{ "cells": [ { "cell_type": "markdown", "metadata": {}, "source": [ "# Simulating Light Curves from Power Law Power Spectra\n", "\n", "In this notebook, we will show how to simulate a light curve from a power spectrum that \n", "follows a power law shape." ] }, { "cell_type": "code", "execution_count": 1, "metadata": { "collapsed": true }, "outputs": [], "source": [ "import numpy as np\n", "from matplotlib import pyplot as plt\n", "\n", "%matplotlib inline" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "The power distribution is of the form `S(w) = (1/w)^B`. Define a function to recover time series from power law spectrum." ] }, { "cell_type": "code", "execution_count": 21, "metadata": {}, "outputs": [], "source": [ "def simulate(B):\n", " \n", " N = 1024\n", " \n", " # Define frequencies from 0 to 2*pi\n", " w = np.linspace(0.001,2*np.pi,N)\n", " \n", " # Draw two set of 'N' guassian distributed numbers\n", " a1 = np.random.normal(size=N)\n", " a2 = np.random.normal(size=N)\n", " \n", " # Multiply by (1/w)^B to get real and imaginary parts\n", " real = a1 * np.power((1/w),B/2)\n", " imaginary = a2 * np.power((1/w),B/2)\n", " \n", " # Form complex numbers corresponding to each frequency\n", " f = [complex(r, i) for r,i in zip(real,imaginary)]\n", " \n", " # Obtain real valued time series\n", " f_conj = np.conjugate(np.array(f))\n", " \n", " # Obtain time series\n", " f_inv = np.fft.ifft(f_conj)\n", "\n", " return f_inv" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Start with `B=1` to get a _flicker noise_ distribution." ] }, { "cell_type": "code", "execution_count": 22, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 22, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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0gzpduG6mMWNUZIxdhr1/NQ1bVsvGblji0iaJ5O9+l1yuD9uKSbJsXBABL79c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\ngg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "f = simulate(1)\n", "plt.plot(np.real(f)) \n", "plt.xlabel('Time')\n", "plt.ylabel('Counts')\n", "plt.title('Recovered LightCurve with B=1')" ] }, { "cell_type": "markdown", "metadata": {}, "source": [ "Try out with `B=2` to get _random walk_ distribution." ] }, { "cell_type": "code", "execution_count": 23, "metadata": {}, "outputs": [ { "data": { "text/plain": [ "" ] }, "execution_count": 23, "metadata": {}, "output_type": "execute_result" }, { "data": { "image/png": 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zBh58MLWo9OypgX5zf1UfJipdgNbWMMvGOsYWjnIUlWRLpU8fbcsCYWylb1+Y\nMiWz+8sH6SHRzeWLKCEUqXTcdZfOmumD8v69QT+7aGq2UT2YqHQBDjxQLyKgwVoTlcJQCaKy++7w\n73/relQERo4MZ7ZMhZ+QbNw4nf7ZE7VOfM1TOrzV5MUMEkVl0KCwB51RPVi1QpWzeTM8+6zOEQ5m\nqRSSShCV0aPhsst0/Sc/CbePHQtz52rg3s+iGcVXwM+Z036CrXXrdEqAbOnAGzbA5z4HU6eG26Ki\nMmGCFkY2NZVn12cjP8xSqQJaWvSOMhXen77vvrq0mErhqARRiT4+5phwfeed9Ybj/fdTH6tnT23R\nkmrGxn799PuWzVLZsEGzvKKCERWV2lqtrDdrpbowUakC1q+H994LW2h4zjkH9tlH130FvVkqhaOS\nROWggxK3i6iLK934oxX4qfD9zzLR2Ng+ccA/9t/HwYOzpzYblYWJShXgfdbJd45//3toqfhaBYup\nFI5KEhXvAotSW5ve2sg2r3xdHTQ05D6eLbZIdLkNHmz9v6oNE5UqwPu2k5sEer94nz46095Xv2qW\nSiHp2bNwsysWgkyikmr645qa9HGRbKIyaFDY9iUdr7wSxvLSseWWMHly2ALGqHxMVKoAf2FIbhLo\nxcP3r7r/fvjlL01UCkUlWSqpBCKdpTJnjjakzFQxP3Bg5jqX9eu1vc3kyZnH7L+zVq9SPZioVAE7\n7KDL5LtmX5uy//6J2y1QXxh69tS79XKJCaQqfswkKuksFT8b6MyZ6d9r0KDMre8//FAzzzJZOxCK\nSragv1E5mKhUMA89BK+/Hj7euFF/6D5g70XliCMSW4xn+6Eb8fDi/OMfl3YcoP/fVKm5+Vgq/kJ/\nySXp32/XXXWSrXRdmlevVtdWNvx4TVSqBxOVCubooxNn87vuOs3YeeABfezFZfBgDYx+97v62NqN\nF4YttkicbreUbNyoIpfsssonpuJdUckWbpQtt1QhS9c+f/VqtWaycfPNMGaMfSerCROVKuLmm3Xp\nM768v99XR/tJprIFWI34DBgQzlFTSlLFUyCzpTJ7tiZvJBM35ta9e2K1fJTVq8NEkUwMGgSf+YxZ\nKtVEzqIiIgNFZNfsexqdje887Ntx+DtO76Y5/XRdRiecMjpGuYjKww+nzkTLJCp+XpRkdt4ZXnop\n+3v26JG+/9eaNfEsFcichWZUHrHatIjILOCoYP9XgOUi8n/OuXOKODYjR7xl4n/ovlmfr7YfMUJr\nArzlYnQ8lhtBAAAgAElEQVScAQOyt5DvDNJNZeAD96ncX562tsSeXo2N8dqmZBKVuO4vyFwvY1Qe\ncS2VOufcOuAY4Hbn3N7AocUblpELzsEdd4Si8pOfwFNPqaXS0JDYJXbQIJv1sZAMHFgelko6tthC\nkzdStan/wx90GXVhrV4N77zTPossFYVwf4FZKtVGXFHpLiLbAMcDfy/ieIwc2GKLMPsruWbimms0\niyfOxcHIn3Jxf2XCx9KSOeMMdY1GheG3v9VlnO9NJkvl3XfNUumqxBWVS4FHgfeccy+JyFjg3eIN\ny4jL+PG67NkzMRNn4UK94JlVUlz69dPPPd0de7nTvXuiMHi3Vz6iMm+efg5tbfDkkzrlQhzMUqku\n4orKEufcrs657wE45z4Afle8YRnZ8BNv+cZ8PXsm3jEvXJi5IaBRGLp108QH31stFVOnwnnndd6Y\nciHZheVFJU4GWPJrx4/XGSO9hRyd8TET5daZwOgYcUXlmpjbjE7iyisTG/P17JkYMF671kSls8jW\nsuSOO+Cee4o/ju23z/01PXokCsP69fCzn6WeYyXVa5PdXytXpk9vTkffvnDBBYkFukblkjH7S0T2\nBfYDhohINNOrP2COlRJy552Jj3v3Vj+2p7lZ3V9G8YkTV8nlf3HvvXqhPeKI7PuuW6f/+/7946UB\nJxO1NpqbNbFj2LB4r40Kkk9nbm7OXVS8td3YmDhdsVGZZLNUaoC+qPj0i/ytA1KUTRmdRfId4vjx\n7e/0bDa9zqHQwfoTToCvfEXneM92915XBz/8Yf6zJ0ZjKj17wrJl8XvD+dc+9VT43k1NuYuKF6Z0\n1flGZZHRUnHOPQU8JSK3OucyzGhtdDbJBYz+QrDDDjBpkvq2rXFk5xBHVNJlSWXipJO02nzXLKXG\nzzyjF/hMtSjp8NaGH9+aNfF7w3n313vvhdsWLzZR6erEnaO+VkT+CIyOvsY5d3AxBmVkp6kJXn45\ncduLL8K22+qP3ESl8xg8OHPHXsg/ZTZOB+T6+vy7JHTvri4rP/61a+OLk3edRQV13jxYujR9GnMq\nfFKAL9Y1Kpu4gfq/ArOB/wbOi/wZJeDZZ+HNN2HChMTte+6phY7+R2qi0jmMGwfz52fep7k5fiA6\nekHOJlagcZB8uyR0765B8uHD9fHq1blbKgsX6uNJkzSu9/rr4XQMcfjRj9SyMVGpDuKKyifOuf91\nzr3onHvF/xV1ZEZajj1Wl+nSPr2YWEylc9huO/jgg9TPeSFZvBh23DHe8erqwv/t4sXxXvPxx/H2\nS8XfI+XM+YjKhx/qYxEYMgSuvhoOOij++/fqpR2RswmzURnEFZWHReR7IrKNiAzyf0UdmZGWb3xD\ng7Pp8GJilkrnMGRI6KZ66SWtSwF1ea1cGRagRmMPmWhpCV1QyS7OQvPWW4mPV6+O7/7q21dTkD/8\nEI4/XtsDjR+v28aOzW0cX/oS/OtfVllfDcQVlVNQd9ezaEPJV4Aif92NZF59Ve8GW1pg1Kj0+/n0\nVROVzmHwYI1nicDvf691KaANPI89NvfU7pYWzQADjU/E4XcFKkVubY1vqYwcqZ2OFyyAG2/UqYO3\n3Vaf81NYx2X77eEvf4FjjsntdUb5EUtUnHNjUvzleC9idJS339Zl9E42Fd6/Hrehn9Exhg4Ns6ei\n9UMrVsBrr+U+02ZzM1x+OTz/PDzxhE7Glo1C9Hjzwf644x01Sgslo6/18aBcRcUX6v7jH7m9ziOi\nqc1G6YklKiIyNdVfsQdnJOKnbm1pyfzD9x1pLabSOaRqnOhjKRs26AX24ov18ciR2Y/nbxp8Wu5D\nD2V/Tb7/6699TZeHHhpaR3HdX/5cohaxF5Vc05sL0f1h5syOH8PoOHHdX3tG/j4PTEfnVzGKxGmn\nhdP/eryoNDfH+9GOGFH4cRmpSf5/RDOZamrgsMN0/aOPsh+ruVlvGnKp9cjXUrnnHth3X5gyJTxG\nXEvFi2l0nH5bvpZKPrU2ftrsOJ+tUXxi1ak4586KPhaRAUAndDPquvzpT+2DnbmIytq1NhlXZ5Kc\nLuxn3QS9wCbHt557DvbYo/0F3DcK3WKLsGVJnIt8R9xfzz6rS+/KihuL22ef9tv8a3MVFT/+fLo9\nNzToMl0GntG55DtHfSMwppADMdrTowd87nPhY19x3NCQXVRMUDqXqKgkdy2uqUm8UN92G+y3H1x/\nffvjvPhi2CjUi4q/mUgm2i4+F6smHf4YQ4fG2z9V00l/nvlYHKCZdLniBTxTp2ij84g7nfDDQGBk\nsgUwHvhLsQZVLFasgEsuSf1jLkfeeUeX69frBWbVKn382GPwgx+UblxGe6Ki4hy8Eqni6tEjseJ9\n2jRdLlvW/jg//Wni677whfSi0tAAW26pbp9CZvrlUp1/xRVhxheE9TW5Wiqgn9m3v5376zZu1Dii\niUp5ELdNy28j658A9c65DpRbdT5tbaHfthxExbnQzZHquSjz58NnP5tYXZ1qelijdNxwA8yerVP0\nrl+vtUSemprUc4usXt1+W3Ic7Oyz4fbbU79nQ4OmKxdKUCZP1my1OG3vPT/5SeJjb6Hk8/2sqcmv\nTmXjRrWuTFTKg7gpxU8B89AOxQOBiitRKrcWEDfcELb8TiZ5rL7SOCoqcXpCGZ3H6afDt76l69/9\nrrq3ohfnVDcPq1fDrbcmptFusw2cf374OHqhff99ePrp8LlCx80mToS77+7YMToy02i+otLUpDeM\n0TiWUTriphQfD7wIHIfOU/+CiHSo9b2IDBSRx0TkHRF5VETa/TxEZISIPCEib4nIHBHJ2+kTvVAn\nWwKlYPbs9M95N5fHByBXrAhTR8eNK864jPzx6bTHH6/Bb/89Szer4eLFcOqpcOaZ4ba1a2H06PBx\n9EJ70knqDvN4S6WcSHejFIeOWCoDB+rnbdMSl564RupPgT2dc6c456YCewE/6+B7XwDMdM7tCDwB\nXJhin0+Ac5xzE4B9gTNFZKd83ix6F1OKqUsvvxx+/OPwcaYsl1WrEt0HflbBFSvCIGqqzBujtIwe\nrRe25LoVn53k8Vl9zz2ny/r60PJcty4xphG90CbHVsoxw68UlsrGjeoCzDats9E5xBWVbs655ZHH\nq3J4bTqmALcF67cB7eqGnXNLnXOvBesbgLnA8HzeLCoqpfji/f73ia00Ms2vsWoV7BRI58CBYWvx\nlSttiuBKYNddE4UhOXaSSgimT9elv0B6amrCu+/kWEc5Wiod+X7mIyqrVmlWpBcVc4GVnrjC8K/A\nRTVNRKYB/wAe6eB7b+WcWwYqHkDGr6OIjAZ2A17I9Y1WrNC28J5SxCP8Reb113WZ6cezZAnssouu\nDx6sF4+2NrVYcpmnwigd0Qp3LypvvKHLVNlV110Hs2bBjBmJolJbG35Xkl1L5WipjBmTX60J5Ccq\ngwfDr3+tn3e/fmaplAMZRUVEtheR/Z1z5wE3ALsGf88Bf8x2cBH5t4i8EfmbEyxTVeOnjXSISF/g\nPuDswGLJCZ+a64nbTryQ+JqD44/XZaYf3oIFYcyke3e9eLS06Ho+qZpG5+OtigsuCF2V/kbBF/od\neGDiaw46SN1n0SkNevUK65OiorJokX6Py3FO93xdYLW17V3Tn3ySPqXa88ornef+8paRkZ5sYbWr\nCGIdzrm/AX8DEJFdgueOzPRi59xh6Z4TkWUiMtQ5t0xEtgaWp9mvOyoodzjnsnZBmu79CMCkSZOY\nNGlSO7dBKUTF37n69964UZezZmnBV3TCrQUL4IADdL1nz1BUamq0xiHdPCpG+eBjYpdd1v65MUHZ\n8MyZcMstcMYZic9HLZUBA8KYjK+FaWkJU49/+cvCjbnU1NaqGG/aFH7Hd99dLfdk78L99yd2NO4s\n99fw4frbrOQ+Y7NmzWLWrFlFO342URnqnJuTvNE5NydwR3WEGcA04Aq0tX46wbgZeNs5d3Wcg0ZF\nxZOcEVIKUfGtNnwev/+f+smMohlpCxbAySfreq9eOgHTpk362ilT9M8ob9LVeixfrv/r665Tq3Pr\nrdvvkywqy5bBI4+E3+Noj6tqu8Goq1MR9ef15pu6XLcODjlE56tpa4OvflVnmfT06tU57q/mZpjT\n7opYWfibbc+ll15a0ONni6lkCgN2tOTqCuAwEXkHOAS4HCCYCOzvwfr+wEnAwSIyW0ReFZHJub5R\nNJ145MjSiIoXE79sakq/74IFYVppr146XeuBB7ZPNTbKl3SiMmSIBrP9TcR222m8L1ocGRUKv/6H\nP4Suoe23D5/Pta1+ueNFxbPddrr84AOdsKy5OUxyiXYt6N278wL1lgyQmWyi8rKInJa8UUS+jU7U\nlTfOudXOuUOdczs6577onFsbbF/inPtKsP5/zrktnHO7Oed2d87t4Zz7V67v5b8Ee+yhbSWWLOnI\nyPPDi0mPHpkF5RvfUFHxrS/8RSM5LmSUN8Nj5ihOmKD9vqLZgFFR8eI0erSKSnKlejnUXBWSujqd\nOdMLqHfz+cnK6uvDYP68eeHrUsVUmpoy/9byQSR0XRupyeb++iHwgIicRCginwNqgP8q5sAKic++\n6dNHv3ilCLT5YGNrq7ozBgwIU4Wj+EmevAjFbe5nlBe33Za5wDWZaNZTctuVH/xALexNm8LZFj3J\n3ZErncGD4dFHdYri8ePVaqmtDb0LO+4Yxleyub9OPFFrgVL1WMuX3r0tUJ+NjKISpPzuJyIHAZ8J\nNv/DOfdE0UdWQD78UJfNzfqlKMWdhveH19Vp8dvYsYmi0traPmtm0SIVn0GD4MorO2+sRsfZYQf9\ni4u/M29tbW+N9O6t359Nm9SyiYpKtsyoSsNbJj47csMGFdJFi8J9vABHxaJ3b7X2Fi4Mt61dqzGs\nQtKR4s6uQtzeX086564J/ipKUCAMbLa06B1NKURl0yb4n/8JaxSS579IFWAcNkx/LIVoa26UNy0t\nGm9J1YixtjYUlWOP1c7EnnxrQsoVf24rVsB99+lvtbY2nDkTQlGJurEHDNBYVTReWoymq9bINTtd\n4iPyftWWFr1IF9rPGofmZhUHbzr36qX+8Msv14uJF76amvZdaQsx/7hR3vzjH5rhlQpfVd/UBN/7\nngbtPdXm/vKicsghcNxxKhw+A8wTFZXx43V9zBjtQvHOOzB3rt6Q5dJtOS5mqWSnS4iKdy2U0lJp\nblafr89s8f2hzj9f77AmTlSXWEtLWKPiMUul+jn88MQJ2aLU1mo3hZ499aLmL5YHHqhzy1cTRyWV\nRacSTf/7Xb1aBeTXv1a34LBh6hJ79VUVnGJYFSYq2alqUdljD03D9aIyaJCKSqkslaionHRS+Jy3\nRHzsJzlQa6LStamt1eB08vfgqad0np1qYqed4JprErsHPPNM4j7LliVmyJ13nlpz/ftrlthbb+l2\ns1RKQ1WLyuzZWnn77LPw8MPwz3+WNlDft6/GTsaODYsbof0dVXJBmxedX/yiuGM0ypOaGr058i1Z\ninGxLCeOPDIxAWG//XR55pnq7qqvD5MgRo4M9/NdK3wXA/85zZ1buLGZqGSnqkUFwhYYY8aElkop\nRQXaWyL+y+9npExnqUTn3TC6DrW1iaJS7WyzTWL9jb/pmjhRn6uvV6tk4kSt8fGkE9srrijc2ExU\nslO1opJcFObv/n3X185OxfTuL0g//asfU3KVtL8Dy2XucKN66NNHYwT+5mKXXRK7IFcbvkYryj33\nwCmnaN3WRx/pb+S11zLXcT32mC4L+bvxN6Q2GVh6qlZUklto+wu5iK539kRdmzaFX+7kC4KP8aTr\nW+QF0u6SuibDhydaKuPGdb0CvK99TcWmXz+tpB82LPV+yc05oXDTRbz+elj3UsR+jBVP1YpKcn+e\naOCvFC6w5ubwh5BcSb/ffnD00emL5bqK28NIjW/ZY98D/QzeeisxlhLlt79NfLzvvoX73HyrpL32\nsj58mejAjNLlTfKdzMCB4Xpn16o4F7auh/ZtI3wsxe+bzG67lWZiMaM8GDJEl10xCzDZqu/fX6vs\n/WeSTN++mmF57bXw05/qfoVyVS1eDGedpW5qE5X0VKWlsnFjYoO+q65KnNyqsy2VlhZ9fx9wzCee\nE62iNroWPsbW1aq5u3Vr7+bzVkemguD+/bVHGKjrq1Cu7g0bVLT+8x/tx1btWXj5UpVf0+Q7k+S7\nnc62VDZuTBxDtfVrMjqHamvJko1UIuqLhrN1mfA3YYMHF85SaWxUUTnnnMIcr1qpSlFJvjNJ/gJ6\nS+XttztnPE1NJipGx0nn8qlWUonK5z+vy7iisuWWhbVU+vQJpwSHRI+IoVS1qJx4oi6TLZVevXT2\ntgkTOqd3komK0VGuvhp+9KNSj6JzSeVe8kkL2Wa89PGnPn0Ka6n06ZNYElCK7hzlTlWLig+Mp3J/\nffyxrv/ud8Wf6KipKfGLWG1NAI3i84MfJM4OWe185jM6I2YyPjaazfoYPRr+/e/CtmXy7i/Qxp4A\nF11UmGNXE1UtKv4LmMpS8XNSnHde4vSlxSBqqTz+uE5CZBhGel56CWbOTP+8n247HSLabLOurnDz\n1nv3F8B11+nSCpLbU5UpxV5Upk6F+fPVzRWld+/EWePWr9f5GIpFVFQOPrh472MY1UIm91YunoXk\nOe+jHHigdob+3e/iHStqqXhMVNpTlZbKf/6j7eMPOEArX6M1KqCWSnTO91TT+haS5JiKYRidQypR\nWb9eM+meeQZmzIh/LB9T8ey6K3zpS4UZZzVRdZaKc+rSykSvXonFS53p/jIMo/Ooq9OpiF9+OZyv\npn//MC04l6SZqPsLtG2L0Z6qs1TipPglX+CLbakk16kYhtE5DBigc6wkB/19O/wNG8Jt6dxqv/kN\n7L13aveX0Z6qExVfKX/BBen32X13XfoviFkqhlGd1NWl3t7SonU/69ZpUP/UU7Uu5vnn2+/75z9r\ni/1kS8VITdWJyqZN2jxy+vT0+xxzDPz+9zpZFoTzwxcLExXDKA3J00h4Wlpg663Dbua33qrL5L58\nEGaR+jYtRmaqTlQ2bFA/aao5GTwi2hjOdy6+8EL1uRaL5DoVwzBKS0tL+wQegPPPb7/Nu9R79Mhe\ndGlUoag8+aRaBXGavUV9qMXsOmqWimGUF01NqcsIolmh0X2h67XJyZeqE5XTTovfeC9qGhez46iJ\nimGUnttuC28k58zR9eTCyFQT4flOydYpPB5VJyoQv8nbPfeEk/oUs1XL+vXmizWMUjFvni6nTUvs\nA/aPf2gr/ejMkN27t58Ww0/4Z66veFSlqAwfHm+/UaNgzBhdnzateMKydm1q/61hGMXHz60CcPjh\n4bpvTnnqqeqpWLhQg/dLliS+3nfo6Grz2eRLVX5Mu+wSf18frF+6NLF1SyFZu7a4bWAMw8jMDTfo\n8sknw20vvKDLX/9am7xuu6027YyKSmtr6E43UYlHVX5M48bF3zeax/7BB4UfC8CaNSYqhlFKRo1q\nv23o0Pbbhg1LLDHYuDHM3DRRiUfVfUwffACXXx5//wMPhPHjdT1aXVtIzP1lGKUlbtHi7rvDK6+E\nj6OiYtMHx6PqRGXMmNwCaiKw8866XkxRMUvFMEpHXFHZZZcwsA+JomKT68Wj6kQlH3waYTFEpa1N\n0xbTtYswDKP4jBgRb78xYxLd4FFRWb688OOqRkxUCH2lxRCVdes0nThV/rthGJ3DkCFw7726fsMN\n8OGHqffbdlvtauzxonLQQbD//sUfZzVgokJ4wff56IVk7VqzUgyjHPCdirfaKv3MkQMGaINZP31G\nY6MWLj/xBPzpT50yzIrHRIVQVLLNe50P1i7bMMoD30EjUx8+H4y/7z5dmus6d0xUCEXFdywtJM3N\n6TulGobRefgEnjgi8eUv63LdOpsyOFdMVIBDDtFloUXl44/V+rH2DoZRenwGmJ9PKR2//GUoPOvX\nm6jkiokKcNJJcPPNhRWV+noN+j33nFkqhlEO1NZqK6Zsv8fa2vBasG6d9gcz4lN1c9TnS01NYUXF\nN6U791zrUGwYlURNTdh40txfuVMyS0VEBorIYyLyjog8KiJpPZ0i0k1EXhWRGcUaT/SLVAh8u2wI\n52MwDKP8SbZUTFRyo5TurwuAmc65HYEngAsz7Hs28HYxB5PKUnn3Xa2izad+JSoqhmFUDrW1Zql0\nhFKKyhTgtmD9NuDoVDuJyAjgcKCoWeLRuxOABQtghx3gwQfh29/O/XjFavliGEZx8V6Lpia46SaL\nqeRKKUVlK+fcMgDn3FJgqzT7/T/gPKCI02i1t1T8PCsLF8LKlbkfzywVw6hM/A1mfb0+thvE3Chq\noF5E/g1EG0wLKg7/nWL3dqIhIkcAy5xzr4nIpOD1GZk+ffqn65MmTWLSpEmxxhoVlba2cPvSpflV\n2jc2wtSpOj9DtOupYRjljXd/LVyojz/zmdKOp9DMmjWLWbNmFe34RRUV59xh6Z4TkWUiMtQ5t0xE\ntgZStWvbHzhKRA4HegH9ROR259zUdMeNikoueJO3rS2xT9fSpe3nsY6Dr6TPpQ2/YRilx18L1q6F\n446DffYp9YgKS/LN9qWXXlrQ45fS/TUDmBasnwI8lLyDc+4i59xI59xY4ATgiUyC0hFqa+Hll+Hi\nixO33357aKk88gg8/ni8423YEL/dtmEY5YN3f1k3jPwoZZ3KFcBfROSbQD1wPICIbAPc6Jz7SmcO\npqZGl7/8ZfvnvKgccYQu48xl39hoomIYlYh3f5mo5EfJRMU5txo4NMX2JUA7QXHOPQU8VazxeFFJ\nxfr1KiRDhsCKFfGO19io8RTDMCoLH181UckPa9MSkEpUvvY1XToXP5urXz9YssS6ExtGpWKWSscw\nUQlIJSrnnhuuz5oVr43Lhg3w/vvm/jKMSsVEpWOYqASk+vJsFamcOfLI+G1cXnwR7rzT3F+GUYmY\n+6tjmKgERC2VUaN0OXBg4j7ZLJXWVl3++Me6HD++MGMzDKPzqK3VaSsWLTJRyQcTlQAvKocfDvvu\nq+s+JjJhgi7b2sL57FMRbRy5554wfHjhx2kYRnHxQnLTTSYq+WCiEuALHk8+ObRIRNRq8fNVQ+Ys\nsWgwv9qqcA2jqxD9jZuo5I7NpxLg56bu2zcxdrJggWZ//e1vMGNG5hqVqKhkmgfbMIzyJSok3kth\nxMcslST69m0fOxHRGhXQ59IJS2Nj+CXMZNEYhlG+dOsGW2+t6xYXzR0TlSQGDEid5dXQoMs+fdJ3\nLd1zT3jrLV03UTGMyuXoYCKOnj1LO45KxEQlwvPPw267pc7yGjtWzeIBA2DNmtSvj77ORMUwKhcv\nJiYquWOiEmHvvdXVdc45iYWPAJddpt2KBw5MLypRTFQMo3Lp0UOX9jvOHROVFBx3HPzmN4nbunXT\nL1hjY7z5USyd2DAqF5+4I1lncDKSMVHJkS23hL/+NXMW2KJFMG1apw3JMIwCE6cTuZEaE5UcOeMM\nzQTr1g1eeCH1PsOGZS6SNAyjvLHfb/7YR5cjtbWwPJij8qOP2j//7LOdOx7DMAqP9e3LHxOVHKmt\nDedUiQbsP/lE726qbepRw+iKHHYYDBpU6lFUJiYqORIVldWrw+1r12q6sQX2DKPy2XlnWLWq1KOo\nTExUcqS2NnR7RS2V1avtzsYwDMNEJUeieetr1sDf/65pxiYqhmEYJio5E202t3q1Tt51990qMAMG\nlG5chmEY5YCJSo74FvkQur9699a5VGz6YMMwujomKjmycaMuH300UVQ2brR294ZhGCYqOeLjJttv\nH2aB1daqpdK7d+nGZRiGUQ7YJF05suuusHkzrF8fZoG1tpqlYhiGAWap5EX37lBXFz7evNlExTAM\nA0xU8ibaG2jzZnN/GYZhgIlKh/BTjpqlYhiGoZiodIBRo3RplophGIZiotIBpk/XpVkqhmEYiolK\nB5g8Gb7zHZ2b3iwVwzAME5UOU1NjlophGIbHRKWD9OhhMRXDMAyPiUoH8aJilophGIaJSofxzSRN\nVAzDMExUOkz//rBunQqLiYphGF0dE5UO4kWlsRH69Sv1aAzDMEqLiUoHqatTUdmwAfr2LfVoDMMw\nSouJSgfxloqJimEYholKh+nfH+rrNQMsOn+9YRhGV8REpYP07w/vvVfqURiGYZQHJRMVERkoIo+J\nyDsi8qiI1KXZr05E/ioic0XkLRHZu7PHmon+/Us9AsMwjPKhlJbKBcBM59yOwBPAhWn2uxp4xDk3\nHpgIzO2k8cXCi8q//lXc95k1a1Zx36DE2PlVNnZ+hqeUojIFuC1Yvw04OnkHEekPfN45dwuAc+4T\n59y6zhtidvr00eXYscV9n2r/Utv5VTZ2foanlKKylXNuGYBzbimwVYp9xgArReQWEXlVRP4oImVV\nYigCN98M221X6pEYhmGUnqKKioj8W0TeiPzNCZZHpdjdpdjWHdgDuM45twfQhLrNyopTT02cXtgw\nDKOrIs6lupZ3whuLzAUmOeeWicjWwJNB3CS6z1DgOefc2ODxAcD5zrkj0xyzNCdjGIZRwTjnpFDH\n6l6oA+XBDGAacAVwCvBQ8g6B4HwkIjs45+YDhwBvpztgIT8YwzAMI3dKaakMAv4CbAvUA8c759aK\nyDbAjc65rwT7TQT+BPQAPgBOdc41lGTQhmEYRkZKJiqGYRhG9VEV4WURmSwi80RkvoicX+rx5IOI\njBCRJ4ICzzki8oNge9oiURG5UETeDQpDv1i60cdDRLoFWXwzgsfVdG7tinSr7Px+JCJvBok2fxaR\nmko+PxG5SUSWicgbkW05n4+I7BF8JvNF5KrOPo90pDm/Xwfjf01E7g9KNvxzhTs/51xF/6HC+B4w\nCnWRvQbsVOpx5XEeWwO7Bet9gXeAndCY00+C7ecDlwfrOwOz0bjY6OAzkFKfR5Zz/BFwJzAjeFxN\n53Yr6polGHddtZwfMAx1PdcEj+9F46AVe37AAcBuwBuRbTmfD/ACsGew/gjwpVKfW4bzOxToFqxf\nDknFLRMAAAQfSURBVFxWjPOrBktlL+Bd51y9c24zcA9aWFlROOeWOudeC9Y3oJ0DRpC+SPQo4B6n\nBaELgHfRz6IsEZERwOFofMxTLeeWqki3gSo5v4AtgD4i0h3oBSyigs/POfcfYE3S5pzOJ8ha7eec\neynY73ZSFHGXglTn55yb6ZxrCx4+j15foMDnVw2iMhz4KPL442BbxSIio9G7jOeBoS51kWjyeS+i\nvM/7/wHnkViPVC3nlqpItzdVcn7OucXAlcBCdKwNzrmZVMn5RUhXkJ3ufIaj1xtPJV17volaHlDg\n86sGUakqRKQvcB9wdmCxJGdSVFxmhYgcASwLLLFMad8Vd24ByUW6jWiRbsX/7wBEZAB6Fz8KdYX1\nEZGTqJLzy0C1nQ8AIvJTYLNz7u5iHL8aRGURMDLyeESwreIIXAv3AXc453zdzrKgCJTAHF0ebF+E\npmN7yvm89weOEpEPgLuBg0XkDmBpFZwb6B3cR865l4PH96MiUw3/O1Bf/AfOudXOuVbgAWA/quf8\nPLmeT8Wdp4hMQ93QJ0Y2F/T8qkFUXgK2F5FRIlIDnIAWVlYiNwNvO+eujmzzRaKQWCQ6AzghyMIZ\nA2wPvNhZA80F59xFzrmRTjsjnAA84Zz7BvAwFX5uoEW6wEciskOw6RDgLargfxewENhHRHqKiBAW\nIVf6+QmJlnNO5xO4yBpEZK/gc5lKiiLuEpJwfiIyGXVBH+Wca47sV9jzK3WWQoEyHSaj2VLvAheU\nejx5nsP+QCuavTYbeDU4r0HAzOD8HgMGRF5zIZqpMRf4YqnPIeZ5foEw+6tqzg2dluGl4P/3NzT7\nq5rO75JgrG+gQewelXx+wF3AYqAZFc1TgYG5ng/wWWBOcO25utTnleX83kULzV8N/q4vxvlZ8aNh\nGIZRMKrB/WUYhmGUCSYqhmEYRsEwUTEMwzAKhomKYRiGUTBMVAzDMIyCYaJiGIZhFIxSzvxoGBWL\n6CRzj6OtPLZBa4yWo8Vmjc65A0o4PMMoGVanYhgdREQuBjY4535X6rEYRqkx95dhdJyEJpkisj5Y\nfkFEZonIgyLynohcJiInisgLIvJ60BIDERksIvcF218Qkf1KcRKGUQhMVAyj8ETN/12B09GJkL4B\njHPO7Q3cBJwV7HM18Ltg+1dJnHPGMCoKi6kYRnF5yTm3HEBE3kd7SoH2U5oUrB8KjA+a9gH0FZHe\nzrmmTh2pYRQAExXDKC7RbrBtkcdthL8/AfZ2OnOpYVQ05v4yjMKTaSKyVDwGnP3pi0UmFnY4htF5\nmKgYRuFJl1KZbvvZwOeC4P2bwBnFGZZhFB9LKTYMwzAKhlkqhmEYRsEwUTEMwzAKhomKYRiGUTBM\nVAzDMIyCYaJiGIZhFAwTFcMwDKNgmKgYhmEYBcNExTAMwygY/x/mMNGYLMmcywAAAABJRU5ErkJg\ngg==\n", "text/plain": [ "" ] }, "metadata": {}, "output_type": "display_data" } ], "source": [ "f = simulate(2)\n", "plt.plot(np.real(f)) \n", "plt.xlabel('Time')\n", "plt.ylabel('Counts')\n", "plt.title('Recovered LightCurve with B=2')" ] } ], "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": "3.6.4" } }, "nbformat": 4, "nbformat_minor": 1 }