Package statechum.model.testset.PTASequenceEngine

Examples of statechum.model.testset.PTASequenceEngine.SequenceSet.cross()

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    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","a","a","b"}, // +
      },mainConfiguration,converter));
    precComputer.crossWith(engine);
    assertEquals("true negatives",0, precComputer.resultTN);assertEquals("true positives",1, precComputer.resultTP);
    assertEquals("false negatives",0, precComputer.resultFN);assertEquals("false positives",0, precComputer.resultFP);
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          }     
        });
      }
    };
    SequenceSet seq = en.new SequenceSet();seq.setIdentity();
    Map<String,String> actual = getDebugDataMap(en,seq.cross(TestFSMAlgo.buildList(new String[][] {
        new String[] {"a","a","b"},
        new String[] {"d","d"},
        new String[] {"c"}
       
    },mainConfiguration,converter)).crossWithSet(labelList(new String[] {"b","a"})));
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  public final void testPrecisionRecall_ign6() 
  {
    LearnerGraph mach = buildLearnerGraph("AM-a->AM-b->AM-c->AM","testPrecisionRecall_ign1",mainConfiguration,converter);
    PTASequenceEngine engine = new PTA_FSMStructure(mach,null);
    SequenceSet partialPTA = engine.new SequenceSet();partialPTA.setIdentity();
    partialPTA = partialPTA.cross(TestFSMAlgo.buildSet(new String[][] {
        new String[] {"a","a","a","b"}, // +
      },mainConfiguration,converter));
    PTA_computePrecisionRecall precComputer = new PTA_computePrecisionRecall(fsm);
    precComputer.crossWith(engine);
   
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          }     
        });
      }
    };
    SequenceSet seq = en.new SequenceSet();seq.setIdentity();
    Map<String,String> actual = getDebugDataMap(en,seq.cross(TestFSMAlgo.buildList(new String[][] {
        new String[] {"a","a","b"},
        new String[] {"a","a","c","c"},
        new String[] {"d","d"},
        new String[] {"c"}
       
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    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","a","a"}, // +
      },mainConfiguration,converter));
    precComputer.crossWith(engine);
    assertEquals("true negatives",0, precComputer.resultTN);assertEquals("true positives",1, precComputer.resultTP);
    assertEquals("false negatives",0, precComputer.resultFN);assertEquals("false positives",0, precComputer.resultFP);
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  public final void testPrecisionRecall_ign7() 
  {
    LearnerGraph mach = buildLearnerGraph("AM-a->AM-b->AM-c->AM","testPrecisionRecall_ign1",mainConfiguration,converter);
    PTASequenceEngine engine = new PTA_FSMStructure(mach,null);
    SequenceSet partialPTA = engine.new SequenceSet();partialPTA.setIdentity();
    partialPTA = partialPTA.cross(TestFSMAlgo.buildSet(new String[][] {
        new String[] {"a","a","a","b"}, // +
      },mainConfiguration,converter));
    PTA_computePrecisionRecall precComputer = new PTA_computePrecisionRecall(fsm);
    precComputer.crossWith(engine);
   
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          }     
        });
      }
    };
    SequenceSet seq = en.new SequenceSet();seq.setIdentity();
    Map<String,String> actual = getDebugDataMap(en,seq.cross(TestFSMAlgo.buildList(new String[][] {
        new String[] {"a","a","b","c"}
       
    },mainConfiguration,converter)).crossWithSet(labelList(new String[] {"b","a"})));
    vertifyPTA(en, 2, new String[][] {
        new String[] {"a","a","b","c","a"},
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    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","a","a","b"}, // +
      },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);
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  public final void testPrecisionRecall_ign8() // a complex structure, most of which gets ignored.
  {
    LearnerGraph mach = buildLearnerGraph("AM-a->BM-a->AM\nBM-b->CM-a->DM","testPrecisionRecall_ign2",mainConfiguration,converter);
    PTASequenceEngine engine = new PTA_FSMStructure(mach,null);
    SequenceSet partialPTA = engine.new SequenceSet();partialPTA.setIdentity();
    partialPTA = partialPTA.cross(TestFSMAlgo.buildSet(new String[][] {
        new String[] {"a","a","a","a","b"}, new String[]{"b"}, new String[]{"a", "b", "c"}, new String[]{"a", "b", "a"}
      },mainConfiguration,converter));
    PTA_computePrecisionRecall precComputer = new PTA_computePrecisionRecall(fsm);
    precComputer.crossWith(engine);
    precComputer.crossWith(engine);
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  @Test
  public final void test_sequenceSet4_1() // a more complex composition
  {
    SequenceSet seq = en.new SequenceSet();seq.setIdentity();
    Map<String,String> actual = getDebugDataMap(en,seq.cross(TestFSMAlgo.buildList(new String[][] {
        new String[] {"a","b","c"}
    },mainConfiguration,converter)));
    vertifyPTA(en, 1, new String[][] {
        new String[] {"a","b","c"}
    });
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