def main():
files = my.get_grouped_files(source_path=source_path,
delay=delay,
index_delay=index_delay)
i = 1
my_list_ble = dict()
my_list_wifi = dict()
my_list_total = dict()
my_list_times = dict() # cambio delay_wifi_send
my_list_times_1 = dict() # cambio delay_wifi_send
for item in files:
print("\x1b[1;30;43m " + str(i) + " \x1b[1;34;40m " + item[28:] +
" \x1b[0m ")
data = my.open_file_and_return_data(path=item)
if i == 1:
my_dictionary['_command'] = data['_command']
l_ble, l_wifi, latency = statistics(data=data, run=i)
t, t1 = get_times_change_delay(data['_time'],
data['_command']['delay'],
data['_info'])
my_list_ble[i] = l_ble
my_list_wifi[i] = l_wifi
my_list_total[i] = latency
my_list_times[i] = t
my_list_times_1[i] = t1
i += 1
# Summary
summary_statistics()
save_statistics_data()
# PLOT
plot_1(my_list_ble, my_list_wifi, my_list_total, my_list_times,
my_list_times_1)
def main():
my_list_ble = dict()
my_list_wifi = dict()
for index_delay in range(len(delay)):
source_path = my.path_media + "json_file/relay_" + str(relay[index_relay]) + "/delay_" + str(
delay[index_delay]) + "/*_analysis.json"
cuts_path = my.path_media + "json_file/relay_" + str(relay[index_relay]) + "/outcomes/cuts/delay_x_" + str(
delay[index_delay]) + ".json"
files = my.get_grouped_files(source_path=source_path, delay=delay, index_delay=index_delay)
cuts = my.open_file_and_return_data(path=cuts_path)
i = 1
my_list_ble[delay[index_delay]] = dict()
my_list_wifi[delay[index_delay]] = dict()
for item in files:
data = my.open_file_and_return_data(path=item)['_mex']
l_ble, l_wifi = get_all_value_cuts(dataset=data, run=i, cut=cuts)
my_list_ble[delay[index_delay]][i] = l_ble
my_list_wifi[delay[index_delay]][i] = l_wifi
i += 1
df = get_list_and_return_df(my_list_ble, 'ble', 'latency')
define_base_plot()
# plot(df, "BLE", 'latency')
smooth_interpolation(df, 'ble', 'latency')
def main():
files = my.get_grouped_files(source_path=source_path,
delay=delay,
index_delay=index_delay)
path = delay_path + "delay_" + str(delay[index_delay]) + ".json"
data_delay = my.open_file_and_return_data(path=path)
i = 1
err = list()
dictionaries = dict()
data = dict()
for item in files:
data = my.open_file_and_return_data(path=item)
print("\x1b[1;30;43m " + item[28:] + " \x1b[0m ")
start = dt.datetime.strptime(data_delay[str(i)]['_info']['start'],
'%Y-%m-%d %H:%M:%S.%f')
end = dt.datetime.strptime(data_delay[str(i)]['_info']['end_sent'],
'%Y-%m-%d %H:%M:%S.%f')
# TODO shift focus about data --- duration 4 minute
new_start = start + dt.timedelta(0, 30) # right shift --> default 40 s
new_end = new_start + dt.timedelta(0, 240) # 4m <- (60s*4)
# end = end - dt.timedelta(0, 15)
new_diff = new_end - new_start
h, m, s = my.convert_timedelta(new_diff)
fault, outcome = analysis(data, new_start, new_end, i)
print("start: {} -- end: {} --- {}:{}.{} -- min: {} -- max: {}".format(
new_start, new_end, h, m, s, outcome['smaller'],
outcome['bigger']))
time = str(h) + ":" + str(m) + "." + str(s) + " [h:m.s]"
outcome['time'] = {
'old_start': start,
'old_end': end,
'new_start': new_start,
'new_end': new_end,
'new_time': time
}
err.append(fault)
dictionaries[i] = outcome
i += 1
mex_removed = (60 * 1000) / delay[index_delay]
total = data['_command']['n_mex'] - mex_removed
print("\x1b[1;34;40m [{}] Mex_removed: {} --> total: {} \x1b[0m ".format(
delay[index_delay], mex_removed, total))
print("err: --> ", err)
dictionaries['error'] = err
dictionaries['info'] = {'mex_removed': mex_removed, 'n_mex': total}
save_data(dictionaries)
def main():
files = my.get_grouped_files(source_path=source_path, delay=delay, index_delay=index_delay)
cuts = my.open_file_and_return_data(path=cuts_path)
i = 1
my_list_ble = dict()
for item in files:
print("\x1b[1;30;43m " + str(i) + " \x1b[1;34;40m " + item[28:] + " \x1b[0m ")
data = my.open_file_and_return_data(path=item)
if i == 1:
my_dictionary['_command'] = data['_command']
l_ble = statistics(data=data, run=i, x=cuts)
my_list_ble[i] = l_ble
i += 1
# Summary
summary_statistics()
# PLOT
plot_1(my_list_ble)
def main_cut():
my_list_ble = dict()
if directory == 'ble_wifi_output':
my_list_wifi = dict()
my_list_total = dict()
for index_delay in range(len(delay)):
source_path = my.path_media + "json_file/" + directory + "/relay_" + str(
relay[index_relay]) + "/" + str(
delay[index_delay]) + "/*_analysis.json"
cuts_path = my.path_media + "json_file/" + directory + "/relay_" + str(
relay[index_relay]) + "/x/delay_x_" + str(
delay[index_delay]) + ".json"
files = my.get_grouped_files(source_path=source_path,
delay=delay,
index_delay=index_delay)
cuts = my.open_file_and_return_data(path=cuts_path)
i = 1
my_list_ble[delay[index_delay]] = dict()
if directory == 'ble_wifi_output':
my_list_wifi[delay[index_delay]] = dict()
my_list_total[delay[index_delay]] = dict()
for item in files:
data = my.open_file_and_return_data(path=item)['_mex']
if directory == 'ble_wifi_output':
l_ble, l_wifi, l_total = get_all_value_cuts(dataset=data,
run=i,
cut=cuts)
my_list_ble[delay[index_delay]][i] = l_ble
my_list_wifi[delay[index_delay]][i] = l_wifi
my_list_total[delay[index_delay]][i] = l_total
else:
l_ble = get_all_value_cuts_ble(dataset=data, run=i, cut=cuts)
my_list_ble[delay[index_delay]][i] = l_ble
i += 1
plot(my_list_ble, "BLE")
plot(my_list_wifi, "WiFi")
plot(my_list_total, "BLE - WiFi")
def main_2():
my_list = {'delay': list(), 'latency': list(), 'type': list()}
for index_delay in range(len(delay)):
source_path = my.path_media + "json_file/ble_wifi_output/relay_" + str(
relay[index_relay]) + "/" + str(
delay[index_delay]) + "/*_analysis.json"
cuts_path = my.path_media + "json_file/ble_wifi_output/relay_" + str(
relay[index_relay]) + "/x/delay_x_" + str(
delay[index_delay]) + ".json"
files = my.get_grouped_files(source_path=source_path,
delay=delay,
index_delay=index_delay)
cuts = my.open_file_and_return_data(path=cuts_path)
i = 1
for item in files:
data = my.open_file_and_return_data(path=item)
pxs, pys, pzs = get_all_value_2(dataset=data, run=i, cut=cuts)
my_list['delay'].append(pxs)
my_list['latency'].append(pys)
my_list['type'].append(pzs)
i += 1
pxs = list()
pys = list()
pzs = list()
runs = len(my_list['delay'])
for r in range(runs):
item = len(my_list['delay'][r])
for i in range(item):
pxs.append(my_list['delay'][r][i])
pys.append(my_list['latency'][r][i])
pzs.append(my_list['type'][r][i])
dataframe = {'delay': pxs, 'y_data': pys, 'type': pzs}
df = pd.DataFrame(dataframe)
print(df.head())
plot_2(df)
def main_3():
x = list()
y = list()
z = list()
dictionary = dict()
if directory == 'ble_output':
tech = " - [BLE]"
else:
tech = " - [BLE - WiFi]"
if type_graph == 'latency':
y_label = 'Latency (s)'
title = 'Latency' + tech
name = directory[:-6] + 'latency.png'
elif type_graph == 'pdr':
y_label = 'Packet Delivery Ratio'
title = y_label + tech
name = directory[:-6] + 'pdr.png'
else:
y_label = 'Goodput (byte/s)'
title = 'Goodput' + tech
name = directory[:-6] + 'goodput.png'
for r in range(len(relay)):
dictionary[r] = {'x': list(), 'y': list()}
for d in range(len(delay)):
path = my.path_media + "json_file/" + directory + "/relay_" + str(
relay[r]) + "/x/delay_XXX_" + str(delay[d]) + ".json"
files = my.get_grouped_files(source_path=path,
delay=delay,
index_delay=d)
i = 1
for item in files:
data = my.open_file_and_return_data(path=item)
t = 'config_' + str(int(r + 1))
z.append(t)
time_ = convert_time_in_num(data['_command']['delay'])
x.append(time_)
dictionary[r]['x'].append(time_)
if directory == 'ble_wifi_output':
if type_graph == 'latency':
value = data['summary']['statistic_']['total'][
type_graph]['mean']
else:
value = data['summary']['statistic_']['total'][
type_graph]
else:
if type_graph == 'latency':
value = data['summary']['statistic_'][type_graph][
'mean']
else:
value = data['summary']['statistic_'][type_graph]
y.append(value)
dictionary[r]['y'].append(value)
i += 1
dataframe = {'delay': x, 'y_data': y, 'type': z}
df = pd.DataFrame(dataframe)
print(df.head())
print("path: " + my.path_media + "json_file/" + directory + "/last_plot/")
print("name: " + name)
plot_3(df, dictionary, y_label, title)
plot_x(df, dictionary, y_label, title)
def main_4():
x = list()
y = list()
z = list()
dir = ['ble_wifi_output', 'ble_output']
dictionary = dict()
if type_graph == 'latency':
y_label = 'Latency (s)'
title = 'Latency'
name = 'mixed_latency.png'
elif type_graph == 'pdr':
y_label = 'Packet Delivery Ratio'
title = y_label
name = 'mixed_pdr.png'
else:
y_label = 'Goodput (byte/s)'
title = 'Goodput'
name = 'mixed_goodput.png'
for d1 in dir:
if d1 == 'ble_wifi_output':
hue = 'ble_wifi'
else:
hue = 'ble'
dictionary[hue] = dict()
for r in range(len(relay)):
dictionary[hue][r] = {'x': list(), 'y': list()}
for d in range(len(delay)):
path = my.path_media + "json_file/" + d1 + "/relay_" + str(
relay[r]) + "/x/delay_XXX_" + str(delay[d]) + ".json"
files = my.get_grouped_files(source_path=path,
delay=delay,
index_delay=d)
i = 1
for item in files:
data = my.open_file_and_return_data(path=item)
t = hue + ' config_' + str(r)
if hue == 'ble_wifi':
if type_graph == 'latency':
value = data['summary']['statistic_']['total'][
type_graph]['mean']
else:
value = data['summary']['statistic_']['total'][
type_graph]
else:
if type_graph == 'latency':
value = data['summary']['statistic_'][type_graph][
'mean']
else:
value = data['summary']['statistic_'][type_graph]
time_ = convert_time_in_num(data['_command']['delay'])
x.append(time_)
y.append(value)
z.append(t)
dictionary[hue][r]['x'].append(time_)
dictionary[hue][r]['y'].append(value)
i += 1
dataframe = {'delay': x, 'latency': y, 'type': z}
df = pd.DataFrame(dataframe)
# print(df)
print("path: " + my.path_media + "json_file/" + directory + "/last_plot/")
print("name: " + name)
# colors = ['#4878D0', '#EE854A', '#6ACC64', '#D65F5F', '#82C6E2', '#D5BB67']
# sns.set_palette(sns.color_palette(colors))
xs_b_0 = np.linspace(min(dictionary['ble'][0]['x']),
max(dictionary['ble'][0]['x']), 100)
xs_b_1 = np.linspace(min(dictionary['ble'][1]['x']),
max(dictionary['ble'][1]['x']), 100)
xs_b_2 = np.linspace(min(dictionary['ble'][2]['x']),
max(dictionary['ble'][2]['x']), 100)
xs_bw_0 = np.linspace(min(dictionary['ble_wifi'][0]['x']),
max(dictionary['ble_wifi'][0]['x']), 100)
xs_bw_1 = np.linspace(min(dictionary['ble_wifi'][1]['x']),
max(dictionary['ble_wifi'][1]['x']), 100)
xs_bw_2 = np.linspace(min(dictionary['ble_wifi'][2]['x']),
max(dictionary['ble_wifi'][2]['x']), 100)
f_b_0 = sc.interpolate.interp1d(dictionary['ble'][0]['x'],
dictionary['ble'][0]['y'],
kind='linear')
f_b_1 = sc.interpolate.interp1d(dictionary['ble'][1]['x'],
dictionary['ble'][1]['y'],
kind='linear')
f_b_2 = sc.interpolate.interp1d(dictionary['ble'][2]['x'],
dictionary['ble'][2]['y'],
kind='linear')
f_bw_0 = sc.interpolate.interp1d(dictionary['ble_wifi'][0]['x'],
dictionary['ble_wifi'][0]['y'],
kind='linear')
f_bw_1 = sc.interpolate.interp1d(dictionary['ble_wifi'][1]['x'],
dictionary['ble_wifi'][1]['y'],
kind='linear')
f_bw_2 = sc.interpolate.interp1d(dictionary['ble_wifi'][2]['x'],
dictionary['ble_wifi'][2]['y'],
kind='linear')
sns.set_context('notebook')
sns.lmplot(
x='delay',
y='latency',
data=df,
palette='muted',
fit_reg=False,
ci=None,
legend_out=False,
# hue='type',
height=4,
aspect=2,
markers=".",
scatter_kws={"s": 30})
# plot line
plt.plot(xs_b_0, f_b_0(xs_b_0), '-.', color='#D65F5F') # red
plt.plot(xs_b_1, f_b_1(xs_b_1), '-.', color='#956CB4') # purple
plt.plot(xs_b_2, f_b_2(xs_b_2), '-.', color='#8C613C') # brown
plt.plot(xs_bw_0, f_bw_0(xs_bw_0), '--', color='#4878D0') # blue
plt.plot(xs_bw_1, f_bw_1(xs_bw_1), '--', color='#EE854A') # orange
plt.plot(xs_bw_2, f_bw_2(xs_bw_2), '--', color='#6ACC64') # green
# plot point
plt.plot(dictionary['ble'][0]['x'],
dictionary['ble'][0]['y'],
'o',
markersize=6,
color='#D65F5F',
label="ble config_0") # red
plt.plot(dictionary['ble'][1]['x'],
dictionary['ble'][1]['y'],
'o',
markersize=6,
color='#956CB4',
label="ble config_1") # purple
plt.plot(dictionary['ble'][2]['x'],
dictionary['ble'][2]['y'],
'o',
markersize=6,
color='#8C613C',
label="ble confgi_2") # brown
plt.plot(dictionary['ble_wifi'][0]['x'],
dictionary['ble_wifi'][0]['y'],
'D',
markersize=6,
color='#4878D0',
label="ble_wifi config_0") # blue
plt.plot(dictionary['ble_wifi'][1]['x'],
dictionary['ble_wifi'][1]['y'],
'D',
markersize=6,
color='#EE854A',
label="ble_wifi config_1") # orange
plt.plot(dictionary['ble_wifi'][2]['x'],
dictionary['ble_wifi'][2]['y'],
'D',
markersize=6,
color='#6ACC64',
label="ble_wifi config_2") # green
plt.legend(loc='best')
my_point = list()
my_label = list()
delay.reverse()
for i in range(len(delay)):
my_point.append(i + 1)
frequency = 1 / (delay[i] / 1000)
my_label.append(round(frequency, 2))
plt.xticks(my_point, my_label, rotation=30)
plt.xlabel("Frequency (Hz)", fontsize=16)
plt.ylabel(y_label, fontsize=16)
# plt.title(title)
sns.despine(
) # is a function that removes the spines from the right and upper portion of the plot by default.
plt.show()
def main_5():
x = dict()
y = list()
z = list()
l_1 = list()
l_2 = list()
if directory == 'ble_output':
raise Exception('wrong - directory- ')
r = 0
for d in range(len(delay)):
path = my.path_media + "json_file/" + directory + "/relay_" + str(
relay[r]) + "/x/delay_XXX_" + str(delay[d]) + ".json"
files = my.get_grouped_files(source_path=path,
delay=delay,
index_delay=d)
for item in files:
data = my.open_file_and_return_data(path=item)
time_ = (data['_command']['delay'])
ble = data['summary']['mex_']['ble']['R']
wifi = data['summary']['mex_']['wifi']['R']
total = data['summary']['mex_']['total']['R']
p_ble = ble * 100 / total
p_wifi = wifi * 100 / total
x[time_] = list()
x[time_].append(p_ble)
z.append('ble')
x[time_].append(p_wifi)
z.append('wifi')
l_1.append(time_)
y.append(p_ble)
l_2.append(100)
dataframe = {'total': l_2, 'ble': y, 'delay': l_1}
df = pd.DataFrame(dataframe)
print(df)
fig_dims = (10, 4)
fig, ax = plt.subplots(figsize=fig_dims)
sns.set_context('notebook')
sns.set_color_codes("muted")
sns.barplot(x='delay', y='total', data=df, label="total", color='b', ax=ax)
sns.set_color_codes("muted")
sns.barplot(x='delay', y='ble', data=df, label="ble", color='y', ax=ax)
sns.despine()
plt.show()
print("--")
dataframe = {
'type': ['ble', 'wifi'],
'50': x[50],
'100': x[100],
'150': x[150],
'200': x[200],
'250': x[250],
'500': x[500],
'1000': x[1000]
}
df = pd.DataFrame(dataframe)
print(df.head())
sns.set_context('notebook')
df.set_index('type').T.plot(kind='bar', stacked=True)
plt.legend(loc='best')
my_point = list()
my_label = list()
delay.reverse()
for i in range(len(delay)):
my_point.append(i + 1)
frequency = 1 / (delay[i] / 1000)
my_label.append(round(frequency, 2))
plt.xticks(my_point, my_label, rotation=30)
plt.xlabel("Frequency (Hz)", fontsize=16)
plt.ylabel("Percentage", fontsize=16)
# plt.title(title)
sns.despine(
) # is a function that removes the spines from the right and upper portion of the plot by default.
plt.show()