diff --git a/Learner-timing.ipynb b/Learner-timing.ipynb
deleted file mode 100644
index 85bbf2dd1f3e175e1c89dff07519d741666be534..0000000000000000000000000000000000000000
--- a/Learner-timing.ipynb
+++ /dev/null
@@ -1,80 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Timing"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import holoviews as hv\n",
-    "hv.notebook_extension()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "import learner\n",
-    "from time import time"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "times = []\n",
-    "xs = np.random.random((1000, 1000))\n",
-    "ys = np.random.random((1000, 1000))\n",
-    "for (i, (x, y)) in enumerate(zip(xs, ys)):\n",
-    "    learner = learner.Learner1D(x[:i+2], y[:i+2])\n",
-    "    start = time()\n",
-    "    learner.choose_points(n=1)\n",
-    "    stop = time()\n",
-    "    times.append(stop-start)"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "hv.Curve(times)"
-   ]
-  }
- ],
- "metadata": {
-  "anaconda-cloud": {},
-  "kernelspec": {
-   "display_name": "Python [conda env:py36]",
-   "language": "python",
-   "name": "conda-env-py36-py"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.6.0"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 1
-}
diff --git a/Learner-widgets.ipynb b/Learner-widgets.ipynb
deleted file mode 100644
index dc2e5ee18923a82e8ad84c9908669f00e78f1878..0000000000000000000000000000000000000000
--- a/Learner-widgets.ipynb
+++ /dev/null
@@ -1,132 +0,0 @@
-{
- "cells": [
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# Adaptive"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import holoviews as hv\n",
-    "hv.notebook_extension()"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "import numpy as np\n",
-    "import learner\n",
-    "import importlib\n",
-    "importlib.reload(learner)\n",
-    "\n",
-    "def func(x):\n",
-    "    \"\"\"Function with a sharp peak on a smooth background\"\"\"\n",
-    "    x = np.asarray(x)\n",
-    "    a = 0.01\n",
-    "    return x + a**2/(a**2 + x**2)\n",
-    "\n",
-    "def plot(learner, nan_is_zero=False, interpolation=False):\n",
-    "    if interpolation:\n",
-    "        learner.interpolate()\n",
-    "        d = learner.interp_data\n",
-    "    else:\n",
-    "        d = learner.data\n",
-    "\n",
-    "    xy = [(k, d[k]) for k in sorted(d)]\n",
-    "    x, y  = np.array(xy, dtype=float).T\n",
-    "\n",
-    "    if nan_is_zero:\n",
-    "        y = np.nan_to_num(y)\n",
-    "    return hv.Scatter((x, y))"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# With direct results"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "hm = {}\n",
-    "xs = np.linspace(-1, 1, 5)\n",
-    "ys = func(xs)\n",
-    "learner = learner.Learner1D(xs, ys)\n",
-    "hm[0] = plot(learner)\n",
-    "\n",
-    "for i in range(1, 30):\n",
-    "    xs = learner.choose_points(n=1, add_to_data=True)\n",
-    "    ys = func(xs)\n",
-    "    learner.add_data(xs, ys)\n",
-    "    hm[i] = plot(learner, nan_is_zero=True)\n",
-    "    \n",
-    "hv.HoloMap(hm)"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "# With `concurrent.futures`\n",
-    "\n",
-    "It's plotting the points without a result at zero"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "hm = {}\n",
-    "xs = np.linspace(-1, 1, 5)\n",
-    "ys = func(xs)\n",
-    "learner = learner.Learner1D(xs, ys)\n",
-    "hm[0] = plot(learner)\n",
-    "\n",
-    "for i in range(1, 20):\n",
-    "    xs = learner.choose_points(n=1)\n",
-    "    # Do not calculate ys here (as if it's a `concurrent.futures`)\n",
-    "    hm[i] = plot(learner, interpolation=True)\n",
-    "    \n",
-    "hv.HoloMap(hm)"
-   ]
-  }
- ],
- "metadata": {
-  "anaconda-cloud": {},
-  "kernelspec": {
-   "display_name": "Python [conda env:py36]",
-   "language": "python",
-   "name": "conda-env-py36-py"
-  },
-  "language_info": {
-   "codemirror_mode": {
-    "name": "ipython",
-    "version": 3
-   },
-   "file_extension": ".py",
-   "mimetype": "text/x-python",
-   "name": "python",
-   "nbconvert_exporter": "python",
-   "pygments_lexer": "ipython3",
-   "version": "3.6.0"
-  }
- },
- "nbformat": 4,
- "nbformat_minor": 1
-}
diff --git a/Learner-parallel-plotter.ipynb b/learner.ipynb
similarity index 95%
rename from Learner-parallel-plotter.ipynb
rename to learner.ipynb
index 10693ad4b558effc90844b4b52ff4537d45adfe9..cec531763b95fa73ba100a2deaf87e503964ff02 100644
--- a/Learner-parallel-plotter.ipynb
+++ b/learner.ipynb
@@ -10,7 +10,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "import adaptive\n",
@@ -42,6 +44,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "collapsed": true,
     "scrolled": false
    },
    "outputs": [],
@@ -54,7 +57,9 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "metadata": {},
+   "metadata": {
+    "collapsed": true
+   },
    "outputs": [],
    "source": [
     "# Same function evaluated on homogeneous grid with same amount of points\n",
@@ -105,6 +110,7 @@
    "cell_type": "code",
    "execution_count": null,
    "metadata": {
+    "collapsed": true,
     "scrolled": false
    },
    "outputs": [],