This file contains data structure and subroutines implementing Markov Chain Monte Carlo sampler. More...

#include <cstddef>

Classes
struct	mcmc_opts

struct	mcmc_recs

Typedefs
typedef double(*	ObjectiveFunction_t) (double , double , int, int, void *)

Functions
void	_choldc (double *a, int n, double p)

int	_acor (double mean, double sigma, double tau, double X, int L)

void	mcmc_alloc (mcmc_recs *recs, int nstep, int nwalker, int ndim, int nvalue)

void	mcmc_free (mcmc_recs *recs)

void	mcmc_statistics (double mean, double sigma, double tau, mcmc_recs recs)

void	mcmc_save_fits (char const fname, mcmc_opts opts, mcmc_recs *recs, int include_last=false)

void	mcmc_load_fits (char const fname, mcmc_opts opts, mcmc_recs *recs, int alloc=true)

void	mcmc_append_recs (mcmc_recs dst, mcmc_recs src)

void	mcmc_report (mcmc_opts opts, mcmc_recs recs, char const *mode)

void	mcmc_init (ObjectiveFunction_t lnprob, double *par, mcmc_opts opts, mcmc_recs recs, void obj)

void	mcmc_advance (ObjectiveFunction_t lnprob, mcmc_opts opts, mcmc_recs recs, void *obj)

double	mcmc_stretch_move (double newp, double oldp, int iwalker, int nwalker, int ndim, mcmc_opts opts)

void	mcmc_walk_move (double newp, double oldp, int k, int nwalker, int np, mcmc_opts opts)

Detailed Description

This file contains data structure and subroutines implementing Markov Chain Monte Carlo sampler.

Author : Cheng Li, California Institute of Technology
Contact : cli@g.nosp@m.ps.c.nosp@m.altec.nosp@m.h.ed.nosp@m.u
Revision history :

June 21 2015, initial document
July 18 2016, remove MathHelper dependence

Definition in file mcmc.hpp.

Typedef Documentation

◆ ObjectiveFunction_t

typedef double(* ObjectiveFunction_t) (double *, double *, int, int, void *)

Definition at line 93 of file mcmc.hpp.

Function Documentation

◆ _choldc()

void _choldc	(	double **	a,
		int	n,
		double *	p
	)

Given a positive definite symmetric matrix a[0..n-1][0..n-1], this subroutine constructs its Cholesky decomposition: A = L*L'. On input, only the upper triangle of A need be given; it is not modified. The Cholesky factor L is returned in the lower triangle of A, except for its diagonal elements which are returned in p[0..n-1]. see Numerical Recipes in C, pg 97

Definition at line 27 of file mcmc.cpp.

◆ _acor()

int _acor	(	double *	mean,
		double *	sigma,
		double *	tau,
		double *	X,
		int	L
	)

calculate auto-correlation time given a time series Written by Jonathan Goodman, March 2009, goodm.nosp@m.an@c.nosp@m.ims.n.nosp@m.yu.e.nosp@m.du Modified by Cheng Li, June 2016, cli@g.nosp@m.ps.c.nosp@m.altec.nosp@m.h.ed.nosp@m.u

Definition at line 60 of file mcmc.cpp.

◆ mcmc_alloc()

void mcmc_alloc	(	mcmc_recs *	recs,
		int	nstep,
		int	nwalker,
		int	ndim,
		int	nvalue
	)

allocate memory for mcmc chains

Definition at line 126 of file mcmc.cpp.

◆ mcmc_free()

void mcmc_free ( mcmc_recs * recs )

free memory

Definition at line 151 of file mcmc.cpp.

◆ mcmc_statistics()

void mcmc_statistics	(	double *	mean,
		double *	sigma,
		double *	tau,
		mcmc_recs *	recs
	)

calculate autocorrelation time

Definition at line 160 of file mcmc.cpp.

◆ mcmc_save_fits()

void mcmc_save_fits	(	char const *	fname,
		mcmc_opts *	opts,
		mcmc_recs *	recs,
		int	include_last = `false`
	)

save mcmc chains to a FITS file

Definition at line 179 of file mcmc.cpp.

◆ mcmc_load_fits()

void mcmc_load_fits	(	char const *	fname,
		mcmc_opts *	opts,
		mcmc_recs *	recs,
		int	alloc = `true`
	)

load mcmc chains from a FITS file

Definition at line 379 of file mcmc.cpp.

◆ mcmc_append_recs()

void mcmc_append_recs	(	mcmc_recs *	dst,
		mcmc_recs *	src
	)

copy mcmc chains

Definition at line 459 of file mcmc.cpp.

◆ mcmc_report()

void mcmc_report	(	mcmc_opts *	opts,
		mcmc_recs *	recs,
		char const *	mode
	)

Definition at line 486 of file mcmc.cpp.

◆ mcmc_init()

void mcmc_init	(	ObjectiveFunction_t	lnprob,
		double **	par,
		mcmc_opts *	opts,
		mcmc_recs *	recs,
		void *	obj
	)

Definition at line 698 of file mcmc.cpp.

◆ mcmc_advance()

void mcmc_advance	(	ObjectiveFunction_t	lnprob,
		mcmc_opts *	opts,
		mcmc_recs *	recs,
		void *	obj
	)

implement Ensemble Samplers with Affine Invariance, Goodman and Weare (2010)

Parameters

lnprob	I, function calculating log probabiligy
par	I/O, parameter vector
val	I, measurement vector
np	I, size of input parameter vector
nv	I, size of measurement vector
nwalker	I, number of walkers
nstep	I, number of steps
opts	I, mcmc options
recs	O, mcmc chains

Definition at line 738 of file mcmc.cpp.

◆ mcmc_stretch_move()

double mcmc_stretch_move	(	double *	newp,
		double **	oldp,
		int	iwalker,
		int	nwalker,
		int	ndim,
		mcmc_opts *	opts
	)

Definition at line 784 of file mcmc.cpp.

◆ mcmc_walk_move()

void mcmc_walk_move	(	double *	newp,
		double **	oldp,
		int	k,
		int	nwalker,
		int	np,
		mcmc_opts *	opts
	)

Definition at line 827 of file mcmc.cpp.

Classes

Typedefs

Functions