static void SaveModel(NetworkModel model, OxyPlot.Series.LineSeries series = null)
{
Console.WriteLine("\nSaving model...");
if (series != null)
{
try
{
var graphPoints = new List <Vector <double> >();
foreach (var point in series.Points)
{
graphPoints.Add(Vector <double> .Build.Dense(new double[] { point.Y }));
}
DelimitedWriter.Write(model.Path("graph"), Matrix <double> .Build.DenseOfRowVectors(graphPoints));
Console.WriteLine("Saved graph data");
}
catch
{
Console.WriteLine("Unable to save graph data");
}
}
model.Save();
Console.WriteLine("Model has been saved.");
}
static void Main(string[] args)
{
var data = Matrix <double> .Build.Random(2, 2);
DelimitedWriter.Write("123", data);
MatlabWriter.Write("123", Matrix <double> .Build.Random(2, 2), "a");
}
/// <summary>
/// Save currently loaded model.
/// </summary>
public override void Save()
{
Directory.CreateDirectory(Path("layers"));
int count = 0;
foreach (var layer in layers)
{
var state = Matrix <double> .Build.Dense(layer.Size, layer.InputCount + 1, (row, column) =>
{
if (column == 0)
{
// First column is neuron bias.
return(layer.Neurons[row].Bias);
}
else
{
// Everything else is weights.
return(layer.Neurons[row].Weights.At(column - 1));
}
});
DelimitedWriter.Write(Path(String.Format("layers/{0}", count)), state);
count++;
}
}
public void Save(string folderPath)
{
string layerPath = folderPath + "\\" + Name;
Directory.CreateDirectory(layerPath);
if (Activations != null)
{
Matrix <double> a = DenseMatrix.Build.DenseOfRowVectors(Activations);
var activationsFilePath = String.Format("{0}\\Activations.csv", layerPath);
DelimitedWriter.Write(activationsFilePath, a, ",");
}
if (Biases != null)
{
Matrix <double> bm = DenseMatrix.Build.DenseOfRowVectors(Biases);
var biasesFilePath = String.Format("{0}\\Biases.csv", layerPath);
DelimitedWriter.Write(biasesFilePath, bm, ",");
}
if (Weights != null)
{
var weightsFilePath = String.Format("{0}\\Weights.csv", layerPath);
DelimitedWriter.Write(weightsFilePath, Weights, ",");
}
}
private void OnShipFinished(float score, int index)
{
finishedShips++;
finishedBatchShips++;
scores[index] = score;
if (finishedBatchShips >= shipsPerBatch)
{
EndBatch();
currentBatch++;
if (currentBatch >= batches)
{
currentGeneration++;
chart.AddGenerationData(currentGeneration, GetMaxScore(), GetAvgScore());
if (currentGeneration < generations)
{
NewGeneration();
}
else
{
DelimitedWriter.Write(Application.dataPath + "/trained.csv", Evolution.GetFittestChromosome(chromosomes, scores).ToColumnMatrix(), ",", null, null, System.Globalization.CultureInfo.InvariantCulture.NumberFormat);
SceneManager.LoadScene("Playing");
}
}
else
{
StartBatch();
}
}
}
public void savematrix(ref Matrix <float> stored, int casenum)
{
switch (casenum)
{
case 0: DelimitedWriter.Write("Kmatrix.csv", stored, ","); break;
case 1: DelimitedWriter.Write("Mmatrix.csv", stored, ","); break;
case 2: DelimitedWriter.Write("Gmatrix.csv", stored, ","); break;
case 3: DelimitedWriter.Write("Dmatrix.csv", stored, ","); break;
}
}
void TrainingFinished()
{
Time.timeScale = 1.0f;
Debug.Log(Y);
nn.train(X, Y);
DelimitedWriter.Write <double>("X.csv", X, ",");
DelimitedWriter.Write <double>("Y.csv", Y, ",");
DelimitedWriter.Write <double>("predict.csv", nn.predict(X), ",");
training = false;
Debug.Log("TrainingFinished");
state = State.Idle;
}
static void Main(string[] args)
{
Utils.SetNumberDecimalSeparatorToDotInCultureSettings();
var x_data = DelimitedReader.Read <double>(Path.Combine(Utils.GetAssemblyPath(), "..\\..\\TestData\\x_data.txt"));
var y_data = DelimitedReader.Read <double>(Path.Combine(Utils.GetAssemblyPath(), "..\\..\\TestData\\y_data.txt"));
NeuralNetwork.CostFunctionWithThetaParameter backProp =
tt =>
{
var backPropagationResult = NeuralNetwork.BackPropagation(x_data, y_data, tt, new List <int>()
{
25
}, 10, 0);
return(backPropagationResult);
};
var thetas = NeuralNetwork.RandomInitialiseWeights(400, 10, new List <int>()
{
25
});
var theta = NeuralNetwork.PackThetas(thetas);
var resultGradientDescent = NeuralNetwork.GradientDescent(backProp, theta, 1, 300);
DelimitedWriter.Write("..\\..\\TestData\\ThetaGradient.txt", resultGradientDescent.Item1, "thetaGradient");
DelimitedWriter.Write("..\\..\\TestData\\JHistory.txt", resultGradientDescent.Item2, "JHistory");
var resultTheta = resultGradientDescent.Item1;
//var resultComputeNumericalGradient = NeuralNetwork.ComputeNumericalGradient(backProp, resultTheta);
//resultComputeNumericalGradient.Save("D:/test/numericalGradients.txt");
var result5 = NeuralNetwork.BackPropagation(x_data, y_data, resultTheta, new List <int>(25), 10, 0);
var JJ = result5.Item1;
DelimitedWriter.Write("..\\..\\TestData\\GradientForBackPropagation.txt", result5.Item2, "gradBackPropagation");
var resultThetaLoadedFromFile = (DenseMatrix)DelimitedReader.Read <double>("..\\..\\TestData\\thetaGradient.txt");
var thetasList = NeuralNetwork.UnpackThetas(resultThetaLoadedFromFile, 400, new List <int>()
{
25
}, 10);
var result = NeuralNetwork.GetPredictions(x_data, y_data, thetasList);
Console.WriteLine(result.Item1);
DelimitedWriter.Write("..\\..\\TestData\\Predictions.txt", result.Item2, "");
}
public void CanWriteCommaDelimitedData()
{
var matrix = new DenseMatrix(new[,] { { 1.1f, 2.2f, 3.3f }, { 4.4f, 5.5f, 6.6f }, { 7.7f, 8.8f, 9.9f } });
var writer = new DelimitedWriter(',');
var stream = new MemoryStream();
writer.WriteMatrix(matrix, stream);
var data = stream.ToArray();
var reader = new StreamReader(new MemoryStream(data));
var text = reader.ReadToEnd();
const string expected = @"1.1,2.2,3.3
4.4,5.5,6.6
7.7,8.8,9.9";
Assert.AreEqual(expected, text);
}
public void CanWriteSpaceDelimitedData()
{
var matrix = new SparseMatrix(new[,] { { 1.1, 0, 0 }, { 0, 5.5, 0 }, { 0, 0, 9.9 } });
var writer = new DelimitedWriter(' ');
var stream = new MemoryStream();
writer.WriteMatrix(matrix, stream);
var data = stream.ToArray();
var reader = new StreamReader(new MemoryStream(data));
var text = reader.ReadToEnd();
const string expected = @"1.1 0 0
0 5.5 0
0 0 9.9";
Assert.AreEqual(expected, text);
}
public void CanWriteCommaDelimitedData()
{
var matrix = new DenseMatrix(new[,] { { 1.1, 2.2, 3.3 }, { 4.4, 5.5, 6.6 }, { 7.7, 8.8, 9.9 } });
var writer = new DelimitedWriter(',');
var stream = new MemoryStream();
writer.WriteMatrix(matrix, stream);
var data = stream.ToArray();
var reader = new StreamReader(new MemoryStream(data));
var text = reader.ReadToEnd();
var expected = @"1.1,2.2,3.3" + Environment.NewLine
+ "4.4,5.5,6.6" + Environment.NewLine
+ "7.7,8.8,9.9";
Assert.AreEqual(expected, text);
}
public void CanWriteCommaDelimitedData()
{
var matrix = new DenseMatrix(new[,] { { new Complex(1.1, 1.1), new Complex(2.2, 2.2), new Complex(3.3, 3.3) }, { new Complex(4.4, 4.4), new Complex(5.5, 5.5), new Complex(6.6, 6.6) }, { new Complex(7.7, 7.7), new Complex(8.8, 8.8), new Complex(9.9, 9.9) } });
var writer = new DelimitedWriter(',');
var stream = new MemoryStream();
writer.WriteMatrix(matrix, stream);
var data = stream.ToArray();
var reader = new StreamReader(new MemoryStream(data));
var text = reader.ReadToEnd();
var expected = "(1.1, 1.1),(2.2, 2.2),(3.3, 3.3)" + Environment.NewLine
+ "(4.4, 4.4),(5.5, 5.5),(6.6, 6.6)" + Environment.NewLine
+ "(7.7, 7.7),(8.8, 8.8),(9.9, 9.9)";
Assert.AreEqual(expected, text);
}
/// <summary>
/// Save currently loaded model.
/// </summary>
override public void Save()
{
var state = Vector <double> .Build.Dense(perceptron.Weights.Count + 1, (index) =>
{
if (index == 0)
{
return(perceptron.Bias);
}
else
{
return(perceptron.Weights.At(index - 1));
}
});
DelimitedWriter.Write <double>(Path(Config.State), state.ToRowMatrix());
}
public void CanWriteTabDelimitedDataWithMissingValues()
{
var matrix = DenseMatrix.OfArray(new[, ] {
{ 1.1, double.NaN, 0 }, { 0, 5.5, 0 }, { double.NaN, double.NaN, 9.9 }
});
var stream = new MemoryStream();
DelimitedWriter.Write(stream, matrix, "\t", missingValue: double.NaN);
var data = stream.ToArray();
var reader = new StreamReader(new MemoryStream(data));
var text = reader.ReadToEnd();
var expected = "1.1\t\t0" + Environment.NewLine
+ "0\t5.5\t0" + Environment.NewLine
+ "\t\t9.9";
Assert.AreEqual(expected, text);
}
public void CanWriteCommaDelimitedDataWithMissingValues()
{
var matrix = SparseMatrix.OfArray(new[, ] {
{ 1.1, 0, 0 }, { 0, 5.5, 0 }, { 0, 0, 9.9 }
});
var stream = new MemoryStream();
DelimitedWriter.Write(stream, matrix, ",", missingValue: 0);
var data = stream.ToArray();
var reader = new StreamReader(new MemoryStream(data));
var text = reader.ReadToEnd();
var expected = @"1.1,," + Environment.NewLine
+ ",5.5," + Environment.NewLine
+ ",,9.9";
Assert.AreEqual(expected, text);
}
public void CanWriteSpaceDelimitedData()
{
var matrix = SparseMatrix.OfArray(new[, ] {
{ 1.1, 0, 0 }, { 0, 5.5, 0 }, { 0, 0, 9.9 }
});
var stream = new MemoryStream();
DelimitedWriter.Write(stream, matrix, " ");
var data = stream.ToArray();
var reader = new StreamReader(new MemoryStream(data));
var text = reader.ReadToEnd();
var expected = @"1.1 0 0" + Environment.NewLine
+ "0 5.5 0" + Environment.NewLine
+ "0 0 9.9";
Assert.AreEqual(expected, text);
}
public void CanWritePeriodDelimitedData()
{
var matrix = DenseMatrix.OfArray(new[, ] {
{ 1.1, 2.2, 3.3 }, { 4.4, 5.5, 6.6 }, { 7.7, 8.8, 9.9 }
});
var stream = new MemoryStream();
DelimitedWriter.Write(stream, matrix, delimiter: ".", formatProvider: new CultureInfo("tr-TR"));
var data = stream.ToArray();
var reader = new StreamReader(new MemoryStream(data));
var text = reader.ReadToEnd();
var expected = @"1,1.2,2.3,3" + Environment.NewLine
+ "4,4.5,5.6,6" + Environment.NewLine
+ "7,7.8,8.9,9";
Assert.AreEqual(expected, text);
}
public void CanWriteCommaDelimitedData()
{
var matrix = DenseMatrix.OfArray(new[,] {{new Complex32(1.1f, 1.1f), new Complex32(2.2f, 2.2f), new Complex32(3.3f, 3.3f)}, {new Complex32(4.4f, 4.4f), new Complex32(5.5f, 5.5f), new Complex32(6.6f, 6.6f)}, {new Complex32(7.7f, 7.7f), new Complex32(8.8f, 8.8f), new Complex32(9.9f, 9.9f)}});
var writer = new DelimitedWriter(',')
{
CultureInfo = CultureInfo.InvariantCulture
};
var stream = new MemoryStream();
writer.WriteMatrix(matrix, stream);
var data = stream.ToArray();
var reader = new StreamReader(new MemoryStream(data));
var text = reader.ReadToEnd();
var expected = "(1.1, 1.1),(2.2, 2.2),(3.3, 3.3)" + Environment.NewLine
+ "(4.4, 4.4),(5.5, 5.5),(6.6, 6.6)" + Environment.NewLine
+ "(7.7, 7.7),(8.8, 8.8),(9.9, 9.9)";
Assert.AreEqual(expected, text);
}
public void CanWriteCommaDelimitedData()
{
var matrix = DenseMatrix.OfArray(new[,] {{1.1f, 2.2f, 3.3f}, {4.4f, 5.5f, 6.6f}, {7.7f, 8.8f, 9.9f}});
var writer = new DelimitedWriter(',')
{
CultureInfo = CultureInfo.InvariantCulture
};
var stream = new MemoryStream();
writer.WriteMatrix(matrix, stream);
var data = stream.ToArray();
var reader = new StreamReader(new MemoryStream(data));
var text = reader.ReadToEnd();
var expected = @"1.1,2.2,3.3" + Environment.NewLine
+ "4.4,5.5,6.6" + Environment.NewLine
+ "7.7,8.8,9.9";
Assert.AreEqual(expected, text);
}
public void CanWriteCommaDelimitedDoubleData()
{
var matrix = DenseMatrix.OfArray(new[, ] {
{ 1.1, 2.2, 3.3 }, { 4.4, 5.5, 6.6 }, { 7.7, 8.8, 9.9 }
});
var stream = new MemoryStream();
DelimitedWriter.Write(stream, matrix, ",", formatProvider: CultureInfo.InvariantCulture);
var data = stream.ToArray();
var reader = new StreamReader(new MemoryStream(data));
var text = reader.ReadToEnd();
var expected = @"1.1,2.2,3.3" + Environment.NewLine
+ "4.4,5.5,6.6" + Environment.NewLine
+ "7.7,8.8,9.9";
Assert.AreEqual(expected, text);
}
public void CanWriteCommaDelimitedData()
{
var matrix = new DenseMatrix(new[, ] {
{ new Complex(1.1, 1.1), new Complex(2.2, 2.2), new Complex(3.3, 3.3) }, { new Complex(4.4, 4.4), new Complex(5.5, 5.5), new Complex(6.6, 6.6) }, { new Complex(7.7, 7.7), new Complex(8.8, 8.8), new Complex(9.9, 9.9) }
});
var writer = new DelimitedWriter(',');
var stream = new MemoryStream();
writer.WriteMatrix(matrix, stream);
var data = stream.ToArray();
var reader = new StreamReader(new MemoryStream(data));
var text = reader.ReadToEnd();
var expected = "(1.1, 1.1),(2.2, 2.2),(3.3, 3.3)" + Environment.NewLine
+ "(4.4, 4.4),(5.5, 5.5),(6.6, 6.6)" + Environment.NewLine
+ "(7.7, 7.7),(8.8, 8.8),(9.9, 9.9)";
Assert.AreEqual(expected, text);
}
public void CanWritePeriodDelimitedData()
{
var matrix = new DenseMatrix(new[,] { { 1.1, 2.2, 3.3 }, { 4.4, 5.5, 6.6 }, { 7.7, 8.8, 9.9 } });
var culture = new CultureInfo("tr-TR");
var writer = new DelimitedWriter('.')
{
CultureInfo = culture
};
var stream = new MemoryStream();
writer.WriteMatrix(matrix, stream);
var data = stream.ToArray();
var reader = new StreamReader(new MemoryStream(data));
var text = reader.ReadToEnd();
const string expected = @"1,1.2,2.3,3
4,4.5,5.6,6
7,7.8,8.9,9";
Assert.AreEqual(expected, text);
}
public void Writer_ExistingFile()
{
using (var writer = new DelimitedWriter(TestExistingOutputFile, true))
{
writer.Write("testing 1-1", "testing 1-2");
writer.Write("testing 2-1", "testing 2-2", "testing 2-3");
}
var expected = "Testing\tcontent\r\ntesting 1-1\ttesting 1-2\r\ntesting 2-1\ttesting 2-2\ttesting 2-3\r\n";
string output;
using (var outFile = File.OpenText(TestExistingOutputFile))
{
output = outFile.ReadToEnd();
}
Assert.That(expected, Is.EqualTo(output));
}
public void CanWritePeriodDelimitedData()
{
var matrix = DenseMatrix.OfArray(new[,] {{new Complex32(1.1f, 1.1f), new Complex32(2.2f, 2.2f), new Complex32(3.3f, 3.3f)}, {new Complex32(4.4f, 4.4f), new Complex32(5.5f, 5.5f), new Complex32(6.6f, 6.6f)}, {new Complex32(7.7f, 7.7f), new Complex32(8.8f, 8.8f), new Complex32(9.9f, 9.9f)}});
var culture = new CultureInfo("tr-TR");
var writer = new DelimitedWriter('.')
{
CultureInfo = culture
};
var stream = new MemoryStream();
writer.WriteMatrix(matrix, stream);
var data = stream.ToArray();
var reader = new StreamReader(new MemoryStream(data));
var text = reader.ReadToEnd();
var expected = "(1,1, 1,1).(2,2, 2,2).(3,3, 3,3)" + Environment.NewLine
+ "(4,4, 4,4).(5,5, 5,5).(6,6, 6,6)" + Environment.NewLine
+ "(7,7, 7,7).(8,8, 8,8).(9,9, 9,9)";
Assert.AreEqual(expected, text);
}
public void CanWriteSpaceDelimitedData()
{
var matrix = new DenseMatrix(new[, ] {
{ new Complex32(1.1f, 1.1f), new Complex32(2.2f, 2.2f), new Complex32(3.3f, 3.3f) }, { new Complex32(4.4f, 4.4f), new Complex32(5.5f, 5.5f), new Complex32(6.6f, 6.6f) }, { new Complex32(7.7f, 7.7f), new Complex32(8.8f, 8.8f), new Complex32(9.9f, 9.9f) }
});
var writer = new DelimitedWriter(' ');
var stream = new MemoryStream();
writer.WriteMatrix(matrix, stream);
var data = stream.ToArray();
var reader = new StreamReader(new MemoryStream(data));
var text = reader.ReadToEnd();
var expected = "(1.1, 1.1) (2.2, 2.2) (3.3, 3.3)" + Environment.NewLine
+ "(4.4, 4.4) (5.5, 5.5) (6.6, 6.6)" + Environment.NewLine
+ "(7.7, 7.7) (8.8, 8.8) (9.9, 9.9)";
Assert.AreEqual(expected, text);
}
public void CanWritePeriodDelimitedData()
{
var matrix = new DenseMatrix(new[,] { { 1.1f, 2.2f, 3.3f }, { 4.4f, 5.5f, 6.6f }, { 7.7f, 8.8f, 9.9f } });
var culture = new CultureInfo("tr-TR");
var writer = new DelimitedWriter('.')
{
CultureInfo = culture
};
var stream = new MemoryStream();
writer.WriteMatrix(matrix, stream);
var data = stream.ToArray();
var reader = new StreamReader(new MemoryStream(data));
var text = reader.ReadToEnd();
var expected = @"1,1.2,2.3,3" + Environment.NewLine
+ "4,4.5,5.6,6" + Environment.NewLine
+ "7,7.8,8.9,9";
Assert.AreEqual(expected, text);
}
public void CanWritePeriodDelimitedData()
{
var matrix = new DenseMatrix(new[,] { { new Complex(1.1, 1.1), new Complex(2.2, 2.2), new Complex(3.3, 3.3) }, { new Complex(4.4, 4.4), new Complex(5.5, 5.5), new Complex(6.6, 6.6) }, { new Complex(7.7, 7.7), new Complex(8.8, 8.8), new Complex(9.9, 9.9) } });
var culture = new CultureInfo("tr-TR");
var writer = new DelimitedWriter('.')
{
CultureInfo = culture
};
var stream = new MemoryStream();
writer.WriteMatrix(matrix, stream);
var data = stream.ToArray();
var reader = new StreamReader(new MemoryStream(data));
var text = reader.ReadToEnd();
var expected = "(1,1, 1,1).(2,2, 2,2).(3,3, 3,3)" + Environment.NewLine
+ "(4,4, 4,4).(5,5, 5,5).(6,6, 6,6)" + Environment.NewLine
+ "(7,7, 7,7).(8,8, 8,8).(9,9, 9,9)";
Assert.AreEqual(expected, text);
}
public void CanWriteCommaDelimitedData()
{
var matrix = new DenseMatrix(new[, ] {
{ 1.1f, 2.2f, 3.3f }, { 4.4f, 5.5f, 6.6f }, { 7.7f, 8.8f, 9.9f }
});
var writer = new DelimitedWriter(',');
var stream = new MemoryStream();
writer.WriteMatrix(matrix, stream);
var data = stream.ToArray();
var reader = new StreamReader(new MemoryStream(data));
var text = reader.ReadToEnd();
var expected = @"1.1,2.2,3.3" + Environment.NewLine
+ "4.4,5.5,6.6" + Environment.NewLine
+ "7.7,8.8,9.9";
Assert.AreEqual(expected, text);
}
public void Writer_CustomSeparator()
{
using (var writer = new DelimitedWriter(TestOutputFile, false, ','))
{
writer.Write("testing 1-1", "testing 1-2");
writer.Write("testing 2-1", "testing 2-2", "testing 2-3");
}
var expected = "testing 1-1,testing 1-2\r\ntesting 2-1,testing 2-2,testing 2-3\r\n";
string output;
using (var outFile = File.OpenText(TestOutputFile))
{
output = outFile.ReadToEnd();
}
Assert.That(expected, Is.EqualTo(output));
}
public void Save(string file)
{
if (file.EndsWith(".mat"))
{
MatlabWriter.Write <Complex>(file, matrix, "A");
}
else if (file.EndsWith(".mtx"))
{
MatrixMarketWriter.WriteMatrix <Complex>(file, matrix);
}
else if (file.EndsWith(".csv"))
{
DelimitedWriter.Write <Complex>(file, matrix, ";");
}
else
{
throw new NotImplementedException();
}
}
public void CanWriteSpaceDelimitedData()
{
var matrix = SparseMatrix.OfArray(new[, ] {
{ 1.1f, 0, 0 }, { 0, 5.5f, 0 }, { 0, 0, 9.9f }
});
var writer = new DelimitedWriter(' ')
{
CultureInfo = CultureInfo.InvariantCulture
};
var stream = new MemoryStream();
writer.WriteMatrix(matrix, stream);
var data = stream.ToArray();
var reader = new StreamReader(new MemoryStream(data));
var text = reader.ReadToEnd();
var expected = @"1.1 0 0" + Environment.NewLine
+ "0 5.5 0" + Environment.NewLine
+ "0 0 9.9";
Assert.AreEqual(expected, text);
}
public void CanWriteCommaDelimitedComplexData()
{
var matrix =
LinearAlgebra.Complex.DenseMatrix.OfArray(new[, ]
{
{ new Complex(1.1, 1.1), new Complex(2.2, 2.2), new Complex(3.3, 3.3) },
{ new Complex(4.4, 4.4), new Complex(5.5, 5.5), new Complex(6.6, 6.6) },
{ new Complex(7.7, 7.7), new Complex(8.8, 8.8), new Complex(9.9, 9.9) }
});
var stream = new MemoryStream();
DelimitedWriter.Write(stream, matrix, ",", formatProvider: CultureInfo.InvariantCulture);
var data = stream.ToArray();
var reader = new StreamReader(new MemoryStream(data));
var text = reader.ReadToEnd();
var expected = "(1.1, 1.1),(2.2, 2.2),(3.3, 3.3)" + Environment.NewLine
+ "(4.4, 4.4),(5.5, 5.5),(6.6, 6.6)" + Environment.NewLine
+ "(7.7, 7.7),(8.8, 8.8),(9.9, 9.9)";
Assert.AreEqual(expected, text);
}
public void CanWriteCommaDelimitedSingleData()
{
var matrix = LinearAlgebra.Single.DenseMatrix.OfArray(new[, ] {
{ 1.1f, 2.2f, 3.3f }, { 4.4f, 5.5f, 6.6f }, { 7.7f, 8.8f, 9.9f }
});
var writer = new DelimitedWriter(",")
{
FormatProvider = CultureInfo.InvariantCulture
};
var stream = new MemoryStream();
writer.WriteMatrix(matrix, stream);
var data = stream.ToArray();
var reader = new StreamReader(new MemoryStream(data));
var text = reader.ReadToEnd();
var expected = @"1.1,2.2,3.3" + Environment.NewLine
+ "4.4,5.5,6.6" + Environment.NewLine
+ "7.7,8.8,9.9";
Assert.AreEqual(expected, text);
}
public void CanWriteSpaceDelimitedData()
{
var matrix = DenseMatrix.OfArray(new[, ] {
{ new Complex(1.1, 1.1), new Complex(2.2, 2.2), new Complex(3.3, 3.3) }, { new Complex(4.4, 4.4), new Complex(5.5, 5.5), new Complex(6.6, 6.6) }, { new Complex(7.7, 7.7), new Complex(8.8, 8.8), new Complex(9.9, 9.9) }
});
var writer = new DelimitedWriter(' ')
{
CultureInfo = CultureInfo.InvariantCulture
};
var stream = new MemoryStream();
writer.WriteMatrix(matrix, stream);
var data = stream.ToArray();
var reader = new StreamReader(new MemoryStream(data));
var text = reader.ReadToEnd();
var expected = "(1.1, 1.1) (2.2, 2.2) (3.3, 3.3)" + Environment.NewLine
+ "(4.4, 4.4) (5.5, 5.5) (6.6, 6.6)" + Environment.NewLine
+ "(7.7, 7.7) (8.8, 8.8) (9.9, 9.9)";
Assert.AreEqual(expected, text);
}
public void CanWriteTabDelimitedData()
{
var matrix = new UserDefinedMatrix(new[,] { { 1.1, 2.2, 3.3 }, { 4.4, 5.5, 6.6 }, { 7.7, 8.8, 9.9 } });
var headers = new[] { "a", "b", "c" };
var writer = new DelimitedWriter('\t')
{
ColumnHeaders = headers
};
var stream = new MemoryStream();
writer.WriteMatrix(matrix, stream);
var data = stream.ToArray();
var reader = new StreamReader(new MemoryStream(data));
var text = reader.ReadToEnd();
var expected = "a\tb\tc"
+ Environment.NewLine
+ "1.1\t2.2\t3.3"
+ Environment.NewLine
+ "4.4\t5.5\t6.6"
+ Environment.NewLine
+ "7.7\t8.8\t9.9";
Assert.AreEqual(expected, text);
}
public void CanWritePeriodDelimitedData()
{
var matrix = DenseMatrix.OfArray(new[, ] {
{ new Complex(1.1, 1.1), new Complex(2.2, 2.2), new Complex(3.3, 3.3) }, { new Complex(4.4, 4.4), new Complex(5.5, 5.5), new Complex(6.6, 6.6) }, { new Complex(7.7, 7.7), new Complex(8.8, 8.8), new Complex(9.9, 9.9) }
});
var culture = new CultureInfo("tr-TR");
var writer = new DelimitedWriter('.')
{
CultureInfo = culture
};
var stream = new MemoryStream();
writer.WriteMatrix(matrix, stream);
var data = stream.ToArray();
var reader = new StreamReader(new MemoryStream(data));
var text = reader.ReadToEnd();
var expected = "(1,1, 1,1).(2,2, 2,2).(3,3, 3,3)" + Environment.NewLine
+ "(4,4, 4,4).(5,5, 5,5).(6,6, 6,6)" + Environment.NewLine
+ "(7,7, 7,7).(8,8, 8,8).(9,9, 9,9)";
Assert.AreEqual(expected, text);
}
public void CanWritePeriodDelimitedData()
{
var matrix = new DenseMatrix(new[, ] {
{ new Complex32(1.1f, 1.1f), new Complex32(2.2f, 2.2f), new Complex32(3.3f, 3.3f) }, { new Complex32(4.4f, 4.4f), new Complex32(5.5f, 5.5f), new Complex32(6.6f, 6.6f) }, { new Complex32(7.7f, 7.7f), new Complex32(8.8f, 8.8f), new Complex32(9.9f, 9.9f) }
});
var culture = new CultureInfo("tr-TR");
var writer = new DelimitedWriter('.')
{
CultureInfo = culture
};
var stream = new MemoryStream();
writer.WriteMatrix(matrix, stream);
var data = stream.ToArray();
var reader = new StreamReader(new MemoryStream(data));
var text = reader.ReadToEnd();
var expected = "(1,1, 1,1).(2,2, 2,2).(3,3, 3,3)" + Environment.NewLine
+ "(4,4, 4,4).(5,5, 5,5).(6,6, 6,6)" + Environment.NewLine
+ "(7,7, 7,7).(8,8, 8,8).(9,9, 9,9)";
Assert.AreEqual(expected, text);
}
public void CanWritePeriodDelimitedData()
{
var matrix = new DenseMatrix(new[, ] {
{ 1.1f, 2.2f, 3.3f }, { 4.4f, 5.5f, 6.6f }, { 7.7f, 8.8f, 9.9f }
});
var culture = new CultureInfo("tr-TR");
var writer = new DelimitedWriter('.')
{
CultureInfo = culture
};
var stream = new MemoryStream();
writer.WriteMatrix(matrix, stream);
var data = stream.ToArray();
var reader = new StreamReader(new MemoryStream(data));
var text = reader.ReadToEnd();
var expected = @"1,1.2,2.3,3" + Environment.NewLine
+ "4,4.5,5.6,6" + Environment.NewLine
+ "7,7.8,8.9,9";
Assert.AreEqual(expected, text);
}
public void CanWriteTabDelimitedData()
{
var matrix = new DenseMatrix(new[, ] {
{ new Complex32(1.1f, 1.1f), new Complex32(2.2f, 2.2f), new Complex32(3.3f, 3.3f) }, { new Complex32(4.4f, 4.4f), new Complex32(5.5f, 5.5f), new Complex32(6.6f, 6.6f) }, { new Complex32(7.7f, 7.7f), new Complex32(8.8f, 8.8f), new Complex32(9.9f, 9.9f) }
});
var headers = new[] { "a", "b", "c" };
var writer = new DelimitedWriter('\t')
{
ColumnHeaders = headers
};
var stream = new MemoryStream();
writer.WriteMatrix(matrix, stream);
var data = stream.ToArray();
var reader = new StreamReader(new MemoryStream(data));
var text = reader.ReadToEnd();
var expected = "a\tb\tc" + Environment.NewLine
+ "(1.1, 1.1)\t(2.2, 2.2)\t(3.3, 3.3)" + Environment.NewLine
+ "(4.4, 4.4)\t(5.5, 5.5)\t(6.6, 6.6)" + Environment.NewLine
+ "(7.7, 7.7)\t(8.8, 8.8)\t(9.9, 9.9)";
Assert.AreEqual(expected, text);
}
public void CanWriteTabDelimitedData()
{
var matrix = new UserDefinedMatrix(new[, ] {
{ 1.1f, 2.2f, 3.3f }, { 4.4f, 5.5f, 6.6f }, { 7.7f, 8.8f, 9.9f }
});
var headers = new[] { "a", "b", "c" };
var writer = new DelimitedWriter('\t')
{
ColumnHeaders = headers
};
var stream = new MemoryStream();
writer.WriteMatrix(matrix, stream);
var data = stream.ToArray();
var reader = new StreamReader(new MemoryStream(data));
var text = reader.ReadToEnd();
var expected = "a\tb\tc" + Environment.NewLine
+ "1.1\t2.2\t3.3" + Environment.NewLine
+ "4.4\t5.5\t6.6" + Environment.NewLine
+ "7.7\t8.8\t9.9";
Assert.AreEqual(expected, text);
}
public void CanWriteTabDelimitedData()
{
var matrix = DenseMatrix.OfArray(new[, ] {
{ new Complex(1.1, 1.1), new Complex(2.2, 2.2), new Complex(3.3, 3.3) }, { new Complex(4.4, 4.4), new Complex(5.5, 5.5), new Complex(6.6, 6.6) }, { new Complex(7.7, 7.7), new Complex(8.8, 8.8), new Complex(9.9, 9.9) }
});
var headers = new[] { "a", "b", "c" };
var writer = new DelimitedWriter('\t')
{
ColumnHeaders = headers,
CultureInfo = CultureInfo.InvariantCulture
};
var stream = new MemoryStream();
writer.WriteMatrix(matrix, stream);
var data = stream.ToArray();
var reader = new StreamReader(new MemoryStream(data));
var text = reader.ReadToEnd();
var expected = "a\tb\tc" + Environment.NewLine
+ "(1.1, 1.1)\t(2.2, 2.2)\t(3.3, 3.3)" + Environment.NewLine
+ "(4.4, 4.4)\t(5.5, 5.5)\t(6.6, 6.6)" + Environment.NewLine
+ "(7.7, 7.7)\t(8.8, 8.8)\t(9.9, 9.9)";
Assert.AreEqual(expected, text);
}
public void CanWriteTabDelimitedData()
{
var matrix = new DenseMatrix(new[,] { { new Complex32(1.1f, 1.1f), new Complex32(2.2f, 2.2f), new Complex32(3.3f, 3.3f) }, { new Complex32(4.4f, 4.4f), new Complex32(5.5f, 5.5f), new Complex32(6.6f, 6.6f) }, { new Complex32(7.7f, 7.7f), new Complex32(8.8f, 8.8f), new Complex32(9.9f, 9.9f) } });
var headers = new[] { "a", "b", "c" };
var writer = new DelimitedWriter('\t')
{
ColumnHeaders = headers,
CultureInfo = CultureInfo.InvariantCulture
};
var stream = new MemoryStream();
writer.WriteMatrix(matrix, stream);
var data = stream.ToArray();
var reader = new StreamReader(new MemoryStream(data));
var text = reader.ReadToEnd();
var expected = "a\tb\tc" + Environment.NewLine
+ "(1.1, 1.1)\t(2.2, 2.2)\t(3.3, 3.3)" + Environment.NewLine
+ "(4.4, 4.4)\t(5.5, 5.5)\t(6.6, 6.6)" + Environment.NewLine
+ "(7.7, 7.7)\t(8.8, 8.8)\t(9.9, 9.9)";
Assert.AreEqual(expected, text);
}
public void CanWriteSpaceDelimitedData()
{
var matrix = DenseMatrix.OfArray(new[,] {{new Complex(1.1, 1.1), new Complex(2.2, 2.2), new Complex(3.3, 3.3)}, {new Complex(4.4, 4.4), new Complex(5.5, 5.5), new Complex(6.6, 6.6)}, {new Complex(7.7, 7.7), new Complex(8.8, 8.8), new Complex(9.9, 9.9)}});
var writer = new DelimitedWriter(' ')
{
CultureInfo = CultureInfo.InvariantCulture
};
var stream = new MemoryStream();
writer.WriteMatrix(matrix, stream);
var data = stream.ToArray();
var reader = new StreamReader(new MemoryStream(data));
var text = reader.ReadToEnd();
var expected = "(1.1, 1.1) (2.2, 2.2) (3.3, 3.3)" + Environment.NewLine
+ "(4.4, 4.4) (5.5, 5.5) (6.6, 6.6)" + Environment.NewLine
+ "(7.7, 7.7) (8.8, 8.8) (9.9, 9.9)";
Assert.AreEqual(expected, text);
}
public void CanWriteTabDelimitedData()
{
var matrix = new DenseMatrix(new[,] { { new Complex(1.1, 1.1), new Complex(2.2, 2.2), new Complex(3.3, 3.3) }, { new Complex(4.4, 4.4), new Complex(5.5, 5.5), new Complex(6.6, 6.6) }, { new Complex(7.7, 7.7), new Complex(8.8, 8.8), new Complex(9.9, 9.9) } });
var headers = new[] { "a", "b", "c" };
var writer = new DelimitedWriter('\t')
{
ColumnHeaders = headers
};
var stream = new MemoryStream();
writer.WriteMatrix(matrix, stream);
var data = stream.ToArray();
var reader = new StreamReader(new MemoryStream(data));
var text = reader.ReadToEnd();
var expected = "a\tb\tc" + Environment.NewLine
+ "(1.1, 1.1)\t(2.2, 2.2)\t(3.3, 3.3)" + Environment.NewLine
+ "(4.4, 4.4)\t(5.5, 5.5)\t(6.6, 6.6)" + Environment.NewLine
+ "(7.7, 7.7)\t(8.8, 8.8)\t(9.9, 9.9)";
Assert.AreEqual(expected, text);
}
public void CanWriteSpaceDelimitedData()
{
var matrix = new SparseMatrix(new[,] { { 1.1f, 0, 0 }, { 0, 5.5f, 0 }, { 0, 0, 9.9f } });
var writer = new DelimitedWriter(' ')
{
CultureInfo = CultureInfo.InvariantCulture
};
var stream = new MemoryStream();
writer.WriteMatrix(matrix, stream);
var data = stream.ToArray();
var reader = new StreamReader(new MemoryStream(data));
var text = reader.ReadToEnd();
var expected = @"1.1 0 0" + Environment.NewLine
+ "0 5.5 0" + Environment.NewLine
+ "0 0 9.9";
Assert.AreEqual(expected, text);
}
