Merge branch 'main' of https://github.com/matsim-vsp/epi-net-sim

README.md

@@ -1,2 +1,50 @@
 # epi-net-sim
-epidemiological network-based ABM written in Julia
+EpiNetSim is an epidemiological network-based ABM toy model written in Julia. 
+
+## Run Locally
+
+After cloning this repository and navigating into the folder on your terminal, you can run the toy model with the following command:
+``` bash
+julia src/main/julia/run_locally.jl
+```
+
+ You can change the input variables in run_locally.jl as needed: 
+- seeds: number of times to run model.
+- iterations: number of time steps (e.g. days) to simulate.
+- base_susceptibilities: probability that a susceptible agent will be infected by an infectious agent given contact. Multiple values may be provided in array.
+- recovery rate: probality an agent will switch from the disease state "Infectious" to the disease state "Recovered". For instance, a value of 0.2 means it will take an average of 5 days for an individual to recover.
+- network_structures: network structure connecting agents, options include ["regular", "random", "smallworld", "smallworldreg", "preferential"]
+- local_global_scenarios: the risk reduction stategy that agents will apply. Options include ["base","global","local1","local2","local1_and_2","global_local1","global_local1_and_2"]
+- mean_degree: mean degree of network
+- days_until_showing_symtoms: length of "Presymptomatic" state, in which agent can transmit disease but it is not detectable in the context of risk reduction strategies. If set to 0, "Presymptomatic" State is excluded.
+- output_folder: custom folder name for storing output files. If missing, a folder will be generated with timestamp as name.
+
+## Run on Cluster
+For large parameter combinations, it may make sense to run the toy model on a computing cluster. run_on_cluster.jl is one example of a run script for this purpose. On SLURM-based cluster, the following exemplary shell script can begin the simulation: 
+```bash
+#!/bin/sh
+
+#SBATCH -N 1
+#SBATCH -t 01:30:00
+
+module load julia
+
+OUTPUT_FOLDER_NAME=sensitivity_rec_0.5
+
+mkdir $OUTPUT_FOLDER_NAME
+
+for prob in `seq 0.1 0.05 .3`; do
+        julia run_on_cluster.jl $prob 0 $OUTPUT_FOLDER_NAME &
+        julia run_on_cluster.jl $prob 1 $OUTPUT_FOLDER_NAME &
+        julia run_on_cluster.jl $prob 2 $OUTPUT_FOLDER_NAME &
+done
+
+wait
+```
+
+
+
+
+
+
+