{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "4b941a47-56e3-418b-ab2f-0d2737e4ff35",
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np\n",
    "import matplotlib.pyplot as plt\n",
    "from astropy.io import ascii, fits\n",
    "import pandas as pd\n",
    "from scipy.interpolate import interpn\n",
    "from matplotlib import rc\n",
    "from matplotlib.ticker import MultipleLocator\n",
    "rc('font',**{'family':'sans-serif'})\n",
    "rc('text', usetex=True)\n",
    "\n",
    "%matplotlib inline"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "132576a1-60d4-4c37-ad52-7d44241ad4fc",
   "metadata": {},
   "outputs": [],
   "source": [
    "# load calibration table into pandas (I like to use astropy for this!)\n",
    "calibration_table = ascii.read('calibration_values_final.dat').to_pandas()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "e096c657-bae5-4712-b03a-5599d6012c14",
   "metadata": {},
   "outputs": [
    {
     "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>Element</th>\n",
       "      <th>Source</th>\n",
       "      <th>C_ZP</th>\n",
       "      <th>MG_H</th>\n",
       "      <th>C_LOGG_0.25</th>\n",
       "      <th>C_LOGG_0.75</th>\n",
       "      <th>C_LOGG_1.25</th>\n",
       "      <th>C_LOGG_1.75</th>\n",
       "      <th>C_LOGG_2.25</th>\n",
       "      <th>C_LOGG_2.75</th>\n",
       "      <th>C_LOGG_3.25</th>\n",
       "      <th>C_LOGG_RC</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>O</td>\n",
       "      <td>ASPCAP</td>\n",
       "      <td>-0.025233</td>\n",
       "      <td>-0.7</td>\n",
       "      <td>0.122413</td>\n",
       "      <td>0.110120</td>\n",
       "      <td>0.077184</td>\n",
       "      <td>0.008790</td>\n",
       "      <td>-0.078782</td>\n",
       "      <td>-0.081200</td>\n",
       "      <td>-0.081200</td>\n",
       "      <td>-0.057636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>O</td>\n",
       "      <td>ASPCAP</td>\n",
       "      <td>-0.025233</td>\n",
       "      <td>-0.6</td>\n",
       "      <td>0.077489</td>\n",
       "      <td>0.071658</td>\n",
       "      <td>0.062236</td>\n",
       "      <td>0.008790</td>\n",
       "      <td>-0.069021</td>\n",
       "      <td>-0.090320</td>\n",
       "      <td>-0.090320</td>\n",
       "      <td>-0.057636</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>O</td>\n",
       "      <td>ASPCAP</td>\n",
       "      <td>-0.025233</td>\n",
       "      <td>-0.5</td>\n",
       "      <td>0.059866</td>\n",
       "      <td>0.044108</td>\n",
       "      <td>0.042094</td>\n",
       "      <td>0.008790</td>\n",
       "      <td>-0.059546</td>\n",
       "      <td>-0.074037</td>\n",
       "      <td>-0.061900</td>\n",
       "      <td>-0.057785</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>O</td>\n",
       "      <td>ASPCAP</td>\n",
       "      <td>-0.025233</td>\n",
       "      <td>-0.4</td>\n",
       "      <td>0.043405</td>\n",
       "      <td>0.023815</td>\n",
       "      <td>0.029638</td>\n",
       "      <td>0.008790</td>\n",
       "      <td>-0.036640</td>\n",
       "      <td>-0.050375</td>\n",
       "      <td>-0.055643</td>\n",
       "      <td>-0.033883</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>O</td>\n",
       "      <td>ASPCAP</td>\n",
       "      <td>-0.025233</td>\n",
       "      <td>-0.3</td>\n",
       "      <td>0.000877</td>\n",
       "      <td>0.003671</td>\n",
       "      <td>0.018772</td>\n",
       "      <td>0.008790</td>\n",
       "      <td>-0.020035</td>\n",
       "      <td>-0.022795</td>\n",
       "      <td>-0.032122</td>\n",
       "      <td>-0.019297</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>259</th>\n",
       "      <td>Ce</td>\n",
       "      <td>BAWLAS</td>\n",
       "      <td>-0.270557</td>\n",
       "      <td>0.0</td>\n",
       "      <td>0.475912</td>\n",
       "      <td>0.475912</td>\n",
       "      <td>0.395491</td>\n",
       "      <td>0.360345</td>\n",
       "      <td>0.333374</td>\n",
       "      <td>0.322095</td>\n",
       "      <td>0.332321</td>\n",
       "      <td>0.327706</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>260</th>\n",
       "      <td>Ce</td>\n",
       "      <td>BAWLAS</td>\n",
       "      <td>-0.270557</td>\n",
       "      <td>0.1</td>\n",
       "      <td>0.517316</td>\n",
       "      <td>0.517316</td>\n",
       "      <td>0.411855</td>\n",
       "      <td>0.360345</td>\n",
       "      <td>0.334116</td>\n",
       "      <td>0.323325</td>\n",
       "      <td>0.322559</td>\n",
       "      <td>0.325892</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>261</th>\n",
       "      <td>Ce</td>\n",
       "      <td>BAWLAS</td>\n",
       "      <td>-0.270557</td>\n",
       "      <td>0.2</td>\n",
       "      <td>0.569010</td>\n",
       "      <td>0.569010</td>\n",
       "      <td>0.452310</td>\n",
       "      <td>0.360345</td>\n",
       "      <td>0.326639</td>\n",
       "      <td>0.329709</td>\n",
       "      <td>0.326591</td>\n",
       "      <td>0.332544</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>262</th>\n",
       "      <td>Ce</td>\n",
       "      <td>BAWLAS</td>\n",
       "      <td>-0.270557</td>\n",
       "      <td>0.3</td>\n",
       "      <td>0.567933</td>\n",
       "      <td>0.567933</td>\n",
       "      <td>0.465626</td>\n",
       "      <td>0.360345</td>\n",
       "      <td>0.332176</td>\n",
       "      <td>0.304676</td>\n",
       "      <td>0.315799</td>\n",
       "      <td>0.301838</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>263</th>\n",
       "      <td>Ce</td>\n",
       "      <td>BAWLAS</td>\n",
       "      <td>-0.270557</td>\n",
       "      <td>0.4</td>\n",
       "      <td>0.567933</td>\n",
       "      <td>0.567933</td>\n",
       "      <td>0.486645</td>\n",
       "      <td>0.360345</td>\n",
       "      <td>0.317754</td>\n",
       "      <td>0.319478</td>\n",
       "      <td>0.327736</td>\n",
       "      <td>0.302264</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>264 rows × 12 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "    Element  Source      C_ZP  MG_H  C_LOGG_0.25  C_LOGG_0.75  C_LOGG_1.25  \\\n",
       "0         O  ASPCAP -0.025233  -0.7     0.122413     0.110120     0.077184   \n",
       "1         O  ASPCAP -0.025233  -0.6     0.077489     0.071658     0.062236   \n",
       "2         O  ASPCAP -0.025233  -0.5     0.059866     0.044108     0.042094   \n",
       "3         O  ASPCAP -0.025233  -0.4     0.043405     0.023815     0.029638   \n",
       "4         O  ASPCAP -0.025233  -0.3     0.000877     0.003671     0.018772   \n",
       "..      ...     ...       ...   ...          ...          ...          ...   \n",
       "259      Ce  BAWLAS -0.270557   0.0     0.475912     0.475912     0.395491   \n",
       "260      Ce  BAWLAS -0.270557   0.1     0.517316     0.517316     0.411855   \n",
       "261      Ce  BAWLAS -0.270557   0.2     0.569010     0.569010     0.452310   \n",
       "262      Ce  BAWLAS -0.270557   0.3     0.567933     0.567933     0.465626   \n",
       "263      Ce  BAWLAS -0.270557   0.4     0.567933     0.567933     0.486645   \n",
       "\n",
       "     C_LOGG_1.75  C_LOGG_2.25  C_LOGG_2.75  C_LOGG_3.25  C_LOGG_RC  \n",
       "0       0.008790    -0.078782    -0.081200    -0.081200  -0.057636  \n",
       "1       0.008790    -0.069021    -0.090320    -0.090320  -0.057636  \n",
       "2       0.008790    -0.059546    -0.074037    -0.061900  -0.057785  \n",
       "3       0.008790    -0.036640    -0.050375    -0.055643  -0.033883  \n",
       "4       0.008790    -0.020035    -0.022795    -0.032122  -0.019297  \n",
       "..           ...          ...          ...          ...        ...  \n",
       "259     0.360345     0.333374     0.322095     0.332321   0.327706  \n",
       "260     0.360345     0.334116     0.323325     0.322559   0.325892  \n",
       "261     0.360345     0.326639     0.329709     0.326591   0.332544  \n",
       "262     0.360345     0.332176     0.304676     0.315799   0.301838  \n",
       "263     0.360345     0.317754     0.319478     0.327736   0.302264  \n",
       "\n",
       "[264 rows x 12 columns]"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# let's see what the calibration table looks like!\n",
    "calibration_table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "c1bdd89a-3942-4598-9fb1-c3be01611acb",
   "metadata": {},
   "outputs": [],
   "source": [
    "# set up element arrays\n",
    "calib_elems = pd.unique(np.array([calibration_table['Element'][i]+'_'+calibration_table['Source'][i] for i in range(len(calibration_table))]))\n",
    "all_elems = np.insert(calib_elems, 0, 'Mg_ASPCAP')\n",
    "\n",
    "# set up arrays for [Mg/H] and logg bins\n",
    "MgH_bin_centers = np.unique(calibration_table['MG_H'])\n",
    "logg_bin_centers = np.linspace(0.25, 3.75, 7, endpoint=False)\n",
    "\n",
    "logg_col_names = ['C_LOGG_0.25', 'C_LOGG_0.75', 'C_LOGG_1.25', 'C_LOGG_1.75','C_LOGG_2.25', 'C_LOGG_2.75','C_LOGG_3.25']"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "060c1a12-ac2e-49fb-8d18-a3677cc230c8",
   "metadata": {
    "tags": []
   },
   "source": [
    "### Reproduce Sit et al. Figure 3\n",
    "The position of Cu and Ce are switched in the paper to match the later median residual plots (where Cu, as a BAWLAS-only element, was frequently not measured and thus placed at the end of the sequence), but the order here groups all Fe-peak elements by atomic number and places the s-process element Ce at the end."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "b0daad78-5ad2-45e2-a3f5-65bb9f185285",
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0.5, 0.08, '$\\\\log(g)$')"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 994.5x1287 with 16 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig, axs = plt.subplots(16, 1, sharex=True, sharey=True, figsize=(8.5*1.17,11*1.17))\n",
    "\n",
    "mgh_bin = 0\n",
    "i = 0\n",
    "all_ele = pd.unique(np.array([elem.split('_')[0] for elem in calib_elems]))\n",
    "for ele in all_ele:\n",
    "    ele_aspcap = calibration_table[(calibration_table['MG_H']==mgh_bin) & (calibration_table['Element']==ele) & (calibration_table['Source']=='ASPCAP')]\n",
    "    ele_bawlas = calibration_table[(calibration_table['MG_H']==mgh_bin) & (calibration_table['Element']==ele) & (calibration_table['Source']=='BAWLAS')]\n",
    "    if len(ele_aspcap)>0:\n",
    "        logg_zp_aspcap = ele_aspcap['C_LOGG_1.75'].iloc[0]\n",
    "        p1 = axs[i].plot(logg_bin_centers, ele_aspcap[logg_col_names].values.flatten() - logg_zp_aspcap, c='#0173b2', marker='^', mfc='none', ms=7)\n",
    "        axs[i].plot(2.5, ele_aspcap['C_LOGG_RC'].iloc[0] - logg_zp_aspcap, marker='^', ms=7, c=p1[0].get_color())\n",
    "    if len(ele_bawlas)>0:\n",
    "        logg_zp_bawlas = ele_bawlas['C_LOGG_1.75'].iloc[0]\n",
    "        p2 = axs[i].plot(logg_bin_centers, ele_bawlas[logg_col_names].values.flatten() - logg_zp_bawlas, ls='--', c='#de8f05', marker='s', mfc='none', ms=7)\n",
    "        axs[i].plot(2.5, ele_bawlas['C_LOGG_RC'].iloc[0] - logg_zp_bawlas, marker='s', ms=7, c=p2[0].get_color())\n",
    "    axs[i].text(0.99, 0.9, ele, ha='right', va='top', fontsize=15, transform=axs[i].transAxes)\n",
    "    i += 1\n",
    "\n",
    "axs[0].set_xlim(0.1,3.4)\n",
    "axs[0].set_ylim(-0.25,0.19)\n",
    "for ax in axs:\n",
    "    ax.axhspan(-0.05, 0.05, facecolor='gray', alpha=0.2)\n",
    "    ax.xaxis.set_minor_locator(MultipleLocator(0.25))\n",
    "    ax.xaxis.set_major_locator(MultipleLocator(0.5))\n",
    "    ax.yaxis.set_minor_locator(MultipleLocator(0.05))\n",
    "    ax.yaxis.set_major_locator(MultipleLocator(0.1))\n",
    "    ax.tick_params(axis='y', which='both', direction='in', right=True, labelsize=11)\n",
    "    ax.tick_params(axis='x', which='both', direction='in', top=True, labelsize=11)\n",
    "    \n",
    "fig.subplots_adjust(hspace=0)\n",
    "fig.supylabel(r'$C_{\\log(g)}(\\mathrm{[Mg/H]}=0) + \\mathrm{Offset}$', fontsize=16, x=0.06)\n",
    "fig.supxlabel(r'$\\log(g)$', fontsize=16, y=0.08)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "31747d94-d940-47a6-8fd9-d76112303586",
   "metadata": {
    "tags": []
   },
   "source": [
    "### Apply $C_{\\log(g)}$ and $C_{ZP}$ to raw abundances\n",
    "We'll use the first 10 entries in the residual abundance catalog to demonstrate, but this can be extended to any number of stars. The APOGEE DR17 red clump catalog can be accessed at https://www.sdss4.org/dr17/data_access/value-added-catalogs/?vac_id=apogee-red-clump-(rc)-catalog"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "id": "30a3cb4c-e0b2-4dc6-bafc-f9b6f4ebc01f",
   "metadata": {},
   "outputs": [],
   "source": [
    "# load residual abundance catalog data\n",
    "with fits.open('2process_residual_abund_catalog_final.fits') as hdul:\n",
    "    catalog_data = hdul[1].data\n",
    "\n",
    "# get red clump stars\n",
    "with fits.open('apogee-rc-DR17.fits') as rc_hdul: # adjust file path as needed\n",
    "    rc_ids = rc_hdul[1].data['APOGEE_ID']\n",
    "rc_mask = np.isin(catalog_data['APOGEE_ID'], list(rc_ids))\n",
    "\n",
    "# make an array of raw abundances for the first 10 stars in the residual abundance catalog\n",
    "nstars = 10\n",
    "xh_arr = np.empty((len(all_elems), nstars))\n",
    "for i, elem in enumerate(all_elems):\n",
    "    elem = elem.upper()\n",
    "    ele, source = elem.split('_')\n",
    "    xh_arr[i,:] = catalog_data[ele+'_H_'+source+'_RAW'][:nstars]"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "id": "ab52cc78-b249-44e4-94a2-5be17c144733",
   "metadata": {},
   "outputs": [],
   "source": [
    "# in this cell define some functions to get the correct logg calibrations and apply them\n",
    "def extract_logg_grid_for_elem(ele, source, rc=False):\n",
    "    \"\"\"\n",
    "    Input\n",
    "    -----\n",
    "    ele : str\n",
    "          Element symbol matching entries in calibration_table (e.g., \"O\" or \"Ca\")\n",
    "    source : str\n",
    "             Element source matching entries in calibration_table (e.g., \"ASPCAP\" or \"BAWLAS\")\n",
    "    rc : bool\n",
    "         True = extract red clump calibrations\n",
    "    \n",
    "    Output\n",
    "    ------\n",
    "    grid : ndarray (dtype=float)\n",
    "           Array of log(g) calibration values for a given element.\n",
    "           2D array for non-RC, 1D array for RC\n",
    "    \"\"\"\n",
    "    if rc==True:\n",
    "        grid = calibration_table[(calibration_table['Element']==ele) & (calibration_table['Source']==source)]['C_LOGG_RC'].values\n",
    "    elif rc==False:\n",
    "        grid = calibration_table[(calibration_table['Element']==ele) & (calibration_table['Source']==source)][logg_col_names].values\n",
    "    return grid\n",
    "\n",
    "def apply_logg_offsets_to_star(mgh, logg, xh_vals, rc):\n",
    "    \"\"\"\n",
    "    Input\n",
    "    -----\n",
    "    mgh : float\n",
    "          [Mg/H] of star\n",
    "    logg : float\n",
    "           log(g) of star\n",
    "    xh_vals : ndarray (dtype=float)\n",
    "              1D array of [X/H] values. [Mg/H] must be the first element in the array.\n",
    "    rc : bool\n",
    "         Red clump membership (True = RC, False = Not RC)\n",
    "    \n",
    "    Output\n",
    "    ------\n",
    "    corr_xh : ndarray (dtype=float)\n",
    "              1D array of log(g)-calibrated [X/H] values, \n",
    "              in the order of xh_vals\n",
    "    \"\"\"\n",
    "    star_offsets = np.zeros_like(xh_vals)\n",
    "    for i, elem in enumerate(calib_elems):\n",
    "        ele, source = elem.split('_')\n",
    "        if rc==True:\n",
    "            offsets = extract_logg_grid_for_elem(ele, source, rc=True)\n",
    "            star_offsets[i+1] = np.interp(mgh, MgH_bin_centers, offsets)\n",
    "\n",
    "        elif rc==False:\n",
    "            offsets = extract_logg_grid_for_elem(ele, source)\n",
    "            grid = (MgH_bin_centers, logg_bin_centers)\n",
    "            interp_point = np.array([mgh, logg])\n",
    "            star_offsets[i+1] = interpn(grid, offsets, interp_point, bounds_error=False, fill_value=None)\n",
    "            \n",
    "    corr_xh = xh_vals + star_offsets\n",
    "    \n",
    "    return corr_xh"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "id": "e7ed8b27-2f4d-4195-bccf-2345ea94c213",
   "metadata": {},
   "outputs": [],
   "source": [
    "# now actually apply the logg calibrations to our sample of stars\n",
    "corr_xh_arr = np.empty((len(all_elems), nstars))\n",
    "for i in range(nstars):\n",
    "    corr_xh_arr[:,i] = apply_logg_offsets_to_star(xh_arr[0,i], catalog_data['LOGG'][i], xh_arr[:,i], rc_mask[i])\n",
    "    \n",
    "# make [X/Mg] array (first column of xh_arr is [Mg/H])\n",
    "corr_xmg_arr = corr_xh_arr - xh_arr[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "5682a962-d0b4-4b43-8431-19d4ff8bcb47",
   "metadata": {},
   "source": [
    "While the $\\log(g)$ calibrations are derived for \\[X/H\\], the zeropoint offsets are derived for \\[X/Mg\\] since they force \\[X/Mg\\] = 0 at \\[Mg/H\\] = 0. If you are only looking to correct the $\\log(g)$ systematics and do not need the overall zeropoint, no need to run the next cell."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "id": "a8c130ae-07ef-4c47-a80c-d52790820681",
   "metadata": {},
   "outputs": [],
   "source": [
    "# apply zeropoint offsets to [X/Mg] values\n",
    "for j, elem in enumerate(calib_elems):\n",
    "    ele, source = elem.split('_')\n",
    "    zp = pd.unique(calibration_table[(calibration_table['Element']==ele) & (calibration_table['Source']==source)]['C_ZP'])[0]\n",
    "    corr_xmg_arr[j+1] = corr_xmg_arr[j+1] + zp\n",
    "\n",
    "# convert ZP-corrected [X/Mg] to [X/H]\n",
    "corr_xh_arr = corr_xmg_arr + xh_arr[0]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "cac1c2aa-3322-4a7a-9644-f0dc6947caa0",
   "metadata": {},
   "source": [
    "Each row in the final `corr_xh_arr` array (matching the order of `all_elems`) should match the corresponding `_ADJ` column for that element in the catalog table (up to the occasional floating-point rounding error, which I have occasionally found, but which are too small to meaningfully affect any abundance analyses)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "355eb71f-5958-436a-8e9b-d55e69439d8a",
   "metadata": {},
   "outputs": [],
   "source": []
  }
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