public static BoxAndWhisker OutlierQuartileMedian(double[] data, double xPosition)
{
var baw = new BoxAndWhisker(xPosition, data);
var stats = new PopulationStats(data);
baw.midline.position = stats.median;
baw.whisker.max = stats.highOutliers.Length == 0 ? stats.maxNonOutlier : stats.Q3 + 1.5 * stats.IQR;
baw.whisker.min = stats.lowOutliers.Length == 0 ? stats.minNonOutlier : stats.Q1 - 1.5 * stats.IQR;
baw.box.max = stats.Q3;
baw.box.min = stats.Q1;
return(baw);
}
public static BoxAndWhisker StdevStderrMean(double[] data, double xPosition)
{
var baw = new BoxAndWhisker(xPosition, data);
var stats = new PopulationStats(data);
baw.midline.position = stats.median;
baw.whisker.max = stats.max;
baw.whisker.min = stats.min;
baw.box.max = stats.mean + stats.stDev;
baw.box.min = stats.mean - stats.stDev;
return(baw);
}
public static BoxAndWhisker GetBoxAndWhisker_OutliersAndQuartiles(double[] data, double xPosition)
{
var baw = new BoxAndWhisker(xPosition);
var stats = new PopulationStats(data);
baw.midline.position = stats.median;
baw.whisker.max = stats.highOutliers.Length == 0 ? stats.maxNonOutlier : stats.Q3 + 1.5 * stats.IQR;
baw.whisker.min = stats.lowOutliers.Length == 0 ? stats.minNonOutlier : stats.Q1 - 1.5 * stats.IQR;
baw.box.max = stats.Q3;
baw.box.min = stats.Q1;
List <double> pointsList = new List <double>();
pointsList.AddRange(stats.highOutliers);
pointsList.AddRange(stats.lowOutliers);
baw.points = pointsList.ToArray();
return(baw);
}
