public double dbaStep(TimeSeries seed, ArrayList samples)
{
TimeSeriesPair[] results = new TimeSeriesPair[samples.Count];
double error = 0.0;
for (int i = 0; i < samples.Count; i++)
{
TimeSeries ts = (TimeSeries)samples[i];
results[i] = new TimeSeriesPair(seed, (TimeSeries)samples[i]);
results[i].DTW();
error += results[i].error;
}
int m = seed.length;
for (int i = 0; i < m; i++)
{
double mean = 0.0;
int n = 0;
for (int j = 0; j < samples.Count; j++)
{
TimeSeries ts = (TimeSeries)samples[j];
int k0 = results[j].associates[i][0];
int k1 = results[j].associates[i][1];
for (int k = k0; k <= k1; k++)
{
mean += ts.data[k];
n++;
}
}
seed.data[i] = mean / n;
}
return(error);
}
private void btn_gDPDP_Click(object sender, EventArgs e)
{
TimeSeriesPair res = new TimeSeriesPair(test1, test2);
res.DTW();
TimeSeries center = res.gDPDP();
showMessage(res, center);
}
private void showMessage(TimeSeriesPair res, TimeSeries center)
{
TimeSeriesPair m13 = new TimeSeriesPair(test1, center);
m13.DTW();
TimeSeriesPair m23 = new TimeSeriesPair(test2, center);
m23.DTW();
string line = "error = " + string.Format("{0:f}", m13.error + m23.error);
lbxData.Items.Add(line);
}
public double mDPDP(
ArrayList samples,
ListBox lbx, int classIndex, int classCount,
TimeSeries seed)
{
if (samples.Count == 0)
{
return(0.0);
}
double error = 0.0;
int groupCount = 4;
TimeSeries[] seedList = new TimeSeries[groupCount];
int[] numberList = new int[samples.Count];
ArrayList[] dataList = new ArrayList[groupCount];
for (int i = 0; i < samples.Count; i++)
{
numberList[i] = i;
}
Random random = new Random();
for (int i = 0; i < groupCount; i++)
{
dataList[i] = new ArrayList();
int lastIndex = samples.Count - i - 1;
int randIndex = random.Next(lastIndex + 1);
int randValue = numberList[randIndex];
numberList[randIndex] = numberList[lastIndex];
seedList[i] = (TimeSeries)samples[randValue];
}
int tempGroup = groupCount;
while (tempGroup > 0)
{
for (int i = 0; i < tempGroup; i++)
{
dataList[i].Clear();
seedList[i].weight = 1.0;
}
double[][] dtwMatrix = new double[samples.Count][];
for (int i = 0; i < samples.Count; i++)
{
TimeSeries ts = (TimeSeries)samples[i];
dtwMatrix[i] = new double[tempGroup];
for (int j = 0; j < tempGroup; j++)
{
TimeSeriesPair pair = new TimeSeriesPair(seedList[j], ts);
pair.DTW();
dtwMatrix[i][j] = pair.error;
}
}
for (int i = 0; i < samples.Count; i++)
{
TimeSeries ts = (TimeSeries)samples[i];
int k = 0;
double minError = 1.0e20;
for (int j = 0; j < tempGroup; j++)
{
if (dataList[j].Count > (samples.Count / tempGroup + 1))
{
continue;
}
if (dtwMatrix[i][j] < minError)
{
minError = dtwMatrix[i][j];
k = j;
}
}
dataList[k].Add(ts);
}
for (int i = 0; i < tempGroup; i++)
{
int loopMax = (tempGroup == 1) ? 30 : 15;
for (int j = 0; j < loopMax; j++)
{
error = dbaStep(seedList[i], dataList[i]);
string line = string.Format(
"class = {0:d}/{1:d}; size = {2:d}; group = {3:d}/{4:d}; loop = {5:d}; error = {6:f}, avgError = {7:f}",
classIndex, classCount, dataList[i].Count, i + 1, tempGroup, j, error, error / dataList[i].Count
);
lbx.Items.Add(line);
lbx.SetSelected(lbx.Items.Count - 1, true);
Application.DoEvents();
}
}
if (tempGroup > 1)
{
ArrayList pairList = new ArrayList();
//calculate the pairwise DTW distances among the group seeds
for (int i = 0; i < tempGroup; i++)
{
for (int j = 0; j < tempGroup; j++)
{
if (i == j)
{
continue;
}
TimeSeriesPair pair = new TimeSeriesPair(seedList[i], seedList[j]);
pair.DTW();
pairList.Add(new DTWPair(pair.error,
i, dataList[i].Count,
j, dataList[j].Count
));
}
}
DTWPair[] pairVect = getPairsFromList(pairList, tempGroup / 2);
//Each element of pairVect is a pair of indice which corresponding seeds will be merged.
TimeSeries[] newSeeds = new TimeSeries[tempGroup / 2];
for (int i = 0; i < tempGroup / 2; i++)
{
int i0 = pairVect[i].i0;
int i1 = pairVect[i].i1;
double w0 = pairVect[i].w0;
double w1 = pairVect[i].w1;
TimeSeries ts0 = (TimeSeries)seedList[i0];
TimeSeries ts1 = (TimeSeries)seedList[i1];
if (Math.Abs(w0 + w1) < 0.000001)
{
newSeeds[i] = ts0.clone();
}
else
{
ts0.weight = w0 / (w0 + w1);
ts1.weight = w1 / (w0 + w1);
TimeSeriesPair pair = new TimeSeriesPair(ts0, ts1);
newSeeds[i] = pair.gDPDP();
//Merge the two old seeds into a new seed.
}
}
for (int i = 0; i < tempGroup / 2; i++)
{
seedList[i] = newSeeds[i];
//update new seeds
}
}
tempGroup /= 2;
//the group count becomes the half
}
seed.copy(seedList[0]);
return(error);
}
