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R version 4.0.3 Patched (2021-01-18 r79850) -- "Bunny-Wunnies Freak Out"Copyright (C) 2021 The R Foundation for Statistical ComputingPlatform: x86_64-pc-linux-gnu (64-bit)R is free software and comes with ABSOLUTELY NO WARRANTY.You are welcome to redistribute it under certain conditions.Type 'license()' or 'licence()' for distribution details.R is a collaborative project with many contributors.Type 'contributors()' for more information and'citation()' on how to cite R or R packages in publications.Type 'demo()' for some demos, 'help()' for on-line help, or'help.start()' for an HTML browser interface to help.Type 'q()' to quit R.> library(cluster)> options(digits = 6)> data(votes.repub)>> ## IGNORE_RDIFF_BEGIN> source(system.file("test-tools.R", package = "cluster"), keep.source = FALSE)Loading required package: toolsdoExtras <- cluster:::doExtras() : TRUE> ## IGNORE_RDIFF_END> ## -> showProc.time() ... & doExtras>> agn1 <- agnes(votes.repub, metric = "manhattan", stand = TRUE)> summary(agn1)Object of class 'agnes' from call:agnes(x = votes.repub, metric = "manhattan", stand = TRUE)Agglomerative coefficient: 0.797756Order of objects:[1] Alabama Georgia Arkansas Louisiana Mississippi[6] South Carolina Alaska Vermont Arizona Montana[11] Nevada Colorado Idaho Wyoming Utah[16] California Oregon Washington Minnesota Connecticut[21] New York New Jersey Illinois Ohio Indiana[26] Michigan Pennsylvania New Hampshire Wisconsin Delaware[31] Kentucky Maryland Missouri New Mexico West Virginia[36] Iowa South Dakota North Dakota Kansas Nebraska[41] Maine Massachusetts Rhode Island Florida North Carolina[46] Tennessee Virginia Oklahoma Hawaii TexasMerge:[,1] [,2][1,] -7 -32[2,] -13 -35[3,] -12 -50[4,] 1 -30[5,] 2 -14[6,] -26 -28[7,] -5 -37[8,] -15 -41[9,] -22 -38[10,] -25 -31[11,] 7 -47[12,] -21 -39[13,] -16 -27[14,] 4 5[15,] -42 -46[16,] -20 10[17,] 14 9[18,] -3 6[19,] -6 3[20,] -33 15[21,] 17 -29[22,] -17 16[23,] 8 -34[24,] 21 -49[25,] 22 -48[26,] -8 25[27,] 19 -44[28,] 11 -23[29,] 28 24[30,] -11 -43[31,] 18 27[32,] 23 13[33,] 29 26[34,] 20 -36[35,] -1 -10[36,] 32 -19[37,] 31 33[38,] -9 34[39,] 37 36[40,] 35 -4[41,] -2 -45[42,] 40 -18[43,] -24 -40[44,] 39 12[45,] 44 38[46,] 41 45[47,] 42 43[48,] 46 30[49,] 47 48Height:[1] 27.36345 31.15453 35.61832 51.44421 35.69152 87.45523 31.58222 47.53682[9] 16.34184 11.49397 22.11426 16.35662 10.46294 19.03961 28.41137 11.70132[17] 12.72838 19.07671 20.90246 8.38200 11.10094 12.92659 9.23004 11.37867[25] 15.97442 12.70819 16.91515 17.74499 24.83533 18.78225 17.03525 15.77893[33] 12.71848 18.52818 30.74557 12.55524 17.14634 22.33846 12.80419 27.38835[41] 37.23685 12.79160 38.76377 29.38432 16.63215 14.75762 25.59605 53.03627[49] 21.076841225 dissimilarities, summarized :Min. 1st Qu. Median Mean 3rd Qu. Max.8.38 25.54 34.51 45.06 56.02 167.60Metric : manhattanNumber of objects : 50Available components:[1] "order" "height" "ac" "merge" "diss" "call"[7] "method" "order.lab" "data"> Dvr <- daisy(votes.repub)> agn2 <- agnes(Dvr, method = "complete")> summary(agn2)Object of class 'agnes' from call:agnes(x = Dvr, method = "complete")Agglomerative coefficient: 0.88084Order of objects:[1] Alabama Georgia Louisiana Arkansas Florida[6] Texas Mississippi South Carolina Alaska Michigan[11] Connecticut New York New Hampshire Indiana Ohio[16] Illinois New Jersey Pennsylvania Minnesota North Dakota[21] Wisconsin Iowa South Dakota Kansas Nebraska[26] Arizona Nevada Montana Oklahoma Colorado[31] Idaho Wyoming Utah California Oregon[36] Washington Missouri New Mexico West Virginia Delaware[41] Kentucky Maryland North Carolina Tennessee Virginia[46] Hawaii Maine Massachusetts Rhode Island VermontMerge:[,1] [,2][1,] -12 -50[2,] -7 -32[3,] -14 -35[4,] -13 -30[5,] -25 -31[6,] -37 -47[7,] -21 -39[8,] -3 -28[9,] 4 -38[10,] -16 -27[11,] -15 -41[12,] 8 -26[13,] -2 -22[14,] -33 -42[15,] 14 -46[16,] 1 -44[17,] -11 -19[18,] 2 -29[19,] -5 6[20,] -17 -20[21,] -34 -49[22,] 5 -48[23,] 18 3[24,] 11 10[25,] 23 9[26,] -23 21[27,] -8 20[28,] 12 -36[29,] -6 16[30,] 13 25[31,] 28 29[32,] -1 -10[33,] 19 22[34,] 17 7[35,] -4 -9[36,] 30 26[37,] 35 -43[38,] 32 -18[39,] -24 -40[40,] 36 24[41,] 27 15[42,] 31 33[43,] 38 37[44,] 40 42[45,] 34 -45[46,] 43 39[47,] 44 41[48,] 47 45[49,] 46 48Height:[1] 48.2397 60.8984 72.9221 56.1363 58.8227 116.7048 63.0951 281.9508[9] 28.1437 47.1690 19.4218 32.9438 36.7643 20.2258 39.1728 20.8792[17] 25.3229 56.3813 42.2230 33.6978 64.5254 26.1547 37.4564 25.9221[25] 80.4894 23.4206 27.8273 43.4492 48.0483 43.7055 17.1992 31.1988[33] 70.4868 33.2328 22.1831 54.3057 21.1413 35.1129 121.4022 43.3829[41] 33.4744 66.7591 29.5099 30.1541 178.4119 32.7611 55.3633 22.6334[49] 83.10401225 dissimilarities, summarized :Min. 1st Qu. Median Mean 3rd Qu. Max.17.2 48.3 64.7 82.2 105.5 282.0Metric : euclideanNumber of objects : 50Available components:[1] "order" "height" "ac" "merge" "diss" "call"[7] "method" "order.lab"> ## almost same:> (ag2. <- agnes(Dvr, method= "complete", keep.diss=FALSE))Call: agnes(x = Dvr, method = "complete", keep.diss = FALSE)Agglomerative coefficient: 0.88084Order of objects:[1] Alabama Georgia Louisiana Arkansas Florida[6] Texas Mississippi South Carolina Alaska Michigan[11] Connecticut New York New Hampshire Indiana Ohio[16] Illinois New Jersey Pennsylvania Minnesota North Dakota[21] Wisconsin Iowa South Dakota Kansas Nebraska[26] Arizona Nevada Montana Oklahoma Colorado[31] Idaho Wyoming Utah California Oregon[36] Washington Missouri New Mexico West Virginia Delaware[41] Kentucky Maryland North Carolina Tennessee Virginia[46] Hawaii Maine Massachusetts Rhode Island VermontHeight (summary):Min. 1st Qu. Median Mean 3rd Qu. Max.17.2 28.1 39.2 52.3 58.8 282.0Available components:[1] "order" "height" "ac" "merge" "diss" "call"[7] "method" "order.lab"> ag22 <- agnes(votes.repub, method= "complete", keep.diss=FALSE,keep.data=FALSE)> stopifnot(identical(agn2[-5:-6], ag2.[-5:-6]),+ identical(Dvr, daisy(votes.repub)), # DUP=FALSE (!)+ identical(ag2.[-6], ag22[-6])+ )>> data(agriculture)> summary(agnes(agriculture))Object of class 'agnes' from call:agnes(x = agriculture)Agglomerative coefficient: 0.781893Order of objects:[1] B NL D F UK DK L I GR P E IRLMerge:[,1] [,2][1,] -1 -10[2,] -2 -9[3,] 1 -3[4,] 3 -6[5,] -5 -7[6,] 4 -12[7,] 6 2[8,] -4 -11[9,] 7 -8[10,] 8 5[11,] 9 10Height:[1] 1.64924 2.24836 2.76918 4.02677 4.78835 2.22036 5.29409 14.77963[9] 5.16236 8.55075 3.1400666 dissimilarities, summarized :Min. 1st Qu. Median Mean 3rd Qu. Max.1.65 4.36 7.99 9.59 13.25 24.04Metric : euclideanNumber of objects : 12Available components:[1] "order" "height" "ac" "merge" "diss" "call"[7] "method" "order.lab" "data">> data(ruspini)> summary(ar0 <- agnes(ruspini, keep.diss=FALSE, keep.data=FALSE))Object of class 'agnes' from call:agnes(x = ruspini, keep.diss = FALSE, keep.data = FALSE)Agglomerative coefficient: 0.947954Order of objects:[1] 1 2 3 5 4 6 8 7 9 10 14 15 17 16 18 19 11 12 13 20 61 62 66 63 64[26] 68 65 67 69 70 71 72 75 73 74 21 22 23 24 27 28 29 30 25 26 32 35 31 36 39[51] 40 33 34 37 38 41 42 43 44 45 49 51 53 50 54 52 55 56 57 59 60 58 46 47 48Merge:[,1] [,2][1,] -18 -19[2,] -55 -56[3,] -27 -28[4,] -49 -51[5,] -33 -34[6,] -23 -24[7,] -67 -69[8,] -59 -60[9,] -29 -30[10,] -36 -39[11,] -32 -35[12,] -50 -54[13,] -25 -26[14,] -16 1[15,] -70 -71[16,] -64 -68[17,] -37 -38[18,] 12 -52[19,] -62 -66[20,] -12 -13[21,] -9 -10[22,] -42 -43[23,] -15 -17[24,] -47 -48[25,] -21 -22[26,] 7 15[27,] 2 -57[28,] 4 -53[29,] 10 -40[30,] 3 9[31,] -73 -74[32,] -72 -75[33,] -11 20[34,] 13 11[35,] -6 -8[36,] -14 23[37,] -2 -3[38,] -65 26[39,] 5 17[40,] 25 6[41,] 36 14[42,] 34 -31[43,] -4 35[44,] 28 18[45,] 27 8[46,] 19 -63[47,] -46 24[48,] -1 37[49,] 16 38[50,] 40 30[51,] 42 29[52,] 33 -20[53,] 49 32[54,] 51 39[55,] 21 41[56,] 48 -5[57,] 45 -58[58,] 53 31[59,] 43 -7[60,] 50 54[61,] 44 57[62,] -41 22[63,] -61 46[64,] 55 52[65,] 63 58[66,] -44 -45[67,] 59 64[68,] 56 67[69,] 66 61[70,] 60 62[71,] 69 47[72,] 70 71[73,] 68 65[74,] 73 72Height:[1] 9.26758 6.40312 12.13789 22.37868 7.63441 6.32456 14.58991[8] 21.63544 4.12311 12.07902 6.36396 4.24264 7.23741 3.56155[15] 1.41421 16.38921 5.85486 4.12311 10.69547 67.75052 15.48443[22] 4.12311 8.94386 17.00500 3.60555 9.53375 6.46443 2.82843[29] 4.48680 3.60555 10.91541 5.83095 14.34411 5.65685 101.14200[36] 4.47214 6.98022 2.23607 9.56136 2.00000 5.61339 2.82843[43] 14.95692 3.16228 6.19728 3.00000 7.28356 9.97147 3.00000[50] 5.47542 11.07404 2.23607 6.60456 3.60555 24.90532 15.45463[57] 4.24264 64.42555 17.02939 22.56493 2.23607 5.22383 8.28122[64] 3.16228 3.81721 15.20808 2.00000 5.19258 8.51123 2.82843[71] 12.62990 34.72475 9.14005 4.47214Available components:[1] "order" "height" "ac" "merge" "diss" "call"[7] "method" "order.lab"> summary(ar1 <- agnes(ruspini, metric = "manhattan"))Object of class 'agnes' from call:agnes(x = ruspini, metric = "manhattan")Agglomerative coefficient: 0.946667Order of objects:[1] 1 2 3 5 4 6 8 7 9 10 14 16 18 19 15 17 11 12 13 20 61 62 66 63 73[26] 74 64 68 65 67 69 70 71 72 75 21 22 23 24 27 28 29 30 25 26 32 35 31 36 39[51] 40 33 34 37 38 41 42 43 44 45 49 51 53 50 54 52 55 56 57 59 60 58 46 47 48Merge:[,1] [,2][1,] -55 -56[2,] -27 -28[3,] -18 -19[4,] -49 -51[5,] -36 -39[6,] -33 -34[7,] -32 -35[8,] -23 -24[9,] -67 -69[10,] -59 -60[11,] -50 -54[12,] -29 -30[13,] -25 -26[14,] -16 3[15,] -70 -71[16,] -64 -68[17,] -62 -66[18,] 11 -52[19,] -37 -38[20,] -12 -13[21,] -9 -10[22,] 9 15[23,] 1 -57[24,] -47 -48[25,] -42 -43[26,] -21 -22[27,] -15 -17[28,] 4 -53[29,] 2 12[30,] 5 -40[31,] 6 19[32,] 13 7[33,] -11 20[34,] -73 -74[35,] -72 -75[36,] -6 -8[37,] -65 22[38,] -14 14[39,] -2 -3[40,] 32 -31[41,] 38 27[42,] 26 8[43,] 28 18[44,] -46 24[45,] -4 36[46,] 23 10[47,] -1 39[48,] 42 29[49,] 33 -20[50,] 37 35[51,] 40 30[52,] 17 -63[53,] 16 50[54,] 51 31[55,] 46 -58[56,] 21 41[57,] 47 -5[58,] 45 -7[59,] 52 34[60,] -44 -45[61,] 48 54[62,] 43 55[63,] 59 53[64,] 56 49[65,] -41 25[66,] -61 63[67,] 57 58[68,] 67 64[69,] 60 62[70,] 61 65[71,] 69 44[72,] 70 71[73,] 68 66[74,] 73 72Height:[1] 11.50000 9.00000 16.00000 26.25000 10.00000 8.00000 16.66667[8] 28.70833 5.00000 15.50000 8.66667 4.00000 2.00000 9.25000[15] 6.00000 20.50000 7.50000 5.00000 12.33333 94.33333 22.78571[22] 5.00000 12.50000 18.00000 8.00000 20.20000 5.00000 13.78571[29] 8.25000 4.00000 5.50000 5.00000 12.40000 8.00000 125.71357[36] 6.00000 9.50000 3.00000 11.87500 2.00000 7.00000 4.00000[43] 18.72917 4.00000 7.50000 3.00000 9.25000 12.40000 3.00000[50] 7.50000 14.43750 3.00000 7.50000 5.00000 32.38333 21.00000[57] 6.00000 85.49616 18.00000 28.75000 3.00000 6.50000 9.55556[64] 4.00000 5.00000 19.61111 2.00000 6.00000 11.00000 4.00000[71] 15.40000 47.02381 10.00000 6.000002775 dissimilarities, summarized :Min. 1st Qu. Median Mean 3rd Qu. Max.2.0 52.5 97.0 91.0 128.0 187.0Metric : manhattanNumber of objects : 75Available components:[1] "order" "height" "ac" "merge" "diss" "call"[7] "method" "order.lab" "data"> str(ar1)List of 9$ order : int [1:75] 1 2 3 5 4 6 8 7 9 10 ...$ height : num [1:74] 11.5 9 16 26.2 10 ...$ ac : num 0.947$ merge : int [1:74, 1:2] -55 -27 -18 -49 -36 -33 -32 -23 -67 -59 ...$ diss : 'dissimilarity' num [1:2775] 11 12 29 13 25 43 33 22 27 39 .....- attr(*, "Size")= int 75..- attr(*, "Metric")= chr "manhattan"..- attr(*, "Labels")= chr [1:75] "1" "2" "3" "4" ...$ call : language agnes(x = ruspini, metric = "manhattan")$ method : chr "average"$ order.lab: chr [1:75] "1" "2" "3" "5" ...$ data : num [1:75, 1:2] 4 5 10 9 13 13 12 15 18 19 .....- attr(*, "dimnames")=List of 2.. ..$ : chr [1:75] "1" "2" "3" "4" ..... ..$ : chr [1:2] "x" "y"- attr(*, "class")= chr [1:2] "agnes" "twins">> showProc.time()Time (user system elapsed): 0.602 0.061 0.667>> summary(ar2 <- agnes(ruspini, metric="manhattan", method = "weighted"))Object of class 'agnes' from call:agnes(x = ruspini, metric = "manhattan", method = "weighted")Agglomerative coefficient: 0.942387Order of objects:[1] 1 2 3 5 9 10 14 16 18 19 15 17 4 6 8 7 11 12 13 20 61 64 68 65 67[26] 69 70 71 62 66 63 72 75 73 74 21 22 23 24 27 28 29 30 25 26 32 35 31 36 39[51] 40 33 34 37 38 41 42 43 44 45 49 51 53 50 54 52 55 56 57 59 60 58 46 47 48Merge:[,1] [,2][1,] -55 -56[2,] -27 -28[3,] -18 -19[4,] -49 -51[5,] -36 -39[6,] -33 -34[7,] -32 -35[8,] -23 -24[9,] -67 -69[10,] -59 -60[11,] -50 -54[12,] -29 -30[13,] -25 -26[14,] -16 3[15,] -70 -71[16,] -64 -68[17,] -62 -66[18,] 11 -52[19,] -37 -38[20,] -12 -13[21,] -9 -10[22,] 9 15[23,] 1 -57[24,] -47 -48[25,] -42 -43[26,] -21 -22[27,] -15 -17[28,] 4 -53[29,] 2 12[30,] 5 -40[31,] 6 19[32,] 13 7[33,] -11 20[34,] -73 -74[35,] -72 -75[36,] -14 14[37,] -6 -8[38,] -65 22[39,] 36 27[40,] -2 -3[41,] 32 -31[42,] 28 18[43,] 26 8[44,] -46 24[45,] -4 37[46,] 23 10[47,] -1 40[48,] 16 38[49,] 43 29[50,] 17 -63[51,] 41 30[52,] 33 -20[53,] 35 34[54,] 46 -58[55,] 47 -5[56,] 51 31[57,] 21 39[58,] 45 -7[59,] -44 -45[60,] -61 48[61,] 42 54[62,] 49 56[63,] -41 25[64,] 55 57[65,] 60 50[66,] 65 53[67,] 58 52[68,] 59 61[69,] 64 67[70,] 62 63[71,] 68 44[72,] 70 71[73,] 69 66[74,] 73 72Height:[1] 11.5000 9.0000 15.2500 21.7734 5.0000 15.8750 8.0000 4.0000[9] 2.0000 9.0000 6.0000 32.1172 10.0000 8.0000 16.0000 27.9062[17] 7.5000 5.0000 13.2500 97.9766 18.3125 5.0000 11.8750 8.2500[25] 4.0000 5.5000 5.0000 22.3438 5.0000 12.5000 23.7812 8.0000[33] 14.5000 8.0000 114.9764 6.0000 9.5000 3.0000 11.8750 2.0000[41] 7.0000 4.0000 20.2031 4.0000 7.5000 3.0000 9.2500 12.6250[49] 3.0000 7.5000 15.6875 3.0000 7.5000 5.0000 33.5469 21.0000[57] 6.0000 69.4453 18.0000 28.4375 3.0000 6.5000 9.5000 4.0000[65] 5.0000 19.1250 2.0000 6.0000 10.5000 4.0000 15.0000 41.5312[73] 10.0000 6.00002775 dissimilarities, summarized :Min. 1st Qu. Median Mean 3rd Qu. Max.2.0 52.5 97.0 91.0 128.0 187.0Metric : manhattanNumber of objects : 75Available components:[1] "order" "height" "ac" "merge" "diss" "call"[7] "method" "order.lab" "data"> print (ar3 <- agnes(ruspini, metric="manhattan", method = "flexible",+ par.method = 0.5))Call: agnes(x = ruspini, metric = "manhattan", method = "flexible", par.method = 0.5)Agglomerative coefficient: 0.942387Order of objects:[1] 1 2 3 5 9 10 14 16 18 19 15 17 4 6 8 7 11 12 13 20 61 64 68 65 67[26] 69 70 71 62 66 63 72 75 73 74 21 22 23 24 27 28 29 30 25 26 32 35 31 36 39[51] 40 33 34 37 38 41 42 43 44 45 49 51 53 50 54 52 55 56 57 59 60 58 46 47 48Height (summary):Min. 1st Qu. Median Mean 3rd Qu. Max.2.00 5.00 8.12 14.22 15.58 114.98Available components:[1] "order" "height" "ac" "merge" "diss" "call"[7] "method" "order.lab" "data"> stopifnot(all.equal(ar2[1:4], ar3[1:4], tol=1e-12))>> showProc.time()Time (user system elapsed): 0.003 0.001 0.004>> ## Small example, testing "flexible" vs "single"> i8 <- -c(1:2, 9:10)> dim(agr8 <- agriculture[i8, ])[1] 8 2> i5 <- -c(1:2, 8:12)> dim(agr5 <- agriculture[i5, ])[1] 5 2>> ##' Check equivalence of method "flexible" (par=...) with one> ##' of ("single", "complete", "weighted")> chk <- function(d, method=c("single", "complete", "weighted"),+ trace.lev = 1,+ iC = -(6:7), # <- not using 'call' and 'method' for comparisons+ doplot = FALSE, tol = 1e-12)+ {+ if(!inherits(d, "dist")) d <- daisy(d, "manhattan")+ method <- match.arg(method)+ par.meth <- list("single" = c(.5, .5, 0, -.5),+ "complete"= c(.5, .5, 0, +.5),+ "weighted"= c(0.5))+ a.s <- agnes(d, method=method, trace.lev=trace.lev)+ ## From theory, this should give the same, but it does not --- why ???+ a.f <- agnes(d, method="flex", par.method = par.meth[[method]], trace.lev=trace.lev)++ if(doplot) {+ op <- par(mfrow = c(2,2), mgp = c(1.6, 0.6, 0), mar = .1 + c(4,4,2,1))+ on.exit(par(op))+ plot(a.s)+ plot(a.f)+ }+ structure(all.equal(a.s[iC], a.f[iC], tolerance = tol),+ fits = list(s = a.s, f = a.f))+ }>> chk(agr5, trace = 3)C agnes(n=5, method = 2, ..): 4 merging stepsnmerge=0, j=2, d_min = D(1,4) = 3.40000; -> (-1,-4); last=4; upd(n,b);old D(A, j), D(B, j), j=2 = (31.5,28.1); new D(A', 2) = 28.1old D(A, j), D(B, j), j=3 = (14.7,11.3); new D(A', 3) = 11.3old D(A, j), D(B, j), j=5 = (18.3,14.9); new D(A', 5) = 14.9--> size(A_new)= 2nmerge=1, j=2, d_min = D(3,5) = 3.60000; -> (-3,-5); last=5;old D(A, j), D(B, j), j=1 = (11.3,14.9); new D(A', 1) = 11.3old D(A, j), D(B, j), j=2 = (16.8,13.2); new D(A', 2) = 13.2--> size(A_new)= 2nmerge=2, j=2, d_min = D(1,3) = 11.3000; -> (1,2); last=4; upd(n,b);old D(A, j), D(B, j), j=2 = (28.1,13.2); new D(A', 2) = 13.2--> size(A_new)= 4nmerge=3, j=2, d_min = D(1,2) = 13.2000; -> (3,-2); last=5;--> size(A_new)= 5C agnes(n=5, method = 6, ..): |par| = 4, alpha[1:4] = (0.5,0.5,0,-0.5); 4 merging stepsnmerge=0, j=2, d_min = D(1,4) = 3.40000; -> (-1,-4); last=4; upd(n,b);old D(A, j), D(B, j), j=2 = (31.5,28.1); new D(A', 2) = 28.1old D(A, j), D(B, j), j=3 = (14.7,11.3); new D(A', 3) = 11.3old D(A, j), D(B, j), j=5 = (18.3,14.9); new D(A', 5) = 14.9--> size(A_new)= 2nmerge=1, j=2, d_min = D(3,5) = 3.60000; -> (-3,-5); last=5;old D(A, j), D(B, j), j=1 = (11.3,14.9); new D(A', 1) = 11.3old D(A, j), D(B, j), j=2 = (16.8,13.2); new D(A', 2) = 13.2--> size(A_new)= 2nmerge=2, j=2, d_min = D(1,3) = 11.3000; -> (1,2); last=4; upd(n,b);old D(A, j), D(B, j), j=2 = (28.1,13.2); new D(A', 2) = 13.2--> size(A_new)= 4nmerge=3, j=2, d_min = D(1,2) = 13.2000; -> (3,-2); last=5;--> size(A_new)= 5[1] TRUEattr(,"fits")attr(,"fits")$sCall: agnes(x = d, method = method, trace.lev = trace.lev)Agglomerative coefficient: 0.587879Order of objects:[1] D F E IRL GRHeight (summary):Min. 1st Qu. Median Mean 3rd Qu. Max.3.40 3.55 7.45 7.88 11.78 13.20Available components:[1] "order" "height" "ac" "merge" "diss" "call"[7] "method" "order.lab"attr(,"fits")$fCall: agnes(x = d, method = "flex", par.method = par.meth[[method]], trace.lev = trace.lev)Agglomerative coefficient: 0.587879Order of objects:[1] D F E IRL GRHeight (summary):Min. 1st Qu. Median Mean 3rd Qu. Max.3.40 3.55 7.45 7.88 11.78 13.20Available components:[1] "order" "height" "ac" "merge" "diss" "call"[7] "method" "order.lab">> stopifnot(chk(agr5), chk(agr5, "complete", trace = 2), chk(agr5, "weighted"),+ chk(agr8), chk(agr8, "complete"), chk(agr8, "weighted", trace.lev=2),+ chk(agriculture), chk(agriculture, "complete"),+ chk(ruspini), chk(ruspini, "complete"), chk(ruspini, "weighted"))C agnes(n=5, method = 2, ..): 4 merging stepsC agnes(n=5, method = 6, ..): |par| = 4, alpha[1:4] = (0.5,0.5,0,-0.5); 4 merging stepsC agnes(n=5, method = 3, ..): 4 merging stepsnmerge=0, j=2, d_min = D(1,4) = 3.40000; last=4; upd(n,b); size(A_new)= 2nmerge=1, j=2, d_min = D(3,5) = 3.60000; last=5; size(A_new)= 2nmerge=2, j=2, d_min = D(2,3) = 16.8000; last=4; size(A_new)= 3nmerge=3, j=2, d_min = D(1,2) = 31.5000; last=3; size(A_new)= 5C agnes(n=5, method = 6, ..): |par| = 4, alpha[1:4] = (0.5,0.5,0,0.5); 4 merging stepsnmerge=0, j=2, d_min = D(1,4) = 3.40000; last=4; upd(n,b); size(A_new)= 2nmerge=1, j=2, d_min = D(3,5) = 3.60000; last=5; size(A_new)= 2nmerge=2, j=2, d_min = D(2,3) = 16.8000; last=4; size(A_new)= 3nmerge=3, j=2, d_min = D(1,2) = 31.5000; last=3; size(A_new)= 5C agnes(n=5, method = 5, ..): 4 merging stepsC agnes(n=5, method = 6, ..): 4 merging stepsC agnes(n=8, method = 2, ..): 7 merging stepsC agnes(n=8, method = 6, ..): |par| = 4, alpha[1:4] = (0.5,0.5,0,-0.5); 7 merging stepsC agnes(n=8, method = 3, ..): 7 merging stepsC agnes(n=8, method = 6, ..): |par| = 4, alpha[1:4] = (0.5,0.5,0,0.5); 7 merging stepsC agnes(n=8, method = 5, ..): 7 merging stepsnmerge=0, j=2, d_min = D(1,4) = 3.40000; last=4; upd(n,b); size(A_new)= 2nmerge=1, j=2, d_min = D(3,5) = 3.60000; last=5; size(A_new)= 2nmerge=2, j=2, d_min = D(1,6) = 5.40000; last=6; upd(n,b); size(A_new)= 3nmerge=3, j=2, d_min = D(2,7) = 6.70000; last=7; upd(n,b); size(A_new)= 2nmerge=4, j=2, d_min = D(1,8) = 7.75000; last=8; upd(n,b); size(A_new)= 4nmerge=5, j=2, d_min = D(2,3) = 11.6500; last=7; size(A_new)= 4nmerge=6, j=2, d_min = D(1,2) = 18.3750; last=5; size(A_new)= 8C agnes(n=8, method = 6, ..): 7 merging stepsnmerge=0, j=2, d_min = D(1,4) = 3.40000; last=4; upd(n,b); size(A_new)= 2nmerge=1, j=2, d_min = D(3,5) = 3.60000; last=5; size(A_new)= 2nmerge=2, j=2, d_min = D(1,6) = 5.40000; last=6; upd(n,b); size(A_new)= 3nmerge=3, j=2, d_min = D(2,7) = 6.70000; last=7; upd(n,b); size(A_new)= 2nmerge=4, j=2, d_min = D(1,8) = 7.75000; last=8; upd(n,b); size(A_new)= 4nmerge=5, j=2, d_min = D(2,3) = 11.6500; last=7; size(A_new)= 4nmerge=6, j=2, d_min = D(1,2) = 18.3750; last=5; size(A_new)= 8C agnes(n=12, method = 2, ..): 11 merging stepsC agnes(n=12, method = 6, ..): |par| = 4, alpha[1:4] = (0.5,0.5,0,-0.5); 11 merging stepsC agnes(n=12, method = 3, ..): 11 merging stepsC agnes(n=12, method = 6, ..): |par| = 4, alpha[1:4] = (0.5,0.5,0,0.5); 11 merging stepsC agnes(n=75, method = 2, ..): 74 merging stepsC agnes(n=75, method = 6, ..): |par| = 4, alpha[1:4] = (0.5,0.5,0,-0.5); 74 merging stepsC agnes(n=75, method = 3, ..): 74 merging stepsC agnes(n=75, method = 6, ..): |par| = 4, alpha[1:4] = (0.5,0.5,0,0.5); 74 merging stepsC agnes(n=75, method = 5, ..): 74 merging stepsC agnes(n=75, method = 6, ..): 74 merging steps>> showProc.time()Time (user system elapsed): 0.04 0.001 0.041>> ## an invalid "flexible" case - now must give error early:> x <- rbind(c( -6, -9), c( 0, 13),+ c(-15, 6), c(-14, 0), c(12,-10))> (dx <- daisy(x, "manhattan"))Dissimilarities :1 2 3 42 283 24 224 17 27 75 19 35 43 36Metric : manhattanNumber of objects : 5> a.x <- tryCatch(agnes(dx, method="flexible", par = -.2),+ error = function(e)e)> ## agnes(method=6, par.method=*) lead to invalid merge; step 4, D(.,.)=-26.1216> if(!inherits(a.x, "error")) stop("invalid 'par' in \"flexible\" did not give error")> if(!all(vapply(c("par[.]method", "merge"), grepl, NA, x=a.x$message)))+ stop("error message did not contain expected words")>>> proc.time()user system elapsed0.767 0.094 0.859