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#ifdef HAVE_CONFIG_H
#include "config.h"
#endif

#include "SigProc_FLP.h"
#include "tuning_parameters.h"
#include "define.h"

/* This code implements the method from https://www.opus-codec.org/docs/vos_fastburg.pdf */

/* Compute reflection coefficients from input signal */
silk_float silk_burg_modified_FLP(
    silk_float          af[],               /* O    prediction coefficients (length order)                      */
    const silk_float    x[],                /* I    input signal, length: nb_subfr*(D+L_sub)                    */
    const silk_float    minInvGain,         /* I    minimum inverse prediction gain                             */
    const opus_int      subfr_length,       /* I    input signal subframe length (incl. D preceding samples)    */
    const opus_int      nb_subfr,           /* I    number of subframes stacked in x                            */
    const opus_int      D                   /* I    order                                                       */
)
{
    opus_int         k, n, s, reached_max_gain;
    double           invGain, num, nrg, rc, tmp1, tmp2, x1, x2, atmp;
    const silk_float *x_ptr;
	double           c[ SILK_MAX_ORDER_LPC + 1 ];
	double           g[ SILK_MAX_ORDER_LPC + 1 ];
    double           a[ SILK_MAX_ORDER_LPC ];

    /* Compute autocorrelations, added over subframes */
    silk_memset( c, 0, (D + 1) * sizeof( double ) );
    for( s = 0; s < nb_subfr; s++ ) {
        x_ptr = x + s * subfr_length;
        for( n = 0; n < D + 1; n++ ) {
            c[ n ] += silk_inner_product_FLP( x_ptr, x_ptr + n, subfr_length - n );
        }
    }
    for( n = 0; n < D + 1; n++ ) {
		c[ n ] *= 2.0;
	}

    /* Initialize */
	c[ 0 ] += FIND_LPC_COND_FAC * c[ 0 ] + 1e-9f ;
    g[ 0 ] = c[ 0 ];
	tmp1 = 0.0f;
    for( s = 0; s < nb_subfr; s++ ) {
        x_ptr = x + s * subfr_length;
		x1 = x_ptr[ 0 ];
		x2 = x_ptr[ subfr_length - 1 ];
		tmp1 += x1 * x1 + x2 * x2;
	}
	g[ 0 ] -= tmp1;
	g[ 1 ] = c[ 1 ];
	rc = - g[ 1 ] / g[ 0 ];
    silk_assert( rc > -1.0 && rc < 1.0 );
	a[ 0 ] = rc;
    invGain = ( 1.0 - rc * rc );
    reached_max_gain = 0;
    for( n = 1; n < D; n++ ) {
        for( k = 0; k < (n >> 1) + 1; k++ ) {
            tmp1 = g[ k ];
            tmp2 = g[ n - k ];
            g[ k ]     = tmp1 + rc * tmp2;
            g[ n - k ] = tmp2 + rc * tmp1;
        }
        for( s = 0; s < nb_subfr; s++ ) {
            x_ptr = x + s * subfr_length;
			x1 = x_ptr[ n ];
			x2 = x_ptr[ subfr_length - n - 1 ];
            tmp1 = x1;
            tmp2 = x2;
            for( k = 0; k < n; k++ ) {
				atmp = a[ k ];
				c[ k + 1 ] -= x1 * x_ptr[ n - k - 1 ] + x2 * x_ptr[ subfr_length - n + k ];
                tmp1 += x_ptr[ n - k - 1 ] * atmp;
                tmp2 += x_ptr[ subfr_length - n + k ] * atmp;
            }
            for( k = 0; k <= n; k++ ) {
                g[ k ] -= tmp1 * x_ptr[ n - k ] + tmp2 * x_ptr[ subfr_length - n + k - 1 ];
            }
        }

        /* Calculate nominator and denominator for the next order reflection (parcor) coefficient */
		tmp1 = c[ n + 1 ];
        num = 0.0f;
        nrg = g[ 0 ];
        for( k = 0; k < n; k++ ) {
			atmp = a[ k ];
			tmp1 += c[ n - k ] * atmp;
            num  += g[ n - k ] * atmp;
            nrg  += g[ k + 1 ] * atmp;
        }
		g[ n + 1] = tmp1;
		num += tmp1;
        silk_assert( nrg > 0.0 );

        /* Calculate the next order reflection (parcor) coefficient */
        rc = -num / nrg;
        silk_assert( rc > -1.0 && rc < 1.0 );

        /* Update inverse prediction gain */
        tmp1 = invGain * ( 1.0 - rc * rc );
        if( tmp1 <= minInvGain ) {
            /* Max prediction gain exceeded; set reflection coefficient such that max prediction gain is exactly hit */
            rc = sqrt( 1.0 - minInvGain / invGain );
            if( num > 0 ) {
                /* Ensure adjusted reflection coefficient has the original sign */
                rc = -rc;
            }
            invGain = minInvGain;
            reached_max_gain = 1;
        } else {
            invGain = tmp1;
        }

        /* Update the AR coefficients */
        for( k = 0; k < (n + 1) >> 1; k++ ) {
            tmp1 = a[ k ];
            tmp2 = a[ n - k - 1 ];
            a[ k ]         = tmp1 + rc * tmp2;
            a[ n - k - 1 ] = tmp2 + rc * tmp1;
        }
        a[ n ] = rc;

        if( reached_max_gain ) {
            /* Reached max prediction gain; set remaining coefficients to zero and exit loop */
            for( k = n + 1; k < D; k++ ) {
                a[ k ] = 0.0;
            }
            break;
        }
    }

	/* Convert to silk_float */
	for( k = 0; k < D; k++ ) {
		af[ k ] = (silk_float)( -a[ k ] );
	}

    nrg = c[ 0 ] * 0.5 * (1.0 - FIND_LPC_COND_FAC);
    /* Subtract energy of preceding samples from C0 */
    for( s = 0; s < nb_subfr; s++ ) {
        nrg -= silk_energy_FLP( x + s * subfr_length, D );
    }
    /* Approximate residual energy */
    nrg *= invGain;

    /* Return approximate residual energy */
    return (silk_float)nrg;
}