public void TestSampleSegregate()
{
DataNormalization norm = CreateSampleSegregate();
norm.Process();
Check(norm, 6);
}
public void TestAbsolute()
{
DataNormalization norm = Create();
norm.Process();
Check(norm);
}
public void TestIndexSegregate()
{
DataNormalization norm = CreateIndexSegregate();
norm.Process();
Check(norm, 6);
}
public void TestIntegerBalance()
{
DataNormalization norm = CreateIntegerBalance();
norm.Process();
Check(norm, 3);
}
private void Generate()
{
IInputField a;
IInputField b;
IInputField c;
IInputField d;
IInputField e;
var norm = new DataNormalization();
norm.Report = new NullStatusReportable();
norm.Storage = new NormalizationStorageCSV(FILENAME.ToString());
norm.AddInputField(a = new InputFieldArray2D(false, ARRAY_2D, 0));
norm.AddInputField(b = new InputFieldArray2D(false, ARRAY_2D, 1));
norm.AddInputField(c = new InputFieldArray2D(false, ARRAY_2D, 2));
norm.AddInputField(d = new InputFieldArray2D(false, ARRAY_2D, 3));
norm.AddInputField(e = new InputFieldArray2D(false, ARRAY_2D, 4));
norm.AddOutputField(new OutputFieldDirect(a));
norm.AddOutputField(new OutputFieldDirect(b));
norm.AddOutputField(new OutputFieldDirect(c));
norm.AddOutputField(new OutputFieldDirect(d));
norm.AddOutputField(new OutputFieldDirect(e));
norm.Storage = new NormalizationStorageCSV(FILENAME.ToString());
norm.Process();
}
public void TestRangeSegregate()
{
DataNormalization norm = CreateRangeSegregate();
norm.Process();
Check(norm, 1);
}
public void TestOutputFieldEncode()
{
double[][] arrayOutput = EngineArray.AllocateDouble2D(2, 2);
DataNormalization norm = Create(arrayOutput);
norm.Process();
Check(arrayOutput);
}
public void TestAbsoluteSerial()
{
DataNormalization norm = Create();
norm = (DataNormalization)SerializeRoundTrip.RoundTrip(norm);
norm.Process();
Check(norm);
}
public void TestArray2D()
{
double[][] arrayOutput = EngineArray.AllocateDouble2D(2, 2);
DataNormalization norm = Create2D(arrayOutput);
norm.Process();
Check2D(arrayOutput);
}
public void TestArray1D()
{
var arrayOutput = new double[5];
DataNormalization norm = Create1D(arrayOutput);
norm.Process();
Check1D(arrayOutput);
}
public void TestGenerateAndLoad()
{
double[][] outputArray = EngineArray.AllocateDouble2D(2, 5);
Generate();
DataNormalization norm = Create(outputArray);
norm.Process();
Check(norm);
}
public void TestOutputFieldEncodeSerialize()
{
double[][] arrayOutput = EngineArray.AllocateDouble2D(2, 2);
DataNormalization norm = Create(arrayOutput);
norm = (DataNormalization)SerializeRoundTrip.RoundTrip(norm);
arrayOutput = ((NormalizationStorageArray2D)norm.Storage).GetArray();
norm.Process();
Check(arrayOutput);
}
public void TestGenerateAndLoadSerial()
{
double[][] outputArray = EngineArray.AllocateDouble2D(2, 5);
Generate(FILENAME2.ToString());
DataNormalization norm = Create(FILENAME2.ToString(), outputArray);
norm = (DataNormalization)SerializeRoundTrip.RoundTrip(norm);
norm.Process();
Check(norm);
}
public void TestGenerateAndLoad()
{
var outputArray = EngineArray.AllocateDouble2D(2, 5);
Generate(FILENAME1.ToString());
DataNormalization norm = Create(FILENAME1.ToString(), outputArray);
norm.Process();
Check(norm);
}
public void TestArray2DSerial()
{
var arrayOutput = EngineArray.AllocateDouble2D(2, 2);
DataNormalization norm = Create2D(arrayOutput);
norm = (DataNormalization)SerializeRoundTrip.RoundTrip(norm);
arrayOutput = ((NormalizationStorageArray2D)norm.Storage).GetArray();
norm.Process();
Check2D(arrayOutput);
}
public void TestArray1DSerial()
{
var arrayOutput = new double[5];
DataNormalization norm = Create1D(arrayOutput);
norm = (DataNormalization)SerializeRoundTrip.RoundTrip(norm);
arrayOutput = ((NormalizationStorageArray1D)norm.Storage).GetArray();
norm.Process();
Check1D(arrayOutput);
}
public void TestAbsolute()
{
double[][] arrayOutput = EngineArray.AllocateDouble2D(2, 3);
DataNormalization norm = Create(arrayOutput);
norm.Process();
for (int i = 0; i < arrayOutput[0].Length; i++)
{
Assert.AreEqual(arrayOutput[0][i], arrayOutput[1][i], 0.01);
}
}
public void TestAbsoluteSerial()
{
double[][] arrayOutput = EngineArray.AllocateDouble2D(2, 3);
DataNormalization norm = Create(arrayOutput);
norm = (DataNormalization)SerializeRoundTrip.RoundTrip(norm);
arrayOutput = ((NormalizationStorageArray2D)norm.Storage).GetArray();
norm.Process();
for (int i = 0; i < arrayOutput[0].Length; i++)
{
Assert.AreEqual(arrayOutput[0][i], arrayOutput[1][i], 0.01);
}
}
public void Copy(FileInfo source, FileInfo target, int start, int stop, int size)
{
var inputField = new IInputField[55];
var norm = new DataNormalization {Report = this, Storage = new NormalizationStorageCSV(target.ToString())};
for (int i = 0; i < 55; i++)
{
inputField[i] = new InputFieldCSV(true, source.ToString(), i);
norm.AddInputField(inputField[i]);
IOutputField outputField = new OutputFieldDirect(inputField[i]);
norm.AddOutputField(outputField);
}
// load only the part we actually want, i.e. training or eval
var segregator2 = new IndexSampleSegregator(start, stop, size);
norm.AddSegregator(segregator2);
norm.Process();
}
private void Generate()
{
IInputField a;
IInputField b;
IInputField c;
IInputField d;
IInputField e;
var norm = new DataNormalization();
norm.Report = new NullStatusReportable();
norm.Storage = new NormalizationStorageCSV(FILENAME.ToString());
norm.AddInputField(a = new InputFieldArray2D(false, ARRAY_2D, 0));
norm.AddInputField(b = new InputFieldArray2D(false, ARRAY_2D, 1));
norm.AddInputField(c = new InputFieldArray2D(false, ARRAY_2D, 2));
norm.AddInputField(d = new InputFieldArray2D(false, ARRAY_2D, 3));
norm.AddInputField(e = new InputFieldArray2D(false, ARRAY_2D, 4));
norm.AddOutputField(new OutputFieldDirect(a));
norm.AddOutputField(new OutputFieldDirect(b));
norm.AddOutputField(new OutputFieldDirect(c));
norm.AddOutputField(new OutputFieldDirect(d));
norm.AddOutputField(new OutputFieldDirect(e));
norm.Storage = new NormalizationStorageCSV(FILENAME.ToString());
norm.Process();
}
public void Narrow(FileInfo source, FileInfo target, int field, int count)
{
var inputField = new IInputField[55];
var norm = new DataNormalization {Report = this, Storage = new NormalizationStorageCSV(target.ToString())};
for (int i = 0; i < 55; i++)
{
inputField[i] = new InputFieldCSV(true, source.ToString(), i);
norm.AddInputField(inputField[i]);
IOutputField outputField = new OutputFieldDirect(inputField[i]);
norm.AddOutputField(outputField);
}
var segregator = new IntegerBalanceSegregator(inputField[field], count);
norm.AddSegregator(segregator);
norm.Process();
Console.WriteLine(@"Samples per tree type:");
Console.WriteLine(segregator.DumpCounts());
}
public DataNormalization Step3(bool useOneOf)
{
Console.WriteLine(@"Step 3: Normalize training data");
IInputField inputElevation;
IInputField inputAspect;
IInputField inputSlope;
IInputField hWater;
IInputField vWater;
IInputField roadway;
IInputField shade9;
IInputField shade12;
IInputField shade3;
IInputField firepoint;
var wilderness = new IInputField[4];
var soilType = new IInputField[40];
IInputField coverType;
var norm = new DataNormalization
{
Report = this,
Storage = new NormalizationStorageCSV(_config.NormalizedDataFile.ToString())
};
norm.AddInputField(inputElevation = new InputFieldCSV(true, _config.BalanceFile.ToString(), 0));
norm.AddInputField(inputAspect = new InputFieldCSV(true, _config.BalanceFile.ToString(), 1));
norm.AddInputField(inputSlope = new InputFieldCSV(true, _config.BalanceFile.ToString(), 2));
norm.AddInputField(hWater = new InputFieldCSV(true, _config.BalanceFile.ToString(), 3));
norm.AddInputField(vWater = new InputFieldCSV(true, _config.BalanceFile.ToString(), 4));
norm.AddInputField(roadway = new InputFieldCSV(true, _config.BalanceFile.ToString(), 5));
norm.AddInputField(shade9 = new InputFieldCSV(true, _config.BalanceFile.ToString(), 6));
norm.AddInputField(shade12 = new InputFieldCSV(true, _config.BalanceFile.ToString(), 7));
norm.AddInputField(shade3 = new InputFieldCSV(true, _config.BalanceFile.ToString(), 8));
norm.AddInputField(firepoint = new InputFieldCSV(true, _config.BalanceFile.ToString(), 9));
for (int i = 0; i < 4; i++)
{
norm.AddInputField(wilderness[i] = new InputFieldCSV(true, _config.BalanceFile.ToString(), 10 + i));
}
for (int i = 0; i < 40; i++)
{
norm.AddInputField(soilType[i] = new InputFieldCSV(true, _config.BalanceFile.ToString(), 14 + i));
}
norm.AddInputField(coverType = new InputFieldCSV(false, _config.BalanceFile.ToString(), 54));
norm.AddOutputField(new OutputFieldRangeMapped(inputElevation));
norm.AddOutputField(new OutputFieldRangeMapped(inputAspect));
norm.AddOutputField(new OutputFieldRangeMapped(inputSlope));
norm.AddOutputField(new OutputFieldRangeMapped(hWater));
norm.AddOutputField(new OutputFieldRangeMapped(vWater));
norm.AddOutputField(new OutputFieldRangeMapped(roadway));
norm.AddOutputField(new OutputFieldRangeMapped(shade9));
norm.AddOutputField(new OutputFieldRangeMapped(shade12));
norm.AddOutputField(new OutputFieldRangeMapped(shade3));
norm.AddOutputField(new OutputFieldRangeMapped(firepoint));
for (int i = 0; i < 40; i++)
{
norm.AddOutputField(new OutputFieldDirect(soilType[i]));
}
if (useOneOf)
BuildOutputOneOf(norm, coverType);
else
BuildOutputEquilateral(norm, coverType);
norm.Process();
return norm;
}