private void btn_simulate_Click(object sender, RoutedEventArgs e)
{
int nbrSim = Convert.ToInt32(txt_nbrsim.Text);
double initWealth = Properties.Settings.Default.InitWealth;
List<double> finalEarnings = new List<double>();
List<int> counts = new List<int>();
for (int i = 0; i < nbrSim; i++)
{
MartStrategy MStrat = new MartStrategy(5, 250, initWealth);
double bid = MStrat.Bet();
Number res;
double payoff;
int count = 0;
while (bid <= MStrat.Wealth)
{
MStrat.PlaceBet(bid);
res = _RGame.Play();
payoff = _RGame.GetPayoffColor(NumberColor.Red, bid, res);
MStrat.Setup(payoff);
bid = MStrat.Bet();
count++;
}
finalEarnings.Add(MStrat.Earnings-initWealth);
counts.Add(count);
}
txt_earnings.Text = finalEarnings.Average().ToString();
txt_plays.Text = counts.Average().ToString();
txt_maxEarnings.Text = finalEarnings.Max().ToString();
txt_maxLosses.Text = finalEarnings.Min().ToString();
txt_totEarnings.Text = finalEarnings.Where(x => x > 0).Sum().ToString();
txt_totLosses.Text = finalEarnings.Where(x => x < 0).Sum().ToString();
txt_balance.Text = finalEarnings.Sum().ToString();
}
//At the end of a trajectory, this updates the row with final info
public void updateTrajectory()
{
try
{
TrajectoryDbDataSet.trajectoriesRow currentRow = Globals.ds.trajectories.FindByt_id(this.t_id);
//update row with final values
//currentRow.end_time = DateTime.Now;
//Average velocity and direction
double velocitySum = 0;
int directionSumH = 0;
int directionSumV = 0;
int rows = 0;
List<double> velocities = new List<double>();
List<double> velocities_filtered = new List<double>();
TrajectoryDbDataSet.pointsRow[] pointrows = Globals.ds.points.Select(String.Format("t_id = {0}", t_id)) as TrajectoryDbDataSet.pointsRow[];
foreach (TrajectoryDbDataSet.pointsRow row in pointrows)
{
velocities.Add((double)row[5]);
directionSumH += Direction.Contains("E") ? 1 : 0;
directionSumV += Direction.Contains("N") ? 1 : 0;
velocities_filtered.Add(Math.Sqrt(row.vx * row.vx + row.vz * row.vz));
rows++;
if (rows == pointrows.Count())
{
currentRow.end_time = currentRow.start_time.AddMilliseconds(row.milliseconds);
}
}
///<summary>
///Filtering out outliers. Find the standard deviation of all velocity values. If values lie outside of two standard
///deviations they are ignored from the average velocity calculation.
double mean = velocities.Average();
double stdev = StandardDeviation(velocities);
int n = 0;
foreach (double v in velocities)
{
if (v > (mean - 2* stdev) && v < (mean + 2*stdev))
{
velocitySum += v;
n++;
}
}
double tester = velocitySum/n;
currentRow.average_velocity = (tester.CompareTo(double.NaN)>0) ? tester: mean;
currentRow.average_direction = ((directionSumV / rows > 0.5) ? "N" : "S") + ((directionSumH / rows > 0.5) ? "E" : "W");
currentRow.length = this.Distance;
currentRow.speed_kalmanized = velocities_filtered.Average();
}
catch (Exception e)
{
return;
}
}
/// <summary>
/// CreateRandomList
/// </summary>
/// <returns></returns>
private List<Value> CreateRandomValueList()
{
List<Value> List = new List<Value>();
for (int i = 0; i < LIST_SIZE; i++)
List.Add(new Value(i, RandomDouble(0,10,3)));
if (TheResult == null)
TheResult = new Result();
TheResult.ResultValue = List.Average<Value>(x => x.DValue);
return List;
}
private void Button_Click(object sender, RoutedEventArgs e)
{
//LUCAS
try
{
Random rand = new Random(42);
List<int> numbers = new List<int>();
ListDisjointSet<int> disjointSet;
disjointSet = new ListDisjointSet<int>();
Stopwatch iterationTimer = new Stopwatch();
List<long> ticksList = new List<long>();
for (int i = 0; i < 10000; i++)
{
int n = rand.Next();
numbers.Add(n);
iterationTimer.Start();
disjointSet.MakeSet(n);
iterationTimer.Stop();
ticksList.Add(iterationTimer.ElapsedTicks);
iterationTimer.Reset();
}
mksetOne.Text = String.Format("Avg : {0}, Max: {1}, Min: {2}", ticksList.Average(), ticksList.Max(), ticksList.Min());
ticksList.Clear();
for (int i = 0; i < numbers.Count * 3; i++)
{
int lookup = numbers[rand.Next(numbers.Count)];
iterationTimer.Start();
disjointSet.Find(lookup);
iterationTimer.Stop();
ticksList.Add(iterationTimer.ElapsedTicks);
iterationTimer.Reset();
}
findOne.Text = String.Format("Avg : {0}, Max: {1}, Min: {2}", ticksList.Average(), ticksList.Max(), ticksList.Min());
ticksList.Clear();
for (int i = 0; i < numbers.Count * 3; i++)
{
int lookupA = numbers[rand.Next(numbers.Count)];
int lookupB = numbers[rand.Next(numbers.Count)];
iterationTimer.Start();
disjointSet.Union(disjointSet.Find(lookupA), disjointSet.Find(lookupB));
iterationTimer.Stop();
ticksList.Add(iterationTimer.ElapsedTicks);
iterationTimer.Reset();
}
unionOne.Text = String.Format("Avg : {0}, Max: {1}, Min: {2}", ticksList.Average(), ticksList.Max(), ticksList.Min());
}
catch (Exception err)
{
Console.WriteLine(err.StackTrace);
}
//PAUL
try
{
Random rand = new Random(42);
List<int> numbers = new List<int>();
DisjointDataSet<int> disjointSet;
disjointSet = new DisjointDataSet<int>();
Stopwatch iterationTimer = new Stopwatch();
List<long> ticksList = new List<long>();
for (int i = 0; i < 10000; i++)
{
int n = rand.Next();
numbers.Add(n);
iterationTimer.Start();
disjointSet.MakeSet(n);
iterationTimer.Stop();
ticksList.Add(iterationTimer.ElapsedTicks);
iterationTimer.Reset();
}
mksetTwo.Text = String.Format("Avg : {0}, Max: {1}, Min: {2}", ticksList.Average(), ticksList.Max(), ticksList.Min());
ticksList.Clear();
for (int i = 0; i < numbers.Count * 3; i++)
{
int lookup = numbers[rand.Next(numbers.Count)];
iterationTimer.Start();
disjointSet.Find(lookup);
iterationTimer.Stop();
ticksList.Add(iterationTimer.ElapsedTicks);
iterationTimer.Reset();
}
findTwo.Text = String.Format("Avg : {0}, Max: {1}, Min: {2}", ticksList.Average(), ticksList.Max(), ticksList.Min());
ticksList.Clear();
for (int i = 0; i < numbers.Count * 3; i++)
{
int lookupA = numbers[rand.Next(numbers.Count)];
int lookupB = numbers[rand.Next(numbers.Count)];
iterationTimer.Start();
disjointSet.Union(lookupA, lookupB);
iterationTimer.Stop();
ticksList.Add(iterationTimer.ElapsedTicks);
iterationTimer.Reset();
}
unionTwo.Text = String.Format("Avg : {0}, Max: {1}, Min: {2}", ticksList.Average(), ticksList.Max(), ticksList.Min());
}
catch (Exception err)
{
Console.WriteLine(err.StackTrace);
}
}
private void buttonDepthErrorEvaluation_Click(object sender, RoutedEventArgs e)
{
//以下改造
MotionDataHandler handler;
string path;
if (openMotionData(out handler, out path))
{
CvMat resultMat = null;
List<double> errorVarList = new List<double>();
int length = handler.FrameCount;
IEnumerable<CvMat> depthImages;
Utility.LoadImages(handler.GetDepthImagePaths(), out depthImages);
foreach (CvMat depthMat in depthImages)
{
double errorVar = DepthUndistortionLinearCalibrator.EvaluateUndistortion(ref resultMat, depthMat, _undistortion);
errorVarList.Add(errorVar);
viewDepthUndistionMat(resultMat, depthMat);
}
displayLabels();
viewDepthUndistionMat(this.UndistortionData.UndistortionDepthMat);
if (errorVarList.Count > 0)
{
double errorVarAvg = errorVarList.Average();
System.Windows.MessageBox.Show(string.Format("誤差分散の平均: {0}", errorVarAvg));
}
}
}
private void buttonScalingScore_Click(object sender, RoutedEventArgs e)
{
int cols, rows;
double horizLength, vertLength;
if (!parseChessboardParameters(out cols, out rows, out horizLength, out vertLength))
{
return;
}
// 以下改造
MotionDataHandler handler;
string path;
if (openMotionData(out handler, out path))
{
CvMat displayMat1 = null;
CvMat displayMat3 = null;
CvMat displayMat4 = null;
CvMat gray = null;
int length = handler.FrameCount;
if (length == 0) { return; }
CvSize boardSize = new CvSize(cols, rows);
CvSize imageSize = new CvSize();
List<Tuple<double, double>> pairs = new List<Tuple<double, double>>();
CvPoint2D32f[] lastCorners = null;
IEnumerable<CvMat> colorImages, depthImages;
Utility.LoadImages(handler.GetColorImagePaths(), out colorImages);
Utility.LoadImages(handler.GetDepthImagePaths(), out depthImages);
var images = colorImages.Zip(depthImages, (first, second) => Tuple.Create(first, second));
foreach (Tuple<CvMat, CvMat> imagePair in images)
{
CvMat imageMat = imagePair.Item1;
CvMat depthMat = imagePair.Item2;
if (displayMat4 == null)
{
displayMat4 = CvEx.InitCvMat(imageMat);
}
imageSize = new CvSize(imageMat.Cols, imageMat.Rows);
CvPoint2D32f[] corners;
int count;
CvEx.InitCvMat(ref gray, imageMat, MatrixType.U8C1);
imageMat.CvtColor(gray, ColorConversion.RgbToGray);
if (gray.FindChessboardCorners(boardSize, out corners, out count, ChessboardFlag.AdaptiveThresh))
{
CvEx.CloneCvMat(ref displayMat1, imageMat);
CvTermCriteria criteria = new CvTermCriteria(50, 0.01);
gray.FindCornerSubPix(corners, count, new CvSize(3, 3), new CvSize(-1, -1), criteria);
CvPoint3D32f?[] cornerPoints = new CvPoint3D32f?[corners.Length];
for (int j = 0; j < corners.Length; j++)
{
CvPoint2D32f corner = corners[j];
double? value = CalcEx.BilateralFilterDepthMatSinglePixel(corner, depthMat, 100, 4, 9);
if (value.HasValue)
{
cornerPoints[j] = new CvPoint3D32f(corner.X, corner.Y, value.Value);
}
}
for (int x = 0; x < cols; x++)
{
for (int y = 0; y < rows; y++)
{
if (!cornerPoints[x + y * cols].HasValue)
continue;
CvPoint3D32f point1 = cornerPoints[x + y * cols].Value;
CvPoint3D64f undistortPoint1 = this.UndistortionData.GetRealFromScreenPos(point1, imageSize);
foreach (var offset in new[] { new { X = 1, Y = 0, D = horizLength }, new { X = 0, Y = 1, D = vertLength } })
{
int dx = x + offset.X;
int dy = y + offset.Y;
if (dx >= cols || dy >= rows)
continue;
if (!cornerPoints[dx + dy * cols].HasValue)
continue;
CvPoint3D32f point2 = cornerPoints[dx + dy * cols].Value;
CvPoint3D64f undistortPoint2 = this.UndistortionData.GetRealFromScreenPos(point2, imageSize);
double distance = Math.Sqrt(CvEx.GetDistanceSq(undistortPoint1, undistortPoint2));
double scale = distance / offset.D;
CvColor color = CalcEx.HSVtoRGB(Math.Max(0, Math.Min(300, scale * 600 - 450)), scale, 2 - scale);
displayMat4.DrawLine((int)point1.X, (int)point1.Y, (int)point2.X, (int)point2.Y, new CvScalar(color.R, color.G, color.B), 1, LineType.AntiAlias);
pairs.Add(new Tuple<double, double>(distance, offset.D));
}
}
}
CvEx.DrawChessboardCornerFrame(displayMat1, boardSize, corners, new CvScalar(64, 128, 64));
displayMat1.DrawChessboardCorners(boardSize, corners, true);
lastCorners = corners;
putImage(displayMat1, PixelFormats.Rgb24);
}
else
{
CvEx.CloneCvMat(ref displayMat3, imageMat);
putImage(displayMat3, PixelFormats.Rgb24);
}
}
CvMat displayMat2 = CvEx.InitCvMat(displayMat1);
displayMat1.Undistort2(displayMat2, this.UndistortionData.CameraStruct.CreateCvMat(), this.UndistortionData.DistortStruct.CreateCvMat(true));
if (lastCorners != null)
{
drawUndistortedCornerFrame(displayMat2, lastCorners, boardSize);
}
displayMat2.PutText(string.Format("Min: {0}", pairs.Min(x => x.Item1 / x.Item2)), new CvPoint(20, 20), new CvFont(FontFace.HersheyPlain, 1, 1), new CvScalar(255, 255, 255));
displayMat2.PutText(string.Format("Max: {0}", pairs.Max(x => x.Item1 / x.Item2)), new CvPoint(20, 40), new CvFont(FontFace.HersheyPlain, 1, 1), new CvScalar(255, 255, 255));
displayMat2.PutText(string.Format("Avg: {0}", pairs.Average(x => x.Item1 / x.Item2)), new CvPoint(20, 60), new CvFont(FontFace.HersheyPlain, 1, 1), new CvScalar(255, 255, 255));
displayMat2.PutText(string.Format("Med: {0}", CalcEx.GetMedian(pairs.Select(x => x.Item1 / x.Item2).ToList())), new CvPoint(20, 80), new CvFont(FontFace.HersheyPlain, 1, 1), new CvScalar(255, 255, 255));
putImage(displayMat4, PixelFormats.Rgb24);
displayLabels();
}
}
/// <summary>On avearage, do these two joints fall along nearby XYZ coordinates?</summary>
/// <param name="j1">List of joints representing one joint's recent history</param>
/// <param name="j2">List of joints representing one joint's recent history</param>
/// <param name="Threshhold">Maximum standard deviation</param>
/// <returns>True for close; false for far or excessive out of bounds</returns>
public static bool arePointsCloseXYZ(List<Joint> j1, List<Joint> j2, double Threshhold = 0.2)
{
if (!arePointsCloseXYZ(j1, Threshhold)) return false;
if (!arePointsCloseXYZ(j2, Threshhold)) return false;
if (j1.Average(j => j.Position.X) - j2.Average(j => j.Position.X) > Threshhold) return false;
if (j2.Average(j => j.Position.X) - j1.Average(j => j.Position.X) > Threshhold) return false;
if (j1.Average(j => j.Position.Y) - j2.Average(j => j.Position.Y) > Threshhold) return false;
if (j2.Average(j => j.Position.Y) - j1.Average(j => j.Position.Y) > Threshhold) return false;
if (j1.Average(j => j.Position.Z) - j2.Average(j => j.Position.Z) > Threshhold) return false;
if (j2.Average(j => j.Position.Z) - j1.Average(j => j.Position.Z) > Threshhold) return false;
return true;
}
private static void MoveStep_1(IList<Dot> dots, double percent)
{
// Find shortest pair lengths
Tuple<int, int, double, Vector3D> absShortest = null;
var subShortest = new List<Tuple<int, int, double, Vector3D>>();
for (int outer = 0; outer < dots.Count - 1; outer++)
{
Tuple<int, int, double, Vector3D> currentShortest = null;
for (int inner = outer + 1; inner < dots.Count; inner++)
{
if (dots[outer].IsStatic && dots[inner].IsStatic)
{
continue;
}
Vector3D link = dots[inner].Position - dots[outer].Position;
double lenSqr = (link).LengthSquared;
if (currentShortest == null || lenSqr < currentShortest.Item3)
{
currentShortest = Tuple.Create(outer, inner, lenSqr, link);
}
}
if (currentShortest == null)
{
continue;
}
currentShortest = Tuple.Create(currentShortest.Item1, currentShortest.Item2, Math.Sqrt(currentShortest.Item3), currentShortest.Item4);
subShortest.Add(currentShortest);
if (absShortest == null || currentShortest.Item3 < absShortest.Item3)
{
absShortest = currentShortest;
}
}
if (subShortest.Count == 0)
{
return;
}
// Move the shortest pair away from each other (based on how far they are away from the avg)
double avg = subShortest.Average(o => o.Item3);
double distToMove = avg - absShortest.Item3; // the shortest will always be less than average
Vector3D displace = absShortest.Item4.ToUnit() * (distToMove * percent);
if (!dots[absShortest.Item1].IsStatic)
dots[absShortest.Item1].Position -= displace;
if (!dots[absShortest.Item2].IsStatic)
dots[absShortest.Item2].Position += displace;
}
private static double CalculateFrameRate(TimeSpan currentTimeStamp, ref TimeSpan lastTimeStamp, ref List<double> oldIntervals)
{
double newInterval = currentTimeStamp.TotalMilliseconds - lastTimeStamp.TotalMilliseconds;
lastTimeStamp = currentTimeStamp;
if (oldIntervals.Count >= 20) //Computes a running average of 20 frames for stability
{
oldIntervals.RemoveAt(0);
}
oldIntervals.Add(newInterval);
return (1.0 / oldIntervals.Average() * 1000.0);
}