download
introduction
first steps
how to
documentation
scripting tutorial
trouble shooting
javadoc
imprint
For single pixel ensemble correlation, you need hundreds or even thousands of small images of a steady flow. The interrogation window size can then be reduced to a single pixel (see Westerweel et al., Exp Fluids, 37:3 375-384, 2004 for details). Single pixel ensemble correlation (or two-point correlation) is escpecially useful, if you want to measure steady flows at high magnifications, e.g. in microfluidics. Load the files that you want to process into the "Files" window and select them. In the "Settings" window, open the tab PIV - Single Pixel Correlation and modify the parameters. Start the evaluation by choosing PIV - run single-pixel-sum-of-correlation from the menu bar. You are asked about a filename for the output. Wait until the link to the result file is added to the list of files in the "Files" window.
Single pixel ensemble evaluation of 1000 64×64 pixel images with sparse seeding
In the "Settings" window, open the panel Vector Processing - Profile Extraction and modify the parameters. Open a velocity field and display the context menu by right clicking somewhere on the vector plot. Select draw profile line. Set the first end point of your velocity profile with the left mouse button. Keep the button pressed and drag the mouse to draw a line. Release the mouse button to mark the end point of the profile. The velocity field is interpolated along the line. Depending on your settings on the Vector Processing - Profile Extraction panel, some profile properties are printed into the "Cmd" window. From the area of the profile you may derive a flow rate.
A velocity profile.
Display the context menu of a vector field plot (right mouse button). Select export as pixel image for pgm, tiff, and png or export as vector graphics for swf, emf, svg, eps, and pdf.
Display a PIV image and right click somewhere in the image to display the context menu. Select show correlation map. The correlation function is calculated for a rectangle that has its upper, left corner at the position of the mouse. At the moment, this function is only supported for double images. The size of the interrogation area is defined on the PIV - PIVware - Interrogation Window panel. Only the parameters Interrogation window width and Interrogation window height of the first pass are considered. The magnification of the correlation function is identical to the image magnification (set on the Preferences - Image Display panel). The correlation functions float on top of your image. You can delete them by clicking on them.
A correlation function of 64×64 pixel.
You can use the method
public void setExportCorrFunction(boolean export,
int num,
int pass)
of the class jpiv2.Settings to switch the export of a specific correlation function on. Therefore, prior to the PIV evaluation, execute the line jpiv.getSettings().setExportCorrFunction(true,420,1); in the "Cmd" frame. Adjust the parameters to your needs, refer to
the source code documentation for details.
Switching on the export of the correlation function of the 419th vector (second pass, counted from top left).
ImageJ plot of an exported correlation function.
At the AHD Laboratory of the TU Delft, you can use JPIV as a front-end for the command line PIV analysis package PIVware, by Jerry Westerweel. PivWare is integrated into JPIV via two scrips. They are stored in the directory /usr/local/pivware/jpiv/jlib/jsc/. Define the jlib directory as your jpiv library directory, as described in the documentation section. The two scripts pivware_piv_evaluation.jsc and pivware_tools_collection.jsc should be directly accessible via the Script menu in the menu bar. Execute them, to see a description.
Example:
Use the PIVware tools script, to calculate the vorticity distribution of your flow field. First, select some velocity data files in the "Files" window. Execute the script by choosing Script - pivware_tools_collection from the menu bar. The following dialog appears.
The PIVware vector processing dialog.
Select the command flipy | vortlp | flipy and press execute. Afterwards you are asked about an output filename. Wait until the result appears in the "Files" window. You can visualize the vorticity in the vector plots as a color coded background. Just expand the tree nodes in the "Settings" frame to see the "Preferences - Vector Plot" panel. Select Color coding for the background and set the Data column to 4. Deselect color coding for Vectors and choose a dark vector color. Now display one of the post-processed vector fields.