Scientific measurement interface
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The main features of TeraPy are:

Flexible measurement definition

Measurement procedures are defined graphically as sequences of configurable events. Sequences can be saved as XML files.

TeraPy comes with a set of events, which allow you to build a wide range of measurement sequences. Should you however not find one for your needs, TeraPy's architecture makes it easy to add your own with little coding. Examples are provided in the documentation.

Modular device driver architecture

Your instrument has a Python driver? TeraPy can control it. All you need is a device module that provides some basic functions in a standardized way.

Advanced filter banks

Data post-processing can done within TeraPy's interface with fully customizable filter banks. You can then save the result to any supported data format.

Versatile plotting capabilities

TeraPy can display data thanks to a flexible plotting interface. Currently, plotting modules relying on matplotlib are provided for 1D and 2D data.

Tracking of physical units

TeraPy remembers the physical units of your data. Changes propagate automatically through the whole post-processing chain.

TeraPy uses the Pint unit management package.

Extensible file input/output management

TeraPy reads and saves data with dedicated file filters. Filters included in the package provide read and save support for HDF5, Microsoft Excel spreadsheets and plain text files.

cross-platform compatibility

TeraPy is written in Python and uses the wxPython GUI library. It is therefore compatible with Windows, Linux and Mac OS.