free(sensor_info[s].filter);
sensor_info[s].filter = NULL;
}
+
void denoise_median(struct sensor_info_t* info, struct sensors_event_t* data,
unsigned int num_fields)
{
f_data->idx = (f_data->idx + 1) % f_data->sample_size;
}
+
+#define GLOBAL_HISTORY_SIZE 100
+
+struct recorded_sample_t
+{
+ int sensor;
+ int motion_trigger;
+ sensors_event_t data;
+};
+
+/*
+ * 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 struct recorded_sample_t global_history[GLOBAL_HISTORY_SIZE];
+
+static int initialized_entries; /* How many of these are initialized */
+static int insertion_index; /* Index of sample to evict next time */
+
+
+void record_sample (int s, const struct sensors_event_t* event)
+{
+ struct recorded_sample_t *cell;
+ int i;
+
+ /* Don't record duplicate samples, as they are not useful for filters */
+ if (sensor_info[s].report_pending == DATA_DUPLICATE)
+ return;
+
+ if (initialized_entries == GLOBAL_HISTORY_SIZE) {
+ i = insertion_index;
+ insertion_index = (insertion_index+1) % GLOBAL_HISTORY_SIZE;
+ } else {
+ i = initialized_entries;
+ initialized_entries++;
+ }
+
+ cell = &global_history[i];
+
+ cell->sensor = s;
+
+ cell->motion_trigger = (sensor_info[s].selected_trigger ==
+ sensor_info[s].motion_trigger_name);
+
+ memcpy(&cell->data, event, sizeof(sensors_event_t));
+}