QtiPlot - Data Analysis and Scientific Plotting

QtiPlot 0.9.7 released: click here for a preview of the new features!

Scientists often need to use data analysis and plotting software. The purpose of this project is to develop an open source platform independent alternative to proprietary scientific software like Origin, SigmaPlot or Igor Pro. QtiPlot can be successfully used for teaching as well as for complex data analysis and visualisation and is being used in companies, universities and reseach institutes all over the world. QtiPlot is being actively improved, all your suggestions to our "wish to" list and all your contributions are most welcome!

Features:

  • QtiPlot is cross-platform: it can be used on Windows, Linux/Unix and Mac OS X systems.
  • QtiPlot is fully scriptable via Python, which gives you the possibility to use powerfull existing scientific tools, such as SciPy, thus bringing unlimited data analysis power.
  • OpenGL based 3D plotting: height maps, user defined functions and parametric surfaces.
  • Publication quality 2D plots: Error Bars, Multilayer Plots, Bar Plots, Pie Plots, Vector Plots, Contour and Image Plots
  • Statistical Plots: Box/Whiskers Diagramms, Histograms
  • Easy export of plots to vector formats (EPS, PS, PDF, SVG) and to various raster image formats (BMP, JPG, PNG, TIFF etc ...)
  • Powerful and versatile spreadsheets and calculations in column-logic
  • Easy ASCII-Import/Export of single or multiple files
  • Linear and non-linear curve fitting with weighting and estimation of statistical errors of the fit-parameters, using Levenberg-Marquardt  Least-Squares Algorithm or Nelder-Mead simplex minimization algorithm. 
  • Multi-peak fitting with Gaussian and Lorentzian peak profiles
  • Built-in data analysis routines: statistics, sorting, FFT, data smoothing (Savitzky-Golay, FFT smoothing, and moving window average), data filtering (low/high/band pass and band block filters), convolution/deconvolution, correlation, interpolation, numerical integration/differentiation, etc...
  • Matrices optimized for image analysis
  • Templates support: all the settings for plots (2D/3D), tables and matrixes can be saved to ASCII files and restored later on for a fast editing process
  • Project files based on folders, a powerful project explorer with extensive built-in features: drag and drop, searching facilities, etc...
  • Import of Origin 7.5 files

Dependencies:

QtiPlot uses the following libraries: Qt, Qwt (5.1), QwtPlot3D, GSL, muParser, zlib (1.2.3), and liborigin.
To enable Python scripting support, QtiPlot uses Python 2.5, SIP and PyQt v4.

License:

QtiPlot is distributed under the GNU General Public License. Thus it is "free software". "Free software" is a matter of liberty, not price. To understand the concept, you should think of "free" as in "free speech", not as in "free beer". "Free software" is also often called Open Source, FOSS, or FLOSS.

Free software is a matter of the users' freedom to run, copy, distribute, study, change and improve the software. More precisely, it refers to four kinds of freedom, for the users of the software:
  • The freedom to run the program, for any purpose (freedom 0).
  • The freedom to study how the program works, and adapt it to your needs (freedom 1). Access to the source code is a precondition for this.
  • The freedom to redistribute copies so you can help your neighbor (freedom 2).
  • The freedom to improve the program, and release your improvements to the public, so that the whole community benefits (freedom 3). Access to the source code is a precondition for this.

Supported platforms:

QtiPlot should work on all systems supported by Qt.

Installation:

Have a look at the qtiplot.pro project file. It is prepared for building the application in Win32 and Unix/X11 environments. If you don't know what to do with it, read the INSTALL notes and/or Trolltechs qmake documentation.

Mailing list:

For all kind of QtiPlot related questions there is a mailing list dedicated to the users.