def test_get_election0_xlsx(self):
        response = self.client.get(
            reverse('results-export'),
            { 'election': str(Election.objects.get(name='Election 0').id) }
        )

        self.assertEqual(response.status_code, 200)        

        self.assertEqual(
            response['Content-Disposition'],
            'attachment; filename="Election 0 Results.xlsx"'
        )

        wb = openpyxl.load_workbook(io.BytesIO(response.content))

        self.assertEqual(len(wb.worksheets), 1)

        # Check first worksheet.
        ws = wb.worksheets[0]

        self.assertEqual(wb.sheetnames[0], 'Election 0')

        row_count = ws.max_row
        col_count = ws.max_column
        self.assertEqual(row_count, 25)
        self.assertEqual(col_count, 5)

        self.assertEqual(str(ws.cell(1, 1).value), 'Election 0 Results')

        self.assertEqual(str(ws.cell(2, 1).value), 'Candidates')

        cellContents = [
            'Position 0',
            'Party 0',
            '0, 0',
            'Party 1',
            '3, 3',
            'Party 2',
            'None',
            'Position 1',
            'Party 0',
            '1, 1',
            'Party 1',
            '4, 4',
            'Party 2',
            'None',
            'Position 2',
            'Party 0',
            '2, 2',
            'Party 1',
            '5, 5',
            'Party 2',
            'None'
        ]
        for cellIndex, content in enumerate(cellContents, 5):
            self.assertEqual(str(ws.cell(cellIndex, 1).value), content) 

        self.assertEqual(str(ws.cell(2, 2).value), 'Number of Votes')

        self.assertEqual(str(ws.cell(3, 2).value), '0')

        self.assertEqual(str(ws.cell(4, 2).value), '0') # Section

        self.assertEqual(str(ws.cell(7, 2).value), '1')
        self.assertEqual(str(ws.cell(9, 2).value), '0')
        self.assertEqual(str(ws.cell(11, 2).value), 'N/A')
        self.assertEqual(str(ws.cell(14, 2).value), '2')
        self.assertEqual(str(ws.cell(16, 2).value), '0')
        self.assertEqual(str(ws.cell(18, 2).value), 'N/A')
        self.assertEqual(str(ws.cell(21, 2).value), '0')
        self.assertEqual(str(ws.cell(23, 2).value), '0')
        self.assertEqual(str(ws.cell(25, 2).value), 'N/A')

        self.assertEqual(str(ws.cell(4, 3).value), '1') # Section

        self.assertEqual(str(ws.cell(7, 3).value), '0')
        self.assertEqual(str(ws.cell(9, 3).value), '1')
        self.assertEqual(str(ws.cell(11, 2).value), 'N/A')
        self.assertEqual(str(ws.cell(14, 3).value), '0')
        self.assertEqual(str(ws.cell(16, 3).value), '0')
        self.assertEqual(str(ws.cell(18, 2).value), 'N/A')
        self.assertEqual(str(ws.cell(21, 3).value), '1')
        self.assertEqual(str(ws.cell(23, 3).value), '0')
        self.assertEqual(str(ws.cell(25, 2).value), 'N/A')

        self.assertEqual(str(ws.cell(3, 4).value), '1')

        self.assertEqual(str(ws.cell(4, 4).value), '2') # Section

        self.assertEqual(str(ws.cell(7, 4).value), '0')
        self.assertEqual(str(ws.cell(9, 4).value), '0')
        self.assertEqual(str(ws.cell(11, 2).value), 'N/A')
        self.assertEqual(str(ws.cell(14, 4).value), '0')
        self.assertEqual(str(ws.cell(16, 4).value), '1')
        self.assertEqual(str(ws.cell(18, 2).value), 'N/A')
        self.assertEqual(str(ws.cell(21, 4).value), '0')
        self.assertEqual(str(ws.cell(23, 4).value), '1')
        self.assertEqual(str(ws.cell(25, 2).value), 'N/A')

        self.assertEqual(str(ws.cell(3, 5).value), 'Total Votes')
        self.assertEqual(str(ws.cell(7, 5).value), '1')
        self.assertEqual(str(ws.cell(9, 5).value), '1')
        self.assertEqual(str(ws.cell(11, 2).value), 'N/A')
        self.assertEqual(str(ws.cell(14, 5).value), '2')
        self.assertEqual(str(ws.cell(16, 5).value), '1')
        self.assertEqual(str(ws.cell(18, 2).value), 'N/A')
        self.assertEqual(str(ws.cell(21, 5).value), '1')
        self.assertEqual(str(ws.cell(23, 5).value), '1')
        self.assertEqual(str(ws.cell(25, 2).value), 'N/A')
def find_storm_images_3d(
        top_directory_name, radar_source, radar_field_names,
        radar_heights_m_agl, first_spc_date_string, last_spc_date_string):
    """Locates files with 3-D storm-centered radar images.

    D = number of SPC dates in time period (`first_spc_date_string`...
        `last_spc_date_string`)

    :param top_directory_name: See doc for `find_storm_images_2d`.
    :param radar_source: Same.
    :param radar_field_names: List (length F_r) of radar fields.  Each item must
        be accepted by `radar_utils.check_field_name`.
    :param radar_heights_m_agl: numpy array (length H_r) of radar heights
        (metres above ground level).
    :param first_spc_date_string: First SPC date (format "yyyymmdd").  This
        method will locate files from `first_spc_date_string`...
        `last_spc_date_string`.
    :param last_spc_date_string: Same.
    :return: radar_file_name_matrix: numpy array (D x F_r x H_r) of file paths.
    """

    radar_utils.check_data_source(radar_source)
    first_spc_date_unix_sec = time_conversion.spc_date_string_to_unix_sec(
        first_spc_date_string)
    last_spc_date_unix_sec = time_conversion.spc_date_string_to_unix_sec(
        last_spc_date_string)

    if radar_source == radar_utils.GRIDRAD_SOURCE_ID:
        file_dict = storm_images.find_many_files_gridrad(
            top_directory_name=top_directory_name,
            radar_field_names=radar_field_names,
            radar_heights_m_agl=radar_heights_m_agl,
            start_time_unix_sec=first_spc_date_unix_sec,
            end_time_unix_sec=last_spc_date_unix_sec,
            one_file_per_time_step=False, raise_error_if_all_missing=True)
    else:
        file_dict = storm_images.find_many_files_myrorss_or_mrms(
            top_directory_name=top_directory_name, radar_source=radar_source,
            radar_field_names=[radar_utils.REFL_NAME],
            reflectivity_heights_m_agl=radar_heights_m_agl,
            start_time_unix_sec=first_spc_date_unix_sec,
            end_time_unix_sec=last_spc_date_unix_sec,
            one_file_per_time_step=False,
            raise_error_if_all_missing=True, raise_error_if_any_missing=False)

    radar_file_name_matrix = file_dict[storm_images.IMAGE_FILE_NAMES_KEY]
    num_file_times = radar_file_name_matrix.shape[0]

    if radar_source != radar_utils.GRIDRAD_SOURCE_ID:
        radar_file_name_matrix = numpy.reshape(
            radar_file_name_matrix,
            (num_file_times, 1, len(radar_heights_m_agl))
        )

    time_missing_indices = numpy.unique(
        numpy.where(radar_file_name_matrix == '')[0]
    )
    return numpy.delete(
        radar_file_name_matrix, time_missing_indices, axis=0)