Mercurial > repos > dlalgroup > simtext_app
diff text_to_wordmatrix.R @ 0:34ed44f3f85c draft
"planemo upload for repository https://github.com/dlal-group/simtext commit fd3f5b7b0506fbc460f2a281f694cb57f1c90a3c-dirty"
author | dlalgroup |
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date | Thu, 24 Sep 2020 02:17:05 +0000 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/text_to_wordmatrix.R Thu Sep 24 02:17:05 2020 +0000 @@ -0,0 +1,104 @@ +#!/usr/bin/env Rscript +# tool: text_to_wordmatrix +# +#The tool extracts the most frequent words per entity (per row). Text of columns starting with "ABSTRACT" or "TEXT" are considered. +#All extracted terms are used to generate a word matrix with rows = entities and columns = extracted words. +#The resulting matrix is binary with 0= word not present in abstracts of entity and 1= word present in abstracts of entity. +# +#Input: Output of 'pubmed_by_queries' or 'abstracts_by_pmids', or tab-delimited table with entities in column called “ID_<name>”, +#e.g. “ID_genes” and text in columns starting with "ABSTRACT" or "TEXT". +# +#Output: Binary matrix with rows = entities and columns = extracted words. +# +#usage: text_to_wordmatrix.R [-h] [-i INPUT] [-o OUTPUT] [-n NUMBER] [-r] [-l] [-w] [-s] [-p] +# +# optional arguments: +# -h, --help show help message +# -i INPUT, --input INPUT input file name. add path if file is not in working directory +# -o OUTPUT, --output OUTPUT output file name. [default "text_to_wordmatrix_output"] +# -n NUMBER, --number NUMBER number of most frequent words that should be extracted [default "50"] +# -r, --remove_num remove any numbers in text +# -l, --lower_case by default all characters are translated to lower case. otherwise use -l +# -w, --remove_stopwords by default a set of english stopwords (e.g., 'the' or 'not') are removed. otherwise use -w +# -s, --stemDoc apply Porter's stemming algorithm: collapsing words to a common root to aid comparison of vocabulary +# -p, --plurals by default words in plural and singular are merged to the singular form. otherwise use -p + +if ( '--install_packages' %in% commandArgs()) { + print('Installing packages') + if (!require('argparse')) install.packages('argparse', repo="http://cran.rstudio.com/"); + if (!require("PubMedWordcloud")) install.packages("PubMedWordcloud", repo="http://cran.rstudio.com/"); + if (!require('SnowballC')) install.packages('SnowballC', repo="http://cran.rstudio.com/"); + if (!require('textclean')) install.packages('textclean', repo="http://cran.rstudio.com/"); + if (!require('SemNetCleaner')) install.packages('SemNetCleaner',repo="http://cran.rstudio.com/"); + if (!require('stringi')) install.packages('stringi',repo="http://cran.rstudio.com/"); + if (!require('stringr')) install.packages('stringr',repo="http://cran.rstudio.com/"); +} + +suppressPackageStartupMessages(library("argparse")) +suppressPackageStartupMessages(library("PubMedWordcloud")) +suppressPackageStartupMessages(library("SnowballC")) +suppressPackageStartupMessages(library("SemNetCleaner")) +suppressPackageStartupMessages(library("textclean")) +suppressPackageStartupMessages(library("stringi")) +suppressPackageStartupMessages(library("stringr")) + +parser <- ArgumentParser() +parser$add_argument("-i", "--input", + help = "input fie name. add path if file is not in workind directory") +parser$add_argument("-o", "--output", default="text_to_wordmatrix_output", + help = "output file name. [default \"%(default)s\"]") +parser$add_argument("-n", "--number", type="integer", default=50, choices=seq(1, 500), metavar="{0..500}", + help="number of most frequent words used per ID in word matrix [default \"%(default)s\"]") +parser$add_argument("-r", "--remove_num", action="store_true", default=FALSE, + help= "remove any numbers in text") +parser$add_argument("-l", "--lower_case", action="store_false", default=TRUE, + help="by default all characters are translated to lower case. otherwise use -l") +parser$add_argument("-w", "--remove_stopwords", action="store_false", default=TRUE, + help="by default a set of English stopwords (e.g., 'the' or 'not') are removed. otherwise use -s") +parser$add_argument("-s", "--stemDoc", action="store_true", default=FALSE, + help="apply Porter's stemming algorithm: collapsing words to a common root to aid comparison of vocabulary") +parser$add_argument("-p", "--plurals", action="store_false", default=TRUE, + help="by default words in plural and singular are merged to the singular form. otherwise use -p") +parser$add_argument("--install_packages", action="store_true", default=FALSE, + help="If you want to auto install missing required packages.") + +args <- parser$parse_args() + + +data = read.delim(args$input, stringsAsFactors=FALSE, header = TRUE, sep='\t') +word_matrix = data.frame() + +text_cols_index <- grep(c("ABSTRACT|TEXT"), names(data)) + +for(row in 1:nrow(data)){ + top_words = cleanAbstracts(abstracts= data[row,text_cols_index], + rmNum = args$remove_num, + tolw= args$lower_case, + rmWords= args$remove_stopwords, + stemDoc= args$stemDoc) + + top_words$word <- as.character(top_words$word) + + # δ γ ε + + cat("Most frequent words for row", row, " are extracted.", "\n") + + if(args$plurals == TRUE){ + top_words$word <- sapply(top_words$word, function(x){singularize(x)}) + top_words = aggregate(freq~word,top_words,sum) + } + + top_words = top_words[order(top_words$freq, decreasing = TRUE), ] + top_words$word = as.character(top_words$word) + + number_extract = min(args$number, nrow(top_words)) + word_matrix[row,sapply(1:number_extract, function(x){paste0(top_words$word[x])})] <- top_words$freq[1:number_extract] + } + + word_matrix <- as.matrix(word_matrix) + word_matrix[is.na(word_matrix)] <- 0 + word_matrix <- (word_matrix>0) *1 #binary matrix + +cat("A matrix with ", nrow(word_matrix), " rows and ", ncol(word_matrix), "columns is generated.", "\n") + +write.table(word_matrix, args$output, row.names = FALSE, sep = '\t')