internal void Update(VisualOdometer visualOdometer)
{
if (!this.Created)
{
return;
}
List <double> headingChanges = visualOdometer.RotationAnalyzer.MeasuredRotationIncrements;
if (headingChanges.Count == 0)
{
return;
}
double[] degreeAngles = new double[headingChanges.Count];
for (int i = 0; i < headingChanges.Count; i++)
{
degreeAngles[i] = headingChanges[i] * s_RadToDegree;
}
m_Histogram.Fill(degreeAngles);
m_HistogramSeries.Points.Clear();
for (int i = 0; i < m_Histogram.BinsCount; i++)
{
HistogramBin bin = m_Histogram[i];
// Add data point into the histogram series
double x = (bin.Min + bin.Max) / 2.0;
m_HistogramSeries.Points.AddXY(x, bin.Count);
}
m_CurrentHeadingChangeSeries.Points.Clear();
m_CurrentHeadingChangeSeries.Points.AddXY(visualOdometer.RotationAnalyzer.HeadingChange.Degrees, 0);
m_CurrentHeadingChangeAnnotation.AnchorDataPoint = m_CurrentHeadingChangeSeries.Points[0];
}
public static HistogramBin[] Histogram(this IList <MetaNum> self, int binCount = -1, double binWidth = double.NaN)
{
var min = (double)self.Min();
var max = (double)self.Max();
HistogramInterval intervals;
if (!double.IsNaN(binWidth))
{
intervals = HistogramHelper.GetHistogramIntervalFromBinWidth(min, max, binWidth);
}
else
{
if (binCount < 0)
{
binCount = HistogramHelper.GetBinCount(min, max, self.Count);
}
intervals = HistogramHelper.GetHistogramIntervalFromBinCount(min, max, binCount);
}
var collect = CollectHistogram(self, intervals);
var counts = collect.Item1;
var total = collect.Item2;
return(HistogramBin.CreateHistogram(intervals, counts, total));
}
public static PlotModel CreateNormalDistributionHistogram(int n, int binCount)
{
var bins = new HistogramBin[binCount];
double min = -10;
double max = 10;
for (int i = 0; i < bins.Length; i++)
{
var v = min + (max - min) * i / (bins.Length - 1);
bins[i] = new HistogramBin {
Label = v.ToString("0.0")
};
}
var r = new Random(31);
for (int i = 0; i < n; i++)
{
// http://en.wikipedia.org/wiki/Box%E2%80%93Muller_transform
var u1 = r.NextDouble();
var u2 = r.NextDouble();
var v = Math.Sqrt(-2 * Math.Log(u1)) * Math.Cos(2 * Math.PI * u2);
int bin = (int)Math.Round((v - min) / (max - min) * (bins.Length - 1));
if (bin >= 0 && bin < bins.Length)
{
bins[bin].Value++;
}
}
var temp = new PlotModel {
Title = string.Format("Histogram (bins={0}, n={1})", binCount, n), Subtitle = "Standard normal distribution by Box-Muller transform"
};
var series1 = new TSeries {
ItemsSource = bins, ValueField = "Value"
};
temp.Series.Add(series1);
var categoryAxis = new CategoryAxis
{
Position = CategoryAxisPosition(),
GapWidth = 0
};
categoryAxis.Labels.AddRange(bins.Select(b => b.Label));
categoryAxis.IsAxisVisible = false;
temp.Axes.Add(categoryAxis);
// todo: link category and linear axis
temp.Axes.Add(new LinearAxis {
Position = CategoryAxisPosition(), Minimum = min, Maximum = max
});
temp.Axes.Add(new LinearAxis {
Position = ValueAxisPosition(), MinimumPadding = 0, AbsoluteMinimum = 0
});
return(temp);
}
private void InitializeHistogramChart()
{
m_HistogramSeries = m_Chart.Series.Add("Histogram");
// Set new series chart type and other attributes
m_HistogramSeries.ChartType = SeriesChartType.Column;
m_HistogramSeries.BorderColor = Color.Black;
m_HistogramSeries.BorderWidth = 1;
m_HistogramSeries.BorderDashStyle = ChartDashStyle.Solid;
m_HistogramSeries["PointWidth"] = "1.0";
m_HistogramSeries["BarLabelStyle"] = "Center";
// Adjust chart area
ChartArea chartArea = m_Chart.ChartAreas[m_HistogramSeries.ChartArea];
//chartArea.AxisY.Title = "Frequency";
chartArea.AxisX.Minimum = 3;
chartArea.AxisX.Maximum = 18;
//Series series1 = new Series();
//m_Chart.Series.Add(series1);
//for (int index = 3; index < 19; index++)
//{
// m_HistogramSeries.Points.AddXY(index, 2 * index);
//}
for (int i = 0; i < m_Data.Histogram.BinsCount; i++)
{
HistogramBin bin = m_Data.Histogram[i];
// Add data point into the histogram series
double x = (bin.Min + bin.Max) / 2.0;
m_HistogramSeries.Points.AddXY(x, bin.Count);
}
}
public static PlotModel CreateHistogram(int n, int binCount)
{
var bins = new HistogramBin[binCount];
for (int i = 0; i < bins.Length; i++)
{
bins[i] = new HistogramBin {
Label = i.ToString()
};
}
var r = new Random(31);
for (int i = 0; i < n; i++)
{
int value = r.Next(binCount);
bins[value].Value++;
}
var temp = new PlotModel {
Title = string.Format("Histogram (bins={0}, n={1})", binCount, n), Subtitle = "Pseudorandom numbers"
};
var series1 = new TSeries {
ItemsSource = bins, ValueField = "Value"
};
if (binCount < 100)
{
series1.LabelFormatString = "{0}";
}
temp.Series.Add(series1);
temp.Axes.Add(new CategoryAxis {
Position = CategoryAxisPosition(), ItemsSource = bins, LabelField = "Label", GapWidth = 0
});
temp.Axes.Add(new LinearAxis {
Position = ValueAxisPosition(), MinimumPadding = 0, MaximumPadding = 0.1, AbsoluteMinimum = 0
});
return(temp);
}
public static List <HistogramBin> BinData(List <double> theData, double minBin, double maxBin, int noBins, bool discardValuesBeyondMinMax)
{
if (discardValuesBeyondMinMax)
{
int itemsRemoved = theData.RemoveAll(a => a <minBin || a> maxBin);
//Console.WriteLine(itemsRemoved + " items removed when generating histogram; out of bounds");
}
List <HistogramBin> histogramBins = new List <HistogramBin>(noBins);
theData.Sort();
double interval = (maxBin - minBin) / noBins;
double intervalFloor = minBin;
//Create all bins
for (double i = 0; i <= noBins; i++)
{
histogramBins.Add(new HistogramBin(minBin + i * interval));
}
//Fill the bins
foreach (double d in theData)
{
HistogramBin b = histogramBins.Find(a => a.IntervalFloor > d && d < a.IntervalFloor + interval);
try
{
b.TheData.Add(d);
}
catch
{
Console.WriteLine("Null Bin");
}
}
Normalize(histogramBins);
return(histogramBins);
}
public static List <HistogramBin> BinData(List <double> theData, int noBins)
{
if (theData.Count == 0)
{
throw new Exception("No datapoint provided for binning");
}
List <HistogramBin> histogramBins = new List <HistogramBin>(noBins);
double min = theData.Min();
double max = theData.Max();
double delta = max - min;
double step = delta / noBins;
theData.Sort();
double intervalFloor = double.MinValue;
HistogramBin hb = new HistogramBin(0);
//Fill the bins
intervalFloor = min;
foreach (double datapoint in theData)
{
if (datapoint > (intervalFloor + step))
{
hb = new HistogramBin(datapoint);
hb.TheData.Add(datapoint);
histogramBins.Add(hb);
intervalFloor += step;
}
else
{
hb.TheData.Add(datapoint);
}
}
Normalize(histogramBins);
return(histogramBins);
}
public static List <HistogramBin> BinData(List <int> theData)
{
if (theData.Count == 0)
{
throw new Exception("No datapoint provided for binning");
}
List <HistogramBin> histogramBins = new List <HistogramBin>();
var groups = from integer in theData
group integer by integer into theBin
select new { theBin.Key, theBin };
foreach (var group in groups)
{
HistogramBin h = new HistogramBin((double)group.Key);
h.TheData = group.theBin.Select(a => (double)a).ToList();
histogramBins.Add(h);
}
return(histogramBins);
}
public static HistogramBin[] Histogram <T>(this IEnumerable <T> list, Func <T, float> select, int bins)
{
var result = new HistogramBin[bins];
var min = list.Min(v => select(v));
var max = list.Max(v => select(v));
if (min == max)
{
return(result);
}
for (int i = 0; i < bins; ++i)
{
result[i].Start = i * ((max - min) / bins) + min;
}
foreach (var one in list)
{
var ix = Math.Min(result.Length - 1, (int)((bins * (select(one) - min)) / (max - min)));
++result[ix].Count;
}
return(result);
}
public static PlotModel Histogram()
{
int n = 1000;
int binCount = 20;
var bins = new HistogramBin[binCount];
for (int i = 0; i < bins.Length; i++)
{
bins[i] = new HistogramBin {
Label = i.ToString()
};
}
var r = new Random();
for (int i = 0; i < n; i++)
{
int value = r.Next(binCount);
bins[value].Value++;
}
var temp = new PlotModel();
var series1 = new TSeries {
ItemsSource = bins, ValueField = "Value"
};
temp.Series.Add(series1);
temp.Axes.Add(new CategoryAxis {
Position = CategoryAxisPosition(), ItemsSource = bins, LabelField = "Label", GapWidth = 0
});
temp.Axes.Add(new LinearAxis {
Position = ValueAxisPosition(), MinimumPadding = 0, AbsoluteMinimum = 0
});
return(temp);
}
public static HistogramBin[] Histogram <T>(this IEnumerable <T> list,
Func <T, float> select,
int bins,
float lowerabsdevs = float.MaxValue,
float upperabsdevs = float.MaxValue)
{
if (list == null || !list.Any())
{
return(default(HistogramBin[]));
}
var dbgcount = list.Count();
var result = new HistogramBin[bins];
float avg = 0f;
float absdev = 0f;
var values = list.Select(v => select(v));
if (lowerabsdevs != float.MaxValue || upperabsdevs != float.MaxValue)
{
avg = values.Average();
absdev = values.AbsDev();
}
var min = values.Min();
var max = values.Max();
if (lowerabsdevs != float.MaxValue && list.Count() > 3)
{
min = Math.Max(avg - absdev * lowerabsdevs, min);
}
if (upperabsdevs != float.MaxValue && list.Count() > 3)
{
max = Math.Min(avg + absdev * upperabsdevs, max);
}
if (min == max)
{
return(result);
}
for (int i = 0; i < bins; ++i)
{
result[i].Start = i * ((max - min) / bins) + min;
}
foreach (var one in values)
{
var val = one;
if (lowerabsdevs != float.MaxValue && list.Count() > 3)
{
val = Math.Max(avg - absdev * lowerabsdevs, val);
}
if (upperabsdevs != float.MaxValue && list.Count() > 3)
{
val = Math.Min(avg + absdev * upperabsdevs, val);
}
var ix = Math.Max(0,
Math.Min(
result.Length - 1,
(int)((bins * (val - min)) / (max - min))));
++result[ix].Count;
}
return(result);
}
