public void CalculateMean()
{
var statsHelper = new StatsHelper();
var mean = statsHelper.CalculateMean(new List <double> {
5, 10, 15, 20, 25
});
Assert.AreEqual(mean, 15);
}
private StatsSummary <decimal> CalculateBasicStats()
{
var count = _records.Count;
var sum = StatsHelper.CalculateSum(_records);
var mean = StatsHelper.CalculateMean(sum, count);
var standardDeviation = StatsHelper.CalculateStandardDeviation(_records, mean);
var frequencyHistogram = StatsHelper.GenerateHistogram(_records, 10);
return(new StatsSummary <decimal>()
{
NumRecords = count,
Sum = sum,
Mean = mean,
StandardDeviation = standardDeviation,
FrequencyHistogram = frequencyHistogram
});
}
/// <summary>
/// Populate DataItemDto.Score and DataItemDto.IsOutlier
/// </summary>
/// <param name="input"></param>
public void CalculateOutlier(IEnumerable <DataItemDto> input)
{
foreach (var item in input)
{
_trainingData.Enqueue(item);
if (_trainingData.Count > _trainingDataSize)
{
_trainingData.Dequeue();
}
}
var mean = _statsHelper.CalculateMean(_trainingData.Select(x => (double)x.Value));
var std = _statsHelper.CalculateStandardDeviation(_trainingData.Select(x => (double)x.Value));
foreach (var item in input)
{
item.Score = _statsHelper.CalculateZScore((double)item.Value, mean, std);
item.IsOutlier = Math.Abs(item.Score) >= _outlierThreshHold;
}
}
public void Should_Return_CorrectMean(decimal sum, int count, decimal expectedResult)
{
var result = StatsHelper.CalculateMean(sum, count);
Assert.Equal(expectedResult, result);
}
