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# Copyright 2022-2024 ETSI OSG/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.
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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()