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knucleotide.clj-14-for-clj13.clj
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knucleotide.clj-14-for-clj13.clj
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;; The Computer Language Benchmarks Game
;; http://shootout.alioth.debian.org/
;; contributed by Andy Fingerhut
(ns knucleotide
(:gen-class))
(set! *warn-on-reflection* true)
;; Handle slight difference in function name between Clojure 1.2.0 and
;; 1.3.0-alpha* ability to use type hints to infer fast bit
;; operations.
(defmacro my-unchecked-inc-int [& args]
(if (and (== (*clojure-version* :major) 1)
(== (*clojure-version* :minor) 2))
`(unchecked-inc ~@args)
`(unchecked-inc-int ~@args)))
(defmacro key-type [num]
(if (and (== (*clojure-version* :major) 1)
(== (*clojure-version* :minor) 2))
num
`(long ~num)))
(definterface ITallyCounter
(^int get_count [])
(inc_BANG_ []))
(deftype TallyCounter [^{:unsynchronized-mutable true :tag int} cnt]
ITallyCounter
(get-count [this] cnt)
(inc! [this]
(set! cnt (my-unchecked-inc-int cnt))))
(defn my-lazy-map [f coll]
(lazy-seq
(when-let [s (seq coll)]
(cons (f (first s)) (my-lazy-map f (rest s))))))
;; modified-pmap is like pmap from Clojure 1.1, but with only as much
;; parallelism as specified by the parameter num-threads. Uses
;; my-lazy-map instead of map from core.clj, since that version of map
;; can use unwanted additional parallelism for chunked collections,
;; like ranges.
(defn modified-pmap
([num-threads f coll]
(if (== num-threads 1)
(map f coll)
(let [n (if (>= num-threads 2) (dec num-threads) 1)
rets (my-lazy-map #(future (f %)) coll)
step (fn step [[x & xs :as vs] fs]
(lazy-seq
(if-let [s (seq fs)]
(cons (deref x) (step xs (rest s)))
(map deref vs))))]
(step rets (drop n rets)))))
([num-threads f coll & colls]
(let [step (fn step [cs]
(lazy-seq
(let [ss (my-lazy-map seq cs)]
(when (every? identity ss)
(cons (my-lazy-map first ss)
(step (my-lazy-map rest ss)))))))]
(modified-pmap num-threads #(apply f %) (step (cons coll colls))))))
;; Return true when the line l is a FASTA description line
(defn fasta-description-line [l]
(= \> (first (seq l))))
;; Return true when the line l is a FASTA description line that begins
;; with the string desc-str.
(defn fasta-description-line-beginning [desc-str l]
(and (fasta-description-line l)
(= desc-str (subs l 1 (min (count l) (inc (count desc-str)))))))
;; Take a sequence of lines from a FASTA format file, and a string
;; desc-str. Look for a FASTA record with a description that begins
;; with desc-str, and if one is found, return its DNA sequence as a
;; single (potentially quite long) string. If input file is big,
;; you'll save lots of memory if you call this function in a with-open
;; for the file, and don't hold on to the head of the lines parameter.
(defn fasta-dna-str-with-desc-beginning [desc-str lines]
(when-let [x (drop-while
(fn [l] (not (fasta-description-line-beginning desc-str l)))
lines)]
(when-let [x (seq x)]
(let [y (take-while (fn [l] (not (fasta-description-line l)))
(map (fn [#^java.lang.String s] (.toUpperCase s))
(rest x)))]
(apply str y)))))
(def dna-char-to-code-val {\A 0, \C 1, \T 2, \G 3})
(def code-val-to-dna-char {0 \A, 1 \C, 2 \T, 3 \G})
;; In the hash map 'tally' in tally-dna-subs-with-len, it is more
;; straightforward to use a Clojure string (same as a Java string) as
;; the key, but such a key is significantly bigger than it needs to
;; be, increasing memory and time required to hash the value. By
;; converting a string of A, C, T, and G characters down to an integer
;; that contains only 2 bits for each character, we make a value that
;; is significantly smaller and faster to use as a key in the map.
;; most least
;; significant significant
;; bits of int bits of int
;; | |
;; V V
;; code code code .... code code
;; ^ ^
;; | |
;; code for code for
;; *latest* *earliest*
;; char in char in
;; sequence sequence
;; Note: Given Clojure 1.2's implementation of bit-shift-left/right
;; operations, when the value being shifted is larger than a 32-bit
;; int, they are faster when the shift amount is a compile time
;; constant.
(defn dna-str-to-key [s]
;; Accessing a local let binding is much faster than accessing a var
(let [dna-char-to-code-val dna-char-to-code-val]
(loop [key 0
offset (int (dec (count s)))]
(if (neg? offset)
key
(let [c (nth s offset)
code (int (dna-char-to-code-val c))
new-key (+ (bit-shift-left key 2) code)]
(recur new-key (dec offset)))))))
(defn key-to-dna-str [k len]
(apply str (map code-val-to-dna-char
(map (fn [pos] (bit-and 3 (bit-shift-right k pos)))
(range 0 (* 2 len) 2)))))
(defn tally-dna-subs-with-len [len dna-str]
(let [mask-width (* 2 len)
mask (key-type (dec (bit-shift-left 1 mask-width)))
dna-char-to-code-val dna-char-to-code-val]
(loop [offset (int (- (count dna-str) len))
key (key-type (dna-str-to-key (subs dna-str offset (+ offset len))))
tally (let [h (java.util.HashMap.)
one (TallyCounter. (int 1))]
(.put h key one)
h)]
(if (zero? offset)
tally
(let [new-offset (dec offset)
new-first-char-code (dna-char-to-code-val
(nth dna-str new-offset))
new-key (key-type (bit-and mask (+ (bit-shift-left key 2)
new-first-char-code)))]
(if-let [^TallyCounter cur-count (get tally new-key)]
(.inc! cur-count)
(let [one (TallyCounter. (int 1))]
(.put tally new-key one)))
(recur new-offset new-key tally))))))
(defn getcnt [^TallyCounter tc]
(.get-count tc))
(defn all-tally-to-str [tally fn-key-to-str]
(with-out-str
(let [total (reduce + (map getcnt (vals tally)))
cmp-keys (fn [k1 k2]
;; Return negative integer if k1 should come earlier
;; in the sort order than k2, 0 if they are equal,
;; otherwise a positive integer.
(let [cnt1 (int (getcnt (get tally k1)))
cnt2 (int (getcnt (get tally k2)))]
(if (not= cnt1 cnt2)
(- cnt2 cnt1)
(let [^String s1 (fn-key-to-str k1)
^String s2 (fn-key-to-str k2)]
(.compareTo s1 s2)))))]
(doseq [k (sort cmp-keys (keys tally))]
(printf "%s %.3f\n" (fn-key-to-str k)
(double (* 100 (/ (getcnt (get tally k)) total))))))))
(defn one-tally-to-str [dna-str tally]
(let [zerotc (TallyCounter. 0)]
(format "%d\t%s" (getcnt (get tally (dna-str-to-key dna-str) zerotc))
dna-str)))
(defn compute-one-part [dna-str part]
[part
(condp = part
0 (all-tally-to-str (tally-dna-subs-with-len 1 dna-str)
(fn [k] (key-to-dna-str k 1)))
1 (all-tally-to-str (tally-dna-subs-with-len 2 dna-str)
(fn [k] (key-to-dna-str k 2)))
2 (one-tally-to-str "GGT"
(tally-dna-subs-with-len 3 dna-str))
3 (one-tally-to-str "GGTA"
(tally-dna-subs-with-len 4 dna-str))
4 (one-tally-to-str "GGTATT"
(tally-dna-subs-with-len 6 dna-str))
5 (one-tally-to-str "GGTATTTTAATT"
(tally-dna-subs-with-len 12 dna-str))
6 (one-tally-to-str "GGTATTTTAATTTATAGT"
(tally-dna-subs-with-len 18 dna-str)))])
(def +default-modified-pmap-num-threads+
(+ 2 (.. Runtime getRuntime availableProcessors)))
(defn -main [& args]
(def num-threads
(if (and (>= (count args) 1)
(re-matches #"^\d+$" (nth args 0)))
(let [n (. Integer valueOf (nth args 0) 10)]
(if (== n 0)
+default-modified-pmap-num-threads+
n))
+default-modified-pmap-num-threads+))
(with-open [br (java.io.BufferedReader. *in*)]
(let [dna-str (fasta-dna-str-with-desc-beginning "THREE" (line-seq br))
;; Select the order of computing parts such that it is
;; unlikely that parts 5 and 6 will be computed concurrently.
;; Those are the two that take the most memory. It would be
;; nice if we could specify a DAG for which jobs should finish
;; before others begin -- then we could prevent those two
;; parts from running simultaneously.
results (map second
(sort #(< (first %1) (first %2))
(modified-pmap num-threads
#(compute-one-part dna-str %)
'(0 5 6 1 2 3 4)
)))]
(doseq [r results]
(println r)
(flush))))
(shutdown-agents))