permutation

问题 The original question is here: Cartesian power (a special Cartesian product) -- choose elements from array, in repeatable style In the old question, there are already answers gave a solution via iteration. I am wondering is there a recursive solution, similar as the solution from following link, which print permutations with recursion: https://www.geeksforgeeks.org/write-a-c-program-to-print-all-permutations-of-a-given-string/ Currently I have wrote following program, which is not correct yet

问题 The original question is here: Cartesian power (a special Cartesian product) -- choose elements from array, in repeatable style In the old question, there are already answers gave a solution via iteration. I am wondering is there a recursive solution, similar as the solution from following link, which print permutations with recursion: https://www.geeksforgeeks.org/write-a-c-program-to-print-all-permutations-of-a-given-string/ Currently I have wrote following program, which is not correct yet

问题 Below is an implementation of a function that returns the lexographically next permutation. This is useful in one of the Euler problems. It's written to work on Strings (which I needed for that). However, it should work on any indexed sequence of comparable values. I've tried generalising it by changing the two occurrences of String to IndexedSeq[Char], but this gets an error: euler-lib.scala:26: error: type mismatch; found : IndexedSeq[Char] required: String ((n.slice(pivot+1, successor):+ n

问题 I recently received help with optimizing my code to use generators to save on memory while running code that needs to check many permutations. To put it in perspective, I believe the generator is iterating over a list that has 2! * 2! * 4! * 2! * 2! * 8! * 4! * 10! elements in it. Unfortunately, while I now no longer run out of memory generating the permutations, it is taking >24 hours to run my code. Is it possible to parallelize this through GPU? Generating the iterator with all the above

问题 I recently received help with optimizing my code to use generators to save on memory while running code that needs to check many permutations. To put it in perspective, I believe the generator is iterating over a list that has 2! * 2! * 4! * 2! * 2! * 8! * 4! * 10! elements in it. Unfortunately, while I now no longer run out of memory generating the permutations, it is taking >24 hours to run my code. Is it possible to parallelize this through GPU? Generating the iterator with all the above

问题 Hey all, basically, i have an array: array('a', 'b', 'c'); Now i run it through an array permutation function and the result is: Array ( [0] => Array ( [0] => C ) [1] => Array ( [0] => B ) [2] => Array ( [0] => B [1] => C ) [3] => Array ( [0] => C [1] => B ) [4] => Array ( [0] => A ) [5] => Array ( [0] => A [1] => C ) [6] => Array ( [0] => C [1] => A ) [7] => Array ( [0] => A [1] => B ) [8] => Array ( [0] => B [1] => A ) [9] => Array ( [0] => A [1] => B [2] => C ) [10] => Array ( [0] => A [1]

问题 for example if we consider the case for 3 places with numbers from [1..3]..we can do it in 5 ways: 1 1 1 1 1 2 1 2 1 1 2 2 1 2 3 In second place we cant have 3 as the difference between 2nd and 1 first place will be more than 1. Any place (say i ) can have value atmost 1 more than the LARGEST value at its previous positions (i.e from 1 ..i-1) 回答1: Let dp[i, j] = how many possibilities of generating i positions such that the max is j, following the restrictions . We have: dp[0, 0] = dp[1, 1] =

问题 Someone know how can I randomize all the data inside my dataframe? I mean, I would get a new data frame where data are permuted by rows and by columns, to obtain an aleatory new data frame with the same numbers that I have in the first. Something like this: Thanks! 回答1: It would be a lot faster to do this on a matrix: dm <- matrix(1:25, ncol = 5); dm dm[] <- sample(dm); dm Edit: This is wrong: "I'm pretty sure that permuting first on columns and then on rows should give you the same result as

问题 I had a similar question using Postgres SQL, but I figured that this kind of task is really hard to do in Postgres, and I think python/pandas would make this a lot easier, although I still can't quite come up with the solution. I now have a Pandas Dataframe which looks like this: df={'planid' : ['A', 'A', 'B', 'B', 'C', 'C'], 'x' : ['a1', 'a2', 'b1', 'b2', 'c1', 'c2']} df=pd.DataFrame(df) df planid x 0 A a1 1 A a2 2 B b1 3 B b2 4 C c1 5 C c2 I want to get all possible permutations where

问题 I just can't wrap my head around recursion. I understand all of the concepts (breaking solution into smaller cases) and I can understand solutions after I read them over and over again. But I can never figure out how to use recursion to solve a problem. Is there any systematic way to come up with a recursive solution? Can someone please explain to me their thought process when they try to solve the following recursive problem: "Return all permutations of a string using recursion" . Here is an