Tag: ggpmisc

ggpmisc 0.4.0 and ggpp 0.4.0

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The main change is the split of package ‘ggpmisc’ into two packages. Starting from this version, package ‘ggpmisc’ focuses only on plot annotations related to model fits and statistical summaries. The new package ‘ggpp’ contains generally useful extensions to the grammar of graphics such as new geometries and position functions. As package ‘ggpmisc’ loads package ‘ggpp’ the migration should have minimal if any impact on users’ code. Package ‘ggpp’ will be most useful to authors of packages that currently import ‘ggpmisc’, including myself. It is good to be aware that the split almost exactly follows the subject matter of the two vignettes previously part of ‘ggpmisc’. When using ‘ggpmisc’, users will notice that some functions have migrated only when consulting the documentation.

‘ggpp’

The package documentation web site at: https://docs.r4photobiology.info/ggpp/ includes a changelog.

Compared to ‘ggpmisc’ 0.3.9, the following changes have been introduced. New justification styles have being implemented to complement position_nudge_center(). They are supported in geom_text_linked(), geom_plot(), geom_table(), geom_grob() and geom_marging_grob(). In the current implementation all rows in data should contain the same hjust or vjust value when using the new types of justification described here, this seems reasonable as they compute the individual justification values from the data. All other justification values, either numeric or character do not have this restriction and can be used as in geoms from ‘ggplot2’. These new features may change in the near future.

  • Rename geom_text_linked().
  • Implement justifications "outward_mean", "inward_mean", "outward_median" and "inward_median" so that outward and inward are with respect to the centroid of the data instead of to the middle of the x or y scales. This should be useful in combination with position_nudge_center().
  • Implement justifications "outward_nnn" and "inward_nnn" so that outward and inward are with respect to the number resulting from applying as.numeric() to the characters that replace nnn. For example strings like "outward_0.5", "inward_3e5" or "outward_-3e-2" are supported. This should be useful when manual tweaking is desired. As special cases "outward_0" and "inward_0" apply justification outward and inward with respect to the origin. This should be useful for biplots used for PCA and similar cases with arrows radiating out of the origin. (The "outward" and "inward" justification implemented in ‘ggplot2’ is relative to the middle of the x or y scales.)
  • Revise compute_npcx() and compute_npcy() to support multiple steps per group (needed in ‘ggpmisc’).
  • Fix problem related to "outward" and "inward" justification of text labels when angle aesthetic takes values < -45 or > 45 degrees. This code change alters how old plots are rendered if text labels have been rotated by more than 45 degrees.
  • [‘ggplot2’, ‘ggrepel’] The problem with angle was a “bug” in ‘ggplot2’ also present in ‘ggrepel’. A pull request for ggplot2::geom_text() has been submitted and merged. This is now in the ‘ggplot2’ 3.3.4 milestone retaining consistent behaviour between ‘ggplot2’, ‘ggrepel’, ‘ggpp’ and ‘ggpmisc’.

Please raise issues concerning bugs or enhancements to this package through GitHub at https://github.com/aphalo/ggpp/issues. Pull requests are also welcome.

‘ggpmisc’

The package documentation web site at: https://docs.r4photobiology.info/ggpmisc/ includes a changelog.

Changes from ‘ggpmisc’ version 0.3.9, the most recent CRAN release, are:

  • Add stat_quant_eq() based on quantile regression as implemented in package ‘quantreg’. (enhancement suggested by Mark Neal)
  • Add n.label and n to the values returned by stat_poly_eq() and stat_quant_eq(). (enhancement suggested by a question from ganidat)
  • Add r.squared, adj.r.squared, p.value and n as numeric to values returned in addition to the corresponding character labels when stat_poly_eq() is called with output.type other than numeric. Similarly for n and rho in the case of stat_quant_eq(). (enhancement suggested by a question from Tiptop)
  • Fix bug in stat_poly_eq() leading to empty returned value when data contains too few observations to fit the model. (reported by ganidat)
  • Add support for quantile regression rq, robust regression rlm, and resistant regression lqs and function objects to stat_fit_deviations().

Please raise issues concerning bugs or enhancements to this package through GitHub at https://github.com/aphalo/ggpmisc/issues. Pull requests are also welcome.

Acknowlegements: I thank Kamil Slowikowski for his contributions of ideas and for his willingness to keep the development of our packages coordinated. This update was done in part to address questions raised and reports of bugs by users, which I thank. The tag [ggpmisc] is in use at stackoverflow for questions related to the use these two packages. I thank Mark Neal for the suggestion that lead to the new statistic stat_quant_eq() and for his help during its testing. I thank Stackoverflow users ganidat and Tiptop for enhancement ideas.

Documentation web sites at https://docs.r4photobiology.info/ggpmisc/ and https://docs.r4photobiology.info/ggpp/ include all help pages, with output from all examples, and vignettes in HTML format. The online vignettes include the output of all code examples, while the vignettes as included in the package, contain the output of only a subset of the code examples so as to keep the documentation at a reasonable size for package distribution.

NOTE: The new package ‘ggpp’ (0.4.0)  is in CRAN and updated ‘ggpmisc’ (0.4.0) is on its way to CRAN. The latest development versions of both packages can be installed from GitHub.

remotes::install_github("aphalo/ggpp")
remotes::install_github("aphalo/ggpmisc")

ggpmisc 0.3.9

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Package ‘ggpmisc’ focuses mainly on plot annotations. The new version fixes minor bugs and adds a major new feature: position functions for data aware nudging. These nudge functions were born out of an exchange of ideas with Kamil Slowikowski, the author and maintainer of the very popular package ‘ggrepel’. We are currently considering how to make them compatible with geom_text_repel() and geom_label_repel().

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

Changes from version 0.3.8, the most recent CRAN release, are:

  • Update the documentation of geom_plot().
  • [Under development!] Link repositioned text to its original position with a segment or arrow: geom_linked_text(). Except for
    the drawing of segments or arrows this new geometry behaves as ggplot2::geom_text() . Note: Segments and arrows are drawn only
    if the position function used returns both the repositioned and original coordinates.
  • Add support for advanced nudging: position_nudge_centre() and position_nudge_line() compute the direction of nudging and return
    both the nudged and original positions.
  • Add support for simple nudging: position_nudge_to() nudges to new user-supplied position(s); position_nudge_keep() nudges to
    position(s) based on user-supplies position shift. These functions return both nudged and original position(s).

Example: Nudging text labels away from a curve.

library(ggpmisc)

set.seed(16532)
df <- data.frame(
  x = -10:10,
  y = (-10:10)^2 + rnorm(21, 0, 4),
  l = letters[1:21]
)

ggplot(df, aes(x, y, label = l)) +
  geom_point() +
  stat_smooth(method = "lm", formula = y ~ poly(x, 2, raw = TRUE)) +
  geom_text(aes(y = y, label = l),
            position = position_nudge_line(method = "lm",
                                           x = 0.4, 
                                           y = 4,
                                           formula = y ~ poly(x, 2, raw = TRUE),
                                           direction = "split"))
The resulting plot.

Nudging of text labels away from a curve.

Roadmap: A split of the ‘ggpmisc’ package into two packages, one including the extensions to the grammar of graphics and another one including the functions related to plot annotations based on model fitting and statistical summaries seems necessary as the package has grown to include several extensions to the grammar of graphics that are generally useful. We are also working on improved inter-operation between ‘ggpmisc’ and ‘ggrepel’.

Acknowlegement: I thank Kamil Slowikowski for his contributions of ideas and for his willingness to keep the development of our packages coordinated. This update was done in part to address questions raised and reports of bugs by users, which I thank. The tag [ggpmisc] is in use at stackoverflow for questions related to the use this package. Please raise issues concerning bugs or enhancements to this package through GitHub at https://github.com/aphalo/ggpmisc/issues. Pull requests are also welcome.

Documentation web site at http://docs.r4photobiology.info/ggpmisc/ includes all help pages, with output from all examples, and vignettes in HTML format. The online vignettes include the output of all code examples, while the vignettes as included in the package, contain the output of only a subset of the code examples so as to keep the documentation at a reasonable size for package distribution.

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

ggpmisc 0.3.8

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[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

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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.