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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.

Prerequisite

You should have already downloaded and extracted the IM Lup DSHARP dataset as described in Example 00. Then, you will need to copy the IM_Lup_baselines_and_weights.npz into this directory in a new data folder. For example, from within this 01 folder, run

$ mkdir data
$ cp ../00-download-and-extract-datasets/data/IM_Lup_baselines_and_weights.npz data/

Installation

You can install necessary Python packages into your environment by

$ pip install -r requirements.txt

and then you can run the code by

snakemake -c1 all

Description of Contents

Note that this script does not actually 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 on demand.

  • 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.
  • package_data.py combines the two numpy arrays into a single archive, saved as float32 to save space.

The end result will be this mock image (sourced from ceyda/smithsonian_butterflies) stuffed into data/mock_data.npz Mock Image