My new book was published on 28 July. Within the next few days I will make available on-line supplementary material, and explain how I created in R the word cloud in the front cover of the book. The word list I used is that for the R index from the book. I typeset the book using LaTeX. It is currently available from the publisher through the book’s web page.
This update provides the following enhancements compared to ‘gginnards’ 0.0.3.
geom_sf() .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
[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:
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().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.
During the last two years development has continued at a slow pace. Most changes are to the functions for interactive acquisition of spectra, correction of bugs and tracking to changes in packages from which imports are made. Testing was done with new OmniDriver releases. Some data examples have been added and also replaced. Some progress with the vignettes has been done. However, the documentation still needs work.
One visible change is the move of the Git repository from Bitbucket to GitHub. Package ‘rOmniDriver’ has also been moved to GitHub and its documentation updated to reflect this.
Starting from this release, the changelog is included in the online documentation at http://docs.r4photobiology.info/ooacquire/.
Please raise issues concerning bugs or enhancements to this package through GitHub at https://github.com/aphalo/ooacquire/issues
NOTE: This package is NOT available through CRAN.
This package is available through the r4photobiology repository and through GitHub.
INSTALLATION:
devtools::install_github("aphalo/romnidriver")
devtools::install_github("aphalo/ooacquire")
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:
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.
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().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.stat_dens2d_labels() to accept not only character strings but also functions as argument to label.fill as the new stat_dens1d_labels() does.Updates to statistics stat_fmt_tb() and stat_fit_tb() add flexibility.
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.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.