diff --git a/examples/contours.ipynb b/examples/contours.ipynb
index 10410f26..5952e2aa 100644
--- a/examples/contours.ipynb
+++ b/examples/contours.ipynb
@@ -3242,29 +3242,16 @@
     "collapsed": false
    },
    "outputs": [],
-   "source": [
-    "using Gadfly"
-   ]
+   "source": []
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": null,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [
-    {
-     "name": "stderr",
-     "output_type": "stream",
-     "text": [
-      "INFO: No packages to install, update or remove\n",
-      "INFO: Package database updated\n"
-     ]
-    }
-   ],
-   "source": [
-    "Pkg.add(\"Contour\")"
-   ]
+   "outputs": [],
+   "source": []
   },
   {
    "cell_type": "code",
@@ -3382,18 +3369,46 @@
    ],
    "source": [
     "Pkg.add(\"GeometricalPredicates\")\n",
-    "Pkg.clone(\"https://github.com/JuliaGeometry/VoronoiDelaunay.jl\")"
+    "Pkg.clone(\"https://github.com/JuliaGeometry/VoronoiDelaunay.jl\")\n",
+    "Pkg.add(\"Contour\")"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 3,
    "metadata": {
     "collapsed": false
    },
-   "outputs": [],
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "[Plots.jl] Switched to backend: gadfly"
+     ]
+    },
+    {
+     "data": {
+      "image/png": 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",
+      "text/plain": [
+       "Plot{Plots.GadflyPackage() n=1}"
+      ]
+     },
+     "execution_count": 3,
+     "metadata": {},
+     "output_type": "execute_result"
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "[Plots.jl] Initializing backend: gadfly\n"
+     ]
+    }
+   ],
    "source": [
-    "using Plots\n",
+    "using Plots; gadfly()\n",
     "default(size=(500,300))\n",
     "n = 100\n",
     "x = randn(n)*3\n",
@@ -3404,7 +3419,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 13,
+   "execution_count": 4,
    "metadata": {
     "collapsed": false
    },
@@ -3415,14 +3430,14 @@
        "zippoints (generic function with 2 methods)"
       ]
      },
-     "execution_count": 13,
+     "execution_count": 4,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "using VoronoiDelaunay\n",
-    "tess = DelaunayTessellation()\n",
+    "tess = DelaunayTessellation(n)\n",
     "tmin, tmax = min_coord, max_coord\n",
     "twidth = tmax - tmin\n",
     "function squash(a)\n",
@@ -3434,16 +3449,18 @@
     "    v\n",
     "end\n",
     "function zippoints(x, y)\n",
+    "    x, y = squash(x), squash(y)\n",
     "    Point2D[Point(x[i], y[i]) for i in eachindex(x)]\n",
     "end\n",
     "function zippoints(x, y, z)\n",
+    "    x, y, z = squash(x), squash(y), squash(z)\n",
     "    Point3D[Point(x[i], y[i], z[i]) for i in eachindex(x)]\n",
     "end"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 5,
    "metadata": {
     "collapsed": false
    },
@@ -3455,7 +3472,122 @@
       "WARNING: Base.Uint64 is deprecated, use UInt64 instead.\n",
       "WARNING: Base.Uint64 is deprecated, use UInt64 instead.\n",
       "WARNING: Base.Uint64 is deprecated, use UInt64 instead.\n",
-      "WARNING: int(x::AbstractFloat) is deprecated, use round(Int,x) instead.\n"
+      "WARNING: int(x::AbstractFloat) is deprecated, use round(Int,x) instead.\n",
+      " in depwarn at deprecated.jl:73\n",
+      " in int at deprecated.jl:50\n",
+      " in _mssort! at /Users/tom/.julia/v0.4/GeometricalPredicates/src/GeometricalPredicates.jl:1133\n",
+      " in push! at /Users/tom/.julia/v0.4/VoronoiDelaunay/src/VoronoiDelaunay.jl:634\n",
+      " in include_string at loading.jl:266\n",
+      " in execute_request_0x535c5df2 at /Users/tom/.julia/v0.4/IJulia/src/execute_request.jl:177\n",
+      " in eventloop at /Users/tom/.julia/v0.4/IJulia/src/IJulia.jl:141\n",
+      " in anonymous at task.jl:447\n",
+      "while loading In[5], in expression starting on line 2\n",
+      "WARNING: int(x::AbstractFloat) is deprecated, use round(Int,x) instead.\n",
+      " in depwarn at deprecated.jl:73\n",
+      " in int at deprecated.jl:50\n",
+      " in _mssort! at /Users/tom/.julia/v0.4/GeometricalPredicates/src/GeometricalPredicates.jl:1133\n",
+      " in push! at /Users/tom/.julia/v0.4/VoronoiDelaunay/src/VoronoiDelaunay.jl:634\n",
+      " in include_string at loading.jl:266\n",
+      " in execute_request_0x535c5df2 at /Users/tom/.julia/v0.4/IJulia/src/execute_request.jl:177\n",
+      " in eventloop at /Users/tom/.julia/v0.4/IJulia/src/IJulia.jl:141\n",
+      " in anonymous at task.jl:447\n",
+      "while loading In[5], in expression starting on line 2\n",
+      "WARNING: int64(x) is deprecated, use Int64(x) instead.\n",
+      " in depwarn at deprecated.jl:73\n",
+      " in int64 at deprecated.jl:50\n",
+      " in _exact_intriangle! at /Users/tom/.julia/v0.4/GeometricalPredicates/src/GeometricalPredicates.jl:576\n",
+      " in _exact_intriangle at /Users/tom/.julia/v0.4/GeometricalPredicates/src/GeometricalPredicates.jl:648\n",
+      " in _sz_intriangle at /Users/tom/.julia/v0.4/GeometricalPredicates/src/GeometricalPredicates.jl:672\n",
+      " in intriangle at /Users/tom/.julia/v0.4/GeometricalPredicates/src/GeometricalPredicates.jl:701\n",
+      " in findindex at /Users/tom/.julia/v0.4/VoronoiDelaunay/src/VoronoiDelaunay.jl:268\n",
+      " in _pushunfixed! at /Users/tom/.julia/v0.4/VoronoiDelaunay/src/VoronoiDelaunay.jl:282\n",
+      " in _pushunsorted! at /Users/tom/.julia/v0.4/VoronoiDelaunay/src/VoronoiDelaunay.jl:627\n",
+      " in push! at /Users/tom/.julia/v0.4/VoronoiDelaunay/src/VoronoiDelaunay.jl:635\n",
+      " in include_string at loading.jl:266\n",
+      " in execute_request_0x535c5df2 at /Users/tom/.julia/v0.4/IJulia/src/execute_request.jl:177\n",
+      " in eventloop at /Users/tom/.julia/v0.4/IJulia/src/IJulia.jl:141\n",
+      " in anonymous at task.jl:447\n",
+      "while loading In[5], in expression starting on line 2\n",
+      "WARNING: int64(x) is deprecated, use Int64(x) instead.\n",
+      " in depwarn at deprecated.jl:73\n",
+      " in int64 at deprecated.jl:50\n",
+      " in _exact_intriangle! at /Users/tom/.julia/v0.4/GeometricalPredicates/src/GeometricalPredicates.jl:577\n",
+      " in _exact_intriangle at /Users/tom/.julia/v0.4/GeometricalPredicates/src/GeometricalPredicates.jl:648\n",
+      " in _sz_intriangle at /Users/tom/.julia/v0.4/GeometricalPredicates/src/GeometricalPredicates.jl:672\n",
+      " in intriangle at /Users/tom/.julia/v0.4/GeometricalPredicates/src/GeometricalPredicates.jl:701\n",
+      " in findindex at /Users/tom/.julia/v0.4/VoronoiDelaunay/src/VoronoiDelaunay.jl:268\n",
+      " in _pushunfixed! at /Users/tom/.julia/v0.4/VoronoiDelaunay/src/VoronoiDelaunay.jl:282\n",
+      " in _pushunsorted! at /Users/tom/.julia/v0.4/VoronoiDelaunay/src/VoronoiDelaunay.jl:627\n",
+      " in push! at /Users/tom/.julia/v0.4/VoronoiDelaunay/src/VoronoiDelaunay.jl:635\n",
+      " in include_string at loading.jl:266\n",
+      " in execute_request_0x535c5df2 at /Users/tom/.julia/v0.4/IJulia/src/execute_request.jl:177\n",
+      " in eventloop at /Users/tom/.julia/v0.4/IJulia/src/IJulia.jl:141\n",
+      " in anonymous at task.jl:447\n",
+      "while loading In[5], in expression starting on line 2\n",
+      "WARNING: int64(x) is deprecated, use Int64(x) instead.\n",
+      " in depwarn at deprecated.jl:73\n",
+      " in int64 at deprecated.jl:50\n",
+      " in _exact_intriangle! at /Users/tom/.julia/v0.4/GeometricalPredicates/src/GeometricalPredicates.jl:580\n",
+      " in _exact_intriangle at /Users/tom/.julia/v0.4/GeometricalPredicates/src/GeometricalPredicates.jl:648\n",
+      " in _sz_intriangle at /Users/tom/.julia/v0.4/GeometricalPredicates/src/GeometricalPredicates.jl:672\n",
+      " in intriangle at /Users/tom/.julia/v0.4/GeometricalPredicates/src/GeometricalPredicates.jl:701\n",
+      " in findindex at /Users/tom/.julia/v0.4/VoronoiDelaunay/src/VoronoiDelaunay.jl:268\n",
+      " in _pushunfixed! at /Users/tom/.julia/v0.4/VoronoiDelaunay/src/VoronoiDelaunay.jl:282\n",
+      " in _pushunsorted! at /Users/tom/.julia/v0.4/VoronoiDelaunay/src/VoronoiDelaunay.jl:627\n",
+      " in push! at /Users/tom/.julia/v0.4/VoronoiDelaunay/src/VoronoiDelaunay.jl:635\n",
+      " in include_string at loading.jl:266\n",
+      " in execute_request_0x535c5df2 at /Users/tom/.julia/v0.4/IJulia/src/execute_request.jl:177\n",
+      " in eventloop at /Users/tom/.julia/v0.4/IJulia/src/IJulia.jl:141\n",
+      " in anonymous at task.jl:447\n",
+      "while loading In[5], in expression starting on line 2\n",
+      "WARNING: int64(x) is deprecated, use Int64(x) instead.\n",
+      " in depwarn at deprecated.jl:73\n",
+      " in int64 at deprecated.jl:50\n",
+      " in _exact_intriangle! at /Users/tom/.julia/v0.4/GeometricalPredicates/src/GeometricalPredicates.jl:584\n",
+      " in _exact_intriangle at /Users/tom/.julia/v0.4/GeometricalPredicates/src/GeometricalPredicates.jl:648\n",
+      " in _sz_intriangle at /Users/tom/.julia/v0.4/GeometricalPredicates/src/GeometricalPredicates.jl:672\n",
+      " in intriangle at /Users/tom/.julia/v0.4/GeometricalPredicates/src/GeometricalPredicates.jl:701\n",
+      " in findindex at /Users/tom/.julia/v0.4/VoronoiDelaunay/src/VoronoiDelaunay.jl:268\n",
+      " in _pushunfixed! at /Users/tom/.julia/v0.4/VoronoiDelaunay/src/VoronoiDelaunay.jl:282\n",
+      " in _pushunsorted! at /Users/tom/.julia/v0.4/VoronoiDelaunay/src/VoronoiDelaunay.jl:627\n",
+      " in push! at /Users/tom/.julia/v0.4/VoronoiDelaunay/src/VoronoiDelaunay.jl:635\n",
+      " in include_string at loading.jl:266\n",
+      " in execute_request_0x535c5df2 at /Users/tom/.julia/v0.4/IJulia/src/execute_request.jl:177\n",
+      " in eventloop at /Users/tom/.julia/v0.4/IJulia/src/IJulia.jl:141\n",
+      " in anonymous at task.jl:447\n",
+      "while loading In[5], in expression starting on line 2\n",
+      "WARNING: int64(x) is deprecated, use Int64(x) instead.\n",
+      " in depwarn at deprecated.jl:73\n",
+      " in int64 at deprecated.jl:50\n",
+      " in _exact_intriangle! at /Users/tom/.julia/v0.4/GeometricalPredicates/src/GeometricalPredicates.jl:589\n",
+      " in _exact_intriangle at /Users/tom/.julia/v0.4/GeometricalPredicates/src/GeometricalPredicates.jl:648\n",
+      " in _sz_intriangle at /Users/tom/.julia/v0.4/GeometricalPredicates/src/GeometricalPredicates.jl:672\n",
+      " in intriangle at /Users/tom/.julia/v0.4/GeometricalPredicates/src/GeometricalPredicates.jl:701\n",
+      " in findindex at /Users/tom/.julia/v0.4/VoronoiDelaunay/src/VoronoiDelaunay.jl:268\n",
+      " in _pushunfixed! at /Users/tom/.julia/v0.4/VoronoiDelaunay/src/VoronoiDelaunay.jl:282\n",
+      " in _pushunsorted! at /Users/tom/.julia/v0.4/VoronoiDelaunay/src/VoronoiDelaunay.jl:627\n",
+      " in push! at /Users/tom/.julia/v0.4/VoronoiDelaunay/src/VoronoiDelaunay.jl:635\n",
+      " in include_string at loading.jl:266\n",
+      " in execute_request_0x535c5df2 at /Users/tom/.julia/v0.4/IJulia/src/execute_request.jl:177\n",
+      " in eventloop at /Users/tom/.julia/v0.4/IJulia/src/IJulia.jl:141\n",
+      " in anonymous at task.jl:447\n",
+      "while loading In[5], in expression starting on line 2\n",
+      "WARNING: int64(x) is deprecated, use Int64(x) instead.\n",
+      " in depwarn at deprecated.jl:73\n",
+      " in int64 at deprecated.jl:50\n",
+      " in _exact_intriangle! at /Users/tom/.julia/v0.4/GeometricalPredicates/src/GeometricalPredicates.jl:592\n",
+      " in _exact_intriangle at /Users/tom/.julia/v0.4/GeometricalPredicates/src/GeometricalPredicates.jl:648\n",
+      " in _sz_intriangle at /Users/tom/.julia/v0.4/GeometricalPredicates/src/GeometricalPredicates.jl:672\n",
+      " in intriangle at /Users/tom/.julia/v0.4/GeometricalPredicates/src/GeometricalPredicates.jl:701\n",
+      " in findindex at /Users/tom/.julia/v0.4/VoronoiDelaunay/src/VoronoiDelaunay.jl:268\n",
+      " in _pushunfixed! at /Users/tom/.julia/v0.4/VoronoiDelaunay/src/VoronoiDelaunay.jl:282\n",
+      " in _pushunsorted! at /Users/tom/.julia/v0.4/VoronoiDelaunay/src/VoronoiDelaunay.jl:627\n",
+      " in push! at /Users/tom/.julia/v0.4/VoronoiDelaunay/src/VoronoiDelaunay.jl:635\n",
+      " in include_string at loading.jl:266\n",
+      " in execute_request_0x535c5df2 at /Users/tom/.julia/v0.4/IJulia/src/execute_request.jl:177\n",
+      " in eventloop at /Users/tom/.julia/v0.4/IJulia/src/IJulia.jl:141\n",
+      " in anonymous at task.jl:447\n",
+      "while loading In[5], in expression starting on line 2\n"
      ]
     }
    ],
@@ -3464,6 +3596,19 @@
     "push!(tess, a)"
    ]
   },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {
+    "collapsed": false
+   },
+   "outputs": [],
+   "source": [
+    "for tri in tess\n",
+    "    println(tri)\n",
+    "end"
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": null,