private static ErrorType _getErrorType(ClasterizedSentenceError error)
{
if (error.SampleWordsCount == 0)
return ErrorType.SurplusLinguisticObject;
if (error.DetectedWordsCount == 0)
return ErrorType.MissedLinguisticObject;
return ErrorType.DetectionDefect;
}
private static LinguisticObject _correctErrors(LinguisticObject linguisticObject, ClasterizedSentenceError error, int correctionClass)
{
if (error.ErrorClass > correctionClass) return linguisticObject;
return new LinguisticObject
{
MappedObjects = linguisticObject.MappedObjects,
WasEmulated = true,
Metrics = _getCorrectedMetrics(linguisticObject.Metrics)
};
}
private static bool _isMatch(ClasterizedSentenceError error, LinguisticObjectDetectionMetrics metrics)
{
if (error.DetectedWordsCount != metrics.TargetWordsCount ||
error.SampleWordsCount != metrics.SampleWordsCount || error.ErrorType != metrics.Type)
{
return false;
}
var metricsSampleWords = Enumerable.Zip(metrics.SampleWords, metrics.SampleWordIndexes,
(s, i) => String.Format("{0} ({1})", s, i)).ToList();
var metricsDetectedWords = Enumerable.Zip(metrics.TargetWords, metrics.TargetWordIndexes,
(s, i) => String.Format("{0} ({1})", s, i)).ToList();
return !metricsSampleWords.Except(error.SampleWords).Any() &&
!metricsDetectedWords.Except(error.DetectedWords).Any() &&
!error.SampleWords.Except(metricsSampleWords).Any() &&
!error.DetectedWords.Except(metricsDetectedWords).Any();
}
