AndrewWalker

import argparse
import sys
import os

def ssh_copy_id(host='localhost', ssh='ssh', keyfile='~/id_rsa.pub', sshopts=()):
    opts = ' '.join('-o ' + opt for opt in sshopts )
    cmd = 'cat %(keyfile)s | %(ssh)s %(opts)s %(host)s \'umask 077; mkdir -p .ssh; cat >> .ssh/authorized_keys\''
    os.system(cmd % locals())

if __name__ == "__main__":

AndrewWalker

from clang.cindex import *

def is_function_call(funcdecl, c):
    """ Determine where a call-expression cursor refers to a particular function declaration
    """
    defn = c.get_definition()
    return (defn is not None) and (defn == funcdecl)

def fully_qualified(c):
    """ Retrieve a fully qualified function name (with namespaces)

AndrewWalker

import scommon

scommon.sconscript_validator(Environment)

menv = Environment()
menv.SConscript('SConscript', exports=['menv'])

AndrewWalker

# IPython notebook build process for Ubuntu 12.04 from pypi
#
#  This is probably very far from good practice for docker, but it's a demonstration
#  of how to get very precise control of an environment that suitable for testing
#
# docker build -t ipynb .
# docker run -t -i -p 127.0.0.1:8888:8888 ipynb

FROM ubuntu

AndrewWalker

# Based on "Approximate Inversion of the Laplace Transform" by Cheng and Sidauruk, 
# in the Mathematica Journal, vol 4, issue 2, 1994
import scipy.misc

fact = scipy.misc.factorial

def csteh(n, i):
    acc = 0.0
    for k in xrange(int(np.floor((i+1)/2.0)), int(min(i, n/2.0))+1):
        num = k**(n/2.0) * fact(2 * k)

AndrewWalker

# This is a python port of the minimum time solution of the double integrator 
# (with no damping) minimum time value iteration problem, based on the course notes of
# MIT OCWs Underactuated robotics.  
#
# The original material that this work is derived from is:
#
# Prof. Russel Tedrake, Underactuated Robotics, Spring 2009. (Massachusetts Institute of # Technology: MIT OpenCouseWare), http://ocw.mit.edu (Accessed May 2012). License: 
# Creative Commons BY-NC-SA

import sys

AndrewWalker

import numpy as np
import matplotlib.pyplot as plt 
from scipy.integrate import odeint
import glob
import os

def simple_pendulum_deriv(x, t, m, g, l): 
    """The simple pendulum subject to zero damping and zero control input

    Based on material from the MIT OCW subject "Underactuated Robotics"