public void LearningTest()
{
MathTextBitmap bitmap =
new MathTextBitmap(new FloatBitmap(5,5), new Gdk.Point(0,0));
bitmap.ProcessImage(new List<BitmapProcesses.BitmapProcess>());
CharacteristicTreeDatabase database =
new CharacteristicTreeDatabase();
MathSymbol aSymbol = new MathSymbol("a");
MathSymbol bSymbol = new MathSymbol("b");
database.Learn(bitmap, aSymbol);
List<MathSymbol> symbols = database.Match(bitmap);
bool a1Learned = symbols.Count == 1
&& symbols[0] == aSymbol;
bool a2Learned = true;
a2Learned = database.Learn(bitmap, aSymbol);
database.Learn(bitmap, bSymbol);
symbols = database.Match(bitmap);
bool b1Learned = symbols.Count == 2;
Assert.IsTrue(a1Learned, "Fallo el aprender la primera a");
Assert.IsFalse(a2Learned, "No se detecto el conflicto de la segunda a");
Assert.IsTrue(b1Learned, "Fallo el aprender la b");
}
private void OnImagesIVSelectionChanged(object s, EventArgs a)
{
removeImageBtn.Sensitive = imagesIV.SelectedItems.Length > 0;
TreeIter selectedIter;
if(imagesIV.SelectedItems.Length > 0)
{
TreePath selectedImagePath = imagesIV.SelectedItems[0];
imagesStore.GetIter(out selectedIter, selectedImagePath);
Gdk.Pixbuf orig = (Gdk.Pixbuf)(imagesStore.GetValue(selectedIter,1));
mtb = new MathTextBitmap(orig);
mtb.ProcessImage(database.Processes);
imageAreaOriginal.Image = orig;
imageAreaProcessed.Image = mtb.LastProcessedImage.CreatePixbuf();
}
else
{
imageAreaOriginal.Image = null;
imageAreaProcessed.Image = null;
}
}