Spectra Verification.ipynb

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  {
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   "source": [
    "from Simulation import *\n",
    "from Geometry import *\n",
    "from mie_data import mie_10nm\n",
    "from mie_data import mie_40nm"
   ]
  },
  {
   "source": [
    "# Mie Theory Verification"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "wavelength_list = np.linspace(400,700,30)"
   ]
  },
  {
   "source": [
    "## 10 nm radius "
   ],
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   "execution_count": 3,
   "metadata": {
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     "text": [
      "DoF:  126435\n",
      "Max Error:  0.8852706333470328\n",
      "DoF:  243076\n",
      "Max Error:  0.2652403583383671\n",
      "DoF:  294898\n",
      "Max Error:  0.16589977519717428\n",
      "DoF:  361058\n",
      "Max Error:  0.2668991260053699\n",
      "DoF:  377127\n",
      "Max Error:  0.17993164595616612\n",
      "Wall time: 9min 8s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "mesh = Nanosphere(10,0,300,600)\n",
    "sim10nm = Simulation(mesh)\n",
    "sim10nm.RefineMesh()"
   ]
  },
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   "execution_count": 4,
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     "text": [
      "Wavelength:  400.0\n",
      "Wavelength:  410.3448275862069\n",
      "Wavelength:  420.6896551724138\n",
      "Wavelength:  431.0344827586207\n",
      "Wavelength:  441.37931034482756\n",
      "Wavelength:  451.7241379310345\n",
      "Wavelength:  462.0689655172414\n",
      "Wavelength:  472.41379310344826\n",
      "Wavelength:  482.7586206896552\n",
      "Wavelength:  493.1034482758621\n",
      "Wavelength:  503.44827586206895\n",
      "Wavelength:  513.7931034482758\n",
      "Wavelength:  524.1379310344828\n",
      "Wavelength:  534.4827586206897\n",
      "Wavelength:  544.8275862068965\n",
      "Wavelength:  555.1724137931035\n",
      "Wavelength:  565.5172413793103\n",
      "Wavelength:  575.8620689655172\n",
      "Wavelength:  586.2068965517242\n",
      "Wavelength:  596.551724137931\n",
      "Wavelength:  606.8965517241379\n",
      "Wavelength:  617.2413793103449\n",
      "Wavelength:  627.5862068965517\n",
      "Wavelength:  637.9310344827586\n",
      "Wavelength:  648.2758620689656\n",
      "Wavelength:  658.6206896551724\n",
      "Wavelength:  668.9655172413793\n",
      "Wavelength:  679.3103448275863\n",
      "Wavelength:  689.6551724137931\n",
      "Wavelength:  700.0\n",
      "Wall time: 21min 12s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "ext_list10nm = np.array([(wavelength,sim10nm.Extinction(wavelength)) for wavelength in wavelength_list])"
   ]
  },
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     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "plt.figure(figsize=(20,10))\n",
    "plt.plot(ext_list10nm[:,0],-ext_list10nm[:,1],label=\"FEM\")\n",
    "plt.plot(mie_10nm[:,0]*1e+9,mie_10nm[:,1],label=\"Mie Theory\")\n",
    "plt.xlabel(\"Wavelength (nm)\")\n",
    "plt.ylabel(\"Extinction Cross Section (m$^2$)\")\n",
    "plt.grid()\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## 40 nm radius"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "DoF:  104868\n",
      "Max Error:  5.39232903968863\n",
      "DoF:  132799\n",
      "Max Error:  1.5318547215732496\n",
      "DoF:  190208\n",
      "Max Error:  1.3053367599229855\n",
      "DoF:  234257\n",
      "Max Error:  1.1384688297085555\n",
      "DoF:  254039\n",
      "Max Error:  0.6062383925323491\n",
      "DoF:  313184\n",
      "Max Error:  1.9798849506469316\n",
      "DoF:  318597\n",
      "Max Error:  1.8481338550709645\n",
      "Wall time: 9min 36s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "mesh = Nanosphere(40,0,300,600)\n",
    "sim40nm = Simulation(mesh)\n",
    "sim40nm.RefineMesh()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "Wavelength:  400.0\n",
      "Wavelength:  403.0\n",
      "Wavelength:  406.0\n",
      "Wavelength:  409.0\n",
      "Wavelength:  412.0\n",
      "Wavelength:  415.0\n",
      "Wavelength:  418.0\n",
      "Wavelength:  421.0\n",
      "Wavelength:  424.0\n",
      "Wavelength:  427.0\n",
      "Wavelength:  430.0\n",
      "Wavelength:  433.0\n",
      "Wavelength:  436.0\n",
      "Wavelength:  439.0\n",
      "Wavelength:  442.0\n",
      "Wavelength:  445.0\n",
      "Wavelength:  448.0\n",
      "Wavelength:  451.0\n",
      "Wavelength:  454.0\n",
      "Wavelength:  457.0\n",
      "Wavelength:  460.0\n",
      "Wavelength:  463.0\n",
      "Wavelength:  466.0\n",
      "Wavelength:  469.0\n",
      "Wavelength:  472.0\n",
      "Wavelength:  475.0\n",
      "Wavelength:  478.0\n",
      "Wavelength:  481.0\n",
      "Wavelength:  484.0\n",
      "Wavelength:  487.0\n",
      "Wavelength:  490.0\n",
      "Wavelength:  493.0\n",
      "Wavelength:  496.0\n",
      "Wavelength:  499.0\n",
      "Wavelength:  502.0\n",
      "Wavelength:  505.0\n",
      "Wavelength:  508.0\n",
      "Wavelength:  511.0\n",
      "Wavelength:  514.0\n",
      "Wavelength:  517.0\n",
      "Wavelength:  520.0\n",
      "Wavelength:  523.0\n",
      "Wavelength:  526.0\n",
      "Wavelength:  529.0\n",
      "Wavelength:  532.0\n",
      "Wavelength:  535.0\n",
      "Wavelength:  538.0\n",
      "Wavelength:  541.0\n",
      "Wavelength:  544.0\n",
      "Wavelength:  547.0\n",
      "Wavelength:  550.0\n",
      "Wavelength:  553.0\n",
      "Wavelength:  556.0\n",
      "Wavelength:  559.0\n",
      "Wavelength:  562.0\n",
      "Wavelength:  565.0\n",
      "Wavelength:  568.0\n",
      "Wavelength:  571.0\n",
      "Wavelength:  574.0\n",
      "Wavelength:  577.0\n",
      "Wavelength:  580.0\n",
      "Wavelength:  583.0\n",
      "Wavelength:  586.0\n",
      "Wavelength:  589.0\n",
      "Wavelength:  592.0\n",
      "Wavelength:  595.0\n",
      "Wavelength:  598.0\n",
      "Wavelength:  601.0\n",
      "Wavelength:  604.0\n",
      "Wavelength:  607.0\n",
      "Wavelength:  610.0\n",
      "Wavelength:  613.0\n",
      "Wavelength:  616.0\n",
      "Wavelength:  619.0\n",
      "Wavelength:  622.0\n",
      "Wavelength:  625.0\n",
      "Wavelength:  628.0\n",
      "Wavelength:  631.0\n",
      "Wavelength:  634.0\n",
      "Wavelength:  637.0\n",
      "Wavelength:  640.0\n",
      "Wavelength:  643.0\n",
      "Wavelength:  646.0\n",
      "Wavelength:  649.0\n",
      "Wavelength:  652.0\n",
      "Wavelength:  655.0\n",
      "Wavelength:  658.0\n",
      "Wavelength:  661.0\n",
      "Wavelength:  664.0\n",
      "Wavelength:  667.0\n",
      "Wavelength:  670.0\n",
      "Wavelength:  673.0\n",
      "Wavelength:  676.0\n",
      "Wavelength:  679.0\n",
      "Wavelength:  682.0\n",
      "Wavelength:  685.0\n",
      "Wavelength:  688.0\n",
      "Wavelength:  691.0\n",
      "Wavelength:  694.0\n",
      "Wavelength:  697.0\n",
      "Wavelength:  700.0\n",
      "Wall time: 56min 48s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "ext_list40nm = np.array([(wavelength,sim40nm.Extinction(wavelength)) for wavelength in wavelength_list])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
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\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "plt.figure(figsize=(20,10))\n",
    "plt.plot(ext_list40nm[:,0],-ext_list40nm[:,1],label=\"FEM\")\n",
    "plt.plot(mie_40nm[:,0]*1e+9,mie_40nm[:,1],label=\"Mie Theory\")\n",
    "plt.xlabel(\"Wavelength (nm)\")\n",
    "plt.ylabel(\"Extinction Cross Section (m$^2$)\")\n",
    "plt.grid()\n",
    "plt.legend()\n",
    "plt.show()"
   ]
  },
  {
   "source": [
    "# Model Verification"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "source": [
    "## 10nm Microtubules"
   ],
   "cell_type": "markdown",
   "metadata": {}
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "DoF:  31380\nMax Error:  3.1286863914019074\n"
     ]
    },
    {
     "output_type": "error",
     "ename": "KeyboardInterrupt",
     "evalue": "",
     "traceback": [
      "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m                         Traceback (most recent call last)",
      "\u001b[1;32m<timed exec>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m\u001b[0m\n",
      "\u001b[1;32mf:\\foile\\Documents\\Python Scripts\\LSPyR\\Simulation.py\u001b[0m in \u001b[0;36mRefineMesh\u001b[1;34m(self, fmin, fmax, tol, percentage, iteration)\u001b[0m\n\u001b[0;32m    145\u001b[0m                                 \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mRefineMesh\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfmin\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mfmid1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfmax\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mfmid\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtol\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mtol\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mpercentage\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mpercentage\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0miteration\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0miteration\u001b[0m\u001b[1;33m+\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    146\u001b[0m                         \u001b[1;32melse\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 147\u001b[1;33m                                 \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mRefineMesh\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfmin\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mfmid\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfmax\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mfmid2\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mtol\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mtol\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mpercentage\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mpercentage\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0miteration\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0miteration\u001b[0m\u001b[1;33m+\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    148\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    149\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mf:\\foile\\Documents\\Python Scripts\\LSPyR\\Simulation.py\u001b[0m in \u001b[0;36mRefineMesh\u001b[1;34m(self, fmin, fmax, tol, percentage, iteration)\u001b[0m\n\u001b[0;32m    116\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    117\u001b[0m                 \u001b[0mfmid\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mfmin\u001b[0m \u001b[1;33m+\u001b[0m \u001b[0mfmax\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m/\u001b[0m\u001b[1;36m2\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 118\u001b[1;33m                 \u001b[0melerr\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmaxerr\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mError\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfmid\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    119\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    120\u001b[0m                 \u001b[0mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m\"DoF: \"\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mfes\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mndof\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mf:\\foile\\Documents\\Python Scripts\\LSPyR\\Simulation.py\u001b[0m in \u001b[0;36mError\u001b[1;34m(self, wavelength)\u001b[0m\n\u001b[0;32m     93\u001b[0m                 \u001b[0mfesLO\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfesLO\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     94\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m---> 95\u001b[1;33m                 \u001b[0mEsc\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mGetEsc\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mwavelength\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     96\u001b[0m                 \u001b[0mEsc_approx\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mGridFunction\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfesLO\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     97\u001b[0m                 \u001b[0mEsc_approx\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mSet\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mEsc\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32mf:\\foile\\Documents\\Python Scripts\\LSPyR\\Simulation.py\u001b[0m in \u001b[0;36mGetEsc\u001b[1;34m(self, wavelength)\u001b[0m\n\u001b[0;32m     84\u001b[0m                 \u001b[0mf\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mAssemble\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     85\u001b[0m \t\tEsc.vec.data = solvers.GMRes(\n\u001b[1;32m---> 86\u001b[1;33m \t\t\ta.mat, f.vec, pre=c.mat, printrates=False, restart=750)\n\u001b[0m\u001b[0;32m     87\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     88\u001b[0m                 \u001b[1;32mreturn\u001b[0m \u001b[0mEsc\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\envs\\ngsolve\\lib\\site-packages\\ngsolve\\krylovspace.py\u001b[0m in \u001b[0;36mGMRes\u001b[1;34m(A, b, pre, freedofs, x, maxsteps, tol, innerproduct, callback, restart, startiteration, printrates, reltol)\u001b[0m\n\u001b[0;32m    699\u001b[0m     \u001b[1;32mfor\u001b[0m \u001b[0mk\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mm\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    700\u001b[0m         \u001b[0mstartiteration\u001b[0m \u001b[1;33m+=\u001b[0m \u001b[1;36m1\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 701\u001b[1;33m         \u001b[0mh\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mq\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0marnoldi\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mA\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mQ\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mk\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    702\u001b[0m         \u001b[0mH\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mh\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    703\u001b[0m         \u001b[1;32mif\u001b[0m \u001b[0mq\u001b[0m \u001b[1;32mis\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;32m~\\Anaconda3\\envs\\ngsolve\\lib\\site-packages\\ngsolve\\krylovspace.py\u001b[0m in \u001b[0;36marnoldi\u001b[1;34m(A, Q, k)\u001b[0m\n\u001b[0;32m    657\u001b[0m         \u001b[0mh\u001b[0m\u001b[1;33m[\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;36m0\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    658\u001b[0m         \u001b[1;32mfor\u001b[0m \u001b[0mi\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mrange\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mk\u001b[0m\u001b[1;33m+\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 659\u001b[1;33m             \u001b[0mh\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0minnerproduct\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mQ\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m,\u001b[0m\u001b[0mq\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    660\u001b[0m             \u001b[0mq\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdata\u001b[0m \u001b[1;33m+=\u001b[0m \u001b[1;33m(\u001b[0m\u001b[1;33m-\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m*\u001b[0m \u001b[0mh\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m*\u001b[0m \u001b[0mQ\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    661\u001b[0m         \u001b[0mh\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mk\u001b[0m\u001b[1;33m+\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mnorm\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mq\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
      "\u001b[1;31mKeyboardInterrupt\u001b[0m: "
     ]
    }
   ],
   "source": [
    "%%time\n",
    "mesh_radial = Nanosphere(40, 10, 300, 600, mt_model=\"radial\")\n",
    "sim_radial = Simulation(mesh_radial)\n",
    "sim_radial.RefineMesh(percentage=.3)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "DoF:  143736\n",
      "Max Error:  6.860739822228391\n",
      "DoF:  193610\n",
      "Max Error:  2.2895126833634922\n",
      "DoF:  233847\n",
      "Max Error:  3.1574208197054836\n",
      "DoF:  308832\n",
      "Max Error:  2.1492926753578083\n",
      "DoF:  561475\n",
      "Max Error:  3.0791026153411125\n",
      "DoF:  609429\n",
      "Max Error:  2.991263085888792\n",
      "DoF:  652523\n",
      "Max Error:  2.9371425526945574\n",
      "Wall time: 20min 34s\n"
     ]
    }
   ],
   "source": [
    "%%time\n",
    "mesh_cylinder = Nanosphere(40, 10, 300, 600, mt_model=\"cylinder\")\n",
    "sim_cylinder = Simulation(mesh_cylinder)\n",
    "sim_cylinder.RefineMesh()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "%%time\n",
    "ext_list_radial = np.array([sim_radial.Extinction(wavelength) for wavelength in wavelength_list])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "output_type": "stream",
     "name": "stdout",
     "text": [
      "Wavelength:  400.0\n",
      "Wavelength:  403.0\n",
      "Wavelength:  406.0\n",
      "Wavelength:  409.0\n",
      "Wavelength:  412.0\n",
      "Wavelength:  415.0\n",
      "Wavelength:  418.0\n",
      "Wavelength:  421.0\n",
      "Wavelength:  424.0\n",
      "Wavelength:  427.0\n",
      "Wavelength:  430.0\n",
      "Wavelength:  433.0\n",
      "Wavelength:  436.0\n",
      "Wavelength:  439.0\n",
      "Wavelength:  442.0\n",
      "Wavelength:  445.0\n",
      "Wavelength:  448.0\n",
      "Wavelength:  451.0\n",
      "Wavelength:  454.0\n",
      "Wavelength:  457.0\n",
      "Wavelength:  460.0\n",
      "Wavelength:  463.0\n",
      "Wavelength:  466.0\n",
      "Wavelength:  469.0\n",
      "Wavelength:  472.0\n",
      "Wavelength:  475.0\n",
      "Wavelength:  478.0\n",
      "Wavelength:  481.0\n",
      "Wavelength:  484.0\n",
      "Wavelength:  487.0\n",
      "Wavelength:  490.0\n",
      "Wavelength:  493.0\n",
      "Wavelength:  496.0\n",
      "Wavelength:  499.0\n",
      "Wavelength:  502.0\n",
      "Wavelength:  505.0\n",
      "Wavelength:  508.0\n",
      "Wavelength:  511.0\n",
      "Wavelength:  514.0\n",
      "Wavelength:  517.0\n",
      "Wavelength:  520.0\n",
      "Wavelength:  523.0\n",
      "Wavelength:  526.0\n",
      "Wavelength:  529.0\n",
      "Wavelength:  532.0\n",
      "Wavelength:  535.0\n",
      "Wavelength:  538.0\n",
      "Wavelength:  541.0\n",
      "Wavelength:  544.0\n",
      "Wavelength:  547.0\n",
      "Wavelength:  550.0\n",
      "Wavelength:  553.0\n",
      "Wavelength:  556.0\n",
      "Wavelength:  559.0\n",
      "Wavelength:  562.0\n",
      "Wavelength:  565.0\n",
      "Wavelength:  568.0\n",
      "Wavelength:  571.0\n",
      "Wavelength:  574.0\n",
      "Wavelength:  577.0\n",
      "Wavelength:  580.0\n",
      "Wavelength:  583.0\n",
      "Wavelength:  586.0\n",
      "Wavelength:  589.0\n",
      "Wavelength:  592.0\n",
      "Wavelength:  595.0\n",
      "Wavelength:  598.0\n",
      "Wavelength:  601.0\n",
      "Wavelength:  604.0\n",
      "Wavelength:  607.0\n",
      "Wavelength:  610.0\n",
      "Wavelength:  613.0\n",
      "Wavelength:  616.0\n",
      "Wavelength:  619.0\n",
      "Wavelength:  622.0\n",
      "Wavelength:  625.0\n",
      "Wavelength:  628.0\n",
      "Wavelength:  631.0\n",
      "Wavelength:  634.0\n",
      "Wavelength:  637.0\n",
      "Wavelength:  640.0\n",
      "Wavelength:  643.0\n",
      "Wavelength:  646.0\n",
      "Wavelength:  649.0\n",
      "Wavelength:  652.0\n",
      "Wavelength:  655.0\n",
      "Wavelength:  658.0\n",
      "Wavelength:  661.0\n",
      "Wavelength:  664.0\n",
      "Wavelength:  667.0\n",
      "Wavelength:  670.0\n",
      "Wavelength:  673.0\n",
      "Wavelength:  676.0\n",
      "Wavelength:  679.0\n",
      "Wavelength:  682.0\n",
      "Wavelength:  685.0\n",
      "Wavelength:  688.0\n",
      "Wavelength:  691.0\n",
      "Wavelength:  694.0\n",
      "Wavelength:  697.0\n",
      "Wavelength:  700.0\n",
      "Wall time: 2h 11min 41s\n"
     ]
    }
   ],
   "source": [
    "%%time \n",
    "ext_list_cylinder = np.array([sim_cylinder.Extinction(wavelength) for wavelength in wavelength_list])"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "output_type": "display_data",
     "data": {
      "text/plain": "<Figure size 432x288 with 1 Axes>",
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\n"
     },
     "metadata": {
      "needs_background": "light"
     }
    }
   ],
   "source": [
    "plt.figure()\n",
    "plt.plot(wavelength_list,-ext_list_radial,label=\"Radial Model\")\n",
    "plt.plot(wavelength_list,-ext_list_cylinder,label=\"Cylinder Model\")\n",
    "plt.grid()\n",
    "plt.legend()\n",
    "plt.show()\n"
   ]
  }
 ]
}