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11ReplaceInOnEv_ZN17vtkImageThreshold11SetOutValueEd_ZN17vtkImageThreshold10SetInValueEd_ZN17vtkImageThreshold16ThresholdByUpperEd_ZN17vtkImageThreshold16ThresholdByLowerEd_ZN17vtkImageThreshold16ThresholdBetweenEddPyvtkImageThreshold_ClassNewPyVTKAddFile_vtkImageThreshold_ZN23vtkImageTranslateExtent14SetTranslationEiii_ZN23vtkImageTranslateExtent14GetTranslationEv_ZN23vtkImageTranslateExtent3NewEv_ZNK23vtkImageTranslateExtent19NewInstanceInternalEv_ZN23vtkImageTranslateExtent3IsAEPKc_ZN23vtkImageTranslateExtent14SetTranslationEPiPyvtkImageTranslateExtent_ClassNewPyVTKAddFile_vtkImageTranslateExtent_ZN15vtkImageWrapPad3NewEv_ZNK15vtkImageWrapPad19NewInstanceInternalEv_ZN15vtkImageWrapPad3IsAEPKcPyvtkImageWrapPad_ClassNewPyVTKAddFile_vtkImageWrapPad_ZN19vtkRTAnalyticSource14GetWholeExtentEv_ZN19vtkRTAnalyticSource9SetCenterEddd_ZN19vtkRTAnalyticSource9GetCenterEv_ZN19vtkRTAnalyticSource10SetMaximumEd_ZN19vtkRTAnalyticSource10GetMaximumEv_ZN19vtkRTAnalyticSource20SetStandardDeviationEd_ZN19vtkRTAnalyticSource20GetStandardDeviationEv_ZN19vtkRTAnalyticSource8SetXFreqEd_ZN19vtkRTAnalyticSource8GetXFreqEv_ZN19vtkRTAnalyticSource8SetYFreqEd_ZN19vtkRTAnalyticSource8GetYFreqEv_ZN19vtkRTAnalyticSource8SetZFreqEd_ZN19vtkRTAnalyticSource8GetZFreqEv_ZN19vtkRTAnalyticSource7SetXMagEd_ZN19vtkRTAnalyticSource7GetXMagEv_ZN19vtkRTAnalyticSource7SetYMagEd_ZN19vtkRTAnalyticSource7GetYMagEv_ZN19vtkRTAnalyticSource7SetZMagEd_ZN19vtkRTAnalyticSource7GetZMagEv_ZN19vtkRTAnalyticSource16SetSubsampleRateEi_ZN19vtkRTAnalyticSource16GetSubsampleRateEv_ZN19vtkRTAnalyticSource3NewEv_ZNK19vtkRTAnalyticSource19NewInstanceInternalEv_ZN19vtkRTAnalyticSource3IsAEPKc_ZN19vtkRTAnalyticSource9SetCenterEPd_ZN19vtkRTAnalyticSource14SetWholeExtentEiiiiiiPyvtkRTAnalyticSource_ClassNewPyVTKAddFile_vtkRTAnalyticSource_ZN14vtkImageResize15SetResizeMethodEi_ZN14vtkImageResize23GetResizeMethodMinValueEv_ZN14vtkImageResize23GetResizeMethodMaxValueEv_ZN14vtkImageResize15GetResizeMethodEv_ZN14vtkImageResize19SetOutputDimensionsEiii_ZN14vtkImageResize19GetOutputDimensionsEv_ZN14vtkImageResize16SetOutputSpacingEddd_ZN14vtkImageResize16GetOutputSpacingEv_ZN14vtkImageResize23SetMagnificationFactorsEddd_ZN14vtkImageResize23GetMagnificationFactorsEv_ZN14vtkImageResize9SetBorderEi_ZN14vtkImageResize9GetBorderEv_ZN14vtkImageResize11SetCroppingEi_ZN14vtkImageResize11GetCroppingEv_ZN14vtkImageResize17SetCroppingRegionEdddddd_ZN14vtkImageResize17GetCroppingRegionEv_ZN14vtkImageResize14SetInterpolateEi_ZN14vtkImageResize14GetInterpolateEv_ZN14vtkImageResize3NewEv_ZNK14vtkImageResize19NewInstanceInternalEv_ZN14vtkImageResize3IsAEPKc_ZN14vtkImageResize13InterpolateOnEv_ZN14vtkImageResize14InterpolateOffEv_ZN14vtkImageResize9BorderOffEv_ZN14vtkImageResize10CroppingOnEv_ZN14vtkImageResize11CroppingOffEv_ZN14vtkImageResize8BorderOnEv_ZN14vtkImageResize19SetOutputDimensionsEPi_ZN14vtkImageResize23SetMagnificationFactorsEPd_ZN14vtkImageResize16SetOutputSpacingEPd_ZN14vtkImageResize17SetCroppingRegionEPdPyvtkImageResize_ClassNewPyVTKAddFile_vtkImageResize_ZN14vtkImageResize8GetMTimeEv_ZN14vtkImageResize15GetInterpolatorEv_ZN14vtkImageResize15SetInterpolatorEP28vtkAbstractImageInterpolator_ZN14vtkImageResize23GetResizeMethodAsStringEv_ZN27vtkImageBSplineCoefficients15SetSplineDegreeEi_ZN27vtkImageBSplineCoefficients23GetSplineDegreeMinValueEv_ZN27vtkImageBSplineCoefficients23GetSplineDegreeMaxValueEv_ZN27vtkImageBSplineCoefficients15GetSplineDegreeEv_ZN27vtkImageBSplineCoefficients13SetBorderModeEi_ZN27vtkImageBSplineCoefficients21GetBorderModeMinValueEv_ZN27vtkImageBSplineCoefficients21GetBorderModeMaxValueEv_ZN27vtkImageBSplineCoefficients13GetBorderModeEv_ZN27vtkImageBSplineCoefficients19SetOutputScalarTypeEi_ZN27vtkImageBSplineCoefficients27GetOutputScalarTypeMinValueEv_ZN27vtkImageBSplineCoefficients27GetOutputScalarTypeMaxValueEv_ZN27vtkImageBSplineCoefficients19GetOutputScalarTypeEv_ZN27vtkImageBSplineCoefficients9SetBypassEi_ZN27vtkImageBSplineCoefficients9GetBypassEv_ZN27vtkImageBSplineCoefficients3NewEv_ZNK27vtkImageBSplineCoefficients19NewInstanceInternalEv_ZN27vtkImageBSplineCoefficients3IsAEPKc_ZN27vtkImageBSplineCoefficients9BypassOffEv_ZN27vtkImageBSplineCoefficients8BypassOnEv_ZN27vtkImageBSplineCoefficients11CheckBoundsEPKd_ZN27vtkImageBSplineCoefficients27GetOutputScalarTypeAsStringEv_ZN27vtkImageBSplineCoefficients21GetBorderModeAsStringEv_ZN27vtkImageBSplineCoefficients8EvaluateEddd_ZN27vtkImageBSplineCoefficients8EvaluateEPKdPdPyvtkImageBSplineCoefficients_ClassNewPyVTKAddFile_vtkImageBSplineCoefficients_ZN19vtkImageStencilData17GetDataObjectTypeEv_ZN19vtkImageStencilData13GetExtentTypeEv_ZN19vtkImageStencilData10SetSpacingEddd_ZN19vtkImageStencilData10GetSpacingEv_ZN19vtkImageStencilData9SetOriginEddd_ZN19vtkImageStencilData9GetOriginEv_ZN19vtkImageStencilData9GetExtentEv_ZN19vtkImageStencilData3NewEv_ZNK19vtkImageStencilData19NewInstanceInternalEv_ZN19vtkImageStencilData7GetDataEP14vtkInformation_ZN19vtkImageStencilData7GetDataEP20vtkInformationVectori_ZN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Source16SetOutputSpacingEPd_ZN21vtkImageStencilSource20SetOutputWholeExtentEPiPyvtkImageStencilSource_ClassNewPyVTKAddFile_vtkImageStencilSource_ZN21vtkImageStencilSource16ReportReferencesEP19vtkGarbageCollector_ZN21vtkImageStencilSource19SetInformationInputEP12vtkImageDatareal_initvtkImagingCorePythonPyModule_Create2PyModule_GetDict_Py_FatalErrorFunc_ZNSt8ios_base4InitC1Ev_ZNSt8ios_base4InitD1Ev__cxa_atexitlibvtkCommonExecutionModelPython310D-8.1.so.1libvtkImagingCore-8.1.so.1libvtkCommonDataModelPython310D-8.1.so.1libvtkCommonCorePython310D-8.1.so.1libvtkWrappingPython310Core-8.1.so.1libvtkCommonExecutionModel-8.1.so.1libvtkCommonCore-8.1.so.1libstdc++.so.6libgcc_s.so.1libc.so.6libvtkImagingCorePython310D-8.1.so.1GCC_3.0CXXABI_1.3GLIBCXX_3.4GLIBC_2.4GLIBC_2.2.5/mnt/storage/workspace/med-ubuntu-free/build/ExtProjs/VTK/lib:z 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HH5őLHtHmtH]A\HH]A\1UH@fnFdH%(HD$81HHt$HD$HGfnȉD$(fbfD$ uLHo(Ht!D$ +D$$tFH|$b1HT$8dH+%(uzH@]f.HHuϐH5HT$H|$ |$HtD$$u(HEHPpHuHHH!UH@fnFdH%(HD$81HHt$HD$HGfnȉD$(fbfD$ uLHo(Ht!D$ +D$$tFH|$R1HT$8dH+%(uzH@]f.HHuϐH5KIHT$H|$|$HtD$$u(HEH`HuHH@HH@f.f(fz"u f.zuf.z uHH@f.f(fz"u f.zuf.z uHH@fnfAnfnt$fnfAnfbfbfnflfb9tHf֗@9u9uD9uD9u9uf.H@UH=Hu]ÐHH=6'tHH=|tHH=vtH]>f.@fHVf(HpH;&ff(uDf.z"u f.zuf.z uf.@fHVf(HH;ff(uDf.z"u f.zuf.z uf.@HoVDNLL;pDF ND^f~uW9tDDD9u9uD9uD;u;u@HRDAHATH=CUHHIyHNHH5H HHHHHH HH=HeH=HHH%HMHuHHH}HH=HHmHH]HHHH]HHHH-HHHHHHHL]A\H5ےH= HHSafeDownCastvtkObjectBasevtkExtractVOIIsTypeOfGetVOIGetSampleRateGetIncludeBoundaryIncludeBoundaryOffIncludeBoundaryOnSetIncludeBoundaryNewInstanceIsASetSampleRateSetVOIvtkImageAlgorithmvtkAlgorithmvtkObjectvtkExtractVOI - select piece (e.g., volume of interest) and/or subsample structured points dataset Superclass: vtkImageAlgorithm vtkExtractVOI is a filter that selects a portion of an input structured points dataset, or subsamples an input dataset. (The selected portion of interested is referred to as the Volume Of Interest, or VOI.) The output of this filter is a structured points dataset. The filter treats input data of any topological dimension (i.e., point, line, image, or volume) and can generate output data of any topological dimension. To use this filter set the VOI ivar which are i-j-k min/max indices that specify a rectangular region in the data. (Note that these are 0-offset.) You can also specify a sampling rate to subsample the data. Typical applications of this filter are to extract a slice from a volume for image processing, subsampling large volumes to reduce data size, or extracting regions of a volume with interesting data. @sa vtkGeometryFilter vtkExtractGeometry vtkExtractGrid vtkImagingCorePython.vtkExtractVOIV.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. V.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. V.SafeDownCast(vtkObjectBase) -> vtkExtractVOI C++: static vtkExtractVOI *SafeDownCast(vtkObjectBase *o) V.NewInstance() -> vtkExtractVOI C++: vtkExtractVOI *NewInstance() V.SetVOI(int, int, int, int, int, int) C++: void SetVOI(int, int, int, int, int, int) V.SetVOI((int, int, int, int, int, int)) C++: void SetVOI(int a[6]) V.GetVOI() -> (int, int, int, int, int, int) C++: int *GetVOI() Specify i-j-k (min,max) pairs to extract. The resulting structured points dataset can be of any topological dimension (i.e., point, line, image, or volume). V.SetSampleRate(int, int, int) C++: void SetSampleRate(int, int, int) V.SetSampleRate((int, int, int)) C++: void SetSampleRate(int a[3]) V.GetSampleRate() -> (int, int, int) C++: int *GetSampleRate() Set the sampling rate in the i, j, and k directions. If the rate is > 1, then the resulting VOI will be subsampled representation of the input. For example, if the SampleRate=(2,2,2), every other point will be selected, resulting in a volume 1/8th the original size. V.SetIncludeBoundary(int) C++: virtual void SetIncludeBoundary(int _arg) Control whether to enforce that the "boundary" of the grid is output in the subsampling process. (This ivar only has effect when the SampleRate in any direction is not equal to 1.) When this ivar IncludeBoundary is on, the subsampling will always include the boundary of the grid even though the sample rate is not an even multiple of the grid dimensions. (By default IncludeBoundary is off.) V.GetIncludeBoundary() -> int C++: virtual int GetIncludeBoundary() Control whether to enforce that the "boundary" of the grid is output in the subsampling process. (This ivar only has effect when the SampleRate in any direction is not equal to 1.) When this ivar IncludeBoundary is on, the subsampling will always include the boundary of the grid even though the sample rate is not an even multiple of the grid dimensions. (By default IncludeBoundary is off.) V.IncludeBoundaryOn() C++: virtual void IncludeBoundaryOn() Control whether to enforce that the "boundary" of the grid is output in the subsampling process. (This ivar only has effect when the SampleRate in any direction is not equal to 1.) When this ivar IncludeBoundary is on, the subsampling will always include the boundary of the grid even though the sample rate is not an even multiple of the grid dimensions. (By default IncludeBoundary is off.) V.IncludeBoundaryOff() C++: virtual void IncludeBoundaryOff() Control whether to enforce that the "boundary" of the grid is output in the subsampling process. (This ivar only has effect when the SampleRate in any direction is not equal to 1.) When this ivar IncludeBoundary is on, the subsampling will always include the boundary of the grid even though the sample rate is not an even multiple of the grid dimensions. (By default IncludeBoundary is off.) vtkImageAppendComponentsGetNumberOfInputsGetInputSetInputDatavtkDataObjectReplaceNthInputConnectionvtkAlgorithmOutputvtkThreadedImageAlgorithmvtkImageAppendComponents - Collects components from two inputs into one output. Superclass: vtkThreadedImageAlgorithm vtkImageAppendComponents takes the components from two inputs and merges them into one output. If Input1 has M components, and Input2 has N components, the output will have M+N components with input1 components coming first. vtkImagingCorePython.vtkImageAppendComponentsV.SafeDownCast(vtkObjectBase) -> vtkImageAppendComponents C++: static vtkImageAppendComponents *SafeDownCast( vtkObjectBase *o) V.NewInstance() -> vtkImageAppendComponents C++: vtkImageAppendComponents *NewInstance() V.ReplaceNthInputConnection(int, vtkAlgorithmOutput) C++: virtual void ReplaceNthInputConnection(int idx, vtkAlgorithmOutput *input) Replace one of the input connections with a new input. You can only replace input connections that you previously created with AddInputConnection() or, in the case of the first input, with SetInputConnection(). V.SetInputData(int, vtkDataObject) C++: void SetInputData(int num, vtkDataObject *input) V.SetInputData(vtkDataObject) C++: void SetInputData(vtkDataObject *input) Assign a data object as input. Note that this method does not establish a pipeline connection. Use SetInputConnection() to setup a pipeline connection. V.GetInput(int) -> vtkDataObject C++: vtkDataObject *GetInput(int num) V.GetInput() -> vtkDataObject C++: vtkDataObject *GetInput() Get one input to this filter. This method is only for support of old-style pipeline connections. When writing new code you should use vtkAlgorithm::GetInputConnection(0, num). V.GetNumberOfInputs() -> int C++: int GetNumberOfInputs() Get the number of inputs to this filter. This method is only for support of old-style pipeline connections. When writing new code you should use vtkAlgorithm::GetNumberOfInputConnections(0). vtkImageBlendGetStencilGetBlendModeMinValueGetBlendModeMaxValueGetBlendModeGetCompoundThresholdSetStencilConnectionSetStencilDatavtkImageStencilDataGetOpacitySetOpacityUnknown Blend ModeGetBlendModeAsStringSetBlendModeToNormalSetBlendModeToCompoundSetCompoundThresholdSetBlendModeVTK_IMAGE_BLEND_MODE_NORMALVTK_IMAGE_BLEND_MODE_COMPOUNDvtkImageBlend - blend images together using alpha or opacity Superclass: vtkThreadedImageAlgorithm vtkImageBlend takes L, LA, RGB, or RGBA images as input and blends them according to the alpha values and/or the opacity setting for each input. The spacing, origin, extent, and number of components of the output are the same as those for the first input. If the input has an alpha component, then this component is copied unchanged into the output. In addition, if the first input has either one component or two components i.e. if it is either L (greyscale) or LA (greyscale + alpha) then all other inputs must also be L or LA. Different blending modes are available: Normal (default) : This is the standard blending mode used by OpenGL and other graphics packages. The output always has the same number of components and the same extent as the first input. The alpha value of the first input is not used in the blending computation, instead it is copied directly to the output. output <- input[0] foreach input i { foreach pixel px { r <- input[i](px)(alpha) * opacity[i] f <- (255 - r) output(px) <- output(px) * f + input(px) * r } } Compound : Images are compounded together and each component is scaled by the sum of the alpha/opacity values. Use the CompoundThreshold method to set specify a threshold in compound mode. Pixels with opacity*alpha less or equal than this threshold are ignored. The alpha value of the first input, if present, is NOT copied to the alpha value of the output. The output always has the same number of components and the same extent as the first input. output <- 0 foreach pixel px { sum <- 0 foreach input i { r <- input[i](px)(alpha) * opacity(i) sum <- sum + r if r > threshold { output(px) <- output(px) + input(px) * r } } output(px) <- output(px) / sum } vtkImagingCorePython.vtkImageBlendV.SafeDownCast(vtkObjectBase) -> vtkImageBlend C++: static vtkImageBlend *SafeDownCast(vtkObjectBase *o) V.NewInstance() -> vtkImageBlend C++: vtkImageBlend *NewInstance() V.SetOpacity(int, float) C++: void SetOpacity(int idx, double opacity) Set the opacity of an input image: the alpha values of the image are multiplied by the opacity. The opacity of image idx=0 is ignored. V.GetOpacity(int) -> float C++: double GetOpacity(int idx) Set the opacity of an input image: the alpha values of the image are multiplied by the opacity. The opacity of image idx=0 is ignored. V.SetStencilConnection(vtkAlgorithmOutput) C++: void SetStencilConnection(vtkAlgorithmOutput *algOutput) Set a stencil to apply when blending the data. Create a pipeline connection. V.SetStencilData(vtkImageStencilData) C++: void SetStencilData(vtkImageStencilData *stencil) Set a stencil to apply when blending the data. V.GetStencil() -> vtkImageStencilData C++: vtkImageStencilData *GetStencil() Set a stencil to apply when blending the data. V.SetBlendMode(int) C++: virtual void SetBlendMode(int _arg) Set the blend mode V.GetBlendModeMinValue() -> int C++: virtual int GetBlendModeMinValue() Set the blend mode V.GetBlendModeMaxValue() -> int C++: virtual int GetBlendModeMaxValue() Set the blend mode V.GetBlendMode() -> int C++: virtual int GetBlendMode() Set the blend mode V.SetBlendModeToNormal() C++: void SetBlendModeToNormal() Set the blend mode V.SetBlendModeToCompound() C++: void SetBlendModeToCompound() Set the blend mode V.GetBlendModeAsString() -> string C++: const char *GetBlendModeAsString(void) Set the blend mode V.SetCompoundThreshold(float) C++: virtual void SetCompoundThreshold(double _arg) Specify a threshold in compound mode. Pixels with opacity*alpha less or equal the threshold are ignored. V.GetCompoundThreshold() -> float C++: virtual double GetCompoundThreshold() Specify a threshold in compound mode. Pixels with opacity*alpha less or equal the threshold are ignored. vtkImageCacheFilterGetCacheSizeSetCacheSizevtkImageCacheFilter - Caches multiple vtkImageData objects. Superclass: vtkImageAlgorithm vtkImageCacheFilter keep a number of vtkImageDataObjects from previous updates to satisfy future updates without needing to update the input. It does not change the data at all. It just makes the pipeline more efficient at the expense of using extra memory. vtkImagingCorePython.vtkImageCacheFilterV.SafeDownCast(vtkObjectBase) -> vtkImageCacheFilter C++: static vtkImageCacheFilter *SafeDownCast(vtkObjectBase *o) V.NewInstance() -> vtkImageCacheFilter C++: vtkImageCacheFilter *NewInstance() V.SetCacheSize(int) C++: void SetCacheSize(int size) This is the maximum number of images that can be retained in memory. it defaults to 10. V.GetCacheSize() -> int C++: int GetCacheSize() This is the maximum number of images that can be retained in memory. it defaults to 10. vtkImageCastGetClampOverflowGetOutputScalarTypeSetClampOverflowClampOverflowOffClampOverflowOnSetOutputScalarTypeToFloatSetOutputScalarTypeToIntSetOutputScalarTypeToDoubleSetOutputScalarTypeToLongSetOutputScalarTypeToCharSetOutputScalarTypeToShortSetOutputScalarTypeSetOutputScalarTypeToUnsignedShortSetOutputScalarTypeToUnsignedIntSetOutputScalarTypeToUnsignedCharSetOutputScalarTypeToUnsignedLongvtkImageCast - Image Data type Casting Filter Superclass: vtkThreadedImageAlgorithm vtkImageCast filter casts the input type to match the output type in the image processing pipeline. The filter does nothing if the input already has the correct type. To specify the "CastTo" type, use "SetOutputScalarType" method. @warning As vtkImageCast only casts values without rescaling them, its use is not recommented. vtkImageShiftScale is the recommented way to change the type of an image data. @sa vtkImageThreshold vtkImageShiftScale vtkImagingCorePython.vtkImageCastV.SafeDownCast(vtkObjectBase) -> vtkImageCast C++: static vtkImageCast *SafeDownCast(vtkObjectBase *o) V.NewInstance() -> vtkImageCast C++: vtkImageCast *NewInstance() V.SetOutputScalarType(int) C++: virtual void SetOutputScalarType(int _arg) Set the desired output scalar type to cast to. V.GetOutputScalarType() -> int C++: virtual int GetOutputScalarType() Set the desired output scalar type to cast to. V.SetOutputScalarTypeToFloat() C++: void SetOutputScalarTypeToFloat() Set the desired output scalar type to cast to. V.SetOutputScalarTypeToDouble() C++: void SetOutputScalarTypeToDouble() Set the desired output scalar type to cast to. V.SetOutputScalarTypeToInt() C++: void SetOutputScalarTypeToInt() Set the desired output scalar type to cast to. V.SetOutputScalarTypeToUnsignedInt() C++: void SetOutputScalarTypeToUnsignedInt() Set the desired output scalar type to cast to. V.SetOutputScalarTypeToLong() C++: void SetOutputScalarTypeToLong() Set the desired output scalar type to cast to. V.SetOutputScalarTypeToUnsignedLong() C++: void SetOutputScalarTypeToUnsignedLong() Set the desired output scalar type to cast to. V.SetOutputScalarTypeToShort() C++: void SetOutputScalarTypeToShort() Set the desired output scalar type to cast to. V.SetOutputScalarTypeToUnsignedShort() C++: void SetOutputScalarTypeToUnsignedShort() Set the desired output scalar type to cast to. V.SetOutputScalarTypeToUnsignedChar() C++: void SetOutputScalarTypeToUnsignedChar() Set the desired output scalar type to cast to. V.SetOutputScalarTypeToChar() C++: void SetOutputScalarTypeToChar() Set the desired output scalar type to cast to. V.SetClampOverflow(int) C++: virtual void SetClampOverflow(int _arg) When the ClampOverflow flag is on, the data is thresholded so that the output value does not exceed the max or min of the data type. Clamping is safer because otherwise you might invoke undefined behavior (and may crash) if the type conversion is out of range of the data type. On the other hand, clamping is slower. By default ClampOverflow is off. V.GetClampOverflow() -> int C++: virtual int GetClampOverflow() When the ClampOverflow flag is on, the data is thresholded so that the output value does not exceed the max or min of the data type. Clamping is safer because otherwise you might invoke undefined behavior (and may crash) if the type conversion is out of range of the data type. On the other hand, clamping is slower. By default ClampOverflow is off. V.ClampOverflowOn() C++: virtual void ClampOverflowOn() When the ClampOverflow flag is on, the data is thresholded so that the output value does not exceed the max or min of the data type. Clamping is safer because otherwise you might invoke undefined behavior (and may crash) if the type conversion is out of range of the data type. On the other hand, clamping is slower. By default ClampOverflow is off. V.ClampOverflowOff() C++: virtual void ClampOverflowOff() When the ClampOverflow flag is on, the data is thresholded so that the output value does not exceed the max or min of the data type. Clamping is safer because otherwise you might invoke undefined behavior (and may crash) if the type conversion is out of range of the data type. On the other hand, clamping is slower. By default ClampOverflow is off. vtkImageChangeInformationGetOutputOriginGetOutputSpacingGetOutputExtentStartGetExtentTranslationGetSpacingScaleGetOriginScaleGetOriginTranslationGetCenterImageSetCenterImageCenterImageOnCenterImageOffSetOriginTranslationSetOriginScaleSetSpacingScaleSetOutputOriginSetExtentTranslationSetOutputSpacingSetOutputExtentStartGetInformationInputSetInformationInputDatavtkImageDatavtkImageChangeInformation - modify spacing, origin and extent. Superclass: vtkImageAlgorithm vtkImageChangeInformation modify the spacing, origin, or extent of the data without changing the data itself. The data is not resampled by this filter, only the information accompanying the data is modified. vtkImagingCorePython.vtkImageChangeInformationV.SafeDownCast(vtkObjectBase) -> vtkImageChangeInformation C++: static vtkImageChangeInformation *SafeDownCast( vtkObjectBase *o) V.NewInstance() -> vtkImageChangeInformation C++: vtkImageChangeInformation *NewInstance() V.SetInformationInputData(vtkImageData) C++: virtual void SetInformationInputData(vtkImageData *) Copy the information from another data set. By default, the information is copied from the input. V.GetInformationInput() -> vtkImageData C++: virtual vtkImageData *GetInformationInput() Copy the information from another data set. By default, the information is copied from the input. V.SetOutputExtentStart(int, int, int) C++: void SetOutputExtentStart(int, int, int) V.SetOutputExtentStart((int, int, int)) C++: void SetOutputExtentStart(int a[3]) V.GetOutputExtentStart() -> (int, int, int) C++: int *GetOutputExtentStart() V.SetOutputSpacing(float, float, float) C++: void SetOutputSpacing(double, double, double) V.SetOutputSpacing((float, float, float)) C++: void SetOutputSpacing(double a[3]) V.GetOutputSpacing() -> (float, float, float) C++: double *GetOutputSpacing() V.SetOutputOrigin(float, float, float) C++: void SetOutputOrigin(double, double, double) V.SetOutputOrigin((float, float, float)) C++: void SetOutputOrigin(double a[3]) V.GetOutputOrigin() -> (float, float, float) C++: double *GetOutputOrigin() V.SetCenterImage(int) C++: virtual void SetCenterImage(int _arg) Set the Origin of the output so that image coordinate (0,0,0) lies at the Center of the data set. This will override SetOutputOrigin. This is often a useful operation to apply before using vtkImageReslice to apply a transformation to an image. V.CenterImageOn() C++: virtual void CenterImageOn() Set the Origin of the output so that image coordinate (0,0,0) lies at the Center of the data set. This will override SetOutputOrigin. This is often a useful operation to apply before using vtkImageReslice to apply a transformation to an image. V.CenterImageOff() C++: virtual void CenterImageOff() Set the Origin of the output so that image coordinate (0,0,0) lies at the Center of the data set. This will override SetOutputOrigin. This is often a useful operation to apply before using vtkImageReslice to apply a transformation to an image. V.GetCenterImage() -> int C++: virtual int GetCenterImage() Set the Origin of the output so that image coordinate (0,0,0) lies at the Center of the data set. This will override SetOutputOrigin. This is often a useful operation to apply before using vtkImageReslice to apply a transformation to an image. V.SetExtentTranslation(int, int, int) C++: void SetExtentTranslation(int, int, int) V.SetExtentTranslation((int, int, int)) C++: void SetExtentTranslation(int a[3]) V.GetExtentTranslation() -> (int, int, int) C++: int *GetExtentTranslation() V.SetSpacingScale(float, float, float) C++: void SetSpacingScale(double, double, double) V.SetSpacingScale((float, float, float)) C++: void SetSpacingScale(double a[3]) V.GetSpacingScale() -> (float, float, float) C++: double *GetSpacingScale() V.SetOriginTranslation(float, float, float) C++: void SetOriginTranslation(double, double, double) V.SetOriginTranslation((float, float, float)) C++: void SetOriginTranslation(double a[3]) V.GetOriginTranslation() -> (float, float, float) C++: double *GetOriginTranslation() V.SetOriginScale(float, float, float) C++: void SetOriginScale(double, double, double) V.SetOriginScale((float, float, float)) C++: void SetOriginScale(double a[3]) V.GetOriginScale() -> (float, float, float) C++: double *GetOriginScale() vtkImageClipResetOutputWholeExtentGetClipDataClipDataOffClipDataOnSetClipDataGetOutputWholeExtentSetOutputWholeExtentvtkImageClip - Reduces the image extent of the input. Superclass: vtkImageAlgorithm vtkImageClip will make an image smaller. The output must have an image extent which is the subset of the input. The filter has two modes of operation: 1: By default, the data is not copied in this filter. Only the whole extent is modified. 2: If ClipDataOn is set, then you will get no more that the clipped extent. vtkImagingCorePython.vtkImageClipV.SafeDownCast(vtkObjectBase) -> vtkImageClip C++: static vtkImageClip *SafeDownCast(vtkObjectBase *o) V.NewInstance() -> vtkImageClip C++: vtkImageClip *NewInstance() V.SetOutputWholeExtent([int, int, int, int, int, int], vtkInformation) C++: void SetOutputWholeExtent(int extent[6], vtkInformation *outInfo=nullptr) V.SetOutputWholeExtent(int, int, int, int, int, int) C++: void SetOutputWholeExtent(int minX, int maxX, int minY, int maxY, int minZ, int maxZ) The whole extent of the output has to be set explicitly. V.GetOutputWholeExtent([int, int, int, int, int, int]) C++: void GetOutputWholeExtent(int extent[6]) V.GetOutputWholeExtent() -> (int, int, int, int, int, int) C++: int *GetOutputWholeExtent() The whole extent of the output has to be set explicitly. V.ResetOutputWholeExtent() C++: void ResetOutputWholeExtent() V.SetClipData(int) C++: virtual void SetClipData(int _arg) By default, ClipData is off, and only the WholeExtent is modified. the data's extent may actually be larger. When this flag is on, the data extent will be no more than the OutputWholeExtent. V.GetClipData() -> int C++: virtual int GetClipData() By default, ClipData is off, and only the WholeExtent is modified. the data's extent may actually be larger. When this flag is on, the data extent will be no more than the OutputWholeExtent. V.ClipDataOn() C++: virtual void ClipDataOn() By default, ClipData is off, and only the WholeExtent is modified. the data's extent may actually be larger. When this flag is on, the data extent will be no more than the OutputWholeExtent. V.ClipDataOff() C++: virtual void ClipDataOff() By default, ClipData is off, and only the WholeExtent is modified. the data's extent may actually be larger. When this flag is on, the data extent will be no more than the OutputWholeExtent. vtkImageConstantPadGetConstantSetConstantvtkImagePadFiltervtkImageConstantPad - Makes image larger by padding with constant. Superclass: vtkImagePadFilter vtkImageConstantPad changes the image extent of its input. Any pixels outside of the original image extent are filled with a constant value (default is 0.0). @sa vtkImageWrapPad vtkImageMirrorPad vtkImagingCorePython.vtkImageConstantPadV.SafeDownCast(vtkObjectBase) -> vtkImageConstantPad C++: static vtkImageConstantPad *SafeDownCast(vtkObjectBase *o) V.NewInstance() -> vtkImageConstantPad C++: vtkImageConstantPad *NewInstance() V.SetConstant(float) C++: virtual void SetConstant(double _arg) Set/Get the pad value. V.GetConstant() -> float C++: virtual double GetConstant() Set/Get the pad value. vtkImageDataStreamerSetNumberOfStreamDivisionsGetNumberOfStreamDivisionsGetExtentTranslatorSetExtentTranslatorvtkExtentTranslatorvtkImageDataStreamer - Initiates streaming on image data. Superclass: vtkImageAlgorithm To satisfy a request, this filter calls update on its input many times with smaller update extents. All processing up stream streams smaller pieces. vtkImagingCorePython.vtkImageDataStreamerV.SafeDownCast(vtkObjectBase) -> vtkImageDataStreamer C++: static vtkImageDataStreamer *SafeDownCast(vtkObjectBase *o) V.NewInstance() -> vtkImageDataStreamer C++: vtkImageDataStreamer *NewInstance() V.SetNumberOfStreamDivisions(int) C++: virtual void SetNumberOfStreamDivisions(int _arg) Set how many pieces to divide the input into. void SetNumberOfStreamDivisions(int num); int GetNumberOfStreamDivisions(); V.GetNumberOfStreamDivisions() -> int C++: virtual int GetNumberOfStreamDivisions() Set how many pieces to divide the input into. void SetNumberOfStreamDivisions(int num); int GetNumberOfStreamDivisions(); V.SetExtentTranslator(vtkExtentTranslator) C++: virtual void SetExtentTranslator(vtkExtentTranslator *) Get the extent translator that will be used to split the requests V.GetExtentTranslator() -> vtkExtentTranslator C++: virtual vtkExtentTranslator *GetExtentTranslator() Get the extent translator that will be used to split the requests PermuteExtentvtkImageDecomposeFilterGetDimensionalitySetDimensionalityPermuteIncrementsvtkImageIterateFiltervtkImageDecomposeFilter - Filters that execute axes in series. Superclass: vtkImageIterateFilter This superclass molds the vtkImageIterateFilter superclass so it iterates over the axes. The filter uses dimensionality to determine how many axes to execute (starting from x). The filter also provides convenience methods for permuting information retrieved from input, output and vtkImageData. vtkImagingCorePython.vtkImageDecomposeFilterV.IsTypeOf(string) -> int C++: static vtkTypeBool IsTypeOf(const char *type) Construct an instance of vtkImageDecomposeFilter filter with default dimensionality 3. V.IsA(string) -> int C++: vtkTypeBool IsA(const char *type) override; Construct an instance of vtkImageDecomposeFilter filter with default dimensionality 3. V.SafeDownCast(vtkObjectBase) -> vtkImageDecomposeFilter C++: static vtkImageDecomposeFilter *SafeDownCast( vtkObjectBase *o) Construct an instance of vtkImageDecomposeFilter filter with default dimensionality 3. V.NewInstance() -> vtkImageDecomposeFilter C++: vtkImageDecomposeFilter *NewInstance() Construct an instance of vtkImageDecomposeFilter filter with default dimensionality 3. V.SetDimensionality(int) C++: void SetDimensionality(int dim) Dimensionality is the number of axes which are considered during execution. To process images dimensionality would be set to 2. V.GetDimensionality() -> int C++: virtual int GetDimensionality() Dimensionality is the number of axes which are considered during execution. To process images dimensionality would be set to 2. V.PermuteIncrements([int, ...], int, int, int) C++: void PermuteIncrements(vtkIdType *increments, vtkIdType &inc0, vtkIdType &inc1, vtkIdType &inc2) Private methods kept public for template execute functions. V.PermuteExtent([int, ...], int, int, int, int, int, int) C++: void PermuteExtent(int *extent, int &min0, int &max0, int &min1, int &max1, int &min2, int &max2) Private methods kept public for template execute functions. vtkImageDifferenceGetImageGetAveragingGetAllowShiftGetThresholdSetImageDataSetImageConnectionSetAveragingSetAllowShiftSetThresholdAveragingOffAllowShiftOnAveragingOnAllowShiftOffGetThresholdedErrorGetErrorvtkImageDifference - Compares images for regression tests. Superclass: vtkThreadedImageAlgorithm vtkImageDifference takes two rgb unsigned char images and compares them. It allows the images to be slightly different. If AllowShift is on, then each pixel can be shifted by one pixel. Threshold is the allowable error for each pixel. This is not a symetric filter and the difference computed is not symetric when AllowShift is on. Specifically in that case a pixel in SetImage input will be compared to the matching pixel in the input as well as to the input's eight connected neighbors. BUT... the opposite is not true. So for example if a valid image (SetImage) has a single white pixel in it, it will not find a match in the input image if the input image is black (because none of the nine suspect pixels are white). In contrast, if there is a single white pixel in the input image and the valid image (SetImage) is all black it will match with no error because all it has to do is find black pixels and even though the input image has a white pixel, its neighbors are not white. vtkImagingCorePython.vtkImageDifferenceV.SafeDownCast(vtkObjectBase) -> vtkImageDifference C++: static vtkImageDifference *SafeDownCast(vtkObjectBase *o) V.NewInstance() -> vtkImageDifference C++: vtkImageDifference *NewInstance() V.SetImageConnection(vtkAlgorithmOutput) C++: void SetImageConnection(vtkAlgorithmOutput *output) Specify the Image to compare the input to. V.SetImageData(vtkDataObject) C++: void SetImageData(vtkDataObject *image) Specify the Image to compare the input to. V.GetImage() -> vtkImageData C++: vtkImageData *GetImage() Specify the Image to compare the input to. V.GetError() -> float C++: double GetError() V.GetError([float, ...]) C++: void GetError(double *e) Return the total error in comparing the two images. V.GetThresholdedError() -> float C++: double GetThresholdedError() V.GetThresholdedError([float, ...]) C++: void GetThresholdedError(double *e) Return the total thresholded error in comparing the two images. The thresholded error is the error for a given pixel minus the threshold and clamped at a minimum of zero. V.SetThreshold(int) C++: virtual void SetThreshold(int _arg) Specify a threshold tolerance for pixel differences. V.GetThreshold() -> int C++: virtual int GetThreshold() Specify a threshold tolerance for pixel differences. V.SetAllowShift(int) C++: virtual void SetAllowShift(int _arg) Specify whether the comparison will allow a shift of one pixel between the images. If set, then the minimum difference between input images will be used to determine the difference. Otherwise, the difference is computed directly between pixels of identical row/column values. V.GetAllowShift() -> int C++: virtual int GetAllowShift() Specify whether the comparison will allow a shift of one pixel between the images. If set, then the minimum difference between input images will be used to determine the difference. Otherwise, the difference is computed directly between pixels of identical row/column values. V.AllowShiftOn() C++: virtual void AllowShiftOn() Specify whether the comparison will allow a shift of one pixel between the images. If set, then the minimum difference between input images will be used to determine the difference. Otherwise, the difference is computed directly between pixels of identical row/column values. V.AllowShiftOff() C++: virtual void AllowShiftOff() Specify whether the comparison will allow a shift of one pixel between the images. If set, then the minimum difference between input images will be used to determine the difference. Otherwise, the difference is computed directly between pixels of identical row/column values. V.SetAveraging(int) C++: virtual void SetAveraging(int _arg) Specify whether the comparison will include comparison of averaged 3x3 data between the images. For graphics renderings you normally would leave this on. For imaging operations it should be off. V.GetAveraging() -> int C++: virtual int GetAveraging() Specify whether the comparison will include comparison of averaged 3x3 data between the images. For graphics renderings you normally would leave this on. For imaging operations it should be off. V.AveragingOn() C++: virtual void AveragingOn() Specify whether the comparison will include comparison of averaged 3x3 data between the images. For graphics renderings you normally would leave this on. For imaging operations it should be off. V.AveragingOff() C++: virtual void AveragingOff() Specify whether the comparison will include comparison of averaged 3x3 data between the images. For graphics renderings you normally would leave this on. For imaging operations it should be off. vtkImageExtractComponentsGetComponentsGetNumberOfComponentsSetComponentsvtkImageExtractComponents - Outputs a single component Superclass: vtkThreadedImageAlgorithm vtkImageExtractComponents takes an input with any number of components and outputs some of them. It does involve a copy of the data. @sa vtkImageAppendComponents vtkImagingCorePython.vtkImageExtractComponentsV.SafeDownCast(vtkObjectBase) -> vtkImageExtractComponents C++: static vtkImageExtractComponents *SafeDownCast( vtkObjectBase *o) V.NewInstance() -> vtkImageExtractComponents C++: vtkImageExtractComponents *NewInstance() V.SetComponents(int) C++: void SetComponents(int c1) V.SetComponents(int, int) C++: void SetComponents(int c1, int c2) V.SetComponents(int, int, int) C++: void SetComponents(int c1, int c2, int c3) Set/Get the components to extract. V.GetComponents() -> (int, int, int) C++: int *GetComponents() V.GetNumberOfComponents() -> int C++: virtual int GetNumberOfComponents() Get the number of components to extract. This is set implicitly by the SetComponents() method. vtkImageFlipGetFlipAboutOriginGetPreserveImageExtentGetFilteredAxisGetFilteredAxesSetFilteredAxisSetFlipAboutOriginSetPreserveImageExtentFlipAboutOriginOffPreserveImageExtentOffPreserveImageExtentOnFlipAboutOriginOnSetFilteredAxesvtkImageReslicevtkImageFlip - This flips an axis of an image. Superclass: vtkImageReslice Right becomes left ... vtkImageFlip will reflect the data along the filtered axis. This filter is actually a thin wrapper around vtkImageReslice. vtkImagingCorePython.vtkImageFlipV.SafeDownCast(vtkObjectBase) -> vtkImageFlip C++: static vtkImageFlip *SafeDownCast(vtkObjectBase *o) V.NewInstance() -> vtkImageFlip C++: vtkImageFlip *NewInstance() V.SetFilteredAxis(int) C++: virtual void SetFilteredAxis(int _arg) Specify which axis will be flipped. This must be an integer between 0 (for x) and 2 (for z). Initial value is 0. V.GetFilteredAxis() -> int C++: virtual int GetFilteredAxis() Specify which axis will be flipped. This must be an integer between 0 (for x) and 2 (for z). Initial value is 0. V.SetFlipAboutOrigin(int) C++: virtual void SetFlipAboutOrigin(int _arg) By default the image will be flipped about its center, and the Origin, Spacing and Extent of the output will be identical to the input. However, if you have a coordinate system associated with the image and you want to use the flip to convert +ve values along one axis to -ve values (and vice versa) then you actually want to flip the image about coordinate (0,0,0) instead of about the center of the image. This method will adjust the Origin of the output such that the flip occurs about (0,0,0). Note that this method only changes the Origin (and hence the coordinate system) the output data: the actual pixel values are the same whether or not this method is used. Also note that the Origin in this method name refers to (0,0,0) in the coordinate system associated with the image, it does not refer to the Origin ivar that is associated with a vtkImageData. V.GetFlipAboutOrigin() -> int C++: virtual int GetFlipAboutOrigin() By default the image will be flipped about its center, and the Origin, Spacing and Extent of the output will be identical to the input. However, if you have a coordinate system associated with the image and you want to use the flip to convert +ve values along one axis to -ve values (and vice versa) then you actually want to flip the image about coordinate (0,0,0) instead of about the center of the image. This method will adjust the Origin of the output such that the flip occurs about (0,0,0). Note that this method only changes the Origin (and hence the coordinate system) the output data: the actual pixel values are the same whether or not this method is used. Also note that the Origin in this method name refers to (0,0,0) in the coordinate system associated with the image, it does not refer to the Origin ivar that is associated with a vtkImageData. V.FlipAboutOriginOn() C++: virtual void FlipAboutOriginOn() By default the image will be flipped about its center, and the Origin, Spacing and Extent of the output will be identical to the input. However, if you have a coordinate system associated with the image and you want to use the flip to convert +ve values along one axis to -ve values (and vice versa) then you actually want to flip the image about coordinate (0,0,0) instead of about the center of the image. This method will adjust the Origin of the output such that the flip occurs about (0,0,0). Note that this method only changes the Origin (and hence the coordinate system) the output data: the actual pixel values are the same whether or not this method is used. Also note that the Origin in this method name refers to (0,0,0) in the coordinate system associated with the image, it does not refer to the Origin ivar that is associated with a vtkImageData. V.FlipAboutOriginOff() C++: virtual void FlipAboutOriginOff() By default the image will be flipped about its center, and the Origin, Spacing and Extent of the output will be identical to the input. However, if you have a coordinate system associated with the image and you want to use the flip to convert +ve values along one axis to -ve values (and vice versa) then you actually want to flip the image about coordinate (0,0,0) instead of about the center of the image. This method will adjust the Origin of the output such that the flip occurs about (0,0,0). Note that this method only changes the Origin (and hence the coordinate system) the output data: the actual pixel values are the same whether or not this method is used. Also note that the Origin in this method name refers to (0,0,0) in the coordinate system associated with the image, it does not refer to the Origin ivar that is associated with a vtkImageData. V.SetFilteredAxes(int) C++: void SetFilteredAxes(int axis) Keep the mis-named Axes variations around for compatibility with old scripts. Axis is singular, not plural... V.GetFilteredAxes() -> int C++: int GetFilteredAxes() V.SetPreserveImageExtent(int) C++: virtual void SetPreserveImageExtent(int _arg) PreserveImageExtentOff wasn't covered by test scripts and its implementation was broken. It is deprecated now and it has no effect (i.e. the ImageExtent is always preserved). V.GetPreserveImageExtent() -> int C++: virtual int GetPreserveImageExtent() PreserveImageExtentOff wasn't covered by test scripts and its implementation was broken. It is deprecated now and it has no effect (i.e. the ImageExtent is always preserved). V.PreserveImageExtentOn() C++: virtual void PreserveImageExtentOn() PreserveImageExtentOff wasn't covered by test scripts and its implementation was broken. It is deprecated now and it has no effect (i.e. the ImageExtent is always preserved). V.PreserveImageExtentOff() C++: virtual void PreserveImageExtentOff() PreserveImageExtentOff wasn't covered by test scripts and its implementation was broken. It is deprecated now and it has no effect (i.e. the ImageExtent is always preserved). GetNumberOfIterationsGetIterationvtkImageIterateFilter - Multiple executes per update. Superclass: vtkThreadedImageAlgorithm vtkImageIterateFilter is a filter superclass that supports calling execute multiple times per update. The largest hack/open issue is that the input and output caches are temporarily changed to "fool" the subclasses. I believe the correct solution is to pass the in and out cache to the subclasses methods as arguments. Now the data is passes. Can the caches be passed, and data retrieved from the cache? vtkImagingCorePython.vtkImageIterateFilterV.SafeDownCast(vtkObjectBase) -> vtkImageIterateFilter C++: static vtkImageIterateFilter *SafeDownCast(vtkObjectBase *o) V.NewInstance() -> vtkImageIterateFilter C++: vtkImageIterateFilter *NewInstance() V.GetIteration() -> int C++: virtual int GetIteration() Get which iteration is current being performed. Normally the user will not access this method. V.GetNumberOfIterations() -> int C++: virtual int GetNumberOfIterations() Get which iteration is current being performed. Normally the user will not access this method. vtkImageMagnifyGetMagnificationFactorsGetInterpolateInterpolateOnInterpolateOffSetInterpolateSetMagnificationFactorsvtkImageMagnify - magnify an image by an integer value Superclass: vtkThreadedImageAlgorithm vtkImageMagnify maps each pixel of the input onto a nxmx... region of the output. Location (0,0,...) remains in the same place. The magnification occurs via pixel replication, or if Interpolate is on, by bilinear interpolation. Initially, interpolation is off and magnification factors are set to 1 in all directions. vtkImagingCorePython.vtkImageMagnifyV.SafeDownCast(vtkObjectBase) -> vtkImageMagnify C++: static vtkImageMagnify *SafeDownCast(vtkObjectBase *o) V.NewInstance() -> vtkImageMagnify C++: vtkImageMagnify *NewInstance() V.SetMagnificationFactors(int, int, int) C++: void SetMagnificationFactors(int, int, int) V.SetMagnificationFactors((int, int, int)) C++: void SetMagnificationFactors(int a[3]) V.GetMagnificationFactors() -> (int, int, int) C++: int *GetMagnificationFactors() V.SetInterpolate(int) C++: virtual void SetInterpolate(int _arg) Turn interpolation on and off (pixel replication is used when off). Initially, interpolation is off. V.GetInterpolate() -> int C++: virtual int GetInterpolate() Turn interpolation on and off (pixel replication is used when off). Initially, interpolation is off. V.InterpolateOn() C++: virtual void InterpolateOn() Turn interpolation on and off (pixel replication is used when off). Initially, interpolation is off. V.InterpolateOff() C++: virtual void InterpolateOff() Turn interpolation on and off (pixel replication is used when off). Initially, interpolation is off. vtkImageMapToColorsSetOutputFormatToLuminanceSetOutputFormatToRGBASetOutputFormatToRGBGetNaNColorGetActiveComponentGetLookupTableGetPassAlphaToOutputGetOutputFormatSetPassAlphaToOutputSetOutputFormatSetActiveComponentPassAlphaToOutputOnPassAlphaToOutputOffSetNaNColorGetMTimeSetLookupTablevtkScalarsToColorsSetOutputFormatToLuminanceAlphavtkImageMapToColors - map the input image through a lookup table Superclass: vtkThreadedImageAlgorithm The vtkImageMapToColors filter will take an input image of any valid scalar type, and map the first component of the image through a lookup table. The result is an image of type VTK_UNSIGNED_CHAR. If the lookup table is not set, or is set to nullptr, then the input data will be passed through if it is already of type VTK_UNSIGNED_CHAR. @sa vtkLookupTable vtkScalarsToColors vtkImagingCorePython.vtkImageMapToColorsV.SafeDownCast(vtkObjectBase) -> vtkImageMapToColors C++: static vtkImageMapToColors *SafeDownCast(vtkObjectBase *o) V.NewInstance() -> vtkImageMapToColors C++: vtkImageMapToColors *NewInstance() V.SetLookupTable(vtkScalarsToColors) C++: virtual void SetLookupTable(vtkScalarsToColors *) Set the lookup table. V.GetLookupTable() -> vtkScalarsToColors C++: virtual vtkScalarsToColors *GetLookupTable() Set the lookup table. V.SetOutputFormat(int) C++: virtual void SetOutputFormat(int _arg) Set the output format, the default is RGBA. V.GetOutputFormat() -> int C++: virtual int GetOutputFormat() Set the output format, the default is RGBA. V.SetOutputFormatToRGBA() C++: void SetOutputFormatToRGBA() Set the output format, the default is RGBA. V.SetOutputFormatToRGB() C++: void SetOutputFormatToRGB() Set the output format, the default is RGBA. V.SetOutputFormatToLuminanceAlpha() C++: void SetOutputFormatToLuminanceAlpha() Set the output format, the default is RGBA. V.SetOutputFormatToLuminance() C++: void SetOutputFormatToLuminance() Set the output format, the default is RGBA. V.SetActiveComponent(int) C++: virtual void SetActiveComponent(int _arg) Set the component to map for multi-component images (default: 0) V.GetActiveComponent() -> int C++: virtual int GetActiveComponent() Set the component to map for multi-component images (default: 0) V.SetPassAlphaToOutput(int) C++: virtual void SetPassAlphaToOutput(int _arg) Use the alpha component of the input when computing the alpha component of the output (useful when converting monochrome+alpha data to RGBA) V.PassAlphaToOutputOn() C++: virtual void PassAlphaToOutputOn() Use the alpha component of the input when computing the alpha component of the output (useful when converting monochrome+alpha data to RGBA) V.PassAlphaToOutputOff() C++: virtual void PassAlphaToOutputOff() Use the alpha component of the input when computing the alpha component of the output (useful when converting monochrome+alpha data to RGBA) V.GetPassAlphaToOutput() -> int C++: virtual int GetPassAlphaToOutput() Use the alpha component of the input when computing the alpha component of the output (useful when converting monochrome+alpha data to RGBA) V.GetMTime() -> int C++: vtkMTimeType GetMTime() override; We need to check the modified time of the lookup table too. V.SetNaNColor(int, int, int, int) C++: void SetNaNColor(unsigned char, unsigned char, unsigned char, unsigned char) V.SetNaNColor((int, int, int, int)) C++: void SetNaNColor(unsigned char a[4]) V.GetNaNColor() -> (int, int, int, int) C++: unsigned char *GetNaNColor() vtkImageMaskGetMaskedOutputValueLengthGetMaskAlphaMaxValueGetMaskAlphaMinValueGetMaskAlphaGetNotMaskGetMaskedOutputValuep_voidSetImageInputDataSetMaskInputDataSetInput2DataSetInput1DataSetMaskedOutputValueSetNotMaskNotMaskOffNotMaskOnSetMaskAlpha@iP *d@ddvtkImageMask - Combines a mask and an image. Superclass: vtkThreadedImageAlgorithm vtkImageMask combines a mask with an image. Non zero mask implies the output pixel will be the same as the image. If a mask pixel is zero, then the output pixel is set to "MaskedValue". The filter also has the option to pass the mask through a boolean not operation before processing the image. This reverses the passed and replaced pixels. The two inputs should have the same "WholeExtent". The mask input should be unsigned char, and the image scalar type is the same as the output scalar type. vtkImagingCorePython.vtkImageMaskV.SafeDownCast(vtkObjectBase) -> vtkImageMask C++: static vtkImageMask *SafeDownCast(vtkObjectBase *o) V.NewInstance() -> vtkImageMask C++: vtkImageMask *NewInstance() V.SetMaskedOutputValue(int, [float, ...]) C++: void SetMaskedOutputValue(int num, double *v) V.SetMaskedOutputValue(float) C++: void SetMaskedOutputValue(double v) V.SetMaskedOutputValue(float, float) C++: void SetMaskedOutputValue(double v1, double v2) V.SetMaskedOutputValue(float, float, float) C++: void SetMaskedOutputValue(double v1, double v2, double v3) SetGet the value of the output pixel replaced by mask. V.GetMaskedOutputValue() -> (float, ...) C++: double *GetMaskedOutputValue() V.GetMaskedOutputValueLength() -> int C++: int GetMaskedOutputValueLength() V.SetMaskAlpha(float) C++: virtual void SetMaskAlpha(double _arg) Set/Get the alpha blending value for the mask The input image is assumed to be at alpha = 1.0 and the mask image uses this alpha to blend using an over operator. V.GetMaskAlphaMinValue() -> float C++: virtual double GetMaskAlphaMinValue() Set/Get the alpha blending value for the mask The input image is assumed to be at alpha = 1.0 and the mask image uses this alpha to blend using an over operator. V.GetMaskAlphaMaxValue() -> float C++: virtual double GetMaskAlphaMaxValue() Set/Get the alpha blending value for the mask The input image is assumed to be at alpha = 1.0 and the mask image uses this alpha to blend using an over operator. V.GetMaskAlpha() -> float C++: virtual double GetMaskAlpha() Set/Get the alpha blending value for the mask The input image is assumed to be at alpha = 1.0 and the mask image uses this alpha to blend using an over operator. V.SetImageInputData(vtkImageData) C++: void SetImageInputData(vtkImageData *in) Set the input to be masked. V.SetMaskInputData(vtkImageData) C++: void SetMaskInputData(vtkImageData *in) Set the mask to be used. V.SetNotMask(int) C++: virtual void SetNotMask(int _arg) When Not Mask is on, the mask is passed through a boolean not before it is used to mask the image. The effect is to pass the pixels where the input mask is zero, and replace the pixels where the input value is non zero. V.GetNotMask() -> int C++: virtual int GetNotMask() When Not Mask is on, the mask is passed through a boolean not before it is used to mask the image. The effect is to pass the pixels where the input mask is zero, and replace the pixels where the input value is non zero. V.NotMaskOn() C++: virtual void NotMaskOn() When Not Mask is on, the mask is passed through a boolean not before it is used to mask the image. The effect is to pass the pixels where the input mask is zero, and replace the pixels where the input value is non zero. V.NotMaskOff() C++: virtual void NotMaskOff() When Not Mask is on, the mask is passed through a boolean not before it is used to mask the image. The effect is to pass the pixels where the input mask is zero, and replace the pixels where the input value is non zero. V.SetInput1Data(vtkDataObject) C++: virtual void SetInput1Data(vtkDataObject *in) Set the two inputs to this filter V.SetInput2Data(vtkDataObject) C++: virtual void SetInput2Data(vtkDataObject *in) ?vtkImageMirrorPadvtkImageMirrorPad - Extra pixels are filled by mirror images. Superclass: vtkImagePadFilter vtkImageMirrorPad makes an image larger by filling extra pixels with a mirror image of the original image (mirror at image boundaries). vtkImagingCorePython.vtkImageMirrorPadV.SafeDownCast(vtkObjectBase) -> vtkImageMirrorPad C++: static vtkImageMirrorPad *SafeDownCast(vtkObjectBase *o) V.NewInstance() -> vtkImageMirrorPad C++: vtkImageMirrorPad *NewInstance() GetOutputNumberOfScalarComponentsSetOutputNumberOfScalarComponentsvtkImagePadFilter - Super class for filters that fill in extra pixels. Superclass: vtkThreadedImageAlgorithm vtkImagePadFilter Changes the image extent of an image. If the image extent is larger than the input image extent, the extra pixels are filled by an algorithm determined by the subclass. The image extent of the output has to be specified. vtkImagingCorePython.vtkImagePadFilterV.SafeDownCast(vtkObjectBase) -> vtkImagePadFilter C++: static vtkImagePadFilter *SafeDownCast(vtkObjectBase *o) V.NewInstance() -> vtkImagePadFilter C++: vtkImagePadFilter *NewInstance() V.SetOutputWholeExtent([int, int, int, int, int, int]) C++: void SetOutputWholeExtent(int extent[6]) V.SetOutputWholeExtent(int, int, int, int, int, int) C++: void SetOutputWholeExtent(int minX, int maxX, int minY, int maxY, int minZ, int maxZ) The image extent of the output has to be set explicitly. V.GetOutputWholeExtent([int, int, int, int, int, int]) C++: void GetOutputWholeExtent(int extent[6]) V.GetOutputWholeExtent() -> (int, int, int, int, int, int) C++: int *GetOutputWholeExtent() The image extent of the output has to be set explicitly. V.SetOutputNumberOfScalarComponents(int) C++: virtual void SetOutputNumberOfScalarComponents(int _arg) Set/Get the number of output scalar components. V.GetOutputNumberOfScalarComponents() -> int C++: virtual int GetOutputNumberOfScalarComponents() Set/Get the number of output scalar components. vtkImagePermutevtkImagePermute - Permutes axes of input. Superclass: vtkImageReslice vtkImagePermute reorders the axes of the input. Filtered axes specify the input axes which become X, Y, Z. The input has to have the same scalar type of the output. The filter does copy the data when it executes. This filter is actually a very thin wrapper around vtkImageReslice. vtkImagingCorePython.vtkImagePermuteV.SafeDownCast(vtkObjectBase) -> vtkImagePermute C++: static vtkImagePermute *SafeDownCast(vtkObjectBase *o) V.NewInstance() -> vtkImagePermute C++: vtkImagePermute *NewInstance() V.SetFilteredAxes(int, int, int) C++: void SetFilteredAxes(int x, int y, int z) V.SetFilteredAxes((int, int, int)) C++: void SetFilteredAxes(const int xyz[3]) The filtered axes are the input axes that get relabeled to X,Y,Z. V.GetFilteredAxes() -> (int, int, int) C++: int *GetFilteredAxes() GetVoidPointervtkDataArraySpanEndIdGetIdIsInStencilNextSpanIsAtEndInitializeGetIndex@W vtkImagePointDataIteratorV|kP *vtkImageData *iV|kP *vtkDataArray *ithis function takes no keyword argumentsvtkImagePointDataIterator - iterate over point data in an image. This class will iterate over an image. For each position, it will provide the (I,J,K) index, the point Id, and if a stencil is supplied, it will report whether the point is inside or outside of the stencil. For efficiency, this class iterates over spans rather than points. Each span is one image row or partial row, defined by a start position and a size. Within a span, only the X index and the point Id will change. The vtkImagePointDataIterator and related iterators are the preferred method of iterating over image data within the VTK image filters. @sa vtkImageData vtkImageStencilData vtkImageProgressIterator vtkImagePointDataIterator() vtkImagePointDataIterator(vtkImageData *image, const int extent[6]=nullptr, vtkImageStencilData *stencil=nullptr, vtkAlgorithm *algorithm=nullptr, int threadId=0) vtkImagePointDataIterator(const &vtkImagePointDataIterator) vtkImagingCorePython.vtkImagePointDataIterator@V|PVVi *vtkImageData *i *vtkImageStencilData *vtkAlgorithmV.Initialize(vtkImageData, (int, int, int, int, int, int), vtkImageStencilData, vtkAlgorithm, int) C++: void Initialize(vtkImageData *image, const int extent[6]=nullptr, vtkImageStencilData *stencil=nullptr, vtkAlgorithm *algorithm=nullptr, int threadId=0) Initialize an iterator. See constructor for more details. V.NextSpan() C++: void NextSpan() Move the iterator to the beginning of the next span. A span is a contiguous region of the image over which nothing but the point Id and the X index changes. V.IsAtEnd() -> bool C++: bool IsAtEnd() Test if the iterator has completed iterating over the entire extent. V.IsInStencil() -> bool C++: bool IsInStencil() Check if the iterator is within the region specified by the stencil. This is updated when NextSpan() is called. V.GetIndex([int, int, int]) C++: void GetIndex(int result[3]) V.GetIndex() -> (int, int, int) C++: const int *GetIndex() Get the index at the beginning of the current span. V.GetId() -> int C++: vtkIdType GetId() Get the point Id at the beginning of the current span. V.SpanEndId() -> int C++: vtkIdType SpanEndId() Get the end of the span. V.GetVoidPointer(vtkImageData, int, [int, ...]) -> void C++: static void *GetVoidPointer(vtkImageData *image, vtkIdType i=0, int *pixelIncrement=nullptr) V.GetVoidPointer(vtkDataArray, int, [int, ...]) -> void C++: static void *GetVoidPointer(vtkDataArray *array, vtkIdType i=0, int *pixelIncrement=nullptr) Get a void pointer and pixel increment for the given point Id. The pixel increment is the number of scalar components. NextGetPosition@W vtkImagePointIteratorvtkImagePointIterator - iterate over all data points in an image. Superclass: vtkImagePointDataIterator This class will iterate over an image. For each position, it provides the (x,y,z) position, the (I,J,K) index, and the point Id. If a stencil is provided, then it also reports, for each point, whether the point is inside the stencil. The iterator can go through the image point-by-point or span-by-span. The Next() method advances to the next point, while the NextSpan() method skips to the beginning of the next span, where a span is defined as a start position and point count within an image row. @sa vtkImageData vtkImageStencilData vtkImageProgressIterator vtkImagePointIterator() vtkImagePointIterator(vtkImageData *image, const int extent[6]=nullptr, vtkImageStencilData *stencil=nullptr, vtkAlgorithm *algorithm=nullptr, int threadId=0) vtkImagePointIterator(const &vtkImagePointIterator) vtkImagingCorePython.vtkImagePointIteratorV.Next() C++: void Next() Move to the next position (rather than directly to the next span). This will automatically advance to the next span if the end of the current span is reached. V.GetPosition() -> (float, float, float) C++: double *GetPosition() V.GetPosition([float, float, float]) C++: void GetPosition(double x[3]) Get the current position. vtkImageResampleSetAxisOutputSpacingSetAxisMagnificationFactorGetAxisMagnificationFactorvtkImageResample - Resamples an image to be larger or smaller. Superclass: vtkImageReslice This filter produces an output with different spacing (and extent) than the input. Linear interpolation can be used to resample the data. The Output spacing can be set explicitly or relative to input spacing with the SetAxisMagnificationFactor method. vtkImagingCorePython.vtkImageResampleV.SafeDownCast(vtkObjectBase) -> vtkImageResample C++: static vtkImageResample *SafeDownCast(vtkObjectBase *o) V.NewInstance() -> vtkImageResample C++: vtkImageResample *NewInstance() V.SetOutputSpacing(float, float, float) C++: void SetOutputSpacing(double sx, double sy, double sz) override; V.SetOutputSpacing((float, float, float)) C++: void SetOutputSpacing(const double spacing[3]) override; Set desired spacing. Zero is a reserved value indicating spacing has not been set. V.SetAxisOutputSpacing(int, float) C++: void SetAxisOutputSpacing(int axis, double spacing) Set desired spacing. Zero is a reserved value indicating spacing has not been set. V.SetMagnificationFactors(float, float, float) C++: void SetMagnificationFactors(double fx, double fy, double fz) V.SetMagnificationFactors((float, float, float)) C++: void SetMagnificationFactors(const double f[3]) Set/Get Magnification factors. Zero is a reserved value indicating values have not been computed. V.GetMagnificationFactors() -> (float, float, float) C++: double *GetMagnificationFactors() V.SetAxisMagnificationFactor(int, float) C++: void SetAxisMagnificationFactor(int axis, double factor) Set/Get Magnification factors. Zero is a reserved value indicating values have not been computed. V.GetAxisMagnificationFactor(int, vtkInformation) -> float C++: double GetAxisMagnificationFactor(int axis, vtkInformation *inInfo=nullptr) Get the computed magnification factor for a specific axis. The input information is required to compute the value. V.SetDimensionality(int) C++: virtual void SetDimensionality(int _arg) Dimensionality is the number of axes which are considered during execution. To process images dimensionality would be set to 2. This has the same effect as setting the magnification of the third axis to 1.0 V.GetDimensionality() -> int C++: virtual int GetDimensionality() Dimensionality is the number of axes which are considered during execution. To process images dimensionality would be set to 2. This has the same effect as setting the magnification of the third axis to 1.0 SetOutputExtentToDefaultSetOutputOriginToDefaultSetOutputSpacingToDefaultGetStencilOutputGetInterpolationModeMaxValueGetSlabModeMinValueGetSlabModeMaxValueGetInterpolationModeMinValueGetBackgroundColorGetOutputExtentGetStencilOutputPortGetSlabTrapezoidIntegrationGetResliceTransformGetInterpolationModeGetMirrorGetTransformInputSamplingGetSlabModeGetGenerateStencilOutputGetWrapGetScalarScaleGetSlabNumberOfSlicesGetResliceAxesGetBorderGetAutoCropOutputGetOutputDimensionalityGetOptimizationGetSlabSliceSpacingFractionGetScalarShiftSetStencilOutputGetBackgroundLevelSetSlabModeToSumSetSlabModeToMeanSetInterpolationModeToCubicSetInterpolationModeToLinearSetSlabModeToMinSetSlabModeToMaxSetAutoCropOutputSetSlabNumberOfSlicesSetScalarShiftSetOptimizationSetOutputDimensionalitySetGenerateStencilOutputSetMirrorSetBorderSetSlabSliceSpacingFractionSetScalarScaleSetWrapSetSlabTrapezoidIntegrationSetTransformInputSamplingOptimizationOnTransformInputSamplingOffWrapOnMirrorOffAutoCropOutputOffAutoCropOutputOnSlabTrapezoidIntegrationOnBorderOffMirrorOnGenerateStencilOutputOnOptimizationOffBorderOnTransformInputSamplingOnSlabTrapezoidIntegrationOffGenerateStencilOutputOffWrapOffSetInterpolationModeSetSlabModeSetBackgroundLevelGetResliceAxesOriginSetResliceAxesOriginSetBackgroundColorReportReferencesvtkGarbageCollectorSetOutputExtentGetSlabModeAsStringGetInterpolatorSetInterpolatorvtkAbstractImageInterpolatorGetInterpolationModeAsStringSetInformationInputSetResliceTransformvtkAbstractTransformSetResliceAxesvtkMatrix4x4VTK_RESLICE_NEARESTVTK_RESLICE_LINEARVTK_RESLICE_CUBICSetInterpolationModeToNearestNeighborGetResliceAxesDirectionCosinesSetResliceAxesDirectionCosinesvtkImageReslice - Reslices a volume along a new set of axes. Superclass: vtkThreadedImageAlgorithm vtkImageReslice is the swiss-army-knife of image geometry filters: It can permute, rotate, flip, scale, resample, deform, and pad image data in any combination with reasonably high efficiency. Simple operations such as permutation, resampling and padding are done with similar efficiently to the specialized vtkImagePermute, vtkImageResample, and vtkImagePad filters. There are a number of tasks that vtkImageReslice is well suited for: 1) Application of simple rotations, scales, and translations to an image. It is often a good idea to use vtkImageChangeInformation to center the image first, so that scales and rotations occur around the center rather than around the lower-left corner of the image. 2) Resampling of one data set to match the voxel sampling of a second data set via the SetInformationInput() method, e.g. for the purpose of comparing two images or combining two images. A transformation, either linear or nonlinear, can be applied at the same time via the SetResliceTransform method if the two images are not in the same coordinate space. 3) Extraction of slices from an image volume. The most convenient way to do this is to use SetResliceAxesDirectionCosines() to specify the orientation of the slice. The direction cosines give the x, y, and z axes for the output volume. The method SetOutputDimensionality(2) is used to specify that want to output a slice rather than a volume. The SetResliceAxesOrigin() command is used to provide an (x,y,z) point that the slice will pass through. You can use both the ResliceAxes and the ResliceTransform at the same time, in order to extract slices from a volume that you have applied a transformation to. @warning This filter is very inefficient if the output X dimension is 1. @sa vtkAbstractTransform vtkMatrix4x4 vtkImagingCorePython.vtkImageResliceV.SafeDownCast(vtkObjectBase) -> vtkImageReslice C++: static vtkImageReslice *SafeDownCast(vtkObjectBase *o) V.NewInstance() -> vtkImageReslice C++: vtkImageReslice *NewInstance() V.SetResliceAxes(vtkMatrix4x4) C++: virtual void SetResliceAxes(vtkMatrix4x4 *) This method is used to set up the axes for the output voxels. The output Spacing, Origin, and Extent specify the locations of the voxels within the coordinate system defined by the axes. The ResliceAxes are used most often to permute the data, e.g. to extract ZY or XZ slices of a volume as 2D XY images. The first column of the matrix specifies the x-axis vector (the fourth element must be set to zero), the second column specifies the y-axis, and the third column the z-axis. The fourth column is the origin of the axes (the fourth element must be set to one). An alternative to SetResliceAxes() is to use SetResliceAxesDirectionCosines() to set the directions of the axes and SetResliceAxesOrigin() to set the origin of the axes. V.GetResliceAxes() -> vtkMatrix4x4 C++: virtual vtkMatrix4x4 *GetResliceAxes() This method is used to set up the axes for the output voxels. The output Spacing, Origin, and Extent specify the locations of the voxels within the coordinate system defined by the axes. The ResliceAxes are used most often to permute the data, e.g. to extract ZY or XZ slices of a volume as 2D XY images. The first column of the matrix specifies the x-axis vector (the fourth element must be set to zero), the second column specifies the y-axis, and the third column the z-axis. The fourth column is the origin of the axes (the fourth element must be set to one). An alternative to SetResliceAxes() is to use SetResliceAxesDirectionCosines() to set the directions of the axes and SetResliceAxesOrigin() to set the origin of the axes. V.SetResliceAxesDirectionCosines(float, float, float, float, float, float, float, float, float) C++: void SetResliceAxesDirectionCosines(double x0, double x1, double x2, double y0, double y1, double y2, double z0, double z1, double z2) V.SetResliceAxesDirectionCosines((float, float, float), (float, float, float), (float, float, float)) C++: void SetResliceAxesDirectionCosines(const double x[3], const double y[3], const double z[3]) V.SetResliceAxesDirectionCosines((float, float, float, float, float, float, float, float, float)) C++: void SetResliceAxesDirectionCosines(const double xyz[9]) Specify the direction cosines for the ResliceAxes (i.e. the first three elements of each of the first three columns of the ResliceAxes matrix). This will modify the current ResliceAxes matrix, or create a new matrix if none exists. V.GetResliceAxesDirectionCosines([float, float, float], [float, float, float], [float, float, float]) C++: void GetResliceAxesDirectionCosines(double x[3], double y[3], double z[3]) V.GetResliceAxesDirectionCosines([float, float, float, float, float, float, float, float, float]) C++: void GetResliceAxesDirectionCosines(double xyz[9]) V.GetResliceAxesDirectionCosines() -> (float, float, float, float, float, float, float, float, float) C++: double *GetResliceAxesDirectionCosines() Specify the direction cosines for the ResliceAxes (i.e. the first three elements of each of the first three columns of the ResliceAxes matrix). This will modify the current ResliceAxes matrix, or create a new matrix if none exists. V.SetResliceAxesOrigin(float, float, float) C++: void SetResliceAxesOrigin(double x, double y, double z) V.SetResliceAxesOrigin((float, float, float)) C++: void SetResliceAxesOrigin(const double xyz[3]) Specify the origin for the ResliceAxes (i.e. the first three elements of the final column of the ResliceAxes matrix). This will modify the current ResliceAxes matrix, or create new matrix if none exists. V.GetResliceAxesOrigin([float, float, float]) C++: void GetResliceAxesOrigin(double xyz[3]) V.GetResliceAxesOrigin() -> (float, float, float) C++: double *GetResliceAxesOrigin() Specify the origin for the ResliceAxes (i.e. the first three elements of the final column of the ResliceAxes matrix). This will modify the current ResliceAxes matrix, or create new matrix if none exists. V.SetResliceTransform(vtkAbstractTransform) C++: virtual void SetResliceTransform(vtkAbstractTransform *) Set a transform to be applied to the resampling grid that has been defined via the ResliceAxes and the output Origin, Spacing and Extent. Note that applying a transform to the resampling grid (which lies in the output coordinate system) is equivalent to applying the inverse of that transform to the input volume. Nonlinear transforms such as vtkGridTransform and vtkThinPlateSplineTransform can be used here. V.GetResliceTransform() -> vtkAbstractTransform C++: virtual vtkAbstractTransform *GetResliceTransform() Set a transform to be applied to the resampling grid that has been defined via the ResliceAxes and the output Origin, Spacing and Extent. Note that applying a transform to the resampling grid (which lies in the output coordinate system) is equivalent to applying the inverse of that transform to the input volume. Nonlinear transforms such as vtkGridTransform and vtkThinPlateSplineTransform can be used here. V.SetInformationInput(vtkImageData) C++: virtual void SetInformationInput(vtkImageData *) Set a vtkImageData from which the default Spacing, Origin, and WholeExtent of the output will be copied. The spacing, origin, and extent will be permuted according to the ResliceAxes. Any values set via SetOutputSpacing, SetOutputOrigin, and SetOutputExtent will override these values. By default, the Spacing, Origin, and WholeExtent of the Input are used. V.GetInformationInput() -> vtkImageData C++: virtual vtkImageData *GetInformationInput() Set a vtkImageData from which the default Spacing, Origin, and WholeExtent of the output will be copied. The spacing, origin, and extent will be permuted according to the ResliceAxes. Any values set via SetOutputSpacing, SetOutputOrigin, and SetOutputExtent will override these values. By default, the Spacing, Origin, and WholeExtent of the Input are used. V.SetTransformInputSampling(int) C++: virtual void SetTransformInputSampling(int _arg) Specify whether to transform the spacing, origin and extent of the Input (or the InformationInput) according to the direction cosines and origin of the ResliceAxes before applying them as the default output spacing, origin and extent (default: On). V.TransformInputSamplingOn() C++: virtual void TransformInputSamplingOn() Specify whether to transform the spacing, origin and extent of the Input (or the InformationInput) according to the direction cosines and origin of the ResliceAxes before applying them as the default output spacing, origin and extent (default: On). V.TransformInputSamplingOff() C++: virtual void TransformInputSamplingOff() Specify whether to transform the spacing, origin and extent of the Input (or the InformationInput) according to the direction cosines and origin of the ResliceAxes before applying them as the default output spacing, origin and extent (default: On). V.GetTransformInputSampling() -> int C++: virtual int GetTransformInputSampling() Specify whether to transform the spacing, origin and extent of the Input (or the InformationInput) according to the direction cosines and origin of the ResliceAxes before applying them as the default output spacing, origin and extent (default: On). V.SetAutoCropOutput(int) C++: virtual void SetAutoCropOutput(int _arg) Turn this on if you want to guarantee that the extent of the output will be large enough to ensure that none of the data will be cropped (default: Off). V.AutoCropOutputOn() C++: virtual void AutoCropOutputOn() Turn this on if you want to guarantee that the extent of the output will be large enough to ensure that none of the data will be cropped (default: Off). V.AutoCropOutputOff() C++: virtual void AutoCropOutputOff() Turn this on if you want to guarantee that the extent of the output will be large enough to ensure that none of the data will be cropped (default: Off). V.GetAutoCropOutput() -> int C++: virtual int GetAutoCropOutput() Turn this on if you want to guarantee that the extent of the output will be large enough to ensure that none of the data will be cropped (default: Off). V.SetWrap(int) C++: virtual void SetWrap(int _arg) Turn on wrap-pad feature (default: Off). V.GetWrap() -> int C++: virtual int GetWrap() Turn on wrap-pad feature (default: Off). V.WrapOn() C++: virtual void WrapOn() Turn on wrap-pad feature (default: Off). V.WrapOff() C++: virtual void WrapOff() Turn on wrap-pad feature (default: Off). V.SetMirror(int) C++: virtual void SetMirror(int _arg) Turn on mirror-pad feature (default: Off). This will override the wrap-pad. V.GetMirror() -> int C++: virtual int GetMirror() Turn on mirror-pad feature (default: Off). This will override the wrap-pad. V.MirrorOn() C++: virtual void MirrorOn() Turn on mirror-pad feature (default: Off). This will override the wrap-pad. V.MirrorOff() C++: virtual void MirrorOff() Turn on mirror-pad feature (default: Off). This will override the wrap-pad. V.SetBorder(int) C++: virtual void SetBorder(int _arg) Extend the apparent input border by a half voxel (default: On). This changes how interpolation is handled at the borders of the input image: if the center of an output voxel is beyond the edge of the input image, but is within a half voxel width of the edge (using the input voxel width), then the value of the output voxel is calculated as if the input's edge voxels were duplicated past the edges of the input. This has no effect if Mirror or Wrap are on. V.GetBorder() -> int C++: virtual int GetBorder() Extend the apparent input border by a half voxel (default: On). This changes how interpolation is handled at the borders of the input image: if the center of an output voxel is beyond the edge of the input image, but is within a half voxel width of the edge (using the input voxel width), then the value of the output voxel is calculated as if the input's edge voxels were duplicated past the edges of the input. This has no effect if Mirror or Wrap are on. V.BorderOn() C++: virtual void BorderOn() Extend the apparent input border by a half voxel (default: On). This changes how interpolation is handled at the borders of the input image: if the center of an output voxel is beyond the edge of the input image, but is within a half voxel width of the edge (using the input voxel width), then the value of the output voxel is calculated as if the input's edge voxels were duplicated past the edges of the input. This has no effect if Mirror or Wrap are on. V.BorderOff() C++: virtual void BorderOff() Extend the apparent input border by a half voxel (default: On). This changes how interpolation is handled at the borders of the input image: if the center of an output voxel is beyond the edge of the input image, but is within a half voxel width of the edge (using the input voxel width), then the value of the output voxel is calculated as if the input's edge voxels were duplicated past the edges of the input. This has no effect if Mirror or Wrap are on. V.SetInterpolationMode(int) C++: virtual void SetInterpolationMode(int _arg) Set interpolation mode (default: nearest neighbor). V.GetInterpolationModeMinValue() -> int C++: virtual int GetInterpolationModeMinValue() Set interpolation mode (default: nearest neighbor). V.GetInterpolationModeMaxValue() -> int C++: virtual int GetInterpolationModeMaxValue() Set interpolation mode (default: nearest neighbor). V.GetInterpolationMode() -> int C++: virtual int GetInterpolationMode() Set interpolation mode (default: nearest neighbor). V.SetInterpolationModeToNearestNeighbor() C++: void SetInterpolationModeToNearestNeighbor() Set interpolation mode (default: nearest neighbor). V.SetInterpolationModeToLinear() C++: void SetInterpolationModeToLinear() Set interpolation mode (default: nearest neighbor). V.SetInterpolationModeToCubic() C++: void SetInterpolationModeToCubic() Set interpolation mode (default: nearest neighbor). V.GetInterpolationModeAsString() -> string C++: virtual const char *GetInterpolationModeAsString() Set interpolation mode (default: nearest neighbor). V.SetInterpolator(vtkAbstractImageInterpolator) C++: virtual void SetInterpolator( vtkAbstractImageInterpolator *sampler) Set the interpolator to use. The default interpolator supports the Nearest, Linear, and Cubic interpolation modes. V.GetInterpolator() -> vtkAbstractImageInterpolator C++: virtual vtkAbstractImageInterpolator *GetInterpolator() Set the interpolator to use. The default interpolator supports the Nearest, Linear, and Cubic interpolation modes. V.SetSlabMode(int) C++: virtual void SetSlabMode(int _arg) Set the slab mode, for generating thick slices. The default is Mean. If SetSlabNumberOfSlices(N) is called with N greater than one, then each output slice will actually be a composite of N slices. This method specifies the compositing mode to be used. V.GetSlabModeMinValue() -> int C++: virtual int GetSlabModeMinValue() Set the slab mode, for generating thick slices. The default is Mean. If SetSlabNumberOfSlices(N) is called with N greater than one, then each output slice will actually be a composite of N slices. This method specifies the compositing mode to be used. V.GetSlabModeMaxValue() -> int C++: virtual int GetSlabModeMaxValue() Set the slab mode, for generating thick slices. The default is Mean. If SetSlabNumberOfSlices(N) is called with N greater than one, then each output slice will actually be a composite of N slices. This method specifies the compositing mode to be used. V.GetSlabMode() -> int C++: virtual int GetSlabMode() Set the slab mode, for generating thick slices. The default is Mean. If SetSlabNumberOfSlices(N) is called with N greater than one, then each output slice will actually be a composite of N slices. This method specifies the compositing mode to be used. V.SetSlabModeToMin() C++: void SetSlabModeToMin() Set the slab mode, for generating thick slices. The default is Mean. If SetSlabNumberOfSlices(N) is called with N greater than one, then each output slice will actually be a composite of N slices. This method specifies the compositing mode to be used. V.SetSlabModeToMax() C++: void SetSlabModeToMax() Set the slab mode, for generating thick slices. The default is Mean. If SetSlabNumberOfSlices(N) is called with N greater than one, then each output slice will actually be a composite of N slices. This method specifies the compositing mode to be used. V.SetSlabModeToMean() C++: void SetSlabModeToMean() Set the slab mode, for generating thick slices. The default is Mean. If SetSlabNumberOfSlices(N) is called with N greater than one, then each output slice will actually be a composite of N slices. This method specifies the compositing mode to be used. V.SetSlabModeToSum() C++: void SetSlabModeToSum() Set the slab mode, for generating thick slices. The default is Mean. If SetSlabNumberOfSlices(N) is called with N greater than one, then each output slice will actually be a composite of N slices. This method specifies the compositing mode to be used. V.GetSlabModeAsString() -> string C++: virtual const char *GetSlabModeAsString() Set the slab mode, for generating thick slices. The default is Mean. If SetSlabNumberOfSlices(N) is called with N greater than one, then each output slice will actually be a composite of N slices. This method specifies the compositing mode to be used. V.SetSlabNumberOfSlices(int) C++: virtual void SetSlabNumberOfSlices(int _arg) Set the number of slices that will be combined to create the slab. V.GetSlabNumberOfSlices() -> int C++: virtual int GetSlabNumberOfSlices() Set the number of slices that will be combined to create the slab. V.SetSlabTrapezoidIntegration(int) C++: virtual void SetSlabTrapezoidIntegration(int _arg) Use trapezoid integration for slab computation. All this does is weigh the first and last slices by half when doing sum and mean. It is off by default. V.SlabTrapezoidIntegrationOn() C++: virtual void SlabTrapezoidIntegrationOn() Use trapezoid integration for slab computation. All this does is weigh the first and last slices by half when doing sum and mean. It is off by default. V.SlabTrapezoidIntegrationOff() C++: virtual void SlabTrapezoidIntegrationOff() Use trapezoid integration for slab computation. All this does is weigh the first and last slices by half when doing sum and mean. It is off by default. V.GetSlabTrapezoidIntegration() -> int C++: virtual int GetSlabTrapezoidIntegration() Use trapezoid integration for slab computation. All this does is weigh the first and last slices by half when doing sum and mean. It is off by default. V.SetSlabSliceSpacingFraction(float) C++: virtual void SetSlabSliceSpacingFraction(double _arg) The slab spacing as a fraction of the output slice spacing. When one of the various slab modes is chosen, each output slice is produced by generating several "temporary" output slices and then combining them according to the slab mode. By default, the spacing between these temporary slices is the Z component of the OutputSpacing. This method sets the spacing between these temporary slices to be a fraction of the output spacing. V.GetSlabSliceSpacingFraction() -> float C++: virtual double GetSlabSliceSpacingFraction() The slab spacing as a fraction of the output slice spacing. When one of the various slab modes is chosen, each output slice is produced by generating several "temporary" output slices and then combining them according to the slab mode. By default, the spacing between these temporary slices is the Z component of the OutputSpacing. This method sets the spacing between these temporary slices to be a fraction of the output spacing. V.SetOptimization(int) C++: virtual void SetOptimization(int _arg) Turn on and off optimizations (default on, they should only be turned off for testing purposes). V.GetOptimization() -> int C++: virtual int GetOptimization() Turn on and off optimizations (default on, they should only be turned off for testing purposes). V.OptimizationOn() C++: virtual void OptimizationOn() Turn on and off optimizations (default on, they should only be turned off for testing purposes). V.OptimizationOff() C++: virtual void OptimizationOff() Turn on and off optimizations (default on, they should only be turned off for testing purposes). V.SetScalarShift(float) C++: virtual void SetScalarShift(double _arg) Set a value to add to all the output voxels. After a sample value has been interpolated from the input image, the equation u = (v + ScalarShift)*ScalarScale will be applied to it before it is written to the output image. The result will always be clamped to the limits of the output data type. V.GetScalarShift() -> float C++: virtual double GetScalarShift() Set a value to add to all the output voxels. After a sample value has been interpolated from the input image, the equation u = (v + ScalarShift)*ScalarScale will be applied to it before it is written to the output image. The result will always be clamped to the limits of the output data type. V.SetScalarScale(float) C++: virtual void SetScalarScale(double _arg) Set multiplication factor to apply to all the output voxels. After a sample value has been interpolated from the input image, the equation u = (v + ScalarShift)*ScalarScale will be applied to it before it is written to the output image. The result will always be clamped to the limits of the output data type. V.GetScalarScale() -> float C++: virtual double GetScalarScale() Set multiplication factor to apply to all the output voxels. After a sample value has been interpolated from the input image, the equation u = (v + ScalarShift)*ScalarScale will be applied to it before it is written to the output image. The result will always be clamped to the limits of the output data type. V.SetOutputScalarType(int) C++: virtual void SetOutputScalarType(int _arg) Set the scalar type of the output to be different from the input. The default value is -1, which means that the input scalar type will be used to set the output scalar type. Otherwise, this must be set to one of the following types: VTK_CHAR, VTK_SIGNED_CHAR, VTK_UNSIGNED_CHAR, VTK_SHORT, VTK_UNSIGNED_SHORT, VTK_INT, VTK_UNSIGNED_INT, VTK_FLOAT, or VTK_DOUBLE. Other types are not permitted. If the output type is an integer type, the output will be rounded and clamped to the limits of the type. V.GetOutputScalarType() -> int C++: virtual int GetOutputScalarType() Set the scalar type of the output to be different from the input. The default value is -1, which means that the input scalar type will be used to set the output scalar type. Otherwise, this must be set to one of the following types: VTK_CHAR, VTK_SIGNED_CHAR, VTK_UNSIGNED_CHAR, VTK_SHORT, VTK_UNSIGNED_SHORT, VTK_INT, VTK_UNSIGNED_INT, VTK_FLOAT, or VTK_DOUBLE. Other types are not permitted. If the output type is an integer type, the output will be rounded and clamped to the limits of the type. V.SetBackgroundColor(float, float, float, float) C++: void SetBackgroundColor(double, double, double, double) V.SetBackgroundColor((float, float, float, float)) C++: void SetBackgroundColor(double a[4]) V.GetBackgroundColor() -> (float, float, float, float) C++: double *GetBackgroundColor() V.SetBackgroundLevel(float) C++: void SetBackgroundLevel(double v) Set background grey level (for single-component images). V.GetBackgroundLevel() -> float C++: double GetBackgroundLevel() Set background grey level (for single-component images). V.SetOutputSpacing(float, float, float) C++: virtual void SetOutputSpacing(double x, double y, double z) V.SetOutputSpacing((float, float, float)) C++: virtual void SetOutputSpacing(const double a[3]) Set the voxel spacing for the output data. The default output spacing is the input spacing permuted through the ResliceAxes. V.SetOutputSpacingToDefault() C++: void SetOutputSpacingToDefault() Set the voxel spacing for the output data. The default output spacing is the input spacing permuted through the ResliceAxes. V.SetOutputOrigin(float, float, float) C++: virtual void SetOutputOrigin(double x, double y, double z) V.SetOutputOrigin((float, float, float)) C++: virtual void SetOutputOrigin(const double a[3]) Set the origin for the output data. The default output origin is the input origin permuted through the ResliceAxes. V.SetOutputOriginToDefault() C++: void SetOutputOriginToDefault() Set the origin for the output data. The default output origin is the input origin permuted through the ResliceAxes. V.SetOutputExtent(int, int, int, int, int, int) C++: virtual void SetOutputExtent(int a, int b, int c, int d, int e, int f) V.SetOutputExtent((int, int, int, int, int, int)) C++: virtual void SetOutputExtent(const int a[6]) Set the extent for the output data. The default output extent is the input extent permuted through the ResliceAxes. V.GetOutputExtent() -> (int, int, int, int, int, int) C++: int *GetOutputExtent() V.SetOutputExtentToDefault() C++: void SetOutputExtentToDefault() Set the extent for the output data. The default output extent is the input extent permuted through the ResliceAxes. V.SetOutputDimensionality(int) C++: virtual void SetOutputDimensionality(int _arg) Force the dimensionality of the output to either 1, 2, 3 or 0 (default: 3). If the dimensionality is 2D, then the Z extent of the output is forced to (0,0) and the Z origin of the output is forced to 0.0 (i.e. the output extent is confined to the xy plane). If the dimensionality is 1D, the output extent is confined to the x axis. For 0D, the output extent consists of a single voxel at (0,0,0). V.GetOutputDimensionality() -> int C++: virtual int GetOutputDimensionality() Force the dimensionality of the output to either 1, 2, 3 or 0 (default: 3). If the dimensionality is 2D, then the Z extent of the output is forced to (0,0) and the Z origin of the output is forced to 0.0 (i.e. the output extent is confined to the xy plane). If the dimensionality is 1D, the output extent is confined to the x axis. For 0D, the output extent consists of a single voxel at (0,0,0). V.GetMTime() -> int C++: vtkMTimeType GetMTime() override; When determining the modified time of the filter, this check the modified time of the transform and matrix. V.ReportReferences(vtkGarbageCollector) C++: void ReportReferences(vtkGarbageCollector *) override; Report object referenced by instances of this class. V.SetInterpolate(int) C++: void SetInterpolate(int t) Convenient methods for switching between nearest-neighbor and linear interpolation. InterpolateOn() is equivalent to SetInterpolationModeToLinear() and InterpolateOff() is equivalent to SetInterpolationModeToNearestNeighbor() You should not use these methods if you use the SetInterpolationMode methods. V.InterpolateOn() C++: void InterpolateOn() Convenient methods for switching between nearest-neighbor and linear interpolation. InterpolateOn() is equivalent to SetInterpolationModeToLinear() and InterpolateOff() is equivalent to SetInterpolationModeToNearestNeighbor() You should not use these methods if you use the SetInterpolationMode methods. V.InterpolateOff() C++: void InterpolateOff() Convenient methods for switching between nearest-neighbor and linear interpolation. InterpolateOn() is equivalent to SetInterpolationModeToLinear() and InterpolateOff() is equivalent to SetInterpolationModeToNearestNeighbor() You should not use these methods if you use the SetInterpolationMode methods. V.GetInterpolate() -> int C++: int GetInterpolate() Convenient methods for switching between nearest-neighbor and linear interpolation. InterpolateOn() is equivalent to SetInterpolationModeToLinear() and InterpolateOff() is equivalent to SetInterpolationModeToNearestNeighbor() You should not use these methods if you use the SetInterpolationMode methods. V.SetStencilData(vtkImageStencilData) C++: void SetStencilData(vtkImageStencilData *stencil) Use a stencil to limit the calculations to a specific region of the output. Portions of the output that are 'outside' the stencil will be cleared to the background color. V.GetStencil() -> vtkImageStencilData C++: vtkImageStencilData *GetStencil() Use a stencil to limit the calculations to a specific region of the output. Portions of the output that are 'outside' the stencil will be cleared to the background color. V.SetGenerateStencilOutput(int) C++: virtual void SetGenerateStencilOutput(int _arg) Generate an output stencil that defines which pixels were interpolated and which pixels were out-of-bounds of the input. V.GetGenerateStencilOutput() -> int C++: virtual int GetGenerateStencilOutput() Generate an output stencil that defines which pixels were interpolated and which pixels were out-of-bounds of the input. V.GenerateStencilOutputOn() C++: virtual void GenerateStencilOutputOn() Generate an output stencil that defines which pixels were interpolated and which pixels were out-of-bounds of the input. V.GenerateStencilOutputOff() C++: virtual void GenerateStencilOutputOff() Generate an output stencil that defines which pixels were interpolated and which pixels were out-of-bounds of the input. V.GetStencilOutputPort() -> vtkAlgorithmOutput C++: vtkAlgorithmOutput *GetStencilOutputPort() Get the output stencil. V.GetStencilOutput() -> vtkImageStencilData C++: vtkImageStencilData *GetStencilOutput() Get the output stencil. V.SetStencilOutput(vtkImageStencilData) C++: void SetStencilOutput(vtkImageStencilData *stencil) Get the output stencil. vtkImageResliceToColorsGetBypassBypassOffBypassOnGetOutputFormatMinValueGetOutputFormatMaxValueSetBypassvtkImageResliceToColors - Reslice and produce color scalars. Superclass: vtkImageReslice vtkImageResliceToColors is an extension of vtkImageReslice that produces color scalars. It should be provided with a lookup table that defines the output colors and the desired range of input values to map to those colors. If the input has multiple components, then you should use the SetVectorMode() method of the lookup table to specify how the vectors will be colored. If no lookup table is provided, then the input must already be color scalars, but they will be converted to the specified output format. @sa vtkImageMapToColors vtkImagingCorePython.vtkImageResliceToColorsV.SafeDownCast(vtkObjectBase) -> vtkImageResliceToColors C++: static vtkImageResliceToColors *SafeDownCast( vtkObjectBase *o) V.NewInstance() -> vtkImageResliceToColors C++: vtkImageResliceToColors *NewInstance() V.SetLookupTable(vtkScalarsToColors) C++: virtual void SetLookupTable(vtkScalarsToColors *table) Set a lookup table to apply to the data. Use the Range, VectorMode, and VectorComponents of the table to control the mapping of the input data to colors. If any output voxel is transformed to a point outside the input volume, then that voxel will be set to the BackgroundColor. V.GetLookupTable() -> vtkScalarsToColors C++: virtual vtkScalarsToColors *GetLookupTable() Set a lookup table to apply to the data. Use the Range, VectorMode, and VectorComponents of the table to control the mapping of the input data to colors. If any output voxel is transformed to a point outside the input volume, then that voxel will be set to the BackgroundColor. V.GetOutputFormatMinValue() -> int C++: virtual int GetOutputFormatMinValue() Set the output format, the default is RGBA. V.GetOutputFormatMaxValue() -> int C++: virtual int GetOutputFormatMaxValue() Set the output format, the default is RGBA. V.SetBypass(int) C++: void SetBypass(int bypass) Bypass the color mapping operation and output the scalar values directly. The output values will be float, rather than the input data type. V.BypassOn() C++: void BypassOn() V.BypassOff() C++: void BypassOff() V.GetBypass() -> int C++: int GetBypass() V.GetMTime() -> int C++: vtkMTimeType GetMTime() override; When determining the modified time of the filter, this checks the modified time of the transform and matrix. vtkImageShiftScaleGetShiftGetScaleSetShiftSetScalevtkImageShiftScale - shift and scale an input image Superclass: vtkThreadedImageAlgorithm With vtkImageShiftScale Pixels are shifted (a constant value added) and then scaled (multiplied by a scalar. As a convenience, this class allows you to set the output scalar type similar to vtkImageCast. This is because shift scale operations frequently convert data types. vtkImagingCorePython.vtkImageShiftScaleV.SafeDownCast(vtkObjectBase) -> vtkImageShiftScale C++: static vtkImageShiftScale *SafeDownCast(vtkObjectBase *o) V.NewInstance() -> vtkImageShiftScale C++: vtkImageShiftScale *NewInstance() V.SetShift(float) C++: virtual void SetShift(double _arg) Set/Get the shift value. This value is added to each pixel V.GetShift() -> float C++: virtual double GetShift() Set/Get the shift value. This value is added to each pixel V.SetScale(float) C++: virtual void SetScale(double _arg) Set/Get the scale value. Each pixel is multiplied by this value. V.GetScale() -> float C++: virtual double GetScale() Set/Get the scale value. Each pixel is multiplied by this value. V.SetOutputScalarType(int) C++: virtual void SetOutputScalarType(int _arg) Set the desired output scalar type. The result of the shift and scale operations is cast to the type specified. V.GetOutputScalarType() -> int C++: virtual int GetOutputScalarType() Set the desired output scalar type. The result of the shift and scale operations is cast to the type specified. V.SetOutputScalarTypeToDouble() C++: void SetOutputScalarTypeToDouble() Set the desired output scalar type. The result of the shift and scale operations is cast to the type specified. V.SetOutputScalarTypeToFloat() C++: void SetOutputScalarTypeToFloat() Set the desired output scalar type. The result of the shift and scale operations is cast to the type specified. V.SetOutputScalarTypeToLong() C++: void SetOutputScalarTypeToLong() Set the desired output scalar type. The result of the shift and scale operations is cast to the type specified. V.SetOutputScalarTypeToUnsignedLong() C++: void SetOutputScalarTypeToUnsignedLong() Set the desired output scalar type. The result of the shift and scale operations is cast to the type specified. V.SetOutputScalarTypeToInt() C++: void SetOutputScalarTypeToInt() Set the desired output scalar type. The result of the shift and scale operations is cast to the type specified. V.SetOutputScalarTypeToUnsignedInt() C++: void SetOutputScalarTypeToUnsignedInt() Set the desired output scalar type. The result of the shift and scale operations is cast to the type specified. V.SetOutputScalarTypeToShort() C++: void SetOutputScalarTypeToShort() Set the desired output scalar type. The result of the shift and scale operations is cast to the type specified. V.SetOutputScalarTypeToUnsignedShort() C++: void SetOutputScalarTypeToUnsignedShort() Set the desired output scalar type. The result of the shift and scale operations is cast to the type specified. V.SetOutputScalarTypeToChar() C++: void SetOutputScalarTypeToChar() Set the desired output scalar type. The result of the shift and scale operations is cast to the type specified. V.SetOutputScalarTypeToUnsignedChar() C++: void SetOutputScalarTypeToUnsignedChar() Set the desired output scalar type. The result of the shift and scale operations is cast to the type specified. V.SetClampOverflow(int) C++: virtual void SetClampOverflow(int _arg) When the ClampOverflow flag is on, the data is thresholded so that the output value does not exceed the max or min of the data type. Clamping is safer because otherwise you might invoke undefined behavior (and may crash) if the type conversion is out of range of the data type. On the other hand, clamping is slower. By default, ClampOverflow is off. V.GetClampOverflow() -> int C++: virtual int GetClampOverflow() When the ClampOverflow flag is on, the data is thresholded so that the output value does not exceed the max or min of the data type. Clamping is safer because otherwise you might invoke undefined behavior (and may crash) if the type conversion is out of range of the data type. On the other hand, clamping is slower. By default, ClampOverflow is off. V.ClampOverflowOn() C++: virtual void ClampOverflowOn() When the ClampOverflow flag is on, the data is thresholded so that the output value does not exceed the max or min of the data type. Clamping is safer because otherwise you might invoke undefined behavior (and may crash) if the type conversion is out of range of the data type. On the other hand, clamping is slower. By default, ClampOverflow is off. V.ClampOverflowOff() C++: virtual void ClampOverflowOff() When the ClampOverflow flag is on, the data is thresholded so that the output value does not exceed the max or min of the data type. Clamping is safer because otherwise you might invoke undefined behavior (and may crash) if the type conversion is out of range of the data type. On the other hand, clamping is slower. By default, ClampOverflow is off. vtkImageShrink3DGetShrinkFactorsGetMinimumGetMeanGetMedianGetMaximumMedianOnMeanOffMinimumOnMaximumOnMeanOnMedianOffMinimumOffMaximumOffSetMedianSetMaximumSetMeanSetMinimumSetShrinkFactorsvtkImageShrink3D - Subsamples an image. Superclass: vtkThreadedImageAlgorithm vtkImageShrink3D shrinks an image by sub sampling on a uniform grid (integer multiples). vtkImagingCorePython.vtkImageShrink3DV.SafeDownCast(vtkObjectBase) -> vtkImageShrink3D C++: static vtkImageShrink3D *SafeDownCast(vtkObjectBase *o) V.NewInstance() -> vtkImageShrink3D C++: vtkImageShrink3D *NewInstance() V.SetShrinkFactors(int, int, int) C++: void SetShrinkFactors(int, int, int) V.SetShrinkFactors((int, int, int)) C++: void SetShrinkFactors(int a[3]) V.GetShrinkFactors() -> (int, int, int) C++: int *GetShrinkFactors() V.SetShift(int, int, int) C++: void SetShift(int, int, int) V.SetShift((int, int, int)) C++: void SetShift(int a[3]) V.GetShift() -> (int, int, int) C++: int *GetShift() V.SetAveraging(int) C++: void SetAveraging(int) Choose Mean, Minimum, Maximum, Median or sub sampling. The neighborhood operations are not centered on the sampled pixel. This may cause a half pixel shift in your output image. You can changed "Shift" to get around this. vtkImageGaussianSmooth or vtkImageMean with strides. V.GetAveraging() -> int C++: int GetAveraging() Choose Mean, Minimum, Maximum, Median or sub sampling. The neighborhood operations are not centered on the sampled pixel. This may cause a half pixel shift in your output image. You can changed "Shift" to get around this. vtkImageGaussianSmooth or vtkImageMean with strides. V.AveragingOn() C++: virtual void AveragingOn() Choose Mean, Minimum, Maximum, Median or sub sampling. The neighborhood operations are not centered on the sampled pixel. This may cause a half pixel shift in your output image. You can changed "Shift" to get around this. vtkImageGaussianSmooth or vtkImageMean with strides. V.AveragingOff() C++: virtual void AveragingOff() Choose Mean, Minimum, Maximum, Median or sub sampling. The neighborhood operations are not centered on the sampled pixel. This may cause a half pixel shift in your output image. You can changed "Shift" to get around this. vtkImageGaussianSmooth or vtkImageMean with strides. V.SetMean(int) C++: void SetMean(int) V.GetMean() -> int C++: virtual int GetMean() V.MeanOn() C++: virtual void MeanOn() V.MeanOff() C++: virtual void MeanOff() V.SetMinimum(int) C++: void SetMinimum(int) V.GetMinimum() -> int C++: virtual int GetMinimum() V.MinimumOn() C++: virtual void MinimumOn() V.MinimumOff() C++: virtual void MinimumOff() V.SetMaximum(int) C++: void SetMaximum(int) V.GetMaximum() -> int C++: virtual int GetMaximum() V.MaximumOn() C++: virtual void MaximumOn() V.MaximumOff() C++: virtual void MaximumOff() V.SetMedian(int) C++: void SetMedian(int) V.GetMedian() -> int C++: virtual int GetMedian() V.MedianOn() C++: virtual void MedianOn() V.MedianOff() C++: virtual void MedianOff() vtkImageThresholdGetUpperThresholdGetInValueGetReplaceInGetOutValueGetLowerThresholdGetReplaceOutSetOutValueSetInValueThresholdByUpperThresholdByLowerThresholdBetweenSetReplaceOutSetReplaceInReplaceInOnReplaceOutOnReplaceOutOffReplaceInOffSetOutputScalarTypeToSignedCharvtkImageThreshold - Flexible threshold Superclass: vtkThreadedImageAlgorithm vtkImageThreshold can do binary or continuous thresholding for lower, upper or a range of data. The output data type may be different than the output, but defaults to the same type. vtkImagingCorePython.vtkImageThresholdV.SafeDownCast(vtkObjectBase) -> vtkImageThreshold C++: static vtkImageThreshold *SafeDownCast(vtkObjectBase *o) V.NewInstance() -> vtkImageThreshold C++: vtkImageThreshold *NewInstance() V.ThresholdByUpper(float) C++: void ThresholdByUpper(double thresh) The values greater than or equal to the value match. V.ThresholdByLower(float) C++: void ThresholdByLower(double thresh) The values less than or equal to the value match. V.ThresholdBetween(float, float) C++: void ThresholdBetween(double lower, double upper) The values in a range (inclusive) match V.SetReplaceIn(int) C++: virtual void SetReplaceIn(int _arg) Determines whether to replace the pixel in range with InValue V.GetReplaceIn() -> int C++: virtual int GetReplaceIn() Determines whether to replace the pixel in range with InValue V.ReplaceInOn() C++: virtual void ReplaceInOn() Determines whether to replace the pixel in range with InValue V.ReplaceInOff() C++: virtual void ReplaceInOff() Determines whether to replace the pixel in range with InValue V.SetInValue(float) C++: void SetInValue(double val) Replace the in range pixels with this value. V.GetInValue() -> float C++: virtual double GetInValue() Replace the in range pixels with this value. V.SetReplaceOut(int) C++: virtual void SetReplaceOut(int _arg) Determines whether to replace the pixel out of range with OutValue V.GetReplaceOut() -> int C++: virtual int GetReplaceOut() Determines whether to replace the pixel out of range with OutValue V.ReplaceOutOn() C++: virtual void ReplaceOutOn() Determines whether to replace the pixel out of range with OutValue V.ReplaceOutOff() C++: virtual void ReplaceOutOff() Determines whether to replace the pixel out of range with OutValue V.SetOutValue(float) C++: void SetOutValue(double val) Replace the in range pixels with this value. V.GetOutValue() -> float C++: virtual double GetOutValue() Replace the in range pixels with this value. V.GetUpperThreshold() -> float C++: virtual double GetUpperThreshold() Get the Upper and Lower thresholds. V.GetLowerThreshold() -> float C++: virtual double GetLowerThreshold() Get the Upper and Lower thresholds. V.SetOutputScalarType(int) C++: virtual void SetOutputScalarType(int _arg) Set the desired output scalar type to cast to V.GetOutputScalarType() -> int C++: virtual int GetOutputScalarType() Set the desired output scalar type to cast to V.SetOutputScalarTypeToDouble() C++: void SetOutputScalarTypeToDouble() Set the desired output scalar type to cast to V.SetOutputScalarTypeToFloat() C++: void SetOutputScalarTypeToFloat() Set the desired output scalar type to cast to V.SetOutputScalarTypeToLong() C++: void SetOutputScalarTypeToLong() Set the desired output scalar type to cast to V.SetOutputScalarTypeToUnsignedLong() C++: void SetOutputScalarTypeToUnsignedLong() Set the desired output scalar type to cast to V.SetOutputScalarTypeToInt() C++: void SetOutputScalarTypeToInt() Set the desired output scalar type to cast to V.SetOutputScalarTypeToUnsignedInt() C++: void SetOutputScalarTypeToUnsignedInt() Set the desired output scalar type to cast to V.SetOutputScalarTypeToShort() C++: void SetOutputScalarTypeToShort() Set the desired output scalar type to cast to V.SetOutputScalarTypeToUnsignedShort() C++: void SetOutputScalarTypeToUnsignedShort() Set the desired output scalar type to cast to V.SetOutputScalarTypeToChar() C++: void SetOutputScalarTypeToChar() Set the desired output scalar type to cast to V.SetOutputScalarTypeToSignedChar() C++: void SetOutputScalarTypeToSignedChar() Set the desired output scalar type to cast to V.SetOutputScalarTypeToUnsignedChar() C++: void SetOutputScalarTypeToUnsignedChar() Set the desired output scalar type to cast to vtkImageTranslateExtentGetTranslationSetTranslationvtkImageTranslateExtent - Changes extent, nothing else. Superclass: vtkImageAlgorithm vtkImageTranslateExtent shift the whole extent, but does not change the data. vtkImagingCorePython.vtkImageTranslateExtentV.SafeDownCast(vtkObjectBase) -> vtkImageTranslateExtent C++: static vtkImageTranslateExtent *SafeDownCast( vtkObjectBase *o) V.NewInstance() -> vtkImageTranslateExtent C++: vtkImageTranslateExtent *NewInstance() V.SetTranslation(int, int, int) C++: void SetTranslation(int, int, int) V.SetTranslation((int, int, int)) C++: void SetTranslation(int a[3]) V.GetTranslation() -> (int, int, int) C++: int *GetTranslation() vtkImageWrapPadvtkImageWrapPad - Makes an image larger by wrapping existing data. Superclass: vtkImagePadFilter vtkImageWrapPad performs a modulo operation on the output pixel index to determine the source input index. The new image extent of the output has to be specified. Input has to be the same scalar type as output. vtkImagingCorePython.vtkImageWrapPadV.SafeDownCast(vtkObjectBase) -> vtkImageWrapPad C++: static vtkImageWrapPad *SafeDownCast(vtkObjectBase *o) V.NewInstance() -> vtkImageWrapPad C++: vtkImageWrapPad *NewInstance() vtkRTAnalyticSourceGetWholeExtentGetCenterGetXFreqGetStandardDeviationGetZFreqGetYMagGetSubsampleRateGetYFreqGetZMagGetXMagSetSubsampleRateSetXMagSetYMagSetYFreqSetZFreqSetZMagSetStandardDeviationSetXFreqSetWholeExtentSetCentervtkRTAnalyticSource - Create an image for regression testing Superclass: vtkImageAlgorithm vtkRTAnalyticSource just produces images with pixel values determined by a Maximum*Gaussian*XMag*sin(XFreq*x)*sin(YFreq*y)*cos(ZFreq*z) Values are float scalars on point data with name "RTData". vtkImagingCorePython.vtkRTAnalyticSourceV.SafeDownCast(vtkObjectBase) -> vtkRTAnalyticSource C++: static vtkRTAnalyticSource *SafeDownCast(vtkObjectBase *o) V.NewInstance() -> vtkRTAnalyticSource C++: vtkRTAnalyticSource *NewInstance() V.SetWholeExtent(int, int, int, int, int, int) C++: void SetWholeExtent(int xMinx, int xMax, int yMin, int yMax, int zMin, int zMax) Set/Get the extent of the whole output image. Initial value is {-10,10,-10,10,-10,10} V.GetWholeExtent() -> (int, int, int, int, int, int) C++: int *GetWholeExtent() V.SetCenter(float, float, float) C++: void SetCenter(double, double, double) V.SetCenter((float, float, float)) C++: void SetCenter(double a[3]) V.GetCenter() -> (float, float, float) C++: double *GetCenter() V.SetMaximum(float) C++: virtual void SetMaximum(double _arg) Set/Get the Maximum value of the function. Initial value is 255.0. V.GetMaximum() -> float C++: virtual double GetMaximum() Set/Get the Maximum value of the function. Initial value is 255.0. V.SetStandardDeviation(float) C++: virtual void SetStandardDeviation(double _arg) Set/Get the standard deviation of the function. Initial value is 0.5. V.GetStandardDeviation() -> float C++: virtual double GetStandardDeviation() Set/Get the standard deviation of the function. Initial value is 0.5. V.SetXFreq(float) C++: virtual void SetXFreq(double _arg) Set/Get the natural frequency in x. Initial value is 60. V.GetXFreq() -> float C++: virtual double GetXFreq() Set/Get the natural frequency in x. Initial value is 60. V.SetYFreq(float) C++: virtual void SetYFreq(double _arg) Set/Get the natural frequency in y. Initial value is 30. V.GetYFreq() -> float C++: virtual double GetYFreq() Set/Get the natural frequency in y. Initial value is 30. V.SetZFreq(float) C++: virtual void SetZFreq(double _arg) Set/Get the natural frequency in z. Initial value is 40. V.GetZFreq() -> float C++: virtual double GetZFreq() Set/Get the natural frequency in z. Initial value is 40. V.SetXMag(float) C++: virtual void SetXMag(double _arg) Set/Get the magnitude in x. Initial value is 10. V.GetXMag() -> float C++: virtual double GetXMag() Set/Get the magnitude in x. Initial value is 10. V.SetYMag(float) C++: virtual void SetYMag(double _arg) Set/Get the magnitude in y. Initial value is 18. V.GetYMag() -> float C++: virtual double GetYMag() Set/Get the magnitude in y. Initial value is 18. V.SetZMag(float) C++: virtual void SetZMag(double _arg) Set/Get the magnitude in z. Initial value is 5. V.GetZMag() -> float C++: virtual double GetZMag() Set/Get the magnitude in z. Initial value is 5. V.SetSubsampleRate(int) C++: virtual void SetSubsampleRate(int _arg) Set/Get the sub-sample rate. Initial value is 1. V.GetSubsampleRate() -> int C++: virtual int GetSubsampleRate() Set/Get the sub-sample rate. Initial value is 1. vtkImageResizeGetResizeMethodMinValueGetResizeMethodMaxValueGetOutputDimensionsGetCroppingRegionGetResizeMethodGetCroppingSetCroppingCroppingOnCroppingOffSetResizeMethodSetOutputDimensionsSetCroppingRegionGetResizeMethodAsStringOUTPUT_DIMENSIONSOUTPUT_SPACINGMAGNIFICATION_FACTORSSetResizeMethodToOutputSpacingSetResizeMethodToOutputDimensionsSetResizeMethodToMagnificationFactorsvtkImageResize - High-quality image resizing filter Superclass: vtkThreadedImageAlgorithm vtkImageResize will magnify or shrink an image with interpolation and antialiasing. The resizing is done with a 5-lobe Lanczos-windowed sinc filter that is bandlimited to the output sampling frequency in order to avoid aliasing when the image size is reduced. This filter utilizes a O(n) algorithm to provide good effiency even though the filtering kernel is large. The sinc interpolator can be turned off if nearest-neighbor interpolation is required, or it can be replaced with a different vtkImageInterpolator object.@par Thanks: Thanks to David Gobbi for contributing this class to VTK. vtkImagingCorePython.vtkImageResizeV.SafeDownCast(vtkObjectBase) -> vtkImageResize C++: static vtkImageResize *SafeDownCast(vtkObjectBase *o) V.NewInstance() -> vtkImageResize C++: vtkImageResize *NewInstance() V.SetResizeMethod(int) C++: virtual void SetResizeMethod(int _arg) The resizing method to use. The default is to set the output image dimensions, and allow the filter to resize the image to these new dimensions. It is also possible to resize the image by setting the output image spacing or by setting a magnification factor. V.GetResizeMethodMinValue() -> int C++: virtual int GetResizeMethodMinValue() The resizing method to use. The default is to set the output image dimensions, and allow the filter to resize the image to these new dimensions. It is also possible to resize the image by setting the output image spacing or by setting a magnification factor. V.GetResizeMethodMaxValue() -> int C++: virtual int GetResizeMethodMaxValue() The resizing method to use. The default is to set the output image dimensions, and allow the filter to resize the image to these new dimensions. It is also possible to resize the image by setting the output image spacing or by setting a magnification factor. V.GetResizeMethod() -> int C++: virtual int GetResizeMethod() The resizing method to use. The default is to set the output image dimensions, and allow the filter to resize the image to these new dimensions. It is also possible to resize the image by setting the output image spacing or by setting a magnification factor. V.SetResizeMethodToOutputDimensions() C++: void SetResizeMethodToOutputDimensions() The resizing method to use. The default is to set the output image dimensions, and allow the filter to resize the image to these new dimensions. It is also possible to resize the image by setting the output image spacing or by setting a magnification factor. V.SetResizeMethodToOutputSpacing() C++: void SetResizeMethodToOutputSpacing() The resizing method to use. The default is to set the output image dimensions, and allow the filter to resize the image to these new dimensions. It is also possible to resize the image by setting the output image spacing or by setting a magnification factor. V.SetResizeMethodToMagnificationFactors() C++: void SetResizeMethodToMagnificationFactors() The resizing method to use. The default is to set the output image dimensions, and allow the filter to resize the image to these new dimensions. It is also possible to resize the image by setting the output image spacing or by setting a magnification factor. V.GetResizeMethodAsString() -> string C++: virtual const char *GetResizeMethodAsString() The resizing method to use. The default is to set the output image dimensions, and allow the filter to resize the image to these new dimensions. It is also possible to resize the image by setting the output image spacing or by setting a magnification factor. V.SetOutputDimensions(int, int, int) C++: void SetOutputDimensions(int, int, int) V.SetOutputDimensions((int, int, int)) C++: void SetOutputDimensions(int a[3]) V.GetOutputDimensions() -> (int, int, int) C++: int *GetOutputDimensions() V.SetMagnificationFactors(float, float, float) C++: void SetMagnificationFactors(double, double, double) V.SetMagnificationFactors((float, float, float)) C++: void SetMagnificationFactors(double a[3]) V.SetBorder(int) C++: virtual void SetBorder(int _arg) If Border is Off (the default), then the centers of each of the corner voxels will be considered to form the rectangular bounds of the image. This is the way that VTK normally computes image bounds. If Border is On, then the image bounds will be defined by the outer corners of the voxels. This setting impacts how the resizing is done. For example, if a MagnificationFactor of two is applied to a 256x256 image, the output image will be 512x512 if Border is On, or 511x511 if Border is Off. V.BorderOn() C++: virtual void BorderOn() If Border is Off (the default), then the centers of each of the corner voxels will be considered to form the rectangular bounds of the image. This is the way that VTK normally computes image bounds. If Border is On, then the image bounds will be defined by the outer corners of the voxels. This setting impacts how the resizing is done. For example, if a MagnificationFactor of two is applied to a 256x256 image, the output image will be 512x512 if Border is On, or 511x511 if Border is Off. V.BorderOff() C++: virtual void BorderOff() If Border is Off (the default), then the centers of each of the corner voxels will be considered to form the rectangular bounds of the image. This is the way that VTK normally computes image bounds. If Border is On, then the image bounds will be defined by the outer corners of the voxels. This setting impacts how the resizing is done. For example, if a MagnificationFactor of two is applied to a 256x256 image, the output image will be 512x512 if Border is On, or 511x511 if Border is Off. V.GetBorder() -> int C++: virtual int GetBorder() If Border is Off (the default), then the centers of each of the corner voxels will be considered to form the rectangular bounds of the image. This is the way that VTK normally computes image bounds. If Border is On, then the image bounds will be defined by the outer corners of the voxels. This setting impacts how the resizing is done. For example, if a MagnificationFactor of two is applied to a 256x256 image, the output image will be 512x512 if Border is On, or 511x511 if Border is Off. V.SetCropping(int) C++: virtual void SetCropping(int _arg) Whether to crop the input image before resizing (Off by default). If this is On, then the CroppingRegion must be set. V.CroppingOn() C++: virtual void CroppingOn() Whether to crop the input image before resizing (Off by default). If this is On, then the CroppingRegion must be set. V.CroppingOff() C++: virtual void CroppingOff() Whether to crop the input image before resizing (Off by default). If this is On, then the CroppingRegion must be set. V.GetCropping() -> int C++: virtual int GetCropping() Whether to crop the input image before resizing (Off by default). If this is On, then the CroppingRegion must be set. V.SetCroppingRegion(float, float, float, float, float, float) C++: void SetCroppingRegion(double, double, double, double, double, double) V.SetCroppingRegion((float, float, float, float, float, float)) C++: void SetCroppingRegion(double a[6]) V.GetCroppingRegion() -> (float, float, float, float, float, float) C++: double *GetCroppingRegion() V.SetInterpolate(int) C++: virtual void SetInterpolate(int _arg) Turn interpolation on or off (by default, interpolation is on). V.InterpolateOn() C++: virtual void InterpolateOn() Turn interpolation on or off (by default, interpolation is on). V.InterpolateOff() C++: virtual void InterpolateOff() Turn interpolation on or off (by default, interpolation is on). V.GetInterpolate() -> int C++: virtual int GetInterpolate() Turn interpolation on or off (by default, interpolation is on). V.SetInterpolator(vtkAbstractImageInterpolator) C++: virtual void SetInterpolator( vtkAbstractImageInterpolator *sampler) Set the interpolator for resampling the data. V.GetInterpolator() -> vtkAbstractImageInterpolator C++: virtual vtkAbstractImageInterpolator *GetInterpolator() Set the interpolator for resampling the data. V.GetMTime() -> int C++: vtkMTimeType GetMTime() override; Get the modified time of the filter. vtkImageBSplineCoefficientsGetOutputScalarTypeMinValueGetOutputScalarTypeMaxValueGetBorderModeMinValueGetSplineDegreeMaxValueGetSplineDegreeMinValueGetBorderModeMaxValueGetSplineDegreeGetBorderModeCheckBoundsGetOutputScalarTypeAsStringGetBorderModeAsStringSetBorderModeToClampSetBorderModeToMirrorSetBorderModeToRepeatSetBorderModeSetSplineDegreeEvaluatevtkImageBSplineCoefficients - convert image to b-spline knots Superclass: vtkThreadedImageAlgorithm vtkImageBSplineCoefficients prepares an image for b-spline interpolation by converting the image values into b-spline knot coefficients. It is a necessary pre-filtering step before applying b-spline interpolation with vtkImageReslice. This class is based on code provided by Philippe Thevenaz of EPFL, Lausanne, Switzerland. Please acknowledge his contribution by citing the following paper: [1] P. Thevenaz, T. Blu, M. Unser, "Interpolation Revisited," IEEE Transactions on Medical Imaging 19(7):739-758, 2000. The clamped boundary condition (which is the default) is taken from code presented in the following paper: [2] D. Ruijters, P. Thevenaz, "GPU Prefilter for Accurate Cubic B-spline Interpolation," The Computer Journal, doi: 10.1093/comjnl/bxq086, 2010. @par Thanks: This class was written by David Gobbi at the Seaman Family MR Research Centre, Foothills Medical Centre, Calgary, Alberta. DG Gobbi and YP Starreveld, "Uniform B-Splines for the VTK Imaging Pipeline," VTK Journal, 2011, http://hdl.handle.net/10380/3252 vtkImagingCorePython.vtkImageBSplineCoefficientsV.SafeDownCast(vtkObjectBase) -> vtkImageBSplineCoefficients C++: static vtkImageBSplineCoefficients *SafeDownCast( vtkObjectBase *o) V.NewInstance() -> vtkImageBSplineCoefficients C++: vtkImageBSplineCoefficients *NewInstance() V.SetSplineDegree(int) C++: virtual void SetSplineDegree(int _arg) Set the degree of the spline polynomial. The default value is 3, and the maximum is 9. V.GetSplineDegreeMinValue() -> int C++: virtual int GetSplineDegreeMinValue() Set the degree of the spline polynomial. The default value is 3, and the maximum is 9. V.GetSplineDegreeMaxValue() -> int C++: virtual int GetSplineDegreeMaxValue() Set the degree of the spline polynomial. The default value is 3, and the maximum is 9. V.GetSplineDegree() -> int C++: virtual int GetSplineDegree() Set the degree of the spline polynomial. The default value is 3, and the maximum is 9. V.SetBorderMode(int) C++: virtual void SetBorderMode(int _arg) Set the border mode. The filter that is used to create the coefficients must repeat the image somehow to make a theoritically infinite input. The default is to clamp values that are off the edge of the image, to the value at the closest point on the edge. The other ways of virtually extending the image are to produce mirrored copies, which results in optimal smoothness at the boundary, or to repeat the image, which results in a cyclic or periodic spline. V.GetBorderModeMinValue() -> int C++: virtual int GetBorderModeMinValue() Set the border mode. The filter that is used to create the coefficients must repeat the image somehow to make a theoritically infinite input. The default is to clamp values that are off the edge of the image, to the value at the closest point on the edge. The other ways of virtually extending the image are to produce mirrored copies, which results in optimal smoothness at the boundary, or to repeat the image, which results in a cyclic or periodic spline. V.GetBorderModeMaxValue() -> int C++: virtual int GetBorderModeMaxValue() Set the border mode. The filter that is used to create the coefficients must repeat the image somehow to make a theoritically infinite input. The default is to clamp values that are off the edge of the image, to the value at the closest point on the edge. The other ways of virtually extending the image are to produce mirrored copies, which results in optimal smoothness at the boundary, or to repeat the image, which results in a cyclic or periodic spline. V.SetBorderModeToClamp() C++: void SetBorderModeToClamp() Set the border mode. The filter that is used to create the coefficients must repeat the image somehow to make a theoritically infinite input. The default is to clamp values that are off the edge of the image, to the value at the closest point on the edge. The other ways of virtually extending the image are to produce mirrored copies, which results in optimal smoothness at the boundary, or to repeat the image, which results in a cyclic or periodic spline. V.SetBorderModeToRepeat() C++: void SetBorderModeToRepeat() Set the border mode. The filter that is used to create the coefficients must repeat the image somehow to make a theoritically infinite input. The default is to clamp values that are off the edge of the image, to the value at the closest point on the edge. The other ways of virtually extending the image are to produce mirrored copies, which results in optimal smoothness at the boundary, or to repeat the image, which results in a cyclic or periodic spline. V.SetBorderModeToMirror() C++: void SetBorderModeToMirror() Set the border mode. The filter that is used to create the coefficients must repeat the image somehow to make a theoritically infinite input. The default is to clamp values that are off the edge of the image, to the value at the closest point on the edge. The other ways of virtually extending the image are to produce mirrored copies, which results in optimal smoothness at the boundary, or to repeat the image, which results in a cyclic or periodic spline. V.GetBorderMode() -> int C++: virtual int GetBorderMode() Set the border mode. The filter that is used to create the coefficients must repeat the image somehow to make a theoritically infinite input. The default is to clamp values that are off the edge of the image, to the value at the closest point on the edge. The other ways of virtually extending the image are to produce mirrored copies, which results in optimal smoothness at the boundary, or to repeat the image, which results in a cyclic or periodic spline. V.GetBorderModeAsString() -> string C++: const char *GetBorderModeAsString() Set the border mode. The filter that is used to create the coefficients must repeat the image somehow to make a theoritically infinite input. The default is to clamp values that are off the edge of the image, to the value at the closest point on the edge. The other ways of virtually extending the image are to produce mirrored copies, which results in optimal smoothness at the boundary, or to repeat the image, which results in a cyclic or periodic spline. V.SetOutputScalarType(int) C++: virtual void SetOutputScalarType(int _arg) Set the scalar type of the output. Default is float. Floating-point output is used to avoid overflow, since the range of the output values is larger than the input values. V.GetOutputScalarTypeMinValue() -> int C++: virtual int GetOutputScalarTypeMinValue() Set the scalar type of the output. Default is float. Floating-point output is used to avoid overflow, since the range of the output values is larger than the input values. V.GetOutputScalarTypeMaxValue() -> int C++: virtual int GetOutputScalarTypeMaxValue() Set the scalar type of the output. Default is float. Floating-point output is used to avoid overflow, since the range of the output values is larger than the input values. V.GetOutputScalarType() -> int C++: virtual int GetOutputScalarType() Set the scalar type of the output. Default is float. Floating-point output is used to avoid overflow, since the range of the output values is larger than the input values. V.SetOutputScalarTypeToFloat() C++: void SetOutputScalarTypeToFloat() Set the scalar type of the output. Default is float. Floating-point output is used to avoid overflow, since the range of the output values is larger than the input values. V.SetOutputScalarTypeToDouble() C++: void SetOutputScalarTypeToDouble() Set the scalar type of the output. Default is float. Floating-point output is used to avoid overflow, since the range of the output values is larger than the input values. V.GetOutputScalarTypeAsString() -> string C++: const char *GetOutputScalarTypeAsString() Set the scalar type of the output. Default is float. Floating-point output is used to avoid overflow, since the range of the output values is larger than the input values. V.SetBypass(int) C++: virtual void SetBypass(int _arg) Bypass the filter, do not do any processing. If this is on, then the output data will reference the input data directly, and the output type will be the same as the input type. This is useful a downstream filter sometimes uses b-spline interpolation and sometimes uses other forms of interpolation. V.BypassOn() C++: virtual void BypassOn() Bypass the filter, do not do any processing. If this is on, then the output data will reference the input data directly, and the output type will be the same as the input type. This is useful a downstream filter sometimes uses b-spline interpolation and sometimes uses other forms of interpolation. V.BypassOff() C++: virtual void BypassOff() Bypass the filter, do not do any processing. If this is on, then the output data will reference the input data directly, and the output type will be the same as the input type. This is useful a downstream filter sometimes uses b-spline interpolation and sometimes uses other forms of interpolation. V.GetBypass() -> int C++: virtual int GetBypass() Bypass the filter, do not do any processing. If this is on, then the output data will reference the input data directly, and the output type will be the same as the input type. This is useful a downstream filter sometimes uses b-spline interpolation and sometimes uses other forms of interpolation. V.CheckBounds((float, float, float)) -> int C++: int CheckBounds(const double point[3]) Check a point against the image bounds. Return 0 if out of bounds, and 1 if inside bounds. Calling Evaluate on a point outside the bounds will not generate an error, but the value returned will depend on the BorderMode. V.Evaluate((float, float, float), [float, ...]) C++: void Evaluate(const double point[3], double *value) V.Evaluate(float, float, float) -> float C++: double Evaluate(double x, double y, double z) V.Evaluate((float, float, float)) -> float C++: double Evaluate(const double point[3]) Interpolate a value from the image. You must call Update() before calling this method for the first time. The first signature can return multiple components, while the second signature is for use on single-component images. GetDatavtkImageStencilRasterGetToleranceSetTolerancePrepareForNewDataFillStencilDataInsertLineAllocateExtentsFillGetExtentTypeGetDataObjectTypeGetOriginGetSpacingGetExtentInternalImageStencilDataCopyIsInsideRemoveExtentInsertNextExtentInsertAndMergeExtentGetNextExtentSetExtentSetSpacingSetOriginReplaceSubtractAddCopyInformationToPipelineCopyInformationFromPipelineShallowCopyDeepCopy@P *iV *vtkInformationV|i *vtkInformationVectorvtkImageStencilData - efficient description of an image stencil Superclass: vtkDataObject vtkImageStencilData describes an image stencil in a manner which is efficient both in terms of speed and storage space. The stencil extents are stored for each x-row across the image (multiple extents per row if necessary) and can be retrieved via the GetNextExtent() method. @sa vtkImageStencilSource vtkImageStencil vtkImageStencilRaster - This is a helper class for stencil creation. It is a raster with infinite resolution in the X direction (approximately, since it uses double precision). Lines that represent polygon edges can be drawn into this raster, and then filled given a tolerance. vtkImageStencilRaster(const int wholeExtent[2]) vtkImagingCorePython.vtkImageStencilRasterV.PrepareForNewData((int, int)) C++: void PrepareForNewData(const int allocateExtent[2]=nullptr) Reset the raster to its original state, but keep the same whole extent. Pre-allocate the specified 1D allocateExtent, which must be within the whole extent. V.InsertLine((float, float), (float, float)) C++: void InsertLine(const double p1[2], const double p2[2]) V.InsertLine((float, float), (float, float), bool, bool) C++: void InsertLine(const double[2], const double[2], bool, bool) Insert a line into the raster, given the two end points. V.FillStencilData(vtkImageStencilData, (int, int, int, int, int, int), int, int) C++: void FillStencilData(vtkImageStencilData *data, const int extent[6], int xj=0, int yj=1) Fill the specified extent of a vtkImageStencilData with the raster, after permuting the raster according to xj and yj. V.SetTolerance(float) C++: void SetTolerance(double tol) The tolerance for float-to-int conversions. V.GetTolerance() -> float C++: double GetTolerance() vtkImagingCorePython.vtkImageStencilDataV.SafeDownCast(vtkObjectBase) -> vtkImageStencilData C++: static vtkImageStencilData *SafeDownCast(vtkObjectBase *o) V.NewInstance() -> vtkImageStencilData C++: vtkImageStencilData *NewInstance() V.Initialize() C++: void Initialize() override; Restore data object to initial state, V.DeepCopy(vtkDataObject) C++: void DeepCopy(vtkDataObject *o) override; Shallow and Deep copy. These copy the data, but not any of the pipeline connections. V.ShallowCopy(vtkDataObject) C++: void ShallowCopy(vtkDataObject *f) override; Shallow and Deep copy. These copy the data, but not any of the pipeline connections. V.InternalImageStencilDataCopy(vtkImageStencilData) C++: void InternalImageStencilDataCopy(vtkImageStencilData *s) V.GetDataObjectType() -> int C++: int GetDataObjectType() override; Get the data type as an integer (this will return VTK_DATA_OBJECT for now, maybe a proper type constant will be reserved later). V.GetExtentType() -> int C++: int GetExtentType() override; The extent type is 3D, just like vtkImageData. V.GetNextExtent(int, int, int, int, int, int, int) -> int C++: int GetNextExtent(int &r1, int &r2, int xMin, int xMax, int yIdx, int zIdx, int &iter) Given the total output x extent [xMin,xMax] and the current y, z indices, return each sub-extent [r1,r2] that lies within within the unclipped region in sequence. A value of '0' is returned if no more sub-extents are available. The variable 'iter' must be initialized to zero before the first call, unless you want the complementary sub-extents in which case you must initialize 'iter' to -1. The variable 'iter' is used internally to keep track of which sub-extent should be returned next. V.IsInside(int, int, int) -> int C++: int IsInside(int xIdx, int yIdx, int zIdx) Checks if an image index is inside the stencil. Even though GetNextExtent and the vtkImageStencilIterator are faster if every voxel in the volume has to be checked, IsInside provides an efficient alternative for if just a single voxel has to be checked. V.InsertNextExtent(int, int, int, int) C++: void InsertNextExtent(int r1, int r2, int yIdx, int zIdx) This method is used by vtkImageStencilDataSource to add an x sub extent [r1,r2] for the x row (yIdx,zIdx). The specified sub extent must not intersect any other sub extents along the same x row. As well, r1 and r2 must both be within the total x extent [Extent[0],Extent[1]]. V.InsertAndMergeExtent(int, int, int, int) C++: void InsertAndMergeExtent(int r1, int r2, int yIdx, int zIdx) Similar to InsertNextExtent, except that the extent (r1,r2) at yIdx, zIdx is merged with other extents, (if any) on that row. So a unique extent may not necessarily be added. For instance, if an extent [5,11] already exists adding an extent, [7,9] will not affect the stencil. Likewise adding [10, 13] will replace the existing extent with [5,13]. V.RemoveExtent(int, int, int, int) C++: void RemoveExtent(int r1, int r2, int yIdx, int zIdx) Remove the extent from (r1,r2) at yIdx, zIdx V.SetSpacing(float, float, float) C++: void SetSpacing(double, double, double) V.SetSpacing((float, float, float)) C++: void SetSpacing(double a[3]) V.GetSpacing() -> (float, float, float) C++: double *GetSpacing() V.SetOrigin(float, float, float) C++: void SetOrigin(double, double, double) V.SetOrigin((float, float, float)) C++: void SetOrigin(double a[3]) V.GetOrigin() -> (float, float, float) C++: double *GetOrigin() V.SetExtent([int, int, int, int, int, int]) C++: void SetExtent(int extent[6]) V.SetExtent(int, int, int, int, int, int) C++: void SetExtent(int x1, int x2, int y1, int y2, int z1, int z2) Set the extent of the data. This is should be called only by vtkImageStencilSource, as it is part of the basic pipeline functionality. V.GetExtent() -> (int, int, int, int, int, int) C++: int *GetExtent() V.AllocateExtents() C++: void AllocateExtents() Allocate space for the sub-extents. This is called by vtkImageStencilSource. V.Fill() C++: void Fill() Fill the sub-extents. V.CopyInformationFromPipeline(vtkInformation) C++: void CopyInformationFromPipeline(vtkInformation *info) override; Override these to handle origin, spacing, scalar type, and scalar number of components. See vtkDataObject for details. V.CopyInformationToPipeline(vtkInformation) C++: void CopyInformationToPipeline(vtkInformation *info) override; Override these to handle origin, spacing, scalar type, and scalar number of components. See vtkDataObject for details. V.GetData(vtkInformation) -> vtkImageStencilData C++: static vtkImageStencilData *GetData(vtkInformation *info) V.GetData(vtkInformationVector, int) -> vtkImageStencilData C++: static vtkImageStencilData *GetData(vtkInformationVector *v, int i=0) Retrieve an instance of this class from an information object. V.Add(vtkImageStencilData) C++: virtual void Add(vtkImageStencilData *) Add merges the stencil supplied as argument into Self. V.Subtract(vtkImageStencilData) C++: virtual void Subtract(vtkImageStencilData *) Subtract removes the portion of the stencil, supplied as argument, that lies within Self from Self. V.Replace(vtkImageStencilData) C++: virtual void Replace(vtkImageStencilData *) Replaces the portion of the stencil, supplied as argument, that lies within Self from Self. V.Clip([int, int, int, int, int, int]) -> int C++: virtual int Clip(int extent[6]) Clip the stencil with the supplied extents. In other words, discard data outside the specified extents. Return 1 if something changed. vtkImageStencilAlgorithmGetOutputSetOutputvtkImageStencilAlgorithm - producer of vtkImageStencilData Superclass: vtkAlgorithm vtkImageStencilAlgorithm is a superclass for filters that generate the special vtkImageStencilData type. This data type is a special representation of a binary image that can be used as a mask by several imaging filters. @sa vtkImageStencilData vtkImageStencilSource vtkImagingCorePython.vtkImageStencilAlgorithmV.SafeDownCast(vtkObjectBase) -> vtkImageStencilAlgorithm C++: static vtkImageStencilAlgorithm *SafeDownCast( vtkObjectBase *o) V.NewInstance() -> vtkImageStencilAlgorithm C++: vtkImageStencilAlgorithm *NewInstance() V.SetOutput(vtkImageStencilData) C++: void SetOutput(vtkImageStencilData *output) Get or set the output for this source. V.GetOutput() -> vtkImageStencilData C++: vtkImageStencilData *GetOutput() Get or set the output for this source. GetComponentOffsetGetComponentCountGetSlidingWindowUpdateSlidingWindowOnSlidingWindowOffIsSeparableSetComponentOffsetSetComponentCountSetSlidingWindowComputeNumberOfComponentsCheckBoundsIJKComputeSupportSizeInterpolateIJKReleaseDataVTK_IMAGE_BORDER_CLAMPVTK_IMAGE_BORDER_REPEATVTK_IMAGE_BORDER_MIRRORvtkAbstractImageInterpolator - interpolate data values from images Superclass: vtkObject vtkAbstractImageInterpolator provides an abstract interface for interpolating image data. You specify the data set you want to interpolate values from, then call Interpolate(x,y,z) to interpolate the data.@par Thanks: Thanks to David Gobbi at the Seaman Family MR Centre and Dept. of Clinical Neurosciences, Foothills Medical Centre, Calgary, for providing this class. @sa vtkImageReslice vtkImageInterpolator vtkImageSincInterpolator vtkImagingCorePython.vtkAbstractImageInterpolatorV.SafeDownCast(vtkObjectBase) -> vtkAbstractImageInterpolator C++: static vtkAbstractImageInterpolator *SafeDownCast( vtkObjectBase *o) V.NewInstance() -> vtkAbstractImageInterpolator C++: vtkAbstractImageInterpolator *NewInstance() V.Initialize(vtkDataObject) C++: virtual void Initialize(vtkDataObject *data) Initialize the interpolator with the data that you wish to interpolate. V.ReleaseData() C++: virtual void ReleaseData() Release any data stored by the interpolator. V.DeepCopy(vtkAbstractImageInterpolator) C++: void DeepCopy(vtkAbstractImageInterpolator *obj) Copy the interpolator. It is possible to duplicate an interpolator by calling NewInstance() followed by DeepCopy(). V.Update() C++: void Update() Update the interpolator. If the interpolator has been modified by a Set method since Initialize() was called, you must call this method to update the interpolator before you can use it. V.Interpolate(float, float, float, int) -> float C++: double Interpolate(double x, double y, double z, int component) V.Interpolate((float, float, float), [float, ...]) -> bool C++: bool Interpolate(const double point[3], double *value) Get the result of interpolating the specified component of the input data, which should be set to zero if there is only one component. If the point is not within the bounds of the data set, then OutValue will be returned. This method is primarily meant for use by the wrapper languages. V.SetOutValue(float) C++: void SetOutValue(double outValue) The value to return when the point is out of bounds. V.GetOutValue() -> float C++: double GetOutValue() V.SetTolerance(float) C++: void SetTolerance(double tol) The tolerance to apply when checking whether a point is out of bounds. This is a fractional distance relative to the voxel size, so a tolerance of 1 expands the bounds by one voxel. V.SetComponentOffset(int) C++: void SetComponentOffset(int offset) This method specifies which component of the input will be interpolated, or if ComponentCount is also set, it specifies the first component. When the interpolation is performed, it will be clamped to the number of available components. V.GetComponentOffset() -> int C++: int GetComponentOffset() V.SetComponentCount(int) C++: void SetComponentCount(int count) This method specifies the number of components to extract. The default value is -1, which extracts all available components. When the interpolation is performed, this will be clamped to the number of available components. V.GetComponentCount() -> int C++: int GetComponentCount() V.ComputeNumberOfComponents(int) -> int C++: int ComputeNumberOfComponents(int inputComponents) Compute the number of output components based on the ComponentOffset, ComponentCount, and the number of components in the input data. V.GetNumberOfComponents() -> int C++: int GetNumberOfComponents() Get the number of components that will be returned when Interpolate() is called. This is only valid after initialization. Before then, use ComputeNumberOfComponents instead. V.InterpolateIJK((float, float, float), [float, ...]) C++: void InterpolateIJK(const double point[3], double *value) A version of Interpolate that takes structured coords instead of data coords. Structured coords are the data coords after subtracting the Origin and dividing by the Spacing. V.CheckBoundsIJK((float, float, float)) -> bool C++: bool CheckBoundsIJK(const double x[3]) Check an x,y,z point to see if it is within the bounds for the structured coords of the image. This is meant to be called prior to InterpolateIJK. The bounds that are checked against are the input image extent plus the tolerance. V.SetBorderMode(int) C++: void SetBorderMode(int mode) The border mode (default: clamp). This controls how out-of-bounds lookups are handled, i.e. how data will be extrapolated beyond the bounds of the image. The default is to clamp the lookup point to the bounds. The other modes wrap around to the opposite boundary, or mirror the image at the boundary. V.SetBorderModeToClamp() C++: void SetBorderModeToClamp() The border mode (default: clamp). This controls how out-of-bounds lookups are handled, i.e. how data will be extrapolated beyond the bounds of the image. The default is to clamp the lookup point to the bounds. The other modes wrap around to the opposite boundary, or mirror the image at the boundary. V.SetBorderModeToRepeat() C++: void SetBorderModeToRepeat() The border mode (default: clamp). This controls how out-of-bounds lookups are handled, i.e. how data will be extrapolated beyond the bounds of the image. The default is to clamp the lookup point to the bounds. The other modes wrap around to the opposite boundary, or mirror the image at the boundary. V.SetBorderModeToMirror() C++: void SetBorderModeToMirror() The border mode (default: clamp). This controls how out-of-bounds lookups are handled, i.e. how data will be extrapolated beyond the bounds of the image. The default is to clamp the lookup point to the bounds. The other modes wrap around to the opposite boundary, or mirror the image at the boundary. V.GetBorderMode() -> int C++: int GetBorderMode() The border mode (default: clamp). This controls how out-of-bounds lookups are handled, i.e. how data will be extrapolated beyond the bounds of the image. The default is to clamp the lookup point to the bounds. The other modes wrap around to the opposite boundary, or mirror the image at the boundary. V.GetBorderModeAsString() -> string C++: const char *GetBorderModeAsString() The border mode (default: clamp). This controls how out-of-bounds lookups are handled, i.e. how data will be extrapolated beyond the bounds of the image. The default is to clamp the lookup point to the bounds. The other modes wrap around to the opposite boundary, or mirror the image at the boundary. V.SetSlidingWindow(bool) C++: void SetSlidingWindow(bool x) Enable sliding window for separable kernels. When this is enabled, the interpolator will cache partial sums in in order to accelerate the computation. It only makes sense to do this if the interpolator is used by calling InterpolateRow() while incrementing first the Y, and then the Z index with every call. V.SlidingWindowOn() C++: void SlidingWindowOn() V.SlidingWindowOff() C++: void SlidingWindowOff() V.GetSlidingWindow() -> bool C++: bool GetSlidingWindow() V.ComputeSupportSize((float, float, float, float, float, float, float, float, float, float, float, float, float, float, float, float), [int, int, int]) C++: virtual void ComputeSupportSize(const double matrix[16], int support[3]) Get the support size for use in computing update extents. If the data will be sampled on a regular grid, then pass a matrix describing the structured coordinate transformation between the output and the input. Otherwise, pass nullptr as the matrix to retrieve the full kernel size. V.IsSeparable() -> bool C++: virtual bool IsSeparable() True if the interpolation is separable, which means that the weights can be precomputed in order to accelerate the interpolation. Any interpolator which is separable will implement the methods PrecomputeWeightsForExtent and InterpolateRow V.GetWholeExtent() -> (int, ...) C++: int *GetWholeExtent() V.GetWholeExtent([int, int, int, int, int, int]) C++: void GetWholeExtent(int extent[6]) Get the whole extent of the data being interpolated, including parts of the data that are not currently in memory. vtkImageBSplineInterpolatorVTK_IMAGE_BSPLINE_DEGREE_MAXvtkImageBSplineInterpolator - perform b-spline interpolation on images Superclass: vtkAbstractImageInterpolator vtkImageBSplineInterpolator can be used to perform b-spline interpolation on images that have been filtered with vtkImageBSplineCoefficients. The b-spline interpolants provide the maximum possible degree of continuity for a given kernel size, but require that the image data be pre-filtered to generate b-spline coefficients before the interpolation is performed. Interpolating data that has not been pre-filtered will give incorrect results. @sa vtkImageReslice vtkImageBSplineCoefficients vtkBSplineTransform@par Thanks: This class was written by David Gobbi at the Seaman Family MR Research Centre, Foothills Medical Centre, Calgary, Alberta. DG Gobbi and YP Starreveld, "Uniform B-Splines for the VTK Imaging Pipeline," VTK Journal, 2011, http://hdl.handle.net/10380/3252 vtkImagingCorePython.vtkImageBSplineInterpolatorV.SafeDownCast(vtkObjectBase) -> vtkImageBSplineInterpolator C++: static vtkImageBSplineInterpolator *SafeDownCast( vtkObjectBase *o) V.NewInstance() -> vtkImageBSplineInterpolator C++: vtkImageBSplineInterpolator *NewInstance() V.SetSplineDegree(int) C++: void SetSplineDegree(int degree) Set the degree of the spline polynomial. The default value is 3, and the maximum is 9. The data must be pre-filtered for the same degree of polynomial with vtkImageBSplineCoefficients. V.GetSplineDegree() -> int C++: int GetSplineDegree() Set the degree of the spline polynomial. The default value is 3, and the maximum is 9. The data must be pre-filtered for the same degree of polynomial with vtkImageBSplineCoefficients. V.GetSplineDegreeMinValue() -> int C++: int GetSplineDegreeMinValue() Set the degree of the spline polynomial. The default value is 3, and the maximum is 9. The data must be pre-filtered for the same degree of polynomial with vtkImageBSplineCoefficients. V.GetSplineDegreeMaxValue() -> int C++: int GetSplineDegreeMaxValue() Set the degree of the spline polynomial. The default value is 3, and the maximum is 9. The data must be pre-filtered for the same degree of polynomial with vtkImageBSplineCoefficients. V.ComputeSupportSize((float, float, float, float, float, float, float, float, float, float, float, float, float, float, float, float), [int, int, int]) C++: void ComputeSupportSize(const double matrix[16], int support[3]) override; Get the support size for use in computing update extents. If the data will be sampled on a regular grid, then pass a matrix describing the structured coordinate transformation between the output and the input. Otherwise, pass nullptr as the matrix to retrieve the full kernel size. V.IsSeparable() -> bool C++: bool IsSeparable() override; Returns true if the interpolator supports weight precomputation. This will always return true for this interpolator. vtkImageSincInterpolatorGetWindowParameterGetUseWindowParameterGetAntialiasingGetWindowFunctionGetRenormalizationGetWindowHalfWidthAntialiasingOffRenormalizationOffUseWindowParameterOnUseWindowParameterOffRenormalizationOnAntialiasingOnSetWindowFunctionToNuttallSetWindowFunctionToLanczosSetWindowFunctionToKaiserSetWindowFunctionToCosineSetWindowFunctionToHannSetWindowFunctionToHammingSetWindowFunctionToBlackmanSetUseWindowParameterSetWindowHalfWidthSetWindowParameterSetRenormalizationSetAntialiasingGetBlurFactorsSetBlurFactorsGetWindowFunctionAsStringSetWindowFunctionVTK_LANCZOS_WINDOWVTK_KAISER_WINDOWVTK_COSINE_WINDOWVTK_HANN_WINDOWVTK_HAMMING_WINDOWVTK_BLACKMAN_WINDOWVTK_BLACKMAN_HARRIS3VTK_BLACKMAN_HARRIS4VTK_NUTTALL_WINDOWVTK_BLACKMAN_NUTTALL3VTK_BLACKMAN_NUTTALL4VTK_SINC_KERNEL_SIZE_MAXSetWindowFunctionToBlackmanHarris4SetWindowFunctionToBlackmanNuttall3SetWindowFunctionToBlackmanNuttall4SetWindowFunctionToBlackmanHarris3vtkImageSincInterpolator - perform sinc interpolation on images Superclass: vtkAbstractImageInterpolator vtkImageSincInterpolator provides various windowed sinc interpolation methods for image data. The default is a five-lobed Lanczos interpolant, with a kernel size of 6. The interpolator can also bandlimit the image, which can be used for antialiasing. The interpolation kernels are evaluated via a lookup table for efficiency.@par Thanks: Thanks to David Gobbi at the Seaman Family MR Centre and Dept. of Clinical Neurosciences, Foothills Medical Centre, Calgary, for providing this class. @sa vtkImageReslice vtkImagingCorePython.vtkImageSincInterpolatorV.SafeDownCast(vtkObjectBase) -> vtkImageSincInterpolator C++: static vtkImageSincInterpolator *SafeDownCast( vtkObjectBase *o) V.NewInstance() -> vtkImageSincInterpolator C++: vtkImageSincInterpolator *NewInstance() V.SetWindowFunction(int) C++: virtual void SetWindowFunction(int mode) The window function to use. The default is Lanczos, which is very popular and performs well with a kernel width of 6. The Cosine window is included for historical reasons. All other windows are described in AH Nuttall, "Some windows with very good sidelobe behavior," IEEE Transactions on Acoustics, Speech, and Signal Processing 29:84-91, 1981. V.SetWindowFunctionToLanczos() C++: void SetWindowFunctionToLanczos() The window function to use. The default is Lanczos, which is very popular and performs well with a kernel width of 6. The Cosine window is included for historical reasons. All other windows are described in AH Nuttall, "Some windows with very good sidelobe behavior," IEEE Transactions on Acoustics, Speech, and Signal Processing 29:84-91, 1981. V.SetWindowFunctionToKaiser() C++: void SetWindowFunctionToKaiser() The window function to use. The default is Lanczos, which is very popular and performs well with a kernel width of 6. The Cosine window is included for historical reasons. All other windows are described in AH Nuttall, "Some windows with very good sidelobe behavior," IEEE Transactions on Acoustics, Speech, and Signal Processing 29:84-91, 1981. V.SetWindowFunctionToCosine() C++: void SetWindowFunctionToCosine() The window function to use. The default is Lanczos, which is very popular and performs well with a kernel width of 6. The Cosine window is included for historical reasons. All other windows are described in AH Nuttall, "Some windows with very good sidelobe behavior," IEEE Transactions on Acoustics, Speech, and Signal Processing 29:84-91, 1981. V.SetWindowFunctionToHann() C++: void SetWindowFunctionToHann() The window function to use. The default is Lanczos, which is very popular and performs well with a kernel width of 6. The Cosine window is included for historical reasons. All other windows are described in AH Nuttall, "Some windows with very good sidelobe behavior," IEEE Transactions on Acoustics, Speech, and Signal Processing 29:84-91, 1981. V.SetWindowFunctionToHamming() C++: void SetWindowFunctionToHamming() The window function to use. The default is Lanczos, which is very popular and performs well with a kernel width of 6. The Cosine window is included for historical reasons. All other windows are described in AH Nuttall, "Some windows with very good sidelobe behavior," IEEE Transactions on Acoustics, Speech, and Signal Processing 29:84-91, 1981. V.SetWindowFunctionToBlackman() C++: void SetWindowFunctionToBlackman() The window function to use. The default is Lanczos, which is very popular and performs well with a kernel width of 6. The Cosine window is included for historical reasons. All other windows are described in AH Nuttall, "Some windows with very good sidelobe behavior," IEEE Transactions on Acoustics, Speech, and Signal Processing 29:84-91, 1981. V.SetWindowFunctionToBlackmanHarris3() C++: void SetWindowFunctionToBlackmanHarris3() The window function to use. The default is Lanczos, which is very popular and performs well with a kernel width of 6. The Cosine window is included for historical reasons. All other windows are described in AH Nuttall, "Some windows with very good sidelobe behavior," IEEE Transactions on Acoustics, Speech, and Signal Processing 29:84-91, 1981. V.SetWindowFunctionToBlackmanHarris4() C++: void SetWindowFunctionToBlackmanHarris4() The window function to use. The default is Lanczos, which is very popular and performs well with a kernel width of 6. The Cosine window is included for historical reasons. All other windows are described in AH Nuttall, "Some windows with very good sidelobe behavior," IEEE Transactions on Acoustics, Speech, and Signal Processing 29:84-91, 1981. V.SetWindowFunctionToNuttall() C++: void SetWindowFunctionToNuttall() The window function to use. The default is Lanczos, which is very popular and performs well with a kernel width of 6. The Cosine window is included for historical reasons. All other windows are described in AH Nuttall, "Some windows with very good sidelobe behavior," IEEE Transactions on Acoustics, Speech, and Signal Processing 29:84-91, 1981. V.SetWindowFunctionToBlackmanNuttall3() C++: void SetWindowFunctionToBlackmanNuttall3() The window function to use. The default is Lanczos, which is very popular and performs well with a kernel width of 6. The Cosine window is included for historical reasons. All other windows are described in AH Nuttall, "Some windows with very good sidelobe behavior," IEEE Transactions on Acoustics, Speech, and Signal Processing 29:84-91, 1981. V.SetWindowFunctionToBlackmanNuttall4() C++: void SetWindowFunctionToBlackmanNuttall4() The window function to use. The default is Lanczos, which is very popular and performs well with a kernel width of 6. The Cosine window is included for historical reasons. All other windows are described in AH Nuttall, "Some windows with very good sidelobe behavior," IEEE Transactions on Acoustics, Speech, and Signal Processing 29:84-91, 1981. V.GetWindowFunction() -> int C++: int GetWindowFunction() The window function to use. The default is Lanczos, which is very popular and performs well with a kernel width of 6. The Cosine window is included for historical reasons. All other windows are described in AH Nuttall, "Some windows with very good sidelobe behavior," IEEE Transactions on Acoustics, Speech, and Signal Processing 29:84-91, 1981. V.GetWindowFunctionAsString() -> string C++: virtual const char *GetWindowFunctionAsString() The window function to use. The default is Lanczos, which is very popular and performs well with a kernel width of 6. The Cosine window is included for historical reasons. All other windows are described in AH Nuttall, "Some windows with very good sidelobe behavior," IEEE Transactions on Acoustics, Speech, and Signal Processing 29:84-91, 1981. V.SetWindowHalfWidth(int) C++: void SetWindowHalfWidth(int n) Set the window half-width, this must be an integer between 1 and 16, with a default value of 3. The kernel size will be twice this value if no blur factors are applied. The total number of sinc lobes will be one less than twice the half-width, so if the half-width is 3 then the kernel size will be 6 and there will be 5 sinc lobes. V.GetWindowHalfWidth() -> int C++: int GetWindowHalfWidth() V.SetUseWindowParameter(int) C++: void SetUseWindowParameter(int val) Turn this on in order to use SetWindowParameter. If it is off, then the default parameter will be used for the window. V.UseWindowParameterOn() C++: void UseWindowParameterOn() V.UseWindowParameterOff() C++: void UseWindowParameterOff() V.GetUseWindowParameter() -> int C++: int GetUseWindowParameter() V.SetWindowParameter(float) C++: void SetWindowParameter(double parm) Set the alpha parameter for the Kaiser window function. This parameter will be ignored unless UseWindowParameter is On. If UseWindowParameter is Off, then alpha is set to be the same as n where n is the window half-width. Using an alpha less than n increases the sharpness and ringing, while using an alpha greater than n increases the blurring. V.GetWindowParameter() -> float C++: double GetWindowParameter() V.SetBlurFactors(float, float, float) C++: void SetBlurFactors(double x, double y, double z) V.SetBlurFactors((float, float, float)) C++: void SetBlurFactors(const double f[3]) Blur the image by widening the windowed sinc kernel by the specified factors for the x, y, and z directions. This reduces the bandwidth by these same factors. If you turn Antialiasing on, then the blur factors will be computed automatically from the output sampling rate. Blurring increases the computation time because the kernel size increases by the blur factor. V.GetBlurFactors([float, float, float]) C++: void GetBlurFactors(double f[3]) V.GetBlurFactors() -> (float, float, float) C++: double *GetBlurFactors() Blur the image by widening the windowed sinc kernel by the specified factors for the x, y, and z directions. This reduces the bandwidth by these same factors. If you turn Antialiasing on, then the blur factors will be computed automatically from the output sampling rate. Blurring increases the computation time because the kernel size increases by the blur factor. V.SetAntialiasing(int) C++: void SetAntialiasing(int antialiasing) Turn on antialiasing. If antialiasing is on, then the BlurFactors will be computed automatically from the output sampling rate such that that the image will be bandlimited to the Nyquist frequency. This is only applicable when the interpolator is being used by a resampling filter like vtkImageReslice. Such a filter will indicate the output sampling by calling the interpolator's ComputeSupportSize() method, which will compute the blur factors at the same time that it computes the support size. V.AntialiasingOn() C++: void AntialiasingOn() V.AntialiasingOff() C++: void AntialiasingOff() V.GetAntialiasing() -> int C++: int GetAntialiasing() V.SetRenormalization(int) C++: void SetRenormalization(int renormalization) Turn off renormalization. Most of the sinc windows provide kernels for which the weights do not sum to one, and for which the sum depends on the offset. This results in small ripple artifacts in the output. By default, the vtkImageSincInterpolator will renormalize these kernels. This method allows the renormalization to be turned off. V.RenormalizationOn() C++: void RenormalizationOn() V.RenormalizationOff() C++: void RenormalizationOff() V.GetRenormalization() -> int C++: int GetRenormalization() vtkImageInterpolatorSetInterpolationModeToNearestvtkImageInterpolator - interpolate data values from images Superclass: vtkAbstractImageInterpolator vtkImageInterpolator provides a simple interface for interpolating image data. It provides linear, cubic, and nearest-neighbor interpolation.@par Thanks: Thanks to David Gobbi at the Seaman Family MR Centre and Dept. of Clinical Neurosciences, Foothills Medical Centre, Calgary, for providing this class. @sa vtkImageReslice vtkImagingCorePython.vtkImageInterpolatorV.SafeDownCast(vtkObjectBase) -> vtkImageInterpolator C++: static vtkImageInterpolator *SafeDownCast(vtkObjectBase *o) V.NewInstance() -> vtkImageInterpolator C++: vtkImageInterpolator *NewInstance() V.SetInterpolationMode(int) C++: virtual void SetInterpolationMode(int mode) The interpolation mode for point scalars (default: linear). Subclasses will provide additional interpolation modes, so this is a virtual method. V.SetInterpolationModeToNearest() C++: void SetInterpolationModeToNearest() The interpolation mode for point scalars (default: linear). Subclasses will provide additional interpolation modes, so this is a virtual method. V.SetInterpolationModeToLinear() C++: void SetInterpolationModeToLinear() The interpolation mode for point scalars (default: linear). Subclasses will provide additional interpolation modes, so this is a virtual method. V.SetInterpolationModeToCubic() C++: void SetInterpolationModeToCubic() The interpolation mode for point scalars (default: linear). Subclasses will provide additional interpolation modes, so this is a virtual method. V.GetInterpolationMode() -> int C++: int GetInterpolationMode() The interpolation mode for point scalars (default: linear). Subclasses will provide additional interpolation modes, so this is a virtual method. V.GetInterpolationModeAsString() -> string C++: virtual const char *GetInterpolationModeAsString() The interpolation mode for point scalars (default: linear). Subclasses will provide additional interpolation modes, so this is a virtual method. vtkImageStencilSourcevtkImageStencilSource - generate an image stencil Superclass: vtkImageStencilAlgorithm vtkImageStencilSource is a superclass for filters that generate image stencils. Given a clipping object such as a vtkImplicitFunction, it will set up a list of clipping extents for each x-row through the image data. The extents for each x-row can be retrieved via the GetNextExtent() method after the extent lists have been built with the BuildExtents() method. For large images, using clipping extents is much more memory efficient (and slightly more time-efficient) than building a mask. This class can be subclassed to allow clipping with objects other than vtkImplicitFunction. @sa vtkImplicitFunction vtkImageStencil vtkPolyDataToImageStencil vtkImagingCorePython.vtkImageStencilSourceV.SafeDownCast(vtkObjectBase) -> vtkImageStencilSource C++: static vtkImageStencilSource *SafeDownCast(vtkObjectBase *o) V.NewInstance() -> vtkImageStencilSource C++: vtkImageStencilSource *NewInstance() V.SetInformationInput(vtkImageData) C++: virtual void SetInformationInput(vtkImageData *) Set a vtkImageData that has the Spacing, Origin, and WholeExtent that will be used for the stencil. This input should be set to the image that you wish to apply the stencil to. If you use this method, then any values set with the SetOutputSpacing, SetOutputOrigin, and SetOutputWholeExtent methods will be ignored. V.GetInformationInput() -> vtkImageData C++: virtual vtkImageData *GetInformationInput() Set a vtkImageData that has the Spacing, Origin, and WholeExtent that will be used for the stencil. 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