protected override void UpdateLevelsValues(List<List<SamplePrimitive>> primitives, MobileObservableCollection<SampleUnit> samples)
{
var dataList = primitives.SelectMany(x => x.Select(y => !((bool)y.SampleValue)));
var dataSum = dataList.Sum(x => Convert.ToInt32(x));
var dataCount = dataList.Count();
var p = 0.0;
var np = 0.0;
var delta = 0.0;
if (samples.Any())
{
p = (double) dataSum/dataCount;
np = ParentPanel.SubgroupSize * p;
delta = 3 * Math.Sqrt(np * (1 - p));
Mean = Math.Round(np, 2);
UCL = Math.Round(Mean + delta, 2);
LCL = Math.Round(Math.Max(Mean - delta, 0), 2);
}
foreach (var sample in samples)
{
sample.SetUCL(UCL);
sample.SetMean(Mean);
sample.SetLCL(LCL);
sample.SetUCL(ParentPanel.CustomUCL, true);
sample.SetLCL(ParentPanel.CustomLCL, true);
sample.SetUSL(ParentPanel.USL);
sample.SetLSL(ParentPanel.LSL);
}
}
protected override void UpdateLevelsValues(List<List<SamplePrimitive>> primitives, MobileObservableCollection<SampleUnit> samples)
{
Mean = samples.Any() ? Math.Round(samples.Average(x => (double)x.SampleValue), 2) : 0;
foreach (var sample in samples)
{
sample.SetUCL(UCL);
sample.SetMean(Mean);
sample.SetLCL(LCL);
sample.SetUCL(ParentPanel.CustomUCL, true);
sample.SetLCL(ParentPanel.CustomLCL, true);
sample.SetUSL(ParentPanel.USL);
sample.SetLSL(ParentPanel.LSL);
}
}
protected override void UpdateLevelsValues(List<List<SamplePrimitive>> primitives, MobileObservableCollection<SampleUnit> samples)
{
Mean = samples.Any(x => x.SampleValue != null) ? Math.Round(samples.Where(x => x.SampleValue != null).Average(x => (double)x.SampleValue), 2) : 0;
UCL = Math.Round(Mean * StatisticConstants.D4(ParentPanel.SubgroupSize), 2);
LCL = Math.Round(Math.Max(Mean * StatisticConstants.D3(ParentPanel.SubgroupSize), 0), 2);
foreach (var sample in samples)
{
sample.SetUCL(UCL);
sample.SetMean(Mean);
sample.SetLCL(LCL);
sample.SetUCL(ParentPanel.CustomUCL, true);
sample.SetLCL(ParentPanel.CustomLCL, true);
sample.SetUSL(ParentPanel.USL);
sample.SetLSL(ParentPanel.LSL);
}
}
protected override void UpdateLevelsValues(List<List<SamplePrimitive>> primitives, MobileObservableCollection<SampleUnit> samples)
{
var stdDevAv = samples.Any() ? Math.Round(samples.Average(x => (double)x.SampleValue), 2) : 0;
Mean = Math.Round(stdDevAv, 3);
UCL = Math.Round(StatisticConstants.B4(ParentPanel.SubgroupSize) * Mean, 2);
LCL = Math.Round(StatisticConstants.B3(ParentPanel.SubgroupSize) * Mean, 2);
foreach (var sample in samples)
{
sample.SetUCL(UCL);
sample.SetMean(Mean);
sample.SetLCL(LCL);
sample.SetUCL(ParentPanel.CustomUCL, true);
sample.SetLCL(ParentPanel.CustomLCL, true);
sample.SetUSL(ParentPanel.USL);
sample.SetLSL(ParentPanel.LSL);
}
}
protected override void UpdateLevelsValues(List<List<SamplePrimitive>> primitives, MobileObservableCollection<SampleUnit> samples)
{
var rValues = primitives.Select(t => t.Select(x => (double)x.SampleValue).Range()).ToList();
Mean = samples.Any() ? Math.Round(samples.Average(x => (double)x.SampleValue), 2) : 0;
var rBar = rValues.Any() ? rValues.Average() : 0;
UCL = Math.Round(rBar * StatisticConstants.D4(ParentPanel.SubgroupSize), 2);
LCL = Math.Round(rBar * StatisticConstants.D3(ParentPanel.SubgroupSize), 2);
foreach (var sample in samples)
{
sample.SetUCL(UCL);
sample.SetMean(Mean);
sample.SetLCL(LCL);
sample.SetUCL(ParentPanel.CustomUCL, true);
sample.SetLCL(ParentPanel.CustomLCL, true);
sample.SetUSL(ParentPanel.USL);
sample.SetLSL(ParentPanel.LSL);
}
}
private IFilterDescriptor PrepareFilter()
{
var list = new MobileObservableCollection<IFilterDescriptor>();
foreach (var filter in _filterValues)
{
list.Add(new FilterDescriptor(filter.Key, FilterOperator.Contains, filter.Value));
}
return list.Any() ? new FilterDescriptor(LogicalOperators.And, list) : null;
}
protected override void UpdateLevelsValues(List<List<SamplePrimitive>> primitives, MobileObservableCollection<SampleUnit> samples)
{
var dataList = primitives.SelectMany(x => x.Select(y => !((bool) y.SampleValue)));
var dataSum = dataList.Sum(x => Convert.ToInt32(x));
var dataCount = dataList.Count();
var averageSampleSize = primitives.Select(x => x.Count).Average();
Mean = samples.Any() ? Math.Round((double) dataSum / dataCount, 4) : 0;
var delta = 3 * Math.Sqrt((Mean * (1 - Mean)) / averageSampleSize);
UCL = Math.Round(Math.Min(Mean + delta, 1), 4);
LCL = Math.Round(Math.Max(Mean - delta, 0), 4);
foreach (var sample in samples)
{
if (AverageLimits)
{
sample.SetUCL(UCL);
sample.SetMean(Mean);
sample.SetLCL(LCL);
}
else
{
delta = 3 * Math.Sqrt((Mean * (1 - Mean)) / sample.SampleSize);
sample.SetUCL(Math.Round(Math.Min(Mean + delta, 1), 4));
sample.SetMean(Mean);
sample.SetLCL(Math.Round(Math.Max(Mean - delta, 0), 4));
}
sample.SetUCL(ParentPanel.CustomUCL, true);
sample.SetLCL(ParentPanel.CustomLCL, true);
sample.SetUSL(ParentPanel.USL);
sample.SetLSL(ParentPanel.LSL);
}
}
private void ResolveLimitsCalculationMethod(List<List<SamplePrimitive>> primitives, MobileObservableCollection<SampleUnit> samples)
{
var allRenderedCharts = ParentPanel.Charts.Select(x => x.ChartType);
if (allRenderedCharts.Contains(ChartTypesEnum.RChart))
{
var rValues = new List<double>();
for (var i = 0; i < primitives.Count; i++)
rValues.Add(primitives[i].Select(x => (double)x.SampleValue).Range());
var rBar = rValues.Any() ? rValues.Average() : 0;
Mean = samples.Any() ? Math.Round(samples.Average(x => (double)x.SampleValue), 2) : 0;
var a2 = StatisticConstants.A2(ParentPanel.SubgroupSize);
UCL = Math.Round(Mean + rBar * a2, 2);
LCL = Math.Round(Mean - rBar * a2, 2);
}
else if (allRenderedCharts.Contains(ChartTypesEnum.StDevChart))
{
var stDevList = new List<double>();
for (var i = 0; i < primitives.Count; i++)
{
var data = primitives[i].Select(x => x.SampleValue).Cast<double>();
var calculatedValue = data != null && data.Any() ? Math.Round(data.StdDev(), 3) : 0;
stDevList.Add(calculatedValue);
}
var stdDevAv = stDevList.Any() ? stDevList.Average() : 0;
Mean = samples.Any() ? Math.Round(samples.Average(x => (double)x.SampleValue), 2) : 0;
var a3 = StatisticConstants.A3(ParentPanel.SubgroupSize);
UCL = Math.Round(Mean + stdDevAv * a3, 2);
LCL = Math.Round(Mean - stdDevAv * a3, 2);
}
else if (allRenderedCharts.Contains(ChartTypesEnum.XMRChart))
{
var mrList = new List<double>();
var list = primitives.SelectMany(x => x.Select(y => y.SampleValue)).Cast<double>().ToList();
for (var i = 0; i < list.Count; i++)
{
if (i >= ParentPanel.SubgroupSize - 1)
{
var data = list.GetRange(i - (ParentPanel.SubgroupSize - 1), ParentPanel.SubgroupSize);
var sampleValue = data != null && data.Any() ? (double?)Math.Abs(data.Max() - data.Min()) : null;
if (sampleValue.HasValue)
mrList.Add(sampleValue.Value);
}
}
var mrAv = mrList.Any() ? mrList.Average() : 0;
Mean = samples.Any() ? Math.Round(samples.Average(x => (double)x.SampleValue), 2) : 0;
var d2 = StatisticConstants.d2(ParentPanel.SubgroupSize);
UCL = Math.Round(Mean + 3 * (mrAv / d2), 2);
LCL = Math.Round(Mean - 3 * (mrAv / d2), 2);
}
}
private void AddMandatoryFilter(MobileObservableCollection<IFilterDescriptor> filterList, string processSystemName)
{
var filterInfoType = DynamicTypeManager.GetFilterInfoType(processSystemName);
if (filterInfoType != null)
{
IFilter[] filters = (IFilter[])filterInfoType.GetProperty("FilterList", BindingFlags.Static | BindingFlags.Public).GetValue(null, null);
if (filters != null)
{
IList<int> identityRoles = ((Library.Security.MQ1Identity)ApplicationContext.User.Identity).RolesId;
if (identityRoles == null || identityRoles.Count == 0) return;
var mandatoryFilters = filters.Where(x => !string.IsNullOrEmpty(x.RoleIds));
foreach (IFilter filter in mandatoryFilters)
{
var filterRoles = filter.RoleIds.Split(',').Select(int.Parse).ToList();
if (filterRoles.Contains(Constants.AllRolesId) || identityRoles.Intersect(filterRoles).Any())
{
IFilterDescriptor filterDescriptor = (FilterDescriptor)FilterDescriptor.FromJSON(filter.Definition);
var filterValue = filterDescriptor.Value as FilterValue;
if (filterValue != null && filterValue.Type == FilterValueType.Udp)
filterValue.ProvidedValue = filterValue.DefaultValue;
filterDescriptor.ReplacePredefinedValues(null);
if (!filterList.Any(f => f.FilterGuid.Equals(filterDescriptor.FilterGuid)))
filterList.Add(filterDescriptor);
}
}
}
}
}
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;
}
}
/// <summary>
/// Updates the list.
/// </summary>
/// <param name="newValue">The new value.</param>
/// <param name="list">The list.</param>
private void UpdateList(MobileObservableCollection<DisponibleProcess> newValue, IList<IRecentEntry> list)
{
for (var i = list.Count - 1; i >= 0 ; i--)
{
if (!newValue.Any(e => e.ProcessId == list[i].Id && e.ProcessName == list[i].Name))
//new environment or process renamed/removed
list.Remove(list[i]);
}
}
