private EEGDataListener GetTrialDataListener(out BlockingQueue <IArrayView <EEGDataEntry> > trialQueue)
{
var entryList = new List <EEGDataEntry>();
var queue = new BlockingQueue <IArrayView <EEGDataEntry> >();
trialQueue = queue;
var invoker = new SingleThreadedInvoker();
return(new EEGDataListener(invoker,
null,
entries =>
{
foreach (var entry in entries)
{
// got a new marker, so flush!
if (entryList.Count > 0 && entry.Marker != entryList[0].Marker)
{
queue.Enqueue(entryList.AsIArray());
entryList = new List <EEGDataEntry>(entryList.Count);
}
// save stimulus entries
if (entry.HasStimulusMarker())
{
entryList.Add(entry);
}
}
},
null,
() => invoker.Dispose()));
}
/// <summary>
/// Groups entries using the sequences formed by their relative timestamps
/// </summary>
public static IEnumerable <IArrayView <EEGDataEntry> > SectionByStimulus(this IEnumerable <EEGDataEntry> entries)
{
if (entries.IsEmpty())
{
yield break;
}
var section = new List <EEGDataEntry>()
{
entries.First()
};
foreach (var entry in entries.Skip(1))
{
if (entry.RelativeTimeStamp >= section.LastItem().RelativeTimeStamp)
{
section.Add(entry);
}
else
{
yield return(section.AsIArray());
section = new List <EEGDataEntry>()
{
entry
};
}
}
yield return(section.AsIArray()); // return the last section
}
/// <summary>
/// Groups the entries by their respective time bins
/// </summary>
public static IArrayView <IArrayView <EEGDataEntry> > BinByTime(this IEnumerable <EEGDataEntry> entries, int binWidthMillis)
{
if (binWidthMillis <= 0)
{
throw new ArgumentOutOfRangeException("binWidthMillis");
}
int baseTime = entries.First().TimeStamp;
var bins = new List <IArrayView <EEGDataEntry> >();
var bin = new List <EEGDataEntry>();
foreach (var entry in entries)
{
// add it the the current bin
if (entry.TimeStamp < baseTime + binWidthMillis)
{
bin.Add(entry);
}
else // save the old bin and add it to the new one
{
bins.Add(bin.AsIArray());
while (true)
{
baseTime += binWidthMillis;
if (entry.TimeStamp < baseTime + binWidthMillis)
{
bin = new List <EEGDataEntry>()
{
entry
};
break;
}
bins.Add(Arrays.New <EEGDataEntry>(0)); // empty array
}
}
}
// make sure to get the last bin!
if (bin.Count > 0)
{
bins.Add(bin.AsIArray());
}
return(bins.AsIArray());
}
/// <summary>
/// Computes the average of each "feature"
/// </summary>
public static IArray<double> Averages(this IEnumerable<IEnumerable<double>> data)
{
var sums = new List<double>(data.First());
int count = 1, i;
foreach (var enumerable in data.Skip(1))
{
count++;
i = 0;
foreach (double d in enumerable)
if (sums.Count <= i)
break;
else
sums[i++] += d;
for (int j = sums.Count - 1; j >= i; j--)
sums.RemoveAt(j);
}
for (i = 0; i < sums.Count; i++)
sums[i] /= count;
return sums.AsIArray();
}
/// <summary>
/// Computes the average of each "feature"
/// </summary>
public static IArray<double> Averages(this IEnumerable<IEnumerable<double>> data)
{
var sums = new List<double>(data.First());
int count = 1, i;
foreach (var enumerable in data.Skip(1))
{
count++;
i = 0;
foreach (double d in enumerable)
if (sums.Count <= i)
break;
else
sums[i++] += d;
for (int j = sums.Count - 1; j >= i; j--)
sums.RemoveAt(j);
}
for (i = 0; i < sums.Count; i++)
sums[i] /= count;
return sums.AsIArray();
}
public IEnumerable <View> RunCompTrial(string stimulus, int cls, StreamWriter dataWriter, StreamWriter logWriter, List <EEGDataEntry> currentTrialEntries)
{
//Rest
yield return(new RestView(this.settings.BlinkTime));
//Fixate
yield return(new FixationView(this.settings.FixationTime));
//Generate stimulus view
var stimulusView = new TextView(stimulus, this.settings.DisplayTime, GUIUtils.Constants.DISPLAY_FONT_LARGE);
stimulusView.DoOnDeploy(c => this.dataSource.Marker = cls);
bool needToRerun = false;
stimulusView.DoOnFinishing(() =>
{
this.dataSource.Marker = EEGDataEntry.MARKER_DEFAULT;
lock (currentTrialEntries)
{
if (this.settings.ArtifactDetectionSettings.HasMotionArtifact(currentTrialEntries))
{
logWriter.WriteLine("Motion Artifact Detected");
needToRerun = true;
}
else
{
if (this.settings.SaveTrialData)
{
foreach (var entry in currentTrialEntries)
{
dataWriter.WriteLine(entry);
}
}
//Add training trials to the classifier
classifier.AddTrial(currentTrialEntries.AsIArray());
}
currentTrialEntries.Clear();
}
});
logWriter.WriteLine(stimulus);
yield return(stimulusView);
yield return(new TextView(stimulus + "*", settings.SpeakTime, GUIUtils.Constants.DISPLAY_FONT_LARGE));
//Check number of artifacts
if (needToRerun)
{
if (cls == 1)
{
numArt1++;
}
if (cls == 2)
{
numArt2++;
}
numArt++;
}
if (numArt > 12)
{
numArt = 0;
yield return(new TextView("Please keep face movements to a minimum", settings.InstructionTime, GUIUtils.Constants.DISPLAY_FONT_LARGE));
}
}
/// <summary>
/// Groups entries using the sequences formed by their relative timestamps
/// </summary>
public static IEnumerable<IArrayView<EEGDataEntry>> SectionByStimulus(this IEnumerable<EEGDataEntry> entries)
{
if (entries.IsEmpty())
yield break;
var section = new List<EEGDataEntry>() { entries.First() };
foreach (var entry in entries.Skip(1))
{
if (entry.RelativeTimeStamp >= section.LastItem().RelativeTimeStamp)
section.Add(entry);
else
{
yield return section.AsIArray();
section = new List<EEGDataEntry>() { entry };
}
}
yield return section.AsIArray(); // return the last section
}
/// <summary>
/// Groups the entries by their respective time bins
/// </summary>
public static IArrayView<IArrayView<EEGDataEntry>> BinByTime(this IEnumerable<EEGDataEntry> entries, int binWidthMillis)
{
if (binWidthMillis <= 0)
throw new ArgumentOutOfRangeException("binWidthMillis");
int baseTime = entries.First().TimeStamp;
var bins = new List<IArrayView<EEGDataEntry>>();
var bin = new List<EEGDataEntry>();
foreach (var entry in entries)
// add it the the current bin
if (entry.TimeStamp < baseTime + binWidthMillis)
bin.Add(entry);
else // save the old bin and add it to the new one
{
bins.Add(bin.AsIArray());
while (true)
{
baseTime += binWidthMillis;
if (entry.TimeStamp < baseTime + binWidthMillis)
{
bin = new List<EEGDataEntry>() { entry };
break;
}
bins.Add(Arrays.New<EEGDataEntry>(0)); // empty array
}
}
// make sure to get the last bin!
if (bin.Count > 0)
bins.Add(bin.AsIArray());
return bins.AsIArray();
}
