/// <summary>
/// Supplies data for training and testing.
/// </summary>
/// <param name="record"></param>
public void SetRecord(EEGRecord record)
{
_er = record;
_ml.ActionList = _er.actions;
#region convert
double[][] input = new double[record.FeatureVectorsOutputInput.Count][];
double[][] output = new double[record.FeatureVectorsOutputInput.Count][];
for (int i = 0; i < record.FeatureVectorsOutputInput.Count; i++)
{
input[i] = new double[_er.FeatureVectorsOutputInput[i].Length - 1];
Array.Copy(_er.FeatureVectorsOutputInput[i], 1, input[i], 0, input[i].Length);
output[i] = new double[1];
output[i][0] = _er.FeatureVectorsOutputInput[i][0];
}
#endregion
#region seperate data for training and testing (evaluating final computed model)
int ratio = 5;
NNTrainDataIterator iter = new NNTrainDataIterator(ratio, input, output);
iter.NextData(out trainDataInput, out trainDataOutput, out testDataInput, out testDataOutput);
#endregion
}
public ManageRecordedData(EEGRecord record)
{
InitializeComponent();
AsyncWorkerLoadEEGRecords = new BackgroundWorker();
AsyncWorkerLoadEEGRecords.DoWork += new DoWorkEventHandler(AsyncWorkerLoadEEGRecords_DoWork);
AsyncWorkerLoadEEGRecords.RunWorkerCompleted += new RunWorkerCompletedEventHandler(AsyncWorkerLoadEEGRecords_RunWorkerCompleted);
AsyncWorkerSaveEEGRecord = new BackgroundWorker();
AsyncWorkerSaveEEGRecord.DoWork += new DoWorkEventHandler(AsyncWorkerSaveEEGRecord_DoWork);
AsyncWorkerSaveEEGRecord.RunWorkerCompleted += new RunWorkerCompletedEventHandler(AsyncWorkerSaveEEGRecord_RunWorkerCompleted);
providedRecord = record;
//listBox1.DisplayMember = "Name";
toolStripStatusLabel1.Text = "Loading EEG records... please wait";
buttonLoad.Enabled = false;
rs = new EEGRecordStorage();
AsyncWorkerLoadEEGRecords.RunWorkerAsync();
if (AsyncWorkerLoadEEGRecords.IsBusy)
{
buttonSave.Enabled = false;
}
listBox1.Items.Add("Loading...");
}
public Experiment(string name, EEGRecord er, AMLearning ml, bool enabled)
{
Name = name;
_er = er;
_ml = ml;
_enabled = enabled;
_ml.Progress += new ChangedValuesEventHandler(_ml_Progress);
}
/// <summary>
/// Checks dimensions
/// </summary>
/// <param name="record"></param>
/// <returns></returns>
public static bool IsRecordValid(EEGRecord record)
{
int m = record.FeatureVectorsOutputInput[0].Length;
foreach (var k in record.FeatureVectorsOutputInput)
{
if (k.Length != m)
{
return(false);
}
}
return(true);
}
public void SaveRecord(EEGRecord record)
{
if (!File.Exists(DbSettings.fullpath + ".eq"))
{
db.CreateDatabase(DbSettings.fullpath);
}
db.OpenDatabase(DbSettings.fullpath);
db.RefreshMode = ObjectRefreshMode.AlwaysReturnUpdatedValues;
db.Store(record);
db.Close();
}
public EEGRecord(EEGRecord rec)
{
FeatureVectorsOutputInput = new List <double[]>();
actions = new Dictionary <string, int>(rec.actions);
for (int i = 0; i < rec.FeatureVectorsOutputInput.Count; i++)
{
double[] newItem = new double[rec.FeatureVectorsOutputInput[i].Length];
rec.FeatureVectorsOutputInput[i].CopyTo(newItem, 0);
FeatureVectorsOutputInput.Add(newItem);
}
Name = rec.Name;
}
void AsyncWorkerSaveEEGRecord_DoWork(object sender, DoWorkEventArgs e)
{
if (providedRecord.FeatureVectorsOutputInput.Count == 0)
{
MessageBox.Show("Save operation aborted. Record seems empty!");
return;
}
toolStripStatusLabel1.Text = "Saving... please wait";
EEGRecord saveRecord = new EEGRecord(providedRecord);//create a copy
saveRecord.Name = textBoxName.Text;
rs.SaveRecord(saveRecord);
records.Add(saveRecord);
}
public EEGRecord LoadModel(string name)
{
EEGRecord result = null;
if (File.Exists(DbSettings.fullpath + ".eq"))
{
db.OpenDatabase(DbSettings.fullpath);
db.RefreshMode = ObjectRefreshMode.AlwaysReturnUpdatedValues;
result = (from EEGRecord sample in db
where sample.Name == name
select sample).FirstOrDefault();
db.Close();
}
return(result);
}
void rd_ReocordSelected(EEGRecord record)
{
foreach (double[] vector in record.FeatureVectorsOutputInput)
{
double[] input = new double[vector.Length - 1];
Array.Copy(vector, 1, input, 0, vector.Length - 1);
int result = model.Classify(input);
if (result == vector[0])
{
listBoxResult.Items.Insert(0, "OK");
}
else
{
listBoxResult.Items.Insert(0, "wrong");
}
}
}
public abstract void Train(EEGRecord record);
private void buttonClearRecord_Click(object sender, EventArgs e)
{
currentRecord = new EEGRecord();
listBoxLogger.Items.Insert(0, "Recorded data cleared. Now you can record or load data.");
}
void rd_ReocordSelected(EEGRecord selectedRecord)
{
currentRecord = new EEGRecord(selectedRecord);//create a copy
listBoxLogger.Items.Insert(0, "Pre-recorded data '" + selectedRecord.Name + "' has been loaded containing: " + currentRecord.FeatureVectorsOutputInput.Count + " feature vectors. You can now record additional data or start 'Computing'.");
}