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PhyAAt lib with dataset API
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‎LICENSE‎

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MIT License
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Copyright (c) [2020] [Nikesh Bajaj]
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Permission is hereby granted, free of charge, to any person obtaining a copy
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of this software and associated documentation files (the "Software"), to deal
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in the Software without restriction, including without limitation the rights
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to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
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copies of the Software, and to permit persons to whom the Software is
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furnished to do so, subject to the following conditions:
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The above copyright notice and this permission notice shall be included in all
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copies or substantial portions of the Software.
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THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
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IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
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FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
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AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
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LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
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OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
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SOFTWARE.

‎MANIFEST.in‎

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include *.md
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include *.rst
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include LICENSE
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include Version
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include requirements.txt
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include phyaat/__init__.py
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recursive-include phyaat *.py
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recursive-include phyaat *.txt
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recursive-include examples *.py
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recursive-include examples *.ipynb
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recursive-include *.ipynb
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### Exclude
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recursive-exclude * __pycache__
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recursive-exclude *.yml

‎README.md‎

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# phyaat
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PhyAAt: Physiology of Auditory Attention - Processing Library
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# Phyaat -Physiology of Auditory Attention
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## Predictive analysis of auditory attention from physiological signals
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### **[Project Homepage](https://phyaat.github.io)**
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### **[PyPi - project](https://pypi.org/project/phyaat/)**
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<p align="center">
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<img src="https://phyaat.github.io/_images0/ExperimentModel.png" width="500"/>
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</p>
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<p align="center">
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<img src="https://phyaat.github.io/_images0/EEGViz_Raw1.gif" width="500"/>
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</p>
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### Requirement :
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['numpy','scipy','matplotlib','seaborn','PyWavelet']
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## Installation
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### with pip
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```
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pip install phyaat
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```
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### Build from the source
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Download the repository or clone it with git, after cd in directory build it from source with
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```
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python setup.py install
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```
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## Contents will be updated soon on homepage as well as in the phyaat library
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______________________________________
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# Contacts:
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* **Nikesh Bajaj**
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* http://nikeshbajaj.in
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* n.bajaj@qmul.ac.uk
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* bajaj.nikkey@gmail.com
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### PhD Student: Queen Mary University of London & University of Genoa
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______________________________________

‎Version‎

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0.0.2

‎docs/Contacts.rst‎

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Contacts
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----------
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If any doubt, confusion or feedback please contact me at
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* `n.bajaj@qmul.ac.uk`
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* `nikkeshbajaj@gmail.com`
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Nikesh Bajaj: http://nikeshbajaj.in
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PhD Student: **Queen Mary University of London**

‎docs/Examples.rst‎

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**Examples**
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======================================
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::
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import numpy as np
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import matplotlib.pyplot as plt
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import phyaat as ph

‎docs/README.rst‎

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PhyAAt: Physiology of Auditory Attention
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======================================
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**Links**
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----------
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* **Homepage** : https://PhyAAt.github.io
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* **Documentation** : https://phyaat.readthedocs.io/
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* **Github Page** : https://github.com/Nikeshbajaj/phyaat
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* **PyPi-project**: https://pypi.org/project/phyaat/
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**Installation**
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----------
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With **pip**
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::
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pip install phyaat

‎docs/index.rst‎

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PhyAAt: Physiology of Auditory Attention
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=====================================
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Predictive Analysis of Auditory Attention from Physiological Signals documentation!
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-------------------------------------
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This package includes following components:
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.. toctree::
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:maxdepth: 2
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README
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Examples
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Contacts

‎examples/example1.py‎

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import numpy as np
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import pandas as pd
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import phyaat as ph
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DataDir = ph.download_data(baseDir = '../Phyaat/',subject=1)

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