I\'m currently cooking up a wrapper container template class for std::vector that automatically creates a multi-resolution pyramid of the elements in its std::vector.
I have two 3-dimensional arrays, the first two dimensions of which represent matrices and the last one counts through a parameterspace, as a simple example take
I would like to find a way to replace a for loop that I am using. Quick version of my question is: how can I go from a vector [a,b,c,d,e] to [1,a,a*b,a*b*c,a*b*c*d] ?
Here\'s the code I use to find numeric variables in a data frame: Data <- iris numericvars <- NULL
I need to filter an image using a bank of filters in Matlab.My first attempt was to use a开发者_如何转开发 simple for loop to repeatedly call the \"imfilter\" function for each filter in the bank.
I want all pairwise comparisons for all rows in the matrix, obviou开发者_如何学编程sly double for loop will work but extremely expensive for large dataset.
I\'m trying to write a stream compaction (take an array and get rid of empty elements) with SIMD intrinsics. Each iteration of the loop processes 8 elements at a time (SIMD width).
Is there a version of Vectorize that uses apply rather than mapply? I wo开发者_如何转开发uld like to vectorize a function that takes vector input in a way that allows me
I want a function f such that (outer(X, Y, f))[i, j] is a side-by-side concatenation of the i-th element of X and the j-th element of Y, something like c(X[i], Y[j]), or having a similar structure.
The standard R expression outer(X, Y, f) evaluates to a matrix whose (i, j)-th entry has the value f(X[i], Y[j]).
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