-
-
- 73 for (size_t i = 0; i < burn_in_time; i++) {
-
-
+
+
+
+
+
+
+ 59 for (size_t i = 0; i < burn_in_time; i++) {
+
+
+
+
+
+
+
+
+ 68 for (size_t i = 1; i <= cycles; i++) {
+
+ 70 tmp = data / (i * n_spins);
+ 71 ofile << i <<
',' << tmp
.E <<
',' << tmp
.E2 <<
',' << tmp
.M <<
','
+
+
+
+
-
-
-
-
-
- 82 for (size_t i = 1; i <= cycles; i++) {
-
- 84 tmp = data / (i * n_spins);
- 85 ofile << i <<
',' << tmp
.E <<
',' << tmp
.E2 <<
',' << tmp
.M <<
','
-
-
-
-
-
- 91void pd_estimate(
double T,
int L,
int cycles,
const std::string filename,
-
-
-
-
-
+ 77void pd_estimate(
double T,
int L,
int cycles,
const std::string filename,
+
+
+
+
+
+
+
+
+
+
+
+
+ 90 for (size_t i = 0; i < burn_in_time; i++) {
+
+
+
+
+
+
-
-
-
-
-
-
- 104 for (size_t i = 0; i < burn_in_time; i++) {
-
-
-
-
-
- 110 ofile.open(filename);
-
-
- 113 for (size_t i = 1; i <= cycles; i++) {
-
- 115 ofile << data
.E <<
',' << data
.E2 <<
',' << data
.M <<
',' << data
.M2
- 116 <<
',' << data
.M_abs <<
'\n';
-
-
-
-
-
-
-
-
-
+
+ 99 for (size_t i = 1; i <= cycles; i++) {
+
+ 101 ofile << data
.E <<
',' << data
.E2 <<
',' << data
.M <<
',' << data
.M2
+ 102 <<
',' << data
.M_abs <<
'\n';
+
+
+
+
+
+
+
+
+
+
+ 113 for (size_t i = 0; i < burn_in_time; i++) {
+
+
+
+
+ 118 for (size_t i = 0; i < (uint)cycles; i++) {
+
+
+
+ 122 double norm = 1. / (
double)cycles;
+
+
+
- 127 for (size_t i = 0; i < burn_in_time; i++) {
-
-
-
-
- 132 for (size_t i = 0; i < (uint)cycles; i++) {
-
-
-
- 136 double norm = 1. / (
double)cycles;
-
-
-
+
+
+
+
+
+
+
+
+
+
+ 137 for (size_t i = 0; i < burn_in_time; i++) {
+
+
-
-
-
-
-
-
-
-
-
-
- 151 for (size_t i = 0; i < burn_in_time; i++) {
-
-
+
+
+
+ 144#pragma omp for schedule(static) reduction(+ : data)
+ 145 for (size_t i = 0; i < (uint)cycles; i++) {
+
+
+
+
+ 150 double norm = 1. / (
double)cycles;
+
+
+
-
-
-
- 158#pragma omp for schedule(static) reduction(+ : data)
- 159 for (size_t i = 0; i < (uint)cycles; i++) {
-
-
-
-
- 164 double norm = 1. / (
double)cycles;
-
-
-
-
-
- 170 std::function<
data_t(
int,
double,
int,
int)> monte_carlo,
- 171 std::string outfile,
int burn_in_time)
-
- 173 double dt = (end - start) / (
double)points;
-
-
+
+ 156 std::function<
data_t(
int,
double,
int,
int)> monte_carlo,
+ 157 std::string outfile,
int burn_in_time)
+
+ 159 double dt = (end - start) / (
double)points;
+
+
+
+
+
+
+
+
+ 168 double temp, CV, X, E_var, M_var;
+
+ 170 using utils::scientific_format;
+ 171 for (size_t i = 0; i < points; i++) {
+ 172 temp = start + dt * i;
+ 173 data = monte_carlo(L, temp, cycles, burn_in_time);
+ 174 E_var = (data
.E2 - data
.E * data
.E) / (
double)N;
+
-
-
-
-
-
- 182 double temp, CV, X, E_var, M_var;
-
- 184 using utils::scientific_format;
- 185 for (size_t i = 0; i < points; i++) {
- 186 temp = start + dt * i;
- 187 data = monte_carlo(L, temp, cycles, burn_in_time);
- 188 E_var = (data
.E2 - data
.E * data
.E) / (
double)N;
-
-
-
-
-
-
-
-
-
-
-
+
+
+
+
+
+
+
+
+
The Ising model in 2 dimensions.
IsingModel(int L, double T, int val)
Constructor for the Ising model.
IsingModel(int L, double T)
Constructor for the Ising model.
double M2
Magnetization squared.
void progression(double T, int L, int cycles, int value, const std::string filename, int burn_in_time=BURN_IN_TIME)
Write the expected values for each Monte Carlo cycles to file.
void phase_transition(int L, double start_T, double end_T, int points_T, int cycles, std::function< data_t(int, double, int, int)> monte_carlo, std::string outfile, int burn_in_time=BURN_IN_TIME)
Perform the MCMC algorithm using a range of temperatures.
void progression(double T, int L, int cycles, int value, const std::string filename, int burn_in_time=BURN_IN_TIME)
Write the expected values for each Monte Carlo cycles to file.
void phase_transition(int L, double start_T, double end_T, int points_T, int cycles, std::function< data_t(int, double, int, int)> monte_carlo, std::string outfile, int burn_in_time=BURN_IN_TIME)
Perform the MCMC algorithm using a range of temperatures.
void progression(double T, int L, int cycles, const std::string filename, int burn_in_time=BURN_IN_TIME)
Write the expected values for each Monte Carlo cycles to file.
data_t mcmc_parallel(int L, double T, int cycles, int burn_in_time=BURN_IN_TIME)
Execute the Metropolis algorithm for a certain amount of Monte Carlo cycles in parallel.
data_t mcmc_serial(int L, double T, int cycles, int burn_in_time=BURN_IN_TIME)
Execute the Metropolis algorithm for a certain amount of Monte Carlo cycles.
void pd_estimate(double T, int L, int cycles, const std::string filename, int burn_in_time=BURN_IN_TIME)
Estimate the probability distribution for the energy.
data_t mcmc_parallel(int L, double T, int cycles, int burn_in_time=BURN_IN_TIME)
Execute the Metropolis algorithm for a certain amount of Monte Carlo cycles in parallel.
data_t mcmc_serial(int L, double T, int cycles, int burn_in_time=BURN_IN_TIME)
Execute the Metropolis algorithm for a certain amount of Monte Carlo cycles.
void pd_estimate(double T, int L, int cycles, const std::string filename, int burn_in_time=BURN_IN_TIME)
Estimate the probability distribution for the energy.
bool mkpath(std::string path, int mode=0777)
Make path given.
std::string scientific_format(double d, int width=20, int prec=10)
Turns a double into a string written in scientific format.
std::string dirname(const std::string &path)
Get the directory name of the path.
- Returns
- data_t
-Definition at line 141 of file monte_carlo.cpp.
+Definition at line 127 of file monte_carlo.cpp.
@@ -273,7 +273,7 @@ Janita Ovidie Sandtrøen Willumsen (janitaws)
- Returns
- data_t
-Definition at line 122 of file monte_carlo.cpp.
+Definition at line 108 of file monte_carlo.cpp.
@@ -333,7 +333,7 @@ Janita Ovidie Sandtrøen Willumsen (janitaws)
-Definition at line 91 of file monte_carlo.cpp.
+Definition at line 77 of file monte_carlo.cpp.
@@ -413,7 +413,7 @@ Janita Ovidie Sandtrøen Willumsen (janitaws)
-Definition at line 169 of file monte_carlo.cpp.
+Definition at line 155 of file monte_carlo.cpp.
@@ -540,7 +540,7 @@ Janita Ovidie Sandtrøen Willumsen (janitaws)
-Definition at line 53 of file monte_carlo.cpp.
+Definition at line 46 of file monte_carlo.cpp.
diff --git a/docs/monte__carlo_8hpp_source.html b/docs/monte__carlo_8hpp_source.html
index b04f385..2f04bf6 100644
--- a/docs/monte__carlo_8hpp_source.html
+++ b/docs/monte__carlo_8hpp_source.html
@@ -207,18 +207,18 @@ $(document).ready(function(){initNavTree('monte__carlo_8hpp_source.html',''); in
Type to use with the IsingModel class and montecarlo module.
void test_parallel_speedup()
Test how much Openmp speeds up.
int main(int argc, char **argv)
The main function.
void create_pd_estimate_data()
Create the data used to estimate the probability distribution for tempratures 1.0 anbd 2....
void create_pd_estimate_data()
Create the data used to estimate the probability distribution for tempratures 1.0 and 2....
void create_burn_in_time_data()
Create the data for the burn-in time for temperatures 1.0 and 2.4 for both unordered and ordered init...
void test_burn_in_time()
Create data using the same parameters except one uses burn-in time, while the other doesn't.
void create_phase_transition_data()
Create data for studying phase transition.
void usage(std::string filename)
A function that displays how to use the program and quits.
void progression(double T, int L, int cycles, int value, const std::string filename, int burn_in_time=BURN_IN_TIME)
Write the expected values for each Monte Carlo cycles to file.
void phase_transition(int L, double start_T, double end_T, int points_T, int cycles, std::function< data_t(int, double, int, int)> monte_carlo, std::string outfile, int burn_in_time=BURN_IN_TIME)
Perform the MCMC algorithm using a range of temperatures.
void progression(double T, int L, int cycles, int value, const std::string filename, int burn_in_time=BURN_IN_TIME)
Write the expected values for each Monte Carlo cycles to file.
void phase_transition(int L, double start_T, double end_T, int points_T, int cycles, std::function< data_t(int, double, int, int)> monte_carlo, std::string outfile, int burn_in_time=BURN_IN_TIME)
Perform the MCMC algorithm using a range of temperatures.
void progression(double T, int L, int cycles, const std::string filename, int burn_in_time=BURN_IN_TIME)
Write the expected values for each Monte Carlo cycles to file.
data_t mcmc_parallel(int L, double T, int cycles, int burn_in_time=BURN_IN_TIME)
Execute the Metropolis algorithm for a certain amount of Monte Carlo cycles in parallel.
data_t mcmc_serial(int L, double T, int cycles, int burn_in_time=BURN_IN_TIME)
Execute the Metropolis algorithm for a certain amount of Monte Carlo cycles.
void pd_estimate(double T, int L, int cycles, const std::string filename, int burn_in_time=BURN_IN_TIME)
Estimate the probability distribution for the energy.
data_t mcmc_parallel(int L, double T, int cycles, int burn_in_time=BURN_IN_TIME)
Execute the Metropolis algorithm for a certain amount of Monte Carlo cycles in parallel.
data_t mcmc_serial(int L, double T, int cycles, int burn_in_time=BURN_IN_TIME)
Execute the Metropolis algorithm for a certain amount of Monte Carlo cycles.
void pd_estimate(double T, int L, int cycles, const std::string filename, int burn_in_time=BURN_IN_TIME)
Estimate the probability distribution for the energy.
int main(int argc, char **argv)
The main function.
void usage(std::string filename)
A function that displays how to use the program and quits.
void pd_estimate(double T, int L, int cycles, const std::string filename, int burn_in_time=BURN_IN_TIME)
Estimate the probability distribution for the energy.
void pd_estimate(double T, int L, int cycles, const std::string filename, int burn_in_time=BURN_IN_TIME)
Estimate the probability distribution for the energy.
int main(int argc, char **argv)
The main function.
void usage(std::string filename)
A function that displays how to use the program and quits.
void phase_transition(int L, double start_T, double end_T, int points_T, int cycles, std::function< data_t(int, double, int, int)> monte_carlo, std::string outfile, int burn_in_time=BURN_IN_TIME)
Perform the MCMC algorithm using a range of temperatures.
data_t mcmc_parallel(int L, double T, int cycles, int burn_in_time=BURN_IN_TIME)
Execute the Metropolis algorithm for a certain amount of Monte Carlo cycles in parallel.
void phase_transition(int L, double start_T, double end_T, int points_T, int cycles, std::function< data_t(int, double, int, int)> monte_carlo, std::string outfile, int burn_in_time=BURN_IN_TIME)
Perform the MCMC algorithm using a range of temperatures.
data_t mcmc_parallel(int L, double T, int cycles, int burn_in_time=BURN_IN_TIME)
Execute the Metropolis algorithm for a certain amount of Monte Carlo cycles in parallel.
Type to use with the IsingModel class and montecarlo module.
int main(int argc, char **argv)
The main function.
void usage(std::string filename)
A function that displays how to use the program and quits.
data_t mcmc_parallel(int L, double T, int cycles, int burn_in_time=BURN_IN_TIME)
Execute the Metropolis algorithm for a certain amount of Monte Carlo cycles in parallel.
data_t mcmc_parallel(int L, double T, int cycles, int burn_in_time=BURN_IN_TIME)
Execute the Metropolis algorithm for a certain amount of Monte Carlo cycles in parallel.
bool mkpath(std::string path, int mode=0777)
Make path given.
std::string scientific_format(double d, int width=20, int prec=10)
Turns a double into a string written in scientific format.
std::string dirname(const std::string &path)
Get the directory name of the path.
The main function.
-Definition at line 79 of file time.cpp.
+Definition at line 87 of file time.cpp.
@@ -210,7 +210,7 @@ Janita Ovidie Sandtrøen Willumsen (janitaws)
Time phase transition using different sample sizes.
-Definition at line 45 of file time.cpp.
+Definition at line 49 of file time.cpp.
@@ -232,7 +232,7 @@ Janita Ovidie Sandtrøen Willumsen (janitaws)
A function that displays how to use the program and quits.
-Definition at line 67 of file time.cpp.
+Definition at line 75 of file time.cpp.
diff --git a/docs/time_8cpp_source.html b/docs/time_8cpp_source.html
index b4559b7..19b3f8a 100644
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21
- 24 std::string outfile =
"data/timing/lattice_sizes.txt";
+ 24 std::string outfile =
"data/hp/timing/lattice_sizes.txt";
27 int lattice_sizes[] = {20, 40, 60, 80, 100};
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int L : lattice_sizes) {
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"\t[ -h | --help ]\n"
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"\t[ --time-lattice-sizes ]\n"
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"\t[ --time-sample-sizes ]\n";
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- 79int main(
int argc,
char **argv)
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- 81 struct option long_options[] = {{
"all", 0, 0, 0},
- 82 {
"time-lattice-sizes", 0, 0, 0},
- 83 {
"time-sample-sizes", 0, 0, 0},
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- 87 int option_index = -1;
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+ 77 std::cout <<
"Usage: " << filename <<
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+ 78 <<
"At least one option should be used.\n\n"
+ 79 <<
"\t[ -h | --help ]\n"
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+ 81 <<
"\t[ --time-lattice-sizes ]\n"
+ 82 <<
"\t[ --time-sample-sizes ]\n";
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+ 87int main(
int argc,
char **argv)
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+ 89 struct option long_options[] = {{
"all", 0, 0, 0},
+ 90 {
"time-lattice-sizes", 0, 0, 0},
+ 91 {
"time-sample-sizes", 0, 0, 0},
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+ 95 int option_index = -1;
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+ 99 c = getopt_long(argc, argv,
"h", long_options, &option_index);
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int main(int argc, char **argv)
The main function.
void usage(std::string filename)
A function that displays how to use the program and quits.
void phase_transition(int L, double start_T, double end_T, int points_T, int cycles, std::function< data_t(int, double, int, int)> monte_carlo, std::string outfile, int burn_in_time=BURN_IN_TIME)
Perform the MCMC algorithm using a range of temperatures.
data_t mcmc_parallel(int L, double T, int cycles, int burn_in_time=BURN_IN_TIME)
Execute the Metropolis algorithm for a certain amount of Monte Carlo cycles in parallel.
void phase_transition(int L, double start_T, double end_T, int points_T, int cycles, std::function< data_t(int, double, int, int)> monte_carlo, std::string outfile, int burn_in_time=BURN_IN_TIME)
Perform the MCMC algorithm using a range of temperatures.
data_t mcmc_parallel(int L, double T, int cycles, int burn_in_time=BURN_IN_TIME)
Execute the Metropolis algorithm for a certain amount of Monte Carlo cycles in parallel.
data_t mcmc_serial(int L, double T, int cycles, int burn_in_time=BURN_IN_TIME)
Execute the Metropolis algorithm for a certain amount of Monte Carlo cycles.
void time_lattice_sizes()
Time phase transition using different lattice sizes.
void time_sample_sizes()
Time phase transition using different sample sizes.
void time_sample_sizes()
Time phase transition using different sample sizes.
bool mkpath(std::string path, int mode=0777)
Make path given.
std::string scientific_format(double d, int width=20, int prec=10)
Turns a double into a string written in scientific format.
std::string dirname(const std::string &path)
Get the directory name of the path.