jpoehls

PS> time { ping -n 1 google.com } -Samples 10 -Silent
..........
Avg: 62.1674ms
Min: 56.9945ms
Max: 87.9602ms

PS> time { ping -n 1 google.com } -Samples 10 -Silent -Long
..........
Avg: 00:00:00.0612480
Min: 00:00:00.0572167

jexchan

Multiple SSH Keys settings for different github account

create different public key

create different ssh key according the article Mac Set-Up Git

$ ssh-keygen -t rsa -C "your_email@youremail.com"

bobthecat

bigcorPar <- function(x, nblocks = 10, verbose = TRUE, ncore="all", ...){
  library(ff, quietly = TRUE)
  require(doMC)
	if(ncore=="all"){
		ncore = multicore:::detectCores()
		registerDoMC(cores = ncore)
	} else{
		registerDoMC(cores = ncore)
	}

stared

Software for scientists

Some things takes much less time and stress once you know the right tool. Below, there is a community edited list of software for scientists.

Text editors

in General purpose text/code editors. It may be better to have a good editor for everything, than different ones for different languages, scripts, notes.

VGonPa

[General]
IniMode=true

[formats]
data\align-ampersand\bold=true
data\align-ampersand\fontFamily=<default>
data\align-ampersand\foreground=#dc322f
data\align-ampersand\italic=false
data\align-ampersand\overline=false
data\align-ampersand\pointSize=0

sighingnow

# Detect operating system in Makefile.
# Author: He Tao
# Date: 2015-05-30

OSFLAG 				:=
ifeq ($(OS),Windows_NT)
	OSFLAG += -D WIN32
	ifeq ($(PROCESSOR_ARCHITECTURE),AMD64)
		OSFLAG += -D AMD64
	endif

ebenolson

# Context manager to generate batches in the background via a process pool
# Usage:
#
# def batch(seed):
#    .... # generate minibatch
#    return minibatch
#
# with BatchGenCM(batch) as bg:
#    minibatch = next(bg)
#    .... # do something with minibatch

daroczig

m1 <- lm(mpg ~ hp, data = mtcars)
m2 <- lm(mpg ~ hp + drat, data = mtcars)
m3 <- lm(mpg ~ hp + drat + factor(gear), data = mtcars)

library(pander); library(memisc)
panderOptions('table.alignment.rownames', 'left')
pander(relabel(
    mtable(m1, m2, m3,
           summary.stats=c('N', 'R-squared', 'F')),
    '(Intercept)'       = 'Constant',

ericclemmons

Using <details> in GitHub

Suppose you're opening an issue and there's a lot noisey logs that may be useful.

Rather than wrecking readability, wrap it in a <details> tag!

<details>
 Summary Goes Here

kevinushey

# Place this in a file at '~/.Rprofile' to ensure it's sourced on startup
.First <- function() {
    # RStudio-specific startup
    if (!is.na(Sys.getenv("RSTUDIO", unset = NA)) &&
        Sys.info()[["sysname"]] == "Windows")
    {
        # work around mis-encoded environment variables
        USERPROFILE <- Sys.getenv("USERPROFILE")
        HOME <- file.path(USERPROFILE, "Documents", fsep = "\\")
        R_USER <- HOME