Summer School on Data Science Tools and Techniques in Modelling Complex Networks

Przemysław Szufel

Installation instructions

Copy this repository to your local folder. This can be done by clicking the green "Clone or download" button and selecting "Download ZIP" or by running the following command:
```
git clone https://github.com/pszufe/ComplexNetworks2019.git
```
Note that on the Windows platform the above command requires the git tool available at https://git-scm.com/download/win.
Please download Julia from https://julialang.org/downloads/ and install Current stable release (at the time of the workshop it is version 1.1.1. We recommend selecting the 64-bit platform.

Type julia to start Julia and run the following installation scripts:

using Pkg
Pkg.add("PyCall")
Pkg.add("Conda")
using Conda
Conda.runconda(`install folium -c conda-forge`)

Note that on the day 4 we will be processing XML data.

On the Linux platform processing such data requires the XML library libexpat to be present in the operating system. When using Linux Ubuntu run the following command:
```
   sudo apt install libexpat-dev
```
The above step is not required on Windows.
The programming environment for Julia is an Atom (https://atom.io/) plugin named Juno. In order to install Atom with Juno please follow the steps below:

a) Download and install Atom (available at https://atom.io/).

b) Start Atom and press Ctrl + , ( Ctrl key + comma key ) to open the Atom settings screen.

c) Select the Install tab.

d) In the Search packages field, type uber-juno and press Enter .

e) You will see the uber-juno package developed by JunoLab—click Install to install the package.
Optionally, it is possible to use Julia within Jupyter notebook (this was largely used during the days 1 and 2 of the workshop).

In order to try Julia inside a Jupyter notebook start the Julia console and run the two following commands:
```
using IJulia
notebook(dir="/folder/to/source/codes")   # a new web browser tab should open
```

Modelling hyperaphs in Julia with the Hypergraphs.jl package

Day 3, Wednesday, August 21st, 2019, 13:00 to 16:00

Objective: Understand how SimpleHypergraphs.jl can be used to process hypergraph data. Represent the Yelp reviews dataset as a hyperaph and measure modularity across different communities.

All files needed for this part have been stored in the day3 folder.

After installing Julia You can run julia 1_prepareenv.jl command from system shell in the day1 directory before the workshop (this will load and install all required packages).

Graph-based analysis of spatial data and transportation system modeling in Julia

Day 4, Thursday, August 22nd, 2019, 13:00 to 16:00

Objective: Provide overview of working with road network and map data in Julia using the OpenStreetMapX.jl library.

All files needed for this part will be stored in day4 folder.

After installing Julia You can run julia 1_prepareenv.jl command from system shell in the day4 directory before the workshop (this will load and install all required packages).

Large scale graph analysis with parallel and distributed computing tools in Julia

Day 5, Friday, August 23rd, 2019, 13:00 to 16:00

Objective: understand how to perform distributed computing in Julia and how it can be applied to distribute workloads on graph data.

All files needed for this part will be stored in day5 folder.

After installing Julia You can run julia 1_prepareenv.jl command from system shell in the day5 directory before the workshop (this will load and install all required packages).

pszufe/ComplexNetworks2019