Covid_Math_Modeling.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "1448f7e5",
   "metadata": {},
   "source": [
    "# Mathematical Modeling of AZ Covid Data\n",
    "\n",
    "In this notebook, we organize and visualize Covid-19 hospitalization data for the state of Arizona, and then attmept to model the first 160 days using a dynamical system. If you would like to follow along with this notebook, you can download the data from [HealthData.gov](https://healthdata.gov/Hospital/COVID-19-Reported-Patient-Impact-and-Hospital-Capa/g62h-syeh)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "id": "036cc5cb",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>state</th>\n",
       "      <th>date</th>\n",
       "      <th>critical_staffing_shortage_today_yes</th>\n",
       "      <th>critical_staffing_shortage_today_no</th>\n",
       "      <th>critical_staffing_shortage_today_not_reported</th>\n",
       "      <th>critical_staffing_shortage_anticipated_within_week_yes</th>\n",
       "      <th>critical_staffing_shortage_anticipated_within_week_no</th>\n",
       "      <th>critical_staffing_shortage_anticipated_within_week_not_reported</th>\n",
       "      <th>hospital_onset_covid</th>\n",
       "      <th>hospital_onset_covid_coverage</th>\n",
       "      <th>...</th>\n",
       "      <th>previous_day_admission_pediatric_covid_confirmed_5_11</th>\n",
       "      <th>previous_day_admission_pediatric_covid_confirmed_5_11_coverage</th>\n",
       "      <th>previous_day_admission_pediatric_covid_confirmed_unknown</th>\n",
       "      <th>previous_day_admission_pediatric_covid_confirmed_unknown_coverage</th>\n",
       "      <th>staffed_icu_pediatric_patients_confirmed_covid</th>\n",
       "      <th>staffed_icu_pediatric_patients_confirmed_covid_coverage</th>\n",
       "      <th>staffed_pediatric_icu_bed_occupancy</th>\n",
       "      <th>staffed_pediatric_icu_bed_occupancy_coverage</th>\n",
       "      <th>total_staffed_pediatric_icu_beds</th>\n",
       "      <th>total_staffed_pediatric_icu_beds_coverage</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>RI</td>\n",
       "      <td>2021-02-13</td>\n",
       "      <td>4</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>4</td>\n",
       "      <td>10</td>\n",
       "      <td>1</td>\n",
       "      <td>5.0</td>\n",
       "      <td>14</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>74.0</td>\n",
       "      <td>14</td>\n",
       "      <td>80.0</td>\n",
       "      <td>14</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>AK</td>\n",
       "      <td>2021-02-05</td>\n",
       "      <td>1</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>1</td>\n",
       "      <td>23</td>\n",
       "      <td>0</td>\n",
       "      <td>0.0</td>\n",
       "      <td>24</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>57.0</td>\n",
       "      <td>24</td>\n",
       "      <td>74.0</td>\n",
       "      <td>24</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>MA</td>\n",
       "      <td>2021-02-02</td>\n",
       "      <td>8</td>\n",
       "      <td>70</td>\n",
       "      <td>1</td>\n",
       "      <td>7</td>\n",
       "      <td>71</td>\n",
       "      <td>1</td>\n",
       "      <td>58.0</td>\n",
       "      <td>78</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>KS</td>\n",
       "      <td>2021-01-26</td>\n",
       "      <td>10</td>\n",
       "      <td>128</td>\n",
       "      <td>3</td>\n",
       "      <td>16</td>\n",
       "      <td>122</td>\n",
       "      <td>3</td>\n",
       "      <td>3.0</td>\n",
       "      <td>138</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>38.0</td>\n",
       "      <td>138</td>\n",
       "      <td>219.0</td>\n",
       "      <td>138</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>MD</td>\n",
       "      <td>2021-01-20</td>\n",
       "      <td>2</td>\n",
       "      <td>56</td>\n",
       "      <td>1</td>\n",
       "      <td>2</td>\n",
       "      <td>56</td>\n",
       "      <td>1</td>\n",
       "      <td>30.0</td>\n",
       "      <td>58</td>\n",
       "      <td>...</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>NaN</td>\n",
       "      <td>0</td>\n",
       "      <td>164.0</td>\n",
       "      <td>58</td>\n",
       "      <td>241.0</td>\n",
       "      <td>58</td>\n",
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       "<p>5 rows × 135 columns</p>\n",
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      "text/plain": [
       "  state       date  critical_staffing_shortage_today_yes  \\\n",
       "0    RI 2021-02-13                                     4   \n",
       "1    AK 2021-02-05                                     1   \n",
       "2    MA 2021-02-02                                     8   \n",
       "3    KS 2021-01-26                                    10   \n",
       "4    MD 2021-01-20                                     2   \n",
       "\n",
       "   critical_staffing_shortage_today_no  \\\n",
       "0                                   10   \n",
       "1                                   23   \n",
       "2                                   70   \n",
       "3                                  128   \n",
       "4                                   56   \n",
       "\n",
       "   critical_staffing_shortage_today_not_reported  \\\n",
       "0                                              1   \n",
       "1                                              0   \n",
       "2                                              1   \n",
       "3                                              3   \n",
       "4                                              1   \n",
       "\n",
       "   critical_staffing_shortage_anticipated_within_week_yes  \\\n",
       "0                                                  4        \n",
       "1                                                  1        \n",
       "2                                                  7        \n",
       "3                                                 16        \n",
       "4                                                  2        \n",
       "\n",
       "   critical_staffing_shortage_anticipated_within_week_no  \\\n",
       "0                                                 10       \n",
       "1                                                 23       \n",
       "2                                                 71       \n",
       "3                                                122       \n",
       "4                                                 56       \n",
       "\n",
       "   critical_staffing_shortage_anticipated_within_week_not_reported  \\\n",
       "0                                                  1                 \n",
       "1                                                  0                 \n",
       "2                                                  1                 \n",
       "3                                                  3                 \n",
       "4                                                  1                 \n",
       "\n",
       "   hospital_onset_covid  hospital_onset_covid_coverage  ...  \\\n",
       "0                   5.0                             14  ...   \n",
       "1                   0.0                             24  ...   \n",
       "2                  58.0                             78  ...   \n",
       "3                   3.0                            138  ...   \n",
       "4                  30.0                             58  ...   \n",
       "\n",
       "   previous_day_admission_pediatric_covid_confirmed_5_11  \\\n",
       "0                                                NaN       \n",
       "1                                                NaN       \n",
       "2                                                NaN       \n",
       "3                                                NaN       \n",
       "4                                                NaN       \n",
       "\n",
       "   previous_day_admission_pediatric_covid_confirmed_5_11_coverage  \\\n",
       "0                                                  0                \n",
       "1                                                  0                \n",
       "2                                                  0                \n",
       "3                                                  0                \n",
       "4                                                  0                \n",
       "\n",
       "   previous_day_admission_pediatric_covid_confirmed_unknown  \\\n",
       "0                                                NaN          \n",
       "1                                                NaN          \n",
       "2                                                NaN          \n",
       "3                                                NaN          \n",
       "4                                                NaN          \n",
       "\n",
       "   previous_day_admission_pediatric_covid_confirmed_unknown_coverage  \\\n",
       "0                                                  0                   \n",
       "1                                                  0                   \n",
       "2                                                  0                   \n",
       "3                                                  0                   \n",
       "4                                                  0                   \n",
       "\n",
       "   staffed_icu_pediatric_patients_confirmed_covid  \\\n",
       "0                                             NaN   \n",
       "1                                             NaN   \n",
       "2                                             NaN   \n",
       "3                                             NaN   \n",
       "4                                             NaN   \n",
       "\n",
       "   staffed_icu_pediatric_patients_confirmed_covid_coverage  \\\n",
       "0                                                  0         \n",
       "1                                                  0         \n",
       "2                                                  0         \n",
       "3                                                  0         \n",
       "4                                                  0         \n",
       "\n",
       "   staffed_pediatric_icu_bed_occupancy  \\\n",
       "0                                 74.0   \n",
       "1                                 57.0   \n",
       "2                                  NaN   \n",
       "3                                 38.0   \n",
       "4                                164.0   \n",
       "\n",
       "   staffed_pediatric_icu_bed_occupancy_coverage  \\\n",
       "0                                            14   \n",
       "1                                            24   \n",
       "2                                             0   \n",
       "3                                           138   \n",
       "4                                            58   \n",
       "\n",
       "   total_staffed_pediatric_icu_beds  total_staffed_pediatric_icu_beds_coverage  \n",
       "0                              80.0                                         14  \n",
       "1                              74.0                                         24  \n",
       "2                               NaN                                          0  \n",
       "3                             219.0                                        138  \n",
       "4                             241.0                                         58  \n",
       "\n",
       "[5 rows x 135 columns]"
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#Import the necessary packages to visualize our data\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "#Load the data from csv file into a pandas dataframe\n",
    "covid_pd = pd.read_csv('Covid-19.csv', parse_dates = ['date'])\n",
    "\n",
    "#Visualize the first few rows of our dataframe\n",
    "covid_pd.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "id": "86b9b2e8",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Focus on hospitalizations using inpatient_beds_used_covid column\n",
    "covid_pd = covid_pd[['state','date','inpatient_beds_used_covid']]\n",
    "#Rename column\n",
    "covid_pd.rename({'inpatient_beds_used_covid':'Hospitalizations'}, axis = 1, inplace = True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "id": "696796ba",
   "metadata": {},
   "outputs": [
    {
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       "      <th></th>\n",
       "      <th>state</th>\n",
       "      <th>date</th>\n",
       "      <th>Hospitalizations</th>\n",
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       "    <tr>\n",
       "      <th>20720</th>\n",
       "      <td>AZ</td>\n",
       "      <td>2020-03-02</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>14351</th>\n",
       "      <td>AZ</td>\n",
       "      <td>2020-03-03</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>19060</th>\n",
       "      <td>AZ</td>\n",
       "      <td>2020-03-04</td>\n",
       "      <td>0.0</td>\n",
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       "    <tr>\n",
       "      <th>17686</th>\n",
       "      <td>AZ</td>\n",
       "      <td>2020-03-05</td>\n",
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       "      <th>17615</th>\n",
       "      <td>AZ</td>\n",
       "      <td>2020-03-06</td>\n",
       "      <td>0.0</td>\n",
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      "text/plain": [
       "      state       date  Hospitalizations\n",
       "20720    AZ 2020-03-02               0.0\n",
       "14351    AZ 2020-03-03               0.0\n",
       "19060    AZ 2020-03-04               0.0\n",
       "17686    AZ 2020-03-05               0.0\n",
       "17615    AZ 2020-03-06               0.0"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "covid_pd = covid_pd[covid_pd['state'] == 'AZ'] # Extract data for Arizona\n",
    "covid_pd = covid_pd.sort_values('date') #Order based on date\n",
    "#Re-visualize table\n",
    "covid_pd.head()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "id": "30d13249",
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>state</th>\n",
       "      <th>date</th>\n",
       "      <th>Hospitalizations</th>\n",
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       "      <th>1</th>\n",
       "      <td>AZ</td>\n",
       "      <td>2020-03-03</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>AZ</td>\n",
       "      <td>2020-03-04</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>AZ</td>\n",
       "      <td>2020-03-05</td>\n",
       "      <td>0.0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>AZ</td>\n",
       "      <td>2020-03-06</td>\n",
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      "text/plain": [
       "  state       date  Hospitalizations\n",
       "0    AZ 2020-03-02               0.0\n",
       "1    AZ 2020-03-03               0.0\n",
       "2    AZ 2020-03-04               0.0\n",
       "3    AZ 2020-03-05               0.0\n",
       "4    AZ 2020-03-06               0.0"
      ]
     },
     "execution_count": 45,
     "metadata": {},
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    }
   ],
   "source": [
    "#Let's reset the index for this new sorted dataframe\n",
    "covid_pd.reset_index(drop=True, inplace=True)\n",
    "covid_pd.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "id": "f983ef66",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Plot covid data\n",
    "plt.plot(covid_pd['date'], covid_pd['Hospitalizations'])\n",
    "plt.xlabel('Date')\n",
    "plt.ylabel('Number of Hospitalizations')\n",
    "plt.title('AZ Covid Hospitalizations (2020 - 2023)')\n",
    "plt.tick_params(axis='x', labelrotation = 45) # rotate X-lables to avoid overlap\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b25cc921",
   "metadata": {},
   "source": [
    "Now let's see if we can use a system of differential equations to model the first major spike in hospitalizations. First, we'll edit our dataframe to only include dates up to 09/2020"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "id": "ea5edb43",
   "metadata": {},
   "outputs": [],
   "source": [
    "covid_pd = covid_pd[covid_pd['date']<'2020-08-30']\n",
    "plt.plot(covid_pd['date'], covid_pd['Hospitalizations'])\n",
    "plt.xlabel('Date')\n",
    "plt.ylabel('Number of Hospitalizations')\n",
    "plt.title('AZ Covid Hospitalizations (2020 - 2023)')\n",
    "plt.tick_params(axis='x', labelrotation = 45) # rotate X-lables to avoid overlap\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "219c8728",
   "metadata": {},
   "source": [
    "To approximate this data, we will use the SIHR model:\n",
    "\\begin{align*}\n",
    "\\frac{dS}{dt} & = -\\frac{\\beta S I}{N} \\\\\n",
    "\\frac{dI}{dt} & = \\frac{\\beta S I}{N} - \\gamma I \\\\\n",
    "\\frac{dH}{dt} & =  \\gamma  f I - c  H \\\\\n",
    "\\frac{dR}{dt} & = \\gamma (1-f) I + c  H\n",
    "\\end{align*}\n",
    "In this model, infected people are progressed to the next stage H (hospitalization) or R (recovered) with the progression rate $\\gamma$. Among these people, about $f=1\\%$ of them developed severe symtoms and were hospitalized in early 2020. For those hospitalized, the daily recover rate was approximately $c=0.17$. \n",
    "\n",
    "Our aim is to find the infection rate, $\\beta$ and progression rate $\\gamma$ manually to fit the data. In order to do this, we will create sliders to vary these two parameters"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "id": "ceb51826",
   "metadata": {},
   "outputs": [],
   "source": [
    "#Import package to solve the system of differential equations\n",
    "from scipy.integrate import odeint\n",
    "\n",
    "#Create our Model\n",
    "\n",
    "# Arizona Population from google search\n",
    "N = 7.276 *(10**6)\n",
    "# Initial number of infected and recovered individuals, I0 and R0.\n",
    "I0, R0 = 1, 0\n",
    "#Initial number of hospitalized individuals H0\n",
    "H0 = 0\n",
    "# Everyone else, S0, is susceptible to infection initially.\n",
    "S0 = N - I0 - R0 - H0\n",
    "# Contact rate, beta, and mean recovery rate, gamma, (in 1/days).\n",
    "beta, gamma = .175, .05\n",
    "\n",
    "#Add in parameters f and c, percent hospitalization and recovery rate (1/day)\n",
    "f,c = 0.01, 0.17\n",
    "# A grid of time points (in days)\n",
    "t = np.linspace(0, 181, 181)\n",
    "\n",
    "# The SIR model differential equations.\n",
    "def deriv(y, t, N, beta, gamma,f,c):\n",
    "    S, I, H, R = y\n",
    "    dSdt = -beta * S * I / N\n",
    "    dIdt = beta * S * I / N - gamma * I\n",
    "    dHdt = gamma*f*I-c*H\n",
    "    dRdt = gamma * (1-f)*I + c*H\n",
    "    return dSdt, dIdt, dHdt, dRdt\n",
    "\n",
    "# Initial conditions vector\n",
    "y0 = S0, I0, H0, R0\n",
    "# Integrate the SIHR equations over the time grid, t.\n",
    "ret = odeint(deriv, y0, t, args=(N, beta, gamma,f,c))\n",
    "S, I, H, R = ret.T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "id": "669d8ff1",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/javascript": [
       "/* Put everything inside the global mpl namespace */\n",
       "/* global mpl */\n",
       "window.mpl = {};\n",
       "\n",
       "mpl.get_websocket_type = function () {\n",
       "    if (typeof WebSocket !== 'undefined') {\n",
       "        return WebSocket;\n",
       "    } else if (typeof MozWebSocket !== 'undefined') {\n",
       "        return MozWebSocket;\n",
       "    } else {\n",
       "        alert(\n",
       "            'Your browser does not have WebSocket support. ' +\n",
       "                'Please try Chrome, Safari or Firefox ≥ 6. ' +\n",
       "                'Firefox 4 and 5 are also supported but you ' +\n",
       "                'have to enable WebSockets in about:config.'\n",
       "        );\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure = function (figure_id, websocket, ondownload, parent_element) {\n",
       "    this.id = figure_id;\n",
       "\n",
       "    this.ws = websocket;\n",
       "\n",
       "    this.supports_binary = this.ws.binaryType !== undefined;\n",
       "\n",
       "    if (!this.supports_binary) {\n",
       "        var warnings = document.getElementById('mpl-warnings');\n",
       "        if (warnings) {\n",
       "            warnings.style.display = 'block';\n",
       "            warnings.textContent =\n",
       "                'This browser does not support binary websocket messages. ' +\n",
       "                'Performance may be slow.';\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.imageObj = new Image();\n",
       "\n",
       "    this.context = undefined;\n",
       "    this.message = undefined;\n",
       "    this.canvas = undefined;\n",
       "    this.rubberband_canvas = undefined;\n",
       "    this.rubberband_context = undefined;\n",
       "    this.format_dropdown = undefined;\n",
       "\n",
       "    this.image_mode = 'full';\n",
       "\n",
       "    this.root = document.createElement('div');\n",
       "    this.root.setAttribute('style', 'display: inline-block');\n",
       "    this._root_extra_style(this.root);\n",
       "\n",
       "    parent_element.appendChild(this.root);\n",
       "\n",
       "    this._init_header(this);\n",
       "    this._init_canvas(this);\n",
       "    this._init_toolbar(this);\n",
       "\n",
       "    var fig = this;\n",
       "\n",
       "    this.waiting = false;\n",
       "\n",
       "    this.ws.onopen = function () {\n",
       "        fig.send_message('supports_binary', { value: fig.supports_binary });\n",
       "        fig.send_message('send_image_mode', {});\n",
       "        if (fig.ratio !== 1) {\n",
       "            fig.send_message('set_device_pixel_ratio', {\n",
       "                device_pixel_ratio: fig.ratio,\n",
       "            });\n",
       "        }\n",
       "        fig.send_message('refresh', {});\n",
       "    };\n",
       "\n",
       "    this.imageObj.onload = function () {\n",
       "        if (fig.image_mode === 'full') {\n",
       "            // Full images could contain transparency (where diff images\n",
       "            // almost always do), so we need to clear the canvas so that\n",
       "            // there is no ghosting.\n",
       "            fig.context.clearRect(0, 0, fig.canvas.width, fig.canvas.height);\n",
       "        }\n",
       "        fig.context.drawImage(fig.imageObj, 0, 0);\n",
       "    };\n",
       "\n",
       "    this.imageObj.onunload = function () {\n",
       "        fig.ws.close();\n",
       "    };\n",
       "\n",
       "    this.ws.onmessage = this._make_on_message_function(this);\n",
       "\n",
       "    this.ondownload = ondownload;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_header = function () {\n",
       "    var titlebar = document.createElement('div');\n",
       "    titlebar.classList =\n",
       "        'ui-dialog-titlebar ui-widget-header ui-corner-all ui-helper-clearfix';\n",
       "    var titletext = document.createElement('div');\n",
       "    titletext.classList = 'ui-dialog-title';\n",
       "    titletext.setAttribute(\n",
       "        'style',\n",
       "        'width: 100%; text-align: center; padding: 3px;'\n",
       "    );\n",
       "    titlebar.appendChild(titletext);\n",
       "    this.root.appendChild(titlebar);\n",
       "    this.header = titletext;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (_canvas_div) {};\n",
       "\n",
       "mpl.figure.prototype._init_canvas = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var canvas_div = (this.canvas_div = document.createElement('div'));\n",
       "    canvas_div.setAttribute(\n",
       "        'style',\n",
       "        'border: 1px solid #ddd;' +\n",
       "            'box-sizing: content-box;' +\n",
       "            'clear: both;' +\n",
       "            'min-height: 1px;' +\n",
       "            'min-width: 1px;' +\n",
       "            'outline: 0;' +\n",
       "            'overflow: hidden;' +\n",
       "            'position: relative;' +\n",
       "            'resize: both;'\n",
       "    );\n",
       "\n",
       "    function on_keyboard_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.key_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    canvas_div.addEventListener(\n",
       "        'keydown',\n",
       "        on_keyboard_event_closure('key_press')\n",
       "    );\n",
       "    canvas_div.addEventListener(\n",
       "        'keyup',\n",
       "        on_keyboard_event_closure('key_release')\n",
       "    );\n",
       "\n",
       "    this._canvas_extra_style(canvas_div);\n",
       "    this.root.appendChild(canvas_div);\n",
       "\n",
       "    var canvas = (this.canvas = document.createElement('canvas'));\n",
       "    canvas.classList.add('mpl-canvas');\n",
       "    canvas.setAttribute('style', 'box-sizing: content-box;');\n",
       "\n",
       "    this.context = canvas.getContext('2d');\n",
       "\n",
       "    var backingStore =\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        this.context.webkitBackingStorePixelRatio ||\n",
       "        this.context.mozBackingStorePixelRatio ||\n",
       "        this.context.msBackingStorePixelRatio ||\n",
       "        this.context.oBackingStorePixelRatio ||\n",
       "        this.context.backingStorePixelRatio ||\n",
       "        1;\n",
       "\n",
       "    this.ratio = (window.devicePixelRatio || 1) / backingStore;\n",
       "\n",
       "    var rubberband_canvas = (this.rubberband_canvas = document.createElement(\n",
       "        'canvas'\n",
       "    ));\n",
       "    rubberband_canvas.setAttribute(\n",
       "        'style',\n",
       "        'box-sizing: content-box; position: absolute; left: 0; top: 0; z-index: 1;'\n",
       "    );\n",
       "\n",
       "    // Apply a ponyfill if ResizeObserver is not implemented by browser.\n",
       "    if (this.ResizeObserver === undefined) {\n",
       "        if (window.ResizeObserver !== undefined) {\n",
       "            this.ResizeObserver = window.ResizeObserver;\n",
       "        } else {\n",
       "            var obs = _JSXTOOLS_RESIZE_OBSERVER({});\n",
       "            this.ResizeObserver = obs.ResizeObserver;\n",
       "        }\n",
       "    }\n",
       "\n",
       "    this.resizeObserverInstance = new this.ResizeObserver(function (entries) {\n",
       "        var nentries = entries.length;\n",
       "        for (var i = 0; i < nentries; i++) {\n",
       "            var entry = entries[i];\n",
       "            var width, height;\n",
       "            if (entry.contentBoxSize) {\n",
       "                if (entry.contentBoxSize instanceof Array) {\n",
       "                    // Chrome 84 implements new version of spec.\n",
       "                    width = entry.contentBoxSize[0].inlineSize;\n",
       "                    height = entry.contentBoxSize[0].blockSize;\n",
       "                } else {\n",
       "                    // Firefox implements old version of spec.\n",
       "                    width = entry.contentBoxSize.inlineSize;\n",
       "                    height = entry.contentBoxSize.blockSize;\n",
       "                }\n",
       "            } else {\n",
       "                // Chrome <84 implements even older version of spec.\n",
       "                width = entry.contentRect.width;\n",
       "                height = entry.contentRect.height;\n",
       "            }\n",
       "\n",
       "            // Keep the size of the canvas and rubber band canvas in sync with\n",
       "            // the canvas container.\n",
       "            if (entry.devicePixelContentBoxSize) {\n",
       "                // Chrome 84 implements new version of spec.\n",
       "                canvas.setAttribute(\n",
       "                    'width',\n",
       "                    entry.devicePixelContentBoxSize[0].inlineSize\n",
       "                );\n",
       "                canvas.setAttribute(\n",
       "                    'height',\n",
       "                    entry.devicePixelContentBoxSize[0].blockSize\n",
       "                );\n",
       "            } else {\n",
       "                canvas.setAttribute('width', width * fig.ratio);\n",
       "                canvas.setAttribute('height', height * fig.ratio);\n",
       "            }\n",
       "            canvas.setAttribute(\n",
       "                'style',\n",
       "                'width: ' + width + 'px; height: ' + height + 'px;'\n",
       "            );\n",
       "\n",
       "            rubberband_canvas.setAttribute('width', width);\n",
       "            rubberband_canvas.setAttribute('height', height);\n",
       "\n",
       "            // And update the size in Python. We ignore the initial 0/0 size\n",
       "            // that occurs as the element is placed into the DOM, which should\n",
       "            // otherwise not happen due to the minimum size styling.\n",
       "            if (fig.ws.readyState == 1 && width != 0 && height != 0) {\n",
       "                fig.request_resize(width, height);\n",
       "            }\n",
       "        }\n",
       "    });\n",
       "    this.resizeObserverInstance.observe(canvas_div);\n",
       "\n",
       "    function on_mouse_event_closure(name) {\n",
       "        return function (event) {\n",
       "            return fig.mouse_event(event, name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousedown',\n",
       "        on_mouse_event_closure('button_press')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseup',\n",
       "        on_mouse_event_closure('button_release')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'dblclick',\n",
       "        on_mouse_event_closure('dblclick')\n",
       "    );\n",
       "    // Throttle sequential mouse events to 1 every 20ms.\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mousemove',\n",
       "        on_mouse_event_closure('motion_notify')\n",
       "    );\n",
       "\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseenter',\n",
       "        on_mouse_event_closure('figure_enter')\n",
       "    );\n",
       "    rubberband_canvas.addEventListener(\n",
       "        'mouseleave',\n",
       "        on_mouse_event_closure('figure_leave')\n",
       "    );\n",
       "\n",
       "    canvas_div.addEventListener('wheel', function (event) {\n",
       "        if (event.deltaY < 0) {\n",
       "            event.step = 1;\n",
       "        } else {\n",
       "            event.step = -1;\n",
       "        }\n",
       "        on_mouse_event_closure('scroll')(event);\n",
       "    });\n",
       "\n",
       "    canvas_div.appendChild(canvas);\n",
       "    canvas_div.appendChild(rubberband_canvas);\n",
       "\n",
       "    this.rubberband_context = rubberband_canvas.getContext('2d');\n",
       "    this.rubberband_context.strokeStyle = '#000000';\n",
       "\n",
       "    this._resize_canvas = function (width, height, forward) {\n",
       "        if (forward) {\n",
       "            canvas_div.style.width = width + 'px';\n",
       "            canvas_div.style.height = height + 'px';\n",
       "        }\n",
       "    };\n",
       "\n",
       "    // Disable right mouse context menu.\n",
       "    this.rubberband_canvas.addEventListener('contextmenu', function (_e) {\n",
       "        event.preventDefault();\n",
       "        return false;\n",
       "    });\n",
       "\n",
       "    function set_focus() {\n",
       "        canvas.focus();\n",
       "        canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    window.setTimeout(set_focus, 100);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'mpl-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'mpl-button-group';\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'mpl-button-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        var button = (fig.buttons[name] = document.createElement('button'));\n",
       "        button.classList = 'mpl-widget';\n",
       "        button.setAttribute('role', 'button');\n",
       "        button.setAttribute('aria-disabled', 'false');\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "\n",
       "        var icon_img = document.createElement('img');\n",
       "        icon_img.src = '_images/' + image + '.png';\n",
       "        icon_img.srcset = '_images/' + image + '_large.png 2x';\n",
       "        icon_img.alt = tooltip;\n",
       "        button.appendChild(icon_img);\n",
       "\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    var fmt_picker = document.createElement('select');\n",
       "    fmt_picker.classList = 'mpl-widget';\n",
       "    toolbar.appendChild(fmt_picker);\n",
       "    this.format_dropdown = fmt_picker;\n",
       "\n",
       "    for (var ind in mpl.extensions) {\n",
       "        var fmt = mpl.extensions[ind];\n",
       "        var option = document.createElement('option');\n",
       "        option.selected = fmt === mpl.default_extension;\n",
       "        option.innerHTML = fmt;\n",
       "        fmt_picker.appendChild(option);\n",
       "    }\n",
       "\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.request_resize = function (x_pixels, y_pixels) {\n",
       "    // Request matplotlib to resize the figure. Matplotlib will then trigger a resize in the client,\n",
       "    // which will in turn request a refresh of the image.\n",
       "    this.send_message('resize', { width: x_pixels, height: y_pixels });\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_message = function (type, properties) {\n",
       "    properties['type'] = type;\n",
       "    properties['figure_id'] = this.id;\n",
       "    this.ws.send(JSON.stringify(properties));\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.send_draw_message = function () {\n",
       "    if (!this.waiting) {\n",
       "        this.waiting = true;\n",
       "        this.ws.send(JSON.stringify({ type: 'draw', figure_id: this.id }));\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    var format_dropdown = fig.format_dropdown;\n",
       "    var format = format_dropdown.options[format_dropdown.selectedIndex].value;\n",
       "    fig.ondownload(fig, format);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_resize = function (fig, msg) {\n",
       "    var size = msg['size'];\n",
       "    if (size[0] !== fig.canvas.width || size[1] !== fig.canvas.height) {\n",
       "        fig._resize_canvas(size[0], size[1], msg['forward']);\n",
       "        fig.send_message('refresh', {});\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_rubberband = function (fig, msg) {\n",
       "    var x0 = msg['x0'] / fig.ratio;\n",
       "    var y0 = (fig.canvas.height - msg['y0']) / fig.ratio;\n",
       "    var x1 = msg['x1'] / fig.ratio;\n",
       "    var y1 = (fig.canvas.height - msg['y1']) / fig.ratio;\n",
       "    x0 = Math.floor(x0) + 0.5;\n",
       "    y0 = Math.floor(y0) + 0.5;\n",
       "    x1 = Math.floor(x1) + 0.5;\n",
       "    y1 = Math.floor(y1) + 0.5;\n",
       "    var min_x = Math.min(x0, x1);\n",
       "    var min_y = Math.min(y0, y1);\n",
       "    var width = Math.abs(x1 - x0);\n",
       "    var height = Math.abs(y1 - y0);\n",
       "\n",
       "    fig.rubberband_context.clearRect(\n",
       "        0,\n",
       "        0,\n",
       "        fig.canvas.width / fig.ratio,\n",
       "        fig.canvas.height / fig.ratio\n",
       "    );\n",
       "\n",
       "    fig.rubberband_context.strokeRect(min_x, min_y, width, height);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_figure_label = function (fig, msg) {\n",
       "    // Updates the figure title.\n",
       "    fig.header.textContent = msg['label'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_cursor = function (fig, msg) {\n",
       "    fig.rubberband_canvas.style.cursor = msg['cursor'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_message = function (fig, msg) {\n",
       "    fig.message.textContent = msg['message'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_draw = function (fig, _msg) {\n",
       "    // Request the server to send over a new figure.\n",
       "    fig.send_draw_message();\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_image_mode = function (fig, msg) {\n",
       "    fig.image_mode = msg['mode'];\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_history_buttons = function (fig, msg) {\n",
       "    for (var key in msg) {\n",
       "        if (!(key in fig.buttons)) {\n",
       "            continue;\n",
       "        }\n",
       "        fig.buttons[key].disabled = !msg[key];\n",
       "        fig.buttons[key].setAttribute('aria-disabled', !msg[key]);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_navigate_mode = function (fig, msg) {\n",
       "    if (msg['mode'] === 'PAN') {\n",
       "        fig.buttons['Pan'].classList.add('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    } else if (msg['mode'] === 'ZOOM') {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.add('active');\n",
       "    } else {\n",
       "        fig.buttons['Pan'].classList.remove('active');\n",
       "        fig.buttons['Zoom'].classList.remove('active');\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Called whenever the canvas gets updated.\n",
       "    this.send_message('ack', {});\n",
       "};\n",
       "\n",
       "// A function to construct a web socket function for onmessage handling.\n",
       "// Called in the figure constructor.\n",
       "mpl.figure.prototype._make_on_message_function = function (fig) {\n",
       "    return function socket_on_message(evt) {\n",
       "        if (evt.data instanceof Blob) {\n",
       "            var img = evt.data;\n",
       "            if (img.type !== 'image/png') {\n",
       "                /* FIXME: We get \"Resource interpreted as Image but\n",
       "                 * transferred with MIME type text/plain:\" errors on\n",
       "                 * Chrome.  But how to set the MIME type?  It doesn't seem\n",
       "                 * to be part of the websocket stream */\n",
       "                img.type = 'image/png';\n",
       "            }\n",
       "\n",
       "            /* Free the memory for the previous frames */\n",
       "            if (fig.imageObj.src) {\n",
       "                (window.URL || window.webkitURL).revokeObjectURL(\n",
       "                    fig.imageObj.src\n",
       "                );\n",
       "            }\n",
       "\n",
       "            fig.imageObj.src = (window.URL || window.webkitURL).createObjectURL(\n",
       "                img\n",
       "            );\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        } else if (\n",
       "            typeof evt.data === 'string' &&\n",
       "            evt.data.slice(0, 21) === 'data:image/png;base64'\n",
       "        ) {\n",
       "            fig.imageObj.src = evt.data;\n",
       "            fig.updated_canvas_event();\n",
       "            fig.waiting = false;\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        var msg = JSON.parse(evt.data);\n",
       "        var msg_type = msg['type'];\n",
       "\n",
       "        // Call the  \"handle_{type}\" callback, which takes\n",
       "        // the figure and JSON message as its only arguments.\n",
       "        try {\n",
       "            var callback = fig['handle_' + msg_type];\n",
       "        } catch (e) {\n",
       "            console.log(\n",
       "                \"No handler for the '\" + msg_type + \"' message type: \",\n",
       "                msg\n",
       "            );\n",
       "            return;\n",
       "        }\n",
       "\n",
       "        if (callback) {\n",
       "            try {\n",
       "                // console.log(\"Handling '\" + msg_type + \"' message: \", msg);\n",
       "                callback(fig, msg);\n",
       "            } catch (e) {\n",
       "                console.log(\n",
       "                    \"Exception inside the 'handler_\" + msg_type + \"' callback:\",\n",
       "                    e,\n",
       "                    e.stack,\n",
       "                    msg\n",
       "                );\n",
       "            }\n",
       "        }\n",
       "    };\n",
       "};\n",
       "\n",
       "// from https://stackoverflow.com/questions/1114465/getting-mouse-location-in-canvas\n",
       "mpl.findpos = function (e) {\n",
       "    //this section is from http://www.quirksmode.org/js/events_properties.html\n",
       "    var targ;\n",
       "    if (!e) {\n",
       "        e = window.event;\n",
       "    }\n",
       "    if (e.target) {\n",
       "        targ = e.target;\n",
       "    } else if (e.srcElement) {\n",
       "        targ = e.srcElement;\n",
       "    }\n",
       "    if (targ.nodeType === 3) {\n",
       "        // defeat Safari bug\n",
       "        targ = targ.parentNode;\n",
       "    }\n",
       "\n",
       "    // pageX,Y are the mouse positions relative to the document\n",
       "    var boundingRect = targ.getBoundingClientRect();\n",
       "    var x = e.pageX - (boundingRect.left + document.body.scrollLeft);\n",
       "    var y = e.pageY - (boundingRect.top + document.body.scrollTop);\n",
       "\n",
       "    return { x: x, y: y };\n",
       "};\n",
       "\n",
       "/*\n",
       " * return a copy of an object with only non-object keys\n",
       " * we need this to avoid circular references\n",
       " * https://stackoverflow.com/a/24161582/3208463\n",
       " */\n",
       "function simpleKeys(original) {\n",
       "    return Object.keys(original).reduce(function (obj, key) {\n",
       "        if (typeof original[key] !== 'object') {\n",
       "            obj[key] = original[key];\n",
       "        }\n",
       "        return obj;\n",
       "    }, {});\n",
       "}\n",
       "\n",
       "mpl.figure.prototype.mouse_event = function (event, name) {\n",
       "    var canvas_pos = mpl.findpos(event);\n",
       "\n",
       "    if (name === 'button_press') {\n",
       "        this.canvas.focus();\n",
       "        this.canvas_div.focus();\n",
       "    }\n",
       "\n",
       "    var x = canvas_pos.x * this.ratio;\n",
       "    var y = canvas_pos.y * this.ratio;\n",
       "\n",
       "    this.send_message(name, {\n",
       "        x: x,\n",
       "        y: y,\n",
       "        button: event.button,\n",
       "        step: event.step,\n",
       "        guiEvent: simpleKeys(event),\n",
       "    });\n",
       "\n",
       "    /* This prevents the web browser from automatically changing to\n",
       "     * the text insertion cursor when the button is pressed.  We want\n",
       "     * to control all of the cursor setting manually through the\n",
       "     * 'cursor' event from matplotlib */\n",
       "    event.preventDefault();\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (_event, _name) {\n",
       "    // Handle any extra behaviour associated with a key event\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.key_event = function (event, name) {\n",
       "    // Prevent repeat events\n",
       "    if (name === 'key_press') {\n",
       "        if (event.key === this._key) {\n",
       "            return;\n",
       "        } else {\n",
       "            this._key = event.key;\n",
       "        }\n",
       "    }\n",
       "    if (name === 'key_release') {\n",
       "        this._key = null;\n",
       "    }\n",
       "\n",
       "    var value = '';\n",
       "    if (event.ctrlKey && event.key !== 'Control') {\n",
       "        value += 'ctrl+';\n",
       "    }\n",
       "    else if (event.altKey && event.key !== 'Alt') {\n",
       "        value += 'alt+';\n",
       "    }\n",
       "    else if (event.shiftKey && event.key !== 'Shift') {\n",
       "        value += 'shift+';\n",
       "    }\n",
       "\n",
       "    value += 'k' + event.key;\n",
       "\n",
       "    this._key_event_extra(event, name);\n",
       "\n",
       "    this.send_message(name, { key: value, guiEvent: simpleKeys(event) });\n",
       "    return false;\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onclick = function (name) {\n",
       "    if (name === 'download') {\n",
       "        this.handle_save(this, null);\n",
       "    } else {\n",
       "        this.send_message('toolbar_button', { name: name });\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.toolbar_button_onmouseover = function (tooltip) {\n",
       "    this.message.textContent = tooltip;\n",
       "};\n",
       "\n",
       "///////////////// REMAINING CONTENT GENERATED BY embed_js.py /////////////////\n",
       "// prettier-ignore\n",
       "var _JSXTOOLS_RESIZE_OBSERVER=function(A){var t,i=new WeakMap,n=new WeakMap,a=new WeakMap,r=new WeakMap,o=new Set;function s(e){if(!(this instanceof s))throw new TypeError(\"Constructor requires 'new' operator\");i.set(this,e)}function h(){throw new TypeError(\"Function is not a constructor\")}function c(e,t,i,n){e=0 in arguments?Number(arguments[0]):0,t=1 in arguments?Number(arguments[1]):0,i=2 in arguments?Number(arguments[2]):0,n=3 in arguments?Number(arguments[3]):0,this.right=(this.x=this.left=e)+(this.width=i),this.bottom=(this.y=this.top=t)+(this.height=n),Object.freeze(this)}function d(){t=requestAnimationFrame(d);var s=new WeakMap,p=new Set;o.forEach((function(t){r.get(t).forEach((function(i){var r=t instanceof window.SVGElement,o=a.get(t),d=r?0:parseFloat(o.paddingTop),f=r?0:parseFloat(o.paddingRight),l=r?0:parseFloat(o.paddingBottom),u=r?0:parseFloat(o.paddingLeft),g=r?0:parseFloat(o.borderTopWidth),m=r?0:parseFloat(o.borderRightWidth),w=r?0:parseFloat(o.borderBottomWidth),b=u+f,F=d+l,v=(r?0:parseFloat(o.borderLeftWidth))+m,W=g+w,y=r?0:t.offsetHeight-W-t.clientHeight,E=r?0:t.offsetWidth-v-t.clientWidth,R=b+v,z=F+W,M=r?t.width:parseFloat(o.width)-R-E,O=r?t.height:parseFloat(o.height)-z-y;if(n.has(t)){var k=n.get(t);if(k[0]===M&&k[1]===O)return}n.set(t,[M,O]);var S=Object.create(h.prototype);S.target=t,S.contentRect=new c(u,d,M,O),s.has(i)||(s.set(i,[]),p.add(i)),s.get(i).push(S)}))})),p.forEach((function(e){i.get(e).call(e,s.get(e),e)}))}return s.prototype.observe=function(i){if(i instanceof window.Element){r.has(i)||(r.set(i,new Set),o.add(i),a.set(i,window.getComputedStyle(i)));var n=r.get(i);n.has(this)||n.add(this),cancelAnimationFrame(t),t=requestAnimationFrame(d)}},s.prototype.unobserve=function(i){if(i instanceof window.Element&&r.has(i)){var n=r.get(i);n.has(this)&&(n.delete(this),n.size||(r.delete(i),o.delete(i))),n.size||r.delete(i),o.size||cancelAnimationFrame(t)}},A.DOMRectReadOnly=c,A.ResizeObserver=s,A.ResizeObserverEntry=h,A}; // eslint-disable-line\n",
       "mpl.toolbar_items = [[\"Home\", \"Reset original view\", \"fa fa-home icon-home\", \"home\"], [\"Back\", \"Back to previous view\", \"fa fa-arrow-left icon-arrow-left\", \"back\"], [\"Forward\", \"Forward to next view\", \"fa fa-arrow-right icon-arrow-right\", \"forward\"], [\"\", \"\", \"\", \"\"], [\"Pan\", \"Left button pans, Right button zooms\\nx/y fixes axis, CTRL fixes aspect\", \"fa fa-arrows icon-move\", \"pan\"], [\"Zoom\", \"Zoom to rectangle\\nx/y fixes axis\", \"fa fa-square-o icon-check-empty\", \"zoom\"], [\"\", \"\", \"\", \"\"], [\"Download\", \"Download plot\", \"fa fa-floppy-o icon-save\", \"download\"]];\n",
       "\n",
       "mpl.extensions = [\"eps\", \"jpeg\", \"pgf\", \"pdf\", \"png\", \"ps\", \"raw\", \"svg\", \"tif\"];\n",
       "\n",
       "mpl.default_extension = \"png\";/* global mpl */\n",
       "\n",
       "var comm_websocket_adapter = function (comm) {\n",
       "    // Create a \"websocket\"-like object which calls the given IPython comm\n",
       "    // object with the appropriate methods. Currently this is a non binary\n",
       "    // socket, so there is still some room for performance tuning.\n",
       "    var ws = {};\n",
       "\n",
       "    ws.binaryType = comm.kernel.ws.binaryType;\n",
       "    ws.readyState = comm.kernel.ws.readyState;\n",
       "    function updateReadyState(_event) {\n",
       "        if (comm.kernel.ws) {\n",
       "            ws.readyState = comm.kernel.ws.readyState;\n",
       "        } else {\n",
       "            ws.readyState = 3; // Closed state.\n",
       "        }\n",
       "    }\n",
       "    comm.kernel.ws.addEventListener('open', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('close', updateReadyState);\n",
       "    comm.kernel.ws.addEventListener('error', updateReadyState);\n",
       "\n",
       "    ws.close = function () {\n",
       "        comm.close();\n",
       "    };\n",
       "    ws.send = function (m) {\n",
       "        //console.log('sending', m);\n",
       "        comm.send(m);\n",
       "    };\n",
       "    // Register the callback with on_msg.\n",
       "    comm.on_msg(function (msg) {\n",
       "        //console.log('receiving', msg['content']['data'], msg);\n",
       "        var data = msg['content']['data'];\n",
       "        if (data['blob'] !== undefined) {\n",
       "            data = {\n",
       "                data: new Blob(msg['buffers'], { type: data['blob'] }),\n",
       "            };\n",
       "        }\n",
       "        // Pass the mpl event to the overridden (by mpl) onmessage function.\n",
       "        ws.onmessage(data);\n",
       "    });\n",
       "    return ws;\n",
       "};\n",
       "\n",
       "mpl.mpl_figure_comm = function (comm, msg) {\n",
       "    // This is the function which gets called when the mpl process\n",
       "    // starts-up an IPython Comm through the \"matplotlib\" channel.\n",
       "\n",
       "    var id = msg.content.data.id;\n",
       "    // Get hold of the div created by the display call when the Comm\n",
       "    // socket was opened in Python.\n",
       "    var element = document.getElementById(id);\n",
       "    var ws_proxy = comm_websocket_adapter(comm);\n",
       "\n",
       "    function ondownload(figure, _format) {\n",
       "        window.open(figure.canvas.toDataURL());\n",
       "    }\n",
       "\n",
       "    var fig = new mpl.figure(id, ws_proxy, ondownload, element);\n",
       "\n",
       "    // Call onopen now - mpl needs it, as it is assuming we've passed it a real\n",
       "    // web socket which is closed, not our websocket->open comm proxy.\n",
       "    ws_proxy.onopen();\n",
       "\n",
       "    fig.parent_element = element;\n",
       "    fig.cell_info = mpl.find_output_cell(\"<div id='\" + id + \"'></div>\");\n",
       "    if (!fig.cell_info) {\n",
       "        console.error('Failed to find cell for figure', id, fig);\n",
       "        return;\n",
       "    }\n",
       "    fig.cell_info[0].output_area.element.on(\n",
       "        'cleared',\n",
       "        { fig: fig },\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_close = function (fig, msg) {\n",
       "    var width = fig.canvas.width / fig.ratio;\n",
       "    fig.cell_info[0].output_area.element.off(\n",
       "        'cleared',\n",
       "        fig._remove_fig_handler\n",
       "    );\n",
       "    fig.resizeObserverInstance.unobserve(fig.canvas_div);\n",
       "\n",
       "    // Update the output cell to use the data from the current canvas.\n",
       "    fig.push_to_output();\n",
       "    var dataURL = fig.canvas.toDataURL();\n",
       "    // Re-enable the keyboard manager in IPython - without this line, in FF,\n",
       "    // the notebook keyboard shortcuts fail.\n",
       "    IPython.keyboard_manager.enable();\n",
       "    fig.parent_element.innerHTML =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "    fig.close_ws(fig, msg);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.close_ws = function (fig, msg) {\n",
       "    fig.send_message('closing', msg);\n",
       "    // fig.ws.close()\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.push_to_output = function (_remove_interactive) {\n",
       "    // Turn the data on the canvas into data in the output cell.\n",
       "    var width = this.canvas.width / this.ratio;\n",
       "    var dataURL = this.canvas.toDataURL();\n",
       "    this.cell_info[1]['text/html'] =\n",
       "        '<img src=\"' + dataURL + '\" width=\"' + width + '\">';\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.updated_canvas_event = function () {\n",
       "    // Tell IPython that the notebook contents must change.\n",
       "    IPython.notebook.set_dirty(true);\n",
       "    this.send_message('ack', {});\n",
       "    var fig = this;\n",
       "    // Wait a second, then push the new image to the DOM so\n",
       "    // that it is saved nicely (might be nice to debounce this).\n",
       "    setTimeout(function () {\n",
       "        fig.push_to_output();\n",
       "    }, 1000);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._init_toolbar = function () {\n",
       "    var fig = this;\n",
       "\n",
       "    var toolbar = document.createElement('div');\n",
       "    toolbar.classList = 'btn-toolbar';\n",
       "    this.root.appendChild(toolbar);\n",
       "\n",
       "    function on_click_closure(name) {\n",
       "        return function (_event) {\n",
       "            return fig.toolbar_button_onclick(name);\n",
       "        };\n",
       "    }\n",
       "\n",
       "    function on_mouseover_closure(tooltip) {\n",
       "        return function (event) {\n",
       "            if (!event.currentTarget.disabled) {\n",
       "                return fig.toolbar_button_onmouseover(tooltip);\n",
       "            }\n",
       "        };\n",
       "    }\n",
       "\n",
       "    fig.buttons = {};\n",
       "    var buttonGroup = document.createElement('div');\n",
       "    buttonGroup.classList = 'btn-group';\n",
       "    var button;\n",
       "    for (var toolbar_ind in mpl.toolbar_items) {\n",
       "        var name = mpl.toolbar_items[toolbar_ind][0];\n",
       "        var tooltip = mpl.toolbar_items[toolbar_ind][1];\n",
       "        var image = mpl.toolbar_items[toolbar_ind][2];\n",
       "        var method_name = mpl.toolbar_items[toolbar_ind][3];\n",
       "\n",
       "        if (!name) {\n",
       "            /* Instead of a spacer, we start a new button group. */\n",
       "            if (buttonGroup.hasChildNodes()) {\n",
       "                toolbar.appendChild(buttonGroup);\n",
       "            }\n",
       "            buttonGroup = document.createElement('div');\n",
       "            buttonGroup.classList = 'btn-group';\n",
       "            continue;\n",
       "        }\n",
       "\n",
       "        button = fig.buttons[name] = document.createElement('button');\n",
       "        button.classList = 'btn btn-default';\n",
       "        button.href = '#';\n",
       "        button.title = name;\n",
       "        button.innerHTML = '<i class=\"fa ' + image + ' fa-lg\"></i>';\n",
       "        button.addEventListener('click', on_click_closure(method_name));\n",
       "        button.addEventListener('mouseover', on_mouseover_closure(tooltip));\n",
       "        buttonGroup.appendChild(button);\n",
       "    }\n",
       "\n",
       "    if (buttonGroup.hasChildNodes()) {\n",
       "        toolbar.appendChild(buttonGroup);\n",
       "    }\n",
       "\n",
       "    // Add the status bar.\n",
       "    var status_bar = document.createElement('span');\n",
       "    status_bar.classList = 'mpl-message pull-right';\n",
       "    toolbar.appendChild(status_bar);\n",
       "    this.message = status_bar;\n",
       "\n",
       "    // Add the close button to the window.\n",
       "    var buttongrp = document.createElement('div');\n",
       "    buttongrp.classList = 'btn-group inline pull-right';\n",
       "    button = document.createElement('button');\n",
       "    button.classList = 'btn btn-mini btn-primary';\n",
       "    button.href = '#';\n",
       "    button.title = 'Stop Interaction';\n",
       "    button.innerHTML = '<i class=\"fa fa-power-off icon-remove icon-large\"></i>';\n",
       "    button.addEventListener('click', function (_evt) {\n",
       "        fig.handle_close(fig, {});\n",
       "    });\n",
       "    button.addEventListener(\n",
       "        'mouseover',\n",
       "        on_mouseover_closure('Stop Interaction')\n",
       "    );\n",
       "    buttongrp.appendChild(button);\n",
       "    var titlebar = this.root.querySelector('.ui-dialog-titlebar');\n",
       "    titlebar.insertBefore(buttongrp, titlebar.firstChild);\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._remove_fig_handler = function (event) {\n",
       "    var fig = event.data.fig;\n",
       "    if (event.target !== this) {\n",
       "        // Ignore bubbled events from children.\n",
       "        return;\n",
       "    }\n",
       "    fig.close_ws(fig, {});\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._root_extra_style = function (el) {\n",
       "    el.style.boxSizing = 'content-box'; // override notebook setting of border-box.\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._canvas_extra_style = function (el) {\n",
       "    // this is important to make the div 'focusable\n",
       "    el.setAttribute('tabindex', 0);\n",
       "    // reach out to IPython and tell the keyboard manager to turn it's self\n",
       "    // off when our div gets focus\n",
       "\n",
       "    // location in version 3\n",
       "    if (IPython.notebook.keyboard_manager) {\n",
       "        IPython.notebook.keyboard_manager.register_events(el);\n",
       "    } else {\n",
       "        // location in version 2\n",
       "        IPython.keyboard_manager.register_events(el);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype._key_event_extra = function (event, _name) {\n",
       "    // Check for shift+enter\n",
       "    if (event.shiftKey && event.which === 13) {\n",
       "        this.canvas_div.blur();\n",
       "        // select the cell after this one\n",
       "        var index = IPython.notebook.find_cell_index(this.cell_info[0]);\n",
       "        IPython.notebook.select(index + 1);\n",
       "    }\n",
       "};\n",
       "\n",
       "mpl.figure.prototype.handle_save = function (fig, _msg) {\n",
       "    fig.ondownload(fig, null);\n",
       "};\n",
       "\n",
       "mpl.find_output_cell = function (html_output) {\n",
       "    // Return the cell and output element which can be found *uniquely* in the notebook.\n",
       "    // Note - this is a bit hacky, but it is done because the \"notebook_saving.Notebook\"\n",
       "    // IPython event is triggered only after the cells have been serialised, which for\n",
       "    // our purposes (turning an active figure into a static one), is too late.\n",
       "    var cells = IPython.notebook.get_cells();\n",
       "    var ncells = cells.length;\n",
       "    for (var i = 0; i < ncells; i++) {\n",
       "        var cell = cells[i];\n",
       "        if (cell.cell_type === 'code') {\n",
       "            for (var j = 0; j < cell.output_area.outputs.length; j++) {\n",
       "                var data = cell.output_area.outputs[j];\n",
       "                if (data.data) {\n",
       "                    // IPython >= 3 moved mimebundle to data attribute of output\n",
       "                    data = data.data;\n",
       "                }\n",
       "                if (data['text/html'] === html_output) {\n",
       "                    return [cell, data, j];\n",
       "                }\n",
       "            }\n",
       "        }\n",
       "    }\n",
       "};\n",
       "\n",
       "// Register the function which deals with the matplotlib target/channel.\n",
       "// The kernel may be null if the page has been refreshed.\n",
       "if (IPython.notebook.kernel !== null) {\n",
       "    IPython.notebook.kernel.comm_manager.register_target(\n",
       "        'matplotlib',\n",
       "        mpl.mpl_figure_comm\n",
       "    );\n",
       "}\n"
      ],
      "text/plain": [
       "<IPython.core.display.Javascript object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
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\" width=\"640\">"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#Allows for interactive plot and slider functionality\n",
    "%matplotlib notebook\n",
    "from matplotlib.widgets import Slider\n",
    "\n",
    "#Create a figure object and plot Covid Data and our solution, H\n",
    "fig, ax = plt.subplots()\n",
    "line, = ax.plot(t, H, lw=2) #This will be manipulated by our sliders\n",
    "ax.plot(t,covid_pd['Hospitalizations'])\n",
    "ax.set_xlabel('Time [days]')\n",
    "ax.set_ylabel('Number of Hospitalizations')\n",
    "ax.set_title('Arizona COVID Hospitalization Data')\n",
    "\n",
    "\n",
    "# adjust the main plot to make room for the sliders\n",
    "fig.subplots_adjust(bottom=0.4)\n",
    "\n",
    "# Make a horizontal slider to control the gamma.\n",
    "axgamma = fig.add_axes([0.1, 0.1, 0.8, 0.03])\n",
    "gamma_slider = Slider(\n",
    "    ax=axgamma,\n",
    "    label='Gamma',\n",
    "    valmin=0.01,\n",
    "    valmax=3,\n",
    "    valinit=0.19,\n",
    ")\n",
    "\n",
    "# Make another horizontal slider to control beta\n",
    "axbeta = fig.add_axes([0.1, 0.25, 0.8, 0.03])\n",
    "beta_slider = Slider(\n",
    "    ax=axbeta,\n",
    "    label=\"Beta\",\n",
    "    valmin=0.01,\n",
    "    valmax=0.8,\n",
    "    valinit= 0.3121,\n",
    ")\n",
    "\n",
    "\n",
    "# The function to be called anytime a slider's value changes\n",
    "def update(val):\n",
    "    ret = odeint(deriv, y0, t, args=(N, beta_slider.val, gamma_slider.val,f,c))\n",
    "    S, I, H, R = ret.T\n",
    "    line.set_ydata(H)\n",
    "    fig.canvas.draw_idle()\n",
    "\n",
    "\n",
    "# register the update function with each slider\n",
    "beta_slider.on_changed(update)\n",
    "gamma_slider.on_changed(update)\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "0ee53742",
   "metadata": {},
   "source": [
    "The parameters $\\beta$ and $\\gamma$ can be varied using our sliders to try to fit the data with our solution curve. I've found that values of $\\beta=0.312$ and $\\gamma = .19$ seem to approximate the data reasonably well, but one could continue to try different combinations to better fit our observed results. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "b111a21a",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3 (ipykernel)",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.9.13"
  }
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