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annotate python/utils.py @ 324:99ca91a46007

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minor change
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Thu, 09 May 2013 04:02:46 +0200
parents efd4dd4665ac
children a6ca86107f27
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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 numpy import *
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5 #from pylab import *
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6
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7 __metaclass__ = type
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8
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9 commentChar = '#'
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11 delimiterChar = '%';
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12
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13 #########################
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14 # Enumerations
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15 #########################
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16
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17 def inverseEnumeration(l):
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18 'Returns the dictionary that provides for each element in the input list its index in the input list'
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19 result = {}
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20 for i,x in enumerate(l):
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21 result[x] = i
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22 return result
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23
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24 #########################
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25 # CLI utils
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26 #########################
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27
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28 def parseCLIOptions(helpMessage, options, cliArgs, optionalOptions=[]):
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29 ''' Simple function to handle similar argument parsing
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30 Returns the dictionary of options and their values
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31
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32 * cliArgs are most likely directly sys.argv
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33 (only the elements after the first one are considered)
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34
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35 * options should be a list of strings for getopt options,
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36 eg ['frame=','correspondences=','video=']
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37 A value must be provided for each option, or the program quits'''
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38 import sys, getopt
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39 from numpy.core.fromnumeric import all
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40 optionValues, args = getopt.getopt(cliArgs[1:], 'h', ['help']+options+optionalOptions)
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41 optionValues = dict(optionValues)
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42
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43 if '--help' in optionValues.keys() or '-h' in optionValues.keys():
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44 print(helpMessage+
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45 '\n - Compulsory options: '+' '.join([opt.replace('=','') for opt in options])+
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46 '\n - Non-compulsory options: '+' '.join([opt.replace('=','') for opt in optionalOptions]))
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47 sys.exit()
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48
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49 missingArgument = [('--'+opt.replace('=','') in optionValues.keys()) for opt in options]
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50 if not all(missingArgument):
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51 print('Missing argument')
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52 print(optionValues)
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53 sys.exit()
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54
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55 return optionValues
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56
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57 #########################
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58 # simple statistics
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59 #########################
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60
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61 def confidenceInterval(mean, stdev, nSamples, percentConfidence, printLatex = False):
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62 from math import sqrt
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63 from scipy.stats.distributions import norm
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64 k = round(norm.ppf(0.5+percentConfidence/200., 0, 1)*100)/100. # 1.-(100-percentConfidence)/200.
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65 e = k*stdev/sqrt(nSamples)
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66 if printLatex:
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67 print('${0} \pm {1}\\frac{{{2}}}{{\sqrt{{{3}}}}}$'.format(mean, k, stdev, nSamples))
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68 return mean-e, mean+e
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69
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70 def computeChi2(expected, observed):
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71 '''Returns the Chi2 statistics'''
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72 result = 0.
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73 for e, o in zip(expected, observed):
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74 result += ((e-o)*(e-o))/e
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75 return result
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76
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77 class EmpiricalDistribution:
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78 def nSamples(self):
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79 return sum(self.counts)
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80
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81 def cumulativeDensityFunction(sample):
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82 '''Returns the cumulative density function of the sample of a random variable'''
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83 from numpy.core.multiarray import array
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84 from numpy.lib.function_base import unique
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85 from numpy.core.fromnumeric import sum
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86 a = array(sample)
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87 a.sort()
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88 xaxis = unique(a)
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89 counts = [sum(a <= x) for x in xaxis]
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90 return xaxis, counts
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91
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92 class EmpiricalDiscreteDistribution(EmpiricalDistribution):
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93 '''Class to represent a sample of a distribution for a discrete random variable
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94 '''
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95 from numpy.core.fromnumeric import sum
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96
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97 def __init__(self, categories, counts):
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98 self.categories = categories
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99 self.counts = counts
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100
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101 def mean(self):
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102 result = [float(x*y) for x,y in zip(self.categories, self.counts)]
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103 return sum(result)/self.nSamples()
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104
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105 def var(self, mean = None):
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106 if not mean:
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107 m = self.mean()
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108 else:
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109 m = mean
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110 result = 0.
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111 squares = [float((x-m)*(x-m)*y) for x,y in zip(self.categories, self.counts)]
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112 return sum(squares)/(self.nSamples()-1)
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113
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114 def referenceCounts(self, probability):
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115 '''probability is a function that returns the probability of the random variable for the category values'''
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116 refProba = [probability(c) for c in self.categories]
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117 refProba[-1] = 1-sum(refProba[:-1])
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118 refCounts = [r*self.nSamples() for r in refProba]
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119 return refCounts, refProba
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120
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121 class EmpiricalContinuousDistribution(EmpiricalDistribution):
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122 '''Class to represent a sample of a distribution for a continuous random variable
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123 with the number of observations for each interval
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124 intervals (categories variable) are defined by their left limits, the last one being the right limit
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125 categories contain therefore one more element than the counts'''
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126 def __init__(self, categories, counts):
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127 # todo add samples for initialization and everything to None? (or setSamples?)
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128 self.categories = categories
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129 self.counts = counts
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130
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131 def mean(self):
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132 result = 0.
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133 for i in range(len(self.counts)-1):
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134 result += self.counts[i]*(self.categories[i]+self.categories[i+1])/2
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135 return result/self.nSamples()
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136
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diff changeset
137 def var(self, mean = None):
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diff changeset
138 if not mean:
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diff changeset
139 m = self.mean()
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parents: 32
diff changeset
140 else:
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parents: 32
diff changeset
141 m = mean
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parents: 32
diff changeset
142 result = 0.
76
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diff changeset
143 for i in range(len(self.counts)-1):
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diff changeset
144 mid = (self.categories[i]+self.categories[i+1])/2
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diff changeset
145 result += self.counts[i]*(mid - m)*(mid - m)
35
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diff changeset
146 return result/(self.nSamples()-1)
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diff changeset
147
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diff changeset
148 def referenceCounts(self, cdf):
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diff changeset
149 '''cdf is a cumulative distribution function
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diff changeset
150 returning the probability of the variable being less that x'''
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diff changeset
151 # refCumulativeCounts = [0]#[cdf(self.categories[0][0])]
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diff changeset
152 # for inter in self.categories:
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diff changeset
153 # refCumulativeCounts.append(cdf(inter[1]))
76
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diff changeset
154 refCumulativeCounts = [cdf(x) for x in self.categories[1:-1]]
35
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diff changeset
155
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parents: 32
diff changeset
156 refProba = [refCumulativeCounts[0]]
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parents: 32
diff changeset
157 for i in xrange(1,len(refCumulativeCounts)):
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diff changeset
158 refProba.append(refCumulativeCounts[i]-refCumulativeCounts[i-1])
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parents: 32
diff changeset
159 refProba.append(1-refCumulativeCounts[-1])
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parents: 32
diff changeset
160 refCounts = [p*self.nSamples() for p in refProba]
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diff changeset
161
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parents: 32
diff changeset
162 return refCounts, refProba
31
c000f37c316d moved tests to independent file, added chi2 computation
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diff changeset
163
77
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diff changeset
164 def printReferenceCounts(self, refCounts=None):
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diff changeset
165 if refCounts:
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diff changeset
166 ref = refCounts
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parents: 76
diff changeset
167 else:
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diff changeset
168 ref = self.referenceCounts
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parents: 76
diff changeset
169 for i in xrange(len(ref[0])):
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diff changeset
170 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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diff changeset
171
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diff changeset
172
31
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diff changeset
173 #########################
27
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parents: 24
diff changeset
174 # maths section
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parents: 24
diff changeset
175 #########################
24
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diff changeset
176
285
5957aa1d69e1 Integrating Mohamed's changes
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diff changeset
177 def LCSS(l1, l2, threshold, distance, delta = float('inf')):
284
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parents: 282
diff changeset
178 '''returns the longest common subsequence similarity
285
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parents: 284
diff changeset
179 based on the threshold on distance between two elements of lists l1, l2
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diff changeset
180 '''
284
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parents: 282
diff changeset
181 from numpy import zeros, int as npint
322
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diff changeset
182 n1 = len(l1)
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diff changeset
183 n2 = len(l2)
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parents: 312
diff changeset
184 similarity = zeros((n1+1,n2+1), dtype = npint)
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parents: 312
diff changeset
185 for i in xrange(1,n1+1):
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parents: 312
diff changeset
186 for j in xrange(max(1,i-delta),min(n2+1,i+delta+1)):
286
fa95796a76b3 simplified indicators (only non-measured values, whether measurable or not)
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 285
diff changeset
187 if distance(l1[i-1], l2[j-1])<=threshold:
281
4f012e3d881b corrected lcss bug
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parents: 279
diff changeset
188 similarity[i][j] = similarity[i-1][j-1]+1
279
3af4c267a7bf generic simple LCSS
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 276
diff changeset
189 else:
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parents: 276
diff changeset
190 similarity[i][j] = max(similarity[i-1][j], similarity[i][j-1])
322
28661c5887d3 Corrected a major bug for LCSS
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parents: 312
diff changeset
191 return max(max(similarity[:,-1]), max(similarity[-1,:]))
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parents: 312
diff changeset
192
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diff changeset
193 def normalizedLCSS(l1, l2, threshold, distance, delta = float('inf'), lengthMethod = min):
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diff changeset
194 ''' compute the normalized LCSS
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parents: 312
diff changeset
195 ie, the LCSS divided by the min or mean of the indicator lengths (using lengthMethod)
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parents: 312
diff changeset
196 lengthMethod = lambda x,y:float(x,y)/2'''
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parents: 312
diff changeset
197 return float(LCSS(l1, l2, threshold, distance, delta))/lengthMethod(len(l1), len(l2))
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diff changeset
198
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diff changeset
199 def DLCSS(l1, l2, threshold, distance, delta = float('inf'), lengthMethod = min):
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diff changeset
200 ''' compute the LCSS distance'''
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parents: 312
diff changeset
201 return 1-normalizedLCSS(l1, l2, threshold, distance, delta, lengthMethod)
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parents: 312
diff changeset
202
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parents: 312
diff changeset
203 def alignedLCSS(_l1, _l2, threshold, distance, delta):
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parents: 312
diff changeset
204 '''returns the best matching if using a finite delta by shiftinig the series alignments'''
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parents: 312
diff changeset
205 if len(_l2) < len(_l1): # l1 is the shortest
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parents: 312
diff changeset
206 l1 = _l2
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diff changeset
207 l2 = _l1
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parents: 312
diff changeset
208 else:
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diff changeset
209 l1 = _l1
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diff changeset
210 l2 = _l2
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parents: 312
diff changeset
211 n1 = len(l1)
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parents: 312
diff changeset
212 n2 = len(l2)
323
efd4dd4665ac corrected issues with large deltas
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 322
diff changeset
213 # for i in xrange(min(delta,n1), max(n1+n2-delta, n2+1)): # i is the alignment of the end of l1 in l2
322
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parents: 312
diff changeset
214 # print l1[min(-i-1,n1):] # min(n1+n2-i,n1)
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parents: 312
diff changeset
215 # print l2[max(0,i-n1):]
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parents: 312
diff changeset
216 # print LCSS(l1[min(-i-1,n1):], l2[max(0,i-n1):], threshold, distance, delta)
323
efd4dd4665ac corrected issues with large deltas
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 322
diff changeset
217 lcss = [LCSS(l1[min(-i-1,n1):], l2[max(0,i-n1):], threshold, distance, delta) for i in xrange(min(delta,n1), max(n1+n2-delta, n2+1))]
322
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parents: 312
diff changeset
218 return max(lcss)
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parents: 312
diff changeset
219
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Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 312
diff changeset
220 def normalizedAlignedLCSS(l1, l2, threshold, distance, delta, lengthMethod = min):
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parents: 312
diff changeset
221 return float(alignedLCSS(l1, l2, threshold, distance, delta))/lengthMethod(len(l1), len(l2))
28661c5887d3 Corrected a major bug for LCSS
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parents: 312
diff changeset
222
28661c5887d3 Corrected a major bug for LCSS
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 312
diff changeset
223 def alignedDLCSS(l1, l2, threshold, distance, delta, lengthMethod = min):
28661c5887d3 Corrected a major bug for LCSS
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parents: 312
diff changeset
224 return 1-normalizedAlignedLCSS(l1, l2, threshold, distance, delta, lengthMethod)
279
3af4c267a7bf generic simple LCSS
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parents: 276
diff changeset
225
248
571ba5ed22e2 added utils for bus processing
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 241
diff changeset
226 def framesToTime(nFrames, frameRate, initialTime = (0.,0.,0.)):
571ba5ed22e2 added utils for bus processing
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 241
diff changeset
227 'returns hour, minutes and seconds'
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parents: 241
diff changeset
228 from math import floor
261
4aa792cb0fa9 changing framesToTime to return a datetime.time
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 248
diff changeset
229 from datetime import time
262
a048066bd20f correcting bug in framesToTime
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 261
diff changeset
230 seconds = int(floor(float(nFrames)/float(frameRate))+initialTime[0]*3600+initialTime[1]*60+initialTime[2])
261
4aa792cb0fa9 changing framesToTime to return a datetime.time
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 248
diff changeset
231 h = int(floor(seconds/3600.))
248
571ba5ed22e2 added utils for bus processing
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 241
diff changeset
232 seconds = seconds - h*3600
261
4aa792cb0fa9 changing framesToTime to return a datetime.time
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 248
diff changeset
233 m = int(floor(seconds/60))
248
571ba5ed22e2 added utils for bus processing
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 241
diff changeset
234 seconds = seconds - m*60
262
a048066bd20f correcting bug in framesToTime
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 261
diff changeset
235 return time(h, m, seconds)
248
571ba5ed22e2 added utils for bus processing
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 241
diff changeset
236
241
ee1caff48b03 added function to sort to list of paired data X,Y
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 235
diff changeset
237 def sortXY(X,Y):
ee1caff48b03 added function to sort to list of paired data X,Y
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 235
diff changeset
238 'returns the sorted (x, Y(x)) sorted on X'
ee1caff48b03 added function to sort to list of paired data X,Y
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 235
diff changeset
239 D = {}
ee1caff48b03 added function to sort to list of paired data X,Y
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 235
diff changeset
240 for x, y in zip(X,Y):
ee1caff48b03 added function to sort to list of paired data X,Y
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 235
diff changeset
241 D[x]=y
ee1caff48b03 added function to sort to list of paired data X,Y
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 235
diff changeset
242 xsorted = sorted(D.keys())
ee1caff48b03 added function to sort to list of paired data X,Y
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 235
diff changeset
243 return xsorted, [D[x] for x in xsorted]
ee1caff48b03 added function to sort to list of paired data X,Y
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 235
diff changeset
244
32
48e56179c39e added ceil function
Nicolas Saunier <nico@confins.net>
parents: 31
diff changeset
245 def ceilDecimals(v, nDecimals):
48e56179c39e added ceil function
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parents: 31
diff changeset
246 '''Rounds the number at the nth decimal
48e56179c39e added ceil function
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parents: 31
diff changeset
247 eg 1.23 at 0 decimal is 2, at 1 decimal is 1.3'''
48e56179c39e added ceil function
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parents: 31
diff changeset
248 from math import ceil,pow
48e56179c39e added ceil function
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parents: 31
diff changeset
249 tens = pow(10,nDecimals)
48e56179c39e added ceil function
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parents: 31
diff changeset
250 return ceil(v*tens)/tens
48e56179c39e added ceil function
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parents: 31
diff changeset
251
152
74b1fc68d4df re-organized code to avoid cyclic python module dependencies
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 116
diff changeset
252 def inBetween(bound1, bound2, x):
74b1fc68d4df re-organized code to avoid cyclic python module dependencies
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 116
diff changeset
253 return bound1 <= x <= bound2 or bound2 <= x<= bound1
24
6fb59cfb201e first version of segmentIntersection
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parents: 19
diff changeset
254
6fb59cfb201e first version of segmentIntersection
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parents: 19
diff changeset
255 def crossProduct(l1, l2):
6fb59cfb201e first version of segmentIntersection
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parents: 19
diff changeset
256 return l1[0]*l2[1]-l1[1]*l2[0]
6fb59cfb201e first version of segmentIntersection
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parents: 19
diff changeset
257
29
ca8e716cc231 added moving average filter
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parents: 27
diff changeset
258 def filterMovingWindow(input, halfWidth):
ca8e716cc231 added moving average filter
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parents: 27
diff changeset
259 '''Returns an array obtained after the smoothing of the input by a moving average
ca8e716cc231 added moving average filter
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parents: 27
diff changeset
260 The first and last points are copied from the original.'''
ca8e716cc231 added moving average filter
Nicolas Saunier <nico@confins.net>
parents: 27
diff changeset
261 width = float(halfWidth*2+1)
ca8e716cc231 added moving average filter
Nicolas Saunier <nico@confins.net>
parents: 27
diff changeset
262 win = ones(width,'d')
ca8e716cc231 added moving average filter
Nicolas Saunier <nico@confins.net>
parents: 27
diff changeset
263 result = convolve(win/width,array(inputSignal),'same')
ca8e716cc231 added moving average filter
Nicolas Saunier <nico@confins.net>
parents: 27
diff changeset
264 result[:halfWidth] = inputSignal[:halfWidth]
ca8e716cc231 added moving average filter
Nicolas Saunier <nico@confins.net>
parents: 27
diff changeset
265 result[-halfWidth:] = inputSignal[-halfWidth:]
ca8e716cc231 added moving average filter
Nicolas Saunier <nico@confins.net>
parents: 27
diff changeset
266 return result
ca8e716cc231 added moving average filter
Nicolas Saunier <nico@confins.net>
parents: 27
diff changeset
267
199
ca9d9104afba added utility to calibrate polynoms and plot
Nicolas Saunier <nicolas.saunier@polymtl.ca>
parents: 197
diff changeset
268 def linearRegression(x, y, deg = 1, plotData = False):
ca9d9104afba added utility to calibrate polynoms and plot
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parents: 197
diff changeset
269 '''returns the least square estimation of the linear regression of y = ax+b
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270 as well as the plot'''
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diff changeset
271 from numpy.lib.polynomial import polyfit
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diff changeset
272 from matplotlib.pyplot import plot
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273 from numpy.core.multiarray import arange
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274 coef = polyfit(x, y, deg)
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diff changeset
275 if plotData:
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diff changeset
276 def poly(x):
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diff changeset
277 result = 0
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diff changeset
278 for i in range(len(coef)):
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279 result += coef[i]*x**(len(coef)-i-1)
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280 return result
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281 plot(x, y, 'x')
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282 xx = arange(min(x), max(x),(max(x)-min(x))/1000)
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283 plot(xx, [poly(z) for z in xx])
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diff changeset
284 return coef
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285
27
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286 #########################
45
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287 # plotting section
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288 #########################
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289
324
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290 def stepPlot(X, firstX, lastX, initialCount = 0, increment = 1):
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291 '''for each value in X, increment by increment the initial count
297
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292 returns the lists that can be plotted
324
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293 to obtain a step plot increasing by one for each value in x, from first to last value
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294 firstX and lastX should be respectively smaller and larger than all elements in X'''
297
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295
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296 sortedX = []
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297 counts = [initialCount]
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298 for x in sorted(X):
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299 sortedX += [x,x]
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300 counts.append(counts[-1])
324
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301 counts.append(counts[-1]+increment)
297
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302 counts.append(counts[-1])
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303 return [firstX]+sortedX+[lastX], counts
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304
45
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305 class PlottingPropertyValues:
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306 def __init__(self, values):
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307 self.values = values
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308
116
2bf5b76320c0 moved intersection plotting and added markers for scatter plots
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309 def __getitem__(self, i):
45
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310 return self.values[i%len(self.values)]
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311
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312 markers = PlottingPropertyValues(['+', '*', ',', '.', 'x', 'D', 's', 'o'])
116
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313 scatterMarkers = PlottingPropertyValues(['s','o','^','>','v','<','d','p','h','8','+','x'])
45
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314
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315 linestyles = PlottingPropertyValues(['-', '--', '-.', ':'])
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316
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317 colors = PlottingPropertyValues('brgmyck') # 'w'
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318
115
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319 def plotIndicatorMap(indicatorMap, squareSize, masked = True, defaultValue=-1):
65
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diff changeset
320 from numpy import array, arange, ones, ma
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321 from matplotlib.pyplot import pcolor
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322 coords = array(indicatorMap.keys())
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323 minX = min(coords[:,0])
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324 minY = min(coords[:,1])
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325 X = arange(minX, max(coords[:,0])+1.1)*squareSize
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326 Y = arange(minY, max(coords[:,1])+1.1)*squareSize
115
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327 C = defaultValue*ones((len(Y), len(X)))
65
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diff changeset
328 for k,v in indicatorMap.iteritems():
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diff changeset
329 C[k[1]-minY,k[0]-minX] = v
115
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330 if masked:
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331 pcolor(X, Y, ma.masked_where(C==defaultValue,C))
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diff changeset
332 else:
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diff changeset
333 pcolor(X, Y, C)
65
75cf537b8d88 moved and generalized map making functions to the library
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diff changeset
334
45
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diff changeset
335 #########################
27
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336 # file I/O section
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diff changeset
337 #########################
24
6fb59cfb201e first version of segmentIntersection
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parents: 19
diff changeset
338
0
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339 def openCheck(filename, option = 'r', quit = False):
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340 '''Open file filename in read mode by default
31
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diff changeset
341 and checks it is open'''
0
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342 try:
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343 return open(filename, option)
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344 except IOError:
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345 print 'File %s could not be opened.' % filename
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346 if quit:
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347 from sys import exit
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348 exit()
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349 return None
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diff changeset
350
48
8aed225f71d8 rearranged code for function readline and getlines (and characters), moved invertHomography to cvutils
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diff changeset
351 def readline(f, commentCharacter = commentChar):
0
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parents:
diff changeset
352 '''Modified readline function to skip comments.'''
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diff changeset
353 s = f.readline()
48
8aed225f71d8 rearranged code for function readline and getlines (and characters), moved invertHomography to cvutils
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diff changeset
354 while (len(s) > 0) and s.startswith(commentCharacter):
0
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355 s = f.readline()
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356 return s.strip()
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diff changeset
357
48
8aed225f71d8 rearranged code for function readline and getlines (and characters), moved invertHomography to cvutils
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diff changeset
358 def getLines(f, delimiterCharacter = delimiterChar):
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diff changeset
359 '''Gets a complete entry (all the lines) in between delimiterChar.'''
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parents: 46
diff changeset
360 dataStrings = []
8aed225f71d8 rearranged code for function readline and getlines (and characters), moved invertHomography to cvutils
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parents: 46
diff changeset
361 s = readline(f)
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parents: 46
diff changeset
362 while (len(s) > 0) and (not s.startswith(delimiterCharacter)):
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diff changeset
363 dataStrings += [s.strip()]
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parents: 46
diff changeset
364 s = readline(f)
8aed225f71d8 rearranged code for function readline and getlines (and characters), moved invertHomography to cvutils
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diff changeset
365 return dataStrings
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diff changeset
366
304
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parents: 301
diff changeset
367 class FakeSecHead(object):
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parents: 301
diff changeset
368 '''Add fake section header [asection]
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diff changeset
369
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diff changeset
370 from http://stackoverflow.com/questions/2819696/parsing-properties-file-in-python/2819788#2819788
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diff changeset
371 use read_file in Python 3.2+
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diff changeset
372 '''
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diff changeset
373 def __init__(self, fp):
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diff changeset
374 self.fp = fp
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diff changeset
375 self.sechead = '[main]\n'
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parents: 301
diff changeset
376
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diff changeset
377 def readline(self):
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diff changeset
378 if self.sechead:
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diff changeset
379 try: return self.sechead
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diff changeset
380 finally: self.sechead = None
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diff changeset
381 else: return self.fp.readline()
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parents: 301
diff changeset
382
0
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parents:
diff changeset
383 def removeExtension(filename, delimiter = '.'):
31
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parents: 29
diff changeset
384 '''Returns the filename minus the extension (all characters after last .)'''
0
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parents:
diff changeset
385 i = filename.rfind(delimiter)
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parents:
diff changeset
386 if i>0:
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parents:
diff changeset
387 return filename[:i]
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parents:
diff changeset
388 else:
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parents:
diff changeset
389 return filename
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parents:
diff changeset
390
46
b5d007612e16 added filename util
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parents: 45
diff changeset
391 def cleanFilename(s):
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parents: 45
diff changeset
392 'cleans filenames obtained when contatenating figure characteristics'
266
aba9711b3149 small modificatons and reorganization
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parents: 262
diff changeset
393 return s.replace(' ','-').replace('.','').replace('/','-')
46
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parents: 45
diff changeset
394
0
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parents:
diff changeset
395 def listfiles(dirname, extension, remove = False):
14
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parents: 7
diff changeset
396 '''Returns the list of files with the extension in the directory dirname
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diff changeset
397 If remove is True, the filenames are stripped from the extension'''
0
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parents:
diff changeset
398 from os import listdir
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parents:
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399 tmp = [f for f in listdir(dirname) if f.endswith(extension)]
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400 tmp.sort()
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401 if remove:
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402 return [removeExtension(f, extension) for f in tmp]
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403 else:
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404 return tmp
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405
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406 def mkdir(dirname):
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407 'Creates a directory if it does not exist'
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408 import os
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409 if not os.path.exists(dirname):
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410 os.mkdir(dirname)
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411 else:
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412 print(dirname+' already exists')
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413
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414 def removeFile(filename):
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415 '''Deletes the file while avoiding raising an error
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416 if the file does not exist'''
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417 import os
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418 if (os.path.exists(filename)):
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419 os.remove(filename)
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420 else:
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421 print(filename+' does not exist')
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422
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423 def plotPolygon(poly, options = ''):
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424 from numpy.core.multiarray import array
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425 from matplotlib.pyplot import plot
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426 from shapely.geometry import Polygon
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427
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428 tmp = array(poly.exterior)
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429 plot(tmp[:,0], tmp[:,1], options)
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430
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431 def line2Floats(l, separator=' '):
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432 '''Returns the list of floats corresponding to the string'''
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433 return [float(x) for x in l.split(separator)]
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434
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435 def line2Ints(l, separator=' '):
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436 '''Returns the list of ints corresponding to the string'''
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437 return [int(x) for x in l.split(separator)]
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438
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439 #########################
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440 # sqlite
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441 #########################
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442
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443 def dropTables(connection, tableNames):
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444 'deletes the table with names in tableNames'
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445 cursor = connection.cursor()
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446 for tableName in tableNames:
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447 cursor.execute('DROP TABLE '+tableName)
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448
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449 #########################
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450 # running tests
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451 #########################
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452
0
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453 if __name__ == "__main__":
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454 import doctest
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455 import unittest
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456 suite = doctest.DocFileSuite('tests/utils.txt')
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457 #suite = doctest.DocTestSuite()
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458 unittest.TextTestRunner().run(suite)
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459 #doctest.testmod()
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460 #doctest.testfile("example.txt")