|PIVMat Getting Started|
The PIVMat Toolbox for Matlab contains a set of command-line functions to import, post-process and analyse 2- and 3-components vector fields from PIV (particle image velocimetry), stereo-PIV, DIC (digital image correlation) SS (synthetic schlieren) or BOS (background-oriented schlieren) applications.
The PIVMat Toolbox enables to handle and perform complex operations over large amount of velocity fields, and to produce high-quality vector/scalar outputs. This toolbox in itself does not perform any PIV computations.
PIVMat supports files from:
By default, PIVMat can import files from DynamicStudio, DPIVSoft, VidPIV and MatPIV. In order to import files from DaVis (VC7 files), it is necessary to install an additional package: ReadIMX. See PIVMat installation
The first step is to import some vector fields into a MATLAB structure array. The simplest way to import data is to double-click on a file on the Current Directory Browser. You can also import data using the function loadvec. Each element of this structure array contains the two matrices of the velocity components, the coordinate system, and some additional informations (units, axe names, PIV parameters...)
Once imported, the velocity fields can be displayed using showf, or converted into scalar fields using vec2scal.
A sample directory, named sample, with 4 experimental series of PIV fields, is provided with the toolbox to test the following examples. These examples are given for DaVis files (VC7 format), but they also work with any other file format supported by PIVMat).Example 1
v = loadvec('B00001.VC7'); % loads the file B00001.VC7 showf(v); % displays it curl = vec2scal(filterf(v,2),'rot'); % computes the filtered vorticity figure, showf(curl); % displays it
Various statistics may be computed from vector and scalar fields:
v = loadvec('*.vc7'); % loads all the VC7 files curl = vec2scal(filterf(v,2),'rot'); % computes the filtered vorticity showf(curl); % displays it as a movie showf(averf(curl)); % displays its ensemble-average histscal_disp(curl); % displays its histogram statf(v) % computes some statistics
Go to the Frequently Asked Questions section or to the Function by category section to learn more about this toolbox.