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beaucronin / gist:1258210
Created October 3, 2011 00:55
Metropolis sampler pseudocode
x = initial()
prob = target_dist(x)
for i in range(steps):
x_star = propose(x)
prob_star = target_dist(x)
if prob_star > prob or random() < prob_star / prob:
x = x_star
prob = prob_star
@beaucronin
beaucronin / crp_generator.py
Created October 9, 2011 16:37
A Python generator for the Chinese Restaurant Process
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
@beaucronin
beaucronin / iris.csv
Created April 18, 2012 17:59
Veritable python analysis for Fisher iris data
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
@beaucronin
beaucronin / example1.py
Created April 19, 2012 15:26
Veritable uncertainty quantification examples
pr = analysis.predict({'petal_length': 1.5, 'petal_width': None})
interval = pr.credible_values('petal_width')
# => (0.06619570898596525, 0.45519138428493605)
interval[1] - interval[0]
# => 0.38899567529897083
pr = analysis.predict({'petal_length': 5.0, 'petal_width': None})
interval = pr.credible_values('petal_width')
# => (1.3341578189754613, 2.4761532421771784)
interval[1] - interval[0]
@beaucronin
beaucronin / generate.py
Created April 19, 2012 17:43
Learning noisy-XOR with Veritable
# generate some noisy-XOR data
from random import random
N = 1000
noise = 0.1
data = []
for _ in range(N):
x1 = random() < 0.5
@beaucronin
beaucronin / correlation_examples.R
Created April 27, 2012 14:36
Examples of dependence beyond correlation
#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.
@beaucronin
beaucronin / 0_preprocess.py
Created May 15, 2012 21:04
Single-malt scotch
import csv
import json
rd = csv.reader(open('scotch.csv'))
header = rd.next()
colors = header[1:15]
data = []
schema = {
'color': { 'type': 'categorical' },
'AGE': { 'type': 'count' },
@beaucronin
beaucronin / gist:3094654
Created July 12, 2012 00:18
Veritable code to analyze heights and weights with different units
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
@beaucronin
beaucronin / gist:2229f825095db7d7dfd2
Last active April 6, 2021 14:19
Get transactions via Yodlee
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>' }
@beaucronin
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: