#ifndef AVUTIL_LLS_H
#define AVUTIL_LLS_H
+#include "macros.h"
+#include "mem.h"
+#include "version.h"
+
#define MAX_VARS 32
+#define MAX_VARS_ALIGN FFALIGN(MAX_VARS+1,4)
//FIXME avoid direct access to LLSModel from outside
* Linear least squares model.
*/
typedef struct LLSModel {
- double covariance[MAX_VARS + 1][MAX_VARS + 1];
- double coeff[MAX_VARS][MAX_VARS];
+ DECLARE_ALIGNED(32, double, covariance[MAX_VARS_ALIGN][MAX_VARS_ALIGN]);
+ DECLARE_ALIGNED(32, double, coeff[MAX_VARS][MAX_VARS]);
double variance[MAX_VARS];
int indep_count;
+ /**
+ * Take the outer-product of var[] with itself, and add to the covariance matrix.
+ * @param m this context
+ * @param var training samples, starting with the value to be predicted
+ * 32-byte aligned, and any padding elements must be initialized
+ * (i.e not denormal/nan).
+ */
+ void (*update_lls)(struct LLSModel *m, double *var);
+ /**
+ * Inner product of var[] and the LPC coefs.
+ * @param m this context
+ * @param var training samples, excluding the value to be predicted. unaligned.
+ * @param order lpc order
+ */
+ double (*evaluate_lls)(struct LLSModel *m, double *var, int order);
} LLSModel;
-void av_init_lls(LLSModel *m, int indep_count);
-void av_update_lls(LLSModel *m, double *param, double decay);
-void av_solve_lls(LLSModel *m, double threshold, int min_order);
-double av_evaluate_lls(LLSModel *m, double *param, int order);
+void avpriv_init_lls(LLSModel *m, int indep_count);
+void ff_init_lls_x86(LLSModel *m);
+void avpriv_solve_lls(LLSModel *m, double threshold, unsigned short min_order);
#endif /* AVUTIL_LLS_H */