Beau Cronin beaucronin

## crp_generator.py
from random import random

def crpgen(N = None, alpha = 1.0):
  """
  A generator that implements the Chinese Restaurant Process
  """
  counts = []
  n = 0
  while N == None or n < N:
    # Compute the (unnormalized) probabilities of assigning the new object

## gist:2229f825095db7d7dfd2
import requests
import json

URL_BASE = 'https://rest.developer.yodlee.com/services/srest/restserver/v1.0'

# assumes you've signed up for dev access, and already done the one-time linking of bank accounts
# to user accounts via the Yodlee website

# cobrand login
payload = { 'cobrandLogin': 'sbCob<account>', 'cobrandPassword': '<something>' }

## greenbushes_tantalum.json
{
    "observer": {
        "email": "beau.cronin@gmail.com"
    },
    "method": {
        "mode": "web",
        "platform": "orbital",
        "identity": "3rdparty",
        "encoding": "human"
    },

## index.html
<div id="mapid"></div>

## iris.csv

          
            sepal_length
            sepal_width
            petal_length
            petal_width
            class

            
              5.1
              3.5
              1.4
              0.2
              Iris-setosa

            
              4.9
              3.0
              1.4
              0.2
              Iris-setosa

            
              4.7
              3.2
              1.3
              0.2
              Iris-setosa

            
              4.6
              3.1
              1.5
              0.2
              Iris-setosa

            
              5.0
              3.6
              1.4
              0.2
              Iris-setosa

            
              5.4
              3.9
              1.7
              0.4
              Iris-setosa

            
              4.6
              3.4
              1.4
              0.3
              Iris-setosa

            
              5.0
              3.4
              1.5
              0.2
              Iris-setosa

            
              4.4
              2.9
              1.4
              0.2
              Iris-setosa

## gist:0a0517d58e21dbc3d241ee3b647df60f
Verifying my Blockstack ID is secured with the address 18UUDfVMEwcVHGtjM8jqxzHvLSX95i6fJ9 https://explorer.blockstack.org/address/18UUDfVMEwcVHGtjM8jqxzHvLSX95i6fJ9

## correlation_examples.R
#From http://en.wikipedia.org/wiki/File:Correlation_examples2.svg

#Title: An example of the correlation of x and y for various distributions of (x,y) pairs
#Tags: Mathematics; Statistics; Correlation
#Author: Denis Boigelot
#Packets needed : mvtnorm (rmvnorm), RSVGTipsDevice (devSVGTips)
#How to use: output()
#
#This is an translated version in R of an Matematica 6 code by Imagecreator.

## README.md

      
              3 files
            
          
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                beaucronin
                / README.md
            
            
              Last active
              October 26, 2016 22:01
            
              
                SSH into an EC2 instance by tag
              
          
    Usage:
$ ec2-login-amazon <tag>

Aside from the AWS CLI tools, you'll need jq: https://stedolan.github.io/jq/
If multiple instances have the tag you specify, the first one will be chosen
There are separate commands for Amazon Linux and Ubuntu because, aside from looking at the AMI ID, there's no way to know which user name to use


## keybase.md

      
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                beaucronin
                / keybase.md
            
            
              Created
              May 31, 2016 17:47
            
          
    Keybase proof

I hereby claim:

I am beaucronin on github.
I am beaucronin (https://keybase.io/beaucronin) on keybase.
I have a public key ASA8QFopPai5WRhYagivUf6FMWlePH57Q7CPv5R3NK3Irgo

To claim this, I am signing this object:

  
## gist:3094654
import veritable
import csv
import matplotlib.pyplot as plt

# Load the csv and read into a Veritable dataset using inches and pounds
print 'Reading data from file'
data_inches_pounds = []
with open('heights_weights_genders.csv') as fd:
    rd = csv.reader(fd)
    rd.next() # skip the header
	from random import random

	def crpgen(N = None, alpha = 1.0):
	"""
	A generator that implements the Chinese Restaurant Process
	"""
	counts = []
	n = 0
	while N == None or n < N:
	# Compute the (unnormalized) probabilities of assigning the new object
	import requests
	import json

	URL_BASE = 'https://rest.developer.yodlee.com/services/srest/restserver/v1.0'

	# assumes you've signed up for dev access, and already done the one-time linking of bank accounts
	# to user accounts via the Yodlee website

	# cobrand login
	payload = { 'cobrandLogin': 'sbCob<account>', 'cobrandPassword': '<something>' }
	{
	"observer": {
	"email": "beau.cronin@gmail.com"
	},
	"method": {
	"mode": "web",
	"platform": "orbital",
	"identity": "3rdparty",
	"encoding": "human"
	},
sepal_length	sepal_width	petal_length	petal_width	class
5.1	3.5	1.4	0.2	Iris-setosa
4.9	3.0	1.4	0.2	Iris-setosa
4.7	3.2	1.3	0.2	Iris-setosa
4.6	3.1	1.5	0.2	Iris-setosa
5.0	3.6	1.4	0.2	Iris-setosa
5.4	3.9	1.7	0.4	Iris-setosa
4.6	3.4	1.4	0.3	Iris-setosa
5.0	3.4	1.5	0.2	Iris-setosa
4.4	2.9	1.4	0.2	Iris-setosa
	#From http://en.wikipedia.org/wiki/File:Correlation_examples2.svg

	#Title: An example of the correlation of x and y for various distributions of (x,y) pairs
	#Tags: Mathematics; Statistics; Correlation
	#Author: Denis Boigelot
	#Packets needed : mvtnorm (rmvnorm), RSVGTipsDevice (devSVGTips)
	#How to use: output()
	#
	#This is an translated version in R of an Matematica 6 code by Imagecreator.
	import veritable
	import csv
	import matplotlib.pyplot as plt

	# Load the csv and read into a Veritable dataset using inches and pounds
	print 'Reading data from file'
	data_inches_pounds = []
	with open('heights_weights_genders.csv') as fd:
	rd = csv.reader(fd)
	rd.next() # skip the header