Washington_Des_Oct_2_READONLY.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "import bqplot\n",
    "import pandas as pd\n",
    "import ipywidgets as widgets\n",
    "from restart import RestartModel\n",
    "from restart import util\n",
    "from restart.util import set_config, to_df, to_sheet, display_population, format_population, format_cells\n",
    "from bqplot import pyplot as plt\n",
    "import restart\n",
    "\n",
    "gr_restart = RestartModel(\n",
    "    config='wa_groups',\n",
    "    population='oes',\n",
    "    state='Washington',\n",
    "    subpop='wa_groupings'\n",
    ")\n",
    "\n",
    "gr_model = gr_restart.model\n",
    "gr_model.inventory.set_average_orders_per_period(gr_model.demand.demand_by_popsum1_total_rp1n_tc)\n",
    "\n",
    "gr_slider = widgets.IntSlider(min=1, max=120, value=30, description = \"Days\", continuous_update=False)\n",
    "\n",
    "def gr_dashboard(backstop):\n",
    "    gr_set_stock(backstop)\n",
    "    \n",
    "def gr_display_stock(df):\n",
    "    df_round = df.round()\n",
    "    index_name = \"Population\"\n",
    "    headers = ['EMTs', 'Firefighters', 'Other Public Safety']\n",
    "    df_round.insert(loc=0, column=index_name, value=headers)\n",
    "    sheet = to_sheet(df_round)\n",
    "    format_cells(sheet)\n",
    "    sheet.row_headers = False\n",
    "    display(sheet)\n",
    "    \n",
    "def gr_set_stock(backstop):\n",
    "    backstop = [backstop]\n",
    "    gr_model.inventory.order(gr_model.inventory.inv_by_popsum1_total_rp1n_tc)\n",
    "    gr_model.inventory.set_min_in_periods(backstop)\n",
    "    gr_display_stock(gr_model.inventory.inv_by_popsum1_total_rp1n_tc.df)\n",
    "    \n",
    "wa_burn_sheet = format_population(to_sheet(gr_model.demand.demand_per_unit_map_dn_um.df))\n",
    "gr_pop = format_population(to_sheet(gr_model.population.population_pP_tr.df))\n",
    "    \n",
    "gr_out = widgets.interactive_output(gr_dashboard, {'backstop': gr_slider})\n",
    "gr_sum_sheet = format_population(to_sheet(gr_model.population.pop_to_popsum1_per_unit_map_pp1_us.df))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import ipysheet\n",
    "import ipywidgets as widgets\n",
    "from ipywidgets import Layout\n",
    "\n",
    "restart = RestartModel(config='des', population='oes', state='Washington', subpop='wa_tier2_opt2')\n",
    "model = restart.model\n",
    "model.inventory.set_average_orders_per_period(model.demand.demand_by_popsum1_total_rp1n_tc)\n",
    "\n",
    "slider = widgets.IntSlider(min=1, max=120, value=30, description = \"Days\", continuous_update=False)\n",
    "\n",
    "def dashboard(backstop):\n",
    "    set_stock(backstop)\n",
    "    \n",
    "def display_stock(df):\n",
    "    df_round = df.round()\n",
    "    index_name = \"Population\"\n",
    "    headers = ['Essential', 'Non-Essential']\n",
    "    df_round.insert(loc=0, column=index_name, value=headers)\n",
    "    sheet = to_sheet(df_round)\n",
    "    format_cells(sheet)\n",
    "    sheet.row_headers = False\n",
    "    df_chart = df\n",
    "    df_chart.index = df_chart.index.get_level_values(1)\n",
    "    chart = util.generate_group_bar_legend(df_chart, scientific_notation=True)\n",
    "    display(sheet)\n",
    "    display(chart)\n",
    "    \n",
    "def set_stock(backstop):\n",
    "    backstop = [backstop]\n",
    "    model.inventory.order(model.inventory.inv_by_popsum1_total_rp1n_tc)\n",
    "    model.inventory.set_min_in_periods(backstop)\n",
    "    display_stock(model.inventory.inv_by_popsum1_total_rp1n_tc.df)\n",
    "\n",
    "pop = format_population(to_sheet(model.population.population_pP_tr.df))\n",
    "\n",
    "burn_chart = util.generate_group_bar_legend(model.demand.demand_per_unit_map_dn_um.df)\n",
    "out = widgets.interactive_output(dashboard, {'backstop': slider})\n",
    "\n",
    "wa_burn_sheet = format_population(to_sheet(model.demand.demand_per_unit_map_dn_um.df))\n",
    "pop = format_population(to_sheet(model.population.population_pP_tr.df))\n",
    "\n",
    "essential_arr = restart.model.population.pop_to_popsum1_per_unit_map_pp1_us.array\n",
    "population_labels = list(restart.model.population.pop_to_popsum1_per_unit_map_pp1_us.df.index)\n",
    "\n",
    "\n",
    "essential_list = []\n",
    "\n",
    "for row in essential_arr:\n",
    "    if row[0] == 1:\n",
    "        essential_list.append('Y')\n",
    "    else:\n",
    "        essential_list.append('N')\n",
    "\n",
    "essential_df = pd.DataFrame(essential_list)\n",
    "essential_df.insert(loc=0, column='Population', value=population_labels)\n",
    "essential_df.columns = ['Population', 'Essential Worker']\n",
    "essential_sheet = to_sheet(essential_df)\n",
    "essential_sheet.row_headers = False"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import ipyvuetify as v\n",
    "v.theme.themes.light.primary = 'colors.teal'\n",
    "\n",
    "v.Tabs(_metadata={'mount_id': 'content-main'}, children=[\n",
    "    v.Tab(children=['PPE Analysis']),\n",
    "    v.Tab(children=['Methodology']),\n",
    "    v.Tab(children=['Burn Rates']),\n",
    "    v.Tab(children=['First Responders/Public Safety']),\n",
    "    v.Tab(children=['Healthcare - Selected']),\n",
    "                \n",
    "    v.TabItem(children=[\n",
    "        v.Layout(column=True, wrap=True, align_left=True, children=[\n",
    "            v.Card(xs12=True, lg6=True, xl4=True, children=[\n",
    "                v.CardTitle(primary_title=True, class_='headline', children=[\"PPE Stockpile\"]),\n",
    "                v.CardText(children=[\n",
    "                    \"First responders/public safety officers - manually selected SOC codes:\"\n",
    "                ]),\n",
    "                gr_slider, gr_out,\n",
    "                v.CardText(children=[\n",
    "                    \"Healthcare providers (inpatient and outpatient) - broad view (desired populations may be a percentage of this):\"\n",
    "                ]),\n",
    "                slider, out,\n",
    "            ])\n",
    "                \n",
    "        ])\n",
    "    ]),\n",
    "    v.TabItem(children=[\n",
    "        v.Layout(column=True, wrap=True, align_left=True, children=[\n",
    "            v.Card(xs12=True, lg6=True, xl4=True, children=[\n",
    "                v.CardTitle(primary_title=True, class_='headline', children=[\"Covid Incremental Ventilator Requirements\"]),\n",
    "                v.CardText(children=[(\n",
    "                    \"\"\"Group 1: Backstop to Large Providers\"\"\")]),\n",
    "                v.CardText(children=[(\n",
    "                    \"\"\"These are the large hospitals and other facilities that take care of our \n",
    "                     sickest patients. With the fall, we will face the difficult challenge of  \n",
    "                     both the flu season and the recurrence of COVID-19 as the climate worsens \n",
    "                     and people move indoors. This group will provide most of their own PPE,  \n",
    "                     disinfection and other resources with the state acting as a backstop in extreme \n",
    "                     emergencies. Given the exponential nature of infection, we need this backstop  \n",
    "                     because even the best predictions have a large variance. For example, if the \n",
    "                     disease doubles every week, then even a two week error in estimate will increase \n",
    "                     PPE requirements in COVID wards by 4x.\"\"\")]),           \n",
    "                v.CardText(children=[(\n",
    "                    \"\"\"Group 2: Aggregate Demand of Smaller Providers\"\"\")]),       \n",
    "                v.CardText(children=[(\n",
    "                    \"\"\"This second group consists of several different populations: \n",
    "                     Smaller health care providers such as hospitals with 299 beds or less, long-term care \n",
    "                     providers and nursing homes, behavioral health facilities, dentists, morticians, \n",
    "                     Federally Qualified Health Centers (FQHC), public health organizations, tribal clinics, \n",
    "                     independent physician practices, first responders including EMOs, police, and fire\"\"\")]),            \n",
    "                v.CardText(children=[(\n",
    "                    \"\"\"We use two different methods to estimate these populations. More detailed surveys and  \n",
    "                     census methods are also possible, so consider these methods as ways to get a broad measure \n",
    "                     of the scope of the problem.\"\"\")]),            \n",
    "                v.CardText(children=[(\n",
    "                    \"\"\"Employee Classification (SOC) Analysis: \"\"\")]),                  \n",
    "                v.CardText(children=[(\n",
    "                    \"\"\"SOC codes starting with \"29-\", \"31-\", and \"33-\" refer to, respectively, healthcare occupations, \n",
    "                     healthcare support occupations, and protection services. We estimate of the percentage of \n",
    "                     healthcare workers or healthcare-support workers fall into the Group 2 category, and simply \n",
    "                     scale all the numbers by that amount. It seems like a safe assumption that all the protection \n",
    "                     services would fall into this group.\"\"\")]),                  \n",
    "                 v.CardText(children=[(\n",
    "                    \"\"\"This analysis provides the stockpile that you would need to 100% cover the group for 30 days.\n",
    "                     A key policy decision is the size of the back stop needed. If you want to cover 50% of the \n",
    "                     demand for 30 days, then the figures would be half that.\"\"\")]),                     \n",
    "            ]),\n",
    "        ])\n",
    "    ]),\n",
    "                \n",
    "    v.TabItem(children=[\n",
    "        v.Layout(column=True, wrap=True, align_left=True, children=[\n",
    "            v.Card(xs12=True, lg6=True, x14=True, children=[\n",
    "                v.CardTitle(primary_title=True, class_='headline', children=[\"Burn Rates\"]),\n",
    "                v.CardSubtitle(children=[\"Per Capita Resource Demand\"]),\n",
    "                wa_burn_sheet, burn_chart\n",
    "            ])\n",
    "        ])\n",
    "    ]),\n",
    "    v.TabItem(children=[\n",
    "        v.Layout(column=True, wrap=True, align_left=True, children=[\n",
    "            v.Card(xs12=True, lg6=True, x14=True, children=[\n",
    "                v.CardTitle(primary_title=True, class_='headline', children=[\"First Responders/Public Safety\"]),\n",
    "                v.CardSubtitle(children=[\"Population Breakdown\"]),\n",
    "                gr_pop,\n",
    "            ])\n",
    "        ])\n",
    "    ]),\n",
    "    v.TabItem(children=[\n",
    "        v.Layout(column=True, wrap=True, align_left=True, children=[\n",
    "            v.Card(xs12=True, lg6=True, x14=True, children=[\n",
    "                v.CardTitle(primary_title=True, class_='headline', children=[\"Healthcare - Broad\"]),\n",
    "                v.CardSubtitle(children=[\"Population Breakdown\"]),\n",
    "                pop,\n",
    "            ])\n",
    "        ])\n",
    "    ]),\n",
    "])"
   ]
  }
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