palday

library(shiny)
library(ggplot2)
library(gridExtra)
library(scales)
library(reshape2)
library(zoo)


shinyServer(function(input, output) {
  output$distribution <- renderPlot({

palday

#! /usr/bin/python2

import sys
import codecs
from bibtexparser.bparser import BibTexParser

non_local_fields = ['address',
                    'annote',
                    'author',
                    'booktitle',

palday

#! /bin/bash

# prep and chroot into the existing system
sudo mkdir -p /mnt/root
sudo mount /dev/sda4 /mnt/root/
sudo mount -t proc none /mnt/root/proc/
sudo mount -o bind /dev /mnt/root/dev
sudo mount --bind /sys /mnt/root/sys
sudo chroot /mnt/root/ /bin/bash

palday

hg bookmarks | awk '{if (NF == 3) print $2; else print $1;}' | xargs -n 1 hg push -f -B

palday

sudo apt-get build-dep atlas
sudo apt-get install  build-essential dpkg-dev cdbs devscripts gfortran liblapack-dev liblapack-pic 
sudo apt-get source atlas
cd atlas*
sudo fakeroot debian/rules custom
# set n equal to the number of cpus (including virtual HT cpus) minus one
for i in {0..n}; do sudo cpufreq-set -g performance -c$i; done 
sudo fakeroot debian/rules custom
sudo apt-get install libatlas-base-dev libatlas-base
sudo dpkg -i libatlas3gf-*.de

palday

#! /usr/bin/env python
# -*- coding: utf-8 -*-

# License: CC-BY-NC-SA 3.0

import re
import codecs

# download kate_chopin_the_awakening_and_other_short_stories.txt
# from Project Gutenberg:

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packages.rforge <- c(
"R2admb"
,"lme4.0"
,"glmmADMB"
)

rforge.prefix <- c(
""
,"lme4."
,"coefplot2."

palday

tr < file-with-nulls -d '\000' > file-without-nulls

sed 's/\x0//g' file-with-nulls > file-without-nulls

sed 's/\x0/ /g' file-with-nulls > file-without-nulls

grep -P '\000' < file-with-nulls >file-without-nulls

awk '/\000/ { print }'

palday

using Random, DataFrames, MixedModels, PooledArrays
gendata(n::Int, nID::Int, nested=true) = gendata(MersenneTwister(42), n, nID, nested)

function gendata(rng::AbstractRNG, n::Int, nID::Int, nested::Bool)
    df = DataFrame(y = zeros(n),
                   w = rand(rng, n),
                   x = rand(rng, n),
                   z = rand(rng, n),
                   sex = CategoricalArray([randstring(rng,"mf",1) for ii in 1:n]),
                   group = CategoricalArray(rand(rng, 1:5, n)),

palday

using MixedModels, RCall, GLM

R"library(lme4)"
R"library(languageR)"
R"lexdec = as.data.frame(lexdec)";
R"lexdec$rt_raw = exp(lexdec$RT)";
R"ldform = rt_raw ~ 1 + Class * NativeLanguage + (1 | Subject) + (1 | Word)";
R"""summary(ldmod <- glmer(ldform, lexdec, family=Gamma(link="identity"),nAGQ=0))"""
lexdec = rcopy(R"lexdec");
ldform = @formula(rt_raw ~ 1 + Class * NativeLanguage + (1 | Subject) + (1 | Word));