Alaska-Oct9-READONLY.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import pathlib\n",
    "import restart\n",
    "\n",
    "# need this ugly variable for now to directly access config\n",
    "PATH = pathlib.Path(restart.__file__).parent.absolute()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from restart import RestartModel\n",
    "from restart import Data\n",
    "from restart.util import set_config, to_df, to_sheet, display_population, format_population, format_cells\n",
    "import ipywidgets as widgets\n",
    "import bqplot\n",
    "from bqplot import pyplot as plt\n",
    "\n",
    "restart = RestartModel(population='oes', state='Alaska')\n",
    "model = restart.model\n",
    "chart_colors = [\"#77AADD\", \"#99DDFF\", \"#44BB99\", \"#BBCC33\", \"#AAAA00\", \"#EEDD88\",\n",
    "                \"#EE8866\", \"#FFAABB\", \"#DDDDDD\", \"#000000\"]\n",
    "\n",
    "def generate_pie_chart(df, title=\"\", show_decimal=False):\n",
    "    fig=plt.figure(title=title)\n",
    "    \n",
    "    pie_chart = plt.pie(sizes=df.values.tolist(),\n",
    "                        labels=df.index.values.tolist(),\n",
    "                        display_labels=\"outside\",\n",
    "                        colors=chart_colors[:df.index.values.size],\n",
    "                        display_values=True)\n",
    "    if not show_decimal:\n",
    "        pie_chart.values_format = \"0\"\n",
    "    return fig\n",
    "\n",
    "def generate_bar(df, title=\"\", scientific_notation=False, small_xlabel=False):\n",
    "    fig = plt.figure(title=title)\n",
    "    x_vals = df.index.values.tolist()\n",
    "    if len(x_vals) > 5:\n",
    "        small_xlabel=True\n",
    "    x_titles = []\n",
    "    for val in x_vals:\n",
    "        if len(val.split(' ')) < 3:\n",
    "            x_titles.append(val)\n",
    "        else:\n",
    "            x_titles.append(\" \".join(val.split(' ')[:2]))\n",
    "    bar_chart = plt.bar(x=x_titles,\n",
    "                        y=df,\n",
    "                        colors=chart_colors[:df.index.values.size])\n",
    "    if small_xlabel:\n",
    "        fig.axes[0].tick_style = {\"font-size\": \"6\"}\n",
    "    if not scientific_notation:\n",
    "        fig.axes[1].tick_format = \".1f\"\n",
    "    return fig\n",
    "\n",
    "def generate_group_bar(df, title=\"\", scientific_notation=False):\n",
    "    fig = plt.figure(title=title)\n",
    "    bar_chart = plt.bar(x=df.columns.values.tolist(),\n",
    "                        y=df,\n",
    "                        labels=df.index.values.tolist(),\n",
    "                        display_legend=False,\n",
    "                        type=\"grouped\",\n",
    "                        colors=chart_colors[:df.index.values.size])\n",
    "    if df.columns.name:\n",
    "        plt.xlabel(df.columns.name.rsplit(\" \", 1)[0])\n",
    "    plt.ylim(0, np.amax(df.values))\n",
    "    if not scientific_notation:\n",
    "        fig.axes[1].tick_format = \".1f\"\n",
    "    return fig\n",
    "\n",
    "def generate_scatter(df, title=\"\", scientific_notation=False, small_xlabel=True):\n",
    "    fig = plt.figure(title=title)\n",
    "    x_vals = df.index.values.tolist()\n",
    "    if len(x_vals) > 5:\n",
    "        small_xlabel=True\n",
    "    x_titles = []\n",
    "    for val in x_vals:\n",
    "        if len(val.split(' ')) < 3:\n",
    "            x_titles.append(val)\n",
    "        else:\n",
    "            x_titles.append(\" \".join(val.split(' ')[:2]))\n",
    "    scatter = plt.scatter(x=x_titles, y=df)\n",
    "    \n",
    "    if small_xlabel:\n",
    "        fig.axes[0].tick_style = {\"font-size\": \"6\"}\n",
    "    if not scientific_notation:\n",
    "        fig.axes[1].tick_format = \".1f\"\n",
    "    return fig\n",
    "    \n",
    "def generate_stacked_bar(df, title=\"\", scientific_notation=False):\n",
    "    fig = plt.figure(title=title)\n",
    "    \n",
    "    bar_chart = plt.bar(x=df.columns.values.tolist(),\n",
    "                        y=df,\n",
    "                        labels=df.index.values.tolist(),\n",
    "                        display_legend=False,\n",
    "                        type=\"stacked\",\n",
    "                        colors=chart_colors[:df.index.values.size])\n",
    "    if df.columns.name:\n",
    "        plt.xlabel(df.columns.name.rsplit(\" \", 1)[0])\n",
    "    plt.ylim(0, np.amax(df.values))\n",
    "    if not scientific_notation:\n",
    "        fig.axes[1].tick_format = \".1f\"\n",
    "    return fig\n",
    "\n",
    "def generate_separate_bar_list(df, scientific_notation=False, small_xlabel=False): # returns list, NOT widget\n",
    "    bar_list = []\n",
    "    for col in df.columns: # .values.tolist()\n",
    "        bar_list.append(generate_bar(df[col][df[col] != 0], title=col, scientific_notation=scientific_notation, small_xlabel=small_xlabel))\n",
    "    return bar_list\n",
    "\n",
    "def generate_separate_scatter_list(df, scientific_notation=False, small_xlabel=False): # returns list, NOT widget\n",
    "    scatter_list = []\n",
    "    for col in df.columns: # .values.tolist()\n",
    "        scatter_list.append(generate_scatter(df[col][df[col] != 0], title=col, scientific_notation=scientific_notation, small_xlabel=small_xlabel))\n",
    "    return scatter_list\n",
    "\n",
    "def generate_html_legend(df, colors=chart_colors, table=True, font_size=13):\n",
    "    name = df.index.name.rsplit(\" \", 1)[0]\n",
    "    html_string = f\"<div style='font-size:{font_size}px; font-family:helvetica'><b style='font-weight:bold'>{name}</b>\"\n",
    "    indices = df.index.values\n",
    "    if table:\n",
    "        html_string += \"<table><tr>\"\n",
    "        for i in range(0, indices.size):\n",
    "            if i % 2 == 0:\n",
    "                index_num = int(i / 2)\n",
    "            else:\n",
    "                index_num = int(i / 2 + indices.size / 2)\n",
    "            html_string += f\"<td style='padding:0 5px'><span style='color:{colors[index_num]}'>█</span> {indices[index_num]}</td>\"\n",
    "            if i % 2 != 0:\n",
    "                html_string += \"</tr><tr>\"\n",
    "        html_string += \"</tr></table>\"\n",
    "    else:\n",
    "        for_count = 0\n",
    "        for string in indices:\n",
    "            if for_count == 0:\n",
    "                html_string += \"<br>\"\n",
    "            else:\n",
    "                html_string += \"&emsp;\"\n",
    "            html_string += f\"<span style='color:{colors[for_count]}'>█</span> {string}\"\n",
    "            for_count += 1\n",
    "    html_string += \"</div>\"\n",
    "    return widgets.HTML(html_string)\n",
    "\n",
    "def generate_group_bar_legend(df, title=\"\", scientific_notation=False, legend_table=True):\n",
    "    chart = generate_group_bar(df, title=title, scientific_notation=scientific_notation)\n",
    "    legend = generate_html_legend(df, table=legend_table)\n",
    "    return widgets.VBox([chart, legend])\n",
    "\n",
    "def generate_stacked_bar_legend(df, title=\"\", scientific_notation=False, legend_table=True):\n",
    "    chart = generate_stacked_bar(df, title=title, scientific_notation=scientific_notation)\n",
    "    legend = generate_html_legend(df, table=legend_table)\n",
    "    return widgets.VBox([chart, legend])\n",
    "\n",
    "burn_sheet = format_population(to_sheet(model.demand.demand_per_unit_map_dn_um.df))\n",
    "burn_chart = generate_group_bar_legend(model.demand.demand_per_unit_map_dn_um.df)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "import sys\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "from restart import RestartModel\n",
    "from restart import Data\n",
    "from restart.util import set_config, to_df, to_sheet, display_population, format_population, format_cells\n",
    "import ipywidgets as widgets\n",
    "import bqplot\n",
    "from bqplot import pyplot as plt\n",
    "\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 = 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",
    "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",
    "out = widgets.interactive_output(dashboard, {'backstop': slider})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def dashboard_h(backstop):\n",
    "    set_stock_h(backstop)\n",
    "    \n",
    "def set_stock_h(backstop):\n",
    "    backstop = [backstop]\n",
    "    model_health.inventory.order(model_health.inventory.inv_by_popsum1_total_rp1n_tc)\n",
    "    model_health.inventory.set_min_in_periods(backstop)\n",
    "    display_stock(model_health.inventory.inv_by_popsum1_total_rp1n_tc.df)\n",
    "    \n",
    "restart_health = RestartModel(population='oes', state='Alaska', subpop='healthcare')\n",
    "model_health = restart_health.model\n",
    "pop_health = format_population(to_sheet(model_health.population.population_pP_tr.df))\n",
    "\n",
    "model_health.inventory.set_average_orders_per_period(model_health.demand.demand_by_popsum1_total_rp1n_tc)\n",
    "\n",
    "slider_health = widgets.IntSlider(min=1, max=120, value=30, description = \"Days\", continuous_update=False)\n",
    "out_health = widgets.interactive_output(dashboard_h, {'backstop': slider_health})"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "def dashboard_fr(backstop):\n",
    "    set_stock_fr(backstop)\n",
    "    \n",
    "def set_stock_fr(backstop):\n",
    "    backstop = [backstop]\n",
    "    model_fr.inventory.order(model_fr.inventory.inv_by_popsum1_total_rp1n_tc)\n",
    "    model_fr.inventory.set_min_in_periods(backstop)\n",
    "    display_stock(model_fr.inventory.inv_by_popsum1_total_rp1n_tc.df)\n",
    "    \n",
    "restart_fr = RestartModel(population='oes', state='Alaska', subpop='wa_tier2_opt2')\n",
    "model_fr = restart_fr.model\n",
    "pop_fr = format_population(to_sheet(model_fr.population.population_pP_tr.df))\n",
    "\n",
    "model_fr.inventory.set_average_orders_per_period(model_fr.demand.demand_by_popsum1_total_rp1n_tc)\n",
    "\n",
    "slider_fr = widgets.IntSlider(min=1, max=120, value=30, description = \"Days\", continuous_update=False)\n",
    "out_fr = widgets.interactive_output(dashboard_fr, {'backstop': slider_fr})"
   ]
  },
  {
   "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=['General Population']),\n",
    "    v.Tab(children=['Healthcare Population']),\n",
    "    v.Tab(children=['Outpatient/First Responders']),\n",
    "    v.Tab(children=['Burn Rates']),\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 PPE Projections\"]),\n",
    "                v.CardText(children=[\n",
    "                    \"Analysis for general population\"\n",
    "                ]),\n",
    "                slider, out,\n",
    "                v.CardText(children=[\n",
    "                    \"Analysis for healthcare workers\"\n",
    "                ]),\n",
    "                slider_health, out_health,\n",
    "                v.CardText(children=[\n",
    "                    \"Analysis for outpatient healthcare workers and first responders\"\n",
    "                ]),\n",
    "                slider_fr, out_fr\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=[\"BLS P\"]),\n",
    "                v.CardText(children=[\n",
    "                    \"All OES codes in the state of Alaska\"\n",
    "                ]),\n",
    "                pop\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=[\"BLS Population with High Granularity\"]),\n",
    "                v.CardText(children=[\n",
    "                    \"OES codes filtered for healthcare workers\"\n",
    "                ]),\n",
    "                pop_health\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=[\"BLS Population with High Granularity\"]),\n",
    "                v.CardText(children=[\n",
    "                    \"OES codes filtered for outpatient healthcare providers and first responders\"\n",
    "                ]),\n",
    "                pop_fr,\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 Assumptions\"]),\n",
    "                burn_sheet,\n",
    "                burn_chart,\n",
    "            ])\n",
    "        ])\n",
    "    ])\n",
    "])"
   ]
  }
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