Framework that uses artificial intelligence applied to mathematical models to make predictions

Related tags

Deep LearningLiconIA
Overview

LiconIA

Framework that uses artificial intelligence applied to mathematical models to make predictions

GitHub Release GitHub license


Interface Overview

image

Table of contents

[TOC]


1 Articles, theses for technical support

1.1 Final Coursework



1.2 Dissertation



1.3 Theses


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1.4 Articles



2 Requirements


  • Python 3.6 or superior (sudo apt-get install python3.6 under Linux)
  • Python virtual environment (sudo apt-get install python3.6-venv under Linux)

3 Package structure (need to update)


The initial directory structure should look like this:


4 Development and Tests

4.1 Installing the package


Start by creating a new virtual environment for your project. Next, update the packages pip and setuptools to the latest version. Then install the package itself.

$ sudo apt-get install python3-tk
$ /usr/bin/python3.6 -m venv --prompt="LiconIA" venv
$ source venv/bin/activate
(LiconIA) $ pip install --upgrade setuptools pip
(LiconIA) $ pip install numpy matplotlib pandas xlrd PyQt5
(LiconIA) $ pip install xlrd==1.2.0

4.2 Run program


To run the code just type:

$ python run.py

4.3 Qt-desing Information


Information about running the interface in qt-desing https://pythonbasics.org/qt-designer-python/

How to start Designer

$ cd /usr/lib/x86_64-linux-gnu/qt5/bin/ && ./designer
$ ./designer

Information about widgets the interface in qt-desing https://doc.qt.io/qtforpython/PySide2/QtWidgets/

Convert ui to py

pyuic5 /home/linux/helloworld.ui -o helloworld.py

4.4 Code checking


It is also possible to check for errors in Python code using:

use a pep8 -> pycodestyle


4.5 Development Team



5 License


This package is released and distributed under the license GNU GPL Version 3, 29 June 2007.

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