static void Main(string[] args)
{
Random rnd = new Random();
//Creating an array with values, corresponding to linear function with added white noise
const int n = 360;
double[] array = new double[n];
for (int i = 0; i < n; i++)
{
double noise = 0;
noise = (double)rnd.Next(Int32.MinValue, Int32.MaxValue) / (Int32.MaxValue / rnd.Next(1, 30));
//if (i % 10 == 0) noise = 100; //Noise for tukey filter testing
array[i] = (double)i + noise;
}
BSDataObject source = new BSDataObject(array, "SourceData");
IVisualizer visualizer = new SimpleVisualizationHandler();
visualizer.AddToGraph(source);
visualizer.AddToGraph(new MedianPreprocessor().Process(source));
using (var ms = new MemoryStream(n * (sizeof(double) + sizeof(char))))
{
StreamWriter sw = new StreamWriter(ms);
for (int i = 0; i < n; i++)
{
array[i] = 80 * Math.Sin((double)i * Math.PI / 180.0);
sw.WriteLine(array[i]);
}
sw.Flush();
ms.Position = 0;
BSDataObject target = DataObjectSupplier.GetDataObjectForStream(ms, "Sine from memory stream");
visualizer.AddToGraph(target);
}
(visualizer as SimpleVisualizationHandler)._TestShow();
}
static void Main(string[] args)
{
Random rnd = new Random();
//Creating an array with values, corresponding to linear function with added white noise
const int n = 360;
double[] array = new double[n];
for (int i = 0; i < n; i++)
{
double noise = 0;
noise = (double)rnd.Next(Int32.MinValue, Int32.MaxValue) / (Int32.MaxValue / rnd.Next(1, 30));
//if (i % 10 == 0) noise = 100; //Noise for tukey filter testing
array[i] = (double)i + noise;
}
BSDataObject source = new BSDataObject(array, "SourceData");
IVisualizer visualizer = new SimpleVisualizationHandler();
visualizer.AddToGraph(source);
visualizer.AddToGraph(new MedianPreprocessor().Process(source));
using (var ms = new MemoryStream(n * (sizeof(double) + sizeof(char))))
{
StreamWriter sw = new StreamWriter(ms);
for (int i = 0; i < n; i++)
{
array[i] = 80 * Math.Sin((double)i * Math.PI / 180.0);
sw.WriteLine(array[i]);
}
sw.Flush();
ms.Position = 0;
BSDataObject target = DataObjectSupplier.GetDataObjectForStream(ms, "Sine from memory stream");
visualizer.AddToGraph(target);
}
(visualizer as SimpleVisualizationHandler)._TestShow();
}
//
//You can use the following additional attributes as you write your tests:
//
//Use ClassInitialize to run code before running the first test in the class
//[ClassInitialize()]
//public static void MyClassInitialize(TestContext testContext)
//{
//}
//
//Use ClassCleanup to run code after all tests in a class have run
//[ClassCleanup()]
//public static void MyClassCleanup()
//{
//}
//
//Use TestInitialize to run code before running each test
//[TestInitialize()]
//public void MyTestInitialize()
//{
//}
//
//Use TestCleanup to run code after each test has run
//[TestCleanup()]
//public void MyTestCleanup()
//{
//}
//
#endregion
/// <summary>
/// A test for GenerateInputAndOutput
///</summary>
//[TestMethod()]
public void GenerateInputAndOutputTest()
{
uint iLag = 1;
uint iWindowSize = 5;
int pointsNum = 360;
IInputProvider target = new WindowingInputProvider(iLag, iWindowSize);
Random rnd = new Random();
double[] iTimeSeries = new double[pointsNum];
for (int i = 0; i < pointsNum; i++)
{
iTimeSeries[i] = 1 * Math.Sin(2 * i * Math.PI / 180.0) + (Convert.ToDouble(rnd.Next(-2, 2)) / 5) * ((i % 3 == 0) ? 1 : 0);
}
double[][] oInput = null;
double[][] oOutput = null;
target.GenerateInputAndOutput(iTimeSeries, out oInput, out oOutput);
IForecastingModelBuilder modelBuilder = new ANNmodelBuilder();
IForecastingModel model = modelBuilder.TrainNewModel(oInput, oOutput);
double[] forecast = new double[oInput.LongLength], actual = new double[oInput.LongLength];
for (int i = 0; i < oInput.LongLength; ++i)
{
forecast[i] = model.CalculateOutput(oInput[i])[0]; actual[i] = oOutput[i][0];
}
BSDataObject forecastDO = new BSDataObject(forecast, "Forecast"), actualDO = new BSDataObject(actual, "Actual");
SimpleVisualizationHandler handler = new SimpleVisualizationHandler();
handler.AddToGraph(actualDO);
handler.AddToGraph(forecastDO);
handler._TestShow();
}
/// <summary>
/// A test for GenerateInputAndOutput
///</summary>
//[TestMethod()]
public void GenerateInputAndOutputTest()
{
uint iLag = 1;
uint iWindowSize = 5;
int pointsNum = 360;
IInputProvider target = new WindowingInputProvider(iLag, iWindowSize);
Random rnd = new Random();
double[] iTimeSeries = new double[pointsNum];
for (int i = 0; i < pointsNum; i++)
{
iTimeSeries[i] = 1 * Math.Sin(2 * i * Math.PI / 180.0) + (Convert.ToDouble(rnd.Next(-2, 2)) / 5) * ((i % 3 == 0) ? 1 : 0);
}
double[][] oInput = null;
double[][] oOutput = null;
target.GenerateInputAndOutput(iTimeSeries, out oInput, out oOutput);
IForecastingModelBuilder modelBuilder = new ANNmodelBuilder();
IForecastingModel model = modelBuilder.TrainNewModel(oInput, oOutput);
double[] forecast = new double[oInput.LongLength], actual = new double[oInput.LongLength];
for (int i = 0; i < oInput.LongLength; ++i)
{
forecast[i] = model.CalculateOutput(oInput[i])[0]; actual[i] = oOutput[i][0];
}
BSDataObject forecastDO = new BSDataObject(forecast, "Forecast"), actualDO = new BSDataObject(actual, "Actual");
SimpleVisualizationHandler handler = new SimpleVisualizationHandler();
handler.AddToGraph(actualDO);
handler.AddToGraph(forecastDO);
handler._TestShow();
}
/// <summary>
///A test for Visualize
///</summary>
//[TestMethod()]
public void VisualizeTest()
{
SimpleVisualizationHandler target = new SimpleVisualizationHandler();
double[] iArray = {1.2, 3.4, 5.6, 2.2, 7.7};
BSDataObject obj = new BSDataObject(iArray, "asdasd");
target.AddToGraph(obj);
iArray = new double[] { 2.6, 7.8, 12.2, 10, 2.2, 3.3, 4.4, 5.5, 3.3, -5, 30};
target.AddToGraph(new BSDataObject(iArray, "anotherGraph"));
target._TestShow();
}
//
//You can use the following additional attributes as you write your tests:
//
//Use ClassInitialize to run code before running the first test in the class
//[ClassInitialize()]
//public static void MyClassInitialize(TestContext testContext)
//{
//}
//
//Use ClassCleanup to run code after all tests in a class have run
//[ClassCleanup()]
//public static void MyClassCleanup()
//{
//}
//
//Use TestInitialize to run code before running each test
//[TestInitialize()]
//public void MyTestInitialize()
//{
//}
//
//Use TestCleanup to run code after each test has run
//[TestCleanup()]
//public void MyTestCleanup()
//{
//}
//
#endregion
/// <summary>
///A test for Visualize
///</summary>
//[TestMethod()]
public void VisualizeTest()
{
SimpleVisualizationHandler target = new SimpleVisualizationHandler();
double[] iArray = { 1.2, 3.4, 5.6, 2.2, 7.7 };
BSDataObject obj = new BSDataObject(iArray, "asdasd");
target.AddToGraph(obj);
iArray = new double[] { 2.6, 7.8, 12.2, 10, 2.2, 3.3, 4.4, 5.5, 3.3, -5, 30 };
target.AddToGraph(new BSDataObject(iArray, "anotherGraph"));
target._TestShow();
}
public override void Start()
{
CheckIfInputsAreProvided();
foreach (BSDataObject dataObj in Inputs)
{
visualizer.AddToGraph(dataObj);
}
visualizer.ShowGraph();
//Will possibly need refactoring.
visualizer = new SimpleVisualizationHandler();
//
}
public override void Start()
{
CheckIfInputsAreProvided();
foreach (BSDataObject dataObj in Inputs)
{
visualizer.AddToGraph(dataObj);
}
visualizer.ShowGraph();
//Will possibly need refactoring.
visualizer = new SimpleVisualizationHandler();
//
}
