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08b_Interactive_Catalog_Visualization.ipynb

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"\n",
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"# LSST imports\n",
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"from lsst.daf.butler import Butler\n",
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"from lsst.rsp import get_tap_service, retrieve_query\n",
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"from rubin_jupyter_utils.lab.notebook import get_tap_service, retrieve_query\n",
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"\n",
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"# Bokeh and Holoviews for visualization\n",
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"import bokeh\n",
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"cell_type": "markdown",
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"metadata": {},
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"source": [
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"Now we will plot a spatial distribution on the sky of all the data and link it to a two-dimensional histogram of the data in the box selection."
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"#### 5.3 Linked plots with interactive selection\n",
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"\n",
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"Now we will plot a spatial distribution on the sky of all the data (in the left-hand plot below), and link it to a two-dimensional histogram of the data (right-hand plot below). Use a box selection in the spatial distribution to change which data are included in the histogram."
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README.md

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| 05. Intro to Source Detection | Use the LSST Science Pipelines tasks for image characterization, source detection, deblending, measurement, and to interact with a source footprint. |
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| 06. Comparing Object and Truth Table | Retrieve and merge data from the DC2 Object and Truth-Match tables, and compare simulated and measured properties. |
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| 07. *(time-domain tutorial)* | TBD |
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| 08. *(data visualization)* | TBD |
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| 08a. Interactive Image Visualization | Use Holoviews to display an image and overlay detected sources. Use DynamicMap to interact with image data. |
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| 08b. Interactive Catalog Visualization | Use Holoviews and Bokeh to display and interact with catalog data. Use Datashader to visualize very large datasets interactively. |
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| 09. Single Star LC with Butler | Demonstrate limits of building light curves during DP0.1: use the Butler to retrieve all PVI sources within a small radius of a given sky coordinate. |
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These tutorials will only work on the Rubin Science Platform deployed at the Interim Data Facility for Data Preview 0.

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