demo.ipynb

{
 "cells": [
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Examples of Game-Theoretic Models applied to Energy Markets\n",
    "\n",
    "by: Julia Barbosa\n",
    "Date: 07.05.23\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "using Plots"
   ]
  },
  {
   "attachments": {},
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### 1. Cournout Model single Market\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Feasibility\n",
      "Subject to"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " [-x[1] + πel - 20, -x[2] + πel - 20, -x[3] + πel - 20, x[1], x[2], x[3]] in MathOptInterface.Complements(3)\n",
      " [-πel - D + 100, D] in MathOptInterface.Complements(1)\n",
      " [-x[1] - x[2] - x[3] + D, πel] in MathOptInterface.Complements(1)"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Path 5.0.03 (Fri Jun 26 10:05:33 2020)\n",
      "Written by Todd Munson, Steven Dirkse, Youngdae Kim, and Michael Ferris\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Crash Log\n",
      "major  func  diff  size  residual    step       prox   (label)\n",
      "    0     0             2.8284e+20             0.0e+00 (f[    4])\n",
      "pn_search terminated: empty basis.\n",
      "\n",
      "Major Iteration Log\n",
      "major minor  func  grad  residual    step  type prox    inorm  (label)\n",
      "    0     0     1     1 2.8284e+20           I 0.0e+00 2.0e+20 (f[    4])\n",
      "    1     1     2     2 2.8284e+20  1.0e+00 SO 0.0e+00 2.0e+20 (f[    4])\n",
      "    2     1     3     3 2.8284e+20  1.0e+00 SO 0.0e+00 2.0e+20 (f[    4])\n",
      "    3     1     4     4 2.8284e+20  1.0e+00 SO 0.0e+00 2.0e+20 (f[    4])\n",
      "    4     1     5     5 2.8284e+20  1.0e+00 SO 0.0e+00 2.0e+20 (f[    4])\n",
      "    5     1     6     6 2.8284e+20  1.0e+00 SO 0.0e+00 2.0e+20 (f[    4])\n",
      "    6     1     7     7 2.8284e+20  1.0e+00 SO 0.0e+00 2.0e+20 (f[    4])\n",
      "    7     1     8     8 2.8284e+20  1.0e+00 SO 0.0e+00 2.0e+20 (f[    4])\n",
      "    8     1     9     9 2.8284e+20  1.0e+00 SO 0.0e+00 2.0e+20 (f[    4])\n",
      "    9     1    10    10 2.8284e+20  1.0e+00 SO 0.0e+00 2.0e+20 (f[    4])\n",
      "\n",
      "Restart Log\n",
      "proximal_perturbation 0\n",
      "crash_method none\n",
      "crash_perturb yes\n",
      "nms_initial_reference_factor 2\n",
      "lemke_start_type slack\n",
      "proximal_perturbation 1.0000e-01\n",
      "\n",
      "Major Iteration Log\n",
      "major minor  func  grad  residual    step  type prox    inorm  (label)\n",
      "    9     0    12    11 2.8284e+20           R 1.0e-01 2.0e+20 (f[    4])\n",
      "   10     1    13    12 2.8284e+20  1.0e+00 SO 4.0e-02 2.0e+20 (f[    4])\n",
      "   11     1    14    13 2.8284e+20  1.0e+00 SO 1.6e-02 2.0e+20 (f[    4])\n",
      "   12     1    15    14 2.8284e+20  1.0e+00 SO 6.4e-03 2.0e+20 (f[    4])\n",
      "   13     1    16    15 2.8284e+20  1.0e+00 SO 2.6e-03 2.0e+20 (f[    4])\n",
      "   14     1    17    16 2.8284e+20  1.0e+00 SO 1.0e-03 2.0e+20 (f[    4])\n",
      "   15     1    18    17 2.8284e+20  1.0e+00 SO 4.1e-04 2.0e+20 (f[    4])\n",
      "   16     1    19    18 2.8284e+20  1.0e+00 SO 1.6e-04 2.0e+20 (f[    4])\n",
      "   17     1    20    19 2.8284e+20  1.0e+00 SO 6.6e-05 2.0e+20 (f[    4])\n",
      "   18     1    21    20 2.8284e+20  1.0e+00 SO 2.6e-05 2.0e+20 (f[    4])\n",
      "\n",
      "Restart Log\n",
      "proximal_perturbation 0\n",
      "crash_method none\n",
      "crash_perturb no\n",
      "nms_initial_reference_factor 10\n",
      "nms_memory_size 2\n",
      "nms_mstep_frequency 1\n",
      "lemke_search_type slack\n",
      "\n",
      "Major Iteration Log\n",
      "major minor  func  grad  residual    step  type prox    inorm  (label)\n",
      "   18     0    23    21 2.8284e+20           R 0.0e+00 2.0e+20 (f[    4])\n",
      "   19     1    24    22 2.8284e+20  1.0e+00 SM 0.0e+00 2.0e+20 (f[    4])\n",
      "   20     1    25    23 2.8284e+20  1.0e+00 SM 0.0e+00 2.0e+20 (f[    4])\n",
      "   21     1    33    24 2.8284e+20  5.5e-02 SB 0.0e+00 2.0e+20 (f[    5])\n",
      "   22     1    34    25 3.2768e+04  1.0e+00 SM 0.0e+00 3.3e+04 (f[    4])\n",
      "   23     1    35    26 0.0000e+00  1.0e+00 SM 0.0e+00 0.0e+00 (f[    1])\n",
      "\n",
      "Major Iterations. . . . 23\n",
      "Minor Iterations. . . . 25\n",
      "Restarts. . . . . . . . 2\n",
      "Crash Iterations. . . . 0\n",
      "Gradient Steps. . . . . 0\n",
      "Function Evaluations. . 35\n",
      "Gradient Evaluations. . 26\n",
      "Basis Time. . . . . . . 0.000000\n",
      "Total Time. . . . . . . 1.343000\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Residual. . . . . . . . 0.000000e+00\n"
     ]
    },
    {
     "data": {
      "image/png": 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     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "include(\"src/ex1.jl\")\n",
    "\n",
    "number_producers = 3\n",
    "marginal_cost = 20.0\n",
    "D0 = 100.0\n",
    "a = 1.0 # \n",
    "\n",
    "res = run_model(EX1Input(number_producers, marginal_cost, D0, a))\n",
    "\n",
    "p1 = plot_energy(res)\n",
    "p2 = plot_prices(res)\n",
    "\n",
    "plot(p1, p2, size=(800, 400))\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "include(\"src/ex2.jl\")\n",
    "\n",
    "number_of_producer = 3\n",
    "marginal_cost = [20.0, 20, 20]\n",
    "emissions_intensity = [0, 0,0.0]\n",
    "emission_budget = 1000.0\n",
    "\n",
    "D0 = 100.0\n",
    "a = 1.0\n",
    "\n",
    "res = run_model(EX2Input(number_of_producer, marginal_cost, emissions_intensity, emission_budget, D0, a)) \n",
    "\n",
    "p1 = plot_energy(res)\n",
    "p2 = plot_prices(res)\n",
    "\n",
    "plot(p1, p2, size=(800, 400)\n",
    "\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Max πel*x[2] - 20 x[2]\n",
      "Subject to"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      " dLdx[1] : -x[1] + πel - δ[1] == 20.0\n",
      " dLdx[3] : -x[3] + πel - δ[3] == 20.0\n",
      " -πel - D == -100.0\n",
      " -x[1] - x[2] - x[3] + D == 0.0\n",
      " x[2] <= 100.0\n",
      " δ[1] >= 0.0\n",
      " δ[3] >= 0.0\n",
      " (100.0 - x[1]) - 0.0 >= 0\n",
      " δ[1] - 0.0 >= 0\n",
      " (sqrt((δ[1] - 0.0) ^ 2.0 + ((100.0 - x[1]) - 0.0) ^ 2.0 + 1.0e-8) - ((δ[1] - 0.0) + ((100.0 - x[1]) - 0.0))) - 0.0 == 0\n",
      " (100.0 - x[3]) - 0.0 >= 0\n",
      " δ[3] - 0.0 >= 0\n",
      " (sqrt((δ[3] - 0.0) ^ 2.0 + ((100.0 - x[3]) - 0.0) ^ 2.0 + 1.0e-8) - ((δ[3] - 0.0) + ((100.0 - x[3]) - 0.0))) - 0.0 == 0"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "This is Ipopt version 3.13.4, running with linear solver mumps.\n",
      "NOTE: Other linear solvers might be more efficient (see Ipopt documentation).\n",
      "\n",
      "Number of nonzeros in equality constraint Jacobian...:       16\n",
      "Number of nonzeros in inequality constraint Jacobian.:        5\n",
      "Number of nonzeros in Lagrangian Hessian.............:        7\n",
      "\n",
      "Total number of variables............................:        7\n",
      "                     variables with only lower bounds:        2\n",
      "                variables with lower and upper bounds:        0\n",
      "                     variables with only upper bounds:        0\n",
      "Total number of equality constraints.................:        6\n",
      "Total number of inequality constraints...............:        5\n",
      "        inequality constraints with only lower bounds:        4\n",
      "   inequality constraints with lower and upper bounds:        0\n",
      "        inequality constraints with only upper bounds:        1\n",
      "\n",
      "iter    objective    inf_pr   inf_du lg(mu)  ||d||  lg(rg) alpha_du alpha_pr  ls\n",
      "   0  0.0000000e+00 1.00e+02 7.63e+00  -1.0 0.00e+00    -  0.00e+00 0.00e+00   0\n",
      "   1  5.1474548e+02 1.00e+00 1.00e-01  -1.0 6.65e+01    -  1.00e+00 9.90e-01h  1\n",
      "   2  5.3314772e+02 9.94e-03 8.22e+00  -1.0 8.46e-01    -  9.98e-01 9.90e-01f  1\n",
      "   3  5.3333333e+02 1.42e-14 2.28e-03  -1.0 1.66e-02    -  1.00e+00 1.00e+00h  1\n",
      "   4  5.3333333e+02 1.42e-14 1.84e-11  -5.7 1.35e-03    -  1.00e+00 1.00e+00f  1\n",
      "   5  5.3333333e+02 1.42e-14 2.84e-14  -8.6 8.72e-08    -  1.00e+00 1.00e+00h  1\n",
      "\n",
      "Number of Iterations....: 5\n",
      "\n",
      "                                   (scaled)                 (unscaled)\n",
      "Objective...............:  -5.3333333333487167e+02    5.3333333333487167e+02\n",
      "Dual infeasibility......:   2.8421709430404007e-14    2.8421709430404007e-14\n",
      "Constraint violation....:   1.4210854715202004e-14    1.4210854715202004e-14\n",
      "Complementarity.........:   2.5059095092637007e-09   -2.5059095092637007e-09\n",
      "Overall NLP error.......:   2.5059095092637007e-09    2.8421709430404007e-14\n",
      "\n",
      "\n",
      "Number of objective function evaluations             = 6\n",
      "Number of objective gradient evaluations             = 6\n",
      "Number of equality constraint evaluations            = 6\n",
      "Number of inequality constraint evaluations          = 6\n",
      "Number of equality constraint Jacobian evaluations   = 6\n",
      "Number of inequality constraint Jacobian evaluations = 6\n",
      "Number of Lagrangian Hessian evaluations             = 5\n",
      "Total CPU secs in IPOPT (w/o function evaluations)   =      0.003\n",
      "Total CPU secs in NLP function evaluations           =      0.000\n",
      "\n",
      "EXIT: Optimal Solution Found.\n"
     ]
    },
    {
     "data": {
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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "include(\"src/ex3.jl\")\n",
    "\n",
    "number_of_producer = 3\n",
    "leader = 2\n",
    "marginal_cost = [20.0, 20.0, 20.0]\n",
    "maximum_capacity = [100.0, 100, 100]\n",
    "\n",
    "D0 = 100.0\n",
    "a = 1.0\n",
    "\n",
    "input = EX3Input(number_of_producer, leader, marginal_cost,maximum_capacity, D0, a)\n",
    "\n",
    "res = run_model(input)\n",
    "\n",
    "plot(plot_production(res), plot_prices(res), size=(800, 400))\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Staring Diagonalization...  \n",
      "   1  - Production: [0.0, 0.0]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "   2  - Production: [550.0, 725.0]\n",
      "   3  - Production: [450.0, 650.0]\n",
      "   4  - Production: [675.0, 450.0]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "   5  - Production: [650.0, 675.0]\n",
      "   6  - Production: [450.0, 650.0]\n",
      "   7  - Production: [675.0, 450.0]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "   8  - Production: [650.0, 675.0]\n",
      "   9  - Production: [450.0, 650.0]\n",
      "   10  - Production: [675.0, 450.0]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "   11  - Production: [650.0, 675.0]\n",
      "   12  - Production: [450.0, 650.0]\n",
      "   13  - Production: [675.0, 450.0]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "   14  - Production: [650.0, 675.0]\n",
      "   15  - Production: [450.0, 650.0]\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "   16  - Production: [675.0, 450.0]\n",
      "   17  - Production: [650.0, 675.0]\n",
      "   18  - Production: [450.0, 650.0]\n",
      "   19  - Production: [675.0, 450.0]"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "   20  - Production: [650.0, 675.0]\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┌ Warning: Model DID NOT converge in 20 iterations\n",
      "└ @ Main d:\\GIT-OTHER\\GT4EM\\src\\ex4.jl:202\n"
     ]
    },
    {
     "data": {
      "image/png": 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      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model did not converge!! Results are not NE.\n",
      "LeadersOutput([450.0000000181086, 649.9998500182489], [45.00001999817712, 44.999994998187105], [99.99980000012005, -99.99980000012005], [549.9998000182286, 550.000050018129], 44.999994998187105, [2.500001500506999e-5, 2.4984500973221046e-11], LeadersInput([1, 2], [450.0000000181086, 649.9998500182489], [1000.0, 1000.0], [0.1, 0.1], 100.0), :not_converged)"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "┌ Warning: Model did not converge!! Results are not NE.\n",
      "└ @ Main d:\\GIT-OTHER\\GT4EM\\src\\ex4.jl:262\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Leader 1 production: LeadersOutput([550.0000000028698, 250.0], [54.99999999966483, 65.00000000004819], [-99.99999999951807, 99.99999999951807], [450.0000000033517, 349.9999999995181], 65.00000000004819, [2.4982142552098513e-11, 10.000000000408342], LeadersInput([1, 2], [0.0, 250.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([550.0000000015498, 255.0], [54.999999999792394, 64.50000000005262], [-99.99999999947376, 99.99999999947376], [450.000000002076, 354.9999999994738], 64.50000000005262, [2.4977131939829515e-11, 9.50000000028521], LeadersInput([1, 2], [0.0, 255.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([550.0000000029229, 260.0], [54.9999999996553, 64.0000000000524], [-99.9999999994759, 99.9999999994759], [450.0000000034469, 359.9999999994759], 64.0000000000524, [2.500560644783465e-11, 9.000000000422101], LeadersInput([1, 2], [0.0, 260.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Leader 1 production: LeadersOutput([550.0000000019182, 265.0], [54.999999999749356, 63.50000000005881], [-99.99999999941177, 99.99999999941177], [450.0000000025065, 364.9999999994118], 63.50000000005881, [2.5009885042893523e-11, 8.50000000033447], LeadersInput([1, 2], [0.0, 265.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([550.0000000021626, 270.0], [54.99999999972125, 63.000000000062506], [-99.999999999375, 99.999999999375], [450.0000000027876, 369.999999999375], 63.000000000062506, [2.4976477854301286e-11, 8.000000000366239], LeadersInput([1, 2], [0.0, 270.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Leader 1 production: LeadersOutput([550.0000000024576, 275.0], [54.99999999968756, 62.50000000006666], [-99.99999999933333, 99.99999999933333], [450.0000000031243, 374.99999999933334], 62.50000000006666, [2.5003949016381597e-11, 7.500000000404105], LeadersInput([1, 2], [0.0, 275.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([550.0000000032713, 280.0], [54.999999999601634, 62.00000000007122], [-99.99999999928775, 99.99999999928775], [450.00000000398364, 379.99999999928775], 62.00000000007122, [2.497020882731731e-11, 7.000000000494555], LeadersInput([1, 2], [0.0, 280.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([550.0000000038667, 285.0], [54.999999999536676, 61.50000000007666], [-99.99999999923345, 99.99999999923345], [450.00000000463325, 384.99999999923347], 61.50000000007666, [2.5012219173954733e-11, 6.5000000005650005], LeadersInput([1, 2], [0.0, 285.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Leader 1 production: LeadersOutput([550.0000000040553, 290.0], [54.99999999951131, 61.00000000008314], [-99.99999999916847, 99.99999999916847], [450.00000000488694, 389.99999999916844], 61.00000000008314, [2.4979560846975764e-11, 6.0000000005968115], LeadersInput([1, 2], [0.0, 290.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([550.0000000047563, 295.0], [54.99999999943364, 60.500000000090715], [-99.99999999909275, 99.99999999909275], [450.00000000566365, 394.9999999990927], 60.500000000090715, [2.501056827535211e-11, 5.500000000682087], LeadersInput([1, 2], [0.0, 295.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Leader 1 production: LeadersOutput([550.000000005501, 300.0], [54.999999999349896, 60.0000000001], [-99.999999999, 99.999999999], [450.00000000650095, 399.999999999], 60.0000000001, [2.4979857668208043e-11, 5.000000000775082], LeadersInput([1, 2], [0.0, 300.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([550.0000000069901, 305.0], [54.9999999991901, 59.50000000011087], [-99.99999999889121, 99.99999999889121], [450.00000000809894, 404.9999999988912], 59.50000000011087, [2.5005252771529758e-11, 4.500000000945774], LeadersInput([1, 2], [0.0, 305.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([550.0000000079687, 310.0], [54.99999999907812, 59.000000000125], [-99.99999999875, 99.99999999875], [450.0000000092187, 409.99999999875], 59.000000000125, [2.4973458755606963e-11, 4.000000001071852], LeadersInput([1, 2], [0.0, 310.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([550.0000000112049, 315.0], [54.999999998736655, 58.500000000142855], [-99.99999999857143, 99.99999999857143], [450.00000001263345, 414.9999999985714], 58.500000000142855, [2.497740705818106e-11, 3.5000000014311765], LeadersInput([1, 2], [0.0, 315.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Leader 1 production: LeadersOutput([550.0000000152506, 320.0], [54.999999998308276, 58.00000000016665], [-99.99999999833352, 99.99999999833352], [450.00000001691717, 419.9999999983335], 58.00000000016665, [2.4989437630136052e-11, 3.0000000018833655], LeadersInput([1, 2], [0.0, 320.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([550.0000000219757, 325.0], [54.999999997602565, 57.50000000019986], [-99.99999999800127, 99.99999999800127], [450.00000002397434, 424.9999999980013], 57.50000000019986, [2.4986021839284927e-11, 2.5000000026222873], LeadersInput([1, 2], [0.0, 325.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([550.0000000342753, 330.0], [54.999999996322465, 57.00000000025], [-99.9999999975, 99.9999999975], [450.00000003677525, 429.9999999975], 57.00000000025, [2.498199249566416e-11, 2.000000003952512], LeadersInput([1, 2], [0.0, 330.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Leader 1 production: LeadersOutput([550.0000000609291, 335.0], [54.99999999357375, 56.50000000033332], [-99.9999999966667, 99.9999999966667], [450.00000006426234, 434.9999999966667], 56.50000000033332, [2.4973075082272715e-11, 1.5000000067845438], LeadersInput([1, 2], [0.0, 335.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([550.0000001371108, 340.0], [54.99999998578892, 56.0000000005], [-99.999999995, 99.999999995], [450.00000014211076, 439.999999995], 56.0000000005, [2.4981588693904632e-11, 1.0000000147360657], LeadersInput([1, 2], [0.0, 340.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Leader 1 production: LeadersOutput([550.0000005487826, 345.0], [54.99999994412174, 55.500000001000004], [-99.99999999, 99.99999999], [450.0000005587827, 444.99999999], 55.500000001000004, [2.5012934763115613e-11, 0.5000000569032802], LeadersInput([1, 2], [0.0, 345.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([550.0239531003076, 350.0], [54.99760448126437, 55.000000208704876], [-99.99999791295126, 99.99999791295126], [450.0239551873563, 449.99999791295124], 55.000000208704876, [2.4985588542330084e-11, 0.002395727465491928], LeadersInput([1, 2], [0.0, 350.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([555.0015741247945, 355.0], [54.49983952993416, 54.50000305758638], [-99.99996942413611, 99.99996942413611], [455.0016047006584, 454.9999694241361], 54.50000305758638, [2.4993584811154053e-11, 0.00016352767722242778], LeadersInput([1, 2], [0.0, 355.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([560.0010524002647, 360.0], [53.9998903744366, 54.00000438553692], [-99.99995614463074, 99.99995614463074], [460.00109625563397, 459.99995614463074], 54.00000438553692, [2.4988050308281394e-11, 0.00011401112530762984], LeadersInput([1, 2], [0.0, 360.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Leader 1 production: LeadersOutput([565.000808392119, 365.0], [53.49991371058195, 53.50000545020615], [-99.99994549793853, 99.99994549793853], [465.00086289418044, 464.9999454979385], 53.50000545020615, [2.4981629544176965e-11, 9.173964918446793e-5], LeadersInput([1, 2], [0.0, 365.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([570.0006548310195, 370.0], [52.99992812801163, 53.000006388886426], [-99.99993611113577, 99.99993611113577], [470.00071871988365, 469.99993611113575], 53.000006388886426, [2.4968861658233997e-11, 7.826089976459908e-5], LeadersInput([1, 2], [0.0, 370.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([575.000544095996, 375.0], [52.499938335542744, 52.50000725485765], [-99.99992745142355, 99.99992745142355], [475.0006166445725, 474.9999274514235], 52.50000725485765, [2.498804702125489e-11, 6.89193399001367e-5], LeadersInput([1, 2], [0.0, 375.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Leader 1 production: LeadersOutput([580.000457616849, 380.0], [51.9999461625088, 52.00000807580629], [-99.99991924193696, 99.99991924193696], [480.000538374912, 479.99991924193694], 52.00000807580629, [2.4986057410164535e-11, 6.191332248123533e-5], LeadersInput([1, 2], [0.0, 380.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([585.000386410948, 385.0], [51.49995249026158, 51.50000886864362], [-99.99991131356379, 99.99991131356379], [485.00047509738414, 484.9999113135638], 51.50000886864362, [2.5001856365459742e-11, 5.637840703881784e-5], LeadersInput([1, 2], [0.0, 385.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([590.0003255095797, 390.0], [50.99995780413032, 51.0000096449117], [-99.99990355088298, 99.99990355088298], [490.0004219586968, 489.99990355088295], 51.0000096449117, [2.4983941088592127e-11, 5.1840806364306956e-5], LeadersInput([1, 2], [0.0, 390.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([595.0002718955918, 395.0], [50.499962397241475, 50.50001041319932], [-99.99989586800672, 99.99989586800672], [495.00037602758516, 494.99989586800666], 50.50001041319932, [2.497085305678153e-11, 4.8015982813633543e-5], LeadersInput([1, 2], [0.0, 395.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Leader 1 production: LeadersOutput([600.0002236041106, 400.0], [49.99996645920843, 50.00001118038051], [-99.99988819619495, 99.99988819619495], [500.00033540791566, 499.9998881961949], 50.00001118038051, [2.4996244750857473e-11, 4.472119707712952e-5], LeadersInput([1, 2], [0.0, 400.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([605.0001792821287, 405.0], [49.49997011946626, 49.50001195232086], [-99.99988047679126, 99.99988047679126], [505.00029880533737, 504.9998804767913], 49.50001195232086, [2.4997263941427572e-11, 4.183287959720124e-5], LeadersInput([1, 2], [0.0, 405.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([610.0001379530668, 410.0], [48.99997347037301, 49.00001273432032], [-99.99987265679685, 99.99987265679685], [510.00026529626996, 509.9998726567968], 49.00001273432032, [2.497587943212402e-11, 3.926397229049556e-5], LeadersInput([1, 2], [0.0, 410.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([615.0000988818404, 415.0], [48.499976580398524, 48.50001353141744], [-99.99986468582566, 99.99986468582566], [515.0002341960147, 514.9998646858256], 48.50001353141744, [2.5014070012156094e-11, 3.6951043925911884e-5], LeadersInput([1, 2], [0.0, 415.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Leader 1 production: LeadersOutput([620.0000614928721, 420.0], [47.99997950209178, 48.000014348621], [-99.99985651379001, 99.99985651379001], [520.0002049790821, 519.99985651379], 48.000014348621, [2.502490571228359e-11, 3.484655424469265e-5], LeadersInput([1, 2], [0.0, 420.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([625.0000253175975, 425.0], [47.49998227713445, 47.50001519110579], [-99.99984808894214, 99.99984808894214], [525.0001772286554, 524.9998480889421], 47.50001519110579, [2.4986332713630517e-11, 3.291399632608231e-5], LeadersInput([1, 2], [0.0, 425.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([629.9999899590929, 430.0], [46.999984939693576, 47.00001606439713], [-99.99983935602862, 99.99983935602862], [530.0001506030643, 529.9998393560286], 47.00001606439713, [2.4983490851913082e-11, 3.1124728533269514e-5], LeadersInput([1, 2], [0.0, 430.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([634.9999550668882, 435.0], [46.49998751874831, 46.50001697456286], [-99.99983025437136, 99.99983025437136], [535.0001248125169, 534.9998302543713], 46.50001697456286, [2.499145126636113e-11, 2.9455839540365977e-5], LeadersInput([1, 2], [0.0, 435.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Leader 1 production: LeadersOutput([639.9999203178302, 440.0], [45.99999003978749, 46.000017928429486], [-99.99982071570513, 99.99982071570513], [540.000099602125, 539.9998207157051], 46.000017928429486, [2.501994088102383e-11, 2.788866701186739e-5], LeadersInput([1, 2], [0.0, 440.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([644.9998854003345, 445.0], [45.499992526124906, 45.50001893384164], [-99.99981066158364, 99.99981066158364], [545.0000747387509, 544.9998106615836], 45.50001893384164, [2.5001499593246972e-11, 2.6407741736438183e-5], LeadersInput([1, 2], [0.0, 445.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([649.9998500001404, 450.0], [44.99999499999796, 45.000019999987984], [-99.99980000012008, 99.99980000012008], [550.0000500000203, 549.9998000001201], 45.000019999987984, [2.4987474332545578e-11, 2.5000015010049855e-5], LeadersInput([1, 2], [0.0, 450.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([654.999813786007, 455.0], [44.49999748357338, 44.5000211378259], [-99.99978862174085, 99.99978862174085], [555.000025164266, 554.9997886217409], 44.5000211378259, [2.4986422344707605e-11, 2.3654277503242866e-5], LeadersInput([1, 2], [0.0, 455.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Leader 1 production: LeadersOutput([659.9997763938051, 460.0], [43.99999999996814, 44.00002236065134], [-99.99977639348643, 99.99977639348643], [560.0000000003187, 559.9997763934865], 44.00002236065134, [2.4985545555073155e-11, 2.2360708192575224e-5], LeadersInput([1, 2], [0.0, 460.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([664.9997374071617, 465.0], [43.50000257439925, 43.500023684884574], [-99.99976315115416, 99.99976315115416], [564.9999742560075, 564.9997631511542], 43.500023684884574, [2.498011628489027e-11, 2.1110510301309048e-5], LeadersInput([1, 2], [0.0, 465.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([669.9996963321248, 470.0], [43.00000523560526, 43.000025131182255], [-99.99974868817739, 99.99974868817739], [569.9999476439474, 569.9997486881774], 43.000025131182255, [2.5003739533426922e-11, 1.9895601997785444e-5], LeadersInput([1, 2], [0.0, 470.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([674.9996525619927, 475.0], [42.50000801774533, 42.5000267260554], [-99.99973273944593, 99.99973273944593], [574.9999198225466, 574.999732739446], 42.5000267260554, [2.501387168941349e-11, 1.870833508311628e-5], LeadersInput([1, 2], [0.0, 475.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Leader 1 production: LeadersOutput([679.9996053259994, 480.0], [42.00001096310459, 42.000028504295464], [-99.99971495704526, 99.99971495704526], [579.9998903689541, 579.9997149570453], 42.000028504295464, [2.4992492789122123e-11, 1.7541215865213654e-5], LeadersInput([1, 2], [0.0, 480.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([684.9995536109507, 485.0], [41.50001412616579, 41.50003051273913], [-99.99969487260867, 99.99969487260867], [584.999858738342, 584.9996948726086], 41.50003051273913, [2.4983829875736542e-11, 1.6386598325838187e-5], LeadersInput([1, 2], [0.0, 485.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([689.9994960358567, 490.0], [41.0000175800656, 41.000032816348714], [-99.99967183651282, 99.99967183651282], [589.999824199344, 589.9996718365128], 41.000032816348714, [2.499147458980936e-11, 1.5236308106262928e-5], LeadersInput([1, 2], [0.0, 490.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Leader 1 production: LeadersOutput([694.9994306408108, 495.0], [40.50002142740663, 40.500035508512276], [-99.99964491487718, 99.99964491487718], [594.9997857259336, 594.9996449148772], 40.500035508512276, [2.4987378193053665e-11, 1.4081130632488926e-5], LeadersInput([1, 2], [0.0, 495.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([699.9993545094285, 500.0], [40.00002581951952, 40.00003872953762], [-99.99961270462376, 99.99961270462376], [599.9997418048047, 599.9996127046238], 40.00003872953762, [2.5000440134658606e-11, 1.2910043100763349e-5], LeadersInput([1, 2], [0.0, 500.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([704.9992630417405, 505.0], [39.50003099345025, 39.50004270237569], [-99.99957297624317, 99.99957297624317], [604.9996900654974, 604.9995729762431], 39.50004270237569, [2.499777346792115e-11, 1.1708950427350557e-5], LeadersInput([1, 2], [0.0, 505.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([709.9991484139047, 510.0], [39.00003735012043, 39.00004780848911], [-99.99952191510906, 99.99952191510906], [609.9996264987956, 609.999521915109], 39.00004780848911, [2.4998069802053523e-11, 1.0458393675947556e-5], LeadersInput([1, 2], [0.0, 510.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Leader 1 production: LeadersOutput([714.9989958655277, 515.0], [38.500045642289926, 38.50005477115731], [-99.99945228842684, 99.99945228842684], [614.9995435771008, 614.9994522884269], 38.50005477115731, [2.4986271393971933e-11, 9.128892367758937e-6], LeadersInput([1, 2], [0.0, 515.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([719.9987729011143, 520.0], [38.000057520005875, 38.000065189882704], [-99.9993481011731, 99.9993481011731], [619.9994247999413, 619.999348101173], 38.000065189882704, [2.4996633834449015e-11, 7.669901821638017e-6], LeadersInput([1, 2], [0.0, 520.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([724.998386557847, 525.0], [37.50007768384736, 37.50008366036792], [-99.99916339632067, 99.99916339632067], [624.9992231615263, 624.9991633963207], 37.50008366036792, [2.4992339511842175e-11, 5.976545553814245e-6], LeadersInput([1, 2], [0.0, 525.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([729.9973547177337, 530.0], [37.00013040023448, 37.00013412799214], [-99.99865872007865, 99.99865872007865], [629.9986959976551, 629.9986587200787], 37.00013412799214, [2.4978241941318082e-11, 3.7277826353784652e-6], LeadersInput([1, 2], [0.0, 530.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Leader 1 production: LeadersOutput([732.4999941157012, 535.0], [36.62500029222752, 36.625000296202366], [-98.74999703797637, 98.74999703797637], [633.7499970777249, 633.7499970379764], 36.625000296202366, [2.514407547252713e-11, 3.9999904758366346e-9], LeadersInput([1, 2], [0.0, 535.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([729.9999996279356, 540.0], [36.50000001811603, 36.500000019090386], [-94.9999998090961, 94.9999998090961], [634.9999998188396, 634.999999809096], 36.500000019090386, [2.5649670432959826e-11, 1.0000003097500089e-9], LeadersInput([1, 2], [0.0, 540.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([727.4999998770684, 545.0], [36.37500000587392, 36.375000006419235], [-91.24999993580762, 91.24999993580762], [636.2499999412607, 636.2499999358076], 36.375000006419235, [2.6118712223178172e-11, 5.714288778385735e-10], LeadersInput([1, 2], [0.0, 545.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Leader 1 production: LeadersOutput([724.999999939051, 550.0], [36.25000000286077, 36.25000000323411], [-87.49999996765878, 87.49999996765878], [637.4999999713923, 637.4999999676588], 36.25000000323411, [2.6660213821110837e-11, 4.000000788749074e-10], LeadersInput([1, 2], [0.0, 550.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([722.4999999635061, 555.0], [36.12500000168444, 36.12500000196494], [-83.7499999803505, 83.7499999803505], [638.7499999831556, 638.7499999803505], 36.12500000196494, [2.7189361259918186e-11, 3.0769203494817105e-10], LeadersInput([1, 2], [0.0, 555.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([719.9999999755915, 560.0], [36.00000000110931, 36.000000001331536], [-79.99999998668466, 79.99999998668466], [639.9999999889069, 639.9999999866847], 36.000000001331536, [2.77764090374818e-11, 2.5000048289944003e-10], LeadersInput([1, 2], [0.0, 560.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Leader 1 production: LeadersOutput([717.4999999824973, 565.0], [35.87500000078405, 35.87500000096621], [-76.2499999903379, 76.2499999903379], [641.2499999921595, 641.2499999903379], 35.87500000096621, [2.8366624900841312e-11, 2.1052845050069516e-10], LeadersInput([1, 2], [0.0, 565.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([714.9999999867708, 570.0], [35.750000000585054, 35.75000000073786], [-72.49999999262133, 72.49999999262133], [642.4999999941494, 642.4999999926214], 35.75000000073786, [2.900180899237111e-11, 1.8181596546290582e-10], LeadersInput([1, 2], [0.0, 570.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Leader 1 production: LeadersOutput([712.4999999896315, 575.0], [35.62500000045323, 35.62500000058361], [-68.74999999416379, 68.74999999416379], [643.7499999954678, 643.7499999941638], 35.62500000058361, [2.961214243613154e-11, 1.5999996599150812e-10], LeadersInput([1, 2], [0.0, 575.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([709.9999999916291, 580.0], [35.500000000362256, 35.50000000047483], [-64.99999999525173, 64.99999999525173], [644.9999999963774, 644.9999999952518], 35.50000000047483, [3.028341941211729e-11, 1.4285206791659851e-10], LeadersInput([1, 2], [0.0, 580.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([707.4999999930722, 585.0], [35.375000000297376, 35.3750000003954], [-61.24999999604599, 61.24999999604599], [646.2499999970262, 646.249999996046], 35.3750000003954, [3.099950456410357e-11, 1.2902724621229486e-10], LeadersInput([1, 2], [0.0, 585.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([704.9999999941607, 590.0], [35.25000000024902, 35.25000000033491], [-57.499999996651006, 57.499999996651006], [647.4999999975098, 647.499999996651], 35.25000000033491, [3.175427643597272e-11, 1.176453883672649e-10], LeadersInput([1, 2], [0.0, 590.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Leader 1 production: LeadersOutput([702.4999999949969, 595.0], [35.12500000021236, 35.125000000287955], [-53.74999999712037, 53.74999999712037], [648.7499999978764, 648.7499999971204], 35.125000000287955, [3.250814318350791e-11, 1.0810720183408905e-10], LeadersInput([1, 2], [0.0, 595.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([699.9999999956509, 600.0], [35.00000000018413, 35.00000000025078], [-49.9999999974921, 49.9999999974921], [649.9999999981587, 649.9999999974921], 35.00000000025078, [3.3338085836623316e-11, 9.99916303988547e-11], LeadersInput([1, 2], [0.0, 600.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([697.4999999961719, 605.0], [34.87500000016199, 34.875000000220815], [-46.24999999779186, 46.24999999779186], [651.2499999983801, 651.2499999977919], 34.875000000220815, [3.4204884893747175e-11, 9.3026931134836e-11], LeadersInput([1, 2], [0.0, 605.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Leader 1 production: LeadersOutput([694.999999997228, 610.0], [34.75000000011528, 34.75000000016192], [-42.499999998380744, 42.499999998380744], [652.4999999988472, 652.4999999983808], 34.75000000016192, [3.403909875580044e-11, 8.068241296679841e-11], LeadersInput([1, 2], [0.0, 610.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([692.4999999969389, 615.0], [34.62500000013026, 34.625000000175845], [-38.7499999982415, 38.7499999982415], [653.7499999986974, 653.7499999982415], 34.625000000175845, [3.603714575786534e-11, 8.162726626774846e-11], LeadersInput([1, 2], [0.0, 615.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Leader 1 production: LeadersOutput([689.9999999972242, 620.0], [34.50000000011885, 34.50000000015873], [-34.99999999841276, 34.99999999841276], [654.9999999988115, 654.9999999984127], 34.50000000015873, [3.704362886608237e-11, 7.691735372763442e-11], LeadersInput([1, 2], [0.0, 620.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([687.4999999974608, 625.0], [34.37500000010964, 34.37500000014428], [-31.249999998557243, 31.249999998557243], [656.2499999989036, 656.2499999985572], 34.37500000014428, [3.8080870451279515e-11, 7.272586071147944e-11], LeadersInput([1, 2], [0.0, 625.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([684.9999999976583, 630.0], [34.25000000010221, 34.250000000131955], [-27.499999998680465, 27.499999998680465], [657.4999999989778, 657.4999999986804], 34.250000000131955, [3.92255543665537e-11, 6.896903514549803e-11], LeadersInput([1, 2], [0.0, 630.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Leader 1 production: LeadersOutput([682.4999999978244, 635.0], [34.12500000009619, 34.12500000012136], [-23.749999998786294, 23.749999998786294], [658.749999999038, 658.7499999987863], 34.12500000012136, [4.039972866852117e-11, 6.556397013828428e-11], LeadersInput([1, 2], [0.0, 635.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([679.9999999979627, 640.0], [34.00000000009145, 34.00000000011228], [-19.999999998877136, 19.999999998877136], [659.9999999990855, 659.9999999988771], 34.00000000011228, [4.16664791444289e-11, 6.249580413429711e-11], LeadersInput([1, 2], [0.0, 640.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Leader 1 production: LeadersOutput([677.4999999980781, 645.0], [33.87500000008775, 33.87500000010443], [-16.249999998955648, 16.249999998955648], [661.2499999991225, 661.2499999989557], 33.87500000010443, [4.301583494201334e-11, 5.969389734515468e-11], LeadersInput([1, 2], [0.0, 645.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([674.9999999981732, 650.0], [33.75000000008499, 33.750000000097685], [-12.499999999022988, 12.499999999022988], [662.4999999991501, 662.499999999023], 33.750000000097685, [4.444771088064669e-11, 5.714450971396315e-11], LeadersInput([1, 2], [0.0, 650.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([450.00000045499985, 655.0], [44.9999999555, 44.499999999], [99.99999998999999, -99.99999998999999], [550.0000004449998, 555.00000001], 44.499999999, [0.4999999565250262, 2.502404136108712e-11], LeadersInput([1, 2], [0.0, 655.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([450.0000001128132, 660.0], [44.999999989218665, 43.9999999995], [99.999999995, -99.999999995], [550.0000001078132, 560.000000005], 43.9999999995, [0.9999999897436441, 2.4976442002407146e-11], LeadersInput([1, 2], [0.0, 660.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([450.00000005022514, 665.0], [44.99999999531081, 43.49999999966668], [99.99999999666667, -99.99999999666667], [550.0000000468918, 565.0000000033333], 43.49999999966668, [1.4999999956691168, 2.4986051423903983e-11], LeadersInput([1, 2], [0.0, 665.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([450.0000000282741, 670.0], [44.9999999974226, 42.99999999975], [99.9999999975, -99.9999999975], [550.000000025774, 570.0000000025], 42.99999999975, [1.9999999976975789, 2.498447381339283e-11], LeadersInput([1, 2], [0.0, 670.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([450.00000001810866, 675.0], [44.99999999838913, 42.4999999998], [99.999999998, -99.999999998], [550.0000000161086, 575.000000002], 42.4999999998, [2.499999998614115, 2.4985986778243314e-11], LeadersInput([1, 2], [0.0, 675.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Leader 1 production: LeadersOutput([450.0000000125853, 680.0], [44.99999999890813, 41.999999999833335], [99.99999999833334, -99.99999999833334], [550.0000000109186, 580.0000000016666], 41.999999999833335, [2.9999999990997637, 2.497051684727435e-11], LeadersInput([1, 2], [0.0, 680.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([450.00000000925445, 685.0], [44.999999999217415, 41.49999999985714], [99.99999999857143, -99.99999999857143], [550.0000000078259, 585.0000000014286], 41.49999999985714, [3.4999999993852815, 2.5006585600857498e-11], LeadersInput([1, 2], [0.0, 685.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([450.0000000070923, 690.0], [44.99999999941576, 40.999999999875], [99.99999999875, -99.99999999875], [550.0000000058423, 590.00000000125], 40.999999999875, [3.9999999995657336, 2.4969844833568585e-11], LeadersInput([1, 2], [0.0, 690.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([450.0000000056098, 695.0], [44.99999999955013, 40.499999999888885], [99.99999999888888, -99.99999999888888], [550.0000000044988, 595.0000000011112], 40.499999999888885, [4.49999999968626, 2.50182311276711e-11], LeadersInput([1, 2], [0.0, 695.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([450.0000000045493, 700.0], [44.99999999964507, 39.999999999900005], [99.999999999, -99.999999999], [550.0000000035493, 600.000000001], 39.999999999900005, [4.999999999770039, 2.4975162072730572e-11], LeadersInput([1, 2], [0.0, 700.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([450.00000000376457, 705.0], [44.99999999971444, 39.49999999990909], [99.9999999990909, -99.9999999990909], [550.0000000028556, 605.000000000909], 39.49999999990909, [5.499999999830341, 2.4995589521944847e-11], LeadersInput([1, 2], [0.0, 705.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([450.0000000031678, 710.0], [44.99999999976656, 38.99999999991667], [99.99999999916666, -99.99999999916666], [550.0000000023344, 610.0000000008333], 38.99999999991667, [5.999999999874885, 2.499779759538383e-11], LeadersInput([1, 2], [0.0, 710.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([450.0000000027033, 715.0], [44.99999999980659, 38.49999999992308], [99.99999999923077, -99.99999999923077], [550.000000001934, 615.0000000007692], 38.49999999992308, [6.499999999908506, 2.4990006811645746e-11], LeadersInput([1, 2], [0.0, 715.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([450.00000000233473, 720.0], [44.999999999837954, 37.99999999992857], [99.99999999928572, -99.99999999928572], [550.0000000016205, 620.0000000007143], 37.99999999992857, [6.999999999934381, 2.4993031774776382e-11], LeadersInput([1, 2], [0.0, 720.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([450.0000000020374, 725.0], [44.99999999986293, 37.49999999993333], [99.99999999933333, -99.99999999933333], [550.0000000013707, 625.0000000006667], 37.49999999993333, [7.499999999954588, 2.4989753366240102e-11], LeadersInput([1, 2], [0.0, 725.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([450.0000000017939, 730.0], [44.999999999883094, 36.999999999937494], [99.999999999375, -99.999999999375], [550.000000001169, 630.000000000625], 36.999999999937494, [7.999999999970613, 2.501600616690025e-11], LeadersInput([1, 2], [0.0, 730.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n"
     ]
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Leader 1 production: LeadersOutput([450.0000000015923, 735.0], [44.99999999989959, 36.499999999941174], [99.99999999941177, -99.99999999941177], [550.0000000010041, 635.0000000005882], 36.499999999941174, [8.499999999983435, 2.5014651377641947e-11], LeadersInput([1, 2], [0.0, 735.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([450.0000000014233, 740.0], [44.99999999991323, 35.999999999944436], [99.99999999944444, -99.99999999944444], [550.0000000008678, 640.0000000005556], 35.999999999944436, [8.999999999993765, 2.4973586054987717e-11], LeadersInput([1, 2], [0.0, 740.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([450.0000000012802, 745.0], [44.999999999924604, 35.499999999947356], [99.99999999947369, -99.99999999947369], [550.0000000007539, 645.0000000005264], 35.499999999947356, [9.500000000002242, 2.4998008131784303e-11], LeadersInput([1, 2], [0.0, 745.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([450.0000000011581, 750.0], [44.99999999993419, 34.99999999994999], [99.9999999995, -99.9999999995], [550.000000000658, 650.0000000005], 34.99999999994999, [10.000000000009209, 2.501295514644419e-11], LeadersInput([1, 2], [0.0, 750.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([450.0000000010531, 755.0], [44.999999999942325, 34.499999999952365], [99.99999999952381, -99.99999999952381], [550.0000000005768, 655.0000000004762], 34.499999999952365, [10.500000000014925, 2.4970865079144428e-11], LeadersInput([1, 2], [0.0, 755.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([450.00000000096185, 760.0], [44.99999999994926, 33.99999999995454], [99.99999999954545, -99.99999999954545], [550.0000000005073, 660.0000000004545], 33.99999999995454, [11.000000000019698, 2.4977969711431738e-11], LeadersInput([1, 2], [0.0, 760.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([450.00000000088244, 765.0], [44.999999999955236, 33.49999999995652], [99.99999999956522, -99.99999999956522], [550.0000000004476, 665.0000000004347], 33.49999999995652, [11.5000000000237, 2.498678610156509e-11], LeadersInput([1, 2], [0.0, 765.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([450.00000000081263, 770.0], [44.9999999999604, 32.99999999995833], [99.99999999958334, -99.99999999958334], [550.000000000396, 670.0000000004167], 32.99999999995833, [12.00000000002708, 2.5003816504381337e-11], LeadersInput([1, 2], [0.0, 770.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([450.000000000751, 775.0], [44.999999999964885, 32.499999999959996], [99.99999999959999, -99.99999999959999], [550.0000000003511, 675.0000000004], 32.499999999959996, [12.500000000029862, 2.4976699479968334e-11], LeadersInput([1, 2], [0.0, 775.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([450.00000000069656, 780.0], [44.99999999996881, 31.99999999996154], [99.99999999961538, -99.99999999961538], [550.000000000312, 680.0000000003846], 31.99999999996154, [13.000000000032248, 2.4978533726688043e-11], LeadersInput([1, 2], [0.0, 780.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n"
     ]
    },
    {
     "data": {
      "image/png": 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     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "nothing"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\n",
      "Leader 1 production: LeadersOutput([450.00000000064784, 785.0], [44.999999999972246, 31.499999999962945], [99.99999999962962, -99.99999999962962], [550.0000000002775, 685.0000000003704], 31.499999999962945, [13.500000000034277, 2.49761771284884e-11], LeadersInput([1, 2], [0.0, 785.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([450.00000000060436, 790.0], [44.99999999997528, 30.999999999964277], [99.99999999964285, -99.99999999964285], [550.0000000002473, 690.0000000003572], 30.999999999964277, [14.00000000003601, 2.5009980154261343e-11], LeadersInput([1, 2], [0.0, 790.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([450.00000000056525, 795.0], [44.99999999997795, 30.499999999965507], [99.99999999965517, -99.99999999965517], [550.0000000002204, 695.0000000003448], 30.499999999965507, [14.500000000037447, 2.4998665655452504e-11], LeadersInput([1, 2], [0.0, 795.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n",
      "Leader 1 production: LeadersOutput([450.00000000053, 800.0], [44.999999999980325, 29.999999999966665], [99.99999999966667, -99.99999999966667], [550.0000000001968, 700.0000000003333], 29.999999999966665, [15.000000000038657, 2.499281175144187e-11], LeadersInput([1, 2], [0.0, 800.0], [1000.0, 1000.0], [0.1, 0.1], 100.0), #undef) \n",
      "\n"
     ]
    }
   ],
   "source": [
    "include(\"src/ex4.jl\")\n",
    "\n",
    "\n",
    "N = [1,2]\n",
    "a = [0.1,0.1]\n",
    "D0=[1000.0, 1000]\n",
    "cap = 100\n",
    "\n",
    "input = EX4Input(N, a, D0, cap)\n",
    "\n",
    "res = run_model(input)\n",
    "display(plot_production(res))\n",
    "\n",
    "display(plot_best_response(input))\n",
    "# plot_prices(res)\n"
   ]
  }
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