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 (working)
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
1 maintainer
Metadata
1 maintainer
Release files for ssnp 0.0.1
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Source distribution (sdist)
| File | Size | Uploaded | Provenance | Actions |
|---|---|---|---|---|
| ssnp-0.0.1.tar.gz | 28.9 kB | Without provenance | Details for ssnp-0.0.1.tar.gz |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Actions Reset |
|---|---|---|---|---|
| ssnp-0.0.1-py3-none-any.whl | Python 3 | none | any | Details for ssnp-0.0.1-py3-none-any.whl |
Total release size: 60.8 kB
Release files / ssnp-0.0.1.tar.gz
| Download URL | ssnp-0.0.1.tar.gz |
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| Size | 28.9 kB |
| Tags | Source |
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Release files / ssnp-0.0.1-py3-none-any.whl
| Download URL | ssnp-0.0.1-py3-none-any.whl |
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| Size | 31.8 kB |
| Tags | Python 3 |
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