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Issue 1253013003: Remove all perl scripts from Tools/Scripts (Closed) Base URL: svn://svn.chromium.org/blink/trunk
Patch Set: Remove the python code to invoke Perl \o/ Created 5 years, 4 months ago
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1 #!/usr/bin/env python
2
3 # Copyright (C) 2007, 2012 Apple Inc. All rights reserved.
4 #
5 # Redistribution and use in source and binary forms, with or without
6 # modification, are permitted provided that the following conditions
7 # are met:
8 # 1. Redistributions of source code must retain the above copyright
9 # notice, this list of conditions and the following disclaimer.
10 # 2. Redistributions in binary form must reproduce the above copyright
11 # notice, this list of conditions and the following disclaimer in the
12 # documentation and/or other materials provided with the distribution.
13 #
14 # THIS SOFTWARE IS PROVIDED BY APPLE COMPUTER, INC. ``AS IS'' AND ANY
15 # EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
16 # IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR
17 # PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL APPLE COMPUTER, INC. OR
18 # CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
19 # EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
20 # PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR
21 # PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY
22 # OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT
23 # (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
24 # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
25
26 import math
27 import sys
28 import re
29 import fileinput
30 from optparse import OptionParser
31
32 usage = "usage: %prog [options] [FILES]\n Compute the mean and 95% confidence i nterval of a sample set.\n Standard input or files must contain two or more dec imal numbers, one per line."
33 parser = OptionParser(usage=usage)
34 parser.add_option("-u", "--unit", dest="unit", default="",
35 help="assume values are in units of UNIT", metavar="UNIT")
36 parser.add_option("-v", "--verbose",
37 action="store_true", dest="verbose", default=False,
38 help="print all values (with units)")
39 (options, files) = parser.parse_args()
40
41 def sum(items):
42 return reduce(lambda x,y: x+y, items)
43
44 def arithmeticMean(items):
45 return sum(items) / len(items)
46
47 def standardDeviation(mean, items):
48 deltaSquares = [(item - mean) ** 2 for item in items]
49 return math.sqrt(sum(deltaSquares) / (len(items) - 1))
50
51 def standardError(stdDev, items):
52 return stdDev / math.sqrt(len(items))
53
54 # t-distribution for 2-sided 95% confidence intervals
55 tDistribution = [float('NaN'), float('NaN'), 12.71, 4.30, 3.18, 2.78, 2.57, 2.45 , 2.36, 2.31, 2.26, 2.23, 2.20, 2.18, 2.16, 2.14, 2.13, 2.12, 2.11, 2.10, 2.09, 2.09, 2.08, 2.07, 2.07, 2.06, 2.06, 2.06, 2.05, 2.05, 2.05, 2.04, 2.04, 2.04, 2. 03, 2.03, 2.03, 2.03, 2.03, 2.02, 2.02, 2.02, 2.02, 2.02, 2.02, 2.02, 2.01, 2.01 , 2.01, 2.01, 2.01, 2.01, 2.01, 2.01, 2.01, 2.00, 2.00, 2.00, 2.00, 2.00, 2.00, 2.00, 2.00, 2.00, 2.00, 2.00, 2.00, 2.00, 2.00, 2.00, 1.99, 1.99, 1.99, 1.99, 1. 99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99 , 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.99, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1. 98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98 , 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.98, 1. 98, 1.98, 1.98, 1.98, 1.98, 1.98, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97 , 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1. 97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97 , 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1. 97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97 , 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1. 97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97 , 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1. 97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97 , 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1. 97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97 , 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1. 97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97 , 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1. 97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97 , 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1.97, 1. 96]
56 tMax = len(tDistribution)
57 tLimit = 1.96
58
59 def tDist(n):
60 if n > tMax:
61 return tLimit
62 return tDistribution[n]
63
64 def twoSidedConfidenceInterval(items):
65 mean = arithmeticMean(items)
66 stdDev = standardDeviation(mean, items)
67 stdErr = standardError(stdDev, items)
68 return tDist(len(items)) * stdErr
69
70 results = []
71
72 decimalNumberPattern = re.compile(r"\d+\.?\d*")
73 for line in fileinput.input(files):
74 match = re.search(decimalNumberPattern, line)
75 if match:
76 results.append(float(match.group(0)))
77
78 if len(results) == 0:
79 parser.print_help()
80 quit()
81
82
83 mean = arithmeticMean(results)
84 confidenceInterval = twoSidedConfidenceInterval(results)
85 confidencePercent = 100 * confidenceInterval / mean
86
87 if options.verbose:
88 length = 7
89 for item in results:
90 line = " %.2f %s" % (item, options.unit)
91 print line
92 length = len(line) if len(line) > length else length
93
94 print "-" * length
95
96 prefix = "Mean: " if options.verbose else ""
97 print "%s%.2f %s +/- %.2f %s (%.1f%%)" % (prefix, mean, options.unit, confidence Interval, options.unit, confidencePercent)
98
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