Table of Contents
This module is only available in the pro-version of the library.
Matrix graphs are used to visualize the content of a rectangular matrix. Each entry in the matrix is mapped to a specific color which are then displayed in a rectangular plot corresponding to the size of the input matrix. The size of each module (corresponding to a matrix entry) is user customizable. There are two types of possible modules; circular and rectangular shape.
In order to achieve high quality rendering when circles are used the matrix module makes use of an optional (user settable) super-sampling to achieve an anti-alias effect to take the edge of the filled circles.
The color assignment to each value is controlled by the selected color map. The library first establish the min and max value in the matrix and then equates the min value with the "lower" end of the specified color map and the max value with the "higher" end of the color map. All values in between is linearly interpolated to a have a color between the "low" and "high" end in relation to the value (which are guaranteed to be between the min and max value previously established). There are several pre-defined color maps available as well as completely user configurable color maps.
The (optional) legend shows the range associated to each color in the corresponding plot.
The library supports mesh interpolation. Mesh interpolation which by itself doesn't produce any new data but can help produce smoother plots by creating "false" interpolated values in between the original entries in the matrix. This is similar to the Matlab (tm) command interp2
The overall structure and capabilities of matrix graphs follows that of other graphs in the library, e.g. Windrose plots, in that a graph can have multiple plots, title, footers, texts, icons, image backgrounds etc. Figure 22.1 shows a medium complex example of two matrix plots in a matrix graphs which uses both a background image, icon (the logo in the top left corner), timing of the graph and free positioned text. We have also used a small degree of alpha blending in the plots just to let the background "shine" through a little bit. The two plots shows the same data but uses different color maps.
Figure 22.1. A medium complex example to shows some capabilities of matrix plots
The library offers an extensive range of formatting for the appearance of the plot when it comes to adjusting exactly how the colors are used. There are several built in color maps as well as the possibility to specify manual color maps and adjusting the contrast (scale range) of the plot.
Both manual and automatic scale range setting
Customizable legend position and layout
Row and column legends (edge labels)
Several built in color maps (22)
Option for manual specified color maps
Adjustable color contrast
Layout classes to position multiple plots in the sam graph
Both circular and rectangular module type
Mesh interpolation of input data
Flexible sizing of matrix plots both manual, automatic and a mix of them
Alpha blending support for matrix plot
All the usual graph support for background images, text objects and icons