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Description
The classes are time-and-the-sky functions for planning and carrying out ground-based astronomical observations, based on astropy.coordinates and astropy.time, with a few end-runs to speed things up. There is also a Tkl/TK program similar to JSkyCalc for interactive use. The functions are also useful for data processing for such tasks as, inferring barycentric corrections from image header data.
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Yes, I somehow submitted it twice - the less complete one should be
withdrawn. I didn't see how to do that immediately, though to be
fair I haven't looked very hard!
John
On Mon, 23 Dec 2024, Derek Homeier wrote:
Duplicated (with more complete description) in #229?
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John R. Thorstensen
Department of Physics and Astronomy
Dartmouth College
6127 Wilder Laboratory
Hanover, NH 03755
Office: 239 Wilder Hall
Phone: 603 646 2869 Fax: 1446 Hinman Box 6127
--------------------------------------------------------
Submitting Author: Name
jrthorstensen
Package Name:
thorsky
One-Line Description of Package:
astropy-based time-and-the-sky software for astronomical observations and reduction
Repository Link (if existing):
https://github.com/jrthorstensen/thorsky
EiC: TBD
Code of Conduct & Commitment to Maintain Package
Description
The classes are time-and-the-sky functions for planning and carrying out ground-based astronomical observations, based on astropy.coordinates and astropy.time, with a few end-runs to speed things up. There is also a Tkl/TK program similar to JSkyCalc for interactive use. The functions are also useful for data processing for such tasks as, inferring barycentric corrections from image header data.
Community Partnerships
We partner with communities to support peer review with an additional layer of
checks that satisfy community requirements. If your package fits into an
existing community please check below:
Scope
Please indicate which category or categories this package falls under:
Domain Specific
Explain how and why the package falls under these categories (briefly, 1-2 sentences). For community partnerships, check also their specific guidelines as documented in the links above. Please note any areas you are unsure of:
Who is the target audience and what are the scientific applications of this package?
Are there other Python packages that accomplish similar things? If so, how does yours differ?
Any other questions or issues we should be aware of:
P.S. Have feedback/comments about our review process? Leave a comment here
The text was updated successfully, but these errors were encountered: