X oxo__text__TEXT|#x0rd__data__DATA#%P}k__cstring__TEXT`)Q<+__compact_unwind__LDe`0h#__eh_frame__TEXTjl h2  d P$$&>UHH=H5HG)H uHH=H]ÐUH]fDUHSPHH=H5H(H uHH=H5(HHt H tH[]H=H[]fUHAVSH0HuH6HEЋFEHEHEH}ȃu\Hut^H]H=(HAtH=cHt HLcHuL1H0[A^]ÐUHAWAVSH(HuH7HED~D}HG]ԉ]؅yHHLw(HEMA)AuQHuH}t|}L}tYH=2'LAtOH=bLt}utBA9vptAvpILHu6H}1H([A^A_]ILHuHHfDUHAVSH HuH<HEDvDuHG]]y HHt H(HtD9uEt"_pHt*11H}111 HHuHcHHH [A^]UHAVSH HuH{<HEDvDuHG]]y HHt+H(Ht"D9u!Et-HHt(1.H}111HHuHHHH [A^]f.DUHAVSH HuH<HEDvDuHG]]y HHt(H(HtD9uEt*H1Ht(1.H}111HHuHHHH [A^]fUHAWAVSH(HuH=HED~D}HG]ԉ]؅y HHtaLw(MtXA)Au}utBA9vttAvtILHu6H}1H([A^A_]ILHuHHfDUHAVSH HuH=HEDvDuHG]]y HHt H(HtD9uEt"_tHt*11H}111 HHuHcHHH [A^]UHAVSH HuH=HEDvDuHG]]y HHt+H(Ht"D9u!Et-HHt(1.H}111HHuHHHH [A^]f.DUHAVSH HuH=HEDvDuHG]]y HHt(H(HtD9uEt*H1Ht(1.H}111HHuHHHH [A^]fUHAWAVSH(HuH&=HED~D}HG]ԉ]؅y HHtuLw(MtlA)AuPHuH}tRH5IH}HU}t8uLHHHuHH}1H([A^A_]@UHAWAVAUATSH8HHZHG)σk|HUH=>H}]MĉMȅyHHHHH^(HHuH}H5PHH}HU}IH5"HH}HU}IH5)HH}HU}vIH5HH}HU}UIH5GH}HU}4HEHuH}H5GH}HU}uHHLLMMPuuH H=H8[A\A]A^A_]HUH=e=H}]MĉMȅyHHHHH^(Ht|HuH}tkH5GH}HU}tQIH5GH}HU}t4uHLHHHuHH5<1H8[A\A]A^A_]f.fUHSH8^HG)ЃtHuHAHEЉ]؉U܉UyHHH_(HH5EH}HU}HHHHyHuH@HEЉ]؉U܉Uy HHtmH_(HtdHuH}tSH5jEH}HU}t9HuHHHHuHH8[]H5@1H8[]f.@UHAVSH HuHBAHEDvDuHG]]y HHtH(HtD9uHt1H}111 HHHH [A^]UHAWAVATSH0HuHxAHEDvDuHG]̉]ЅyHHLg(MA)AHuH}H5FDH}HU}twIH52DH}HU}tZIH5"DH}HU}t=uLLLIHuHcH}1H0[A\A^A_]ÐUHAWAVSH(HuH9HED~D}HG]ԉ]؅y HHtuLw(MtlA)AuPHuH}tRH5BH}HU}t8uLHHHuHH}1H([A^A_]@UHAWAVSH(HuH8HED~D}HG]ԉ]؅y HHtuLw(MtlA)AuPHuH}tRH5BH}HU}t8uLHHHuHH}1H([A^A_]w)HD)778899N:Z:::U=a=BBCCDDFFH&HxIIJJdKtKLM}NNOPQQRRSSTTUUxVV?WOWWXXX{[[,`9`aaRb_b e%evtkOrderedTriangulatorvtkCommonDataModelPython.vtkOrderedTriangulatorvtkOrderedTriangulator - helper class to generate triangulations Superclass: vtkObject This class is used to generate unique triangulations of points. The uniqueness of the triangulation is controlled by the id of the inserted points in combination with a Delaunay criterion. The class is designed to be as fast as possible (since the algorithm can be slow) and uses block memory allocations to support rapid triangulation generation. Also, the assumption behind the class is that a maximum of hundreds of points are to be triangulated. If you desire more robust triangulation methods use vtkPolygon::Triangulate(), vtkDelaunay2D, or vtkDelaunay3D. @par Background: This work is documented in the technical paper: W.J. Schroeder, B. Geveci, M. Malaterre. Compatible Triangulations of Spatial Decompositions. In Proceedings of Visualization 2004, IEEE Press October 2004. @par Background: Delaunay triangulations are unique assuming a random distribution of input points. The 3D Delaunay criterion is as follows: the circumsphere of each tetrahedron contains no other points of the triangulation except for the four points defining the tetrahedron. In application this property is hard to satisfy because objects like cubes are defined by eight points all sharing the same circumsphere (center and radius); hence the Delaunay triangulation is not unique. These so-called degenerate situations are typically resolved by arbitrary selecting a triangulation. This code does something different: it resolves degenerate triangulations by modifying the "InCircumsphere" method to use a slightly smaller radius. Hence, degenerate points are always considered "out" of the circumsphere. This, in combination with an ordering (based on id) of the input points, guarantees a unique triangulation. @par Background: There is another related characteristic of Delaunay triangulations. Given a N-dimensional Delaunay triangulation, points laying on a (N-1) dimensional plane also form a (N-1) Delaunay triangulation. This means for example, that if a 3D cell is defined by a set of (2D) planar faces, then the face triangulations are Delaunay. Combining this with the method to generate unique triangulations described previously, the triangulations on the face are guaranteed unique. This fact can be used to triangulate 3D objects in such a way to guarantee compatible face triangulations. This is a very useful fact for parallel processing, or performing operations like clipping that require compatible triangulations across 3D cell faces. (See vtkClipVolume for an example.) @par Background: A special feature of this class is that it can generate triangulation templates on the fly. If template triangulation is enabled, then the ordered triangulator will first triangulate the cell using the slower ordered Delaunay approach, and then store the result as a template. Later, if the same cell type and cell configuration is encountered, then the template is reused which greatly speeds the triangulation. @warning Duplicate vertices will be ignored, i.e., if two points have the same coordinates the second one is discarded. The implications are that the user of this class must prevent duplicate points. Because the precision of this algorithm is double, it's also a good idea to merge points that are within some epsilon of one another. @warning The triangulation is performed using the parametric coordinates of the inserted points. Therefore the bounds (see InitTriangulation()) should represent the range of the parametric coordinates of the inserted points. @sa vtkDelaunay2D vtkDelaunay3D vtkPolygon IsTypeOfV.IsTypeOf(string) -> int C++: static vtkTypeBool IsTypeOf(const char *type) Return 1 if this class type is the same type of (or a subclass of) the named class. Returns 0 otherwise. This method works in combination with vtkTypeMacro found in vtkSetGet.h. IsAV.IsA(string) -> int C++: vtkTypeBool IsA(const char *type) override; Return 1 if this class is the same type of (or a subclass of) the named class. Returns 0 otherwise. This method works in combination with vtkTypeMacro found in vtkSetGet.h. SafeDownCastV.SafeDownCast(vtkObjectBase) -> vtkOrderedTriangulator C++: static vtkOrderedTriangulator *SafeDownCast(vtkObjectBase *o) NewInstanceV.NewInstance() -> vtkOrderedTriangulator C++: vtkOrderedTriangulator *NewInstance() InitTriangulationV.InitTriangulation(float, float, float, float, float, float, int) C++: void InitTriangulation(double xmin, double xmax, double ymin, double ymax, double zmin, double zmax, int numPts) V.InitTriangulation([float, float, float, float, float, float], int) C++: void InitTriangulation(double bounds[6], int numPts) Initialize the triangulation process. Provide a bounding box and the maximum number of points to be inserted. Note that since the triangulation is performed using parametric coordinates (see InsertPoint()) the bounds should be represent the range of the parametric coordinates inserted. \post no_point_inserted: GetNumberOfPoints()==0 InsertPointV.InsertPoint(int, [float, float, float], [float, float, float], int) -> int C++: vtkIdType InsertPoint(vtkIdType id, double x[3], double p[3], int type) V.InsertPoint(int, int, [float, float, float], [float, float, float], int) -> int C++: vtkIdType InsertPoint(vtkIdType id, vtkIdType sortid, double x[3], double p[3], int type) V.InsertPoint(int, int, int, [float, float, float], [float, float, float], int) -> int C++: vtkIdType InsertPoint(vtkIdType id, vtkIdType sortid, vtkIdType sortid2, double x[3], double p[3], int type) For each point to be inserted, provide an id, a position x, parametric coordinate p, and whether the point is inside (type=0), outside (type=1), or on the boundary (type=2). You must call InitTriangulation() prior to invoking this method. Make sure that the number of points inserted does not exceed the numPts specified in InitTriangulation(). Also note that the "id" can be any integer and can be greater than numPts. It is used to create tetras (in AddTetras()) with the appropriate connectivity ids. The method returns an internal id that can be used prior to the Triangulate() method to update the type of the point with UpdatePointType(). (Note: the algorithm triangulated with the parametric coordinate p[3] and creates tetras with the global coordinate x[3]. The parametric coordinates and global coordinates may be the same.) TriangulateV.Triangulate() C++: void Triangulate() Perform the triangulation. (Complete all calls to InsertPoint() prior to invoking this method.) A special version is available when templates should be used. TemplateTriangulateV.TemplateTriangulate(int, int, int) C++: void TemplateTriangulate(int cellType, int numPts, int numEdges) Perform the triangulation. (Complete all calls to InsertPoint() prior to invoking this method.) A special version is available when templates should be used. UpdatePointTypeV.UpdatePointType(int, int) C++: void UpdatePointType(vtkIdType internalId, int type) Update the point type. This is useful when the merging of nearly coincident points is performed. The id is the internal id returned from InsertPoint(). The method should be invoked prior to the Triangulate method. The type is specified as inside (type=0), outside (type=1), or on the boundary (type=2). \pre valid_range: internalId>=0 && internalIdGetNumberOfPoints() GetPointPositionV.GetPointPosition(int) -> (float, ...) C++: double *GetPointPosition(vtkIdType internalId) Return the parametric coordinates of point `internalId'. It assumes that the point has already been inserted. The method should be invoked prior to the Triangulate method. \pre valid_range: internalId>=0 && internalIdGetNumberOfPoints() GetPointLocationV.GetPointLocation(int) -> (float, ...) C++: double *GetPointLocation(vtkIdType internalId) Return the global coordinates of point `internalId'. It assumes that the point has already been inserted. The method should be invoked prior to the Triangulate method. \pre valid_range: internalId>=0 && internalIdGetNumberOfPoints() GetPointIdV.GetPointId(int) -> int C++: vtkIdType GetPointId(vtkIdType internalId) Return the Id of point `internalId'. This id is the one passed in argument of InsertPoint. It assumes that the point has already been inserted. The method should be invoked prior to the Triangulate method. \pre valid_range: internalId>=0 && internalIdGetNumberOfPoints() GetNumberOfPointsV.GetNumberOfPoints() -> int C++: virtual int GetNumberOfPoints() Return the number of inserted points. SetUseTemplatesV.SetUseTemplates(int) C++: virtual void SetUseTemplates(int _arg) If this flag is set, then the ordered triangulator will create and use templates for the triangulation. To use templates, the TemplateTriangulate() method should be called when appropriate. (Note: the TemplateTriangulate() method works for complete (interior) cells without extra points due to intersection, etc.) GetUseTemplatesV.GetUseTemplates() -> int C++: virtual int GetUseTemplates() If this flag is set, then the ordered triangulator will create and use templates for the triangulation. To use templates, the TemplateTriangulate() method should be called when appropriate. (Note: the TemplateTriangulate() method works for complete (interior) cells without extra points due to intersection, etc.) UseTemplatesOnV.UseTemplatesOn() C++: virtual void UseTemplatesOn() If this flag is set, then the ordered triangulator will create and use templates for the triangulation. To use templates, the TemplateTriangulate() method should be called when appropriate. (Note: the TemplateTriangulate() method works for complete (interior) cells without extra points due to intersection, etc.) UseTemplatesOffV.UseTemplatesOff() C++: virtual void UseTemplatesOff() If this flag is set, then the ordered triangulator will create and use templates for the triangulation. To use templates, the TemplateTriangulate() method should be called when appropriate. (Note: the TemplateTriangulate() method works for complete (interior) cells without extra points due to intersection, etc.) SetPreSortedV.SetPreSorted(int) C++: virtual void SetPreSorted(int _arg) Boolean indicates whether the points have been pre-sorted. If pre-sorted is enabled, the points are not sorted on point id. By default, presorted is off. (The point id is defined in InsertPoint().) GetPreSortedV.GetPreSorted() -> int C++: virtual int GetPreSorted() Boolean indicates whether the points have been pre-sorted. If pre-sorted is enabled, the points are not sorted on point id. By default, presorted is off. (The point id is defined in InsertPoint().) PreSortedOnV.PreSortedOn() C++: virtual void PreSortedOn() Boolean indicates whether the points have been pre-sorted. If pre-sorted is enabled, the points are not sorted on point id. By default, presorted is off. (The point id is defined in InsertPoint().) PreSortedOffV.PreSortedOff() C++: virtual void PreSortedOff() Boolean indicates whether the points have been pre-sorted. If pre-sorted is enabled, the points are not sorted on point id. By default, presorted is off. (The point id is defined in InsertPoint().) SetUseTwoSortIdsV.SetUseTwoSortIds(int) C++: virtual void SetUseTwoSortIds(int _arg) Tells the triangulator that a second sort id is provided for each point and should also be considered when sorting. GetUseTwoSortIdsV.GetUseTwoSortIds() -> int C++: virtual int GetUseTwoSortIds() Tells the triangulator that a second sort id is provided for each point and should also be considered when sorting. UseTwoSortIdsOnV.UseTwoSortIdsOn() C++: virtual void UseTwoSortIdsOn() Tells the triangulator that a second sort id is provided for each point and should also be considered when sorting. UseTwoSortIdsOffV.UseTwoSortIdsOff() C++: virtual void UseTwoSortIdsOff() Tells the triangulator that a second sort id is provided for each point and should also be considered when sorting. GetTetrasV.GetTetras(int, vtkUnstructuredGrid) -> int C++: vtkIdType GetTetras(int classification, vtkUnstructuredGrid *ugrid) Initialize and add the tetras and points from the triangulation to the unstructured grid provided. New points are created and the mesh is allocated. (This method differs from AddTetras() in that it inserts points and cells; AddTetras only adds the tetra cells.) The tetrahdera added are of the type specified (0=inside,1=outside,2=all). Inside tetrahedron are those whose points are classified "inside" or on the "boundary." Outside tetrahedron have at least one point classified "outside." The method returns the number of tetrahedrahedron of the type requested. AddTetrasV.AddTetras(int, vtkUnstructuredGrid) -> int C++: vtkIdType AddTetras(int classification, vtkUnstructuredGrid *ugrid) V.AddTetras(int, vtkCellArray) -> int C++: vtkIdType AddTetras(int classification, vtkCellArray *connectivity) V.AddTetras(int, vtkIncrementalPointLocator, vtkCellArray, vtkPointData, vtkPointData, vtkCellData, int, vtkCellData) -> int C++: vtkIdType AddTetras(int classification, vtkIncrementalPointLocator *locator, vtkCellArray *outConnectivity, vtkPointData *inPD, vtkPointData *outPD, vtkCellData *inCD, vtkIdType cellId, vtkCellData *outCD) V.AddTetras(int, vtkIdList, vtkPoints) -> int C++: vtkIdType AddTetras(int classification, vtkIdList *ptIds, vtkPoints *pts) Add the tetras to the unstructured grid provided. The unstructured grid is assumed to have been initialized (with Allocate()) and points set (with SetPoints()). The tetrahdera added are of the type specified (0=inside,1=outside,2=all). Inside tetrahedron are those whose points are classified "inside" or on the "boundary." Outside tetrahedron have at least one point classified "outside." The method returns the number of tetrahedrahedron of the type requested. AddTrianglesV.AddTriangles(vtkCellArray) -> int C++: vtkIdType AddTriangles(vtkCellArray *connectivity) V.AddTriangles(int, vtkCellArray) -> int C++: vtkIdType AddTriangles(vtkIdType id, vtkCellArray *connectivity) Add the triangle faces classified (2=boundary) to the connectivity list provided. The method returns the number of triangles. InitTetraTraversalV.InitTetraTraversal() C++: void InitTetraTraversal() Methods to get one tetra at a time. Start with InitTetraTraversal() and then invoke GetNextTetra() until the method returns 0. GetNextTetraV.GetNextTetra(int, vtkTetra, vtkDataArray, vtkDoubleArray) -> int C++: int GetNextTetra(int classification, vtkTetra *tet, vtkDataArray *cellScalars, vtkDoubleArray *tetScalars) Methods to get one tetra at a time. Start with InitTetraTraversal() and then invoke GetNextTetra() until the method returns 0. cellScalars are point-centered scalars on the original cell. tetScalars are point-centered scalars on the tetra: the values will be copied from cellScalars. \pre tet_exists: tet!=0 \pre cellScalars_exists: cellScalars!=0 \pre tetScalars_exists: tetScalars!=0 \pre tetScalars_valid_size: tetScalars->GetNumberOfTuples()==4 vtkObjectvtkObjectBasep_voidvtkUnstructuredGrid@iV *vtkUnstructuredGrid@iV *vtkCellArrayvtkCellArrayvtkIncrementalPointLocatorvtkPointDatavtkCellDatavtkIdListvtkPointsvtkTetravtkDataArrayvtkDoubleArrayOP `!a!`!`0 ! aaaPa a!a`!!!a`!!!a`!!!aPXB0 !  !a"azRx $ȕOAC $D AC $lؕAC B$@AC G$ȖAC I$AC G$ 8AC G$4AC H$\AC H$AC G$AC I$AC I$hAC I$$AC I$LAC I$t@AC G$ȥAC I$AC G$AC G$AC G$<(AC I$dAC G$hAC G$AC G$AC I$@AC G$,ȫAC G$T`AC G$|AC I,AC M$BAC E$AC G,$AC K$TpAC I$|AC Ik#@-V#)-I#'-A#\--#A- ##F-"B-""@-")-y"'-q"]-]"A-P"E"F-"B-!!@-!(-!'-!S-!A-|!l!A-_!O!A-B!3!F-!B-  == @- '- Y-l B-B  ?-  )-'-R-A-G-B-t'-lQ-WA-J*B-?-)-'-_-A-xhA-[PF-.B-K-^-A-G-A-t`A-S?A-2A-A-F-B-;@-&)-'-`-A-F-B-k==_'-O@-7'- B-=='-@-z'-LB-"(-'-@-'-B-rQ==E'-'@- '-F-B-k==_'-O@-7'- B-=='-@-z'-LB-"(-'-@-'-B-rQ==E'-'@- '-F-B-k==_'-O@-7'- B-=='-@-z'-LB-"(-'-@-'-B-rW==K'--@-'-F-B-f(-Y'-G@-/'- B-@-)-'-L-G-^B-4==@-/-I-'-U-G-B-dG==3@-/-I-'-V-G-B-b@-J==>'-9T-&F-G-B-@-q==e'-`Z-KF-:F-)F- B-  == @- '- P-l B-B ! 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