// Time Series Forecast
//
// time_series_forecast
//
// Time Series Forecast
//
// 
//
// Inputs:    1
// Outputs:   1
// Constants: 0


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


ts_parameter_t const ts_time_series_forecast_p = { .n_inputs = 1, .n_outputs = 1, .n_constants = 0, .params_size = 0 };

uint_t ts_time_series_forecast_offset( ts_constant_t const *c )
{
	( void )c;
	return ( 4 );
}

int ts_time_series_forecast(
	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_time_series_forecast_p );
	(void)c;
	for ( uint_t j = 0; j < n && j < 4; ++j ) y[0][j] = 0;
	for ( uint_t i = 4; i < n; ++i )
	{
		fp_t sum_x = 0, sum_y = 0, sum_xy = 0, sum_x2 = 0;
		for ( uint_t j = 0; j < 5; ++j )
		{
			fp_t xv = (fp_t)j;
			fp_t yv = x[0][i - 4 + j];
			sum_x += xv;
			sum_y += yv;
			sum_xy += xv * yv;
			sum_x2 += xv * xv;
		}
		fp_t denom = 5.0 * sum_x2 - sum_x * sum_x;
		if (denom == 0) {
			y[0][i] = sum_y / 5.0;
		} else {
			fp_t slope = (5.0 * sum_xy - sum_x * sum_y) / denom;
			fp_t intercept = (sum_y - slope * sum_x) / 5.0;
			y[0][i] = intercept + slope * 5.0;
		}
	}
	return 0;
}