3696789509

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Pull Request Pull Request #81: Update coveralls.io configuration

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60.42

/src/Utility/randomConnectionGenerator.py

import json

import numpy as np


class RandomConnectionGenerator:
    def __init__(self, N):
        """
        init
        @param N number of nodes of the topology
        """
        self.num_nodes = N

    # Output: list of tuples of request
    def randomConnectionGenerator(self, querynum, l_bw, u_bw, l_lat, u_lat, seed=2022):
        """
        Create a random TM
        @param querynum number of connections
        @return a list of connections, each of which is a list [src, des, bw, lat]
        """
        np.random.seed(seed)
        connection = []
        bw = self.lognormal((l_bw + u_bw) / 2.0, 1, querynum)
        if querynum <= self.num_nodes:
            for i in range(querynum):
                query = []
                query.append(np.random.randint(1, (self.num_nodes + 1) / 2.0))
                query.append(
                    np.random.randint((self.num_nodes + 1) / 2.0, self.num_nodes)
                )
                # query.append(np.random.randint(l_bw, u_bw))
                query.append(bw[i])
                query.append(np.random.randint(l_lat, u_lat))
                connection.append(tuple(query))
        else:
            for i in range(querynum):
                query = []
                src = np.random.randint(0, self.num_nodes)
                query.append(src)
                dest = np.random.randint(0, self.num_nodes)
                while dest == src:
                    dest = np.random.randint(0, self.num_nodes)
                query.append(dest)
                # query.append(np.random.randint(l_bw, u_bw))
                query.append(bw[i])
                query.append(np.random.randint(l_lat, u_lat))
                connection.append(tuple(query))

        with open("connection.json", "w") as json_file:
            data = connection
            json.dump(data, json_file, indent=4)

        return connection

    def lognormal(self, mu, sigma, size):
        normal_std = 0.5
        # normal_std = np.sqrt(np.log(1 + (sigma/mu)**2))
        normal_mean = np.log(mu) - normal_std**2 / 2
        return np.random.lognormal(normal_mean, normal_std, size)

    def random(self, min, mx, size):
        return np.random.randint(min, max, 1000)

    def linearGrouping(self, tm, k):
        if len(tm) > 20:
            tm.sort(key=lambda x: x[2])

        group_list = [tm[x : x + k] for x in range(0, len(tm), k)]

        # with open('splittedconnection.json', 'w') as json_file:
        #    data = splitted_list
        #    json.dump(data, json_file, indent=4)

        print(group_list)

        return group_list

    def geometricGrouping(self, tm, k):
        pass

    def altGeometricGrouping(self, tm, k):
        pass


# tm = RandomConnectionGenerator(20)
# connection = tm.randomConnectionGenerator(3, 100, 1000, 1000, 1500, 2022)
# split_connection = tm.connectionSplitter(5)

1	import json	3✔
2
3	import numpy as np	3✔
4
5
6	class RandomConnectionGenerator:	3✔
7	def __init__(self, N):	3✔
8	"""
9	init
10	@param N number of nodes of the topology
11	"""
12	self.num_nodes = N	3✔
13
14	# Output: list of tuples of request
15	def randomConnectionGenerator(self, querynum, l_bw, u_bw, l_lat, u_lat, seed=2022):	3✔
16	"""
17	Create a random TM
18	@param querynum number of connections
19	@return a list of connections, each of which is a list [src, des, bw, lat]
20	"""
21	np.random.seed(seed)	3✔
22	connection = []	3✔
23	bw = self.lognormal((l_bw + u_bw) / 2.0, 1, querynum)	3✔
24	if querynum <= self.num_nodes:	3✔
25	for i in range(querynum):	3✔
26	query = []	3✔
27	query.append(np.random.randint(1, (self.num_nodes + 1) / 2.0))	3✔
28	query.append(	3✔
29	np.random.randint((self.num_nodes + 1) / 2.0, self.num_nodes)
30	)
31	# query.append(np.random.randint(l_bw, u_bw))
32	query.append(bw[i])	3✔
33	query.append(np.random.randint(l_lat, u_lat))	3✔
34	connection.append(tuple(query))	3✔
35	else:
36	for i in range(querynum):	×
37	query = []	×
38	src = np.random.randint(0, self.num_nodes)	×
39	query.append(src)	×
40	dest = np.random.randint(0, self.num_nodes)	×
41	while dest == src:	×
42	dest = np.random.randint(0, self.num_nodes)	×
43	query.append(dest)	×
44	# query.append(np.random.randint(l_bw, u_bw))
45	query.append(bw[i])	×
46	query.append(np.random.randint(l_lat, u_lat))	×
47	connection.append(tuple(query))	×
48
49	with open("connection.json", "w") as json_file:	3✔
50	data = connection	3✔
51	json.dump(data, json_file, indent=4)	3✔
52
53	return connection	3✔
54
55	def lognormal(self, mu, sigma, size):	3✔
56	normal_std = 0.5	3✔
57	# normal_std = np.sqrt(np.log(1 + (sigma/mu)**2))
58	normal_mean = np.log(mu) - normal_std**2 / 2	3✔
59	return np.random.lognormal(normal_mean, normal_std, size)	3✔
60
61	def random(self, min, mx, size):	3✔
62	return np.random.randint(min, max, 1000)	×
63
64	def linearGrouping(self, tm, k):	3✔
65	if len(tm) > 20:	×
66	tm.sort(key=lambda x: x[2])	×
67
68	group_list = [tm[x : x + k] for x in range(0, len(tm), k)]	×
69
70	# with open('splittedconnection.json', 'w') as json_file:
71	# data = splitted_list
72	# json.dump(data, json_file, indent=4)
73
74	print(group_list)	×
75
76	return group_list	×
77
78	def geometricGrouping(self, tm, k):	3✔
79	pass	×
80
81	def altGeometricGrouping(self, tm, k):	3✔
82	pass	×
83
84
85	# tm = RandomConnectionGenerator(20)
86	# connection = tm.randomConnectionGenerator(3, 100, 1000, 1000, 1500, 2022)
87	# split_connection = tm.connectionSplitter(5)

atlanticwave-sdx / pce / 3696789509

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