/// <summary>
/// Static all-in-one method to fit the splines and evaluate at X coordinates.
/// </summary>
/// <param name="x">Input. X coordinates to fit.</param>
/// <param name="y">Input. Y coordinates to fit.</param>
/// <param name="xs">Input. X coordinates to evaluate the fitted curve at.</param>
/// <param name="startSlope">Optional slope constraint for the first point. Single.NaN means no constraint.</param>
/// <param name="endSlope">Optional slope constraint for the final point. Single.NaN means no constraint.</param>
/// <param name="debug">Turn on console output. Default is false.</param>
/// <returns>The computed y values for each xs.</returns>
public static float[] Compute(float[] x, float[] y, float[] xs, float startSlope = float.NaN, float endSlope = float.NaN, bool debug = false)
{
CubicSpline spline = new CubicSpline();
return(spline.FitAndEval(x, y, xs, startSlope, endSlope, debug));
}
public static string[] TesteMathNetInterpolation()
{
double DataPoints = 1000;
// Create the data to be fitted
//var x = new List<double> { 1, 8, 16, 25, 30 }; // 5 pontos
var x = new List <double> {
1, 2, 3, 4, 16, 30
}; // 5 pontos
//var x = new List<double> { 1, 2, 3, 4, 5, 10, 15, 20, 25, 30 }; // 10 pontos
var y = new List <double> {
8.33, 9.25, 9.16, 8.43, 9.5, 9.14
};
//var y = new List<double> { 8.33, 9.37, 8.47, 9.32, 9.11, 9.04, 8.93, 9.49, 8.29, 8.88
//var y = new List<double> { 10.255, 10.064, 9.961, 9.945, 9.930 , 9.37, 9.65, 9.95, 10.40, 10.88};
//var y = new List<double> { 3, 3, 3, 3, 15, 40, 50, 60, 70, 80 };
//Lembre-se sempre de modificar as variacoes de X e Y da plotagem
var xAkima = new List <double>();
var yAkima = new List <double>();
var xLinear = new List <double>();
var yLinear = new List <double>();
/// Interpolação Linear
var linearInterpolation = Interpolate.Linear(x.ToArray(), y.ToArray());
/// Interpolação Polinomial
//var PolinomialInterpolation = new NevillePolynomialInterpolation(x.ToArray(), y.ToArray());
/// Interpolação Akima Spline
var akimaInterpolation = CubicSpline.InterpolateAkima(x.ToArray(), y.ToArray());
var ep = 0;
var a = x.Min();
var b = x.Max();
#region Akima Interpolation
for (int i = 0; i <= DataPoints; i++)
{
/// nomalizedForm = (b−a) (x−min / max − min) + a
/// b = valor maximo do intervalo que os numeros devem ficar
/// a = valor minimo do intervalo que os numeros devem ficar
/// max = valor maximo do intervalo atual
/// min = valor minimo do intervalo atual
double normalized = ((b + ep) - (a - ep)) * (i / DataPoints) + (a - ep);
var yInterpoled = akimaInterpolation.Interpolate(normalized);
xAkima.Add(normalized);
yAkima.Add(yInterpoled);
}
#endregion
#region Linear Interpolation
for (int i = 0; i <= DataPoints; i++)
{
double normalized = ((b + ep) - (a - ep)) * (i / DataPoints) + (a - ep);
var yInterpoled = linearInterpolation.Interpolate(normalized);
xLinear.Add(normalized);
yLinear.Add(yInterpoled);
}
#endregion
var pointsX = new List <double>();
var pointSY = new List <double>();
List <Point> logLinear = new List <Point>();
List <Point> logAkima = new List <Point>();
#region Normalizar pontos dos periodos
for (int i = 1; i <= 30; i++)
{
var cY = akimaInterpolation.Interpolate(i);
pointsX.Add(i);
pointSY.Add(cY);
logAkima.Add(new Point(i, cY));
}
for (int i = 1; i <= 30; i++)
{
var cY = linearInterpolation.Interpolate(i);
pointsX.Add(i);
pointSY.Add(cY);
logLinear.Add(new Point(i, cY));
}
#endregion
//---plotar solução-- -
PlotSolution(NameMethod,
x.ToArray(), y.ToArray(),
xAkima.ToArray(), yAkima.ToArray(),
xLinear.ToArray(), yLinear.ToArray(),
@"..\..\" + NameMethod + ".png");
string[] output = new string[] { "", "" };
foreach (Point p in logAkima)
{
output[0] += p.ToString() + "\n";
}
foreach (Point p in logLinear)
{
output[1] += p.ToString() + "\n";
}
return(output);
}
public void setArm(float [] alpha, int time, SerialPort port)
{
string result;
int servo;
float[] angle = new float[6];
float[] newMusecAngles;
//sets all the servos of the arm
//checks to see if the angles lie within the limits
for (int i = 0; i < 6; i++)
{
if (alpha[i] < alphaLims[0, i])
{
alpha[i] = alphaLims[0, i];
}
if (alpha[i] > alphaLims[2, i])
{
alpha[i] = alphaLims[2, i];
}
}
//goes through each alpha converts it to musecs
//use spline stuff.
// Create the test points.
for (int i = 0; i < 6; i++)
{
float[] x = new float[] { alphaLims[0, i],alphaLims[1,i], alphaLims[2,i]};
float[] y = new float[] { musecLims[0, i], musecLims[1, i], musecLims[2, i]};
float[] xs = new float[1];
xs[0] = alpha[i];
CubicSpline spline = new CubicSpline();
newMusecAngles = spline.FitAndEval(x, y, xs, false);
angle[i] = newMusecAngles[0];
//string check = string.Format("{0}", newMusecAngles[0]);
//Console.WriteLine(check);
//Console.ReadLine();
}
//DEBUG
//Console.WriteLine("Done conversion");
//Console.Write("conversion check: ");
//string check2 = string.Format("{0}", angle);
//Console.WriteLine(check2);
//cycles through all of the Angles sending them to the serial port one by one.
for (int i = 0; i < 6; i++)
{
//angle = conversion
servo = servoId[i];
result = string.Format("#{0} P{1} T{2} {3}", servo, angle[i], time, Environment.NewLine);
port.Write(result);
}
//prints a statement when finished
//Console.WriteLine("Done and dusted");
//string name = Console.ReadLine();
}
private double mapDist(double coordinate)
{
float[] x = new float[] { (float)kneexlims[0], (float)kneexlims[1], (float)kneexlims[2] };
float[] y = new float[] { (float)finglims[0], (float)finglims[1], (float)finglims[2] };
float[] xs = new float[1];
xs[0] = (float)coordinate;
CubicSpline spline = new CubicSpline();
distance = spline.FitAndEval(x, y, xs, false);
return distance[0];
}
private double mapAngle(double coordinate)
{
float[] x = new float[] {(float)xslidelims[0], (float)xslidelims[1], (float)xslidelims[2] };
float[] y = new float[] { (float)brotlims[0], (float)brotlims[1], (float)brotlims[2] };
float[] xs = new float[1];
xs[0] = (float)coordinate;
CubicSpline spline = new CubicSpline();
angle= spline.FitAndEval(x, y, xs, false);
return angle[0];
}
/// <summary>
/// This is the Wikipedia "Spline Interpolation" article example.
/// </summary>
private static void TestSplineOnWikipediaExample()
{
//파일 읽고 -> 클래스에 파일 데이터(nm,n,k)저장 -> stringToSingle -> 계산 -> 그래프 그리기(Plot)
//파일 입력
string[] Silines = File.ReadAllLines("C://SiN.txt", Encoding.Default);
string[] WaveData = File.ReadAllLines("c://SiO2 2nm_on_Si.dat", Encoding.Default);
List <WaveLengthData> waveLengthDatas = new List <WaveLengthData>();
List <SiData> ReadData = new List <SiData>();
List <SiNData> SINDATA = new List <SiNData>();
List <SIO2Data> sIO2Datas = new List <SIO2Data>();
//x,y 배열
float ValX = 0.0f, ValY1 = 0.0f, ValY2 = 0.0f;
//파일 읽기위해 여백 및 기타 제거
char[] replace = { ' ', ',', '\t', '\n', Convert.ToChar(10), Convert.ToChar(13) };
//파일 생성 및 데이터 add
using (StreamWriter newdatFile = new StreamWriter(new FileStream("SiN_new.txt", FileMode.Create)))
{
//// Create the test points.
//float[] x = new float[] { };
//float[] yToN = new float[] { };
//float[] yToK = new float[] { };
foreach (var line in Silines)
{
string[] splitData = line.Split(replace, StringSplitOptions.RemoveEmptyEntries);
if (ReadData.Count <= 1)
{
ReadData.Add(new SiData());
}
if (ReadData.Count > 1)
{
ReadData.Add(
new SiData
{
NM = splitData[0],
N = splitData[1],
K = splitData[2]
});
}
}
List <float> ListOfFloatNM = new List <float>();
List <float> ListOfFloatN = new List <float>();
List <float> ListOfFloatK = new List <float>();
for (int i = 3; i < Silines.Length; i++)
{
ValX = float.Parse(ReadData[i].NM);
ValY1 = float.Parse(ReadData[i].N);
ValY2 = float.Parse(ReadData[i].K);
ListOfFloatNM.Add(ValX);
ListOfFloatN.Add(ValY1);
ListOfFloatK.Add(ValY2);
}
//ListOfFloatNM.RemoveRange(0, 3);
//ListOfFloatN.RemoveRange(0, 3);
//ListOfFloatK.RemoveRange(0, 3);
float[] x = ListOfFloatNM.ToArray();
float[] yToN = ListOfFloatN.ToArray();
float[] yToK = ListOfFloatK.ToArray();
for (int i = 0; i < yToN.Length; i++)
{
x[i] = (float)Math.Round(x[i], 5);
yToN[i] = (float)Math.Round(yToN[i], 5);
yToK[i] = (float)Math.Round(yToK[i], 5);
}
// silineNum 1470
// 배열의 길이는 1466
int n = 2;
float[] xs = new float[n + 1];
float stepSize = (x[x.Length - 1] - x[0]) / (n - 1);
for (int i = 0; i < n; i++)
{
xs[i] = x[0] + i + stepSize;
}
//fit and eval
CubicSpline spline = new CubicSpline();
float[] ysToN = spline.FitAndEval(x, yToN, xs);
float[] ysToK = spline.FitAndEval(x, yToN, xs);
//plot
string pathToN = "spline-Si-ToN.png";
string pathToK = "spline-Si-ToK.png";
PlotSplineSolution("DolargeSplineToN", x, yToN, xs, ysToN, pathToN);
PlotSplineSolution("DolargeSplineToK", x, yToK, xs, ysToN, pathToK);
}
}