Posts

What is YOUR machines processing speed?

Hi!
How fast is your computer running PIVlab? There is a script included with PIVlab, that allows to test your computers processing speed. Just run Testspeed.m from the command window to see your results. You can post them as a comment.  Here are my results:
Surface Pro 3 Intel Core i5-4300U @ 1.9GHz 2.5GHz
8 GB RAM
64 bit Win 8.1 Pro
MATLAB R2014b 64 bit

DCC calculation speed: 13.8081 ms
DFT calculation speed: 0.30431 ms
Linear interpolation speed: 0.56215 ms
Spline interpolation speed: 1.9602 ms

PC Intel Core i7-2600K @ 3.4GHz
16 GB RAM
64 bit Win 7 Pro
MATLAB R2014b 64 bit

DCC calculation speed: 6.0144 ms
DFT calculation speed: 0.28481 ms
Linear interpolation speed: 0.53755 ms
Spline interpolation speed: 1.1093 ms

Acer Switch5 Intel Core i5-7200U CPU @ 2.50GHz
8 GB RAM
64 bit Win 10 Home
MATLAB 8.6.0.267246 (R2015b)

DCC calculation speed: 4.1283 ms
DFT calculation speed: 0.18304 ms
Linear interpolation speed: 0.25262 ms
Spline interpolation speed: 0.8413 ms

PIVlab 1.42 update

Download @ Matlab File Exchange: https://de.mathworks.com/matlabcentral/fileexchange/27659-pivlab-time-resolved-particle-image-velocimetry--piv--tool Fixed a graphics issue in the user interface  As my latest Matlab is version R2015b, I cannot check how well PIVlab runs with more recent Matlab releases. Any issues...? I might consider to start a new "crowd funding" for PIVlab if there are issues. This would help me to collect the necessary 70 USD for an update of Matlab (which would enable me to update PIVlab).

PIVlab on the playground...

Image
This is a quick and dirty analysis of my daughters on the playground. Solid body rotation X-D.

PIVlab direct download

Hi everybody! For those who do not want to register on the Matlab website in order to download PIVlab, I added a direct link to the zip archive (see the column on the right side). You can also click here to get the zipped PIVlab toolbox:

http://william.thielicke.org/PIVlab/PIVlab.zip

There were no updates of PIVlab since quite a while. The reason is that I am currently not working with particle image velocimetry after I finished my PhD. That is a pity. But the good thing is that I converted one of my other hobbies into a profession: Since 2014, I am working as a mechanical design engineer at TobyRich GmbH. Over there, I am responsible for the design of fixed-wing drones, which is - similar to doing PIV - a lot of fun.
I am sorry that (in most cases) I can not react to your emails or forum entries. My life is currently filled up with too many other things that require my attention.
Success with your analyses!!

PIVlab 1.41 - now 10x faster processing!

Recently, Sergey, a Junior Researcher at the ISSP RAS contacted me and told me that he found a way to make PIVlab (specifically the DFT window deformation part) much faster. He rewrote PIV_FFTmulti.m in a way that doesn't use 'for loops' anymore. The result is a heavily improved processing speed of PIVlab. I tested MATLAB versions 2011a, 2014b and 2015a. The speed was improved by a factor between 7.9 and 10.6 for a 'standard analysis' with three passes. Improvements up to a factor of 30 seem possible.

Thanks a lot Sergey, this will save a lot of people a lot of time!!

Download: http://www.mathworks.com/matlabcentral/fileexchange/27659-pivlab-time-resolved-particle-image-velocimetry--piv--tool

PIVlab 1.4

I just uploaded the 1.4 release (compatible with R2014b and earlier). Download it here:
PIVlab1.4

PIVlab is now also available as 'App'. You can install it in Matlab by double-clicking on 'PIVlab.mlappinstall'.

Features:
MATLAB R2014b compatibility (yaay!)Backwards compatible (the oldest version I could test is R2011a, but it should also work with much older releases)Improved speed of FFT and the spline window deformation (due to some changes in R2014b)Speed testing tool (run Testspeed.m to benchmark your hardware)New default colormap ParulaPackaged app makes installation and execution simplerSeveral minor fixes / improvements

Working on r2014b release...

I am making progress with the r2014 update of PIVlab, several incompatibilities are fixed already. This requires some extra attention, because PIVlab must stay compatible with earlier Matlab releases. I think that I will be ready to post a beta release of PIVlab 1.4 at the end of this week.