SHOGUN  6.1.3
List of all members | Public Types | Public Member Functions | Static Public Member Functions | Public Attributes | Protected Member Functions | Protected Attributes
CGaussianDistribution Class Reference

Detailed Description

Dense version of the well-known Gaussian probability distribution, defined as

\[ \mathcal{N}_x(\mu,\Sigma)= \frac{1}{\sqrt{|2\pi\Sigma|}} \exp\left(-\frac{1}{2}(x-\mu)^T\Sigma^{-1}(x-\mu)\right) \]

.

The implementation represents the covariance matrix \(\Sigma \), as Cholesky factorisation, such that the covariance can be computed as \(\Sigma=LL^T\).

Definition at line 60 of file GaussianDistribution.h.

Inheritance diagram for CGaussianDistribution:
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Public Types

typedef rxcpp::subjects::subject< ObservedValueSGSubject
 
typedef rxcpp::observable< ObservedValue, rxcpp::dynamic_observable< ObservedValue > > SGObservable
 
typedef rxcpp::subscriber< ObservedValue, rxcpp::observer< ObservedValue, void, void, void, void > > SGSubscriber
 

Public Member Functions

 CGaussianDistribution ()
 
 CGaussianDistribution (SGVector< float64_t > mean, SGMatrix< float64_t > cov, bool cov_is_factor=false)
 
virtual ~CGaussianDistribution ()
 
virtual SGMatrix< float64_tsample (int32_t num_samples, SGMatrix< float64_t > pre_samples=SGMatrix< float64_t >()) const
 
virtual SGVector< float64_tlog_pdf_multiple (SGMatrix< float64_t > samples) const
 
virtual const char * get_name () const
 
virtual SGVector< float64_tsample () const
 
virtual float64_t log_pdf (SGVector< float64_t > sample_vec) const
 
int32_t ref ()
 
int32_t ref_count ()
 
int32_t unref ()
 
virtual CSGObjectshallow_copy () const
 
virtual CSGObjectdeep_copy () const
 
virtual bool is_generic (EPrimitiveType *generic) const
 
template<class T >
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
template<>
void set_generic ()
 
void unset_generic ()
 
virtual void print_serializable (const char *prefix="")
 
virtual bool save_serializable (CSerializableFile *file, const char *prefix="")
 
virtual bool load_serializable (CSerializableFile *file, const char *prefix="")
 
void set_global_io (SGIO *io)
 
SGIOget_global_io ()
 
void set_global_parallel (Parallel *parallel)
 
Parallelget_global_parallel ()
 
void set_global_version (Version *version)
 
Versionget_global_version ()
 
SGStringList< char > get_modelsel_names ()
 
void print_modsel_params ()
 
char * get_modsel_param_descr (const char *param_name)
 
index_t get_modsel_param_index (const char *param_name)
 
void build_gradient_parameter_dictionary (CMap< TParameter *, CSGObject *> *dict)
 
bool has (const std::string &name) const
 
template<typename T >
bool has (const Tag< T > &tag) const
 
template<typename T , typename U = void>
bool has (const std::string &name) const
 
template<typename T >
void set (const Tag< T > &_tag, const T &value)
 
template<typename T , typename U = void>
void set (const std::string &name, const T &value)
 
template<typename T >
get (const Tag< T > &_tag) const
 
template<typename T , typename U = void>
get (const std::string &name) const
 
SGObservableget_parameters_observable ()
 
void subscribe_to_parameters (ParameterObserverInterface *obs)
 
void list_observable_parameters ()
 
virtual void update_parameter_hash ()
 
virtual bool parameter_hash_changed ()
 
virtual bool equals (CSGObject *other, float64_t accuracy=0.0, bool tolerant=false)
 
virtual CSGObjectclone ()
 

Static Public Member Functions

static float64_t univariate_log_pdf (float64_t sample, float64_t mu=0.0, float64_t sigma2=1.0)
 

Public Attributes

SGIOio
 
Parallelparallel
 
Versionversion
 
Parameterm_parameters
 
Parameterm_model_selection_parameters
 
Parameterm_gradient_parameters
 
uint32_t m_hash
 

Protected Member Functions

virtual void load_serializable_pre () throw (ShogunException)
 
virtual void load_serializable_post () throw (ShogunException)
 
virtual void save_serializable_pre () throw (ShogunException)
 
virtual void save_serializable_post () throw (ShogunException)
 
template<typename T >
void register_param (Tag< T > &_tag, const T &value)
 
template<typename T >
void register_param (const std::string &name, const T &value)
 
bool clone_parameters (CSGObject *other)
 
void observe (const ObservedValue value)
 
void register_observable_param (const std::string &name, const SG_OBS_VALUE_TYPE type, const std::string &description)
 

Protected Attributes

SGVector< float64_tm_mean
 
SGMatrix< float64_tm_L
 
int32_t m_dimension
 

Member Typedef Documentation

◆ SGObservable

Definition at line 130 of file SGObject.h.

◆ SGSubject

Definition at line 127 of file SGObject.h.

◆ SGSubscriber

typedef rxcpp::subscriber< ObservedValue, rxcpp::observer<ObservedValue, void, void, void, void> > SGSubscriber
inherited

Definition at line 133 of file SGObject.h.

Constructor & Destructor Documentation

◆ CGaussianDistribution() [1/2]

Default constructor

Definition at line 19 of file GaussianDistribution.cpp.

◆ CGaussianDistribution() [2/2]

CGaussianDistribution ( SGVector< float64_t mean,
SGMatrix< float64_t cov,
bool  cov_is_factor = false 
)

Constructor for which takes Gaussian mean and its covariance matrix. It is also possible to pass a precomputed matrix factor of the specified form. In this case, the factorization is not explicitly computed.

Parameters
meanmean of the Gaussian
covcovariance of the Gaussian, or covariance factor
cov_is_factorwhether cov is a factor of the covariance or not (default is false). If false, the factorization is explicitly computed

Definition at line 24 of file GaussianDistribution.cpp.

◆ ~CGaussianDistribution()

~CGaussianDistribution ( )
virtual

Destructor

Definition at line 64 of file GaussianDistribution.cpp.

Member Function Documentation

◆ build_gradient_parameter_dictionary()

void build_gradient_parameter_dictionary ( CMap< TParameter *, CSGObject *> *  dict)
inherited

Builds a dictionary of all parameters in SGObject as well of those of SGObjects that are parameters of this object. Dictionary maps parameters to the objects that own them.

Parameters
dictdictionary of parameters to be built.

Definition at line 635 of file SGObject.cpp.

◆ clone()

CSGObject * clone ( )
virtualinherited

Creates a clone of the current object. This is done via recursively traversing all parameters, which corresponds to a deep copy. Calling equals on the cloned object always returns true although none of the memory of both objects overlaps.

Returns
an identical copy of the given object, which is disjoint in memory. NULL if the clone fails. Note that the returned object is SG_REF'ed

Reimplemented in CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool >, CDynamicObjectArray, CAlphabet, and CMKL.

Definition at line 734 of file SGObject.cpp.

◆ clone_parameters()

bool clone_parameters ( CSGObject other)
protectedinherited

Definition at line 759 of file SGObject.cpp.

◆ deep_copy()

CSGObject * deep_copy ( ) const
virtualinherited

A deep copy. All the instance variables will also be copied.

Definition at line 232 of file SGObject.cpp.

◆ equals()

bool equals ( CSGObject other,
float64_t  accuracy = 0.0,
bool  tolerant = false 
)
virtualinherited

Recursively compares the current SGObject to another one. Compares all registered numerical parameters, recursion upon complex (SGObject) parameters. Does not compare pointers!

May be overwritten but please do with care! Should not be necessary in most cases.

Parameters
otherobject to compare with
accuracyaccuracy to use for comparison (optional)
tolerantallows linient check on float equality (within accuracy)
Returns
true if all parameters were equal, false if not

Definition at line 656 of file SGObject.cpp.

◆ get() [1/2]

T get ( const Tag< T > &  _tag) const
inherited

Getter for a class parameter, identified by a Tag. Throws an exception if the class does not have such a parameter.

Parameters
_tagname and type information of parameter
Returns
value of the parameter identified by the input tag

Definition at line 381 of file SGObject.h.

◆ get() [2/2]

T get ( const std::string &  name) const
inherited

Getter for a class parameter, identified by a name. Throws an exception if the class does not have such a parameter.

Parameters
namename of the parameter
Returns
value of the parameter corresponding to the input name and type

Definition at line 404 of file SGObject.h.

◆ get_global_io()

SGIO * get_global_io ( )
inherited

get the io object

Returns
io object

Definition at line 269 of file SGObject.cpp.

◆ get_global_parallel()

Parallel * get_global_parallel ( )
inherited

get the parallel object

Returns
parallel object

Definition at line 311 of file SGObject.cpp.

◆ get_global_version()

Version * get_global_version ( )
inherited

get the version object

Returns
version object

Definition at line 324 of file SGObject.cpp.

◆ get_modelsel_names()

SGStringList< char > get_modelsel_names ( )
inherited
Returns
vector of names of all parameters which are registered for model selection

Definition at line 536 of file SGObject.cpp.

◆ get_modsel_param_descr()

char * get_modsel_param_descr ( const char *  param_name)
inherited

Returns description of a given parameter string, if it exists. SG_ERROR otherwise

Parameters
param_namename of the parameter
Returns
description of the parameter

Definition at line 560 of file SGObject.cpp.

◆ get_modsel_param_index()

index_t get_modsel_param_index ( const char *  param_name)
inherited

Returns index of model selection parameter with provided index

Parameters
param_namename of model selection parameter
Returns
index of model selection parameter with provided name, -1 if there is no such

Definition at line 573 of file SGObject.cpp.

◆ get_name()

virtual const char* get_name ( ) const
virtual
Returns
name of the SGSerializable

Implements CProbabilityDistribution.

Definition at line 111 of file GaussianDistribution.h.

◆ get_parameters_observable()

SGObservable* get_parameters_observable ( )
inherited

Get parameters observable

Returns
RxCpp observable

Definition at line 415 of file SGObject.h.

◆ has() [1/3]

bool has ( const std::string &  name) const
inherited

Checks if object has a class parameter identified by a name.

Parameters
namename of the parameter
Returns
true if the parameter exists with the input name

Definition at line 304 of file SGObject.h.

◆ has() [2/3]

bool has ( const Tag< T > &  tag) const
inherited

Checks if object has a class parameter identified by a Tag.

Parameters
tagtag of the parameter containing name and type information
Returns
true if the parameter exists with the input tag

Definition at line 315 of file SGObject.h.

◆ has() [3/3]

bool has ( const std::string &  name) const
inherited

Checks if a type exists for a class parameter identified by a name.

Parameters
namename of the parameter
Returns
true if the parameter exists with the input name and type

Definition at line 326 of file SGObject.h.

◆ is_generic()

bool is_generic ( EPrimitiveType *  generic) const
virtualinherited

If the SGSerializable is a class template then TRUE will be returned and GENERIC is set to the type of the generic.

Parameters
genericset to the type of the generic if returning TRUE
Returns
TRUE if a class template.

Definition at line 330 of file SGObject.cpp.

◆ list_observable_parameters()

void list_observable_parameters ( )
inherited

Print to stdout a list of observable parameters

Definition at line 878 of file SGObject.cpp.

◆ load_serializable()

bool load_serializable ( CSerializableFile file,
const char *  prefix = "" 
)
virtualinherited

Load this object from file. If it will fail (returning FALSE) then this object will contain inconsistent data and should not be used!

Parameters
filewhere to load from
prefixprefix for members
Returns
TRUE if done, otherwise FALSE

Definition at line 403 of file SGObject.cpp.

◆ load_serializable_post()

void load_serializable_post ( )
throw (ShogunException
)
protectedvirtualinherited

Can (optionally) be overridden to post-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::LOAD_SERIALIZABLE_POST is called.

Exceptions
ShogunExceptionwill be thrown if an error occurs.

Reimplemented in CKernel, CWeightedDegreePositionStringKernel, CList, CAlphabet, CLinearHMM, CGaussianKernel, CInverseMultiQuadricKernel, CCircularKernel, and CExponentialKernel.

Definition at line 460 of file SGObject.cpp.

◆ load_serializable_pre()

void load_serializable_pre ( )
throw (ShogunException
)
protectedvirtualinherited

Can (optionally) be overridden to pre-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::LOAD_SERIALIZABLE_PRE is called.

Exceptions
ShogunExceptionwill be thrown if an error occurs.

Reimplemented in CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool >, and CDynamicObjectArray.

Definition at line 455 of file SGObject.cpp.

◆ log_pdf()

float64_t log_pdf ( SGVector< float64_t sample_vec) const
virtualinherited

Computes the log-pdf for a single provided sample. Wrapper method which calls log_pdf_multiple

Parameters
sample_vecsample_vec to compute log-pdf for
Returns
log-pdf of the given sample

Definition at line 61 of file ProbabilityDistribution.cpp.

◆ log_pdf_multiple()

SGVector< float64_t > log_pdf_multiple ( SGMatrix< float64_t samples) const
virtual

Computes the log-pdf for all provided samples. That is

\[ \log(\mathcal{N}_x(\mu,\Sigma))= - \frac{d}{2} \log(2\pi) -\frac{1}{2}\log(\det(\Sigma)) -\frac{1}{2}(x-\mu)^T\Sigma^{-1}(x-\mu), \]

where \(d\) is the dimension of the Gaussian. The method to compute the log-determinant is based on the factorization of the covariance matrix.

Parameters
samplessamples to compute log-pdf of (column vectors)
Returns
vector with log-pdfs of given samples

Reimplemented from CProbabilityDistribution.

Definition at line 110 of file GaussianDistribution.cpp.

◆ observe()

void observe ( const ObservedValue  value)
protectedinherited

Observe a parameter value and emit them to observer.

Parameters
valueObserved parameter's value

Definition at line 828 of file SGObject.cpp.

◆ parameter_hash_changed()

bool parameter_hash_changed ( )
virtualinherited
Returns
whether parameter combination has changed since last update

Definition at line 296 of file SGObject.cpp.

◆ print_modsel_params()

void print_modsel_params ( )
inherited

prints all parameter registered for model selection and their type

Definition at line 512 of file SGObject.cpp.

◆ print_serializable()

void print_serializable ( const char *  prefix = "")
virtualinherited

prints registered parameters out

Parameters
prefixprefix for members

Definition at line 342 of file SGObject.cpp.

◆ ref()

int32_t ref ( )
inherited

increase reference counter

Returns
reference count

Definition at line 186 of file SGObject.cpp.

◆ ref_count()

int32_t ref_count ( )
inherited

display reference counter

Returns
reference count

Definition at line 193 of file SGObject.cpp.

◆ register_observable_param()

void register_observable_param ( const std::string &  name,
const SG_OBS_VALUE_TYPE  type,
const std::string &  description 
)
protectedinherited

Register which params this object can emit.

Parameters
namethe param name
typethe param type
descriptiona user oriented description

Definition at line 871 of file SGObject.cpp.

◆ register_param() [1/2]

void register_param ( Tag< T > &  _tag,
const T &  value 
)
protectedinherited

Registers a class parameter which is identified by a tag. This enables the parameter to be modified by set() and retrieved by get(). Parameters can be registered in the constructor of the class.

Parameters
_tagname and type information of parameter
valuevalue of the parameter

Definition at line 472 of file SGObject.h.

◆ register_param() [2/2]

void register_param ( const std::string &  name,
const T &  value 
)
protectedinherited

Registers a class parameter which is identified by a name. This enables the parameter to be modified by set() and retrieved by get(). Parameters can be registered in the constructor of the class.

Parameters
namename of the parameter
valuevalue of the parameter along with type information

Definition at line 485 of file SGObject.h.

◆ sample() [1/2]

SGVector< float64_t > sample ( ) const
virtualinherited

Samples from the distribution once. Wrapper method. No pre-sample passing is possible with this method.

Returns
vector with single sample

Definition at line 46 of file ProbabilityDistribution.cpp.

◆ sample() [2/2]

SGMatrix< float64_t > sample ( int32_t  num_samples,
SGMatrix< float64_t pre_samples = SGMatrix<float64_t>() 
) const
virtual

Samples from the distribution multiple times

Parameters
num_samplesnumber of samples to generate
pre_samplesa matrix of standard normal samples that might be used for sampling the Gaussian. Ignored by default. If passed, the pre-samples will be modified.
Returns
matrix with samples (column vectors)

Reimplemented from CProbabilityDistribution.

Definition at line 69 of file GaussianDistribution.cpp.

◆ save_serializable()

bool save_serializable ( CSerializableFile file,
const char *  prefix = "" 
)
virtualinherited

Save this object to file.

Parameters
filewhere to save the object; will be closed during returning if PREFIX is an empty string.
prefixprefix for members
Returns
TRUE if done, otherwise FALSE

Definition at line 348 of file SGObject.cpp.

◆ save_serializable_post()

void save_serializable_post ( )
throw (ShogunException
)
protectedvirtualinherited

Can (optionally) be overridden to post-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::SAVE_SERIALIZABLE_POST is called.

Exceptions
ShogunExceptionwill be thrown if an error occurs.

Reimplemented in CKernel.

Definition at line 470 of file SGObject.cpp.

◆ save_serializable_pre()

void save_serializable_pre ( )
throw (ShogunException
)
protectedvirtualinherited

Can (optionally) be overridden to pre-initialize some member variables which are not PARAMETER::ADD'ed. Make sure that at first the overridden method BASE_CLASS::SAVE_SERIALIZABLE_PRE is called.

Exceptions
ShogunExceptionwill be thrown if an error occurs.

Reimplemented in CKernel, CDynamicArray< T >, CDynamicArray< float64_t >, CDynamicArray< float32_t >, CDynamicArray< int32_t >, CDynamicArray< char >, CDynamicArray< bool >, and CDynamicObjectArray.

Definition at line 465 of file SGObject.cpp.

◆ set() [1/2]

void set ( const Tag< T > &  _tag,
const T &  value 
)
inherited

Setter for a class parameter, identified by a Tag. Throws an exception if the class does not have such a parameter.

Parameters
_tagname and type information of parameter
valuevalue of the parameter

Definition at line 342 of file SGObject.h.

◆ set() [2/2]

void set ( const std::string &  name,
const T &  value 
)
inherited

Setter for a class parameter, identified by a name. Throws an exception if the class does not have such a parameter.

Parameters
namename of the parameter
valuevalue of the parameter along with type information

Definition at line 368 of file SGObject.h.

◆ set_generic() [1/16]

void set_generic ( )
inherited

Definition at line 73 of file SGObject.cpp.

◆ set_generic() [2/16]

void set_generic ( )
inherited

Definition at line 78 of file SGObject.cpp.

◆ set_generic() [3/16]

void set_generic ( )
inherited

Definition at line 83 of file SGObject.cpp.

◆ set_generic() [4/16]

void set_generic ( )
inherited

Definition at line 88 of file SGObject.cpp.

◆ set_generic() [5/16]

void set_generic ( )
inherited

Definition at line 93 of file SGObject.cpp.

◆ set_generic() [6/16]

void set_generic ( )
inherited

Definition at line 98 of file SGObject.cpp.

◆ set_generic() [7/16]

void set_generic ( )
inherited

Definition at line 103 of file SGObject.cpp.

◆ set_generic() [8/16]

void set_generic ( )
inherited

Definition at line 108 of file SGObject.cpp.

◆ set_generic() [9/16]

void set_generic ( )
inherited

Definition at line 113 of file SGObject.cpp.

◆ set_generic() [10/16]

void set_generic ( )
inherited

Definition at line 118 of file SGObject.cpp.

◆ set_generic() [11/16]

void set_generic ( )
inherited

Definition at line 123 of file SGObject.cpp.

◆ set_generic() [12/16]

void set_generic ( )
inherited

Definition at line 128 of file SGObject.cpp.

◆ set_generic() [13/16]

void set_generic ( )
inherited

Definition at line 133 of file SGObject.cpp.

◆ set_generic() [14/16]

void set_generic ( )
inherited

Definition at line 138 of file SGObject.cpp.

◆ set_generic() [15/16]

void set_generic ( )
inherited

Definition at line 143 of file SGObject.cpp.

◆ set_generic() [16/16]

void set_generic ( )
inherited

set generic type to T

◆ set_global_io()

void set_global_io ( SGIO io)
inherited

set the io object

Parameters
ioio object to use

Definition at line 262 of file SGObject.cpp.

◆ set_global_parallel()

void set_global_parallel ( Parallel parallel)
inherited

set the parallel object

Parameters
parallelparallel object to use

Definition at line 275 of file SGObject.cpp.

◆ set_global_version()

void set_global_version ( Version version)
inherited

set the version object

Parameters
versionversion object to use

Definition at line 317 of file SGObject.cpp.

◆ shallow_copy()

CSGObject * shallow_copy ( ) const
virtualinherited

A shallow copy. All the SGObject instance variables will be simply assigned and SG_REF-ed.

Reimplemented in CGaussianKernel.

Definition at line 226 of file SGObject.cpp.

◆ subscribe_to_parameters()

void subscribe_to_parameters ( ParameterObserverInterface obs)
inherited

Subscribe a parameter observer to watch over params

Definition at line 811 of file SGObject.cpp.

◆ univariate_log_pdf()

static float64_t univariate_log_pdf ( float64_t  sample,
float64_t  mu = 0.0,
float64_t  sigma2 = 1.0 
)
static

Computes the univariate pdf for one given sample.

Parameters
sampleis a given sample
muis the mean of univariate Normal distribution (default value is 0.0)
sigma2is the variance of univariate Normal distribution (default value is 1.0)
Returns
the pdf of the distribution given the sample

Definition at line 124 of file GaussianDistribution.h.

◆ unref()

int32_t unref ( )
inherited

decrement reference counter and deallocate object if refcount is zero before or after decrementing it

Returns
reference count

Definition at line 200 of file SGObject.cpp.

◆ unset_generic()

void unset_generic ( )
inherited

unset generic type

this has to be called in classes specializing a template class

Definition at line 337 of file SGObject.cpp.

◆ update_parameter_hash()

void update_parameter_hash ( )
virtualinherited

Updates the hash of current parameter combination

Definition at line 282 of file SGObject.cpp.

Member Data Documentation

◆ io

SGIO* io
inherited

io

Definition at line 600 of file SGObject.h.

◆ m_dimension

int32_t m_dimension
protectedinherited

Dimension of the distribution

Definition at line 82 of file ProbabilityDistribution.h.

◆ m_gradient_parameters

Parameter* m_gradient_parameters
inherited

parameters wrt which we can compute gradients

Definition at line 615 of file SGObject.h.

◆ m_hash

uint32_t m_hash
inherited

Hash of parameter values

Definition at line 618 of file SGObject.h.

◆ m_L

SGMatrix<float64_t> m_L
protected

Lower factor of covariance matrix (depends on factorization type). Covariance (approximation) is given by \(\Sigma=LL^T\)

Definition at line 141 of file GaussianDistribution.h.

◆ m_mean

SGVector<float64_t> m_mean
protected

Mean

Definition at line 137 of file GaussianDistribution.h.

◆ m_model_selection_parameters

Parameter* m_model_selection_parameters
inherited

model selection parameters

Definition at line 612 of file SGObject.h.

◆ m_parameters

Parameter* m_parameters
inherited

parameters

Definition at line 609 of file SGObject.h.

◆ parallel

Parallel* parallel
inherited

parallel

Definition at line 603 of file SGObject.h.

◆ version

Version* version
inherited

version

Definition at line 606 of file SGObject.h.


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

SHOGUN Machine Learning Toolbox - Documentation