public async Task TrainNeuralNetwork()
{
BloodDonatonNeuralNet net = new BloodDonatonNeuralNet();
await Task.Run(() =>
{
try
{
Init();
}
catch (Exception ex)
{
}
});
}
protected override async void OnCreate(Bundle savedInstanceState)
{
base.OnCreate(savedInstanceState);
SetContentView(Resource.Layout.MainMenu);
// Create your application here
textViewLastBloodPicture = FindViewById <TextView>(Resource.Id.textViewLastBloodPicture);
textViewAnalyzeName = FindViewById <TextView>(Resource.Id.textViewAnalyzeName);
textViewAnalyzeResults = FindViewById <TextView>(Resource.Id.textViewAnalyzeResults);
textViewShouldDo = FindViewById <TextView>(Resource.Id.textViewShouldDo);
textViewShouldDo1 = FindViewById <TextView>(Resource.Id.textViewShouldDo1);
textViewShouldDo2 = FindViewById <TextView>(Resource.Id.textViewShouldDo2);
imageViewShuldDo1 = FindViewById <ImageView>(Resource.Id.imageViewShuldDo1);
imageViewShuldDo2 = FindViewById <ImageView>(Resource.Id.imageViewShuldDo2);
buttonGetLastBP = FindViewById <Button>(Resource.Id.buttonGetLastBP);
buttonGetLastBP.Click += ButtonGetLastBP_Click;
buttonAnalyzeBP = FindViewById <Button>(Resource.Id.buttonAnalyzeBP);
buttonAnalyzeBP.Click += ButtonAnalyzeBP_Click;
buttonGetPlan = FindViewById <Button>(Resource.Id.buttonGetPlan);
buttonGetPlan.Click += ButtonGetPlan_Click;
BloodPictureGraph = FindViewById <PlotView>(Resource.Id.BloodPictureGraph);
buttonGetPlan.Visibility = ViewStates.Invisible;
textViewAnalyzeName.Visibility = ViewStates.Invisible;
textViewAnalyzeResults.Visibility = ViewStates.Invisible;
textViewShouldDo.Visibility = ViewStates.Invisible;
progressDialog = new ProgressDialog(this);
progressDialog.Indeterminate = true;
progressDialog.SetProgressStyle(ProgressDialogStyle.Spinner);
progressDialog.SetMessage("Calculating...");
progressDialog.SetCancelable(false);
progressDialog.Create();
progressDialog.Show();
//await TrainNeuralNetwork();
neuralNetwork = await LoadNeuralNetwork();
bloodPictureData = DatabaseAdapter.GetLastBloodData().Result;
BloodPictureGraph.Model = CalculateBP();
progressDialog.Hide();
}
public async Task <BloodDonatonNeuralNet> LoadNeuralNetwork()
{
BloodDonatonNeuralNet net = new BloodDonatonNeuralNet();
await Task.Run(() =>
{
try
{
var FullFilePath = System.IO.Path.Combine(System.Environment.GetFolderPath(System.Environment.SpecialFolder.Personal), filename);
BinaryFormatter bf = new BinaryFormatter();
using (Stream fsout = new FileStream(FullFilePath, FileMode.Open, FileAccess.Read, FileShare.None))
{
bf.Binder = new PreMergeToMergedDeserializationBinder();
net = (BloodDonatonNeuralNet)bf.Deserialize(fsout);
}
}
catch (Exception ex)
{
}
});
return(net);
}
public void Init()
{
var dataset = CreateDataSet();
int counter = 0;
needToStop = false;
// initialize input and output values
double[][] input = new double[dataSetArrayCount][];
double[][] output = new double[dataSetArrayCount][];
for (int i = 0; i < dataset.Count; i++)
{
input[i] = new double[6];
input[i][0] = dataset[i].Erytrocyt;
input[i][1] = dataset[i].Fibrinogen;
input[i][2] = dataset[i].Hemocyt;
input[i][3] = dataset[i].Leukocyt;
input[i][4] = dataset[i].Protrombin;
input[i][5] = dataset[i].Trombocyt;
output[i] = new double[2];
output[i][0] = dataset[i].Result1;
output[i][1] = dataset[i].Result2;
}
SigmoidFunction sigmoidFunction = new SigmoidFunction(5);
// create neural network
ActivationNetwork network = new ActivationNetwork(
sigmoidFunction,
6, // two inputs in the network
5, // two neurons in the first layer
2); // one neuron in the second layer
// create teacher
network.Randomize();
BackPropagationLearning teacher =
new BackPropagationLearning(network);
teacher.LearningRate = 5;
// loop
while (!needToStop)
{
// run epoch of learning procedure
double error = teacher.RunEpoch(input, output);
// check error value to see if we need to stop
// ...
counter++;
if (counter == 2000)
{
Console.WriteLine(error);
counter = 0;
}
//if (error < 200)
if (error < 0.05)
{
needToStop = true;
}
}
BloodDonatonNeuralNet bloodDonatonNeuralNet = new BloodDonatonNeuralNet();
bloodDonatonNeuralNet.NeuralNetwork = network;
AssetManager assets = this.Assets;
IFormatter formatter;
using (MemoryStream stream = new MemoryStream())
{
formatter = new BinaryFormatter();
formatter.Serialize(stream, bloodDonatonNeuralNet);
var FullFilePath = System.IO.Path.Combine(System.Environment.GetFolderPath(System.Environment.SpecialFolder.Personal), filename);
stream.Seek(0, SeekOrigin.Begin);
using (FileStream fs = new FileStream(FullFilePath, FileMode.OpenOrCreate))
{
stream.CopyTo(fs);
fs.Flush();
}
}
}
