void sctrCtxRegResults_Completed(object sender, EventArgs e)
{
InvokeOperation <LinRegressionResults> result = (InvokeOperation <LinRegressionResults>)sender;
if (result.HasError)
{
ex = result.Error;
result.MarkErrorAsHandled();
}
//else
//{
LinRegressionResults returnedData = ((InvokeOperation <LinRegressionResults>)sender).Value;
_rresultsCompleted(returnedData, null);
//}
}
/// <summary>
/// Completion for regresion results Table
/// </summary>
/// <param name="result"></param>
/// <param name="e"></param>
private void GetRegressionResultsCompleted(LinRegressionResults result, Exception e)
{
if (e != null)
{
NotificationEventArgs <Exception> notification = new NotificationEventArgs <Exception>("", e);
this.Notify(ErrorNotice, notification);
}
else
{
this.RegressionResults = result;
if (this.RegressionResults == null)
{
Exception exp = new Exception(SharedStrings.NO_RECORDS_SELECTED.ToString());
this.Notify(ErrorNotice, new NotificationEventArgs <Exception>("", exp));
}
else
{
this.Notify(RegressResultsLoadedEvent, new NotificationEventArgs <Exception>());
}
}
}
internal LinRegressionResults FormatLinRegressionResults(LinRegressionResults LinRegressionResults)
{
LinRegressionResults.RegressionSumOfSquares = Convert.ToDouble(LinRegressionResults.RegressionSumOfSquares.ToString("F4"));
LinRegressionResults.RegressionMeanSquare = Convert.ToDouble(LinRegressionResults.RegressionMeanSquare.ToString("F4"));
LinRegressionResults.RegressionF = Convert.ToDouble(LinRegressionResults.RegressionF.ToString("F4"));
LinRegressionResults.ResidualsSumOfSquares = Convert.ToDouble(LinRegressionResults.ResidualsSumOfSquares.ToString("F4"));
LinRegressionResults.ResidualsMeanSquare = Convert.ToDouble(LinRegressionResults.ResidualsMeanSquare.ToString("F4"));
LinRegressionResults.TotalSumOfSquares = Convert.ToDouble(LinRegressionResults.TotalSumOfSquares.ToString("F4"));
LinRegressionResults.CorrelationCoefficient = Convert.ToDouble(LinRegressionResults.CorrelationCoefficient.ToString("F2"));
foreach (var item in LinRegressionResults.Variables)
{
item.Coefficient = Convert.ToDouble(item.Coefficient.ToString("F3"));
item.StdError = Convert.ToDouble(item.StdError.ToString("F3"));
item.Ftest = Convert.ToDouble(item.Ftest.ToString("F4"));
item.P = Convert.ToDouble(item.P.ToString("F6"));
}
return(LinRegressionResults);
}
// POST api/<controller>
public HttpResponseMessage Post([FromBody] JObject value)
{
LinearRegressionDomainService LinearRegressionDomainService = new LinearRegressionDomainService();
GadgetParameters GadgetParameters;
ControllerCommon CommonClass = new ControllerCommon();
List <EwavRule_Base> Rules = new List <EwavRule_Base>();
JObject gadgetJSON = (JObject)value["gadget"];
List <EwavDataFilterCondition> dashboardFilters = new List <EwavDataFilterCondition>();
GadgetParameters = new GadgetParameters();
GadgetParameters.DatasourceName = gadgetJSON["@DatasourceName"].ToString();
GadgetParameters.InputVariableList = new Dictionary <string, string>();
GadgetParameters.TableName = CommonClass.GetDatabaseObject(GadgetParameters.DatasourceName);
Mapper Mapper = new Controllers.Mapper();
Rules = CommonClass.ReadRules(value);
dashboardFilters = CommonClass.GetFilters(value);
GadgetParameters.GadgetFilters = CommonClass.GetFilters(gadgetJSON, true);
List <string> columnNames = new List <string>();
Dictionary <string, string> inputVariableList = Mapper.MapJSONToRegressionInputVariableList(gadgetJSON);
foreach (KeyValuePair <string, string> kvp in inputVariableList)
{
if (kvp.Value.ToLower().Equals("unsorted") || kvp.Value.ToLower().Equals("dependvar") || kvp.Value.ToLower().Equals("weightvar") || kvp.Value.ToLower().Equals("matchvar"))
{
columnNames.Add(kvp.Key);
}
else if (kvp.Value.ToLower().Equals("discrete"))
{
columnNames.Add(kvp.Key);
}
}
List <DictionaryDTO> inputDtoList = new List <DictionaryDTO>();
inputDtoList = Mapper.MapDictToList(inputVariableList);
LinRegressionResults LinRegressionResults = LinearRegressionDomainService.GetRegressionResult(
GadgetParameters,
columnNames,
inputDtoList,
dashboardFilters,
Rules,
CommonClass.AdvancedDataFilterString);
LinRegressionResults = Mapper.FormatLinRegressionResults(LinRegressionResults);
var obj = new HttpResponseMessage()
{
Content = new StringContent(Newtonsoft.Json.JsonConvert.SerializeObject(LinRegressionResults))//dt.GetJson())
};
obj.Content.Headers.ContentType = new MediaTypeHeaderValue("application/json");
return(obj);
}
