Clear R memory using Rpy2

Question

I have a bunch of R functions which I need to call through python. However, I reach memory errors when I try to allocate a large matrix. The same functions run fine on RStudio on the same computer. Here is a code chunk which crashes:

#python:
import rpy2.robjects as ro 
import gc
gc.collect()
ro.r.source("calibration_functions.R")
result1 = ro.r.func1()  #Does some calculations, works fine.
result2 = ro.r.func2(result1) #Crashes at this step

#R code:
func2 <- function(result1){
  preds_mat = matrix(data=NA, nrow = 263310, ncol = 1000)
  # do something...
  return(preds_mat)
}

The error I get is: RRuntimeError: Error: cannot allocate vector of size 1004.4 Mb

How can I clean the R memory? gc() or gc.collect() doesn't work.

Answer 1

清洁R存储器：

rm(list = ls())

Answer 2

(...)

The same functions run fine on RStudio on the same computer.

May be the same function, but likely with differences in memory usage from other applications.

Your R function func2() returns the following object size:

> object.size(func2(1))
1053240200 bytes

This is about 1.05Gb.

The error I get is: RRuntimeError: Error: cannot allocate vector of size 1004.4 Mb

The error observed is likely occurring either because of what is happening in the unspecified function func1() , or because something has changed between the execution in RStudio and the execution in rpy2.

Answer 3

I typically deal with the issue by allocating more memory

from rpy2 import robjects
R = robjects.r


R('memory.limit()')
R('memory.limit(size = 10000)') ## in MB
R('memory.limit()')

…
R('gc()')## trigger garbage collection