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LICENSE.txt (1069, 2024-01-08)
example_files/ (0, 2024-01-08)
example_files/TF.h5 (325280, 2024-01-08)
example_files/config.yaml (153, 2024-01-08)
example_files/shaking_0.h5 (12806192, 2024-01-08)
lib/ (0, 2024-01-08)
lib/data_processing.py (86846, 2024-01-08)
lib/funcs.py (5044, 2024-01-08)
lib/plotting.py (37211, 2024-01-08)
lib/signals.py (4279, 2024-01-08)
lib/stats.py (14257, 2024-01-08)
lib/synthetic_data.py (6664, 2024-01-08)
notebooks/ (0, 2024-01-08)
notebooks/example.ipynb (21926, 2024-01-08)
pyproject.toml (431, 2024-01-08)
requirements.txt (98, 2024-01-08)
scripts/ (0, 2024-01-08)
scripts/make_figures.py (8256, 2024-01-08)
scripts/make_limit_plots.py (6392, 2024-01-08)
scripts/optlevstyle.mplstyle (1273, 2024-01-08)
scripts/process_dataset.py (1131, 2024-01-08)
scripts/process_in_chunks.py (3137, 2024-01-08)
update.sh (269, 2024-01-08)

# OptLevAnalysis This package contains analysis code used by the Stanford optical levitation lab to search for non-Newtonian interactions at the micron scale. ## Installation It is highly recommended that you install this inside a virtual environment using `venv` or `conda`, since the specific `numpy` and `scipy` versions listed in [`requirements.txt`](https://github.com/stanfordbeads/OptLevAnalysis/blob/master/requirements.txt) are required in order to avoid known performance issues with later versions. From within the environment, run the following in the `OptLevAnalysis` directory: ``` pip install -e . ``` This will install the package in developer mode, which is currently the only available method of installation. To uninstall, run: ``` pip uninstall optlevanalysis ``` If you do not plan to make regular changes to the code and only want to use the latest stable release, run the following from the `OptLevAnalysis` directory: ``` bash update.sh ``` ## Usage An example notebook that demonstrates how to use the `FileData` and `AggregateData` classes can be found [here](https://github.com/stanfordbeads/OptLevAnalysis/blob/master/notebooks/example.ipynb). To run out-of-the-box, use the [`process_dataset`](https://github.com/stanfordbeads/OptLevAnalysis/blob/master/scripts/process_dataset.py) script. The only required arguments are the path to a folder containing the raw data (including both the `.h5` files and a `config.yaml` file) and a file prefix: ``` cd scripts python process_dataset.py /path/to/data/ file_prefix ``` This will save the `AggregateData` object to the default folder with a filename generated using the path to the raw data. Some basic figures can then be produced using the [`make_figures`](https://github.com/stanfordbeads/OptLevAnalysis/blob/master/scripts/make_figures.py) script with the path to the saved `AggregateData` object: ``` python make_figures.py /path/to/aggdat.h5 ``` ## Related packages [`opt_lev_analysis`](https://github.com/stanfordbeads/OptLevAnalysis/blob/master/https://github.com/stanfordbeads/opt_lev_analysis) - the package from which much of this code was originally adapted. ## Authors Clarke Hardy ([cahardy@stanford.edu](https://github.com/stanfordbeads/OptLevAnalysis/blob/master/mailto:cahardy@stanford.edu)), adapted from analysis code originally developed by Chas Blakemore and Alexander Rider.

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