Search results
Results from the WOW.Com Content Network
Range minimum query reduced to the lowest common ancestor problem. Given an array A[1 … n] of n objects taken from a totally ordered set, such as integers, the range minimum query RMQ A (l,r) =arg min A[k] (with 1 ≤ l ≤ k ≤ r ≤ n) returns the position of the minimal element in the specified sub-array A[l … r].
extract-max (or extract-min): returns the node of maximum value from a max heap [or minimum value from a min heap] after removing it from the heap (a.k.a., pop [5]) delete-max (or delete-min): removing the root node of a max heap (or min heap), respectively; replace: pop root and push a new key. This is more efficient than a pop followed by a ...
Selection sort can be implemented as a stable sort if, rather than swapping in step 2, the minimum value is inserted into the first position and the intervening values shifted up. However, this modification either requires a data structure that supports efficient insertions or deletions, such as a linked list, or it leads to performing Θ ( n 2 ...
Python's heapq module implements a binary min-heap on top of a list. Java's library contains a PriorityQueue class, which implements a min-priority-queue as a binary heap. .NET's library contains a PriorityQueue class, which implements an array-backed, quaternary min-heap.
As a baseline algorithm, selection of the th smallest value in a collection of values can be performed by the following two steps: . Sort the collection; If the output of the sorting algorithm is an array, retrieve its th element; otherwise, scan the sorted sequence to find the th element.
However, the normalised sinc function (blue) has arg min of {−1.43, 1.43}, approximately, because their global minima occur at x = ±1.43, even though the minimum value is the same. [ 1 ] In mathematics , the arguments of the maxima (abbreviated arg max or argmax ) and arguments of the minima (abbreviated arg min or argmin ) are the input ...
This makes the min-max heap a very useful data structure to implement a double-ended priority queue. Like binary min-heaps and max-heaps, min-max heaps support logarithmic insertion and deletion and can be built in linear time. [3] Min-max heaps are often represented implicitly in an array; [4] hence it's referred to as an implicit data structure.
To make worstsort truly pessimal, k may be assigned to the value of a computable increasing function such as : (e.g. f(n) = A(n, n), where A is Ackermann's function). Therefore, to sort a list arbitrarily badly, one would execute worstsort( L , f ) = badsort( L , f (length( L ))) , where length( L ) is the number of elements in L .