Examples of PTA_computePrecisionRecall

Examples of statechum.model.testset.PTA_computePrecisionRecall

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    partialPTA = partialPTA.cross(TestFSMAlgo.buildSet(new String[][] {
        new String[] {"a","a","a","b","a","d"}, // -
        new String[] {"a","a","a","b","a","e","f"}, // -
        new String[] {"a","a","a","b","a","c","c","c"}, // +, FN
      },mainConfiguration,converter));
    PTA_computePrecisionRecall precComputer = new PTA_computePrecisionRecall(fsm);
    precComputer.crossWith(engine);
    assertEquals("true negatives",2, precComputer.resultTN);assertEquals("true positives",0, precComputer.resultTP);
    assertEquals("false negatives",1, precComputer.resultFN);assertEquals("false positives",0, precComputer.resultFP);
    assertEquals("positives relevant",1, precComputer.pos_Rel);assertEquals("negatives relevant",2, precComputer.neg_Rel);
    assertEquals("positives retrieved",0, precComputer.pos_Ret);assertEquals("negatives retrieved",3, precComputer.neg_Ret);
  }
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Examples of statechum.model.testset.PTA_computePrecisionRecall

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    partialPTA = partialPTA.cross(TestFSMAlgo.buildSet(new String[][] {
        new String[] {"a","a","a","a","a","b","c"}, // +
        new String[] {"a","b"}, // +
        new String[] {"a","a","a","b","c"}, // +
      },mainConfiguration,converter));
    PTA_computePrecisionRecall precComputer = new PTA_computePrecisionRecall(fsm);
    precComputer.crossWith(engine);
    assertEquals("true negatives",0, precComputer.resultTN);assertEquals("true positives",3, precComputer.resultTP);
    assertEquals("false negatives",0, precComputer.resultFN);assertEquals("false positives",0, precComputer.resultFP);
    assertEquals("positives relevant",3, precComputer.pos_Rel);assertEquals("negatives relevant",0, precComputer.neg_Rel);
    assertEquals("positives retrieved",3, precComputer.pos_Ret);assertEquals("negatives retrieved",0, precComputer.neg_Ret);
  }
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Examples of statechum.model.testset.PTA_computePrecisionRecall

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    PTASequenceEngine engine = new PTA_FSMStructure(mach,null);
    SequenceSet partialPTA = engine.new SequenceSet();partialPTA.setIdentity();
    partialPTA = partialPTA.cross(TestFSMAlgo.buildSet(new String[][] {
        new String[] {"a"}, // +
      },mainConfiguration,converter));
    PTA_computePrecisionRecall precComputer = new PTA_computePrecisionRecall(fsm);
    precComputer.crossWith(engine);
   
    engine = new PTA_FSMStructure(mach,null);
    partialPTA = engine.new SequenceSet();partialPTA.setIdentity();
    partialPTA = partialPTA.cross(TestFSMAlgo.buildSet(new String[][] {
        new String[] {"a","b","b","c","c"}, // +, FN
      },mainConfiguration,converter));
    precComputer.crossWith(engine);
    assertEquals("true negatives",0, precComputer.resultTN);assertEquals("true positives",0, precComputer.resultTP);
    assertEquals("false negatives",1, precComputer.resultFN);assertEquals("false positives",0, precComputer.resultFP);
    assertEquals("positives relevant",1, precComputer.pos_Rel);assertEquals("negatives relevant",0, precComputer.neg_Rel);
    assertEquals("positives retrieved",0, precComputer.pos_Ret);assertEquals("negatives retrieved",1, precComputer.neg_Ret);
  }
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Examples of statechum.model.testset.PTA_computePrecisionRecall

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    PTASequenceEngine engine = new PTA_FSMStructure(mach,null);
    SequenceSet partialPTA = engine.new SequenceSet();partialPTA.setIdentity();
    partialPTA = partialPTA.cross(TestFSMAlgo.buildSet(new String[][] {
        new String[] {"a","b","b","c","c"}, // +
      },mainConfiguration,converter));
    PTA_computePrecisionRecall precComputer = new PTA_computePrecisionRecall(fsm);
    precComputer.crossWith(engine);
   
    engine = new PTA_FSMStructure(mach,null);
    partialPTA = engine.new SequenceSet();partialPTA.setIdentity();
    partialPTA = partialPTA.cross(TestFSMAlgo.buildSet(new String[][] {
        new String[] {"a","b","b","c","c"}, // +, FN
      },mainConfiguration,converter));
    precComputer.crossWith(engine);
    assertEquals("true negatives",0, precComputer.resultTN);assertEquals("true positives",0, precComputer.resultTP);
    assertEquals("false negatives",0, precComputer.resultFN);assertEquals("false positives",0, precComputer.resultFP);
    assertEquals("positives relevant",0, precComputer.pos_Rel);assertEquals("negatives relevant",0, precComputer.neg_Rel);
    assertEquals("positives retrieved",0, precComputer.pos_Ret);assertEquals("negatives retrieved",0, precComputer.neg_Ret);
  }
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Examples of statechum.model.testset.PTA_computePrecisionRecall

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    PTASequenceEngine engine = new PTA_FSMStructure(mach,null);
    SequenceSet partialPTA = engine.new SequenceSet();partialPTA.setIdentity();
    partialPTA = partialPTA.cross(TestFSMAlgo.buildSet(new String[][] {
        new String[] {"a","b","b","c","c","c","c"}, // +
      },mainConfiguration,converter));
    PTA_computePrecisionRecall precComputer = new PTA_computePrecisionRecall(fsm);
    precComputer.crossWith(engine);

    engine = new PTA_FSMStructure(mach,null);
    partialPTA = engine.new SequenceSet();partialPTA.setIdentity();
    partialPTA = partialPTA.cross(TestFSMAlgo.buildSet(new String[][] {
        new String[] {"a","b","b","c","c"}, // +, FN
      },mainConfiguration,converter));
    precComputer.crossWith(engine);
    assertEquals("true negatives",0, precComputer.resultTN);assertEquals("true positives",0, precComputer.resultTP);
    assertEquals("false negatives",1, precComputer.resultFN);assertEquals("false positives",0, precComputer.resultFP);
    assertEquals("positives relevant",1, precComputer.pos_Rel);assertEquals("negatives relevant",0, precComputer.neg_Rel);
    assertEquals("positives retrieved",0, precComputer.pos_Ret);assertEquals("negatives retrieved",1, precComputer.neg_Ret);
  }
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Examples of statechum.model.testset.PTA_computePrecisionRecall

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      };
      QuestionAndRestartCounter l = new QuestionAndRestartCounter(learner);
      sPlus = rpg.getExtraSequences(percent/10-1);sMinus = rpg.getAllSequences(percent/10-1);

      LearnerGraph learnt = learn(l,sMinus);
      PTA_computePrecisionRecall precRec = new PTA_computePrecisionRecall(learnt);
      PTASequenceEngine engine = new PTA_FSMStructure(graph,null);
      precRec.crossWith(sMinus);PosNegPrecisionRecall ptaPR = precRec.getPosNegPrecisionRecallNum();
      SequenceSet ptaTestSet = engine.new SequenceSet();ptaTestSet.setIdentity();
      ptaTestSet = ptaTestSet.cross(graph.wmethod.getFullTestSet(1));
      precRec.crossWith(engine);PosNegPrecisionRecall prNeg = precRec.getPosNegPrecisionRecallNum();
     
      assert questionNumber.get() == l.getQuestionCounter();
     
      // Column 0 is the name of the learner.
      // Columns 3 and 4
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Examples of statechum.model.testset.PTA_computePrecisionRecall

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    /*
    List<List<String>> data = generator.getExtraSequences(0).getData();
    for(List<String> str:data)
      System.out.println(str);
    */
    PTA_computePrecisionRecall precRec = null;
   
    {
      precRec = new PTA_computePrecisionRecall(markovD);
      precRec.crossWith(generator.getAllSequences(0));PosNegPrecisionRecall result = precRec.getPosNegPrecisionRecallNum();
      System.out.println("Markov: precision "+result.getPosprecision()+" recall: "+result.getPosrecall());
    }

    {
      precRec = new PTA_computePrecisionRecall(edsm);
      precRec.crossWith(generator.getAllSequences(0));PosNegPrecisionRecall result = precRec.getPosNegPrecisionRecallNum();
      System.out.println("EDSM: precision "+result.getPosprecision()+" recall: "+result.getPosrecall());
    }
   
    //Visualiser.updateFrame(edsm, null);
    //Visualiser.waitForKey();
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Examples of statechum.model.testset.PTA_computePrecisionRecall

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    /*
    List<List<String>> data = generator.getExtraSequences(0).getData();
    for(List<String> str:data)
      System.out.println(str);
    */
    PTA_computePrecisionRecall precRec = null;
   
    {
      precRec = new PTA_computePrecisionRecall(markovD);
      precRec.crossWith(generator.getAllSequences(0));PosNegPrecisionRecall result = precRec.getPosNegPrecisionRecallNum();
      System.out.println("Markov: precision "+result.getPosprecision()+" recall: "+result.getPosrecall());
    }

    {
      precRec = new PTA_computePrecisionRecall(edsm);
      precRec.crossWith(generator.getAllSequences(0));PosNegPrecisionRecall result = precRec.getPosNegPrecisionRecallNum();
      System.out.println("EDSM: precision "+result.getPosprecision()+" recall: "+result.getPosrecall());
    }
   
    //Visualiser.updateFrame(edsm, null);
    //Visualiser.waitForKey();
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Examples of statechum.model.testset.PTA_computePrecisionRecall

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      };
      QuestionAndRestartCounter l = new QuestionAndRestartCounter(learner);
      sPlus = rpg.getExtraSequences(percent/10-1);sMinus = rpg.getAllSequences(percent/10-1);

      LearnerGraph learnt = learn(l,sMinus);
      PTA_computePrecisionRecall precRec = new PTA_computePrecisionRecall(learnt);
      PTASequenceEngine engine = new PTA_FSMStructure(graph,null);
      precRec.crossWith(sMinus);PosNegPrecisionRecall ptaPR = precRec.getPosNegPrecisionRecallNum();
      SequenceSet ptaTestSet = engine.new SequenceSet();ptaTestSet.setIdentity();
      ptaTestSet = ptaTestSet.cross(graph.wmethod.getFullTestSet(1));
      precRec.crossWith(engine);PosNegPrecisionRecall prNeg = precRec.getPosNegPrecisionRecallNum();
     
      assert questionNumber.get() == l.getQuestionCounter();
     
      // Column 0 is the name of the learner.
      // Columns 3 and 4
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Examples of statechum.model.testset.PTA_computePrecisionRecall

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            (testSequencesB==null?"NONE":testSequencesB.getData(PTASequenceEngine.truePred)));
        */
       
        double bcrA = 0., bcrB= 0.;
        {
          PTA_computePrecisionRecall precRec = new PTA_computePrecisionRecall(stateToCorrespondingGraph.get(stateA).graph);
          if (testSequencesB != null) precRec.crossWith(testSequencesB);
          bcrA=precRec.getBCR();
        }
        {
          PTA_computePrecisionRecall precRec = new PTA_computePrecisionRecall(stateToCorrespondingGraph.get(stateB).graph);
          if (testSequencesA != null) precRec.crossWith(testSequencesA);
          bcrB=precRec.getBCR();
        }
        double multiplier = 100.;
        if (config.getGdScoreComputation() == GDScoreComputationEnum.GD_RH)
          rightHandSide = multiplier*(bcrA+bcrB)*totalOutgoing/2.;
        else
 
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