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Split-step non-paraxial beam propagation simulation package

Project description

SSNP

Split-step non-paraxial beam propagation method

Features

  • Forward model calculation based on CUDA
  • Read/write data of common file type
  • Gradient calculation
  • Image reconstruction with regularization

Reference

Sharma, A., & Agrawal, A. (2004). Split-step non-paraxial beam propagation method. Physics and Simulation of Optoelectronic Devices XII, 5349, 132. https://doi.org/10.1117/12.528172

Lim, J., Ayoub, A. B., Antoine, E. E., & Psaltis, D. (2019). High-fidelity optical diffraction tomography of multiple scattering samples. Light: Science & Applications, 8(1), 82. https://doi.org/10.1038/s41377-019-0195-1

Changelog

To do list in current version

  • Support background refractive index (n0 > 1) in gradient computation

0.0.2.beta (developing)

  • Add skcuda as a substitution of reikna (no need to compile FFT)
  • Compute several illumination on the same object in a batch
  • Support background refractive index (n0 > 1) in model computation
  • Add stream parameter for async operation and related small tools
  • Add cache to avoid unnecessary recompiling
  • Fix errors:
    • data.write: fix unexpectedly changing input data when scaling before write

0.0.1 (Sep 7, 2020)

  • Add gradient calculation support (tracking operations and doing autograd)
  • Add config to set package-wise constant
  • Add Multiplier class to generate auto-cached numpy/gpu array
  • Add MATLAB .mat file read & write support (rely on scipy lib)

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