ba98f95aa5
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284 lines
10 KiB
Python
284 lines
10 KiB
Python
'''
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Created on May 19, 2011
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@author: bungeman
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'''
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import re
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import math
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# bench representation algorithm constant names
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ALGORITHM_AVERAGE = 'avg'
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ALGORITHM_MEDIAN = 'med'
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ALGORITHM_MINIMUM = 'min'
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ALGORITHM_25TH_PERCENTILE = '25th'
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class BenchDataPoint:
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"""A single data point produced by bench.
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(str, str, str, float, {str:str}, str, [floats])"""
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def __init__(self, bench, config, time_type, time, settings,
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tile_layout='', per_tile_values=[]):
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self.bench = bench
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self.config = config
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self.time_type = time_type
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self.time = time
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self.settings = settings
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# how tiles cover the whole picture. '5x3' means 5 columns and 3 rows.
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self.tile_layout = tile_layout
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# list of per_tile bench values, if applicable
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self.per_tile_values = per_tile_values
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def __repr__(self):
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return "BenchDataPoint(%s, %s, %s, %s, %s)" % (
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str(self.bench),
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str(self.config),
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str(self.time_type),
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str(self.time),
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str(self.settings),
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)
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class _ExtremeType(object):
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"""Instances of this class compare greater or less than other objects."""
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def __init__(self, cmpr, rep):
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object.__init__(self)
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self._cmpr = cmpr
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self._rep = rep
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def __cmp__(self, other):
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if isinstance(other, self.__class__) and other._cmpr == self._cmpr:
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return 0
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return self._cmpr
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def __repr__(self):
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return self._rep
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Max = _ExtremeType(1, "Max")
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Min = _ExtremeType(-1, "Min")
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class _ListAlgorithm(object):
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"""Algorithm for selecting the representation value from a given list.
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representation is one of the ALGORITHM_XXX representation types."""
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def __init__(self, data, representation=None):
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if not representation:
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representation = ALGORITHM_AVERAGE # default algorithm
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self._data = data
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self._len = len(data)
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if representation == ALGORITHM_AVERAGE:
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self._rep = sum(self._data) / self._len
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else:
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self._data.sort()
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if representation == ALGORITHM_MINIMUM:
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self._rep = self._data[0]
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else:
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# for percentiles, we use the value below which x% of values are
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# found, which allows for better detection of quantum behaviors.
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if representation == ALGORITHM_MEDIAN:
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x = int(round(0.5 * self._len + 0.5))
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elif representation == ALGORITHM_25TH_PERCENTILE:
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x = int(round(0.25 * self._len + 0.5))
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else:
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raise Exception("invalid representation algorithm %s!" %
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representation)
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self._rep = self._data[x - 1]
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def compute(self):
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return self._rep
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def _ParseAndStoreTimes(config_re, time_re, line, bench, value_dic, layout_dic,
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representation=None):
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"""Parses given bench time line with regex and adds data to value_dic.
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For per-tile benches, adds tile layout into layout_dic as well.
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config_re: regular expression for parsing the config line.
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time_re: regular expression for parsing bench time.
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line: input string line to parse.
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bench: name of bench for the time values.
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value_dic: dictionary to store bench values. See bench_dic in parse() below.
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layout_dic: dictionary to store tile layouts. See parse() for descriptions.
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representation: should match one of the ALGORITHM_XXX types."""
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# for extracting tile layout
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tile_layout_re = ' out of \[(\d+),(\d+)\] <averaged>: '
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for config in re.finditer(config_re, line):
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current_config = config.group(1)
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tile_layout = ''
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if config_re.startswith(' tile_'): # per-tile bench, add name prefix
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current_config = 'tile_' + current_config
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layouts = re.search(tile_layout_re, line)
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if layouts and len(layouts.groups()) == 2:
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tile_layout = '%sx%s' % layouts.groups()
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times = config.group(2)
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for new_time in re.finditer(time_re, times):
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current_time_type = new_time.group(1)
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iters = [float(i) for i in
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new_time.group(2).strip().split(',')]
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value_dic.setdefault(bench, {}).setdefault(
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current_config, {}).setdefault(current_time_type, []).append(
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_ListAlgorithm(iters, representation).compute())
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layout_dic.setdefault(bench, {}).setdefault(
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current_config, {}).setdefault(current_time_type, tile_layout)
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def parse(settings, lines, representation=None):
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"""Parses bench output into a useful data structure.
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({str:str}, __iter__ -> str) -> [BenchDataPoint]
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representation is one of the ALGORITHM_XXX types."""
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benches = []
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current_bench = None
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bench_dic = {} # [bench][config][time_type] -> [list of bench values]
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# [bench][config][time_type] -> tile_layout
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layout_dic = {}
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setting_re = '([^\s=]+)(?:=(\S+))?'
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settings_re = 'skia bench:((?:\s+' + setting_re + ')*)'
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bench_re = 'running bench (?:\[\d+ \d+\] )?\s*(\S+)'
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time_re = '(?:(\w*)msecs = )?\s*((?:\d+\.\d+)(?:,\d+\.\d+)*)'
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# non-per-tile benches have configs that don't end with ']' or '>'
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config_re = '(\S+[^\]>]): ((?:' + time_re + '\s+)+)'
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# per-tile bench lines are in the following format. Note that there are
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# non-averaged bench numbers in separate lines, which we ignore now due to
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# their inaccuracy.
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tile_re = (' tile_(\S+): tile \[\d+,\d+\] out of \[\d+,\d+\] <averaged>:'
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' ((?:' + time_re + '\s+)+)')
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for line in lines:
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# see if this line is a settings line
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settingsMatch = re.search(settings_re, line)
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if (settingsMatch):
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settings = dict(settings)
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for settingMatch in re.finditer(setting_re, settingsMatch.group(1)):
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if (settingMatch.group(2)):
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settings[settingMatch.group(1)] = settingMatch.group(2)
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else:
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settings[settingMatch.group(1)] = True
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# see if this line starts a new bench
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new_bench = re.search(bench_re, line)
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if new_bench:
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current_bench = new_bench.group(1)
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# add configs on this line to the bench_dic
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if current_bench:
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for regex in [config_re, tile_re]:
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_ParseAndStoreTimes(regex, time_re, line, current_bench,
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bench_dic, layout_dic, representation)
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# append benches to list, use the total time as final bench value.
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for bench in bench_dic:
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for config in bench_dic[bench]:
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for time_type in bench_dic[bench][config]:
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tile_layout = ''
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per_tile_values = []
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if len(bench_dic[bench][config][time_type]) > 1:
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# per-tile values, extract tile_layout
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per_tile_values = bench_dic[bench][config][time_type]
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tile_layout = layout_dic[bench][config][time_type]
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benches.append(BenchDataPoint(
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bench,
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config,
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time_type,
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sum(bench_dic[bench][config][time_type]),
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settings,
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tile_layout,
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per_tile_values))
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return benches
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class LinearRegression:
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"""Linear regression data based on a set of data points.
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([(Number,Number)])
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There must be at least two points for this to make sense."""
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def __init__(self, points):
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n = len(points)
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max_x = Min
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min_x = Max
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Sx = 0.0
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Sy = 0.0
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Sxx = 0.0
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Sxy = 0.0
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Syy = 0.0
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for point in points:
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x = point[0]
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y = point[1]
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max_x = max(max_x, x)
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min_x = min(min_x, x)
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Sx += x
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Sy += y
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Sxx += x*x
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Sxy += x*y
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Syy += y*y
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denom = n*Sxx - Sx*Sx
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if (denom != 0.0):
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B = (n*Sxy - Sx*Sy) / denom
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else:
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B = 0.0
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a = (1.0/n)*(Sy - B*Sx)
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se2 = 0
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sB2 = 0
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sa2 = 0
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if (n >= 3 and denom != 0.0):
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se2 = (1.0/(n*(n-2)) * (n*Syy - Sy*Sy - B*B*denom))
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sB2 = (n*se2) / denom
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sa2 = sB2 * (1.0/n) * Sxx
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self.slope = B
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self.intercept = a
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self.serror = math.sqrt(max(0, se2))
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self.serror_slope = math.sqrt(max(0, sB2))
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self.serror_intercept = math.sqrt(max(0, sa2))
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self.max_x = max_x
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self.min_x = min_x
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def __repr__(self):
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return "LinearRegression(%s, %s, %s, %s, %s)" % (
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str(self.slope),
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str(self.intercept),
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str(self.serror),
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str(self.serror_slope),
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str(self.serror_intercept),
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)
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def find_min_slope(self):
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"""Finds the minimal slope given one standard deviation."""
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slope = self.slope
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intercept = self.intercept
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error = self.serror
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regr_start = self.min_x
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regr_end = self.max_x
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regr_width = regr_end - regr_start
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if slope < 0:
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lower_left_y = slope*regr_start + intercept - error
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upper_right_y = slope*regr_end + intercept + error
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return min(0, (upper_right_y - lower_left_y) / regr_width)
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elif slope > 0:
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upper_left_y = slope*regr_start + intercept + error
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lower_right_y = slope*regr_end + intercept - error
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return max(0, (lower_right_y - upper_left_y) / regr_width)
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return 0
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def CreateRevisionLink(revision_number):
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"""Returns HTML displaying the given revision number and linking to
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that revision's change page at code.google.com, e.g.
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http://code.google.com/p/skia/source/detail?r=2056
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"""
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return '<a href="http://code.google.com/p/skia/source/detail?r=%s">%s</a>'%(
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revision_number, revision_number)
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def main():
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foo = [[0.0, 0.0], [0.0, 1.0], [0.0, 2.0], [0.0, 3.0]]
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LinearRegression(foo)
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if __name__ == "__main__":
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main()
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