Relassify continuous raster data into binned class

Question

I would like to:

1. Reclassify the raster ras into nine classes using reclassify

2. Provide a colorkey with values written beside each colour (see sample plot below). The colorkey should not be split, as in the sample plot, but rather shown as a single colour ramp with 9 colours.

3. Display the data using levelplot function (this I can do)

Thanks for your help. AEZ

library(rasterVis)

Please use these colors:

col <- colorRampPalette(c("yellow4", "yellow", "orange", "red3", "darkred"))
levelplot(reclassras, col.regions = col)

Below is the dput of my raster layer:

 ras=new("RasterLayer"
        , file = new(".RasterFile"
        , name = ""
        , datanotation = "FLT4S"
        , byteorder = "little"
        , nodatavalue = -Inf
        , NAchanged = FALSE
        , nbands = 1L
        , bandorder = "BIL"
        , offset = 0L
        , toptobottom = TRUE
        , blockrows = 4L
        , blockcols = 230L
        , driver = ""
        , open = FALSE
    )
        , data = new(".SingleLayerData"
        , values = c(NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, 0.693928846555399, 0.788672037295368, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, 0.63077312659247, 0.646355947246998, 0.877268680738184, 
    1.18198745233929, 1.17243141777504, 1.16780606010241, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, 0.796574503892096, 0.619565545705973, 0.548990505935034, 
    0.595313378137405, 0.661379946396662, 0.780858688754648, 1.32843871685037, 
    1.3513059907622, 1.47504896477768, 1.33220740188043, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    1.02493198234592, 0.871180733341381, 0.588561527602423, 0.495423050558386, 
    0.398352388696117, 0.609004794796874, 0.757493518742196, 0.968962672868491, 
    1.3989459779932, 1.66210327179263, 1.4993019355018, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.605206815154586, 
    0.542575959157491, 0.509368162877491, 0.461856452801692, 0.543152629728101, 
    0.630122267439296, 0.70810504838076, 0.788478557501378, 0.918580431438071, 
    0.925176992886461, 0.712139151650403, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.523779588981426, 0.497759414675531, 
    0.539521493581999, 0.472379195067506, 0.503370029793095, 0.549265480778097, 
    0.570528210136693, 0.710933566259782, 0.726885712871992, 0.755087833088479, 
    0.692253167927366, 0.632483742020028, 0.572268262363865, 0.438810629423197, 
    0.495519373283201, 0.461307895792857, 0.413954466042644, 0.368257331706444, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.777296738735527, 
    0.750850589920605, 0.513284076851117, 0.491285172798063, 0.555785245510632, 
    0.611268469163931, 0.813189823687993, 0.756674620262126, 0.872121251992992, 
    0.613545590220432, 0.481851214001446, 0.496306521393404, 0.437621615262168, 
    0.339745859876615, 0.303638244461432, 0.311408628670555, 0.307152533981348, 
    0.31488062771456, 0.324014538449246, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, 0.682358704297568, 0.706551558881091, 0.502018311967365, 
    0.456684326929721, 0.473559918237202, 0.463389646751083, 0.441190726838794, 
    0.439217524749229, 0.584294316557062, 0.267633271553189, 0.256528025697032, 
    0.337787793432092, 0.330618969832041, 0.13803984358201, 0.157341965515659, 
    0.25899384267949, 0.217328457675264, 0.242480963818602, 0.272211051701126, 
    0.281644918669069, NA, NA, NA, NA, NA, NA, NA, NA, 0.414616765967516, 
    0.460428280883944, 0.439029889808256, 0.373948128082835, 0.352871572842356, 
    0.357951354005567, 0.328436868901166, 0.203201513096291, 0.141472917108049, 
    0.269096407445964, 0.15745212479733, 0.135179353417107, 0.219985246649717, 
    0.283005986377796, 0.209135929188723, 0.195612120899385, 0.163726230506747, 
    0.117276078938131, 0.169752099589576, 0.20586142557315, 0.244209631644345, 
    NA, NA, NA, NA, NA, 0.214238769725864, 0.208010897733397, 0.222208413054847, 
    0.212686463354896, 0.281732716326432, 0.300708262469288, 0.223204487650159, 
    0.200983714892431, 0.156651839437054, 0.224474592578023, 0.145079279318955, 
    0.137658404085203, 0.196204204670511, 0.157445860015357, 0.205907596393374, 
    0.250666664848486, 0.277186662044126, 0.265355210400489, 0.241808654124976, 
    0.199713317093066, 0.143711490248281, 0.0842822747178765, NA, 
    NA, NA, NA, 0.264092813395827, NA, 0.212441257972578, 0.189725290483582, 
    0.168955415365627, 0.158197543230828, 0.147705597579244, 0.157228804810736, 
    0.211249178305103, 0.222557582448186, 0.215124944446001, 0.210152099165574, 
    0.224764230646078, 0.192500267075076, 0.174923484036373, 0.121073670585186, 
    0.140937204004106, 0.213437474831745, 0.248947340425651, 0.265571783211699, 
    0.266099597629565, 0.254099129610638, 0.225777564711763, 0.178602219399, 
    NA, NA, NA, 0.245068225382459, 0.250977120426067, 0.255618295682899, 
    0.215763680642785, 0.192426673071868, 0.15695069948531, 0.113984884275593, 
    0.132801862169494, 0.166848777379759, 0.115940552527949, 0.157310632213977, 
    0.227022907248424, 0.239855727768449, 0.239340572413914, 0.231675634554819, 
    0.215388496476701, 0.185506053849589, 0.104971870404521, 0.112957653991221, 
    0.184468284077724, 0.222974948120878, 0.234747755547275, 0.240936436264378, 
    0.246124530363775, 0.242871371021741, NA, NA, NA, NA, 0.237419647069358, 
    0.238880206380025, 0.231523511204313, 0.179362897056799, 0.16381508377734, 
    0.133186183020653, 0.0908146529276369, 0.141301676274407, 0.17155039695241, 
    0.176667304881711, 0.192368230921037, 0.21608936753556, 0.226766198129308, 
    0.221609735358686, 0.196435659994756, 0.18030618027393, 0.178648959768383, 
    0.131173639965412, 0.0673928945097901, 0.144030029855376, 0.183644454323076, 
    0.164135425763568, 0.177071512975595, 0.218027665373501, 0.24020227724051, 
    NA, NA, NA, NA, 0.222719673381422, 0.203163737836875, 0.193893900175302, 
    0.173629261933378, 0.118612596801245, 0.120337304279883, 0.132270235949265, 
    0.145957944294342, 0.158947316774427, 0.171811369315789, 0.178481215022077, 
    0.182769116915529, 0.193576475278923, 0.187526186900056, 0.116642925509998, 
    0.0810130524927432, 0.155361056173399, 0.148275096869829, 0.110248050354185, 
    0.150980011296809, 0.149035884104822, 0.0943587027445095, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, 0.155642765186448, 0.165539811602326, 
    0.138858875725954, 0.115966143137369, 0.110762436834703, 0.116558297180592, 
    0.109461897495481, 0.137020886546595, 0.130569369589671, 0.106845763992692, 
    0.139732412594499, 0.167204357520135, 0.121743769239998, 0.0978888268526515, 
    0.161034204706105, 0.182178539628265, 0.179821789305561, 0.183479109899686, 
    0.160540641903203, 0.112272216175425, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, 0.163697841087448, 0.17328205868045, 0.160040552656876, 
    0.134655975429996, 0.12409849785916, 0.107880400167541, 0.0924636872864672, 
    0.103225290747982, 0.0767026155342135, 0.0661780888537736, 0.112966312114504, 
    0.16666404802081, 0.172067566098574, 0.172700784074864, 0.192001569629986, 
    0.206098509476636, 0.210359965210036, 0.209377663322926, 0.197655864616846, 
    0.180297988050893, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.181675191082483, 
    0.176935554759326, 0.16390655974363, 0.154194456563158, 0.142896144640483, 
    0.133243173249838, 0.114015642056713, 0.0928738807683648, 0.116223803463035, 
    0.146600649670514, 0.180171520048675, 0.197023191340036, 0.203375499409087, 
    NA, NA, NA, NA, 0.220951932247611, 0.216562385948588, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.176899006540279, 
    0.169734384672319, 0.164263225996517, 0.143295516102167, 0.13599420407605, 
    NA, 0.177143713627865, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 0.189498742688049, 
    0.185499135750397, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, NA, 
    NA, NA, NA, NA, NA, NA, NA, NA, NA, NA)
        , offset = 0
        , gain = 1
        , inmemory = TRUE
        , fromdisk = FALSE
        , isfactor = FALSE
        , attributes = list()
        , haveminmax = TRUE
        , min = 0.0661780888537736
        , max = 1.66210327179263
        , band = 1L
        , unit = ""
        , names = "myfile"
    )
        , legend = new(".RasterLegend"
        , type = character(0)
        , values = logical(0)
        , color = logical(0)
        , names = logical(0)
        , colortable = logical(0)
    )
        , title = character(0)
        , extent = new("Extent"
        , xmin = 73.39696
        , xmax = 96.59696
        , ymin = 33.98298
        , ymax = 49.18298
    )
        , rotated = FALSE
        , rotation = new(".Rotation"
        , geotrans = numeric(0)
        , transfun = function () 
    NULL
    )
        , ncols = 29L
        , nrows = 19L
        , crs = new("CRS"
        , projargs = "+proj=longlat +a=6378140 +b=6356755.288157528 +no_defs"
    )
        , history = list()
        , z = list()
    )

Answer 1

You can cut your raster, and then specify the colour breaks with at, and the colorkey breaks with a list containing at and labels, passed to the colorkey arg:

    levelplot(cut(ras, 9), col.regions=col, 
              at=0:9, margin=FALSE,
              colorkey=list(labels=list(at=0:8 + 0.5, labels=levels(cut(ras[], 9)))))

Above, we are saying that we want to split ras into 9 equal-width bins. These bins will be denoted by the numbers 1 through 9, and at=0:9 specifies that we want colours to change at values 0 through 9. To label the colorkey correctly, we pass a list called labels, with argument at indicating where we want the labels to be located, and argument labels providing the corresponding labels. Note that you can pass whatever you want to the labels element of the labels list passed to the colorkey argument (e.g. to match the format of your example plot, you might want to use something like labels=list(at=0:8 + 0.5, labels=sub('\\((.+),(.+)]', '>\\1 ~ \\2', levels(cut(ras[], 9))))).

You could instead use ratify to coerce the raster layer to a factor, and set the factor levels to the desired label text, but this can be a bit fiddly if levels are missing.