guassian_process::gaussp_class Type Reference

Base class representing a gaussian process. More...

Public Member Functions
procedure	set_signal (this, signal, index)
	Set the object and coefficient for an index.
procedure	set_profile (this, a_model)
	Set the object and coefficient for an index.
procedure	get_evidence (this, a_model)
	Calculates the evidence.
FINAL	gaussp_destruct (this)
	Deconstruct a gaussp_class object.

Public Attributes
integer	flags = model_state_all_off
	Type descriptor of the gaussian procees type.
type(signal_pointer), dimension(:), pointer	signals => null()
	Array of signal_pointer.
real(rprec)	tolerance
	Gradient ascent convergence stop.
real(rprec), dimension(:,:), pointer	kls => null()
	Matrix of signal profile.
real(rprec), dimension(:,:), pointer	kll => null()
	Matrix of signal signal.
real(rprec), dimension(:,:), pointer	work => null()
	Work matrix for the cholesky factorization.
real(rprec)	cholesky_fac
	Positive factor to add to the diagonal entries of the matrix before factoring.
integer	profile_index = -1
	Profile index for sxrem profiles.
real(rprec), dimension(:), pointer	fpoints => null()
	Pointer to the profile af array.
type(param_recon_pointer), dimension(:), pointer	params => null()
	Array of hyper parameters.
integer	iou
	Log file input output unit.

Detailed Description

Base class representing a gaussian process.

Member Function/Subroutine Documentation

gaussp_destruct()

FINAL guassian_process::gaussp_class::gaussp_destruct ( type (gaussp_class), intent(inout)  this )

final

Deconstruct a gaussp_class object.

Deallocates memory and uninitializes a gaussp_class object.

Parameters

[in,out]

this

A gaussp_class instance.

Note

The destructors of the signals in the signal array are not called her because the gaussian process signals do not own the memory for those signals.

get_evidence()

procedure guassian_process::gaussp_class::get_evidence	(	class (gaussp_class), intent(inout)	this,
		class (model_class), pointer	a_model
	)

Calculates the evidence.

This method finds a gaussian process evidence. The matrices computed can be later used to set the profile.

Parameters

[in]	this	A gaussp_class instance.
[in,out]	a_model	A model instance.

Returns

The log evidence for the current hyper parameters.

set_profile()

procedure guassian_process::gaussp_class::set_profile	(	class (gaussp_class), intent(inout)	this,
		class (model_class), pointer	a_model
	)

Set the object and coefficient for an index.

This method uses a gaussian process to set a model using the signals pointed in the gaussp_class::signals array. Hyper parameters are determined by maximizing the evidence.

Parameters

[in]	this	A gaussp_class instance.
[in,out]	a_model	A model instance.

set_signal()

procedure guassian_process::gaussp_class::set_signal	(	class (gaussp_class), intent(inout)	this,
		class (signal_class), pointer	signal,
		integer, intent(in)	index
	)

Set the object and coefficient for an index.

Parameters

[in,out]	this	A gaussp_class instance.
[in]	signal	A signal_class instance.
[in]	a	A weight for the signal
[in]	index	The index to place the gaussp signal.

Note

Only signals that were created before this gaussian process can be added. Otherwise it will creat an infinitely recursive loop in gaussp_get_modeled_signal

Member Data Documentation

flags

integer guassian_process::gaussp_class::flags = model_state_all_off

Type descriptor of the gaussian procees type.

Possible values are:

• gaussp_no_type
• gaussp_sxrem_type
• gaussp_te_type
• gaussp_ne_type

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

• V3FIT/Sources/guassian_process.f