#define GRAVITY 9.80665f
/* 720 LSG = 1G */
-#define LSG (1024.0f)
-#define NUMOFACCDATA (8.0f)
+#define LSG (1024.0)
+#define NUMOFACCDATA (8.0)
/* conversion of acceleration data to SI units (m/s^2) */
#define CONVERT_A (GRAVITY_EARTH / LSG / NUMOFACCDATA)
#define CONVERT_A_Z(x) ((float(x)/1000) * (GRAVITY * 1.0))
/* conversion of magnetic data to uT units */
-#define CONVERT_M (1.0f/6.6f)
+#define CONVERT_M (1.0/6.6)
#define CONVERT_M_X (-CONVERT_M)
#define CONVERT_M_Y (-CONVERT_M)
#define CONVERT_M_Z (CONVERT_M)
-#define CONVERT_GAUSS_TO_MICROTESLA(x) ( (x) * 100 )
+#define CONVERT_GAUSS_TO_MICROTESLA(x) ((x) * 100 )
/* conversion of orientation data to degree units */
-#define CONVERT_O (1.0f/64.0f)
+#define CONVERT_O (1.0/64)
#define CONVERT_O_A (CONVERT_O)
#define CONVERT_O_P (CONVERT_O)
#define CONVERT_O_R (-CONVERT_O)
/*conversion of gyro data to SI units (radian/sec) */
-#define CONVERT_GYRO ((2000.0f/32767.0f)*((float)M_PI / 180.0f))
+#define CONVERT_GYRO (2000.0/32767*M_PI/180)
#define CONVERT_GYRO_X (-CONVERT_GYRO)
#define CONVERT_GYRO_Y (-CONVERT_GYRO)
#define CONVERT_GYRO_Z (CONVERT_GYRO)
}
}
-// Platform sensor orientation
+/* Platform sensor orientation */
#define DEF_ORIENT_ACCEL_X -1
#define DEF_ORIENT_ACCEL_Y -1
#define DEF_ORIENT_ACCEL_Z -1
#define DEF_ORIENT_GYRO_Y 1
#define DEF_ORIENT_GYRO_Z 1
-// G to m/s2
+/* G to m/s2 */
#define CONVERT_FROM_VTF16(s,d,x) (convert_from_vtf_format(s,d,x))
#define CONVERT_A_G_VTF16E14_X(s,d,x) (DEF_ORIENT_ACCEL_X *\
convert_from_vtf_format(s,d,x)*GRAVITY)
#define CONVERT_A_G_VTF16E14_Z(s,d,x) (DEF_ORIENT_ACCEL_Z *\
convert_from_vtf_format(s,d,x)*GRAVITY)
-// Degree/sec to radian/sec
+/* Degree/sec to radian/sec */
#define CONVERT_G_D_VTF16E14_X(s,d,x) (DEF_ORIENT_GYRO_X *\
convert_from_vtf_format(s,d,x) * \
- ((float)M_PI/180.0f))
+ M_PI/180)
#define CONVERT_G_D_VTF16E14_Y(s,d,x) (DEF_ORIENT_GYRO_Y *\
convert_from_vtf_format(s,d,x) * \
- ((float)M_PI/180.0f))
+ M_PI/180)
#define CONVERT_G_D_VTF16E14_Z(s,d,x) (DEF_ORIENT_GYRO_Z *\
convert_from_vtf_format(s,d,x) * \
- ((float)M_PI/180.0f))
+ M_PI/180)
-// Milli gauss to micro tesla
+/* Milli gauss to micro tesla */
#define CONVERT_M_MG_VTF16E14_X(s,d,x) (convert_from_vtf_format(s,d,x)/10)
#define CONVERT_M_MG_VTF16E14_Y(s,d,x) (convert_from_vtf_format(s,d,x)/10)
#define CONVERT_M_MG_VTF16E14_Z(s,d,x) (convert_from_vtf_format(s,d,x)/10)
}
-static void denoise (struct sensor_info_t* si, struct sensors_event_t* data,
- int num_fields, int max_samples)
+static void clamp_gyro_readings_to_zero (int s, struct sensors_event_t* data)
{
- /*
- * Smooth out incoming data using a moving average over a number of
- * samples. We accumulate one second worth of samples, or max_samples,
- * depending on which is lower.
- */
+ float x, y, z;
+ float near_zero;
- int i;
- int f;
- int sampling_rate = (int) si->sampling_rate;
- int history_size;
- int history_full = 0;
-
- /* Don't denoise anything if we have less than two samples per second */
- if (sampling_rate < 2)
- return;
-
- /* Restrict window size to the min of sampling_rate and max_samples */
- if (sampling_rate > max_samples)
- history_size = 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));
- }
- }
+ x = data->data[0];
+ y = data->data[1];
+ z = data->data[2];
- if (!si->history || !si->history_sum)
- return; /* Unlikely, but still... */
- /* Update initialized samples count */
- if (si->history_entries < si->history_size)
- si->history_entries++;
+ /* If we're calibrated, don't filter out as much */
+ if (sensor[s].cal_level > 0)
+ near_zero = 0.02; /* rad/s */
else
- history_full = 1;
+ near_zero = 0.1;
- /* 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
- */
- if (history_full)
- si->history_sum[f] -=
- si->history[si->history_index * num_fields + f];
+ /* If motion on all axes is small enough */
+ if (fabs(x) < near_zero && fabs(y) < near_zero && fabs(z) < near_zero) {
- si->history[si->history_index * num_fields + f] = data->data[f];
- si->history_sum[f] += data->data[f];
+ /*
+ * Report that we're not moving at all... but not exactly zero
+ * as composite sensors (orientation, rotation vector) don't
+ * seem to react very well to it.
+ */
- /* 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[0] *= 0.000001;
+ data->data[1] *= 0.000001;
+ data->data[2] *= 0.000001;
}
-
- /* Update our rolling index (next evicted cell) */
- si->history_index = (si->history_index + 1) % si->history_size;
}
+static void process_event_gyro_uncal(int s, int i, struct sensors_event_t* data)
+{
+ struct gyro_cal_t* gyro_data;
+
+ if (sensor[s].type == SENSOR_TYPE_GYROSCOPE) {
+ gyro_data = (struct gyro_cal_t*) sensor[s].cal_data;
+
+ memcpy(&sensor[i].sample, data, sizeof(struct sensors_event_t));
+
+ sensor[i].sample.type = SENSOR_TYPE_GYROSCOPE_UNCALIBRATED;
+ sensor[i].sample.sensor = s;
+
+ sensor[i].sample.data[0] = data->data[0] + gyro_data->bias_x;
+ sensor[i].sample.data[1] = data->data[1] + gyro_data->bias_y;
+ sensor[i].sample.data[2] = data->data[2] + gyro_data->bias_z;
+
+ sensor[i].sample.uncalibrated_gyro.bias[0] = gyro_data->bias_x;
+ sensor[i].sample.uncalibrated_gyro.bias[1] = gyro_data->bias_y;
+ sensor[i].sample.uncalibrated_gyro.bias[2] = gyro_data->bias_z;
+
+ sensor[i].report_pending = 1;
+ }
+}
-static int finalize_sample_default(int s, struct sensors_event_t* data)
+static void process_event(int s, struct sensors_event_t* data)
{
- int i = sensor_info[s].catalog_index;
- int sensor_type = sensor_catalog[i].type;
+ /*
+ * This gets the real event (post process - calibration, filtering & co.)
+ * and makes it into a virtual one.
+ * The specific processing function for each sensor will populate the
+ * necessary fields and set up the report pending flag.
+ */
+
+ int i;
+ /* Go through out virtual sensors and check if we can use this event */
+ for (i = 0; i < sensor_count; i++) {
+ switch (sensor[i].type) {
+ case SENSOR_TYPE_GYROSCOPE_UNCALIBRATED:
+ process_event_gyro_uncal(s, i, data);
+ break;
+
+ default:
+ break;
+ }
+ }
+}
+
+static int finalize_sample_default (int s, struct sensors_event_t* data)
+{
/* Swap fields if we have a custom channel ordering on this sensor */
- if (sensor_info[s].quirks & QUIRK_FIELD_ORDERING)
- reorder_fields(data->data, sensor_info[s].order);
+ if (sensor[s].quirks & QUIRK_FIELD_ORDERING)
+ reorder_fields(data->data, sensor[s].order);
- switch (sensor_type) {
+ sensor[s].event_count++;
+ switch (sensor[s].type) {
case SENSOR_TYPE_ACCELEROMETER:
/* Always consider the accelerometer accurate */
data->acceleration.status = SENSOR_STATUS_ACCURACY_HIGH;
- if (sensor_info[s].quirks & QUIRK_NOISY)
- denoise(&sensor_info[s], data, 3, 20);
+ if (sensor[s].quirks & QUIRK_NOISY)
+ denoise(s, data);
break;
case SENSOR_TYPE_MAGNETIC_FIELD:
- calibrate_compass (data, &sensor_info[s], get_timestamp());
- if (sensor_info[s].quirks & QUIRK_NOISY)
- denoise(&sensor_info[s], data, 3, 100);
+ calibrate_compass (data, &sensor[s]);
+ if (sensor[s].quirks & QUIRK_NOISY)
+ denoise(s, data);
break;
case SENSOR_TYPE_GYROSCOPE:
- case SENSOR_TYPE_GYROSCOPE_UNCALIBRATED:
+
/*
* Report medium accuracy by default ; higher accuracy
* levels will be reported once, and if, we achieve
* movement thresholds that may lead us to incorrectly
* estimate bias.
*/
- if (sensor_info[s].selected_trigger !=
- sensor_info[s].motion_trigger_name)
- calibrate_gyro(data, &sensor_info[s]);
+ if (sensor[s].selected_trigger !=
+ sensor[s].motion_trigger_name)
+ calibrate_gyro(data, &sensor[s]);
- if (sensor_info[s].quirks & QUIRK_NOISY)
- denoise_median(&sensor_info[s], data, 3);
+ /*
+ * For noisy sensors drop a few samples to make sure we
+ * have at least GYRO_MIN_SAMPLES events in the
+ * filtering queue. This improves mean and std dev.
+ */
+ if (sensor[s].quirks & QUIRK_NOISY) {
+ if (sensor[s].selected_trigger !=
+ sensor[s].motion_trigger_name &&
+ sensor[s].event_count<GYRO_MIN_SAMPLES)
+ return 0;
+
+ denoise(s, data);
+ }
+
+ /* Clamp near zero moves to (0,0,0) if appropriate */
+ clamp_gyro_readings_to_zero(s, data);
break;
case SENSOR_TYPE_LIGHT:
* These are on change sensors ; drop the sample if it
* has the same value as the previously reported one.
*/
- if (data->data[0] == sensor_info[s].prev_val)
+ if (data->data[0] == sensor[s].prev_val)
return 0;
- sensor_info[s].prev_val = data->data[0];
+ sensor[s].prev_val = data->data[0];
break;
}
+ /* If there are active virtual sensors depending on this one - process the event */
+ if (sensor[s].ref_count)
+ process_event(s, data);
+ /* We will drop samples if the sensor is not directly enabled */
+ if (!sensor[s].directly_enabled)
+ return 0;
return 1; /* Return sample to Android */
}
static float transform_sample_default(int s, int c, unsigned char* sample_data)
{
- struct datum_info_t* sample_type = &sensor_info[s].channel[c].type_info;
+ struct datum_info_t* sample_type = &sensor[s].channel[c].type_info;
int64_t s64 = sample_as_int64(sample_data, sample_type);
- float scale = sensor_info[s].scale ?
- sensor_info[s].scale : sensor_info[s].channel[c].scale;
+ float scale = sensor[s].scale ?
+ sensor[s].scale : sensor[s].channel[c].scale;
/* In case correction has been requested using properties, apply it */
- scale *= sensor_info[s].channel[c].opt_scale;
+ scale *= sensor[s].channel[c].opt_scale;
/* Apply default scaling rules */
- return (sensor_info[s].offset + s64) * scale;
+ return (sensor[s].offset + s64) * scale;
}
-static int finalize_sample_ISH(int s, struct sensors_event_t* data)
+static int finalize_sample_ISH (int s, struct sensors_event_t* data)
{
- int i = sensor_info[s].catalog_index;
- int sensor_type = sensor_catalog[i].type;
float pitch, roll, yaw;
/* Swap fields if we have a custom channel ordering on this sensor */
- if (sensor_info[s].quirks & QUIRK_FIELD_ORDERING)
- reorder_fields(data->data, sensor_info[s].order);
+ if (sensor[s].quirks & QUIRK_FIELD_ORDERING)
+ reorder_fields(data->data, sensor[s].order);
- if (sensor_type == SENSOR_TYPE_ORIENTATION) {
+ if (sensor[s].type == SENSOR_TYPE_ORIENTATION) {
pitch = data->data[0];
roll = data->data[1];
data->data[2] = -roll;
}
+ /* Add this event to our global records, for filtering purposes */
+ record_sample(s, data);
+
return 1; /* Return sample to Android */
}
-static float transform_sample_ISH(int s, int c, unsigned char* sample_data)
+static float transform_sample_ISH (int s, int c, unsigned char* sample_data)
{
- struct datum_info_t* sample_type = &sensor_info[s].channel[c].type_info;
+ struct datum_info_t* sample_type = &sensor[s].channel[c].type_info;
int val = (int) sample_as_int64(sample_data, sample_type);
- int i = sensor_info[s].catalog_index;
- int sensor_type = sensor_catalog[i].type;
float correction;
int data_bytes = (sample_type->realbits)/8;
- int exponent = sensor_info[s].offset;
+ int exponent = sensor[s].offset;
/* In case correction has been requested using properties, apply it */
- correction = sensor_info[s].channel[c].opt_scale;
+ correction = sensor[s].channel[c].opt_scale;
- switch (sensor_type) {
+ switch (sensor[s].type) {
case SENSOR_TYPE_ACCELEROMETER:
switch (c) {
case 0:
{
char prop_name[PROP_NAME_MAX];
char prop_val[PROP_VALUE_MAX];
- int i = sensor_info[s].catalog_index;
+ int i = sensor[s].catalog_index;
const char *prefix = sensor_catalog[i].tag;
sprintf(prop_name, PROP_BASE, prefix, "transform");
if (property_get(prop_name, prop_val, "")) {
if (!strcmp(prop_val, "ISH")) {
ALOGI( "Using Intel Sensor Hub semantics on %s\n",
- sensor_info[s].friendly_name);
+ sensor[s].friendly_name);
- sensor_info[s].ops.transform = transform_sample_ISH;
- sensor_info[s].ops.finalize = finalize_sample_ISH;
+ sensor[s].ops.transform = transform_sample_ISH;
+ sensor[s].ops.finalize = finalize_sample_ISH;
return;
}
}
- sensor_info[s].ops.transform = transform_sample_default;
- sensor_info[s].ops.finalize = finalize_sample_default;
+ sensor[s].ops.transform = transform_sample_default;
+ sensor[s].ops.finalize = finalize_sample_default;
}
char sysfs_path[PATH_MAX];
float val;
int ret;
- int dev_num = sensor_info[s].dev_num;
- int i = sensor_info[s].catalog_index;
+ int dev_num = sensor[s].dev_num;
+ int i = sensor[s].catalog_index;
const char* raw_path = sensor_catalog[i].channel[c].raw_path;
const char* input_path = sensor_catalog[i].channel[c].input_path;
- float scale = sensor_info[s].scale ?
- sensor_info[s].scale : sensor_info[s].channel[c].scale;
- float offset = sensor_info[s].offset;
+ float scale = sensor[s].scale ?
+ sensor[s].scale : sensor[s].channel[c].scale;
+ float offset = sensor[s].offset;
int sensor_type = sensor_catalog[i].type;
float correction;
/* In case correction has been requested using properties, apply it */
- correction = sensor_info[s].channel[c].opt_scale;
+ correction = sensor[s].channel[c].opt_scale;
/* Acquire a sample value for sensor s / channel c through sysfs */
return 0;
/*
- There is no transform ops defined yet for Raw sysfs values
- Use this function to perform transformation as well.
- */
+ * There is no transform ops defined yet for raw sysfs values.
+ * Use this function to perform transformation as well.
+ */
if (sensor_type == SENSOR_TYPE_MAGNETIC_FIELD)
return CONVERT_GAUSS_TO_MICROTESLA ((val + offset) * scale) *
correction;
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