Changes in version 0.8 (2025-06-16)                   

  - Changed the default colours if influence/contrastive plots to the
    brick red / blue used by LIME in R version.
  - Corrected the function "ciu.contrastive" that was implemented in a
    very strange (and presumably incorrect) way.
  - Added possibility to get line segment IO-plots for categorical
    features, rather than the earlier histogram visualisation. Added
    parameter to ggplot.ciu() "categorical_style="segment"", where the
    default is now to use line segments, even though that breaks
    backwards compatibility a little. However, for some reason setting
    "ylim" breaks the old "geom_col" plot so the bar plots are now
    un-scaled. But, strange enough, "+ ylim" applied to the returned
    ggplot works so it's possible to adjust afterwards. Something
    happened somewhere, no change in the CIU code and it worked in the
    past.
  - Added new function ciu.contrastive that uses CU values of one
    class/instance/whatever as the baseline "normal.CU" values of the
    other.
  - Added new function ciu.contextual.influence that calculates
    contextual influence value(s) from CI and CU value(s) and
    "baseline".
  - Added new file ContextualInfluence.R for functions related to
    contextual influence.
  - Fixed x-axis label error for influence plot in ciu.ggplot.col.

                 Changes in version 0.6.0 (2022-11-29)                  

  - Extensive tests on Intermediate Concepts, which are also integrated
    into the new README.Rmd file (and README) as well as in test scripts
    TestCases.R and TestCases_NoObject.R on Github.
  - Fixed inverted axis bug in plot in plot.ciu.3D.
  - Integrated support for mlr3. Only tested with "classif.rpart" model
    though because other tested models (xgboost, nnet, ...) don't like R
    types and no need/time to dive into mlr3 for the moment. To fix in
    the future in case bugs are discovered.
  - Added parameter "plot.mode" to "ciu.ggplot.col" function, which
    allows for value "overlap" that plots CI as a bar and then CU as
    another bar over it, scaled into CI bar. Colour of CU bar can either
    be fixed (dark green by default) or set to NULL, which then uses the
    green-yellow-red color scale (unless those colours are changed by
    the function parameters).
  - Removed parameter for min/max values of contextual influence because
    the range of contextual influence is (and should be) always one (1)
    based on the mathematical constructs.
  - Added new method "ggplot.ciu" to ciu.new for plotting input/output
    graphs with ggplot. Identical to old plot.ciu, except that 1) ggplot
    offers some advantages, notably what comes to figure scaling, 2)
    added possibility to include CIU visualisation (cmin, cmax, neutral)
    by setting "illustrate.CIU=TRUE".
  - Added new method "influence" to ciu.new for getting numerical
    contextual influence (rather than just seeing them in plots). TO-DO:
    add corresponding function to "ciu.R".
  - Corrected axis in plot.ciu.3D.

                 Changes in version 0.5.0 (2021-06-30)                  

  - Textual explanations have been implemented with function
    "ciu.textual".
  - Implemented "meta.explain" method, which returns a self-contained
    "ciu.meta.result" object with CIU results for a given instance. This
    mainly makes it possible to visualize exactly the same CIU result in
    different ways. Before this (and still if no "ciu.meta" parameter is
    given), every visualization method ran "explain" again, so CIU
    results could differ somewhat between different runs.
  - Added parameters "use.influence" and "influence.minmax" to
    "ggplot.col" and "barplot.ciu" functions/methods, which produces a
    LIME/SHAP/etc-like plot where "influence = (influence.max -
    influence.min)*ci(cu-neutral.CU)", bars go either right or left of
    zero and there are only two colours.
  - Added support for factor-type inputs to method "$plot.ciu".
  - Created new "class" called "ciu", which is just a list object with
    the "instance variables" of a CIU object. This makes it possible to
    create plot functions that are not methods of CIU but rather take a
    "ciu" object as their first parameter. The main reason for doing
    this modification is that CIU objects seem to use much more memory
    than a simple data-based "ciu" object. The documentation and package
    tools in R are also not too aware about "inner functions" (methods),
    which is an inconvenient. Finally, the plan was indeed to go for
    this approach in any case because increasing the code length of CIU
    was not desirable in the long run. The way in which it is
    implemented now allows functions and methods to be used
    interchangeably in any case.

                 Changes in version 0.1.0 (2020-11-20)                  

  - First version of ciu published at CRAN