public LinRegressionResults GetRegressionResult(GadgetParameters gadgetOptions, List <string> columnNames, List <DictionaryDTO> inputDtoList, IEnumerable <EwavDataFilterCondition> ewavDataFilters, List <EwavRule_Base> rules, string filterString = "")
{
if (gadgetOptions.UseAdvancedDataFilter)
{
dh = new DashboardHelper(gadgetOptions, filterString, rules);
gadgetOptions.UseAdvancedDataFilter = true;
gadgetOptions.AdvancedDataFilterText = filterString;
}
else
{
dh = new DashboardHelper(gadgetOptions, ewavDataFilters, rules);
}
DataTable dt;
LinRegressionResults results = new LinRegressionResults();
try
{
dt = dh.GenerateTable(columnNames, gadgetOptions);
}
catch (Exception e)
{
results.ErrorMessage = e.Message;
return(results);
}
Dictionary <string, string> inputVariableList = RegressionManager.ConvertDtoToDic(inputDtoList);
StatisticsRepository.LinearRegression linearRegression = new StatisticsRepository.LinearRegression();
StatisticsRepository.LinearRegression.LinearRegressionResults regressionResults = linearRegression.LinearRegression(inputVariableList, dt);
results.RegressionResults = RegressionManager.ConvertToLinRegResults(regressionResults);
results.CorrelationCoefficient = results.RegressionResults.CorrelationCoefficient;
results.RegressionDf = results.RegressionResults.RegressionDf;
results.RegressionF = results.RegressionResults.RegressionF;
results.RegressionMeanSquare = results.RegressionResults.RegressionMeanSquare;
results.RegressionSumOfSquares = results.RegressionResults.RegressionSumOfSquares;
results.ResidualsDf = results.RegressionResults.ResidualsDf;
results.ResidualsMeanSquare = results.RegressionResults.ResidualsMeanSquare;
results.ResidualsSumOfSquares = results.RegressionResults.ResidualsSumOfSquares;
results.TotalDf = results.RegressionResults.TotalDf;
results.TotalSumOfSquares = results.RegressionResults.TotalSumOfSquares;
results.Variables = results.RegressionResults.Variables;
if (results.RegressionResults.ErrorMessage != null)
{
results.ErrorMessage = results.RegressionResults.ErrorMessage.Replace("<tlt>", string.Empty).Replace("</tlt>", string.Empty);
}
return(results);
}
/// <summary>
/// GetFactory that converts LogisticRegressionResults values to LogRessionResults(custom) class.
/// </summary>
/// <param name="logisticRegressionResults"></param>
/// <returns></returns>
internal static LinRegressionResults ConvertToLinRegResults(StatisticsRepository.LinearRegression.LinearRegressionResults linearRegressionResults)
{
LinRegressionResults linRegResults = new LinRegressionResults();
linRegResults.CorrelationCoefficient = linearRegressionResults.correlationCoefficient;
linRegResults.RegressionDf = linearRegressionResults.regressionDf;
linRegResults.RegressionF = linearRegressionResults.regressionF;
linRegResults.RegressionMeanSquare = linearRegressionResults.regressionMeanSquare;
linRegResults.RegressionSumOfSquares = linearRegressionResults.regressionSumOfSquares;
linRegResults.ResidualsDf = linearRegressionResults.residualsDf;
linRegResults.ResidualsMeanSquare = linearRegressionResults.residualsMeanSquare;
linRegResults.ResidualsSumOfSquares = linearRegressionResults.residualsSumOfSquares;
linRegResults.TotalDf = linearRegressionResults.totalDf;
linRegResults.TotalSumOfSquares = linearRegressionResults.totalSumOfSquares;
linRegResults.Variables = ConvertToVariableClass(linearRegressionResults.variables);
linRegResults.ErrorMessage = linearRegressionResults.errorMessage;
return(linRegResults);
}
public ScatterDataDTO GenerateTable(GadgetParameters gadgetOptions,
IEnumerable <EwavDataFilterCondition> ewavDataFilters, List <EwavRule_Base> rules, string filterString = "")
{
List <ListOfStringClass> lls = new List <ListOfStringClass>();
if (gadgetOptions.UseAdvancedDataFilter)
{
dh = new DashboardHelper(gadgetOptions, filterString, rules);
gadgetOptions.UseAdvancedDataFilter = true;
gadgetOptions.AdvancedDataFilterText = filterString;
}
else
{
dh = new DashboardHelper(gadgetOptions, ewavDataFilters, rules);
}
MyString ms = new MyString();
string xAxisVar = gadgetOptions.MainVariableName;
string yAxisVar = gadgetOptions.CrosstabVariableName;
List <string> columns = new List <string>();
columns.Add(xAxisVar);
columns.Add(yAxisVar);
DataTable dt = dh.GenerateTable(columns, gadgetOptions);
List <NumericDataValue> dataValues = new List <NumericDataValue>();
NumericDataValue minValue = null;
NumericDataValue maxValue = null;
//regressTable.FieldsList.Fields
//foreach (DataRow row in regressTable.Rows)
foreach (DataRow row in dt.Rows)
{
//if (regressTable.GetValueAtRow(yAxisVar, row).Equals(DBNull.Value) || regressTable.GetValueAtRow(xAxisVar, row).Equals(DBNull.Value))
if (row[yAxisVar].Equals(DBNull.Value) || row[xAxisVar].Equals(DBNull.Value))
{
continue;
}
NumericDataValue currentValue = new NumericDataValue()
{
DependentValue = Convert.ToDecimal(row[yAxisVar]), IndependentValue = Convert.ToDecimal(row[xAxisVar])
};
//NumericDataValue currentValue = new NumericDataValue() { DependentValue = Convert.ToDecimal(regressTable.GetValueAtRow(yAxisVar, row)), IndependentValue = Convert.ToDecimal(regressTable.GetValueAtRow(xAxisVar, row)) };
dataValues.Add(currentValue);
if (minValue == null)
{
minValue = currentValue;
}
else
{
if (currentValue.IndependentValue < minValue.IndependentValue)
{
minValue = currentValue;
}
}
if (maxValue == null)
{
maxValue = currentValue;
}
else
{
if (currentValue.IndependentValue > maxValue.IndependentValue)
{
maxValue = currentValue;
}
}
}
StatisticsRepository.LinearRegression linearRegression = new StatisticsRepository.LinearRegression();
Dictionary <string, string> inputVariableList = new Dictionary <string, string>();
inputVariableList.Add(yAxisVar, "dependvar");
inputVariableList.Add("intercept", "true");
inputVariableList.Add("includemissing", "false");
inputVariableList.Add("p", "0.95");
inputVariableList.Add(xAxisVar, "unsorted");
StatisticsRepository.LinearRegression.LinearRegressionResults regresResults = linearRegression.LinearRegression(inputVariableList, dt);
LinRegressionResults results = new LinRegressionResults();
results = RegressionManager.ConvertToLinRegResults(regresResults);
//results.CorrelationCoefficient = results.RegressionResults.CorrelationCoefficient;
//results.RegressionDf = results.RegressionResults.RegressionDf;
//results.RegressionF = results.RegressionResults.RegressionF;
//results.RegressionMeanSquare = results.RegressionResults.RegressionMeanSquare;
//results.RegressionSumOfSquares = results.RegressionResults.RegressionSumOfSquares;
//results.ResidualsDf = results.RegressionResults.ResidualsDf;
//results.ResidualsMeanSquare = results.RegressionResults.ResidualsMeanSquare;
//results.ResidualsSumOfSquares = results.RegressionResults.ResidualsSumOfSquares;
//results.TotalDf = results.RegressionResults.TotalDf;
//results.TotalSumOfSquares = results.RegressionResults.TotalSumOfSquares;
//results.Variables = results.RegressionResults.Variables;
if (results.ErrorMessage != null)
{
results.ErrorMessage = results.ErrorMessage.Replace("<tlt>", string.Empty).Replace("</tlt>", string.Empty);
}
ScatterDataDTO scatterDTO = new ScatterDataDTO();
scatterDTO.DataValues = dataValues;
scatterDTO.RegresResults = results;
scatterDTO.MinValue = minValue;
scatterDTO.MaxValue = maxValue;
//RegressionManager lrm = new RegressionManager();
//lls = lrm.ConvertDataTableToList(dt);
//return new List<ListOfStringClass>();
return(scatterDTO);
}
