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ProjTry2.py

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+import networkx as nx
+import operator
+import matplotlib.pyplot as plt
+import random as rnd
+import collections
+
+#ls = [1,2,3,4]
+ls = []
+
+k=10
+
+for i in range(1,k):
+    ls.append(i)
+
+Gr = nx.Graph()
+Gr.add_nodes_from(ls)
+
+
+for i in range(0,int(k*2)):
+    j = rnd.choice(ls)
+    k = rnd.choice(ls)
+    Gr.add_edge(j,k)
+
+#Gr.add_edge(2,3)
+
+'''
+G.add_edge(1,2)
+#G.add_edge(1,3)
+G.add_edge(2,3)
+G.add_edge(2,4)
+G.add_edge(2,10)
+G.add_edge(1,9)
+G.add_edge(4,8)
+G.add_edge(6,1)
+G.add_edge(6,10)
+G.add_edge(5,2)
+'''
+
+def degreeHistogram(G,clr):
+    degree_sequence = sorted([d for n, d in G.degree()], reverse=True)
+    degreeCount = collections.Counter(degree_sequence)
+    deg, cnt = zip(*degreeCount.items())
+    plt.bar(deg, cnt, width=0.80, color=clr)
+    plt.title("Degree Histogram")
+    plt.ylabel("Count")
+    plt.xlabel("Degree")
+    plt.show()
+
+#probability of each node's degree
+#in resepect to WHOLE NETWORK
+def perMap(G):
+    per = []
+    permap = {}
+    temp = nx.degree(G)
+    sum = 0
+    for i in temp:
+        sum = sum + i[1]
+    for i in temp:
+        per.append(i[1]/sum)
+    for i,j in zip(temp,per):
+        permap[i[0]]=j
+    return permap
+
+#ROULETTE METHOD
+def perMapRange(permap):
+    #first mapping permap to [0,1]
+    permap_mapped = {}
+    _sum = 0.0
+    for keys in permap:
+        _sum = _sum + permap[keys]
+    for keys in permap:
+        permap_mapped[keys] = permap[keys]/_sum
+    #finding out ranges     
+    permaprange = {}
+    prev = 0.0
+    sorted_permap = dict(sorted(permap_mapped.items(), key=operator.itemgetter(1)))
+    for keys in sorted_permap:
+        t = []
+        new = sorted_permap[keys]
+        margin = 0.00001
+        a = prev
+        b = new+prev-margin
+        if a==0.0 and b==-margin:
+            t.append(0.0)
+            t.append(0.0)
+        else:
+            t.append(a)
+            t.append(new+prev-margin)
+        permaprange[keys] = tuple(t)
+        prev = new+prev
+        del t        
+    return permaprange
+
+def prefAttachment(G):
+    permap = perMap(G)
+    #print('Permap: {}'.format(permap))
+    permaprange = perMapRange(permap)
+    #print('\nPermarange: {}'.format(permaprange))
+    G.add_node('NEW')
+    #randInt to select a node from permarange
+    select = rnd.randint(0,100)/100
+    print('\n\nselect probability: {}'.format(select))
+    for keys in permaprange:
+        t = permaprange[keys]
+        if select>=t[0] and select<=t[1]:
+            print('Node Choosed: {}, Its degree: {}'.format(keys,G.degree(int(keys))))
+            #G.add_edge(rnd.randint(0,10),keys)
+            G.add_edge('NEW',keys)
+
+for i in range(0,int(k*5)):
+    prefAttachment(Gr)
+
+d = dict(nx.degree(Gr))
+pos = nx.circular_layout(Gr)
+nx.draw(Gr,pos,node_size=[v*100 for v in d.values()],node_color='y', with_labels=True)
+plt.show()
+degreeHistogram(Gr,'r')

projBackup.py

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+# -*- coding: utf-8 -*-
+"""
+Created on Mon Feb 18 14:19:14 2019
+
+@author: Om
+"""
+
+#Imported Packages
+#import numpy as np
+import random as rnd
+import matplotlib.pyplot as plt
+import networkx as nx
+
+###### GLOBAL VARIABLES ######
+nodes = [] #nodes list 
+D = 500 #Max size of WSN deployment area
+N = 250#Number of Nodes
+R = 50 #Radius of transmission 
+##############################
+
+####### FUNCTIONS ######## 
+
+#function to sort values in the nodes
+def sorti(n):
+    return(sorted(nodes,key=lambda x:x[0])) #sorting via 'x'
+
+def distance(i,j):
+    x = abs(i[0]-j[0])
+    y = abs(i[1]-j[1])
+    d = (x**2 + y**2)**(1/2)
+    return d    
+
+def neighbour():
+    nodes_nbr = {} #dict of nbrs
+    temp_nodes = nodes.copy()
+    for i in nodes:
+        temp_nbr = []
+        for j in temp_nodes:
+            if distance(i,j) < R and j!=i:
+                temp_nbr.append(j)
+        nodes_nbr[tuple(i)] = temp_nbr
+        del temp_nbr
+    return nodes_nbr
+
+#function to generate nodes
+def generateNode():
+    i=0
+    while i<N:
+        tempNode1 = rnd.randint(0,D)
+        tempNode2 = rnd.randint(0,D)
+        tempNodes = []
+        tempNodes.append(tempNode1)
+        tempNodes.append(tempNode2)
+        if not nodes:
+            nodes.append(tempNodes)
+            i = i+1
+        else:
+            if tempNodes not in nodes:
+                nodes.append(tempNodes)
+                i = i+1
+
+#function to plot nodes 
+def plotNodes():
+    x = []
+    y = []
+    for i in nodes:
+        x.append(i[0])
+        y.append(i[1])
+    fig = plt.figure()
+    ax = fig.add_subplot(111)
+    plt.plot(x,y,'ro')
+    for i,j in zip(x,y):
+        ax.annotate('%s)' %j, xy=(i,j), xytext=(30,0), textcoords='offset points')
+        ax.annotate('(%s,' %i, xy=(i,j))
+    plt.grid()
+    plt.show()
+
+#function to print nodes and neighbour pair
+def printPairs(data):
+    for key in data:
+        print('{} -> {} \n'.format(key,data[tuple(key)]))
+
+#function to generate network from nodePair data
+def generateGraph(data):
+    G = nx.Graph()
+    for key in data:
+        nbr = data[tuple(key)]
+        for i in nbr:
+            G.add_edge(tuple(key),tuple(i))
+    d = nx.degree(G)
+    print(d)
+    print(nx.clustering(G))
+    pos = nx.spring_layout(G)
+    nx.draw(G,pos,node_size=6)
+    plt.show()
+
+
+##########################
+
+#Calling function to generate nodes
+generateNode()
+
+#Calling function generate node & neighbour pairs
+nodePair  = neighbour()
+
+#Calling function to print the pair
+#printPairs(nodePair)
+
+#Calling function to generate graph
+generateGraph(nodePair)
+
+#Plot the graph
+plotNodes()

projBackup_2.py

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+# -*- coding: utf-8 -*-
+"""
+Created on Mon Feb 18 18:47:25 2019
+
+@author: Om
+"""
+
+#Imported Packages
+#import numpy as np
+import random as rnd
+import matplotlib.pyplot as plt
+import networkx as nx
+import collections
+
+###### GLOBAL VARIABLES ######
+nodes = [] #nodes list 
+D = 500 #Max size of WSN deployment area
+N = 250#Number of Nodes
+R = 50 #Radius of transmission 
+##############################
+
+####### FUNCTIONS ######## 
+
+#function to sort values in the nodes
+def sorti(n):
+    return(sorted(nodes,key=lambda x:x[0])) #sorting via 'x'
+
+def distance(i,j):
+    x = abs(i[0]-j[0])
+    y = abs(i[1]-j[1])
+    d = (x**2 + y**2)**(1/2)
+    return d    
+
+def neighbour():
+    nodes_nbr = {} #dict of nbrs
+    temp_nodes = nodes.copy()
+    for i in nodes:
+        temp_nbr = []
+        for j in temp_nodes:
+            if distance(i,j) < R and j!=i:
+                temp_nbr.append(j)
+        nodes_nbr[tuple(i)] = temp_nbr
+        del temp_nbr
+    return nodes_nbr
+
+#function to generate nodes
+def generateNode():
+    i=0
+    while i<N:
+        tempNode1 = rnd.randint(0,D)
+        tempNode2 = rnd.randint(0,D)
+        tempNodes = []
+        tempNodes.append(tempNode1)
+        tempNodes.append(tempNode2)
+        if not nodes:
+            nodes.append(tempNodes)
+            i = i+1
+        else:
+            if tempNodes not in nodes:
+                nodes.append(tempNodes)
+                i = i+1
+
+#function to plot nodes 
+def plotNodes():
+    x = []
+    y = []
+    for i in nodes:
+        x.append(i[0])
+        y.append(i[1])
+    fig = plt.figure()
+    ax = fig.add_subplot(111)
+    plt.plot(x,y,'ro')
+    for i,j in zip(x,y):
+        ax.annotate('%s)' %j, xy=(i,j), xytext=(30,0), textcoords='offset points')
+        ax.annotate('(%s,' %i, xy=(i,j))
+    plt.grid()
+    plt.show()
+
+#function to print nodes and neighbour pair
+def printPairs(data):
+    for key in data:
+        print('{} -> {} \n'.format(key,data[tuple(key)]))
+
+#function to generate network from nodePair data
+'''
+def generateGraph(data):
+    G = nx.Graph()
+    for key in data:
+        nbr = data[tuple(key)]
+        for i in nbr:
+            G.add_edge(tuple(key),tuple(i))
+    d = nx.degree(G)
+    print(d)
+    print(nx.clustering(G))
+    pos = nx.spring_layout(G)
+    nx.draw(G,pos,node_size=6)
+    plt.show()
+'''
+
+def generateGraph(data):
+    G = nx.Graph()
+    for i in nodes:
+        G.add_node(tuple(i),pos=i)
+    for key in data:
+        nbr = data[tuple(key)]
+        for i in nbr:
+            G.add_edge(tuple(i),tuple(key))
+    pos = nx.get_node_attributes(G,'pos')
+    d = dict(nx.degree(G))
+    nx.draw(G,pos,node_size=[v*10 for v in d.values()],node_color='g')
+    plt.title("WSN with edges to all neighbours: Area {} X {}".format(D,D))
+    plt.show()
+    return G
+
+def degreeHistogram(G):
+    degree_sequence = sorted([d for n, d in G.degree()], reverse=True)
+    degreeCount = collections.Counter(degree_sequence)
+    deg, cnt = zip(*degreeCount.items())
+    plt.bar(deg, cnt, width=0.80, color='b')
+    plt.title("Degree Histogram")
+    plt.ylabel("Count")
+    plt.xlabel("Degree")
+    plt.show()
+
+
+##########################
+
+#Calling function to generate nodes
+generateNode()
+
+#Calling function generate node & neighbour pairs
+nodePair  = neighbour()
+
+#Calling function to print the pair
+#printPairs(nodePair)
+
+#Calling function to generate graph
+G = generateGraph(nodePair)
+
+#calling function to generate degree historgram
+degreeHistogram(G)
+
+#Plot the graph
+#plotNodes()