我在 R 中有一个这样的矩阵：
bio1 bio10 bio11 bio12 bio13 bio14 bio15 bio16 bio17 bio18 bio19 bio2 bio3 bio4 bio5 bio6 bio7 bio8 bio9
bio1 1.00 0.90 0.91 -0.40 -0.21 -0.54 0.71 -0.22 -0.54 -0.57 0.02 0.45 0.45 -0.13 0.84 0.85 0.05 -0.07 0.73
bio10 0.90 1.00 0.64 -0.60 -0.44 -0.64 0.57 -0.45 -0.65 -0.68 -0.19 0.48 0.19 0.32 0.97 0.56 0.44 0.02 0.71
bio11 0.91 0.64 1.00 -0.13 0.04 -0.35 0.71 0.04 -0.35 -0.38 0.23 0.32 0.58 -0.52 0.57 0.98 -0.33 -0.15 0.62
bio12 -0.40 -0.60 -0.13 1.00 0.93 0.74 -0.23 0.94 0.76 0.71 0.78 -0.31 0.07 -0.51 -0.60 -0.04 -0.55 -0.08 -0.40
bio13 -0.21 -0.44 0.04 0.93 1.00 0.48 0.06 1.00 0.50 0.51 0.87 -0.19 0.19 -0.55 -0.43 0.11 -0.53 -0.17 -0.22
bio14 -0.54 -0.64 -0.35 0.74 0.48 1.00 -0.64 0.50 0.99 0.90 0.27 -0.44 -0.17 -0.28 -0.67 -0.25 -0.43 0.27 -0.65
bio15 0.71 0.57 0.71 -0.23 0.06 -0.64 1.00 0.05 -0.64 -0.56 0.21 0.64 0.67 -0.25 0.62 0.60 0.06 -0.45 0.68
bio16 -0.22 -0.45 0.04 0.94 1.00 0.50 0.05 1.00 0.52 0.52 0.88 -0.19 0.19 -0.54 -0.44 0.11 -0.53 -0.17 -0.23
bio17 -0.54 -0.65 -0.35 0.76 0.50 0.99 -0.64 0.52 1.00 0.90 0.29 -0.46 -0.18 -0.29 -0.69 -0.25 -0.45 0.27 -0.65
bio18 -0.57 -0.68 -0.38 0.71 0.51 0.90 -0.56 0.52 0.90 1.00 0.18 -0.43 -0.16 -0.29 -0.71 -0.29 -0.44 0.38 -0.75
bio19 0.02 -0.19 0.23 0.78 0.87 0.27 0.21 0.88 0.29 0.18 1.00 -0.02 0.31 -0.50 -0.17 0.28 -0.42 -0.36 0.07
bio2 0.45 0.48 0.32 -0.31 -0.19 -0.44 0.64 -0.19 -0.46 -0.43 -0.02 1.00 0.76 0.13 0.66 0.13 0.53 -0.33 0.47
bio3 0.45 0.19 0.58 0.07 0.19 -0.17 0.67 0.19 -0.18 -0.16 0.31 0.76 1.00 -0.52 0.31 0.47 -0.13 -0.37 0.36
bio4 -0.13 0.32 -0.52 -0.51 -0.55 -0.28 -0.25 -0.54 -0.29 -0.29 -0.50 0.13 -0.52 1.00 0.37 -0.58 0.90 0.21 0.02
bio5 0.84 0.97 0.57 -0.60 -0.43 -0.67 0.62 -0.44 -0.69 -0.71 -0.17 0.66 0.31 0.37 1.00 0.45 0.57 -0.08 0.72
bio6 0.85 0.56 0.98 -0.04 0.11 -0.25 0.60 0.11 -0.25 -0.29 0.28 0.13 0.47 -0.58 0.45 1.00 -0.47 -0.08 0.54
bio7 0.05 0.44 -0.33 -0.55 -0.53 -0.43 0.06 -0.53 -0.45 -0.44 -0.42 0.53 -0.13 0.90 0.57 -0.47 1.00 0.00 0.22
bio8 -0.07 0.02 -0.15 -0.08 -0.17 0.27 -0.45 -0.17 0.27 0.38 -0.36 -0.33 -0.37 0.21 -0.08 -0.08 0.00 1.00 -0.48
bio9 0.73 0.71 0.62 -0.40 -0.22 -0.65 0.68 -0.23 -0.65 -0.75 0.07 0.47 0.36 0.02 0.72 0.54 0.22 -0.48 1.00
correlation_bio <- `structure(c(1, 0.9, 0.91, -0.4, -0.21, -0.54, 0.71, -0.22, -0.54, -0.57, 0.02, 0.45, 0.45, -0.13, 0.84, 0.85, 0.05, -0.07, 0.73, 0.9, 1, 0.64, -0.6, -0.44, -0.64, 0.57, -0.45, -0.65, -0.68, -0.19, 0.48, 0.19, 0.32, 0.97, 0.56, 0.44, 0.02, 0.71, 0.91, 0.64, 1, -0.13, 0.04, -0.35, 0.71, 0.04, -0.35, -0.38, 0.23, 0.32, 0.58, -0.52, 0.57, 0.98, -0.33, -0.15, 0.62, -0.4, -0.6, -0.13, 1, 0.93, 0.74, -0.23, 0.94, 0.76, 0.71, 0.78, -0.31, 0.07, -0.51, -0.6, -0.04, -0.55, -0.08, -0.4, -0.21, -0.44, 0.04, 0.93, 1, 0.48, 0.06, 1, 0.5, 0.51, 0.87, -0.19, 0.19, -0.55, -0.43, 0.11, -0.53, -0.17, -0.22, -0.54, -0.64, -0.35, 0.74, 0.48, 1, -0.64, 0.5, 0.99, 0.9, 0.27, -0.44, -0.17, -0.28, -0.67, -0.25, -0.43, 0.27, -0.65, 0.71, 0.57, 0.71, -0.23, 0.06, -0.64, 1, 0.05, -0.64, -0.56, 0.21, 0.64, 0.67, -0.25, 0.62, 0.6, 0.06, -0.45, 0.68, -0.22, -0.45, 0.04, 0.94, 1, 0.5, 0.05, 1, 0.52, 0.52, 0.88, -0.19, 0.19, -0.54, -0.44, 0.11, -0.53, -0.17, -0.23, -0.54, -0.65, -0.35, 0.76, 0.5, 0.99, -0.64, 0.52, 1, 0.9, 0.29, -0.46, -0.18, -0.29, -0.69, -0.25, -0.45, 0.27, -0.65, -0.57, -0.68, -0.38, 0.71, 0.51, 0.9, -0.56, 0.52, 0.9, 1, 0.18, -0.43, -0.16, -0.29, -0.71, -0.29, -0.44, 0.38, -0.75, 0.02, -0.19, 0.23, 0.78, 0.87, 0.27, 0.21, 0.88, 0.29, 0.18, 1, -0.02, 0.31, -0.5, -0.17, 0.28, -0.42, -0.36, 0.07, 0.45, 0.48, 0.32, -0.31, -0.19, -0.44, 0.64, -0.19, -0.46, -0.43, -0.02, 1, 0.76, 0.13, 0.66, 0.13, 0.53, -0.33, 0.47, 0.45, 0.19, 0.58, 0.07, 0.19, -0.17, 0.67, 0.19, -0.18, -0.16, 0.31, 0.76, 1, -0.52, 0.31, 0.47, -0.13, -0.37, 0.36, -0.13, 0.32, -0.52, -0.51, -0.55, -0.28, -0.25, -0.54, -0.29, -0.29, -0.5, 0.13, -0.52, 1, 0.37, -0.58, 0.9, 0.21, 0.02, 0.84, 0.97, 0.57, -0.6, -0.43, -0.67, 0.62, -0.44, -0.69, -0.71, -0.17, 0.66, 0.31, 0.37, 1, 0.45, 0.57, -0.08, 0.72, 0.85, 0.56, 0.98, -0.04, 0.11, -0.25, 0.6, 0.11, -0.25, -0.29, 0.28, 0.13, 0.47, -0.58, 0.45, 1, -0.47, -0.08, 0.54, 0.05, 0.44, -0.33, -0.55, -0.53, -0.43, 0.06, -0.53, -0.45, -0.44, -0.42, 0.53, -0.13, 0.9, 0.57, -0.47, 1, 0, 0.22, -0.07, 0.02, -0.15, -0.08, -0.17, 0.27, -0.45, -0.17, 0.27, 0.38, -0.36, -0.33, -0.37, 0.21, -0.08, -0.08, 0, 1, -0.48, 0.73, 0.71, 0.62, -0.4, -0.22, -0.65, 0.68, -0.23, -0.65, -0.75, 0.07, 0.47, 0.36, 0.02, 0.72, 0.54, 0.22, -0.48, 1), dim = c(19L, 19L), dimnames = list( c("bio1", "bio10", "bio11", "bio12", "bio13", "bio14", "bio15", "bio16", "bio17", "bio18", "bio19", "bio2", "bio3", "bio4", "bio5", "bio6", "bio7", "bio8", "bio9"), c("bio1", "bio10", "bio11", "bio12", "bio13", "bio14", "bio15", "bio16", "bio17", "bio18", "bio19", "bio2", "bio3", "bio4", "bio5", "bio6", "bio7", "bio8", "bio9")))`
如您所见，行和列都以“bio 1”开头，但随后以“bio10”而不是“bio2”继续。
行和列都应该这样排序； “生物1”，“生物2”，“生物3”，“生物4”，“生物5”，“生物6”，“生物7”，“生物8”，“生物9”，“生物10”，“生物11”，“生物12”，“生物13” “ ”、“bio14”、“bio15”、“bio16”、“bio17”、“bio18”、“bio19”。
我该如何解决这个问题？
您可以使用
mixedsort()gtoolscorrelation_bio[gtools::mixedsort(rownames(correlation_bio)),
gtools::mixedsort(colnames(correlation_bio))]