Skip to main content

New R package debugr – use automatic debug messages to improve your code

(This article was first published on Topics in R, and kindly contributed to R-bloggers)

debugr is a new package designed to support debugging in R. It mainly provides the dwatch() function which prints a debug output to the console or to a file. A debug output can consist of a static text message, the values of one or more objects (potentially transformed by applying some functions) or the value of one or multiple (more complex) R expressions. Whether or not a debug message is displayed can be made dependent on the evaluation of a criterion phrased as an R expression. Generally, debug messages are only shown if the debug mode is activated. The debug mode is activated and deactivated with debugr_switchOn() and debugr_switchOff(), respectively, which change the logical debugr.active value in the global options. Since debug messages are only displayed in debug mode, the dwatch() function calls can even remain in the original code as they remain silent and won’t have any effect until the debug mode is switched on again. Read more:

To leave a comment for the author, please follow the link and comment on their blog: Topics in R.
R-bloggers.com offers daily e-mail updates about R news and tutorials on topics such as: Data science, Big Data, R jobs, visualization (ggplot2, Boxplots, maps, animation), programming (RStudio, Sweave, LaTeX, SQL, Eclipse, git, hadoop, Web Scraping) statistics (regression, PCA, time series, trading) and more...


from R-bloggers https://ift.tt/2OvvJYd
via IFTTT
Labels:

Comments

Post a Comment

Popular posts from this blog

Explaining models with Triplot, part 1

[This article was first published on R in ResponsibleML on Medium , and kindly contributed to R-bloggers ]. (You can report issue about the content on this page here ) Want to share your content on R-bloggers? click here if you have a blog, or here if you don't. Explaining models with triplot, part 1 tl;dr Explaining black box models built on correlated features may prove difficult and provide misleading results. R package triplot , part of the DrWhy.AI project, is aiming at facilitating the process of explaining the importance of the whole group of variables, thus solving the problem of correlated features. Calculating the importance of explanatory variables is one of the main tasks of explainable artificial intelligence (XAI). There are a lot of tools at our disposal that helps us with that, like Feature Importance or Shapley values, to name a few. All these methods calculate individual feature importance for each variable separately. The problem arises when features used ...
Post a Comment
Read more

The con behind every wedding

With her marriage on the rocks, one writer struggles to reconcile her cynicism about happily-ever-after as her own children rush to tie the knot A lavish wedding, a couple in love; romance was in the air, as it should be when two people are getting married. But on the top table, the mothers of the happy pair were bonding over their imminent plans for … divorce. That story was told to me by the mother of the bride. The wedding in question was two summers ago: she is now divorced, and the bridegroom’s parents are separated. “We couldn’t but be aware of the crushing irony of the situation,” said my friend. “There we were, celebrating our children’s marriage, while plotting our own escapes from relationships that had long ago gone sour, and had probably been held together by our children. Now they were off to start their lives together, we could be off, too – on our own, or in search of new partners.” Continue reading... The Guardian http://ift.tt/2xZTguV October 07, 2017 at 09:00AM
Post a Comment
Read more