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The following JavaScript function applies De Casteljau's algorithm to an array of control points or poles as originally named by De Casteljau to reduce them one by one until reaching a point in the curve for a given t between 0 for the first point of the curve and 1 for the last one
An algorithm for the dynamic closest-pair problem in dimensional space was developed by Sergey Bespamyatnikh in 1998. [10] Points can be inserted and deleted in O ( log n ) {\displaystyle O(\log n)} time per point (in the worst case).
Then A[I] is equivalent to an array of the first 10 elements of A. A practical example of this is a sorting operation such as: I = array_sort(A); % Obtain a list of sort indices B = A[I]; % B is the sorted version of A C = A[array_sort(A)]; % Same as above but more concise.
The Bentley–Ottmann algorithm processes a sequence of + events, where denotes the number of input line segments and denotes the number of crossings. Each event is processed by a constant number of operations in the binary search tree and the event queue, and (because it contains only segment endpoints and crossings between adjacent segments ...
Function rank is an important concept to array programming languages in general, by analogy to tensor rank in mathematics: functions that operate on data may be classified by the number of dimensions they act on. Ordinary multiplication, for example, is a scalar ranked function because it operates on zero-dimensional data (individual numbers).
Each possible contiguous sub-array is represented by a point on a colored line. That point's y-coordinate represents the sum of the sample. Its x-coordinate represents the end of the sample, and the leftmost point on that colored line represents the start of the sample. In this case, the array from which samples are taken is [2, 3, -1, -20, 5, 10].
The rotating calipers technique for designing geometric algorithms may also be interpreted as a form of the plane sweep, in the projective dual of the input plane: a form of projective duality transforms the slope of a line in one plane into the x-coordinate of a point in the dual plane, so the progression through lines in sorted order by their ...
Coordinate descent is an optimization algorithm that successively minimizes along coordinate directions to find the minimum of a function.At each iteration, the algorithm determines a coordinate or coordinate block via a coordinate selection rule, then exactly or inexactly minimizes over the corresponding coordinate hyperplane while fixing all other coordinates or coordinate blocks.