Unpacking squished bits (Bit Packer part 2) @LowByteProductions

Uploaded April 2022 | Updated September 2026, 2 weeks ago

In this video, we're writing the unpack half of the Bit Packer API, where we can recognise patterns in the bitstream, and return the value they actually represent!

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Unpacking squished bits (Bit Packer part 2)

$Fixed-point math is better than floating point (sometimes) In this video, were learning about fixed-point: A different method for doing non-integer arithmetic without floats! Floating point is a ubiquitous standard that works everywhere, but it needs specialised hardware to have any chance of running fast. This can make calculations on low-powered microcontrollers extremely expensive. Fixed-point solves, giving us a method for cheaply computing fractional results with flexible precision! 00:00:00 Intro 00:03:46 Floating point vs fixed point 00:10:07 Fixed point bit representation 00:17:10 Code: Fixed point defines 00:21:30 Getting to the integer and fractional parts 00:24:24 Sign function and representing ints in fixed point 00:32:14 Converting to and from floating point 00:36:23 Addition and subtraction 00:38:27 Multiplication 00:42:20 Division 00:48:52 Rounding operations 00:50:14 Absolute value 00:54:50 Floor 00:58:57 Getting the fractional part 01:02:38 Ceiling 01:05:37 Round 01:14:14 Motivating example: Analog to digital converter readings 01:30:10 Next time: Sines and cosines =[ 🔗 Links 🔗 ]= ⭐️ Become a patron and get bonus videos! https://www.patreon.com/lowleveljavascript 🗣 Discord: https://discord.gg/FPWaVgk 💻 Github Repo: https://github.com/lowbyteproductions/fixed-point-math$

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Unpacking squished bits (Bit Packer part 2)