PH_TESS_I_LightCurveViewer.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Planet Hunters TESS Subject Lightcurve Viewer\n",
    "\n",
    "See https://www.zooniverse.org/projects/nora-dot-eisner/planet-hunters-tess"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<style>.container { width:99% !important; }</style>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from ipywidgets import interact, interactive, IntSlider, Layout, interact_manual\n",
    "import ipywidgets as widgets\n",
    "from IPython.display import display\n",
    "\n",
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "import matplotlib as matplotlib\n",
    "#%matplotlib inline\n",
    "\n",
    "import pandas as pd\n",
    "\n",
    "from IPython.core.display import display, HTML\n",
    "display(HTML(\"<style>.container { width:99% !important; }</style>\"))"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Sample data\n",
    "\n",
    "sample_subject_id = \"36971891\"\n",
    "sample_lightcurve_data = '{\"y\": [0.22792696952819824, 0.16853570938110352, -0.05636930465698242, 0.3116273880004883, 0.2547609806060791, 0.30231475830078125, 0.1367342472076416, 0.14853119850158691, -0.0015997886657714844, 0.2745521068572998, 0.02760171890258789, 0.21951079368591309, 0.08598566055297852, 0.2728390693664551, 0.06356000900268555, 0.1374530792236328, 0.13327836990356445, 0.28473496437072754, 0.14550566673278809, 0.005651712417602539, 0.07713079452514648, 0.0025641918182373047, 0.13686060905456543, -0.049561262130737305, -0.28811097145080566, 0.07416009902954102, -0.010502338409423828, 0.004711151123046875, -0.022346973419189453, -0.12843728065490723, -0.048841238021850586, 0.187225341796875, -0.14483332633972168, -0.1710820198059082, -0.11440515518188477, -0.1907062530517578, -0.08075952529907227, 0.16850590705871582, -0.16894936561584473, 0.13225793838500977, -0.14524102210998535, -0.11053681373596191, 0.06059408187866211, 0.07509589195251465, -0.2390456199645996, 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26.836350250937766, 26.843294755612213, 26.85023926028689]}'\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "last_lightcurve_data = \"\"\n",
    "last_df = None\n",
    "widget_out2 = None  # to be defined later by UI\n",
    "def plot_lightcurve(lightcurve_data, xmin=None, xmax=None, moving_average_window = None, subject_id = None):\n",
    "    global last_lightcurve_data\n",
    "    global last_df\n",
    "    global widget_out2\n",
    "    # process input arguments\n",
    "    df = None\n",
    "    if lightcurve_data.startswith('{\"y\"'):\n",
    "        # process data into a dataframe, and cache it in last_df to make UI more responsive\n",
    "        if (lightcurve_data != last_lightcurve_data):\n",
    "            df = pd.read_json(lightcurve_data)\n",
    "            last_lightcurve_data = lightcurve_data\n",
    "            last_df = df\n",
    "        else:\n",
    "            df = last_df    \n",
    "        # zoom in to a subset of data\n",
    "        if xmin != None:\n",
    "            df = df[df.x >= xmin]\n",
    "        if xmax != None:\n",
    "            df = df[df.x <= xmax]\n",
    "    else: # case non lightcurve json data, ignore them\n",
    "        df = pd.DataFrame()\n",
    "    \n",
    "    subject_info = f\"Subject {subject_id}\" if subject_id != None else \"\"\n",
    "        \n",
    "    # default plot text properties\n",
    "    matplotlib.rcParams.update({'font.size':24}) \n",
    "    matplotlib.rcParams.update({'font.family':'sans-serif'})\n",
    "\n",
    "    plt.figure(figsize=(30,15)) \n",
    "\n",
    "    # Misc. labels, setup etc.\n",
    "    plt.gca().set_facecolor(\"darkslategrey\")\n",
    "    plt.xlabel(\"Days\")\n",
    "    plt.ylabel(\"Brighness\", labelpad=16)    \n",
    "    \n",
    "    if len(df) > 0:\n",
    "        y_series = df['y']\n",
    "        y_label = \"Brightness\"\n",
    "        dot_color = 'whitesmoke'\n",
    "        if (moving_average_window != None):\n",
    "            df['x_ts'] = df['x'].apply(lambda x: pd.Timestamp(x * 1000000000 * 60 * 60 * 24))\n",
    "            y_series = df.rolling(moving_average_window, on='x_ts')['y'].mean()\n",
    "            y_label = f\"Brightness,  {moving_average_window} moving average\"\n",
    "            dot_color = 'lightyellow'\n",
    "\n",
    "        plt.scatter(df['x'], y_series, color=dot_color, alpha=1.0, label=\"observation\")\n",
    "        plt.ylabel(y_label, labelpad=16)\n",
    "        \n",
    "        # draw -3 standard deviation line (of the data shown only if the user zooms in)\n",
    "#         xmax_shown = np.max(df['x'])    \n",
    "#         xmin_shown = np.min(df['x'])    \n",
    "#         plt.hlines(np.nanmean(df['y'])- 3 * np.nanstd(df['y']), xmin, xmax_shown, linewidth=4, color=\"red\", label=r\"$-3\\sigma$\")\n",
    "        plt.legend()\n",
    "        plt.title(f\"Lightcurve - {subject_info} ({len(df)} observations)\", fontdict={'fontsize': 36}, pad=24)\n",
    "        \n",
    "        # add a textual summary\n",
    "        widget_out2.clear_output()\n",
    "        with widget_out2:\n",
    "            print('Brightness summary:')\n",
    "            print(df['y'].describe())\n",
    "\n",
    "    else:\n",
    "        plt.title(f\"Lightcurve - No data\", fontdict={'fontsize': 36}, pad=24)\n",
    "        widget_out2.clear_output()\n",
    "        \n",
    "    plt.show()\n",
    "    return \"\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "80c05b7224d243338de228a70ea0569b",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "interactive(children=(Text(value='{\"y\": [0.22792696952819824, 0.16853570938110352, -0.05636930465698242, 0.311…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "desc_style = {'description_width': '25ch'} # \n",
    "slider_style = {'description_width': '25ch'}\n",
    "slider_layout = { 'width': '60ch' }\n",
    "w = interactive(plot_lightcurve\n",
    "                , lightcurve_data = widgets.Text(value = sample_lightcurve_data\n",
    "                                                 , description = 'Lightcurve data'\n",
    "                                                 , style = desc_style)\n",
    "                , xmin = widgets.FloatSlider(min=0, max=30.0, step=0.2, value=0.0\n",
    "                                             , description = 'days min.'\n",
    "                                             , continuous_update = False\n",
    "                                             , readout_format=\".1f\"\n",
    "                                             , layout = slider_layout, style = slider_style)\n",
    "                , xmax = widgets.FloatSlider(min=0, max=30.0, step=0.2, value=30.0\n",
    "                                             , description = 'days max.'\n",
    "                                             , continuous_update = False\n",
    "                                             , readout_format=\".1f\"\n",
    "                                             , layout = slider_layout, style = slider_style)\n",
    "                , moving_average_window = widgets.Dropdown(options = [('None', None), ('20 min', '20min'), ('30 min', '30min'), ('1 hour', '1h'), ('2 hours', '2h'), ('4 hours', '4h')]\n",
    "                                                           , value = None\n",
    "                                                           , description = 'Moving average window'\n",
    "                                                           , style = desc_style)                \n",
    "                , subject_id = widgets.IntText(value = sample_subject_id\n",
    "                                               , description = 'Subject ID'\n",
    "                                               , style = desc_style)\n",
    "               )\n",
    "w.layout.border = '1px solid lightgray'\n",
    "w.layout.padding = '1em 0px'\n",
    "\n",
    "# Add a second output for textual summary \n",
    "widget_out2 = widgets.Output()\n",
    "widget_out2.layout.padding = '1em'\n",
    "w.children = w.children + (widget_out2,)\n",
    "\n",
    "display(w)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Learn More\n",
    "- [About Planet Hunters TESS](https://www.zooniverse.org/projects/nora-dot-eisner/planet-hunters-tess/about/research)\n",
    "- [Light curve](https://en.wikipedia.org/wiki/Light_curve)\n",
    "- [Exoplanets detection methods](https://en.wikipedia.org/wiki/Methods_of_detecting_exoplanets)\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
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