examples/run-example1.ipynb

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   "cell_type": "markdown",
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   "metadata": {},
   "source": [
    "# Run Example 1\n",
    "\n",
    "This notbook shows the workflow for running ESCAPE simulators on your personal computer.\n",
    "\n",
    "This notebook expects that you have installed plotly and escape_abm."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "988bb29c-1eb2-4dd6-b5da-c5398037a6aa",
   "metadata": {},
   "outputs": [],
   "source": [
    "import tempfile\n",
    "from pathlib import Path\n",
    "\n",
    "import polars as pl\n",
    "import plotly.express as px\n",
    "import plotly.io as pio\n",
    "pio.renderers.default = \"svg\"\n",
    "\n",
    "from escape_abm.utils import OpenMPSimulator"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9d075b51-4237-4c98-893d-676823123123",
   "metadata": {},
   "source": [
    "For running an ESCAPE simulators we need two things:\n",
    "1) the simulator description (the ESL file) and\n",
    "2) the network (nodes and edges)\n",
    "\n",
    "For this demo we shall use the following files.\n",
    "The node and edge file can be in parquet or CSV format."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "0c013870-5644-4707-8b65-b0cc7f7e684a",
   "metadata": {},
   "outputs": [],
   "source": [
    "sim_file = \"example1.esl\"\n",
    "node_file = \"nodes.parquet\"\n",
    "edge_file = \"edges.parquet\""
   ]
  },
  {
   "cell_type": "markdown",
   "id": "858c2c81-0b3c-40d7-93a3-b2160cb3bfeb",
   "metadata": {},
   "source": [
    "The node table contains the node key (pid for this simulation) and any other static node attributes that the simulation may depend on.\n",
    "\n",
    "Similarly, the edge table contains the source and target node key (source_pid and target_pid for this simulation) and any other static edge attributes that the simulation may depend on.\n",
    "\n",
    "The column names in the node and edge file must match those provided in the simulation file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e0711e65-3989-4984-8a0c-a17710ab8110",
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       "<small>shape: (5, 2)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>pid</th><th>is_in_school</th></tr><tr><td>i64</td><td>bool</td></tr></thead><tbody><tr><td>3723936</td><td>true</td></tr><tr><td>3723937</td><td>true</td></tr><tr><td>3723938</td><td>false</td></tr><tr><td>3723939</td><td>true</td></tr><tr><td>3723940</td><td>true</td></tr></tbody></table></div>"
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       "shape: (5, 2)\n",
       "┌─────────┬──────────────┐\n",
       "│ pid     ┆ is_in_school │\n",
       "│ ---     ┆ ---          │\n",
       "│ i64     ┆ bool         │\n",
       "╞═════════╪══════════════╡\n",
       "│ 3723936 ┆ true         │\n",
       "│ 3723937 ┆ true         │\n",
       "│ 3723938 ┆ false        │\n",
       "│ 3723939 ┆ true         │\n",
       "│ 3723940 ┆ true         │\n",
       "└─────────┴──────────────┘"
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     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pl.read_parquet(node_file).head()"
   ]
  },
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   "execution_count": 4,
   "id": "7224c96a-2f03-4440-a699-75758d08be62",
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       "</style>\n",
       "<small>shape: (5, 5)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>target_pid</th><th>source_pid</th><th>duration</th><th>is_school_edge</th><th>is_non_home_edge</th></tr><tr><td>i64</td><td>i64</td><td>i64</td><td>bool</td><td>bool</td></tr></thead><tbody><tr><td>3723936</td><td>3723937</td><td>14400</td><td>false</td><td>true</td></tr><tr><td>3723936</td><td>3723937</td><td>20519</td><td>false</td><td>true</td></tr><tr><td>3723936</td><td>3723937</td><td>41520</td><td>false</td><td>true</td></tr><tr><td>3723936</td><td>3731305</td><td>1020</td><td>false</td><td>true</td></tr><tr><td>3723936</td><td>3742032</td><td>1320</td><td>false</td><td>true</td></tr></tbody></table></div>"
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      "text/plain": [
       "shape: (5, 5)\n",
       "┌────────────┬────────────┬──────────┬────────────────┬──────────────────┐\n",
       "│ target_pid ┆ source_pid ┆ duration ┆ is_school_edge ┆ is_non_home_edge │\n",
       "│ ---        ┆ ---        ┆ ---      ┆ ---            ┆ ---              │\n",
       "│ i64        ┆ i64        ┆ i64      ┆ bool           ┆ bool             │\n",
       "╞════════════╪════════════╪══════════╪════════════════╪══════════════════╡\n",
       "│ 3723936    ┆ 3723937    ┆ 14400    ┆ false          ┆ true             │\n",
       "│ 3723936    ┆ 3723937    ┆ 20519    ┆ false          ┆ true             │\n",
       "│ 3723936    ┆ 3723937    ┆ 41520    ┆ false          ┆ true             │\n",
       "│ 3723936    ┆ 3731305    ┆ 1020     ┆ false          ┆ true             │\n",
       "│ 3723936    ┆ 3742032    ┆ 1320     ┆ false          ┆ true             │\n",
       "└────────────┴────────────┴──────────┴────────────────┴──────────────────┘"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "pl.read_parquet(edge_file).head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3a58bcf7-d38f-457b-b884-09a82931b575",
   "metadata": {},
   "source": [
    "We shall create a working directory for ESCAPE.\n",
    "\n",
    "ESCAPE shall use that folder to store the generated C++ codes and the compiled simulator.\n",
    "\n",
    "We shall also store the input.h5 and output.h5 files in that work directory."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f0e0a3b1-83c8-4b2d-ac9f-4aeec59809d7",
   "metadata": {},
   "outputs": [],
   "source": [
    "work_dir = Path(Path.home() / \"escape-work-dir\")\n",
    "\n",
    "input_file = work_dir / \"input.h5\""
   ]
  },
  {
   "cell_type": "raw",
   "id": "e41a73dc-1447-409b-8238-b2e6a636968d",
   "metadata": {},
   "source": [
    "Next we shall instantiate a OpenMP based multi-threaded simulator."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "8d390dca-c63e-46ac-a9aa-5ffc3ad2ee30",
   "metadata": {},
   "outputs": [],
   "source": [
    "simulator = OpenMPSimulator(sim_file, work_dir)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "09a3de09-bbbd-4bf0-9329-540c00fb6336",
   "metadata": {},
   "source": [
    "Next we shall call the prepare_build() method.\n",
    "This uses CMake to find or fetch the C++ libraries needed for building the simulator.\n",
    "It is not necessary to re-execute this method every time the simulation file is changed."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "70d64ad3-ace3-48b8-93e9-6388f50b7cfa",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "-- The C compiler identification is GNU 14.2.1\n",
      "-- The CXX compiler identification is GNU 14.2.1\n",
      "-- Detecting C compiler ABI info\n",
      "-- Detecting C compiler ABI info - done\n",
      "-- Check for working C compiler: /usr/bin/cc - skipped\n",
      "-- Detecting C compile features\n",
      "-- Detecting C compile features - done\n",
      "-- Detecting CXX compiler ABI info\n",
      "-- Detecting CXX compiler ABI info - done\n",
      "-- Check for working CXX compiler: /usr/bin/c++ - skipped\n",
      "-- Detecting CXX compile features\n",
      "-- Detecting CXX compile features - done\n",
      "-- Found HDF5: /usr/lib/libhdf5.so;/usr/lib/libsz.so;/usr/lib/libz.so;/usr/lib/libdl.a;/usr/lib/libm.so;/usr/lib/libhdf5_cpp.so;/usr/lib/libhdf5.so;/usr/lib/libsz.so;/usr/lib/libz.so;/usr/lib/libdl.a;/usr/lib/libm.so (found version \"1.14.4-3\") found components: C CXX\n",
      "-- Found OpenMP_C: -fopenmp (found version \"4.5\")\n",
      "-- Found OpenMP_CXX: -fopenmp (found version \"4.5\")\n",
      "-- Found OpenMP: TRUE (found version \"4.5\") found components: C CXX\n",
      "-- Version: 10.1.0\n",
      "-- Build type: \n",
      "-- Configuring done (4.7s)\n",
      "-- Generating done (0.0s)\n",
      "-- Build files have been written to: /home/parantapa/escape-work-dir/build\n"
     ]
    }
   ],
   "source": [
    "simulator.prepare_build()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "ebaa78a6-c473-4163-9cdf-5b4c549aee32",
   "metadata": {},
   "source": [
    "The build method actually builds the simulator.\n",
    "It first compiles the ESL code to C++ and then uses a C++ compiler to build the simulator binary.\n",
    "It is necessary to rerun this method every time the simulation file is updated."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "8bb4fb89-fe43-4711-b385-a2c8038fbb72",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 16%] \u001b[32mBuilding CXX object _deps/fmt-build/CMakeFiles/fmt.dir/src/format.cc.o\u001b[0m\n",
      "[ 33%] \u001b[32mBuilding CXX object _deps/fmt-build/CMakeFiles/fmt.dir/src/os.cc.o\u001b[0m\n",
      "[ 50%] \u001b[32m\u001b[1mLinking CXX static library libfmt.a\u001b[0m\n",
      "[ 50%] Built target fmt\n",
      "[ 66%] \u001b[34m\u001b[1mGenerating simulator_openmp.cpp, simulator_openmp_common.h\u001b[0m\n",
      "[ 66%] \u001b[34m\u001b[1mGenerating simulator_openmp.cpp, simulator_openmp_common.h\u001b[0m\n",
      "[ 83%] \u001b[32mBuilding CXX object CMakeFiles/simulator_openmp.dir/simulator_openmp.cpp.o\u001b[0m\n",
      "[100%] \u001b[32m\u001b[1mLinking CXX executable simulator_openmp\u001b[0m\n",
      "[100%] Built target simulator_openmp\n"
     ]
    }
   ],
   "source": [
    "simulator.build()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "feae47a4-a581-4d0b-92b1-028b900dccc7",
   "metadata": {},
   "source": [
    "Now that the simulator binary has been built, we can add the network to create a full simulation."
   ]
  },
  {
   "cell_type": "markdown",
   "id": "c72a0a2f-44c4-4835-9da8-33270fe748ff",
   "metadata": {},
   "source": [
    "The prepare input step creates the input_file from the network files (node and edge file).\n",
    "This also provides other relevant metadata to the simulator."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "883e99cf-08a2-445a-8a4a-57a26a603809",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008080; text-decoration-color: #008080\">Reading node table.</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[36mReading node table.\u001b[0m\n"
      ]
     },
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     "output_type": "display_data"
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008080; text-decoration-color: #008080\">Sorting node table.</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[36mSorting node table.\u001b[0m\n"
      ]
     },
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008080; text-decoration-color: #008080\">Making node index.</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[36mMaking node index.\u001b[0m\n"
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     "text": [
      "### num_nodes:  83313\n"
     ]
    },
    {
     "data": {
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       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008080; text-decoration-color: #008080\">Reading edge table.</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[36mReading edge table.\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008080; text-decoration-color: #008080\">Sorting edge table.</span>\n",
       "</pre>\n"
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      "text/plain": [
       "\u001b[36mSorting edge table.\u001b[0m\n"
      ]
     },
     "metadata": {},
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    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008080; text-decoration-color: #008080\">Computing incoming incidence CSR graph's indptr.</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[36mComputing incoming incidence CSR graph's indptr.\u001b[0m\n"
      ]
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     "text": [
      "### num_edges:  3269342\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008080; text-decoration-color: #008080\">Creating input file.</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[36mCreating input file.\u001b[0m\n"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/html": [
       "<pre style=\"white-space:pre;overflow-x:auto;line-height:normal;font-family:Menlo,'DejaVu Sans Mono',consolas,'Courier New',monospace\"><span style=\"color: #008000; text-decoration-color: #008000\">Input file created successfully.</span>\n",
       "</pre>\n"
      ],
      "text/plain": [
       "\u001b[32mInput file created successfully.\u001b[0m\n"
      ]
     },
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   ],
   "source": [
    "simulator.prepare_input(node_file, edge_file, input_file)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "43dab982-0de1-4611-92ed-54f8906cb32a",
   "metadata": {},
   "source": [
    "We can view the node and edge tables in the input file using extract_nodes() and extract_edges() helper methods."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "faa5d15a-5ebe-4cae-bd22-cff6d62bd8bf",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<div><style>\n",
       ".dataframe > thead > tr,\n",
       ".dataframe > tbody > tr {\n",
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       "}\n",
       "</style>\n",
       "<small>shape: (5, 2)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>pid</th><th>is_in_school</th></tr><tr><td>i64</td><td>u8</td></tr></thead><tbody><tr><td>3723936</td><td>1</td></tr><tr><td>3723937</td><td>1</td></tr><tr><td>3723938</td><td>0</td></tr><tr><td>3723939</td><td>1</td></tr><tr><td>3723940</td><td>1</td></tr></tbody></table></div>"
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      "text/plain": [
       "shape: (5, 2)\n",
       "┌─────────┬──────────────┐\n",
       "│ pid     ┆ is_in_school │\n",
       "│ ---     ┆ ---          │\n",
       "│ i64     ┆ u8           │\n",
       "╞═════════╪══════════════╡\n",
       "│ 3723936 ┆ 1            │\n",
       "│ 3723937 ┆ 1            │\n",
       "│ 3723938 ┆ 0            │\n",
       "│ 3723939 ┆ 1            │\n",
       "│ 3723940 ┆ 1            │\n",
       "└─────────┴──────────────┘"
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     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "simulator.extract_nodes(input_file).head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a8f40d6c-4090-4c04-b0e7-5fcedfeb7f0b",
   "metadata": {},
   "outputs": [
    {
     "data": {
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       ".dataframe > thead > tr,\n",
       ".dataframe > tbody > tr {\n",
       "  text-align: right;\n",
       "  white-space: pre-wrap;\n",
       "}\n",
       "</style>\n",
       "<small>shape: (5, 7)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>target_pid</th><th>source_pid</th><th>duration</th><th>is_school_edge</th><th>is_non_home_edge</th><th>_target_node_index</th><th>_source_node_index</th></tr><tr><td>i64</td><td>i64</td><td>i64</td><td>u8</td><td>u8</td><td>i32</td><td>i32</td></tr></thead><tbody><tr><td>3723936</td><td>3723937</td><td>14400</td><td>0</td><td>1</td><td>0</td><td>1</td></tr><tr><td>3723936</td><td>3723937</td><td>20519</td><td>0</td><td>1</td><td>0</td><td>1</td></tr><tr><td>3723936</td><td>3723937</td><td>41520</td><td>0</td><td>1</td><td>0</td><td>1</td></tr><tr><td>3723936</td><td>3731305</td><td>1020</td><td>0</td><td>1</td><td>0</td><td>7369</td></tr><tr><td>3723936</td><td>3733825</td><td>5700</td><td>1</td><td>1</td><td>0</td><td>9889</td></tr></tbody></table></div>"
      ],
      "text/plain": [
       "shape: (5, 7)\n",
       "┌────────────┬────────────┬──────────┬───────────────┬───────────────┬──────────────┬──────────────┐\n",
       "│ target_pid ┆ source_pid ┆ duration ┆ is_school_edg ┆ is_non_home_e ┆ _target_node ┆ _source_node │\n",
       "│ ---        ┆ ---        ┆ ---      ┆ e             ┆ dge           ┆ _index       ┆ _index       │\n",
       "│ i64        ┆ i64        ┆ i64      ┆ ---           ┆ ---           ┆ ---          ┆ ---          │\n",
       "│            ┆            ┆          ┆ u8            ┆ u8            ┆ i32          ┆ i32          │\n",
       "╞════════════╪════════════╪══════════╪═══════════════╪═══════════════╪══════════════╪══════════════╡\n",
       "│ 3723936    ┆ 3723937    ┆ 14400    ┆ 0             ┆ 1             ┆ 0            ┆ 1            │\n",
       "│ 3723936    ┆ 3723937    ┆ 20519    ┆ 0             ┆ 1             ┆ 0            ┆ 1            │\n",
       "│ 3723936    ┆ 3723937    ┆ 41520    ┆ 0             ┆ 1             ┆ 0            ┆ 1            │\n",
       "│ 3723936    ┆ 3731305    ┆ 1020     ┆ 0             ┆ 1             ┆ 0            ┆ 7369         │\n",
       "│ 3723936    ┆ 3733825    ┆ 5700     ┆ 1             ┆ 1             ┆ 0            ┆ 9889         │\n",
       "└────────────┴────────────┴──────────┴───────────────┴───────────────┴──────────────┴──────────────┘"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "simulator.extract_edges(input_file).head()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "9ee5e13d-56a4-4f68-aab0-d732fe8a68a0",
   "metadata": {},
   "source": [
    "Finally to run a simulation, we provide the location of the output file and call simulate.\n",
    "Here we can also pass a dictionary of configuration variables that were defined in the simulation."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "cd786e1c-9903-4eb5-b5b2-dbf58c23e81d",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "### num_threads = 12\n",
      "### enable_hybrid_learning = 1\n",
      "### enable_day_30_antigen_test = 1\n",
      "### enable_day_30_pcr_test = 0\n",
      "### transmissibility_scale = 0.3\n",
      "### num_ticks = 100\n",
      "### input_file = /home/parantapa/escape-work-dir/input.h5\n",
      "### output_file = /home/parantapa/escape-work-dir/output.h5\n",
      "### num_nodes = 83313\n",
      "### num_edges = 3269342\n",
      "### cur_tick = 0\n",
      "### cur_tick = 1\n",
      "### cur_tick = 2\n",
      "### cur_tick = 3\n",
      "### cur_tick = 4\n",
      "### cur_tick = 5\n",
      "### cur_tick = 6\n",
      "### cur_tick = 7\n",
      "### cur_tick = 8\n",
      "### cur_tick = 9\n",
      "### cur_tick = 10\n",
      "### cur_tick = 11\n",
      "### cur_tick = 12\n",
      "### cur_tick = 13\n",
      "### cur_tick = 14\n",
      "### cur_tick = 15\n",
      "### cur_tick = 16\n",
      "### cur_tick = 17\n",
      "### cur_tick = 18\n",
      "### cur_tick = 19\n",
      "### cur_tick = 20\n",
      "### cur_tick = 21\n",
      "### cur_tick = 22\n",
      "### cur_tick = 23\n",
      "### cur_tick = 24\n",
      "### cur_tick = 25\n",
      "### cur_tick = 26\n",
      "### cur_tick = 27\n",
      "### cur_tick = 28\n",
      "### cur_tick = 29\n",
      "### cur_tick = 30\n",
      "### cur_tick = 31\n",
      "### cur_tick = 32\n",
      "### cur_tick = 33\n",
      "### cur_tick = 34\n",
      "### cur_tick = 35\n",
      "### cur_tick = 36\n",
      "### cur_tick = 37\n",
      "### cur_tick = 38\n",
      "### cur_tick = 39\n",
      "### cur_tick = 40\n",
      "### cur_tick = 41\n",
      "### cur_tick = 42\n",
      "### cur_tick = 43\n",
      "### cur_tick = 44\n",
      "### cur_tick = 45\n",
      "### cur_tick = 46\n",
      "### cur_tick = 47\n",
      "### cur_tick = 48\n",
      "### cur_tick = 49\n",
      "### cur_tick = 50\n",
      "### cur_tick = 51\n",
      "### cur_tick = 52\n",
      "### cur_tick = 53\n",
      "### cur_tick = 54\n",
      "### cur_tick = 55\n",
      "### cur_tick = 56\n",
      "### cur_tick = 57\n",
      "### cur_tick = 58\n",
      "### cur_tick = 59\n",
      "### cur_tick = 60\n",
      "### cur_tick = 61\n",
      "### cur_tick = 62\n",
      "### cur_tick = 63\n",
      "### cur_tick = 64\n",
      "### cur_tick = 65\n",
      "### cur_tick = 66\n",
      "### cur_tick = 67\n",
      "### cur_tick = 68\n",
      "### cur_tick = 69\n",
      "### cur_tick = 70\n",
      "### cur_tick = 71\n",
      "### cur_tick = 72\n",
      "### cur_tick = 73\n",
      "### cur_tick = 74\n",
      "### cur_tick = 75\n",
      "### cur_tick = 76\n",
      "### cur_tick = 77\n",
      "### cur_tick = 78\n",
      "### cur_tick = 79\n",
      "### cur_tick = 80\n",
      "### cur_tick = 81\n",
      "### cur_tick = 82\n",
      "### cur_tick = 83\n",
      "### cur_tick = 84\n",
      "### cur_tick = 85\n",
      "### cur_tick = 86\n",
      "### cur_tick = 87\n",
      "### cur_tick = 88\n",
      "### cur_tick = 89\n",
      "### cur_tick = 90\n",
      "### cur_tick = 91\n",
      "### cur_tick = 92\n",
      "### cur_tick = 93\n",
      "### cur_tick = 94\n",
      "### cur_tick = 95\n",
      "### cur_tick = 96\n",
      "### cur_tick = 97\n",
      "### cur_tick = 98\n",
      "### cur_tick = 99\n",
      "### mem_use_gb = 0.0761571\n",
      "### init_time_s = 0.0296614\n",
      "### main_time_s = 4.13791\n"
     ]
    }
   ],
   "source": [
    "output_file = work_dir / \"output.h5\"\n",
    "\n",
    "simulator.simulate(input_file, output_file, num_ticks=100, configs={\"enable_hybrid_learning\": True}, verbose=True)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3d17157c-2b4a-4dcc-9edf-43c35d8004b5",
   "metadata": {},
   "source": [
    "Once the simulation is complete we can extract summary, transitions, transmissions and interventions from the output file."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "06364a63-064d-472f-8865-3ff67dfe32a1",
   "metadata": {},
   "outputs": [
    {
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       "<small>shape: (5, 7)</small><table border=\"1\" class=\"dataframe\"><thead><tr><th>S</th><th>E</th><th>Ipresymp</th><th>Isymp</th><th>Iasymp</th><th>R</th><th>tick</th></tr><tr><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td><td>i64</td></tr></thead><tbody><tr><td>83308</td><td>5</td><td>0</td><td>0</td><td>0</td><td>0</td><td>0</td></tr><tr><td>83303</td><td>10</td><td>0</td><td>0</td><td>0</td><td>0</td><td>1</td></tr><tr><td>83298</td><td>11</td><td>4</td><td>0</td><td>0</td><td>0</td><td>2</td></tr><tr><td>83293</td><td>12</td><td>7</td><td>0</td><td>1</td><td>0</td><td>3</td></tr><tr><td>83283</td><td>19</td><td>5</td><td>4</td><td>2</td><td>0</td><td>4</td></tr></tbody></table></div>"
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       "┌───────┬─────┬──────────┬───────┬────────┬─────┬──────┐\n",
       "│ S     ┆ E   ┆ Ipresymp ┆ Isymp ┆ Iasymp ┆ R   ┆ tick │\n",
       "│ ---   ┆ --- ┆ ---      ┆ ---   ┆ ---    ┆ --- ┆ ---  │\n",
       "│ i64   ┆ i64 ┆ i64      ┆ i64   ┆ i64    ┆ i64 ┆ i64  │\n",
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       "│ 83293 ┆ 12  ┆ 7        ┆ 0     ┆ 1      ┆ 0   ┆ 3    │\n",
       "│ 83283 ┆ 19  ┆ 5        ┆ 4     ┆ 2      ┆ 0   ┆ 4    │\n",
       "└───────┴─────┴──────────┴───────┴────────┴─────┴──────┘"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
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   ],
   "source": [
    "summary = simulator.extract_summary(output_file)\n",
    "summary.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "433f3045-b199-4ea8-929a-530f32cd95d9",
   "metadata": {},
   "outputs": [
    {
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     "execution_count": 14,
     "metadata": {},
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   ],
   "source": [
    "transitions = simulator.extract_transitions(output_file)\n",
    "transitions.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "fba483a8-bc3d-482c-83d7-07274aa5b4f8",
   "metadata": {},
   "outputs": [
    {
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   "source": [
    "transmissions = simulator.extract_transmissions(output_file)\n",
    "transmissions.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "099e408a-4eed-4b54-a168-62dc21a370fb",
   "metadata": {},
   "outputs": [
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   "source": [
    "interventions = simulator.extract_interventions(output_file)\n",
    "interventions.head()"
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  {
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   "id": "f3b7691a-027a-4954-9822-536b4ec408a9",
   "metadata": {},
   "source": [
    "Get the user defined statistics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "id": "70045dee-8ba8-4da6-a849-298b645dd2d5",
   "metadata": {},
   "outputs": [
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   "source": [
    "statistics = simulator.extract_statistics(output_file)\n",
    "statistics.head()"
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  },
  {
   "cell_type": "markdown",
   "id": "d65cc15a-986f-4b29-824e-b556a0665108",
   "metadata": {},
   "source": [
    "Runtime statistics are also saved in the output file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "id": "84f95242-a5b8-46dc-bbff-4e32cc3d1355",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'init_time_s': 0.02966140199714573,\n",
       " 'main_time_s': 4.137906273001136,\n",
       " 'mem_use_gb': 0.07615712,\n",
       " 'num_threads': 12}"
      ]
     },
     "execution_count": 18,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "simulator.runtime_stats(output_file)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1fea1e17-285e-41c0-8a02-ef3cb64ab07a",
   "metadata": {},
   "source": [
    "Configuration variables are also saved in output file"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "id": "3fb4b2fc-4a76-46c4-af44-5ab5045c473f",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'enable_day_30_antigen_test': 1,\n",
       " 'enable_day_30_pcr_test': 0,\n",
       " 'enable_hybrid_learning': 1,\n",
       " 'transmissibility_scale': 0.3}"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "simulator.extract_configs(output_file)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aec76b95-9c83-4c25-87b0-c90a7df3829d",
   "metadata": {},
   "source": [
    "Compute attack rate as follows:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "id": "96bc4e32-319a-45de-88a6-51f91b54c4ee",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "0.8149268421494845"
      ]
     },
     "execution_count": 20,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "num_nodes = simulator.num_nodes(input_file)\n",
    "attack_rate = simulator.compute_cum_count(transitions, [\"E\"]) / num_nodes\n",
    "attack_rate"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "id": "34b341d2-175e-46be-894d-c476a917443c",
   "metadata": {
    "scrolled": true
   },
   "outputs": [
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font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 17px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Number of individuals in each state over time</text></g><g class=\"g-xtitle\"><text class=\"xtitle\" x=\"327.5\" y=\"460.3\" text-anchor=\"middle\" style=\"opacity: 1; font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">tick</text></g><g class=\"g-ytitle\"><text class=\"ytitle\" transform=\"rotate(-90,37.240625,260)\" x=\"37.240625\" y=\"260\" text-anchor=\"middle\" style=\"opacity: 1; font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">count</text></g></g></svg>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "states = summary.columns\n",
    "states.remove(\"tick\")\n",
    "\n",
    "title = \"Number of individuals in each state over time\"\n",
    "pdf = summary.unpivot(index=\"tick\", on=states, variable_name=\"state\", value_name=\"count\")\n",
    "px.line(pdf, x=\"tick\", y=\"count\", color=\"state\", title=title)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "id": "9ed94027-7e42-4cee-8871-ce01f6354bd9",
   "metadata": {},
   "outputs": [
    {
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font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 17px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Cumulative number of individuals who have visited each state over time</text></g><g class=\"g-xtitle\"><text class=\"xtitle\" x=\"327.5\" y=\"460.3\" text-anchor=\"middle\" style=\"opacity: 1; font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">tick</text></g><g class=\"g-ytitle\"><text class=\"ytitle\" transform=\"rotate(-90,37.240625,260)\" x=\"37.240625\" y=\"260\" text-anchor=\"middle\" style=\"opacity: 1; font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">count</text></g></g></svg>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "num_ticks = simulator.num_ticks(output_file)\n",
    "state_tick_cum_counts = simulator.compute_state_tick_unique_counts(transitions, num_ticks)\n",
    "\n",
    "states = state_tick_cum_counts.columns\n",
    "states.remove(\"tick\")\n",
    "\n",
    "state_tick_cum_counts = state_tick_cum_counts.with_columns(\n",
    "    *[pl.col(state).cum_sum() for state in states]\n",
    ")\n",
    "\n",
    "title = \"Cumulative number of individuals who have visited each state over time\"\n",
    "pdf = state_tick_cum_counts.unpivot(index=\"tick\", on=states, variable_name=\"state\", value_name=\"count\")\n",
    "px.line(pdf, x=\"tick\", y=\"count\", color=\"state\", title=title)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "id": "4c6c4a96-542f-4599-bd5d-3a983e121439",
   "metadata": {},
   "outputs": [
    {
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font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 17px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">Number of individuals state S or R over time</text></g><g class=\"g-xtitle\"><text class=\"xtitle\" x=\"350\" y=\"460.3\" text-anchor=\"middle\" style=\"opacity: 1; font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">tick</text></g><g class=\"g-ytitle\"><text class=\"ytitle\" transform=\"rotate(-90,37.240625,260)\" x=\"37.240625\" y=\"260\" text-anchor=\"middle\" style=\"opacity: 1; font-family: 'Open Sans', verdana, arial, sans-serif; font-size: 14px; fill: rgb(42, 63, 95); fill-opacity: 1; white-space: pre;\">S_or_R</text></g></g></svg>"
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     "metadata": {},
     "output_type": "display_data"
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   ],
   "source": [
    "title = \"Number of individuals state S or R over time\"\n",
    "px.line(statistics, x=\"tick\", y=\"S_or_R\", title=title)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "id": "b02e3548-4b24-46b6-b257-99adc10eeab4",
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     "metadata": {},
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   ],
   "source": [
    "title = \"Number of enabled edges over time\"\n",
    "px.line(statistics, x=\"tick\", y=\"enabled_edge_count\", title=title)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "66da3ce3-e99f-4829-bb58-84dc225b9681",
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   "source": []
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