2011-06-17 13:58:14 +00:00
|
|
|
'''
|
|
|
|
Created on May 19, 2011
|
|
|
|
|
|
|
|
@author: bungeman
|
|
|
|
'''
|
|
|
|
|
|
|
|
import re
|
|
|
|
import math
|
|
|
|
|
|
|
|
class BenchDataPoint:
|
|
|
|
"""A single data point produced by bench.
|
|
|
|
|
|
|
|
(str, str, str, float, {str:str})"""
|
|
|
|
def __init__(self, bench, config, time_type, time, settings):
|
|
|
|
self.bench = bench
|
|
|
|
self.config = config
|
|
|
|
self.time_type = time_type
|
|
|
|
self.time = time
|
|
|
|
self.settings = settings
|
|
|
|
|
|
|
|
def __repr__(self):
|
|
|
|
return "BenchDataPoint(%s, %s, %s, %s, %s)" % (
|
|
|
|
str(self.bench),
|
|
|
|
str(self.config),
|
|
|
|
str(self.time_type),
|
|
|
|
str(self.time),
|
|
|
|
str(self.settings),
|
|
|
|
)
|
|
|
|
|
|
|
|
class _ExtremeType(object):
|
|
|
|
"""Instances of this class compare greater or less than other objects."""
|
|
|
|
def __init__(self, cmpr, rep):
|
|
|
|
object.__init__(self)
|
|
|
|
self._cmpr = cmpr
|
|
|
|
self._rep = rep
|
|
|
|
|
|
|
|
def __cmp__(self, other):
|
|
|
|
if isinstance(other, self.__class__) and other._cmpr == self._cmpr:
|
|
|
|
return 0
|
|
|
|
return self._cmpr
|
|
|
|
|
|
|
|
def __repr__(self):
|
|
|
|
return self._rep
|
|
|
|
|
|
|
|
Max = _ExtremeType(1, "Max")
|
|
|
|
Min = _ExtremeType(-1, "Min")
|
|
|
|
|
|
|
|
def parse(settings, lines):
|
|
|
|
"""Parses bench output into a useful data structure.
|
|
|
|
|
|
|
|
({str:str}, __iter__ -> str) -> [BenchDataPoint]"""
|
|
|
|
|
|
|
|
benches = []
|
|
|
|
current_bench = None
|
|
|
|
setting_re = '([^\s=]+)(?:=(\S+))?'
|
|
|
|
settings_re = 'skia bench:((?:\s+' + setting_re + ')*)'
|
|
|
|
bench_re = 'running bench (?:\[\d+ \d+\] )?\s*(\S+)'
|
2012-07-02 20:48:51 +00:00
|
|
|
time_re = '(?:(\w*)msecs = )?\s*((?:\d+\.\d+)(?:,\d+\.\d+)*)'
|
2011-06-17 13:58:14 +00:00
|
|
|
config_re = '(\S+): ((?:' + time_re + '\s+)+)'
|
|
|
|
|
|
|
|
for line in lines:
|
|
|
|
|
|
|
|
#see if this line is a settings line
|
|
|
|
settingsMatch = re.search(settings_re, line)
|
|
|
|
if (settingsMatch):
|
|
|
|
settings = dict(settings)
|
|
|
|
for settingMatch in re.finditer(setting_re, settingsMatch.group(1)):
|
|
|
|
if (settingMatch.group(2)):
|
|
|
|
settings[settingMatch.group(1)] = settingMatch.group(2)
|
|
|
|
else:
|
|
|
|
settings[settingMatch.group(1)] = True
|
|
|
|
|
|
|
|
#see if this line starts a new bench
|
|
|
|
new_bench = re.search(bench_re, line)
|
|
|
|
if new_bench:
|
|
|
|
current_bench = new_bench.group(1)
|
|
|
|
|
|
|
|
#add configs on this line to the current bench
|
|
|
|
if current_bench:
|
|
|
|
for new_config in re.finditer(config_re, line):
|
|
|
|
current_config = new_config.group(1)
|
|
|
|
times = new_config.group(2)
|
|
|
|
for new_time in re.finditer(time_re, times):
|
|
|
|
current_time_type = new_time.group(1)
|
2012-07-02 21:49:30 +00:00
|
|
|
iters = [float(i) for i in
|
2012-07-02 20:48:51 +00:00
|
|
|
new_time.group(2).strip().split(',')]
|
|
|
|
current_time = sum(iters) / len(iters)
|
2011-06-17 13:58:14 +00:00
|
|
|
benches.append(BenchDataPoint(
|
|
|
|
current_bench
|
|
|
|
, current_config
|
|
|
|
, current_time_type
|
|
|
|
, current_time
|
|
|
|
, settings))
|
|
|
|
|
|
|
|
return benches
|
|
|
|
|
|
|
|
class LinearRegression:
|
|
|
|
"""Linear regression data based on a set of data points.
|
|
|
|
|
|
|
|
([(Number,Number)])
|
|
|
|
There must be at least two points for this to make sense."""
|
|
|
|
def __init__(self, points):
|
|
|
|
n = len(points)
|
|
|
|
max_x = Min
|
|
|
|
min_x = Max
|
|
|
|
|
|
|
|
Sx = 0.0
|
|
|
|
Sy = 0.0
|
|
|
|
Sxx = 0.0
|
|
|
|
Sxy = 0.0
|
|
|
|
Syy = 0.0
|
|
|
|
for point in points:
|
|
|
|
x = point[0]
|
|
|
|
y = point[1]
|
|
|
|
max_x = max(max_x, x)
|
|
|
|
min_x = min(min_x, x)
|
|
|
|
|
|
|
|
Sx += x
|
|
|
|
Sy += y
|
|
|
|
Sxx += x*x
|
|
|
|
Sxy += x*y
|
|
|
|
Syy += y*y
|
|
|
|
|
|
|
|
B = (n*Sxy - Sx*Sy) / (n*Sxx - Sx*Sx)
|
|
|
|
a = (1.0/n)*(Sy - B*Sx)
|
|
|
|
|
|
|
|
se2 = 0
|
|
|
|
sB2 = 0
|
|
|
|
sa2 = 0
|
|
|
|
if (n >= 3):
|
|
|
|
se2 = (1.0/(n*(n-2)) * (n*Syy - Sy*Sy - B*B*(n*Sxx - Sx*Sx)))
|
|
|
|
sB2 = (n*se2) / (n*Sxx - Sx*Sx)
|
|
|
|
sa2 = sB2 * (1.0/n) * Sxx
|
|
|
|
|
|
|
|
|
|
|
|
self.slope = B
|
|
|
|
self.intercept = a
|
|
|
|
self.serror = math.sqrt(max(0, se2))
|
|
|
|
self.serror_slope = math.sqrt(max(0, sB2))
|
|
|
|
self.serror_intercept = math.sqrt(max(0, sa2))
|
|
|
|
self.max_x = max_x
|
|
|
|
self.min_x = min_x
|
|
|
|
|
|
|
|
def __repr__(self):
|
|
|
|
return "LinearRegression(%s, %s, %s, %s, %s)" % (
|
|
|
|
str(self.slope),
|
|
|
|
str(self.intercept),
|
|
|
|
str(self.serror),
|
|
|
|
str(self.serror_slope),
|
|
|
|
str(self.serror_intercept),
|
|
|
|
)
|
|
|
|
|
|
|
|
def find_min_slope(self):
|
|
|
|
"""Finds the minimal slope given one standard deviation."""
|
|
|
|
slope = self.slope
|
|
|
|
intercept = self.intercept
|
|
|
|
error = self.serror
|
|
|
|
regr_start = self.min_x
|
|
|
|
regr_end = self.max_x
|
|
|
|
regr_width = regr_end - regr_start
|
|
|
|
|
|
|
|
if slope < 0:
|
|
|
|
lower_left_y = slope*regr_start + intercept - error
|
|
|
|
upper_right_y = slope*regr_end + intercept + error
|
|
|
|
return min(0, (upper_right_y - lower_left_y) / regr_width)
|
|
|
|
|
|
|
|
elif slope > 0:
|
|
|
|
upper_left_y = slope*regr_start + intercept + error
|
|
|
|
lower_right_y = slope*regr_end + intercept - error
|
|
|
|
return max(0, (lower_right_y - upper_left_y) / regr_width)
|
|
|
|
|
|
|
|
return 0
|
2011-08-08 17:19:23 +00:00
|
|
|
|
|
|
|
def CreateRevisionLink(revision_number):
|
|
|
|
"""Returns HTML displaying the given revision number and linking to
|
|
|
|
that revision's change page at code.google.com, e.g.
|
|
|
|
http://code.google.com/p/skia/source/detail?r=2056
|
|
|
|
"""
|
|
|
|
return '<a href="http://code.google.com/p/skia/source/detail?r=%s">%s</a>'%(
|
|
|
|
revision_number, revision_number)
|