R 如何使用表示第四个变量的颜色和表示p值的符号创建三维曲面图？

您好，我一直在尝试创建一个3D曲面图，其颜色表示第四个变量。我在类似问题（，&）的线程中看到，persp函数可能适用于此问题

但是，我希望图例表示z_perc_diff的值，而不是z_abs。图例应以零为基础，以便正值以蓝色表示，负值以红色显示

# My data
my_predictions <- structure(list(x = c(15, 15, 15, 15, 15, 15, 15, 15, 15, 15, 
15, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 16, 17, 17, 17, 17, 
17, 17, 17, 17, 17, 17, 17, 18, 18, 18, 18, 18, 18, 18, 18, 18, 
18, 18, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 19, 20, 20, 20, 
20, 20, 20, 20, 20, 20, 20, 20, 21, 21, 21, 21, 21, 21, 21, 21, 
21, 21, 21, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 22, 23, 23, 
23, 23, 23, 23, 23, 23, 23, 23, 23, 24, 24, 24, 24, 24, 24, 24, 
24, 24, 24, 24, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 25, 26, 
26, 26, 26, 26, 26, 26, 26, 26, 26, 26, 27, 27, 27, 27, 27, 27, 
27, 27, 27, 27, 27, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 28, 
29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 29, 30, 30, 30, 30, 30, 
30, 30, 30, 30, 30, 30), y = c(0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 
10, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 0, 1, 2, 3, 4, 5, 6, 7, 
8, 9, 10, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 0, 1, 2, 3, 4, 5, 
6, 7, 8, 9, 10, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 0, 1, 2, 3, 
4, 5, 6, 7, 8, 9, 10, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 0, 1, 
2, 3, 4, 5, 6, 7, 8, 9, 10, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 
0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 0, 1, 2, 3, 4, 5, 6, 7, 8, 
9, 10, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 0, 1, 2, 3, 4, 5, 6, 
7, 8, 9, 10, 0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 0, 1, 2, 3, 4, 
5, 6, 7, 8, 9, 10), z_abs = c(5.89166468662797, 5.71620477294708, 
5.58788336363503, 5.53270398714009, 5.56546653858478, 5.68342133665583, 
5.87218359073286, 6.11616406250311, 6.39777721054453, 6.6948141489067, 
6.9860537204931, 5.39084997268418, 5.18447060891215, 5.06611974736902, 
5.05075093844761, 5.14083166394895, 5.32870615805878, 5.5985017027444, 
5.92779768435751, 6.29238950293484, 6.66793117670472, 7.03298204408324, 
4.95653965694727, 4.7201086564947, 4.61480313575268, 4.64210971213064, 
4.79047427954843, 5.04685231896118, 5.39548242946584, 5.80689146180237, 
6.24996353898745, 6.69863843503938, 7.13191977541987, 4.64349151345873, 
4.3813155170918, 4.29167517000888, 4.36216601705974, 4.56533037621608, 
4.88310350730247, 5.30286040109652, 5.78703626665416, 6.2985097044599, 
6.80988120783696, 7.30132906244365, 4.51154727409438, 4.23073821797019, 
4.15854107473001, 4.26878934910127, 4.51798461407076, 4.88613817165596, 
5.36094446401933, 5.90080872941022, 6.46448442210873, 7.02292641564077, 
7.55775948840835, 4.61292568988059, 4.32507754750285, 4.26865597663617, 
4.41008780184542, 4.6929100839265, 5.09614963145159, 5.60427338841452, 
6.17534998926212, 6.76908828925627, 7.35452667149962, 7.91346606720368, 
4.9753260711446, 4.69588399333344, 4.65475068309446, 4.81371724113417, 
5.11437712173564, 5.53272532866221, 6.0484175670245, 6.62476913845804, 
7.22335838291607, 7.81254366865306, 8.3738269431778, 5.60569497498954, 
5.34785911948806, 5.32333516039646, 5.48927127025166, 5.78797585594766, 
6.19531699139295, 6.69382015172285, 7.25054778841329, 7.82693134543372, 
8.39443251400023, 8.93623441442297, 6.49158407263714, 6.27115324385354, 
6.26151299468792, 6.422816894535, 6.7018558318732, 7.07402287605816, 
7.53213005441985, 8.04277431372036, 8.57058750914082, 9.09206029329992, 
9.59247435372804, 7.61240997323185, 7.44115030318242, 7.44379765058154, 
7.58744143657664, 7.82808733399817, 8.14750787068668, 8.53909801474392, 
8.97861443975292, 9.43532939424452, 9.88959953483834, 10.3284770236408, 
8.92394937199725, 8.81086054834368, 8.82321640103571, 8.93818150369879, 
9.12499157686584, 9.37318975819927, 9.68003486446225, 10.0269790914747, 
10.3929730388823, 10.7616293567185, 11.1226201190418, 10.3712483746667, 
10.3234108220576, 10.3435258045377, 10.4214375724401, 10.5426393201315, 
10.7059853803208, 10.9109947969652, 11.1497118719974, 11.4094098184639, 
11.6786118672507, 11.9490255615482, 11.8887255053356, 11.9086496168692, 
11.934785192405, 11.9700207074413, 12.0181188024101, 12.0864895097675, 
12.1807184656665, 12.3012160515108, 12.4446783000884, 12.6055375734207, 
12.7777833711724, 13.4042784224739, 13.4916045348718, 13.5217402312418, 
13.5110508490485, 13.4824532270308, 13.4527571217012, 13.4326577589613, 
13.431591868524, 13.4557730469364, 13.505528343313, 13.5772898734717, 
14.8446701299156, 14.9954392456614, 15.0273941315244, 14.9704701616451, 
14.8666619887902, 14.7414587466546, 14.6098827085824, 14.4908729477804, 
14.3994241171268, 14.3416767614794, 14.3162484009104, 16.1383527788051, 
16.3443675699097, 16.3768858295625, 16.2778130284893, 16.1045505862423, 
15.8917019503952, 15.6587768285966, 15.4317358581075, 15.2347126709423, 
15.0786301284417, 14.964770211412), z_perc_diff = c(0, -3.02312003579871, 
-5.29256590351525, -6.28412317106163, -5.69423779183659, -3.59813049429173, 
-0.331202773714748, 3.73921681538612, 8.23654203585939, 12.7620992776987, 
16.9966293603681, 0, -3.90303749526381, -6.21079020038523, -6.51430823934265, 
-4.74792758386405, -1.15944753434667, 3.77914432431019, 9.48784215116509, 
15.4330403332402, 21.1809334326506, 26.4351943777542, 0, -4.88663001473628, 
-7.14082712522282, -6.55154559201976, -3.40751287483119, 1.80564077127878, 
8.48032913482058, 15.8007571279721, 23.0834518034026, 29.8939881371674, 
35.9910231844426, 0, -5.81011860928264, -7.87486917509452, -6.24775027132952, 
-1.69752739664305, 5.03038059918695, 13.2585071049594, 21.9268818856078, 
30.250740390906, 37.8297248696042, 44.5019250326266, 0, -6.42415662080771, 
-8.14308194246352, -5.52958127714146, 0.142584135171283, 7.97198203161749, 
17.2073517498276, 26.6848627697371, 35.5854866689191, 43.5456217439958, 
50.4786608586009, 0, -6.4409943637927, -7.75244153960337, -4.49601207448427, 
1.71901580879046, 9.95406721192679, 19.4054689731923, 28.9652275460889, 
37.8871894434132, 45.817620974475, 52.6973839127532, 0, -5.77884413528626, 
-6.65779507746964, -3.30183093188919, 2.75629615525582, 10.6089937384178, 
19.4687309702012, 28.4384401594915, 36.8569630641303, 44.3735767604614, 
50.9171011582073, 0, -4.70780265980463, -5.16715227417771, -2.09867614131442, 
3.19968662712593, 9.99273652264851, 17.6937898042842, 25.5883906938357, 
33.0722573152648, 39.8387449143425, 45.8060185859283, 0, -3.45428763935744, 
-3.60808165631693, -1.06496891767484, 3.18751986984344, 8.58699217254015, 
14.8398059509087, 21.3451491954295, 27.6056267878243, 33.3744297495256, 
38.5585552960673, 0, -2.27533775272767, -2.23977148646158, -0.328536588707702, 
2.79365821546852, 6.79061785415733, 11.4749414383097, 16.4691996408832, 
21.3860545579483, 26.0220354760575, 30.2779572814035, 0, -1.27533166875238, 
-1.13520065400643, 0.159355362476933, 2.22774516730026, 4.91049866326503, 
8.12821041831724, 11.6409042607444, 15.2097071742408, 18.6703170889313, 
21.9356309120861, 0, -0.462317858481415, -0.267659882643973, 
0.482758195848795, 1.63901564324992, 3.17628973085539, 5.0722700417025, 
7.23446805726413, 9.53287485246492, 11.8582474286945, 14.13761490016, 
0, 0.167447976353206, 0.386674219881325, 0.681470865071801, 1.08247910438433, 
1.649737066444, 2.42625430552338, 3.41043028323062, 4.5694617916871, 
5.85289760120903, 7.20862340339978, 0, 0.649364161321318, 0.872478105868887, 
0.793394912598341, 0.581512141944205, 0.361013032488915, 0.211494607995026, 
0.203559234367959, 0.383429082563038, 0.752513176481438, 1.28244176987912, 
0, 1.01051315763124, 1.22337713262576, 0.843866777076174, 0.148036841880626, 
-0.697701167269985, -1.59423517729535, -2.41207180789635, -3.0450319919469, 
-3.44677167243881, -3.62417753368461, 0, 1.26845774548987, 1.46720775221974, 
0.860436428621641, -0.209672138889854, -1.5401211799062, -3.01647322339994, 
-4.47649627357374, -5.7606108609966, -6.78939828049445, -7.54639698246566
)), .Names = c("x", "y", "z_abs", "z_perc_diff"), row.names = c(81L, 
82L, 83L, 84L, 85L, 86L, 87L, 88L, 89L, 90L, 91L, 97L, 98L, 99L, 
100L, 101L, 102L, 103L, 104L, 105L, 106L, 107L, 113L, 114L, 115L, 
116L, 117L, 118L, 119L, 120L, 121L, 122L, 123L, 129L, 130L, 131L, 
132L, 133L, 134L, 135L, 136L, 137L, 138L, 139L, 145L, 146L, 147L, 
148L, 149L, 150L, 151L, 152L, 153L, 154L, 155L, 161L, 162L, 163L, 
164L, 165L, 166L, 167L, 168L, 169L, 170L, 171L, 177L, 178L, 179L, 
180L, 181L, 182L, 183L, 184L, 185L, 186L, 187L, 193L, 194L, 195L, 
196L, 197L, 198L, 199L, 200L, 201L, 202L, 203L, 209L, 210L, 211L, 
212L, 213L, 214L, 215L, 216L, 217L, 218L, 219L, 225L, 226L, 227L, 
228L, 229L, 230L, 231L, 232L, 233L, 234L, 235L, 241L, 242L, 243L, 
244L, 245L, 246L, 247L, 248L, 249L, 250L, 251L, 257L, 258L, 259L, 
260L, 261L, 262L, 263L, 264L, 265L, 266L, 267L, 273L, 274L, 275L, 
276L, 277L, 278L, 279L, 280L, 281L, 282L, 283L, 289L, 290L, 291L, 
292L, 293L, 294L, 295L, 296L, 297L, 298L, 299L, 305L, 306L, 307L, 
308L, 309L, 310L, 311L, 312L, 313L, 314L, 315L, 321L, 322L, 323L, 
324L, 325L, 326L, 327L, 328L, 329L, 330L, 331L), class = "data.frame")

#我的数据
我的预测
# Rearranging data
x = unique(my_predictions$x)
nx = length(x)
y =  unique(my_predictions$y)
ny = length(y)
zmat <- matrix(my_predictions$z_abs, nrow=nx, byrow=TRUE) 

# Create color variable
library(grDevices) # for the colorRampPalette function
colfunc = colorRampPalette(c("red","white","blue"))
class_borders = seq(-50, 50, 5)
cols = cut(unique(my_predictions$z_perc_diff), breaks = class_borders)
cols = colfunc(21)[as.numeric(cols)]

# plot using persp (base package)
persp(x, y, zmat, col = cols,
        ticktype = "detailed",
        theta=-35, phi=10)

# plot using persp3D (plot3D)
library(plot3D)
persp3D(x, y, zmat, col = cols,
      ticktype = "detailed",
      theta=-35, phi=10)

my_predictions$p_val = runif(nrow(my_predictions), min = 0, max = 1)
class_borders = c(-1,0.001,0.01,0.05,1)

my_predictions$p_cut = cut(my_predictions[,"p_val"], breaks = class_borders)
my_predictions$p_cut[my_predictions$p_val > 0.05 ] <- NA

persp4d <- function(data, x, y, z, color_var, colors = c("red","white","blue"), class_borders = seq(-100, 100, 2), ...){
      x  = sort(unique(data[,x]))
      nx = length(x)
      y  = sort(unique(data[,y]))
      ny = length(y)

      z  = matrix(data[,z], nrow = nx, byrow = FALSE) 
      z_col = matrix(data[,color_var], nrow = length(x), byrow = FALSE)

      ## Average the values at the corner of each facet
      hgt = 0.25 * (z_col[-nx,-ny] + z_col[-1,-ny] + z_col[-nx,-1] + z_col[-1,-1])

      require(grDevices)
      colfunc = colorRampPalette(colors)
      cols = cut(hgt, breaks = class_borders)
      cols = colfunc(length(class_borders))[as.numeric(cols)]
      persp(x, y, z, col = cols, ...)
    }