Class GWRMultiscale

Inheritance Relationships

Base Types

Class Documentation

class GWRMultiscale : public gwm::SpatialMultiscaleAlgorithm, public gwm::IBandwidthSelectable, public gwm::IRegressionAnalysis, public gwm::IParallelizable, public gwm::IParallelOpenmpEnabled, public gwm::IParallelCudaEnabled, public gwm::IParallelMpiEnabled

Multiscale GWR Algorithm.

Public Types

enum BandwidthInitilizeType

Type of bandwidth initilization.

Values:

enumerator Null
enumerator Initial
enumerator Specified
enum BandwidthSelectionCriterionType

Type of criterion for bandwidth selection.

Values:

enumerator CV
enumerator AIC
enum BackFittingCriterionType

Type of criterion for backfitting convergence.

Values:

enumerator CVR
enumerator dCVR
typedef double (GWRMultiscale::* BandwidthSizeCriterionFunction)(BandwidthWeight*)

Function to calculate the criterion for given bandwidth size.

typedef arma::vec (GWRMultiscale::* FitVarFunction)(const size_t)

Function to fit a model for the given variable.

typedef arma::vec (GWRMultiscale::* FitVarCoreFunction)(const arma::vec&, const arma::vec&, const SpatialWeight&, arma::mat&)

Function to fit a model for the given variable.

typedef arma::vec (GWRMultiscale::* FitVarCoreCVFunction)(const arma::vec&, const arma::vec&, const SpatialWeight&)

Function to fit a model for the given variable.

typedef arma::vec (GWRMultiscale::* FitVarCoreSHatFunction)(const arma::vec&, const arma::vec&, const SpatialWeight&, arma::vec&)

Function to fit a model for the given variable.

Public Functions

inline GWRMultiscale()

Construct a new GWRMultiscale object.

inline GWRMultiscale(const arma::mat &x, const arma::vec &y, const arma::mat &coords, const std::vector<SpatialWeight> &spatialWeights)

Construct a new GWRMultiscale object.

Parameters:

  • x – Independent variables.

  • y – Dependent variable.

  • coords – Coordinate matrix.

  • spatialWeights – Spatial weighting configuration.

inline virtual ~GWRMultiscale()

Destroy the GWRMultiscale object.

inline void setGoldenUpperBounds(double value)

Set the upper bounds of golden selection.

inline void setGoldenLowerBounds(double value)

Set the lower bounds of golden selection.

inline const std::vector<BandwidthInitilizeType> &bandwidthInitilize() const

Get the type of bandwidth initilization.

Returns:

std::vector<BandwidthInitilizeType> The type of bandwidth initilization

void setBandwidthInitilize(const std::vector<BandwidthInitilizeType> &bandwidthInitilize)

Set the bandwidth initilization type.

Parameters:

bandwidthInitilize – The type of bandwidth initilization

inline const std::vector<BandwidthSelectionCriterionType> &bandwidthSelectionApproach() const

Get the bandwidth selection approach.

Returns:

std::vector<BandwidthSelectionCriterionType> Bandwidth selection approach.

void setBandwidthSelectionApproach(const std::vector<BandwidthSelectionCriterionType> &bandwidthSelectionApproach)

Set the bandwidth selection approach.

Parameters:

bandwidthSelectionApproach – Bandwidth selection approach.

inline const std::vector<bool> &preditorCentered() const

Get whether preditors are centered.

Returns:

std::vector<bool> Whether preditors are centered.

inline void setPreditorCentered(const std::vector<bool> &preditorCentered)

Set the Preditor Centered object.

Parameters:

preditorCentered – Whether preditors are centered.

inline const std::vector<double> &bandwidthSelectThreshold() const

Get the threshold of bandwidth selection.

Returns:

std::vector<double> Threshold of bandwidth selection.

inline void setBandwidthSelectThreshold(const std::vector<double> &bandwidthSelectThreshold)

Set the threshold of bandwidth selection.

Parameters:

bandwidthSelectThreshold – Threshold of bandwidth selection.

inline bool hasHatMatrix() const

Get whether has hat matrix \(S\).

Returns:

true Has hat matrix.

Returns:

false Doesn’t have.

inline void setHasHatMatrix(bool hasHatMatrix)

Set whether has hat matrix \(S\).

Parameters:

hasHatMatrix – Whether has hat matrix \(S\).

inline size_t bandwidthSelectRetryTimes() const

Get maximum retry times when select bandwidths.

Returns:

size_t The maximum retry times when select bandwidths.

inline void setBandwidthSelectRetryTimes(size_t bandwidthSelectRetryTimes)

Set maximum retry times when select bandwidths.

Parameters:

bandwidthSelectRetryTimes – The maximum retry times when select bandwidths.

inline size_t maxIteration() const

Get maximum iteration times.

Returns:

size_t The maximum iteration times.

inline void setMaxIteration(size_t maxIteration)

Set maximum iteration times.

Parameters:

maxIteration – The maximum iteration times.

inline BackFittingCriterionType criterionType() const

Get type of backfitting convergence criterion.

Returns:

BackFittingCriterionType The type of backfitting convergence criterion.

inline void setCriterionType(const BackFittingCriterionType &criterionType)

Set type of backfitting convergence criterion.

Parameters:

criterionType – The type of backfitting convergence criterion.

inline double criterionThreshold() const

Get threshold of criterion.

Returns:

double The threshold of criterion.

inline void setCriterionThreshold(double criterionThreshold)

Set threshold of criterion.

Parameters:

criterionThreshold – The threshold of criterion.

inline int adaptiveLower() const

Get lower bound for optimizing adaptive bandwidth.

Returns:

int The lower bound for optimizing adaptive bandwidth.

inline void setAdaptiveLower(int adaptiveLower)

Set lower bound for optimizing adaptive bandwidth.

Parameters:

adaptiveLower – The lower bound for optimizing adaptive bandwidth.

inline const arma::mat &betas() const

Get coefficient estimates \(\beta\).

Returns:

arma::mat Coefficient estimates \(\beta\).

BandwidthSizeCriterionFunction bandwidthSizeCriterionVar(BandwidthSelectionCriterionType type)

Get criterion calculator function for optimize bandwidth size for one variable.

Parameters:

type – The criterion type for optimize bandwidth size for one variable.

Returns:

BandwidthSizeCriterionFunction The criterion calculator for optimize bandwidth size for one variable.

virtual bool isValid() override

Check whether the algorithm’s configuration is valid.

Returns:

true if the algorithm’s configuration is valid.

Returns:

false if the algorithm’s configuration is invalid.

virtual void setSpatialWeights(const std::vector<SpatialWeight> &spatialWeights) override

Set the spatial weight configuration.

Use gwmodel_set_gwr_spatial_weight() to set this property to GWRBasic in shared build.

Use gwmodel_set_gwss_spatial_weight() to set this property to GWSS in shared build.

Parameters:

spatialWeights – Reference of spatial weight configuration object.

inline virtual Status getCriterion(BandwidthWeight *weight, double &criterion) override

Get criterion value with given bandwidth for bandwidth optimization.

Parameters:

  • weight – Given bandwidth.

  • criterion – [out] Criterion value.

Returns:

Status Algorithm status.

inline virtual const arma::vec &dependentVariable() const override

Get the Dependent Variable object.

Returns:

arma::vec Dependent Variable.

inline virtual void setDependentVariable(const arma::vec &y) override

Set the Dependent Variable object.

Parameters:

y –

inline virtual const arma::mat &independentVariables() const override

Get the Independent Variables object.

Returns:

arma::mat Independent Variables.

inline virtual void setIndependentVariables(const arma::mat &x) override

Set the Independent Variables object.

Parameters:

x –

inline virtual bool hasIntercept() const override

Get whether has intercept.

Returns:

true if has intercept.

Returns:

false if doesnot has intercept.

inline virtual void setHasIntercept(const bool has) override

Set the Has Intercept object.

Parameters:

has – true if has intercept, otherwise false.

inline virtual RegressionDiagnostic diagnostic() const override

Get diagnostic information.

Returns:

RegressionDiagnostic Diagnostic information.

inline virtual arma::mat predict(const arma::mat &locations) override

Predict coefficients on specified locations.

Parameters:

locations – Locations where to predict coefficients.

Returns:

mat Predicted coefficients.

virtual arma::mat fit() override

Fit coefficient estimates.

Returns:

mat Coefficient estimates

inline virtual int parallelAbility() const override

Return the parallel ability of this algorithm.

Returns:

Bitwise OR of aviliable parallel types of this algorithm.

inline virtual ParallelType parallelType() const override

Return the parallel type of this algorithm.

Returns:

Parallel type of this algorithm

virtual void setParallelType(const ParallelType &type) override

Set the parallel type of this algorithm.

Parameters:

type – Parallel type of this algorithm.

inline virtual void setOmpThreadNum(const int threadNum) override

Set the thread numbers while paralleling.

Parameters:

threadNum – Number of threads.

inline virtual void setGPUId(const int gpuId) override

Set ID of used GPU while paralleling.

Parameters:

gpuId – ID of used GPU. Start from 0.

inline virtual void setGroupSize(const std::size_t size) override

Set the group size while paralleling.

Parameters:

size – Group size \(g\) while paralleling. Usually this is up to memory size \(m\) (B) of GPU with ID gpuId. If there are \(n\) samples and \(k\) variables,

\[ k * n * g * 8 < m \]
For most GPU, 64 is OK.

inline virtual int workerId() override
inline virtual void setWorkerId(int id) override
inline virtual void setWorkerNum(int size) override

Public Static Attributes

static std::unordered_map<BandwidthInitilizeType, std::string> BandwidthInitilizeTypeNameMapper

A mapper from bandwidth inilization types to their names.

static std::unordered_map<BandwidthSelectionCriterionType, std::string> BandwidthSelectionCriterionTypeNameMapper

A mapper from bandwidth selection criterion types to their names.

static std::unordered_map<BackFittingCriterionType, std::string> BackFittingCriterionTypeNameMapper

A mapper from backfitting convergence criterion types to their names.

static int treeChildCount

Protected Functions

inline BandwidthWeight *bandwidth(size_t i)

Get the \(i\)-th bandwidth.

Parameters:

i – The index of bandwidth.

Returns:

BandwidthWeight* The \(i\)-th bandwidth.

arma::mat fitInitial()
arma::mat backfitting(const arma::mat &betas0)

The backfitting algorithm.

Parameters:

  • x – Independent variables \(X\).

  • y – Dependent variable \(y\).

Returns:

arma::mat Coefficient estimates \(\beta\).

arma::vec fitVarBase(const size_t var)
double bandwidthSizeCriterionVarCVBase(BandwidthWeight *bandwidthWeight)

The serial implementation of CV criterion calculator for given bandwidth size and one variable.

Parameters:

bandwidthWeight – Badwidth weight.

Returns:

double CV criterion value.

double bandwidthSizeCriterionVarAICBase(BandwidthWeight *bandwidthWeight)

The serial implementation of AIC criterion calculator for given bandwidth size and one variable.

Parameters:

bandwidthWeight – Badwidth weight.

Returns:

double AIC criterion value.

arma::vec fitVarCoreSerial(const arma::vec &x, const arma::vec &y, const SpatialWeight &sw, arma::mat &S)

The serial implementation of fit function for one variable.

Parameters:

  • x – Independent variables \(X\).

  • y – Dependent variable \(y\).

  • var – The index of this variable.

  • S – The hat matrix \(S\).

Returns:

arma::vec The coefficient estimates corresponding to this variable.

arma::vec fitVarCoreCVSerial(const arma::vec &x, const arma::vec &y, const SpatialWeight &sw)
arma::vec fitVarCoreSHatSerial(const arma::vec &x, const arma::vec &y, const SpatialWeight &sw, arma::vec &shat)