From d21c1d72a822ad276280e88bedb3ed69bc757a7c Mon Sep 17 00:00:00 2001
From: Philipp Rudiger <philippjfr@continuum.io>
Date: Tue, 11 Dec 2018 01:14:27 +0000
Subject: [PATCH] Updates to matplotlib element references to use opts (#3270)

---
 .../reference/elements/matplotlib/Arrow.ipynb |  7 +++--
 .../reference/elements/matplotlib/Bars.ipynb  |  8 +++---
 .../elements/matplotlib/Bivariate.ipynb       |  8 +++---
 .../elements/matplotlib/Bounds.ipynb          |  4 +--
 .../reference/elements/matplotlib/Box.ipynb   | 14 +++++++---
 .../elements/matplotlib/BoxWhisker.ipynb      |  9 ++++---
 .../reference/elements/matplotlib/Chord.ipynb |  8 +++---
 .../elements/matplotlib/Contours.ipynb        |  5 ++--
 .../reference/elements/matplotlib/Curve.ipynb |  8 +++---
 .../elements/matplotlib/Distribution.ipynb    |  3 +--
 .../elements/matplotlib/Ellipse.ipynb         |  6 +++--
 .../reference/elements/matplotlib/Graph.ipynb | 13 +++++-----
 .../reference/elements/matplotlib/HLine.ipynb |  9 +++++--
 .../reference/elements/matplotlib/HSV.ipynb   |  5 +++-
 .../elements/matplotlib/HeatMap.ipynb         |  7 ++---
 .../elements/matplotlib/HexTiles.ipynb        | 19 +++++++++-----
 .../elements/matplotlib/Histogram.ipynb       |  6 +++--
 .../reference/elements/matplotlib/Image.ipynb |  6 +++--
 .../elements/matplotlib/Labels.ipynb          | 17 ++++++------
 .../elements/matplotlib/Points.ipynb          | 20 +++++++-------
 .../elements/matplotlib/Polygons.ipynb        | 10 +++----
 .../elements/matplotlib/QuadMesh.ipynb        |  5 ++--
 .../reference/elements/matplotlib/RGB.ipynb   |  6 +++--
 .../elements/matplotlib/RadialHeatMap.ipynb   | 13 +++++-----
 .../elements/matplotlib/Sankey.ipynb          | 15 +++++------
 .../elements/matplotlib/Spikes.ipynb          | 26 +++++++++++--------
 .../elements/matplotlib/Spline.ipynb          |  9 +++++--
 .../elements/matplotlib/Spread.ipynb          |  7 ++---
 .../elements/matplotlib/Surface.ipynb         | 18 +++++++++----
 .../reference/elements/matplotlib/Text.ipynb  |  6 +++--
 .../elements/matplotlib/TriMesh.ipynb         |  6 +++--
 .../elements/matplotlib/TriSurface.ipynb      |  8 +++---
 .../reference/elements/matplotlib/VLine.ipynb |  9 +++++--
 .../elements/matplotlib/VectorField.ipynb     | 20 +++++++++-----
 .../elements/matplotlib/Violin.ipynb          |  9 ++++---
 holoviews/plotting/mpl/annotation.py          |  6 ++++-
 .../tests/plotting/matplotlib/testlabels.py   | 15 +++++++----
 37 files changed, 228 insertions(+), 142 deletions(-)

diff --git a/examples/reference/elements/matplotlib/Arrow.ipynb b/examples/reference/elements/matplotlib/Arrow.ipynb
index fc857d79a5..32ce7aeb44 100644
--- a/examples/reference/elements/matplotlib/Arrow.ipynb
+++ b/examples/reference/elements/matplotlib/Arrow.ipynb
@@ -37,10 +37,13 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts  Curve (color='#D3D3D3')\n",
     "xs = np.linspace(-5,5,100)\n",
     "ys = -(xs-2)**3\n",
-    "hv.Curve((xs,ys)) * hv.Arrow(0, 5, 'Inflection', 'v')"
+    "\n",
+    "curve = hv.Curve((xs,ys))\n",
+    "arrow = hv.Arrow(0, 5, 'Inflection', 'v')\n",
+    "\n",
+    "curve.opts(color='#D3D3D3') * arrow"
    ]
   },
   {
diff --git a/examples/reference/elements/matplotlib/Bars.ipynb b/examples/reference/elements/matplotlib/Bars.ipynb
index cc7f3fd91b..021473fd4d 100644
--- a/examples/reference/elements/matplotlib/Bars.ipynb
+++ b/examples/reference/elements/matplotlib/Bars.ipynb
@@ -73,15 +73,17 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts Bars.Grouped [category_index=0 group_index=1 stack_index=5] \n",
-    "%%opts Bars.Stacked [color_by=['stack'] stack_index=1 category_index=5]\n",
     "from itertools import product\n",
     "np.random.seed(3)\n",
     "index, groups = ['A', 'B'], ['a', 'b']\n",
     "keys = product(index, groups)\n",
     "bars = hv.Bars([k+(np.random.rand()*100.,) for k in keys],\n",
     "               ['Index', 'Group'], 'Count')\n",
-    "bars.relabel(group='Grouped') + bars.relabel(group='Stacked')"
+    "\n",
+    "grouped = bars.relabel('Grouped').opts(category_index=5, color_by=['stack'], stack_index=1)\n",
+    "stacked = bars.relabel('Stacked').opts(stack_index=5)\n",
+    "\n",
+    "grouped + stacked"
    ]
   },
   {
diff --git a/examples/reference/elements/matplotlib/Bivariate.ipynb b/examples/reference/elements/matplotlib/Bivariate.ipynb
index 4f2f6804b1..dfe0578edd 100644
--- a/examples/reference/elements/matplotlib/Bivariate.ipynb
+++ b/examples/reference/elements/matplotlib/Bivariate.ipynb
@@ -21,6 +21,8 @@
    "source": [
     "import numpy as np\n",
     "import holoviews as hv\n",
+    "from holoviews import opts\n",
+    "\n",
     "hv.extension('matplotlib')"
    ]
   },
@@ -58,8 +60,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts Bivariate [filled=True colorbar=True] (cmap='Blues')\n",
-    "hv.Bivariate(normal)"
+    "hv.Bivariate(normal).opts(colorbar=True, cmap='Blues', filled=True)"
    ]
   },
   {
@@ -75,8 +76,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts Bivariate {+axiswise}\n",
-    "hv.NdLayout({bw: hv.Bivariate(normal).options(bandwidth=bw)\n",
+    "hv.NdLayout({bw: hv.Bivariate(normal).options(axiswise=True, bandwidth=bw)\n",
     "             for bw in [0.05, 0.1, 0.5, 1]}, 'Bandwidth')"
    ]
   },
diff --git a/examples/reference/elements/matplotlib/Bounds.ipynb b/examples/reference/elements/matplotlib/Bounds.ipynb
index 25e834af88..1857ae7db5 100644
--- a/examples/reference/elements/matplotlib/Bounds.ipynb
+++ b/examples/reference/elements/matplotlib/Bounds.ipynb
@@ -36,9 +36,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts Bounds (color='orange' linewidth=6)\n",
     "penguins = hv.RGB.load_image('../assets/penguins.png')\n",
-    "penguins * hv.Bounds((-0.15, -0.4, 0.2, 0))"
+    "bounds = hv.Bounds((-0.15, -0.4, 0.2, 0))\n",
+    "penguins * bounds.opts(color='orange', linewidth=6)"
    ]
   },
   {
diff --git a/examples/reference/elements/matplotlib/Box.ipynb b/examples/reference/elements/matplotlib/Box.ipynb
index 3add4f43eb..b0a42a8c30 100644
--- a/examples/reference/elements/matplotlib/Box.ipynb
+++ b/examples/reference/elements/matplotlib/Box.ipynb
@@ -21,6 +21,8 @@
    "source": [
     "import numpy as np\n",
     "import holoviews as hv\n",
+    "from holoviews import opts\n",
+    "\n",
     "hv.extension('matplotlib')"
    ]
   },
@@ -37,11 +39,12 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts Box (linewidth=5 color='red') Image (cmap='gray')\n",
     "data = np.sin(np.mgrid[0:100,0:100][1]/10.0)\n",
     "data[np.arange(40, 60), np.arange(20, 40)] = -1\n",
     "data[np.arange(40, 50), np.arange(70, 80)] = -3    \n",
-    "hv.Image(data) * hv.Box(-0.2, 0, 0.25 ) * hv.Box(-0, 0, (0.4,0.9) )"
+    "(hv.Image(data) * hv.Box(-0.2, 0, 0.25 ) * hv.Box(-0, 0, (0.4,0.9))).opts(\n",
+    "    opts.Box(color='red', linewidth=5),\n",
+    "    opts.Image(cmap='gray'))"
    ]
   },
   {
@@ -59,10 +62,13 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts Box (linewidth=5 color='purple') Image (cmap='gray')\n",
     "data = np.sin(np.mgrid[0:100,0:100][1]/10.0)\n",
     "data[np.arange(30, 70), np.arange(30, 70)] = -3\n",
-    "hv.Image(data) * hv.Box(-0, 0, 0.25, aspect=3, orientation=-np.pi/4)"
+    "box = hv.Box(-0, 0, 0.25, aspect=3, orientation=-np.pi/4)\n",
+    "\n",
+    "(hv.Image(data) * box).opts(\n",
+    "    opts.Box(color='purple', linewidth=5),\n",
+    "    opts.Image(cmap='gray'))"
    ]
   },
   {
diff --git a/examples/reference/elements/matplotlib/BoxWhisker.ipynb b/examples/reference/elements/matplotlib/BoxWhisker.ipynb
index a1308c8079..d42b69fcd2 100644
--- a/examples/reference/elements/matplotlib/BoxWhisker.ipynb
+++ b/examples/reference/elements/matplotlib/BoxWhisker.ipynb
@@ -21,6 +21,8 @@
    "source": [
     "import numpy as np\n",
     "import holoviews as hv\n",
+    "from holoviews import opts\n",
+    "\n",
     "hv.extension('matplotlib')"
    ]
   },
@@ -62,10 +64,11 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts BoxWhisker [aspect=2 fig_size=200 show_legend=False] (whiskerprops={'color': 'gray'})\n",
     "groups = [chr(65+g) for g in np.random.randint(0, 3, 200)]\n",
-    "hv.BoxWhisker((groups, np.random.randint(0, 5, 200), np.random.randn(200)),\n",
-    "              ['Group', 'Category'], 'Value').sort()"
+    "box = hv.BoxWhisker((groups, np.random.randint(0, 5, 200), np.random.randn(200)),\n",
+    "                    ['Group', 'Category'], 'Value').sort()\n",
+    "\n",
+    "box.opts(opts.BoxWhisker(aspect=2, fig_size=200, whiskerprops={'color': 'gray'}))"
    ]
   },
   {
diff --git a/examples/reference/elements/matplotlib/Chord.ipynb b/examples/reference/elements/matplotlib/Chord.ipynb
index aa3924ff61..fb193b0290 100644
--- a/examples/reference/elements/matplotlib/Chord.ipynb
+++ b/examples/reference/elements/matplotlib/Chord.ipynb
@@ -23,10 +23,12 @@
    "source": [
     "import pandas as pd\n",
     "import holoviews as hv\n",
+    "\n",
+    "from holoviews import dim, opts\n",
     "from bokeh.sampledata.les_mis import data\n",
     "\n",
     "hv.extension('matplotlib')\n",
-    "%output size=200 fig='svg'"
+    "hv.output(fig='svg', size=200)"
    ]
   },
   {
@@ -96,8 +98,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts Chord [labels='name'] (node_color=dim('index').astype(str) edge_color=dim('source').astype(str) cmap='Category20' edge_cmap='Category20')\n",
-    "hv.Chord((links, nodes)).select(value=(5, None))"
+    "hv.Chord((links, nodes)).select(value=(5, None)).opts(\n",
+    "    opts.Chord(cmap='Category20', edge_color=dim('source').astype(str), labels='name', node_color=dim('index').astype(str)))"
    ]
   }
  ],
diff --git a/examples/reference/elements/matplotlib/Contours.ipynb b/examples/reference/elements/matplotlib/Contours.ipynb
index 3cedf8afa8..cc728d23c5 100644
--- a/examples/reference/elements/matplotlib/Contours.ipynb
+++ b/examples/reference/elements/matplotlib/Contours.ipynb
@@ -60,12 +60,11 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts Contours [colorbar=True] (cmap='fire')\n",
     "x,y = np.mgrid[-50:51, -50:51] * 0.05\n",
     "img = hv.Image(np.sin(x**2+y**3))\n",
+    "contours = hv.operation.contours(img, levels=5)\n",
     "\n",
-    "z0, z1 = img.range('z')\n",
-    "img + hv.operation.contours(img, levels=5)"
+    "img + contours.opts(colorbar=True, cmap='fire')"
    ]
   },
   {
diff --git a/examples/reference/elements/matplotlib/Curve.ipynb b/examples/reference/elements/matplotlib/Curve.ipynb
index 1d6016862e..6486bdc3ad 100644
--- a/examples/reference/elements/matplotlib/Curve.ipynb
+++ b/examples/reference/elements/matplotlib/Curve.ipynb
@@ -70,9 +70,11 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts NdOverlay [legend_position='right']\n",
-    "hv.NdOverlay({interp: hv.Curve(points[::8]).options(interpolation=interp)\n",
-    "              for interp in ['linear', 'steps-mid', 'steps-pre', 'steps-post']})"
+    "overlay = hv.NdOverlay({\n",
+    "    interp: hv.Curve(points[::8]).options(interpolation=interp)\n",
+    "    for interp in ['linear', 'steps-mid', 'steps-pre', 'steps-post']})\n",
+    "\n",
+    "overlay.opts(legend_position='right')"
    ]
   },
   {
diff --git a/examples/reference/elements/matplotlib/Distribution.ipynb b/examples/reference/elements/matplotlib/Distribution.ipynb
index e9c82442b8..ddfb9d5922 100644
--- a/examples/reference/elements/matplotlib/Distribution.ipynb
+++ b/examples/reference/elements/matplotlib/Distribution.ipynb
@@ -62,8 +62,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts Distribution [filled=False] (alpha=1)\n",
-    "hv.NdOverlay({bw: hv.Distribution(normal).options(bandwidth=bw)\n",
+    "hv.NdOverlay({bw: hv.Distribution(normal).opts(alpha=1, bandwidth=bw, filled=False)\n",
     "              for bw in [0.05, 0.1, 0.5, 1]}, 'Bandwidth')"
    ]
   },
diff --git a/examples/reference/elements/matplotlib/Ellipse.ipynb b/examples/reference/elements/matplotlib/Ellipse.ipynb
index cf91d51a08..37f26c388c 100644
--- a/examples/reference/elements/matplotlib/Ellipse.ipynb
+++ b/examples/reference/elements/matplotlib/Ellipse.ipynb
@@ -21,6 +21,8 @@
    "source": [
     "import numpy as np\n",
     "import holoviews as hv\n",
+    "from holoviews import opts\n",
+    "\n",
     "hv.extension('matplotlib')"
    ]
   },
@@ -37,7 +39,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts Ellipse (linewidth=6)\n",
+    "opts.defaults(opts.Ellipse(linewidth=6))\n",
+    "\n",
     "# Generate some data\n",
     "c1 = np.random.normal(loc=2, scale=0.2, size=(200,200))\n",
     "c2x = np.random.normal(loc=-2, scale=0.6, size=200)\n",
@@ -61,7 +64,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts Ellipse (linewidth=6)\n",
     "clusters = hv.Points(c1) * hv.Points((c2x, c2y)) * hv.Points(c3)\n",
     "clusters *  hv.Ellipse(0,0, 4, orientation=np.pi/5, aspect=2) "
    ]
diff --git a/examples/reference/elements/matplotlib/Graph.ipynb b/examples/reference/elements/matplotlib/Graph.ipynb
index 76dadf13d8..1300f643c0 100644
--- a/examples/reference/elements/matplotlib/Graph.ipynb
+++ b/examples/reference/elements/matplotlib/Graph.ipynb
@@ -23,6 +23,7 @@
    "source": [
     "import numpy as np\n",
     "import holoviews as hv\n",
+    "from holoviews import opts\n",
     "\n",
     "hv.extension('matplotlib')"
    ]
@@ -60,8 +61,8 @@
     "\n",
     "padding = dict(x=(-1.2, 1.2), y=(-1.2, 1.2))\n",
     "\n",
-    "simple_graph = hv.Graph(((source, target),)).options(padding=0.1)\n",
-    "simple_graph"
+    "simple_graph = hv.Graph(((source, target),))\n",
+    "simple_graph.opts(padding=0.1)"
    ]
   },
   {
@@ -79,7 +80,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "simple_graph.options(directed=True, arrowhead_length=0.08)"
+    "simple_graph.opts(directed=True, arrowhead_length=0.08)"
    ]
   },
   {
@@ -107,7 +108,7 @@
     "#### Additional features\n",
     "\n",
     "\n",
-    "Next we will extend this example by supplying explicit edges, node information and edge weights. By constructing the ``Nodes`` explicitly we can declare an additional value dimensions, which are revealed when hovering and/or can be mapped to the color by specifying the ``color_index``. We can also associate additional information with each edge by supplying a value dimension to the ``Graph`` itself, which we can map to a color using the ``edge_color_index``."
+    "Next we will extend this example by supplying explicit edges, node information and edge weights. By constructing the ``Nodes`` explicitly we can declare an additional value dimensions, which are revealed when hovering and/or can be mapped to the color by specifying the ``color``. We can also associate additional information with each edge by supplying a value dimension to the ``Graph`` itself, which we can map to a color using the ``edge_color``."
    ]
   },
   {
@@ -135,8 +136,8 @@
     "nodes = hv.Nodes((x, y, node_indices, node_labels), vdims='Type')\n",
     "graph = hv.Graph(((source, target, edge_weights), nodes, paths), vdims='Weight')\n",
     "\n",
-    "graph.redim.range(**padding).options(color_index='Type', edge_color_index='Weight',\n",
-    "                                     cmap=['blue', 'red'], edge_cmap='viridis')"
+    "graph.opts(\n",
+    "    opts.Graph(cmap=['blue', 'red'], edge_cmap='viridis', edge_color='Weight', node_color='Type', padding=0.1))"
    ]
   },
   {
diff --git a/examples/reference/elements/matplotlib/HLine.ipynb b/examples/reference/elements/matplotlib/HLine.ipynb
index bbd7f102c6..ef7b40b2f1 100644
--- a/examples/reference/elements/matplotlib/HLine.ipynb
+++ b/examples/reference/elements/matplotlib/HLine.ipynb
@@ -21,6 +21,8 @@
    "source": [
     "import numpy as np\n",
     "import holoviews as hv\n",
+    "from holoviews import opts\n",
+    "\n",
     "hv.extension('matplotlib')"
    ]
   },
@@ -37,10 +39,13 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts HLine (color='blue' linewidth=6) Points (color='#D3D3D3')\n",
     "xs = np.random.normal(size=100)\n",
     "ys = np.random.normal(size=100) * xs\n",
-    "hv.Points((xs,ys)) * hv.HLine(ys.mean())"
+    "points = hv.Points((xs,ys))\n",
+    "\n",
+    "(points * hv.HLine(ys.mean())).opts(\n",
+    "    opts.HLine(color='#D3D3D3')\n",
+    "    opts.Points(color='blue', linewidth=6))"
    ]
   },
   {
diff --git a/examples/reference/elements/matplotlib/HSV.ipynb b/examples/reference/elements/matplotlib/HSV.ipynb
index 932ba1b31e..f071af0ced 100644
--- a/examples/reference/elements/matplotlib/HSV.ipynb
+++ b/examples/reference/elements/matplotlib/HSV.ipynb
@@ -21,6 +21,8 @@
    "source": [
     "import numpy as np\n",
     "import holoviews as hv\n",
+    "from holoviews import opts\n",
+    "\n",
     "hv.extension('matplotlib')"
    ]
   },
@@ -67,7 +69,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%opts Image (cmap='gray')\n",
+    "opts.defaults(opts.Image(cmap='gray'))\n",
+    "\n",
     "hsv[..., 'H'].relabel('H') + hsv[..., 'S'].relabel('S') + hsv[..., 'V'].relabel('V')"
    ]
   },
diff --git a/examples/reference/elements/matplotlib/HeatMap.ipynb b/examples/reference/elements/matplotlib/HeatMap.ipynb
index 01b3272efd..e78226c1c3 100644
--- a/examples/reference/elements/matplotlib/HeatMap.ipynb
+++ b/examples/reference/elements/matplotlib/HeatMap.ipynb
@@ -75,9 +75,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts HeatMap [ colorbar=True fig_size=250]\n",
-    "hv.HeatMap((np.random.randint(0, 10, 100), np.random.randint(0, 10, 100),\n",
-    "            np.random.randn(100), np.random.randn(100)), vdims=['z', 'z2']).redim.range(z=(-2, 2))"
+    "heatmap = hv.HeatMap((np.random.randint(0, 10, 100), np.random.randint(0, 10, 100),\n",
+    "                      np.random.randn(100), np.random.randn(100)), vdims=['z', 'z2']).redim.range(z=(-2, 2))\n",
+    "\n",
+    "heatmap.opts(colorbar=True, fig_size=250)"
    ]
   },
   {
diff --git a/examples/reference/elements/matplotlib/HexTiles.ipynb b/examples/reference/elements/matplotlib/HexTiles.ipynb
index 3a311120a3..7575735dac 100644
--- a/examples/reference/elements/matplotlib/HexTiles.ipynb
+++ b/examples/reference/elements/matplotlib/HexTiles.ipynb
@@ -19,8 +19,10 @@
    "source": [
     "import numpy as np\n",
     "import holoviews as hv\n",
+    "from holoviews import opts\n",
+    "\n",
     "hv.extension('matplotlib')\n",
-    "%output fig='svg' size=200"
+    "hv.output(fig='svg', size=200)"
    ]
   },
   {
@@ -40,7 +42,7 @@
    "source": [
     "np.random.seed(44)\n",
     "hex_tiles = hv.HexTiles(np.random.randn(100000, 2))\n",
-    "hex_tiles.options(colorbar=True)"
+    "hex_tiles.opts(colorbar=True)"
    ]
   },
   {
@@ -60,9 +62,11 @@
    "source": [
     "xs, ys = np.random.randn(2, 1000)\n",
     "hex_with_values = hv.HexTiles((xs, ys, xs*(ys/2.), (xs**2)*ys), vdims=['Values', 'Hover Values'])\n",
+    "points = hv.Points(hex_with_values)\n",
     "\n",
-    "hex_with_values.options(aggregator=np.sum) *\\\n",
-    "hv.Points(hex_with_values).options(s=3, color='black')"
+    "(hex_with_values * points).opts(\n",
+    "    opts.HexTiles(aggregator=np.sum),\n",
+    "    opts.Points(s=3, color='black'))"
    ]
   },
   {
@@ -82,8 +86,11 @@
    "source": [
     "x, y = np.hstack([np.random.randn(2, 10000), np.random.randn(2, 10000)*0.8+2])\n",
     "hex_two_distributions = hv.HexTiles((x, y))\n",
-    "hex_two_distributions.options(min_count=0) *\\\n",
-    "hv.Bivariate(hex_two_distributions).options(show_legend=False, linewidth=3)"
+    "bivariate = hv.Bivariate((x, y))\n",
+    "\n",
+    "(hex_two_distributions * bivariate).opts(\n",
+    "    opts.Bivariate(linewidth=3, show_legend=False),\n",
+    "    opts.HexTiles(min_count=0))"
    ]
   }
  ],
diff --git a/examples/reference/elements/matplotlib/Histogram.ipynb b/examples/reference/elements/matplotlib/Histogram.ipynb
index 365864537e..16c1607967 100644
--- a/examples/reference/elements/matplotlib/Histogram.ipynb
+++ b/examples/reference/elements/matplotlib/Histogram.ipynb
@@ -21,6 +21,8 @@
    "source": [
     "import numpy as np\n",
     "import holoviews as hv\n",
+    "from holoviews import opts\n",
+    "\n",
     "hv.extension('matplotlib')"
    ]
   },
@@ -110,14 +112,14 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts Histogram (alpha=0.3)\n",
     "from holoviews.operation import histogram\n",
     "points2 = hv.Points(np.random.randn(100,2)*2+1).redim.range(x=(-5, 5), y=(-5, 5))\n",
     "\n",
     "xhist, yhist = (histogram(points2, bin_range=(-5, 5), dimension=dim) *\n",
     "                histogram(points,  bin_range=(-5, 5), dimension=dim) \n",
     "                for dim in 'xy')\n",
-    "(points2 * points) << yhist(plot=dict(width=125)) << xhist(plot=dict(height=125))"
+    "((points2 * points) << yhist << xhist).opts(\n",
+    "    opts.Histogram(alpha=0.3))"
    ]
   },
   {
diff --git a/examples/reference/elements/matplotlib/Image.ipynb b/examples/reference/elements/matplotlib/Image.ipynb
index d592f23955..6479792731 100644
--- a/examples/reference/elements/matplotlib/Image.ipynb
+++ b/examples/reference/elements/matplotlib/Image.ipynb
@@ -82,10 +82,12 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts Points (color='black' marker='x' size=20)\n",
     "closest = img.closest((0.1,0.1))\n",
+    "points = hv.Points([closest])\n",
+    "\n",
     "print('The value at position %s is %s' % (closest, img[0.1, 0.1]))\n",
-    "img * hv.Points([img.closest((0.1,0.1))])"
+    "\n",
+    "img * points.opts(color='black', marker='x', s=60)"
    ]
   },
   {
diff --git a/examples/reference/elements/matplotlib/Labels.ipynb b/examples/reference/elements/matplotlib/Labels.ipynb
index 068b00ce64..99f20f38dd 100644
--- a/examples/reference/elements/matplotlib/Labels.ipynb
+++ b/examples/reference/elements/matplotlib/Labels.ipynb
@@ -21,6 +21,8 @@
    "source": [
     "import numpy as np\n",
     "import holoviews as hv\n",
+    "from holoviews import opts\n",
+    "\n",
     "hv.extension('matplotlib')"
    ]
   },
@@ -30,7 +32,7 @@
    "source": [
     "The ``Labels`` element may be used to annotate a plot with a number of labels. Unlike the ``Text`` element, ``Labels`` is vectorized and allows plotting many labels at once. It also supports any [tabular](../../../user_guide/07-Tabular_Datasets.ipynb) or [gridded](../../../user_guide/08-Gridded_Datasets.ipynb) data format. This also means that most other elements may be cast to a ``Labels`` element to annotate or label the values.\n",
     "\n",
-    "``Labels`` also support various options that make it convenient to use as an annotation, e.g. ``xoffset`` and ``yoffset`` options allow adjusting the position of the labels relative to an existing data point and the ``color_index`` option allows us to colormap the data by a certain dimension."
+    "``Labels`` also support various options that make it convenient to use as an annotation, e.g. ``xoffset`` and ``yoffset`` options allow adjusting the position of the labels relative to an existing data point and the ``color`` option allows us to colormap the data by a certain dimension."
    ]
   },
   {
@@ -42,11 +44,11 @@
     "np.random.seed(9)\n",
     "data = np.random.rand(10, 2)\n",
     "points = hv.Points(data)\n",
-    "labels = hv.Labels({('x', 'y'): data, 'text': [chr(65+i) for i in range(10)]}, ['x', 'y'], 'text').options(\n",
-    "    color_index='text', cmap='Category20', xoffset=0.05, yoffset=0.05, size=14\n",
-    ")\n",
+    "labels = hv.Labels({('x', 'y'): data, 'text': [chr(65+i) for i in range(10)]}, ['x', 'y'], 'text')\n",
     "\n",
-    "(points.options(color='black', s=25) * labels).redim.range(x=(-0.2, 1.2), y=(-.2, 1.2))"
+    "(points* labels).opts(\n",
+    "    opts.Labels(color='text', cmap='Category20', xoffset=0.05, yoffset=0.05, size=14, padding=0.2),\n",
+    "    opts.Points(color='black', s=25))"
    ]
   },
   {
@@ -68,9 +70,8 @@
     "xs = ys = np.linspace(-2.5, 2.5, 25)\n",
     "zs = np.sin(xs**2)*np.sin(ys**2)[:, np.newaxis]\n",
     "\n",
-    "hv.Labels((xs, ys, zs), vdims=value_dimension).options(\n",
-    "    bgcolor='black', cmap='viridis', color_index='Values', fig_size=200, size=8\n",
-    ").redim.range(x=(-2.6, 2.6), y=(-2.6, 2.6))"
+    "hv.Labels((xs, ys, zs), vdims=value_dimension).opts(\n",
+    "    opts.Labels(bgcolor='black', cmap='viridis', color='Values', fig_size=200, padding=0.05, size=8))"
    ]
   }
  ],
diff --git a/examples/reference/elements/matplotlib/Points.ipynb b/examples/reference/elements/matplotlib/Points.ipynb
index 163735eb74..a76812c406 100644
--- a/examples/reference/elements/matplotlib/Points.ipynb
+++ b/examples/reference/elements/matplotlib/Points.ipynb
@@ -21,6 +21,8 @@
    "source": [
     "import numpy as np\n",
     "import holoviews as hv\n",
+    "from holoviews import dim, opts\n",
+    "\n",
     "hv.extension('matplotlib')"
    ]
   },
@@ -28,7 +30,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "The ``Points`` element visualizes as markers placed in a space of two independent variables, traditionally denoted *x* and *y*. In HoloViews, the names ``'x'`` and ``'y'`` are used as the default ``key_dimensions`` of the element.  We can see this from the default axis labels when visualizing a simple ``Points`` element:"
+    "The ``Points`` element visualizes as markers placed in a space of two independent variables, traditionally denoted ``x`` and ``y``. In HoloViews, the names ``'x'`` and ``'y'`` are used as the default key dimensions (``kdims``) of the element.  We can see this from the default axis labels when visualizing a simple ``Points`` element:"
    ]
   },
   {
@@ -37,17 +39,18 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts Points (color='k' marker='+' size=10)\n",
     "np.random.seed(12)\n",
     "coords = np.random.rand(50,2)\n",
-    "hv.Points(coords)"
+    "points = hv.Points(coords)\n",
+    "\n",
+    "points.opts(color='k', marker='+', s=50)"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Here both the random *x* values and random *y* values are *both* considered to be the 'data' with no dependency between them (compare this to how [``Scatter``](./Scatter.ipynb) elements are defined). You can think of ``Points`` as simply marking positions in some two-dimensional space that can be sliced by specifying a 2D region-of-interest:"
+    "Here both the random ``x`` values and random ``y`` values are *both* considered to be the coordinates with no dependency between them (compare this to how [``Scatter``](./Scatter.ipynb) elements are defined). You can think of ``Points`` as simply marking positions in some two-dimensional space that can be sliced by specifying a 2D region-of-interest:"
    ]
   },
   {
@@ -56,15 +59,14 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts Points (color='k' marker='+' size=10)\n",
-    "hv.Points(coords) + hv.Points(coords)[0.6:0.8,0.2:0.5]"
+    "points + points[0.6:0.8,0.2:0.5]"
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "Although the simplest ``Points`` element simply mark positions in a two-dimensional space without any associated value this doesn't mean value dimensions aren't supported. Here is an example with two additional quantities for each point, declared as the ``value_dimension``s *z* and &alpha; visualized as the color and size of the dots, respectively:"
+    "Although the simplest ``Points`` element simply mark positions in a two-dimensional space without any associated value this doesn't mean value dimensions aren't supported. Here is an example with two additional quantities for each point, declared as the ``vdims``s ``z`` and ``size`` visualized as the color and size of the dots, respectively:"
    ]
   },
   {
@@ -73,12 +75,12 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts Points [color_index=2 size_index=3 scaling_factor=50]\n",
     "np.random.seed(10)\n",
     "data = np.random.rand(100,4)\n",
     "\n",
     "points = hv.Points(data, vdims=['z', 'size'])\n",
-    "points + points[0.3:0.7, 0.3:0.7].hist()"
+    "(points + points[0.3:0.7, 0.3:0.7].hist()).opts(\n",
+    "    opts.Points(color='z', s=dim('size')*50))"
    ]
   },
   {
diff --git a/examples/reference/elements/matplotlib/Polygons.ipynb b/examples/reference/elements/matplotlib/Polygons.ipynb
index da9c13bbaf..4e618f0165 100644
--- a/examples/reference/elements/matplotlib/Polygons.ipynb
+++ b/examples/reference/elements/matplotlib/Polygons.ipynb
@@ -32,7 +32,7 @@
     "\n",
     "In order to efficiently represent the scalar values associated with each path the dictionary format is preferable since it can store the scalar values without expanding them into a whole column. Additionally it allows passing multiple columns as a single array by specifying the dimension names as a tuple.\n",
     "\n",
-    "In this example we will create a list of random polygons each with an associated ``level`` value. Polygons will default to using the first value dimension as the ``color_index`` but for clarity we will define the ``color_index`` explicitly:"
+    "In this example we will create a list of random polygons each with an associated ``level`` value. Polygons will default to using the first value dimension as the ``color`` but for clarity we will define the ``color`` explicitly:"
    ]
   },
   {
@@ -41,13 +41,13 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts Polygons [color_index='level'] (linewidth=1)\n",
-    "\n",
     "def rectangle(x=0, y=0, width=.05, height=.05):\n",
     "    return np.array([(x,y), (x+width, y), (x+width, y+height), (x, y+height)])\n",
     "\n",
-    "hv.Polygons([{('x', 'y'): rectangle(x, y), 'level': z}\n",
-    "             for x, y, z in np.random.rand(100, 3)], vdims='level').redim.range(x=(-.1,1.1), y=(-0.1, 1.1))"
+    "polys = hv.Polygons([{('x', 'y'): rectangle(x, y), 'level': z}\n",
+    "                     for x, y, z in np.random.rand(100, 3)], vdims='level')\n",
+    "\n",
+    "polys.opts(color='level', linewidth=1, padding=0.1)"
    ]
   },
   {
diff --git a/examples/reference/elements/matplotlib/QuadMesh.ipynb b/examples/reference/elements/matplotlib/QuadMesh.ipynb
index cbb9291c88..8cc854b7d1 100644
--- a/examples/reference/elements/matplotlib/QuadMesh.ipynb
+++ b/examples/reference/elements/matplotlib/QuadMesh.ipynb
@@ -70,8 +70,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts QuadMesh [xticks=[10, 100,1000]] QuadMesh.LogScale [logx=True]\n",
-    "hv.QuadMesh((xs, ys, zs), group='LinearScale') + hv.QuadMesh((xs, ys, zs), group='LogScale')"
+    "qmesh = hv.QuadMesh((xs, ys, zs), label='Linear Axis')\n",
+    "log_qmesh = qmesh.relabel('Log x-axis')\n",
+    "qmesh + log_qmesh.opts(logx=True)"
    ]
   },
   {
diff --git a/examples/reference/elements/matplotlib/RGB.ipynb b/examples/reference/elements/matplotlib/RGB.ipynb
index e3c42bf6eb..08f5e7dda1 100644
--- a/examples/reference/elements/matplotlib/RGB.ipynb
+++ b/examples/reference/elements/matplotlib/RGB.ipynb
@@ -21,6 +21,8 @@
    "source": [
     "import numpy as np\n",
     "import holoviews as hv\n",
+    "from holoviews import opts\n",
+    "\n",
     "hv.extension('matplotlib')"
    ]
   },
@@ -92,7 +94,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts Image (cmap='gray')\n",
+    "opts.defaults(opts.Image(cmap='gray'))\n",
+    "\n",
     "hv.Image(r,label=\"R\") + hv.Image(g,label=\"G\") + hv.Image(b,label=\"B\")"
    ]
   },
@@ -109,7 +112,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts Image (cmap='gray')\n",
     "mask = 0.5*np.sin(0.2*(x**2+y**2))+0.5\n",
     "rgba = hv.RGB(np.dstack([r,g,b,mask]))\n",
     "\n",
diff --git a/examples/reference/elements/matplotlib/RadialHeatMap.ipynb b/examples/reference/elements/matplotlib/RadialHeatMap.ipynb
index 9920055fc2..53a5a4624b 100644
--- a/examples/reference/elements/matplotlib/RadialHeatMap.ipynb
+++ b/examples/reference/elements/matplotlib/RadialHeatMap.ipynb
@@ -22,10 +22,12 @@
     "import numpy as np\n",
     "import pandas as pd\n",
     "import holoviews as hv\n",
+    "from holoviews import opts\n",
+    "\n",
     "hv.extension('matplotlib')\n",
     "\n",
-    "%output fig='svg'\n",
-    "%opts HeatMap [fig_size=250]"
+    "hv.output(fig='svg')\n",
+    "opts.defaults(opts.HeatMap(fig_size=250))"
    ]
   },
   {
@@ -76,8 +78,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts HeatMap [radial=True]\n",
-    "hv.HeatMap(df, [\"hour\", \"day\"])"
+    "hv.HeatMap(df, [\"hour\", \"day\"]).opts(radial=True)"
    ]
   },
   {
@@ -98,8 +99,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts HeatMap [radial=True radius_inner=0.2 xmarks=8 xticks=8 ymarks=4] (cmap='viridis')\n",
-    "hv.HeatMap(df, [\"hour\", \"day\"])"
+    "hv.HeatMap(df, [\"hour\", \"day\"]).opts(\n",
+    "    opts.HeatMap(cmap='viridis', radial=True, radius_inner=0.2, xmarks=8, xticks=8, ymarks=4))"
    ]
   }
  ],
diff --git a/examples/reference/elements/matplotlib/Sankey.ipynb b/examples/reference/elements/matplotlib/Sankey.ipynb
index f2b05e9f89..8ab08248f3 100644
--- a/examples/reference/elements/matplotlib/Sankey.ipynb
+++ b/examples/reference/elements/matplotlib/Sankey.ipynb
@@ -18,10 +18,10 @@
    "outputs": [],
    "source": [
     "import holoviews as hv\n",
-    "from holoviews import dim\n",
-    "hv.extension('matplotlib')\n",
+    "from holoviews import dim, opts\n",
     "\n",
-    "%output fig='svg'"
+    "hv.extension('matplotlib')\n",
+    "hv.output(fig='svg')"
    ]
   },
   {
@@ -46,7 +46,7 @@
     "    ('B', 'X', 2),\n",
     "    ('B', 'Y', 9),\n",
     "    ('B', 'Z', 4)]\n",
-    ").options(fig_size=200)"
+    ").opts(fig_size=200)"
    ]
   },
   {
@@ -72,10 +72,9 @@
     "]\n",
     "\n",
     "value_dim = hv.Dimension('Percentage', unit='%')\n",
-    "hv.Sankey((edges, nodes), ['From', 'To'], vdims=value_dim).options(\n",
-    "    labels='label', label_position='right', fig_size=300, edge_color=dim('To').str(),\n",
-    "    node_color=dim('index').str(), cmap='Set1'\n",
-    ")"
+    "hv.Sankey((edges, nodes), ['From', 'To'], vdims=value_dim).opts(\n",
+    "    opts.Sankey(cmap='Set1', labels='label', label_position='right', fig_size=300,\n",
+    "                edge_color=dim('To').str(), node_color=dim('index').str()))"
    ]
   }
  ],
diff --git a/examples/reference/elements/matplotlib/Spikes.ipynb b/examples/reference/elements/matplotlib/Spikes.ipynb
index 28f48c7497..103a9a26f6 100644
--- a/examples/reference/elements/matplotlib/Spikes.ipynb
+++ b/examples/reference/elements/matplotlib/Spikes.ipynb
@@ -21,6 +21,8 @@
    "source": [
     "import numpy as np\n",
     "import holoviews as hv\n",
+    "from holoviews import opts\n",
+    "\n",
     "hv.extension('matplotlib')"
    ]
   },
@@ -39,9 +41,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts Spikes (alpha=0.4) [spike_length=0.1]\n",
     "xs = np.random.rand(50)\n",
-    "hv.Spikes(xs)"
+    "hv.Spikes(xs).opts(alpha=0.4, spike_length=0.1)"
    ]
   },
   {
@@ -57,9 +58,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts Points (color='red')\n",
     "ys = np.random.rand(50)\n",
-    "hv.Points((xs, ys)) * hv.Spikes(xs)"
+    "points = hv.Points((xs, ys))\n",
+    "spikes = hv.Spikes(xs)\n",
+    "points.opts(color='red') * spikes"
    ]
   },
   {
@@ -75,8 +77,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts Spikes (color='Intensity' cmap='Reds')\n",
-    "hv.Spikes(np.random.rand(20, 2), 'Mass', 'Intensity')"
+    "hv.Spikes(np.random.rand(20, 2), 'Mass', 'Intensity').opts(cmap='Reds', color='Intensity')"
    ]
   },
   {
@@ -92,9 +93,12 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts Spikes [spike_length=0.1] NdOverlay [show_legend=False]\n",
-    "hv.NdOverlay({i: hv.Spikes(np.random.randint(0, 100, 10), 'Time').options(position=0.1*i)\n",
-    "              for i in range(10)}).options(yticks=[((i+1)*0.1-0.05, i) for i in range(10)])"
+    "overlay = hv.NdOverlay({i: hv.Spikes(np.random.randint(0, 100, 10), 'Time').options(\n",
+    "    position=0.1*i, spike_length=0.1) for i in range(10)})\n",
+    "\n",
+    "ticks = [((i+1)*0.1-0.05, i) for i in range(10)]\n",
+    "\n",
+    "overlay.opts(show_legend=False, yticks=ticks)"
    ]
   },
   {
@@ -110,9 +114,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts Spikes (alpha=0.2)\n",
     "points = hv.Points(np.random.randn(500, 2))\n",
-    "points << hv.Spikes(points['y']) << hv.Spikes(points['x'])"
+    "(points << hv.Spikes(points['y']) << hv.Spikes(points['x'])).opts(\n",
+    "    opts.Spikes(alpha=0.2))"
    ]
   },
   {
diff --git a/examples/reference/elements/matplotlib/Spline.ipynb b/examples/reference/elements/matplotlib/Spline.ipynb
index dab3cf1b6d..14e5d003da 100644
--- a/examples/reference/elements/matplotlib/Spline.ipynb
+++ b/examples/reference/elements/matplotlib/Spline.ipynb
@@ -20,6 +20,8 @@
    "outputs": [],
    "source": [
     "import holoviews as hv\n",
+    "from holoviews import opts\n",
+    "\n",
     "hv.extension('matplotlib')"
    ]
   },
@@ -36,9 +38,12 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts Curve (color='#D3D3D3') Spline (linewidth=6 edgecolor='green')\n",
     "points = [(-0.3, -0.3), (0,0), (0.25, -0.25), (0.3, 0.3)]\n",
-    "hv.Spline((points, [1,4,4,4])) * hv.Curve(points)"
+    "spline = hv.Spline((points, [1,4,4,4]))\n",
+    "\n",
+    "(spline * hv.Curve(points)).opts(\n",
+    "    opts.Curve(color='#D3D3D3')\n",
+    "    opts.Spline(linewidth=6, edgecolor='green'))"
    ]
   },
   {
diff --git a/examples/reference/elements/matplotlib/Spread.ipynb b/examples/reference/elements/matplotlib/Spread.ipynb
index 6da7cc0bf4..13ceb18572 100644
--- a/examples/reference/elements/matplotlib/Spread.ipynb
+++ b/examples/reference/elements/matplotlib/Spread.ipynb
@@ -74,10 +74,11 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts Spread (facecolor='indianred' alpha=1)\n",
     "xs = np.linspace(0, np.pi*2, 20)\n",
-    "hv.Spread((xs, np.sin(xs), 0.1+np.random.rand(len(xs)), 0.1+np.random.rand(len(xs))),\n",
-    "          vdims=['y', 'yerrneg', 'yerrpos'])"
+    "spread = hv.Spread((xs, np.sin(xs), 0.1+np.random.rand(len(xs)), 0.1+np.random.rand(len(xs))),\n",
+    "                   vdims=['y', 'yerrneg', 'yerrpos'])\n",
+    "\n",
+    "spread.opts(alpha=1, facecolor='indianred')"
    ]
   },
   {
diff --git a/examples/reference/elements/matplotlib/Surface.ipynb b/examples/reference/elements/matplotlib/Surface.ipynb
index cd7de562c1..c797510f55 100644
--- a/examples/reference/elements/matplotlib/Surface.ipynb
+++ b/examples/reference/elements/matplotlib/Surface.ipynb
@@ -22,6 +22,8 @@
    "source": [
     "import numpy as np\n",
     "import holoviews as hv\n",
+    "from holoviews import opts\n",
+    "\n",
     "hv.extension('matplotlib')"
    ]
   },
@@ -40,8 +42,9 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts Surface [azimuth=30 elevation=30] (cmap='plasma' rstride=20, cstride=2)\n",
-    "hv.Surface(np.sin(np.linspace(0,100*np.pi*2,10000)).reshape(100,100))"
+    "surface = hv.Surface(np.sin(np.linspace(0,100*np.pi*2,10000)).reshape(100,100))\n",
+    "\n",
+    "surface.opts(opts.Surface(azimuth=30, elevation=30, rstride=20, cstride=2, cmap='plasma'))"
    ]
   },
   {
@@ -57,14 +60,19 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts Surface [azimuth=60] (cmap='fire' linewidth=1 edgecolor='black') Layout [fig_size=150 hspace=0.1]\n",
     "xs = np.arange(-4, 4, 0.25)\n",
     "ys = np.arange(-4, 4, 0.25)\n",
     "X, Y = np.meshgrid(xs, ys)\n",
     "R = np.sqrt(X**2 + Y**2)\n",
     "Z = np.sin(R)\n",
-    "surface = hv.Surface((xs, ys, Z))\n",
-    "surface + surface.options(plot_type='wireframe') + surface.options(plot_type='contour')"
+    "\n",
+    "surface = hv.Surface((xs, ys, Z), label='Surface')\n",
+    "wireframe = surface.relabel('Wireframe').opts(plot_type='wireframe')\n",
+    "contour = surface.relabel('Contour').opts(plot_type='contour')\n",
+    "\n",
+    "(surface + wireframe + contour).opts(\n",
+    "    opts.Layout(fig_size=150, hspace=0.1),\n",
+    "    opts.Surface(azimuth=60, cmap='fire'))"
    ]
   },
   {
diff --git a/examples/reference/elements/matplotlib/Text.ipynb b/examples/reference/elements/matplotlib/Text.ipynb
index d90fbf4116..1fcd6dcd25 100644
--- a/examples/reference/elements/matplotlib/Text.ipynb
+++ b/examples/reference/elements/matplotlib/Text.ipynb
@@ -37,9 +37,11 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts Curve (color='#D3D3D3')\n",
     "xs = np.linspace(-5,5,100)\n",
-    "hv.Curve((xs,-(xs-2)**2))  * hv.Text(0, -30, 'Quadratic Curve')"
+    "curve = hv.Curve((xs,-(xs-2)**2))\n",
+    "text = hv.Text(0, -30, 'Quadratic Curve')\n",
+    "\n",
+    "curve.opts(color='#D3D3D3') * text"
    ]
   },
   {
diff --git a/examples/reference/elements/matplotlib/TriMesh.ipynb b/examples/reference/elements/matplotlib/TriMesh.ipynb
index 6eac8ff003..8435cd6a8f 100644
--- a/examples/reference/elements/matplotlib/TriMesh.ipynb
+++ b/examples/reference/elements/matplotlib/TriMesh.ipynb
@@ -21,6 +21,8 @@
    "source": [
     "import numpy as np\n",
     "import holoviews as hv\n",
+    "\n",
+    "from holoviews import opts\n",
     "from scipy.spatial import Delaunay\n",
     "\n",
     "hv.extension('matplotlib')"
@@ -150,8 +152,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts TriMesh [filled=True fig_size=200] (cmap='viridis' edge_color='z')\n",
-    "hv.TriMesh((simplices, hv.Points(nodes, vdims='z')))"
+    "hv.TriMesh((simplices, hv.Points(nodes, vdims='z'))).opts(\n",
+    "    opts.TriMesh(cmap='viridis', edge_color='z', filled=True, fig_size=200))"
    ]
   },
   {
diff --git a/examples/reference/elements/matplotlib/TriSurface.ipynb b/examples/reference/elements/matplotlib/TriSurface.ipynb
index 67f775b6c1..e68561732a 100644
--- a/examples/reference/elements/matplotlib/TriSurface.ipynb
+++ b/examples/reference/elements/matplotlib/TriSurface.ipynb
@@ -38,10 +38,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts TriSurface [azimuth=30 elevation=30 fig_size=200]\n",
     "y,x = np.mgrid[-5:5, -5:5] * 0.1\n",
     "heights = np.sin(x**2+y**2)\n",
-    "hv.TriSurface((x.flat,y.flat,heights.flat))"
+    "hv.TriSurface((x.flat,y.flat,heights.flat)).opts(\n",
+    "    azimuth=30, elevation=30, fig_size=200)"
    ]
   },
   {
@@ -57,8 +57,6 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts TriSurface [fig_size=200 colorbar=True] (cmap='fire')\n",
-    "\n",
     "u=np.linspace(0,2*np.pi, 24)\n",
     "v=np.linspace(-1,1, 8)\n",
     "u,v=np.meshgrid(u,v)\n",
@@ -72,7 +70,7 @@
     "z=0.5*v*np.sin(u/2.)\n",
     "\n",
     "surface = hv.TriSurface((x, y, z), label='Moebius band')\n",
-    "surface"
+    "surface.opts(cmap='fire', colorbar=True, fig_size=200)"
    ]
   },
   {
diff --git a/examples/reference/elements/matplotlib/VLine.ipynb b/examples/reference/elements/matplotlib/VLine.ipynb
index 9b37c9984b..a464e1e07c 100644
--- a/examples/reference/elements/matplotlib/VLine.ipynb
+++ b/examples/reference/elements/matplotlib/VLine.ipynb
@@ -21,6 +21,8 @@
    "source": [
     "import numpy as np\n",
     "import holoviews as hv\n",
+    "from holoviews import opts\n",
+    "\n",
     "hv.extension('matplotlib')"
    ]
   },
@@ -37,10 +39,13 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts VLine (color='red' linewidth=6) Curve (color='#D3D3D3')\n",
     "xs = np.linspace(-5,5,100)\n",
     "ys = -(xs-2)**2\n",
-    "hv.Curve((xs,ys)) * hv.VLine(xs[ys.argmax()])"
+    "vline = hv.VLine(xs[ys.argmax()])\n",
+    "\n",
+    "(hv.Curve((xs,ys)) * vline).opts(\n",
+    "    opts.Curve(color='#D3D3D3'),\n",
+    "    opts.Vline(color='red', linewidth=6)"
    ]
   },
   {
diff --git a/examples/reference/elements/matplotlib/VectorField.ipynb b/examples/reference/elements/matplotlib/VectorField.ipynb
index 44fe4d0863..8d2204aeeb 100644
--- a/examples/reference/elements/matplotlib/VectorField.ipynb
+++ b/examples/reference/elements/matplotlib/VectorField.ipynb
@@ -21,6 +21,8 @@
    "source": [
     "import numpy as np\n",
     "import holoviews as hv\n",
+    "from holoviews import dim, opts\n",
+    "\n",
     "hv.extension('matplotlib')"
    ]
   },
@@ -37,13 +39,12 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts VectorField [magnitude='Magnitude']\n",
     "x,y  = np.mgrid[-10:10,-10:10] * 0.25\n",
     "sine_rings  = np.sin(x**2+y**2)*np.pi+np.pi\n",
     "exp_falloff = 1/np.exp((x**2+y**2)/8)\n",
     "\n",
     "vector_data = (x, y, sine_rings, exp_falloff)\n",
-    "hv.VectorField(vector_data)"
+    "hv.VectorField(vector_data).opts(magnitude='Magnitude')"
    ]
   },
   {
@@ -78,9 +79,10 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts VectorField [magnitude=dim('Magnitude').norm()*0.2 rescale_lengths=False] (color='Angle')\n",
-    "hv.HoloMap({phase: hv.VectorField([x, y,(vector_data[2]+phase)%np.pi*2, vector_data[3]+np.abs(phase)])\n",
-    "            for phase in np.linspace(-np.pi,np.pi,5)}, kdims='Phase')"
+    "hmap = hv.HoloMap({phase: hv.VectorField((x, y,(vector_data[2]+phase)%np.pi*2, vector_data[3]+np.abs(phase)))\n",
+    "                   for phase in np.linspace(-np.pi,np.pi,5)}, kdims='Phase')\n",
+    "\n",
+    "hmap.opts(opts.VectorField(color='Angle', magnitude=dim('Magnitude').norm()*0.2, rescale_lengths=False))"
    ]
   },
   {
@@ -119,8 +121,12 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts VectorField [magnitude='Magnitude' aspect=2 fig_size=300] (pivot='tip' cmap='fire' scale=0.8 color='Magnitude') Points (color='black' s=1)\n",
-    "hv.VectorField((xs, ys, angle, mag)) * hv.Points((X.flat, Y.flat))"
+    "vectors = hv.VectorField((xs, ys, angle, mag))\n",
+    "points = hv.Points((X.flat, Y.flat))\n",
+    "\n",
+    "(vectors * points).opts(\n",
+    "    opts.Points(color='black', s=1),\n",
+    "    opts.VectorField(aspect=2, color='Magnitude', cmap='fire', fig_size=300, magnitude='Magnitude', pivot='tip', scale=0.8))"
    ]
   },
   {
diff --git a/examples/reference/elements/matplotlib/Violin.ipynb b/examples/reference/elements/matplotlib/Violin.ipynb
index 0558243f11..9450e4b84c 100644
--- a/examples/reference/elements/matplotlib/Violin.ipynb
+++ b/examples/reference/elements/matplotlib/Violin.ipynb
@@ -59,7 +59,7 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "violin.relabel(group='Medians').options(inner='medians', cut=0.1, bandwidth=0.1)"
+    "violin.relabel(group='Medians').opts(inner='medians', bandwidth=0.1)"
    ]
   },
   {
@@ -75,10 +75,11 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "%%opts Violin [fig_size=300 aspect=2.5 show_legend=False]\n",
     "groups = [chr(65+g) for g in np.random.randint(0, 3, 200)]\n",
-    "hv.Violin((groups, np.random.randint(0, 5, 200), np.random.randn(200)),\n",
-    "          ['Group', 'Category'], 'Value')"
+    "violin = hv.Violin((groups, np.random.randint(0, 5, 200), np.random.randn(200)),\n",
+    "                   ['Group', 'Category'], 'Value')\n",
+    "\n",
+    "violin.opts(aspect=2.5, fig_size=300)"
    ]
   },
   {
diff --git a/holoviews/plotting/mpl/annotation.py b/holoviews/plotting/mpl/annotation.py
index a1e2bbbaa2..6fe08be6fd 100644
--- a/holoviews/plotting/mpl/annotation.py
+++ b/holoviews/plotting/mpl/annotation.py
@@ -121,10 +121,14 @@ def get_data(self, element, ranges, style):
         if self.yoffset is not None:
             ys += self.yoffset
 
+        cs = None
         cdim = element.get_dimension(self.color_index)
         if cdim:
             self._norm_kwargs(element, ranges, style, cdim)
-        cs = element.dimension_values(cdim) if cdim else None
+            cs = element.dimension_values(cdim)
+        if 'c' in style:
+            cs = style.pop('c')
+
         if 'size' in style: style['fontsize'] = style.pop('size')
         if 'horizontalalignment' not in style: style['horizontalalignment'] = 'center'
         if 'verticalalignment' not in style: style['verticalalignment'] = 'center'
diff --git a/holoviews/tests/plotting/matplotlib/testlabels.py b/holoviews/tests/plotting/matplotlib/testlabels.py
index 5da51f7915..8776c4ca5f 100644
--- a/holoviews/tests/plotting/matplotlib/testlabels.py
+++ b/holoviews/tests/plotting/matplotlib/testlabels.py
@@ -3,6 +3,7 @@
 from holoviews.core.dimension import Dimension
 from holoviews.core.spaces import HoloMap
 from holoviews.element import Labels
+from holoviews.plotting.util import rgb2hex
 
 from .testplot import TestMPLPlot, mpl_renderer
 
@@ -92,14 +93,18 @@ def test_label_color_op_update(self):
     def test_label_linear_color_op(self):
         labels = Labels([(0, 0, 0), (0, 1, 1), (0, 2, 2)],
                         vdims='color').options(color='color')
-        with self.assertRaises(Exception):
-            mpl_renderer.get_plot(labels)
+        plot = mpl_renderer.get_plot(labels)
+        artist = plot.handles['artist']
+        self.assertEqual([rgb2hex(a.get_color()) for a in artist],
+                         ['#440154', '#20908c', '#fde724'])
 
     def test_label_categorical_color_op(self):
         labels = Labels([(0, 0, 'A'), (0, 1, 'B'), (0, 2, 'A')],
-                        vdims='color').options(color='color')
-        with self.assertRaises(Exception):
-            mpl_renderer.get_plot(labels)
+                        vdims='color').options(color='color', cmap='tab10')
+        plot = mpl_renderer.get_plot(labels)
+        artist = plot.handles['artist']
+        self.assertEqual([rgb2hex(a.get_color()) for a in artist],
+                         ['#1f77b4', '#ff7f0e', '#1f77b4'])
 
     def test_label_size_op(self):
         labels = Labels([(0, 0, 8), (0, 1, 12), (0, 2, 6)],