3680947894

Build Type

github

Committed by GitHub

Commit Message

Merge a6cd61918 into b40be3bdd

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

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/src/Utility/results_plot_simulation.py

import json
import re

import matplotlib.pyplot as plt
import numpy as np


# Function to read
# last N lines of the file
def LastNlines(fname, N):
    # opening file using with() method
    # so that file get closed
    # after completing work
    results = None
    try:
        with open(fname) as file:

            # loop to read iterate
            # last n lines and convert to a dict
            results = {}
            for line in file.readlines()[-N:]:
                # print(line, end ='')
                list = re.split(", |=|;|:|\+", line.splitlines()[0])
                it = iter(list)
                res_dct = dict(zip(it, it))
                results = {**results, **res_dct}
            results["Script Execution Time"] = results["Script Execution Time"].split()[
                0
            ]
            print(results)
    except IOError as e:
        print(e)
    return results


def plot_simulation(path, title):
    tag = " Simulation"
    N = 5
    num_connection_list = []

    time_list_dict = {}
    total_util_list_dict = {}
    max_util_list_dict = {}
    mean_util_list_dict = {}
    std_util_list_dict = {}
    ninetypercetile_util_list_dict = {}
    objective_list_dict = {}

    for dir, name in title.items():
        time_list = []
        total_util_list = []
        max_util_list = []
        mean_util_list = []
        std_util_list = []
        ninetypercetile_util_list = []
        objective_list = []

        key = re.split(r"\D+", dir)[1]
        print("key=" + key)

        time_list_dict[key] = time_list
        total_util_list_dict[key] = total_util_list
        max_util_list_dict[key] = max_util_list
        mean_util_list_dict[key] = mean_util_list
        std_util_list_dict[key] = std_util_list
        ninetypercetile_util_list_dict[key] = ninetypercetile_util_list
        objective_list_dict[key] = objective_list

        for i in range(10, 210, 10):
            fname = path + dir + name + str(i) + ".out"
            results = LastNlines(fname, N)
            if results is not None:
                time_list.append(float(results["Script Execution Time"]))
                total_util_list.append(float(results["total_util"]))
                max_util_list.append(float(results["max_util"]))
                mean_util_list.append(float(results["mean_util"]))
                std_util_list.append(float(results["std_util"]))
                ninetypercetile_util_list.append(float(results["ninetypercetile_util"]))
                objective_list.append(float(results["Objective value "]))
            else:
                time_list.append(None)
                total_util_list.append(None)
                max_util_list.append(None)
                mean_util_list.append(None)
                std_util_list.append(None)
                ninetypercetile_util_list.append(None)
                objective_list.append(None)

    num_connection_list = [*range(10, 210, 10)]
    y_label = [
        "Compuation Time (s)",
        "Total Utility",
        "Max Utility",
        "Mean Utility",
        "STD Utility",
        "90% Utility",
        "Objective value",
    ]
    x_label = "Number of Connections"

    fig1, ax1 = plt.subplots()
    ax1.set_title(y_label[0])
    ax1.set_xlabel(x_label)
    for key in time_list_dict.keys():
        ax1.plot(num_connection_list, time_list_dict[key], label=str(key))
    # ax1.plot(num_connection_list,time_list, label = 'N=25')

    plt.legend()
    name = y_label[0] + tag + ".png"
    plt.savefig(name, bbox_inches="tight")

    fig2, ax2 = plt.subplots()
    ax2.set_title(y_label[1])
    ax2.set_xlabel(x_label)
    for key in total_util_list_dict.keys():
        ax2.plot(num_connection_list, total_util_list_dict[key], label=str(key))

    plt.legend()
    name = y_label[1] + tag + ".png"
    plt.savefig(name, bbox_inches="tight")
    ax2.legend()

    fig3, ax3 = plt.subplots()
    ax3.set_title(y_label[2])
    ax3.set_xlabel(x_label)
    for key in max_util_list_dict.keys():
        ax3.plot(num_connection_list, max_util_list_dict[key], label=str(key))

    plt.legend()
    name = y_label[2] + tag + ".png"
    plt.savefig(name, bbox_inches="tight")

    fig4, ax4 = plt.subplots()
    ax4.set_title(y_label[3])
    ax4.set_xlabel(x_label)
    for key in mean_util_list_dict.keys():
        ax4.plot(num_connection_list, mean_util_list_dict[key], label=str(key))
    plt.legend()
    name = y_label[3] + tag + ".png"
    plt.savefig(name, bbox_inches="tight")

    fig5, ax5 = plt.subplots()
    ax5.set_title(y_label[4])
    ax5.set_xlabel(x_label)
    for key in std_util_list_dict.keys():
        ax5.plot(num_connection_list, std_util_list_dict[key], label=str(key))
    plt.legend()
    name = y_label[4] + tag + ".png"
    plt.savefig(name, bbox_inches="tight")

    fig6, ax6 = plt.subplots()
    ax6.set_title(y_label[5])
    ax4.set_xlabel(x_label)
    for key in ninetypercetile_util_list_dict.keys():
        ax6.plot(
            num_connection_list, ninetypercetile_util_list_dict[key], label=str(key)
        )
    plt.legend()
    name = y_label[5] + tag + ".png"
    plt.savefig(name, bbox_inches="tight")

    fig7, ax7 = plt.subplots()
    ax7.set_title(y_label[6])
    ax4.set_xlabel(x_label)
    for key in objective_list_dict.keys():
        ax7.plot(num_connection_list, objective_list_dict[key], label=str(key))
    plt.legend()
    name = y_label[6] + tag + ".png"
    plt.savefig(name, bbox_inches="tight")


def plot_heur(title, path):
    tag = "heur"

    num_connection_list = []
    time_list = []
    weight_list = []
    util_list = []
    max_util_list = []
    for i in (2, 4, 8, 10):
        name = path + title + str(i) + ".out"
        num_connection_list.append(i)
        results = LastNlines(name, 2)
        time_list.append(float(results["Script Execution Time"]))
        weight_list.append(float(results["total_weight"]))
        util_list.append(float(results["total_util"]))
        max_util_list.append(float(results["max_util"]))

    y_label = ["Compuation Time (s)", "Total Weight", "Total Utility", "Max Utility"]
    x_label = "Number of Groups"
    fig1, ax1 = plt.subplots()
    ax1.set_title(y_label[0])
    ax1.set_xlabel(x_label)
    # for key in score_dict.keys():
    #    ax1.plot(missing_rate_list,score_dict[key], label = str(key))
    ax1.plot(num_connection_list, time_list, label="N=25")

    plt.legend()
    name = y_label[0] + tag + ".png"
    plt.savefig(name, bbox_inches="tight")

    fig2, ax2 = plt.subplots()
    ax2.set_title(y_label[1])
    ax2.set_xlabel(x_label)
    # for key in rmse_dict.keys():
    #    ax2.plot(missing_rate_list,rmse_dict[key], label = str(key))
    print(weight_list)
    ax2.plot(num_connection_list, weight_list, label="N=25")

    plt.legend()
    name = y_label[1] + tag + ".png"
    plt.savefig(name, bbox_inches="tight")

    fig3, ax3 = plt.subplots()
    ax3.set_title(y_label[2])
    ax3.set_xlabel(x_label)
    # for key in mse_dict.keys():
    #    ax3.plot(missing_rate_list,mse_dict[key], label = str(key))
    ax3.plot(num_connection_list, util_list, label="N=25")
    print(util_list)

    plt.legend()
    name = y_label[2] + tag + ".png"
    plt.savefig(name, bbox_inches="tight")

    fig4, ax4 = plt.subplots()
    ax4.set_title(y_label[3])
    ax4.set_xlabel(x_label)
    # for key in mse_dict.keys():
    #    ax3.plot(missing_rate_list,mse_dict[key], label = str(key))
    ax4.plot(num_connection_list, max_util_list, label="N=25")
    print(max_util_list)

    plt.legend()
    name = y_label[3] + tag + ".png"
    plt.savefig(name, bbox_inches="tight")


# Driver Code:
if __name__ == "__main__":
    # fname = '/Users/yxin/NSF/aw-sdx/sdx/pce/tests/results/simulation.57036414_10.out'
    # N = 2
    # LastNlines(fname, N)
    path = "../../tests/results/"
    title = {
        "out_simulation_50_10_28/": "simulation.57510402_",
        "out_simulation_25_10_28_200/": "simulation.57466833_",
    }
    plot_simulation(path, title)

    # title = "heur.57082350_"
    # path = '../../tests/results/out_heur_10_25/'
    # plot_heur(title,path)

1	import json	×
2	import re	×
3
4	import matplotlib.pyplot as plt	×
5	import numpy as np	×
6
7
8	# Function to read
9	# last N lines of the file
10	def LastNlines(fname, N):	×
11	# opening file using with() method
12	# so that file get closed
13	# after completing work
14	results = None	×
15	try:	×
16	with open(fname) as file:	×
17
18	# loop to read iterate
19	# last n lines and convert to a dict
20	results = {}	×
21	for line in file.readlines()[-N:]:	×
22	# print(line, end ='')
23	list = re.split(", \|=\|;\|:\|\+", line.splitlines()[0])	×
24	it = iter(list)	×
25	res_dct = dict(zip(it, it))	×
26	results = {results, res_dct}	×
27	results["Script Execution Time"] = results["Script Execution Time"].split()[	×
28	0
29	]
30	print(results)	×
31	except IOError as e:	×
32	print(e)	×
33	return results	×
34
35
36	def plot_simulation(path, title):	×
37	tag = " Simulation"	×
38	N = 5	×
39	num_connection_list = []	×
40
41	time_list_dict = {}	×
42	total_util_list_dict = {}	×
43	max_util_list_dict = {}	×
44	mean_util_list_dict = {}	×
45	std_util_list_dict = {}	×
46	ninetypercetile_util_list_dict = {}	×
47	objective_list_dict = {}	×
48
49	for dir, name in title.items():	×
50	time_list = []	×
51	total_util_list = []	×
52	max_util_list = []	×
53	mean_util_list = []	×
54	std_util_list = []	×
55	ninetypercetile_util_list = []	×
56	objective_list = []	×
57
58	key = re.split(r"\D+", dir)[1]	×
59	print("key=" + key)	×
60
61	time_list_dict[key] = time_list	×
62	total_util_list_dict[key] = total_util_list	×
63	max_util_list_dict[key] = max_util_list	×
64	mean_util_list_dict[key] = mean_util_list	×
65	std_util_list_dict[key] = std_util_list	×
66	ninetypercetile_util_list_dict[key] = ninetypercetile_util_list	×
67	objective_list_dict[key] = objective_list	×
68
69	for i in range(10, 210, 10):	×
70	fname = path + dir + name + str(i) + ".out"	×
71	results = LastNlines(fname, N)	×
72	if results is not None:	×
73	time_list.append(float(results["Script Execution Time"]))	×
74	total_util_list.append(float(results["total_util"]))	×
75	max_util_list.append(float(results["max_util"]))	×
76	mean_util_list.append(float(results["mean_util"]))	×
77	std_util_list.append(float(results["std_util"]))	×
78	ninetypercetile_util_list.append(float(results["ninetypercetile_util"]))	×
79	objective_list.append(float(results["Objective value "]))	×
80	else:
81	time_list.append(None)	×
82	total_util_list.append(None)	×
83	max_util_list.append(None)	×
84	mean_util_list.append(None)	×
85	std_util_list.append(None)	×
86	ninetypercetile_util_list.append(None)	×
87	objective_list.append(None)	×
88
89	num_connection_list = [*range(10, 210, 10)]	×
90	y_label = [	×
91	"Compuation Time (s)",
92	"Total Utility",
93	"Max Utility",
94	"Mean Utility",
95	"STD Utility",
96	"90% Utility",
97	"Objective value",
98	]
99	x_label = "Number of Connections"	×
100
101	fig1, ax1 = plt.subplots()	×
102	ax1.set_title(y_label[0])	×
103	ax1.set_xlabel(x_label)	×
104	for key in time_list_dict.keys():	×
105	ax1.plot(num_connection_list, time_list_dict[key], label=str(key))	×
106	# ax1.plot(num_connection_list,time_list, label = 'N=25')
107
108	plt.legend()	×
109	name = y_label[0] + tag + ".png"	×
110	plt.savefig(name, bbox_inches="tight")	×
111
112	fig2, ax2 = plt.subplots()	×
113	ax2.set_title(y_label[1])	×
114	ax2.set_xlabel(x_label)	×
115	for key in total_util_list_dict.keys():	×
116	ax2.plot(num_connection_list, total_util_list_dict[key], label=str(key))	×
117
118	plt.legend()	×
119	name = y_label[1] + tag + ".png"	×
120	plt.savefig(name, bbox_inches="tight")	×
121	ax2.legend()	×
122
123	fig3, ax3 = plt.subplots()	×
124	ax3.set_title(y_label[2])	×
125	ax3.set_xlabel(x_label)	×
126	for key in max_util_list_dict.keys():	×
127	ax3.plot(num_connection_list, max_util_list_dict[key], label=str(key))	×
128
129	plt.legend()	×
130	name = y_label[2] + tag + ".png"	×
131	plt.savefig(name, bbox_inches="tight")	×
132
133	fig4, ax4 = plt.subplots()	×
134	ax4.set_title(y_label[3])	×
135	ax4.set_xlabel(x_label)	×
136	for key in mean_util_list_dict.keys():	×
137	ax4.plot(num_connection_list, mean_util_list_dict[key], label=str(key))	×
138	plt.legend()	×
139	name = y_label[3] + tag + ".png"	×
140	plt.savefig(name, bbox_inches="tight")	×
141
142	fig5, ax5 = plt.subplots()	×
143	ax5.set_title(y_label[4])	×
144	ax5.set_xlabel(x_label)	×
145	for key in std_util_list_dict.keys():	×
146	ax5.plot(num_connection_list, std_util_list_dict[key], label=str(key))	×
147	plt.legend()	×
148	name = y_label[4] + tag + ".png"	×
149	plt.savefig(name, bbox_inches="tight")	×
150
151	fig6, ax6 = plt.subplots()	×
152	ax6.set_title(y_label[5])	×
153	ax4.set_xlabel(x_label)	×
154	for key in ninetypercetile_util_list_dict.keys():	×
155	ax6.plot(	×
156	num_connection_list, ninetypercetile_util_list_dict[key], label=str(key)
157	)
158	plt.legend()	×
159	name = y_label[5] + tag + ".png"	×
160	plt.savefig(name, bbox_inches="tight")	×
161
162	fig7, ax7 = plt.subplots()	×
163	ax7.set_title(y_label[6])	×
164	ax4.set_xlabel(x_label)	×
165	for key in objective_list_dict.keys():	×
166	ax7.plot(num_connection_list, objective_list_dict[key], label=str(key))	×
167	plt.legend()	×
168	name = y_label[6] + tag + ".png"	×
169	plt.savefig(name, bbox_inches="tight")	×
170
171
172	def plot_heur(title, path):	×
173	tag = "heur"	×
174
175	num_connection_list = []	×
176	time_list = []	×
177	weight_list = []	×
178	util_list = []	×
179	max_util_list = []	×
180	for i in (2, 4, 8, 10):	×
181	name = path + title + str(i) + ".out"	×
182	num_connection_list.append(i)	×
183	results = LastNlines(name, 2)	×
184	time_list.append(float(results["Script Execution Time"]))	×
185	weight_list.append(float(results["total_weight"]))	×
186	util_list.append(float(results["total_util"]))	×
187	max_util_list.append(float(results["max_util"]))	×
188
189	y_label = ["Compuation Time (s)", "Total Weight", "Total Utility", "Max Utility"]	×
190	x_label = "Number of Groups"	×
191	fig1, ax1 = plt.subplots()	×
192	ax1.set_title(y_label[0])	×
193	ax1.set_xlabel(x_label)	×
194	# for key in score_dict.keys():
195	# ax1.plot(missing_rate_list,score_dict[key], label = str(key))
196	ax1.plot(num_connection_list, time_list, label="N=25")	×
197
198	plt.legend()	×
199	name = y_label[0] + tag + ".png"	×
200	plt.savefig(name, bbox_inches="tight")	×
201
202	fig2, ax2 = plt.subplots()	×
203	ax2.set_title(y_label[1])	×
204	ax2.set_xlabel(x_label)	×
205	# for key in rmse_dict.keys():
206	# ax2.plot(missing_rate_list,rmse_dict[key], label = str(key))
207	print(weight_list)	×
208	ax2.plot(num_connection_list, weight_list, label="N=25")	×
209
210	plt.legend()	×
211	name = y_label[1] + tag + ".png"	×
212	plt.savefig(name, bbox_inches="tight")	×
213
214	fig3, ax3 = plt.subplots()	×
215	ax3.set_title(y_label[2])	×
216	ax3.set_xlabel(x_label)	×
217	# for key in mse_dict.keys():
218	# ax3.plot(missing_rate_list,mse_dict[key], label = str(key))
219	ax3.plot(num_connection_list, util_list, label="N=25")	×
220	print(util_list)	×
221
222	plt.legend()	×
223	name = y_label[2] + tag + ".png"	×
224	plt.savefig(name, bbox_inches="tight")	×
225
226	fig4, ax4 = plt.subplots()	×
227	ax4.set_title(y_label[3])	×
228	ax4.set_xlabel(x_label)	×
229	# for key in mse_dict.keys():
230	# ax3.plot(missing_rate_list,mse_dict[key], label = str(key))
231	ax4.plot(num_connection_list, max_util_list, label="N=25")	×
232	print(max_util_list)	×
233
234	plt.legend()	×
235	name = y_label[3] + tag + ".png"	×
236	plt.savefig(name, bbox_inches="tight")	×
237
238
239	# Driver Code:
240	if __name__ == "__main__":	×
241	# fname = '/Users/yxin/NSF/aw-sdx/sdx/pce/tests/results/simulation.57036414_10.out'
242	# N = 2
243	# LastNlines(fname, N)
244	path = "../../tests/results/"	×
245	title = {	×
246	"out_simulation_50_10_28/": "simulation.57510402_",
247	"out_simulation_25_10_28_200/": "simulation.57466833_",
248	}
249	plot_simulation(path, title)	×
250
251	# title = "heur.57082350_"
252	# path = '../../tests/results/out_heur_10_25/'
253	# plot_heur(title,path)

atlanticwave-sdx / pce / 3680947894

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