model-extended_v1.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "bdc15275",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from sklearn.metrics import mean_squared_error\n",
    "import pandas as pd"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "6b798aaf",
   "metadata": {},
   "outputs": [],
   "source": [
    "N = 10000000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "5bf2245d",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Date</th>\n",
       "      <th>Uncovered</th>\n",
       "      <th>Du</th>\n",
       "      <th>Ru</th>\n",
       "      <th>Exposed</th>\n",
       "      <th>Isolated</th>\n",
       "      <th>Apathetic</th>\n",
       "      <th>Da</th>\n",
       "      <th>Ra</th>\n",
       "      <th>Infected</th>\n",
       "      <th>Di</th>\n",
       "      <th>Ri</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>24-03-20</td>\n",
       "      <td>39</td>\n",
       "      <td>6</td>\n",
       "      <td>33</td>\n",
       "      <td>557</td>\n",
       "      <td>10</td>\n",
       "      <td>11</td>\n",
       "      <td>2</td>\n",
       "      <td>9</td>\n",
       "      <td>536</td>\n",
       "      <td>14</td>\n",
       "      <td>522</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>25-03-20</td>\n",
       "      <td>57</td>\n",
       "      <td>10</td>\n",
       "      <td>47</td>\n",
       "      <td>692</td>\n",
       "      <td>12</td>\n",
       "      <td>23</td>\n",
       "      <td>4</td>\n",
       "      <td>19</td>\n",
       "      <td>657</td>\n",
       "      <td>33</td>\n",
       "      <td>624</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>26-03-20</td>\n",
       "      <td>71</td>\n",
       "      <td>13</td>\n",
       "      <td>58</td>\n",
       "      <td>781</td>\n",
       "      <td>18</td>\n",
       "      <td>34</td>\n",
       "      <td>6</td>\n",
       "      <td>28</td>\n",
       "      <td>729</td>\n",
       "      <td>69</td>\n",
       "      <td>660</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>27-03-20</td>\n",
       "      <td>83</td>\n",
       "      <td>11</td>\n",
       "      <td>72</td>\n",
       "      <td>946</td>\n",
       "      <td>20</td>\n",
       "      <td>39</td>\n",
       "      <td>8</td>\n",
       "      <td>31</td>\n",
       "      <td>887</td>\n",
       "      <td>109</td>\n",
       "      <td>778</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>28-03-20</td>\n",
       "      <td>97</td>\n",
       "      <td>15</td>\n",
       "      <td>82</td>\n",
       "      <td>1057</td>\n",
       "      <td>24</td>\n",
       "      <td>46</td>\n",
       "      <td>9</td>\n",
       "      <td>37</td>\n",
       "      <td>987</td>\n",
       "      <td>144</td>\n",
       "      <td>843</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Date  Uncovered  Du  Ru  Exposed  Isolated  Apathetic  Da  Ra  \\\n",
       "0  24-03-20         39   6  33      557        10         11   2   9   \n",
       "1  25-03-20         57  10  47      692        12         23   4  19   \n",
       "2  26-03-20         71  13  58      781        18         34   6  28   \n",
       "3  27-03-20         83  11  72      946        20         39   8  31   \n",
       "4  28-03-20         97  15  82     1057        24         46   9  37   \n",
       "\n",
       "   Infected   Di   Ri  \n",
       "0       536   14  522  \n",
       "1       657   33  624  \n",
       "2       729   69  660  \n",
       "3       887  109  778  \n",
       "4       987  144  843  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = pd.read_csv(\"trial_data.csv\", header = 0) \n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "926592c3",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Available 52 days\n"
     ]
    }
   ],
   "source": [
    "available = len(df.index)\n",
    "print(\"Available\", available, \"days\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "b656adda",
   "metadata": {},
   "outputs": [],
   "source": [
    "start_date = df['Date'].iloc[0]  \n",
    "uncovered = df['Uncovered'].values.tolist() \n",
    "Du = df['Du'].values.tolist() # shob gula ek ekta col k tar nijeder moddhe rakhlam.. \n",
    "Ru = df['Ru'].values.tolist() # shob gula ek ekta col k tar nijeder moddhe rakhlam..\n",
    "exposed= df['Exposed'].values.tolist()\n",
    "isolated = df['Isolated'].values.tolist()\n",
    "infected = df['Infected'].values.tolist()  # shob gula ek ekta col k tar nijeder moddhe rakhlam..\n",
    "Di = df['Di'].values.tolist()\n",
    "Ri = df['Ri'].values.tolist()\n",
    "Apathetic = df['Apathetic'].values.tolist() \n",
    "Da = df['Da'].values.tolist() # shob gula ek ekta col k tar nijeder moddhe rakhlam.. \n",
    "Ra = df['Ra'].values.tolist() # shob gula ek ekta col k tar nijeder moddhe rakhlam..\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "df835fee",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "24-03-20\n"
     ]
    }
   ],
   "source": [
    "print(start_date)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "cdd00fb7",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['2020-03-24', '2020-03-25', '2020-03-26', '2020-03-27', '2020-03-28', '2020-03-29', '2020-03-30', '2020-03-31', '2020-04-01', '2020-04-02', '2020-04-03', '2020-04-04', '2020-04-05', '2020-04-06', '2020-04-07', '2020-04-08', '2020-04-09', '2020-04-10', '2020-04-11', '2020-04-12', '2020-04-13', '2020-04-14', '2020-04-15', '2020-04-16', '2020-04-17', '2020-04-18', '2020-04-19', '2020-04-20', '2020-04-21', '2020-04-22', '2020-04-23', '2020-04-24', '2020-04-25', '2020-04-26', '2020-04-27', '2020-04-28', '2020-04-29', '2020-04-30', '2020-05-01', '2020-05-02', '2020-05-03', '2020-05-04', '2020-05-05', '2020-05-06', '2020-05-07', '2020-05-08', '2020-05-09', '2020-05-10', '2020-05-11', '2020-05-12', '2020-05-13', '2020-05-14', '2020-05-15', '2020-05-16', '2020-05-17', '2020-05-18', '2020-05-19', '2020-05-20', '2020-05-21', '2020-05-22', '2020-05-23', '2020-05-24', '2020-05-25', '2020-05-26', '2020-05-27', '2020-05-28', '2020-05-29', '2020-05-30', '2020-05-31', '2020-06-01', '2020-06-02', '2020-06-03', '2020-06-04']\n",
      "73\n"
     ]
    }
   ],
   "source": [
    "#Helper Function\n",
    "\n",
    "t_max = available + 21\n",
    "\n",
    "date = np.array('2020-03-24', dtype=np.datetime64) \n",
    "dates = date + np.arange(t_max)\n",
    "str_dates = []\n",
    "for i in dates:\n",
    "    str_dates.append(str(i))\n",
    "print(str_dates)\n",
    "print(len(str_dates))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "9760834d",
   "metadata": {},
   "outputs": [],
   "source": [
    "def seird_model(init_vals, params, t):\n",
    "\n",
    "    DATE_0, S_0, U_0, Du_0, Ru_0, E_0, Is_0, I_0,  Di_0, Ri_0, A_0, Da_0, Ra_0 = init_vals  # jehetu ajk r real data niye kaj kortesi tai date takeo mention korte hobe.\n",
    "    DATE, S, U, Du, Ru, E, Is, I, Di, Ri, A, Da, Ra = [DATE_0] , [S_0] , [U_0] , [Du_0], [Ru_0] , [E_0] , [Is_0] , [I_0] ,  [Di_0] , [Ri_0], [A_0], [Da_0] , [Ra_0]\n",
    "    \n",
    "    beta, sigma, tao, alpha, rho, gamma, delta, miu, lamda, womega, eta  = params\n",
    "    \n",
    "    ##### Create next t days ######\n",
    "    date = np.array(DATE, dtype=np.datetime64)\n",
    "    dates = date + np.arange(len(t))\n",
    "    str_dates = []\n",
    "    for i in dates:\n",
    "        str_dates.append(str(i))\n",
    "        \n",
    "    ##### End creating t days #####\n",
    "    for tic in t[1:]:                # 1st din er initial value deya ache tai 1 theke shuru kore baki shob add dilam.\n",
    "\n",
    "        DATE.append(str_dates[tic])\n",
    "\n",
    "        \n",
    "        next_S = S[-1] - ( alpha * (S[-1]  * E[-1] / N ) ) - ( beta * (S[-1]  * U[-1] / N ) )  # Susceptible\n",
    "        next_U = U[-1] + ( beta * (S[-1]  * U[-1] / N ) ) - ( sigma * U[-1] ) - ( tao * U[-1] )  # Unknown\n",
    "        next_E = E[-1] + ( alpha * (S[-1]  * E[-1] / N ) ) -  ( gamma * I[-1] ) - ( lamda * A[-1] ) - ( rho * Is[-1] ) # Exposed\n",
    "        next_Du = Du[-1] + ( sigma * U[-1] )\n",
    "        next_Ru = Ru[-1] + ( tao * U[-1]) \n",
    "        next_Di = Di[-1] + ( delta * I[-1] )  \n",
    "        next_Ri = Ri[-1] + ( miu * I[-1] )\n",
    "        next_A = A[-1] + ( lamda * A[-1] ) - ( womega * A[-1] ) - ( miu * A[-1] )  # Unknown \n",
    "        next_Da = Da[-1] + ( womega * U[-1] )\n",
    "        next_Ra = Ra[-1] + ( eta * U[-1] )\n",
    "        next_Is = Is[-1] + (rho *  Is[-1] )  #isolation\n",
    "        next_I = I[-1] + ( gamma * I[-1] ) - ( delta * I[-1] ) - ( miu * I[-1] ) # Infected\n",
    "       \n",
    "        \n",
    "        \n",
    "\n",
    "        \n",
    "        S.append(next_S)\n",
    "        U.append(next_U)\n",
    "        E.append(next_E)\n",
    "        Du.append(next_Du)                   \n",
    "        Ru.append(next_Ru)\n",
    "        Di.append(next_Di)\n",
    "        Ri.append(next_Ri)\n",
    "        A.append(next_A)\n",
    "        Da.append(next_Da)\n",
    "        Ra.append(next_Ra)\n",
    "        Is.append(next_Is)\n",
    "        I.append(next_I)\n",
    "        \n",
    "        \n",
    "\n",
    "    return np.stack([DATE, S, U, E, Du, Ru, Di, Ri, A, Da, Ra, Is, I]).T"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "0050ffdd",
   "metadata": {},
   "outputs": [],
   "source": [
    "# Spliting the data for one day rolling window approach\n",
    "\n",
    "train_min = 1  # diffrence ber korar jnno ami 1 din er diffrence k niye cal kortesi\n",
    "train_max = available + 1\n",
    "\n",
    "uncovered_train = []\n",
    "Du_train = []\n",
    "Ru_train = []\n",
    "exposed_train = []\n",
    "isolated_train = []\n",
    "infected_train = []\n",
    "Di_train = []\n",
    "Ri_train = []\n",
    "Apathetic_train = []\n",
    "Da_train = []\n",
    "Ra_train = []\n",
    "\n",
    "\n",
    "for i in range(train_min+1, train_max):\n",
    "    j = i - 2\n",
    "    uncovered_train.append(uncovered[j:i])\n",
    "    Du_train.append(Du[j:i])\n",
    "    Ru_train.append(Ru[j:i])\n",
    "    exposed_train.append(exposed[j:i])\n",
    "    isolated_train.append(isolated[j:i])\n",
    "    infected_train.append(infected[j:i])\n",
    "    Di_train.append(Di[j:i])\n",
    "    Ri_train.append(Ri[j:i])\n",
    "    Apathetic_train.append(Apathetic[j:i])\n",
    "    Da_train.append(Da[j:i])\n",
    "    Ra_train.append(Ra[j:i])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "id": "c6908e88",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0 [557, 692]\n",
      "1 [692, 781]\n",
      "2 [781, 946]\n",
      "3 [946, 1057]\n",
      "4 [1057, 1102]\n",
      "5 [1102, 1337]\n",
      "6 [1337, 1488]\n",
      "7 [1488, 2114]\n",
      "8 [2114, 2678]\n",
      "9 [2678, 2705]\n",
      "10 [2705, 3254]\n",
      "11 [3254, 3778]\n",
      "12 [3778, 5049]\n",
      "13 [5049, 5615]\n",
      "14 [5615, 6303]\n",
      "15 [6303, 7234]\n",
      "16 [7234, 8237]\n",
      "17 [8237, 9280]\n",
      "18 [9280, 10157]\n",
      "19 [10157, 11468]\n",
      "20 [11468, 12663]\n",
      "21 [12663, 13542]\n",
      "22 [13542, 14974]\n",
      "23 [14974, 16160]\n",
      "24 [16160, 17919]\n",
      "25 [17919, 20146]\n",
      "26 [20146, 21476]\n",
      "27 [21476, 23695]\n",
      "28 [23695, 25351]\n",
      "29 [25351, 27655]\n",
      "30 [27655, 29580]\n",
      "31 [29580, 31732]\n",
      "32 [31732, 33898]\n",
      "33 [33898, 36054]\n",
      "34 [36054, 38511]\n",
      "35 [38511, 40924]\n",
      "36 [40924, 43341]\n",
      "37 [43341, 46623]\n",
      "38 [46623, 49855]\n",
      "39 [49855, 53545]\n",
      "40 [53545, 58527]\n",
      "41 [58527, 62764]\n",
      "42 [62764, 67453]\n",
      "43 [67453, 72197]\n",
      "44 [72197, 76581]\n",
      "45 [76581, 81068]\n",
      "46 [81068, 85025]\n",
      "47 [85025, 90215]\n",
      "48 [90215, 96068]\n",
      "49 [96068, 102657]\n",
      "50 [102657, 108097]\n"
     ]
    }
   ],
   "source": [
    "for i in range(len(exposed_train)): \n",
    "    print(i,exposed_train[i])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "id": "a6c64272",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[0 1 2 3 4 5 6 7 8 9]\n"
     ]
    }
   ],
   "source": [
    "t2 = np.arange(0, 10, 1)   # 0 - 3 PORJNTO JABE.. R PROTTEKBAR 1 KORE KORE BARBE. 0 initial value tar mane 0 theke shuRa hoye aro 2 din porjnto simulation cholbe.\n",
    "print(t2)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "id": "3f8d1cb9",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-04-29\n",
      "2020-04-30\n",
      "2020-05-01\n",
      "2020-05-02\n",
      "2020-05-03\n",
      "2020-05-04\n",
      "2020-05-05\n",
      "2020-05-06\n",
      "2020-05-07\n",
      "2020-05-08\n",
      "2020-05-09\n",
      "2020-05-10\n",
      "2020-05-11\n",
      "2020-05-12\n",
      "2020-05-13\n"
     ]
    }
   ],
   "source": [
    "last5_vals = []\n",
    "last5_params = []\n",
    "\n",
    "\n",
    "t_incub = 21  # Assumption 30 days\n",
    "\n",
    "for sample in range(len(uncovered_train)):\n",
    "    \n",
    "    u_0 = uncovered_train[sample][0]\n",
    "    u_1 = uncovered_train[sample][1]\n",
    "    u_diff = u_1 - u_0\n",
    "\n",
    "    du_0 = Du_train[sample][0]\n",
    "    du_1 = Du_train[sample][1]\n",
    "    du_diff = du_1 - du_0\n",
    "\n",
    "    ru_0 = Ru_train[sample][0]\n",
    "    ru_1 = Ru_train[sample][1]\n",
    "    ru_diff = ru_1 - ru_0\n",
    "    \n",
    "    e_0 = exposed_train[sample][0]\n",
    "    e_1 = exposed_train[sample][1]\n",
    "    e_diff = e_1 - e_0\n",
    "    \n",
    "    is_0 = isolated_train[sample][0]\n",
    "    is_1 = isolated_train[sample][1]\n",
    "    is_diff = is_1 - is_0\n",
    "\n",
    "    i_0 = infected_train[sample][0]\n",
    "    i_1 = infected_train[sample][1]\n",
    "    i_diff = i_1 - i_0\n",
    "    \n",
    "    di_0 = Di_train[sample][0]\n",
    "    di_1 = Di_train[sample][1]\n",
    "    di_diff = di_1 - di_0\n",
    "    \n",
    "    ri_0 = Ri_train[sample][0]\n",
    "    ri_1 = Ri_train[sample][1]\n",
    "    ri_diff = ri_1 - ri_0\n",
    "    \n",
    "    \n",
    "    a_0 = Apathetic_train[sample][0]\n",
    "    a_1 = Apathetic_train[sample][1]\n",
    "    a_diff = a_1 - a_0\n",
    "\n",
    "    Da_0 = Da_train[sample][0]\n",
    "    Da_1 = Da_train[sample][1]\n",
    "    Da_diff = Da_1 - Da_0\n",
    "\n",
    "    Ra_0 = Ra_train[sample][0]\n",
    "    Ra_1 = Ra_train[sample][1]\n",
    "    Ra_diff = Ra_1 - Ra_0\n",
    "\n",
    "  \n",
    "    s_0 = N - du_0 - ru_0 - is_0 - di_0 - ri_0 - Da_0 - Ra_0 \n",
    "    \n",
    "    beta =   (( u_diff + du_diff + ru_diff ) / (s_0 * u_0 )) * N     # beta\n",
    "    sigma = ( du_diff / u_0 )     # sigma\n",
    "    tao = ( ru_diff / u_0 )      # tao\n",
    "    alpha = (( e_diff + is_diff + i_diff + di_diff + ri_diff + a_diff + Da_diff + Ra_diff ) / (s_0 * e_0 ) )* N  # alpha\n",
    "    rho = ( is_diff / is_0 )      # rho\n",
    "    gamma = ( i_diff + di_diff + ri_diff) / i_0    # gamma\n",
    "    delta = ( di_diff / i_0 )   # delta\n",
    "    miu =  ( ri_diff / i_0 )     # miu\n",
    "    lamda = (a_diff + Da_diff + Ra_diff ) / a_0\n",
    "    womega = (Da_diff / a_0)\n",
    "    eta =  (Ra_diff / a_0)\n",
    "    \n",
    "\n",
    "    init_vals = str_dates[sample], s_0, u_0, du_0, ru_0, e_0, is_0, i_0, di_0, ri_0, a_0, Da_0, Ra_0  \n",
    "    params = beta, sigma, tao, alpha, rho, gamma, delta, miu, lamda, womega, eta \n",
    "    pred = seird_model(init_vals, params, t2) # t2 cz etar upor porer day gula depend kortese.\n",
    "    \n",
    "\n",
    "    # Store Last five cases for predecting future\n",
    "    if ((len(uncovered_train)  - sample ) <= 15):\n",
    "        print(str_dates[sample])\n",
    "        last5_vals.append(init_vals)\n",
    "        last5_params.append(params)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "id": "8a602518",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "('2020-04-29', 9950639, 8437, 1265, 7172, 40924, 1079, 33062, 4955, 28107, 6783, 949, 5834)\n",
      "('2020-04-30', 9947591, 9068, 1321, 7747, 43341, 1154, 34863, 5077, 29786, 7324, 991, 6333)\n",
      "('2020-05-01', 9943370, 10007, 1408, 8599, 46623, 1223, 37257, 5296, 31961, 8143, 1006, 7137)\n",
      "('2020-05-02', 9939326, 10819, 1593, 9226, 49855, 1323, 39699, 5843, 33856, 8833, 1195, 7638)\n",
      "('2020-05-03', 9934680, 11775, 1760, 10015, 53545, 1391, 42505, 6353, 36152, 9649, 1320, 8329)\n",
      "('2020-05-04', 9928626, 12847, 1878, 10969, 58527, 1566, 46437, 6785, 39652, 10524, 1409, 9115)\n",
      "('2020-05-05', 9923094, 14142, 2122, 12020, 62764, 1693, 49400, 7410, 41990, 11671, 1592, 10079)\n",
      "('2020-05-06', 9917216, 15331, 2291, 13040, 67453, 1785, 52987, 7916, 45071, 12681, 1719, 10962)\n",
      "('2020-05-07', 9911027, 16776, 2514, 14262, 72197, 1889, 56351, 8444, 47907, 13957, 1886, 12071)\n",
      "('2020-05-08', 9905532, 17887, 2680, 15207, 76581, 1985, 59695, 8944, 50751, 14901, 2010, 12891)\n",
      "('2020-05-09', 9898839, 19301, 2796, 16505, 81068, 2101, 62808, 9238, 54362, 16159, 2047, 14112)\n",
      "('2020-05-10', 9893666, 21309, 2923, 18386, 85025, 2259, 65764, 9681, 56083, 17002, 2164, 14838)\n",
      "('2020-05-11', 9887613, 22172, 3091, 19081, 90215, 2397, 69840, 9967, 59873, 17978, 2305, 15673)\n",
      "('2020-05-12', 9881170, 22762, 3326, 19436, 96068, 2502, 74549, 10401, 64148, 19017, 2411, 16606)\n",
      "('2020-05-13', 9873772, 23571, 3479, 20092, 102657, 2668, 79878, 10923, 68955, 20111, 2523, 17588)\n"
     ]
    }
   ],
   "source": [
    "for v in last5_vals: \n",
    "    print(v)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "id": "33a17d9c",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "(0.150321234972947, 0.0066374303662439255, 0.0681521867962546, 0.17621926411799912, 0.06950880444856349, 0.10894682717318976, 0.0036900369003690036, 0.05078337668622588, 0.15951643815420904, 0.006191950464396285, 0.07356626861270824)\n",
      "(0.20819301555510808, 0.009594177326863696, 0.09395677106307895, 0.22677165361466547, 0.05979202772963605, 0.13733757852164186, 0.006281731348420962, 0.062387057912399964, 0.22364827962861825, 0.0020480611687602405, 0.10977607864554888)\n",
      "(0.16321066149638983, 0.01848705905865894, 0.06265614070150895, 0.2069933646534687, 0.08176614881439084, 0.13108945969884853, 0.014681804761521325, 0.050862925087902945, 0.16947071104015718, 0.02321011912071718, 0.061525236399361416)\n",
      "(0.17780494367179214, 0.015435807375912746, 0.07292725760236621, 0.22202709913988516, 0.05139833711262283, 0.14136376231139322, 0.012846671200785914, 0.057835209954910705, 0.18476168912034416, 0.014151477414242046, 0.07822936714593004)\n",
      "(0.18327785032383548, 0.010021231422505307, 0.08101910828025477, 0.27767519937194923, 0.12580877066858376, 0.18501352782025643, 0.010163510175273498, 0.08234325373485472, 0.18136594465747746, 0.009223753756865996, 0.08145921857187273)\n",
      "(0.20305275593566943, 0.018992760955865183, 0.08180898264186191, 0.21655753259431385, 0.08109833971902937, 0.12761375627193833, 0.013459095118117019, 0.050347783017852143, 0.21797795515013302, 0.017388825541619156, 0.09160015203344736)\n",
      "(0.1694548143429728, 0.011950219205204355, 0.07212558336868902, 0.22438514270825527, 0.054341405788541054, 0.14522267206477732, 0.010242914979757085, 0.06236842105263158, 0.17307857081655384, 0.01088167252163482, 0.0756576128866421)\n",
      "(0.1900805091966151, 0.014545691735698911, 0.07970778161894201, 0.21119792353469766, 0.05826330532212885, 0.12697454092513258, 0.009964708324683413, 0.053522562137882874, 0.2012459585206214, 0.01316930841416292, 0.08745367084614777)\n",
      "(0.13364015721937347, 0.009895088221268479, 0.05633047210300429, 0.1824619577743712, 0.05082053996823716, 0.11868467285407534, 0.00887295700165037, 0.050469379425387303, 0.13527262305653076, 0.008884430751594181, 0.058751880776671206)\n",
      "(0.15961146831491355, 0.006485156817800638, 0.07256666853021748, 0.18636245358594072, 0.058438287153652395, 0.11756428511600636, 0.004925035597621241, 0.06049082837758606, 0.16884772834037984, 0.0024830548285349977, 0.08194080934165492)\n",
      "(0.21019850976009627, 0.006579969949743537, 0.09745609035801253, 0.1360907750927579, 0.0752022846263684, 0.08151827792637881, 0.007053241625270666, 0.027400968029550377, 0.10433813973636982, 0.007240547063555913, 0.044928522804629)\n",
      "(0.08186918688451003, 0.007883992679149654, 0.03261532685719649, 0.18345025893662575, 0.06108897742363878, 0.12395839669119883, 0.004348883887841372, 0.05763031445775804, 0.11481002235031172, 0.008293141983296082, 0.04911186919185978)\n",
      "(0.0538252031384026, 0.010598953635215588, 0.01601118527872993, 0.19567023127564656, 0.04380475594493116, 0.13485108820160366, 0.006214203894616265, 0.061211340206185565, 0.11558571587495828, 0.005896095227500278, 0.051896762709978866)\n",
      "(0.07193822653425556, 0.0067217291977857835, 0.028819963096388717, 0.20648623621474874, 0.06634692246203037, 0.14296637111161786, 0.007002105997397685, 0.06448107955841124, 0.1150549508334648, 0.005889467318714834, 0.051638008098017565)\n",
      "(0.12357419196499614, 0.005175851682151796, 0.055831318145178395, 0.15969624470735938, 0.04985007496251874, 0.10803976063496833, 0.00544580485239991, 0.04857407546508425, 0.09865247874297647, 0.006364676047933966, 0.042961563323554275)\n"
     ]
    }
   ],
   "source": [
    "for p in last5_params: \n",
    "    print(p)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "id": "dcfef1b0",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 0  1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16 17 18 19 20]\n"
     ]
    }
   ],
   "source": [
    "t7 = np.arange(0, 21, 1)  #13 din er data ashbe\n",
    "print(t7)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "id": "84e842e4",
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Predictions using 2020-04-29 parameters\n",
      "\n",
      "---------------------------------------------------------------------------------------------------------------------------\n",
      "Date      Uncovered  Exposed  Du      Ru    Di      Ri  Apathetic  Da     Ra  Isolated  Infected\n",
      "---------------------------------------------------------------------------------------------------------------------------\n",
      "2020-05-05   12980   56851   1670   11333   5794   39656   12184   1327   10325   1614   45450\n",
      "2020-05-06   13939   59753   1756   12217   5961   41964   13433   1407   11280   1727   47926\n",
      "2020-05-07   14967   62672   1848   13167   6138   44398   14810   1493   12306   1847   50537\n",
      "2020-05-08   16068   65573   1948   14187   6325   46965   16329   1586   13407   1975   53290\n",
      "2020-05-09   17247   68412   2054   15283   6521   49671   18004   1685   14589   2112   56193\n",
      "2020-05-10   18508   71135   2169   16458   6729   52525   19850   1792   15858   2259   59254\n",
      "2020-05-11   19858   73673   2292   17719   6947   55534   21885   1907   17219   2416   62482\n",
      "2020-05-12   21301   75945   2424   19073   7178   58707   24129   2030   18680   2584   65885\n",
      "2020-05-13   22845   77847   2565   20524   7421   62053   26604   2162   20247   2764   69474\n",
      "2020-05-14   24494   79258   2717   22081   7677   65581   29332   2303   21928   2956   73259\n",
      "2020-05-15   26257   80027   2879   23751   7948   69301   32339   2455   23730   3162   77250\n",
      "2020-05-16   28140   79976   3053   25540   8233   73224   35656   2617   25662   3381   81458\n",
      "2020-05-17   30150   78888   3240   27458   8533   77361   39312   2792   27732   3616   85895\n",
      "2020-05-18   32296   76506   3440   29513   8850   81723   43343   2978   29950   3868   90574\n",
      "2020-05-19   34586   72522   3655   31714   9185   86323   47787   3178   32326   4137   95508\n",
      "---------------------------------------------------------------------------------------------------------------\n",
      "\n",
      "\n",
      "Predictions using 2020-04-30 parameters\n",
      "\n",
      "---------------------------------------------------------------------------------------------------------------------------\n",
      "Date      Uncovered  Exposed  Du      Ru    Di      Ri  Apathetic  Da     Ra  Isolated  Infected\n",
      "---------------------------------------------------------------------------------------------------------------------------\n",
      "2020-05-05   14806   60636   1855   12982   6333   42260   15330   1105   12450   1542   48593\n",
      "2020-05-06   16318   64026   1997   14373   6638   45292   17771   1135   14075   1635   51930\n",
      "2020-05-07   17979   67142   2154   15907   6964   48532   20601   1168   15866   1732   55496\n",
      "2020-05-08   19802   69800   2326   17596   7313   51994   23881   1205   17840   1836   59307\n",
      "2020-05-09   21803   71759   2516   19456   7685   55694   27683   1246   20014   1946   63380\n",
      "2020-05-10   23997   72706   2725   21505   8083   59648   32090   1290   22408   2062   67732\n",
      "2020-05-11   26402   72240   2956   23760   8509   63874   37200   1340   25042   2185   72383\n",
      "2020-05-12   29036   69846   3209   26240   8964   68389   43122   1394   27940   2316   77353\n",
      "2020-05-13   31920   64874   3488   28969   9449   73215   49988   1453   31128   2455   82665\n",
      "2020-05-14   35076   56498   3794   31968   9969   78373   57947   1518   34632   2601   88342\n",
      "2020-05-15   38529   43681   4130   35263   10524   83884   67173   1590   38482   2757   94408\n",
      "2020-05-16   42306   25119   4500   38884   11117   89774   77868   1669   42712   2922   100891\n",
      "2020-05-17   46438   -821   4906   42859   11750   96068   90266   1756   47356   3097   107819\n",
      "2020-05-18   50961   -36181   5351   47222   12428   102795   104637   1851   52454   3282   115223\n",
      "2020-05-19   55914   -83516   5840   52010   13152   109983   121297   1955   58048   3478   123135\n",
      "---------------------------------------------------------------------------------------------------------------\n",
      "\n",
      "\n",
      "Predictions using 2020-05-01 parameters\n",
      "\n",
      "---------------------------------------------------------------------------------------------------------------------------\n",
      "Date      Uncovered  Exposed  Du      Ru    Di      Ri  Apathetic  Da     Ra  Isolated  Infected\n",
      "---------------------------------------------------------------------------------------------------------------------------\n",
      "2020-05-05   13657   60723   2242   11428   7708   40319   11723   2054   9915   1674   48028\n",
      "2020-05-06   14754   64739   2495   12284   8413   42762   12842   2371   10755   1811   51175\n",
      "2020-05-07   15936   68944   2768   13208   9165   45365   14067   2713   11663   1959   54530\n",
      "2020-05-08   17208   73328   3062   14207   9965   48138   15409   3083   12644   2120   58104\n",
      "2020-05-09   18578   77872   3380   15285   10818   51094   16879   3482   13702   2293   61912\n",
      "2020-05-10   20050   82551   3724   16449   11727   54243   18489   3914   14845   2481   65970\n",
      "2020-05-11   21634   87330   4095   17705   12696   57598   20253   4379   16079   2683   70295\n",
      "2020-05-12   23335   92160   4494   19061   13728   61174   22185   4881   17410   2903   74902\n",
      "2020-05-13   25162   96980   4926   20523   14828   64983   24302   5423   18846   3140   79811\n",
      "2020-05-14   27123   101708   5391   22100   15999   69043   26620   6007   20394   3397   85043\n",
      "2020-05-15   29227   106241   5893   23799   17248   73368   29160   6636   22063   3675   90617\n",
      "2020-05-16   31481   110448   6433   25630   18578   77977   31941   7315   23861   3975   96556\n",
      "2020-05-17   33897   114165   7015   27603   19996   82889   34989   8045   25798   4300   102885\n",
      "2020-05-18   36482   117190   7642   29727   21507   88122   38327   8832   27883   4652   109629\n",
      "2020-05-19   39248   119271   8316   32013   23116   93698   41983   9679   30128   5033   116814\n",
      "---------------------------------------------------------------------------------------------------------------\n",
      "\n",
      "\n",
      "Predictions using 2020-05-02 parameters\n",
      "\n",
      "---------------------------------------------------------------------------------------------------------------------------\n",
      "Date      Uncovered  Exposed  Du      Ru    Di      Ri  Apathetic  Da     Ra  Isolated  Infected\n",
      "---------------------------------------------------------------------------------------------------------------------------\n",
      "2020-05-05   13938   61564   2139   11808   7483   41242   12171   1696   10407   1537   48726\n",
      "2020-05-06   15160   65877   2354   12824   8109   44060   13543   1893   11498   1616   52170\n",
      "2020-05-07   16484   70370   2588   13930   8779   47077   15071   2107   12684   1699   55857\n",
      "2020-05-08   17918   75014   2843   15132   9497   50308   16770   2341   13973   1787   59805\n",
      "2020-05-09   19472   79768   3119   16439   10265   53767   18662   2594   15375   1879   64032\n",
      "2020-05-10   21154   84576   3420   17859   11088   57470   20766   2870   16898   1975   68558\n",
      "2020-05-11   22973   89359   3746   19401   11969   61435   23108   3169   18553   2077   73404\n",
      "2020-05-12   24939   94018   4101   21077   12912   65680   25714   3494   20350   2183   78593\n",
      "2020-05-13   27064   98419   4486   22896   13921   70226   28614   3847   22302   2296   84148\n",
      "2020-05-14   29357   102392   4904   24869   15002   75093   31841   4230   24419   2414   90095\n",
      "2020-05-15   31831   105723   5357   27010   16160   80303   35432   4646   26715   2538   96464\n",
      "2020-05-16   34499   108137   5848   29332   17399   85882   39428   5096   29206   2668   103282\n",
      "2020-05-17   37373   109295   6381   31848   18726   91856   43875   5584   31904   2805   110582\n",
      "2020-05-18   40466   108769   6958   34573   20146   98251   48823   6113   34828   2950   118398\n",
      "2020-05-19   43795   106032   7582   37524   21667   105099   54329   6686   37994   3101   126767\n",
      "---------------------------------------------------------------------------------------------------------------\n",
      "\n",
      "\n",
      "Predictions using 2020-05-03 parameters\n",
      "\n",
      "---------------------------------------------------------------------------------------------------------------------------\n",
      "Date      Uncovered  Exposed  Du      Ru    Di      Ri  Apathetic  Da     Ra  Isolated  Infected\n",
      "---------------------------------------------------------------------------------------------------------------------------\n",
      "2020-05-05   14012   63949   2006   12009   7256   43475   11459   1547   10334   1763   50732\n",
      "2020-05-06   15279   69841   2147   13145   7772   47653   12488   1676   11476   1984   55425\n",
      "2020-05-07   16654   76230   2300   14383   8335   52217   13610   1817   12720   2234   60553\n",
      "2020-05-08   18147   83143   2467   15732   8951   57203   14832   1970   14077   2515   66154\n",
      "2020-05-09   19765   90599   2649   17202   9623   62650   16164   2138   15555   2832   72274\n",
      "2020-05-10   21519   98612   2847   18804   10358   68602   17615   2320   17165   3188   78960\n",
      "2020-05-11   23416   107184   3062   20547   11160   75103   19197   2519   18918   3589   86264\n",
      "2020-05-12   25468   116305   3297   22444   12037   82207   20921   2735   20826   4041   94244\n",
      "2020-05-13   27685   125941   3552   24508   12995   89967   22800   2970   22900   4549   102963\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-05-14   30076   136034   3830   26751   14041   98445   24848   3225   25156   5121   112487\n",
      "2020-05-15   32652   146488   4131   29188   15185   107708   27079   3502   27606   5766   122893\n",
      "2020-05-16   35424   157159   4458   31833   16434   117828   29511   3803   30266   6491   134262\n",
      "2020-05-17   38402   167843   4813   34703   17798   128883   32161   4130   33151   7308   146682\n",
      "2020-05-18   41596   178257   5198   37814   19289   140961   35049   4484   36279   8228   160251\n",
      "2020-05-19   45018   188018   5615   41184   20918   154157   38196   4868   39668   9263   175075\n",
      "---------------------------------------------------------------------------------------------------------------\n",
      "\n",
      "\n",
      "Predictions using 2020-05-04 parameters\n",
      "\n",
      "---------------------------------------------------------------------------------------------------------------------------\n",
      "Date      Uncovered  Exposed  Du      Ru    Di      Ri  Apathetic  Da     Ra  Isolated  Infected\n",
      "---------------------------------------------------------------------------------------------------------------------------\n",
      "2020-05-05   14142   62764   2122   12020   7410   41990   12105   1632   10291   1693   49400\n",
      "2020-05-06   15563   67158   2390   13176   8074   44477   13923   1878   11587   1830   52552\n",
      "2020-05-07   17122   71662   2686   14450   8782   47123   16015   2148   13012   1978   55905\n",
      "2020-05-08   18830   76208   3011   15850   9534   49937   18421   2446   14581   2139   59472\n",
      "2020-05-09   20703   80704   3369   17391   10335   52932   21189   2774   16306   2312   63267\n",
      "2020-05-10   22753   85022   3762   19085   11186   56117   24373   3134   18202   2500   67304\n",
      "2020-05-11   24996   88998   4194   20946   12092   59506   28035   3529   20286   2703   71598\n",
      "2020-05-12   27449   92412   4669   22991   13056   63110   32247   3964   22576   2922   76166\n",
      "2020-05-13   30129   94984   5190   25237   14081   66945   37092   4441   25090   3159   81026\n",
      "2020-05-14   33055   96354   5762   27701   15171   71025   42664   4965   27850   3415   86196\n",
      "2020-05-15   36249   96063   6390   30406   16331   75365   49074   5540   30878   3692   91696\n",
      "2020-05-16   39731   93534   7078   33371   17566   79981   56447   6170   34198   3991   97547\n",
      "2020-05-17   43525   88040   7833   36622   18878   84893   64928   6861   37838   4315   103772\n",
      "2020-05-18   47658   78675   8660   40182   20275   90117   74683   7618   41825   4665   110393\n",
      "2020-05-19   52157   64309   9565   44081   21761   95675   85904   8447   46190   5043   117437\n",
      "---------------------------------------------------------------------------------------------------------------\n",
      "\n",
      "\n",
      "Predictions using 2020-05-05 parameters\n",
      "\n",
      "---------------------------------------------------------------------------------------------------------------------------\n",
      "Date      Uncovered  Exposed  Du      Ru    Di      Ri  Apathetic  Da     Ra  Isolated  Infected\n",
      "---------------------------------------------------------------------------------------------------------------------------\n",
      "2020-05-05   14142   62764   2122   12020   7410   41990   11671   1592   10079   1693   49400\n",
      "2020-05-06   15331   67453   2291   13040   7916   45071   12836   1745   11148   1785   52987\n",
      "2020-05-07   16615   72433   2474   14145   8458   48375   14117   1912   12308   1881   56834\n",
      "2020-05-08   18003   77707   2672   15344   9040   51920   15526   2093   13565   1984   60961\n",
      "2020-05-09   19500   83269   2887   16642   9665   55722   17076   2289   14928   2092   65387\n",
      "2020-05-10   21116   89108   3120   18049   10335   59800   18781   2501   16403   2205   70135\n",
      "2020-05-11   22857   95204   3373   19572   11053   64174   20656   2731   18001   2325   75228\n",
      "2020-05-12   24733   101524   3646   21220   11824   68866   22718   2980   19730   2452   80690\n",
      "2020-05-13   26753   108021   3942   23004   12650   73899   24986   3249   21601   2585   86549\n",
      "2020-05-14   28926   114629   4261   24934   13537   79297   27481   3540   23625   2725   92834\n",
      "2020-05-15   31261   121260   4607   27020   14487   85087   30224   3855   25814   2873   99575\n",
      "2020-05-16   33769   127795   4980   29275   15507   91297   33241   4195   28179   3030   106805\n",
      "2020-05-17   36461   134080   5384   31711   16601   97958   36560   4562   30734   3194   114560\n",
      "2020-05-18   39346   139919   5820   34340   17775   105103   40209   4959   33492   3368   122879\n",
      "2020-05-19   42436   145061   6290   37178   19033   112767   44223   5387   36469   3551   131801\n",
      "---------------------------------------------------------------------------------------------------------------\n",
      "\n",
      "\n",
      "Predictions using 2020-05-06 parameters\n",
      "\n",
      "---------------------------------------------------------------------------------------------------------------------------\n",
      "Date      Uncovered  Exposed  Du      Ru    Di      Ri  Apathetic  Da     Ra  Isolated  Infected\n",
      "---------------------------------------------------------------------------------------------------------------------------\n",
      "2020-05-26   85751   -54834   13867   76477   28082   153391   158364   12200   80564   5540   181474\n",
      "2020-05-06   15331   67453   2291   13040   7916   45071   12681   1719   10962   1785   52987\n",
      "2020-05-07   16776   72197   2514   14262   8444   47907   14387   1920   12302   1889   56351\n",
      "2020-05-08   18351   77132   2758   15599   9005   50923   16323   2141   13769   1999   59928\n",
      "2020-05-09   20069   82219   3024   17061   9602   54130   18519   2383   15374   2115   63733\n",
      "2020-05-10   21939   87401   3316   18661   10237   57541   21011   2647   17129   2238   67779\n",
      "2020-05-11   23976   92603   3636   20410   10913   61169   23838   2936   19048   2369   72082\n",
      "2020-05-12   26191   97719   3984   22321   11631   65027   27046   3252   21145   2507   76658\n",
      "2020-05-13   28599   102612   4365   24409   12395   69130   30685   3597   23435   2653   81525\n",
      "2020-05-14   31215   107105   4781   26688   13207   73493   34814   3974   25937   2807   86701\n",
      "2020-05-15   34054   110967   5235   29176   14071   78134   39498   4385   28667   2971   92206\n",
      "2020-05-16   37134   113909   5731   31891   14990   83069   44813   4833   31645   3144   98060\n",
      "2020-05-17   40471   115560   6271   34851   15967   88318   50842   5322   34892   3327   104285\n",
      "2020-05-18   44086   115462   6859   38077   17006   93899   57684   5855   38432   3521   110906\n",
      "2020-05-19   47997   113039   7501   41591   18111   99835   65445   6436   42287   3726   117947\n",
      "---------------------------------------------------------------------------------------------------------------\n",
      "\n",
      "\n",
      "Predictions using 2020-05-07 parameters\n",
      "\n",
      "---------------------------------------------------------------------------------------------------------------------------\n",
      "Date      Uncovered  Exposed  Du      Ru    Di      Ri  Apathetic  Da     Ra  Isolated  Infected\n",
      "---------------------------------------------------------------------------------------------------------------------------\n",
      "2020-05-26   54182   176077   8385   47685   25212   143284   56053   7157   46931   4844   168496\n",
      "2020-05-27   57421   178540   8921   50737   26707   151788   60308   7638   50114   5090   178495\n",
      "2020-05-07   16776   72197   2514   14262   8444   47907   13957   1886   12071   1889   56351\n",
      "2020-05-08   17887   76581   2680   15207   8944   50751   15016   2035   13056   1985   59695\n",
      "2020-05-09   19067   81191   2856   16214   9473   53763   16156   2193   14107   2085   63237\n",
      "2020-05-10   20322   86030   3045   17288   10034   56955   17383   2363   15227   2191   66990\n",
      "2020-05-11   21655   91098   3246   18433   10629   60336   18702   2543   16421   2303   70965\n",
      "2020-05-12   23070   96391   3461   19653   11258   63917   20122   2736   17694   2420   75176\n",
      "2020-05-13   24571   101904   3689   20952   11925   67711   21650   2941   19049   2543   79637\n",
      "2020-05-14   26163   107625   3932   22337   12632   71731   23294   3159   20493   2672   84363\n",
      "2020-05-15   27851   113537   4191   23810   13381   75989   25062   3392   22030   2808   89370\n",
      "2020-05-16   29640   119617   4466   25379   14174   80499   26965   3639   23666   2951   94673\n",
      "2020-05-17   31534   125835   4760   27049   15014   85277   29012   3902   25408   3101   100291\n",
      "2020-05-18   33538   132147   5072   28825   15903   90339   31215   4182   27260   3258   106243\n",
      "2020-05-19   35658   138503   5404   30714   16846   95701   33585   4480   29231   3424   112547\n",
      "---------------------------------------------------------------------------------------------------------------\n",
      "\n",
      "\n",
      "Predictions using 2020-05-08 parameters\n",
      "\n",
      "---------------------------------------------------------------------------------------------------------------------------\n",
      "Date      Uncovered  Exposed  Du      Ru    Di      Ri  Apathetic  Da     Ra  Isolated  Infected\n",
      "---------------------------------------------------------------------------------------------------------------------------\n",
      "2020-05-26   66815   112468   6901   62441   17382   154397   91183   3626   66227   5517   149047\n",
      "2020-05-27   71603   99019   7334   67290   18116   163413   100837   3792   71702   5839   156819\n",
      "2020-05-28   76701   80585   7798   72486   18889   172899   111513   3969   77569   6181   164997\n",
      "2020-05-08   17887   76581   2680   15207   8944   50751   14901   2010   12891   1985   59695\n",
      "2020-05-09   19301   81068   2796   16505   9238   54362   16478   2054   14356   2101   62808\n",
      "2020-05-10   20821   85718   2921   17905   9547   58161   18223   2102   15938   2223   66083\n",
      "2020-05-11   22455   90510   3056   19416   9872   62158   20152   2154   17644   2353   69529\n",
      "2020-05-12   24211   95413   3201   21046   10215   66364   22286   2209   19484   2491   73155\n",
      "2020-05-13   26097   100386   3358   22803   10575   70789   24645   2269   21468   2636   76970\n",
      "2020-05-14   28120   105374   3528   24696   10954   75445   27255   2334   23606   2790   80984\n",
      "2020-05-15   30290   110309   3710   26737   11353   80344   30140   2404   25910   2954   85207\n",
      "2020-05-16   32616   115102   3906   28935   11773   85498   33331   2479   28392   3126   89650\n",
      "2020-05-17   35108   119643   4118   31302   12214   90921   36860   2560   31065   3309   94325\n",
      "2020-05-18   37776   123795   4346   33850   12679   96627   40763   2647   33942   3502   99244\n",
      "2020-05-19   40630   127386   4591   36591   13167   102631   45079   2741   37037   3707   104420\n",
      "---------------------------------------------------------------------------------------------------------------\n",
      "\n",
      "\n",
      "Predictions using 2020-05-09 parameters\n",
      "\n",
      "---------------------------------------------------------------------------------------------------------------------------\n",
      "Date      Uncovered  Exposed  Du      Ru    Di      Ri  Apathetic  Da     Ra  Isolated  Infected\n",
      "---------------------------------------------------------------------------------------------------------------------------\n",
      "2020-05-26   98395   157948   8030   94035   20396   97711   50797   7807   49854   7207   137265\n",
      "2020-05-27   107753   161281   8678   103624   21364   101472   54338   8519   54275   7749   143725\n",
      "2020-05-28   117911   164019   9387   114125   22378   105410   58125   9299   59116   8331   150489\n",
      "2020-05-29   128923   166025   10162   125617   23439   109534   62176   10153   64414   8958   157572\n",
      "2020-05-09   19301   81068   2796   16505   9238   54362   16159   2047   14112   2101   62808\n",
      "2020-05-10   21309   85025   2923   18386   9681   56083   17285   2186   14979   2259   65764\n",
      "2020-05-11   23519   89127   3063   20462   10144   57884   18489   2341   15936   2428   68859\n",
      "2020-05-12   25950   93371   3217   22754   10630   59771   19778   2511   16993   2611   72099\n",
      "2020-05-13   28624   97752   3388   25283   11139   61747   21157   2699   18159   2807   75493\n",
      "2020-05-14   31563   102260   3577   28073   11671   63815   22631   2906   19445   3019   79046\n",
      "2020-05-15   34790   106886   3784   31149   12229   65981   24209   3135   20863   3246   82766\n",
      "2020-05-16   38333   111616   4013   34540   12812   68249   25896   3386   22426   3490   86661\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2020-05-17   42220   116432   4265   38275   13424   70624   27701   3664   24148   3752   90740\n",
      "2020-05-18   46480   121312   4543   42390   14064   73110   29631   3970   26045   4034   95011\n",
      "2020-05-19   51147   126228   4849   46920   14734   75714   31697   4306   28133   4338   99482\n",
      "---------------------------------------------------------------------------------------------------------------\n",
      "\n",
      "\n",
      "Predictions using 2020-05-10 parameters\n",
      "\n",
      "---------------------------------------------------------------------------------------------------------------------------\n",
      "Date      Uncovered  Exposed  Du      Ru    Di      Ri  Apathetic  Da     Ra  Isolated  Infected\n",
      "---------------------------------------------------------------------------------------------------------------------------\n",
      "2020-05-26   39370   209427   6579   33512   17144   154981   36488   6010   37615   5833   172125\n",
      "2020-05-27   40828   219929   6889   34796   17892   164900   38272   6336   39549   6190   182793\n",
      "2020-05-28   42327   230548   7211   36128   18687   175435   40143   6675   41554   6568   194122\n",
      "2020-05-29   43866   241188   7545   37508   19531   186622   42105   7026   43633   6969   206154\n",
      "2020-05-30   45446   251729   7891   38939   20428   198503   44164   7390   45787   7395   218931\n",
      "2020-05-10   21309   85025   2923   18386   9681   56083   17002   2164   14838   2259   65764\n",
      "2020-05-11   22172   90215   3091   19081   9967   59873   17833   2340   15884   2397   69840\n",
      "2020-05-12   23066   95709   3265   19804   10270   63897   18704   2524   16973   2543   74168\n",
      "2020-05-13   23994   101522   3447   20556   10593   68172   19619   2715   18106   2698   78765\n",
      "2020-05-14   24955   107665   3636   21339   10935   72711   20578   2914   19284   2863   83647\n",
      "2020-05-15   25950   114153   3833   22152   11299   77532   21584   3121   20510   3038   88831\n",
      "2020-05-16   26981   120995   4038   22999   11685   82651   22639   3337   21784   3224   94337\n",
      "2020-05-17   28047   128202   4250   23879   12096   88088   23746   3560   23109   3421   100184\n",
      "2020-05-18   29151   135781   4472   24794   12531   93861   24907   3793   24487   3630   106393\n",
      "2020-05-19   30291   143738   4701   25744   12994   99993   26125   4035   25919   3851   112987\n",
      "---------------------------------------------------------------------------------------------------------------\n",
      "\n",
      "\n",
      "Predictions using 2020-05-11 parameters\n",
      "\n",
      "---------------------------------------------------------------------------------------------------------------------------\n",
      "Date      Uncovered  Exposed  Du      Ru    Di      Ri  Apathetic  Da     Ra  Isolated  Infected\n",
      "---------------------------------------------------------------------------------------------------------------------------\n",
      "2020-05-26   32438   217704   7337   25496   20659   165193   36570   4667   36467   4559   185852\n",
      "2020-05-27   33227   228516   7681   26015   21814   176569   38343   4858   38150   4759   198383\n",
      "2020-05-28   34027   239238   8033   26547   23046   188712   40202   5054   39875   4968   211759\n",
      "2020-05-29   34839   249704   8394   27092   24362   201674   42151   5255   41641   5185   226037\n",
      "2020-05-30   35661   259706   8763   27650   25767   215510   44194   5460   43449   5412   241278\n",
      "2020-05-31   36494   268992   9141   28221   27266   230279   46337   5670   45299   5650   257546\n",
      "2020-05-11   22172   90215   3091   19081   9967   59873   17978   2305   15673   2397   69840\n",
      "2020-05-12   22762   96068   3326   19436   10401   64148   18849   2435   16823   2502   74549\n",
      "2020-05-13   23365   102278   3567   19800   10864   68711   19763   2569   18004   2611   79575\n",
      "2020-05-14   23982   108859   3814   20174   11358   73582   20721   2707   19217   2725   84940\n",
      "2020-05-15   24612   115825   4069   20558   11886   78781   21725   2849   20462   2845   90668\n",
      "2020-05-16   25257   123186   4329   20952   12450   84331   22779   2994   21739   2970   96781\n",
      "2020-05-17   25914   130952   4597   21357   13051   90255   23883   3143   23050   3100   103307\n",
      "2020-05-18   26586   139127   4872   21771   13693   96579   25041   3295   24395   3235   110272\n",
      "2020-05-19   27271   147712   5154   22197   14378   103329   26255   3452   25774   3377   117707\n",
      "---------------------------------------------------------------------------------------------------------------\n",
      "\n",
      "\n",
      "Predictions using 2020-05-12 parameters\n",
      "\n",
      "---------------------------------------------------------------------------------------------------------------------------\n",
      "Date      Uncovered  Exposed  Du      Ru    Di      Ri  Apathetic  Da     Ra  Isolated  Infected\n",
      "---------------------------------------------------------------------------------------------------------------------------\n",
      "2020-05-26   36474   230070   6026   31014   22296   173694   35069   4777   37351   6149   195991\n",
      "2020-05-27   37652   242412   6271   32065   23669   186332   36636   4991   39235   6557   210001\n",
      "2020-05-28   38856   254710   6524   33150   25139   199873   38273   5213   41179   6993   225012\n",
      "2020-05-29   40084   266767   6785   34270   26715   214382   39984   5442   43186   7456   241097\n",
      "2020-05-30   41336   278336   7055   35425   28403   229928   41770   5678   45255   7951   258332\n",
      "2020-05-31   42612   289111   7333   36617   30212   246586   43637   5922   47390   8479   276798\n",
      "2020-06-01   43909   298717   7619   37845   32150   264434   45587   6173   49590   9041   296584\n",
      "2020-05-12   22762   96068   3326   19436   10401   64148   19017   2411   16606   2502   74549\n",
      "2020-05-13   23571   102657   3479   20092   10923   68955   19866   2545   17781   2668   79878\n",
      "2020-05-14   24405   109674   3637   20771   11482   74105   20754   2683   18998   2845   85587\n",
      "2020-05-15   25264   117139   3801   21474   12081   79624   21681   2827   20258   3033   91706\n",
      "2020-05-16   26150   125069   3971   22202   12723   85537   22650   2976   21563   3235   98261\n",
      "2020-05-17   27062   133477   4147   22956   13411   91873   23662   3130   22913   3449   105285\n",
      "2020-05-18   28000   142376   4328   23736   14149   98662   24720   3289   24311   3678   112811\n",
      "2020-05-19   28965   151770   4517   24543   14938   105936   25824   3454   25757   3922   120875\n",
      "---------------------------------------------------------------------------------------------------------------\n",
      "\n",
      "\n",
      "Predictions using 2020-05-13 parameters\n",
      "\n",
      "---------------------------------------------------------------------------------------------------------------------------\n",
      "Date      Uncovered  Exposed  Du      Ru    Di      Ri  Apathetic  Da     Ra  Isolated  Infected\n",
      "---------------------------------------------------------------------------------------------------------------------------\n",
      "2020-05-26   49839   194932   5781   44933   18828   139464   35074   5354   36703   5021   158292\n",
      "2020-05-27   52672   203802   6039   47715   19690   147153   36607   5672   38844   5271   166843\n",
      "2020-05-28   55641   212820   6312   50656   20598   155258   38208   6007   41107   5534   175856\n",
      "2020-05-29   58753   221935   6600   53763   21556   163800   39878   6361   43497   5810   185356\n",
      "2020-05-30   62011   231085   6904   57043   22565   172803   41621   6735   46021   6100   195369\n",
      "2020-05-31   65418   240196   7225   60505   23629   182293   43440   7130   48685   6404   205923\n",
      "2020-06-01   68979   249177   7564   64158   24751   192296   45339   7546   51496   6723   217047\n",
      "2020-06-02   72697   257920   7921   68009   25933   202838   47321   7985   54459   7058   228772\n",
      "2020-05-13   23571   102657   3479   20092   10923   68955   20111   2523   17588   2668   79878\n",
      "2020-05-14   25009   108097   3601   21408   11358   72835   20990   2673   18600   2801   84193\n",
      "2020-05-15   26528   113802   3730   22804   11816   76924   21907   2832   19675   2940   88741\n",
      "2020-05-16   28134   119780   3867   24285   12299   81235   22865   3001   20814   3087   93534\n",
      "2020-05-17   29829   126036   4013   25856   12809   85778   23864   3180   22023   3241   98587\n",
      "2020-05-18   31619   132577   4167   27521   13346   90567   24908   3369   23305   3402   103913\n",
      "2020-05-19   33507   139404   4331   29287   13911   95614   25996   3571   24663   3572   109526\n",
      "---------------------------------------------------------------------------------------------------------------\n",
      "\n",
      "\n"
     ]
    }
   ],
   "source": [
    "for z in range(1, len(last5_params)+1):\n",
    "    results = seird_model(last5_vals[z-1], last5_params[z-1], t7)\n",
    "    t_z = np.arange(7 - z, 22 - z, 1)\n",
    "    print(\"Predictions using\", last5_vals[z-1][0], \"parameters\\n\")\n",
    "    print(\"---------------------------------------------------------------------------------------------------------------------------\")\n",
    "    print(\"Date\", \" \",\" \",\" \" \"Uncovered\", \" \" \"Exposed\" , \" \" \"Du\", \" \",\" \",\" \" \"Ru\", \" \", \" \" \"Di\", \" \", \" \", \" \" \"Ri\", \" \" \"Apathetic\", \" \" \"Da\", \" \", \" \", \"Ra\", \" \" \"Isolated\", \" \" \"Infected\")\n",
    "    print(\"---------------------------------------------------------------------------------------------------------------------------\")\n",
    "    for day in t_z:\n",
    "        print(results[day][0],\" \",int(float(results[day][2])),\" \",int(float(results[day][3])),\" \", int(float(results[day][4])),\" \", int(float(results[day][5])), \" \", int(float(results[day][6])),\" \",int(float(results[day][7])),\" \",int(float(results[day][8])),\" \",int(float(results[day][9])), \" \", int(float(results[day][10])), \" \", int(float(results[day][11])), \" \", int(float(results[day][12])))\n",
    "    print(\"---------------------------------------------------------------------------------------------------------------\\n\\n\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "4912c23d",
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "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": "3.8.8"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 5
}