blob: 4cb9ac1bc6c873232d598248edfbe9b8321053b9 [file] [log] [blame]
Christophe Favergeon3b2a0ee2019-06-12 13:29:14 +02001# Process the test results
2# Test status (like passed, or failed with error code)
3
4import argparse
5import re
6import TestScripts.NewParser as parse
7import TestScripts.CodeGen
8from collections import deque
9import os.path
10import numpy as np
11import pandas as pd
12import statsmodels.api as sm
13import statsmodels.formula.api as smf
14import csv
Christophe Favergeon37b86222019-07-17 11:49:00 +020015import TestScripts.Deprecate as d
Christophe Favergeon3b2a0ee2019-06-12 13:29:14 +020016
17def findItem(root,path):
18 """ Find a node in a tree
19
20 Args:
21 path (list) : A list of node ID
22 This list is describing a path in the tree.
23 By starting from the root and following this path,
24 we can find the node in the tree.
25 Raises:
26 Nothing
27 Returns:
28 TreeItem : A node
29 """
30 # The list is converted into a queue.
31 q = deque(path)
32 q.popleft()
33 c = root
34 while q:
35 n = q.popleft()
36 # We get the children based on its ID and continue
37 c = c[n-1]
38 return(c)
39
40
41
42NORMAL = 1
43INTEST = 2
44TESTPARAM = 3
45
46def joinit(iterable, delimiter):
47 it = iter(iterable)
48 yield next(it)
49 for x in it:
50 yield delimiter
51 yield x
52
53def formatProd(a,b):
54 if a == "Intercept":
55 return(str(b))
56 return("%s * %s" % (a,b))
57
Christophe Favergeon5cacf9d2019-08-14 10:41:17 +020058def summaryBenchmark(resultPath,elem,path):
Christophe Favergeon3b2a0ee2019-06-12 13:29:14 +020059 regressionPath=os.path.join(os.path.dirname(path),"regression.csv")
Christophe Favergeon3b2a0ee2019-06-12 13:29:14 +020060
Christophe Favergeon74a31ba2019-09-09 09:14:18 +010061 if os.path.isfile(path):
62 print(" Generating %s" % regressionPath)
63 full=pd.read_csv(path,dtype={'OLDID': str} ,keep_default_na = False)
64 #print(full)
65
66 csvheaders = []
67 with open(os.path.join(resultPath,'currentConfig.csv'), 'r') as f:
68 reader = csv.reader(f)
69 csvheaders = next(reader, None)
70
71 groupList = list(set(elem.params.full) - set(elem.params.summary))
72 #grouped=full.groupby(list(elem.params.summary) + ['ID','CATEGORY']).max()
73 #grouped.reset_index(level=grouped.index.names, inplace=True)
74 #print(grouped)
75 #print(grouped.columns)
Christophe Favergeon3b2a0ee2019-06-12 13:29:14 +020076
77
Christophe Favergeon74a31ba2019-09-09 09:14:18 +010078 def reg(d):
79 m=d["CYCLES"].max()
80 results = smf.ols('CYCLES ~ ' + elem.params.formula, data=d).fit()
81 f=joinit([formatProd(a,b) for (a,b) in zip(results.params.index,results.params.values)]," + ")
82 f="".join(f)
83 f = re.sub(r':','*',f)
84 #print(results.summary())
85 return(pd.Series({'Regression':"%s" % f,'MAX' : m,'MAXREGCOEF' : results.params.values[-1]}))
Christophe Favergeon3b2a0ee2019-06-12 13:29:14 +020086
Christophe Favergeon74a31ba2019-09-09 09:14:18 +010087 regList = ['ID','OLDID','CATEGORY','NAME'] + csvheaders + groupList
88
89 regression=full.groupby(regList).apply(reg)
90 regression.reset_index(level=regression.index.names, inplace=True)
91 renamingDict = { a : b for (a,b) in zip(elem.params.full,elem.params.paramNames)}
92 regression = regression.rename(columns=renamingDict)
93 regression.to_csv(regressionPath,index=False,quoting=csv.QUOTE_NONNUMERIC)
Christophe Favergeon3b2a0ee2019-06-12 13:29:14 +020094
95
Christophe Favergeon5cacf9d2019-08-14 10:41:17 +020096def extractBenchmarks(resultPath,benchmark,elem):
Christophe Favergeon37b86222019-07-17 11:49:00 +020097 if not elem.data["deprecated"]:
98 if elem.params:
99 benchPath = os.path.join(benchmark,elem.fullPath(),"fullBenchmark.csv")
100 print("Processing %s" % benchPath)
Christophe Favergeon5cacf9d2019-08-14 10:41:17 +0200101 summaryBenchmark(resultPath,elem,benchPath)
Christophe Favergeon37b86222019-07-17 11:49:00 +0200102
103 for c in elem.children:
Christophe Favergeon5cacf9d2019-08-14 10:41:17 +0200104 extractBenchmarks(resultPath,benchmark,c)
Christophe Favergeon3b2a0ee2019-06-12 13:29:14 +0200105
Christophe Favergeon3b2a0ee2019-06-12 13:29:14 +0200106
107
108parser = argparse.ArgumentParser(description='Generate summary benchmarks')
109
Christophe Favergeon512b1482020-02-07 11:25:11 +0100110parser.add_argument('-f', nargs='?',type = str, default="Output.pickle", help="Test description cache")
Christophe Favergeon3b2a0ee2019-06-12 13:29:14 +0200111parser.add_argument('-b', nargs='?',type = str, default="FullBenchmark", help="Full Benchmark dir path")
Christophe Favergeon5cacf9d2019-08-14 10:41:17 +0200112# Needed to find the currentConfig.csv and know the headers
113parser.add_argument('-r', nargs='?',type = str, default=None, help="Result file path")
Christophe Favergeon3b2a0ee2019-06-12 13:29:14 +0200114
Christophe Favergeon37b86222019-07-17 11:49:00 +0200115parser.add_argument('others', nargs=argparse.REMAINDER)
116
Christophe Favergeon3b2a0ee2019-06-12 13:29:14 +0200117args = parser.parse_args()
118
119if args.f is not None:
Christophe Favergeon6f8eee92019-10-09 12:21:27 +0100120 #p = parse.Parser()
Christophe Favergeon3b2a0ee2019-06-12 13:29:14 +0200121 # Parse the test description file
Christophe Favergeon6f8eee92019-10-09 12:21:27 +0100122 #root = p.parse(args.f)
123 root=parse.loadRoot(args.f)
Christophe Favergeon37b86222019-07-17 11:49:00 +0200124 d.deprecate(root,args.others)
Christophe Favergeon5cacf9d2019-08-14 10:41:17 +0200125 resultPath=os.path.dirname(args.r)
126 extractBenchmarks(resultPath,args.b,root)
Christophe Favergeon3b2a0ee2019-06-12 13:29:14 +0200127
128else:
129 parser.print_help()