我有以下数据:
simres_auc2 <- structure(list(MINDGDP = c(1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L, 3L,
3L, 3L, 3L, 3L, 3L, 3L, 3L), PSIZE = c(5L, 5L, 5L, 5L, 10L, 10L,
10L, 10L, 20L, 20L, 20L, 20L, 50L, 50L, 50L, 50L, 5L, 5L, 5L,
5L, 10L, 10L, 10L, 10L, 20L, 20L, 20L, 20L, 50L, 50L, 50L, 50L,
5L, 5L, 5L, 5L, 10L, 10L, 10L, 10L, 20L, 20L, 20L, 20L, 50L,
50L, 50L, 50L), simno = c(13L, 13L, 13L, 13L, 16L, 16L, 16L,
16L, 19L, 19L, 19L, 19L, 22L, 22L, 22L, 22L, 13L, 13L, 13L, 13L,
16L, 16L, 16L, 16L, 19L, 19L, 19L, 19L, 22L, 22L, 22L, 22L, 13L,
13L, 13L, 13L, 16L, 16L, 16L, 16L, 19L, 19L, 19L, 19L, 22L, 22L,
22L, 22L), METHOD_RED = c("EVA (alpha = 0.001)", "EVA (alpha = 0.005)",
"EVA (alpha = 0.01)", "EVA (alpha = 0.05)", "EVA (alpha = 0.001)",
"EVA (alpha = 0.005)", "EVA (alpha = 0.01)", "EVA (alpha = 0.05)",
"EVA (alpha = 0.001)", "EVA (alpha = 0.005)", "EVA (alpha = 0.01)",
"EVA (alpha = 0.05)", "EVA (alpha = 0.001)", "EVA (alpha = 0.005)",
"EVA (alpha = 0.01)", "EVA (alpha = 0.05)", "EVA (alpha = 0.001)",
"EVA (alpha = 0.005)", "EVA (alpha = 0.01)", "EVA (alpha = 0.05)",
"EVA (alpha = 0.001)", "EVA (alpha = 0.005)", "EVA (alpha = 0.01)",
"EVA (alpha = 0.05)", "EVA (alpha = 0.001)", "EVA (alpha = 0.005)",
"EVA (alpha = 0.01)", "EVA (alpha = 0.05)", "EVA (alpha = 0.001)",
"EVA (alpha = 0.005)", "EVA (alpha = 0.01)", "EVA (alpha = 0.05)",
"EVA (alpha = 0.001)", "EVA (alpha = 0.005)", "EVA (alpha = 0.01)",
"EVA (alpha = 0.05)", "EVA (alpha = 0.001)", "EVA (alpha = 0.005)",
"EVA (alpha = 0.01)", "EVA (alpha = 0.05)", "EVA (alpha = 0.001)",
"EVA (alpha = 0.005)", "EVA (alpha = 0.01)", "EVA (alpha = 0.05)",
"EVA (alpha = 0.001)", "EVA (alpha = 0.005)", "EVA (alpha = 0.01)",
"EVA (alpha = 0.05)"), auc = c(0.5, 0.440423333333333, 0.73412,
0.570526, 0.5, 0.465404, 0.695695333333333, 0.536143333333333,
0.5, 0.482674, 0.673217333333333, 0.517231333333333, 0.5, 0.478126666666667,
0.661129333333333, 0.530846, 0.5, 0.4520975, 0.742583, 0.577082,
0.5, 0.4546035, 0.694907, 0.550087, 0.5, 0.4706495, 0.6585825,
0.544709, 0.5, 0.473219, 0.659395, 0.546985, 0.5, 0.45364, 0.754459333333333,
0.58385, 0.5, 0.442713333333333, 0.699316, 0.563635333333333,
0.5, 0.486780666666667, 0.678044666666667, 0.554051333333333,
0.5, 0.462297333333333, 0.651185333333333, 0.544234666666667)), class = c("tbl_df",
"tbl", "data.frame"), row.names = c(NA, -48L), .Names = c("MINDGDP",
"PSIZE", "simno", "METHOD_RED", "auc"))
以下代码生成以下图表,其中position_dodge
正常工作。
ggplot2::ggplot(data = simres_auc2,
aes_string(x = "factor(METHOD_RED)",
y = "auc")) +
ggplot2::geom_point(aes_string(shape = "factor(MINDGDP)",
group = "factor(MINDGDP)",
colour = paste0("factor(PSIZE)")),
position = position_dodge(width = 0.25))
但是,我想在y轴上factor(METHOD_RED)
,在x轴上想auc
。因此,在以下代码中,我互换了x
和y
,并将width
中的position_dodge
替换为height
。
ggplot2::ggplot(data = simres_auc2,
aes_string(y = "factor(METHOD_RED)",
x = "auc")) +
ggplot2::geom_point(aes_string(shape = "factor(MINDGDP)",
group = "factor(MINDGDP)",
colour = paste0("factor(PSIZE)")),
position = position_dodge(height = 0.25))
但是,此代码给出了以下图表,其中position_dodge
无法正常工作。
有谁知道为什么会这样,我怎么能绕过这个问题?请注意,使用coord_flip
对我来说不是一个选项,因为它会对我想在代码中使用的分面产生负面影响。例如,请参阅this question和this Github issue。
答案 0 :(得分:0)
您问题的可能解决方案可能是使用position_jitter
并使用width
0
和height
0.25
:
ggplot(data = simres_auc2, aes(y = factor(METHOD_RED), x = auc)) +
geom_point(aes(shape = factor(MINDGDP), group = factor(MINDGDP), colour = factor(PSIZE)),
position = position_jitter(width = 0, height = 0.25))
给出:
答案 1 :(得分:0)
您可以使用连续y比例并手动将y位置映射到不同的数据组。
RANGE <- .5
ggplot(data = simres_auc2, aes(y = as.integer(factor(METHOD_RED)), x = auc)) +
geom_point(aes(y = as.integer(factor(METHOD_RED)) +
RANGE *(-.5+(as.integer(factor(MINDGDP))-1)/(length(unique(MINDGDP))-1)),
shape = factor(MINDGDP), group = factor(MINDGDP),
colour = factor(PSIZE, levels = sort(unique(PSIZE))) ), size = 4 ) +
scale_y_continuous(labels = function(x) levels(factor(simres_auc2$METHOD_RED))[x]) +
guides(color = guide_legend(title = "PSIZE"), shape = guide_legend(title = "MINDGDP"))
答案 2 :(得分:0)