Question

我有一些看起来像这样的数据

         variable      value   rfvalue  stdfvalue mean_value                    model
1 Protocol Active  0.7975318  0.000000 0.00000000  0.8833071 2013-07-24 to 2019-07-22
2 Protocol Active  0.2716946  0.000000 0.00000000  0.3929385 2011-10-12 to 2017-10-10
3            Wind  0.7384344  1.806452 0.07128713  0.2818933 2010-01-01 to 2015-12-31
4 Protocol Active  1.2555754  0.000000 0.00000000  0.8833071 2013-07-24 to 2019-07-22
5 Protocol Active  0.8638037  0.000000 0.00000000  0.8833071 2013-07-24 to 2019-07-22
6            Wind -0.4009561 13.419355 0.54027120  0.4125869 2013-07-24 to 2019-07-22

我可以使用以下内容绘制数据：

d %>% 
  ggplot() +
  coord_flip() +
  ggforce::geom_sina(aes(
    x = variable,
    y = value,
    color = stdfvalue,
    alpha = value),
    method = "counts", maxwidth = 1, size = 1) +
  facet_wrap(~model) +
  scale_color_gradient(
    low = "darkblue",
    high = "darkred",
    breaks = c(0, 1),
    labels = c("     Low", "     High"), 
    guide = guide_colorbar(barwidth = 12, barheight = 0.3))

但是，在我的完整数据集上，绘图如下：

（我将darkblue更改为yellow的位置）。 Wind变量看起来不错，它是一个连续变量，但是Protocol Active变量“隐藏”了我要显示的某些数据。它是（0,1）的离散变量，我想更加强调1的值。我尝试添加scale_alpha_manual(values = c(1, 0.1), guide = FALSE)，这将返回错误。我也似乎无法使scale_alpha_manual既可以用于离散的也可以用于连续的。

一种尝试是创建两个geom_sina图，并根据两个变量对它们进行过滤-我希望将不同的alpha值应用于它们。我无法使它正常工作。

 ggplot() +
  coord_flip() +
  ggforce::geom_sina(aes(
    x = variable,
    y = value,
    color = stdfvalue),
    method = "counts", maxwidth = 1, size = 1, data = d %>% filter(variable == "Protocol Active")
  ) +
  ggforce::geom_sina(aes(
    x = variable,
    y = value,
    color = stdfvalue,
    alpha = 0.1),
    method = "counts", maxwidth = 1, size = 1, data = d %>% 
      filter(variable == "Wind")
  ) +
  facet_wrap(~model) +
  scale_color_gradient(
    low = "yellow",
    high = "blue1",
    breaks = c(0, 1),
    labels = c("     Low", "     High"), 
    guide = guide_colorbar(barwidth = 12, barheight = 0.3))

我的问题是，如何设置离散变量的alpha，以便可以更强调地显示某个类。知道是否可以在同一图上设置scale_alpha_continuous和scale_alpha_discrete会很有趣。我也乐意听到其他解决方法。

数据：

    d <- structure(list(variable = c("Wind", "Wind", "Wind", "Protocol Active", 
"Protocol Active", "Wind", "Wind", "Wind", "Protocol Active", 
"Protocol Active", "Wind", "Wind", "Wind", "Protocol Active", 
"Wind", "Wind", "Wind", "Wind", "Wind", "Protocol Active", "Protocol Active", 
"Wind", "Protocol Active", "Protocol Active", "Protocol Active", 
"Protocol Active", "Wind", "Protocol Active", "Wind", "Wind", 
"Protocol Active", "Protocol Active", "Wind", "Protocol Active", 
"Wind", "Protocol Active", "Wind", "Protocol Active", "Protocol Active", 
"Protocol Active", "Protocol Active", "Wind", "Protocol Active", 
"Protocol Active", "Wind", "Protocol Active", "Wind", "Wind", 
"Protocol Active", "Wind", "Protocol Active", "Wind", "Protocol Active", 
"Protocol Active", "Wind", "Wind", "Wind", "Protocol Active", 
"Wind", "Protocol Active", "Protocol Active", "Protocol Active", 
"Protocol Active", "Protocol Active", "Wind", "Protocol Active", 
"Protocol Active", "Wind", "Wind", "Wind", "Protocol Active", 
"Protocol Active", "Wind", "Protocol Active", "Protocol Active", 
"Wind", "Protocol Active", "Protocol Active", "Wind", "Wind", 
"Wind", "Wind", "Protocol Active", "Wind", "Protocol Active", 
"Wind", "Wind", "Protocol Active", "Protocol Active", "Wind", 
"Protocol Active", "Wind", "Protocol Active", "Wind", "Wind", 
"Protocol Active", "Protocol Active", "Wind", "Protocol Active", 
"Wind", "Protocol Active", "Protocol Active", "Protocol Active", 
"Wind", "Wind", "Wind", "Wind", "Wind", "Protocol Active", "Wind", 
"Protocol Active", "Protocol Active", "Protocol Active", "Wind", 
"Protocol Active", "Wind", "Wind", "Protocol Active", "Wind", 
"Wind", "Wind", "Wind", "Protocol Active", "Wind", "Protocol Active", 
"Protocol Active", "Protocol Active", "Protocol Active", "Wind", 
"Wind", "Protocol Active", "Wind", "Wind", "Protocol Active", 
"Protocol Active", "Wind", "Wind", "Wind", "Wind", "Protocol Active", 
"Wind", "Protocol Active", "Protocol Active", "Protocol Active", 
"Protocol Active", "Wind", "Wind", "Protocol Active", "Wind", 
"Wind", "Protocol Active", "Wind", "Wind", "Protocol Active", 
"Wind", "Protocol Active", "Wind", "Wind", "Protocol Active", 
"Wind", "Protocol Active", "Protocol Active", "Wind", "Wind", 
"Wind", "Wind", "Protocol Active", "Wind", "Protocol Active", 
"Protocol Active", "Protocol Active", "Protocol Active", "Wind", 
"Wind", "Wind", "Wind", "Wind", "Protocol Active", "Protocol Active", 
"Wind", "Wind", "Wind", "Protocol Active", "Wind", "Protocol Active", 
"Wind", "Protocol Active", "Wind", "Wind", "Wind", "Protocol Active", 
"Protocol Active", "Protocol Active", "Protocol Active", "Wind", 
"Wind", "Protocol Active", "Protocol Active", "Wind", "Protocol Active"
), value = c(-0.0989474654197693, 0.629822552204132, -0.0962040945887566, 
1.29249930381775, 0, 0.434465348720551, -0.28844028711319, 0.217110589146614, 
0, 0.315992414951324, 0.538330733776093, -0.096613846719265, 
0.845123291015625, 0, -0.398098558187485, -0.275375932455063, 
0.623717963695526, 0.767583787441254, -0.220980376005173, 0, 
0.856497704982758, -0.0572838261723518, 0, 0, 0.503492951393127, 
0.283374071121216, -0.0997775197029114, 0, -0.185573473572731, 
0.541458964347839, 0.828957080841064, 0.298303335905075, -0.0101631181314588, 
0, -0.15062090754509, 0.81750363111496, 0.598546028137207, 0, 
0.826459050178528, 0.250531941652298, 0, -0.297038346529007, 
0.415378659963608, 0, -0.242933213710785, 0.753650367259979, 
-0.161409094929695, -0.752240180969238, 0, 0.736700534820557, 
0, -0.0983792245388031, 1.13214647769928, 0.286624670028687, 
0.849360644817352, 0.906382441520691, 0.768399834632874, 0.542866706848145, 
-0.312404543161392, 0, 0.483780354261398, 0, 0.791863441467285, 
0.487868845462799, -0.336384683847427, 0.365867704153061, 0.458498805761337, 
-0.326053828001022, 0.786870658397675, 0.625235676765442, 1.05334162712097, 
1.27674341201782, -0.402126729488373, 1.35678279399872, 0, -0.0197668727487326, 
0.977747678756714, 0.666797459125519, -0.267341256141663, 0.655228078365326, 
0.0420738272368908, 0.430610090494156, 0, -0.122896425426006, 
0.267312049865723, -0.18688802421093, 0.650719821453094, 0, 0, 
0.00512066995725036, 0.715728044509888, 0.593662261962891, 0.810122668743134, 
0.635514199733734, 0.599373757839203, 0, 0, -0.549852848052979, 
1.05160856246948, -0.0583889335393906, 0.485096544027328, 0, 
1.2462295293808, -0.339758694171906, -0.306385368108749, -0.29257345199585, 
-0.198688685894012, -0.140972256660461, 0, -0.0293861590325832, 
0.26350411772728, 0, 0.714957416057587, -0.100245490670204, 0, 
-0.0799269378185272, -0.141207844018936, 0, -0.260594755411148, 
-0.495336472988129, 0.0901876837015152, -0.392557889223099, 0.269983738660812, 
-0.415697365999222, 0.537323653697968, 1.01686215400696, 0.707460880279541, 
0.279224544763565, 0.56487512588501, -0.134432524442673, 0.54803729057312, 
0.477457016706467, -0.189187243580818, 0.871891617774963, 0.69837349653244, 
-0.58046156167984, 0.443165421485901, -0.421287506818771, 1.06587362289429, 
0.272987455129623, 0.540521800518036, 0, 0, 0.536158978939056, 
0, 0.0309308655560017, 0.625024020671844, 0, -0.286852031946182, 
0.626144170761108, 0.507866978645325, 0.529027938842773, -0.101144313812256, 
0, 0.777739226818085, 0, -0.414799422025681, 1.35438084602356, 
0.860056400299072, 0.590310633182526, 0.667994678020477, 0.537133276462555, 
-0.0919286012649536, -0.29287400841713, 0.899238407611847, 0.0362688936293125, 
0, -0.550533652305603, 0, 0.5471071600914, 1.18974375724792, 
0.381776362657547, 0.682958662509918, -0.35002875328064, -0.254838764667511, 
0.856454491615295, 0.0177191141992807, 0.781686365604401, 0.759931743144989, 
1.08820796012878, 0.626882433891296, -0.242740288376808, 0.770202159881592, 
0.904597997665405, 0.892723023891449, -0.386538952589035, 0, 
-0.393929898738861, -0.103308126330376, -0.377305179834366, 0.483622252941132, 
0.743905782699585, 0.778063476085663, 0, -0.440237790346146, 
-0.12215880304575, 0.73518306016922, 0, -0.288508862257004, 1.30829179286957
), rfvalue = c(3.96153846153846, 2.03703703703704, 4.83870967741935, 
0, 0, 2.48387096774194, 12.4117647058824, 2.87096774193548, 0, 
0, 3.1875, 4.375, 3.11538461538462, 0, 11.3636363636364, 8.20833333333333, 
0.653846153846154, 0.935483870967742, 4.51612903225806, 0, 0, 
3.80645161290323, 0, 0, 0, 0, 4.16129032258065, 0, 6.0625, 2.83870967741935, 
0, 0, 3.7, 0, 7.58064516129032, 0, 1.96551724137931, 0, 0, 0, 
0, 11.8064516129032, 0, 0, 8.48387096774194, 0, 4.06451612903226, 
24.5, 0, 1.23076923076923, 0, 7.55555555555556, 0, 0, 0.612903225806452, 
0.566666666666667, 2.07142857142857, 0, 10.3548387096774, 0, 
0, 0, 0, 0, 5.55555555555556, 0, 0, 10.6363636363636, 2.2, 2.87096774193548, 
0, 0, 12.9259259259259, 0, 0, 3.73076923076923, 0, 0, 8.83870967741935, 
1.07407407407407, 3.32258064516129, 2.7037037037037, 0, 4.66666666666667, 
0, 6.59375, 1.48148148148148, 0, 0, 3.57575757575758, 0, 0.259259259259259, 
0, 1.96296296296296, 1.88888888888889, 0, 0, 13.6818181818182, 
0, 4.24, 0, 0, 1, 11.3214285714286, 10.741935483871, 5.54838709677419, 
3.94117647058824, 6.44117647058824, 0, 7.16129032258065, 0, 0, 
0, 3.96774193548387, 0, 4.48387096774194, 4.16129032258065, 0, 
5.12121212121212, 15.7741935483871, 3.78787878787879, 7, 0, 7.52, 
0, 0, 1, 0, 2.51612903225806, 5.24242424242424, 0, 2.21875, 5.16129032258065, 
0, 0, 15.962962962963, 1.96875, 11.8666666666667, 0.407407407407407, 
0, 1.87096774193548, 0, 0, 0, 0, 3.42424242424242, 2.2, 0, 6.87096774193548, 
2.41666666666667, 0, 1.74193548387097, 8.04761904761905, 0, 2.16129032258065, 
0, 13.4516129032258, 0.555555555555556, 0, 2.14285714285714, 
0, 0, 4.32352941176471, 4.56521739130435, 1.88888888888889, 3.64705882352941, 
0, 20.2222222222222, 0, 0, 0, 0, 2.38709677419355, 11.6774193548387, 
9.41935483870968, 0.407407407407407, 3.09677419354839, 0, 0, 
0.807692307692308, 2.72, 6.09677419354839, 0, 0.833333333333333, 
0, 9.125, 0, 14, 4.70588235294118, 6.43333333333333, 0, 0, 0, 
0, 13.0645161290323, 5.61290322580645, 0, 0, 11.8076923076923, 
0), stdfvalue = c(0.157298598329322, 0.0798326069229873, 0.195379537953795, 
0, 1, 0.099009900990099, 0.505299941758882, 0.113583763574862, 
1, 0, 0.125955684553306, 0.174040775874274, 0.123035537307093, 
1, 0.457029590825428, 0.329599628113069, 0.0233611779697013, 
0.035250133523233, 0.180167349118747, 1, 0, 0.151018711778327, 
1, 1, 0, 0, 0.167656765676568, 1, 0.242752655628746, 0.111832219700118, 
0, 0, 0.148778877887789, 1, 0.304195596700493, 0, 0.0769380308955367, 
1, 0, 0, 1, 0.480528052805281, 0, 1, 0.340751290724586, 0, 0.1618895021067, 
0.988956534050687, 1, 0.0467223559394025, 1, 0.306563989732307, 
0, 0, 0.0221945285146282, 0.0205500550055006, 0.0807629295523958, 
0, 0.416180641507538, 1, 0, 1, 0, 0, 0.221844667830793, 0, 0, 
0.427867782327458, 0.0859691349285006, 0.113138436102725, 0, 
0, 0.520531807102337, 0, 1, 0.15003808073115, 0, 0, 0.355112456234051, 
0.0403773446389898, 0.133333333333333, 0.108006356191175, 1, 
0.188338833883388, 0, 0.264253605127292, 0.0573479538526123, 
1, 1, 0.141677285383926, 0, 0.00738328587684385, 0, 0.0768346531802707, 
0.073836699437554, 1, 1, 0.550899051394591, 0, 0.168574260229364, 
0, 1, 1, 0.460678925035361, 0.43214052578482, 0.221554397519102, 
0.156897653132822, 0.258078591949509, 1, 0.29042904290429, 0, 
1, 0, 0.15973597359736, 1, 0.180858085808581, 0.167656765676568, 
1, 0.204256925763368, 0.635807963919055, 0.152375237523752, 0.280334135636415, 
0, 0.301390344046439, 0, 0, 1, 0, 0.0992225980653967, 0.211901190119012, 
0, 0.0881600660066007, 0.206278559135956, 0, 0, 0.643268782020021, 
0.0779290429042904, 0.482992299229923, 0.0138776245832207, 0, 
0.0731113880481871, 1, 1, 0, 1, 0.137493749374937, 0.086428105156964, 
1, 0.275109270025987, 0.094742555099344, 0, 0.0686468646864686, 
0.326701241552727, 1, 0.0844016752453723, 1, 0.541577416157806, 
0.019873532068654, 0, 0.0850542197076851, 0, 0, 0.171956592349527, 
0.181743193248343, 0.0746607994132747, 0.144564466024269, 1, 
0.824935826916025, 1, 0, 0, 0, 0.093545190063621, 0.469735514014423, 
0.382838283828383, 0.0138776245832207, 0.124092409240924, 0, 
0, 0.0304138106118304, 0.107473740430835, 0.24413981366091, 0, 
0.0314631463146315, 0, 0.366699305679188, 1, 0.57029702970297, 
0.189943700252378, 0.257388267497286, 0, 0, 0, 1, 0.526140881846775, 
0.227062706270627, 0, 1, 0.475010618717259, 0), mean_value = c(0.412586940491501, 
0.357086707604185, 0.281893344972611, 0.88330711205256, 0, 0.281893344972611, 
0.281893344972611, 0.357086707604185, 0, 0.392938510590492, 0.412586940491501, 
0.412586940491501, 0.412586940491501, 0, 0.412586940491501, 0.357086707604185, 
0.412586940491501, 0.357086707604185, 0.357086707604185, 0, 0.88330711205256, 
0.412586940491501, 0, 0, 0.392938510590492, 0.392938510590492, 
0.281893344972611, 0, 0.357086707604185, 0.412586940491501, 0.88330711205256, 
0.392938510590492, 0.281893344972611, 0, 0.357086707604185, 0.88330711205256, 
0.357086707604185, 0, 0.88330711205256, 0.392938510590492, 0, 
0.281893344972611, 0.392938510590492, 0, 0.357086707604185, 0.88330711205256, 
0.357086707604185, 0.412586940491501, 0, 0.412586940491501, 0, 
0.281893344972611, 0.88330711205256, 0.392938510590492, 0.357086707604185, 
0.281893344972611, 0.412586940491501, 0.392938510590492, 0.412586940491501, 
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0.412586940491501, 0.392938510590492, 0.392938510590492, 0.357086707604185, 
0.412586940491501, 0.412586940491501, 0.88330711205256, 0.88330711205256, 
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0.281893344972611, 0, 0.281893344972611, 0.392938510590492, 0.357086707604185, 
0.357086707604185, 0, 0, 0.412586940491501, 0.88330711205256, 
0.412586940491501, 0.88330711205256, 0.357086707604185, 0.357086707604185, 
0, 0, 0.412586940491501, 0.88330711205256, 0.412586940491501, 
0.392938510590492, 0, 0.88330711205256, 0.281893344972611, 0.357086707604185, 
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0.392938510590492, 0, 0.88330711205256, 0.281893344972611, 0, 
0.281893344972611, 0.281893344972611, 0, 0.412586940491501, 0.357086707604185, 
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0.281893344972611, 0.281893344972611, 0, 0.412586940491501, 0, 
0.412586940491501, 0.357086707604185, 0.88330711205256, 0.281893344972611, 
0.88330711205256, 0.392938510590492, 0.412586940491501, 0.412586940491501, 
0.281893344972611, 0.412586940491501, 0, 0.281893344972611, 0, 
0.392938510590492, 0.88330711205256, 0.392938510590492, 0.412586940491501, 
0.412586940491501, 0.281893344972611, 0.357086707604185, 0.281893344972611, 
0.88330711205256, 0.88330711205256, 0.281893344972611, 0.357086707604185, 
0.357086707604185, 0.88330711205256, 0.281893344972611, 0.88330711205256, 
0.357086707604185, 0, 0.281893344972611, 0.281893344972611, 0.412586940491501, 
0.392938510590492, 0.88330711205256, 0.88330711205256, 0, 0.357086707604185, 
0.281893344972611, 0.88330711205256, 0, 0.412586940491501, 0.88330711205256
), model = c("2013-07-24 to 2019-07-22", "2011-10-12 to 2017-10-10", 
"2010-01-01 to 2015-12-31", "2013-07-24 to 2019-07-22", "2010-01-01 to 2015-12-31", 
"2010-01-01 to 2015-12-31", "2010-01-01 to 2015-12-31", "2011-10-12 to 2017-10-10", 
"2010-01-01 to 2015-12-31", "2011-10-12 to 2017-10-10", "2013-07-24 to 2019-07-22", 
"2013-07-24 to 2019-07-22", "2013-07-24 to 2019-07-22", "2010-01-01 to 2015-12-31", 
"2013-07-24 to 2019-07-22", "2011-10-12 to 2017-10-10", "2013-07-24 to 2019-07-22", 
"2011-10-12 to 2017-10-10", "2011-10-12 to 2017-10-10", "2010-01-01 to 2015-12-31", 
"2013-07-24 to 2019-07-22", "2013-07-24 to 2019-07-22", "2010-01-01 to 2015-12-31", 
"2010-01-01 to 2015-12-31", "2011-10-12 to 2017-10-10", "2011-10-12 to 2017-10-10", 
"2010-01-01 to 2015-12-31", "2010-01-01 to 2015-12-31", "2011-10-12 to 2017-10-10", 
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)), row.names = c(NA, -200L), class = "data.frame")

Answer 1

如果我理解的正确，那么您想要实现的目标可以通过scale_alpha_identity完成。作为示例，我向您的数据集中添加了一个变量alpha，该变量定义了value到特定alpha级别的映射（或中断）。然后，将这个新变量映射到ggplot内部的alpha美观度上。默认情况下，不会显示图例，因此您必须通过指定所需的中断和标签来手动设置它。

关于第二个问题。据我所知，不可能将scale_xxx_discrete和scale_xxx_continuous混合使用。您可以将不同的变量映射到相同的比例，但是每种美学仅具有比例，它可以是离散的也可以是连续的。如果要对比例尺进行更多控制，则必须绘制两个图并将其粘在一起，例如由patchwork。

# Packages ----------------------------------------------------------------
library(ggplot2)
library(ggforce)
library(dplyr)
# Data --------------------------------------------------------------------


d <- structure(list(variable = c(
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  "2013-07-24 to 2019-07-22", "2013-07-24 to 2019-07-22", "2010-01-01 to 2015-12-31",
  "2011-10-12 to 2017-10-10", "2010-01-01 to 2015-12-31", "2013-07-24 to 2019-07-22",
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)), row.names = c(NA, -200L), class = "data.frame")



# Plot --------------------------------------------------------------------

d %>%
  mutate(alpha = case_when(
    variable == "Wind" ~ ifelse(value > 1, 1, 0.5),
    TRUE ~ ifelse(value > 0, 1, .2)
  )) %>%
  ggplot() +
  coord_flip() +
  ggforce::geom_sina(aes(
    x = variable,
    y = value,
    color = stdfvalue,
    alpha = alpha
  ),
  method = "counts", maxwidth = 1, size = 1
  ) +
  facet_wrap(~model) +
  scale_color_gradient(
    low = "yellow",
    high = "darkred",
    breaks = c(0, 1),
    labels = c("     Low", "     High"),
    guide = guide_colorbar(barwidth = 12, barheight = 0.3)
  ) +
  scale_alpha_identity(breaks = c(.2, .5, 1), labels = c("One", "Two", "Three"), guide = "legend") +
  theme(legend.position = "bottom")

^{由reprex package（v0.3.0）于2020-03-15创建}

ggplot scale_alpha_manual用于数据中的离散变量和连续变量

1 个答案: