Mercurial Hosting > traffic-intelligence
annotate trafficintelligence/utils.py @ 1064:cbc026dacf0b
changed interval string representation
author | Nicolas Saunier <nicolas.saunier@polymtl.ca> |
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date | Sun, 15 Jul 2018 22:52:26 -0400 |
parents | c04550f957ab |
children | 8734742c08c0 |
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1 #! /usr/bin/env python |
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2 ''' Generic utilities.''' |
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3 |
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4 from datetime import time, datetime |
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5 from argparse import ArgumentTypeError |
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6 from pathlib import Path |
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7 from math import sqrt, ceil, floor |
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8 from copy import deepcopy, copy |
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9 from collections import Counter |
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10 |
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11 from scipy.stats import rv_continuous, kruskal, shapiro, lognorm, norm, t |
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12 from scipy.spatial import distance |
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13 from scipy.sparse import dok_matrix |
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14 from numpy import zeros, array, exp, sum as npsum, int as npint, arange, cumsum, mean, median, percentile, isnan, ones, convolve, dtype, isnan, NaN, ma, isinf, savez, load as npload, log, polyfit, float as npfloat |
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15 from numpy.random import permutation as nppermutation |
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16 from pandas import DataFrame, concat |
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17 import matplotlib.pyplot as plt |
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18 |
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19 datetimeFormat = "%Y-%m-%d %H:%M:%S" |
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20 |
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21 sjcamDatetimeFormat = "%Y_%m%d_%H%M%S"#2017_0626_143720 |
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22 |
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23 ######################### |
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24 # txt files |
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25 ######################### |
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26 |
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27 commentChar = '#' |
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28 |
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29 delimiterChar = '%'; |
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30 |
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31 def openCheck(filename, option = 'r', quitting = False): |
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32 '''Open file filename in read mode by default |
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33 and checks it is open''' |
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34 try: |
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35 return open(filename, option) |
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36 except IOError: |
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37 print('File {} could not be opened.'.format(filename)) |
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38 if quitting: |
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39 from sys import exit |
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40 exit() |
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41 return None |
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42 |
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43 def readline(f, commentCharacters = commentChar): |
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44 '''Modified readline function to skip comments |
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45 Can take a list of characters or a string (in will work in both)''' |
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46 s = f.readline() |
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47 while (len(s) > 0) and s[0] in commentCharacters: |
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48 s = f.readline() |
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49 return s.strip() |
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50 |
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51 def getLines(f, delimiterChar = delimiterChar, commentCharacters = commentChar): |
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52 '''Gets a complete entry (all the lines) in between delimiterChar.''' |
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53 dataStrings = [] |
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54 s = readline(f, commentCharacters) |
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55 while len(s) > 0 and s[0] != delimiterChar: |
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56 dataStrings += [s.strip()] |
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57 s = readline(f, commentCharacters) |
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58 return dataStrings |
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59 |
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60 ######################### |
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61 # Strings |
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62 ######################### |
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63 |
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64 def upperCaseFirstLetter(s): |
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65 words = s.split(' ') |
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66 lowerWords = [w[0].upper()+w[1:].lower() for w in words] |
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67 return ' '.join(lowerWords) |
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68 |
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69 class TimeConverter: |
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70 def __init__(self, datetimeFormat = datetimeFormat): |
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71 self.datetimeFormat = datetimeFormat |
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72 |
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73 def convert(self, s): |
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74 try: |
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75 return datetime.strptime(s, self.datetimeFormat) |
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76 except ValueError: |
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77 msg = "Not a valid date: '{0}'.".format(s) |
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78 raise ArgumentTypeError(msg) |
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79 |
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80 ######################### |
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81 # Enumerations |
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82 ######################### |
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83 |
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84 def inverseEnumeration(l): |
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85 'Returns the dictionary that provides for each element in the input list its index in the input list' |
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86 result = {} |
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87 for i,x in enumerate(l): |
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88 result[x] = i |
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89 return result |
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90 |
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91 ######################### |
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92 # Simple statistics |
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93 ######################### |
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94 |
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95 def logNormalMeanVar(loc, scale): |
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96 '''location and scale are respectively the mean and standard deviation of the normal in the log-normal distribution |
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97 https://en.wikipedia.org/wiki/Log-normal_distribution |
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98 |
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99 same as lognorm.stats(scale, 0, exp(loc))''' |
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100 mean = exp(loc+(scale**2)/2) |
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101 var = (exp(scale**2)-1)*exp(2*loc+scale**2) |
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102 return mean, var |
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103 |
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104 def fitLogNormal(x): |
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105 'returns the fitted location and scale of the lognormal (general definition)' |
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106 shape, loc, scale = lognorm.fit(x, floc=0.) |
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107 return log(scale), shape |
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108 |
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109 def sampleSize(stdev, tolerance, percentConfidence, nRoundingDigits = None, printLatex = False): |
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110 if nRoundingDigits is None: |
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111 k = round(norm.ppf(0.5+percentConfidence/200., 0, 1), 2) # 1.-(100-percentConfidence)/200. |
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112 else: |
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113 k = round(norm.ppf(0.5+percentConfidence/200., 0, 1), nRoundingDigits) |
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114 stdev = round(stdev, nRoundingDigits) |
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115 tolerance = round(tolerance, nRoundingDigits) |
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116 if printLatex: |
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117 print('$z_{{{}}}^2\\frac{{s^2}}{{e^2}}={}^2\\frac{{{}^2}}{{{}^2}}$'.format(0.5+percentConfidence/200.,k, stdev, tolerance)) |
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118 return (k*stdev/tolerance)**2 |
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119 |
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120 def confidenceInterval(mean, stdev, nSamples, percentConfidence, trueStd = True, printLatex = False): |
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121 '''if trueStd, use normal distribution, otherwise, Student |
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122 |
973 | 123 Use otherwise t.interval or norm.interval for the boundaries |
124 ex: norm.interval(0.95) | |
125 t.interval(0.95, nSamples-1)''' | |
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126 if trueStd: |
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127 k = round(norm.ppf(0.5+percentConfidence/200., 0, 1), 2) |
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128 else: # use Student |
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129 k = round(t.ppf(0.5+percentConfidence/200., nSamples-1), 2) |
301
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130 e = k*stdev/sqrt(nSamples) |
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131 if printLatex: |
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132 print('${0} \pm {1}\\frac{{{2}}}{{\sqrt{{{3}}}}}$'.format(mean, k, stdev, nSamples)) |
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133 return mean-e, mean+e |
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134 |
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135 def computeChi2(expected, observed): |
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136 '''Returns the Chi2 statistics''' |
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137 return sum([((e-o)*(e-o))/float(e) for e, o in zip(expected, observed)]) |
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138 |
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139 class EmpiricalContinuousDistribution(rv_continuous): |
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140 def __init__(self, values, probabilities, **kwargs): |
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141 '''The values (and corresponding probabilities) are supposed to be sorted by value |
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142 for v, p in zip(values, probabilities): P(X<=v)=p''' |
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143 assert probabilities[0]==0 |
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144 super(EmpiricalContinuousDistribution, self).__init__(**kwargs) |
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145 self.values = values |
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146 self.probabilities = probabilities |
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147 |
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148 def _cdf(self, x): |
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149 if x < self.values[0]: |
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150 return self.probabilities[0] |
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151 else: |
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152 i=0 |
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153 while i+1<len(self.values) and self.values[i+1] < x: |
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154 i += 1 |
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155 if i == len(self.values)-1: |
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156 return self.probabilities[-1] |
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157 else: |
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158 return self.probabilities[i]+(x-self.values[i])*float(self.probabilities[i+1]-self.probabilities[i])/float(self.values[i+1]-self.values[i]) |
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159 |
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160 class DistributionSample(object): |
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161 def nSamples(self): |
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162 return sum(self.counts) |
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163 |
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164 def cumulativeDensityFunction(sample, normalized = False): |
276 | 165 '''Returns the cumulative density function of the sample of a random variable''' |
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166 xaxis = sorted(sample) |
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167 counts = arange(1,len(sample)+1) # dtype = float |
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168 if normalized: |
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169 counts = counts.astype(float)/float(len(sample)) |
197
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170 return xaxis, counts |
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171 |
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172 class DiscreteDistributionSample(DistributionSample): |
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173 '''Class to represent a sample of a distribution for a discrete random variable''' |
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174 def __init__(self, categories, counts): |
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175 self.categories = categories |
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176 self.counts = counts |
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177 |
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178 def mean(self): |
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179 result = [float(x*y) for x,y in zip(self.categories, self.counts)] |
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180 return npsum(result)/self.nSamples() |
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181 |
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182 def var(self, mean = None): |
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183 if not mean: |
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184 m = self.mean() |
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185 else: |
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186 m = mean |
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187 result = 0. |
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188 squares = [float((x-m)*(x-m)*y) for x,y in zip(self.categories, self.counts)] |
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189 return npsum(squares)/(self.nSamples()-1) |
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190 |
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191 def referenceCounts(self, probability): |
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192 '''probability is a function that returns the probability of the random variable for the category values''' |
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193 refProba = [probability(c) for c in self.categories] |
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194 refProba[-1] = 1-npsum(refProba[:-1]) |
86
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195 refCounts = [r*self.nSamples() for r in refProba] |
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196 return refCounts, refProba |
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197 |
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198 class ContinuousDistributionSample(DistributionSample): |
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199 '''Class to represent a sample of a distribution for a continuous random variable |
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200 with the number of observations for each interval |
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201 intervals (categories variable) are defined by their left limits, the last one being the right limit |
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202 categories contain therefore one more element than the counts''' |
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203 def __init__(self, categories, counts): |
276 | 204 # todo add samples for initialization and everything to None? (or setSamples?) |
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205 self.categories = categories |
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206 self.counts = counts |
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207 |
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208 @staticmethod |
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209 def generate(sample, categories): |
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210 if min(sample) < min(categories): |
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211 print('Sample has lower min than proposed categories ({}, {})'.format(min(sample), min(categories))) |
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212 if max(sample) > max(categories): |
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213 print('Sample has higher max than proposed categories ({}, {})'.format(max(sample), max(categories))) |
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214 dist = ContinuousDistributionSample(sorted(categories), [0]*(len(categories)-1)) |
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215 for s in sample: |
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216 i = 0 |
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217 while i<len(dist.categories) and dist.categories[i] <= s: |
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218 i += 1 |
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219 if i <= len(dist.counts): |
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220 dist.counts[i-1] += 1 |
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221 #print('{} in {} {}'.format(s, dist.categories[i-1], dist.categories[i])) |
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222 else: |
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223 print('Element {} is not in the categories'.format(s)) |
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224 return dist |
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225 |
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226 def mean(self): |
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227 result = 0. |
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228 for i in range(len(self.counts)-1): |
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229 result += self.counts[i]*(self.categories[i]+self.categories[i+1])/2 |
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230 return result/self.nSamples() |
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231 |
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232 def var(self, mean = None): |
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233 if not mean: |
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234 m = self.mean() |
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235 else: |
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236 m = mean |
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237 result = 0. |
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238 for i in range(len(self.counts)-1): |
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239 mid = (self.categories[i]+self.categories[i+1])/2 |
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240 result += self.counts[i]*(mid - m)*(mid - m) |
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241 return result/(self.nSamples()-1) |
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242 |
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243 def referenceCounts(self, cdf): |
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244 '''cdf is a cumulative distribution function |
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245 returning the probability of the variable being less that x''' |
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246 # refCumulativeCounts = [0]#[cdf(self.categories[0][0])] |
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247 # for inter in self.categories: |
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248 # refCumulativeCounts.append(cdf(inter[1])) |
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249 refCumulativeCounts = [cdf(x) for x in self.categories[1:-1]] |
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250 |
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251 refProba = [refCumulativeCounts[0]] |
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252 for i in xrange(1,len(refCumulativeCounts)): |
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253 refProba.append(refCumulativeCounts[i]-refCumulativeCounts[i-1]) |
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254 refProba.append(1-refCumulativeCounts[-1]) |
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255 refCounts = [p*self.nSamples() for p in refProba] |
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256 |
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257 return refCounts, refProba |
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258 |
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259 def printReferenceCounts(self, refCounts=None): |
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260 if refCounts: |
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261 ref = refCounts |
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262 else: |
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263 ref = self.referenceCounts |
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264 for i in xrange(len(ref[0])): |
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265 print('{0}-{1} & {2:0.3} & {3:0.3} \\\\'.format(self.categories[i],self.categories[i+1],ref[1][i], ref[0][i])) |
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266 |
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267 |
31
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268 ######################### |
370
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269 # maths section |
27
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270 ######################### |
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271 |
433
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272 # def kernelSmoothing(sampleX, X, Y, weightFunc, halfwidth): |
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273 # '''Returns a smoothed weighted version of Y at the predefined values of sampleX |
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274 # Sum_x weight(sample_x,x) * y(x)''' |
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275 # from numpy import zeros, array |
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276 # smoothed = zeros(len(sampleX)) |
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277 # for i,x in enumerate(sampleX): |
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278 # weights = array([weightFunc(x,xx, halfwidth) for xx in X]) |
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279 # if sum(weights)>0: |
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280 # smoothed[i] = sum(weights*Y)/sum(weights) |
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281 # else: |
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282 # smoothed[i] = 0 |
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283 # return smoothed |
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284 |
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285 def kernelSmoothing(x, X, Y, weightFunc, halfwidth): |
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286 '''Returns the smoothed estimate of (X,Y) at x |
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287 Sum_x weight(sample_x,x) * y(x)''' |
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288 weights = array([weightFunc(x,observedx, halfwidth) for observedx in X]) |
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289 if sum(weights)>0: |
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290 return sum(weights*Y)/sum(weights) |
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291 else: |
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292 return 0 |
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293 |
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294 def uniform(center, x, halfwidth): |
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295 if abs(center-x)<halfwidth: |
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296 return 1. |
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297 else: |
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298 return 0. |
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299 |
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300 def gaussian(center, x, halfwidth): |
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301 return exp(-((center-x)/halfwidth)**2/2) |
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302 |
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303 def epanechnikov(center, x, halfwidth): |
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304 diff = abs(center-x) |
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305 if diff<halfwidth: |
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306 return 1.-(diff/halfwidth)**2 |
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307 else: |
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308 return 0. |
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309 |
434 | 310 def triangular(center, x, halfwidth): |
311 diff = abs(center-x) | |
312 if diff<halfwidth: | |
313 return 1.-abs(diff/halfwidth) | |
314 else: | |
315 return 0. | |
433
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|
316 |
518
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diff
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317 def medianSmoothing(x, X, Y, halfwidth): |
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diff
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318 '''Returns the media of Y's corresponding to X's in the interval [x-halfwidth, x+halfwidth]''' |
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319 return median([y for observedx, y in zip(X,Y) if abs(x-observedx)<halfwidth]) |
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320 |
521
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changed argMaxDict name to argmaxDict
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518
diff
changeset
|
321 def argmaxDict(d): |
561
ee45c6eb6d49
added Mohamed Gomaa Mohamed function to smooth object trajectories
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553
diff
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|
322 return max(d, key=d.get) |
279
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generic simple LCSS
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diff
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|
323 |
837
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minor modifications to merge-features
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324 def deltaFrames(t1, t2, frameRate): |
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325 '''Returns the number of frames between t1 and t2 |
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326 positive if t1<=t2, negative otherwise''' |
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327 if t1 > t2: |
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328 return -(t1-t2).seconds*frameRate |
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329 else: |
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|
330 return (t2-t1).seconds*frameRate |
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|
331 |
395
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391
diff
changeset
|
332 def framesToTime(nFrames, frameRate, initialTime = time()): |
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391
diff
changeset
|
333 '''returns a datetime.time for the time in hour, minutes and seconds |
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391
diff
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|
334 initialTime is a datetime.time''' |
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diff
changeset
|
335 seconds = int(floor(float(nFrames)/float(frameRate))+initialTime.hour*3600+initialTime.minute*60+initialTime.second) |
261
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changing framesToTime to return a datetime.time
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diff
changeset
|
336 h = int(floor(seconds/3600.)) |
248
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diff
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|
337 seconds = seconds - h*3600 |
261
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diff
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|
338 m = int(floor(seconds/60)) |
248
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diff
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339 seconds = seconds - m*60 |
262
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correcting bug in framesToTime
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261
diff
changeset
|
340 return time(h, m, seconds) |
248
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diff
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|
341 |
381
387cc0142211
script to replay event annotations
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diff
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|
342 def timeToFrames(t, frameRate): |
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diff
changeset
|
343 return frameRate*(t.hour*3600+t.minute*60+t.second) |
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diff
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|
344 |
1059
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diff
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345 def timeModulo(t, duration): |
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346 'returns the time modulo the duration in min' |
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347 return time(t.hour, t.minute//duration, t.second) |
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diff
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348 |
241
ee1caff48b03
added function to sort to list of paired data X,Y
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diff
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|
349 def sortXY(X,Y): |
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diff
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|
350 'returns the sorted (x, Y(x)) sorted on X' |
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diff
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|
351 D = {} |
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diff
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|
352 for x, y in zip(X,Y): |
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diff
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353 D[x]=y |
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354 xsorted = sorted(D.keys()) |
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355 return xsorted, [D[x] for x in xsorted] |
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356 |
733 | 357 def compareLengthForSort(i, j): |
358 if len(i) < len(j): | |
359 return -1 | |
360 elif len(i) == len(j): | |
361 return 0 | |
362 else: | |
363 return 1 | |
364 | |
365 def sortByLength(instances, reverse = False): | |
366 '''Returns a new list with the instances sorted by length (method __len__) | |
367 reverse is passed to sorted''' | |
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368 return sorted(instances, key = len, reverse = reverse) |
733 | 369 |
32 | 370 def ceilDecimals(v, nDecimals): |
371 '''Rounds the number at the nth decimal | |
372 eg 1.23 at 0 decimal is 2, at 1 decimal is 1.3''' | |
670
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373 tens = 10**nDecimals |
32 | 374 return ceil(v*tens)/tens |
375 | |
152
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376 def inBetween(bound1, bound2, x): |
698
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377 'useful if one does not know the order of bound1/bound2' |
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378 return bound1 <= x <= bound2 or bound2 <= x <= bound1 |
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379 |
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380 def pointDistanceL2(x1,y1,x2,y2): |
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381 ''' Compute point-to-point distance (L2 norm, ie Euclidean distance)''' |
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382 return sqrt((x2-x1)**2+(y2-y1)**2) |
24
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383 |
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384 def crossProduct(l1, l2): |
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385 return l1[0]*l2[1]-l1[1]*l2[0] |
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386 |
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387 def cat_mvgavg(cat_list, halfWidth): |
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388 ''' Return a list of categories/values smoothed according to a window. |
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389 halfWidth is the search radius on either side''' |
659
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390 smoothed = deepcopy(cat_list) |
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391 for point in range(len(cat_list)): |
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392 lower_bound_check = max(0,point-halfWidth) |
659
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393 upper_bound_check = min(len(cat_list)-1,point+halfWidth+1) |
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394 window_values = cat_list[lower_bound_check:upper_bound_check] |
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395 smoothed[point] = max(set(window_values), key=window_values.count) |
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396 return smoothed |
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397 |
547 | 398 def filterMovingWindow(inputSignal, halfWidth): |
29
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399 '''Returns an array obtained after the smoothing of the input by a moving average |
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400 The first and last points are copied from the original.''' |
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401 width = float(halfWidth*2+1) |
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402 win = ones(width,'d') |
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403 result = convolve(win/width,array(inputSignal),'same') |
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404 result[:halfWidth] = inputSignal[:halfWidth] |
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405 result[-halfWidth:] = inputSignal[-halfWidth:] |
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406 return result |
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407 |
199
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408 def linearRegression(x, y, deg = 1, plotData = False): |
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409 '''returns the least square estimation of the linear regression of y = ax+b |
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410 as well as the plot''' |
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411 coef = polyfit(x, y, deg) |
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412 if plotData: |
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413 def poly(x): |
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414 result = 0 |
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415 for i in range(len(coef)): |
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416 result += coef[i]*x**(len(coef)-i-1) |
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417 return result |
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418 plt.plot(x, y, 'x') |
199
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419 xx = arange(min(x), max(x),(max(x)-min(x))/1000) |
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420 plt.plot(xx, [poly(z) for z in xx]) |
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421 return coef |
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422 |
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423 def correlation(data, correlationMethod = 'pearson', plotFigure = False, displayNames = None, figureFilename = None): |
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424 '''Computes (and displays) the correlation matrix for a pandas DataFrame''' |
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425 columns = data.columns.tolist() |
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426 for var in data.columns: |
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427 uniqueValues = data[var].unique() |
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428 if len(uniqueValues) == 1 or data.dtypes[var] == dtype('O') or (len(uniqueValues) == 2 and len(data.loc[~isnan(data[var]), var].unique()) == 1): # last condition: only one other value than nan |
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429 columns.remove(var) |
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430 c=data[columns].corr(correlationMethod) |
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431 if plotFigure: |
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432 fig = plt.figure(figsize=(4+0.4*c.shape[0], 0.4*c.shape[0])) |
668
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433 fig.add_subplot(1,1,1) |
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434 #plt.imshow(np.fabs(c), interpolation='none') |
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435 plt.imshow(c, vmin=-1., vmax = 1., interpolation='none', cmap = 'RdYlBu_r') # coolwarm |
847
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436 if displayNames is not None: |
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437 colnames = [displayNames.get(s.strip(), s.strip()) for s in columns] |
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438 else: |
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439 colnames = columns |
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440 #correlation.plot_corr(c, xnames = colnames, normcolor=True, title = filename) |
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441 plt.xticks(range(len(colnames)), colnames, rotation=90) |
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442 plt.yticks(range(len(colnames)), colnames) |
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443 plt.tick_params('both', length=0) |
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444 plt.subplots_adjust(bottom = 0.29) |
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445 plt.colorbar() |
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446 plt.title('Correlation ({})'.format(correlationMethod)) |
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447 plt.tight_layout() |
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448 if len(colnames) > 50: |
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449 plt.subplots_adjust(left=.06) |
668
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450 if figureFilename is not None: |
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451 plt.savefig(figureFilename, dpi = 150, transparent = True) |
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452 return c |
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453 |
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454 def addDummies(data, variables, allVariables = True): |
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455 '''Add binary dummy variables for each value of a nominal variable |
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456 in a pandas DataFrame''' |
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457 newVariables = [] |
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458 for var in variables: |
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459 if var in data.columns and data.dtypes[var] == dtype('O') and len(data[var].unique()) > 2: |
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460 values = data[var].unique() |
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461 if not allVariables: |
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462 values = values[:-1] |
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463 for val in values: |
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464 if val is not NaN: |
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465 newVariable = (var+'_{}'.format(val)).replace('.','').replace(' ','').replace('-','') |
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466 data[newVariable] = (data[var] == val) |
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467 newVariables.append(newVariable) |
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468 return newVariables |
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469 |
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470 def kruskalWallis(data, dependentVariable, independentVariable, plotFigure = False, filenamePrefix = None, figureFileType = 'pdf', saveLatex = False, renameVariables = lambda s: s, kwCaption = ''): |
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471 '''Studies the influence of (nominal) independent variable over the dependent variable |
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472 |
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473 Makes tests if the conditional distributions are normal |
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474 using the Shapiro-Wilk test (in which case ANOVA could be used) |
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475 Implements uses the non-parametric Kruskal Wallis test''' |
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476 tmp = data[data[independentVariable].notnull()] |
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477 independentVariableValues = sorted(tmp[independentVariable].unique().tolist()) |
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478 if len(independentVariableValues) >= 2: |
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479 if saveLatex: |
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480 out = openCheck(filenamePrefix+'-{}-{}.tex'.format(dependentVariable, independentVariable), 'w') |
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481 for x in independentVariableValues: |
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482 print('Shapiro-Wilk normality test for {} when {}={}: {} obs'.format(dependentVariable,independentVariable, x, len(tmp.loc[tmp[independentVariable] == x, dependentVariable]))) |
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483 if len(tmp.loc[tmp[independentVariable] == x, dependentVariable]) >= 3: |
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484 print(shapiro(tmp.loc[tmp[independentVariable] == x, dependentVariable])) |
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485 if plotFigure: |
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486 plt.figure() |
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487 plt.boxplot([tmp.loc[tmp[independentVariable] == x, dependentVariable] for x in independentVariableValues]) |
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488 plt.xticks(range(1,len(independentVariableValues)+1), independentVariableValues) |
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489 plt.title('{} vs {}'.format(dependentVariable, independentVariable)) |
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490 if filenamePrefix is not None: |
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491 plt.savefig(filenamePrefix+'-{}-{}.{}'.format(dependentVariable, independentVariable, figureFileType)) |
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492 table = tmp.groupby([independentVariable])[dependentVariable].describe().unstack().sort(['50%'], ascending = False) |
676 | 493 table['count'] = table['count'].astype(int) |
494 testResult = kruskal(*[tmp.loc[tmp[independentVariable] == x, dependentVariable] for x in independentVariableValues]) | |
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495 if saveLatex: |
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496 out.write('\\begin{minipage}{\\linewidth}\n' |
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497 +'\\centering\n' |
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498 +'\\captionof{table}{'+(kwCaption.format(dependentVariable, independentVariable, *testResult))+'}\n' |
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499 +table.to_latex(float_format = lambda x: '{:.3f}'.format(x)).encode('ascii')+'\n' |
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500 +'\\end{minipage}\n' |
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501 +'\\ \\vspace{0.5cm}\n') |
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502 else: |
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503 print(table) |
676 | 504 return testResult |
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505 else: |
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506 return None |
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507 |
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508 def prepareRegression(data, dependentVariable, independentVariables, maxCorrelationThreshold, correlations, maxCorrelationP, correlationFunc, stdoutText = ['Removing {} (constant: {})', 'Removing {} (correlation {} with {})', 'Removing {} (no correlation: {}, p={})'], saveFiles = False, filenamePrefix = None, latexHeader = '', latexTable = None, latexFooter=''): |
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509 '''Removes variables from candidate independent variables if |
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510 - if two independent variables are correlated (> maxCorrelationThreshold), one is removed |
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511 - if an independent variable is not correlated with the dependent variable (p>maxCorrelationP) |
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512 Returns the remaining non-correlated variables, correlated with the dependent variable |
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513 |
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514 correlationFunc is spearmanr or pearsonr from scipy.stats |
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515 text is the template to display for the two types of printout (see default): 3 elements if no saving to latex file, 8 otherwise |
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516 |
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517 TODO: pass the dummies for nominal variables and remove if all dummies are correlated, or none is correlated with the dependentvariable''' |
668
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518 result = copy(independentVariables) |
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519 table1 = '' |
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520 table2 = {} |
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521 # constant variables |
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522 for var in independentVariables: |
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523 uniqueValues = data[var].unique() |
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524 if (len(uniqueValues) == 1) or (len(uniqueValues) == 2 and uniqueValues.dtype != dtype('O') and len(data.loc[~isnan(data[var]), var].unique()) == 1): |
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525 print(stdoutText[0].format(var, uniqueValues)) |
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526 if saveFiles: |
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527 table1 += latexTable[0].format(var, *uniqueValues) |
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528 result.remove(var) |
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529 # correlated variables |
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530 for v1 in copy(result): |
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531 if v1 in correlations.index: |
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532 for v2 in copy(result): |
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533 if v2 != v1 and v2 in correlations.index: |
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534 if abs(correlations.loc[v1, v2]) > maxCorrelationThreshold: |
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535 if v1 in result and v2 in result: |
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536 if saveFiles: |
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537 table1 += latexTable[1].format(v2, v1, correlations.loc[v1, v2]) |
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538 print(stdoutText[1].format(v2, v1, correlations.loc[v1, v2])) |
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539 result.remove(v2) |
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540 # not correlated with dependent variable |
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541 table2['Correlations'] = [] |
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542 table2['Valeurs p'] = [] |
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543 for var in copy(result): |
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544 if data.dtypes[var] != dtype('O'): |
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545 cor, p = correlationFunc(data[dependentVariable], data[var]) |
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546 if p > maxCorrelationP: |
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547 if saveFiles: |
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548 table1 += latexTable[2].format(var, cor, p) |
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549 print(stdoutText[2].format(var, cor, p)) |
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550 result.remove(var) |
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551 else: |
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552 table2['Correlations'].append(cor) |
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553 table2['Valeurs p'].append(p) |
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554 |
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555 if saveFiles: |
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556 out = openCheck(filenamePrefix+'-removed-variables.tex', 'w') |
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557 out.write(latexHeader) |
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558 out.write(table1) |
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559 out.write(latexFooter) |
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560 out.close() |
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561 out = openCheck(filenamePrefix+'-correlations.html', 'w') |
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562 table2['Variables'] = [var for var in result if data.dtypes[var] != dtype('O')] |
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563 out.write(DataFrame(table2)[['Variables', 'Correlations', 'Valeurs p']].to_html(formatters = {'Correlations': lambda x: '{:.2f}'.format(x), 'Valeurs p': lambda x: '{:.3f}'.format(x)}, index = False)) |
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564 out.close() |
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565 return result |
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566 |
841 | 567 def saveDokMatrix(filename, m, lowerTriangle = False): |
840
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568 'Saves a dok_matrix using savez' |
841 | 569 if lowerTriangle: |
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570 keys = [k for k in m if k[0] > k[1]] |
841 | 571 savez(filename, shape = m.shape, keys = keys, values = [m[k[0],k[1]] for k in keys]) |
572 else: | |
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573 savez(filename, shape = m.shape, keys = list(m.keys()), values = list(m.values())) |
840
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574 |
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575 def loadDokMatrix(filename): |
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576 'Loads a dok_matrix saved using the above saveDokMatrix' |
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577 data = npload(filename) |
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578 m = dok_matrix(tuple(data['shape'])) |
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579 for k, v in zip(data['keys'], data['values']): |
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580 m[tuple(k)] = v |
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581 return m |
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582 |
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583 def aggregationFunction(funcStr, centile = 50): |
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584 '''return the numpy function corresponding to funcStr |
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585 centile can be a list of centiles to compute at once, eg [25, 50, 75] for the 3 quartiles''' |
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586 if funcStr == 'median': |
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587 return median |
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588 elif funcStr == 'mean': |
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589 return mean |
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590 elif funcStr == 'centile': |
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591 return lambda x: percentile(x, centile) |
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592 elif funcStr == '85centile': |
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593 return lambda x: percentile(x, 85) |
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594 else: |
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595 print('Unknown aggregation method: {}'.format(funcStr)) |
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596 return None |
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597 |
1058
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598 def aggregationMethods(methods, centiles = None): |
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599 aggFunctions = {} |
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600 headers = [] |
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601 for method in methods: |
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602 if method == 'centile': |
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603 aggFunctions[method] = aggregationFunction(method, centiles) |
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604 for c in centiles: |
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605 headers.append('{}{}'.format(method,c)) |
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606 else: |
1060
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607 aggFunctions[method] = aggregationFunction(method) |
1058
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608 headers.append(method) |
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609 return aggFunctions, headers |
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610 |
667
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611 ######################### |
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612 # regression analysis using statsmodels (and pandas) |
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613 ######################### |
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614 |
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615 # TODO make class for experiments? |
668
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616 # TODO add tests with public dataset downloaded from Internet (IRIS et al) |
667
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617 def modelString(experiment, dependentVariable, independentVariables): |
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618 return dependentVariable+' ~ '+' + '.join([independentVariable for independentVariable in independentVariables if experiment[independentVariable]]) |
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619 |
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620 def runModel(experiment, data, dependentVariable, independentVariables, regressionType = 'ols'): |
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621 import statsmodels.formula.api as smf |
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622 modelStr = modelString(experiment, dependentVariable, independentVariables) |
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623 if regressionType == 'ols': |
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624 model = smf.ols(modelStr, data = data) |
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625 elif regressionType == 'gls': |
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626 model = smf.gls(modelStr, data = data) |
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627 elif regressionType == 'rlm': |
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628 model = smf.rlm(modelStr, data = data) |
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629 else: |
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630 print('Unknown regression type {}. Exiting'.format(regressionType)) |
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diff
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631 import sys |
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632 sys.exit() |
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diff
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|
633 return model.fit() |
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|
634 |
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635 def runModels(experiments, data, dependentVariable, independentVariables, regressionType = 'ols'): |
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diff
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636 '''Runs several models and stores 3 statistics |
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637 adjusted R2, condition number (should be small, eg < 1000) |
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|
638 and p-value for Shapiro-Wilk test of residual normality''' |
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639 for i,experiment in experiments.iterrows(): |
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640 if experiment[independentVariables].any(): |
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641 results = runModel(experiment, data, dependentVariable, independentVariables, regressionType = 'ols') |
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642 experiments.loc[i,'r2adj'] = results.rsquared_adj |
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643 experiments.loc[i,'condNum'] = results.condition_number |
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644 experiments.loc[i, 'shapiroP'] = shapiro(results.resid)[1] |
668
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diff
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|
645 experiments.loc[i,'nobs'] = int(results.nobs) |
667
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646 return experiments |
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|
647 |
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|
648 def generateExperiments(independentVariables): |
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649 '''Generates all possible models for including or not each independent variable''' |
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650 experiments = {} |
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diff
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|
651 nIndependentVariables = len(independentVariables) |
669 | 652 if nIndependentVariables != len(set(independentVariables)): |
667
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653 print("Duplicate variables. Exiting") |
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654 import sys |
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655 sys.exit() |
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diff
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|
656 nModels = 2**nIndependentVariables |
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|
657 for i,var in enumerate(independentVariables): |
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658 pattern = [False]*(2**i)+[True]*(2**i) |
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diff
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659 experiments[var] = pattern*(2**(nIndependentVariables-i-1)) |
670
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diff
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660 experiments = DataFrame(experiments) |
667
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661 experiments['r2adj'] = 0. |
677
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676
diff
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|
662 experiments['condNum'] = NaN |
667
179b81faa1f8
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|
663 experiments['shapiroP'] = -1 |
668
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diff
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|
664 experiments['nobs'] = -1 |
667
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diff
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|
665 return experiments |
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diff
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|
666 |
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diff
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|
667 def findBestModel(data, dependentVariable, independentVariables, regressionType = 'ols', nProcesses = 1): |
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diff
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|
668 '''Generates all possible model with the independentVariables |
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|
669 and runs them, saving the results in experiments |
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diff
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|
670 with multiprocess option''' |
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671 experiments = generateExperiments(independentVariables) |
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672 nModels = len(experiments) |
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673 print("Running {} models with {} processes".format(nModels, nProcesses)) |
674
01b89182891a
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672
diff
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|
674 print("IndependentVariables: {}".format(independentVariables)) |
667
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diff
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|
675 if nProcesses == 1: |
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676 return runModels(experiments, data, dependentVariable, independentVariables, regressionType) |
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|
677 else: |
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diff
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|
678 pool = Pool(processes = nProcesses) |
670
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diff
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|
679 chunkSize = int(ceil(nModels/nProcesses)) |
667
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680 jobs = [pool.apply_async(runModels, args = (experiments[i*chunkSize:(i+1)*chunkSize], data, dependentVariable, independentVariables, regressionType)) for i in range(nProcesses)] |
670
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diff
changeset
|
681 return concat([job.get() for job in jobs]) |
667
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diff
changeset
|
682 |
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diff
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|
683 def findBestModelFwd(data, dependentVariable, independentVariables, modelFunc, experiments = None): |
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diff
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|
684 '''Forward search for best model (based on adjusted R2) |
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diff
changeset
|
685 Randomly starting with one variable and adding randomly variables |
179b81faa1f8
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diff
changeset
|
686 if they improve the model |
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665
diff
changeset
|
687 |
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diff
changeset
|
688 The results are added to experiments if provided as argument |
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diff
changeset
|
689 Storing in experiment relies on the index being the number equal |
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diff
changeset
|
690 to the binary code derived from the independent variables''' |
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|
691 if experiments is None: |
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692 experiments = generateExperiments(independentVariables) |
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diff
changeset
|
693 nIndependentVariables = len(independentVariables) |
997
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990
diff
changeset
|
694 permutation = nppermutation(list(range(nIndependentVariables))) |
667
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diff
changeset
|
695 variableMapping = {j: independentVariables[i] for i,j in enumerate(permutation)} |
997
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diff
changeset
|
696 print('Tested variables '+', '.join([variableMapping[i] for i in range(nIndependentVariables)])) |
667
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|
697 bestModel = [False]*nIndependentVariables |
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diff
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|
698 currentVarNum = 0 |
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diff
changeset
|
699 currentR2Adj = 0. |
997
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diff
changeset
|
700 for currentVarNum in range(nIndependentVariables): |
667
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diff
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|
701 currentModel = [i for i in bestModel] |
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added regression analysis functions
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
665
diff
changeset
|
702 currentModel[currentVarNum] = True |
997
4f3387a242a1
updated utils to python 3
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
990
diff
changeset
|
703 rowIdx = sum([0]+[2**i for i in range(nIndependentVariables) if currentModel[permutation[i]]]) |
4f3387a242a1
updated utils to python 3
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parents:
990
diff
changeset
|
704 #print currentVarNum, sum(currentModel), ', '.join([independentVariables[i] for i in range(nIndependentVariables) if currentModel[permutation[i]]]) |
667
179b81faa1f8
added regression analysis functions
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
665
diff
changeset
|
705 if experiments.loc[rowIdx, 'shapiroP'] < 0: |
179b81faa1f8
added regression analysis functions
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
665
diff
changeset
|
706 modelStr = modelString(experiments.loc[rowIdx], dependentVariable, independentVariables) |
179b81faa1f8
added regression analysis functions
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
665
diff
changeset
|
707 model = modelFunc(modelStr, data = data) |
179b81faa1f8
added regression analysis functions
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parents:
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diff
changeset
|
708 results = model.fit() |
179b81faa1f8
added regression analysis functions
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parents:
665
diff
changeset
|
709 experiments.loc[rowIdx, 'r2adj'] = results.rsquared_adj |
179b81faa1f8
added regression analysis functions
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
665
diff
changeset
|
710 experiments.loc[rowIdx, 'condNum'] = results.condition_number |
179b81faa1f8
added regression analysis functions
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
665
diff
changeset
|
711 experiments.loc[rowIdx, 'shapiroP'] = shapiro(results.resid)[1] |
668
f8dcf483b296
code to prepare regression variables (remove correlated variables) and record dataset size in experimnets
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
667
diff
changeset
|
712 experiments.loc[rowIdx, 'nobs'] = int(results.nobs) |
667
179b81faa1f8
added regression analysis functions
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
665
diff
changeset
|
713 if currentR2Adj < experiments.loc[rowIdx, 'r2adj']: |
179b81faa1f8
added regression analysis functions
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
665
diff
changeset
|
714 currentR2Adj = experiments.loc[rowIdx, 'r2adj'] |
179b81faa1f8
added regression analysis functions
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
665
diff
changeset
|
715 bestModel[currentVarNum] = True |
179b81faa1f8
added regression analysis functions
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parents:
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diff
changeset
|
716 return experiments |
179b81faa1f8
added regression analysis functions
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
665
diff
changeset
|
717 |
677
ae07c7b4cf87
update to utils for pavement results
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
676
diff
changeset
|
718 def displayModelResults(results, model = None, plotFigures = True, filenamePrefix = None, figureFileType = 'pdf', text = {'title-shapiro': 'Shapiro-Wilk normality test for residuals: {:.2f} (p={:.3f})', 'true-predicted.xlabel': 'Predicted values', 'true-predicted.ylabel': 'True values', 'residuals-predicted.xlabel': 'Predicted values', 'residuals-predicted.ylabel': 'Residuals'}): |
667
179b81faa1f8
added regression analysis functions
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parents:
665
diff
changeset
|
719 import statsmodels.api as sm |
677
ae07c7b4cf87
update to utils for pavement results
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parents:
676
diff
changeset
|
720 '''Displays some model results |
ae07c7b4cf87
update to utils for pavement results
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parents:
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diff
changeset
|
721 |
ae07c7b4cf87
update to utils for pavement results
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parents:
676
diff
changeset
|
722 3 graphics, true-predicted, residuals-predicted, ''' |
676 | 723 print(results.summary()) |
677
ae07c7b4cf87
update to utils for pavement results
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
676
diff
changeset
|
724 shapiroResult = shapiro(results.resid) |
ae07c7b4cf87
update to utils for pavement results
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
676
diff
changeset
|
725 print(shapiroResult) |
676 | 726 if plotFigures: |
677
ae07c7b4cf87
update to utils for pavement results
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
676
diff
changeset
|
727 fig = plt.figure(figsize=(7,6.3*(2+int(model is not None)))) |
676 | 728 if model is not None: |
677
ae07c7b4cf87
update to utils for pavement results
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
676
diff
changeset
|
729 ax = fig.add_subplot(3,1,1) |
676 | 730 plt.plot(results.predict(), model.endog, 'x') |
731 x=plt.xlim() | |
732 y=plt.ylim() | |
733 plt.plot([max(x[0], y[0]), min(x[1], y[1])], [max(x[0], y[0]), min(x[1], y[1])], 'r') | |
677
ae07c7b4cf87
update to utils for pavement results
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
676
diff
changeset
|
734 #plt.axis('equal') |
ae07c7b4cf87
update to utils for pavement results
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
676
diff
changeset
|
735 if text is not None: |
ae07c7b4cf87
update to utils for pavement results
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
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diff
changeset
|
736 plt.title(text['title-shapiro'].format(*shapiroResult)) |
ae07c7b4cf87
update to utils for pavement results
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
676
diff
changeset
|
737 #plt.title(text['true-predicted.title']) |
ae07c7b4cf87
update to utils for pavement results
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
676
diff
changeset
|
738 plt.xlabel(text['true-predicted.xlabel']) |
ae07c7b4cf87
update to utils for pavement results
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
676
diff
changeset
|
739 plt.ylabel(text['true-predicted.ylabel']) |
ae07c7b4cf87
update to utils for pavement results
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
676
diff
changeset
|
740 fig.add_subplot(3,1,2, sharex = ax) |
ae07c7b4cf87
update to utils for pavement results
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
676
diff
changeset
|
741 plt.plot(results.predict(), results.resid, 'x') |
ae07c7b4cf87
update to utils for pavement results
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
676
diff
changeset
|
742 nextSubplotNum = 3 |
ae07c7b4cf87
update to utils for pavement results
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
676
diff
changeset
|
743 else: |
ae07c7b4cf87
update to utils for pavement results
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
676
diff
changeset
|
744 fig.add_subplot(2,1,1) |
ae07c7b4cf87
update to utils for pavement results
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
676
diff
changeset
|
745 plt.plot(results.predict(), results.resid, 'x') |
ae07c7b4cf87
update to utils for pavement results
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
676
diff
changeset
|
746 nextSubplotNum = 2 |
ae07c7b4cf87
update to utils for pavement results
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
676
diff
changeset
|
747 if text is not None: |
ae07c7b4cf87
update to utils for pavement results
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
676
diff
changeset
|
748 if model is None: |
ae07c7b4cf87
update to utils for pavement results
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
676
diff
changeset
|
749 plt.title(text['title-shapiro'].format(*shapiroResult)) |
ae07c7b4cf87
update to utils for pavement results
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
676
diff
changeset
|
750 plt.xlabel(text['residuals-predicted.xlabel']) |
ae07c7b4cf87
update to utils for pavement results
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
676
diff
changeset
|
751 plt.ylabel(text['residuals-predicted.ylabel']) |
ae07c7b4cf87
update to utils for pavement results
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
676
diff
changeset
|
752 qqAx = fig.add_subplot(nextSubplotNum,1,nextSubplotNum) |
ae07c7b4cf87
update to utils for pavement results
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
676
diff
changeset
|
753 sm.qqplot(results.resid, fit = True, line = '45', ax = qqAx) |
ae07c7b4cf87
update to utils for pavement results
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
676
diff
changeset
|
754 plt.axis('equal') |
ae07c7b4cf87
update to utils for pavement results
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
676
diff
changeset
|
755 if text is not None and 'qqplot.xlabel' in text: |
ae07c7b4cf87
update to utils for pavement results
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
676
diff
changeset
|
756 plt.xlabel(text['qqplot.xlabel']) |
ae07c7b4cf87
update to utils for pavement results
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
676
diff
changeset
|
757 plt.ylabel(text['qqplot.ylabel']) |
ae07c7b4cf87
update to utils for pavement results
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
676
diff
changeset
|
758 plt.tight_layout() |
676 | 759 if filenamePrefix is not None: |
677
ae07c7b4cf87
update to utils for pavement results
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
676
diff
changeset
|
760 out = openCheck(filenamePrefix+'-coefficients.html', 'w') |
ae07c7b4cf87
update to utils for pavement results
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
676
diff
changeset
|
761 out.write(results.summary().as_html()) |
ae07c7b4cf87
update to utils for pavement results
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
676
diff
changeset
|
762 plt.savefig(filenamePrefix+'-model-results.'+figureFileType) |
667
179b81faa1f8
added regression analysis functions
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
665
diff
changeset
|
763 |
27
44689029a86f
updated segmentIntersection and other
Nicolas Saunier <nico@confins.net>
parents:
24
diff
changeset
|
764 ######################### |
455
abe0b2347d4c
added most common utility function
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
434
diff
changeset
|
765 # iterable section |
abe0b2347d4c
added most common utility function
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
434
diff
changeset
|
766 ######################### |
abe0b2347d4c
added most common utility function
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
434
diff
changeset
|
767 |
1034
4069d8545922
updated mostCommong function
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
1031
diff
changeset
|
768 def mostCommon(l): |
456 | 769 '''Returns the most frequent element in a iterable |
1034
4069d8545922
updated mostCommong function
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
1031
diff
changeset
|
770 The element must be hashable |
456 | 771 |
1034
4069d8545922
updated mostCommong function
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
1031
diff
changeset
|
772 new version from https://stackoverflow.com/questions/41612368/find-most-common-element |
4069d8545922
updated mostCommong function
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
1031
diff
changeset
|
773 previous version from from http://stackoverflow.com/questions/1518522/python-most-common-element-in-a-list''' |
4069d8545922
updated mostCommong function
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
1031
diff
changeset
|
774 return Counter(l).most_common(1)[0][0] |
4069d8545922
updated mostCommong function
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
1031
diff
changeset
|
775 |
455
abe0b2347d4c
added most common utility function
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parents:
434
diff
changeset
|
776 ######################### |
370
97e8fa0ee9a1
work in progress for complete alignment
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parents:
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diff
changeset
|
777 # sequence section |
97e8fa0ee9a1
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parents:
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diff
changeset
|
778 ######################### |
97e8fa0ee9a1
work in progress for complete alignment
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parents:
369
diff
changeset
|
779 |
665
15e244d2a1b5
corrected bug with circular import for VideoFilenameAddable, moved to base module
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
659
diff
changeset
|
780 class LCSS(object): |
370
97e8fa0ee9a1
work in progress for complete alignment
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
369
diff
changeset
|
781 '''Class that keeps the LCSS parameters |
686
cdee6a3a47b4
allowing alternate database and filename for classify-objects
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
680
diff
changeset
|
782 and puts together the various computations |
cdee6a3a47b4
allowing alternate database and filename for classify-objects
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
680
diff
changeset
|
783 |
cdee6a3a47b4
allowing alternate database and filename for classify-objects
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
680
diff
changeset
|
784 the methods with names starting with _ are not to be shadowed |
cdee6a3a47b4
allowing alternate database and filename for classify-objects
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
680
diff
changeset
|
785 in child classes, who will shadow the other methods, |
cdee6a3a47b4
allowing alternate database and filename for classify-objects
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
680
diff
changeset
|
786 ie compute and computeXX methods''' |
689
9990ef119bce
added version of LCSS with cdist computations
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
687
diff
changeset
|
787 def __init__(self, similarityFunc = None, metric = None, epsilon = None, delta = float('inf'), aligned = False, lengthFunc = min): |
9990ef119bce
added version of LCSS with cdist computations
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
687
diff
changeset
|
788 '''One should provide either a similarity function |
9990ef119bce
added version of LCSS with cdist computations
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
687
diff
changeset
|
789 that indicates (return bool) whether elements in the compares lists are similar |
9990ef119bce
added version of LCSS with cdist computations
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
687
diff
changeset
|
790 |
9990ef119bce
added version of LCSS with cdist computations
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
687
diff
changeset
|
791 eg distance(p1, p2) < epsilon |
9990ef119bce
added version of LCSS with cdist computations
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
687
diff
changeset
|
792 |
9990ef119bce
added version of LCSS with cdist computations
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
687
diff
changeset
|
793 or a type of metric usable in scipy.spatial.distance.cdist with an epsilon''' |
9990ef119bce
added version of LCSS with cdist computations
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
687
diff
changeset
|
794 if similarityFunc is None and metric is None: |
9990ef119bce
added version of LCSS with cdist computations
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
687
diff
changeset
|
795 print("No way to compute LCSS, similarityFunc and metric are None. Exiting") |
9990ef119bce
added version of LCSS with cdist computations
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
687
diff
changeset
|
796 import sys |
9990ef119bce
added version of LCSS with cdist computations
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
687
diff
changeset
|
797 sys.exit() |
9990ef119bce
added version of LCSS with cdist computations
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
687
diff
changeset
|
798 elif metric is not None and epsilon is None: |
9990ef119bce
added version of LCSS with cdist computations
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
687
diff
changeset
|
799 print("Please provide a value for epsilon if using a cdist metric. Exiting") |
9990ef119bce
added version of LCSS with cdist computations
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
687
diff
changeset
|
800 import sys |
9990ef119bce
added version of LCSS with cdist computations
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
687
diff
changeset
|
801 sys.exit() |
9990ef119bce
added version of LCSS with cdist computations
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
687
diff
changeset
|
802 else: |
741 | 803 if similarityFunc is None and metric is not None and not isinf(delta): |
737
fb60b54e1041
added warning for finite delta
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
733
diff
changeset
|
804 print('Warning: you are using a cdist metric and a finite delta, which will make probably computation slower than using the equivalent similarityFunc (since all pairwise distances will be computed by cdist).') |
689
9990ef119bce
added version of LCSS with cdist computations
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
687
diff
changeset
|
805 self.similarityFunc = similarityFunc |
9990ef119bce
added version of LCSS with cdist computations
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
687
diff
changeset
|
806 self.metric = metric |
9990ef119bce
added version of LCSS with cdist computations
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
687
diff
changeset
|
807 self.epsilon = epsilon |
9990ef119bce
added version of LCSS with cdist computations
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
687
diff
changeset
|
808 self.aligned = aligned |
9990ef119bce
added version of LCSS with cdist computations
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
687
diff
changeset
|
809 self.delta = delta |
9990ef119bce
added version of LCSS with cdist computations
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
687
diff
changeset
|
810 self.lengthFunc = lengthFunc |
9990ef119bce
added version of LCSS with cdist computations
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
687
diff
changeset
|
811 self.subSequenceIndices = [(0,0)] |
370
97e8fa0ee9a1
work in progress for complete alignment
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
369
diff
changeset
|
812 |
373
d0b86ed50f32
work in progress on LCSS
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
372
diff
changeset
|
813 def similarities(self, l1, l2, jshift=0): |
370
97e8fa0ee9a1
work in progress for complete alignment
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
369
diff
changeset
|
814 n1 = len(l1) |
97e8fa0ee9a1
work in progress for complete alignment
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diff
changeset
|
815 n2 = len(l2) |
97e8fa0ee9a1
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
369
diff
changeset
|
816 self.similarityTable = zeros((n1+1,n2+1), dtype = npint) |
689
9990ef119bce
added version of LCSS with cdist computations
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
687
diff
changeset
|
817 if self.similarityFunc is not None: |
997
4f3387a242a1
updated utils to python 3
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
990
diff
changeset
|
818 for i in range(1,n1+1): |
4f3387a242a1
updated utils to python 3
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
990
diff
changeset
|
819 for j in range(max(1,i-jshift-self.delta),min(n2,i-jshift+self.delta)+1): |
689
9990ef119bce
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diff
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|
820 if self.similarityFunc(l1[i-1], l2[j-1]): |
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added version of LCSS with cdist computations
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parents:
687
diff
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|
821 self.similarityTable[i,j] = self.similarityTable[i-1,j-1]+1 |
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diff
changeset
|
822 else: |
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parents:
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diff
changeset
|
823 self.similarityTable[i,j] = max(self.similarityTable[i-1,j], self.similarityTable[i,j-1]) |
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diff
changeset
|
824 elif self.metric is not None: |
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diff
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|
825 similarElements = distance.cdist(l1, l2, self.metric) <= self.epsilon |
997
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
990
diff
changeset
|
826 for i in range(1,n1+1): |
4f3387a242a1
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
990
diff
changeset
|
827 for j in range(max(1,i-jshift-self.delta),min(n2,i-jshift+self.delta)+1): |
689
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parents:
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diff
changeset
|
828 if similarElements[i-1, j-1]: |
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diff
changeset
|
829 self.similarityTable[i,j] = self.similarityTable[i-1,j-1]+1 |
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diff
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|
830 else: |
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diff
changeset
|
831 self.similarityTable[i,j] = max(self.similarityTable[i-1,j], self.similarityTable[i,j-1]) |
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diff
changeset
|
832 |
370
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|
833 |
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|
834 def subSequence(self, i, j): |
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diff
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|
835 '''Returns the subsequence of two sequences |
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|
836 http://en.wikipedia.org/wiki/Longest_common_subsequence_problem''' |
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|
837 if i == 0 or j == 0: |
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|
838 return [] |
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|
839 elif self.similarityTable[i][j] == self.similarityTable[i][j-1]: |
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840 return self.subSequence(i, j-1) |
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841 elif self.similarityTable[i][j] == self.similarityTable[i-1][j]: |
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842 return self.subSequence(i-1, j) |
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|
843 else: |
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|
844 return self.subSequence(i-1, j-1) + [(i-1,j-1)] |
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|
845 |
373
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|
846 def _compute(self, _l1, _l2, computeSubSequence = False): |
370
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|
847 '''returns the longest common subsequence similarity |
689
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diff
changeset
|
848 l1 and l2 should be the right format |
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added version of LCSS with cdist computations
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diff
changeset
|
849 eg list of tuple points for cdist |
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diff
changeset
|
850 or elements that can be compare using similarityFunc |
370
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|
851 |
607 | 852 if aligned, returns the best matching if using a finite delta by shifting the series alignments |
370
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|
853 ''' |
372
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|
854 if len(_l2) < len(_l1): # l1 is the shortest |
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|
855 l1 = _l2 |
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|
856 l2 = _l1 |
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|
857 revertIndices = True |
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diff
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|
858 else: |
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diff
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|
859 l1 = _l1 |
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|
860 l2 = _l2 |
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|
861 revertIndices = False |
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diff
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|
862 n1 = len(l1) |
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|
863 n2 = len(l2) |
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diff
changeset
|
864 |
370
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diff
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|
865 if self.aligned: |
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diff
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|
866 lcssValues = {} |
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|
867 similarityTables = {} |
997
4f3387a242a1
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parents:
990
diff
changeset
|
868 for i in range(-n2-self.delta+1, n1+self.delta): # interval such that [i-shift-delta, i-shift+delta] is never empty, which happens when i-shift+delta < 1 or when i-shift-delta > n2 |
373
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|
869 self.similarities(l1, l2, i) |
d0b86ed50f32
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|
870 lcssValues[i] = self.similarityTable.max() |
370
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|
871 similarityTables[i] = self.similarityTable |
374
a7af3519687e
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373
diff
changeset
|
872 #print self.similarityTable |
521
3707eeb20f25
changed argMaxDict name to argmaxDict
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
518
diff
changeset
|
873 alignmentShift = argmaxDict(lcssValues) # ideally get the medium alignment shift, the one that minimizes distance |
389
6d26dcc7bba0
modifications to compute alignment for None indicators
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parents:
381
diff
changeset
|
874 self.similarityTable = similarityTables[alignmentShift] |
372
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371
diff
changeset
|
875 else: |
389
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
381
diff
changeset
|
876 alignmentShift = 0 |
372
349eb1e09f45
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371
diff
changeset
|
877 self.similarities(l1, l2) |
373
d0b86ed50f32
work in progress on LCSS
Nicolas Saunier <nicolas.saunier@polymtl.ca>
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372
diff
changeset
|
878 |
374
a7af3519687e
finished implementation of aligned LCSS with matching sequence decoded
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parents:
373
diff
changeset
|
879 # threshold values for the useful part of the similarity table are n2-n1-delta and n1-n2-delta |
389
6d26dcc7bba0
modifications to compute alignment for None indicators
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
381
diff
changeset
|
880 self.similarityTable = self.similarityTable[:min(n1, n2+alignmentShift+self.delta)+1, :min(n2, n1-alignmentShift+self.delta)+1] |
373
d0b86ed50f32
work in progress on LCSS
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
372
diff
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|
881 |
372
349eb1e09f45
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
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371
diff
changeset
|
882 if computeSubSequence: |
349eb1e09f45
Cleaned the methods/functions indicating if a point is in a polygon
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parents:
371
diff
changeset
|
883 self.subSequenceIndices = self.subSequence(self.similarityTable.shape[0]-1, self.similarityTable.shape[1]-1) |
371
924e38c9f70e
work in progress
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
370
diff
changeset
|
884 if revertIndices: |
374
a7af3519687e
finished implementation of aligned LCSS with matching sequence decoded
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parents:
373
diff
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|
885 self.subSequenceIndices = [(j,i) for i,j in self.subSequenceIndices] |
372
349eb1e09f45
Cleaned the methods/functions indicating if a point is in a polygon
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
371
diff
changeset
|
886 return self.similarityTable[-1,-1] |
370
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
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369
diff
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|
887 |
97e8fa0ee9a1
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
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369
diff
changeset
|
888 def compute(self, l1, l2, computeSubSequence = False): |
97e8fa0ee9a1
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369
diff
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|
889 '''get methods are to be shadowed in child classes ''' |
97e8fa0ee9a1
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369
diff
changeset
|
890 return self._compute(l1, l2, computeSubSequence) |
97e8fa0ee9a1
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
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369
diff
changeset
|
891 |
375
2ea8584aa80a
making indicator LCSS work
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
374
diff
changeset
|
892 def computeAlignment(self): |
374
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373
diff
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|
893 return mean([j-i for i,j in self.subSequenceIndices]) |
370
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369
diff
changeset
|
894 |
376
2e6b8610bcaa
work on indicator similarity
Nicolas Saunier <nicolas.saunier@polymtl.ca>
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375
diff
changeset
|
895 def _computeNormalized(self, l1, l2, computeSubSequence = False): |
370
97e8fa0ee9a1
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369
diff
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|
896 ''' compute the normalized LCSS |
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369
diff
changeset
|
897 ie, the LCSS divided by the min or mean of the indicator lengths (using lengthFunc) |
97e8fa0ee9a1
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369
diff
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|
898 lengthFunc = lambda x,y:float(x,y)/2''' |
376
2e6b8610bcaa
work on indicator similarity
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375
diff
changeset
|
899 return float(self._compute(l1, l2, computeSubSequence))/self.lengthFunc(len(l1), len(l2)) |
370
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369
diff
changeset
|
900 |
376
2e6b8610bcaa
work on indicator similarity
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
375
diff
changeset
|
901 def computeNormalized(self, l1, l2, computeSubSequence = False): |
2e6b8610bcaa
work on indicator similarity
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375
diff
changeset
|
902 return self._computeNormalized(l1, l2, computeSubSequence) |
370
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369
diff
changeset
|
903 |
376
2e6b8610bcaa
work on indicator similarity
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parents:
375
diff
changeset
|
904 def _computeDistance(self, l1, l2, computeSubSequence = False): |
370
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diff
changeset
|
905 ''' compute the LCSS distance''' |
376
2e6b8610bcaa
work on indicator similarity
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375
diff
changeset
|
906 return 1-self._computeNormalized(l1, l2, computeSubSequence) |
370
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diff
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|
907 |
376
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work on indicator similarity
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parents:
375
diff
changeset
|
908 def computeDistance(self, l1, l2, computeSubSequence = False): |
2e6b8610bcaa
work on indicator similarity
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375
diff
changeset
|
909 return self._computeDistance(l1, l2, computeSubSequence) |
370
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diff
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|
910 |
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369
diff
changeset
|
911 ######################### |
45
74d2de078baf
added colors, linestyles and markers to pick from
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parents:
42
diff
changeset
|
912 # plotting section |
74d2de078baf
added colors, linestyles and markers to pick from
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parents:
42
diff
changeset
|
913 ######################### |
74d2de078baf
added colors, linestyles and markers to pick from
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42
diff
changeset
|
914 |
940
d8ab183a7351
verified motion prediction with prototypes at constant speed (test needed)
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
876
diff
changeset
|
915 def plotPolygon(poly, options = '', **kwargs): |
332
a6ca86107f27
reorganized utils module
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parents:
324
diff
changeset
|
916 'Plots shapely polygon poly' |
940
d8ab183a7351
verified motion prediction with prototypes at constant speed (test needed)
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
876
diff
changeset
|
917 x,y = poly.exterior.xy |
1029
c6cf75a2ed08
reorganization of imports
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
1028
diff
changeset
|
918 plt.plot(x, y, options, **kwargs) |
332
a6ca86107f27
reorganized utils module
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
324
diff
changeset
|
919 |
324 | 920 def stepPlot(X, firstX, lastX, initialCount = 0, increment = 1): |
921 '''for each value in X, increment by increment the initial count | |
297
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adding function to generate step plots (for cumulative number of vehicles)
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286
diff
changeset
|
922 returns the lists that can be plotted |
324 | 923 to obtain a step plot increasing by one for each value in x, from first to last value |
924 firstX and lastX should be respectively smaller and larger than all elements in X''' | |
297
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diff
changeset
|
925 |
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286
diff
changeset
|
926 sortedX = [] |
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diff
changeset
|
927 counts = [initialCount] |
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diff
changeset
|
928 for x in sorted(X): |
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diff
changeset
|
929 sortedX += [x,x] |
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diff
changeset
|
930 counts.append(counts[-1]) |
324 | 931 counts.append(counts[-1]+increment) |
297
f6f423e25c7f
adding function to generate step plots (for cumulative number of vehicles)
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
286
diff
changeset
|
932 counts.append(counts[-1]) |
f6f423e25c7f
adding function to generate step plots (for cumulative number of vehicles)
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
286
diff
changeset
|
933 return [firstX]+sortedX+[lastX], counts |
f6f423e25c7f
adding function to generate step plots (for cumulative number of vehicles)
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
286
diff
changeset
|
934 |
665
15e244d2a1b5
corrected bug with circular import for VideoFilenameAddable, moved to base module
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
659
diff
changeset
|
935 class PlottingPropertyValues(object): |
45
74d2de078baf
added colors, linestyles and markers to pick from
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
42
diff
changeset
|
936 def __init__(self, values): |
74d2de078baf
added colors, linestyles and markers to pick from
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
42
diff
changeset
|
937 self.values = values |
74d2de078baf
added colors, linestyles and markers to pick from
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
42
diff
changeset
|
938 |
116
2bf5b76320c0
moved intersection plotting and added markers for scatter plots
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
115
diff
changeset
|
939 def __getitem__(self, i): |
45
74d2de078baf
added colors, linestyles and markers to pick from
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
42
diff
changeset
|
940 return self.values[i%len(self.values)] |
74d2de078baf
added colors, linestyles and markers to pick from
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
42
diff
changeset
|
941 |
74d2de078baf
added colors, linestyles and markers to pick from
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
42
diff
changeset
|
942 markers = PlottingPropertyValues(['+', '*', ',', '.', 'x', 'D', 's', 'o']) |
116
2bf5b76320c0
moved intersection plotting and added markers for scatter plots
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
115
diff
changeset
|
943 scatterMarkers = PlottingPropertyValues(['s','o','^','>','v','<','d','p','h','8','+','x']) |
45
74d2de078baf
added colors, linestyles and markers to pick from
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
42
diff
changeset
|
944 |
74d2de078baf
added colors, linestyles and markers to pick from
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
42
diff
changeset
|
945 linestyles = PlottingPropertyValues(['-', '--', '-.', ':']) |
74d2de078baf
added colors, linestyles and markers to pick from
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
42
diff
changeset
|
946 |
74d2de078baf
added colors, linestyles and markers to pick from
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
42
diff
changeset
|
947 colors = PlottingPropertyValues('brgmyck') # 'w' |
74d2de078baf
added colors, linestyles and markers to pick from
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
42
diff
changeset
|
948 |
990 | 949 def monochromeCycler(withMarker = False): |
950 from cycler import cycler | |
951 if withMarker: | |
952 monochrome = (cycler('color', ['k']) * cycler('linestyle', ['-', '--', ':', '-.']) * cycler('marker', ['^',',', '.'])) | |
953 else: | |
954 monochrome = (cycler('color', ['k']) * cycler('linestyle', ['-', '--', ':', '-.'])) | |
955 plt.rc('axes', prop_cycle=monochrome) | |
956 | |
115
550556378466
added functionalities to indicator maps
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
86
diff
changeset
|
957 def plotIndicatorMap(indicatorMap, squareSize, masked = True, defaultValue=-1): |
997
4f3387a242a1
updated utils to python 3
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
990
diff
changeset
|
958 coords = array(list(indicatorMap.keys())) |
65
75cf537b8d88
moved and generalized map making functions to the library
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
48
diff
changeset
|
959 minX = min(coords[:,0]) |
75cf537b8d88
moved and generalized map making functions to the library
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
48
diff
changeset
|
960 minY = min(coords[:,1]) |
75cf537b8d88
moved and generalized map making functions to the library
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
48
diff
changeset
|
961 X = arange(minX, max(coords[:,0])+1.1)*squareSize |
75cf537b8d88
moved and generalized map making functions to the library
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
48
diff
changeset
|
962 Y = arange(minY, max(coords[:,1])+1.1)*squareSize |
115
550556378466
added functionalities to indicator maps
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
86
diff
changeset
|
963 C = defaultValue*ones((len(Y), len(X))) |
997
4f3387a242a1
updated utils to python 3
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
990
diff
changeset
|
964 for k,v in indicatorMap.items(): |
65
75cf537b8d88
moved and generalized map making functions to the library
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
48
diff
changeset
|
965 C[k[1]-minY,k[0]-minX] = v |
115
550556378466
added functionalities to indicator maps
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
86
diff
changeset
|
966 if masked: |
1029
c6cf75a2ed08
reorganization of imports
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
1028
diff
changeset
|
967 plt.pcolor(X, Y, ma.masked_where(C==defaultValue,C)) |
115
550556378466
added functionalities to indicator maps
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
86
diff
changeset
|
968 else: |
1029
c6cf75a2ed08
reorganization of imports
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
1028
diff
changeset
|
969 plt.pcolor(X, Y, C) |
65
75cf537b8d88
moved and generalized map making functions to the library
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
48
diff
changeset
|
970 |
45
74d2de078baf
added colors, linestyles and markers to pick from
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
42
diff
changeset
|
971 ######################### |
637
c9a0b72979fd
added function to get canadian public weather data
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
615
diff
changeset
|
972 # Data download |
c9a0b72979fd
added function to get canadian public weather data
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
615
diff
changeset
|
973 ######################### |
c9a0b72979fd
added function to get canadian public weather data
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
615
diff
changeset
|
974 |
c9a0b72979fd
added function to get canadian public weather data
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
615
diff
changeset
|
975 def downloadECWeather(stationID, years, months = [], outputDirectoryname = '.', english = True): |
c9a0b72979fd
added function to get canadian public weather data
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
615
diff
changeset
|
976 '''Downloads monthly weather data from Environment Canada |
c9a0b72979fd
added function to get canadian public weather data
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
615
diff
changeset
|
977 If month is provided (number 1 to 12), it means hourly data for the whole month |
c9a0b72979fd
added function to get canadian public weather data
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
615
diff
changeset
|
978 Otherwise, means the data for each day, for the whole year |
c9a0b72979fd
added function to get canadian public weather data
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
615
diff
changeset
|
979 |
c9a0b72979fd
added function to get canadian public weather data
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
615
diff
changeset
|
980 Example: MONTREAL MCTAVISH 10761 |
c9a0b72979fd
added function to get canadian public weather data
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
615
diff
changeset
|
981 MONTREALPIERRE ELLIOTT TRUDEAU INTL A 5415 |
856
e310577cc0b8
updated function (url) for weather data
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
855
diff
changeset
|
982 see ftp://client_climate@ftp.tor.ec.gc.ca/Pub/Get_More_Data_Plus_de_donnees/Station%20Inventory%20EN.csv |
637
c9a0b72979fd
added function to get canadian public weather data
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
615
diff
changeset
|
983 |
c9a0b72979fd
added function to get canadian public weather data
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
615
diff
changeset
|
984 To get daily data for 2010 and 2011, downloadECWeather(10761, [2010,2011], [], '/tmp') |
973 | 985 To get hourly data for 2009 and 2012, January, March and October, downloadECWeather(10761, [2009,2012], [1,3,10], '/tmp') |
986 | |
987 for annee in `seq 2016 2017`;do wget --content-disposition "http://climat.meteo.gc.ca/climate_data/bulk_data_f.html?format=csv&stationID=10761&Year=${annee}&timeframe=2&submit=++T%C3%A9l%C3%A9charger+%0D%0Ades+donn%C3%A9es" ;done | |
988 for annee in `seq 2016 2017`;do for mois in `seq 1 12`;do wget --content-disposition "http://climat.meteo.gc.ca/climate_data/bulk_data_f.html?format=csv&stationID=10761&Year=${annee}&Month=${mois}&timeframe=1&submit=++T%C3%A9l%C3%A9charger+%0D%0Ades+donn%C3%A9es" ;done;done | |
989 ''' | |
997
4f3387a242a1
updated utils to python 3
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
990
diff
changeset
|
990 import urllib.request |
637
c9a0b72979fd
added function to get canadian public weather data
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
615
diff
changeset
|
991 if english: |
c9a0b72979fd
added function to get canadian public weather data
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
615
diff
changeset
|
992 language = 'e' |
c9a0b72979fd
added function to get canadian public weather data
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
615
diff
changeset
|
993 else: |
c9a0b72979fd
added function to get canadian public weather data
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
615
diff
changeset
|
994 language = 'f' |
c9a0b72979fd
added function to get canadian public weather data
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
615
diff
changeset
|
995 if len(months) == 0: |
c9a0b72979fd
added function to get canadian public weather data
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
615
diff
changeset
|
996 timeFrame = 2 |
c9a0b72979fd
added function to get canadian public weather data
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
615
diff
changeset
|
997 months = [1] |
c9a0b72979fd
added function to get canadian public weather data
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
615
diff
changeset
|
998 else: |
c9a0b72979fd
added function to get canadian public weather data
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
615
diff
changeset
|
999 timeFrame = 1 |
c9a0b72979fd
added function to get canadian public weather data
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
615
diff
changeset
|
1000 |
c9a0b72979fd
added function to get canadian public weather data
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
615
diff
changeset
|
1001 for year in years: |
c9a0b72979fd
added function to get canadian public weather data
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
615
diff
changeset
|
1002 for month in months: |
c9a0b72979fd
added function to get canadian public weather data
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
615
diff
changeset
|
1003 outFilename = '{}/{}-{}'.format(outputDirectoryname, stationID, year) |
c9a0b72979fd
added function to get canadian public weather data
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
615
diff
changeset
|
1004 if timeFrame == 1: |
c9a0b72979fd
added function to get canadian public weather data
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
615
diff
changeset
|
1005 outFilename += '-{}-hourly'.format(month) |
c9a0b72979fd
added function to get canadian public weather data
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
615
diff
changeset
|
1006 else: |
c9a0b72979fd
added function to get canadian public weather data
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
615
diff
changeset
|
1007 outFilename += '-daily' |
c9a0b72979fd
added function to get canadian public weather data
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
615
diff
changeset
|
1008 outFilename += '.csv' |
997
4f3387a242a1
updated utils to python 3
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
990
diff
changeset
|
1009 url = urllib.request.urlretrieve('http://climate.weather.gc.ca/climate_data/bulk_data_{}.html?format=csv&stationID={}&Year={}&Month={}&Day=1&timeframe={}&submit=Download+Data'.format(language, stationID, year, month, timeFrame), outFilename) |
637
c9a0b72979fd
added function to get canadian public weather data
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
615
diff
changeset
|
1010 |
c9a0b72979fd
added function to get canadian public weather data
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
615
diff
changeset
|
1011 ######################### |
c9a0b72979fd
added function to get canadian public weather data
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
615
diff
changeset
|
1012 # File I/O |
27
44689029a86f
updated segmentIntersection and other
Nicolas Saunier <nico@confins.net>
parents:
24
diff
changeset
|
1013 ######################### |
24
6fb59cfb201e
first version of segmentIntersection
Nicolas Saunier <nico@confins.net>
parents:
19
diff
changeset
|
1014 |
0
aed8eb63cdde
initial commit with non-functional python code for NGSIM
Nicolas Saunier <nico@confins.net>
parents:
diff
changeset
|
1015 def removeExtension(filename, delimiter = '.'): |
31
c000f37c316d
moved tests to independent file, added chi2 computation
Nicolas Saunier <nico@confins.net>
parents:
29
diff
changeset
|
1016 '''Returns the filename minus the extension (all characters after last .)''' |
0
aed8eb63cdde
initial commit with non-functional python code for NGSIM
Nicolas Saunier <nico@confins.net>
parents:
diff
changeset
|
1017 i = filename.rfind(delimiter) |
aed8eb63cdde
initial commit with non-functional python code for NGSIM
Nicolas Saunier <nico@confins.net>
parents:
diff
changeset
|
1018 if i>0: |
aed8eb63cdde
initial commit with non-functional python code for NGSIM
Nicolas Saunier <nico@confins.net>
parents:
diff
changeset
|
1019 return filename[:i] |
aed8eb63cdde
initial commit with non-functional python code for NGSIM
Nicolas Saunier <nico@confins.net>
parents:
diff
changeset
|
1020 else: |
aed8eb63cdde
initial commit with non-functional python code for NGSIM
Nicolas Saunier <nico@confins.net>
parents:
diff
changeset
|
1021 return filename |
aed8eb63cdde
initial commit with non-functional python code for NGSIM
Nicolas Saunier <nico@confins.net>
parents:
diff
changeset
|
1022 |
969
5d788d2e8ffc
work in progress
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
940
diff
changeset
|
1023 def getExtension(filename, delimiter = '.'): |
5d788d2e8ffc
work in progress
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
940
diff
changeset
|
1024 '''Returns the filename minus the extension (all characters after last .)''' |
5d788d2e8ffc
work in progress
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
940
diff
changeset
|
1025 i = filename.rfind(delimiter) |
5d788d2e8ffc
work in progress
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
940
diff
changeset
|
1026 if i>0: |
5d788d2e8ffc
work in progress
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
940
diff
changeset
|
1027 return filename[i+1:] |
5d788d2e8ffc
work in progress
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
940
diff
changeset
|
1028 else: |
5d788d2e8ffc
work in progress
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
940
diff
changeset
|
1029 return '' |
5d788d2e8ffc
work in progress
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
940
diff
changeset
|
1030 |
46
b5d007612e16
added filename util
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
45
diff
changeset
|
1031 def cleanFilename(s): |
b5d007612e16
added filename util
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
45
diff
changeset
|
1032 'cleans filenames obtained when contatenating figure characteristics' |
739 | 1033 return s.replace(' ','-').replace('.','').replace('/','-').replace(',','') |
46
b5d007612e16
added filename util
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
45
diff
changeset
|
1034 |
1021
16932cefabc1
work on paths in line with new configurations from tracker
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
997
diff
changeset
|
1035 def getRelativeFilename(parentPath, filename): |
16932cefabc1
work on paths in line with new configurations from tracker
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
997
diff
changeset
|
1036 'Returns filename if absolute, otherwise parentPath/filename as string' |
16932cefabc1
work on paths in line with new configurations from tracker
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
997
diff
changeset
|
1037 filePath = Path(filename) |
16932cefabc1
work on paths in line with new configurations from tracker
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
997
diff
changeset
|
1038 if filePath.is_absolute(): |
16932cefabc1
work on paths in line with new configurations from tracker
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
997
diff
changeset
|
1039 return filename |
16932cefabc1
work on paths in line with new configurations from tracker
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
997
diff
changeset
|
1040 else: |
16932cefabc1
work on paths in line with new configurations from tracker
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
997
diff
changeset
|
1041 return str(parentPath/filePath) |
16932cefabc1
work on paths in line with new configurations from tracker
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
997
diff
changeset
|
1042 |
0
aed8eb63cdde
initial commit with non-functional python code for NGSIM
Nicolas Saunier <nico@confins.net>
parents:
diff
changeset
|
1043 def listfiles(dirname, extension, remove = False): |
14
e7bbe8465591
homography and other utils
Nicolas Saunier <nico@confins.net>
parents:
7
diff
changeset
|
1044 '''Returns the list of files with the extension in the directory dirname |
e7bbe8465591
homography and other utils
Nicolas Saunier <nico@confins.net>
parents:
7
diff
changeset
|
1045 If remove is True, the filenames are stripped from the extension''' |
1021
16932cefabc1
work on paths in line with new configurations from tracker
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
997
diff
changeset
|
1046 d = Path(dirname) |
16932cefabc1
work on paths in line with new configurations from tracker
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
997
diff
changeset
|
1047 if d.is_dir(): |
16932cefabc1
work on paths in line with new configurations from tracker
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
997
diff
changeset
|
1048 tmp = [str(f) for f in d.glob('*.extension')] |
16932cefabc1
work on paths in line with new configurations from tracker
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
997
diff
changeset
|
1049 if remove: |
16932cefabc1
work on paths in line with new configurations from tracker
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
997
diff
changeset
|
1050 return [removeExtension(f, extension) for f in tmp] |
16932cefabc1
work on paths in line with new configurations from tracker
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parents:
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diff
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|
1051 else: |
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work on paths in line with new configurations from tracker
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parents:
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diff
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|
1052 return tmp |
0
aed8eb63cdde
initial commit with non-functional python code for NGSIM
Nicolas Saunier <nico@confins.net>
parents:
diff
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|
1053 else: |
1021
16932cefabc1
work on paths in line with new configurations from tracker
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents:
997
diff
changeset
|
1054 print(dirname+' is not a directory') |
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work on paths in line with new configurations from tracker
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parents:
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diff
changeset
|
1055 return [] |
0
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initial commit with non-functional python code for NGSIM
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parents:
diff
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|
1056 |
266
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diff
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|
1057 def mkdir(dirname): |
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diff
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|
1058 'Creates a directory if it does not exist' |
1021
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parents:
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diff
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|
1059 p = Path(dirname) |
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diff
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|
1060 if not p.exists(): |
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diff
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|
1061 p.mkdir() |
266
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1062 else: |
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diff
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|
1063 print(dirname+' already exists') |
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|
1064 |
14
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homography and other utils
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parents:
7
diff
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|
1065 def removeFile(filename): |
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homography and other utils
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parents:
7
diff
changeset
|
1066 '''Deletes the file while avoiding raising an error |
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homography and other utils
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parents:
7
diff
changeset
|
1067 if the file does not exist''' |
1021
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|
1068 f = Path(filename) |
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diff
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|
1069 if (f.exists()): |
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|
1070 f.unlink() |
266
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1071 else: |
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262
diff
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|
1072 print(filename+' does not exist') |
14
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homography and other utils
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parents:
7
diff
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|
1073 |
42
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35
diff
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|
1074 def line2Floats(l, separator=' '): |
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parents:
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diff
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1075 '''Returns the list of floats corresponding to the string''' |
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diff
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|
1076 return [float(x) for x in l.split(separator)] |
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35
diff
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|
1077 |
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35
diff
changeset
|
1078 def line2Ints(l, separator=' '): |
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parents:
35
diff
changeset
|
1079 '''Returns the list of ints corresponding to the string''' |
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diff
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|
1080 return [int(x) for x in l.split(separator)] |
31
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29
diff
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|
1081 |
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diff
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|
1082 ######################### |
553
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parents:
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diff
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|
1083 # Profiling |
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|
1084 ######################### |
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|
1085 |
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|
1086 def analyzeProfile(profileFilename, stripDirs = True): |
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parents:
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diff
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|
1087 '''Analyze the file produced by cProfile |
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diff
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|
1088 |
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diff
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|
1089 obtained by for example: |
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parents:
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diff
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|
1090 - call in script (for main() function in script) |
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|
1091 import cProfile, os |
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|
1092 cProfile.run('main()', os.path.join(os.getcwd(),'main.profile')) |
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parents:
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diff
changeset
|
1093 |
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diff
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|
1094 - or on the command line: |
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diff
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|
1095 python -m cProfile [-o profile.bin] [-s sort] scriptfile [arg]''' |
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|
1096 import pstats, os |
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|
1097 p = pstats.Stats(os.path.join(os.pardir, profileFilename)) |
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diff
changeset
|
1098 if stripDirs: |
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diff
changeset
|
1099 p.strip_dirs() |
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diff
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|
1100 p.sort_stats('time') |
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|
1101 p.print_stats(.2) |
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|
1102 #p.sort_stats('time') |
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|
1103 # p.print_callees(.1, 'int_prediction.py:') |
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diff
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|
1104 return p |
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parents:
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diff
changeset
|
1105 |
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diff
changeset
|
1106 ######################### |
31
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parents:
29
diff
changeset
|
1107 # running tests |
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parents:
29
diff
changeset
|
1108 ######################### |
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diff
changeset
|
1109 |
0
aed8eb63cdde
initial commit with non-functional python code for NGSIM
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diff
changeset
|
1110 if __name__ == "__main__": |
aed8eb63cdde
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parents:
diff
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|
1111 import doctest |
2
de5642925615
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parents:
0
diff
changeset
|
1112 import unittest |
31
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moved tests to independent file, added chi2 computation
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29
diff
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|
1113 suite = doctest.DocFileSuite('tests/utils.txt') |
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29
diff
changeset
|
1114 #suite = doctest.DocTestSuite() |
2
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started implementation of TimeInterval and Spatio-temporal object
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parents:
0
diff
changeset
|
1115 unittest.TextTestRunner().run(suite) |
de5642925615
started implementation of TimeInterval and Spatio-temporal object
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parents:
0
diff
changeset
|
1116 #doctest.testmod() |
0
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diff
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|
1117 #doctest.testfile("example.txt") |