pybo.ipynb

{
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  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# How to optimise an n-dimensional function with pybo.solve_bayesopt"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "from pybo import solve_bayesopt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "As an example, define some function with an obvious maximum:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# function with maximum at (1,2,3)\n",
    "def f(input):\n",
    "    x,y,z = input\n",
    "    x = float(x)\n",
    "    y = float(y)\n",
    "    z = float(z)\n",
    "    x = x - 1\n",
    "    y = y - 2\n",
    "    z = z - 3\n",
    "    return -(x**2)*(y**2)*(z**2)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Now all you need to do is:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "i=000, x=[ 1.899  2.941  2.008], y=-0.704, xbest=[ 0.000  3.000  3.053]\n",
      "i=001, x=[ 1.834  1.024  3.999], y=-0.660, xbest=[ 0.000  1.000  3.264]\n",
      "i=002, x=[ 0.050  1.017  2.016], y=-0.843, xbest=[ 0.891  3.000  2.372]\n",
      "i=003, x=[ 0.342  3.000  4.000], y=-0.433, xbest=[ 1.237  3.000  3.520]\n",
      "i=004, x=[ 1.134  2.971  3.485], y=-0.004, xbest=[ 1.517  2.058  3.204]\n",
      "i=005, x=[ 0.191  1.265  3.297], y=-0.031, xbest=[ 1.426  2.878  3.279]\n",
      "i=006, x=[ 0.000  3.000  3.304], y=-0.092, xbest=[ 1.406  3.000  3.382]\n",
      "i=007, x=[ 1.406  2.974  3.324], y=-0.016, xbest=[ 0.928  2.020  2.464]\n",
      "i=008, x=[ 0.341  2.864  2.718], y=-0.026, xbest=[ 1.328  1.752  3.378]\n",
      "i=009, x=[ 0.446  1.041  2.279], y=-0.146, xbest=[ 0.825  2.426  2.408]\n",
      "i=010, x=[ 0.866  2.935  2.409], y=-0.005, xbest=[ 1.606  1.900  2.961]\n",
      "i=011, x=[ 1.677  1.052  2.451], y=-0.124, xbest=[ 1.638  2.046  3.077]\n",
      "i=012, x=[ 0.049  2.041  3.191], y=-0.000, xbest=[ 1.484  1.631  3.086]\n",
      "i=013, x=[ 0.240  2.100  3.057], y=-0.000, xbest=[ 1.386  1.000  3.036]\n",
      "i=014, x=[ 0.014  2.024  3.996], y=-0.001, xbest=[ 1.617  1.226  3.008]\n",
      "i=015, x=[ 0.005  1.278  3.850], y=-0.373, xbest=[ 0.260  1.431  3.025]\n",
      "i=016, x=[ 0.007  2.801  3.894], y=-0.505, xbest=[ 1.532  2.168  3.063]\n",
      "i=017, x=[ 0.495  1.323  3.229], y=-0.006, xbest=[ 1.454  2.217  2.878]\n",
      "i=018, x=[ 1.453  2.222  2.753], y=-0.001, xbest=[ 1.395  1.420  2.000]\n",
      "i=019, x=[ 0.024  2.948  2.004], y=-0.849, xbest=[ 0.827  1.870  3.842]\n",
      "i=020, x=[ 0.522  1.005  2.713], y=-0.019, xbest=[ 1.151  2.075  4.000]\n",
      "i=021, x=[ 1.157  2.154  3.996], y=-0.001, xbest=[ 0.975  2.208  3.464]\n",
      "i=022, x=[ 1.456  1.820  2.250], y=-0.004, xbest=[ 0.850  2.126  3.452]\n",
      "i=023, x=[ 0.869  2.154  3.461], y=-0.000, xbest=[ 0.303  1.802  3.277]\n",
      "i=024, x=[ 1.998  1.456  3.247], y=-0.018, xbest=[ 0.254  1.704  3.260]\n",
      "i=025, x=[ 1.800  1.030  2.006], y=-0.595, xbest=[ 0.326  1.774  3.373]\n",
      "i=026, x=[ 2.000  3.000  3.981], y=-0.962, xbest=[ 0.747  2.226  4.000]\n",
      "i=027, x=[ 0.598  2.089  4.000], y=-0.001, xbest=[ 0.290  1.649  3.180]\n",
      "i=028, x=[ 1.768  1.609  2.806], y=-0.003, xbest=[ 0.281  1.657  3.205]\n",
      "i=029, x=[ 1.025  2.104  2.330], y=-0.000, xbest=[ 1.499  2.296  3.322]\n"
     ]
    }
   ],
   "source": [
    "# Define the ranges in which to look for an optimum\n",
    "bounds = [[0,2],[1,3],[2,4]]\n",
    "# Define how many iterations to do\n",
    "n = 30\n",
    "# Run the solver:\n",
    "xbest,model,info = solve_bayesopt(f,bounds,niter=n,verbose=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "[ 1.49889517  2.29618329  3.32210738]\n"
     ]
    }
   ],
   "source": [
    "print xbest"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Looks like it did okay... Probably needs some more iterations but it's quite slow on my laptop"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
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