{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Discovery of prime integrals with dCGP"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Lets first import dcgpy and pyaudi and set up things as to use dCGP on gduals defined over vectorized floats"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from dcgpy import expression_gdual_vdouble as expression\n",
    "from dcgpy import kernel_set_gdual_vdouble as kernel_set\n",
    "from pyaudi import gdual_vdouble as gdual\n",
    "from matplotlib import pyplot as plt\n",
    "import numpy as np\n",
    "from numpy import sin, cos\n",
    "from random import randint, random\n",
    "np.seterr(all='ignore') # avoids numpy complaining about early on malformed expressions being evalkuated\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We consider a set of differential equations in the form:\n",
    "\n",
    "$$\n",
    "\\left\\{\n",
    "\\begin{array}{c}\n",
    "\\frac{dx_1}{dt} = f_1(x_1, \\cdots, x_n) \\\\\n",
    "\\vdots \\\\\n",
    "\\frac{dx_n}{dt} = f_n(x_1, \\cdots, x_n)\n",
    "\\end{array}\n",
    "\\right.\n",
    "$$\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "and we search for expressions $P(x_1, \\cdots, x_n) = 0$ which we call prime integrals of motion.\n",
    "\n",
    "The straight forward approach to design such a search would be to represent $P$ via a $dCGP$ program and evolve its chromosome so that the expression, computed along points of some trajectory, evaluates to zero. This naive approach brings to the evolution of trivial programs that are identically zero and that \"do not represent the intrinsic reltations between state varaibles\" - Schmidt 2009. \n",
    "\n",
    "Let us, though, differentiate $P$ along a trajectory solution to the ODEs above. We get:\n",
    "$$\n",
    "\\frac{dP}{dt} = \\sum_{i=0}^n \\frac{\\partial P}{\\partial x_i} \\frac{dx_i}{dt} = \\sum_{i=0}^n \\frac{\\partial P}{\\partial x_i} f_i = 0\n",
    "$$\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "we may try to evolve the expression $P$ so that the above relation is satisfied on chosen points (belonging to a real trajectory or just defined on a grid). To avoid evolution to go towards trivial solutions, unlike Schmidt, we suppress all mutations that give raise to expressions for which $\\sum_{i=0}^n \\left(\\frac{\\partial P}{\\partial x_i}\\right)^2 = 0$. That is, expressions that do not depend on the state."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### A mass spring system\n",
    "\n",
    "As a simple example, consider the following mass-spring system. \n",
    "\n",
    "The ODEs are:\n",
    "$$\\left\\{\n",
    "\\begin{array}{l}\n",
    "\\dot v = -kx \\\\\n",
    "\\dot x = v\n",
    "\\end{array}\\right.\n",
    "$$\n",
    "\n",
    "We define a dCGP having three inputs (the state and the constant $k$) and one output ($P$)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "kernels = kernel_set([\"sum\", \"mul\", \"pdiv\", \"diff\"])() # note the call operator (returns the list of kernels)\n",
    "dCGP = expression(inputs=3, outputs=1, rows=1, cols=15, levels_back=16, arity=2, kernels=kernels, seed = randint(0,234213213))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We define 50 random control of points where we check that the prime integral holds: $x \\in [2,4]$, $v \\in [2,4]$ and $k \\in[2, 4]$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "n_points = 50\n",
    "x = []\n",
    "v = []\n",
    "k = []\n",
    "for i in range(n_points):\n",
    "    x.append(random()*2 + 2)\n",
    "    v.append(random()*2 + 2)\n",
    "    k.append(random()*2 + 2)\n",
    "x = gdual(x,\"x\",1)\n",
    "v = gdual(v,\"v\",1)\n",
    "k = gdual(k)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "def fitness_call(dCGP, x, v, k):\n",
    "    res = dCGP([x,v,k])[0]\n",
    "    dPdx = np.array(res.get_derivative({\"dx\": 1}))\n",
    "    dPdv = np.array(res.get_derivative({\"dv\": 1}))\n",
    "    xcoeff = np.array(x.constant_cf)\n",
    "    vcoeff = np.array(v.constant_cf)\n",
    "    kcoeff = np.array(k.constant_cf)\n",
    "    err = dPdx/dPdv - kcoeff * xcoeff / vcoeff\n",
    "    return sum(err * err), 3\n",
    "    \n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [],
   "source": [
    "# We run an evolutionary strategy ES(1 + offspring)\n",
    "def run_experiment(max_gen, offsprings, dCGP, x, v, k, screen_output=False):\n",
    "    chromosome = [1] * offsprings\n",
    "    fitness = [1] *offsprings\n",
    "    best_chromosome = dCGP.get()\n",
    "    best_fitness = 1e10\n",
    "        \n",
    "    for g in range(max_gen):\n",
    "        for i in range(offsprings):\n",
    "            check = 0\n",
    "            while(check < 1e-3):\n",
    "                dCGP.set(best_chromosome)\n",
    "                dCGP.mutate_active(i+1) #  we mutate a number of increasingly higher active genes\n",
    "                fitness[i], check = fitness_call(dCGP, x,v,k)\n",
    "            chromosome[i] = dCGP.get()\n",
    "        for i in range(offsprings):\n",
    "            if fitness[i] <= best_fitness:\n",
    "                if (fitness[i] != best_fitness) and screen_output:\n",
    "                    dCGP.set(chromosome[i])\n",
    "                    print(\"New best found: gen: \", g, \" value: \", fitness[i], \" \", dCGP.simplify([\"x\",\"v\",\"k\"]))\n",
    "                best_chromosome = chromosome[i]\n",
    "                best_fitness = fitness[i]\n",
    "        if best_fitness < 1e-12:\n",
    "            break\n",
    "    dCGP.set(best_chromosome)\n",
    "    return g, dCGP\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "restart: \t gen: \t expression:\n",
      "0 \t\t 1221 \t ['(((k-k)+x)*(((v/k)/(x/((v/k)*k)))+((k-k)+x)))']  a.k.a  [x**2 + v**2/k]\n",
      "3 \t\t 557 \t ['((v*v)+((x*k)*x))']  a.k.a  [k*x**2 + v**2]\n",
      "5 \t\t 382 \t ['(((x*k)+((((v-x)/x)*v)+v))/(((v-x)/x)/(v-x)))']  a.k.a  [k*x**2 + v**2]\n",
      "8 \t\t 1249 \t ['((((k/v)+v)/(k/v))+(x*x))']  a.k.a  [x**2 + 1 + v**2/k]\n",
      "10 \t\t 9 \t ['((v*v)+(k*(x*x)))']  a.k.a  [k*x**2 + v**2]\n",
      "14 \t\t 198 \t ['(((k-(k*x))*x)-((v*v)+(k*x)))']  a.k.a  [-k*x**2 - v**2]\n",
      "15 \t\t 1281 \t ['(((k*x)/k)*((v/(x/v))+(k*x)))']  a.k.a  [k*x**2 + v**2]\n",
      "21 \t\t 1595 \t ['(((k*x)*(((k/(k*x))*k)+x))+(v*v))']  a.k.a  [k**2 + k*x**2 + v**2]\n",
      "23 \t\t 321 \t ['(((x*x)+v)-(((x*x)+((x*x)+v))+((v*v)/k)))']  a.k.a  [-x**2 - v**2/k]\n",
      "24 \t\t 1804 \t ['((k/(x*k))/((v/(x/v))+(x*k)))']  a.k.a  [1/(k*x**2 + v**2)]\n",
      "31 \t\t 1292 \t ['((v*v)+(k+(x*(k*x))))']  a.k.a  [k*x**2 + k + v**2]\n",
      "34 \t\t 417 \t ['((k-v)/(((v/(k/v))+(x*x))*(k-v)))']  a.k.a  [1/(x**2 + v**2/k)]\n",
      "42 \t\t 880 \t ['(((((x*k)-((v*v)/x))-(x*k))-(((x*k)*((v*v)/(v*v)))*((v*v)/(v*v))))*((x*k)*((v*v)/(v*v))))']  a.k.a  [-k**2*x**2 - k*v**2]\n",
      "45 \t\t 849 \t ['((k*(x+k))*(((k-(((v/k)/(x+k))*v))-x)-((k*((v/k)/(x+k)))/(v+v))))']  a.k.a  [k**3 - k**2*v**2/(k**2 + k*x) - k**2/(2*(k + x)) - k*v**2*x/(k**2 + k*x) - k*x**2 - k*x/(2*(k + x))]\n",
      "46 \t\t 252 \t ['((((x*x)+((v/k)*v))+(v/(v/k)))*((x*x)+((v/k)*v)))']  a.k.a  [k*x**2 + v**2 + x**4 + 2*v**2*x**2/k + v**4/k**2]\n",
      "49 \t\t 1010 \t ['((v*v)+((v-v)-(x*(((v-v)-x)*k))))']  a.k.a  [k*x**2 + v**2]\n",
      "51 \t\t 912 \t ['(((((v/x)/k)+(x+x))-((v/x)/k))*(x+(((v/x)/k)*v)))']  a.k.a  [2*x**2 + 2*v**2/k]\n",
      "53 \t\t 1144 \t ['((v*(k-k))+(((v*v)/k)+(x*x)))']  a.k.a  [x**2 + v**2/k]\n",
      "57 \t\t 700 \t ['(((v/k)*v)+(x*x))']  a.k.a  [x**2 + v**2/k]\n",
      "58 \t\t 1444 \t ['(((x*(k*x))+(v*v))+((x*(k*x))+(v*v)))']  a.k.a  [2*k*x**2 + 2*v**2]\n",
      "59 \t\t 842 \t ['(((v*v)+(k*(x*x)))+((v*v)+(k*(x*x))))']  a.k.a  [2*k*x**2 + 2*v**2]\n",
      "63 \t\t 853 \t ['((k+(k+k))+((v/(k/v))+(x*x)))']  a.k.a  [3*k + x**2 + v**2/k]\n",
      "65 \t\t 834 \t ['(((x*(k*x))+(v*v))*k)']  a.k.a  [k**2*x**2 + k*v**2]\n",
      "69 \t\t 276 \t ['((x*(k*x))+(v*v))']  a.k.a  [k*x**2 + v**2]\n",
      "76 \t\t 1568 \t ['((((x/x)/k)-(k+((x*k)*x)))-(v*v))']  a.k.a  [-k*x**2 - k - v**2 + 1/k]\n",
      "79 \t\t 406 \t ['((x*(k*x))+(v*v))']  a.k.a  [k*x**2 + v**2]\n",
      "83 \t\t 1888 \t ['((x*x)+((v*v)/k))']  a.k.a  [x**2 + v**2/k]\n",
      "87 \t\t 955 \t ['((v/(k/v))+(v+((x*x)-v)))']  a.k.a  [x**2 + v**2/k]\n",
      "90 \t\t 1928 \t ['((v*v)+((k*x)*x))']  a.k.a  [k*x**2 + v**2]\n",
      "93 \t\t 1144 \t ['((((v*v)-(x*k))+((x*(k*x))+(k*x)))/k)']  a.k.a  [x**2 + v**2/k]\n",
      "94 \t\t 690 \t ['((x*x)+((v*x)/((k*(x*x))/(v*x))))']  a.k.a  [x**2 + v**2/k]\n",
      "96 \t\t 1161 \t ['(((((x*k)-v)-(x*k))*(k*v))+(k-((x*k)*(x*k))))']  a.k.a  [-k**2*x**2 - k*v**2 + k]\n",
      "99 \t\t 636 \t ['(((v/(x/v))+(k*x))*(k*x))']  a.k.a  [k**2*x**2 + k*v**2]\n"
     ]
    }
   ],
   "source": [
    "# We run nexp experiments to accumulate statistic for the ERT\n",
    "nexp = 100\n",
    "offsprings = 10\n",
    "stop = 2000\n",
    "res = []\n",
    "print(\"restart: \\t gen: \\t expression:\")\n",
    "for i in range(nexp):\n",
    "    dCGP = expression(inputs=3, outputs=1, rows=1, cols=15, levels_back=16, arity=2, kernels=kernels, seed = randint(0,234213213))\n",
    "    g, dCGP = run_experiment(stop, 10, dCGP, x,v,k, False)\n",
    "    res.append(g)\n",
    "    if g < (stop-1):\n",
    "        print(i, \"\\t\\t\", res[i], \"\\t\", dCGP([\"x\",\"v\",\"k\"]), \" a.k.a \", dCGP.simplify([\"x\",\"v\",\"k\"]))\n",
    "        one_sol = dCGP\n",
    "res = np.array(res)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ERT Expected run time - avg. number of function evaluations needed:  49888.1818182\n"
     ]
    }
   ],
   "source": [
    "ERT = sum(res) / sum(res<(stop-1))\n",
    "print(\"ERT Expected run time - avg. number of function evaluations needed: \", ERT * offsprings)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[k**2*x**2 + k*v**2]\n"
     ]
    },
    {
     "data": {
      "image/png": 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37kROTg6TRmnk9/tx4MAByLJsdChERLTMZNWv9Z133onS0lI89NBDeOaZZxa1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8EVHnwKlq3dl3332HJUuW4NVXX8XUqVO5phFdkSRJyMjIwMqVK6HX67Fo0SKkpKQoHRYREREF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\nRERERCTr/wGNeBnxcj7NyAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5acdb3b710>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f5acc2fc390>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(one_sol.simplify([\"x\",\"v\",\"k\"]))\n",
    "plt.rcParams[\"figure.figsize\"] = [20,20]\n",
    "one_sol.visualize([\"x\",\"v\",\"k\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Simple pendulum\n",
    "\n",
    "Consider the simple pendulum problem. In particular its differential formulation:\n",
    "\n",
    "The ODEs are:\n",
    "$$\\left\\{\n",
    "\\begin{array}{l}\n",
    "\\dot \\omega = - \\frac gL\\sin\\theta \\\\\n",
    "\\dot \\theta = \\omega \\\\\n",
    "\\end{array}\\right.\n",
    "$$\n",
    "\n",
    "We define a dCGP having three inputs (the state and the constant $\\frac gL$) and one output ($P$)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "kernels = kernel_set([\"sum\", \"mul\", \"pdiv\", \"diff\",\"sin\",\"cos\"])() # note the call operator (returns the list of kernels)\n",
    "dCGP = expression(inputs=3, outputs=1, rows=1, cols=15, levels_back=16, arity=2, kernels=kernels, seed = randint(0,234213213))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We define 50 random control of points where we check that the prime integral holds: $\\omega \\in [-1, 1]$, $\\theta \\in [-1, 1]$, and $\\frac gL \\in [1,2]$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "n_points = 50\n",
    "omega = []\n",
    "theta = []\n",
    "c = []\n",
    "for i in range(n_points):\n",
    "    omega.append(random()*10 - 5)\n",
    "    theta.append(random()*10 - 5)\n",
    "    c.append(random()*10)\n",
    "    \n",
    "omega = gdual(omega,\"omega\",1)\n",
    "theta = gdual(theta,\"theta\",1)\n",
    "c = gdual(c)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "def fitness_call(dCGP, theta, omega, c):\n",
    "    res = dCGP([theta, omega, c])[0]\n",
    "    dPdtheta = np.array(res.get_derivative({\"dtheta\": 1}))\n",
    "    dPdomega = np.array(res.get_derivative({\"domega\": 1}))\n",
    "    thetacoeff = np.array(theta.constant_cf)\n",
    "    omegacoeff = np.array(omega.constant_cf)\n",
    "    ccoeff = np.array(c.constant_cf)\n",
    "    err = dPdtheta/dPdomega + (-ccoeff * np.sin(thetacoeff)) / omegacoeff\n",
    "    check = sum(dPdtheta*dPdtheta + dPdomega*dPdomega)\n",
    "    return sum(err * err ), check"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# We run an evolutionary strategy ES(1 + offspring)\n",
    "def run_experiment(max_gen, offsprings, dCGP,  theta, omega, c, screen_output=False):\n",
    "    chromosome = [1] * offsprings\n",
    "    fitness = [1] *offsprings\n",
    "    best_chromosome = dCGP.get()\n",
    "    best_fitness = 1e10\n",
    "        \n",
    "    for g in range(max_gen):\n",
    "        for i in range(offsprings):\n",
    "            check = 0\n",
    "            while(check < 1e-3):\n",
    "                dCGP.set(best_chromosome)\n",
    "                dCGP.mutate_active(i+1) #  we mutate a number of increasingly higher active genes\n",
    "                fitness[i], check = fitness_call(dCGP, theta, omega, c)\n",
    "            chromosome[i] = dCGP.get()\n",
    "        for i in range(offsprings):\n",
    "            if fitness[i] <= best_fitness:\n",
    "                if (fitness[i] != best_fitness) and screen_output:\n",
    "                    dCGP.set(chromosome[i])\n",
    "                    print(\"New best found: gen: \", g, \" value: \", fitness[i], \" \", dCGP.simplify([\"theta\",\"omega\",\"c\"]))\n",
    "                best_chromosome = chromosome[i]\n",
    "                best_fitness = fitness[i]\n",
    "        if best_fitness < 1e-12:\n",
    "            break\n",
    "    dCGP.set(best_chromosome)\n",
    "    return g, dCGP\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "restart: \t gen: \t expression:\n",
      "5 \t\t 1087 \t ['(((c*cos(theta))+(c*cos(theta)))-(omega*omega))']  a.k.a  [2*c*cos(theta) - omega**2]\n",
      "9 \t\t 1007 \t ['(((((omega*omega)/c)-cos(theta))-cos(theta))/c)']  a.k.a  [-2*cos(theta)/c + omega**2/c**2]\n",
      "11 \t\t 727 \t ['(((cos(theta)-((omega*omega)/c))+cos(theta))-((omega*omega)/((omega*omega)/c)))']  a.k.a  [-c + 2*cos(theta) - omega**2/c]\n",
      "17 \t\t 509 \t ['(cos(((theta-theta)+(theta+(theta-theta))))-(((omega*omega)-(theta-theta))/(c+c)))']  a.k.a  [cos(theta) - omega**2/(2*c)]\n",
      "19 \t\t 1780 \t ['(sin(((omega*omega)/((omega*omega)/c)))*((cos(theta)-((omega*omega)/c))+cos(theta)))']  a.k.a  [2*sin(c)*cos(theta) - omega**2*sin(c)/c]\n",
      "31 \t\t 246 \t ['(cos(theta)-(((omega*omega)/c)-cos(theta)))']  a.k.a  [2*cos(theta) - omega**2/c]\n",
      "34 \t\t 154 \t ['(((c*cos(theta))+(cos(theta)*c))-(omega*omega))']  a.k.a  [2*c*cos(theta) - omega**2]\n",
      "38 \t\t 506 \t ['((cos(theta)*c)-(((omega*omega)+c)-(cos(theta)*c)))']  a.k.a  [2*c*cos(theta) - c - omega**2]\n",
      "54 \t\t 1063 \t ['((((c+c)*cos(theta))-(omega*omega))-sin((theta/theta)))']  a.k.a  [2*c*cos(theta) - omega**2 - sin(1)]\n",
      "62 \t\t 966 \t ['((cos(theta)-((omega*omega)/c))+((omega*omega)/(c+c)))']  a.k.a  [cos(theta) - omega**2/(2*c)]\n",
      "64 \t\t 1159 \t ['sin(cos((((omega*(omega/c))-cos(theta))-(cos(theta)+c))))']  a.k.a  [sin(cos(c + 2*cos(theta) - omega**2/c))]\n",
      "71 \t\t 687 \t ['(c+((cos(theta)*c)+((((cos(theta)*c)*theta)/theta)-(omega*omega))))']  a.k.a  [2*c*cos(theta) + c - omega**2]\n",
      "72 \t\t 1970 \t ['((omega*omega)-((c+c)*cos(theta)))']  a.k.a  [-2*c*cos(theta) + omega**2]\n",
      "86 \t\t 1215 \t ['(((c-(cos(theta)*c))+(omega*omega))+(c-(cos(theta)*c)))']  a.k.a  [-2*c*cos(theta) + 2*c + omega**2]\n",
      "93 \t\t 1545 \t ['((omega*omega)-((c+c)*cos(theta)))']  a.k.a  [-2*c*cos(theta) + omega**2]\n",
      "98 \t\t 264 \t ['((omega/(c+c))*(omega-(cos(theta)/(omega/(c+c)))))']  a.k.a  [-cos(theta) + omega**2/(2*c)]\n"
     ]
    }
   ],
   "source": [
    "# We run nexp experiments to accumulate statistic for the ERT\n",
    "nexp = 100\n",
    "offsprings = 10\n",
    "stop = 2000\n",
    "res = []\n",
    "print(\"restart: \\t gen: \\t expression:\")\n",
    "for i in range(nexp):\n",
    "    dCGP = expression(inputs=3, outputs=1, rows=1, cols=15, levels_back=16, arity=2, kernels=kernels, seed = randint(0,234213213))\n",
    "    g, dCGP = run_experiment(stop, 10, dCGP, theta, omega, c, False)\n",
    "    res.append(g)\n",
    "    if g < (stop-1):\n",
    "        print(i, \"\\t\\t\", res[i], \"\\t\", dCGP([\"theta\",\"omega\",\"c\"]), \" a.k.a \", dCGP.simplify([\"theta\",\"omega\",\"c\"]))\n",
    "        one_sol = dCGP\n",
    "res = np.array(res)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ERT Expected run time - avg. number of function evaluations needed:  114250.625\n"
     ]
    }
   ],
   "source": [
    "ERT = sum(res) / sum(res<(stop-1))\n",
    "print(\"ERT Expected run time - avg. number of function evaluations needed: \", ERT * offsprings)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[-cos(theta) + omega**2/(2*c)]\n"
     ]
    },
    {
     "data": {
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bNBoNkpOTkZubq3QoRETkB3p7e/22J89YjaaNRqPfxkxERET+jZVAQUyWZbjdbq9l5kRE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\n782TAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5ace9e4128>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f5acc2352e8>"
      ]
     },
     "execution_count": 15,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(one_sol.simplify([\"theta\",\"omega\",\"c\"]))\n",
    "plt.rcParams[\"figure.figsize\"] = [20,20]\n",
    "one_sol.visualize([\"theta\",\"omega\",\"c\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### The two-body problem\n",
    "\n",
    "Consider the two body problem. In particular its differential formulation in polar coordinates:\n",
    "\n",
    "The ODEs are:\n",
    "$$\\left\\{\n",
    "\\begin{array}{l}\n",
    "\\dot v = -\\frac\\mu{r^2} + r\\omega^2 \\\\\n",
    "\\dot \\omega = - 2 \\frac{v\\omega}{r} \\\\\n",
    "\\dot r = v \\\\\n",
    "\\dot \\theta = \\omega\n",
    "\\end{array}\\right.\n",
    "$$\n",
    "\n",
    "We define a dCGP having five inputs (the state and the constant $\\mu$) and one output ($P$)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "kernels = kernel_set([\"sum\", \"mul\", \"pdiv\", \"diff\"])() # note the call operator (returns the list of kernels)\n",
    "dCGP = expression(inputs=3, outputs=1, rows=1, cols=15, levels_back=16, arity=2, kernels=kernels, seed = randint(0,234213213))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "We define 50 random control of points where we check that the prime integral holds: $r \\in [0.1,1.1]$, $v \\in [2,4]$, $\\omega \\in [1,2]$ and $\\theta \\in[2, 4]$ and $\\mu \\in [1,2]$"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "n_points = 50\n",
    "v = []\n",
    "omega = []\n",
    "r = []\n",
    "theta = []\n",
    "mu = []\n",
    "for i in range(n_points):\n",
    "    v.append(random()*2 + 2)\n",
    "    omega.append(random()*1 + 1)\n",
    "    r.append(random() + 0.1)\n",
    "    theta.append(random()*2 + 2)\n",
    "    mu.append(random() + 1)\n",
    "    \n",
    "r = gdual(r,\"r\",1)\n",
    "omega = gdual(omega,\"omega\",1)\n",
    "v = gdual(v,\"v\",1)\n",
    "theta = gdual(theta,\"theta\",1)\n",
    "mu = gdual(mu)\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "## Use this fitness if energy conservation is to be found (it basically forces the expression to depend on v)\n",
    "def fitness_call(dCGP, r, v, theta, omega, mu):\n",
    "    res = dCGP([r, v, theta, omega, mu])[0]\n",
    "    dPdr = np.array(res.get_derivative({\"dr\": 1}))\n",
    "    dPdv = np.array(res.get_derivative({\"dv\": 1}))\n",
    "    dPdtheta = np.array(res.get_derivative({\"dtheta\": 1}))\n",
    "    dPdomega = np.array(res.get_derivative({\"domega\": 1}))\n",
    "    rcoeff = np.array(r.constant_cf)\n",
    "    vcoeff = np.array(v.constant_cf)\n",
    "    thetacoeff = np.array(theta.constant_cf)\n",
    "    omegacoeff = np.array(omega.constant_cf)\n",
    "    mucoeff = np.array(mu.constant_cf)\n",
    "    err = dPdr / dPdv +  (-mucoeff/rcoeff**2 + rcoeff*omegacoeff**2) / vcoeff + dPdtheta / dPdv  / vcoeff * omegacoeff + dPdomega / dPdv  / vcoeff * (-2*vcoeff*omegacoeff/rcoeff)\n",
    "    check = sum(dPdr*dPdr + dPdv*dPdv + dPdomega*dPdomega + dPdtheta*dPdtheta)\n",
    "    return sum(err * err), check\n",
    "\n",
    "## Use this fitness if any conservation is to be found (will always converge to angular momentum)\n",
    "def fitness_call_free(dCGP, r, v, theta, omega, mu):\n",
    "    res = dCGP([r, v, theta, omega, mu])[0]\n",
    "    dPdr = np.array(res.get_derivative({\"dr\": 1}))\n",
    "    dPdv = np.array(res.get_derivative({\"dv\": 1}))\n",
    "    dPdtheta = np.array(res.get_derivative({\"dtheta\": 1}))\n",
    "    dPdomega = np.array(res.get_derivative({\"domega\": 1}))\n",
    "    rcoeff = np.array(r.constant_cf)\n",
    "    vcoeff = np.array(v.constant_cf)\n",
    "    thetacoeff = np.array(theta.constant_cf)\n",
    "    omegacoeff = np.array(omega.constant_cf)\n",
    "    mucoeff = np.array(mu.constant_cf)\n",
    "    err = dPdr * vcoeff +  dPdv * (-mucoeff/rcoeff**2 + rcoeff*omegacoeff**2) + dPdtheta * omegacoeff + dPdomega * (-2*vcoeff*omegacoeff/rcoeff)\n",
    "    check = sum(dPdr*dPdr + dPdv*dPdv +dPdomega*dPdomega+ dPdtheta*dPdtheta)\n",
    "    return sum(err * err ), check"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# We run an evolutionary strategy ES(1 + offspring)\n",
    "def run_experiment(max_gen, offsprings, dCGP,  r, v, theta, omega, mu, obj_fun, screen_output=False):\n",
    "    chromosome = [1] * offsprings\n",
    "    fitness = [1] *offsprings\n",
    "    best_chromosome = dCGP.get()\n",
    "    best_fitness = 1e10\n",
    "        \n",
    "    for g in range(max_gen):\n",
    "        for i in range(offsprings):\n",
    "            check = 0\n",
    "            while(check < 1e-3):\n",
    "                dCGP.set(best_chromosome)\n",
    "                dCGP.mutate_active(i+1) #  we mutate a number of increasingly higher active genes\n",
    "                fitness[i], check = obj_fun(dCGP, r, v, theta, omega, mu)\n",
    "            chromosome[i] = dCGP.get()\n",
    "        for i in range(offsprings):\n",
    "            if fitness[i] <= best_fitness:\n",
    "                if (fitness[i] != best_fitness) and screen_output:\n",
    "                    dCGP.set(chromosome[i])\n",
    "                    print(\"New best found: gen: \", g, \" value: \", fitness[i], \" \", dCGP.simplify([\"r\",\"v\",\"theta\",\"omega\",\"mu\"]))\n",
    "                best_chromosome = chromosome[i]\n",
    "                best_fitness = fitness[i]\n",
    "        if best_fitness < 1e-12:\n",
    "            break\n",
    "    dCGP.set(best_chromosome)\n",
    "    return g, dCGP\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "restart: \t gen: \t expression:\n",
      "0 \t\t 117 \t ['((r+r)/((r+r)+((mu/omega)/(r+r))))']  a.k.a  [2*r/(mu/(2*omega*r) + 2*r)]\n",
      "1 \t\t 76 \t ['((omega*r)*r)']  a.k.a  [omega*r**2]\n",
      "2 \t\t 421 \t ['((mu+theta)/((((mu+theta)*(theta-(mu+theta)))*r)*(r*omega)))']  a.k.a  [-1/(mu*omega*r**2)]\n",
      "3 \t\t 22 \t ['((omega*((theta*(theta-theta))-r))*((theta*(theta-theta))-r))']  a.k.a  [omega*r**2]\n",
      "4 \t\t 634 \t ['(((omega/omega)/(mu+((r*omega)*r)))/(omega/omega))']  a.k.a  [1/(mu + omega*r**2)]\n",
      "5 \t\t 408 \t ['((r*(omega*r))/(theta/theta))']  a.k.a  [omega*r**2]\n",
      "6 \t\t 533 \t ['(mu-((r*omega)*(r/mu)))']  a.k.a  [mu - omega*r**2/mu]\n",
      "7 \t\t 73 \t ['((omega/((r/mu)*omega))/((r/mu)*omega))']  a.k.a  [mu**2/(omega*r**2)]\n",
      "8 \t\t 1573 \t ['((r*(mu*omega))*(v-(r+v)))']  a.k.a  [-mu*omega*r**2]\n",
      "9 \t\t 196 \t ['((((r/theta)*theta)/(mu*(theta/v)))*((omega*(mu*(theta/v)))*r))']  a.k.a  [omega*r**2]\n",
      "10 \t\t 21 \t ['(omega*(r*r))']  a.k.a  [omega*r**2]\n",
      "12 \t\t 316 \t ['((r*(omega/v))*(v*r))']  a.k.a  [omega*r**2]\n",
      "14 \t\t 6 \t ['(((r*r)*omega)/mu)']  a.k.a  [omega*r**2/mu]\n",
      "16 \t\t 68 \t ['((omega*r)*r)']  a.k.a  [omega*r**2]\n",
      "18 \t\t 1660 \t ['((r*omega)*r)']  a.k.a  [omega*r**2]\n",
      "19 \t\t 267 \t ['((theta/r)/((r*omega)*theta))']  a.k.a  [1/(omega*r**2)]\n",
      "20 \t\t 1392 \t ['((((mu+theta)-theta)/omega)/((r*((mu+theta)-theta))*r))']  a.k.a  [1/(omega*r**2)]\n",
      "21 \t\t 231 \t ['((((omega/v)/(((r*omega)*r)*((r*omega)*r)))/((r*omega)*r))/(omega/v))']  a.k.a  [1/(omega**3*r**6)]\n",
      "23 \t\t 337 \t ['((((theta/theta)/((theta/theta)*mu))/((mu/r)/omega))/(mu/r))']  a.k.a  [omega*r**2/mu**3]\n",
      "24 \t\t 27 \t ['((mu/(mu-theta))/(omega/((((mu-theta)/r)*((mu-theta)/r))*(mu/(mu-theta)))))']  a.k.a  [mu**2/(omega*r**2)]\n",
      "25 \t\t 42 \t ['(((omega*(r*theta))*mu)/(((omega*(r*theta))+(theta/r))*mu))']  a.k.a  [omega*r*theta/(omega*r*theta + theta/r)]\n",
      "26 \t\t 16 \t ['(theta/(((r*r)*theta)*omega))']  a.k.a  [1/(omega*r**2)]\n",
      "27 \t\t 261 \t ['(r*((((v*(mu*mu))*(mu*theta))-(((v*(mu*mu))*(mu*theta))+omega))*r))']  a.k.a  [-omega*r**2]\n",
      "28 \t\t 285 \t ['(mu*(omega*(r*r)))']  a.k.a  [mu*omega*r**2]\n",
      "29 \t\t 1021 \t ['((mu/(((r*omega)*r)+mu))/(((r*omega)*r)+mu))']  a.k.a  [mu/(mu**2 + 2*mu*omega*r**2 + omega**2*r**4)]\n",
      "30 \t\t 120 \t ['(((r*omega)*(v+r))+((r*omega)*(r-v)))']  a.k.a  [2*omega*r**2]\n",
      "31 \t\t 528 \t ['(omega/((omega*r)*(omega*r)))']  a.k.a  [1/(omega*r**2)]\n",
      "33 \t\t 931 \t ['(mu/(r*(omega*r)))']  a.k.a  [mu/(omega*r**2)]\n",
      "34 \t\t 153 \t ['(((mu/r)/(r/mu))/omega)']  a.k.a  [mu**2/(omega*r**2)]\n",
      "35 \t\t 113 \t ['((((r*r)*omega)+mu)/mu)']  a.k.a  [1 + omega*r**2/mu]\n",
      "36 \t\t 142 \t ['((omega*mu)*((r*r)*mu))']  a.k.a  [mu**2*omega*r**2]\n",
      "37 \t\t 193 \t ['((mu/(mu+mu))-((r*omega)*r))']  a.k.a  [-omega*r**2 + 1/2]\n",
      "38 \t\t 5 \t ['(r/((mu/omega)/r))']  a.k.a  [omega*r**2/mu]\n",
      "39 \t\t 31 \t ['((r*omega)*r)']  a.k.a  [omega*r**2]\n",
      "40 \t\t 87 \t ['((omega/(mu/r))/(mu/r))']  a.k.a  [omega*r**2/mu**2]\n",
      "41 \t\t 118 \t ['(r*(r*omega))']  a.k.a  [omega*r**2]\n",
      "42 \t\t 301 \t ['((r*(omega*r))-(((theta-theta)+(theta-theta))/r))']  a.k.a  [omega*r**2]\n",
      "43 \t\t 1147 \t ['(r*(omega*r))']  a.k.a  [omega*r**2]\n",
      "44 \t\t 649 \t ['((r*(r*(omega*theta)))/(mu*theta))']  a.k.a  [omega*r**2/mu]\n",
      "46 \t\t 57 \t ['((r*r)/(mu/omega))']  a.k.a  [omega*r**2/mu]\n",
      "47 \t\t 309 \t ['((r/(((r*mu)*omega)/((r*mu)*omega)))*((r*mu)*omega))']  a.k.a  [mu*omega*r**2]\n",
      "48 \t\t 194 \t ['(((mu*(omega/mu))*r)*r)']  a.k.a  [omega*r**2]\n",
      "49 \t\t 516 \t ['(r*(omega*r))']  a.k.a  [omega*r**2]\n",
      "50 \t\t 623 \t ['((omega*r)*r)']  a.k.a  [omega*r**2]\n",
      "51 \t\t 291 \t ['(r*(r*omega))']  a.k.a  [omega*r**2]\n",
      "52 \t\t 245 \t ['(omega/((mu/r)/r))']  a.k.a  [omega*r**2/mu]\n",
      "53 \t\t 60 \t ['((omega/(mu*mu))*(r*(r-(v-v))))']  a.k.a  [omega*r**2/mu**2]\n",
      "56 \t\t 202 \t ['(((omega*r)*(omega*r))/omega)']  a.k.a  [omega*r**2]\n",
      "57 \t\t 85 \t ['((r*r)*omega)']  a.k.a  [omega*r**2]\n",
      "58 \t\t 72 \t ['(r/(((theta*mu)/omega)/(r*theta)))']  a.k.a  [omega*r**2/mu]\n",
      "59 \t\t 5 \t ['(((mu*mu)/(mu*r))/(omega*(mu*r)))']  a.k.a  [1/(omega*r**2)]\n",
      "60 \t\t 7 \t ['(omega*((r+r)*r))']  a.k.a  [2*omega*r**2]\n",
      "61 \t\t 545 \t ['(r*(r*omega))']  a.k.a  [omega*r**2]\n",
      "62 \t\t 178 \t ['((((r*v)*omega)*(r/v))*(((r*v)*omega)*(r/v)))']  a.k.a  [omega**2*r**4]\n",
      "63 \t\t 233 \t ['((r*((r*omega)*mu))*(r*((r*omega)*mu)))']  a.k.a  [mu**2*omega**2*r**4]\n",
      "64 \t\t 1 \t ['((r/r)/(omega*(r*r)))']  a.k.a  [1/(omega*r**2)]\n",
      "65 \t\t 100 \t ['(((mu/r)*(mu/r))/omega)']  a.k.a  [mu**2/(omega*r**2)]\n",
      "66 \t\t 389 \t ['(((omega/(theta/((r*theta)*r)))-(mu-(r*theta)))+(mu-(r*theta)))']  a.k.a  [omega*r**2]\n",
      "67 \t\t 17 \t ['(r/((mu/r)/omega))']  a.k.a  [omega*r**2/mu]\n",
      "68 \t\t 19 \t ['(r*(r*omega))']  a.k.a  [omega*r**2]\n",
      "69 \t\t 29 \t ['((r*r)*omega)']  a.k.a  [omega*r**2]\n",
      "70 \t\t 882 \t ['(((((theta+theta)*((theta+theta)-mu))/omega)/r)/(r*((theta+theta)*((theta+theta)-mu))))']  a.k.a  [1/(omega*r**2)]\n",
      "71 \t\t 965 \t ['(((mu/r)/(mu*omega))/r)']  a.k.a  [1/(omega*r**2)]\n",
      "72 \t\t 363 \t ['(((r*r)/(r*r))*((r*r)*omega))']  a.k.a  [omega*r**2]\n",
      "73 \t\t 397 \t ['((omega*r)*r)']  a.k.a  [omega*r**2]\n",
      "74 \t\t 270 \t ['((omega/(r*(omega*mu)))/(r*(omega*mu)))']  a.k.a  [1/(mu**2*omega*r**2)]\n",
      "75 \t\t 3 \t ['(r*(omega*r))']  a.k.a  [omega*r**2]\n",
      "76 \t\t 98 \t ['((mu/omega)/((mu*r)*(mu*r)))']  a.k.a  [1/(mu*omega*r**2)]\n",
      "77 \t\t 161 \t ['(r*(r*omega))']  a.k.a  [omega*r**2]\n",
      "78 \t\t 947 \t ['((mu/r)*((mu/r)/omega))']  a.k.a  [mu**2/(omega*r**2)]\n",
      "79 \t\t 5 \t ['((omega-(omega/mu))/((mu/(r*r))+(mu/(r*r))))']  a.k.a  [omega*r**2/(2*mu) - omega*r**2/(2*mu**2)]\n",
      "80 \t\t 169 \t ['(omega/((((mu/r)-v)+v)*(mu/r)))']  a.k.a  [omega*r**2/mu**2]\n",
      "81 \t\t 568 \t ['((r*omega)*r)']  a.k.a  [omega*r**2]\n",
      "82 \t\t 400 \t ['(((r*r)*(r*r))*(omega/(r*r)))']  a.k.a  [omega*r**2]\n",
      "83 \t\t 37 \t ['(omega*(r*r))']  a.k.a  [omega*r**2]\n",
      "84 \t\t 211 \t ['(((v-v)-((r-omega)+omega))*(r*omega))']  a.k.a  [-omega*r**2]\n",
      "85 \t\t 1423 \t ['(((omega/((mu/theta)/r))*r)/theta)']  a.k.a  [omega*r**2/mu]\n",
      "86 \t\t 17 \t ['(r*((omega/(v/r))*v))']  a.k.a  [omega*r**2]\n",
      "87 \t\t 127 \t ['(r*((r*mu)*omega))']  a.k.a  [mu*omega*r**2]\n",
      "88 \t\t 1078 \t ['(r*(omega*r))']  a.k.a  [omega*r**2]\n",
      "89 \t\t 7 \t ['((mu-((r*(r*omega))-mu))*(mu-((r*(r*omega))-mu)))']  a.k.a  [4*mu**2 - 4*mu*omega*r**2 + omega**2*r**4]\n",
      "90 \t\t 376 \t ['(((mu/r)/((r+(theta+theta))-(theta+theta)))/(omega*mu))']  a.k.a  [1/(omega*r**2)]\n",
      "91 \t\t 45 \t ['(((omega/(mu+r))/(omega/(mu+r)))/(((r*(r/mu))*mu)*(mu*omega)))']  a.k.a  [1/(mu*omega*r**2)]\n",
      "92 \t\t 219 \t ['((r*r)*(omega*mu))']  a.k.a  [mu*omega*r**2]\n",
      "93 \t\t 679 \t ['((mu/omega)/((r+r)*(r+r)))']  a.k.a  [mu/(4*omega*r**2)]\n",
      "94 \t\t 608 \t ['(omega/(((theta/r)/theta)*((theta/r)/theta)))']  a.k.a  [omega*r**2]\n",
      "95 \t\t 15 \t ['((omega*r)*r)']  a.k.a  [omega*r**2]\n",
      "96 \t\t 259 \t ['((r*(r*omega))-mu)']  a.k.a  [-mu + omega*r**2]\n",
      "97 \t\t 829 \t ['((((r/v)*v)*omega)*((r+v)-v))']  a.k.a  [omega*r**2]\n",
      "98 \t\t 101 \t ['(((r+(mu*r))+(mu*r))*(omega*r))']  a.k.a  [2*mu*omega*r**2 + omega*r**2]\n",
      "99 \t\t 18 \t ['((r/(mu/(omega+omega)))*r)']  a.k.a  [2*omega*r**2/mu]\n"
     ]
    }
   ],
   "source": [
    "# We run nexp experiments to accumulate statistic for the ERT (angular momentum case)\n",
    "nexp = 100\n",
    "offsprings = 10\n",
    "stop = 2000 #100000\n",
    "res = []\n",
    "print(\"restart: \\t gen: \\t expression:\")\n",
    "for i in range(nexp):\n",
    "    dCGP = expression(inputs=5, outputs=1, rows=1, cols=15, levels_back=16, arity=2, kernels=kernels, seed = randint(0,234213213))\n",
    "    g, dCGP = run_experiment(stop, 10, dCGP, r, v, theta, omega, mu, fitness_call_free, False)\n",
    "    res.append(g)\n",
    "    if g < (stop-1):\n",
    "        print(i, \"\\t\\t\", res[i], \"\\t\", dCGP([\"r\",\"v\",\"theta\",\"omega\",\"mu\"]), \" a.k.a \", dCGP.simplify([\"r\",\"v\",\"theta\",\"omega\",\"mu\"]))\n",
    "        one_sol = dCGP\n",
    "res = np.array(res)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ERT Expected run time - avg. number of function evaluations needed:  5270.98901099\n"
     ]
    }
   ],
   "source": [
    "ERT = sum(res) / sum(res<(stop-1))\n",
    "print(\"ERT Expected run time - avg. number of function evaluations needed: \", ERT * offsprings)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[2*omega*r**2/mu]\n"
     ]
    },
    {
     "data": {
      "image/png": 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Vvyczk0DUJ5hMJhw+fBiHDx/GgQMHUFtbi/DwcEyaNAmTJ0/GpEmT2jUdHhFR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/w1VVxdDQEILBIK6++mq4XK5F2zbRCsLC0MVMCIG+vj4MDg6uyGXXLRYLVq9ejba2Nt0NlBAC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\nT38an/jEJ7B27dqSSZj4fD5Eo1F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      "text/plain": [
       "<matplotlib.figure.Figure at 0x7f5acd94b208>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "text/plain": [
       "<matplotlib.image.AxesImage at 0x7f5acc158cc0>"
      ]
     },
     "execution_count": 22,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "print(one_sol.simplify([\"r\",\"v\",\"theta\",\"omega\",\"mu\"]))\n",
    "plt.rcParams[\"figure.figsize\"] = [20,20]\n",
    "one_sol.visualize([\"r\",\"v\",\"theta\",\"omega\",\"mu\"])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "restart: \t gen: \t expression:\n",
      "2 \t\t 25413 \t ['(((v-r)*(v+r))-((((mu-r)+(mu-r))/r)-((r-(r*omega))*(r-(r*omega)))))']  a.k.a  [-2*mu/r + omega**2*r**2 - 2*omega*r**2 + v**2 + 2]\n",
      "3 \t\t 46221 \t ['((v*(v*(mu+mu)))-((((mu+mu)*(mu+mu))/((r*r)/r))-(((omega*omega)*(r*r))*(mu+mu))))']  a.k.a  [-4*mu**2/r + 2*mu*omega**2*r**2 + 2*mu*v**2]\n",
      "6 \t\t 97122 \t ['(((((v*(v*r))-mu)+(((omega*r)*(r*(omega*r)))-mu))*(omega*r))*mu)']  a.k.a  [-2*mu**2*omega*r + mu*omega**3*r**4 + mu*omega*r**2*v**2]\n",
      "8 \t\t 28010 \t ['(((mu/r)-((v*v)-(mu/r)))-((r*omega)*(r*omega)))']  a.k.a  [2*mu/r - omega**2*r**2 - v**2]\n",
      "16 \t\t 22942 \t ['(((omega*r)*((mu/(mu/r))+(omega*r)))+(mu-((mu/r)+((mu/r)-(v*v)))))']  a.k.a  [mu - 2*mu/r + omega**2*r**2 + omega*r**2 + v**2]\n",
      "28 \t\t 63318 \t ['(((((mu/r)+mu)-((omega*r)*(omega*r)))+(((mu/r)+mu)-(v*v)))+((((mu/r)+mu)-((omega*r)*(omega*r)))+(((mu/r)+mu)-(v*v))))']  a.k.a  [4*mu + 4*mu/r - 2*omega**2*r**2 - 2*v**2]\n",
      "36 \t\t 12543 \t ['(((omega*r)*(r-(omega*r)))+((mu/r)-((v*v)-(mu/r))))']  a.k.a  [2*mu/r - omega**2*r**2 + omega*r**2 - v**2]\n",
      "42 \t\t 64916 \t ['((((omega*r)*(omega*r))-mu)-(((mu/(r*v))+((mu/(r*v))-v))*v))']  a.k.a  [-mu - 2*mu/r + omega**2*r**2 + v**2]\n",
      "48 \t\t 86173 \t ['(((r*(omega*omega))*r)+((((v*r)*v)+((r-mu)+(r-mu)))/r))']  a.k.a  [-2*mu/r + omega**2*r**2 + v**2 + 2]\n",
      "56 \t\t 29174 \t ['(((omega*(omega+(mu/mu)))/(((mu/mu)/r)/r))-((mu/r)+((mu/r)-(v*v))))']  a.k.a  [-2*mu/r + omega**2*r**2 + omega*r**2 + v**2]\n",
      "59 \t\t 47790 \t ['((((r*omega)*(r*omega))-(((mu-r)+(mu-r))/r))+((mu/mu)+(v*v)))']  a.k.a  [-2*mu/r + omega**2*r**2 + v**2 + 3]\n",
      "61 \t\t 36982 \t ['((((r*omega)*omega)*r)-(((mu/r)+(mu/r))-(v*v)))']  a.k.a  [-2*mu/r + omega**2*r**2 + v**2]\n",
      "81 \t\t 34496 \t ['((v*v)-((((((mu/r)+(mu/r))+(omega*(r*r)))-((omega*(r*r))*omega))+(omega*(r*r)))+mu))']  a.k.a  [-mu - 2*mu/r + omega**2*r**2 - 2*omega*r**2 + v**2]\n",
      "86 \t\t 58369 \t ['(((omega*r)*(omega*r))-(((mu/r)+(mu/r))-(v*v)))']  a.k.a  [-2*mu/r + omega**2*r**2 + v**2]\n",
      "90 \t\t 63291 \t ['(((omega*r)*(omega*r))+((v*v)+(((omega*(mu/(omega*r)))*r)-((mu+mu)/r))))']  a.k.a  [mu - 2*mu/r + omega**2*r**2 + v**2]\n"
     ]
    }
   ],
   "source": [
    "# We run nexp experiments to accumulate statistic for the ERT (angular momentum case)\n",
    "nexp = 100\n",
    "offsprings = 10\n",
    "stop = 100000\n",
    "res = []\n",
    "print(\"restart: \\t gen: \\t expression:\")\n",
    "for i in range(nexp):\n",
    "    dCGP = expression(inputs=5, outputs=1, rows=1, cols=15, levels_back=16, arity=2, kernels=kernels, seed = randint(0,234213213))\n",
    "    g, dCGP = run_experiment(stop, 10, dCGP, r, v, theta, omega, mu, fitness_call, False)\n",
    "    res.append(g)\n",
    "    if g < (stop-1):\n",
    "        print(i, \"\\t\\t\", res[i], \"\\t\", dCGP([\"r\",\"v\",\"theta\",\"omega\",\"mu\"]), \" a.k.a \", dCGP.simplify([\"r\",\"v\",\"theta\",\"omega\",\"mu\"]))\n",
    "        one_sol = dCGP\n",
    "res = np.array(res)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "ERT = sum(res) / sum(res<(stop-1))\n",
    "print(\"ERT Expected run time - avg. number of function evaluations needed: \", ERT * offsprings)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
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