/*
 *  R : A Computer Language for Statistical Data Analysis
 *  Copyright (C) 1995, 1996  Robert Gentleman and Ross Ihaka
 *  Copyright (C) 1998--2001  Robert Gentleman, Ross Ihaka and the
 *                            R Development Core Team
 *
 *  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., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301  USA
 */

/*	Spline Interpolation
 *	--------------------
 *	C code to perform spline fitting and interpolation.
 *	There is code here for:
 *
 *	1. Natural splines.
 *
 *	2. Periodic splines
 *
 *	3. Splines with end-conditions determined by fitting
 *	   cubics in the start and end intervals (Forsythe et al).
 *
 *
 *	Computational Techniques
 *	------------------------
 *	A special LU decomposition for symmetric tridiagonal matrices
 *	is used for all computations, except for periodic splines where
 *	Choleski is more efficient.
 */

#ifdef HAVE_CONFIG_H
#include <config.h>
#endif

#include <R_ext/Arith.h>
#include <R_ext/Applic.h>
#include <stdio.h>
#include <errno.h>

/*
 *	Natural Splines
 *	---------------
 *	Here the end-conditions are determined by setting the second
 *	derivative of the spline at the end-points to equal to zero.
 *
 *	There are n-2 unknowns (y[i]'' at x[2], ..., x[n-1]) and n-2
 *	equations to determine them.  Either Choleski or Gaussian
 *	elimination could be used.
 */

void natural_spline(int n, double *x, double *y, double *b, double *c, double *d)
{
    int nm1, i;
    double t;

    x--; y--; b--; c--; d--;

    if(n < 2) {
	errno = EDOM;
	return;
    }

    if(n < 3) {
	t = (y[2] - y[1]);
	b[1] = t / (x[2]-x[1]);
	b[2] = b[1];
	c[1] = c[2] = d[1] = d[2] = 0.0;
	return;
    }

    nm1 = n - 1;

    /* Set up the tridiagonal system */
    /* b = diagonal, d = offdiagonal, c = right hand side */

    d[1] = x[2] - x[1];
    c[2] = (y[2] - y[1])/d[1];
    for( i=2 ; i<n ; i++) {
	d[i] = x[i+1] - x[i];
	b[i] = 2.0 * (d[i-1] + d[i]);
	c[i+1] = (y[i+1] - y[i])/d[i];
	c[i] = c[i+1] - c[i];
    }

    /* Gaussian elimination */

    for(i=3 ; i<n ; i++) {
	t = d[i-1]/b[i-1];
	b[i] = b[i] - t*d[i-1];
	c[i] = c[i] - t*c[i-1];
    }

    /* Backward substitution */

    c[nm1] = c[nm1]/b[nm1];
    for(i=n-2 ; i>1 ; i--)
	c[i] = (c[i]-d[i]*c[i+1])/b[i];

    /* End conditions */

    c[1] = c[n] = 0.0;

    /* Get cubic coefficients */

    b[1] = (y[2] - y[1])/d[1] - d[i] * c[2];
    c[1] = 0.0;
    d[1] = c[2]/d[1];
    b[n] = (y[n] - y[nm1])/d[nm1] + d[nm1] * c[nm1];
    for(i=2 ; i<n ; i++) {
	b[i] = (y[i+1]-y[i])/d[i] - d[i]*(c[i+1]+2.0*c[i]);
	d[i] = (c[i+1]-c[i])/d[i];
	c[i] = 3.0*c[i];
    }
    c[n] = 0.0;
    d[n] = 0.0;

    return;
}

/*
 *	Splines a la Forsythe Malcolm and Moler
 *	---------------------------------------
 *	In this case the end-conditions are determined by fitting
 *	cubic polynomials to the first and last 4 points and matching
 *	the third derivitives of the spline at the end-points to the
 *	third derivatives of these cubics at the end-points.
 */

void fmm_spline(int n, double *x, double *y, double *b, double *c, double *d)
{
    int nm1, i;
    double t;

    /* Adjustment for 1-based arrays */

    x--; y--; b--; c--; d--;

    if(n < 2) {
	errno = EDOM;
	return;
    }

    if(n < 3) {
	t = (y[2] - y[1]);
	b[1] = t / (x[2]-x[1]);
	b[2] = b[1];
	c[1] = c[2] = d[1] = d[2] = 0.0;
	return;
    }

    nm1 = n - 1;

    /* Set up tridiagonal system */
    /* b = diagonal, d = offdiagonal, c = right hand side */

    d[1] = x[2] - x[1];
    c[2] = (y[2] - y[1])/d[1];/* = +/- Inf	for x[1]=x[2] -- problem? */
    for(i=2 ; i<n ; i++) {
	d[i] = x[i+1] - x[i];
	b[i] = 2.0 * (d[i-1] + d[i]);
	c[i+1] = (y[i+1] - y[i])/d[i];
	c[i] = c[i+1] - c[i];
    }

    /* End conditions. */
    /* Third derivatives at x[0] and x[n-1] obtained */
    /* from divided differences */

    b[1] = -d[1];
    b[n] = -d[nm1];
    c[1] = c[n] = 0.0;
    if(n > 3) {
	c[1] = c[3]/(x[4]-x[2]) - c[2]/(x[3]-x[1]);
	c[n] = c[nm1]/(x[n] - x[n-2]) - c[n-2]/(x[nm1]-x[n-3]);
	c[1] = c[1]*d[1]*d[1]/(x[4]-x[1]);
	c[n] = -c[n]*d[nm1]*d[nm1]/(x[n]-x[n-3]);
    }

    /* Gaussian elimination */

    for(i=2 ; i<=n ; i++) {
	t = d[i-1]/b[i-1];
	b[i] = b[i] - t*d[i-1];
	c[i] = c[i] - t*c[i-1];
    }

    /* Backward substitution */

    c[n] = c[n]/b[n];
    for(i=nm1 ; i>=1 ; i--)
	c[i] = (c[i]-d[i]*c[i+1])/b[i];

    /* c[i] is now the sigma[i-1] of the text */
    /* Compute polynomial coefficients */

    b[n] = (y[n] - y[n-1])/d[n-1] + d[n-1]*(c[n-1]+ 2.0*c[n]);
    for(i=1 ; i<=nm1 ; i++) {
	b[i] = (y[i+1]-y[i])/d[i] - d[i]*(c[i+1]+2.0*c[i]);
	d[i] = (c[i+1]-c[i])/d[i];
	c[i] = 3.0*c[i];
    }
    c[n] = 3.0*c[n];
    d[n] = d[nm1];
    return;
}


/*
 *	Periodic Spline
 *	---------------
 *	The end conditions here match spline (and its derivatives)
 *	at x[1] and x[n].
 *
 *	Note: There is an explicit check that the user has supplied
 *	data with y[1] equal to y[n].
 */

void periodic_spline(int n, double *x, double *y,
		     double *b, double *c, double *d, double *e)
{
    double s;
    int i, nm1;

    /* Adjustment for 1-based arrays */

    x--; y--; b--; c--; d--; e--;

    if(n < 2 || y[1] != y[n]) {
	errno = EDOM;
	return;
    }

    nm1 = n-1;

    /* Set up the matrix system */
    /* A = diagonal	 B = off-diagonal  C = rhs */

#define A	b
#define B	d
#define C	c

    B[1]  = x[2] - x[1];
    B[nm1]= x[n] - x[nm1];
    A[1] = 2.0 * (B[1] + B[nm1]);
    C[1] = (y[2] - y[1])/B[1] - (y[n] - y[nm1])/B[nm1];

    for(i = 2; i < n; i++) {
	B[i] = x[i+1] - x[i];
	A[i] = 2.0 * (B[i] + B[i-1]);
	C[i] = (y[i+1] - y[i])/B[i] - (y[i] - y[i-1])/B[i-1];
    }

    /* Choleski decomposition */

#define L	b
#define M	d
#define E	e

    L[1] = sqrt(A[1]);
    E[1] = (x[n] - x[nm1])/L[1];
    s = 0.0;
    for(i = 1; i <= nm1 - 2; i++) {
	M[i] = B[i]/L[i];
	if(i != 1) E[i] = -E[i-1] * M[i-1] / L[i];
	L[i+1] = sqrt(A[i+1]-M[i]*M[i]);
	s = s + E[i] * E[i];
    }
    M[nm1-1] = (B[nm1-1] - E[nm1-2] * M[nm1-2])/L[nm1-1];
    L[nm1] = sqrt(A[nm1] - M[nm1-1]*M[nm1-1] - s);

    /* Forward Elimination */

#define Y	c
#define D	c

    Y[1] = D[1]/L[1];
    s = 0.0;
    for(i=2 ; i<=nm1-1 ; i++) {
	Y[i] = (D[i] - M[i-1]*Y[i-1])/L[i];
	s = s + E[i-1] * Y[i-1];
    }
    Y[nm1] = (D[nm1] - M[nm1-1] * Y[nm1-1] - s) / L[nm1];

#define X	c

    X[nm1] = Y[nm1]/L[nm1];
    X[nm1-1] = (Y[nm1-1] - M[nm1-1] * X[nm1])/L[nm1-1];
    for(i=nm1-2 ; i>=1 ; i--)
	X[i] = (Y[i] - M[i] * X[i+1] - E[i] * X[nm1])/L[i];

    /* Wrap around */

    X[n] = X[1];

    /* Compute polynomial coefficients */

    for(i=1 ; i<=nm1 ; i++) {
	s = x[i+1] - x[i];
	b[i] = (y[i+1]-y[i])/s - s*(c[i+1]+2.0*c[i]);
	d[i] = (c[i+1]-c[i])/s;
	c[i] = 3.0*c[i];
    }
    b[n] = b[1];
    c[n] = c[1];
    d[n] = d[1];
    return;
}
#undef A
#undef B
#undef C
#undef L
#undef M
#undef E
#undef Y
#undef D
#undef X

void spline_coef(int *method, int *n, double *x, double *y,
		 double *b, double *c, double *d, double *e)
{
    switch(*method) {
    case 1:
	periodic_spline(*n, x, y, b, c, d, e);	break;

    case 2:
	natural_spline(*n, x, y, b, c, d);	break;

    case 3:
	fmm_spline(*n, x, y, b, c, d);	break;
    }
}

void spline_eval(int *method, int *nu, double *u, double *v,
		 int *n, double *x, double *y, double *b, double *c, double *d)
{
/* Evaluate  v[l] := spline(u[l], ...),	    l = 1,..,nu, i.e. 0:(nu-1)
 * Nodes x[i], coef (y[i]; b[i],c[i],d[i]); i = 1,..,n , i.e. 0:(*n-1)
 */
    const int n_1 = *n - 1;
    int i, j, k, l;
    double ul, dx, tmp;

    if(*method == 1 && *n > 1) {
	dx = x[n_1] - x[0];
	for(l = 0; l < *nu; l++) {
	    v[l] = fmod(u[l]-x[0], dx);
	    if(v[l] < 0.0) v[l] += dx;
	    v[l] += x[0];
	}
    }
    else {
	for(l = 0; l < *nu; l++)
	    v[l] = u[l];
    }

    i = 0;
    for(l = 0; l < *nu; l++) {
	ul = v[l];
	if(ul < x[i] || (i < n_1 && x[i+1] < ul)) {
	    i = 0;
	    j = *n;
	    do {
		k = (i+j)/2;
		if(ul < x[k]) j = k;
		else i = k;
	    }
	    while(j > i+1);
	}
	dx = ul - x[i];
	/* for natural splines extrapolate linearly left */
	tmp = (*method == 2 && ul < x[0]) ? 0.0 : d[i];

	v[l] = y[i] + dx*(b[i] + dx*(c[i] + dx*tmp));
    }
}