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  2. Maximum subarray problem - Wikipedia

    en.wikipedia.org/wiki/Maximum_subarray_problem

    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].

  3. Closest pair of points problem - Wikipedia

    en.wikipedia.org/wiki/Closest_pair_of_points_problem

    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).

  4. Ramer–Douglas–Peucker algorithm - Wikipedia

    en.wikipedia.org/wiki/Ramer–Douglas–Peucker...

    Initially it is given all the points between the first and last point. It automatically marks the first and last point to be kept. It then finds the point that is farthest from the line segment with the first and last points as end points; this point is always farthest on the curve from the approximating line segment between the end points.

  5. Array slicing - Wikipedia

    en.wikipedia.org/wiki/Array_slicing

    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.

  6. k-d tree - Wikipedia

    en.wikipedia.org/wiki/K-d_tree

    Once the algorithm reaches a leaf node, it checks the node point and if the distance is better than the "current best", that node point is saved as the "current best". The algorithm unwinds the recursion of the tree, performing the following steps at each node: If the current node is closer than the current best, then it becomes the current best.

  7. Array programming - Wikipedia

    en.wikipedia.org/wiki/Array_programming

    In array languages, operations are generalized to apply to both scalars and arrays. Thus, a+b expresses the sum of two scalars if a and b are scalars, or the sum of two arrays if they are arrays. An array language simplifies programming but possibly at a cost known as the abstraction penalty.

  8. Plotting algorithms for the Mandelbrot set - Wikipedia

    en.wikipedia.org/wiki/Plotting_algorithms_for...

    These are stored in an array: IterationCounts[x][y], where x and y are the x and y coordinates of said pixel on the screen respectively. The top row is a series of plots using the escape time algorithm for 10000, 1000 and 100 maximum iterations per pixel respectively.

  9. Convex hull algorithms - Wikipedia

    en.wikipedia.org/wiki/Convex_hull_algorithms

    Find the two points with the lowest and highest x-coordinates, and the two points with the lowest and highest y-coordinates. (Each of these operations takes O ( n ).) These four points form a convex quadrilateral , and all points that lie in this quadrilateral (except for the four initially chosen vertices) are not part of the convex hull.