filter_median_t;
-static unsigned int partition ( float* list, unsigned int left,
- unsigned int right, unsigned int pivot_index)
+static unsigned int partition (float* list, unsigned int left, unsigned int right, unsigned int pivot_index)
{
unsigned int i;
unsigned int store_index = left;
}
-static void denoise_median_init(int s, unsigned int num_fields,
- unsigned int max_samples)
+static void denoise_median_init (int s, unsigned int num_fields, unsigned int max_samples)
{
- filter_median_t* f_data = (filter_median_t*)
- malloc(sizeof(filter_median_t));
+ filter_median_t* f_data = (filter_median_t*) malloc(sizeof(filter_median_t));
f_data->buff = (float*) calloc(max_samples, sizeof(float) * num_fields);
f_data->sample_size = max_samples;
}
-static void denoise_median ( sensor_info_t* info,
- sensors_event_t* data,
- unsigned int num_fields)
+static void denoise_median (sensor_info_t* info, sensors_event_t* data, unsigned int num_fields)
{
float x, y, z;
float scale;
}
-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, int num_fields, int max_samples)
{
/*
* Smooth out incoming data using a moving average over a number of
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));
+ 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));
+ 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));
}
/* Record new sample and calculate the moving sum */
for (f=0; f < num_fields; f++) {
- /**
- * A field is going to be overwritten if
- * history is full, so decrease the history sum
- */
+ /** 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];
si->history[si->history_index * num_fields + f] = data->data[f];
si->history_sum[f] += data->data[f];
- /* For now simply compute a mobile mean for each field */
- /* and output filtered data */
+ /* For now simply compute a mobile mean for each field and output filtered data */
data->data[f] = si->history_sum[f] / si->history_entries;
}
recorded_sample_t;
/*
- * This is a circular buffer holding the last GLOBAL_HISTORY_SIZE events,
- * covering the entire sensor collection. It is intended as a way to correlate
- * data coming from active sensors, no matter the sensor type, over a recent
- * window of time. The array is not sorted ; we simply evict the oldest cell
- * (by insertion time) and replace its contents. Timestamps don't necessarily
- * grow monotonically as they tell the data acquisition type, and that there can
- * be a delay between acquisition and insertion into this table.
+ * This is a circular buffer holding the last GLOBAL_HISTORY_SIZE events, covering the entire sensor collection. It is intended as a way to correlate
+ * data coming from active sensors, no matter the sensor type, over a recent window of time. The array is not sorted ; we simply evict the oldest cell
+ * (by insertion time) and replace its contents. Timestamps don't necessarily grow monotonically as they tell the data acquisition type, and that there
+ * can be a delay between acquisition and insertion into this table.
*/
static recorded_sample_t global_history[GLOBAL_HISTORY_SIZE];
cell->sensor = s;
- cell->motion_trigger = (sensor[s].selected_trigger ==
- sensor[s].motion_trigger_name);
+ cell->motion_trigger = (sensor[s].selected_trigger == sensor[s].motion_trigger_name);
memcpy(&cell->data, event, sizeof(sensors_event_t));
}