async Task<List<SignificantActivity>> aggregateSignificantActivitiesAsync (CMMotionActivity[] activities)
{
List<CMMotionActivity> filteredActivities = new List<CMMotionActivity> ();
// Skip all contiguous unclassified actiivty so that only one remains.
for (int i = 0; i < activities.Length; ++i) {
CMMotionActivity activity = activities [i];
filteredActivities.Add (activity);
if (!activity.Walking && !activity.Running && !activity.Automotive) {
while (++i < activities.Length) {
CMMotionActivity skipThisActivity = activities [i];
if (skipThisActivity.Walking || skipThisActivity.Running || skipThisActivity.Automotive) {
i = i - 1;
break;
}
}
}
}
// Ignore all low confidence activities.
for (int i = 0; i < filteredActivities.Count;) {
CMMotionActivity activity = filteredActivities[i];
if (activity.Confidence == CMMotionActivityConfidence.Low) {
filteredActivities.RemoveAt (i);
} else {
++i;
}
}
// Skip all unclassified activities if their duration is smaller than
// some threshold. This has the effect of coalescing the remaining med + high
// confidence activies together.
for (int i = 0; i < filteredActivities.Count - 1;){
CMMotionActivity activity = filteredActivities [i];
CMMotionActivity nextActivity = filteredActivities [i + 1];
var duration = nextActivity.StartDate.SecondsSinceReferenceDate - activity.StartDate.SecondsSinceReferenceDate;
if (duration < 60 * 3 && !activity.Walking && !activity.Running && !activity.Automotive) {
filteredActivities.RemoveAt (i);
} else {
++i;
}
}
// Coalesce activities where they differ only in confidence.
for (int i = 1; i < filteredActivities.Count;) {
CMMotionActivity prevActivity = filteredActivities [i - 1];
CMMotionActivity activity = filteredActivities [i];
if ((prevActivity.Walking && activity.Walking) ||
(prevActivity.Running && activity.Running) ||
(prevActivity.Automotive && activity.Automotive)) {
filteredActivities.RemoveAt (i);
} else {
++i;
}
}
// Finally transform into SignificantActivity;
List<SignificantActivity> significantActivities = new List<SignificantActivity> ();
for (int i = 0; i < filteredActivities.Count - 1; i++) {
CMMotionActivity activity = filteredActivities [i];
CMMotionActivity nextActivity = filteredActivities [i + 1];
if (!activity.Walking && !activity.Running && !activity.Automotive)
continue;
var significantActivity = new SignificantActivity (ActivityDataManager.ActivityToType (activity), activity.StartDate, nextActivity.StartDate);
try {
var pedometerData = await pedometer.QueryPedometerDataAsync (significantActivity.StartDate, significantActivity.EndDate);
significantActivity.StepCounts = pedometerData.NumberOfSteps.Int32Value;
} catch {
Console.WriteLine ("Error, unable to retrieve step counts for range {0}, {1}", significantActivity.StartDate.SecondsSinceReferenceDate, significantActivity.EndDate.SecondsSinceReferenceDate);
}
significantActivities.Add (significantActivity);
}
return significantActivities;
}
async Task <List <SignificantActivity> > aggregateSignificantActivitiesAsync(CMMotionActivity[] activities)
{
List <CMMotionActivity> filteredActivities = new List <CMMotionActivity> ();
// Skip all contiguous unclassified actiivty so that only one remains.
for (int i = 0; i < activities.Length; ++i)
{
CMMotionActivity activity = activities [i];
filteredActivities.Add(activity);
if (!activity.Walking && !activity.Running && !activity.Automotive)
{
while (++i < activities.Length)
{
CMMotionActivity skipThisActivity = activities [i];
if (skipThisActivity.Walking || skipThisActivity.Running || skipThisActivity.Automotive)
{
i = i - 1;
break;
}
}
}
}
// Ignore all low confidence activities.
for (int i = 0; i < filteredActivities.Count;)
{
CMMotionActivity activity = filteredActivities [i];
if (activity.Confidence == CMMotionActivityConfidence.Low)
{
filteredActivities.RemoveAt(i);
}
else
{
++i;
}
}
// Skip all unclassified activities if their duration is smaller than
// some threshold. This has the effect of coalescing the remaining med + high
// confidence activies together.
for (int i = 0; i < filteredActivities.Count - 1;)
{
CMMotionActivity activity = filteredActivities [i];
CMMotionActivity nextActivity = filteredActivities [i + 1];
var duration = nextActivity.StartDate.SecondsSinceReferenceDate - activity.StartDate.SecondsSinceReferenceDate;
if (duration < 60 * 3 && !activity.Walking && !activity.Running && !activity.Automotive)
{
filteredActivities.RemoveAt(i);
}
else
{
++i;
}
}
// Coalesce activities where they differ only in confidence.
for (int i = 1; i < filteredActivities.Count;)
{
CMMotionActivity prevActivity = filteredActivities [i - 1];
CMMotionActivity activity = filteredActivities [i];
if ((prevActivity.Walking && activity.Walking) ||
(prevActivity.Running && activity.Running) ||
(prevActivity.Automotive && activity.Automotive))
{
filteredActivities.RemoveAt(i);
}
else
{
++i;
}
}
// Finally transform into SignificantActivity;
List <SignificantActivity> significantActivities = new List <SignificantActivity> ();
for (int i = 0; i < filteredActivities.Count - 1; i++)
{
CMMotionActivity activity = filteredActivities [i];
CMMotionActivity nextActivity = filteredActivities [i + 1];
if (!activity.Walking && !activity.Running && !activity.Automotive)
{
continue;
}
var significantActivity = new SignificantActivity(ActivityDataManager.ActivityToType(activity), (DateTime)activity.StartDate, (DateTime)nextActivity.StartDate);
try {
var pedometerData = await pedometer.QueryPedometerDataAsync(significantActivity.StartDate, significantActivity.EndDate);
significantActivity.StepCounts = pedometerData.NumberOfSteps.Int32Value;
} catch {
Console.WriteLine("Error, unable to retrieve step counts for range {0}, {1}", significantActivity.StartDate.SecondsSinceReferenceDate, significantActivity.EndDate.SecondsSinceReferenceDate);
}
significantActivities.Add(significantActivity);
}
return(significantActivities);
}
