Last weeks was filled with lost of programming and designing works.

With R and rJava there are sometimes troubles, especially when you need to train topic model using mallet ar now textmining package:

I recommend to read this post to configure Java properly:
https://www.r-statistics.com/2012/08/how-to-load-the-rjava-package-after-the-error-java_home-cannot-be-determined-from-the-registry/

Also, R tests implementation for both architectures on Windows 32 bit and 64 bit. This was hard to discover during the automatic build in RStudio. There was two solutions for this problem:
Set no multi-architecture argument in check options:
devtools::check(document = FALSE, args=”–no-multiarch”)
or install properly Java for both architectures 32 bit and 64 bit

Lots of time I have spent on technical cases like how to export functions that are already implemented in other packages as S3 methods and I just add new class, how to write assignment function appropriately.

Another big step was systematization of different types of functions and output produced by them. The most important was unification of train and predict functions for topic models from different packages and application of output to topic_wordcloud and topic_network functions.

I meet Maciej Eder in Lepizig at the Digital Humanities Summer School in Leipzig. Thanks to his help and lots of insights gained during work on stylo R package, he saved lots of my time on code refactoring and preparing for cran submission.

After that we prepared another GSOC meeting with my mentors in Wrocław. We discussed progress in GSOC 2016 and decided what kind of steps should we take next.

For now I plan to finish works on the documentation of existing objects, preparation for the cran check and cleaning up the code. Because, my approach for the GSOC was test driven development I have almost all tests written already. Also, thanks to that most of the examples are prepared.