plot.py is an open source application which is a measurement data visualization and treatment framework. It provides the option to include new data types easily for array based data analysis and data plotting. The data analysis that Plot.py provides is primarily based on python standards Numpy and Scipy. The data model is derived from a Numpy ndarray class which provides automatic error propagation, to make user specified data treatment easy. The data visualization which Plot.py provides is made using the gnuplot software which gives users full control to create custom designs for their data plots. plot.py has versions available for Windows, Mac OS X and Linux based distributions.
To get started, select the data-files to evaluate using the menu entries for the desired data-type. You can Open templates, save database, import/export snapshots, print results, change active session and transfer database to session via the File menu.
The Plot tab on the main interface provides an overview of all imported plots, including a list containing the source file name. The toolbar on top, allows you to view first and next plot, apply current plot settings to all sequences, turn mouse navigation on/off, add/remove plot from multi-plot list, save the current state of the measurement and load a state for measurement. The Multi-plot tab adds the active/all plots from this file to the Multi Plot list. When you press the Multi Plot button from the top toolbar, every item in this list will be plot together.
The Dataset Info tab provides the source path from where the data is being read, the information read from headers and Lattic Parameters.
You can perform the following tasks from the data Treatment drop down menu: Fit data (fits functions to the dataset), Filter the data to define filters for excluding points from the plot, transform the units/dimensions, combine points, view color coded points and remove the active plot.
plot.py works on Windows XP, Windows Vista, Windows 7, Mac OS X and Linux based operating system such as Ubuntu, Debian and Redhat.