Random bits of working Python code and examples (aka 'snippets') for MR spectroscopy scienctific explorations, radical file I/O and astounding GUI applications. No adjectives were harmed in the word smithing of this project description.
Basically, download a zip file of the repository locally, or fork a copy of the repository to your Github account and you are ready to go.
Most files are standalone algorithms. If multiple files are required, I have tried to put these code bits into their own sub-subdirectories.
algos - algorithms for filters and other sciency things like 'lowess' and 'hlsvdpro'.
wxpython_stuff - like the name says, I've got routines to generalize including matplotlib plots and image displays into wxpython windows.
All modules have built in examples for running/using the code. Typically just type:
>python module_name.py
at the command line and something should happen. The module and method docstrings should shed some light on each module's API, but take a look at the test code too to see more details about using the code.
- Fork it!
- Create your feature branch:
git checkout -b my-new-feature - Commit your changes:
git commit -am 'Add some feature' - Push to the branch:
git push origin my-new-feature - Submit a pull request :D
Most of these modules/algorithms have been developed as part of the Vespa: Versatile Simulation Pulses and Analysis package. This is a multi-application, open-source Python project for MR Spectroscopy research. The main website for this project is:
https://scion.duhs.duke.edu/vespa/project
This work was supported by NIH grant funding this through grant number 1R01EB008387-01A1.
We've had a lot of people support this effort, but I'd like to mention Dr. Karl Young and Philip Semanchuk (http://pyspoken.com) for their early contributions.
This project is licensed under the BSD 3-clause, please see the LICENSE.md file for details
- Brian J. Soher - Principal Investigator - Duke Radiology
- Lots of online ('google') searches have inspired this work
- We have tried to list these in each module as relevant.