Wording of the rationale | Jens Axel Søgaard | 07 Nov 2006 12:49 UTC |

Re: Wording of the rationale | Jens Axel Søgaard | 07 Nov 2006 21:24 UTC |

Re: Wording of the rationale

*Jens Axel SÃ¸gaard*07 Nov 2006 21:24 UTCJens Axel Søgaard skrev: Quoting the rational of srfi-95: > * Four varieties of algorithms were provided (quick, heap, > insert, merge) even though quick, heap, and insert sorts have > no significant advantage over merge-sort. Commenting: > Second: What does "no significant advantage" mean? I were of the > impression, that the "hidden constants" of O(n log (n)) of > vector-quick-sort were smaller than that of vector-merge-sort. ... > Also: Is merge-sort the fastest algorithm, if the elements are "almost > sorted"? I tried a few experiments, and discovered that heap-sort beats the other algorithms when the elements are in almost reverse order. (The most surprising about this, is that I didn't figured it out before running the test). That is: If you know something about the data to be sorted, you are in a position, where you *want* to choose between the various algorithms. /Jens Axel Søgaard A sorted, long vector: (vector 1 2 3 ... 1000000) with < ---------------------------------------------------------- vector-merge-sort! and vector-insert-sort! roughly the same time vector-heap-sort! *much* slower vector-merge-sort! cpu time: 62 real time: 63 gc time: 0 vector-insert-sort! cpu time: 62 real time: 63 gc time: 0 vector-heap-sort! cpu time: 2343 real time: 2359 gc time: 0 A reverse-sorted, long vector: (vector 10000 ... 3 2 1) with < ------------------------------------------------------------- vector-heap-sort! *very* fast vector-merge-sort! and vector-insert-sort! roughly the same time vector-merge-sort! cpu time: 2203 real time: 2219 gc time: 0 vector-insert-sort! cpu time: 2047 real time: 2046 gc time: 0 vector-heap-sort! cpu time: 16 real time: 16 gc time: 0 My test program and results follow: (require (lib "32.ss" "srfi")) ; interval : integer integer -> (list integer) ; (interval n m) => (list n n+1 ... m) (define (interval n m) (do ((i m (- i 1)) (xs '() (cons i xs))) ((< i n) xs))) ; copy the input vector, and time the sorting only (define (test orig-v sorter) (let (; copy v so we can sort the same vector several times (v (list->vector (vector->list orig-v)))) ; make sure the garbage of one test doesn't affect the next (collect-garbage) (collect-garbage) ; time the sorting only (time (sorter < v)))) 'SORTED-VECTOR-TEST (define n 1000000) (define v (list->vector (interval 1 n))) 'vector-merge-sort! (test v vector-merge-sort!) 'vector-insert-sort! (test v vector-insert-sort!) 'vector-heap-sort! (test v vector-heap-sort!) 'REVERSE-SORTED-VECTOR-TEST (define n 10000) (define v (list->vector (reverse! (interval 1 n)))) 'vector-merge-sort! (test v vector-merge-sort!) 'vector-insert-sort! (test v vector-insert-sort!) 'vector-heap-sort! (test v vector-heap-sort!) 'RANDOM-VECTOR-TEST (define n 10000) (define v (list->vector (map (lambda (n) (random 1000000)) (interval 1 n)))) 'vector-merge-sort! (test v vector-merge-sort!) 'vector-insert-sort! (test v vector-insert-sort!) 'vector-heap-sort! (test v vector-heap-sort!) The results were (a different run than the above): Welcome to DrScheme, version 359.100-svn6nov2006. Language: Pretty Big (includes MrEd and Advanced Student). SORTED-VECTOR-TEST vector-merge-sort! cpu time: 63 real time: 62 gc time: 0 vector-insert-sort! cpu time: 62 real time: 62 gc time: 0 vector-heap-sort! cpu time: 2359 real time: 2359 gc time: 0 REVERSE-SORTED-VECTOR-TEST vector-merge-sort! cpu time: 2110 real time: 2110 gc time: 0 vector-insert-sort! cpu time: 2000 real time: 2000 gc time: 0 vector-heap-sort! cpu time: 15 real time: 15 gc time: 0 RANDOM-VECTOR-TEST vector-merge-sort! cpu time: 16 real time: 16 gc time: 0 vector-insert-sort! cpu time: 1031 real time: 1062 gc time: 0 vector-heap-sort! cpu time: 31 real time: 31 gc time: 0