jFransham

Achieving warp speed with Rust

Contents:

• Number one optimization tip: don't
• Never optimize blindly
• Don't bother optimizing one-time costs
• Improve your algorithms
• CPU architecture primer
• Keep as much as possible in cache
• Keep as much as possible in registers

allejo

This snippet is no longer maintained on GitHub Gist and has moved to its own repository.

jblang

Emulators

VICE is the best by such a commanding margin that you really needn't look elsewhere. Open source and has the largest community.

However, other options are:

• CCS64, Lots of features, but I found it to be painfully slow. Shareware.
• Hoxs64. Decent, but not as full-featured as VICE. The ML monitor seems nice.
• Frodo is pretty outdated and the author admits as much.
• micro64 seems promising but incomplete.

zshaheen

How to Setup Automatic Uploads to Anaconda from Travis CI in 15 minutes

TL;DR: Edit .travis.yaml to install Anaconda and to run conda_upload.sh after testing. Edit meta.yaml to take in the environmental variables $VERSION and $CONDA_BLD_PATH. Create conda_upload.sh which sets the needed environmental variables, builds the tar archive, and uploads it to Anaconda. Finally edit some stuff on your Anaconda and Travis CI account so they can talk.

Intro

The following steps will detail how to automatically trigger Anaconda builds and uploads from Travis CI. This will only upload successful builds in the master branch and if there are multiple commits in a single day, it'll only keep the latest one. Both of these settings can easily be changed.

Edit .travis.yaml

First, edit .travis.yml so that it installs Anaconda.

install:

imneme

/*
 * Random-Number Utilities (randutil)
 *     Addresses common issues with C++11 random number generation.
 *     Makes good seeding easier, and makes using RNGs easy while retaining
 *     all the power.
 *
 * The MIT License (MIT)
 *
 * Copyright (c) 2015-2022 Melissa E. O'Neill
 *

mikelove

Issues with latex math in markdown files, for display on Github Pages (using jekyll)

Our solution: use kramdown parser, with GFM option (Github flavored Markdown). In the .Rmd, use $$ for display math and $ for inline math. then have a script which turns the inline math demarkation in the .md file from $ into $$ when appropriate (avoiding data frame usage), before uploading the .md to Github. This way, RStudio preview looks the same as the Github Pages version.

redcarpet math

• doesn't respect $ or $$ (will parse characters within these, such as _), but has workarounds:
• has a useful option, no_intra_emphasis, so underscores between ascii characters are not converted to <em> tags, so $x_1$ is fine
• need to escape underscores after non-ascii characters, for example $\mathbf{x}\_1$
• need to double escape curly bracket: \\{

ialhashim

#pragma once

// Code adapted from https://github.com/propanoid/DBSCAN

#include <vector>
#include <algorithm>
#include <omp.h>

// Any basic vector/matrix library should also work
#include <Eigen/Core>

fenbf

#include "particles.h"
#include <assert.h>
#include <algorithm>

namespace particles
{
	void ParticleData::generate(size_t maxSize)
	{
		m_count = maxSize;
		m_countAlive = 0;

killercup

/*
 * I add this to html files generated with pandoc.
 */

html {
  font-size: 100%;
  overflow-y: scroll;
  -webkit-text-size-adjust: 100%;
  -ms-text-size-adjust: 100%;
}

damonsk

# Send SMS messages using Raspberry Pi.
# Using gammu and Huawei E220

# Prepare SD card with wheezy.

# Login / complete rasp-config / reboot / login

# Set vimrc to prevent annoying ADBC arrow keys
cp /etc/vim/vimrc ~/.vimrc