gilesc

(defn levenshtein [vec1 vec2]
  (cond (empty? vec1) (count vec2)
	(empty? vec2) (count vec1)
	:else
	(let [distance (make-array Integer (count vec1) (count vec2))]
	  (doseq [i (range (count vec1))]
	    (aset distance i 0 i))
	  (doseq [j (range (count vec2))]
	    (aset distance 0 j j))
	  (doseq [i (range 1 (count vec1))]

gilesc

from numpy import argmax
from scipy import arange
from scipy.io import wavfile
from scipy.fftpack import fftfreq, rfft, fftshift
import pylab

sample_rate, signal =  wavfile.read("goodnight.wav")


N = len(signal)

gilesc

(require '[net.cgrand.enlive-html :as html])

(defn fetch-url [url]
  (html/html-resource
   (java.net.URL. url)))

(defn fetch-twss [n]
  (drop-last 2
             (map #(second (re-find #"\"(.+?)\"" (html/text %)))
                  (html/select

gilesc

import re
print [g.start() for g in re.finditer("AT", "CAAATATGAGACATAGACATAGACAGATACG")]

#to match any base (really, any character), use a dot:
print [g.start() for g in re.finditer("G.G", "CAAATATGAGACATAGACATAGACAGAGACG")]

#to match a subgroup:
print [g.start() for g in re.finditer("[AT][AT]", "CAAATATGAGACATAGACATAGACAGAGACG")]

gilesc

--- a/Rakefile
+++ b/Rakefile

@@ -163,7 +163,7 @@ desc "deploy public directory to github pages"
 task :push do
   puts "## Deploying branch to Github Pages "
   (Dir["#{deploy_dir}/*"]).each { |f| rm_rf(f) }
-  system "cp -R #{public_dir}/ #{deploy_dir}"
+  system "cp -R #{public_dir}/* #{deploy_dir}"
   puts "\n## copying #{public_dir} to #{deploy_dir}"

gilesc

Religiosity negatively correlated with:

- IQ [1]
- Societal health (homicide, suicide, life expectancy) [2]
- hippocampus (part of the brain involved in memory) size [7]

and positively correlated with:
- abortion rates (!) [2]
- poverty [3]
- teen pregnancy [4]

gilesc

extern mod std;

fn main() {
    let s = @"foo bar baz";
    // similar results with ~"foo bar baz"

    // These work
    s.substr(1, 5);
    s.slice(1,5);

gilesc

module app1;

import std.stdio;

import lib1;

void main() {
    add(2,3).println;
}

gilesc

#!/usr/bin/env bash

cat <<EOF | ftp
open hgdownload.cse.ucsc.edu
anonymous
[email protected]
cd goldenPath/mm9/database
prompt
mget chr*rmsk.txt.gz
bye

gilesc

import os

import psutil
import numpy as np
import sklearn.decomposition

def memory_usage():
    return psutil.Process(os.getpid()).memory_info().rss / 1024 ** 2

def pca(X):