Instead allocate it using NA_real_ (or NA_integer_ for integers)Īs recommended: let's test it.
The originally allocated logical matrix was allocated in vain and just adds an unnecessary memory footprint and extra work for the garbage collector. From the article:Īs soon as you assign a numeric value to any of the cells in 'x', the matrix will first have to be coerced to numeric when a new value is assigned. While the former is more concise, it isn't breathtakingly easier to understand, so I feel like this could go either way.Īlso, what is the difference between NA and NULL in R?NA and ?NULL tell me that "NA" has a length of "1" whereas NULL has a length of "0" - but is there more here? Or a best practice? This will affect which method I use to create my matrix.Īccording to this article we can do better than preallocating with NA by preallocating with NA_real_. Which is the "better" way to do this? In this case, I'm defining "better" as "better performance", because this is statistical computing and this operation will be taking place with large datasets. Also, the former fills the matrix with NAs, whereas the latter is filled with NULLs. My question is really simple: what is the best way to pre-allocate this matrix? Thus far, I have two ways: > x xĪs far as I can see, the former is a more concise method than the latter. Thus, for the quadprog The vector g module would be a of Matlab, H would be H zero vector with 2M elements.
Loop through each element of my matrix and fill it with an appropriate value.
Allocate null vector matlab code#
I am writing R code to create a square matrix.
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