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; }