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erocoar
the "nudge" parameter spoils the shape of the geom_half_violin
I wanted to separate the violin plot a bit from the vertical grid, where I draw some data points. Using the nudge parameter distorted the shape of the violin:
I expected this:
PS: My intention was to put both boxplot and the violin on a spaghetti plot for a longitudinal experiment. Unfortunatelty, the violin plot overlaps the data points, that's why I wanted to "nudge" it a bit.
ggplot(data, aes(x = time, y = value)) +
geom_half_boxplot(nudge = 0.1, width=0.4)+
geom_half_violin(nudge = 0.1, side = "r", trim = FALSE)
data <- structure(list(ID = c("9891AA2", "9891AA2", "9891AA3", "9891AA3",
"9891AA3", "9891A11", "9891A11", "9891A11", "9891A13", "9891A13",
"9891A13", "9891A16", "9891A16", "9891A16", "9891A18", "9891A18",
"9891A18", "9891A19", "9891A19", "9891A19", "9891A21", "9891A21",
"9891A21", "9891A22", "9891A22", "9891A22", "9891A23", "9891A23",
"9891A23", "9891A25", "9891A25", "9891A25", "9891A25", "9891A25",
"9891A25", "9891A28", "9891A28", "9891A28", "9892AA1", "9892AA1",
"9892AA2", "9892AA2", "9892AA5", "9892AA5", "9892AA6", "9892AA6",
"9892AA9", "9892AA9", "9892A1A", "9892A1A", "9892A12", "9892A12",
"9892A15", "9892A15", "9892A16", "9892A16", "9892A17", "9892A17",
"9892A2A", "9892A2A", "9892A22", "9892A22", "9892A25", "9892A25",
"9892A3A", "9892A3A", "9892A33", "9892A33", "9892A4A", "9892A4A",
"9892A45", "9892A45", "9892A48", "9892A48", "9892A49", "9892A49",
"9892A5A", "9892A5A", "9892A51", "9892A51", "9897AA1", "9897AA1",
"9897AA4", "9897AA4", "9897AA4", "9897AA4", "989AAA2", "989AAA2",
"989AAA2", "989AAA2", "989AAA4", "989AAA4", "989AAA5", "989AAA5",
"989AAA5", "989AAA5", "989AAA5", "989AAA7", "989AAA7", "989AAA7",
"989AAA7", "989AAA7", "989AAA8", "989AAA8", "989AA24", "989AA24",
"989AA24", "989AA24", "989AA24", "989AA24", "989AA31", "989AA31",
"989AA31", "989AA31", "989AA31", "989AA37", "989AA37", "989AA37",
"989AA37", "989AA37", "989AA37", "989AA38", "989AA38", "989AA38",
"989AA38", "989AA38", "989AA38", "989AA39", "989AA39", "989AA39",
"989AA41", "989AA41", "989AA41", "989AA41", "989AA41", "989AA41",
"989AA43", "989AA43", "989AA43", "989AA43", "989AA45", "989AA45",
"989AA45", "989AA45", "989AA45", "989AA45", "989AA47", "989AA47",
"989AA47", "989AA47", "989AA47", "989AA47", "989AA5A", "989AA5A",
"989AA5A", "989AA5A", "9899AA1", "9899AA1", "9899AA3", "9899AA3",
"9899AA5", "9899AA5", "9899AA7", "9899AA7", "9899A1A", "9899A1A",
"9899A11", "9899A11", "9899A17", "9899A17", "9899A22", "9899A22",
"9891A1A", "9891A1A", "9891A18", "9891A18", "9892AA2", "9892AA2",
"9892AA3", "9892AA3", "9892AA8", "9892AA8", "9892AA9", "9892AA9",
"9892A1A", "9892A1A", "9892A11", "9892A11", "9892A17", "9892A17",
"9892A19", "9892A19", "9892A2A", "9892A2A", "9892A21", "9892A21",
"9892A22", "9892A22", "9892A26", "9892A26", "9896AA1", "9896AA1",
"9896AA2", "9896AA2", "9896AA2", "9896AA2", "9896AA5", "9896AA5",
"9896AA7", "9896AA7", "9896AA8", "9896AA8", "9896AA9", "9896AA9",
"9896A1A", "9896A1A", "9896A11", "9896A11", "9896A12", "9896A12",
"9896A13", "9896A13", "9896A14", "9896A14", "9896A15", "9896A15",
"9896A16", "9896A16", "9896A18", "9896A18", "9896A19", "9896A19",
"9896A24", "9896A24", "9896A24", "9896A26", "9896A26", "9896A32",
"9896A32", "9896A34", "9896A34", "9896A35", "9896A35", "9896A37",
"9896A37", "9896A37", "9896A39", "9896A39", "9897AA3", "9897AA3",
"9897AA3", "9897AA3", "9897AA3", "9897AA3", "9897AA4", "9897AA4",
"9897AA4", "9897AA4", "9897AA4", "9897AA4", "9897AA5", "9897AA5",
"9897AA5", "9897AA5", "9897AA5", "9897AA5", "9897AA6", "9897AA6",
"9897AA6", "9897AA6", "9897AA6", "9897AA6", "9897AA7", "9897AA7",
"9897AA7", "9897A1A", "9897A1A", "9897A1A", "9897A1A", "9897A1A",
"9897A1A", "9897A11", "9897A11", "9897A11", "9897A11", "9897A11",
"9897A11", "9897A13", "9897A13", "9897A13", "9897A13", "9897A13",
"9897A13", "9897A14", "9897A14", "9897A14", "9897A14", "9897A14",
"9897A14", "9897A16", "9897A16", "9897A16", "9897A16", "9897A16",
"9897A16", "9897A17", "9897A17", "9897A17", "9897A17", "9897A17",
"9897A17", "9899AA2", "9899AA2", "9899AA5", "9899AA5", "9899AA8",
"9899AA8", "9899AA9", "9899AA9", "9899AA9", "9899AA9", "9899A15",
"9899A15", "9899A15", "9899A15", "9899A17", "9899A17", "9899A22",
"9899A22", "9899A22", "9899A22", "9899A23", "9899A23", "9899A23",
"9899A23", "9899A24", "9899A24", "9899A25", "9899A25", "9899A26",
"9899A26", "9899A26", "9899A26", "9899A27", "9899A27", "9899A27",
"9899A27", "9899A29", "9899A29", "9899A3A", "9899A3A", "9899A3A",
"9899A3A", "9899A31", "9899A31", "9899A31", "9899A31", "9899A32",
"9899A32", "9899A38", "9899A38", "9899A38", "9899A38", "9899A4A",
"9899A4A", "9899A4A", "9899A4A", "9899A42", "9899A42", "9899A44",
"9899A44", "9899A44", "9899A44", "9899A48", "9899A48", "9899A49",
"9899A49", "989AA12", "989AA12", "989AA22", "989AA22", "989AA22",
"989AA22", "989AA23", "989AA23", "989AA23", "9894AA2", "9894AA2",
"9894AA3", "9894AA3", "9894AA4", "9894AA4", "9894AA6", "9894AA6",
"9894AA7", "9894AA7", "9894A14", "9894A14", "9894A15", "9894A15",
"9894A16", "9894A16", "9894A17", "9894A17", "9894A18", "9894A18",
"9894A21", "9894A21", "9894A22", "9894A22", "9894A23", "9894A23",
"9894A25", "9894A25", "9897AA3", "9897AA3"), value = c(8.22,
8.42, 7.82, 8.02, 8.22, 8.62, 8.62, 8.52, 8.62, 9.02, 9.52, 7.82,
7.92, 7.82, 8.22, 8.42, 8.72, 8.72, 9.22, 9.22, 7.22, 7.42, 7.22,
8.02, 8.32, 8.32, 7.82, 9.32, 9.12, 8.62, 8.62, 8.42, 8.42, 9.02,
8.92, 7.92, 7.82, 8.42, 8.12, 8.32, 8.42, 8.62, 7.32, 7.52, 7.62,
7.62, 9.92, 12.02, 7.62, 7.92, 7.72, 8.22, 8.12, 8.32, 8.82,
9.32, 8.62, 8.72, 8.62, 8.62, 8.02, 7.92, 9.82, 9.82, 8.52, 8.92,
7.92, 8.42, 7.52, 7.92, 8.52, 8.32, 8.62, 8.62, 8.02, 8.02, 8.32,
8.82, 8.32, 8.42, 8.52, 8.32, 9.12, 9.32, 8.82, 11.82, 8.82,
9.12, 7.42, 7.42, 7.52, 8.32, 8.82, 8.92, 8.92, 8.52, 9.32, 8.92,
8.82, 8.22, 8.32, 8.52, 8.52, 8.42, 9.32, 9.22, 9.12, 8.72, 9.42,
8.92, 9.02, 9.42, 9.62, 8.02, 8.42, 9.92, 10.02, 10.22, 8.62,
8.52, 8.52, 9.02, 9.22, 9.02, 8.02, 7.92, 7.72, 8.72, 9.12, 9.02,
7.42, 7.72, 7.62, 7.32, 7.22, 8.22, 9.32, 9.22, 8.22, 9.12, 9.42,
9.52, 9.32, 8.92, 8.62, 8.82, 9.52, 9.62, 9.82, 8.02, 7.92, 8.82,
9.02, 9.62, 7.22, 7.22, 7.92, 7.42, 8.12, 8.62, 8.62, 8.32, 8.22,
8.22, 7.42, 7.52, 8.52, 7.72, 6.82, 7.02, 7.32, 7.92, 8.72, 9.32,
8.62, 9.72, 7.32, 7.72, 7.82, 8.52, 7.22, 7.62, 8.12, 10.52,
7.02, 7.32, 7.12, 7.12, 6.82, 6.62, 7.42, 7.62, 8.42, 9.52, 7.62,
8.12, 7.32, 7.42, 7.82, 7.82, 8.08, 7.87, 8.84, 8.54, 8.81, 8.85,
6.24, 6.84, 8.23, 8.28, 8.03, 8.34, 8.95, 9.42, 8.32, 8.37, 8.78,
9.3, 8.65, 8.53, 7.86, 7.91, 8.04, 8.17, 8.68, 9.03, 7.51, 7.66,
8.15, 8.59, 8.61, 7.95, 8.34, 8.46, 9.52, 7.83, 8.52, 8.76, 9.16,
8.4, 8.78, 8.69, 9.32, 7.76, 8.62, 8.72, 7.54, 7.8, 8.76, 8.85,
8.88, 9.35, 9.23, 9.48, 7.71, 8.15, 7.95, 9.14, 9, 9.06, 8.57,
8.57, 8.5, 9.18, 9.54, 9.45, 8.01, 8.34, 8.21, 8.91, 9.08, 9.24,
8.61, 8.63, 8.67, 8.17, 8.38, 8.22, 9.22, 9.37, 9.54, 8.46, 8.68,
8.64, 10.33, 10.53, 10.71, 7.75, 8.08, 7.87, 10.1, 10.6, 10.72,
8.24, 8.51, 8.71, 8.97, 9.25, 9.3, 8.92, 8.28, 8.11, 6.72, 7.97,
8.03, 8.76, 9.05, 9.18, 8.67, 9.06, 8.59, 7.02, 7.72, 8.62, 9.02,
8.62, 9.12, 8.82, 9.02, 9.02, 9.22, 7.82, 7.82, 7.52, 7.52, 8.82,
9.22, 8.22, 7.92, 7.52, 7.92, 8.62, 8.82, 9.42, 9.52, 8.12, 8.52,
8.72, 9.22, 8.42, 8.42, 8.92, 9.42, 8.42, 8.72, 9.22, 9.42, 8.42,
9.02, 8.92, 8.92, 9.22, 9.32, 8.22, 8.12, 7.82, 7.92, 8.22, 8.82,
8.52, 8.72, 9.92, 9.82, 8.32, 9.12, 8.72, 8.92, 9.12, 9.42, 8.52,
9.32, 8.32, 8.42, 8.22, 8.52, 9.52, 9.92, 7.92, 8.22, 9.32, 10.42,
8.22, 9.82, 8.42, 8.52, 8.22, 8.72, 9.12, 7.52, 7.82, 8.02, 8.32,
8.52, 8.22, 8.62, 9.62, 8.52, 8.72, 8.82, 8.82, 8.62, 8.62, 8.92,
9.42, 8.32, 8.42, 8.72, 9.02, 8.62, 8.62, 8.32, 8.42, 8.72, 9.12,
8.42, 8.52), time = structure(c(1L, 3L, 1L, 2L, 3L, 1L, 2L, 3L,
1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L,
2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 3L,
1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L,
1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L,
1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L,
1L, 3L, 1L, 3L, 1L, 2L, 3L, 1L, 3L, 1L, 3L, 1L, 2L, 3L, 1L, 3L,
1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 3L, 1L, 2L, 3L, 1L, 2L,
3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L,
1L, 3L, 1L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L,
1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L,
1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L,
1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L,
1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L,
1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L,
1L, 2L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 2L, 3L, 1L, 3L,
1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L,
2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L,
3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L,
1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L, 2L, 3L, 1L,
3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L,
3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L,
3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L,
3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L,
3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 2L, 3L, 1L, 3L, 1L, 3L, 1L, 3L,
1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L,
1L, 3L, 1L, 3L, 1L, 3L, 1L, 3L), .Label = c("Baseline", "Visit 2",
"Visit 3"), class = "factor")), row.names = c(NA, 416L), class = "data.frame")
Hi, thanks for pointing this out! The nudge parameter wasn't added to both xmaxv and xminv. I've fixed this in b34a203
Running the same example now, I get:
Thank you for a quick reaction!
By the way, do you plan to release it to the CRAN in, say, the next month or two? (I am asking because of working in a controlled environment, where CRAN is a preferred source of packages).