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removed instructions.md to be put in Plugins repo; Added README to pybind directory
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.gitignore

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.vscode
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venv
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build
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**/venv
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build
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tests/**/EmotiBit_*.csv

pybind/README

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# Running EmotiBit Brainflow SpO2 Algorithm using `pybind`
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## Requirements
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- Python
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- Python virtual environment (refer to the Emotibit Plugins [repo](https://github.com/EmotiBit/EmotiBit_Plugins/blob/main/README_py.md#setting-up-python-virtual-environment) for specific instructions on how to setup)
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- CMake
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- [EmotiBit ArduinoFilters](https://github.com/EmotiBit/EmotiBit_ArduinoFilters) installed using Arduino Library Manager (or manually cloned/copied into the Arduino/libraries folder)
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## Build
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- Open a terminal window
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- `cd` into the `pybind` directory
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- Activate the Python virtual environment (instructions found in Emotibit Plugins [repo](https://github.com/EmotiBit/EmotiBit_Plugins/blob/main/README_py.md#setting-up-python-virtual-environment))
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- Run `cmake -B build` to generate the build files (the build files will be under a directory named `build`)
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- Run `cmake --build build --config Release` to generate the `.pyd` file
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- On Windows using MSVC, the `.pyd` file will be under `pybind/build/Release`
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- Otherwise, the `.pyd` file will be under `pybind/build`
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## Testing
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- Run the EmotiBit Data Parser on `tests/simulated-unobstructed-airway_v0.0.0/ip900ap/EmotiBit.csv`
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- Verify that `EmotiBit_PI.csv`, `EmotiBit_PR.csv`, and `EmotiBit_UN.csv` exist under `tests/simulated-unobstructed-airway_v0.0.0/ip900ap`
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- Switch to the terminal window in the `pybind` directory
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- Run `python run.py ../tests/simulated-unobstructed-airway_v0.0.0/ip900ap`
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- `matplotlib` may need to be installed for the script to run successfully
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- A plot of the raw PPG data overlayed with the calculated SpO2 should appear

tests/simulated-unobstructed-airway_v0.0.0/ip900ap/instructions.md

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