/// <summary>
/// Pop up a window for running examples, when compiled with .NET 4.6.1 or higher, then exit the application. Otherwise do nothing.
/// </summary>
public static void RunBrowser() // Must not be called "Run"
{
#if NETFULL
InferenceEngine.Visualizer = new Compiler.Visualizers.WindowsVisualizer();
// Show all tutorials, in a browser
IAlgorithm[] algs = InferenceEngine.GetBuiltInAlgorithms();
// Avoid max product in the examples browser, as none of the examples apply.
List <IAlgorithm> algList = new List <IAlgorithm>(algs);
algList.RemoveAll(alg => alg is MaxProductBeliefPropagation);
ExamplesViewer tview = new ExamplesViewer(typeof(ExamplesBrowser), algList.ToArray());
tview.RunBrowser();
Environment.Exit(0);
#endif
}
internal GUITextWriter(ExamplesViewer view)
{
this.view = view;
}
public static void Main()
{
Type tutorialClass = null;
// ********** UNCOMMENT AND EDIT THIS LINE TO RUN A PARTICULAR TUTORIAL DIRECTLY *************
//tutorialClass = typeof(Microsoft.ML.Probabilistic.Tutorials.FirstExample);
//Choose one of the algorithms
InferenceEngine.DefaultEngine.Algorithm = new ExpectationPropagation();
//InferenceEngine.DefaultEngine.Algorithm = new VariationalMessagePassing();
//InferenceEngine.DefaultEngine.Algorithm = new GibbsSampling();
//Options
InferenceEngine.DefaultEngine.ShowProgress = true;
InferenceEngine.DefaultEngine.ShowTimings = false;
InferenceEngine.DefaultEngine.ShowMsl = false;
InferenceEngine.DefaultEngine.ShowFactorGraph = false;
InferenceEngine.DefaultEngine.ShowSchedule = false;
#if NETCORE
//Tutorials
//Uncomment one of these lines to run a particular tutorial in console application
tutorialClass = typeof(Microsoft.ML.Probabilistic.Tutorials.FirstExample);
//tutorialClass = typeof(Microsoft.ML.Probabilistic.Tutorials.TruncatedGaussian);
//tutorialClass = typeof(Microsoft.ML.Probabilistic.Tutorials.TruncatedGaussianEfficient);
//tutorialClass = typeof(Microsoft.ML.Probabilistic.Tutorials.LearningAGaussian);
//tutorialClass = typeof(Microsoft.ML.Probabilistic.Tutorials.LearningAGaussianWithRanges);
//tutorialClass = typeof(Microsoft.ML.Probabilistic.Tutorials.BayesPointMachineExample);
//tutorialClass = typeof(Microsoft.ML.Probabilistic.Tutorials.ClinicalTrial);
//tutorialClass = typeof(Microsoft.ML.Probabilistic.Tutorials.MixtureOfGaussians);
//String tutorials
//tutorialClass = typeof(Microsoft.ML.Probabilistic.Tutorials.HelloStrings);
//tutorialClass = typeof(Microsoft.ML.Probabilistic.Tutorials.StringFormat);
//Applications
//tutorialClass = typeof(Microsoft.ML.Probabilistic.Tutorials.BayesianPCA);
//tutorialClass = typeof(Microsoft.ML.Probabilistic.Tutorials.BugsRats);
//tutorialClass = typeof(Microsoft.ML.Probabilistic.Tutorials.ChessAnalysis);
//tutorialClass = typeof(Microsoft.ML.Probabilistic.Tutorials.ClickModel);
//tutorialClass = typeof(Microsoft.ML.Probabilistic.Tutorials.DifficultyAbility);
//tutorialClass = typeof(Microsoft.ML.Probabilistic.Tutorials.GaussianProcessClassifier);
//tutorialClass = typeof(Microsoft.ML.Probabilistic.Tutorials.MultinomialRegression);
//tutorialClass = typeof(Microsoft.ML.Probabilistic.Tutorials.RecommenderSystem);
//tutorialClass = typeof(Microsoft.ML.Probabilistic.Tutorials.StudentSkills);
//tutorialClass = typeof(Microsoft.ML.Probabilistic.Tutorials.WetGrassSprinklerRain);
#endif
if (tutorialClass != null)
{
// Run the specified tutorial
RunTutorial(tutorialClass);
}
#if NETFULL
else
{
InferenceEngine.Visualizer = new WindowsVisualizer();
// Show all tutorials, in a browser
IAlgorithm[] algs = InferenceEngine.GetBuiltInAlgorithms();
// Avoid max product in the examples browser, as none of the examples apply.
List <IAlgorithm> algList = new List <IAlgorithm>(algs);
algList.RemoveAll(alg => alg is MaxProductBeliefPropagation);
ExamplesViewer tview = new ExamplesViewer(typeof(RunMe), algList.ToArray());
tview.RunBrowser();
}
#endif
}