def diameter_vs_prob(k, q, probs):
"""diameter and clustering coefficient vs rewiring prob with k trials"""
xdata = []
ydata = []
# zdata = []
# prob = 0.0005
# while prob < 0.5:
for prob in probs:
print(prob)
xdata += [prob]
diameters = []
# coeffs = []
for i in range(k):
graph = make_ring_graph(20, 20, prob, q)
diameters += [diameter(graph)]
# coeffs += [clustering_coefficient(graph)]
ydata += [sum(diameters) / k
] #divide by 19 as this diameter of circle lattice
# zdata += [sum(coeffs) / k / 0.7] #divide by 0.7 as this is clustering coefficient of circle lattice
# prob = 1.2*prob#*1.1
return xdata, ydata #, zdata
margin=dict(b=20, l=5, r=5, t=40),
annotations=[
dict(
text=
"Python code: <a href='https://plot.ly/ipython-notebooks/network-graphs/'> https://plot.ly/ipython-notebooks/network-graphs/</a>",
showarrow=False,
xref="paper",
yref="paper",
x=0.005,
y=-0.002)
],
xaxis=dict(showgrid=False, zeroline=False, showticklabels=False),
yaxis=dict(showgrid=False, zeroline=False, showticklabels=False)))
plot(fig)
if __name__ == "__main__":
m, k = 12, 6
p, q = 0.495, 0.005
# p + q = 0.5
# investigate diameter
graph = make_ring_graph(m, k, p, q)
brilliance = br(graph)
# {0:{v1, v2, ..}, 1:{v, ...}, ...}
# graph = {0:[2, 5, 9, 11, 13],1:[7, 9, 12, 13],2:[0,6,7,11],3:[4,8,10,12],4:[3,9],5:[0,7,12],6:[2],7:[1,2,5],8:[3],9:[0,1,4],10:[3],11:[0,2],12:[1,3,5],13:[0,1]}
draw_network(graph)
###################################################################
'''RANDOM RING GRAPHS'''
m, k = 20, 20
rrg = [(m, k, 0.5 - x * 0.05) for x in range(11)] #(m, k, p, q)
xs, ys = [], []
exps = []
ranges = []
for b in rrg:
d_size = 600
d = {}
for i in range(d_size):
d[i] = 0
a = 20
for i in range(a):
g = make_ring_graph(b[0], b[1], b[2], 0.5 - b[2])
dg = in_degree_distribution(g)
for i in range(d_size):
if i in dg.keys():
d[i] += float(dg[i]) / a
total = 0
for i in range(d_size):
if d[i] == 0:
del d[i]
else:
total += float(i * d[i]) / (b[0] * b[1])
exps.append(total)
x, y = d.keys(), d.values()
x = [float(x_i) * b[2]**0 for x_i in x]
y = [float(y_i) / (b[0] * b[1]) for y_i in y]
ranges.append(find_range(x, y))