bmorris3 / 2014_fall_astr599

Content for my Astronomy 599 / Applied Math 500 Course: Intro to scientific computing in Python

Hi there, I'm Brett 👋

Roles

• 👨🏻‍💻 Senior Software Engineer at the Space Telescope Science Institute, supporting JWST and Roman
• 🔭 Astronomer with interests in exoplanets, stellar activity, and statistical inference
• 🪐 Maintainer, Contributor, and Workshops Coordinator for astropy
• ⏰ Maintainer of the astropy-affiliated package for observation planning astroplan

Read more

• 🕸 http://brettmorr.is/
• 🎓 Curriculum Vitae
• 🆔 ORCID
• 📝 First author papers on NASA ADS

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Software by topic

General astronomy utilities

• astroplan (ApJ paper): Observation planning package for astronomers
• tynt: Light-weight astronomical color filter curves
• expecto: Retrieve PHOENIX model stellar spectra via FTP
• arcesetc (JOSS paper): Exposure time calculator for the ARC Echelle Spectrograph (ARCES) on the Apache Point Observatory 3.5 m Telescope
• aesop (JOSS paper): Echelle Spectroscopic Observation Pipeline for the ARC 3.5 m Telescope at APO

Exoplanet photometry

• kelp (Nature Astronomy paper, A&A paper): Photometric phase curves of exoplanets
• linea (A&A paper): Linear light curve detrending for CHEOPS
• robin (AJ paper): Robust exoplanet radii from ingress/egress durations
• stash (MNRAS paper, presentation): Simulate solar transits with observations from SDO HMI

Stellar oscillations, granulation, and magnetic activity packages

• fleck (JOSS paper, ApJ paper, presentation): Fast approximate light curves for starspot rotational modulation
• gadfly: Simulate stellar oscillations and granulation with Gaussian processes
• hipparchos (AJ paper): Cross-correlation functions for high resolution spectroscopy

STScI projects w/ significant contributions

• jdaviz (presentation): JWST astronomical data analysis tools in the Jupyter platform
• romancal: Python library to process science observations from the Nancy Grace Roman Space Telescope
• lcviz: Light curve visualization and analysis tool

Other

• shampoo (presentation): Digital holographic microscopy pipeline for astrobiology and beyond

Stats tutorials

Jupyter notebook tutorials

• Introduction to JAX+numpyro for physical scientists
• Pareto smoothed importance sampling leave-one-out cross validation (presentation)
• How to compute leave-one-out cross validation stats for a numpyro (jax) model with a Gaussian process from celerite2
• Sample posteriors with SVI in numpyro

Pedagogical Jupyter notebook tutorials with interactive features

• Interactive MCMC demo
• Interactive Gaussian process demo
• Interactive Approximate Bayesian Computation demo

In-person workshops

• Python for Astronomy Tutorial at Exeter (2019)
• Intro to Astropy Affiliated Packages at .Astronomy 9
• Linear model selection with PyMC3