{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Fraunhoferova difrakcija na dvostrukoj pukotini\n",
    "#### Kod je pisan u Python programskom jeziku koristeći Jupyter notebook"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import math\n",
    "\n",
    "from scipy.fftpack import fft      #paket za FFT\n",
    "from scipy.fftpack import ifftshift,  fftshift\n",
    "\n",
    "from mpl_toolkits.mplot3d import Axes3D   #paket za 3d plot\n",
    "plt.style.use('dark_background')          # izbor boja za plot\n",
    "plt.rcParams['image.cmap'] = 'plasma'"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": [
    "\n",
    "def Fraunhofer_input(lambd,w,z):\n",
    "    N=1048   #rezolucija\n",
    "    L=5.    # širina zaslona na kojoj se javlja difrakciona slika\n",
    "\n",
    "    lamb=lambd*10**(-6) #(mm) talasna dužina svjetlosti\n",
    "#    w širina otvora (mm)\n",
    "#    z= udaljenost otvor - zaslon (mm)\n",
    "    k=2*np.pi/lamb   #talasni broj \n",
    "\n",
    "    delta_src=L/N     #prostorna frekvencija\n",
    "    \n",
    "    #definisati ravan otvora\n",
    "    xv=np.linspace(-N/2,N/2-1,N)\n",
    "    yv=np.linspace(-N/2,N/2-1,N)\n",
    "    [x1,y1]=np.meshgrid(xv,yv)\n",
    "    x1=x1*delta_src  #(mm)\n",
    "    y1=y1*delta_src  # (mm) \n",
    " \n",
    "    #definisati dvostruku pukotinu\n",
    "    X=np.where(np.abs(x1)<w/4,0,0)\n",
    "    Y=np.where(np.abs(y1)<10*w,1,0)\n",
    "    X[np.logical_and(x1<-1*w, x1>-3*w)]=1.0\n",
    "    X[np.logical_and(x1<3*w, x1>1*w)]=1.0\n",
    "\n",
    "    u1=X #elekticno polje na pukotini\n",
    "    ap1=u1\n",
    "\n",
    "# Fourierova transformacija  izračunavanje integrala\n",
    "    g=u1\n",
    "    G=fftshift(np.fft.fft(g))\n",
    "    h=np.exp(1j*k*z)/1j*lamb*z*np.exp(1j*np.pi/(lamb*z)*x1**2)\n",
    "    H=fftshift(h)\n",
    "    u2=H*G\n",
    "    identity=np.ones((N,N))\n",
    "    u2=u2*identity\n",
    "    \n",
    "    # Intenzitet zračenja (normiran na jedinicu)\n",
    "    I=1./(lamb*z)**2*(np.abs(u2))**2\n",
    "    I_1d=np.zeros(N, dtype='complex128')\n",
    "    for a in range (1,N):\n",
    "        I_1d[a]=I[0][a]\n",
    "        \n",
    "    \n",
    "    I_1d=I_1d/I_1d.max()\n",
    "        \n",
    "    return(u2,I_1d,y1,ap1) #OUTPUT: električno polje na zaslonu, intenzitet, koordinate ravni otvora i polje na otvoru"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {
    "collapsed": true,
    "scrolled": true
   },
   "outputs": [],
   "source": [
    "lamb=632.\n",
    "w=0.05\n",
    "z=20.\n",
    "\n",
    "u1,I1,x1,ap1=Fraunhofer_input(lamb,2*w,1000.)\n",
    "u2,I2,x2,ap2=Fraunhofer_input(lamb,w/5,1000.)\n",
    "u3,I3,x3,ap3=Fraunhofer_input(lamb,w,1000.)\n",
    "\n",
    "I1=I1/I1.max()\n",
    "I2=I2/I2.max()\n",
    "I3=I3/I3.max()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
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np9na3NS/WzXr16y7du1alZeXKz8/X/fdd59OPPFE9e7du873P5L62DEXOLds2aJevXr5\nX19xxRVq06aN/vGPfygrK0tZWVmKj4/XTTfdFDBd796969zz0L59e3344YeaOHGi/9dYMFW/IOsq\nF1xwQfMsZDNKSUnRhRdeqEGDBiklJUWffvqpBgwYoMTERKWkpNQ53aJFi+pczkWLFgWdJjU1Vd27\ndw/4wJ9xxhlKTU1t9uVC86nZp2oqKChQcnJyrT109KnDq0/l5eVpz549OuOMMxqsi5ZVs48tX75c\nw4YNU0RERL3T1dfHwsLC9NFHH+n555/X4sWL65xHQkJCvX2s5s6Zw8H69et18skn64orrlBKSoq2\nb9+uLl266NJLL623j73yyit1LufWrVuDTvP999/L6XTqpJNO8g+rr9+kpqY2qY8ZY2Sz2Rpa5CPC\nMRc4Fy1apMTERP/r8ePH6/XXX9dpp52mvn37qm/fvhowYID69u2rU089VZLv8GDbtm31+eef15qf\nw+HQ+++/r3feeUfz5s2r970//fRTRUdH11lqHnKsLjQ0VCEhIbX+3xyMMQHrpLq0tDQVFxfrhhtu\n0Jo1a+R2u7V3715deeWV9XbckSNH1rmcI0eODDrNzp079c0332jKlCkKDQ3VmDFjdPrpp+v9998P\nWt9utys0NFROpzPg/2hZNftUTZGRkbr22msDvlTpU4dnn5o1a5Yee+wxxcbG6uSTT9aECRP01ltv\n+ceHhIQoNDS01v9hrZp9bPbs2crIyND777+vk08+WTabTW3bttUjjzyiESNGSPJtn7PPPlvLli0L\nOs833nhDO3bs0DPPPFPve2dkZNTbx5KTk+ucNjQ01P8Zqf7/5pCenq7x48cHHVdcXKyvvvpK99xz\nj79PrV+/Xn/4wx/q7WN33XVXnctZlQdqOnjwoD744ANNmzZNEREROv/88zV69GjNnj07aP1Zs2bp\nf/7nf9SpUyedcMIJmjRpkr+P9enTR2eccYbsdrsiIyM1Y8YM7d69W9u3b2/Cmjl8HXOBc9asWRo5\ncqTCwsLUqVMnDRkyRM8//7z27t3rL19//bUWL17s/zCPGzdOb7/9tsrKymrNr3Pnzho4cKDuv//+\ngF9DCQkJzdbmrl27qqSkRNu2bZMklZSU6LvvvmuWecfHx8vtduvbb7+ts05KSopycnKUkZHhf22z\n2bRp06ZmaUN11157rc455xzl5ubqb3/7m6666ir/4dRx48YF/Mq88cYbVVJSon/+858aOHCgSkpK\nlJSU1OxtQv2q96kqnTp18veFXbt2qW3btrr++uv94+lTh2efmjJlin744Qft2rVLKSkpeuaZZ7Rk\nyRL/+O+++04lJSXq3Lmzli5dqpKSEnXt2rXZ24xANftYWVmZhg4dqh07dmjZsmUqKCjQF198ofbt\n22vDhg2SpMsvv1yrV69WVlZW0Hled911uuKKKyw9IlBSUqKioiJJhz47zcHlcqldu3ZBf7BWSUlJ\nkcvl0hdffOF/HRMTozVr1jRLG6q7++67FR4ern379undd9/VXXfd5f9uqXlu7KuvvqqFCxfq22+/\n1datW/Xf//5Xr776qiTp+OOP19y5c1VQUKAff/xR3bp102WXXRb0/PUjlWVXJB2u5amnnmr0rUdC\nQkLM9u3bzXHHHdfq7baiXH/99ebpp59u9XZQjuxCnzpU6FMUK0pT+pgk8/nnn5vf/e53rd5uK8qA\nAQNMcnJyq7eD0rRiq/wPAAAAYIlj7pA6AAAAWhaBEwAAAJYicAIAAMBSR9w9ZKJCn5ZTNjmMXVHG\npRA5JEll8ijHXqIo45JDNpXJq2JbhZyyqUJGbUyIIoxLTtlVJo8KbGXyyihMjoC6kuQwdrU34Qox\ndnlt0kGVK9deokjjkiSVyCOPzSuH8eX1WBOqGBMih+xy28qUbSuWS3aFGocqbF4V2crlMg4V2yoU\nZ0LV3huuKONSqc2jXFupsuxFaucNk9dmlGsrVRsT4n+fk71xauN1ySab3LZyfevMVjtvuJyyq9BW\nJo+MIo1LOfZi9fG0U7eKSLWTQzny6HunW3vtRYr3RqlcXuXZStXJG6kCW5nC5dTjfdw67bytCosp\nUvrmkzRjeR89etk3Ou3B/6qgf6liNoTq22cv1dP/6atJQ7fpxDPSVFIQqW8/P1VPbotWsSoUY0K0\nx16kWBMql+zabS/U8d5I9aqI9rfjJ2eRtjly1M4briJbuRyyKcqEqEJe5diLdVpFe0Ubl4yM8u3l\n+s6eq7DK7ZpvK1OcCZXd2JRjL9EJ3kjFmVCFGocKbeXKthcr11aqcONUuc2jSOOS09hVavOoXF51\n8kYqVE555FWBrUx5tlJJ8m+/qvcpspUrzhumCLlkN1KZzatsW7E8Nt+N3itkFG6cCpFdJfLILpti\nTIhC5FCFvDpoK1e+rcz/eauq65FRoa1c7bxhAZ/VQlu5PDavKmRUWPpoS3SdRrtd78ojo3IZldt8\n/5bZvCq1eXRQFSqxeXTQVqFCW5lybaU6rvLzHK0QRRqnorxOxRmnomVXhE2KcnkVG1muiPAyRYSX\nKSysTOHhJYqMOqjQsFK5QssVElYmV2i5QiNK5AypkCOkXA6XR3ZXhRyhFbI7PbLZjWwOr2SrPO3c\n2GSMTcZjl7fcIW+FQ95yhzxlTnnKXCopDFN5cYjKSkJUcjBMJcVhKsiLVlFRuAoKw1VQFKrcIqf2\neKQcW4X220u0z16sElXoBBOpDt4wtfe61N5mV0KbUsVGl6hNmyJFRxcqKqZIse3zFBZdrNCoYoXG\nFMsVVSJX+0LZIktliyqTIivkifPIGyZ5w2zyhNpkXJLX5ZGxe/3r2+a1y17ukK1ccpQa2UuM7CWS\nI9chFTllCkNkikJVnh2l8sIwlRaEq7QwXCXucOVlx6qwIFJud5Ty8yOV5w5TRn6oso1X2fZy7bOX\nKMtWpDA51cEbruO8YWpnnOrkkOIiKxQTWaqYqGJFRhYrJtatsPAShUWU+LZHeJnCokp82yKkQnaX\nR3anR3aXRzaHVzabCdwWHruM1yZvhUOeUqe85U55yh3ylLlUUeZU6cEwlZe6VFYSovJSl0pLQlVU\nGKHi4jCVlIToYLGv5BW5VFhu10EjueVVrq1ChfYKFdkq5FaZCm3l2m8vVpwJVZQJUYRxKsw4FCGn\nQo1DIcYul2xyGZtcsskhm17Tda3Qk4KLCn3a//0gSR4Zldgq5DB2tTVhijBOhcohl7HLKbu8Miq1\neVQqX79z28pULq/C5JDT2OW1GZXIo2JbhUKNwz9ckkptvu+aOBOqGBOqtt5QRRinXLLLLt/3WpGt\nQoW2cuXZSpVnK1WEnAoxDtllU4W8KrN5VCKP/++tU3ZVyKsDthJFyKn23nC1N2GK87rU1jgVWvl3\ntERGBTaPMu3F+sV+UAdsJWpvwtXGhMgrqdhWoTxbiTwy6uKNVrjx/QUutFUoy16oPp62Ot0ToVM7\nudW9+251TNirtgn7ZbNJxfkR2v/z8Vq07Ey9Z3J1RkWsxvbZp7MHblKnazequI9H5THlchW4FL7N\noT1z+umrNWfqg20dtNmZp6ttcRp58SYd12WvwtsclDHSgYzj9EvG8frxx3ht3ROtLY6D2uY4oBO8\nUYoyTpnKNv9sd8shm2JNmMKNU3b5/k5l24rV1oSpozdCnb3hijEOhVWui1IZHbBVKNdermxbibLt\nxTqoCrU1Yf71WfV3IUwOhRiHf9tXZZVYE6pYE6oo41Kkccopm7ySyuXVQVuFDthLVWArVa6tVFHG\npVDj+3tTYfOqRB6V2jwKN06FySG7sfmHu2RXdGU/CpVDodW2fbnN6//cHbCVyGPzKsw45ahcrqrs\n1Ni/YezhBAAAgKUInAAAALAUgRMAAACWInACAADAUgROAAAAWIrACQAAAEsROAEAAGApAicAAAAs\nReAEAACApQicAAAAsBSBEwAAAJYicAIAAMBSBE4AAABYisAJAAAASxE4AQAAYCkCJwAAACxF4AQA\nAIClCJwAAACwFIETAAAAliJwAgAAwFIETgAAAFiKwAkAAABLETgBAABgKQInAAAALEXgBAAAgKUI\nnAAAALAUgRMAAACWInACAADAUgROAAAAWIrACQAAAEsROAEAAGApAicAAAAsReAEAACApQicAAAA\nsBSBEwAAAJYicAIAAMBSBE4AAABYisAJAAAASxE4AQAAYCkCJwAAACxF4AQAAIClCJwAAACwFIET\nAAAAliJwAgAAwFIETgAAAFiKwAkAAABLETgBAABgKQInAAAALEXgBAAAgKUInAAAALAUgRMAAACW\nInACAADAUgROAAAAWIrACQAAAEsROAEAAGApAicAAAAsReAEAACApWySTGs3AgAAAEcv9nACAADA\nUgROAAAAWIrACQAAAEsROAEAAGApAicAAAAsReAEAACApQicAAAAsBSBEwAAAJYicAIAAMBSBE4A\nAABYisAJAAAASxE4AQAAYCkCJwAAACxF4AQAAIClCJwAAACwFIETAAAAliJwAgAAwFIETgAAAFiK\nwAkAAABLETgBAABgKQInAAAALEXgBAAAgKUInAAAALAUgRMAAACWInACAADAUgROAAAAWIrACQAA\nAEsROAEAAGApAicAAAAsReAEAACApQicAAAAsBSBEwAAAJYicAIAAMBSBE4AAABYisAJAAAASxE4\nAQAAYCkCJwAAACxF4AQAAIClCJwAAACwFIETAAAAliJwAgAAwFIETgAAAFiKwAkAAABLETgBAABg\nKQInAAAALEXgBAAAgKUInAAAALAUgRMAAACWInACAADAUgROAAAAWIrACRzFxo8fr7Vr1/7q6d94\n4w0dOHBAGzZsaMZWWS89PV1DhgyRJD3yyCNKSkryjxszZox+/vlnud1u9e3bt8nz/rXrdOvWrUpM\nTAzaJislJiYqIyOjRd7rt1i1apVuu+22Vm1D165dZYyRw+H4zfNKSEiQ2+2W3c6fWUCSnK3dAOBo\nlJ6eruOPP14ej8c/rFevXsrKymrFVjXNBRdcoIsvvlidO3fWwYMHW7s5v9r06dMDXj/77LOaOHGi\nPv744xZtx6mnnlpnm45kXbt21U8//SSn0xnweT/WpKen6/bbb9eKFSskSRkZGYqOjm7lVgGHD356\nARYZNWqUoqOj/SVY2GyOPSlWqQoSvyZsHu7LlZqaGnTc4dzuIxnrFQCBE2hBVYfsbr31Vu3atUsr\nV66UJM2bN09ZWVnKy8tTSkqK+vTp45+m5qHGmod0jTH6wx/+oO+//14HDhzQyy+/XOt9n3nmGR04\ncEA//vijhg8f7h9+wgknaMGCBcrJydHOnTt1++23S5JuvfVWvfbaa/r9738vt9utqVOnSpIuvfRS\nbdq0Sbm5uVq3bp1OO+00/7zS09P10EMPafPmzSoqKpLD4dApp5yiVatWKTc3V1u3btWoUaMkSf37\n91dWVlbA4cYxY8Zo8+bNkqR+/fpp/fr1ys3N1Z49e/TSSy/J5XLVuV5vuOEG/fTTT8rOztajjz4a\nMG7KlCmaPXu2QkJC5Ha75XQ6tXnzZqWlpdXZ7ocfflhpaWkqKChQamqqxowZU+d7/+///q/Wrl2r\nmJgYSdLtt9+ubdu2+ac988wz/e9TdZi/qk1V6tv+TRUWFqY333xTBw4cUGpqqvr16+cf9/DDD+u9\n994LqP/888/rhRdekFT350HybZONGzcqPz9fv/zyi2bMmCFJWrNmjSQpLy9Pbrdb5513nsaPH69P\nP/1U//d//6ecnBxNnTq11jLXd/i6Y8eO2rx5syZNmiRJuvnmm/3r9IcfftAdd9xR5/JXvfeLL76o\nvLw8bd++XYMHD/aPr74dpNrborqxY8cqPT1dv/vd7yT5fkRu3bpVubm5WrVqlU455RRJ0qxZs9Sl\nSxctXLhQbrdbkydPrrV8q1at0rRp0/Tpp5+qoKBAS5YsUbt27fzv1ZyfAeBwZSgUSvOW9PR0M2TI\nkFrDu3btaowx5u233zYREREmLCzMSDK33HKLiYqKMiEhIea5554zmzZt8k+zatUqc9ttt/lfjx8/\n3qxdu9b/2hhjFi5caNq0aWMSEhLMvn37zLBhw/x1y8rKzO23327sdru58847ze7du/3Trl692syc\nOdOEhoaaM844w+zbt88MHjw46PuceeaZZu/evebcc881drvd3HTTTSY9Pd2EhIT4l3nTpk2mc+fO\nJiwszDidTrNz507zyCOPGJdCmbFFAAAgAElEQVTLZS666CJTUFBgevXqZSSZtLQ0M3ToUP/8582b\nZx5++GEjyZx11lmmf//+xuFwmK5du5pt27aZ++67L+i67t27t3G73ebCCy80ISEhZsaMGaa8vNy/\n/qdMmWJmz54dsL569OgRsK2qt1uSueqqq8wJJ5xgbDabueaaa0xhYaHp2LFjwHqx2WzmX//6l1m8\neLEJDw/3T5eZmWnOOeccI8n06NHDdOnSpdZnomab6tv+TS3Tp083a9asMXFxcaZz587m22+/NRkZ\nGUaS6dKliykqKjLR0dFGkrHb7WbPnj2mf//+DX4e1q9fb2644QYjyURGRvqnqfpMOxyOgM9oeXm5\nmThxonE4HCYsLKzWMtecrupz3rVrV/Pdd9+ZCRMm+OuOHDnSdO/e3UgyAwcONEVFRebMM88MuvxV\n733//fcbp9NprrnmGpOXl2fi4uKC9s3q7arepptvvtns3LnT/1np2bOnKSwsNEOHDjVOp9NMnjzZ\n7Ny507hcrqDzDbZ8aWlppmfPniYsLMysWrXKTJ8+3ZLPAIVymJZWbwCFctSV9PR043a7TW5ursnN\nzTUffvihkQ79ETrxxBPrnLZNmzbGGGNiYmKM1LjAOWDAAP/ruXPn+oPb+PHjzc6dO/3jwsPDjTHG\nHH/88aZz586moqLCREVF+cc//fTT5s033wz6Pv/4xz/MtGnTAtq6Y8cOM3DgQP8y33LLLf5xF1xw\ngcnKyjI2m80/LDk52UyZMsVIMk8++aR5/fXXjSQTFRVlCgsL/eGsZrnvvvvMBx98EHTc448/bt59\n913/64iICFNaWtqkwFm93cHKpk2bzOWXX+5fL59//rmZM2eOmT9/vj9wSDKLFy829957b52fibra\nVN/2b2r54Ycf/D84JJkJEyb4A6cks3btWnPjjTcaSWbo0KEmLS3NSGrw85CSkmKmTp1q2rVrF/B+\ndQXOXbt2BdRrTOCcMWOGSU9PN9dee229y/jhhx/WuZ7Hjx8f8KNKktmwYYM/LDcmcE6aNMmkpqaa\n+Ph4f73HHnvMzJ071//aZrOZzMxMk5iYGHS+wZbvz3/+s3/8XXfdZT755BNLPgMUyuFYOKQOWGTM\nmDGKi4tTXFycrrjiioBx1a8attvtmj59utLS0pSfn6+ffvpJktS+fftGv9cvv/zi///BgwcVFRUV\ndFxxcbEkKSoqSp06ddKBAwdUWFjoH79r1y7Fx8cHfY+uXbtq0qRJys3N9ZeEhAR16tQp6HJ16tRJ\nGRkZMsYEnX9ycrLGjh2rkJAQjR07Vl9//bV+/vlnSVLPnj21cOFCZWVlKT8/X08//XSd66Pqfaov\nf05OTj1rq7aaV3HfeOON/lMHcnNzdeqppwa8/0knnaTRo0friSeeUHl5uX94QkKCfvjhhya9d1O2\n/wUXXCC32y23262tW7cGnV/N9bFr166A8cnJybruuuskSePGjVNycrJ/uvo+D7fddpt69eqlHTt2\n6IsvvtCll15a73L9mivjr7/+eu3evVvz588PGD58+HB99tlnysnJUW5urkaOHFlv/9i9e3fA6127\ndgV8ThsyefJkzZw5M2A+nTp1CliXxhhlZGTU2V+CqaufNsd3AHC4I3ACraB6CBs3bpxGjx6toUOH\nqk2bNurWrZskyWazSZKKiooUERHhr9+xY8dmacOePXvUtm3bgHDapUuXWn+sq2RkZOipp57yh+i4\nuDhFRkZqzpw5QZdrz549SkhI8C9Hzflv375du3bt0ogRIwKCjyS98sor2rFjh3r27Kk2bdro0Ucf\nDZhPdVlZWUpISPC/Dg8PDzg3rjGqt7tLly5KSkrSxIkT1a5dO8XFxWnr1q0B7799+3bdcsst+uST\nT9SrV6+AddSjR48mvXdD27+6Tz/91H8RWvWr3quruT66dOkSMP69997ToEGDFB8fryuuuMK/3hv6\nPKSlpWncuHHq0KGD/v73v2v+/PmKiIgIWHfV1RzemM/x1KlTlZ2dreTkZP/5vSEhIXr//ff17LPP\n6vjjj1dcXJwWLVpU5+dBUq0Q2KVLF+3Zs6fR7bjkkkv02GOPaezYsf5he/bsUdeuXQPqJSQk+NdP\nXeuhMZryGQCOVAROoJVFR0ertLRUOTk5ioiI0NNPPx0w/ptvvtHYsWMVHh6uHj16NNu9CjMzM7V+\n/XpNnz5doaGhOu2003TbbbfpnXfeCVo/KSlJd955p84991xJUkREhEaOHBkQUKrbsGGDioqK9NBD\nD8npdCoxMVGjRo0KCKjJycm69957NXDgwICLWaKjo1VQUKDCwkKdfPLJuuuuu+pcjvnz5+uyyy7T\ngAED5HK5NG3atN9078PIyEgZY7R//35JvgtWgoW7OXPm6NFHH9Xy5cvVvXt3SdJrr72mBx98UGed\ndZYkqUePHrUCX00Nbf+mmjdvnh555BHFxsYqPj5ef/zjHwPGZ2dna/Xq1XrzzTeVnp6uHTt2SGr4\n83D99derffv2MsYoLy9PkuTxeLR//355PB7/OqjLN998o4EDByohIUExMTF65JFHatUpLy/X1Vdf\nrcjISM2ePVs2m00hISEKDQ3V/v37VVFRoeHDh+uSSy6p9706dOige++9V06nU1dddZV69+6tRYsW\n+dtx7bXXyul06uyzz9ZVV11Va/rU1FQNHz5cM2fO9F/oNm/ePF166aUaPHiwnE6nJk2apNLSUq1f\nv16StHfv3gbXQV2a+zMAHI4InEArmzVrlnbt2qXdu3dr27Zt+vzzzwPGP/fccyorK9PevXv19ttv\n1xkIf43rrrtO3bp10549e/Thhx9qypQpWr58edC6X331lSZMmKCXX35Zubm5SktL080331znvMvL\ny3X55ZdrxIgRys7O1j/+8Q/ddNNN+u677/x13n33XQ0aNEgrV64MOAz+4IMPaty4cXK73UpKStLc\nuXPrfJ9t27bpnnvuUXJysrKyspSbm6vMzMymr4xK27dv14wZM/TZZ59p7969Ou2007Ru3bqgdWfN\nmqVp06Zp5cqV6tq1q+bPn6+nnnpKycnJcrvd+uijj9S2bdt636+h7d9UTzzxhHbt2qX09HQtXbo0\n6BXYycnJuvjiiwP2Kkv1fx6GDx+u1NRUud1uvfDCC7r22mtVWlqq4uJiPfXUU1q3bp1yc3PVv3//\noO1avny55s6dqy1btuirr77Sf/7zn6D1ysvLNXbsWHXo0EFvvPGGioqKdO+992revHnKzc3VuHHj\nGryH6oYNG9SzZ09lZ2frqaee0lVXXaUDBw5Ikh5//HH16NFDubm5euKJJ2qtgypbtmzRZZddpqSk\nJA0fPlzff/+9brjhBr300kvKzs7WqFGjNGrUKP8pFdOnT9djjz2m3Nxc/9X1jdXcnwHgcGST72RO\nAEALeeKJJ9S5c+dWf7LO0Wj8+PG6/fbbdeGFF7Z2UwBUwx5OAGhhffr0UXp6ems3AwBaDI+2BIAW\n9PXXX6u0tFQTJ05s7aYAQIvhkDoAAAAsxSF1AAAAWIrACQAAAEsdcedw7tu3r9aTMwAAANDyunbt\nqg4dOjRY74gLnLt27VK/fv1auxkAAADHvI0bNzaqHofUAQAAYCkCJwAAACxF4AQAAIClCJwAAACw\nFIETAAAAlrIscL7++uvau3evvv322zrrvPDCC9q5c6c2b96sM88806qmAAAAoBVZFjjfeustDR8+\nvM7xI0aMUM+ePdWzZ0/dcccdeuWVV6xqCgAAAFqRZYFz7dq1OnDgQJ3jR48erVmzZkmSNmzYoNjY\nWHXs2NGq5gAAAKCVtNo5nPHx8crIyPC/zszMVHx8fGs1BwBayE+SvJWlvHWbAgAtpNWeNGSz2WoN\nM8YErTthwgTdcccdkqT27dtb2i4AsFYXLV/u+60/dKhXUomksFZtEQBYrdX2cGZmZiohIcH/unPn\nztqzZ0/QuklJSerXr5/69eun7OzslmoiADSzMkk22e2SwyH99792SSGt3SgAsFyrBc6PP/5YN910\nkySpf//+ys/P1y+//NJazQGAFuCUZOTx+F6F+XdsFrVSewCgZVh2SD05OVmDBg1S+/btlZGRoSlT\npsjlckmSXn31VS1atEgjR45UWlqaDh48qFtuucWqpgDAYWCe/3/O7yX1kvIKJMkmDqkDONrZJAU/\ncfIwtXHjRvXr16+1mwEATVQuyak5c2w6/jhJHumiSyTfxUMSz+EAcCRqbC7jGw4AWoRDklFsrHzf\nvE5p1bLq43NapVUA0BIInADQgv72N0lVtyh2SL49nDZJbVqrSQBgOQInAFju0N01Vq+WBl0p3xH2\nkqpxRnwdAziatdp9OAHg2BEr315MjxYvlla7JJVIF14qSR116DxOADg68ZMaACxX9aCLQjmd8n3z\nhklrl9est7olGwUALYbACQCWq7ohSKyGDpWUWTnI/w1sKgec3yqtAwCrETgBoIUNulFSsSrP4ZSk\nisp/Ha3SHgCwGoETACzlVvVbHi9bJq1eIWmjNHBkVZ0FOrSXEwCOPgROALBUeOW/vsDpcMh/9HzN\niqo617R8swCgBRE4AcBSVXstfcfPTxks6Wv5jp7bpeTkVmoWALQgAicAWKrqcHqUJN9T0wc9KClP\n0kHpX/+qqld1SL2o5ZsIABbjPpwA0II2Vx5GHzTEFzFX+8eYyn9DW7pJAGA5AicAtKTKI+yrl0hy\nSh+5pTFjJN8h90hx4RCAoxGH1AHAMkWqfoW6JJ07WBo0WL6f+3YpvOqaIkWJK9UBHK3YwwkAlgmp\n/PdQ4PTHyQxJbaUFi1u4SQDQCgicAGCZqoNI5f4hG2qcw3lRi7cJAFoegRMALFN1OP3vgYMkrV4k\nKVRaXC4NH141suqQeoakhJZrJgBYjHM4AcByU/3/O7/qHE6XJLvkrPWz3ybp+BZrGQC0BAInALSG\ndZJypA8+qD7QU/kvX80Aji4cUgcAS0wNOnT9SkmmrnM43ZLaiivVARxtCJwAYImH5AuO3tqjbNLq\n9yXFSks90iWXVI1oV1mfwAng6MJxGwCwhKvyXxMw9IKqczjDJdklh6Ol2wUALY/ACQCWqPp69QQf\nPVJSmjRkSEu1BwBaD4fUAcBS+wJefbpSklcaNFQyE1qnRQDQ0tjDCQCWqLoH56H7aQ4adGjUakkp\nK6Xly2tOV3UvzkLLWwgALYU9nADQQlavlpavlqpO21wtyV7rZ3/VOZ+hLdMoAGgB7OEEgFZgJGma\nNHhwzTFVV7Xz9Qzg6MEeTgBodvOCDl2wQFobLckjJV4sJa4OVqtAvtsjAcDRg5/QANDsLtOhczgP\ncVXdKanyNpspK4Kdw9leh87jBICjA3s4AaDZBb8H58iRUoV853AaSbJJdnIlgGMAgRMAml0D9+Cs\nlDiYw0wAjg0ETgCwTFbAq8WLpbUhkiqkxEuCTwEARyN+XANAs6s6f7NbwFD/LZCqncO5YkWw6avO\n4XRb1D4AaFns4QSAFnLJJb6D7HYdOocz+Cmc3IsTwNGFwAkAraTuczirAicHoQAcHQicANBCli2T\n1jgklUuJw+qrWS7f1zOXsAM4Olj683nYsGHasWOHdu7cqYcffrjW+ISEBK1cuVJff/21Nm/erBEj\nRljZHABoARkKdg9OSbLVyI91n8P5H3EvTgBHG2NFsdvtJi0tzZx44onG5XKZb775xvTu3Tugzquv\nvmruvPNOI8n07t3bpKenNzjfjRs3WtJeCoVCaZ5SYiRjJE/Q8R7fSOOVzKqVMitX1jUfb2Vp7eWh\nUCiUuktjc5llh9TPPfdcpaWlKT09XZI0Z84cjR49Wtu3b/fXMcYoJiZGktSmTRvt2bPHquYAQAup\n+lo1DdbkPpwAjhWWBc74+HhlZGT4X2dmZqp///4BdaZOnaqlS5fqj3/8oyIjIzV06FCrmgMALaTq\nMHjtm74vXy6tsUsqkhJHtWijAKBVWfbj2lbzZCX59mhWd9111+mtt95SQkKCRo4cqdmzZwedbsKE\nCdq4caM2btyo9u3bW9VkAGhG+Q3WSFkhrVzZAk0BgFZm2R7OzMxMJSQk+F937ty51iHz2267TcOH\nD5ckff755woLC1P79u21f//+gHpJSUlKSkqSJG3cuNGqJgNAM6i6YKhDrTFDh9a+D2fdTGXNHEnt\nmruRANCiLNvDuXHjRvXs2VPdunWTy+XStddeq48//jigzs8//6whQ4ZIkk455RSFhYXVCpsAcLRK\nHCwNHtxQraiWaAoAWMqyPZwej0cTJ07UkiVL5HA49MYbb2jbtm164okn9OWXX2rhwoWaNGmSkpKS\n9MADD8gYo5tvvtmq5gBAq1uxQlpjk/S1lPhgQ7W98u0TcFjeLgCwWvCbxR3GNm7cqH79+rV2MwCg\nDt7Kf2sfQFqxQrLbJE2TElf7zuE0trr2cpbI92hLrwidAA5Xjc1lPGkIAJrNl/WOHTLkUBxtWIak\nk35jewDg8EDgBIBm8zv5Dhw1HCuNpEFDpJQ6a/SsnA9PGwJw5OOewwDQbOq/6fuKFVJKjdsgxVvb\nIAA4LBA4AaDZVO2NbNyp8auXS5krpcq7vgHAUYtD6gDQbKoCZ0XQsbXO4ays3qaNlW0CgNZH4ASA\nZre3UbUGDfE9jyi2wZpTKwsAHJk4pA4AzabqTnPdgo5dubL2OZz1fwmbynlOaoa2AUDrYQ8nALQQ\nYyRbtYvOVy+XZJf+c1C67LL6pgy1uGUAYC0CJwC0kLruw+mo877uVU8b4mAUgCMbgRMAWsmgoVKx\npIg6a1TFU+7FCeDIxs9mAGghwc7hrD9K5lvYGgBoOezhBIBmkarGPmWoyuplkhzSknJp2LBgNTqI\npw0BOBoQOAGgWZzYYI3Bg4PHURt5EsBRjsAJAM2i/sdaBjPoYqlMXIMO4OjHOZwA0Cyqvk7rDpzB\nzuEEgGMBezgBoFlUHRf31F+tWh5dvUSSS1rmkS6+2Kp2AUDra3AP5/nnn9+oYQAASTpQ55jBg6XE\nIb7/N/7Ae9XThn75bc0CgFbUYOB86aWXGjUMAI5tVY+17NToKQYNkwYMbuzezYafuA4Ah6s6D6mf\nd955Ov/883XcccfpgQce8A+PiYmRo+7HYgAA6rBypZQiKXFwU6aq2hfK9y6AI1edgTMkJERRUVFy\nOp2Kjo72Dy8oKNBVV13VIo0DgKNO9XM4/yspXFrulYYOrWsCr3xhk3snAThy1Rk416xZozVr1uit\nt97Szz//rIiICB08eLAl2wYAR5Va9+Fs1D3iSyW5ROAEcCRr8BzOTp06KTU1Vdu3b5cknX766Zo5\nc6blDQOAo92gUdIFg+vbuylJM3TowiEAODI1GDiff/55DRs2TDk5OZKkLVu2aODAgZY3DACOHF/q\n0EVDdVu5UkpZ0dR5T/11TQKAw0ij7sOZmZkZ8NrjaeA+cwBwTOnT+KrVz+FMktRDWmGkIUOavVEA\ncNhoMHBmZGTo97//vYwxcrlcuvfee/2H1wEAUmMfa1nrHM7dknpY1CQAOIw0GDjvvPNOvfDCC4qP\nj1dmZqaWLl2qu+++uyXaBgBHiIYfa1mTkTRoqu+5RDzyDcDRrsHvuZNPPlk33HBDwLDzzz9f69ev\nt6xRAHBkafixlrNnS/HxUoo59LQhADhW8KQhAGg2BXWO8Z/6XmMn6NqV0ooGLySquko9/9c3DQBa\nEU8aAoDfrOoK9Q511rj5Zt+/jbr1Zp3CftPUANBa6tzDWfNJQ1WFJw0BaC4vSvo4yPDr5YtvX9Ux\nXV9JRZISLGpXS7pwcGOuUPftFn3xxQf0cY0VlpAgvfSS9P33UnGx5HZLX3whPfqoFBPjq9Oxo1RU\nJPXr15wtr771ula2sXrZL2m1pEtqTHc0bT0ATVHzWyKgdOnSpd7xLV02btzY6m2gUCi/vXSXTKlk\nzg4ybqlkTGU5tY7pP5LMW4fBcviKt7LUXWfRIpmVK2VWrZDxSqascvkqGjX/MtO9e5opLXWZs88+\nNPzCC2Vyc2W++05m4kSZQYNkLr5Y5vHHZXbvlvm//ztU9/nnZVavbq7l7W6kUiOdXfm6a+XmespI\n/SvL5UZaaqSyytfVp//ISG8dBtuNQqH81tLYXFbnIfXnnntODzzwgF5++WUZY2qNHz16dF2TAkCD\n7pe0WbX3YsZLGizpv5IulTRe0uQg078qaYGkRyRlWdfMZlNeLoWFqdYx9bUrpZXy3TKpbmW6//7n\ntXnzGfrqqy8lSbGx0vz50vbtvicVVX/y8LJl0owZ0vnnHxr26qvStm2+vZwbN/7Wpalr6/0oaUO1\n18sk5Uq6osbwI23rAfit6gycs2fPliQ9++yzLdYYAMeGEEk3SJoWZNyNkhzyPV+njXyH1x9W7XMf\nl8p3ic7NkqZb1M7mVPUbPdg5nEF+0wcICVmgG274t6ZNe1y+pxpJEyZIHTpII0cGhs0qBw9Ky5cf\ner19u7Rli3T77b81cNa39WoqkVQu37PgqzvSth6A36rOczi//vprSVKXLl309ddfa82aNf4SHR3d\nYg0EcPQ5T1KcpLVBxt0kaZt8sWqWpBNU+yxAyXcDos8kDbeojY23+ldNVZUxBzbiHM7zzrtecXF5\nWrv2Qv+woUOlrCzpq7pOdA1izRpp+G9eYfVtPbt8Pxcc8m25GfJd6PR+jXqHz9YD0DIadVuktWvX\n6pRTTvEPmzatMb9sASC48+Tb07elxvBzJfWWNLvy9VxJxfIdVg9mU+U0tjrGt4x+asxz1JcurXyW\n+vJ6qwV13nmS12vTli2n+4clJEg//dS0+WzaJHXpIp1wQtPbUK01Cr71JOlfkioqyx5Jd0m6Q1Kw\n+zYfHlsPQMtoMHCmp6fr1ltv1fz58/1Xp9tsfEEA+PU6yXdAtbzG8PHy7fv6d+XrAvnO9BstKSbI\nfPbLt/+srTXNbKSqw8X1B86Kisr/1Lg3/JqVviBan06dpIKCGJWXh/yqFlbZv//Q/H69uraeJD0p\n6ZzKcomkJPlC6P8L1hodDlsPQMtoMHAaY7Rp0yYlJibqjjvu0DPPPNPo+3AOGzZMO3bs0M6dO/Xw\nww8HrXP11VcrNTVVW7du1TvvvNO01gM4IoVJKq0xLES+WPKZJLd852+2kfShpHBJ1wSZT3Hlv+HW\nNLORGvdYy5EjfRcGJQ6rUds0fA5nWJhUWhoaMCwjQ+rWrWktLa5cYeG/aYUF23pVdsl3IdFX8l0w\ndK+kJZKeD9aayn9bd+sBaBkNBs6sLN8VhDk5ORo2bJiMMTr11FMbnrHdrpkzZ2rEiBHq06ePrrvu\nOvXu3TugzkknnaRHHnlEAwYM0Kmnnqr777//Vy4GgCNJjnxnAVY3SlI7SRdIyqtW5laOD3ZYvWrf\nWLYFbWy8qiM+v+6W7gOHNHwOZ06OFBeXGzBs+XLfofGzzmr8e7WtXGHZv2mFBdt69UmV1FG1b4p/\neGw9AC2jwcB52WWX+f9vjNFDDz3UqD2c5557rtLS0pSenq7y8nLNmTOn1q2UJkyYoJkzZyovL0+S\ntL/qeA+Ao9oO+fZoxlcbNl6+24EPkTSoRnlTviDavcZ8TpT0s3zXQrc+d71jly+XVq2SUpb5Xjew\nUzPAjh1SSEi54uN3S/pFkvTaa75D5C+/LEVE1J4mPLx2kD3xRKm0VEpPb8Kb126Nam+9+pwu3x7R\nmo/lPLy2HgBr1XlbpCo9e/bU5MmT1bVrVzmdh6oPaeAneXx8vDIyMvyvMzMz1b9//4A6vXr1kiR9\n+umncjgcmjp1qpYsWdKkBQBw5FlT+e+58h0yP06+65X/Ld89KWv6RdIt8l3BPrXa8P7V5tV6qi4Y\nal9vrYoKyW6XbJXnclYFzjWNuA/nmsqFPPfcL/Thh5dKknJzpSuvlD7+WPr6a9/ThrZulVwu6dxz\npTvv9N2ns/pz2vv3990SqbSuI+KNUnPrVdddvq0i+faCjpJvy85U7cPwh8fWA9AyGgyc7733nv75\nz38qKSlJHo+noep+wS4sqnkDeafTqZ49e2rQoEHq3Lmz1q5dq1NPPVX5+YG/hCdMmKA77rhDktS+\nff1f6gAOf7vkuw34KPkiy/XyXXrzRh31v5O0ToGBs7OkMyQ9bmVDm1HV7YiqDrwHnMPZwLS7dkkb\nNvTTqFEL9eGHl/uHr10rnXGGNHmy9MADUufOvhvMb98uzZwp/eMfh+YRFubb4/noo791SWpuveoe\nrSySb4/mD5Lulu/CoeqOtK0HoDnU+yiiL7/88lc96ui8884zixcv9r/+05/+ZP70pz8F1HnllVfM\n+PHj/a+XL19uzjnnnGZ5hBKFQjm8y3jJ5Ekm/FdO/5Bk0iVjb/VlafixlpLM3XfLPPuszCr5Hm3p\nlu/Rlp7Grq/xr5m8vBgTHl7wq9p5zTUyBQUybdo0xzKPN1KekcJ/5fQPGSndSPZW3nYUCuW3lsbm\nsgbP4Vy4cKHuuusudezYUXFxcf7SkI0bN6pnz57q1q2bXC6Xrr32Wn388ccBdT766CNddNFFkqR2\n7dqpV69e+vHHHxucN4Aj32xJu+Xb/9VUoZLuk/QX/dpLdVrelVdKZ58t30Xb8n0DN8Xs2f9Pu3fH\n6+67//mr3v/hh6VnnpHya55K+asca1sPwG/V4CH18ePHS5ImTz70NGNjjHr06FHvdB6PRxMnTtSS\nJUvkcDj0xhtvaNu2bXriiSf05ZdfauHChVqyZIkuueQSpaamyuPxaPLkyTpw4MBvXCQARwKvpFsl\nNeEia79ukl7QoRvEHwmqzkiyV57KWBW1GnMOpyR5vb/o1lvf0FlnNeHRQv+/vTOPjqO6Ev6vu7XZ\nlle8gW0w8DksYcJmtthGQrZkGwxygj+PxzmZMEmc5BgOywkZmJAQEcg3JCEwJ4OdSZxkOCFwHAcn\nxqtkLZa8DExktgA2IIMTyxjjfdfW3fX98ep1Ve/dUldXt3x/59TpflWvqm5tr27dd+99JmPGwMsv\nQ+ZGKj7brp4gCH0l+aDtmRMAACAASURBVPAYOUZrayvXXXed22IIgiAAK4B55v+kHUaApWgeRSUG\nam4Ew5Nc4QxfO7V9CYIgOE2qelnSVmvAgAE88sgj/PKXvwRU7szbbrut7xIKgiDkPbeS6nf7kiWw\nYgW0mGU9Ts/N01NVNgVBEPKXpArnf//3f9Pd3c3nP/95QKU3euKJJxwXTBAEIffRQ00mVzgvvRRG\njQLWqHKsgSEFQRD6K0kVzosvvpif/vSn9PSo5rGzs1PGUhcEQQBSHdYSlA9nMIgaqAc1GjmkNpa6\nIAhCvpM0aKi7u5uSkpJQDs2LLrqIrr5lDRYEQegnpD6sZVWVyiH6A7N2aFy1IOKSKQhCvyepwllT\nU0NtbS0TJkzg97//PVOmTOFf/uVfsiGbIAhCnnA6aY3ly2HMAGiuhptRQ3YawM0zIPlgwRoDpZ2+\nC3y2V5IKgiC4QVKFs76+ntdee40bb7wRj8fDfffdx+HDh7MhmyAIQo6jA4ZGJK05erRZvRxoDt9C\n+lzYq7UEQRDcImlHTkNDA0eOHGH9+vWsW7eOw4cP09DQkA3ZBEE462gHTrkthCMEAkAQyputeQbQ\n0qh8OFPLkal9RZPaCnKEv5GK9VcQhP5P3FaruLiYgQMHMnLkSIYNGxYKFBoyZAjnnXde1gQUBOFs\nIYCy93lQjo0ngGGuSpRJKivhQKwFBmmYObXCmQ9On5HX8zQw2FWJBEFwj7gK5ze/+U3uv/9+zjvv\nPF577bWQwnnixAmWLFmSNQEFQTgb8KOUKAOlnHiAIa5KlGlWrYJ3C6B8Tvj8shnpqI8BVLOd65lC\neggPqPIAg4DtwGS3hBIEwUXiKpw///nP+fnPf84999zDs88+m02ZBEE4qziCpWx+CExCKVZelCKa\nL93HiRmSEf35BDAqExtykDasMKgjwEjUdfQBV7sllCAILpO0JX/22We56aabmDhxIgUFVvXnn5dx\ncAVByARDURYwP0rZBFiJGjLSi4qwKXdDsCSsSKt2IAAFMUyZLY2wyQtnzkDyQdxGY1kMc5WLUPIF\nUMomqFeNlvuQbb4gCGcLSRXO3/3ud1x88cW8+eabBAIBAAzDEIVTEIQM0IYV6V1omz8fyyo21QW5\nUkEPa5k8BycoH86Y4VBBNZZ6/0lvrK9n5OtFuwMMz7pEgiC4T1KFc/LkyVx++eXZkEUQhLMOuzUs\nkjeBa8jdAJmi5FVsrF0LrV4ovzV8flll7h5h+mjfzVhKeCG5b50VBMEpkrZz77zzDmPHjs2GLIIg\nnHVoa9gTMZbZg0tyMVWSbj5Ts3AOHAiURM9vAZYsgfLyDInlKj7U9TwWZ7kOyZeR5AXhbCOphXPk\nyJHs2LGDv/zlL2FDWlZXVzsqmCAI/Z2Ttv81cer4UZaxAY5Lkz6pD2sJpg9nLONeA1zug+9+F5qb\nMyWbG9TY/p8Tp85xVKqr1MdWEgShf5DS0JaCIAiZZyDJrV1F5H43bEdKtSoroTPWggAEPdDdne5+\na4ivqLvBIyT3aR2RZLkgCP2VpArn5s2bsyGHIAhnHbo7PVVfyL8BE50Sphdo+VNLTr9hA7wClM8O\nn182M10fTj2e+rfJLYVTp7ZK5v6g5e8mXT9YQRDyl7jt3JYtWwCV6P348eOhSZcFQRB6z/Y06moL\n53iHZMkOxcVAcfT8lsWwYgWk35kUY2Ouoq3QQ5PU0xZh6VYXhLOJuBbOadOmAWooS0EQhMxyJfGj\n0yM5huqKze9Y7mAwjor1RRjlg6kpZ3/KxeEtj6RRt5Tcd5MQBCHT9I8hPARByDN0NPOJFOqOpD/4\n/c2YATFTbfYoH86elAO3A6jzl0sK2xBS/4CwcwCVzF4QhP6OKJyCILjIiDTr7wPOc0IQx6mrg/8J\nKh9Owza/bHa6tspOcs/3UftvfpJi/SBKaU73+guCkK/kUp+MIAhnBcexAm5SRXfB5oo1rCbtNQoL\nievD+fLLsGxZqlsaipXPMteYkGK9T7CChwRBOBsQC6cgCFlmkPmbTjf5aaxu21zg26QzrCWYPpyx\ndOy5MKQQBg2KsSwvaOvFOhPoD24SgiCkTlyFc8uWLUybNo0TJ05gGFYr6fF4MAyDoUOTRSIKgiDE\nQne/HkxjnaHkVqBJ+hHiM2bEyTjaAUGfSgyfn0ykd/6bmr+RW+muBEFwAolSFwTBJfLTF1Ohu4JT\ndwvYuBG2BqF8Vvj8sup871jW0scMiUqA9uMcl1lxBEHISVLqUvd6vYwZM4aCAqt6e3u7Y0IJgtBf\nebcP62qfv9NY3fJuoS2tqVv1CuK0ti2LYd1tcPIkLFjQd8myj/bHTfeadKBSJOW3ui0IQmokVTjv\nuecefvCDH/Dpp58SDCqfG8MwuPLKKx0XThCE/sZn6H33axClnORSwvOYg1XGJBgEXyy3xdtg4EAo\nKcmcVPnBYHLLTUIQBCdJqnDed999XHLJJRw5kk5iX0EQhFj0tvsV4DAqSj0XLGLaqpe6L3tcH84j\nECwBvz+d/Wtr7xHcTS20z8V9C4KQTyRVONvb22UoS0EQMkRvu18BxpLPkc319bDVH2Ms9S/3RYV2\n27VgFH0LGNKKcxe5ZbkWBCHTJFU4P/roI5qbm1m3bh1dXZZV4plnnnFUMEEQhHyhoUH9zpgRv47P\nR2hsS3uoUQuwYQN0dcHcuanuMVeGt9T7T3mYpAgC5jYkQ58g9HeSPuV79uxhz549FBUVUVSUa6Nb\nCIKQP+iE732xUmqL2ClUwElu4PWCJ4krYjAIvliGwCXKfzNR87p2rfLzDAa1UqsjvN32f9QW6wG9\nXP+vwDW4fxyCIDhNUoVz9erVvPnmm9mQRRCEfo3u/k1nhKFI9Lq5FWFz+jS89lriOjNmQEw3zbsh\n2Jg4D+d778E119iV2m6gkPxX1CaTz24SgiCkTlKF8+mnn+bcc8/lj3/8I8uXL2fHjh3ZkEsQhH6H\nVo7O9GEbOpVObilat9+eeHl5OXzve7ClJ4YPJ+Cdnnj9a64Bw4DpoXrrgXm4ex62Z3h7K4D5Gd6m\nIAi5QlKFs6KigjFjxjB//nx+9atfMWTIEP7whz/wox/9KBvyCYLQb9Ddr30ZTCIXUumEuwY0NlqW\nx3Cl0LLdtXyNhD3gtbUqSn32HCsEp9BcVlMTa435uG8Z/Af67iIBlptEdZ8lEgQhd0nJ4/zTTz/l\nP//zP/nWt77Fm2++yaOPPuq0XIIgCDlKeHe+beTfKD9Ojznxipn2qNtcJ2KLRUXKR1PXtzfMNTVQ\nUaH+NzX1TfLMYkZA9TpCXaPXl8AhQejPJH3CL730Uv7xH/+RefPmcfjwYZYvX863v/3tbMgmCEK/\n4RiZsYbZcasLVitaSm1MFJmumbIUipbG8eFEKa2pjqW+eDEsXZpaXWfRFutDfdzOKtx3DxAEIRsY\niaZXXnnFuPfee41zzz03Yb1Y08yZM4333nvPaGtrMx566KG49e68807DMAzj2muvTbrN1tbWtOWQ\nSSaZ3J78Bhjmb1+3FTC31eXSsej9dyest11VMgwwNj2H0dCAsWm9KnebdYLmhK1sgBGwzWtowGhq\nwtiwIXIfQXNy65pmcv9uH4tMMsnU2ylVvSyphfOmm25KViUmXq+XJUuWUFlZyd69e2ltbWX16tXs\n3LkzrF5paSn33nsvr776aq/2IwhCPpCJgCGNzt3oS1bRYVReYt3NbRiqS113f19krzrGzMNp5jY3\nIrZUV6dSHmEGFMWy9aVqARUEQchF4vpw/uEPfwDgr3/9K2+99VZo0uVkXH/99ezatYvdu3fT09PD\n8uXLqa6Odgp//PHH+clPfkJnZ+pjEguCkG9kImBI86m5LbeSnutj+RlAyIwZSZin517Th7Mj9hYL\nC6E4zkA7M2YoJbawUCm3Osm8ksED7E//EPpMW4a3p49F3gOC0F+Ja+G87777AJgzZ06vNjxu3Dja\n29tD5b1793LDDTeE1bnqqquYMGEC69at48EHH+zVfgRBONuYgPsR2gA1QHhUuh27OjxtkWpstZEy\nUj8NBmMrrXYCAaV0RtcbloqwGeYCMuuTG0RGHBKE/k3cp3v/fvXVvHjxYh5++OGwZU8++WTUvEg8\nMYbdMGwtpcfj4ZlnnuGuu+5KKuSiRYv4xje+AcDIkSOT1hcEIZf4m9sCuIJd4dyyEhqGwuYuKL8t\nuq4OPIqlvum0S7qr3kK3p264FmQqQl1zGBiNBA4JQv8laZ9UZWVl1LzZs2fHqBnO3r17mTBhQqg8\nfvx49u3bFyoPHjyYK664gubmZnbv3s2NN97I6tWrufbaa6O2tWzZMq677jquu+46Dh3qa0SkIAjZ\n5TysbuhMU+PANtPYe43q5m5sVF3dTU2wfr1aFqY6DU7uw1lXl+7etXrqhpKmr+e+ZBVTZKxtu4Ig\n9EfiWji/9a1vsXjxYi666KIwn83Bgwezbdu2pBtubW1l0qRJTJw4kY8//pgFCxawcOHC0PITJ04w\natSoUHnTpk08+OCDvJZsfDhBEPIMbQ2LlxSoN2gfzodxU+kcN86UxqZBes3P+DDV6RD0jITCODFT\nhYWx50N4l31TE7bk8n7cH95yoov7FgQhn4ircL744ots2LCBf//3fw/rPj958iRHjx5NuuFAIMA9\n99xDXV0dPp+P3/72t+zYsYPHHnuM7du3s2bNmswcgSAIOY62hr2SwW3mhs/fokWp1bt5oVK74/lw\n6gj09FTH3cDlaa2R2+iPiEOAuE4JQn8j5X6uUaNGUVJixV3aA4KySWtrK9ddd50r+xYEoTfort9M\nRpWfRI2pHiS7PozHgKEp7VcnbwJoXguBEvB1QPntKjnUIMLPTDsw3izbY/B12qVoH05w5twmowbQ\no81lcr9+1DnVlltBEPKBVPWypOaBOXPm8PTTT3Peeedx4MABLrjgAnbu3MkVV1yREUEFQRDSx60x\n1QeElRoaVBd6IADd3TBggIo4jxp9qMT04TS/2SODg+rqYJcHxlfF3muyCPbs8hCZHzUKoAelcLqV\n7koQBCdJ+mQ/8cQT3HjjjXzwwQdcdNFFTJ8+PSUfTkEQBDiOcwFDbhA+rKXuCvf74yuFBsAR6OlB\nBWMTfTYKCwl9/kcuq6iw/DibmnJhPHVtfcz0NR2AlY9TEIT+RlILZ09PD0eOHMHr9eLxeGhububH\nP/5xNmQTBCHvGWj+9heFUytDStOcOTO1tcrmq6977cMZaRv0+6EwBT1Lj2bkLlqAblelEAQhv0iq\ncB47doxBgwaxefNmXnjhBQ4cOIDfn8loU0EQ+i+6E8UJ5UR7Oh4j+8nP1Yg4NTXQ3KymRLTUQmMh\nbD4O5V+Mzl5ZVRX7DD31FFxzjRWZHi/JfHbRFuuBySr2gRrcTnklCEJmSdqlXl1dTUdHBw888AC1\ntbV8+OGH3H777dmQTRCEvMdJ5URbTQc5sO146OMZCsC0afCDH8Dzz6ulOienvSYAhWa6JFPUnoit\n1tXBtvrovY0Zo37j+3DqLuhMDzXpFvp4Eg8sIghC/pHUwnnmjJU47ne/+52jwgiCIKROALeDTIJB\n1cX95S8nqXgUugdD0S5VjFQ4I/NweoAVwPyI7epRh374w0ir6rg0Jc9VciPdlSAImSfuU33ixImo\noSgNwwj9Dh06NCsCCoIgxOZt4BrcDDKJHIgtduoiKJsX7sN5ImJ5Tw8URejNU2NsR/tw/t//qxVO\n3UZnS0H7m8PbPwqMQgKHBKH/EbeVGjJkSDblEASh39GBM+lzNJMd3HZqvPgiHD0Kd9+duF7LRmj0\nweZ2KL8LDkYsnzkzehymgcDGjVBQYKVaikq3FFI4s2Xl1cOUOnXeR+NOuitBEJwmpVZqypQp3HXX\nXQCcc845TJw40UGRBEHoH+h+YneVQicZOxYuu8wqx01b5DN9OM3v+PKIxXV1sKUhfF4BStHE9huN\ntplmS0HTr4zIsCdBEITEJO2HefTRR5k8eTKXXHIJzz33HEVFRfz+979n6tRYHT6CIAgarQSdzsK+\nanA+qnlF1Bztw5mUo9BVCsU/j7041ljqPmDWrPB5OtG8368i21WE/pgUBMgU+mBPZmFf7cCELOxH\nEIRskFTh/MIXvsDVV1/N66+/DsAnn3zC4MGDHRdMEIR8R8dpO5mySKdG+lecVzhvI7I7ObKLO5kP\nZ5DojKQe1ChFxb7o+ZEEAtbIRoqxZLcLWl/Tcxzchx42NJuKtCAITpNU4ezuVtnhdADRwIFO5l4T\nBEFIB62+FWVhX9Ej7KxeDcePJ49Sb6mHRi8QkUdTJwF6dRZ8P2IdL1ZUemcn3Hpr6onm8xudfSDx\nWPWCIOQXSX04V6xYwX/9138xbNgwvv71r9PQ0MCvf/3rbMgmCELesj1L+9GhNtmw8Onm0lI4S0th\nnC0jUSIfzkRd72V1sLkBmgm3gGrfzc7O3kmcn7yMDHEpCP2PpBbOn/3sZ8yYMYMTJ05wySWX8Oij\nj9LQ0JBsNUEQzmo+h7PRzJrVwDyyo5yED2sJKk2RPSl73KEnD0FHovz0BSh99ingQWtvkWmX1q+H\nkhJr5KHscoLsXNP5WdiHIAjZJqXkbQ0NDSEl0+v1snDhQl588UVHBRMEIZ/R3aFORzO7oZwcCf2L\nVPriKYF6LPW4knaieuzXJt7zqVNK4Ywfte4kA8zfuMMeCYIgxCWuwjl48GDuvvtuxo0bx+rVq6mv\nr+fuu+/mO9/5Dm+++aYonIIgJEAHl/SXIRfBOqbzQnPWr4djx2DhwsRrtjRAo4coH07NZ29TYTj2\n5PAerO55HYw0f36stXXg1H5UEJFTZDMlkj6mU0BpFvYnCILTxFU4n3/+eY4ePcorr7zC17/+db7z\nne9QVFREdXU1b731VjZlFAQhb/lsFvdVg/OR6hbPPQcDBkBxsTVPB/ns3AnYk8F7E3f6v1uLsnC2\nw7S7rPnBoJm/M4KaGjWF42Q2ALAU7j0O7wcsK2pJFvYlCEI2iKtwXnTRRXzuc58D4Ne//jWHDh3i\n/PPP59SpU1kTThAEITnZTI1kcfq0UggDNoOf9uEcPjyi8n44kSjBRyHqEEaFd1hHjywUKyhJr5Gt\nqO5JWdhHB8qyKYFDgtBfiKtw9vT0hP4Hg0F2794tyqYgCClwiOwEl2iymRrJItZwlnYFcYFtftnC\nJD6cp1HGvJ3W0cRTtSIDlay8ldka3jIbDEaGuBSE/kVchfPKK6/k+PHjAHg8HgYMGMDx48fxeDwY\nhsHQoUOzJqQgCPmEbhuyFVziRylc2VVOnntODW25fz+YI//GJZkP53V3qJAcL9Blmx/pwwmxApM6\nsHKECoIg5CZxFc6CgpQC2AVBECLQljZ/wlqZIxupkfYRabUdNw4KCmD8eKuWfehJqtQ8A8Cb2P7Y\nugFloD0ON3zRmm/E0NkXL4abbrInmx+K89bAbKVEikUz0aPPC4KQb4hWKQhChtHBJU9maX/ZSI00\nImpOV5dSLs3B2AAryCcqbdGHQKI8nNqHszQ8BjxWmqV581IWOoO4kRJJ++belMV9CoLgFKJwCoLg\nEDVuC5BBdECOpXDNmRNdq6rK+m/XOcsXwdFEmz+GclvcAzb9laeeggcfDK8ay+rpPNlMiaQJmPuV\n15Qg9AfkSRYEQUiK7q621MiXX1ZJ2F95JVaKonCaG9VvWRwfzpvmWSFPH2LZU6+5RvlxJvbhzAbZ\nTImk+TtwMRI4JAj9A1E4BUHIIGdwx9dPd7+eARLlH+otWumxQnpKS1X3+eTJVq3aWigqAk8QPDNs\nZyGJzvTKeqAY6IRbbrNGEo+OSIclS5TfaHV1X46nt2QjJZJ9XzLEpSD0F0ThFAQhg2g7nRsKJzgX\nra0tfINDc3p6oLAQ/v53q1Z3t1I4o1wdfwjE6IIPUYTSl80k8nr1WNbMyy6LtQGtcLcDExLsSBAE\nwR1E4RQEIYNoU96ZLO9Xp0bKXi7KWbOi591xh/o9HjG/vBm6mhNs7BNgJLA3fPaKFdDcDEuXWvMC\ngdijDylGJdhJPqIV6cOowT8FQchXROEUBCGDaEtgtvP0ZiM1UjgbNoDPFx4opIlsWJsbAQPKIkYO\n0pbMKV+O3RiPHKmi0u0KZ2VlLGmcHG3IzZRI+riGuLBvQRAyiSicgiD0A7KRGikc+xjqdpqa4C8G\nlJvd4QYofS2BLrztZdRIjj2AzXJqGNEplpYsgYkTobXVHqykRxtyQuF2IyWSpof+N4qSIJydiMIp\nCEKG2O62AFnF70/QtR2hm5VXqPTlcSlB6VQRLqixfDgvvVTt96aw9JRd5spOKJxupETSDECGuBSE\n/oEonIIgZIjP4V7Xq5McJtZxxepKB5XCSOfStOudUxPt4m3gMuCgNatlMbw8E9rawnNx6mClLvsY\nmPwMeBRnFDM3UiIJgtDfEIVTEIQMof0H3bCEgXOpkUpjzt24UXV5z5yZfAvNTUAw2odTM/XBGN6X\nt8OQErj66vDZsYKVVJL9R5ML0ieymRJJEIT+hiicgiBkCG0Ja3Np/06lRtKqYLiFsyBO69nUBNtQ\n3eh2qRK5IW59HjgPpatry2kHBItUVLqdmhq44QY4eRLmz0/tCPIb/SHRgeVPKghCviEKpyAIGeaz\nLu3XqdRI0aMMQbQiqDGM6I7t8orYdt+QMjqYKLHLvhj7SG66SeX6LCqKsbBfEiSmg6sgCHmFKJyC\nIPQTnE6NFD4aeuz0RCrQx2/+N0gxtvs/gAeAA9asludg3SjYuTPch/PUKRg2TPlyOo+bKZE0J4Hh\nSOCQIOQ3onAKgpABjuG+YuJUaiTtKjA2bG59vbJyxvKp3AKUm/+3PQVcQ0IfzmnN4G2OmDkeBvrg\nyivDZ995Zzw5nUiS7mZKJM0IJFJdEPIfR5ObzZw5k/fee4+2tjYeeuihqOUPPPAA7777Lm+99RYN\nDQ2cf/75ToojCIJjDDJ/3VRMsovPF7tbu6kJaFL/DQDdrCXRl1oaoaXeNqNH5eDs7o6uW1sLa9fG\n29LgeAt6gZspkQRB6E84ZuH0er0sWbKEyspK9u7dS2trK6tXr2bnzp2hOm+88QaTJ0+mo6ODb33r\nW/zkJz9hwYIFTokkCIJjaMUkhnbkCitQFk/nCARi+3HafTgN4Kb5aoj0WLbXMPXcQ1ioetns+BaB\n2D6c2tcxk3aEXEuJ1IZEywtCfuKYhfP6669n165d7N69m56eHpYvX051dXVYnebmZjo6OgB49dVX\nGT9+vFPiCILgKFoxyWQ6ot5gmLLc4fieKitjd6dPnw4320YZSrmT/xDwulVsWamGz1y8OLqqYajE\n8+HoGU50Pbut5OnreoHLcgiC0Fscs3COGzeO9vb2UHnv3r3ccMMNcet/7WtfY8OGDU6JIwjCWYG2\n8mWqaYs9etLy5Wqc864uuO226OWbl0H5IiXN/65GpfIMQFmcQCOAskiD7DAo8art28dSh9gjEMG7\nKGfR/ujr6AeKcGaseEEQsoFjCqfHE93oGUZs/64vfelLTJ48mbKyspjLFy1axDe+8Q0ARo4cmTkh\nBUHIACvcFsBGD6pZy5TSdQWxgqGGD1c+nCUl0Ws0NVn//WBl84nRn6RbRA/KhxMD0IFFfggWwL59\n0evV1qrfcAvr5Cg5+w+vADfTP5VpQTg7cEzh3Lt3LxMmTAiVx48fz74YLef06dN55JFHKCsrozuW\ndzywbNkyli1bBkBra6szAguC0EuqcT9CXTOQzEY0a4ta+Mfy4cMwahR0dkavEQyCz9x9N3DZbBhD\nCmfHQ5jYZTMT+3A6z3Fy57qWkxtyCILQWxxTOFtbW5k0aRITJ07k448/ZsGCBSxcuDCszlVXXcUv\nf/lLZs2axcGDB+NsSRCE3EY3I/0xkjl2lHZEUxbGjBlW7U/N3zFx6oapsa8DtnybLWuhtiC2n2gw\nqPw4nUX74549mQcEQXAOxxTOQCDAPffcQ11dHT6fj9/+9rfs2LGDxx57jO3bt7NmzRp++tOfUlpa\nyh//+EcA9uzZExVYJAhCrqMDhv7HbUEc5HBYaf16ZWU8dgzmzQuvuXgxbK4AnoVbmlX394EiwA9l\nVeF17apc2YPhyxiovBZjMSNOPs/MkmspkXSe0ZNkNvWTIAjZwNHE7xs2bIgKBPrBD34Q+l8Zb6gO\nQRDykHK3BYjgXfo+zKZWps8Lm1tcDF4vDI6h99x5J0ov+legWdUDEvpwgunDCTDdnO8HI06MzIYN\nyoe0qipyiVbKjgHD4hxTquhj/6SP28kU+mzJeOqCkI/ISEOCIPQztNL1fxzbw8mTMHAgfBJDFwsE\nTN3S9O+sqorvfRiVh9NGeRXsjbNecXEyCTOZnmpiBrfVF7pQxyWBQ4KQj4jCKQhCH+gkdwJLNDo1\nknMpdObOjb8skYIZSVi9ChWHrWk2I9GJ4cPp99ssp1FbzHTy91xhEDLEpSDkL6JwCoLQB3IxYKgD\n5ePnnGKycaNS+GL5UtbUQMs1QDtwt6rbUgB0Q1mE8mg/a+VEKKAJItGju9I1mUoLVdPH9QVBEMIR\nhVMQhD7gRXUM/91tQWwMITOWsGPEs94WJGg5p05FGVcvUeVEPpxa4fQAzTYfztDCOIewdq3qVv/g\nA7j77rAlwLz4K6bMQ+Se5dqODHEpCPmGKJyCIGSA/vjyj58W6PTp+H6U3d0woBhlbERZQeOpbV32\nQqQPZ2XEchsDBihF9qKLIpfMJzNKos5Wn2sKZxClzU90WQ5BENJFFE5BEISYaJNktMJ5++3x17r1\n1vhqmo771py2/S+vCF+veSNqRgwfzq4ulZbp0KH4cvQNrf3GU3ndohsVpd4ffVQFoX8jCqcgCL0k\nFwOGNDpS/QAwupfb0EpX9AhoDQ3qN5YP5+LF0HIbSpucr+q2eIETUD43XOH8mNix9AYkbJ1vvTW5\n9H1Dq8alTu8oTTI9kpQgCNlCFE5BEHqJ7nbNpYAhjVbr+pKLUitdg6KWxI4QV9x2G0ovMsdZ9yTQ\njcqxJG1uQOnIh38U1QAAIABJREFUFeaMIHF1+ZUrYehQ6OiIZW3VyvYRYET8nQuCIGQRUTgFQegl\nuTzCUADl6+dMaqQzZ+IrnQcPwgUTAL8qT5+e2AYcsnhGbK98RmgTUQwerBK/D4iZA11vMdesk5ki\nk8ntBUHIFqJwCoLQR8rdFiAGbwPX4FTX65w58ZfddVfvnAzKKyxbsQE016MCj2J0nx87BsOHK8U3\nGh1Y01s/xyPkrqsE9H+FWhD6J6JwCoLQC9rcFiAJk+mbwlSTcGljIwSDEG903pYNKPPk7apuiwfK\nKmLXjcXWp1Ctcxydcf78RGt3oNwdeqts6/E6o4OlcoMTKMum+HEKQj4hCqcgCL1gIuqFn4v+m5ng\nX4ln5Vu8WHWnJ/LNpNic0kD7cC77EHgDuIq4feqLF8MXv6iG0Zw5M3LpUPoWWKO13Fy9tiOQwCFB\nyD9E4RQEoRdopSQ6gjv3+Bvp523UAVHRVr6lS1WUuD+eg6VezdRVk/lwhjD1pxEj4PNLoWhp4vV8\nvsTBS71H++a+7cTGBUE4SxGFUxCEXqCVkoHJKrqIDi45rxfrak0utlaZyIcToGx64uWxKJ+ubIoF\nwKblwEhU73iMnJ9Ll8IXvqCSzDvHZCc33kf0te0ibVOyIAiuIAqnIAj9lABKKelNpLpWqF+NWrJ2\nrYoO7+mBWTGSsoPpwwkwOz0fzpA9dQRK7JhR6Ip4/qPh1NA/x0X3owabl1eYIOQL8rQKgpAmXeR2\nFLNmH3A+ffP1K4+aU1ysurITjaduN7ol9PW00VwP+GB9JypQ/BxUbv041NerbcdKPm9ZAB8mPYXz\nEPlxbYsRP05ByC9E4RQEIU10s9HjqhTJmYgTitOf/6wCdQ4cSFApSMhcWVGRompkVvD54MoFMJzk\nPpyJBfCSfhM/1PzN1Qh1QRDyFVE4BUFIE93dXOK2IK6wdKmaElEW0+qYmPIZKgSrGNi0zvxzHLgz\ndv3ubjDi6oVdqOY9XQtgYt/V3EJbcTs5W+9FQcgnROEUBKEf05tRaU6TqFu5vl51qX/6KSxcGL28\nGdOH0wvMhKYmaEEldo+HVgu1/hgoNi2Yg+OsQHz/UUUpvetyzqePCe2jW5isoiAIOYAjSTUEQeiv\naP/NfOly1XJGj4ceH+2AGfsYvV41FRXFXvtSvYk4elC8M9dcC680wcaNcOoUysh4KL6UGzeqgKSz\nl/+HOpvixykI+YAonIIgpEG++G9quszfdJo6rcB0xVz6+ONw+DDMmxd77VJQxjfTQFpRkeIoQ6aI\nXi/MnQtllVAWw4Kq0Xk4X3wxhW33S2ri/BcEIReRLnVBENIgn7pcQVk20+1a1scY2yra3KymeBQA\n5ZXphyuVV8FBYDRQVwctPmArcXWp06eVlfVXv4q3Re1OcASVZykZHeRHhLodfYyPIEqnIOQ2onAK\ngpAi+9wWICfQ3djT4yR39wLN61Fd6pWmD6ehErtDYmeEg+ZvgR5HfVT8unfckUxSvacEjqBhaB+A\nfFI4O1AfBtJZJwi5jiicgiCkyGjye/z0d4HP9nkryfJqekAZgD1QXp76dpuXgzEaGoLQ0QGDioC7\n49fXCei7u2H27Fg1elDZ41NVxrwoJfVgsoo5RG+DowRByDaicAoucQYVWRH5ojBQyWESDLEiuIRW\nSPa6LUia6G7XSSnUTRyhDsonc9my+FvwQEjXu/xyVd+uose1cJ4ERiuFds6c5HbGoiLlw1kYN0h7\nAL1TxnozFGgucAIY4rYQQhjbgatQ96D9PjRQ9+Y2Yg2uIPRPROEUskgN8D0si0usaGcvyjykM2e/\nQW6P6Xy2sML2f6JbQvSSHtTHTSpDXOoI9cTq3qJFibdSPlMFmd8SY1k8hbNskfVk1Nebw2EmyOfZ\n1gYXXgi7dyeWpf+jR6BPJxOB4CxdWC4akUm/QN3pXuBm1LPWCQzMmnSCO4jCKWQJP6qB0UqmYc77\nK5ZC2Qx8HqUYeMz616BeKL0ZD1vIHF8g/wJKNPoDJhVLn74/j8at0dQEwWC8ISXVFppXAYOgNqAs\nkZuDKrE7pJZQKvEoQoq7E3S3R1ND4qCaTvL3+hYi3eq5Qgdh47oCqv0+Q7j1+SRKwdTXTD+jx0gt\nwE3IR8TTWnCYY6iGRL9Bg8Bms1xEuPWy3Jyn/c50R6TXXK/beXGFOPjIP/++3qBfgKNjLtVd6UnH\nRy8FCmKPt57IA7apSQUldXSQ0u3e2AgNDYlq6DyV/5ZkS9oala/+uZpTbgtwlrICde/Ylc0OrOFV\nI10dBmO18/pG96AGZ8iHUa6E3iAWTsFBurFuMQPYQ3rdsQUoq8z3UY1RAapRexxJgZJNmm3/x7ol\nRK/YsEEH1Gg/zpOkHrUdTjNQbnalJw0GOgMMhBMn4ItfDFfjkr1OPR647bbUbI0ej6X8rgDmR9Xw\noz7ikjX12rK7ipdfhtJSNWxmPCtu7uFHKc3i+519tFVT30PdpJc2TdfVQW4+1N2/k0wE+Qm5g1g4\nBYfQflX6v5fe+f7VoBqgM2bZCzyKCu44WzmDesEGzKkHlWvRKaaSj92ta9ZAcbG2AGrZEykkZ4g3\nilIQ5W2m090nysMJUH4HXDJDKZuRdCRYr6JCTY2N0FKfeB8AZ87A5s1KvnnESlX/76Q3Gs98iovD\nFdn8oIjsjDrUhfXs+VHKVZvD+8xl/IT7PWsf/N5QCHyMdR0vw2r3hf6AWDiFDLMd5XepX9yn6a1F\nKZxS8zdgbnsAqrE7W27hWE74Gi+qK8qpQCsdnf5+BrfpHI2Nyjr3yScwaJDyt4S/AReT+Bs7dsDQ\nKawzvrUemnwq6frtt8feigdoXgaBC6HRVNw2+1Vid4D3UjgGj4eU3JbnzLEGG4VYo2nWoD7QEhEe\nmT9rFtTUqCm/0FbsbpQCmikSPXs+1H2ln733ODuscvux0qT1xqoZjwnmr27nS1CfeXFTMQh5xNny\ntu4HdKIuV6z0EgbqoXS7O+m0KYNuhDaT+ZQXPqwXgO56SberPp/Q3Ux2y1vQNungKq1I6UCrTCnj\ndntcfrxItXXuy1+2z51EcgutPsd/DpurnyoDUu8TGq0Cfwx9yWxG0/IEqzU1qd/OThgQVBK1ET+h\nU309/I9XJZWPH4ykFbFjqA+TSJSiUF7u4/vfV/6jc+aoJQ0N6lzGS3KfW5wm5Dybse1FtqmRz55+\nNkGd48tQytJB8s39JHUiXaVeJ/OZRHy2/fjIjcDRvwHjCM+yAuHt8kHyN62Y80iXes5yCGtA5iBW\nWhf7JdPKhg8ryi+IO+Nc2xVe3bVS7tC+ilFKpu56OZ94417nL12o86gb9iCqe0lf70LUedD+eV7g\nh1jegloZP9lHObTVL3/O7+bNygKpWb9ejw6k75dEndoQ6Qlpz6tQPh0+XxHfuhmiDvx+pbxVVMC0\nmfGrxlIUb70VbjaVvkSvL6+Z+KH5Kevoop1NtKJdGrVEoY7wkUfU9gbYdCyvN5+61u2BKX11ufET\nrmzGe/Z0m2x/9rwo618ANdhAf0EHBtnbJC/Opa0rQn0kgRU4+jeH9hWPU1jv4fOx2lr7e1iXC1Af\nGUFzHQlyjUQUzpyiBtXQBVGpIeyXJ2guO4lq3LzAY6hkx3odTQHWTX8M57F/ffrJzpfoRMIj2QvJ\n/whbUA1ckPBhBg+hzmk8hUFTg7r2m7Huh0H0PurT7j/ltvU8dWpqwhVC7ZO4YYO+L2N1t+pxxOPb\nCe13WjLKlkJlpQr+SYeKCjh0SCnIm+uS72/fPmAzlD1oXfHIpDQquba2ckayPfSvslKNWrTPNoLp\nmTPw0kvpHYO76I/t3t6vbYRn1ehBnbdUnz0v1vNmt3jmO50oL2F9D50kOx2kI1DvO7txIdkHYybQ\nH/wDCX9uAuayvViK5i6Ucmm/zh6sdF0B1PkTErewOUhrayvXXXed22JkmE6sl6D9kgRQ3XvRsafx\n2QeMwep619vSYw5nkkg/nlO4M9JHZFd+pvyJsskB4BzC3SXOkPxFlwh71xek7+KgVZj8OJ/19aob\nu6cHZtosii+/rJTOWbPAOqZI5UsHtnVjV9kOYWUF3AwYTYABtyToYtZ7aKy38ml6fgjlzeb/OHvW\nKuHGjeboQUFlUbXblCLR8mnvwcviHJ0l1Q8Jz/CgPxAT7UVF5ScLlModenvf6nZYtyN9jZKOzD1s\n77HIF1YAdxLefexW17Y+n+DcudQuTJHzoj/jEnMK651kP3c6x+/IPsiYe6Sql4mF0zWOYZnq7Tdz\nEBWp50V9IaWjbILqgNPdPPaudT3MXaa+tHqwchUGUS8yt4aVG2TuX79oilDndr9L8qRDG0rWkViP\nY6pWlWQUYZ0DDyrOOtWozx7CkzL3nYYG5aOYOG9k3zkakbO9ulormxC/W10rBeEvlmFY4TTl9qop\n4PNZ3dE3Nqe2TkODyt3Z3U0o5Wmi3b1dAy1NsLkhmWqkj/uR0BzV4adU3cbGApqaYgcKbdwIjz6q\nfjPJ2rXW/8ZG9cGQGXQbl07gkE4fBdYnQF99lguAl7DaJe3mki9drT2EWzW7cdePsgDrnaa72DOR\nIaAGq5fQrsRqN4p0lU1Qbbd+D3cS/qE7AqvHckXMtfsrjiqcM2fO5L333qOtrY2HHnooanlRURHL\nly+nra2NV199lQsuuMBJcXKAI1hK5hDCv9Y6sXyEJsRcO32KCE+sq+f1pdE7TnQidx/u58WsQcmh\nXzZ2PyonUwb1luMo2eyR0/oLvjcNXDzOw2qcQSmP4V3sa9cqZcJSNk5hJXo/kDFJTpk5uY+ZXh71\n9bBuXcY2T2Wl6pJesCB62apVsKkJGhr0cRXbOsB0nHd0Z8+WemjeYKUTL6tQUyqvuZ4eFfxTUQFr\n0jyWQACujnEckdxcY/6xaaUtdbCpEV580V7zIHbr1AGgyJYk3WuuH0vh7DB180z6cjY0wMCBUFdn\nbdvnSyG/aUoMxFKww7uzly+H556zz9lHeHsW2SvQV+ab2/4Y6xnULk+5muC8h2j/8b6kO8okxVjt\nuQfVfvb2PO5D3R+PEv4+O0RmPvg1A7CUT7usPpRCn08fIX3DMYXT6/WyZMkSZs+ezeWXX84//dM/\ncdlll4XV+drXvsbRo0eZNGkSzzzzDD/+8Y+dEsclDmDlbAui7CX2U64tWT6cHUe2xNyP3apj9y9p\nT2Eb2nnanuLoCLnXRaR9bux+VDplkB/VyLjFcawv6cFY94K2qFjeeslHkEkXH5Z1wGcqFocB9eIv\nKIBx4wDO8NxzuqH109dI240blVXzqadg7lylfM2bp0bs8flUgEqzKVk6Ta62GQSBTcCmBmsUoHhy\nAPhsSpOP0xwH6uuL2bjRQ0zrvw8ohj+a29axyROxnurjWK9ovdxAdeurpPOJ+ynsHW4zZihls7gY\n5pZbapPedo1tv6F0SAesLv4ghFzLRocNlqSuY329l8ZGeHcDWEML9lBWobr9Y1Fdra5bZWX4cabj\nmajvfN0CdZkxaDq468ABlSS/uRmefx6WLElj4zFRHxbLlvlobLSUzFGj4PzzobYWrPtbX7EP6atS\ntXat+rgBdc83NMDKlaCMCD7CR0LSFk8dYFKT9v7+9Kc+iWujC+vOsiua2n88l9C9QZEBkqkqnto/\ncyzhRp/N5rZijzKWGQrNfe4h/AnS72N9P3ThvhEn8zimLVx//fXs2rWL3bt3A7B8+XKqq6vZuXNn\nqE51dTU15if1Sy+9xLPPPuuUOL2itlaNg+z3Q1VVD2vWFDJggGokq6v9rFpVwMCBcOQILFgQYNUq\nHwMHwqefwpe/HGT1ai8DBsD+/aq8dq2X4mL4+GP40l2wdSPq/m6HqXfB1gbUvXgUpt4JW9ej7sNK\nlXp763qgAKaa+fyiyrVqe1MrzXKd2t40s7ylcRB44JaKI8BQGhp8ZsoTdaPX1amHb+ZMpZjU1RWa\n5aBZ1su78VPEFtM6oSNwt5gK0jRzdJItpr/btOl6/2ZZL98I+GHarbZyD0y7DbYA1JvlW2FLOao3\n0A9TZsO2l1E6WwCmVMK2DaiP3yBMnQFbny+Ec+FUB9x+e5AVK7wMGwYnT8KddwZZudLLkCHqJXfn\nnepaDhoEx4/DvHndrFpVRGmpehEuXNhNY2MRHo9av7q6h8bGQjwenY+xh3XrCikqgsrKHvPeKcTn\ng8pKlU+uttaL1zuUqirlx1Nb68Xngwrz2mxuADy2c2W6/ugmVJ/Lm83lmzcC3TBlDmxbjBrqvBum\n3gZbnwKutJ27JcAlQFcxt9zWTn39BHw+2LjxHKqqgvT0KFkWLVKynn8+NDV5Ka9Q+2rZqM7zVFN5\n2tqgrsPUWbC1HPieKt88S726W+qBDrj5DthsvquuvUIdS8iGuMi8/4Oqo79lA1AAwUozoVajqnaz\nme5ni3kvT61Uj4heXjbdvE988H8uUvuwe8xpfEvV66RsKbz0kroXnngChjYHaDIdLTctGwQvoAwe\nAbi5EjZ3q/0uWqQU5y0oC6e94dSfYJHJynT7AUphi+csr+1roU43MzJc+0zat/uorVxo/i8zLaEN\nDXBoBipG6PNwS5V6dW3eCByDW+Z3hlJGdZkbqa/3qGOphLLm6PwW9s/jzYth6zzAD2VVarubClR5\nShVsewkYChyGaQuUdVhnMRs8G1pqgSLYVKGecX28PQDmMWwClXlmnPpfBrQ0qJNzc5VaZ2s96n40\n77ctDWZ5pnlv1Kt93jLnYy68UJ3PCRMA/AQCBfh82sXCR2OjB8OAW2aY9+5GdfGmzVTXa2u92veU\nmWq5vmdD+9b38CzYvJ6Q51IPsPUf1PGPGGaWVwGDh8BBuGVBO2vWTKCkRLmAzJ9vsGZNDSUlcPAg\nLFwYYM0aHyUl6n1x113drF1bREmJum+bm1Ub5A1dID+NjQV4PPD66/Dgg35qa1VZt+e1tap+VZV6\nSurqVPtfVRU0yx6zrNI6bWpQHynTZpjnwkzZNdVsF7bGas8DMG12eHmKWd4W57pNmwlbnkPp5EGz\nPX8OFR9kwNTpZpt2tbpZps2CLcuACwo40QHV1QGef97HmDHKGl9dHeTFF72MGqXa57lz/axYUcDw\n4bq9L6KuzkNhoXJdmTULNm1EPdTdMGUWbFuHep8chyl3mu+bAcDfYcoi2LYa9W3SBlPuhm1rzfpv\nwZQHYdt6da/zBExphm363V4BU4BtDRPNkwC31Jxmw4ZB+Hz6WnhZv76YggJdhg0bvObyAGBQV1eA\n12u9b+rr1bWdPl1/tgfJDYt0OI5ZOMeNG0d7u2U527t3L+OUCSVmnUAgwPHjxznnnHOcEilt9MOs\nupIKGDBAWWUGDgTwUVqqnPuVyN5QecwYtd6gQcpyNHo0GHgZNECVLxhrvrC0lX2MWdZvkpNmuRj1\nZ7FZLlHlAuKUzSwdobKZqlIPFqa3bzACA19UypPCQjNYwdyCVbaWFxWCQZHaXqGaQts3LSuhsknY\n/u3LC9QxhJUH2Na1LedLZrnItAPqrCdes6yfM8M89rFqo6UD1LkfPlzJP3SoqjZ0qLoWqqyupVUu\npLRUXetRo1Q5GLTOARSE8iv+7GeqrO8Nfe6KinRZ3URFRXpcbT+wmeIiKPDZEmyYsQVb9Lk4DexR\n/7fYrD1eYPMSQqP4FYJyLjTPVQHAZ8xysbmtiYQyZxlMoCDCkDdzpsGMGTpkxYthgMeuHZnbCt1X\nXnUdCkCZJ32q7AVanjMrDTITY00HjkD5LFWtwDaVV6n5gJX1S58PU+HW9n99LxfEWH5zJUqzWmk9\nUjp5jZ68KGXzNDBsmLo23/ue2tuJE8qqWLbICuzBa64zC66usk5F0HZeIpVau0K9G0L3TMA0ZOxH\n2YsiKUDJpR+1xx+35e80CWBZOw2sDxEdItfYqI7p7XrVzV5eZd4r68wdnANBBvKnPykFZ9YstQOf\nDwwftDxvyWKfvLaJanOn5n1rd0srBNWRYO7L3t6E3jL6AOvCr0/YPaEPylDKZmj9AivxjL7fdIZG\n3Tmg8zPoDqMgE5gxQxkMVB5RH1VVBtOn6yunFCyf1/YiLCDUpoX2VWjJqdug0L7Nshcov5WQoa0A\n4BPzwnWY5VJT1nPUc1hqvg+GDVMnU/c06PeJLo8dq06ebmOUd1oBwaC+x8IDeR58UJWLisLbc6sN\nUk9JYaEuq/0XFkJhARj4MBgb1p4X2K5LqB2I1Z4XR5f1dY533XwAfyGU1rQQrHAA3Z5/NqL+BPV/\nSKmSd/RodaylZufMyJHq2FTZx/Dh9vY9qN59QLEvIr+uvpdLTCEHm+VS8yAmmOVBZvkiszzAPN5L\nzbJuz+43y/pZWGGWdSxZDRgMoqRYnXvl89tDSYn92qgej4JQ4+ujsDD8fWP5i+uzncmBDzKHYxZO\nTwyHHyOiFU2lDsCiRYv4xje+AcDIkdmL7qqq8lNTU0BNjeoWP3IEhg/XQQkBurrUjaC6hU7T3Q0D\niqDwFPjxsqULKIKi46bxvBN1Ix40y6Y+Pu0uVdbWLbV1rADSpWbZDKALGeJNl79QOXJ5T/jyaRXh\nLytPBbAcesynrTm0ovqjX5R6+daAtVtbNavcBXRYZf0lHFr+EjDV9mI2exBCVhVbeQqwzRy5sQeU\n5cm0pAWAaQuVcjbNFGOafhlqsY6jrC2dZvztGWAQ+DrVtVl/Rn04nDmjJOzoIGS9hgCdnVBSor6I\nIUBlpb27JsCMGeFlv19/oKiT0tOjy0fwcw5bzGvlN9+6W8xrcwrzITyDsmyb52vq7da5m3q3+m9g\ny6ppnpsAwA5CKwYAPgCuAnrMc78P/BOhoEedy2lhOSRPYblz9KhrM111feo2eJN5XcJuD3Pf00Ad\nm1/d3q8dgqvGqxehDjGYNs92z9n2bJibKgHqelQD6sWUsUIp2t16Hb+1awNoqYArzHQ9PuD0DPVo\n+bHGJYlsXfaidO+1neq5/dGP1Ibnzm0GyjmEmRb9DFwyR23rNFaq9DNnVEL0dlQeCN2k6w66Aajr\nU4iZqP3W8P0nyqdp9xZrbrasm6+jjNWFqPCCL6AyEU7CundKgFUn1f1cZSrHuuubfcCFquAF9i+F\nsUs7UGfyffx+dVxzv6yOI7LzVHuXF6OsfKttKZJumaVkKDG3Rod5EjrN+3YGbDXrek0ZPR64odqy\nRMdi2nTLe3gssNGv2iLtgKR7fvW9oEeZDIDSWIPQE7TCNQoqQeXD1HsNAv8PP7Dlh8D96thXA8MD\nUGBE3OtxyqE2LGANy6Hb8ACqXbevxpuoi3nGdN4wz1fhCfDjY4t5oo8fBzhDV5f6UD1yRG2hq0sp\nVR99pMpWm6R+p0/vCStHtklWuQfdZhV6VHsI5nPssR1bB3DaOmv2YwOUB8IoW/tuthOR5YC9HIi+\nbn5g6lLYOh2m3WmeO9uQsAFQl+8fgC5z+8dQPes9annRSWAYeLsBXuLUKRgyRLtuBDh9Wimfvi51\nrqkM37620ob2dxKlVO4zy92oh/BERPloRPkTW7kA+NgsT1dtZWh/FcpKq99f+t3tN51vrPeFujZN\noWvXBXjx+7WCqc7umTP640Of7dxNPmQ4Md14441GbW1tqPzwww8bDz/8cFid2tpa48YbbzQAw+fz\nGQcPHky63dbWVkfklUkmmWSSSSaZZJIpvSlVvcyxLvXW1lYmTZrExIkTKSwsZMGCBaxevTqszurV\nq/nKV74CwLx582jS47oJgiAIgiAI/QbHutQDgQD33HMPdXV1+Hw+fvvb37Jjxw4ee+wxtm/fzpo1\na/jNb37D888/T1tbG0eOHGFBrHwmgiAIgiAIQl4jIw0JgiAIgiAIvUJGGhIEQRAEQRByAlE4BUEQ\nBEEQBEcRhVMQBEEQBEFwFFE4BUEQBEEQBEcRhVMQBEEQBEFwFFE4BUEQBEEQBEfJu7RIBw4c4O9/\n/7vbYvQbRo4cyaFDsUZ4FvIBuX75i1y7/EauX34j1y9zXHDBBYwePTqluq4PiySTe5MMFZrfk1y/\n/J3k2uX3JNcvvye5ftmfpEtdEARBEARBcBRROAVBEARBEARH8QE1bgshuMvrr7/utghCH5Drl7/I\ntctv5PrlN3L9skveBQ0JgiAIgiAI+YV0qQuCIAiCIAiOIgqnwE9+8hN27tzJW2+9xZ/+9CeGDh3q\ntkhCisybN4933nmHQCDAtdde67Y4QorMnDmT9957j7a2Nh566CG3xRHS4De/+Q2ffvopb7/9ttui\nCGkyfvx4mpqa2LFjB++88w733nuv2yKddbgeKi+Tu1NlZaXh8/kMwHjyySeNJ5980nWZZEptuvTS\nS43PfOYzxqZNm4xrr73WdXlkSj55vV5j165dxoUXXmgUFhYab775pnHZZZe5LpdMqU3Tpk0zrr76\nauPtt992XRaZ0pvGjh1rXH311QZglJaWGu+//748e1mcxMIpUF9fTyAQAODVV19l/PjxLkskpMp7\n773HBx984LYYQhpcf/317Nq1i927d9PT08Py5cuprq52WywhRbZs2cKRI0fcFkPoBfv37+eNN94A\n4NSpU+zcuZNx48a5LNXZgyicQhhf/epX2bBhg9tiCEK/Zdy4cbS3t4fKe/fulZeeIGSZCy64gKuv\nvpr//d//dVuUs4YCtwUQskN9fT1jx46Nmv/II4+wevVqAL773e/i9/t54YUXsi2ekIBUrp2QP3g8\nnqh5hmG4IIkgnJ0MGjSIlStXcv/993Py5Em3xTlrEIXzLKGysjLh8n/+539mzpw5TJ8+PUsSCamS\n7NoJ+cXevXuZMGFCqDx+/Hj27dvnokSCcPZQUFDAypUreeGFF/jzn//stjhnFdKlLjBz5kweeugh\n7rjjDjo6OtwWRxD6Na2trUyaNImJEydSWFjIggULxFItCFniN7/5DTt37uSZZ55xW5SzEtcjl2Ry\nd2prazP27NljvPHGG8Ybb7xh/OIXv3BdJplSm+bOnWu0t7cbnZ2dxv79+43a2lrXZZIp+TR79mzj\n/fffN3bOqKf4AAADqUlEQVTt2mV897vfdV0emVKfXnzxRWPfvn1Gd3e30d7ebnz1q191XSaZUpum\nTJliGIZhvPXWW6H33ezZs12X62yZZKQhQRAEQRAEwVGkS10QBEEQBEFwFFE4BUEQBEEQBEcRhVMQ\nBEEQBEFwFFE4BUEQBEEQBEcRhVMQBEEQBEFwFFE4BUEQBEEQBEcRhVMQBCFNxo8fz0cffcTw4cMB\nGDZsGB999BHnn38+Y8eOZc2aNRnfZ2FhIS0tLfh8voxvWxAEwWl8QI3bQgiCIOQTJ06coKioiPnz\n57N27Vr+4z/+g8bGRtatW8ejjz7KqlWreP/99zO6z2AwyPnnn895553H22+/ndFtC4IgZAPXs8/L\nJJNMMuXbVFBQYLz11lvGfffdZ7zzzjtGYWGhARgffvihUVRUZADGV77yFePPf/6zsXr1auOjjz4y\n7r77buOBBx4wXn/9deOVV14xhg8fbgDGpk2bjKefftpoaWkxduzYYUyePNlYuXKl8cEHHxiPP/54\naJ+f+9znjHXr1rl+7DLJJJNMvZhcF0AmmWSSKS+nqqoqwzAMY8aMGQZgTJw40di+fXto+Ve+8hWj\nra3NKC0tNUaOHGkcO3bM+OY3v2kAxtNPP23cd999BiiF88knnzQA49577zU+/vhjY+zYsUZRUZHR\n3t5ujBgxwgAMr9drHDhwwPXjlkkmmWRKdxIfTkEQhF4ye/Zs9u3bxxVXXAHAueeey8GDB8PqbNq0\niVOnTnHo0CGOHz8e8u98++23mThxYqje6tWrQ/Pfffdd9u/fT3d3Nx999BETJkwAVLd6d3c3paWl\nWTg6QRCEzCEKpyAIQi+48sorqays5MYbb+SBBx5g7NixdHR0UFJSElavq6sr9D8YDIbKwWCQgoKC\nqHr2OrHqFRcX09nZ6cgxCYIgOIUonIIgCL3gF7/4Bffffz/t7e389Kc/5amnnuKDDz4Is1pmmhEj\nRnDw4EH8fr9j+xAEQXACUTgFQRDSZNGiRezZs4eGhgYAli5dyqWXXsrkyZP58MMPufjiix3Z7y23\n3ML69esd2bYgCIKTeFDOnIIgCEIGmDt3Ltdeey3f//73M77tlStX8m//9m988MEHGd+2IAiCkxQk\nryIIgiCkyqpVqzjnnHMyvt3CwkJWrVolyqYgCHmJWDgFQRAEQRAERxEfTkEQBEEQBMFRROEUBEEQ\nBEEQHEUUTkEQBEEQBMFRROEUBEEQBEEQHEUUTkEQBEEQBMFR/j/X+QZFU5/GoQAAAABJRU5ErkJg\ngg==\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x7fb7847db750>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# PLOTANJE relativne veličine otvora, difrakcione slike i intenziteta zračenja\n",
    "\n",
    "fig2=plt.figure(figsize=(11,10)) \n",
    "\n",
    "ax1=fig2.add_subplot(4,3,1)\n",
    "plt.imshow(np.abs(ap1))\n",
    "plt.xlim(324,724)\n",
    "plt.ylim(460,588)\n",
    "plt.axis('off')\n",
    "\n",
    "ax1=fig2.add_subplot(4,3,2)\n",
    "plt.imshow(np.abs(ap2))\n",
    "plt.xlim(324,724)\n",
    "plt.ylim(460,588)\n",
    "plt.axis('off')\n",
    "\n",
    "ax1=fig2.add_subplot(4,3,3)\n",
    "plt.imshow(np.abs(ap3))\n",
    "plt.xlim(324,724)\n",
    "plt.ylim(460,588)\n",
    "plt.axis('off')\n",
    "\n",
    "\n",
    "ax1=fig2.add_subplot(4,3,4)\n",
    "plt.title('(A) z = 1 m, w = 0.1 mm')\n",
    "plt.imshow(np.abs(u1))\n",
    "plt.xlim(324,724)\n",
    "plt.ylim(460,588)\n",
    "plt.axis('off')\n",
    "plt.xlabel('(A)')\n",
    "\n",
    "ax2=fig2.add_subplot(4,3,5)\n",
    "plt.title('(B) z = 1 m, w = 0.01 mm')\n",
    "plt.imshow(np.abs(u2))\n",
    "plt.xlim(324,724)\n",
    "plt.ylim(460,588)\n",
    "plt.xlabel('(B)')\n",
    "plt.axis('off')\n",
    "\n",
    "ax3=fig2.add_subplot(4,3,6)\n",
    "plt.title('(C) z = 1 m, w = 0.05 mm')\n",
    "plt.imshow(np.abs(u3))\n",
    "plt.xlim(324,724)\n",
    "plt.ylim(460,588)\n",
    "plt.xlabel('(C)')\n",
    "plt.axis('off')\n",
    "\n",
    "ax4=fig2.add_subplot(2,1,2)\n",
    "plt.title('Fraunhoferova difrakcija - dvostruka pukotina')\n",
    "\n",
    "ax4_1=ax4.plot(x1,np.abs(I1),'r-')\n",
    "ax4_2=ax4.plot(x2,np.abs(I2),'b-')\n",
    "ax4_3=ax4.plot(x2,np.abs(I3),'y:')\n",
    "\n",
    "ax4.text(-0.6,0.6,'(A)', color='red',fontsize=16)\n",
    "ax4.text(0.4,0.6,'(B)', color='blue',fontsize=16)\n",
    "ax4.text(0.08,0.6,'(C)', color='yellow',fontsize=16)\n",
    "\n",
    "plt.xlabel('X(mm)')\n",
    "plt.ylabel('Relativni intenzitet')\n",
    "fig2.savefig('Fraunhofer_2slit.png')\n",
    "plt.show()"
   ]
  },
  {
   "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": 2
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython2",
   "version": "2.7.14"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}