How to use the vaex.superagg.Grid function in vaex

def test_ref_count():
    x = np.array([-1, -2, 0.5, 1.5, 4.5, 5], dtype='f8')
    bins = 5
    binner = vaex.superagg.BinnerScalar_float64('x', 0, 5, bins)
    start_count_binner = sys.getrefcount(binner)
    grid = vaex.superagg.Grid([binner])
    assert sys.getrefcount(binner) == start_count_binner + 1
    start_count_grid = sys.getrefcount(grid)

    agg = vaex.superagg.AggCount_float64(grid)
    assert sys.getrefcount(binner) == start_count_grid + 1
    del agg
    assert sys.getrefcount(grid) == start_count_grid
    assert sys.getrefcount(binner) == start_count_binner + 1
    del grid
    assert sys.getrefcount(binner) == start_count_binner

def test_count_1d_ordinal():
    x = np.array([-1, -2, 0, 1, 4, 6, 10], dtype='i8')
    ordinal_count = 5
    binner = vaex.superagg.BinnerOrdinal_int64('x', ordinal_count, 0)
    binner.set_data(x)
    grid = vaex.superagg.Grid([binner])
    agg = vaex.superagg.AggCount_int64(grid)
    agg_data = np.asarray(agg)
    grid.bin([agg])
    assert agg_data.tolist() == [0, 2, 1, 1, 0, 0, 1, 2]

def test_count_1d():
    x = np.array([-1, -2, 0.5, 1.5, 4.5, 5], dtype='f8')
    df = vaex.from_arrays(x=x)

    bins = 5
    binner = df._binner_scalar('x', [0, 5], bins)
    grid = vaex.superagg.Grid([binner])
    agg = vaex.agg.count()
    grid = df._agg(agg, grid)
    assert grid.tolist() == [0, 2, 1, 1, 0, 0, 1, 1]

def test_min_max_1d_ordinal():
    x = np.array([-1, -1, 0, 0, 4, 6, 10], dtype='i8')
    y = np.array([-1,  2, 4, 1, 9, 6, 10], dtype='i8')
    ordinal_count = 5
    binner = vaex.superagg.BinnerOrdinal_int64('x', ordinal_count, 0)
    binner.set_data(x)
    grid = vaex.superagg.Grid([binner])
    agg = vaex.superagg.AggMax_int64(grid)
    agg_data = np.asarray(agg)
    agg_data -= 100
    agg.set_data(y, 0)
    grid.bin([agg])
    assert agg_data.tolist() == [-100, 2, 4, -100, -100, -100, 9, 10]
    
    grid = vaex.superagg.Grid([binner])
    agg = vaex.superagg.AggMin_int64(grid)
    agg_data = np.asarray(agg)
    agg_data += 100
    agg.set_data(y, 0)
    grid.bin([agg])
    assert agg_data.tolist() == [100, -1, 1, 100, 100, 100, 9, 6]

def test_count_1d_ordinal():
    x = np.array([-1, -2, 0, 1, 4, 5], dtype='i8')
    df = vaex.from_arrays(x=x)

    bins = 5
    binner = df._binner_ordinal('x', 5)
    grid = vaex.superagg.Grid([binner])
    agg = vaex.agg.count()
    grid = df._agg(agg, grid)
    assert grid.tolist() == [0, 2, 1, 1, 0, 0, 1, 1]

def test_count_1d_object():
    x = np.array([-1, -1, 0, 0, 2, 6, 10], dtype='i8')
    y = np.array([ 1,  1, 1, None, 1, '1', np.nan], dtype='O')
    ordinal_count = 5
    binner = vaex.superagg.BinnerOrdinal_int64('x', ordinal_count, 0)
    binner.set_data(x)
    grid = vaex.superagg.Grid([binner])
    agg = vaex.superagg.AggCount_object(grid)
    agg_data = np.asarray(agg)
    agg.set_data(y, 0)
    grid.bin([agg])
    assert agg_data.tolist() == [0, 2, 1, 0, 1, 0, 0, 1]

def __init__(self, df, grid):
        expressions = [binner.expression for binner in grid.binners]
        Task.__init__(self, df, expressions, name="statisticNd", pre_filter=df.filtered)

        self.df = df
        self.parent_grid = grid
        self.nthreads = self.df.executor.thread_pool.nthreads
        # for each thread, we have 1 grid and a set of binners
        self.grids = [vaex.superagg.Grid([binner.copy() for binner in grid.binners]) for i in range(self.nthreads)]
        self.aggregations = []
        # self.grids = []