/// <summary>
/// Close the dataset.
/// </summary>
public void Close()
{
Object[] obj = _additional.ToArray();
foreach (var set in obj.Cast <BufferedMLDataSet>())
{
set.Close();
}
_additional.Clear();
if (_owner != null)
{
_owner.RemoveAdditional(this);
}
_egb.Close();
_egb = null;
}
/// <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);
var egb = new EncogEGBFile(binaryFile);
egb.Open();
_codec.PrepareWrite(egb.NumberOfRecords, egb.InputCount,
egb.IdealCount);
int inputCount = egb.InputCount;
int idealCount = egb.IdealCount;
var input = new double[inputCount];
var 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();
}
double significance = egb.Read();
_codec.Write(input, ideal, significance);
currentRecord++;
lastUpdate++;
if (lastUpdate >= 10000)
{
lastUpdate = 0;
Status.Report(egb.NumberOfRecords, currentRecord,
"Exporting...");
}
}
egb.Close();
_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);
var egb = new EncogEGBFile(binaryFile);
egb.Create(_codec.InputSize, _codec.IdealSize);
var input = new double[_codec.InputSize];
var ideal = new double[_codec.IdealSize];
_codec.PrepareRead();
int currentRecord = 0;
int lastUpdate = 0;
double significance = 0;
while (_codec.Read(input, ideal, ref significance))
{
egb.Write(input);
egb.Write(ideal);
currentRecord++;
lastUpdate++;
if (lastUpdate >= 10000)
{
lastUpdate = 0;
Status.Report(0, currentRecord, "Importing...");
}
egb.Write(significance);
}
egb.Close();
_codec.Close();
Status.Report(0, 0, "Done importing to binary file: "
+ binaryFile);
}
/// <inheritdoc />
public override sealed bool ExecuteCommand(String args)
{
// get filenames
String trainingID = Prop.GetPropertyString(
ScriptProperties.MlConfigTrainingFile);
String resourceID = Prop.GetPropertyString(
ScriptProperties.MlConfigMachineLearningFile);
FileInfo trainingFile = Script.ResolveFilename(trainingID);
FileInfo resourceFile = Script.ResolveFilename(resourceID);
String type = Prop.GetPropertyString(
ScriptProperties.MlConfigType);
String arch = Prop.GetPropertyString(
ScriptProperties.MlConfigArchitecture);
EncogLogging.Log(EncogLogging.LevelDebug, "Beginning create");
EncogLogging.Log(EncogLogging.LevelDebug, "training file:"
+ trainingID);
EncogLogging.Log(EncogLogging.LevelDebug, "resource file:"
+ resourceID);
EncogLogging.Log(EncogLogging.LevelDebug, "type:" + type);
EncogLogging.Log(EncogLogging.LevelDebug, "arch:" + arch);
var egb = new EncogEGBFile(trainingFile.ToString());
egb.Open();
int input = egb.InputCount;
int ideal = egb.IdealCount;
egb.Close();
var factory = new MLMethodFactory();
IMLMethod obj = factory.Create(type, arch, input, ideal);
if (obj is BayesianNetwork)
{
string query = Prop.GetPropertyString(ScriptProperties.MLConfigQuery);
((BayesianNetwork) obj).DefineClassificationStructure(query);
}
EncogDirectoryPersistence.SaveObject(resourceFile, obj);
return false;
}
/// <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);
var egb = new EncogEGBFile(binaryFile);
egb.Create(_codec.InputSize, _codec.IdealSize);
var input = new double[_codec.InputSize];
var ideal = new double[_codec.IdealSize];
_codec.PrepareRead();
int currentRecord = 0;
int lastUpdate = 0;
double significance = 0;
while (_codec.Read(input, ideal, ref significance))
{
egb.Write(input);
egb.Write(ideal);
currentRecord++;
lastUpdate++;
if (lastUpdate >= 10000)
{
lastUpdate = 0;
Status.Report(0, currentRecord, "Importing...");
}
egb.Write(significance);
}
egb.Close();
_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);
var egb = new EncogEGBFile(binaryFile);
egb.Open();
_codec.PrepareWrite(egb.NumberOfRecords, egb.InputCount,
egb.IdealCount);
int inputCount = egb.InputCount;
int idealCount = egb.IdealCount;
var input = new double[inputCount];
var 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();
}
double significance = egb.Read();
_codec.Write(input, ideal, significance);
currentRecord++;
lastUpdate++;
if (lastUpdate >= 10000)
{
lastUpdate = 0;
Status.Report(egb.NumberOfRecords, currentRecord,
"Exporting...");
}
}
egb.Close();
_codec.Close();
Status.Report(0, 0, "Done exporting binary file: "
+ binaryFile);
}
