Erlang: a List in disorder _ PHP Tutorial

Erlang unordered List scheme. I recently read erlang systematically. now I use erlangprogramming as the learning material. after reading the first seven or eight chapters, I tried to write something and found that I was helpless, you can find help materials and documents, and recently read erlang systematically. Currently, erlang programming is used as the learning material. after reading the first seven or eight chapters, I tried to write something and found that I was at a loss, there are very few materials and documents that can help.

In fact, I hope someone can study or discuss it together.

Today's question: a List in disorder.

Method 1: a more sophisticated disordered solution.

[Php]

-Module (shuffle ).

-Export ([do/1]).

Do (L)->

Len = length (L ),

NL = lists: map (fun (X)-> {random: uniform (Len), X} end, L ),

NLL = lists: sort (NL ),

[V | {_, V} <-NLL].

In fact, this problem is quite confusing to me. Once a variable is assigned a value, it cannot be modified. This feature makes the idea and idea of writing a program completely different. My above practice is to use a random number to generate a list like [{Rand1, Elem1},..., {RandN, ElemN.

Then, sort it by sort and print the Elem again. The unordered result is achieved.

The result is as follows:

[Php]

45> c (shuffle ).

{OK, shuffle}

46> shuffle: do ([1, 2, 3, 4, 5]).

[4, 5, 1, 2, 3]

47> shuffle: do ([1, 2, 3, 4, 5]).

[2, 1, 5, 3, 4]

48> shuffle: do ([1, 2, 3, 4, 5]).

[3, 1, 2, 4, 5]

49> shuffle: do ([1, 2, 3, 4, 5]).

[1, 5, 2, 3, 4]

50> shuffle: do ([1, 2, 3, 4, 5]).

[5, 1, 4, 3, 2]

51>

Method 2: General shuffling algorithm

Next, a List in disorder. I think the original general shuffling algorithm is feasible. I tried to write another function. The test is effective, but I think there is definitely room for optimization. The style of the code still reveals a strong procedural ideology.

% Shuffling algorithm scheme

[Php]

Do2 (L)->

Do2 (L, []).

Do2 ([], L)->

L;

Do2 (L1, L2)->

% Io: format ("L1 = ~ W L2 = ~ W ~ N ", [L1, L2]),

Len = length (L1 ),

If

Len> 1->

NL = lists: split (random: uniform (Len-1), L1 ),

{[H1 | T1], [H2 | T2]} = NL,

NL2 = lists: flatten ([T1], [H1 | T2]),

L11 = lists: append (L2, [H2]),

Do2 (NL2, L11 );

True->

Do2 ([], lists: append (L2, L1 ))

End.

The result is:

128> c (shuffle ).

{OK, shuffle}

129> shuffle: do2 (lists: seq )).

[9, 2, 5, 1, 8, 0, 7, 3, 6, 4]

130> shuffle: do2 (lists: seq )).

[8, 3, 6, 5, 7, 4, 9, 0, 2, 1]

131> shuffle: do2 (lists: seq )).

[,]

132> shuffle: do2 (lists: seq )).

[,]

133>

There are several points worth thinking about whether these two solutions are true shuffling algorithms. Is it equal to the probability that each number appears at a certain position.

Other methods are not supported.

Explain programming is the learning material. after reading the first seven or eight chapters, I tried to write something and found that I was helpless. I could find help materials and documents...