private void ui_load_Click(object sender, EventArgs e)
{
DataLoader fileLoader = new DataLoader();
fileLoader.prepareOpen(dataPath, "train", "gauss_5", 1000, 0);
fileLoader.open();
data.trainingData = fileLoader._imgArr;
fileLoader.prepareOpen(labelPath, "train", "clean", 1000, 0);
fileLoader.open();
data.trainingLabels = fileLoader._imgArr;
for (int i=0; i<999; i++)
{
double[] input = data.normalize(data.trainingData[i]);
double[] target = data.normalize(data.trainingLabels[i]);
nn.prepareFeed(input, target);
nn.feedForward();
nn.backprop();
nn.trainingErrors[i] = nn.getError();
}
//FileLoader testDataLoader = new FileLoader();
//FileLoader testLabelLoader = new FileLoader();
//FileLoader trainDataLoader = new FileLoader();
//FileLoader trainLabelLoader = new FileLoader();
//status_bar.Text = "Loading test Data. PLease wait!";
//int type = ui_noiseType.SelectedIndex;
//string noiseType = string.Empty;
//switch (type)
//{
// case 0:
// noiseType = "gauss_5";
// break;
// case 1:
// noiseType = "gauss_10";
// break;
// case 2:
// noiseType = "gauss_15";
// break;
// case 3:
// noiseType = "snp_002";
// break;
// case 4:
// noiseType = "snp_005";
// break;
// case 5:
// noiseType = "snp_01";
// break;
// case 6:
// noiseType = "gauss_5_snp_005";
// break;
// case 7:
// noiseType = "gauss_10_snp_002";
// break;
// case 8:
// noiseType = "gauss_15_snp_01";
// break;
// case 9:
// noiseType = "random";
// break;
//}
//try
//{
// testDataLoader.prepareOpen(dataPath, "test", noiseType, 100);
// Thread testDataThread = new Thread(new ThreadStart(testDataLoader.open));
// testLabelLoader.prepareOpen(labelPath, "test", "clean", 100);
// Thread testLabelThread = new Thread(new ThreadStart(testLabelLoader.open));
// trainDataLoader.prepareOpen(dataPath, "train", noiseType, 600);
// Thread trainDataThread = new Thread(new ThreadStart(trainDataLoader.open));
// trainLabelLoader.prepareOpen(labelPath, "train", "clean", 600);
// Thread trainLabelThread = new Thread(new ThreadStart(trainLabelLoader.open));
// testDataThread.Start();
// testDataThread.Join();
// testLabelThread.Start();
// testLabelThread.Join();
// trainDataThread.Start();
// trainDataThread.Join();
// trainLabelThread.Start();
// trainLabelThread.Join();
// //file_loader.open(label_path, "test", "clean", 10000);
//}
//catch (Exception ex)
//{
// //somethign went wrong
// status_bar.Text = "Shit happened with the file loader... fix it!";
//}
//data.testData = testDataLoader._imgArr;
//data.testLabels = testLabelLoader._imgArr;
//data.trainingData = trainDataLoader._imgArr;
//data.trainingLabels = trainLabelLoader._imgArr;
}
private void ui_experiment_Click(object sender, EventArgs e)
{
DataLoader fileLoader = new DataLoader();
fileLoader.prepareOpen(dataPath, "train", "gauss_15", 1000, 0);
fileLoader.open();
data.trainingData = fileLoader._imgArr;
fileLoader.prepareOpen(labelPath, "train", "clean", 1000, 0);
fileLoader.open();
data.trainingLabels = fileLoader._imgArr;
NN nn = new NN(9, 2, 4); //units, (hidden) layers, sidmoid levels
for (int i = 0; i < 999; i++)
{
for (int j = 1; j <= 9; j++)
{
for (int k = 1; k <= 9; k++)
{
}
}
double[] input = data.normalize(data.trainingData[i]);
double[] target = data.normalize(data.trainingLabels[i]);
nn.prepareFeed(input, target);
nn.feedForward();
nn.backprop();
nn.trainingErrors[i] = nn.getError();
}
}
