ANTARES/ANTARES-SkyPortal.ipynb

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    "__author__ = 'Chien-Hsiu Lee <lee@noao.edu>'\n",
    "__version__ = '20210308' # yyyymmdd\n",
    "__datasets__ = ['']\n",
    "__keywords__ = ['ANTARES', 'SkyPortal']"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Interfacing ANTARES with SkyPortal\n",
    "\n",
    "**This notebook requires the installation of ANTARES client (https://noao.gitlab.io/antares/client/) and SkyPortal (https://https://skyportal.io). For more detail on programmatic access of SkyPortal with RestAPI, please see (https://skyportal.io/docs/api.html).**\n",
    "\n",
    "\n",
    "\n",
    "SkyPortal is an astronomical data platform that interactively displays astronomical datasets for annotation, analysis, and discovery. We can ingest ANTARES locus/alert with the SkyPortal API as follows.\n",
    "\n",
    "\n",
    "### Table of contents\n",
    "* [Imports & setup](#import)\n",
    "* [Create a SkyPortal candidate for an ANTARES locus object](#candidate)\n",
    "* [Populate the candidate with photometry/light curve](#lightcurve)\n",
    "* [Ingest a stream of locus based on ANTARES filters](#stream)\n",
    "\n",
    "\n",
    "<a class=\"anchor\" id=\"import\"></a>\n",
    "# Imports & Setup\n",
    "The first step is to import ANTARES client, API function, and define API token for SkyPortal\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "outputs": [],
   "source": [
    "from antares_client.search import get_by_id, get_by_ztf_object_id, search\n",
    "import astropy.time as atime\n",
    "import datetime\n",
    "import requests\n",
    "\n",
    "#token can be generated by SkyPortal account manager\n",
    "token = 'xxxxxx'\n",
    "\n",
    "def api(method, endpoint, data=None):\n",
    "    headers = {'Authorization': f'token {token}'}\n",
    "    response = requests.request(method, endpoint, json=data, headers=headers)\n",
    "    return response"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a class=\"anchor\" id=\"candidate\"></a>\n",
    "# Create a SkyPortal candidate for an ANTARES locus object\n",
    "\n",
    "The next step is to provide the locus information. The following piece of code will create a candidate in the SkyPortal database using API **POST** function. It will also tell you if the object already exists, and in that case will not attempt to re-create the candidate."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
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   "source": [
    "obj_id=\"ANT2020pcud2\"\n",
    "\n",
    "locus = get_by_id(obj_id)\n",
    "print(locus.locus_id,locus.ra,locus.dec)\n",
    "\n",
    "data = {\n",
    "\"ra\": locus.ra,\n",
    "\"dec\": locus.dec,\n",
    "\"id\": obj_id,\n",
    "\"filter_ids\": [ 20 ],\n",
    "}\n",
    "\n",
    "response = api('POST', 'http://localhost:5000/api/candidates', data)\n",
    "\n",
    "print(f'HTTP code: {response.status_code}, {response.reason}')\n",
    "if response.status_code in (200, 400):\n",
    "    print(f'JSON response: {response.json()}')\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a class=\"anchor\" id=\"lightcurve\"></a>\n",
    "# Populate the candidate with photometry/light curve\n",
    "\n",
    "Once the candidate is posted, we can populate the light curve information with all the alerts associated with this locus. This can be done as follows. This piece of code will use the **POST** function to upload photometry from ZTF. "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
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   "source": [
    "for alert in locus.alerts:\n",
    "    if 'ztf_magpsf' in alert.properties:\n",
    "        if alert.properties['ztf_fid'] == 1:\n",
    "            filterid='ztfg'\n",
    "        if alert.properties['ztf_fid'] == 2:\n",
    "            filterid='ztfr'\n",
    "        print(\"AlertID\",alert.properties['ztf_candid'])\n",
    "        phot={\n",
    "            \"magerr\": alert.properties['ztf_sigmapsf'],\n",
    "            \"limiting_mag\": alert.properties['ztf_diffmaglim'],\n",
    "            \"instrument_id\": 6,\n",
    "            \"group_ids\": [ 1 ],\n",
    "            \"obj_id\": obj_id,\n",
    "            \"mjd\": alert.properties['ztf_jd']-2400000.5,\n",
    "            \"magsys\": 'ab',\n",
    "            \"filter\": filterid,\n",
    "            \"mag\": alert.properties['ztf_magpsf']\n",
    "        }\n",
    "        response = api('POST', 'http://localhost:5000/api/photometry', phot)\n",
    "        print(f'HTTP code: {response.status_code}, {response.reason}')\n",
    "        if response.status_code in (200, 400):\n",
    "            print(f'JSON response: {response.json()}')\n",
    "\n",
    "\n",
    "\n"
   ]
  },
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   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "<a class=\"anchor\" id=\"stream\"></a>\n",
    "# Ingest a stream of locus based on ANTARES filters\n",
    "\n",
    "Now we have gone through the process of ingesting a locus. In ANTARES we provide streams based on user-definied filters. We can use ANTARES search client to find locus tagged by a given filter, and ingest those alerts to SkyPortal as follows."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "currentmjd=atime.Time(datetime.datetime.utcnow()).mjd\n",
    "\n",
    "query = {\n",
    "    \"query\": {\n",
    "        \"bool\": {\n",
    "            \"filter\": [\n",
    "                {\n",
    "                    \"range\": {\n",
    "                        \"properties.oldest_alert_observation_time\": {\n",
    "                            \"gte\": currentmjd-15,\n",
    "                        }\n",
    "                    }\n",
    "                },\n",
    "                {\n",
    "                    \"range\": {\n",
    "                        \"properties.newest_alert_observation_time\": {\n",
    "                            \"gte\": currentmjd-7,\n",
    "                        }\n",
    "                    }\n",
    "                },\n",
    "                {\n",
    "                    \"range\": {\n",
    "                        \"properties.num_alerts\": {\n",
    "                            \"gte\": 3,\n",
    "                        }\n",
    "                    }\n",
    "                },\n",
    "                {\n",
    "                     \"term\": {\n",
    "                         \"tags\": \"desi_target\"\n",
    "                     }\n",
    "                }\n",
    "             ]\n",
    "        }\n",
    "    }\n",
    "}\n",
    "\n",
    "\n",
    "result_set = search(query)\n",
    "for locus in search(query):\n",
    "    print(locus.locus_id)\n",
    "    data = {\n",
    "\"ra\": locus.ra,\n",
    "\"dec\": locus.dec,\n",
    "\"id\": locus.locus_id,\n",
    "\"filter_ids\": [ 20 ],\n",
    "\"passed_at\": datetime.datetime.utcnow().strftime('%Y-%m-%dT%H:%M:%S'),\n",
    "}\n",
    "response = api('POST', 'http://localhost:5000/api/candidates', data) \n",
    "print(f'HTTP code: {response.status_code}, {response.reason}')\n",
    "    if response.status_code in (200, 400):\n",
    "        print(f'JSON response: {response.json()}')\n",
    "    for alert in locus.alerts:\n",
    "        if 'ztf_magpsf' in alert.properties:\n",
    "            if alert.properties['ztf_fid'] == 1:\n",
    "                filterid='ztfg'\n",
    "            if alert.properties['ztf_fid'] == 2:\n",
    "                filterid='ztfr'\n",
    "        print(\"AlertID\",alert.properties['ztf_candid'])\n",
    "        phot={\n",
    "            \"magerr\": alert.properties['ztf_sigmapsf'],\n",
    "#           \"alert_id\": alert.properties['ztf_candid'],\n",
    "            \"limiting_mag\": alert.properties['ztf_diffmaglim'],\n",
    "            \"instrument_id\": 6,\n",
    "            \"group_ids\": [ 26 ],\n",
    "            \"obj_id\": locus.locus_id,\n",
    "            \"mjd\": alert.properties['ztf_jd']-2400000.5,\n",
    "            \"magsys\": 'ab',\n",
    "            \"filter\": filterid,\n",
    "            \"mag\": alert.properties['ztf_magpsf']\n",
    "        }\n",
    "        response = api('POST', 'http://localhost:5000/api/photometry', phot)\n",
    "        print(f'HTTP code: {response.status_code}, {response.reason}')\n",
    "        if response.status_code in (200, 400):\n",
    "            print(f'JSON response: {response.json()}')\n",
    " \n",
    "\n"
   ]
  }
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