DataLabNotebookTemplate.ipynb

{
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  {
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   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "__author__ = 'Jane Author <jane@noao.edu>, John Writer <john.doe@noao.edu>' # single string; emails in <>\n",
    "__version__ = '20190207' # yyyymmdd; version datestamp of this notebook\n",
    "__datasets__ = ['']  # datasets used in this notebook; for available datasets, see cell \"Available datasets in Data Lab\" further below\n",
    "__keywords__ = [''], # keywords relevant to this notebook, e.g. ['science case','dwarf galaxies'] Use only keywords from the master list: https://github.com/noaodatalab/notebooks-latest/blob/master/internal/keywords.txt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Short self-describing title of this notebook (e.g. Finding Dwarf Galaxies in DES DR1)\n",
    "\n",
    "*Jane Author, John Writer & NOAO Data Lab Team*"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Table of contents\n",
    "* [Goals & notebook summary](#goals)\n",
    "* [Disclaimer & Attribution](#attribution)\n",
    "* [Imports & setup](#import)\n",
    "* [Authentication](#auth)\n",
    "* [First chapter](#chapter1)\n",
    "* [Resources and references](#resources)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a class=\"anchor\" id=\"goals\"></a>\n",
    "# Goals\n",
    "One or two sentences, or a bullet list, of the goals of this notebook. E.g. \"To find dwarf galaxies in DES DR1 images\"."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Summary\n",
    "Description of the content of this notebook: we do X, using data Y. The technique used is Z. Also rename the notebook file to something meaningful, e.g. 'TimeSeriesAnalysisRRLyrae_20171011'."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a class=\"anchor\" id=\"attribution\"></a>\n",
    "# Disclaimer & attribution\n",
    "If you use this notebook for your published science, please acknowledge the following:\n",
    "\n",
    "* Data Lab concept paper: Fitzpatrick et al., \"The NOAO Data Laboratory: a conceptual overview\", SPIE, 9149, 2014, http://dx.doi.org/10.1117/12.2057445\n",
    "\n",
    "* Data Lab disclaimer: http://datalab.noao.edu/disclaimers.php"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a class=\"anchor\" id=\"import\"></a>\n",
    "# Imports and setup"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "# std lib\n",
    "from getpass import getpass\n",
    "\n",
    "# 3rd party # remove imports that are not needed\n",
    "import numpy as np\n",
    "import pylab as plt\n",
    "import matplotlib\n",
    "%matplotlib inline\n",
    "\n",
    "# Data Lab\n",
    "from dl import authClient as ac, queryClient as qc, storeClient as sc\n",
    "# Data Lab helpers as needed, e.g.: (uncomment as needed)\n",
    "# from dl.helpers import cluster  # import one particular helper module\n",
    "# from dl.helpers.plot import plotSkymapScatter  # import one function from a helper module\n",
    "# from dl.helpers import all  # convenience import of all helper modules\n",
    "#\n",
    "# or old-style:\n",
    "#from dl.helpers import convert"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a class=\"anchor\" id=\"auth\"></a>\n",
    "# Authentication\n",
    "Use this mini-section to authenticate the user, IF the notebook needs authentication (e.g. for saving files to VOSpace). If the notebook does not require authnetication at all, remove this entire subsection."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "#token = ac.login(input(\"Enter user name: (+ENTER) \"),getpass(\"Enter password: (+ENTER) \"))\n",
    "#if not ac.isValidToken(token):\n",
    "#    raise Exception('Token is not valid. Please check your usename/password and execute this cell again.')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Available datasets in Data Lab\n",
    "This is a way to find out about available datasets. Use it only internally, and the list the datasets used in the ``__datasets__`` list in the very first cell of the notebook. Remove then this subsection from the notebook."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Datasets available in Data Lab (with current profile):\n",
      " ['allwise', 'cp_calib', 'dad_dr1', 'dad_dr2', 'decaps_dr1', 'des_dr1', 'des_sva1', 'gaia_dr1', 'gaia_dr2', 'ivoa', 'ivoa_calibrated', 'ivoa_coadd', 'ivoa_des_dr1', 'ivoa_des_sva1', 'ivoa_des_y1', 'ivoa_des_y2', 'ivoa_des_y3', 'ivoa_ls_dr3', 'ivoa_ls_dr4', 'ivoa_ls_dr5', 'ivoa_ls_dr6', 'ivoa_ls_dr7', 'ivoa_nsa', 'ivoa_raw', 'ivoa_smash_dr1', 'ivoa_splus_dr1', 'ivoa_stripe82', 'ls_dr3', 'ls_dr4', 'ls_dr5', 'ls_dr6', 'ls_dr7', 'neo_dr1', 'nsc_dr1', 'phat_v2', 'sdss_dr13', 'sdss_dr14', 'smash_dr1', 'splus_dr1', 'stripe82', 'twomass', 'usno']\n"
     ]
    }
   ],
   "source": [
    "# these schemas are not astronomical datasets\n",
    "_remove = set(['ivao','ivao_smash','tap_schema','schema'])\n",
    "\n",
    "# get all schemas from DB\n",
    "_schemas = set(qc.query(sql='SELECT schema FROM tbl_stat').split())\n",
    "\n",
    "# remove non-astro schemas\n",
    "_alldatasets = sorted(list(_schemas - _remove))\n",
    "print(\"Datasets available in Data Lab (with current profile):\\n\", _alldatasets)\n",
    "\n",
    "# TODO: Enter used datasets by hand in the list __datasets__ in the very first cell above"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a class=\"anchor\" id=\"chapter1\"></a>\n",
    "# Chapter 1 -- your content below..."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "5\n"
     ]
    }
   ],
   "source": [
    "a = 2+3\n",
    "print(a)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a class=\"anchor\" id=\"resources\"></a>\n",
    "# Resources and references\n",
    "Add some resources and \"further reading\" links relevant to this notebook.\n",
    "\n",
    "Lomb, N.R. (1976) \"Least-squares frequency analysis of unequally spaced data\". Astrophysics and Space Science. 39 (2): 447–462: http://adsabs.harvard.edu/abs/1976Ap%26SS..39..447L\n",
    "\n",
    "Scargle, J. D. (1982) \"Studies in astronomical time series analysis. II - Statistical aspects of spectral analysis of unevenly spaced data\". Astrophysical Journal. 263, 835: http://adsabs.harvard.edu/doi/10.1086/160554\n",
    "\n",
    "Lomb-Scargle periodograms in `astropy`: http://docs.astropy.org/en/stable/stats/lombscargle.html"
   ]
  }
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