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@patriciogonzalezvivo
patriciogonzalezvivo / GLSL-Noise.md
Last active May 3, 2024 08:26
GLSL Noise Algorithms

Please consider using http://lygia.xyz instead of copy/pasting this functions. It expand suport for voronoi, voronoise, fbm, noise, worley, noise, derivatives and much more, through simple file dependencies. Take a look to https://github.com/patriciogonzalezvivo/lygia/tree/main/generative

Generic 1,2,3 Noise

float rand(float n){return fract(sin(n) * 43758.5453123);}

float noise(float p){
	float fl = floor(p);
  float fc = fract(p);
@millermedeiros
millermedeiros / osx_setup.md
Last active May 1, 2024 20:46
Mac OS X setup

Setup Mac OS X

I've done the same process every couple years since 2013 (Mountain Lion, Mavericks, High Sierra, Catalina) and I updated the Gist each time I've done it.

I kinda regret for not using something like Boxen (or anything similar) to automate the process, but TBH I only actually needed to these steps once every couple years...

@andreyvit
andreyvit / tmux.md
Created June 13, 2012 03:41
tmux cheatsheet

tmux cheat sheet

(C-x means ctrl+x, M-x means alt+x)

Prefix key

The default prefix is C-b. If you (or your muscle memory) prefer C-a, you need to add this to ~/.tmux.conf:

remap prefix to Control + a

@mikhailov-work
mikhailov-work / turbo_colormap.py
Created August 8, 2019 23:31
Turbo Colormap Look-up Table
# Copyright 2019 Google LLC.
# SPDX-License-Identifier: Apache-2.0
# Author: Anton Mikhailov
turbo_colormap_data = [[0.18995,0.07176,0.23217],[0.19483,0.08339,0.26149],[0.19956,0.09498,0.29024],[0.20415,0.10652,0.31844],[0.20860,0.11802,0.34607],[0.21291,0.12947,0.37314],[0.21708,0.14087,0.39964],[0.22111,0.15223,0.42558],[0.22500,0.16354,0.45096],[0.22875,0.17481,0.47578],[0.23236,0.18603,0.50004],[0.23582,0.19720,0.52373],[0.23915,0.20833,0.54686],[0.24234,0.21941,0.56942],[0.24539,0.23044,0.59142],[0.24830,0.24143,0.61286],[0.25107,0.25237,0.63374],[0.25369,0.26327,0.65406],[0.25618,0.27412,0.67381],[0.25853,0.28492,0.69300],[0.26074,0.29568,0.71162],[0.26280,0.30639,0.72968],[0.26473,0.31706,0.74718],[0.26652,0.32768,0.76412],[0.26816,0.33825,0.78050],[0.26967,0.34878,0.79631],[0.27103,0.35926,0.81156],[0.27226,0.36970,0.82624],[0.27334,0.38008,0.84037],[0.27429,0.39043,0.85393],[0.27509,0.40072,0.86692],[0.27576,0.41097,0.87936],[0.27628,0.42118,0.89123],[0.27667,0.43134,0.90254],[0.27691,0.44145,0.913
@callumlocke
callumlocke / scale-canvas.ts
Last active April 12, 2024 03:25
How to fix a canvas so it will look good on retina/high-DPI screens.
/*
UPDATED for 2023 - Now much simpler. The old tricks are no longer needed.
The following code makes an 800×600 canvas that is always as sharp as possible for the device.
You still draw on it as if it's the logical size (800×600 in this case), but everything just
looks sharper on high-DPI screens. Regular non-sharp screens are not affected.
*/
const width = 800
# Prepare world data
# First up, we need to load the built-up area data that we’re going to be plotting. We download this from the European Commission’s Global Human Settlement Data portal [https://ghsl.jrc.ec.europa.eu/datasets.php] — specifically using the links from this page [http://cidportal.jrc.ec.europa.eu/ftp/jrc-opendata/GHSL/GHS_BUILT_LDSMT_GLOBE_R2015B/]. We want the 250m-resolution rasters for 1975 and 2015 (GHS_BUILT_LDS1975_GLOBE_R2016A_54009_250 and GHS_BUILT_LDS2014_GLOBE_R2016A_54009_250).
# Once you’ve downloaded these (they’re BIG, so might take a little while...), we can save ourselves a lot of hassle later on by re-projecting them into the same co-ordinate space as the other data we’re going to be using. Specifically we want to change their units from metres to lat/lon. We do this by:
# 1) Unzipping the archive, and then
# 2) Running the following script on the command-line:
# gdalwarp -t_srs EPSG:4326 -tr 0.01 0.01 path/to/your/built-up-area.tif path/to/your/built-up-area_reprojected.
@briantjacobs
briantjacobs / storytelling_from_space.md
Last active February 18, 2024 10:02
Storytelling from Space

Storytelling from Space: Tools/Resources

This list of resources is all about acquring and processing aerial imagery. It's generally broken up in three ways: how to go about this in Photoshop/GIMP, using command-line tools, or in GIS software, depending what's most comfortable to you. Often these tools can be used in conjunction with each other.

Acquiring Landsat & MODIS

Web Interface

  • Landsat archive
@prophetgoddess
prophetgoddess / pixelsort.py
Last active November 24, 2023 11:39
Python pixel sorting.
# The MIT License (MIT)
# Copyright (c) 2014 Lycaon (lycaon.me)
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
@mbostock
mbostock / README.md
Last active June 7, 2023 18:33
Underscore’s Equivalents in D3

Collections

each(array)

Underscore example:

_.each([1, 2, 3], function(num) { alert(num); });
@jasonrdsouza
jasonrdsouza / combineS3Files.py
Last active June 3, 2023 17:22
Python script to efficiently concatenate S3 files
'''
This script performs efficient concatenation of files stored in S3. Given a
folder, output location, and optional suffix, all files with the given suffix
will be concatenated into one file stored in the output location.
Concatenation is performed within S3 when possible, falling back to local
operations when necessary.
Run `python combineS3Files.py -h` for more info.
'''