CircuMat

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CircuMat is a modified (forked) version of Rama-Scene EIT Raw Materials project related to analyzing Environmentally Extended Input-Output (EEIO) tables. CircuMat focuses on NUTS2 level classification as opposed to Rama-Scene country level analysis tool.

Developers Guide

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For more information on the tool architecture, please refer to Rama-Scene's documenation: http://rama-scene.readthedocs.io/en/latest/

Getting started

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Retrieve the raw datasets

• EXIOBASE-Rama-Scene (v4 - modified version including secondary materials + CircuMat Eurostat data):

https://surfdrive.surf.nl/files/index.php/s/bEVnoyJUeYMUiyr

pass: circumat

Download the circumat_v4_clean.zip folder.

Clone the project

$ git clone https://[email protected]/CML-IE/circumat.git

Create a virtual environment (python3.5 or higher) and install the app requirements (make sure you have python-dev installed via apt-get)

$ pip3 install -r requirements.txt 

Install node.js (node version: 3.10.10 or higher)

$ sudo apt-get update
$ sudo apt-get install nodejs

Note: On debian apt install nodejs-legacy

Install redis (for Django Channels)

$ sudo apt install redis-server

Install rabbitMQ (for Celery)

$ sudo apt-get install -y erlang

$ sudo apt-get install rabbitmq-server

Then enable and start the RabbitMQ service:

$ sudo systemctl enable rabbitmq-server

$ sudo systemctl start rabbitmq-server

Check the status to make sure everything is running: $ sudo systemctl status rabbitmq-server

Note: Perform all next steps in the virtualenv and in the rootfolder of the project

Set the following environment variables (see sample-dev-env.sh):

export DJANGO_SETTINGS_MODULE=circumatMasterProject.config.dev
export DATASETS_VERSION=[version downloaded e.g. v3]
export DATASETS_DIR=my/path/to/datasets (make sure that inside this folder is a folder containing the year 2011)
export OPENBLAS_NUM_THREADS=<adjust according to how many cores you want to use>

If you are on Linux and using the OpenBlas library for Numpy. It is advised to set the number of threads Numpy uses. To find which library is used in python:

>>>import numpy as np
>>>np.__config__.show()

Prepare the database

$ python3 manage.py makemigrations
$ python3 manage.py migrate

Populate the database

$ python3 manage.py populateHierarchies

Prepare static resources (npm version 4.6.1 or higher)

$ npm install

Built React bundle

$ ./node_modules/.bin/webpack --config dev-webpack.config.js 

Start Celery

Start the celery module to enable handling of calculations:

$ celery -A circumatMasterProject worker -l info  --concurrency 1 

Start the development server

$ python3 manage.py runserver

Access the app via the webbrowser: http://127.0.0.1:8000/circumat/

Core dependencies

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TO BE UPDATED

The app uses Celery [4.1.0] (http://docs.celeryproject.org/en/latest/django/first-steps-with-django.html), Django channels [2.1.5] (https://channels.readthedocs.io/en/latest/)

Contributers

(Ramascene & Circumat) Back-end developer: Sidney Niccolson & Franco Donati (CML) (Ramascene) Front-end developer: Franco Donati (CML) & Bart Daniels (VITO) (Ramascene) IO calculations: Arjan de Koning, Hale Cetinay & Franco Donati (CML) (Ramascene) IO modelling: Franco Donati (CML) Eurostat data: Elmer Rietveld (TNO) Project manager: Hale Cetinay Iyicil & Franco Donati (CML)