add an if to check if the number is positive.”; var pattern = function() { var $numVar = $numVal; if ($numVar > 0) { rect($x, $y, $w, $h); } }; result = match(pattern); if (passes(result)) { var goodX = structure(pattern, inRange(“$x”, 10, 20)); if (!matches(goodX)) { result = fail(“Hm, does your rect start on the side?”); } } assertMatch(result, descrip, displayP); }); Friday, October 18, 13
of Wilson score 90% confidence interval. This is the algorithm Reddit uses to sort comments. You should not use this if downvotes are disallowed - it is only useful in the presence of both upvotes and downvotes because its ranking is based on an estimate of the ratio of upvotes to downvotes. See http://www.evanmiller.org/how-not-to-sort-by-average-rating.html """ upvotes = getattr(score, upvotes_name) downvotes = getattr(score, downvotes_name) if upvotes == 0: return -downvotes elif upvotes == downvotes: return 0 n = upvotes + downvotes z = 1.64485 # 90% confidence z-score phat = float(upvotes) / n # p-hat return ((phat + z * z / (2 * n) - z * math.sqrt((phat * (1 - phat) + z * z / (4 * n)) / n)) / (1 + z * z / n)) class TimeIndependentScoreProperty(ndb.ComputedProperty): def __init__(self, upvotes_name="upvotes", downvotes_name="downvotes", **kwargs): super(TimeIndependentScoreProperty, self).__init__( functools.partial(wilson_confidence, upvotes_name, downvotes_name), **kwargs) Friday, October 18, 13
"""Ranking based on both age and quality. This is the algorithm Reddit uses to sort stories. We want there to be churn, a constant stream of new programs hitting the hot page, so this algorithm takes into account both the score of the scratchpad and the age. See http://amix.dk/blog/post/19588 """ s = getattr(score, upvotes_name) - getattr(score, downvotes_name) # Weight votes logarithmically - initial votes are worth a ton order = math.log(max(abs(s), 1), 10) sign = 1 if s > 0 else -1 if s < 0 else 0 # Seconds since this algorithm's start date date = getattr(score, created_name) or datetime.datetime.now() seconds = epoch_seconds(date) - 1349108492 return round(order + sign * seconds / decay_seconds, 7) class TimeDependentScoreProperty(ndb.ComputedProperty): def __init__(self, decay_seconds, upvotes_name="upvotes", downvotes_name="downvotes", created_name="created", **kwargs): super(TimeDependentScoreProperty, self).__init__(functools.partial( time_dependent, decay_seconds, upvotes_name, downvotes_name, created_name), **kwargs) Friday, October 18, 13
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