update for circle topology

main.py

@@ -1,8 +1,25 @@
 import matplotlib.pyplot as plt
 import networkx as nx
+import pandas as pd
+
+nn_total_levels = 0
 
 def nn(cluster_no, node_name):
-    return str(cluster_no) + '-' + node_name
+    if not nn_total_levels:
+        return str(cluster_no) + '-' + node_name
+    return str(cluster_no % nn_total_levels) + '-' + node_name
+
+def join_nodes(g, a, b):
+    if not (g.degree[a] == 6 or g.degree[b] == 6):
+        g.add_edge(a, b)
+
+def start_file(p):
+    index = ['i', 'N', 'E', 'S', 'D', 'D_avg', 'T', 'C']
+    open(p, 'w').write(','.join(index) + '\n')
+
+def write_file(p, data):
+    index = ['i', 'N', 'E', 'S', 'D', 'D_avg', 'T', 'C']
+    open(p, 'a').write(','.join([str(data[i]) for i in index]) + '\n')
 
 def build_cluster(n):
     g = nx.Graph()
@@ -17,50 +34,56 @@ def build_cluster(n):
 
     return g
 
-def analyze_network(N_max):
+def build_network(n):
-    i = 0
-    g = build_cluster(i)
-    stats = []
-
     throw_dist = 4
 
-    while g.number_of_nodes() < N_max:
+    g = build_cluster(0)
-        i += 1
+
+    global nn_total_levels
+    nn_total_levels = n
+
+    for i in range(1, n):
         c = build_cluster(i)
         g = nx.union(g, c)
 
-        if i % 2:
+    for i in range(n):
-            g.add_edge(nn(i, 'lu'), nn(i-1, 'lu'))
+        if n >= 2:
-            g.add_edge(nn(i, 'rd'), nn(i-1, 'rd'))
+            if i % 2:
-        else:
+                g.add_edge(nn(i, 'lu'), nn(i-1, 'lu'))
-            g.add_edge(nn(i, 'ld'), nn(i-1, 'ld'))
+                g.add_edge(nn(i, 'rd'), nn(i-1, 'rd'))
-            g.add_edge(nn(i, 'ru'), nn(i-1, 'ru'))
+            else:
+                g.add_edge(nn(i, 'ld'), nn(i-1, 'ld'))
+                g.add_edge(nn(i, 'ru'), nn(i-1, 'ru'))
 
-        #if not i % 2:
+            g.add_edge(nn(i, 'ls'), nn(i-1, 'rs'))
+            g.add_edge(nn(i, 'rs'), nn(i-1, 'ls'))
 
-        #elif i % 5 != 1:
+        if n >= 1 * throw_dist:
-        g.add_edge(nn(i, 'ls'), nn(i-1, 'rs'))
-        g.add_edge(nn(i, 'rs'), nn(i-1, 'ls'))
-
-        if i >= 1 * throw_dist:
             g.add_edge(nn(i, 'rs'), nn(i-(1*throw_dist), 'ls'))
             g.add_edge(nn(i, 'ls'), nn(i-(1*throw_dist), 'rs'))
 
-        if i >= 2 * throw_dist:
+        if n > 2 * throw_dist:
-            g.add_edge(nn(i, 'lu'), nn(i-(2*throw_dist), 'lu'))
+            a = nn(i, 'lu')
-        if i >= 3 * throw_dist:
+            b = nn(i-(2*throw_dist), 'lu')
-            g.add_edge(nn(i, 'ld'), nn(i-(3*throw_dist), 'ld'))
+            join_nodes(g, a, b)
-        if i >= 4 * throw_dist:
+        if n > 3 * throw_dist:
-            g.add_edge(nn(i, 'ru'), nn(i-(4*throw_dist), 'ru'))
+            a = nn(i, 'ld')
-        if i >= 5 * throw_dist:
+            b = nn(i-(3*throw_dist), 'ld')
-            g.add_edge(nn(i, 'rd'), nn(i-(5*throw_dist), 'rd'))
+            join_nodes(g, a, b)
-        if i >= 7 * throw_dist:
+        if n > 4 * throw_dist:
-            g.add_edge(nn(i, 'm'), nn(i-(7*throw_dist), 'm'))
+            a = nn(i, 'ru')
+            b = nn(i-(4*throw_dist), 'ru')
+            join_nodes(g, a, b)
+        if n > 5 * throw_dist:
+            a = nn(i, 'rd')
+            b = nn(i-(5*throw_dist), 'rd')
+            join_nodes(g, a, b)
+        if n > 7 * throw_dist:
+            a = nn(i, 'm')
+            b = nn(i-(7*throw_dist), 'm')
+            join_nodes(g, a, b)
 
-        stats.append(analyze(g))
+    return g
-        print(stats[-1])
-
-    return g, stats
 
 def analyze(G: nx.Graph) -> dict:
     N = G.number_of_nodes()
@@ -75,19 +98,57 @@ def analyze(G: nx.Graph) -> dict:
     return {
             'N': N,
             'E': E,
-            'Ступінь': S,
+            'S': S,
-            'Діаметр': D,
+            'D': D,
-            'Середній діаметр': D_average,
+            'D_avg': round(D_average, 4),
-            'Топологічний трафік': Q,
+            'T': round(Q, 4),
-            'Вартість': C,
+            'C': C,
     }
 
 def main():
-    g, r = analyze_network(1000)
+    i = 0
+
+    start_file('data.csv')
+    d = None
+
+    while True:
+        i += 1
+        g = build_network(i)
+
+        r = analyze(g)
+        r.update({"i": i})
+
+        '''
+        if d.__class__ == None.__class__:
+            d = pd.DataFrame(r, index = ['i', 'N', 'E', 'S', 'D', 'D_avg', 'T', 'C'])
+        else:
+            d.add(r)
+        '''
+
+        print(r)
+        write_file('data.csv', r)
+
+        if g.number_of_nodes() > 1000:
+            break
 
     #print(r)
+    #nx.draw(g, with_labels = True)
+    #plt.show()
+
+    #d.to_csv('data.csv')
+
+def test():
+    g = build_network(15)
+    print(analyze(g))
+    print([i for i, v in g.degree if v > 6])
+    print(g.adj['14-ld'])
     nx.draw(g, with_labels = True)
     plt.show()
 
+def test2():
+    g = build_network(150)
+    print(analyze(g))
+    print(set([v for i, v in g.degree()]))
+
 if __name__=="__main__":
     main()