// Variance
//
// variance - smv
//
// Calculates the moving variance
//
// Inputs:    1
// Outputs:   1
// Constants: 0


#include "ts.h"


typedef struct {
    uint_t k;
} ts_variance_params_t;

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


uint_t ts_variance_offset( ts_constant_t const *c )
{
	( void )c;
	return ( c ? ((ts_variance_params_t const *)c)->k > 0 ? ((ts_variance_params_t const *)c)->k - 1 : 0 : 0 );
}

int ts_variance(
	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_variance_p );
	if ( !c ) return -1;
	TS_CHECK_INPUT(x, x_n, n);
	uint_t k = ((ts_variance_params_t const *)c)->k;
	if (k == 0 || n < k) return -1;

	uint_t xi = 0;
	uint_t yi = k;

	fp_t sum = 0;  // Sum of terms
	fp_t sum2 = 0; // Sum of squared terms
	fp_t mean;     // Mean
	fp_t mean2;    // Mean of squares

	for( ; xi < k; ++xi )
	{
		sum += x[0][xi];
		sum2 += _ts_square( x[0][xi] );

		mean = sum / ( xi + 1 );
		mean2 = sum2 / ( xi + 1 );
	}

	fp_t var = mean2 - _ts_square( mean );
	y[0][k - 1] = var >= 0 ? var : 0.0;

    fp_t rk = _ts_reciprocal( k );

	for( ; xi < n; ++xi, ++yi )
	{
		mean = mean + ( x[0][xi] - x[0][xi - k] ) * rk;
		mean2 = mean2 + ( _ts_square( x[0][xi] ) - _ts_square( x[0][xi - k] ) ) * rk;

		var = mean2 - _ts_square( mean );
		y[0][yi] = var >= 0 ? var : 0.0;
	}
	return 0;
}