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Distorted/blurred plots in plot-pane for specific scaling settings
Plots created with ggplot are quite distorted/blurred, in particular labels. See:
And also for this small reprex.
ggplot2::ggplot(iris, ggplot2::aes(x = Sepal.Width, y = Sepal.Length)) +
ggplot2::geom_point()
I'm using Positron on Windows 11.
Thanks for testing out Positron! I was not able to reproduce this issue on Windows 11 with R 4.4.0. Could you please share more about your environment, perhaps the output of sessionInfo() if you can share it, or at least the version of R in use and the versions of libraries loaded?
Sure:
sessioninfo::session_info()
#> ─ Session info ───────────────────────────────────────────────────────────────
#> setting value
#> version R version 4.4.1 (2024-06-14 ucrt)
#> os Windows 11 x64 (build 22631)
#> system x86_64, mingw32
#> ui RTerm
#> language (EN)
#> collate German_Germany.utf8
#> ctype German_Germany.utf8
#> tz Europe/Berlin
#> date 2024-07-01
#> pandoc 3.1.12.3 @ c:\\Program Files\\Positron\\bin\\pandoc/ (via rmarkdown)
#>
#> ─ Packages ───────────────────────────────────────────────────────────────────
#> ! package * version date (UTC) lib source
#> backports 1.5.0 2024-05-23 [1] CRAN (R 4.4.0)
#> base64enc 0.1-3 2015-07-28 [1] CRAN (R 4.4.0)
#> bayestestR * 0.13.2.2 2024-06-30 [1] local
#> boot 1.3-30 2024-02-26 [2] CRAN (R 4.4.1)
#> checkmate 2.3.1 2023-12-04 [1] CRAN (R 4.4.0)
#> cli 3.6.2 2023-12-11 [1] CRAN (R 4.4.0)
#> cluster 2.1.6 2023-12-01 [1] CRAN (R 4.4.0)
#> coda 0.19-4.1 2024-01-31 [1] CRAN (R 4.4.0)
#> codetools 0.2-20 2024-03-31 [2] CRAN (R 4.4.1)
#> colorspace 2.1-0 2023-01-23 [1] CRAN (R 4.4.0)
#> correlation * 0.8.5 2024-06-16 [1] https://easystats.r-universe.dev (R 4.4.0)
#> data.table 1.15.4 2024-03-30 [1] CRAN (R 4.4.0)
#> datawizard * 0.11.0.4 2024-06-30 [1] Github (easystats/datawizard@ebe48b4)
#> digest 0.6.35 2024-03-11 [1] CRAN (R 4.4.0)
#> dplyr 1.1.4 2023-11-17 [1] CRAN (R 4.4.0)
#> easystats * 0.7.2.2 2024-06-18 [1] https://easystats.r-universe.dev (R 4.4.0)
#> effectsize * 0.8.8.2 2024-06-23 [1] https://easystats.r-universe.dev (R 4.4.0)
#> emmeans 1.10.2 2024-05-20 [1] CRAN (R 4.4.0)
#> estimability 1.5.1 2024-05-12 [1] CRAN (R 4.4.0)
#> evaluate 0.24.0 2024-06-10 [1] CRAN (R 4.4.0)
#> fansi 1.0.6 2023-12-08 [1] CRAN (R 4.4.0)
#> fastmap 1.2.0 2024-05-15 [1] CRAN (R 4.4.0)
#> foreign 0.8-86 2023-11-28 [2] CRAN (R 4.4.1)
#> Formula 1.2-5 2023-02-24 [1] CRAN (R 4.4.0)
#> fs 1.6.4 2024-04-25 [1] CRAN (R 4.4.0)
#> generics 0.1.3 2022-07-05 [1] CRAN (R 4.4.0)
#> ggeffects * 1.7.0.2 2024-06-26 [1] local
#> ggplot2 * 3.5.1 2024-04-23 [1] CRAN (R 4.4.0)
#> glmmTMB * 1.1.9 2024-03-20 [1] CRAN (R 4.4.0)
#> glue 1.7.0 2024-01-09 [1] CRAN (R 4.4.0)
#> gridExtra 2.3 2017-09-09 [1] CRAN (R 4.4.0)
#> gtable 0.3.5 2024-04-22 [1] CRAN (R 4.4.0)
#> Hmisc 5.1-3 2024-05-28 [1] CRAN (R 4.4.0)
#> htmlTable 2.4.2 2023-10-29 [1] CRAN (R 4.4.0)
#> htmltools 0.5.8.1 2024-04-04 [1] CRAN (R 4.4.0)
#> htmlwidgets 1.6.4 2023-12-06 [1] CRAN (R 4.4.0)
#> insight * 0.20.1 2024-06-11 [1] CRAN (R 4.4.1)
#> knitr 1.47 2024-05-29 [1] CRAN (R 4.4.0)
#> lattice 0.22-6 2024-03-20 [1] CRAN (R 4.4.0)
#> lifecycle 1.0.4 2023-11-07 [1] CRAN (R 4.4.0)
#> lme4 1.1-35.4 2024-06-19 [1] CRAN (R 4.4.1)
#> magrittr 2.0.3 2022-03-30 [1] CRAN (R 4.4.0)
#> MASS 7.3-60.2 2024-04-26 [2] CRAN (R 4.4.1)
#> Matrix 1.7-0 2024-04-26 [2] CRAN (R 4.4.1)
#> mgcv 1.9-1 2023-12-21 [1] CRAN (R 4.4.0)
#> minqa 1.2.7 2024-05-20 [1] CRAN (R 4.4.0)
#> modelbased * 0.8.8 2024-06-11 [1] https://easystats.r-universe.dev (R 4.4.0)
#> multcomp 1.4-25 2023-06-20 [1] CRAN (R 4.4.0)
#> munsell 0.5.1 2024-04-01 [1] CRAN (R 4.4.0)
#> mvtnorm 1.2-5 2024-05-21 [1] CRAN (R 4.4.0)
#> nlme 3.1-164 2023-11-27 [2] CRAN (R 4.4.1)
#> nloptr 2.1.0 2024-06-19 [1] CRAN (R 4.4.1)
#> nnet 7.3-19 2023-05-03 [1] CRAN (R 4.4.0)
#> numDeriv 2016.8-1.1 2019-06-06 [1] CRAN (R 4.4.0)
#> parameters * 0.22.0.1 2024-06-30 [1] local
#> performance * 0.12.0.4 2024-06-18 [1] https://easystats.r-universe.dev (R 4.4.0)
#> pillar 1.9.0 2023-03-22 [1] CRAN (R 4.4.0)
#> pkgconfig 2.0.3 2019-09-22 [1] CRAN (R 4.4.0)
#> purrr 1.0.2 2023-08-10 [1] CRAN (R 4.4.0)
#> R.cache 0.16.0 2022-07-21 [1] CRAN (R 4.4.0)
#> R.methodsS3 1.8.2 2022-06-13 [1] CRAN (R 4.4.0)
#> R.oo 1.26.0 2024-01-24 [1] CRAN (R 4.4.0)
#> R.utils 2.12.3 2023-11-18 [1] CRAN (R 4.4.0)
#> R6 2.5.1 2021-08-19 [1] CRAN (R 4.4.0)
#> Rcpp 1.0.12 2024-01-09 [1] CRAN (R 4.4.0)
#> report * 0.5.8.4 2024-06-23 [1] https://easystats.r-universe.dev (R 4.4.0)
#> reprex 2.1.0 2024-01-11 [1] CRAN (R 4.4.0)
#> rlang 1.1.4 2024-06-04 [1] CRAN (R 4.4.0)
#> rmarkdown 2.27 2024-05-17 [1] CRAN (R 4.4.0)
#> rpart 4.1.23 2023-12-05 [2] CRAN (R 4.4.1)
#> rstudioapi 0.16.0 2024-03-24 [1] CRAN (R 4.4.0)
#> sandwich 3.1-0 2023-12-11 [1] CRAN (R 4.4.0)
#> scales 1.3.0 2023-11-28 [1] CRAN (R 4.4.0)
#> see * 0.8.4.6 2024-06-17 [1] https://easystats.r-universe.dev (R 4.4.0)
#> sessioninfo 1.2.2 2021-12-06 [1] CRAN (R 4.4.0)
#> stringi 1.8.4 2024-05-06 [1] CRAN (R 4.4.0)
#> stringr 1.5.1 2023-11-14 [1] CRAN (R 4.4.0)
#> styler 1.10.3 2024-04-07 [1] CRAN (R 4.4.0)
#> survival 3.7-0 2024-06-05 [1] CRAN (R 4.4.0)
#> TH.data 1.1-2 2023-04-17 [1] CRAN (R 4.4.0)
#> tibble 3.2.1 2023-03-20 [1] CRAN (R 4.4.0)
#> tidyselect 1.2.1 2024-03-11 [1] CRAN (R 4.4.0)
#> D TMB 1.9.12 2024-06-19 [1] CRAN (R 4.4.1)
#> utf8 1.2.4 2023-10-22 [1] CRAN (R 4.4.0)
#> vctrs 0.6.5 2023-12-01 [1] CRAN (R 4.4.0)
#> withr 3.0.0 2024-01-16 [1] CRAN (R 4.4.0)
#> xfun 0.45 2024-06-16 [1] CRAN (R 4.4.1)
#> xtable 1.8-4 2019-04-21 [1] CRAN (R 4.4.0)
#> yaml 2.3.8 2023-12-11 [1] CRAN (R 4.4.0)
#> zoo 1.8-12 2023-04-13 [1] CRAN (R 4.4.0)
#>
#> [1] C:/Users/Daniel/AppData/Local/R/win-library/4.4
#> [2] C:/Program Files/R/R-4.4.1/library
#>
#> D ── DLL MD5 mismatch, broken installation.
#>
#> ──────────────────────────────────────────────────────────────────────────────
Here's a reprex, including the data for plotting.
library(ggplot2)
load("positron_issue.RData")
axis_labels <- gsub(
"(high education|intermediate education|low education), (.*)",
"\\2",
levels(pr$x)
)
ggplot(
pr,
aes(
x = forcats::fct_reorder(x, predicted, .desc = TRUE),
y = predicted,
ymin = conf.low,
ymax = conf.high,
color = group
)) +
geom_pointrange(fatten = 2) +
coord_flip() +
scale_y_log10(
limits = c(0.045, 0.4),
labels = scales::percent,
breaks = c(0.05, 0.075, 0.1, 0.15, 0.2, 0.3, 0.4)
) +
scale_x_discrete(labels = axis_labels[order(pr$predicted, decreasing = TRUE)]) +
labs(x = NULL, y = NULL, color = "Education") +
theme(
legend.position = "bottom",
axis.text = element_text(color = "black")
)
Here is what you see in Positron:
This is when you change the scaling of the plot pane to "Landscape":
Portrait:
Square:
Positron version info:
Positron Version: 2024.06.1 (system setup) build 2024.06.1-27 Code - OSS Version: 1.90.0 Commit: a893e5b282612ccb2200102957ac38d3c14e5196 Date: 2024-06-26T01:33:58.809Z Electron: 29.4.0 Chromium: 122.0.6261.156 Node.js: 20.9.0 V8: 12.2.281.27-electron.0 OS: Windows_NT x64 10.0.22631
Looks like that it's not a general issue, but only for specific scaling, like auto or fill.
No, it happens on different computers, all 100% scaling and recommended resolution:
Not sure if this is helpful at all but I'm also experiencing the same issue on Windows 10.
I find that when I change the modes (Landscape/Auto/etc.) and play with the pane width I eventually find a resolution that looks nice. The resolution is definitely not as consistent as it is in RStudio. I'm enjoying the Positron experience a lot though and likely won't go back to RStudio despite this current issue.
Just wanted to add that this issue may have been resolved. I can't say I've experienced this in a while. Would be interested to hear if @strengejacke is still seeing this.
No, doesn't seem to be resolved.
Positron Version: 2024.09.0 (system setup) build 27 Code - OSS Version: 1.92.0 Commit: d996153f3be6bcc9af460300e61103425323b973 Date: 2024-09-11T02:38:49.688Z Electron: 30.1.2 Chromium: 124.0.6367.243 Node.js: 20.14.0 V8: 12.4.254.20-electron.0 OS: Windows_NT x64 10.0.22631
The next two are interesting, see the difference between "Fit" and "100%"
Here's a short update (not sure whether the behaviour has changed, but I'm now reporting results from the latest Positron version):
Positron Version: 2025.06.0 (system setup) build 167 Code - OSS Version: 1.100.0 Commit: e7e5d5590adc6bf7b760f837051cd2f57ea9e3dc Date: 2025-05-29T21:27:54.586Z Electron: 34.5.1 Chromium: 132.0.6834.210 Node.js: 20.19.0 V8: 13.2.152.41-electron.0 OS: Windows_NT x64 10.0.26100
Note Plots seem to be ok / not blurred, if you use the "copy" command. But the visual appearance is different, that's why I'm posting screenshots here.
Code:
m <- MASS::polr(Species ~ Sepal.Width, data = iris)
modelbased::estimate_means(m, by = "Sepal.Width", length = 100) |> plot()
Zoom: fit; Scale: auto
Zoom: fit; Scale: landscape
Zoom: 100%; Scale: landscape
It seems that "Fit" and scaling that doesn't use the full height (square, landscape) render differently from "100%" and square or landscape. Using "fit" makes the plot blurry.
In general, I'd like to have lager axis labels and titles, these are to small in comparison to the remaining plot area. A "scaling" option that re-scales text/labels while the plot dimensions are maintained, would be really cool.
I believe the improved behavior you are seeing (no distortion) is because of the work in https://github.com/posit-dev/ark/pull/763 and related. 🎉
Can you add your examples on scaling to https://github.com/posit-dev/positron/issues/3765, so we can consider them there? I think we can likely close out this issue on blurring and distortion in R plots.
