{ "cells": [ { "cell_type": "code", "execution_count": null, "id": "a6eaeebf", "metadata": {}, "outputs": [], "source": [ "# Access astronomical databases\n", "from pyvo import registry # version >=1.6\n", "\n", "# Moc and HEALPix tools\n", "from mocpy import MOC\n", "\n", "# Coordinates manipulation\n", "from astropy.coordinates import SkyCoord\n", "\n", "# Sky visualization\n", "from ipyaladin import Aladin # version >=0.4.0\n", "\n", "# For plots\n", "import matplotlib.pyplot as plt\n" ] }, { "cell_type": "markdown", "id": "7ad7861f", "metadata": {}, "source": [ "# Welcome to VizieR example workflow\n", "\n", "[![Vizier](https://custom-icon-badges.demolab.com/badge/Vizier-gray.svg?logo=vizier&logoColor=orange&logoWidth=20)](https://vizier.cds.unistra.fr/viz-bin/VizieR \"https://vizier.cds.unistra.fr/viz-bin/VizieR\")\n", "\n", "**Notes:** \n", "\n", "It is a generic notebook, highlighting what can be done once you chose a catalog. This workflow is suggested by [CDS](https://cdsweb.unistra.fr/) (Strasbourg Astronomical Data Center, house of [VizieR](https://vizier.cds.unistra.fr/viz-bin/VizieR)).\n", "\n", "The notebook exploits [pyVO](https://pyvo.readthedocs.io/en/latest/), an advanced library of The [Virtual Observatory](https://ivoa.net/).\n", "\n", "[Astroquery](https://astroquery.readthedocs.io/en/latest/vizier/vizier.html) (not used here) is a well-documented, user-friendly alternative.\n", "\n", "--------------------------------------------------------\n", "\n", "## 1. Setup\n", "\n", "This example notebook has the following dependencies: \n", "\n", "**Required**\n", "- pyvo : this library facilitates the access to the Virtual Observatory (VO) resources. VizieR is part of the VO.\n", "This notebook needs version >=1.4.1\n", "**Optional, for visualization**\n", "- ipyaladin : this is the Aladin-lite sky viewer, bundled as a jupyter widget. It allows to plot catalogs and multi-order coverages (MOC)\n", "- matplotlib : an other option to see catalog points and MOCs\n", "\n", "## 2. Metadata exploration with the Virtual Observatory registry\n", "\n", "This part uses [pyvo](https://pyvo.readthedocs.io/en) to connect to the VO registry." ] }, { "cell_type": "code", "execution_count": null, "id": "95888801", "metadata": {}, "outputs": [], "source": [ "# the catalogue name in VizieR\n", "CATALOGUE = \"J/A+A/676/A18\"" ] }, { "cell_type": "markdown", "id": "26ad3c69", "metadata": {}, "source": [ "We first retrieve the catalogue information." ] }, { "cell_type": "code", "execution_count": null, "id": "6db57e6b", "metadata": {}, "outputs": [], "source": [ "# each resource in the VO has an identifier, called ivoid. For vizier catalogs,\n", "# the VO ids can be constructed like this:\n", "catalogue_ivoid = f\"ivo://CDS.VizieR/{CATALOGUE}\"\n", "# the actual query to the registry\n", "voresource = registry.search(ivoid=catalogue_ivoid)[0]" ] }, { "cell_type": "code", "execution_count": null, "id": "f3e975e3", "metadata": {}, "outputs": [], "source": [ "# We can print metadata information about the catalogue\n", "voresource.describe(verbose=True)" ] }, { "cell_type": "markdown", "id": "bd2a7ae3", "metadata": {}, "source": [ "We can also inspect in details the `resource` object and access the attributes not provided by the describe method. See for example, the first author of a resource: " ] }, { "cell_type": "code", "execution_count": null, "id": "f5a53605", "metadata": {}, "outputs": [], "source": [ "voresource.creators[0]" ] }, { "cell_type": "markdown", "id": "5a457510", "metadata": {}, "source": [ "## 3. Access the tabular data of this catalog\n", "\n", "We can have a look at the tables available in the catalogue." ] }, { "cell_type": "code", "execution_count": null, "id": "92ebe10f", "metadata": {}, "outputs": [], "source": [ "tables = voresource.get_tables()\n", "print(f\"In this catalogue, we have {len(tables)} tables.\")\n", "for table_name, table in tables.items():\n", " print(f\"{table_name}: {table.description}\")" ] }, { "cell_type": "code", "execution_count": null, "id": "81514878", "metadata": {}, "outputs": [], "source": [ "# We can also extract the tables names for later use\n", "tables_names = list(tables.keys())\n", "tables_names" ] }, { "cell_type": "markdown", "id": "eedac527", "metadata": {}, "source": [ "The actual data can then be accessed using any of the ``access_modes`` of the voresource." ] }, { "cell_type": "code", "execution_count": null, "id": "32db444e", "metadata": {}, "outputs": [], "source": [ "voresource.access_modes()" ] }, { "cell_type": "markdown", "id": "4a7dd42f", "metadata": {}, "source": [ "The web access is found by following the ``reference_url``" ] }, { "cell_type": "code", "execution_count": null, "id": "545f9bf8", "metadata": {}, "outputs": [], "source": [ "voresource.reference_url" ] }, { "cell_type": "markdown", "id": "abee6ce7", "metadata": {}, "source": [ "### 3.1 Execute a SQL/ADQL query\n", "\n", "The ``tap#aux`` in the ``access_mode`` response indicates that we can also do a SQL/ADQL query for these VizieR tables.\n", "\n", "On the first table of the catalogue, we execute an ADQL query." ] }, { "cell_type": "code", "execution_count": null, "id": "3a8b8d60", "metadata": {}, "outputs": [], "source": [ "# get the first table of the catalogue\n", "first_table_name = tables_names[0]\n", "\n", "# execute a synchronous ADQL query\n", "tap_service = voresource.get_service(\"tap\")\n", "tap_records = tap_service.search(\n", " f'select TOP 10 * from \"{first_table_name}\"',\n", ")\n", "tap_records" ] } ], "metadata": { "language_info": { "name": "python" } }, "nbformat": 4, "nbformat_minor": 5 }