Define fortify and autoplot functions to allow ggplot2 to handle some popular R packages.

Hi,

please, when i try to run

library(ggfortify) library(survival) fit <- survfit(Surv(time, status) ~ sex, data = lung) autoplot(fit)

gave this error: Error: GeomConfint was built with an incompatible version of ggproto. Please reinstall the package that provides this extension.

thank you so much

survfit from the survival package keeps the user's order of factor levels, but they become alphabetically reordered once ggfortify is used. This change keeps the levels in their original order.

closes #142. closes #143.

Dear Sir, I have written a function in which I used ggfortify to plot PCA the overall function is pretty simple, see below. When I do the package (https://github.com/kendomaniac/docker4seq) check I get the following warning: samplesPca: no visible global function definition for ‘autoplot’ Undefined global functions or variables: autoplot

I import in my function ggfortify, but it seems that the autoplot in not imported from ggfortify Could please suggest a way of fix this problem? Cheers Raf

###################################### #' @title Sample PCA on raw counts #' @description This function runs PCA via ggfortify and ggplot2 on the output of samples2experiments function #' #' @param data, the counts dataframe generated by samples2experiemtn function #' @param groups, a character string indicating association between samples and experimental groups #' @param label, a boolean value, TRUE or FALSE to ad the names of the samples in the plot #' @param label.size, an integer value indicating the size of label #' @param output.file, a tab delimited file in which the first column are names from counts object from experiment.table.Rda file generated with samples2experiment function. In the pdf will be also rpesent the istigram fo the PCA variance dispersion. #' @import ggfortify #' @importFrom graphics plot #' @importFrom grDevices pdf #' @importFrom grDevices dev.off #' @importFrom stats prcomp #' @return a pdf file with the PCA plot #' @examples #'\dontrun{ #' load("test_experiment.tables.Rda") #' samplesPca(data=counts, groups=c("d","eb","wb","ws"), label = TRUE, label.size = 3) #' output.file="test.pdf", label = FALSE, label.size = 3) #' } #' @export samplesPca <- function(data, groups=NULL, output.file=NULL, label, label.size){ if(!is.null(groups)){ data.df <- data.frame(names(data), as.factor(groups)) names(data.df) <- c("samples","groups") if(is.null(output.file)){ autoplot.prcomp(prcomp(t(data)), data=data.df, colour='groups', label = label, label.size = label.size) }else{ pdf(output.file) plot(prcomp(t(data)), main="") autoplot(prcomp(t(data)), data=data.df, colour='groups', label = label, label.size = label.size) dev.off() cat(paste("\nPCA is saved in ",output.file, sep="")) } }else{ if(is.null(output.file)){ autoplot(prcomp(t(data))) }else{ pdf(output.file) plot(prcomp(t(data)), main="") autoplot(prcomp(t(data))) dev.off() cat(paste("\nPCA is saved in ",output.file, sep="")) } } return(data.df) }

Hi,

Thanks for the amazing package. Is there a way to remove label legend which is a small "a" in ggforty? Some parameters to work as geom_text(show.legend=F)? Thanks.

Bests, oben

https://cran.r-project.org/web/packages/ggfortify/index.html shows:

Package ‘ggfortify’ was removed from the CRAN repository.

Formerly available versions can be obtained from the archive.

Archived on 2016-05-02 as check problems were not corrected despite reminders.

> install.packages fails as expected; however, the devtools install continues to work as expected after:

library(devtools)
install_github('sinhrks/ggfortify')

plotdiag <-autoplot(result, which=c(1:3,5), mfrow=c(2,2)) plotdiag

***partdiage;

ggsave(plot=plotdiag, file='cuckoo-R-diag.png', h=4, w=6, units="in", dpi=300)

returns Error in UseMethod("grid.draw") : no applicable method for 'grid.draw' applied to an object of class "ggmultiplot"

I think Wickham modifies ggsave() to accept gtable objects. Do you create such an object? Perhaps add that as a class as well?

Using ggfortify 0.1.0 and ggplot 2.0.0

It appears that autoplot.lm() uses deprecated dplyr functions. This is a problem because dplyr is now throwing warnings about this and people using ggfortify on a daily basis for creating diagnostic plots shouldn't think that ggfortify has been abandoned.

In particular lines 132, 136 and 140 in R/fortify_stats_lm.R use this to sort the fortified data by some column, but we can now just specify the arrangement without quoting desc(abs(.resid)). The same is true of the other instances.

I cloned ggfortify and made the changes and it appears to work. However when I went to build the package, it seems that there are a bunch more dplyr deprecated function calls in the vignettes "basics.Rmd", "plot_pca.Rmd", "plot_surv.Rmd", "plot_ts.Rmd". I was reluctant to dive into all of those vignettes just to report this bug.

I suspect that it wouldn't take to long to fix the vignettes, but I suspect this issue will touch a few other classes. I would be happy to start fixing those if it would be appreciated, but I didn't want to invest too much time before contacting people in charge.

library(ggfortify) options(lifecycle_verbosity = 'error') # error out on deprecation warnings model <- lm( Volume ~ Height, data=trees) autoplot(model)

The output (via reprex::reprex() ) is as follows:

library(ggfortify) #> Loading required package: ggplot2 options(lifecycle_verbosity = 'error') model <- lm( Volume ~ Height, data=trees) autoplot(model) #> Error: arrange_() was deprecated in lifecycle 0.7.0 and is now defunct. #> Please use arrange() instead. #> See vignette('programming') for more help

Greetings.

This PR adds support of survfitms - multistate survival models built using Surv(..., type = 'mstate').

Here is an overview of changes to fortify:

• To preserve original variable name depending on model class (surv or pstate) it is added to the end of the output data.frame;
• Where necessary checks for variable name are made;
• If surv.connect = T new rows are repeated according to number of states;
• In the end columns are sorted to be in usual order.

To autoplot:

• Added facet_grid support - argument grid. It's more convenient for 2-dim set plots;
• Added support to swap order of faceting (if facets) or column with rows (if grid). By default event first, then strata. Argument strip_swap;
• An argument conf.int.group = NULL was added to plot_confint. It's required to split CI ribbons by both - event and strata, because it can't be done with fill only;
• such artificial column group is assembled in autoplot.

Feedback or questions are welcome.

In fortify_surv.R, changed the regular expression on line 49 to be "[^,]=" instead of ".=". This is in response to Issue #214, and the change is meant to allow autoplot to work on survfit objects with multiple stratification variables.

testResults.txt

My attempt at #128. Unfortunately, I can't test it myself because the package fails devtools::check() with a nonsensical error message. It says:

Installation failed.
See ‘/private/var/folders/d3/ff25_6td3sjc02d8rfbwvmxc0000gn/T/RtmpxbR4VD/ggfortify.Rcheck/00install.out’ for details.

And when I check the suggested log file, I see:

* installing *source* package ‘ggfortify’ ...
** R
** inst
** preparing package for lazy loading
** help
*** installing help indices
** building package indices
** installing vignettes
** testing if installed package can be loaded
Warning: namespace ‘IRanges’ is not available and has been replaced
by .GlobalEnv when processing object ‘’
Warning in library(package, lib.loc = lib.loc, character.only = TRUE, logical.return = TRUE,  :
  there is no package called ‘IRanges’
Error in .requirePackage(package) :
  unable to find required package ‘IRanges’
Error: loading failed
Execution halted
ERROR: loading failed
* removing ‘/private/var/folders/d3/ff25_6td3sjc02d8rfbwvmxc0000gn/T/RtmpxbR4VD/ggfortify.Rcheck/ggfortify’

I can't figure out why it's trying to load IRanges, and I can't figure out why it would be unable to do so, since I have it installed.

Closes #67. Some changes are required for ggplot2 1.1.0 (dev). This works on my local with ggplot2 dev, still needs followings.

• [x] Add a logic to distinguish ggplot2 version (and use previous logic for earlier vers...).
• [x] Allow Travis to test 1.1.0 and earlier ggplot2 versions
• ~~R CMD check with R dev version~~ Using R dev version is little hard to maintain dep packages. Skipped.

When I follow your sample code to plot a PCA object, but call color= instead of colour=, the argument is ignored.

library(ggfortify)
library(cowplot)
pca_res <- prcomp(iris[1:4], scale = TRUE)
british <- autoplot(pca_res, data=iris, colour='Species')
us <- autoplot(pca_res, data=iris, color='Species')
plot_grid(british, us,  labels=c('colour', 'color'))

I think this is the only time I've ever encountered a difference between the American and British spellings.

> sessionInfo()
R version 4.1.2 (2021-11-01)
Platform: x86_64-w64-mingw32/x64 (64-bit)
Running under: Windows 10 x64 (build 19044)

Matrix products: default

locale:
[1] LC_COLLATE=English_United States.1252  LC_CTYPE=English_United States.1252   
[3] LC_MONETARY=English_United States.1252 LC_NUMERIC=C                          
[5] LC_TIME=English_United States.1252    

attached base packages:
[1] stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
[1] cowplot_1.1.1    ggfortify_0.4.14 ggplot2_3.3.5  

Hello,

with the ggdistribution() function x and y labels do not appear.

Code to reproduce the issue:

p <- ggfortify::ggdistribution(dnorm, seq(-3, 3, 0.1), mean = 0, sd = 1)

p <- p +
    labs(
    title = "Title",
    subtitle = "subtitle",
    caption = "name of the author copyright",
    tag = "Plot A",
    x = "x label",
    y = "y label"
) 
p

Plot produced by the code:

System information

• OS Platform and Distribution:macOS Monterey 12.1
• ggfortify installed from (e.g. CRAN or Github): CRAN
• ggfortify version: 0.4.14
• ggplot2: 3.3.5
• R: 4.1.2 (2021-11-01)

Thanks, Peter

Hello!

First, thank you for developing the package, it has been very useful.

I actually open an issue to request (if possible) a new feature at plotting the factor loadings in a PCA. There are already nice aesthetic options for the loadings. However, I would be interested on setting a loadings.cutoff option to select the desired ones. When working with PCAs based on many variables (50 in my case) it can become very messy even when playing with sizes and all. Furthermore, there are some factors that I may not be interested on, because they don't explain any variance in the samples, so it's also a nice feature to filter-out some factors.

Thank you in advance.

Regards, Cristian

I am trying to change the confidence level but conf.int.value gets ignored. Is there a workaround? No matter what level I put, it gets ignored.

library(forecast) library(ggfortify) d.arima <- auto.arima(AirPassengers) autoplot(d.arima, predict=predict(d.arima,n.ahead=3),ts.colour = 'blue', predict.colour = 'blue', predict.linetype = 'dashed', conf.int = TRUE,conf.int.value=0.99)

I have tried autoplot with ggfortify loaded for a model output of the function lmer of the package lme4. I have tried also ggfortify:::autoplot.lm applied to the model and did not work any of both options. It would be great if you could add a method for the class merMod (lmerMod, glmerMod).

Thanks!