gluonicpenguin/voronoi-mapper

Plot a series of places on a map in the style of a Voronoi diagram

voronoi-mapper

Plot a series of places on a map in the style of a Voronoi diagram, based on an input csv file formatted in the following style (columns in this order - the column header names do not matter):

Labels / Places	Y-Coord / Latitude	X-Coord / Longitude	Colour Place / Been to Place
England	52.3555	-1.1743	Y
Isle of Man	54.2361	-4.5481	N
N Ireland	54.7877	-6.4923	N
Scotland	56.4907	-4.2026	Y
Wales	52.1307	-3.7837	Y

Step 1: Clone voronoi-mapper repo

Clone the voronoi-mapper repo to your area. Note you may need to set up ssh keys and add them to your GitHub account first, see here.

git clone [email protected]:GluonicPenguin/voronoi-mapper.git

Step 2: Install requirements

voronoi-mapper uses a conda installer, with the conda environment set up in Miniconda. To set up Miniconda3 and install the mapper requirements, do the following:

MINICONDA_DIR=/path/to/miniconda3 # change this to somewhere outside the voronoi-mapper repo
wget https://repo.continuum.io/miniconda/Miniconda3-latest-Linux-x86_64.sh
bash Miniconda3-latest-Linux-x86_64.sh -b -p $MINICONDA_DIR # this creates the miniconda3 directory at the known /path/to
rm Miniconda3-latest-Linux-x86_64.sh

source $MINICONDA_DIR/etc/profile.d/conda.sh
conda update -y -n base -c defaults conda
export PYTHONNOUSERSITE=true

Then back in your voronoi-mapper directory, set up the environment:

conda env create -f mapper_env_requirements.yml
conda activate voronoi_mapper_env

In future setups, use the setup_env.sh file to start up the voronoi-mapper environment. Note that you will need to change the first line to the MINICONDA_DIR.

Step 3: Use mapper

voronoi-mapper takes two positional arguments: the input csv file and the output file name and path. An optional argument for the output plot type, e.g. pdf or png, is available (default is png). For example:

python voronoi_mapper.py /path/to/places.csv /path/for/places_plot

The result should look like the following:

Step 4: Customisation options

voronoi-mapper can be modified at the dataframe stage to any format that will appear at the Voronoi diagram creation stage. The options currently are:

-f, --fisheye some_label # choose to magnify the diagram about a central point or label, good if there are a lot of places clustered together in one area