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Python has built-in set and frozenset types since 2.4, and since Python 3.0 and 2.7, supports non-empty set literals using a curly-bracket syntax, e.g.: {x, y, z}; empty sets must be created using set(), because Python uses {} to represent the empty dictionary.
The most naïve algorithm would be to cycle through all subsets of n numbers and, for every one of them, check if the subset sums to the right number. The running time is of order (), since there are subsets and, to check each subset, we need to sum at most n elements.
In mathematics, a multiset (or bag, or mset) is a modification of the concept of a set that, unlike a set, [1] allows for multiple instances for each of its elements.The number of instances given for each element is called the multiplicity of that element in the multiset.
The set of subsets of a given set (its power set) ordered by inclusion (see Fig. 1). Similarly, the set of sequences ordered by subsequence, and the set of strings ordered by substring. The set of natural numbers equipped with the relation of divisibility. (see Fig. 3 and Fig. 6) The vertex set of a directed acyclic graph ordered by reachability.
Nested Sets is a clever solution – maybe too clever. It also fails to support referential integrity. It’s best used when you need to query a tree more frequently than you need to modify the tree. [9] The model doesn't allow for multiple parent categories. For example, an 'Oak' could be a child of 'Tree-Type', but also 'Wood-Type'.
In the set cover optimization problem, the input is a pair (,), and the task is to find a set cover that uses the fewest sets. The decision version of set covering is NP-complete . It is one of Karp's 21 NP-complete problems shown to be NP-complete in 1972.
A bijection from the natural numbers to the integers, which maps 2n to −n and 2n − 1 to n, for n ≥ 0. For any set X, the identity function 1 X: X → X, 1 X (x) = x is bijective. The function f: R → R, f(x) = 2x + 1 is bijective, since for each y there is a unique x = (y − 1)/2 such that f(x) = y.
In computer science, a disjoint-set data structure, also called a union–find data structure or merge–find set, is a data structure that stores a collection of disjoint (non-overlapping) sets. Equivalently, it stores a partition of a set into disjoint subsets .