The Sieve of Eratosthenes

We start with no primes, and a list of candidate integers.

```
#{} #{2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20}
```

The lowest of the candidates is a prime. Add it to the list of primes and remove all multiples of it from the candidates

```
#{2} #{3 5 7 9 11 13 15 17 19}
```

and repeat

```
#{2 3} #{5 7 11 13 17 19}
```

and repeat.

```
#{2 3 5} #{7 11 13 17 19}
```

Nothing interesting happens after here, because 5*5 is larger than 19, so we'd already have eliminated anything that we're going to eliminate from now on, but let's not get too clever, and follow the recursion to its natural end.

```
#{2 3 5 7} #{11 13 17 19}
#{2 3 5 7 11} #{13 17 19}
#{2 3 5 7 11 13} #{17 19}
#{2 3 5 7 11 13 17} #{19}
#{2 3 5 7 11 13 17 19} #{}
```

And we're done. No more candidates to sieve

```
#{2 3 5 7 11 13 17 19} #{}
#{2 3 5 7 11 13 17 19} #{}
```

so nothing happens at all from now on.

How to model this recursion with a function? We can use the clojure set library to do the striking off.

```
(use 'clojure.set)
```

Here's a function which takes one row from above, and produces the next:

```
(defn sievefn [[primes, candidates]]
(if (empty? candidates) [primes, candidates]
(let [prime (first candidates) ;;the first candidate is always a prime
end (inc (apply max candidates)) ;;we want to strike out all multiples
multiples (range prime end prime) ;;up to max(candidates)
newprimes (conj primes prime)
newcandidates (clojure.set/difference candidates multiples)]
[ newprimes, newcandidates])))
```

Let's try it:

```
(def to20 [(sorted-set) #{2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20}])
(sievefn to20)
(sievefn (sievefn to20))
```

Here are the first ten iterations:

```
(take 10 (iterate sievefn to20))
```

Of course, this is all a bit long-winded. Let us instead define sieve like this, mixing the iteration in with the transforming function:

```
(defn sieverecur [primes candset]
(if (empty? candset) primes
(let [prime (first candset)
end (inc (apply max candset))]
(recur (conj primes prime), (clojure.set/difference candset (range prime end prime))))))
(sieverecur (sorted-set) (apply sorted-set (range 2 100)))
```

We shouldn't have to recalculate the end value every time, though, so we can pull that bit out:

```
(defn sieverecur1
([primes candset]
(sieverecur1 primes candset (inc (apply max candset))))
([primes candset end]
(if (empty? candset) primes
(let [prime (first candset)]
(recur (conj primes prime)
(clojure.set/difference candset (range prime end prime))
end)))))
(sieverecur1 (sorted-set) (apply sorted-set (range 2 100)))
```

Finally, we can incorporate our initial conditions, and also the optimization that we noticed above, that nothing happens once the largest prime is above the square root of the range.

```
(defn sieve
([n]
(sieve (sorted-set) (apply sorted-set (range 2 (inc n))) (+ n 2)))
([primes candset end]
(let [prime (first candset)]
(if ( > (* prime prime) end)
(clojure.set/union primes candset)
(recur (conj primes prime)
(clojure.set/difference candset (range prime end prime))
end)))))
```

That's about it for the Sieve of Eratosthenes over a finite list.

What about producing an infinite list of primes?

A similar algorithm on paper might look like:

Start with a counter set to 2. Two is prime, so we can add it to a list of primes The first multiple of 2 is 2, so we write [[multiple, prime]] counter

```
[[2,2]] 2
```

Now up the counter to 3.

```
[[2,2]] 3
```

The multiple of 2 is lower than 3, so add 2 to get the next multiple of 2, 4

```
[[4,2]] 3
```

Now our multiple is higher, so we know 3 is also a prime, and we add it to the list The first multiple of 3 is 3

```
[[3,3][4,2]] 3
```

Three is already on the list, so up the counter to 4.

```
[[3,3][4,2]] 4
```

4 is larger than our lowest prime multiple, so increase the multiple, by adding its prime.

```
[[4,2][6,3]] 4
```

We will keep the list of primes and multiples sorted in order of the multiples, so that we always know which one to look at next. We now have the primes 2 and 3, and their multiples 4 and 6 4 is equal to the lowest multiple. So discard it and increase the counter to 5

```
[[4,2][6,3]] 5
```

The lowest multiple is 4, less than 5, so we add its prime 2+4=6

```
[[6,2][6,3]] 5
```

5 is lower than any multiple, so it is a prime too. And so on........ the iteration goes:

```
[[5,5][6,2][6,3]] 5
[[5,5][6,2][6,3]] 6
[[6,2][6,3][10,5]] 6
[[6,2][6,3][10,5]] 7
[[6,3][8,2][10,5]] 7
[[8,2][9,3][10,5]] 7
[[7,7][8,2][9,3][10,5]] 7
[[7,7][8,2][9,3][10,5]] 8
[[8,2][9,3][10,5][14,7]] 8
[[8,2][9,3][10,5][14,7]] 9
[[9,3][10,2][10,5][14,7]] 9
[[9,3][10,2][10,5][14,7]] 10
```

and as the counter increases, the primes accumulate on the left hand side.

We can construct a function which performs this iteration, too:

```
(defn infinite-sieve-fn [[testset int]]
(let [pair (first testset)
[multiple prime] pair]
(cond (= int multiple) (list testset (inc int))
(> int multiple) (list (conj (disj testset pair) [(+ multiple prime) prime]) int)
(< int multiple) (list (conj testset [int int]) int))))
```

and iterate it infinitely:

```
(def sieves (iterate infinite-sieve-fn [(sorted-set [2,2]) 3]))
```

note the use of a sorted set, so that when we add in new pairs, the lowest will be the first element

Here are the first five iterations:

```
(take 5 sieves)
```

How to extract the primes? Consider the 20th iteration

```
(nth sieves 20)
```

is

```
'(#{[10 2] [10 5] [12 3] [14 7]} 11)
```

So we'd like to extract the second elements of the first element

```
(map second (first (nth sieves 200)))
```

and it might be better if we sort them

```
(sort (map second (first (nth sieves 200))))
```

again we can construct an infinite list, derived from the first one

```
(def sieveprimes (map (fn[x] (sort (map second (first x)))) sieves))
```

What primes have we got after 1000 iterations?

```
(nth sieveprimes 1000)
```

after 10000 iterations, what are the last ten primes we found?

```
(take 10 (reverse (nth sieveprimes 10000)))
```

If all we want is a list of primes, it's silly to construct an entire list of iterations. Just like above, we can fold the iteration into the function, but this time we need to decide when to stop iterating.

```
(defn infinite-sieve-recur [testset int stop]
(if (> int stop) testset
(let [pair (first testset)
[multiple prime] pair]
(cond (= int multiple) (recur testset (inc int) stop)
(> int multiple) (recur (conj (disj testset pair) [(+ multiple prime) prime]) int stop)
(< int multiple) (recur (conj testset [int int]) int stop)))))
```

here's the test set when the counter has got to ten.

```
(infinite-sieve-recur (sorted-set [2,2]) 2 10)
```

now we can ask for all the primes up to 100.

```
(map second (infinite-sieve-recur (sorted-set [2,2]) 2 100))
```

we've lost memoization by abandoning the infinite sequence, but we also don't need to keep all that intermediate data in memory for ever. This alone has given us a speed up of a factor of 100.

Here are the last ten primes before 10000

```
(take 10 (reverse (sort (map second (infinite-sieve-recur (sorted-set [2,2]) 2 10000)))))
```

Again, there's no point in testing numbers for factors over their square root, so we can optimise that by setting the first test multiple of a prime to be its square. Note that we now need to remember to up the counter at the same time!

```
[[4,2]] 2
[[4,2]] 3
[[4,2][9,3]] 4
[[4,2][9,3]] 5
[[6,2][9,3][25,5]] 5
[[6,2][9,3][25,5]] 6
[[8,2][9,3][25,5]] 7
[[8,2][9,3][25,5][49,7]] 8
[[8,2][9,3][25,5][49,7]] 9
[[9,3][10,2][25,5][49,7]] 9
[[9,3][10,2][25,5][49,7]] 10
[[9,3][10,2][25,5][49,7]] 11
```

And again, we may as well fold in our initial conditions to make a tidy function

```
(defn infinite-sieve
([n] (sort (map second (infinite-sieve (sorted-set [2,2]) 2 n))))
([testset int stop]
(if (> int stop) testset
(let [pair (first testset)
[multiple prime] pair]
(cond (= int multiple) (recur testset (inc int) stop)
(> int multiple) (recur (conj (disj testset pair) [(+ multiple prime) prime]) int stop)
(< int multiple) (recur (conj testset [(* int int) int]) (inc int) stop))))))
(infinite-sieve 100)
(take 10 (reverse (infinite-sieve 10000)))
```

Now all we have to do is figure out why the thing is so slow! Which I think will be a blog post for another day.

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