Newer
Older
# Copyright 2022-2025 ETSI SDG TeraFlowSDN (TFS) (https://tfs.etsi.org/)
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
import enum, sys
import numpy as np
import matplotlib.pyplot as plt
class PlotName(enum.Enum):
DEVICE_DRIVER_MW = 'dev-drv-mw'
SERVICE_HANDLER_MW = 'srv-hlr-mw'
plot_name = PlotName.__members__.get(sys.argv[1])
if plot_name is None: raise Exception('Unsupported plot: {:s}'.format(str(plot_name)))
PLOTS = {
PlotName.DEVICE_DRIVER_MW: (
#'Device Driver - MicroWave', '0.0001-100', [
# ('GetConfig', [0,0,0,0,0,0,0,0,0,0,0,0,0,0,1,0,10,172,0,1,0,0,0,0,0,0]),
# ('SetConfig', [89,1,0,0,0,0,0,0,0,0,0,0,0,0,0,6,34,50,1,0,0,0,0,0,0,0]),
# ('DeleteConfig', [90,1,0,0,0,0,0,0,0,0,0,0,0,0,2,3,0,4,72,12,0,0,0,0,0,0]),
#]),
'Device Driver - MicroWave', '0.1-10', [
('GetConfig', [0,1,0,10,172,0,1,0]),
('SetConfig', [0,0,6,34,50,1,0,0]),
('DeleteConfig', [0,2,3,0,4,72,12,0]),
]),
PlotName.SERVICE_HANDLER_MW: (
'Service Handler - L2NM MicroWave', '1-100', [
('SetEndpoint', [0,1,0,1,5,75,6,0]),
('DeleteEndpoint', [0,0,0,0,1,77,17,0]),
]),
}
BINS_RANGES = {
'0.0001-100' : [0, 0.0001, 0.00025, 0.0005, 0.00075, 0.001, 0.0025, 0.005, 0.0075,
0.01, 0.025, 0.05, 0.075, 0.1, 0.25, 0.5, 0.75, 1, 2.5, 5, 7.5, 10,
25, 50, 75, 100, 200],
'0.1-10' : [0.1, 0.25, 0.5, 0.75, 1, 2.5, 5, 7.5, 10],
'0.0001-1' : [0, 0.0001, 0.00025, 0.0005, 0.00075, 0.001, 0.0025, 0.005, 0.0075,
0.01, 0.025, 0.05, 0.075, 0.1, 0.25, 0.5, 0.75, 1],
'0.0001-0.25' : [0, 0.0001, 0.00025, 0.0005, 0.00075, 0.001, 0.0025, 0.005, 0.0075,
0.01, 0.025, 0.05, 0.075, 0.1, 0.25],
'1-100' : [1, 2.5, 5, 7.5, 10, 25, 50, 75, 100],
'0.001-100' : [0, 0.001, 0.0025, 0.005, 0.0075, 0.01, 0.025, 0.05, 0.075,
0.1, 0.25, 0.5, 0.75, 1, 2.5, 5, 7.5, 10, 25, 50, 75, 100, 200],
'0.001-7.5' : [0, 0.001, 0.0025, 0.005, 0.0075, 0.01, 0.025, 0.05, 0.075,
0.1, 0.25, 0.5, 0.75, 1, 2.5, 5, 7.5, 10],
'0.01-5' : [0, 0.1, 0.25, 0.5, 0.75, 1, 2.5, 5],
}
# plot the cumulative histogram
fig, ax = plt.subplots(figsize=(8, 8))
bins = PLOTS[plot_name][1]
if isinstance(bins, str): bins = BINS_RANGES[PLOTS[plot_name][1]]
bins = np.array(bins).astype(float)
for label, counts in PLOTS[plot_name][2]:
counts = np.array(counts).astype(float)
assert len(bins) == len(counts) + 1
centroids = (bins[1:] + bins[:-1]) / 2
ax.hist(centroids, bins=bins, weights=counts, range=(min(bins), max(bins)), density=True,
histtype='step', cumulative=True, label=label)
ax.grid(True)
ax.legend(loc='upper left')
ax.set_title(PLOTS[plot_name][0])
ax.set_xlabel('seconds')
ax.set_ylabel('Likelihood of occurrence')
plt.xscale('log')
plt.savefig('{:s}.png'.format(plot_name.value), dpi = (600))
plt.show()