An extensible Python toolbox for efficient optical brain mapping
Project description
NeuroDOT_py README
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Installation:
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First, download Python. NeuroDOT_py is optimized for Python version 3.8.8: https://www.python.org/downloads/
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Download VSCode: https://code.visualstudio.com
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Download the Jupyter notebook extension for VSCode: launch your VS Code and type “jupyter notebook” in the extension search box. Select the first result (Jupyter) and click 'Install'.
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Install NeuroDOT_py using Pip: pip install neuro_dot
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Geting Started
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The toolbox contains 4 folders: Data, neuro_dot, Support Files, and outputfiles/output_Images.
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The Data folder contains 10 data samples including both retinotopic mapping of visual cortex and mapping of hierarchical language processing with HD-DOT. There are also two example parameter files, 'params.txt,' and 'params2.txt' to be used with 'getting_started' (the NeuroDOT Preprocessing script).
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The neuro_dot folder contains the library, consisting of modules for each category of function involved in NeuroDOT_py (Analysis, File_IO, Light Modeling, Matlab Equivalent Functions, Reconstruction, Spatial Transforms, Temporal Transforms, and Visualizations). There is also a function named DynamicFilter, which is used in 'getting_started.ipynb' to simplify visualizations for data pre-processing. There is also 'requirements.txt' which contains all of the necessary libraries to be installed to use NeuroDOT_py.
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The Support Files folder contains necessary files for running NeuroDOT pipelines.
- The A matrix file required for Reconstruction is too large to be posted on GitHub, so it can be downloaded from: https://www.nitrc.org/projects/neurodot/. Other A matrices will be added in the future.
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The 'outputfiles' folder is created after running 'getting_started' and is where all of the images (.png) generated will be saved to.
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'getting_started.ipynb' is the Jupyter notebook for getting acquainted with NeuroDOT_Py. This is the file that you will open in VSCode/Jupter Notebook to run and manipulate the code.
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