ece486_running_mean.c

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/*!
 * @file
 * 
 * @brief Running Mean Filter Implementation
 * 
 * @author ECE486 Lab Group 0
 * @author Don Hummels
 * 
 * @date Jan 2022
 */
 
 
 
#include <stdlib.h>
#include "ece486_running_mean.h"
 
 
/*
 * build the RUNNING_MEAN_T structure...
 */
RUNNING_MEAN_T *init_running_mean(
        int     M,
            int     blocksize    )
{
  RUNNING_MEAN_T *s;
  int i;
  
  s = (RUNNING_MEAN_T *)malloc( sizeof(RUNNING_MEAN_T) );
  s->M = M;
  s->blocksize = blocksize;
  
  s->history = (float *) malloc ( M * sizeof(float) );
  for (i=0; i<M; i++) s->history[i] = 0.0f;
  
  return(s);
}
 
/*
 * Calculate a filter output samples from a block of input data
 * 
 * Note... This is not a particularly efficient way to implement a running mean filter.  It is meant 
 * simply to provide some test code that returns a (hopefully) correct answer.
 *
 */
void calc_running_mean( RUNNING_MEAN_T *s, float *x_in, float *y_out)
{
  int n; /* Time index for output sample calculation */
  int i;
  
  for (n=0; n< s->blocksize; n++) {
      // Update the "history" buffer to contain the most recent M samples
      //    Current and previous samples are arranged in the history buffer by
      //      s->history[0] = x_in[n]
      //      s->history[1] = x_in[n-1]
      //      s->history[2] = x_in[n-2]
      //      ...
      //      s->history[M-1] = x_in[n-M+1]
      //
      for (i=s->M-1; i>0; i--) {   
          s->history[i] = s->history[i-1];
      }
      s->history[0] = x_in[n];
      
      // Get the nth filter output by averaging the samples in the history buffer
      y_out[n] = 0.0f;
      for (i=0; i<s->M; i++) y_out[n] += s->history[i];
      y_out[n] /= (float) s->M;
  }
 
}
 
/*
 * Release previously allocated memory
 */ 
void destroy_running_mean(RUNNING_MEAN_T *s)
{
  free(s->history);
  free(s);
}