Examples of edu.stanford.nlp.trees.TreeTransformer.transformTree()

Class edu.stanford.nlp.trees.TreeTransformer

Examples of edu.stanford.nlp.trees.TreeTransformer.transformTree()

edu.stanford.nlp.trees.TreeTransformer.transformTree()
Does whatever one needs to do to a particular tree. This routine is passed a whole Tree, and could itself work recursively, but the canonical usage is to invoke this method via the Tree.transform() method, which will apply the transformer in a bottom-up manner to each local Tree, and hence the implementation of TreeTransformer should merely examine and change a local (one-level) Tree. @param t A tree. Classes implementing this interface can assumethat the tree passed in is not null. @return the transformed Tree

        pwOut.printf("Yield mismatch gold: %d tokens vs. guess: %d tokens (lines: gold %d guess %d)%n", goldYield.size(), guessYield.size(), goldLineId, guessLineId);
        skippedGuessTrees++;
        continue;
      }


      final Tree evalGuess = tc.transformTree(guessTree);
      final Tree evalGold = tc.transformTree(goldTree);


      metric.evaluate(evalGuess, evalGold, ((VERBOSE) ? pwOut : null));
    }

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        skippedGuessTrees++;
        continue;
      }


      final Tree evalGuess = tc.transformTree(guessTree);
      final Tree evalGold = tc.transformTree(goldTree);


      metric.evaluate(evalGuess, evalGold, ((VERBOSE) ? pwOut : null));
    }


    if(guessItr.hasNext() || goldItr.hasNext()) {

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        pwOut.printf("Yield mismatch gold: %d tokens vs. guess: %d tokens (lines: gold %d guess %d)%n", goldYield.size(), guessYield.size(), goldLineId, guessLineId);
        skippedGuessTrees++;
        continue;
      }


      final Tree evalGuess = tc.transformTree(guessTree);
      evalGuess.indexLeaves(true);
      final Tree evalGold = tc.transformTree(goldTree);
      evalGold.indexLeaves(true);


      metric.evaluate(evalGuess, evalGold, ((VERBOSE) ? pwOut : null));

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        continue;
      }


      final Tree evalGuess = tc.transformTree(guessTree);
      evalGuess.indexLeaves(true);
      final Tree evalGold = tc.transformTree(goldTree);
      evalGold.indexLeaves(true);


      metric.evaluate(evalGuess, evalGold, ((VERBOSE) ? pwOut : null));
    }

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      TreeReaderFactory trf = new ArabicTreeReaderFactory.ArabicRawTreeReaderFactory();
      TreeReader tr = trf.newTreeReader(br);


      int nTrees = 0;
      for(Tree t; (t = tr.readTree()) != null;nTrees++) {
        Tree fixedT = tt.transformTree(t);
        System.out.println(fixedT.toString());
      }


      tr.close();

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        pwOut.printf("Yield mismatch gold: %d tokens vs. guess: %d tokens (lines: gold %d guess %d)%n", goldYield.size(), guessYield.size(), goldLineId, guessLineId);
        skippedGuessTrees++;
        continue;
      }


      final Tree evalGuess = tc.transformTree(guessTree);
      final Tree evalGold = tc.transformTree(goldTree);


      metric.evaluate(evalGuess, evalGold, ((VERBOSE) ? pwOut : null));
    }

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        skippedGuessTrees++;
        continue;
      }


      final Tree evalGuess = tc.transformTree(guessTree);
      final Tree evalGold = tc.transformTree(goldTree);


      metric.evaluate(evalGuess, evalGold, ((VERBOSE) ? pwOut : null));
    }


    if(guessItr.hasNext() || goldItr.hasNext()) {

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    // I've hardwired this to load English ones.  Otherwise need training data.
    // op.trainOptions.splitters = new HashSet(Arrays.asList(op.tlpParams.splitters()));
    op.trainOptions.splitters = ParentAnnotationStats.getEnglishSplitCategories(treebankRoot);
    op.trainOptions.sisterSplitters = Generics.newHashSet(Arrays.asList(op.tlpParams.sisterSplitters()));
    for (Tree goldTree : testTreebank) {
      goldTree = annotator.transformTree(goldTree);
      //      System.out.println();
      //      System.out.println("Checking tree: " + goldTree);
      for (Tree localTree : goldTree) {
        // now try to use the grammar to score this local tree
        if (localTree.isLeaf() || localTree.isPreTerminal() || localTree.children().length < 2) {

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          }
          //tree4.pennPrint();
          comboPE.evaluate(tc.transformTree(tree4), tc.transformTree(tree), pw);
        }
        //pcfgTE.evaluate(tree2, tree);
        pcfgTE.evaluate(tcEvalb.transformTree(tree2), tcEvalb.transformTree(tree), pw);
        pcfgTEnoPunct.evaluate(tc.transformTree(tree2), tc.transformTree(tree), pw);


        if (op.doDep) {
          comboTE.evaluate(tcEvalb.transformTree(tree4), tcEvalb.transformTree(tree), pw);
          comboTEnoPunct.evaluate(tc.transformTree(tree4), tc.transformTree(tree), pw);

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          }
          //tree4.pennPrint();
          comboPE.evaluate(tc.transformTree(tree4), tc.transformTree(tree), pw);
        }
        //pcfgTE.evaluate(tree2, tree);
        pcfgTE.evaluate(tcEvalb.transformTree(tree2), tcEvalb.transformTree(tree), pw);
        pcfgTEnoPunct.evaluate(tc.transformTree(tree2), tc.transformTree(tree), pw);


        if (op.doDep) {
          comboTE.evaluate(tcEvalb.transformTree(tree4), tcEvalb.transformTree(tree), pw);
          comboTEnoPunct.evaluate(tc.transformTree(tree4), tc.transformTree(tree), pw);

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