@@ -280,6 +280,100 @@

     "adaptive.live_plot(runner)"

    ]

   },

+  {

+   "cell_type": "markdown",

+   "metadata": {},

+   "source": [

+    "# 1D integration learner with `cquad`"

+   ]

+  },

+  {

+   "cell_type": "markdown",

+   "metadata": {},

+   "source": [

+    "This learner learns a 1D function and calculates the integral and error of the integral with it. It is based on Pedro Gonnet's [implementation](https://www.academia.edu/1976055/Adaptive_quadrature_re-revisited).\n",

+    "\n",

+    "Let's try the following function with cusps (that is difficult to integrate):"

+   ]

+  },

+  {

+   "cell_type": "code",

+   "execution_count": null,

+   "metadata": {},

+   "outputs": [],

+   "source": [

+    "import numpy as np\n",

+    "import holoviews as hv\n",

+    "\n",

+    "def f24(x):\n",

+    "    return np.floor(np.exp(x))\n",

+    "\n",

+    "xs = np.linspace(0, 3, 200)\n",

+    "hv.Scatter((xs, [f24(x) for x in xs]))"

+   ]

+  },

+  {

+   "cell_type": "markdown",

+   "metadata": {},

+   "source": [

+    "Just to prove that this really is a difficult to integrate function, let's try a familiar function integrator `scipy.integrate.quad`, which will give us warnings that it encounters difficulties."

+   ]

+  },

+  {

+   "cell_type": "code",

+   "execution_count": null,

+   "metadata": {},

+   "outputs": [],

+   "source": [

+    "import scipy.integrate\n",

+    "scipy.integrate.quad(f24, 0, 3)"

+   ]

+  },

+  {

+   "cell_type": "markdown",

+   "metadata": {},

+   "source": [

+    "We initialize a learner again and pass the bounds and relative tolerance we want to reach. Then in the `Runner` we pass `goal=lambda l: l.done()` where `learner.done()` is `True` when the relative tolerance has been reached."

+   ]

+  },

+  {

+   "cell_type": "code",

+   "execution_count": null,

+   "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())"

+   ]

+  },

+  {

+   "cell_type": "markdown",

+   "metadata": {},

+   "source": [

+    "Now we could do the live plotting again, but lets just wait untill the runner is done."

+   ]

+  },

+  {

+   "cell_type": "code",

+   "execution_count": null,

+   "metadata": {},

+   "outputs": [],

+   "source": [

+    "if not runner.task.done():\n",

+    "    raise RuntimeError('Wait for the runner to finish before executing the cells below!')"

+   ]

+  },

+  {

+   "cell_type": "code",

+   "execution_count": null,

+   "metadata": {},

+   "outputs": [],

+   "source": [

+    "print('The integral value is {} with the corresponding error of {}'.format(learner.igral, learner.err))\n",

+    "learner.plot()"

+   ]

+  },

   {

    "cell_type": "markdown",

    "metadata": {},