public void paintGraph()
{
int count = Form1.data[channel].Count();
if (count < 500)
{
return;
}
//int i = count > 500 ? count - 500 : 0;
//List<double> data = Form1.data[channel].GetRange(i, count - i);
List <double> data = Form1.data[channel].GetRange(count - 500, 500);
NormalData normalData = new NormalData();
if (count > 500)
{
Form1.data[channel].RemoveRange(0, count - 500);
}
//求当前数据的平均值 方差 标准差
normalData.dealWithData(data);
readyNormalGraphData(normalData);
//if (basedata != 0)
//{
// readyNormalGraphData(normalData);
//}
}
public void data_pant()
{
double PowOfE = 0;
double result = 0;
NormalData normalData = new NormalData();
int count = Form1.data[channel].Count();
int i = count > 100 ? count - 100 : 0;
List <double> data = Form1.data[channel].GetRange(i, count - i);
if (count > 100)
{
Form1.data[channel].RemoveRange(0, count - 100);
}
//求当前数据的平均值 方差 标准差
normalData.dealWithData(data);
int intA = 0;
string str = tBx_X_value.Text;
bool rst = Int32.TryParse(str, out intA); // return bool value hint y/n
if (rst)
{
data_pic_X[0] = intA - 0.98;
}
else
{
data_pic_X[0] = 999982 - 0.98;
}
if (normalData.mDataVariance != 0 && normalData.mDataVarianceSqrt != 0)
{
PowOfE = -(Math.Pow(Math.Abs(data_pic_X[0] - normalData.mDataMean), 2) / (2 * normalData.mDataVariance));
result = ((1 / Math.Sqrt(2 * Math.PI)) / normalData.mDataVarianceSqrt) * Math.Pow(Math.E, PowOfE);
}
data_pic_Y[0] = result;
for (int k = 1; k < 102; k++)
{
data_pic_X[k] = data_pic_X[k - 1] + 0.02;
PowOfE = -(Math.Pow(Math.Abs(data_pic_X[k] - normalData.mDataMean), 2) / (2 * normalData.mDataVariance));
result = ((1 / Math.Sqrt(2 * Math.PI)) / normalData.mDataVarianceSqrt) * Math.Pow(Math.E, PowOfE);
data_pic_Y[k] = result;
}
//*****************画图*****************************************
chart.Series["概率密度"].Points.Clear();
for (int pointIndex = 0; pointIndex < 102; pointIndex++)
{
chart.Series["概率密度"].Points.AddXY(data_pic_X[pointIndex], data_pic_Y[pointIndex]);
//chart.Series["概率密度"].Points.c
}
// Set fast line chart type
chart.Series["概率密度"].ChartType = SeriesChartType.FastLine;
}
public void readyNormalGraphData(NormalData normalData)
{
chart.Series["概率密度"].Points.Clear();
chart.ChartAreas[0].AxisX.LabelStyle.Format = "N3";
chart.ChartAreas[0].AxisX.LabelAutoFitMinFontSize = 6;
chart.ChartAreas[0].AxisX.IsLabelAutoFit = true;
//chart.ChartAreas[0].AxisX.LabelStyle.Font = new System.Drawing.Font("Microsoft Sans Serif", 6.5F, System.Drawing.FontStyle.Regular, System.Drawing.GraphicsUnit.Point, ((byte)(0)));
//chart.ChartAreas[0].AxisX.;
chart.ChartAreas[0].AxisX.Minimum = normalData.mDataMean - 0.5;
chart.ChartAreas[0].AxisX.Maximum = normalData.mDataMean + 0.5;
//chart.ChartAreas[0].AxisX.Interval = 10;
//chart.ChartAreas[0].AxisX.MinorCount = 10; //显示X轴间隔数量
double data_FWHM = normalData.mDataVarianceSqrt * 2.355;
tBx_junzhi.Text = "" + Math.Round(normalData.mDataMean, 3);
tBx_fangcha.Text = "" + Math.Round(normalData.mDataVarianceSqrt * 1000, 5);
tBx_bangaokuan.Text = "" + Math.Round(data_FWHM * 1000, 5);
tBx_X_value.Text = normalData.mPeriods.Count.ToString();
//tBx_X_value.Text = basedata.ToString();
//tBx_X_value.Text = Form1.data[channel].Count().ToString();
double leftPart = 1 / (normalData.mDataVarianceSqrt * Math.Sqrt(2 * Math.PI)); //
double pointX = normalData.mDataMean - 0.5;
while (pointX <= normalData.mDataMean + 0.5)
{
double resultPointX = leftPart * Math.Exp(-1 * (pointX - normalData.mDataMean)
* (pointX - normalData.mDataMean) / (2 * normalData.mDataVariance));
//resultPointX = resultPointX > 1 ? 1 : resultPointX;
resultPointX = resultPointX < 0 ? 0 : resultPointX;
chart.Series["概率密度"].Points.AddXY(pointX, resultPointX);
pointX += 0.02;
}
}
