public void UpdateLevelValues(MobileObservableCollection<SampleUnit> samples, bool recalculateSamples = false)
{
if (recalculateSamples)
{
var sampleList = OriginalData.Select(item => new SamplePrimitive(item.YValue, 0, "Number")).ToList();
samples.Clear();
foreach (var computeSubgroup in ComputeSubgroups(sampleList, 0, 0))
samples.Add(computeSubgroup);
return;
}
var minX = 0.0;
var maxx = 0.0;
var standardStepCount = GetStepCount(OriginalData.Count);
_minimum = OriginalData.Count > 0 ? Math.Floor(OriginalData.Min(x => (double)x.YValue)) : 0;
var max = OriginalData.Count > 0 ? OriginalData.Max(x => (double)x.YValue) : 0;
var integerMax = Math.Ceiling(max);
if ((max % integerMax).Equals(0.0))
integerMax++;
_maximum = integerMax;
_stepWidth = Math.Abs(_maximum - _minimum) / ParentPanel.RangeSteps;
if (_stepWidth > 1 && ParentPanel.RangeSteps == standardStepCount)
{
_stepWidth = Convert.ToInt32(_stepWidth);
ParentPanel.SetSilently(ChartPanel.ExponentProperty, 0);
}
else
{
var e = ParentPanel.Exponent == 0 ? (int) Math.Ceiling(Math.Log10(1/_stepWidth)) : ParentPanel.Exponent;
if (ParentPanel.Exponent < e)
ParentPanel.SetSilently(ChartPanel.ExponentProperty, e);
else
e = ParentPanel.Exponent;
_stepWidth = Math.Round(_stepWidth, e);
}
if (samples.Any())
_maximum = Convert.ToDouble(samples.Last().CategoryValue.LabelValue, CultureInfo.InvariantCulture);
var list = new List<double>();
if (ShowLSL)
list.Add(ParentPanel.LSL);
list.Add(UseCustomCLs ? ParentPanel.CustomLCL : LCL);
list.Add(_minimum);
minX = list.Min();
list = new List<double>();
if (ShowUSL)
list.Add(ParentPanel.USL);
list.Add(UseCustomCLs ? ParentPanel.CustomUCL : UCL);
list.Add(_maximum);
maxx = list.Max();
var deltaMin = _minimum - minX;
if (deltaMin > 0)
{
var newDelta = deltaMin + (_stepWidth - (deltaMin % _stepWidth));
var deltaLength = newDelta / _stepWidth;
var startValue = _minimum - _stepWidth;
for (var i = 0; i < deltaLength; i++)
{
var subgroupSample = SpcManager.CreateSample(null, 0, i);
subgroupSample.SetXLabelValue(startValue, LabelValueDataTypes.Number);
subgroupSample.SetSampleSize(0);
samples.Insert(0, subgroupSample);
startValue -= _stepWidth;
}
_minimum = startValue + _stepWidth;
}
else
{
var sample = SpcManager.CreateSample(null, 0, 0);
sample.SetXLabelValue(_minimum - _stepWidth, LabelValueDataTypes.Number);
sample.SetSampleSize(0);
samples.Insert(0, sample);
}
var deltaMax = maxx - _maximum;
if (deltaMax > 0)
{
var newDelta = deltaMax + (_stepWidth - (deltaMax % _stepWidth));
var deltaLength = newDelta / _stepWidth;
var startValue = _maximum + _stepWidth;
for (var i = 0; i < deltaLength; i++)
{
var subgroupSample = SpcManager.CreateSample(null, 0, i);
subgroupSample.SetXLabelValue(startValue, LabelValueDataTypes.Number);
subgroupSample.SetSampleSize(0);
samples.Add(subgroupSample);
startValue += _stepWidth;
}
_maximum = startValue - _stepWidth;
}
else
{
var sample = SpcManager.CreateSample(null, 0, 0);
sample.SetXLabelValue(_maximum + _stepWidth, LabelValueDataTypes.Number);
sample.SetSampleSize(0);
samples.Add(sample);
}
for (var i = 0; i < samples.Count; i++)
{
samples[i].SetIndex(i);
samples[i].CategoryValue.Index = i;
}
MinXValue = _minimum = deltaMin > 0 ? _minimum : _minimum - _stepWidth;
MaxXValue = _maximum = deltaMax > 0 ? _maximum + _stepWidth : _maximum + _stepWidth * 2;
XStep = _stepWidth;
BellCurveData = new MobileObservableCollection<ElementarySampleInfo>();
var nh = 0.0;
if (OriginalData != null)
nh = (OriginalData.Count * XStep); //needed to bring bell curve to the scale of histogram
var floatingSigma = Mean - 4 * Sigma;
for (var i = 0; i < 49; i++)
{
var value = (1 / (Sigma * Math.Sqrt(2 * Math.PI))) * Math.Pow(Math.E, -0.5 * Math.Pow((floatingSigma - Mean) / Sigma, 2)) * nh;
BellCurveData.Add(DataPortal.Fetch<ElementarySampleInfo>(new LimitData(floatingSigma, value)));
floatingSigma += 1 / 6.0 * Sigma;
}
}
