#! /usr/bin/python3
from subprocess import call
-import sys
+from collections import defaultdict
+import csv
import numpy as np
import pandas as pd
+import sys
def test_case(df):
- df['nsecperiter']=(df['duration']*1000)/(df['nbiter'])
- stdev = pd.DataFrame({'perevent_stdev' :
- df.groupby(['nbthreads', 'tracer', 'testcase','sleeptime'])['nsecperiter'].std()}).reset_index()
- mean = pd.DataFrame({'perevent_mean' :
- df.groupby(['nbthreads', 'tracer', 'testcase','sleeptime'])['nsecperiter'].mean()}).reset_index()
- mem_mean = pd.DataFrame({'mem_mean' :
- df.groupby(['nbthreads','tracer','testcase','sleeptime'])['maxmem'].mean()}).reset_index()
- mem_stdev = pd.DataFrame({'mem_stdev' :
- df.groupby(['nbthreads','tracer','testcase','sleeptime'])['maxmem'].std()}).reset_index()
- tmp = mean.merge(stdev)
- tmp = tmp.merge(mem_mean)
- tmp = tmp.merge(mem_stdev)
+ # Duration is in usec
+ # usecPecIter = Duration/(average number of iteration per thread)
+ df['usecperiter'] = (df['nbthreads'] * df['duration']) / df['nbiter']
+
+ periter_mean = pd.DataFrame({'periter_mean' :
+ df.groupby(['nbthreads', 'tracer', 'testcase','sleeptime'])['usecperiter'].mean()}).reset_index()
+
+ periter_stdev = pd.DataFrame({'periter_stdev' :
+ df.groupby(['nbthreads', 'tracer', 'testcase','sleeptime'])['usecperiter'].std()}).reset_index()
+
+ nbiter_mean = pd.DataFrame({'nbiter_mean' :
+ df.groupby(['nbthreads', 'tracer', 'testcase','sleeptime'])['nbiter'].mean()}).reset_index()
+
+ nbiter_stdev = pd.DataFrame({'nbiter_stdev' :
+ df.groupby(['nbthreads', 'tracer', 'testcase','sleeptime'])['nbiter'].std()}).reset_index()
+
+ duration_mean = pd.DataFrame({'duration_mean' :
+ df.groupby(['nbthreads', 'tracer', 'testcase','sleeptime'])['duration'].mean()}).reset_index()
+ duration_stdev = pd.DataFrame({'duration_stdev' :
+ df.groupby(['nbthreads', 'tracer', 'testcase','sleeptime'])['duration'].std()}).reset_index()
+
+ tmp = periter_mean.merge(periter_stdev)
+
+ tmp = tmp.merge(nbiter_mean)
+ tmp = tmp.merge(nbiter_stdev)
+
+ tmp = tmp.merge(duration_mean)
+ tmp = tmp.merge(duration_stdev)
+
+ # if there is any NaN or None value in the DF we raise an exeception
+ if tmp.isnull().values.any():
+ raise Exception('NaN value found in dataframe')
for i, row in tmp.iterrows():
- testcase_name='_'.join([row['tracer'],str(row['nbthreads'])+'thr', 'pereventmean'])
- yield( {"name": testcase_name, "result": "pass", "units": "nsec/event",
- "measurement": str(row['perevent_mean'])})
+ testcase_name='_'.join([row['tracer'],str(row['nbthreads'])+'thr', 'peritermean'])
+ yield( {"name": testcase_name, "result": "pass", "units": "usec/iter",
+ "measurement": str(row['periter_mean'])})
- testcase_name='_'.join([row['tracer'],str(row['nbthreads'])+'thr', 'pereventstdev'])
- yield( {"name": testcase_name, "result": "pass", "units": "nsec/event",
- "measurement": str(row['perevent_stdev'])})
+ testcase_name='_'.join([row['tracer'],str(row['nbthreads'])+'thr', 'periterstdev'])
+ yield( {"name": testcase_name, "result": "pass", "units": "usec/iter",
+ "measurement": str(row['periter_stdev'])})
- testcase_name='_'.join([row['tracer'],str(row['nbthreads'])+'thr', 'memmean'])
- yield( {"name": testcase_name, "result": "pass", "units": "kB",
- "measurement": str(row['mem_mean'])})
+ testcase_name='_'.join([row['tracer'],str(row['nbthreads'])+'thr', 'nbitermean'])
+ yield( {"name": testcase_name, "result": "pass", "units": "iterations",
+ "measurement": str(row['nbiter_mean'])})
- testcase_name='_'.join([row['tracer'],str(row['nbthreads'])+'thr', 'memstdev'])
- yield( {"name": testcase_name, "result": "pass", "units": "kB",
- "measurement": str(row['mem_stdev'])})
+ testcase_name='_'.join([row['tracer'],str(row['nbthreads'])+'thr', 'nbiterstdev'])
+ yield( {"name": testcase_name, "result": "pass", "units": "iterations",
+ "measurement": str(row['nbiter_stdev'])})
+ testcase_name='_'.join([row['tracer'],str(row['nbthreads'])+'thr', 'durationmean'])
+ yield( {"name": testcase_name, "result": "pass", "units": "usec",
+ "measurement": str(row['duration_mean'])})
+
+ testcase_name='_'.join([row['tracer'],str(row['nbthreads'])+'thr', 'durationstdev'])
+ yield( {"name": testcase_name, "result": "pass", "units": "usec",
+ "measurement": str(row['duration_stdev'])})
def main():
results_file=sys.argv[1]
df = pd.read_csv(results_file)
+ results=defaultdict()
data = test_case(df)
for res in data:
call(
'--measurement', res['measurement'],
'--units', res['units']])
+ # Save the results to write to the CSV file
+ results[res['name']]=res['measurement']
+
+ # Write the dictionnary to a csv file where each key is a column
+ with open('processed_results.csv', 'w') as output_csv:
+ dict_csv_write=csv.DictWriter(output_csv, results.keys())
+ dict_csv_write.writeheader()
+ dict_csv_write.writerow(results)
+
if __name__ == '__main__':
main()