hackerrank coding

If coin Order matters, that's, each sequence are unique, the DP function is a simple enough-to-make it 1D DP. But the key is this order doesn ' T matter, so we need to add one more state:ending coin. And for each DP advance step, we only put >= coins.#include #include#include#includeusing namespacestd;typedef unsignedLong LongULL;intMain () {unsigned n, m; CIN>> N >>m; VectorV (m); for(Unsigned i =0; I ) Cin>>V[i]; Std::sort (V.begin (), V.end ()); //dp[val][ending Coin]Vector1, Vector0)); d

Test instructions: Give you a positive integer n, ask how many positive integers you exist on a, B (aThe approximate number of all the numbers within N is preprocessed, then the violent enumeration A, the violent enumeration of X, and then enumerates all the n-ax, the sentence weight, the statistical answer can be.#include "Enumeration approximate" Hackerrank-week of Code 26-satisfactory Pairs

I made a few questions in HackerRank, so let's talk about it... Question: Give n and k, then give n numbers, and find the number of k pairs in the array. Where [N /* * Author: illuz

Kinda similar with another palindrome DP from Leetcode. Feel it, it is a bottom-up dp-palindrome subsequence.str =input () Slen=Len (str) DP= [[0 forXinchRange (Slen)] forXinchrange (Slen)] forCleninchRange (1, Slen + 1): forIinchRange (0, Slen-clen + 1): ifClen = = 1: Dp[i][i]= 1elifClen = = 2: Dp[i][i+ 1] = 2ifStr[i] = = Str[i+1]Else1Else: ifStr[i] = = Str[i + clen-1]: Dp[i][i+ Clen-1] = dp[i + 1][i + clen-2] + 2Else: Dp[i][i+ clen-1] = max (dp[i + 1][i + clen-2], dp[

Greedy-though Simple, but fun!#include #includeusing namespacestd;intMain () {intN1; intN2; intN3; CIN>> N1 >> n2 >>N3; Long LongL1 =0, L2 =0, L3 =0; Vectorint>H1 (N1); for(intH1_i =0; H1_i ) {cin>>H1[h1_i]; L1+=H1[h1_i]; } Vectorint>H2 (N2); for(intH2_i =0; H2_i ) {cin>>H2[h2_i]; L2+=H2[h2_i]; } Vectorint>H3 (N3); for(intH3_i =0; H3_i ) {cin>>H3[h3_i]; L3+=H3[h3_i]; } intI1 =0, I2 =0, i3 =0; while(! (L1 = = L2 L2 = =L3)) { //which stack is highest now? intMaxi =1; intM

(1, CC, 1): - # Down ins[(rr-1 + i) * m + (j + i)] = (rr-1 + i) * m + (j-1 +i) - forJinchXrange (Rr-2,-1,-1): to # Right +s[(j + i) * m + (cc-1 + i)] = (j + 1 + i) * m + (cc-1 +i) - forJinchXrange (Cc-2,-1,-1): the #Top *S[i * m + (j + i)] = i * m + (j + 1 +)i) $i + = 1Panax Notoginseng returns - the defMultiply (A, b): +n =Len (a) Ac = [] the forIinchxrange (n): + c.append (A[b[i]) - returnC $ $ defDisplacepow (A, k): -

DescriptionHave \ (n\) skills, each time through a wizard, a skill can be turned into another skill, ask most how many different skills.SolNetwork flow.First of all, the very naive I started, the skill will be split, the middle plus a list of wizards, \ (s\) to the initial skills of the number of edge capacity, the corresponding point between the capacity of the inf\, and then from the point to \ (t\) to the edge, the capacity is \ (1\), the wizard from the left side of a point to the right even

Please note input constraints. String length won't exceed, which means, we can use relatively naive representation\calculation for Anagrams:sorti Ng.#include #include#include#include#include#includeusing namespacestd;intCalcstringstr) { intRET =0; size_t Len=str.length (); Unordered_mapstring,int>Rec; for(size_t Ilen =1; Ilen ) { for(size_t i =0; I ) { stringCurr =str.substr (i, Ilen); Std::sort (Curr.begin (), Curr.end ()); Rec[curr]++; }

Original title AddressLeetcode also have this problem, directly sweep over the line, even the array is not open, feel like a certain kind of moving into the thought in the inside, to not be a moving titleCode:1#include 2#include 3#include 4#include 5#include 6 using namespacestd;7 8 intMain () {9 /*Enter your code here. Read input from STDIN. Print output to STDOUT*/ Ten intN; One intCurr_score, Prev_score, curr_cnt; A intdir, Len; - intres =0; - thePrev_score =-1; -curr_c

Typical tree recursion works. The key Is:any node can be treated as the root, since it was about edge and not on node. This simplifies things a lot.#include #include#include#include#include#includeusing namespaceStd;typedefLong Longlong64;structnode{Node (): Val (0{} Node (unsigned v): Val (v) {} long64 val; Unordered_setint>Inx;}; LONG64 ret= std::numeric_limits:: Max (); long64 Go (Vectorintroot, long64 tsum) {Noden =Nodes[root]; long64 Currsum=N.val; for(intI:n.inx) {nodes[i].inx.eras

Simplied a dfs\bfs with minor modification.#include #include#include#include#include#includeusing namespacestd;typedef VectorChar>>Matrix;typedef pairint,int>Pos;BOOLIsway (Matrix m,intIintj) { returnM[j][i] = ='.'|| M[j][i] = ='*';}BOOLGo (Matrix m, pos curr, POS DST,Const intKintN) { if(Curr = =DST) { returnn = =K; } inth =m.size (); intW = m[0].size (); inti =Curr.first; intj =Curr.second; VectorCands; if(I >0 Isway (M, I-1, J)) {Cands.push_back (Pos (i-1, J)); } if(I 1 Isw

]; -START_INDEX_A[I][J] = start_index_a[i +1][j]; theSTART_INDEX_B[I][J] = start_index_b[i +1][j]; +}Else { ALCD[I][J] = lcd[i][j +1]; theSTART_INDEX_A[I][J] = start_index_a[i][j +1]; +START_INDEX_B[I][J] = start_index_b[i][j +1]; - } $ } $ } - - inti = start_index_a[0][0]; the intj = start_index_b[0][0]; - while(I >=0 J >=0) {Wuyicout " "; the intII = Start_index_a[i +1][j +1]; - intJJ = Start_index_b[i +1][j +1]; Wui =II; -j =JJ; About

) Constraints1 S-1000 XX∈ ar Sample Input 71 3 9 8 2 7 5 Sample output 1 ExplanationInsertion Sort will take 9 "shifts" to sort the array. quicksort will take 8 "swaps" to sort it, as shown in the dimo-below. 9-8 = 1, the output. Question: the difference in the number of moves between quick sorting and inserted sorting elements in sorting. For insert sorting, count the number of moving elements; for fast sorting, count the number of switching elements (including switching between yourself and

Static intGetnumberofprimes (intN) {intn = n+1;//To include 0 as the first number for easy index operations later Final BooleanA[] =New Boolean[n];//Initialized to NULL by default.Arrays.fill (A,true); a[0] =false; a[1] =false; for(inti = 2; i i) {if(A[i]) { for(intj = i + i; J i) a[j]=false; } } intCount = 0; for(inti = 2;ii) {if(A[i]) {//System.out.print (i+ ",");++count; } } returncount; }[Hackerrank] P

A natural thought is brutal-force. But as you may have already thought of, there must be a smarter one. And yes there is. Think like this: XOR gives you all different bits, if you cocould imagine the binary representation of L ^ r, it can be represented as: 1xxxxx... what is asked is the 'maximum 'value of L ^ r-and that means 1111111... so this maximum value only depends on which is the highest 1-it is irrelevant with all intermediate values. so now the question turns to be: Which is the highe

We know that the encoding method should be declared in the header file of Python source code. If you don't just use ASCII code, many people may write a little different: # Coding = UTF-8 # Coding: UTF-8 #-*-Coding: UTF-8 -*- So how can we effectively write data? What advantages are ineffective? For more information, see http://www.python.org/dev/peps/p

1. Prediction code CompressionAlgorithmThe essence is to remove redundancy between signals. What is signal redundancy? The correlation between signals is redundancy. human hearing or visual systems that do not feel or mask can also be used as redundant components. Today we will talk about the concept of predictive coding, which is a very intuitive and simple method. It is intuitive. Taking an image as an example, There Are similarity and correlation

First, the concept of entropy coding:The bigger the entropy, the more chaotic.Entropy in Informatics: Used to measure the entropy of messages, and the uncertainty of information The more random and irrelevant information, the higher the entropy Source code theorem: This shows the relationship between the entropy of Shannon and the probability of the source sign. Entropy of information is the lower limit of average code length after lossless

Both arithmetic coding and program encoding are lossless compression. Arithmetic Coding) Arithmetic coding is a lossless data compression method and an entropy encoding method. Different from other entropy coding methods, other entropy coding methods usually divide input mes

commonly used in pixel encoding: 1. pulse Code Modulation (PCM); 2. entropy Coding; 3. run Length Coding; 4. bit Plane Coding (Bit Plane Coding ). Here, we will introduce the Huffman encoding and travel encoding in entropy (taking reading the. PCX file as an example ).The so-called predictive encoding is to remove the