Detailed Description

This class provides methods to perform bayesian interpolation/smoothing of data using a gaussian process prior on the function to be interpolated. It takes a dataset as input (via its sufficient statistics) along with prior mean and covariance functions. It outputs the value of the posterior mean and covariance functions at points requested by the user.

Definition at line 32 of file GaussianProcessInterpolation.h.

Public Member Functions
	GaussianProcessInterpolation (FloatsList x, Floats sample_mean, Floats sample_std, unsigned n_obs, UnivariateFunction mean_function, BivariateFunction covariance_function, kernel::Particle *sigma, double sparse_cutoff=1e-7)

void	force_covariance_update ()

void	force_mean_update ()

FloatsList	get_data_abscissa () const

Floats	get_data_mean () const

FloatsList	get_data_variance () const

ContainersTemp	get_input_containers () const

kernel::ParticlesTemp	get_input_particles () const

bool	get_m_particle_is_optimized (unsigned i) const

unsigned	get_number_of_m_particles () const

unsigned	get_number_of_Omega_particles () const

bool	get_Omega_particle_is_optimized (unsigned i) const

double	get_posterior_covariance (Floats x1, Floats x2) const

IMP_Eigen::VectorXd	get_posterior_covariance_derivative (Floats x) const

Floats	get_posterior_covariance_derivative (Floats x, bool) const

IMP_Eigen::MatrixXd	get_posterior_covariance_hessian (Floats x) const

FloatsList	get_posterior_covariance_hessian (Floats x, bool) const

IMP_Eigen::MatrixXd	get_posterior_covariance_matrix (FloatsList x) const

FloatsList	get_posterior_covariance_matrix (FloatsList x, bool) const

double	get_posterior_mean (Floats x) const

virtual std::string	get_type_name () const

virtual ::IMP::base::VersionInfo	get_version_info () const
	Get information about the module and version of the object. More...

Public Member Functions inherited from IMP::base::Object
virtual void	clear_caches ()

CheckLevel	get_check_level () const

LogLevel	get_log_level () const

void	set_check_level (CheckLevel l)

void	set_log_level (LogLevel l)
	Set the logging level used in this object. More...

void	set_was_used (bool tf) const

void	show (std::ostream &out=std::cout) const

const std::string &	get_name () const

void	set_name (std::string name)

Protected Member Functions
void	add_to_m_particle_derivative (unsigned particle, double value, DerivativeAccumulator &accum)

void	add_to_Omega_particle_derivative (unsigned particle, double value, DerivativeAccumulator &accum)

IMP_Eigen::VectorXd	get_I () const

IMP_Eigen::LDLT < IMP_Eigen::MatrixXd, IMP_Eigen::Upper >	get_ldlt () const

IMP_Eigen::VectorXd	get_m () const

IMP_Eigen::VectorXd	get_m_derivative (unsigned particle) const

IMP_Eigen::VectorXd	get_m_second_derivative (unsigned particle1, unsigned particle2) const

IMP_Eigen::MatrixXd	get_Omega () const

IMP_Eigen::MatrixXd	get_Omega_derivative (unsigned particle) const

IMP_Eigen::MatrixXd	get_Omega_second_derivative (unsigned particle1, unsigned particle2) const

IMP_Eigen::MatrixXd	get_Omi () const

IMP_Eigen::VectorXd	get_OmiIm () const

IMP_Eigen::DiagonalMatrix < double, IMP_Eigen::Dynamic >	get_S () const

IMP_Eigen::MatrixXd	get_W () const

IMP_Eigen::VectorXd	get_wx_vector (Floats xval) const

Protected Member Functions inherited from IMP::base::Object
	Object (std::string name)
	Construct an object with the given name. More...

virtual void	do_destroy ()

Constructor & Destructor Documentation

IMP::isd::GaussianProcessInterpolation::GaussianProcessInterpolation	(	FloatsList	x,
		Floats	sample_mean,
		Floats	sample_std,
		unsigned	n_obs,
		UnivariateFunction *	mean_function,
		BivariateFunction *	covariance_function,
		kernel::Particle *	sigma,
		double	sparse_cutoff = `1e-7`
	)

Constructor for the gaussian process

Parameters

[in]	x	: a list of coordinates in N-dimensional space corresponding to the abscissa of each observation
[in]	sample_mean	\(I\) : vector of mean observations at each of the previously defined coordinates
[in]	sample_std	\(s\) : vector of sample standard deviations
[in]	n_obs	\(N\) : sample size for mean and std
[in]	mean_function	\(m\) : a pointer to the prior mean function to use. Should be compatible with the size of x(i).
[in]	covariance_function	\(w\): prior covariance function.
[in]	sigma	: ISD Scale (proportionality factor to S)
[in]	sparse_cutoff	: when to consider that a matrix entry is zero

Computes the necessary matrices and inverses when called.

Member Function Documentation

double IMP::isd::GaussianProcessInterpolation::get_posterior_mean ( Floats x ) const

Get posterior mean and covariance functions, at the points requested Posterior mean is defined as

\[\hat{I}(x) = m(x) + {}^t\mathbf{w}(q) (\mathbf{W}+\mathbf{S})^{-1} (\mathbf{I}-\mathbf{m}) \]

Posterior covariance

\[\hat{\sigma}^2(x,x') = w(x,x') - {}^t\mathbf{w}(x) (\mathbf{W} + \mathbf{S})^{-1} \mathbf{w}(x') \]

where \(\mathbf{m}\) is the vector built by evaluating the prior mean function at the observation points; \(\mathbf{w}(x)\) is the vector of covariances between each observation point and the current point; \(\mathbf{W}\) is the prior covariance matrix built by evaluating the covariance function at each of the observations; \(\mathbf{S}\) is the diagonal covariance matrix built from sample_std and n_obs.

Both functions will check if the mean or covariance functions have changed since the last call, and will recompute \((\mathbf{W} + \mathbf{S})^{-1}\) if necessary.

virtual ::IMP::base::VersionInfo IMP::isd::GaussianProcessInterpolation::get_version_info ( ) const

virtual

Get information about the module and version of the object.

Reimplemented from IMP::base::Object.

Definition at line 146 of file GaussianProcessInterpolation.h.

The documentation for this class was generated from the following file:

GaussianProcessInterpolation.h

Detailed Description

Public Member Functions

Protected Member Functions

Constructor & Destructor Documentation

Member Function Documentation