Difference between revisions of "ParaView/Users Guide/List of filters"

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Clip with scalars. Tetrahedra.
Clip with scalars. Tetrahedra.




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Copies geometry from first input. Puts all of the arrays into the output.
Copies geometry from first input. Puts all of the arrays into the output.


The Append Attributes filter takes multiple input data sets with the same geometry and merges their point and cell attributes to produce a single output containing all the point and cell attributes of the inputs. Any inputs without the same number of points and cells as the first input are ignored. The input data sets must already be collected together, either as a result of a reader that loads multiple parts (e.g., EnSight reader) or because the Group Parts filter has been run to form a collection of data sets.<br>
The Append Attributes filter takes multiple input data sets with the same geometry and merges their point and cell attributes to produce a single output containing all the point and cell attributes of the inputs. Any inputs without the same number of points and cells as the first input are ignored. The input data sets must already be collected together, either as a result of a reader that loads multiple parts (e.g., EnSight reader) or because the Group Parts filter has been run to form a collection of data sets.<br>
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|
|
If this property is set to 1, then the input cell data is passed through to the output; otherwise, only the generated point data will be available in the output.
If this property is set to 1, then the input cell data is passed through to the output; otherwise, only the generated point data will be available in the output.
| 0
|
Only the values 0 and 1 are accepted.
|-
| '''Piece Invariant'''<br>''(PieceInvariant)''
|
If the value of this property is set to 1, this filter will request ghost levels so that the values at boundary points match across processes. NOTE: Enabling this option might cause multiple executions of the data source because more information is needed to remove internal surfaces.


| 0
| 0
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Compute a statistical model of a dataset and/or assess the dataset with a statistical model.
Compute a statistical model of a dataset and/or assess the dataset with a statistical model.


This filter either computes a statistical model of a dataset or takes such a model as its second input. Then, the model (however it is obtained) may optionally be used to assess the input dataset.<br>
This filter either computes a statistical model of a dataset or takes such a model as its second input. Then, the model (however it is obtained) may optionally be used to assess the input dataset.<br>
This filter computes contingency tables between pairs of attributes. This result is a tabular bivariate probability distribution which serves as a Bayesian-style prior model. Data is assessed by computing <br>
This filter computes contingency tables between pairs of attributes. This result is a tabular bivariate probability distribution which serves as a Bayesian-style prior model. Data is assessed by computing <br>
*  the probability of observing both variables simultaneously;<br>
*  the probability of observing both variables simultaneously;<br>
*  the probability of each variable conditioned on the other (the two values need not be identical); and<br>
*  the probability of each variable conditioned on the other (the two values need not be identical); and<br>
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| '''Input'''<br>''(Input)''
| '''Input'''<br>''(Input)''
|
|
The input to the filter. Arrays from this dataset will be used for computing statistics and/or assessed by a statistical model.
The input to the filter. Arrays from this dataset will be used for computing statistics and/or assessed by a statistical model.


|
|
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#  "Model a subset of the data," creates an output table (or tables) summarizing a '''randomly-chosen subset''' of the input dataset;
#  "Model a subset of the data," creates an output table (or tables) summarizing a '''randomly-chosen subset''' of the input dataset;
#  "Assess the data with a model," adds attributes to the first input dataset using a model provided on the second input port; and
#  "Assess the data with a model," adds attributes to the first input dataset using a model provided on the second input port; and
#  "Model and assess the same data," is really just operations 2 and 3 above applied to the same input dataset. The model is first trained using a fraction of the input data and then the entire dataset is assessed using that model.
#  "Model and assess the same data," is really just operations 2 and 3 above applied to the same input dataset. The model is first trained using a fraction of the input data and then the entire dataset is assessed using that model.


When the task includes creating a model (i.e., tasks 2, and 4), you may adjust the fraction of the input dataset used for training. You should avoid using a large fraction of the input data for training as you will then not be able to detect overfitting. The ''Training fraction'' setting will be ignored for tasks 1 and 3.
When the task includes creating a model (i.e., tasks 2, and 4), you may adjust the fraction of the input dataset used for training. You should avoid using a large fraction of the input data for training as you will then not be able to detect overfitting. The ''Training fraction'' setting will be ignored for tasks 1 and 3.


| 3
| 3
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The dataset must contain a point or cell array with 1 components.
The dataset must contain a point array with 1 components.




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==Cosmology FOF Halo Finder==
==Curvature==




Sorry, no help is currently available.
This filter will compute the Gaussian or mean curvature of the mesh at each point.


The Curvature filter computes the curvature at each point in a polygonal data set. This filter supports both Gaussian and mean curvatures.<br><br><br>
; the type can be selected from the Curvature type menu button.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
{| class="PropertiesTable" border="1" cellpadding="5"
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| '''Restrictions'''
| '''Restrictions'''
|-
|-
| '''bb (linking length/distance)'''<br>''(BB)''
| '''Curvature Type'''<br>''(CurvatureType)''
|
|
Linking length measured in units of interparticle spacing and is dimensionless.  Used to link particles into halos for the friend-of-a-friend algorithm.
This propery specifies which type of curvature to compute.


| 0.2
| 0
|
|
The value must be greater than or equal to 0.
The value must be one of the following: Gaussian (0), Mean (1).




|-
|-
| '''Compute the most bound particle for halos'''<br>''(ComputeMostBoundParticle)''
| '''Input'''<br>''(Input)''
|
|
If checked, the most bound particle will be calculated.  This can be very slow.
This property specifies the input to the Curvature filter.


| 0
|
|
Only the values 0 and 1 are accepted.
|
The selected object must be the result of the following: sources (includes readers), filters.
 
 
The selected dataset must be one of the following types (or a subclass of one of them): vtkPolyData.




|-
|-
| '''Compute the most connected particle for halos'''<br>''(ComputeMostConnectedParticle)''
| '''Invert Mean Curvature'''<br>''(InvertMeanCurvature)''
|
|
If checked, the most connected particle will be calculated. This can be very slow.
If this property is set to 1, the mean curvature calculation will be inverted. This is useful for meshes with inward-pointing normals.


| 0
| 0
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|-
|}
| '''Copy halo catalog information to original particles'''<br>''(CopyHaloDataToParticles)''
 
|
 
If checked, the halo catalog information will be copied to the original particles as well.
==D3==
 


| 1
Repartition a data set into load-balanced spatially convex regions. Create ghost cells if requested.
|
Only the values 0 and 1 are accepted.


The D3 filter is available when ParaView is run in parallel. It operates on any type of data set to evenly divide it across the processors into spatially contiguous regions. The output of this filter is of type unstructured grid.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
|-
|-
| '''Halo position for 3D visualization'''<br>''(HaloPositionType)''
| '''Property'''
| '''Description'''
| '''Default Value(s)'''
| '''Restrictions'''
|-
| '''Boundary Mode'''<br>''(BoundaryMode)''
|
|
This sets the position for the halo catalog particles (second output) in 3D space for visualization. Input particle positions (first output) will be unaltered by this.  MBP and MCP for particle positions can potentially take a very long time to calculate.
This property determines how cells that lie on processor boundaries are handled. The "Assign cells uniquely" option assigns each boundary cell to exactly one process, which is useful for isosurfacing. Selecting "Duplicate cells" causes the cells on the boundaries to be copied to each process that shares that boundary. The "Divide cells" option breaks cells across process boundary lines so that pieces of the cell lie in different processes. This option is useful for volume rendering.


| 0
| 0
|
|
The value must be one of the following: Average (0), Center of Mass (1), Most Bound Particle (2), Most Connected Particle (3).
The value must be one of the following: Assign cells uniquely (0), Duplicate cells (1), Divide cells (2).




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| '''Input'''<br>''(Input)''
| '''Input'''<br>''(Input)''
|
|
This property specifies the input to the D3 filter.
|
|
|
|
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The selected dataset must be one of the following types (or a subclass of one of them): vtkUnstructuredGrid.
The selected dataset must be one of the following types (or a subclass of one of them): vtkDataSet.




|-
|-
| '''np (number of seeded particles in one dimension, i.e., total particles = np^3)'''<br>''(NP)''
| '''Minimal Memory'''<br>''(UseMinimalMemory)''
|
|
Number of seeded particles in one dimension.  Therefore, total simulation particles is np^3 (cubed).
If this property is set to 1, the D3 filter requires communication routines to use minimal memory than without this restriction.


| 256
| 0
|
|
The value must be greater than or equal to 0.
Only the values 0 and 1 are accepted.
 
 
|-
| '''overlap (shared point/ghost cell gap distance)'''<br>''(Overlap)''
|
The space in rL units to extend processor particle ownership for ghost particles/cells.  Needed for correct halo calculation when halos cross processor boundaries in parallel computation.
 
| 5
|
The value must be greater than or equal to 0.
 
 
|-
| '''pmin (minimum particle threshold for a halo)'''<br>''(PMin)''
|
Minimum number of particles (threshold) needed before a group is called a halo.
 
| 10
|
The value must be greater than or equal to 1.
 
 
|-
| '''rL (physical box side length)'''<br>''(RL)''
|
The box side length used to wrap particles around if they exceed rL (or less than 0) in any dimension (only positive positions are allowed in the input, or the are wrapped around).
 
| 90.1408
|
The value must be greater than or equal to 0.




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==Curvature==
==Decimate==




This filter will compute the Gaussian or mean curvature of the mesh at each point.
Simplify a polygonal model using an adaptive edge collapse algorithm. This filter works with triangles only.


The Curvature filter computes the curvature at each point in a polygonal data set. This filter supports both Gaussian and mean curvatures.<br><br><br>
The Decimate filter reduces the number of triangles in a polygonal data set. Because this filter only operates on triangles, first run the Triangulate filter on a dataset that contains polygons other than triangles.<br>
; the type can be selected from the Curvature type menu button.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
{| class="PropertiesTable" border="1" cellpadding="5"
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| '''Restrictions'''
| '''Restrictions'''
|-
|-
| '''Curvature Type'''<br>''(CurvatureType)''
| '''Boundary Vertex Deletion'''<br>''(BoundaryVertexDeletion)''
|
|
This propery specifies which type of curvature to compute.
If this property is set to 1, then vertices on the boundary of the dataset can be removed. Setting the value of this property to 0 preserves the boundary of the dataset, but it may cause the filter not to reach its reduction target.


| 0
| 1
|
|
The value must be one of the following: Gaussian (0), Mean (1).
Only the values 0 and 1 are accepted.




|-
|-
| '''Input'''<br>''(Input)''
| '''Feature Angle'''<br>''(FeatureAngle)''
|
|
This property specifies the input to the Curvature filter.
The value of thie property is used in determining where the data set may be split. If the angle between two adjacent triangles is greater than or equal to the FeatureAngle value, then their boundary is considered a feature edge where the dataset can be split.
 
| 15
|
The value must be greater than or equal to 0 and less than or equal to 180.
 
 
|-
| '''Input'''<br>''(Input)''
|
This property specifies the input to the Decimate filter.


|
|
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|-
|-
| '''Invert Mean Curvature'''<br>''(InvertMeanCurvature)''
| '''Preserve Topology'''<br>''(PreserveTopology)''
|
|
If this property is set to 1, the mean curvature calculation will be inverted. This is useful for meshes with inward-pointing normals.
If this property is set to 1, decimation will not split the dataset or produce holes, but it may keep the filter from reaching the reduction target. If it is set to 0, better reduction can occur (reaching the reduction target), but holes in the model may be produced.


| 0
| 0
|
|
Only the values 0 and 1 are accepted.
Only the values 0 and 1 are accepted.
|-
| '''Target Reduction'''<br>''(TargetReduction)''
|
This property specifies the desired reduction in the total number of polygons in the output dataset. For example, if the TargetReduction value is 0.9, the Decimate filter will attempt to produce an output dataset that is 10% the size of the input.)
| 0.9
|
The value must be greater than or equal to 0 and less than or equal to 1.




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==D3==
==Delaunay 2D==




Repartition a data set into load-balanced spatially convex regions. Create ghost cells if requested.
Create 2D Delaunay triangulation of input points. It expects a vtkPointSet as input and produces vtkPolyData as output. The points are expected to be in a mostly planar distribution.


The D3 filter is available when ParaView is run in parallel. It operates on any type of data set to evenly divide it across the processors into spatially contiguous regions. The output of this filter is of type unstructured grid.<br>
Delaunay2D is a filter that constructs a 2D Delaunay triangulation from a list of input points. These points may be represented by any dataset of type vtkPointSet and subclasses. The output of the filter is a polygonal dataset containing a triangle mesh.<br><br><br>
The 2D Delaunay triangulation is defined as the triangulation that satisfies the Delaunay criterion for n-dimensional simplexes (in this case n=2 and the simplexes are triangles). This criterion states that a circumsphere of each simplex in a triangulation contains only the n+1 defining points of the simplex. In two dimensions, this translates into an optimal triangulation. That is, the maximum interior angle of any triangle is less than or equal to that of any possible triangulation.<br><br><br>
Delaunay triangulations are used to build topological structures from unorganized (or unstructured) points. The input to this filter is a list of points specified in 3D, even though the triangulation is 2D. Thus the triangulation is constructed in the x-y plane, and the z coordinate is ignored (although carried through to the output). You can use the option ProjectionPlaneMode in order to compute the best-fitting plane to the set of points, project the points and that plane and then perform the triangulation using their projected positions and then use it as the plane in which the triangulation is performed.<br><br><br>
The Delaunay triangulation can be numerically sensitive in some cases. To prevent problems, try to avoid injecting points that will result in triangles with bad aspect ratios (1000:1 or greater). In practice this means inserting points that are "widely dispersed", and enables smooth transition of triangle sizes throughout the mesh. (You may even want to add extra points to create a better point distribution.) If numerical problems are present, you will see a warning message to this effect at the end of the triangulation process.<br><br><br>
Warning:<br>
Points arranged on a regular lattice (termed degenerate cases) can be triangulated in more than one way (at least according to the Delaunay criterion). The choice of triangulation (as implemented by this algorithm) depends on the order of the input points. The first three points will form a triangle; other degenerate points will not break this triangle.<br><br><br>
Points that are coincident (or nearly so) may be discarded by the algorithm. This is because the Delaunay triangulation requires unique input points. The output of the Delaunay triangulation is supposedly a convex hull. In certain cases this implementation may not generate the convex hull.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
{| class="PropertiesTable" border="1" cellpadding="5"
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| '''Restrictions'''
| '''Restrictions'''
|-
|-
| '''Boundary Mode'''<br>''(BoundaryMode)''
| '''Alpha'''<br>''(Alpha)''
|
The value of this property controls the output of this filter. For a non-zero alpha value, only edges or triangles contained within a sphere centered at mesh vertices will be output. Otherwise, only triangles will be output.
 
| 0
|
The value must be greater than or equal to 0.
 
 
|-
| '''Bounding Triangulation'''<br>''(BoundingTriangulation)''
|
|
This property determines how cells that lie on processor boundaries are handled. The "Assign cells uniquely" option assigns each boundary cell to exactly one process, which is useful for isosurfacing. Selecting "Duplicate cells" causes the cells on the boundaries to be copied to each process that shares that boundary. The "Divide cells" option breaks cells across process boundary lines so that pieces of the cell lie in different processes. This option is useful for volume rendering.
If this property is set to 1, bounding triangulation points (and associated triangles) are included in the output. These are introduced as an initial triangulation to begin the triangulation process. This feature is nice for debugging output.


| 0
| 0
|
|
The value must be one of the following: Assign cells uniquely (0), Duplicate cells (1), Divide cells (2).
Only the values 0 and 1 are accepted.




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| '''Input'''<br>''(Input)''
| '''Input'''<br>''(Input)''
|
|
This property specifies the input to the D3 filter.
This property specifies the input dataset to the Delaunay 2D filter.


|
|
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The selected dataset must be one of the following types (or a subclass of one of them): vtkDataSet.
The selected dataset must be one of the following types (or a subclass of one of them): vtkPointSet.




|-
|-
| '''Minimal Memory'''<br>''(UseMinimalMemory)''
| '''Offset'''<br>''(Offset)''
|
|
If this property is set to 1, the D3 filter requires communication routines to use minimal memory than without this restriction.
This property is a multiplier to control the size of the initial, bounding Delaunay triangulation.


| 0
| 1
|
|
Only the values 0 and 1 are accepted.
The value must be greater than or equal to 0.75.
 


|}


==Decimate==
Simplify a polygonal model using an adaptive edge collapse algorithm.  This filter works with triangles only.
The Decimate filter reduces the number of triangles in a polygonal data set. Because this filter only operates on triangles, first run the Triangulate filter on a dataset that contains polygons other than triangles.<br>
{| class="PropertiesTable" border="1" cellpadding="5"
|-
|-
| '''Property'''
| '''Projection Plane Mode'''<br>''(ProjectionPlaneMode)''
| '''Description'''
| '''Default Value(s)'''
| '''Restrictions'''
|-
| '''Boundary Vertex Deletion'''<br>''(BoundaryVertexDeletion)''
|
|
If this property is set to 1, then vertices on the boundary of the dataset can be removed. Setting the value of this property to 0 preserves the boundary of the dataset, but it may cause the filter not to reach its reduction target.
This property determines type of projection plane to use in performing the triangulation.


| 1
| 0
|
|
Only the values 0 and 1 are accepted.
The value must be one of the following: XY Plane (0), Best-Fitting Plane (2).




|-
|-
| '''Feature Angle'''<br>''(FeatureAngle)''
| '''Tolerance'''<br>''(Tolerance)''
|
|
The value of thie property is used in determining where the data set may be split. If the angle between two adjacent triangles is greater than or equal to the FeatureAngle value, then their boundary is considered a feature edge where the dataset can be split.
This property specifies a tolerance to control discarding of closely spaced points. This tolerance is specified as a fraction of the diagonal length of the bounding box of the points.


| 15
| 1e-05
|
|
The value must be greater than or equal to 0 and less than or equal to 180.
The value must be greater than or equal to 0 and less than or equal to 1.




|-
|}
| '''Input'''<br>''(Input)''
|
This property specifies the input to the Decimate filter.


|
|
The selected object must be the result of the following: sources (includes readers), filters.


==Delaunay 3D==


The selected dataset must be one of the following types (or a subclass of one of them): vtkPolyData.


Create a 3D Delaunay triangulation of input points. It expects a vtkPointSet as input and produces vtkUnstructuredGrid as output.


|-
Delaunay3D is a filter that constructs a 3D Delaunay triangulation<br>
| '''Preserve Topology'''<br>''(PreserveTopology)''
from a list of input points. These points may be represented by any<br>
|
dataset of type vtkPointSet and subclasses. The output of the filter<br>
If this property is set to 1, decimation will not split the dataset or produce holes, but it may keep the filter from reaching the reduction target. If it is set to 0, better reduction can occur (reaching the reduction target), but holes in the model may be produced.
is an unstructured grid dataset. Usually the output is a tetrahedral<br>
 
mesh, but if a non-zero alpha distance value is specified (called<br>
| 0
the "alpha" value), then only tetrahedra, triangles, edges, and<br>
|
vertices lying within the alpha radius are output. In other words,<br>
Only the values 0 and 1 are accepted.
non-zero alpha values may result in arbitrary combinations of<br>
 
tetrahedra, triangles, lines, and vertices. (The notion of alpha<br>
 
value is derived from Edelsbrunner's work on "alpha shapes".)<br><br><br>
|-
The 3D Delaunay triangulation is defined as the triangulation that<br>
| '''Target Reduction'''<br>''(TargetReduction)''
satisfies the Delaunay criterion for n-dimensional simplexes (in<br>
|
this case n=3 and the simplexes are tetrahedra). This criterion<br>
This property specifies the desired reduction in the total number of polygons in the output dataset. For example, if the TargetReduction value is 0.9, the Decimate filter will attempt to produce an output dataset that is 10% the size of the input.)
states that a circumsphere of each simplex in a triangulation<br>
 
contains only the n+1 defining points of the simplex. (See text for<br>
| 0.9
more information.) While in two dimensions this translates into an<br>
|
"optimal" triangulation, this is not true in 3D, since a measurement<br>
The value must be greater than or equal to 0 and less than or equal to 1.
for optimality in 3D is not agreed on.<br><br><br>
 
Delaunay triangulations are used to build topological structures<br>
 
from unorganized (or unstructured) points. The input to this filter<br>
|}
is a list of points specified in 3D. (If you wish to create 2D<br>
 
triangulations see Delaunay2D.) The output is an unstructured<br>
 
grid.<br><br><br>
==Delaunay 2D==
The Delaunay triangulation can be numerically sensitive. To prevent<br>
 
problems, try to avoid injecting points that will result in<br>
 
triangles with bad aspect ratios (1000:1 or greater). In practice<br>
Create 2D Delaunay triangulation of input points. It expects a vtkPointSet as input and produces vtkPolyData as output. The points are expected to be in a mostly planar distribution.
this means inserting points that are "widely dispersed", and enables<br>
 
smooth transition of triangle sizes throughout the mesh. (You may<br>
Delaunay2D is a filter that constructs a 2D Delaunay triangulation from a list of input points. These points may be represented by any dataset of type vtkPointSet and subclasses. The output of the filter is a polygonal dataset containing a triangle mesh.<br><br><br>
even want to add extra points to create a better point<br>
The 2D Delaunay triangulation is defined as the triangulation that satisfies the Delaunay criterion for n-dimensional simplexes (in this case n=2 and the simplexes are triangles). This criterion states that a circumsphere of each simplex in a triangulation contains only the n+1 defining points of the simplex. In two dimensions, this translates into an optimal triangulation. That is, the maximum interior angle of any triangle is less than or equal to that of any possible triangulation.<br><br><br>
distribution.) If numerical problems are present, you will see a<br>
Delaunay triangulations are used to build topological structures from unorganized (or unstructured) points. The input to this filter is a list of points specified in 3D, even though the triangulation is 2D. Thus the triangulation is constructed in the x-y plane, and the z coordinate is ignored (although carried through to the output). You can use the option ProjectionPlaneMode in order to compute the best-fitting plane to the set of points, project the points and that plane and then perform the triangulation using their projected positions and then use it as the plane in which the triangulation is performed.<br><br><br>
warning message to this effect at the end of the triangulation<br>
The Delaunay triangulation can be numerically sensitive in some cases. To prevent problems, try to avoid injecting points that will result in triangles with bad aspect ratios (1000:1 or greater). In practice this means inserting points that are "widely dispersed", and enables smooth transition of triangle sizes throughout the mesh. (You may even want to add extra points to create a better point distribution.) If numerical problems are present, you will see a warning message to this effect at the end of the triangulation process.<br><br><br>
process.<br><br><br>
Warning:<br>
Warning:<br>
Points arranged on a regular lattice (termed degenerate cases) can be triangulated in more than one way (at least according to the Delaunay criterion). The choice of triangulation (as implemented by this algorithm) depends on the order of the input points. The first three points will form a triangle; other degenerate points will not break this triangle.<br><br><br>
Points arranged on a regular lattice (termed degenerate cases) can<br>
Points that are coincident (or nearly so) may be discarded by the algorithm. This is because the Delaunay triangulation requires unique input points. The output of the Delaunay triangulation is supposedly a convex hull. In certain cases this implementation may not generate the convex hull.<br>
be triangulated in more than one way (at least according to the<br>
Delaunay criterion). The choice of triangulation (as implemented by<br>
this algorithm) depends on the order of the input points. The first<br>
four points will form a tetrahedron; other degenerate points<br>
(relative to this initial tetrahedron) will not break it.<br><br><br>
Points that are coincident (or nearly so) may be discarded by the<br>
algorithm. This is because the Delaunay triangulation requires<br>
unique input points. You can control the definition of coincidence<br>
with the "Tolerance" instance variable.<br><br><br>
The output of the Delaunay triangulation is supposedly a convex<br>
hull. In certain cases this implementation may not generate the<br>
convex hull. This behavior can be controlled by the Offset instance<br>
variable. Offset is a multiplier used to control the size of the<br>
initial triangulation. The larger the offset value, the more likely<br>
you will generate a convex hull; and the more likely you are to see<br>
numerical problems.<br><br><br>
The implementation of this algorithm varies from the 2D Delaunay<br>
algorithm (i.e., Delaunay2D) in an important way. When points are<br>
injected into the triangulation, the search for the enclosing<br>
tetrahedron is quite different. In the 3D case, the closest<br>
previously inserted point point is found, and then the connected<br>
tetrahedra are searched to find the containing one. (In 2D, a "walk"<br>
towards the enclosing triangle is performed.) If the triangulation<br>
is Delaunay, then an enclosing tetrahedron will be found. However,<br>
in degenerate cases an enclosing tetrahedron may not be found and<br>
the point will be rejected.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
{| class="PropertiesTable" border="1" cellpadding="5"
Line 1,491: Line 1,523:
| '''Alpha'''<br>''(Alpha)''
| '''Alpha'''<br>''(Alpha)''
|
|
The value of this property controls the output of this filter. For a non-zero alpha value, only edges or triangles contained within a sphere centered at mesh vertices will be output. Otherwise, only triangles will be output.
This property specifies the alpha (or distance) value to control
the output of this filter. For a non-zero alpha value, only
edges, faces, or tetra contained within the circumsphere (of
radius alpha) will be output. Otherwise, only tetrahedra will be
output.


| 0
| 0
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| '''Bounding Triangulation'''<br>''(BoundingTriangulation)''
| '''Bounding Triangulation'''<br>''(BoundingTriangulation)''
|
|
If this property is set to 1, bounding triangulation points (and associated triangles) are included in the output. These are introduced as an initial triangulation to begin the triangulation process. This feature is nice for debugging output.
This boolean controls whether bounding triangulation points (and
associated triangles) are included in the output. (These are
introduced as an initial triangulation to begin the triangulation
process. This feature is nice for debugging output.)


| 0
| 0
Line 1,511: Line 1,550:
| '''Input'''<br>''(Input)''
| '''Input'''<br>''(Input)''
|
|
This property specifies the input dataset to the Delaunay 2D filter.
This property specifies the input dataset to the Delaunay 3D filter.


|
|
Line 1,524: Line 1,563:
| '''Offset'''<br>''(Offset)''
| '''Offset'''<br>''(Offset)''
|
|
This property is a multiplier to control the size of the initial, bounding Delaunay triangulation.
This property specifies a multiplier to control the size of the
initial, bounding Delaunay triangulation.


| 1
| 2.5
|
|
The value must be greater than or equal to 0.75.
The value must be greater than or equal to 2.5.




|-
|-
| '''Projection Plane Mode'''<br>''(ProjectionPlaneMode)''
| '''Tolerance'''<br>''(Tolerance)''
|
This property specifies a tolerance to control discarding of
closely spaced points. This tolerance is specified as a fraction
of the diagonal length of the bounding box of the points.
 
| 0.001
|
The value must be greater than or equal to 0 and less than or equal to 1.
 
 
|}
 
 
==Descriptive Statistics==
 
 
Compute a statistical model of a dataset and/or assess the dataset with a statistical model.
 
This filter either computes a statistical model of a dataset or takes such a model as its second input. Then, the model (however it is obtained) may optionally be used to assess the input dataset.
<br>
This filter computes the min, max, mean, raw moments M2 through M4, standard deviation, skewness, and kurtosis for each array you select.
 
<br>
The model is simply a univariate Gaussian distribution with the mean and standard deviation provided. Data is assessed using this model by detrending the data (i.e., subtracting the mean) and then dividing by the standard deviation. Thus the assessment is an array whose entries are the number of standard deviations from the mean that each input point lies.<br>
 
 
{| class="PropertiesTable" border="1" cellpadding="5"
|-
| '''Property'''
| '''Description'''
| '''Default Value(s)'''
| '''Restrictions'''
|-
| '''Attribute Mode'''<br>''(AttributeMode)''
|
|
This property determines type of projection plane to use in performing the triangulation.
Specify which type of field data the arrays will be drawn from.


| 0
| 0
|
|
The value must be one of the following: XY Plane (0), Best-Fitting Plane (2).
Valud array names will be chosen from point and cell data.




|-
|-
| '''Tolerance'''<br>''(Tolerance)''
| '''Input'''<br>''(Input)''
|
|
This property specifies a tolerance to control discarding of closely spaced points. This tolerance is specified as a fraction of the diagonal length of the bounding box of the points.
The input to the filter. Arrays from this dataset will be used for computing statistics and/or assessed by a statistical model.


| 1e-05
|
|
The value must be greater than or equal to 0 and less than or equal to 1.
|
The selected object must be the result of the following: sources (includes readers), filters.




|}
The dataset must contain a point or cell array.




==Delaunay 3D==
The selected dataset must be one of the following types (or a subclass of one of them): vtkImageData, vtkStructuredGrid, vtkPolyData, vtkUnstructuredGrid, vtkTable, vtkGraph.
 


Create a 3D Delaunay triangulation of input                                points.  It expects a vtkPointSet as input and                                produces vtkUnstructuredGrid as output.


Delaunay3D is a filter that constructs a 3D Delaunay triangulation<br>
|-
from a list of input points. These points may be represented by any<br>
| '''Model Input'''<br>''(ModelInput)''
dataset of type vtkPointSet and subclasses. The output of the filter<br>
|
is an unstructured grid dataset. Usually the output is a tetrahedral<br>
A previously-calculated model with which to assess a separate dataset. This input is optional.
mesh, but if a non-zero alpha distance value is specified (called<br>
 
the "alpha" value), then only tetrahedra, triangles, edges, and<br>
|
vertices lying within the alpha radius are output. In other words,<br>
|
non-zero alpha values may result in arbitrary combinations of<br>
The selected object must be the result of the following: sources (includes readers), filters.
tetrahedra, triangles, lines, and vertices. (The notion of alpha<br>
 
value is derived from Edelsbrunner's work on "alpha shapes".)<br><br><br>
 
The 3D Delaunay triangulation is defined as the triangulation that<br>
The selected dataset must be one of the following types (or a subclass of one of them): vtkTable, vtkMultiBlockDataSet.
satisfies the Delaunay criterion for n-dimensional simplexes (in<br>
 
this case n=3 and the simplexes are tetrahedra). This criterion<br>
 
states that a circumsphere of each simplex in a triangulation<br>
|-
contains only the n+1 defining points of the simplex. (See text for<br>
| '''Variables of Interest'''<br>''(SelectArrays)''
more information.) While in two dimensions this translates into an<br>
|
"optimal" triangulation, this is not true in 3D, since a measurement<br>
Choose arrays whose entries will be used to form observations for statistical analysis.
for optimality in 3D is not agreed on.<br><br><br>
 
Delaunay triangulations are used to build topological structures<br>
|
from unorganized (or unstructured) points. The input to this filter<br>
|
is a list of points specified in 3D. (If you wish to create 2D<br>
An array of scalars is required.
triangulations see Delaunay2D.) The output is an unstructured<br>
 
grid.<br><br><br>
 
The Delaunay triangulation can be numerically sensitive. To prevent<br>
|-
problems, try to avoid injecting points that will result in<br>
| '''Deviations should be'''<br>''(SignedDeviations)''
triangles with bad aspect ratios (1000:1 or greater). In practice<br>
|
this means inserting points that are "widely dispersed", and enables<br>
Should the assessed values be signed deviations or unsigned?
smooth transition of triangle sizes throughout the mesh. (You may<br>
even want to add extra points to create a better point<br>
distribution.) If numerical problems are present, you will see a<br>
warning message to this effect at the end of the triangulation<br>
process.<br><br><br>
Warning:<br>
Points arranged on a regular lattice (termed degenerate cases) can<br>
be triangulated in more than one way (at least according to the<br>
Delaunay criterion). The choice of triangulation (as implemented by<br>
this algorithm) depends on the order of the input points. The first<br>
four points will form a tetrahedron; other degenerate points<br>
(relative to this initial tetrahedron) will not break it.<br><br><br>
Points that are coincident (or nearly so) may be discarded by the<br>
algorithm. This is because the Delaunay triangulation requires<br>
unique input points. You can control the definition of coincidence<br>
with the "Tolerance" instance variable.<br><br><br>
The output of the Delaunay triangulation is supposedly a convex<br>
hull. In certain cases this implementation may not generate the<br>
convex hull. This behavior can be controlled by the Offset instance<br>
variable. Offset is a multiplier used to control the size of the<br>
initial triangulation. The larger the offset value, the more likely<br>
you will generate a convex hull; and the more likely you are to see<br>
numerical problems.<br><br><br>
The implementation of this algorithm varies from the 2D Delaunay<br>
algorithm (i.e., Delaunay2D) in an important way. When points are<br>
injected into the triangulation, the search for the enclosing<br>
tetrahedron is quite different. In the 3D case, the closest<br>
previously inserted point point is found, and then the connected<br>
tetrahedra are searched to find the containing one. (In 2D, a "walk"<br>
towards the enclosing triangle is performed.) If the triangulation<br>
is Delaunay, then an enclosing tetrahedron will be found. However,<br>
in degenerate cases an enclosing tetrahedron may not be found and<br>
the point will be rejected.<br>
 
{| class="PropertiesTable" border="1" cellpadding="5"
|-
| '''Property'''
| '''Description'''
| '''Default Value(s)'''
| '''Restrictions'''
|-
| '''Alpha'''<br>''(Alpha)''
|
This property specifies the alpha (or distance) value to control
the output of this filter.  For a non-zero alpha value, only
edges, faces, or tetra contained within the circumsphere (of
radius alpha) will be output.  Otherwise, only tetrahedra will be
output.


| 0
| 0
|
|
The value must be greater than or equal to 0.
The value must be one of the following: Unsigned (0), Signed (1).




|-
|-
| '''Bounding Triangulation'''<br>''(BoundingTriangulation)''
| '''Task'''<br>''(Task)''
|
|
This boolean controls whether bounding triangulation points (and
Specify the task to be performed: modeling and/or assessment.
associated triangles) are included in the output. (These are
#  "Statistics of all the data," creates an output table (or tables) summarizing the '''entire''' input dataset;
introduced as an initial triangulation to begin the triangulation
#  "Model a subset of the data," creates an output table (or tables) summarizing a '''randomly-chosen subset''' of the input dataset;
process. This feature is nice for debugging output.)
#  "Assess the data with a model," adds attributes to the first input dataset using a model provided on the second input port; and
#  "Model and assess the same data," is really just operations 2 and 3 above applied to the same input dataset. The model is first trained using a fraction of the input data and then the entire dataset is assessed using that model.


| 0
When the task includes creating a model (i.e., tasks 2, and 4), you may adjust the fraction of the input dataset used for training. You should avoid using a large fraction of the input data for training as you will then not be able to detect overfitting. The ''Training fraction'' setting will be ignored for tasks 1 and 3.
|
Only the values 0 and 1 are accepted.


 
| 3
|-
| '''Input'''<br>''(Input)''
|
|
This property specifies the input dataset to the Delaunay 3D filter.
The value must be one of the following: Statistics of all the data (0), Model a subset of the data (1), Assess the data with a model (2), Model and assess the same data (3).
 
|
|
The selected object must be the result of the following: sources (includes readers), filters.
 
 
The selected dataset must be one of the following types (or a subclass of one of them): vtkPointSet.




|-
|-
| '''Offset'''<br>''(Offset)''
| '''Training Fraction'''<br>''(TrainingFraction)''
|
|
This property specifies a multiplier to control the size of the
Specify the fraction of values from the input dataset to be used for model fitting. The exact set of values is chosen at random from the dataset.
initial, bounding Delaunay triangulation.


| 2.5
| 0.1
|
The value must be greater than or equal to 2.5.
 
 
|-
| '''Tolerance'''<br>''(Tolerance)''
|
This property specifies a tolerance to control discarding of
closely spaced points. This tolerance is specified as a fraction
of the diagonal length of the bounding box of the points.
 
| 0.001
|
|
The value must be greater than or equal to 0 and less than or equal to 1.
The value must be greater than or equal to 0 and less than or equal to 1.
Line 1,692: Line 1,693:




==Descriptive Statistics==
==Elevation==




Compute a statistical model of a dataset and/or assess the dataset with a statistical model.
Create point attribute array by projecting points onto an elevation vector.
 
This filter either computes a statistical model of a dataset or takes such a model as its second input.  Then, the model (however it is obtained) may optionally be used to assess the input dataset.
<br>
This filter computes the min, max, mean, raw moments M2 through M4, standard deviation, skewness, and kurtosis for each array you select.
 
<br>
The model is simply a univariate Gaussian distribution with the mean and standard deviation provided. Data is assessed using this model by detrending the data (i.e., subtracting the mean) and then dividing by the standard deviation. Thus the assessment is an array whose entries are the number of standard deviations from the mean that each input point lies.<br>


The Elevation filter generates point scalar values for an input dataset along a specified direction vector.<br><br><br>
The Input menu allows the user to select the data set to which this filter will be applied. Use the Scalar range entry boxes to specify the minimum and maximum scalar value to be generated. The Low Point and High Point define a line onto which each point of the data set is projected. The minimum scalar value is associated with the Low Point, and the maximum scalar value is associated with the High Point. The scalar value for each point in the data set is determined by the location along the line to which that point projects.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
{| class="PropertiesTable" border="1" cellpadding="5"
Line 1,712: Line 1,708:
| '''Restrictions'''
| '''Restrictions'''
|-
|-
| '''Attribute Mode'''<br>''(AttributeMode)''
| '''High Point'''<br>''(HighPoint)''
|
|
Specify which type of field data the arrays will be drawn from.
This property defines the other end of the direction vector (large scalar values).


| 0
| 0 0 1
|
|
Valud array names will be chosen from point and cell data.
The coordinate must lie within the bounding box of the dataset. It will default to the maximum in each dimension.




Line 1,724: Line 1,720:
| '''Input'''<br>''(Input)''
| '''Input'''<br>''(Input)''
|
|
The input to the filter.  Arrays from this dataset will be used for computing statistics and/or assessed by a statistical model.
This property specifies the input dataset to the Elevation filter.


|
|
Line 1,731: Line 1,727:




The dataset must contain a point or cell array.
The selected dataset must be one of the following types (or a subclass of one of them): vtkDataSet.
 


|-
| '''Low Point'''<br>''(LowPoint)''
|
This property defines one end of the direction vector (small scalar values).


The selected dataset must be one of the following types (or a subclass of one of them): vtkImageData, vtkStructuredGrid, vtkPolyData, vtkUnstructuredGrid, vtkTable, vtkGraph.
| 0 0 0
|
The coordinate must lie within the bounding box of the dataset. It will default to the minimum in each dimension.




|-
|-
| '''Model Input'''<br>''(ModelInput)''
| '''Scalar Range'''<br>''(ScalarRange)''
|
|
A previously-calculated model with which to assess a separate dataset.  This input is optional.
This property determines the range into which scalars will be mapped.


| 0 1
|
|
|
|}
The selected object must be the result of the following: sources (includes readers), filters.
 
 
==Extract AMR Blocks==




The selected dataset must be one of the following types (or a subclass of one of them): vtkTable, vtkMultiBlockDataSet.
This filter extracts a list of datasets from hierarchical datasets.


This filter extracts a list of datasets from hierarchical datasets.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
|-
| '''Property'''
| '''Description'''
| '''Default Value(s)'''
| '''Restrictions'''
|-
|-
| '''Variables of Interest'''<br>''(SelectArrays)''
| '''Input'''<br>''(Input)''
|
|
Choose arrays whose entries will be used to form observations for statistical analysis.
This property specifies the input to the Extract Datasets filter.


|
|
|
|
An array of scalars is required.
The selected object must be the result of the following: sources (includes readers), filters.
 
 
The selected dataset must be one of the following types (or a subclass of one of them): vtkHierarchicalBoxDataSet.




|-
|-
| '''Deviations should be'''<br>''(SignedDeviations)''
| '''Selected Data Sets'''<br>''(SelectedDataSets)''
|
|
Should the assessed values be signed deviations or unsigned?
This property provides a list of datasets to extract.


| 0
|
|
The value must be one of the following: Unsigned (0), Signed (1).
|
|}
 


==Extract Block==


|-
| '''Task'''<br>''(Task)''
|
Specify the task to be performed: modeling and/or assessment.
#  "Statistics of all the data," creates an output table (or tables) summarizing the '''entire''' input dataset;
#  "Model a subset of the data," creates an output table (or tables) summarizing a '''randomly-chosen subset''' of the input dataset;
#  "Assess the data with a model," adds attributes to the first input dataset using a model provided on the second input port; and
#  "Model and assess the same data," is really just operations 2 and 3 above applied to the same input dataset.  The model is first trained using a fraction of the input data and then the entire dataset is assessed using that model.


When the task includes creating a model (i.e., tasks 2, and 4), you may adjust the fraction of the input dataset used for training.  You should avoid using a large fraction of the input data for training as you will then not be able to detect overfitting.  The ''Training fraction'' setting will be ignored for tasks 1 and 3.
This filter extracts a range of blocks from a multiblock dataset.


| 3
This filter extracts a range of groups from a multiblock dataset<br>
|
The value must be one of the following: Statistics of all the data (0), Model a subset of the data (1), Assess the data with a model (2), Model and assess the same data (3).
 
 
|-
| '''Training Fraction'''<br>''(TrainingFraction)''
|
Specify the fraction of values from the input dataset to be used for model fitting. The exact set of values is chosen at random from the dataset.
 
| 0.1
|
The value must be greater than or equal to 0 and less than or equal to 1.
 
 
|}
 
 
==Elevation==
 
 
Create point attribute array by projecting points onto an elevation vector.
 
The Elevation filter generates point scalar values for an input dataset along a specified direction vector.<br><br><br>
The Input menu allows the user to select the data set to which this filter will be applied. Use the Scalar range entry boxes to specify the minimum and maximum scalar value to be generated. The Low Point and High Point define a line onto which each point of the data set is projected. The minimum scalar value is associated with the Low Point, and the maximum scalar value is associated with the High Point. The scalar value for each point in the data set is determined by the location along the line to which that point projects.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
{| class="PropertiesTable" border="1" cellpadding="5"
Line 1,814: Line 1,800:
| '''Restrictions'''
| '''Restrictions'''
|-
|-
| '''High Point'''<br>''(HighPoint)''
| '''Block Indices'''<br>''(BlockIndices)''
|
|
This property defines the other end of the direction vector (large scalar values).
This property lists the ids of the blocks to extract
from the input multiblock dataset.


| 0 0 1
|
|
The coordinate must lie within the bounding box of the dataset. It will default to the maximum in each dimension.
|
 
 
|-
|-
| '''Input'''<br>''(Input)''
| '''Input'''<br>''(Input)''
|
|
This property specifies the input dataset to the Elevation filter.
This property specifies the input to the Extract Group filter.


|
|
Line 1,833: Line 1,817:




The selected dataset must be one of the following types (or a subclass of one of them): vtkDataSet.
The selected dataset must be one of the following types (or a subclass of one of them): vtkMultiBlockDataSet.




|-
|-
| '''Low Point'''<br>''(LowPoint)''
| '''Maintain Structure'''<br>''(MaintainStructure)''
|
|
This property defines one end of the direction vector (small scalar values).
This is used only when PruneOutput is ON. By default, when pruning the
output i.e. remove empty blocks, if node has only 1 non-null child
block, then that node is removed. To preserve these parent nodes, set
this flag to true.


| 0 0 0
| 0
|
|
The coordinate must lie within the bounding box of the dataset. It will default to the minimum in each dimension.
Only the values 0 and 1 are accepted.




|-
|-
| '''Scalar Range'''<br>''(ScalarRange)''
| '''Prune Output'''<br>''(PruneOutput)''
|
|
This property determines the range into which scalars will be mapped.
When set, the output mutliblock dataset will be pruned to remove empty
nodes. On by default.


| 0 1
| 1
|
|
Only the values 0 and 1 are accepted.
|}
|}




==Extract AMR Blocks==
==Extract CTH Parts==




This filter extracts a list of datasets from hierarchical datasets.
Create a surface from a CTH volume fraction.


This filter extracts a list of datasets from hierarchical datasets.<br>
Extract CTH Parts is a specialized filter for visualizing the data from a CTH simulation. It first converts the selected cell-centered arrays to point-centered ones. It then contours each array at a value of 0.5. The user has the option of clipping the resulting surface(s) with a plane. This filter only operates on unstructured data. It produces polygonal output.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
{| class="PropertiesTable" border="1" cellpadding="5"
Line 1,870: Line 1,861:
| '''Restrictions'''
| '''Restrictions'''
|-
|-
| '''Input'''<br>''(Input)''
| '''Double Volume Arrays'''<br>''(AddDoubleVolumeArrayName)''
|
|
This property specifies the input to the Extract Datasets filter.
This property specifies the name(s) of the volume fraction array(s) for generating parts.


|
|
|
|
The selected object must be the result of the following: sources (includes readers), filters.
An array of scalars is required.
 


|-
| '''Float Volume Arrays'''<br>''(AddFloatVolumeArrayName)''
|
This property specifies the name(s) of the volume fraction array(s) for generating parts.


The selected dataset must be one of the following types (or a subclass of one of them): vtkHierarchicalBoxDataSet.
|
|
An array of scalars is required.




|-
|-
| '''Selected Data Sets'''<br>''(SelectedDataSets)''
| '''Unsigned Character Volume Arrays'''<br>''(AddUnsignedCharVolumeArrayName)''
|
|
This property provides a list of datasets to extract.
This property specifies the name(s) of the volume fraction array(s) for generating parts.


|
|
|
|
|}
An array of scalars is required.




==Extract Block==
|-
| '''Clip Type'''<br>''(ClipPlane)''
|
This property specifies whether to clip the dataset, and if so, it also specifies the parameters of the plane with which to clip.


|
|
The value must be set to one of the following: None, Plane, Box, Sphere.


This filter extracts a range of blocks from a multiblock dataset.
This filter extracts a range of groups from a multiblock dataset<br>


{| class="PropertiesTable" border="1" cellpadding="5"
|-
|-
| '''Property'''
| '''Input'''<br>''(Input)''
| '''Description'''
| '''Default Value(s)'''
| '''Restrictions'''
|-
| '''Block Indices'''<br>''(BlockIndices)''
|
|
This property lists the ids of the blocks to extract
This property specifies the input to the Extract CTH Parts filter.
from the input multiblock dataset.
 
|
|
|-
| '''Input'''<br>''(Input)''
|
This property specifies the input to the Extract Group filter.


|
|
Line 1,923: Line 1,910:




The selected dataset must be one of the following types (or a subclass of one of them): vtkMultiBlockDataSet.
The dataset must contain a cell array with 1 components.




|-
The selected dataset must be one of the following types (or a subclass of one of them): vtkDataSet.
| '''Maintain Structure'''<br>''(MaintainStructure)''
|
This is used only when PruneOutput is ON. By default, when pruning the
output i.e. remove empty blocks, if node has only 1 non-null child
block, then that node is removed. To preserve these parent nodes, set
this flag to true.
 
| 0
|
Only the values 0 and 1 are accepted.




|-
|-
| '''Prune Output'''<br>''(PruneOutput)''
| '''Volume Fraction Value'''<br>''(VolumeFractionSurfaceValue)''
|
|
When set, the output mutliblock dataset will be pruned to remove empty
The value of this property is the volume fraction value for the surface.
nodes. On by default.


| 1
| 0.1
|
|
Only the values 0 and 1 are accepted.
The value must be greater than or equal to 0 and less than or equal to 1.




Line 1,953: Line 1,929:




==Extract CTH Parts==
==Extract Cells By Region==




Create a surface from a CTH volume fraction.
This filter extracts cells that are inside/outside a region or at a region boundary.


Extract CTH Parts is a specialized filter for visualizing the data from a CTH simulation. It first converts the selected cell-centered arrays to point-centered ones. It then contours each array at a value of 0.5. The user has the option of clipping the resulting surface(s) with a plane. This filter only operates on unstructured data. It produces polygonal output.<br>
This filter extracts from its input dataset all cells that are either completely inside or outside of a specified region (implicit function). On output, the filter generates an unstructured grid.<br>
To use this filter you must specify a region (implicit function). You must also specify whethter to extract cells lying inside or outside of the region. An option exists to extract cells that are neither inside or outside (i.e., boundary).<br>


{| class="PropertiesTable" border="1" cellpadding="5"
{| class="PropertiesTable" border="1" cellpadding="5"
Line 1,967: Line 1,944:
| '''Restrictions'''
| '''Restrictions'''
|-
|-
| '''Double Volume Arrays'''<br>''(AddDoubleVolumeArrayName)''
| '''Extract intersected'''<br>''(Extract intersected)''
|
|
This property specifies the name(s) of the volume fraction array(s) for generating parts.
This parameter controls whether to extract cells that are on the boundary of the region.


| 0
|
|
|
Only the values 0 and 1 are accepted.
An array of scalars is required.




|-
|-
| '''Float Volume Arrays'''<br>''(AddFloatVolumeArrayName)''
| '''Extract only intersected'''<br>''(Extract only intersected)''
|
|
This property specifies the name(s) of the volume fraction array(s) for generating parts.
This parameter controls whether to extract only cells that are on the boundary of the region. If this parameter is set, the Extraction Side parameter is ignored. If Extract Intersected is off, this parameter has no effect.


| 0
|
|
|
Only the values 0 and 1 are accepted.
An array of scalars is required.




|-
|-
| '''Unsigned Character Volume Arrays'''<br>''(AddUnsignedCharVolumeArrayName)''
| '''Extraction Side'''<br>''(ExtractInside)''
|
|
This property specifies the name(s) of the volume fraction array(s) for generating parts.
This parameter controls whether to extract cells that are inside or outside the region.


| 1
|
|
|
The value must be one of the following: outside (0), inside (1).
An array of scalars is required.




|-
|-
| '''Clip Type'''<br>''(ClipPlane)''
| '''Intersect With'''<br>''(ImplicitFunction)''
|
|
This property specifies whether to clip the dataset, and if so, it also specifies the parameters of the plane with which to clip.
This property sets the region used to extract cells.


|
|
|
|
The value must be set to one of the following: None, Plane, Box, Sphere.
The value must be set to one of the following: Plane, Box, Sphere.




Line 2,009: Line 1,986:
| '''Input'''<br>''(Input)''
| '''Input'''<br>''(Input)''
|
|
This property specifies the input to the Extract CTH Parts filter.
This property specifies the input to the Slice filter.


|
|
|
|
The selected object must be the result of the following: sources (includes readers), filters.
The selected object must be the result of the following: sources (includes readers), filters.
The dataset must contain a cell array with 1 components.




The selected dataset must be one of the following types (or a subclass of one of them): vtkDataSet.
The selected dataset must be one of the following types (or a subclass of one of them): vtkDataSet.
|-
| '''Volume Fraction Value'''<br>''(VolumeFractionSurfaceValue)''
|
The value of this property is the volume fraction value for the surface.
| 0.1
|
The value must be greater than or equal to 0 and less than or equal to 1.




Line 2,035: Line 1,999:




==Extract Cells By Region==
==Extract Edges==




This filter extracts cells that are inside/outside a region or at a region boundary.
Extract edges of 2D and 3D cells as lines.


This filter extracts from its input dataset all cells that are either completely inside or outside of a specified region (implicit function). On output, the filter generates an unstructured grid.<br>
The Extract Edges filter produces a wireframe version of the input dataset by extracting all the edges of the dataset's cells as lines. This filter operates on any type of data set and produces polygonal output.<br>
To use this filter you must specify a region  (implicit function). You must also specify whethter to extract cells lying inside or outside of the region. An option exists to extract cells that are neither inside or outside (i.e., boundary).<br>


{| class="PropertiesTable" border="1" cellpadding="5"
{| class="PropertiesTable" border="1" cellpadding="5"
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| '''Restrictions'''
| '''Restrictions'''
|-
|-
| '''Extract intersected'''<br>''(Extract intersected)''
| '''Input'''<br>''(Input)''
|
|
This parameter controls whether to extract cells that are on the boundary of the region.
This property specifies the input to the Extract Edges filter.


| 0
|
|
Only the values 0 and 1 are accepted.
|
The selected object must be the result of the following: sources (includes readers), filters.
 


The selected dataset must be one of the following types (or a subclass of one of them): vtkDataSet.


|-
| '''Extract only intersected'''<br>''(Extract only intersected)''
|
This parameter controls whether to extract only cells that are on the boundary of the region. If this parameter is set, the Extraction Side parameter is ignored. If Extract Intersected is off, this parameter has no effect.


| 0
|}
|
 
Only the values 0 and 1 are accepted.


==Extract Level==


|-
| '''Extraction Side'''<br>''(ExtractInside)''
|
This parameter controls whether to extract cells that are inside or outside the region.


| 1
This filter extracts a range of groups from a hierarchical dataset.
|
The value must be one of the following: outside (0), inside (1).


This filter extracts a range of levels from a hierarchical dataset<br>


{| class="PropertiesTable" border="1" cellpadding="5"
|-
|-
| '''Intersect With'''<br>''(ImplicitFunction)''
| '''Property'''
| '''Description'''
| '''Default Value(s)'''
| '''Restrictions'''
|-
| '''Input'''<br>''(Input)''
|
|
This property sets the region used to extract cells.
This property specifies the input to the Extract Group filter.


|
|
|
|
The value must be set to one of the following: Plane, Box, Sphere.
The selected object must be the result of the following: sources (includes readers), filters.
 
 
The selected dataset must be one of the following types (or a subclass of one of them): vtkHierarchicalBoxDataSet.




|-
|-
| '''Input'''<br>''(Input)''
| '''Levels'''<br>''(Levels)''
|
|
This property specifies the input to the Slice filter.
This property lists the levels to extract
from the input hierarchical dataset.


|
|
|
|
The selected object must be the result of the following: sources (includes readers), filters.
The selected dataset must be one of the following types (or a subclass of one of them): vtkDataSet.
|}
|}




==Extract Edges==
==Extract Selection==




Extract edges of 2D and 3D cells as lines.
Extract different type of selections.


The Extract Edges filter produces a wireframe version of the input dataset by extracting all the edges of the dataset's cells as lines. This filter operates on any type of data set and produces polygonal output.<br>
This filter extracts a set of cells/points given a selection.<br>
The selection can be obtained from a rubber-band selection<br>
(either cell, visible or in a frustum) or threshold selection<br>
and passed to the filter or specified by providing an ID list.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
{| class="PropertiesTable" border="1" cellpadding="5"
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| '''Input'''<br>''(Input)''
| '''Input'''<br>''(Input)''
|
|
This property specifies the input to the Extract Edges filter.
This property specifies the input from which the selection is extracted.


|
|
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The selected dataset must be one of the following types (or a subclass of one of them): vtkDataSet.
The selected dataset must be one of the following types (or a subclass of one of them): vtkDataSet, vtkTable.




|}
|-
| '''Preserve Topology'''<br>''(PreserveTopology)''
|
If this property is set to 1 the output preserves the topology of its
input and adds an insidedness array to mark which cells are inside or
out. If 0 then the output is an unstructured grid which contains only
the subset of cells that are inside.


| 0
|
Only the values 0 and 1 are accepted.


==Extract Level==


This filter extracts a range of groups from a hierarchical dataset.
This filter extracts a range of levels from a hierarchical dataset<br>
{| class="PropertiesTable" border="1" cellpadding="5"
|-
|-
| '''Property'''
| '''Selection'''<br>''(Selection)''
| '''Description'''
| '''Default Value(s)'''
| '''Restrictions'''
|-
| '''Input'''<br>''(Input)''
|
|
This property specifies the input to the Extract Group filter.
The input that provides the selection object.


|
|
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The selected dataset must be one of the following types (or a subclass of one of them): vtkHierarchicalBoxDataSet.
The selected dataset must be one of the following types (or a subclass of one of them): vtkSelection.




|-
|-
| '''Levels'''<br>''(Levels)''
| '''Show Bounds'''<br>''(ShowBounds)''
|
|
This property lists the levels to extract
For frustum selection, if this property is set to 1 the output is the
from the input hierarchical dataset.
outline of the frustum instead of the contents of the input that lie
within the frustum.


| 0
|
|
|
Only the values 0 and 1 are accepted.
 
 
|}
|}




==Extract Selection==
==Extract Subset==




Extract different type of selections.
Extract a subgrid from a structured grid with the option of setting subsample strides.


This filter extracts a set of cells/points given a selection.<br>
The Extract Grid filter returns a subgrid of a structured input data set (uniform rectilinear, curvilinear, or nonuniform rectilinear). The output data set type of this filter is the same as the input type.<br>
The selection can be obtained from a rubber-band selection<br>
(either cell, visible or in a frustum) or threshold selection<br>
and passed to the filter or specified by providing an ID list.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
{| class="PropertiesTable" border="1" cellpadding="5"
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| '''Restrictions'''
| '''Restrictions'''
|-
|-
| '''Input'''<br>''(Input)''
| '''Include Boundary'''<br>''(IncludeBoundary)''
|
|
This property specifies the input from which the selection is extracted.
If the value of this property is 1, then if the sample rate in any dimension is greater than 1, the boundary indices of the input dataset will be passed to the output even if the boundary extent is not an even multiple of the sample rate in a given dimension.
 
| 0
|
Only the values 0 and 1 are accepted.
 
 
|-
| '''Input'''<br>''(Input)''
|
This property specifies the input to the Extract Grid filter.


|
|
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The selected dataset must be one of the following types (or a subclass of one of them): vtkDataSet, vtkTable.
The selected dataset must be one of the following types (or a subclass of one of them): vtkImageData, vtkRectilinearGrid, vtkStructuredPoints, vtkStructuredGrid.




|-
|-
| '''Preserve Topology'''<br>''(PreserveTopology)''
| '''Sample Rate I'''<br>''(SampleRateI)''
|
|
If this property is set to 1 the output preserves the topology of its
This property indicates the sampling rate in the I dimension. A value grater than 1 results in subsampling; every nth index will be included in the output.
input and adds an insidedness array to mark which cells are inside or
out. If 0 then the output is an unstructured grid which contains only
the subset of cells that are inside.


| 0
| 1
|
|
Only the values 0 and 1 are accepted.
The value must be greater than or equal to 1.




|-
|-
| '''Selection'''<br>''(Selection)''
| '''Sample Rate J'''<br>''(SampleRateJ)''
|
|
The input that provides the selection object.
This property indicates the sampling rate in the J dimension. A value grater than 1 results in subsampling; every nth index will be included in the output.


| 1
|
|
The value must be greater than or equal to 1.
|-
| '''Sample Rate K'''<br>''(SampleRateK)''
|
|
The selected object must be the result of the following: sources (includes readers), filters.
This property indicates the sampling rate in the K dimension. A value grater than 1 results in subsampling; every nth index will be included in the output.


 
| 1
The selected dataset must be one of the following types (or a subclass of one of them): vtkSelection.
|
The value must be greater than or equal to 1.




|-
|-
| '''Show Bounds'''<br>''(ShowBounds)''
| '''V OI'''<br>''(VOI)''
|
|
For frustum selection, if this property is set to 1 the output is the
This property specifies the minimum and maximum point indices along each of the I, J, and K axes; these values indicate the volume of interest (VOI). The output will have the (I,J,K) extent specified here.
outline of the frustum instead of the contents of the input that lie
within the frustum.


| 0
| 0 0 0 0 0 0
|
|
Only the values 0 and 1 are accepted.
The values must lie within the extent of the input dataset.




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==Extract Subset==
==Extract Surface==




Extract a subgrid from a structured grid with the option of setting subsample strides.
Extract a 2D boundary surface using neighbor relations to eliminate internal faces.


The Extract Grid filter returns a subgrid of a structured input data set (uniform rectilinear, curvilinear, or nonuniform rectilinear). The output data set type of this filter is the same as the input type.<br>
The Extract Surface filter extracts the polygons forming the outer surface of the input dataset. This filter operates on any type of data and produces polygonal data as output.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
{| class="PropertiesTable" border="1" cellpadding="5"
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| '''Default Value(s)'''
| '''Default Value(s)'''
| '''Restrictions'''
| '''Restrictions'''
|-
| '''Include Boundary'''<br>''(IncludeBoundary)''
|
If the value of this property is 1, then if the sample rate in any dimension is greater than 1, the boundary indices of the input dataset will be passed to the output even if the boundary extent is not an even multiple of the sample rate in a given dimension.
| 0
|
Only the values 0 and 1 are accepted.
|-
|-
| '''Input'''<br>''(Input)''
| '''Input'''<br>''(Input)''
|
|
This property specifies the input to the Extract Grid filter.
This property specifies the input to the Extract Surface filter.


|
|
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The selected dataset must be one of the following types (or a subclass of one of them): vtkImageData, vtkRectilinearGrid, vtkStructuredPoints, vtkStructuredGrid.
The selected dataset must be one of the following types (or a subclass of one of them): vtkDataSet.




|-
|-
| '''Sample Rate I'''<br>''(SampleRateI)''
| '''Nonlinear Subdivision Level'''<br>''(NonlinearSubdivisionLevel)''
|
|
This property indicates the sampling rate in the I dimension. A value grater than 1 results in subsampling; every nth index will be included in the output.
If the input is an unstructured grid with nonlinear faces, this
parameter determines how many times the face is subdivided into
linear faces. If 0, the output is the equivalent of its linear
couterpart (and the midpoints determining the nonlinear
interpolation are discarded). If 1, the nonlinear face is
triangulated based on the midpoints. If greater than 1, the
triangulated pieces are recursively subdivided to reach the
desired subdivision. Setting the value to greater than 1 may
cause some point data to not be passed even if no quadratic faces
exist. This option has no effect if the input is not an
unstructured grid.


| 1
| 1
|
|
The value must be greater than or equal to 1.
The value must be greater than or equal to 0 and less than or equal to 4.




|-
|-
| '''Sample Rate J'''<br>''(SampleRateJ)''
| '''Piece Invariant'''<br>''(PieceInvariant)''
|
|
This property indicates the sampling rate in the J dimension. A value grater than 1 results in subsampling; every nth index will be included in the output.
If the value of this property is set to 1, internal surfaces along process boundaries will be removed. NOTE: Enabling this option might cause multiple executions of the data source because more information is needed to remove internal surfaces.


| 1
| 1
|
|
The value must be greater than or equal to 1.
Only the values 0 and 1 are accepted.




|-
|}
| '''Sample Rate K'''<br>''(SampleRateK)''
|
This property indicates the sampling rate in the K dimension. A value grater than 1 results in subsampling; every nth index will be included in the output.


| 1
|
The value must be greater than or equal to 1.


==FFT Of Selection Over Time==


|-
| '''V OI'''<br>''(VOI)''
|
This property specifies the minimum and maximum point indices along each of the I, J, and K axes; these values indicate the volume of interest (VOI). The output will have the (I,J,K) extent specified here.


| 0 0 0 0 0 0
Extracts selection over time and plots the FFT
|
The values must lie within the extent of the input dataset.


 
Extracts the data of a selection (e.g. points or cells) over time,<br>
|}
takes the FFT of them, and plots them.<br>
 
 
==Extract Surface==
 
 
Extract a 2D boundary surface using neighbor relations to eliminate internal faces.
 
The Extract Surface filter extracts the polygons forming the outer surface of the input dataset. This filter operates on any type of data and produces polygonal data as output.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
{| class="PropertiesTable" border="1" cellpadding="5"
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| '''Input'''<br>''(Input)''
| '''Input'''<br>''(Input)''
|
|
This property specifies the input to the Extract Surface filter.
The input from which the selection is extracted.


|
|
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The selected dataset must be one of the following types (or a subclass of one of them): vtkDataSet.
The selected dataset must be one of the following types (or a subclass of one of them): vtkDataSet, vtkTable, vtkCompositeDataSet.




|-
|-
| '''Nonlinear Subdivision Level'''<br>''(NonlinearSubdivisionLevel)''
| '''Selection'''<br>''(Selection)''
|
|
If the input is an unstructured grid with nonlinear faces, this
The input that provides the selection object.
parameter determines how many times the face is subdivided into
linear faces.  If 0, the output is the equivalent of its linear
couterpart (and the midpoints determining the nonlinear
interpolation are discarded).  If 1, the nonlinear face is
triangulated based on the midpoints.  If greater than 1, the
triangulated pieces are recursively subdivided to reach the
desired subdivision.  Setting the value to greater than 1 may
cause some point data to not be passed even if no quadratic faces
exist.  This option has no effect if the input is not an
unstructured grid.


| 1
|
|
The value must be greater than or equal to 0 and less than or equal to 4.
|
The selected object must be the result of the following: sources (includes readers), filters.




|-
The selected dataset must be one of the following types (or a subclass of one of them): vtkSelection.
| '''Piece Invariant'''<br>''(PieceInvariant)''
|
If the value of this property is set to 1, internal surfaces along process boundaries will be removed. NOTE: Enabling this option might cause multiple executions of the data source because more information is needed to remove internal surfaces.
 
| 1
|
Only the values 0 and 1 are accepted.




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==FFT Of Selection Over Time==
==FOF/SOD Halo Finder==




Extracts selection over time and plots the FFT
Sorry, no help is currently available.


Extracts the data of a selection (e.g. points or cells) over time,<br>
takes the FFT of them, and plots them.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
{| class="PropertiesTable" border="1" cellpadding="5"
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| '''Restrictions'''
| '''Restrictions'''
|-
|-
| '''Input'''<br>''(Input)''
| '''bb (linking length)'''<br>''(BB)''
|
|
The input from which the selection is extracted.
Linking length measured in units of interparticle spacing and is dimensionless. Used to link particles into halos for the friends-of-friends (FOF) algorithm.


| 0.2
|
|
|
The value must be greater than or equal to 0.
The selected object must be the result of the following: sources (includes readers), filters.
 
 
The selected dataset must be one of the following types (or a subclass of one of them): vtkDataSet, vtkTable, vtkCompositeDataSet.




|-
|-
| '''Selection'''<br>''(Selection)''
| '''Compute the most bound particle'''<br>''(ComputeMostBoundParticle)''
|
|
The input that provides the selection object.
If checked, the most bound particle for an FOF halo will be calculated. WARNING: This can be very slow.


| 0
|
|
|
Only the values 0 and 1 are accepted.
The selected object must be the result of the following: sources (includes readers), filters.
 
 
The selected dataset must be one of the following types (or a subclass of one of them): vtkSelection.
 
 
|}
 
 
==Feature Edges==




This filter will extract edges along sharp edges of surfaces or boundaries of surfaces.
The Feature Edges filter extracts various subsets of edges from the input data set. This filter operates on polygonal data and produces polygonal output.<br>
{| class="PropertiesTable" border="1" cellpadding="5"
|-
|-
| '''Property'''
| '''Compute the most connected particle'''<br>''(ComputeMostConnectedParticle)''
| '''Description'''
| '''Default Value(s)'''
| '''Restrictions'''
|-
| '''Boundary Edges'''<br>''(BoundaryEdges)''
|
|
If the value of this property is set to 1, boundary edges will be extracted. Boundary edges are defined as lines cells or edges that are used by only one polygon.
If checked, the most connected particle for an FOF halo will be calculated. WARNING: This can be very slow.


| 1
| 0
|
|
Only the values 0 and 1 are accepted.
Only the values 0 and 1 are accepted.
Line 2,446: Line 2,359:


|-
|-
| '''Coloring'''<br>''(Coloring)''
| '''Compute spherical overdensity (SOD) halos'''<br>''(ComputeSOD)''
|
|
If the value of this property is set to 1, then the extracted edges are assigned a scalar value based on the type of the edge.
If checked, spherical overdensity (SOD) halos will be calculated in addition to friends-of-friends (FOF) halos.


| 0
| 0
Line 2,456: Line 2,369:


|-
|-
| '''Feature Angle'''<br>''(FeatureAngle)''
| '''Copy FOF halo catalog to original particles'''<br>''(CopyHaloDataToParticles)''
|
|
Ths value of this property is used to define a feature edge. If the surface normal between two adjacent triangles is at least as large as this Feature Angle, a feature edge exists. (See the FeatureEdges property.)
If checked, the friends-of-friends (FOF) halo catalog information will be copied to the original particles as well.


| 30
| 0
|
The value must be greater than or equal to 0 and less than or equal to 180.
 
 
|-
| '''Feature Edges'''<br>''(FeatureEdges)''
|
If the value of this property is set to 1, feature edges will be extracted. Feature edges are defined as edges that are used by two polygons whose dihedral angle is greater than the feature angle. (See the FeatureAngle property.)
Toggle whether to extract feature edges.
 
| 1
|
|
Only the values 0 and 1 are accepted.
Only the values 0 and 1 are accepted.
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| '''Input'''<br>''(Input)''
| '''Input'''<br>''(Input)''
|
|
This property specifies the input to the Feature Edges filter.
|
|
|
|
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The selected dataset must be one of the following types (or a subclass of one of them): vtkPolyData.
The selected dataset must be one of the following types (or a subclass of one of them): vtkUnstructuredGrid.




|-
|-
| '''Manifold Edges'''<br>''(ManifoldEdges)''
| '''np (number of seeded particles in one dimension, i.e., total particles = np^3)'''<br>''(NP)''
|
|
If the value of this property is set to 1, manifold edges will be extracted. Manifold edges are defined as edges that are used by exactly two polygons.
Number of seeded particles in one dimension. Therefore, total simulation particles is np^3 (cubed).


| 0
| 256
|
|
Only the values 0 and 1 are accepted.
The value must be greater than or equal to 0.




|-
|-
| '''Non-Manifold Edges'''<br>''(NonManifoldEdges)''
| '''overlap (shared point/ghost cell gap distance)'''<br>''(Overlap)''
|
|
If the value of this property is set to 1, non-manifold ediges will be extracted. Non-manifold edges are defined as edges that are use by three or more polygons.
The space (in rL units) to extend processor particle ownership for ghost particles/cells. Needed for correct halo calculation when halos cross processor boundaries in parallel computation.


| 1
| 5
|
|
Only the values 0 and 1 are accepted.
The value must be greater than or equal to 0.




|}
|-
| '''pmin (minimum particle threshold for an FOF halo)'''<br>''(PMin)''
|
Minimum number of particles (threshold) needed before a group is called a friends-of-friends (FOF) halo.


| 100
|
The value must be greater than or equal to 1.


==Generate Ids==


|-
| '''rL (physical box side length)'''<br>''(RL)''
|
The box side length used to wrap particles around if they exceed rL (or less than 0) in any dimension (only positive positions are allowed in the input, or they are wrapped around).


Generate scalars from point and cell ids.
| 100
|
The value must be greater than or equal to 0.


This filter generates scalars  using cell and point ids. That is, the point attribute data scalars are generated from the point ids, and the cell attribute data scalars or field data are generated from the the cell ids.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
|-
|-
| '''Property'''
| '''scale factor for rho_c'''<br>''(RhoCScale)''
| '''Description'''
| '''Default Value(s)'''
| '''Restrictions'''
|-
| '''Array Name'''<br>''(ArrayName)''
|
|
The name of the array that will contain ids.
Scale factor for rho_c in SOD halo finding such that rho_c' = rho_c * scale factor. Initial rho_c is 2.77536627e11 (M_sun/h) / (Mpc/h)^3.


| Ids
| 1
|
|
|-
|-
| '''Input'''<br>''(Input)''
| '''initial SOD center'''<br>''(SODCenterType)''
|
|
This property specifies the input to the Cell Data to Point Data filter.
The initial friends-of-friends (FOF) center used for calculating a spherical overdensity (SOD) halo. WARNING: Using MBP or MCP can be very slow.


| 0
|
|
|
The value must be one of the following: Center of mass (0), Average position (1), Most bound particle (2), Most connected particle (3).
The selected object must be the result of the following: sources (includes readers), filters.




The selected dataset must be one of the following types (or a subclass of one of them): vtkDataSet.
|-
 
| '''scale factor for initial SOD mass'''<br>''(SODMassScale)''
|
Scale factor for the initial SOD mass such that mass' = mass * scale factor. Initial SOD mass is 1.0e14 (M_sun/h).


| 1
|
|}
|}




==Generate Quadrature Points==
==Feature Edges==




Create a point set with data at quadrature points.
This filter will extract edges along sharp edges of surfaces or boundaries of surfaces.


"Create a point set with data at quadrature points."<br>
The Feature Edges filter extracts various subsets of edges from the input data set. This filter operates on polygonal data and produces polygonal output.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
{| class="PropertiesTable" border="1" cellpadding="5"
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| '''Restrictions'''
| '''Restrictions'''
|-
|-
| '''Input'''<br>''(Input)''
| '''Boundary Edges'''<br>''(BoundaryEdges)''
|
|
If the value of this property is set to 1, boundary edges will be extracted. Boundary edges are defined as lines cells or edges that are used by only one polygon.
| 1
|
|
|
Only the values 0 and 1 are accepted.
The selected object must be the result of the following: sources (includes readers), filters.




The dataset must contain a cell array.
|-
| '''Coloring'''<br>''(Coloring)''
|
If the value of this property is set to 1, then the extracted edges are assigned a scalar value based on the type of the edge.


 
| 0
The selected dataset must be one of the following types (or a subclass of one of them): vtkUnstructuredGrid.
|
Only the values 0 and 1 are accepted.




|-
|-
| '''Select Source Array'''<br>''(SelectSourceArray)''
| '''Feature Angle'''<br>''(FeatureAngle)''
|
|
Specifies the offset array from which we generate quadrature points.
Ths value of this property is used to define a feature edge. If the surface normal between two adjacent triangles is at least as large as this Feature Angle, a feature edge exists. (See the FeatureEdges property.)


| 30
|
|
|
The value must be greater than or equal to 0 and less than or equal to 180.
An array of scalars is required.




|}
|-
| '''Feature Edges'''<br>''(FeatureEdges)''
|
If the value of this property is set to 1, feature edges will be extracted. Feature edges are defined as edges that are used by two polygons whose dihedral angle is greater than the feature angle. (See the FeatureAngle property.)
Toggle whether to extract feature edges.


| 1
|
Only the values 0 and 1 are accepted.


==Generate Quadrature Scheme Dictionary==
Generate quadrature scheme dictionaries in data sets that do not have them.
Generate quadrature scheme dictionaries in data sets that do not have them.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
|-
| '''Property'''
| '''Description'''
| '''Default Value(s)'''
| '''Restrictions'''
|-
|-
| '''Input'''<br>''(Input)''
| '''Input'''<br>''(Input)''
|
|
This property specifies the input to the Feature Edges filter.
|
|
|
|
Line 2,609: Line 2,520:




The selected dataset must be one of the following types (or a subclass of one of them): vtkUnstructuredGrid.
The selected dataset must be one of the following types (or a subclass of one of them): vtkPolyData.




|}
|-
| '''Manifold Edges'''<br>''(ManifoldEdges)''
|
If the value of this property is set to 1, manifold edges will be extracted. Manifold edges are defined as edges that are used by exactly two polygons.


| 0
|
Only the values 0 and 1 are accepted.


==Generate Surface Normals==


 
|-
This filter will produce surface normals used for smooth shading. Splitting is used to avoid smoothing across feature edges.
| '''Non-Manifold Edges'''<br>''(NonManifoldEdges)''
 
This filter generates surface normals at the points of the input polygonal dataset to provide smooth shading of the dataset. The resulting dataset is also polygonal. The filter works by calculating a normal vector for each polygon in the dataset and then averaging the normals at the shared points.<br>
 
{| class="PropertiesTable" border="1" cellpadding="5"
|-
| '''Property'''
| '''Description'''
| '''Default Value(s)'''
| '''Restrictions'''
|-
| '''Compute Cell Normals'''<br>''(ComputeCellNormals)''
|
|
This filter computes the normals at the points in the data set. In the process of doing this it computes polygon normals too. If you want these normals to be passed to the output of this filter, set the value of this property to 1.
If the value of this property is set to 1, non-manifold ediges will be extracted. Non-manifold edges are defined as edges that are use by three or more polygons.


| 0
| 1
|
|
Only the values 0 and 1 are accepted.
Only the values 0 and 1 are accepted.




|-
|}
| '''Consistency'''<br>''(Consistency)''
|
The value of this property controls whether consistent polygon ordering is enforced. Generally the normals for a data set should either all point inward or all point outward. If the value of this property is 1, then this filter will reorder the points of cells that whose normal vectors are oriented the opposite direction from the rest of those in the data set.


| 1
|
Only the values 0 and 1 are accepted.


==Generate Ids==


|-
| '''Feature Angle'''<br>''(FeatureAngle)''
|
The value of this property  defines a feature edge. If the surface normal between two adjacent triangles is at least as large as this Feature Angle, a feature edge exists. If Splitting is on, points are duplicated along these feature edges. (See the Splitting property.)


| 30
Generate scalars from point and cell ids.
|
The value must be greater than or equal to 0 and less than or equal to 180.


This filter generates scalars using cell and point ids. That is, the point attribute data scalars are generated from the point ids, and the cell attribute data scalars or field data are generated from the the cell ids.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
|-
|-
| '''Flip Normals'''<br>''(FlipNormals)''
| '''Property'''
| '''Description'''
| '''Default Value(s)'''
| '''Restrictions'''
|-
| '''Array Name'''<br>''(ArrayName)''
|
|
If the value of this property is 1, this filter will reverse the normal direction (and reorder the points accordingly) for all polygons in the data set; this changes front-facing polygons to back-facing ones, and vice versa. You might want to do this if your viewing position will be inside the data set instead of outside of it.
The name of the array that will contain ids.


| 0
| Ids
|
|
Only the values 0 and 1 are accepted.
|-
|-
| '''Input'''<br>''(Input)''
| '''Input'''<br>''(Input)''
|
|
This property specifies the input to the Normals Generation filter.
This property specifies the input to the Cell Data to Point Data filter.


|
|
Line 2,678: Line 2,576:




The selected dataset must be one of the following types (or a subclass of one of them): vtkPolyData.
The selected dataset must be one of the following types (or a subclass of one of them): vtkDataSet.




|}
==Generate Quadrature Points==
Create a point set with data at quadrature points.
"Create a point set with data at quadrature points."<br>
{| class="PropertiesTable" border="1" cellpadding="5"
|-
|-
| '''Non-Manifold Traversal'''<br>''(NonManifoldTraversal)''
| '''Property'''
| '''Description'''
| '''Default Value(s)'''
| '''Restrictions'''
|-
| '''Input'''<br>''(Input)''
|
|
|
|
Turn on/off traversal across non-manifold edges. Not traversing non-manifold edges will prevent problems where the consistency of polygonal ordering is corrupted due to topological loops.
The selected object must be the result of the following: sources (includes readers), filters.


| 1
|
Only the values 0 and 1 are accepted.


The dataset must contain a cell array.


|-
| '''Piece Invariant'''<br>''(PieceInvariant)''
|
Turn this option to to produce the same results regardless of the number of processors used (i.e., avoid seams along processor boundaries). Turn this off if you do want to process ghost levels and do not mind seams.


| 1
The selected dataset must be one of the following types (or a subclass of one of them): vtkUnstructuredGrid.
|
Only the values 0 and 1 are accepted.




|-
|-
| '''Splitting'''<br>''(Splitting)''
| '''Select Source Array'''<br>''(SelectSourceArray)''
|
|
This property controls the splitting of sharp edges. If sharp edges are split (property value = 1), then points are duplicated along these edges, and separate normals are computed for both sets of points to give crisp (rendered) surface definition.
Specifies the offset array from which we generate quadrature points.


| 1
|
|
Only the values 0 and 1 are accepted.
|
An array of scalars is required.




Line 2,714: Line 2,622:




==Glyph==
==Generate Quadrature Scheme Dictionary==




This filter generates an arrow, cone, cube, cylinder, line, sphere, or 2D glyph at each point of the input data set.  The glyphs can be oriented and scaled by point attributes of the input dataset.
Generate quadrature scheme dictionaries in data sets that do not have them.


The Glyph filter generates a glyph (i.e., an arrow, cone, cube, cylinder, line, sphere, or 2D glyph) at each point in the input dataset. The glyphs can be oriented and scaled by the input point-centered scalars and vectors. The Glyph filter operates on any type of data set. Its output is polygonal. This filter is available on the Toolbar.<br>
Generate quadrature scheme dictionaries in data sets that do not have them.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
{| class="PropertiesTable" border="1" cellpadding="5"
Line 2,728: Line 2,636:
| '''Restrictions'''
| '''Restrictions'''
|-
|-
| '''Glyph Transform'''<br>''(GlyphTransform)''
| '''Input'''<br>''(Input)''
|
|
The values in this property allow you to specify the transform
(translation, rotation, and scaling) to apply to the glyph source.
|
|
|
|
The value must be set to one of the following: Transform2.
The selected object must be the result of the following: sources (includes readers), filters.




|-
The selected dataset must be one of the following types (or a subclass of one of them): vtkUnstructuredGrid.
| '''Input'''<br>''(Input)''
|
This property specifies the input to the Glyph filter. This is the dataset to which the glyphs will be applied.


|
|
The selected object must be the result of the following: sources (includes readers), filters.


|}


The selected dataset must be one of the following types (or a subclass of one of them): vtkDataSet.


==Generate Surface Normals==


|-
| '''Maximum Number of Points'''<br>''(MaximumNumberOfPoints)''
|
The value of this property specifies the maximum number of glyphs that should appear in the output dataset if the value of the UseMaskPoints property is 1. (See the UseMaskPoints property.)


| 5000
This filter will produce surface normals used for smooth shading. Splitting is used to avoid smoothing across feature edges.
|
The value must be greater than or equal to 0.


This filter generates surface normals at the points of the input polygonal dataset to provide smooth shading of the dataset. The resulting dataset is also polygonal. The filter works by calculating a normal vector for each polygon in the dataset and then averaging the normals at the shared points.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
|-
|-
| '''Random Mode'''<br>''(RandomMode)''
| '''Property'''
| '''Description'''
| '''Default Value(s)'''
| '''Restrictions'''
|-
| '''Compute Cell Normals'''<br>''(ComputeCellNormals)''
|
|
If the value of this property is 1, then the points to glyph are chosen randomly. Otherwise the point ids chosen are evenly spaced.
This filter computes the normals at the points in the data set. In the process of doing this it computes polygon normals too. If you want these normals to be passed to the output of this filter, set the value of this property to 1.


| 1
| 0
|
|
Only the values 0 and 1 are accepted.
Only the values 0 and 1 are accepted.
Line 2,772: Line 2,673:


|-
|-
| '''Scalars'''<br>''(SelectInputScalars)''
| '''Consistency'''<br>''(Consistency)''
|
|
This property indicates the name of the scalar array on which to operate. The indicated array may be used for scaling the glyphs. (See the SetScaleMode property.)
The value of this property controls whether consistent polygon ordering is enforced. Generally the normals for a data set should either all point inward or all point outward. If the value of this property is 1, then this filter will reorder the points of cells that whose normal vectors are oriented the opposite direction from the rest of those in the data set.


| 1
|
|
|
Only the values 0 and 1 are accepted.
An array of scalars is required.




|-
|-
| '''Vectors'''<br>''(SelectInputVectors)''
| '''Feature Angle'''<br>''(FeatureAngle)''
|
|
This property indicates the name of the vector array on which to operate. The indicated array may be used for scaling and/or orienting the glyphs. (See the SetScaleMode and SetOrient properties.)
The value of this property defines a feature edge. If the surface normal between two adjacent triangles is at least as large as this Feature Angle, a feature edge exists. If Splitting is on, points are duplicated along these feature edges. (See the Splitting property.)


| 1
| 30
|
|
An array of vectors is required.
The value must be greater than or equal to 0 and less than or equal to 180.




|-
|-
| '''Orient'''<br>''(SetOrient)''
| '''Flip Normals'''<br>''(FlipNormals)''
|
|
If this property is set to 1, the glyphs will be oriented based on the selected vector array.
If the value of this property is 1, this filter will reverse the normal direction (and reorder the points accordingly) for all polygons in the data set; this changes front-facing polygons to back-facing ones, and vice versa. You might want to do this if your viewing position will be inside the data set instead of outside of it.


| 1
| 0
|
|
Only the values 0 and 1 are accepted.
Only the values 0 and 1 are accepted.
Line 2,802: Line 2,703:


|-
|-
| '''Set Scale Factor'''<br>''(SetScaleFactor)''
| '''Input'''<br>''(Input)''
|
|
The value of this property will be used as a multiplier for scaling the glyphs before adding them to the output.
This property specifies the input to the Normals Generation filter.


| 1
|
|
The value must be less than the largest dimension of the dataset multiplied by a scale factor of 0.1.
|
The selected object must be the result of the following: sources (includes readers), filters.




The value must lie within the range of the selected data array.
The selected dataset must be one of the following types (or a subclass of one of them): vtkPolyData.
 
 
The value must lie within the range of the selected data array.




|-
|-
| '''Scale Mode'''<br>''(SetScaleMode)''
| '''Non-Manifold Traversal'''<br>''(NonManifoldTraversal)''
|
|
The value of this property specifies how/if the glyphs should be scaled based on the point-centered scalars/vectors in the input dataset.
Turn on/off traversal across non-manifold edges. Not traversing non-manifold edges will prevent problems where the consistency of polygonal ordering is corrupted due to topological loops.


| 1
| 1
|
|
The value must be one of the following: scalar (0), vector (1), vector_components (2), off (3).
Only the values 0 and 1 are accepted.




|-
|-
| '''Glyph Type'''<br>''(Source)''
| '''Piece Invariant'''<br>''(PieceInvariant)''
|
|
This property determines which type of glyph will be placed at the points in the input dataset.
Turn this option to to produce the same results regardless of the number of processors used (i.e., avoid seams along processor boundaries). Turn this off if you do want to process ghost levels and do not mind seams.


| 1
|
|
|
Only the values 0 and 1 are accepted.
The selected object must be the result of the following: sources (includes readers), glyph_sources.
 
 
The selected dataset must be one of the following types (or a subclass of one of them): vtkPolyData.
 
 
The value must be set to one of the following: ArrowSource, ConeSource, CubeSource, CylinderSource, LineSource, SphereSource, GlyphSource2D.




|-
|-
| '''Mask Points'''<br>''(UseMaskPoints)''
| '''Splitting'''<br>''(Splitting)''
|
|
If the value of this property is set to 1, limit the maximum number of glyphs to the value indicated by MaximumNumberOfPoints. (See the MaximumNumberOfPoints property.)
This property controls the splitting of sharp edges. If sharp edges are split (property value = 1), then points are duplicated along these edges, and separate normals are computed for both sets of points to give crisp (rendered) surface definition.


| 1
| 1
Line 2,856: Line 2,748:




==Glyph With Custom Source==
==Glyph==




This filter generates a glyph at each point of the input data set. The glyphs can be oriented and scaled by point attributes of the input dataset.
This filter generates an arrow, cone, cube, cylinder, line, sphere, or 2D glyph at each point of the input data set. The glyphs can be oriented and scaled by point attributes of the input dataset.


The Glyph filter generates a glyph at each point in the input dataset. The glyphs can be oriented and scaled by the input point-centered scalars and vectors. The Glyph filter operates on any type of data set. Its output is polygonal. This filter is available on the Toolbar.<br>
The Glyph filter generates a glyph (i.e., an arrow, cone, cube, cylinder, line, sphere, or 2D glyph) at each point in the input dataset. The glyphs can be oriented and scaled by the input point-centered scalars and vectors. The Glyph filter operates on any type of data set. Its output is polygonal. This filter is available on the Toolbar.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
{| class="PropertiesTable" border="1" cellpadding="5"
Line 2,869: Line 2,761:
| '''Default Value(s)'''
| '''Default Value(s)'''
| '''Restrictions'''
| '''Restrictions'''
|-
| '''Glyph Transform'''<br>''(GlyphTransform)''
|
The values in this property allow you to specify the transform
(translation, rotation, and scaling) to apply to the glyph source.
|
|
The value must be set to one of the following: Transform2.
|-
|-
| '''Input'''<br>''(Input)''
| '''Input'''<br>''(Input)''
Line 2,969: Line 2,872:


The selected dataset must be one of the following types (or a subclass of one of them): vtkPolyData.
The selected dataset must be one of the following types (or a subclass of one of them): vtkPolyData.
The value must be set to one of the following: ArrowSource, ConeSource, CubeSource, CylinderSource, LineSource, SphereSource, GlyphSource2D.




Line 2,984: Line 2,890:




==Gradient==
==Glyph With Custom Source==




This filter computes gradient vectors for an image/volume.
This filter generates a glyph at each point of the input data set. The glyphs can be oriented and scaled by point attributes of the input dataset.


The Gradient filter computes the gradient vector at each point in an image or volume. This filter uses central differences to compute the gradients. The Gradient filter operates on uniform rectilinear (image) data and produces image data output.<br>
The Glyph filter generates a glyph at each point in the input dataset. The glyphs can be oriented and scaled by the input point-centered scalars and vectors. The Glyph filter operates on any type of data set. Its output is polygonal. This filter is available on the Toolbar.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
{| class="PropertiesTable" border="1" cellpadding="5"
Line 2,998: Line 2,904:
| '''Restrictions'''
| '''Restrictions'''
|-
|-
| '''Dimensionality'''<br>''(Dimensionality)''
| '''Input'''<br>''(Input)''
|
|
This property indicates whether to compute the gradient in two dimensions or in three. If the gradient is being computed in two dimensions, the X and Y dimensions are used.
This property specifies the input to the Glyph filter. This is the dataset to which the glyphs will be applied.


| 3
|
|
The value must be one of the following: Two (2), Three (3).
|
The selected object must be the result of the following: sources (includes readers), filters.
 
 
The selected dataset must be one of the following types (or a subclass of one of them): vtkDataSet.




|-
|-
| '''Input'''<br>''(Input)''
| '''Maximum Number of Points'''<br>''(MaximumNumberOfPoints)''
|
|
This property specifies the input to the Gradient filter.
The value of this property specifies the maximum number of glyphs that should appear in the output dataset if the value of the UseMaskPoints property is 1. (See the UseMaskPoints property.)


| 5000
|
|
|
The value must be greater than or equal to 0.
The selected object must be the result of the following: sources (includes readers), filters.




The dataset must contain a point array with 1 components.
|-
| '''Random Mode'''<br>''(RandomMode)''
|
If the value of this property is 1, then the points to glyph are chosen randomly. Otherwise the point ids chosen are evenly spaced.


 
| 1
The selected dataset must be one of the following types (or a subclass of one of them): vtkImageData.
|
Only the values 0 and 1 are accepted.




|-
|-
| '''Select Input Scalars'''<br>''(SelectInputScalars)''
| '''Scalars'''<br>''(SelectInputScalars)''
|
|
This property lists the name of the array from which to compute the gradient.
This property indicates the name of the scalar array on which to operate. The indicated array may be used for scaling the glyphs. (See the SetScaleMode property.)


|
|
Line 3,033: Line 2,946:




|}
|-
| '''Vectors'''<br>''(SelectInputVectors)''
|
This property indicates the name of the vector array on which to operate. The indicated array may be used for scaling and/or orienting the glyphs. (See the SetScaleMode and SetOrient properties.)


| 1
|
An array of vectors is required.


==Gradient Of Unstructured DataSet==


|-
| '''Orient'''<br>''(SetOrient)''
|
If this property is set to 1, the glyphs will be oriented based on the selected vector array.


Estimate the gradient for each point or cell in any type of dataset.
| 1
|
Only the values 0 and 1 are accepted.


The Gradient (Unstructured) filter estimates the gradient vector at each point or cell. It operates on any type of vtkDataSet, and the output is the same type as the input. If the dataset is a vtkImageData, use the Gradient filter instead; it will be more efficient for this type of dataset.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
|-
|-
| '''Property'''
| '''Set Scale Factor'''<br>''(SetScaleFactor)''
| '''Description'''
| '''Default Value(s)'''
| '''Restrictions'''
|-
| '''Compute Vorticity'''<br>''(ComputeVorticity)''
|
|
When this flag is on, the gradient filter will compute the
The value of this property will be used as a multiplier for scaling the glyphs before adding them to the output.
vorticity/curl of a 3 component array.


| 0
| 1
|
|
Only the values 0 and 1 are accepted.
The value must be less than the largest dimension of the dataset multiplied by a scale factor of 0.1.
 
 
The value must lie within the range of the selected data array.
 
 
The value must lie within the range of the selected data array.




|-
|-
| '''Faster Approximation'''<br>''(FasterApproximation)''
| '''Scale Mode'''<br>''(SetScaleMode)''
|
|
When this flag is on, the gradient filter will provide a less
The value of this property specifies how/if the glyphs should be scaled based on the point-centered scalars/vectors in the input dataset.
accurate (but close) algorithm that performs fewer derivative
calculations (and is therefore faster).  The error contains some
smoothing of the output data and some possible errors on the
boundary.  This parameter has no effect when performing the
gradient of cell data.


| 0
| 1
|
|
Only the values 0 and 1 are accepted.
The value must be one of the following: scalar (0), vector (1), vector_components (2), off (3).




|-
|-
| '''Input'''<br>''(Input)''
| '''Glyph Type'''<br>''(Source)''
|
|
This property specifies the input to the Gradient (Unstructured) filter.
This property determines which type of glyph will be placed at the points in the input dataset.


|
|
|
|
The selected object must be the result of the following: sources (includes readers), filters.
The selected object must be the result of the following: sources (includes readers), glyph_sources.




The dataset must contain a point or cell array.
The selected dataset must be one of the following types (or a subclass of one of them): vtkPolyData.
 
 
The selected dataset must be one of the following types (or a subclass of one of them): vtkPointSet.




|-
|-
| '''Result Array Name'''<br>''(ResultArrayName)''
| '''Mask Points'''<br>''(UseMaskPoints)''
|
|
This property provides a name for the output array containing the gradient vectors.
If the value of this property is set to 1, limit the maximum number of glyphs to the value indicated by MaximumNumberOfPoints. (See the MaximumNumberOfPoints property.)


| Gradients
| 1
|
|
|-
Only the values 0 and 1 are accepted.
| '''Scalar Array'''<br>''(SelectInputScalars)''
 
|
This property lists the name of the scalar array from which to compute the gradient.
 
|
|
An array of scalars is required.
 
 
Valud array names will be chosen from point and cell data.
 


|}
|}




==Grid Connectivity==
==Gradient==




Mass properties of connected fragments for unstructured grids.
This filter computes gradient vectors for an image/volume.


This filter works on multiblock unstructured grid inputs and also works in<br>
The Gradient filter computes the gradient vector at each point in an image or volume. This filter uses central differences to compute the gradients. The Gradient filter operates on uniform rectilinear (image) data and produces image data output.<br>
parallel.  It Ignores any cells with a cell data Status value of 0.<br>
It performs connectivity to distict fragments separately.  It then integrates<br>
attributes of the fragments.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
{| class="PropertiesTable" border="1" cellpadding="5"
Line 3,130: Line 3,031:
| '''Default Value(s)'''
| '''Default Value(s)'''
| '''Restrictions'''
| '''Restrictions'''
|-
| '''Dimensionality'''<br>''(Dimensionality)''
|
This property indicates whether to compute the gradient in two dimensions or in three. If the gradient is being computed in two dimensions, the X and Y dimensions are used.
| 3
|
The value must be one of the following: Two (2), Three (3).
|-
|-
| '''Input'''<br>''(Input)''
| '''Input'''<br>''(Input)''
|
|
This property specifies the input to the Gradient filter.
|
|
|
|
Line 3,138: Line 3,051:




The selected dataset must be one of the following types (or a subclass of one of them): vtkUnstructuredGrid, vtkCompositeDataSet.
The dataset must contain a point array with 1 components.
 
 
The selected dataset must be one of the following types (or a subclass of one of them): vtkImageData.
 
 
|-
| '''Select Input Scalars'''<br>''(SelectInputScalars)''
|
This property lists the name of the array from which to compute the gradient.
 
|
|
An array of scalars is required.




Line 3,144: Line 3,070:




==Group Datasets==
==Gradient Of Unstructured DataSet==




Group data sets.
Estimate the gradient for each point or cell in any type of dataset.


Groups multiple datasets to create a multiblock dataset<br>
The Gradient (Unstructured) filter estimates the gradient vector at each point or cell. It operates on any type of vtkDataSet, and the output is the same type as the input. If the dataset is a vtkImageData, use the Gradient filter instead; it will be more efficient for this type of dataset.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
{| class="PropertiesTable" border="1" cellpadding="5"
Line 3,158: Line 3,084:
| '''Restrictions'''
| '''Restrictions'''
|-
|-
| '''Input'''<br>''(Input)''
| '''Compute Vorticity'''<br>''(ComputeVorticity)''
|
|
This property indicates the the inputs to the Group Datasets filter.
When this flag is on, the gradient filter will compute the
vorticity/curl of a 3 component array.


| 0
|
|
Only the values 0 and 1 are accepted.
|-
| '''Faster Approximation'''<br>''(FasterApproximation)''
|
|
The selected object must be the result of the following: sources (includes readers), filters.
When this flag is on, the gradient filter will provide a less
accurate (but close) algorithm that performs fewer derivative
calculations (and is therefore faster). The error contains some
smoothing of the output data and some possible errors on the
boundary. This parameter has no effect when performing the
gradient of cell data.


| 0
|
Only the values 0 and 1 are accepted.


The selected dataset must be one of the following types (or a subclass of one of them): vtkDataObject.


|-
| '''Input'''<br>''(Input)''
|
This property specifies the input to the Gradient (Unstructured) filter.


|}
|
|
The selected object must be the result of the following: sources (includes readers), filters.




==Histogram==
The dataset must contain a point or cell array.




Extract a histogram from field data.
The selected dataset must be one of the following types (or a subclass of one of them): vtkPointSet.




{| class="PropertiesTable" border="1" cellpadding="5"
|-
|-
| '''Property'''
| '''Result Array Name'''<br>''(ResultArrayName)''
| '''Description'''
| '''Default Value(s)'''
| '''Restrictions'''
|-
| '''Bin Count'''<br>''(BinCount)''
|
|
The value of this property specifies the number of bins for the histogram.
This property provides a name for the output array containing the gradient vectors.


| 10
| Gradients
|
|
The value must be greater than or equal to 1 and less than or equal to 256.
|-
|-
| '''Calculate Averages'''<br>''(CalculateAverages)''
| '''Scalar Array'''<br>''(SelectInputScalars)''
|
|
This option controls whether the algorithm calculates averages
This property lists the name of the scalar array from which to compute the gradient.
of variables other than the primary variable that fall into each
bin.


| 1
|
|
Only the values 0 and 1 are accepted.
|
An array of scalars is required.




|-
Valud array names will be chosen from point and cell data.
| '''Component'''<br>''(Component)''
 
|
 
The value of this property specifies the array component from which the histogram should be computed.
|}
 
 
==Grid Connectivity==


| 0
|
|-
| '''Custom Bin Ranges'''<br>''(CustomBinRanges)''
|
Set custom bin ranges to use. These are used only when
UseCustomBinRanges is set to true.


| 0 100
Mass properties of connected fragments for unstructured grids.
|
The value must lie within the range of the selected data array.


This filter works on multiblock unstructured grid inputs and also works in<br>
parallel. It Ignores any cells with a cell data Status value of 0.<br>
It performs connectivity to distict fragments separately. It then integrates<br>
attributes of the fragments.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
|-
| '''Property'''
| '''Description'''
| '''Default Value(s)'''
| '''Restrictions'''
|-
|-
| '''Input'''<br>''(Input)''
| '''Input'''<br>''(Input)''
|
|
This property specifies the input to the Histogram filter.
|
|
|
|
Line 3,235: Line 3,172:




The dataset must contain a point or cell array.
The selected dataset must be one of the following types (or a subclass of one of them): vtkUnstructuredGrid, vtkCompositeDataSet.
 
 
|}
 


==Group Datasets==


The selected dataset must be one of the following types (or a subclass of one of them): vtkDataSet.


Group data sets.


Groups multiple datasets to create a multiblock dataset<br>
{| class="PropertiesTable" border="1" cellpadding="5"
|-
|-
| '''Select Input Array'''<br>''(SelectInputArray)''
| '''Property'''
| '''Description'''
| '''Default Value(s)'''
| '''Restrictions'''
|-
| '''Input'''<br>''(Input)''
|
|
This property indicates the name of the array from which to compute the histogram.
This property indicates the the inputs to the Group Datasets filter.


|
|
|
|
An array of scalars is required.
The selected object must be the result of the following: sources (includes readers), filters.




Valud array names will be chosen from point and cell data.
The selected dataset must be one of the following types (or a subclass of one of them): vtkDataObject.
 
 
|-
| '''Use Custom Bin Ranges'''<br>''(UseCustomBinRanges)''
|
When set to true, CustomBinRanges will  be used instead of using the
full range for the selected array. By default, set to false.
 
| 0
|
Only the values 0 and 1 are accepted.




Line 3,268: Line 3,207:




==Integrate Variables==
==Histogram==




This filter integrates cell and point attributes.
Extract a histogram from field data.


The Integrate Attributes filter integrates point and cell data over lines and surfaces.  It also computes length of lines, area of surface, or volume.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
{| class="PropertiesTable" border="1" cellpadding="5"
Line 3,282: Line 3,220:
| '''Restrictions'''
| '''Restrictions'''
|-
|-
| '''Input'''<br>''(Input)''
| '''Bin Count'''<br>''(BinCount)''
|
|
This property specifies the input to the Integrate Attributes filter.
The value of this property specifies the number of bins for the histogram.


| 10
|
|
|
The value must be greater than or equal to 1 and less than or equal to 256.
The selected object must be the result of the following: sources (includes readers), filters.




The selected dataset must be one of the following types (or a subclass of one of them): vtkDataSet.
|-
| '''Calculate Averages'''<br>''(CalculateAverages)''
|
This option controls whether the algorithm calculates averages
of variables other than the primary variable that fall into each
bin.


| 1
|
Only the values 0 and 1 are accepted.


|}


|-
| '''Component'''<br>''(Component)''
|
The value of this property specifies the array component from which the histogram should be computed.


==Interpolate to Quadrature Points==
| 0
|
|-
| '''Custom Bin Ranges'''<br>''(CustomBinRanges)''
|
Set custom bin ranges to use. These are used only when
UseCustomBinRanges is set to true.


| 0 100
|
The value must lie within the range of the selected data array.


Create scalar/vector data arrays interpolated to quadrature points.
"Create scalar/vector data arrays interpolated to quadrature points."<br>


{| class="PropertiesTable" border="1" cellpadding="5"
|-
| '''Property'''
| '''Description'''
| '''Default Value(s)'''
| '''Restrictions'''
|-
|-
| '''Input'''<br>''(Input)''
| '''Input'''<br>''(Input)''
|
|
This property specifies the input to the Histogram filter.
|
|
|
|
Line 3,318: Line 3,269:




The selected dataset must be one of the following types (or a subclass of one of them): vtkUnstructuredGrid.
The dataset must contain a point or cell array.
 
 
The selected dataset must be one of the following types (or a subclass of one of them): vtkDataSet.




|-
|-
| '''Select Source Array'''<br>''(SelectSourceArray)''
| '''Select Input Array'''<br>''(SelectInputArray)''
|
|
Specifies the offset array from which we interpolate values to quadrature points.
This property indicates the name of the array from which to compute the histogram.


|
|
|
|
An array of scalars is required.
An array of scalars is required.
Valud array names will be chosen from point and cell data.
|-
| '''Use Custom Bin Ranges'''<br>''(UseCustomBinRanges)''
|
When set to true, CustomBinRanges will be used instead of using the
full range for the selected array. By default, set to false.
| 0
|
Only the values 0 and 1 are accepted.




Line 3,334: Line 3,302:




==Intersect Fragments==
==Integrate Variables==




The Intersect Fragments filter perform geometric intersections on sets of fragments.
This filter integrates cell and point attributes.


The Intersect Fragments filter perform geometric intersections on sets of<br>
The Integrate Attributes filter integrates point and cell data over lines and surfaces. It also computes length of lines, area of surface, or volume.<br>
fragments. The filter takes two inputs, the first containing fragment<br>
geometry and the second containing fragment centers. The filter has two<br>
outputs. The first is geometry that results from the intersection. The<br>
second is a set of points that is an approximation of the center of where<br>
each fragment has been intersected.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
{| class="PropertiesTable" border="1" cellpadding="5"
Line 3,352: Line 3,315:
| '''Default Value(s)'''
| '''Default Value(s)'''
| '''Restrictions'''
| '''Restrictions'''
|-
| '''Slice Type'''<br>''(CutFunction)''
|
This property sets the type of intersecting geometry, and
associated parameters.
|
|
The value must be set to one of the following: Plane, Box, Sphere.
|-
|-
| '''Input'''<br>''(Input)''
| '''Input'''<br>''(Input)''
|
|
This input must contian fragment geometry.
This property specifies the input to the Integrate Attributes filter.


|
|
Line 3,373: Line 3,325:




The selected dataset must be one of the following types (or a subclass of one of them): vtkMultiBlockDataSet.
The selected dataset must be one of the following types (or a subclass of one of them): vtkDataSet.
 
 
|-
| '''Source'''<br>''(Source)''
|
This input must contian fragment centers.
 
|
|
The selected object must be the result of the following: sources (includes readers), filters.
 
 
The selected dataset must be one of the following types (or a subclass of one of them): vtkMultiBlockDataSet.




Line 3,392: Line 3,331:




==Iso Volume==
==Interpolate to Quadrature Points==




This filter extracts cells by clipping cells that have point        scalars not in the specified range.
Create scalar/vector data arrays interpolated to quadrature points.


This filter clip away the cells using lower and upper thresholds.<br>
"Create scalar/vector data arrays interpolated to quadrature points."<br>


{| class="PropertiesTable" border="1" cellpadding="5"
{| class="PropertiesTable" border="1" cellpadding="5"
Line 3,408: Line 3,347:
| '''Input'''<br>''(Input)''
| '''Input'''<br>''(Input)''
|
|
This property specifies the input to the Threshold filter.
|
|
|
|
Line 3,415: Line 3,352:




The dataset must contain a point or cell array with 1 components.
The selected dataset must be one of the following types (or a subclass of one of them): vtkUnstructuredGrid.
 
 
The selected dataset must be one of the following types (or a subclass of one of them): vtkDataSet.




|-
|-
| '''Input Scalars'''<br>''(SelectInputScalars)''
| '''Select Source Array'''<br>''(SelectSourceArray)''
|
|
The value of this property contains the name of the scalar array from which to perform thresholding.
Specifies the offset array from which we interpolate values to quadrature points.


|
|
|
|
An array of scalars is required.
An array of scalars is required.
Valud array names will be chosen from point and cell data.
|-
| '''Threshold Range'''<br>''(ThresholdBetween)''
|
The values of this property specify the upper and lower bounds of the thresholding operation.
| 0 0
|
The value must lie within the range of the selected data array.




Line 3,447: Line 3,368:




==K Means==
==Intersect Fragments==




Compute a statistical model of a dataset and/or assess the dataset with a statistical model.
The Intersect Fragments filter perform geometric intersections on sets of fragments.
 
This filter either computes a statistical model of a dataset or takes such a model as its second input.  Then, the model (however it is obtained) may optionally be used to assess the input dataset.
<br>
This filter iteratively computes the center of k clusters in a space whose coordinates are specified by the arrays you select. The clusters are chosen as local minima of the sum of square Euclidean distances from each point to its nearest cluster center. The model is then a set of cluster centers. Data is assessed by assigning a cluster center and distance to the cluster to each point in the input data set.<br>


The Intersect Fragments filter perform geometric intersections on sets of<br>
fragments. The filter takes two inputs, the first containing fragment<br>
geometry and the second containing fragment centers. The filter has two<br>
outputs. The first is geometry that results from the intersection. The<br>
second is a set of points that is an approximation of the center of where<br>
each fragment has been intersected.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
{| class="PropertiesTable" border="1" cellpadding="5"
Line 3,464: Line 3,387:
| '''Restrictions'''
| '''Restrictions'''
|-
|-
| '''Attribute Mode'''<br>''(AttributeMode)''
| '''Slice Type'''<br>''(CutFunction)''
|
|
Specify which type of field data the arrays will be drawn from.
This property sets the type of intersecting geometry, and
associated parameters.


| 0
|
|
Valud array names will be chosen from point and cell data.
|
The value must be set to one of the following: Plane, Box, Sphere.




Line 3,476: Line 3,400:
| '''Input'''<br>''(Input)''
| '''Input'''<br>''(Input)''
|
|
The input to the filter.  Arrays from this dataset will be used for computing statistics and/or assessed by a statistical model.
This input must contian fragment geometry.


|
|
Line 3,483: Line 3,407:




The dataset must contain a point or cell array.
The selected dataset must be one of the following types (or a subclass of one of them): vtkMultiBlockDataSet.
 
 
The selected dataset must be one of the following types (or a subclass of one of them): vtkImageData, vtkStructuredGrid, vtkPolyData, vtkUnstructuredGrid, vtkTable, vtkGraph.




|-
|-
| '''k'''<br>''(K)''
| '''Source'''<br>''(Source)''
|
|
Specify the number of clusters.
This input must contian fragment centers.


| 5
|
|
The value must be greater than or equal to 1.
|
The selected object must be the result of the following: sources (includes readers), filters.
 
 
The selected dataset must be one of the following types (or a subclass of one of them): vtkMultiBlockDataSet.
 
 
|}




|-
==Iso Volume==
| '''Max Iterations'''<br>''(MaxNumIterations)''
 
|
Specify the maximum number of iterations in which cluster centers are moved before the algorithm terminates.


| 50
This filter extracts cells by clipping cells that have point scalars not in the specified range.
|
The value must be greater than or equal to 1.


This filter clip away the cells using lower and upper thresholds.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
|-
|-
| '''Model Input'''<br>''(ModelInput)''
| '''Property'''
| '''Description'''
| '''Default Value(s)'''
| '''Restrictions'''
|-
| '''Input'''<br>''(Input)''
|
|
A previously-calculated model with which to assess a separate dataset. This input is optional.
This property specifies the input to the Threshold filter.


|
|
Line 3,519: Line 3,449:




The selected dataset must be one of the following types (or a subclass of one of them): vtkTable, vtkMultiBlockDataSet.
The dataset must contain a point or cell array with 1 components.




|-
The selected dataset must be one of the following types (or a subclass of one of them): vtkDataSet.
| '''Variables of Interest'''<br>''(SelectArrays)''
|
Choose arrays whose entries will be used to form observations for statistical analysis.
 
|
|
An array of scalars is required.




|-
|-
| '''Task'''<br>''(Task)''
| '''Input Scalars'''<br>''(SelectInputScalars)''
|
|
Specify the task to be performed: modeling and/or assessment.
The value of this property contains the name of the scalar array from which to perform thresholding.
#  "Statistics of all the data," creates an output table (or tables) summarizing the '''entire''' input dataset;
#  "Model a subset of the data," creates an output table (or tables) summarizing a '''randomly-chosen subset''' of the input dataset;
#  "Assess the data with a model," adds attributes to the first input dataset using a model provided on the second input port; and
#  "Model and assess the same data," is really just operations 2 and 3 above applied to the same input dataset.  The model is first trained using a fraction of the input data and then the entire dataset is assessed using that model.


When the task includes creating a model (i.e., tasks 2, and 4), you may adjust the fraction of the input dataset used for training.  You should avoid using a large fraction of the input data for training as you will then not be able to detect overfitting.  The ''Training fraction'' setting will be ignored for tasks 1 and 3.
| 3
|
|
The value must be one of the following: Statistics of all the data (0), Model a subset of the data (1), Assess the data with a model (2), Model and assess the same data (3).
|
An array of scalars is required.




|-
Valud array names will be chosen from point and cell data.
| '''Tolerance'''<br>''(Tolerance)''
|
Specify the relative tolerance that will cause early termination.
 
| 0.01
|
The value must be greater than or equal to 0 and less than or equal to 1.




|-
|-
| '''Training Fraction'''<br>''(TrainingFraction)''
| '''Threshold Range'''<br>''(ThresholdBetween)''
|
|
Specify the fraction of values from the input dataset to be used for model fitting. The exact set of values is chosen at random from the dataset.
The values of this property specify the upper and lower bounds of the thresholding operation.


| 0.1
| 0 0
|
|
The value must be greater than or equal to 0 and less than or equal to 1.
The value must lie within the range of the selected data array.




Line 3,571: Line 3,481:




==Level Scalars==
==K Means==
 


Compute a statistical model of a dataset and/or assess the dataset with a statistical model.


The Level Scalars filter uses colors to show levels of a hierarchical dataset.
This filter either computes a statistical model of a dataset or takes such a model as its second input. Then, the model (however it is obtained) may optionally be used to assess the input dataset.
<br>
This filter iteratively computes the center of k clusters in a space whose coordinates are specified by the arrays you select. The clusters are chosen as local minima of the sum of square Euclidean distances from each point to its nearest cluster center. The model is then a set of cluster centers. Data is assessed by assigning a cluster center and distance to the cluster to each point in the input data set.<br>


The Level Scalars filter uses colors to show levels of a hierarchical dataset.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
{| class="PropertiesTable" border="1" cellpadding="5"
Line 3,585: Line 3,498:
| '''Restrictions'''
| '''Restrictions'''
|-
|-
| '''Input'''<br>''(Input)''
| '''Attribute Mode'''<br>''(AttributeMode)''
|
|
This property specifies the input to the Level Scalars filter.
Specify which type of field data the arrays will be drawn from.


| 0
|
|
|
Valud array names will be chosen from point and cell data.
The selected object must be the result of the following: sources (includes readers), filters.




The selected dataset must be one of the following types (or a subclass of one of them): vtkHierarchicalBoxDataSet.
|-
| '''Input'''<br>''(Input)''
|
The input to the filter. Arrays from this dataset will be used for computing statistics and/or assessed by a statistical model.
 
|
|
The selected object must be the result of the following: sources (includes readers), filters.




|}
The dataset must contain a point or cell array.




==Linear Extrusion==
The selected dataset must be one of the following types (or a subclass of one of them): vtkImageData, vtkStructuredGrid, vtkPolyData, vtkUnstructuredGrid, vtkTable, vtkGraph.




This filter creates a swept surface defined by translating the input along a vector.
|-
| '''k'''<br>''(K)''
|
Specify the number of clusters.
 
| 5
|
The value must be greater than or equal to 1.


The Linear Extrusion filter creates a swept surface by translating the input dataset along a specified vector. This filter is intended to operate on 2D polygonal data. This filter operates on polygonal data and produces polygonal data output.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
|-
|-
| '''Property'''
| '''Max Iterations'''<br>''(MaxNumIterations)''
| '''Description'''
| '''Default Value(s)'''
| '''Restrictions'''
|-
| '''Capping'''<br>''(Capping)''
|
|
The value of this property indicates whether to cap the ends of the swept surface. Capping works by placing a copy of the input dataset on either end of the swept surface, so it behaves properly if the input is a 2D surface composed of filled polygons. If the input dataset is a closed solid (e.g., a sphere), then if capping is on (i.e., this property is set to 1), two copies of the data set will be displayed on output (the second translated from the first one along the specified vector). If instead capping is off (i.e., this property is set to 0), then an input closed solid will produce no output.
Specify the maximum number of iterations in which cluster centers are moved before the algorithm terminates.


| 1
| 50
|
|
Only the values 0 and 1 are accepted.
The value must be greater than or equal to 1.




|-
|-
| '''Input'''<br>''(Input)''
| '''Model Input'''<br>''(ModelInput)''
|
|
This property specifies the input to the Linear Extrusion filter.
A previously-calculated model with which to assess a separate dataset. This input is optional.


|
|
Line 3,633: Line 3,553:




The selected dataset must be one of the following types (or a subclass of one of them): vtkPolyData.
The selected dataset must be one of the following types (or a subclass of one of them): vtkTable, vtkMultiBlockDataSet.




|-
|-
| '''Piece Invariant'''<br>''(PieceInvariant)''
| '''Variables of Interest'''<br>''(SelectArrays)''
|
|
The value of this property determines whether the output will be the same regardless of the number of processors used to compute the result. The difference is whether there are internal polygonal faces on the processor boundaries. A value of 1 will keep the results the same; a value of 0 will allow internal faces on processor boundaries.
Choose arrays whose entries will be used to form observations for statistical analysis.


| 0
|
|
Only the values 0 and 1 are accepted.
|
An array of scalars is required.




|-
|-
| '''Scale Factor'''<br>''(ScaleFactor)''
| '''Task'''<br>''(Task)''
|
|
The value of this property determines the distance along the vector the dataset will be translated. (A scale factor of 0.5 will move the dataset half the length of the vector, and a scale factor of 2 will move it twice the vector's length.)
Specify the task to be performed: modeling and/or assessment.
#  "Statistics of all the data," creates an output table (or tables) summarizing the '''entire''' input dataset;
#  "Model a subset of the data," creates an output table (or tables) summarizing a '''randomly-chosen subset''' of the input dataset;
#  "Assess the data with a model," adds attributes to the first input dataset using a model provided on the second input port; and
#  "Model and assess the same data," is really just operations 2 and 3 above applied to the same input dataset. The model is first trained using a fraction of the input data and then the entire dataset is assessed using that model.
 
When the task includes creating a model (i.e., tasks 2, and 4), you may adjust the fraction of the input dataset used for training. You should avoid using a large fraction of the input data for training as you will then not be able to detect overfitting. The ''Training fraction'' setting will be ignored for tasks 1 and 3.
 
| 3
|
The value must be one of the following: Statistics of all the data (0), Model a subset of the data (1), Assess the data with a model (2), Model and assess the same data (3).
 


| 1
|-
| '''Tolerance'''<br>''(Tolerance)''
|
Specify the relative tolerance that will cause early termination.
 
| 0.01
|
|
The value must be greater than or equal to 0 and less than or equal to 1.
|-
|-
| '''Vector'''<br>''(Vector)''
| '''Training Fraction'''<br>''(TrainingFraction)''
|
|
The value of this property indicates the X, Y, and Z components of the vector along which to sweep the input dataset.
Specify the fraction of values from the input dataset to be used for model fitting. The exact set of values is chosen at random from the dataset.


| 0 0 1
| 0.1
|
|
The value must be greater than or equal to 0 and less than or equal to 1.
|}
|}




==Loop Subdivision==
==Level Scalars==




This filter iteratively divides each triangle into four triangles.  New points are placed so the output surface is smooth.
The Level Scalars filter uses colors to show levels of a hierarchical dataset.


The Loop Subdivision filter increases the granularity of a polygonal mesh. It works by dividing each triangle in the input into four new triangles. It is named for Charles Loop, the person who devised this subdivision scheme. This filter only operates on triangles, so a data set that contains other types of polygons should be passed through the Triangulate filter before applying this filter to it. This filter only operates on polygonal data (specifically triangle meshes), and it produces polygonal output.<br>
The Level Scalars filter uses colors to show levels of a hierarchical dataset.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
{| class="PropertiesTable" border="1" cellpadding="5"
Line 3,679: Line 3,621:
| '''Input'''<br>''(Input)''
| '''Input'''<br>''(Input)''
|
|
This property specifies the input to the Loop Subdivision filter.
This property specifies the input to the Level Scalars filter.


|
|
Line 3,686: Line 3,628:




The selected dataset must be one of the following types (or a subclass of one of them): vtkPolyData.
The selected dataset must be one of the following types (or a subclass of one of them): vtkHierarchicalBoxDataSet.
 
 
|-
| '''Number of Subdivisions'''<br>''(NumberOfSubdivisions)''
|
Set the number of subdivision iterations to perform. Each subdivision divides single triangles into four new triangles.
 
| 1
|
The value must be greater than or equal to 1 and less than or equal to 4.




Line 3,702: Line 3,634:




==Mask Points==
==Linear Extrusion==




Reduce the number of points.  This filter is often used before glyphing. Generating vertices is an option.
This filter creates a swept surface defined by translating the input along a vector.


The Mask Points filter reduces the number of points in the dataset. It operates on any type of dataset, but produces only points / vertices as output. This filter is often used before the Glyph filter, but the basic point-masking functionality is also available on the Properties page for the Glyph filter.<br>
The Linear Extrusion filter creates a swept surface by translating the input dataset along a specified vector. This filter is intended to operate on 2D polygonal data. This filter operates on polygonal data and produces polygonal data output.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
{| class="PropertiesTable" border="1" cellpadding="5"
Line 3,716: Line 3,648:
| '''Restrictions'''
| '''Restrictions'''
|-
|-
| '''Generate Vertices'''<br>''(GenerateVertices)''
| '''Capping'''<br>''(Capping)''
|
|
This property specifies whether to generate vertex cells as the topography of the output. If set to 1, the geometry (vertices) will be displayed in the rendering window; otherwise no geometry will be displayed.
The value of this property indicates whether to cap the ends of the swept surface. Capping works by placing a copy of the input dataset on either end of the swept surface, so it behaves properly if the input is a 2D surface composed of filled polygons. If the input dataset is a closed solid (e.g., a sphere), then if capping is on (i.e., this property is set to 1), two copies of the data set will be displayed on output (the second translated from the first one along the specified vector). If instead capping is off (i.e., this property is set to 0), then an input closed solid will produce no output.


| 0
| 1
|
|
Only the values 0 and 1 are accepted.
Only the values 0 and 1 are accepted.
Line 3,728: Line 3,660:
| '''Input'''<br>''(Input)''
| '''Input'''<br>''(Input)''
|
|
This property specifies the input to the Mask Points filter.
This property specifies the input to the Linear Extrusion filter.


|
|
Line 3,735: Line 3,667:




The selected dataset must be one of the following types (or a subclass of one of them): vtkDataSet.
The selected dataset must be one of the following types (or a subclass of one of them): vtkPolyData.




|-
|-
| '''Maximum Number of Points'''<br>''(MaximumNumberOfPoints)''
| '''Piece Invariant'''<br>''(PieceInvariant)''
|
|
The value of this property indicates the maximum number of points in the output dataset.
The value of this property determines whether the output will be the same regardless of the number of processors used to compute the result. The difference is whether there are internal polygonal faces on the processor boundaries. A value of 1 will keep the results the same; a value of 0 will allow internal faces on processor boundaries.


| 5000
| 0
|
|
The value must be greater than or equal to 0.
Only the values 0 and 1 are accepted.




|-
|-
| '''Offset'''<br>''(Offset)''
| '''Scale Factor'''<br>''(ScaleFactor)''
|
|
The value of this property indicates the point in the input dataset from which to start masking.
The value of this property determines the distance along the vector the dataset will be translated. (A scale factor of 0.5 will move the dataset half the length of the vector, and a scale factor of 2 will move it twice the vector's length.)


| 0
| 1
|
|
The value must be greater than or equal to 0.
|-
|-
| '''On Ratio'''<br>''(OnRatio)''
| '''Vector'''<br>''(Vector)''
|
|
The value of this property specifies the ratio of points to retain in the output. (For example, if the on ratio is 3, then the output will contain 1/3 as many points -- up to the value of the MaximumNumberOfPoints property -- as the input.)
The value of this property indicates the X, Y, and Z components of the vector along which to sweep the input dataset.


| 2
| 0 0 1
|
|
The value must be greater than or equal to 1.
|}
 


==Loop Subdivision==


|-
| '''Random'''<br>''(RandomMode)''
|
If the value of this property is set to 0, then the points in the output will be randomly selected from the input; otherwise this filter will subsample regularly. Selecting points at random is helpful to avoid striping when masking the points of a structured dataset.


| 0
This filter iteratively divides each triangle into four triangles. New points are placed so the output surface is smooth.
|
Only the values 0 and 1 are accepted.


The Loop Subdivision filter increases the granularity of a polygonal mesh. It works by dividing each triangle in the input into four new triangles. It is named for Charles Loop, the person who devised this subdivision scheme. This filter only operates on triangles, so a data set that contains other types of polygons should be passed through the Triangulate filter before applying this filter to it. This filter only operates on polygonal data (specifically triangle meshes), and it produces polygonal output.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
|-
|-
| '''Single Vertex Per Cell'''<br>''(SingleVertexPerCell)''
| '''Property'''
| '''Description'''
| '''Default Value(s)'''
| '''Restrictions'''
|-
| '''Input'''<br>''(Input)''
|
|
Tell filter to only generate one vertex per cell instead of multiple vertices in one cell.
This property specifies the input to the Loop Subdivision filter.


| 0
|
|
Only the values 0 and 1 are accepted.
|
The selected object must be the result of the following: sources (includes readers), filters.
 
 
The selected dataset must be one of the following types (or a subclass of one of them): vtkPolyData.
 
 
|-
| '''Number of Subdivisions'''<br>''(NumberOfSubdivisions)''
|
Set the number of subdivision iterations to perform. Each subdivision divides single triangles into four new triangles.
 
| 1
|
The value must be greater than or equal to 1 and less than or equal to 4.




Line 3,791: Line 3,736:




==Material Interface Filter==
==Mask Points==




The Material Interface filter finds volumes in the input data containg material above a certain material fraction.
Reduce the number of points. This filter is often used before glyphing. Generating vertices is an option.


The Material Interface filter finds voxels inside of which a material<br>
The Mask Points filter reduces the number of points in the dataset. It operates on any type of dataset, but produces only points / vertices as output. This filter is often used before the Glyph filter, but the basic point-masking functionality is also available on the Properties page for the Glyph filter.<br>
fraction (or normalized amount of material) is higher than a given<br>
threshold. As these voxels are identified surfaces enclosing adjacent<br>
voxels above the threshold are generated. The resulting volume and its<br>
surface are what we call a fragment. The filter has the ability to<br>
compute various volumetric attributes such as fragment volume, mass,<br>
center of mass as well as volume and mass weighted averages for any of<br>
the fields present. Any field selected for such computation will be also<br>
be coppied into the fragment surface's point data for visualization. The<br>
filter also has the ability to generate Oriented Bounding Boxes (OBB) for<br>
each fragment.<br><br><br>
The data generated by the filter is organized in three outputs. The<br>
"geometry" output, containing the fragment surfaces. The "statistics"<br>
output, containing a point set of the centers of mass. The "obb<br>
representaion" output, containing OBB representations (poly data). All<br>
computed attributes are coppied into the statistics and geometry output.<br>
The obb representation output is used for validation and debugging<br>
puproses and is turned off by default.<br><br><br>
To measure the size of craters, the filter can invert a volume fraction<br>
and clip the volume fraction with a sphere and/or a plane.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
{| class="PropertiesTable" border="1" cellpadding="5"
Line 3,824: Line 3,750:
| '''Restrictions'''
| '''Restrictions'''
|-
|-
| '''Clip Center'''<br>''(ClipCenter)''
| '''Generate Vertices'''<br>''(GenerateVertices)''
|
|
This property specifies center of the clipping plane or sphere.
This property specifies whether to generate vertex cells as the topography of the output. If set to 1, the geometry (vertices) will be displayed in the rendering window; otherwise no geometry will be displayed.


| 0 0 0
| 0
|
|
Only the values 0 and 1 are accepted.
|-
|-
| '''Clip Plane Vector'''<br>''(ClipPlaneVector)''
| '''Input'''<br>''(Input)''
|
|
This property specifies the normal of the clipping plane.
This property specifies the input to the Mask Points filter.


| 0 0 1
|
|
|-
| '''Clip Radius'''<br>''(ClipRadius)''
|
|
This property specifies the radius of the clipping sphere.
The selected object must be the result of the following: sources (includes readers), filters.


| 1
 
|
The selected dataset must be one of the following types (or a subclass of one of them): vtkDataSet.
The value must be greater than or equal to 0.




|-
|-
| '''Clip With Plane'''<br>''(ClipWithPlane)''
| '''Maximum Number of Points'''<br>''(MaximumNumberOfPoints)''
|
|
This option masks all material on on side of a plane.  It is useful for
The value of this property indicates the maximum number of points in the output dataset.
finding the properties of a crater.


| 0
| 5000
|
|
Only the values 0 and 1 are accepted.
The value must be greater than or equal to 0.




|-
|-
| '''Clip With Sphere'''<br>''(ClipWithSphere)''
| '''Offset'''<br>''(Offset)''
|
|
This option masks all material outside of a sphere.
The value of this property indicates the point in the input dataset from which to start masking.


| 0
| 0
|
|
Only the values 0 and 1 are accepted.
The value must be greater than or equal to 0.




|-
|-
| '''Compute OBB'''<br>''(ComputeOBB)''
| '''On Ratio'''<br>''(OnRatio)''
|
|
Compute Object Oriented Bounding boxes (OBB). When active the result of
The value of this property specifies the ratio of points to retain in the output. (For example, if the on ratio is 3, then the output will contain 1/3 as many points -- up to the value of the MaximumNumberOfPoints property -- as the input.)
this computation is coppied into the statistics output. In the case
that the filter is built in its validation mode, the OBB's are
rendered.


| 0
| 2
|
|
Only the values 0 and 1 are accepted.
The value must be greater than or equal to 1.




|-
|-
| '''Input'''<br>''(Input)''
| '''Random'''<br>''(RandomMode)''
|
|
Input to the filter can be a hierarchical box data set containing image
If the value of this property is set to 0, then the points in the output will be randomly selected from the input; otherwise this filter will subsample regularly. Selecting points at random is helpful to avoid striping when masking the points of a structured dataset.
data or a multi-block of rectilinear grids.


| 0
|
|
|
Only the values 0 and 1 are accepted.
The selected object must be the result of the following: sources (includes readers), filters.
 
 
The dataset must contain a cell array.
 
 
The selected dataset must be one of the following types (or a subclass of one of them): vtkHierarchicalBoxDataSet.




|-
|-
| '''Invert Volume Fraction'''<br>''(InvertVolumeFraction)''
| '''Single Vertex Per Cell'''<br>''(SingleVertexPerCell)''
|
|
Inverting the volume fraction generates the negative of the material.
Tell filter to only generate one vertex per cell instead of multiple vertices in one cell.
It is useful for analyzing craters.


| 0
| 0
Line 3,909: Line 3,822:




|-
|}
| '''Material Fraction Threshold'''<br>''(MaterialFractionThreshold)''
|
Material fraction is defined as normalized amount of material per
voxel. Any voxel in the input data set with a material fraction greater
than this value is included in the output data set.


| 0.5
|
The value must be greater than or equal to 0.08 and less than or equal to 1.


==Material Interface Filter==
The Material Interface filter finds volumes in the input data containg material above a certain material fraction.


The Material Interface filter finds voxels inside of which a material<br>
fraction (or normalized amount of material) is higher than a given<br>
threshold. As these voxels are identified surfaces enclosing adjacent<br>
voxels above the threshold are generated. The resulting volume and its<br>
surface are what we call a fragment. The filter has the ability to<br>
compute various volumetric attributes such as fragment volume, mass,<br>
center of mass as well as volume and mass weighted averages for any of<br>
the fields present. Any field selected for such computation will be also<br>
be coppied into the fragment surface's point data for visualization. The<br>
filter also has the ability to generate Oriented Bounding Boxes (OBB) for<br>
each fragment.<br><br><br>
The data generated by the filter is organized in three outputs. The<br>
"geometry" output, containing the fragment surfaces. The "statistics"<br>
output, containing a point set of the centers of mass. The "obb<br>
representaion" output, containing OBB representations (poly data). All<br>
computed attributes are coppied into the statistics and geometry output.<br>
The obb representation output is used for validation and debugging<br>
puproses and is turned off by default.<br><br><br>
To measure the size of craters, the filter can invert a volume fraction<br>
and clip the volume fraction with a sphere and/or a plane.<br>
{| class="PropertiesTable" border="1" cellpadding="5"
|-
|-
| '''Output Base Name'''<br>''(OutputBaseName)''
| '''Property'''
|
| '''Description'''
This property specifies the base including path of where to write the
| '''Default Value(s)'''
statistics and gemoetry output text files. It follows the pattern
| '''Restrictions'''
"/path/to/folder/and/file" here file has no extention, as the filter
will generate a unique extention.
 
|
|
|-
|-
| '''Select Mass Arrays'''<br>''(SelectMassArray)''
| '''Clip Type'''<br>''(ClipFunction)''
|
|
Mass arrays are paired with material fraction arrays. This means that
This property sets the type of clip geometry, and
the first selected material fraction array is paired with the first
associated parameters.
selected mass array, and so on sequentially. As the filter identifies
voxels meeting the minimum material fraction threshold, these voxel's
mass will be used in fragment center of mass and mass calculation.
 
A warning is generated if no mass array is selected for an individual
material fraction array. However, in that case the filter will run
without issue because the statistics output can be generated using
fragments' centers computed from axis aligned bounding boxes.


|
|
|
|
An array of scalars is required.
The value must be set to one of the following: None, Plane, Sphere.




|-
|-
| '''Compute mass weighted average over:'''<br>''(SelectMassWtdAvgArray)''
| '''Compute OBB'''<br>''(ComputeOBB)''
|
|
For arrays selected a mass weighted average is computed. These arrays
Compute Object Oriented Bounding boxes (OBB). When active the result of
are also coppied into fragment geometry cell data as the fragment
this computation is coppied into the statistics output. In the case
surfaces are generated.
that the filter is built in its validation mode, the OBB's are
rendered.


| 0
|
|
|
Only the values 0 and 1 are accepted.
An array of scalars is required.




|-
|-
| '''Select Material Fraction Arrays'''<br>''(SelectMaterialArray)''
| '''Input'''<br>''(Input)''
|
|
Material fraction is defined as normalized amount of material per
Input to the filter can be a hierarchical box data set containing image
voxel. It is expected that arrays containing material fraction data has
data or a multi-block of rectilinear grids.
been down converted to a unsigned char.


|
|
|
|
An array of scalars is required.
The selected object must be the result of the following: sources (includes readers), filters.
 


The dataset must contain a cell array.


|-
| '''Compute volume weighted average over:'''<br>''(SelectVolumeWtdAvgArray)''
|
For arrays selected a volume weighted average is computed. The values
of these arrays are also coppied into fragment geometry cell data as
the fragment surfaces are generated.


|
The selected dataset must be one of the following types (or a subclass of one of them): vtkHierarchicalBoxDataSet.
|
An array of scalars is required.




|-
|-
| '''Write Geometry Output'''<br>''(WriteGeometryOutput)''
| '''Invert Volume Fraction'''<br>''(InvertVolumeFraction)''
|
|
If this property is set, then the geometry output is written to a text
Inverting the volume fraction generates the negative of the material.
file. The file name will be coonstructed using the path in the "Output
It is useful for analyzing craters.
Base Name" widget.


| 0
| 0
Line 3,999: Line 3,910:


|-
|-
| '''Write Statistics Output'''<br>''(WriteStatisticsOutput)''
| '''Material Fraction Threshold'''<br>''(MaterialFractionThreshold)''
|
|
If this property is set, then the statistics output is written to a
Material fraction is defined as normalized amount of material per
text file. The file name will be coonstructed using the path in the
voxel. Any voxel in the input data set with a material fraction greater
"Output Base Name" widget.
than this value is included in the output data set.


| 0
| 0.5
|
|
Only the values 0 and 1 are accepted.
The value must be greater than or equal to 0.08 and less than or equal to 1.




|}
|-
| '''Output Base Name'''<br>''(OutputBaseName)''
|
This property specifies the base including path of where to write the
statistics and gemoetry output text files. It follows the pattern
"/path/to/folder/and/file" here file has no extention, as the filter
will generate a unique extention.


|
|
|-
| '''Select Mass Arrays'''<br>''(SelectMassArray)''
|
Mass arrays are paired with material fraction arrays. This means that
the first selected material fraction array is paired with the first
selected mass array, and so on sequentially. As the filter identifies
voxels meeting the minimum material fraction threshold, these voxel's
mass will be used in fragment center of mass and mass calculation.


==Median==
A warning is generated if no mass array is selected for an individual
material fraction array. However, in that case the filter will run
without issue because the statistics output can be generated using
fragments' centers computed from axis aligned bounding boxes.


|
|
An array of scalars is required.


Compute the median scalar values in a specified neighborhood for image/volume datasets.
The Median filter operates on uniform rectilinear (image or volume) data and produces uniform rectilinear output. It replaces the scalar value at each pixel / voxel with the median scalar value in the specified surrounding neighborhood. Since the median operation removes outliers, this filter is useful for removing high-intensity, low-probability noise (shot noise).<br>


{| class="PropertiesTable" border="1" cellpadding="5"
|-
|-
| '''Property'''
| '''Compute mass weighted average over:'''<br>''(SelectMassWtdAvgArray)''
| '''Description'''
| '''Default Value(s)'''
| '''Restrictions'''
|-
| '''Input'''<br>''(Input)''
|
|
This property specifies the input to the Median filter.
For arrays selected a mass weighted average is computed. These arrays
are also coppied into fragment geometry cell data as the fragment
surfaces are generated.


|
|
|
|
The selected object must be the result of the following: sources (includes readers), filters.
An array of scalars is required.




The dataset must contain a point array with 1 components.
|-
| '''Select Material Fraction Arrays'''<br>''(SelectMaterialArray)''
|
Material fraction is defined as normalized amount of material per
voxel. It is expected that arrays containing material fraction data has
been down converted to a unsigned char.


 
|
The selected dataset must be one of the following types (or a subclass of one of them): vtkImageData.
|
An array of scalars is required.




|-
|-
| '''Kernel Size'''<br>''(KernelSize)''
| '''Compute volume weighted average over:'''<br>''(SelectVolumeWtdAvgArray)''
|
|
The value of this property specifies the number of pixels/voxels in each dimension to use in computing the median to assign to each pixel/voxel. If the kernel size in a particular dimension is 1, then the median will not be computed in that direction.
For arrays selected a volume weighted average is computed. The values
of these arrays are also coppied into fragment geometry cell data as
the fragment surfaces are generated.


| 1 1 1
|
|
|
An array of scalars is required.
|-
|-
| '''Select Input Scalars'''<br>''(SelectInputScalars)''
| '''Write Geometry Output'''<br>''(WriteGeometryOutput)''
|
If this property is set, then the geometry output is written to a text
file. The file name will be coonstructed using the path in the "Output
Base Name" widget.
 
| 0
|
|
The value of thie property lists the name of the scalar array to use in computing the median.
Only the values 0 and 1 are accepted.
 


|-
| '''Write Statistics Output'''<br>''(WriteStatisticsOutput)''
|
|
If this property is set, then the statistics output is written to a
text file. The file name will be coonstructed using the path in the
"Output Base Name" widget.
| 0
|
|
An array of scalars is required.
Only the values 0 and 1 are accepted.




Line 4,062: Line 4,013:




==Merge Blocks==
==Median==
 


Compute the median scalar values in a specified neighborhood for image/volume datasets.


vtkCompositeDataToUnstructuredGridFilter appends all vtkDataSet<br>
The Median filter operates on uniform rectilinear (image or volume) data and produces uniform rectilinear output. It replaces the scalar value at each pixel / voxel with the median scalar value in the specified surrounding neighborhood. Since the median operation removes outliers, this filter is useful for removing high-intensity, low-probability noise (shot noise).<br>
leaves of the input composite dataset to a single unstructure grid. The<br>
subtree to be combined can be choosen using the SubTreeCompositeIndex. If<br>
the SubTreeCompositeIndex is a leaf node, then no appending is required.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
{| class="PropertiesTable" border="1" cellpadding="5"
Line 4,079: Line 4,029:
| '''Input'''<br>''(Input)''
| '''Input'''<br>''(Input)''
|
|
Set the input composite dataset.
This property specifies the input to the Median filter.


|
|
|
|
The selected dataset must be one of the following types (or a subclass of one of them): vtkCompositeDataSet.
The selected object must be the result of the following: sources (includes readers), filters.




|}
The dataset must contain a point array with 1 components.




==Mesh Quality==
The selected dataset must be one of the following types (or a subclass of one of them): vtkImageData.




This filter creates a new cell array containing a geometric measure of each cell's fitness. Different quality measures can be chosen for different cell shapes.
|-
 
| '''Kernel Size'''<br>''(KernelSize)''
This filter creates a new cell array containing a geometric measure of each cell's fitness. Different quality measures can be chosen for different cell shapes. Supported shapes include triangles, quadrilaterals, tetrahedra, and hexahedra. For other shapes, a value of 0 is assigned.<br>
|
The value of this property specifies the number of pixels/voxels in each dimension to use in computing the median to assign to each pixel/voxel. If the kernel size in a particular dimension is 1, then the median will not be computed in that direction.
 
| 1 1 1
|
|-
| '''Select Input Scalars'''<br>''(SelectInputScalars)''
|
The value of thie property lists the name of the scalar array to use in computing the median.
 
|
|
An array of scalars is required.
 
 
|}
 
 
==Merge Blocks==
 
 
vtkCompositeDataToUnstructuredGridFilter appends all vtkDataSet<br>
leaves of the input composite dataset to a single unstructure grid. The<br>
subtree to be combined can be choosen using the SubTreeCompositeIndex. If<br>
the SubTreeCompositeIndex is a leaf node, then no appending is required.<br>
 
{| class="PropertiesTable" border="1" cellpadding="5"
|-
| '''Property'''
| '''Description'''
| '''Default Value(s)'''
| '''Restrictions'''
|-
| '''Input'''<br>''(Input)''
|
Set the input composite dataset.
 
|
|
The selected dataset must be one of the following types (or a subclass of one of them): vtkCompositeDataSet.
 
 
|}
 
 
==Mesh Quality==
 
 
This filter creates a new cell array containing a geometric measure of each cell's fitness. Different quality measures can be chosen for different cell shapes.
 
This filter creates a new cell array containing a geometric measure of each cell's fitness. Different quality measures can be chosen for different cell shapes. Supported shapes include triangles, quadrilaterals, tetrahedra, and hexahedra. For other shapes, a value of 0 is assigned.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
{| class="PropertiesTable" border="1" cellpadding="5"
Line 4,178: Line 4,178:


<br>
<br>
The remaining columns (there are N, one for each array) contain 2 matrices in triangular format. The upper right triangle contains the covariance matrix (which is symmetric, so its lower triangle may be inferred). The lower left triangle contains the Cholesky decomposition of the covariance matrix (which is triangular, so its upper triangle is zero). Because the diagonal must be stored for both matrices, an additional row is required hence the N+1 rows and the final entry of the column named "Column".<br>
The remaining columns (there are N, one for each array) contain 2 matrices in triangular format. The upper right triangle contains the covariance matrix (which is symmetric, so its lower triangle may be inferred). The lower left triangle contains the Cholesky decomposition of the covariance matrix (which is triangular, so its upper triangle is zero). Because the diagonal must be stored for both matrices, an additional row is required — hence the N+1 rows and the final entry of the column named "Column".<br>




Line 4,220: Line 4,220:
|
|
|
|
The selected object must be the result of the following: sources (includes readers), filters.
The selected object must be the result of the following: sources (includes readers), filters.
 
 
 
 
The selected dataset must be one of the following types (or a subclass of one of them): vtkTable, vtkMultiBlockDataSet.
The selected dataset must be one of the following types (or a subclass of one of them): vtkTable, vtkMultiBlockDataSet.
 
 
 
 
|-
|-
| '''Variables of Interest'''<br>''(SelectArrays)''
| '''Variables of Interest'''<br>''(SelectArrays)''
|
|
Choose arrays whose entries will be used to form observations for statistical analysis.
Choose arrays whose entries will be used to form observations for statistical analysis.
 
 
|
|
|
|
An array of scalars is required.
An array of scalars is required.
 
 
 
 
|-
|-
| '''Task'''<br>''(Task)''
| '''Task'''<br>''(Task)''
|
|
Specify the task to be performed: modeling and/or assessment.
Specify the task to be performed: modeling and/or assessment.
#  "Statistics of all the data," creates an output table (or tables) summarizing the '''entire''' input dataset;
#  "Statistics of all the data," creates an output table (or tables) summarizing the '''entire''' input dataset;
#  "Model a subset of the data," creates an output table (or tables) summarizing a '''randomly-chosen subset''' of the input dataset;
#  "Model a subset of the data," creates an output table (or tables) summarizing a '''randomly-chosen subset''' of the input dataset;
#  "Assess the data with a model," adds attributes to the first input dataset using a model provided on the second input port; and
#  "Assess the data with a model," adds attributes to the first input dataset using a model provided on the second input port; and
#  "Model and assess the same data," is really just operations 2 and 3 above applied to the same input dataset. The model is first trained using a fraction of the input data and then the entire dataset is assessed using that model.
#  "Model and assess the same data," is really just operations 2 and 3 above applied to the same input dataset. The model is first trained using a fraction of the input data and then the entire dataset is assessed using that model.
 
 
When the task includes creating a model (i.e., tasks 2, and 4), you may adjust the fraction of the input dataset used for training. You should avoid using a large fraction of the input data for training as you will then not be able to detect overfitting. The ''Training fraction'' setting will be ignored for tasks 1 and 3.
When the task includes creating a model (i.e., tasks 2, and 4), you may adjust the fraction of the input dataset used for training. You should avoid using a large fraction of the input data for training as you will then not be able to detect overfitting. The ''Training fraction'' setting will be ignored for tasks 1 and 3.
 
 
| 3
| 3
|
|
The value must be one of the following: Statistics of all the data (0), Model a subset of the data (1), Assess the data with a model (2), Model and assess the same data (3).
The value must be one of the following: Statistics of all the data (0), Model a subset of the data (1), Assess the data with a model (2), Model and assess the same data (3).
 
 
 
 
|-
|-
| '''Training Fraction'''<br>''(TrainingFraction)''
| '''Training Fraction'''<br>''(TrainingFraction)''
|
|
Specify the fraction of values from the input dataset to be used for model fitting. The exact set of values is chosen at random from the dataset.
Specify the fraction of values from the input dataset to be used for model fitting. The exact set of values is chosen at random from the dataset.
 
 
| 0.1
| 0.1
|
|
The value must be greater than or equal to 0 and less than or equal to 1.
The value must be greater than or equal to 0 and less than or equal to 1.
 
 
|}
 
 
==Normal Glyphs==
 
 
Filter computing surface normals.
 
Filter computing surface normals.<br>
 
{| class="PropertiesTable" border="1" cellpadding="5"
|-
| '''Property'''
| '''Description'''
| '''Default Value(s)'''
| '''Restrictions'''
|-
| '''Consistency'''<br>''(Consistency)''
|
The value of this property controls whether consistent polygon ordering is enforced. Generally the normals for a data set should either all point inward or all point outward. If the value of this property is 1, then this filter will reorder the points of cells that whose normal vectors are oriented the opposite direction from the rest of those in the data set.
 
| 1
|
Only the values 0 and 1 are accepted.




|}
==Normal Glyphs==
Filter computing surface normals.
Filter computing surface normals.<br>
{| class="PropertiesTable" border="1" cellpadding="5"
|-
| '''Property'''
| '''Description'''
| '''Default Value(s)'''
| '''Restrictions'''
|-
|-
| '''Maximum Number of Points'''<br>''(Glyph Max. Points)''
| '''Maximum Number of Points'''<br>''(Glyph Max. Points)''
Line 4,512: Line 4,522:
Particle Pathlines takes any dataset as input, it extracts the<br>
Particle Pathlines takes any dataset as input, it extracts the<br>
point locations of all cells over time to build up a polyline<br>
point locations of all cells over time to build up a polyline<br>
trail. The point number (index) is used as the 'key' if the points<br>
trail. The point number (index) is used as the 'key' if the points<br>
are randomly changing their respective order in the points list,<br>
are randomly changing their respective order in the points list,<br>
then you should specify a scalar that represents the unique<br>
then you should specify a scalar that represents the unique<br>
Line 4,565: Line 4,575:
If a particle disappears from one end of a simulation and
If a particle disappears from one end of a simulation and
reappears on the other side, the track left will be
reappears on the other side, the track left will be
unrepresentative. Set a MaxStepDistance{x,y,z} which acts as a
unrepresentative. Set a MaxStepDistance{x,y,z} which acts as a
threshold above which if a step occurs larger than the value (for
threshold above which if a step occurs larger than the value (for
the dimension), the track will be dropped and restarted after the
the dimension), the track will be dropped and restarted after the
Line 4,581: Line 4,591:
displayed. Tracks longer then the Max will disappear and the
displayed. Tracks longer then the Max will disappear and the
trace will apppear like a snake of fixed length which progresses
trace will apppear like a snake of fixed length which progresses
as the particle moves. This length is given with respect to
as the particle moves. This length is given with respect to
timesteps.
timesteps.


Line 4,734: Line 4,744:
| '''Termination Time Unit'''<br>''(TerminationTimeUnit)''
| '''Termination Time Unit'''<br>''(TerminationTimeUnit)''
|
|
The termination time may be specified as TimeSteps or Simulation time
The termination time may be specified as TimeSteps or Simulation time


| 1
| 1
Line 4,878: Line 4,888:




Sample data attributes at the points along a line. Probed lines will be displayed in a graph of the attributes.
Sample data attributes at the points along a line. Probed lines will be displayed in a graph of the attributes.


The Plot Over Line filter samples the data set attributes of the current<br>
The Plot Over Line filter samples the data set attributes of the current<br>
Line 4,915: Line 4,925:
data-arrays that are not available in all of the blocks. By default,
data-arrays that are not available in all of the blocks. By default,
this filter only passes those point and cell data-arrays that are
this filter only passes those point and cell data-arrays that are
available in all the blocks i.e. partial array are removed. When
available in all the blocks i.e. partial array are removed. When
PassPartialArrays is turned on, this behavior is changed to take a
PassPartialArrays is turned on, this behavior is changed to take a
union of all arrays present thus partial arrays are passed as well.
union of all arrays present thus partial arrays are passed as well.
Line 4,950: Line 4,960:
Extracts selection over time and then plots it.
Extracts selection over time and then plots it.


This filter extracts the selection over time, i.e. cell and/or point<br>
This filter extracts the selection over time, i.e. cell and/or point<br>
variables at a cells/point selected are extracted over time<br>
variables at a cells/point selected are extracted over time<br>
The output multi-block consists of 1D rectilinear grids where the x coordinate<br>
The output multi-block consists of 1D rectilinear grids where the x coordinate<br>
Line 5,169: Line 5,179:
#  "Model a subset of the data," creates an output table (or tables) summarizing a '''randomly-chosen subset''' of the input dataset;
#  "Model a subset of the data," creates an output table (or tables) summarizing a '''randomly-chosen subset''' of the input dataset;
#  "Assess the data with a model," adds attributes to the first input dataset using a model provided on the second input port; and
#  "Assess the data with a model," adds attributes to the first input dataset using a model provided on the second input port; and
#  "Model and assess the same data," is really just operations 2 and 3 above applied to the same input dataset. The model is first trained using a fraction of the input data and then the entire dataset is assessed using that model.
#  "Model and assess the same data," is really just operations 2 and 3 above applied to the same input dataset. The model is first trained using a fraction of the input data and then the entire dataset is assessed using that model.


When the task includes creating a model (i.e., tasks 2, and 4), you may adjust the fraction of the input dataset used for training. You should avoid using a large fraction of the input data for training as you will then not be able to detect overfitting. The ''Training fraction'' setting will be ignored for tasks 1 and 3.
When the task includes creating a model (i.e., tasks 2, and 4), you may adjust the fraction of the input dataset used for training. You should avoid using a large fraction of the input data for training as you will then not be able to detect overfitting. The ''Training fraction'' setting will be ignored for tasks 1 and 3.


| 3
| 3
Line 5,373: Line 5,383:
valid Python variable, it has to be accessed through a dictionary called<br>
valid Python variable, it has to be accessed through a dictionary called<br>
arrays (i.e. arrays['array_name']). The points can be accessed using the<br>
arrays (i.e. arrays['array_name']). The points can be accessed using the<br>
points variable.       <br>
points variable. <br>


{| class="PropertiesTable" border="1" cellpadding="5"
{| class="PropertiesTable" border="1" cellpadding="5"
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This filter is the same filter used to generate level of detail for ParaView. It uses a structured grid of bins and merges all points contained in each bin.
This filter is the same filter used to generate level of detail for ParaView. It uses a structured grid of bins and merges all points contained in each bin.


The Quadric Clustering filter produces a reduced-resolution polygonal approximation of the input polygonal dataset. This filter is the one used by ParaView for computing LODs. It uses spatial binning to reduce the number of points in the data set; points that lie within the same spatial bin are collapsed into one representative point.<br>
The Quadric Clustering filter produces a reduced-resolution polygonal approximation of the input polygonal dataset. This filter is the one used by ParaView for computing LODs. It uses spatial binning to reduce the number of points in the data set; points that lie within the same spatial bin are collapsed into one representative point.<br>
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This filter generates ribbon surface from lines. It is useful for displaying streamlines.
This filter generates ribbon surface from lines. It is useful for displaying streamlines.


The Ribbon filter creates ribbons from the lines in the input data set. This filter is useful for visualizing streamlines. Both the input and output of this filter are polygonal data. The input data set must also have at least one point-centered vector array.<br>
The Ribbon filter creates ribbons from the lines in the input data set. This filter is useful for visualizing streamlines. Both the input and output of this filter are polygonal data. The input data set must also have at least one point-centered vector array.<br>
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This filter iteratively divide triangles into four smaller triangles. New points are placed linearly so the output surface matches the input surface.
This filter iteratively divide triangles into four smaller triangles. New points are placed linearly so the output surface matches the input surface.


The Subdivide filter iteratively divides each triangle in the input dataset into 4 new triangles. Three new points are added per triangle -- one at the midpoint of each edge. This filter operates only on polygonal data containing triangles, so run your polygonal data through the Triangulate filter first if it is not composed of triangles. The output of this filter is also polygonal.<br>
The Subdivide filter iteratively divides each triangle in the input dataset into 4 new triangles. Three new points are added per triangle -- one at the midpoint of each edge. This filter operates only on polygonal data containing triangles, so run your polygonal data through the Triangulate filter first if it is not composed of triangles. The output of this filter is also polygonal.<br>
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This filter integrates flow through a surface.
This filter integrates flow through a surface.


The flow integration fitler integrates the dot product of a point flow vector field and surface normal. It computes the net flow across the 2D surface. It operates on any type of dataset and produces an unstructured grid output.<br>
The flow integration fitler integrates the dot product of a point flow vector field and surface normal. It computes the net flow across the 2D surface. It operates on any type of dataset and produces an unstructured grid output.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
{| class="PropertiesTable" border="1" cellpadding="5"
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The dataset must contain a array with 1 components.
The dataset must contain a array with 1 components.




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The TableToStructuredGrid filter converts a vtkTable to a<br>
The TableToStructuredGrid filter converts a vtkTable to a<br>
vtkStructuredGrid. One must specifies the columns in the input table to<br>
vtkStructuredGrid. One must specifies the columns in the input table to<br>
use as the X, Y and Z coordinates for the points in the output, and the<br>
use as the X, Y and Z coordinates for the points in the output, and the<br>
whole extent.<br>
whole extent.<br>
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The dataset must contain a array with 1 components.
The dataset must contain a array with 1 components.




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Saves a copy of the data set for a fixed number of time steps.
Saves a copy of the data set for a fixed number of time steps.


The Temporal Cache can be used to save multiple copies of a data set at different time steps to prevent thrashing in the pipeline caused by downstream filters that adjust the requested time step. For example, assume that there is a downstream Temporal Interpolator filter. This filter will (usually) request two time steps from the upstream filters, which in turn (usually) causes the upstream filters to run twice, once for each time step. The next time the interpolator requests the same two time steps, they might force the upstream filters to re-evaluate the same two time steps. The Temporal Cache can keep copies of both of these time steps and provide the requested data without having to run upstream filters.<br>
The Temporal Cache can be used to save multiple copies of a data set at different time steps to prevent thrashing in the pipeline caused by downstream filters that adjust the requested time step. For example, assume that there is a downstream Temporal Interpolator filter. This filter will (usually) request two time steps from the upstream filters, which in turn (usually) causes the upstream filters to run twice, once for each time step. The next time the interpolator requests the same two time steps, they might force the upstream filters to re-evaluate the same two time steps. The Temporal Cache can keep copies of both of these time steps and provide the requested data without having to run upstream filters.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
{| class="PropertiesTable" border="1" cellpadding="5"
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| '''Cache Size'''<br>''(CacheSize)''
| '''Cache Size'''<br>''(CacheSize)''
|
|
The cache size determines the number of time steps that can be cached at one time. The maximum number is 10. The minimum is 2 (since it makes little sense to cache less than that).
The cache size determines the number of time steps that can be cached at one time. The maximum number is 10. The minimum is 2 (since it makes little sense to cache less than that).


| 2
| 2
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Interpolate between time steps.
Interpolate between time steps.


The Temporal Interpolator converts data that is defined at discrete time steps to one that is defined over a continuum of time by linearly interpolating the data's field data between two adjacent time steps. The interpolated values are a simple approximation and should not be interpreted as anything more. The Temporal Interpolator assumes that the topology between adjacent time steps does not change.<br>
The Temporal Interpolator converts data that is defined at discrete time steps to one that is defined over a continuum of time by linearly interpolating the data's field data between two adjacent time steps. The interpolated values are a simple approximation and should not be interpreted as anything more. The Temporal Interpolator assumes that the topology between adjacent time steps does not change.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
{| class="PropertiesTable" border="1" cellpadding="5"
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| '''Discrete Time Step Interval'''<br>''(DiscreteTimeStepInterval)''
| '''Discrete Time Step Interval'''<br>''(DiscreteTimeStepInterval)''
|
|
If Discrete Time Step Interval is set to 0, then the Temporal Interpolator will provide a continuous region of time on its output. If set to anything else, then the output will define a finite set of time points on its output, each spaced by the Discrete Time Step Interval. The output will have (time range)/(discrete time step interval) time steps. (Note that the time range is defined by the time range of the data of the input filter, which may be different from other pipeline objects or the range defined in the animation inspector.) This is a useful option to use if you have a dataset with one missing time step and wish to 'file-in' the missing data with an interpolated value from the steps on either side.
If Discrete Time Step Interval is set to 0, then the Temporal Interpolator will provide a continuous region of time on its output. If set to anything else, then the output will define a finite set of time points on its output, each spaced by the Discrete Time Step Interval. The output will have (time range)/(discrete time step interval) time steps. (Note that the time range is defined by the time range of the data of the input filter, which may be different from other pipeline objects or the range defined in the animation inspector.) This is a useful option to use if you have a dataset with one missing time step and wish to 'file-in' the missing data with an interpolated value from the steps on either side.


| 0
| 0
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Shift and scale time values.
Shift and scale time values.


The Temporal Shift Scale filter linearly transforms the time values of a pipeline object by applying a shift and then scale. Given a data at time t on the input, it will be transformed to time t*Shift + Scale on the output. Inversely, if this filter has a request for time t, it will request time (t-Shift)/Scale on its input.<br>
The Temporal Shift Scale filter linearly transforms the time values of a pipeline object by applying a shift and then scale. Given a data at time t on the input, it will be transformed to time t*Shift + Scale on the output. Inversely, if this filter has a request for time t, it will request time (t-Shift)/Scale on its input.<br>


{| class="PropertiesTable" border="1" cellpadding="5"
{| class="PropertiesTable" border="1" cellpadding="5"
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Given an input that changes over time, vtkTemporalStatistics looks<br>
Given an input that changes over time, vtkTemporalStatistics looks<br>
at the data for each time step and computes some statistical<br>
at the data for each time step and computes some statistical<br>
information of how a point or cell variable changes over time. For<br>
information of how a point or cell variable changes over time. For<br>
example, vtkTemporalStatistics can compute the average value of<br>
example, vtkTemporalStatistics can compute the average value of<br>
"pressure" over time of each point.<br><br><br>
"pressure" over time of each point.<br><br><br>
Note that this filter will require the upstream filter to be run on<br>
Note that this filter will require the upstream filter to be run on<br>
every time step that it reports that it can compute. This may be a<br>
every time step that it reports that it can compute. This may be a<br>
time consuming operation.<br><br><br>
time consuming operation.<br><br><br>
vtkTemporalStatistics ignores the temporal spacing. Each timestep<br>
vtkTemporalStatistics ignores the temporal spacing. Each timestep<br>
will be weighted the same regardless of how long of an interval it<br>
will be weighted the same regardless of how long of an interval it<br>
is to the next timestep. Thus, the average statistic may be quite<br>
is to the next timestep. Thus, the average statistic may be quite<br>
different from an integration of the variable if the time spacing<br>
different from an integration of the variable if the time spacing<br>
varies.<br>
varies.<br>
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This filter converts 3-d cells to tetrahedrons and polygons to triangles. The output is always of type unstructured grid.
This filter converts 3-d cells to tetrahedrons and polygons to triangles. The output is always of type unstructured grid.


The Tetrahedralize filter converts the 3D cells of any type of dataset to tetrahedrons and the 2D ones to triangles. This filter always produces unstructured grid output.<br>
The Tetrahedralize filter converts the 3D cells of any type of dataset to tetrahedrons and the 2D ones to triangles. This filter always produces unstructured grid output.<br>
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This filter moves point coordinates along a vector scaled by a point attribute. It can be used to produce carpet plots.
This filter moves point coordinates along a vector scaled by a point attribute. It can be used to produce carpet plots.


The Warp (scalar) filter translates the points of the input data set along a vector by a distance determined by the specified scalars. This filter operates on polygonal, curvilinear, and unstructured grid data sets containing single-component scalar arrays. Because it only changes the positions of the points, the output data set type is the same as that of the input. Any scalars in the input dataset are copied to the output, so the data can be colored by them.<br>
The Warp (scalar) filter translates the points of the input data set along a vector by a distance determined by the specified scalars. This filter operates on polygonal, curvilinear, and unstructured grid data sets containing single-component scalar arrays. Because it only changes the positions of the points, the output data set type is the same as that of the input. Any scalars in the input dataset are copied to the output, so the data can be colored by them.<br>

Revision as of 22:37, 1 February 2011