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*** caught segfault *** address (nil), cause 'memory not mapped' #6
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What is your data size? Does this happen on the same row if you rerun the script? Can you provide the argument values that caused the script to memory map failure? |
My file has 3 Mb, a dataframe with dimension 1729 × 36.
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I have I hint, the size of the table was not the problem. |
I was able to run the script on your data without problem. I have R 4.1.3 GUI 1.77 High Sierra build (8051) in a Mac. I tested this both in R and RStudio. Looking at the output of your error, it seems your 'memory not mapped' problem has something to do with interaction with another package. https://stackoverflow.com/questions/49190251/caught-segfault-memory-not-mapped-error-in-r Can you test this script in a new environment without loading other packages?
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My system is Linux Mint 20.1. I believe the problem is on the compilation of CooccurrenceAffinity, but I have no clue how to solve this. |
I was able to pinpoint the source of the problem. It is the updated BiasedUrn package that is failing the script. I was able to run affinity() on your data without any problem as I indicated earlier. Then I updated BiasedUrn from 1.07 -> 2.0.8 and it started crashing. I am working with my collaborator to resolve it within our package. Allow me a few days. |
Please see the Readme for a temporary solution of this problem. Can you check if this resolves your problem? |
Yes, it solved the problem! Thank you very much! |
Hi @fhsantanna please see our readme for the permanent solution to the problem you reported earlier. I have copied the notice below. And, thanks for bringing this issue to us. "Feb 6, 2023: We are pleased to inform you that the interaction issue between our package and BiasedUrn v2.0.8 has been resolved in the latest version, BiasedUrn v2.0.9. We kindly request that you remove any previous versions of BiasedUrn and install v2.0.9 to ensure proper operation of the CooccurrenceAffinity package. We extend our heartfelt thanks to Agner Fox for promptly updating BiasedUrn and addressing these important issues." |
Hi.
Very nice tool!
When I try to run a data frame having a dimension of 1729 × 36, I get the following error:
I can run the function if I reduce the data frame to 1729 × 5. I am running the analysis on a Xeon with 64 Gb of RAM.
Any idea on how to avoid this issue?
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