public string writeModel(string outModelPath)
{
outPath = outModelPath;
using (System.IO.StreamWriter sw = new System.IO.StreamWriter(outPath))
{
sw.WriteLine(modelTypes.LinearRegression.ToString());
sw.WriteLine(InTablePath);
sw.WriteLine(String.Join(",", IndependentFieldNames));
sw.WriteLine(String.Join(",", DependentFieldNames));
sw.WriteLine(String.Join(",", ClassFieldNames));
sw.WriteLine(SampleSize.ToString());
sw.WriteLine(NumberOfVariables.ToString());
sw.WriteLine(InterceptThroughOrigin.ToString());
sw.WriteLine(RMSE);
sw.WriteLine(FValue.ToString());
sw.WriteLine(PValue.ToString());
sw.WriteLine(Rsquared.ToString());
sw.WriteLine(AdjustedRsquared.ToString());
sw.WriteLine(String.Join(" ", (from double d in Coefficients select d.ToString()).ToArray()));
sw.WriteLine(String.Join(" ", (from double d in StandardErrors select d.ToString()).ToArray()));
sw.WriteLine(String.Join(" ", (from double d in minValues select d.ToString()).ToArray()));
sw.WriteLine(String.Join(" ", (from double d in maxValues select d.ToString()).ToArray()));
sw.WriteLine(String.Join(" ", (from double d in sumValues select d.ToString()).ToArray()));
sw.Close();
}
return(outPath);
}
// Full constructor takes Capture instance and specific values for
// channels, bits, and samples.
internal SoundFormat(Capture captureDevice, SampleRate rate, SampleSize size, short channels)
{
if (captureDevice == null)
{
throw new ArgumentNullException("captureDevice");
}
this._captureDevice = captureDevice;
try
{
// Test the supplied format characteristics.
this._currentFormat = ConstructFormat((int)rate, (short)size, (short)channels);
}
catch (Exception ex)
{
string errMsg =
string.Format("Sound format not supported: {0} samples/sec, {1} bits/sample, {2} channels.",
(int)rate, (short)size, (short)channels);
throw new Exception(errMsg, ex);
}
this._channels = channels;
this._bitsPerSample = (short)size;
this._samplesPerSecond = (int)rate;
}
public void getReport(double alpha)
{
Forms.RunningProcess.frmRunningProcessDialog rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.Text = "GLM Results";
rd.TopLevel = true;
rd.pgbProcess.Visible = false;
rd.FormBorderStyle = System.Windows.Forms.FormBorderStyle.Sizable;
rd.addMessage("Dependent field = " + DependentFieldNames[0]);
rd.addMessage("Independent fields = " + String.Join(", ", IndependentFieldNames));
rd.addMessage("Sample size = " + SampleSize.ToString());
rd.addMessage("Iteration = " + Iterations.ToString());
rd.addMessage("Delta Convergence " + DeltaC.ToString());
rd.addMessage("Chi-Sqr = " + ChiSquare.ToString() + " p-value = " + PValue.ToString());
rd.addMessage("Deviance = " + Deviance.ToString());
rd.addMessage("Log Likelihood = " + LogLikelihood.ToString());
rd.addMessage("Log Likelihood Ratio = " + LogLikelihoodratio.ToString() + "\n\nCoefficents and standard errors:\n");
rd.addMessage("Param: Intercept, " + String.Join(", ", IndependentFieldNames));
rd.addMessage("Coef: " + string.Join(", ", (from double d in Coefficients select d.ToString()).ToArray()));
rd.addMessage("STE: " + string.Join(", ", (from double d in StdError select d.ToString()).ToArray()) + "\n");
try
{
if (ModelHelper.chartingAvailable() && System.Windows.Forms.MessageBox.Show("Do you want to build distribution graphs?", "Graphs", System.Windows.Forms.MessageBoxButtons.YesNo) == System.Windows.Forms.DialogResult.Yes)
{
createRegChart();
}
}
catch
{
System.Windows.Forms.MessageBox.Show("Cannot create charts.");
}
rd.Show();
rd.enableClose();
}
public IEnumerable <INode> ReadNodeCollectionFile(SampleSize sampleSize)
{
string fileName = string.Empty;
switch (sampleSize)
{
case SampleSize.Small:
{
fileName = "SmallSample";
break;
}
case SampleSize.Medium:
{
fileName = "MediumSample";
break;
}
case SampleSize.Large:
{
fileName = "LargeSample";
break;
}
case SampleSize.CrazyBalls:
{
fileName = "CrazyBallsSample";
break;
}
}
JsonParser jsonParser = new JsonParser();
return(jsonParser.ReadJson <IEnumerable <INode> >(_fileReader.ReadSample(fileName)));
}
// Full constructor takes Capture instance and specific values for
// channels, bits, and samples.
internal SoundFormat(Capture captureDevice, SampleRate rate, SampleSize size, short channels)
{
if (captureDevice == null)
{
throw new ArgumentNullException("captureDevice");
}
this._captureDevice = captureDevice;
try
{
// Test the supplied format characteristics.
this._currentFormat = ConstructFormat((int)rate, (short)size, (short)channels);
}
catch (Exception ex)
{
string errMsg =
string.Format("Sound format not supported: {0} samples/sec, {1} bits/sample, {2} channels.",
(int)rate, (short)size, (short)channels);
throw new Exception(errMsg, ex);
}
this._channels = channels;
this._bitsPerSample = (short)size;
this._samplesPerSecond = (int)rate;
}
public string writeModel(string outModelPath)
{
outPath = outModelPath;
using (System.IO.StreamWriter sw = new System.IO.StreamWriter(outPath))
{
sw.WriteLine(modelTypes.GLM.ToString());
sw.WriteLine(InTablePath);
sw.WriteLine(String.Join(",", IndependentFieldNames));
sw.WriteLine(String.Join(",", DependentFieldNames));
sw.WriteLine(String.Join(",", ClassFieldNames));
sw.WriteLine(SampleSize.ToString());
sw.WriteLine(NumberOfVariables.ToString());
sw.WriteLine(Iterations.ToString());
sw.WriteLine(DeltaC.ToString());
sw.WriteLine(LogLikelihood);
sw.WriteLine(LogLikelihoodratio);
sw.WriteLine(PValue.ToString());
sw.WriteLine(Deviance.ToString());
sw.WriteLine(ChiSquare.ToString());
sw.WriteLine(linkfunction.ToString());
sw.WriteLine(String.Join(" ", (from double d in Coefficients select d.ToString()).ToArray()));
sw.WriteLine(String.Join(" ", (from double d in StdError select d.ToString()).ToArray()));
sw.WriteLine(String.Join(" ", (from double d in waldTestValues select d.ToString()).ToArray()));
sw.WriteLine(String.Join(" ", (from double d in waldTestPValues select d.ToString()).ToArray()));
sw.WriteLine(String.Join(" ", (from double d in minValues select d.ToString()).ToArray()));
sw.WriteLine(String.Join(" ", (from double d in maxValues select d.ToString()).ToArray()));
sw.WriteLine(String.Join(" ", (from double d in sumValues select d.ToString()).ToArray()));
sw.Close();
}
return(outPath);
}
public static int GetSampleResolution(SampleSize size)
{
switch (size)
{
case SampleSize._32:
return(32);
case SampleSize._64:
return(64);
case SampleSize._128:
return(128);
case SampleSize._256:
return(256);
case SampleSize._512:
return(512);
case SampleSize._1024:
return(1024);
case SampleSize._2048:
return(2048);
default:
return(256);
}
}
public string writeModel(string outModelPath)
{
outPath = outModelPath;
string outPathSvm = outModelPath.Replace(".mdl", ".svm");
svmMachine.Save(outPathSvm);
using (System.IO.StreamWriter sw = new System.IO.StreamWriter(outPath))
{
sw.WriteLine(modelTypes.SVM.ToString());
sw.WriteLine(InTablePath);
sw.WriteLine(String.Join(",", IndependentFieldNames));
sw.WriteLine(String.Join(",", DependentFieldNames));
if (ClassFieldNames != null)
{
sw.WriteLine(String.Join(",", ClassFieldNames));
}
else
{
sw.WriteLine();
}
sw.WriteLine(SampleSize.ToString());
sw.WriteLine(NumberOfVariables.ToString());
sw.WriteLine(sserror.ToString());
sw.WriteLine(kTyp.ToString());
sw.WriteLine(String.Join(" ", (from double d in minValues select d.ToString()).ToArray()));
sw.WriteLine(String.Join(" ", (from double d in maxValues select d.ToString()).ToArray()));
sw.WriteLine(String.Join(" ", (from double d in sumValues select d.ToString()).ToArray()));
sw.Close();
}
return(outPath);
}
public void getReport(double alpha)
{
Forms.RunningProcess.frmRunningProcessDialog rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.Text = "Regression Results";
rd.TopLevel = true;
rd.pgbProcess.Visible = false;
rd.FormBorderStyle = System.Windows.Forms.FormBorderStyle.Sizable;
rd.addMessage("Dependent field = " + DependentFieldNames[0]);
rd.addMessage("Independent fields = " + String.Join(", ", IndependentFieldNames));
rd.addMessage("Sample size = " + SampleSize.ToString());
rd.addMessage("Intercept Through Origin = " + InterceptThroughOrigin.ToString());
rd.addMessage("F-statistic = " + FValue.ToString() + " p-value = " + PValue.ToString());
rd.addMessage("RMSE = " + RMSE.ToString());
rd.addMessage("R2 = " + Rsquared.ToString());
rd.addMessage("Adj-R2 = " + AdjustedRsquared.ToString() + "\n\nCoefficents and standard errors:\n");
rd.addMessage("Param: Intercept, " + String.Join(", ", IndependentFieldNames));
rd.addMessage("Coef: " + string.Join(", ", (from double d in Coefficients select d.ToString()).ToArray()));
rd.addMessage("STE: " + string.Join(", ", (from double d in StandardErrors select d.ToString()).ToArray()) + "\n");
try
{
if (ModelHelper.chartingAvailable())
{
regChart();
}
}
catch
{
System.Windows.Forms.MessageBox.Show("Cannot create charts");
}
rd.Show();
rd.enableClose();
}
public void getReport()
{
Forms.RunningProcess.frmRunningProcessDialog rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.Text = "SVM Results";
rd.TopLevel = true;
rd.pgbProcess.Visible = false;
rd.FormBorderStyle = System.Windows.Forms.FormBorderStyle.Sizable;
rd.addMessage("Dependent field = " + DependentFieldNames[0]);
rd.addMessage("Independent fields = " + String.Join(", ", IndependentFieldNames));
rd.addMessage("Sample size = " + SampleSize.ToString());
rd.addMessage("Sum of Squared Error: " + sserror.ToString());
rd.Show();
rd.enableClose();
}
/// <summary>
/// Converts sample size format to specified sample size, if
/// sample size is not supported will throw a FormatException.
/// Good idea to surround with a try catch block if you don't
/// know the specified sample size
/// </summary>
/// <param name="sampleSize">Size of sample in bytes</param>
public void ConvertTo(SampleSize sampleSize)
{
if (this.Data.Length == (int)sampleSize)
{
return;
}
else
{
decimal value = this.GetValue();
this.Data = new byte[(int)sampleSize];
this.SetValue(value);
}
throw new FormatException();
}
public void getReport()
{
Forms.RunningProcess.frmRunningProcessDialog rd = new Forms.RunningProcess.frmRunningProcessDialog(false);
rd.Text = "LDA Results";
rd.TopLevel = true;
rd.pgbProcess.Visible = false;
rd.FormBorderStyle = System.Windows.Forms.FormBorderStyle.Sizable;
rd.addMessage("Dependent field = " + DependentFieldNames[0]);
rd.addMessage("Independent fields = " + String.Join(", ", IndependentFieldNames));
rd.addMessage("Sample size = " + SampleSize.ToString());
rd.addMessage("Means: " + string.Join(", ", (from double d in meanValues select d.ToString()).ToArray()));
rd.addMessage("Standard Dev: " + string.Join(", ", (from double d in stdValues select d.ToString()).ToArray()) + "\n");
rd.Show();
rd.enableClose();
}
/// <summary>
/// Create a new sound recorder.
/// </summary>
/// <param name="type">Sound capture device.</param>
/// <param name="rate">Desired sample rate.</param>
/// <param name="size">Desired sample size.</param>
/// <param name="channels">Desired channels to use.</param>
public SoundRecorder(SoundDeviceType type, SampleRate rate, SampleSize size, short channels)
{
this._desiredDeviceType = type;
this._devices = new CaptureDevicesCollection();
if (this._devices == null || this._devices.Count < 1)
{
throw new InvalidOperationException("No sound capture devices detected.");
}
this.Find(type);
InitDirectSound();
this._recorderFormat = new SoundFormat(this._applicationDevice, rate, size, channels);
}
public override int GetHashCode()
{
unchecked
{
var hashCode = Id?.GetHashCode() ?? 0;
hashCode = (hashCode * 397) ^ (Chromosome?.GetHashCode() ?? 0);
hashCode = (hashCode * 397) ^ Start.GetHashCode();
hashCode = (hashCode * 397) ^ End.GetHashCode();
hashCode = (hashCode * 397) ^ VariantType.GetHashCode();
hashCode = (hashCode * 397) ^ SampleSize.GetHashCode();
hashCode = (hashCode * 397) ^ ObservedGains.GetHashCode();
hashCode = (hashCode * 397) ^ ObservedLosses.GetHashCode();
hashCode = (hashCode * 397) ^ (VariantFreqAll?.GetHashCode() ?? 0);
return(hashCode);
}
}
public override int GetHashCode()
{
int hash = 1;
if (Id.Length != 0)
{
hash ^= Id.GetHashCode();
}
if (Algorithm != 0)
{
hash ^= Algorithm.GetHashCode();
}
if (ErrorTolerance != 0D)
{
hash ^= ErrorTolerance.GetHashCode();
}
if (File.Length != 0)
{
hash ^= File.GetHashCode();
}
if (Support != 0D)
{
hash ^= Support.GetHashCode();
}
if (SampleSize != 0)
{
hash ^= SampleSize.GetHashCode();
}
if (K != 0)
{
hash ^= K.GetHashCode();
}
if (UseTopK != false)
{
hash ^= UseTopK.GetHashCode();
}
if (DBSize != 0)
{
hash ^= DBSize.GetHashCode();
}
if (ShutdownServer != false)
{
hash ^= ShutdownServer.GetHashCode();
}
return(hash);
}
public string writeModel(string outModelPath)
{
if (lm == null)
{
getMnlModel();
}
outPath = outModelPath;
double[,] coef = null;
alglib.mnlunpack(lm, out coef, out nvars, out nclasses);
using (System.IO.StreamWriter sw = new System.IO.StreamWriter(outPath))
{
sw.WriteLine(modelTypes.SoftMax.ToString());
sw.WriteLine(InTablePath);
sw.WriteLine(SampleSize.ToString());
sw.WriteLine(String.Join(",", IndependentFieldNames));
sw.WriteLine(String.Join(",", DependentFieldNames));
sw.WriteLine(String.Join(",", ClassFieldNames));
sw.WriteLine(string.Join(",", Categories));
sw.WriteLine(NumberOfVariables.ToString());
sw.WriteLine(NumberOfClasses.ToString());
sw.WriteLine(RMSE.ToString());
sw.WriteLine(AverageCrossEntropyError.ToString());
sw.WriteLine(AverageError.ToString());
sw.WriteLine(AverageRelativeError.ToString());
sw.WriteLine(ClassificationError.ToString());
sw.WriteLine(RelativeClassificationError.ToString());
sw.WriteLine(String.Join(",", (from double d in minValues select d.ToString()).ToArray()));
sw.WriteLine(String.Join(",", (from double d in maxValues select d.ToString()).ToArray()));
sw.WriteLine(String.Join(",", (from double d in sumValues select d.ToString()).ToArray()));
int rws = coef.GetUpperBound(1);
int clms = coef.GetUpperBound(0);
for (int r = 0; r <= rws; r++)
{
string[] ln = new string[clms + 1];
for (int c = 0; c <= clms; c++)
{
ln[c] = coef[c, r].ToString();
}
sw.WriteLine(String.Join(" ", ln));
}
sw.Close();
}
return(outPath);
}
protected override void afterPopulateProps()
{
RetestSampleRegime.SetOnBeforeRender(delegate(CswNbtNodeProp Prop)
{
CswNbtObjClassLevel LevelNode = _CswNbtResources.Nodes.GetNode(Level.RelatedNodeId);
if (null != LevelNode && LevelNode.LabUseOnly.Checked == CswEnumTristate.True) //On Add, LevelNode will be null
{
Prop.setHidden(true, false);
}
});
SampleSize.SetOnBeforeRender(delegate(CswNbtNodeProp Prop)
{
if (false == IsTemp)
{
SampleSize.View = _getSampleSizeUnitsView();
}
});
}
public string writeModel(string outModelPath)
{
outPath = outModelPath;
using (System.IO.StreamWriter sw = new System.IO.StreamWriter(outPath))
{
sw.WriteLine(modelTypes.LDA.ToString());
sw.WriteLine(InTablePath);
sw.WriteLine(String.Join(",", IndependentFieldNames));
sw.WriteLine(String.Join(",", DependentFieldNames));
sw.WriteLine(String.Join(",", ClassFieldNames));
sw.WriteLine(SampleSize.ToString());
sw.WriteLine(NumberOfVariables.ToString());
sw.WriteLine(String.Join(" ", (from double d in minValues select d.ToString()).ToArray()));
sw.WriteLine(String.Join(" ", (from double d in maxValues select d.ToString()).ToArray()));
sw.WriteLine(String.Join(" ", (from double d in sumValues select d.ToString()).ToArray()));
sw.WriteLine(String.Join(" ", (from double d in meanValues select d.ToString()).ToArray()));
sw.WriteLine(String.Join(" ", (from double d in stdValues select d.ToString()).ToArray()));
sw.Close();
}
return(outPath);
}
public void WriteXml(XmlWriter writer)
{
writer.WriteAttributeString("nominal", Nominal.ToString(CultureInfo.InvariantCulture));
writer.WriteAttributeString("mean", Mean.ToString(CultureInfo.InvariantCulture));
writer.WriteAttributeString("standardDeviation", StandardDeviation.ToString(CultureInfo.InvariantCulture));
writer.WriteAttributeString("lowerSpecLimit", LowerSpecLimit.ToString(CultureInfo.InvariantCulture));
writer.WriteAttributeString("upperSpecLimit", UpperSpecLimit.ToString(CultureInfo.InvariantCulture));
writer.WriteAttributeString("cp", Cp.ToString(CultureInfo.InvariantCulture));
writer.WriteAttributeString("cpk", Cpk.ToString(CultureInfo.InvariantCulture));
writer.WriteAttributeString("distribution", Distribution);
writer.WriteAttributeString("skewness", Skewness.ToString(CultureInfo.InvariantCulture));
writer.WriteAttributeString("kurtosis", Kurtosis.ToString(CultureInfo.InvariantCulture));
writer.WriteAttributeString("sampleSize", SampleSize.ToString(CultureInfo.InvariantCulture));
writer.WriteStartElement("Sample");
Sample.WriteXml(writer);
writer.WriteEndElement();
writer.WriteStartElement("Estimate");
Estimate.WriteXml(writer);
writer.WriteEndElement();
}
public IEnumerable <INode> GetNodes(SampleSize sampleSize)
{
return(_dataInterfaceProvider.ReadNodeCollectionFile(sampleSize));
}
/// <summary>
/// Sample constructor
/// </summary>
/// <param name="sampleSize">Sample size in bytes</param>
public Sample(SampleSize sampleSize)
: this((int)sampleSize)
{
// Skip
}
static void Main(string[] args)
{
bool showUsage = true;
if (args.Length >= 1) // requires port at least
{
try
{
// todo: validate with a regex (ip or name)
int port = int.Parse(args[0]);
if (port > 0 && port < 65536)
{
showUsage = false;
String adrs = "127.0.0.1";
if (args.Length >= 2)
{
adrs = args[1];
}
// todo: retreive list of devices and select from/display it in Show Usage
// todo: parse and set these parameters
SampleRate rate = SampleRate.Rate11KHz;
SampleSize size = SampleSize.Bits8;
short channels = 1;
SoundRecorder recorder = new SoundRecorder(SoundDeviceType.Default, rate, size, channels);
UdpClient udpClient = new UdpClient(adrs, port);
Console.WriteLine("Sending sound packets on UDP port " + port);
try
{
recorder.Start("");
while (recorder.Capturing())
{
//Sit here and wait for a message to arrive
recorder.NotificationEvent.WaitOne(System.Threading.Timeout.Infinite, true);
recorder.SendCapturedData(udpClient);
}
}
catch (Exception e)
{
Console.WriteLine(e.ToString());
Console.WriteLine("Hit any key to continue");
Console.ReadKey();
}
finally
{
recorder.Stop();
udpClient.Close();
}
}
}
catch (Exception e)
{
Console.WriteLine(e);
}
}
if (showUsage)
{
Console.WriteLine("Send direct sound data as UDP packets.");
Console.WriteLine("USAGE: UDPSoundSender targetIP port [8000 8 1]");
Console.WriteLine("where:");
Console.WriteLine(" targetIP is address where to send the packets (yes, multicast addresses should works!)");
Console.WriteLine(" port is the one of the target ip listening");
Console.WriteLine(" [optional parameters]");
Console.WriteLine(" 8000 is the default sample rate (choose 8000, 11025, 22050, 44100 or 48000 sample/sec)");
Console.WriteLine(" 8 is the default bit depth (choose 8 or 16 bits)");
Console.WriteLine(" 1 is the channels selected (choose 1 or 2 channels)");
Console.WriteLine("Hit any key to exit");
Console.Read();
}
}
/**
* Load and parse data from dat_mes.csv
*/
internal static void LoadData(StudyData studyData)
{
if (IsDataLoaded)
{
return;
}
List <string[]> rows = new List <string[]>();
using (StreamReader reader = File.OpenText("Data/dat_mes.csv"))
{
while (reader.Peek() >= 0)
{
string line = reader.ReadLine();
string[] rowArray = CSVRowToStringArray(line);
if (rowArray.Length > 0)
{
rows.Add(rowArray);
}
}
}
string[] headers = rows[0];
rows.Remove(headers);
/**
* Parse each row array into a Study object.
* Assumes CSV column ordering:
* id,PublicationYear,n,r,VariablesControlled,StudyDesign,
* AdherenceMeasure,ConscientiousnessMeasure ,MeanAge,MethodologicalQuality
*/
foreach (string[] row in rows)
{
PublicationYear publicationYear = studyData.PublicationYears.AddUnique(row[1]);
CorrelationCoefficient correlationCoefficient = studyData.CorrelationCoefficients.AddUnique(row[2]);
SampleSize sampleSize = studyData.SampleSizes.AddUnique(row[3]);
VariablesControlled variablesControlled = studyData.VariablesControlled.AddUnique(row[4]);
StudyDesign studyDesign = studyData.StudyDesigns.AddUnique(row[5]);
AdherenceMeasure adherenceMeasure = studyData.AdherenceMeasures.AddUnique(row[6]);
ConscientiousnessMeasure conscientiousnessMeasure = studyData.ConscientiousnessMeasures.AddUnique(row[7]);
MeanAge meanAge = studyData.MeanAges.AddUnique(row[8]);
MethodologicalQuality methodologicalQuality = studyData.MethodologicalQualities.AddUnique(row[9]);
Study newStudy = new Study
{
Id = row[0],
PublicationYear = publicationYear,
CorrelationCoefficient = correlationCoefficient,
SampleSize = sampleSize,
VariablesControlled = variablesControlled,
StudyDesign = studyDesign,
AdherenceMeasure = adherenceMeasure,
ConscientiousnessMeasure = conscientiousnessMeasure,
MeanAge = meanAge,
MethodologicalQuality = methodologicalQuality
};
studyData.Studies.Add(newStudy);
}
IsDataLoaded = true;
}
