SEEGVIS

Introduction

It is a web system for visualizing and processing EEG/SEEG FC (Functional Connectivity) data.

Methodological Techniques:

1. Non-linear regression (Piecewise linear regression )
2. Sliding windows and max time lag
3. Anomaly detection and handling

Project Techniques:

1. Django
2. D3.js
3. Vue.js

Visualization:

1. line chart
2. box chart
3. violin chart
4. heat map
5. theme river / stream graph
6. 3-D scatter chart

Install

Python 3.7.x

Package	Version
Django	1.11.8
numpy
scipy
pandas	0.24.2
xlwt

Deployment

1. Install Miniconda

   For Windows 64, click here to download installation package, then install it.

2. Use conda to create an environment with python3.7

   conda create -n seegvis python=3.7

3. Activate this environment

   conda activate seegvis

4. Install those python packages:

   pip install django==1.11.8 scipy pandas==0.24.2 xlwt

   you can use image sources to speed up installation, like:

   pip install -i https://pypi.tuna.tsinghua.edu.cn/simple django==1.11.8 scipy pandas==0.24.2 xlwt

5. Enter the SEEGVIS project folder, then run it:

   python manage.py runserver 0.0.0.0:80

   now the project is running on your localhost

Note: If there is a SyntaxError: Generator expression must be parenthesized Please delete the last comma in this code: '%s=%s' % (k, v) for k, v in params.items(), reference link Then repeat the step 5.

Data Description