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comparison python/indicators.py @ 368:2db4e76599a1

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implemented subsequence extraction and rearranged arguments
author Nicolas Saunier <nicolas.saunier@polymtl.ca>
date Mon, 15 Jul 2013 15:08:53 -0400
parents 2f39c4ed0b62
children 027e254f0b53
comparison
equal deleted inserted replaced
367:d44eba0db517 368:2db4e76599a1
94 keys.sort() 94 keys.sort()
95 for key in keys: 95 for key in keys:
96 values.append(self.values[key]) 96 values.append(self.values[key])
97 return values 97 return values
98 98
99 @staticmethod
100 def getDLCSS(indic1, indic2, threshold, delta = float('inf') , method ='min' ):
101 ''' compute the distance between two indicators using LCSS
102 two common methods are used: min or mean of the indicators length'''
103 print('Deprecated: this is not appropriate method for indicator comparison')
104 l1 = indic1.valueSorted
105 l2 = indic2.valueSorted
106 DLCSS = None
107 if method == 'min':
108 DLCSS = 1- (LCSS(l1,l2, threshold, delta, distance))/min(len(l1),len(l2))
109 if method == 'mean':
110 average = len(l1)+len(l2)/2
111 DLCSS = 1- ((LCSS(l1,l2, threshold, delta, distance))/average)
112 return DLCSS
113
114 99
115 def distanceForLCSS(x, y): # lambda x,y:abs(x-y) 100 def distanceForLCSS(x, y): # lambda x,y:abs(x-y)
116 if x == None or y == None: 101 if x == None or y == None:
117 return float('inf') 102 return float('inf')
118 else: 103 else:
121 # non-aligned LCSS computations, ok for delta = inf 106 # non-aligned LCSS computations, ok for delta = inf
122 def computeLCSS(indicator1, indicator2, threshold, delta = float('inf')): 107 def computeLCSS(indicator1, indicator2, threshold, delta = float('inf')):
123 ''' compute the LCSS between two indicators using LCSS''' 108 ''' compute the LCSS between two indicators using LCSS'''
124 from utils import LCSS 109 from utils import LCSS
125 if indicator1 and indicator2: 110 if indicator1 and indicator2:
126 return LCSS(indicator1.getValues(), indicator2.getValues(), threshold, distanceForLCSS, delta) 111 return LCSS(indicator1.getValues(), indicator2.getValues(), lambda x,y: (distanceForLCSS(x,y) <= threshold), delta)
127 else: 112 else:
128 return 0 113 return 0
129 114
130 def computeNormalizedLCSS(indicator1, indicator2, threshold, delta = float('inf'), method= min): 115 def computeNormalizedLCSS(indicator1, indicator2, threshold, delta = float('inf'), method= min):
131 ''' compute the normalized LCSS between two indicators using LCSS 116 ''' compute the normalized LCSS between two indicators using LCSS
132 ie, the LCSS divided by the min or mean of the indicator lengths''' 117 ie, the LCSS divided by the min or mean of the indicator lengths'''
133 from utils import normalizedLCSS 118 from utils import normalizedLCSS
134 if indicator1 and indicator2: 119 if indicator1 and indicator2:
135 return normalizedLCSS(indicator1.getValues(), indicator2.getValues(), threshold, distanceForLCSS, delta, method) 120 return normalizedLCSS(indicator1.getValues(), indicator2.getValues(), lambda x,y: (distanceForLCSS(x,y) <= threshold), delta, method)
136 else: 121 else:
137 return 0. 122 return 0.
138 123
139 def computeDLCSS(indicator1, indicator2, threshold, delta = float('inf'), method = min): 124 def computeDLCSS(indicator1, indicator2, threshold, delta = float('inf'), method = min):
140 ''' compute the LCSS distance between two indicators using LCSS''' 125 ''' compute the LCSS distance between two indicators using LCSS'''
141 from utils import DLCSS 126 from utils import DLCSS
142 return DLCSS(indicator1.getValues(), indicator2.getValues(), threshold, distanceForLCSS, delta, method) 127 if indicator1 and indicator2:
128 return DLCSS(indicator1.getValues(), indicator2.getValues(), lambda x,y: (distanceForLCSS(x,y) <= threshold), delta, method)
129 else:
130 return 1.
143 131
144 # aligned LCSS computations 132 # aligned LCSS computations
145 def computeAlignedLCSS(indicator1, indicator2, threshold, delta = float('inf')): 133 def computeAlignedLCSS(indicator1, indicator2, threshold, delta = float('inf')):
146 ''' compute the aligned LCSS between two indicators using LCSS''' 134 ''' compute the aligned LCSS between two indicators using LCSS'''
147 from utils import alignedLCSS 135 from utils import alignedLCSS
148 if indicator1 and indicator2: 136 if indicator1 and indicator2:
149 return alignedLCSS(indicator1.getValues(), indicator2.getValues(), threshold, distanceForLCSS, delta) 137 return alignedLCSS(indicator1.getValues(), indicator2.getValues(), lambda x,y: (distanceForLCSS(x,y) <= threshold), delta)
150 else: 138 else:
151 return 0 139 return 0
152 140
153 def computeNormalizedAlignedLCSS(indicator1, indicator2, threshold, delta = float('inf'), method= min): 141 def computeNormalizedAlignedLCSS(indicator1, indicator2, threshold, delta = float('inf'), method= min):
154 ''' compute the normalized aligned LCSS between two indicators using LCSS 142 ''' compute the normalized aligned LCSS between two indicators using LCSS
155 ie, the LCSS divided by the min or mean of the indicator lengths''' 143 ie, the LCSS divided by the min or mean of the indicator lengths'''
156 from utils import normalizedAlignedLCSS 144 from utils import normalizedAlignedLCSS
157 if indicator1 and indicator2: 145 if indicator1 and indicator2:
158 return normalizedAlignedLCSS(indicator1.getValues(), indicator2.getValues(), threshold, distanceForLCSS, delta, method) 146 return normalizedAlignedLCSS(indicator1.getValues(), indicator2.getValues(), lambda x,y: (distanceForLCSS(x,y) <= threshold), delta, method)
159 else: 147 else:
160 return 0. 148 return 0.
161 149
162 def computeAlignedDLCSS(indicator1, indicator2, threshold, delta = float('inf'), method = min): 150 def computeAlignedDLCSS(indicator1, indicator2, threshold, delta = float('inf'), method = min):
163 ''' compute the aligned LCSS distance between two indicators using LCSS''' 151 ''' compute the aligned LCSS distance between two indicators using LCSS'''
164 from utils import alignedDLCSS 152 from utils import alignedDLCSS
165 return alignedDLCSS(indicator1.getValues(), indicator2.getValues(), threshold, distanceForLCSS, delta, method) 153 if indicator1 and indicator2:
154 return alignedDLCSS(indicator1.getValues(), indicator2.getValues(), lambda x,y: (distanceForLCSS(x,y) <= threshold), delta, method)
155 else:
156 return 1.
166 157
167 class SeverityIndicator(TemporalIndicator): 158 class SeverityIndicator(TemporalIndicator):
168 '''Class for severity indicators 159 '''Class for severity indicators
169 field mostSevereIsMax is True 160 field mostSevereIsMax is True
170 if the most severe value taken by the indicator is the maximum''' 161 if the most severe value taken by the indicator is the maximum'''