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 7 and 10 (x64).
$ pip install matisse-controller
If you plan on using PLE features with Andor instruments, copy the required DLL files from the Andor SDK into
[package install dir]/shamrock_ple/lib (see the README in that directory for more details)
To launch the GUI, connect the Matisse and a supported wavemeter, and then run:
$ matisse-controller
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 config subpackage
contains configuration functionality, etc.
To configure the behavior of the program using a GUI, click the ‘Configuration’ menu option from the main GUI, or run:
$ matisse-config
Hovering over most fields in this configuration dialog will reveal tooltips with more information about what the options do.
API documentation for this project can be found at https://0xSiO.github.io/matisse-controller/docs/.
The changelog for this project can be found at https://0xSiO.github.io/matisse-controller/CHANGELOG.
There are a few important bits of terminology that may be confusing:
PLE data from this application is stored in text files as a list of counts separated by newlines, as well as a .pickle file, which is an efficient form of binary storage that Python uses to serialize objects.
To load the data from a .pickle file:
import pickle
with open('file_name_here.pickle', 'rb') as data_file:
data = pickle.load(data_file)
After checking out the repo, run pipenv install --dev to install dependencies. Using a virtual environment is
recommended.
To install this package onto your local machine, run pip install -e ..
Useful documentation: PyVISA, pySerial, SciPy, matplotlib, Qt 5
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.
Currently I’ve only implemented an interface for the WaveMaster, but any class will do, as long as it implements the
get_raw_value and 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.
Logging and UI updates should have top priority, so take care not to block the UI thread. Here’s the process I use:
setup_menus and connect it to a Qt slot under setup_slots, to be executed on the main
thread later.add_done_callback on it, passing
in matisse_controller.gui.utils.raise_error_from_future if you want to log errors from that thread. For an example of
a method that runs tasks one-by-one on the Matisse, see ControlApplication.run_matisse_task.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 start_ple_scan, stop_ple_scan, and
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/0xSiO/matisse-controller.
The package is available as open source under the terms of the MIT License.