Notebooks corresponding to preprint available at arXiv. Bibtex citation:

@misc{ubald2022density,
      title={Density Estimation from Schlieren Images through Machine Learning}, 
      author={Bryn Noel Ubald and Pranay Seshadri and Andrew Duncan},
      year={2022},
      eprint={2201.05233},
      archivePrefix={arXiv},
      primaryClass={physics.flu-dyn}
}

Cases available in this repo:

• Case 1a: Analytical test case, using gradients in x and y
  • {Case1-Analytical-1.0.ipynb}
• Case 1b: Analytical test case, using gradients only along x
  • {Case1-Analytical-1.0-dx-only.ipynb}
• Case 2: Experimental sting shock case paper
  • {Case2-Sting-shock-Ota-1.0.ipynb}
• Case 3: NASA T38 supersonic shock captured with BOS
  • {Case3-NASA-T38-1.0-redo.ipynb}