Legacy Tutorial

Presentations, notebooks , etc.

May 2020 Update:

  • The Tutorial material (notebooks and data) is now in a Github Repo which you can clone or download.

  • All paths are relative in that folder to simplify things, run the notebooks on your local machine immediately

  • All notebooks are coded in Jupyter Python and require rather standard packages except for the starshade image analysis demo script (SS_Photometry_Tutorial.m) written in MatLab

  • The hlc_VIP_demo.ipynb - Demo application of the VIP high-contrast image analysis package - is more difficult to get to work, you may want to start with a fresh environment.

  • A more detailed description on how to use this repo is available in the README.

Introduction to Participants

Margaret Turnbull (SIT PI) and Julien Girard (DC Coordinator) welcome participants.

Video 00:00 - 11:03

General Presentation

Presented by Julien Girard

What the 2019 Data Challenge is about, its aims, what we hope to learn from running it. PDF of the slides

Video with questions (00:11:00 - 1:07:00)

NeilZ_flatiron_cgi_day1_intro.pdf

Intro to CGI Simulations

Presented by Neil Zimmerman

HLC OS6 Simulations presented by Neil Zimmerman. PDF of the slides

Video with questions (02:11:50 - 2:23:00)

HLC Data Tour

Presented by Neil Zimmerman

Download the Jupyter python notebook (hlc_data_tour.ipynb) or simply view it on nbviewer

Video with questions (02:23:30 - 3:05:00)

Parallax & Proper Motion

Presented by Neil Zimmerman

Download the Jupyter python notebook or simply view it on nbviewer

Video with questions (03:05:35 - 4:54:30)

Orbital fitting with orbitize!

Presented by Junellie Gonzalez Quiles

orbitize!/OFTI

OFTI (Orbits For The Impatient) is an orbit-generating algorithm designed specifically to handle data covering short fractions of long-period exoplanets (Blunt et al. 2017). Here we go through steps of using OFTI within orbitize!

Download the Jupyter python notebook or simply view it on nbviewer

orbital parameters

Obtaining orbital solutions using orbitize!



Download the Jupyter python notebook or simply view it on nbviewer

plotting orbits

Code to define the orbitize! coordinate system and help you visualize orbits



Download the Jupyter python notebook or simply view it on nbviewer


RadVel to analyze precursor RV data

Presented by Neil Zimmerman

RadVel is a Python package for modeling and fitting radial velocity time series data.

Download the Jupyter python notebook or simply view it on nbviewer

Video with questions (02:25:28 - 2:57:45)

SISTER_DataChallenge_Official.pdf

Star Shade Simulations & Calibrations

Presented (remotely) by Sergi Hildebrandt

New! HLC Quick-Look Photometry & Flux Ratio Calibration

Demo prepared by Neil Zimmerman (not included in the videos)

We realized that many participants encountered trouble to provide flux ratios in the range we expected them to be: exoplanets in reflected light! To help participants revise their photometry, Neil had come up with this demo.

Jupyter python notebook or simply view it on nbviewer

New! Starshade Photometry

Demo prepared by Sergi Hildebrandt (not included in the video)

This demo derives the flux ratios of the same astronomical scenario as with the HLC before, but for the Starshade.

Get the PDF presentation, data and Matlab script in WFIRST-CGI-2019-DC-Tutorial.