public void Bind(object pArgument)
{
if (pArgument is randomForestArguments)
{
randomForestArguments arg = (randomForestArguments)pArgument;
inrsBandsCoef = arg.InRasterCoefficients;
//coefRaster = arg.RasterUtility.createRaster(inrsBandsCoef);
outrs = arg.OutRaster;
xVls = new double[((IRasterBandCollection)inrsBandsCoef).Count];
Console.WriteLine("Number of Bands in outrs = " + ((IRasterBandCollection)outrs).Count.ToString());
df = arg.RandomForestModel;
myFunctionHelper.Bind(outrs);
myFunctionHelperCoef.Bind(inrsBandsCoef);
myRasterInfo = myFunctionHelper.RasterInfo;
myPixeltype = myRasterInfo.PixelType;
myValidFlag = true;
}
else
{
throw new System.Exception("Incorrect arguments object. Expected: randomForestArguments");
}
}
private void btnExecute_Click(object sender, EventArgs e)
{
string smpFtrNm = cmbSampleFeatureClass.Text;
string depFld = cmbDepedent.Text;
string outP = txtOutputPath.Text;
int trees = System.Convert.ToInt32(nudTrees.Value);
double ratio = System.Convert.ToDouble(nudratio.Value);
int split = System.Convert.ToInt32(nudSplit.Value);
if (smpFtrNm == null || smpFtrNm == "")
{
MessageBox.Show("You must select a feature Class", "Error", MessageBoxButtons.OK, MessageBoxIcon.Error);
return;
}
if (depFld == null || depFld == "")
{
MessageBox.Show("You must select a dependent field", "Error", MessageBoxButtons.OK, MessageBoxIcon.Error);
return;
}
if (outP == null || outP == "")
{
MessageBox.Show("You must select an output model path", "Error", MessageBoxButtons.OK, MessageBoxIcon.Error);
return;
}
List <string> lstInd = new List <string>();
for (int i = 0; i < lstIndependent.Items.Count; i++)
{
string s = lstIndependent.Items[i].ToString();
lstInd.Add(s);
}
if (lstInd.Count < 1)
{
MessageBox.Show("You must select at least one independent field", "Error", MessageBoxButtons.OK, MessageBoxIcon.Error);
return;
}
this.Visible = false;
try
{
Statistics.ModelHelper.runProgressBar("Running Random Forest");
if (!chbReg.Checked && !lstCategoricalFlds.Contains(depFld))
{
lstCategoricalFlds.Add(depFld);
}
ITable ftrCls = ftrDic[smpFtrNm];
Statistics.dataPrepRandomForest rf = null;
if (split > 0)
{
rf = new Statistics.dataPrepRandomForest(ftrCls, new string[] { depFld }, lstInd.ToArray(), lstCategoricalFlds.ToArray(), trees, ratio, split, chbVI.Checked, qf);
}
else
{
rf = new Statistics.dataPrepRandomForest(ftrCls, new string[] { depFld }, lstInd.ToArray(), lstCategoricalFlds.ToArray(), trees, ratio, chbVI.Checked, qf);
}
rf.writeModel(outP);
rf.getReport();
}
catch (Exception ex)
{
MessageBox.Show(ex.ToString());
}
finally
{
Statistics.ModelHelper.closeProgressBar();
this.Close();
}
}
private void btnExecute_Click(object sender, EventArgs e)
{
string smpFtrNm = cmbSampleFeatureClass.Text;
string depFld = cmbDepedent.Text;
string outP = txtOutputPath.Text;
int trees = System.Convert.ToInt32(nudTrees.Value);
double ratio = System.Convert.ToDouble(nudratio.Value);
int split = System.Convert.ToInt32(nudSplit.Value);
if (smpFtrNm == null || smpFtrNm == "")
{
MessageBox.Show("You must select a feature Class","Error",MessageBoxButtons.OK,MessageBoxIcon.Error);
return;
}
if (depFld == null || depFld == "")
{
MessageBox.Show("You must select a dependent field", "Error", MessageBoxButtons.OK, MessageBoxIcon.Error);
return;
}
if (outP == null || outP == "")
{
MessageBox.Show("You must select an output model path", "Error", MessageBoxButtons.OK, MessageBoxIcon.Error);
return;
}
List<string> lstInd = new List<string>();
for (int i = 0; i < lstIndependent.Items.Count; i++)
{
string s = lstIndependent.Items[i].ToString();
lstInd.Add(s);
}
if (lstInd.Count < 1)
{
MessageBox.Show("You must select at least one independent field", "Error", MessageBoxButtons.OK, MessageBoxIcon.Error);
return;
}
this.Visible = false;
try
{
Statistics.ModelHelper.runProgressBar("Running Random Forest");
if (!chbReg.Checked && !lstCategoricalFlds.Contains(depFld))
{
lstCategoricalFlds.Add(depFld);
}
ITable ftrCls = ftrDic[smpFtrNm];
Statistics.dataPrepRandomForest rf = null;
if (split > 0)
{
rf = new Statistics.dataPrepRandomForest(ftrCls, new string[] { depFld }, lstInd.ToArray(), lstCategoricalFlds.ToArray(), trees, ratio, split,chbVI.Checked,qf);
}
else
{
rf = new Statistics.dataPrepRandomForest(ftrCls, new string[] { depFld }, lstInd.ToArray(), lstCategoricalFlds.ToArray(), trees, ratio,chbVI.Checked,qf);
}
rf.writeModel(outP);
rf.getReport();
}
catch (Exception ex)
{
MessageBox.Show(ex.ToString());
}
finally
{
Statistics.ModelHelper.closeProgressBar();
this.Close();
}
}
