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   "source": [

    "# FEMR Ontology support\n",

    "\n",

    "FEMR provides support for querying ontologies using the OMOP Vocabulary. \n",

    "\n",

    "This enables easier definition of labeling functions as well as better feature generation."

   ]

  },

  {

   "cell_type": "markdown",

   "metadata": {},

   "source": [

    "# Downloading the OMOP Vocabulary\n",

    "\n",

    "The OMOP Vocabulary can be downloaded for free from the [OHDSI ATHENA website.](https://athena.ohdsi.org/)"

   ]

  },

  {

   "cell_type": "markdown",

   "metadata": {},

   "source": [

    "# Processing the OMOP Vocabulary\n",

    "\n",

    "femr.ontology.Ontology allows you to process, and then use the OMOP Vocabulary, optionally combining it with [code metadata from MEDS](https://github.com/Medical-Event-Data-Standard/meds/blob/e93f63a2f9642123c49a31ecffcdb84d877dc54a/src/meds/__init__.py#L94).\n",

    "\n",

    "```python \n",

    "ontology = femr.ontology.Ontology(path_to_athena, code_metadata)\n",

    "```"

   ]

  },

  {

   "cell_type": "markdown",

   "metadata": {},

   "source": [

    "# Working with an Ontology object\n",

    "\n",

    "The following code samples illustrate the main ways to use a vocabulary object"

   ]

  },

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     "text": [

      "/home/esteinberg/miniconda3/envs/debug_document_femr/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",

      "  from .autonotebook import tqdm as notebook_tqdm\n"

     ]

    },

    {

     "name": "stdout",

     "output_type": "stream",

     "text": [

      "Loaded ontology\n"

     ]

    }

   ],

   "source": [

    "import pickle\n",

    "\n",

    "# You can load / save ontology objects with pickle\n",

    "\n",

    "with open('input/meds/ontology.pkl', 'rb') as f:\n",

    "    ontology = pickle.load(f)\n",

    "\n",

    "print(\"Loaded ontology\")"

   ]

  },

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    {

     "name": "stderr",

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     "text": [

      "Generating train split: 200 examples [00:00, 34972.93 examples/s]\n",

      "Map: 100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 200/200 [00:00<00:00, 3282.29 examples/s]\n"

     ]

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   "source": [

    "# Ontology datasets downloaded by Athena tend to be very large as they contain many codes, including several that are no longer used.\n",

    "# We therefore provide a function to prune ontologies to a particular dataset of interest.\n",

    "# This makes it much cheaper to store and use an ontology object, both in terms of disk space and RAM\n",

    "\n",

    "import datasets\n",

    "dataset = datasets.Dataset.from_parquet(\"input/meds/data/*\")\n",

    "\n",

    "ontology.prune_to_dataset(dataset)"

   ]

  },

  {

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    {

     "name": "stdout",

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     "text": [

      "Description DRUGS FOR PEPTIC ULCER AND GASTRO-OESOPHAGEAL REFLUX DISEASE (GORD)\n",

      "Parents {'ATC/A02'}\n",

      "Children {'ATC/A02BX'}\n",

      "All children {'RxNorm/2344', 'ATC/A02BX', 'RxNorm/4501', 'ATC/A02BX71', 'ATC/A02B', 'RxNorm/7815', 'RxNorm/7019', 'ATC/A02BX77', 'RxNorm/2353', 'RxNorm/8705', 'RxNorm/38574', 'RxNorm/2620', 'RxNorm/2018', 'RxNorm/8704', 'RxNorm/8730', 'RxNorm/6852', 'RxNorm/2017', 'RxNorm/2403'}\n",

      "All parents {'ATC/A', 'ATC/A02', 'ATC/A02B'}\n"

     ]

    }

   ],

   "source": [

    "# First, we can query the description for a particular code\n",

    "print(\"Description\", ontology.get_description(\"ATC/A02B\"))\n",

    "\n",

    "# Second, we can search for the parents of a particular code\n",

    "print(\"Parents\", ontology.get_parents(\"ATC/A02B\"))\n",

    "\n",

    "# Finally, we can search for the children of a particular code\n",

    "print(\"Children\", ontology.get_children(\"ATC/A02B\"))\n",

    "\n",

    "# For the sake of convience, we also support the recursive versions of querying parents and children\n",

    "print(\"All children\", ontology.get_all_children(\"ATC/A02B\"))\n",

    "print(\"All parents\", ontology.get_all_parents(\"ATC/A02B\"))"

   ]

  }

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