/// <summary>
/// Construct a buffered dataset using the specified file.
/// </summary>
/// <param name="binaryFile">The file to read/write binary data to/from.</param>
public BufferedNeuralDataSet(String binaryFile)
{
this.file = binaryFile;
this.egb = new EncogEGBFile(binaryFile);
if (File.Exists(this.file))
{
this.egb.Open();
}
}
/// <summary>
/// Convert an Encog binary file to an external form, such as CSV.
/// </summary>
/// <param name="binaryFile">THe binary file to use.</param>
public void Binary2External(String binaryFile)
{
Status.Report(0, 0, "Exporting binary file: " + binaryFile);
EncogEGBFile egb = new EncogEGBFile(binaryFile);
egb.Open();
this.codec.PrepareWrite(egb.NumberOfRecords, egb.InputCount,
egb.IdealCount);
int inputCount = egb.InputCount;
int idealCount = egb.IdealCount;
double[] input = new double[inputCount];
double[] ideal = new double[idealCount];
int currentRecord = 0;
int lastUpdate = 0;
// now load the data
for (int i = 0; i < egb.NumberOfRecords; i++)
{
for (int j = 0; j < inputCount; j++)
{
input[j] = egb.Read();
}
for (int j = 0; j < idealCount; j++)
{
ideal[j] = egb.Read();
}
this.codec.Write(input, ideal);
currentRecord++;
lastUpdate++;
if (lastUpdate >= 10000)
{
lastUpdate = 0;
this.Status.Report(egb.NumberOfRecords, currentRecord,
"Exporting...");
}
}
egb.Close();
this.codec.Close();
Status.Report(0, 0, "Done exporting binary file: "
+ binaryFile);
}
/// <summary>
/// Convert an external file format, such as CSV, to the Encog binary
/// training format.
/// </summary>
/// <param name="binaryFile">The binary file to create.</param>
public void External2Binary(String binaryFile)
{
Status.Report(0, 0, "Importing to binary file: "
+ binaryFile);
EncogEGBFile egb = new EncogEGBFile(binaryFile);
egb.Create(codec.InputSize, codec.IdealSize);
double[] input = new double[this.codec.InputSize];
double[] ideal = new double[this.codec.IdealSize];
this.codec.PrepareRead();
int index = 3;
int currentRecord = 0;
int lastUpdate = 0;
while (codec.Read(input, ideal))
{
egb.Write(input);
egb.Write(ideal);
index += input.Length;
index += ideal.Length;
currentRecord++;
lastUpdate++;
if (lastUpdate >= 10000)
{
lastUpdate = 0;
this.Status.Report(0, currentRecord, "Importing...");
}
}
egb.Close();
this.codec.Close();
Status.Report(0, 0, "Done importing to binary file: "
+ binaryFile);
}
/// <summary>
/// Close the dataset.
/// </summary>
public void Close()
{
Object[] obj = this.additional.ToArray();
for (int i = 0; i < obj.Length; i++)
{
BufferedNeuralDataSet set = (BufferedNeuralDataSet)obj[i];
set.Close();
}
this.additional.Clear();
if (this.owner != null)
{
this.owner.RemoveAdditional(this);
}
this.egb.Close();
this.egb = null;
}
/// <summary>
/// Convert an external file format, such as CSV, to the Encog binary
/// training format.
/// </summary>
/// <param name="binaryFile">The binary file to create.</param>
public void External2Binary(String binaryFile)
{
Status.Report(0, 0, "Importing to binary file: "
+ binaryFile);
EncogEGBFile egb = new EncogEGBFile(binaryFile);
egb.Create(codec.InputSize, codec.IdealSize);
double[] input = new double[this.codec.InputSize];
double[] ideal = new double[this.codec.IdealSize];
this.codec.PrepareRead();
int index = 3;
int currentRecord = 0;
int lastUpdate = 0;
while (codec.Read(input, ideal))
{
egb.Write(input);
egb.Write(ideal);
index += input.Length;
index += ideal.Length;
currentRecord++;
lastUpdate++;
if (lastUpdate >= 10000)
{
lastUpdate = 0;
this.Status.Report(0, currentRecord, "Importing...");
}
}
egb.Close();
this.codec.Close();
Status.Report(0, 0, "Done importing to binary file: "
+ binaryFile);
}
/// <summary>
/// Convert an Encog binary file to an external form, such as CSV.
/// </summary>
/// <param name="binaryFile">THe binary file to use.</param>
public void Binary2External(String binaryFile)
{
Status.Report(0, 0, "Exporting binary file: " + binaryFile);
EncogEGBFile egb = new EncogEGBFile(binaryFile);
egb.Open();
this.codec.PrepareWrite(egb.NumberOfRecords, egb.InputCount,
egb.IdealCount);
int inputCount = egb.InputCount;
int idealCount = egb.IdealCount;
double[] input = new double[inputCount];
double[] ideal = new double[idealCount];
int currentRecord = 0;
int lastUpdate = 0;
// now load the data
for (int i = 0; i < egb.NumberOfRecords; i++)
{
for (int j = 0; j < inputCount; j++)
{
input[j] = egb.Read();
}
for (int j = 0; j < idealCount; j++)
{
ideal[j] = egb.Read();
}
this.codec.Write(input, ideal);
currentRecord++;
lastUpdate++;
if (lastUpdate >= 10000)
{
lastUpdate = 0;
this.Status.Report(egb.NumberOfRecords, currentRecord,
"Exporting...");
}
}
egb.Close();
this.codec.Close();
Status.Report(0, 0, "Done exporting binary file: "
+ binaryFile);
}
/// <summary>
/// Close the dataset.
/// </summary>
public void Close()
{
Object[] obj = this.additional.ToArray();
for (int i = 0; i < obj.Length; i++)
{
BufferedNeuralDataSet set = (BufferedNeuralDataSet)obj[i];
set.Close();
}
this.additional.Clear();
if (this.owner != null)
{
this.owner.RemoveAdditional(this);
}
this.egb.Close();
this.egb = null;
}
/// <summary>
/// Construct a buffered dataset using the specified file.
/// </summary>
/// <param name="binaryFile">The file to read/write binary data to/from.</param>
public BufferedNeuralDataSet(String binaryFile)
{
this.file = binaryFile;
this.egb = new EncogEGBFile(binaryFile);
if (File.Exists(this.file))
{
this.egb.Open();
}
}
