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Jan 22, 2024 •218 likes •498 views

Tree Recursion Announcements Recursive Factorial factorial (!) if n == 0 n! = 1 if n > 0 n! = n x (n-1) x (n-2) x ... x 1 factorial(5) def factorial(n): fact = 1 i = 1 while i <= n: 1 = 1*1 fact *= i 2 = 2*1! i += 1 6 =

  1. Tree Recursion

  2. Announcements

  3. Recursive Factorial

  4. factorial (!) if n == 0 n! = 1 if n > 0 n! = n x (n-1) x (n-2) x ... x 1

  5. factorial(5) def factorial(n): fact = 1 i = 1 while i <= n: 1 = 1*1 fact *= i 2 = 2*1! i += 1 6 = 3*2! return fact 24 = 4*3! 120 = 5*4!

  6. factorial (!) base case if n == 0 n! = 1 recursive case if n > 0 n! = n x (n-1)!

  7. def factorial(n): if n == 0: return 1 else: return n * factorial(n-1) factorial(3) 3 * factorial(2) 2 * factorial(1) 1 * factorial(0)

  8. Order of Recursive Calls

  9. The Cascade Function (Demo) • Each cascade frame is from a different call to cascade. • Until the Return value appears, that call has not completed. • Any statement can appear before or after the recursive call. 9 http://pythontutor.com/composingprograms.html#code=def%20cascade%28n%29%3A%20%20%20%20%0A%20%20%20%20if%20n%20%3C%2010%3A%20%20%20%20%20%20%20%20%0A%20%20%20%20%20%20%20%20print%28n%29%20%20%20%20%0A%20%20%20%20else%3A%20%20%20%20%20%20%20%20%0A%20%20%20%20%20%20%20%20print%28n%29%20%20%20%20%20%20%20%20%0A%20%20%20%20%20%20%20%20cascade%28n// 10%29%20%20%20%20%20%20%20%20%0A%20%20%20%20%20%20%20%20print%28n%29%20%20%20%20%20%20%20%20%0A%20%20%20%20%20%20%20%20%0Acascade%28123%29&cumulative=true&curInstr=0&mode=display&origin=composingprograms.js&py=3&rawInputLstJSON=%5B%5D

  10. Two Definitions of Cascade (Demo) def cascade(n): def cascade(n): print(n) if n < 10: if n >= 10: print(n) cascade(n//10) else: print(n) print(n) cascade(n//10) print(n) • If two implementations are equally clear, then shorter is usually better • In this case, the longer implementation is more clear (at least to me) • When learning to write recursive functions, put the base cases first • Both are recursive functions, even though only the first has typical structure 10

  11. Example: Inverse Cascade

  12. Inverse Cascade Write a function that prints an inverse cascade: 1 1 def inverse_cascade(n): grow(n) 12 12 print(n) 123 123 shrink(n) 1234 1234 123 123 def f_then_g(f, g, n): 12 12 if n: 1 1 f(n) g(n) grow = lambda n: f_then_g(grow, print, n//10) shrink = lambda n: f_then_g(print, shrink, n//10) 12

  13. Tree Recursion

  14. Tree Recursion Tree-shaped processes arise whenever executing the body of a recursive function makes more than one recursive call n: 0, 1, 2, 3, 4, 5, 6, 7, 8, ... , 35 fib(n): 0, 1, 1, 2, 3, 5, 8, 13, 21, ... , 9,227,465 def fib (n): if n == 0 : return 0 elif n == 1 : return 1 else : return fib(n- 2 ) + fib(n- 1 ) 14 http://en.wikipedia.org/wiki/File:Fibonacci.jpg

  15. A Tree-Recursive Process The computational process of fib evolves into a tree structure fib(5) fib(3) fib(4) fib(1) fib(2) fib(2) fib(3) fib(0) fib(1) 1 fib(0) fib(1) fib(1) fib(2) 0 1 fib(0) fib(1) 0 1 1 0 1 (Demo) 15

  16. Repetition in Tree-Recursive Computation This process is highly repetitive; fib is called on the same argument multiple times fib(5) fib(3) fib(4) fib(1) fib(2) fib(2) fib(3) fib(0) fib(1) 1 fib(0) fib(1) fib(1) fib(2) 0 1 fib(0) fib(1) 0 1 1 0 1 (We will speed up this computation dramatically in a few weeks by remembering results) 16

  17. Example: Towers of Hanoi

  18. Towers of Hanoi n = 1: move disk from post 1 to post 2 3 2 1

  19. Towers of Hanoi n = 1: move disk from post 1 to post 2 3 2 1

  20. Towers of Hanoi n = 1: move disk from post 1 to post 2 3 2 1

  21. def move_disk(disk_number, from_peg, to_peg): print("Move disk " + str(disk_number) + " from peg " \ + str(from_peg) + " to peg " + str(to_peg) + ".") def solve_hanoi(n, start_peg, end_peg): if n == 1: move_disk(n, start_peg, end_peg) else:

  22. def move_disk(disk_number, from_peg, to_peg): print("Move disk " + str(disk_number) + " from peg " \ + str(from_peg) + " to peg " + str(to_peg) + ".") def solve_hanoi(n, start_peg, end_peg): if n == 1: move_disk(n, start_peg, end_peg) else: spare_peg = 6 - start_peg - end_peg solve_hanoi(n - 1, start_peg, spare_peg) move_disk(n, start_peg, end_peg) solve_hanoi(n - 1, spare_peg, end_peg)

  23. def solve_hanoi(n, start_peg, end_peg): if n == 1: move_disk(n, start_peg, end_peg) else: spare_peg = 6 - start_peg - end_peg solve_hanoi(n - 1, start_peg, spare_peg) move_disk(n, start_peg, end_peg) solve_hanoi(n - 1, spare_peg, end_peg) hanoi(3,1,2) 1 2 3 3 2 1

  24. Example: Counting Partitions

  25. Counting Partitions The number of partitions of a positive integer n, using parts up to size m, is the number of ways in which n can be expressed as the sum of positive integer parts up to m in increasing order. count_partitions(6, 4) 2 + 4 = 6 1 + 1 + 4 = 6 3 + 3 = 6 1 + 2 + 3 = 6 1 + 1 + 1 + 3 = 6 2 + 2 + 2 = 6 1 + 1 + 2 + 2 = 6 1 + 1 + 1 + 1 + 2 = 6 1 + 1 + 1 + 1 + 1 + 1 = 6 25

  26. Counting Partitions The number of partitions of a positive integer n, using parts up to size m, is the number of ways in which n can be expressed as the sum of positive integer parts up to m in non- decreasing order. count_partitions(6, 4) • Recursive decomposition: finding simpler instances of the problem. • Explore two possibilities: • Use at least one 4 • Don't use any 4 • Solve two simpler problems: • count_partitions(2, 4) • count_partitions(6, 3) • Tree recursion often involves exploring different choices. 26

  27. Counting Partitions The number of partitions of a positive integer n, using parts up to size m, is the number of ways in which n can be expressed as the sum of positive integer parts up to m in increasing order. def count_partitions(n, m): • Recursive decomposition: finding if n == 0: simpler instances of the problem. return 1 • Explore two possibilities: elif n < 0: return 0 • Use at least one 4 elif m == 0: • Don't use any 4 return 0 • Solve two simpler problems: else: with_m = count_partitions(n-m, m) • count_partitions(2, 4) without_m = count_partitions(n, m-1) • count_partitions(6, 3) return with_m + without_m • Tree recursion often involves exploring different choices. (Demo) 27 pythontutor.com/composingprograms.html#code=def%20count_partitions%28n,%20m%29%3A%0A%20%20%20%20if%20n%20%3D%3D%200%3A%0A%20%20%20%20%20%20%20%20return%201%0A%20%20%20%20elif%20n%20<%200%3A%0A%20%20%20%20%20%20%20%20return%200%0A%20%20%20%20elif%20m%20%3D%3D%200%3A%0A%20%20%20%20%20%20%20%20return%200%0A%20%20%20%20else%3A%0A%20%20%20%20%20%20%20%20with_m%20%3D%20count_partitions%28n-m, %20m%29%20%0A%20%20%20%20%20%20%20%20without_m%20%3D%20count_partitions%28n, %20m-1%29%0A%20%20%20%20%20%20%20%20return%20with_m%20%2B%20without_m%0A%20%20%20%20%20%20%20%20%0Aresult%20%3D%20count_partitions%285,%203%29%0A%0A#%201%20%2B%201%20%2B%201%20%2B%201%20%2B%201%20%3D%205%0A#%201%20%2B%201%20%2B%201%20%2B%202%20%2B%20%20%20%3D%205%0A#%201%20%2B%202%20%2B%202%20%2B%20%20%20%20%20%20%20%3D%205%0A#%201%20%2B%201%20%2B%203%20%2B%20%20%20%20%20%20%20%3D%205%0A#%202% 20%2B%203%20%2B%20%20%20%20%20%20%20%20%20%20%20%3D%205&mode=display&origin=composingprograms.js&cumulative=false&py=3&rawInputLstJSON=[]&curInstr=0

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