updates to 103_4 nb

Author: christinawilliams

DP1/100_How_to_Use_RSP_Tools/103_Image_access_and_display/103_4_Small_Image_Cutout.ipynb

@@ -22,7 +22,7 @@
     "Data Release: DP1 <br>\n",
     "Container Size: large <br>\n",
     "LSST Science Pipelines version: r29.2.0 <br>\n",
-    "Last verified to run: 2025-11-20 <br>\n",
+    "Last verified to run: 2025-12-15 <br>\n",
     "Repository: <a href=\"https://github.com/lsst/tutorial-notebooks\">github.com/lsst/tutorial-notebooks</a> <br>"
    ]
   },
@@ -98,12 +98,13 @@
    "source": [
     "import numpy as np\n",
     "import matplotlib.pyplot as plt\n",
-    "import os\n",
     "\n",
     "import lsst.afw.display as afwDisplay\n",
+    "import lsst.afw.image as afwImage\n",
     "from lsst.afw.image import ExposureF\n",
     "from lsst.afw.fits import MemFileManager\n",
     "\n",
+    "\n",
     "from lsst.rsp.utils import get_pyvo_auth\n",
     "from lsst.rsp.service import get_siav2_service\n",
     "\n",
@@ -113,7 +114,10 @@
     "\n",
     "from astropy import units as u\n",
     "from astropy.coordinates import Angle\n",
-    "from astropy.time import Time"
+    "from astropy.time import Time\n",
+    "\n",
+    "from astropy.io import fits\n",
+    "import io\n"
    ]
   },
   {
@@ -324,7 +328,7 @@
    "id": "d945e191-7ee4-458a-bb0f-fb00cd219e30",
    "metadata": {},
    "source": [
-    "Lastly, call the Rubin Image Cutout Service. Three types of cutout services exist: `cutout-sync` which, by default, returns just the image extension of the LSST imaging; `cutout-sync-exposure`, which returns the full set of metadata and image extensions that are contained in the `ExposureF` data type; and `cutout-sync-mask` which contains just the mask extension. This section will demonstrate the use of `cutout-sync-exposure` and Section 4 below will demonstrate the other two. \n",
+    "Lastly, call the Rubin Image Cutout Service. This notebook demonstrates two types of cutout services: `cutout-sync` which, by default, returns just the image extension of the LSST imaging; `cutout-sync-exposure`, which returns the full set of metadata and image extensions that are contained in the `ExposureF` data type. This section will demonstrate the use of `cutout-sync-exposure` and Section 4 below will demonstrate the other. \n",
     "\n",
     "To use the cutout service in this example, the IVOA procedure `cutout-sync-exposure` is called using `get_adhocservice_by_id`. It is done by feeding the data link created above (called `dl_result`) to `from_resource`. Since the Rubin DP1 imaging is proprietary it is necessary to again provide the authorization for the current RSP session. Do this using the `get_pyvo_auth` function."
    ]
@@ -681,31 +685,11 @@
    "id": "99e75a7a-348e-409e-88f6-871b68a4e9dc",
    "metadata": {},
    "source": [
-    "## 4. Other cutout service data types\n",
-    "\n",
-    "As mentioned in Section 3, there are three types of cutout services: `cutout-sync-exposure` to return an `ExposureF` type image with all LSST image extensions (demonstrated above); `cutout-sync` which returns just the image extension, and and `cutout-sync-mask` which contains just the mask extension. The latter 2 will be demonstrated below.\n",
-    "\n",
-    "### 4.1 Single extension image cutouts\n",
-    "\n",
-    "Below demonstrates how to retrieve single extension images using `cutout-sync`."
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "c2c8ab4c-cd1d-4ae8-937d-b34a21035e1e",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from astropy.io import fits\n",
-    "import io\n",
+    "## 4. Single extension image cutouts\n",
     "\n",
-    "print(results[0])\n",
-    "datalink_url = results[0].access_url\n",
-    "dl_result = DatalinkResults.from_result_url(datalink_url,\n",
-    "                                            session=get_pyvo_auth())\n",
+    "As mentioned in Section 3, there are three types of cutout services: `cutout-sync-exposure` to return an `ExposureF` type image with all LSST image extensions (demonstrated above); `cutout-sync` which returns just the image extension. The latter 2 will be demonstrated below.\n",
     "\n",
-    "f\"Datalink status: {dl_result.status}. Datalink service url: {datalink_url}\"\n"
+    "First, reuse the data link `dl_result` that was defined in Section 3 to define a new cutout, this time using `cutout-sync`. Call this soda query `sq4` to differentiate from the earlier ones. Define the cutout as a square subtended by a circle of radius 0.01 degrees, as done in Section 3.\n"
    ]
   },
   {
@@ -715,169 +699,113 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "\n",
-    "sq5 = SodaQuery.from_resource(dl_result,\n",
-    "                             dl_result.get_adhocservice_by_id(\"cutout-sync\"),\n",
-    "                             session=get_pyvo_auth())\n",
+    "sq4 = SodaQuery.from_resource(dl_result,\n",
+    "                              dl_result.get_adhocservice_by_id(\"cutout-sync\"),\n",
+    "                              session=get_pyvo_auth())\n",
     "\n",
     "spherePoint = geom.SpherePoint(target_ra*geom.degrees, target_dec*geom.degrees)\n",
     "Radius = 0.01 * u.deg\n",
-    "sq5.circle = (spherePoint.getRa().asDegrees() * u.deg,\n",
-    "             spherePoint.getDec().asDegrees() * u.deg,\n",
-    "             Radius)\n",
     "\n",
-    "cutout_bytes = sq5.execute_stream().read()\n",
-    "sq5.raise_if_error()\n"
+    "sq4.circle = (spherePoint.getRa().asDegrees() * u.deg,\n",
+    "              spherePoint.getDec().asDegrees() * u.deg,\n",
+    "              Radius)\n",
+    "\n",
+    "cutout_bytes = sq4.execute_stream().read()\n",
+    "sq4.raise_if_error()\n"
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "516dbd86-d573-4d81-a017-2ebbce8fb445",
+   "cell_type": "markdown",
+   "id": "454a017b-df88-48cc-975e-cac4ff3a37b5",
    "metadata": {},
-   "outputs": [],
    "source": [
-    "mem = MemFileManager(len(cutout_bytes))\n",
-    "mem.setData(cutout_bytes, len(cutout_bytes))\n",
-    "\n"
+    "Receive the cutout into memory, as in Section 3."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "ed3f7908-a256-42f5-939f-61f38645c7ca",
+   "id": "516dbd86-d573-4d81-a017-2ebbce8fb445",
    "metadata": {},
    "outputs": [],
    "source": [
-    "data = mem.getData()   # returns `bytes`\n",
-    "\n",
-    "# this doesn't work\n",
-    "import lsst.afw.image as afwImage\n",
-    "\n",
-    "#image = afwImage.ImageF(mem)\n"
+    "mem = MemFileManager(len(cutout_bytes))\n",
+    "mem.setData(cutout_bytes, len(cutout_bytes))\n"
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "d23a0397-6500-4e36-b956-7917ed6a7173",
+   "cell_type": "markdown",
+   "id": "2ae72a88-8002-46b5-8eee-164a2c903314",
    "metadata": {},
-   "outputs": [],
    "source": [
-    "\n",
-    "#data = mem.getData()\n",
-    "hdul = fits.open(io.BytesIO(data))\n",
-    "hdul.info()\n",
-    "\n",
-    "image_hdu = hdul[1]        # IMAGE extension\n",
-    "image_data = image_hdu.data  # NumPy array\n",
-    "#image = afwImage.ImageF(image_data)\n",
-    "image = afwImage.ImageF(image_data.astype(\"float32\"))\n",
-    "print(type(image_data))   # numpy.ndarray\n",
-    "print(type(image))        # lsst.afw.image._image.ImageF\n"
+    "Use the `getData` method from the `MemFileManager` class to return and store the bytes associated with the cutout. "
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "1aa9009a-b493-41ea-bc3c-e0c79adef913",
+   "id": "ed3f7908-a256-42f5-939f-61f38645c7ca",
    "metadata": {},
    "outputs": [],
    "source": [
-    "\n",
-    "display = afwDisplay.Display()\n",
-    "display.scale('asinh', 'zscale')\n",
-    "display.image(image)\n",
-    "plt.show()"
+    "data = mem.getData()\n"
    ]
   },
   {
    "cell_type": "markdown",
-   "id": "918e8779-2939-4978-9ec4-c8a4047f04e9",
+   "id": "441a49fb-42be-4f37-853e-141419f1da14",
    "metadata": {},
    "source": [
-    "### 4.2 Single extension mask cutouts\n",
-    "\n",
-    "Below demonstrates how to retrieve the corresponding mask using `cutout-sync-mask`."
+    "Use the astropy.io fits package to access the bytes and store in an HDUList object. Then, the image extension `image_hdu`, and pixel values `image_data` (a numpy array) can be accessed similar to opening a fits file. "
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "a1213ce5-9049-43ce-8032-f1ea2db9c576",
+   "id": "d23a0397-6500-4e36-b956-7917ed6a7173",
    "metadata": {},
    "outputs": [],
    "source": [
+    "hdul = fits.open(io.BytesIO(data))\n",
+    "hdul.info()\n",
     "\n",
-    "sq5 = SodaQuery.from_resource(dl_result,\n",
-    "                             dl_result.get_adhocservice_by_id(\"cutout-sync-maskedimage\"),\n",
-    "                             session=get_pyvo_auth())\n",
-    "\n",
-    "spherePoint = geom.SpherePoint(target_ra*geom.degrees, target_dec*geom.degrees)\n",
-    "Radius = 0.01 * u.deg\n",
-    "sq5.circle = (spherePoint.getRa().asDegrees() * u.deg,\n",
-    "             spherePoint.getDec().asDegrees() * u.deg,\n",
-    "             Radius)\n",
-    "\n",
-    "cutout_bytes = sq5.execute_stream().read()\n",
-    "sq5.raise_if_error()\n"
+    "image_hdu = hdul[1]\n",
+    "image_data = image_hdu.data\n"
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "a2f5ed28-c17d-451b-969c-b7d9186eeb23",
+   "cell_type": "markdown",
+   "id": "c0eea8e5-ae86-456d-9d67-798557a4a707",
    "metadata": {},
-   "outputs": [],
    "source": [
-    "mem = MemFileManager(len(cutout_bytes))\n",
-    "mem.setData(cutout_bytes, len(cutout_bytes))\n",
-    "\n"
+    "To enable image display, first store `image_data` as an LSST `ImageF` object."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "770c6bc2-67f5-4d3f-9d3a-98cd27e28b35",
+   "id": "78e1c658-916c-4a73-8c0b-a50d281f4764",
    "metadata": {},
    "outputs": [],
    "source": [
-    "data = mem.getData()   # returns `bytes`\n",
-    "\n",
-    "# this doesn't work\n",
-    "import lsst.afw.image as afwImage\n",
-    "\n",
-    "#image = afwImage.ImageF(mem)\n"
+    "image = afwImage.ImageF(image_data.astype(\"float32\"))\n"
    ]
   },
   {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "ba884db3-cd3e-45b9-bba0-ecd98cd95358",
+   "cell_type": "markdown",
+   "id": "6a19e7cd-4096-44b9-832f-baa6b6c40482",
    "metadata": {},
-   "outputs": [],
    "source": [
-    "\n",
-    "#data = mem.getData()\n",
-    "hdul = fits.open(io.BytesIO(data))\n",
-    "hdul.info()\n",
-    "\n",
-    "image_hdu = hdul[2]        # IMAGE extension\n",
-    "image_data = image_hdu.data  # NumPy array\n",
-    "#image = afwImage.ImageF(image_data)\n",
-    "image = afwImage.ImageF(image_data)#.astype(\"float32\"))\n",
-    "print(type(image_data))   # numpy.ndarray\n",
-    "print(type(image))        # lsst.afw.image._image.ImageF\n"
+    "Display the image cutout."
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "cceab1fb-7f66-4858-b46f-d71fddb50159",
+   "id": "1aa9009a-b493-41ea-bc3c-e0c79adef913",
    "metadata": {},
    "outputs": [],
    "source": [
-    "\n",
     "display = afwDisplay.Display()\n",
     "display.scale('asinh', 'zscale')\n",
     "display.image(image)\n",
@@ -904,14 +832,6 @@
     "\n",
     "</div>\n"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "id": "6b611f9f-aaa5-4e2b-b4a5-b7acc6aecbf9",
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {