Version 1.0

Author: wcota

README.md

@@ -1,4 +1,6 @@
-# Optimized Gillespie algorithms for the efficient simulation of Markovian epidemic processes on large and heterogeneous networks: SIS-OGA
+# Optimized Gillespie algorithms for the simulation of Markovian epidemic processes on large and heterogeneous networks: SIS-OGA
+
+This code is part of the article "[Optimized Gillespie algorithms for the simulation of Markovian epidemic processes on large and heterogeneous networks](http://wesleycota.com/)"
 
 ### Python implementation
 
@@ -12,7 +14,7 @@
 
 ## Synopsis
 
-This code is a implementation of the SIS-OGA algorithm, as detailed in our paper (to be cited). It receives as input a network file, containing a list of edges and read, via terminal, the dynamical parameters.
+This code is a implementation of the SIS-OGA algorithm, as detailed in our [paper](http://wesleycota.com/). It receives as input a network file, containing a list of edges and read, via terminal, the dynamical parameters.
 
 For performance, see https://github.com/wcota/dynSIS (Fortran implementation)
 

dynamics.py

@@ -3,11 +3,12 @@
 # ! ## See README.md for more information and use
 # !-----------------------------------------------------------------------------
 # ! SIS epidemic model algorithm based on the article 
-# !           "Optimized Gillespie algorithms for the efficient simulation of 
-# !            Markovian epidemic processes on large and heterogeneous networks"
+# !           "Optimized Gillespie algorithms for the simulation of Markovian
+# !            epidemic processes on large and heterogeneous networks"
 # ! Copyright (C) 2017 Wesley Cota, Silvio C. Ferreira
 # ! 
-# ! Please cite the above cited paper as reference to our code.
+# ! Please cite the above cited paper (available at <http://wesleycota.com/ ) as reference
+# ! to our code.
 # ! 
 # !    This program is free software: you can redistribute it and/or modify
 # !    it under the terms of the GNU General Public License as published by
@@ -24,8 +25,8 @@
 # !-----------------------------------------------------------------------------
 # ! Author    : Wesley Cota
 # ! Email     : wesley.cota@ufv.br
-# ! Date      : 10 Mar 2017
-# ! Version   : 0.2
+# ! Date      : 27 Mar 2017
+# ! Version   : 1.0
 # !-----------------------------------------------------------------------------
 # ! See README.md for more details
 # ! This code is available at <https://github.com/wcota/dynSIS-py>
@@ -37,7 +38,17 @@
 from math import log
 import sys
 
-print_header()
+print(  '################################################################################',
+        '######### Optimized Gillespie algorithms for the simulation of Markovian  ######',
+        '####### epidemic processes on large and heterogeneous networks: SIS-OGA. #######',
+        '##============ Copyright (C) 2017 Wesley Cota, Silvio C. Ferreira ============##',
+        '##================ Paper available at <http://wesleycota.com/ ================##',
+        '##======= The codes are available at <https://github.com/wcota/dynSIS> =======##',
+        '##======== Please cite the above cited paper as reference to our code ========##',
+        '##=== This code is under GNU General Public License. Please see README.md. ===##',
+        '################################################################################',
+        '',
+        sep='\n')
 
 # READING PARAMETERS
 if len(sys.argv) < 3:
@@ -162,7 +173,8 @@
 
     # Write output file
     flOutput = open(fnOutput, 'wt')
-    print(  '#@ Network file: '+fnInput,
+    print(  '## ***** Algorithm used: Optimized Gillespie Algorithm for SIS (SIS-OGA, Python) *****',
+            '#@ Network file: '+fnInput,
             '#@ Number of nodes: '+str(netw.size),
             '#@ Number of edges: '+str(netw.skk),
             '#@ Samples: '+str(dynp_sam),
@@ -181,6 +193,10 @@
     flOutput.close()
 # / RUNNING DYNAMICS
 
+print_info('')
 print_info('Everything ok!',True)
 print_info('Input file (edges list): '+ fnInput)
 print_info('Output file: '+ fnOutput)
+print_info('')
+print_info('*****Algorithm used: Optimized Gillespie Algorithm for SIS (SIS-OGA, Python)*****')
+print_info('Codes available at <https://github.com/wcota/dynSIS>.')

network.py

@@ -4,11 +4,12 @@
 # ! ## See README.md for more information and use
 # !-----------------------------------------------------------------------------
 # ! SIS epidemic model algorithm based on the article 
-# !           "Optimized Gillespie algorithms for the efficient simulation of 
-# !            Markovian epidemic processes on large and heterogeneous networks"
+# !           "Optimized Gillespie algorithms for the simulation of Markovian
+# !            epidemic processes on large and heterogeneous networks"
 # ! Copyright (C) 2017 Wesley Cota, Silvio C. Ferreira
 # ! 
-# ! Please cite the above cited paper as reference to our code.
+# ! Please cite the above cited paper (available at <http://wesleycota.com/ ) as reference
+# ! to our code.
 # ! 
 # !    This program is free software: you can redistribute it and/or modify
 # !    it under the terms of the GNU General Public License as published by
@@ -25,8 +26,8 @@
 # !-----------------------------------------------------------------------------
 # ! Author    : Wesley Cota
 # ! Email     : wesley.cota@ufv.br
-# ! Date      : 10 Mar 2017
-# ! Version   : 0.2
+# ! Date      : 27 Mar 2017
+# ! Version   : 1.0
 # !-----------------------------------------------------------------------------
 # ! See README.md for more details
 # ! This code is available at <https://github.com/wcota/dynSIS-py>

saida.dat

@@ -0,0 +1,75 @@
+## ***** Algorithm used: Optimized Gillespie Algorithm for SIS (SIS-OGA, Python) *****
+#@ Network file: ../s01.edges.dat
+#@ Number of nodes: 1000
+#@ Number of edges: 5194
+#@ Samples: 100
+#! Infection rate (lambda): 0.12
+#! Maximum time steps: 100000
+#! Fraction of infected vertices (initial condition): 1.0
+1.00352972966 0.44824
+2.00499799431 0.24959
+3.00704023407 0.15691
+4.01001232771 0.10614
+5.01577421927 0.07921
+6.01609706905 0.0604
+7.02307735175 0.04713
+8.04162008125 0.03823
+9.0896170984 0.03011
+10.1002839368 0.02493
+11.1004329189 0.02157
+12.126221364 0.0183
+13.0989557029 0.01639
+14.0978684298 0.0143
+15.1670344282 0.0122
+16.1680031981 0.01019
+17.198487686 0.00858
+18.1754388668 0.00719
+19.23483838 0.00651
+20.2052089979 0.0061
+21.2348967268 0.00514
+22.2493223728 0.00424
+23.1905867937 0.00376
+24.18701619 0.00315
+25.2296574833 0.00251
+26.201148954 0.00266
+27.201825163 0.00226
+28.0779979196 0.00216
+29.4279870216 0.00164
+30.4486392255 0.00174
+31.3286636469 0.00173
+32.5629792245 0.00148
+33.3235209261 0.00125
+34.1923405827 0.00122
+35.1393685318 0.00101
+36.1865645312 0.00072
+37.1201577327 0.0006
+38.2781095783 0.00046
+39.0241456601 0.0005
+40.1539064218 0.00044
+41.1021747133 0.00049
+42.2467154855 0.00034
+43.4352451344 0.00034
+44.1380860192 0.00028
+45.1787946027 0.0002
+46.0883031418 0.00032
+47.2589765801 0.00028
+48.5505203581 0.00023
+49.1443231985 0.00025
+50.0515121313 0.00023
+51.0417713446 0.00019
+52.0895263144 0.00018
+53.0030927503 0.00016
+54.0241556001 0.00023
+55.0287812782 0.00027
+56.0163104215 0.00026
+57.0794846247 0.00012
+58.0193112177 0.00023
+59.0065588239 0.00031
+60.0017457919 0.0004
+61.0472794528 0.00035
+62.0494306342 0.00033
+63.0045712802 0.00038
+64.0073553421 0.00031
+65.0874090484 0.00012
+66.0874026347 0.0001
+67.1585283646 6e-05

tools.py

@@ -1,14 +1,14 @@
 #!/usr/bin/env python
 # ! ## File: tools.py
 # ! ## Print and read functions.
-# ! ## See README.md for more information and use
-# !-----------------------------------------------------------------------------
+# ! ## See README.md for more information and use# !-----------------------------------------------------------------------------
 # ! SIS epidemic model algorithm based on the article 
-# !           "Optimized Gillespie algorithms for the efficient simulation of 
-# !            Markovian epidemic processes on large and heterogeneous networks"
+# !           "Optimized Gillespie algorithms for the simulation of Markovian
+# !            epidemic processes on large and heterogeneous networks"
 # ! Copyright (C) 2017 Wesley Cota, Silvio C. Ferreira
 # ! 
-# ! Please cite the above cited paper as reference to our code.
+# ! Please cite the above cited paper (available at <http://wesleycota.com/ ) as reference
+# ! to our code.
 # ! 
 # !    This program is free software: you can redistribute it and/or modify
 # !    it under the terms of the GNU General Public License as published by
@@ -25,8 +25,8 @@
 # !-----------------------------------------------------------------------------
 # ! Author    : Wesley Cota
 # ! Email     : wesley.cota@ufv.br
-# ! Date      : 10 Mar 2017
-# ! Version   : 0.2
+# ! Date      : 27 Mar 2017
+# ! Version   : 1.0
 # !-----------------------------------------------------------------------------
 # ! See README.md for more details
 # ! This code is available at <https://github.com/wcota/dynSIS-py>
@@ -40,18 +40,5 @@ def print_error(st):
 def print_info(st,nl=False):
     if nl:
         print('')
-    print('$!', st, '!$')
-    
-def print_header():
-    
-    
-    print(  '################################################################################',
-            '### Optimized Gillespie algorithms for the efficient simulation of Markovian ###',
-            '####### epidemic processes on large and heterogeneous networks: SIS-OGA. #######',
-            '##============ Copyright (C) 2017 Wesley Cota, Silvio C. Ferreira ============##',
-            '##======= This code is available at <https://github.com/wcota/dynSIS>. =======##',
-            '##======== Please cite the above cited paper as reference to our code ========##',
-            '##=== This code is under GNU General Public License. Please see README.md. ===##',
-            '################################################################################',
-            '',
-            sep='\n')
+    print('$!', st)
+