diff --git a/examples/gallery/apps/bokeh/crossfilter.py b/examples/gallery/apps/bokeh/crossfilter.py index 7b15b964d1..8d71002992 100644 --- a/examples/gallery/apps/bokeh/crossfilter.py +++ b/examples/gallery/apps/bokeh/crossfilter.py @@ -52,7 +52,7 @@ def create_figure(): if size.value != 'None': opts['size_index'] = size.value opts['scaling_factor'] = (1./df[size.value].max())*200 - points = hv.Points(df, kdims=kdims, label=label)(plot=opts, style=style) + points = hv.Points(df, kdims=kdims, label=label).opts(plot=opts, style=style) return renderer.get_plot(points).state def update(attr, old, new): diff --git a/holoviews/operation/element.py b/holoviews/operation/element.py index 69f4b2423f..54c519acc9 100644 --- a/holoviews/operation/element.py +++ b/holoviews/operation/element.py @@ -775,7 +775,7 @@ def _process(self, p, element, ranges={}): opts = dict(axiswise=True, framewise=True) el = p.diagonal_operation(element, dimension=d1.name, - bin_range=bin_range)(norm=opts) + bin_range=bin_range).opts(norm=opts) else: el = p.diagonal_operation(element, dimension=d1.name) else: diff --git a/tests/testplotinstantiation.py b/tests/testplotinstantiation.py index 1eecda01e1..a0ad48e322 100644 --- a/tests/testplotinstantiation.py +++ b/tests/testplotinstantiation.py @@ -171,7 +171,7 @@ def history_callback(x, history=deque(maxlen=10)): def test_points_non_numeric_size_warning(self): data = (np.arange(10), np.arange(10), list(map(chr, range(94,104)))) - points = Points(data, vdims=['z'])(plot=dict(size_index=2)) + points = Points(data, vdims=['z']).opts(plot=dict(size_index=2)) with ParamLogStream() as log: plot = mpl_renderer.get_plot(points) log_msg = log.stream.read() @@ -235,7 +235,7 @@ def test_image_cbar_extend_max(self): self.assertEqual(plot.handles['cbar'].extend, 'max') def test_image_cbar_extend_clime(self): - img = Image(np.array([[0, 1], [2, 3]]))(style=dict(clim=(None, None))) + img = Image(np.array([[0, 1], [2, 3]])).opts(style=dict(clim=(None, None))) plot = mpl_renderer.get_plot(img(plot=dict(colorbar=True, color_index=1))) self.assertEqual(plot.handles['cbar'].extend, 'neither') @@ -255,7 +255,7 @@ def test_points_cbar_extend_max(self): self.assertEqual(plot.handles['cbar'].extend, 'max') def test_points_cbar_extend_clime(self): - img = Points(([0, 1], [0, 3]))(style=dict(clim=(None, None))) + img = Points(([0, 1], [0, 3])).opts(style=dict(clim=(None, None))) plot = mpl_renderer.get_plot(img(plot=dict(colorbar=True, color_index=1))) self.assertEqual(plot.handles['cbar'].extend, 'neither') @@ -294,13 +294,13 @@ def test_layout_instantiate_subplots_transposed(self): def test_points_rcparams_do_not_persist(self): opts = dict(fig_rcparams={'text.usetex': True}) - points = Points(([0, 1], [0, 3]))(plot=opts) + points = Points(([0, 1], [0, 3])).opts(plot=opts) mpl_renderer.get_plot(points) self.assertFalse(pyplot.rcParams['text.usetex']) def test_points_rcparams_used(self): opts = dict(fig_rcparams={'grid.color': 'red'}) - points = Points(([0, 1], [0, 3]))(plot=opts) + points = Points(([0, 1], [0, 3])).opts(plot=opts) plot = mpl_renderer.get_plot(points) ax = plot.state.axes[0] lines = ax.get_xgridlines() @@ -425,7 +425,7 @@ def test_batched_plot(self): self.assertEqual(extents, (0, 0, 98, 98)) def test_batched_spike_plot(self): - overlay = NdOverlay({i: Spikes([i], kdims=['Time'])(plot=dict(position=0.1*i, + overlay = NdOverlay({i: Spikes([i], kdims=['Time']).opts(plot=dict(position=0.1*i, spike_length=0.1, show_legend=False)) for i in range(10)}) @@ -438,7 +438,7 @@ def test_batched_curve_subscribers_correctly_attached(self): opts = {'NdOverlay': dict(plot=dict(legend_limit=0)), 'Curve': dict(style=dict(line_color=Cycle(values=['red', 'blue'])))} overlay = DynamicMap(lambda x: NdOverlay({i: Curve([(i, j) for j in range(2)]) - for i in range(2)})(opts), kdims=[], + for i in range(2)}).opts(opts), kdims=[], streams=[posx]) plot = bokeh_renderer.get_plot(overlay) self.assertIn(plot.refresh, posx.subscribers) @@ -451,7 +451,7 @@ def test_batched_curve_subscribers_correctly_linked(self): opts = {'NdOverlay': dict(plot=dict(legend_limit=0)), 'Curve': dict(style=dict(line_color=Cycle(values=['red', 'blue'])))} overlay = DynamicMap(lambda x: NdOverlay({i: Curve([(i, j) for j in range(2)]) - for i in range(2)})(opts), kdims=[], + for i in range(2)}).opts(opts), kdims=[], streams=[posx]) plot = bokeh_renderer.get_plot(overlay) self.assertEqual(len(Callback._callbacks), 1) @@ -462,7 +462,7 @@ def test_batched_points_size_and_color(self): opts = {'NdOverlay': dict(plot=dict(legend_limit=0)), 'Points': dict(style=dict(size=Cycle(values=[1, 2])))} overlay = NdOverlay({i: Points([(i, j) for j in range(2)]) - for i in range(2)})(opts) + for i in range(2)}).opts(opts) plot = bokeh_renderer.get_plot(overlay).subplots[()] size = np.array([1, 1, 2, 2]) color = np.array(['#30a2da', '#30a2da', '#fc4f30', '#fc4f30'], @@ -473,7 +473,7 @@ def test_batched_points_size_and_color(self): def test_cyclic_palette_curves(self): palette = Palette('Set1') opts = dict(color=palette) - hmap = HoloMap({i: NdOverlay({j: Curve(np.random.rand(3))(style=opts) + hmap = HoloMap({i: NdOverlay({j: Curve(np.random.rand(3)).opts(style=opts) for j in range(3)}) for i in range(3)}) colors = palette[3].values @@ -486,7 +486,7 @@ def test_batched_points_line_color_and_color(self): opts = {'NdOverlay': dict(plot=dict(legend_limit=0)), 'Points': dict(style=dict(line_color=Cycle(values=['red', 'blue'])))} overlay = NdOverlay({i: Points([(i, j) for j in range(2)]) - for i in range(2)})(opts) + for i in range(2)}).opts(opts) plot = bokeh_renderer.get_plot(overlay).subplots[()] line_color = np.array(['red', 'red', 'blue', 'blue']) fill_color = np.array(['#30a2da', '#30a2da', '#fc4f30', '#fc4f30'], @@ -498,7 +498,7 @@ def test_batched_points_alpha_and_color(self): opts = {'NdOverlay': dict(plot=dict(legend_limit=0)), 'Points': dict(style=dict(alpha=Cycle(values=[0.5, 1])))} overlay = NdOverlay({i: Points([(i, j) for j in range(2)]) - for i in range(2)})(opts) + for i in range(2)}).opts(opts) plot = bokeh_renderer.get_plot(overlay).subplots[()] alpha = np.array([0.5, 0.5, 1., 1.]) color = np.array(['#30a2da', '#30a2da', '#fc4f30', '#fc4f30'], @@ -510,7 +510,7 @@ def test_batched_points_line_width_and_color(self): opts = {'NdOverlay': dict(plot=dict(legend_limit=0)), 'Points': dict(style=dict(line_width=Cycle(values=[0.5, 1])))} overlay = NdOverlay({i: Points([(i, j) for j in range(2)]) - for i in range(2)})(opts) + for i in range(2)}).opts(opts) plot = bokeh_renderer.get_plot(overlay).subplots[()] line_width = np.array([0.5, 0.5, 1., 1.]) color = np.array(['#30a2da', '#30a2da', '#fc4f30', '#fc4f30'], @@ -522,7 +522,7 @@ def test_batched_curve_line_color_and_color(self): opts = {'NdOverlay': dict(plot=dict(legend_limit=0)), 'Curve': dict(style=dict(line_color=Cycle(values=['red', 'blue'])))} overlay = NdOverlay({i: Curve([(i, j) for j in range(2)]) - for i in range(2)})(opts) + for i in range(2)}).opts(opts) plot = bokeh_renderer.get_plot(overlay).subplots[()] line_color = ['red', 'blue'] self.assertEqual(plot.handles['source'].data['line_color'], line_color) @@ -531,7 +531,7 @@ def test_batched_curve_alpha_and_color(self): opts = {'NdOverlay': dict(plot=dict(legend_limit=0)), 'Curve': dict(style=dict(alpha=Cycle(values=[0.5, 1])))} overlay = NdOverlay({i: Curve([(i, j) for j in range(2)]) - for i in range(2)})(opts) + for i in range(2)}).opts(opts) plot = bokeh_renderer.get_plot(overlay).subplots[()] alpha = [0.5, 1.] color = ['#30a2da', '#fc4f30'] @@ -542,7 +542,7 @@ def test_batched_curve_line_width_and_color(self): opts = {'NdOverlay': dict(plot=dict(legend_limit=0)), 'Curve': dict(style=dict(line_width=Cycle(values=[0.5, 1])))} overlay = NdOverlay({i: Curve([(i, j) for j in range(2)]) - for i in range(2)})(opts) + for i in range(2)}).opts(opts) plot = bokeh_renderer.get_plot(overlay).subplots[()] line_width = [0.5, 1.] color = ['#30a2da', '#fc4f30'] @@ -553,7 +553,7 @@ def test_batched_path_line_color_and_color(self): opts = {'NdOverlay': dict(plot=dict(legend_limit=0)), 'Path': dict(style=dict(line_color=Cycle(values=['red', 'blue'])))} overlay = NdOverlay({i: Path([[(i, j) for j in range(2)]]) - for i in range(2)})(opts) + for i in range(2)}).opts(opts) plot = bokeh_renderer.get_plot(overlay).subplots[()] line_color = ['red', 'blue'] self.assertEqual(plot.handles['source'].data['line_color'], line_color) @@ -562,7 +562,7 @@ def test_batched_path_alpha_and_color(self): opts = {'NdOverlay': dict(plot=dict(legend_limit=0)), 'Path': dict(style=dict(alpha=Cycle(values=[0.5, 1])))} overlay = NdOverlay({i: Path([[(i, j) for j in range(2)]]) - for i in range(2)})(opts) + for i in range(2)}).opts(opts) plot = bokeh_renderer.get_plot(overlay).subplots[()] alpha = [0.5, 1.] color = ['#30a2da', '#fc4f30'] @@ -573,7 +573,7 @@ def test_batched_path_line_width_and_color(self): opts = {'NdOverlay': dict(plot=dict(legend_limit=0)), 'Path': dict(style=dict(line_width=Cycle(values=[0.5, 1])))} overlay = NdOverlay({i: Path([[(i, j) for j in range(2)]]) - for i in range(2)})(opts) + for i in range(2)}).opts(opts) plot = bokeh_renderer.get_plot(overlay).subplots[()] line_width = [0.5, 1.] color = ['#30a2da', '#fc4f30'] @@ -689,7 +689,7 @@ def test_polygons_overlay_hover(self): def test_hover_tool_instance_renderer_association(self): hover = HoverTool(tooltips=[("index", "$index")]) opts = dict(tools=[hover]) - overlay = Curve(np.random.rand(10,2))(plot=opts) * Points(np.random.rand(10,2)) + overlay = Curve(np.random.rand(10,2)).opts(plot=opts) * Points(np.random.rand(10,2)) plot = bokeh_renderer.get_plot(overlay) curve_plot = plot.subplots[('Curve', 'I')] self.assertEqual(len(curve_plot.handles['hover'].renderers), 1) @@ -718,7 +718,7 @@ def test_polygons_colored(self): def test_polygons_colored_batched(self): polygons = NdOverlay({j: Polygons([[(i**j, i) for i in range(10)]], level=j) - for j in range(5)})(plot=dict(legend_limit=0)) + for j in range(5)}).opts(plot=dict(legend_limit=0)) plot = list(bokeh_renderer.get_plot(polygons).subplots.values())[0] cmapper = plot.handles['color_mapper'] self.assertEqual(cmapper.low, 0) @@ -730,7 +730,7 @@ def test_polygons_colored_batched(self): def test_polygons_colored_batched_unsanitized(self): polygons = NdOverlay({j: Polygons([[(i**j, i) for i in range(10)] for i in range(2)], level=j, vdims=['some ? unescaped name']) - for j in range(5)})(plot=dict(legend_limit=0)) + for j in range(5)}).opts(plot=dict(legend_limit=0)) plot = list(bokeh_renderer.get_plot(polygons).subplots.values())[0] cmapper = plot.handles['color_mapper'] self.assertEqual(cmapper.low, 0) @@ -740,18 +740,18 @@ def test_polygons_colored_batched_unsanitized(self): [j for i in range(5) for j in [i, i]]) def test_points_colormapping(self): - points = Points(np.random.rand(10, 4), vdims=['a', 'b'])(plot=dict(color_index=3)) + points = Points(np.random.rand(10, 4), vdims=['a', 'b']).opts(plot=dict(color_index=3)) self._test_colormapping(points, 3) def test_points_colormapping_with_nonselection(self): opts = dict(plot=dict(color_index=3), style=dict(nonselection_color='red')) - points = Points(np.random.rand(10, 4), vdims=['a', 'b'])(**opts) + points = Points(np.random.rand(10, 4), vdims=['a', 'b']).opts(**opts) self._test_colormapping(points, 3) def test_points_colormapping_categorical(self): points = Points([(i, i*2, i*3, chr(65+i)) for i in range(10)], - vdims=['a', 'b'])(plot=dict(color_index='b')) + vdims=['a', 'b']).opts(plot=dict(color_index='b')) plot = bokeh_renderer.get_plot(points) plot.initialize_plot() cmapper = plot.handles['color_mapper'] @@ -761,7 +761,7 @@ def test_points_colormapping_categorical(self): def test_points_color_selection_nonselection(self): opts = dict(color='green', selection_color='red', nonselection_color='blue') points = Points([(i, i*2, i*3, chr(65+i)) for i in range(10)], - vdims=['a', 'b'])(style=opts) + vdims=['a', 'b']).opts(style=opts) plot = bokeh_renderer.get_plot(points) glyph_renderer = plot.handles['glyph_renderer'] self.assertEqual(glyph_renderer.glyph.fill_color, 'green') @@ -774,7 +774,7 @@ def test_points_color_selection_nonselection(self): def test_points_alpha_selection_nonselection(self): opts = dict(alpha=0.8, selection_alpha=1.0, nonselection_alpha=0.2) points = Points([(i, i*2, i*3, chr(65+i)) for i in range(10)], - vdims=['a', 'b'])(style=opts) + vdims=['a', 'b']).opts(style=opts) plot = bokeh_renderer.get_plot(points) glyph_renderer = plot.handles['glyph_renderer'] self.assertEqual(glyph_renderer.glyph.fill_alpha, 0.8) @@ -787,7 +787,7 @@ def test_points_alpha_selection_nonselection(self): def test_points_alpha_selection_partial(self): opts = dict(selection_alpha=1.0, selection_fill_alpha=0.2) points = Points([(i, i*2, i*3, chr(65+i)) for i in range(10)], - vdims=['a', 'b'])(style=opts) + vdims=['a', 'b']).opts(style=opts) plot = bokeh_renderer.get_plot(points) glyph_renderer = plot.handles['glyph_renderer'] self.assertEqual(glyph_renderer.glyph.fill_alpha, 1.0) @@ -796,7 +796,7 @@ def test_points_alpha_selection_partial(self): self.assertEqual(glyph_renderer.selection_glyph.line_alpha, 1) def test_image_colormapping(self): - img = Image(np.random.rand(10, 10))(plot=dict(logz=True)) + img = Image(np.random.rand(10, 10)).opts(plot=dict(logz=True)) self._test_colormapping(img, 2, True) def test_heatmap_colormapping(self): @@ -906,14 +906,14 @@ def history_callback(x, history=deque(maxlen=10)): self.assertEqual(data['y'], np.arange(10, 20)) def test_bars_suppress_legend(self): - bars = Bars([('A', 1), ('B', 2)])(plot=dict(show_legend=False)) + bars = Bars([('A', 1), ('B', 2)]).opts(plot=dict(show_legend=False)) plot = bokeh_renderer.get_plot(bars) plot.initialize_plot() fig = plot.state self.assertEqual(len(fig.legend), 0) def test_empty_bars(self): - bars = Bars([], kdims=['x', 'y'], vdims=['z'])(plot=dict(group_index=1)) + bars = Bars([], kdims=['x', 'y'], vdims=['z']).opts(plot=dict(group_index=1)) plot = bokeh_renderer.get_plot(bars) plot.initialize_plot() source = plot.handles['source'] @@ -949,7 +949,7 @@ def test_layout_title(self): def test_layout_title_fontsize(self): hmap1 = HoloMap({a: Image(np.random.rand(10,10)) for a in range(3)}) hmap2 = HoloMap({a: Image(np.random.rand(10,10)) for a in range(3)}) - layout = Layout([hmap1, hmap2])(plot=dict(fontsize={'title': '12pt'})) + layout = Layout([hmap1, hmap2]).opts(plot=dict(fontsize={'title': '12pt'})) plot = bokeh_renderer.get_plot(layout) title = plot.handles['title'] self.assertIsInstance(title, Div) @@ -959,7 +959,7 @@ def test_layout_title_fontsize(self): def test_layout_title_show_title_false(self): hmap1 = HoloMap({a: Image(np.random.rand(10,10)) for a in range(3)}) hmap2 = HoloMap({a: Image(np.random.rand(10,10)) for a in range(3)}) - layout = Layout([hmap1, hmap2])(plot=dict(show_title=False)) + layout = Layout([hmap1, hmap2]).opts(plot=dict(show_title=False)) plot = bokeh_renderer.get_plot(layout) self.assertTrue('title' not in plot.handles) @@ -996,7 +996,7 @@ def test_grid_title_update(self): def test_points_non_numeric_size_warning(self): data = (np.arange(10), np.arange(10), list(map(chr, range(94,104)))) - points = Points(data, vdims=['z'])(plot=dict(size_index=2)) + points = Points(data, vdims=['z']).opts(plot=dict(size_index=2)) with ParamLogStream() as log: plot = bokeh_renderer.get_plot(points) log_msg = log.stream.read() @@ -1012,7 +1012,7 @@ def test_curve_categorical_xaxis(self): self.assertEqual(x_range.factors, ['A', 'B', 'C']) def test_curve_categorical_xaxis_invert_axes(self): - curve = Curve((['A', 'B', 'C'], (1,2,3)))(plot=dict(invert_axes=True)) + curve = Curve((['A', 'B', 'C'], (1,2,3))).opts(plot=dict(invert_axes=True)) plot = bokeh_renderer.get_plot(curve) y_range = plot.handles['y_range'] self.assertIsInstance(y_range, FactorRange) @@ -1034,7 +1034,7 @@ def test_points_categorical_xaxis_mixed_type(self): self.assertEqual(x_range.factors, list(map(str, range(10))) + ['A', 'B', 'C', '2.0']) def test_points_categorical_xaxis_invert_axes(self): - points = Points((['A', 'B', 'C'], (1,2,3)))(plot=dict(invert_axes=True)) + points = Points((['A', 'B', 'C'], (1,2,3))).opts(plot=dict(invert_axes=True)) plot = bokeh_renderer.get_plot(points) y_range = plot.handles['y_range'] self.assertIsInstance(y_range, FactorRange) @@ -1049,7 +1049,7 @@ def test_points_overlay_categorical_xaxis(self): self.assertEqual(x_range.factors, ['A', 'B', 'C', 'D']) def test_points_overlay_categorical_xaxis_invert_axis(self): - points = Points((['A', 'B', 'C'], (1,2,3)))(plot=dict(invert_xaxis=True)) + points = Points((['A', 'B', 'C'], (1,2,3))).opts(plot=dict(invert_xaxis=True)) points2 = Points((['B', 'C', 'D'], (1,2,3))) plot = bokeh_renderer.get_plot(points*points2) x_range = plot.handles['x_range'] @@ -1057,7 +1057,7 @@ def test_points_overlay_categorical_xaxis_invert_axis(self): self.assertEqual(x_range.factors, ['A', 'B', 'C', 'D'][::-1]) def test_points_overlay_categorical_xaxis_invert_axes(self): - points = Points((['A', 'B', 'C'], (1,2,3)))(plot=dict(invert_axes=True)) + points = Points((['A', 'B', 'C'], (1,2,3))).opts(plot=dict(invert_axes=True)) points2 = Points((['B', 'C', 'D'], (1,2,3))) plot = bokeh_renderer.get_plot(points*points2) y_range = plot.handles['y_range'] @@ -1076,7 +1076,7 @@ def test_heatmap_categorical_axes_string_int(self): def test_heatmap_categorical_axes_string_int_invert_xyaxis(self): opts = dict(invert_xaxis=True, invert_yaxis=True) - hmap = HeatMap([('A',1, 1), ('B', 2, 2)])(plot=opts) + hmap = HeatMap([('A',1, 1), ('B', 2, 2)]).opts(plot=opts) plot = bokeh_renderer.get_plot(hmap) x_range = plot.handles['x_range'] y_range = plot.handles['y_range'] @@ -1086,7 +1086,7 @@ def test_heatmap_categorical_axes_string_int_invert_xyaxis(self): self.assertEqual(y_range.factors, ['1', '2'][::-1]) def test_heatmap_categorical_axes_string_int_inverted(self): - hmap = HeatMap([('A',1, 1), ('B', 2, 2)])(plot=dict(invert_axes=True)) + hmap = HeatMap([('A',1, 1), ('B', 2, 2)]).opts(plot=dict(invert_axes=True)) plot = bokeh_renderer.get_plot(hmap) x_range = plot.handles['x_range'] y_range = plot.handles['y_range'] @@ -1107,7 +1107,7 @@ def test_heatmap_points_categorical_axes_string_int(self): self.assertEqual(y_range.factors, ['1', '2', '3']) def test_heatmap_points_categorical_axes_string_int_inverted(self): - hmap = HeatMap([('A',1, 1), ('B', 2, 2)])(plot=dict(invert_axes=True)) + hmap = HeatMap([('A',1, 1), ('B', 2, 2)]).opts(plot=dict(invert_axes=True)) points = Points([('A', 2), ('B', 1), ('C', 3)]) plot = bokeh_renderer.get_plot(hmap*points) x_range = plot.handles['x_range'] @@ -1138,7 +1138,7 @@ def test_points_errorbars_text_ndoverlay_categorical_xaxis_invert_axes(self): overlay = NdOverlay({i: Points(([chr(65+i)]*10,np.random.randn(10))) for i in range(5)}) error = ErrorBars([(el['x'][0], np.mean(el['y']), np.std(el['y'])) - for el in overlay])(plot=dict(invert_axes=True)) + for el in overlay]).opts(plot=dict(invert_axes=True)) text = Text('C', 0, 'Test') plot = bokeh_renderer.get_plot(overlay*error*text) x_range = plot.handles['x_range'] @@ -1148,7 +1148,7 @@ def test_points_errorbars_text_ndoverlay_categorical_xaxis_invert_axes(self): self.assertEqual(y_range.factors, ['A', 'B', 'C', 'D', 'E']) def test_hline_invert_axes(self): - hline = HLine(1.1)(plot=dict(invert_axes=True)) + hline = HLine(1.1).opts(plot=dict(invert_axes=True)) plot = bokeh_renderer.get_plot(hline) span = plot.handles['glyph'] self.assertEqual(span.dimension, 'height') @@ -1162,7 +1162,7 @@ def test_hline_plot(self): self.assertEqual(span.location, 1.1) def test_vline_invert_axes(self): - vline = VLine(1.1)(plot=dict(invert_axes=True)) + vline = VLine(1.1).opts(plot=dict(invert_axes=True)) plot = bokeh_renderer.get_plot(vline) span = plot.handles['glyph'] self.assertEqual(span.dimension, 'width') @@ -1231,19 +1231,19 @@ def test_curve_heterogeneous_datetime_types_with_pd_overlay(self): self.assertEqual(plot.handles['x_range'].end, np.datetime64(dt.datetime(2016, 1, 13))) def test_curve_fontsize_xlabel(self): - curve = Curve(range(10))(plot=dict(fontsize={'xlabel': '14pt'})) + curve = Curve(range(10)).opts(plot=dict(fontsize={'xlabel': '14pt'})) plot = bokeh_renderer.get_plot(curve) self.assertEqual(plot.handles['xaxis'].axis_label_text_font_size, {'value': '14pt'}) def test_curve_fontsize_ylabel(self): - curve = Curve(range(10))(plot=dict(fontsize={'ylabel': '14pt'})) + curve = Curve(range(10)).opts(plot=dict(fontsize={'ylabel': '14pt'})) plot = bokeh_renderer.get_plot(curve) self.assertEqual(plot.handles['yaxis'].axis_label_text_font_size, {'value': '14pt'}) def test_curve_fontsize_both_labels(self): - curve = Curve(range(10))(plot=dict(fontsize={'labels': '14pt'})) + curve = Curve(range(10)).opts(plot=dict(fontsize={'labels': '14pt'})) plot = bokeh_renderer.get_plot(curve) self.assertEqual(plot.handles['xaxis'].axis_label_text_font_size, {'value': '14pt'}) @@ -1251,19 +1251,19 @@ def test_curve_fontsize_both_labels(self): {'value': '14pt'}) def test_curve_fontsize_xticks(self): - curve = Curve(range(10))(plot=dict(fontsize={'xticks': '14pt'})) + curve = Curve(range(10)).opts(plot=dict(fontsize={'xticks': '14pt'})) plot = bokeh_renderer.get_plot(curve) self.assertEqual(plot.handles['xaxis'].major_label_text_font_size, {'value': '14pt'}) def test_curve_fontsize_yticks(self): - curve = Curve(range(10))(plot=dict(fontsize={'yticks': '14pt'})) + curve = Curve(range(10)).opts(plot=dict(fontsize={'yticks': '14pt'})) plot = bokeh_renderer.get_plot(curve) self.assertEqual(plot.handles['yaxis'].major_label_text_font_size, {'value': '14pt'}) def test_curve_fontsize_both_ticks(self): - curve = Curve(range(10))(plot=dict(fontsize={'ticks': '14pt'})) + curve = Curve(range(10)).opts(plot=dict(fontsize={'ticks': '14pt'})) plot = bokeh_renderer.get_plot(curve) self.assertEqual(plot.handles['xaxis'].major_label_text_font_size, {'value': '14pt'}) @@ -1271,7 +1271,7 @@ def test_curve_fontsize_both_ticks(self): {'value': '14pt'}) def test_curve_fontsize_xticks_and_both_ticks(self): - curve = Curve(range(10))(plot=dict(fontsize={'xticks': '18pt', 'ticks': '14pt'})) + curve = Curve(range(10)).opts(plot=dict(fontsize={'xticks': '18pt', 'ticks': '14pt'})) plot = bokeh_renderer.get_plot(curve) self.assertEqual(plot.handles['xaxis'].major_label_text_font_size, {'value': '18pt'}) @@ -1381,57 +1381,57 @@ def test_layout_instantiate_subplots_transposed(self): self.assertEqual(sorted(plot.subplots.keys()), positions) def test_element_show_frame_disabled(self): - curve = Curve(range(10))(plot=dict(show_frame=False)) + curve = Curve(range(10)).opts(plot=dict(show_frame=False)) plot = bokeh_renderer.get_plot(curve).state self.assertEqual(plot.outline_line_alpha, 0) def test_overlay_show_frame_disabled(self): - overlay = (Curve(range(10)) * Curve(range(10)))(plot=dict(show_frame=False)) + overlay = (Curve(range(10)) * Curve(range(10))).opts(plot=dict(show_frame=False)) plot = bokeh_renderer.get_plot(overlay).state self.assertEqual(plot.outline_line_alpha, 0) def test_element_no_xaxis(self): - curve = Curve(range(10))(plot=dict(xaxis=None)) + curve = Curve(range(10)).opts(plot=dict(xaxis=None)) plot = bokeh_renderer.get_plot(curve).state self.assertFalse(plot.xaxis[0].visible) def test_element_no_yaxis(self): - curve = Curve(range(10))(plot=dict(yaxis=None)) + curve = Curve(range(10)).opts(plot=dict(yaxis=None)) plot = bokeh_renderer.get_plot(curve).state self.assertFalse(plot.yaxis[0].visible) def test_overlay_no_xaxis(self): - overlay = (Curve(range(10)) * Curve(range(10)))(plot=dict(xaxis=None)) + overlay = (Curve(range(10)) * Curve(range(10))).opts(plot=dict(xaxis=None)) plot = bokeh_renderer.get_plot(overlay).state self.assertFalse(plot.xaxis[0].visible) def test_overlay_no_yaxis(self): - overlay = (Curve(range(10)) * Curve(range(10)))(plot=dict(yaxis=None)) + overlay = (Curve(range(10)) * Curve(range(10))).opts(plot=dict(yaxis=None)) plot = bokeh_renderer.get_plot(overlay).state self.assertFalse(plot.yaxis[0].visible) def test_element_xrotation(self): - curve = Curve(range(10))(plot=dict(xrotation=90)) + curve = Curve(range(10)).opts(plot=dict(xrotation=90)) plot = bokeh_renderer.get_plot(curve).state self.assertEqual(plot.xaxis[0].major_label_orientation, np.pi/2) def test_element_yrotation(self): - curve = Curve(range(10))(plot=dict(yrotation=90)) + curve = Curve(range(10)).opts(plot=dict(yrotation=90)) plot = bokeh_renderer.get_plot(curve).state self.assertEqual(plot.yaxis[0].major_label_orientation, np.pi/2) def test_overlay_xrotation(self): - overlay = (Curve(range(10)) * Curve(range(10)))(plot=dict(xrotation=90)) + overlay = (Curve(range(10)) * Curve(range(10))).opts(plot=dict(xrotation=90)) plot = bokeh_renderer.get_plot(overlay).state self.assertEqual(plot.xaxis[0].major_label_orientation, np.pi/2) def test_overlay_yrotation(self): - overlay = (Curve(range(10)) * Curve(range(10)))(plot=dict(yrotation=90)) + overlay = (Curve(range(10)) * Curve(range(10))).opts(plot=dict(yrotation=90)) plot = bokeh_renderer.get_plot(overlay).state self.assertEqual(plot.yaxis[0].major_label_orientation, np.pi/2) def test_element_xticks_list(self): - curve = Curve(range(10))(plot=dict(xticks=[0, 5, 10])) + curve = Curve(range(10)).opts(plot=dict(xticks=[0, 5, 10])) plot = bokeh_renderer.get_plot(curve).state self.assertIsInstance(plot.xaxis[0].ticker, FixedTicker) self.assertEqual(plot.xaxis[0].ticker.ticks, [0, 5, 10]) @@ -1440,13 +1440,13 @@ def test_element_xticks_list_of_tuples_xaxis(self): if bokeh_version < str('0.12.6'): raise SkipTest('Bokeh 0.12.6 required for specifying explicit tick labels') ticks = [(0, 'zero'), (5, 'five'), (10, 'ten')] - curve = Curve(range(10))(plot=dict(xticks=ticks)) + curve = Curve(range(10)).opts(plot=dict(xticks=ticks)) plot = bokeh_renderer.get_plot(curve).state self.assertIsInstance(plot.xaxis[0].ticker, FixedTicker) self.assertEqual(plot.xaxis[0].major_label_overrides, dict(ticks)) def test_element_yticks_list(self): - curve = Curve(range(10))(plot=dict(yticks=[0, 5, 10])) + curve = Curve(range(10)).opts(plot=dict(yticks=[0, 5, 10])) plot = bokeh_renderer.get_plot(curve).state self.assertIsInstance(plot.yaxis[0].ticker, FixedTicker) self.assertEqual(plot.yaxis[0].ticker.ticks, [0, 5, 10]) @@ -1455,19 +1455,19 @@ def test_element_xticks_list_of_tuples_yaxis(self): if bokeh_version < str('0.12.6'): raise SkipTest('Bokeh 0.12.6 required for specifying explicit tick labels') ticks = [(0, 'zero'), (5, 'five'), (10, 'ten')] - curve = Curve(range(10))(plot=dict(yticks=ticks)) + curve = Curve(range(10)).opts(plot=dict(yticks=ticks)) plot = bokeh_renderer.get_plot(curve).state self.assertIsInstance(plot.yaxis[0].ticker, FixedTicker) self.assertEqual(plot.yaxis[0].major_label_overrides, dict(ticks)) def test_overlay_xticks_list(self): - overlay = (Curve(range(10)) * Curve(range(10)))(plot=dict(xticks=[0, 5, 10])) + overlay = (Curve(range(10)) * Curve(range(10))).opts(plot=dict(xticks=[0, 5, 10])) plot = bokeh_renderer.get_plot(overlay).state self.assertIsInstance(plot.xaxis[0].ticker, FixedTicker) self.assertEqual(plot.xaxis[0].ticker.ticks, [0, 5, 10]) def test_overlay_yticks_list(self): - overlay = (Curve(range(10)) * Curve(range(10)))(plot=dict(yticks=[0, 5, 10])) + overlay = (Curve(range(10)) * Curve(range(10))).opts(plot=dict(yticks=[0, 5, 10])) plot = bokeh_renderer.get_plot(overlay).state self.assertIsInstance(plot.yaxis[0].ticker, FixedTicker) self.assertEqual(plot.yaxis[0].ticker.ticks, [0, 5, 10]) @@ -1499,7 +1499,7 @@ def test_shared_axes(self): def test_shared_axes_disable(self): curve = Curve(range(10)) - img = Image(np.random.rand(10,10))(plot=dict(shared_axes=False)) + img = Image(np.random.rand(10,10)).opts(plot=dict(shared_axes=False)) plot = bokeh_renderer.get_plot(curve+img) plot = plot.subplots[(0, 1)].subplots['main'] x_range, y_range = plot.handles['x_range'], plot.handles['y_range'] @@ -1529,7 +1529,7 @@ def test_layout_shared_source_synced_update(self): # Pop key (1,) for one of the HoloMaps and make Layout hmap2.pop((1,)) - layout = (hmap1 + hmap2)(plot=dict(shared_datasource=True)) + layout = (hmap1 + hmap2).opts(plot=dict(shared_datasource=True)) # Get plot plot = bokeh_renderer.get_plot(layout) @@ -1566,7 +1566,7 @@ def test_grid_shared_source_synced_update(self): # Pop key (1,) for one of the HoloMaps and make GridSpace hmap2.pop(1) - grid = GridSpace({0: hmap1, 2: hmap2}, kdims=['X'])(plot=dict(shared_datasource=True)) + grid = GridSpace({0: hmap1, 2: hmap2}, kdims=['X']).opts(plot=dict(shared_datasource=True)) # Get plot plot = bokeh_renderer.get_plot(grid)