test analysis output

cmsWebApp/src/performa/form/TestAnalysisFP.java

@@ -36,9 +36,9 @@ public class TestAnalysisFP extends ORMProcessFormProcessor
         
         try
         {
-            loadData(testInput, process.getTransaction());
+            SingleValueTableModel model = loadData(testInput, process.getTransaction());
             
-            ExcelExporter.ExportAppender    excelRenderer   = getExportAppender(testInput.getCSV());
+            ExcelExporter.ExportAppender    excelRenderer   = getExportAppender(model);
             excelRenderer.export(bos);
             bytes = bos.toByteArray();
         }
@@ -55,7 +55,7 @@ public class TestAnalysisFP extends ORMProcessFormProcessor
         };
     }
     
-    private static ExcelExporter.ExportAppender getExportAppender(BinaryContent file) throws IOException
+    private static ExcelExporter.ExportAppender getExportAppender(SingleValueTableModel model) throws IOException
     {
         Properties props = new Properties();
         props.load(TestAnalysisFP.class.getClassLoader().getResourceAsStream("excel-styles.properties"));
@@ -67,7 +67,7 @@ public class TestAnalysisFP extends ORMProcessFormProcessor
         
         ExcelExporter.ExportAppender    exportAppender      = new ExcelExporter(props).getAppender();
         
-        exportAppender.appendTable("New Sheet", 1, getExcelContent(file));
+        exportAppender.appendTable("New Sheet", 0, model);
         
         return exportAppender;
     }
@@ -81,8 +81,9 @@ public class TestAnalysisFP extends ORMProcessFormProcessor
     }
     
     
-    public void loadData(TestInput testInput, ObjectTransaction objTran)
+    public SingleValueTableModel loadData(TestInput testInput, ObjectTransaction objTran)
     {
+        SingleValueTableModel   model           = null;
         BufferedReader          bReader         = null;
         String                  line            = "";
         String                  csvSeparator    = ",";
@@ -128,7 +129,7 @@ public class TestAnalysisFP extends ORMProcessFormProcessor
                 }
             }
 
-            AnalysisEngine.analyseAnswers(answers.toArray(new Answer[0]), testInput.getLevel());
+            model = AnalysisEngine.analyseAnswers(answers.toArray(new Answer[0]), testInput.getLevel());
             
         }
         catch (FileNotFoundException ex)
@@ -161,6 +162,8 @@ public class TestAnalysisFP extends ORMProcessFormProcessor
                 throw new NestedException(ex);
             }
         }
+        
+        return model;
     }
     
 

cmsWebApp/src/performa/utils/AnalysisEngine.java

@@ -11,11 +11,15 @@ import oneit.objstore.ObjectTransaction;
 import oneit.objstore.rdbms.filters.EqualsFilter;
 import oneit.objstore.rdbms.filters.GreaterThanEqualFilter;
 import oneit.objstore.rdbms.filters.LessThanEqualFilter;
+import oneit.utils.MultiHashtable;
+import oneit.utils.table.SingleValueTableModel;
 import performa.orm.Answer;
+import performa.orm.Candidate;
 import performa.orm.Factor;
 import performa.orm.FactorQuestionLink;
 import performa.orm.FactorScoreResult;
 import performa.orm.Level;
+import performa.orm.types.QuestionType;
 
 /**
  *
@@ -24,13 +28,26 @@ import performa.orm.Level;
 public class AnalysisEngine 
 {
   
-    public static void analyseAnswers(Answer[] answers, Level level)
+    public static SingleValueTableModel analyseAnswers(Answer[] answers, Level level)
     {
     
+        SingleValueTableModel               model               =   new SingleValueTableModel();
         ObjectTransaction                   objTran             =   level.getTransaction();
+        MultiHashtable<Candidate, Answer>   answersByCandidate  =   new MultiHashtable<>();
+        
+        answersByCandidate.groupValues(answers, Answer.pipesAnswer().toCandidate());
+        
+        int     index   =   0;
+        
+        for (Candidate candidate : answersByCandidate.keySet())
+        {           
+            int                     rowNumber       =   0;
+            int                     colNumber       =   ( index * 3 ) + 1;
             Map<Factor, Integer>    factorScoreMap  =   new HashMap<>();
             
-        for (Answer answer : answers)
+            model.addCell(rowNumber++, colNumber, new SingleValueTableModel.CellModel(candidate.getFirstName(), ""));
+            
+            for (Answer answer : answersByCandidate.getValuesForKey(candidate))
             {
                 FactorQuestionLink[]    links   = FactorQuestionLink.SearchByAll()
                                                                 .andQuestion(new EqualsFilter<>(answer.getQuestion()))
@@ -47,14 +64,19 @@ public class AnalysisEngine
                         factorScore += factorScoreMap.get(factor);
                     }
 
-                if(link.getReverseScore().equals("Yes"))
+                    if(link.getReverseScore())
+                    {
+                        if(answer.getQuestion().getSection().getQuestionType() == QuestionType.IPSATIVE)
                         {
-                    // ipsative is stored in quest_hdr. bo not created yet
-                    
                             factorScore += (10 - answer.getAnswerNo());
                         }
                         else
                         {
+                            factorScore += (8 - answer.getAnswerNo());
+                        }
+                    }
+                    else
+                    {
                         factorScore += answer.getAnswerNo();
                     }
 
@@ -67,6 +89,11 @@ public class AnalysisEngine
                 Factor  factor      = entrySet.getKey();
                 Integer factorScore = entrySet.getValue();
 
+                if(index == 0)
+                {
+                    model.addCell(rowNumber, 0, new SingleValueTableModel.CellModel(factor.getDescription(), ""));
+                }
+                
                 FactorScoreResult result    = FactorScoreResult.SearchByFactorScore()
                                                             .andFactor(new EqualsFilter<>(factor))
                                                             .andLevel(new EqualsFilter<>(level))
@@ -76,9 +103,18 @@ public class AnalysisEngine
 
 
                 int score   = result != null ? result.getColorCode().getWeightage() : 0;
-            System.out.println("score :: " + score);
 
                 // TODO: calculate normalised score based on importance
+
+                model.addCell(rowNumber, colNumber, new SingleValueTableModel.CellModel(String.valueOf(score), ""));
+                model.addCell(rowNumber, colNumber + 1, new SingleValueTableModel.CellModel(result != null ? result.getColorCode().getDescription() : "", ""));
+                model.addCell(rowNumber++, colNumber + 2, new SingleValueTableModel.CellModel(result != null ? result.getNarrative().getGraphicNotes(): "", ""));
+
+            }
+            
+            index++;
         }
+                
+        return model;
     }
 }
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