/// <summary>
/// Fit the input x,y points using a 'geometric' strategy so that y does not have to be a single-valued
/// function of x.
/// </summary>
/// <param name="x">Input x coordinates.</param>
/// <param name="y">Input y coordinates, do not need to be a single-valued function of x.</param>
/// <param name="nOutputPoints">How many output points to create.</param>
/// <param name="xs">Output (interpolated) x values.</param>
/// <param name="ys">Output (interpolated) y values.</param>
public static void FitGeometric(float[] x, float[] y, int nOutputPoints, out float[] xs, out float[] ys)
{
// Compute distances
int n = x.Length;
float[] dists = new float[n]; // cumulative distance
dists[0] = 0;
float totalDist = 0;
for (int i = 1; i < n; i++)
{
float dx = x[i] - x[i - 1];
float dy = y[i] - y[i - 1];
float dist = (float)Math.Sqrt(dx * dx + dy * dy);
totalDist += dist;
dists[i] = totalDist;
}
// Create 'times' to interpolate to
float dt = totalDist / (nOutputPoints - 1);
float[] times = new float[nOutputPoints];
times[0] = 0;
for (int i = 1; i < nOutputPoints; i++)
{
times[i] = times[i - 1] + dt;
}
// Spline fit both x and y to times
CubicSpline xSpline = new CubicSpline();
xs = xSpline.FitAndEval(dists, x, times);
CubicSpline ySpline = new CubicSpline();
ys = ySpline.FitAndEval(dists, y, times);
}
/// <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));
}
/// <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 void FilterNoiseBySlope(double slopeThreshold = 10000)
{
if (Peaks.Length < 2) return;
var mzData = new float[Peaks.Length];
var intensityData = new float[Peaks.Length];
var i = 0;
for (i = 0; i < Peaks.Length; i++)
{
mzData[i] = (float) Peaks[i].Mz;
intensityData[i] = (float) Peaks[i].Intensity;
}
var spline = new CubicSpline();
spline.Fit(mzData, intensityData);
var intensitySlope = spline.EvalSlope(mzData);
var filteredPeaks = new List<Peak>();
for (i = 0; i < Peaks.Length; i++)
{
if (Math.Abs(intensitySlope[i]) > slopeThreshold)
filteredPeaks.Add(Peaks[i]);
}
Peaks = filteredPeaks.ToArray();
}
