# fastlens:
Public package of FFT based evaluation of extended source magnification, `fastlens`, which is named after `fast microlensing`.
Please cite [Sugiyama 2022](https://arxiv.org/abs/2203.06637).
FFT based method of extended soruce magnification is implemented in `fastlens/mag_fft.py`.
FFT based method of time averaged magnification is implemented in `fastlens/timeave.py`.
Please cite my paper if you use my code for your project.
FFT based method uses public FFTLog code by Xiao Fang, available at [FFTLog-and-beyond](https://github.com/xfangcosmo/FFTLog-and-beyond), and developed in [Fang et al (2019); arXiv:1911.11947](https://arxiv.org/abs/1911.11947).
`fastlens` is open source and distributed with [MIT license](https://opensource.org/licenses/mit).
# Installation
This package is installable with both of pip and conda. Just install by running below on your shell
```
pip install fastlens
```
for pip user, or
```
conda install -c XXX fastlens
```
for conda user.
If you prefer to download the repo and install the package from source, run
```
python setup.py install
```
## Contents: notebooks and a script
All the ipython notebooks are saved in [ipynb](ipynb) direcotry. Tutorials are available in
- [`howtouse.ipynb`](ipynb/howtouse.ipynb) shows how to use module in `magnification`.
- [`howtouse-previous-methods.ipynb`](ipynb/howtouse-previous-methods.ipynb) shows how to use modeles for methods developed in the previous studies.
Validation and comparison to previous methods are performed in
- [`timeave.ipynb`](ipynb/timeave.ipynb) validate the accuracy of implementation of time averaging effect with FFT.
- [`comparison.ipynb`](ipynb/comparison.ipynb) makes a plot of comparison of residuals by various evaluation methods of extended source magnification.
- [`timeit_methods.ipynb`](ipynb/timeit_methos.ipynb) measures computational time of various methods.
- [`paperfig.ipynb`](ipynb/paperfig.ipynb) can reproduce figures shown in the paper.
- [`testdata.py`](ipynb/testdata.py) is a module to generate reference magnification using `scipy.integrate.quad`, which will be used for validation of the FFT based method.
Raw data
{
"_id": null,
"home_page": "https://github.com/git-sunao/fft-extended-source",
"name": "fastlens",
"maintainer": "",
"docs_url": null,
"requires_python": "",
"maintainer_email": "",
"keywords": "microlensing,fft",
"author": "Sunao Sugiyama",
"author_email": "sunaosugiyama@gmail.com",
"download_url": "https://files.pythonhosted.org/packages/c4/38/05b44c91147ae97ac563769bf3b959dc6a5951bae6bffaf99d7911274940/fastlens-1.0.5.tar.gz",
"platform": null,
"description": "# fastlens:\nPublic package of FFT based evaluation of extended source magnification, `fastlens`, which is named after `fast microlensing`.\nPlease cite [Sugiyama 2022](https://arxiv.org/abs/2203.06637).\n\nFFT based method of extended soruce magnification is implemented in `fastlens/mag_fft.py`. \nFFT based method of time averaged magnification is implemented in `fastlens/timeave.py`.\n\nPlease cite my paper if you use my code for your project. \n\nFFT based method uses public FFTLog code by Xiao Fang, available at [FFTLog-and-beyond](https://github.com/xfangcosmo/FFTLog-and-beyond), and developed in [Fang et al (2019); arXiv:1911.11947](https://arxiv.org/abs/1911.11947).\n\n`fastlens` is open source and distributed with [MIT license](https://opensource.org/licenses/mit).\n\n# Installation\nThis package is installable with both of pip and conda. Just install by running below on your shell \n```\npip install fastlens\n```\nfor pip user, or\n```\nconda install -c XXX fastlens\n```\nfor conda user.\n\nIf you prefer to download the repo and install the package from source, run\n```\npython setup.py install\n```\n\n## Contents: notebooks and a script\nAll the ipython notebooks are saved in [ipynb](ipynb) direcotry. Tutorials are available in\n- [`howtouse.ipynb`](ipynb/howtouse.ipynb) shows how to use module in `magnification`.\n- [`howtouse-previous-methods.ipynb`](ipynb/howtouse-previous-methods.ipynb) shows how to use modeles for methods developed in the previous studies.\nValidation and comparison to previous methods are performed in\n- [`timeave.ipynb`](ipynb/timeave.ipynb) validate the accuracy of implementation of time averaging effect with FFT.\n- [`comparison.ipynb`](ipynb/comparison.ipynb) makes a plot of comparison of residuals by various evaluation methods of extended source magnification.\n- [`timeit_methods.ipynb`](ipynb/timeit_methos.ipynb) measures computational time of various methods.\n- [`paperfig.ipynb`](ipynb/paperfig.ipynb) can reproduce figures shown in the paper.\n- [`testdata.py`](ipynb/testdata.py) is a module to generate reference magnification using `scipy.integrate.quad`, which will be used for validation of the FFT based method.\n\n",
"bugtrack_url": null,
"license": "",
"summary": "fft based microlensing package",
"version": "1.0.5",
"project_urls": {
"Homepage": "https://github.com/git-sunao/fft-extended-source"
},
"split_keywords": [
"microlensing",
"fft"
],
"urls": [
{
"comment_text": "",
"digests": {
"blake2b_256": "2f167cd1d75e0cd4dad0bc01444ae76593ebda19c90bb876ad7734d6ff9d60d3",
"md5": "1de0eecf050d4ac73046b6019c3deb3e",
"sha256": "99499355eef9b4003e2f3b4ef48a4a1afb6abb1a75c24d39e66b9530395f4499"
},
"downloads": -1,
"filename": "fastlens-1.0.5-py3-none-any.whl",
"has_sig": false,
"md5_digest": "1de0eecf050d4ac73046b6019c3deb3e",
"packagetype": "bdist_wheel",
"python_version": "py3",
"requires_python": null,
"size": 8676,
"upload_time": "2023-12-30T03:25:55",
"upload_time_iso_8601": "2023-12-30T03:25:55.625880Z",
"url": "https://files.pythonhosted.org/packages/2f/16/7cd1d75e0cd4dad0bc01444ae76593ebda19c90bb876ad7734d6ff9d60d3/fastlens-1.0.5-py3-none-any.whl",
"yanked": false,
"yanked_reason": null
},
{
"comment_text": "",
"digests": {
"blake2b_256": "c43805b44c91147ae97ac563769bf3b959dc6a5951bae6bffaf99d7911274940",
"md5": "b1f36c66ddc9bde18616878a51c5b03a",
"sha256": "b07e07e37c102d1ebe6bf6c6cff3510d719688ea880e1ab17429a2648690b426"
},
"downloads": -1,
"filename": "fastlens-1.0.5.tar.gz",
"has_sig": false,
"md5_digest": "b1f36c66ddc9bde18616878a51c5b03a",
"packagetype": "sdist",
"python_version": "source",
"requires_python": null,
"size": 8223,
"upload_time": "2023-12-30T03:25:57",
"upload_time_iso_8601": "2023-12-30T03:25:57.175848Z",
"url": "https://files.pythonhosted.org/packages/c4/38/05b44c91147ae97ac563769bf3b959dc6a5951bae6bffaf99d7911274940/fastlens-1.0.5.tar.gz",
"yanked": false,
"yanked_reason": null
}
],
"upload_time": "2023-12-30 03:25:57",
"github": true,
"gitlab": false,
"bitbucket": false,
"codeberg": false,
"github_user": "git-sunao",
"github_project": "fft-extended-source",
"travis_ci": false,
"coveralls": false,
"github_actions": false,
"lcname": "fastlens"
}
JSON
