knthls

#!/usr/bin/env bash

set -Eeuo pipefail
trap cleanup SIGINT SIGTERM ERR EXIT

script_dir=$(cd "$(dirname "${BASH_SOURCE[0]}")" &>/dev/null && pwd -P)

usage() {
  cat <<EOF
Usage: $(basename "${BASH_SOURCE[0]}") [-h] [-v] -s my_service/semaphore -t my-distributed-task

knthls

# Isolate execution of set.seed (or anything else) in own env
s1 <- .GlobalEnv$.Random.seed

draw <- function(){
  eval({
    set.seed(12)
    samples = runif(10)   
  }, envir = new.env())
  
  samples

knthls

#/bin/bash

wd=$(mktemp -d)

docx_file=$1

if [ -z $docx_file ]; then
    echo "Usage: inspect_docx.sh []"
fi

knthls

# remove low variance columns
rna_data = rna_data.loc[:, (rna_data.var() > 0.5)]

# remove correlated columns
vars = rna_data.var()

tbd = []

# from each pair of highly correlated columns, remove columns with lower variance
for i, j in zip(*np.where(np.corrcoef(rna_data.values.T) > 0.5)):

knthls

"""
Basic Idea taken from http://stackoverflow.com/a/8111621/6420372
"""

import os
import socket
import subprocess
from select import select
import time
import contextlib

knthls

import os
import socket
import subprocess
from select import select
import time
import contextlib
import settings

try:
    import winreg