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  2. Rotation matrix - Wikipedia

    en.wikipedia.org/wiki/Rotation_matrix

    Noting that any identity matrix is a rotation matrix, and that matrix multiplication is associative, we may summarize all these properties by saying that the n × n rotation matrices form a group, which for n > 2 is non-abelian, called a special orthogonal group, and denoted by SO(n), SO(n,R), SO n, or SO n (R), the group of n × n rotation ...

  3. Magic cube - Wikipedia

    en.wikipedia.org/wiki/Magic_cube

    An example of a 3 × 3 × 3 magic cube. In this example, no slice is a magic square. In this case, the cube is classed as a simple magic cube.. In mathematics, a magic cube is the 3-dimensional equivalent of a magic square, that is, a collection of integers arranged in an n × n × n pattern such that the sums of the numbers on each row, on each column, on each pillar and on each of the four ...

  4. Marching squares - Wikipedia

    en.wikipedia.org/wiki/Marching_squares

    Typical applications include the contour lines on topographic maps or the generation of isobars for weather maps. Marching squares takes a similar approach to the 3D marching cubes algorithm: Process each cell in the grid independently. Calculate a cell index using comparisons of the contour level(s) with the data values at the cell corners.

  5. Linear map - Wikipedia

    en.wikipedia.org/wiki/Linear_map

    In mathematics, and more specifically in linear algebra, a linear map (also called a linear mapping, linear transformation, vector space homomorphism, or in some contexts linear function) is a mapping between two vector spaces that preserves the operations of vector addition and scalar multiplication.

  6. Matrix (mathematics) - Wikipedia

    en.wikipedia.org/wiki/Matrix_(mathematics)

    A matrix with one column, sometimes used to represent a vector Square matrix: n × n [] A matrix with the same number of rows and columns, sometimes used to represent a linear transformation from a vector space to itself, such as reflection, rotation, or shearing.

  7. Bicubic interpolation - Wikipedia

    en.wikipedia.org/wiki/Bicubic_interpolation

    At the edges of the dataset, when one is missing some of the surrounding points, the missing points can be approximated by a number of methods. A simple and common method is to assume that the slope from the existing point to the target point continues without further change, and using this to calculate a hypothetical value for the missing point.

  8. Trilinear interpolation - Wikipedia

    en.wikipedia.org/wiki/Trilinear_interpolation

    Eight corner points on a cube surrounding the interpolation point C On a periodic and cubic lattice, let x d {\displaystyle x_{\text{d}}} , y d {\displaystyle y_{\text{d}}} , and z d {\displaystyle z_{\text{d}}} be the differences between each of x {\displaystyle x} , y {\displaystyle y} , z {\displaystyle z} and the smaller coordinate related ...

  9. Transfinite interpolation - Wikipedia

    en.wikipedia.org/wiki/Transfinite_interpolation

    The transfinite interpolation method, first introduced by William J. Gordon and Charles A. Hall, [2] receives its name due to how a function belonging to this class is able to match the primitive function at a nondenumerable number of points. [3] In the authors' words: