/*
- * Copyright (C) 2014 Intel Corporation.
+ * Copyright (C) 2014-2015 Intel Corporation.
*/
+#include <ctype.h>
+#include <stdlib.h>
#include <hardware/sensors.h>
#include <utils/Log.h>
#include "common.h"
filter_median_t;
+typedef struct
+{
+ int max_samples; /* Maximum averaging window size */
+ int num_fields; /* Number of fields per sample (usually 3) */
+ float *history; /* Working buffer containing recorded samples */
+ float *history_sum; /* The current sum of the history elements */
+ int history_size; /* Number of recorded samples */
+ int history_entries; /* How many of these are initialized */
+ int history_index; /* Index of sample to evict next time */
+}
+filter_average_t;
+
+
static unsigned int partition (float* list, unsigned int left, unsigned int right, unsigned int pivot_index)
{
unsigned int i;
}
+static void denoise_average_init (int s, unsigned int num_fields, unsigned int max_samples)
+{
+ filter_average_t* filter = (filter_average_t*) malloc(sizeof(filter_average_t));
+
+ if (filter) {
+ memset(filter, 0, sizeof(filter_average_t));
+ filter->max_samples = max_samples;
+ filter->num_fields = num_fields;
+ }
+
+ sensor[s].filter = filter;
+}
+
+
static void denoise_median_reset (sensor_info_t* info)
{
filter_median_t* f_data = (filter_median_t*) info->filter;
static void denoise_median (sensor_info_t* info, sensors_event_t* data, unsigned int num_fields)
{
- float x, y, z;
- float scale;
unsigned int field, offset;
filter_median_t* f_data = (filter_median_t*) info->filter;
}
-static void denoise_average (sensor_info_t* si, sensors_event_t* data, int num_fields, int max_samples)
+static void denoise_average (sensor_info_t* si, sensors_event_t* data)
{
/*
* Smooth out incoming data using a moving average over a number of
* depending on which is lower.
*/
- int i;
int f;
int sampling_rate = (int) si->sampling_rate;
int history_size;
int history_full = 0;
+ filter_average_t* filter;
/* Don't denoise anything if we have less than two samples per second */
if (sampling_rate < 2)
return;
+ filter = (filter_average_t*) si->filter;
+
+ if (!filter)
+ return;
+
/* Restrict window size to the min of sampling_rate and max_samples */
- if (sampling_rate > max_samples)
- history_size = max_samples;
+ if (sampling_rate > filter->max_samples)
+ history_size = filter->max_samples;
else
history_size = sampling_rate;
/* Reset history if we're operating on an incorrect window size */
- if (si->history_size != history_size) {
- si->history_size = history_size;
- si->history_entries = 0;
- si->history_index = 0;
- si->history = (float*) realloc(si->history, si->history_size * num_fields * sizeof(float));
- if (si->history) {
- si->history_sum = (float*) realloc(si->history_sum, num_fields * sizeof(float));
- if (si->history_sum)
- memset(si->history_sum, 0, num_fields * sizeof(float));
+ if (filter->history_size != history_size) {
+ filter->history_size = history_size;
+ filter->history_entries = 0;
+ filter->history_index = 0;
+ filter->history = (float*) realloc(filter->history, filter->history_size * filter->num_fields * sizeof(float));
+ if (filter->history) {
+ filter->history_sum = (float*) realloc(filter->history_sum, filter->num_fields * sizeof(float));
+ if (filter->history_sum)
+ memset(filter->history_sum, 0, filter->num_fields * sizeof(float));
}
}
- if (!si->history || !si->history_sum)
+ if (!filter->history || !filter->history_sum)
return; /* Unlikely, but still... */
/* Update initialized samples count */
- if (si->history_entries < si->history_size)
- si->history_entries++;
+ if (filter->history_entries < filter->history_size)
+ filter->history_entries++;
else
history_full = 1;
/* Record new sample and calculate the moving sum */
- for (f=0; f < num_fields; f++) {
+ for (f=0; f < filter->num_fields; f++) {
/** A field is going to be overwritten if history is full, so decrease the history sum */
if (history_full)
- si->history_sum[f] -=
- si->history[si->history_index * num_fields + f];
+ filter->history_sum[f] -= filter->history[filter->history_index * filter->num_fields + f];
- si->history[si->history_index * num_fields + f] = data->data[f];
- si->history_sum[f] += data->data[f];
+ filter->history[filter->history_index * filter->num_fields + f] = data->data[f];
+ filter->history_sum[f] += data->data[f];
/* For now simply compute a mobile mean for each field and output filtered data */
- data->data[f] = si->history_sum[f] / si->history_entries;
+ data->data[f] = filter->history_sum[f] / filter->history_entries;
}
/* Update our rolling index (next evicted cell) */
- si->history_index = (si->history_index + 1) % si->history_size;
+ filter->history_index = (filter->history_index + 1) % filter->history_size;
}
void setup_noise_filtering (int s)
{
char filter_buf[MAX_NAME_SIZE];
+ int num_fields;
+ char* cursor;
+ int window_size = 0;
/* By default, don't apply filtering */
sensor[s].filter_type = FILTER_TYPE_NONE;
+ /* Restrict filtering to a few sensor types for now */
+ switch (sensor[s].type) {
+ case SENSOR_TYPE_ACCELEROMETER:
+ case SENSOR_TYPE_GYROSCOPE:
+ case SENSOR_TYPE_MAGNETIC_FIELD:
+ num_fields = 3 /* x,y,z */;
+ break;
+
+ default:
+ return; /* No filtering */
+ }
+
/* If noisy, start with default filter for sensor type */
if (sensor[s].quirks & QUIRK_NOISY)
switch (sensor[s].type) {
filter_buf[0] = '\0';
sensor_get_st_prop(s, "filter", filter_buf);
- if (strstr(filter_buf, "median"))
+ cursor = strstr(filter_buf, "median");
+ if (cursor)
sensor[s].filter_type = FILTER_TYPE_MEDIAN;
+ else {
+ cursor = strstr(filter_buf, "average");
+ if (cursor)
+ sensor[s].filter_type = FILTER_TYPE_MOVING_AVERAGE;
+ }
- if (strstr(filter_buf, "average"))
- sensor[s].filter_type = FILTER_TYPE_MOVING_AVERAGE;
+ /* Check if an integer is part of the string, and use it as window size */
+ if (cursor) {
+ while (*cursor && !isdigit(*cursor))
+ cursor++;
+
+ if (*cursor)
+ window_size = atoi(cursor);
+ }
switch (sensor[s].filter_type) {
+
case FILTER_TYPE_MEDIAN:
- denoise_median_init(s, 3, 5);
+ denoise_median_init(s, num_fields, window_size ? window_size : 5);
+ break;
+
+ case FILTER_TYPE_MOVING_AVERAGE:
+ denoise_average_init(s, num_fields, window_size ? window_size: 20);
break;
}
}
void denoise (int s, sensors_event_t* data)
{
switch (sensor[s].filter_type) {
+
case FILTER_TYPE_MEDIAN:
denoise_median(&sensor[s], data, 3);
break;
case FILTER_TYPE_MOVING_AVERAGE:
- denoise_average(&sensor[s], data, 3 , 20);
+ denoise_average(&sensor[s], data);
break;
}
}
void release_noise_filtering_data (int s)
{
- void *buff;
-
- /* Delete moving average structures */
- if (sensor[s].history) {
- free(sensor[s].history);
- sensor[s].history = NULL;
- sensor[s].history_size = 0;
- if (sensor[s].history_sum) {
- free(sensor[s].history_sum);
- sensor[s].history_sum = NULL;
- }
- }
+ void *buf;
+
+ if (!sensor[s].filter)
+ return;
+
+ switch (sensor[s].filter_type) {
- /* Delete median filter structures */
- if (sensor[s].filter) {
- buff = ((filter_median_t*) sensor[s].filter)->buff;
+ case FILTER_TYPE_MEDIAN:
+ buf = ((filter_median_t*) sensor[s].filter)->buff;
+ if (buf)
+ free(buf);
+ break;
- if (buff)
- free(buff);
+ case FILTER_TYPE_MOVING_AVERAGE:
+ buf = ((filter_average_t*) sensor[s].filter)->history;
+ if (buf)
+ free(buf);
- free(sensor[s].filter);
- sensor[s].filter = NULL;
+ buf = ((filter_average_t*) sensor[s].filter)->history_sum;
+ if (buf)
+ free(buf);
+ break;
}
+
+ free(sensor[s].filter);
+ sensor[s].filter = NULL;
}