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  • Octrees and Vertex Buffer Objects

    - by sharethis
    As many others I want to code a game with a voxel based terrain. The data is represented by voxels which are rendered using triangles. I head of two different approaches and want to combine them. First, I could once divide the space in chunks of a fixed size like many games do. What I could do now is to generate a polygon shape for each chunk and store that in a vertex buffer object (vbo). Each time a voxel changes, the polygon and vbo of its chunk is recreated. Additionally it is easy to dynamically load and reload parts of the terrain. Another approach would be to use octrees and divide the space in eight cubes which are divided again and again. So I could efficiently render the terrain because I don't have to go deeper in a solid cube and can draw that as a single one (with a repeated texture). What I like to use for my game is an octree datastructure. But I can't imagine how to use vbos with that. How is that done, or is this impossible?

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  • nginx hashing on GET parameter

    - by Sparsh Gupta
    I have two Varnish servers and I plan to add more varnish servers. I am using a nginx load balancer to divide traffic to these varnish servers. To utilize maximum RAM of each varnish server, I need that same request reaches same varnish server. Same request can be identified by one GET parameter in the request URL say 'a' In a normal code, I would do something like- (if I need to divide all traffic between 2 Varnish servers) if($arg_a % 2 == 0) { proxy_pass varnish1; } if($arg_a % 2 == 1) { proxy_pass varnish2; } This is basically doing a even / odd check on GET parameter a and then deciding which upstream pool to send the request. My question are- What is the nginx equivalent of such a code. I dont know if nginx accepts modulas Is there a better/ efficient hashing function built in with nginx (0.8.54) which I can possibly use. In future I want to add more upstream pools so I need not to change %2 to %3 %4 and so on Any other alternate way to solve this problem

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  • How to reference or vlookup a list of values based on a comma separated list of column references within a cell in excel?

    - by glallen
    I want to do a vlookup (or similar) against a column which is a list of values. This works fine for looking up a value from a single row, but I want to be able to look up multiple rows, sum the results, and divide by the number of rows referenced. For example: A B C D E F G [----given values----------------] [Work/Auth] [sum(vlookup(each(G),table,5)) /count(G)] [given vals] 1 Item Authorized OnHand Working Operational% DependencyOR% Dependencies 2 A 1 1 1 1 .55 B 3 B 10 5 5 .50 .55 C,D 4 C 100 75 50 .50 .60 D 5 D 10 10 6 .60 1 I want to be able to show an Operational Rate, and an operational rate of the systems each system depends on (F). In order to get a value for F, I want to sum over each value in column-E that was referenced by a dependency in column-G then divide by the number of dependencies in G. Column-G can have varying lengths, and will be a comma separated list of values from column-A. Is there any way to do this in excel?

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  • Can i use a switch to hold a function?

    - by TIMOTHY
    I have a 3 file program, basically teaching myself c++. I have an issue. I made a switch to use the math function. I need and put it in a variable, but for some reason I get a zero as a result. Also another issue, when I select 4 (divide) it crashes... Is there a reason? Main file: #include <iostream> #include "math.h" #include <string> using namespace std; int opersel; int c; int a; int b; string test; int main(){ cout << "Welcome to Math-matrix v.34"<< endl; cout << "Shall we begin?" <<endl; //ASK USER IF THEY ARE READY TO BEGIN string answer; cin >> answer; if(answer == "yes" || answer == "YES" || answer == "Yes") { cout << "excellent lets begin..." << endl; cout << "please select a operator..." << endl << endl; cout << "(1) + " << endl; cout << "(2) - " << endl; cout << "(3) * " << endl; cout << "(4) / " << endl; cin >> opersel; switch(opersel){ case 1: c = add(a,b); break; case 2: c = sub(a,b); break; case 3: c = multi(a,b); break; case 4: c = divide(a,b); break; default: cout << "error... retry" << endl; }// end retry cout << "alright, how please select first digit?" << endl; cin >> a; cout << "excellent... and your second?" << endl; cin >> b; cout << c; cin >> test; }else if (answer == "no" || answer == "NO" || answer == "No"){ }//GAME ENDS }// end of int main Here is my math.h file #ifndef MATH_H #define MATH_H int add(int a, int b); int sub(int a, int b); int multi(int a, int b); int divide(int a, int b); #endif Here is my math.cpp: int add(int a, int b) { return a + b; } int sub(int a, int b) { return a - b; } int multi(int a, int b) { return a * b; } int divide(int a, int b) { return a / b; } }// end of int main

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  • Scala parser combinator runs out of memory

    - by user3217013
    I wrote the following parser in Scala using the parser combinators: import scala.util.parsing.combinator._ import scala.collection.Map import scala.io.StdIn object Keywords { val Define = "define" val True = "true" val False = "false" val If = "if" val Then = "then" val Else = "else" val Return = "return" val Pass = "pass" val Conj = ";" val OpenParen = "(" val CloseParen = ")" val OpenBrack = "{" val CloseBrack = "}" val Comma = "," val Plus = "+" val Minus = "-" val Times = "*" val Divide = "/" val Pow = "**" val And = "&&" val Or = "||" val Xor = "^^" val Not = "!" val Equals = "==" val NotEquals = "!=" val Assignment = "=" } //--------------------------------------------------------------------------------- sealed abstract class Op case object Plus extends Op case object Minus extends Op case object Times extends Op case object Divide extends Op case object Pow extends Op case object And extends Op case object Or extends Op case object Xor extends Op case object Not extends Op case object Equals extends Op case object NotEquals extends Op case object Assignment extends Op //--------------------------------------------------------------------------------- sealed abstract class Term case object TrueTerm extends Term case object FalseTerm extends Term case class FloatTerm(value : Float) extends Term case class StringTerm(value : String) extends Term case class Identifier(name : String) extends Term //--------------------------------------------------------------------------------- sealed abstract class Expression case class TermExp(term : Term) extends Expression case class UnaryOp(op : Op, exp : Expression) extends Expression case class BinaryOp(op : Op, left : Expression, right : Expression) extends Expression case class FuncApp(funcName : Term, args : List[Expression]) extends Expression //--------------------------------------------------------------------------------- sealed abstract class Statement case class ExpressionStatement(exp : Expression) extends Statement case class Pass() extends Statement case class Return(value : Expression) extends Statement case class AssignmentVar(variable : Term, exp : Expression) extends Statement case class IfThenElse(testBody : Expression, thenBody : Statement, elseBody : Statement) extends Statement case class Conjunction(left : Statement, right : Statement) extends Statement case class AssignmentFunc(functionName : Term, args : List[Term], body : Statement) extends Statement //--------------------------------------------------------------------------------- class myParser extends JavaTokenParsers { val keywordMap : Map[String, Op] = Map( Keywords.Plus -> Plus, Keywords.Minus -> Minus, Keywords.Times -> Times, Keywords.Divide -> Divide, Keywords.Pow -> Pow, Keywords.And -> And, Keywords.Or -> Or, Keywords.Xor -> Xor, Keywords.Not -> Not, Keywords.Equals -> Equals, Keywords.NotEquals -> NotEquals, Keywords.Assignment -> Assignment ) def floatTerm : Parser[Term] = decimalNumber ^^ { case x => FloatTerm( x.toFloat ) } def stringTerm : Parser[Term] = stringLiteral ^^ { case str => StringTerm(str) } def identifier : Parser[Term] = ident ^^ { case value => Identifier(value) } def boolTerm : Parser[Term] = (Keywords.True | Keywords.False) ^^ { case Keywords.True => TrueTerm case Keywords.False => FalseTerm } def simpleTerm : Parser[Expression] = (boolTerm | floatTerm | stringTerm) ^^ { case term => TermExp(term) } def argument = expression def arguments_aux : Parser[List[Expression]] = (argument <~ Keywords.Comma) ~ arguments ^^ { case arg ~ argList => arg :: argList } def arguments = arguments_aux | { argument ^^ { case arg => List(arg) } } def funcAppArgs : Parser[List[Expression]] = funcEmptyArgs | ( Keywords.OpenParen ~> arguments <~ Keywords.CloseParen ^^ { case args => args.foldRight(List[Expression]()) ( (a,b) => a :: b ) } ) def funcApp = identifier ~ funcAppArgs ^^ { case funcName ~ argList => FuncApp(funcName, argList) } def variableTerm : Parser[Expression] = identifier ^^ { case name => TermExp(name) } def atomic_expression = simpleTerm | funcApp | variableTerm def paren_expression : Parser[Expression] = Keywords.OpenParen ~> expression <~ Keywords.CloseParen def unary_operation : Parser[String] = Keywords.Not def unary_expression : Parser[Expression] = operation(0) ~ expression(0) ^^ { case op ~ exp => UnaryOp(keywordMap(op), exp) } def operation(precedence : Int) : Parser[String] = precedence match { case 0 => Keywords.Not case 1 => Keywords.Pow case 2 => Keywords.Times | Keywords.Divide | Keywords.And case 3 => Keywords.Plus | Keywords.Minus | Keywords.Or | Keywords.Xor case 4 => Keywords.Equals | Keywords.NotEquals case _ => throw new Exception("No operations with this precedence.") } def binary_expression(precedence : Int) : Parser[Expression] = precedence match { case 0 => throw new Exception("No operation with zero precedence.") case n => (expression (n-1)) ~ operation(n) ~ (expression (n)) ^^ { case left ~ op ~ right => BinaryOp(keywordMap(op), left, right) } } def expression(precedence : Int) : Parser[Expression] = precedence match { case 0 => unary_expression | paren_expression | atomic_expression case n => binary_expression(n) | expression(n-1) } def expression : Parser[Expression] = expression(4) def expressionStmt : Parser[Statement] = expression ^^ { case exp => ExpressionStatement(exp) } def assignment : Parser[Statement] = (identifier <~ Keywords.Assignment) ~ expression ^^ { case varName ~ exp => AssignmentVar(varName, exp) } def ifthen : Parser[Statement] = ((Keywords.If ~ Keywords.OpenParen) ~> expression <~ Keywords.CloseParen) ~ ((Keywords.Then ~ Keywords.OpenBrack) ~> statements <~ Keywords.CloseBrack) ^^ { case ifBody ~ thenBody => IfThenElse(ifBody, thenBody, Pass()) } def ifthenelse : Parser[Statement] = ((Keywords.If ~ Keywords.OpenParen) ~> expression <~ Keywords.CloseParen) ~ ((Keywords.Then ~ Keywords.OpenBrack) ~> statements <~ Keywords.CloseBrack) ~ ((Keywords.Else ~ Keywords.OpenBrack) ~> statements <~ Keywords.CloseBrack) ^^ { case ifBody ~ thenBody ~ elseBody => IfThenElse(ifBody, thenBody, elseBody) } def pass : Parser[Statement] = Keywords.Pass ^^^ { Pass() } def returnStmt : Parser[Statement] = Keywords.Return ~> expression ^^ { case exp => Return(exp) } def statement : Parser[Statement] = ((pass | returnStmt | assignment | expressionStmt) <~ Keywords.Conj) | ifthenelse | ifthen def statements_aux : Parser[Statement] = statement ~ statements ^^ { case st ~ sts => Conjunction(st, sts) } def statements : Parser[Statement] = statements_aux | statement def funcDefBody : Parser[Statement] = Keywords.OpenBrack ~> statements <~ Keywords.CloseBrack def funcEmptyArgs = Keywords.OpenParen ~ Keywords.CloseParen ^^^ { List() } def funcDefArgs : Parser[List[Term]] = funcEmptyArgs | Keywords.OpenParen ~> repsep(identifier, Keywords.Comma) <~ Keywords.CloseParen ^^ { case args => args.foldRight(List[Term]()) ( (a,b) => a :: b ) } def funcDef : Parser[Statement] = (Keywords.Define ~> identifier) ~ funcDefArgs ~ funcDefBody ^^ { case funcName ~ funcArgs ~ body => AssignmentFunc(funcName, funcArgs, body) } def funcDefAndStatement : Parser[Statement] = funcDef | statement def funcDefAndStatements_aux : Parser[Statement] = funcDefAndStatement ~ funcDefAndStatements ^^ { case stmt ~ stmts => Conjunction(stmt, stmts) } def funcDefAndStatements : Parser[Statement] = funcDefAndStatements_aux | funcDefAndStatement def parseProgram : Parser[Statement] = funcDefAndStatements def eval(input : String) = { parseAll(parseProgram, input) match { case Success(result, _) => result case Failure(m, _) => println(m) case _ => println("") } } } object Parser { def main(args : Array[String]) { val x : myParser = new myParser() println(args(0)) val lines = scala.io.Source.fromFile(args(0)).mkString println(x.eval(lines)) } } The problem is, when I run the parser on the following example it works fine: define foo(a) { if (!h(IM) && a) then { return 0; } if (a() && !h()) then { return 0; } } But when I add threes characters in the first if statement, it runs out of memory. This is absolutely blowing my mind. Can anyone help? (I suspect it has to do with repsep, but I am not sure.) define foo(a) { if (!h(IM) && a(1)) then { return 0; } if (a() && !h()) then { return 0; } } EDIT: Any constructive comments about my Scala style is also appreciated.

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  • Sorting Algorithms

    - by MarkPearl
    General Every time I go back to university I find myself wading through sorting algorithms and their implementation in C++. Up to now I haven’t really appreciated their true value. However as I discovered this last week with Dictionaries in C# – having a knowledge of some basic programming principles can greatly improve the performance of a system and make one think twice about how to tackle a problem. I’m going to cover briefly in this post the following: Selection Sort Insertion Sort Shellsort Quicksort Mergesort Heapsort (not complete) Selection Sort Array based selection sort is a simple approach to sorting an unsorted array. Simply put, it repeats two basic steps to achieve a sorted collection. It starts with a collection of data and repeatedly parses it, each time sorting out one element and reducing the size of the next iteration of parsed data by one. So the first iteration would go something like this… Go through the entire array of data and find the lowest value Place the value at the front of the array The second iteration would go something like this… Go through the array from position two (position one has already been sorted with the smallest value) and find the next lowest value in the array. Place the value at the second position in the array This process would be completed until the entire array had been sorted. A positive about selection sort is that it does not make many item movements. In fact, in a worst case scenario every items is only moved once. Selection sort is however a comparison intensive sort. If you had 10 items in a collection, just to parse the collection you would have 10+9+8+7+6+5+4+3+2=54 comparisons to sort regardless of how sorted the collection was to start with. If you think about it, if you applied selection sort to a collection already sorted, you would still perform relatively the same number of iterations as if it was not sorted at all. Many of the following algorithms try and reduce the number of comparisons if the list is already sorted – leaving one with a best case and worst case scenario for comparisons. Likewise different approaches have different levels of item movement. Depending on what is more expensive, one may give priority to one approach compared to another based on what is more expensive, a comparison or a item move. Insertion Sort Insertion sort tries to reduce the number of key comparisons it performs compared to selection sort by not “doing anything” if things are sorted. Assume you had an collection of numbers in the following order… 10 18 25 30 23 17 45 35 There are 8 elements in the list. If we were to start at the front of the list – 10 18 25 & 30 are already sorted. Element 5 (23) however is smaller than element 4 (30) and so needs to be repositioned. We do this by copying the value at element 5 to a temporary holder, and then begin shifting the elements before it up one. So… Element 5 would be copied to a temporary holder 10 18 25 30 23 17 45 35 – T 23 Element 4 would shift to Element 5 10 18 25 30 30 17 45 35 – T 23 Element 3 would shift to Element 4 10 18 25 25 30 17 45 35 – T 23 Element 2 (18) is smaller than the temporary holder so we put the temporary holder value into Element 3. 10 18 23 25 30 17 45 35 – T 23   We now have a sorted list up to element 6. And so we would repeat the same process by moving element 6 to a temporary value and then shifting everything up by one from element 2 to element 5. As you can see, one major setback for this technique is the shifting values up one – this is because up to now we have been considering the collection to be an array. If however the collection was a linked list, we would not need to shift values up, but merely remove the link from the unsorted value and “reinsert” it in a sorted position. Which would reduce the number of transactions performed on the collection. So.. Insertion sort seems to perform better than selection sort – however an implementation is slightly more complicated. This is typical with most sorting algorithms – generally, greater performance leads to greater complexity. Also, insertion sort performs better if a collection of data is already sorted. If for instance you were handed a sorted collection of size n, then only n number of comparisons would need to be performed to verify that it is sorted. It’s important to note that insertion sort (array based) performs a number item moves – every time an item is “out of place” several items before it get shifted up. Shellsort – Diminishing Increment Sort So up to now we have covered Selection Sort & Insertion Sort. Selection Sort makes many comparisons and insertion sort (with an array) has the potential of making many item movements. Shellsort is an approach that takes the normal insertion sort and tries to reduce the number of item movements. In Shellsort, elements in a collection are viewed as sub-collections of a particular size. Each sub-collection is sorted so that the elements that are far apart move closer to their final position. Suppose we had a collection of 15 elements… 10 20 15 45 36 48 7 60 18 50 2 19 43 30 55 First we may view the collection as 7 sub-collections and sort each sublist, lets say at intervals of 7 10 60 55 – 20 18 – 15 50 – 45 2 – 36 19 – 48 43 – 7 30 10 55 60 – 18 20 – 15 50 – 2 45 – 19 36 – 43 48 – 7 30 (Sorted) We then sort each sublist at a smaller inter – lets say 4 10 55 60 18 – 20 15 50 2 – 45 19 36 43 – 48 7 30 10 18 55 60 – 2 15 20 50 – 19 36 43 45 – 7 30 48 (Sorted) We then sort elements at a distance of 1 (i.e. we apply a normal insertion sort) 10 18 55 60 2 15 20 50 19 36 43 45 7 30 48 2 7 10 15 18 19 20 30 36 43 45 48 50 55 (Sorted) The important thing with shellsort is deciding on the increment sequence of each sub-collection. From what I can tell, there isn’t any definitive method and depending on the order of your elements, different increment sequences may perform better than others. There are however certain increment sequences that you may want to avoid. An even based increment sequence (e.g. 2 4 8 16 32 …) should typically be avoided because it does not allow for even elements to be compared with odd elements until the final sort phase – which in a way would negate many of the benefits of using sub-collections. The performance on the number of comparisons and item movements of Shellsort is hard to determine, however it is considered to be considerably better than the normal insertion sort. Quicksort Quicksort uses a divide and conquer approach to sort a collection of items. The collection is divided into two sub-collections – and the two sub-collections are sorted and combined into one list in such a way that the combined list is sorted. The algorithm is in general pseudo code below… Divide the collection into two sub-collections Quicksort the lower sub-collection Quicksort the upper sub-collection Combine the lower & upper sub-collection together As hinted at above, quicksort uses recursion in its implementation. The real trick with quicksort is to get the lower and upper sub-collections to be of equal size. The size of a sub-collection is determined by what value the pivot is. Once a pivot is determined, one would partition to sub-collections and then repeat the process on each sub collection until you reach the base case. With quicksort, the work is done when dividing the sub-collections into lower & upper collections. The actual combining of the lower & upper sub-collections at the end is relatively simple since every element in the lower sub-collection is smaller than the smallest element in the upper sub-collection. Mergesort With quicksort, the average-case complexity was O(nlog2n) however the worst case complexity was still O(N*N). Mergesort improves on quicksort by always having a complexity of O(nlog2n) regardless of the best or worst case. So how does it do this? Mergesort makes use of the divide and conquer approach to partition a collection into two sub-collections. It then sorts each sub-collection and combines the sorted sub-collections into one sorted collection. The general algorithm for mergesort is as follows… Divide the collection into two sub-collections Mergesort the first sub-collection Mergesort the second sub-collection Merge the first sub-collection and the second sub-collection As you can see.. it still pretty much looks like quicksort – so lets see where it differs… Firstly, mergesort differs from quicksort in how it partitions the sub-collections. Instead of having a pivot – merge sort partitions each sub-collection based on size so that the first and second sub-collection of relatively the same size. This dividing keeps getting repeated until the sub-collections are the size of a single element. If a sub-collection is one element in size – it is now sorted! So the trick is how do we put all these sub-collections together so that they maintain their sorted order. Sorted sub-collections are merged into a sorted collection by comparing the elements of the sub-collection and then adjusting the sorted collection. Lets have a look at a few examples… Assume 2 sub-collections with 1 element each 10 & 20 Compare the first element of the first sub-collection with the first element of the second sub-collection. Take the smallest of the two and place it as the first element in the sorted collection. In this scenario 10 is smaller than 20 so 10 is taken from sub-collection 1 leaving that sub-collection empty, which means by default the next smallest element is in sub-collection 2 (20). So the sorted collection would be 10 20 Lets assume 2 sub-collections with 2 elements each 10 20 & 15 19 So… again we would Compare 10 with 15 – 10 is the winner so we add it to our sorted collection (10) leaving us with 20 & 15 19 Compare 20 with 15 – 15 is the winner so we add it to our sorted collection (10 15) leaving us with 20 & 19 Compare 20 with 19 – 19 is the winner so we add it to our sorted collection (10 15 19) leaving us with 20 & _ 20 is by default the winner so our sorted collection is 10 15 19 20. Make sense? Heapsort (still needs to be completed) So by now I am tired of sorting algorithms and trying to remember why they were so important. I think every year I go through this stuff I wonder to myself why are we made to learn about selection sort and insertion sort if they are so bad – why didn’t we just skip to Mergesort & Quicksort. I guess the only explanation I have for this is that sometimes you learn things so that you can implement them in future – and other times you learn things so that you know it isn’t the best way of implementing things and that you don’t need to implement it in future. Anyhow… luckily this is going to be the last one of my sorts for today. The first step in heapsort is to convert a collection of data into a heap. After the data is converted into a heap, sorting begins… So what is the definition of a heap? If we have to convert a collection of data into a heap, how do we know when it is a heap and when it is not? The definition of a heap is as follows: A heap is a list in which each element contains a key, such that the key in the element at position k in the list is at least as large as the key in the element at position 2k +1 (if it exists) and 2k + 2 (if it exists). Does that make sense? At first glance I’m thinking what the heck??? But then after re-reading my notes I see that we are doing something different – up to now we have really looked at data as an array or sequential collection of data that we need to sort – a heap represents data in a slightly different way – although the data is stored in a sequential collection, for a sequential collection of data to be in a valid heap – it is “semi sorted”. Let me try and explain a bit further with an example… Example 1 of Potential Heap Data Assume we had a collection of numbers as follows 1[1] 2[2] 3[3] 4[4] 5[5] 6[6] For this to be a valid heap element with value of 1 at position [1] needs to be greater or equal to the element at position [3] (2k +1) and position [4] (2k +2). So in the above example, the collection of numbers is not in a valid heap. Example 2 of Potential Heap Data Lets look at another collection of numbers as follows 6[1] 5[2] 4[3] 3[4] 2[5] 1[6] Is this a valid heap? Well… element with the value 6 at position 1 must be greater or equal to the element at position [3] and position [4]. Is 6 > 4 and 6 > 3? Yes it is. Lets look at element 5 as position 2. It must be greater than the values at [4] & [5]. Is 5 > 3 and 5 > 2? Yes it is. If you continued to examine this second collection of data you would find that it is in a valid heap based on the definition of a heap.

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  • linear interpolation on 8bit microcontroller

    - by JB
    I need to do a linear interpolation over time between two values on an 8 bit PIC microcontroller (Specifically 16F627A but that shouldn't matter) using PIC assembly language. Although I'm looking for an algorithm here as much as actual code. I need to take an 8 bit starting value, an 8 bit ending value and a position between the two (Currently represented as an 8 bit number 0-255 where 0 means the output should be the starting value and 255 means it should be the final value but that can change if there is a better way to represent this) and calculate the interpolated value. Now PIC doesn't have a divide instruction so I could code up a general purpose divide routine and effectivly calculate (B-A)/(x/255)+A at each step but I feel there is probably a much better way to do this on a microcontroller than the way I'd do it on a PC in c++ Has anyone got any suggestions for implementing this efficiently on this hardware?

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  • How is schoolbook long division an O(n^2) algorithm?

    - by eSKay
    Premise: This Wikipedia page suggests that the computational complexity of Schoolbook long division is O(n^2). Deduction: Instead of taking "Two n-digit numbers", if I take one n-digit number and one m-digit number, then the complexity would be O(n*m). Contradiction: Suppose you divide 100000000 (n digits) by 1000 (m digits), you get 100000, which takes six steps to arrive at. Now, if you divide 100000000 (n digits) by 10000 (m digits), you get 10000 . Now this takes only five steps. Conclusion: So, it seems that the order of computation should be something like O(n/m). Question: Who is wrong, me or Wikipedia, and where?

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  • assembly language programming (prime number)

    - by chris
    Prompt the user for a positive three digit number, then read it. Let's call it N. Divide into N all integer values from 2 to (N/2)+1 and test to see if the division was even, in which case N is instantly shown to be non-prime. Output a message printing N and saying that it is not prime. If none of those integer values divide evenly (remainder never is zero), then N is shown to be prime. Output a message printing N and saying that it is prime. Ask the user if he or she wants to test another number; if the user types "n" or "N", quit. If "y" or "Y", jump back and repeat. Comments in your code are essential. Hi. I am kinda in rush to do this.. please help me doing it. I'll be much appreciated. thank you

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  • Clojure: Avoiding stack overflow in Sieve of Erathosthene?

    - by nixx
    Here's my implementation of Sieve of Erathosthene in Clojure (based on SICP lesson on streams): (defn nats-from [n] (iterate inc n)) (defn divide? [p q] (zero? (rem q p))) (defn sieve [stream] (lazy-seq (cons (first stream) (sieve (remove #(divide? (first stream) %) (rest stream)))))) (def primes (sieve (nats-from 2))) Now, it's all OK when i take first 100 primes: (take 100 primes) But, if i try to take first 1000 primes, program breaks because of stack overflow. I'm wondering if is it possible to change somehow function sieve to become tail-recursive and, still, to preserve "streamnes" of algorithm? Any help???

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  • Changing floating point behavior in Python to Numpy style.

    - by Tristan
    Is there a way to make Python floating point numbers follow numpy's rules regarding +/- Inf and NaN? For instance, making 1.0/0.0 = Inf. >>> from numpy import * >>> ones(1)/0 array([ Inf]) >>> 1.0/0.0 Traceback (most recent call last): File "<stdin>", line 1, in <module> ZeroDivisionError: float division Numpy's divide function divide(1.0,0.0)=Inf however it is not clear if it can be used similar to from __future__ import division.

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  • convert function from Access SQL to T-SQL 2005

    - by Pace
    Can someone please convert this access sql function for me to work in t-sql 2005. I am tring to take the selling price minus the cost as one number. And divide that by the original selling price to produce a second number Thanks :) =IIf([Selling Price]=0,0,([Selling Price]-Nz([Cost]))/[Selling Price]) IIRC it should be something along the lines of; ISNULL((ISNULL([Selling Price],0) - ISNULL(Cost,0)),0) / ISNULL([Selling Price],0) AS Margin But here I am getting a divide by Zero error. any suggestions?

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  • Dividing n-bit binary integers

    - by Julian
    Was wondering if anyone could help me with creating a pseudocode for how to go about dividing n-bit binary integers. Here is what I'm thinking could possibly work right now, could someone correct this if I'm wrong: divide (x,y) if x=0: return (0,0) //(quotient, remainder) (q,r) = divide(floor(x/2), y) q=2q, r=2r if x is odd: r = r+1 if r >= y: r = r-y, q = q+1 return (q,r) Would you guys say that this general pseudocode algorithm would accomplish the intended task of dividing n-bit numbers or am I missing something in my psuedocode before I start coding up something that's wrong?

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  • Second largest number in list python

    - by Manu Lakaster
    So I have to find THE SECOND LARGEST NUMBER IN A LIST. I am doing it through simple loops.My approach is I am going to divide a list into two parts and then find the largest number into two parts and then compare two nuumbers. I will choose the smaller number from two of them. I can not use ready functions or different approaches. Basically, this is my code....But it does not run correctly....Help me please to fix it because I spent a lot of time on it :( Thanks....P.S. Can we use indices to "divide" a list ??? #!/usr/local/bin/python2.7 alist=[-45,0,3,10,90,5,-2,4,18,45,100,1,-266,706] largest=alist[0] h=len(alist)/2 m=len(alist)-h print(alist) for i in alist: if alist[h]>largest: largest=alist[h] i=i+1 print(largest)

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  • C# log base 10 and rounding up to nearest power of 10?

    - by Tom
    Hi, if i have a number between 100 and 1000 i want to get the value 3 because 10^3 = 1000. Likewise, if i had a number between 10 and 100 i would want to get the value 2, because 10^2 is 100. Incase you're wondering, its to do with calculating a probability and i always need to divide through by 10^value, to keep the probability between 0 and 1. For example if i calculate 9256, i need to divide through by 10^4, so that i get a probability of 0.92 I'm not sure how to do the rounding up and how to do the base 10, could someone please help?

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  • SQL SERVER – Various Leap Year Logics

    - by pinaldave
    Earlier I wrote one article on Leap Year and created one video about Leap Year. My point of view was to demonstrate how we can use SQL Server 2012 features to identify Leap year. How ever during the conversation I had some really good conversation. Here are updates for those who have missed reading the excellent comments on the blog. Incorrect Logic There are so many people still think Leap Year is the event which is consistently happening at every four year and the way to find it is divide the year with 4 and if the remainder is 0. That year is leap year. Well, it is not correct. Comment by David Bridge Check out this excerpt from wikipedia page http://en.wikipedia.org/wiki/Leap_year “most years that are evenly divisible by 4 are leap years…” “…Some exceptions to this rule are required since the duration of a solar year is slightly less than 365.25 days. Years that are evenly divisible by 100 are not leap years, unless they are also evenly divisible by 400, in which case they are leap years. For example, 1600 and 2000 were leap years, but 1700, 1800 and 1900 were not. Similarly, 2100, 2200, 2300, 2500, 2600, 2700, 2900 and 3000 will not be leap years, but 2400 and 2800 will be.” If you use logic of divide by 4 and remainder is 0 to find leap year, you will may end up with inaccurate result. The correct way to identify the year is to figure out the days of February and if the count is 29, the year is for sure leap year. Valid Alternate Solutions Comment by sainswor99insworth IIF((@Year%4=0 AND @Year%100 != 0) OR @Year%400=0, 1,0) Comment by Madhivanan Madhivanan has written a blog post about an year ago where he listed multiple ways to find leap year. Comment by Jayan DECLARE @year INT SET @year = 2012 IF (((@year % 4 = 0) AND (@year % 100 != 0)) OR (@year % 400 = 0)) PRINT ’1' ELSE print ’0' Comment by David DECLARE @Year INT = 2012 SELECT ISDATE('2/29/' + CAST(@Year AS CHAR(4))) Comment by David Bridge Incidentally – Another approach would be to take one day off March 1st and see if it is 29. Reference: Pinal Dave (http://blog.sqlauthority.com) Filed under: PostADay, SQL, SQL Authority, SQL DateTime, SQL Query, SQL Server, SQL Tips and Tricks, T SQL, Technology

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  • Some of my favourite Visual Studio 2012 things&ndash;Teams

    - by Aaron Kowall
    Getting the balance right for when and how many team projects to create has always been a bit of a balance.  On large initiatives, there are often teams who work toward a common system.  These teams often have quite a bit of autonomy, but need to roll up to some higher level initiative.  In TFS 2010, people were often tempted to create separate Team Projects for each of the sub-teams and then do some magic with reporting and cross-team queries to get the consolidated view.  My recommendation was always to use Areas as a means of separating work across the team, but that always resulted in a large number of queries that need to be maintained and just seemed confusing.  When doing anything you had to remember to filter the query or view by Area in order to get correct results. Along with the awesome web access portal that comes in TFS 2012 (which I will cover details of in another post) the product group has introduced the concept of Teams.  A team is a sub-group within a TFS 2012 Team Project which allows us to more easily divide work along team boundaries. Technically, a Team is defined by an Area Path and a TFS Group, both of which could be done in TFS 2012.  However, by allowing for creation of a ‘Team’ in TFS 2012, the web portal is able to do a bunch of ‘magic’ for us.  We can view the project site (backlog, taskboard, etc) for the the team, we can assign items to the team and we can view the burndown for the team.  Basically, all the stuff that we had to prepare manually we now get created and managed for us with a nice UI. When you create a Team Project in TFS 2012, a ‘Default’ team is created with the same name as the Team Project.  So, if you only have 1 team working on the project, you are set.  If you want to divide the work into additional teams, you can create teams by using the Team Web Client. Teams are created using the ‘Administer Server’ icon in the top right of the web site.   You can select the team site by using the team chooser: Once you have selected a team, the Product Backlog, TaskBoard, Burndown Charts, etc. are all filtered to that team. NOTE: You always have the ability to choose the ‘Default’ team to see items for the entire project. PS: It’s been a long while since I shared on this blog.  To help with that I’m in a blogging challenge with some other developer and agilist friends.  Please check out their blogs as well: Steve Rogalsky: http://winnipegagilist.blogspot.ca Dylan Smith: http://www.geekswithblogs.net/optikal Tyler Doerkson: http://blog.tylerdoerksen.com David Alpert: http://www.spinthemoose.com Dave White: http://www.agileramblings.com   Technorati Tags: TFS 2012,Agile,Team

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  • Terrain sqaure loading

    - by AndroidXTr3meN
    Games like Skyrim, Morrowind, and more are using quads or sqaure to divide the terrain if im correct. The player is always at #5 1 | 2 | 3 4 | 5 | 6 7 | 8 | 9 So whenever you cross the border you unload and load the new "areas" But if the user goes just over the edge and then the second after goes back previous area a lot of uneccessary loading and unloading is done. Is there a general approach to this becuase I dont think games like skyrim have this issue? Cheers!

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  • Given a project and working with 1 other person - never worked with someone before

    - by Celeritas
    I'm taking a class where I work with a partner to implement the link layer of the OSI model. I've worked programmed with a partner once before and it went bad. Is the goal to divide the work up and decides who does what or should one person code and the other person reviews and switch roles after a while? Any tips are much appreciated. Literally I know nothing about working with a partner to program so even if it's basic please tell me.

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  • Terrain square loading

    - by AndroidXTr3meN
    Games like Skyrim, Morrowind, and more are using quads or square to divide the terrain if im correct. The player is always at #5 1 | 2 | 3 4 | 5 | 6 7 | 8 | 9 So whenever you cross the border you unload and load the new "areas" But if the user goes just over the edge and then the second after goes back previous area a lot of unnecessary loading and unloading is done. Is there a general approach to this because I dont think games like skyrim have this issue? Cheers!

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  • Accounting for waves when doing planar reflections

    - by CloseReflector
    I've been studying Nvidia's examples from the SDK, in particular the Island11 project and I've found something curious about a piece of HLSL code which corrects the reflections up and down depending on the state of the wave's height. Naturally, after examining the brief paragraph of code: // calculating correction that shifts reflection up/down according to water wave Y position float4 projected_waveheight = mul(float4(input.positionWS.x,input.positionWS.y,input.positionWS.z,1),g_ModelViewProjectionMatrix); float waveheight_correction=-0.5*projected_waveheight.y/projected_waveheight.w; projected_waveheight = mul(float4(input.positionWS.x,-0.8,input.positionWS.z,1),g_ModelViewProjectionMatrix); waveheight_correction+=0.5*projected_waveheight.y/projected_waveheight.w; reflection_disturbance.y=max(-0.15,waveheight_correction+reflection_disturbance.y); My first guess was that it compensates for the planar reflection when it is subjected to vertical perturbation (the waves), shifting the reflected geometry to a point where is nothing and the water is just rendered as if there is nothing there or just the sky: Now, that's the sky reflecting where we should see the terrain's green/grey/yellowish reflection lerped with the water's baseline. My problem is now that I cannot really pinpoint what is the logic behind it. Projecting the actual world space position of a point of the wave/water geometry and then multiplying by -.5f, only to take another projection of the same point, this time with its y coordinate changed to -0.8 (why -0.8?). Clues in the code seem to indicate it was derived with trial and error because there is redundancy. For example, the author takes the negative half of the projected y coordinate (after the w divide): float waveheight_correction=-0.5*projected_waveheight.y/projected_waveheight.w; And then does the same for the second point (only positive, to get a difference of some sort, I presume) and combines them: waveheight_correction+=0.5*projected_waveheight.y/projected_waveheight.w; By removing the divide by 2, I see no difference in quality improvement (if someone cares to correct me, please do). The crux of it seems to be the difference in the projected y, why is that? This redundancy and the seemingly arbitrary selection of -.8f and -0.15f lead me to conclude that this might be a combination of heuristics/guess work. Is there a logical underpinning to this or is it just a desperate hack? Here is an exaggeration of the initial problem which the code fragment fixes, observe on the lowest tessellation level. Hopefully, it might spark an idea I'm missing. The -.8f might be a reference height from which to deduce how much to disturb the texture coordinate sampling the planarly reflected geometry render and -.15f might be the lower bound, a security measure.

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  • contractor vs full time employee

    - by Victor
    What is the long term career prospect of a contractor/consultant in IT field vs a full time salaried employee? The usual arguments aside: Stability vs more upfront money;paid leaves vs tax savings;less paperwork vs more freedom;stagnation vs changing job environments etc etc etc Can some one with a long career experience in hopefully both sides of the divide comment on the pros and cons of contracting vs being an employee? This will be beneficial for all if only people with ample experience choose to answer. Comments are always welcome though.

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  • The Expectations of RIA Technologies in the Coming Future

    A rich Internet application (RIA) is a web application designed to distribute the features and functions usually connected with desktop applications. RIAs commonly divide the dispensation across the Internet and network segregate by locating the user interface and related activity and capability on the client side, and the data manipulation and operation on the application server side.

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  • Can't install Dual Boot from USB live - crash and nouvea problem

    - by user215064
    I just got a new laptop with Windows 8 pre-installed and I'm trying to make a dual boot with Ubuntu on my other hard drive but I can't make the Live USB work. I followed all the procedure for disabling the Security Boot and the UEFI setting but still doesn't work. It seems to start the installing procedure but I never get to choose anything: after a few seconds the screen turns black with an error message [18.707838] divide error: 0000 [#1] SMP (it goes on for several lines quoting some nouveau problem). Any ideas?

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  • The battle between Java vs. C#

    The battle between Java vs. C# has been a big debate amongst the development community over the last few years. Both languages have specific pros and cons based on the needs of a particular project. In general both languages utilize a similar coding syntax that is based on C++, and offer developers similar functionality. This being said, the communities supporting each of these languages are very different. The divide amongst the communities is much like the political divide in America, where the Java community would represent the Democrats and the .Net community would represent the Republicans. The Democratic Party is a proponent of the working class and the general population. Currently, Java is deeply entrenched in the open source community that is distributed freely to anyone who has an interest in using it. Open source communities rely on developers to keep it alive by constantly contributing code to make applications better; essentially they develop code by the community. This is in stark contrast to the C# community that is typically a pay to play community meaning that you must pay for code that you want to use because it is developed as products to be marketed and sold for a profit. This ties back into my reference to the Republicans because they typically represent the needs of business and personal responsibility. This is emphasized by the belief that code is a commodity and that it can be sold for a profit which is in direct conflict to the laissez-faire beliefs of the open source community. Beyond the general differences between Java and C#, they also target two different environments. Java is developed to be environment independent and only requires that users have a Java virtual machine running in order for the java code to execute. C# on the other hand typically targets any system running a windows operating system and has the appropriate version of the .Net Framework installed. However, recently there has been push by a segment of the Open source community based around the Mono project that lets C# code run on other non-windows operating systems. In addition, another feature of C# is that it compiles into an intermediate language, and this is what is executed when the program runs. Because C# is reduced down to an intermediate language called Common Language Runtime (CLR) it can be combined with other languages that are also compiled in to the CLR like Visual Basic (VB) .Net, and F#. The allowance and interaction between multiple languages in the .Net Framework enables projects to utilize existing code bases regardless of the actual syntax because they can be compiled in to CLR and executed as one codebase. As a software engineer I personally feel that it is really important to learn as many languages as you can or at least be open to learn as many languages as you can because no one language will work in every situation.  In some cases Java may be a better choice for a project and others may be C#. It really depends on the requirements of a project and the time constraints. In addition, I feel that is really important to concentrate on understanding the logic of programming and be able to translate business requirements into technical requirements. If you can understand both programming logic and business requirements then deciding which language to use is just basically choosing what syntax to write for a given business problem or need. In regards to code refactoring and dynamic languages it really does not matter. Eventually all projects will be refactored or decommissioned to allow for progress. This is the way of life in the software development industry. The language of a project should not be chosen based on the fact that a project will eventually be refactored because they all will get refactored.

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