{
 "cells": [
  {
   "cell_type": "markdown",
   "id": "35323959",
   "metadata": {},
   "source": [
    "# FITS_tutorial5\n",
    "Open a FITS file whose primary array represents\n",
    "a spectrum (flux vs wavelength)\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "**Author:** Claudi Martinez  \n",
    "<i><small>This notebook tutorial was automatically generated with <a href= \"https://github.com/root-project/root/blob/master/documentation/doxygen/converttonotebook.py\">ROOTBOOK-izer</a> from the macro found in the ROOT repository  on Tuesday, May 19, 2026 at 08:13 PM.</small></i>"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "id": "830e6088",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:14:01.823379Z",
     "iopub.status.busy": "2026-05-19T20:14:01.823269Z",
     "iopub.status.idle": "2026-05-19T20:14:02.138076Z",
     "shell.execute_reply": "2026-05-19T20:14:02.137344Z"
    }
   },
   "outputs": [],
   "source": [
    "using Upvd_t = std::unique_ptr<TVectorD>;"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "8c622d4f",
   "metadata": {},
   "source": [
    "We open a FITS file that contains a table with 9 rows and 8 columns. Column 4 has name\n",
    "'mag' and contains a vector of 6 numeric components. The values of vectors in rows 1 and 2 (column 4) are:\n",
    "Row1: (99.0, 24.768, 23.215, 21.68, 21.076, 20.857)\n",
    "Row2: (99.0, 21.689, 20.206, 18.86, 18.32 , 18.128 )\n",
    "WARNING: when coding, row and column indices start from 0"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "id": "4faaef34",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:14:02.139937Z",
     "iopub.status.busy": "2026-05-19T20:14:02.139819Z",
     "iopub.status.idle": "2026-05-19T20:14:02.344341Z",
     "shell.execute_reply": "2026-05-19T20:14:02.343690Z"
    }
   },
   "outputs": [],
   "source": [
    "TString dir = gROOT->GetTutorialDir();"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bb04bf65",
   "metadata": {},
   "source": [
    "Open the table"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "id": "4da4625c",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:14:02.346319Z",
     "iopub.status.busy": "2026-05-19T20:14:02.346205Z",
     "iopub.status.idle": "2026-05-19T20:14:02.550123Z",
     "shell.execute_reply": "2026-05-19T20:14:02.549414Z"
    }
   },
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Info in <TFITSHDU::LoadHDU>: The selected HDU contains a Table Extension\n"
     ]
    }
   ],
   "source": [
    "TFITSHDU hdu(dir + \"/io/fitsio/sample4.fits[1]\");"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "02327c6c",
   "metadata": {},
   "source": [
    "Read vectors at rows 1 and 2 (indices 0 and 1)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "id": "3e22370d",
   "metadata": {
    "collapsed": false,
    "execution": {
     "iopub.execute_input": "2026-05-19T20:14:02.551818Z",
     "iopub.status.busy": "2026-05-19T20:14:02.551699Z",
     "iopub.status.idle": "2026-05-19T20:14:02.754324Z",
     "shell.execute_reply": "2026-05-19T20:14:02.753801Z"
    }
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "99, 24.768, 23.215, 21.68, 21.076, 20.857)\n",
      "99, 21.689, 20.206, 18.86, 18.32, 18.128)\n",
      "99, 24.768, 23.215, 21.68, 21.076, 20.857)\n",
      "99, 21.689, 20.206, 18.86, 18.32, 18.128)\n",
      "99, 23.993, 22.575, 21.51, 21.07, 20.915)\n",
      "99, 22.26, 20.717, 19.404, 18.888, 18.706)\n",
      "99, 21.957, 20.41, 18.874, 18.271, 18.054)\n",
      "99, 22.113, 20.535, 18.872, 18.229, 17.995)\n",
      "99, 22.177, 20.678, 19.275, 18.714, 18.513)\n",
      "99, 23.394, 21.846, 20.27, 19.649, 19.424)\n",
      "99, 23.094, 21.452, 19.482, 18.723, 18.434)\n"
     ]
    }
   ],
   "source": [
    "std::array<Upvd_t, 2> vs{Upvd_t(hdu.GetTabRealVectorCell(0, \"mag\")), Upvd_t(hdu.GetTabRealVectorCell(1, \"mag\"))};\n",
    "for (auto &&v : vs) {\n",
    "   for(auto i : ROOT::TSeqI(v->GetNoElements())) {\n",
    "      if (i > 0)\n",
    "         printf(\", \");\n",
    "      printf(\"%lg\", (*v)[i]); // NOTE: the asterisk is for using the overloaded [] operator of the TVectorD object\n",
    "   }\n",
    "   printf(\")\\n\");\n",
    "}\n",
    "\n",
    "// We now dump all rows using the function GetTabRealVectorCells()\n",
    "std::unique_ptr<TObjArray> vectorCollection(hdu.GetTabRealVectorCells(\"mag\"));\n",
    "for (auto vObj : *vectorCollection) {\n",
    "   auto &v = *static_cast<TVectorD*>(vObj);\n",
    "   for (auto i : ROOT::TSeqI(v.GetNoElements())) {\n",
    "      if (i > 0) printf(\", \");\n",
    "      printf(\"%lg\", (v[i]));\n",
    "   }\n",
    "   printf(\")\\n\");\n",
    "}"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "edab2b53",
   "metadata": {},
   "source": [
    "Draw all canvases "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "id": "f777a341",
   "metadata": {
    "collapsed": false,
    "execution": {
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     "shell.execute_reply": "2026-05-19T20:14:02.959521Z"
    }
   },
   "outputs": [],
   "source": [
    "gROOT->GetListOfCanvases()->Draw()"
   ]
  }
 ],
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