private void uiKnownObjects_SelectionChanged(object sender, EventArgs e)
{
TeachingSet.Element elementSelected =
_programLogic.TeachingSet[uiKnownObjects.CurrentRow.Index];
for (int i = 0; i < _programLogic.ExaminedNetwork.InputCount; i++)
{
double val = elementSelected.Inputs[i];
_inputSignals[i] = val;
uiInputData.Rows[0].Cells[i].Value = val.ToString();
}
}
private void PerformTeachingCycle()
{
MlpNetwork.LearningMethod method =
uiMethodWidrowHoff.Checked ? MlpNetwork.LearningMethod.WidrowHoff
: MlpNetwork.LearningMethod.Perceptron;
int stepCount = (int)uiCycleLength.Value;
for (int i = 0; i < stepCount; i++)
{
int teachingElementIndex = _randomGenerator.Next(_teachingSet.Count);
TeachingSet.Element teachingElement =
_teachingSet[teachingElementIndex];
double[] prevResp = null;
double[] prevErr = null;
_examinedNetwork.LearnSimple(teachingElement, 0.1,
ref prevResp, ref prevErr, method);
}
StepNumber += stepCount;
uiChartPlotter.Invalidate();
}
private void ShowResults()
{
TeachingSet.Element currentElement = _programLogic.CurrentElement;
uiStepNumber.Text =
String.Format("Step: {0}", _programLogic.TeachingStep);
uiComment.Text =
String.Format("Comment: {0}", currentElement.Comment);
if (uiDataBefore.ColumnCount == 0)
{
BuildGrids();
}
PutNumbers(currentElement.Inputs, uiDataBefore.Rows[1]);
PutNumbers(_programLogic.CurrentNormalizedInputs, uiDataBefore.Rows[2]);
PutNumbers(_programLogic.PreviousWeights, uiDataBefore.Rows[3]);
uiOutputBefore.Text = _programLogic.PreviousResponse.ToString("g6");
uiCorrectBefore.Text = currentElement.ExpectedOutputs[0].ToString("g6");
uiErrorBefore.Text = _programLogic.PreviousError.ToString("g6");
PutNumbers(_programLogic.ExaminedNeuron.Weights, uiDataAfter.Rows[1]);
uiOutputAfter.Text = _programLogic.CurrentResponse.ToString("g6");
uiCorrectAfter.Text = currentElement.ExpectedOutputs[0].ToString("g6");
uiErrorAfter.Text = _programLogic.CurrentError.ToString("g6");
}
private void ShowResults()
{
TeachingSet.Element currentElement = _programLogic.CurrentElement;
TeachingSet.Element currentNormalizedElement =
_programLogic.CurrentNormalizedElement;
uiStepNumber.Text =
String.Format("Step: {0}", _programLogic.TeachingStep);
uiComment.Text =
String.Format("Comment: {0}", currentElement.Comment);
if (uiInputData.ColumnCount == 0)
{
BuildGrids();
}
PutNumbers(currentElement.Inputs, uiInputData.Rows[1]);
PutNumbers(currentNormalizedElement.Inputs, uiInputData.Rows[2]);
PutNumbers(_programLogic.PreviousResponse, uiTeachingProgress.Rows[1]);
PutNumbers(currentElement.ExpectedOutputs, uiTeachingProgress.Rows[2]);
PutNumbers(_programLogic.PreviousError, uiTeachingProgress.Rows[3]);
PutNumbers(_programLogic.CurrentResponse, uiTeachingProgress.Rows[4]);
PutNumbers(_programLogic.CurrentError, uiTeachingProgress.Rows[5]);
}
private void UseStandardTeachingSet()
{
/* We divide by 2, because each teaching set part takes half
* of the gap size as its offset. */
double offset = GetGapSize(uiGapSize.Value) / 2.0;
_teachingSet = new TeachingSet(2, 1);
TeachingSet.Element elem = new TeachingSet.Element();
for (int x = 0; x < 3; x++)
{
for (int y = 0; y < 3; y++)
{
// Careful! We shouldn't make anything 0; it will render
// the element unuseful.
elem.Inputs =
new double[] { 0.2 + x * 0.2 + offset, -0.3 + y * 0.2 };
elem.ExpectedOutputs = new double[] { 1.0 };
_teachingSet.Add(elem);
elem.Inputs =
new double[] { -0.2 - x * 0.2 - offset, -0.3 + y * 0.2 };
elem.ExpectedOutputs = new double[] { -1.0 };
_teachingSet.Add(elem);
}
}
elem.Inputs = new double[] { offset, 0.3 };
elem.ExpectedOutputs = new double[] { 1.0 };
_teachingSet.Add(elem);
elem.Inputs = new double[] { -offset, 0.3 };
elem.ExpectedOutputs = new double[] { -1.0 };
_teachingSet.Add(elem);
ShowTeachingSet();
RestartTeaching();
}
