Modelo SIR.ipynb

{
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  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "using Plots\n",
    "gr()\n",
    "plot(rand(3), rand(3))\n",
    "nothing"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$$ y_{k+1} = y_k + \\delta f(t_k, y_k) $$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "euler (generic function with 2 methods)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "function euler(t0, y0 :: Real, f, tN, N)\n",
    "    δ = (tN - t0) / N\n",
    "    y = zeros(N + 1)\n",
    "    y[1] = y0\n",
    "    t = range(t0, tN, length=N+1)\n",
    "    for k = 1:N\n",
    "        y[k+1] = y[k] + δ * f(t[k], y[k])\n",
    "    end\n",
    "    return t, y\n",
    "end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 116,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "runge_kutta (generic function with 2 methods)"
      ]
     },
     "execution_count": 116,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "function runge_kutta(t0, y0 :: Real, f, tN, N)\n",
    "    δ = (tN - t0) / N\n",
    "    y = zeros(N + 1)\n",
    "    y[1] = y0\n",
    "    t = range(t0, tN, length=N+1)\n",
    "    for k = 1:N\n",
    "        k1 = f(t[k], y[k])\n",
    "        k2 = f(t[k] + 0.5, y[k] + δ * k1 / 2)\n",
    "        k3 = f(t[k] + 0.5, y[k] + δ * k2 / 2)\n",
    "        k4 = f(t[k+1], y[k] + δ * k3)\n",
    "        y[k+1] = y[k] + δ * (k1 + 2k2 + 2k3 + k4) / 6\n",
    "    end\n",
    "    return t, y\n",
    "end"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exemplo 1\n",
    "\n",
    "$$ y'(t) = y, \\qquad y(0) = 1 $$"
   ]
  },
  {
   "cell_type": "code",
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    "f(t,y) = y\n",
    "t0 = 0.0\n",
    "tN = 4.0\n",
    "y0 = 1.0\n",
    "N = 4\n",
    "t, y = euler(t0, y0, f, tN, N)\n",
    "plot(t -> exp(t), t0, tN, c=:blue)\n",
    "scatter!(t, y, ms=3, c=:red, leg=false)\n",
    "plot!(t, y, c=:red)\n",
    "t, y = runge_kutta(t0, y0, f, tN, N)\n",
    "scatter!(t, y, ms=3, c=:magenta, leg=false)\n",
    "plot!(t, y, c=:magenta)"
   ]
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     },
     "execution_count": 118,
     "metadata": {},
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    }
   ],
   "source": [
    "f(t,y) = y * (1 - y)\n",
    "t0 = 0.0\n",
    "tN = 9.0\n",
    "y0 = 0.01\n",
    "N = 50\n",
    "t, y = euler(t0, y0, f, tN, N)\n",
    "#plot(t -> exp(t), t0, tN, c=:blue)\n",
    "scatter(t, y, ms=3, c=:red, leg=false)\n",
    "plot!(t, y, c=:red)\n",
    "t, y = runge_kutta(t0, y0, f, tN, N)\n",
    "scatter!(t, y, ms=3, c=:magenta, leg=false)\n",
    "plot!(t, y, c=:magenta)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "euler (generic function with 3 methods)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "function euler(t0, y0 :: Vector, f, tN, N)\n",
    "    δ = (tN - t0) / N\n",
    "    m = length(y0)\n",
    "    y = zeros(m, N + 1)\n",
    "    y[:,1] = y0\n",
    "    t = range(t0, tN, length=N+1)\n",
    "    for k = 1:N\n",
    "        y[:,k+1] = y[:,k] + δ * f(t[k], y[:,k])\n",
    "    end\n",
    "    return t, y\n",
    "end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "runge_kutta (generic function with 2 methods)"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "function runge_kutta(t0, y0 :: Vector, f, tN, N)\n",
    "    δ = (tN - t0) / N\n",
    "    m = length(y0)\n",
    "    y = zeros(m, N + 1)\n",
    "    y[:,1] = y0\n",
    "    t = range(t0, tN, length=N+1)\n",
    "    for k = 1:N\n",
    "        k1 = f(t[k], y[:,k])\n",
    "        k2 = f(t[k] + 0.5, y[:,k] + δ * k1 / 2)\n",
    "        k3 = f(t[k] + 0.5, y[:,k] + δ * k2 / 2)\n",
    "        k4 = f(t[k+1], y[:,k] + δ * k3)\n",
    "        y[:,k+1] = y[:,k] + δ * (k1 + 2k2 + 2k3 + k4) / 6\n",
    "    end\n",
    "    return t, y\n",
    "end"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Presa-presador\n",
    "\n",
    "- $x$ - presa\n",
    "- $y$ - predador\n",
    "\n",
    "$$ x'(t) = \\alpha x(t) - \\beta x(t) y(t) $$\n",
    "$$ y'(t) = \\delta x(t) y(t) - \\gamma y(t) $$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┌ Info: Saved animation to \n",
      "│   fn = /home/abel/Documents/aulas/notebooks/presa-predador-1.gif\n",
      "└ @ Plots /home/abel/.julia/packages/Plots/qZHsp/src/animation.jl:98\n"
     ]
    },
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\" />"
      ],
      "text/plain": [
       "Plots.AnimatedGif(\"/home/abel/Documents/aulas/notebooks/presa-predador-1.gif\")"
      ]
     },
     "execution_count": 27,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y0 = [3.0; 1.0]\n",
    "t0 = 0.0\n",
    "tf = 20.0\n",
    "α = 1.0\n",
    "β = 0.5\n",
    "γ = 0.5\n",
    "δ = 0.75\n",
    "N = 1000\n",
    "\n",
    "F(t, y) = [α * y[1] - β * y[1] * y[2]; γ * y[1] * y[2] - δ * y[2]]\n",
    "t, Y = euler(t0, y0, F, tf, N)\n",
    "\n",
    "anim = Animation()\n",
    "for i = 1:4:N\n",
    "    layout = @layout [a b]\n",
    "    p = plot(size=(800,300), layout=layout)\n",
    "    xi, yi = Y[:,i]\n",
    "    plot!(p[1], Y[1,1:i], Y[2,1:i], c=:black, leg=false)\n",
    "    scatter!(p[1], [xi], [yi], c=:black, ms=5)\n",
    "    xlabel!(p[1], \"Coelhos\")\n",
    "    ylabel!(p[1], \"Raposas\")\n",
    "    xlims!(p[1], 0, maximum(Y[1,:]) + 0.5)\n",
    "    ylims!(p[1], 0, maximum(Y[2,:]) + 0.5)\n",
    "    plot!(p[2], t[1:i], Y[1,1:i], c=:red, lab=\"Coelhos\")\n",
    "    plot!(p[2], t[1:i], Y[2,1:i], c=:blue, lab=\"Raposas\")\n",
    "    xlims!(p[2], 0, t[end])\n",
    "    ylims!(p[2], 0, maximum(Y) + 2.5)\n",
    "    xlabel!(p[2], \"Tempo\")\n",
    "    frame(anim)\n",
    "end\n",
    "gif(anim, \"presa-predador-1.gif\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┌ Info: Saved animation to \n",
      "│   fn = /home/abel/Documents/aulas/notebooks/presa-predador-1.gif\n",
      "└ @ Plots /home/abel/.julia/packages/Plots/qZHsp/src/animation.jl:98\n"
     ]
    },
    {
     "data": {
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\" />"
      ],
      "text/plain": [
       "Plots.AnimatedGif(\"/home/abel/Documents/aulas/notebooks/presa-predador-1.gif\")"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "y0 = [3.0; 1.0]\n",
    "t0 = 0.0\n",
    "tf = 20.0\n",
    "α = 1.0\n",
    "β = 0.5\n",
    "γ = 0.5\n",
    "δ = 0.75\n",
    "N = 200\n",
    "\n",
    "F(t, y) = [α * y[1] - β * y[1] * y[2]; γ * y[1] * y[2] - δ * y[2]]\n",
    "t, Y = runge_kutta(t0, y0, F, tf, N)\n",
    "\n",
    "anim = Animation()\n",
    "for i = 1:N\n",
    "    layout = @layout [a b]\n",
    "    p = plot(size=(800,300), layout=layout)\n",
    "    xi, yi = Y[:,i]\n",
    "    plot!(p[1], Y[1,1:i], Y[2,1:i], c=:black, leg=false)\n",
    "    scatter!(p[1], [xi], [yi], c=:black, ms=5)\n",
    "    xlabel!(p[1], \"Coelhos\")\n",
    "    ylabel!(p[1], \"Raposas\")\n",
    "    xlims!(p[1], 0, maximum(Y[1,:]) + 0.5)\n",
    "    ylims!(p[1], 0, maximum(Y[2,:]) + 0.5)\n",
    "    plot!(p[2], t[1:i], Y[1,1:i], c=:red, lab=\"Coelhos\")\n",
    "    plot!(p[2], t[1:i], Y[2,1:i], c=:blue, lab=\"Raposas\")\n",
    "    xlims!(p[2], 0, t[end])\n",
    "    ylims!(p[2], 0, maximum(Y) + 2.5)\n",
    "    xlabel!(p[2], \"Tempo\")\n",
    "    frame(anim)\n",
    "end\n",
    "gif(anim, \"presa-predador-1.gif\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Modelo SIR"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$$ \\begin{align}\n",
    "S'(t) & = -\\frac{\\beta}{T} I S \\\\\n",
    "I'(t) & = \\frac{\\beta}{T} I S - \\gamma I \\\\\n",
    "R'(t) & = \\gamma I\n",
    "\\end{align} $$"
   ]
  },
  {
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   "source": [
    "T = 1000.0\n",
    "β = 0.3\n",
    "γ = 0.1\n",
    "\n",
    "#y = [S, I, R]\n",
    "F(t,y) = [-β / T * y[2] * y[1]; \n",
    "           β / T * y[2] * y[1] - γ * y[2];\n",
    "           γ * y[2]]\n",
    "\n",
    "t0 = 0.0\n",
    "y0 = [T - 1; 1.0; 0.0]\n",
    "tf = 60.0\n",
    "N = 100\n",
    "t, y = runge_kutta(t0, y0, F, tf, N)\n",
    "plot(t, y[1,:], c=:blue, lab=\"S\", legend=:right)\n",
    "plot!(t, y[2,:], c=:green, lab=\"I\")\n",
    "plot!(t, y[3,:], c=:red, lab=\"R\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "search: \u001b[0m\u001b[1md\u001b[22m\u001b[0m\u001b[1mo\u001b[22m\u001b[0m\u001b[1mw\u001b[22m\u001b[0m\u001b[1mn\u001b[22m\u001b[0m\u001b[1ml\u001b[22m\u001b[0m\u001b[1mo\u001b[22m\u001b[0m\u001b[1ma\u001b[22m\u001b[0m\u001b[1md\u001b[22m\n",
      "\n"
     ]
    },
    {
     "data": {
      "text/latex": [
       "\\begin{verbatim}\n",
       "download(url::AbstractString, [localfile::AbstractString])\n",
       "\\end{verbatim}\n",
       "Download a file from the given url, optionally renaming it to the given local file name. If no filename is given this will download into a randomly-named file in your temp directory. Note that this function relies on the availability of external tools such as \\texttt{curl}, \\texttt{wget} or \\texttt{fetch} to download the file and is provided for convenience. For production use or situations in which more options are needed, please use a package that provides the desired functionality instead.\n",
       "\n",
       "Returns the filename of the downloaded file.\n",
       "\n"
      ],
      "text/markdown": [
       "```\n",
       "download(url::AbstractString, [localfile::AbstractString])\n",
       "```\n",
       "\n",
       "Download a file from the given url, optionally renaming it to the given local file name. If no filename is given this will download into a randomly-named file in your temp directory. Note that this function relies on the availability of external tools such as `curl`, `wget` or `fetch` to download the file and is provided for convenience. For production use or situations in which more options are needed, please use a package that provides the desired functionality instead.\n",
       "\n",
       "Returns the filename of the downloaded file.\n"
      ],
      "text/plain": [
       "\u001b[36m  download(url::AbstractString, [localfile::AbstractString])\u001b[39m\n",
       "\n",
       "  Download a file from the given url, optionally renaming it to the given\n",
       "  local file name. If no filename is given this will download into a\n",
       "  randomly-named file in your temp directory. Note that this function relies\n",
       "  on the availability of external tools such as \u001b[36mcurl\u001b[39m, \u001b[36mwget\u001b[39m or \u001b[36mfetch\u001b[39m to\n",
       "  download the file and is provided for convenience. For production use or\n",
       "  situations in which more options are needed, please use a package that\n",
       "  provides the desired functionality instead.\n",
       "\n",
       "  Returns the filename of the downloaded file."
      ]
     },
     "execution_count": 55,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "?download"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 56,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "\"covid-full.csv\""
      ]
     },
     "execution_count": 56,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "download(\"https://github.com/datasets/covid-19/blob/master/data/time-series-19-covid-combined.csv?raw=true\", \"covid-full.csv\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"data-frame\"><thead><tr><th></th><th>Date</th><th>Country/Region</th><th>Province/State</th><th>Lat</th><th>Long</th><th>Confirmed</th><th>Recovered</th></tr><tr><th></th><th>Dates…</th><th>String</th><th>String⍰</th><th>Float64</th><th>Float64</th><th>Int64</th><th>Int64</th></tr></thead><tbody><p>5 rows × 8 columns (omitted printing of 1 columns)</p><tr><th>1</th><td>2020-01-22</td><td>Thailand</td><td>missing</td><td>15.0</td><td>101.0</td><td>2</td><td>0</td></tr><tr><th>2</th><td>2020-01-23</td><td>Thailand</td><td>missing</td><td>15.0</td><td>101.0</td><td>3</td><td>0</td></tr><tr><th>3</th><td>2020-01-24</td><td>Thailand</td><td>missing</td><td>15.0</td><td>101.0</td><td>5</td><td>0</td></tr><tr><th>4</th><td>2020-01-25</td><td>Thailand</td><td>missing</td><td>15.0</td><td>101.0</td><td>7</td><td>0</td></tr><tr><th>5</th><td>2020-01-26</td><td>Thailand</td><td>missing</td><td>15.0</td><td>101.0</td><td>8</td><td>2</td></tr></tbody></table>"
      ],
      "text/latex": [
       "\\begin{tabular}{r|cccccccc}\n",
       "\t& Date & Country/Region & Province/State & Lat & Long & Confirmed & Recovered & \\\\\n",
       "\t\\hline\n",
       "\t& Dates… & String & String⍰ & Float64 & Float64 & Int64 & Int64 & \\\\\n",
       "\t\\hline\n",
       "\t1 & 2020-01-22 & Thailand &  & 15.0 & 101.0 & 2 & 0 & $\\dots$ \\\\\n",
       "\t2 & 2020-01-23 & Thailand &  & 15.0 & 101.0 & 3 & 0 & $\\dots$ \\\\\n",
       "\t3 & 2020-01-24 & Thailand &  & 15.0 & 101.0 & 5 & 0 & $\\dots$ \\\\\n",
       "\t4 & 2020-01-25 & Thailand &  & 15.0 & 101.0 & 7 & 0 & $\\dots$ \\\\\n",
       "\t5 & 2020-01-26 & Thailand &  & 15.0 & 101.0 & 8 & 2 & $\\dots$ \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "5×8 DataFrame. Omitted printing of 3 columns\n",
       "│ Row │ Date       │ Country/Region │ Province/State │ Lat     │ Long    │\n",
       "│     │ \u001b[90mDates.Date\u001b[39m │ \u001b[90mString\u001b[39m         │ \u001b[90mString⍰\u001b[39m        │ \u001b[90mFloat64\u001b[39m │ \u001b[90mFloat64\u001b[39m │\n",
       "├─────┼────────────┼────────────────┼────────────────┼─────────┼─────────┤\n",
       "│ 1   │ 2020-01-22 │ Thailand       │ \u001b[90mmissing\u001b[39m        │ 15.0    │ 101.0   │\n",
       "│ 2   │ 2020-01-23 │ Thailand       │ \u001b[90mmissing\u001b[39m        │ 15.0    │ 101.0   │\n",
       "│ 3   │ 2020-01-24 │ Thailand       │ \u001b[90mmissing\u001b[39m        │ 15.0    │ 101.0   │\n",
       "│ 4   │ 2020-01-25 │ Thailand       │ \u001b[90mmissing\u001b[39m        │ 15.0    │ 101.0   │\n",
       "│ 5   │ 2020-01-26 │ Thailand       │ \u001b[90mmissing\u001b[39m        │ 15.0    │ 101.0   │"
      ]
     },
     "execution_count": 60,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "using CSV, DataFrames\n",
    "data = CSV.read(\"covid-full.csv\")\n",
    "first(data, 5)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 193,
   "metadata": {},
   "outputs": [
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    "df = data[findall(data[!,Symbol(\"Country/Region\")] .== \"Brazil\"),:]\n",
    "\n",
    "C = df.Confirmed\n",
    "idx = findfirst(C .≥ 100)\n",
    "C = C[idx:end]\n",
    "R = df.Recovered[idx:end] + df.Deaths[idx:end]\n",
    "scatter(C)\n",
    "scatter!(R)"
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  {
   "cell_type": "code",
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     "execution_count": 194,
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   "source": [
    "T = 60_000_000\n",
    "β = 0.30\n",
    "γ = 0.08\n",
    "\n",
    "#y = [S, I, R]\n",
    "F(t,y) = [-β / T * y[2] * y[1]; \n",
    "           β / T * y[2] * y[1] - γ * y[2];\n",
    "           γ * y[2]]\n",
    "\n",
    "t0 = 0.0\n",
    "y0 = [T - 100; 100.0; 0.0]\n",
    "tf = length(C)\n",
    "N = length(C)\n",
    "t, y = runge_kutta(t0, y0, F, tf, N)\n",
    "#plot(t, y[1,:], c=:blue, lab=\"S\", legend=:right)\n",
    "scatter(C, c=:green)\n",
    "scatter!(R, c=:red)\n",
    "plot!(t, y[2,:], c=:green, lab=\"I\")\n",
    "plot!(t, y[3,:], c=:red, lab=\"R\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Otimização sem derivada para encontrar os parâmetros da EDO"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 109,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
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      "\u001b[32m\u001b[1m  Updating\u001b[22m\u001b[39m registry at `~/.julia/registries/General`\n",
      "\u001b[32m\u001b[1m  Updating\u001b[22m\u001b[39m git-repo `https://github.com/JuliaRegistries/General.git`\n",
      "\u001b[2K\u001b[?25h[1mFetching:\u001b[22m\u001b[39m [========================================>]  100.0 %.0 %\u001b[32m\u001b[1m  Updating\u001b[22m\u001b[39m git-repo `https://github.com/CiDAMO/DerivativeFreeSolvers.jl`\n",
      "\u001b[2K\u001b[?25h[1mFetching:\u001b[22m\u001b[39m [========================================>]  100.0 %.0 %\u001b[32m\u001b[1m  Updating\u001b[22m\u001b[39m git-repo `https://github.com/CiDAMO/DerivativeFreeSolvers.jl`\n",
      "\u001b[?25l\u001b[2K\u001b[?25h\u001b[32m\u001b[1m Resolving\u001b[22m\u001b[39m package versions...\n",
      "\u001b[32m\u001b[1m  Updating\u001b[22m\u001b[39m `~/.julia/environments/v1.3/Project.toml`\n",
      " \u001b[90m [704b706e]\u001b[39m\u001b[92m + DerivativeFreeSolvers v0.1.0 #master (https://github.com/CiDAMO/DerivativeFreeSolvers.jl)\u001b[39m\n",
      "\u001b[32m\u001b[1m  Updating\u001b[22m\u001b[39m `~/.julia/environments/v1.3/Manifest.toml`\n",
      " \u001b[90m [704b706e]\u001b[39m\u001b[92m + DerivativeFreeSolvers v0.1.0 #master (https://github.com/CiDAMO/DerivativeFreeSolvers.jl)\u001b[39m\n",
      " \u001b[90m [e30172f5]\u001b[39m\u001b[93m ↑ Documenter v0.24.6 ⇒ v0.24.7\u001b[39m\n",
      " \u001b[90m [1914dd2f]\u001b[39m\u001b[93m ↑ MacroTools v0.5.4 ⇒ v0.5.5\u001b[39m\n"
     ]
    }
   ],
   "source": [
    "using Pkg\n",
    "pkg\"add https://github.com/CiDAMO/DerivativeFreeSolvers.jl\""
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 155,
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     "execution_count": 155,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "t = range(0, 1, length=5)\n",
    "y = exp.(t) + randn(5) * 0.1\n",
    "scatter(t, y, leg=false)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "$$ y'(t) = \\alpha y(t) \\qquad y'(0) = y_0. $$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "sqr (generic function with 1 method)"
      ]
     },
     "execution_count": 156,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# β₁ = y₀, β₂ = α\n",
    "function sqr(β)\n",
    "    f(t, y) = β[2] * y\n",
    "    t_rk, y_rk = runge_kutta(0.0, β[1], (t,y) -> β[2] * y, 1.0, 4)\n",
    "    SQR = 0.0\n",
    "    for i = 1:5\n",
    "        SQR += (y[i] - y_rk[i])^2\n",
    "    end\n",
    "    return SQR / 2\n",
    "end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 131,
   "metadata": {},
   "outputs": [],
   "source": [
    "using DerivativeFreeSolvers, NLPModels\n",
    "\n",
    "mutable struct NLPSQR <: AbstractNLPModel\n",
    "    meta :: NLPModelMeta\n",
    "    counters :: Counters\n",
    "end"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┌ Info:   iter      f(x)  ‖x₁ - xₙ₊₁‖  \n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:55\n",
      "┌ Info:      0   2.2e-02   5.0e-02\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:      1   2.2e-02   5.0e-02\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:      2   2.0e-02   4.0e-02\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:      3   1.8e-02   4.0e-02\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:      4   1.8e-02   7.1e-02\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:      5   1.8e-02   1.1e-02\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:      6   1.8e-02   1.1e-02\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:      7   1.8e-02   3.1e-02\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:      8   1.8e-02   7.1e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:      9   1.8e-02   1.3e-02\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     10   1.8e-02   4.5e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     11   1.8e-02   9.7e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     12   1.8e-02   5.2e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     13   1.8e-02   4.8e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     14   1.8e-02   2.8e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     15   1.8e-02   6.9e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     16   1.8e-02   1.6e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     17   1.8e-02   4.7e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     18   1.8e-02   7.5e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     19   1.8e-02   3.9e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     20   1.8e-02   1.5e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     21   1.8e-02   2.8e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     22   1.8e-02   2.8e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     23   1.8e-02   6.3e-05\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     24   1.8e-02   2.0e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     25   1.8e-02   8.7e-05\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     26   1.8e-02   1.6e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     27   1.8e-02   7.9e-05\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     28   1.8e-02   8.1e-05\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     29   1.8e-02   5.9e-05\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     30   1.8e-02   4.3e-05\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     31   1.8e-02   3.0e-05\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     32   1.8e-02   1.9e-05\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     33   1.8e-02   1.9e-05\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     34   1.8e-02   1.0e-05\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     35   1.8e-02   7.4e-06\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     36   1.8e-02   5.0e-06\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     37   1.8e-02   7.1e-07\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     38   1.8e-02   3.3e-06\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     39   1.8e-02   3.3e-06\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     40   1.8e-02   2.5e-06\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     41   1.8e-02   2.3e-06\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     42   1.8e-02   7.9e-07\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     43   1.8e-02   7.9e-07\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     44   1.8e-02   4.8e-07\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     45   1.8e-02   4.4e-07\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     46   1.8e-02   1.9e-07\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     47   1.8e-02   1.5e-07\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     48   1.8e-02   8.2e-08\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     49   1.8e-02   1.0e-07\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     50   1.8e-02   6.2e-08\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     51   1.8e-02   2.8e-08\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     52   1.8e-02   4.1e-08\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     53   1.8e-02   3.5e-08\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     54   1.8e-02   3.5e-08\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n"
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    {
     "data": {
      "text/plain": [
       "\"Execution stats: solved to within acceptable tolerances\""
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     },
     "execution_count": 157,
     "metadata": {},
     "output_type": "execute_result"
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   "source": [
    "function NLPSQR()\n",
    "    return NLPSQR(NLPModelMeta(2, x0=[1.0; 1.0]), Counters())\n",
    "end\n",
    "\n",
    "function NLPModels.obj(nlp :: NLPSQR, β :: AbstractVector)\n",
    "    return sqr(β)\n",
    "end\n",
    "\n",
    "nlp = NLPSQR()\n",
    "output = nelder_mead(nlp)"
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  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {},
   "outputs": [
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     "execution_count": 159,
     "metadata": {},
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   ],
   "source": [
    "β = output.solution\n",
    "f(t, y) = β[2] * y\n",
    "scatter(t, y, c=:blue, ms=8)\n",
    "t_rk, y_rk = runge_kutta(t0, β[1], f, 1.0, 4)\n",
    "scatter!(t_rk, y_rk, c=:red)"
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  },
  {
   "cell_type": "code",
   "execution_count": 235,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
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     "text": [
      "┌ Info:   iter      f(x)  ‖x₁ - xₙ₊₁‖  \n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:55\n",
      "┌ Info:      0   1.3e+09   7.1e-02\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:      1   1.3e+09   2.4e-02\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:      2   1.3e+09   1.2e-02\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:      3   1.3e+09   6.0e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:      4   7.3e+08   1.4e-02\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:      5   6.3e+08   1.5e-02\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:      6   5.7e+08   1.1e-02\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:      7   5.7e+08   1.4e-02\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:      8   5.7e+08   7.8e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:      9   5.7e+08   9.3e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     10   5.7e+08   9.2e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     11   5.6e+08   7.6e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     12   5.6e+08   4.6e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     13   5.6e+08   3.7e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     14   5.5e+08   3.4e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     15   5.5e+08   4.8e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     16   5.5e+08   4.3e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     17   5.3e+08   8.0e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     18   5.3e+08   7.6e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     19   5.3e+08   7.0e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     20   5.3e+08   7.4e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     21   5.3e+08   5.9e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     22   5.2e+08   1.2e-02\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     23   5.0e+08   1.7e-02\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     24   5.0e+08   1.4e-02\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     25   5.0e+08   1.5e-02\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     26   5.0e+08   8.5e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     27   5.0e+08   1.5e-02\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     28   5.0e+08   4.2e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     29   5.0e+08   1.3e-02\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     30   5.0e+08   1.5e-02\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     31   5.0e+08   2.8e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     32   5.0e+08   1.4e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     33   5.0e+08   1.4e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     34   4.9e+08   4.5e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     35   4.9e+08   4.6e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     36   4.9e+08   2.8e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     37   4.9e+08   4.4e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     38   4.9e+08   3.1e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     39   4.9e+08   1.9e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     40   4.9e+08   3.0e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     41   4.9e+08   3.1e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     42   4.9e+08   1.2e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     43   4.9e+08   6.8e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     44   4.9e+08   8.6e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     45   4.9e+08   1.1e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     46   4.9e+08   1.1e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     47   4.9e+08   1.4e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     48   4.9e+08   3.8e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     49   4.9e+08   2.8e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     50   4.9e+08   5.0e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     51   4.9e+08   5.7e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     52   4.9e+08   5.3e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     53   4.9e+08   4.9e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     54   4.9e+08   3.6e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     55   4.9e+08   2.4e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     56   4.9e+08   2.4e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     57   4.9e+08   8.9e-05\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     58   4.9e+08   2.0e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     59   4.9e+08   3.0e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     60   4.9e+08   1.6e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     61   4.9e+08   2.2e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     62   4.9e+08   2.0e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     63   4.9e+08   6.3e-05\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     64   4.9e+08   1.6e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     65   4.9e+08   2.6e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     66   4.9e+08   8.9e-05\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     67   4.9e+08   2.2e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     68   4.9e+08   4.4e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     69   4.9e+08   3.8e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     70   4.9e+08   2.7e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┌ Info:     71   4.9e+08   6.5e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     72   4.9e+08   9.3e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     73   4.9e+08   8.2e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     74   4.9e+08   9.0e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     75   4.9e+08   1.8e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     76   4.9e+08   1.9e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     77   4.9e+08   2.1e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     78   4.9e+08   3.8e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     79   4.9e+08   5.0e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     80   4.9e+08   6.1e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     81   4.9e+08   5.7e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     82   4.9e+08   3.8e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     83   4.9e+08   1.1e-02\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     84   4.9e+08   9.0e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     85   4.9e+08   1.1e-02\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     86   4.9e+08   1.7e-02\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     87   4.9e+08   2.9e-02\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     88   4.9e+08   2.8e-02\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     89   4.9e+08   4.2e-02\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     90   4.9e+08   6.0e-02\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     91   4.9e+08   8.6e-02\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     92   4.9e+08   1.2e-01\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     93   4.9e+08   1.7e-01\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     94   4.9e+08   2.4e-01\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     95   4.9e+08   3.4e-01\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     96   4.9e+08   4.9e-01\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     97   4.9e+08   7.0e-01\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     98   4.9e+08   9.9e-01\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:     99   4.9e+08   8.5e-01\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    100   4.9e+08   1.6e+00\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    101   4.8e+08   2.2e+00\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    102   4.8e+08   1.7e+00\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    103   4.7e+08   3.3e+00\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    104   4.4e+08   4.9e+00\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    105   4.4e+08   4.1e+00\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    106   4.4e+08   4.0e+00\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    107   4.4e+08   2.5e+00\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    108   4.4e+08   2.3e+00\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    109   4.4e+08   5.6e-01\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    110   4.4e+08   1.5e+00\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    111   4.4e+08   1.3e+00\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    112   4.4e+08   1.0e+00\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    113   4.4e+08   8.7e-01\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    114   4.4e+08   4.4e-01\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    115   4.4e+08   8.7e-01\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    116   4.4e+08   4.0e-01\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    117   4.3e+08   2.0e-01\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    118   4.3e+08   6.6e-01\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    119   4.3e+08   4.2e-01\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    120   4.3e+08   6.1e-02\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    136   2.9e+08   7.2e-01\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    137   2.9e+08   1.7e-01\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    138   2.8e+08   3.2e-01\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    139   2.8e+08   5.6e-01\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    140   2.8e+08   6.4e-02\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    141   2.7e+08   1.1e-01\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    142   2.7e+08   3.4e-01\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    143   2.7e+08   1.8e-02\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    144   2.7e+08   8.9e-02\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    209   4.4e+07   4.7e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    210   4.4e+07   5.7e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    211   4.4e+07   2.7e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    212   4.4e+07   1.4e-03\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    213   4.4e+07   4.1e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    215   4.4e+07   1.3e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    216   4.4e+07   1.5e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    217   4.4e+07   8.4e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    225   4.4e+07   7.6e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    226   4.4e+07   5.1e-05\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    227   4.4e+07   9.3e-06\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    228   4.4e+07   2.9e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    229   4.4e+07   5.0e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    230   4.4e+07   2.9e-05\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    231   4.4e+07   2.5e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    232   4.4e+07   1.8e-05\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    233   4.4e+07   1.7e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    234   4.4e+07   1.4e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    235   4.4e+07   1.7e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    236   4.4e+07   8.5e-05\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    237   4.4e+07   2.5e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    238   4.4e+07   1.4e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    239   4.4e+07   3.5e-05\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    240   4.4e+07   1.5e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    241   4.4e+07   1.4e-04\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    242   4.4e+07   5.5e-05\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    243   4.4e+07   2.9e-06\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    244   4.4e+07   1.3e-05\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    245   4.4e+07   6.0e-05\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    246   4.4e+07   2.3e-05\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    247   4.4e+07   7.6e-05\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    248   4.4e+07   1.2e-05\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    249   4.4e+07   3.2e-05\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    250   4.4e+07   5.8e-05\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    251   4.4e+07   2.5e-05\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    252   4.4e+07   4.0e-05\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    253   4.4e+07   5.0e-06\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    254   4.4e+07   3.1e-05\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    255   4.4e+07   2.2e-05\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    256   4.4e+07   1.0e-05\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    257   4.4e+07   1.7e-05\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    258   4.4e+07   7.1e-06\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    259   4.4e+07   2.1e-05\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    260   4.4e+07   9.2e-06\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    261   4.4e+07   1.4e-06\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    262   4.4e+07   2.1e-07\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    263   4.4e+07   6.7e-06\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    264   4.4e+07   7.9e-06\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    265   4.4e+07   3.3e-06\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    266   4.4e+07   2.1e-06\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    267   4.4e+07   1.8e-06\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    268   4.4e+07   1.4e-06\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    269   4.4e+07   3.8e-06\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    270   4.4e+07   1.9e-06\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    271   4.4e+07   1.6e-06\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    272   4.4e+07   7.2e-07\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    273   4.4e+07   1.9e-06\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    274   4.4e+07   1.5e-06\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    275   4.4e+07   1.2e-06\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    276   4.4e+07   9.0e-07\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    277   4.4e+07   2.5e-07\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    278   4.4e+07   1.2e-06\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    279   4.4e+07   6.9e-07\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    280   4.4e+07   7.2e-07\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    281   4.4e+07   5.5e-07\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    282   4.4e+07   1.1e-06\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    283   4.4e+07   7.5e-07\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    284   4.4e+07   3.6e-07\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    285   4.4e+07   1.1e-06\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    286   4.4e+07   3.7e-08\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    287   4.4e+07   4.5e-07\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    288   4.4e+07   7.3e-08\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    289   4.4e+07   2.0e-07\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    290   4.4e+07   6.4e-07\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    291   4.4e+07   2.0e-07\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    292   4.4e+07   2.5e-07\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
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      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    294   4.4e+07   3.3e-07\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    295   4.4e+07   3.2e-07\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    296   4.4e+07   6.7e-08\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    297   4.4e+07   2.4e-08\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    298   4.4e+07   3.3e-07\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    299   4.4e+07   9.5e-08\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    300   4.4e+07   2.1e-08\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    301   4.4e+07   6.0e-08\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    302   4.4e+07   2.7e-07\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n",
      "┌ Info:    303   4.4e+07   1.1e-07\n",
      "└ @ DerivativeFreeSolvers /home/abel/.julia/packages/DerivativeFreeSolvers/Kot19/src/nelder_mead.jl:65\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "\"Execution stats: solved to within acceptable tolerances\""
      ]
     },
     "execution_count": 235,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df = data[findall(data[!,Symbol(\"Country/Region\")] .== \"Italy\"),:]\n",
    "\n",
    "C = df.Confirmed\n",
    "idx = findfirst(C .≥ 100)\n",
    "C = C[idx:end]\n",
    "R = df.Recovered[idx:end] + df.Deaths[idx:end]\n",
    "scatter(C)\n",
    "scatter!(R)\n",
    "\n",
    "# β₁ = β, β₂ = γ, β₃ = T\n",
    "function sqr(β)\n",
    "    f(t, y) = β[2] * y\n",
    "    t_rk, y_rk = runge_kutta(0.0, [exp(β[3]) - β[4]; β[4]; 0.0],\n",
    "        (t,y) -> [-β[1] / exp(β[3]) * y[2] * y[1]; \n",
    "                   β[1] / exp(β[3]) * y[2] * y[1] - β[2] * y[2];\n",
    "                   β[2] * y[2]],\n",
    "        length(C)-1, length(C)-1)\n",
    "    SQR = 0.0\n",
    "    for i = 1:length(C)\n",
    "        SQR += (C[i] - y_rk[2,i])^2\n",
    "        SQR += (R[i] - y_rk[3,i])^2\n",
    "    end\n",
    "    return SQR / 2\n",
    "end\n",
    "\n",
    "function NLPSQR()\n",
    "    return NLPSQR(NLPModelMeta(4, x0=[0.30; 0.08; log(60_000_000); 100]), Counters())\n",
    "    #return NLPSQR(NLPModelMeta(3, x0=[0.00; 0.00; 10000]), Counters())\n",
    "end\n",
    "\n",
    "function NLPModels.obj(nlp :: NLPSQR, β :: AbstractVector)\n",
    "    return sqr(β)\n",
    "end\n",
    "\n",
    "nlp = NLPSQR()\n",
    "output = nelder_mead(nlp)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 241,
   "metadata": {},
   "outputs": [
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       "<polyline clip-path=\"url(#clip2000)\" style=\"stroke:#000000; stroke-width:4; stroke-opacity:1; fill:none\" points=\"\n",
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       "<polyline clip-path=\"url(#clip2000)\" style=\"stroke:#000000; stroke-width:4; stroke-opacity:1; fill:none\" points=\"\n",
       "  247.807,383.416 273.066,383.416 \n",
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       "<polyline clip-path=\"url(#clip2000)\" style=\"stroke:#000000; stroke-width:4; stroke-opacity:1; fill:none\" points=\"\n",
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       "<text style=\"fill:#000000; fill-opacity:1; font-family:Arial,Helvetica Neue,Helvetica,sans-serif; font-size:48px; text-anchor:middle;\" transform=\"rotate(0, 307.381, 1541.47)\" x=\"307.381\" y=\"1541.47\">0</text>\n",
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       "<g clip-path=\"url(#clip2000)\">\n",
       "<text style=\"fill:#000000; fill-opacity:1; font-family:Arial,Helvetica Neue,Helvetica,sans-serif; font-size:48px; text-anchor:middle;\" transform=\"rotate(0, 909.139, 1541.47)\" x=\"909.139\" y=\"1541.47\">10</text>\n",
       "</g>\n",
       "<g clip-path=\"url(#clip2000)\">\n",
       "<text style=\"fill:#000000; fill-opacity:1; font-family:Arial,Helvetica Neue,Helvetica,sans-serif; font-size:48px; text-anchor:middle;\" transform=\"rotate(0, 1510.9, 1541.47)\" x=\"1510.9\" y=\"1541.47\">20</text>\n",
       "</g>\n",
       "<g clip-path=\"url(#clip2000)\">\n",
       "<text style=\"fill:#000000; fill-opacity:1; font-family:Arial,Helvetica Neue,Helvetica,sans-serif; font-size:48px; text-anchor:middle;\" transform=\"rotate(0, 2112.65, 1541.47)\" x=\"2112.65\" y=\"1541.47\">30</text>\n",
       "</g>\n",
       "<g clip-path=\"url(#clip2000)\">\n",
       "<text style=\"fill:#000000; fill-opacity:1; font-family:Arial,Helvetica Neue,Helvetica,sans-serif; font-size:48px; text-anchor:end;\" transform=\"rotate(0, 223.807, 1464.21)\" x=\"223.807\" y=\"1464.21\">0</text>\n",
       "</g>\n",
       "<g clip-path=\"url(#clip2000)\">\n",
       "<text style=\"fill:#000000; fill-opacity:1; font-family:Arial,Helvetica Neue,Helvetica,sans-serif; font-size:48px; text-anchor:start;\" transform=\"rotate(0, 93.6653, 1257.78)\" x=\"93.6653\" y=\"1257.78\">1×10</text>\n",
       "</g>\n",
       "<g clip-path=\"url(#clip2000)\">\n",
       "<text style=\"fill:#000000; fill-opacity:1; font-family:Arial,Helvetica Neue,Helvetica,sans-serif; font-size:38px; text-anchor:start;\" transform=\"rotate(0, 202.062, 1230.37)\" x=\"202.062\" y=\"1230.37\">4</text>\n",
       "</g>\n",
       "<g clip-path=\"url(#clip2000)\">\n",
       "<text style=\"fill:#000000; fill-opacity:1; font-family:Arial,Helvetica Neue,Helvetica,sans-serif; font-size:48px; text-anchor:start;\" transform=\"rotate(0, 93.6653, 1045.12)\" x=\"93.6653\" y=\"1045.12\">2×10</text>\n",
       "</g>\n",
       "<g clip-path=\"url(#clip2000)\">\n",
       "<text style=\"fill:#000000; fill-opacity:1; font-family:Arial,Helvetica Neue,Helvetica,sans-serif; font-size:38px; text-anchor:start;\" transform=\"rotate(0, 202.062, 1017.71)\" x=\"202.062\" y=\"1017.71\">4</text>\n",
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       "<g clip-path=\"url(#clip2000)\">\n",
       "<text style=\"fill:#000000; fill-opacity:1; font-family:Arial,Helvetica Neue,Helvetica,sans-serif; font-size:48px; text-anchor:start;\" transform=\"rotate(0, 93.6653, 832.463)\" x=\"93.6653\" y=\"832.463\">3×10</text>\n",
       "</g>\n",
       "<g clip-path=\"url(#clip2000)\">\n",
       "<text style=\"fill:#000000; fill-opacity:1; font-family:Arial,Helvetica Neue,Helvetica,sans-serif; font-size:38px; text-anchor:start;\" transform=\"rotate(0, 202.062, 805.052)\" x=\"202.062\" y=\"805.052\">4</text>\n",
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       "<g clip-path=\"url(#clip2000)\">\n",
       "<text style=\"fill:#000000; fill-opacity:1; font-family:Arial,Helvetica Neue,Helvetica,sans-serif; font-size:48px; text-anchor:start;\" transform=\"rotate(0, 93.6653, 619.803)\" x=\"93.6653\" y=\"619.803\">4×10</text>\n",
       "</g>\n",
       "<g clip-path=\"url(#clip2000)\">\n",
       "<text style=\"fill:#000000; fill-opacity:1; font-family:Arial,Helvetica Neue,Helvetica,sans-serif; font-size:38px; text-anchor:start;\" transform=\"rotate(0, 202.062, 592.393)\" x=\"202.062\" y=\"592.393\">4</text>\n",
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       "</g>\n",
       "<g clip-path=\"url(#clip2000)\">\n",
       "<text style=\"fill:#000000; fill-opacity:1; font-family:Arial,Helvetica Neue,Helvetica,sans-serif; font-size:38px; text-anchor:start;\" transform=\"rotate(0, 202.062, 379.733)\" x=\"202.062\" y=\"379.733\">4</text>\n",
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       "</g>\n",
       "<g clip-path=\"url(#clip2000)\">\n",
       "<text style=\"fill:#000000; fill-opacity:1; font-family:Arial,Helvetica Neue,Helvetica,sans-serif; font-size:38px; text-anchor:start;\" transform=\"rotate(0, 202.062, 167.074)\" x=\"202.062\" y=\"167.074\">4</text>\n",
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       "<circle clip-path=\"url(#clip2002)\" style=\"fill:#008000; stroke:none; fill-opacity:1\" cx=\"367.557\" cy=\"1441.84\" r=\"28\"/>\n",
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       "<circle clip-path=\"url(#clip2002)\" style=\"fill:#008000; stroke:none; fill-opacity:1\" cx=\"427.732\" cy=\"1439.87\" r=\"28\"/>\n",
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     "execution_count": 241,
     "metadata": {},
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   ],
   "source": [
    "β = output.solution\n",
    "\n",
    "F(t,y) = [-β[1] / exp(β[3]) * y[2] * y[1]; \n",
    "           β[1] / exp(β[3]) * y[2] * y[1] - β[2] * y[2];\n",
    "           β[2] * y[2]]\n",
    "\n",
    "t0 = 0.0\n",
    "y0 = [exp(β[3]) - β[4]; β[4]; 0.0]\n",
    "next = 5\n",
    "tf = length(C) - 1 + next\n",
    "N = length(C) - 1 + next\n",
    "t, y = runge_kutta(t0, y0, F, tf, N)\n",
    "#plot(t, y[1,:], c=:blue, lab=\"S\", legend=:right)\n",
    "scatter(t[1:length(C)], C, c=:green, ms=8)\n",
    "scatter!(t[1:length(R)], R, c=:red, ms=8)\n",
    "scatter!(t, y[2,:], c=:lightgreen, lab=\"I\")\n",
    "scatter!(t, y[3,:], c=:pink, lab=\"R\")\n",
    "plot!(t, y[2,:], c=:green, lab=\"I\")\n",
    "plot!(t, y[3,:], c=:red, lab=\"R\")\n",
    "plot!(leg=:topleft)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 237,
   "metadata": {},
   "outputs": [
    {
     "data": {
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     "execution_count": 237,
     "metadata": {},
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   "execution_count": null,
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