public void LabelStoreToExcel()
{
DataTable labelDt = new DataTable();
for (int i = 0; i < highbounds[0] - lowbounds[0] + 1; i++)
{
labelDt.Columns.Add(i.ToString(), Type.GetType("System.Double"));
}
for (int i = 0; i < labelMatrix.RowCount; i++)
{
var row = labelDt.NewRow();
row.ItemArray = labelMatrix.Row(labelMatrix.RowCount - i - 1).Select(x => (object)x).ToArray();
labelDt.Rows.Add(row);
}
if (File.Exists(@"C:\Users\shiya\Desktop\record\label.xlsx"))
{
File.Delete(@"C:\Users\shiya\Desktop\record\label.xlsx");
}
File.Create(@"C:\Users\shiya\Desktop\record\label.xlsx").Close();
ExcelOperation.dataTableListToExcel(new List <DataTable>()
{
labelDt
}, false,
@"C:\Users\shiya\Desktop\record\label.xlsx");
_data.strbuf = "Finish Write Labels to Excel";
_data.update = true;
}
void UpdateRecordAndDisplay()
{
Console.WriteLine("Generation: {0}", gen);
List <GAEncoding> currentBests = cePool.Where(x => x.Key.entropy == cePool.Max(y => y.Key.entropy))
.Select(x => x.Key).ToList();
for (int i = 0; i < currentBests.Count; i++)
{
Console.WriteLine("Solution: {1}, Entropy: {0}", currentBests[i].entropy, i);
}
var a = currentBests[0].weightsVect.Sum();
var solutions = Print_Solution(currentBests[0]);
object[] temp = new object[pNumOfParams * pNumOfParams];
var newRow = dt.NewRow();
for (int i = 0; i < pNumOfParams * pNumOfParams; i++)
{
temp[i] = currentBests[0].weightsVect.ToArray()[i];
}
newRow.ItemArray = temp;
dt.Rows.Add(newRow);
int fake = 0;
if (fake > 0)
{
ExcelOperation.dataTableListToExcel(new List <DataTable>()
{
dt
}, false,
@"C:\Users\shiya\Desktop\record\a.xlsx");
}
}
void UpdateRecordAndDisplay()
{
Console.WriteLine("Generation: {0}", gen);
List <GAEncoding> currentBests = cePool.Where(x => x.Key.rank == 0)
.Select(x => x.Key).ToList();
//for (int i = 0; i < currentBests.Count; i++)
//{
// Console.WriteLine("Solution: {1}, Entropy: {0}", currentBests[i].entropy, i);
// Console.WriteLine("Solution: {1}, Diversity: {0}", currentBests[i].diversity, i);
//}
Console.WriteLine("Max_Entropy: {0}", currentBests.Where(x => x.entropy == currentBests
.Max(y => y.entropy)).First().entropy);
Console.WriteLine("Max_Diversity: {0}", currentBests.Where(x => x.diversity == currentBests
.Max(y => y.diversity)).First().diversity);
_data.fitness = currentBests.Where(x => x.entropy == currentBests
.Max(y => y.entropy)).First().entropy;
_data.generation = gen;
_data.strbuf = "Fitness: " + _data.fitness.ToString();
_data.update = true;
var a = currentBests[0].weightsVect.Sum();
var solutions = Print_Solution(currentBests[0]);
object[] temp = new object[pNumOfParams * pNumOfParams];
var newRow = dt.NewRow();
for (int i = 0; i < pNumOfParams * pNumOfParams; i++)
{
temp[i] = currentBests[0].weightsVect.ToArray()[i];
}
newRow.ItemArray = temp;
dt.Rows.Add(newRow);
int fake = 0;
if (fake > 0)
{
ExcelOperation.dataTableListToExcel(new List <DataTable>()
{
dt
}, false,
@"C:\Users\shiya\Desktop\record\a.xlsx");
}
}