public void FromTwoPointsは2つの点から直線を求める(double x0, double y0, double x1, double y1, double expectedA,
double expectedB)
{
var lf = new Linear(new Point(x0, y0), new Point(x1, y1));
Assert.AreEqual(expectedA, lf.A);
Assert.AreEqual(expectedB, lf.B);
}
public void InverseFunctionは引数0の時0()
{
var lf = new Linear(0, 0);
var f = lf.InverseFunction;
Assert.AreEqual(0, f(1));
Assert.AreEqual(0, f(2));
Assert.AreEqual(0, f(3));
}
public void InverseFunctionはFunctionの逆関数(double arg)
{
var lf = new Linear(2, 3);
var f = lf.InverseFunction(lf.Function(arg));
var g = lf.Function(lf.InverseFunction(arg));
Assert.AreEqual(arg, f);
Assert.AreEqual(arg, g);
}
public void GetLeastSquareLineTest_Intercept()
{
var expected = new Linear(1.8993, 0);
const double expectedR2 = 0.8653;
var actual = Statistics.GetLeastSquaresLine(TestPoints(), 0.0);
var actualR2 = Statistics.GetR2(actual, TestPoints());
Assert.AreEqual(expected.A, actual.A, 0.001);
Assert.AreEqual(expected.B, actual.B, 0.001);
Assert.AreEqual(expectedR2, actualR2, 0.01);
}
public void GetLeastSquareLineTest()
{
var expected = new Linear(1.4872, 13.762);
const double expectedR2 = 0.9454;
var actual = Statistics.GetLeastSquaresLine(TestPoints());
var actualR2 = Statistics.GetR2(actual, TestPoints());
Assert.AreEqual(expected.A, actual.A, 0.001);
Assert.AreEqual(expected.B, actual.B, 0.001);
Assert.AreEqual(expectedR2, actualR2, 0.01);
}
public static double GetR2(Linear func, [NotNull] IEnumerable<Point> points)
{
if (points == null) throw new ArgumentNullException("points");
var pointArray = points as Point[] ?? points.ToArray();
if (!pointArray.Any())
throw new ArgumentException("points");
var f = func.Function;
var a = pointArray.Sum(p => Math.Pow(p.Y - f(p.X), 2));
var ave = pointArray.Average(p => p.Y);
var b = pointArray.Sum(p => Math.Pow(p.Y - ave, 2));
return !b.IsZero() ? 1.0 - (a/b) : 0.0;
}
/// <summary>
/// Saves the current set of spectrums in a CSV file.
/// </summary>
public static void SaveAsCsv([NotNull] double[][] spectrums, double realTime, double liveTime, Linear intoEnergy,
[NotNull] string path)
{
if (spectrums == null) throw new ArgumentNullException("spectrums");
var sb = new StringBuilder();
sb.AppendLine("RT," + realTime);
sb.AppendLine("LT," + liveTime);
sb.AppendLine("CAL," + intoEnergy);
foreach (var j in Enumerable.Range(0, NumOfChannels)) {
var j1 = j;
sb.AppendLine(Enumerable.Range(0, spectrums.Count())
.Select(i => spectrums[i][j1].ToString(CultureInfo.InvariantCulture))
.ConcatWithComma());
}
File.WriteAllText(path, sb.ToString());
}
public void XPlotRegionTest()
{
var cr = new Region(0, 1000);
var calibrated = new Region(3, 2003);
var calibration = new Linear(2, 3);
var sg = new SpectralGraph {
XChannelRegion = cr,
IsCalibrated = false,
Calibration = calibration
};
Assert.AreEqual(cr, sg.XChannelRegion);
Assert.AreEqual(cr, sg.XPlotRegion);
sg.IsCalibrated = true;
Assert.AreEqual(cr, sg.XChannelRegion);
Assert.AreEqual(calibrated, sg.XPlotRegion);
sg.Calibration = new Linear(3, 4);
Assert.AreEqual(cr, sg.XChannelRegion);
Assert.AreEqual(new Region(4, 3004), sg.XPlotRegion);
sg.IsCalibrated = false;
Assert.AreEqual(cr, sg.XChannelRegion);
Assert.AreEqual(cr, sg.XPlotRegion);
}
public void インスタンス生成_引数あり()
{
var lf = new Linear(2, 3);
Assert.AreEqual(2, lf.A);
Assert.AreEqual(3, lf.B);
Assert.IsNotNull(lf.Function);
Assert.IsNotNull(lf.InverseFunction);
}
public void インスタンス生成()
{
var lf = new Linear();
Assert.IsNotNull(lf.A);
Assert.IsNotNull(lf.B);
Assert.IsNotNull(lf.Function);
Assert.IsNotNull(lf.InverseFunction);
}
public void ToStringは右辺のみでこんな感じ(double a, double b, [NotNull] string expected)
{
var lf = new Linear(a, b);
Assert.AreEqual(expected, lf.ToString());
}
public void FunctionはAx_plus_Bのはず(double arg, double expected)
{
var lf = new Linear(2, 3);
var f = lf.Function;
Assert.AreEqual(expected, f(arg));
}
public void FromTwoPointsは同じ点２つや傾き無限大なら傾きnaNを返す(double x0, double y0, double x1, double y1)
{
var lf = new Linear(new Point(x0, y0), new Point(x1, y1));
Assert.AreEqual(new Linear(double.NaN, x0).A, lf.A);
}
public void FromGradientAndPointは傾きと一点から直線を求める(double grad, double x, double y, double expectedA,
double expectedB)
{
var lf = new Linear(grad, new Point(x, y));
Assert.AreEqual(new Linear(expectedA, expectedB), lf);
}
