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
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
Data Inventory	Explore the available datasets in the LSST Science Platform shared folders.	ipynb, rendered	Phil Marshall

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
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
“With Globular” LSST 2018 Tutorial	General purpose tutorial including interactive Firefly visualization.	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
Re-run HSC	End-to-end processing of the ci_hsc test dataset using the DM Stack.	ipynb, rendered, bash script	Justin Myles
BrighterFatterCorrection.ipynb	Analysis of Beam Simulator Images and 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
LowSurfaceBrightness.ipynb	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

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	Introduction to the SCARLET deblender, how to configure and run it.	ipynb, rendered	Fred Moolekamp
Deblending in DRP	Where and how the deblending happens, in the DRP pipeline.	ipynb, rendered	Fred Moolekamp

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.ipynb	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