keuv-grvl

loadOrInstall <- function(pkgname, CRANmirror.index=1) {
    chooseCRANmirror(ind=CRANmirror.index)
    if (! pkgname %in% installed.packages()[,1]) {
        write("installing", stderr())
        install.packages(pkgname, dep=T)
    } else { write("already installed", stderr()) }
    library(pkgname, character.only = TRUE)
    write("loaded",stderr())
}

keuv-grvl

Keybase proof

I hereby claim:

• I am keuv-grvl on github.
• I am keuvgrvl (https://keybase.io/keuvgrvl) on keybase.
• I have a public key whose fingerprint is 0D53 14FA F5B7 F41B 057D 9E19 FF46 2EC3 CA1D 38EE

To claim this, I am signing this object:

keuv-grvl

#!/usr/bin/env python3

# MetaGeneAnnotator: http://metagene.nig.ac.jp/

import argparse
import sys

_VERSION = "0.3"

keuv-grvl

#!/usr/bin/env bash

# trap signals
trap vmsavestate INT

function vmsavestate() {
    cleaner=$(head -c $(( $(tput cols) - 1 )) < /dev/zero | tr '\0' ' ')
    echo -en "\r${cleaner}\rSaving state of 'win7word' "
    vboxmanage controlvm win7word savestate
}

keuv-grvl

#!/usr/bin/env bash

docker run  \
  --volume $(pwd):/data  \
  --user $(id -u $USER):$(id -g $USER)  \
  --entrypoint /path/to/your_program  \
  CONTAINER_NAME  \
  --input /data/inputfile --output /data/outputfile
  
# Will run '/path/to/your_program --input /data/inputfile --output /data/output' inside the container,

keuv-grvl

#!/usr/bin/env bash

# usage: toggle-vpn.sh vpn-name

set -e           # this script exits on error
set -o pipefail  # a pipeline returns error code if any command fails
set -u           # unset variables as an error, and immediately exit

command -v nmcli > /dev/null  # ensure nmcli is installed

keuv-grvl

#!/usr/bin/env python3

import argparse
import gzip
import logging
import sys
from time import time

from lxml import etree

keuv-grvl

.PHONY: pdf display clean nuke

PDFREADER :=evince
OUTPUT    :=document.pdf
BUILD     :=build
SRC       :=$(shell find src -name '*.tex' -o -name '*.png')
LMKFLAGS   = -pdf -outdir=$(BUILD)

pdf: $(OUTPUT)

keuv-grvl

class FItSNE_wrapper:
    """
    Wrapper class for FItSNE `fast_tsne.fast_tsne` v1.1.0.
    It is currently designed to work in a Conda environment with Python 3.7 and FFTW 3.
    
    Install and compile as follow:
    
      $ conda create -n YOUR-ENV python=3.7 fftw=3
      $ source activate YOUR-ENV

keuv-grvl

[user]
	name = Keuv Grvl
	email = k***@***m
[core]
    quotepath = false
    editor = vim
    pager = less -F -x2
[init]
    defaultBranch = main
[push]