/// <summary>
/// Constructs a new general regression reconciler.
/// </summary>
/// <param name="estimatorFactory">The delegate to create the training estimator. It is assumed that this estimator
/// will produce a single new scalar <see cref="float"/> column named <see cref="DefaultColumnNames.Score"/>.</param>
/// <param name="label">The input label column.</param>
/// <param name="features">The input features column.</param>
/// <param name="weights">The input weights column, or <c>null</c> if there are no weights.</param>
public Regression(EstimatorFactory estimatorFactory, Scalar <float> label, Vector <float> features, Scalar <float> weights)
: base(MakeInputs(Contracts.CheckRef(label, nameof(label)), Contracts.CheckRef(features, nameof(features)), weights),
_fixedOutputNames)
{
Contracts.CheckValue(estimatorFactory, nameof(estimatorFactory));
_estFact = estimatorFactory;
Contracts.Assert(Inputs.Length == 2 || Inputs.Length == 3);
Score = new Impl(this);
}
/// <summary>
/// Constructs a new general regression reconciler.
/// </summary>
/// <param name="estimatorFactory">The delegate to create the training estimator. It is assumed that this estimator
/// will produce a single new scalar <see cref="float"/> column named <see cref="DefaultColumnNames.Score"/>.</param>
/// <param name="label">The input label column.</param>
/// <param name="features">The input features column.</param>
/// <param name="weights">The input weights column, or <c>null</c> if there are no weights.</param>
public BinaryClassifier(EstimatorFactory estimatorFactory, Scalar <bool> label, Vector <float> features, Scalar <float> weights)
: base(MakeInputs(Contracts.CheckRef(label, nameof(label)), Contracts.CheckRef(features, nameof(features)), weights),
_fixedOutputNames)
{
Contracts.CheckValue(estimatorFactory, nameof(estimatorFactory));
_estFact = estimatorFactory;
Contracts.Assert(Inputs.Length == 2 || Inputs.Length == 3);
Output = (new Impl(this), new Impl(this), new ImplBool(this));
}
public FloodingSimulator()
{
environment = new Environment();
BuildSimulation();
sensorFactory = new DummySensorFactory(environment);
actuatorFactory = new DummyActuatorFactory(environment);
estimatorFactory = new EstimatorFactory(sensorFactory, actuatorFactory);
warnerFactory = new WarnerFactory(actuatorFactory);
var speedEstimator = estimatorFactory.GetUltrasoundSpeedEstimator();
var depthEstimator = estimatorFactory.GetRadarDepthEstimator();
warner = warnerFactory.GetSMSWarner();
controller = new FloodingWarningSystem(speedEstimator, depthEstimator, warner);
}
public async Task <double> GetRiskFromValuables(IHasValuables subject)
{
var totalValue = 0;
double result = 0;
foreach (var item in subject.Valuables)
{
using (var estimator = EstimatorFactory.GetEstimator(item))
{
var value = await estimator.GetValue(item).ConfigureAwait(false);
totalValue += value;
}
}
if (totalValue > 100)
{
result = 1.0;
}
return(result);
}
private void btnStart_Click(object sender, EventArgs e)
{
if (String.IsNullOrEmpty(ecgFile) || String.IsNullOrEmpty(segmentStartFile) || String.IsNullOrEmpty(segmentStopFile))
{
MessageBox.Show("Load all neccesary files", "Missing files", MessageBoxButtons.OK, MessageBoxIcon.Error);
}
else
{
//"D:\\Fax\\Diplomski\\3.Semestar\\ISS\\data\\S_04_ecg.csv"
reader = new CSVReader(ecgFile, bufferSize, samplingFrequency);
reader.DataReady += new EventHandler <Herz.Common.DataReadyEventArgs>(reader_DataReady);
PanTompkins = new Pipeline <ECGSample>(reader.Frequency);
PanTompkins.Register(lp);
PanTompkins.Register(derivative);
PanTompkins.Register(square);
PanTompkins.Register(integrator);
PanTompkins.Register(new Delay(PanTompkins.FilterDelay));
detector = new Detector(samplingFrequency, bufferSize);
estimator = EstimatorFactory.CreateEstimatorFromFile(segmentStartFile, segmentStopFile, samplingFrequency);
cBoxSegments.DataSource = estimator.Segments;
cBoxSegments.DisplayMember = "Index";
cBoxSegments.ValueMember = "Index";
// Plot data with 50 samples per second.
plotFrequency = reader.Frequency / 50;
TaskScheduler uiScheduler = TaskScheduler.FromCurrentSynchronizationContext();
Task.Factory.StartNew(() => reader.Read());
Task.Factory.StartNew(() => PlotRaw(uiScheduler));
//Task.Factory.StartNew(() => PlotProcessed(uiScheduler));
Task.Factory.StartNew(() => PlotDetectedQRS(uiScheduler));
}
}
