private void showRules(FuzzyRules rls)
{
string[] values = rls.getValues();
string[][] args = rls.getKeys();
for (int i=nDiv; i<nDiv*nIn; i++)
{
dataGridView2.Columns.Add(keys[i], keys[i]);
}
dataGridView2.Rows.Add(nDiv);
dataGridView2.RowHeadersWidth = 110;
dataGridView2.Height = dataGridView2.Rows[0].Height * (dataGridView2.Rows.Count+2);
for (int i=0; i<nDiv; i++)
{
dataGridView2.Rows[i].HeaderCell.Value = keys[i];
}
for (int i=0; i<values.Length; i++)
{
int index = 0;
int ct = 0;
for (int j=0; j< dataGridView2.Rows.Count-1; j++)
{
if (dataGridView2.Rows[j].HeaderCell.Value.ToString() == args[i][0])
{
index = j;
break;
}
}
dataGridView2.Rows[index].Cells[args[i][1]].Value = values[i].ToString();
}
}
private void initData()
{
membershipIn = new List<double[,]>();
membershipOut = new List<double[,]>();
m = new double[size, nIn];
mY = new double[size];
rT = new double[size];
categoryXL = new string[size, nIn];
categoryYL = new string[size];
categoryYT1 = new string[size];
categoryYT2 = new string[size];
LearningX = new List<double[]>();
LearningY = new List<double[]>();
TestX = new List<double[]>();
TestY = new List<double[]>();
genData = new List<double[]>();
decisions = new List<string[]>();
inputDef = new List<DeFuzzySet>();
data = new List<double[]>();
rules = new FuzzyRules();
fuzzy = new FuzzySet();
rFuzzy = new FuzzySet();
func = new Membership();
keys = new string[nDiv * nIn];
classes = new string[nDiv];
double d = 0;
for (int i = 0; i < nDiv * nIn; i++)
{
if (i < nDiv)
{
keys[i] = i + "A" + i;
classes[i] = i + "B" + i;
}
else
{
keys[i] = (i - nDiv) + "A." + (i - nDiv);
}
}
if (fu == "tr")
{
int ln = nDiv + 1;
d = (minGen + maxGen) / ln;
}
else if (fu == "trap")
{
if (nDiv==3)
d= (minGen + maxGen) / 7;
else d = (minGen + maxGen) / 11;
}
else if (fu == "gauss")
{
int ln = nDiv + 1;
d = (minGen + maxGen) / ln;
}
if (nDiv == 3)
{
if (fu == "tr")
{
data.Add(new double[] { minGen, minGen + d, minGen + 2 * d });
data.Add(new double[] { minGen + d, minGen + 2 * d, minGen + 3 * d });
data.Add(new double[] { minGen + 2 * d, minGen + 3 * d, maxGen });
data.Add(new double[] { minGen, minGen + d, minGen + 2 * d });
data.Add(new double[] { minGen + d, minGen + 2 * d, minGen + 3 * d });
data.Add(new double[] { minGen + 2 * d, minGen + 3 * d, maxGen });
data.Add(new double[] { minGen, minGen + d, minGen + 2 * d });
data.Add(new double[] { minGen + d, minGen + 2 * d, minGen + 3 * d });
data.Add(new double[] { minGen + 2 * d, minGen + 3 * d, maxGen });
}
else if (fu == "trap")
{
data.Add(new double[] { minGen, minGen + d, minGen + 2 * d, minGen + 3 * d });
data.Add(new double[] { minGen + 2 * d, minGen + 3 * d, minGen + 4 * d, minGen + 5 * d });
data.Add(new double[] { minGen + 4 * d, minGen + 5 * d, minGen + 6 * d, maxGen });
data.Add(new double[] { minGen, minGen + d, minGen + 2 * d, minGen + 3 * d });
data.Add(new double[] { minGen + 2 * d, minGen + 3 * d, minGen + 4 * d, minGen + 5 * d });
data.Add(new double[] { minGen + 4 * d, minGen + 5 * d, minGen + 6 * d, maxGen });
data.Add(new double[] { minGen, minGen + d, minGen + 2 * d, minGen + 3 * d });
data.Add(new double[] { minGen + 2 * d, minGen + 3 * d, minGen + 4 * d, minGen + 5 * d });
data.Add(new double[] { minGen + 4 * d, minGen + 5 * d, minGen + 6 * d, maxGen });
}
else if (fu == "gauss")
{
data.Add(new double[] { minGen + d, d/3 });
data.Add(new double[] { minGen + 2 * d, d / 3 });
data.Add(new double[] { minGen + 3 * d, d / 3 });
data.Add(new double[] { minGen + d, d / 3 });
data.Add(new double[] { minGen + 2 * d, d / 3 });
data.Add(new double[] { minGen + 3 * d, d / 3 });
data.Add(new double[] { minGen + d, d / 3 });
data.Add(new double[] { minGen + 2 * d, d / 3 });
data.Add(new double[] { minGen + 3 * d, d / 3 });
}
}
else
{
if (fu == "tr")
{
data.Add(new double[] { minGen, minGen + d, minGen + 2 * d });
data.Add(new double[] { minGen + d, minGen + 2 * d, minGen + 3 * d });
data.Add(new double[] { minGen + 2 * d, minGen + 3 * d, minGen + 4 * d });
data.Add(new double[] { minGen + 3 * d, minGen + 4 * d, minGen + 5 * d });
data.Add(new double[] { minGen + 4 * d, minGen + 5 * d, maxGen });
data.Add(new double[] { minGen, minGen + d, minGen + 2 * d });
data.Add(new double[] { minGen + d, minGen + 2 * d, minGen + 3 * d });
data.Add(new double[] { minGen + 2 * d, minGen + 3 * d, minGen + 4 * d });
data.Add(new double[] { minGen + 3 * d, minGen + 4 * d, minGen + 5 * d });
data.Add(new double[] { minGen + 4 * d, minGen + 5 * d, maxGen });
data.Add(new double[] { minGen, minGen + d, minGen + 2 * d });
data.Add(new double[] { minGen + d, minGen + 2 * d, minGen + 3 * d });
data.Add(new double[] { minGen + 2 * d, minGen + 3 * d, minGen + 4 * d });
data.Add(new double[] { minGen + 3 * d, minGen + 4 * d, minGen + 5 * d });
data.Add(new double[] { minGen + 4 * d, minGen + 5 * d, maxGen });
}
else if (fu == "trap")
{
data.Add(new double[] { minGen, minGen + d, minGen + 2 * d, minGen + 3 * d });
data.Add(new double[] { minGen + 2 * d, minGen + 3 * d, minGen + 4 * d, minGen + 5 * d });
data.Add(new double[] { minGen + 4 * d, minGen + 5 * d, minGen + 6 * d, minGen + 7 * d });
data.Add(new double[] { minGen + 6 * d, minGen + 7 * d, minGen + 8 * d, minGen + 9 * d });
data.Add(new double[] { minGen + 8 * d, minGen + 9 * d, minGen + 10 * d, maxGen });
data.Add(new double[] { minGen, minGen + d, minGen + 2 * d, minGen + 3 * d });
data.Add(new double[] { minGen + 2 * d, minGen + 3 * d, minGen + 4 * d, minGen + 5 * d });
data.Add(new double[] { minGen + 4 * d, minGen + 5 * d, minGen + 6 * d, minGen + 7 * d });
data.Add(new double[] { minGen + 6 * d, minGen + 7 * d, minGen + 8 * d, minGen + 9 * d });
data.Add(new double[] { minGen + 8 * d, minGen + 9 * d, minGen + 10 * d, maxGen });
data.Add(new double[] { minGen, minGen + d, minGen + 2 * d, minGen + 3 * d });
data.Add(new double[] { minGen + 2 * d, minGen + 3 * d, minGen + 4 * d, minGen + 5 * d });
data.Add(new double[] { minGen + 4 * d, minGen + 5 * d, minGen + 6 * d, minGen + 7 * d });
data.Add(new double[] { minGen + 6 * d, minGen + 7 * d, minGen + 8 * d, minGen + 9 * d });
data.Add(new double[] { minGen + 8 * d, minGen + 9 * d, minGen + 10 * d, maxGen });
}
else if (fu == "gauss")
{
data.Add(new double[] { minGen + d, d / 3 });
data.Add(new double[] { minGen + 2 * d, d / 3 });
data.Add(new double[] { minGen + 3 * d, d / 3 });
data.Add(new double[] { minGen + 4 * d, d / 3 });
data.Add(new double[] { minGen + 5 * d, d / 3 });
data.Add(new double[] { minGen + d, d / 3 });
data.Add(new double[] { minGen + 2 * d, d / 3 });
data.Add(new double[] { minGen + 3 * d, d / 3 });
data.Add(new double[] { minGen + 4 * d, d / 3 });
data.Add(new double[] { minGen + 5 * d, d / 3 });
data.Add(new double[] { minGen + d, d / 3 });
data.Add(new double[] { minGen + 2 * d, d / 3 });
data.Add(new double[] { minGen + 3 * d, d / 3 });
data.Add(new double[] { minGen + 4 * d, d / 3 });
data.Add(new double[] { minGen + 5 * d, d / 3 });
}
}
int ct = 0;
foreach (string obj in keys)
{
fuzzy.Set.Add(obj, data[ct]);
ct++;
}
ct = 0;
foreach (string obj in classes)
{
rFuzzy.Set.Add(obj, data[ct]);
ct++;
}
for (int i = 0; i < nIn; i++)
{
LearningX.Add(new double[size + 1]);
TestX.Add(new double[size + 1]);
genData.Add(new double[size]);
}
LearningY.Add(new double[size]);
TestY.Add(new double[size]);
rL = new double[size + 1];
}
