/// <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>
/// 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();
}
