minrk

import time
import random

from IPython import parallel

# create client & view
rc = parallel.Client()
dv = rc[:]

# scatter 'id', so id=0,1,2 on engines 0,1,2

hadley

ks.default <- function(rows) seq(2, max(3, rows %/% 4))

many_kmeans <- function(x, ks = ks.default(nrow(x)), ...) {
  ldply(seq_along(ks), function(i) {
    cl <- kmeans(x, centers = ks[i], ...)
    data.frame(obs = seq_len(nrow(x)), i = i, k = ks[i], cluster = cl$cluster)
  })
}

all_hclust <- function(x, ks = ks.default(nrow(x)), point.dist = "euclidean", cluster.dist = "ward") {

vsajip

import logging

class QueueHandler(logging.Handler):
    """
    This handler sends events to a queue. Typically, it would be used together
    with a multiprocessing Queue to centralise logging to file in one process
    (in a multi-process application), so as to avoid file write contention
    between processes.

    This code is new in Python 3.2, but this class can be copy pasted into

ctokheim

Stacked and Grouped Bar Plot

Oddly enough ggplot2 has no support for a stacked and grouped (position="dodge") bar plot. The seaborn python package, although excellent, also does not provide an alternative. However, I knew it was surely possible to make such a plot in regular matplotlib. Matplotlib, although sometimes clunky, gives you enough flexibility to precisely place plotting elements which is needed for a stacked and grouped bar plot.

Below is a working example of making a stacked and grouped bar plot.

import seaborn as sns
import matplotlib.pyplot as plt
import numpy as np

stuaxo

# modified from https://gist.github.com/schlamar/2311116#file-processify-py-L17
# also see http://stackoverflow.com/questions/2046603/is-it-possible-to-run-function-in-a-subprocess-without-threading-or-writing-a-se

import inspect
import os
import sys
import traceback

from functools import wraps
from multiprocessing import Process, Queue

endolith

from __future__ import division
from numpy.fft import rfft
from numpy import argmax, mean, diff, log, nonzero
from scipy.signal import blackmanharris, correlate
from time import time
import sys
try:
    import soundfile as sf
except ImportError:
    from scikits.audiolab import flacread

seberg

def rolling_window(array, window=(0,), asteps=None, wsteps=None, axes=None, toend=True):
    """Create a view of `array` which for every point gives the n-dimensional
    neighbourhood of size window. New dimensions are added at the end of
    `array` or after the corresponding original dimension.
    
    Parameters
    ----------
    array : array_like
        Array to which the rolling window is applied.
    window : int or tuple

iamatypeofwalrus

What

Roll your own iPython Notebook server with Amazon Web Services (EC2) using their Free Tier.

What are we using? What do you need?

• An active AWS account. First time sign-ups are eligible for the free tier for a year
• One Micro Tier EC2 Instance
• With AWS we will use the stock Ubuntu Server AMI and customize it.
• Anaconda for Python.
• Coffee/Beer/Time

wadey

# Usage:
# source iterm2.zsh

# iTerm2 tab color commands
# https://iterm2.com/documentation-escape-codes.html

if [[ -n "$ITERM_SESSION_ID" ]]; then
    tab-color() {
        echo -ne "\033]6;1;bg;red;brightness;$1\a"
        echo -ne "\033]6;1;bg;green;brightness;$2\a"

vertexclique

MacOS

Build 3059

MD5: 59bab8f71f8c096cd3f72cd73851515d

Rename it to: Sublime Text

Make it executable with: chmod u+x Sublime\ Text