NAME
vtkShepardMethod - sample unstructured points onto structured points using the method of Shepard
SYNOPSIS
#include "/opt/vtk-c++/graphics/vtkShepardMethod.h"
class VTK_EXPORT vtkShepardMethod : public vtkDataSetToStructuredPointsFilter
vtkShepardMethod();
static vtkShepardMethod *New() {return new vtkShepardMethod;};
const char *GetClassName() {return "vtkShepardMethod";};
void PrintSelf(ostream& os, vtkIndent indent);
float ComputeModelBounds(float origin[3], float ar[3]);
int *GetSampleDimensions();
void GetSampleDimensions(int data[3]);
void SetSampleDimensions(int i, int j, int k);
void SetSampleDimensions(int dim[3]);
void SetMaximumDistance(float);
float GetMaximumDistance();
void SetModelBounds(float data[6]);
void SetModelBounds(float *);
float *GetModelBounds();
void GetModelBounds(float data[6]);
void SetModelBounds(float xmin, float xmax, float ymin, float ymax,
float zmin, float zmax);
void SetNullValue(float);
float GetNullValue();
DESCRIPTION
vtkShepardMethod is a filter used to visualize unstructured point data using Shepard's method. The method works by resampling the unstructured points onto a structured points set. The influence functions are described as "inverse distance weighted". Once the structured points are computed, the usual visualization techniques can be used visualize the structured points.
CAVEATS
The input to this filter is any dataset type. This filter can be used to resample any form of data, i.e., the input data need not be unstructured.
The bounds of the data (i.e., the sample space) is automatically computed if not set by the user.
If you use a maximum distance less than 1.0, some output points may never receive a contribution. The final value of these points can be specified with the "NullValue" instance variable.
SUMMARY
int *GetSampleDimensions()
void GetSampleDimensions(int data[3])
Specify i-j-k dimensions on which to sample input points.
void SetMaximumDistance(float)
Specify influence distance of each input point. This distance is a fraction of the length of the diagonal of the sample space. Thus, values of 1.0 will cause each input point to influence all points in the structured point dataset. Values less than 1.0 can improve performance significantly.
void SetModelBounds(float data[6])
void SetModelBounds(float *)
Specify the position in space to perform the sampling.
void SetNullValue(float)
Set the Null value for output points not receiving a contribution from the input points.
vtkShepardMethod()
Construct with sample dimensions=(50,50,50) and so that model bounds are automatically computed from input. Null value for each unvisited output point is 0.0. Maximum distance is 0.25.
float ComputeModelBounds(float origin[3], float spacing[3]) Compute ModelBounds from input geometry.
void SetSampleDimensions(int i, int j, int k)
Set the i-j-k dimensions on which to sample the distance function.
void SetSampleDimensions(int dim[3])
Set the i-j-k dimensions on which to sample the distance function.