GitHub - LeuphanaDataScience/sfrosenb-Immunization_Strategies_in_Networks_with_Missing_Data: Code and data associated with the upcoming PLoS Comp Bio paper about targeted immunization strategies using incomplete network data

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Code and data associated with the upcoming PLoS Comp Bio paper about targeted immunization strategies using incomplete network data

MIT license

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.ipynb_checkpoints		.ipynb_checkpoints
data		data
figures		figures
.DS_Store		.DS_Store
.gitattributes		.gitattributes
LICENSE.txt		LICENSE.txt
README.txt		README.txt
TODO_general.txt		TODO_general.txt
graph_getters.py		graph_getters.py
make_all_figures_NotebookVersion.ipynb		make_all_figures_NotebookVersion.ipynb
plot_degree_distribution.py		plot_degree_distribution.py
run_sims.py		run_sims.py
run_sims_justGGandGbarGpy.py		run_sims_justGGandGbarGpy.py
sim_utils.py		sim_utils.py

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This package contains the code and data for Immunization Strategies in Networks with Missing Data
Samuel F. Rosenblatt, Jeffrey A. Smith, G. Robin Gauthier, and Laurent Hébert-Dufresne
PLoS Comput. Biol. (in press).

The main simulation code can be found in run_sims.py which can be used with command line arguments or bash scripts (for compute clusters) with flexArgs used for different network types

The figures are generated in the make_all_figures_NotebookVersion.ipynb Jupiter Notebook using the data in data/results and are stored in figures/