Tutorial Notebooks¶

Getting Started¶

Wondering how you can get started learning about the LSST software stack, by writing tutorial notebooks and contributing them to the Stack Club’s growing library? Need help getting going on the LSST Science Platform (LSP) JupyterLab? See the index table below for links to various resources, including: notes on the LSP, notebooks to walk you through the Stack Club workflow, and some help on how to explore the Stack code. Click on the “rendered” links to see the notebooks with their outputs.

Notebook	Short description	Links	Owner
Notes on Getting Started	Some brief notes on the LSST Science Platform JupyterLab set-up.	markdown	Phil Marshall
Hello World	Read about the Stack Club git/GitHub workflow, and make your first contribution to a notebook.	ipynb, rendered	Phil Marshall
Templates	A folder containing a template notebook, and a template folder README file, to help you get your project started.	link	Phil Marshall
Finding Docs	Locate the documentation for Stack code objects, including using the `stackclub` library `where_is` utility function.	ipynb, rendered	Phil Marshall
Import Tricks	Learn how to use some `stackclub` library utilities for importing notebooks and remote modules.	ipynb, rendered	Phil Marshall

Basics¶

This set of tutorial notebooks will help you explore the basic properties of the LSST software Stack data structures, classes and functions. The table contains links to the notebook code, and also to auto-rendered views of the notebooks with their outputs.

Notebook	Short description	Links	Owner
Gen-3 Butler Tutorial	Demonstrates basic data access and manipulations using the Gen-3 Butler	ipynb, rendered	Alex Drlica-Wagner
Calexp Guided Tour	Shows how to read an exposure object from a data repository, and how to access and display various parts.	ipynb, rendered	David Shupe
AFW Table Guided Tour	Shows how to read and write catalogs using the AFW Table class, and how to access and display various parts.	ipynb, rendered	Imran Hasan

Visualization¶

See the table below for a set of tutorial notebooks (some provided by the Project) demonstrating visualization technologies available in the LSST Science Platform notebook aspect.

Notebook	Short description	Links	Owner
Visualizing Images with AFW Display	How to access the lsst.afw.display routines, and use the LSST data Butler to access processed image data and inspect it visually.	ipynb, rendered	Brant Robertson
Firefly Visualization Demo	Introduction to the Firefly interactive plotter and image viewer.	ipynb, video	Simon Krughoff
Interactive Visualization with Bokeh, HoloViews, and Datashader	Examples of interactive visualization with the Boken, HoloViews, and Datashader plotting packages available in PyViz suite of data analysis python modules; brushing and linking with large datasets	ipynb, rendered	Keith Bechtol
Visualizing the LSST Camera Focal Plane	Create a labeled visualization of the LSST Camera including amps, detectors, rafts integrated into the full focal plane.	ipynb, rendered	Alex Drlica-Wagner
Globular Cluster Intro	General purpose tutorial including interactive Firefly visualization of a globular cluster from LSST 2018.	ipynb	Jim Bosch

Image Processing¶

Here, we explore the image processing routines in the LSST science pipelines. See the index table below for links to the notebook code, and an auto-rendered view of the notebook with outputs.

Notebook	Short description	Links	Owner
Brighter-Fatter Correction	Analysis of beam simulator images and the brighter-fatter correction.	ipynb, rendered	Andrew Bradshaw

Source Detection¶

While source detection in the LSST science pipelines is carried out (first) during the image processing step, there are subsequent detection phases - and, moreover, we are interested in how sources are detected (and how their measured properties depends on that process). See the index table below for links to tutorial notebooks exploring this.

Notebook	Short description	Links	Owner
Low Surface Brightness	Run source detection, deblending, and measurement tasks; subtract bright sources from an image; convolve image and detect low-surface brightness sources.	ipynb, rendered	Alex Drlica-Wagner
Footprints	Investigate the concept of a footprint: the region of an image used for detecting and measuring source properties.	ipynb, rendered	Imran Hasan

Deblending¶

This folder contains a set of tutorial notebooks exploring the deblending of LSST objects. See the index table below for links to the notebook code, and an auto-rendered view of the notebook with outputs.

Notebook	Short description	Links	Owner
Scarlet Tutorial	Standalone introduction to the scarlet deblender, including how to configure and run it.	ipynb, rendered	Fred Moolekamp
Deblending in the Stack	Where and how deblending happens in the LSST Science Pipelines.	ipynb, rendered	Fred Moolekamp

Measurement¶

This folder contains a set of tutorial notebooks exploring the Object measurement routines in the LSST science pipelines. See the index table below for links to the notebook code, and an auto-rendered view of the notebook with outputs.

Notebook	Short description	Links	Owner
Asteroid Light Curve	Find an asteroid from 2015 HiTS data, create postage stamps and generate a light curve. This notebook was used in the Summer 2020 Stack Club Course Session 06.	ipynb, rendered	Bryce Kalmbach
Undersampled Moments	Examine biases introduced by undersampled moments.	ipynb, rendered	Andrew Bradshaw
Resolved Dwarf Galaxy	Explore resolved sources around a nearby dwarf galaxy	ipynb, rendered	Jeff Carlin

Validation¶

This set of tutorial notebooks explores the validation packages accompanying the LSST software Stack, and also contains some stand-alone notebooks useful for examining various aspects of data quality.

Notebook	Short description	Links	Owner
Image Quality Demo	Examples of image shape measurements in the Stack including PSF size and ellipticity, shape measurements with and without PSF corrections; visualizing image quality statistics aggregated with pandas; examining PSF model ellipticity residuals	ipynb, rendered	Keith Bechtol
Verify Quality Demo	Examples use of LSST verify package	ipynb, rendered	Keith Bechtol