rpubs - Adición de puntos suspensivos a un gráfico de análisis de componentes principales(PCA)

prcomp in r

Question

Estoy teniendo problemas para agregar elipsis de variables de agrupación en la parte superior de un gráfico de factor PCA de sitio individual que también incluye flechas de factor variable de PCA.

Mi código:

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).

He intentado usar las funciones dataellipse, plotellipses y ellipse, pero sin éxito. La ignorancia está ganando en esto. Si no he suministrado suficiente información por favor hágamelo saber.

Datos (log10 transformados):

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"))

Answer 1

Aquí hay una solución ggplot , usando la bonita biblioteca ggbiplot . Una mejora obvia sobre la plot son las etiquetas en este caso.

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)

Answer 2

Como no menciona esto en su pregunta, asumiré que el paquete que usó es vegan , ya que tiene la función rda() que acepta el argumento scale=TRUE .

Su llamada plot() inicial se modificó ya que no se dan algunas de las variables.

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)

Para hacer puntos suspensivos, se ordiellipse() función ordiellipse() del paquete vegan . Como argumentos se deben proporcionar el objeto de análisis PCA y la variable de agrupación. Para controlar el número de puntos incluidos en la elipse, se puede usar el argumento conf= .

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