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David Blei's talk about arXiv:1206.7051 was really awesome today.

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import numpy as np

N = 5000
I_true = np.random.randn(N)
D = I_true[:, None] - I_true[None, :]

I0 = np.zeros_like(I_true)

eta = 1.0 / N  # Learning rate.
tol = 1.25e-11  # Error tolerance.

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diff --git a/old.html b/index.html
index e17fcfc..1f320f3 100644
--- a/old.html
+++ b/index.html
@@ -9,10 +9,12 @@
     <link href="http://twitter.github.com/bootstrap/assets/css/bootstrap.css" rel="stylesheet">
     <link href="http://twitter.github.com/bootstrap/assets/css/docs.css" rel="stylesheet">
     <link href="http://twitter.github.com/bootstrap/assets/js/google-code-prettify/prettify.css" rel="stylesheet">
+    <link href="ADSASS_applet/jquery-ui-1.9.2.custom.min.css" rel="stylesheet">
 

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import requests

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from __future__ import print_function

import requests
from bs4 import BeautifulSoup


def get_table(fn=u"koi.txt"):
    url = u"http://archive.stsci.edu/kepler/planet_candidates.html"
    r = requests.get(url)
    if r.status_code != requests.codes.ok:

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import bart

# Initialize a planet.
planet = bart.Planet(r=0.01, a=21.3, t0=3.85)
planet.parameters += [bart.parameters.Parameter(r"$r$", "r"),
                      bart.parameters.LogParameter(r"$a$", "a")]

# Initialize the star.
ldp = bart.kepler.fiducial_ldp(teff=6438, logg=4.28, feh=0.0)
star = bart.Star(mass=planet.get_mstar(12.4138), ldp=ldp)

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You'll need numpy, matplotlib, emcee, triangle.py and acor to run this example.

Here's the model:

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pro autokep_event,event
  Widget_Control, event.id, Get_UValue=info
  Call_Method, info.method, info.object, event
end

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Here's what happens if you want to display the progress of the default emcee example from the main documentation page.