| using UnityEngine; | |
| [RequireComponent( typeof(Camera) )] | |
| public class FlyCamera : MonoBehaviour { | |
| public float acceleration = 50; // how fast you accelerate | |
| public float accSprintMultiplier = 4; // how much faster you go when "sprinting" | |
| public float lookSensitivity = 1; // mouse look sensitivity | |
| public float dampingCoefficient = 5; // how quickly you break to a halt after you stop your input | |
| public bool focusOnEnable = true; // whether or not to focus and lock cursor immediately on enable |
| #include <stdio.h> | |
| #include <stdlib.h> | |
| const int H = 40; | |
| const int W = 80; | |
| char map[H][W]; | |
| int rnd(int max) { | |
| return rand() % max; |
This is a short post that explains how to write a high-performance matrix multiplication program on modern processors. In this tutorial I will use a single core of the Skylake-client CPU with AVX2, but the principles in this post also apply to other processors with different instruction sets (such as AVX512).
Matrix multiplication is a mathematical operation that defines the product of
| const round(value, decimals) =>Number(Math.round(value+'e'+decimals)+'e-'+decimals); | |
| round(1.005, 2); // 1.01 | |
| Math.round(1.005, 2); // 1.00 | |
| // via http://www.jacklmoore.com/notes/rounding-in-javascript/ |
| console.clear(); | |
| const w = 4; | |
| const h = 6; | |
| const res = Array.from({ | |
| length: w * h | |
| }, (_, i) => i).map(i => { | |
| const x = i % w; | |
| const y = i / w | 0; |
| function logColor(color, args) { | |
| console.log(`%c ${args.join(' ')}`, `color: ${color}`); | |
| } | |
| const log = { | |
| aliceblue: (...args) => { logColor('aliceblue', args)}, | |
| antiquewhite: (...args) => { logColor('antiquewhite', args)}, | |
| aqua: (...args) => { logColor('aqua', args)}, | |
| aquamarine: (...args) => { logColor('aquamarine', args)}, | |
| azure: (...args) => { logColor('azure', args)}, |
| --[[ | |
| Implemented as described here: | |
| http://flafla2.github.io/2014/08/09/perlinnoise.html | |
| ]]-- | |
| perlin = {} | |
| perlin.p = {} | |
| -- Hash lookup table as defined by Ken Perlin | |
| -- This is a randomly arranged array of all numbers from 0-255 inclusive |
Using the REST API to upload a file to WordPress is
quite simple. All you need is to send the file in a
POST-Request to the wp/v2/media route.
There are two ways of sending a file. The first method simply sends the file in the body of the request. The following PHP script shows the basic principle:
https://gist.github.com/ljharb/58faf1cfcb4e6808f74aae4ef7944cff
While attempting to explain JavaScript's reduce method on arrays, conceptually, I came up with the following - hopefully it's helpful; happy to tweak it if anyone has suggestions.
JavaScript Arrays have lots of built in methods on their prototype. Some of them mutate - ie, they change the underlying array in-place. Luckily, most of them do not - they instead return an entirely distinct array. Since arrays are conceptually a contiguous list of items, it helps code clarity and maintainability a lot to be able to operate on them in a "functional" way. (I'll also insist on referring to an array as a "list" - although in some languages, List is a native data type, in JS and this post, I'm referring to the concept. Everywhere I use the word "list" you can assume I'm talking about a JS Array) This means, to perform a single operation on the list as a whole ("atomically"), and to return a new list - thus making it mu
Code is clean if it can be understood easily – by everyone on the team. Clean code can be read and enhanced by a developer other than its original author. With understandability comes readability, changeability, extensibility and maintainability.
