Is your R code running slow? Do you know the slowest part? Here, Pat uses the R profvis package to identify the slow points or bottlenecks in his R code. He then uses his test driven design platform written with testthat to optimize the performance the code. Calculating log likelihoods and using the Rfast R package also appear in the refactoring effort. This episode is part of an ongoing effort to develop an R package that implements the naive Bayesian classifier.
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End of the episode: https://github.com/riffomonas/phyloty...
#rstats #paste #paste0 #refactor #testthat #tdd #microbenchmark #vectors #rdp #16S #classification #classifier #microbialecology #microbiome
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0:00 Introduction
1:28 Creating and testing classify_sequence
9:17 Detecting bottlenecks in classify_sequence
12:04 Converting to use the log-likelihood
18:41 Refactoring to speed up column sum with Rfast::colsums