🌙 The minimal & fast library for functional user interfaces
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Updated
Feb 29, 2024 - JavaScript
🌙 The minimal & fast library for functional user interfaces
🌓 Moon is a minimal, one column jekyll theme.
Weather, tides, the sun, the moon, maps, and a planetarium, in your terminal. The Old Farmer's Almanac meets Minitel.
Advanced date, time and interval library for Java with sun/moon-astronomy and calendars like Chinese, Coptic, Ethiopian, French Republican, Hebrew, Hijri, Historic Christian, Indian National, Japanese, Julian, Korean, Minguo, Persian, Thai, Vietnamese
A library designed to ease geographic coordinate format conversions, and determine sun/moon information in C#
Browser automation solution for Kubernetes and Openshift supporting Selenium, Playwright, Puppeteer and Cypress
Multi-Mission Geographic Information System - A Web-based Mapping and Spatial Data Infrastructure for Earth, Lunar and Planetary Visualization, Research, Science, Planning and Operations.
This is the GitHub home of Race Into Space, the computer version of the Liftoff! board game by Fritz Bronner. It was developed by Strategic Visions and published by Interplay as a disk-based game in 1993 and a CD-ROM in 1994. It was open-sourced in 2005 and a number of improvements have been made over the original.
🌘 Custom card for tracking Moon phases
Browser images for Selenoid and Moon 1.x
Astro: Go Astronomy Algorithms Library - Chinese Lunar Calendar, Solar/Lunar Eclipses, Sun/Moon/Planet Positions, Rise/Set, Planet Events, Stars, Coordinates, Orbits, Sundials and Lightweight Ephemerides (天文算法 Go 库:农历、日月食、日月行星位置、升落、行星天象、恒星、坐标、轨道、日晷与轻量星历)
Convolutional neural network code for extracting Lunar craters from Digital Elevation Maps (DEMs).
A 3D lunar rover survey game. WebGL2, no build step, no third-party assets - every texture and sound generated at runtime.
🌑 Lune.js — Calculate the phases of the moon
Collaborative Multiphysics Cosimulator For Space Missions 🌎🚀🌚
(NeurIPS 2022) Official Implementation of "Preservation of the Global Knowledge by Not-True Distillation in Federated Learning"
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