/* CCs_to_DTW.c
 *
 *	Dynamic Time Warp of two CCs.
 *
 * Copyright (C) 1993-2011 David Weenink
 *
 * This program is free software; you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation; either version 2 of the License, or (at
 * your option) any later version.
 *
 * This program is distributed in the hope that it will be useful, but
 * WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the GNU
 * General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License
 * along with this program; if not, write to the Free Software
 * Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.
 */

/*
 djmw 2001
 djmw 20020315 GPL header
 djmw 20080122 float -> double
 */

#include "CCs_to_DTW.h"

static void regression (I, long frame, double r[], long nr) {
	iam (CC);

	// sum(i^2;i=-n..n) = 2n^3/3 + n^2 +n/3 = n (n (2n/3 + 1) + 1/3);

	long nrd2 = nr / 2;
	double sumsq = nrd2 * (nrd2 * (nr / 3 + 1) + 1 / 3);

	if (frame <= nrd2 || frame >= my nx - nrd2) {
		return;
	}

	for (long i = 0; i <= my maximumNumberOfCoefficients; i++) {
		r[i] = 0;
	}

	long nmin = CC_getMinimumNumberOfCoefficients (me, frame - nrd2, frame + nrd2);

	for (long i = 0; i <= nmin; i++) {
		double ri = 0;
		for (long j = -nrd2; j <= nrd2; j++) {
			CC_Frame cf = & my frame[frame + j];
			double c = i == 0 ? cf -> c0 : cf -> c[i];
			ri += c * j;
		}
		r[i] = ri / sumsq / my dx;
	}
}


DTW CCs_to_DTW (I, thou, double wc, double wle, double wr, double wer, double dtr, int matchStart, int matchEnd, int constraint) {
	try {
		iam (CC); thouart (CC);

		if (my maximumNumberOfCoefficients != thy maximumNumberOfCoefficients) {
			Melder_throw ("CC orders must be equal.");
		}
		long nr = dtr / my dx;
		if (wr != 0 && nr < 2) {
			Melder_throw ("Time window for regression is too small.");
		}

		if (nr % 2 == 0) {
			nr++;
		}
		if (wr != 0) {
			Melder_casual ("%ld frames used for regression coefficients.", nr);
		}

		autoDTW him = DTW_create (my xmin, my xmax, my nx, my dx, my x1, thy xmin, thy xmax, thy nx, thy dx, thy x1);
		autoNUMvector<double> ri (0L, my maximumNumberOfCoefficients);
		autoNUMvector<double> rj (0L, my maximumNumberOfCoefficients);

		// Calculate distance matrix

		autoMelderProgress progess (L"CCs_to_DTW");
		for (long i = 1; i <= my nx; i++) {
			CC_Frame fi = & my frame[i];

			regression (me, i, ri.peek(), nr);

			for (long j = 1; j <= thy nx; j++) {
				CC_Frame fj = & thy frame[j];
				double dist = 0, distr = 0;

				// Cepstral distance

				if (wc != 0) {
					for (long k = 1; k <= fj -> numberOfCoefficients; k++) {
						double d = fi -> c[k] - fj -> c[k];
						dist += d * d;
					}
					dist *= wc;
				}

				// Log energy distance

				if (wle != 0) {
					double d = fi -> c0 - fj -> c0;
					dist += wle * d * d;
				}

				// Regression distance

				if (wr != 0) {
					regression (thee, j, rj.peek(), nr);
					for (long k = 1; k <= fj -> numberOfCoefficients; k++) {
						double d = ri[k] - rj[k];
						distr += d * d;
					}
					dist += wr * distr;
				}

				// Regression on c[0]: log(energy)

				if (wer != 0) {
					if (wr == 0) {
						regression (thee, j, rj.peek(), nr);
					}
					double d = ri[0] - rj[0];
					dist += wer * d * d;
				}

				dist /= wc + wle + wr + wer;
				his z[i][j] = sqrt (dist);	/* prototype along y-direction */
			}

			if ( (i % 10) == 1) {
				Melder_progress (0.999 * i / my nx, L"Calculate distances: frame ", Melder_integer (i), L" from ", Melder_integer (my nx), L"."); therror
			}
		}
		DTW_findPath (him.peek(), matchStart, matchEnd, constraint);
		return him.transfer();
	} catch (MelderError) {
		Melder_throw ("DTW not created from CCs.");
	}
}

/* End of file CCs_to_DTW.cpp */
