MetaWards disease metapopulation modelling
Project description
MetaWards
References
-
"Individual identity and movement networks for disease metapopulations" Matt J. Keeling, Leon Danon, Matthew C. Vernon, Thomas A. House Proceedings of the National Academy of Sciences May 2010, 107 (19) 8866-8870; DOI: 10.1073/pnas.1000416107
-
"A spatial model of CoVID-19 transmission in England and Wales: early spread and peak timing" Leon Danon, Ellen Brooks-Pollock, Mick Bailey, Matt J Keeling medRxiv 2020.02.12.20022566; doi: 10.1101/2020.02.12.20022566
Summary
This repository has the code used for the papers and preprints in the References section
Dependancies
The code depends on the GSL - the GNU Scientific Library, install with your operating system's package manager or load the appropriate module if you are on an HPC system.
Building
Clone the repository
[user@host ~]$ git clone https://github.com/ldanon/MetaWards.git
Change in to the repository and run make
[user@host ~]$ cd MetaWards
[user@host MetaWards]$ make
This produces an executable named wards.o
Running
MetaWards currently expects the data files to be found in a hard coded path under your home Directory
~/GitHub/MetaWards/2011Data/
. If you don't have the cloned repository there you can create a symlink.
Running a single experiment
[user@host MetaWards]$ mkdir expt
[user@host MetaWards]$ cd expt
[user@host MetaWards]$ ../wards.o 42 Testing/ncovparams.csv 4 1
Where the command line arguments are
./wards.o <RANDOM_SEED> <PARAMETER_FILE> <SOME_NUMBER> <SOME_OTHER_NUMBER>
Running an ensemble
To run multiple experiments use the driving shellscript run_repeats.sh
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
Built Distribution
Hashes for metawards-0.2.0a0-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm | Hash digest | |
---|---|---|
SHA256 | edfcfbbc47f1a30887c61995eed13e40c8c3ccbe95cb1406e3db6baa95738f65 |
|
MD5 | 8931397853409b20428f33518f0fbf72 |
|
BLAKE2b-256 | dc2a8f9270b850a37235a8444f0e21db404391aa3285c21d36bdd611b2dd8d97 |