Tag: CRAN

gginnards 0.0.4

Package update / R packagesLeave a comment

This update provides the following enhancements compared to ‘gginnards’ 0.0.3.

  • Track updates to package ‘ggplot2’, adding support and examples for plot layers created with geom_sf() .
  • Revise documentation.
  • Move git repository from Bitbucket to Github.
  • Set up Github action for CRAN-checks on Windows, OS X and Ubuntu.

Documentation web site at http://docs.r4photobiology.info/gginnards/ includes all help pages, with output from all examples, and vignettes in HTML format.
NOTE: The new version of the package is on its way to CRAN.

Please raise issues concerning bugs or enhancements to this package through GitHub https://github.com/aphalo/gginnards/issues

ggpmisc 0.3.8

Package update / R packagesLeave a comment

[27 January] ‘ggpmisc’ 0.3.8-1 is on its way to CRAN. The only change is correcting a mistake in a vignette. This was caused by the code-breaking change now highlighted below.

Package ‘ggpmisc’ focuses mainly on plot annotations. The new version adds fixes bugs and adds some minor feature. There are more significant changes to the documentation.

The package documentation web site at: https://docs.r4photobiology.info/ggpmisc/ now includes a changelog, so I am brief here.

Changes from version 0.3.7 the most recent CRAN release, are:

  • Move of the Git repository from Bitbucket to GitHub.
  • Revise stat_fit_glance(), stat_fit_augment(), stat_fit_tidy() and stat_fit_tb() to add support for additional methods and make it possible to pass additional arguments. This is a code-breaking change in that packages ‘broom’ and/or ‘broom.mixed’ need to be loaded explicitly with library().
  • Fix bugs related to handling of Date values.

Acknowlegement: This update was done in part to address questions raised at stackoverflow. The tag [ggpmisc] is in use at stackoverflow for questions related to this package.

Documentation web site at http://docs.r4photobiology.info/ggpmisc/ includes all help pages, with output from all examples, and vignettes in HTML format.

NOTE: The new version of the package is on its way to CRAN.

Please raise issues concerning bugs or enhancements to this package through GitHub https://github.com/aphalo/ggpmisc/issues.

ggpmisc 0.3.7

Package update / R packagesLeave a comment

Package ‘ggpmisc’ focuses mainly on plot annotations. The new version adds features that I hope will be found useful.

Package documentation web site at: https://docs.r4photobiology.info/ggpmisc/

Changes from version 0.3.6 the most recent CRAN release, are:

New

Filtering based on 1D density

Three new statistics stat_dens1d_filter(), stat_dens1d_filter_g() and stat_dens1d_labels() are 1D versions of the existing 2D functions which received a minor update.

  • Add stat_dens1d_filter(), stat_dens1d_filter_g() and stat_dens1d_labels(), to complement existing stat_dens2d_filter(), stat_dens2d_filter_g() and stat_dens2d_labels().
  • Update stat_dens2d_filter(), stat_dens2d_filter_g() and stat_dens2d_labels() adding formal parameters keep.sparse and invert.selection, as available in the new 1D versions.
  • Update stat_dens2d_labels() to accept not only character strings but also functions as argument to label.fill as the new stat_dens1d_labels() does.

Table insets and their formatting

Updates to statistics stat_fmt_tb() and stat_fit_tb() add flexibility.

  • Update stat_fit_tb() to support renaming of terms/parameter names in the table (Suggested by Big Old Dave and Z. Lin). In addition implement selection, reordering and renaming of columns and terms/parameters using positional indexes and pattern matching of truncated names in addition to whole names. Improve formatting of small P-values.
  • Update stat_fmt_tb() to support the same expanded syntax as stat_fit_tb().

Here is an example for an ANOVA table inset.

formula <- y ~ x
ggplot(PlantGrowth, aes(group, weight)) +
  stat_summary(fun.data = "mean_se") +
  stat_fit_tb(method = "lm",
              method.args = list(formula = formula),
              tb.type = "fit.anova",
              tb.vars = c(Term = "term", "df", "M.S." = "meansq",
                          "italic(F)" = "statistic",
                          "italic(p)" = "p.value"),
              tb.params = c("Group" = 1, "Error" = 2),
              table.theme = ttheme_gtbw(parse = TRUE)) +
  labs(x = "Group", y = "Dry weight of plants") +
  theme_classic()

 

Acknowlegement: This update was encouraged by recent questions at stackoverflow. The tag [ggpmisc] is in use at stackoverflow for questions related to this package.

Documentation web site at http://docs.r4photobiology.info/ggpmisc/ includes all help pages, with output from all examples, and vignettes in HTML format.

NOTE: The new version of the package is on its way to CRAN.

Please raise issues concerning bugs or enhancements to this package through Bitbucket https://github.com/aphalo/ggpmisc/issues.

photobiologySensors 0.5.0

News / Package updateLeave a comment

Package documentation web site at: https://docs.r4photobiology.info/photobiologySensors/

The main changes from version 0.4.0, the current CRAN version:

New

  • Rename member spectra by prepending suppliers’ names and rebuild sensors.mspct with ‘photobiology’ (0.10.5) which is now required.
  • Add data for angular responses saved in a list of data frames named diffusers.lst.
  • Update the User Guide.

Backward incompatibilities

Code breaking because of renaming of members of the collection of sensor response spectra.

NOTE: The updated package has been submitted to CRAN.

Please raise issues concerning bugs or enhancements to this package through Bitbucket at https://bitbucket.org/aphalo/photobiologySensors/issues

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