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# http://badhessian.org/2012/09/lessons-on-exponential-random-graph-modeling-from-greys-anatomy-hook-ups/ | |
library(ergm) | |
path <- "/Users/juarez.bochi/Dropbox/mestrado/inf2035/Random Graphs/fbergm" | |
friends_path <- paste(path, "friends_manual.tsv", sep="/") | |
relationships_path <- paste(path, "relationships.tsv", sep="/") | |
friends <- read.table(friends_path, sep="\t", header=T, stringsAsFactors=F, strip.white=F, as.is=T) |
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PriorityQueue <- function() { | |
keys <<- values <<- NULL | |
insert <- function(key, value) { | |
temp <- c(keys, key) | |
ord <- order(temp) | |
keys <<- temp[ord] | |
values <<- c(values, list(value))[ord] | |
} | |
pop <- function() { | |
key <- keys[[1]] |
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<!DOCTYPE html> | |
<html> | |
<head> | |
<meta http-equiv="content-type" content="text/html; charset=UTF-8"> | |
<title> - jsFiddle demo</title> | |
<script type='text/javascript' src='/js/lib/dummy.js'></script> | |
<link rel="stylesheet" type="text/css" href="/css/normalize.css"> | |
<link rel="stylesheet" type="text/css" href="/css/result-light.css"> |
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def ifilter(funcao, seq): | |
for x in seq: | |
if funcao(x): | |
yield x | |
def take(seq, n): | |
i = 0 | |
for x in seq: | |
if i < n: |
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class Natural(object): | |
def __init__(self, anterior): | |
self.anterior = anterior | |
def __str__(self): | |
return str(self.anterior) + " + 1" | |
def __add__(self, other): | |
return self.anterior + other.sucessor() |
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def change(n, coins): | |
if n == 0: | |
return 1 | |
elif n < 0 or len(coins) == 0: | |
return 0 | |
else: | |
return change(n, coins[1:]) + change(n - coins[0], coins) | |
print change(10, [10, 5, 2, 1]) |
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#from functools import partial | |
def partial(funcao, argumento): | |
def fn(arg): | |
return funcao(argumento, arg) | |
return fn | |
def to_tag(tag, texto): | |
return "<{tag}>{texto}</{tag}>".format(tag=tag, texto=texto) | |
negrito = partial(to_tag, 'b') |
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def print_pascal_triangle(n_lines): | |
for row in xrange(n_lines): | |
for col in xrange(row + 1): | |
print pascal(row, col), | |
def pascal(row, col): | |
if col == 0 or row == col: | |
return 1 |
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def msort(xs: List[Int]): List[Int] = { | |
val n = xs.length / 2 | |
if (n == 0) xs | |
else { | |
def merge(xs: List[Int], ys: List[Int]): List[Int] = (xs, ys) match { | |
case (Nil, ys) => ys | |
case (xs, Nil) => xs | |
case (x :: xs1, y :: ys1) => | |
if (x < y) x :: merge(xs1, ys) | |
else y :: merge(xs, ys1) |
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class O(): | |
def __repr__(self): | |
return "<" + ' *o* '.join(map(repr, self.funs)) + ">" if self.funs else "<composer>" | |
def __init__(self, funs=None): | |
self.funs = funs if funs else [] | |
def __rmul__(self, other): | |
other_funs = other.funs if isinstance(other, O) else [other] | |
return O(other_funs + self.funs) |