public void GetRandomCases_File()
{
exp_random_cases.Clear();
exp_random_cases_nonstandrize.Clear();
Case Max_Mean = Db.get_Case_data(standrize_table, -2);
Case Min_Sd = Db.get_Case_data(standrize_table, -3);
List <Case> templist = new List <Case>();
templist = Db.read_file();
if (templist.Count != 0)
{
for (int i = 0; i < templist.Count; i++)
{
exp_random_cases_nonstandrize.Add(templist[i]);
// i have to put general seetings for normalization a
Case c = BestChoice.StandardizeCase(templist[i], Max_Mean, Min_Sd, standrize_type);
exp_random_cases.Add(c);
}
}
}
//=========================================================================================
public void GenerateRandomCases()
{
exp_random_cases.Clear();
Case Max_Mean = Db.get_Case_data(standrize_table, -2);
Case Min_Sd = Db.get_Case_data(standrize_table, -3);
Random r = new Random();
List <Case> Cases = Db.get_cases_condition(tablename, casename);
for (int i = 0; i < 100; i++)
{
double x = 0;
Case c = new Case(0, Max_Mean.GetCaseName(), "");
for (int j = 0; j < Max_Mean.GetFeatures().Count; j++)
{
Feature max_f = (Feature)Max_Mean.GetFeatures()[j];
Feature min_f = (Feature)Min_Sd.GetFeatures()[j];
if (max_f.GetFeatureName() == "id")
{
x = (double)i;
}
else if (max_f.GetFeatureName() == "cluster")
{
x = -1;
}
else if (max_f.GetFeatureType() >= 5 && max_f.GetFeatureType() <= 9)// mstring, string, ordinal, categorical
{
int k = r.Next(0, Cases.Count);
Feature f = (Feature)Cases[k].GetFeatures()[j];
c.AddFeature(max_f.GetFeatureName(), max_f.GetFeatureType(), f.GetFeatureValue(), max_f.GetWeight(), max_f.GetIsKey(), max_f.GetIsIndex(), max_f.GetFeatureUnit());
continue;
}
else if (max_f.GetFeatureType() == 1)// mstring, string, ordinal, categorical
{
int k = r.Next(0, 2);
bool o = false;
if (k == 1)
{
o = true;
}
c.AddFeature(max_f.GetFeatureName(), max_f.GetFeatureType(), o, max_f.GetWeight(), max_f.GetIsKey(), max_f.GetIsIndex(), max_f.GetFeatureUnit());
continue;
}
else if (max_f.GetFeatureType() == 2)
{
int max = Convert.ToInt32(max_f.GetFeatureValue());
int min = Convert.ToInt32(min_f.GetFeatureValue());
x = r.Next(min, max + 1);
}
else
{
double max = Convert.ToDouble(max_f.GetFeatureValue());
double min = Convert.ToDouble(min_f.GetFeatureValue());
x = r.NextDouble(min, max + 0.05);
x = Math.Round(x, 1);
}
c.AddFeature(max_f.GetFeatureName(), max_f.GetFeatureType(), x, max_f.GetWeight(), max_f.GetIsKey(), max_f.GetIsIndex(), max_f.GetFeatureUnit());
}
exp_random_cases_nonstandrize.Add(c);
// i have to put general seetings for normalization
exp_random_cases.Add(BestChoice.StandardizeCase(c, Max_Mean, Min_Sd, standrize_type));
}
}
private void button5_Click_1(object sender, EventArgs e)
{
statistics = new Statistics(mybestchoice.TableName, mybestchoice.CaseName);
Case Max_Mean = Db.get_Case_data(statistics.standrize_table, -2);
Case Min_Sd = Db.get_Case_data(statistics.standrize_table, -3);
string url = "";
System.IO.StreamReader reader = null;
OpenFileDialog openFileDialog1 = new OpenFileDialog();
ArrayList inputs = new ArrayList();
// Set filter options and filter index.
openFileDialog1.Filter = "Text Files (.key)|*.key|All Files (*.*)|*.*";
openFileDialog1.FilterIndex = 1;
openFileDialog1.Multiselect = true;
// Call the ShowDialog method to show the dialog box.
DialogResult userClickedOK = openFileDialog1.ShowDialog();
// Process input if the user clicked OK.
if (userClickedOK.Equals(DialogResult.OK))
{
url = openFileDialog1.FileName;
reader = File.OpenText(url);
if (reader == null)
{
System.Console.WriteLine("file open failed " + url);
return;
}
for (int i = 0; i < dataGV_CaseEntries.Rows.Count; i++)
{
string s = reader.ReadLine();
dataGV_CaseEntries.Rows[i].Cells["UserEntry"].Value = s;
inputs.Add(s);
}
reader.Close();
}
Case _problem = new Case(0, mybestchoice.CaseName, "");
_problem.AddFeature("id", FeatureType.TYPE_FEATURE_INT, 0, 1.0, false, false, "num");
for (int i = 0; i < dataGV_CaseEntries.Rows.Count - 1; i++)
{
if (dataGV_CaseEntries.Rows[i].Cells["UserEntry"].Value.ToString() != "".ToString())
{
_problem.AddFeature(
dataGV_CaseEntries.Rows[i].Cells["FeatureName"].Value.ToString().Trim(),
Token.GetType(dataGV_CaseEntries.Rows[i].Cells["FeatureType"].Value.ToString().Trim()),
dataGV_CaseEntries.Rows[i].Cells["UserEntry"].Value.ToString().Trim(),
Convert.ToDouble(dataGV_CaseEntries.Rows[i].Cells["FeatureWeight"].Value.ToString().Trim()),
Convert.ToBoolean(dataGV_CaseEntries.Rows[i].Cells["FeatureKey"].Value.ToString().Trim()),
Convert.ToBoolean(dataGV_CaseEntries.Rows[i].Cells["FeatureIndex"].Value.ToString().Trim()),
dataGV_CaseEntries.Rows[i].Cells["FeatureUnit"].Value.ToString().Trim());
}
}
_problem.AddFeature("cluster", FeatureType.TYPE_FEATURE_INT, 0, 1.0, false, false, "num");
statistics.exp_random_cases.Add(BestChoice.StandardizeCase(_problem, Max_Mean, Min_Sd, statistics.standrize_type));
statistics.exp_random_cases_nonstandrize.Add(_problem);
mybestchoice.Problem = statistics.exp_random_cases_nonstandrize[0];
mybestchoice.StandrizeProblem = statistics.exp_random_cases[0];
}