Examples of gnu.trove.set.hash.TIntHashSet.toArray()

gnu.trove.set.hash.TIntHashSet.toArray()
{@inheritDoc}

        Tensor factor, newFactor;
        int toResolvePosition = toResolve.size();
        for (i = factors.length - 1; i >= 0; --i)
            if (result[i] == null) {
                factor = toResolve.get(--toResolvePosition);
                newFactor = ApplyIndexMapping.renameDummy(factor, forbidden.toArray());
                forbidden.addAll(TensorUtils.getAllIndicesNamesT(newFactor));
                result[i] = newFactor;
            }
//        for (int i = toResolve.size() - 1; i >= 0; --i) {
//            factor = toResolve.get(i);

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        int i;
        for (i = factors.length - 1; i >= 0; --i)
            forbidden.addAll(TensorUtils.getAllIndicesNamesT(factors[i]));


        for (i = factors.length - 1; i >= 0; --i) {
            factors[i] = ApplyIndexMapping.renameDummy(factors[i], forbidden.toArray());
            forbidden.addAll(TensorUtils.getAllIndicesNamesT(factors[i]));
        }
    }


    /**

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                return null;
            TIntHashSet added = new TIntHashSet(initialForbidden);
            ProductBuilder builder = new ProductBuilder();
            builder.put(base.get(tuple[0]));
            for (int i = 1; i < tuple.length; ++i)
                builder.put(ApplyIndexMapping.renameDummy(base.get(tuple[i]), added.toArray(), added));


            return createPort(builder.build());
        }


        @Override

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                    forbidden.forbidden = new TIntHashSet(iterator.getForbidden());


                TIntHashSet remainderIndices = new TIntHashSet(forbidden.forbidden);
                remainderIndices.addAll(getAllIndicesNamesT(indexlessRemainder));
                remainderIndices.addAll(getAllIndicesNamesT(dataRemainderT));
                newTo = applyIndexMapping(to, mapping, remainderIndices.toArray());
                forbidden.forbidden.addAll(getAllIndicesNamesT(newTo));
            } else {
                TIntHashSet allowed = new TIntHashSet();
                for (int index : indexlessBijection)
                    allowed.addAll(TensorUtils.getAllDummyIndicesT(content.indexless[index]));

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                    allowed.addAll(TensorUtils.getAllDummyIndicesT(currentData[index]));
                    ib.append(currentData[index]);
                }
                allowed.addAll(ib.getIndices().getNamesOfDummies());
                allowed.removeAll(IndicesUtils.getIndicesNames(mapping.getToData()));
                newTo = applyIndexMappingAndRenameAllDummies(to, mapping, allowed.toArray());
            }
        }
        return new SubsResult(newTo, remainder);
    }

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            //All dummy indices in this sum
            TIntHashSet allDummyIndicesT = TensorUtils.getAllDummyIndicesT(tensor);


            //Creating array to index individual indices origin
            allDummyIndices = allDummyIndicesT.toArray();
            Arrays.sort(allDummyIndices);


            //For performance
            final int size = tensor.size();

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        if (fromL == null)
            return tensor;


        allIndicesNames.addAll(getIndicesNames(tensor.getIndices().getFree()));
        IndexGeneratorImpl generator = new IndexGeneratorImpl(allIndicesNames.toArray());
        int[] from = fromL.toArray(), to = new int[fromL.size()];
        Arrays.sort(from);
        int i;
        for (i = from.length - 1; i >= 0; --i)
            to[i] = generator.generate(IndicesUtils.getType(from[i]));

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        ).transform(content[0].toTensor());
        result = ApplyIndexMapping.optimizeDummies(result);
        TIntHashSet generated = TensorUtils.getAllDummyIndicesT(result);
        generated.removeAll(allowedDummies);


        result = ApplyIndexMapping.renameDummy(result, generated.toArray(), allowedDummies.toArray());
        return result;
    }
}

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            if (indicator.is(scalars[i])) {
                if (scalars[i] instanceof SimpleTensor && scalars[i].getIndices().size() == 0)//simple symbolic factor
                    factorOut.add(Tensors.pow(scalars[i], exponent));
                else
                    for (j = 0; j < exponent; ++j) {
                        temp = ApplyIndexMapping.renameDummy(scalars[i], allForbidden.toArray());
                        allForbidden.addAll(TensorUtils.getAllIndicesNamesT(temp));
                        factorOut.add(temp);
                    }
            } else leave.add(scalars[i]);
        }

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        if (TensorUtils.passOutDummies(tensor)) {
            TIntHashSet forbidden = new TIntHashSet();
            for (j = 0; j < size; ++j)
                if (j != i)
                    TensorUtils.appendAllIndicesNamesT(get(j), forbidden);
            tensor = ApplyIndexMapping.renameDummy(tensor, forbidden.toArray());
        }


        Boolean compare = TensorUtils.compare1(old, tensor);
        if (compare == null)
            return super.set(i, tensor);

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