Attempt to calculate an appropriate block size to maximize efficiency of block-wise calcualtions.
The function uses a rather primitive way to estimate available memory and use it to suggest a block size appropriate for the many block-by-block calculations in this package.
blockSize( matrixSize, rectangularBlocks = TRUE, maxMemoryAllocation = NULL, overheadFactor = 3);
matrixSize |
the relevant dimension (usually the number of columns) of the matrix that is to be operated on block-by-block. |
rectangularBlocks |
logical indicating whether the bocks of data are rectangular (of size
|
maxMemoryAllocation |
maximum desired memory allocation, in bytes. Should not exceed 2GB or total installed RAM (whichever is greater) on 32-bit systems, while on 64-bit systems it should not exceed the total installed RAM. If not supplied, the available memory will be estimated internally. |
overheadFactor |
overhead factor for the memory use by R. Recommended values are between 2 (for simple calculations) and 4 or more for complicated calculations where intermediate results (for which R must also allocate memory) take up a lot of space. |
Multiple functions within the WGCNA package use a divide-and-conquer (also known as block-by-block, or block-wise) approach to handling large data sets. This function is meant to assist in choosing a suitable block size, given the size of the data and the available memory.
If the entire expected result fits
into the allowed memory (after taking into account the expected overhead), the returned block size will
equal the input matrixSize.
The internal estimation of available memory works by returning the size of largest successfully allocated block of memory. It is hoped that this will lead to reasonable results but some operating systems may actually allocate more than is available. It is therefore preferable that the user specifies the available memory by hand.
A single integer giving the suggested block size, or matrixSize if the entire calculation is
expected to fit into memory in one piece.
Peter Langfelder
# Suitable blocks for handling 30,000 genes within 2GB (=2^31 bytes) of memory blockSize(30000, rectangularBlocks = TRUE, maxMemoryAllocation = 2^31)
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