Initial commit

.gitignore

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+# Add any directories, files, or patterns you don't want to be tracked by version control
+.idea/
+.idea/*
+medusa.egg-info/
+medusa.egg-info/*
+*.pyc
+*.pyo
+*.mds
+*.csv
+*.mat
+venv/
+python-env/
+build/
+dist/
+*.egg*

LICENSE.txt

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+MIT License
+Copyright (c) 2022 Eduardo Santamaría Vázquez
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

README.md

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+# Medusa-core
+
+This package is your advanced tool for biosignal processing. It implements state-of-the-art methods that are use currently in research/engineering. Additionaly, is the base toolbox for MEDUSA, a platform to easily run and implement biofeedback experiments.
+
+Medusa-core provides:
+- State-of-the-art signal processing methods: especialized deep learning models, entropy metrics, connectivity, graph theory, etc
+- High-level functionalities: brain-computer interfaces, beautiful plots
+- Base functions for MEDUSA platform

ReleaseToPyPi.txt

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+cd "C://PATH//TO//YOUR//FOLDER"
+python setup.py sdist
+pip install twine
+twine upload dist/*

medusa/__init__.py

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+from .frequency_filtering import *
+from .spatial_filtering import *
+from .epoching import *