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Creates the daily pages of a Nautical Almanac using Skyfield

Project description

Skyalmanac is a Python 3 script that creates the daily pages of the Nautical Almanac (based on the UT timescale). The generated tables are needed for celestial navigation with a sextant. Although you are strongly advised to purchase the official Nautical Almanac, this program will reproduce the tables with no warranty or guarantee of accuracy.

NOTE: The original Skyalmanac that was a hybrid version using both Skyfield and Ephem has been abolished and replaced with the Skyfield version. It is now the same as the SFalmanac version (except for the new name). There is no justification for the hybrid version any more.

     smileyMultiprocessing version for increased performance!smiley

Skyalmanac-Py3 can now employ multiprocessing (if your processor has multiple cores) reducing the processing time. Single-processing is also available as an option if required. Testing has been successfully performed on Windows 10 and Ubuntu 20.04 LTS. (No testing done on Mac OS.) Compared to single-processing, data processing (excluding conversion from TEX to PDF)

  • … of a 6-day Nautical Almanac is 4x faster on Windows 10; 2x faster on Linux.

  • … of 6-day Event Time Tables is almost 5x faster on Windows 10; 3x faster on Linux.

Windows 10 uses up to 8 threads; Linux uses up to 12 threads in parallel. Testing was performed on a PC with an AMD Ryzen 7 3700X 8-Core (16 threads) Processor. Windows & Mac OS spawn new processes; Linux forks new processes (the code is compatible with both techniques and will also run on CPUs with fewer cores/threads).

Quick Overview

This is the PyPI edition of Skyalmanac-Py3 (a Changelog can be viewed here). Version numbering follows the scheme Major.Minor.Patch, whereby the Patch number represents some small correction to the intended release.

NOTE: Version numbering in PyPI restarted from 1.0 as the previous well-tested versions that exist since early 2019 were never published as PyPI packages.

The astronomical library employed is: Skyfield.
Skyalmanac uses the Hipparcos catalog as its star database.

If a current version of Skyfield (>= 1.31) is used, you have two options (which one, you specify by manually editing config.py):

  • if “useIERS = False”, the built-in UT1 tables in the installed version of Skyfield will be employed.

  • if “useIERS = True”, for optimal accuracy (specifically for all GHA data), Earth orientation data from IERS (International Earth Rotation and Reference Systems Service) is downloaded and then used until it ‘expires’. It expires after a chosen number of days (also specifiable in config.py). Note that IERS specifies the range of Earth Orientation Parameter (EOP) data from 2nd January 1973 and is updated weekly. Refer to the IERS web site for current information.

Software Requirements


Nearly all of the astronomical computation is done by the Skyfield library.
Typesetting is done typically by MiKTeX or TeX Live.
Here are the requirements/recommendations:

Installation

Install a TeX/LaTeX program on your operating system so that pdflatex is available.

Ensure that the pip Python installer tool is installed. You may check that the latest version of SFalmanac is installed:

python -m pip uninstall skyalmanac
python -m pip install skyalmanac

Installing Skyalmanac ensures that Skyfield and Pandas (and their dependencies) are also installed. If previous versions of Skyalmanac were installed, consider upgrading Skyfield and Pandas thus:

python -m pip install --upgrade skyfield pandas

Thereafter run it with:

python -m skyalmanac

On a POSIX system (Linux or Mac OS), use python3 instead of python in the commands above.

This PyPI edition also supports installing and running in a venv virtual environment.

Finally check or change the settings in config.py. Its location is printed immediately whenever Skyalmanac runs.

Guidelines for Linux & Mac OS

Quote from Chris Johnson:

It’s best to not use the system-provided Python directly. Leave that one alone since the OS can change it in undesired ways.

The best practice is to configure your own Python version(s) and manage them on a per-project basis using venv (for Python 3). This eliminates all dependency on the system-provided Python version, and also isolates each project from other projects on the machine.

Each project can have a different Python point version if needed, and gets its own site_packages directory so pip-installed libraries can also have different versions by project. This approach is a major problem-avoider.

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