How to use the holoviews.core.spaces.DynamicMap function in holoviews

def test_dynamic_compute_overlayable_zorders_three_deep_dynamic_layers(self):
        area = DynamicMap(lambda: Area(range(10)), kdims=[])
        curve = DynamicMap(lambda: Curve(range(10)), kdims=[])
        curve2 = DynamicMap(lambda: Curve(range(10)), kdims=[])
        area_redim = area.redim(x='x2')
        curve_redim = curve.redim(x='x2')
        curve2_redim = curve2.redim(x='x3')
        combined = area_redim*curve_redim
        combined1 = (combined*curve2_redim)
        combined1[()]
        sources = compute_overlayable_zorders(combined1)
        self.assertIn(area_redim, sources[0])
        self.assertIn(area, sources[0])
        self.assertNotIn(curve_redim, sources[0])
        self.assertNotIn(curve, sources[0])
        self.assertNotIn(curve2_redim, sources[0])
        self.assertNotIn(curve2, sources[0])

def setUp(self):
        self.dimstream = PointerX(x=0)
        self.stream = PointerY(y=0)
        self.dmap = DynamicMap(lambda x, y, z: Curve([x, y, z]),
                               kdims=['x', 'z'], streams=[self.stream, self.dimstream])

def test_deep_map_apply_dmap_function(self):
        fn = lambda i: Curve(np.arange(i))
        dmap1 = DynamicMap(fn, kdims=[Dimension('Test', range=(10, 20))])
        dmap2 = DynamicMap(fn, kdims=[Dimension('Test', range=(10, 20))])
        mapped = (dmap1 + dmap2).map(lambda x: x[10], DynamicMap)
        self.assertEqual(mapped, Layout([('DynamicMap.I', fn(10)),
                                         ('DynamicMap.II', fn(10))]))

def test_redim_dimension_values_cache_reset_1D(self):
        # Setting the values should drop mismatching keys from the cache
        fn = lambda i: Curve([i,i])
        dmap = DynamicMap(fn, kdims=['i'])[{0,1,2,3,4,5}]
        self.assertEqual(dmap.keys(), [0,1,2,3,4,5])
        redimmed = dmap.redim.values(i=[2,3,5,6,8])
        self.assertEqual(redimmed.keys(), [2,3,5])

def test_deep_relabel_group(self):
        fn = lambda i: Image(sine_array(0,i))
        dmap = DynamicMap(fn, kdims=['i']).relabel(group='Test')
        self.assertEqual(dmap[0].group, 'Test')

def test_deep_select_slice_kdim_no_match(self):
        fn = lambda i: Curve(np.arange(i))
        dmap = DynamicMap(fn, kdims=[Dimension('Test', range=(10, 20))])
        self.assertEqual(dmap.select(DynamicMap, x=(5, 10))[10], fn(10))

def test_dynamic_compute_overlayable_zorders_mixed_dynamic_and_non_dynamic_ndoverlays_reverse(self):
        ndoverlay = NdOverlay({i: Area(range(10+i)) for i in range(2)})
        curve = DynamicMap(lambda: Curve(range(10)), kdims=[])
        curve_redim = curve.redim(x='x2')
        combined = curve_redim*ndoverlay
        combined[()]
        sources = compute_overlayable_zorders(combined)

        self.assertIn(curve_redim, sources[0])
        self.assertIn(curve, sources[0])
        self.assertNotIn(ndoverlay, sources[0])

        self.assertIn(ndoverlay[0], sources[1])
        self.assertIn(ndoverlay, sources[1])
        self.assertNotIn(curve_redim, sources[1])
        self.assertNotIn(curve, sources[1])

        self.assertIn(ndoverlay[1], sources[2])
        self.assertIn(ndoverlay, sources[2])

sliced = self.clone(self)
        for i, slc in enumerate(tuple_key):
            (start, stop) = slc.start, slc.stop
            if start is not None and start < sliced.kdims[i].range[0]:
                raise Exception("Requested slice below defined dimension range.")
            if stop is not None and stop > sliced.kdims[i].range[1]:
                raise Exception("Requested slice above defined dimension range.")
            sliced.kdims[i].soft_range = (start, stop)
        if data_slice:
            if not isinstance(sliced, DynamicMap):
                return self._dataslice(sliced, data_slice)
            else:
                from ..util import Dynamic
                if len(self):
                    slices = [slice(None) for _ in range(self.ndims)] + list(data_slice)
                    sliced = super(DynamicMap, sliced).__getitem__(tuple(slices))
                dmap = Dynamic(self, operation=lambda obj, **dynkwargs: obj[data_slice],
                               streams=self.streams)
                dmap.data = sliced.data
                return dmap
        return sliced

layers.append(self_el)
            except KeyError:
                pass
            try:
                other_el = other.select(HoloMap, **key_map) if other.kdims else other[()]
                layers.append(other_el)
            except KeyError:
                pass
            return Overlay(layers)
        callback = Callable(dynamic_mul, inputs=[self, other])
        callback._is_overlay = True
        if map_obj:
            return map_obj.clone(callback=callback, shared_data=False,
                                 kdims=dimensions, streams=streams)
        else:
            return DynamicMap(callback=callback, kdims=dimensions,
                              streams=streams)

def update_frame(self, key, ranges=None, element=None):
        reused = isinstance(self.hmap, DynamicMap) and self.overlaid
        if not reused and element is None:
            element = self._get_frame(key)
        elif element is not None:
            self.current_frame = element
            self.current_key = key
        items = [] if element is None else list(element.data.items())

        # Instantiate dynamically added subplots
        for k, subplot in self.subplots.items():
            # If in Dynamic mode propagate elements to subplots
            if not (isinstance(self.hmap, DynamicMap) and element is not None):
                continue
            idx, _, _ = dynamic_update(self, subplot, k, element, items)
            if idx is not None:
                items.pop(idx)
        if isinstance(self.hmap, DynamicMap) and items: