alexsavio

# based on http://www.damian.oquanta.info/posts/48-themes-for-your-ipython-notebook.html
# run this in a notebook

import os
import os.path as op
import subprocess
import urllib.request

theme_names = ['3024-dark',
               '3024-light',

alexsavio

import logging

# prints to stdout
FORMAT = '%(asctime)s - %(name)s - %(levelname)s - %(message)s'
logging.basicConfig(format=FORMAT)
log = logging.getLogger(__file__)
log.setLevel(logging.DEBUG)

# prints log to stdout and also saves to specified log file
log = logging.getLogger('my_logfile')

alexsavio

#!/bin/bash

qmake_path=$1
if [ -z "${qmake_path}" ]; then
    qmake_path=`which qmake`
fi
echo "Using qmake from ${qmake_path}. If you want to change, usage: install_pyqt_venv.sh qmake_path"

cwd=`pwd`
siproot=`find . -type d -name 'sip-*'`

alexsavio

# Written by Brendan O'Connor, [email protected], www.anyall.org
#  * Originally written Aug. 2005
#  * Posted to gist.github.com/16173 on Oct. 2008

#   Copyright (c) 2003-2006 Open Source Applications Foundation
#
#   Licensed under the Apache License, Version 2.0 (the "License");
#   you may not use this file except in compliance with the License.
#   You may obtain a copy of the License at
#

alexsavio

"""
Some python code for
Markov Chain Monte Carlo and Gibs sampling
by Bruce Walsh
"""


import numpy as np
import numpy.linalg as npla

alexsavio

# -*- coding: utf-8 -*-
"""Example Google style docstrings.

This module demonstrates documentation as specified by the `Google Python
Style Guide`_. Docstrings may extend over multiple lines. Sections are created
with a section header and a colon followed by a block of indented text.

Example:
  Examples can be given using either the ``Example`` or ``Examples``
  sections. Sections support any reStructuredText formatting, including

alexsavio

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

import os
import os.path as op
import base64
import argparse
import logging
from lxml import etree

alexsavio

'''
Non-parametric computation of entropy and mutual-information

Adapted by G Varoquaux for code created by R Brette, itself
from several papers (see in the code).

These computations rely on nearest-neighbor statistics
'''
import numpy as np

alexsavio

#!/usr/bin/env python

import os
import shutil
import tempfile
import logging
import argparse
import subprocess

alexsavio

import numpy as np

for x_idx, y_idx in zip(*np.triu_indices(n_elems, k=1)):