NEWS.md
refine_keywords() function to refine keywords by dropping topics that do not have any occurrence in the documents (#222)save() function (thank you @AMindToThink for repoting this error in #214)shuffled_indexes() that internally used std::random_shuffle(). This change does not guarantee backward compatibility across all platforms.cli instead of the base R message() and warning() functions.label model in keyATM() (it was an experimental feature).plot_timetrend() output (thank you @WenHanGao for the suggestion in #188).plot_topicprop() function.semantic_coherence() function (thanks to Seo-young Silvia Kim for your suggestion).width) in the plot_timetrend() function.Rcpp::message() if verbose = TRUE.parallel::mclapply.by_strata_DocTopic() takes the correct arguments (#180, thank you @pmeiners for reporting this!).future.apply instead of parallel (no backward compatibility if you use the init_parallel option).keyATM_read() function returns a list of objects (e.g., text and document index).keep_docnames option in the keyATM_read() function (thank you Morgan ‘Les’ DeBusk-Lane for the suggestion!).method = "hdi") in plot.strata_doctopic(), plot_timetrend(), and plot_pi(). The previous version uses the Equal-tailed Interval (method = "eti").read_keywords for reading dictionary files (e.g. YAML, LIWC).predict() function for the covariate keyATM (thank you Sanja Hajdinjak for the suggestion!).standardize option in model_settings argument of the keyATM() function now takes one of "all", "none", or "non-factor" (default)."all" standardizes all covariates (except the intercept), "none" does not standardize any covariates, and "non-factor" standardizes non-factor covariates.TRUE (default, standardizing all covariates) or FALSE.by_strata_DocTopic() function.keyATM() includes the index of documents used for fitting (this will be useful if the input includes documents with zero length).progress_bar option in the keyATM_read() function (thank you Jae Yeon Kim for the suggestion!).by_strata_DocTopic() function.save_fig() function.plot.strata_doctopic(): showing by topic by default (thank you Soichiro Yamauchi for the suggestion!).weightedLDA() without specifying the number of iterations (Chung-hong Chan independently reported this bug, thank you!).summary.strata_doctopic(): the last topic is removed when the number of no-keyword topic is 0 (thank you Emma Ebowe for pointing out this issue!).hashmap with fastmap.