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  • How Facebook's Ad Bid System Works

    - by pnongrata
    When you are creating an ad on Facebook, you are provided with a "suggested bid" range (e.g., $0.90 - $2.15 USD). According to this page: The suggested bid range is there to help you pick a maximum bid so your ad will be successful. It’s based on how many other advertisers are competing to show their ad to the same audience as you are. I'm interested in understanding what's actually going on (technically) under the hood here. Say a user logs into Facebook. On the server-side, it the HTTP request that the user's browser sent (as part of the login) is handled, and the server needs to figure out which ad to display back to the user. I assume this is where the "bidding" system comes into play? Say that, based on this user's demographics, and based on the audience targeting that several competing advertisers designed their campaign with, let's pretend that Facebook sees a pool of 20 different ads it could return. How does this bidding system help Facebook determine which of the 20 ads it returns to the client-side? I'm guessing that advertisers who "bid more" get prioritized over those who "bid less". But when does this bidding take place? How often does an advertiser need to re-bid? How long is a bid binding for? Once I understand these usage-related concepts behind ads, it will probably be obvious between which of the following "selection strategies" the backend is using: Round robin Prioritized round robin Randomized (doubtful) History-based MVP-based Thanks to anyone who can help point me in the right direction and explain what these suggested bid systems are and how they work.

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  • Shuffling algorithm with no "self-mapping"?

    - by OregonTrail
    To randomly shuffle an array, with no bias towards any particular permutation, there is the Knuth Fischer-Yeats algorithm. In Python: #!/usr/bin/env python import sys from random import randrange def KFYShuffle(items): i = len(items) - 1 while i > 0: j = randrange(i+1) # 0 <= j <= i items[j], items[i] = items[i], items[j] i = i - 1 return items print KFYShuffle(range(int(sys.argv[1]))) There is also Sattolo's algorithm, which produces random cycles. In Python: #!/usr/bin/env python import sys from random import randrange def SattoloShuffle(items): i = len(items) while i > 1: i = i - 1 j = randrange(i) # 0 <= j <= i-1 items[j], items[i] = items[i], items[j] return items print SattoloShuffle(range(int(sys.argv[1]))) I'm currently writing a simulation with the following specifications for a shuffling algorithm: The algorithm is unbiased. If a true random number generator was used, no permutation would be more likely than any other. No number ends up at its original index. The input to the shuffle will always be A[i] = i for i from 0 to N-1 Permutations are produced that are not cycles, but still meet specification 2. The cycles produced by Sattolo's algorithm meet specification 2, but not specification 1 or 3. I've been working at creating an algorithm that meets these specifications, what I came up with was equivalent to Sattolo's algorithm. Does anyone have an algorithm for this problem?

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  • Finding the lowest average Hamming distance when the order of the strings matter

    - by user1049697
    I have a sequence of binary strings that I want to find a match for among a set of longer sequences of binary strings. A match means that the compared sequence gives the lowest average Hamming distance when all elements in the shorter sequence have been matched against a sequence in one of the longer sets. Let me try to explain with an example. I have a set of video frames that have been hashed using a perceptual hashing algorithm so that the video frames that look the same has roughly the same hash. I want to match a short video clip against a set of longer videos, to see if the clip is contained in one of these. This means that I need to find out where the sequence of the hashed frames in the short video has the lowest average Hamming distance when compared with the long videos. The short video is the sub strings Sub1, Sub2 and Sub3, and I want to match them against the hashes of the long videos in Src. The clue here is that the strings need to match in the specific order that they are given in, e.g. that Sub1 always has to match the element before Sub2, and Sub2 always has to match the element before Sub3. In this example it would map thusly: Sub1-Src3, Sub2-Src4 and Sub3-Src5. So the question is this: is there an algorithm for finding the lowest average Hamming distance when the order of the elements compared matter? The naïve approach to compare the substring sequence to every source string won't cut it of course, so I need something that preferably can match a (much) shorter sub string to a set of million of elements. I have looked at MVP-trees, BK-trees and similar, but everything seems to only take into account one binary string and not a sequence of them. Sub1: 100111011111011101 Sub2: 110111000010010100 Sub3: 111111010110101101 Src1: 001011010001010110 Src2: 010111101000111001 Src3: 101111001110011101 Src4: 010111100011010101 Src5: 001111010110111101 Src6: 101011111111010101 I have added a calculation of the examples below. (The Hamming distances aren't correct, but it doesn't matter) **Run 1.** dist(Sub1, Src1) = 8 dist(Sub2, Src2) = 10 dist(Sub3, Src3) = 12 average = 10 **Run 2.** dist(Sub1, Src2) = 10 dist(Sub2, Src3) = 12 dist(Sub3, Src4) = 10 average = 11 **Run 3.** dist(Sub1, Src3) = 7 dist(Sub2, Src4) = 6 dist(Sub3, Src5) = 10 average = 8 **Run 4.** dist(Sub1, Src3) = 10 dist(Sub2, Src4) = 4 dist(Sub3, Src5) = 2 average = 5 So the winner here is sequence 4 with an average distance of 5.

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  • Designing Algorithm Flowchart Application

    - by l46kok
    I need to develop an GUI application in C# where users can freely add conditional/statement blocks on the algorithm flowchart like the one shown below. By freely, I mean users can add a block on wherever the arrows are. I'm having some problems brainstorming how to approach this problem, especially what to choose for my datastructure to store the blocks. I was thinking LinkedList since everything follows a linear fashion and every node always has a head and tail, but the If/Else block (ba) has two branches (heads) to store, so this complicates things a little bit. How would a smart one approach problems like this? My apologies if this question isn't suited for Programmers stackexchange, but this is more of a conceptual problem rather than implementation problem so I figured this place was appropriate for the question.

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  • How/where to run the algorithm on large dataset?

    - by niko
    I would like to run the PageRank algorithm on graph with 4 000 000 nodes and around 45 000 000 edges. Currently I use neo4j graph databse and classic relational database (postgres) and for software projects I mostly use C# and Java. Does anyone know what would be the best way to perform a PageRank computation on such graph? Is there any way to modify the PageRank algorithm in order to run it at home computer or server (48GB RAM) or is there any useful cloud service to push the data along the algorithm and retrieve the results? At this stage the project is at the research stage so in case of using cloud service if possible, would like to use such provider that doesn't require much administration and service setup, but instead focus just on running the algorith once and get the results without much overhead administration work.

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  • How to round currency values [migrated]

    - by Kenny
    I already have several ways to solve this, but I am interested in whether there is a better solution to this problem. Please only respond with a pure numeric algorithm. String manipulation is not acceptable. I am looking for an elegant and efficient solution. Given a currency value (ie $251.03), split the value into two half and round to two decimal places. The key is that the first half should round up and the second should round down. So the outcome in this scenario should be $125.52 and $125.51.

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  • Improving grepping over a huge file performance

    - by rogerio_marcio
    I have FILE_A which has over 300K lines and FILE_B which has over 30M lines. I created a bash script that greps each line in FILE_A over in FILE_B and writes the result of the grep to a new file. This whole process is taking over 5+ hours. I'm looking for suggestions on whether you see any way of improving the performance of my script. I'm using grep -F -m 1 as the grep command. FILE_A looks like this: 123456789 123455321 and FILE_B is like this: 123456789,123456789,730025400149993, 123455321,123455321,730025400126097, So with bash I have a while loop that picks the next line in FILE_A and greps it over in FILE_B. When the pattern is found in FILE_B i write it to result.txt. while read -r line; do grep -F -m1 $line 30MFile done < 300KFile Thanks a lot in advance for your help.

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  • Does it matter the direction of a Huffman's tree child node?

    - by Omega
    So, I'm on my quest about creating a Java implementation of Huffman's algorithm for compressing/decompressing files (as you might know, ever since Why create a Huffman tree per character instead of a Node?) for a school assignment. I now have a better understanding of how is this thing supposed to work. Wikipedia has a great-looking algorithm here that seemed to make my life way easier. Taken from http://en.wikipedia.org/wiki/Huffman_coding: Create a leaf node for each symbol and add it to the priority queue. While there is more than one node in the queue: Remove the two nodes of highest priority (lowest probability) from the queue Create a new internal node with these two nodes as children and with probability equal to the sum of the two nodes' probabilities. Add the new node to the queue. The remaining node is the root node and the tree is complete. It looks simple and great. However, it left me wondering: when I "merge" two nodes (make them children of a new internal node), does it even matter what direction (left or right) will each node be afterwards? I still don't fully understand Huffman coding, and I'm not very sure if there is a criteria used to tell whether a node should go to the right or to the left. I assumed that, perhaps the highest-frequency node would go to the right, but I've seen some Huffman trees in the web that don't seem to follow such criteria. For instance, Wikipedia's example image http://upload.wikimedia.org/wikipedia/commons/thumb/8/82/Huffman_tree_2.svg/625px-Huffman_tree_2.svg.png seems to put the highest ones to the right. But other images like this one http://thalia.spec.gmu.edu/~pparis/classes/notes_101/img25.gif has them all to the left. However, they're never mixed up in the same image (some to the right and others to the left). So, does it matter? Why?

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  • Simplified knapsack in PHP

    - by Mikhail
    I have two instances where I'd like to display information in a "justified" alignment - but I don't care if the values are switched in order. One example being displaying the usernames of people online: Anton Brother68 Commissar Dougheater Elflord Foobar Goop Hoo Iee Joo Rearranging them we could get exactly 22 characters long on each line: Anton Brother68 Foobar Commissar Elflord Goop Dougheater Hoo Iee Joo This is kind of a knapsack, except seems like there ought to be a P solution since I don't care about perfection, and I have multiple lines. Second instance is identical, except instead of names and character count I would be displaying random images and use their width.

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  • C# 5 Async, Part 2: Asynchrony Today

    - by Reed
    The .NET Framework has always supported asynchronous operations.  However, different mechanisms for supporting exist throughout the framework.  While there are at least three separate asynchronous patterns used through the framework, only the latest is directly usable with the new Visual Studio Async CTP.  Before delving into details on the new features, I will talk about existing asynchronous code, and demonstrate how to adapt it for use with the new pattern. The first asynchronous pattern used in the .NET framework was the Asynchronous Programming Model (APM).  This pattern was based around callbacks.  A method is used to start the operation.  It typically is named as BeginSomeOperation.  This method is passed a callback defined as an AsyncCallback, and returns an object that implements IAsyncResult.  Later, the IAsyncResult is used in a call to a method named EndSomeOperation, which blocks until completion and returns the value normally directly returned from the synchronous version of the operation.  Often, the EndSomeOperation call would be called from the callback function passed, which allows you to write code that never blocks. While this pattern works perfectly to prevent blocking, it can make quite confusing code, and be difficult to implement.  For example, the sample code provided for FileStream’s BeginRead/EndRead methods is not simple to understand.  In addition, implementing your own asynchronous methods requires creating an entire class just to implement the IAsyncResult. Given the complexity of the APM, other options have been introduced in later versions of the framework.  The next major pattern introduced was the Event-based Asynchronous Pattern (EAP).  This provides a simpler pattern for asynchronous operations.  It works by providing a method typically named SomeOperationAsync, which signals its completion via an event typically named SomeOperationCompleted. The EAP provides a simpler model for asynchronous programming.  It is much easier to understand and use, and far simpler to implement.  Instead of requiring a custom class and callbacks, the standard event mechanism in C# is used directly.  For example, the WebClient class uses this extensively.  A method is used, such as DownloadDataAsync, and the results are returned via the DownloadDataCompleted event. While the EAP is far simpler to understand and use than the APM, it is still not ideal.  By separating your code into method calls and event handlers, the logic of your program gets more complex.  It also typically loses the ability to block until the result is received, which is often useful.  Blocking often requires writing the code to block by hand, which is error prone and adds complexity. As a result, .NET 4 introduced a third major pattern for asynchronous programming.  The Task<T> class introduced a new, simpler concept for asynchrony.  Task and Task<T> effectively represent an operation that will complete at some point in the future.  This is a perfect model for thinking about asynchronous code, and is the preferred model for all new code going forward.  Task and Task<T> provide all of the advantages of both the APM and the EAP models – you have the ability to block on results (via Task.Wait() or Task<T>.Result), and you can stay completely asynchronous via the use of Task Continuations.  In addition, the Task class provides a new model for task composition and error and cancelation handling.  This is a far superior option to the previous asynchronous patterns. The Visual Studio Async CTP extends the Task based asynchronous model, allowing it to be used in a much simpler manner.  However, it requires the use of Task and Task<T> for all operations.

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  • deciphering columnar transposition cipher

    - by Arfan M
    I am looking for an idea on how to decipher a columnar transposition cipher without knowing the key or the length of the key. When I take the cipher text as input to my algorithm I will guess the length of the key to be the factors of the length of the cipher text. I will take the first factor suppose the length was 20 letters so I will take 2*10 (2 rows and 10 columns). Now I want to arrange the cipher text in the columns and read it row wise to see if there is any word forming and match it with a dictionary if it is something sensible. If it matches the dictionary then it means it is in correct order or else I want to know how to make other combinations of the columns and read the string again row wise. Please suggest another approach that is more efficient.

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  • How can I find the shortest path between two subgraphs of a larger graph?

    - by Pops
    I'm working with a weighted, undirected multigraph (loops not permitted; most node connections have multiplicity 1; a few node connections have multiplicity 2). I need to find the shortest path between two subgraphs of this graph that do not overlap with each other. There are no other restrictions on which nodes should be used as start/end points. Edges can be selectively removed from the graph at certain times (as explained in my previous question) so it's possible that for two given subgraphs, there might not be any way to connect them. I'm pretty sure I've heard of an algorithm for this before, but I can't remember what it's called, and my Google searches for strings like "shortest path between subgraphs" haven't helped. Can someone suggest a more efficient way to do this than comparing shortest paths between all nodes in one subgraph with all nodes in the other subgraph? Or at least tell me the name of the algorithm so I can look it up myself? For example, if I have the graph below, the nodes circled in red might be one subgraph and the nodes circled in blue might be another. The edges would all have positive integer weights, although they're not shown in the image. I'd want to find whatever path has the shortest total cost as long as it starts at a red node and ends at a blue node. I believe this means the specific node positions and edge weights cannot be ignored. (This is just an example graph I grabbed off Wikimedia and drew on, not my actual problem.)

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  • Complex algorithm for complex problem

    - by Locaaaaa
    I got this question in an interview and I was not able to solve it. You have a circular road, with N number of gas stations. You know the ammount of gas that each station has. You know the ammount of gas you need to GO from one station to the next one. Your car starts with 0. The question is: Create an algorithm, to know from which gas station you must start driving. As an exercise to me, I would translate the algorithm to C#.

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  • Is it just me or is this a baffling tech interview question

    - by Matthew Patrick Cashatt
    Background I was just asked in a tech interview to write an algorithm to traverse an "object" (notice the quotes) where A is equal to B and B is equal to C and A is equal to C. That's it. That is all the information I was given. I asked the interviewer what the goal was but apparently there wasn't one, just "traverse" the "object". I don't know about anyone else, but this seems like a silly question to me. I asked again, "am I searching for a value?". Nope. Just "traverse" it. Why would I ever want to endlessly loop through this "object"?? To melt my processor maybe?? The answer according to the interviewer was that I should have written a recursive function. OK, so why not simply ask me to write a recursive function? And who would write a recursive function that never ends? My question: Is this a valid question to the rest of you and, if so, can you provide a hint as to what I might be missing? Perhaps I am thinking too hard about solving real world problems. I have been successfully coding for a long time but this tech interview process makes me feel like I don't know anything. Final Answer: CLOWN TRAVERSAL!!! (See @Matt's answer below) Thanks! Matt

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  • how to work with strings and integers as bit strings in python?

    - by Manuel
    Hello! I'm developing a Genetic Algorithm in python were chromosomes are composed of strings and integers. To apply the genetic operations, I want to convert these groups of integers and strings into bit strings. For example, if one chromosome is: ["Hello", 4, "anotherString"] I'd like it to become something like: 0100100100101001010011110011 (this is not actual translation). So... How can I do this? Chromosomes will contain the same amount of strings and integers, but this numbers can vary from one algorithm run to another. To be clear, what I want to obtain is the bit representation of each element in the chromosome concatenated. If you think this would not be the best way to apply genetic operators (such as mutation and simple crossover) just tell me! I'm open to new ideas. Thanks a lot! Manuel

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  • Number crunching algo for learning multithreading?

    - by Austin Henley
    I have never really implemented anything dealing with threads; my only experience with them is reading about them in my undergrad. So I want to change that by writing a program that does some number crunching, but splits it up into several threads. My first ideas for this hopefully simple multithreaded program were: Beal's Conjecture brute force based on my SO question. Bailey-Borwein-Plouffe formula for calculating Pi. Prime number brute force search As you can see I have an interest in math and thought it would be fun to incorporate it into this, rather than coding something such as a server which wouldn't be nearly as fun! But the 3 ideas don't seem very appealing and I have already done some work on them in the past so I was curious if anyone had any ideas in the same spirit as these 3 that I could implement?

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  • Algorithm to figure out appointment times?

    - by Rachel
    I have a weird situation where a client would like a script that automatically sets up thousands of appointments over several days. The tricky part is the appointments are for a variety of US time zones, and I need to take the consumer's local time zone into account when generating appointment dates and times for each record. Appointment Rules: Appointments should be set from 8AM to 8PM Eastern Standard Time, with breaks from 12P-2P and 4P-6P. This leaves a total of 8 hours per day available for setting appointments. Appointments should be scheduled 5 minutes apart. 8 hours of 5-minute intervals means 96 appointments per day. There will be 5 users at a time handling appointments. 96 appointments per day multiplied by 5 users equals 480, so the maximum number of appointments that can be set per day is 480. Now the tricky requirement: Appointments are restricted to 8am to 8pm in the consumer's local time zone. This means that the earliest time allowed for each appointment is different depending on the consumer's time zone: Eastern: 8A Central: 9A Mountain: 10A Pacific: 11A Alaska: 12P Hawaii or Undefined: 2P Arizona: 10A or 11A based on current Daylight Savings Time Assuming a data set can be several thousand records, and each record will contain a timezone value, is there an algorithm I could use to determine a Date and Time for every record that matches the rules above?

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  • How can I best study a problem to determine whether recursion can/should be used?

    - by user10326
    In some cases, I fail to see that a problem could be solved by the divide and conquer method. To give a specific example, when studying the find max sub-array problem, my first approach is to brute force it by using a double loop to find the max subarray. When I saw the solution using the divide and conquer approach which is recursion-based, I understood it but ok. From my side, though, when I first read the problem statement, I did not think that recursion is applicable. When studying a problem, is there any technique or trick to see that a recursion based (i.e. divide and conquer) approach can be used or not?

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  • Is it possible to efficiently store all possible phone numbers in memory?

    - by Spencer K
    Given the standard North American phone number format: (Area Code) Exchange - Subscriber, the set of possible numbers is about 6 billion. However, efficiently breaking down the nodes into the sections listed above would yield less than 12000 distinct nodes that can be arranged in groupings to get all the possible numbers. This seems like a problem already solved. Would it done via a graph or tree?

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  • How to find Sub-trees in non-binary tree

    - by kenny
    I have a non-binary tree. I want to find all "sub-trees" that are connected to root. Sub-tree is a a link group of tree nodes. every group is colored in it's own color. What would be be the best approach? Run recursion down and up for every node? The data structure of every treenode is a list of children, list of parents. (the type of children and parents are treenodes) Clarification: Group defined if there is a kind of "closure" between nodes where root itself is not part of the closure. As you can see from the graph you can't travel from pink to other nodes (you CAN NOT use root). From brown node you can travel to it's child so this form another group. Finally you can travel from any cyan node to other cyan nodes so the form another group

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  • Advice for a getting a job in algorithmic trading - writing faster code

    - by Alex
    I am currently an intermediate Java developer working in the financial industry. I am considering trying to get into an algorithmic trading developer position. I am looking for any advice/resources that may help me obtain such a job. My naive initial thoughts are to concentrate on learning how to write faster, more memory efficient code whilst maintaining readability. Can anyone point me in the right direction of some useful resources for what I am aiming to achieve?

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  • Algorithm for Shortest Job First with Preemption

    - by Shray
    I want to implement a shortest job first routine using C# or C++. Priority of Jobs are based on their processing time. Jobs are processed using a binary (min) heap. There are three types of jobs. Type 1 is when jobs come in between every 4-6 seconds, with processing times between 4-6. Type 2 job comes in between 8-12 seconds, with processing times between 8-12. Type 3 job comes in between 24-26 seconds, with processing times between 14-16. So far, I have written the binary heap functionality, but Im kinda confused on how to start processing spawn and also the processor. #include <iostream> #include <stdlib.h> #include <time.h> using namespace std; int timecounting = 20; struct process{ int atime; int ptime; int type; }; class pque{ private: int count; public: process pheap[100]; process type1[100]; process type2[100]; process type3[100]; process type4[100]; pque(){ count = 0; } void swap(int a, int b){ process tempa = pheap[a]; process tempb = pheap[b]; pheap[b] = tempa; pheap[a] = tempb; } void add(process c){ int current; count++; pheap[count] = c; if(count > 0){ current = count; while(pheap[count/2].ptime > pheap[current].ptime){ swap(current/2, current); current = current/2; } } } void remove(){ process temp = pheap[1]; // saves process to temporary pheap[1] = pheap[count]; //takes last process in heap, and puts it at the root int n = 1; int leftchild = 2*n; int rightchild = 2*n + 1; while(leftchild < count && rightchild < count) { if(pheap[leftchild].ptime > pheap[rightchild].ptime) { if(pheap[leftchild].ptime > pheap[n].ptime) { swap(leftchild, n); n = leftchild; int leftchild = 2*n; int rightchild = 2*n + 1; } } else { if(pheap[rightchild].ptime > pheap[n].ptime) { swap(rightchild, n); n = rightchild; int leftchild = 2*n; int rightchild = 2*n + 1; } } } } void spawn1(){ process p; process p1; p1.atime = 0; int i = 0; srand(time(NULL)); while(i < timecounting) { p.atime = rand()%3 + 4 + p1.atime; p.ptime = rand()%5 + 1; p1.atime = p.atime; p.type = 1; type1[i+1] = p; i++; } } void spawn2(){ process p; process p1; p1.atime = 0; srand(time(NULL)); int i = 0; while(i < timecounting) { p.atime = rand()%3 + 9 + p1.atime; p.ptime = rand()%5 + 6; p1.atime = p.atime; p.type = 2; type2[i+1] = p; i++; } } void spawn3(){ process p; process p1; p1.atime = 0; srand(time(NULL)); int i = 0; while(i < timecounting) { p.atime = rand()%3 + 25 + p1.atime; p.ptime = rand()%5 + 11; p1.atime = p.atime; p.type = 3; type3[i+1] = p; i++; } } void spawn4(){ process p; process p1; p1.atime = 0; srand(time(NULL)); int i = 0; while(i < timecounting) { p.atime = rand()%6 + 30 + p1.atime; p.ptime = rand()%5 + 8; p1.atime = p.atime; p.type = 4; type4[i+1] = p; i++; } } void processor() { process p; process p1; p1.atime = 0; int n = 1; int n1 = 1; int n2 = 1; for(int i = 0; i<timecounting;i++) { if(type1[n].atime == i) { add(type1[n]); n++; } if(type2[n1].atime == i) { add(type1[n1]); n1++; } if(type3[n2].atime == i) { add(type1[n2]); n2++; } /* if(pheap[1].atime <= i) { while(pheap[1].atime != 0){ pheap[1].atime--; i++; } remove(); }*/ } } };

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  • Conways Game of Life C#

    - by Darren Young
    Hi, Not sure if this is the correct place for this question or SO - mods please move if necessary. I am going to have a go at creating GoL over the weekend as a little test project : http://en.wikipedia.org/wiki/Conway's_Game_of_Life I understand the algorithm, however I just wanted to check regarding the implementation, from maybe somebody that has tried it. Essentially, my first (basic) implementation, will be a static grid at a set speed. If I understand correctly, these are the steps I will need: Initial seed Create 2d array with initial set up Foreach iteration, create temporary array, calculating each cells new state based on the Game of Life algorithm Assign temp array to proper array. Redraw grid from proper array. My concerns are over speed. When I am populating the grid from the array, would it simply be a case of looping through the array, assigning on or off to each grid cell and then redraw the grid? Am I on the correct path?

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  • evaluating a code of a graph [migrated]

    - by mazen.r.f
    This is relatively a long code,if you have the tolerance and the will to find out how to make this code work then take a look please, i will appreciate your feed back. i have spent two days trying to come up with a code to represent a graph , then calculate the shortest path using dijkastra algorithm , but i am not able to get the right result , even the code runs without errors , but the result is not correct , always i am getting 0. briefly,i have three classes , Vertex, Edge, Graph , the Vertex class represents the nodes in the graph and it has id and carried ( which carry the weight of the links connected to it while using dijkastra algorithm ) and a vector of the ids belong to other nodes the path will go through before arriving to the node itself , this vector is named previous_nodes. the Edge class represents the edges in the graph it has two vertices ( one in each side ) and a wight ( the distance between the two vertices ). the Graph class represents the graph , it has two vectors one is the vertices included in this graph , and the other is the edges included in the graph. inside the class Graph there is a method its name shortest takes the sources node id and the destination and calculates the shortest path using dijkastra algorithm, and i think that it is the most important part of the code. my theory about the code is that i will create two vectors one for the vertices in the graph i will name it vertices and another vector its name is ver_out it will include the vertices out of calculation in the graph, also i will have two vectors of type Edge , one its name edges for all the edges in the graph and the other its name is track to contain temporarily the edges linked to the temporarily source node in every round , after the calculation of every round the vector track will be cleared. in main() i created five vertices and 10 edges to simulate a graph , the result of the shortest path supposedly to be 4 , but i am always getting 0 , that means i am having something wrong in my code , so if you are interesting in helping me find my mistake and how to make the code work , please take a look. the way shortest work is as follow at the beginning all the edges will be included in the vector edges , we select the edges related to the source and put them in the vector track , then we iterate through track and add the wight of every edge to the vertex (node ) related to it ( not the source vertex ) , then after we clear track and remove the source vertex from the vector vertices and select a new source , and start over again select the edges related to the new source , put them in track , iterate over edges in tack , adding the weights to the corresponding vertices then remove this vertex from the vector vertices, and clear track , and select a new source , and so on . here is the code. #include<iostream> #include<vector> #include <stdlib.h> // for rand() using namespace std; class Vertex { private: unsigned int id; // the name of the vertex unsigned int carried; // the weight a vertex may carry when calculating shortest path vector<unsigned int> previous_nodes; public: unsigned int get_id(){return id;}; unsigned int get_carried(){return carried;}; void set_id(unsigned int value) {id = value;}; void set_carried(unsigned int value) {carried = value;}; void previous_nodes_update(unsigned int val){previous_nodes.push_back(val);}; void previous_nodes_erase(unsigned int val){previous_nodes.erase(previous_nodes.begin() + val);}; Vertex(unsigned int init_val = 0, unsigned int init_carried = 0) :id (init_val), carried(init_carried) // constructor { } ~Vertex() {}; // destructor }; class Edge { private: Vertex first_vertex; // a vertex on one side of the edge Vertex second_vertex; // a vertex on the other side of the edge unsigned int weight; // the value of the edge ( or its weight ) public: unsigned int get_weight() {return weight;}; void set_weight(unsigned int value) {weight = value;}; Vertex get_ver_1(){return first_vertex;}; Vertex get_ver_2(){return second_vertex;}; void set_first_vertex(Vertex v1) {first_vertex = v1;}; void set_second_vertex(Vertex v2) {second_vertex = v2;}; Edge(const Vertex& vertex_1 = 0, const Vertex& vertex_2 = 0, unsigned int init_weight = 0) : first_vertex(vertex_1), second_vertex(vertex_2), weight(init_weight) { } ~Edge() {} ; // destructor }; class Graph { private: std::vector<Vertex> vertices; std::vector<Edge> edges; public: Graph(vector<Vertex> ver_vector, vector<Edge> edg_vector) : vertices(ver_vector), edges(edg_vector) { } ~Graph() {}; vector<Vertex> get_vertices(){return vertices;}; vector<Edge> get_edges(){return edges;}; void set_vertices(vector<Vertex> vector_value) {vertices = vector_value;}; void set_edges(vector<Edge> vector_ed_value) {edges = vector_ed_value;}; unsigned int shortest(unsigned int src, unsigned int dis) { vector<Vertex> ver_out; vector<Edge> track; for(unsigned int i = 0; i < edges.size(); ++i) { if((edges[i].get_ver_1().get_id() == vertices[src].get_id()) || (edges[i].get_ver_2().get_id() == vertices[src].get_id())) { track.push_back (edges[i]); edges.erase(edges.begin()+i); } }; for(unsigned int i = 0; i < track.size(); ++i) { if(track[i].get_ver_1().get_id() != vertices[src].get_id()) { track[i].get_ver_1().set_carried((track[i].get_weight()) + track[i].get_ver_2().get_carried()); track[i].get_ver_1().previous_nodes_update(vertices[src].get_id()); } else { track[i].get_ver_2().set_carried((track[i].get_weight()) + track[i].get_ver_1().get_carried()); track[i].get_ver_2().previous_nodes_update(vertices[src].get_id()); } } for(unsigned int i = 0; i < vertices.size(); ++i) if(vertices[i].get_id() == src) vertices.erase(vertices.begin() + i); // removing the sources vertex from the vertices vector ver_out.push_back (vertices[src]); track.clear(); if(vertices[0].get_id() != dis) {src = vertices[0].get_id();} else {src = vertices[1].get_id();} for(unsigned int i = 0; i < vertices.size(); ++i) if((vertices[i].get_carried() < vertices[src].get_carried()) && (vertices[i].get_id() != dis)) src = vertices[i].get_id(); //while(!edges.empty()) for(unsigned int round = 0; round < vertices.size(); ++round) { for(unsigned int k = 0; k < edges.size(); ++k) { if((edges[k].get_ver_1().get_id() == vertices[src].get_id()) || (edges[k].get_ver_2().get_id() == vertices[src].get_id())) { track.push_back (edges[k]); edges.erase(edges.begin()+k); } }; for(unsigned int n = 0; n < track.size(); ++n) if((track[n].get_ver_1().get_id() != vertices[src].get_id()) && (track[n].get_ver_1().get_carried() > (track[n].get_ver_2().get_carried() + track[n].get_weight()))) { track[n].get_ver_1().set_carried((track[n].get_weight()) + track[n].get_ver_2().get_carried()); track[n].get_ver_1().previous_nodes_update(vertices[src].get_id()); } else if(track[n].get_ver_2().get_carried() > (track[n].get_ver_1().get_carried() + track[n].get_weight())) { track[n].get_ver_2().set_carried((track[n].get_weight()) + track[n].get_ver_1().get_carried()); track[n].get_ver_2().previous_nodes_update(vertices[src].get_id()); } for(unsigned int t = 0; t < vertices.size(); ++t) if(vertices[t].get_id() == src) vertices.erase(vertices.begin() + t); track.clear(); if(vertices[0].get_id() != dis) {src = vertices[0].get_id();} else {src = vertices[1].get_id();} for(unsigned int tt = 0; tt < edges.size(); ++tt) { if(vertices[tt].get_carried() < vertices[src].get_carried()) { src = vertices[tt].get_id(); } } } return vertices[dis].get_carried(); } }; int main() { cout<< "Hello, This is a graph"<< endl; vector<Vertex> vers(5); vers[0].set_id(0); vers[1].set_id(1); vers[2].set_id(2); vers[3].set_id(3); vers[4].set_id(4); vector<Edge> eds(10); eds[0].set_first_vertex(vers[0]); eds[0].set_second_vertex(vers[1]); eds[0].set_weight(5); eds[1].set_first_vertex(vers[0]); eds[1].set_second_vertex(vers[2]); eds[1].set_weight(9); eds[2].set_first_vertex(vers[0]); eds[2].set_second_vertex(vers[3]); eds[2].set_weight(4); eds[3].set_first_vertex(vers[0]); eds[3].set_second_vertex(vers[4]); eds[3].set_weight(6); eds[4].set_first_vertex(vers[1]); eds[4].set_second_vertex(vers[2]); eds[4].set_weight(2); eds[5].set_first_vertex(vers[1]); eds[5].set_second_vertex(vers[3]); eds[5].set_weight(5); eds[6].set_first_vertex(vers[1]); eds[6].set_second_vertex(vers[4]); eds[6].set_weight(7); eds[7].set_first_vertex(vers[2]); eds[7].set_second_vertex(vers[3]); eds[7].set_weight(1); eds[8].set_first_vertex(vers[2]); eds[8].set_second_vertex(vers[4]); eds[8].set_weight(8); eds[9].set_first_vertex(vers[3]); eds[9].set_second_vertex(vers[4]); eds[9].set_weight(3); unsigned int path; Graph graf(vers, eds); path = graf.shortest(2, 4); cout<< path << endl; return 0; }

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  • Is there a way to add unique items to an array without doing a ton of comparisons?

    - by hydroparadise
    Please bare with me, I want this to be as language agnostic as possible becuase of the languages I am working with (One of which is a language called PowerOn). However, most languanges support for loops and arrays. Say I have the following list in an aray: 0x 0 Foo 1x 1 Bar 2x 0 Widget 3x 1 Whatsit 4x 0 Foo 5x 1 Bar Anything with a 1 should be uniqely added to another array with the following result: 0x 1 Bar 1x 1 Whatsit Keep in mind this is a very elementry example. In reality, I am dealing with 10's of thousands of elements on the old list. Here is what I have so far. Pseudo Code: For each element in oldlist For each element in newlist Compare If values oldlist.element equals newlist.element, break new list loop If reached end of newlist with with nothing equal from oldlist, add value from old list to new list End End Is there a better way of doing this? Algorithmicly, is there any room for improvement? And as a bonus qeustion, what is the O notation for this type of algorithm (if there is one)?

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