EHT Sgr A* Theory Paper Analysis Toolkit

This repository contains tools and Jupyter notebooks for data analysis and visualization for the EHT Sgr A* Theory Paper. All user scripts and notebooks are in the top directory. To use the scripts and notebooks in this package, simply run

pip3 install -r requirements.txt

to obtain the necessary packages.

Dependency

This repository tries to keep its dependency minimal. We only require standard libraries:

astropy
click (only used in the top level driver scripts)
h5py
jupyterlab (only used to open the notebooks)
matplotlib
numpy
pandas
parse
ruamel.yaml (only used in the top level driver scripts)
tqdm (only used in the top level driver scripts)

Because of this, instead of using custom libraries such as hallmark and mockservation, we put all the dependent functions in the "common/" directory. This makes this repository easy to use and self-contained.

When we are about to finish the Sgr A* papers, it is possible that we will push the code upstream back to the individual packages, and turn this into a meta-package that help us manage all upstream packages.

Design

We design this toolkit so it allows multiple people to work together. To make it a smooth experience, we define three data stage.

models/: the "input models" of this toolkit include images at different frequencies or full SEDs. These are usually outputs of high performance C or Fortran codes such as ipole and igrmonty that require significant computing resource to run. The number of files is of order of million and total size may reach 10s of TB. The intention is that the people who generate the models are responsible to their own models, who may copy or link the input models in the models/ directory in their own clones of this repository.
cache/: this toolkit then preprocesses the input models to summary tables and/or compressed movies that are directly relevant to the science. Examples include total flux, image size, spectral filtered movies. The number and total size of these cache files is usually a few orders of mangitude smaller than the files in models/. Because of the more managable size, the intension is that people can share/rsync the full copy of these cache files to their own laptops to perform further analysis.
output/: stores outputs including LaTeX tables, plots, and movies, that are generated from files in cache/ and possibility models/. The intention is these output files should be identical no matter who generate them. These files should be at publication qualitity that we can place them directly to the Sgr A* Theory Paper.

Other Tools

SYMBA Pegasus Workflow: https://github.com/bhpire/symba-osg
ipole Condor Workflow: https://github.com/bhpire/ipole-osg
igrmonty Condor Workflow: https://github.com/bhpire/igrmonty-osg
calsz Condor Workflow: https://github.com/bhpire/calsz-osg

Name		Name	Last commit message	Last commit date
Latest commit History 231 Commits
cache		cache
common		common
config		config
data		data
model		model
output		output
test/ipole_86GHz/Ma0_w1		test/ipole_86GHz/Ma0_w1
.gitignore		.gitignore
README.md		README.md
cache_avg.py		cache_avg.py
cache_gt.py		cache_gt.py
cache_null.py		cache_null.py
cache_sed.py		cache_sed.py
cache_stat.py		cache_stat.py
cache_summ.py		cache_summ.py
environment.yml		environment.yml
match.ipynb		match.ipynb
output_2nd_moment.ipynb		output_2nd_moment.ipynb
output_GRRT_vs_MCRT.ipynb		output_GRRT_vs_MCRT.ipynb
output_avggrid.ipynb		output_avggrid.ipynb
output_bestbet_explain.ipynb		output_bestbet_explain.ipynb
output_bestbet_imgs.ipynb		output_bestbet_imgs.ipynb
output_bestbet_imgs2.ipynb		output_bestbet_imgs2.ipynb
output_bestbet_imgs3.ipynb		output_bestbet_imgs3.ipynb
output_bestbet_imgs4.ipynb		output_bestbet_imgs4.ipynb
output_bestbet_imgs_backup.ipynb		output_bestbet_imgs_backup.ipynb
output_bestbet_movie.ipynb		output_bestbet_movie.ipynb
output_bestbet_va_sed_old.ipynb		output_bestbet_va_sed_old.ipynb
output_corr.ipynb		output_corr.ipynb
output_dist.ipynb		output_dist.ipynb
output_forward.ipynb		output_forward.ipynb
output_lc.ipynb		output_lc.ipynb
output_likelyhood.ipynb		output_likelyhood.ipynb
output_mi.ipynb		output_mi.ipynb
output_mov.ipynb		output_mov.ipynb
output_null.ipynb		output_null.ipynb
output_passfail_sed.ipynb		output_passfail_sed.ipynb
output_passfail_sz.ipynb		output_passfail_sz.ipynb
output_passfail_va.ipynb		output_passfail_va.ipynb
output_plots.ipynb		output_plots.ipynb
output_sample.ipynb		output_sample.ipynb
output_sample_vas_sed.ipynb		output_sample_vas_sed.ipynb
output_sedgrid.ipynb		output_sedgrid.ipynb
output_snapshot.ipynb		output_snapshot.ipynb
output_snapshot2.ipynb		output_snapshot2.ipynb
output_stat.ipynb		output_stat.ipynb
output_va.ipynb		output_va.ipynb
requirements.txt		requirements.txt
test_compress.ipynb		test_compress.ipynb
test_fft.ipynb		test_fft.ipynb
test_filter.ipynb		test_filter.ipynb
test_io.ipynb		test_io.ipynb
test_iotext.ipynb		test_iotext.ipynb
test_mockservation.ipynb		test_mockservation.ipynb
test_moments.ipynb		test_moments.ipynb
test_va.ipynb		test_va.ipynb
testfits.ipynb		testfits.ipynb

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