Hinzufügen von Ellipsen zu einem PCA-Diagramm (Principal Component Analysis)

Ich habe Probleme beim Hinzufügen von gruppierenden Variablen-Ellipsen auf einem PCA-Faktor-Plot für einzelne Standorte, der auch PCA-Variable-Faktor-Pfeile enthält.Hinzufügen von Ellipsen zu einem PCA-Diagramm (Principal Component Analysis)

Mein Code:

prin_comp<-rda(data[,2:9], scale=TRUE) 
pca_scores<-scores(prin_comp) 

#sites=individual site PC1 & PC2 scores, Waterbody=Row Grouping Variable. 
#site scores in the PCA plot are stratified by Waterbody type. 

plot(pca_scores$sites[,1], 
    pca_scores$sites[,2], 
    pch=21, 
    bg=point_colors[data$Waterbody], 
    xlim=c(-2,2), 
    ylim=c(-2,2), 
    xlab=x_axis_text, 
    ylab=y_axis_text) 

#species=column PCA1 & PCA2 Response variables 
arrows(0,0,pca_scores$species[,1],pca_scores$species[,2],lwd=1,length=0.2) 

#I want to draw 'Waterbody' Grouping Variable ellipses that encompass completely, 
# their appropriate individual site scores (this is to visualise total error/variance).

habe ich versucht, beide dataellipse zu verwenden, plotellipses & Ellipse Funktionen, aber ohne Erfolg. Ignoranz gewinnt auf diesem einen. Wenn ich nicht genügend Informationen zur Verfügung gestellt habe, lass es mich wissen.

Daten (log10 transformierte):

dput(data) 

structure(list(Waterbody = structure(c(4L, 4L, 4L, 4L, 4L, 4L, 
4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 4L, 5L, 5L, 
5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 5L, 
5L, 5L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 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), .Label = c("Ditch", "Garden Pond", 
"Peri-Urban Ponds", "River", "Stream"), class = "factor"), Catchment_Size = c(9.73045926, 
9.73045926, 9.73045926, 9.73045926, 9.73045926, 9.73045926, 9.73045926, 
9.73045926, 9.73045926, 9.73045926, 9.73045926, 9.73045926, 9.73045926, 
9.73045926, 9.73045926, 9.73045926, 9.73045926, 9.73045926, 9.73045926, 
9.73045926, 8.602059991, 8.602059991, 8.602059991, 8.602059991, 
8.602059991, 8.602059991, 8.602059991, 8.602059991, 8.602059991, 
8.602059991, 8.602059991, 8.602059991, 8.602059991, 8.602059991, 
8.602059991, 8.602059991, 8.602059991, 8.602059991, 8.602059991, 
8.602059991, 5.230525555, 5.271197816, 5.310342762, 5.674064357, 
5.745077916, 5.733059168, 5.90789752, 5.969640923, 0, 0, 0.419955748, 
0, 0.079181246, 0, 0.274157849, 0, 0.301029996, 1, 0.62838893, 
0.243038049, 0, 0, 0, 1.183269844, 0, 1.105510185, 0, 0.698970004, 
2, 1.079181246, 2.954242509, 1.84509804, 1.477121255, 2.477121255, 
3.662757832, 1.397940009, 1.84509804, 0), pH = c(0.888740961, 
0.891537458, 0.890421019, 0.904715545, 0.886490725, 0.88592634, 
0.892651034, 0.891537458, 0.895422546, 0.8876173, 0.881384657, 
0.888179494, 0.876794976, 0.898725182, 0.894316063, 0.882524538, 
0.881384657, 0.916980047, 0.890979597, 0.886490725, 0.88592634, 
0.903089987, 0.889301703, 0.897627091, 0.896526217, 0.890979597, 
0.927370363, 0.904174368, 0.907948522, 0.890979597, 0.910090546, 
0.892094603, 0.896526217, 0.891537458, 0.894869657, 0.894316063, 
0.898725182, 0.914343157, 0.923244019, 0.905256049, 0.870988814, 
0.868644438, 0.872156273, 0.874481818, 0.88422877, 0.876217841, 
0.874481818, 0.8876173, 0.859138297, 0.887054378, 0.856124444, 
0.856124444, 0.860936621, 0.903089987, 0.860338007, 0.8876173, 
0.860338007, 0.906335042, 0.922206277, 0.851869601, 0.862131379, 
0.868056362, 0.869818208, 0.861534411, 0.875061263, 0.852479994, 
0.868644438, 0.898725182, 0.870403905, 0.88422877, 0.867467488, 
0.905256049, 0.88536122, 0.8876173, 0.876794976, 0.914871818, 
0.899820502, 0.946943271), Conductivity = c(2.818885415, 2.824125834, 
2.824776462, 2.829303773, 2.824125834, 2.82672252, 2.829303773, 
2.82672252, 2.824776462, 2.829946696, 2.846337112, 2.862727528, 
2.845718018, 2.848804701, 2.86923172, 2.85308953, 2.867467488, 
2.847572659, 2.86569606, 2.849419414, 2.504606771, 2.506775537, 
2.691346764, 2.628797486, 2.505963518, 2.48756256, 2.501470072, 
2.488973525, 2.457124626, 2.778295991, 2.237040791, 2.429267666, 
2.3287872, 2.461198289, 2.384174139, 2.386320574, 2.410608543, 
2.404320467, 2.426836454, 2.448397103, 2.768704683, 2.76718556, 
2.771602178, 2.775289978, 2.90579588, 2.909020854, 3.007747778, 
3.017867719, 2.287129621, 2.099680641, 2.169674434, 1.980457892, 
2.741781696, 2.597804842, 2.607669437, 2.419129308, 2.786751422, 
2.639884742, 2.19893187, 2.683497318, 2.585235063, 2.393048466, 
2.562411833, 2.785329835, 2.726808683, 2.824776462, 2.699056855, 
2.585122186, 2.84260924, 2.94792362, 2.877371346, 2.352568386, 
2.202760687, 2.819543936, 2.822168079, 2.426348574, 2.495683068, 
2.731266349), NO3 = c(1.366236124, 1.366236124, 1.376029182, 
1.385606274, 1.376029182, 1.385606274, 1.385606274, 1.385606274, 
1.376029182, 1.385606274, 1.458637849, 1.489114369, 1.482158695, 
1.496098992, 1.502290528, 1.50174373, 1.500785173, 1.499549626, 
1.485721426, 1.490520309, 0.693726949, 0.693726949, 1.246005904, 
1.159266331, 0.652246341, 0.652246341, 0.883093359, 0.85672889, 
0.828659897, 1.131297797, 0.555094449, 0.85672889, 0.731588765, 
0.883093359, 0.731588765, 0.731588765, 0.693726949, 0.693726949, 
0.693726949, 0.693726949, 1.278524965, 1.210853365, 1.318480725, 
1.308777774, 1.404833717, 1.412796429, 0, 0, 0, 0, 0, 0, 1.204391332, 
0, 0, 0, 0.804820679, 0, 0, 0.021189299, 0, 0, 0.012837225, 0, 
0, 0, 0, 0.539076099, 0, 0, 1.619406411, 0, 0, 1.380753771, 0, 
0, 0, 0.931966115), NH4 = c(0.14, 0.14, 0.18, 0.19, 0.2, 0.2, 
0.15, 0.14, 0.11, 0.11, 0.04, 0.06, 0.04, 0.03, 0.07, 0.03, 0.03, 
0.04, 0.04, 0.03, 0.01, 0, 0, 0.01, 0.02, 0.02, 0.05, 0.03, 0.04, 
0.02, 0.21, 0.19, 0.2, 0.1, 0.05, 0.05, 0.08, 0.11, 0.04, 0.04, 
0.15, 2.03, 0.14, 0.09, 0.05, 0.04, 2.82, 3.18, 0.06, 0.12, 2.06, 
0.1, 0.14, 0.06, 1.06, 0.03, 0.04, 0.03, 0.03, 1.91, 0.2, 1.35, 
0.69, 0.05, 0.17, 3.18, 0.21, 0.1, 0.03, 1.18, 0.01, 0.03, 0.02, 
0.09, 0.14, 0.02, 0.07, 0.17), SRP = c(0.213348889, 0.221951667, 
0.24776, 0.228833889, 0.232275, 0.249480556, 0.259803889, 0.244318889, 
0.249480556, 0.240877778, 0.314861667, 0.292494444, 0.311420556, 
0.306258889, 0.285612222, 0.323464444, 0.316582222, 0.34067, 
0.285612222, 0.321743889, 0.074328, 0.074328, 0.120783, 0.133171, 
0.0820705, 0.080522, 0.0789735, 0.0820705, 0.080522, 0.0913615, 
0.136268, 0.1656895, 0.1223315, 0.130074, 0.1192345, 0.1285255, 
0.1873685, 0.167238, 0.15485, 0.157947, 0.1378165, 0.1966595, 
0.198208, 0.241566, 0.037164, 0.0325185, 0.455259, 0.560557, 
0.07987, 0.02119, 0.02119, 0.03912, 0.36349, 0.40098, 0.04401, 
0.07172, 0.15322, 0.92421, 0.02282, 0.17604, 0.17767, 0.66667, 
0.28688, 0.03586, 0.17278, 0.07661, 0.10432, 1.12959, 0.0170335, 
0.0975555, 0.009291, 0.0263245, 0.037164, 0.2214355, 0.0449065, 
0.068134, 0.09291, 0.545072), Zn = c(0.802630077, 1.172124009, 
0.891565332, 0.600253919, 0.583912562, 0.962473516, 0.99881711, 
0.709787074, 1.139860204, 0.953730706, 0.945832806, 0.906270378, 
0.81663232, 0.912514323, 0.935073763, 1.032328597, 1.357197063, 
1.070662063, 0.51200361, 0.987514325, 1.433709044, 1.380974206, 
1.143661074, 0.999774108, 1.449654241, 1.366165106, 1.014239038, 
0.891258617, 0.703978825, 1.086487964, 1.503432481, 1.243241499, 
0.890504851, 0.291391053, 0, 0.802855789, 0.776316103, 0.927421695, 
0.421505212, 0.952099537, 0.688802331, 0.852504392, 0.773545103, 
1.006581553, 1.028229538, 0.880619259, 0.833408503, 1.038608242, 
1.107084413, 0.973967909, 2.135781222, 1.819197019, 1.629353525, 
1.163194184, 1.343286462, 1.273614642, 1.92374902, 1.70523233, 
1.377623112, 1.119971423, 1.461175762, 1.691856516, 1.661826878, 
1.104531494, 1.449455257, 1.092376721, 1.519029523, 1.553407226, 
1.52652924, 1.332876573, 1.293079563, 0.996734891, 1.590475126, 
1.525755949, 1.180418366, 0.712624451, 0.6739512, 0.585043155 
), Mn = c(0.817367016, 0.799340549, 1.023910606, 1.012921546, 
0.821579028, 1.321888278, 1.115077717, 1.02031984, 1.135482491, 
1.073645046, 1.016866271, 1.052809328, 0.818423855, 0.836387419, 
1.151032582, 0.720490068, 1.03746634, 1.072580733, 1.041590047, 
0.979548375, 1.073168262, 1.134336511, 0.916137983, 0.641374945, 
1.083753378, 0.84441504, 0.547159121, 0.144262774, 1.084826417, 
0.674861141, 0.478566496, 1.211654401, 1.095518042, 0.387033701, 
0.647480773, 0.775828814, 0.533899101, 0.854548936, 0.755188586, 
0.714497409, 0.851808514, 0.390051496, 0.832508913, 1.222482357, 
1.477048866, 1.475147977, 2.127826941, 2.132205239, 1.639576128, 
1.155578931, 2.203783274, 1.148448404, 1.644586284, 1.122609024, 
1.577319427, 1.633417953, 1.583901241, 1.215478936, 1.135418905, 
1.612847407, 1.95593777, 1.783639208, 1.567837703, 2.251767151, 
0.992155711, 1.738923187, 0.681964459, 0.852845818, 1.77749932, 
2.465019796, 0.887729797, 0.610447221, 1.777760209, 1.034588354, 
0.303196057, 1.793371249, 1.677734668, 1.802157753)), .Names = c("Waterbody", 
"Catchment_Size", "pH", "Conductivity", "NO3", "NH4", "SRP", 
"Zn", "Mn"), class = "data.frame", row.names = c("1_1", "1_2", 
"1_3", "1_4", "1_5", "1_6", "1_7", "1_8", "1_9", "1_10", "1_11", 
"1_12", "1_13", "1_14", "1_15", "1_16", "1_17", "1_18", "1_19", 
"1_20", "2_1", "2_2", "2_3", "2_4", "2_5", "2_6", "2_7", "2_8", 
"2_9", "2_10", "2_11", "2_12", "2_13", "2_14", "2_15", "2_16", 
"2_17", "2_18", "2_19", "2_20", "3_1", "3_2", "3_3", "3_4", "3_5", 
"3_6", "3_7", "3_8", "4_1", "4_2", "4_3", "4_4", "4_5", "4_6", 
"4_7", "4_8", "4_9", "4_10", "4_11", "4_12", "4_13", "4_14", 
"4_15", "4_16", "4_17", "4_18", "4_19", "4_20", "5_1", "5_2", 
"5_3", "5_4", "5_5", "5_6", "5_7", "5_8", "5_9", "5_10"))

Quelle

2012-12-18 Lew

Willkommen bei Stackoverflow! Könnten Sie eine reproduzierbare Version Ihrer Daten zeigen, indem Sie 'dput (data)' machen? (Wenn Ihre Daten groß sind, möchten Sie vielleicht nur eine Teilmenge der Zeilen ausgeben) –

Außerdem ist dies das 'rda' Paket aus dem [rda Paket] (http://cran.r-project.org/web /packages/rda/index.html)? Wenn ja, wo kommt das 'scale'-Argument her (es scheint in dieser Funktion nicht verwendbar zu sein). –

Ich bin neu in diesem so entschuldigen Sie meine Etikette David – Lew

Da Sie dies nicht in Ihrer Frage erwähnt, gehe ich davon aus, dass das Paket, das Sie ist vegan verwendet, da es die Funktion rda(), die das scale=TRUE Argument akzeptiert hat.

Ihr ursprünglicher Aufruf plot() wurde geändert, da einige der Variablen nicht angegeben sind.

library(vegan) 
prin_comp<-rda(data[,2:9], scale=TRUE) 
pca_scores<-scores(prin_comp) 

plot(pca_scores$sites[,1], 
    pca_scores$sites[,2], 
    pch=21, 
    bg=as.numeric(data$Waterbody), 
    xlim=c(-2,2), 
    ylim=c(-2,2)) 
arrows(0,0,pca_scores$species[,1],pca_scores$species[,2],lwd=1,length=0.2)

zu Ellipsen, Funktion ordiellipse() des Pakets machen vegan verwendet wird. Als Argumente müssen PCA-Analyseobjekt und Gruppierungsvariable bereitgestellt werden. Um die Anzahl der in der Ellipse enthaltenen Punkte zu steuern, kann das Argument conf= verwendet werden.

ordiellipse(prin_comp,data$Waterbody,conf=0.99)

enter image description here

Quelle

2012-12-18 17:50:09

Ich würde Ihnen auch vorschlagen, Bibliothek vegan zu erkunden, wie es Funktionen hat zum Zeichnen von PCA-Ergebnissen. –

Danke Didzis. Genau das habe ich gesucht. Ich glaube, das vegane Paket wird automatisch heruntergeladen, wenn Sie das BiodiversityR-Paket installieren. – Lew

sehr schätzen jeden Input. stackoverflow war ein großartiger Fund – Lew

Hier ist eine ggplot Lösung, die schöne ggbiplot Bibliothek. Eine deutliche Verbesserung gegenüber plot sind die Etiketten auf diesem.

library(devtools) # don't forget to install Rtools first 
install_github("ggbiplot", "vqv") 

library(ggbiplot) 
data.class <- data[,1] 
data.pca <- prcomp(data[,2:9], scale. = TRUE) 
g <- ggbiplot(data.pca, obs.scale = 1, var.scale = 1, 
       groups = data.class, ellipse = TRUE, circle = TRUE) 
g <- g + scale_color_discrete(name = '') 
g <- g + theme(legend.direction = 'horizontal', 
       legend.position = 'top') 
print(g)

enter image description here

Quelle

2013-01-10 05:17:17 Ben

Hinzufügen von Ellipsen zu einem PCA-Diagramm (Principal Component Analysis)

Antwort

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