From 8e46fd779aef00932012db304fbd2a92ab9dca64 Mon Sep 17 00:00:00 2001 From: MARCHAND MANON Date: Thu, 21 Dec 2023 16:42:56 +0100 Subject: [PATCH] switch to DES survey --- ...intro-to-python-vizier-and-ipyaladin.ipynb | 131 +++++++++--------- 1 file changed, 68 insertions(+), 63 deletions(-) diff --git a/content/01-intro-to-python-vizier-and-ipyaladin.ipynb b/content/01-intro-to-python-vizier-and-ipyaladin.ipynb index 9ba047d..663bf26 100644 --- a/content/01-intro-to-python-vizier-and-ipyaladin.ipynb +++ b/content/01-intro-to-python-vizier-and-ipyaladin.ipynb @@ -1,11 +1,10 @@ { "cells": [ { - "attachments": {}, "cell_type": "markdown", "metadata": {}, "source": [ - "# Introduction to ipyaladin" + "The first cells here are required to make the notebooks work without any installation in a browser. A normal notebook running on your personal machine would start later." ] }, { @@ -25,35 +24,57 @@ "outputs": [], "source": [ "import micropip, http.client, pyodide_http\n", - "await micropip.install([\"ssl\",\"https://files.pythonhosted.org/packages/c3/c8/d74794dff5c6802994d3dfe506d691d9e0ff3e6b2f34df577899685b2617/astroquery-0.4.7.dev9008-py3-none-any.whl\"])\n", + "await micropip.install([\"ssl\",\"https://files.pythonhosted.org/packages/c3/c8/d74794dff5c6802994d3dfe506d691d9e0ff3e6b2f34df577899685b2617/astroquery-0.4.7.dev9008-py3-none-any.whl\",\n", + " \"https://rawcdn.githack.com/cds-astro/jupyterlite/88f05119a3c0f6c37c0c5475666d4bd9e0bd8a69/content/pyodide/wheels/cdshealpix-0.6.5-cp311-cp311-emscripten_3_1_45_wasm32.whl\",\n", + " \"https://rawcdn.githack.com/cds-astro/jupyterlite/88f05119a3c0f6c37c0c5475666d4bd9e0bd8a69/content/pyodide/wheels/mocpy-0.13.1-cp311-cp311-emscripten_3_1_45_wasm32.whl\"])\n", "pyodide_http.patch_all()\n", "from importlib import reload\n", - "reload(http.client)" + "reload(http.client);" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "Here is the true beginning of the story.\n", + "\n", + "# Introduction to ipyaladin\n", + "(and VizieR and MOCs)" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 12, "metadata": {}, "outputs": [], "source": [ "from ipyaladin import Aladin\n", "from sidecar import Sidecar\n", - "from astroquery.vizier import Vizier" + "from astroquery.vizier import Vizier\n", + "from mocpy import MOC" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 5, "metadata": {}, "outputs": [], "source": [ "sidecar = Sidecar(title='aladin')\n", - "aladin = Aladin()\n", + "aladin = Aladin(fov=200, target='galactic center', height=1000)\n", "with sidecar:\n", " display(aladin)" ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "aladin.target = \"M51\"" + ] + }, { "attachments": {}, "cell_type": "markdown", @@ -64,11 +85,20 @@ }, { "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "list_catalogs = Vizier.find_catalogs([\"DESI\", \"legacy\"])\n", + "execution_count": 15, + "metadata": {}, + "outputs": [ + { + "name": "stdout", + "output_type": "stream", + "text": [ + "II/371 The Dark Energy Survey (DES): Data Release 2 (Abbott+, 2021)\n", + "J/ApJS/264/9 Southern phot. quasars from DES DR2 & NIR surveys (Yang+, 2023)\n" + ] + } + ], + "source": [ + "list_catalogs = Vizier.find_catalogs([\"Dark Energy Survey\", \"Data Release 2\"])\n", "[print(catalog, description.description) for catalog, description in list_catalogs.items()];" ] }, @@ -76,16 +106,16 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "The identifier is `VII/192`" + "The identifier is `II/371`" ] }, { "cell_type": "code", - "execution_count": null, + "execution_count": 10, "metadata": {}, "outputs": [], "source": [ - "catalog = \"VII/292\"" + "catalog = \"II/371\"" ] }, { @@ -95,16 +125,33 @@ "## 2. A glimpse at its coverage" ] }, + { + "cell_type": "code", + "execution_count": 14, + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": "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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + } + ], + "source": [ + "catalog_coverage = MOC.from_fits(f\"https://cdsarc.cds.unistra.fr/viz-bin/moc/{catalog}\")" + ] + }, { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], "source": [ - "catalogue_coverage = MOC.from_fits(\n", - " f\"https://cdsarc.cds.unistra.fr/viz-bin/moc/{CATALOGUE}\",\n", - ")\n", - "catalogue_coverage" + "aladin.add_moc_from_dict()" ] }, { @@ -126,20 +173,6 @@ "outputs": [], "source": [] }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "# here, let's take all columns and remove the upper limit on the number of rows\n", - "# we comment the line about how to do the query in real python\n", - "# table_2Mass = Vizier(columns=[\"**\"], row_limit=-1).query_region(\"08:29:58, 1:30:10\", 10 * u.arcmin, catalog=\"II/246\")\n", - "# and get it from the file system\n", - "table_2Mass = parse_single_table(\"data/2MASS_PSC.vot\").to_table()\n", - "table_2Mass" - ] - }, { "attachments": {}, "cell_type": "markdown", @@ -149,34 +182,6 @@ "\n", "We load the widget around the desired position first. The following cell adds the table to the view." ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "aladin = Aladin(fov=2, target=\"08:29:58, 1:30:10\")\n", - "aladin" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "aladin.add_table(table_2Mass)" - ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [ - "aladin.height=800" - ] } ], "metadata": { @@ -195,7 +200,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.9" + "version": "3.10.11" }, "orig_nbformat": 4, "vscode": {