09. Numerical Optimization.ipynb

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   "execution_count": 1,
   "metadata": {},
   "outputs": [
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     "text": [
      "┌ Info: Precompiling XLSX [fdbf4ff8-1666-58a4-91e7-1b58723a45e0]\n",
      "└ @ Base loading.jl:1317\n"
     ]
    }
   ],
   "source": [
    "using Pkg\n",
    "using Convex\n",
    "using SCS\n",
    "using XLSX\n",
    "using DataFrames\n",
    "using Plots\n",
    "using CSV\n",
    "using Statistics\n",
    "using Images\n",
    "using DelimitedFiles"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### 📈 Problem 1 Portfolio investment.\n",
    "Our first problem will be an investment problem. We will look at stock prices from three companies and decide how to spend an amount of $1000 on these three companies. Let's first load some data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table class=\"data-frame\"><thead><tr><th></th><th>MSFT</th><th>FB</th><th>AAPL</th></tr><tr><th></th><th>Any</th><th>Any</th><th>Any</th></tr></thead><tbody><p>13 rows × 3 columns</p><tr><th>1</th><td>101.93</td><td>137.95</td><td>148.26</td></tr><tr><th>2</th><td>102.8</td><td>143.8</td><td>152.29</td></tr><tr><th>3</th><td>107.71</td><td>150.04</td><td>156.82</td></tr><tr><th>4</th><td>107.17</td><td>149.01</td><td>157.76</td></tr><tr><th>5</th><td>102.78</td><td>165.71</td><td>166.52</td></tr><tr><th>6</th><td>105.67</td><td>167.33</td><td>170.41</td></tr><tr><th>7</th><td>108.22</td><td>162.5</td><td>170.42</td></tr><tr><th>8</th><td>110.97</td><td>161.89</td><td>172.97</td></tr><tr><th>9</th><td>112.53</td><td>162.28</td><td>174.97</td></tr><tr><th>10</th><td>110.51</td><td>169.6</td><td>172.91</td></tr><tr><th>11</th><td>115.91</td><td>165.98</td><td>186.12</td></tr><tr><th>12</th><td>117.05</td><td>164.34</td><td>191.05</td></tr><tr><th>13</th><td>117.94</td><td>166.69</td><td>189.95</td></tr></tbody></table>"
      ],
      "text/latex": [
       "\\begin{tabular}{r|ccc}\n",
       "\t& MSFT & FB & AAPL\\\\\n",
       "\t\\hline\n",
       "\t& Any & Any & Any\\\\\n",
       "\t\\hline\n",
       "\t1 & 101.93 & 137.95 & 148.26 \\\\\n",
       "\t2 & 102.8 & 143.8 & 152.29 \\\\\n",
       "\t3 & 107.71 & 150.04 & 156.82 \\\\\n",
       "\t4 & 107.17 & 149.01 & 157.76 \\\\\n",
       "\t5 & 102.78 & 165.71 & 166.52 \\\\\n",
       "\t6 & 105.67 & 167.33 & 170.41 \\\\\n",
       "\t7 & 108.22 & 162.5 & 170.42 \\\\\n",
       "\t8 & 110.97 & 161.89 & 172.97 \\\\\n",
       "\t9 & 112.53 & 162.28 & 174.97 \\\\\n",
       "\t10 & 110.51 & 169.6 & 172.91 \\\\\n",
       "\t11 & 115.91 & 165.98 & 186.12 \\\\\n",
       "\t12 & 117.05 & 164.34 & 191.05 \\\\\n",
       "\t13 & 117.94 & 166.69 & 189.95 \\\\\n",
       "\\end{tabular}\n"
      ],
      "text/plain": [
       "\u001b[1m13×3 DataFrame\u001b[0m\n",
       "\u001b[1m Row \u001b[0m│\u001b[1m MSFT   \u001b[0m\u001b[1m FB     \u001b[0m\u001b[1m AAPL   \u001b[0m\n",
       "\u001b[1m     \u001b[0m│\u001b[90m Any    \u001b[0m\u001b[90m Any    \u001b[0m\u001b[90m Any    \u001b[0m\n",
       "─────┼────────────────────────\n",
       "   1 │ 101.93  137.95  148.26\n",
       "   2 │ 102.8   143.8   152.29\n",
       "   3 │ 107.71  150.04  156.82\n",
       "   4 │ 107.17  149.01  157.76\n",
       "   5 │ 102.78  165.71  166.52\n",
       "   6 │ 105.67  167.33  170.41\n",
       "   7 │ 108.22  162.5   170.42\n",
       "   8 │ 110.97  161.89  172.97\n",
       "   9 │ 112.53  162.28  174.97\n",
       "  10 │ 110.51  169.6   172.91\n",
       "  11 │ 115.91  165.98  186.12\n",
       "  12 │ 117.05  164.34  191.05\n",
       "  13 │ 117.94  166.69  189.95"
      ]
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     "execution_count": 2,
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   ],
   "source": [
    "T = DataFrame(XLSX.readtable(\"data/stock_prices.xlsx\",\"Sheet2\")...)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "`T` is a `DataFrame` that has weekly stock prices value of three companies (Microsoft, Facebook, Apple) from the period of January 2019 - March 2019. We will first take a quick look at these prices in a quick plot."
   ]
  },
  {
   "cell_type": "code",
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      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "plot(T[!,:MSFT],label=\"Microsoft\")\n",
    "plot!(T[!,:AAPL],label=\"Apple\")\n",
    "plot!(T[!,:FB],label=\"FB\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "13×3 Matrix{Any}:\n",
       " 101.93  137.95  148.26\n",
       " 102.8   143.8   152.29\n",
       " 107.71  150.04  156.82\n",
       " 107.17  149.01  157.76\n",
       " 102.78  165.71  166.52\n",
       " 105.67  167.33  170.41\n",
       " 108.22  162.5   170.42\n",
       " 110.97  161.89  172.97\n",
       " 112.53  162.28  174.97\n",
       " 110.51  169.6   172.91\n",
       " 115.91  165.98  186.12\n",
       " 117.05  164.34  191.05\n",
       " 117.94  166.69  189.95"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# convert the prices to a Matrix to be used later in the optimization problem\n",
    "prices_matrix = Matrix(T)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "To compute the weekly return, we will use the formula: `R[i,t] = (price[i,t] - price[i,t-1])/price[i,t-1]`. This is the return of stock `i` from week `t`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "12×3 Matrix{Float64}:\n",
       "  0.00853527   0.0424067    0.027182\n",
       "  0.0477626    0.0433936    0.0297459\n",
       " -0.00501346  -0.00686484   0.00599413\n",
       " -0.040963     0.112073     0.0555274\n",
       "  0.0281183    0.00977611   0.0233606\n",
       "  0.0241317   -0.0288651    5.8682e-5\n",
       "  0.0254112   -0.00375385   0.014963\n",
       "  0.0140579    0.00240904   0.0115627\n",
       " -0.0179508    0.0451072   -0.0117734\n",
       "  0.0488644   -0.0213443    0.0763981\n",
       "  0.00983522  -0.00988071   0.0264883\n",
       "  0.00760359   0.0142996   -0.00575766"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "M1 = prices_matrix[1:end-1,:]\n",
    "M2 = prices_matrix[2:end,:]\n",
    "R = (M2.-M1)./M1"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's assume that the vector `x = [x1 x2 x3]` will contain the total number of dollars we will invest in these companies, i.e. `x1` is how much we will invest in the first company (MSFT), `x2` is how much we will invest in FB, and `x3` is how much we will invest in `AAPL`. The return on the investment will be `dot(r,x)`, where `r = [r1 r2 r3]` is the return from each of the companies.\n",
    "\n",
    "Here, `r` is a random variable and we will have to model it in terms of expected values. And the expected value `E(dot(r,x))` will be `E[dot(mean(R,dims=2),x)`. If we want a return of `10%` or more, then we need `dot(r,x) >= 0.1`.\n",
    "\n",
    "Next, we will model the risk matrix. We will skip the derivation of the risk matrix here, but you can read about it here: https://www.kdnuggets.com/2019/06/optimization-python-money-risk.html. The risk matrix will be the covariance matrix of the computed return prices (`R`)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3×3 Matrix{Float64}:\n",
       "  0.000659383  -0.000630653  0.000139112\n",
       " -0.000630653   0.00152162   0.000192288\n",
       "  0.000139112   0.000192288  0.000635503"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "risk_matrix = cov(R)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "true"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# note that the risk matrix is positive definite\n",
    "isposdef(risk_matrix)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3-element Vector{Float64}:\n",
       " 0.012532748705136576\n",
       " 0.016563036855293173\n",
       " 0.021145804655032917"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "r = mean(R,dims=1)[:]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now let's solve the following problem: Someone gives you $1000 and tells you to spend them in the form of investment on these three compnaies such that you get a return of 2\\% on what you spent.\n",
    "\n",
    "The goal will be to minimize the risk, that is x'\\*risk_matrix\\*x.\n",
    "The constraints will be \n",
    "- `sum(x) = 1`, we will compute the percentage of investment rather than the exact amount\n",
    "- `dot(r,x) >= 0.02`\n",
    "- `x[i] >= 0`\n",
    "\n",
    "This problem is a convext problem, and we will use `Convex.jl` to it."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "minimize\n",
       "└─ * (Convex.NotDcp; real)\n",
       "   ├─ * (affine; real)\n",
       "   │  ├─ adjoint (affine; real)\n",
       "   │  │  └─ …\n",
       "   │  └─ 3×3 Matrix{Float64}\n",
       "   └─ 3-element real variable (id: 382…507)\n",
       "subject to\n",
       "├─ == constraint (affine)\n",
       "│  ├─ sum (affine; real)\n",
       "│  │  └─ 3-element real variable (id: 382…507)\n",
       "│  └─ 1\n",
       "├─ >= constraint (affine)\n",
       "│  ├─ * (affine; real)\n",
       "│  │  ├─ [0.0125327 0.016563 0.0211458]\n",
       "│  │  └─ 3-element real variable (id: 382…507)\n",
       "│  └─ 0.02\n",
       "├─ >= constraint (affine)\n",
       "│  ├─ index (affine; real)\n",
       "│  │  └─ 3-element real variable (id: 382…507)\n",
       "│  └─ 0\n",
       "├─ >= constraint (affine)\n",
       "│  ├─ index (affine; real)\n",
       "│  │  └─ 3-element real variable (id: 382…507)\n",
       "│  └─ 0\n",
       "└─ >= constraint (affine)\n",
       "   ├─ index (affine; real)\n",
       "   │  └─ 3-element real variable (id: 382…507)\n",
       "   └─ 0\n",
       "\n",
       "status: `solve!` not called yet"
      ]
     },
     "execution_count": 9,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┌ Warning: Expression not DCP compliant. Trying to solve non-DCP compliant problems can lead to unexpected behavior.\n",
      "└ @ Convex /Users/logankilpatrick/.julia/packages/Convex/ubaUN/src/dcp.jl:25\n"
     ]
    }
   ],
   "source": [
    "x = Variable(length(r))\n",
    "problem = minimize(x'*risk_matrix*x,[sum(x)==1;r'*x>=0.02;x.>=0])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Note the `Convex.NotDcp` in the answer above and the warning. `Convex.jl` requires that we pass Dcp compliant problem (Disciplined convex programming). Learn more about the DCP ruleset here: http://cvxr.com/cvx/doc/dcp.html"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "minimize\n",
       "└─ * (convex; positive)\n",
       "   ├─ 1\n",
       "   └─ qol_elem (convex; positive)\n",
       "      ├─ norm2 (convex; positive)\n",
       "      │  └─ …\n",
       "      └─ [1.0]\n",
       "subject to\n",
       "├─ == constraint (affine)\n",
       "│  ├─ sum (affine; real)\n",
       "│  │  └─ 3-element real variable (id: 382…507)\n",
       "│  └─ 1\n",
       "├─ >= constraint (affine)\n",
       "│  ├─ * (affine; real)\n",
       "│  │  ├─ [0.0125327 0.016563 0.0211458]\n",
       "│  │  └─ 3-element real variable (id: 382…507)\n",
       "│  └─ 0.02\n",
       "├─ >= constraint (affine)\n",
       "│  ├─ index (affine; real)\n",
       "│  │  └─ 3-element real variable (id: 382…507)\n",
       "│  └─ 0\n",
       "├─ >= constraint (affine)\n",
       "│  ├─ index (affine; real)\n",
       "│  │  └─ 3-element real variable (id: 382…507)\n",
       "│  └─ 0\n",
       "└─ >= constraint (affine)\n",
       "   ├─ index (affine; real)\n",
       "   │  └─ 3-element real variable (id: 382…507)\n",
       "   └─ 0\n",
       "\n",
       "status: `solve!` not called yet"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# make the problem DCP compliant\n",
    "problem = minimize(Convex.quadform(x,risk_matrix),[sum(x)==1;r'*x>=0.02;x.>=0])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "----------------------------------------------------------------------------\n",
      "\tSCS v2.1.3 - Splitting Conic Solver\n",
      "\t(c) Brendan O'Donoghue, Stanford University, 2012\n",
      "----------------------------------------------------------------------------\n",
      "Lin-sys: sparse-indirect, nnz in A = 24, CG tol ~ 1/iter^(2.00)\n",
      "eps = 1.00e-05, alpha = 1.50, max_iters = 5000, normalize = 1, scale = 1.00\n",
      "acceleration_lookback = 10, rho_x = 1.00e-03\n",
      "Variables n = 6, constraints m = 14\n",
      "Cones:\tprimal zero / dual free vars: 2\n",
      "\tlinear vars: 5\n",
      "\tsoc vars: 7, soc blks: 2\n",
      "Setup time: 7.39e-05s\n",
      "----------------------------------------------------------------------------\n",
      " Iter | pri res | dua res | rel gap | pri obj | dua obj | kap/tau | time (s)\n",
      "----------------------------------------------------------------------------\n",
      "     0| 1.71e+19  2.86e+19  1.00e+00 -3.40e+19  5.17e+18  5.49e+19  2.18e-05 \n",
      "    99| 2.59e-11  7.73e-11  5.25e-11  4.85e-04  4.85e-04  1.49e-17  1.62e-03 \n",
      "----------------------------------------------------------------------------\n",
      "Status: Solved\n",
      "Timing: Solve time: 1.62e-03s\n",
      "\tLin-sys: avg # CG iterations: 3.28, avg solve time: 4.16e-07s\n",
      "\tCones: avg projection time: 3.67e-08s\n",
      "\tAcceleration: avg step time: 1.52e-05s\n",
      "----------------------------------------------------------------------------\n",
      "Error metrics:\n",
      "dist(s, K) = 1.4091e-16, dist(y, K*) = 0.0000e+00, s'y/|s||y| = 8.2412e-17\n",
      "primal res: |Ax + s - b|_2 / (1 + |b|_2) = 2.5893e-11\n",
      "dual res:   |A'y + c|_2 / (1 + |c|_2) = 7.7263e-11\n",
      "rel gap:    |c'x + b'y| / (1 + |c'x| + |b'y|) = 5.2529e-11\n",
      "----------------------------------------------------------------------------\n",
      "c'x = 0.0005, -b'y = 0.0005\n",
      "============================================================================\n"
     ]
    }
   ],
   "source": [
    "solve!(problem, SCS.Optimizer)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Variable\n",
       "size: (3, 1)\n",
       "sign: real\n",
       "vexity: affine\n",
       "id: 382…507\n",
       "value: [0.06795413162617518, 0.12230860097293451, 0.8097372674602319]"
      ]
     },
     "execution_count": 12,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1.0000000000593416"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "sum(x.value)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1×1 adjoint(::Vector{Float64}) with eltype Float64:\n",
       " 0.020000000000394896"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# return \n",
    "r'*x.value "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "3×1 Matrix{Float64}:\n",
       "  67.95413162617518\n",
       " 122.30860097293451\n",
       " 809.7372674602319"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "x.value .* 1000"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The conclusion is that we should invest **67.9USD in Microsoft**, **122.3USD in Facebook**, and **809.7USD in Apple**."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "### 🖼️ Problem 2 Image recovery.\n",
    "In this problem, we are given an image where some of the pixels have been altered. The goal is to recover the unknonwn pixels by solving an optimization problem. Let's first load the figure."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "283×283 Array{RGB{N0f8},2} with eltype RGB{N0f8}:\n",
       " RGB{N0f8}(0.153,0.082,0.075)  …  RGB{N0f8}(0.678,0.659,0.675)\n",
       " RGB{N0f8}(0.118,0.047,0.039)     RGB{N0f8}(0.514,0.494,0.51)\n",
       " RGB{N0f8}(0.129,0.059,0.043)     RGB{N0f8}(0.624,0.604,0.62)\n",
       " RGB{N0f8}(0.137,0.067,0.051)     RGB{N0f8}(0.157,0.137,0.153)\n",
       " RGB{N0f8}(0.129,0.063,0.035)     RGB{N0f8}(0.243,0.224,0.239)\n",
       " RGB{N0f8}(0.125,0.059,0.027)  …  RGB{N0f8}(0.184,0.161,0.176)\n",
       " RGB{N0f8}(0.169,0.114,0.071)     RGB{N0f8}(0.208,0.184,0.2)\n",
       " RGB{N0f8}(0.482,0.427,0.384)     RGB{N0f8}(0.153,0.129,0.145)\n",
       " RGB{N0f8}(0.498,0.451,0.396)     RGB{N0f8}(0.141,0.106,0.125)\n",
       " RGB{N0f8}(0.49,0.443,0.388)      RGB{N0f8}(0.161,0.125,0.145)\n",
       " RGB{N0f8}(0.49,0.455,0.396)   …  RGB{N0f8}(0.149,0.114,0.125)\n",
       " RGB{N0f8}(0.498,0.463,0.404)     RGB{N0f8}(0.145,0.102,0.118)\n",
       " RGB{N0f8}(0.478,0.451,0.388)     RGB{N0f8}(0.145,0.102,0.118)\n",
       " ⋮                             ⋱  \n",
       " RGB{N0f8}(0.51,0.49,0.478)       RGB{N0f8}(0.459,0.431,0.459)\n",
       " RGB{N0f8}(0.49,0.475,0.439)      RGB{N0f8}(0.443,0.424,0.439)\n",
       " RGB{N0f8}(0.51,0.494,0.459)      RGB{N0f8}(0.467,0.443,0.459)\n",
       " RGB{N0f8}(0.482,0.471,0.443)     RGB{N0f8}(0.451,0.404,0.42)\n",
       " RGB{N0f8}(0.463,0.459,0.439)  …  RGB{N0f8}(0.463,0.404,0.424)\n",
       " RGB{N0f8}(0.443,0.443,0.435)     RGB{N0f8}(0.392,0.329,0.341)\n",
       " RGB{N0f8}(0.471,0.475,0.482)     RGB{N0f8}(0.4,0.341,0.353)\n",
       " RGB{N0f8}(0.471,0.482,0.502)     RGB{N0f8}(0.349,0.31,0.314)\n",
       " RGB{N0f8}(0.537,0.557,0.58)      RGB{N0f8}(0.396,0.361,0.365)\n",
       " RGB{N0f8}(0.529,0.557,0.588)  …  RGB{N0f8}(0.424,0.4,0.4)\n",
       " RGB{N0f8}(0.541,0.569,0.6)       RGB{N0f8}(0.443,0.408,0.412)\n",
       " RGB{N0f8}(0.541,0.576,0.604)     RGB{N0f8}(0.459,0.412,0.427)"
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "Kref = load(\"data/khiam-small.jpg\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We will convert the image to gray scale and disrupt some of the pixels"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "283×283 Array{Gray{N0f8},2} with eltype Gray{N0f8}:\n",
       " Gray{N0f8}(0.102)  Gray{N0f8}(0.063)  …  Gray{N0f8}(0.667)\n",
       " Gray{N0f8}(0.067)  Gray{N0f8}(0.098)     Gray{N0f8}(0.502)\n",
       " Gray{N0f8}(0.078)  Gray{N0f8}(0.086)     Gray{N0f8}(0.612)\n",
       " Gray{N0f8}(0.086)  Gray{N0f8}(0.067)     Gray{N0f8}(0.145)\n",
       " Gray{N0f8}(0.078)  Gray{N0f8}(0.102)     Gray{N0f8}(0.231)\n",
       " Gray{N0f8}(0.075)  Gray{N0f8}(0.075)  …  Gray{N0f8}(0.169)\n",
       " Gray{N0f8}(0.125)  Gray{N0f8}(0.098)     Gray{N0f8}(0.192)\n",
       " Gray{N0f8}(0.439)  Gray{N0f8}(0.447)     Gray{N0f8}(0.137)\n",
       " Gray{N0f8}(0.459)  Gray{N0f8}(0.455)     Gray{N0f8}(0.118)\n",
       " Gray{N0f8}(0.451)  Gray{N0f8}(0.467)     Gray{N0f8}(0.137)\n",
       " Gray{N0f8}(0.459)  Gray{N0f8}(0.459)  …  Gray{N0f8}(0.125)\n",
       " Gray{N0f8}(0.467)  Gray{N0f8}(0.451)     Gray{N0f8}(0.118)\n",
       " Gray{N0f8}(0.451)  Gray{N0f8}(0.451)     Gray{N0f8}(0.118)\n",
       " ⋮                                     ⋱  \n",
       " Gray{N0f8}(0.494)  Gray{N0f8}(0.475)     Gray{N0f8}(0.443)\n",
       " Gray{N0f8}(0.475)  Gray{N0f8}(0.482)     Gray{N0f8}(0.431)\n",
       " Gray{N0f8}(0.494)  Gray{N0f8}(0.502)     Gray{N0f8}(0.451)\n",
       " Gray{N0f8}(0.471)  Gray{N0f8}(0.494)     Gray{N0f8}(0.42)\n",
       " Gray{N0f8}(0.459)  Gray{N0f8}(0.482)  …  Gray{N0f8}(0.424)\n",
       " Gray{N0f8}(0.443)  Gray{N0f8}(0.459)     Gray{N0f8}(0.349)\n",
       " Gray{N0f8}(0.475)  Gray{N0f8}(0.478)     Gray{N0f8}(0.361)\n",
       " Gray{N0f8}(0.482)  Gray{N0f8}(0.478)     Gray{N0f8}(0.322)\n",
       " Gray{N0f8}(0.553)  Gray{N0f8}(0.553)     Gray{N0f8}(0.373)\n",
       " Gray{N0f8}(0.553)  Gray{N0f8}(0.545)  …  Gray{N0f8}(0.408)\n",
       " Gray{N0f8}(0.565)  Gray{N0f8}(0.553)     Gray{N0f8}(0.42)\n",
       " Gray{N0f8}(0.569)  Gray{N0f8}(0.553)     Gray{N0f8}(0.427)"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "K = copy(Kref)\n",
    "p = prod(size(K))\n",
    "missingids = rand(1:p,400)\n",
    "K[missingids] .= RGBX{N0f8}(0.0,0.0,0.0)\n",
    "K\n",
    "Gray.(K)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {},
   "outputs": [],
   "source": [
    "Y = Float64.(Gray.(K));"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Given this image, the goal is now to complete the matrix. We will use a common technique for this problem developed by Candes and Tao. The goal will be to create a new matrix `X` where we minimize the nuclear norm of `X` (i.e. the sum of the singular values of `X`), and such that the entries that are already known in `Y` remain the same in `X`. We will again use `Convex.jl` to solve this problem. Let's write it down below."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1-element Vector{Constraint}:\n",
       " == constraint (affine)\n",
       "├─ index (affine; real)\n",
       "│  └─ 283×283 real variable (id: 149…295)\n",
       "└─ 79689-element Vector{Float64}"
      ]
     },
     "execution_count": 19,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "correctids = findall(Y[:].!=0)\n",
    "X = Convex.Variable(size(Y))\n",
    "problem = minimize(nuclearnorm(X))\n",
    "problem.constraints += X[correctids]==Y[correctids]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "----------------------------------------------------------------------------\n",
      "\tSCS v2.1.3 - Splitting Conic Solver\n",
      "\t(c) Brendan O'Donoghue, Stanford University, 2012\n",
      "----------------------------------------------------------------------------\n",
      "Lin-sys: sparse-indirect, nnz in A = 400329, CG tol ~ 1/iter^(2.00)\n",
      "eps = 1.00e-03, alpha = 1.50, max_iters = 5000, normalize = 1, scale = 1.00\n",
      "acceleration_lookback = 10, rho_x = 1.00e-03\n",
      "Variables n = 240268, constraints m = 400046\n",
      "Cones:\tprimal zero / dual free vars: 239585\n",
      "\tsd vars: 160461, sd blks: 1\n",
      "Setup time: 4.63e-02s\n",
      "----------------------------------------------------------------------------\n",
      " Iter | pri res | dua res | rel gap | pri obj | dua obj | kap/tau | time (s)\n",
      "----------------------------------------------------------------------------\n",
      "     0| 1.04e+21  5.63e+19  1.00e+00 -1.54e+24  1.44e+22  1.16e+24  3.09e-01 \n",
      "   100| 3.73e-02  2.11e-02  1.68e-04  4.41e+02  4.41e+02  1.99e-15  2.48e+01 \n",
      "   200| 2.04e-02  1.24e-02  9.63e-05  4.45e+02  4.45e+02  1.41e-14  4.55e+01 \n",
      "   300| 9.88e-03  7.18e-03  3.64e-05  4.45e+02  4.45e+02  6.48e-15  6.59e+01 \n",
      "   400| 1.50e-03  8.62e-04  1.11e-05  4.45e+02  4.45e+02  9.68e-15  8.58e+01 \n",
      "   500| 1.70e-03  1.14e-03  2.10e-05  4.45e+02  4.45e+02  1.42e-14  1.06e+02 \n",
      "   600| 2.55e-03  1.42e-03  1.55e-05  4.45e+02  4.45e+02  1.88e-14  1.26e+02 \n",
      "   700| 2.57e-03  1.51e-03  1.34e-06  4.45e+02  4.45e+02  2.58e-15  1.46e+02 \n",
      "   800| 1.40e-03  9.18e-04  6.61e-06  4.45e+02  4.45e+02  1.07e-14  1.65e+02 \n",
      "   840| 6.12e-04  3.60e-04  1.87e-06  4.45e+02  4.45e+02  3.99e-15  1.73e+02 \n",
      "----------------------------------------------------------------------------\n",
      "Status: Solved\n",
      "Timing: Solve time: 1.73e+02s\n",
      "\tLin-sys: avg # CG iterations: 6.42, avg solve time: 1.88e-02s\n",
      "\tCones: avg projection time: 1.39e-01s\n",
      "\tAcceleration: avg step time: 3.94e-02s\n",
      "----------------------------------------------------------------------------\n",
      "Error metrics:\n",
      "dist(s, K) = 6.9605e-10, dist(y, K*) = 8.3156e-10, s'y/|s||y| = -1.7057e-12\n",
      "primal res: |Ax + s - b|_2 / (1 + |b|_2) = 6.1176e-04\n",
      "dual res:   |A'y + c|_2 / (1 + |c|_2) = 3.5967e-04\n",
      "rel gap:    |c'x + b'y| / (1 + |c'x| + |b'y|) = 1.8728e-06\n",
      "----------------------------------------------------------------------------\n",
      "c'x = 445.4954, -b'y = 445.4971\n",
      "============================================================================\n"
     ]
    }
   ],
   "source": [
    "solve!(problem, SCS.Optimizer(eps=1e-3, alpha=1.5))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "norm(float.(Gray.(Kref)) - X.value) = 1.2818300340904802\n",
      "norm(-(X.value)) = 124.34145989236622\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "283×283 reinterpret(reshape, Gray{Float64}, ::Matrix{Float64}) with eltype Gray{Float64}:\n",
       " Gray{Float64}(0.101852)   …  Gray{Float64}(0.66673)\n",
       " Gray{Float64}(0.0667327)     Gray{Float64}(0.502004)\n",
       " Gray{Float64}(0.078334)      Gray{Float64}(0.611723)\n",
       " Gray{Float64}(0.0863073)     Gray{Float64}(0.145132)\n",
       " Gray{Float64}(0.0784298)     Gray{Float64}(0.231344)\n",
       " Gray{Float64}(0.0746291)  …  Gray{Float64}(0.168597)\n",
       " Gray{Float64}(0.125416)      Gray{Float64}(0.192135)\n",
       " Gray{Float64}(0.439239)      Gray{Float64}(0.137224)\n",
       " Gray{Float64}(0.458867)      Gray{Float64}(0.117681)\n",
       " Gray{Float64}(0.450943)      Gray{Float64}(0.137247)\n",
       " Gray{Float64}(0.458806)   …  Gray{Float64}(0.125502)\n",
       " Gray{Float64}(0.46666)       Gray{Float64}(0.117553)\n",
       " Gray{Float64}(0.450944)      Gray{Float64}(0.117603)\n",
       " ⋮                         ⋱  \n",
       " Gray{Float64}(0.494059)      Gray{Float64}(0.443025)\n",
       " Gray{Float64}(0.474435)      Gray{Float64}(0.431389)\n",
       " Gray{Float64}(0.494203)      Gray{Float64}(0.451027)\n",
       " Gray{Float64}(0.470626)      Gray{Float64}(0.419584)\n",
       " Gray{Float64}(0.458774)   …  Gray{Float64}(0.423615)\n",
       " Gray{Float64}(0.443147)      Gray{Float64}(0.348978)\n",
       " Gray{Float64}(0.474438)      Gray{Float64}(0.360768)\n",
       " Gray{Float64}(0.482381)      Gray{Float64}(0.321581)\n",
       " Gray{Float64}(0.552847)      Gray{Float64}(0.372583)\n",
       " Gray{Float64}(0.552724)   …  Gray{Float64}(0.407666)\n",
       " Gray{Float64}(0.564911)      Gray{Float64}(0.419785)\n",
       " Gray{Float64}(0.56882)       Gray{Float64}(0.427406)"
      ]
     },
     "execution_count": 21,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "@show norm(float.(Gray.(Kref))-X.value)\n",
    "@show norm(-X.value)\n",
    "colorview(Gray, X.value)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "norm(float.(Gray.(Kref)) - X.value) = 1.2818300340904802\n",
      "norm(-(X.value)) = 124.34145989236622\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "283×283 reinterpret(reshape, Gray{Float64}, ::Matrix{Float64}) with eltype Gray{Float64}:\n",
       " Gray{Float64}(0.101852)   …  Gray{Float64}(0.66673)\n",
       " Gray{Float64}(0.0667327)     Gray{Float64}(0.502004)\n",
       " Gray{Float64}(0.078334)      Gray{Float64}(0.611723)\n",
       " Gray{Float64}(0.0863073)     Gray{Float64}(0.145132)\n",
       " Gray{Float64}(0.0784298)     Gray{Float64}(0.231344)\n",
       " Gray{Float64}(0.0746291)  …  Gray{Float64}(0.168597)\n",
       " Gray{Float64}(0.125416)      Gray{Float64}(0.192135)\n",
       " Gray{Float64}(0.439239)      Gray{Float64}(0.137224)\n",
       " Gray{Float64}(0.458867)      Gray{Float64}(0.117681)\n",
       " Gray{Float64}(0.450943)      Gray{Float64}(0.137247)\n",
       " Gray{Float64}(0.458806)   …  Gray{Float64}(0.125502)\n",
       " Gray{Float64}(0.46666)       Gray{Float64}(0.117553)\n",
       " Gray{Float64}(0.450944)      Gray{Float64}(0.117603)\n",
       " ⋮                         ⋱  \n",
       " Gray{Float64}(0.494059)      Gray{Float64}(0.443025)\n",
       " Gray{Float64}(0.474435)      Gray{Float64}(0.431389)\n",
       " Gray{Float64}(0.494203)      Gray{Float64}(0.451027)\n",
       " Gray{Float64}(0.470626)      Gray{Float64}(0.419584)\n",
       " Gray{Float64}(0.458774)   …  Gray{Float64}(0.423615)\n",
       " Gray{Float64}(0.443147)      Gray{Float64}(0.348978)\n",
       " Gray{Float64}(0.474438)      Gray{Float64}(0.360768)\n",
       " Gray{Float64}(0.482381)      Gray{Float64}(0.321581)\n",
       " Gray{Float64}(0.552847)      Gray{Float64}(0.372583)\n",
       " Gray{Float64}(0.552724)   …  Gray{Float64}(0.407666)\n",
       " Gray{Float64}(0.564911)      Gray{Float64}(0.419785)\n",
       " Gray{Float64}(0.56882)       Gray{Float64}(0.427406)"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "@show norm(float.(Gray.(Kref))-X.value)\n",
    "@show norm(-X.value)\n",
    "colorview(Gray, X.value)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "---\n",
    "### 🥒 Problem 3 Diet optimization problem.\n",
    "This is a common problem in Numerical Optimization, and you can find multiple references about it online. Here, we will use one of the examples in the JuMP package. Refer to this page for details: https://github.com/JuliaOpt/JuMP.jl/blob/master/examples/diet.jl.\n",
    "\n",
    "In this porblem we are given constraints on the number of (minimum, maximum) number of calories, protein, fat, and sodium to consume. We will first build a JuMP container to store this information and pass it as constraints later."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [],
   "source": [
    "using JuMP\n",
    "using GLPK"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "2-dimensional DenseAxisArray{Float64,2,...} with index sets:\n",
       "    Dimension 1, [\"calories\", \"protein\", \"fat\", \"sodium\"]\n",
       "    Dimension 2, [\"min\", \"max\"]\n",
       "And data, a 4×2 Matrix{Float64}:\n",
       " 1800.0  2200.0\n",
       "   91.0    Inf\n",
       "    0.0    65.0\n",
       "    0.0  1779.0"
      ]
     },
     "execution_count": 24,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "category_data = JuMP.Containers.DenseAxisArray(\n",
    "    [1800 2200;\n",
    "     91   Inf;\n",
    "     0    65;\n",
    "     0    1779], \n",
    "    [\"calories\", \"protein\", \"fat\", \"sodium\"], \n",
    "    [\"min\", \"max\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "You can think of this matrix as indexed by rows via the vector `[\"calories\", \"protein\", \"fat\", \"sodium\"]`, and indexed by columns via the vector `[\"min\", \"max\"]`. In fact, we can now checkout the values: `category_data[\"calories\",\"max\"]` or `category_data[\"fat\",\"min\"]`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "category_data[\"calories\", \"max\"] = 2200.0\n",
      "category_data[\"fat\", \"min\"] = 0.0\n"
     ]
    }
   ],
   "source": [
    "@show category_data[\"calories\",\"max\"] \n",
    "@show category_data[\"fat\",\"min\"]\n",
    ";"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next, we will encode some information about food data we have."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1-dimensional DenseAxisArray{Float64,1,...} with index sets:\n",
       "    Dimension 1, [\"hamburger\", \"chicken\", \"hot dog\", \"fries\", \"macaroni\", \"pizza\", \"salad\", \"milk\", \"ice cream\"]\n",
       "And data, a 9-element Vector{Float64}:\n",
       " 2.49\n",
       " 2.89\n",
       " 1.5\n",
       " 1.89\n",
       " 2.09\n",
       " 1.99\n",
       " 2.49\n",
       " 0.89\n",
       " 1.59"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "foods = [\"hamburger\", \"chicken\", \"hot dog\", \"fries\", \"macaroni\", \"pizza\",\"salad\", \"milk\", \"ice cream\"]\n",
    "\n",
    "# we will use the same concept we used above to create an array indexed \n",
    "# by foods this time to record the cost of each of these items\n",
    "cost = JuMP.Containers.DenseAxisArray(\n",
    "    [2.49, 2.89, 1.50, 1.89, 2.09, 1.99, 2.49, 0.89, 1.59],\n",
    "    foods)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Next we will create a new matrix to encode the calories,protein, fat, and sodium present in each of these foods. This will be a matrix encoded by foods by rows, and `[\"calories\", \"protein\", \"fat\", \"sodium\"]` by columns."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "food_data[\"chicken\", \"fat\"] = 10.0\n",
      "food_data[\"milk\", \"sodium\"] = 125.0\n"
     ]
    }
   ],
   "source": [
    "food_data = JuMP.Containers.DenseAxisArray(\n",
    "    [410 24 26 730;\n",
    "     420 32 10 1190;\n",
    "     560 20 32 1800;\n",
    "     380  4 19 270;\n",
    "     320 12 10 930;\n",
    "     320 15 12 820;\n",
    "     320 31 12 1230;\n",
    "     100  8 2.5 125;\n",
    "     330  8 10 180], \n",
    "    foods, \n",
    "    [\"calories\", \"protein\", \"fat\", \"sodium\"])\n",
    "\n",
    "@show food_data[\"chicken\", \"fat\"]\n",
    "@show food_data[\"milk\", \"sodium\"]\n",
    ";"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And now, we will build the model."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "1-dimensional DenseAxisArray{ConstraintRef{Model, MathOptInterface.ConstraintIndex{MathOptInterface.ScalarAffineFunction{Float64}, MathOptInterface.EqualTo{Float64}}, ScalarShape},1,...} with index sets:\n",
       "    Dimension 1, [\"calories\", \"protein\", \"fat\", \"sodium\"]\n",
       "And data, a 4-element Vector{ConstraintRef{Model, MathOptInterface.ConstraintIndex{MathOptInterface.ScalarAffineFunction{Float64}, MathOptInterface.EqualTo{Float64}}, ScalarShape}}:\n",
       " -nutrition[calories] + 410 buy[hamburger] + 420 buy[chicken] + 560 buy[hot dog] + 380 buy[fries] + 320 buy[macaroni] + 320 buy[pizza] + 320 buy[salad] + 100 buy[milk] + 330 buy[ice cream] = 0.0\n",
       " -nutrition[protein] + 24 buy[hamburger] + 32 buy[chicken] + 20 buy[hot dog] + 4 buy[fries] + 12 buy[macaroni] + 15 buy[pizza] + 31 buy[salad] + 8 buy[milk] + 8 buy[ice cream] = 0.0\n",
       " -nutrition[fat] + 26 buy[hamburger] + 10 buy[chicken] + 32 buy[hot dog] + 19 buy[fries] + 10 buy[macaroni] + 12 buy[pizza] + 12 buy[salad] + 2.5 buy[milk] + 10 buy[ice cream] = 0.0\n",
       " -nutrition[sodium] + 730 buy[hamburger] + 1190 buy[chicken] + 1800 buy[hot dog] + 270 buy[fries] + 930 buy[macaroni] + 820 buy[pizza] + 1230 buy[salad] + 125 buy[milk] + 180 buy[ice cream] = 0.0"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# set up the model\n",
    "model = Model(GLPK.Optimizer)\n",
    "\n",
    "categories = [\"calories\", \"protein\", \"fat\", \"sodium\"]\n",
    "\n",
    "# add the variables\n",
    "@variables(model, begin\n",
    "    # Variables for nutrition info\n",
    "    category_data[c, \"min\"] <= nutrition[c = categories] <= category_data[c, \"max\"]\n",
    "    # Variables for which foods to buy\n",
    "    buy[foods] >= 0\n",
    "end)\n",
    "\n",
    "# Objective - minimize cost\n",
    "@objective(model, Min, sum(cost[f] * buy[f] for f in foods))\n",
    "\n",
    "# Nutrition constraints\n",
    "@constraint(model, [c in categories],\n",
    "    sum(food_data[f, c] * buy[f] for f in foods) == nutrition[c]\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And finally, all what's left to be done is to solve the problem"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "JuMP.primal_status(model) == MOI.FEASIBLE_POINT = true\n",
      "JuMP.objective_value(model) ≈ 11.8288 = false\n",
      "atol = 0.0001 = 0.0001\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "0.0001"
      ]
     },
     "execution_count": 29,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "JuMP.optimize!(model)\n",
    "term_status = JuMP.termination_status(model)\n",
    "is_optimal = term_status == MOI.OPTIMAL\n",
    "@show JuMP.primal_status(model) == MOI.FEASIBLE_POINT\n",
    "@show JuMP.objective_value(model) ≈ 11.8288 atol = 1e-4"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And to actually look at the solution, we can look at the `buy` variable."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "9×2 Matrix{AffExpr}:\n",
       " buy[hamburger]  0.6045138888888888\n",
       " buy[chicken]    0\n",
       " buy[hot dog]    0\n",
       " buy[fries]      0\n",
       " buy[macaroni]   0\n",
       " buy[pizza]      0\n",
       " buy[salad]      0\n",
       " buy[milk]       6.9701388888888935\n",
       " buy[ice cream]  2.591319444444441"
      ]
     },
     "execution_count": 30,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "hcat(buy.data,JuMP.value.(buy.data))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "----\n",
    "### 🗺️ How many passports do you need to travel the world without obtaining a visa in advance?\n",
    "This problem is the same problem shown in the JuliaCon 2018 JuMP workshop, with updated code and data. The original post can be found here: https://github.com/juan-pablo-vielma/JuliaCon2018_JuMP_Workshop/blob/master/Introduction_Slides.ipynb.\n",
    "\n",
    "We will first get the data."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Cloning into 'passport-index-dataset'...\n"
     ]
    }
   ],
   "source": [
    ";git clone https://github.com/ilyankou/passport-index-dataset.git"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The file we need is `passport-index-dataset/passport-index-matrix.csv`, and we will use the `DelimitedFiles` package to read it -- this is mainly because what we are loading is a matrix and we will have to extract the matrix out of the DataFrame if we use the `CSV` package. Both are viable options, this will just be quicker."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "200×200 Matrix{Any}:\n",
       " \"Passport\"                \"Albania\"    \"Algeria\"        …    \"Afghanistan\"\n",
       " \"Afghanistan\"             \"e-visa\"     \"visa required\"     -1\n",
       " \"Albania\"               -1             \"visa required\"       \"visa required\"\n",
       " \"Algeria\"                 \"e-visa\"   -1                      \"visa required\"\n",
       " \"Andorra\"               90             \"visa required\"       \"visa required\"\n",
       " \"Angola\"                  \"e-visa\"     \"visa required\"  …    \"visa required\"\n",
       " \"Antigua and Barbuda\"   90             \"visa required\"       \"visa required\"\n",
       " \"Argentina\"             90             \"visa required\"       \"visa required\"\n",
       " \"Armenia\"               90             \"visa required\"       \"visa required\"\n",
       " \"Australia\"             90             \"visa required\"       \"visa required\"\n",
       " \"Austria\"               90             \"visa required\"  …    \"visa required\"\n",
       " \"Azerbaijan\"            90             \"visa required\"       \"visa required\"\n",
       " \"Bahamas\"               90             \"visa required\"       \"visa required\"\n",
       " ⋮                                                       ⋱  \n",
       " \"United Arab Emirates\"  90             \"visa required\"       \"visa required\"\n",
       " \"United Kingdom\"        90             \"visa required\"       \"visa required\"\n",
       " \"United States\"         90             \"visa required\"  …    \"visa required\"\n",
       " \"Uruguay\"               90             \"visa required\"       \"visa required\"\n",
       " \"Uzbekistan\"              \"e-visa\"     \"visa required\"       \"visa required\"\n",
       " \"Vanuatu\"                 \"e-visa\"     \"visa required\"       \"visa required\"\n",
       " \"Vatican\"               90             \"visa required\"       \"visa required\"\n",
       " \"Venezuela\"             90             \"visa required\"  …    \"visa required\"\n",
       " \"Vietnam\"                 \"e-visa\"     \"visa required\"       \"visa required\"\n",
       " \"Yemen\"                   \"e-visa\"     \"visa required\"       \"visa required\"\n",
       " \"Zambia\"                  \"e-visa\"     \"visa required\"       \"visa required\"\n",
       " \"Zimbabwe\"                \"e-visa\"     \"visa required\"       \"visa required\""
      ]
     },
     "execution_count": 32,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "passportdata = readdlm(joinpath(\"passport-index-dataset\",\"passport-index-matrix.csv\"),',')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "These are the possible options in this matrix:\n",
    "\n",
    "| Value | Explanation |\n",
    "|---|---|\n",
    "|7-360| number of visa-free days|\n",
    "|VF| visa-free travel (where number of days is not applicable or known, eg freedom of movement)|\n",
    "|VOA| visa on arrival|\n",
    "|ETA| eTA (electronic travel authority) required|\n",
    "|VR| visa required|\n",
    "|-1| where passport=destination, in matrix files only|\n",
    "\n",
    "So anything that is a number or \"VF\" or \"VOA\", can be entered without a visa in advance."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {},
   "outputs": [],
   "source": [
    "cntr = passportdata[2:end,1]\n",
    "vf = (x ->  typeof(x)==Int64 || x == \"VF\" || x == \"VOA\" ? 1 : 0).(passportdata[2:end,2:end]);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Set up the model"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$$ \\begin{alignat*}{1}\\text{feasibility}\\\\\n",
       "\\text{Subject to} \\quad\\end{alignat*}\n",
       " $$"
      ],
      "text/plain": [
       "A JuMP Model\n",
       "Feasibility problem with:\n",
       "Variables: 0\n",
       "Model mode: AUTOMATIC\n",
       "CachingOptimizer state: EMPTY_OPTIMIZER\n",
       "Solver name: GLPK"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "model = Model(GLPK.Optimizer)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Add the variables, constrains, and the objective function."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/latex": [
       "$$ pass_{1} + pass_{2} + pass_{3} + pass_{4} + pass_{5} + pass_{6} + pass_{7} + pass_{8} + pass_{9} + pass_{10} + pass_{11} + pass_{12} + pass_{13} + pass_{14} + pass_{15} + pass_{16} + pass_{17} + pass_{18} + pass_{19} + pass_{20} + pass_{21} + pass_{22} + pass_{23} + pass_{24} + pass_{25} + pass_{26} + pass_{27} + pass_{28} + pass_{29} + pass_{30} + pass_{31} + pass_{32} + pass_{33} + pass_{34} + pass_{35} + pass_{36} + pass_{37} + pass_{38} + pass_{39} + pass_{40} + pass_{41} + pass_{42} + pass_{43} + pass_{44} + pass_{45} + pass_{46} + pass_{47} + pass_{48} + pass_{49} + pass_{50} + pass_{51} + pass_{52} + pass_{53} + pass_{54} + pass_{55} + pass_{56} + pass_{57} + pass_{58} + pass_{59} + pass_{60} + pass_{61} + pass_{62} + pass_{63} + pass_{64} + pass_{65} + pass_{66} + pass_{67} + pass_{68} + pass_{69} + pass_{70} + pass_{71} + pass_{72} + pass_{73} + pass_{74} + pass_{75} + pass_{76} + pass_{77} + pass_{78} + pass_{79} + pass_{80} + pass_{81} + pass_{82} + pass_{83} + pass_{84} + pass_{85} + pass_{86} + pass_{87} + pass_{88} + pass_{89} + pass_{90} + pass_{91} + pass_{92} + pass_{93} + pass_{94} + pass_{95} + pass_{96} + pass_{97} + pass_{98} + pass_{99} + pass_{100} + pass_{101} + pass_{102} + pass_{103} + pass_{104} + pass_{105} + pass_{106} + pass_{107} + pass_{108} + pass_{109} + pass_{110} + pass_{111} + pass_{112} + pass_{113} + pass_{114} + pass_{115} + pass_{116} + pass_{117} + pass_{118} + pass_{119} + pass_{120} + pass_{121} + pass_{122} + pass_{123} + pass_{124} + pass_{125} + pass_{126} + pass_{127} + pass_{128} + pass_{129} + pass_{130} + pass_{131} + pass_{132} + pass_{133} + pass_{134} + pass_{135} + pass_{136} + pass_{137} + pass_{138} + pass_{139} + pass_{140} + pass_{141} + pass_{142} + pass_{143} + pass_{144} + pass_{145} + pass_{146} + pass_{147} + pass_{148} + pass_{149} + pass_{150} + pass_{151} + pass_{152} + pass_{153} + pass_{154} + pass_{155} + pass_{156} + pass_{157} + pass_{158} + pass_{159} + pass_{160} + pass_{161} + pass_{162} + pass_{163} + pass_{164} + pass_{165} + pass_{166} + pass_{167} + pass_{168} + pass_{169} + pass_{170} + pass_{171} + pass_{172} + pass_{173} + pass_{174} + pass_{175} + pass_{176} + pass_{177} + pass_{178} + pass_{179} + pass_{180} + pass_{181} + pass_{182} + pass_{183} + pass_{184} + pass_{185} + pass_{186} + pass_{187} + pass_{188} + pass_{189} + pass_{190} + pass_{191} + pass_{192} + pass_{193} + pass_{194} + pass_{195} + pass_{196} + pass_{197} + pass_{198} + pass_{199} $$"
      ],
      "text/plain": [
       "pass[1] + pass[2] + pass[3] + pass[4] + pass[5] + pass[6] + pass[7] + pass[8] + pass[9] + pass[10] + pass[11] + pass[12] + pass[13] + pass[14] + pass[15] + pass[16] + pass[17] + pass[18] + pass[19] + pass[20] + pass[21] + pass[22] + pass[23] + pass[24] + pass[25] + pass[26] + pass[27] + pass[28] + pass[29] + pass[30] + pass[31] + pass[32] + pass[33] + pass[34] + pass[35] + pass[36] + pass[37] + pass[38] + pass[39] + pass[40] + pass[41] + pass[42] + pass[43] + pass[44] + pass[45] + pass[46] + pass[47] + pass[48] + pass[49] + pass[50] + pass[51] + pass[52] + pass[53] + pass[54] + pass[55] + pass[56] + pass[57] + pass[58] + pass[59] + pass[60] + pass[61] + pass[62] + pass[63] + pass[64] + pass[65] + pass[66] + pass[67] + pass[68] + pass[69] + pass[70] + pass[71] + pass[72] + pass[73] + pass[74] + pass[75] + pass[76] + pass[77] + pass[78] + pass[79] + pass[80] + pass[81] + pass[82] + pass[83] + pass[84] + pass[85] + pass[86] + pass[87] + pass[88] + pass[89] + pass[90] + pass[91] + pass[92] + pass[93] + pass[94] + pass[95] + pass[96] + pass[97] + pass[98] + pass[99] + pass[100] + pass[101] + pass[102] + pass[103] + pass[104] + pass[105] + pass[106] + pass[107] + pass[108] + pass[109] + pass[110] + pass[111] + pass[112] + pass[113] + pass[114] + pass[115] + pass[116] + pass[117] + pass[118] + pass[119] + pass[120] + pass[121] + pass[122] + pass[123] + pass[124] + pass[125] + pass[126] + pass[127] + pass[128] + pass[129] + pass[130] + pass[131] + pass[132] + pass[133] + pass[134] + pass[135] + pass[136] + pass[137] + pass[138] + pass[139] + pass[140] + pass[141] + pass[142] + pass[143] + pass[144] + pass[145] + pass[146] + pass[147] + pass[148] + pass[149] + pass[150] + pass[151] + pass[152] + pass[153] + pass[154] + pass[155] + pass[156] + pass[157] + pass[158] + pass[159] + pass[160] + pass[161] + pass[162] + pass[163] + pass[164] + pass[165] + pass[166] + pass[167] + pass[168] + pass[169] + pass[170] + pass[171] + pass[172] + pass[173] + pass[174] + pass[175] + pass[176] + pass[177] + pass[178] + pass[179] + pass[180] + pass[181] + pass[182] + pass[183] + pass[184] + pass[185] + pass[186] + pass[187] + pass[188] + pass[189] + pass[190] + pass[191] + pass[192] + pass[193] + pass[194] + pass[195] + pass[196] + pass[197] + pass[198] + pass[199]"
      ]
     },
     "execution_count": 35,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "@variable(model, pass[1:length(cntr)], Bin)\n",
    "@constraint(model, [j=1:length(cntr)], sum( vf[i,j]*pass[i] for i in 1:length(cntr)) >= 1)\n",
    "@objective(model, Min, sum(pass))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "And finally, solve the problem"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [],
   "source": [
    "JuMP.optimize!(model)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "65.0 passports: Afghanistan, Angola, Australia, Azerbaijan, Bahrain, Bosnia and Herzegovina, Brunei, Cambodia, Cameroon, Canada, Chile, Colombia, Comoros, DR Congo, Djibouti, Equatorial Guinea, Eritrea, Fiji, Gabon, Guinea-Bissau, Hong Kong, Hungary, India, Indonesia, Iraq, Ireland, Israel, Jamaica, Japan, Kuwait, Laos, Liberia, Libya, Macao, Madagascar, Malaysia, Marshall Islands, Mauritania, Mauritius, Micronesia, Mongolia, Nauru, Nepal, New Zealand, North Korea, Norway, Oman, Palestine, Papua New Guinea, Qatar, Russia, Saudi Arabia, Singapore, Solomon Islands, Somalia, South Sudan, Sri Lanka, Syria, Taiwan, Timor-Leste, Togo, Turkmenistan, United States, Uruguay, Vietnam"
     ]
    }
   ],
   "source": [
    "print(JuMP.objective_value(model),\" passports: \",join(cntr[findall(JuMP.value.(pass) .== 1)],\", \"))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Finally...\n",
    "After finishing this notebook, you should be able to:\n",
    "- [ ] solve optimization problems via the Convex.jl package\n",
    "- [ ] solve optimization problems via the JuMP.jl package"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 🥳 One cool finding\n",
    "\n",
    "We found out that you need at least 21 passports to tour the world visa free. Here is one solutions we found:\n",
    "\n",
    "`Afghanistan, Austria, Comoros, Equatorial Guinea, Eritrea, Gambia, Georgia, Hong Kong, India, Iraq, Kenya, Madagascar, Maldives, North Korea, Papua New Guinea, Seychelles, Singapore, Somalia, Tunisia, United Arab Emirates, Zimbabwe`\n"
   ]
  }
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