/// <summary>
/// Evaluate disk.
/// </summary>
private void EvalBinary()
{
FileInfo file = FileUtil.CombinePath( new FileInfo(Path.GetTempPath()), "temp.egb" );
BasicMLDataSet training = RandomTrainingFactory.Generate(
1000, 10000, 10, 10, -1, 1);
// create the binary file
if (file.Exists)
{
file.Delete();
}
var training2 = new BufferedMLDataSet(file.ToString());
training2.Load(training);
const long stop = (10*Evaluate.Milis);
int record = 0;
IMLDataPair pair;
var watch = new Stopwatch();
watch.Start();
int iterations = 0;
while(true)
{
iterations++;
pair = training[record++];
if(record >= training.Count)
record = 0;
if((iterations & 0xff) == 0 && watch.ElapsedMilliseconds >= stop)
break;
}
training2.Close();
iterations /= 100000;
_report.Report(Steps, Step3,
"Disk(binary) dataset, result: "
+ Format.FormatInteger(iterations));
if (file.Exists)
{
file.Delete();
}
_binaryScore = iterations;
}
/// <summary>
/// Load an EGB file to memory.
/// </summary>
/// <param name="filename">The file to load.</param>
/// <returns>A memory data set.</returns>
public static IMLDataSet LoadEGB2Memory(FileInfo filename)
{
var buffer = new BufferedMLDataSet(filename.ToString());
var result = buffer.LoadToMemory();
buffer.Close();
return result;
}
/// <summary>
/// Called to generate the training file.
/// </summary>
public void Generate()
{
string[] list = Directory.GetFiles(_path);
_trainingFile.Delete();
var output = new BufferedMLDataSet(_trainingFile.ToString());
output.BeginLoad(Config.InputWindow, 1);
foreach (string file in list)
{
var fn = new FileInfo(file);
if (fn.Name.StartsWith("collected") && fn.Name.EndsWith(".csv"))
{
ProcessFile(file, output);
}
}
output.EndLoad();
output.Close();
}
/// <summary>
/// Convert a CSV file to binary.
/// </summary>
/// <param name="csvFile">The CSV file to convert.</param>
/// <param name="format">The format.</param>
/// <param name="binFile">The binary file.</param>
/// <param name="input">The input.</param>
/// <param name="ideal">The ideal.</param>
/// <param name="headers">True, if headers are present.</param>
public static void ConvertCSV2Binary(FileInfo csvFile, CSVFormat format,
FileInfo binFile, int[] input, int[] ideal, bool headers)
{
binFile.Delete();
var csv = new ReadCSV(csvFile.ToString(), headers, format);
var buffer = new BufferedMLDataSet(binFile.ToString());
buffer.BeginLoad(input.Length, ideal.Length);
while (csv.Next())
{
var inputData = new BasicMLData(input.Length);
var idealData = new BasicMLData(ideal.Length);
// handle input data
for (int i = 0; i < input.Length; i++)
{
inputData[i] = csv.GetDouble(input[i]);
}
// handle input data
for (int i = 0; i < ideal.Length; i++)
{
idealData[i] = csv.GetDouble(ideal[i]);
}
// add to dataset
buffer.Add(inputData, idealData);
}
buffer.EndLoad();
buffer.Close();
csv.Close();
}
