README.md

Setup Mock Image and Baselines

This example generates a mock sky brightness image and a realistic set of baselines $(u,v)$, which are later used by other examples in this repository, and as a fixture within the MPoL test suite. It uses the IM Lup DSHARP dataset for realistic baselines, weight values, and source flux.

Note that this script does not sample mock visibility values $\mathcal{V}(u,v)$. That is done on the fly using mpol.fourier.generate_fake_data in scripts like sgd/src/load_data.py, so that sky image size, flux, and measurement noise level can be adjusted as needed.

• create_butterfly.py downloads a nice looking image from the ceyda/smithsonian_butterflies collection, uses PIL to greyscale and crop it, adjusts the flux value to match DSHARP IM Lup, then saves it as a numpy array.
• export_baselines.py uses MPoL-dev/visread and casatools to extract real baselines from the IM Lup measurement set, and saves them as a numpy array. To save space, we take <5% of the visibilities.
• package_data.py combines the two numpy arrays into a single archive, saved as float32 to save space.
• requirements.txt lists the python packages necessary for the analysis. You can install them with pip install -r requirements.txt
• Snakefile is a snakemake file setting up the workflow. From this directory, you can run

$ snakemake -c 1 all

Will create this mock image (sourced from ceyda/smithsonian_butterflies) stuffed into data/mock_data.npz