VTK
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A class for multivariate principal component analysis. More...
#include <vtkPCAStatistics.h>
Public Types | |
typedef vtkMultiCorrelativeStatistics | Superclass |
enum | NormalizationType { NONE, TRIANGLE_SPECIFIED, DIAGONAL_SPECIFIED, DIAGONAL_VARIANCE, NUM_NORMALIZATION_SCHEMES } |
enum | ProjectionType { FULL_BASIS, FIXED_BASIS_SIZE, FIXED_BASIS_ENERGY, NUM_BASIS_SCHEMES } |
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typedef vtkStatisticsAlgorithm | Superclass |
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typedef vtkTableAlgorithm | Superclass |
enum | InputPorts { INPUT_DATA = 0, LEARN_PARAMETERS = 1, INPUT_MODEL = 2 } |
enum | OutputIndices { OUTPUT_DATA = 0, OUTPUT_MODEL = 1, ASSESSMENT = 2, OUTPUT_TEST = 2 } |
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typedef vtkAlgorithm | Superclass |
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typedef vtkObject | Superclass |
enum | DesiredOutputPrecision { SINGLE_PRECISION, DOUBLE_PRECISION, DEFAULT_PRECISION } |
Public Member Functions | |
virtual int | IsA (const char *type) |
vtkPCAStatistics * | NewInstance () const |
virtual void | PrintSelf (ostream &os, vtkIndent indent) |
virtual void | SetNormalizationScheme (int) |
virtual int | GetNormalizationScheme () |
virtual void | SetNormalizationSchemeByName (const char *sname) |
virtual const char * | GetNormalizationSchemeName (int scheme) |
virtual vtkTable * | GetSpecifiedNormalization () |
virtual void | SetSpecifiedNormalization (vtkTable *) |
void | GetEigenvalues (int request, vtkDoubleArray *) |
void | GetEigenvalues (vtkDoubleArray *) |
double | GetEigenvalue (int request, int i) |
double | GetEigenvalue (int i) |
void | GetEigenvectors (int request, vtkDoubleArray *eigenvectors) |
void | GetEigenvectors (vtkDoubleArray *eigenvectors) |
void | GetEigenvector (int i, vtkDoubleArray *eigenvector) |
void | GetEigenvector (int request, int i, vtkDoubleArray *eigenvector) |
virtual void | SetBasisScheme (int) |
virtual int | GetBasisScheme () |
virtual const char * | GetBasisSchemeName (int schemeIndex) |
virtual void | SetBasisSchemeByName (const char *schemeName) |
virtual void | SetFixedBasisSize (int) |
virtual int | GetFixedBasisSize () |
virtual void | SetFixedBasisEnergy (double) |
virtual double | GetFixedBasisEnergy () |
virtual bool | SetParameter (const char *parameter, int index, vtkVariant value) |
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vtkMultiCorrelativeStatistics * | NewInstance () const |
virtual void | Aggregate (vtkDataObjectCollection *, vtkMultiBlockDataSet *) |
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vtkStatisticsAlgorithm * | NewInstance () const |
void | PrintSelf (ostream &os, vtkIndent indent) |
virtual void | SetColumnStatus (const char *namCol, int status) |
virtual void | ResetAllColumnStates () |
virtual int | RequestSelectedColumns () |
virtual void | ResetRequests () |
virtual vtkIdType | GetNumberOfRequests () |
virtual vtkIdType | GetNumberOfColumnsForRequest (vtkIdType request) |
void | AddColumn (const char *namCol) |
void | AddColumnPair (const char *namColX, const char *namColY) |
virtual void | SetLearnOptionParameterConnection (vtkAlgorithmOutput *params) |
virtual void | SetLearnOptionParameters (vtkDataObject *params) |
virtual void | SetInputModelConnection (vtkAlgorithmOutput *model) |
virtual void | SetInputModel (vtkDataObject *model) |
virtual void | SetLearnOption (bool) |
virtual bool | GetLearnOption () |
virtual void | SetDeriveOption (bool) |
virtual bool | GetDeriveOption () |
virtual void | SetAssessOption (bool) |
virtual bool | GetAssessOption () |
virtual void | SetTestOption (bool) |
virtual bool | GetTestOption () |
virtual void | SetNumberOfPrimaryTables (vtkIdType) |
virtual vtkIdType | GetNumberOfPrimaryTables () |
virtual void | SetAssessNames (vtkStringArray *) |
virtual vtkStringArray * | GetAssessNames () |
virtual const char * | GetColumnForRequest (vtkIdType r, vtkIdType c) |
virtual int | GetColumnForRequest (vtkIdType r, vtkIdType c, vtkStdString &columnName) |
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vtkTableAlgorithm * | NewInstance () const |
void | PrintSelf (ostream &os, vtkIndent indent) |
virtual int | ProcessRequest (vtkInformation *, vtkInformationVector **, vtkInformationVector *) |
vtkTable * | GetOutput () |
vtkTable * | GetOutput (int index) |
void | SetInputData (vtkDataObject *obj) |
void | SetInputData (int index, vtkDataObject *obj) |
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vtkAlgorithm * | NewInstance () const |
void | PrintSelf (ostream &os, vtkIndent indent) |
int | HasExecutive () |
vtkExecutive * | GetExecutive () |
virtual void | SetExecutive (vtkExecutive *executive) |
virtual int | ModifyRequest (vtkInformation *request, int when) |
vtkInformation * | GetInputPortInformation (int port) |
vtkInformation * | GetOutputPortInformation (int port) |
int | GetNumberOfInputPorts () |
int | GetNumberOfOutputPorts () |
void | UpdateProgress (double amount) |
vtkInformation * | GetInputArrayInformation (int idx) |
void | RemoveAllInputs () |
vtkDataObject * | GetOutputDataObject (int port) |
virtual void | RemoveInputConnection (int port, vtkAlgorithmOutput *input) |
virtual void | RemoveInputConnection (int port, int idx) |
virtual void | RemoveAllInputConnections (int port) |
int | GetNumberOfInputConnections (int port) |
int | GetTotalNumberOfInputConnections () |
vtkAlgorithmOutput * | GetInputConnection (int port, int index) |
vtkAlgorithm * | GetInputAlgorithm (int port, int index, int &algPort) |
vtkAlgorithm * | GetInputAlgorithm (int port, int index) |
vtkExecutive * | GetInputExecutive (int port, int index) |
vtkInformation * | GetInputInformation (int port, int index) |
vtkInformation * | GetOutputInformation (int port) |
virtual void | UpdateInformation () |
virtual void | PropagateUpdateExtent () |
virtual void | UpdateWholeExtent () |
void | ConvertTotalInputToPortConnection (int ind, int &port, int &conn) |
virtual double | ComputePriority () |
int | SetUpdateExtentToWholeExtent (int port) |
int | SetUpdateExtentToWholeExtent () |
void | SetUpdateExtent (int port, int extent[6]) |
int | ProcessRequest (vtkInformation *request, vtkCollection *inInfo, vtkInformationVector *outInfo) |
virtual int | ComputePipelineMTime (vtkInformation *request, vtkInformationVector **inInfoVec, vtkInformationVector *outInfoVec, int requestFromOutputPort, unsigned long *mtime) |
virtual vtkInformation * | GetInformation () |
virtual void | SetInformation (vtkInformation *) |
virtual void | Register (vtkObjectBase *o) |
virtual void | UnRegister (vtkObjectBase *o) |
virtual void | SetAbortExecute (int) |
virtual int | GetAbortExecute () |
virtual void | AbortExecuteOn () |
virtual void | AbortExecuteOff () |
virtual void | SetProgress (double) |
virtual double | GetProgress () |
void | SetProgressText (const char *ptext) |
virtual char * | GetProgressText () |
virtual unsigned long | GetErrorCode () |
virtual void | SetInputArrayToProcess (int idx, int port, int connection, int fieldAssociation, const char *name) |
virtual void | SetInputArrayToProcess (int idx, int port, int connection, int fieldAssociation, int fieldAttributeType) |
virtual void | SetInputArrayToProcess (int idx, vtkInformation *info) |
virtual void | SetInputArrayToProcess (int idx, int port, int connection, const char *fieldAssociation, const char *attributeTypeorName) |
vtkDataObject * | GetInputDataObject (int port, int connection) |
virtual void | SetInputConnection (int port, vtkAlgorithmOutput *input) |
virtual void | SetInputConnection (vtkAlgorithmOutput *input) |
virtual void | AddInputConnection (int port, vtkAlgorithmOutput *input) |
virtual void | AddInputConnection (vtkAlgorithmOutput *input) |
virtual void | SetInputDataObject (int port, vtkDataObject *data) |
virtual void | SetInputDataObject (vtkDataObject *data) |
virtual void | AddInputDataObject (int port, vtkDataObject *data) |
virtual void | AddInputDataObject (vtkDataObject *data) |
vtkAlgorithmOutput * | GetOutputPort (int index) |
vtkAlgorithmOutput * | GetOutputPort () |
vtkAlgorithm * | GetInputAlgorithm () |
vtkExecutive * | GetInputExecutive () |
vtkInformation * | GetInputInformation () |
virtual void | Update (int port) |
virtual void | Update () |
virtual void | SetReleaseDataFlag (int) |
virtual int | GetReleaseDataFlag () |
void | ReleaseDataFlagOn () |
void | ReleaseDataFlagOff () |
int | UpdateExtentIsEmpty (vtkInformation *pinfo, vtkDataObject *output) |
int | UpdateExtentIsEmpty (vtkInformation *pinfo, int extentType) |
void | SetUpdateExtent (int port, int piece, int numPieces, int ghostLevel) |
void | SetUpdateExtent (int piece, int numPieces, int ghostLevel) |
void | SetUpdateExtent (int extent[6]) |
int * | GetUpdateExtent () |
int * | GetUpdateExtent (int port) |
void | GetUpdateExtent (int &x0, int &x1, int &y0, int &y1, int &z0, int &z1) |
void | GetUpdateExtent (int port, int &x0, int &x1, int &y0, int &y1, int &z0, int &z1) |
void | GetUpdateExtent (int extent[6]) |
void | GetUpdateExtent (int port, int extent[6]) |
int | GetUpdatePiece () |
int | GetUpdatePiece (int port) |
int | GetUpdateNumberOfPieces () |
int | GetUpdateNumberOfPieces (int port) |
int | GetUpdateGhostLevel () |
int | GetUpdateGhostLevel (int port) |
Static Public Member Functions | |
static int | IsTypeOf (const char *type) |
static vtkPCAStatistics * | SafeDownCast (vtkObjectBase *o) |
static vtkPCAStatistics * | New () |
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static int | IsTypeOf (const char *type) |
static vtkMultiCorrelativeStatistics * | SafeDownCast (vtkObjectBase *o) |
static vtkMultiCorrelativeStatistics * | New () |
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static int | IsTypeOf (const char *type) |
static vtkStatisticsAlgorithm * | SafeDownCast (vtkObjectBase *o) |
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static vtkTableAlgorithm * | New () |
static int | IsTypeOf (const char *type) |
static vtkTableAlgorithm * | SafeDownCast (vtkObjectBase *o) |
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static vtkAlgorithm * | New () |
static int | IsTypeOf (const char *type) |
static vtkAlgorithm * | SafeDownCast (vtkObjectBase *o) |
static void | SetDefaultExecutivePrototype (vtkExecutive *proto) |
static vtkInformationIntegerKey * | INPUT_IS_OPTIONAL () |
static vtkInformationIntegerKey * | INPUT_IS_REPEATABLE () |
static vtkInformationInformationVectorKey * | INPUT_REQUIRED_FIELDS () |
static vtkInformationStringVectorKey * | INPUT_REQUIRED_DATA_TYPE () |
static vtkInformationInformationVectorKey * | INPUT_ARRAYS_TO_PROCESS () |
static vtkInformationIntegerKey * | INPUT_PORT () |
static vtkInformationIntegerKey * | INPUT_CONNECTION () |
static vtkInformationIntegerKey * | PRESERVES_DATASET () |
static vtkInformationIntegerKey * | PRESERVES_GEOMETRY () |
static vtkInformationIntegerKey * | PRESERVES_BOUNDS () |
static vtkInformationIntegerKey * | PRESERVES_TOPOLOGY () |
static vtkInformationIntegerKey * | PRESERVES_ATTRIBUTES () |
static vtkInformationIntegerKey * | PRESERVES_RANGES () |
static vtkInformationIntegerKey * | MANAGES_METAINFORMATION () |
Protected Member Functions | |
virtual vtkObjectBase * | NewInstanceInternal () const |
vtkPCAStatistics () | |
~vtkPCAStatistics () | |
virtual int | FillInputPortInformation (int port, vtkInformation *info) |
virtual void | Derive (vtkMultiBlockDataSet *) |
virtual vtkDoubleArray * | CalculatePValues (vtkIdTypeArray *, vtkDoubleArray *) |
virtual void | Test (vtkTable *, vtkMultiBlockDataSet *, vtkTable *) |
virtual void | Assess (vtkTable *, vtkMultiBlockDataSet *, vtkTable *) |
virtual void | SelectAssessFunctor (vtkTable *inData, vtkDataObject *inMeta, vtkStringArray *rowNames, AssessFunctor *&dfunc) |
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vtkMultiCorrelativeStatistics () | |
~vtkMultiCorrelativeStatistics () | |
virtual void | Learn (vtkTable *, vtkTable *, vtkMultiBlockDataSet *) |
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vtkStatisticsAlgorithm () | |
~vtkStatisticsAlgorithm () | |
virtual int | FillOutputPortInformation (int port, vtkInformation *info) |
virtual int | RequestData (vtkInformation *, vtkInformationVector **, vtkInformationVector *) |
void | Assess (vtkTable *, vtkMultiBlockDataSet *, vtkTable *, int) |
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vtkTableAlgorithm () | |
~vtkTableAlgorithm () | |
virtual int | RequestInformation (vtkInformation *request, vtkInformationVector **inputVector, vtkInformationVector *outputVector) |
virtual int | RequestUpdateExtent (vtkInformation *, vtkInformationVector **, vtkInformationVector *) |
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vtkAlgorithm () | |
~vtkAlgorithm () | |
virtual void | SetNumberOfInputPorts (int n) |
virtual void | SetNumberOfOutputPorts (int n) |
int | InputPortIndexInRange (int index, const char *action) |
int | OutputPortIndexInRange (int index, const char *action) |
int | GetInputArrayAssociation (int idx, vtkInformationVector **inputVector) |
virtual vtkExecutive * | CreateDefaultExecutive () |
virtual void | ReportReferences (vtkGarbageCollector *) |
virtual void | SetNumberOfInputConnections (int port, int n) |
int | GetInputArrayAssociation (int idx, int connection, vtkInformationVector **inputVector) |
int | GetInputArrayAssociation (int idx, vtkDataObject *input) |
vtkDataArray * | GetInputArrayToProcess (int idx, vtkInformationVector **inputVector) |
vtkDataArray * | GetInputArrayToProcess (int idx, vtkInformationVector **inputVector, int &association) |
vtkDataArray * | GetInputArrayToProcess (int idx, int connection, vtkInformationVector **inputVector) |
vtkDataArray * | GetInputArrayToProcess (int idx, int connection, vtkInformationVector **inputVector, int &association) |
vtkDataArray * | GetInputArrayToProcess (int idx, vtkDataObject *input) |
vtkDataArray * | GetInputArrayToProcess (int idx, vtkDataObject *input, int &association) |
vtkAbstractArray * | GetInputAbstractArrayToProcess (int idx, vtkInformationVector **inputVector) |
vtkAbstractArray * | GetInputAbstractArrayToProcess (int idx, vtkInformationVector **inputVector, int &association) |
vtkAbstractArray * | GetInputAbstractArrayToProcess (int idx, int connection, vtkInformationVector **inputVector) |
vtkAbstractArray * | GetInputAbstractArrayToProcess (int idx, int connection, vtkInformationVector **inputVector, int &association) |
vtkAbstractArray * | GetInputAbstractArrayToProcess (int idx, vtkDataObject *input) |
vtkAbstractArray * | GetInputAbstractArrayToProcess (int idx, vtkDataObject *input, int &association) |
vtkInformation * | GetInputArrayFieldInformation (int idx, vtkInformationVector **inputVector) |
virtual void | SetNthInputConnection (int port, int index, vtkAlgorithmOutput *input) |
void | SetInputDataInternal (int port, vtkDataObject *input) |
void | AddInputDataInternal (int port, vtkDataObject *input) |
virtual void | SetErrorCode (unsigned long) |
Protected Attributes | |
int | NormalizationScheme |
int | BasisScheme |
int | FixedBasisSize |
double | FixedBasisEnergy |
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int | NumberOfPrimaryTables |
bool | LearnOption |
bool | DeriveOption |
bool | AssessOption |
bool | TestOption |
vtkStringArray * | AssessNames |
vtkStatisticsAlgorithmPrivate * | Internals |
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vtkInformation * | Information |
double | Progress |
char * | ProgressText |
unsigned long | ErrorCode |
Static Protected Attributes | |
static const char * | BasisSchemeEnumNames [NUM_BASIS_SCHEMES+1] |
static const char * | NormalizationSchemeEnumNames [NUM_NORMALIZATION_SCHEMES+1] |
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static vtkExecutive * | DefaultExecutivePrototype |
Additional Inherited Members | |
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int | AbortExecute |
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static vtkInformationIntegerKey * | PORT_REQUIREMENTS_FILLED () |
A class for multivariate principal component analysis.
This class derives from the multi-correlative statistics algorithm and uses the covariance matrix and Cholesky decomposition computed by it. However, when it finalizes the statistics in learn operation, the PCA class computes the SVD of the covariance matrix in order to obtain its eigenvectors.
In the assess operation, the input data are
In the test operation, a Jarque-Bera-Srivastava test of n-d normality is performed.
Definition at line 58 of file vtkPCAStatistics.h.
Definition at line 61 of file vtkPCAStatistics.h.
Methods by which the covariance matrix may be normalized.
Definition at line 68 of file vtkPCAStatistics.h.
These are the enumeration values that SetBasisScheme() accepts and GetBasisScheme returns.
Definition at line 81 of file vtkPCAStatistics.h.
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Reimplemented from vtkMultiCorrelativeStatistics.
Reimplemented in vtkPCAStatisticsGnuR, and vtkPPCAStatistics.
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Reimplemented from vtkMultiCorrelativeStatistics.
Reimplemented in vtkPCAStatisticsGnuR, and vtkPPCAStatistics.
vtkPCAStatistics* vtkPCAStatistics::NewInstance | ( | ) | const |
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Reimplemented from vtkMultiCorrelativeStatistics.
Reimplemented in vtkPCAStatisticsGnuR, and vtkPPCAStatistics.
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This determines how (or if) the covariance matrix cov is normalized before PCA. When set to NONE, no normalization is performed. This is the default. When set to TRIANGLE_SPECIFIED, each entry cov(i,j) is divided by V(i,j). The list V of normalization factors must be set using the SetNormalization method before the filter is executed. When set to DIAGONAL_SPECIFIED, each entry cov(i,j) is divided by sqrt(V(i)*V(j)). The list V of normalization factors must be set using the SetNormalization method before the filter is executed. When set to DIAGONAL_VARIANCE, each entry cov(i,j) is divided by sqrt(cov(i,i)*cov(j,j)). Warning: Although this is accepted practice in some fields, some people think you should not turn this option on unless there is a good physically-based reason for doing so. Much better instead to determine how component magnitudes should be compared using physical reasoning and use DIAGONAL_SPECIFIED, TRIANGLE_SPECIFIED, or perform some pre-processing to shift and scale input data columns appropriately than to expect magical results from a shady normalization hack.
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This determines how (or if) the covariance matrix cov is normalized before PCA. When set to NONE, no normalization is performed. This is the default. When set to TRIANGLE_SPECIFIED, each entry cov(i,j) is divided by V(i,j). The list V of normalization factors must be set using the SetNormalization method before the filter is executed. When set to DIAGONAL_SPECIFIED, each entry cov(i,j) is divided by sqrt(V(i)*V(j)). The list V of normalization factors must be set using the SetNormalization method before the filter is executed. When set to DIAGONAL_VARIANCE, each entry cov(i,j) is divided by sqrt(cov(i,i)*cov(j,j)). Warning: Although this is accepted practice in some fields, some people think you should not turn this option on unless there is a good physically-based reason for doing so. Much better instead to determine how component magnitudes should be compared using physical reasoning and use DIAGONAL_SPECIFIED, TRIANGLE_SPECIFIED, or perform some pre-processing to shift and scale input data columns appropriately than to expect magical results from a shady normalization hack.
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This determines how (or if) the covariance matrix cov is normalized before PCA. When set to NONE, no normalization is performed. This is the default. When set to TRIANGLE_SPECIFIED, each entry cov(i,j) is divided by V(i,j). The list V of normalization factors must be set using the SetNormalization method before the filter is executed. When set to DIAGONAL_SPECIFIED, each entry cov(i,j) is divided by sqrt(V(i)*V(j)). The list V of normalization factors must be set using the SetNormalization method before the filter is executed. When set to DIAGONAL_VARIANCE, each entry cov(i,j) is divided by sqrt(cov(i,i)*cov(j,j)). Warning: Although this is accepted practice in some fields, some people think you should not turn this option on unless there is a good physically-based reason for doing so. Much better instead to determine how component magnitudes should be compared using physical reasoning and use DIAGONAL_SPECIFIED, TRIANGLE_SPECIFIED, or perform some pre-processing to shift and scale input data columns appropriately than to expect magical results from a shady normalization hack.
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This determines how (or if) the covariance matrix cov is normalized before PCA. When set to NONE, no normalization is performed. This is the default. When set to TRIANGLE_SPECIFIED, each entry cov(i,j) is divided by V(i,j). The list V of normalization factors must be set using the SetNormalization method before the filter is executed. When set to DIAGONAL_SPECIFIED, each entry cov(i,j) is divided by sqrt(V(i)*V(j)). The list V of normalization factors must be set using the SetNormalization method before the filter is executed. When set to DIAGONAL_VARIANCE, each entry cov(i,j) is divided by sqrt(cov(i,i)*cov(j,j)). Warning: Although this is accepted practice in some fields, some people think you should not turn this option on unless there is a good physically-based reason for doing so. Much better instead to determine how component magnitudes should be compared using physical reasoning and use DIAGONAL_SPECIFIED, TRIANGLE_SPECIFIED, or perform some pre-processing to shift and scale input data columns appropriately than to expect magical results from a shady normalization hack.
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These methods allow you to set/get values used to normalize the covariance matrix before PCA. The normalization values apply to all requests, so you do not specify a single vector but a 3-column table. The first two columns contain the names of columns from input 0 and the third column contains the value to normalize the corresponding entry in the covariance matrix. The table must always have 3 columns even when the NormalizationScheme is DIAGONAL_SPECIFIED. When only diagonal entries are to be used, only table rows where the first two columns are identical to one another will be employed. If there are multiple rows specifying different values for the same pair of columns, the entry nearest the bottom of the table takes precedence. These functions are actually convenience methods that set/get the third input of the filter. Because the table is the third input, you may use other filters to produce a table of normalizations and have the pipeline take care of updates. Any missing entries will be set to 1.0 and a warning issued. An error will occur if the third input to the filter is not set and the NormalizationScheme is DIAGONAL_SPECIFIED or TRIANGLE_SPECIFIED. NOTE: SetSpecifiedNormalization( table ) is equivalent to SetInputData(3, table) and therefore does not make a pipeline connection.
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These methods allow you to set/get values used to normalize the covariance matrix before PCA. The normalization values apply to all requests, so you do not specify a single vector but a 3-column table. The first two columns contain the names of columns from input 0 and the third column contains the value to normalize the corresponding entry in the covariance matrix. The table must always have 3 columns even when the NormalizationScheme is DIAGONAL_SPECIFIED. When only diagonal entries are to be used, only table rows where the first two columns are identical to one another will be employed. If there are multiple rows specifying different values for the same pair of columns, the entry nearest the bottom of the table takes precedence. These functions are actually convenience methods that set/get the third input of the filter. Because the table is the third input, you may use other filters to produce a table of normalizations and have the pipeline take care of updates. Any missing entries will be set to 1.0 and a warning issued. An error will occur if the third input to the filter is not set and the NormalizationScheme is DIAGONAL_SPECIFIED or TRIANGLE_SPECIFIED. NOTE: SetSpecifiedNormalization( table ) is equivalent to SetInputData(3, table) and therefore does not make a pipeline connection.
void vtkPCAStatistics::GetEigenvalues | ( | int | request, |
vtkDoubleArray * | |||
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Get the eigenvalues. The eigenvalues are ordered according from largest to smallest. This function: void GetEigenvalues(int request, int i, vtkDoubleArray*); does all of the work. The other functions simply call this function with the appropriate parameters. These functions are not valid unless Update() has been called and the Derive option is turned on.
void vtkPCAStatistics::GetEigenvalues | ( | vtkDoubleArray * | ) |
Get the eigenvalues. The eigenvalues are ordered according from largest to smallest. This function: void GetEigenvalues(int request, int i, vtkDoubleArray*); does all of the work. The other functions simply call this function with the appropriate parameters. These functions are not valid unless Update() has been called and the Derive option is turned on.
double vtkPCAStatistics::GetEigenvalue | ( | int | request, |
int | i | ||
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Get the eigenvalues. The eigenvalues are ordered according from largest to smallest. This function: void GetEigenvalues(int request, int i, vtkDoubleArray*); does all of the work. The other functions simply call this function with the appropriate parameters. These functions are not valid unless Update() has been called and the Derive option is turned on.
double vtkPCAStatistics::GetEigenvalue | ( | int | i | ) |
Get the eigenvalues. The eigenvalues are ordered according from largest to smallest. This function: void GetEigenvalues(int request, int i, vtkDoubleArray*); does all of the work. The other functions simply call this function with the appropriate parameters. These functions are not valid unless Update() has been called and the Derive option is turned on.
void vtkPCAStatistics::GetEigenvectors | ( | int | request, |
vtkDoubleArray * | eigenvectors | ||
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Get the eigenvectors. The eigenvectors are ordered according to the magnitude of their associated eigenvalues, sorted from largest to smallest. That is, eigenvector 0 corresponds to the largest eigenvalue. This function: void GetEigenvectors(int request, vtkDoubleArray* eigenvectors) does all of the work. The other functions are convenience functions that call this function with default arguments. These functions are not valid unless Update() has been called and the Derive option is turned on.
void vtkPCAStatistics::GetEigenvectors | ( | vtkDoubleArray * | eigenvectors | ) |
Get the eigenvectors. The eigenvectors are ordered according to the magnitude of their associated eigenvalues, sorted from largest to smallest. That is, eigenvector 0 corresponds to the largest eigenvalue. This function: void GetEigenvectors(int request, vtkDoubleArray* eigenvectors) does all of the work. The other functions are convenience functions that call this function with default arguments. These functions are not valid unless Update() has been called and the Derive option is turned on.
void vtkPCAStatistics::GetEigenvector | ( | int | i, |
vtkDoubleArray * | eigenvector | ||
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Get the eigenvectors. The eigenvectors are ordered according to the magnitude of their associated eigenvalues, sorted from largest to smallest. That is, eigenvector 0 corresponds to the largest eigenvalue. This function: void GetEigenvectors(int request, vtkDoubleArray* eigenvectors) does all of the work. The other functions are convenience functions that call this function with default arguments. These functions are not valid unless Update() has been called and the Derive option is turned on.
void vtkPCAStatistics::GetEigenvector | ( | int | request, |
int | i, | ||
vtkDoubleArray * | eigenvector | ||
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Get the eigenvectors. The eigenvectors are ordered according to the magnitude of their associated eigenvalues, sorted from largest to smallest. That is, eigenvector 0 corresponds to the largest eigenvalue. This function: void GetEigenvectors(int request, vtkDoubleArray* eigenvectors) does all of the work. The other functions are convenience functions that call this function with default arguments. These functions are not valid unless Update() has been called and the Derive option is turned on.
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This variable controls the dimensionality of output tuples in Assess operation. Consider the case where you have requested a PCA on D columns. When set to vtkPCAStatistics::FULL_BASIS, the entire set of basis vectors is used to derive new coordinates for each tuple being assessed. In this mode, you are guaranteed to have output tuples of the same dimension as the input tuples. (That dimension is D, so there will be D additional columns added to the table for the request.) When set to vtkPCAStatistics::FIXED_BASIS_SIZE, only the first N basis vectors are used to derive new coordinates for each tuple being assessed. In this mode, you are guaranteed to have output tuples of dimension min(N,D). You must set N prior to assessing data using the SetFixedBasisSize() method. When N < D, this turns the PCA into a projection (instead of change of basis). When set to vtkPCAStatistics::FIXED_BASIS_ENERGY, the number of basis vectors used to derive new coordinates for each tuple will be the minimum number of columns N that satisfy
You must set T prior to assessing data using the SetFixedBasisEnergy() method. When T < 1, this turns the PCA into a projection (instead of change of basis). By default BasisScheme is set to vtkPCAStatistics::FULL_BASIS.
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This variable controls the dimensionality of output tuples in Assess operation. Consider the case where you have requested a PCA on D columns. When set to vtkPCAStatistics::FULL_BASIS, the entire set of basis vectors is used to derive new coordinates for each tuple being assessed. In this mode, you are guaranteed to have output tuples of the same dimension as the input tuples. (That dimension is D, so there will be D additional columns added to the table for the request.) When set to vtkPCAStatistics::FIXED_BASIS_SIZE, only the first N basis vectors are used to derive new coordinates for each tuple being assessed. In this mode, you are guaranteed to have output tuples of dimension min(N,D). You must set N prior to assessing data using the SetFixedBasisSize() method. When N < D, this turns the PCA into a projection (instead of change of basis). When set to vtkPCAStatistics::FIXED_BASIS_ENERGY, the number of basis vectors used to derive new coordinates for each tuple will be the minimum number of columns N that satisfy
You must set T prior to assessing data using the SetFixedBasisEnergy() method. When T < 1, this turns the PCA into a projection (instead of change of basis). By default BasisScheme is set to vtkPCAStatistics::FULL_BASIS.
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This variable controls the dimensionality of output tuples in Assess operation. Consider the case where you have requested a PCA on D columns. When set to vtkPCAStatistics::FULL_BASIS, the entire set of basis vectors is used to derive new coordinates for each tuple being assessed. In this mode, you are guaranteed to have output tuples of the same dimension as the input tuples. (That dimension is D, so there will be D additional columns added to the table for the request.) When set to vtkPCAStatistics::FIXED_BASIS_SIZE, only the first N basis vectors are used to derive new coordinates for each tuple being assessed. In this mode, you are guaranteed to have output tuples of dimension min(N,D). You must set N prior to assessing data using the SetFixedBasisSize() method. When N < D, this turns the PCA into a projection (instead of change of basis). When set to vtkPCAStatistics::FIXED_BASIS_ENERGY, the number of basis vectors used to derive new coordinates for each tuple will be the minimum number of columns N that satisfy
You must set T prior to assessing data using the SetFixedBasisEnergy() method. When T < 1, this turns the PCA into a projection (instead of change of basis). By default BasisScheme is set to vtkPCAStatistics::FULL_BASIS.
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This variable controls the dimensionality of output tuples in Assess operation. Consider the case where you have requested a PCA on D columns. When set to vtkPCAStatistics::FULL_BASIS, the entire set of basis vectors is used to derive new coordinates for each tuple being assessed. In this mode, you are guaranteed to have output tuples of the same dimension as the input tuples. (That dimension is D, so there will be D additional columns added to the table for the request.) When set to vtkPCAStatistics::FIXED_BASIS_SIZE, only the first N basis vectors are used to derive new coordinates for each tuple being assessed. In this mode, you are guaranteed to have output tuples of dimension min(N,D). You must set N prior to assessing data using the SetFixedBasisSize() method. When N < D, this turns the PCA into a projection (instead of change of basis). When set to vtkPCAStatistics::FIXED_BASIS_ENERGY, the number of basis vectors used to derive new coordinates for each tuple will be the minimum number of columns N that satisfy
You must set T prior to assessing data using the SetFixedBasisEnergy() method. When T < 1, this turns the PCA into a projection (instead of change of basis). By default BasisScheme is set to vtkPCAStatistics::FULL_BASIS.
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The number of basis vectors to use. See SetBasisScheme() for more information. When FixedBasisSize <= 0 (the default), the fixed basis size scheme is equivalent to the full basis scheme.
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The number of basis vectors to use. See SetBasisScheme() for more information. When FixedBasisSize <= 0 (the default), the fixed basis size scheme is equivalent to the full basis scheme.
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The minimum energy the new basis should use, as a fraction. See SetBasisScheme() for more information. When FixedBasisEnergy >= 1 (the default), the fixed basis energy scheme is equivalent to the full basis scheme.
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The minimum energy the new basis should use, as a fraction. See SetBasisScheme() for more information. When FixedBasisEnergy >= 1 (the default), the fixed basis energy scheme is equivalent to the full basis scheme.
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A convenience method (in particular for access from other applications) to set parameter values. Return true if setting of requested parameter name was excuted, false otherwise.
Reimplemented from vtkStatisticsAlgorithm.
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This algorithm accepts a vtkTable containing normalization values for its fourth input (port 3). We override FillInputPortInformation to indicate this.
Reimplemented from vtkStatisticsAlgorithm.
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Execute the calculations required by the Derive option.
Reimplemented from vtkMultiCorrelativeStatistics.
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Execute the calculations required by the Test option.
Reimplemented from vtkMultiCorrelativeStatistics.
Reimplemented in vtkPPCAStatistics.
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Execute the calculations required by the Assess option.
Reimplemented from vtkMultiCorrelativeStatistics.
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Calculate p-value. This will be overridden using the object factory with an R implementation if R is present.
Reimplemented in vtkPCAStatisticsGnuR.
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Provide the appropriate assessment functor.
Reimplemented from vtkMultiCorrelativeStatistics.
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Definition at line 262 of file vtkPCAStatistics.h.
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Definition at line 263 of file vtkPCAStatistics.h.
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Definition at line 264 of file vtkPCAStatistics.h.
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Definition at line 265 of file vtkPCAStatistics.h.
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Definition at line 268 of file vtkPCAStatistics.h.
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Definition at line 269 of file vtkPCAStatistics.h.