QtPlaskin is a graphical interface to analyze results from a plasma kinetic code such as ZdPlasKin (1). It supports both a specific data format based on HDF5 and importing directories with certain filesets that can be written from a running FORTRAN code.
QtPlaskin was developed by Alejandro Luque (see original version) at the Instituto de Astrofísica de Andalucía (IAA), CSIC and is licensed under the LGPLv3 License. The development of current Fork is open-sourced. Feel free to contribute!. For any questions you can look at the Issues or join the Community Chat below:
QtPlaskin runs in Linux, Mac OS X and Windows. QtPlaskin is now a Python library. Install it from GitHub with:
git clone https://github.com/erwanp/qtplaskin.git
cd qtplaskin
pip install -e .
-e
is for the editable version. Keep it up to date with git pull
in the
qtplaskin
directory
If the install procedure does not work, please refer to the former installation procedure. See the file INSTALL.txt for information on the libraries that must be installed in your system and how to obtain them.
Installing the library creates a script that you can use from the command line to
start the QtPlaskin GUI. Just select the folder where ZdPlaskin created the qt_*.txt
files (for instance Results/TestCase/
in the example below):
qtplaskin Results/TestCase/
Remember that you need to tell your ZdPlaskin user code to generate the qt_*.txt
files:
see the Generate Qt Files
section below
Without starting the QtPlaskin GUI interface, you can still use the functions defined in QtPlaskin to load the data generated by ZdPlaskin:
from qtplaskin import FastDirData
d = FastDirData([results folder])
# access d attributes:
d.plot('CO') # to plot
d.get('...') # to retrieve data
With the latest version of ZDPlaskin you can use
call ZDPlaskin_set_config(QTPLASKIN_SAVE=.true.)
Then you can import the data of your simulation into QtPlaskin by using File -> Import from directory... in the program menu.
(1) ZdPlaskin is a computer code developed by S. Pancheshnyi, B. Eismann, G.J.M. Hagelaar and L.C. Pitchford, http://www.zdplaskin.laplace.univ-tlse.fr (University of Toulouse, LAPLACE, CNRS-UPS-INP, Toulouse, France, 2008).
Improvements over A. Luque's initial version:
-
Dynamic tooltips on plots to analyze graphs with dozens of different lines
-
Synchronized timescales over all plots, and dynamic ticks to deal with nanosecond to microsecond ranges
-
ported to PyQt5 to keep up with the latest Python environnements
-
Python3 compatible
-
Made qtplaskin an installable Python library
-
call qtplaskin from the command line with with
qtplaskin $FOLDER
to analyze a given directory -
faster Results folder loading using Pandas instead of Numpy