zed

#!/usr/bin/env python
"""Find height, width of the largest rectangle containing all 0's in the matrix.

The algorithm for `max_size()` is suggested by @j_random_hacker [1].
The algorithm for `max_rectangle_size()` is from [2].
The Python implementation [3] is dual licensed under CC BY-SA 3.0
and ISC license.

[1]: http://stackoverflow.com/questions/2478447/find-largest-rectangle-containing-only-zeros-in-an-nn-binary-matrix#comment5169734_4671342

trey

Creating a Happy Git Environment on OS X

Step 1: Install Git

brew install git bash-completion

Configure things:

git config --global user.name "Your Name"

git config --global user.email "you@example.com"

ajmendez

import urllib2, json, pprint, re, datetime
import mwparserfromhell

def _parseDate(wikiDate):
  ''' Parse a mediawiki date template -- assumes years, month, day
  Input:
    a mwparser object containing just the date to be parsed
  Returns:
    datetime.date object of the date
  '''

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

ijy

Sublime Text 3 Setup

Install Package Control

Install Package Control for easy package management.

1. Open the console with Ctrl+`
2. Paste in the following:

jakevdp

# By Jake VanderPlas
# License: BSD-style

import matplotlib.pyplot as plt
import numpy as np


def discrete_cmap(N, base_cmap=None):
    """Create an N-bin discrete colormap from the specified input map"""

nbremer

height: 750

model_selection.ipynb

warmlogic

# calculate and visualize silhouette score from k-means clustering.
# plots first two features in 2D and first three features in 3D.
# from: http://scikit-learn.org/stable/auto_examples/cluster/plot_kmeans_silhouette_analysis.html

from sklearn.cluster import KMeans
from sklearn.metrics import silhouette_score, silhouette_samples
from mpl_toolkits.mplot3d import Axes3D

##### cluster data into K=1..K_MAX clusters #####
K_MAX = 10

cfperez

from sklearn.base import BaseEstimator,TransformerMixin

class LogTransformer(BaseEstimator,TransformerMixin):
    def __init__(self, constant=1, base='e'):
        from numpy import log,log10
        if base == 'e' or base == np.e:
            self.log = log
        elif base == '10' or base == 10:
            self.log = log10
        else: