Based on the WordNet corpus, omitting results containing:
- slashes (e.g.
lo/ovral) - spaces (e.g.
living_thing) - digits (e.g.
1900s)
Generated with the following Python script using NLTK:
from pathlib import Path
from nltk.corpus import wordnetBased on the WordNet corpus, omitting results containing:
lo/ovral)living_thing)1900s)Generated with the following Python script using NLTK:
from pathlib import Path
from nltk.corpus import wordnet| // Hyperboloc functions by toneburst from | |
| // https://machinesdontcare.wordpress.com/2008/03/10/glsl-cosh-sinh-tanh/ | |
| // These are missing in GLSL 1.10 and 1.20, uncomment if you need them | |
| /* | |
| /// COSH Function (Hyperbolic Cosine) | |
| float cosh(float val) | |
| { | |
| float tmp = exp(val); | |
| float cosH = (tmp + 1.0 / tmp) / 2.0; |
| import numpy as np | |
| def perspective_fov(fov, aspect_ratio, near_plane, far_plane): | |
| num = 1.0 / np.tan(fov / 2.0) | |
| num9 = num / aspect_ratio | |
| return np.array([ | |
| [num9, 0.0, 0.0, 0.0], | |
| [0.0, num, 0.0, 0.0], | |
| [0.0, 0.0, far_plane / (near_plane - far_plane), -1.0], | |
| [0.0, 0.0, (near_plane * far_plane) / (near_plane - far_plane), 0.0] |
| #!/bin/bash | |
| ### steps #### | |
| # verify the system has a cuda-capable gpu | |
| # download and install the nvidia cuda toolkit and cudnn | |
| # setup environmental variables | |
| # verify the installation | |
| ### | |
| ### to verify your gpu is cuda enable check |
| /** | |
| * Resize the image to a new width and height using nearest neigbor algorithm. To make the image scale | |
| * proportionally, use 0 as the value for the wide or high parameter. | |
| * For instance, to make the width of an image 150 pixels, and change | |
| * the height using the same proportion, use resize(150, 0). | |
| * Otherwise same usage as the regular resize(). | |
| * | |
| * Note: Disproportionate resizing squashes the "pixels" from squares to rectangles. | |
| * This works about 10 times slower than the regular resize. Any suggestions for performance increase are welcome. | |
| */ |
| /** | |
| * Resize the image to a new width and height using nearest neighbor algorithm. | |
| * To make the image scale proportionally, | |
| * use 0 as the value for the wide or high parameters. | |
| * For instance, to make the width of an image 150 pixels, | |
| * and change the height using the same proportion, use resize(150, 0). | |
| * Otherwise same usage as the regular resize(). | |
| * | |
| * Note: Disproportionate resizing squashes "pixels" from squares to rectangles. | |
| * This works about 10 times slower than the regular resize. |
| javascript:(function(){ | |
| const MY_MASTO_LOCAL_DOMAIN = 'front-end.social'; /* 👈 Change this value */ | |
| const MY_MASTO_WEB_DOMAIN = MY_MASTO_LOCAL_DOMAIN; /* 👈 Only change this value if your Masto host is hosted an different domain than the LOCAL_DOMAIN */ | |
| function tryAndGetUserName() { | |
| /* Profile with a moved banner (e.g. https://mastodon.social/@bramus): follow that link */ | |
| const userNewProfile = document.querySelector('.moved-account-banner .button')?.getAttribute('href'); | |
| if (userNewProfile) { | |
| return userNewProfile.substring(2); | |
| } |
| let heights = []; | |
| let moving_heights = []; | |
| let r = 0; | |
| function setup() { | |
| createCanvas(800, 400, WEBGL); | |
| for (let i=0; i<17; i++) { | |
| heights.push([]); | |
| moving_heights.push([]); | |
| for (let j=0; j<17; j++) { |