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Or, create a k-d tree point locator from a list of points. This class can also generate a PolyData representation of the boundaries of the spatial regions in the decomposition. It can sort the regions with respect to a viewing direction, and it can decompose a list of regions into subsets, each of which represent a convex spatial region (since many algorithms require a convex region). If the points were derived from cells, vtkKdTree can create a list of cell Ids for each region for each data set. Two lists are available - all cells with centroid in the region, and all cells that intersect the region but whose centroid lies in another region. For the purpose of removing duplicate points quickly from large data sets, or for finding nearby points, we added another mode for building the locator. BuildLocatorFromPoints will build a k-d tree from one or more vtkPoints objects. This can be followed by BuildMapForDuplicatePoints which returns a mapping from the original ids to a subset of the ids that is unique within a supplied tolerance, or you can use FindPoint and FindClosestPoint to locate points in the original set that the tree was built from. @sa vtkLocator vtkCellLocator vtkPKdTree IsTypeOfV.IsTypeOf(string) -> int C++: static vtkTypeBool IsTypeOf(const char *type) Standard type and print methods. IsAV.IsA(string) -> int C++: vtkTypeBool IsA(const char *type) override; Standard type and print methods. SafeDownCastV.SafeDownCast(vtkObjectBase) -> vtkKdTree C++: static vtkKdTree *SafeDownCast(vtkObjectBase *o) Standard type and print methods. NewInstanceV.NewInstance() -> vtkKdTree C++: vtkKdTree *NewInstance() Standard type and print methods. TimingOnV.TimingOn() C++: virtual void TimingOn() Turn on timing of the k-d tree build TimingOffV.TimingOff() C++: virtual void TimingOff() Turn on timing of the k-d tree build SetTimingV.SetTiming(int) C++: virtual void SetTiming(int _arg) Turn on timing of the k-d tree build GetTimingV.GetTiming() -> int C++: virtual int GetTiming() Turn on timing of the k-d tree build SetMinCellsV.SetMinCells(int) C++: virtual void SetMinCells(int _arg) Minimum number of cells per spatial region. Default is 100. GetMinCellsV.GetMinCells() -> int C++: virtual int GetMinCells() Minimum number of cells per spatial region. Default is 100. GetNumberOfRegionsOrLessV.GetNumberOfRegionsOrLess() -> int C++: virtual int GetNumberOfRegionsOrLess() Set/Get the number of spatial regions you want to get close to without going over. (The number of spatial regions is normally a power of two.) Call this before BuildLocator(). Default is unset (0). SetNumberOfRegionsOrLessV.SetNumberOfRegionsOrLess(int) C++: virtual void SetNumberOfRegionsOrLess(int _arg) GetNumberOfRegionsOrMoreV.GetNumberOfRegionsOrMore() -> int C++: virtual int GetNumberOfRegionsOrMore() Set/Get the number of spatial regions you want to get close to while having at least this many regions. (The number of spatial regions is normally a power of two.) Default is unset (0). SetNumberOfRegionsOrMoreV.SetNumberOfRegionsOrMore(int) C++: virtual void SetNumberOfRegionsOrMore(int _arg) GetFudgeFactorV.GetFudgeFactor() -> float C++: virtual double GetFudgeFactor() Some algorithms on k-d trees require a value that is a very small distance relative to the diameter of the entire space divided by the k-d tree. This factor is the maximum axis-aligned width of the space multiplied by 10e-6. SetFudgeFactorV.SetFudgeFactor(float) C++: virtual void SetFudgeFactor(double _arg) GetCutsV.GetCuts() -> vtkBSPCuts C++: virtual vtkBSPCuts *GetCuts() Get a vtkBSPCuts object, a general object representing an axis- aligned spatial partitioning. Used by vtkBSPIntersections. SetCutsV.SetCuts(vtkBSPCuts) C++: void SetCuts(vtkBSPCuts *cuts) Normally the k-d tree is computed from the dataset(s) provided in SetDataSet. Alternatively, you can provide the cuts that will be applied by calling SetCuts. OmitXPartitioningV.OmitXPartitioning() C++: void OmitXPartitioning() Omit partitions along the X axis, yielding shafts in the X direction OmitYPartitioningV.OmitYPartitioning() C++: void OmitYPartitioning() Omit partitions along the Y axis, yielding shafts in the Y direction OmitZPartitioningV.OmitZPartitioning() C++: void OmitZPartitioning() Omit partitions along the Z axis, yielding shafts in the Z direction OmitXYPartitioningV.OmitXYPartitioning() C++: void OmitXYPartitioning() Omit partitions along the X and Y axes, yielding slabs along Z OmitYZPartitioningV.OmitYZPartitioning() C++: void OmitYZPartitioning() Omit partitions along the Y and Z axes, yielding slabs along X OmitZXPartitioningV.OmitZXPartitioning() C++: void OmitZXPartitioning() Omit partitions along the Z and X axes, yielding slabs along Y OmitNoPartitioningV.OmitNoPartitioning() C++: void OmitNoPartitioning() Partition along all three axes - this is the default SetDataSetV.SetDataSet(vtkDataSet) C++: void SetDataSet(vtkDataSet *set) override; This class can compute a spatial decomposition based on the cells in a list of one or more input data sets. SetDataSet sets the first data set in the list to the named set. SetNthDataSet sets the data set at index N to the data set named. RemoveData set takes either the data set itself or an index and removes that data set from the list of data sets. AddDataSet adds a data set to the list of data sets. Clear out all data sets and replace with single data set. For backward compatibility with superclass. AddDataSetV.AddDataSet(vtkDataSet) C++: virtual void AddDataSet(vtkDataSet *set) This class can compute a spatial decomposition based on the cells in a list of one or more input data sets. Add them one at a time with this method. RemoveDataSetV.RemoveDataSet(int) C++: virtual void RemoveDataSet(int index) V.RemoveDataSet(vtkDataSet) C++: virtual void RemoveDataSet(vtkDataSet *set) Remove the given data set. RemoveAllDataSetsV.RemoveAllDataSets() C++: virtual void RemoveAllDataSets() Remove the given data set. GetNumberOfDataSetsV.GetNumberOfDataSets() -> int C++: int GetNumberOfDataSets() Get the number of data sets included in spatial paritioning GetDataSetV.GetDataSet(int) -> vtkDataSet C++: vtkDataSet *GetDataSet(int n) V.GetDataSet() -> vtkDataSet C++: vtkDataSet *GetDataSet() override; Get the nth defined data set in the spatial partitioning. (If you used SetNthDataSet to define 0,1 and 3 and ask for data set 2, you get 3.) Return the n'th data set. GetDataSetsV.GetDataSets() -> vtkDataSetCollection C++: virtual vtkDataSetCollection *GetDataSets() Return a collection of all the data sets. GetDataSetIndexV.GetDataSetIndex(vtkDataSet) -> int C++: int GetDataSetIndex(vtkDataSet *set) Return the index of the given data set. Returns -1 if that data set does not exist. GetBoundsV.GetBounds([float, ...]) C++: void GetBounds(double *bounds) Get the spatial bounds of the entire k-d tree space. Sets bounds array to xmin, xmax, ymin, ymax, zmin, zmax. SetNewBoundsV.SetNewBounds([float, ...]) C++: void SetNewBounds(double *bounds) There are certain applications where you want the bounds of the k-d tree space to be at least as large as a specified box. If the k-d tree has been built, you can expand it's bounds with this method. If the bounds supplied are smaller than those computed, they will be ignored. GetNumberOfRegionsV.GetNumberOfRegions() -> int C++: virtual int GetNumberOfRegions() The number of leaf nodes of the tree, the spatial regions GetRegionBoundsV.GetRegionBounds(int, [float, float, float, float, float, float]) C++: void GetRegionBounds(int regionID, double bounds[6]) Get the spatial bounds of k-d tree region GetRegionDataBoundsV.GetRegionDataBounds(int, [float, float, float, float, float, float]) C++: void GetRegionDataBounds(int regionID, double bounds[6]) Get the bounds of the data within the k-d tree region PrintTreeV.PrintTree() C++: void PrintTree() Print out nodes of kd tree PrintVerboseTreeV.PrintVerboseTree() C++: void PrintVerboseTree() Print out nodes of kd tree PrintRegionV.PrintRegion(int) C++: void PrintRegion(int id) Print out leaf node data for given id CreateCellListsV.CreateCellLists(int, [int, ...], int) C++: void CreateCellLists(int dataSetIndex, int *regionReqList, int reqListSize) V.CreateCellLists(vtkDataSet, [int, ...], int) C++: void CreateCellLists(vtkDataSet *set, int *regionReqList, int reqListSize) V.CreateCellLists([int, ...], int) C++: void CreateCellLists(int *regionReqList, int listSize) V.CreateCellLists() C++: void CreateCellLists() Create a list for each of the requested regions, listing the IDs of all cells whose centroid falls in the region. These lists are obtained with GetCellList(). If no DataSet is specified, the cell list is created for DataSet 0. If no list of requested regions is provided, the cell lists for all regions are created. * When CreateCellLists is called again, the lists created * on the previous call are deleted. SetIncludeRegionBoundaryCellsV.SetIncludeRegionBoundaryCells(int) C++: virtual void SetIncludeRegionBoundaryCells(int _arg) If IncludeRegionBoundaryCells is ON, CreateCellLists() will also create a list of cells which intersect a given region, but are not assigned to the region. These lists are obtained with GetBoundaryCellList(). Default is OFF. GetIncludeRegionBoundaryCellsV.GetIncludeRegionBoundaryCells() -> int C++: virtual int GetIncludeRegionBoundaryCells() If IncludeRegionBoundaryCells is ON, CreateCellLists() will also create a list of cells which intersect a given region, but are not assigned to the region. These lists are obtained with GetBoundaryCellList(). Default is OFF. IncludeRegionBoundaryCellsOnV.IncludeRegionBoundaryCellsOn() C++: virtual void IncludeRegionBoundaryCellsOn() If IncludeRegionBoundaryCells is ON, CreateCellLists() will also create a list of cells which intersect a given region, but are not assigned to the region. These lists are obtained with GetBoundaryCellList(). Default is OFF. IncludeRegionBoundaryCellsOffV.IncludeRegionBoundaryCellsOff() C++: virtual void IncludeRegionBoundaryCellsOff() If IncludeRegionBoundaryCells is ON, CreateCellLists() will also create a list of cells which intersect a given region, but are not assigned to the region. These lists are obtained with GetBoundaryCellList(). Default is OFF. DeleteCellListsV.DeleteCellLists() C++: void DeleteCellLists() Free the memory used by the cell lists. GetCellListV.GetCellList(int) -> vtkIdList C++: vtkIdList *GetCellList(int regionID) Get the cell list for a region. This returns a pointer to vtkKdTree's memory, so don't free it. GetBoundaryCellListV.GetBoundaryCellList(int) -> vtkIdList C++: vtkIdList *GetBoundaryCellList(int regionID) The cell list obtained with GetCellList is the list of all cells such that their centroid is contained in the spatial region. It may also be desirable to get a list of all cells intersecting a spatial region, but with centroid in some other region. This is that list. This list is computed in CreateCellLists() if and only if IncludeRegionBoundaryCells is ON. This returns a pointer to KdTree's memory, so don't free it. GetCellListsV.GetCellLists(vtkIntArray, int, vtkIdList, vtkIdList) -> int C++: vtkIdType GetCellLists(vtkIntArray *regions, int set, vtkIdList *inRegionCells, vtkIdList *onBoundaryCells) V.GetCellLists(vtkIntArray, vtkDataSet, vtkIdList, vtkIdList) -> int C++: vtkIdType GetCellLists(vtkIntArray *regions, vtkDataSet *set, vtkIdList *inRegionCells, vtkIdList *onBoundaryCells) V.GetCellLists(vtkIntArray, vtkIdList, vtkIdList) -> int C++: vtkIdType GetCellLists(vtkIntArray *regions, vtkIdList *inRegionCells, vtkIdList *onBoundaryCells) * For a list of regions, get two cell lists. The first lists * the IDs all cells whose centroids lie in one of the regions. * The second lists the IDs of all cells that intersect the regions, * but whose centroid lies in a region not on the list. * The total number of cell IDs written to both lists is returned. * Either list pointer passed in can be nullptr, and it will be ignored. * If there are multiple data sets, you must specify which data set * you wish cell IDs for. * The caller should delete these two lists when done. This method * uses the cell lists created in CreateCellLists(). * If the cell list for any of the requested regions does not * exist, then this method will call CreateCellLists() to create * cell lists for *every* region of the k-d tree. You must remember * to DeleteCellLists() when done with all calls to this method, as * cell lists can require a great deal of memory. GetRegionContainingCellV.GetRegionContainingCell(vtkDataSet, int) -> int C++: int GetRegionContainingCell(vtkDataSet *set, vtkIdType cellID) V.GetRegionContainingCell(int, int) -> int C++: int GetRegionContainingCell(int set, vtkIdType cellID) V.GetRegionContainingCell(int) -> int C++: int GetRegionContainingCell(vtkIdType cellID) Get the id of the region containing the cell centroid. If no DataSet is specified, assume DataSet 0. If you need the region ID for every cell, use AllGetRegionContainingCell instead. It is more efficient. AllGetRegionContainingCellV.AllGetRegionContainingCell() -> (int, ...) C++: int *AllGetRegionContainingCell() Get a list (in order by data set by cell id) of the region IDs of the region containing the centroid for each cell. This is faster than calling GetRegionContainingCell for each cell in the DataSet. vtkKdTree uses this list, so don't delete it. GetRegionContainingPointV.GetRegionContainingPoint(float, float, float) -> int C++: int GetRegionContainingPoint(double x, double y, double z) Get the id of the region containing the specified location. BuildLocatorV.BuildLocator() C++: void BuildLocator() override; Create the k-d tree decomposition of the cells of the data set or data sets. Cells are assigned to k-d tree spatial regions based on the location of their centroids. ViewOrderAllRegionsInDirectionV.ViewOrderAllRegionsInDirection((float, float, float), vtkIntArray) -> int C++: int ViewOrderAllRegionsInDirection( const double directionOfProjection[3], vtkIntArray *orderedList) Given a direction of projection (typically obtained with vtkCamera::GetDirectionOfProjection()), this method, creates a list of the k-d tree region IDs in order from front to back with respect to that direction. The number of ordered regions is returned. Use this method to view order regions for cameras that use parallel projection. ViewOrderRegionsInDirectionV.ViewOrderRegionsInDirection(vtkIntArray, (float, float, float), vtkIntArray) -> int C++: int ViewOrderRegionsInDirection(vtkIntArray *regionIds, const double directionOfProjection[3], vtkIntArray *orderedList) Given a direction of projection and a list of k-d tree region IDs, this method, creates a list of the k-d tree region IDs in order from front to back with respect to that direction. The number of ordered regions is returned. Use this method to view order regions for cameras that use parallel projection. ViewOrderAllRegionsFromPositionV.ViewOrderAllRegionsFromPosition((float, float, float), vtkIntArray) -> int C++: int ViewOrderAllRegionsFromPosition( const double directionOfProjection[3], vtkIntArray *orderedList) Given a camera position (typically obtained with vtkCamera::GetPosition()), this method, creates a list of the k-d tree region IDs in order from front to back with respect to that direction. The number of ordered regions is returned. Use this method to view order regions for cameras that use perspective projection. ViewOrderRegionsFromPositionV.ViewOrderRegionsFromPosition(vtkIntArray, (float, float, float), vtkIntArray) -> int C++: int ViewOrderRegionsFromPosition(vtkIntArray *regionIds, const double directionOfProjection[3], vtkIntArray *orderedList) Given a camera position and a list of k-d tree region IDs, this method, creates a list of the k-d tree region IDs in order from front to back with respect to that direction. The number of ordered regions is returned. Use this method to view order regions for cameras that use perspective projection. BuildLocatorFromPointsV.BuildLocatorFromPoints(vtkPointSet) C++: void BuildLocatorFromPoints(vtkPointSet *pointset) V.BuildLocatorFromPoints(vtkPoints) C++: void BuildLocatorFromPoints(vtkPoints *ptArray) This is a special purpose locator that builds a k-d tree to find duplicate and near-by points. It builds the tree from one or more vtkPoints objects instead of from the cells of a vtkDataSet. This build would normally be followed by BuildMapForDuplicatePoints, FindPoint, or FindClosestPoint. Since this will build a normal k-d tree, all the region intersection queries will still work, as will most other calls except those that have "Cell" in the name. * This method works most efficiently when the point arrays are * float arrays. BuildMapForDuplicatePointsV.BuildMapForDuplicatePoints(float) -> vtkIdTypeArray C++: vtkIdTypeArray *BuildMapForDuplicatePoints(float tolerance) This call returns a mapping from the original point IDs supplied to BuildLocatorFromPoints to a subset of those IDs that is unique within the specified tolerance. If points 2, 5, and 12 are the same, then IdMap[2] = IdMap[5] = IdMap[12] = 2 (or 5 or 12). * "original point IDs" - For point IDs we start at 0 for the first * point in the first vtkPoints object, and increase by 1 for subsequent * points and subsequent vtkPoints objects. * You must have called BuildLocatorFromPoints() before calling this. * You are responsible for deleting the returned array. FindPointV.FindPoint([float, ...]) -> int C++: vtkIdType FindPoint(double *x) V.FindPoint(float, float, float) -> int C++: vtkIdType FindPoint(double x, double y, double z) Find the Id of the point that was previously supplied to BuildLocatorFromPoints(). Returns -1 if the point was not in the original array. FindClosestPointV.FindClosestPoint([float, ...], float) -> int C++: vtkIdType FindClosestPoint(double *x, double &dist2) V.FindClosestPoint(float, float, float, float) -> int C++: vtkIdType FindClosestPoint(double x, double y, double z, double &dist2) Find the Id of the point that was previously supplied to BuildLocatorFromPoints() which is closest to the given point. Set the square of the distance between the two points. FindClosestPointWithinRadiusV.FindClosestPointWithinRadius(float, (float, float, float), float) -> int C++: vtkIdType FindClosestPointWithinRadius(double radius, const double x[3], double &dist2) Given a position x and a radius r, return the id of the point closest to the point in that radius. dist2 returns the squared distance to the point. FindClosestPointInRegionV.FindClosestPointInRegion(int, [float, ...], float) -> int C++: vtkIdType FindClosestPointInRegion(int regionId, double *x, double &dist2) V.FindClosestPointInRegion(int, float, float, float, float) -> int C++: vtkIdType FindClosestPointInRegion(int regionId, double x, double y, double z, double &dist2) Find the Id of the point in the given region which is closest to the given point. Return the ID of the point, and set the square of the distance of between the points. FindPointsWithinRadiusV.FindPointsWithinRadius(float, (float, float, float), vtkIdList) C++: void FindPointsWithinRadius(double R, const double x[3], vtkIdList *result) Find all points within a specified radius R of position x. The result is not sorted in any specific manner. These methods are thread safe if BuildLocator() is directly or indirectly called from a single thread first. FindClosestNPointsV.FindClosestNPoints(int, (float, float, float), vtkIdList) C++: void FindClosestNPoints(int N, const double x[3], vtkIdList *result) Find the closest N points to a position. This returns the closest N points to a position. A faster method could be created that returned N close points to a position, but necessarily the exact N closest. The returned points are sorted from closest to farthest. These methods are thread safe if BuildLocator() is directly or indirectly called from a single thread first. GetPointsInRegionV.GetPointsInRegion(int) -> vtkIdTypeArray C++: vtkIdTypeArray *GetPointsInRegion(int regionId) Get a list of the original IDs of all points in a region. You must have called BuildLocatorFromPoints before calling this. FreeSearchStructureV.FreeSearchStructure() C++: void FreeSearchStructure() override; Delete the k-d tree data structure. Also delete any cell lists that were computed with CreateCellLists(). GenerateRepresentationV.GenerateRepresentation(int, vtkPolyData) C++: void GenerateRepresentation(int level, vtkPolyData *pd) override; V.GenerateRepresentation([int, ...], int, vtkPolyData) C++: void GenerateRepresentation(int *regionList, int len, vtkPolyData *pd) Create a polydata representation of the boundaries of the k-d tree regions. If level equals GetLevel(), the leaf nodes are represented. GenerateRepresentationUsingDataBoundsOnV.GenerateRepresentationUsingDataBoundsOn() C++: virtual void GenerateRepresentationUsingDataBoundsOn() The polydata representation of the k-d tree shows the boundaries of the k-d tree decomposition spatial regions. The data inside the regions may not occupy the entire space. To draw just the bounds of the data in the regions, set this variable ON. GenerateRepresentationUsingDataBoundsOffV.GenerateRepresentationUsingDataBoundsOff() C++: virtual void GenerateRepresentationUsingDataBoundsOff() The polydata representation of the k-d tree shows the boundaries of the k-d tree decomposition spatial regions. The data inside the regions may not occupy the entire space. To draw just the bounds of the data in the regions, set this variable ON. SetGenerateRepresentationUsingDataBoundsV.SetGenerateRepresentationUsingDataBounds(int) C++: virtual void SetGenerateRepresentationUsingDataBounds( int _arg) The polydata representation of the k-d tree shows the boundaries of the k-d tree decomposition spatial regions. The data inside the regions may not occupy the entire space. To draw just the bounds of the data in the regions, set this variable ON. GetGenerateRepresentationUsingDataBoundsV.GetGenerateRepresentationUsingDataBounds() -> int C++: virtual int GetGenerateRepresentationUsingDataBounds() The polydata representation of the k-d tree shows the boundaries of the k-d tree decomposition spatial regions. The data inside the regions may not occupy the entire space. To draw just the bounds of the data in the regions, set this variable ON. NewGeometryV.NewGeometry() -> int C++: virtual int NewGeometry() Return 1 if the geometry of the input data sets has changed since the last time the k-d tree was built. InvalidateGeometryV.InvalidateGeometry() C++: virtual void InvalidateGeometry() Forget about the last geometry used. The next call to NewGeometry will return 1. A new k-d tree will be built the next time BuildLocator is called. CopyTreeV.CopyTree(vtkKdNode) -> vtkKdNode C++: static vtkKdNode *CopyTree(vtkKdNode *kd) Create a copy of the binary tree representation of the k-d tree spatial partitioning provided. 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