![]() |
iTool User's Guide: Working with Vectors |
![]() |
The iVector window is a self-contained vector visualization and manipulation device. You can import and export vector data, and modify and manipulate vector data. For more information on the basic iVector interface and its layout, see iTools Interface Reference.
By selecting Edit Properties from the iVector tool, you may modify your vector properties. You may modify your vector visualization's name, description, grid units, style, arrow properties, direction convention, as well as the show/hide properties. For more information on editing properties in the iTools, see Visualization Properties.
If you have a vector dataset with a large number of vectors, and thus very high resolution, seeing individual vectors may be difficult. Subsampling allows you to decrease the number of displayed vectors, making it easier to view the vector dataset.
You can set subsampling using keywords to iVector from the command line or from the iVector visualization's property sheet.
The following table shows subsampling functions and how you can invoke them.
For example, a subsampling factor of 2 for both x and y indicates that every other vector will be displayed. A subsampling factor of 10 indicates that one out of every 10 vectors will be displayed.
You can also enable autosubsampling. Autosubsampling will automatically decrease the number of displayed vectors, based on the current view zoom factor. Zooming out (a smaller zoom percentage) will increase subsampling factors, in turn decreasing the number of displayed vectors. Zooming in (a larger zoom percentage) will decrease subsampling factors, in turn increasing the number of displayed vectors. The following table shows the two ways to enable autosubsampling.
Imagine you have global wind data and want to color each wind vector according to the surface temperature at that location. In a case like this you want to visualize your vector data using one dataset for the magnitude and direction, and another dataset for the color of each vector.
There are two ways to do this:
Your auxiliary dataset can be either integer or floating-point type. For either type, the data will automatically be scaled into the 0-255 range to be used as the color indices. These color indices are then converted into actual colors as given by your current palette for the vector visualization.
If you insert a colorbar (Insert Colorbar), the colorbar axis will have the correct (original) range for your auxiliary dataset.
IDL Online Help (March 01, 2006)