updated 301_1

Author: shenmingfu

DP1/300_Science_Demos/301_Field_explorations/301_1_47Tuc_Globular_Cluster.ipynb

@@ -78,7 +78,7 @@
    "source": [
     "Import `numpy`, a fundamental package for scientific computing with arrays in Python (<a href=\"https://numpy.org\">numpy.org</a>), and `matplotlib`, a comprehensive library for data visualization (<a href=\"https://matplotlib.org/\">matplotlib.org</a>; <a href=\"https://matplotlib.org/stable/gallery/index.html\">matplotlib gallery</a>), including custom shapes (`Polygon`) and lines (`mlines`). `itertools` supports efficient iteration and combinatorics.\n",
     "\n",
-    "From the `lsst` package, import modules for accessing the Table Access Protocol (TAP) service, for retrieving datasets from the butler, and for image displaying from the LSST Science Pipelines (<a href=\"https://pipelines.lsst.io/\">pipelines.lsst.io</a>). Additional modules support spherical geometry (`sphgeom`), 2D geometry (`geom`), and standardized multiband plotting (`lsst.utils.plotting`) for LSST data analysis and visualization."
+    "From the `lsst` package, import modules for accessing the Table Access Protocol (TAP) service, for retrieving datasets from the butler, and for image displaying from the LSST Science Pipelines (<a href=\"https://pipelines.lsst.io/\">pipelines.lsst.io</a>). Additional modules support spherical geometry (`sphgeom`), and standardized multiband plotting (`lsst.utils.plotting`) for LSST data analysis and visualization."
    ]
   },
   {
@@ -98,7 +98,6 @@
     "from lsst.daf.butler import Butler\n",
     "import lsst.afw.display as afw_display\n",
     "import lsst.sphgeom as sphgeom\n",
-    "import lsst.geom as geom\n",
     "from lsst.utils.plotting import (\n",
     "    get_multiband_plot_colors,\n",
     "    get_multiband_plot_symbols,\n",
@@ -444,14 +443,58 @@
     "}"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "858dcd92-c913-4b31-ae82-ff8dd96c5e92",
+   "metadata": {},
+   "source": [
+    "Use TAP to find vertices of each patch covering the field in the `dp1.coaddPatches` table."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "127a6e54-d56b-4a1e-b6a6-a72796a3b3f0",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "query = \"SELECT lsst_patch, lsst_tract, s_ra, s_dec, s_region \" \\\n",
+    "        \"FROM dp1.CoaddPatches \" \\\n",
+    "        \"WHERE CONTAINS(POINT('ICRS', s_ra, s_dec), \" \\\n",
+    "        \"CIRCLE('ICRS', {}, {}, {})) = 1 \".format(ra_cen, dec_cen, radius)\n",
+    "job = service.submit_job(query)\n",
+    "job.run()\n",
+    "job.wait(phases=['COMPLETED', 'ERROR'])\n",
+    "print('Job phase is', job.phase)\n",
+    "if job.phase == 'ERROR':\n",
+    "    job.raise_if_error()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "id": "00f38067-8ee3-422c-b774-63ac8b83b60f",
+   "metadata": {},
+   "source": [
+    "Fetch the results as an `astropy` table."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "de109d47-9c87-4c92-98af-7f83bca9c0c8",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "assert job.phase == 'COMPLETED'\n",
+    "coadd_patches = job.fetch_result().to_table()"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "76ef7e00-f9e5-425e-9c74-26b4697107c1",
    "metadata": {},
    "source": [
-    "The `coadd_datasetrefs` returned from the butler include region information for each dataset, stored as a `ConvexPolygon3D` with four vertices defining the sky footprint of each overlapping tract and patch.\n",
-    "\n",
-    "Convert these vertices to 2D sky coordinates (RA, Dec) using `geom.SpherePoint`, and use `matplotlib.patches.Polygon` along with `ax.add_patch()` to draw each patch outline. Each tract is plotted with a distinct color and linestyle for visual clarity."
+    "Use `matplotlib.patches.Polygon` along with `ax.add_patch()` to draw each patch outline. Each tract is plotted with a distinct color and linestyle for visual clarity."
    ]
   },
   {
@@ -466,17 +509,23 @@
     "mesh = ax.pcolormesh(x, y, values_rmaglim, cmap='Greys_r', shading='auto')\n",
     "fig.colorbar(mesh, ax=ax, label=\"r-band limiting magnitude (mag)\")\n",
     "\n",
-    "for rec in coadd_datasetrefs:\n",
-    "    vertices = rec.dataId.patch.region.getVertices()\n",
-    "    vertices_deg = []\n",
-    "    for vertex in vertices:\n",
-    "        vertices_deg.append([geom.SpherePoint(vertex).getRa().asDegrees(),\n",
-    "                             geom.SpherePoint(vertex).getDec().asDegrees()])\n",
-    "    polygon = Polygon(vertices_deg, closed=True, facecolor='None',\n",
-    "                      edgecolor=style_dict[rec.dataId['tract']]['color'],\n",
-    "                      linestyle=style_dict[rec.dataId['tract']]['linestyle'],\n",
-    "                      linewidth=2)\n",
-    "    ax.add_patch(polygon)\n",
+    "tracts = set(coadd_patches['lsst_tract'])\n",
+    "\n",
+    "for tract in tracts:\n",
+    "    s_regions = coadd_patches[coadd_patches['lsst_tract'] == tract]['s_region']\n",
+    "\n",
+    "    for s_region in s_regions:\n",
+    "        coordinates = np.array(s_region.split()[2:], dtype=float)\n",
+    "        ra = coordinates[0::2]\n",
+    "        ra = (ra + 180) % 360 - 180\n",
+    "        dec = coordinates[1::2]\n",
+    "        vertices_deg = np.vstack([ra, dec]).T\n",
+    "\n",
+    "        polygon = Polygon(vertices_deg, closed=True, facecolor='None',\n",
+    "                          edgecolor=style_dict[tract]['color'],\n",
+    "                          linestyle=style_dict[tract]['linestyle'],\n",
+    "                          linewidth=2)\n",
+    "        ax.add_patch(polygon)\n",
     "\n",
     "ax.set_xlim(ra_max, ra_min)\n",
     "ax.set_ylim(dec_min, dec_max)\n",
@@ -526,7 +575,8 @@
     "del coadd_datasetrefs\n",
     "del hspmap_rmaglim, hspmap_rexptime\n",
     "del x, y, values_rmaglim, values_rexptime\n",
-    "del style_dict"
+    "del style_dict\n",
+    "del tracts, s_regions, coordinates, ra, dec"
    ]
   },
   {
@@ -1218,7 +1268,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "b2961b68-461c-42b8-bc67-e17a6d63f60f",
+   "id": "d7a90cd6-86c2-4944-b0ba-6e02dbdb9bd5",
    "metadata": {},
    "outputs": [],
    "source": []