- filters.R
 * Created belowFactor filter (to set a threshold, and filter under that threshold).
 * Modified belowDiff to use belowFactor.

- measures.R
  * Added RelCount,SumSQRel, SQRTRel, DiffRel measures.
  * Modified measures to select only the columns (all or rels) *explicitely* (i.e. instead of rowSums(dframe) -> rowSums(dframe[,all]).
  * Deleted "application constants for relations" (now using the ones defined at simplify.R for the whole system.
  * Added drop=FALSE parameter to return option. If the resulting dataframe has only one column, it won't coerce it to array (handy for later operation with mdf).
  * Renamed NormallR -> NormRAll
- simplify.R
  * Added global environment variables (rels and all). Binding blocked to prevent accidental reasignation.
  * Added getDf function, to simplify the creation of dataframes, encapsulate functionality and avoid repetition.
  * Added labeldf function, to simplify the "relabeling" of the columns of a dataframe, encapsulate func. and avoid repetition.
  * Modified abcol, to support another kind of column names (lowercaps, without '[]').
  * Created pivot function, to encapsulate colselect and simplify calls (makes more sense from an external/user POV).
  * Renamed variable 'd' to 'data' (a little bit more clear/readable).

- filter_data.R
  * Huge rewrite: support for all the previously described modifications in the libraries/aux. functions.
  * Modified focus/purpose: to serve as an example of the application of filters, with different cases (one filter, combination, all).

- cflower.R
  * Rewrite to support the modifications previously described in the libraries/aux functions.
  * Modified output file name.
  * Changed several variable names (data -> raw_data, d-> data, etc.) to improve readability.

- excel.R
  * More or less the same as for cflower. It becomes almost a version of the former (consider merging both).