FOXSISIM_Energy_Response_Big_Angles.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Creating a big shell, if the energy response works welll, the high energy photons should not appear on the detector."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Playing the focal lengths of the FOXSI optics"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "from foxsisim.module import Module\n",
    "from foxsisim.detector import Detector\n",
    "from foxsisim.source import Source\n",
    "from foxsisim.plotting import plot,scatterHist\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Creating spectrum"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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JzwD/DXg6LY+jvLFC9tz2WyStljQ3rSvjd+F5QD9wXWqO+7KksRQQa8Mnpo0E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\nWfL/Abmnq56Z2zXDAAAAAElFTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x10b2bcd30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "max_energy = 30.0\n",
    "def spectrum(z):\n",
    "        if (type(z) is not type([1])) and (type(z) is not type(np.array(1))):\n",
    "            x = np.array([z])\n",
    "        else:\n",
    "            x = np.array(z)\n",
    "        return np.piecewise(x, [x < 0, ((x < max_energy) & (x > 0)), (x >= max_energy)], [0, 1./max_energy, 0])\n",
    "    \n",
    "source_distance = -1e4 ##cm\n",
    "source = Source(type='point', center=[0, 0, source_distance])\n",
    "source.loadSpectrum(spectrum)\n",
    "energies = np.arange(-10, 60, 0.1)\n",
    "plt.plot(energies, source._spectrum(energies))\n",
    "plt.xlabel('Energy [keV]')\n",
    "plt.title('Source Spectrum')\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# F = 200"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "collapsed": false
   },
   "outputs": [],
   "source": [
    "module = Module(radii=[5.151,4.9],focal=200.0)\n",
    "detector = Detector(width=8, \n",
    "                    height=8,\n",
    "                    normal = [0,0,1],\n",
    "                    center = [0,0,230],\n",
    "                    reso = [1024,1024])\n",
    "\n",
    "rays = source.generateRays(module.targetFront, 500)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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fX1+guWZm1hpFAoLKpEXBPJsr+8mIGAkcA3xZ0hHldh4R0yOiOiKq+/fvX6C5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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1135cb7f0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.hist([ray.energy for ray in rays], normed=True, label='generated rays')\n",
    "plt.xlabel('Energy [keV]')\n",
    "plt.title('Histogram generated rays')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Pass and catch rays "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of rays on Detector 32\n",
      "Time total: 164 seconds\n",
      "Time per ray (s): 0.1951219512195122\n"
     ]
    }
   ],
   "source": [
    "from datetime import datetime\n",
    "tstart = datetime.now()\n",
    "\n",
    "# pass rays through module\n",
    "module.passRays(rays, robust=True)\n",
    "# catch rays at detector\n",
    "detector.catchRays(rays)\n",
    "\n",
    "\n",
    "rays_on_detector = len(detector.rays)\n",
    "print('Number of rays on Detector ' + str(rays_on_detector))\n",
    "print('Time total: ' + str((datetime.now() - tstart).seconds) + ' seconds')\n",
    "print('Time per ray (s): ' + str(rays_on_detector / float((datetime.now() - tstart).seconds)))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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      "text/plain": [
       "<matplotlib.figure.Figure at 0x11328dd68>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "drays = [ray for ray in rays if ray.des[2]==230.0]\n",
    "scatterHist(drays)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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a15QnqYukP0l6KtX37VrXVEpSJ0lPSvp1rWspJel5SX+WNFtSU63ryZO0u6Rp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\nDEs70wTUngAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x114bcdc88>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.hist([ray.energy for ray in detector.rays], normed=True, label='rays on detector',color='r')\n",
    "plt.xlabel('Energy [keV]')\n",
    "plt.title('Histogram caught rays on detector')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# F = 190"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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CHPpmZglx6JuZJcShb2aWEIe+mVlCHPpmZglx6JuZJcShb2aWkJJCX9LRkp6TtFzSpHq2\nd5J0a779CUkVRdv3klQj6ZyWqbaZmTVHo6EvqR3wc+AYYAAwTtKAomITgDcjYh/gKuDyou1XAb/b\n8uqamdmWKKWnfwiwPCJejIgPgBnAqKIyo4Bp+f2ZwHBJApA0GngRWNIyVTYzs+YqJfT3AFYWLFfn\n6+otExEbgLeBnpK6AucCF2/uBJImSqqSVOXf7DQz23pKCX3Vsy5KLHMxcFVE1GzuBBExNSIqI6Ky\nV69eJVTJzMyao5QfRq8G9ixY7gOsaqBMtaT2QHfgDeBQ4HhJPwJ6ABsl1UbEz7a45mZm1mSlhP58\nYF9J/YBXgLHAN4rKzAJOAR4DjgdmR0QAh9cVkHQRUOPANzMrn0ZDPyI2SDoLeBBoB1wXEUskXQJU\nRcQs4FpguqTlZD38sVuz0mZm1jyl9PSJiPuB+4vWXVBwvxYY08gxLmpG/czMrAX5G7lmZglx6JuZ\nJcShb2aWEIe+mVlCHPpmZgkp6dM7ZvWpmHRfWc674odfK8t5zbYH7umbmSXEoW9mlhCHvplZQhz6\nZmYJceibmSXEn96xNqdcnxoCf3JoW/Knw7YO9/TNzBLi0DczS4hD38wsIQ59M7OEOPTNzBLi0Dcz\nS4hD38wsIQ59M7OE+MtZZm2Av5BmLcU9fTOzhDj0zcwS4tA3M0uIQ9/MLCEOfTOzhDj0zcwS4tA3\nM0uIQ9/MLCEOfTOzhDj0zcwS4tA3M0uIQ9/MLCEOfTOzhDj0zcwSUlLoSzpa0nOSlkuaVM/2TpJu\nzbc/IakiX3+IpMX57SlJX2/Z6puZWVM0GvqS2gE/B44BBgDjJA0oKjYBeDMi9gGuAi7P1z8DVEbE\nIOBo4FeSPIe/mVmZlNLTPwRYHhEvRsQHwAxgVFGZUcC0/P5MYLgkRcR7EbEhX98ZiJaotJmZNU8p\nve49gJUFy9XAoQ2ViYgNkt4GegLrJB0KXAf0BU4qeBLYRNJEYCLAXnvt1dQ2mNlWVM5f7bKWV0pP\nX/WsK+6xN1gmIp6IiIHAwcB5kjp/omDE1IiojIjKXr16lVAlMzNrjlJ6+tXAngXLfYBVDZSpzsfs\nuwNvFBaIiGWS/g7sD1Q1u8atVLl6Q/79UjNrilJ6+vOBfSX1k9QRGAvMKiozCzglv388MDsiIt+n\nPYCkvsA/AStapOZmZtZkjfb08zH6s4AHgXbAdRGxRNIlQFVEzAKuBaZLWk7Wwx+b7z4UmCRpPbAR\nODMi1m2NhpiZWeNK+vhkRNwP3F+07oKC+7XAmHr2mw5M38I6mrUaflNz+1fOa7wthmv9jVwzs4Q4\n9M3MEuLQNzNLiEPfzCwhDn0zs4Q49M3MEuLQNzNLiEPfzCwhDn0zs4Q49M3MEuLQNzNLiH+6sI3z\nXDBm1hTu6ZuZJcShb2aWEIe+mVlCHPpmZglx6JuZJcShb2aWEIe+mVlCHPpmZglx6JuZJcShb2aW\nEIe+mVlCHPpmZglx6JuZJcShb2aWEIe+mVlCHPpmZglx6JuZJcShb2aWEIe+mVlCHPpmZglx6JuZ\nJcShb2aWkJJCX9LRkp6TtFzSpHq2d5J0a779CUkV+foRkhZI+kv+75dbtvpmZtYUjYa+pHbAz4Fj\ngAHAOEkDiopNAN6MiH2Aq4DL8/XrgJER8TngFGB6S1XczMyarpSe/iHA8oh4MSI+AGYAo4rKjAKm\n5fdnAsMlKSIWRcSqfP0SoLOkTi1RcTMza7pSQn8PYGXBcnW+rt4yEbEBeBvoWVTmOGBRRLxffAJJ\nEyVVSapau3ZtqXU3M7MmKiX0Vc+6aEoZSQPJhnxOr+8EETE1IiojorJXr14lVMnMzJqjlNCvBvYs\nWO4DrGqojKT2QHfgjXy5D3AXcHJEvLClFTYzs+YrJfTnA/tK6iepIzAWmFVUZhbZG7UAxwOzIyIk\n9QDuA86LiEdbqtJmZtY8jYZ+PkZ/FvAgsAy4LSKWSLpE0rF5sWuBnpKWA/8J1H2s8yxgH+B8SYvz\nW+8Wb4WZmZWkfSmFIuJ+4P6idRcU3K8FxtSz32Rg8hbW0czMWoi/kWtmlhCHvplZQhz6ZmYJceib\nmSXEoW9mlhCHvplZQhz6ZmYJceibmSXEoW9mlhCHvplZQhz6ZmYJceibmSXEoW9mlhCHvplZQhz6\nZmYJceibmSXEoW9mlhCHvplZQhz6ZmYJceibmSXEoW9mlhCHvplZQhz6ZmYJceibmSXEoW9mlhCH\nvplZQhz6ZmYJceibmSXEoW9mlhCHvplZQhz6ZmYJceibmSXEoW9mlhCHvplZQhz6ZmYJKSn0JR0t\n6TlJyyVNqmd7J0m35tufkFSRr+8paY6kGkk/a9mqm5lZUzUa+pLaAT8HjgEGAOMkDSgqNgF4MyL2\nAa4CLs/X1wLnA+e0WI3NzKzZSunpHwIsj4gXI+IDYAYwqqjMKGBafn8mMFySIuLvETGPLPzNzKzM\nSgn9PYCVBcvV+bp6y0TEBuBtoGeplZA0UVKVpKq1a9eWupuZmTVRKaGvetZFM8o0KCKmRkRlRFT2\n6tWr1N3MzKyJSgn9amDPguU+wKqGykhqD3QH3miJCpqZWcspJfTnA/tK6iepIzAWmFVUZhZwSn7/\neGB2RJTc0zczs22jfWMFImKDpLOAB4F2wHURsUTSJUBVRMwCrgWmS1pO1sMfW7e/pBXAzkBHSaOB\nIyNiacs3xczMGtNo6ANExP3A/UXrLii4XwuMaWDfii2on5mZtSB/I9fMLCEOfTOzhDj0zcwS4tA3\nM0uIQ9/MLCEOfTOzhDj0zcwS4tA3M0uIQ9/MLCEOfTOzhDj0zcwS4tA3M0uIQ9/MLCEOfTOzhDj0\nzcwS4tA3M0uIQ9/MLCEOfTOzhDj0zcwS4tA3M0uIQ9/MLCEOfTOzhDj0zcwS4tA3M0uIQ9/MLCEO\nfTOzhDj0zcwS4tA3M0uIQ9/MLCEOfTOzhDj0zcwS4tA3M0uIQ9/MLCEOfTOzhDj0zcwSUlLoSzpa\n0nOSlkuaVM/2TpJuzbc/IamiYNt5+frnJB3VclU3M7OmajT0JbUDfg4cAwwAxkkaUFRsAvBmROwD\nXAVcnu87ABgLDASOBn6RH8/MzMqglJ7+IcDyiHgxIj4AZgCjisqMAqbl92cCwyUpXz8jIt6PiJeA\n5fnxzMysDNqXUGYPYGXBcjVwaENlImKDpLeBnvn6x4v23aP4BJImAhPzxRpJz5VU+0/aDVjXzH1b\nG7eldXJbWqftoi26fIva0beUQqWEvupZFyWWKWVfImIqMLWEumyWpKqIqNzS47QGbkvr5La0TttL\nW7ZFO0oZ3qkG9ixY7gOsaqiMpPZAd+CNEvc1M7NtpJTQnw/sK6mfpI5kb8zOKiozCzglv388MDsi\nIl8/Nv90Tz9gX+DJlqm6mZk1VaPDO/kY/VnAg0A74LqIWCLpEqAqImYB1wLTJS0n6+GPzfddIuk2\nYCmwAfj3iPhwK7UFWmCIqBVxW1ont6V12l7astXboaxDbmZmKfA3cs3MEuLQNzNLyHYT+o1NFdGW\nSFoh6S+SFkuqKnd9mkLSdZJek/RMwbpdJf1e0vP5v7uUs46laqAtF0l6Jb82iyV9tZx1LIWkPSXN\nkbRM0hJJ38rXt7nrspm2tMXr0lnSk5Keyttycb6+Xz6dzfP59DYdW/S828OYfj61w1+BEWQfE50P\njIuIpWWtWDNJWgFURkSb+7KJpGFADXBDROyfr/sR8EZE/DB/Qt4lIs4tZz1L0UBbLgJqImJKOevW\nFJJ2B3aPiIWSdgIWAKOB8bSx67KZtvwLbe+6COgaETWSOgDzgG8B/wncGREzJP038FRE/LKlzru9\n9PRLmSrCtoGImEv2Ca5ChdN0TCP7T9rqNdCWNiciVkfEwvz+u8Aysm/Gt7nrspm2tDmRqckXO+S3\nAL5MNp0NbIXrsr2Efn1TRbTJP4RcAA9JWpBPUdHWfSoiVkP2nxboXeb6bKmzJD2dD/+0+iGRQvkM\nuAcBT9DGr0tRW6ANXhdJ7SQtBl4Dfg+8ALwVERvyIi2eZdtL6Jc03UMb8sWIGEw2s+m/58MM1jr8\nEvgMMAhYDfy4vNUpnaRuwB3AtyPinXLXZ0vU05Y2eV0i4sOIGEQ2W8EhwH71FWvJc24vob9dTfcQ\nEavyf18D7qLtz0y6Jh+LrRuTfa3M9Wm2iFiT/0fdCPyaNnJt8jHjO4CbIuLOfHWbvC71taWtXpc6\nEfEW8DBwGNAjn84GtkKWbS+hX8pUEW2CpK75G1RI6gocCTyz+b1avcJpOk4BflvGumyRupDMfZ02\ncG3yNwyvBZZFxJUFm9rcdWmoLW30uvSS1CO/3wX4Ctl7FHPIprOBrXBdtotP7wDkH9G6mo+miris\nzFVqFkl7k/XuIZsm4+a21BZJtwBfIpvqdg1wIXA3cBuwF/A3YExEtPo3SBtoy5fIhhACWAGcXjcu\n3lpJGgo8AvwF2Jiv/h7ZWHibui6bacs42t51OYDsjdp2ZB3w2yLikjwDZgC7AouAEyPi/RY77/YS\n+mZm1rjtZXjHzMxK4NA3M0uIQ9/MLCEOfTOzhDj0zcwS4tC3NkXShwUzKS5uLTOqFsyMWlmwvFuJ\n+14v6fSidaMl3S+pS97OD0o9ntnmNPpziWatzD/yr623GEntC+Y62RJHNHNm1FuAScCvCtaNBW6J\niH8Ag/KZV822mHv6tl3Ie9YXS1qY97j75+u75hNwzZe0SNKofP14SbdLuodscrsdJP0in9f83ryX\nfbyk4ZLuKjjPCEl3NlCN+urVRdIDkk7Ll0/M51BfLOlX+bTgfwD6F0yJsCPZtzPvbrEHyCzn0Le2\npm64o+72rwXb1uUT1f0SOCdf931gdkQcDBwBXJFPbwEwBDglIr4M/DNQAXwO+Ga+DWA2sJ+kXvny\n/wZ+U2JduwH3kH2r+teS9gP+lWxCvUHAh8AJEfEhcCfZnPAAxwJz8qmDzVqUh3esrdnc8E5dD3wB\nWYhDNnfRsZLqngQ6k007APD7gmkHhgK35xN2vSppDmRznkuaDpwo6TdkTwYnl1jX3wI/ioib8uXh\nwOeB+dkUMnTho0nObgGuAH5CNrRzQ4nnMGsSh75tT+rmJ/mQj/62BRwXEc8VFpR0KPD3wlWbOe5v\nyHrstWRPDKWO/z8KHCPp5sjmOxEwLSLOa6Ds7pIOBL5AFvxmLc7DO7a9exD4j3x2RiQd1EC5ecBx\n+dj+p8gmVgM2TXW9CvgBcH0Tzn0B8Drwi3z5j8DxknrnddlVUt/8HEE2+dk04P6IqG3CecxK5tC3\ntqZ4TP+HjZS/lOxn6J5W9gPnlzZQ7g6y32V4huxTNE8AbxdsvwlY2YzfXf420FnSj/J9f0D2xvHT\nZL+UVDgl8C3AgWQzLJptFZ5l0ywnqVv+I9U9gSfJ3nB9Nd/2M2BRRFzbwL4r2Io/Zr+1j2/pcE/f\n7CP35r9X+ghwaUHgLwAOAG7czL5rgT/WfTmrpdR9OYvs1crGxsqbNcY9fTOzhLinb2aWEIe+mVlC\nHPpmZglx6JuZJcShb2aWkP8PKqb7mxrWhMoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1155cfd30>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "module = Module(radii=[5.151,4.9],focal=190.0)\n",
    "detector = Detector(width=8, \n",
    "                    height=8,\n",
    "                    normal = [0,0,1],\n",
    "                    center = [0,0,230],\n",
    "                    reso = [1024,1024])\n",
    "\n",
    "rays = source.generateRays(module.targetFront, 500)\n",
    "\n",
    "plt.figure()\n",
    "plt.hist([ray.energy for ray in rays], normed=True, label='generated rays')\n",
    "plt.xlabel('Energy [keV]')\n",
    "plt.title('Histogram generated rays')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of rays on Detector 28\n",
      "Time total: 194 seconds\n",
      "Time per ray (s): 0.14432989690721648\n"
     ]
    },
    {
     "data": {
      "image/png": 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HxDbARcBgoOkujssj4uymxhHRPyK2j4jtgf7A2OLrzZu1+UlE7BURG0fE7sB1FHo+sveL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\nulZnj6mfQTYet+7XF4/xz4EJwCHlLmR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      "text/plain": [
       "<matplotlib.figure.Figure at 0x115c9af98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tstart = datetime.now()\n",
    "\n",
    "# pass rays through module\n",
    "module.passRays(rays, robust=True)\n",
    "# catch rays at detector\n",
    "detector.catchRays(rays)\n",
    "\n",
    "\n",
    "rays_on_detector = len(detector.rays)\n",
    "print('Number of rays on Detector ' + str(rays_on_detector))\n",
    "print('Time total: ' + str((datetime.now() - tstart).seconds) + ' seconds')\n",
    "print('Time per ray (s): ' + str(rays_on_detector / float((datetime.now() - tstart).seconds)))\n",
    "\n",
    "drays = [ray for ray in rays if ray.des[2]==230.0]\n",
    "scatterHist(drays)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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OmZltYg59M7OMOPTNzDLi0Dczy4hD38wsIw59a1MkrU5ncKy9tYpfS5acXbKq\nZLhrmfPeLul/1Rl3gqTfSNombefH5S7PbENazff0zcr0QTrNQouR1DEiVrXAoo5q5tkl76P4qf9N\nJeNGA/dFxAfAwPQrXbON5j19axfSnvX3Jb2Y9rg/m8Z3Ttc6mJpOoDUqjR8r6QFJj1CcIGwLSTek\n8/D/Ou1lnyRpmKSHStbzBUlln6Ii7an/VtLX0vAZ6Zz/0yXdlH5I9nvgs+n01kjaluLXxA+32ANk\nljj0ra2p7e6ovZ1aMu2ddLKvG4FvpXH/RnE6g88BRwFXl5w18RDgrIg4Gvgy0BvYH/ifaRrAk0Bf\nSd3S8DjgtjJr3Q54hOKXqb+Q1Bc4leKkZAOB1cDpEbEaeBA4Jc03EngqneLarEW5e8famg1179Tu\ngU+jCHEozv8yUlLtm0AnYI90//GIqL0GwmHAAxGxBnhL0lNQnKNf0l3AGZJuo3gz+GqZtf43cFVE\n3JOGhwGDganpVAXbUJwCGoounquBn1F07dxZ5jrMmsShb+3JR+nvav752hbwlYh4pbShpIMoTptL\nSbuG3Eaxx/4hxRtDuf3/fwCOlXRvFOc7EXBHRHyngba7SRoAHEoR/GYtzt071t49BlyYziKKpEEN\ntHsO+Erq29+V4uR5wNrTBS8Evgfc3oR1/zuwBLghDT8BnCTpU6mWXST1SusIYCJwB/CbiPiwCesx\nK5tD39qaun36P2qk/RUUl018ScVF669ooN2vKM6l/leKb9H8EXi3ZPo9wIJmXDP4G0AnSVeleb9H\nceD4JeBxijOD1roPGEBxLn2zTcJn2TRLJG2XLqreBfgTxQHXt9K0/wL+3NDpsjf1BcHbwwXHrXXw\nnr7ZP/06XUvgWeCKksCfBhwAbOgqVouBJ2p/nNVSan+cRfFppa1eN9daEe/pm5llxHv6ZmYZceib\nmWXEoW9mlhGHvplZRhz6ZmYZ+f8Ypa48ATo1EAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11a22ccc0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.hist([ray.energy for ray in detector.rays], normed=True, label='rays on detector',color='r')\n",
    "plt.xlabel('Energy [keV]')\n",
    "plt.title('Histogram caught rays on detector')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "collapsed": true
   },
   "source": [
    "# F = 180"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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1OZprZmbNkScgqERa5MyzqbJHRMQQ4FjgG5KGldp5REyNiKqIqKqoqMjRXDMz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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x119e95470>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "module = Module(radii=[5.151,4.9],focal=180.0)\n",
    "detector = Detector(width=8, \n",
    "                    height=8,\n",
    "                    normal = [0,0,1],\n",
    "                    center = [0,0,230],\n",
    "                    reso = [1024,1024])\n",
    "\n",
    "rays = source.generateRays(module.targetFront, 500)\n",
    "\n",
    "plt.figure()\n",
    "plt.hist([ray.energy for ray in rays], normed=True, label='generated rays')\n",
    "plt.xlabel('Energy [keV]')\n",
    "plt.title('Histogram generated rays')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of rays on Detector 29\n",
      "Time total: 174 seconds\n",
      "Time per ray (s): 0.16666666666666666\n"
     ]
    },
    {
     "data": {
      "image/png": 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A1RExpTIVS5JUvfobEi4APjSQhfTSF4DzU0ozU0qPAicBy4Fju2j/OeCPKaX/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\n9P8BrWcF+Y3ALzoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11a1c2048>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tstart = datetime.now()\n",
    "\n",
    "# pass rays through module\n",
    "module.passRays(rays, robust=True)\n",
    "# catch rays at detector\n",
    "detector.catchRays(rays)\n",
    "\n",
    "\n",
    "rays_on_detector = len(detector.rays)\n",
    "print('Number of rays on Detector ' + str(rays_on_detector))\n",
    "print('Time total: ' + str((datetime.now() - tstart).seconds) + ' seconds')\n",
    "print('Time per ray (s): ' + str(rays_on_detector / float((datetime.now() - tstart).seconds)))\n",
    "\n",
    "drays = [ray for ray in rays if ray.des[2]==230.0]\n",
    "scatterHist(drays)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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HRO319Y8EpkTEBuAtSU9Bca14SXcBZ0m6jSL0v1Bhrb8EromIe9LwcGAIMDN9\nnX9HiksUQ9E1MxG4nqJL5s4K12HWJA53a4/+kf6u57+fwwJOiYhXShtKOpTicrCUtCvnNooj8LUU\nLwCV9s//FjhB0r1RXM9DwB0R8Y0ybfeRNBA4nCLgzVqcu2UsF48BF6erXCJpcJl2zwGnpL73vSku\n8AZsvOTtUuBy4PYmrPvbwArgxjT8BHCqpI+kWvaUtF9aRwCTgTuA6RGxtgnrMauYw93aqrp97v/R\nSPurKH52748qfpj8qjLtfkFxLfA/U3xq5XfAeyXT7wGWNOM3ZC8BOku6Js17OcUJ3D8Cj1Nc0bLW\nfcBAimu8m7UKXxXStjmSdk4/st0V+D3Fic+30rT/BP5Q7hLNauUfkW7t5du2w0futi16JF27/lng\nqpJgnw0MABr6taTlwBO1X2JqKbVfYqJ499Eefm/V2jgfuZuZZchH7mZmGXK4m5llyOFuZpYhh7uZ\nWYYc7mZmGfr/vEMU4uyXBYYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1152b4588>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.hist([ray.energy for ray in detector.rays], normed=True, label='rays on detector',color='r')\n",
    "plt.xlabel('Energy [keV]')\n",
    "plt.title('Histogram caught rays on detector')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# F = 170"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
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0yJlnS+seEREjgeOAr0s6qtTGI2J6RJRHRHm/fv1yVNfMzJojT0CoBvYsmB8A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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1153476d8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "module = Module(radii=[5.151,4.9],focal=170.0)\n",
    "detector = Detector(width=8, \n",
    "                    height=8,\n",
    "                    normal = [0,0,1],\n",
    "                    center = [0,0,230],\n",
    "                    reso = [1024,1024])\n",
    "\n",
    "rays = source.generateRays(module.targetFront, 500)\n",
    "\n",
    "plt.figure()\n",
    "plt.hist([ray.energy for ray in rays], normed=True, label='generated rays')\n",
    "plt.xlabel('Energy [keV]')\n",
    "plt.title('Histogram generated rays')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 18,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of rays on Detector 27\n",
      "Time total: 223 seconds\n",
      "Time per ray (s): 0.1210762331838565\n"
     ]
    },
    {
     "data": {
      "image/png": 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SREQESE7FPO7f4+h3dz9Kbyyl3Q3tOHD8gbw056Wwo0lIVCSIiAgJT3Dec+dx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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x115347a20>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tstart = datetime.now()\n",
    "\n",
    "# pass rays through module\n",
    "module.passRays(rays, robust=True)\n",
    "# catch rays at detector\n",
    "detector.catchRays(rays)\n",
    "\n",
    "\n",
    "rays_on_detector = len(detector.rays)\n",
    "print('Number of rays on Detector ' + str(rays_on_detector))\n",
    "print('Time total: ' + str((datetime.now() - tstart).seconds) + ' seconds')\n",
    "print('Time per ray (s): ' + str(rays_on_detector / float((datetime.now() - tstart).seconds)))\n",
    "\n",
    "drays = [ray for ray in rays if ray.des[2]==230.0]\n",
    "scatterHist(drays)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 19,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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TpgBwxx13cOSRR1Zcz9FHH829997LW2+9xZo1a7jvvvsA2G233ejXrx/Tpk0DsnB+5pln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\n3YUpuQAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11599f400>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.hist([ray.energy for ray in detector.rays], normed=True, label='rays on detector',color='r')\n",
    "plt.xlabel('Energy [keV]')\n",
    "plt.title('Histogram caught rays on detector')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# F = 160"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 20,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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34E+SXoqIGZ/ZeRYsxgDsueeeOZprZmYNkecMoRrYo2C9J7C0tjyS2gKdgbc3\nVzYiav6+CUyhlqGkiBgfEWURUdatW7cczTUzs4bIExBmAX0l9ZHUnuwicUVRngrgzLR8MjAtIiKl\nl6e7kPoAfYFnJHWStBOApE7AMcCLje+OmZk1VJ1DRhGxXtIFwCNAG+DmiJgn6XKgMiIqgJuAiZKq\nyM4MylPZeZLuBuYD64FvR8Qnkr4ATMmuO9MWuCMiHt4C/TMzs5zyXEMgIqYCU4vSLilYXgOMrKXs\nFcAVRWmLgAPq21gzM9ty/KSymZkBDghmZpY4IJiZGeCAYGZmiQOCmZkBDghmZpY4IJiZGeCAYGZm\niQOCmZkBDghmZpY4IJiZGeCAYGZmiQOCmZkBDghmZpY4IJiZGeCAYGZmiQOCmZkBDghmZpY4IJiZ\nGZAzIEgaJmmhpCpJF5bY3kHSXWn705J6F2y7KKUvlHRs3jrNzGzrqjMgSGoD3AAcB/QHRknqX5Rt\nNLAqIvYGfg1clcr2B8qBAcAw4D8ktclZp5mZbUV5zhAOAaoiYlFErAUmAcOL8gwHJqTlycAQSUrp\nkyLi44h4FahK9eWp08zMtqK2OfL0AJYUrFcDh9aWJyLWS3oX6JrS/1ZUtkdarqtOACSNAcak1dWS\nFuZocym7ASsbWLYl2Vb6Ae5LS+W+tDC6CmhcX3rlyZQnIKhEWuTMU1t6qTOT4jqzxIjxwPjNNTAP\nSZURUdbYeprbttIPcF9aKvelZdoafckzZFQN7FGw3hNYWlseSW2BzsDbmymbp04zM9uK8gSEWUBf\nSX0ktSe7SFxRlKcCODMtnwxMi4hI6eXpLqQ+QF/gmZx1mpnZVlTnkFG6JnAB8AjQBrg5IuZJuhyo\njIgK4CZgoqQqsjOD8lR2nqS7gfnAeuDbEfEJQKk6m757m2j0sFMLsa30A9yXlsp9aZm2eF+UfZE3\nM7PPOz+pbGZmgAOCmZkl23xA2JamyJC0WNILkuZKqmzu9tSHpJslvSnpxYK0XSX9SdLL6e8uzdnG\nvGrpy6WSXk/HZq6kf2rONuYhaQ9J0yUtkDRP0ndTeqs7LpvpS2s8Lh0lPSPpudSXy1J6nzQ10Mtp\nqqD2Tb7vbfkaQpoi4+/AULJbXWcBoyJifrM2rIEkLQbKIqLVPWgj6ShgNXBrROyb0n4BvB0RV6Zg\nvUtE/Kg525lHLX25FFgdEeOas231IWl3YPeIeFbSTsBsYARwFq3suGymL/+b1ndcBHSKiNWS2gEz\nge8C/wpDYxvyAAAFBUlEQVTcFxGTJP0n8FxE3NiU+97WzxA8RUYLEREzyO5AK1Q45ckEsv/ALV4t\nfWl1ImJZRDyblt8HFpDNJNDqjstm+tLqRGZ1Wm2XXgF8lWxqINhCx2VbDwilpt1olf9IkgAelTQ7\nTenR2n0hIpZB9h8a6N7M7WmsCyQ9n4aUWvwwS6E0Q/GBwNO08uNS1BdohcclTQI6F3gT+BPwCvBO\nRKxPWbbIZ9m2HhDyTLvRmhwREYPIZon9dhq6sJbhRuAfgIHAMuCXzduc/CTtCNwLfC8i3mvu9jRG\nib60yuMSEZ9ExECyWRwOAfYpla2p97utB4RtaoqMiFia/r4JTCH7h9KaLU9jvzVjwG82c3saLCKW\np//EG4Df0kqOTRqjvhe4PSLuS8mt8riU6ktrPS41IuId4HHgMKBLmhoIttBn2bYeELaZKTIkdUoX\ny5DUCTgGeHHzpVq8wilPzgTub8a2NErNB2hyIq3g2KSLlzcBCyLiVwWbWt1xqa0vrfS4dJPUJS1v\nD3yN7JrIdLKpgWALHZdt+i4jgHSb2TV8OkXGFc3cpAaRtBfZWQFkU47c0Zr6IulO4CtkU/guB34G\n/AG4G9gT+C9gZES0+Iu1tfTlK2TDEgEsBs6tGYdvqSQNBp4AXgA2pOQfk429t6rjspm+jKL1HZf9\nyS4atyH70n53RFyePgMmAbsCc4DTIuLjJt33th4QzMwsn219yMjMzHJyQDAzM8ABwczMEgcEMzMD\nHBDMzCxxQLBthqRPCma1nNtSZrctmKW2rGB9t5xlb5F0blHaCElTJW2f+rk2b31mm1PnT2iatSIf\npcf9m4yktgXzxzTG0Q2cpfZO4ELgNwVp5cCdEfERMDDNgmvWaD5DsG1e+kZ+maRn0zf1fim9U5rw\nbJakOZKGp/SzJN0j6QGyyQS3k/QfaW76B9O385MlDZE0pWA/QyXdV0szSrVre0kPSzonrZ+W5sGf\nK+k3afr2x4B+BVNJ7ED25OofmuwNMkscEGxbUjOEUvM6pWDbyjQx4I3AD1LaT4BpEXEwcDRwdZoW\nBOBw4MyI+Crwv4DewH7AN9M2gGnAPpK6pfX/A/w+Z1t3BB4ge+L8t5L2AU4hm8BwIPAJcGpEfALc\nRzavP8AJwPQ0xbNZk/KQkW1LNjdkVPPNfTbZBzxk80GdIKkmQHQkm64B4E8F0zUMBu5JE6S9IWk6\nZPPWS5oInCbp92SB4oycbb0f+EVE3J7WhwAHAbOyaXnYnk8nlbsTuBq4lmy46Nac+zCrFwcE+7yo\nmfPlEz79dy/gpIhYWJhR0qHAB4VJm6n392Tf9NeQBY281xueBI6TdEdk88cImBARF9WSd3dJBwBf\nJgsKZk3OQ0b2efYI8C9ppkwkHVhLvpnASelawhfIJrIDNk5JvhT4KXBLPfZ9CfAW8B9p/c/AyZK6\np7bsKqlX2keQTTY3AZgaEWvqsR+z3BwQbFtSfA3hyjry/5zs5wmfl/RiWi/lXrLf1niR7G6fp4F3\nC7bfDixpwG91fw/oKOkXqexPyS5iP0/2K1mFUzffCRxANtul2Rbh2U7NcpC0Y/rR867AM2QXf99I\n264H5kTETbWUXQyUNfC20zxt26L12+eHzxDM8nkw/cbtE8DPC4LBbGB/4LbNlF0B/LnmwbSmUvNg\nGtlZzoa68pvVxWcIZmYG+AzBzMwSBwQzMwMcEMzMLHFAMDMzwAHBzMyS/wYeE3uIauqy6QAAAABJ\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1135a8be0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "module = Module(radii=[5.151,4.9],focal=160.0)\n",
    "detector = Detector(width=8, \n",
    "                    height=8,\n",
    "                    normal = [0,0,1],\n",
    "                    center = [0,0,230],\n",
    "                    reso = [1024,1024])\n",
    "\n",
    "rays = source.generateRays(module.targetFront, 500)\n",
    "\n",
    "plt.figure()\n",
    "plt.hist([ray.energy for ray in rays], normed=True, label='generated rays')\n",
    "plt.xlabel('Energy [keV]')\n",
    "plt.title('Histogram generated rays')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 21,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of rays on Detector 18\n",
      "Time total: 208 seconds\n",
      "Time per ray (s): 0.08653846153846154\n"
     ]
    },
    {
     "data": {
      "image/png": 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bICklLvnDJez2b7sx7V+nMf1b09nxWzsyb+E8Wtta8y5PkqQ+MyQMgJQSp998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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1150c3b38>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tstart = datetime.now()\n",
    "\n",
    "# pass rays through module\n",
    "module.passRays(rays, robust=True)\n",
    "# catch rays at detector\n",
    "detector.catchRays(rays)\n",
    "\n",
    "\n",
    "rays_on_detector = len(detector.rays)\n",
    "print('Number of rays on Detector ' + str(rays_on_detector))\n",
    "print('Time total: ' + str((datetime.now() - tstart).seconds) + ' seconds')\n",
    "print('Time per ray (s): ' + str(rays_on_detector / float((datetime.now() - tstart).seconds)))\n",
    "\n",
    "drays = [ray for ray in rays if ray.des[2]==230.0]\n",
    "scatterHist(drays)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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Ct6T7U4GRkpTGT46I9yJiITAvLc/MzGqge4E2ewKLcsMNwMHNtYmI1ZLeBHql\n8U82mXfPpg8g6Vzg3DS4StLcQtWvb3fg9TbM15G0bR2k9q+kbbbMa7D51rezv4e6Vv0d531d1KY/\n/5u2znsXaVQk9KtVEQXbFJmXiLgeuL5ALc2SVB8RlU1ZRq119nVw/bXl+murs9RfZPdOA9A3N9wH\nWNxcG0ndgZ2B5QXnNTOzLaRI6M8ABkjqL2kbsgOzdU3a1AFnpfsnAw9FRKTx49Ove/oDA4A/tU/p\nZmbWWi3u3kn76CcC04BuwI0RMVvSpUB9RNQBNwC3SZpHtoU/Ps07W9IUYA6wGvhyRKzZTOuySbuH\nOojOvg6uv7Zcf211ivqVbZCbmVkZ+IxcM7MSceibmZVIlwj9lrqJ6Mgk3SjpNUn/Xeta2kJSX0kP\nS3pO0mxJX6t1Ta0hqYekP0l6JtX/b7WuqS0kdZP0tKTf1LqWtpD0oqQ/S5olqb7W9bSWpF0kTZX0\nfPpf+ESta2pOp9+nn7p1+AvwSbKfiM4ATouIOTUtrCBJRwCrgFsj4oBa19Nakj4MfDginpK0IzAT\nOLETPf8CekbEKklbA48DX4uIJ1uYtUORdB5QAXaKiONrXU9rSXoRqEREpzy5TNItwGMR8fP0K8ft\nI2JFreuqpits6RfpJqLDiohHyX7x1ClFxCsR8VS6vxJ4jipnXXdUkVmVBrdOt061JSSpD/Bp4Oe1\nrqWMJO0EHEH2K0Yi4v2OGvjQNUK/WjcRnSZ0upLUu+ow4I+1raR10q6RWcBrwAMR0anqB34MXACs\nrXUhmyCA/5Q0M3XL0pnsAywFbkq72H4uqWeti2pOVwj9Ql092OYlaQfgF8DXI+KtWtfTGhGxJiKG\nkp0xPkJSp9nNJul44LWImFnrWjbRoRFxEFlvvl9Ouz07i+7AQcC1ETEMeBvosMcWu0Lou6uHGkv7\nwn8B3BERv6x1PW2VvpI/QtYNeGdxKDAm7ROfDBwj6fbaltR6EbE4/X0NuJfO1RtvA9CQ+4Y4lexD\noEPqCqFfpJsI20zSgdAbgOci4ke1rqe1JPWWtEu6vx0wCni+tlUVFxEXRUSfiOhH9t5/KCLOqHFZ\nrSKpZ/oRAGm3yLFAp/k1W0S8CiyStF8aNZKsF4IOqUgvmx1ac91E1LiswiTdBRwF7C6pAbg4Im6o\nbVWtcihwJvDntF8c4F8i4rc1rKk1Pgzckn4FthUwJSI65c8eO7EPAvdm2w90B+6MiN/VtqRW+wpw\nR9rwXAD/D9wZAAAC/0lEQVScXeN6mtXpf7JpZmbFdYXdO2ZmVpBD38ysRBz6ZmYl4tA3MysRh76Z\nWYk49K1TkbQm9cTYeOsQZz7meoms5IZ3LzjvzZL+T5NxJ0r6raTt0nq+X3R5ZhvT6X+nb6XzTuoy\nod1I6h4Rq9thUUe3sZfIu8hO278uN248cFdEvAMMTWfcmm0yb+lbl5C2rP9N0lNpi/sf0vie6ZoF\nM1JnWGPT+AmS7pF0H1lHX1tJuib1qf+btJV9sqSRku7NPc4nJRXuaiJtqf9O0j+l4TNS//2zJF2X\nTgr7PfAPqZtqJG1Pdmbwr9rtCTJLHPrW2TTu7mi8nZqb9nrqtOta4Btp3LfIuib4GHA0cEWuB8RP\nAGdFxDHAZ4B+wIHA/07TAB4C9pfUOw2fDdxUsNYdgPvIzjD9maT9gVPJOhcbCqwBTo+INcAvgc+m\n+cYAD6euqs3alXfvWGezsd07jVvgM8lCHLJ+XMZIavwQ6AHsle4/EBGN1zI4DLgnItYCr0p6GLL+\n9iXdBpwh6SayD4N/LFjrr4HLI+KONDwSGA7MSF0ObEfWnTNku3iuAK4m27Vza8HHMGsVh751Je+l\nv2v4n/e2gJMiYm6+oaSDybrAJdeuOTeRbbG/S/bBUHT//x+A4yTdGVl/JwJuiYiLmmn7YUlDgEPI\ngt+s3Xn3jnV104CvpN5AkTSsmXaPAyelffsfJOsED1jX7e9i4NvAza147H8FlgHXpOEHgZMlfSDV\nspukvdNjBDAFuAX4bUS824rHMSvMoW+dTdN9+t9vof1lZJdAfFbZxecva6bdL8j6Rf9vsl/R/BF4\nMzf9DmBRG679+3Wgh6TL07zfJjtw/CzwAFkvn43uAoaQ9Ytvtlm4l02zRNIO6QLpvYA/kR1wfTVN\n+w/g6ea6vd7cF/bu7BcOt47DW/pm/+M36ZoAjwGX5QJ/JjAY2NgVqZYCDzaenNVeGk/OIvu20pmv\ngWsdhLf0zcxKxFv6ZmYl4tA3MysRh76ZWYk49M3MSsShb2ZWIv8f6rGRcAs1p5MAAAAASUVORK5C\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x115335ba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.hist([ray.energy for ray in detector.rays], normed=True, label='rays on detector',color='r')\n",
    "plt.xlabel('Energy [keV]')\n",
    "plt.title('Histogram caught rays on detector')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# F = 150"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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M8OHDGTFiBMcdd9ynLhgsXryYQYMGMWrUqCYFAzNrW/JcVC519bH4tKKxPBcCl0dEfdFF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\nhmJllAfmpwAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x115ba5c18>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "module = Module(radii=[5.151,4.9],focal=150.0)\n",
    "detector = Detector(width=8, \n",
    "                    height=8,\n",
    "                    normal = [0,0,1],\n",
    "                    center = [0,0,230],\n",
    "                    reso = [1024,1024])\n",
    "\n",
    "rays = source.generateRays(module.targetFront, 500)\n",
    "\n",
    "plt.figure()\n",
    "plt.hist([ray.energy for ray in rays], normed=True, label='generated rays')\n",
    "plt.xlabel('Energy [keV]')\n",
    "plt.title('Histogram generated rays')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of rays on Detector 11\n",
      "Time total: 192 seconds\n",
      "Time per ray (s): 0.057291666666666664\n"
     ]
    },
    {
     "data": {
      "image/png": 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bujfw4f/zYdZ3r2djz8ZN5nWnbu5/9n6+ev1Xc6pOktTMDAkN7v8++H9Z9coqelJP5vzu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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x115793438>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tstart = datetime.now()\n",
    "\n",
    "# pass rays through module\n",
    "module.passRays(rays, robust=True)\n",
    "# catch rays at detector\n",
    "detector.catchRays(rays)\n",
    "\n",
    "\n",
    "rays_on_detector = len(detector.rays)\n",
    "print('Number of rays on Detector ' + str(rays_on_detector))\n",
    "print('Time total: ' + str((datetime.now() - tstart).seconds) + ' seconds')\n",
    "print('Time per ray (s): ' + str(rays_on_detector / float((datetime.now() - tstart).seconds)))\n",
    "\n",
    "drays = [ray for ray in rays if ray.des[2]==230.0]\n",
    "scatterHist(drays)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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FzgROjYi5VS2sjSQdCqwGbo+I/atdT3tI+gjwkYh4VtL2wCzghE783AjoGRGr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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1158c3cf8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.hist([ray.energy for ray in detector.rays], normed=True, label='rays on detector',color='r')\n",
    "plt.xlabel('Energy [keV]')\n",
    "plt.title('Histogram caught rays on detector')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# F = 140"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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dl8GDB/P888/X29czzjiDESNGUF5ezsCBA+nXr9+Wbe3bt+eEE06ga9euW9r76KOPcs01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\nTkSuQmCC\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11a1fd828>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "module = Module(radii=[5.151,4.9],focal=140.0)\n",
    "detector = Detector(width=8, \n",
    "                    height=8,\n",
    "                    normal = [0,0,1],\n",
    "                    center = [0,0,230],\n",
    "                    reso = [1024,1024])\n",
    "\n",
    "rays = source.generateRays(module.targetFront, 500)\n",
    "\n",
    "plt.figure()\n",
    "plt.hist([ray.energy for ray in rays], normed=True, label='generated rays')\n",
    "plt.xlabel('Energy [keV]')\n",
    "plt.title('Histogram generated rays')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of rays on Detector 16\n",
      "Time total: 196 seconds\n",
      "Time per ray (s): 0.08163265306122448\n"
     ]
    },
    {
     "data": {
      "image/png": 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gISGRfcnNZkpXRZQkSQU30JBwCzAnIjYGgvLvc4Bbh6IwSZKUr4GeAvlVSkHh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\nkiQpkyFBkiRl+v8B4RLlw/snqhoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x114bdb240>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tstart = datetime.now()\n",
    "\n",
    "# pass rays through module\n",
    "module.passRays(rays, robust=True)\n",
    "# catch rays at detector\n",
    "detector.catchRays(rays)\n",
    "\n",
    "\n",
    "rays_on_detector = len(detector.rays)\n",
    "print('Number of rays on Detector ' + str(rays_on_detector))\n",
    "print('Time total: ' + str((datetime.now() - tstart).seconds) + ' seconds')\n",
    "print('Time per ray (s): ' + str(rays_on_detector / float((datetime.now() - tstart).seconds)))\n",
    "\n",
    "drays = [ray for ray in rays if ray.des[2]==230.0]\n",
    "scatterHist(drays)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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FF7bY5hFHHMHkyZMBuOuuuzjyyCNL13P00UfzwAMP8P7777NmzRoeeughAHbffXd69+7N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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x115c536d8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.hist([ray.energy for ray in detector.rays], normed=True, label='rays on detector',color='r')\n",
    "plt.xlabel('Energy [keV]')\n",
    "plt.title('Histogram caught rays on detector')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# F = 130"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 29,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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E1AJrgN4NlA3gUUkLJE2pb+eSpkiqlFRZU1OTo7lmZtYUeQKCSqRFzjybK3t4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\nDghmZpY4IJiZGeCAYGZmyf8H+T9mQjm2zAoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x115a57f60>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "module = Module(radii=[5.151,4.9],focal=130.0)\n",
    "detector = Detector(width=8, \n",
    "                    height=8,\n",
    "                    normal = [0,0,1],\n",
    "                    center = [0,0,230],\n",
    "                    reso = [1024,1024])\n",
    "\n",
    "rays = source.generateRays(module.targetFront, 500)\n",
    "\n",
    "plt.figure()\n",
    "plt.hist([ray.energy for ray in rays], normed=True, label='generated rays')\n",
    "plt.xlabel('Energy [keV]')\n",
    "plt.title('Histogram generated rays')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 30,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of rays on Detector 15\n",
      "Time total: 176 seconds\n",
      "Time per ray (s): 0.08522727272727272\n"
     ]
    },
    {
     "data": {
      "image/png": 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dzOz/M5uLbrmIdR3rio4mSWowkVIqOkPdREQr0N7e3k5ra2uhWV569SWOvuZo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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1132d04a8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tstart = datetime.now()\n",
    "\n",
    "# pass rays through module\n",
    "module.passRays(rays, robust=True)\n",
    "# catch rays at detector\n",
    "detector.catchRays(rays)\n",
    "\n",
    "\n",
    "rays_on_detector = len(detector.rays)\n",
    "print('Number of rays on Detector ' + str(rays_on_detector))\n",
    "print('Time total: ' + str((datetime.now() - tstart).seconds) + ' seconds')\n",
    "print('Time per ray (s): ' + str(rays_on_detector / float((datetime.now() - tstart).seconds)))\n",
    "\n",
    "drays = [ray for ray in rays if ray.des[2]==230.0]\n",
    "scatterHist(drays)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 31,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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IRNSPm384cE9EbARel/Q4ZGOxS7oNOF3SzWSh/4Uya/0VcGVE3JFPjwSGAbOy\nYXXYkWwIYMi6ZiYD15B1ydxa5m2YtYjD3Tqi9/K/G/if57CAEyPixWJDSZ8E3inOamK7N5Mdga8j\newEot3/+d8Cxku6MbDwPAb+IiG820nYfSYOBw8gC3qzi3C1jqXgY+FI+AiWShjbS7mngxLzvfW/g\nqPoF+RCvy4CLgVtacNuXACuB6/LpR4GTJH0or2VPSfvntxHAVOAXwIyIWNeC2zErm8Pd2quGfe7/\n1Uz7y8lOa/e8shOOX95Iu1+SnS/gz2TfWvk98HZh+R3A0lac3/UrQFdJV+brXkz2Ae7zwCNkI0bW\nuwsYTDYeulmb8KiQts2RtHN+EuvuZMO5joiI1/NlPwH+GBE3NrLuS7ThSZM7+kmZrf3wkbttix7M\nz3P6FHB5IdhnA4OAps4stAJ4tP5HTJVS/yMmsncfqZ+b1D4APnI3M0uQj9zNzBLkcDczS5DD3cws\nQQ53M7MEOdzNzBL0/wFj8+Un6sqecAAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1150256a0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.hist([ray.energy for ray in detector.rays], normed=True, label='rays on detector',color='r')\n",
    "plt.xlabel('Energy [keV]')\n",
    "plt.title('Histogram caught rays on detector')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# F = 120"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 32,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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A6lSfmZm1MXkCwm7AioL1mpRWMk9E1AHvAn0bKRvAw5IWSprW0M4lTZNUJamq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\nYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11473fc88>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "module = Module(radii=[5.151,4.9],focal=120.0)\n",
    "detector = Detector(width=8, \n",
    "                    height=8,\n",
    "                    normal = [0,0,1],\n",
    "                    center = [0,0,230],\n",
    "                    reso = [1024,1024])\n",
    "\n",
    "rays = source.generateRays(module.targetFront, 500)\n",
    "\n",
    "plt.figure()\n",
    "plt.hist([ray.energy for ray in rays], normed=True, label='generated rays')\n",
    "plt.xlabel('Energy [keV]')\n",
    "plt.title('Histogram generated rays')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 33,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of rays on Detector 18\n",
      "Time total: 164 seconds\n",
      "Time per ray (s): 0.10975609756097561\n"
     ]
    },
    {
     "data": {
      "image/png": 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X8LuNHzueOdvNyTqGJElVUeh9+JIkFYWFL0lSAVj4kiQVgIUvSVIBWPiSJBWA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\nRK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x114e0bb00>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tstart = datetime.now()\n",
    "\n",
    "# pass rays through module\n",
    "module.passRays(rays, robust=True)\n",
    "# catch rays at detector\n",
    "detector.catchRays(rays)\n",
    "\n",
    "\n",
    "rays_on_detector = len(detector.rays)\n",
    "print('Number of rays on Detector ' + str(rays_on_detector))\n",
    "print('Time total: ' + str((datetime.now() - tstart).seconds) + ' seconds')\n",
    "print('Time per ray (s): ' + str(rays_on_detector / float((datetime.now() - tstart).seconds)))\n",
    "\n",
    "drays = [ray for ray in rays if ray.des[2]==230.0]\n",
    "scatterHist(drays)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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LvP766znttNO46qqr6N27N7feemvJ9ey7776MGjWKffbZh/79+3PwwQevnXbnxImcefnl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\nuJuZJcjhbmaWoP8PLeV1oNF4UAYAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x115487e80>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.hist([ray.energy for ray in detector.rays], normed=True, label='rays on detector',color='r')\n",
    "plt.xlabel('Energy [keV]')\n",
    "plt.title('Histogram caught rays on detector')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# F = 110"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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7H8Q/jTqCAfsOZHjle9OqnXzqWXz1jHHs2f/DXHfrXdxwww1MmDCBd9IRxKWXXsrHPvYx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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11a8b3f28>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "module = Module(radii=[5.151,4.9],focal=110.0)\n",
    "detector = Detector(width=8, \n",
    "                    height=8,\n",
    "                    normal = [0,0,1],\n",
    "                    center = [0,0,230],\n",
    "                    reso = [1024,1024])\n",
    "\n",
    "rays = source.generateRays(module.targetFront, 500)\n",
    "\n",
    "plt.figure()\n",
    "plt.hist([ray.energy for ray in rays], normed=True, label='generated rays')\n",
    "plt.xlabel('Energy [keV]')\n",
    "plt.title('Histogram generated rays')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of rays on Detector 5\n",
      "Time total: 152 seconds\n",
      "Time per ray (s): 0.03289473684210526\n"
     ]
    },
    {
     "data": {
      "image/png": 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mwgL+9OUaGkPzbY8DgMtG5mXmcPPykqpydYkFzZ8+D2eIz9fuY+FrWiJiD+A0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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1135b06d8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tstart = datetime.now()\n",
    "\n",
    "# pass rays through module\n",
    "module.passRays(rays, robust=True)\n",
    "# catch rays at detector\n",
    "detector.catchRays(rays)\n",
    "\n",
    "\n",
    "rays_on_detector = len(detector.rays)\n",
    "print('Number of rays on Detector ' + str(rays_on_detector))\n",
    "print('Time total: ' + str((datetime.now() - tstart).seconds) + ' seconds')\n",
    "print('Time per ray (s): ' + str(rays_on_detector / float((datetime.now() - tstart).seconds)))\n",
    "\n",
    "drays = [ray for ray in rays if ray.des[2]==230.0]\n",
    "scatterHist(drays)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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yzTrUscrSp452rCTVSdo5vb4tMAJ4qahZh5qyJEufit7bGUXy/knNZJkVMvck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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11ab4d400>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.hist([ray.energy for ray in detector.rays], normed=True, label='rays on detector',color='r')\n",
    "plt.xlabel('Energy [keV]')\n",
    "plt.title('Histogram caught rays on detector')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# F = 100"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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fzCxHHPpmZjni0Dczy5GSQl/S0ZKek7Rc0qR61neSdGta/4SkiqL1e0mqkXROy1TbzMya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\n8v8BHkD7xIfdVgcAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1159a1be0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "module = Module(radii=[5.151,4.9],focal=100.0)\n",
    "detector = Detector(width=8, \n",
    "                    height=8,\n",
    "                    normal = [0,0,1],\n",
    "                    center = [0,0,230],\n",
    "                    reso = [1024,1024])\n",
    "\n",
    "rays = source.generateRays(module.targetFront, 500)\n",
    "\n",
    "plt.figure()\n",
    "plt.hist([ray.energy for ray in rays], normed=True, label='generated rays')\n",
    "plt.xlabel('Energy [keV]')\n",
    "plt.title('Histogram generated rays')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of rays on Detector 0\n",
      "Time total: 169 seconds\n",
      "Time per ray (s): 0.0\n"
     ]
    },
    {
     "data": {
      "image/png": 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+StIk8tw5Yebr6vQAco5t/BC4JDPvyczPAh8BfmeO37cRWDO0nDBP/ZSkw5nnzgnT9TPx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\nZYhLklSUIS5JUlGGuCRJRf1/OI2hvcQE3/oAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11aaf0f60>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tstart = datetime.now()\n",
    "\n",
    "# pass rays through module\n",
    "module.passRays(rays, robust=True)\n",
    "# catch rays at detector\n",
    "detector.catchRays(rays)\n",
    "\n",
    "\n",
    "rays_on_detector = len(detector.rays)\n",
    "print('Number of rays on Detector ' + str(rays_on_detector))\n",
    "print('Time total: ' + str((datetime.now() - tstart).seconds) + ' seconds')\n",
    "print('Time per ray (s): ' + str(rays_on_detector / float((datetime.now() - tstart).seconds)))\n",
    "\n",
    "drays = [ray for ray in rays if ray.des[2]==230.0]\n",
    "scatterHist(drays)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "/anaconda/lib/python3.6/site-packages/matplotlib/axes/_axes.py:6198: RuntimeWarning: invalid value encountered in true_divide\n",
      "  m = (m.astype(float) / db) / m.sum()\n"
     ]
    },
    {
     "data": {
      "image/png": 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tfuyI/jZocw3t/ORz1QvoSDeyY6szgYXpvv7Frwb4Qa7dpWQnIBcBl5RYT3sK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\nMNcFKxAXn44AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11a298898>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.hist([ray.energy for ray in detector.rays], normed=True, label='rays on detector',color='r')\n",
    "plt.xlabel('Energy [keV]')\n",
    "plt.title('Histogram caught rays on detector')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Now increasing the Focal Lenght"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# F = 250"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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IEcDRwDckHV5q5xExNSIqI6Kyb9++OZprZmbNkScg1AB7FKz3B1Y1lkdSZ6AX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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11ab115f8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "module = Module(radii=[5.151,4.9],focal=250.0)\n",
    "detector = Detector(width=8, \n",
    "                    height=8,\n",
    "                    normal = [0,0,1],\n",
    "                    center = [0,0,230],\n",
    "                    reso = [1024,1024])\n",
    "\n",
    "rays = source.generateRays(module.targetFront, 500)\n",
    "\n",
    "plt.figure()\n",
    "plt.hist([ray.energy for ray in rays], normed=True, label='generated rays')\n",
    "plt.xlabel('Energy [keV]')\n",
    "plt.title('Histogram generated rays')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of rays on Detector 32\n",
      "Time total: 196 seconds\n",
      "Time per ray (s): 0.16326530612244897\n"
     ]
    },
    {
     "data": {
      "image/png": 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NNw4ARALzziJU1Kv0nXM1kmrq7rPdHwBaxryzOBX7Ej4AAFDElvDNrKukgfUG7WxmQyWt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\nZek77AgWFjPTzHE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BnHM5jlK4zGwHSZVh5wCAAtPXOfdJUw+a2U6SPg4sDVqr2b9bQ74t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\nAIAH/j/k/uXhHg3U5AAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11ab1ffd0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tstart = datetime.now()\n",
    "\n",
    "# pass rays through module\n",
    "module.passRays(rays, robust=True)\n",
    "# catch rays at detector\n",
    "detector.catchRays(rays)\n",
    "\n",
    "\n",
    "rays_on_detector = len(detector.rays)\n",
    "print('Number of rays on Detector ' + str(rays_on_detector))\n",
    "print('Time total: ' + str((datetime.now() - tstart).seconds) + ' seconds')\n",
    "print('Time per ray (s): ' + str(rays_on_detector / float((datetime.now() - tstart).seconds)))\n",
    "\n",
    "drays = [ray for ray in rays if ray.des[2]==230.0]\n",
    "scatterHist(drays)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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gSZ3Se3AEbfyAdzl32bTWYThwFvBnSbNSv3+NiN9WsCZr2y4G7k731FoInFPh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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11a831ba8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.hist([ray.energy for ray in detector.rays], normed=True, label='rays on detector',color='r')\n",
    "plt.xlabel('Energy [keV]')\n",
    "plt.title('Histogram caught rays on detector')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# F = 300"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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ExS1cpSaRtCvZ1T1kQ2Tc0pbaIulW4KtkQ92uBM4F7gFuB3YB/g6MiYhWf4O0\nnrZ8laz7IIClwMk1feKtmaShwKPAX4G1afGPyPrC29S52UBbxtHGzo2kPclu1LYjuwC/PSIuSDkw\nDdgemA8cGxEfNdtxt4TQNzOzfLaE7h0zM8vJoW9mViAOfTOzAnHom5kViEPfzKxAHPrWpkj6pGQk\nxQWtZVTVktFRy0vmd8i57fWSTq61bLSkByR1Se38OO/+zDakwa9LNGtl/pk+tt5sJLUvGetkYxzc\nxNFRbwUmAb8uWTYWuDUi/gkMTqOvmm00X+nbFiFdWZ8v6el0xT0gLe+aBuCaK2m+pFFp+XhJd0i6\nl2yAu60k/TKNa35fuso+WtJwSXeXHGeEpLvqqUZd9eoi6UFJJ6X5Y9MY6gsk/ToNDf5HYEDJkAhb\nk306855me4HMEoe+tTU13R01P98qWfdmGqzuV8AZadmPgZkRsS9wMHBZGuIC4EDghIj4GvA/gTLg\nS8B30jqAmcDuknql+f8N/DZnXbsB95J9svo3knYHvkU2qN5g4BPgmIj4BLiLbEx4gCOBWWnoYLNm\n5e4da2s21L1TcwU+jyzEIRu/6EhJNX8EOpMNOwDwh5JhB4YCd6QBu16XNAuyMc8l3QgcK+m3ZH8M\njs9Z198BP42Im9P8cGAfYG42hAxd+HSQs1uBy4Cfk3Xt3JDzGGaN4tC3LUnN+CSf8OnvtoCjIuKF\n0oKS9gf+UbpoA/v9LdkVezXZH4a8/f+PAYdJuiWy8U4ETI2Is+opu6OkvYAvkwW/WbNz945t6R4C\n/i2NzoikvespNwc4KvXtf45scDVg3XDXy4GfANc34tjnAG8Bv0zzfwKOltQ71WV7SX3TMYJs8LOp\nwAMRUd2I45jl5tC3tqZ2n/4lDZS/kOxr6J5V9iXnF9ZT7k6y72Z4juwpmieB90rW3wwsa8J3L38f\n6Czpp2nbn5DdOH6W7JuSSocEvhXYi2yERbNNwqNsmiWSuqUvqe4JPEV2w/X1tO5qYH5EXFvPtkvZ\nhF9ov6n3b8XhK32zT92Xvq/0UeDCksCfB+wJ3LSBbVcBf6r5cFZzqflwFtm7lbUNlTdriK/0zcwK\nxFf6ZmYF4tA3MysQh76ZWYE49M3MCsShb2ZWIP8Fd9mI2wDFAcoAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11a73c940>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "module = Module(radii=[5.151,4.9],focal=300.0)\n",
    "detector = Detector(width=8, \n",
    "                    height=8,\n",
    "                    normal = [0,0,1],\n",
    "                    center = [0,0,230],\n",
    "                    reso = [1024,1024])\n",
    "\n",
    "rays = source.generateRays(module.targetFront, 500)\n",
    "\n",
    "plt.figure()\n",
    "plt.hist([ray.energy for ray in rays], normed=True, label='generated rays')\n",
    "plt.xlabel('Energy [keV]')\n",
    "plt.title('Histogram generated rays')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of rays on Detector 29\n",
      "Time total: 188 seconds\n",
      "Time per ray (s): 0.15425531914893617\n"
     ]
    },
    {
     "data": {
      "image/png": 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KW3HQJgfxkY0+0ueL50hSnrhkU2Hss8E+PH/y8/zhuT8wbdY0xo0Yx94b7M3IYfk7zUiS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\nf595BvbZp3KfJGlA5KbwU0p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      "text/plain": [
       "<matplotlib.figure.Figure at 0x11a65f630>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tstart = datetime.now()\n",
    "\n",
    "# pass rays through module\n",
    "module.passRays(rays, robust=True)\n",
    "# catch rays at detector\n",
    "detector.catchRays(rays)\n",
    "\n",
    "\n",
    "rays_on_detector = len(detector.rays)\n",
    "print('Number of rays on Detector ' + str(rays_on_detector))\n",
    "print('Time total: ' + str((datetime.now() - tstart).seconds) + ' seconds')\n",
    "print('Time per ray (s): ' + str(rays_on_detector / float((datetime.now() - tstart).seconds)))\n",
    "\n",
    "drays = [ray for ray in rays if ray.des[2]==230.0]\n",
    "scatterHist(drays)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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vaRNJV6fruf867WUfJ2mEpHtKy/m8pIovl5H21H8n6V/S8KmS/pT23q+V1An4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\nAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1151923c8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.hist([ray.energy for ray in detector.rays], normed=True, label='rays on detector',color='r')\n",
    "plt.xlabel('Energy [keV]')\n",
    "plt.title('Histogram caught rays on detector')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# F = 400"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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1dO/enffff58jjjiCKVOmMGzYsFZt09a2fv16hg0bxp133rnh2kRepY6hpHkRUVmubJ4z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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x114bd89b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "module = Module(radii=[5.151,4.9],focal=400.0)\n",
    "detector = Detector(width=8, \n",
    "                    height=8,\n",
    "                    normal = [0,0,1],\n",
    "                    center = [0,0,230],\n",
    "                    reso = [1024,1024])\n",
    "\n",
    "rays = source.generateRays(module.targetFront, 500)\n",
    "\n",
    "plt.figure()\n",
    "plt.hist([ray.energy for ray in rays], normed=True, label='generated rays')\n",
    "plt.xlabel('Energy [keV]')\n",
    "plt.title('Histogram generated rays')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 48,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of rays on Detector 50\n",
      "Time total: 183 seconds\n",
      "Time per ray (s): 0.273224043715847\n"
     ]
    },
    {
     "data": {
      "image/png": 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dcUbqFn40CmeemfdXW5QCEItBZaXfVUieUOCLZFqHDnD11bU/VlQEHTvCn/+c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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x110637f98>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tstart = datetime.now()\n",
    "\n",
    "# pass rays through module\n",
    "module.passRays(rays, robust=True)\n",
    "# catch rays at detector\n",
    "detector.catchRays(rays)\n",
    "\n",
    "\n",
    "rays_on_detector = len(detector.rays)\n",
    "print('Number of rays on Detector ' + str(rays_on_detector))\n",
    "print('Time total: ' + str((datetime.now() - tstart).seconds) + ' seconds')\n",
    "print('Time per ray (s): ' + str(rays_on_detector / float((datetime.now() - tstart).seconds)))\n",
    "\n",
    "drays = [ray for ray in rays if ray.des[2]==230.0]\n",
    "scatterHist(drays)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 49,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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ffz2PPfYY/fr1Y9CgQcyePZuuXbty9NFHc9hhhzFu3DhGjBhB//79GTBgACeddBLXXHMN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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11536cf60>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.hist([ray.energy for ray in detector.rays], normed=True, label='rays on detector',color='r')\n",
    "plt.xlabel('Energy [keV]')\n",
    "plt.title('Histogram caught rays on detector')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# F = 500"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 50,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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V5fLlucuo1CBmcRRpLM8lwFURUdeMOrPEiGkRURkRlX37ln0CnFmjJk+ezPDhwxkxYgQn\nn3zyThcMli1bxqBBgxg1alSTgoHtPPIMGdUA+xas9wfWNpKnRlJnoBfwKtlZwimSfgz0BjZJqgcW\n5ajTrEXdcsstrd2EVjV06FBWrlzZ2s2wNixPQFgIDJY0EFgDTAC+WJRnDnAm8ChwCjAvsrGoTzVk\nkHQx2ZDRz1PQKFendTAR4YnS2qFyw8rWcZQdMoqIjcD5wH3AcmBWRCyVdKmkk1K264E+kqqBbwBT\nmlNn87thbV337t155ZVX/OHSzjQ8D6F79+6t3RTbAXL9DiEi5gJzi9IuKliuB8YXlyvKf3G5Oq3j\n6t+/PzU1NdTW1rZ2U6yJGp6YZh2ff6lsO0SXLl38xC2zNs5zGZmZGeCAYGZmiQOCmZkBDghmZpY4\nIJiZGeCAYGZmiQOCmZkBDghmZpY4IJiZGeCAYGZmiQOCmZkBDghmZpZ4crsOzI84NLOm8BmCmZkB\nDghmZpbkCgiSxkhaIala0oeehiapm6Tb0vbHJFWk9MMlLUmvJyV9vqDMKklPp21VLdUhMzNrnrLX\nECR1Aq4FRgM1wEJJcyJiWUG2ScBrETFI0gTgCuALwDNAZURslLQ38KSku9IjNAGOjYgNLdkh27n5\nuolZ8+U5QzgcqI6IlRHxHjATGFuUZywwPS3PBkZJUkS8U/Dh3x3wA3XNzNqoPAFhH2B1wXpNSiuZ\nJwWAN4A+AJKOkLQUeBr4SkGACOB+SYskTW5s55ImS6qSVOXn8ZqZbT95bjtVibTib/qN5omIx4Bh\nkg4Apkv6fUTUA0dHxFpJ/YA/SHo2IhZ8qJKIacA0gMrKSp9hmBVprWEy63jynCHUAPsWrPcH1jaW\nR1JnoBfwamGGiFgOvA0cmNbXpr8vA3eSDU2ZmVkryRMQFgKDJQ2U1BWYAMwpyjMHODMtnwLMi4hI\nZToDSBoA/COwSlIPSbul9B7AcWQXoM3MrJWUHTJKdwidD9wHdAJuiIilki4FqiJiDnA9MENSNdmZ\nwYRUfCQwRdL7wCbgvIjYIGl/4E5JDW24JSLubenOmZlZfrmmroiIucDcorSLCpbrgfElys0AZpRI\nXwkc3NTGmpnZ9uNfKpuZGeCAYGZmyU4z26lvzTMz2zqfIZiZGeCAYGZmiQOCmZkBDghmZpY4IJiZ\nGeCAYGZmiQOCmZkBDghmZpY4IJiZGeCAYGZmiQOCmZkBDghmZpbsNJPbmVnH0JoTVa760edabd87\nQq4zBEljJK2QVC1pSont3STdlrY/JqkipR8uaUl6PSnp83nrNDOzHatsQJDUCbgWOAEYCkyUNLQo\n2yTgtYgYBFwFXJHSnwEqI2I4MAb4haTOOes0M7MdKM8ZwuFAdUSsjIj3gJnA2KI8Y4HpaXk2MEqS\nIuKdiNiY0rsD0YQ6zcxsB8oTEPYBVhes16S0knlSAHgD6AMg6QhJS4Gnga+k7XnqJJWfLKlKUlVt\nbW2O5pqZWXPkCQgqkRZ580TEYxExDDgMuEBS95x1kspPi4jKiKjs27dvjuaamVlz5AkINcC+Bev9\ngbWN5ZHUGegFvFqYISKWA28DB+as08zMdqA8t50uBAZLGgisASYAXyzKMwc4E3gUOAWYFxGRyqyO\niI2SBgD/CKwCXs9Rp1m74Wd2W0dQNiCkD/PzgfuATsANEbFU0qVAVUTMAa4HZkiqJjszmJCKjwSm\nSHof2AScFxEbAErV2cJ9MzOzJsj1w7SImAvMLUq7qGC5HhhfotwMYEbeOs3MrPV46gozMwMcEMzM\nLHFAMDMzwAHBzMwSz3ZqZpZTa91evKNmWfUZgpmZAQ4IZmaWOCCYmRnggGBmZokDgpmZAQ4IZmaW\nOCCYmRnggGBmZokDgpmZAQ4IZmaWOCCYmRmQMyBIGiNphaRqSVNKbO8m6ba0/TFJFSl9tKRFkp5O\nfz9TUObBVOeS9OrXUp0yM7OmKzu5naROwLXAaKAGWChpTkQsK8g2CXgtIgZJmgBcAXwB2ACcGBFr\nJR1I9sjMfQrKnRoRVS3UFzMz2wZ5zhAOB6ojYmVEvAfMBMYW5RkLTE/Ls4FRkhQRiyNibUpfCnSX\n1K0lGm5mZi0rT0DYB1hdsF7Dlt/yt8gTERuBN4A+RXlOBhZHxLsFab9Kw0UXSlKpnUuaLKlKUlVt\nbW2O5pqZWXPkeR5CqQ/qaEoeScPIhpGOK9h+akSskbQb8BvgdOCmD1USMQ2YBlBZWVm8X2uDWmvO\neDPbNnnOEGqAfQvW+wNrG8sjqTPQC3g1rfcH7gTOiIjnGwpExJr09y3gFrKhKTMzayV5AsJCYLCk\ngZK6AhOAOUV55gBnpuVTgHkREZJ6A/cAF0TEIw2ZJXWWtFda7gL8M/DMtnXFzMy2RdmAkK4JnE92\nh9ByYFZELJV0qaSTUrbrgT6SqoFvAA23pp4PDAIuLLq9tBtwn6SngCXAGuCXLdkxMzNrmlzPVI6I\nucDcorSLCpbrgfElyl0GXNZItYfmb6aZmW1v/qWymZkBDghmZpY4IJiZGeCAYGZmiQOCmZkBDghm\nZpY4IJiZGeCAYGZmiQOCmZkBDghmZpY4IJiZGeCAYGZmiQOCmZkBDghmZpY4IJiZGeCAYGZmSa6A\nIGmMpBWSqiVNKbG9m6Tb0vbHJFWk9NGSFkl6Ov39TEGZQ1N6taRrJKmlOmVmZk1XNiBI6gRcC5wA\nDAUmShpalG0S8FpEDAKuAq5I6RuAEyPiE2TPXJ5RUOY6YDIwOL3GbEM/zMxsG+U5QzgcqI6IlRHx\nHjATGFuUZywwPS3PBkZJUkQsjoi1KX0p0D2dTewN7B4Rj0ZEADcB47a5N2Zm1mx5AsI+wOqC9ZqU\nVjJPRGwE3gD6FOU5GVgcEe+m/DVl6gRA0mRJVZKqamtrczTXzMyaI09AKDW2H03JI2kY2TDSOU2o\nM0uMmBYRlRFR2bdv3xzNNTOz5sgTEGqAfQvW+wNrG8sjqTPQC3g1rfcH7gTOiIjnC/L3L1OnmZnt\nQHkCwkJgsKSBkroCE4A5RXnmkF00BjgFmBcRIak3cA9wQUQ80pA5ItYBb0k6Mt1ddAbwu23si5mZ\nbYOyASFdEzgfuA9YDsyKiKWSLpV0Usp2PdBHUjXwDaDh1tTzgUHAhZKWpFe/tO1c4D+BauB54Pct\n1SkzM2u6znkyRcRcYG5R2kUFy/XA+BLlLgMua6TOKuDApjTWzMy2H/9S2czMAAcEMzNLHBDMzAxw\nQDAzs8QBwczMAAcEMzNLHBDMzAxwQDAzs8QBwczMAAcEMzNLHBDMzAxwQDAzs8QBwczMAAcEMzNL\nHBDMzAxwQDAzsyRXQJA0RtIKSdWSppTY3k3SbWn7Y5IqUnofSfMl1Un6eVGZB1OdxU9SMzOzVlD2\niWmSOgHXAqOBGmChpDkRsawg2yTgtYgYJGkCcAXwBaAeuJDsyWilno52anpympmZtbI8ZwiHA9UR\nsTIi3gNmAmOL8owFpqfl2cAoSYqItyPiYbLAYGZmbViegLAPsLpgvSallcwTERuBN4A+Oer+VRou\nulCSSmWQNFlSlaSq2traHFWamVlz5AkIpT6ooxl5ip0aEZ8APpVep5fKFBHTIqIyIir79u1btrFm\nZtY8eQJCDbBvwXp/YG1jeSR1BnoBr26t0ohYk/6+BdxCNjRlZmatJE9AWAgMljRQUldgAjCnKM8c\n4My0fAowLyIaPUOQ1FnSXmm5C/DPwDNNbbyZmbWcsncZRcRGSecD9wGdgBsiYqmkS4GqiJgDXA/M\nkFRNdmYwoaG8pFXA7kBXSeOA44AXgftSMOgEPAD8skV7ZmZmTVI2IABExFxgblHaRQXL9cD4RspW\nNFLtofmaaGZmO4J/qWxmZoADgpmZJQ4IZmYGOCCYmVnigGBmZoADgpmZJQ4IZmYGOCCYmVnigGBm\nZoADgpmZJQ4IZmYGOCCYmVnigGBmZoADgpmZJQ4IZmYGOCCYmVmSKyBIGiNphaRqSVNKbO8m6ba0\n/TFJFSm9j6T5kuok/byozKGSnk5lrpGkluiQmZk1T9mAIKkTcC1wAjAUmChpaFG2ScBrETEIuAq4\nIqXXAxcC3ypR9XXAZGBweo1pTgfMzKxl5DlDOByojoiVEfEeMBMYW5RnLDA9Lc8GRklSRLwdEQ+T\nBYbNJO0N7B4Rj0ZEADcB47alI2Zmtm3yBIR9gNUF6zUprWSeiNgIvAH0KVNnTZk6AZA0WVKVpKra\n2toczTUzs+bIExBKje1HM/I0K39ETIuIyoio7Nu371aqNDOzbZEnINQA+xas9wfWNpZHUmegF/Bq\nmTr7l6nTzMx2oDwBYSEwWNJASV2BCcCcojxzgDPT8inAvHRtoKSIWAe8JenIdHfRGcDvmtx6MzNr\nMZ3LZYiIjZLOB+4DOgE3RMRSSZcCVRExB7gemCGpmuzMYEJDeUmrgN2BrpLGAcdFxDLgXOBGYFfg\n9+llZmatpGxAAIiIucDcorSLCpbrgfGNlK1oJL0KODBvQ83MbPvyL5XNzAxwQDAzs8QBwczMAAcE\nMzNLHBDMzAxwQDAzs8QBwczMAAcEMzNLHBDMzAxwQDAzs8QBwczMAAcEMzNLHBDMzAxwQDAzs8QB\nwczMAAcEMzNLcgUESWMkrZBULWlKie3dJN2Wtj8mqaJg2wUpfYWk4wvSV0l6WtISSVUt0RkzM2u+\nsk9Mk9QJuBYYDdQACyXNSY/BbDAJeC0iBkmaAFwBfEHSULLHaQ4DPgY8IOnjEfFBKndsRGxowf6Y\nmVkz5TlDOByojoiVEfEeMBMYW5RnLDA9Lc8GRklSSp8ZEe9GxAtAdarPzMzamDwBYR9gdcF6TUor\nmSciNgJvAH3KlA3gfkmLJE1ubOeSJkuqklRVW1ubo7lmZtYceQKCSqRFzjxbK3t0RIwATgC+KumY\nUjuPiGkRURkRlX379s3RXDMza448AaEG2LdgvT+wtrE8kjoDvYBXt1Y2Ihr+vgzciYeSzMxaVZ6A\nsBAYLGmgpK5kF4nnFOWZA5yZlk8B5kVEpPQJ6S6kgcBg4HFJPSTtBiCpB3Ac8My2d8fMzJqr7F1G\nEbFR0vnAfUAn4IaIWCrpUqAqIuYA1wMzJFWTnRlMSGWXSpoFLAM2Al+NiA8kfRS4M7vuTGfgloi4\ndzv0z8zMciobEAAiYi4wtyjtooLlemB8I2UvBy4vSlsJHNzUxpqZ2fbjXyqbmRnggGBmZokDgpmZ\nAQ4IZmaWOCCYmRnggGBmZokDgpmZAQ4IZmaWOCCYmRnggGBmZokDgpmZAQ4IZmaWOCCYmRnggGBm\nZokDgpmZAQ4IZmaW5AoIksZIWiGpWtKUEtu7SbotbX9MUkXBtgtS+gpJx+et08zMdqyyAUFSJ+Ba\n4ARgKDBR0tCibJOA1yJiEHAVcEUqO5TscZrDgDHAv0vqlLNOMzPbgfKcIRwOVEfEyoh4D5gJjC3K\nMxaYnpZnA6OUPTB5LDAzIt6NiBeA6lRfnjrNzGwHyvNM5X2A1QXrNcARjeWJiI2S3gD6pPS/FJXd\nJy2XqxMASZOByWm1TtKKHG0uZS9gQzPLtjUdpS8dpR/gvrRVHaIvugLYtr4MyJMpT0BQibTImaex\n9FJnJsV1ZokR04BpW2tgHpKqIqJyW+tpCzpKXzpKP8B9aavcl6bJM2RUA+xbsN4fWNtYHkmdgV7A\nq1spm6dOMzPbgfIEhIXAYEkDJXUlu0g8pyjPHODMtHwKMC8iIqVPSHchDQQGA4/nrNPMzHagskNG\n6ZrA+cB9QCfghohYKulSoCoi5gDXAzMkVZOdGUxIZZdKmgUsAzYCX42IDwBK1dny3dvCNg87tSEd\npS8dpR/gvrRV7ksTKPsib2ZmOzv/UtnMzAAHBDMzSzp8QOhIU2RIWiXpaUlLJFW1dnuaQtINkl6W\n9ExB2p6S/iDpufR3j9ZsY16N9OViSWvSsVki6Z9as415SNpX0nxJyyUtlfQvKb3dHZet9KU9Hpfu\nkh6X9GTqyyUpfWCaGui5NFVQ1xbfd0e+hpCmyPgrMJrsVteFwMSIWNaqDWsmSauAyohodz+0kXQM\nUAfcFBEHprQfA69GxI9SsN4jIr7Tmu3Mo5G+XAzURcTU1mxbU0jaG9g7Ip6QtBuwCBgHnEU7Oy5b\n6cv/pP0VPA1EAAAFFElEQVQdFwE9IqJOUhfgYeBfgG8Ad0TETEn/ATwZEde15L47+hmCp8hoIyJi\nAdkdaIUKpzyZTvYfuM1rpC/tTkSsi4gn0vJbwHKymQTa3XHZSl/ancjUpdUu6RXAZ8imBoLtdFw6\nekAoNe1Gu/xHkgRwv6RFaUqP9u6jEbEOsv/QQL9Wbs+2Ol/SU2lIqc0PsxRKMxQfAjxGOz8uRX2B\ndnhc0iSgS4CXgT8AzwOvR8TGlGW7fJZ19ICQZ9qN9uToiBhBNkvsV9PQhbUN1wH/AAwH1gE/ad3m\n5CepJ/Ab4OsR8WZrt2dblOhLuzwuEfFBRAwnm8XhcOCAUtlaer8dPSB0qCkyImJt+vsycCfZP5T2\nbH0a+20YA365ldvTbBGxPv0n3gT8knZybNIY9W+AX0fEHSm5XR6XUn1pr8elQUS8DjwIHAn0TlMD\nwXb6LOvoAaHDTJEhqUe6WIakHsBxwDNbL9XmFU55cibwu1ZsyzZp+ABNPk87ODbp4uX1wPKI+GnB\npnZ3XBrrSzs9Ln0l9U7LuwKfJbsmMp9saiDYTselQ99lBJBuM7uav0+RcXkrN6lZJO1PdlYA2ZQj\nt7Snvki6Ffg02RS+64EfAL8FZgH7Af8FjI+INn+xtpG+fJpsWCKAVcA5DePwbZWkkcBDwNPAppT8\nXbKx93Z1XLbSl4m0v+NyENlF405kX9pnRcSl6TNgJrAnsBg4LSLebdF9d/SAYGZm+XT0ISMzM8vJ\nAcHMzAAHBDMzSxwQzMwMcEAwM7PEAcE6DEkfFMxquaStzG5bMEttZcH6XjnL3ijpnKK0cZLmSto1\n9fO9vPWZbU3ZR2iatSN/Sz/3bzGSOhfMH7Mtjm3mLLW3AlOAXxSkTQBujYi/AcPTLLhm28xnCNbh\npW/kl0h6In1TH5LSe6QJzxZKWixpbEo/S9Ltku4im0xwF0n/nuamvzt9Oz9F0ihJdxbsZ7SkOxpp\nRql27SrpXklnp/XT0jz4SyT9Ik3f/gAwpGAqiY+Q/XL1ty32BpklDgjWkTQMoTS8vlCwbUOaGPA6\n4Fsp7XvAvIg4DDgWuDJNCwJwFHBmRHwG+B9ABfAJ4MtpG8A84ABJfdP6/wJ+lbOtPYG7yH5x/ktJ\nBwBfIJvAcDjwAXBqRHwA3EE2rz/AScD8NMWzWYvykJF1JFsbMmr45r6I7AMesvmgTpLUECC6k03X\nAPCHgukaRgK3pwnSXpI0H7J56yXNAE6T9CuyQHFGzrb+DvhxRPw6rY8CDgUWZtPysCt/n1TuVuBK\n4Gdkw0U35dyHWZM4INjOomHOlw/4+797ASdHxIrCjJKOAN4uTNpKvb8i+6ZfTxY08l5veAQ4QdIt\nkc0fI2B6RFzQSN69JR0MfJIsKJi1OA8Z2c7sPuB/p5kykXRII/keBk5O1xI+SjaRHbB5SvK1wPeB\nG5uw74uAV4B/T+t/BE6R1C+1ZU9JA9I+gmyyuenA3Iiob8J+zHJzQLCOpPgawo/K5P8h2eMJn5L0\nTFov5Tdkz9Z4huxun8eANwq2/xpY3YxndX8d6C7px6ns98kuYj9F9pSswqmbbwUOJpvt0my78Gyn\nZjlI6pkeet4HeJzs4u9LadvPgcURcX0jZVcBlc287TRP27Zr/bbz8BmCWT53p2fcPgT8sCAYLAIO\nAm7eStla4I8NP0xrKQ0/TCM7y9lULr9ZOT5DMDMzwGcIZmaWOCCYmRnggGBmZokDgpmZAQ4IZmaW\n/H9fi2zzjN+hAgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x114e8a898>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "module = Module(radii=[5.151,4.9],focal=500.0)\n",
    "detector = Detector(width=8, \n",
    "                    height=8,\n",
    "                    normal = [0,0,1],\n",
    "                    center = [0,0,230],\n",
    "                    reso = [1024,1024])\n",
    "\n",
    "rays = source.generateRays(module.targetFront, 500)\n",
    "\n",
    "plt.figure()\n",
    "plt.hist([ray.energy for ray in rays], normed=True, label='generated rays')\n",
    "plt.xlabel('Energy [keV]')\n",
    "plt.title('Histogram generated rays')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 51,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of rays on Detector 53\n",
      "Time total: 160 seconds\n",
      "Time per ray (s): 0.33125\n"
     ]
    },
    {
     "data": {
      "image/png": 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hxAiYOhW6dAm0fBGRYqN7+JJbzsG//gVHHQVr1mz7WEUFXHMNrFwJv/89HHyw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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1159a9978>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tstart = datetime.now()\n",
    "\n",
    "# pass rays through module\n",
    "module.passRays(rays, robust=True)\n",
    "# catch rays at detector\n",
    "detector.catchRays(rays)\n",
    "\n",
    "\n",
    "rays_on_detector = len(detector.rays)\n",
    "print('Number of rays on Detector ' + str(rays_on_detector))\n",
    "print('Time total: ' + str((datetime.now() - tstart).seconds) + ' seconds')\n",
    "print('Time per ray (s): ' + str(rays_on_detector / float((datetime.now() - tstart).seconds)))\n",
    "\n",
    "drays = [ray for ray in rays if ray.des[2]==230.0]\n",
    "scatterHist(drays)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 52,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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7Q40VKdshNzOzIvAvcs3MCsShb2ZWIB029Lfk1A/tVN8ASY9KWiBpnqR/rNDm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\nDdcnRgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11b0c5ac8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.hist([ray.energy for ray in detector.rays], normed=True, label='rays on detector',color='r')\n",
    "plt.xlabel('Energy [keV]')\n",
    "plt.title('Histogram caught rays on detector')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# F = 1000"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 53,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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582yp7JERsUrSHsAfJL0QEfM+sfMsWEwE2HvvvXM018zMmiLPGUI1sFfBeh9g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\nRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11afa3a20>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "module = Module(radii=[5.151,4.9],focal=1000.0)\n",
    "detector = Detector(width=8, \n",
    "                    height=8,\n",
    "                    normal = [0,0,1],\n",
    "                    center = [0,0,230],\n",
    "                    reso = [1024,1024])\n",
    "\n",
    "rays = source.generateRays(module.targetFront, 500)\n",
    "\n",
    "plt.figure()\n",
    "plt.hist([ray.energy for ray in rays], normed=True, label='generated rays')\n",
    "plt.xlabel('Energy [keV]')\n",
    "plt.title('Histogram generated rays')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 54,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of rays on Detector 64\n",
      "Time total: 123 seconds\n",
      "Time per ray (s): 0.5203252032520326\n"
     ]
    },
    {
     "data": {
      "image/png": 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GjfNalhQHBb6ISKFo0gRGjnSBX/NafjgMHTrAH/7gSWnifwp8EZFCcsopMHEi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\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11b0c39b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tstart = datetime.now()\n",
    "\n",
    "# pass rays through module\n",
    "module.passRays(rays, robust=True)\n",
    "# catch rays at detector\n",
    "detector.catchRays(rays)\n",
    "\n",
    "\n",
    "rays_on_detector = len(detector.rays)\n",
    "print('Number of rays on Detector ' + str(rays_on_detector))\n",
    "print('Time total: ' + str((datetime.now() - tstart).seconds) + ' seconds')\n",
    "print('Time per ray (s): ' + str(rays_on_detector / float((datetime.now() - tstart).seconds)))\n",
    "\n",
    "drays = [ray for ray in rays if ray.des[2]==230.0]\n",
    "scatterHist(drays)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 55,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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dYCYwpqTMGOC2dH82MFKS0vyZEfFORLwILE3bMzOzdtC9gjIHASty03XAcY2V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\nCsShb2ZWIA59M7MC+f+AysGSLhRM8gAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11ada1e48>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.hist([ray.energy for ray in detector.rays], normed=True, label='rays on detector',color='r')\n",
    "plt.xlabel('Energy [keV]')\n",
    "plt.title('Histogram caught rays on detector')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# 1500"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 59,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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TVCmpsqamJkdzzcysKfIEBJVIi5x5NlX2yIgYDBwPfEvS0aV2HhGTIqIiIirK\nyspyNNfMzJoiT0CoBvYqWO8FLK8vj6T2QDfgnU2VjYi6v28B0/FQkplZi8oTEOYA/ST1kdSR7CLx\njKI8M4Az0/LJwKyIiJQ+Ot2F1AfoBzwrqYuknQEkdQGOBV7a/O6YmVlTNXiXUUSsk3QB8DDQDrg5\nIhZIugyojIgZwE3AFElVZGcGo1PZBZLuBhYC64BvRcQnkj4HTM+uO9MeuCMiHtoC/TMzs5waDAgA\nETETmFmUdnHB8mpgVD1lLwcuL0pbDBzY2MaamdmW418qm5kZ4IBgZmaJA4KZmQEOCGZmljggmJkZ\n4IBgZmaJA4KZmQEOCGZmljggmJkZ4IBgZmaJA4KZmQEOCGZmljggmJkZ4IBgZmaJA4KZmQEOCGZm\nluQKCJKGS1okqUrS+BLbO0m6K21/RlJ5wbYLU/oiScflrdPMzLauBgOCpHbADcDxwABgjKQBRdnG\nAu9GRF/gauDKVHYA2eM0BwLDgX+X1C5nnWZmthXlOUM4FKiKiMURsQaYCowoyjMCmJyWpwFDlT0w\neQQwNSI+jojXgapUX546zcxsK8rzTOWewNKC9WrgsPryRMQ6Se8DPVL6n4vK9kzLDdUJgKRxwLi0\nWitpUY42l7I7sKqJZVsb96X12Vb6Ae5Lq6Mrgc3rS+88mfIEBJVIi5x56ksvdWZSXGeWGDEJmLSp\nBuYhqTIiKja3ntbAfWl9tpV+gPvSWm2NvuQZMqoG9ipY7wUsry+PpPZAN+CdTZTNU6eZmW1FeQLC\nHKCfpD6SOpJdJJ5RlGcGcGZaPhmYFRGR0kenu5D6AP2AZ3PWaWZmW1GDQ0bpmsAFwMNAO+DmiFgg\n6TKgMiJmADcBUyRVkZ0ZjE5lF0i6G1gIrAO+FRGfAJSqs/m7t5HNHnZqRdyX1mdb6Qe4L63VFu+L\nsi/yZma2vfMvlc3MDHBAMDOzZJsPCNvSFBmSlkh6UdJ8SZUt3Z7GkHSzpLckvVSQtpuk30t6Nf3d\ntSXbmFc9fblE0rJ0bOZL+oeWbGNekvaSNFvSy5IWSPrnlN7mjs0m+tLmjo2kzpKelfR86sulKb1P\nmh7o1TRdUMdm3e+2fA0hTZHxF2AY2a2uc4AxEbGwRRvWRJKWABUR0eZ+aCPpaKAWuDUi9ktpPwPe\niYgrUrDeNSJ+0JLtzKOevlwC1EbExJZsW2NJ2hPYMyKek7QzMBcYCZxFGzs2m+jL/6aNHZs000OX\niKiV1AEUZzYpAAAFDklEQVR4Evhn4F+AeyNiqqT/AJ6PiBuba7/b+hmCp8hoJSLicbI70AoVTnky\nmew/b6tXT1/apIhYERHPpeUPgZfJZhNoc8dmE31pcyJTm1Y7pFcAXyabHgi2wHHZ1gNCqWk32uQ/\nkCSARyTNTVN6tHWfi4gVkP1nBvZo4fZsrgskvZCGlFr9EEuxNEvxQcAztPFjU9QXaIPHJk0EOh94\nC/g98BrwXkSsS1ma/fNsWw8IeabdaEuOjIjBZLPEfisNXVjrcCPwd8AgYAXw85ZtTuNI6gr8BvhO\nRHzQ0u3ZHCX60iaPTUR8EhGDyGZyOBTYt1S25tznth4QtqkpMiJiefr7FjCd7B9JW7YyjfvWjf++\n1cLtabKIWJn+A68HfkUbOjZpjPo3wO0RcW9KbpPHplRf2vKxAYiI94DHgMOB7ml6INgCn2fbekDY\nZqbIkNQlXShDUhfgWOClTZdq9QqnPDkTuK8F27JZ6j48k6/RRo5Nunh5E/ByRPyiYFObOzb19aUt\nHhtJZZK6p+Udga+QXROZTTY9EGyB47JN32UEkG4xu4ZPp8i4vIWb1CSS9iE7K4BsypE72lJfJN0J\nfIlsCt+VwE+A3wJ3A3sD/wWMiohWf7G2nr58iWxIIoAlwLl1Y/CtmaQhwBPAi8D6lPxDsrH3NnVs\nNtGXMbSxYyPpALKLxu3IvrjfHRGXpc+BqcBuwDzgtIj4uNn2u60HBDMzy2dbHzIyM7OcHBDMzAxw\nQDAzs8QBwczMAAcEMzNLHBBsmyHpk4IZLee3ltltC2aprShY3z1n2VsknVuUNlLSTEk7pn6uyVuf\n2aY0+AhNszbkb+mn/s1GUvuCuWM2xzFNnKX2TmA88MuCtNHAnRHxN2BQmgXXbLP5DMG2eekb+aWS\nnkvf1Pun9C5psrM5kuZJGpHSz5J0j6T7ySYT3EHSv6d56R9I385PljRU0vSC/QyTdG89zSjVrh0l\nPSTpnLR+WpoDf76kX6bp2x8F+hdMI7ET2a9Wf9tsb5BZ4oBg25K6IZS61ykF21aliQFvBL6X0n4E\nzIqIQ4BjgKvStCAARwBnRsSXgf8FlAP7A99I2wBmAftKKkvr/wf4dc62dgXuJ/vF+a8k7QucQjaB\n4SDgE+DUiPgEuJdsTn+AE4HZaXpns2blISPblmxqyKjum/tcsg94yOaDOlFSXYDoTDZVA8DvC6Zq\nGALckyZHe1PSbMjmrJc0BThN0q/JAsUZOdt6H/CziLg9rQ8FDgbmZFPysCOfTih3J3AVcC3ZcNGt\nOfdh1igOCLa9qJvv5RM+/Xcv4KSIWFSYUdJhwF8LkzZR76/JvumvJgsaea83PAUcL+mOyOaPETA5\nIi6sJ++ekg4EvkgWFMyanYeMbHv2MPBPaZZMJB1UT74ngZPStYTPkU1kB2yYknw58GPglkbs+2Lg\nbeDf0/ofgJMl7ZHaspuk3mkfQTbR3GRgZkSsbsR+zHJzQLBtSfE1hCsayP9TskcTviDppbReym/I\nnq3xEtndPs8A7xdsvx1Y2oRndX8H6CzpZ6nsj8kuYr9A9oSswmmb7wQOJJvp0myL8GynZjlI6poe\neN4DeJbs4u+badv1wLyIuKmeskuAiibedpqnbVu0ftt++AzBLJ8H0vNtnwB+WhAM5gIHALdtomwN\n8Ie6H6Y1l7ofppGd5axvKL9ZQ3yGYGZmgM8QzMwscUAwMzPAAcHMzBIHBDMzAxwQzMws+W8SNmdh\nmbiPJgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11a5a1f28>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "module = Module(radii=[5.151,4.9],focal=1500.0)\n",
    "detector = Detector(width=8, \n",
    "                    height=8,\n",
    "                    normal = [0,0,1],\n",
    "                    center = [0,0,230],\n",
    "                    reso = [1024,1024])\n",
    "\n",
    "rays = source.generateRays(module.targetFront, 500)\n",
    "\n",
    "plt.figure()\n",
    "plt.hist([ray.energy for ray in rays], normed=True, label='generated rays')\n",
    "plt.xlabel('Energy [keV]')\n",
    "plt.title('Histogram generated rays')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 60,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Number of rays on Detector 80\n",
      "Time total: 81 seconds\n",
      "Time per ray (s): 0.9876543209876543\n"
     ]
    },
    {
     "data": {
      "image/png": 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WA64Hpjjn3k+z6gigqsEypwThiYiEnc6dLVAoEz6+Lb8PcHiG9a7A1wTUL92K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\nwpen9XsAAAAASUVORK5CYII=\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11a757358>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "tstart = datetime.now()\n",
    "\n",
    "# pass rays through module\n",
    "module.passRays(rays, robust=True)\n",
    "# catch rays at detector\n",
    "detector.catchRays(rays)\n",
    "\n",
    "\n",
    "rays_on_detector = len(detector.rays)\n",
    "print('Number of rays on Detector ' + str(rays_on_detector))\n",
    "print('Time total: ' + str((datetime.now() - tstart).seconds) + ' seconds')\n",
    "print('Time per ray (s): ' + str(rays_on_detector / float((datetime.now() - tstart).seconds)))\n",
    "\n",
    "drays = [ray for ray in rays if ray.des[2]==230.0]\n",
    "scatterHist(drays)\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 61,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "data": {
      "image/png": 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6LSNpB+C/gW9GxKpy16e11NOudnG8mqvSQ7/dDvMQEYvS3/eAB2hfo5MuTudZ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\nEYe+mVmO/A8bcGZX1+tLNgAAAABJRU5ErkJggg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x11557dcf8>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.hist([ray.energy for ray in detector.rays], normed=True, label='rays on detector',color='r')\n",
    "plt.xlabel('Energy [keV]')\n",
    "plt.title('Histogram caught rays on detector')\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "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
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.0"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}