// Retrieve end of day price data from yahoo finance
public void GetData(string symbol, int period, int observations)
{
HttpWebRequest req = (HttpWebRequest)WebRequest.Create("http://ichart.yahoo.com/table.csv?s=" + symbol);
HttpWebResponse resp = (HttpWebResponse)req.GetResponse();
StreamReader sr = new StreamReader(resp.GetResponseStream());
DataPointCollection logReturns = new DataPointCollection();
int i = 0;
string line = sr.ReadLine();// skip first line (header)
string[] m = sr.ReadLine().Split(',');
// The # of items we need to retrieve (make sure right amount)
int j = period*4 + 1;
if (j <= observations*4+1)
{
j = ((observations * 4) + 1);
}
while (i < j)
{
string[] n = sr.ReadLine().Split(',');
double l = Convert.ToDouble(m[4]);
double k = Convert.ToDouble(n[4]);
DataPoint t = new DataPoint(Math.Log(l / k), Convert.ToDateTime(m[0]));
logReturns.Add(t);
m = n;
i++;
}
// Calculate volatilities
double annualFactor = Math.Sqrt(252);
for (i = 0; i < j / 2; ++i)
{
double vol = StandardDeviation(logReturns.GetRange(i, period)) * annualFactor;
DataPoint t = new DataPoint(vol, logReturns[i].Date);
_vols.Add(t);
}
// Calculate std-dev of all volatilities
for(i = 0; i < observations; ++i)
{
double stdDev = StandardDeviation(_vols.GetRange(i, period));
DataPoint t = new DataPoint(stdDev, _vols[i].Date);
_volStdDev.Add(t);
}
// Take subset so we can plot on graph
_vols = _vols.GetRange(0, observations);
}
public HistogramRGB(int [,] array)
{
InitializeComponent();
DataPointCollection list1 = chart1.Series[0].Points;
DataPointCollection list2 = chart1.Series[1].Points;
DataPointCollection list3 = chart1.Series[2].Points;
for (int i = 0; i < 256; i++)
{
list1.AddXY(i, array[0, i]);
list2.AddXY(i, array[1, i]);
list3.AddXY(i, array[2, i]);
}
chart1.Series[0].Color = Color.Blue;
chart1.Series[1].Color = Color.Green;
chart1.Series[2].Color = Color.Red;
chart1.ChartAreas[0].AxisX.Maximum = 255;
chart1.ChartAreas[0].AxisX.Minimum = 0;
chart1.ChartAreas[0].AxisX.Title = "Intensidade";
chart1.ChartAreas[0].AxisY.Title = "Numero Pixeis";
chart1.ResumeLayout();
}
/// <summary>
/// Initializes a new instance of the Visifire.Charts.DataSeries class
/// </summary>
public DataSeries()
{
ToolTipText = "";
//IsZIndexSet = false;
// Apply default style from generic
#if WPF
if (!_defaultStyleKeyApplied)
{
DefaultStyleKeyProperty.OverrideMetadata(typeof(DataSeries), new FrameworkPropertyMetadata(typeof(DataSeries)));
_defaultStyleKeyApplied = true;
}
#else
DefaultStyleKey = typeof(DataSeries);
#endif
// Initialize DataPoints list
DataPoints = new DataPointCollection();
// Initialize InternalDataPoints list
InternalDataPoints = new List<DataPoint>();
// Attach event handler for the Title collection changed event
DataPoints.CollectionChanged += new System.Collections.Specialized.NotifyCollectionChangedEventHandler(DataPoints_CollectionChanged);
}
/// <summary>
/// Export the line series to an oxyplot series.
/// </summary>
/// <param name="series">The line series to be exported.</param>
/// <param name="labels">Existing axis labels.</param>
protected override (Series, AxisLabelCollection) Export(LineSeries series, AxisLabelCollection labels)
{
LineSeriesWithTracker result = new LineSeriesWithTracker();
DataPointCollection data = GetDataPoints(series.X, series.Y, labels);
result.ItemsSource = data.Points;
if (series.ShowOnLegend)
{
result.Title = series.Title;
}
// Line style/thickness
result.LineStyle = series.LineConfig.Type.ToOxyPlotLineStyle();
result.StrokeThickness = series.LineConfig.Thickness.ToOxyPlotThickness();
// tbi: line colour configuration
// result.Stroke = series.LineConfig.Colour.ToOxyPlotColour();
// Marker type/thickness
result.MarkerType = series.MarkerConfig.Type.ToOxyPlotMarkerType();
result.MarkerSize = series.MarkerConfig.Size.ToOxyPlotMarkerSize() * series.MarkerConfig.SizeModifier;
if (series.MarkerConfig.IsFilled())
{
result.MarkerFill = series.Colour.ToOxyColour();
}
else
{
result.MarkerFill = OxyColors.Undefined;
}
// Colour
result.Color = series.Colour.ToOxyColour();
return(result, data.Labels);
}
/// <summary>
/// Тоже найти точку, но уже из списка точек серии
/// </summary>
/// <param name="PointList"></param>
/// <param name="Dt"></param>
/// <returns></returns>
public static DataPoint FindPoint(DataPointCollection PointList, DateTime Dt)
{
if (DateTime.FromOADate(PointList[0].XValue).Subtract(Dt).TotalMilliseconds > 0 || DateTime.FromOADate(PointList[PointList.Count - 1].XValue).Subtract(Dt).TotalMilliseconds < 0)
{
MessageBox.Show("Усреднение не произвено. Выбран интервал усреднения, заходящий за начало данных");
return(new DataPoint());
}
else
{
double FrecvencyRegistration = DateTime.FromOADate(PointList[1].XValue).Subtract(DateTime.FromOADate(PointList[0].XValue)).TotalMilliseconds;
TimeSpan MyTS;
foreach (var item in PointList)
{
//if (DateTime.FromOADate(item.XValue).Hour == Dt.Hour && DateTime.FromOADate(item.XValue).Minute == Dt.Minute && Math.Abs(DateTime.FromOADate(item.XValue).Second - Dt.Second) <= FrecvencyRegistration/2)
MyTS = DateTime.FromOADate(item.XValue).Subtract(Dt);
if (Math.Abs(MyTS.TotalMilliseconds) <= FrecvencyRegistration)
{
return(item);
}
}
MessageBox.Show("Не найдено совпадение времени с курсором");
}
return(new DataPoint());
}
public void GetChar()
{
CharTitName = "XXX物料统计图表";
YCharTitName = "数量/个";
XCharTitName = "物料";
DataPointCollection salist = new DataPointCollection();
DataTable table = new DataTable();
table.Columns.Add("Name", Type.GetType("System.String")); //添加Name列，存储数据类型为string
table.Columns.Add("Id", Type.GetType("System.Int32")); //添加Id列，存储数据类型为Int
table.Columns.Add("Number", Type.GetType("System.Int32")); //添加Id列，存储数据类型为Int
Random random = new Random();
for (int i = 0; i < 5; i++)
{
int number = random.Next(10, 100);
DataRow newRow = table.NewRow();
newRow["Name"] = $"物料{i}";
newRow["Id"] = i;
newRow["Number"] = i + number;
table.Rows.Add(newRow);
}
foreach (DataRow item in table.Rows)
{
var datapoint = new DataPoint
{
AxisXLabel = item["Name"].ToString(),
YValue = double.Parse(item["Number"].ToString())
};
salist.Add(datapoint);
}
Chardatas = salist;
}
public void Add(string xname, string yname, bool error, DataPointCollection points)
{
bool register_x = false;
int xindex = -1, yindex;
if (Xname.IndexOf(xname) < 0)
{
register_x = true;
Xname.Add(xname);
Name.Add(xname);
Data.Add(new List <double>());
xindex = Data.Count - 1;
}
Name.Add(yname);
Data.Add(new List <double>());
yindex = Data.Count - 1;
foreach (DataPoint p in points)
{
if (register_x && xindex >= 0)
{
Data[xindex].Add(p.XValue);
}
if (error)
{
Data[yindex].Add(Math.Abs(p.YValues[0] - p.YValues[1]));
}
else
{
Data[yindex].Add(p.YValues[0]);
}
}
}
public static Boolean isStatic(DataPointCollection arr)
{
int shag = arr.Count / 10;
double[] means = new double[10];
double[] meansquares = new double[10];
double[] deviations = new double[10];
for (int i = 0; i < 10; i++)
{
means[i] = ExpectedValue(arr.Skip(shag * i).Take(shag));
// meansquares[i] = MeanSquare(arr.Skip(shag * i).Take(shag));
deviations[i] = StandartDeviation(arr.Skip(shag * i).Take(shag));
}
for (int i = 0; i < means.Length; i++)
{
for (int j = 0; j < means.Length; j++)
{
if (means[i] / means[j] < 0.8)
{
return(false);
}
/* if (meansquares[i] / meansquares[j] < 0.9)
* {
* return false;
* }*/
if (deviations[i] / deviations[j] < 0.8)
{
return(false);
}
}
}
return(true);
}
public HistogramAll(int [] array, int [,] array2)
{
InitializeComponent();
DataPointCollection listGray = chart1.Series[0].Points;
DataPointCollection listBlue = chart1.Series[1].Points;
DataPointCollection listGreen = chart1.Series[2].Points;
DataPointCollection listRed = chart1.Series[3].Points;
for (int i = 0; i < 256; i++)
{
listGray.AddXY(i, array[i]);
}
for (int i = 0; i < 256; i++)
{
listBlue.AddXY(i, array2[0, i]);
listGreen.AddXY(i, array2[1, i]);
listRed.AddXY(i, array2[2, i]);
}
chart1.Series[0].Color = Color.Gray;
chart1.Series[1].Color = Color.Blue;
chart1.Series[2].Color = Color.Green;
chart1.Series[3].Color = Color.Red;
chart1.ChartAreas[0].AxisX.Maximum = 255;
chart1.ChartAreas[0].AxisX.Minimum = 0;
chart1.ChartAreas[0].AxisX.Title = "Intensidade";
chart1.ChartAreas[0].AxisY.Title = "Numero Pixeis";
chart1.ResumeLayout();
}
/// <summary>
/// Exporta los puntos visibles en la gráfica a un .CVS desde el menú.
/// </summary>
/// <param name="sender"></param>
/// <param name="e"></param>
private void Exportar_GraficatoolStripMenuItem_Click(object sender, EventArgs e)
{
try
{
DataPointCollection data = chart_DataOutput.Series[0].Points;
SaveFileDialog dialog = new SaveFileDialog();
dialog.Filter = "CSV | *.csv";
dialog.Title = "Exportar";
dialog.ShowDialog();
using (FileWriter writer = new FileWriter(dialog.FileName))
{
int i = 0;
StringBuilder sb = new StringBuilder();
foreach (DataPoint item in data)
{
sb.AppendLine(i++ + "," + item.YValues.GetValue(0));
}
writer.WriteLine(sb.ToString());
writer.Flush();
data.Dispose();
}
ToolStripStatusLabel_Status_Write(toolStripStatusLabel_ProgramStatus, "Gráfica exportada");
}
catch (Exception ex)
{
string windowTitle = "Error al guardar como";
MessageBox.Show(ex.Message, windowTitle, MessageBoxButtons.OK, MessageBoxIcon.Error);
}
}
// 显示 PlugRTData
private DataPointCollection GetPlugRTDataPointByDateTime(Int64 plugid, DateTime startDateTime, DateTime endDateTime, string itemStr)
{
try
{
bool success = false;
DataTable dt = SmartPlugDAL.GetSelectedPlugRTDataByPlugIDandDateTime(plugid, startDateTime, endDateTime, itemStr + ",DateTime", SqliteDBPath, ref success);
DataPointCollection dpc = new DataPointCollection();
if (success == true)
{
int dtrowcount = dt.Rows.Count;
for (int i = 0; i < dtrowcount; i++)
{
DataPoint dp = new DataPoint()
{
XValue = dt.Rows[i]["DateTime"],
YValue = Convert.ToDouble(dt.Rows[i][itemStr])
};
dpc.Add(dp);
}
return(dpc);
}
return(dpc);
}
catch (Exception ex)
{
//Do any logging operation here if necessary
throw new Exception(ex.Message);
}
}
private void FindMinMax(DataPointCollection collection,
out double minX, out double maxX,
out double minY, out double maxY)
{
minX = 9999.0;
maxX = -9999.0;
minY = 9999.0;
maxY = -9999.0;
foreach (DataPoint data in collection)
{
if (minX > data.XValue)
{
minX = data.XValue;
}
if (maxX < data.XValue)
{
maxX = data.XValue;
}
if (minY > data.YValues[0])
{
minY = data.YValues[0];
}
if (maxY < data.YValues[0])
{
maxY = data.YValues[0];
}
}
}
/// <summary>
/// Procedure to build random graphics
/// </summary>
/// <param name="points">series to fill</param>
/// <param name="location">in which chartarea build</param>
/// <param name="seed">seed for random initialization</param>
internal static void Random(DataPointCollection points, string location, int seed = 1)
{
Random r = new Random(seed);
CustomRandom cr = new CustomRandom(seed);
switch (location)
{
case "ChartAreaTopLeft":
points.Clear();
for (int i = minX; i < maxX; i++)
{
points.AddXY(i, r.NextDouble());
}
break;
case "ChartAreaBottomLeft":
points.Clear();
for (int i = minX; i < maxX; i++)
{
points.AddXY(i, cr.Next());
}
break;
default:
break;
}
}
void HeapsortMax(DataPointCollection input, int heapSize, int index)
{
int left = (index + 1) * 2 - 1;
int right = (index + 1) * 2;
int largest = 0;
HighlightLabel(Form1.ps1);
if (left < heapSize && input.ElementAt(left).YValues.First() > input.ElementAt(index).YValues.First())
{
largest = left;
}
else
{
HighlightLabel(Form1.ps2);
largest = index;
HighlightLabel(Form1.ps3);
}
HighlightLabel(Form1.ps4);
if (right < heapSize && input.ElementAt(right).YValues.First() > input.ElementAt(largest).YValues.First())
{
largest = right;
}
HighlightLabel(Form1.ps5);
if (largest != index)
{
HighlightLabel(Form1.ps6);
swapChartIndices(index, largest);
HighlightLabel(Form1.ps7);
//System.Threading.Thread.Sleep(50);
HeapsortMax(input, heapSize, largest);
}
}
public static double[] AntiSpike(DataPointCollection points, double num = 4)
{
double disp = Statistics.CalcRMS(points);
double mean = Statistics.CalcAVG(points);
double[] values = points.Select(y => y.YValues[0]).ToArray();
for (int i = 0; i < values.Length; i++)
{
if (values[i] > mean + Math.Sqrt(num * disp) || values[i] < -(mean + Math.Sqrt(num * disp)))
{
if (i != 0 && i != values.Length - 1)
{
values[i] = (values[i - 1] + values[i + 1]) / 2;
}
else if (i == 0)
{
values[i] = (values[i + 1] + values[i + 2]) / 2;
}
else
{
values[i] = (values[i - 1] + values[i - 2]) / 2;
}
}
}
return(values);
}
public static void DPF(DataPointCollection points, string location)
{
switch (location)
{
case "ChartAreaTopLeft":
break;
case "ChartAreaTopRight":
points.Clear();
for (int i = minX; i < maxX; i++)
{
points.AddXY(i, FourierArr[i].C);
}
break;
case "ChartAreaBottomLeft":
points.Clear();
for (int i = minX; i < maxX; i++)
{
points.AddXY(i, FourierArr[i].Re);
}
break;
case "ChartAreaBottomRight":
points.Clear();
for (int i = minX; i < maxX - 5; i++)
{
points.AddXY(i, FourierArr[i].C);
}
break;
default:
break;
}
}
private void CalculateFrequencies(List <double> residualValues, Series series)
{
double roundedMax, intervalWidth;
CalculateResidualParameters(residualValues, out roundedMax, out intervalWidth);
IEnumerable <double> relevantResiduals = residualValues;
IRegressionProblemData problemdata = Content.ProblemData;
if (series.Name.Equals(TRAINING_SAMPLES))
{
relevantResiduals = residualValues.Skip(problemdata.TrainingPartition.Start).Take(problemdata.TrainingPartition.Size);
}
else if (series.Name.Equals(TEST_SAMPLES))
{
relevantResiduals = residualValues.Skip(problemdata.TestPartition.Start).Take(problemdata.TestPartition.Size);
}
double intervalCenter = intervalWidth / 2.0;
double sampleCount = relevantResiduals.Count();
double current = -roundedMax;
DataPointCollection seriesPoints = series.Points;
for (int i = 0; i <= bins; i++)
{
IEnumerable <double> help = relevantResiduals.Where(x => x >= (current - intervalCenter) && x < (current + intervalCenter));
seriesPoints.AddXY(current, help.Count() / sampleCount);
seriesPoints[seriesPoints.Count - 1]["from"] = (current - intervalCenter).ToString();
seriesPoints[seriesPoints.Count - 1]["to"] = (current + intervalCenter).ToString();
current += intervalWidth;
}
}
void OnUnloaded(object sender, RoutedEventArgs e)
{
DataContext = null;
archimedianSpiral = null;
cardioid = null;
cartesianFolium = null;
}
public SpareSeriesPrimaryCpu()
{
InitializeComponent();
SeriesNewCycleRecvDataPoints = new DataPointCollection();
SeriesInputRecvDataPoints = new DataPointCollection();
SeriesResultRecvDataPoints = new DataPointCollection();
SeriesHeartBeatRecvDataPoints = new DataPointCollection();
EeuRecvDataPoints = new DataPointCollection();
SeriesNewCycle.DataPoints = SeriesNewCycleRecvDataPoints;
SeriesInput.DataPoints = SeriesInputRecvDataPoints;
SeriesResult.DataPoints = SeriesResultRecvDataPoints;
SeriesHeartBeat.DataPoints = SeriesHeartBeatRecvDataPoints;
CiCycle.DataPoints = CiCycleDataPoints;
Interrupt.DataPoints = InterruptDataPoints;
CpuNewCycle.DataPointsSend = CpuNewCycleSendDataPoints;
CpuNewCycle.DataPointsRecv = CpuNewCycleRecvDataPoints;
CpuInput.DataPointsSend = CpuInputSendDataPoints;
CpuInput.DataPointsRecv = CpuInputRecvDataPoints;
CpuResult.DataPointsSend = CpuResultSendDataPoints;
CpuResult.DataPointsRecv = CpuResultRecvDataPoints;
CpuHeartBeat.DataPointsSend = CpuHeartBeatSendDataPoints;
CpuHeartBeat.DataPointsRecv = CpuHeartBeatRecvDataPoints;
EeuRecv.DataPoints = EeuRecvDataPoints;
}
private void RenderData(int index, Chart target)
{
if (target.Series.Count.Equals(0))
{
target.Series.Add(_src.Series[index]);
}
if (target.Titles.Count.Equals(0))
{
target.Titles.Add(_src.Series[index]);
}
if (target.Series[0].ChartType != SeriesChartType.Pie)
{
target.Series[0].ChartType = SeriesChartType.Pie;
}
target.Series[0].Name = _src.Series[index];
DataPointCollection dpc = target.Series[0].Points;
dpc.Clear();
foreach (PieChartDataPoint dp in _src[index])
{
dpc[dpc.AddXY(dp.SliceName, dp.Value)].LegendText = dp.SliceName;
if (_legends.ContainsKey(dp.SliceName))
{
dpc[dpc.Count - 1].Color = _legends[dp.SliceName].Color;
}
else
{
// _legends.Add(dp.SliceName, dpc[dpc.Count - 1].Color);
}
}
}
void BindYearChart()
{
ChartArea chArea = Chart1.ChartAreas[0];
DataPointCollection dpc = Chart1.Series[0].Points;
chArea.AxisX.Title = "Year";
chArea.AxisY.Title = "Sale Amt";
chArea.AxisY.LabelStyle.Format = "##,###";
using (DBSampleEntities context = new DBSampleEntities())
{
var data = (from item in context.SaleInfoes
group item by item.SaleDate.Value.Year into g
select new { Year = g.Key, SaleAmt = g.Sum(x => x.SaleAmt) });
foreach (var item in data)
{
dpc.AddXY(item.Year, item.SaleAmt);
}
}
Series series = Chart1.Series[0];
series.IsValueShownAsLabel = true;
series.PostBackValue = "#VALX";
series.LabelFormat = "##,###";
series.LabelBackColor = Color.White;
ViewState["ChartMode"] = "Year";
}
void OnMove(int?_x)
{
if (OnCursorMove == null)
{
return;
}
if (_x == null)
{
OnCursorMove(null, 0, Color.Black);
}
else
{
if (_x < 0)
{
OnCursorMove(null, 0, Color.Black);
}
else
{
DataPointCollection p = chart1.Series[0].Points;
if (_x >= p.Count())
{
OnCursorMove(null, 0, Color.Black);
}
else
{
OnCursorMove(p[(int)_x].Tag as PointSubj, p[(int)_x].YValues[0], p[(int)_x].Color);
}
}
}
}
public void updateGraphs()
{
DataPointCollection chart1Points = this.chart1.Series["Series1"].Points;
DataPointCollection chart2Points = this.chart2.Series["Series1"].Points;
chart1Points.Clear();
chart2Points.Clear();
for (int i = Math.Min(graph1ValuesToShow, dataList.Count); i > 0; i--)
{
if (chart1_x.SelectedIndex >= 0 && chart1_y.SelectedIndex >= 0)
{
double chart1XVal = dataList[dataList.Count - i].getValue((String)this.chart1_x.SelectedItem);
double chart1YVal = dataList[dataList.Count - i].getValue((String)this.chart1_y.SelectedItem);
chart1Points.AddXY(chart1XVal, chart1YVal);
}
}
for (int i = Math.Min(graph2ValuesToShow, dataList.Count); i > 0; i--)
{
if (chart2_x.SelectedIndex >= 0 && chart2_y.SelectedIndex >= 0)
{
double chart2XVal = dataList[dataList.Count - i].getValue((String)this.chart2_x.SelectedItem);
double chart2YVal = dataList[dataList.Count - i].getValue((String)this.chart2_y.SelectedItem);
chart2Points.AddXY(chart2XVal, chart2YVal);
}
}
}
private void CheckBoxCheckedChanged(object sender, EventArgs e)
{
CheckBox checkBox = sender as CheckBox;
if (checkBox != null)
{
if (checkBox.Tag != null)
{
CheckBoxTag tag = checkBox.Tag as CheckBoxTag;
if (tag != null)
{
AppManager.ConfigManager.SetConfigData(tag);
if (checkBox.Checked)
{
FillSeriesWithNewData(tag, fromDateTime, toDateTime);
}
else
{
Chart chartMain = AppManager.MainForm.ChartControl.ChartMain;
chartMain.BeginInit();
DataPointCollection points = tag.Series.Points;
points.ClearFast(); //MsChartExtension
if (chartMain.Series.Contains(tag.Series))
{
chartMain.Series.Remove(tag.Series);
}
chartMain.EndInit();
}
}
}
}
}
private void GetMinAndMax(DataPointCollection <CategoricalDataPoint> dataPoints, out double min, out double max)
{
min = double.NaN;
max = double.NaN;
foreach (CategoricalDataPoint dp in dataPoints)
{
if (dp.Value.HasValue)
{
if (double.IsNaN(min) || dp.Value.Value < min)
{
min = dp.Value.Value;
}
if (double.IsNaN(max) || max < dp.Value.Value)
{
max = dp.Value.Value;
}
}
}
if (double.IsNaN(min) || double.IsNaN(max))
{
return;
}
double expansion = (max - min) / 10;
min -= expansion;
max += expansion;
if (min >= 0 && 0.16 < (max - min) / max)
{
min = 0;
}
}
public List <DataPoint> CheckAndCorrectConsecutiveXValues(DataPointCollection points)
{
List <DataPoint> dcp = new List <DataPoint>();
int i = 0;
double currentmax = 0;
List <int> badPoints = new List <int>();
foreach (DataPoint dp in points)
{
if (dp.XValue > currentmax)
{
currentmax = dp.XValue;
dcp.Add(dp);
}
else
{
badPoints.Add(i);
//for (int x = 0; x < points.Count; x++)
//{
// if(points[x].XValue < )
//}
}
i++;
}
return(dcp);
//foreach (int I in badPoints)
//{
// points.RemoveAt(I);
//}
}
private void addValues(DataPointCollection dataPointCollection, double[] p)
{
for (int i = 0; i < p.Length; i++)
{
dataPointCollection.AddXY(i + 1, p[i]);
}
}
/// <summary>
/// the constructor of the chartseries
/// </summary>
/// <param name="document"></param>
/// <param name="node"></param>
public ChartSeries(IDocument document, XElement node)
{
Document = document;
Node = node;
DataPointCollection = new DataPointCollection();
InitStandards();
}
public static void AddY(this DataPointCollection points, double y, double increment)
{
double x = points.Last().XValue + increment;
DataPoint dp = new DataPoint(x, y);
points.Add(dp);
}
/// <summary>
/// Среднее вправо-лево от указанного количества времени.
/// </summary>
/// <param name="PointList"></param>
/// <param name="Dat"></param>
/// <param name="SecCount_for_Aver"></param>
/// <returns></returns>
double FindAverage(DataPointCollection PointList, DateTime Dat, int SecCount_for_Aver)
{
double aver_Start = 0;
double aver_End = 0;
double aver = 0;
int pointcount = 0;
TimeSpan ts = new TimeSpan(0, 0, 0, SecCount_for_Aver, 0);
aver_Start = FindPoint(PointList, Dat.Subtract(ts)).XValue;
aver_End = FindPoint(PointList, Dat.Add(ts)).XValue;
foreach (var item in PointList)
{
if (item.XValue > aver_Start && item.XValue < aver_End)
{
pointcount++;
aver += item.YValues[0];
}
}
aver = aver / pointcount;
return(aver);
}
/* Clicks windowing button. */
private void windowing_Click(object sender, EventArgs e)
{
DataPointCollection wholePoints = chart1.Series["wave"].Points; // gets all the points on the time domain chart.
double[] selectedPoints = new double[endPosition - startPosition + 1]; // gets all the points in the selected area.
for (int i = 0; i < endPosition - startPosition + 1; i++)
{
selectedPoints[i] = wholePoints[i].YValues[0]; // stores all selected points.
}
double[] weighted = new double[selectedPoints.Length]; // stores points from windowing.
for (int i = 0; i < weighted.Length; i++) // applies triangle windowing.
{
weighted[i] = (1 - Math.Abs(((double)i - ((weighted.Length - 1) / 2)) / (weighted.Length - 1) / 2)) * selectedPoints[i];
}
double[] weightedA = Class1.DFT(weighted); // applies DFT after windowing.
chart2.Series["frequency"].Points.Clear(); //clears out all points on frequency domain.
for (int i = 0; i < weightedA.Length; i++) // draws new points on the frequency domain.
{
chart2.Series["frequency"].Points.AddXY(i, weightedA[i]);
}
}
void AddChartPoint(DataPointCollection chartPoints, Double value)
{
chartPoints.AddY(value);
if (chartPoints.Count > MAX_GRAPH_VALUES)
chartPoints.RemoveAt(0);
}
/// <summary>Adds a System.Windows.Forms.DataVisualization.Charting.DataPoint object to the end of the collection, with the specified X-value and Y-value.</summary>
/// <param name="dataPointCollection">The System.Windows.Forms.DataVisualization.Charting.DataPointCollection instance to add a DataPoint to.</param>
/// <param name="xValue">X-value of the data point.</param>
/// <param name="yValue">Y-value of the data point.</param>
/// <returns>The new System.Windows.Forms.DataVisualization.Charting.DataPoint object.</returns>
public static DataPoint AddXYDataPoint(this DataPointCollection dataPointCollection, double xValue, double yValue)
{
int dataPointIndex = dataPointCollection.AddXY(xValue, yValue);
DataPoint dataPoint = dataPointCollection[dataPointIndex];
return(dataPoint);
}
public void DataPointCollection()
{
var dataSource = new DataPointCollection { new DataPoint(2, 3, null), new DataPoint(4, 5, null), new DataPoint(6, 7, null) };
var chartDataSource = ChartDataHelper.CreateChartDataSource(dataSource, null, null, null, null, null, null);
Assert.AreEqual(3, chartDataSource.Count);
Assert.AreEqual(new DataPoint(new Point(2, 3), null), chartDataSource[0]);
Assert.AreEqual(new DataPoint(new Point(4, 5), null), chartDataSource[1]);
Assert.AreEqual(new DataPoint(new Point(6, 7), null), chartDataSource[2]);
}
public static DataPointCollection GetDataPointCollection( List<double> list)
{
DataPointCollection dpc = new DataPointCollection();
double allCount = 100;
double value = allCount / list.Count;
for (int i = 0; i < list.Count; i++)
{
DataPoint dp = new DataPoint() { YValue = System.Math.Abs(list[i]) * 0.1, XValue = i * value };
dpc.Add(dp);
}
return dpc;
}
/// <summary>
/// Turns off the label on the chart of any data point that has no value to be displayed
/// -leaving the label in the legend
/// </summary>
/// <param name="dpcPointsToRefine">The data points collection to be refined</param>
private void UpdatePoints(DataPointCollection dpcPointsToRefine)
{
// Goes over every data point in the collection given
foreach (DataPoint CurrPoint in dpcPointsToRefine)
{
// If the value of the data point is nothing
if (CurrPoint.YValues[0] == 0.0)
{
// Turns off the label that sits on top of the chart
CurrPoint.CustomProperties = "PieLabelStyle=Disabled";
}
}
}
public MonitorChart(Chart c, string name)
{
m_chart = c;
// some shortcuts
m_area = m_chart.ChartAreas[0];
m_series = m_chart.Series[0];
m_points = m_series.Points;
m_axisX = m_area.AxisX;
m_axisY = m_area.AxisY;
m_annotations = new Dictionary<int, List<Annotation>>();
m_name = name;
Init();
}
public NetworkTrainer(BackPropagationNetwork network, DataPointCollection dataSet)
{
Nudge = true;
NudgeTolerance = 0.0001;
NudgeScale = 0.4;
NudgeWindow = 100;
TargetError = 0.001;
MaxIterations = 100000;
TrainingRate = 0.15;
Momentum = 0.10;
Network = network;
DataSet = dataSet;
Initialize();
}
public void DataPoint_CanSerailize()
{
DataPoint point1 = new DataPoint(new[] { 1.0, 1.1 }, new[] { 2.0, 2.2 });
DataPoint point2 = new DataPoint(new[] { 2.0, 2.1 }, new[] { 4.0, 2.2 });
DataPoint point3 = new DataPoint(new[] { 3.0, 3.1 }, new[] { 6.0, 2.2 });
DataPoint point4 = new DataPoint(new[] { 4.0, 4.1 }, new[] { 8.0, 2.2 });
DataPoint point5 = new DataPoint(new[] { 5.0, 5.1 }, new[] { 10.0, 2.2 });
DataPointCollection dataPointCollection = new DataPointCollection();
dataPointCollection.Add(point1);
dataPointCollection.Add(point2);
dataPointCollection.Add(point3);
dataPointCollection.Add(point4);
dataPointCollection.Add(point5);
XmlSerializer serializer = new XmlSerializer(typeof(DataPointCollection));
serializer.Serialize(Console.Out, dataPointCollection);
}
public void CanTrainNetwork()
{
//XOR data
DataPoint _dp1 = new DataPoint(new[] { 1.0, 1.0 }, new[] { 0.0 });
DataPoint _dp2 = new DataPoint(new[] { 1.0, 0.0 }, new[] { 1.0 });
DataPoint _dp3 = new DataPoint(new[] { 0.0, 1.0 }, new[] { 1.0 });
DataPoint _dp4 = new DataPoint(new[] { 0.0, 0.0 }, new[] { 0.0 });
DataPointCollection _dataPointCollection = new DataPointCollection();
_dataPointCollection.Add(_dp1);
_dataPointCollection.Add(_dp2);
_dataPointCollection.Add(_dp3);
_dataPointCollection.Add(_dp4);
int[] _layerSizes = new int[3] { 2, 2, 1 };
TransferFunction[] _transferFunctions = new TransferFunction[3]
{
TransferFunction.None,
TransferFunction.Sigmoid,
TransferFunction.Linear
};
BackPropagationNetwork _bpn = new BackPropagationNetwork(_layerSizes, _transferFunctions);
SimpleNetworkTrainer _networkTrainer = new SimpleNetworkTrainer(_bpn, _dataPointCollection);
_networkTrainer.TargetError = 0.0001;
_networkTrainer.MaxIterations = 1000000;
_networkTrainer.NudgeScale = 0.8;
_networkTrainer.NudgeWindow = 100;
_networkTrainer.TrainNetwork();
Assert.IsTrue(true, "Never Reached Minimum Error");
for (int i = _networkTrainer.ErrorHistory.Count - 100; i < _networkTrainer.ErrorHistory.Count; i++)
{
Console.WriteLine("{0}: {1:0.00000000}", i, _networkTrainer.ErrorHistory[i]);
}
}
public ChartLineUC(DataPointCollection DataPoints, string str, string strtitle)
{
InitializeComponent();
chartC.DataPointWidth = 2;
Title title = new Title();
title.Text = strtitle;
chartC.Titles.Add(title);
chartC.Series[0].DataPoints = DataPoints;
chartC.Series[0].LegendText = str;
chartC.Series[0].ShowInLegend = true;
chartC.Series[0].ToolTipText = string.Format("名称：#AxisXLabel {0}数值：#YValue {0}", System.Environment.NewLine);
chartC.Series[0].AutoFitToPlotArea = true;
chartC.Series[0].LabelEnabled = false;
chartC.Series[0].Bevel = false;
chartC.Series[0].ShadowEnabled = true;
chartC.Series[0].YValueFormatString = "######.## ";
chartC.Series[0].LightingEnabled = true;
chartC.Series[0].LabelText = " #AxisXLabel";
chartC.Series[0].LabelFontSize = 13;
chartC.Series[0].IncludePercentageInLegend = true;
}
private double[] findRange(DataPointCollection collection)
{
double[] range = new double[4];
double minX=0, maxX=0, minY=0, maxY=0;
int i = 0;
foreach (DataPoint item in collection)
{
if (i==0)
{
minX = item.XValue;
maxX = item.XValue;
minY = item.YValues[0];
maxY = item.YValues[0];
i++;
}
if (minX>item.XValue)
{
minX = item.XValue;
}
if (maxX<item.XValue)
{
maxX = item.XValue;
}
if (minY>item.YValues[0])
{
minY = item.YValues[0];
}
if (maxY<item.YValues[0])
{
maxY = item.YValues[0];
}
}
range[0] = minX;
range[1] = maxX;
range[2] = minY;
range[3] = maxY;
return range;
}
public BasicNeuralNetworkTrainerWrapper(DataPointCollection dataSet)
{
DataSet = dataSet;
int[] layerSizes = new int[10] { DataSet.DataPointBound, 5, 5, 5, 5, 5, 5, 5, 3, 1 };
TransferFunction[] transferFunctions = new TransferFunction[10]
{
TransferFunction.None,
TransferFunction.RationalSigmoid,
TransferFunction.RationalSigmoid,
TransferFunction.Sigmoid,
TransferFunction.Sigmoid,
TransferFunction.Sigmoid,
TransferFunction.Sigmoid,
TransferFunction.Gaussian,
TransferFunction.Gaussian,
TransferFunction.Linear
};
Network.Initialize(layerSizes, transferFunctions);
_network = new BackPropagationNetwork(layerSizes, transferFunctions);
_networkTrainer = new SimpleNetworkTrainer(_network, DataSet);
}
// workaround as per http://stackoverflow.com/questions/5744930/datapointcollection-clear-performance
private static void ClearPointsQuick(DataPointCollection points) {
points.SuspendUpdates();
while (points.Count > 0)
points.RemoveAt(points.Count - 1);
points.ResumeUpdates();
}
private static CategoricalDataPoint GetDataPoint(DataPointCollection<CategoricalDataPoint> dataPoints, object xCategory)
{
foreach (var dp in dataPoints)
{
if (object.Equals(xCategory, dp.Category))
{
return dp;
}
}
return null;
}
/// <summary>
/// Extracts the <see cref="Point"/>s from a collection.
/// </summary>
/// <param name="dataSource">The data source (can be <see langword="null"/>).</param>
/// <param name="xyPath">The binding path for the (x, y) value.</param>
/// <param name="culture">
/// The <see cref="CultureInfo"/> object that provides culture-specific formatting
/// information.
/// </param>
/// <returns>The chart data as a list of data points.</returns>
private static IList<DataPoint> ExtractPointsFromCollection(IEnumerable dataSource, PropertyPath xyPath, CultureInfo culture)
{
var pointValueExtractor = new PointValueExtractor
{
Collection = dataSource,
Culture = culture,
ValuePath = xyPath,
};
var points = pointValueExtractor.Extract();
int index = 0;
var chartDataSource = new DataPointCollection();
foreach (var data in dataSource)
{
chartDataSource.Add(new DataPoint(points[index], data));
index++;
}
return chartDataSource;
}
private string GetCSV(DataPointCollection dpc)
{
var s = (from a in dpc where a.YValues.Length > 0 select a.YValues[0].ToString());
return s.Aggregate((a, b) => a + "," + b);
}
/// <summary>
/// Extracts the points from collection.
/// </summary>
/// <param name="dataSource">The data source (can be <see langword="null"/>).</param>
/// <param name="xPath">The binding path for the x value.</param>
/// <param name="yPath">The binding path for the y value.</param>
/// <param name="xLabels">
/// The collection of text labels used for x values. Can be <see langword="null"/>. This
/// parameter is only relevant when one chart axis shows text labels and the data source
/// contains <see cref="String"/> values instead of <see cref="Double"/> values.
/// </param>
/// <param name="yLabels">
/// The collection of text labels used for y values. Can be <see langword="null"/>. This
/// parameter is only relevant when one chart axis shows text labels and the data source
/// contains <see cref="String"/> values instead of <see cref="Double"/> values.
/// </param>
/// <param name="culture">
/// The <see cref="CultureInfo"/> object that provides culture-specific formatting
/// information.
/// </param>
/// <returns>The chart data as a list of data points.</returns>
private static IList<DataPoint> ExtractPointsFromCollection(
IEnumerable dataSource, PropertyPath xPath, PropertyPath yPath, CultureInfo culture,
IList<TextLabel> xLabels, IList<TextLabel> yLabels)
{
var xValueExtractor = new DoubleValueExtractor
{
Collection = dataSource,
Culture = culture,
TextLabels = xLabels,
ValuePath = xPath,
};
var xValues = xValueExtractor.Extract();
var yValueExtractor = new DoubleValueExtractor
{
Collection = dataSource,
Culture = culture,
TextLabels = yLabels,
ValuePath = yPath,
};
var yValues = yValueExtractor.Extract();
Debug.Assert(xValues.Count == yValues.Count, "Number of x values in data source does not match the number of y values?!");
int index = 0;
var chartDataSource = new DataPointCollection();
foreach (var data in dataSource)
{
chartDataSource.Add(new DataPoint(xValues[index], yValues[index], data));
index++;
}
return chartDataSource;
}
public Series()
{
Points = new DataPointCollection();
}
private Program()
{
_volStdDev = new DataPointCollection();
_vols = new List<DataPoint>();
}
private void AddToSeries(DataPointCollection points, int[] values)
{
for (int i = 0; i < values.Length; ++i)
points.AddXY(i, values[i]);
}
public AutoRegressiveTrainer(BackPropagationNetwork network, DataPointCollection dataSet)
: base(network, dataSet)
{
lastOutput = new double[dataSet.Count];
}
public SimpleNetworkTrainer(BackPropagationNetwork network, DataPointCollection dataSet)
: base(network, dataSet)
{
}
private void CallOnChangePoint(DataPointCollection points)
{
if (null != OnChangePoints)
{
var lst = new List<KeyValuePair<float, float>>();
foreach (var point in points)
{
lst.Add(new KeyValuePair<float, float>((float)point.XValue, (float)point.YValues[0]));
}
OnChangePoints(lst);
}
}
public void ConvolutionNetwork()
{
int[] layerSizes = new int[5]
{
841,
1014,
1250,
100,
10
};
TransferFunction[] transferFunctions = new TransferFunction[5]
{
TransferFunction.None,
TransferFunction.Convolution,
TransferFunction.Convolution,
TransferFunction.Linear,
TransferFunction.Linear
};
BackPropagationNetwork backPropagationNetwork = new BackPropagationNetwork(layerSizes, transferFunctions);
double[] input1 = new double[841];
for (int i = 0; i < input1.Length; i++)
{
if(i % 2 == 0)
input1[i] = 1;
}
double[] input2 = new double[841];
for (int i = 0; i < input2.Length; i++)
{
input2[i] = 1;
}
DataPoint _dp1 = new DataPoint(input1, new[] { 1.0 });
DataPoint _dp2 = new DataPoint(input2, new[] { 0.0 });
DataPointCollection _dataPointCollection = new DataPointCollection();
_dataPointCollection.Add(_dp1);
_dataPointCollection.Add(_dp2);
SimpleNetworkTrainer _networkTrainer = new SimpleNetworkTrainer(backPropagationNetwork, _dataPointCollection);
_networkTrainer.TargetError = 0.0001;
_networkTrainer.MaxIterations = 1000000;
_networkTrainer.NudgeScale = 0.8;
_networkTrainer.NudgeWindow = 100;
_networkTrainer.TrainNetwork();
Assert.IsTrue(true, "Never Reached Minimum Error");
for (int i = _networkTrainer.ErrorHistory.Count - 100; i < _networkTrainer.ErrorHistory.Count; i++)
{
Console.WriteLine("{0}: {1:0.00000000}", i, _networkTrainer.ErrorHistory[i]);
}
}
private void GetMinAndMax(DataPointCollection<CategoricalDataPoint> dataPoints, out double min, out double max)
{
min = double.NaN;
max = double.NaN;
foreach (CategoricalDataPoint dp in dataPoints)
{
if (dp.Value.HasValue)
{
if (double.IsNaN(min) || dp.Value.Value < min)
{
min = dp.Value.Value;
}
if (double.IsNaN(max) || max < dp.Value.Value)
{
max = dp.Value.Value;
}
}
}
if (double.IsNaN(min) || double.IsNaN(max))
{
return;
}
double expansion = (max - min) / 10;
min -= expansion;
max += expansion;
if (min >= 0 && 0.16 < (max - min) / max)
{
min = 0;
}
}
private void PopulatePoints(DataPointCollection points, Random rand)
{
foreach (var i in Enumerable.Range(0, 100))
{
points.Add(GetRandomPoint(i, rand));
}
}