@@ -175,11 +175,12 @@

    "metadata": {},

    "outputs": [],

    "source": [

-    "def func(xy):\n",

+    "def func(xy, wait=True):\n",

     "    import numpy as np\n",

     "    from time import sleep\n",

     "    from random import random\n",

-    "    sleep(random())\n",

+    "    if wait:\n",

+    "        sleep(random())\n",

     "    x, y = xy\n",

     "    a = 0.2\n",

     "    return x + np.exp(-(x**2 + y**2 - 0.75**2)**2/a**4)\n",

@@ -204,7 +205,7 @@

    "source": [

     "%%output size=100\n",

     "%%opts Contours (alpha=0.3)\n",

-    "from adaptive.learner import *\n",

+    "import holoviews as hv\n",

     "\n",

     "def plot(learner):\n",

     "    tri = learner.ip().tri\n",

@@ -230,7 +231,7 @@

     "learner2 = adaptive.learner.Learner2D(func, bounds=[(-1, 1), (-1, 1)])\n",

     "lin = np.linspace(-1, 1, len(learner.points)**0.5)\n",

     "xy = [(x, y) for x in lin for y in lin]\n",

-    "learner2.add_data(xy, map(func, xy))\n",

+    "learner2.add_data(xy, map(partial(func, wait=False), xy))\n",

     "learner2.plot().relabel('Homogeneous grid') + learner.plot().relabel('With adaptive')"

    ]

   },

@@ -275,7 +276,7 @@

    "metadata": {},

    "outputs": [],

    "source": [

-    "learner = adaptive.AverageLearner(g, None, 0.01)\n",

+    "learner = adaptive.learner.AverageLearner(g, None, 0.01)\n",

     "runner = adaptive.Runner(learner, goal=lambda l: l.loss() < 1)\n",

     "adaptive.live_plot(runner)"

    ]

@@ -342,9 +343,8 @@

    "metadata": {},

    "outputs": [],

    "source": [

-    "from cquad import Learner\n",

-    "learner = Learner(f24, bounds=(0, 3), tol=1e-3)\n",

-    "runner = adaptive.Runner(learner, goal=lambda l: l.done())"

+    "learner = adaptive.learner.IntegratorLearner(f24, bounds=(0, 3), tol=1e-10)\n",

+    "runner = adaptive.Runner(learner, executor=adaptive.runner.SequentialExecutor(), goal=lambda l: l.done())"

    ]

   },

   {