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@ -37,6 +37,10 @@ def post_process_miles(seconds, miles, days):
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continue
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continue
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good.append(i)
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good.append(i)
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# if there are no 'good' odometer readings, bail on post processing
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if len(good) == 0:
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return [math.nan for i in range(len(miles))]
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corrected_miles = [miles[i] if i in good else 0. for i in range(len(miles))]
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corrected_miles = [miles[i] if i in good else 0. for i in range(len(miles))]
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# identify groups of suspicious data and correct them
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# identify groups of suspicious data and correct them
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for k, g in itertools.groupby(enumerate(suspect), lambda x:x[0]-x[1]):
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for k, g in itertools.groupby(enumerate(suspect), lambda x:x[0]-x[1]):
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