adding lisp-interpreter

lisp-interpreter/tests/code/dp.scm

@@ -0,0 +1,59 @@
+; PROBLEW
+; W - maximum bag weight
+; {m_1, m_2, ... m_n} = item weights
+; {v_1, v_2, ... v_n} = item values
+
+; want to choose a subset I so that
+; sum m_i <= W
+; and
+; sum v_i is maximized
+; In other words, if we choose another subset J
+; then sum v_j <= sum v_i
+
+
+(define (rand-item max-weight max-cost)
+  (cons (random max-weight)
+        (random max-cost)))
+
+(define (build-items n)
+  (if (= n 0)
+    '()
+    (cons (rand-item 100 100)
+          (build-items (- n 1)))))
+;(random-seed! (GET-UNIVERSAL-TIME))
+;(define items (build-items 10))
+
+
+(define items '((23 . 505) (26 . 352) (18 . 220) (32 . 354) (27 . 414) (29 . 498) (26 . 545) (30 . 473) (27 . 543)))
+
+(define (knapsack remaining items)
+  (if (or (null? items) (<= remaining 0))
+    0
+    (let ((weight (car (car items)))
+          (val (cdr (car items))))
+      (max
+        (if (>= (- remaining weight) 0)
+          (+ val (knapsack (- remaining weight) (cdr items)))
+          0)
+        (knapsack remaining (cdr items))))))
+
+(display (knapsack 67 items))
+
+(assert (= (knapsack 67 items) 1270))
+
+
+; https://en.wikipedia.org/wiki/Levenshtein_distance
+(define (edit-distance-list a b eq?)
+  (cond ((null? a) (length b))
+		((null? b) (length a))
+		(else (min
+				(+ 1 (edit-distance-list (cdr a) b eq?)) ; insert
+				(+ 1 (edit-distance-list a (cdr b) eq?)) ; delete
+				(+ 
+				  (if (eq? (car a) (car b)) 0 1) ; replace if needed
+				  (edit-distance-list (cdr a) (cdr b) eq?))))))
+
+(define (edit-distance a b)
+  (edit-distance-list (string->list a) (string->list b) char=?))
+
+(==>  (edit-distance "kitten" "sitting") 3)