QtiPlot - Data Analysis and Scientific Visualisation

A short example of how to create and customize a 2D plot using a very simple Python script. Please watch this video available in our YouTube channel.

A short example demonstrating how easy it is to draw and customize a sphere with just a few lines of Python code.

An example demonstrating how easy it is to perform analysis tasks in QtiPlot using simple Python scripts.

In this example a hidden table is generated, filled with data, plotted and analysed using just a few lines of Python code.

One may note that most of the code is used to generate the test exponential decay data, whilst for the data fit operation itself only six lines of code are needed.

For a detailed example showing how to completely automate analysis tasks in QtiPlot, please download this Python script. It can be used in order to verify the accuracy of the curve fitting algorithms in QtiPlot. The data files used in this example were retrieved from the Statistical Reference Datasets Project of the National Institute of Standards and Technology (NIST). In order to run this example, first you need to download and unzip the nonlinear regression test files and after that unzip the downloaded script and launch QtiPlot from a command interpreter:

qtiplot -x strd_nist_fit.py

If you don't want to display QtiPlot user interface, run the example with the -X option:

qtiplot -X strd_nist_fit.py

Running Python scripts from QtiPlot opens the possibility to use powerfull existing scientific tools, like SymPy, SciPy or rpy2, thus bringing unlimited data analysis power.

This screenshot shows that QtiPlot automatically imports SymPy module if available. The example script from the screenshot demonstrates how QtiPlot turns into a full-featured computer algebra system (CAS) thanks to SymPy.

If SciPy or rpy2 modules are locally installed QtiPlot also imports essential parts like the scipy.special functions, for example.

This short sample script draws the first six special Struve functions provided by the SciPy module.