private IDistribution createGaussianMixture(double mean, double std, double mean2, double std2)
{
IDistribution d1 = create1DGaussian(mean, std);
IDistribution d2 = create1DGaussian(mean2, std2);
int dim = 1;
string [] names = new string [1] {
"x"
};
double [] mins = new double [1] {
0.00
};
double [] maxs = new double [1] {
100.0
};
IBlauSpace s = BlauSpace.create(dim, names, mins, maxs);
Mixture d = new Mixture(s);
d.Add(d1, 0.75);
d.Add(d2, 0.25);
d.DistributionComplete();
return(d);
}
public void DistributionSpaceIterator_GaussianMixtureTest()
{
Console.WriteLine("DistributionSpaceIterator_GaussianMixtureTest");
double mean = 70.0;
double std = 1.0;
IDistribution d1 = create1DGaussian(mean, std);
double mean2 = 20.0;
double std2 = 1.0;
IDistribution d2 = create1DGaussian(mean2, std2);
int dim = 1;
string [] names = new string [1] {
"x"
};
double [] mins = new double [1] {
0.00
};
double [] maxs = new double [1] {
100.0
};
IBlauSpace s = BlauSpace.create(dim, names, mins, maxs);
Mixture d = new Mixture(s);
d.Add(d1, 0.75);
d.Add(d2, 0.25);
d.DistributionComplete();
SingletonLogger.Instance().DebugLog(typeof(dist_tests), "original distribution: " + d);
DistributionSpace ds = new DistributionSpace(d);
int [] steps = new int[ds.ParamSpace.Dimension];
for (int N = 3; N <= 5; N++)
{
for (int i = 0; i < ds.ParamSpace.Dimension; i++)
{
steps[i] = N;
}
IDistributionSpaceIterator it = ds.iterator(steps);
int count = 0;
int validCt = 0;
foreach (IDistribution diter in it)
{
if (diter.IsValid())
{
validCt++;
SingletonLogger.Instance().DebugLog(typeof(dist_tests), "iterator distribution: " + diter);
}
count++;
}
Assert.AreEqual((N + 1) * (N + 1) * (N + 1) * (N + 1) * (N + 1) * (N + 1), count);
SingletonLogger.Instance().InfoLog(typeof(dist_tests), "N=" + N + " valid distributions: " + validCt + " / total: " + count);
}
}
public static void Main1DMixture(string[] args)
{
Console.WriteLine("console_tests");
LoggerInitialization.SetThreshold(typeof(console_tests.MainClass), LogLevel.Debug);
double mean = 70.0;
double std = 1.0;
IDistribution d1 = create1DGaussian(mean, std);
double mean2 = 20.0;
double std2 = 1.0;
IDistribution d2 = create1DGaussian(mean2, std2);
int dim = 1;
string [] names = new string [1] {
"x"
};
double [] mins = new double [1] {
0.00
};
double [] maxs = new double [1] {
100.0
};
IBlauSpace s = BlauSpace.create(dim, names, mins, maxs);
Mixture d = new Mixture(s);
d.Add(d1, 0.75);
d.Add(d2, 0.25);
d.DistributionComplete();
SingletonLogger.Instance().DebugLog(typeof(console_tests.MainClass), "original distribution: " + d);
Console.WriteLine("original distribution: " + d);
DistributionSpace ds = new DistributionSpace(d);
int [] steps = new int[ds.ParamSpace.Dimension];
// N = subdivisions of each of the parameter values
for (int N = 3; N <= 6; N++)
{
for (int i = 0; i < ds.ParamSpace.Dimension; i++)
{
steps[i] = N;
}
IDistributionSpaceIterator it = ds.iterator(steps);
int count = 0;
int validCt = 0;
foreach (IDistribution diter in it)
{
if (diter.IsValid())
{
validCt++;
SingletonLogger.Instance().DebugLog(typeof(console_tests.MainClass), "iterator distribution: " + diter);
Console.WriteLine("valid distribution: " + diter);
}
else
{
Console.WriteLine("invalid distribution: " + diter);
}
count++;
}
Console.WriteLine("# of valid distributions: " + validCt);
Console.WriteLine("# of total distributions: " + count);
Assert.AreEqual((N + 1) * (N + 1) * (N + 1) * (N + 1) * (N + 1) * (N + 1), count);
SingletonLogger.Instance().InfoLog(typeof(console_tests.MainClass), "N=" + N + " valid distributions: " + validCt + " / total: " + count);
}
}
public static void MakeMixture_Main(string[] args)
{
Console.WriteLine("MakeMixture");
// Command line parsing
Arguments CommandLine = new Arguments(args);
bool err = false;
string errString = "";
string file1 = "unassigned";
string file2 = "unassigned";
string outfile = "unassigned";
// Look for specific arguments values and display
// them if they exist (return null if they don't)
if (CommandLine["file1"] != null)
{
file1 = CommandLine["file1"];
if (!File.Exists(file1))
{
errString += ("The specified 'file1' was not found: " + file1 + " ");
err = true;
}
}
else
{
errString += ("The 'file1' was not specified. ");
err = true;
}
double weight1 = -1.0;
// Look for specific arguments values and display
// them if they exist (return null if they don't)
if (CommandLine["weight1"] != null)
{
try {
weight1 = Double.Parse(CommandLine["weight1"]);
if ((weight1 < 0.0) || (weight1 > 1.0))
{
errString += ("The specified 'weight1' was not in the range [0,1]. ");
err = true;
}
}
catch (Exception) {
errString += ("The specified 'weight1' was not valid. ");
err = true;
}
}
else
{
errString += ("The 'weight1' was not specified. ");
err = true;
}
if (CommandLine["file2"] != null)
{
file2 = CommandLine["file2"];
if (!File.Exists(file2))
{
errString += ("The specified 'file2' was not found: " + file2 + " ");
err = true;
}
}
else
{
errString += ("The 'file2' was not specified. ");
err = true;
}
if (CommandLine["outfile"] != null)
{
outfile = CommandLine["outfile"];
}
else
{
errString += ("The 'outfile' was not specified. ");
err = true;
}
if (err)
{
Console.Out.WriteLine("Arguments parsing failed.");
Console.Out.WriteLine(" " + errString);
}
else
{
Console.Out.WriteLine("Arguments parsing successful.");
Console.Out.WriteLine(" file1 = " + file1);
Console.Out.WriteLine(" weight1 = " + weight1);
Console.Out.WriteLine(" file2 = " + file2);
Console.Out.WriteLine(" weight2 = " + (1 - weight1));
Console.Out.WriteLine(" outfile = " + outfile);
SoapFormatter formatter = new SoapFormatter();
FileStream fs = new FileStream(file1, FileMode.Open);
IDistribution d1 = (IDistribution)formatter.Deserialize(fs);
fs.Close();
fs = new FileStream(file2, FileMode.Open);
IDistribution d2 = (IDistribution)formatter.Deserialize(fs);
fs.Close();
if (!BlauSpace.contains(d1.SampleSpace, d2.SampleSpace) || !BlauSpace.contains(d2.SampleSpace, d1.SampleSpace))
{
Console.Out.WriteLine("The sample spaces of the two distributions are not identical intersection.");
Console.Out.WriteLine(" d1: " + d1);
Console.Out.WriteLine(" d2: " + d2);
Console.Out.WriteLine("The mixture must be constructed over identical sample spaces.");
Console.Out.WriteLine("This is a fatal error, preventing the construction of the mixture distribution.");
}
else
{
int dim3 = d1.SampleSpace.Dimension;
string [] names3 = new string [dim3];
double [] mins3 = new double [dim3];
double [] maxs3 = new double [dim3];
for (int i = 0; i < d1.SampleSpace.Dimension; i++)
{
names3[i] = d1.SampleSpace.getAxis(i).Name;
mins3[i] = d1.SampleSpace.getAxis(i).MinimumValue;
maxs3[i] = d1.SampleSpace.getAxis(i).MaximumValue;
}
IBlauSpace s3 = BlauSpace.create(dim3, names3, mins3, maxs3);
Mixture d3 = new Mixture(s3);
d3.Add(d1, weight1);
d3.Add(d2, 1.0 - weight1);
d3.DistributionComplete();
Console.Out.WriteLine("Distribution: " + d3);
fs = new FileStream(outfile, FileMode.Create);
formatter.Serialize(fs, d3);
fs.Close();
}
}
}