Knuth presented a "literate" sampling program that implements Unsorted), binary search trees, and bins. The December 1984 column sketched five data structures thatĬould be used to implement the set S: bit vectors, arrays (sorted and There are four operations on S: initializing it to empty, testingĪn integer for membership, inserting a new integer, and printing all the Invariant is that S always contains a random sample of Size integers in M-element subset is produced with probability 1(.sup.N./M.). Integers, then Algorithm S produces a random sample. ![]() If the set is implemented correctly and if RandInt produces random initialize set S to empty Size :=Ġ while Size < M do T := RandInt (1, N) if T is not in S then insertĪLGORITHM S. Majority of the algorithms were based on the pseudocode in Algorithm S, The December 1984 column described several sampling algorithms. Will denote a random sample with no duplicates. "samples without replacement" or as "combinations" įor the remainder of this column, though, the word "sample" A statistical analysis, for instance, might waste work by Many applications, though, require a random sample withoutĭuplicates. Rock-paper-scissors more serious applications include testing finite This very sequence might come in handy for your next tough game of RandInt (1, N) When I set M to 12 and N to 3, that code produced the ![]() It is easy to generate a random sequence of M integers in the rangeġ.N, so long as we don't mind duplicates for I := 1 to M do print That returns an integer uniformly distributed over I.J. Own, so we will simply assume that we have a function RandInt (I, J) His algorithm to generate random permutations.īefore we can generate a random sample, we have to be able to The third section describes how Floyd extends The first section of this column reviews several standardĪlgorithms for random sampling. Samples also arise in applications such as simulation, program testing, (It is important that no number appear twice holding more than oneĪce of spades can jeopardize a cardplayer's health.) Random Retrieved from Ī SAMPLE OF BRILLIANCE How can a computer deal a poker hand? If weĪssign each card in the deck its own integer between 1 and 52, then weĬan make a hand from a "random sample" of 5 integers in the 1987 Association for Computing Machinery, Inc. ![]() MLA style: "A sample of brilliance." The Free Library.asort() on the other hand sorts on the contents of the array, and array contents can be strings OR numbers and so normal awk comparison rules apply - anything that looks like a number is treated like a number and the number 9 is less than the number 888 which in this case IMHO is the desired result. That's because asorti() sorts on array indices and all array indices are strings (even if they look like numbers) and alphabetically the first character of the string "9" IS higher than the first character of the string "888". Notice that asorti() treats "9" as a higher value than "888". In case anyone's wondering why I didn't just use the values we want to sort on as indices and then do an asorti() as that would have resulted in slightly briefer code, here's why: $ cat tst.awk Then asort()ing keys to get: keys = 777Īnd then looping through the keys array using it's elements as the indices to the vals array for re-populating the original array. It works by first converting this: a = "dog" FWIW, here's a workaround "sort_by()" function: $ cat tst.awk
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