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From the Matlab documentation, bsxfun applies the element-by-element binary operation specified by the. Previously, this functionality was available via the bsxfun function. You may want the more obscure Matlab function bsxfun. \īit-wise functions - bitand, bitor, bitxorĮlementary math functions - max, min, mod, rem, hypot, atan2, atan2dįor example, you can calculate the mean of each column in a matrix A,Īnd then subtract the vector of mean values from each column with A. Element-wise arithmetic operators - +,. See Compatible Array Sizes for Basic Operations andĪrray vs. Two arrays have compatible sizes if, for everyĭimension, the dimension sizes of the inputs are either the same or The element-wise operators and functions listed here can implicitlyĮxpand their inputs to be the same size, as long as the arrays haveĬompatible sizes. Scalar expansion, a scalar expands to be the same size as anotherĪrray to facilitate element-wise operations.
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Implicit expansion is a generalization of scalar expansion. Also, vectors with different orientations (one row vector and one column vector) implicitly expand to form a matrix. Implicit Expansion: Apply element-wise operations and functions to arrays with automatic expansion of dimensions of length 1 For example, if one of A or B is a scalar, then the scalar is combined with each element of the other array. So you'll need to choose whether you want simplicity or speed.Īdding to the evolving nature of the answer to this question, starting with r2016b, MATLAB will implicitly expand singleton dimensions, removing the need for bsxfun in many cases. However, in some informal tests of mine, it turns out that repmat is roughly twice as fast if the function to be applied (like my power function, above) is simple. So bsxfun saves you some steps (you don't need to explicitly calculate the dimensions of A). Or you could do this the classy way using bsxfun, which internally takes care of the repmat step: C = x.^y, A, B) You could do this the brute force way using repmat: C = A.^repmat(B, size(A, 1), 1)
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You want a function power_by_col which returns in a vector C all the elements in A to the power of the corresponding column of B.įrom the above example, C is a 3x3 matrix: C = [1^0 2^1 3^2 However, bsxfun works for any function, including (and especially) user-defined functions.įor example, let's say you have a matrix A and a row vector B. From the Matlab documentation, bsxfun "applies the element-by-element binary operation specified by the function handle fun to arrays A and B, with singleton expansion stated above that sum and other basic functions already operate on the first non-singleton dimension (i.e., rows if there's more than one row, columns if there's only one row, or higher dimensions if the lower dimensions all have size=1). You may want the more obscure Matlab function bsxfun.