public void Algorithm_Sample()
{
Model model = CreateModel();
model.Algorithm.AddCommand(new AlgorithmCommand("engine: set1", "p1=0"));
var measurement = new Measurement();
var client = new Client {
Model = model, Measurement = measurement
};
client.Init();
//
// user inserts "user-define command" to engine's algorithm;
//
// plugin definition (unique and parameters)
const string commandUnique = "pluginB_dependency";
const string commandName = "Command B";
const string commandParameters = "parameter1=P1; parameter2=P2; material1=M1; material2=M2; threshold=0.4";
var command_Plugin_B_v2 = new UserDefinedCommand(client, commandUnique, commandName, commandParameters);
model.Algorithm.AddCommand(command_Plugin_B_v2);
var algorithmExecutor = new AlgorithmExecuter(model);
algorithmExecutor.Run();
var modelDataEntity = client.DataFramework.GetDataEntity <IModelDataEntity>();
Assert.AreEqual(0.1, modelDataEntity.GetParameterNominal("P1"));
Assert.AreEqual(0.4, modelDataEntity.GetParameterNominal("P2"));
}
public void Training_CreateModel_SaveToFile()
{
var modelFile = new DataFile(Path.Combine(Path.GetTempPath(), "model.dat"));
Model model = CreateModel("trainingModel");
var client = new Client {
Model = model, Measurement = new Measurement()
};
client.Init();
var addMessageToHistory = new UserDefinedCommand(client, "message_to_history", "Add message to model history", "message=training");
var saveModelToFile = new UserDefinedCommand(client, "save_model_to_file", "Save model to file", String.Format("file={0}", modelFile.File));
model.Algorithm.AddCommand(addMessageToHistory);
model.Algorithm.AddCommand(saveModelToFile);
var algorithmExecutor = new AlgorithmExecuter(model);
algorithmExecutor.Run();
Assert.AreEqual("training", model.History);
}
public void Algorithm_Sample()
{
Model model = CreateModel();
model.Algorithm.AddCommand(new AlgorithmCommand("engine: set1", "p1=0"));
var measurement = new Measurement();
var client = new Client {Model = model, Measurement = measurement};
client.Init();
//
// user inserts "user-define command" to engine's algorithm;
//
// plugin definition (unique and parameters)
const string commandUnique = "pluginB_dependency";
const string commandName = "Command B";
const string commandParameters = "parameter1=P1; parameter2=P2; material1=M1; material2=M2; threshold=0.4";
var command_Plugin_B_v2 = new UserDefinedCommand(client, commandUnique, commandName, commandParameters);
model.Algorithm.AddCommand(command_Plugin_B_v2);
var algorithmExecutor = new AlgorithmExecuter(model);
algorithmExecutor.Run();
var modelDataEntity = client.DataFramework.GetDataEntity<IModelDataEntity>();
Assert.AreEqual(0.1, modelDataEntity.GetParameterNominal("P1"));
Assert.AreEqual(0.4, modelDataEntity.GetParameterNominal("P2"));
}
public void Training_CreateModel_SaveToFile()
{
var modelFile = new DataFile(Path.Combine(Path.GetTempPath(), "model.dat"));
Model model = CreateModel("trainingModel");
var client = new Client { Model = model, Measurement = new Measurement() };
client.Init();
var addMessageToHistory = new UserDefinedCommand(client, "message_to_history", "Add message to model history", "message=training");
var saveModelToFile = new UserDefinedCommand(client, "save_model_to_file", "Save model to file", String.Format("file={0}", modelFile.File));
model.Algorithm.AddCommand(addMessageToHistory);
model.Algorithm.AddCommand(saveModelToFile);
var algorithmExecutor = new AlgorithmExecuter(model);
algorithmExecutor.Run();
Assert.AreEqual("training", model.History);
}