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#!/usr/bin/python
import re
def getResultColumn(data_dict):
column_string = data_dict['Columns']
return column_string.strip('{}').split()
def getResult(data_dict):
result_string = data_dict['Output']
result_array = result_string.split('} {')
result = []
for line in result_array:
result.append(line.split())
return result
def restrucData(data_string):
try:
data_dict = {}
p = re.compile('-Columns.*-Output')
data_dict['Columns'] = p.findall(data_string)[0].strip('-Columns {} -Output')
p = re.compile('-Output.*-State')
data_dict['Output'] = p.findall(data_string)[0].strip('-Output {} -State')
if data_dict['Columns'] is not None or data_dict['Output'] is not None:
return False, None
return True, data_dict
except:
print("[ERROR]Find the column name or the output result failed.")
def framelossData(column, perfdata):
column_name_dict = {
'TrialNumber': 0,
'Id': 1,
'FrameSize': 3,
'TxFrameCount': 9,
'RxFrameCount': 10,
'PercentLoss(%s)': 12,
'MinimumLatency(us)': 17,
'MaximumLatency(us)': 18,
'AverageLatency(us)': 19,
'MinimumJitter(us)': 20,
'MaximumJitter(us)': 21,
'AverageJitter(us)': 22,
}
# get the column array
column_array = [
column[column_name_dict['FrameSize']],
'ForwardingRate(Mpps)',
column[column_name_dict['TxFrameCount']],
column[column_name_dict['RxFrameCount']],
column[column_name_dict['PercentLoss(%s)']],
column[column_name_dict['AverageLatency(us)']],
column[column_name_dict['MinimumLatency(us)']],
column[column_name_dict['MaximumLatency(us)']],
column[column_name_dict['AverageJitter(us)']],
column[column_name_dict['MinimumJitter(us)']],
column[column_name_dict['MaximumJitter(us)']]
]
data_array = []
for line in perfdata:
line_options = [
# line[column_name_dict['TrialNumber']],
# line[column_name_dict['Id']],
line[column_name_dict['FrameSize']],
str(float(line[column_name_dict['RxFrameCount']]) / 60 / 1000000),
line[column_name_dict['TxFrameCount']],
line[column_name_dict['RxFrameCount']],
line[column_name_dict['PercentLoss(%s)']],
line[column_name_dict['AverageLatency(us)']],
line[column_name_dict['MinimumLatency(us)']],
line[column_name_dict['MaximumLatency(us)']],
line[column_name_dict['AverageJitter(us)']],
line[column_name_dict['MinimumJitter(us)']],
line[column_name_dict['MaximumJitter(us)']]
]
data_array.append(line_options)
return [column_array, data_array]
class analysis(object):
def __init__(self):
pass
def analyseResult(self, suite, column, perfdata):
"""
:type self: object
"""
global data_array, column_array
if suite == 'throughput':
[column_array, data_array] = self.throughputData(column, perfdata)
elif suite == 'frameloss':
[column_array, data_array] = self.framelossData(column, perfdata)
elif suite == 'latency':
self.latencyData(column, perfdata)
else:
return None
for line in data_array:
print line
return [column_array, data_array]
def throughputData(self, column, perfdata):
column_name_dict = {
'TrialNumber': 0,
'Id': 1,
'FrameSize': 3,
'Load(%)': 6,
'Result': 8,
'TxFrameCount': 12,
'RxFrameCount': 13,
'ForwardingRate(mpps)': 17,
'MinimumLatency(us)': 18,
'MaximumLatency(us)': 19,
'AverageLatency(us)': 20,
'MinimumJitter(us)': 21,
'MaximumJitter(us)': 22,
'AverageJitter(us)': 23
}
column_array = {column[column_name_dict['FrameSize']],
column[column_name_dict['Load(%)']],
column[column_name_dict['Result']],
'ForwardingRate(mpps)',
column[column_name_dict['TxFrameCount']],
column[column_name_dict['RxFrameCount']],
column[column_name_dict['AverageLatency(us)']],
column[column_name_dict['MinimumLatency(us)']],
column[column_name_dict['MaximumLatency(us)']],
column[column_name_dict['AverageJitter(us)']],
column[column_name_dict['MinimumJitter(us)']],
column[column_name_dict['MaximumJitter(us)']]}
data_array = []
for line in perfdata:
if line[column_name_dict['Result']] == 'Passed':
line_options = [
# line[column_name_dict['TrialNumber']],
# line[column_name_dict['Id']],
line[column_name_dict['FrameSize']],
line[column_name_dict['Load(%)']],
line[column_name_dict['Result']],
str(float(line[column_name_dict['ForwardingRate(mpps)']]) / 1000000),
line[column_name_dict['TxFrameCount']],
line[column_name_dict['RxFrameCount']],
line[column_name_dict['AverageLatency(us)']],
line[column_name_dict['MinimumLatency(us)']],
line[column_name_dict['MaximumLatency(us)']],
line[column_name_dict['AverageJitter(us)']],
line[column_name_dict['MinimumJitter(us)']],
line[column_name_dict['MaximumJitter(us)']]]
else:
continue
data_array.append(line_options)
# delete the redundant test data
delete_index = []
new_data_array = []
for ele in range(len(data_array) - 1):
if data_array[ele][0] == data_array[ele + 1][0]:
delete_index.append(ele)
for num in len(data_array):
if num not in delete_index:
new_data_array.append(data_array[num])
return column_array, new_data_array
def latencyData(self, column, perfdata):
pass
analysis_instance = analysis()
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