David Tolpin dtolpin

## tournament.html
<html xmlns="http://www.w3.org/1999/xhtml"><head>
<meta http-equiv="content-type" content="text/html; charset=ISO-8859-1">
<!-- $Id: tournament.html,v 1.5 2008/03/10 11:05:35 tolpin Exp $ -->

  <title>Unreal Tournament</title>
  <script type="text/javascript"><!--
/* $Id: util.js,v 1.4 2008/03/05 12:02:31 tolpin Exp $ */

var MIN_INT = -0xFFFF,
    MAX_INT = -MIN_INT;

## tournament.html
<html xmlns="http://www.w3.org/1999/xhtml"><head>
<meta http-equiv="content-type" content="text/html; charset=ISO-8859-1">
<!-- $Id: tournament.html,v 1.5 2008/03/10 11:05:35 tolpin Exp $ -->

  <title>Unreal Tournament</title>
  <script type="text/javascript"><!--
/* $Id: util.js,v 1.4 2008/03/05 12:02:31 tolpin Exp $ */

var MIN_INT = -0xFFFF,
    MAX_INT = -MIN_INT;

## non-local-control-in-anglican.md

      
              1 file
            
          
              0 forks
            
          
              0 comments
            
          
              0 stars
            
          
                dtolpin
                / non-local-control-in-anglican.md
            
            
              Last active
              January 30, 2017 23:44
            
              
                Dynamic non-local control in Anglican
              
          
    Motivation

The BOPP paper needs a way to immediately return result from a query. The easiest way to implement this is to add a kind of return statement. However, imlementing return literally poses two problems:

there is a risk of name catch by the user, when the user declares a variable return (not a special form in Clojure).
return inside an Anglican function implemented as a call to result-cont will not return from the function but rather from the query which calls the function, without any way to intercept.

We would like a solution which

does not pollute Anglican namespace by adding reserved words.
gives control over the scope to return from.


## pww.py
def pww(batches, detect):
    t = 1
    for _ in range(ceil(log2(max_time))):
        # Generate sliding windows with half-window step
        windows = (batches
            .window(2*t, t)
            .reduce(lambda a, b: a + b))

        # Apply data mining/pattern recognition algorithm
        detect(windows)

## _service.md

      
              2 files
            
          
              0 forks
            
          
              0 comments
            
          
              0 stars
            
          
                dtolpin
                / _service.md
            
            
              Last active
              September 21, 2015 15:01
                — forked from naholyr/_service.md
            
              
                Sample /etc/init.d script
              
          
    Sample service script for debianoids

Look at LSB init scripts for more information.
Usage

Copy to /etc/init.d:
# replace "$YOUR_SERVICE_NAME" with your service's name (whenever it's not enough obvious)

  
## resampling.py
from random import uniform

class resample:
    """Particle resampler. Assumes that
    particles is a list of tuples [particle, weight]"""
    def __init__(self, particles):
        assert particles, "at least one particle required"
        self.particles = particles
        self.total = float(sum(w for p,w in self.particles))
	<html xmlns="http://www.w3.org/1999/xhtml"><head>
	<meta http-equiv="content-type" content="text/html; charset=ISO-8859-1">
	<!-- $Id: tournament.html,v 1.5 2008/03/10 11:05:35 tolpin Exp $ -->

	<title>Unreal Tournament</title>
	<script type="text/javascript"><!--
	/* $Id: util.js,v 1.4 2008/03/05 12:02:31 tolpin Exp $ */

	var MIN_INT = -0xFFFF,
	MAX_INT = -MIN_INT;
	def pww(batches, detect):
	t = 1
	for _ in range(ceil(log2(max_time))):
	# Generate sliding windows with half-window step
	windows = (batches
	.window(2*t, t)
	.reduce(lambda a, b: a + b))

	# Apply data mining/pattern recognition algorithm
	detect(windows)
	from random import uniform

	class resample:
	"""Particle resampler. Assumes that
	particles is a list of tuples [particle, weight]"""
	def __init__(self, particles):
	assert particles, "at least one particle required"
	self.particles = particles
	self.total = float(sum(w for p,w in self.particles))