| """ | |
| realertime.lib.spawn | |
| ~~~~~~~~~~~~~~~~~~~~ | |
| :author: Adam Hitchcock | |
| :copyright: (c) 2012 DISQUS. | |
| :license: Apache License 2.0, see LICENSE for more details. | |
| """ | |
| from __future__ import absolute_import |
| import numpy as np | |
| class Resample(object): | |
| def __init__(self, cv, method='under'): | |
| self.cv = cv | |
| self.method = method | |
| def split(self, X, y, **kwargs): | |
| for train_idx, test_idx in self.cv.split(X, y, **kwargs): | |
| counts = np.bincount(y[train_idx]) # assumes y are from {0, 1..., n_classes-1} |
| """ | |
| A decorator for management commands (or any class method) to ensure that there is | |
| only ever one process running the method at any one time. | |
| Requires lockfile - (pip install lockfile) | |
| Author: Ross Lawley | |
| """ | |
| import time |
| brew install qt # should already be done | |
| brew install qwt # should already be done | |
| brew install portaudio # should already be done | |
| brew install wget # makes some downloading easier | |
| # set up your virtualenv (`workon friture` if you've already created it) | |
| mkvirtualenv friture | |
| cd /tmp |
| #!/usr/bin/env python26 | |
| import logging | |
| import pika | |
| logging.basicConfig() | |
| class Consumer(object): | |
| """ | |
| A RabbitMQ topic exchange consumer that will call the specified function |
| [user] | |
| name = My name | |
| email = my_github_email@example.com | |
| [alias] | |
| a = add | |
| ap = add -p | |
| can = commit -S --amend --no-edit | |
| cm = commit -S -m | |
| co = checkout |
| # coding=UTF8 | |
| ######################################################################### | |
| # This class is to help sklearn to handle statistical process # | |
| # Author: Joon Lim from Master of Science in Analytics at Northwestern # | |
| # Date: 04.23.2013 # | |
| ######################################################################### | |
| ''' this Module is built on top of numpy and sklearn. ''' | |
Author: Fernando Pérez.
A demonstration of how to use Python, Julia, Fortran and R cooperatively to analyze data, in the same process.
This is supported by the IPython kernel and a few extensions that take advantage of IPython's magic system to provide low-level integration between Python and other languages.
See the companion notebook for data preparation and setup.
