Munich.ipynb

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  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Traveling salesman example: Munich\n",
    "\n",
    "In this notebook, we solve the traveling salesman problem for a round trip in Munich, with 8 locations. We solve the problem both for a car and a pedestrian, and visualize the respective results on a map."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from traveling_salesman import traveling_salesman"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Instantiate class"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "parameters = {'api_key_filename':'api_key.txt'}\n",
    "# alternatively, we can set the api key via a string as\n",
    "# parameters = {'api_key':'insert_api_key_here'}\n",
    "\n",
    "ts = traveling_salesman(parameters=parameters)"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Set and resolve location names"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Provided location names have been resolved as follows:\n",
      "1. Lindwurmstr. 167 München -> Lindwurmstraße 167, Munich, BY, Germany\n",
      "2. Museumsinsel 1, 80538 München -> Museumsinsel 1, Munich, BY, Germany\n",
      "3. Sendlinger Tor München -> Sendlinger-Tor-Platz, Munich, BY, Germany\n",
      "4. Pinakothek der Moderne, München -> Pinakothek der Moderne, Munich, BY, Germany\n",
      "5. Rotkreuzplatz München -> Rotkreuzplatz, Munich, BY, Germany\n",
      "6. Nordbad, München -> Nordbad, Munich, BY, Germany\n",
      "7. Münchner Stadtbibliothek Maxvorstadt -> Münchner Stadtbibliothek Maxvorstadt, Munich, BY, Germany\n",
      "8. Schellingstr. 4 Muenchen -> Schellingstraße 4, Munich, BY, Germany\n"
     ]
    }
   ],
   "source": [
    "# set some locations for the traveling salesman\n",
    "names = ['Lindwurmstr. 167 München',# salesman always starts at first location\n",
    "         'Museumsinsel 1, 80538 München',\n",
    "        'Sendlinger Tor München',\n",
    "        'Pinakothek der Moderne, München',\n",
    "        'Rotkreuzplatz München',\n",
    "        'Nordbad, München',\n",
    "        'Münchner Stadtbibliothek Maxvorstadt',\n",
    "        'Schellingstr. 4 Muenchen']\n",
    "\n",
    "names_resolved, locations = ts.set_locations(names)\n",
    "\n",
    "# To be sure the provided names resolved to the locations we had in mind, \n",
    "# we print the resolved location names:\n",
    "print(\"Provided location names have been resolved as follows:\")\n",
    "for i,e in enumerate(names_resolved):\n",
    "    print('{0}. {1} -> {2}'.format(i+1,names[i],e))"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Solve traveling salesman problem and plot the result"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Found shortest path:\n",
      "1. Lindwurmstraße 167, Munich, BY, Germany\n",
      "    1.74 km\n",
      "2. Sendlinger-Tor-Platz, Munich, BY, Germany\n",
      "    1.94 km\n",
      "3. Museumsinsel 1, Munich, BY, Germany\n",
      "    2.85 km\n",
      "4. Schellingstraße 4, Munich, BY, Germany\n",
      "    0.89 km\n",
      "5. Pinakothek der Moderne, Munich, BY, Germany\n",
      "    0.84 km\n",
      "6. Münchner Stadtbibliothek Maxvorstadt, Munich, BY, Germany\n",
      "    1.36 km\n",
      "7. Nordbad, Munich, BY, Germany\n",
      "    2.91 km\n",
      "8. Rotkreuzplatz, Munich, BY, Germany\n",
      "    4.93 km\n",
      "9. Lindwurmstraße 167, Munich, BY, Germany\n",
      "\n",
      "Total distance: 17.46 km\n"
     ]
    }
   ],
   "source": [
    "results = ts.solve() # takes ~30s on my MacBook Pro\n",
    "# by default, ts.solve() solves the traveling salesman problem three times\n",
    "# and takes the best path of the three solutions"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
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   "source": [
    "# plot the result\n",
    "ts.plot_shortest_path(filename='munich_car.html')\n",
    "# filename is optional. If no filename is provided, nothing will be saved"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Solve the traveling salesman problem again, now for a pedestrian"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
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      "Found shortest path:\n",
      "1. Lindwurmstraße 167, Munich, BY, Germany\n",
      "    4.16 km\n",
      "2. Rotkreuzplatz, Munich, BY, Germany\n",
      "    2.66 km\n",
      "3. Nordbad, Munich, BY, Germany\n",
      "    1.2 km\n",
      "4. Münchner Stadtbibliothek Maxvorstadt, Munich, BY, Germany\n",
      "    0.9 km\n",
      "5. Pinakothek der Moderne, Munich, BY, Germany\n",
      "    0.88 km\n",
      "6. Schellingstraße 4, Munich, BY, Germany\n",
      "    2.62 km\n",
      "7. Museumsinsel 1, Munich, BY, Germany\n",
      "    1.83 km\n",
      "8. Sendlinger-Tor-Platz, Munich, BY, Germany\n",
      "    1.75 km\n",
      "9. Lindwurmstraße 167, Munich, BY, Germany\n",
      "\n",
      "Total distance: 16.00 km\n"
     ]
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   "source": [
    "# By default, we solve the module for a driving car. One can set a different\n",
    "# mode of transportation via the parameter \"mode_of_transportation\":\n",
    "new_parameters = {'mode_of_transportation':'foot-walking'}\n",
    "ts.set_parameters(parameters=new_parameters)\n",
    "\n",
    "results = ts.solve() # takes ~30s on my MacBook Pro\n",
    "\n",
    "ts.plot_shortest_path(filename='munich_pedestrian.html')"
   ]
  },
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   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
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