def setUpTestData(cls):
        batch_num = 0
        section_num = 0
        voter_num = 0
        party_num = 0
        position_num = 0
        candidate_num = 0
        num_elections = 2
        voters = list()
        positions = dict()
        for i in range(num_elections):
            election = Election.objects.create(name='Election {}'.format(i))
            positions[str(election.name)] = list()

            num_batches = 2
            for j in range(num_batches):
                batch = Batch.objects.create(year=batch_num, election=election)
                batch_num += 1

                num_sections = 2 if j == 0 else 1
                for k in range(num_sections):
                    section = Section.objects.create(
                        section_name=str(section_num)
                    )
                    section_num += 1

                    num_students = 2
                    for l in range(num_students):
                        voter = User.objects.create(
                            username='user{}'.format(voter_num),
                            first_name=str(voter_num),
                            last_name=str(voter_num),
                            type=UserType.VOTER
                        )
                        voter.set_password('voter')
                        voter.save()
                        voter_num += 1

                        VoterProfile.objects.create(
                            user=voter,
                            batch=batch,
                            section=section
                        )

                        voters.append(voter)

            num_positions = 3
            for i in range(num_positions):
                position = CandidatePosition.objects.create(
                    position_name='Position {}'.format(position_num),
                    election=election
                )

                positions[str(election.name)].append(position)

                position_num += 1

            num_parties = 3
            for j in range(num_parties):
                party = CandidateParty.objects.create(
                    party_name='Party {}'.format(party_num),
                    election=election
                )
                party_num += 1

                if j != 2:  # Let every third party have no candidates.
                    num_positions = 3
                    for k in range(num_positions):
                        position = positions[str(election.name)][k]

                        candidate = Candidate.objects.create(
                            user=voters[candidate_num],
                            party=party,
                            position=position,
                            election=election
                        )

                        Vote.objects.create(
                            user=voters[candidate_num],
                            candidate=candidate,
                            election=election
                        )

                        candidate_num += 1

        # Let's give one candidate an additional vote to really make sure that
        # we all got the correct number of votes.
        Vote.objects.create(
            user=voters[0],
            # NOTE: The voter in voter[1] is a Position 1 candidate of
            #       Party 1, where the voter in voter[0] is a member.
            candidate=Candidate.objects.get(user=voters[1]),
            election=Election.objects.get(name='Election 0')
        )

        _admin = User.objects.create(username='admin', type=UserType.ADMIN)
        _admin.set_password('root')
        _admin.save()
def init(cls, eltype, data, kdims, vdims):
        import cudf
        import pandas as pd

        element_params = eltype.param.objects()
        kdim_param = element_params['kdims']
        vdim_param = element_params['vdims']

        if isinstance(data, (cudf.Series, pd.Series)):
            data = data.to_frame()

        if not isinstance(data, cudf.DataFrame):
            data, _, _ = PandasInterface.init(eltype, data, kdims, vdims)
            data = cudf.from_pandas(data)

        columns = list(data.columns)
        ncols = len(columns)
        index_names = [data.index.name]
        if index_names == [None]:
            index_names = ['index']
        if eltype._auto_indexable_1d and ncols == 1 and kdims is None:
            kdims = list(index_names)

        if isinstance(kdim_param.bounds[1], int):
            ndim = min([kdim_param.bounds[1], len(kdim_param.default)])
        else:
            ndim = None
        nvdim = vdim_param.bounds[1] if isinstance(vdim_param.bounds[1], int) else None
        if kdims and vdims is None:
            vdims = [c for c in columns if c not in kdims]
        elif vdims and kdims is None:
            kdims = [c for c in columns if c not in vdims][:ndim]
        elif kdims is None:
            kdims = list(columns[:ndim])
            if vdims is None:
                vdims = [d for d in columns[ndim:((ndim+nvdim) if nvdim else None)]
                         if d not in kdims]
        elif kdims == [] and vdims is None:
            vdims = list(columns[:nvdim if nvdim else None])

        # Handle reset of index if kdims reference index by name
        for kd in kdims:
            kd = dimension_name(kd)
            if kd in columns:
                continue
            if any(kd == ('index' if name is None else name)
                   for name in index_names):
                data = data.reset_index()
                break
        if any(isinstance(d, (np.int64, int)) for d in kdims+vdims):
            raise DataError("cudf DataFrame column names used as dimensions "
                            "must be strings not integers.", cls)

        if kdims:
            kdim = dimension_name(kdims[0])
            if eltype._auto_indexable_1d and ncols == 1 and kdim not in columns:
                data = data.copy()
                data.insert(0, kdim, np.arange(len(data)))

        for d in kdims+vdims:
            d = dimension_name(d)
            if len([c for c in columns if c == d]) > 1:
                raise DataError('Dimensions may not reference duplicated DataFrame '
                                'columns (found duplicate %r columns). If you want to plot '
                                'a column against itself simply declare two dimensions '
                                'with the same name. '% d, cls)
        return data, {'kdims':kdims, 'vdims':vdims}, {}