Simple quasistationary method for simulations of epidemic processes with localized states: Reactivation per activity time (RAT)

This code is part of the article "[]".

Fortran implementation

Versions

• RAT - Fortran 90 (.f90)
• RAT - Python 3.7 (.py)

Citation

Full bibliographic details:

DOI information:

@article{
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Synopsis

This code is a implementation of the RAT (Reactivation per Activity Time) quasistationary method, detailed in our [paper]. It receives a network file, containing a list of edges, as input. Some parameters can be set in the file dyn_par.dat (Fortran) or dyn_par.py (Python).

Inputs

You need to provide a file containing the list of edges. ID of the vertices must be enumerated sequentially as 1, 2, 3,..., N, where N is the total number of vertices of the network. Here, we assume undirected and unweighted networks without multiple neither self connections.

Examples of datasets at /networks. Below, you'll find a brief description of each (all networks have 10⁴ nodes):

• gm23.dat: Power law degree distribution with exponent 2.3
• gm27.dat: Power law degree distribution with exponent 2.7
• rrnhub.dat: Random regular network with m = 4 and a hub with degree = 100

On file dyn_par.dat, you'll find 5 columns. Each column regards one dynamical parameter:

1. Infection rate
2. Averaging time
3. Relaxation time
4. Network file name
5. Initial seed for pseudo-random number generator only Fortran

If going for Python version, the file dyn_par.py will have four rows:

1. Network file
2. Infection rate
3. Relaxation time
4. Averaging time

Outputs

For a given set of parameters, the program outputs the quasistationary distribution P(n) in pn.dat and three quasistationary quantities on terminal or console: density of infected vertices, dynamical susceptibility and lifespam. Details about these measures may be found in the [paper].

Compiling and Executing

• Fortran (Gfortran):

  • gfortran rta.f90 -o name_exec (faster, no debugging, may give multiple warnings regarding identation (insert flag -w to get rid of them))
  • gfortran rta.f90 -fcheck=all -fcheck=bounds -o name_exec (slower, for debugging)

• Fortran (Intel):

  • ifort rta.f90 -o name_exec (faster, no debugging)
  • ifort rta.f90 -traceback -check all -o name_exec (slower, for debugging)

• Python: python rta.py

• Executing (Fortran only): ./name_exec < dyn_par.dat

Obs: The file containing the network input must be in the same folder as the .f90 or .py code.

License

This code is under GNU General Public License v3.0.