本文整理汇总了C#中Class1.identify_main方法的典型用法代码示例。如果您正苦于以下问题：C# Class1.identify_main方法的具体用法？C# Class1.identify_main怎么用？C# Class1.identify_main使用的例子？那么, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类Class1的用法示例。
在下文中一共展示了Class1.identify_main方法的1个代码示例，这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞，您的评价将有助于系统推荐出更棒的C#代码示例。
示例1: IdentifyComputation
public void IdentifyComputation()
{
//set generic simulator behavior - strategy
//GenericSimulator.SimulatorBehavior = new MySincSimulatorBehavior2(); //useless - matlab DLL have different static instance
try
{
BroadcastIdentifyStateMessage("Starting calculation ..." + DateTime.Now);
logger.Log(NLog.LogLevel.Info, "starting calculation ");
//invoke matlab Identification algorithm - does it use the GenericSimulator instance configured before???
Class1 class1 = new Class1();
logger.Log(NLog.LogLevel.Debug, "class1 init");
//set experiment variables and values
MWArray v_names = new MWCellArray(new MWCharArray(Enumerable.ToArray(variable_names)));
MWArray experiment = new MWNumericArray(variable_values);
//set identification parameters
MWArray p_names = new MWCellArray(new MWCharArray(Enumerable.ToArray(parameters.Keys)));
//set worker nodes urls
//var host = AppHostBase.Instance.Config.ServiceEndpointsMetadataConfig.DefaultMetadataUri;
//var myrepository = ((AppHostBase) EndpointHost.AppHost).Container.Resolve<WorkersRepository>();
//MWArray worker_urls = new MWCellArray(new MWCharArray(myrepository.GetByModelName(modelname).Select(x => x.RestUrl).ToArray()));
MWArray p_val = new MWNumericArray(parameters.Values.Select(parameter => parameter.Value).ToArray());
MWArray p_min = new MWNumericArray(parameters.Values.Select(parameter => parameter.Min).ToArray());
MWArray p_max = new MWNumericArray(parameters.Values.Select(parameter => parameter.Max).ToArray());
MWArray p_is_fixed =
new MWLogicalArray(parameters.Values.Select(parameter => !parameter.IsActive).ToArray());
//calculate identification
Stopwatch sw = Stopwatch.StartNew();
if (IAgenerations > 0) //set gaoptions
{
MWArray generations = new MWNumericArray(IAgenerations);
MWArray populationsize = new MWNumericArray(IApopulationsize);
MWArray tolfun = new MWNumericArray(IAtolfun);
class1.identify_gaoptimset(generations, populationsize, tolfun);
} //otherwise the matlab algorithm has it's own default values
logger.Log(NLog.LogLevel.Debug, "mwarray init");
var result = class1.identify_main(experiment, p_names, p_val, p_min, p_max, p_is_fixed, v_names, modelname, masterserviceurl);
logger.Log(NLog.LogLevel.Debug, "identify_main done");
sw.Stop();
/*var fitted_params = result[1];
var fitted_param_L2Enorm = result[2];
var fitted_variablevalues = result[3];
* */
//string fittedparams = "";
//for (int i=1;i < fitted_params.
//BroadcastIdentifyStateMessage("Elapsed time " + sw.Elapsed.ToString() + " Results: " + result);//fitted_params+" "+fitted_param_L2Enorm+" " + fitted_variablevalues);
//var myresult = result.ToArray();
BroadcastIdentifyResult(result.ToArray(),sw.Elapsed,class1.identify_getssq(),class1.identify_getcomputationcycles(),class1.identify_getsimulationtime());
}
catch (Exception e)
{
//TODO handle matlab exception
BroadcastIdentifyStateMessage(e.Message+e.StackTrace);
logger.Log(NLog.LogLevel.Error,"exception during identification "+e.Message+" stacktrace:"+e.StackTrace,e);
var f = e;//.InnerException;
while (f.InnerException != null)
{
f = f.InnerException;
logger.Log(NLog.LogLevel.Error, "innerexception:" + f.Message + " stacktrace:" + f.StackTrace, f);
}
}
// StopIdentify();
FinalizeIdentify();
}