glesica

pburg <- function() {
  p <- 1
  while (sample(1:2, 1)[1] == 1) {
    p <- p * 2
  }
  return(p)
}

ipburg <- function(n) {
  r <- sapply(1:n, function(x) { return(pburg()) })

glesica

[xcb] Unknown sequence number while appending request
[xcb] Most likely this is a multi-threaded client and XInitThreads has not been called
[xcb] Aborting, sorry about that.
invader: ../../src/xcb_io.c:160: append_pending_request: Assertion `!xcb_xlib_unknown_seq_number' failed.

Program received signal SIGABRT, Aborted.
0x00007ffff75ab445 in __GI_raise (sig=<optimized out>) at ../nptl/sysdeps/unix/sysv/linux/raise.c:64
64	../nptl/sysdeps/unix/sysv/linux/raise.c: No such file or directory.
(gdb) bt
#0  0x00007ffff75ab445 in __GI_raise (sig=<optimized out>) at ../nptl/sysdeps/unix/sysv/linux/raise.c:64

glesica

# value_iteration.r
# George Lesica
# CSCI 555 - FA 2012
# Homework 5
# Solution to problem 3

INTENDED <- 0.8
LEFT <- 0.1
RIGHT <- 0.1

glesica

# particle.r
# George Lesica
# CSCI 555 - FA 2012
# Homework 7.5
# Solution to problem 2

samp <- function(S) {
  return(sample(S$X, length(S$X), replace=T, prob=S$W))
}

glesica

convolution <- function(A, B) {
  # Computes the convolution of two vectors.
  #
  # Args:
  #   A, B: column vectors representing polynomial coefficients.
  #
  # Returns:
  #   The coefficient vector resulting from multiplying the polynomial 
  #   represented by A by the polynomial represented by B.
  Ap <- c(A, B*0)

glesica

perceptron <- function(x, y, w, a, verbose=F) {
  # Uses the Perceptron algorithm to find a weight vector that 
  # satisfies the given data.
  #
  # Args:
  #   x: an m by n matrix representing the data under study
  #   y: objective vector of m elements
  #   w: initial guess for the weight vector, n elements
  #   a: learning rate, should be in (0,1]
  #   verbose: echo information w at each iteration (default: False)

glesica

sentiment <- function(str, words, weights=NULL) {
  if (is.null(weights)) {
    weights <- rep(1, length(words))
  }
  
  if (length(words) != length(weights)) {
    stop('Length of words and weights not equal')
  }
  
  str.wts <- rep(0, length(str))

glesica

#!/usr/bin/env sh

# Filename: update-hosts.sh
# Author: George Lesica <george@lesica.com>
# Description: Replaces the HOSTS file with a customized version that blocks
# domains that serve ads and malicious software, creating a backup of the old
# file.

HOSTS_URL="http://someonewhocares.org/hosts/zero/hosts"
NEW_HOSTS="hosts"

glesica

from math import pi
from cairo import SVGSurface, Context, Matrix

WIDTH = 6 * 72
HEIGHT = 4 * 72

s = SVGSurface('example1.svg', WIDTH, HEIGHT)
c = Context(s)

# Transform to normal cartesian coordinate system

glesica

# contour(A, v)
# Implements the Marching Squares contouring algorithm (see:
# https://en.wikipedia.org/wiki/Marching_squares for details). The
# matrix `A` is an m x n scalar field and the scalar `v` is the
# value to be contoured. The return value is an (m-1) x (n-1) matrix
# of contour line type indices (see the Wikipedia article).
# TODO: Implement in parallel
function contour(A, v)
    rows, cols = size(A)