Plotweb三方网络

时间:2019-02-16 08:25:37

标签: r plot bipartite

我有以下矩阵(mat1mat2):

mat1<-structure(c(0.00161711655678567, 0.00671725338972509, 0.000497574325164821, 
0.00186590371936808, 0.0259982584898619, 0.00323423311357134, 
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0.00161711655678567, 0.000124393581291205, 0.000124393581291205, 
0.000373180743873616, 0.00211469088195049, 0.000248787162582411, 
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0, 0.000124393581291205, 0, 0, 0, 0, 0.000621967906456027, 0.000373180743873616, 
0, 0.000497574325164821, 0, 0.000124393581291205, 0, 0, 0, 0.0666749595720861, 
0, 0, 0, 0, 0.000621967906456027, 0.000124393581291205, 0, 0, 
0.000248787162582411, 0, 0, 0, 0, 0, 0, 0, 0.000248787162582411, 
0, 0, 0, 0, 0, 0.000124393581291205, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.000124393581291205, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0.000124393581291205, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0.00808558278392835, 0.000124393581291205, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.000124393581291205, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.00422938176390098, 
0, 0, 0, 0, 0.00671725338972509, 0, 0, 0.000248787162582411, 
0, 0, 0, 0, 0, 0.000124393581291205, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0.000995148650329643, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.00149272297549446, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.00111954223162085, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0.000248787162582411, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0.00174151013807688, 0, 0.000746361487747232, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0.000497574325164821, 0, 0, 0, 0.0120661773852469, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0.000124393581291205, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0.000124393581291205, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0), .Dim = c(79L, 32L), .Dimnames = list(c("Annonaceae", 
"Apocynaceae", "Araceae", "Arecaceae", "Asteraceae", "Boraginaceae", 
"Capparaceae", "Clethraceae", "Convolvulaceae", "Costaceae", 
"Dichapetalaceae", "Dilleniaceae", "Erythroxylaceae", "Euphorbiaceae", 
"Fabaceae", "Gesneriaceae", "Heliconiaceae", "Hypericaceae", 
"Lacistemataceae", "Lamiaceae", "Lauraceae", "Malpighiaceae", 
"Malvaceae", "Marantaceae", "Melastomataceae", "Meliaceae", "Menispermaceae", 
"Moraceae", "Musaceae", "Myrtaceae", "Nyctaginaceae", "Phytolaccaceae", 
"Piperaceae", "Poaceae", "Rhamnaceae", "Rubiaceae", "Sapindaceae", 
"Sapotaceae", "Simaroubaceae", "Solanaceae", "Urticaceae", "Vitaceae", 
"Acanthaceae", "Amaryllidaceae", "Anacardiaceae", "Athyriaceae", 
"Burseraceae", "Clusiaceae", "Commelinaceae", "Cyclanthaceae", 
"Elaeocarpaceae", "Gnetaceae", "Pteridaceae", "Salicaceae", "Smilacaceae", 
"Tiliaceae", "Amaranthaceae", "Bignoniaceae", "Myristicaceae", 
"Verbenaceae", "Violaceae", "Lecythidaceae", "Siparunaceae", 
"Caricaceae", "Bromeliaceae", "Passifloraceae", "Selaginellaceae", 
"Bombacaceae", "Cannaceae", "Rutaceae", "Myrsinaceae", "Marcgraviaceae", 
"Ulmaceae", "Flacourtiaceae", "Aristolochiaceae", "Cactaceae", 
"Cycadaceae", "Hernandiaceae", "Sterculiaceae"), c("Erebidae", 
"Noctuidae", "Pyralidae", "Geometridae", "Sphingidae", "Apatelodidae", 
"Notodontidae", "Saturniidae", "Tortricidae", "Oecophoridae", 
"Limacodidae", "Thyrididae", "Megalopygidae", "Choreutidae", 
"Gelechiidae", "Bombycidae", "Crambidae", "Lasiocampidae", "Cossidae", 
"Nolidae", "Depressariidae", "Uraniidae", "Yponomeutidae", "Glyphipterigidae", 
"Gracillariidae", "Nymphalidae", "Hesperiidae", "Riodinidae", 
"Papilionidae", "Lycaenidae", "Pieridae", "Hedylidae")))

mat2<-structure(c(0.0409356725146199, 0.00584795321637427, 0.00292397660818713, 
0.00292397660818713, 0.0964912280701754, 0, 0, 0, 0, 0, 0.0160818713450292, 
0, 0.00584795321637427, 0.00292397660818713, 0.0233918128654971, 
0, 0, 0, 0, 0, 0.054093567251462, 0, 0.00146198830409357, 0.00292397660818713, 
0.0789473684210526, 0, 0, 0, 0, 0, 0.00146198830409357, 0, 0.00146198830409357, 
0.00146198830409357, 0.00730994152046784, 0, 0, 0, 0, 0, 0.0204678362573099, 
0.00146198830409357, 0.00146198830409357, 0, 0.0614035087719298, 
0.0043859649122807, 0.00146198830409357, 0, 0, 0, 0.0292397660818713, 
0, 0, 0.00146198830409357, 0.0116959064327485, 0, 0, 0, 0, 0, 
0.0131578947368421, 0, 0, 0, 0.010233918128655, 0, 0, 0, 0, 0, 
0.0043859649122807, 0, 0, 0.00584795321637427, 0.0160818713450292, 
0, 0, 0, 0, 0, 0.00730994152046784, 0.00146198830409357, 0, 0, 
0.00730994152046784, 0, 0, 0, 0, 0, 0.0292397660818713, 0, 0, 
0.00146198830409357, 0.00146198830409357, 0, 0, 0.0043859649122807, 
0, 0, 0.00292397660818713, 0, 0, 0.00146198830409357, 0.010233918128655, 
0, 0, 0, 0, 0, 0.00584795321637427, 0.00292397660818713, 0.00292397660818713, 
0.0160818713450292, 0.0146198830409357, 0, 0, 0.0043859649122807, 
0, 0, 0.00146198830409357, 0, 0, 0, 0.00146198830409357, 0, 0, 
0, 0, 0, 0.0160818713450292, 0.00146198830409357, 0.0043859649122807, 
0.00146198830409357, 0.010233918128655, 0, 0, 0, 0.00146198830409357, 
0, 0.0248538011695906, 0.00146198830409357, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0.00584795321637427, 0, 0, 0, 0, 0, 0.0131578947368421, 
0, 0.00146198830409357, 0.00146198830409357, 0.0292397660818713, 
0, 0, 0, 0, 0, 0.00146198830409357, 0, 0.00146198830409357, 0, 
0, 0, 0, 0, 0, 0, 0.0204678362573099, 0.00730994152046784, 0.00146198830409357, 
0.00584795321637427, 0.0818713450292398, 0, 0, 0, 0, 0, 0.043859649122807, 
0.00292397660818713, 0.0043859649122807, 0, 0.0190058479532164, 
0, 0, 0, 0, 0, 0.0116959064327485, 0.0043859649122807, 0, 0, 
0.0175438596491228, 0, 0, 0, 0, 0, 0.00146198830409357, 0.00146198830409357, 
0, 0, 0.00146198830409357, 0, 0, 0, 0, 0, 0, 0, 0, 0.00146198830409357, 
0.0043859649122807, 0, 0, 0, 0, 0, 0, 0.00146198830409357, 0, 
0, 0.00584795321637427, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 
0, 0, 0, 0, 0, 0, 0, 0, 0), .Dim = c(10L, 32L), .Dimnames = list(
    c("Braconidae", "Chalcididae", "Eulophidae", "Ichneumonidae", 
    "Tachinidae", "Phoridae", "Sarcophagidae", "Encyrtidae", 
    "Pteromalidae", "NA"), c("Erebidae", "Noctuidae", "Pyralidae", 
    "Geometridae", "Sphingidae", "Apatelodidae", "Notodontidae", 
    "Saturniidae", "Tortricidae", "Oecophoridae", "Limacodidae", 
    "Thyrididae", "Megalopygidae", "Choreutidae", "Gelechiidae", 
    "Bombycidae", "Crambidae", "Depressariidae", "Nymphalidae", 
    "Hesperiidae", "Riodinidae", "Lycaenidae", "Papilionidae", 
    "Pieridae", "Cossidae", "Glyphipterigidae", "Gracillariidae", 
    "Hedylidae", "Lasiocampidae", "Nolidae", "Uraniidae", "Yponomeutidae"
    )))

mat1中的

行代表生产者,而列是草食动物,值是它们相互作用的频率。 mat1用于创建底层网络。 mat2行是天敌,列是与mat1相同的草食动物。 mat 2是要在第一个矩阵上“堆叠”以创建三营养网络的第二个网络。

我想创建一个三方网络:enter image description here

使用下面生成的代码,底部图的上部节点与上部图的下部节点不匹配,也不以相同顺序出现。您会注意到堆积图只是第一幅图的一小部分。第二层中的所有蓝色节点应与相邻的黑色节点匹配并对齐,因此顶部图应延伸底部图的长度,并且边缘应与关联节点匹配。

两个网络中草食动物的结点丰度是相同的,并且是:

structure(c(11, 8, 8, 7, 6, 6, 5, 5, 3, 2, 2, 1, 1, 1, 1, 1, 
1, 0, 0, 0, 0, 0, 0, 0, 0, 12, 7, 2, 1, 1, 1, 0), .Names = c("Erebidae", 
"Noctuidae", "Pyralidae", "Geometridae", "Sphingidae", "Apatelodidae", 
"Notodontidae", "Saturniidae", "Tortricidae", "Oecophoridae", 
"Limacodidae", "Thyrididae", "Megalopygidae", "Choreutidae", 
"Gelechiidae", "Bombycidae", "Crambidae", "Lasiocampidae", "Cossidae", 
"Nolidae", "Depressariidae", "Uraniidae", "Yponomeutidae", "Glyphipterigidae", 
"Gracillariidae", "Nymphalidae", "Hesperiidae", "Riodinidae", 
"Papilionidae", "Lycaenidae", "Pieridae", "Hedylidae"))

我尝试了以下代码,但未成功:

library("bipartite")
plotweb(mat1, 
        method= "normal", 
        arrow= "down.center", 
        low.abun=plant.abun.vec ,
        high.abun = lep.abun.vec, 
        abuns.type = "independent",
        low.abun.col = adjustcolor("#4DAF4A", alpha.f = 0.9),  
        high.abun.col =c(rep(adjustcolor("#47b8ff", alpha.f = 0.9),25),rep( adjustcolor("#09257a", alpha.f = 0.9),7)),  
        
        bor.col.interaction =ifelse(df$weight<=0.0001243936,
                                      adjustcolor("#55AE3A", alpha.f = 0.3),
                                      adjustcolor("#55AE3A")),
        col.interaction = ifelse(df[,]<=0.0001243936,
                          adjustcolor("#55AE3A", alpha.f = 0.3),
                          adjustcolor("#0b5601", alpha.f=0.9)),
        bor.col.low="#4DAF4A", 
        low.plot=TRUE, 
        text.rot=90,
        text.low.col="#4DAF4A", text.high.col=c(rep("#47b8ff",25), rep("#09257a",7)),
        y.lim=c(0,5.5), empty=FALSE, labsize=1.5, high.lablength=4, low.lablength=4, 
        high.y=2.5)

plotweb(t(mat2), method="normal",
        high.abun=lep.abun.vec,
      
        low.y=3.2,high.y=4.9, add= TRUE,
        low.abun.col  =c(rep(adjustcolor("#47b8ff", alpha.f = 0.9),25),rep( adjustcolor("#09257a", alpha.f = 0.9),7)),  
        high.abun.col=c(rep(adjustcolor("#ffd500", alpha.f = 0.9),4),rep( adjustcolor("#ffc000", alpha.f = 0.9),3)),  
        text.high.col=c(rep(adjustcolor("#ffd500", alpha.f = 0.9),4),rep(adjustcolor("#ffc000", alpha.f = 0.9),3)),        
        low.lab.dis=0, arrow="down.center", adj.low=c(0.5,1.1),low.plot=TRUE, 
        empty=FALSE, text.rot=90, low.lablength=0, labsize=1.5, 
        high.lablength = 4,
        bor.col.interaction =ifelse(df1$weight<=0.001462,
                                    adjustcolor("#55AE3A", alpha.f = 0.3),
                                    adjustcolor("#55AE3A")),
        col.interaction = ifelse(df1[,]<=0.001462,
                                 adjustcolor("#55AE3A", alpha.f = 0.3),
                                 adjustcolor("#0b5601", alpha.f=0.9)))

0 个答案:

没有答案