## ----echo = FALSE, message = FALSE, warning=FALSE-----------------------------
library(dendextend)
library(knitr)
knitr::opts_chunk$set(
   cache = TRUE,
   dpi = 75,
   fig.width = 6, fig.height = 6,
  # comment = "#>",
  tidy = FALSE)

# https://stackoverflow.com/questions/24091735/why-pandoc-does-not-retrieve-the-image-file
# < ! -- rmarkdown v1 -->


## ----fig.show='hold', fig.width=8, fig.height=3-------------------------------
# install.packages("dendextend")
library(dendextend)

dend <- as.dendrogram(hclust(dist(USArrests[1:5,])))
# Like: 
# dend <- USArrests[1:5,] %>% dist %>% hclust %>% as.dendrogram

# By default, the dend has no colors to the labels
labels_colors(dend)
par(mfrow = c(1,2))
plot(dend, main = "Original dend")

# let's add some color:
labels_colors(dend) <- 1:5
# Now each state has a color
labels_colors(dend) 
plot(dend, main = "A color for every state")

## ----fig.show='hold', fig.width=8, fig.height=3-------------------------------
# install.packages("dendextend")
library(dendextend)

small_iris <- iris[c(1, 51, 101, 2, 52, 102), ]
dend <- as.dendrogram(hclust(dist(small_iris[,-5])))
# Like: 
# dend <- small_iris[,-5] %>% dist %>% hclust %>% as.dendrogram

# By default, the dend has no colors to the labels
labels_colors(dend)
par(mfrow = c(1,2))
plot(dend, main = "Original dend")

# Let's add some color:
colors_to_use <- as.numeric(small_iris[,5])
colors_to_use
# But sort them based on their order in dend:
colors_to_use <- colors_to_use[order.dendrogram(dend)]
colors_to_use
# Now we can use them
labels_colors(dend) <- colors_to_use
# Now each state has a color
labels_colors(dend) 
plot(dend, main = "A color for every Species")

## -----------------------------------------------------------------------------
 # define dendrogram object to play with:
 hc <- hclust(dist(USArrests[1:5,]), "ave")
 dend <- as.dendrogram(hc)

 library(dendextend)
 par(mfrow = c(1,2), mar = c(5,2,1,0))
 dend <- dend %>%
          color_branches(k = 3) %>%
          set("branches_lwd", c(2,1,2)) %>%
          set("branches_lty", c(1,2,1))
 
 plot(dend)

 dend <- color_labels(dend, k = 3)
 # The same as:
 # labels_colors(dend)  <- get_leaves_branches_col(dend)
 plot(dend)

## ----fig.show='hold', fig.width=8, fig.height=3-------------------------------
# install.packages("dendextend")
library(dendextend)

dend <- as.dendrogram(hclust(dist(USArrests[1:5,])))
# Like: 
# dend <- USArrests[1:5,] %>% dist %>% hclust %>% as.dendrogram

dend1 <- color_branches(dend, k = 3)
dend2 <- color_labels(dend, k = 3)

par(mfrow = c(1,2))
plot(dend1, main = "Colored branches")
plot(dend2, main = "Colored labels")

## -----------------------------------------------------------------------------
# install.packages("dendextend")
library(dendextend)

dend <- as.dendrogram(hclust(dist(USArrests[1:5,])))
# Like: 
# dend <- USArrests[1:5,] %>% dist %>% hclust %>% as.dendrogram

labels(dend)
labels(dend) <- 1:5
labels(dend)

## ----fig.show='hold', fig.width=8, fig.height=4-------------------------------
# install.packages("dendextend")
library(dendextend)

dend <- as.dendrogram(hclust(dist(USArrests[1:5,])))
# Like: 
# dend <- USArrests[1:5,] %>% dist %>% hclust %>% as.dendrogram

# By default, the dend has no text size to it (showing only the first leaf)
get_leaves_nodePar(dend)[[1]]
par(mfrow = c(1,2), mar = c(10,4,4,2))
plot(dend, main = "Original dend")

# let's increase the size of the labels:
dend <- set(dend, "labels_cex", 2)
# Now each state has a larger label
get_leaves_nodePar(dend)[[1]]
plot(dend, main = "A larger font for labels")

## -----------------------------------------------------------------------------
# install.packages("dendextend")
library(dendextend)

dend <- as.dendrogram(hclust(dist(USArrests[1:5,])))
# Like: 
# dend <- USArrests[1:5,] %>% dist %>% hclust %>% as.dendrogram

# midpoint for all nodes
get_nodes_attr(dend, "midpoint")
# Perhaps also for the height:
get_nodes_attr(dend, "height")

## ----echo = FALSE-------------------------------------------------------------
test0 <- structure(c(0.641122711554543, 1.23425751165366, -0.325822271157288, 
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NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
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NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, -0.285743549594148, 0.118005712942751, -0.341535589078191, 
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NA, NA, -0.231912267498498, -0.238800838323507, -0.342668639895834, 
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0.401469427915879, -0.574781090274838, 2.77796112661622, NA, 
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2.69702217635144, -0.749773851185589, -0.950822394693504, 2.20054435402863, 
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9.13249439800626, 0.410287565674152, 0.246334858379004, 2.87536688078465, 
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3.92574166820804, -0.859739161486886, 1.13068786332753, -0.142268715086565, 
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NA, -0.438313068833612, -0.00321822919649932, -0.347909112419527, 
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0.938729985862128, -0.563757891283266, 2.40020967811283, NA, 
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1.89675400793347, -0.739740914433285, -0.86351610783612, 2.45487143163875, 
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0.701255541661237, -0.383888307390535, -0.336044529662242, 0.393139806862448, 
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1.22704897451653, 0.905058737811027, -1.00553374032088, 0.687598431306886, 
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NA, -0.660520123168617, 0.413765105889694, -0.338713206498253, 
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NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, -0.854113211462064, 0.871787564861266, -0.33869026248453, 
0.0132028881163558, 0.856647894495692, NA, NA, NA, NA, NA, NA, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, -0.192444473424345, 
0.996518302280702, -0.338706120846956, 0.61084537376689, 0.906846534151001, 
NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
NA, NA, -0.49415348164232, -0.462623679297695, -0.338721979209383, 
0.400563758445406, -0.544670169505291, -0.743629438673717, 1.66116863292341, 
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0.40153136206778, -0.338686213540932, -0.186011273767155, -0.557760616696564, 
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0.128110937603993, -0.281649052183906, -0.322001588726745, -0.042581034355684, 
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NA, NA, 0.273200689078779, -0.359805219434367, -0.338649098224616, 
0.511238292825134, -0.574658400325463, -0.752282409309373, 1.34239477747488, 
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0.1942071716789, -0.386116810797702, -0.360182926269214, -0.258642970505114, 
1.60778851126204, -0.369616420336416, -0.817241331571407, -0.125516294714086, 
-0.389829772775058, 0.0101558118433854, -0.631403582709469, 0.165151142034448, 
NA, NA, 1.75597248509856, 1.3422023930688, -0.338599329959555, 
3.77613705702713, -0.612215227974824, -0.760450124254245, 1.27570393140078, 
0.804313816672775, -1.00740478540572, -0.0523199885495147, -0.411384118750968, 
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-0.643898014289614, 0.0659423511102981, NA, NA, -0.244617900283939, 
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0.0336556566235384, -0.417885648282802, -0.337053364367666, -0.49546548066686, 
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NA, NA, -0.976902287602302, 0.0237427792451862, -0.338639819395537, 
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0.928450549270229, -1.01066069850612, 0.28360836509203, 0.790068986325092, 
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1.33407821779525, -0.366909422595968, -0.847391533292537, -0.270698040473154, 
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NA, NA, -0.0259999426132211, 0.543880266790157, -0.338612826438216, 
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0.919024748196333, -1.00782466560193, 0.301297671577668, 0.495727012974764, 
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0.764956997013884, -0.338647411164783, -0.329888168460803, -0.53681299112446, 
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0.263504327879781, -0.380797377544383, -0.335130081924659, -0.319478560468005, 
1.70386111547821, -0.367909834804395, -0.858893433528369, -0.0628589097022777, 
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NA, NA, 0.899609804731586, 0.179485829391368, -0.33859595583989, 
1.03140860440986, -0.559734611511995, -0.750382202445463, 1.2002048603735, 
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1.14841903527445, -0.373323830285291, -0.835382196281596, -0.209568884364073, 
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NA, NA, -0.949522741241089, -0.431758807578255, -0.338640662925453, 
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1.13864089114445, NA, NA, NA, -0.340059800523034, 0.658162500387322, 
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1.76022787716632, -0.677216498503335, -0.0980277338893388, NA, 
NA, -1.05845830592531, -0.502557663070903, -0.338596799369807, 
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0.27725478744702, -0.338426406326718, 4.00855357922456, -0.561141143444366, 
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NA, NA, -0.0671794624991483, 0.913824493047251, -0.33849388872002, 
1.39663456786296, -0.581084796223364, -0.748910886459122, 1.21320747816153, 
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0.277093832020095, -0.338579928771481, 1.93893978632363, -0.559402378969349, 
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0.969060563639134, -0.373441525839223, -0.863587223698138, -0.253887522543156, 
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NA, NA, 0.50268447077147, 0.520964681549955, -0.338482922831109, 
3.07888749043484, -0.58931543308279, -0.747998035633602, 1.34910580601064, 
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1.61549232163043, -0.374088851385852, -0.86295292772925, -0.250831064737702, 
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NA, NA, 0.561997489356783, 0.360404132306868, -0.33856643229282, 
1.49624164880472, -0.596985882224324, -0.756848607051219, 1.32268113115109, 
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-0.523118509014876, 0.0521633523708328, NA, NA, 0.102318031273258, 
0.663396733756286, -0.338420501617304, 0.710452454708645, -0.592349176957611, 
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NA, NA, -0.159841497875308, -0.0824620223384703, -0.338458460463537, 
2.13815394820714, -0.573069989263906, -0.757779598276394, 1.45606282329929, 
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NA, NA, -0.0804201271029547, -0.680059960149504, -0.338598486429639, 
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0.0907445488413357, NA, NA, 2.30469509536822, 2.0209441141375, 
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NA, NA, -0.50936714345912, 1.29903345977391, -0.33856643229282, 
1.2195553128554, -0.543549794069506, -0.7508616272935, 1.35413907741246, 
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0.746970604130502, -0.487140441421054, 1.18861861746503, NA, 
NA, NA, -0.555372852725193, -1.37557427460294, 3.39809986025518, 
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1.71338474383114, NA, NA, NA, -0.511655567772838, -1.34815221335411, 
2.00627549839295, -0.709044735556283, -0.527811186757286, -0.398440308729829, 
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0.499409546442009, -0.459268380028652, 1.73837360699143, NA, 
NA, NA, -0.360179135915996, -1.40454852799793, 2.96789960295231, 
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2.54634684917416, NA, NA, NA, 0.0202616890130045, -1.37867865889526, 
0.150509682576654, -0.723172339869856, -0.546741166522954, -0.404271151476228, 
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0.184511881062246, -0.471003984825452, 1.34688141748021, NA, 
NA, NA, 1.16779134133779, -1.38833674336026, 4.44407695644255, 
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-0.853903638573118, 0.0991333539867875, 0.68161448490074, -0.451933627030651, 
1.70089031225099, NA, NA, NA, -1.16141377040868, -1.35349865296866, 
0.951863103042783, -0.702658814922573, -0.526894515946189, -0.395071377365243, 
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0.204316765677325, -0.456334478829451, 1.53429789118239, NA, 
NA, NA, 2.06201170986725, -1.39799482782526, 2.65579353392866, 
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1.63008853329684, NA, NA, NA, -0.850176397428048, -1.38350770112776, 
3.70177063011603, -0.720274880559794, -0.574687500986132, -0.386519474670525, 
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-0.44459887403265, 1.95494375438061, NA, NA, NA, 0.621142792783853, 
-1.4100674334065, 0.142074383413852, -0.722684265173241, -0.554937852611599, 
-0.387102558945165, 0.444429798640543, 0.44721348098445, -0.614492683907219, 
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6.10815286943251, -0.390321701847446, 3.77496595455512, NA, NA, 
NA, 1.48160544036248, -1.39402811456285, 0.0239801951346332, 
-0.71807024383495, -0.556780894454016, -0.398699457296336, 0.457482749142594, 
0.438001189062128, -0.701857229994927, -1.59134580932855, 0.263445094246494, 
1.86677745239051, 2.94799558408199, -0.80501312782908, -0.371028766983607, 
-0.860288884659922, -0.12857275251954, 0.200355788754309, -0.425528516237849, 
2.52135798601387, NA, NA, NA, 2.06201170986725, -1.39799482782526, 
2.65579353392866, -0.720823826250318, -0.565993678611046, -0.390860213159511, 
0.354791429366983, 0.437869315762626, -0.774172385892316, -1.58943648735867, 
0.0672171120129427, 1.57565938729994, 2.36199345481817, -0.805383757881167, 
-0.367321357034732, -0.856990545621705, -0.0108991270095587, 
0.937097496435265, -0.44459887403265, 1.63008853329684, NA, NA, 
NA), .Dim = c(23L, 96L), .Dimnames = list(c("varA", "varB", "varC", 
"varD", "varE", "varF", "var1", "var2", "var3", "var4", "var5", 
"var6", "var7", "var8", "var9", "var10", "var11", "var12", "var13", 
"var14", "var15", "var16", "var17"), c("2005", "2004", "2003", 
"2002", "2001", "2000", "1999", "1998", "1997", "1996", "1995", 
"1994", "1993", "1992", "1991", "1990", "1989", "1988", "1987", 
"1986", "1985", "1984", "1983", "1982", "1981", "1980", "1979", 
"1978", "1977", "1976", "1975", "1974", "1973", "1972", "1971", 
"1970", "1969", "1968", "1967", "1966", "1965", "1964", "1963", 
"1962", "1961", "1960", "1959", "1958", "1957", "1956", "1955", 
"1954", "1953", "1952", "1951", "1950", "1949", "1948", "1947", 
"1946", "1945", "1944", "1943", "1942", "1941", "1940", "1939", 
"1938", "1937", "1936", "1935", "1934", "1933", "1932", "1931", 
"1930", "1929", "1928", "1927", "1926", "1925", "1924", "1923", 
"1922", "1921", "1920", "1919", "1918", "1917", "1916", "1915", 
"1914", "1913", "1912", "1911", "1910")), "`scaled:center`" = structure(c(0.959427522125, 
0.820192521135417, 40.1571612729063, 39.8070527524375, -2.214884375, 
90.7399054945055, -2.35450769230769, -6.9422956043956, 13.8163230769231, 
2.86136813186813, 0.31370989010989, 2.35576373626374, 2.31022417582418, 
3.05251758241758, 0.643089010989011, 2.04963406593407, 0.0237131868131868, 
0.0351835164835165, 0.0386076923076923, 0.0211604395604396, 0.0468142857142857, 
0.0102808510638298, 0.0371219512195122), .Names = c("varA", "varB", 
"varC", "varD", "varE", "varF", "var1", "var2", "var3", "var4", 
"var5", "var6", "var7", "var8", "var9", "var10", "var11", "var12", 
"var13", "var14", "var15", "var16", "var17")), "`scaled:scale`" = structure(c(0.336695863341967, 
0.579825121668287, 118.549440950462, 90.3550221019193, 41.2361771994966, 
154.351615905927, 23.8413529531975, 15.924375957359, 13.5753008870365, 
1.78073685509237, 0.676763825874441, 5.97936098351871, 4.07984865687008, 
3.77735154533183, 1.69929953441283, 2.36482663232164, 0.0654352236249139, 
0.0504925940966401, 0.0681686213750208, 0.0240106961309648, 0.0725742137660437, 
0.019589600594036, 0.00911700367980407), .Names = c("varA", "varB", 
"varC", "varD", "varE", "varF", "var1", "var2", "var3", "var4", 
"var5", "var6", "var7", "var8", "var9", "var10", "var11", "var12", 
"var13", "var14", "var15", "var16", "var17")))


## ----eval = FALSE-------------------------------------------------------------
#  
#  test <- test0
#  rnames <- test[,1]
#  test <- data.matrix(test[,2:ncol(test)]) # to matrix
#  rownames(test) <- rnames
#  test <- scale(test, center=T, scale=T) # data standarization
#  test <- t(test) # transpose
#  
#  
#  ## Creating a color palette & color breaks
#  
#  my_palette <- colorRampPalette(c("forestgreen", "yellow", "red"))(n = 299)
#  
#  col_breaks = c(seq(-1,-0.5,length=100),  # forestgreen
#                 seq(-0.5,0.5,length=100), # yellow
#                 seq(0.5,1,length=100))    # red
#  
#  # distance & hierarchical clustering
#  distance = dist(test, method ="euclidean")
#  hcluster = hclust(distance, method ="ward.D")
#  
#  
#  dend1 <- as.dendrogram(hcluster)
#  
#  # Get the dendextend package
#  if(!require(dendextend)) install.packages("dendextend")
#  library(dendextend)
#  # get some colors
#  cols_branches <- c("darkred", "forestgreen", "orange", "blue")
#  # Set the colors of 4 branches
#  dend1 <- color_branches(dend1, k = 4, col = cols_branches)
#  # or with:
#  # dend1 <- set(dend1, "branches_k_color", k = 4, value = cols_branches)
#  
#  # Get the colors of the tips of the dendrogram:
#  # col_labels <- cols_branches[cutree(dend1, k = 4)] # this may need tweaking in various cases - the following is a more general solution.
#  
#  col_labels <- get_leaves_branches_col(dend1)
#  # But due to the way heatmap.2 works - we need to fix it to be in the
#  # order of the data!
#  col_labels <- col_labels[order(order.dendrogram(dend1))]
#  
#  dend1
#  # plot(dend1)
#  # a <- heights_per_k.dendrogram(dend1)
#  # a2 <- heights_per_k.dendrogram(dend1)
#  # nleaves(dend1)
#  
#  
#  # Creating Heat Map
#  # if(!require(gplots)) install.packages("gplots")
#  library(gplots)
#  heatmap.2(test,
#     	main = paste( "test"),
#  		trace="none",
#  		margins =c(5,7),
#  		col=my_palette,
#  		breaks=col_breaks,
#  		dendrogram="row",
#  		Rowv = dend1,
#  		Colv = "NA",
#  		key.xlab = "Concentration (index)",
#  		cexRow =0.6,
#  		cexCol = 0.8,
#  		na.rm = TRUE,
#  		RowSideColors = col_labels # to add nice colored strips		
#        # colRow = col_labels # to add nice colored labels - only for qplots 2.17.0 and higher
#  		)
#  		
#  

## ----eval = FALSE-------------------------------------------------------------
#  dendextend::assign_dendextend_options()
#  # This populates the dendextend::dendextend_options() space

## ----fig.width=10, fig.height=10----------------------------------------------
# install.packages("dendextend")
# install.packages("circlize")
library(dendextend)
library(circlize)

# create a dendrogram
hc <- hclust(dist(datasets::mtcars))
dend <- as.dendrogram(hc)

# modify the dendrogram to have some colors in the branches and labels
dend <- dend %>% 
   color_branches(k=4) %>% 
   color_labels

# plot the radial plot
par(mar = rep(0,4))
# circlize_dendrogram(dend, dend_track_height = 0.8) 
circlize_dendrogram(dend, labels_track_height = NA, dend_track_height = .3) 


## -----------------------------------------------------------------------------
hc <- hclust(dist(USArrests[1:4,]), "ave")
dend <- as.dendrogram(hc)
heights_per_k.dendrogram(dend)

## -----------------------------------------------------------------------------
aa1 <- c(2,4,6,8)
bb1 <- c(1,3,7,11)
aa2 <- c(3,6,9,12)
bb2 <- c(3,5,7,9)
data.main <- data.frame(aa1,bb1,aa2,bb2)
d1 <- dist(t(data.main))
hcl1 <- hclust(d1)
# plot(hcl1)

dend <- as.dendrogram(hcl1)
col_aa_red <- ifelse(grepl("aa", labels(dend)), "red", "blue")
dend2 <- assign_values_to_leaves_edgePar(dend=dend, value = col_aa_red, edgePar = "col")
plot(dend2)


## -----------------------------------------------------------------------------
## mtcars example

# Create the dend:
dend <- as.dendrogram(hclust(dist(mtcars)))

# Create a vector giving a color for each car to which company it belongs to
car_type <- rep("Other", length(rownames(mtcars)))
is_x <- grepl("Merc", rownames(mtcars))
car_type[is_x] <- "Mercedes"
is_x <- grepl("Mazda", rownames(mtcars))
car_type[is_x] <- "Mazda"
is_x <- grepl("Toyota", rownames(mtcars))
car_type[is_x] <- "Toyota"
car_type <- factor(car_type)
n_car_types <- length(unique(car_type))
cols_4 <- colorspace::rainbow_hcl(n_car_types, c = 70, l  = 50)
col_car_type <- cols_4[car_type]

# extra: showing the various clusters cuts 
k234 <- cutree(dend, k = 2:4)

# color labels by car company:
labels_colors(dend) <- col_car_type[order.dendrogram(dend)]
# color branches based on cutting the tree into 4 clusters:
dend <- color_branches(dend, k = 4)

### plots
par(mar = c(12,4,1,1))
plot(dend)
colored_bars(cbind(k234[,3:1], col_car_type), dend, rowLabels = c(paste0("k = ", 4:2), "Car Type"))

# horiz version:
# dend <- sort(dend)
par(mar = c(4,1,1,12))
plot(dend, horiz = TRUE)
colored_bars(cbind(k234[,3:1], col_car_type), dend, rowLabels = c(paste0("k = ", 4:2), "Car Type"), horiz = TRUE)
legend("topleft", legend = levels(car_type), fill = cols_4)


## -----------------------------------------------------------------------------

# Create the dend:
hc <- hclust(dist(USArrests), "ave")
d <- as.dendrogram(hc)
library(dendextend)
d <- d %>% color_branches(k=3) %>% color_labels

# horiz normal version
par(mar = c(3,1,1,7))
plot(d, horiz  = TRUE)

# horiz mirror version
par(mar = c(3,7,1,1))
plot_horiz.dendrogram(d, side = TRUE)