Project page





Hosted by:

SourceForge Logo


Releases
27 Mars 2004: py4dat_0.4 :
maintenance release.
24 June 2003 :py4dat_0.3 : Changing pens and labels made easy. Serialisation works fine for  graphics objects and data ones : they are connected correctly when reloaded. Locally defined functions are marshalled.. 

(read more..)

CVS News

11/6/2003      
improved serialisation....

Once you have installed a
Py4dat release, you can update it with the latest features from CVS repository. Click here to
read more ....





The Py4dat/PyDVT Home Page 

  Introduction



PyDVT is a set of  powerful data visualisation widgets, and data abstraction frameworks written by Alexandre Gobbo during a short stay at ESRF. The original PyDVT home pages are accessible on the ESRF web pages.
There you will find a lot of good documentation for using PyDVT in your applications. You will also find the original packages, availables for many platforms.

Py4dat is an application built on PyDVT that allows data manipulation. It has also a window, called MLab, where you have a sort of python shell by which you can interact with py4dat from the command line.  You can, by this mean, import whatever python module you want, manipulate data, write formulas, functions, execute them to operate on datas, and display graphically data in many formats. You can download this package from the pydvt project pages at sf.net.

  Installation of Py4dat

If you are not interested with the MLab fonctionalities fo Py4dat you can grab the PyDVT packages from its original location  on the ESRF web page
 Otherwise for Linux (python2.2, pyqt, pyqwt, qt3.xx, Numeric, PIL) : just grab the latest version of the py4dat package archive at sourceforge.net . It contains  both PyDVT widgets and the Py4dat project.
Untar the archive. The launching script is  Py4dat/WRAPPERS/py4dat. You have to edit such script and change the variable
PACKAGE_HOME to reflect the actual location of the package.

  Demo scripts for MLab


The MLab plugins offer many fonctionalities, the documentation is not rich, however a good way to familiarize with MLab is to try these demos :
These demo are runned copying and pasting their contents in the MLab window. You can run the demo line by line
by pressing simultaneaously <Shift>+<Enter> when the cursor is on the line, or a whole set of selected lines always by
pressing <Shift>+<Enter>.




  COPYRIGHT


ESRF Licence.... read more....


  The Latest Py4dat/PyDVT news








  •          27 March 2004 :
py4dat_0.4 released : Maintenance release.
Serialised workspaces can be reloaded, or saved, from the py4dat fileMenu.


  •          24 June 2003 :
py4dat_0.3 released : Added a properties-editor menu to GraphView.
User can easily change the Pens and labels for 1d graphs.

Now serialisation works fine.
Graphics objects and data ones are connected correctly when reloaded.

Improved serialisation.
The workspace may now contain function objects that are properly
marshalled. The others variables are pickled as before.
The import statements are traked and saved so that the loaded workspace
should work properly. This is an extremely useful feature
to port complicated scientific packages to non-experienced user.
The programmer can prepare a workspace where all the needed modules
are loaded, and some good scripting is done to describe some
scientific model.
Then the workspace can be dumped and the end-user can later reload it
and just execute the top level lines ; all the other symbol and objects
being reloaded as they were defined in the previous session.
Try to load this workspace with the instruction
MLab.LoadMLab("mlabdemo.nb")
 
 

  • 28 May 2003 : py4dat_0.2 released : implements serialisation for 1D graphical objects