TIPTOP
In order to be able to easily predict the AO performance, we have developed this fast algorithm producing the expected Adaptive Optics (AO see https://en.wikipedia.org/wiki/Adaptive_optics) Point Spread Function (PSF) for any of the existing AO observing modes (Single-Conjugate-AO, Laser-Tomographic-AO, Multi-Conjugate-AO, Ground-Layer-AO), and any atmospheric conditions. This TIPTOP tool takes its roots in an analytical approach, where the simulations are done in the Fourier domain. This allows to reach a very fast computation time (few seconds per PSF with GPU acceleration), and efficiently explore the wide parameter space.
See the documentation here: https://astro-tiptop-services.github.io/astro-tiptop-services/
Please note that the documentation included in the repository at https://tiptop.readthedocs.io will no longer be available in future.
3 maintainers
Release files for astro-tiptop 1.5.2
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| astro_tiptop-1.5.2.tar.gz | 21.8 MB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| astro_tiptop-1.5.2-py3-none-any.whl | Python 3 | none | any | Details |
Total release size:42.2 MB
Release files / astro_tiptop-1.5.2.tar.gz
| Download URL | astro_tiptop-1.5.2.tar.gz |
|---|---|
| Size | 21.8 MB |
| Tags | Source |
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Release files / astro_tiptop-1.5.2-py3-none-any.whl
| Download URL | astro_tiptop-1.5.2-py3-none-any.whl |
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| Size | 20.4 MB |
| Tags | Python 3 |
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