// Kaufman Adaptive Ma
//
// kaufman_adaptive_ma
//
// Kaufman Adaptive Moving Average
//
// AMA based on efficiency ratio
//
// Inputs:    1
// Outputs:   1
// Constants: 1


#include <math.h>
#include "ts.h"

typedef struct {
    uint_t k;
} ts_kaufman_adaptive_ma_params_t;

ts_parameter_t const ts_kaufman_adaptive_ma_p = { .n_inputs = 1, .n_outputs = 1, .n_constants = 1, .params_size = sizeof(ts_kaufman_adaptive_ma_params_t) };

uint_t ts_kaufman_adaptive_ma_offset( ts_constant_t const *c )
{
	( void )c;
	return ( c ? ((ts_kaufman_adaptive_ma_params_t const *)c)->k : 0 );
}

int ts_kaufman_adaptive_ma(
	fp_t * const *y, uint_t y_n,
	fp_t const * const *x, uint_t x_n,
	uint_t n, ts_constant_t const *c
)
{
	TS_PROLOGUE( ts_kaufman_adaptive_ma_p );
	if ( !c ) return -1;
    uint_t k = ((ts_kaufman_adaptive_ma_params_t const *)c)->k;
    if (k == 0 || n < k) return -1;

    fp_t ama = x[0][0];
    fp_t sm = 2.0 / ((fp_t)k + 1.0);
    fp_t sn = 2.0 / (sqrt((fp_t)k) + 1.0);

    for (uint_t i = k; i < n; ++i)
    {
        fp_t price_change = fabs(x[0][i] - x[0][i - k]);
        fp_t noise = 0;
        for (uint_t j = i - k + 1; j <= i; ++j)
            noise += fabs(x[0][j] - x[0][j - 1]);

        fp_t er = noise != 0 ? price_change / noise : 0;
        fp_t er_sq = er * er;
        fp_t sc = er_sq * (sn - sm) + sm;
        sc = sc * sc;

        ama = ama + sc * (x[0][i] - ama);
        y[0][i] = ama;
    }
    return 0;
}