ahlusar1989

// Flyweight.js - Copyright Addy Osmani, 2012.
// Consider public domain
// My implementation in JS of this:
// http://en.wikipedia.org/wiki/Flyweight_pattern

// Simulate pure virtual inheritance/'implement' keyword for JS
Function.prototype.implementsFor = function (parentClassOrObject) {
    if (parentClassOrObject.constructor == Function) {
        // Normal Inheritance 
        this.prototype = new parentClassOrObject;

ahlusar1989

// installed Clojure packages:
// 
// * BracketHighlighter
// * lispindent
// * SublimeREPL
// * sublime-paredit

{
  "word_separators": "/\\()\"',;!@$%^&|+=[]{}`~?",
  "paredit_enabled": true,

ahlusar1989

import multiprocessing
import pandas as pd
import numpy as np

def _apply_df(args):
    df, func, kwargs = args
    return df.apply(func, **kwargs)

def apply_by_multiprocessing(df, func, **kwargs):
    workers = kwargs.pop('workers')

ahlusar1989

Contours of San Francisco overlayed over OpenStreeMap vector tiles using code from mbostock's vector tiles with multiple layers example. View the hi-res file

See gist for code used to generate contours.

ahlusar1989

from __future__ import division
from numpy import *

class AdaBoost:

    def __init__(self, training_set):
        self.training_set = training_set
        self.N = len(self.training_set)
        self.weights = ones(self.N)/self.N
        self.RULES = []

ahlusar1989

# -*- coding: utf-8 -*-
""" Small script that shows hot to do one hot encoding
    of categorical columns in a pandas DataFrame.

    See:
    http://scikit-learn.org/dev/modules/generated/sklearn.preprocessing.OneHotEncoder.html#sklearn.preprocessing.OneHotEncoder
    http://scikit-learn.org/dev/modules/generated/sklearn.feature_extraction.DictVectorizer.html
"""
import pandas
import random

ahlusar1989

{"error": 42716.2954, "samples": 506, "value": [22.532806324110698], "label": "RM <= 6.94", "type": "split", "children": [{"error": 17317.3210, "samples": 430, "value": [19.93372093023257], "label": "LSTAT <= 14.40", "type": "split", "children": [{"error": 6632.2175, "samples": 255, "value": [23.349803921568636], "label": "DIS <= 1.38", "type": "split", "children": [{"error": 390.7280, "samples": 5, "value": [45.58], "label": "CRIM <= 10.59", "type": "split", "children": [{"error": 0.0000, "samples": 4, "value": [50.0], "label": "Leaf - 4", "type": "leaf"}, {"error": 0.0000, "samples": 1, "value": [27.9], "label": "Leaf - 5", "type": "leaf"}]}, {"error": 3721.1632, "samples": 250, "value": [22.90520000000001], "label": "RM <= 6.54", "type": "split", "children": [{"error": 1636.0675, "samples": 195, "value": [21.629743589743576], "label": "LSTAT <= 7.57", "type": "split", "children": [{"error": 129.6307, "samples": 43, "value": [23.969767441860473], "label": "TAX <= 222.50", "type": "split", "children": [{"err

ahlusar1989

ahlusar1989

def invalid_xml_remove(c):
    #http://stackoverflow.com/questions/1707890/fast-way-to-filter-illegal-xml-unicode-chars-in-python
    illegal_unichrs = [ (0x00, 0x08), (0x0B, 0x1F), (0x7F, 0x84), (0x86, 0x9F),
                    (0xD800, 0xDFFF), (0xFDD0, 0xFDDF), (0xFFFE, 0xFFFF),
                    (0x1FFFE, 0x1FFFF), (0x2FFFE, 0x2FFFF), (0x3FFFE, 0x3FFFF),
                    (0x4FFFE, 0x4FFFF), (0x5FFFE, 0x5FFFF), (0x6FFFE, 0x6FFFF),
                    (0x7FFFE, 0x7FFFF), (0x8FFFE, 0x8FFFF), (0x9FFFE, 0x9FFFF),
                    (0xAFFFE, 0xAFFFF), (0xBFFFE, 0xBFFFF), (0xCFFFE, 0xCFFFF),
                    (0xDFFFE, 0xDFFFF), (0xEFFFE, 0xEFFFF), (0xFFFFE, 0xFFFFF),

ahlusar1989

"""Playing with tornado.websocket, to add markers to a Google Map using WebSockets

$ pip install tornado
$ python livemap.py --port=8888

Open http://localhost:8888 in one window

Each time http://localhost:8888/ping is opened in a second window, a
new marker is added to the map (at a random location)