gurgeh

function prompt_char {
    git branch >/dev/null 2>/dev/null && echo '±' && return
    hg root >/dev/null 2>/dev/null && echo '☿' && return
    echo '%(!.!.➜)'
}


function parse_hg_dirty {
  if [[ -n $(hg status -mard . 2> /dev/null) ]]; then
    echo "$ZSH_THEME_HG_PROMPT_DIRTY"

gurgeh

# Path to your oh-my-zsh configuration.
ZSH=$HOME/.oh-my-zsh

# Set name of the theme to load.
# Look in ~/.oh-my-zsh/themes/
# Optionally, if you set this to "random", it'll load a random theme each
# time that oh-my-zsh is loaded.
ZSH_THEME="gurgeh"

gurgeh

//Having to include so many different header files to do basic
//things like open a file, use strings, vectors and tuples, etc,
//is still annoying.
#include <fstream>
#include <vector>
#include <map>
#include <tuple>
#include <string>

//To use C++11 lambdas with Boost lambdas we define this.

gurgeh

#include <vector>
#include <string>
#include <map>
#include <iostream>

using namespace std;

/*
d = {"primes" : [2, 3, 5, 7],
     "fib": [1, 1, 2, 3]}

gurgeh

<?xml version="1.0"?>
<!-- See http://gnaural.sourceforge.net -->
<schedule>
<gnauralfile_version>1.20101006</gnauralfile_version>
<gnaural_version>1.0.20110606</gnaural_version>
<date>Mon Jan 28 15:15:33 2013
</date>
<title>Quick meditation</title>
<schedule_description>15 min isochronic 4 Hz meditation followed by 45 minutes 35 Hz</schedule_description>
<author>David Fendrich</author>

gurgeh

import random

def timeto(nguys, nwins):
  guys = [0] * nguys
  i = 0
  while True:
    i += 1
    j = random.randrange(0, nguys)
    guys[j] += 1
    if guys[j] == nwins:

gurgeh

import csv
import os

def add_all(path, prefix):
    rows = []
    first = True
    for fname in os.listdir(path):
        if fname.startswith(prefix):
            with open(os.path.join(path, fname)) as inf: # join path and filename
                c = csv.reader(inf)

gurgeh

import csv
import sys

from scipy import spatial

def compare_year(d, y1, cluster, y2):
  dist = []
  for vec in d[y2]:
    dist.append(spatial.distance.cosine(d[y1][cluster], vec))
  best = [(score, i) for (i, score) in enumerate(dist)]