Untitled1.ipynb

{
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  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
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   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "WARNING:root:pymultinest not imported!\n",
      "WARNING:root:DMDD_MAIN_PATH environment variable not defined, defaulting to:   ~/.dmdd\n"
     ]
    }
   ],
   "source": [
    "import dmdd\n",
    "import numpy as np"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": false
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "model: Anapole, parameters: ['mass', 'sigma_anapole'].\n",
      "model: SI, parameters: ['mass', 'sigma_si'].\n"
     ]
    }
   ],
   "source": [
    "# shortcut for scattering models corresponding to rates coded in rate_UV:\n",
    "anapole_model = dmdd.UV_Model('Anapole', ['mass','sigma_anapole'])\n",
    "SI_model = dmdd.UV_Model('SI', ['mass','sigma_si'])\n",
    "\n",
    "print 'model: {}, parameters: {}.'.format(anapole_model.name, anapole_model.param_names)\n",
    "print 'model: {}, parameters: {}.'.format(SI_model.name, SI_model.param_names)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "# intialize an Experiment with XENON target, to be passed to Simulation_AM:\n",
    "xe = dmdd.Experiment('1xe', 'xenon', 5, 80, 1000, dmdd.eff.efficiency_unit, energy_resolution=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {
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   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Simulation data and/or pickle file does not exist. Forcing simulation.\n",
      "\n",
      "\n",
      "[ 3.57633769] 243.972474054\n",
      "[ 0.13730284] 142.529071895\n",
      "[ 1.61817126] 31.4785785118\n",
      "[ 7.67991422] 249.264481887\n",
      "[ 20.64832812] 43.8431695553\n",
      "[ 18.89741965] 217.013723052\n",
      "[ 17.14495471] 212.550436019\n",
      "[ 0.20921509] 11.6669784235\n",
      "[ 24.63932775] 139.299731251\n",
      "[ 8.55676827] 90.1886965323\n",
      "[ 2.4625456] 159.434277161\n",
      "[ 0.34352606] 109.352095394\n",
      "[ 55.30863931] 176.427195571\n",
      "[ 15.34430534] 200.289295332\n",
      "[ 132.05060909] 34.3918272232\n",
      "1\n",
      "[ 95.85031021] 117.689498641\n",
      "[ 0.10231843] 59.1413294835\n",
      "[ 16.97310936] 29.9203523676\n",
      "[ 0.08108782] 69.9506552194\n",
      "[ 132.6685115] 73.5706154195\n",
      "2\n",
      "[ 0.09735839] 202.066422105\n",
      "[ 0.2746477] 96.4716190672\n",
      "[ 0.1573197] 212.408923733\n",
      "[ 131.91884131] 249.192520993\n"
     ]
    },
    {
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[0;32m<ipython-input-4-70ff853dfa5a>\u001b[0m in \u001b[0;36m<module>\u001b[0;34m()\u001b[0m\n\u001b[1;32m      3\u001b[0m                         \u001b[0mQmax\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0masarray\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m80.\u001b[0m\u001b[0;34m]\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m      4\u001b[0m                         \u001b[0mTmin\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m0\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mTmax\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m365\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msigma_anapole\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0;36m44.25\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m----> 5\u001b[0;31m                         element = 'xenon', force_sim = True)\n\u001b[0m",
      "\u001b[0;32m/Users/katelynneese/dmddACT/dmdd/dmdd.py\u001b[0m in \u001b[0;36m__init__\u001b[0;34m(self, name, experiment, model, parvals, Qmin, Qmax, element, sigma_si, sigma_anapole, mass, v_amplitude, Tmin, Tmax, path, force_sim, asimov, nbins_asimov, plot_nbins, plot_theory, silent)\u001b[0m\n\u001b[1;32m   1068\u001b[0m                 \u001b[0;32mraise\u001b[0m \u001b[0mValueError\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m'Asimov simulations not yet implemented!'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1069\u001b[0m             \u001b[0;32melse\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1070\u001b[0;31m                 \u001b[0mQ\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msimulate_data\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m   1071\u001b[0m                 \u001b[0mnp\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msavetxt\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdatafile\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mQ\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1072\u001b[0m                 \u001b[0mfout\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mopen\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mpicklefile\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m'wb'\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/katelynneese/dmddACT/dmdd/dmdd.py\u001b[0m in \u001b[0;36msimulate_data\u001b[0;34m(self)\u001b[0m\n\u001b[1;32m   1134\u001b[0m                 pdf_value = PDF(Q_rand, T_rand, element = self.element, mass = self.mass,\n\u001b[1;32m   1135\u001b[0m                                         \u001b[0msigma_si\u001b[0m\u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msigma_si\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msigma_anapole\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mself\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0msigma_anapole\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m-> 1136\u001b[0;31m                                         Qmin = np.asarray([self.Qmin]), Qmax = np.asarray([self.Qmax]), Tmin = self.Tmin, Tmax = self.Tmax)\n\u001b[0m\u001b[1;32m   1137\u001b[0m                 \u001b[0;32mprint\u001b[0m \u001b[0mpdf_value\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mU\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m   1138\u001b[0m                 \u001b[0;31m#envelope is 1 so don't need to divide by anything\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/katelynneese/dmddACT/dmdd/dmdd.py\u001b[0m in \u001b[0;36mPDF\u001b[0;34m(Q, time, element, mass, sigma_si, sigma_anapole, Qmin, Qmax, Tmin, Tmax)\u001b[0m\n\u001b[1;32m    117\u001b[0m                     \u001b[0mTmin\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mTmin\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mTmax\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mTmax\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    118\u001b[0m                     \u001b[0melement\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0melement\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msigma_si\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msigma_si\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m--> 119\u001b[0;31m                     sigma_anapole = sigma_anapole, mass = mass)\n\u001b[0m\u001b[1;32m    120\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    121\u001b[0m     \u001b[0;32mreturn\u001b[0m \u001b[0mdrdq\u001b[0m\u001b[0;34m/\u001b[0m\u001b[0mnorm\u001b[0m\u001b[0;34m[\u001b[0m\u001b[0;36m0\u001b[0m\u001b[0;34m]\u001b[0m \u001b[0;31m#for now removed efficiency and made it 1\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/katelynneese/dmddACT/dmdd/dmdd.py\u001b[0m in \u001b[0;36mintegral\u001b[0;34m(Qmin, Qmax, Tmin, Tmax, Qpoints, Tpoints, function, sigma_si, sigma_anapole, mass, element, v_amplitude)\u001b[0m\n\u001b[1;32m    102\u001b[0m         \u001b[0;32mfor\u001b[0m \u001b[0mj\u001b[0m\u001b[0;34m,\u001b[0m\u001b[0mT\u001b[0m \u001b[0;32min\u001b[0m \u001b[0menumerate\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mT_box\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m:\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    103\u001b[0m             a_sum = np.sum(function(Q = np.asarray(Q), time = T, sigma_si = sigma_si, sigma_anapole = sigma_anapole,\n\u001b[0;32m--> 104\u001b[0;31m                                     mass = mass, element = element, v_amplitude = v_amplitude))\n\u001b[0m\u001b[1;32m    105\u001b[0m             \u001b[0mtotal_sum\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0ma_sum\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m    106\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;32m/Users/katelynneese/dmddACT/dmdd/dmdd.py\u001b[0m in \u001b[0;36mdRdQ_AM\u001b[0;34m(mass, sigma_si, sigma_anapole, Q, time, element, vlag_mean, v_amplitude)\u001b[0m\n\u001b[1;32m     81\u001b[0m     \u001b[0;31m#print type(v_lag) #vlag must be a number not an array\u001b[0m\u001b[0;34m\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     82\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0;32m---> 83\u001b[0;31m     \u001b[0mrate_QT\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mrate_UV\u001b[0m\u001b[0;34m.\u001b[0m\u001b[0mdRdQ\u001b[0m\u001b[0;34m(\u001b[0m\u001b[0mQ\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0menergy\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mv_lag\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mv_lag\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0mmass\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0mmass\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msigma_si\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msigma_si\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0msigma_anapole\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0msigma_anapole\u001b[0m\u001b[0;34m,\u001b[0m \u001b[0melement\u001b[0m \u001b[0;34m=\u001b[0m \u001b[0melement\u001b[0m\u001b[0;34m)\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n\u001b[0m\u001b[1;32m     84\u001b[0m \u001b[0;34m\u001b[0m\u001b[0m\n\u001b[1;32m     85\u001b[0m     \u001b[0;34m\"Return a 1D array with the rate based on the time and energy given\"\u001b[0m\u001b[0;34m\u001b[0m\u001b[0m\n",
      "\u001b[0;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "xe_ana_test = dmdd.Simulation_AM('Anapole', xe, anapole_model, \n",
    "                        {'mass':50.,'sigma_anapole':44.25}, Qmin = np.asarray([5.]), \n",
    "                        Qmax = np.asarray([80.]), \n",
    "                        Tmin = 0, Tmax = 365, sigma_anapole = 44.25, \n",
    "                        element = 'xenon', force_sim = True)"
   ]
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