Yves Biener
e981b6eaed
Model assumes that top 10% of centrality values are not effected by the boundary.
This means that they form the basis for the constant part of the two-part function:
- linear function determined through simple linear regression for the remaining
points that are below the calculated threshold
- constant consistenting of the threshold
The threshold describes the median of the centrality values of the top 10% of the
values.
Boundary-aware centrality for Spatial Graphs
University project for boundary-aware node centralities for spatial graphs. For the project details and results see the typst paper. For building the document and the usage of the python library used for this project see the corresponding sections below.
Code usage
Important
The implementation uses gurobi for solving the linear problem for the function fitting which requires a license. Please refer to the gurobi license documentation for details.
Install the requirements into a virtual environment:
# create virtual environment
python -m venv venv
# activate virtual environment
source venv/bin/activate
# install required dependencies
pip install -r requirements.txt
The src directory contains all the python source files that are used for the creation of the diagrams and images found in the doc/figures directory. For the corresponding usages for both datasets used for this project please see merfish.py and mibitof.py.
For running the generation of the diagrams and images you can run one of the two python scripts like so (inside of the virtual environment):
python merfish.py
Document generation
The document is written using typst and can be compiled into a pdf file using:
typst c doc/paper.typ
The generated pdf file will then be generated into the doc directory named paper.pdf.