Untitled.ipynb

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   "cell_type": "code",
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   "source": [
    "# nbi:hide_in\n",
    "import numpy as np\n",
    "import nbinteract as nbi\n",
    "\n",
    "def normal(mean, sd):\n",
    "    '''Returns 1000 points drawn at random fron N(mean, sd)'''\n",
    "    return np.random.normal(mean, sd, 1000)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
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      "text/plain": [
       "VBox(children=(interactive(children=(IntSlider(value=5, description='mean', max=10), FloatSlider(value=1.0, de…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plot aesthetics\n",
    "options = {\n",
    "    'xlim': (-2, 12),\n",
    "    'ylim': (0, 0.7),\n",
    "    'bins': 20\n",
    "}\n",
    "\n",
    "# Pass in the `normal` function and let user change mean and sd.\n",
    "# Whenever the user interacts with the sliders, the `normal` function\n",
    "# is called and the returned data are plotted.\n",
    "nbi.hist(normal, mean=(0, 10), sd=(0, 2.0), options=options)\n",
    "\n",
    "# Clicking the Show widget button below loads all widgets on the page.\n",
    "# Widgets will automatically load for all subsequent pages until you close\n",
    "# the tab/window."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "rolls = np.random.choice([1, 2, 3, 4, 5, 6], size=300)\n",
    "averages = np.cumsum(rolls) / np.arange(1, 301)\n",
    "\n",
    "def x_vals(num_rolls):\n",
    "    return range(num_rolls)\n",
    "\n",
    "# The function to generate y-values gets called with the\n",
    "# x-values as its first argument.\n",
    "def y_vals(xs):\n",
    "    return averages[:len(xs)]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
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       "model_id": "89d43be7ce7643768db1b7ad4dec77da",
       "version_major": 2,
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      },
      "text/plain": [
       "VBox(children=(interactive(children=(IntSlider(value=150, description='num_rolls', max=300, min=1), Output()),…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "nbi.line(x_vals, y_vals, num_rolls=(1, 300))\n"
   ]
  }
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