// Update is called once per frame
void Update () {
if (!networkManager) {
networkManager = GameObject.Find ("NetworkManager").GetComponent<CustomNetworkManager> ();
return;
}
if (isLocalPlayer) {
if (!rup) {
rup = GameObject.FindGameObjectWithTag("ReadyUpPanel");
return;
} else if (!selection) {
selection = rup.GetComponent<ClassSelection>();
}
if (currentClass != selection.selectedClass) {
currentClass = selection.selectedClass;
CmdSendClass(currentClass);
}
}
}
private void ClsidInput_SelectionChanged(object sender, SelectionChangedEventArgs e)
{
ViewModel.SelectedItem = e.AddedItems.Count > 0 &&
e.AddedItems[0] is SearchItem registryClass
? registryClass
: default;
var selectedClass = ViewModel.SelectedClass;
Selection?.Invoke(this, selectedClass);
if (selectedClass != default)
{
ClassSelection?.Invoke(this, selectedClass);
}
else
{
InvalidAddress?.Invoke(this, ViewModel.SearchText);
}
e.Handled = true;
}
private async void Button_Click(object sender, RoutedEventArgs e)
{
OpenFileDialog ofd = new OpenFileDialog();
ofd.Filter = "PatternLab Project (*.plp)|*.plp";
ofd.FileName = "";
if (ofd.ShowDialog() != true)
{
return;
}
Dictionary <int, string> allClassDescriptions = new Dictionary <int, string>();
try
{
WaitWindowWPF.Visibility = Visibility.Visible;
await Task.Run(() => {
plp = new PatternLabProject(ofd.FileName);
allClassDescriptions = plp.MySparseMatrix.ClassDescriptionDictionary;
plp.MySparseMatrix.theMatrixInRows.Sort((a, b) => a.Lable.CompareTo(b.Lable));
//Verify if the sparse matrix classes are appropriate
List <int> theLabels = plp.MySparseMatrix.ExtractLabels();
List <int> newLabels = new List <int>();
for (int i = 0; i < theLabels.Count; i++)
{
newLabels.Add(i + 1);
}
if (theLabels.Count != 2)
{
ClassSelection cs = new ClassSelection(theLabels, newLabels, plp.MySparseMatrix, true, 3);
cs.ShowDialog();
}
});
WaitWindowWPF.Visibility = Visibility.Collapsed;
ComboBoxFonts.Text = "Times New Roman";
ButtonPlot.IsEnabled = true;
ButtonSavePlot.IsEnabled = true;
}
catch
{
MessageBox.Show("Problems loading sparse matrix / index files");
return;
}
//Verify if the classes follow the pattern 1,2,3, else we should correct and warn the uses
List <int> lables = plp.MySparseMatrix.ExtractLabels();
Dictionary <int, int> labelConversion = new Dictionary <int, int>();
Dictionary <int, string> newClassDescriptions = new Dictionary <int, string>();
for (int i = 0; i < lables.Count; i++)
{
labelConversion.Add(lables[i], i + 1);
if (lables[i] != i + 1)
{
MessageBox.Show("Matrix lable " + lables[i] + " will be represented as group " + (i + 1));
}
}
foreach (sparseMatrixRow r in plp.MySparseMatrix.theMatrixInRows)
{
r.Lable = labelConversion[r.Lable];
}
//----------------------------------
//Update the descriptions, in case they have the word group
if (TextBoxC1Name.Text.Equals("Group") && lables.Count >= 1 && plp.MySparseMatrix.ClassDescriptionDictionary.ContainsKey(lables[0]) || allClassDescriptions.ContainsValue(TextBoxC1Name.Text))
{
TextBoxC1Name.Text = plp.MySparseMatrix.ClassDescriptionDictionary[lables[0]];
}
if (TextBoxC2Name.Text.Equals("Group") && lables.Count >= 2 && plp.MySparseMatrix.ClassDescriptionDictionary.ContainsKey(lables[1]) || allClassDescriptions.ContainsValue(TextBoxC2Name.Text))
{
TextBoxC2Name.Text = plp.MySparseMatrix.ClassDescriptionDictionary[lables[1]];
}
if (TextBoxC3Name.Text.Equals("Group") && lables.Count >= 3 && plp.MySparseMatrix.ClassDescriptionDictionary.ContainsKey(lables[2]) || allClassDescriptions.ContainsValue(TextBoxC3Name.Text))
{
TextBoxC3Name.Text = plp.MySparseMatrix.ClassDescriptionDictionary[lables[2]];
}
if (lables.Count != 2)
{
RadioButtonFilteringProbability.IsEnabled = false;
}
}
private void buttonParse_Click(object sender, EventArgs e)
{
openFileDialog1.Filter = "PatternLab Project (*.plp)|*.plp";
openFileDialog1.FileName = "";
if (openFileDialog1.ShowDialog() == DialogResult.Cancel)
{
return;
}
plp = new PatternLabProject(openFileDialog1.FileName);
//To make sure we dont duplicate info in the table
buttonParse.Text = "Wait!";
this.Update();
dataGridView1.Rows.Clear();
folds.Clear();
//try
//{
//Calculate the pscores and folds
ClassSelection cs;
//Verify if the sparse matrix classes are appropriate
List <int> theLabels = plp.MySparseMatrix.ExtractLabels();
buttonOptimizeFStringency.Enabled = true;
if (theLabels.Count > 2 || (theLabels.Count == 2 && ((!theLabels.Contains(1) || !theLabels.Contains(-1)))))
{
if (radioButtonAC.Checked)
{
cs = new ClassSelection(theLabels, new List <int> {
-1, 1
}, plp.MySparseMatrix, false, 2);
}
else if (radioButtonTTest.Checked)
{
cs = new ClassSelection(theLabels, new List <int> {
-1, 1
}, plp.MySparseMatrix, true, 2);
}
else
{
cs = new ClassSelection(theLabels, new List <int> {
-1, 1
}, plp.MySparseMatrix, true, 2);
}
cs.ShowDialog();
}
if (theLabels.Count == 1 && !theLabels.Contains(-1) && radioButtonTTest.Checked)
{
cs = new ClassSelection(theLabels, new List <int> {
-1
}, plp.MySparseMatrix, true, 1);
cs.ShowDialog();
}
//Refresh the labels
theLabels = plp.MySparseMatrix.ExtractLabels();
//Compress the matrix
if (radioButtonAC.Checked)
{
plp.MySparseMatrix.shatterMatrix();
}
else if (radioButtonTTest.Checked)
{
//Eliminate dims that do not satisfy the minimum readings
if (radioButtonAllClasses.Checked)
{
List <int> allDims = plp.MySparseMatrix.allDims();
List <int> dimsToEliminate = new List <int>();
foreach (int dim in allDims)
{
List <double> valuesT = plp.MySparseMatrix.ExtractDimValues(dim, 0, true);
if (valuesT.Count < (double)numericUpDownMinReplicates.Value)
{
dimsToEliminate.Add(dim);
}
}
foreach (int dim in dimsToEliminate)
{
plp.MySparseMatrix.eliminateDim(dim, 0, true);
}
}
else if (radioButtonPerClass.Checked)
{
List <int> allDims = plp.MySparseMatrix.allDims();
List <int> allClasses = plp.MySparseMatrix.ExtractLabels();
List <int> dimsToEliminate = new List <int>();
foreach (int dim in allDims)
{
foreach (int label in allClasses)
{
List <double> valuesT = plp.MySparseMatrix.ExtractDimValues(dim, label, false);
if (valuesT.Count < (double)numericUpDownMinReplicates.Value)
{
dimsToEliminate.Add(dim);
}
}
}
dimsToEliminate = dimsToEliminate.Distinct().ToList();
foreach (int dim in dimsToEliminate)
{
plp.MySparseMatrix.eliminateDim(dim, 0, true);
}
}
}
//matrix.saveMatrix(@"C:\Users\Paulo C Carvalho\Desktop\PatternLabExampleData\ExampleData\mstep2DimElimination.txt");
//Add pseudo spectral counts
if (!radioButtonUsingLabeledData.Checked)
{
plp.MySparseMatrix.addPseudoCounts(1);
}
//Determine what normalization the user specified
int normalization = 0;
if (radioButtonNRowSigma.Checked)
{
normalization = 1;
}
else if (radioButtonNTS.Checked)
{
normalization = 2;
}
else if (radioButtonUsingLabeledData.Checked)
{
normalization = 3;
}
if (theLabels.Count <= 2)
{
XFoldCalculations fs = new XFoldCalculations(plp.MySparseMatrix);
theData = fs.Xfold(normalization, radioButtonAC.Checked, (double)numericUpDownPValueLowerClip.Minimum);
//Calculate all the folds
folds.Clear();
foreach (var dataPoint in theData)
{
double correctedFoldChange;
correctedFoldChange = dataPoint.CorrectedFold();
//keep track of fold Changes
double foldChangeToAdd = correctedFoldChange;
if (foldChangeToAdd > 3)
{
foldChangeToAdd = 3;
}
else if (foldChangeToAdd < -3)
{
foldChangeToAdd = -3;
}
folds.Add(correctedFoldChange);
}
//Populate Result Table
//Fill the Data Table
foreach (XFoldStruct ac in theData)
{
//Just in case
if (ac.GPI == 0)
{
continue;
}
try
{
dataGridView1.Rows.Add(
ac.GPI,
plp.MyIndex.GetName(ac.GPI),
Math.Round(ac.FoldChange, 2),
Math.Round(ac.pValue, 4),
ac.QuantitationPositiveClass,
ac.QuantitationNegativeClass,
plp.MyIndex.GetDescription(ac.GPI)
);
}
catch (Exception e2)
{
MessageBox.Show(e2.Message);
}
}
}
//Were done
groupBoxSelectionParameters.Enabled = true;
groupBoxFunctions.Enabled = true;
//Make sure the canvas is clean
//acPlotWPF1.dispose();
//Clear the labels
labelBlueDots.Text = "0";
labelGreenDots.Text = "0";
labelRedDots.Text = "0";
labelTotalNumber.Text = "0";
//}
//catch (Exception z)
//{
// ErrorWindow ew = new ErrorWindow(z.GetBaseException().ToString());
// ew.ShowDialog();
//}
buttonParse.Text = "Parse";
}
private void buttonLoad_Click(object sender, EventArgs e)
{
openFileDialog1.Filter = "PatternLab Project (*.plp)|*.plp";
openFileDialog1.FileName = "";
if (openFileDialog1.ShowDialog() == DialogResult.Cancel)
{
return;
}
Dictionary <int, string> allClassDescriptions = new Dictionary <int, string>();
try
{
plp = new PatternLabProject(openFileDialog1.FileName);
allClassDescriptions = plp.MySparseMatrix.ClassDescriptionDictionary;
plp.MySparseMatrix.theMatrixInRows.Sort((a, b) => a.Lable.CompareTo(b.Lable));
//Verify if the sparse matrix classes are appropriate
List <int> theLabels = plp.MySparseMatrix.ExtractLabels();
List <int> newLabels = new List <int>();
for (int i = 0; i < theLabels.Count; i++)
{
newLabels.Add(i + 1);
}
if (theLabels.Count != 2 || (theLabels.Count == 2 && (!theLabels.Contains(1) || !theLabels.Contains(-1))))
{
ClassSelection cs = new ClassSelection(theLabels, newLabels, plp.MySparseMatrix, true, 3);
cs.ShowDialog();
}
groupBoxPlotOptions.Enabled = true;
}
catch
{
MessageBox.Show("Problems loading sparse matrix / index files");
return;
}
//Verify if the classes follow the pattern 1,2,3, else we should correct and warn the uses
List <int> lables = plp.MySparseMatrix.ExtractLabels();
Dictionary <int, int> labelConversion = new Dictionary <int, int>();
Dictionary <int, string> newClassDescriptions = new Dictionary <int, string>();
for (int i = 0; i < lables.Count; i++)
{
labelConversion.Add(lables[i], i + 1);
if (lables[i] != i + 1)
{
MessageBox.Show("Matrix lable " + lables[i] + " will be represented as group " + (i + 1));
}
}
foreach (sparseMatrixRow r in plp.MySparseMatrix.theMatrixInRows)
{
r.Lable = labelConversion[r.Lable];
}
//----------------------------------
//Update the descriptions, in case they have the word group
if (textBoxC1Name.Text.Equals("Group") && lables.Count >= 1 && plp.MySparseMatrix.ClassDescriptionDictionary.ContainsKey(lables[0]) || allClassDescriptions.ContainsValue(textBoxC1Name.Text))
{
textBoxC1Name.Text = plp.MySparseMatrix.ClassDescriptionDictionary[lables[0]];
//textBoxC1Name.Text = sMatrix.ClassDescriptionDictionary[1];
}
if (textBoxC2Name.Text.Equals("Group") && lables.Count >= 2 && plp.MySparseMatrix.ClassDescriptionDictionary.ContainsKey(lables[1]) || allClassDescriptions.ContainsValue(textBoxC2Name.Text))
{
textBoxC2Name.Text = plp.MySparseMatrix.ClassDescriptionDictionary[lables[1]];
//textBoxC2Name.Text = sMatrix.ClassDescriptionDictionary[2];
}
if (textBoxC3Name.Text.Equals("Group") && lables.Count >= 3 && plp.MySparseMatrix.ClassDescriptionDictionary.ContainsKey(lables[2]) || allClassDescriptions.ContainsValue(textBoxC3Name.Text))
{
textBoxC3Name.Text = plp.MySparseMatrix.ClassDescriptionDictionary[lables[2]];;
//textBoxC3Name.Text = sMatrix.ClassDescriptionDictionary[3];
}
if (lables.Count != 2)
{
radioButtonFilteringProbability.Enabled = false;
}
}
