내가 윤곽 플롯 만들기 위해 노력하고 그 다음과 같이 보입니다 (또는 레벨 플롯을, 나는 특히 어느 하나를 걱정하지 않는다) :격자에서 등고선에 색상을 어떻게 추가합니까?
contourplot(z~x*y, data=df1, xlim=c(0,100), ylim=c(0,50),
scales=list(x=list(at=c(0,20,40,60,80,100)),
y=list(at=c(0,10,20,30,40,50))),
at=seq(0,5000,by=500))
:
이 코드를
contourplot(z~x*y, data=df1, xlim=c(0,100), ylim=c(0,50),
scales=list(x=list(at=c(0,20,40,60,80,100)),
y=list(at=c(0,10,20,30,40,50))),
at=seq(0,5000,by=500), region=T,
colorkey=list(at=seq(0,5000,by=10)), col.regions=rainbow(5000))
나는이 끔찍한 결과를 얻을 : 잘 작동하지만 나는이 같은 색상을 추가하려고하고 때
나는 문제가 주로 규모하지만 at
또는 col.regions
을 위해 내가 결과를 변경할 수 없습니다 시도 값에 상관없이의 생각합니다. 나는 심지어 interpolate
옵션을 시도했지만 do not snot이 차이를 만듭니다. 나는 많은 것을 수색했지만 격자의 문서가 조금 복잡하다는 것을 알아야한다.
structure(list(x = c(99.9735523336143, 99.9735523336143, 99.9735523336143,
9.99735523336143, 99.9735523336143, 99.9735523336143, 99.9735523336143,
99.9735523336143, 9.99735523336143, 99.9735523336143, 9.99735523336143,
9.99735523336143, 9.99735523336143, 9.99735523336143, 9.99735523336143,
9.99735523336143, 19.9947104667229, 19.9947104667229, 19.9947104667229,
19.9947104667229, 19.9947104667229, 19.9947104667229, 19.9947104667229,
19.9947104667229, 29.9920657000843, 29.9920657000843, 29.9920657000843,
29.9920657000843, 29.9920657000843, 29.9920657000843, 29.9920657000843,
29.9920657000843, 39.9103904572927, 39.9103904572927, 39.9103904572927,
39.9103904572927, 39.9103904572927, 39.9103904572927, 39.9103904572927,
39.9103904572927, 49.9867761668072, 49.9867761668072, 49.9867761668072,
4.99867761668072, 49.9867761668072, 49.9867761668072, 49.9867761668072,
49.9867761668072, 4.99867761668072, 49.9867761668072, 4.99867761668072,
4.99867761668072, 4.99867761668072, 4.99867761668072, 4.99867761668072,
4.99867761668072, 60.0631618763217, 60.0631618763217, 60.0631618763217,
60.0631618763217, 60.0631618763217, 60.0631618763217, 60.0631618763217,
60.0631618763217, 69.9419713954535, 69.9419713954535, 69.9419713954535,
69.9419713954535, 69.9419713954535, 69.9419713954535, 69.9419713954535,
69.9419713954535, 79.8207809145854, 79.8207809145854, 79.8207809145854,
79.8207809145854, 79.8207809145854, 79.8207809145854, 79.8207809145854,
79.8207809145854, 90.0947428144825, 90.0947428144825, 90.0947428144825,
90.0947428144825, 90.0947428144825, 90.0947428144825, 90.0947428144825,
90.0947428144825), y = c(0.0999735523336143, 0.499867761668072,
9.99735523336143, 0.0999735523336143, 0.999735523336143, 19.9947104667229,
1.99947104667229, 49.9867761668072, 0.499867761668072, 4.99867761668072,
9.99735523336143, 0.999735523336143, 19.9947104667229, 1.99947104667229,
49.9867761668072, 4.99867761668072, 0.0999735523336143, 0.499867761668072,
9.99735523336143, 0.999735523336143, 19.9947104667229, 1.99947104667229,
49.9867761668072, 4.99867761668072, 0.0999735523336143, 0.499867761668072,
9.99735523336143, 0.999735523336143, 19.9947104667229, 1.99947104667229,
49.9867761668072, 4.99867761668072, 0.0999735523336143, 0.499867761668072,
9.99735523336143, 0.999735523336143, 19.9947104667229, 1.99947104667229,
49.9867761668072, 4.99867761668072, 0.0999735523336143, 0.499867761668072,
9.99735523336143, 0.0999735523336143, 0.999735523336143, 19.9947104667229,
1.99947104667229, 49.9867761668072, 0.499867761668072, 4.99867761668072,
9.99735523336143, 0.999735523336143, 19.9947104667229, 1.99947104667229,
49.9867761668072, 4.99867761668072, 0.0999735523336143, 0.499867761668072,
9.99735523336143, 0.999735523336143, 19.9947104667229, 1.99947104667229,
49.9867761668072, 4.99867761668072, 0.0999735523336143, 0.499867761668072,
9.99735523336143, 0.999735523336143, 19.9947104667229, 1.99947104667229,
49.9867761668072, 4.99867761668072, 0.0999735523336143, 0.499867761668072,
9.99735523336143, 0.999735523336143, 19.9947104667229, 1.99947104667229,
49.9867761668072, 4.99867761668072, 0.0999735523336143, 0.499867761668072,
9.99735523336143, 0.999735523336143, 19.9947104667229, 1.99947104667229,
49.9867761668072, 4.99867761668072), z = c(7.70262939725884,
72.4762038498177, 1897.66010932237, 1.58054830233696, 165.070646557113,
3792.42153530273, 356.278306229365, 9223.47853672023, 14.2758673767137,
935.839000278543, 341.884101039707, 31.701193606272, 665.004073393329,
66.9391931173054, 1509.15007815714, 171.754281181158, 2.89064204660586,
26.2635839730677, 636.27993673818, 58.5156364281774, 1243.02434222159,
123.885961157754, 2852.46703855471, 318.792649405134, 3.97493187787477,
36.3111148789109, 889.55438527022, 81.1632049285379, 1744.63858516148,
172.284250494152, 4044.24262993302, 444.58461882461, 4.86420556288387,
44.6549593184585, 1105.67331471408, 100.121759918144, 2176.12813241023,
213.072583938431, 5090.54862806588, 551.33727936112, 5.608738003459,
51.7306506719939, 1294.26413375778, 0.827199861040891, 116.33438144459,
2555.52749317869, 248.208540590425, 6028.1869116069, 7.44790194067698,
643.985400190343, 177.310068151686, 16.5109365887457, 344.080667093976,
34.8178598080871, 776.206332364582, 89.2039775124962, 6.21939893932657,
57.6140181031486, 1455.92520463951, 129.934909189257, 2883.12188866332,
277.918147781392, 6852.31788369484, 722.963381835502, 6.70936909598539,
62.4057616449996, 1591.87930397262, 141.11465788703, 3160.532277617,
302.546915494946, 7561.72493964819, 789.007565625702, 7.10911809960051,
66.3821496606545, 1708.59117356901, 150.482643243694, 3400.26770836962,
323.370848584576, 8184.13138429934, 845.374097718433, 7.44465742618642,
69.7893126020086, 1812.39459545251, 158.596014882138, 3614.91792337778,
341.585243605719, 8749.51748025968, 895.192251986793)), .Names = c("x",
"y", "z"), row.names = c(NA, -88L), class = "data.frame")
는 [여기] 좋은 제안이있다 (https://stackoverflow.com/questions/7851602/methods-for-doing-heatmaps- : 당신은 일부 데이터 논쟁을 수행해야합니다 레벨 윤곽 플롯 및 육각형 비닝) –