Mercurial Hosting > traffic-intelligence
changeset 389:6d26dcc7bba0
modifications to compute alignment for None indicators
| author | Nicolas Saunier <nicolas.saunier@polymtl.ca> |
|---|---|
| date | Thu, 25 Jul 2013 16:01:12 -0400 |
| parents | 6e0dedd34920 |
| children | 12be4a0cb9aa 03dbecd3a887 |
| files | python/indicators.py python/utils.py |
| diffstat | 2 files changed, 5 insertions(+), 6 deletions(-) [+] |
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--- a/python/indicators.py Thu Jul 25 14:21:17 2013 -0400 +++ b/python/indicators.py Thu Jul 25 16:01:12 2013 -0400 @@ -132,7 +132,6 @@ else: return 1. - class SeverityIndicator(TemporalIndicator): '''Class for severity indicators field mostSevereIsMax is True
--- a/python/utils.py Thu Jul 25 14:21:17 2013 -0400 +++ b/python/utils.py Thu Jul 25 16:01:12 2013 -0400 @@ -219,7 +219,7 @@ self.aligned = aligned self.delta = delta self.lengthFunc = lengthFunc - self.alignmentShift = 0 + self.subSequenceIndices = [(0,0)] def similarities(self, l1, l2, jshift=0): from numpy import zeros, int as npint @@ -273,14 +273,14 @@ lcssValues[i] = self.similarityTable.max() similarityTables[i] = self.similarityTable #print self.similarityTable - self.alignmentShift = argMaxDict(lcssValues) # ideally get the medium alignment shift, the one that minimizes distance - self.similarityTable = similarityTables[self.alignmentShift] + alignmentShift = argMaxDict(lcssValues) # ideally get the medium alignment shift, the one that minimizes distance + self.similarityTable = similarityTables[alignmentShift] else: - self.alignmentShift = 0 + alignmentShift = 0 self.similarities(l1, l2) # threshold values for the useful part of the similarity table are n2-n1-delta and n1-n2-delta - self.similarityTable = self.similarityTable[:min(n1, n2+self.alignmentShift+self.delta)+1, :min(n2, n1-self.alignmentShift+self.delta)+1] + self.similarityTable = self.similarityTable[:min(n1, n2+alignmentShift+self.delta)+1, :min(n2, n1-alignmentShift+self.delta)+1] if computeSubSequence: self.subSequenceIndices = self.subSequence(self.similarityTable.shape[0]-1, self.similarityTable.shape[1]-1)