I'm using alglib's spline1dfit function to smooth some noisy analog electrical signals for characterization purposes. The fitting works very well along the entire window of input data except for at the edges. Check out the attached picture, which shows the spline diverging from the last few data points in both signals.

Here's my C++ code for performing the fit:

**Code:**

void denoiser::process(const QVector<double> &input_signal, QVector<double> &output_signal)

{

// Set up X and Y arrays

alglib::real_1d_array x, y;

// Populate x array.

x.setlength(input_signal.size());

for(int32_t i = 0; i < input_signal.size(); i++)

{

x[i] = i;

}

// Attach y array to input signal data (shares pointer so no copying)

y.attach_to_ptr(input_signal.size(), const_cast<double*>(input_signal.data()));

// Set up spline interpolant and fit report structures to capture output.

alglib::spline1dinterpolant interpolant;

alglib::spline1dfitreport fit_report;

// Perform fitting.

alglib::spline1dfit(x, y, x.length(), 10*x.length(), denoiser::lambda, interpolant, fit_report);

// Populate output with fitted spline.

output_signal.clear();

output_signal.reserve(input_signal.size());

for(int32_t i = 0; i < input_signal.size(); i++)

{

output_signal.append(alglib::spline1dcalc(interpolant, i));

}

}

The typical data length (N) is between 100 and 500 data points. I've tried using all kinds of values of M, including M = 0.1*N through M = 10*N. It has no effect on the divergence of the spline at the beginning/end of the window. I'm using a lambda of 0.0001.

It seems like spline1dfit is simply ignoring the first/last few points when performing the fit, even though I've specified N.

Anybody have any ideas on what might be going on here? Thanks!