Fleet  0.0.9
Inference in the LOT
Typedefs | Functions | Variables
Main.cpp File Reference
#include <cmath>
#include "Numerics.h"
#include "Strings.h"
#include "MyGrammar.h"
#include "MyHypothesis.h"
#include "MyMCTS.h"
#include "StructureToSamples.h"
#include "PartitionMCMC.h"
#include "FleetArgs.h"
#include "Fleet.h"
Include dependency graph for Main.cpp:

Typedefs

using D = double
 
using X_t = std::array< D, MAX_VARS >
 

Functions

std::ostream & operator<< (std::ostream &o, X_t a)
 
int main (int argc, char **argv)
 

Variables

const double sdscale = 1.0
 
int polynomial_degree = -1
 
double end_at_likelihood = infinity
 
size_t BURN_N = 0
 
size_t nsamples = 100
 
size_t nstructs = 100
 
size_t head_data = 0
 
double FEYNMAN_SD = 0.1
 
double data_X_mean = NaN
 
double data_Y_mean = NaN
 
double data_X_sd = NaN
 
double data_Y_sd = NaN
 
double best_possible_ll = NaN
 
char sep = '\t'
 
const size_t MAX_VARS = 9
 
size_t NUM_VARS = 1
 
MyHypothesis::data_t mydata
 

Typedef Documentation

◆ D

using D = double

◆ X_t

using X_t = std::array<D,MAX_VARS>

Function Documentation

◆ main()

int main ( int  argc,
char **  argv 
)

◆ operator<<()

std::ostream& operator<< ( std::ostream &  o,
X_t  a 
)

Variable Documentation

◆ best_possible_ll

double best_possible_ll = NaN

◆ BURN_N

size_t BURN_N = 0

◆ data_X_mean

double data_X_mean = NaN

◆ data_X_sd

double data_X_sd = NaN

◆ data_Y_mean

double data_Y_mean = NaN

◆ data_Y_sd

double data_Y_sd = NaN

◆ end_at_likelihood

double end_at_likelihood = infinity

◆ FEYNMAN_SD

double FEYNMAN_SD = 0.1

◆ head_data

size_t head_data = 0

◆ MAX_VARS

const size_t MAX_VARS = 9

◆ mydata

◆ nsamples

size_t nsamples = 100

◆ nstructs

size_t nstructs = 100

◆ NUM_VARS

size_t NUM_VARS = 1

◆ polynomial_degree

int polynomial_degree = -1

◆ sdscale

const double sdscale = 1.0

◆ sep

char sep = '\t'