QtiPlot - Data Analysis and Scientific Visualisation
|Try for free|
A short example demonstrating how easy it is to draw and customize a sphere with just a few lines of Python code.
Automated Data Analysis
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:
If you don't want to display QtiPlot user interface, run the example with the -X option:
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.