KOI-54_V1.ipynb

{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import phoebe\n",
    "from phoebe import u # units\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "logger = phoebe.logger()\n",
    "\n",
    "b = phoebe.default_binary()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "ParameterSet: 29 parameters\n",
      "            times@KOI_lc@dataset: [0.         0.00775194 0.01550388 ... 0.98449612\n",
      " 0.99224806 1.        ] d\n",
      "           fluxes@KOI_lc@dataset: [] W / m2\n",
      "         passband@KOI_lc@dataset: Johnson:V\n",
      "  intens_weighting@KOI_lc@dat...: energy\n",
      "*             ebv@KOI_lc@dataset: 0.0\n",
      "               Av@KOI_lc@dataset: 0.0\n",
      "               Rv@KOI_lc@dataset: 3.1\n",
      "    compute_times@KOI_lc@dataset: [] d\n",
      "*  compute_phases@KOI_lc@dataset: []\n",
      "  compute_phases_t0@KOI_lc@da...: t0_supconj\n",
      "           sigmas@KOI_lc@dataset: [] W / m2\n",
      "       pblum_mode@KOI_lc@dataset: component-coupled\n",
      "  pblum_component@KOI_lc@dataset: primary\n",
      "    pblum_dataset@KOI_lc@dataset: \n",
      "           pbflux@KOI_lc@dataset: 1.0 W / m2\n",
      "          l3_mode@KOI_lc@dataset: flux\n",
      "               l3@KOI_lc@dataset: 0.0 W / m2\n",
      "          l3_frac@KOI_lc@dataset: 0.0\n",
      "          exptime@KOI_lc@dataset: 0.0 s\n",
      "  ld_mode@primary@KOI_lc@dataset: interp\n",
      "  ld_mode@secondary@KOI_lc@da...: interp\n",
      "  ld_func@primary@KOI_lc@dataset: logarithmic\n",
      "  ld_func@secondary@KOI_lc@da...: logarithmic\n",
      "  ld_coeffs_source@primary@KO...: auto\n",
      "  ld_coeffs_source@secondary@...: auto\n",
      "  ld_coeffs@primary@KOI_lc@da...: [0.5 0.5]\n",
      "  ld_coeffs@secondary@KOI_lc@...: [0.5 0.5]\n",
      "    pblum@primary@KOI_lc@dataset: 12.566370614359172 W\n",
      "  pblum@secondary@KOI_lc@dataset: 12.566370614359172 W\n"
     ]
    }
   ],
   "source": [
    "# Add a 'light-curve(lc)' dataset to the bundle. \n",
    "\n",
    "b.add_dataset('lc', times = np.linspace(0,1,130), dataset = 'KOI_lc')\n",
    "print(b.get_dataset(kind = 'lc', check_visible = False))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<ParameterSet: 4 parameters | contexts: model, figure>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Computation method given in paper = 'Wilson'\n",
    "\n",
    "#b.run_compute(irrad_method = 'wilson')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'primary' probably has a radiative atm (teff=8498K>8000K), for which gravb_bol>=0.9 might be a better approx than gravb_bol=0.32.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'secondary' probably has a radiative atm (teff=8667K>8000K), for which gravb_bol>=0.9 might be a better approx than gravb_bol=0.32.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'primary' probably has a radiative atm (teff=8498K>=8000K), for which irrad_frac_refl_bol>0.8 (suggestion: 1.0) might be a better approx than irrad_frac_refl_bol=0.60.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'secondary' probably has a radiative atm (teff=8667K>=8000K), for which irrad_frac_refl_bol>0.8 (suggestion: 1.0) might be a better approx than irrad_frac_refl_bol=0.60.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'primary' probably has a radiative atm (teff=8498K>8000K), for which gravb_bol>=0.9 might be a better approx than gravb_bol=0.32.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'secondary' probably has a radiative atm (teff=8667K>8000K), for which gravb_bol>=0.9 might be a better approx than gravb_bol=0.32.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'primary' probably has a radiative atm (teff=8498K>=8000K), for which irrad_frac_refl_bol>0.8 (suggestion: 1.0) might be a better approx than irrad_frac_refl_bol=0.60.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'secondary' probably has a radiative atm (teff=8667K>=8000K), for which irrad_frac_refl_bol>0.8 (suggestion: 1.0) might be a better approx than irrad_frac_refl_bol=0.60.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'primary' probably has a radiative atm (teff=8498K>8000K), for which gravb_bol>=0.9 might be a better approx than gravb_bol=0.32.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'secondary' probably has a radiative atm (teff=8667K>8000K), for which gravb_bol>=0.9 might be a better approx than gravb_bol=0.32.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'primary' probably has a radiative atm (teff=8498K>=8000K), for which irrad_frac_refl_bol>0.8 (suggestion: 1.0) might be a better approx than irrad_frac_refl_bol=0.60.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'secondary' probably has a radiative atm (teff=8667K>=8000K), for which irrad_frac_refl_bol>0.8 (suggestion: 1.0) might be a better approx than irrad_frac_refl_bol=0.60.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'primary' probably has a radiative atm (teff=8498K>8000K), for which gravb_bol>=0.9 might be a better approx than gravb_bol=0.32.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'secondary' probably has a radiative atm (teff=8667K>8000K), for which gravb_bol>=0.9 might be a better approx than gravb_bol=0.32.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'primary' probably has a radiative atm (teff=8498K>=8000K), for which irrad_frac_refl_bol>0.8 (suggestion: 1.0) might be a better approx than irrad_frac_refl_bol=0.60.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'secondary' probably has a radiative atm (teff=8667K>=8000K), for which irrad_frac_refl_bol>0.8 (suggestion: 1.0) might be a better approx than irrad_frac_refl_bol=0.60.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'primary' probably has a radiative atm (teff=8498K>8000K), for which gravb_bol>=0.9 might be a better approx than gravb_bol=0.32.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'secondary' probably has a radiative atm (teff=8667K>8000K), for which gravb_bol>=0.9 might be a better approx than gravb_bol=0.32.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'primary' probably has a radiative atm (teff=8498K>=8000K), for which irrad_frac_refl_bol>0.8 (suggestion: 1.0) might be a better approx than irrad_frac_refl_bol=0.60.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'secondary' probably has a radiative atm (teff=8667K>=8000K), for which irrad_frac_refl_bol>0.8 (suggestion: 1.0) might be a better approx than irrad_frac_refl_bol=0.60.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'primary' probably has a radiative atm (teff=8498K>8000K), for which gravb_bol>=0.9 might be a better approx than gravb_bol=0.32.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'secondary' probably has a radiative atm (teff=8667K>8000K), for which gravb_bol>=0.9 might be a better approx than gravb_bol=0.32.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'primary' probably has a radiative atm (teff=8498K>=8000K), for which irrad_frac_refl_bol>0.8 (suggestion: 1.0) might be a better approx than irrad_frac_refl_bol=0.60.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'secondary' probably has a radiative atm (teff=8667K>=8000K), for which irrad_frac_refl_bol>0.8 (suggestion: 1.0) might be a better approx than irrad_frac_refl_bol=0.60.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'primary' probably has a radiative atm (teff=8498K>8000K), for which gravb_bol>=0.9 might be a better approx than gravb_bol=0.32.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'secondary' probably has a radiative atm (teff=8667K>8000K), for which gravb_bol>=0.9 might be a better approx than gravb_bol=0.32.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'primary' probably has a radiative atm (teff=8498K>=8000K), for which irrad_frac_refl_bol>0.8 (suggestion: 1.0) might be a better approx than irrad_frac_refl_bol=0.60.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'secondary' probably has a radiative atm (teff=8667K>=8000K), for which irrad_frac_refl_bol>0.8 (suggestion: 1.0) might be a better approx than irrad_frac_refl_bol=0.60.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'primary' probably has a radiative atm (teff=8498K>8000K), for which gravb_bol>=0.9 might be a better approx than gravb_bol=0.32.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'secondary' probably has a radiative atm (teff=8667K>8000K), for which gravb_bol>=0.9 might be a better approx than gravb_bol=0.32.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'primary' probably has a radiative atm (teff=8498K>=8000K), for which irrad_frac_refl_bol>0.8 (suggestion: 1.0) might be a better approx than irrad_frac_refl_bol=0.60.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'secondary' probably has a radiative atm (teff=8667K>=8000K), for which irrad_frac_refl_bol>0.8 (suggestion: 1.0) might be a better approx than irrad_frac_refl_bol=0.60.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'primary' probably has a radiative atm (teff=8498K>8000K), for which gravb_bol>=0.9 might be a better approx than gravb_bol=0.32.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'secondary' probably has a radiative atm (teff=8667K>8000K), for which gravb_bol>=0.9 might be a better approx than gravb_bol=0.32.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'primary' probably has a radiative atm (teff=8498K>=8000K), for which irrad_frac_refl_bol>0.8 (suggestion: 1.0) might be a better approx than irrad_frac_refl_bol=0.60.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'secondary' probably has a radiative atm (teff=8667K>=8000K), for which irrad_frac_refl_bol>0.8 (suggestion: 1.0) might be a better approx than irrad_frac_refl_bol=0.60.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'primary' probably has a radiative atm (teff=8498K>8000K), for which gravb_bol>=0.9 might be a better approx than gravb_bol=0.32.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'secondary' probably has a radiative atm (teff=8667K>8000K), for which gravb_bol>=0.9 might be a better approx than gravb_bol=0.32.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'primary' probably has a radiative atm (teff=8498K>=8000K), for which irrad_frac_refl_bol>0.8 (suggestion: 1.0) might be a better approx than irrad_frac_refl_bol=0.60.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'secondary' probably has a radiative atm (teff=8667K>=8000K), for which irrad_frac_refl_bol>0.8 (suggestion: 1.0) might be a better approx than irrad_frac_refl_bol=0.60.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING overwriting model: latest\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'primary' probably has a radiative atm (teff=8498K>8000K), for which gravb_bol>=0.9 might be a better approx than gravb_bol=0.32.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'secondary' probably has a radiative atm (teff=8667K>8000K), for which gravb_bol>=0.9 might be a better approx than gravb_bol=0.32.\n",
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'primary' probably has a radiative atm (teff=8498K>=8000K), for which irrad_frac_refl_bol>0.8 (suggestion: 1.0) might be a better approx than irrad_frac_refl_bol=0.60.\n"
     ]
    },
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Wed, 24 Mar 2021 19:28 BUNDLE       WARNING 'secondary' probably has a radiative atm (teff=8667K>=8000K), for which irrad_frac_refl_bol>0.8 (suggestion: 1.0) might be a better approx than irrad_frac_refl_bol=0.60.\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "<ParameterSet: 8 parameters | contexts: model, figure>"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Setting the value of the parameters in the parameter set. \n",
    "\n",
    "b.set_value('q', value=1.025)\n",
    "b.set_value('period', component='binary', value=42*u.day)\n",
    "b.set_value('sma', component='binary', value=0.395*u.AU)\n",
    "\n",
    "# b.set_value('incl', component='binary', value=5.52)\n",
    "b.set_value('incl', component='binary', value=90.) # Force eclipse # good value = 90\n",
    "\n",
    "b.set_value('requiv', component='primary', value=2.19)\n",
    "b.set_value('requiv', component='secondary', value=2.33)\n",
    "\n",
    "b.set_value('ecc', component='binary', value=0.8342)\n",
    "# b.set_value('ecc', component='binary', value=0.)\n",
    "\n",
    "b.set_value('teff', component='primary', value=8498)\n",
    "b.set_value('teff', component='secondary', value=8667)\n",
    "\n",
    "# b.set_value('gravb_bol@primary', 0.9)\n",
    "# b.set_value('gravb_bol@secondary', 0.9)\n",
    "\n",
    "b.add_dataset('lc', times = np.linspace(0,2*42,100))\n",
    "\n",
    "b.run_compute(irrad_method='none')\n",
    "#b.run_compute(irrad_method = 'wilson')"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Ploting flux vs time.\n",
    "\n",
    "afig, mplfig = b['lc@model'].plot(show=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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FbdT+HB7gVZqsPRvo6x2XxvPWc9k70DRSttvKmADJ21PKto0llJcdPcxBZO4O/sKDNF/vuZ+n2+0mEifbSGH0/AfrI6oxdWbNwxg/zHvoK6b1vo2i3UUV0366+AlSMyPYPj/7qNr0M7vx85QcTnjicoBDI2KyqWV/YrqEbtAyYwLJNpqN8UPht7MZuuhZdu/6E9GJnlNzs5OzeJZbGNMs/qjaqPgwOg89fEGh2+3mIMX0WP8O0dFHn9ZrTGNhWx7G+OGHYfcRwUFKmxwe5nRVmzO4jWdxNm9yVG3R7iLmPfQVm75fBxw+YO5w2NvPNF726jXGD47IcEqIoLTs8FA0h86mOnYwqL0/76TfA6PY8MSHgGe3VTOaMS/1Iqbe9H6oIhsTUNY8jPFDi32ruJi3Kd+XVzHtpFlPspBeuEoPHFXrSG7B2XzKii4XAIcOmEfSbt98yjZtC2luYwLFmocxfmi/5ive5hJ0W07FtPjEcJyxUYRHOY+qdcZF8zlns6tJe8Cz5ZFDBGlsY+Ept4U0tzGBYgfMjfFD+h0XMq1PH/r0aV0x7ZSPbgFu+UWty+Emgb04iiKBWO8xD7vOwzRu9tI1xg+Zg1uRObhVrWpdB/LZTRJTp98DjMftdpMIjOOvpGwbCfQNZlRjgsJ2Wxnjh4LtBWz6bi0H9h4+vvHt2Df4uv2Nv6iNbBrJl73/RNjwYYBnt1Uywl+5j9TsH0OW2ZhAsuZhjB8W3T+RNqd3YO0HCyumhf84kxPX/esXtRHxEYz66RFOfmgE4DlgvoqN5Py4hd5PXRqyzMYEkjUPY/yQ26Evd/EEhYmHb4L4cr83aN0kv8bvVVXUpaT0a0VcalwwYxoTNNY8jPFDUUY3nuIuCpumVUwrK/vlNR6HbAprz9ST/gh4tjyaaiLf3/s1W+ZtD0VcYwLOmocxfjjUJI4cEKp79iR+Xfp2pfUryzuQ424JeJrHCaRy6mMj2PLWlGBHNSYorHkY44fkpd+wh+Y0mzupYtqodc9zX8E9ldafF/EVkzvfCnh2W/3saMr5fMTeroMqrTemobNTdY3xQ2xmEotbDKd5q8P3tmr5/vMU7CmstN7lOnowqL2OGD7mfC5LrrTcmAav3puHiLQG3gKSATfwmqo+e0yNAM8Co4Ai4EpV/SnUWY05pPulveDS946alj60bZX1L5ZcC8u7AbejqoTjJIJcwiSGBvA2NMZnDWG3VRlwp6p2AQYCN4lI12NqzgQ6eL/GAS+HNqIxNVvy4WoWf7C60nmDy6bSau8SwLPlMUJ3kUtTWi75JpQRjQmYem8eqppzaCtCVfOBlUDaMWXnAm+pxxygqYikhDiqMRXWf/kz8xNHsmD84f/8HVddTuTlF1Va37p4LcM2/hPwNI+NzjymDriHxAE2iLlpnBrU9rKIZAC9gbnHzEoDthzxPNs7LefIIhEZh2fLhPR0G6HNBM+B/cUk7vmZ9Zv2V0yb0OIenJTzWCX1R97DSlVZF5nN0Dnjgx/UmCCp9y2PQ0QkFvgIuE1V846dXcm36C8mqL6mqlmqmpWUlBSMmMYAUNq1J5lsZE2vX1dM+yb2PKa3uLDS+hlXvcHsOz4APFsensN4xjReDaJ5iEgYnsbxH1WdWElJNtD6iOetABsIwdSbQ1sSR17nUVZW9V1yW//nUSImvAp4tjxGFPVhrbMTy/6zOMhJjQmOet9t5T2T6h/ASlV9uoqyT4Hfici7wAAgV1Vzqqg1JugiCvbwIM/SYvUZgOdajU/WdmVvbDow6Rf117T+hiZJ4UzEs+VxgGg2u9NICo8IaW5jAqXemwdwMnAZsFREFnmn/RFIB1DVV4Av8ZymuxbPqbpX1UNOYyqEH8jlfh5m6ro4DjWP7D7nQkJCpfU7ozM46B0jyu12811YB/578El+ah+iwMYEWL03D1WdSeXHNI6sUeCm0CQypmYpA9JZNX0HJ2QevrHh0NmPVlnfvXQhYbkK9EFVEQkHbDAo03jZS9cYP4RHu+g0uEWt6/+8ZRyeczzm43a7Oa1sI+dxGZH7HgfsrHPT+DSIA+bGNDYlBSX8eP/nrPt8ZcW0WU1HMXnA/ZXW77rlYXbe/AjgOWDeXvdwHh8TXlr57UyMaehsy8MYPxzYU0T/h89mysB7aXeWZ3eVFORRmltUaf0pj46seOx2u3k3cSWPby4gNiRpjQk8ax7G+MHZJJbRfM6QLu0Z5p12esRMLugPZ1VSX1pUSnlJOZFNI3G73TgcttFvGjd7BRvjh7AoF18ymm1xnSqmVTcY1JLWo9mR1A3w7Lbqnt+RL898noKdlW+pGNPQWfMwxg9hYZDETlyFuRXTHi+5jf6bP6y0fnbK+XwYcyXg2W11SqGDUZNuoXifNQ/TOFnzMMYPDgdsJ5lzf7gbAHeZm1t5li7bKx8Z8Ou21/N0zJ8Bz5bHqxGn0ZXlOBOahiyzMYFkxzyM8dOk/g8QM6g3AOIQinMPMtBR+SVLxw4GtcfRjP10xRUZqrTGBJY1D2P8NGruAxWPxSFExFd9q5ErVtzD3Xt/AGbidrtp495HR+bicvTDdgCYxshetcYEwMHcYiZd/jaL/7200vmRTSPR6BjAs9vqxoPfMJeBuBzuUMY0JmCseRjjp5XRfZne5bcAFOTkM/Jfl7D31Q8qrR0x50FOzJ0MeHZbfZWgzLzmnzjDnSHLa0wgWfMwxk8/a0eyaQVASWQ8g5nO0qya79mpqqxN2M6g169EqjhGYkxDZ83DGD/dmvQO/2nrOYOqzBHOTAZT2CKz0tofbvg3MzpdC3i2PCiPY9cO22VlGi9rHsb46cgzqEoLS2jHWqJLcyutLf1hLgNWv4W7zI3b7ebP6yKISo4PYVpjAsuahzF+un/f7Yxd7TnjSjZuYC0d6LXwn5XWfjzseSIooVwdqCpTnX2YEPHbUMY1JqDsVF1j/NSzeC5FeYkANG2fyNSznqTlBYMrrT00bkdZmWe31TsRZ+Jync7vQhXWmACz5mGMn3oWzOLQ/Q2bd0hg6Gd3VlmbsetHfstPlBVdjWdsM6cNBGUaNdttZYyfjrwxrtsN5eVV156w7hNe4QbKcwtwu908WvQi/94/OvghjQkSax7G+GnWze8w46o3AFj+xlxyXc2ZdtP7ldamP3YTc15eSHRyPG63G6erkLh4e/uZxss2nI3xU8xbLxFTvBf+eTUHI5rwDcNJSKx8SNm2g1JpOygV8Fzn8UaP/cyePTuUcY0JKGsexvjpr93fJScHZgD5aZ35De/xfvfKa3ct38meJVvJHN3VBoMyxwV7BRvjp9zYNLaSBkBpqWdaVYNBLb/7TTqP7cOOn7aiqoxa3oqvBv01REmNCTxrHsb4qd2BZfQs+AGAmKVz+IqRJK7/sdLaLV3OYByvUhKXgNvtZnj+KjJ/qnzgKGMaA9ttZYyfrlhzHxl75gI5RJXl08a1ij2OykcG3N+mJ/9HT26L8lzncVr0e3Tp1IHKW40xDZ81D2P85L79TpZu2UtLoO+9w+HeDbSuovbIiwRVFVUXzjDb8DeNlzUPY/x04t2VX01emW5z36CUcaxZOhe32805Zd+Qkr8GGBm8gMYEkX30McZPpUWlFO4sBGDxhIV8kXU/m2dlV1ob3bMDU9KvJDI1AVXlLyVPcOnWx0IZ15iAqvfmISJviMhOEVlWxfwmIvKZiCwWkeUiUvOACcaEwJxe1+Nq2RyA3GkLGb3gYQrW5FRam3X7YIZvep3MYRm43W4eOqE38f96KYRpjQmsWjcPEWlei6+mfmSYQPXb7jcBK1S1JzAUeEpEwv34OcYE1M/pZ/ActwKwqu8lJLGTkq69avw+t9vN7pQC2p3VJdgRjQkaX7Y8tgHzgQXVfC3xNYCqTgf2VlcCxImIALHe2jJff44xgbao0xju5nHKy6GYCHaThCuq8gs9Fj0zlSXxJ7PizXmoKk1ykln17ZYQJzYmcHw5YL5SVXtXVyAiC+uYpzIvAJ/iaV5xwBhVrXQINhEZB4wDSE9PD0IUYw47dEFgWRlE56xjNCsJLx0GxPyitiCvnPj8fPL2luF2u3luyZdsuDwPtk0MbWhjAsSXLY8TA1TjqxHAIiAV6AW8ICKVDsGmqq+papaqZiUlJQUhijGHnbroaZbTldL9hbRdNJHPOZvI3B2V1u7vcxo9WcKejieiqtznfIAp7a4NcWJjAqfWWx6qevDYaSJSrqrO6moC4CpgvHoGQVgrIhuAzmDXV5n6FZUQTWF0Eu5ype3vL2Bev650655cae2xg0FNkCv5detfbqEY01jU9ToPCUiK6m0GTgNmiEhLoBOwPgQ/15hqDf/oeuB6AOJTY0kf2rbK2rjta/g7LxKz5krcbjeqNhiUadzqfKquiIwVkbtEJF5EfL7iSUTeAWYDnUQkW0SuEZHrReR6b8nDwEkishT4DrhHVXfXNbcxgbRjbT6rZuykvLTSw3HE7N/KbTxL9JZVqCq7y5O56scbQpzSmMCp8bOPiDwFfA9MV9X8SkraAU8DvweaApN8CaCqF9cwfxtwhi/LNCYU5j34JcX/ep8uXzzJyiufYuic8eRu3EeTNr88Y73zdYPJPusAvVPCcb9zM1/HDCRlYFY9pDYmMGqz5fEc0AJ4VkQ+EpG/HTN/vqoWAg8CtkVg/mcUzFtJ1rp3KdiWx6pWp/Eg9+OKi6q0NjLGSav2kUTFOFBVPjgzjsETrglxYmMCpzbNYwuwEliN5/jDke8OVdWvDj0AxotITxHpLyL9A57WmAZk8el3EsVBDqS0ZWXa6fyFB3HFRFRau2/dXmbd/A6bvluL2+3Gc9mSMY1XbQ7ZbQU+wHPG07Yaat/HcxZUKZ6L++yMKHPcOvIMqkODQVV1EHzn/M2c9MJYpu99GVeZi1smbuab819m+EQ77mEap9pseXQCvgF+JyJ/F5H7qqldrqrjVfUpVX06MBGNaZiSdq/kBl5Cd+7i7B/uZR1tcTorry3PbM8QprGu27k41Enz8jxK91Z2CNGYxqE2zcPh/YoCMqDKIQsASkXkGxF5W0TeDkA+Yxqs1E2zeYmbcG7ZSFTbFHa36FplrSM+lhkMIS8mhQJ10Y0V/HDy3SFMa0xg1Wa31TPAVOAZVd1UQ22yqg6vcypjGoH2d57L3JOy6DKiPV2v6AfemyRWxqWltGUzrrxmuN2ez2xVbaUY0xjU2DxU9UoflhctIr8B8rzf+6WfuYxp8FK6J5DSPaFWtZF7trKO9kyd9ShxbuEv/J7kzSPxXP9qTONT14sEjz1lZAoQASR5v4w5buVu2s/Kfy8gd3Muk05/km8zqr5XVWx6c74Y+gRxZw8jzq38nidpvW1uCNMaE1h1ukGCqjqOef5m3eIY03isfGkKAx8/n/mPTCJs9TLSq2kGTdPjGT3lLgC23Laday66mhdfvSNUUY0JOF8Gg/opEDXGHC8KO/XhWv6P/WndePqECZyasrJW3+fGDbEQ2TQyyAmNCR5ftjy6iEh1gz0J0KSOeYxpNMrS2vAPruWspp7rPMIqHwcKgLzsPMrSM1ky5GZiyuJImRnD6q/W0fHMdqELbEwA+dI8OteiptzfIMY0NocuCCwtUYZsfZesogPA1ZXWOqPCmaSnUR7TnnRN4JHVzzP9rS50PNMuEjSNky/jedR0mq4x/1MSVs6knCHMmf5vOma/TEzxXqpqHq7YSMbwPrd2gHU8zql8x7W9O4Y2sDEBZCMKGOOn2PbJfJtxLUnd25E87X3Ki8uqrK3YSilVColgCqdymZ2PaBoxax7G+Kn9yPa03/BarWodDviCUeQvPIN/4KQlm4gsT6Sy8c6NaQx8vs5DRH5xDwYRGRqQNMY0UnOe+5H5ry+qcr4IdHaspunB7fTnAJvIoM3iT0OY0JjA8uciwfdF5B7xiBKR54FHAx3MmIZuy/QNLIsdyKzb3yfx7qtw3XlLtfVty9dy6tyH2cguXk6/jBbDe4YoqTGB589uqwHAY8AsIA74D3ByIEMZ0xiUlkJZ4UH27yrjjcSnaJIYRq8avsftdrOFHFad15wbzqn6RorGNHT+NI9S4ACeu+xGAhtUtfKBm405nmVm0ptFPN4Tvp8F7VtUXz515HgcbVsB2GBQptHzZ7fVPDzfwvXKAAATUklEQVTNox8wCLhYRD4MaCpjGoHDZ1BBWEkhUc6Sauu7f/0Urv9+zAgGcu8zb/Pj+O9DkNKY4PBny+MaVZ3vfbwdOFdELgtgJmMahfCDeTzDn0lcPoLpOdewoXwA8N8q64e2WEmXHk725ZzPD5xMStPmoQtrTID50zxGiciogCcxppFxlRdzK88xZXMTVg7+Lc62baqtzwtPJJ8yfqQFF/AeU2pzzwZjGih/mkfhEY8jgbOA2t0RzpjjSPOOiWzbUEy/5i5i42veAzyodAqJu51M9r7tqhrv3JjGwOeXr6o+deRzEXkSsBPWzf8ch1NIzQivdf3f9oxjz8HWrMDJrZxN7NYngU7BC2hMENV1MCiAaKBtAJZjTKPiLnPzww3/Zvk/f2RFWE++Hnh/tfVb7nuN3LvvI4EC+shPRHEgREmNCTyftzxEZCmg3qdOPCMGPhTIUMY0BupWTn7lMqbNvBF3WXPyNbba+sH3D2P37t28/8c5dPjjn3hkTE1XhRjTcPmz1/WsIx6XATtUteo7wtVARN7wLnOnqnavomYo8AwQBuxW1VP8/XnGBIoz3MlgZjCoayrjl7Xlxiy4oJr6/Rv2sW/7HgAcjkBs9BtTf/w55hHoW7NPAF4A3qpspog0BV4CRqrqZhGp4VIsY0Jnbtgg2ngHgapuMCiArSeMQNxlDKA3aW/sYNfYPSR1Tgh+SGOCwJdhaPNFJK+Sr3wRyfM3gKpOB/ZWUzIWmKiqm731O/39WcYEWifnWuJ2reefXEmfdR9UW/tZy+t4v+m1nEwcv936GkVb94UopTGB58u28yeqGg/cr6rxR3zFeacHS0egmYhMFZEFInJ5EH+WMT6ZcTCLqxbezBjeI31v1XfVBfgy7TreibuOV+hDKlvRNhmhCWlMEPiy26q3iLQBrhKRN/GMWV5BVavbeqgLF9AXOA3P/bRmi8gcVV19bKGIjAPGAaSnpwcpjjGHzTr7UWK7tiFq/BcMraHW5YKyMigimiJScUWGIqExweFL83gVmITntNwFHN08lOCdrpuN5yB5IVAoItOBnsAvmoeqvga8BpCVlaXHzjcm0EZ9WvsxyP/w8+U03buOsfSmLZNxuYcBtb9OxJiGpNa7rVT1OVXtAryhqm1VNfOIr2Be5/EJMFhEXCISjeeW8HZFu2kw9m/J58uzXmLxhIXV1rlbtWFv87ZczjImM5KwA34fKjSm3vlztlXtP2rVgoi8AwwFEkUkG3gAzym5qOorqrpSRCYBSwA38LqqLgtkBmP89XN0b5zuMkYVL2OqPg5X9q6ydsSPD7Nx40ZuyzyVuFPu5sa0YB4qNCa46v3uOqp6cS1qngCeCEEcY3wyJ2Ioe8qa8Gbxf7hxQHKNxz3cbjc/s4HS0YmEx9ouK9N41XvzMKYxeyL17+TkwD6grIY7rE877xncC34khkQKsyNQtyIOGxTKNE52masxdRAWBlJUSF/mE3twd7W15UtX0CZ7LuPpwl+euxV3aXmIUhoTeNY8jKmDP+TczOTiU5hPP9ot+6Ta2gknvUb3yDV8TTf+xh9whDlDlNKYwLPmYUwdpGgOzqhwZlz+f6SNGVRtrec6D+Ez+vBnx8O2y8o0anbMw5g6GLLzw1rXnrD9G+4oXcBjtMTptMuQTONmzcOYOiopVgoKhbi46m+O2HfzxwzhZVIYwdCyZ4DFIctoTKDZbitj6mDmdW+yLOV0miY4WHB/9cc8Mt56iM+em8IODrI31m4ObRo32/Iwpg4iPnmfPvu+51XG0Tk1o9ra9D6J7HM24xymkf74ywwLTURjgsKahzF18FTWO3z5FeQTz6SO1ddumb6BLZ8sxYUTETtYbho3221lTB2URceTj+c2IzUNBrXuD69z1tOX8Qin0uyBH0KQzpjgseZhTB10yP+J57iZ2QykyYbqx/NYccIYLuI9ulBM990LQpTQmOCw3VbG1MHoNc8wiH+xKrInxFZfuyetBx/Qgw/oTsvENLaHJqIxQWHNw5g6iHngLqasvpxhfz29xtowKSOaYg4Qbtd5mEbPmocxddD7ih61rh04++8Ucjd/5B4KDmQA1wctlzHBZsc8jKmDvOw8pox7m8kdb2bbT9XviIoa0o+PMm/gGt7htwUvhSihMcFhzcOYOlh49v0M+79LGLHmBQ7uyK22dsA9Q2n51liGUsKce24KUUJjgsOahzF1sKrdKP7MQ8RQgLbvUGO9qpLNdqK6xIUgnTHBY83DmDrY0OEMHuHPFBFDWET1b6c5d0+k5WnjuJTh7J9ZGKKExgSHNQ9j6iAsDHqyiEv4N67SA9XWFpRGsL00iX/xDVlvTghNQGOCxM62MqYOTpr3LA9xGwC7S0YAUVXWbu87mssYzdl8SkrLA/QPUUZjgsGahzF1EJmRzLKwXuTf8Rey2jStttblfbd9xjn0bpoTgnTGBI81D2PqYOjLY+DlMbWqTdy0gDd4gee4hTBHUpCTGRNcdszDmDraOGc7P727Gnd59VeNx+7P5mLeYSF9eGz9uBClMyY4rHkYUwfzH5lExokp9Lm4E1rurra270Pn8tXEz/gbQ9naq1+IEhoTHNY8jKmD/LU7APgHV+MMd1ZbGxYGERGl/ImpxN+eFYp4xgSNNQ9j6mD94CsQlGv5R421OfO3kjt+Fu1It8GgTKNnzcOYOqhpAKgj7Zi5hotn/JW1bKbg998GL5QxIVDvzUNE3hCRnSKyrIa6fiJSLiIXhiqbMTVpvmMliqDUvCVR1DWLHixmKd05WB4RgnTGBE+9Nw9gAjCyugIRcQKPAZNDEciY2mq+fTkAm12ZNdY64mNZSg96sJSPOtmNEU3jVu/NQ1WnA3trKLsZ+AjYGfxExtRel9vPZOnnm2i2bUWNteFlRfRhAUnsxFn9sXVjGrx6bx41EZE04DzglfrOYsyxmrWK4YTR6cQlRdZYG7N1NQvIYictGbT9ixCkMyZ4GnzzAJ4B7lHV8poKRWSciMwXkfm7du0KQTTzv27fur0sjcxiVtMza6xt3iudN7rfA0DH/YuDHc2YoGoMtyfJAt71ntqYCIwSkTJV/e+xhar6GvAaQFZWlg0SbYJu438X0bt4ARTXXJvUqTkx9/VGfgPfv1S7W5oY01A1+OahqhVHIkVkAvB5ZY3DmPpwsH13LuBD5jKA7FrUu92eq9CdLjvoYRq3em8eIvIOMBRIFJFs4AEgDEBV7TiHadhatGAiF9SqNPuHTVw8diz9yWD+VzkwJMjZjAmiem8eqnqxD7VXBjGKMT5zSTl/4DEKiQFurbZWmsQziRGMZDJLvl8A2K4r03jVe/MwpjGL37SUv/En77Pqm4crqRnn8CndWcbIruWcF/x4xgRNYzjbypgGK659SyZnXs+s+yfVWOtyQSnhLKQPhfE2nodp3GzLw5g6SO2bQur6l2tV6zpYwEIGMY9+bCmzK8xN42bNw5g6mnLvZKJaxjPw9hOrrQuLcNCDJfRiMR+vbQP0Ck1AY4LAdlsZUwc7FuUw7LGRDLzjpBproxOjeeXB57mewUSdcUII0hkTPNY8jKkDtyscgGdqOFh+iCs5jFeZQctT04MZy5igs91WxtSBq2UCgudmBrfVor75Q9P5DcNwu+1zm2nc7BVsTB24XJDCNpqwv1b1F279D+8wheynZwY5mTHBZc3DmDoIcxezjTT2kFCr+h4sZgJXUJjUOsjJjAkuax7G1MGhYWg3ujrUqn4pPbiKCexp1zuIqYwJPjvmYUwdhMdFUFSopNdyLPML+YCdtMDlahvcYMYEmTUPY+pABKKja1//ARcB8MmWTwDbdWUaL9ttZUwIvZZ5I6W4iImscWwzYxo0ax7GhFDejZmEU0bGWLtI0DRu1jyMCaHydcW0JgWHw956pnGzV7AxIXTPK/exmRx2zt9V31GMqRNrHsaE0AwGAVCSva+ekxhTN9Y8jAmhoUwlmkKKOtkxD9O4WfMwJoTcODlANGGRdpa8adyseRgTQltohSJElhbWdxRj6sSahzEh1AzPsY7ofDtgbho3ax7GhNATV9/BUHqS0CO5vqMYUyfWPIwJofJUmMZiopr7cE8TYxogax7GhNAJL65kJr0pL9H6jmJMndgpH8aE0EX7PgJg/bYCSGtRz2mM8Z81D2NCaDDTOZHZ3BQfU99RjKkTax7GhNBMBjOTwdwWl1ffUYypk3o/5iEib4jIThFZVsX8S0Rkifdrloj0DHVGYwLlIt7jzzxERES9v/WMqZOGsOUxAXgBeKuK+RuAU1R1n4icCbwGDAhRNmMC6j1+A0C+8/Z6TmJM3dT7xx9VnQ7srWb+LFU9dBe5OUCrkAQzJgiebXMt39IfZ5izvqMYUyf13jx8dA3wVX2HMMZfK0Y4GOGYT0RkRH1HMaZOGsJuq1oRkWF4msegamrGAeMA0tPTQ5TMmNr71a9+RWZmJk6nbXmYxk1U6/9iJRHJAD5X1e5VzO8BfAycqaqra7PMrKwsnT9/fsAyGmPM/wIRWaCqWTXVNfjdViKSDkwELqtt4zDGGBNc9b7bSkTeAYYCiSKSDTwAhAGo6ivA/UAC8JKIAJTVpisaY4wJnnpvHqp6cQ3zrwWuDVEcY4wxtdDgd1sZY4xpeKx5GGOM8Zk1D2OMMT6z5mGMMcZn1jyMMcb4zJqHMcYYn1nzMMYY4zNrHsYYY3xmzcMYY4zPrHkYY4zxmTUPY4wxPrPmYYwxxmfWPIwxxvisQQwGFQwisgvYVN85giAR2F3fIYLseF/H43394Phfx+N5/dqoalJNRcdt8zheicj84308k+N9HY/39YPjfx2P9/WrDdttZYwxxmfWPIwxxvjMmkfj81p9BwiB430dj/f1g+N/HY/39auRHfMwxhjjM9vyMMYY4zNrHg2ciDQXkW9EZI3332bV1MaLyFYReSGUGeuqNusoIr1EZLaILBeRJSIypj6y+kJERorIKhFZKyL3VjI/QkTe886fKyIZoU/pv1qs3x0issL79/pORNrUR866qGkdj6i7UERURP5nzsCy5tHw3Qt8p6odgO+8z6vyMDAtJKkCqzbrWARcrqrdgJHAMyLSNIQZfSIiTuBF4EygK3CxiHQ9puwaYJ+qtgf+DjwW2pT+q+X6LQSyVLUH8CHweGhT1k0t1xERiQNuAeaGNmH9subR8J0LvOl9/Cbwq8qKRKQv0BL4OkS5AqnGdVTV1aq6xvt4G7ATqPFCpnrUH1irqutVtQR4F896HunI9f4QOE1EJIQZ66LG9VPVKapa5H06B2gV4ox1VZu/IXg+tD0OHAxluPpmzaPha6mqOQDef1scWyAiDuAp4PchzhYoNa7jkUSkPxAOrAtBNn+lAVuOeJ7tnVZpjaqWAblAQkjS1V1t1u9I1wBfBTVR4NW4jiLSG2itqp+HMlhD4KrvAAZE5FsguZJZf6rlIm4EvlTVLQ31g2sA1vHQclKAfwFXqKo7ENmCpLI/xLGnNtampqGqdXYRuRTIAk4JaqLAq3YdvR/a/g5cGapADYk1jwZAVU+vap6I7BCRFFXN8f7HubOSshOBwSJyIxALhItIgapWd3wkpAKwjohIPPAFcJ+qzglS1EDJBlof8bwVsK2KmmwRcQFNgL2hiVdntVk/ROR0PB8QTlHV4hBlC5Sa1jEO6A5M9X5oSwY+FZFzVHV+yFLWE9tt1fB9ClzhfXwF8MmxBap6iaqmq2oGcBfwVkNqHLVQ4zqKSDjwMZ51+yCE2fw1D+ggIpne7L/Bs55HOnK9LwS+18Zz4VWN6+fdpfMqcI6qVvqBoIGrdh1VNVdVE1U1w/vem4NnXY/7xgHWPBqD8cBwEVkDDPc+R0SyROT1ek0WOLVZx4uAIcCVIrLI+9WrfuLWzHsM43fAZGAl8L6qLheRh0TkHG/ZP4AEEVkL3EH1Z9I1KLVcvyfwbAl/4P17Hds8G7RaruP/LLvC3BhjjM9sy8MYY4zPrHkYY4zxmTUPY4wxPrPmYYwxxmfWPIwxxvjMmocxASYiG0Uksb5zGBNM1jyMMcb4zJqHMX4SkQwR+VlE3vSOWfGhiER7Z98sIj+JyFIR6eyt7y8is0RkofffTt7p3UTkR++FdEtEpIN3+qVHTH/Ve4twYxoEax7G1E0n4DXvmBV5eG5SCbBbVfsAL+O5ZQzAz8AQVe0N3A/8zTv9euBZVe2F5waC2SLSBRgDnOydXg5cEooVMqY27MaIxtTNFlX9wfv433gGBQKY6P13AXC+93ET4E3vloUCYd7ps4E/iUgrYKKqrhGR04C+wDzvTfeiqOKGkcbUB2sextTNsff3OfT80B1kyzn8PnsYmKKq53mHnJ0KoKpvi8hcYDQwWUSuxXM78DdV9Q/Bi26M/2y3lTF1ky4iJ3ofXwzMrKa2CbDV+/jKQxNFpC2wXlWfw3PX1h54huO9UERaeGuaN8YxwM3xy5qHMXWzErhCRJYAzfEc46jK48CjIvIDcOTB7zHAMhFZBHTGc9v5FcB9wNfeZX8DpARjBYzxh91V1xg/eXc9fa6q3es5ijEhZ1sexhhjfGZbHsYYY3xmWx7GGGN8Zs3DGGOMz6x5GGOM8Zk1D2OMMT6z5mGMMcZn1jyMMcb47P8BB+ujFMvdNo0AAAAASUVORK5CYII=\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Plotting flux in each phase.\n",
    "\n",
    "afig, mplfig = b['lc@model'].plot(x='phases', show=True)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}