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Module category: Converter



Scalar2Vector

This module combines scalar data given at the input ports to vector data. It can also combine structured scalar data to packed RGBA data. If input data have attributes they are summarized where it makes sense.

Scalar2VectorModule.png

When combining to packed RGBA data the first three components are interpreted as red, green and blue respectively. If connected, the opacity (alpha) component is taken from the fourth input port, otherwise it is computed as the average of red, green, and blue. For generating RGBA data, each component is normalized such that its minimum value is mapped to 0 and its maximum value to 1. When determining these extremal values, one value (as set by the parameters) is ignored.

Scalar2Vector is available since snap-2000-10 on all supported platforms.

Parameters

Name Type Description
normalizeMode Choice Determine the fine-tuning of the normalization of data for the output-port outPortRGBA
Do not: No normalization
Ignore MAX_FLT: Calculate min/max of all components but do not consider values equal to MAX_FLT. Then normalize the colors in these bounds.
Ignore user defined value:Calculate min/max of all components but do not consider values equal to parmeter userIgnoreValue. Then normalize the colors in these bounds.
User defined bounds: Normalize the colors in the bounds given by the parameters userNormalizeMin and userNormalizeMax
userIgnoreValue Scalar Number for use in normalizeMode Ignore user defined value
userNormalizeMin Vector Vector for use in normalizeMode User defined bounds
userNormalizeMax Vector Vector for use in normalizeMode User defined bounds

Input Ports

Name Type(s) Description
inPortU Float
Float
Scalar input for U/red
inPortV Float
Float
Scalar input for V/green
inPortW Float
Float
Scalar input for W/blue
inPortA Float Scalar input for alpha/opacity

Output Ports

Name Type(s) Description
outPort Vec3
Vec3
Vector output
outPortRGBA RGBA_Data Packed color output

Examples

A "classical" combination of three modules is: ReadStar, FixUsg and CellToVert. Whenever results of StarCD data are analysed, this combination of modules is needed.

ReadStar reads a dataset from two files: A file16 for the grid and either a file29 or a file09 for the data. With the field1, field2 and field3 parameters of ReadStar the variables which are available at the output ports are selected. In this example the velocity components U, V, and W are selected.

FixUsg eliminates all unused or duplicate points and cells with zero volume from the data set. Caution: All data sets must also be passed through FixUsg to remove the unused cell's data. Multiple data sets can be filtered through one CheckUsg module.

StarCD calculates finite Volumes, i.e. one value per cell. Since most visualisation modules need per-vertex data, CellToVert interpolates the data to vertices. This is done with all three outputs of CheckUsg.

Scalar2Vector combines the U, V and W component to one vector data object.

The grid and the vector data are connected to TracerUsg , which computes streamlines.

Below you see the example Scalar2Vector.net and the resulting output in the Renderer. Here we use RWCovise instead of ReadStar.

Figure: covise/net/examples/Scalar2Vector.net
ScalarVect.png

ScalarVectRenderer.png

Consider some examples how attribute names and their attribute values can be summarized. Note that in the examples we have only one attribute for each input port but there can be an arbitrary number of them.
Input attribute names Input
attribute
values
Output attribute name Output
attribute
value
XVelocity
yvelocity
ZVELOCITY
foo
bar
foofoo
XyZvelocity (foo,bar,foofoo)
VelocityU
velocityV
VELOCITYW
foo
foo
foo
velocityUVW

foo
XVelocity
velocityY
Z-VELOCITY
foo
foo
foo
Summary of attributes not possible, attributes leave unchanged


Authors: Martin Aumüller, Ruth Lang, Daniela Rainer, Jürgen Schulze-Döbold, Andreas Werner, Peter Wolf, Uwe Wössner
Copyright © 1993-2016 HLRS, 2004-2014 RRZK, 2005-2014 Visenso
COVISE Version 2016.3