MAST Upscope Feedback, April 2026

scientist-user-testing.ipynb

{
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   "source": [
    "<div style=\"display: flex\">\n",
    "<div style=\"align: right; width: 10%; margin: 1em\">\n",
    "<img src=\"https://roman-docs.stsci.edu/files/159122808/221485096/2/1768495009201/Roman+Nexus+Identifier_final_outlined+%281%29.png\">\n",
    "</div>\n",
    "<div style=\"justify: left; margin: 1em\">\n",
    "<h1>Data exploration, access, and visualization for RRN</h1>\n",
    "<h2>Scientist User Feedback Sessions – April 2026</h2>\n",
    "with Jenn Kotler & Brett Morris\n",
    "</div>\n",
    "</div>\n",
    "\n",
    "\n",
    "*** \n",
    "\n",
    "\n",
    "### Introduction\n",
    "\n",
    "Thank you for volunteering to participate! \n",
    "\n",
    "In the cells below, we will guide you through interactive data discovery and analysis. We will use tools designed for the Roman Research Nexus, which you can access from a web browser; they also work on your local machine without the Nexus.\n",
    "\n",
    "##### Outline\n",
    "1. Query MAST using `astroquery` to find relevant observations\n",
    "2. Display query results with `mast-table`\n",
    "3. Open `mast-aladin` in a `Sidecar`\n",
    "4. Overlay observation footprints on sky surveys\n",
    "5. Download selected observations\n",
    "6. Overlay a Roman L4 source catalog on a sky survey in `mast-aladin`\n",
    "7. Display the Roman L2 image associated with the L4 catalog, inspect its data quality array\n",
    "\n",
    "Throughout the session you will be following a tutorial in a notebook. We will watch you work through the notebook and then ask some follow up questions at key points.\n",
    "\n",
    "As you work through the notebook, please **think out loud**. Please tell us if something unexpected happens, if something works well, if you think something that could be improved, or if you’re confused. **I invite you to complain!**\n",
    "\n",
    "\n",
    "\n",
    "\n",
    "<div class=\"alert alert-block alert-info\" style='background-color:#8fffdf'>\n",
    "\n",
    "<em>User questions will be in minty colored boxes.</em>\n",
    "\n",
    "<h3> Questions </h3>\n",
    "\n",
    "<ul> \n",
    "<li>What experience do you have using <strong>jdaviz</strong>, if any?</li>\n",
    "<li> What experience do you have using <strong>astroquery</strong>, if any?</li>\n",
    "<li> What experience do you have using <strong>aladin-lite</strong>, if any?</li>\n",
    "</ul>\n",
    "</div>\n",
    "\n",
    "\n",
    "<div class=\"alert alert-block alert-info\" style='background-color:#f5f242'>\n",
    "<em>Tasks for the user will be in yellow boxes.</em>\n",
    "    \n",
    "<h3> Task 1: </h3>\n",
    "<ol>\n",
    "<li> If the file browser side-panel is open on the left of this notebook, click the folder icon in the upper left of the browser to close the file browser. This will give you more space to work.</li>\n",
    "<li> Run the cell below ⬇️</li>\n",
    "</ol>\n",
    "</div>\n",
    "\n"
   ]
  },
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   "cell_type": "markdown",
   "id": "e360d4ee-3bd4-4e97-8566-d1d87e47655d",
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   "source": [
    "### mast-aladin\n",
    "\n",
    "Let's open [mast-aladin](https://github.com/spacetelescope/mast-aladin), centered on our sky area of interest. We'll open `mast-aladin` in a [Sidecar](https://github.com/jupyter-widgets/jupyterlab-sidecar), which gives us a rearrangeable tab in Jupyter Lab: "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "243e6354-e366-4b53-be91-f1a19f698789",
   "metadata": {},
   "outputs": [],
   "source": [
    "import warnings\n",
    "\n",
    "import numpy as np\n",
    "from sidecar import Sidecar\n",
    "Sidecar.close_all()\n",
    "\n",
    "import astropy.units as u\n",
    "from astropy.coordinates import SkyCoord\n",
    "from astropy.table import Table\n",
    "\n",
    "from astroquery.mast import MastMissions\n",
    "from mast_table import MastTable\n",
    "from mast_aladin import MastAladin\n",
    "import roman_datamodels.datamodels as rdd\n",
    "from jdaviz import Imviz, Rampviz\n",
    "\n",
    "# this import is specific to supporting this demo:\n",
    "from demo_utils import use_mast_test\n",
    "\n",
    "\n",
    "# sky coordinate in the region of interest\n",
    "coord = SkyCoord(ra=267.3515563, dec=-29.8847824, unit=u.degree)\n",
    "\n",
    "# initialize a sidecar. this will pop the widget\n",
    "# into its own tab:\n",
    "footprint_sidecar = Sidecar(\n",
    "    anchor='split-right', \n",
    "    title='mast-aladin'\n",
    ")\n",
    "with footprint_sidecar:\n",
    "    # use a Pan-STARRS color sky backgorund\n",
    "    survey_url = (\n",
    "        'https://alaskybis.cds.unistra.fr/2MASS/Color/'\n",
    "    )\n",
    "\n",
    "    # initialize mast-aladin: \n",
    "    mast_aladin = MastAladin(\n",
    "        survey=survey_url,\n",
    "        target=coord,\n",
    "        fov=3 * u.deg,\n",
    "        full_screen=True\n",
    "    )\n",
    "\n",
    "    # show mast-aladin in the sidecar\n",
    "    display(mast_aladin)"
   ]
  },
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   "cell_type": "markdown",
   "id": "cd055109-3e71-4ce4-b5e6-cf8de18b5d61",
   "metadata": {},
   "source": [
    "### mast-table\n",
    "\n",
    "We query [Missions Mast](https://mast.stsci.edu/search/ui/#/) via [astroquery](https://github.com/astropy/astroquery/) for (synthetic) Roman observations in the Galactic Bulge Time Domain Survey. \n",
    "\n",
    "First we'll query for all detector positions in one pass over all six GBTDS pointings."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "655a4331-0c2d-4765-95a9-0c0e96638ac4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# get access to Roman testing data:\n",
    "mast = MastMissions(mission='roman')\n",
    "use_mast_test(mast)\n",
    "\n",
    "# query for galactic bulge observations:\n",
    "gbtds_fields = {\n",
    "    'program': 340, \n",
    "    'product_type': 'l2',\n",
    "    'pass': 2\n",
    "}\n",
    "\n",
    "# submit the query to MAST:\n",
    "gbtds_pass = mast.query_criteria(**gbtds_fields)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "31b7c32d-f3e7-42ae-b94f-8149d6467e4b",
   "metadata": {},
   "outputs": [],
   "source": [
    "# show the resulting observations' footprints \n",
    "# in mast-aladin, display query results in table below:\n",
    "mast_aladin.load_table(gbtds_pass)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "b53bf542-8d71-48e3-8302-cc8dab12d8e0",
   "metadata": {},
   "source": [
    "\n",
    "\n",
    "<div class=\"alert alert-block alert-info\" style='background-color:#f5f242'>\n",
    "<h3> Task 2:</h3>\n",
    "    \n",
    "With the query results in the `mast-table` above,\n",
    "\n",
    "<ul>\n",
    "    <li>Show us how you would browse through the query results in the table.</li>\n",
    "</ul>\n",
    "\n",
    "\n",
    "With the observation footprints in `mast-aladin` to the right,\n",
    "<ul>\n",
    "    <li>Visually check if the observation footprints are dithered.</li>\n",
    "</ul>\n",
    "</div>\n",
    "\n",
    "\n",
    "<div class=\"alert alert-block alert-info\" style='background-color:#8fffdf'>\n",
    "<h3> Check-in 2: </h3>\n",
    "\n",
    "<ul> \n",
    "    <li>Please explain your understanding of the table widget.</li>\n",
    "    <li>How easy or difficult is it to browse observations in this table?</li>\n",
    "</ul>\n",
    "</div>\n"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "241e73a0-0dcb-44ab-9eff-c9ea534af0f4",
   "metadata": {},
   "source": [
    "#### Narrower search \n",
    "\n",
    "Now we'll query for observations that cover our area of interest, in any observing pass. We'll display the query results using [mast-table](https://github.com/spacetelescope/mast-table)."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "adaf6f5a-6a1a-4885-baf0-1cca5ba161e9",
   "metadata": {},
   "outputs": [],
   "source": [
    "one_detector = mast.query_criteria(\n",
    "    coordinates=coord, \n",
    "    radius=10 * u.arcsec, \n",
    "    program=340,\n",
    "    productLevel=2\n",
    ")\n",
    "\n",
    "# load observations into mast-table\n",
    "observations = MastTable(one_detector)\n",
    "observations"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f790acbd-6367-42d8-9a6a-060fd2292f4f",
   "metadata": {},
   "source": [
    "Overlay footprints from this narrower search in cyan:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "9da2eacc-133a-4f56-a0c1-e16552b728c4",
   "metadata": {},
   "outputs": [],
   "source": [
    "# draw footprints in mast-aladin\n",
    "footprint_layers = mast_aladin.add_graphic_overlay_from_stcs(\n",
    "    stc_string=one_detector['s_region'], \n",
    "    color='cyan'\n",
    ")\n",
    "\n",
    "# recenter viewer\n",
    "mast_aladin.target = coord"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "2fb43bc7-f4f3-4c2a-91cf-4cb207e3f426",
   "metadata": {},
   "source": [
    "\n",
    "<div class=\"alert alert-block alert-info\" style='background-color:#8fffdf'>\n",
    "<h3> Check-in 3: </h3>\n",
    "\n",
    "Referring to the `mast-table` above and `mast-aladin` to the right,\n",
    "<ul> \n",
    "    <li>Explain to us your understanding of what is different between the observations in the table.</li>\n",
    "</ul>\n",
    "</div>\n",
    "\n",
    "\n",
    "<div class=\"alert alert-block alert-info\" style='background-color:#f5f242'>\n",
    "<h3> Task 3: </h3>\n",
    "\n",
    "Turning back to `mast-aladin`,\n",
    "<ul> \n",
    "    <li>Rearrange the mast-aladin sidecar so that it fills the whole Jupyter Lab workspace</li>\n",
    "    <li>Place mast-aladin to the right of the notebook</li>\n",
    "</ul>\n",
    "</div>\n",
    "\n",
    "\n",
    "\n",
    "<div class=\"alert alert-block alert-info\" style='background-color:#8fffdf'>\n",
    "<h3> Check-in 4: </h3>\n",
    "\n",
    "Reflect on browsing observations in `mast-table`:\n",
    "<ul> \n",
    "    <li>How easy or difficult was it for you to complete this task?</li>\n",
    "    <li>Is there anything you would change about how this works?</li>\n",
    "</ul>\n",
    "<br />\n",
    "]\n",
    "\n",
    "Reflect on rearranging `mast-aladin` in the Jupyter Lab workspace:\n",
    "<ul> \n",
    "    <li>How easy or difficult was it for you to complete this task?</li>\n",
    "    <li>Is there anything you would change about how this works?</li>\n",
    "</ul>\n",
    "\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6a091706-43be-436a-afa6-9bf7fd3c6d8f",
   "metadata": {},
   "source": [
    "The observation we're interested in is the first one in the table, so we select it:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "849dbddc-8579-4621-875d-de27b10297ef",
   "metadata": {},
   "outputs": [],
   "source": [
    "observations.selected_rows = observations.items[0:1]"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "51256be9-96cb-4430-b0c7-802a40d09f35",
   "metadata": {},
   "source": [
    "#### Browse files available for download\n",
    "\n",
    "Now search for data products from the selected observation. Products will include: L1 (uncal), L2 (cal), and L4 (cat), among others."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "03925024-d724-41df-9905-18ea55bbe080",
   "metadata": {},
   "outputs": [],
   "source": [
    "selected_obs = observations.selected_rows_table\n",
    "product_list = mast.get_product_list(selected_obs)\n",
    "\n",
    "products = MastTable(\n",
    "    table=product_list,\n",
    "    unique_column='product_key'\n",
    ")\n",
    "\n",
    "products"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "6aa26051-98cc-4d92-9f54-90d5f40f3d6d",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\" style='background-color:#f5f242'>\n",
    "<h3> Task 4: </h3>\n",
    "\n",
    "In the product table above, \n",
    "<ul> \n",
    "    <li>Select one L1 \"_uncal.asdf\" ramp file</li>\n",
    "    <li>Select one L2 \"_cal.asdf\" image file</li>\n",
    "    <li>Select one L4 \"_cat.parquet\" catalog file</li>\n",
    "</ul>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "bee728aa-8331-4e9a-8e2c-89ce94a16837",
   "metadata": {},
   "source": [
    "##### Download\n",
    "\n",
    "We select an L1 ramp, an L2 cal, and a L4 catalog file for download, then download them:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "e6c5ebfb-ca83-4493-a0c3-c631e24a23a5",
   "metadata": {},
   "outputs": [],
   "source": [
    "# select rows by index:\n",
    "select_rows = [1, 2, 3]\n",
    "products.selected_rows = [products.items[i] for i in select_rows]\n",
    "downloaded_products = mast.download_products(products.selected_rows_table)\n",
    "\n",
    "# get access to the paths for each product\n",
    "level2_path, catalog_path, level1_path = sorted(downloaded_products['Local Path'])"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "3e710060-d7c1-4e6e-8e98-812e4c2ea2cc",
   "metadata": {},
   "source": [
    "### Add the source catalog to mast-aladin\n",
    "\n",
    "Add the source catalog to mast-aladin:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "af35309a-3d75-4f4d-806c-b118aa1815d4",
   "metadata": {},
   "outputs": [],
   "source": [
    "with warnings.catch_warnings():\n",
    "    # suppress a units warning:\n",
    "    warnings.simplefilter('ignore')\n",
    "    \n",
    "    # load the Roman catalog `parquet` file with astropy:\n",
    "    source_catalog = Table.read(catalog_path)\n",
    "\n",
    "    # add the sources to mast-aladin\n",
    "    catalog_layer = mast_aladin.add_table(\n",
    "        source_catalog, \n",
    "        shape='circle', \n",
    "        color='lime', \n",
    "        sourceSize=10,\n",
    "        name='catalog'\n",
    "    )"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "445e0162-993f-4b63-87c1-59a44875d6f3",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\" style='background-color:#f5f242'>\n",
    "<h3> Task 5:</h3>\n",
    "    \n",
    "With `mast-aladin` in a sidecar:\n",
    "<ul>\n",
    "    <li>Explore the region of interest on the sky</li>\n",
    "    <li>Select a source</li>\n",
    "    <li>Find the \"ra_centroid\" for the selected source</li>\n",
    "</ul>\n",
    "</div>\n",
    "\n",
    "\n",
    "<div class=\"alert alert-block alert-info\" style='background-color:#8fffdf'>\n",
    "<h3> Check-in 5: </h3>\n",
    "<ul> \n",
    "    <li>How easy or difficult was it for you to select a source?</li>\n",
    "    <li>Is there anything you would change about how this works?</li>\n",
    "</ul>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "23cc7b1c-43ec-4110-bfe5-eeb6fe1ec58d",
   "metadata": {},
   "source": [
    "### Launch jdaviz\n",
    "\n",
    "Launch [jdaviz](https://github.com/spacetelescope/jdaviz/) (specifically [Imviz](https://jdaviz.readthedocs.io/en/stable/imviz/index.html)) in a sidecar below `mast-aladin`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "ddbe8a86-4842-4913-aac4-37d9377e8c72",
   "metadata": {},
   "outputs": [],
   "source": [
    "# initialize imviz\n",
    "imviz = Imviz()\n",
    "\n",
    "# open it in a sidecar:\n",
    "imviz_sidecar = Sidecar(\n",
    "    title='jdaviz',\n",
    "\n",
    "    # place the jdaviz sidecar below \n",
    "    # the mast-aladin sidecar:\n",
    "    ref=footprint_sidecar,\n",
    "    anchor='split-bottom', \n",
    ")\n",
    "\n",
    "with imviz_sidecar:\n",
    "    display(imviz.app)"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "7469555d-667a-4a19-ab08-c93f28a5328d",
   "metadata": {},
   "source": [
    "### L2 cal files in jdaviz\n",
    "\n",
    "Load the L2 and L4 files into `jdaviz`, adjust the \"[Plot Options](https://jdaviz.readthedocs.io/en/stable/imviz/displayimages.html#display-settings)\" to display with a user-defined colormap."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "f23cb57e-4ac1-4429-bb55-a09adf92bdf3",
   "metadata": {},
   "outputs": [],
   "source": [
    "# use `roman_datamodels to open the L2 file:\n",
    "roman_image_datamodel = rdd.open(level2_path)\n",
    "\n",
    "# load the L2 file into imviz:\n",
    "imviz.load(\n",
    "    roman_image_datamodel, \n",
    "    format='Image', \n",
    "\n",
    "    # load the image data extension, and\n",
    "    # the data quality extension:\n",
    "    extension=['data', 'dq'], \n",
    ")\n",
    "\n",
    "# adjust the colormap of the image\n",
    "plot_options = imviz.plugins['Plot Options']\n",
    "plot_options.layer = imviz.app.data_collection[0].label\n",
    "plot_options.stretch_function = 'Arcsinh'\n",
    "plot_options.stretch_vmin = 0.5\n",
    "plot_options.stretch_vmax = 3.3\n",
    "plot_options.image_colormap = 'Gray'\n",
    "\n",
    "# load the source catalog into imviz:\n",
    "imviz.load(source_catalog, format='Catalog')\n",
    "\n",
    "# adjust the marker style for the catalog:\n",
    "plot_options.layer = 'Catalog'\n",
    "plot_options.marker_size_scale = 10\n",
    "plot_options.marker_size = 10\n",
    "plot_options.marker_fill = False"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "1588860e-2ed5-4770-8d83-beb9e26fbc08",
   "metadata": {},
   "source": [
    "<div class=\"alert alert-block alert-info\" style='background-color:#f5f242'>\n",
    "<h3> Task 6: </h3>\n",
    "\n",
    "With the image loaded into `jdaviz`:\n",
    "* Move the `mast-aladin` sidecar to the top-right of your Jupyter Lab workspace, and move the `jdaviz` sidecar to the bottom-right.\n",
    "</ul>\n",
    "</div>\n",
    "\n",
    "\n",
    "<div class=\"alert alert-block alert-info\" style='background-color:#8fffdf'>\n",
    "<h3> Check-in 6: </h3>\n",
    "\n",
    "You can now see one Jupyter notebook, one mast-aladin app, and one jdaviz app on your screen. \n",
    "\n",
    "<ul>\n",
    "<li>How do you prefer to arrange them?</li>\n",
    "<li>How easy or difficult was it for you to rearrange the jupyterlab tabs?</li>\n",
    "<li>Can you see yourself creating layouts of sidecars when doing science?</li>\n",
    "    <ul><li>Why or why not?</li></ul>\n",
    "<li><em>Bonus</em>: open the Data Quality plugin, determine which DQ pixel color maps onto the \"jump detected\" flag</li>\n",
    "</ul>\n",
    "</div>"
   ]
  },
  {
   "cell_type": "markdown",
   "id": "f8f3011b-4d0d-4641-9047-63bf071ab766",
   "metadata": {},
   "source": [
    "### L1 ramp files in jdaviz\n",
    "\n",
    "Bonus: inspect the L1 ramp file in jdaviz (specifically [Rampviz](https://jdaviz.readthedocs.io/en/stable/rampviz/index.html)):"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "id": "d8ab5376-8689-4905-805b-50647ed46625",
   "metadata": {},
   "outputs": [],
   "source": [
    "rampviz = Rampviz()\n",
    "rampviz.load(level1_path, format='Ramp')\n",
    "\n",
    "ramp_sidecar = Sidecar(anchor='tab-after', title='rampviz')\n",
    "with ramp_sidecar:\n",
    "    display(rampviz.app)\n",
    "\n",
    "plot_options = rampviz.plugins['Plot Options']\n",
    "plot_options.viewer = 'group-viewer'\n",
    "plot_options.stretch_function = 'Arcsinh'\n",
    "plot_options.stretch_vmin = 5000\n",
    "plot_options.stretch_vmax = 6000\n",
    "plot_options.image_colormap = 'Magma'\n",
    "\n",
    "plot_options.viewer = 'diff-viewer'\n",
    "plot_options.stretch_function = 'Arcsinh'\n",
    "plot_options.stretch_vmin = 0\n",
    "plot_options.stretch_vmax = 100\n",
    "plot_options.image_colormap = 'Magma'"
   ]
  },
  {
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    "<div class=\"alert alert-block alert-info\" style='background-color:#f5f242'>\n",
    "<h3> (Bonus) Task 7: </h3>\n",
    "\n",
    "In rampviz,\n",
    "<ul> \n",
    "    <li>Zoom and pan around the ramp cube.</li>\n",
    "    <li><em>Bonus</em>: identify a pixel flagged with a apparent cosmic ray hit</li>\n",
    "</ul>\n",
    "</div>\n"
   ]
  },
  {
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   "id": "ba063a1b-2196-4858-8d12-c4afe389b564",
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    "\n",
    "\n",
    "<details>\n",
    "    <summary>installation setup details</summary>\n",
    "\n",
    "    conda install -c conda-forge nodejs\n",
    "    pip install jupyterlab\n",
    "    pip install -U asdf_standard asdf_coordinates_schemas asdf-astropy gwcs asdf_coordinates_schemas roman_datamodels==0.30.0\n",
    "    pip install -U git+https://github.com/spacetelescope/mast-aladin.git@61afc5e08902913dfd2407254b9b956a7009ea80\n",
    "    pip install -U git+https://github.com/bmorris3/jdaviz.git@291afd9bbbc2de1f36d44a5095d5483fb04c832b\n",
    "    pip install -U git+https://github.com/spacetelescope/mast-table.git@7c4c3e17e10685c56ae29678a11dec03ff3feca4\n",
    "\n",
    "\n",
    "</details>"
   ]
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   "id": "5b3392a3-b0e4-47ea-9f8a-577a3f96f85d",
   "metadata": {},
   "outputs": [],
   "source": []
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