Module category: Converter

• Scalar2Vector
  • Parameters
  • Input Ports
  • Output Ports
  • Examples

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.

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

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