public void GrayScaleImageTest(ImageData imageData)
{
byte[] a = Convert.FromBase64String(imageData.Base64);
//MemoryStream memoryStream = new MemoryStream(a);
//Image image = System.Drawing.Image.FromStream(memoryStream);
Analyse z = new Analyse();
MWNumericArray mWNumericArray = a;
MWArray I = z.analyseImage(mWNumericArray, imageData.CoordinateXY[0], imageData.CoordinateXY[1]);
MWNumericArray I_num = I.ToArray();
Byte[] I_bytes = (Byte[])I_num.ToVector(MWArrayComponent.Real);
int w = I.Dimensions[0];
int h = I.Dimensions[1];
Bitmap bmp = new Bitmap(w, h, PixelFormat.Format8bppIndexed);
ColorPalette cp = bmp.Palette;
for (Int32 i = 0; i < 256; ++i)
{
cp.Entries[i] = Color.FromArgb(255, i, i, i);
}
bmp.Palette = cp;
BitmapData data = bmp.LockBits((new Rectangle(0, 0, bmp.Width, bmp.Height)), ImageLockMode.WriteOnly, bmp.PixelFormat);
Marshal.Copy(I_bytes, 0, data.Scan0, I_bytes.Length);
bmp.UnlockBits(data);
bmp.Save("image.png", ImageFormat.Png);
}
draw drawtest = new draw();//创建类 draw 的实例
private void 打开OToolStripMenuItem_Click(object sender, EventArgs e)
{
OpenFileDialog d = new OpenFileDialog();
d.Filter = "(*.mat)|*.mat|所有文件(*.*)|*.*"; if (d.ShowDialog() == DialogResult.OK)
{
FileStream fs = File.OpenRead(d.FileName); StreamReader sr = new StreamReader(fs); string s;
string filename = d.FileName;
d1 = pcl.loaddata(filename);
// MessageBox.Show(filename);
MWArray[] agrsIn = new MWArray[] { d1 };
pcl.pces(4, ref agrsOut, agrsIn);
MWNumericArray x1 = agrsOut[0] as MWNumericArray;
MWNumericArray x2 = agrsOut[1] as MWNumericArray;
MWNumericArray x3 = agrsOut[2] as MWNumericArray;
MWNumericArray x4 = agrsOut[3] as MWNumericArray;
rbegin = (double[, ])x1.ToArray();
pend = (double[, ])x2.ToArray();
rpk = (double[, ])x3.ToArray();
f1 = (double[, ])d1.ToArray();
qt_mean = x4.ToScalarDouble();
textBox4.Text = qt_mean.ToString();
for (int i = 0; i < 12000; i++)
{
data[i].X = (int)i;//强制类型转换，将double转为int，可能会丢失数据
data[i].Y = (int)((1000 - f1[0, i *5]) * 250 / 4500 + 100);
}
this.timer1.Enabled = true; //可以使用
this.timer1.Interval = 100; //定时时间为100毫秒
this.timer1.Tick += new System.EventHandler(this.timer1_Tick);
this.timer1.Start();//启动定时器
}
}
/// <summary>
/// creates 2D array from Matlab MW array
/// </summary>
/// <param name="mwArray">Matlab MW array</param>
/// <returns></returns>
public static double[,] buildTwoDimensionalDoubleArrayFromMWArray(MWArray mwArray)
{
Array tmpArray = mwArray.ToArray();
int rank = tmpArray.Rank;
int[] dimension = new int[rank];
for (int i = 0; i < rank; i++)
{
dimension[i] = tmpArray.GetLength(i);
}
double[,] doubleArray = new double[dimension[0], dimension[1]];
for (int i = 0; i < dimension[0]; i++)
{
for (int j = 0; j < dimension[1]; j++)
{
doubleArray[i, j] = (double)tmpArray.GetValue(i, j);
}
}
return(doubleArray);
}
/// <summary>
/// converts MatLab MW array to C# compatible jagged array
/// </summary>
/// <param name="mwArray">Matlab MW array</param>
/// <returns></returns>
public static double[][] buildJaggedDoubleArrayFromMWArray(MWArray mwArray)
{
Array tmpArray = mwArray.ToArray();
int rank = tmpArray.Rank;
int[] dimension = new int[rank];
for (int i = 0; i < rank; i++)
{
dimension[i] = tmpArray.GetLength(i);
}
double[][] doubleArray = new double[dimension[0]][];
for (int i = 0; i < dimension[0]; i++)
{
double[] tmpArrayLine = new double[dimension[1]];
for (int j = 0; j < dimension[1]; j++)
{
tmpArrayLine[j] = (double)tmpArray.GetValue(i, j);
}
doubleArray[i] = tmpArrayLine;
}
return(doubleArray);
}
public ActionResult GetEmployer(string[] sendforcalc)
{
var pop = 5;
var gem = 10;
var Pa = 0.2;
CalcTsp.Class1 calcTsp = new CalcTsp.Class1();
double[] list = new double[20 * 3];
int i = 0;
foreach (var item in sendforcalc)
{
string[] arr = item.Split(' ');
list[i] = i / 3;
list[i + 1] = double.Parse(arr[0]);
list[i + 2] = double.Parse(arr[1]);
i = i + 3;
}
MWNumericArray array = new MWNumericArray(20, 3, list);
MWArray resultObj = calcTsp.CalcTsp(array, pop, Pa, gem);
Array a = resultObj.ToArray();
var numa = a.GetValue(0, 0);
var aaaaa = numa.ToString();
int num = int.Parse(aaaaa);
return(Json(num, JsonRequestBehavior.AllowGet));
}
public void CalDistrubtionProcess_Prev(double[] dwx, double[] dwvelo, string folderPath, string fileName)
{
MWNumericArray wx = new MWNumericArray(dwx);
Array.Clear(dwx, 0, dwx.Length);
MWNumericArray wvelo = new MWNumericArray(dwvelo);
Array.Clear(dwvelo, 0, dwvelo.Length);
MWArray resultMW = anc.sub_calculate_distrubtion_with_one_output(wx, wvelo);
Array resultArray = resultMW.ToArray();
int count = resultArray.Length / 3;
double[] d1 = new double[count];
double[] d2 = new double[count];
double[] d3 = new double[count];
double[,] resultArray_A = (double[, ])resultArray;
for (int i = 0; i < count; i++)
{
d1[i] = resultArray_A[i, 0];
d2[i] = resultArray_A[i, 1];
d3[i] = resultArray_A[i, 2];
}
CreateExcel(d1, d2, d3, folderPath, fileName);
}
//private string FromChars(char[,] chars)
//{
// string str = "";
// char c;
// for (int i = 0; i < chars.GetLength(0); i++)
// {
// for (int j = 0; j < chars.GetLength(1); j++)
// {
// c = chars[i, j];
// if (chars[i, j] == '"')
// str += "\"";
// else
// str += chars[i, j];
// }
// }
// return str;
//}
public char[] Encrypt(string plaintext)
{
MWArray ciphertext = (MWArray)this.aesMatObj.AESEncrypt((MWArray)plaintext, CipherKey, SboxDec, Rcon, MatMixCol);
char[,] ctchars = (char[, ])ciphertext.ToArray();
char[] chars = MatricesFactory.To1D(ctchars);
return(chars);
}
public char[] Decrypt(char[] ciphertext)
{
double[] ciphervector = BitManipulator.CharToDouble(ciphertext);
//MWArray[] mw = this.aesMatObj.AESDecrypt(2, (MWNumericArray)(MatricesFactory.To2D(ciphervector)), CipherKey, SboxDec, SboxInv, Rcon, MatMixColInv);
//MWNumericArray mn = (MWNumericArray)mw[1];
MWArray plaintext = (MWArray)this.aesMatObj.AESDecrypt((MWNumericArray)(MatricesFactory.To2D(ciphervector)), CipherKey, SboxDec, SboxInv, Rcon, MatMixColInv);
char[,] plaintextchars = (char[, ])plaintext.ToArray();
return(MatricesFactory.To1D(plaintextchars));
}
public void CalDistrubtionProcess(double[] dwx, double[] dwvelo, string folderPath, string fileName, double rmsMean, string fileName_tii)
{
MWNumericArray wx = new MWNumericArray(dwx);
Array.Clear(dwx, 0, dwx.Length);
MWNumericArray wvelo = new MWNumericArray(dwvelo);
Array.Clear(dwvelo, 0, dwvelo.Length);
//MWArray resultMW = anc.sub_calculate_distrubtion_with_one_output(wx, wvelo);
MWArray resultMW = anc.sub_calculate_rms_distrubtion(wx, wvelo);
Array resultArray = resultMW.ToArray();
int count = resultArray.Length / 3;
double[] d1 = new double[count];
double[] d2 = new double[count];
double[] d3 = new double[count];
double[,] resultArray_A = (double[, ])resultArray;
for (int i = 0; i < count; i++)
{
d1[i] = resultArray_A[i, 0];
d2[i] = resultArray_A[i, 1];
d3[i] = resultArray_A[i, 2];
}
MWArray resultMW_tii = anc.sub_calculate_tii_distrubtion(wx, wvelo, rmsMean);
Array resultArray_tii = resultMW_tii.ToArray();
int count_tii = resultArray_tii.Length / 3;
double[] d1_tii = new double[count_tii];
double[] d2_tii = new double[count_tii];
double[] d3_tii = new double[count_tii];
double[,] resultArray_A_tii = (double[, ])resultArray_tii;
for (int i = 0; i < count_tii; i++)
{
d1_tii[i] = resultArray_A_tii[i, 0];
d2_tii[i] = resultArray_A_tii[i, 1];
d3_tii[i] = resultArray_A_tii[i, 2];
}
CreateExcel(d1, d2, d3, folderPath, fileName);
CreateExcel(d1_tii, d2_tii, d3_tii, folderPath, fileName_tii);
}
public void FromMatlabArray(MWArray data)
{
var k = data.ToArray();
for (int i = 0; i < k.GetLength(0); i++)
{
for (int j = 0; j < k.GetLength(1); j++)
{
object a = k.GetValue(i, j);
byte b = (byte)a;
Pixel p = new Pixel((int)b, (int)b, (int)b, 255);
SetPixel(j, i, p);
}
}
}
/// <summary>
/// 自动对齐
/// </summary>
/// <param name="ww">输入参考波形1的数据</param>
///WW(1,:)：左高低
///WW(2,:)：右高低
///WW(3,:)：左轨向
///WW(4,:)：右轨向
///WW(5,:)：轨距------(总共5列数据)
/// <param name="ww1">参考波形2的数据</param>
/// <returns>移动的点数</returns>
/// 备注：波形1不动，波形2减去点数
/// 波形2不动，波形1加上点数
public int AutoTranslation(float[][] ww, float[][] ww1)
{
int retVal = 0;
int rowLen_ww = ww.GetLength(0);
int colLen_ww = ww[0].Length;
MWNumericArray d_ww = new MWNumericArray(MWArrayComplexity.Real, rowLen_ww, colLen_ww);
//matlab中矩阵的下标是从1开始的，而C#是从0开始的
for (int i = 0; i < rowLen_ww; i++)
{
for (int j = 0; j < colLen_ww; j++)
{
d_ww[i + 1, j + 1] = ww[i][j];
}
}
int rowLen_ww1 = ww1.GetLength(0);
int colLen_ww1 = ww1[0].Length;
MWNumericArray d_ww1 = new MWNumericArray(MWArrayComplexity.Real, rowLen_ww1, colLen_ww1);
//matlab中矩阵的下标是从1开始的，而C#是从0开始的
for (int i = 0; i < rowLen_ww1; i++)
{
for (int j = 0; j < colLen_ww1; j++)
{
d_ww1[i + 1, j + 1] = ww1[i][j];
}
}
try
{
//调用算法
MWArray resultArray = ppmc.sub_preprocessing_alignment_data(d_ww, d_ww1);
//MWArray resultArray = null;
double[,] tmpArray = (double[, ])(resultArray.ToArray());
retVal = (int)tmpArray[0, 0];
}
catch (System.Exception ex)
{
MessageBox.Show(ex.Message);
}
return(retVal);
}
public Image Apply(Image img)
{
MWArray arr = m_assets.ConnectedComponent(img.ToSingleMatlabArray());
var d = arr.ToArray();
Elements = new CCElement[d.GetLength(0)];
for (int i = 0; i < d.GetLength(0); i++)
{
var ooo = d.GetValue(i, 0);
Elements[i].Center_X = (double)ooo;
ooo = d.GetValue(i, 1);
Elements[i].Center_Y = (double)ooo;
ooo = d.GetValue(i, 2);
Elements[i].Area = (double)ooo;
}
return(img);
}
/// <summary>
/// convert Matlab MW array to one dimentional integer array
/// </summary>
/// <param name="mwArray">Matlab MW array</param>
/// <returns></returns>
public static int[] buildOneDimensionalIntArray(MWArray mwArray)
{
Array tmpArray = mwArray.ToArray();
int rank = tmpArray.Rank;
int[] dimension = new int[rank];
for (int i = 0; i < rank; i++)
{
dimension[i] = tmpArray.GetLength(i);
}
int[] intArray = new int[dimension[0]];
for (int i = 0; i < dimension[0]; i++)
{
intArray[i] = Convert.ToInt32((double)tmpArray.GetValue(i, 0));
}
return(intArray);
}
// Generate the feature vector of the given image.
public double[] GenerateFeature(short[,] pixelData)
{
// Initialize the parameters of feature (data).
MWStructArray fea_first = new MWStructArray(1, 1, new string[] { "pixels", "maxsize" });
fea_first.SetField("pixels", new MWNumericArray(pixelData));
fea_first.SetField("maxsize", 75);
// Initialize the parameters of dictionary.
MWStructArray dic_first = new MWStructArray(1, 1, new string[] { "dicsize", "patchsize", "samplenum", "dic" });
dic_first.SetField("dicsize", 200);
dic_first.SetField("patchsize", 16);
dic_first.SetField("samplenum", 100);
MWArray array = new MWNumericArray(this.dict_dimension[0], this.dict_dimension[1], MatrixUtil.FlattenMatrix(this.dic, this.dict_dimension[0], this.dict_dimension[1]));
dic_first.SetField("dic", array);
// Orthogonal matching pursuit encoder
Stopwatch ompTimer = Stopwatch.StartNew();
MWArray rgbdfea = ompNormal.extract_feature_normal(fea_first, dic_first);
ompTimer.Stop();
Array feature = rgbdfea.ToArray();
Console.WriteLine("Feature Extraction Time: {0} ms", ompTimer.ElapsedMilliseconds);
double[] feature_vector = new double[feature.Length];
for (int i = 0; i < feature.Length; i++)
{
feature_vector[i] = System.Convert.ToDouble(feature.GetValue(i, 0));
}
return(feature_vector);
}
/// <summary>
/// ���������� �����ϰ� �⺻ ���ļ������� ���
/// </summary>
private void CalcFrequency()
{
//double Resolution;
int MaxPoint = 0;
// Sampled
Resolution = (double)Frequency.GetData(4) - (double)Frequency.GetData(3);
InitFre = (int)Math.Round(300/Resolution);
MaxFre = (int)Math.Round(6400/Resolution);
double[] FrequencySampled = new double[(int)(MaxFre-InitFre)];
double[] MAbsorptionSampled = new double[(int)(MaxFre-InitFre)];
MRealSurfaceImpedanceSampled = new double[(int)(MaxFre-InitFre)];
MlmagSurfaceImpedanceSampled = new double[(int)(MaxFre-InitFre)];
double[] FrequencyFitted = new double[32];
// double[] MAbsorptionFitted = new double[32];
// double[] MSurfaceImpedanceFitted = new double[32];
FrequencySampled[0] = 0;
MAbsorptionSampled[0] = 0;
for (int i=1;i<(MaxFre-InitFre);i++)
{
FrequencySampled[i] = Frequency.GetData(InitFre + i-1);
MAbsorptionSampled[i] = MAbsorption.GetData(InitFre + i-1);
}
for (int i=1;i<33;i++)
{
FrequencyFitted[i-1] = i*200;
}
//MeritCalcClass.polyfitting(FrequencyFitted, FrequencySampled, MAbsorptionSampled, 13); //INSUNG
m_Out = MeritCalcClass.PolyFitting((MWNumericArray)MAbsorptionSampled, (MWNumericArray)FrequencyFitted, (MWNumericArray)FrequencySampled, 13);
//m_Out = MeritCalcClass.PolyFitting(
m_DataFitted = (double[,])m_Out.ToArray();
// MAbsorptionFitted = ((Array)MeritCalcClass.DataFitted).;
long[] temp = new long[2];
temp[0] = 1;
temp[1] = 1;
for (int i=1;i<33;i++)
{
TempFrequency[i-1] = FrequencyFitted[i-1];
temp[1] = i;
TempMAbsorption[i - 1] = (double)m_DataFitted.GetValue(0, temp[1]);
}
if (MRealSurfaceImpedance.GetCount()>0)
{
MRealSurfaceImpedanceSampled[0] = 0;
for (int i=1;i<(MaxFre-InitFre);i++)
{
MRealSurfaceImpedanceSampled[i] = MRealSurfaceImpedance.GetData(InitFre + i-1);
}
//MeritCalcClass.polyfitting(FrequencyFitted, FrequencySampled, MRealSurfaceImpedanceSampled, 13); //INSUNG
m_Out = MeritCalcClass.PolyFitting((MWNumericArray)MRealSurfaceImpedanceSampled, (MWNumericArray)FrequencyFitted, (MWNumericArray)FrequencySampled, 13);
m_DataFitted = (double[,])m_Out.ToArray();
// MSurfaceImpedanceFitted = (double[])MeritCalcClass.DataFitted;
for (int i=1;i<33;i++)
{
temp[1] = i;
TempMRealSurfaceImpedance[i - 1] = (double)m_DataFitted.GetValue(0, temp[1]);
}
}
if (MImagSurfaceImpedance.GetCount()>0)
{
MlmagSurfaceImpedanceSampled[0] = 0;
for (int i=1;i<(MaxFre-InitFre);i++)
{
MlmagSurfaceImpedanceSampled[i] = MImagSurfaceImpedance.GetData(InitFre + i-1);
}
//MeritCalcClass.polyfitting(FrequencyFitted, FrequencySampled, MlmagSurfaceImpedanceSampled, 13); //INSUNG
MeritCalcClass.PolyFitting((MWNumericArray)MlmagSurfaceImpedanceSampled, (MWNumericArray)FrequencyFitted, (MWNumericArray)FrequencySampled, 13);
m_DataFitted = (double[,])m_Out.ToArray();
// MSurfaceImpedanceFitted = (double[])MeritCalcClass.DataFitted;
for (int i=1;i<33;i++)
{
temp[1] = i;
TempMImagSurfaceImpedance[i - 1] = (double)m_DataFitted.GetValue(0, temp[1]);
}
}
MaxPoint = GetMaxPoint(TempMAbsorption) + 1;
SetFreq(1, MaxPoint, 32);
}
static void Main(string[] args)
{
if (args != null && args.Length > 0)
{
string methodName = args[0];//方法名称
Class1 C = null;
#region 水文曲线
if (methodName == MethodName.SWCure)
{
try
{
C = new Class1();
//删除文件
string filePath = Path.Combine(Application.StartupPath, ConfigNames.SvCure);
if (File.Exists(filePath))
{
File.Delete(filePath);
}
double[,] CC = (double[, ])C.miaodian().ToArray();
Console.WriteLine("Cv:" + CC[0, 0]);
Console.WriteLine("Cs:" + CC[0, 1]);
Console.WriteLine("X:" + CC[0, 2]);
Console.WriteLine("Nihe:" + CC[0, 3]);
XmlHelper.Serialize <CvCure>(new CvCure()
{
Cv = CC[0, 0],
Cs = CC[0, 1],
X = CC[0, 2],
Nihe = CC[0, 3].ToString()
}, filePath);
Console.ReadKey(); //不直接关闭
}
catch (Exception ex)
{
Console.WriteLine(ex.Message);
}
finally
{
if (C != null)
{
C.Dispose();
}
}
}
#endregion
#region 拟合曲线
else if (methodName == MethodName.NiHeCure)
{
try
{
double X = Convert.ToDouble(args[1]);
MWNumericArray XX = new MWNumericArray(X);
double Cv = Convert.ToDouble(args[2]);
MWNumericArray Cvv = new MWNumericArray(Cv);
double Cs = Convert.ToDouble(args[3]);
MWNumericArray Css = new MWNumericArray(Cs);
C = new Class1();
double[,] Nihe = (double[, ])C.peixian(Cvv, Css, XX).ToArray();
Console.WriteLine("Nihe:" + Nihe[0, 0]);
XmlHelper.Serialize <string>(Nihe[0, 0].ToString(), Path.Combine(Application.StartupPath, ConfigNames.TempName));
C.Dispose();
Console.ReadKey();
}
catch (Exception ex)
{
Console.WriteLine(ex.Message);
}
finally
{
if (C != null)
{
C.Dispose();
}
}
}
#endregion
#region 曲线反查
else if (methodName == MethodName.ResearchCure)
{
double X = Convert.ToDouble(args[1]);
MWNumericArray XX = new MWNumericArray(X);
double Cv = Convert.ToDouble(args[2]);
MWNumericArray Cvv = new MWNumericArray(Cv);
double Cs = Convert.ToDouble(args[3]);
MWNumericArray Css = new MWNumericArray(Cs);
//反查类型 c1-根据概率查值，c2-根据值查询概率，c3-查询时间段内所有内定概率
string type = args[4].Split('-')[0];
if (type == "c1")
{
double k = Convert.ToDouble(args[4].Split('-')[1]);
MWNumericArray kik = new MWNumericArray(k);
C = new Class1();
double[,] Xcha = (double[, ])C.chaxun1(Cvv, Css, XX, kik).ToArray();
Console.WriteLine(Xcha[0, 0]);
}
else if (type == "c2")
{
double k = Convert.ToDouble(args[4].Split('-')[1]);
MWNumericArray kik = new MWNumericArray(k);
C = new Class1();
double[,] Xcha = (double[, ])C.chaxun2(Cvv, Css, XX, kik).ToArray();
Console.WriteLine(Xcha[0, 0]);
}
// c3-站号-时间段
else if (type == "c3")
{
string state = args[4].Split('-')[1];
string time = args[4].Split('-')[2];
//将时间段转换为小时
double during = 0;
bool success = CollectionCons.DicStrToHour.TryGetValue(time, out during);
if (success == false)
{
Console.WriteLine("参数错误");
return;
}
double value = 0;
string commandText = string.Empty;
C = new Class1();
foreach (double item in CollectionCons.StaticsPercents)
{
try
{
MWNumericArray kik = new MWNumericArray(item);
double[,] Xcha = (double[, ])C.chaxun1(Cvv, Css, XX, kik).ToArray();
value = Xcha[0, 0];
//先查询数据是否存在，存在更新，不存在新增
commandText = string.Format("SELECT * FROM [DB_RainMonitor].[dbo].[RAINFALL_PERCENT] where [PERCENT]={0} and During={1} and MONITORNUM='{2}'", item, during, state);
object obj = SqlHelper.ExecuteScalar(SqlHelper.GetConnSting(), System.Data.CommandType.Text, commandText);
if (obj == null)
{
commandText = string.Format("insert into RAINFALL_PERCENT values(NEWID(),'{0}',{1},{2},{3},{4},{5},{6},{7},'{8}',{9})", state, "null", "null", "null", X, Cv, Cs, item, during, value);
}
else
{
commandText = string.Format("update RAINFALL_PERCENT set [VALUE] = {0} where [PERCENT]={1} and During={2} and MONITORNUM='{3}'", value, item, during, state);
}
SqlHelper.ExecuteNonQuery(SqlHelper.GetConnSting(), System.Data.CommandType.Text, commandText);
}
catch (Exception ex)
{
Console.WriteLine("入库失败-" + ex.Message);
return;
}
}
Console.WriteLine("入库成功！");
}
}
#endregion
#region 暴雨衰减
else if (methodName == MethodName.RainStormSub)
{
//参数值 1-小于一小时的时间段，2-小于一小时的值，3-大于一小时的时间段，4-大于一小时的值
List <double> list1 = new List <double>();
string[] minHour = args[2].Split(',');
Array.ForEach(minHour, t =>
{
list1.Add(Convert.ToDouble(t));
});
MWNumericArray MatY1 = new MWNumericArray(list1.ToArray());
List <double> list2 = new List <double>();
minHour = args[1].Split(',');
Array.ForEach(minHour, t =>
{
list2.Add(Convert.ToDouble(t));
});
MWNumericArray MatX1 = new MWNumericArray(list2.ToArray());
List <double> list3 = new List <double>();
minHour = args[4].Split(',');
Array.ForEach(minHour, t =>
{
list3.Add(Convert.ToDouble(t));
});
MWNumericArray MatY2 = new MWNumericArray(list3.ToArray());
List <double> list4 = new List <double>();
minHour = args[3].Split(',');
Array.ForEach(minHour, t =>
{
list4.Add(Convert.ToDouble(t));
});
MWNumericArray MatX2 = new MWNumericArray(list4.ToArray());
try
{
C = new Class1();
SubCure sub = new SubCure();
//删除文件
string filePath = Path.Combine(Application.StartupPath, ConfigNames.SubCure);
if (File.Exists(filePath))
{
File.Delete(filePath);
}
MWArray polyData3 = C.polyfit_line(MatX1, MatY1);
MWArray polyData1 = C.polyfit_line(MatX1, MatY1);
MWArray polyData2 = C.polyfit_line(MatX2, MatY2);
double[,] DataBox1 = (double[, ])polyData1.ToArray();
double[,] DataBox2 = (double[, ])polyData2.ToArray();
double d = (Math.Abs(DataBox2[0, 0]) / Math.Abs(DataBox1[0, 0]) - 1) * 0.3;
sub.d = d;
double k1 = Math.Log10(10 + d);
double k2 = Math.Log10(0.1 + d);
double nd = Math.Abs((DataBox1[0, 0] + DataBox2[0, 0]) / (k1 - k2));
double Sd = (Math.Pow((10 + d), nd) / Math.Pow(10, Math.Abs(DataBox2[0, 0]))) * Math.Pow(10, DataBox2[0, 1]);
sub.nd = nd;
sub.Sd = Sd;
sub.n1 = DataBox1[0, 0];
sub.j1 = DataBox1[0, 1];
sub.n2 = DataBox2[0, 0];
sub.j2 = DataBox2[0, 1];
XmlHelper.Serialize <SubCure>(sub, filePath);
Console.ReadKey();
}
catch (Exception ex)
{
Console.WriteLine(ex.Message);
}
finally
{
if (C != null)
{
C.Dispose();
}
}
}
#endregion
#region d=0
else if (methodName == MethodName.RainStormSub0)
{
//参数值 1-小于一小时的时间段，2-小于一小时的值，3-大于一小时的时间段，4-大于一小时的值
List <double> list1 = new List <double>();
string[] minHour = args[2].Split(',');
Array.ForEach(minHour, t =>
{
list1.Add(Convert.ToDouble(t));
});
MWNumericArray MatY1 = new MWNumericArray(list1.ToArray());
List <double> list2 = new List <double>();
minHour = args[1].Split(',');
Array.ForEach(minHour, t =>
{
list2.Add(Convert.ToDouble(t));
});
MWNumericArray MatX1 = new MWNumericArray(list2.ToArray());
try
{
C = new Class1();
//删除文件
string filePath = Path.Combine(Application.StartupPath, ConfigNames.SubCure0);
if (File.Exists(filePath))
{
File.Delete(filePath);
}
MWArray polyData3 = C.polyfit_line(MatX1, MatY1);
MWArray polyData1 = C.polyfit_line(MatX1, MatY1);
double[,] DataBox1 = (double[, ])polyData1.ToArray();
SubCure sub = new SubCure();
double nd = Math.Abs(2 * (DataBox1[0, 0]) / (Math.Log(10) - Math.Log(0.1)));
double Sd = (Math.Pow(10, nd) / Math.Pow(10, Math.Abs(DataBox1[0, 0]))) * Math.Pow(10, DataBox1[0, 1]);
sub.nd = nd;
sub.Sd = Sd;
sub.n1 = DataBox1[0, 0];
sub.j1 = DataBox1[0, 1];
XmlHelper.Serialize <SubCure>(sub, filePath);
Console.ReadKey();
}
catch (Exception ex)
{
Console.WriteLine(ex.Message);
}
finally
{
if (C != null)
{
C.Dispose();
}
}
}
#endregion
#region 洪峰流量
else if (methodName == MethodName.FloodPeak)
{
//p1,Qm,eps1,sd,R,d,nd,r1,F,L1,L2,I1,I2,A1,A2,tc,eps2,项目路径
MWNumericArray p1_0 = new MWNumericArray(Convert.ToDouble(args[1]));
//MWArray p1_0 = MWArray(p);
MWNumericArray Qm_0 = new MWNumericArray(Convert.ToDouble(args[2]));
//MWArray Qm_0 = MWArray(Q);
MWNumericArray eps = new MWNumericArray(Convert.ToDouble(args[3]));
//MWArray eps = MWArray(ee);
MWNumericArray sd = new MWNumericArray(Convert.ToDouble(args[4]));
//MWArray sd = MWArray(s);
MWNumericArray R = new MWNumericArray(Convert.ToDouble(args[5]));
//MWArray R = MWArray(RR);
MWNumericArray d = new MWNumericArray(Convert.ToDouble(args[6]));
//MWArray d = MWArray(dd);
MWNumericArray nd = new MWNumericArray(Convert.ToDouble(args[7]));
//MWArray nd = MWArray(ndd);
MWNumericArray r1 = new MWNumericArray(Convert.ToDouble(args[8]));
//MWArray r1 = MWArray(rr1);
MWNumericArray F = new MWNumericArray(Convert.ToDouble(args[9]));
//MWArray F = MWArray(FF);
MWNumericArray L1 = new MWNumericArray(Convert.ToDouble(args[10]));
//MWArray L1 = MWArray(LL1);
MWNumericArray L2 = new MWNumericArray(Convert.ToDouble(args[11]));
//MWArray L2 = MWArray(LL2);
MWNumericArray I1 = new MWNumericArray(Convert.ToDouble(args[12]));
//MWArray I1 = MWArray(II1);
MWNumericArray I2 = new MWNumericArray(Convert.ToDouble(args[13]));
//MWArray I2 = MWArray(II2);
MWNumericArray A1 = new MWNumericArray(Convert.ToDouble(args[14]));
//MWArray A1 = MWArray(AA1);
MWNumericArray A2 = new MWNumericArray(Convert.ToDouble(args[15]));
//MWArray A2 = MWArray(AA2);
MWNumericArray tc = new MWNumericArray(Convert.ToDouble(args[16]));
MWNumericArray eps1 = new MWNumericArray(Convert.ToDouble(args[17]));
try
{
C = new Class1();
MainResult result = new MainResult();
//删除文件
if (File.Exists(args[18]))
{
File.Delete(args[18]);
}
MWArray A = C.fun_main(p1_0, Qm_0, eps, sd, R, d, nd, r1, F, L1, L2, I1, I2, A1, A2);
double[,] AA = (double[, ])A.ToArray();
result.Qm = AA[0, 0];
result.p1 = AA[0, 1];
result.tQ = AA[0, 2];
result.d1 = AA[0, 3];
MWArray B = C.func_getTc(sd, R, d, nd, r1, AA[0, 0], AA[0, 1], AA[0, 2], F, tc, eps1);
double[,] BB = (double[, ])B.ToArray();
result.t = BB[0, 0];
result.a1tc = BB[0, 1];
result.d2 = BB[0, 5];
XmlHelper.Serialize <MainResult>(result, args[18]);
Console.ReadKey();
}
catch (Exception ex)
{
Console.WriteLine(ex.Message);
}
finally
{
if (C != null)
{
C.Dispose();
}
}
}
#endregion
#region 导出Sd-Qm查询表
else if (methodName == MethodName.SdQmTable)
{
// 项目路径-保存表路径
string projectForlder = args[1];
string xmlPath = Path.Combine(projectForlder, ConfigNames.RainStormSub);
//暴雨衰减赋值
BYSJResult bysj = null;
if (File.Exists(xmlPath))
{
bysj = XmlHelper.Deserialize <BYSJResult>(xmlPath);
}
//暴雨损失赋值
BYSSResult byss = null;
xmlPath = Path.Combine(projectForlder, ConfigNames.RainStormLoss);
if (File.Exists(xmlPath))
{
byss = XmlHelper.Deserialize <BYSSResult>(xmlPath);
}
//沟道汇流赋值
HCHLResult hchl = null;
xmlPath = Path.Combine(projectForlder, ConfigNames.RiverConfluence);
if (File.Exists(xmlPath))
{
hchl = XmlHelper.Deserialize <HCHLResult>(xmlPath);
}
//坡面汇流赋值
xmlPath = Path.Combine(projectForlder, ConfigNames.SlopeConfluence);
PMHLResult pmhl = null;
if (File.Exists(xmlPath))
{
pmhl = XmlHelper.Deserialize <PMHLResult>(xmlPath);
}
//默认参数
xmlPath = Path.Combine(projectForlder, ConfigNames.DefaultArgModel);
DefaultArgModel defaultArg = null;
if (File.Exists(xmlPath))
{
defaultArg = XmlHelper.Deserialize <DefaultArgModel>(xmlPath);
}
if (bysj == null || byss == null || hchl == null || pmhl == null || defaultArg == null)
{
Console.WriteLine("参数不全！");
return;
}
double p1 = Convert.ToDouble(defaultArg.p1);
double Qm_v = Convert.ToDouble(defaultArg.Qm);
double eps_0 = Convert.ToDouble(defaultArg.esp1);
MWNumericArray p1_0 = new MWNumericArray(p1);
MWNumericArray Qm_0 = new MWNumericArray(Qm_v);;
MWNumericArray eps = new MWNumericArray(eps_0);
MWNumericArray R = new MWNumericArray(byss.R);
MWNumericArray d = new MWNumericArray(bysj.d);
MWNumericArray nd = new MWNumericArray(bysj.nd);
MWNumericArray r1 = new MWNumericArray(byss.r1);
MWNumericArray F = new MWNumericArray(byss.F);
MWNumericArray L1 = new MWNumericArray(hchl.L1);
MWNumericArray L2 = new MWNumericArray(pmhl.L2);
MWNumericArray I1 = new MWNumericArray(hchl.l1);
MWNumericArray I2 = new MWNumericArray(pmhl.l2);
MWNumericArray A1 = new MWNumericArray(hchl.A1);
MWNumericArray A2 = new MWNumericArray(pmhl.A2);
DataTable aTable = new DataTable();
DataColumn Sd = new DataColumn("Sd", typeof(double));
DataColumn Qm = new DataColumn("Qm", typeof(double));
aTable.Columns.Add(Sd);
aTable.Columns.Add(Qm);
try
{
C = new Class1();
double sd_0 = 10;
for (int i = 0; i < 1001; i++)
{
MWNumericArray sd = new MWNumericArray(sd_0);
MWArray A = C.fun_main(p1_0, Qm_0, eps, sd, R, d, nd, r1, F, L1, L2, I1, I2, A1, A2);
double[,] AA = (double[, ])A.ToArray();
DataRow row = aTable.NewRow();
row["Sd"] = sd_0;
row["Qm"] = AA[0, 0];
aTable.Rows.Add(row);
sd_0 = sd_0 + 0.1;
}
XmlHelper.SaveDataToExcelFile(aTable, args[2]);
Console.WriteLine("导出完成！");
}
catch (Exception ex)
{
Console.WriteLine("导出异常：" + ex.Message);
}
finally
{
if (C != null)
{
C.Dispose();
}
}
}
#endregion
}
}
public async Task <RateResult> PredictMovieRate(User predictedUser, int movieIndex)
{
MWArray[] models = createModel.CreateModel(2);
var userModel = models[0];
var itemModel = models[1];
List <Rate> rates = await GetRates();
// - predictedUser.Rates.Count
int[,] rateArray = new int[rates.Count, 4];
var userCount = await movieContext.Users.CountAsync();
int[,] itemRates = new int[userCount, 1];
//Convert rates to input data set
int count = 0;
for (int i = 0; i < rates.Count; i++)
{
var currentRate = rates[i];
////discard user's rate
//if (currentRate.UserId == predictedUser.Id)
// continue;
if (currentRate.MovieId == movieIndex)
{
itemRates[currentRate.UserId - 1, 0] = currentRate.MovieRate;
}
rateArray[count, 0] = currentRate.UserId;
rateArray[count, 1] = currentRate.MovieId;
rateArray[count, 2] = currentRate.MovieRate;
count++;
}
for (int i = 0; i < itemRates.Length; i++)
{
if (itemRates[i, 0] == 0)
{
itemRates[i, 0] = -1;
}
}
//Create user-item dataset for calculating knn
MWArray newValues = calculateKNN.PrepareDataSet((MWNumericArray)rateArray);
double[,] newRates = (double[, ])newValues.ToArray();
//create a given user's rate matrices for comparing values
var movieCount = newRates.GetLength(1);
double[,] userRates = new double[1, movieCount];
var predictedUserRates = predictedUser.Rates;
for (int i = 0; i < movieCount; i++)
{
userRates[0, i] = -1;
}
predictedUserRates.ForEach(rate => userRates[0, rate.MovieId - 1] = rate.MovieRate);
// trainSet, movieRates , userToGuessIndex, N
MWArray[] itemResult = predictionHelper.ItemBased(2, newValues, (MWNumericArray)itemRates, predictedUser.Id, 60);
var itemPrediction = (double[, ])itemResult[1].ToArray();
var roundedItem = -1;
var itemVal = itemPrediction[0, 0];
if (!Double.IsNaN(itemVal))
{
roundedItem = Convert.ToInt32(itemVal);
}
//RESULT
//mw[0] = distanceValues
//mw[1] = bestSimilartityValues
//mw[2] = guess for selected movie
MWArray[] mW = predictionHelper.KNNCalculation(3, userModel, (MWNumericArray)userRates, movieIndex, 50);
var userPrediction = (double[, ])mW[2].ToArray();
var value = userPrediction[0, 0];
int roundedUser = -1;
if (!Double.IsNaN(value))
{
roundedUser = Convert.ToInt32(value);
}
return(new RateResult {
ItemResult = roundedItem, UserResult = roundedUser
});
}
static void Main()
{
Func <double, double> Result = ((double result) => { return(Math.Pow(Math.E, -result)); });
Console.WriteLine("...bayes_estimation2 Start!!!...");
Class_p pre1 = new Class_p();
MWArray max_m1 = (MWNumericArray)pre1.pre_process();
f_method fsolve_r1 = new f_method();
f_method1 fmincon_r = new f_method1();
Classi integratef = new Classi();
Classi1 integratef1 = new Classi1();
MWCharArray str2 = "theta";
MWCharArray str2f = "n";
string str1tt = "(theta^" + 0.ToString() + "/factorial(" + 0.ToString() + ")*exp(1)^(-theta))", str1t;
Console.WriteLine("please assign the number of points you want deal with:");
int i, j, data_range = int.Parse(Console.ReadLine());
for (i = 0; i <= data_range; i++)
{
str1tt = str1tt + "*" + "(theta^" + i.ToString() + "/factorial(" + i.ToString() + ")*exp(1)^(-theta))";
}
string str1ttf = "(theta^n/factorial(n)*exp(1)^(-theta))" + "*" + str1tt;
double[,] max_m2 = (double[, ])max_m1.ToArray();
var max_m3 = DenseMatrix.OfArray(max_m2);
int s1 = max_m2.GetLength(0), s2 = max_m2.GetLength(1);
var result_p = new DenseMatrix((int)Math.Ceiling((double)(s1 / data_range)), s2);
var result_p1 = new DenseVector(s2);
double[] std_r;
long stop_Value = 0, start_Value = 0, freq = 0;
QueryPerformanceFrequency(ref freq); //获取CPU频率
QueryPerformanceCounter(ref start_Value); //获取初始前值
var count1f = new DenseMatrix((int)Math.Ceiling((double)(s1 / data_range)), s2);
double[] count1t = new double[s2];
MathNet.Numerics.LinearAlgebra.Matrix <double> tmp_m1;
MWArray[] argsOut = new MWArray[3];
MWArray[] argsOut1 = new MWArray[2];
MWArray[] argsIn = new MWArray[6];
MWArray[] argsIn1 = new MWArray[5];
MWArray[] argsIn1f = new MWArray[4];
MWArray[] argsOutf1 = new MWArray[1];
MWArray[] argsIn1f1 = new MWArray[7];
MWArray[] argsOutf2 = new MWArray[1];
int exitflag = 0;
int allmins = 0;
for (i = 0; i < s2; i++)
{
//s2 / data_range???
for (j = 0; j < (int)Math.Ceiling((double)(s1 / data_range)); j++)
{
int count1 = 0;
if ((j + 1) * data_range - 1 > max_m3.RowCount)
{
tmp_m1 = max_m3.SubMatrix(j * data_range, data_range - ((j + 1) * data_range - max_m3.ColumnCount), i, 1);
}
else
{
tmp_m1 = max_m3.SubMatrix(j * data_range, data_range, i, 1);
}
for (int ii = 0; ii < tmp_m1.RowCount; ii++)
{
for (int jj = 0; jj < tmp_m1.ColumnCount; jj++)
{
if (Math.Abs(tmp_m1[ii, jj]) > 0.9 * max_m3.SubMatrix(0, max_m3.RowCount, i, 1).Enumerate().Max())
{
count1++;
}
}
}
count1f[j, i] = count1;
count1t[i] = count1t[i] + count1;
}
count1t[i] = count1t[i] / Math.Ceiling((double)(s1 / data_range));
}
for (i = 0; i < s2; i++)
{
//s2 / data_range???
for (j = 0; j < (int)Math.Ceiling((double)(s1 / data_range)); j++)
{
str1t = "theta^" + count1f[j, i].ToString() + "/factorial(" + ((int)Math.Round(count1f[j, i])).ToString() + ")*exp(1)^(-theta)-" + (count1f[j, i] / data_range).ToString();
MWCharArray str1 = new MWCharArray(str1t);
argsIn[0] = str1;
argsIn[1] = str2;
argsIn[2] = 1;
argsIn[5] = 100;
argsOut[0] = result_p[j, i];
argsOut[1] = exitflag;
argsOut[2] = allmins;
if (count1f[j, i] <= count1t[i])
{
argsIn[3] = 0;
argsIn[4] = count1t[i];
fsolve_r1.fsolve_r1(3, ref argsOut, argsIn);
result_p[j, i] = ((MWNumericArray)argsOut[0]).ToScalarDouble();
}
else
{
argsIn[3] = count1t[i];
argsIn[4] = data_range;
fsolve_r1.fsolve_r1(3, ref argsOut, argsIn);
result_p[j, i] = ((MWNumericArray)argsOut[0]).ToScalarDouble();
}
}
}
std_r = (double[])Std_t1(result_p);
for (i = 0; i < s2; i++)
{
string str3 = "((1/(sqrt(2*pi)*" + std_r[i].ToString() + "))*exp(((theta-" + count1t[i].ToString() + ")^2)/" + "(-2*" + std_r[i].ToString() + "^2)))";
str1tt = str1tt + "*" + str3;
argsIn1f[0] = str1tt;
argsIn1f[1] = str2;
argsIn1f[2] = 0;
argsIn1f[3] = data_range;
integratef.integrate(1, ref argsOutf1, argsIn1f);
result_p1[i] = ((MWNumericArray)argsOutf1[0]).ToScalarDouble();
str1tt = str1tt + "/" + result_p1[i].ToString();
str1tt = str1tt + "*" + str1ttf + "*" + str2f;;
argsIn1f1[0] = str1tt;
argsIn1f1[1] = str2;
argsIn1f1[2] = str2f;
argsIn1f1[3] = 0;
argsIn1f1[4] = data_range;
argsIn1f1[5] = 0;
argsIn1f1[6] = data_range;
integratef1.integrate1(1, ref argsOutf2, argsIn1f1);
result_p1[i] = ((MWNumericArray)argsOutf2[0]).ToScalarDouble();
}
//for (i = 0; i < s2; i++)
//{
// MWCharArray str1tt1;
// //s2 / data_range???
// for (j = 0; j < (int)Math.Ceiling((double)(s1 / data_range)); j++)
// {
// string str3 = "((1/(sqrt(2*pi)*" + std_r[i].ToString() + "))*exp(((theta-" + count1t[i].ToString() + ")^2)/" + "(-2*" + std_r[i].ToString() + "^2)))";
// str1tt = str1tt + "*" + str3;
// str1tt1 = new MWCharArray(str1tt);
// argsIn1[0] = str1tt1;
// argsIn1[1] = str2;
// argsIn1[2] = result_p[j, i];
// argsIn1[3] = 0;
// argsIn1[4] = data_range;
// argsOut1[0] = result_p[j, i];
// argsOut1[1] = exitflag;
// fmincon_r.fmincon_r(2, ref argsOut1, argsIn1);
// result_p[j, i] = Result(((MWNumericArray)argsOut1[0]).ToScalarDouble());
// }
//}
MatlabWriter.Write("result_p1.mat", result_p, "result_p1");
QueryPerformanceCounter(ref stop_Value);//获取终止变量值
var times2 = (stop_Value - start_Value) / (double)freq * 1000;
Console.WriteLine("RunTime " + times2 / 1000 + "s");
}
public void FromMatlabArray(MWArray data)
{
var k = data.ToArray();
for (int i = 0; i < k.GetLength(0); i++)
{
for (int j = 0; j < k.GetLength(1); j++)
{
object a = k.GetValue(i,j);
byte b = (byte) a;
Pixel p = new Pixel((int)b,(int)b,(int)b,255);
SetPixel(j,i,p);
}
}
}
public double[] CalOptValuesIndexFind(double Thickness, double BulkDensity, double tFResist, double[,] SFactorMat, double[,] PorosityMat, double tc1, double tc2, int[] FreRegion, int ParaIndenti,int LoopNum)
{
int RowSizeOfPara=0;
int ColumSizeOfPara=0;
int SizeOfPEFre=FreRegion[1]-FreRegion[0];
double fre;
double[] ValueIndex=new double[3];
int[] CalOptValues=new int[2];
if (ParaIndenti==2)
{
RowSizeOfPara=SFactorMat.GetLength(0);;
ColumSizeOfPara=SFactorMat.GetLength(1);
}
else if (ParaIndenti==3)
{
RowSizeOfPara=PorosityMat.GetLength(0);;
ColumSizeOfPara=PorosityMat.GetLength(1);
}
else if (ParaIndenti==4)
{
RowSizeOfPara=SFactorMat.GetLength(0);;
ColumSizeOfPara=SFactorMat.GetLength(1);
}
double[,,] MAbsorptionMat=new double[RowSizeOfPara,ColumSizeOfPara,SizeOfPEFre];
double[,,] PDAbsorption=new double[RowSizeOfPara,ColumSizeOfPara,SizeOfPEFre];
double[,,] CharFreError=new double[RowSizeOfPara,ColumSizeOfPara,SizeOfPEFre];
double[,] CharFreErrorSum=new double[RowSizeOfPara,ColumSizeOfPara];
double[,] APDAbsorption=new double[RowSizeOfPara,ColumSizeOfPara];
ttempMAbsorption=TempMAbsorption;
APDAbsorption.Initialize();
for (int ff=0;ff<SizeOfPEFre;ff++)
{
fre=(ff+FreRegion[0])*200;
//MeritCalcClass.apfibrous5para(Thickness, tFResist, SFactorMat, PorosityMat, tc1, tc2,fre); //INSUNG
m_Out = MeritCalcClass.APFibrous5para(B, tc1, tc2, m_Density1, Densityo, tFResist, fre, (MWNumericArray)PorosityMat, HeatRatio, ItaAir, Thickness, Npr, P0, (MWNumericArray)SFactorMat, Z0); //INSUNG
APDAbsorption = (double[,])m_Out.ToArray();
for (int i=0;i<RowSizeOfPara;i++)
{
for (int j=0; j<ColumSizeOfPara;j++)
{
MAbsorptionMat[i,j,ff]=ttempMAbsorption[ff+FreRegion[0]];
PDAbsorption[i,j,ff]=APDAbsorption[i+1,j+1];
CharFreError[i,j,ff]=Math.Abs(MAbsorptionMat[i,j,ff]-PDAbsorption[i,j,ff]);
}
}
}
for (int i=0;i<RowSizeOfPara;i++)
{
for(int j=0;j<ColumSizeOfPara;j++)
{
for(int ff=0;ff<(SizeOfPEFre-1);ff++)
{
CharFreErrorSum[i,j] += CharFreError[i,j,ff];
}
}
}
if (ParaIndenti==2)
{
ValueIndex=FindMin(CharFreErrorSum, RowSizeOfPara, ColumSizeOfPara);
}
else if (ParaIndenti==3)
{
ValueIndex=FindMin(CharFreErrorSum, RowSizeOfPara, ColumSizeOfPara);
}
else if (ParaIndenti==4)
{
ValueIndex=FindMin(CharFreErrorSum, RowSizeOfPara, ColumSizeOfPara);
}
return ValueIndex;
}
public double[] CalOptValuesIndexFind(double Thickness, double BulkDensity, double tFResist, double tSFactor, double Porosity, double[,] c1Mat, double[,] c2Mat, int[] FreRegion, int ParaIndenti,int LoopNum)
{
int RowSizeOfPara= 0;
int ColumSizeOfPara= 0;
int SizeOfPEFre=32;
// double TempMaxError=0.0;
double fre;
double[] ValueIndex=new double[3];
int[] CalOptValues=new int[2];
if (ParaIndenti==5)
{
RowSizeOfPara=c1Mat.GetLength(0);;
ColumSizeOfPara=c1Mat.GetLength(1);
}
else if (ParaIndenti==6)
{
RowSizeOfPara=c2Mat.GetLength(0);;
ColumSizeOfPara=c2Mat.GetLength(1);
}
else if (ParaIndenti==7)
{
RowSizeOfPara=c1Mat.GetLength(0);;
ColumSizeOfPara=c1Mat.GetLength(1);
}
double[,,] MAbsorptionMat=new double[RowSizeOfPara,ColumSizeOfPara,SizeOfPEFre];
double[,,] PDAbsorption=new double[RowSizeOfPara,ColumSizeOfPara,SizeOfPEFre];
double[,,] CharFreError=new double[RowSizeOfPara,ColumSizeOfPara,SizeOfPEFre];
double[,] CharFreErrorSum=new double[RowSizeOfPara,ColumSizeOfPara];
double[,] APDAbsorption=new double[RowSizeOfPara,ColumSizeOfPara];
double[,] MaxError=new double[RowSizeOfPara,ColumSizeOfPara];
ttempMAbsorption=TempMAbsorption;
for (int ff=0;ff<SizeOfPEFre;ff++)
{
fre=(ff+1)*200;
//MeritCalcClass.apfibrous5para(Thickness, tFResist, tSFactor, tPorosity, c1Mat, c2Mat,fre); //INSUNG
m_Out = MeritCalcClass.APFibrous5para(B, (MWNumericArray)c1Mat, (MWNumericArray)c2Mat, m_Density1, Densityo, tFResist, fre, tPorosity, HeatRatio, ItaAir, Thickness, Npr, P0, tSFactor, Z0); //INSUNG
APDAbsorption = (double[,])m_Out.ToArray();
for (int i=0;i<RowSizeOfPara;i++)
{
for (int j=0;j<ColumSizeOfPara;j++)
{
MAbsorptionMat[i,j,ff]=ttempMAbsorption[ff];
PDAbsorption[i,j,ff]=APDAbsorption[i+1,j+1];
CharFreError[i,j,ff]=Math.Abs(MAbsorptionMat[i,j,ff]-PDAbsorption[i,j,ff]);
}
}
}
for (int i=0;i<RowSizeOfPara;i++)
{
for(int j=0;j<ColumSizeOfPara;j++)
{
for(int ff=0;ff<SizeOfPEFre;ff++)
{
CharFreErrorSum[i,j] += CharFreError[i,j,ff];
}
}
}
// for (int i=0;i<RowSizeOfPara;i++)
// {
// TempMaxError=0;
// for(int j=0;j<ColumSizeOfPara;j++)
// {
// TempMaxError=0;
// for(int ff=0;ff<(SizeOfPEFre-1);ff++)
// {
// if (TempMaxError < CharFreError[i,j,ff])
// {
// TempMaxError=CharFreError[i,j,ff];
// MaxError[i,j]=TempMaxError;
// }
// CharFreErrorSum[i,j]+= CharFreError[i,j,ff];
// }
// }
// }
if (ParaIndenti==5)
{
ValueIndex=FindMin(CharFreErrorSum, RowSizeOfPara, ColumSizeOfPara);
}
else if (ParaIndenti==6)
{
ValueIndex=FindMin(CharFreErrorSum, RowSizeOfPara, ColumSizeOfPara);
}
else if (ParaIndenti==7)
{
double FirstError=10000;
double tempc1=0;
double tempc2=0;
//double Optc1=tc1;
//double Optc2=tc2;
for (int i=0;i<RowSizeOfPara;i++)
{
for (int j=0;j<ColumSizeOfPara;j++)
{
tempc1= c1Mat[i,j];
tempc2= c2Mat[i,j];
//if ( (MinMaxtError >= MaxError[i,j]) && (tempc1 >= tempc2) )
if ( (FirstError >= CharFreErrorSum[i,j]) && (tempc1 >= tempc2) )
{
ValueIndex[0]=i;
ValueIndex[1]=j;
//ValueIndex[2]=CharFreErrorSum[i,j];
//MinMaxError=MaxError[i,j];
FirstError= CharFreErrorSum[i,j];
}
}
}
}
return ValueIndex;
}
public double[] CalOptValuesIndexFind(double Thickness, double BulkDensity, double[,] FResistMat, double tSFactor, double tPorosity, double tc1, double tc2, int[] FreRegion, int ParaIndenti,int LoopNum)
{
int RowSizeOfPara=0;
int ColumSizeOfPara=0;
int SizeOfPEFre=FreRegion[1]-FreRegion[0];
double TempMaxError=0.0;
double fre;
double[] ValueIndex=new double[3];
int[] CalOptValues=new int[2];
RowSizeOfPara=FResistMat.GetLength(0);
ColumSizeOfPara=FResistMat.GetLength(1);
double[,,] MAbsorptionMat=new double[RowSizeOfPara,ColumSizeOfPara,SizeOfPEFre];
double[,,] PDAbsorption=new double[RowSizeOfPara,ColumSizeOfPara,SizeOfPEFre];
double[,,] CharFreError=new double[RowSizeOfPara,ColumSizeOfPara,SizeOfPEFre];
double[,] CharFreErrorSum=new double[RowSizeOfPara,ColumSizeOfPara];
double[,] APDAbsorption=new double[RowSizeOfPara,ColumSizeOfPara];
double[,] MaxError=new double[RowSizeOfPara,ColumSizeOfPara];
ttempMAbsorption=TempMAbsorption;
for (int ff=0;ff<SizeOfPEFre;ff++)
{
fre=(ff+1)*200;
//MeritCalcClass.apfibrous5para(Thickness, FResistMat, tSFactor, tPorosity, tc1, tc2,fre); //INSUNG
m_Out = MeritCalcClass.APFibrous5para(B, tc1, tc2, m_Density1, Densityo, (MWNumericArray)FResistMat, fre, tPorosity, HeatRatio, ItaAir, Thickness, Npr, P0, tSFactor, Z0); //INSUNG
APDAbsorption = (double[,])m_Out.ToArray();
for (int i=0;i<RowSizeOfPara;i++)
{
for (int j=0; j<ColumSizeOfPara;j++)
{
MAbsorptionMat[i,j,ff]=ttempMAbsorption[ff];
PDAbsorption[i,j,ff]=APDAbsorption[i+1,j+1];
CharFreError[i,j,ff]=Math.Abs(MAbsorptionMat[i,j,ff]-PDAbsorption[i,j,ff]);
}
}
}
for (int i=0;i<RowSizeOfPara;i++)
{
TempMaxError=0;
for(int j=0;j<ColumSizeOfPara;j++)
{
TempMaxError=0;
for(int ff=0;ff<(SizeOfPEFre-1);ff++)
{
if (TempMaxError < CharFreError[i,j,ff])
{
TempMaxError=CharFreError[i,j,ff];
MaxError[i,j]=TempMaxError;
}
//CharFreErrorSum[i,j]+= CharFreError[i,j,ff];
}
}
}
ValueIndex=FindMin(MaxError, RowSizeOfPara, ColumSizeOfPara);
//ValueIndex=FindMin(CharFreErrorSum, RowSizeOfPara, ColumSizeOfPara);
return ValueIndex;
}
public double CalcFiborousGraphData()
{
double Merit=0;
double freq;
double c1 = Math.Sqrt(8*SFactor*ItaAir/(Porosity*FResist))/ViscousCL;
double c2 = Math.Sqrt(8*SFactor*ItaAir/(Porosity*FResist))/ThermalCL;
// H = (Math.Pow(FResist*ViscousCL*Porosity,2))/(4*(Math.Pow(SFactor,2))*ItaAir*Densityo);
// HP = 16*ItaAir/((Math.Pow(Npr*ThermalCL,2))*Densityo);
CAbsorption.Clear();
CRealSurfaceImpedance.Clear();
CImagSurfaceImpedance.Clear();
CAbsorption.AddData(0);
CRealSurfaceImpedance.AddData(0);
CImagSurfaceImpedance.AddData(0);
for (int ff=1;ff<=MaxFre;ff++)
{
freq=Frequency.GetData(ff);
//MeritCalcClass.meritcalc(freq, (double)MAbsorption.GetData(ff),BulkDensity, FResist, SFactor, Porosity, c1, c2, Thickness);//INSUNG
m_Out = MeritCalcClass.MeritCalc(BulkDensity,B,c1,c2,Densityo,FResist,freq,Porosity,HeatRatio,ItaAir,Thickness,(double)MAbsorption.GetData(ff),Npr,P0,SFactor,Z0);//INSUNG
m_Merit = (double)m_Out.ToArray().GetValue(0, 0);
m_Absorption = (double)m_Out.ToArray().GetValue(0, 1);
m_RealSurfaceImpedance = (double)m_Out.ToArray().GetValue(0, 2);
m_ImagSurfaceImpedance = (double)m_Out.ToArray().GetValue(0, 3);
m_Density1 = BulkDensity;//INSUNG
CAbsorption.AddData((double)m_Absorption);
CRealSurfaceImpedance.AddData((double)m_RealSurfaceImpedance);
CImagSurfaceImpedance.AddData((double)m_ImagSurfaceImpedance);
Merit=Merit+(double)m_Merit;
}
return Merit;
}
public double CalcElasticGraphData()
{
double Merit=0;
double freq;
//double c1 = Math.Sqrt(8*SFactor*ItaAir/(Porosity*FResist))/ViscousCL;
//double c2 = Math.Sqrt(8*SFactor*ItaAir/(Porosity*FResist))/ThermalCL;
CAbsorption.Clear();
CRealSurfaceImpedance.Clear();
CImagSurfaceImpedance.Clear();
CAbsorption.AddData(0);
CRealSurfaceImpedance.AddData(0);
CImagSurfaceImpedance.AddData(0);
for (int ff=1;ff<=MaxFre;ff++)
{
freq=Frequency.GetData(ff);
//MeritCalcClass.elasticmeritcalc(freq, (double)MAbsorption.GetData(ff),FResist, SFactor, Porosity, c1, c2, Ymodulus, LossFactor, PoissonR, Thickness); //INSUNG
m_Out = MeritCalcClass.ElasticMeritCalc(C,c1,c2,m_Density1,m_DensityA,Densityo,Ymodulus,FResist,freq,Porosity,HeatRatio,Thickness,LossFactor,(double)MAbsorption.GetData(ff),Npr,PoissonR,SFactor); //INSUNG
m_Merit = (double)m_Out.ToArray().GetValue(0, 0);
m_Absorption = (double)m_Out.ToArray().GetValue(0, 1);
m_RealSurfaceImpedance = (double)m_Out.ToArray().GetValue(0, 2);
m_ImagSurfaceImpedance = (double)m_Out.ToArray().GetValue(0, 3);
CAbsorption.AddData((double)m_Absorption);
CRealSurfaceImpedance.AddData((double)m_RealSurfaceImpedance);
CImagSurfaceImpedance.AddData((double)m_ImagSurfaceImpedance);
Merit=Merit+(double)m_Merit;
}
return Merit;
}
public double[] MeritCalc(double Freq1,double Freq2,double tFResist,double tSFactor,double tPorosity,double tc1,double tc2)
{
double Merit=0;
double MaxError=0;
double freq;
double tempError;
double[] Errors=new double[2];
for (int ff=(int)Freq1;ff<=(int)Freq2;ff++)
{
freq=TempFrequency[ff-1];
//MeritCalcClass.meritcalc(freq, (double)TempMAbsorption[ff-1],BulkDensity, tFResist, tSFactor, tPorosity, tc1, tc2, Thickness);//INSUNG
m_Out = MeritCalcClass.MeritCalc(BulkDensity,B,tc1,tc2,Densityo,tFResist,freq,tPorosity,HeatRatio,ItaAir,Thickness,(double)TempMAbsorption[ff-1],Npr,P0,tSFactor,Z0);//INSUNG
m_Merit = (double)m_Out.ToArray().GetValue(0, 0);
m_Absorption = (double)m_Out.ToArray().GetValue(0, 1);
m_RealSurfaceImpedance = (double)m_Out.ToArray().GetValue(0, 2);
m_ImagSurfaceImpedance = (double)m_Out.ToArray().GetValue(0, 3);
m_Density1 = BulkDensity;//INSUNG
Merit=Merit+(double)(m_Merit);
tempError=(double)(m_Merit);
if(MaxError>tempError)
{
MaxError=tempError;
}
//System.Windows.Forms.Application.DoEvents();
}
Errors=new double[2] {MaxError,Merit};
return Errors;
}
public double[,] SolidCalc()
{
double[,] OptSolidPara=new double[1,3];
double Slope1;
double Slope2;
double Slope3;
double Slope4;
double ResonanceFrequency=0;
double freq;
double Merit=0;
double tLossFactor=0;
double OptLossFactor=0;
int ResonFreIndex=0;
for (int i=2;i<MaxFre-InitFre-2;i++)
{
Slope1=(MRealSurfaceImpedanceSampled[i-1]*415-MRealSurfaceImpedanceSampled[i-2]*415)/Resolution;
Slope2=(MRealSurfaceImpedanceSampled[i]*415-MRealSurfaceImpedanceSampled[i-1]*415)/Resolution;
Slope3=(MRealSurfaceImpedanceSampled[i+1]*415-MRealSurfaceImpedanceSampled[i]*415)/Resolution;
Slope4=(MRealSurfaceImpedanceSampled[i+2]*415-MRealSurfaceImpedanceSampled[i+1]*415)/Resolution;
if ( (Slope1/(Math.Abs(Slope1)) < 0) && (Slope2/(Math.Abs(Slope2)) < 0) && (Slope3/(Math.Abs(Slope3)) > 0) && (Slope4/(Math.Abs(Slope4)) > 0))
{
ResonanceFrequency=(double)i*Resolution+300;
break;
}
}
ResonFreIndex=(int)Math.Round(ResonanceFrequency/Resolution);
//MeritCalcClass.peelasticsolid(Thickness, BulkDensity, ResonanceFrequency);
m_Out = MeritCalcClass.PEElasticSolid(BulkDensity, Thickness, ResonanceFrequency); //INSUNG
OptSolidPara = (double[,])m_Out.ToArray();
Ymodulus=(double)OptSolidPara[1,1];
PoissonR=(double)OptSolidPara[1,3];
double Merittemp=100000;
for (int i=1;i<99;i++)
{
tLossFactor=i*0.01;
freq=ResonFreIndex*Resolution;
//MeritCalcClass.elasticmeritcalc(freq, (double)MAbsorption.GetData(ResonFreIndex),FResist, SFactor, Porosity, c1, c2, Ymodulus, tLossFactor, PoissonR, Thickness); //INSUNG
m_Out = MeritCalcClass.ElasticMeritCalc(C,c1,c2,m_Density1,m_DensityA,Densityo,Ymodulus,FResist,freq,Porosity,HeatRatio,Thickness,tLossFactor,(double)MAbsorption.GetData(ResonFreIndex),Npr,PoissonR,SFactor); //INSUNG
m_Merit = (double)m_Out.ToArray().GetValue(0, 0);
m_Absorption = (double)m_Out.ToArray().GetValue(0, 1);
m_RealSurfaceImpedance = (double)m_Out.ToArray().GetValue(0, 2);
m_ImagSurfaceImpedance = (double)m_Out.ToArray().GetValue(0, 3);
Merit=(double)m_Merit;
if(Merit<Merittemp)
{
OptLossFactor=tLossFactor;
Merittemp=Merit;
}
}
OptSolidPara[1,2]=OptLossFactor;
return OptSolidPara;
}