260 lines
8.1 KiB
Python
260 lines
8.1 KiB
Python
import matplotlib.pyplot as plt
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import networkx as nx
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import pandas as pd
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nn_total_levels = 0
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def nn(cluster_no, node_name):
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if not nn_total_levels:
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return str(cluster_no) + '-' + node_name
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return str(cluster_no % nn_total_levels) + '-' + node_name
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def lvl(node_name):
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return int(node_name.split('-')[0])
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def join_nodes(g, a, b, target_degree = 6):
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if not (g.degree[a] == target_degree or g.degree[b] == target_degree):
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g.add_edge(a, b)
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def start_file(p):
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index = ['i', 'N', 'E', 'S', 'D', 'D_avg', 'T', 'C']
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open(p, 'w').write(','.join(index) + '\n')
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def write_file(p, data):
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index = ['i', 'N', 'E', 'S', 'D', 'D_avg', 'T', 'C']
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open(p, 'a').write(','.join([str(data[i]) for i in index]) + '\n')
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def build_cluster(n):
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g = nx.Graph()
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nodes = ['ls', 'lu', 'ld', 'm', 'rd', 'ru', 'rs']
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edges = [('ls', 'lu'), ('ls', 'ld'), ('ld', 'lu'),
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('rs', 'ru'), ('rs', 'rd'), ('rd', 'ru'),
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('lu', 'm'), ('ld', 'm'),
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('ru', 'm'), ('rd', 'm')]
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g.add_nodes_from([nn(n, x) for x in nodes])
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g.add_edges_from([tuple(nn(n, y) for y in x) for x in edges])
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return g
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def build_network(n):
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throw_dist = 4
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g = build_cluster(0)
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global nn_total_levels
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nn_total_levels = n
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for i in range(1, n):
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c = build_cluster(i)
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g = nx.union(g, c)
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for i in range(n):
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if n >= 2:
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if i % 2:
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join_nodes(g, nn(i, 'lu'), nn(i-1, 'lu'), 4)
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join_nodes(g, nn(i, 'rd'), nn(i-1, 'rd'), 4)
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else:
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join_nodes(g, nn(i, 'ld'), nn(i-1, 'ld'), 4)
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join_nodes(g, nn(i, 'ru'), nn(i-1, 'ru'), 4)
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g.add_edge(nn(i, 'ls'), nn(i-1, 'rs'))
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g.add_edge(nn(i, 'rs'), nn(i-1, 'ls'))
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if n > 1 * throw_dist:
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g.add_edge(nn(i, 'rs'), nn(i-(1*throw_dist), 'ls'))
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g.add_edge(nn(i, 'ls'), nn(i-(1*throw_dist), 'rs'))
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if n > 2 * throw_dist:
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a = nn(i, 'lu')
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b = nn(i-(2*throw_dist), 'lu')
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join_nodes(g, a, b)
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if n > 3 * throw_dist:
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a = nn(i, 'ld')
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b = nn(i-(3*throw_dist), 'ld')
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join_nodes(g, a, b)
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if n > 4 * throw_dist:
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a = nn(i, 'ru')
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b = nn(i-(4*throw_dist), 'ru')
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join_nodes(g, a, b)
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if n > 5 * throw_dist:
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a = nn(i, 'rd')
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b = nn(i-(5*throw_dist), 'rd')
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join_nodes(g, a, b)
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if n > 7 * throw_dist:
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a = nn(i, 'm')
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b = nn(i-(7*throw_dist), 'm')
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join_nodes(g, a, b)
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return g
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def analyze(G: nx.Graph) -> dict:
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N = G.number_of_nodes()
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E = G.number_of_edges()
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degs = G.degree()
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s_vals = [s[1] for s in degs]
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S = max(s_vals)
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D = nx.diameter(G)
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D_average = nx.average_shortest_path_length(G)
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Q = N*D_average/E
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C = N*D*S
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return {
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'N': N,
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'E': E,
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'S': S,
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'D': D,
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'D_avg': round(D_average, 4),
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'T': round(Q, 4),
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'C': C,
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}
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def visualize(g):
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def draw_edges_between(a, b, lvl_min = 0, lvl_max = False, color = 'black', width = 1.0, debug = False, direct = False):
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edgelist = [e for e in g.edges() if all([True if (a in i) or (b in i) else False for i in e])]
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if debug:
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print(edgelist)
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if lvl_max.__class__ == bool:
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if debug:
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print("Running 1 branch")
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edgelist = [(pa, pb) for pa, pb in edgelist if not (abs(lvl(pa) - lvl(pb)) < lvl_min or nn_total_levels - abs(lvl(pa) - lvl(pb)) < lvl_min)]
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'''
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for p in edgelist:
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if abs(lvl(pa) - lvl(pb)) < lvl_min:
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edgelist.remove((pa, pb))
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'''
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else:
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if debug:
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print(f"Running 2 branch on {edgelist}")
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edgelist = [(pa, pb) for pa, pb in edgelist if not ((abs(lvl(pa) - lvl(pb)) < lvl_min or nn_total_levels - abs(lvl(pa) - lvl(pb)) < lvl_min) or (abs(lvl(pa) - lvl(pb)) > lvl_max and nn_total_levels - abs(lvl(pa) - lvl(pb)) > lvl_max))]
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'''
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for pa, pb in edgelist:
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if debug:
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print(f"Processing ({pa}, {pb})")
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if abs(lvl(pa) - lvl(pb)) < lvl_min or abs(lvl(pa) - lvl(pb)) > lvl_max:
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edgelist.remove((pa, pb))
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if debug:
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print(f'Discarding {pa} <-> {pb} (lvl(pa) == {lvl(pa)}, lvl(pb) == {lvl(pb)})')
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elif debug:
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print(f'Leaving {pa} <-> {pb} (lvl(pa) == {lvl(pa)}, lvl(pb) == {lvl(pb)})')
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for pa, pb in edgelist:
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if debug:
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print(f"Processing ({pa}, {pb})")
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if abs(lvl(pa) - lvl(pb)) < lvl_min or abs(lvl(pa) - lvl(pb)) > lvl_max:
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edgelist.remove((pa, pb))
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if debug:
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print(f'Discarding {pa} <-> {pb} (lvl(pa) == {lvl(pa)}, lvl(pb) == {lvl(pb)})')
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elif debug:
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print(f'Leaving {pa} <-> {pb} (lvl(pa) == {lvl(pa)}, lvl(pb) == {lvl(pb)})')
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'''
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if debug:
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print(edgelist)
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if direct:
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nx.draw_networkx_edges(g, exp_pos, edgelist = edgelist, width = width, edge_color = color)
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else:
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nx.draw_networkx_edges(g, exp_pos, edgelist = edgelist, connectionstyle='arc3,rad=0.2', arrows=True, width = width, edge_color = color)
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pos = {
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'ls': (-2, 0),
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'lu': (-1, 1),
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'ld': (-1, -1),
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'm' : (0, 0),
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'ru': (1, 1),
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'rd': (1, -1),
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'rs': (2, 0)
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}
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exp_pos = {}
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for i in range(nn_total_levels):
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for j, v in pos.items():
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exp_pos[nn(i, j)] = (v[0], v[1] * 0.65 + 3 * i)
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nx.draw_networkx_nodes(g, exp_pos, node_size = 600)
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nx.draw_networkx_labels(g, exp_pos, font_size = 8)
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#nx.draw_networkx_edges(g, exp_pos, edgelist = [e for e in g.edges() if all([True if ('ls' in i) or ('rs' in i) else False for i in e])], connectionstyle='arc3,rad=0.2', arrows=True)
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# cluster
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draw_edges_between('', '', lvl_max = 0, color = '#888888', width = 0.5, direct = True)
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# S => 4
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draw_edges_between('ls', 'rs', lvl_max = 1, color = '#33AAAA', width = 2)
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draw_edges_between('lu', 'lu', lvl_max = 1, color = '#AAAA33', width = 1)
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draw_edges_between('ru', 'ru', lvl_max = 1, color = '#AAAA33', width = 1)
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draw_edges_between('ld', 'ld', lvl_max = 1, color = '#AAAA33', width = 1)
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draw_edges_between('rd', 'rd', lvl_max = 1, color = '#AAAA33', width = 1)
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# S => 6
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draw_edges_between('lu', 'lu', lvl_min = 2, color = '#FF0000', width = 1.5)
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draw_edges_between('ld', 'ld', lvl_min = 2, color = '#FFFF00', width = 1.5)
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draw_edges_between('ru', 'ru', lvl_min = 2, color = '#00FF00', width = 1.5)
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draw_edges_between('rd', 'rd', lvl_min = 2, color = '#00FFFF', width = 1.5)
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draw_edges_between('ls', 'ls', lvl_min = 2, color = '#0000FF', width = 1.5)
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draw_edges_between('rs', 'rs', lvl_min = 2, color = '#FF00FF', width = 1.5)
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draw_edges_between('m' , 'm' , lvl_min = 2, color = '#000000', width = 1.5)
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plt.show()
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def main():
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i = 0
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start_file('data.csv')
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d = None
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while True:
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i += 1
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g = build_network(i)
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r = analyze(g)
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r.update({"i": i})
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'''
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if d.__class__ == None.__class__:
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d = pd.DataFrame(r, index = ['i', 'N', 'E', 'S', 'D', 'D_avg', 'T', 'C'])
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else:
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d.add(r)
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'''
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print(r)
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write_file('data.csv', r)
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if g.number_of_nodes() > 1000:
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break
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#print(r)
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#nx.draw(g, with_labels = True)
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#plt.show()
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#d.to_csv('data.csv')
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def test():
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g = build_network(15)
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print(analyze(g))
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print([i for i, v in g.degree if v > 6])
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print(g.adj['14-ld'])
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nx.draw(g, with_labels = True)
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plt.show()
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def test2():
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g = build_network(144)
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print(analyze(g))
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print(set([v for i, v in g.degree()]))
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def test3():
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g = build_network(3)
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#print(g.adj['0-ls'])
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visualize(g)
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if __name__=="__main__":
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test3()
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