Add opts in doc 2

examples/gallery/apps/bokeh/game_of_life.py

@@ -76,6 +76,6 @@ def update(pattern, counter, x, y):
 pattern_dim = hv.Dimension('Pattern', values=sorted(shapes.keys()))
 dmap = hv.DynamicMap(update, kdims=[pattern_dim], streams=[counter, tap])
 
-doc = renderer.server_doc(dmap.redim.range(z=(0, 1))(**opts))
+doc = renderer.server_doc(dmap.redim.range(z=(0, 1)).opts(**opts))
 dmap.periodic(0.05, None)
 doc.title = 'Game of Life'

examples/gallery/demos/bokeh/area_chart.ipynb

@@ -61,7 +61,7 @@
    "source": [
     "style = dict(fill_alpha=0.5)\n",
     "\n",
-    "overlay = (python * pypy * jython)(style={'Area': style})\n",
+    "overlay = (python * pypy * jython).opts(style={'Area': style})\n",
     "overlay.relabel(\"Area Chart\") + hv.Area.stack(overlay).relabel(\"Stacked Area Chart\")"
    ]
   }

examples/gallery/demos/bokeh/bachelors_degrees_by_gender.ipynb

@@ -82,7 +82,7 @@
     "max_year = ds['year'].max()\n",
     "def get_labels():\n",
     "     return hv.NdOverlay({deg: hv.Text(max_year, ds[max_year, deg]+y_offsets.get(deg, 0),\n",
-    "                                        deg, halign='left', fontsize=10)(style=dict(color=col))\n",
+    "                                        deg, halign='left', fontsize=10).opts(style=dict(color=col))\n",
     "                            for deg, col in zip(df.Degree.unique(), color_sequence)})"
    ]
   },

examples/gallery/demos/bokeh/histogram_example.ipynb

@@ -124,7 +124,7 @@
     "                      'plot': dict(height=350, width=350, bgcolor=\"#E8DDCB\")},\n",
     "        'Curve': {'norm': no_norm}, 'Layout': {'plot': dict(shared_axes=False)}}\n",
     "\n",
-    "(norm + lognorm + gamma + beta + weibull)(opts).cols(2)"
+    "(norm + lognorm + gamma + beta + weibull).opts(opts).cols(2)"
    ]
   }
  ],

examples/gallery/demos/bokeh/legend_example.ipynb

@@ -59,7 +59,7 @@
     "example1 = scatter1 * scatter2(style=dict(color='orange')) * scatter3(style=dict(color='green'))\n",
     "example2 = (\n",
     "    scatter1 * hv.Curve(scatter1) *\n",
-    "    hv.Curve(scatter2)(style=dict(line_dash=(4, 4), color='orange')) *\n",
+    "    hv.Curve(scatter2).opts(style=dict(line_dash=(4, 4), color='orange')) *\n",
     "    scatter3(style=dict(line_color='green', marker='square', fill_alpha=0, size=5)) * hv.Curve(scatter3)\n",
     ")\n",
     "\n",

examples/gallery/demos/bokeh/measles_example.ipynb

@@ -71,7 +71,7 @@
     "\n",
     "opts = {'HeatMap': {'plot': hm_opts}, 'Overlay': {'plot': overlay_opts}, 'VLine': {'style': vline_opts}}\n",
     "\n",
-    "(heatmap + agg * vline * marker)(opts).cols(1)"
+    "(heatmap + agg * vline * marker).opts(opts).cols(1)"
    ]
   }
  ],

examples/gallery/demos/bokeh/stocks_example.ipynb

@@ -78,8 +78,8 @@
     "scatter_style = dict(alpha=0.2, size=4, color='darkgrey')\n",
     "curve_style = dict(color='navy')\n",
     "\n",
-    "((aapl * goog * ibm * msft)(plot=plot_opts) +\n",
-    "(avg_scatter(style=scatter_style) * avg_curve(style=curve_style))(plot=plot_opts))"
+    "((aapl * goog * ibm * msft).opts(plot=plot_opts) +\n",
+    "(avg_scatter(style=scatter_style) * avg_curve(style=curve_style)).opts(plot=plot_opts))"
    ]
   }
  ],

examples/gallery/demos/matplotlib/area_chart.ipynb

@@ -62,7 +62,7 @@
    "source": [
     "style = dict(alpha=0.5)\n",
     "\n",
-    "overlay = (python * pypy * jython)(style={'Area': style})\n",
+    "overlay = (python * pypy * jython).opts(style={'Area': style})\n",
     "overlay.relabel(\"Area Chart\") + hv.Area.stack(overlay).relabel(\"Stacked Area Chart\")"
    ]
   }

examples/gallery/demos/matplotlib/bachelors_degrees_by_gender.ipynb

@@ -83,7 +83,7 @@
     "max_year = ds['year'].max()\n",
     "def get_labels():\n",
     "     return hv.NdOverlay({deg: hv.Text(max_year, ds[max_year, deg]+y_offsets.get(deg, 0),\n",
-    "                                        deg, halign='left', fontsize=10)(style=dict(color=col))\n",
+    "                                        deg, halign='left', fontsize=10).opts(style=dict(color=col))\n",
     "                            for deg, col in zip(df.Degree.unique(), color_sequence)})"
    ]
   },

examples/gallery/demos/matplotlib/histogram_example.ipynb

@@ -124,7 +124,7 @@
     "                      'plot': dict(bgcolor=\"#E8DDCB\")},\n",
     "        'Curve': {'norm': no_norm}, 'Layout': {'plot': dict(hspace=0.2)}}\n",
     "\n",
-    "(norm + lognorm + gamma + beta + weibull)(opts).cols(2)"
+    "(norm + lognorm + gamma + beta + weibull).opts(opts).cols(2)"
    ]
   }
  ],

examples/gallery/demos/matplotlib/legend_example.ipynb

@@ -59,7 +59,7 @@
     "example1 = scatter1 * scatter2(style=dict(color='orange')) * scatter3(style=dict(color='green'))\n",
     "example2 = (\n",
     "    scatter1 * hv.Curve(scatter1) *\n",
-    "    hv.Curve(scatter2)(style=dict(linestyle='--', color='orange')) *\n",
+    "    hv.Curve(scatter2).opts(style=dict(linestyle='--', color='orange')) *\n",
     "    scatter3(style=dict(color='green', marker='s')) * hv.Curve(scatter3)\n",
     ")\n",
     "\n",

examples/gallery/demos/matplotlib/measles_example.ipynb

@@ -74,7 +74,7 @@
     "opts = {'Layout': {'plot': layout_opts}, 'HeatMap': {'plot': hm_opts},\n",
     "        'Overlay': {'plot': overlay_opts}, 'VLine': {'style': vline_opts}}\n",
     "\n",
-    "(heatmap + agg * vline * marker)(opts).cols(1)"
+    "(heatmap + agg * vline * marker).opts(opts).cols(1)"
    ]
   }
  ],

examples/gallery/demos/matplotlib/stocks_example.ipynb

@@ -79,8 +79,8 @@
     "scatter_style = dict(alpha=0.2, size=4, color='darkgrey')\n",
     "curve_style = dict(color='navy')\n",
     "\n",
-    "(aapl * goog * ibm * msft)(plot=plot_opts) +\\\n",
-    "(avg_scatter(style=scatter_style) * avg_curve(style=curve_style))(plot=plot_opts)"
+    "(aapl * goog * ibm * msft).opts(plot=plot_opts) +\\\n",
+    "(avg_scatter(style=scatter_style) * avg_curve(style=curve_style)).opts(plot=plot_opts)"
    ]
   }
  ],

examples/reference/elements/bokeh/Curve.ipynb

@@ -71,7 +71,7 @@
    "outputs": [],
    "source": [
     "%%opts Curve [width=600] NdOverlay [legend_position='right']\n",
-    "hv.NdOverlay({interp: hv.Curve(points[::8])(plot=dict(interpolation=interp))\n",
+    "hv.NdOverlay({interp: hv.Curve(points[::8]).opts(plot=dict(interpolation=interp))\n",
     "              for interp in ['linear', 'steps-mid', 'steps-pre', 'steps-post']})"
    ]
   }

examples/reference/elements/bokeh/Polygons.ipynb

@@ -63,9 +63,9 @@
     "def rectangle(x=0, y=0, width=1, height=1):\n",
     "    return np.array([(x,y), (x+width, y), (x+width, y+height), (x, y+height)])\n",
     "\n",
-    "(hv.Polygons([rectangle(width=2), rectangle(x=6, width=2)])(style={'fill_color': '#a50d0d'})\n",
-    "* hv.Polygons([rectangle(x=2, height=2), rectangle(x=5, height=2)])(style={'fill_color': '#ffcc00'})\n",
-    "* hv.Polygons([rectangle(x=3, height=2, width=2)])(style={'fill_color': 'cyan'}))"
+    "(hv.Polygons([rectangle(width=2), rectangle(x=6, width=2)]).opts(style={'fill_color': '#a50d0d'})\n",
+    "* hv.Polygons([rectangle(x=2, height=2), rectangle(x=5, height=2)]).opts(style={'fill_color': '#ffcc00'})\n",
+    "* hv.Polygons([rectangle(x=3, height=2, width=2)]).opts(style={'fill_color': 'cyan'}))"
    ]
   }
  ],

examples/reference/elements/bokeh/Spikes.ipynb

@@ -93,8 +93,8 @@
    "outputs": [],
    "source": [
     "%%opts Spikes [spike_length=0.1] NdOverlay [show_legend=False]\n",
-    "hv.NdOverlay({i: hv.Spikes(np.random.randint(0, 100, 10), kdims=['Time'])(plot=dict(position=0.1*i))\n",
-    "              for i in range(10)})(plot=dict(yticks=[((i+1)*0.1-0.05, i) for i in range(10)]))"
+    "hv.NdOverlay({i: hv.Spikes(np.random.randint(0, 100, 10), kdims=['Time']).opts(plot=dict(position=0.1*i))\n",
+    "              for i in range(10)}).opts(plot=dict(yticks=[((i+1)*0.1-0.05, i) for i in range(10)]))"
    ]
   },
   {

examples/reference/elements/matplotlib/Curve.ipynb

@@ -71,7 +71,7 @@
    "outputs": [],
    "source": [
     "%%opts NdOverlay [legend_position='right']\n",
-    "hv.NdOverlay({interp: hv.Curve(points[::8])(plot=dict(interpolation=interp))\n",
+    "hv.NdOverlay({interp: hv.Curve(points[::8]).opts(plot=dict(interpolation=interp))\n",
     "              for interp in ['linear', 'steps-mid', 'steps-pre', 'steps-post']})"
    ]
   }

examples/reference/elements/matplotlib/Polygons.ipynb

@@ -63,9 +63,9 @@
     "def rectangle(x=0, y=0, width=1, height=1):\n",
     "    return np.array([(x,y), (x+width, y), (x+width, y+height), (x, y+height)])\n",
     "\n",
-    "(hv.Polygons([rectangle(width=2), rectangle(x=6, width=2)])(style={'facecolor': '#a50d0d'})\n",
-    "* hv.Polygons([rectangle(x=2, height=2), rectangle(x=5, height=2)])(style={'facecolor': '#ffcc00'})\n",
-    "* hv.Polygons([rectangle(x=3, height=2, width=2)])(style={'facecolor': 'cyan'}))"
+    "(hv.Polygons([rectangle(width=2), rectangle(x=6, width=2)]).opts(style={'facecolor': '#a50d0d'})\n",
+    "* hv.Polygons([rectangle(x=2, height=2), rectangle(x=5, height=2)]).opts(style={'facecolor': '#ffcc00'})\n",
+    "* hv.Polygons([rectangle(x=3, height=2, width=2)]).opts(style={'facecolor': 'cyan'}))"
    ]
   }
  ],

examples/reference/elements/matplotlib/Spikes.ipynb

@@ -93,8 +93,8 @@
    "outputs": [],
    "source": [
     "%%opts Spikes [spike_length=0.1] NdOverlay [show_legend=False]\n",
-    "hv.NdOverlay({i: hv.Spikes(np.random.randint(0, 100, 10), kdims=['Time'])(plot=dict(position=0.1*i))\n",
-    "              for i in range(10)})(plot=dict(yticks=[((i+1)*0.1-0.05, i) for i in range(10)]))"
+    "hv.NdOverlay({i: hv.Spikes(np.random.randint(0, 100, 10), kdims=['Time']).opts(plot=dict(position=0.1*i))\n",
+    "              for i in range(10)}).opts(plot=dict(yticks=[((i+1)*0.1-0.05, i) for i in range(10)]))"
    ]
   },
   {

examples/reference/elements/plotly/Curve.ipynb

@@ -70,7 +70,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "hv.NdOverlay({interp: hv.Curve(points[::8])(plot=dict(interpolation=interp))\n",
+    "hv.NdOverlay({interp: hv.Curve(points[::8]).opts(plot=dict(interpolation=interp))\n",
     "              for interp in ['linear', 'steps-mid', 'steps-pre', 'steps-post']})"
    ]
   }

examples/reference/streams/bokeh/Selection1D_points.ipynb

@@ -47,7 +47,7 @@
     "        label = 'Mean x, y: %.3f, %.3f' % tuple(selected.array().mean(axis=0))\n",
     "    else:\n",
     "        label = 'No selection'\n",
-    "    return selected.relabel(label)(style=dict(color='red'))\n",
+    "    return selected.relabel(label).opts(style=dict(color='red'))\n",
     "\n",
     "# Combine points and DynamicMap\n",
     "points + hv.DynamicMap(selected_info, streams=[selection])"

examples/topics/simulation/sri_model.ipynb

@@ -633,7 +633,7 @@
     "%%opts HeatMap [show_values=False aspect=1.5 xrotation=90] Histogram {+axiswise} Layout [fig_size=150]\n",
     "group_colors = zip(quantities, ['Blues', 'Reds', 'Greens', 'Purples'])\n",
     "hv.Layout([hv.Table(df).to.heatmap(['pVaccinated', 'Connections'],\n",
-    "                                   q, [], group=q)(style=dict(cmap=c)).hist()\n",
+    "                                   q, [], group=q).opts(style=dict(cmap=c)).hist()\n",
     "           for q, c in group_colors]).cols(2)"
    ]
   },

examples/user_guide/09-Indexing_and_Selecting_Data.ipynb

@@ -363,7 +363,7 @@
    "outputs": [],
    "source": [
     "img_coords = hv.Points(img.table(), extents=extents)\n",
-    "labeled_img = img * img_coords * hv.Points([img.closest([(5.1,4.9)])])(style=dict(color='r'))\n",
+    "labeled_img = img * img_coords * hv.Points([img.closest([(5.1,4.9)])]).opts(style=dict(color='r'))\n",
     "img + labeled_img + img.sample([(5.1,4.9)])"
    ]
   },
@@ -451,9 +451,9 @@
    "source": [
     "%%output backend='matplotlib' size=120\n",
     "sample_style = dict(edgecolors='k', alpha=1)\n",
-    "all_samples = obs_hmap.table().to.scatter3d()(style=dict(alpha=0.15))\n",
+    "all_samples = obs_hmap.table().to.scatter3d().opts(style=dict(alpha=0.15))\n",
     "sampled = obs_hmap.sample((3,3))\n",
-    "subsamples = sampled.to.scatter3d()(style=sample_style)\n",
+    "subsamples = sampled.to.scatter3d().opts(style=sample_style)\n",
     "all_samples * subsamples + sampled"
    ]
   },
@@ -472,7 +472,7 @@
    "source": [
     "%%output backend='matplotlib' size=120\n",
     "sampled = obs_hmap.sample((3,3), bounds=(2,5,5,10))\n",
-    "subsamples = sampled.to.scatter3d()(style=sample_style)\n",
+    "subsamples = sampled.to.scatter3d().opts(style=sample_style)\n",
     "all_samples * subsamples + sampled"
    ]
   },
@@ -500,7 +500,7 @@
     "                   key_dimensions=['Observation'])\n",
     "all_samples = curve.table().to.points()\n",
     "sampled = curve.sample([0, 2, 4, 6, 8])\n",
-    "sampling = all_samples * sampled.to.points(extents=extents)(style=dict(color='r'))\n",
+    "sampling = all_samples * sampled.to.points(extents=extents).opts(style=dict(color='r'))\n",
     "sampling + sampled"
    ]
   },
@@ -518,7 +518,7 @@
    "outputs": [],
    "source": [
     "sampled = curve.table().select(Observation=(0, 1.1), x={0, 2, 4, 6, 8})\n",
-    "sampling = all_samples * sampled.to.points(extents=extents)(style=dict(color='r'))\n",
+    "sampling = all_samples * sampled.to.points(extents=extents).opts(style=dict(color='r'))\n",
     "sampling + sampled"
    ]
   },

examples/user_guide/14-Large_Data.ipynb

@@ -225,7 +225,7 @@
     "\n",
     "from datashader.colors import Sets1to3 # default datashade() and shade() color cycle\n",
     "color_key = list(enumerate(Sets1to3[0:num_ks]))\n",
-    "color_points = hv.NdOverlay({k: hv.Points([0,0], label=str(k))(style=dict(color=v)) for k, v in color_key})\n",
+    "color_points = hv.NdOverlay({k: hv.Points([0,0], label=str(k)).opts(style=dict(color=v)) for k, v in color_key})\n",
     "\n",
     "color_points * gaussspread"
    ]

examples/user_guide/Deploying_Bokeh_Apps.ipynb

@@ -73,7 +73,7 @@
     "        label = 'Mean x, y: %.3f, %.3f' % tuple(arr.mean(axis=0))\n",
     "    else:\n",
     "        label = 'No selection'\n",
-    "    return points.clone(arr, label=label)(style=dict(color='red'))\n",
+    "    return points.clone(arr, label=label).opts(style=dict(color='red'))\n",
     "\n",
     "# Combine points and DynamicMap\n",
     "layout = points + hv.DynamicMap(selected_info, streams=[selection])\n",
@@ -285,7 +285,7 @@
     "\n",
     "renderer = hv.renderers('bokeh')\n",
     "\n",
-    "points = hv.Points(np.random.randn(1000,2 ))(plot=dict(tools=['box_select', 'lasso_select']))\n",
+    "points = hv.Points(np.random.randn(1000,2 )).opts(plot=dict(tools=['box_select', 'lasso_select']))\n",
     "selection = hv.streams.Selection1D(source=points)\n",
     "\n",
     "def selected_info(index):\n",
@@ -294,7 +294,7 @@
     "        label = 'Mean x, y: %.3f, %.3f' % tuple(arr.mean(axis=0))\n",
     "    else:\n",
     "        label = 'No selection'\n",
-    "    return points.clone(arr, label=label)(style=dict(color='red'))\n",
+    "    return points.clone(arr, label=label).opts(style=dict(color='red'))\n",
     "\n",
     "layout = points + hv.DynamicMap(selected_info, streams=[selection])\n",
     "\n",
@@ -336,7 +336,7 @@
    "source": [
     "def sine(frequency, phase, amplitude):\n",
     "    xs = np.linspace(0, np.pi*4)\n",
-    "    return hv.Curve((xs, np.sin(frequency*xs+phase)*amplitude))(plot=dict(width=800))\n",
+    "    return hv.Curve((xs, np.sin(frequency*xs+phase)*amplitude)).opts(plot=dict(width=800))\n",
     "\n",
     "ranges = dict(frequency=(1, 5), phase=(-np.pi, np.pi), amplitude=(-2, 2), y=(-2, 2))\n",
     "dmap = hv.DynamicMap(sine, kdims=['frequency', 'phase', 'amplitude']).redim.range(**ranges)\n",
@@ -498,7 +498,7 @@
     "def sine(counter):\n",
     "    phase = counter*0.1%np.pi*2\n",
     "    xs = np.linspace(0, np.pi*4)\n",
-    "    return hv.Curve((xs, np.sin(xs+phase)))(plot=dict(width=800))\n",
+    "    return hv.Curve((xs, np.sin(xs+phase))).opts(plot=dict(width=800))\n",
     "\n",
     "dmap = hv.DynamicMap(sine, streams=[hv.streams.Counter()])\n",
     "\n",
@@ -564,7 +564,7 @@
     "# Create the holoviews app again\n",
     "def sine(phase):\n",
     "    xs = np.linspace(0, np.pi*4)\n",
-    "    return hv.Curve((xs, np.sin(xs+phase)))(plot=dict(width=800))\n",
+    "    return hv.Curve((xs, np.sin(xs+phase))).opts(plot=dict(width=800))\n",
     "\n",
     "stream = hv.streams.Stream.define('Phase', phase=0.)()\n",
     "dmap = hv.DynamicMap(sine, streams=[stream])\n",

examples/user_guide/Plotting_with_Bokeh.ipynb

@@ -104,9 +104,9 @@
     "xs = np.linspace(0, np.pi*4, 100)\n",
     "data = (xs, np.sin(xs))\n",
     "\n",
-    "(hv.Curve(data)(style=curve_opts) +\n",
-    " hv.Points(data)(style=point_opts) +\n",
-    " hv.Text(6, 0, 'Here is some text')(style=text_opts))"
+    "(hv.Curve(data).opts(style=curve_opts) +\n",
+    " hv.Points(data).opts(style=point_opts) +\n",
+    " hv.Text(6, 0, 'Here is some text').opts(style=text_opts))"
    ]
   },
   {
@@ -168,7 +168,7 @@
     "             ('N Ticks', {'xticks': 3}),\n",
     "             ('List Ticks', {'xticks': [0, 100, 300, 500]})]\n",
     "\n",
-    "hv.Layout([points.relabel(group=group)(plot=opts)\n",
+    "hv.Layout([points.relabel(group=group).opts(plot=opts)\n",
     "           for group, opts in axes_opts]).cols(3).display('all')"
    ]
   },