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This is the repository for the short course for Open Source Spatial Optimization in Aalto University.

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Workshop: Introduction to Open Source Spatial Optimisation @Aalto University, Oct 16, 2023

Setup

Step 1: Download the workshop material

If you are comfortable with GitHub and git, the command-line program, you can download the workshop materials by cloning my repository:

git clone https://github.com/qszhao/Aalto2023-spopt.git
cd Aalto2023-spopt

If you are not comfortable with GitHub, download the repository to your computer as a zip file from the workshop website. To do this, go to https://github.com/qszhao/Aalto2023-spopt, click on the green button labelled "< > Code ", then click the " Download Zip" option.

Step 2: Install the required Python packages

To follow along with the workshop material, it is best if you install Anaconda, a scientific python computing environment. If you do not yet have Anaconda installed, you can install miniconda (https://conda.io/miniconda.html) or the (larger) Anaconda distribution (https://www.anaconda.com/download/).

Option 1: Using the conda program from your command line or within the anaconda prompt, we recommend using the following terminal commands to set up your environment:

# we want to use only the community-distributed packages on "conda-forge" 
conda config --add channels conda-forge
conda config --set channel_priority strict
# and, we want to use the faster implementation of conda, called "mamba"
conda install mamba
# Then, we want to create our actual environment
mamba env create --file environment.yml
# and finally, activate the environment
conda activate spatialopt

Option 2: Alternatively, you can use conda to set up the environment as well.

#Check current conda channel priority

conda config --get channels

# Switch your default conda channel to conda-forge and set it as the highest priority
# we want to use only the community-distributed packages on "conda-forge" 

conda config --add channels conda-forge 
conda config --set channel_priority strict

#Create new environment

conda create --name spatialopt python=3.11

#Check existing conda environment

conda info --envs

#Make sure that you are going to work in newly created environment

conda activate spatialopt

# Install packages
conda install -c conda-forge jupyterlab
conda install -c conda-forge geopandas
conda install -c conda-forge matplotlib
conda install -c conda-forge shapely
conda install -c conda-forge pyogrio
conda install -c conda-forge libpysal
conda install -c conda-forge spopt
conda install -c conda-forge pulp

#Alternatively run the installation in one line

conda install -c conda-forge jupyterlab geopandas matplotlib shapely pyogrio libpysal spopt pulp  

#Start the  jupyter lab

jupyter lab

If you are using the "Anaconda Navigator" interface, you can import the workshop environment using the steps described in its documentation.

Step 3: starting Jupyter Lab

To start your analysis environment locally, you first must activate the spatialopt environment if you have not done so:

conda activate spatialopt

And then, you must start Juptyer Lab, the next-generation user interface for Project Jupyter. The workshop code is implemented in Jupyter Notebooks, a literate and interactive programming environment for scientific computing.

jupyter lab

Acknowledgement

This teaching materials have been co-designed with the spopt development team and special thanks to Dr Levi Wolf in University of Bristol, Dr James Gaboardi in ORNL, and Germano Barcelos from Brazil.

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