cycle

I'm trying to run a JavaScript window resize script on a page with a jQuery cycle slideshow but I'm hitting some bugs I cant seem to work out. It resizes the first image fine on page load but then forgets the new height/width attributes for subsequent slides. I can set these again on before and after using jQuery but the images always flash in at full size for a brief moment before resizing. Is jQuery.cycle resizing the slides back to their native size? If so how do I stop this? $(document).ready(function () { $('.slideshow').cycle({ fx: 'fade', speed: 200, timeout: 1000, pause: 1, before:

Say I have a list: l = [1, 2, 3, 4] And I want to cycle through it. Normally, it would do something like this, 1, 2, 3, 4, 1, 2, 3, 4, 1, 2... I want to be able to start at a certain point in the cycle, not necessarily an index, but perhaps matching an element. Say I wanted to start at whatever element in the list ==4 , then the output would be, 4, 1, 2, 3, 4, 1, 2, 3, 4, 1... How can I accomplish this? Look at itertools module. It provides all the necessary functionality. from itertools import cycle, islice, dropwhile L = [1, 2, 3, 4] cycled = cycle(L) # cycle thorugh the list 'L' skipped =

Here is a working C# implementation of tarjan's cycle detection. The algorithm is found here: http://en.wikipedia.org/wiki/Tarjan%27s_strongly_connected_components_algorithm public class TarjanCycleDetect { private static List<List<Vertex>> StronglyConnectedComponents; private static Stack<Vertex> S; private static int index; private static DepGraph dg; public static List<List<Vertex>> DetectCycle(DepGraph g) { StronglyConnectedComponents = new List<List<Vertex>>(); index = 0; S = new Stack<Vertex>(); dg = g; foreach (Vertex v in g.vertices) { if (v.index < 0) { strongconnect(v); } } return

Note that a graph is represented as an adjacency list. I've heard of 2 approaches to find a cycle in a graph: Keep an array of boolean values to keep track of whether you visited a node before. If you run out of new nodes to go to (without hitting a node you have already been), then just backtrack and try a different branch. The one from Cormen's CLRS or Skiena: For depth-first search in undirected graphs, there are two types of edges, tree and back. The graph has a cycle if and only if there exists a back edge. Can somebody explain what are the back edges of a graph and what's the diffirence

I have implemented a small cycle detection algorithm for a DAG in Scala. The 'return' bothers me - I'd like to have a version without the return...possible? def isCyclic() : Boolean = { lock.readLock().lock() try { nodes.foreach(node => node.marker = 1) nodes.foreach(node => {if (1 == node.marker && visit(node)) return true}) } finally { lock.readLock().unlock() } false } private def visit(node: MyNode): Boolean = { node.marker = 3 val nodeId = node.id val children = vertexMap.getChildren(nodeId).toList.map(nodeId => id2nodeMap(nodeId)) children.foreach(child => { if (3 == child.marker || (1 =

I need an example of the shortest path of a directed cyclic graph from one node (it should reach to all nodes of the graph from a node that will be the input). Please if there is an example, I need it in C++, or the algorithm. EDIT: Oops, misread the question. Thanks @jfclavette for picking this up. Old answer is at the end. The problem you're trying to solve is called the Travelling salesman problem . There are many potential solutions , but it's NP-complete so you won't be able to solve for large graphs. Old answer: What you're trying to find is called the girth of a graph. It can be solved

This question is about an algorithm for determining the number and location of maxima in a sequence of numbers. Thus, there is a statistical flavor to the question, but it is more leaning towards programming, because I am not interested in the specific statistical properties, and the solution needs to be in R. The use of statistics to answer this question is OK, but not a requirement. I want to extract maxima of cycles in time series data (i.e., an ordered sequence of numbers). An example of such data is the solar flare time series (~11 year cycle, between 9 & 14 years). The cycles don't