CI: delete old stats_monitor files

This commit is contained in:
Robert Schmidt
2022-01-14 18:34:40 +01:00
parent 76411447ab
commit 4e0548328d
2 changed files with 0 additions and 195 deletions
-94
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@@ -1,94 +0,0 @@
import subprocess
import time
import shlex
import re
import sys
import matplotlib.pyplot as plt
import pickle
import numpy as np
import os
def collect(d, node_type):
if node_type=='enb':
cmd='cat L1_stats.log MAC_stats.log PDCP_stats.log RRC_stats.log'
else: #'gnb'
cmd='cat nrL1_stats.log nrMAC_stats.log nrPDCP_stats.log nrRRC_stats.log'
process=subprocess.Popen(shlex.split(cmd), stdout=subprocess.PIPE)
output = process.stdout.readlines()
for l in output:
tmp=l.decode("utf-8")
result=re.match(rf'^.*\bPHR\b ([0-9]+).+\bbler\b ([0-9]+\.[0-9]+).+\bmcsoff\b ([0-9]+).+\bmcs\b ([0-9]+)',tmp)
if result is not None:
d['PHR'].append(int(result.group(1)))
d['bler'].append(float(result.group(2)))
d['mcsoff'].append(int(result.group(3)))
d['mcs'].append(int(result.group(4)))
def graph(d, node_type):
figure, axis = plt.subplots(4, 1,figsize=(10, 10))
major_ticks = np.arange(0, len(d['PHR'])+1, 1)
axis[0].set_xticks(major_ticks)
axis[0].set_xticklabels([])
axis[0].plot(d['PHR'],marker='o')
axis[0].set_xlabel('time')
axis[0].set_ylabel('PHR')
axis[0].set_title("PHR")
major_ticks = np.arange(0, len(d['bler'])+1, 1)
axis[1].set_xticks(major_ticks)
axis[1].set_xticklabels([])
axis[1].plot(d['bler'],marker='o')
axis[1].set_xlabel('time')
axis[1].set_ylabel('bler')
axis[1].set_title("bler")
major_ticks = np.arange(0, len(d['mcsoff'])+1, 1)
axis[2].set_xticks(major_ticks)
axis[2].set_xticklabels([])
axis[2].plot(d['mcsoff'],marker='o')
axis[2].set_xlabel('time')
axis[2].set_ylabel('mcsoff')
axis[2].set_title("mcsoff")
major_ticks = np.arange(0, len(d['mcs'])+1, 1)
axis[3].set_xticks(major_ticks)
axis[3].set_xticklabels([])
axis[3].plot(d['mcs'],marker='o')
axis[3].set_xlabel('time')
axis[3].set_ylabel('mcs')
axis[3].set_title("mcs")
plt.tight_layout()
# Combine all the operations and display
plt.savefig(node_type+'_stats_monitor.png')
plt.show()
if __name__ == "__main__":
node_type = sys.argv[1]#enb or gnb
d={}
d['PHR']=[]
d['bler']=[]
d['mcsoff']=[]
d['mcs']=[]
cmd='ps aux | grep modem | grep -v grep'
process=subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE)
output = process.stdout.readlines()
while len(output)!=0 :
collect(d, node_type)
process=subprocess.Popen(cmd, shell=True, stdout=subprocess.PIPE)
output = process.stdout.readlines()
time.sleep(1)
print('process stopped')
with open(node_type+'_stats_monitor.pickle', 'wb') as handle:
pickle.dump(d, handle, protocol=pickle.HIGHEST_PROTOCOL)
graph(d, node_type)
-101
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@@ -1,101 +0,0 @@
"""
To create graphs and pickle from runtime statistics in L1,MAC,RRC,PDCP files
"""
import subprocess
import time
import shlex
import re
import sys
import pickle
import matplotlib.pyplot as plt
import numpy as np
import yaml
class StatMonitor():
def __init__(self,):
with open('stats_monitor_conf.yaml','r') as file:
self.d = yaml.load(file)
for node in self.d:
for metric in self.d[node]:
self.d[node][metric]=[]
def process_gnb (self,node_type,output):
for line in output:
tmp=line.decode("utf-8")
result=re.match(r'^.*\bdlsch_rounds\b ([0-9]+)\/([0-9]+).*\bdlsch_errors\b ([0-9]+)',tmp)
if result is not None:
self.d[node_type]['dlsch_err'].append(int(result.group(3)))
percentage=float(result.group(2))/float(result.group(1))
self.d[node_type]['dlsch_err_perc_round_1'].append(percentage)
result=re.match(r'^.*\bulsch_rounds\b ([0-9]+)\/([0-9]+).*\bulsch_errors\b ([0-9]+)',tmp)
if result is not None:
self.d[node_type]['ulsch_err'].append(int(result.group(3)))
percentage=float(result.group(2))/float(result.group(1))
self.d[node_type]['ulsch_err_perc_round_1'].append(percentage)
def process_enb (self,node_type,output):
for line in output:
tmp=line.decode("utf-8")
result=re.match(r'^.*\bPHR\b ([0-9]+).+\bbler\b ([0-9]+\.[0-9]+).+\bmcsoff\b ([0-9]+).+\bmcs\b ([0-9]+)',tmp)
if result is not None:
self.d[node_type]['PHR'].append(int(result.group(1)))
self.d[node_type]['bler'].append(float(result.group(2)))
self.d[node_type]['mcsoff'].append(int(result.group(3)))
self.d[node_type]['mcs'].append(int(result.group(4)))
def collect(self,node_type):
if node_type=='enb':
cmd='cat L1_stats.log MAC_stats.log PDCP_stats.log RRC_stats.log'
else: #'gnb'
cmd='cat nrL1_stats.log nrMAC_stats.log nrPDCP_stats.log nrRRC_stats.log'
process=subprocess.Popen(shlex.split(cmd), stdout=subprocess.PIPE)
output = process.stdout.readlines()
if node_type=='enb':
self.process_enb(node_type,output)
else: #'gnb'
self.process_gnb(node_type,output)
def graph(self,node_type):
col = 1
figure, axis = plt.subplots(len(self.d[node_type]), col ,figsize=(10, 10))
i=0
for metric in self.d[node_type]:
major_ticks = np.arange(0, len(self.d[node_type][metric])+1, 1)
axis[i].set_xticks(major_ticks)
axis[i].set_xticklabels([])
axis[i].plot(self.d[node_type][metric],marker='o')
axis[i].set_xlabel('time')
axis[i].set_ylabel(metric)
axis[i].set_title(metric)
i+=1
plt.tight_layout()
# Combine all the operations and display
plt.savefig(node_type+'_stats_monitor.png')
plt.show()
if __name__ == "__main__":
node = sys.argv[1]#enb or gnb
mon=StatMonitor()
#collecting stats when modem process is stopped
CMD='ps aux | grep mode | grep -v grep'
process=subprocess.Popen(CMD, shell=True, stdout=subprocess.PIPE)
output = process.stdout.readlines()
while len(output)!=0 :
mon.collect(node)
process=subprocess.Popen(CMD, shell=True, stdout=subprocess.PIPE)
output = process.stdout.readlines()
time.sleep(1)
print('Process stopped')
with open(node+'_stats_monitor.pickle', 'wb') as handle:
pickle.dump(mon.d, handle, protocol=pickle.HIGHEST_PROTOCOL)
mon.graph(node)