01_explore.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This repository investigates [SDSS DR-17 MaStar](https://www.sdss.org/dr17/mastar) dataset of star spectra for the purposes of statistical learning.\n",
    "\n",
    "Our main goal is to familiarise ourselves with the dataset and attempt to build a temperature prediction model based on spectral inputs.\n",
    "\n",
    "This dataset is a great base for such learning exercise. It is of manageable size, provides a large amount of understandable features (thousands of easily plottable spectral samples), and also feasible prediction targets like star temperature (Teff) or metallicity.\n",
    "\n",
    "Not only that - conveniently it also contains two sources of labels. First one is a limited high-quality set of temperature designations coming from other catalogues such as APOGEE (we will use this for training and validation.) Second set of labels comes from professional scientific models in the form of a \"value-added catalog\" and covers all stars in the set. This gives us an alternative way of pitting our amateurish model against what the scientists came up with!\n",
    "\n",
    "External models are described on the [value-added catalog page](https://www.sdss.org/dr17/mastar/mastar-stellar-parameters/). Especially interesting are these [two](https://arxiv.org/pdf/2112.01669.pdf) [papers](https://arxiv.org/pdf/2111.05347.pdf) which can help us understand the dataset and dispel some of the astronomy jargon.\n",
    "\n",
    "Important note: I am not a trained scientist, and am doing my best understanding this dataset. I'm 100% sure I have made mistakes processing the data (for example I haven't accounted for atmospheric vs vacuum spectral differences), but I think results are nevertheless interesting.\n",
    "\n",
    "Alignment of the models contained here with the models provided in the value-added catalogue is close enough, that I can feasibly claim the general techniques employed here are legitimate.\n",
    "\n",
    "Let's dig in."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "from astropy.io import fits\n",
    "from astropy.table import Table\n",
    "import pandas as pd\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "import urllib\n",
    "from IPython.display import Image, display, HTML\n",
    "import base64\n",
    "import io"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Filename: data/mastarall-v3_1_1-v1_7_7.fits\n",
      "No.    Name      Ver    Type      Cards   Dimensions   Format\n",
      "  0  PRIMARY       1 PrimaryHDU       4   ()      \n",
      "  1  GOODSTARS     1 BinTableHDU     54   24290R x 18C   [6A, 6A, 22A, J, J, J, J, D, D, E, 5E, J, E, E, E, E, 14A, 9A]   \n",
      "  2  GOODVISITS    1 BinTableHDU     82   59266R x 32C   [6A, 6A, 22A, J, 5A, J, D, D, 5E, J, E, I, I, E, E, I, E, E, I, I, E, J, E, I, E, E, E, D, D, E, 9A, 9A]   \n",
      "  3  ALLSTARS      1 BinTableHDU     54   28124R x 18C   [6A, 6A, 22A, J, J, J, J, D, D, E, 5E, J, E, E, E, E, 14A, 9A]   \n",
      "  4  ALLVISITS     1 BinTableHDU     82   80592R x 32C   [6A, 6A, 22A, J, 5A, J, D, D, 5E, J, E, I, I, E, E, I, E, E, I, I, E, J, E, I, E, E, E, D, D, E, 9A, 9A]   \n",
      "Total stars: 24290\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Vaues in PHOTOCAT:\n",
      "b'ps1      '    8519\n",
      "b'gaia_dr2 '    5897\n",
      "b'sdss_dr8 '    5674\n",
      "b'apass_dr8'    4200\n",
      "Name: PHOTOCAT, dtype: int64\n",
      "Data points with valid T value from catalogue:\n",
      "count    4280.000000\n",
      "mean     5149.508789\n",
      "std      1090.677368\n",
      "min      2970.199951\n",
      "25%      4396.635010\n",
      "50%      4907.759521\n",
      "75%      5694.222412\n",
      "max      8975.860352\n",
      "Name: INPUT_TEFF, dtype: float64\n",
      "Histogram Teff of good-T stars:\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Map of good-T stars:\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1080x504 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    },
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Random good-T star:\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>DRPVER</th>\n",
       "      <th>MPROCVER</th>\n",
       "      <th>MANGAID</th>\n",
       "      <th>MINMJD</th>\n",
       "      <th>MAXMJD</th>\n",
       "      <th>NVISITS</th>\n",
       "      <th>NPLATES</th>\n",
       "      <th>RA</th>\n",
       "      <th>DEC</th>\n",
       "      <th>EPOCH</th>\n",
       "      <th>MNGTARG2</th>\n",
       "      <th>INPUT_LOGG</th>\n",
       "      <th>INPUT_TEFF</th>\n",
       "      <th>INPUT_FE_H</th>\n",
       "      <th>INPUT_ALPHA_M</th>\n",
       "      <th>INPUT_SOURCE</th>\n",
       "      <th>PHOTOCAT</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6817</th>\n",
       "      <td>b'v3_1_1'</td>\n",
       "      <td>b'v1_7_7'</td>\n",
       "      <td>b'3-48993798            '</td>\n",
       "      <td>58119</td>\n",
       "      <td>58440</td>\n",
       "      <td>2</td>\n",
       "      <td>1</td>\n",
       "      <td>51.130888</td>\n",
       "      <td>28.922009</td>\n",
       "      <td>2011.800049</td>\n",
       "      <td>1152</td>\n",
       "      <td>-999.00000</td>\n",
       "      <td>-999.000000</td>\n",
       "      <td>-999.000000</td>\n",
       "      <td>-999.0</td>\n",
       "      <td>b'LAMOST_Mdwarf '</td>\n",
       "      <td>b'ps1      '</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5110</th>\n",
       "      <td>b'v3_1_1'</td>\n",
       "      <td>b'v1_7_7'</td>\n",
       "      <td>b'3-160658598           '</td>\n",
       "      <td>58116</td>\n",
       "      <td>58148</td>\n",
       "      <td>3</td>\n",
       "      <td>1</td>\n",
       "      <td>107.897058</td>\n",
       "      <td>75.339658</td>\n",
       "      <td>2011.800049</td>\n",
       "      <td>67108992</td>\n",
       "      <td>-999.00000</td>\n",
       "      <td>-999.000000</td>\n",
       "      <td>-999.000000</td>\n",
       "      <td>-999.0</td>\n",
       "      <td>b'              '</td>\n",
       "      <td>b'ps1      '</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16404</th>\n",
       "      <td>b'v3_1_1'</td>\n",
       "      <td>b'v1_7_7'</td>\n",
       "      <td>b'60-2263072041253833984'</td>\n",
       "      <td>58801</td>\n",
       "      <td>58801</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>295.651102</td>\n",
       "      <td>69.732239</td>\n",
       "      <td>2015.500000</td>\n",
       "      <td>134283264</td>\n",
       "      <td>-999.00000</td>\n",
       "      <td>-999.000000</td>\n",
       "      <td>-999.000000</td>\n",
       "      <td>-999.0</td>\n",
       "      <td>b'              '</td>\n",
       "      <td>b'gaia_dr2 '</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15205</th>\n",
       "      <td>b'v3_1_1'</td>\n",
       "      <td>b'v1_7_7'</td>\n",
       "      <td>b'60-1643336096124231936'</td>\n",
       "      <td>58649</td>\n",
       "      <td>58649</td>\n",
       "      <td>1</td>\n",
       "      <td>1</td>\n",
       "      <td>241.826126</td>\n",
       "      <td>67.222719</td>\n",
       "      <td>2015.500000</td>\n",
       "      <td>134283264</td>\n",
       "      <td>-999.00000</td>\n",
       "      <td>-999.000000</td>\n",
       "      <td>-999.000000</td>\n",
       "      <td>-999.0</td>\n",
       "      <td>b'              '</td>\n",
       "      <td>b'gaia_dr2 '</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>710</th>\n",
       "      <td>b'v3_1_1'</td>\n",
       "      <td>b'v1_7_7'</td>\n",
       "      <td>b'3-103225147           '</td>\n",
       "      <td>57652</td>\n",
       "      <td>57673</td>\n",
       "      <td>4</td>\n",
       "      <td>1</td>\n",
       "      <td>30.223162</td>\n",
       "      <td>-1.169525</td>\n",
       "      <td>2011.800049</td>\n",
       "      <td>1152</td>\n",
       "      <td>1.73087</td>\n",
       "      <td>4420.666992</td>\n",
       "      <td>-1.325452</td>\n",
       "      <td>-9999.0</td>\n",
       "      <td>b'SEGUE         '</td>\n",
       "      <td>b'ps1      '</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "          DRPVER   MPROCVER                    MANGAID  MINMJD  MAXMJD  \\\n",
       "6817   b'v3_1_1'  b'v1_7_7'  b'3-48993798            '   58119   58440   \n",
       "5110   b'v3_1_1'  b'v1_7_7'  b'3-160658598           '   58116   58148   \n",
       "16404  b'v3_1_1'  b'v1_7_7'  b'60-2263072041253833984'   58801   58801   \n",
       "15205  b'v3_1_1'  b'v1_7_7'  b'60-1643336096124231936'   58649   58649   \n",
       "710    b'v3_1_1'  b'v1_7_7'  b'3-103225147           '   57652   57673   \n",
       "\n",
       "       NVISITS  NPLATES          RA        DEC        EPOCH   MNGTARG2  \\\n",
       "6817         2        1   51.130888  28.922009  2011.800049       1152   \n",
       "5110         3        1  107.897058  75.339658  2011.800049   67108992   \n",
       "16404        1        1  295.651102  69.732239  2015.500000  134283264   \n",
       "15205        1        1  241.826126  67.222719  2015.500000  134283264   \n",
       "710          4        1   30.223162  -1.169525  2011.800049       1152   \n",
       "\n",
       "       INPUT_LOGG   INPUT_TEFF  INPUT_FE_H  INPUT_ALPHA_M       INPUT_SOURCE  \\\n",
       "6817   -999.00000  -999.000000 -999.000000         -999.0  b'LAMOST_Mdwarf '   \n",
       "5110   -999.00000  -999.000000 -999.000000         -999.0  b'              '   \n",
       "16404  -999.00000  -999.000000 -999.000000         -999.0  b'              '   \n",
       "15205  -999.00000  -999.000000 -999.000000         -999.0  b'              '   \n",
       "710       1.73087  4420.666992   -1.325452        -9999.0  b'SEGUE         '   \n",
       "\n",
       "           PHOTOCAT  \n",
       "6817   b'ps1      '  \n",
       "5110   b'ps1      '  \n",
       "16404  b'gaia_dr2 '  \n",
       "15205  b'gaia_dr2 '  \n",
       "710    b'ps1      '  "
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Data from https://data.sdss.org/sas/dr17/manga/spectro/mastar/v3_1_1/v1_7_7/\n",
    "# Data model description https://data.sdss.org/datamodel/files/MANGA_SPECTRO_MASTAR/DRPVER/MPROCVER/mastarall-DRPVER-MPROCVER.html\n",
    "hdulist = fits.open('data/mastarall-v3_1_1-v1_7_7.fits')\n",
    "hdulist.info()\n",
    "\n",
    "dat = Table.read('data/mastarall-v3_1_1-v1_7_7.fits', format='fits', hdu=1)\n",
    "print('Total stars: %d' % len(dat))\n",
    "\n",
    "names = [name for name in dat.colnames if len(dat[name].shape) <= 1]\n",
    "goodstars = dat[names].to_pandas()\n",
    "goodstars.plot.scatter(x='RA', y='DEC', marker=\"+\", linewidths=0.5, figsize=(15,7))\n",
    "plt.show()\n",
    "\n",
    "print(\"Vaues in PHOTOCAT:\")\n",
    "print(goodstars['PHOTOCAT'].value_counts())\n",
    "\n",
    "print(\"Data points with valid T value from catalogue:\")\n",
    "goodstars['INPUT_TEFF'].describe()\n",
    "tstars = goodstars[goodstars['INPUT_TEFF']>0.0]\n",
    "print(tstars['INPUT_TEFF'].describe())\n",
    "\n",
    "print(\"Histogram Teff of good-T stars:\")\n",
    "tstars['INPUT_TEFF'].hist()\n",
    "plt.show()\n",
    "\n",
    "print(\"Map of good-T stars:\")\n",
    "tstars.plot.scatter(x='RA', y='DEC', marker=\"+\", linewidths=0.5, figsize=(15,7))\n",
    "plt.show()\n",
    "\n",
    "print(\"Random good-T star:\")\n",
    "goodstars.sample(n=5)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Caution is required interpreting the spectra, as resolution differs per star and even per visit https://www.sdss.org/dr17/mastar/mastar-spectra/. SDSS team provides \"unified resolution\" spectra (with resolutions adjusted to match). Best one to use then should be the \"combined\" dataset (multiple visits combined to increase quality) and the unified 99.5th set (which is the largest). I think we don't really care about the shape of these LSF curves, as long as they are comparable.\n",
    "\n",
    "Alternatively, we can use raw data and feed our algorithm with resolution data too. This could give better results because I think normalisation removes detail."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Filename: data/mastarall-gaiaedr3-extcorr-simbad-ps1-v3_1_1-v1_7_7-v1.fits\n",
      "No.    Name      Ver    Type      Cards   Dimensions   Format\n",
      "  0  PRIMARY       1 PrimaryHDU       4   ()      \n",
      "  1  GOODSTARS     1 BinTableHDU    206   24290R x 94C   [6A, 6A, 22A, J, J, J, J, D, D, E, 5E, J, E, E, E, E, 14A, 9A, 29A, K, E, D, D, D, D, E, E, E, E, E, E, I, J, E, I, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, 5A, 16A, E, E, E, E, E, E, E, 3A, I, I, E, I, E, E, E, E, E, E, E, E, E, K, K, 31A, 15A, 18A, A, 19A, 2A, 18A, 19A, 5I, 5E, 5E, 5E, 5E, 5E, 5E, 5E, K]   \n",
      "  2  GOODVISITS    1 BinTableHDU    164   59266R x 73C   [6A, 6A, 22A, J, 5A, J, D, D, 5E, J, E, I, I, E, E, I, E, E, I, I, E, J, E, I, E, E, E, D, D, E, 9A, 9A, K, E, D, D, E, E, E, E, E, E, E, 3A, E, I, E, E, E, E, E, E, E, E, E, K, 31A, 15A, 18A, A, 19A, 2A, 18A, 19A, 5I, 5E, 5E, 5E, 5E, 5E, 5E, 5E, K]   \n",
      "  3  ALLSTARS      1 BinTableHDU    206   28124R x 94C   [6A, 6A, 22A, J, J, J, J, D, D, E, 5E, J, E, E, E, E, 14A, 9A, 29A, K, E, D, D, D, D, E, E, E, E, E, E, I, J, E, I, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, E, 5A, 16A, E, E, E, E, E, E, E, 3A, I, I, E, I, E, E, E, E, E, E, E, E, E, K, K, 31A, 15A, 18A, A, 19A, 2A, 18A, 19A, 5I, 5E, 5E, 5E, 5E, 5E, 5E, 5E, K]   \n",
      "  4  ALLVISITS     1 BinTableHDU    164   80592R x 73C   [6A, 6A, 22A, J, 5A, J, D, D, 5E, J, E, I, I, E, E, I, E, E, I, I, E, J, E, I, E, E, E, D, D, E, 9A, 9A, K, E, D, D, E, E, E, E, E, E, E, 3A, E, I, E, E, E, E, E, E, E, E, E, K, 31A, 15A, 18A, A, 19A, 2A, 18A, 19A, 5I, 5E, 5E, 5E, 5E, 5E, 5E, 5E, K]   \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div><i>Table length=3</i>\n",
       "<table id=\"table4581893328\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>DRPVER</th><th>MPROCVER</th><th>MANGAID</th><th>MINMJD</th><th>MAXMJD</th><th>NVISITS</th><th>NPLATES</th><th>RA</th><th>DEC</th><th>EPOCH</th><th>PSFMAG [5]</th><th>MNGTARG2</th><th>INPUT_LOGG</th><th>INPUT_TEFF</th><th>INPUT_FE_H</th><th>INPUT_ALPHA_M</th><th>INPUT_SOURCE</th><th>PHOTOCAT</th><th>DESIGNATION</th><th>SOURCE_ID</th><th>REF_EPOCH</th><th>GAIARA</th><th>GAIARA_ERROR</th><th>GAIADEC</th><th>GAIADEC_ERROR</th><th>PARALLAX</th><th>PARALLAX_ERROR</th><th>PMRA</th><th>PMRA_ERROR</th><th>PMDEC</th><th>PMDEC_ERROR</th><th>ASTROMETRIC_PARAMS_SOLVED</th><th>ASTROMETRIC_N_GOOD_OBS_AL</th><th>ASTROMETRIC_CHI2_AL</th><th>VISIBILITY_PERIODS_USED</th><th>PHOT_G_MEAN_FLUX</th><th>PHOT_G_MEAN_FLUX_OVER_ERROR</th><th>PHOT_G_MEAN_MAG</th><th>PHOT_BP_MEAN_FLUX</th><th>PHOT_BP_MEAN_FLUX_OVER_ERROR</th><th>PHOT_BP_MEAN_MAG</th><th>PHOT_RP_MEAN_FLUX</th><th>PHOT_RP_MEAN_FLUX_OVER_ERROR</th><th>PHOT_RP_MEAN_MAG</th><th>PHOT_BP_RP_EXCESS_FACTOR</th><th>BP_RP</th><th>R_MED_GEO</th><th>R_LO_GEO</th><th>R_HI_GEO</th><th>R_MED_PHOTOGEO</th><th>R_LO_PHOTOGEO</th><th>R_HI_PHOTOGEO</th><th>R_FLAG</th><th>TMASS_ID</th><th>TMASS_DISTANCE</th><th>J_M</th><th>J_MSIGCOM</th><th>H_M</th><th>H_MSIGCOM</th><th>K_M</th><th>K_MSIGCOM</th><th>PH_QUAL</th><th>GAL_CONTAM</th><th>MP_FLG</th><th>CONTAMINATION</th><th>GAIA_CLEANMATCH</th><th>EBV</th><th>EBV_SIGMA_UP</th><th>EBV_SIGMA_DN</th><th>M_G</th><th>M_G_ERR_UP</th><th>M_G_ERR_DN</th><th>BPRPC</th><th>BPRPC_ERR_UP</th><th>BPRPC_ERR_DN</th><th>DUSTCLEAN</th><th>GOODSTARS</th><th>SIMBAD_MAIN_ID</th><th>OTYPE_S</th><th>SP_TYPE</th><th>SP_QUAL</th><th>SP_BIBCODE</th><th>MK_DS</th><th>MK_SPECTRAL_TYPE</th><th>MK_BIBCODE</th><th>PS1_NMAG_OK [5]</th><th>PS1_MEAN [5]</th><th>PS1_ERR [5]</th><th>PS1_STDEV [5]</th><th>PS1_MEDIAN [5]</th><th>PS1_Q25 [5]</th><th>PS1_Q75 [5]</th><th>PS1_MEDIAN_AP [5]</th><th>PS1_OBJ_ID</th></tr></thead>\n",
       "<thead><tr><th>bytes6</th><th>bytes6</th><th>bytes22</th><th>int32</th><th>int32</th><th>int32</th><th>int32</th><th>float64</th><th>float64</th><th>float32</th><th>float32</th><th>int32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>bytes14</th><th>bytes9</th><th>bytes29</th><th>int64</th><th>float32</th><th>float64</th><th>float64</th><th>float64</th><th>float64</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>int16</th><th>int32</th><th>float32</th><th>int16</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>bytes5</th><th>bytes16</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>bytes3</th><th>int16</th><th>int16</th><th>float32</th><th>int16</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>int64</th><th>int64</th><th>bytes31</th><th>bytes15</th><th>bytes18</th><th>bytes1</th><th>bytes19</th><th>bytes2</th><th>bytes18</th><th>bytes19</th><th>int16</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>int64</th></tr></thead>\n",
       "<tr><td>v3_1_1</td><td>v1_7_7</td><td>13-0</td><td>56741</td><td>56745</td><td>3</td><td>1</td><td>231.01780658696867</td><td>41.913900785404856</td><td>2003.3239</td><td>16.26342 .. 14.904105</td><td>1050624</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td></td><td>sdss_dr8</td><td>Gaia EDR3 1390865480240476288</td><td>1390865480240476288</td><td>2016.0</td><td>231.01766555701496</td><td>0.025298090651631355</td><td>41.913832569495874</td><td>0.030044497922062874</td><td>0.50258994</td><td>0.03409784</td><td>-25.366081</td><td>0.029792115</td><td>-19.648682</td><td>0.04169199</td><td>31</td><td>412</td><td>1206.2949</td><td>27</td><td>18109.506</td><td>3655.1206</td><td>15.042601</td><td>10341.287</td><td>740.6116</td><td>15.302106</td><td>11356.126</td><td>829.0937</td><td>14.60982</td><td>1.1981229</td><td>0.69228554</td><td>1861.5792</td><td>1775.5562</td><td>1976.9001</td><td>1910.0037</td><td>1794.7963</td><td>2007.7109</td><td>10033</td><td>15240428+4154501</td><td>0.13108905</td><td>14.073</td><td>0.026</td><td>13.885</td><td>0.04</td><td>13.821</td><td>0.055</td><td>AAA</td><td>0</td><td>0</td><td>0.0</td><td>1</td><td>0.049999997</td><td>0.010000002</td><td>0.013599997</td><td>3.4985201</td><td>0.17268096</td><td>0.13597098</td><td>0.6241392</td><td>0.01856478</td><td>0.013715437</td><td>1</td><td>1</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>9 .. 8</td><td>7.522757e-07 .. 1.0520259e-06</td><td>2.3831912e-09 .. 3.835339e-09</td><td>9.72428e-09 .. 1.5595141e-08</td><td>7.514121e-07 .. 1.0510656e-06</td><td>7.4521523e-07 .. 1.0422388e-06</td><td>7.607696e-07 .. 1.0611734e-06</td><td>7.5735426e-07 .. 1.0542399e-06</td><td>7230230134580793380</td></tr>\n",
       "<tr><td>v3_1_1</td><td>v1_7_7</td><td>13-1</td><td>56741</td><td>56745</td><td>3</td><td>1</td><td>230.9779115513416</td><td>41.51587852720575</td><td>2003.3239</td><td>16.862331 .. 15.488885</td><td>1050624</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td></td><td>sdss_dr8</td><td>Gaia EDR3 1390839882235285248</td><td>1390839882235285248</td><td>2016.0</td><td>230.97787214740822</td><td>0.024625370278954506</td><td>41.51587864924203</td><td>0.02397824451327324</td><td>0.46039167</td><td>0.029003393</td><td>-6.1111665</td><td>0.029598054</td><td>1.9620645</td><td>0.03524218</td><td>31</td><td>391</td><td>467.0832</td><td>27</td><td>10599.103</td><td>3162.124</td><td>15.624194</td><td>6045.938</td><td>485.68765</td><td>15.884883</td><td>6606.726</td><td>705.4566</td><td>15.197929</td><td>1.1937487</td><td>0.68695354</td><td>2050.3647</td><td>1917.6636</td><td>2204.3506</td><td>2042.8788</td><td>1920.9108</td><td>2151.9128</td><td>10033</td><td>15235469+4130571</td><td>0.052852284</td><td>14.685</td><td>0.037</td><td>14.483</td><td>0.052</td><td>14.341</td><td>0.084</td><td>AAA</td><td>0</td><td>0</td><td>0.0</td><td>1</td><td>0.04</td><td>0.0</td><td>0.017199999</td><td>3.9618852</td><td>0.18124844</td><td>0.11291079</td><td>0.63248146</td><td>0.023503989</td><td>0.0027140335</td><td>1</td><td>1</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>6 .. 5</td><td>4.4493285e-07 .. 6.162903e-07</td><td>1.7645847e-09 .. 3.1219782e-09</td><td>6.6578227e-09 .. 1.0175217e-08</td><td>4.4526698e-07 .. 6.1949964e-07</td><td>4.4003212e-07 .. 6.1321646e-07</td><td>4.4643048e-07 .. 6.203839e-07</td><td>4.4597456e-07 .. 6.12279e-07</td><td>7212198143885268383</td></tr>\n",
       "<tr><td>v3_1_1</td><td>v1_7_7</td><td>13-10</td><td>56741</td><td>56745</td><td>3</td><td>1</td><td>229.95203771283292</td><td>42.26929773840978</td><td>2003.406</td><td>17.795345 .. 16.309675</td><td>1050624</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td></td><td>sdss_dr8</td><td>Gaia EDR3 1392448295948027520</td><td>1392448295948027520</td><td>2016.0</td><td>229.95197348479758</td><td>0.033872004598379135</td><td>42.269222847101084</td><td>0.03682512417435646</td><td>0.44329122</td><td>0.04312375</td><td>-14.153964</td><td>0.04381568</td><td>-18.661991</td><td>0.05284407</td><td>31</td><td>367</td><td>340.86145</td><td>26</td><td>4797.9546</td><td>2022.3936</td><td>16.484726</td><td>2675.991</td><td>294.34412</td><td>16.76983</td><td>3097.7744</td><td>281.9717</td><td>16.020271</td><td>1.2033806</td><td>0.7495594</td><td>2154.3264</td><td>1948.7139</td><td>2397.3086</td><td>2175.3767</td><td>2000.6583</td><td>2383.1648</td><td>10033</td><td>15194848+4216094</td><td>0.14924406</td><td>15.475</td><td>0.061</td><td>15.302</td><td>0.111</td><td>15.432</td><td>0.226</td><td>ABD</td><td>0</td><td>0</td><td>0.0</td><td>1</td><td>0.04</td><td>0.009999998</td><td>0.013599999</td><td>4.687022</td><td>0.21906196</td><td>0.22549295</td><td>0.695674</td><td>0.019022966</td><td>0.014446789</td><td>1</td><td>1</td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td></td><td>8 .. 8</td><td>1.9470079e-07 .. 2.9486222e-07</td><td>7.158463e-10 .. 1.4682996e-09</td><td>1.988472e-09 .. 4.1317323e-09</td><td>1.9514357e-07 .. 2.9469902e-07</td><td>1.9417467e-07 .. 2.9141435e-07</td><td>1.9598181e-07 .. 2.9700522e-07</td><td>1.9603152e-07 .. 2.985393e-07</td><td>7194271706305926916</td></tr>\n",
       "</table></div>"
      ],
      "text/plain": [
       "<Table length=3>\n",
       "DRPVER MPROCVER ...       PS1_MEDIAN_AP [5]             PS1_OBJ_ID    \n",
       "bytes6  bytes6  ...            float32                    int64       \n",
       "------ -------- ... ------------------------------ -------------------\n",
       "v3_1_1   v1_7_7 ... 7.5735426e-07 .. 1.0542399e-06 7230230134580793380\n",
       "v3_1_1   v1_7_7 ...   4.4597456e-07 .. 6.12279e-07 7212198143885268383\n",
       "v3_1_1   v1_7_7 ...  1.9603152e-07 .. 2.985393e-07 7194271706305926916"
      ]
     },
     "execution_count": 4,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# mastarall-gaiaedr3-extcorr-simbad-ps1-v3_1_1-v1_7_7-v1.fits contains some additional columns taken from gaia catalogue, such as parallax\n",
    "# Data def is here https://data.sdss.org/datamodel/files/MANGA_SPECTRO_MASTAR/DRPVER/MPROCVER/vac/crossmatch/VER/mastarall-gaiaedr3-extcorr-simbad-ps1-DRPVER-MPROCVER-VER.html\n",
    "hdulist = fits.open('data/mastarall-gaiaedr3-extcorr-simbad-ps1-v3_1_1-v1_7_7-v1.fits')\n",
    "hdulist.info()\n",
    "dat = Table.read('data/mastarall-gaiaedr3-extcorr-simbad-ps1-v3_1_1-v1_7_7-v1.fits', format='fits', hdu=1)\n",
    "dat[[0,1,2]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Filename: data/mastar-goodstars-v3_1_1-v1_7_7-params-v1.fits\n",
      "No.    Name      Ver    Type      Cards   Dimensions   Format\n",
      "  0  PRIMARY       1 PrimaryHDU       4   ()      \n",
      "  1                1 BinTableHDU    163   24290R x 73C   [6A, 6A, 22A, J, J, I, I, I, D, D, E, J, E, E, E, E, E, E, E, E, E, E, E, E, E, E, I, 4I, 11A, I, 4I, 8A, E, E, E, E, E, E, E, E, E, E, I, E, E, E, E, E, E, E, E, E, E, I, I, E, E, E, E, E, E, E, E, I, E, E, E, E, E, E, E, E, I]   \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div><i>Table length=3</i>\n",
       "<table id=\"table4584996048\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>DRPVER</th><th>MPROCVER</th><th>MANGAID</th><th>MINMJD</th><th>MAXMJD</th><th>NVISITS</th><th>NPLATES</th><th>NGOODVISITS</th><th>RA</th><th>DEC</th><th>EPOCH</th><th>MNGTARG2</th><th>TEFF_MED</th><th>LOGG_MED</th><th>FEH_MED</th><th>FEH_CAL_MED</th><th>ALPHA_MED</th><th>ZH_MED</th><th>ZH_CAL_MED</th><th>TEFF_MED_ERR</th><th>LOGG_MED_ERR</th><th>FEH_MED_ERR</th><th>FEH_CAL_MED_ERR</th><th>ALPHA_MED_ERR</th><th>ZH_MED_ERR</th><th>ZH_CAL_MED_ERR</th><th>NGROUPS</th><th>INPUT_GROUPS [4]</th><th>INPUT_GROUPS_NAME</th><th>NALPHAGROUPS</th><th>INPUT_ALPHA_GROUPS [4]</th><th>INPUT_ALPHA_GROUPS_NAME</th><th>TEFF_JI</th><th>LOGG_JI</th><th>FEH_JI</th><th>ALPHA_JI</th><th>VMICRO_JI</th><th>TEFF_ERR_JI</th><th>LOGG_ERR_JI</th><th>FEH_ERR_JI</th><th>ALPHA_ERR_JI</th><th>VMICRO_ERR_JI</th><th>VALID_JI</th><th>TEFF_DL</th><th>LOGG_DL</th><th>FEH_DL</th><th>ALPHA_DL</th><th>TEFF_ERR_DL</th><th>LOGG_ERR_DL</th><th>FEH_ERR_DL</th><th>ALPHA_ERR_DL</th><th>AV_DL</th><th>AV_ERR_DL</th><th>AV_VALID_DL</th><th>VALID_DL</th><th>TEFF_LH</th><th>LOGG_LH</th><th>FEH_LH</th><th>ALPHA_LH</th><th>TEFF_ERR_LH</th><th>LOGG_ERR_LH</th><th>FEH_ERR_LH</th><th>ALPHA_ERR_LH</th><th>VALID_LH</th><th>TEFF_YC</th><th>LOGG_YC</th><th>FEH_YC</th><th>ALPHA_YC</th><th>TEFF_ERR_YC</th><th>LOGG_ERR_YC</th><th>FEH_ERR_YC</th><th>ALPHA_ERR_YC</th><th>VALID_YC</th></tr></thead>\n",
       "<thead><tr><th>bytes6</th><th>bytes6</th><th>bytes22</th><th>int32</th><th>int32</th><th>int16</th><th>int16</th><th>int16</th><th>float64</th><th>float64</th><th>float32</th><th>int32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>int16</th><th>int16</th><th>bytes11</th><th>int16</th><th>int16</th><th>bytes8</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>int16</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>int16</th><th>int16</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>int16</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>int16</th></tr></thead>\n",
       "<tr><td>v3_1_1</td><td>v1_7_7</td><td>13-0</td><td>56741</td><td>56745</td><td>3</td><td>1</td><td>3</td><td>231.01780658696867</td><td>41.913900785404856</td><td>2003.3239</td><td>1050624</td><td>6191.071</td><td>4.219723</td><td>-1.792098</td><td>-1.9307878</td><td>0.1298964</td><td>-1.7046252</td><td>-1.843315</td><td>137.75697</td><td>0.21835943</td><td>0.28459492</td><td>0.3201387</td><td>0.20890057</td><td>0.32050836</td><td>0.35244876</td><td>4</td><td>1 .. 1</td><td>ji,dl,lh,yc</td><td>3</td><td>1 .. 0</td><td>ji,dl,lh</td><td>6180.511</td><td>4.2151074</td><td>-1.7441205</td><td>0.1298964</td><td>-0.09584684</td><td>18.399563</td><td>0.04323083</td><td>0.02458167</td><td>0.013390596</td><td>0.027287679</td><td>1</td><td>6201.6304</td><td>4.3336077</td><td>-1.8400757</td><td>0.17510231</td><td>77.41988</td><td>0.17680597</td><td>0.18059194</td><td>0.20890057</td><td>0.052960053</td><td>0.012031451</td><td>1</td><td>1</td><td>6163.0</td><td>3.955576</td><td>-1.8851776</td><td>0.05613085</td><td>289.13992</td><td>0.4525479</td><td>0.6131209</td><td>0.2487366</td><td>1</td><td>6230.0244</td><td>4.224339</td><td>-1.6713201</td><td>0.025369195</td><td>198.09407</td><td>0.25991288</td><td>0.3885979</td><td>0.13884951</td><td>1</td></tr>\n",
       "<tr><td>v3_1_1</td><td>v1_7_7</td><td>13-1</td><td>56741</td><td>56745</td><td>3</td><td>1</td><td>3</td><td>230.9779115513416</td><td>41.51587852720575</td><td>2003.3239</td><td>1050624</td><td>6216.574</td><td>4.301462</td><td>-1.3324354</td><td>-1.376784</td><td>0.114812054</td><td>-1.2555526</td><td>-1.2999012</td><td>164.57558</td><td>0.29216492</td><td>0.33033115</td><td>0.3427338</td><td>0.24654767</td><td>0.37251624</td><td>0.38355723</td><td>4</td><td>1 .. 1</td><td>ji,dl,lh,yc</td><td>3</td><td>1 .. 0</td><td>ji,dl,lh</td><td>6138.902</td><td>4.1714764</td><td>-1.3305898</td><td>0.12656641</td><td>-0.09232411</td><td>17.564354</td><td>0.041336466</td><td>0.021629697</td><td>0.012421674</td><td>0.027498843</td><td>1</td><td>6270.5386</td><td>4.8033395</td><td>-1.334281</td><td>0.114812054</td><td>123.59717</td><td>0.32401302</td><td>0.20802689</td><td>0.25351095</td><td>0.026926234</td><td>0.0012748792</td><td>1</td><td>1</td><td>6162.61</td><td>4.0581994</td><td>-1.39935</td><td>-0.0050985515</td><td>347.36853</td><td>0.4111625</td><td>0.6620736</td><td>0.24654767</td><td>1</td><td>6318.235</td><td>4.4314475</td><td>-1.3129147</td><td>0.038700227</td><td>205.55399</td><td>0.26031682</td><td>0.45263544</td><td>0.14582594</td><td>1</td></tr>\n",
       "<tr><td>v3_1_1</td><td>v1_7_7</td><td>13-10</td><td>56741</td><td>56745</td><td>3</td><td>1</td><td>3</td><td>229.95203771283292</td><td>42.26929773840978</td><td>2003.406</td><td>1050624</td><td>6047.921</td><td>5.0</td><td>-1.2175925</td><td>-1.0344117</td><td>0.2564873</td><td>-1.0371149</td><td>-0.85393405</td><td>125.86901</td><td>0.39187005</td><td>0.18854932</td><td>0.15469566</td><td>0.1756774</td><td>0.23127986</td><td>0.20462227</td><td>1</td><td>0 .. 0</td><td>dl</td><td>1</td><td>0 .. 0</td><td>dl</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>0</td><td>6047.921</td><td>5.0</td><td>-1.2175925</td><td>0.2564873</td><td>125.86901</td><td>0.39187005</td><td>0.18854932</td><td>0.1756774</td><td>0.046790883</td><td>0.0016245309</td><td>1</td><td>1</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>-999.0</td><td>0</td></tr>\n",
       "</table></div>"
      ],
      "text/plain": [
       "<Table length=3>\n",
       "DRPVER MPROCVER        MANGAID         ... FEH_ERR_YC ALPHA_ERR_YC VALID_YC\n",
       "bytes6  bytes6         bytes22         ...  float32     float32     int16  \n",
       "------ -------- ---------------------- ... ---------- ------------ --------\n",
       "v3_1_1   v1_7_7 13-0                   ...  0.3885979   0.13884951        1\n",
       "v3_1_1   v1_7_7 13-1                   ... 0.45263544   0.14582594        1\n",
       "v3_1_1   v1_7_7 13-10                  ...     -999.0       -999.0        0"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# mastar-goodstars-v3_1_1-v1_7_7-params-v1.fits contains params derived by different researchers\n",
    "# Data def is here https://data.sdss.org/datamodel/files/MANGA_SPECTRO_MASTAR/DRPVER/MPROCVER/vac/parameters/VER/mastar-goodstars-DRPVER-MPROCVER-params-VER.html\n",
    "hdulist = fits.open('data/mastar-goodstars-v3_1_1-v1_7_7-params-v1.fits')\n",
    "hdulist.info()\n",
    "dat = Table.read('data/mastar-goodstars-v3_1_1-v1_7_7-params-v1.fits', format='fits', hdu=1)\n",
    "dat[[0,1,2]]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Filename: data/mastar-combspec-v3_1_1-v1_7_7-lsfpercent99.5.fits\n",
      "No.    Name      Ver    Type      Cards   Dimensions   Format\n",
      "  0  PRIMARY       1 PrimaryHDU       4   ()      \n",
      "  1                1 BinTableHDU     87   23893R x 35C   [6A, 6A, 22A, D, D, E, 5E, J, 9A, E, I, E, E, I, I, E, 4563D, 4563E, 4563E, 4563E, 4563E, 4563J, I, E, E, E, J, E, I, I, E, E, 2E, I, J]   \n"
     ]
    },
    {
     "data": {
      "text/html": [
       "<div><i>Table length=3</i>\n",
       "<table id=\"table5019627968\" class=\"table-striped table-bordered table-condensed\">\n",
       "<thead><tr><th>DRPVER</th><th>MPROCVER</th><th>MANGAID</th><th>RA</th><th>DEC</th><th>EPOCH</th><th>PSFMAG [5]</th><th>MNGTARG2</th><th>PHOTOCAT</th><th>EXPTIME</th><th>NVELGOOD</th><th>HELIOV</th><th>VERR</th><th>V_ERRCODE</th><th>VELVARFLAG</th><th>DV_MAXSIG</th><th>WAVE [4563]</th><th>FLUX [4563]</th><th>IVAR [4563]</th><th>DISP [4563]</th><th>PREDISP [4563]</th><th>MASK [4563]</th><th>NEXP_USED</th><th>S2N</th><th>S2N10</th><th>BADPIXFRAC</th><th>GOODVISITS_ID</th><th>MAXVSHIFT</th><th>NVISITS</th><th>NPLATES</th><th>EXPTIME_MAX</th><th>EXPTIME_MIN</th><th>SCALEMINMAX [2]</th><th>SCI</th><th>MASTAR_QUAL</th></tr></thead>\n",
       "<thead><tr><th>bytes6</th><th>bytes6</th><th>bytes22</th><th>float64</th><th>float64</th><th>float32</th><th>float32</th><th>int32</th><th>bytes9</th><th>float32</th><th>int16</th><th>float32</th><th>float32</th><th>int16</th><th>int16</th><th>float32</th><th>float64</th><th>float32</th><th>float32</th><th>float32</th><th>float32</th><th>int32</th><th>int16</th><th>float32</th><th>float32</th><th>float32</th><th>int32</th><th>float32</th><th>int16</th><th>int16</th><th>float32</th><th>float32</th><th>float32</th><th>int16</th><th>int32</th></tr></thead>\n",
       "<tr><td>v3_1_1</td><td>v1_7_7</td><td>13-0</td><td>231.01780658696867</td><td>41.913900785404856</td><td>2003.3239</td><td>16.26342 .. 14.904105</td><td>1050624</td><td>sdss_dr8</td><td>900.11</td><td>15</td><td>-60.050854</td><td>0.8497747</td><td>0</td><td>0</td><td>0.91884124</td><td>3621.5959848601933 .. 10353.805444147549</td><td>301.57104 .. 0.0</td><td>0.0072971634 .. 0.0</td><td>1.5208263 .. 2.954979</td><td>1.4960281 .. 2.9099424</td><td>0 .. 167772160</td><td>3</td><td>93.81854</td><td>110.239395</td><td>0.0010957703</td><td>27150</td><td>0.0</td><td>1</td><td>1</td><td>900.11</td><td>900.11</td><td>1.0 .. 1.0</td><td>0</td><td>0</td></tr>\n",
       "<tr><td>v3_1_1</td><td>v1_7_7</td><td>13-1</td><td>230.9779115513416</td><td>41.51587852720575</td><td>2003.3239</td><td>16.862331 .. 15.488885</td><td>1050624</td><td>sdss_dr8</td><td>900.11</td><td>30</td><td>-65.59255</td><td>1.0004026</td><td>0</td><td>1</td><td>4.591554</td><td>3621.5959848601933 .. 10353.805444147549</td><td>164.9537 .. 0.0</td><td>0.041380003 .. 0.0</td><td>1.5208263 .. 2.954979</td><td>1.4960281 .. 2.9099424</td><td>0 .. 167772160</td><td>9</td><td>124.32759</td><td>144.06245</td><td>0.0010957703</td><td>27154</td><td>3.802063</td><td>2</td><td>1</td><td>900.11</td><td>900.105</td><td>0.9608172 .. 1.0230947</td><td>0</td><td>1024</td></tr>\n",
       "<tr><td>v3_1_1</td><td>v1_7_7</td><td>13-10</td><td>229.95203771283292</td><td>42.26929773840978</td><td>2003.406</td><td>17.795345 .. 16.309675</td><td>1050624</td><td>sdss_dr8</td><td>900.105</td><td>45</td><td>-196.76616</td><td>1.1315472</td><td>0</td><td>0</td><td>0.99534094</td><td>3621.5959848601933 .. 10353.805444147549</td><td>70.72167 .. 30.104826</td><td>0.07304844 .. 0.13305204</td><td>1.5208263 .. 2.954979</td><td>1.4960281 .. 2.9099424</td><td>0 .. 167788544</td><td>15</td><td>106.181694</td><td>124.904465</td><td>0.0</td><td>27180</td><td>5.077667</td><td>3</td><td>1</td><td>900.11</td><td>900.1</td><td>0.9692881 .. 1.0158587</td><td>0</td><td>1024</td></tr>\n",
       "</table></div>"
      ],
      "text/plain": [
       "<Table length=3>\n",
       "DRPVER MPROCVER        MANGAID         ...  SCI  MASTAR_QUAL\n",
       "bytes6  bytes6         bytes22         ... int16    int32   \n",
       "------ -------- ---------------------- ... ----- -----------\n",
       "v3_1_1   v1_7_7 13-0                   ...     0           0\n",
       "v3_1_1   v1_7_7 13-1                   ...     0        1024\n",
       "v3_1_1   v1_7_7 13-10                  ...     0        1024"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# As mentioned before, I think using normalised spectra makes most sense, unless we expect our method to be able to deal with resolution variability.\n",
    "# Therefore first try using normalised mastar-combspec-v3_1_1-v1_7_7-lsfpercent99.5.fits\n",
    "# Data def is here https://data.sdss.org/datamodel/files/MANGA_SPECTRO_MASTAR/DRPVER/MPROCVER/mastar-combspec-DRPVER-MPROCVER-lsfpercentPP.P.html\n",
    "hdulist = fits.open('data/mastar-combspec-v3_1_1-v1_7_7-lsfpercent99.5.fits')\n",
    "hdulist.info()\n",
    "spectra = Table.read('data/mastar-combspec-v3_1_1-v1_7_7-lsfpercent99.5.fits', format='fits', hdu=1)\n",
    "spectra[[0,1,2]]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Spectral data consists of: WAVE (frequency value - this is the same for all entries, an x-axis value), FLUX (amount of light reaching the detector, IVAR is the inverse squared, this is the y value), DISP (resolution-related, also PREDISP), MASK (for data goodness?).\n",
    "\n",
    "When using LFS normalised data, we can ignore DISP (they have all been normalised to the same value).\n",
    "\n",
    "IVAR is somewhat [described here](https://www.sdss.org/dr14/manga/manga-tutorials/manga-faq/). Infinite flux is represented by 0.\n",
    "\n",
    "We can join these spectrums with our main data table via MANGAID."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "for s in np.random.choice(spectra, size=10):\n",
    "\tplt.plot(s['FLUX'])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This looks good, although:\n",
    "\n",
    "* some datapoints are negative\n",
    "* there is some significant dips in the flux values - are these the absorption lines?\n",
    "\n",
    "Some more info from [MaNGA IDL tutorial](https://www.sdss.org/dr13/manga/manga-tutorials/how-do-i-look-at-my-data/idl/):\n",
    "\n",
    "* When mask does not equal 0, this indicates a bad pixel. Ivar stands for the inverse variance.\n",
    "* whenever ivar is 0, this also indicates a bad pixel.\n",
    "\n",
    "Hopefully these values will help us remove the bad values. So let's put the algorithm togheter:\n",
    "\n",
    "* zero the values where IVAR is zero or MASK is non-zero\n",
    "* feed the resulting spectral data (FLUX) into the algorithm\n",
    "* target the TEFF_INPUT label via join on MANGAID\n",
    "* initially use a data split on goodstars containing a valid TEFF taken from upstream catalogues (caution is needed, because multiple catalogues are used). There is about 4,000 of these stars.\n",
    "* we can then further test the algorithm on the extra data provided in the \"params\" set by comparing how it fared compared to other algorithms (24,290 stars in total)\n",
    "\n",
    "Alternatively, if 4,000 stars is not enough for training, we can pick one of the values produced by other algorithms (the less-ML) ones, and we can still judge results against other algorithms.\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "One can look up the actual image via e.g. http://skyserver.sdss.org/dr17/VisualTools/explore/summary?ra=48.873343&dec=-8.442834 (need RA and DEC)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/jpeg": "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",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "ra = 48.873343\n",
    "dec = -8.442834\n",
    "\n",
    "# Shipped to 01.py\n",
    "def get_star_image(ra, dec):\n",
    "    # https://skyserver.sdss.org/dr17/SkyServerWS/ImgCutout/getjpeg?TaskName=Skyserver.Explore.Image&ra=48.8733428617884%20&dec=-8.44283369381076&scale=0.2&width=200&height=200&opt=G\n",
    "    params = {\n",
    "        'TaskName': 'Skyserver.Explore.Image',\n",
    "        'ra': ra,\n",
    "        'dec': dec,\n",
    "        'scale': 0.2,\n",
    "        'width': 50,\n",
    "        'height': 50,\n",
    "    }\n",
    "    try:\n",
    "        with urllib.request.urlopen('http://skyserver.sdss.org/dr17/SkyServerWS/ImgCutout/getjpeg?%s' % urllib.parse.urlencode(params)) as response:\n",
    "            return response.read()\n",
    "    except urllib.error.HTTPError as err:\n",
    "        return b''\n",
    "\n",
    "display(Image(get_star_image(ra,dec)))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Add it all together to show all the pieces fit."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<table border=1><tr><th>MANGAID</th><th>SDSS image</th><th>MaStar Spectrum</th><th>Input T</th><th>Input source</th></tr><tr><td>7-8309428             </td><td><img src=\"data:image/png;base64,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\"></td><td>No spectrum</td><td>5891K</td><td>APOGEE        </td></tr>\n",
       "<tr><td>3-125091464           </td><td><img src=\"data:image/png;base64,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\"></td><td><img src=\"data:image/png;base64,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\"></td><td>5730K</td><td>LAMOST        </td></tr>\n",
       "<tr><td>7-18237701            </td><td>No image</td><td><img src=\"data:image/png;base64,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\"></td><td>4151K</td><td>APOGEE        </td></tr>\n",
       "<tr><td>3-137524300           </td><td><img src=\"data:image/png;base64,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\"></td><td><img src=\"data:image/png;base64,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\"></td><td>4692K</td><td>APOGEE        </td></tr>\n",
       "<tr><td>3-134070255           </td><td><img src=\"data:image/png;base64,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\"></td><td><img src=\"data:image/png;base64,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\"></td><td>3884K</td><td>LAMOST        </td></tr>\n",
       "<tr><td>3-36610797            </td><td><img src=\"data:image/png;base64,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\"></td><td><img src=\"data:image/png;base64,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\"></td><td>6648K</td><td>LAMOST        </td></tr>\n",
       "<tr><td>7-2479723             </td><td>No image</td><td><img src=\"data:image/png;base64,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\"></td><td>4351K</td><td>LAMOST_CANNON </td></tr>\n",
       "<tr><td>3-56953115            </td><td>No image</td><td><img src=\"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAJAAAABICAYAAAAZK3z6AAAAOXRFWHRTb2Z0d2FyZQBNYXRwbG90bGliIHZlcnNpb24zLjUuMiwgaHR0cHM6Ly9tYXRwbG90bGliLm9yZy8qNh9FAAAACXBIWXMAAAsTAAALEwEAmpwYAAAGVUlEQVR4nO2dW6hVRRjHf9vUSo20NNQKBoWULghdNFOTHiJronoICyWkwATTKEsaumEROoRWQj1oGalQgXQ5cYZTQSUkWj0YSaBm2VBZGSZamoba6WHN1uU+t733Wmuvffl+cNisua1v7fXfs+ab+WadQmdnJ4JQLf3yNkBobERAQiJEQEIiREBCIkRAQiJEQEIiREBCIkRAQiJEQEIiREB1hDLuEWXcmLztqIT+eRvQiijj+gNXAxOAS4EHY9nLgYIyruCt7rLOpIw7F5gJbPJWb6+Fvb1RkLWwbFDGDQDu9lavV8ZdBiwCHPBOlU1+AVzbTfpqb/W8KttMjAgoRZRx44AdOZx6OjAc6PBWH6nliUVACVHGDQZ+B4bkbUtgMvAzsL8WYhIBVYEy7hzgGuCTlJpcDdyfUlul3Aus9VZ3KuPGA8e81T+k1bgIqAKUcecDlwCbEzY1E7iZ6OYCTAM2ACNjZeYAFhiV8Fxd8FYX0mpL3PgeUMYVlHEjlHGd4W8RsI/exfNa+Hw5fG4BbgXmhZvWDxjnrd4A7AlllnirN3mrRwGPFxvyVq/zVo8G1qZ4WQAo44am1Za48SUo4xRwAfBlSdaKPqqO9FbvVcYt8VbvARaWFghu+Xfh8F3gSeCDWJEXgKXA1FjanyXNfAa0A1cCs4kG7eP7sK2UScBHFdbpFnmEBcLczEKim1gp+7zVI1I2CQBl3AqiKYAi473VO2P5Y4h6qRHAuJC811s9Uhk3GrgReKOk2Une6q/SsE8eYYAy7kxgJ9WJB2BNiuaUUjpeOe3YW73bWz0NeDiWvD/k/Qp0hLRVsfyDaRnX0gJSxg1RxrUDR4FKlhBmAo/FjgekatjplDXg9VZ3hHHWQ8CMWPofRHNE84kcgOXArrSMa/Ux0G6irr8nzib6jv4uSf8YuCd2nOUPsSKPyVu9spu04jhqF7A4DaOKtJyAlHF3AQOBdX2V9VYfDXXeBGYRDVx3easPKeNWAc8A5wHHsrO4C6m54GnQUo8wZZwG3qYM8cTxVs8GBnurv/ZWHwppx4DnQ5EsPZG6EkwpLSOgsOTQXm19b/U/3STX4ua+XoNzVE3LCAiYm2HbmfVA3upvsmo7DVpJQC/2lhk8mCHAVRW0mcfjpa4eaU07iFbGnQUsI1r0nNJDsQNE7nsngLf6MLBVGVcLE5uCphUQ8BLQa6CVt3pYbUxJFemBsiSELJQT6rklxdO27HpQUwgoxOdMA44An5ZRZT6wPoVTO6LFz/dSaKtcSic1c6UpBAT8VWH5jcX5nCR4q7dR20fK9d7qn2p4vj5paAEp4wpUPk8yo4zdDMOJljHqCm/153nbUErDCkgZN4JoHDO2wqrb+ioQWzsS+qChBBTCLgYBE4EPy6y2j6hHAZjirf4tC9syZgHwb95GdEdDBZQp49qA2yqs9grwAKQbCyxENMxMtDJuEL2LJ+6W/wgMBYZx6hpTi4ERTtEwAgLu7CVvHadvsbnJW33QW30AWEkUbTi1u4pCMhppDLSgh/R2b/UcZdzT4fg5b/XJ3ibED1cadC6USV0LKGwVfpYohLSUO4D3ifZTAZwIn3V9Tc1G3T7CwlsodtC9eLZ7q9uAgd7qYnBYUUB1e03NSF1+2cq4sUQr5d2xFLgFTkYFFjkePqUHqiF19WWHvVlXAFt7KuOtfqKHrOI8SV3+KJqV3AWkjOtHFC04Ebivj+K9bb1ZA1xONGYSakTuE4nKuHIN2OitviFTY4SKybW7D71PuXyfmSFC1eQ9XphVQdlKQzaEGpC3gK6roOxTmVkhVE0uAlLGDVXGdQAXl+aFBc+dnHLLAd7qYV+WkDM188KUcYuJdnIOIFodnxHLngu8WjzwVo8PwWL/haT4602EOiJTLywMkgve6hMxb+t2oC1ezltdUMZtBiZLyEVjkfUjrAM4XuKqt/VQdjp1GEYq9E5mPVCYVS7rrRXS6zQuWfZAj2bYtlAnZCmgZRm2LdQJec8DCQ1OXgKSWeUmIUsB9Sf6d0ZnxNKKSxdd3uMnNCY1WY0Pr5a70Fu9Whk3AfiW2EyzeGGNS27hHMq4w0SbBE94q3OPSxKqI88bd1H4+yVHG4SE5B5QJjQ24sYLiRABCYkQAQmJEAEJiRABCYkQAQmJEAEJiRABCYkQAQmJ+B/4j6/QkKZ+1gAAAABJRU5ErkJggg==\"></td><td>5203K</td><td>LAMOST_CANNON </td></tr>\n",
       "<tr><td>3-125091186           </td><td><img src=\"data:image/png;base64,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\"></td><td><img src=\"data:image/png;base64,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\"></td><td>5653K</td><td>LAMOST        </td></tr>\n",
       "<tr><td>3-22904320            </td><td>No image</td><td><img src=\"data:image/png;base64,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\"></td><td>4167K</td><td>APOGEE        </td></tr>\n",
       "</table>"
      ],
      "text/plain": [
       "<IPython.core.display.HTML object>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "# Shipped to 01.py\n",
    "def get_spectrum_plot(spectra, id):\n",
    "    sp = spectra[spectra['MANGAID']==id]    \n",
    "    if len(sp)>0:\n",
    "        plotdata = io.BytesIO()\n",
    "        plt.figure(figsize=(2, 1))\n",
    "        plt.axis('off')\n",
    "        plt.plot(sp[0]['FLUX'])\n",
    "        plt.savefig(plotdata, format='png')\n",
    "        plt.close()    \n",
    "\n",
    "        return plotdata.getvalue()\n",
    "    else:\n",
    "        return b''\n",
    "\n",
    "randomstars = tstars.sample(n=10)\n",
    "o = '<table border=1><tr><th>MANGAID</th><th>SDSS image</th><th>MaStar Spectrum</th><th>Input T</th><th>Input source</th></tr>'\n",
    "for (id,s) in randomstars.iterrows():\n",
    "    o += '<tr>'\n",
    "    id = s['MANGAID']\n",
    "    o += '<td>%s</td>' % (id.decode('ascii'), )\n",
    "\n",
    "    starimg = get_star_image(s['RA'], s['DEC'])\n",
    "    if len(starimg)==0:\n",
    "        o += '<td>No image</td>'\n",
    "    else:\n",
    "        starimg_enc = base64.b64encode(starimg).decode('ascii')\n",
    "        o += '<td><img src=\"data:image/png;base64,%s\"></td>' % starimg_enc\n",
    "\n",
    "    sp = get_spectrum_plot(spectra, id)\n",
    "    if len(sp)>0:\n",
    "        starspec_enc = base64.b64encode(sp).decode('ascii')\n",
    "        o += '<td><img src=\"data:image/png;base64,%s\"></td>' % starspec_enc\n",
    "    else:\n",
    "        o += '<td>No spectrum</td>'\n",
    "\n",
    "    o += \"<td>%.0fK</td><td>%s</td>\" % (s['INPUT_TEFF'], s['INPUT_SOURCE'].decode('ascii'))\n",
    "    o += \"</tr>\\n\"\n",
    "o += '</table>'\n",
    "\n",
    "display(HTML(o))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "At this point I went away and implemented the functionality into stars.py."
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3.8.10 64-bit",
   "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": "3.8.10"
  },
  "vscode": {
   "interpreter": {
    "hash": "e7370f93d1d0cde622a1f8e1c04877d8463912d04d973331ad4851f04de6915a"
   }
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}