A Python package to control the Matisse 2 TS.
A Python package to control the Matisse 2 TS laser for the University of Washington's Optical Spintronics and Sensing Lab.
Requirements: Python 3.7+, NI VISA, PyVISA, pySerial, SciPy, matplotlib, PyQt5
Tested on Windows 10 (x64).
$ pip install matisse-controller
To launch the GUI, connect the Matisse and a supported wavemeter, and then run:
To configure the behavior of the program, click the 'Configuration' menu option from the main GUI, or run:
The GUI uses a Python API to control the Matisse. If you're writing a Python program, just import the subpackages
that contain the APIs you want. The
matisse subpackage contains Matisse-related components, the
contains configuration functionality, etc.
After checking out the repo, run
pipenv install --dev to install dependencies. Using a virtual environment is
To install this package onto your local machine, run
pip install -e ..
Adding features to the Matisse class
The standard way of interacting with the Matisse outside of the existing API is to use the
Matisse.query method. The
Matisse implements several commands that run asynchronously, like motor movements, so if you want to run these
synchronously, you must do it on your own (like checking the motor status until it's idle again).
Long-running tasks should be executed in a thread that can be started and gracefully stopped from the Matisse class. Currently, fetching a measurement from the wavemeter is a relatively expensive process, so avoid doing this too much if possible.
Adding another wavemeter
Currently I've only implemented an interface for the WaveMaster, but any class will do, as long as it implements the
get_wavelength methods. The
get_raw_value method should return a value representing exactly
what is seen on the wavemeter display (this might not be a measurement), and the
get_wavelength method should always
return a floating-point number representing the latest measurement from the wavemeter. The WaveMaster implementation
blocks the thread until a value is returned from the instrument. Additionally, please ensure any code you write that
communicates with instruments is thread-safe.
Adding features to the GUI
Logging and UI updates should have top priority, so take care not to block the UI thread. Here's the process I use:
- Add a menu action under
setup_menusand connect it to a Qt slot under
setup_slots, to be executed on the main thread later.
- Do UI updates in this slot, if you need a long-running task that also updates the UI, use a subclass of QThread with a slot (see LoggingThread, StatusUpdateThread for examples).
- For long-running tasks that do not need access to the UI, submit a runnable object to the ControlApplication's
instance of ThreadPoolExecutor. Hold a reference to the Future it gives you and call
add_done_callbackon it, passing in
ControlApplication.raise_error_from_futureif you want to log errors from that thread. For an example of a method that runs tasks one-by-one on the Matisse, see
Adding another PLE procedure
Currently I've only implemented a PLE scan for the Andor Shamrock 750. If you'd like to implement your own PLE procedure,
create a separate Python package with a class that has the methods
analyze_ple_data. It's up to you to implement the scanning logic for your particular spectrometer and CCD setup.
Modify the Matisse class
__init__ method to use your chosen wavemeter and an instance of your PLE scanning class.
Bug reports and pull requests are welcome on GitHub at https://github.com/lucis-fluxum/matisse-controller.
The package is available as open source under the terms of the MIT License.
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