/// <summary>
/// Calculates the a term (slope) of the linear regression function (y = a*x + b)
/// given the Y and X values.
/// </summary>
/// <param name="y">Y values</param>
/// <param name="x">X values</param>
/// <returns>The a term of y = a*x + b</returns>
public static double ATerm2(Statistics y, Statistics x)
{
try
{
return Covariance(y, x) / (Math.Pow(x.StdDev(), 2));
}
catch (Exception)
{
return double.NaN;
}
}
/// <summary>
/// Calculates the correlation coefficient between two sets
/// of numbers.
/// </summary>
/// <param name="s1">First set of numbers</param>
/// <param name="s2">Second set of numbers</param>
/// <returns>Correlation coefficient</returns>
public static double R(Statistics s1, Statistics s2)
{
try
{
return Covariance(s1, s2)/(s1.StdDev()*s2.StdDev());
}
catch (Exception)
{
return double.NaN;
}
}
private static PointPair CreatePointPair(int iGroup, ICollection<double> listValues, ref double maxY)
{
if (listValues.Count == 0)
return PointPairMissing(iGroup);
var statValues = new Statistics(listValues);
PointPair pointPair;
if (Settings.Default.ShowPeptideCV)
{
double cvRatio = statValues.StdDev() / statValues.Mean();
if (!Settings.Default.PeakDecimalCv)
cvRatio *= 100;
pointPair = MeanErrorBarItem.MakePointPair(iGroup, cvRatio, 0);
}
else
pointPair = MeanErrorBarItem.MakePointPair(iGroup, statValues.Mean(), statValues.StdDev());
maxY = Math.Max(maxY, MeanErrorBarItem.GetYTotal(pointPair));
return pointPair;
}
public SummaryValue(Statistics statistics)
{
Mean = statistics.Mean();
if (statistics.Length > 1)
{
Stdev = statistics.StdDev();
Cv = Stdev/Mean;
}
}
public static RatioValue Calculate(IList<double> numerators, IList<double> denominators)
{
if (numerators.Count != denominators.Count)
{
throw new ArgumentException();
}
if (numerators.Count == 0)
{
return null;
}
if (numerators.Count == 1)
{
return new RatioValue(numerators.First()/denominators.First());
}
var statsNumerators = new Statistics(numerators);
var statsDenominators = new Statistics(denominators);
var ratios = new Statistics(numerators.Select((value, index) => value/denominators[index]));
// The mean ratio is the average of "ratios" weighted by "statsDenominators".
// It's also equal to the sum of the numerators divided by the sum of the denominators.
var meanRatio = statsNumerators.Sum()/statsDenominators.Sum();
// Helpers.Assume(Math.Abs(mean - stats.Mean(statsW)) < 0.0001);
// Make sure the value does not exceed the bounds of a float.
float meanRatioFloat = (float)Math.Min(float.MaxValue, Math.Max(float.MinValue, meanRatio));
return new RatioValue
{
Ratio = meanRatioFloat,
StdDev = (float) ratios.StdDev(statsDenominators),
DotProduct = (float) statsNumerators.Angle(statsDenominators),
};
}