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"""
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
import os
class StatMonitor():
def __init__(self,cfg_file):
with open(cfg_file,'r') as file:
self.d = yaml.load(file)
for node in self.d:#so far we have enb or gnb as nodes
for metric_l1 in self.d[node]: #first level of metric keys
if metric_l1!="graph": #graph is a reserved word to configure graph paging, so it is disregarded
if self.d[node][metric_l1] is None:#first level is None -> create array
self.d[node][metric_l1]=[]
else: #first level is not None -> there is a second level -> create array
for metric_l2 in self.d[node][metric_l1]:
self.d[node][metric_l1][metric_l2]=[]
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)
for k in self.d[node_type]['rt']:
result=re.match(rf'^.*\b{k}\b:\s+([0-9\.]+) us;\s+([0-9]+);\s+([0-9\.]+) us;',tmp)
if result is not None:
self.d[node_type]['rt'][k].append(float(result.group(3)))
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,testcase_id,node_type):
if node_type=='enb':
files = ["L1_stats.log", "MAC_stats.log", "PDCP_stats.log", "RRC_stats.log"]
else: #'gnb'
files = ["nrL1_stats.log", "nrMAC_stats.log", "nrPDCP_stats.log", "nrRRC_stats.log"]
#append each file's contents to another file (prepended with CI-) for debug
for f in files:
if os.path.isfile(f):
cmd = 'cat '+ f + ' >> CI-'+testcase_id+'-'+f
subprocess.Popen(cmd,shell=True)
#join the files for further processing
cmd='cat '
for f in files:
if os.path.isfile(f):
cmd += f+' '
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,testcase_id, node_type):
for page in self.d[node_type]['graph']:#work out a set a graphs per page
col = 1
figure, axis = plt.subplots(len(self.d[node_type]['graph'][page]), col ,figsize=(10, 10))
i=0
for m in self.d[node_type]['graph'][page]:#metric may refer to 1 level or 2 levels
metric_path=m.split('.')
if len(metric_path)==1:#1 level
metric_l1=metric_path[0]
major_ticks = np.arange(0, len(self.d[node_type][metric_l1])+1, 1)
axis[i].set_xticks(major_ticks)
axis[i].set_xticklabels([])
axis[i].plot(self.d[node_type][metric_l1],marker='o')
axis[i].set_xlabel('time')
axis[i].set_ylabel(metric_l1)
axis[i].set_title(metric_l1)
else:#2 levels
metric_l1=metric_path[0]
metric_l2=metric_path[1]
major_ticks = np.arange(0, len(self.d[node_type][metric_l1][metric_l2])+1, 1)
axis[i].set_xticks(major_ticks)
axis[i].set_xticklabels([])
axis[i].plot(self.d[node_type][metric_l1][metric_l2],marker='o')
axis[i].set_xlabel('time')
axis[i].set_ylabel(metric_l2)
axis[i].set_title(metric_l2)
i+=1
plt.tight_layout()
#save as png
plt.savefig(node_type+'_stats_monitor_'+testcase_id+'_'+page+'.png')
if __name__ == "__main__":
cfg_filename = sys.argv[1] #yaml file as metrics config
testcase_id = sys.argv[2] #test case id to name files accordingly, especially if we have several tests in a sequence
node = sys.argv[3]#enb or gnb
mon=StatMonitor(cfg_filename)
#collecting stats when modem process is stopped
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 :
mon.collect(testcase_id,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(testcase_id, node)