Version 0.5.0 (previously announced as 0.4.8) brings enhancements to the annotations based on model fits. The most significant change for all users is the new convenience function
use_label() that greatly simplifies the assembly of labels from components and their mapping to aesthetics. We examplify its use and some of the other new features. It also contains two changes that are not backwards compatible and that can in isolated cases break existing code (hence the version-number change into 0.5.0).
This release corrects problems triggered by recent updates to packages ‘lubridate’ and possibly ‘tibble’ (reported by putmanlab in issue #7 ). It also adds some enhancements for class
solute_spct, still under development.
BUG FIX: Conversions between
POSIXct objects are tricky because objects of the former class do not store information on the time zone. A change in ‘lubridate’ 1.8.0 made a previously working approach to these conversions silently fail to apply the shift to the hours.
If you use any of
sunset_time() either use ‘lubridate’ (< 1.8.0) or update a.s.a.p. to ‘photobiology’ (>= 0.10.12) from GitHub.
This update adds flexibility to the user interface used to indicate the target when searching for wavelengths matching specific spectral data values. It also contains a preliminary implementation of classes
solute_spct and collections
solute_mspct for storing spectral molar or mass coefficients of attenuation.
Version 0.4.7 brings a fix for a bug that could prevent the use of weights passed through aesthetic
weight in some of the model-fitting statistics. Several enhancements to the model fitting statistics make it easier to fit different models to different groups or panels, and make it possible/easier to select among methods supported by a model fit function.
This non-code-breaking update brings a few new features and tracks deprecations in package ‘tidyr’.
This is a major and code-breaking update. Naming conventions have been changed and several new spectra have been added. Previously included spectra have in most cases been recomputed and may slightly differ from earlier versions of the same data. In part this was done to reduce the size of the data objects, making it possible to include more spectra while keeping the size of the package reasonable. The number of spectra is more than 100, including several of the newest high CRI LEDs as well as some recent types for horticulture.
A handbook on how to do calculations used in photobiological research with R has been under preparation for a long time. An 80% complete version has been available through LeanPub for several years. The book describes the use of our suite of R packages and also of functions from base R and a few other packages available through CRAN. I (Pedro J. Aphalo) am the lead author, while Andreas Albert, T. Matthew Robson and Titta Kotilainen have contributed text and examples and feedback.
Although we haven’t had time to finish writing the book, I have been checking that the code examples work with current versions of R and packages. Rather recently I made small edits to a few code chunks that had stopped working and uploaded the new version of the PDF file to LeanPub.
Some minutes ago I tried to build all examples with R 4.2.o, a major update to R released some days ago. R 4.2.o contains a bug, that unluckily prevents a couple some examples in the book from running under MS-Windows. The already available patched version of R 4.2.0 solves this problem. Anyway, this bug affects only a very specific use related to data acquisition.
The book is sold for the amount the buyer wishes to pay, including getting it for free.
For Windows users the most significant changes are that now the binary distribution contains only a 64 bit executable. A new build chain is used and Rtools 4.2 is required to build from sources packages that include C, C++ or FORTRAN code. As is always the case, all CRAN packages are tested on CRAN itself.
Relevant to all operating systems the recently added pipe oprerator (
|>) now supports the use of the underscore (
_) as a placeholder on the rhs of the operator.
1:10 |> mean() |> round()
1:10 |> mean(x = _) |> round(x = _)
These two statements are equivalent, but
_ makes it possible to pipe by name the value returned by the lhs into any parameter on the rhs.
There are also some improvements to the ‘grid’ package adding flexibility to pattern and gradient fills and masks, which are recently added features. They are yet to be well supported by ‘ggplot2’.
Eighteen months from the previous release, this update brings many improvements to
autoplot() methods. These include enhanced capabilities for handling of normalized and scaled spectral data, as well as cosmetic tweaks to labels.
This update also includes smaller enhancements and fixes a bug. It tracks changes in packages ‘ggrepel’ (>= 0.9.1), ‘photobiology’ (>= 0.10.10) and ‘ggplot2’ (>= 3.3.3) and deprecation of functions in ‘tidyr’ (>= 1.0.0). The updated code depends on the revised
normalize() function in ‘photobiology’ (>= 0.10.10) and on ‘ggrepel’ (>= 0.9.1).
Version 0.4.4 fixes a bug affecting most of the geometries in the package. Adding multiple layers using the same geom to the same plot would result in only one of these layers being rendered with others silently missing from the graphical output.
Changes compared to version 0.4.3, the previous version in CRAN are:
- Fix bug caused by repeated grob and grob tree names.
Documentation web site at http://docs.r4photobiology.info/ggpp/ includes all help pages, with output from all examples, vignettes as well as a changelog in HTML format.
NOTE: Version 0.4.4 is on its way to CRAN.
Please raise issues concerning bugs or enhancements to this package through GitHub at https://github.com/aphalo/ggpp/issues. Pull requests are also welcome.
Version 0.4.6 fixes a significant bug occasionally affecting highlighting and labelling of peaks and valleys. Even though when triggered the problem is easily detectable by looking at the plot, please, update.
Changes compared to version 0.4.5, the previous version in CRAN are:
- Fix bug in
stat_valleys(). They could return wrong values for peaks and valleys if the rows in
data in the ggplot object were not sorted by the value of x.
Documentation web site at http://docs.r4photobiology.info/ggpmisc/ includes all help pages, with output from all examples, vignettes as well as a changelog in HTML format.
NOTE: Version 0.4.6 is on its way to CRAN.
Please raise issues concerning bugs or enhancements to this package through GitHub https://github.com/aphalo/ggpmisc/issues
I just want to share what is in my “to do” list and what I wish someone else could contribute to the R for photobiology suite of packages either as part of the suite or as independent extensions. In addition to the enhancements listed below, I hope at some point to be able to submit the packages in the suite to R Open Science to be peer reviewed.