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);
}
public string BuildInputParams(
string chartType,
string chartTitle,
string independentTitle,
string dependentTitle,
string independentValueFormat,
string dependentValueFormat,
string interval,
string intervalUnit,
object startFrom,
DataTable regressionTable)
{
StringBuilder chartLineSeries = new StringBuilder();
string independentValueType = "";
string dependentValueType = "";
chartType = chartType.Replace("\"", "");
chartTitle = chartTitle.Replace("\"", "");
independentTitle = independentTitle.Replace("\"", "");
dependentTitle = dependentTitle.Replace("\"", "");
switch (chartType.ToUpper().Replace(" ", ""))
{
case SilverlightStatics.Area:
chartType = SilverlightStatics.Area;
break;
case SilverlightStatics.Column:
chartType = SilverlightStatics.Bar;
break;
case SilverlightStatics.Bubble:
chartType = SilverlightStatics.Bubble;
break;
case SilverlightStatics.EpiCurve:
chartType = SilverlightStatics.Histogram;
break;
case SilverlightStatics.Bar:
chartType = SilverlightStatics.RotatedBar;
break;
case SilverlightStatics.Line:
chartType = SilverlightStatics.Line;
break;
case SilverlightStatics.Pie:
chartType = SilverlightStatics.Pie;
break;
case SilverlightStatics.Scatter:
chartType = SilverlightStatics.Scatter;
break;
case SilverlightStatics.Stacked:
chartType = SilverlightStatics.Stacked;
break;
case SilverlightStatics.TreeMap:
chartType = SilverlightStatics.TreeMap;
break;
default:
chartType = SilverlightStatics.Bar;
break;
}
chartLineSeries.Append("chartLineSeries=");
DataTable distinct = regressionTable.DefaultView.ToTable(true, "SeriesName");
if (regressionTable.Rows.Count == 0)
{
return string.Empty;
}
foreach (DataRow row in distinct.Rows)
{
string seriesName = row["SeriesName"].ToString();
string filter = string.Format("SeriesName = '{0}'", seriesName);
DataRow[] regressionData = regressionTable.Select(filter);
if (chartLineSeries.ToString().EndsWith("chartLineSeries=") == false)
{
chartLineSeries.Append(SilverlightStatics.SeparateLineSeries);
}
chartLineSeries.Append("(");
chartLineSeries.Append("LineSeriesTitle");
chartLineSeries.Append(seriesName);
chartLineSeries.Append("LineSeriesTitle");
Type indepValueType = typeof(string);
indepValueType = regressionData[0]["Predictor"].GetType();
independentValueType = indepValueType.ToString();
chartLineSeries.Append(SilverlightStatics.IndependentValueFormat);
chartLineSeries.Append(independentValueFormat);
chartLineSeries.Append(SilverlightStatics.IndependentValueFormat);
chartLineSeries.Append(SilverlightStatics.DependentValueFormat);
chartLineSeries.Append(dependentValueFormat);
chartLineSeries.Append(SilverlightStatics.DependentValueFormat);
chartLineSeries.Append(SilverlightStatics.LineSeriesDataString);
foreach (DataRow regression in regressionData)
{
if (regression["Predictor"] is DateTime)
{
string dateTimeString = ((DateTime)regression["Predictor"]).ToString(_dateTimeFormat);
chartLineSeries.Append(dateTimeString);
}
else
{
chartLineSeries.Append(regression["Predictor"].ToString());
}
chartLineSeries.Append(SilverlightStatics.SeparateIndDepValues);
chartLineSeries.Append(regression["Response"].ToString());
chartLineSeries.Append(SilverlightStatics.SeparateDataPoints);
}
if (chartLineSeries.ToString().EndsWith(SilverlightStatics.SeparateDataPoints))
{
string series = chartLineSeries.ToString().Substring(0, chartLineSeries.Length - SilverlightStatics.SeparateDataPoints.Length);
chartLineSeries = new StringBuilder();
chartLineSeries.Append(series);
}
chartLineSeries.Append(SilverlightStatics.LineSeriesDataString);
}
if (chartType == SilverlightStatics.Scatter)
{
List<NumericDataValue> dataValues = new List<NumericDataValue>();
NumericDataValue minValue = null;
NumericDataValue maxValue = null;
foreach (DataRow row in regressionTable.Rows)
{
if (row["Response"].Equals(DBNull.Value) || row["Predictor"].Equals(DBNull.Value))
{
continue;
}
NumericDataValue currentValue = new NumericDataValue() { DependentValue = Convert.ToDecimal(row["Response"]), IndependentValue = Convert.ToDecimal(row["Predictor"]) };
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("Response", "dependvar");
inputVariableList.Add("intercept", "true");
inputVariableList.Add("includemissing", "false");
inputVariableList.Add("p", "0.95");
inputVariableList.Add("Predictor", "unsorted");
StatisticsRepository.LinearRegression.LinearRegressionResults regresResults = linearRegression.LinearRegression(inputVariableList, regressionTable);
object[] result = new object[] { dataValues, regresResults, maxValue, minValue };
decimal coefficient = Convert.ToDecimal(regresResults.variables[0].coefficient);
decimal constant = Convert.ToDecimal(regresResults.variables[1].coefficient);
NumericDataValue newMaxValue = new NumericDataValue();
newMaxValue.IndependentValue = maxValue.IndependentValue + 1;
newMaxValue.DependentValue = (coefficient * maxValue.IndependentValue) + constant;
NumericDataValue newMinValue = new NumericDataValue();
newMinValue.IndependentValue = minValue.IndependentValue - 1;
newMinValue.DependentValue = (coefficient * minValue.IndependentValue) + constant;
chartLineSeries.Append("LineSeriesDataString)^((LineSeriesTitleLinear RegressionLineSeriesTitleIndependentValueFormatIndependentValueFormatDependentValueFormatDependentValueFormatLineSeriesDataString");
chartLineSeries.Append(newMinValue.IndependentValue.ToString());
chartLineSeries.Append("^sidv^");
chartLineSeries.Append(newMinValue.DependentValue.ToString());
chartLineSeries.Append("^&^");
chartLineSeries.Append(newMaxValue.IndependentValue.ToString());
chartLineSeries.Append("^sidv^");
chartLineSeries.Append(newMaxValue.DependentValue.ToString());
chartLineSeries.Append("LineSeriesDataString");
}
chartLineSeries.Append(")");
string inputParams = string.Empty;
if (chartType.Length > 0) inputParams += string.Format("chartType={0},", chartType);
if (chartTitle.Length > 0) inputParams += string.Format("chartTitle={0},", chartTitle);
if (independentTitle.Length > 0) inputParams += string.Format("independentLabel={0},", independentTitle);
if (dependentTitle.Length > 0) inputParams += string.Format("dependentLabel={0},", dependentTitle);
if (independentValueFormat.Length > 0) inputParams += string.Format("independentValueFormat={0},", independentValueFormat);
if (dependentValueFormat.Length > 0) inputParams += string.Format("dependentValueFormat={0},", dependentValueFormat);
if (independentValueType.Length > 0) inputParams += string.Format("independentValueType={0},", independentValueType);
if (dependentValueType.Length > 0) inputParams += string.Format("dependentValueType={0},", dependentValueType);
if (interval.Length > 0) inputParams += string.Format("interval={0},", interval);
if (intervalUnit.Length > 0) inputParams += string.Format("intervalUnit={0},", intervalUnit);
if (startFrom is DateTime)
{
startFrom = ((DateTime)startFrom).ToString(_dateTimeFormat);
}
else
{
startFrom = startFrom.ToString();
}
if (((string)startFrom).Length > 0) inputParams += string.Format("startFrom={0},", ((string)startFrom));
inputParams += chartLineSeries.Replace(",", SilverlightStatics.Comma);
return inputParams;
}
protected override void worker_DoWork(object sender, System.ComponentModel.DoWorkEventArgs e)
{
lock (syncLock)
{
Stopwatch stopwatch = new Stopwatch();
stopwatch.Start();
this.Dispatcher.BeginInvoke(new SimpleCallback(SetGadgetToProcessingState));
this.Dispatcher.BeginInvoke(new SimpleCallback(ClearResults));
string freqVar = GadgetOptions.MainVariableName;
string crosstabVar = GadgetOptions.CrosstabVariableName;
string weightVar = GadgetOptions.WeightVariableName;
string strataVar = string.Empty;
bool includeMissing = GadgetOptions.ShouldIncludeMissing;
List<string> stratas = new List<string>();
if (!string.IsNullOrEmpty(strataVar))
{
stratas.Add(strataVar);
}
try
{
RequestUpdateStatusDelegate requestUpdateStatus = new RequestUpdateStatusDelegate(RequestUpdateStatusMessage);
CheckForCancellationDelegate checkForCancellation = new CheckForCancellationDelegate(IsCancelled);
GadgetOptions.GadgetStatusUpdate += new GadgetStatusUpdateHandler(requestUpdateStatus);
GadgetOptions.GadgetCheckForCancellation += new GadgetCheckForCancellationHandler(checkForCancellation);
if (this.DataFilters != null && this.DataFilters.Count > 0)
{
GadgetOptions.CustomFilter = this.DataFilters.GenerateDataFilterString(false);
}
else
{
GadgetOptions.CustomFilter = string.Empty;
}
DataView dv = DashboardHelper.GenerateView(GadgetOptions);
List<XYChartData> dataList = new List<XYChartData>();
NumericDataValue minValue = null;
NumericDataValue maxValue = null;
foreach (DataRowView drv in dv)
{
DataRow row = drv.Row;
if (row[freqVar] != DBNull.Value && row[freqVar] != null && row[crosstabVar] != DBNull.Value && row[crosstabVar] != null)
{
XYChartData chartData = new XYChartData();
chartData.X = Convert.ToDouble(row[freqVar]);
chartData.Y = Convert.ToDouble(row[crosstabVar]);
dataList.Add(chartData);
NumericDataValue currentValue = new NumericDataValue() { DependentValue = Convert.ToDecimal(row[crosstabVar]), IndependentValue = Convert.ToDecimal(row[freqVar]) };
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(crosstabVar, "dependvar");
inputVariableList.Add("intercept", "true");
inputVariableList.Add("includemissing", "false");
inputVariableList.Add("p", "0.95");
inputVariableList.Add(freqVar, "unsorted");
StatisticsRepository.LinearRegression.LinearRegressionResults regresResults = linearRegression.LinearRegression(inputVariableList, dv.Table);
this.Dispatcher.BeginInvoke(new SetChartDataDelegate(SetChartData), dataList, regresResults, maxValue, minValue);
this.Dispatcher.BeginInvoke(new SimpleCallback(RenderFinish));
}
catch (Exception ex)
{
this.Dispatcher.BeginInvoke(new RenderFinishWithErrorDelegate(RenderFinishWithError), ex.Message);
}
finally
{
stopwatch.Stop();
Debug.Print("Column chart gadget took " + stopwatch.Elapsed.ToString() + " seconds to complete.");
Debug.Print(DashboardHelper.DataFilters.GenerateDataFilterString());
}
}
}
public LinearRegression(IAnalysisStatisticContext AnalysisStatisticContext)
{
LinearRegress = new StatisticsRepository.LinearRegression();
this.Construct(AnalysisStatisticContext);
}
protected override void worker_DoWork(object sender, System.ComponentModel.DoWorkEventArgs e)
{
lock (syncLock)
{
Configuration config = DashboardHelper.Config;
Dictionary<string, string> setProperties = new Dictionary<string, string>();
setProperties.Add("Intercept", "true");
setProperties.Add("P", 0.95.ToString());
setProperties.Add("BLabels", config.Settings.RepresentationOfYes + ";" + config.Settings.RepresentationOfNo + ";" + config.Settings.RepresentationOfMissing); // TODO: Replace Yes, No, Missing with global vars
//Dictionary<string, string> inputVariableList = (Dictionary<string, string>)e.Argument;
Stopwatch stopwatch = new Stopwatch();
stopwatch.Start();
this.Dispatcher.BeginInvoke(new SimpleCallback(SetGadgetToProcessingState));
this.Dispatcher.BeginInvoke(new SimpleCallback(ClearResults));
SetGridTextDelegate setText = new SetGridTextDelegate(SetGridText);
AddGridRowDelegate addRow = new AddGridRowDelegate(AddGridRow);
//SetGridBarDelegate setBar = new SetGridBarDelegate(SetGridBar);
System.Collections.Generic.Dictionary<string, System.Data.DataTable> Freq_ListSet = new Dictionary<string, System.Data.DataTable>();
//string customFilter = string.Empty;
List<string> columnNames = new List<string>();
foreach (KeyValuePair<string, string> kvp in GadgetOptions.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);
}
}
try
{
lock (staticSyncLock)
{
RequestUpdateStatusDelegate requestUpdateStatus = new RequestUpdateStatusDelegate(RequestUpdateStatusMessage);
CheckForCancellationDelegate checkForCancellation = new CheckForCancellationDelegate(IsCancelled);
GadgetOptions.GadgetStatusUpdate += new GadgetStatusUpdateHandler(requestUpdateStatus);
GadgetOptions.GadgetCheckForCancellation += new GadgetCheckForCancellationHandler(checkForCancellation);
DataTable regressTable = DashboardHelper.GenerateTable(columnNames);
RegressionResults results = new RegressionResults();
if (regressTable == null || regressTable.Rows.Count <= 0)
{
this.Dispatcher.BeginInvoke(new RenderFinishWithErrorDelegate(RenderFinishWithError), SharedStrings.NO_RECORDS_SELECTED);
this.Dispatcher.BeginInvoke(new SimpleCallback(SetGadgetToFinishedState));
Debug.Print("Thread stopped due to errors.");
return;
}
else if (worker.CancellationPending)
{
this.Dispatcher.BeginInvoke(new RenderFinishWithErrorDelegate(RenderFinishWithError), SharedStrings.DASHBOARD_GADGET_STATUS_OPERATION_CANCELLED);
this.Dispatcher.BeginInvoke(new SimpleCallback(SetGadgetToFinishedState));
Debug.Print("Thread cancelled");
return;
}
else
{
StatisticsRepository.LinearRegression linearRegression = new StatisticsRepository.LinearRegression();
results.regressionResults = linearRegression.LinearRegression(GadgetOptions.InputVariableList, regressTable);
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.errorMessage = results.regressionResults.errorMessage.Replace("<tlt>", string.Empty).Replace("</tlt>", string.Empty);
if (!string.IsNullOrEmpty(results.errorMessage))
{
throw new ApplicationException(results.errorMessage);
}
results.variables = new List<VariableRow>();
if (results.regressionResults.variables != null)
{
double tScore = 1.9;
while (Epi.Statistics.SharedResources.PFromT(tScore, results.residualsDf) > 0.025)
{
tScore += 0.000001;
}
foreach (StatisticsRepository.LinearRegression.VariableRow vrow in results.regressionResults.variables)
{
VariableRow nrow = new VariableRow();
nrow.coefficient = vrow.coefficient;
nrow.Ftest = vrow.Ftest;
nrow.P = vrow.P;
nrow.stdError = vrow.stdError;
nrow.variableName = vrow.variableName;
nrow.coefficientLower = nrow.coefficient - tScore * nrow.stdError;
nrow.coefficientUpper = nrow.coefficient + tScore * nrow.stdError;
results.variables.Add(nrow);
}
results.regressionFp = Epi.Statistics.SharedResources.PFromF(results.regressionF, results.regressionDf, results.residualsDf);
this.Dispatcher.BeginInvoke(new SimpleCallback(RenderRegressionHeader));
int rowCount = 1;
foreach (VariableRow row in results.variables)
{
this.Dispatcher.Invoke(addRow, grdRegress, 30);
string displayValue = row.variableName;
this.Dispatcher.BeginInvoke(setText, grdRegress, new TextBlockConfig(StringLiterals.SPACE + displayValue + StringLiterals.SPACE, new Thickness(2, 0, 2, 0), VerticalAlignment.Center, HorizontalAlignment.Left, TextAlignment.Left, rowCount, 0, Visibility.Visible));
this.Dispatcher.BeginInvoke(setText, grdRegress, new TextBlockConfig(StringLiterals.SPACE + row.coefficient.ToString("F3") + StringLiterals.SPACE, new Thickness(2, 0, 2, 0), VerticalAlignment.Center, HorizontalAlignment.Right, TextAlignment.Right, rowCount, 1, Visibility.Visible));
this.Dispatcher.BeginInvoke(setText, grdRegress, new TextBlockConfig(StringLiterals.SPACE + row.coefficientLower.ToString("F3") + StringLiterals.SPACE, new Thickness(2, 0, 2, 0), VerticalAlignment.Center, HorizontalAlignment.Right, TextAlignment.Right, rowCount, 2, Visibility.Visible));
this.Dispatcher.BeginInvoke(setText, grdRegress, new TextBlockConfig(StringLiterals.SPACE + row.coefficientUpper.ToString("F3") + StringLiterals.SPACE, new Thickness(2, 0, 2, 0), VerticalAlignment.Center, HorizontalAlignment.Right, TextAlignment.Right, rowCount, 3, Visibility.Visible));
this.Dispatcher.BeginInvoke(setText, grdRegress, new TextBlockConfig(StringLiterals.SPACE + row.stdError.ToString("F3") + StringLiterals.SPACE, new Thickness(2, 0, 2, 0), VerticalAlignment.Center, HorizontalAlignment.Right, TextAlignment.Right, rowCount, 4, Visibility.Visible));
this.Dispatcher.BeginInvoke(setText, grdRegress, new TextBlockConfig(StringLiterals.SPACE + row.Ftest.ToString("F4") + StringLiterals.SPACE, new Thickness(2, 0, 2, 0), VerticalAlignment.Center, HorizontalAlignment.Right, TextAlignment.Right, rowCount, 5, Visibility.Visible));
this.Dispatcher.BeginInvoke(setText, grdRegress, new TextBlockConfig(StringLiterals.SPACE + row.P.ToString("F6") + StringLiterals.SPACE, new Thickness(2, 0, 2, 0), VerticalAlignment.Center, HorizontalAlignment.Right, TextAlignment.Right, rowCount, 6, Visibility.Visible));
rowCount++;
}
//this.Dispatcher.BeginInvoke(new AddGridFooterDelegate(RenderFrequencyFooter), rowCount, count);
this.Dispatcher.BeginInvoke(new SimpleCallback(DrawRegressionBorders));
}
}
this.Dispatcher.BeginInvoke(new RenderGridDelegate(RenderRegressionResults), results);
this.Dispatcher.BeginInvoke(new SimpleCallback(SetGadgetToFinishedState));
}
}
catch (Exception ex)
{
this.Dispatcher.BeginInvoke(new RenderFinishWithErrorDelegate(RenderFinishWithError), ex.Message);
this.Dispatcher.BeginInvoke(new SimpleCallback(SetGadgetToFinishedState));
}
finally
{
stopwatch.Stop();
Debug.Print("Linear regression gadget took " + stopwatch.Elapsed.ToString() + " seconds to complete with " + DashboardHelper.RecordCount.ToString() + " records and the following filters:");
Debug.Print(DashboardHelper.DataFilters.GenerateDataFilterString());
}
}
//gridCells.singleTableResults = new StatisticsRepository.cTable().SigTable((double)gridCells.yyVal, (double)gridCells.ynVal, (double)gridCells.nyVal, (double)gridCells.nnVal, 0.95);
}
public string BuildInputParams(
string chartType,
string chartTitle,
string independentTitle,
string dependentTitle,
string independentValueFormat,
string dependentValueFormat,
string interval,
string intervalUnit,
object startFrom,
DataTable regressionTable)
{
StringBuilder chartLineSeries = new StringBuilder();
string independentValueType = "";
string dependentValueType = "";
chartType = chartType.Replace("\"", "");
chartTitle = chartTitle.Replace("\"", "");
independentTitle = independentTitle.Replace("\"", "");
dependentTitle = dependentTitle.Replace("\"", "");
switch (chartType.ToUpperInvariant().Replace(" ", ""))
{
case SilverlightStatics.Area:
chartType = SilverlightStatics.Area;
break;
case SilverlightStatics.Column:
chartType = SilverlightStatics.Bar;
break;
case SilverlightStatics.Bubble:
chartType = SilverlightStatics.Bubble;
break;
case SilverlightStatics.EpiCurve:
chartType = SilverlightStatics.Histogram;
break;
case SilverlightStatics.Bar:
chartType = SilverlightStatics.RotatedBar;
break;
case SilverlightStatics.Line:
chartType = SilverlightStatics.Line;
break;
case SilverlightStatics.Pie:
chartType = SilverlightStatics.Pie;
break;
case SilverlightStatics.Scatter:
chartType = SilverlightStatics.Scatter;
break;
case SilverlightStatics.Stacked:
chartType = SilverlightStatics.Stacked;
break;
case SilverlightStatics.TreeMap:
chartType = SilverlightStatics.TreeMap;
break;
default:
chartType = SilverlightStatics.Bar;
break;
}
chartLineSeries.Append("chartLineSeries=");
DataTable distinct = regressionTable.DefaultView.ToTable(true, "SeriesName");
if (regressionTable.Rows.Count == 0)
{
return(string.Empty);
}
foreach (DataRow row in distinct.Rows)
{
string seriesName = row["SeriesName"].ToString();
string filter = string.Format("SeriesName = '{0}'", seriesName);
DataRow[] regressionData = regressionTable.Select(filter);
if (chartLineSeries.ToString().EndsWith("chartLineSeries=") == false)
{
chartLineSeries.Append(SilverlightStatics.SeparateLineSeries);
}
chartLineSeries.Append("(");
chartLineSeries.Append("LineSeriesTitle");
chartLineSeries.Append(seriesName);
chartLineSeries.Append("LineSeriesTitle");
Type indepValueType = typeof(string);
indepValueType = regressionData[0]["Predictor"].GetType();
independentValueType = indepValueType.ToString();
chartLineSeries.Append(SilverlightStatics.IndependentValueFormat);
chartLineSeries.Append(independentValueFormat);
chartLineSeries.Append(SilverlightStatics.IndependentValueFormat);
chartLineSeries.Append(SilverlightStatics.DependentValueFormat);
chartLineSeries.Append(dependentValueFormat);
chartLineSeries.Append(SilverlightStatics.DependentValueFormat);
chartLineSeries.Append(SilverlightStatics.LineSeriesDataString);
foreach (DataRow regression in regressionData)
{
if (regression["Predictor"] is DateTime)
{
string dateTimeString = ((DateTime)regression["Predictor"]).ToString(_dateTimeFormat);
chartLineSeries.Append(dateTimeString);
}
else
{
chartLineSeries.Append(regression["Predictor"].ToString());
}
chartLineSeries.Append(SilverlightStatics.SeparateIndDepValues);
chartLineSeries.Append(regression["Response"].ToString());
chartLineSeries.Append(SilverlightStatics.SeparateDataPoints);
}
if (chartLineSeries.ToString().EndsWith(SilverlightStatics.SeparateDataPoints))
{
string series = chartLineSeries.ToString().Substring(0, chartLineSeries.Length - SilverlightStatics.SeparateDataPoints.Length);
chartLineSeries = new StringBuilder();
chartLineSeries.Append(series);
}
chartLineSeries.Append(SilverlightStatics.LineSeriesDataString);
}
if (chartType == SilverlightStatics.Scatter)
{
List <NumericDataValue> dataValues = new List <NumericDataValue>();
NumericDataValue minValue = null;
NumericDataValue maxValue = null;
foreach (DataRow row in regressionTable.Rows)
{
if (row["Response"].Equals(DBNull.Value) || row["Predictor"].Equals(DBNull.Value))
{
continue;
}
NumericDataValue currentValue = new NumericDataValue()
{
DependentValue = Convert.ToDecimal(row["Response"]), IndependentValue = Convert.ToDecimal(row["Predictor"])
};
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("Response", "dependvar");
inputVariableList.Add("intercept", "true");
inputVariableList.Add("includemissing", "false");
inputVariableList.Add("p", "0.95");
inputVariableList.Add("Predictor", "unsorted");
StatisticsRepository.LinearRegression.LinearRegressionResults regresResults = linearRegression.LinearRegression(inputVariableList, regressionTable);
object[] result = new object[] { dataValues, regresResults, maxValue, minValue };
decimal coefficient = Convert.ToDecimal(regresResults.variables[0].coefficient);
decimal constant = Convert.ToDecimal(regresResults.variables[1].coefficient);
NumericDataValue newMaxValue = new NumericDataValue();
newMaxValue.IndependentValue = maxValue.IndependentValue + 1;
newMaxValue.DependentValue = (coefficient * maxValue.IndependentValue) + constant;
NumericDataValue newMinValue = new NumericDataValue();
newMinValue.IndependentValue = minValue.IndependentValue - 1;
newMinValue.DependentValue = (coefficient * minValue.IndependentValue) + constant;
chartLineSeries.Append("LineSeriesDataString)^((LineSeriesTitleLinear RegressionLineSeriesTitleIndependentValueFormatIndependentValueFormatDependentValueFormatDependentValueFormatLineSeriesDataString");
chartLineSeries.Append(newMinValue.IndependentValue.ToString());
chartLineSeries.Append("^sidv^");
chartLineSeries.Append(newMinValue.DependentValue.ToString());
chartLineSeries.Append("^&^");
chartLineSeries.Append(newMaxValue.IndependentValue.ToString());
chartLineSeries.Append("^sidv^");
chartLineSeries.Append(newMaxValue.DependentValue.ToString());
chartLineSeries.Append("LineSeriesDataString");
}
chartLineSeries.Append(")");
string inputParams = string.Empty;
if (chartType.Length > 0)
{
inputParams += string.Format("chartType={0},", chartType);
}
if (chartTitle.Length > 0)
{
inputParams += string.Format("chartTitle={0},", chartTitle);
}
if (independentTitle.Length > 0)
{
inputParams += string.Format("independentLabel={0},", independentTitle);
}
if (dependentTitle.Length > 0)
{
inputParams += string.Format("dependentLabel={0},", dependentTitle);
}
if (independentValueFormat.Length > 0)
{
inputParams += string.Format("independentValueFormat={0},", independentValueFormat);
}
if (dependentValueFormat.Length > 0)
{
inputParams += string.Format("dependentValueFormat={0},", dependentValueFormat);
}
if (independentValueType.Length > 0)
{
inputParams += string.Format("independentValueType={0},", independentValueType);
}
if (dependentValueType.Length > 0)
{
inputParams += string.Format("dependentValueType={0},", dependentValueType);
}
if (interval.Length > 0)
{
inputParams += string.Format("interval={0},", interval);
}
if (intervalUnit.Length > 0)
{
inputParams += string.Format("intervalUnit={0},", intervalUnit);
}
if (startFrom is DateTime)
{
startFrom = ((DateTime)startFrom).ToString(_dateTimeFormat);
}
else
{
startFrom = startFrom.ToString();
}
if (((string)startFrom).Length > 0)
{
inputParams += string.Format("startFrom={0},", ((string)startFrom));
}
inputParams += chartLineSeries.Replace(",", SilverlightStatics.Comma);
return(inputParams);
}
void scatterChartWorker_DoWork(object sender, System.ComponentModel.DoWorkEventArgs e)
{
try
{
this.Dispatcher.BeginInvoke(new SimpleCallback(SetGadgetToProcessingState));
this.Dispatcher.BeginInvoke(new SimpleCallback(ClearResults));
RequestUpdateStatusDelegate requestUpdateStatus = new RequestUpdateStatusDelegate(RequestUpdateStatusMessage);
CheckForCancellationDelegate checkForCancellation = new CheckForCancellationDelegate(IsCancelled);
GadgetOptions.GadgetStatusUpdate += new GadgetStatusUpdateHandler(requestUpdateStatus);
GadgetOptions.GadgetCheckForCancellation += new GadgetCheckForCancellationHandler(checkForCancellation);
string xAxisVar = GadgetOptions.MainVariableName;
string yAxisVar = GadgetOptions.CrosstabVariableName;
List<string> columnNames = new List<string>();
columnNames.Add(xAxisVar);
columnNames.Add(yAxisVar);
DataTable regressTable = DashboardHelper.GenerateTable(columnNames);
if (regressTable == null || regressTable.Rows.Count == 0)
{
this.Dispatcher.BeginInvoke(new RenderFinishWithErrorDelegate(RenderFinishWithError), SharedStrings.NO_RECORDS_SELECTED);
this.Dispatcher.BeginInvoke(new SimpleCallback(SetGadgetToFinishedState));
return;
}
else if (worker.CancellationPending)
{
this.Dispatcher.BeginInvoke(new RenderFinishWithErrorDelegate(RenderFinishWithError), SharedStrings.DASHBOARD_GADGET_STATUS_OPERATION_CANCELLED);
this.Dispatcher.BeginInvoke(new SimpleCallback(SetGadgetToFinishedState));
System.Diagnostics.Debug.Print("Single chart thread was cancelled");
return;
}
else
{
List<NumericDataValue> dataValues = new List<NumericDataValue>();
NumericDataValue minValue = null;
NumericDataValue maxValue = null;
foreach (DataRow row in regressTable.Rows)
{
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]) };
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, regressTable);
object[] result = new object[] { dataValues, regresResults, maxValue, minValue };
e.Result = result;
this.Dispatcher.BeginInvoke(new SimpleCallback(RenderFinish));
}
}
catch (Exception ex)
{
this.Dispatcher.BeginInvoke(new RenderFinishWithErrorDelegate(RenderFinishWithError), ex.Message);
}
}
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);
}
public LinearRegression(IAnalysisStatisticContext AnalysisStatisticContext)
{
LinearRegress = new StatisticsRepository.LinearRegression();
this.Construct(AnalysisStatisticContext);
}
