From 3aee2fd43e3059a699af2b63c6f2395e5a55e515 Mon Sep 17 00:00:00 2001
From: KatolaZ <katolaz@freaknet.org>
Date: Wed, 27 Sep 2017 15:06:31 +0100
Subject: First commit on github -- NetBunch 1.0

---
 src/bbv/bbv.c | 335 ++++++++++++++++++++++++++++++++++++++++++++++++++++++++++
 1 file changed, 335 insertions(+)
 create mode 100644 src/bbv/bbv.c

(limited to 'src/bbv/bbv.c')

diff --git a/src/bbv/bbv.c b/src/bbv/bbv.c
new file mode 100644
index 0000000..60ddd5c
--- /dev/null
+++ b/src/bbv/bbv.c
@@ -0,0 +1,335 @@
+/**
+ *  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 the Free Software Foundation, either version 3 of the
+ *  License, or (at your option) any later version.
+ *
+ *  This program is distributed in the hope that it will be useful,
+ *  but WITHOUT ANY WARRANTY; without even the implied warranty of
+ *  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
+ *  General Public License for more details.
+ *
+ *  You should have received a copy of the GNU General Public License
+ *  along with this program.  If not, see
+ *  <http://www.gnu.org/licenses/>.
+ *
+ *  (c) Vincenzo Nicosia 2009-2017 -- <v.nicosia@qmul.ac.uk>
+ * 
+ *  This file is part of NetBunch, a package for complex network
+ *  analysis and modelling. For more information please visit:
+ *
+ *             http://www.complex-networks.net/
+ *
+ *  If you use this software, please add a reference to 
+ *
+ *               V. Latora, V. Nicosia, G. Russo             
+ *   "Complex Networks: Principles, Methods and Applications"
+ *              Cambridge University Press (2017) 
+ *                ISBN: 9781107103184
+ *
+ ***********************************************************************
+ *
+ *
+ *  This program grows a weighted network using the model proposed by
+ *  Barrat, Barthelemy, and Vespignani.
+ *
+ *  References:
+ *
+ *  [1] A. Barrat, M. Barthelemy, and A. Vespignani. "Weighted
+ *     Evolving Networks: Coupling Topology and Weight
+ *     Dynamics". Phys. Rev. Lett. 92 (2004), 228701. 
+ *
+ *  [2] A. Barrat, M. Barthelemy, and A. Vespignani. "Modeling the
+ *     evolution of weighted networks". Phys. Rev. E 70 (2004),
+ *     066149.  
+ *
+ */
+
+#include <stdio.h>
+#include <stdlib.h>
+#include <time.h>
+#include <math.h>
+
+#include "cum_distr.h"
+
+void usage(char *argv[]){
+  printf("********************************************************************\n"
+         "**                                                                **\n"
+         "**                        -*-    bbv    -*-                       **\n"
+         "**                                                                **\n"
+         "**   Grow a weighted network of 'N' nodes using the model         **\n"
+         "**   proposed by Barrat-Barthelemy-Vespignani.                    **\n"
+         "**                                                                **\n"
+         "**   The initial network is a clique of 'n0' nodes, and each new  **\n"
+         "**   node creates 'm' edges. All edges have an initial weight     **\n"
+         "**   equal to 'w0', and the attachment probability in of the      **\n"
+         "**   form:                                                        **\n"
+         "**                                                                **\n"
+         "**            P(i->j) ~ s_j                                       **\n"
+         "**                                                                **\n"
+         "**   where s_j is the strength of node j. The parameter 'delta'   **\n"
+         "**   tunes the rearrangement of edge weights due to the           **\n"
+         "**   addition of a new edge. The degree, strength, and weight     **\n"
+         "**   distributions of the created graphs are power-laws,          **\n"
+         "**   whose esponents depend on the values of 'w0' and 'delta'.    **\n"
+         "**                                                                **\n"
+         "********************************************************************\n"
+         " This is Free Software - You can use and distribute it under \n"
+         " the terms of the GNU General Public License, version 3 or later\n\n"
+         " (c) Vincenzo Nicosia 2009-2017 (v.nicosia@qmul.ac.uk)\n\n"
+         "********************************************************************\n\n"
+         );
+  printf("Usage: %s <N> <m> <n0> <w0> <delta>\n", argv[0]);
+}
+
+
+typedef struct{
+  int id;
+  double w;
+  double delta_w;
+} link_t;
+
+
+typedef struct {
+  int id;
+  int size;
+  int deg;
+  double s;
+  link_t *neighs;
+} node_t;
+
+
+/* create the initial graph as a clique of n0 nodes */
+void init_seed(node_t *G, int n0, double w0, cum_distr_t *d){
+
+  int i, j, n;
+
+  for(i=0; i< n0; i++){
+    G[i].neighs = malloc((n0-1) * sizeof(link_t));
+    G[i].size = n0-1;
+    G[i].deg = n0-1;
+    n= 0;
+    for (j=0; j<n0; j++){
+      if (i != j){
+        G[i].neighs[n].id = j;
+        G[i].neighs[n].w = w0;
+        n += 1;
+      }
+    }
+    G[i].s = (n0-1) * w0;
+    cum_distr_add(d, i, G[i].s);
+  }
+}
+
+/* add j to the neighbourhood of i with a weight w0, and update the
+   strength of i */
+void add_neigh(node_t *G, unsigned int i, unsigned int j, double w0){
+  
+  if (G[i].deg == G[i].size){
+    G[i].size += 5;
+    G[i].neighs= realloc(G[i].neighs, G[i].size * sizeof(link_t));
+  }
+  G[i].neighs[G[i].deg].id = j;
+  G[i].neighs[G[i].deg].w = w0;
+  G[i].deg += 1;
+  G[i].s += w0;
+}
+
+/* Add w to the weight of the edge (i,j) */
+void add_weight(node_t *G, int i, int j, double w){
+
+  int k;
+  for(k=0; k<G[i].deg; k++){
+    if(G[i].neighs[k].id == j){
+      G[i].neighs[k].w += w;
+    }
+  }
+}
+
+/* Compute the weight increase for each edge connected to node i */
+void compute_delta_weights(node_t *G, int i, double delta){
+  int j;
+  double s;
+
+  s = G[i].s;
+
+  for(j=0; j< G[i].deg; j++){   /* for each neighbour of i */
+    /* compute the delta_weight */
+    G[i].neighs[j].delta_w = delta * G[i].neighs[j].w / s;
+  }
+}
+
+/* set the new weights on the edges connected to node i */
+void set_delta_weights(node_t *G, int i, cum_distr_t *distr){
+
+  int j, neigh;
+
+  double delta_w;
+  
+  for(j=0; j<G[i].deg; j++){
+    neigh = G[i].neighs[j].id;
+    delta_w = G[i].neighs[j].delta_w;
+    /* add delta_w to the weight of (i, neigh) and of (neigh, i) */
+    add_weight(G, i, neigh, delta_w);
+    add_weight(G, neigh, i, delta_w);
+    
+    /* update the strength of neigh */
+    G[neigh].s += delta_w;
+    /* add delta_w to the fraction of cum_distr associated to neigh */
+    cum_distr_add(distr, neigh, delta_w);
+  }
+}
+
+/* return 1 if i is in the array v */
+
+int is_neigh(int *v, int N, int i){
+  
+  int j;
+  
+  for(j=0; j<N; j++){
+    if (v[j] == i)
+      return 1;
+  }
+  return 0;
+}
+
+/* 
+ *  print the edges of the undirected graph G, with the corresponding
+ *  weight. Each edge is printed only once
+ *
+ */
+void dump_net(node_t *G, int N){
+
+  int i, j;
+
+  double tot_w = 0.0;
+  
+  for(i=0; i<N; i++){
+    for(j=0; j<G[i].deg; j++){
+      if(G[i].neighs[j].id > i){
+        tot_w += G[i].neighs[j].w;
+        printf("%d %d %g\n", i, G[i].neighs[j].id, G[i].neighs[j].w);
+      }
+    }
+  }
+}
+
+
+/* grow a weighted graph using the BBV model */
+node_t* bbv(unsigned int N, unsigned int n0, unsigned int m, double w0, double delta){
+
+  node_t *G;
+  int t, i, j;
+  cum_distr_t *distr = NULL;
+  int *tmp_neighs;
+  
+  distr = cum_distr_init(N * m);
+
+  
+  G = malloc(N * sizeof(node_t));
+  tmp_neighs = malloc(m * sizeof(int));
+
+  init_seed(G, n0, w0, distr);
+
+  
+  for(t=n0; t<N; t++){
+    /* Initialize the new node */
+    G[t].neighs = malloc(m * sizeof(link_t));
+    G[t].size = m;
+    G[t].deg = 0;
+    /* Sample the m neighbours */
+    for(i=0; i<m; i++){
+      j = cum_distr_sample(distr);
+      while(is_neigh(tmp_neighs, i, j)){
+          j = cum_distr_sample(distr);
+      }
+      tmp_neighs[i] = j;
+    }
+    /* compute the weight increase for the neighbours of the
+       new node t */
+    for(i=0; i<m; i++){/* for each neighbour 'l' of the new node t */
+      /* compute the weight increase for the edges around 'l' */
+      compute_delta_weights(G, tmp_neighs[i], delta);
+    }
+    /* Now we update the weights */
+    for(i=0; i<m; i++){/* for each neighbour 'l' of the new node t */
+      set_delta_weights(G, tmp_neighs[i], distr);
+      add_neigh(G, t, tmp_neighs[i], w0);
+      add_neigh(G, tmp_neighs[i], t, w0);
+      /* We need to add delta to the strength of tmp_neighs[i] {notice
+         that w0 has been already added by the previous call to
+         add_neigh()}*/
+      G[tmp_neighs[i]].s += delta;
+      cum_distr_add(distr, tmp_neighs[i], delta + w0);
+    }
+    
+    /* Finally, we update the strength of node t */
+    G[t].s = w0 * m;
+    cum_distr_add(distr, t, G[t].s);
+  }
+  free(tmp_neighs);
+  cum_distr_destroy(distr);
+  return G;
+}
+
+
+
+int main(int argc, char *argv[]){
+  
+  int N, n0, m, i;
+  double w0, delta;
+  
+  node_t *net;
+
+  if (argc < 6){
+    usage(argv);
+    exit(1);
+  }
+  
+  N = atoi(argv[1]);
+  m = atoi(argv[2]);
+  n0 = atoi(argv[3]);
+  w0 = atof(argv[4]);
+  delta = atof(argv[5]);
+
+  srand(time(NULL));
+
+  if (N < 1){
+    fprintf(stderr, "N must be positive\n");
+    exit(1);
+  }
+  if(m > n0){
+    fprintf(stderr, "n0 cannot be smaller than m\n");
+    exit(1);
+
+  }
+  if (n0<1){
+    fprintf(stderr, "n0 must be positive\n");
+    exit(1);
+  }
+  
+  if (m < 1){
+    fprintf(stderr, "m must be positive\n");
+    exit(1);
+  }
+
+  if (w0 <= 0.0){
+    fprintf(stderr, "w0 must be positive\n");
+    exit(1);
+  }
+
+  if (delta < 0.0){
+    fprintf(stderr, "delta must be positive\n");
+    exit(1);
+  }
+
+
+  net = bbv(N, n0, m, w0, delta);
+  dump_net(net, N);
+
+  for(i=0; i<N; i++){
+    free(net[i].neighs);
+  }
+  
+  free(net);
+}
-- 
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