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0.1.1 lotus_nlte-0.1.1-py3-none-any.whl

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Project: lotus-nlte
Version: 0.1.1
Filename: lotus_nlte-0.1.1-py3-none-any.whl
Download: [link]
Size: 619229
MD5: c313f03fea4e932d958e46c5c2af8f13
SHA256: f132422d44e7c8c6a1d942c3915ac559cfb187e331ab95ea4c208c30d6409b1f
Uploaded: 2023-01-04 03:37:02 +0000

dist-info

METADATA · WHEEL · RECORD · top_level.txt

METADATA

Metadata-Version: 2.1
Name: lotus-nlte
Version: 0.1.1
Summary: Determine atmospheric stellar parameters in non-LTE
Author: Yangyang Li
Author-Email: ly95astro[at]gmail.com
Maintainer: Yangyang Li
Home-Page: https://github.com/Li-Yangyang/LOTUs
License: MIT
Classifier: Development Status :: 2 - Pre-Alpha
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Operating System :: OS Independent
Classifier: Programming Language :: Python :: 3.7
Requires-Python: >= 3.7, < 3.8
Requires-Dist: cython (==0.29.24)
Requires-Dist: numpy (>=1.16.4)
Requires-Dist: pandas (==0.24.2)
Requires-Dist: tables (==3.7.0)
Requires-Dist: scipy (>=1.5.0)
Requires-Dist: sympy (>=1.6.2)
Requires-Dist: h5py (>=2.10.0)
Requires-Dist: astropy (>=3.2.1)
Requires-Dist: joblib (==1.0.1)
Requires-Dist: numdifftools (==0.9.39)
Requires-Dist: scikit-learn (==0.23.2)
Requires-Dist: pymc3 (==3.7)
Requires-Dist: theano (==1.0.4)
Requires-Dist: matplotlib (>=3.1.3)
Requires-Dist: tqdm
Requires-Dist: corner
Requires-Dist: requests
Requires-Dist: rbf; extra == "advanced-interp"
Requires-Dist: torch; extra == "advanced-interp"
Requires-Dist: gpytorch; extra == "advanced-interp"
Requires-Dist: sphinx-book-theme; extra == "doc"
Provides-Extra: advanced-interp
Provides-Extra: doc
Description-Content-Type: text/markdown
License-File: LICENSE
[Description omitted; length: 2659 characters]

WHEEL

Wheel-Version: 1.0
Generator: bdist_wheel (0.38.4)
Root-Is-Purelib: true
Tag: py3-none-any

RECORD

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lotus_nlte/config.py sha256=ERjLdvEfl-PILAQKGfVO9vQaPnjoczcVOXUIiJM4K7k 1852
lotus_nlte/download.py sha256=8ZbNz8NUq_HyE4YDVh5rqGmTSAclrag1YzfMGgb6zz8 4002
lotus_nlte/lotus_nlte_version.py sha256=rnObPjuBcEStqSO0S6gsdS_ot8ITOQjVj_-P1LUUYpg 22
lotus_nlte/optimize.py sha256=8Sv4MittdjuKBnlHrv7zgeOnOpmC_N8dZpelnuMS0UI 26610
lotus_nlte/plot.py sha256=F74eF0qKH93yAYrYNUHqwYrxDEWN7BdtoDI1O6ckgyE 12309
lotus_nlte/sampling.py sha256=jGeInUCQ7r0Eobr-HPxOIW03PPVAuHd4ISs0OTNTGco 3100
lotus_nlte/utils.py sha256=bBe_sjfRsooVKc3IJEjyrU71HvyZ01lcSsANw9lAEaw 14831
lotus_nlte/gcogs/__init__.py sha256=Rbl6cfpau3uNxeZeHJbKjAEyXbJ1NJkRYz6VtaVNQrM 260
lotus_nlte/gcogs/gcog.py sha256=q1TfTQrpuE-ZuTswLs9GlGvrx3X90ZeRPQEvQqVnwjc 7100
lotus_nlte/gcogs/multigcogs.py sha256=MzOQvDycFphuNKfe3KW04_dozMl3VRH9w17OQbCGVN0 27598
lotus_nlte/gcogs/utils.py sha256=TpERaoYtEDIwDBZqq4XhgrFKGIHmUHQTatMApARLITI 3468
lotus_nlte/interpolation/__init__.py sha256=hcjrMXIOv2_FqzYdHqlZ3s7K3zoTL2ceW4VCuzqdUXQ 153
lotus_nlte/interpolation/gp_interp.py sha256=60tIjiDwHAtVbH8Wd9EGI2g6f33aLcTi5a8PkhSiauE 4342
lotus_nlte/interpolation/multipoly_interp.py sha256=Sx2Q4nPpMP9a32n7NYnLqZba164I07VjvR_THJrHNZs 6541
lotus_nlte/interpolation/rbf_interp.py sha256=jjDmozkS-ESkfqf_E_-j8G3ifb_semabK3AKiNT9huA 1048
lotus_nlte/package_data/linelist/final.linelist sha256=CJHLFgYPnnDtz-NTNJXEkl72eExtIr4B9bhUdVmID9g 7769
lotus_nlte/package_data/linelist/ges.linelist sha256=v5H_0Fe8COcRlaGtdS8EbbivUBbEid4f6t6csdhBmTU 4915029
lotus_nlte/package_data/linelist/metalpoor.linelist sha256=nWdyXcE5cJzW0FXAh3C7BxjMjIxnFRYLza_q6TNY9vc 12285
lotus_nlte/test/data/HD122563.csv sha256=b7LTfefJyQ_leqlrf0DCEfyWfUzb2SEqRCAynDSaXDI 8012
lotus_nlte/test/data/Sun.csv sha256=NjOneI7fedEfN407dhHVwMleHYMK4II5u5YZGRIUrDE 6922
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lotus_nlte/theano_op/likelihood.py sha256=KZyM4WyDhip4vhM_sszziBm_3bO_hBvAtaPkwgo7AYM 3044
lotus_nlte/theano_op/predict.py sha256=RRJSaSyKFHdjbNLS_QX5s-cjAXl1aP1d3yqotTxDuY8 2116
lotus_nlte-0.1.1.dist-info/LICENSE sha256=8-OQewT3hSi0C-006R5lH-RU5F1DXFJhxHXz2egTr7I 1068
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lotus_nlte-0.1.1.dist-info/RECORD — —

top_level.txt

lotus_nlte