Difference between revisions of "ParaView/Users Guide/List of filters"
(Updating for ParaView 4.0) 

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Accepts boolean values (0 or 1).  Accepts boolean values (0 or 1).  
    
'''Generate Cell Origins''' (  '''Generate Cell Origins''' (ScalarMode)  
    
Generate (cell) data for coloring purposes such that the  Generate (cell) data for coloring purposes such that the  
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0  0  
    
The value(s) is an enumeration of the following:  
* None (0)  
* Color (1)  
* Label (2)  
    
'''InsideOut''' (InsideOut)  '''InsideOut''' (InsideOut)  
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An array of scalars is required.The value must be field array name.  An array of scalars is required.The value must be field array name.  
    
'''ComputeNormals''' (ComputeNormals)  '''ComputeNormals''' (ComputeNormals)  
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Accepts boolean values (0 or 1).  Accepts boolean values (0 or 1).  
  
'''GenerateTriangles''' (GenerateTriangles)  
  
This parameter controls whether to produce triangles in the output.  
Warning: Many filters do not properly handle nontrianglular polygons.  
  
1  
  
Accepts boolean values (0 or 1).  
  
'''Isosurfaces''' (ContourValues)  
  
This property specifies the values at which to compute  
isosurfaces/isolines and also the number of such  
values.  
  
  
The value must lie within the range of the selected data array.  
    
'''Point Merge Method''' (Locator)  '''Point Merge Method''' (Locator)  
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An array of scalars is required.The value must be field array name.  An array of scalars is required.The value must be field array name.  
    
'''ComputeNormals''' (ComputeNormals)  '''ComputeNormals''' (ComputeNormals)  
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Accepts boolean values (0 or 1).  Accepts boolean values (0 or 1).  
  
'''Isosurfaces''' (ContourValues)  
  
This property specifies the values at which to compute  
isosurfaces/isolines and also the number of such  
values.  
  
  
The value must lie within the range of the selected data array.  
    
'''Point Merge Method''' (Locator)  '''Point Merge Method''' (Locator)  
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'''Input''' (Input)  '''Input''' (Input)  
    
This property specifies the input of the  This property specifies the input of the filter.  
filter.  
    
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'''  '''Quadrature Scheme Def''' (QuadratureSchemeDefinition)  
    
Specifies the offset array from which we generate  Specifies the offset array from which we generate  
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'''Input''' (Input)  '''Input''' (Input)  
    
This property specifies the input of the  This property specifies the input of the filter.  
filter.  
    
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Accepts input of following types:  Accepts input of following types:  
* vtkUnstructuredGrid  * vtkUnstructuredGrid  
The dataset much contain a field array (cell)  
    
'''  '''Quadrature Scheme Def''' (QuadratureSchemeDefinition)  
    
Specifies the offset array from which we interpolate  Specifies the offset array from which we interpolate  
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Accepts input of following types:  Accepts input of following types:  
* vtkSelection  * vtkSelection  
  
'''Only Report Selection Statistics''' (Only Report Selection Statistics)  
  
If this property is set to 1, the min, max,  
interquartile ranges, and (for numeric arrays) mean and standard  
deviation of all the selected points or cells within each time step  
are reported  instead of breaking each selected point's or cell's  
attributes out into separate time history tables.  
  
0  
  
Accepts boolean values (0 or 1).  
}  
==Point Data to Cell Data==  ==Point Data to Cell Data==  
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}  
==Temporal Particles To Pathlines==  
Creates polylines representing pathlines of animating particles  
Particle Pathlines takes any dataset as input, it extracts the  
point locations of all cells over time to build up a polyline  
trail. The point number (index) is used as the 'key' if the points  
are randomly changing their respective order in the points list,  
then you should specify a scalar that represents the unique  
ID. This is intended to handle the output of a filter such as the  
TemporalStreamTracer.  
{ class="PropertiesTable" border="1" cellpadding="5"  
  
 '''Property'''  
 '''Description'''  
 '''Default Value(s)'''  
 '''Restrictions'''  
  
'''Input''' (Input)  
  
The input cells to create pathlines for.  
  
  
Accepts input of following types:  
* vtkPointSet  
The dataset much contain a field array (point)  
  
'''Selection''' (Selection)  
  
Set a second input, which is a selection. Particles with the same  
Id in the selection as the primary input will be chosen for  
pathlines Note that you must have the same IdChannelArray in the  
selection as the input  
  
  
Accepts input of following types:  
* vtkDataSet  
  
'''MaskPoints''' (MaskPoints)  
  
Set the number of particles to track as a ratio of the input.  
Example: setting MaskPoints to 10 will track every 10th point.  
  
100  
  
  
'''MaxTrackLength''' (MaxTrackLength)  
  
If the Particles being traced animate for a long time, the trails  
or traces will become long and stringy. Setting the  
MaxTraceTimeLength will limit how much of the trace is  
displayed. Tracks longer then the Max will disappear and the  
trace will apppear like a snake of fixed length which progresses  
as the particle moves. This length is given with respect to  
timesteps.  
  
25  
  
  
'''MaxStepDistance''' (MaxStepDistance)  
  
If a particle disappears from one end of a simulation and  
reappears on the other side, the track left will be  
unrepresentative. Set a MaxStepDistance{x,y,z} which acts as a  
threshold above which if a step occurs larger than the value (for  
the dimension), the track will be dropped and restarted after the  
step. (ie the part before the wrap around will be dropped and the  
newer part kept).  
  
1.0 1.0 1.0  
  
  
'''IdChannelArray''' (IdChannelArray)  
  
Specify the name of a scalar array which will be used to fetch  
the index of each point. This is necessary only if the particles  
change position (Id order) on each time step. The Id can be used  
to identify particles at each step and hence track them properly.  
If this array is set to "Global or Local IDs", the global point  
ids are used if they exist or the point index is otherwise.  
  
Global or Local IDs  
  
An array of scalars is required.  
}  }  
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1  1  
  
Accepts boolean values (0 or 1).  
  
'''UseContinuousCellRange''' (UseContinuousCellRange)  
  
If off, the vertex scalars are treated as a discrete set. If on, they  
are treated as a continuous interval over the minimum and maximum. One  
important "on" use case: When setting lower and upper threshold  
equal to some value and turning AllScalars off, the results are  
cells containing the isosurface for that value. WARNING: Whether on  
or off, for higher order input, the filter will not give accurate  
results.  
  
0  
    
Accepts boolean values (0 or 1).  Accepts boolean values (0 or 1). 
Revision as of 09:32, 16 May 2013
AMR Contour
Iso surface cell array.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input of the filter. 
Accepts input of following types:
The dataset much contain a field array (cell) with 1 component(s).  
SelectMaterialArrays (SelectMaterialArrays) 
This property specifies the cell arrays from which the contour filter will compute contour cells. 
An array of scalars is required.  
Volume Fraction Value (VolumeFractionSurfaceValue) 
This property specifies the values at which to compute the isosurface. 
0.1 

Capping (Capping) 
If this property is on, the the boundary of the data set is capped. 
1 
Accepts boolean values (0 or 1). 
DegenerateCells (DegenerateCells) 
If this property is on, a transition mesh between levels is created. 
1 
Accepts boolean values (0 or 1). 
MultiprocessCommunication (MultiprocessCommunication) 
If this property is off, each process executes independantly. 
1 
Accepts boolean values (0 or 1). 
SkipGhostCopy (SkipGhostCopy) 
A simple test to see if ghost values are already set properly. 
1 
Accepts boolean values (0 or 1). 
Triangulate (Triangulate) 
Use triangles instead of quads on capping surfaces. 
1 
Accepts boolean values (0 or 1). 
MergePoints (MergePoints) 
Use more memory to merge points on the boundaries of blocks. 
1 
Accepts boolean values (0 or 1). 
AMR CutPlane
Planar Cut of an AMR grid datasetThis filter creates a cutplane of the
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input for this filter. 
Accepts input of following types:
 
UseNativeCutter (UseNativeCutter) 
This property specifies whether the ParaView's generic dataset cutter is used instead of the specialized AMR cutter. 
0 
Accepts boolean values (0 or 1). 
LevelOfResolution (LevelOfResolution) 
Set maximum slice resolution. 
0 

Center (Center) 
0.5 0.5 0.5 

Normal (Normal) 
0 0 1 

AMR Dual Clip
Clip with scalars. Tetrahedra.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input of the filter. 
Accepts input of following types:
The dataset much contain a field array (cell) with 1 component(s).  
SelectMaterialArrays (SelectMaterialArrays) 
This property specifies the cell arrays from which the clip filter will compute clipped cells. 
An array of scalars is required.  
Volume Fraction Value (VolumeFractionSurfaceValue) 
This property specifies the values at which to compute the isosurface. 
0.1 

InternalDecimation (InternalDecimation) 
If this property is on, internal tetrahedra are decimation 
1 
Accepts boolean values (0 or 1). 
MultiprocessCommunication (MultiprocessCommunication) 
If this property is off, each process executes independantly. 
1 
Accepts boolean values (0 or 1). 
MergePoints (MergePoints) 
Use more memory to merge points on the boundaries of blocks. 
1 
Accepts boolean values (0 or 1). 
All to N
Redistribute data to a subset of available processes.The All to N filter is available when ParaView is run in parallel. It redistributes the data so that it is located on the number of processes specified in the Number of Processes entry box. It also does loadbalancing of the data among these processes. This filter operates on polygonal data and produces polygonal output.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Set the input to the All to N filter. 
Accepts input of following types:
 
Number of Processes (NumberOfProcesses) 
Set the number of processes across which to split the input data. 
1 

Annotate Global Data
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Set the input of the filter. 
Accepts input of following types:
The dataset much contain a field array (none) with 1 component(s).  
SelectArrays (SelectArrays) 
Choose arrays that is going to be displayed 

Prefix (Prefix) 
Text that is used as a prefix to the field value 
Value is: 

Annotate Time Filter
Shows input data time as text annnotation in the view.The Annotate Time filter can be used to show the data time in a text annotation.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input dataset for which to display the time. 

Format (Format) 
The value of this property is a format string used to display the input time. The format string is specified using printf style. 
Time: %f 

Shift (Shift) 
The amount of time the input is shifted (after scaling). 
0.0 

Scale (Scale) 
The factor by which the input time is scaled. 
1.0 

Append Attributes
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.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Append Attributes filter. 
Accepts input of following types:

Append Datasets
Takes an input of multiple datasets and output has only one unstructured grid.The Append Datasets filter operates on multiple data sets of any type (polygonal, structured, etc.). It merges their geometry into a single data set. Only the point and cell attributes that all of the input data sets have in common will appear in the output. 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.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the datasets to be merged into a single dataset by the Append Datasets filter. 
Accepts input of following types:

Append Geometry
Takes an input of multiple poly data parts and output has only one part.The Append Geometry filter operates on multiple polygonal data sets. It merges their geometry into a single data set. Only the point and cell attributes that all of the input data sets have in common will appear in the output.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Set the input to the Append Geometry filter. 
Accepts input of following types:

Balance
Balance data among available processes.The Balance filter is available when ParaView is run in parallel. It does loadbalancing so that all processes have the same number of cells. It operates on polygonal data sets and produces polygonal output.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Set the input to the Balance filter. 
Accepts input of following types:

Block Scalars
The Level Scalars filter uses colors to show levels of a multiblock dataset.The Level Scalars filter uses colors to show levels of a multiblock dataset.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Level Scalars filter. 
Accepts input of following types:

CTH Surface
Not finished yet.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input of the filter. 
Accepts input of following types:

CacheKeeper
vtkPVCacheKeeper manages data cache for flip book animations. When caching is disabled, this simply acts as a pass through filter. When caching is enabled, is the current time step has been previously cached then this filter shuts the update request, otherwise propagates the update and then cache the result for later use. The current time step is set using SetCacheTime().
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Set the input to the Update Suppressor filter. 

CacheTime (CacheTime) 
0.0 

CachingEnabled (CachingEnabled) 
Toggle whether the caching is enabled. 
1 
Accepts boolean values (0 or 1). 
Calculator
Compute new attribute arrays as function of existing arrays.The Calculator filter computes a new data array or new point coordinates as a function of existing scalar or vector arrays. If pointcentered arrays are used in the computation of a new data array, the resulting array will also be pointcentered. Similarly, computations using cellcentered arrays will produce a new cellcentered array. If the function is computing point coordinates, the result of the function must be a threecomponent vector. The Calculator interface operates similarly to a scientific calculator. In creating the function to evaluate, the standard order of operations applies. Each of the calculator functions is described below. Unless otherwise noted, enclose the operand in parentheses using the ( and ) buttons. Clear: Erase the current function (displayed in the readonly text box above the calculator buttons). /: Divide one scalar by another. The operands for this function are not required to be enclosed in parentheses. *: Multiply two scalars, or multiply a vector by a scalar (scalar multiple). The operands for this function are not required to be enclosed in parentheses. : Negate a scalar or vector (unary minus), or subtract one scalar or vector from another. The operands for this function are not required to be enclosed in parentheses. +: Add two scalars or two vectors. The operands for this function are not required to be enclosed in parentheses. sin: Compute the sine of a scalar. cos: Compute the cosine of a scalar. tan: Compute the tangent of a scalar. asin: Compute the arcsine of a scalar. acos: Compute the arccosine of a scalar. atan: Compute the arctangent of a scalar. sinh: Compute the hyperbolic sine of a scalar. cosh: Compute the hyperbolic cosine of a scalar. tanh: Compute the hyperbolic tangent of a scalar. min: Compute minimum of two scalars. max: Compute maximum of two scalars. x^y: Raise one scalar to the power of another scalar. The operands for this function are not required to be enclosed in parentheses. sqrt: Compute the square root of a scalar. e^x: Raise e to the power of a scalar. log: Compute the logarithm of a scalar (deprecated. same as log10). log10: Compute the logarithm of a scalar to the base 10. ln: Compute the logarithm of a scalar to the base 'e'. ceil: Compute the ceiling of a scalar. floor: Compute the floor of a scalar. abs: Compute the absolute value of a scalar. v1.v2: Compute the dot product of two vectors. The operands for this function are not required to be enclosed in parentheses. cross: Compute cross product of two vectors. mag: Compute the magnitude of a vector. norm: Normalize a vector. The operands are described below. The digits 0  9 and the decimal point are used to enter constant scalar values. iHat, jHat, and kHat are vector constants representing unit vectors in the X, Y, and Z directions, respectively. The scalars menu lists the names of the scalar arrays and the components of the vector arrays of either the pointcentered or cellcentered data. The vectors menu lists the names of the pointcentered or cellcentered vector arrays. The function will be computed for each point (or cell) using the scalar or vector value of the array at that point (or cell). The filter operates on any type of data set, but the input data set must have at least one scalar or vector array. The arrays can be either pointcentered or cellcentered. The Calculator filter's output is of the same data set type as the input.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input dataset to the Calculator filter. The scalar and vector variables may be chosen from this dataset's arrays. 
Accepts input of following types:
The dataset much contain a field array ()  
AttributeMode (AttributeMode) 
This property determines whether the computation is to be performed on pointcentered or cellcentered data. 
1 
The value(s) is an enumeration of the following:

CoordinateResults (CoordinateResults) 
The value of this property determines whether the results of this computation should be used as point coordinates or as a new array. 
0 
Accepts boolean values (0 or 1). 
ResultArrayName (ResultArrayName) 
This property contains the name for the output array containing the result of this computation. 
Result 

Function (Function) 
This property contains the equation for computing the new array. 

Replace Invalid Results (ReplaceInvalidValues) 
This property determines whether invalid values in the computation will be replaced with a specific value. (See the ReplacementValue property.) 
1 
Accepts boolean values (0 or 1). 
ReplacementValue (ReplacementValue) 
If invalid values in the computation are to be replaced with another value, this property contains that value. 
0.0 

Cell Centers
Create a point (no geometry) at the center of each input cell.The Cell Centers filter places a point at the center of each cell in the input data set. The center computed is the parametric center of the cell, not necessarily the geometric or bounding box center. The cell attributes of the input will be associated with these newly created points of the output. You have the option of creating a vertex cell per point in the outpuut. This is useful because vertex cells are rendered, but points are not. The points themselves could be used for placing glyphs (using the Glyph filter). The Cell Centers filter takes any type of data set as input and produces a polygonal data set as output.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Cell Centers filter. 
Accepts input of following types:
 
VertexCells (VertexCells) 
If set to 1, a vertex cell will be generated per point in the output. Otherwise only points will be generated. 
0 
Accepts boolean values (0 or 1). 
Cell Data to Point Data
Create point attributes by averaging cell attributes.The Cell Data to Point Data filter averages the values of the cell attributes of the cells surrounding a point to compute point attributes. The Cell Data to Point Data filter operates on any type of data set, and the output data set is of the same type as the input.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Cell Data to Point Data filter. 
Accepts input of following types:
The dataset much contain a field array (cell)  
PassCellData (PassCellData) 
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 
Accepts boolean values (0 or 1). 
PieceInvariant (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 
Accepts boolean values (0 or 1). 
Clean
Merge coincident points if they do not meet a feature edge criteria.The Clean filter takes polygonal data as input and generates polygonal data as output. This filter can merge duplicate points, remove unused points, and transform degenerate cells into their appropriate forms (e.g., a triangle is converted into a line if two of its points are merged).
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Set the input to the Clean filter. 
Accepts input of following types:
 
PieceInvariant (PieceInvariant) 
If this property is set to 1, the whole data set will be processed at once so that cleaning the data set always produces the same results. If it is set to 0, the data set can be processed one piece at a time, so it is not necessary for the entire data set to fit into memory; however the results are not guaranteed to be the same as they would be if the Piece invariant option was on. Setting this option to 0 may produce seams in the output dataset when ParaView is run in parallel. 
1 
Accepts boolean values (0 or 1). 
Tolerance (Tolerance) 
If merging nearby points (see PointMerging property) and not using absolute tolerance (see ToleranceIsAbsolute property), this property specifies the tolerance for performing merging as a fraction of the length of the diagonal of the bounding box of the input data set. 
0.0 

AbsoluteTolerance (AbsoluteTolerance) 
If merging nearby points (see PointMerging property) and using absolute tolerance (see ToleranceIsAbsolute property), this property specifies the tolerance for performing merging in the spatial units of the input data set. 
1.0 

ToleranceIsAbsolute (ToleranceIsAbsolute) 
This property determines whether to use absolute or relative (a percentage of the bounding box) tolerance when performing point merging. 
0 
Accepts boolean values (0 or 1). 
ConvertLinesToPoints (ConvertLinesToPoints) 
If this property is set to 1, degenerate lines (a "line" whose endpoints are at the same spatial location) will be converted to points. 
1 
Accepts boolean values (0 or 1). 
ConvertPolysToLines (ConvertPolysToLines) 
If this property is set to 1, degenerate polygons (a "polygon" with only two distinct point coordinates) will be converted to lines. 
1 
Accepts boolean values (0 or 1). 
ConvertStripsToPolys (ConvertStripsToPolys) 
If this property is set to 1, degenerate triangle strips (a triangle "strip" containing only one triangle) will be converted to triangles. 
1 
Accepts boolean values (0 or 1). 
PointMerging (PointMerging) 
If this property is set to 1, then points will be merged if they are within the specified Tolerance or AbsoluteTolerance (see the Tolerance and AbsoluteTolerance propertys), depending on the value of the ToleranceIsAbsolute property. (See the ToleranceIsAbsolute property.) If this property is set to 0, points will not be merged. 
1 
Accepts boolean values (0 or 1). 
Clean Cells to Grid
This filter merges cells and converts the data set to unstructured grid.Merges degenerate cells. Assumes the input grid does not contain duplicate points. You may want to run vtkCleanUnstructuredGrid first to assert it. If duplicated cells are found they are removed in the output. The filter also handles the case, where a cell may contain degenerate nodes (i.e. one and the same node is referenced by a cell more than once).
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Clean Cells to Grid filter. 
Accepts input of following types:

Clean to Grid
This filter merges points and converts the data set to unstructured grid.The Clean to Grid filter merges points that are exactly coincident. It also converts the data set to an unstructured grid. You may wish to do this if you want to apply a filter to your data set that is available for unstructured grids but not for the initial type of your data set (e.g., applying warp vector to volumetric data). The Clean to Grid filter operates on any type of data set.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Clean to Grid filter. 
Accepts input of following types:

ClientServerMoveData
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Set the input to the Client Server Move Data filter. 

OutputDataType (OutputDataType) 
0 

WholeExtent (WholeExtent) 
0 1 0 1 0 1 

Clip
Clip with an implicit plane. Clipping does not reduce the dimensionality of the data set. The output data type of this filter is always an unstructured grid.The Clip filter cuts away a portion of the input data set using an implicit plane. This filter operates on all types of data sets, and it returns unstructured grid data on output.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the dataset on which the Clip filter will operate. 
Accepts input of following types:
The dataset much contain a field array () with 1 component(s).  
Clip Type (ClipFunction) 
This property specifies the parameters of the clip function (an implicit plane) used to clip the dataset. 
The value can be one of the following:
 
InputBounds (InputBounds)  
Scalars (SelectInputScalars) 
If clipping with scalars, this property specifies the name of the scalar array on which to perform the clip operation. 
An array of scalars is required.The value must be field array name.  
Value (Value) 
If clipping with scalars, this property sets the scalar value about which to clip the dataset based on the scalar array chosen. (See SelectInputScalars.) If clipping with a clip function, this property specifies an offset from the clip function to use in the clipping operation. Neither functionality is currently available in ParaView's user interface. 
0.0 
The value must lie within the range of the selected data array. 
InsideOut (InsideOut) 
If this property is set to 0, the clip filter will return that portion of the dataset that lies within the clip function. If set to 1, the portions of the dataset that lie outside the clip function will be returned instead. 
0 
Accepts boolean values (0 or 1). 
UseValueAsOffset (UseValueAsOffset) 
If UseValueAsOffset is true, Value is used as an offset parameter to the implicit function. Otherwise, Value is used only when clipping using a scalar array. 
0 
Accepts boolean values (0 or 1). 
Crinkle clip (PreserveInputCells) 
This parameter controls whether to extract entire cells in the given region or clip those cells so all of the output one stay only inside that region. 
0 
Accepts boolean values (0 or 1). 
Clip Closed Surface
Clip a polygonal dataset with a plane to produce closed surfaces This clip filter cuts away a portion of the input polygonal dataset using a plane to generate a new polygonal dataset.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the dataset on which the Clip filter will operate. 
Accepts input of following types:
The dataset much contain a field array (point) with 1 component(s).  
Clipping Plane (ClippingPlane) 
This property specifies the parameters of the clipping plane used to clip the polygonal data. 
The value can be one of the following:
 
GenerateFaces (GenerateFaces) 
Generate polygonal faces in the output. 
1 
Accepts boolean values (0 or 1). 
GenerateOutline (GenerateOutline) 
Generate clipping outlines in the output wherever an input face is cut by the clipping plane. 
0 
Accepts boolean values (0 or 1). 
Generate Cell Origins (ScalarMode) 
Generate (cell) data for coloring purposes such that the newly generated cells (including capping faces and clipping outlines) can be distinguished from the input cells. 
0 
The value(s) is an enumeration of the following:

InsideOut (InsideOut) 
If this flag is turned off, the clipper will return the portion of the data that lies within the clipping plane. Otherwise, the clipper will return the portion of the data that lies outside the clipping plane. 
0 
Accepts boolean values (0 or 1). 
Clipping Tolerance (Tolerance) 
Specify the tolerance for creating new points. A small value might incur degenerate triangles. 
0.000001 

Base Color (BaseColor) 
Specify the color for the faces from the input. 
0.10 0.10 1.00 

Clip Color (ClipColor) 
Specifiy the color for the capping faces (generated on the clipping interface). 
1.00 0.11 0.10 

Clip Generic Dataset
Clip with an implicit plane, sphere or with scalars. Clipping does not reduce the dimensionality of the data set. This output data type of this filter is always an unstructured grid. The Generic Clip filter cuts away a portion of the input data set using a plane, a sphere, a box, or a scalar value. The menu in the Clip Function portion of the interface allows the user to select which implicit function to use or whether to clip using a scalar value. Making this selection loads the appropriate user interface. For the implicit functions, the appropriate 3D widget (plane, sphere, or box) is also displayed. The use of these 3D widgets, including their user interface components, is discussed in section 7.4. If an implicit function is selected, the clip filter returns that portion of the input data set that lies inside the function. If Scalars is selected, then the user must specify a scalar array to clip according to. The clip filter will return the portions of the data set whose value in the selected Scalars array is larger than the Clip value. Regardless of the selection from the Clip Function menu, if the Inside Out option is checked, the opposite portions of the data set will be returned. This filter operates on all types of data sets, and it returns unstructured grid data on output.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Set the input to the Generic Clip filter. 
Accepts input of following types:
The dataset much contain a field array (point)  
Clip Type (ClipFunction) 
Set the parameters of the clip function. 
The value can be one of the following:
 
InputBounds (InputBounds)  
Scalars (SelectInputScalars) 
If clipping with scalars, this property specifies the name of the scalar array on which to perform the clip operation. 
An array of scalars is required.The value must be field array name.  
InsideOut (InsideOut) 
Choose which portion of the dataset should be clipped away. 
0 
Accepts boolean values (0 or 1). 
Value (Value) 
If clipping with a scalar array, choose the clipping value. 
0.0 
The value must lie within the range of the selected data array. 
Compute Derivatives
This filter computes derivatives of scalars and vectors. CellDerivatives is a filter that computes derivatives of scalars and vectors at the center of cells. You can choose to generate different output including the scalar gradient (a vector), computed tensor vorticity (a vector), gradient of input vectors (a tensor), and strain matrix of the input vectors (a tensor); or you may choose to pass data through to the output.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the filter. 
Accepts input of following types:
The dataset much contain a field array (point) with 1 component(s). The dataset much contain a field array (point) with 3 component(s).  
Scalars (SelectInputScalars) 
This property indicates the name of the scalar array to differentiate. 
An array of scalars is required.  
Vectors (SelectInputVectors) 
This property indicates the name of the vector array to differentiate. 
1 
An array of vectors is required. 
OutputVectorType (OutputVectorType) 
This property Controls how the filter works to generate vector cell data. You can choose to compute the gradient of the input scalars, or extract the vorticity of the computed vector gradient tensor. By default, the filter will take the gradient of the input scalar data. 
1 
The value(s) is an enumeration of the following:

OutputTensorType (OutputTensorType) 
This property controls how the filter works to generate tensor cell data. You can choose to compute the gradient of the input vectors, or compute the strain tensor of the vector gradient tensor. By default, the filter will take the gradient of the vector data to construct a tensor. 
1 
The value(s) is an enumeration of the following:

Connectivity
Mark connected components with integer point attribute array.The Connectivity filter assigns a region id to connected components of the input data set. (The region id is assigned as a point scalar value.) This filter takes any data set type as input and produces unstructured grid output.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Connectivity filter. 
Accepts input of following types:
 
ExtractionMode (ExtractionMode) 
Controls the extraction of connected surfaces. 
5 
The value(s) is an enumeration of the following:

ColorRegions (ColorRegions) 
Controls the coloring of the connected regions. 
1 
Accepts boolean values (0 or 1). 
Contingency 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. This filter computes contingency tables between pairs of attributes. This result is a tabular bivariate probability distribution which serves as a Bayesianstyle prior model. Data is assessed by computing <ul> <li> the probability of observing both variables simultaneously; <li> the probability of each variable conditioned on the other (the two values need not be identical); and <li> the pointwise mutual information (PMI). </ul> Finally, the summary statistics include the information entropy of the observations.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
The input to the filter. Arrays from this dataset will be used for computing statistics and/or assessed by a statistical model. 
Accepts input of following types:
The dataset much contain a field array ()  
ModelInput (ModelInput) 
A previouslycalculated model with which to assess a separate dataset. This input is optional. 
Accepts input of following types:
 
AttributeMode (AttributeMode) 
Specify which type of field data the arrays will be drawn from. 
0 
The value must be field array name. 
Variables of Interest (SelectArrays) 
Choose arrays whose entries will be used to form observations for statistical analysis. 

Task (Task) 
Specify the task to be performed: modeling and/or assessment. <ol> <li> "Detailed model of input data," creates a set of output tables containing a calculated statistical model of the <b>entire</b> input dataset;</li> <li> "Model a subset of the data," creates an output table (or tables) summarizing a <b>randomlychosen subset</b> of the input dataset;</li> <li> "Assess the data with a model," adds attributes to the first input dataset using a model provided on the second input port; and</li> <li> "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.</li> </ol> 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 <i>Training fraction</i> setting will be ignored for tasks 1 and 3. 
3 
The value(s) is an enumeration of the following:

TrainingFraction (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 

Contour
Generate isolines or isosurfaces using point scalars.The Contour filter computes isolines or isosurfaces using a selected pointcentered scalar array. The Contour filter operates on any type of data set, but the input is required to have at least one pointcentered scalar (singlecomponent) array. The output of this filter is polygonal.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input dataset to be used by the contour filter. 
Accepts input of following types:
The dataset much contain a field array (point) with 1 component(s).  
Contour By (SelectInputScalars) 
This property specifies the name of the scalar array from which the contour filter will compute isolines and/or isosurfaces. 
An array of scalars is required.The value must be field array name.  
ComputeNormals (ComputeNormals) 
If this property is set to 1, a scalar array containing a normal value at each point in the isosurface or isoline will be created by the contour filter; otherwise an array of normals will not be computed. This operation is fairly expensive both in terms of computation time and memory required, so if the output dataset produced by the contour filter will be processed by filters that modify the dataset's topology or geometry, it may be wise to set the value of this property to 0. Select whether to compute normals. 
1 
Accepts boolean values (0 or 1). 
ComputeGradients (ComputeGradients) 
If this property is set to 1, a scalar array containing a gradient value at each point in the isosurface or isoline will be created by this filter; otherwise an array of gradients will not be computed. This operation is fairly expensive both in terms of computation time and memory required, so if the output dataset produced by the contour filter will be processed by filters that modify the dataset's topology or geometry, it may be wise to set the value of this property to 0. Not that if ComputeNormals is set to 1, then gradients will have to be calculated, but they will only be stored in the output dataset if ComputeGradients is also set to 1. 
0 
Accepts boolean values (0 or 1). 
ComputeScalars (ComputeScalars) 
If this property is set to 1, an array of scalars (containing the contour value) will be added to the output dataset. If set to 0, the output will not contain this array. 
0 
Accepts boolean values (0 or 1). 
GenerateTriangles (GenerateTriangles) 
This parameter controls whether to produce triangles in the output. Warning: Many filters do not properly handle nontrianglular polygons. 
1 
Accepts boolean values (0 or 1). 
Isosurfaces (ContourValues) 
This property specifies the values at which to compute isosurfaces/isolines and also the number of such values. 
The value must lie within the range of the selected data array.  
Point Merge Method (Locator) 
This property specifies an incremental point locator for merging duplicate / coincident points. 
The value can be one of the following:

Contour Generic Dataset
Generate isolines or isosurfaces using point scalars.The Generic Contour filter computes isolines or isosurfaces using a selected pointcentered scalar array. The available scalar arrays are listed in the Scalars menu. The scalar range of the selected array will be displayed. The interface for adding contour values is very similar to the one for selecting cut offsets (in the Cut filter). To add a single contour value, select the value from the New Value slider in the Add value portion of the interface and click the Add button, or press Enter. To instead add several evenly spaced contours, use the controls in the Generate range of values section. Select the number of contour values to generate using the Number of Values slider. The Range slider controls the interval in which to generate the contour values. Once the number of values and range have been selected, click the Generate button. The new values will be added to the Contour Values list. To delete a value from the Contour Values list, select the value and click the Delete button. (If no value is selected, the last value in the list will be removed.) Clicking the Delete All button removes all the values in the list. If no values are in the Contour Values list when Accept is pressed, the current value of the New Value slider will be used. In addition to selecting contour values, you can also select additional computations to perform. If any of Compute Normals, Compute Gradients, or Compute Scalars is selected, the appropriate computation will be performed, and a corresponding pointcentered array will be added to the output. The Generic Contour filter operates on a generic data set, but the input is required to have at least one pointcentered scalar (singlecomponent) array. The output of this filter is polygonal.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Set the input to the Generic Contour filter. 
Accepts input of following types:
The dataset much contain a field array (point) with 1 component(s).  
Contour By (SelectInputScalars) 
This property specifies the name of the scalar array from which the contour filter will compute isolines and/or isosurfaces. 
An array of scalars is required.The value must be field array name.  
ComputeNormals (ComputeNormals) 
Select whether to compute normals. 
1 
Accepts boolean values (0 or 1). 
ComputeGradients (ComputeGradients) 
Select whether to compute gradients. 
0 
Accepts boolean values (0 or 1). 
ComputeScalars (ComputeScalars) 
Select whether to compute scalars. 
0 
Accepts boolean values (0 or 1). 
Isosurfaces (ContourValues) 
This property specifies the values at which to compute isosurfaces/isolines and also the number of such values. 
The value must lie within the range of the selected data array.  
Point Merge Method (Locator) 
This property specifies an incremental point locator for merging duplicate / coincident points. 
The value can be one of the following:

Convert AMR dataset to Multiblock
Convert AMR to Multiblock
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input for this filter. 
Accepts input of following types:

ConvertSelection
Converts a selection from one type to another.
Property  Description  Default Value(s)  Restrictions 
DataInput (DataInput) 
Set the vtkDataObject input used to convert the selection. 
Accepts input of following types:
 
Input (Input) 
Set the selection to convert. 
Accepts input of following types:
 
OutputType (OutputType) 
Set the ContentType for the output. 
5 
The value(s) is an enumeration of the following:

ArrayNames (ArrayNames)  
MatchAnyValues (MatchAnyValues) 
0 
Accepts boolean values (0 or 1). 
Crop
Efficiently extract an area/volume of interest from a 2d image or 3d volume.The Crop filter extracts an area/volume of interest from a 2D image or a 3D volume by allowing the user to specify the minimum and maximum extents of each dimension of the data. Both the input and output of this filter are uniform rectilinear data.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Crop filter. 
Accepts input of following types:
 
OutputWholeExtent (OutputWholeExtent) 
This property gives the minimum and maximum point index (extent) in each dimension for the output dataset. 
0 0 0 0 0 0 
The value(s) must lie within the structuredextents of the input dataset. 
Curvature
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. ; the type can be selected from the Curvature type menu button.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Curvature filter. 
Accepts input of following types:
 
InvertMeanCurvature (InvertMeanCurvature) 
If this property is set to 1, the mean curvature calculation will be inverted. This is useful for meshes with inwardpointing normals. 
0 
Accepts boolean values (0 or 1). 
CurvatureType (CurvatureType) 
This propery specifies which type of curvature to compute. 
0 
The value(s) is an enumeration of the following:

D3
Repartition a data set into loadbalanced spatially convex regions. Create ghost cells if requested.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.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the D3 filter. 
Accepts input of following types:
 
BoundaryMode (BoundaryMode) 
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 
The value(s) is an enumeration of the following:

Minimal Memory (UseMinimalMemory) 
If this property is set to 1, the D3 filter requires communication routines to use minimal memory than without this restriction. 
0 
Accepts boolean values (0 or 1). 
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.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Decimate filter. 
Accepts input of following types:
 
TargetReduction (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 

PreserveTopology (PreserveTopology) 
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 
Accepts boolean values (0 or 1). 
FeatureAngle (FeatureAngle) 
The value of this 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. 
15.0 

BoundaryVertexDeletion (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. 
1 
Accepts boolean values (0 or 1). 
Delaunay 2D
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. 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. The 2D Delaunay triangulation is defined as the triangulation that satisfies the Delaunay criterion for ndimensional 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. 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 xy plane, and the z coordinate is ignored (although carried through to the output). You can use the option ProjectionPlaneMode in order to compute the bestfitting 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. 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. Warning: 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. 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.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input dataset to the Delaunay 2D filter. 
Accepts input of following types:
 
ProjectionPlaneMode (ProjectionPlaneMode) 
This property determines type of projection plane to use in performing the triangulation. 
0 
The value(s) is an enumeration of the following:

Alpha (Alpha) 
The value of this property controls the output of this filter. For a nonzero alpha value, only edges or triangles contained within a sphere centered at mesh vertices will be output. Otherwise, only triangles will be output. 
0.0 

Tolerance (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. 
0.00001 

Offset (Offset) 
This property is a multiplier to control the size of the initial, bounding Delaunay triangulation. 
1.0 

BoundingTriangulation (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. 
0 
Accepts boolean values (0 or 1). 
Delaunay 3D
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 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 an unstructured grid dataset. Usually the output is a tetrahedral mesh, but if a nonzero alpha distance value is specified (called the "alpha" value), then only tetrahedra, triangles, edges, and vertices lying within the alpha radius are output. In other words, nonzero alpha values may result in arbitrary combinations of tetrahedra, triangles, lines, and vertices. (The notion of alpha value is derived from Edelsbrunner's work on "alpha shapes".) The 3D Delaunay triangulation is defined as the triangulation that satisfies the Delaunay criterion for ndimensional simplexes (in this case n=3 and the simplexes are tetrahedra). This criterion states that a circumsphere of each simplex in a triangulation contains only the n+1 defining points of the simplex. (See text for more information.) While in two dimensions this translates into an "optimal" triangulation, this is not true in 3D, since a measurement for optimality in 3D is not agreed on. 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. (If you wish to create 2D triangulations see Delaunay2D.) The output is an unstructured grid. The Delaunay triangulation can be numerically sensitive. 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. Warning: 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 four points will form a tetrahedron; other degenerate points (relative to this initial tetrahedron) will not break it. Points that are coincident (or nearly so) may be discarded by the algorithm. This is because the Delaunay triangulation requires unique input points. You can control the definition of coincidence with the "Tolerance" instance variable. The output of the Delaunay triangulation is supposedly a convex hull. In certain cases this implementation may not generate the convex hull. This behavior can be controlled by the Offset instance variable. Offset is a multiplier used to control the size of the initial triangulation. The larger the offset value, the more likely you will generate a convex hull; and the more likely you are to see numerical problems. The implementation of this algorithm varies from the 2D Delaunay algorithm (i.e., Delaunay2D) in an important way. When points are injected into the triangulation, the search for the enclosing tetrahedron is quite different. In the 3D case, the closest previously inserted point point is found, and then the connected tetrahedra are searched to find the containing one. (In 2D, a "walk" towards the enclosing triangle is performed.) If the triangulation is Delaunay, then an enclosing tetrahedron will be found. However, in degenerate cases an enclosing tetrahedron may not be found and the point will be rejected.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input dataset to the Delaunay 3D filter. 
Accepts input of following types:
 
Alpha (Alpha) 
This property specifies the alpha (or distance) value to control the output of this filter. For a nonzero 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 

Tolerance (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 

Offset (Offset) 
This property specifies a multiplier to control the size of the initial, bounding Delaunay triangulation. 
2.5 

BoundingTriangulation (BoundingTriangulation) 
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 
Accepts boolean values (0 or 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.<p> This filter computes the min, max, mean, raw moments M2 through M4, standard deviation, skewness, and kurtosis for each array you select.<p> 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.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
The input to the filter. Arrays from this dataset will be used for computing statistics and/or assessed by a statistical model. 
Accepts input of following types:
The dataset much contain a field array ()  
ModelInput (ModelInput) 
A previouslycalculated model with which to assess a separate dataset. This input is optional. 
Accepts input of following types:
 
AttributeMode (AttributeMode) 
Specify which type of field data the arrays will be drawn from. 
0 
The value must be field array name. 
Variables of Interest (SelectArrays) 
Choose arrays whose entries will be used to form observations for statistical analysis. 

Task (Task) 
Specify the task to be performed: modeling and/or assessment. <ol> <li> "Detailed model of input data," creates a set of output tables containing a calculated statistical model of the <b>entire</b> input dataset;</li> <li> "Model a subset of the data," creates an output table (or tables) summarizing a <b>randomlychosen subset</b> of the input dataset;</li> <li> "Assess the data with a model," adds attributes to the first input dataset using a model provided on the second input port; and</li> <li> "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.</li> </ol> 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 <i>Training fraction</i> setting will be ignored for tasks 1 and 3. 
3 
The value(s) is an enumeration of the following:

TrainingFraction (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 

Deviations should be (SignedDeviations) 
Should the assessed values be signed deviations or unsigned? 
0 
The value(s) is an enumeration of the following:

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. 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.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input dataset to the Elevation filter. 
Accepts input of following types:
 
ScalarRange (ScalarRange) 
This property determines the range into which scalars will be mapped. 
0 1 

Low Point (LowPoint) 
This property defines one end of the direction vector (small scalar values). 
0 0 0 
The value must lie within the bounding box of the dataset. It will default to the min in each dimension. 
High Point (HighPoint) 
This property defines the other end of the direction vector (large scalar values). 
0 0 1 
The value must lie within the bounding box of the dataset. It will default to the max in each dimension.

Extract AMR Blocks
This filter extracts a list of datasets from hierarchical datasets.This filter extracts a list of datasets from hierarchical datasets.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Extract Datasets filter. 
Accepts input of following types:
 
SelectedDataSets (SelectedDataSets) 
This property provides a list of datasets to extract. 

Extract Attributes
Extract attribute data as a table.This is a filter that produces a vtkTable from the chosen attribute in the input dataobject. This filter can accept composite datasets. If the input is a composite dataset, the output is a multiblock with vtkTable leaves.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input of the filter. 
Accepts input of following types:
 
FieldAssociation (FieldAssociation) 
Select the attribute data to pass. 
0 
The value(s) is an enumeration of the following:

AddMetaData (AddMetaData) 
It is possible for this filter to add additional metadata to the field data such as point coordinates (when point attributes are selected and input is pointset) or structured coordinates etc. To enable this addition of extra information, turn this flag on. Off by default. 
0 
Accepts boolean values (0 or 1). 
Extract Block
This filter extracts a range of blocks from a multiblock dataset.This filter extracts a range of groups from a multiblock dataset
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Extract Group filter. 
Accepts input of following types:
 
BlockIndices (BlockIndices) 
This property lists the ids of the blocks to extract from the input multiblock dataset. 

PruneOutput (PruneOutput) 
When set, the output mutliblock dataset will be pruned to remove empty nodes. On by default. 
1 
Accepts boolean values (0 or 1). 
MaintainStructure (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 nonnull child block, then that node is removed. To preserve these parent nodes, set this flag to true. 
0 
Accepts boolean values (0 or 1). 
Extract CTH Parts
Create a surface from a CTH volume fraction.Extract CTH Parts is a specialized filter for visualizing the data from a CTH simulation. It first converts the selected cellcentered arrays to pointcentered 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.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Extract CTH Parts filter. 
Accepts input of following types:
The dataset much contain a field array (cell) with 1 component(s).  
Clip Type (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 can be one of the following:
 
Double Volume Arrays (AddDoubleVolumeArrayName) 
This property specifies the name(s) of the volume fraction array(s) for generating parts. 
An array of scalars is required.  
Float Volume Arrays (AddFloatVolumeArrayName) 
This property specifies the name(s) of the volume fraction array(s) for generating parts. 
An array of scalars is required.  
Unsigned Character Volume Arrays (AddUnsignedCharVolumeArrayName) 
This property specifies the name(s) of the volume fraction array(s) for generating parts. 
An array of scalars is required.  
Volume Fraction Value (VolumeFractionSurfaceValue) 
The value of this property is the volume fraction value for the surface. 
0.1 

Extract Cells By Region
This filter extracts cells that are inside/outside a region or at a region boundary. 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. 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).
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Slice filter. 
Accepts input of following types:
 
Intersect With (ImplicitFunction) 
This property sets the region used to extract cells. 
The value can be one of the following:
 
InputBounds (InputBounds)  
Extraction Side (ExtractInside) 
This parameter controls whether to extract cells that are inside or outside the region. 
1 
The value(s) is an enumeration of the following:

Extract only intersected (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 
Accepts boolean values (0 or 1). 
Extract intersected (Extract intersected) 
This parameter controls whether to extract cells that are on the boundary of the region. 
0 
Accepts boolean values (0 or 1). 
Extract Edges
Extract edges of 2D and 3D cells as lines.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.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Extract Edges filter. 
Accepts input of following types:

Extract Generic Dataset Surface
Extract geometry from a higherorder dataset Extract geometry from a higherorder dataset.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Set the input to the Generic Geometry Filter. 
Accepts input of following types:
 
PassThroughCellIds (PassThroughCellIds) 
Select whether to forward original ids. 
1 
Accepts boolean values (0 or 1). 
Extract Level
This filter extracts a range of groups from a hierarchical dataset.This filter extracts a range of levels from a hierarchical dataset
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Extract Group filter. 
Accepts input of following types:
 
Levels (Levels) 
This property lists the levels to extract from the input hierarchical dataset. 

Extract Selection
Extract different type of selections.This filter extracts a set of cells/points given a selection. The selection can be obtained from a rubberband selection (either cell, visible or in a frustum) or threshold selection and passed to the filter or specified by providing an ID list.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input from which the selection is extracted. 
Accepts input of following types:
 
Selection (Selection) 
The input that provides the selection object. 
Accepts input of following types:
 
PreserveTopology (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 
Accepts boolean values (0 or 1). 
ShowBounds (ShowBounds) 
For frustum selection, if this property is set to 1 the output is the outline of the frustum instead of the contents of the input that lie within the frustum. 
0 
Accepts boolean values (0 or 1). 
Extract Selection (internal)
This filter extracts a given set of cells or points given a selection. The selection can be obtained from a rubberband selection (either point, cell, visible or in a frustum) and passed to the filter or specified by providing an ID list. This is an internal filter, use "ExtractSelection" instead.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
The input from which the selection is extracted. 
Accepts input of following types:
 
Selection (Selection) 
The input that provides the selection object. 
Accepts input of following types:

Extract Subset
Extract a subgrid from a structured grid with the option of setting subsample strides.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.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Extract Grid filter. 
Accepts input of following types:
 
VOI (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 
The value(s) must lie within the structuredextents of the input dataset. 
SampleRateI (SampleRateI) 
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. 
1 

SampleRateJ (SampleRateJ) 
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 

SampleRateK (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 

IncludeBoundary (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 
Accepts boolean values (0 or 1). 
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.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Extract Surface filter. 
Accepts input of following types:
 
PieceInvariant (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 
Accepts boolean values (0 or 1). 
NonlinearSubdivisionLevel (NonlinearSubdivisionLevel) 
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 

FOF/SOD Halo Finder
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input of the filter. 
Accepts input of following types:
 
rL (physical box side length) (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). 
100 

overlap (shared point/ghost cell gap distance) (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 

np (number of seeded particles in one dimension, i.e., total particles = np^3) (NP) 
Number of seeded particles in one dimension. Therefore, total simulation particles is np^3 (cubed). 
256 

bb (linking length) (BB) 
Linking length measured in units of interparticle spacing and is dimensionless. Used to link particles into halos for the friendsoffriends (FOF) algorithm. 
0.20 

pmin (minimum particle threshold for an FOF halo) (PMin) 
Minimum number of particles (threshold) needed before a group is called a friendsoffriends (FOF) halo. 
100 

Copy FOF halo catalog to original particles (CopyHaloDataToParticles) 
If checked, the friendsoffriends (FOF) halo catalog information will be copied to the original particles as well. 
0 
Accepts boolean values (0 or 1). 
Compute the most bound particle (ComputeMostBoundParticle) 
If checked, the most bound particle for an FOF halo will be calculated. WARNING: This can be very slow. 
0 
Accepts boolean values (0 or 1). 
Compute the most connected particle (ComputeMostConnectedParticle) 
If checked, the most connected particle for an FOF halo will be calculated. WARNING: This can be very slow. 
0 
Accepts boolean values (0 or 1). 
Compute spherical overdensity (SOD) halos (ComputeSOD) 
If checked, spherical overdensity (SOD) halos will be calculated in addition to friendsoffriends (FOF) halos. 
0 
Accepts boolean values (0 or 1). 
initial SOD center (SODCenterType) 
The initial friendsoffriends (FOF) center used for calculating a spherical overdensity (SOD) halo. WARNING: Using MBP or MCP can be very slow. 
0 
The value(s) is an enumeration of the following:

rho_c (RhoC) 
rho_c (critical density) for SOD halo finding. 
2.77536627e11 

initial SOD mass (SODMass) 
The initial SOD mass. 
1.0e14 

minimum radius factor (MinRadiusFactor) 
Minimum radius factor for SOD finding. 
0.5 

maximum radius factor (MaxRadiusFactor) 
Maximum radius factor for SOD finding. 
2.0 

number of bins (SODBins) 
Number of bins for SOD finding. 
20 

minimum FOF size (MinFOFSize) 
Minimum FOF halo size to calculate an SOD halo. 
1000 

minimum FOF mass (MinFOFMass) 
Minimum FOF mass to calculate an SOD halo. 
5.0e12 

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.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Feature Edges filter. 
Accepts input of following types:
 
BoundaryEdges (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 
Accepts boolean values (0 or 1). 
FeatureEdges (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 
Accepts boolean values (0 or 1). 
NonManifold Edges (NonManifoldEdges) 
If the value of this property is set to 1, nonmanifold ediges will be extracted. Nonmanifold edges are defined as edges that are use by three or more polygons. 
1 
Accepts boolean values (0 or 1). 
ManifoldEdges (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 
Accepts boolean values (0 or 1). 
Coloring (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 
Accepts boolean values (0 or 1). 
FeatureAngle (FeatureAngle) 
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.) 
30.0 

FlattenFilter
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Set the input to the Flatten Filter. 
Accepts input of following types:

Gaussian Resampling
Splat points into a volume with an elliptical, Gaussian distribution.vtkGaussianSplatter is a filter that injects input points into a structured points (volume) dataset. As each point is injected, it "splats" or distributes values to nearby voxels. Data is distributed using an elliptical, Gaussian distribution function. The distribution function is modified using scalar values (expands distribution) or normals (creates ellipsoidal distribution rather than spherical). Warning: results may be incorrect in parallel as points can't splat into other processor's cells.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the filter. 
Accepts input of following types:
The dataset much contain a field array (point) with 1 component(s).  
Resample Field (SelectInputScalars) 
Choose a scalar array to splat into the output cells. If ignore arrays is chosen, point density will be counted instead. 
An array of scalars is required.The value must be field array name.  
Resampling Grid (SampleDimensions) 
Set / get the dimensions of the sampling structured point set. Higher values produce better results but are much slower. 
50 50 50 

Extent to Resample (ModelBounds) 
Set / get the (xmin,xmax, ymin,ymax, zmin,zmax) bounding box in which the sampling is performed. If any of the (min,max) bounds values are min >= max, then the bounds will be computed automatically from the input data. Otherwise, the userspecified bounds will be used. 
0.0 0.0 0.0 0.0 0.0 0.0 

Gaussian Splat Radius (Radius) 
Set / get the radius of propagation of the splat. This value is expressed as a percentage of the length of the longest side of the sampling volume. Smaller numbers greatly reduce execution time. 
0.1 

Gaussian Exponent Factor (ExponentFactor) 
Set / get the sharpness of decay of the splats. This is the exponent constant in the Gaussian equation. Normally this is a negative value. 
5.0 

Scale Splats (ScalarWarping) 
Turn on/off the scaling of splats by scalar value. 
1 
Accepts boolean values (0 or 1). 
Scale Factor (ScaleFactor) 
Multiply Gaussian splat distribution by this value. If ScalarWarping is on, then the Scalar value will be multiplied by the ScaleFactor times the Gaussian function. 
1.0 

Elliptical Splats (NormalWarping) 
Turn on/off the generation of elliptical splats. If normal warping is on, then the input normals affect the distribution of the splat. This boolean is used in combination with the Eccentricity ivar. 
1 
Accepts boolean values (0 or 1). 
Ellipitical Eccentricity (Eccentricity) 
Control the shape of elliptical splatting. Eccentricity is the ratio of the major axis (aligned along normal) to the minor (axes) aligned along other two axes. So Eccentricity gt 1 creates needles with the long axis in the direction of the normal; Eccentricity lt 1 creates pancakes perpendicular to the normal vector. 
2.5 

Fill Volume Boundary (Capping) 
Turn on/off the capping of the outer boundary of the volume to a specified cap value. This can be used to close surfaces (after isosurfacing) and create other effects. 
1 
Accepts boolean values (0 or 1). 
Fill Value (CapValue) 
Specify the cap value to use. (This instance variable only has effect if the ivar Capping is on.) 
0.0 

Splat Accumulation Mode (Accumulation Mode) 
Specify the scalar accumulation mode. This mode expresses how scalar values are combined when splats are overlapped. The Max mode acts like a set union operation and is the most commonly used; the Min mode acts like a set intersection, and the sum is just weird. 
1 
The value(s) is an enumeration of the following:

Empty Cell Value (NullValue) 
Set the Null value for output points not receiving a contribution from the input points. (This is the initial value of the voxel samples.) 
0.0 

Generate Ids
Generate scalars from point and cell ids. 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.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Cell Data to Point Data filter. 
Accepts input of following types:
 
ArrayName (ArrayName) 
The name of the array that will contain ids. 
Ids 

Generate Quadrature Points
Create a point set with data at quadrature points. "Create a point set with data at quadrature points."
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input of the filter. 
Accepts input of following types:
The dataset much contain a field array (cell)  
Quadrature Scheme Def (QuadratureSchemeDefinition) 
Specifies the offset array from which we generate quadrature points. 
An array of scalars is required. 
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.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input of the filter. 
Accepts input of following types:

Generate Surface Normals
This filter will produce surface normals used for smooth shading. Splitting is used to avoid smoothing across feature edges.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.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Normals Generation filter. 
Accepts input of following types:
 
FeatureAngle (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 

Splitting (Splitting) 
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 
Accepts boolean values (0 or 1). 
Consistency (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 
Accepts boolean values (0 or 1). 
FlipNormals (FlipNormals) 
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 frontfacing polygons to backfacing 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. 
0 
Accepts boolean values (0 or 1). 
NonManifold Traversal (NonManifoldTraversal) 
Turn on/off traversal across nonmanifold edges. Not traversing nonmanifold edges will prevent problems where the consistency of polygonal ordering is corrupted due to topological loops. 
1 
Accepts boolean values (0 or 1). 
ComputeCellNormals (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. 
0 
Accepts boolean values (0 or 1). 
PieceInvariant (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 
Accepts boolean values (0 or 1). 
GeometryFilter
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Set the input to the Geoemtry Filter. 

UseStrips (UseStrips) 
Toggle whether to generate faces containing triangle strips. This should render faster and use less memory, but no cell data is copied. 
0 
Accepts boolean values (0 or 1). 
ForceStrips (ForceStrips) 
This makes UseStrips call Modified() after changing its setting to ensure that the filter's output is immediatley changed. 
0 
Accepts boolean values (0 or 1). 
UseOutline (UseOutline) 
Toggle whether to generate an outline or a surface. 
0 
Accepts boolean values (0 or 1). 
NonlinearSubdivisionLevel (NonlinearSubdivisionLevel) 
Nonlinear faces are approximated with flat polygons. This parameter controls how many times to subdivide nonlinear surface cells. Higher subdivisions generate closer approximations but take more memory and rendering time. Subdivision is recursive, so the number of output polygons can grow exponentially with this parameter. 
1 

PassThroughIds (PassThroughIds) 
If on, the output polygonal dataset will have a celldata array that holds the cell index of the original 3D cell that produced each output cell. This is useful for cell picking. 
1 
Accepts boolean values (0 or 1). 
PassThroughPointIds (PassThroughPointIds) 
If on, the output polygonal dataset will have a pointdata array that holds the point index of the original 3D vertex that produced each output vertex. This is useful for picking. 
1 
Accepts boolean values (0 or 1). 
MakeOutlineOfInput (MakeOutlineOfInput) 
Causes filter to try to make geometry of input to the algorithm on its input. 
0 
Accepts boolean values (0 or 1). 
Glyph
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 (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 pointcentered scalars and vectors. The Glyph filter operates on any type of data set. Its output is polygonal. This filter is available on the Toolbar.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Glyph filter. This is the dataset to which the glyphs will be applied. 
Accepts input of following types:
The dataset much contain a field array (point) with 1 component(s). The dataset much contain a field array (point) with 3 component(s).  
Scalars (SelectInputScalars) 
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.) 
An array of scalars is required.  
Vectors (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. 
Glyph Type (Source) 
This property determines which type of glyph will be placed at the points in the input dataset. 
Accepts input of following types:
 
GlyphTransform (GlyphTransform) 
The values in this property allow you to specify the transform (translation, rotation, and scaling) to apply to the glyph source. 
The value can be one of the following:
 
Orient (SetOrient) 
If this property is set to 1, the glyphs will be oriented based on the selected vector array. 
1 
Accepts boolean values (0 or 1). 
Scale Mode (SetScaleMode) 
The value of this property specifies how/if the glyphs should be scaled based on the pointcentered scalars/vectors in the input dataset. 
1 
The value(s) is an enumeration of the following:

SetScaleFactor (SetScaleFactor) 
The value of this property will be used as a multiplier for scaling the glyphs before adding them to the output. 
1.0 
The value must lie within the range of the selected data array.The value must lie within the range of the selected data array. The value must be less than the largest dimension of the dataset multiplied by a scale factor of 0.1. 
Maximum Number of Points (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 

Mask Points (UseMaskPoints) 
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.) 
1 
Accepts boolean values (0 or 1). 
RandomMode (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 
Accepts boolean values (0 or 1). 
KeepRandomPoints (KeepRandomPoints) 
If the value of this property is 1 and RandomMode is 1, then the randomly chosen points to glyph are saved and reused for other timesteps. This is only useful if the coordinates are the same and in the same order between timesteps. 
0 
Accepts boolean values (0 or 1). 
Glyph With Custom Source
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 Glyph filter generates a glyph at each point in the input dataset. The glyphs can be oriented and scaled by the input pointcentered scalars and vectors. The Glyph filter operates on any type of data set. Its output is polygonal. This filter is available on the Toolbar.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Glyph filter. This is the dataset to which the glyphs will be applied. 
Accepts input of following types:
The dataset much contain a field array (point) with 1 component(s). The dataset much contain a field array (point) with 3 component(s).  
Glyph Type (Source) 
This property determines which type of glyph will be placed at the points in the input dataset. 
Accepts input of following types:
 
Scalars (SelectInputScalars) 
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.) 
An array of scalars is required.  
Vectors (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. 
Orient (SetOrient) 
If this property is set to 1, the glyphs will be oriented based on the selected vector array. 
1 
Accepts boolean values (0 or 1). 
Scale Mode (SetScaleMode) 
The value of this property specifies how/if the glyphs should be scaled based on the pointcentered scalars/vectors in the input dataset. 
1 
The value(s) is an enumeration of the following:

SetScaleFactor (SetScaleFactor) 
The value of this property will be used as a multiplier for scaling the glyphs before adding them to the output. 
1.0 
The value must lie within the range of the selected data array.The value must lie within the range of the selected data array. The value must be less than the largest dimension of the dataset multiplied by a scale factor of 0.1. 
Maximum Number of Points (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 

Mask Points (UseMaskPoints) 
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.) 
1 
Accepts boolean values (0 or 1). 
RandomMode (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 
Accepts boolean values (0 or 1). 
KeepRandomPoints (KeepRandomPoints) 
If the value of this property is 1 and RandomMode is 1, then the randomly chosen points to glyph are saved and reused for other timesteps. This is only useful if the coordinates are the same and in the same order between timesteps. 
0 
Accepts boolean values (0 or 1). 
Gradient
This filter computes gradient vectors for an image/volume.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.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Gradient filter. 
Accepts input of following types:
The dataset much contain a field array (point) with 1 component(s).  
SelectInputScalars (SelectInputScalars) 
This property lists the name of the array from which to compute the gradient. 
An array of scalars is required.  
Dimensionality (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(s) is an enumeration of the following:

Gradient Magnitude
Compute the magnitude of the gradient vectors for an image/volume.The Gradient Magnitude filter computes the magnitude of the gradient vector at each point in an image or volume. This filter operates on uniform rectilinear (image) data and produces image data output.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Gradient Magnitude filter. 
Accepts input of following types:
The dataset much contain a field array (point) with 1 component(s).  
Dimensionality (Dimensionality) 
This property indicates whether to compute the gradient magnitude in two or three dimensions. If computing the gradient magnitude in 2D, the gradients in X and Y are used for computing the gradient magnitude. 
3 
The value(s) is an enumeration of the following:

Gradient Of Unstructured DataSet
Estimate the gradient for each point or cell in any type of dataset. 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.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Gradient (Unstructured) filter. 
Accepts input of following types:
The dataset much contain a field array ()  
Scalar Array (SelectInputScalars) 
This property lists the name of the scalar array from which to compute the gradient. 
An array of scalars is required.The value must be field array name.  
ResultArrayName (ResultArrayName) 
This property provides a name for the output array containing the gradient vectors. 
Gradients 

FasterApproximation (FasterApproximation) 
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 
Accepts boolean values (0 or 1). 
ComputeVorticity (ComputeVorticity) 
When this flag is on, the gradient filter will compute the vorticity/curl of a 3 component array. 
0 
Accepts boolean values (0 or 1). 
VorticityArrayName (VorticityArrayName) 
This property provides a name for the output array containing the vorticity vector. 
Vorticity 

ComputeQCriterion (ComputeQCriterion) 
When this flag is on, the gradient filter will compute the Qcriterion of a 3 component array. 
0 
Accepts boolean values (0 or 1). 
QCriterionArrayName (QCriterionArrayName) 
This property provides a name for the output array containing Q criterion. 
Qcriterion 

Grid Connectivity
Mass properties of connected fragments for unstructured grids.This filter works on multiblock unstructured grid inputs and also works in parallel. It Ignores any cells with a cell data Status value of 0. It performs connectivity to distict fragments separately. It then integrates attributes of the fragments.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input of the filter. 
Accepts input of following types:

Group Datasets
Group data sets. Groups multiple datasets to create a multiblock dataset
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property indicates the the inputs to the Group Datasets filter. 
Accepts input of following types:

Histogram
Extract a histogram from field data.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Histogram filter. 
Accepts input of following types:
The dataset much contain a field array ()  
SelectInputArray (SelectInputArray) 
This property indicates the name of the array from which to compute the histogram. 
An array of scalars is required.The value must be field array name.  
BinCount (BinCount) 
The value of this property specifies the number of bins for the histogram. 
10 

Component (Component) 
The value of this property specifies the array component from which the histogram should be computed. 
0 

CalculateAverages (CalculateAverages) 
This option controls whether the algorithm calculates averages of variables other than the primary variable that fall into each bin. 
1 
Accepts boolean values (0 or 1). 
UseCustomBinRanges (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 
Accepts boolean values (0 or 1). 
CustomBinRanges (CustomBinRanges) 
Set custom bin ranges to use. These are used only when UseCustomBinRanges is set to true. 
0.0 100.0 
The value must lie within the range of the selected data array. 
Image Data To AMR
Converts certain images to AMR.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Cell Data to Point Data filter. 
Accepts input of following types:
 
Number of levels (NumberOfLevels) 
This property specifies the number of levels in the amr data structure. 
2 

Maximum Number of Blocks (MaximumNumberOfLevels) 
This property specifies the maximum number of blocks in the output amr data structure. 
100 

Refinement Ratio (RefinementRatio) 
This property specifies the refinement ratio between levels. 
2 

Image Data To Uniform Grid
Create a uniform grid from an image data by specified blanking arrays. Create a vtkUniformGrid from a vtkImageData by passing in arrays to be used for point and/or cell blanking. By default, values of 0 in the specified array will result in a point or cell being blanked. Use Reverse to switch this.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Accepts input of following types:
The dataset much contain a field array () with 1 component(s).  
SelectInputScalars (SelectInputScalars) 
Specify the array to use for blanking. 
An array of scalars is required.  
Reverse (Reverse) 
Reverse the array value to whether or not a point or cell is blanked. 
0 
Accepts boolean values (0 or 1). 
Image Data to Point Set
The Image Data to Point Set filter takes an image data (uniform rectilinear grid) object and outputs an equivalent structured grid (which as a type of point set). This brings the data to a broader category of data storage but only adds a small amount of overhead. This filter can be helpful in applying filters that expect or manipulate point coordinates.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Accepts input of following types:

Image Shrink
Reduce the size of an image/volume by subsampling.The Image Shrink filter reduces the size of an image/volume dataset by subsampling it (i.e., extracting every nth pixel/voxel in integer multiples). The sbsampling rate can be set separately for each dimension of the image/volume.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Image Shrink filter. 
Accepts input of following types:
 
ShrinkFactors (ShrinkFactors) 
The value of this property indicates the amount by which to shrink along each axis. 
1 1 1 

Averaging (Averaging) 
If the value of this property is 1, an average of neighborhood scalar values will be used as the output scalar value for each output point. If its value is 0, only subsampling will be performed, and the original scalar values at the points will be retained. 
1 
Accepts boolean values (0 or 1). 
Integrate Variables
This filter integrates cell and point attributes. The Integrate Attributes filter integrates point and cell data over lines and surfaces. It also computes length of lines, area of surface, or volume.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Integrate Attributes filter. 
Accepts input of following types:

Interpolate to Quadrature Points
Create scalar/vector data arrays interpolated to quadrature points. "Create scalar/vector data arrays interpolated to quadrature points."
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input of the filter. 
Accepts input of following types:
The dataset much contain a field array (cell)  
Quadrature Scheme Def (QuadratureSchemeDefinition) 
Specifies the offset array from which we interpolate values to quadrature points. 
An array of scalars is required. 
Intersect Fragments
The Intersect Fragments filter perform geometric intersections on sets of fragments. The Intersect Fragments filter perform geometric intersections on sets of fragments. The filter takes two inputs, the first containing fragment geometry and the second containing fragment centers. The filter has two outputs. The first is geometry that results from the intersection. The second is a set of points that is an approximation of the center of where each fragment has been intersected.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This input must contian fragment geometry. 
Accepts input of following types:
 
Source (Source) 
This input must contian fragment centers. 
Accepts input of following types:
 
Slice Type (CutFunction) 
This property sets the type of intersecting geometry, and associated parameters. 
The value can be one of the following:

Iso Volume
This filter extracts cells by clipping cells that have point scalars not in the specified range. This filter clip away the cells using lower and upper thresholds.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Threshold filter. 
Accepts input of following types:
The dataset much contain a field array () with 1 component(s).  
Input Scalars (SelectInputScalars) 
The value of this property contains the name of the scalar array from which to perform thresholding. 
An array of scalars is required.The value must be field array name.  
Threshold Range (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. 
K Means
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.<p> 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.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
The input to the filter. Arrays from this dataset will be used for computing statistics and/or assessed by a statistical model. 
Accepts input of following types:
The dataset much contain a field array ()  
ModelInput (ModelInput) 
A previouslycalculated model with which to assess a separate dataset. This input is optional. 
Accepts input of following types:
 
AttributeMode (AttributeMode) 
Specify which type of field data the arrays will be drawn from. 
0 
The value must be field array name. 
Variables of Interest (SelectArrays) 
Choose arrays whose entries will be used to form observations for statistical analysis. 

Task (Task) 
Specify the task to be performed: modeling and/or assessment. <ol> <li> "Detailed model of input data," creates a set of output tables containing a calculated statistical model of the <b>entire</b> input dataset;</li> <li> "Model a subset of the data," creates an output table (or tables) summarizing a <b>randomlychosen subset</b> of the input dataset;</li> <li> "Assess the data with a model," adds attributes to the first input dataset using a model provided on the second input port; and</li> <li> "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.</li> </ol> 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 <i>Training fraction</i> setting will be ignored for tasks 1 and 3. 
3 
The value(s) is an enumeration of the following:

TrainingFraction (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 

k (K) 
Specify the number of clusters. 
5 

Max Iterations (MaxNumIterations) 
Specify the maximum number of iterations in which cluster centers are moved before the algorithm terminates. 
50 

Tolerance (Tolerance) 
Specify the relative tolerance that will cause early termination. 
0.01 

Level Scalars(NonOverlapping AMR)
The Level Scalars filter uses colors to show levels of a hierarchical dataset.The Level Scalars filter uses colors to show levels of a hierarchical dataset.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Level Scalars filter. 
Accepts input of following types:

Level Scalars(Overlapping AMR)
The Level Scalars filter uses colors to show levels of a hierarchical dataset.The Level Scalars filter uses colors to show levels of a hierarchical dataset.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Level Scalars filter. 
Accepts input of following types:

Linear Extrusion
This filter creates a swept surface defined by translating the input along a vector.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.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Linear Extrusion filter. 
Accepts input of following types:
 
ScaleFactor (ScaleFactor) 
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.) 
1.0 

Vector (Vector) 
The value of this property indicates the X, Y, and Z components of the vector along which to sweep the input dataset. 
0 0 1 

Capping (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. 
1 
Accepts boolean values (0 or 1). 
PieceInvariant (PieceInvariant) 
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. 
0 
Accepts boolean values (0 or 1). 
Loop Subdivision
This filter iteratively divides each triangle into four triangles. New points are placed so the output surface is smooth. 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.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Loop Subdivision filter. 
Accepts input of following types:
 
Number of Subdivisions (NumberOfSubdivisions) 
Set the number of subdivision iterations to perform. Each subdivision divides single triangles into four new triangles. 
1 

MPIMoveData
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Set the input to the MPI Move Data filter. 

MoveMode (MoveMode) 
Specify how the data is to be redistributed. 
0 
The value(s) is an enumeration of the following:

OutputDataType (OutputDataType) 
Specify the type of the dataset. 
none 
The value(s) is an enumeration of the following:

Mask Points
Reduce the number of points. This filter is often used before glyphing. Generating vertices is an option.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.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Mask Points filter. 
Accepts input of following types:
 
OnRatio (OnRatio) 
The value of this property specifies that every OnStrideth points will be retained in the output when not using Random (the skip or stride size for point ids). (For example, if the on ratio is 3, then the output will contain every 3rd point, up to the the maximum number of points.) 
2 

Maximum Number of Points (MaximumNumberOfPoints) 
The value of this property indicates the maximum number of points in the output dataset. 
5000 

Proportionally Distribute Maximum Number Of Points (ProportionalMaximumNumberOfPoints) 
When this is off, the maximum number of points is taken per processor when running in parallel (total number of points = number of processors * maximum number of points). When this is on, the maximum number of points is proportionally distributed across processors depending on the number of points per processor ("total number of points" is the same as "maximum number of points" maximum number of points per processor = number of points on a processor
). 
0 
Accepts boolean values (0 or 1). 
Offset (Offset) 
The value of this property indicates the starting point id in the ordered list of input points from which to start masking. 
0 

Random Sampling (RandomMode) 
If the value of this property is set to true, then the points in the output will be randomly selected from the input in various ways set by Random Mode; otherwise this filter will subsample point ids regularly. 
0 
Accepts boolean values (0 or 1). 
Random Sampling Mode (RandomModeType) 
Randomized Id Strides picks points with random id increments starting at Offset (the output probably isn't a statistically random sample). Random Sampling generates a statistically random sample of the input, ignoring Offset (fast  O(sample size)). Spatially Stratified Random Sampling is a variant of random sampling that splits the points into equal sized spatial strata before randomly sampling (slow  O(N log N)). 
0 
The value(s) is an enumeration of the following:

GenerateVertices (GenerateVertices) 
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 
Accepts boolean values (0 or 1). 
SingleVertexPerCell (SingleVertexPerCell) 
Tell filter to only generate one vertex per cell instead of multiple vertices in one cell. 
0 
Accepts boolean values (0 or 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 fraction (or normalized amount of material) is higher than a given threshold. As these voxels are identified surfaces enclosing adjacent voxels above the threshold are generated. The resulting volume and its surface are what we call a fragment. The filter has the ability to compute various volumetric attributes such as fragment volume, mass, center of mass as well as volume and mass weighted averages for any of the fields present. Any field selected for such computation will be also be coppied into the fragment surface's point data for visualization. The filter also has the ability to generate Oriented Bounding Boxes (OBB) for each fragment. The data generated by the filter is organized in three outputs. The "geometry" output, containing the fragment surfaces. The "statistics" output, containing a point set of the centers of mass. The "obb representaion" output, containing OBB representations (poly data). All computed attributes are coppied into the statistics and geometry output. The obb representation output is used for validation and debugging puproses and is turned off by default. To measure the size of craters, the filter can invert a volume fraction and clip the volume fraction with a sphere and/or a plane.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Input to the filter can be a hierarchical box data set containing image data or a multiblock of rectilinear grids. 
Accepts input of following types:
The dataset much contain a field array (cell)  
Select Material Fraction Arrays (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. 
An array of scalars is required.  
Material Fraction Threshold (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 

InvertVolumeFraction (InvertVolumeFraction) 
Inverting the volume fraction generates the negative of the material. It is useful for analyzing craters. 
0 
Accepts boolean values (0 or 1). 
Clip Type (ClipFunction) 
This property sets the type of clip geometry, and associated parameters. 
The value can be one of the following:
 
Select Mass Arrays (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. 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 volume weighted average over: (SelectVolumeWtdAvgArray) 
Specifies the arrays from which to volume weighted average. 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. 

Compute mass weighted average over: (SelectMassWtdAvgArray) 
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. 

ComputeOBB (ComputeOBB) 
Compute Object Oriented Bounding boxes (OBB). When active the result of 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 
Accepts boolean values (0 or 1). 
WriteGeometryOutput (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 
Accepts boolean values (0 or 1). 
WriteStatisticsOutput (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 
Accepts boolean values (0 or 1). 
OutputBaseName (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. 

Median
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 highintensity, lowprobability noise (shot noise).
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Median filter. 
Accepts input of following types:
The dataset much contain a field array (point) with 1 component(s).  
SelectInputScalars (SelectInputScalars) 
The value of this property lists the name of the scalar array to use in computing the median. 
An array of scalars is required.  
KernelSize (KernelSize) 
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 

Merge Blocks
Appends vtkCompositeDataSet leaves into a single vtkUnstructuredGrid vtkCompositeDataToUnstructuredGridFilter appends all vtkDataSet leaves of the input composite dataset to a single unstructure grid. The subtree to be combined can be choosen using the SubTreeCompositeIndex. If the SubTreeCompositeIndex is a leaf node, then no appending is required.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Set the input composite dataset. 
Accepts input of following types:
 
SubTreeCompositeIndex (SubTreeCompositeIndex) 
Select the index of the subtree to be appended. For now, this property is internal. 
0 

Merge Points (MergePoints) 
1 
Accepts boolean values (0 or 1). 
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.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Mesh Quality filter. 
Accepts input of following types:
 
TriangleQualityMeasure (TriangleQualityMeasure) 
This property indicates which quality measure will be used to evaluate triangle quality. The radius ratio is the size of a circle circumscribed by a triangle's 3 vertices divided by the size of a circle tangent to a triangle's 3 edges. The edge ratio is the ratio of the longest edge length to the shortest edge length. 
2 
The value(s) is an enumeration of the following:

QuadQualityMeasure (QuadQualityMeasure) 
This property indicates which quality measure will be used to evaluate quadrilateral quality. 
0 
The value(s) is an enumeration of the following:

TetQualityMeasure (TetQualityMeasure) 
This property indicates which quality measure will be used to evaluate tetrahedral quality. The radius ratio is the size of a sphere circumscribed by a tetrahedron's 4 vertices divided by the size of a circle tangent to a tetrahedron's 4 faces. The edge ratio is the ratio of the longest edge length to the shortest edge length. The collapse ratio is the minimum ratio of height of a vertex above the triangle opposite it divided by the longest edge of the opposing triangle across all vertex/triangle pairs. 
2 
The value(s) is an enumeration of the following:

HexQualityMeasure (HexQualityMeasure) 
This property indicates which quality measure will be used to evaluate hexahedral quality. 
5 
The value(s) is an enumeration of the following:

MinMax
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Set the input to the Min Max filter. 
Accepts input of following types:
 
Operation (Operation) 
Select whether to perform a min, max, or sum operation on the data. 
MIN 
The value(s) can be one of the following:

Multicorrelative 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.<p> This filter computes the covariance matrix for all the arrays you select plus the mean of each array. The model is thus a multivariate Gaussian distribution with the mean vector and variances provided. Data is assessed using this model by computing the Mahalanobis distance for each input point. This distance will always be positive.<p> The learned model output format is rather dense and can be confusing, so it is discussed here. The first filter output is a multiblock dataset consisting of 2 tables: <ol> <li> Raw covariance data. <li> Covariance matrix and its Cholesky decomposition. </ol> The raw covariance table has 3 meaningful columns: 2 titled "Column1" and "Column2" whose entries generally refer to the N arrays you selected when preparing the filter and 1 column titled "Entries" that contains numeric values. The first row will always contain the number of observations in the statistical analysis. The next N rows contain the mean for each of the N arrays you selected. The remaining rows contain covariances of pairs of arrays.<p> The second table (covariance matrix and Cholesky decomposition) contains information derived from the raw covariance data of the first table. The first N rows of the first column contain the name of one array you selected for analysis. These rows are followed by a single entry labeled "Cholesky" for a total of N+1 rows. The second column, Mean contains the mean of each variable in the first N entries and the number of observations processed in the final (N+1) row.<p> 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 â€” hence the N+1 rows and the final entry of the column named "Column".
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
The input to the filter. Arrays from this dataset will be used for computing statistics and/or assessed by a statistical model. 
Accepts input of following types:
The dataset much contain a field array ()  
ModelInput (ModelInput) 
A previouslycalculated model with which to assess a separate dataset. This input is optional. 
Accepts input of following types:
 
AttributeMode (AttributeMode) 
Specify which type of field data the arrays will be drawn from. 
0 
The value must be field array name. 
Variables of Interest (SelectArrays) 
Choose arrays whose entries will be used to form observations for statistical analysis. 

Task (Task) 
Specify the task to be performed: modeling and/or assessment. <ol> <li> "Detailed model of input data," creates a set of output tables containing a calculated statistical model of the <b>entire</b> input dataset;</li> <li> "Model a subset of the data," creates an output table (or tables) summarizing a <b>randomlychosen subset</b> of the input dataset;</li> <li> "Assess the data with a model," adds attributes to the first input dataset using a model provided on the second input port; and</li> <li> "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.</li> </ol> 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 <i>Training fraction</i> setting will be ignored for tasks 1 and 3. 
3 
The value(s) is an enumeration of the following:

TrainingFraction (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 

Octree Depth Limit
This filter takes in a octree and produces a new octree which is no deeper than the maximum specified depth level.The Octree Depth Limit filter takes in an octree and produces a new octree that is nowhere deeper than the maximum specified depth level. The attribute data of pruned leaf cells are integrated in to their ancestors at the cut level.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Octree Depth Limit filter. 
Accepts input of following types:
 
MaximumLevel (MaximumLevel) 
The value of this property specifies the maximum depth of the output octree. 
4 

Octree Depth Scalars
This filter adds a scalar to each leaf of the octree that represents the leaf's depth within the tree.The vtkHyperOctreeDepth filter adds a scalar to each leaf of the octree that represents the leaf's depth within the tree.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Octree Depth Scalars filter. 
Accepts input of following types:

OrderedCompositeDistributor
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Set the input to the Ordered Composite Distributor filter. 

PassThrough (PassThrough) 
Toggle whether to pass the data through without compositing. 
0 
Accepts boolean values (0 or 1). 
PKdTree (PKdTree) 
Set the vtkPKdTree to distribute with. 

OutputType (OutputType) 
When not empty, the output will be converted to the given type. 

Outline
This filter generates a bounding box representation of the input.The Outline filter generates an axisaligned bounding box for the input dataset. This filter operates on any type of dataset and produces polygonal output.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Outline filter. 
Accepts input of following types:

Outline Corners
This filter generates a bounding box representation of the input. It only displays the corners of the bounding box.The Outline Corners filter generates the corners of a bounding box for the input dataset. This filter operates on any type of dataset and produces polygonal output.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Outline Corners filter. 
Accepts input of following types:
 
CornerFactor (CornerFactor) 
The value of this property sets the size of the corners as a percentage of the length of the corresponding bounding box edge. 
0.2 

Outline Curvilinear DataSet
This filter generates an outline representation of the input.The Outline filter generates an outline of the outside edges of the input dataset, rather than the dataset's bounding box. This filter operates on structured grid datasets and produces polygonal output.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the outline (curvilinear) filter. 
Accepts input of following types:

Outline Generic DataSet
This filter generates a bounding box representation of the input.The Generic Outline filter generates an axisaligned bounding box for the input data set. The Input menu specifies the data set for which to create a bounding box. This filter operates on generic data sets and produces polygonal output.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Set the input to the Generic Outline filter. 
Accepts input of following types:

ParticlePath
Trace Particle Paths through time in a vector field. The Particle Trace filter generates pathlines in a vector field from a collection of seed points. The vector field used is selected from the Vectors menu, so the input data set is required to have pointcentered vectors. The Seed portion of the interface allows you to select whether the seed points for this integration lie in a point cloud or along a line. Depending on which is selected, the appropriate 3D widget (point or line widget) is displayed along with traditional user interface controls for positioning the point cloud or line within the data set. Instructions for using the 3D widgets and the corresponding manual controls can be found in section 7.4. This filter operates on any type of data set, provided it has pointcentered vectors. The output is polygonal data containing polylines. This filter is available on the Toolbar.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Specify which is the Input of the StreamTracer filter. 
Accepts input of following types:
The dataset much contain a field array (point) with 3 component(s).  
Seed Source (Source) 
Specify the seed dataset. Typically fron where the vector field integration should begin. Usually a point/radius or a line with a given resolution. 
Accepts input of following types:
 
TerminationTime (TerminationTime) 
Setting TerminationTime to a positive value will cause particles to terminate when the time is reached. The units of time should be consistent with the primary time variable. 
0.0 

TimestepValues (TimestepValues)  
ForceReinjectionEveryNSteps (ForceReinjectionEveryNSteps) 
When animating particles, it is nice to inject new ones every Nth step to produce a continuous flow. Setting ForceReinjectionEveryNSteps to a non zero value will cause the particle source to reinject particles every Nth step even if it is otherwise unchanged. Note that if the particle source is also animated, this flag will be redundant as the particles will be reinjected whenever the source changes anyway 
0 

SelectInputVectors (SelectInputVectors) 
Specify which vector array should be used for the integration through that filter. 
An array of vectors is required.  
ComputeVorticity (ComputeVorticity) 
Compute vorticity and angular rotation of particles as they progress 
1 
Accepts boolean values (0 or 1). 
DisableResetCache (DisableResetCache) 
Prevents cache from getting reset so that new computation always start from previous results. 
0 
Accepts boolean values (0 or 1). 
ParticleTracer
Trace Particles through time in a vector field. The Particle Trace filter generates pathlines in a vector field from a collection of seed points. The vector field used is selected from the Vectors menu, so the input data set is required to have pointcentered vectors. The Seed portion of the interface allows you to select whether the seed points for this integration lie in a point cloud or along a line. Depending on which is selected, the appropriate 3D widget (point or line widget) is displayed along with traditional user interface controls for positioning the point cloud or line within the data set. Instructions for using the 3D widgets and the corresponding manual controls can be found in section 7.4. This filter operates on any type of data set, provided it has pointcentered vectors. The output is polygonal data containing polylines. This filter is available on the Toolbar.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Specify which is the Input of the StreamTracer filter. 
Accepts input of following types:
The dataset much contain a field array (point) with 3 component(s).  
Seed Source (Source) 
Specify the seed dataset. Typically fron where the vector field integration should begin. Usually a point/radius or a line with a given resolution. 
Accepts input of following types:
 
TimestepValues (TimestepValues)  
ForceReinjectionEveryNSteps (ForceReinjectionEveryNSteps) 
When animating particles, it is nice to inject new ones every Nth step to produce a continuous flow. Setting ForceReinjectionEveryNSteps to a non zero value will cause the particle source to reinject particles every Nth step even if it is otherwise unchanged. Note that if the particle source is also animated, this flag will be redundant as the particles will be reinjected whenever the source changes anyway 
0 

SelectInputVectors (SelectInputVectors) 
Specify which vector array should be used for the integration through that filter. 
An array of vectors is required.  
ComputeVorticity (ComputeVorticity) 
Compute vorticity and angular rotation of particles as they progress 
1 
Accepts boolean values (0 or 1). 
Pass Arrays
Pass specified point and cell data arrays. The Pass Arrays filter makes a shallow copy of the output data object from the input data object except for passing only the arrays specified to the output from the input.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Accepts input of following types:
The dataset much contain a field array ()  
UseFieldTypes (UseFieldTypes) 
This hidden property must always be set to 1 for this proxy to work. 
1 
Accepts boolean values (0 or 1). 
AddPointArrayType (AddPointArrayType) 
This hidden property must always be set to 0 for this proxy to work. 
0 
Accepts boolean values (0 or 1). 
AddCellArrayType (AddCellArrayType) 
This hidden property must always be set to 1 for this proxy to work. 
1 
Accepts boolean values (0 or 1). 
AddFieldArrayType (AddFieldArrayType) 
This hidden property must always be set to 2 for this proxy to work. 
2 
Accepts boolean values (0 or 1). 
PointDataArrays (AddPointDataArray) 
Add a point array by name to be passed. 

CellDataArrays (AddCellDataArray) 
Add a cell array by name to be passed. 

FieldDataArrays (AddFieldDataArray) 
Add a field array by name to be passed. 

Plot Data
Plot data arrays from the inputThis filter prepare arbitrary data to be plotted in any of the plots. By default the data is shown in a XY line plot.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
The input. 
Accepts input of following types:

Plot Global Variables Over Time
Extracts and plots data in field data over time. This filter extracts the variables that reside in a dataset's field data and are defined over time. The output is a 1D rectilinear grid where the x coordinates correspond to time (the same array is also copied to a point array named Time or TimeData (if Time exists in the input)).
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
The input from which the selection is extracted. 
Accepts input of following types:

Plot On Sorted Lines
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Plot Edges filter. 
Accepts input of following types:

Plot Selection Over Time
Extracts selection over time and then plots it. This filter extracts the selection over time, i.e. cell and/or point variables at a cells/point selected are extracted over time The output multiblock consists of 1D rectilinear grids where the x coordinate corresponds to time (the same array is also copied to a point array named Time or TimeData (if Time exists in the input)). If selection input is a Location based selection then the point values are interpolated from the nearby cells, ie those of the cell the location lies in.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
The input from which the selection is extracted. 
Accepts input of following types:
 
Selection (Selection) 
The input that provides the selection object. 
Accepts input of following types:
 
Only Report Selection Statistics (Only Report Selection Statistics) 
If this property is set to 1, the min, max, interquartile ranges, and (for numeric arrays) mean and standard deviation of all the selected points or cells within each time step are reported  instead of breaking each selected point's or cell's attributes out into separate time history tables. 
0 
Accepts boolean values (0 or 1). 
Point Data to Cell Data
Create cell attributes by averaging point attributes.The Point Data to Cell Data filter averages the values of the point attributes of the points of a cell to compute cell attributes. This filter operates on any type of dataset, and the output dataset is the same type as the input.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Point Data to Cell Data filter. 
Accepts input of following types:
The dataset much contain a field array (point)  
PassPointData (PassPointData) 
The value of this property controls whether the input point data will be passed to the output. If set to 1, then the input point data is passed through to the output; otherwise, only generated cell data is placed into the output. 
0 
Accepts boolean values (0 or 1). 
PolyLine To Rectilinear Grid
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Set the input to the Polyline to Rectilinear Grid filter. 
Accepts input of following types:

Principal Component Analysis
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. <p> This filter performs additional analysis above and beyond the multicorrelative filter. It computes the eigenvalues and eigenvectors of the covariance matrix from the multicorrelative filter. Data is then assessed by projecting the original tuples into a possibly lowerdimensional space. <p> Since the PCA filter uses the multicorrelative filter's analysis, it shares the same raw covariance table specified in the multicorrelative documentation. The second table in the multiblock dataset comprising the model output is an expanded version of the multicorrelative version. <p> As with the multicorrlative filter, the second model table contains the mean values, the uppertriangular portion of the symmetric covariance matrix, and the nonzero lowertriangular portion of the Cholesky decomposition of the covariance matrix. Below these entries are the eigenvalues of the covariance matrix (in the column labeled "Mean") and the eigenvectors (as row vectors) in an additional NxN matrix.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
The input to the filter. Arrays from this dataset will be used for computing statistics and/or assessed by a statistical model. 
Accepts input of following types:
The dataset much contain a field array ()  
ModelInput (ModelInput) 
A previouslycalculated model with which to assess a separate dataset. This input is optional. 
Accepts input of following types:
 
AttributeMode (AttributeMode) 
Specify which type of field data the arrays will be drawn from. 
0 
The value must be field array name. 
Variables of Interest (SelectArrays) 
Choose arrays whose entries will be used to form observations for statistical analysis. 

Task (Task) 
Specify the task to be performed: modeling and/or assessment. <ol> <li> "Detailed model of input data," creates a set of output tables containing a calculated statistical model of the <b>entire</b> input dataset;</li> <li> "Model a subset of the data," creates an output table (or tables) summarizing a <b>randomlychosen subset</b> of the input dataset;</li> <li> "Assess the data with a model," adds attributes to the first input dataset using a model provided on the second input port; and</li> <li> "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.</li> </ol> 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 <i>Training fraction</i> setting will be ignored for tasks 1 and 3. 
3 
The value(s) is an enumeration of the following:

TrainingFraction (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 

Normalization Scheme (NormalizationScheme) 
Before the eigenvector decomposition of the covariance matrix takes place, you may normalize each (i,j) entry by sqrt( cov(i,i) * cov(j,j) ). This implies that the variance of each variable of interest should be of equal importance. 
2 
The value(s) is an enumeration of the following:

Basis Scheme (BasisScheme) 
When reporting assessments, should the full eigenvector decomposition be used to project the original vector into the new space (Full basis), or should a fixed subset of the decomposition be used (Fixedsize basis), or should the projection be clipped to preserve at least some fixed "energy" (Fixedenergy basis)?<p> As an example, suppose the variables of interest were {A,B,C,D,E} and that the eigenvalues of the covariance matrix for these were {5,2,1.5,1,.5}. If the "Full basis" scheme is used, then all 5 components of the eigenvectors will be used to project each {A,B,C,D,E}tuple in the original data into a new 5components space.<p> If the "Fixedsize" scheme is used and the "Basis Size" property is set to 4, then only the first 4 eigenvector components will be used to project each {A,B,C,D,E}tuple into the new space and that space will be of dimension 4, not 5.<p> If the "Fixedenergy basis" scheme is used and the "Basis Energy" property is set to 0.8, then only the first 3 eigenvector components will be used to project each {A,B,C,D,E}tuple into the new space, which will be of dimension 3. The number 3 is chosen because 3 is the lowest N for which the sum of the first N eigenvalues divided by the sum of all eigenvalues is larger than the specified "Basis Energy" (i.e., (5+2+1.5)/10 = 0.85 > 0.8). 
0 
The value(s) is an enumeration of the following:

Basis Size (BasisSize) 
The maximum number of eigenvector components to use when projecting into the new space. 
2 

Basis Energy (BasisEnergy) 
The minimum energy to use when determining the dimensionality of the new space into which the assessment will project tuples. 
0.1 

Probe Location
Sample data attributes at the points in a point cloud. The Probe filter samples the data set attributes of the current data set at the points in a point cloud. The Probe filter uses interpolation to determine the values at the selected point, whether or not it lies at an input point. The Probe filter operates on any type of data and produces polygonal output (a point cloud).
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the dataset from which to obtain probe values. 
Accepts input of following types:
The dataset much contain a field array ()  
Probe Type (Source) 
This property specifies the dataset whose geometry will be used in determining positions to probe. 
The value can be one of the following:

Process Id Scalars
This filter uses colors to show how data is partitioned across processes.The Process Id Scalars filter assigns a unique scalar value to each piece of the input according to which processor it resides on. This filter operates on any type of data when ParaView is run in parallel. It is useful for determining whether your data is loadbalanced across the processors being used. The output data set type is the same as that of the input.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Process Id Scalars filter. 
Accepts input of following types:
 
RandomMode (RandomMode) 
The value of this property determines whether to use random id values for the various pieces. If set to 1, the unique value per piece will be chosen at random; otherwise the unique value will match the id of the process. 
0 
Accepts boolean values (0 or 1). 
Programmable Filter
Executes a user supplied python script on its input dataset to produce an output dataset. This filter will execute a python script to produce an output dataset. The filter keeps a copy of the python script in Script, and creates Interpretor, a python interpretor to run the script upon the first execution.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input(s) to the programmable filter. 
Accepts input of following types:
 
OutputDataSetType (OutputDataSetType) 
The value of this property determines the dataset type for the output of the programmable filter. 
8 
The value(s) is an enumeration of the following:

Script (Script) 
This property contains the text of a python program that the programmable filter runs. 

RequestInformation Script (InformationScript) 
This property is a python script that is executed during the RequestInformation pipeline pass. Use this to provide information such as WHOLE_EXTENT to the pipeline downstream. 

RequestUpdateExtent Script (UpdateExtentScript) 
This property is a python script that is executed during the RequestUpdateExtent pipeline pass. Use this to modify the update extent that your filter ask up stream for. 

CopyArrays (CopyArrays) 
If this property is set to true, all the cell and point arrays from first input are copied to the output. 
0 
Accepts boolean values (0 or 1). 
Parameters (Parameters)  
PythonPath (PythonPath) 
A semicolon (;) separated list of directories to add to the python library search path. 

Python Annotation
This filter evaluates a Python expression for a text annotation This filter uses Python to calculate an expression. It depends heavily on the numpy and paraview.vtk modules. To use the parallel functions, mpi4py is also necessary. The expression is evaluated and the resulting scalar value or numpy array is added to the output as an array. See numpy and paraview.vtk documentation for the list of available functions. This filter tries to make it easy for the user to write expressions by defining certain variables. The filter tries to assign each array to a variable of the same name. If the name of the array is not a valid Python variable, it has to be accessed through a dictionary called arrays (i.e. arrays['array_name']).
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Set the input of the filter. 
Accepts input of following types:
 
Expression (Expression) 
The Python expression evaluated during execution. FieldData arrays are direclty available through their name. Set of provided variables [input, t_value, t_steps, t_range, t_index, FieldData, PointData, CellData] (i.e.: "Momentum: (%f, %f, %f)" % (XMOM[t_index,0], YMOM[t_index,0], ZMOM[t_index,0]) ) 

AnnotationValue (AnnotationValue) 
Text that is used as annotation 

Python Calculator
This filter evaluates a Python expressionThis filter uses Python to calculate an expression. It depends heavily on the numpy and paraview.vtk modules. To use the parallel functions, mpi4py is also necessary. The expression is evaluated and the resulting scalar value or numpy array is added to the output as an array. See numpy and paraview.vtk documentation for the list of available functions. This filter tries to make it easy for the user to write expressions by defining certain variables. The filter tries to assign each array to a variable of the same name. If the name of the array is not a valid Python variable, it has to be accessed through a dictionary called arrays (i.e. arrays['array_name']). The points can be accessed using the points variable.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Set the input of the filter. 
Accepts input of following types:
 
Expression (Expression) 
The Python expression evaluated during execution. 

ArrayAssociation (ArrayAssociation) 
This property controls the association of the output array as well as which arrays are defined as variables. 
0 
The value(s) is an enumeration of the following:

ArrayName (ArrayName) 
The name of the output array. 
result 

CopyArrays (CopyArrays) 
If this property is set to true, all the cell and point arrays from first input are copied to the output. 
1 
Accepts boolean values (0 or 1). 
Quadric Clustering
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 reducedresolution 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.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Quadric Clustering filter. 
Accepts input of following types:
 
Number of Dimensions (NumberOfDivisions) 
This property specifies the number of bins along the X, Y, and Z axes of the data set. 
50 50 50 

UseInputPoints (UseInputPoints) 
If the value of this property is set to 1, the representative point for each bin is selected from one of the input points that lies in that bin; the input point that produces the least error is chosen. If the value of this property is 0, the location of the representative point is calculated to produce the least error possible for that bin, but the point will most likely not be one of the input points. 
1 
Accepts boolean values (0 or 1). 
UseFeatureEdges (UseFeatureEdges) 
If this property is set to 1, feature edge quadrics will be used to maintain the boundary edges along processor divisions. 
0 
Accepts boolean values (0 or 1). 
UseFeaturePoints (UseFeaturePoints) 
If this property is set to 1, feature point quadrics will be used to maintain the boundary points along processor divisions. 
0 
Accepts boolean values (0 or 1). 
CopyCellData (CopyCellData) 
If this property is set to 1, the cell data from the input will be copied to the output. 
1 
Accepts boolean values (0 or 1). 
UseInternalTriangles (UseInternalTriangles) 
If this property is set to 1, triangles completely contained in a spatial bin will be included in the computation of the bin's quadrics. When this property is set to 0, the filters operates faster, but the resulting surface may not be as wellbehaved. 
0 
Accepts boolean values (0 or 1). 
Random Vectors
This filter creates a new 3component point data array and sets it as the default vector array. It uses a random number generator to create values.The Random Vectors filter generates a pointcentered array of random vectors. It uses a random number generator to determine the components of the vectors. This filter operates on any type of data set, and the output data set will be of the same type as the input.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Random Vectors filter. 
Accepts input of following types:
 
MinimumSpeed (MinimumSpeed) 
This property specifies the minimum length of the random point vectors generated. 
0 

MaximumSpeed (MaximumSpeed) 
This property specifies the maximum length of the random point vectors generated. 
1 

Rectilinear Data to Point Set
The Rectilinear Grid to Point Set filter takes an rectilinear grid object and outputs an equivalent structured grid (which as a type of point set). This brings the data to a broader category of data storage but only adds a small amount of overhead. This filter can be helpful in applying filters that expect or manipulate point coordinates.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Accepts input of following types:

Rectilinear Grid Connectivity
Parallel fragments extraction and attributes integration on rectilinear grids. Extracts material fragments from multiblock vtkRectilinearGrid datasets based on the selected volume fraction array(s) and a fraction isovalue and integrates the associated attributes.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input of the filter. 
Accepts input of following types:
The dataset much contain a field array (cell) with 1 component(s).  
Double Volume Arrays (AddDoubleVolumeArrayName) 
This property specifies the name(s) of the volume fraction array(s) for generating parts. 
An array of scalars is required.  
Float Volume Arrays (AddFloatVolumeArrayName) 
This property specifies the name(s) of the volume fraction array(s) for generating parts. 
An array of scalars is required.  
Unsigned Character Volume Arrays (AddUnsignedCharVolumeArrayName) 
This property specifies the name(s) of the volume fraction array(s) for generating parts. 
An array of scalars is required.  
Volume Fraction Value (VolumeFractionSurfaceValue) 
The value of this property is the volume fraction value for the surface. 
0.1 

RectilinearGridGeometryFilter
Extracts geometry for a rectilinear grid. Output is a polydata dataset. RectilinearGridGeometryFilter is a filter that extracts geometry from a rectilinear grid. By specifying appropriate ijk indices, it is possible to extract a point, a curve, a surface, or a "volume". The volume is actually a (n x m x o) region of points. The extent specification is zerooffset. That is, the first kplane in a 50x50x50 rectilinear grid is given by (0,49, 0,49, 0,0).
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Set the input to the Rectilinear Grid Geometry filter. 
Accepts input of following types:

ReductionFilter
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Set the input to the Reduction filter. 

PreGatherHelperName (PreGatherHelperName) 
Set the algorithm that runs on each node in parallel. 

PostGatherHelperName (PostGatherHelperName) 
Set the algorithm that takes multiple inputs and produces a single reduced output. 

PostGatherHelper (PostGatherHelper)  
PreGatherHelper (PreGatherHelper)  
PassThrough (PassThrough) 
If set to a nonnegative value, then produce results using only the node Id specified. 
1 

GenerateProcessIds (GenerateProcessIds) 
If true, the filter will generate vtkOriginalProcessIds arrays indicating the process id on which the cell/point was generated. 
0 
Accepts boolean values (0 or 1). 
Reflect
This filter takes the union of the input and its reflection over an axisaligned plane.The Reflect filter reflects the input dataset across the specified plane. This filter operates on any type of data set and produces an unstructured grid output.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Reflect filter. 
Accepts input of following types:
 
Plane (Plane) 
The value of this property determines which plane to reflect across. If the value is X, Y, or Z, the value of the Center property determines where the plane is placed along the specified axis. The other six options (X Min, X Max, etc.) place the reflection plane at the specified face of the bounding box of the input dataset. 
0 
The value(s) is an enumeration of the following:

Center (Center) 
If the value of the Plane property is X, Y, or Z, then the value of this property specifies the center of the reflection plane. 
0.0 

CopyInput (CopyInput) 
If this property is set to 1, the output will contain the union of the input dataset and its reflection. Otherwise the output will contain only the reflection of the input data. 
1 
Accepts boolean values (0 or 1). 
Resample AMR
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input for this filter. 
Accepts input of following types:
 
DemandDriven Mode (DemandDriven Mode) 
This property specifies whether the resampling filter will operate in demanddriven mode or not. 
1 
Accepts boolean values (0 or 1). 
TransferToNodes (TransferToNodes) 
This property specifies whether the solution will be transfered to the nodes of the extracted region or the cells. 
1 
Accepts boolean values (0 or 1). 
NumberOfPartitions (NumberOfPartitions) 
Set the number of subdivisions for recursive coordinate bisection. 
1 

Number of Samples (Number of Samples) 
Sets the number of samples in each dimension 
10 10 10 

Min (Min) 
This property sets the minimum 3D coordinate location by which the particles will be filtered out. 
0.0 0.0 0.0 

Max (Max) 
This property sets the minimum 3D coordinate location by which the particles will be filtered out. 
0.0 0.0 0.0 

Resample With Dataset
Sample data attributes at the points of a dataset. Probe is a filter that computes point attributes at specified point positions. The filter has two inputs: the Input and Source. The Input geometric structure is passed through the filter. The point attributes are computed at the Input point positions by interpolating into the source data. For example, we can compute data values on a plane (plane specified as Input) from a volume (Source). The cell data of the source data is copied to the output based on in which source cell each input point is. If an array of the same name exists both in source's point and cell data, only the one from the point data is probed.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the dataset from which to obtain probe values. 
Accepts input of following types:
The dataset much contain a field array ()  
Source (Source) 
This property specifies the dataset whose geometry will be used in determining positions to probe. 
Accepts input of following types:

Ribbon
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 pointcentered vector array.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Ribbon filter. 
Accepts input of following types:
The dataset much contain a field array (point) with 3 component(s). The dataset much contain a field array (point) with 1 component(s).  
Scalars (SelectInputScalars) 
The value of this property indicates the name of the input scalar array used by this filter. The width of the ribbons will be varied based on the values in the specified array if the value of the Width property is 1. 
An array of scalars is required.  
Vectors (SelectInputVectors) 
The value of this property indicates the name of the input vector array used by this filter. If the UseDefaultNormal property is set to 0, the normal vectors for the ribbons come from the specified vector array. 
1 
An array of vectors is required. 
Width (Width) 
If the VaryWidth property is set to 1, the value of this property is the minimum ribbon width. If the VaryWidth property is set to 0, the value of this property is half the width of the ribbon. 
1 
The value must be less than the largest dimension of the dataset multiplied by a scale factor of 0.01. 
Angle (Angle) 
The value of this property specifies the offset angle (in degrees) of the ribbon from the line normal. 
0 

UseDefaultNormal (UseDefaultNormal) 
If this property is set to 0, and the input contains no vector array, then default ribbon normals will be generated (DefaultNormal property); if a vector array has been set (SelectInputVectors property), the ribbon normals will be set from the specified array. If this property is set to 1, the default normal (DefaultNormal property) will be used, regardless of whether the SelectInputVectors property has been set. 
0 
Accepts boolean values (0 or 1). 
DefaultNormal (DefaultNormal) 
The value of this property specifies the normal to use when the UseDefaultNormal property is set to 1 or the input contains no vector array (SelectInputVectors property). 
0 0 1 

VaryWidth (VaryWidth) 
If this property is set to 1, the ribbon width will be scaled according to the scalar array specified in the SelectInputScalars property. Toggle the variation of ribbon width with scalar value. 
0 
Accepts boolean values (0 or 1). 
Rotational Extrusion
This filter generates a swept surface while translating the input along a circular path. The Rotational Extrusion filter forms a surface by rotating the input about the Z axis. This filter is intended to operate on 2D polygonal data. It produces polygonal output.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Rotational Extrusion filter. 
Accepts input of following types:
 
Resolution (Resolution) 
The value of this property controls the number of intermediate node points used in performing the sweep (rotating from 0 degrees to the value specified by the Angle property. 
12 

Capping (Capping) 
If this property is set to 1, the open ends of the swept surface will be capped with a copy of the input dataset. This works property if the input is a 2D surface composed of filled polygons. If the input dataset is a closed solid (e.g., a sphere), then either two copies of the dataset will be drawn or no surface will be drawn. No surface is drawn if either this property is set to 0 or if the two surfaces would occupy exactly the same 3D space (i.e., the Angle property's value is a multiple of 360, and the values of the Translation and DeltaRadius properties are 0). 
1 
Accepts boolean values (0 or 1). 
Angle (Angle) 
This property specifies the angle of rotation in degrees. The surface is swept from 0 to the value of this property. 
360 

Translation (Translation) 
The value of this property specifies the total amount of translation along the Z axis during the sweep process. Specifying a nonzero value for this property allows you to create a corkscrew (value of DeltaRadius > 0) or spring effect. 
0 

DeltaRadius (DeltaRadius) 
The value of this property specifies the change in radius during the sweep process. 
0 

Scatter Plot
Creates a scatter plot from a dataset.This filter creates a scatter plot from a dataset.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the filter. 
Accepts input of following types:

Shrink
This filter shrinks each input cell so they pull away from their neighbors.The Shrink filter causes the individual cells of a dataset to break apart from each other by moving each cell's points toward the centroid of the cell. (The centroid of a cell is the average position of its points.) This filter operates on any type of dataset and produces unstructured grid output.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Shrink filter. 
Accepts input of following types:
 
ShrinkFactor (ShrinkFactor) 
The value of this property determines how far the points will move. A value of 0 positions the points at the centroid of the cell; a value of 1 leaves them at their original positions. 
0.5 

Slice
This filter slices a data set with a plane. Slicing is similar to a contour. It creates surfaces from volumes and lines from surfaces.This filter extracts the portion of the input dataset that lies along the specified plane. The Slice filter takes any type of dataset as input. The output of this filter is polygonal data.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Slice filter. 
Accepts input of following types:
 
Slice Type (CutFunction) 
This property sets the parameters of the slice function. 
The value can be one of the following:
 
InputBounds (InputBounds)  
Crinkle slice (PreserveInputCells) 
This parameter controls whether to extract the entire cells that are sliced by the region or just extract a triangulated surface of that region. 
0 
Accepts boolean values (0 or 1). 
Triangulate the slice (Triangulate the slice) 
This parameter controls whether to produce triangles in the output. 
1 
Accepts boolean values (0 or 1). 
Slice Offset Values (ContourValues) 
The values in this property specify a list of current offset values. This can be used to create multiple slices with different centers. Each entry represents a new slice with its center shifted by the offset value. 
Determine the length of the dataset's diagonal. The value must lie within diagonal length to +diagonal length.

Slice (demanddrivencomposite)
This filter slices a data set with a plane. Slicing is similar to a contour. It creates surfaces from volumes and lines from surfaces.This filter extracts the portion of the input dataset that lies along the specified plane. The Slice filter takes any type of dataset as input. The output of this filter is polygonal data.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Slice filter. 
Accepts input of following types:
 
Slice Type (CutFunction) 
This property sets the parameters of the slice function. 
The value can be one of the following:
 
InputBounds (InputBounds)  
Slice Offset Values (ContourValues) 
The values in this property specify a list of current offset values. This can be used to create multiple slices with different centers. Each entry represents a new slice with its center shifted by the offset value. 
Determine the length of the dataset's diagonal. The value must lie within diagonal length to +diagonal length.

Slice AMR data
Slices AMR DataThis filter slices AMR data.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input for this filter. 
Accepts input of following types:
 
ForwardUpstream (ForwardUpstream) 
This property specifies whether or not requests will be propagated upstream. 
0 
Accepts boolean values (0 or 1). 
EnablePrefetching (EnablePrefetching) 
This property specifies whether or not requests prefetching of blocks of the next level will be enabled. 
0 
Accepts boolean values (0 or 1). 
Level (Level) 
Set maximum slice resolution. 
0 

OffSet (OffSet) 
Set's the offset from the origin of the dataset 
1.0 

Normal (Normal) 
This property sets the normal of the slice. 
0 
The value(s) is an enumeration of the following:

Slice Generic Dataset
This filter cuts a data set with a plane or sphere. Cutting is similar to a contour. It creates surfaces from volumes and lines from surfaces.The Generic Cut filter extracts the portion of the input data set that lies along the specified plane or sphere. From the Cut Function menu, you can select whether cutting will be performed with a plane or a sphere. The appropriate 3D widget (plane widget or sphere widget) will be displayed. The parameters of the cut function can be specified interactively using the 3D widget or manually using the traditional user interface controls. Instructions for using these 3D widgets and their corresponding user interfaces are found in section 7.4. By default, the cut lies on the specified plane or sphere. Using the Cut Offset Values portion of the interface, it is also possible to cut the data set at some offset from the original cut function. The Cut Offset Values are in the spatial units of the data set. To add a single offset, select the value from the New Value slider in the Add value portion of the interface and click the Add button, or press Enter. To instead add several evenly spaced offsets, use the controls in the Generate range of values section. Select the number of offsets to generate using the Number of Values slider. The Range slider controls the interval in which to generate the offsets. Once the number of values and range have been selected, click the Generate button. The new offsets will be added to the Offset Values list. To delete a value from the Cut Offset Values list, select the value and click the Delete button. (If no value is selected, the last value in the list will be removed.) Clicking the Delete All button removes all the values in the list. The Generic Cut filter takes a generic dataset as input. Use the Input menu to choose a data set to cut. The output of this filter is polygonal data.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Set the input to the Generic Cut filter. 
Accepts input of following types:
 
Cut Type (CutFunction) 
Set the parameters to the implicit function used for cutting. 
The value can be one of the following:
 
InputBounds (InputBounds)  
Slice Offset Values (ContourValues) 
The values in this property specify a list of current offset values. This can be used to create multiple slices with different centers. Each entry represents a new slice with its center shifted by the offset value. 
Determine the length of the dataset's diagonal. The value must lie within diagonal length to +diagonal length.

Smooth
This filter smooths a polygonal surface by iteratively moving points toward their neighbors. The Smooth filter operates on a polygonal data set by iteratively adjusting the position of the points using Laplacian smoothing. (Because this filter only adjusts point positions, the output data set is also polygonal.) This results in bettershaped cells and more evenly distributed points. The Convergence slider limits the maximum motion of any point. It is expressed as a fraction of the length of the diagonal of the bounding box of the data set. If the maximum point motion during a smoothing iteration is less than the Convergence value, the smoothing operation terminates.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Smooth filter. 
Accepts input of following types:
 
Number of Iterations (NumberOfIterations) 
This property sets the maximum number of smoothing iterations to perform. More iterations produce better smoothing. 
20 

Convergence (Convergence) 
The value of this property limits the maximum motion of any point. It is expressed as a fraction of the length of the diagonal of the bounding box of the input dataset. If the maximum point motion during a smoothing iteration is less than the value of this property, the smoothing operation terminates. 
0.0 

StreakLine
Trace Streak lines through time in a vector field. The Particle Trace filter generates pathlines in a vector field from a collection of seed points. The vector field used is selected from the Vectors menu, so the input data set is required to have pointcentered vectors. The Seed portion of the interface allows you to select whether the seed points for this integration lie in a point cloud or along a line. Depending on which is selected, the appropriate 3D widget (point or line widget) is displayed along with traditional user interface controls for positioning the point cloud or line within the data set. Instructions for using the 3D widgets and the corresponding manual controls can be found in section 7.4. This filter operates on any type of data set, provided it has pointcentered vectors. The output is polygonal data containing polylines. This filter is available on the Toolbar.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Specify which is the Input of the StreamTracer filter. 
Accepts input of following types:
The dataset much contain a field array (point) with 3 component(s).  
Seed Source (Source) 
Specify the seed dataset. Typically fron where the vector field integration should begin. Usually a point/radius or a line with a given resolution. 
Accepts input of following types:
 
TerminationTime (TerminationTime) 
Setting TerminationTime to a positive value will cause particles to terminate when the time is reached. The units of time should be consistent with the primary time variable. 
0.0 

TimestepValues (TimestepValues)  
ForceReinjectionEveryNSteps (ForceReinjectionEveryNSteps) 
When animating particles, it is nice to inject new ones every Nth step to produce a continuous flow. Setting ForceReinjectionEveryNSteps to a non zero value will cause the particle source to reinject particles every Nth step even if it is otherwise unchanged. Note that if the particle source is also animated, this flag will be redundant as the particles will be reinjected whenever the source changes anyway 
1 

SelectInputVectors (SelectInputVectors) 
Specify which vector array should be used for the integration through that filter. 
An array of vectors is required.  
ComputeVorticity (ComputeVorticity) 
Compute vorticity and angular rotation of particles as they progress 
1 
Accepts boolean values (0 or 1). 
DisableResetCache (DisableResetCache) 
Prevents cache from getting reset so that new computation always start from previous results. 
0 
Accepts boolean values (0 or 1). 
Stream Tracer
Integrate streamlines in a vector field.The Stream Tracer filter generates streamlines in a vector field from a collection of seed points. Production of streamlines terminates if a streamline crosses the exterior boundary of the input dataset. Other reasons for termination are listed for the MaximumNumberOfSteps, TerminalSpeed, and MaximumPropagation properties. This filter operates on any type of dataset, provided it has pointcentered vectors. The output is polygonal data containing polylines.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Stream Tracer filter. 
Accepts input of following types:
The dataset much contain a field array (any) with 3 component(s).  
Vectors (SelectInputVectors) 
This property contains the name of the vector array from which to generate streamlines. 
An array of vectors is required.  
InterpolatorType (InterpolatorType) 
This property determines which interpolator to use for evaluating the velocity vector field. The first is faster though the second is more robust in locating cells during streamline integration. 
0 
The value(s) is an enumeration of the following:

IntegrationDirection (IntegrationDirection) 
This property determines in which direction(s) a streamline is generated. 
2 
The value(s) is an enumeration of the following:

IntegratorType (IntegratorType) 
This property determines which integrator (with increasing accuracy) to use for creating streamlines. 
2 
The value(s) is an enumeration of the following:

Integration Step Unit (IntegrationStepUnit) 
This property specifies the unit for Minimum/Initial/Maximum integration step size. The Length unit refers to the arc length that a particle travels/advects within a single step. The Cell Length unit represents the step size as a number of cells. 
2 
The value(s) is an enumeration of the following:

Initial Step Length (InitialIntegrationStep) 
This property specifies the initial integration step size. For nonadaptive integrators (RungeKutta 2 and RungeKutta 4), it is fixed (always equal to this initial value) throughout the integration. For an adaptive integrator (RungeKutta 45), the actual step size varies such that the numerical error is less than a specified threshold. 
0.2 

Minimum Step Length (MinimumIntegrationStep) 
When using the RungeKutta 45 ingrator, this property specifies the minimum integration step size. 
0.01 

Maximum Step Length (MaximumIntegrationStep) 
When using the RungeKutta 45 ingrator, this property specifies the maximum integration step size. 
0.5 

Maximum Steps (MaximumNumberOfSteps) 
This property specifies the maximum number of steps, beyond which streamline integration is terminated. 
2000 

Maximum Streamline Length (MaximumPropagation) 
This property specifies the maximum streamline length (i.e., physical arc length), beyond which line integration is terminated. 
1.0 
The value must be less than the largest dimension of the dataset multiplied by a scale factor of 1.0. 
Terminal Speed (TerminalSpeed) 
This property specifies the terminal speed, below which particle advection/integration is terminated. 
0.000000000001 

MaximumError (MaximumError) 
This property specifies the maximum error (for RungeKutta 45) tolerated throughout streamline integration. The RungeKutta 45 integrator tries to adjust the step size such that the estimated error is less than this threshold. 
0.000001 

ComputeVorticity (ComputeVorticity) 
Specify whether or not to compute vorticity. 
1 
Accepts boolean values (0 or 1). 
Seed Type (Source) 
The value of this property determines how the seeds for the streamlines will be generated. 
The value can be one of the following:

Stream Tracer For Generic Datasets
Integrate streamlines in a vector field.The Generic Stream Tracer filter generates streamlines in a vector field from a collection of seed points. The vector field used is selected from the Vectors menu, so the input data set is required to have pointcentered vectors. The Seed portion of the interface allows you to select whether the seed points for this integration lie in a point cloud or along a line. Depending on which is selected, the appropriate 3D widget (point or line widget) is displayed along with traditional user interface controls for positioning the point cloud or line within the data set. Instructions for using the 3D widgets and the corresponding manual controls can be found in section 7.4. The Max. Propagation entry box allows you to specify the maximum length of the streamlines. From the Max. Propagation menu, you can select the units to be either Time (the time a particle would travel with steady flow) or Length (in the data set's spatial coordinates). The Init. Step Len. menu and entry specify the initial step size for integration. (For nonadaptive integrators, RungeKutta 2 and 4, the initial step size is used throughout the integration.) The menu allows you to specify the units. Time and Length have the same meaning as for Max. Propagation. Cell Length specifies the step length as a number of cells. The Integration Direction menu determines in which direction(s) the stream trace will be generated: FORWARD, BACKWARD, or BOTH. The Integrator Type section of the interface determines which calculation to use for integration: RungeKutta 2, RungeKutta 4, or RungeKutta 45. If RungeKutta 45 is selected, controls are displayed for specifying the minimum and maximum step length and the maximum error. The controls for specifying Min. Step Len. and Max. Step Len. are the same as those for Init. Step Len. The RungeKutta 45 integrator tries to choose the step size so that the estimated error is less than the value of the Maximum Error entry. If the integration takes more than Max. Steps to complete, if the speed goes below Term. Speed, if Max. Propagation is reached, or if a boundary of the input data set is crossed, integration terminates. This filter operates on any type of data set, provided it has pointcentered vectors. The output is polygonal data containing polylines.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Set the input to the Generic Stream Tracer filter. 
Accepts input of following types:
The dataset much contain a field array (point) with 3 component(s).  
Seed Type (Source) 
The value of this property determines how the seeds for the streamlines will be generated. 
The value can be one of the following:
 
Vectors (SelectInputVectors) 
This property contains the name of the vector array from which to generate streamlines. 
An array of vectors is required.  
MaximumPropagation (MaximumPropagation) 
Specify the maximum streamline length. 
1.0 
The value must be less than the largest dimension of the dataset multiplied by a scale factor of 1.0. 
InitialIntegrationStep (InitialIntegrationStep) 
Specify the initial integration step. 
0.5 

IntegrationDirection (IntegrationDirection) 
This property determines in which direction(s) a streamline is generated. 
2 
The value(s) is an enumeration of the following:

IntegratorType (IntegratorType) 
This property determines which integrator (with increasing accuracy) to use for creating streamlines. 
2 
The value(s) is an enumeration of the following:

MaximumError (MaximumError) 
Set the maximum error allowed in the integration. The meaning of this value depends on the integrator chosen. 
0.000001 

MinimumIntegrationStep (MinimumIntegrationStep) 
Specify the minimum integration step. 
0.01 

IntegrationStepUnit (IntegrationStepUnit) 
Choose the unit to use for the integration step. 
2 
The value(s) is an enumeration of the following:

MaximumIntegrationStep (MaximumIntegrationStep) 
Specify the maximum integration step. 
0.01 

MaximumNumberOfSteps (MaximumNumberOfSteps) 
Specify the maximum number of steps used in the integration. 
2000 

TerminalSpeed (TerminalSpeed) 
If at any point the speed is below this value, the integration is terminated. 
0.000000000001 

Stream Tracer With Custom Source
Integrate streamlines in a vector field.The Stream Tracer filter generates streamlines in a vector field from a collection of seed points. Production of streamlines terminates if a streamline crosses the exterior boundary of the input dataset. Other reasons for termination are listed for the MaximumNumberOfSteps, TerminalSpeed, and MaximumPropagation properties. This filter operates on any type of dataset, provided it has pointcentered vectors. The output is polygonal data containing polylines. This filter takes a Source input that provides the seed points.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Stream Tracer filter. 
Accepts input of following types:
The dataset much contain a field array (point) with 3 component(s).  
Vectors (SelectInputVectors) 
This property contains the name of the vector array from which to generate streamlines. 
An array of vectors is required.  
IntegrationDirection (IntegrationDirection) 
This property determines in which direction(s) a streamline is generated. 
2 
The value(s) is an enumeration of the following:

IntegratorType (IntegratorType) 
This property determines which integrator (with increasing accuracy) to use for creating streamlines. 
2 
The value(s) is an enumeration of the following:

Integration Step Unit (IntegrationStepUnit) 
This property specifies the unit for Minimum/Initial/Maximum integration step size. The Length unit refers to the arc length that a particle travels/advects within a single step. The Cell Length unit represents the step size as a number of cells. 
2 
The value(s) is an enumeration of the following:

Initial Step Length (InitialIntegrationStep) 
This property specifies the initial integration step size. For nonadaptive integrators (RungeKutta 2 and RungeKutta 4), it is fixed (always equal to this initial value) throughout the integration. For an adaptive integrator (RungeKutta 45), the actual step size varies such that the numerical error is less than a specified threshold. 
0.2 

Minimum Step Length (MinimumIntegrationStep) 
When using the RungeKutta 45 ingrator, this property specifies the minimum integration step size. 
0.01 

Maximum Step Length (MaximumIntegrationStep) 
When using the RungeKutta 45 ingrator, this property specifies the maximum integration step size. 
0.5 

Maximum Steps (MaximumNumberOfSteps) 
This property specifies the maximum number of steps, beyond which streamline integration is terminated. 
2000 

Maximum Streamline Length (MaximumPropagation) 
This property specifies the maximum streamline length (i.e., physical arc length), beyond which line integration is terminated. 
1.0 
The value must be less than the largest dimension of the dataset multiplied by a scale factor of 1.0. 
Terminal Speed (TerminalSpeed) 
This property specifies the terminal speed, below which particle advection/integration is terminated. 
0.000000000001 

MaximumError (MaximumError) 
This property specifies the maximum error (for RungeKutta 45) tolerated throughout streamline integration. The RungeKutta 45 integrator tries to adjust the step size such that the estimated error is less than this threshold. 
0.000001 

ComputeVorticity (ComputeVorticity) 
Specify whether or not to compute vorticity. 
1 
Accepts boolean values (0 or 1). 
Seed Source (Source) 
This property specifies the input used to obtain the seed points. 

Subdivide
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.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This parameter specifies the input to the Subdivide filter. 
Accepts input of following types:
 
Number of Subdivisions (NumberOfSubdivisions) 
The value of this property specifies the number of subdivision iterations to perform. 
1 

Surface Flow
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.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Surface Flow filter. 
Accepts input of following types:
The dataset much contain a field array (point) with 3 component(s).  
SelectInputVectors (SelectInputVectors) 
The value of this property specifies the name of the input vector array containing the flow vector field. 
An array of vectors is required. 
Surface Vectors
This filter constrains vectors to lie on a surface. The Surface Vectors filter is used for 2D data sets. It constrains vectors to lie in a surface by removing components of the vectors normal to the local surface.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Surface Vectors filter. 
Accepts input of following types:
The dataset much contain a field array (point) with 3 component(s).  
SelectInputVectors (SelectInputVectors) 
This property specifies the name of the input vector array to process. 
An array of vectors is required.  
ConstraintMode (ConstraintMode) 
This property specifies whether the vectors will be parallel or perpendicular to the surface. If the value is set to PerpendicularScale (2), then the output will contain a scalar array with the dot product of the surface normal and the vector at each point. 
0 
The value(s) is an enumeration of the following:

Table FFT
Performs the Fast Fourier Transform on the columns of a table.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input of the filter. 
Accepts input of following types:
The dataset much contain a field array (row) with 1 component(s).

Table To Points
Converts table to set of points.The TableToPolyData filter converts a vtkTable to a set of points in a vtkPolyData. One must specifies the columns in the input table to use as the X, Y and Z coordinates for the points in the output.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input.. 
Accepts input of following types:
The dataset much contain a field array (row) with 1 component(s).  
XColumn (XColumn) 
This property specifies which data array is going to be used as the X coordinate in the generated polydata dataset. 

YColumn (YColumn) 
This property specifies which data array is going to be used as the Y coordinate in the generated polydata dataset. 

ZColumn (ZColumn) 
This property specifies which data array is going to be used as the Z coordinate in the generated polydata dataset. 

2D Points (Create2DPoints) 
Specify whether the points of the polydata are 3D or 2D. If this is set to true then the Z Column will be ignored and the z value of each point on the polydata will be set to 0. By default this will be off. 
0 
Accepts boolean values (0 or 1). 
KeepAllDataArrays (KeepAllDataArrays) 
Allow user to keep columns specified as X,Y,Z as Data arrays. By default this will be off. 
0 
Accepts boolean values (0 or 1). 
Table To Structured Grid
Converts to table to structured grid.The TableToStructuredGrid filter converts a vtkTable to a vtkStructuredGrid. One must specifies the columns in the input table to use as the X, Y and Z coordinates for the points in the output, and the whole extent.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input.. 
Accepts input of following types:
The dataset much contain a field array (row) with 1 component(s).  
WholeExtent (WholeExtent) 
0 0 0 0 0 0 

XColumn (XColumn) 
This property specifies which data array is going to be used as the X coordinate in the generated polydata dataset. 

YColumn (YColumn) 
This property specifies which data array is going to be used as the Y coordinate in the generated polydata dataset. 

ZColumn (ZColumn) 
This property specifies which data array is going to be used as the Z coordinate in the generated polydata dataset. 

Temporal Cache
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 reevaluate 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.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input of the Temporal Cache filter. 
Accepts input of following types:
 
CacheSize (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). 
2 

TimestepValues (TimestepValues) 

Temporal Interpolator
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.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input of the Temporal Interpolator. 
Accepts input of following types:
 
DiscreteTimeStepInterval (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 'filein' the missing data with an interpolated value from the steps on either side. 
0.0 

TimestepValues (TimestepValues)  
TimeRange (TimeRange) 

Temporal Particles To Pathlines
Creates polylines representing pathlines of animating particles Particle Pathlines takes any dataset as input, it extracts the point locations of all cells over time to build up a polyline trail. The point number (index) is used as the 'key' if the points are randomly changing their respective order in the points list, then you should specify a scalar that represents the unique ID. This is intended to handle the output of a filter such as the TemporalStreamTracer.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
The input cells to create pathlines for. 
Accepts input of following types:
The dataset much contain a field array (point)  
Selection (Selection) 
Set a second input, which is a selection. Particles with the same Id in the selection as the primary input will be chosen for pathlines Note that you must have the same IdChannelArray in the selection as the input 
Accepts input of following types:
 
MaskPoints (MaskPoints) 
Set the number of particles to track as a ratio of the input. Example: setting MaskPoints to 10 will track every 10th point. 
100 

MaxTrackLength (MaxTrackLength) 
If the Particles being traced animate for a long time, the trails or traces will become long and stringy. Setting the MaxTraceTimeLength will limit how much of the trace is displayed. Tracks longer then the Max will disappear and the trace will apppear like a snake of fixed length which progresses as the particle moves. This length is given with respect to timesteps. 
25 

MaxStepDistance (MaxStepDistance) 
If a particle disappears from one end of a simulation and reappears on the other side, the track left will be unrepresentative. Set a MaxStepDistance{x,y,z} which acts as a threshold above which if a step occurs larger than the value (for the dimension), the track will be dropped and restarted after the step. (ie the part before the wrap around will be dropped and the newer part kept). 
1.0 1.0 1.0 

IdChannelArray (IdChannelArray) 
Specify the name of a scalar array which will be used to fetch the index of each point. This is necessary only if the particles change position (Id order) on each time step. The Id can be used to identify particles at each step and hence track them properly. If this array is set to "Global or Local IDs", the global point ids are used if they exist or the point index is otherwise. 
Global or Local IDs 
An array of scalars is required. 
Temporal Shift Scale
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 (tShift)/Scale on its input.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
The input to the Temporal Shift Scale filter. 
Accepts input of following types:
 
PreShift (PreShift) 
Apply a translation to the data before scaling. To convert T{5,100} to T{0,1} use Preshift=5, Scale=1/95, PostShift=0 To convert T{5,105} to T{5,10} use Preshift=5, Scale=5/100, PostShift=5 
0.0 

PostShift (PostShift) 
The amount of time the input is shifted. 
0.0 

Scale (Scale) 
The factor by which the input time is scaled. 
1.0 

Periodic (Periodic) 
If Periodic is true, requests for time will be wrapped around so that the source appears to be a periodic time source. If data exists for times {0,N1}, setting periodic to true will cause time 0 to be produced when time N, 2N, 2N etc is requested. This effectively gives the source the ability to generate time data indefinitely in a loop. When combined with Shift/Scale, the time becomes periodic in the shifted and scaled time frame of reference. Note: Since the input time may not start at zero, the wrapping of time from the end of one period to the start of the next, will subtract the initial time  a source with T{5..6} repeated periodicaly will have output time {5..6..7..8} etc. 
0 
Accepts boolean values (0 or 1). 
PeriodicEndCorrection (PeriodicEndCorrection) 
If Periodic time is enabled, this flag determines if the last time step is the same as the first. If PeriodicEndCorrection is true, then it is assumed that the input data goes from 01 (or whatever scaled/shifted actual time) and time 1 is the same as time 0 so that steps will be 0,1,2,3...N,1,2,3...N,1,2,3 where step N is the same as 0 and step 0 is not repeated. When this flag is false the data is assumed to be literal and output is of the form 0,1,2,3...N,0,1,2,3... By default this flag is ON 
1 
Accepts boolean values (0 or 1). 
MaximumNumberOfPeriods (MaximumNumberOfPeriods) 
If Periodic time is enabled, this controls how many time periods time is reported for. A filter cannot output an infinite number of time steps and therefore a finite number of periods is generated when reporting time. 
1.0 

TimestepValues (TimestepValues) 

Temporal SnaptoTimeStep
Modifies the time range/steps of temporal data. This file modifies the time range or time steps of the data without changing the data itself. The data is not resampled by this filter, only the information accompanying the data is modified.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input of the filter. 
Accepts input of following types:
 
SnapMode (SnapMode) 
Determine which time step to snap to. 
0 
The value(s) is an enumeration of the following:

TimestepValues (TimestepValues) 

Temporal Statistics
Loads in all time steps of a data set and computes some statistics about how each point and cell variable changes over time.Given an input that changes over time, vtkTemporalStatistics looks at the data for each time step and computes some statistical information of how a point or cell variable changes over time. For example, vtkTemporalStatistics can compute the average value of "pressure" over time of each point. Note that this filter will require the upstream filter to be run on every time step that it reports that it can compute. This may be a time consuming operation. vtkTemporalStatistics ignores the temporal spacing. Each timestep will be weighted the same regardless of how long of an interval it is to the next timestep. Thus, the average statistic may be quite different from an integration of the variable if the time spacing varies.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Set the input to the Temporal Statistics filter. 
Accepts input of following types:
 
ComputeAverage (ComputeAverage) 
Compute the average of each point and cell variable over time. 
1 
Accepts boolean values (0 or 1). 
ComputeMinimum (ComputeMinimum) 
Compute the minimum of each point and cell variable over time. 
1 
Accepts boolean values (0 or 1). 
ComputeMaximum (ComputeMaximum) 
Compute the maximum of each point and cell variable over time. 
1 
Accepts boolean values (0 or 1). 
ComputeStandardDeviation (ComputeStandardDeviation) 
Compute the standard deviation of each point and cell variable over time. 
1 
Accepts boolean values (0 or 1). 
Tessellate
Tessellate nonlinear curves, surfaces, and volumes with lines, triangles, and tetrahedra.The Tessellate filter tessellates cells with nonlinear geometry and/or scalar fields into a simplicial complex with linearly interpolated field values that more closely approximate the original field. This is useful for datasets containing quadratic cells.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Tessellate filter. 
Accepts input of following types:
 
OutputDimension (OutputDimension) 
The value of this property sets the maximum dimensionality of the output tessellation. When the value of this property is 3, 3D cells produce tetrahedra, 2D cells produce triangles, and 1D cells produce line segments. When the value is 2, 3D cells will have their boundaries tessellated with triangles. When the value is 1, all cells except points produce line segments. 
3 

ChordError (ChordError) 
This property controls the maximum chord error allowed at any edge midpoint in the output tessellation. The chord error is measured as the distance between the midpoint of any output edge and the original nonlinear geometry. 
1e3 

Field Error (FieldError2) 
This proeprty controls the maximum field error allowed at any edge midpoint in the output tessellation. The field error is measured as the difference between a field value at the midpoint of an output edge and the value of the corresponding field in the original nonlinear geometry. 

Maximum Number of Subdivisions (MaximumNumberOfSubdivisions) 
This property specifies the maximum number of times an edge may be subdivided. Increasing this number allows further refinement but can drastically increase the computational and storage requirements, especially when the value of the OutputDimension property is 3. 
3 

MergePoints (MergePoints) 
If the value of this property is set to 1, coincident vertices will be merged after tessellation has occurred. Only geometry is considered during the merge and the first vertex encountered is the one whose point attributes will be used. Any discontinuities in point fields will be lost. On the other hand, many operations, such as streamline generation, require coincident vertices to be merged. Toggle whether to merge coincident vertices. 
1 
Accepts boolean values (0 or 1). 
Tessellate Generic Dataset
Tessellate a higherorder datasetTessellate a higherorder dataset.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Set the input to the Generic Tessellator filter. 
Accepts input of following types:

Tetrahedralize
This filter converts 3d 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.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Tetrahedralize filter. 
Accepts input of following types:

Texture Map to Cylinder
Generate texture coordinates by mapping points to cylinder. This is a filter that generates 2D texture coordinates by mapping input dataset points onto a cylinder. The cylinder is generated automatically. The cylinder is generated automatically by computing the axis of the cylinder. Note that the generated texture coordinates for the scoordinate ranges from (01) (corresponding to angle of 0>360 around axis), while the mapping of the tcoordinate is controlled by the projection of points along the axis.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Set the input to the Texture Map to Cylinder filter. 
Accepts input of following types:
 
PreventSeam (PreventSeam) 
Control how the texture coordinates are generated. If Prevent Seam is set, the scoordinate ranges from 0>1 and 1>0 corresponding to the theta angle variation between 0>180 and 180>0 degrees. Otherwise, the scoordinate ranges from 0>1 between 0>360 degrees. 
1 
Accepts boolean values (0 or 1). 
Texture Map to Plane
Generate texture coordinates by mapping points to plane. TextureMapToPlane is a filter that generates 2D texture coordinates by mapping input dataset points onto a plane. The plane is generated automatically. A least squares method is used to generate the plane automatically.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Set the input to the Texture Map to Plane filter. 
Accepts input of following types:

Texture Map to Sphere
Generate texture coordinates by mapping points to sphere. This is a filter that generates 2D texture coordinates by mapping input dataset points onto a sphere. The sphere is generated automatically. The sphere is generated automatically by computing the center i.e. averaged coordinates, of the sphere. Note that the generated texture coordinates range between (0,1). The scoordinate lies in the angular direction around the zaxis, measured counterclockwise from the xaxis. The tcoordinate lies in the angular direction measured down from the north pole towards the south pole.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Set the input to the Texture Map to Sphere filter. 
Accepts input of following types:
 
PreventSeam (PreventSeam) 
Control how the texture coordinates are generated. If Prevent Seam is set, the scoordinate ranges from 0>1 and 1>0 corresponding to the theta angle variation between 0>180 and 180>0 degrees. Otherwise, the scoordinate ranges from 0>1 between 0>360 degrees. 
1 
Accepts boolean values (0 or 1). 
Threshold
This filter extracts cells that have point or cell scalars in the specified range. The Threshold filter extracts the portions of the input dataset whose scalars lie within the specified range. This filter operates on either pointcentered or cellcentered data. This filter operates on any type of dataset and produces unstructured grid output. To select between these two options, select either Point Data or Cell Data from the Attribute Mode menu. Once the Attribute Mode has been selected, choose the scalar array from which to threshold the data from the Scalars menu. The Lower Threshold and Upper Threshold sliders determine the range of the scalars to retain in the output. The All Scalars check box only takes effect when the Attribute Mode is set to Point Data. If the All Scalars option is checked, then a cell will only be passed to the output if the scalar values of all of its points lie within the range indicated by the Lower Threshold and Upper Threshold sliders. If unchecked, then a cell will be added to the output if the specified scalar value for any of its points is within the chosen range.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Threshold filter. 
Accepts input of following types:
The dataset much contain a field array () with 1 component(s).  
Scalars (SelectInputScalars) 
The value of this property contains the name of the scalar array from which to perform thresholding. 
An array of scalars is required.The value must be field array name.  
Threshold Range (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. 
AllScalars (AllScalars) 
If the value of this property is 1, then a cell is only included in the output if the value of the selected array for all its points is within the threshold. This is only relevant when thresholding by a pointcentered array. 
1 
Accepts boolean values (0 or 1). 
UseContinuousCellRange (UseContinuousCellRange) 
If off, the vertex scalars are treated as a discrete set. If on, they are treated as a continuous interval over the minimum and maximum. One important "on" use case: When setting lower and upper threshold equal to some value and turning AllScalars off, the results are cells containing the isosurface for that value. WARNING: Whether on or off, for higher order input, the filter will not give accurate results. 
0 
Accepts boolean values (0 or 1). 
Transform
This filter applies transformation to the polygons.The Transform filter allows you to specify the position, size, and orientation of polygonal, unstructured grid, and curvilinear data sets.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Transform filter. 
Accepts input of following types:
 
Transform (Transform) 
The values in this property allow you to specify the transform (translation, rotation, and scaling) to apply to the input dataset. 
The value can be one of the following:

Triangle Strips
This filter uses a greedy algorithm to convert triangles into triangle stripsThe Triangle Strips filter converts triangles into triangle strips and lines into polylines. This filter operates on polygonal data sets and produces polygonal output.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Triangle Strips filter. 
Accepts input of following types:
 
MaximumLength (MaximumLength) 
This property specifies the maximum number of triangles/lines to include in a triangle strip or polyline. 
1000 

Triangulate
This filter converts polygons and triangle strips to basic triangles.The Triangulate filter decomposes polygonal data into only triangles, points, and lines. It separates triangle strips and polylines into individual triangles and lines, respectively. The output is polygonal data. Some filters that take polygonal data as input require that the data be composed of triangles rather than other polygons, so passing your data through this filter first is useful in such situations. You should use this filter in these cases rather than the Tetrahedralize filter because they produce different output dataset types. The filters referenced require polygonal input, and the Tetrahedralize filter produces unstructured grid output.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Triangulate filter. 
Accepts input of following types:

Tube
Convert lines into tubes. Normals are used to avoid cracks between tube segments.The Tube filter creates tubes around the lines in the input polygonal dataset. The output is also polygonal.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Tube filter. 
Accepts input of following types:
The dataset much contain a field array (point) with 1 component(s). The dataset much contain a field array (point) with 3 component(s).  
Scalars (SelectInputScalars) 
This property indicates the name of the scalar array on which to operate. The indicated array may be used for scaling the tubes. (See the VaryRadius property.) 
An array of scalars is required.  
Vectors (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 tubes. (See the VaryRadius property.) 
1 
An array of vectors is required. 
Number of Sides (NumberOfSides) 
The value of this property indicates the number of faces around the circumference of the tube. 
6 

Capping (Capping) 
If this property is set to 1, endcaps will be drawn on the tube. Otherwise the ends of the tube will be open. 
1 
Accepts boolean values (0 or 1). 
Radius (Radius) 
The value of this property sets the radius of the tube. If the radius is varying (VaryRadius property), then this value is the minimum radius. 
1.0 
The value must be less than the largest dimension of the dataset multiplied by a scale factor of 0.01. 
VaryRadius (VaryRadius) 
The property determines whether/how to vary the radius of the tube. If varying by scalar (1), the tube radius is based on the pointbased scalar values in the dataset. If it is varied by vector, the vector magnitude is used in varying the radius. 
0 
The value(s) is an enumeration of the following:

RadiusFactor (RadiusFactor) 
If varying the radius (VaryRadius property), the property sets the maximum tube radius in terms of a multiple of the minimum radius. If not varying the radius, this value has no effect. 
10 

UseDefaultNormal (UseDefaultNormal) 
If this property is set to 0, and the input contains no vector array, then default ribbon normals will be generated (DefaultNormal property); if a vector array has been set (SelectInputVectors property), the ribbon normals will be set from the specified array. If this property is set to 1, the default normal (DefaultNormal property) will be used, regardless of whether the SelectInputVectors property has been set. 
0 
Accepts boolean values (0 or 1). 
DefaultNormal (DefaultNormal) 
The value of this property specifies the normal to use when the UseDefaultNormal property is set to 1 or the input contains no vector array (SelectInputVectors property). 
0 0 1 

UpdateSuppressor2
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Set the input to the Update Suppressor filter. 

Enabled (Enabled) 
Toggle whether the update suppressor is enabled. 
1 
Accepts boolean values (0 or 1). 
UpdateTime (UpdateTime) 
none 

Warp By Scalar
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 singlecomponent 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.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Warp (scalar) filter. 
Accepts input of following types:
The dataset much contain a field array (point) with 1 component(s).  
Scalars (SelectInputScalars) 
This property contains the name of the scalar array by which to warp the dataset. 
An array of scalars is required.  
ScaleFactor (ScaleFactor) 
The scalar value at a given point is multiplied by the value of this property to determine the magnitude of the change vector for that point. 
1.0 

Normal (Normal) 
The values of this property specify the direction along which to warp the dataset if any normals contained in the input dataset are not being used for this purpose. (See the UseNormal property.) 
0 0 1 

UseNormal (UseNormal) 
If point normals are present in the dataset, the value of this property toggles whether to use a single normal value (value = 1) or the normals from the dataset (value = 0). 
0 
Accepts boolean values (0 or 1). 
XY Plane (XYPlane) 
If the value of this property is 1, then the Zcoordinates from the input are considered to be the scalar values, and the displacement is along the Z axis. This is useful for creating carpet plots. 
0 
Accepts boolean values (0 or 1). 
Warp By Vector
This filter displaces point coordinates along a vector attribute. It is useful for showing mechanical deformation. The Warp (vector) filter translates the points of the input dataset using a specified vector array. The vector array chosen specifies a vector per point in the input. Each point is translated along its vector by a given scale factor. This filter operates on polygonal, curvilinear, and unstructured grid datasets. Because this filter only changes the positions of the points, the output dataset type is the same as that of the input.
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
This property specifies the input to the Warp (vector) filter. 
Accepts input of following types:
The dataset much contain a field array (point) with 3 component(s).  
Vectors (SelectInputVectors) 
The value of this property contains the name of the vector array by which to warp the dataset's point coordinates. 
An array of vectors is required.  
ScaleFactor (ScaleFactor) 
Each component of the selected vector array will be multiplied by the value of this property before being used to compute new point coordinates. 
1.0 

Youngs Material Interface
Computes linear material interfaces in 2D or 3D mixed cells produced by eulerian or ALE simulation codes Computes linear material interfaces in 2D or 3D mixed cells produced by Eulerian or ALE simulation codes
Property  Description  Default Value(s)  Restrictions 
Input (Input) 
Accepts input of following types:
The dataset much contain a field array (cell) with 1 component(s). The dataset much contain a field array (cell) with 3 component(s).  
InverseNormal (InverseNormal) 
0 
Accepts boolean values (0 or 1).  
ReverseMaterialOrder (ReverseMaterialOrder) 
0 
Accepts boolean values (0 or 1).  
OnionPeel (OnionPeel) 
1 
Accepts boolean values (0 or 1).  
AxisSymetric (AxisSymetric) 
1 
Accepts boolean values (0 or 1).  
FillMaterial (FillMaterial) 
1 
Accepts boolean values (0 or 1).  
UseFractionAsDistance (UseFractionAsDistance) 
0 
Accepts boolean values (0 or 1).  
VolumeFractionRange (VolumeFractionRange) 
0.01 0.99 

NumberOfDomainsInformation (NumberOfDomainsInformation)  
VolumeFractionArrays (VolumeFractionArrays) 
An array of scalars is required.  
NormalArrays (NormalArrays) 
An array of vectors is required.The value must be field array name.  
OrderingArrays (OrderingArrays) 
An array of scalars is required.The value must be field array name. 