00_generate_remf.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "694dfd52",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Tue Aug 30 19:36:27 PDT 2022\r\n"
     ]
    }
   ],
   "source": [
    "import numpy as np, matplotlib.pyplot as plt, pandas as pd\n",
    "pd.set_option('display.max_rows', 8)\n",
    "!date\n",
    "\n",
    "%load_ext autoreload\n",
    "%autoreload 2"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "fc70badb",
   "metadata": {},
   "source": [
    "# Cluster run of reconstruction code\n",
    "\n",
    "Refactored in [2022_05_07a_das_dhc_attack_etl_refactor.ipynb](2022_05_07a_das_dhc_attack_etl_refactor.ipynb), updated to run with new DHC Demo Product on 2022-08-30,"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "30c4a3c2",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/ihme/homes/abie/miniconda3/bin/python\r\n"
     ]
    }
   ],
   "source": [
    "# is sbatch smart enough to run the right python?\n",
    "\n",
    "!which python"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "aec1e689",
   "metadata": {},
   "source": [
    "If it is not, try using the shell script approach from https://hub.ihme.washington.edu/display/BIRDS/How+to+SLURM\n",
    "\n",
    "        #!/usr/bin/env bash\n",
    "        #/usr/local/anaconda-current/bin/python \"$@\"\n",
    "        #SBATCH -J test_job\n",
    "        #SBATCH -t 00:01:00\n",
    "        #SBATCH --mem=128m\n",
    "        #SBATCH -c 1\n",
    "        #SBATCH -A ihme_general\n",
    "        #SBATCH -p all.q\n",
    "        /ihme/code/central_comp/miniconda/envs/gbd_env/bin/python \"$@\"\n",
    "        export PYTHONPATH=\"/homes/username/\"\n",
    "        python scriptname.py\n",
    "\n",
    "A python job can be submitted on SLURM by updating the shell script with flags shown above and by using command: \n",
    "\n",
    "\n",
    "    sbatch myshellscript.sh"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "f0ebaa38",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "/mnt/share/homes/abie/projects/2022/linked_census_disclosure\n"
     ]
    }
   ],
   "source": [
    "%cd ~/projects/2022/linked_census_disclosure/"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "997dcaec",
   "metadata": {},
   "outputs": [],
   "source": [
    "# rows = pd.DataFrame(index=range(5,10)).index\n",
    "# t = pd.Series([0,1])\n",
    "# rows = rows.append(t[t>0].index).drop_duplicates()\n",
    "# rows"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "d8e5426c",
   "metadata": {
    "scrolled": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "running 00_generate_remf.py with 1000 splits.\n",
      "processing part 0\n",
      "Loading segment 1\n",
      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
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      "\n",
      ". . . . . . . . . . . . . . . . "
     ]
    }
   ],
   "source": [
    "run 00_generate_remf.py 1_000 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "64019f4f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# import importlib\n",
    "# importlib.reload(lcd_model)\n",
    "# lcd_model.reconstruct_block(dhc_tables, *location_tuple)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "afd919e5",
   "metadata": {},
   "outputs": [],
   "source": [
    "# lcd_model.reconstruct_block(sf1_tables, *location_tuple)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "2e60d618",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
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     ]
    }
   ],
   "source": [
    "n_splits = 1_000\n",
    "for i in range(n_splits):\n",
    "    !sbatch 00_generate_remf.py $n_splits $i"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4a6204d2",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
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