achille

Howdy folks

This is an attempt at standardizing the intro threads, and instructions on how to include a student map in them. Note the map & question set may be added to existing Piazza threads.

Steps:

Create a Google Map

Login to Google Maps, create a new Map
Menu -> Your Places -> Maps -> Create Map

Keybase proof

I hereby claim:

I am achille on github.
I am achille (https://keybase.io/achille) on keybase.
I have a public key whose fingerprint is 381B A447 5045 5140 AC05 46D2 A1D0 FF17 221A 89BF

To claim this, I am signing this object:

	// compactness() calculates how closely the resulting documents are located together
	// It counts the size of the documents vs size of the unique pages they reside on

	function compactness(collection, query, limit) {
	Object.size = function(o) { var size = 0, key;
	for (key in o) { if (o.hasOwnProperty(key)) size++; }
	return size; };

	count=0;
	size=0;

	import numpy as np
	import scipy.optimize as spo
	ir = lambda n: int(round(n))

	# Constants
	s_freq = 500 #server-server heartbeat frequency ms
	c_freq = 10000 #client-server heartbeat frequency ms

	# Simulation boundaries
	threshold = 300000 # 5 minute max lag/skew

	/*
	* Auto-tuning delete that allows for removal of large amounts of data
	* without impacting performance. Configurable to a target load amount.
	*
	* How it works:
	* TL;DR: Delete a small slice every second; Vary the size of each slice
	* based on how long the previous delete took; sleep; repeat.
	*
	* TODO: Modify this to allow for deletion based on objectid's date
	* which is embedded in the first four bytes.

	/* Check for gaps or duplicates in keyspace */

	function check_keyspace(ns) {
	print("Checking: " + ns);
	str = JSON.stringify
	forwardCount=0;
	reverseCount=0;
	min = db.chunks.find(ns).pretty().sort({min: 1}).limit(1)[0]
	max = db.chunks.find(ns).pretty().sort({min:-1}).limit(1)[0]
	current = min

	"""
	Vitter JS (1987) 'An efficient algorithm for sequential
	random sampling.' ACM T. Math. Softw. 13(1): 58--67.

	Copied from: https://gist.github.com/ldoddema/bb4ba2d4ad1b948a05e0
	"""

	from math import exp, log
	import random
	import numpy as np

	//Create 1gb collection & enqueue
	for(i=0;i<1000;i++){db.foo.insert({f:''.pad(1024*1024,true,'A')})}
	enqueueWork("test.foo")

	//Each worker calls dequeue() and works on it's own range
	work = dequeue("test.foo")


	function enqueueWork(ns,splitSizeBytes=320000000){
	split = db.runCommand({splitVector:ns, keyPattern:{_id: 1},

	import cv2
	import os

	#call visualize(QTable) tod display the qtable
	#Press space to proceed, and q to exit (Frame render pauses execution)

	def write(image, output_dir="visualize", name=None, is_test_image=False):
	if not os.path.exists(output_dir):
	os.makedirs(output_dir)
	if name is None:

	// compares MongoDB regular Indexes vs using MultiKey & Elematch

	/* // regular index:
	{ "field0": 0,
	"field1": 1,
	"field2": 2 ... etc }

	MultiKey index:
	{ "props": [
	{ "field": "field0", "value": 0 },