1# 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
15import TestScripts.Deprecate as d
16
17result = []
18commonParams = []
19
20def findItem(root,path):
21        """ Find a node in a tree
22
23        Args:
24          path (list) : A list of node ID
25            This list is describing a path in the tree.
26            By starting from the root and following this path,
27            we can find the node in the tree.
28        Raises:
29          Nothing
30        Returns:
31          TreeItem : A node
32        """
33        # The list is converted into a queue.
34        q = deque(path)
35        q.popleft()
36        c = root
37        while q:
38            n = q.popleft()
39            # We get the children based on its ID and continue
40            c = c[n-1]
41        return(c)
42
43
44
45NORMAL = 1
46INTEST = 2
47TESTPARAM = 3
48
49def joinit(iterable, delimiter):
50    it = iter(iterable)
51    yield next(it)
52    for x in it:
53        yield delimiter
54        yield x
55
56def formatProd(a,b):
57  if a == "Intercept":
58     return(str(b))
59  return("%s * %s" % (a,b))
60
61def convert(elem,fullPath):
62   global commonParams
63   global result
64   regressionPath=os.path.join(os.path.dirname(fullPath),"regression.csv")
65   full=pd.read_csv(fullPath,dtype={'OLDID': str} ,keep_default_na = False)
66   reg=pd.read_csv(regressionPath,dtype={'OLDID': str} ,keep_default_na = False)
67   commonParams = list(joinit(elem.params.full,","))
68   header = ["OLDID"] + commonParams + ["CYCLES"]
69
70   r=full[header].rename(columns = {"OLDID":"TESTNB"})
71   r["TESTNB"] = pd.to_numeric(r["TESTNB"])
72   r["PASSED"]=1
73   result.append(r)
74
75
76def extractBenchmarks(benchmark,elem):
77  if not elem.data["deprecated"]:
78     if elem.params:
79         benchPath = os.path.join(benchmark,elem.fullPath(),"fullBenchmark.csv")
80         print("Processing %s" % benchPath)
81         convert(elem,benchPath)
82
83     for c in elem.children:
84       extractBenchmarks(benchmark,c)
85
86
87
88parser = argparse.ArgumentParser(description='Generate summary benchmarks')
89
90parser.add_argument('-f', nargs='?',type = str, default="Output.pickle", help="Test description file path")
91parser.add_argument('-b', nargs='?',type = str, default="FullBenchmark", help="Full Benchmark dir path")
92parser.add_argument('-e', action='store_true', help="Embedded test")
93parser.add_argument('-o', nargs='?',type = str, default="bench.csv", help="Output csv file using old format")
94
95parser.add_argument('others', nargs=argparse.REMAINDER)
96
97args = parser.parse_args()
98
99if args.f is not None:
100    #p = parse.Parser()
101    # Parse the test description file
102    #root = p.parse(args.f)
103    root=parse.loadRoot(args.f)
104    d.deprecate(root,args.others)
105    extractBenchmarks(args.b,root)
106    finalResult = pd.concat(result)
107    cols = ['TESTNB'] + commonParams
108    finalResult=finalResult.sort_values(by=cols)
109    finalResult.to_csv(args.o,index=False,quoting=csv.QUOTE_NONNUMERIC)
110
111else:
112    parser.print_help()