索引值的热图样式可视化

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Heat map style visualize of index values

我想用一个色标来可视化/绘制数据，代表 GIC.Fish 和 GIC 中的值。按 Dive.Number 缩放列。这有点像相关矩阵或热图，除了 Fish 和 Zoop 值彼此不相关，而是与潜水次数相关。以下数据是数据帧"temp"。

Dive.Number GIC.Fish GIC.Zoop

[1,]      1   0.83   0.37

[2,]      2   0.88   0.41

[3,]      3   0.98   0.57

[4,]      4   0.90   0.43

[5,]      5   1.00   0.58

[6,]      6   0.92   0.44

[7,]      7   0.71   0.33

[8,]      8   0.99   0.55

[9,]      9   0.94   0.47

[10,]     10   0.95   0.48

[11,]     11   0.91   0.44

[12,]     12   0.96   0.50

[13,]     13   0.86   0.39

[14,]     14   0.94   0.47

[15,]     15   0.91   0.43

[16,]     16   0.89   0.41

[17,]     17   0.92   0.45

[18,]     18   0.94   0.47

[19,]     19   1.00   0.59

[20,]     20   0.96   0.53

[21,]     21   0.96   0.52

[22,]     22   1.00   0.68

[23,]     23   0.99   0.73

[24,]     24   0.98   0.77

[25,]     25   0.96   0.80

[26,]     26   0.83   0.98

[27,]     27   0.72   1.00

[28,]     28   0.98   0.77

[29,]     29   0.44   0.73

[30,]     30   0.29   0.44

[31,]     31   0.31   0.48

[32,]     32   0.64   0.97

[33,]     33   0.08   0.04

[34,]     34   0.09   0.05

[35,]     35   0.61   0.96

[36,]     36   0.36   0.59  p<-ggplot(temp, aes(x=GIC.Fish, y=Dive.Number, fill=GIC.Fish))+

  geom_tile() +

  scale_fill_gradient2(midpoint=.5, low="blue", high="red") +

  guides(fill=FALSE)setInternet2(TRUE)

con = gzcon(url('http://www.systematicportfolio.com/sit.gz', 'rb'))

  source(con)

close(con)

as.matrix(temp)

plot.table(temp, highlight=TRUE, colorbar=TRUE)dat$Dive.Number <- factor(dat$Dive.Number)

library(reshape2)

dat.m <- melt(dat, variable.name ="GIC.type", value.name ="GIC")



p <- ggplot(dat.m, aes(GIC, Dive.Number)) + geom_point(aes(colour = GIC)) +

 scale_colour_gradient(low ="blue", high ="red") +

 facet_wrap(~GIC.type)

pp <- ggplot(dat.m, aes(GIC.type, Dive.Number)) + geom_tile(aes(fill = GIC)) +

 scale_fill_gradient(low ="blue", high ="red")plot(GIC.Fish ~ GIC.Zoop, data=dat, ylim=c(0,1.1) )

with(dat, lines(GIC.Fish ~ GIC.Zoop) )

with(dat, text(GIC.Zoop, GIC.Fish+.05, labels=Dive.Number , 

     col= colorRampPalette( c("#FFFFD4","#FED98E","#FE9929", 

      "#D95F0E","#993404"), space ="Lab")(36)[Dive.Number]) )c("#00FFD4","#00D98E","#880088","#D900ff","#993404")

这段代码让我有点接近，但只有一列相关数据。

Dive.Number GIC.Fish GIC.Zoop

[1,]      1   0.83   0.37

[2,]      2   0.88   0.41

[3,]      3   0.98   0.57

[4,]      4   0.90   0.43

[5,]      5   1.00   0.58

[6,]      6   0.92   0.44

[7,]      7   0.71   0.33

[8,]      8   0.99   0.55

[9,]      9   0.94   0.47

[10,]     10   0.95   0.48

[11,]     11   0.91   0.44

[12,]     12   0.96   0.50

[13,]     13   0.86   0.39

[14,]     14   0.94   0.47

[15,]     15   0.91   0.43

[16,]     16   0.89   0.41

[17,]     17   0.92   0.45

[18,]     18   0.94   0.47

[19,]     19   1.00   0.59

[20,]     20   0.96   0.53

[21,]     21   0.96   0.52

[22,]     22   1.00   0.68

[23,]     23   0.99   0.73

[24,]     24   0.98   0.77

[25,]     25   0.96   0.80

[26,]     26   0.83   0.98

[27,]     27   0.72   1.00

[28,]     28   0.98   0.77

[29,]     29   0.44   0.73

[30,]     30   0.29   0.44

[31,]     31   0.31   0.48

[32,]     32   0.64   0.97

[33,]     33   0.08   0.04

[34,]     34   0.09   0.05

[35,]     35   0.61   0.96

[36,]     36   0.36   0.59  p<-ggplot(temp, aes(x=GIC.Fish, y=Dive.Number, fill=GIC.Fish))+

  geom_tile() +

  scale_fill_gradient2(midpoint=.5, low="blue", high="red") +

  guides(fill=FALSE)setInternet2(TRUE)

con = gzcon(url('http://www.systematicportfolio.com/sit.gz', 'rb'))

  source(con)

close(con)

as.matrix(temp)

plot.table(temp, highlight=TRUE, colorbar=TRUE)dat$Dive.Number <- factor(dat$Dive.Number)

library(reshape2)

dat.m <- melt(dat, variable.name ="GIC.type", value.name ="GIC")



p <- ggplot(dat.m, aes(GIC, Dive.Number)) + geom_point(aes(colour = GIC)) +

 scale_colour_gradient(low ="blue", high ="red") +

 facet_wrap(~GIC.type)

pp <- ggplot(dat.m, aes(GIC.type, Dive.Number)) + geom_tile(aes(fill = GIC)) +

 scale_fill_gradient(low ="blue", high ="red")plot(GIC.Fish ~ GIC.Zoop, data=dat, ylim=c(0,1.1) )

with(dat, lines(GIC.Fish ~ GIC.Zoop) )

with(dat, text(GIC.Zoop, GIC.Fish+.05, labels=Dive.Number , 

     col= colorRampPalette( c("#FFFFD4","#FED98E","#FE9929", 

      "#D95F0E","#993404"), space ="Lab")(36)[Dive.Number]) )c("#00FFD4","#00D98E","#880088","#D900ff","#993404")

这让我更接近了，但我不想要 Dive Number 列，也不想在单元格中显示实际值，我希望能够更改颜色栏中的颜色。

Dive.Number GIC.Fish GIC.Zoop

[1,]      1   0.83   0.37

[2,]      2   0.88   0.41

[3,]      3   0.98   0.57

[4,]      4   0.90   0.43

[5,]      5   1.00   0.58

[6,]      6   0.92   0.44

[7,]      7   0.71   0.33

[8,]      8   0.99   0.55

[9,]      9   0.94   0.47

[10,]     10   0.95   0.48

[11,]     11   0.91   0.44

[12,]     12   0.96   0.50

[13,]     13   0.86   0.39

[14,]     14   0.94   0.47

[15,]     15   0.91   0.43

[16,]     16   0.89   0.41

[17,]     17   0.92   0.45

[18,]     18   0.94   0.47

[19,]     19   1.00   0.59

[20,]     20   0.96   0.53

[21,]     21   0.96   0.52

[22,]     22   1.00   0.68

[23,]     23   0.99   0.73

[24,]     24   0.98   0.77

[25,]     25   0.96   0.80

[26,]     26   0.83   0.98

[27,]     27   0.72   1.00

[28,]     28   0.98   0.77

[29,]     29   0.44   0.73

[30,]     30   0.29   0.44

[31,]     31   0.31   0.48

[32,]     32   0.64   0.97

[33,]     33   0.08   0.04

[34,]     34   0.09   0.05

[35,]     35   0.61   0.96

[36,]     36   0.36   0.59  p<-ggplot(temp, aes(x=GIC.Fish, y=Dive.Number, fill=GIC.Fish))+

  geom_tile() +

  scale_fill_gradient2(midpoint=.5, low="blue", high="red") +

  guides(fill=FALSE)setInternet2(TRUE)

con = gzcon(url('http://www.systematicportfolio.com/sit.gz', 'rb'))

  source(con)

close(con)

as.matrix(temp)

plot.table(temp, highlight=TRUE, colorbar=TRUE)dat$Dive.Number <- factor(dat$Dive.Number)

library(reshape2)

dat.m <- melt(dat, variable.name ="GIC.type", value.name ="GIC")



p <- ggplot(dat.m, aes(GIC, Dive.Number)) + geom_point(aes(colour = GIC)) +

 scale_colour_gradient(low ="blue", high ="red") +

 facet_wrap(~GIC.type)

pp <- ggplot(dat.m, aes(GIC.type, Dive.Number)) + geom_tile(aes(fill = GIC)) +

 scale_fill_gradient(low ="blue", high ="red")plot(GIC.Fish ~ GIC.Zoop, data=dat, ylim=c(0,1.1) )

with(dat, lines(GIC.Fish ~ GIC.Zoop) )

with(dat, text(GIC.Zoop, GIC.Fish+.05, labels=Dive.Number , 

     col= colorRampPalette( c("#FFFFD4","#FED98E","#FE9929", 

      "#D95F0E","#993404"), space ="Lab")(36)[Dive.Number]) )c("#00FFD4","#00D98E","#880088","#D900ff","#993404")

这是你所追求的吗？假设您的数据是 dat:

Dive.Number GIC.Fish GIC.Zoop

[1,]      1   0.83   0.37

[2,]      2   0.88   0.41

[3,]      3   0.98   0.57

[4,]      4   0.90   0.43

[5,]      5   1.00   0.58

[6,]      6   0.92   0.44

[7,]      7   0.71   0.33

[8,]      8   0.99   0.55

[9,]      9   0.94   0.47

[10,]     10   0.95   0.48

[11,]     11   0.91   0.44

[12,]     12   0.96   0.50

[13,]     13   0.86   0.39

[14,]     14   0.94   0.47

[15,]     15   0.91   0.43

[16,]     16   0.89   0.41

[17,]     17   0.92   0.45

[18,]     18   0.94   0.47

[19,]     19   1.00   0.59

[20,]     20   0.96   0.53

[21,]     21   0.96   0.52

[22,]     22   1.00   0.68

[23,]     23   0.99   0.73

[24,]     24   0.98   0.77

[25,]     25   0.96   0.80

[26,]     26   0.83   0.98

[27,]     27   0.72   1.00

[28,]     28   0.98   0.77

[29,]     29   0.44   0.73

[30,]     30   0.29   0.44

[31,]     31   0.31   0.48

[32,]     32   0.64   0.97

[33,]     33   0.08   0.04

[34,]     34   0.09   0.05

[35,]     35   0.61   0.96

[36,]     36   0.36   0.59  p<-ggplot(temp, aes(x=GIC.Fish, y=Dive.Number, fill=GIC.Fish))+

  geom_tile() +

  scale_fill_gradient2(midpoint=.5, low="blue", high="red") +

  guides(fill=FALSE)setInternet2(TRUE)

con = gzcon(url('http://www.systematicportfolio.com/sit.gz', 'rb'))

  source(con)

close(con)

as.matrix(temp)

plot.table(temp, highlight=TRUE, colorbar=TRUE)dat$Dive.Number <- factor(dat$Dive.Number)

library(reshape2)

dat.m <- melt(dat, variable.name ="GIC.type", value.name ="GIC")



p <- ggplot(dat.m, aes(GIC, Dive.Number)) + geom_point(aes(colour = GIC)) +

 scale_colour_gradient(low ="blue", high ="red") +

 facet_wrap(~GIC.type)

pp <- ggplot(dat.m, aes(GIC.type, Dive.Number)) + geom_tile(aes(fill = GIC)) +

 scale_fill_gradient(low ="blue", high ="red")plot(GIC.Fish ~ GIC.Zoop, data=dat, ylim=c(0,1.1) )

with(dat, lines(GIC.Fish ~ GIC.Zoop) )

with(dat, text(GIC.Zoop, GIC.Fish+.05, labels=Dive.Number , 

     col= colorRampPalette( c("#FFFFD4","#FED98E","#FE9929", 

      "#D95F0E","#993404"), space ="Lab")(36)[Dive.Number]) )c("#00FFD4","#00D98E","#880088","#D900ff","#993404")

关于 r：索引值的热图样式可视化

编辑

根据您的评论，也许这更像您的想象：

Dive.Number GIC.Fish GIC.Zoop

[1,]      1   0.83   0.37

[2,]      2   0.88   0.41

[3,]      3   0.98   0.57

[4,]      4   0.90   0.43

[5,]      5   1.00   0.58

[6,]      6   0.92   0.44

[7,]      7   0.71   0.33

[8,]      8   0.99   0.55

[9,]      9   0.94   0.47

[10,]     10   0.95   0.48

[11,]     11   0.91   0.44

[12,]     12   0.96   0.50

[13,]     13   0.86   0.39

[14,]     14   0.94   0.47

[15,]     15   0.91   0.43

[16,]     16   0.89   0.41

[17,]     17   0.92   0.45

[18,]     18   0.94   0.47

[19,]     19   1.00   0.59

[20,]     20   0.96   0.53

[21,]     21   0.96   0.52

[22,]     22   1.00   0.68

[23,]     23   0.99   0.73

[24,]     24   0.98   0.77

[25,]     25   0.96   0.80

[26,]     26   0.83   0.98

[27,]     27   0.72   1.00

[28,]     28   0.98   0.77

[29,]     29   0.44   0.73

[30,]     30   0.29   0.44

[31,]     31   0.31   0.48

[32,]     32   0.64   0.97

[33,]     33   0.08   0.04

[34,]     34   0.09   0.05

[35,]     35   0.61   0.96

[36,]     36   0.36   0.59  p<-ggplot(temp, aes(x=GIC.Fish, y=Dive.Number, fill=GIC.Fish))+

  geom_tile() +

  scale_fill_gradient2(midpoint=.5, low="blue", high="red") +

  guides(fill=FALSE)setInternet2(TRUE)

con = gzcon(url('http://www.systematicportfolio.com/sit.gz', 'rb'))

  source(con)

close(con)

as.matrix(temp)

plot.table(temp, highlight=TRUE, colorbar=TRUE)dat$Dive.Number <- factor(dat$Dive.Number)

library(reshape2)

dat.m <- melt(dat, variable.name ="GIC.type", value.name ="GIC")



p <- ggplot(dat.m, aes(GIC, Dive.Number)) + geom_point(aes(colour = GIC)) +

 scale_colour_gradient(low ="blue", high ="red") +

 facet_wrap(~GIC.type)

pp <- ggplot(dat.m, aes(GIC.type, Dive.Number)) + geom_tile(aes(fill = GIC)) +

 scale_fill_gradient(low ="blue", high ="red")plot(GIC.Fish ~ GIC.Zoop, data=dat, ylim=c(0,1.1) )

with(dat, lines(GIC.Fish ~ GIC.Zoop) )

with(dat, text(GIC.Zoop, GIC.Fish+.05, labels=Dive.Number , 

     col= colorRampPalette( c("#FFFFD4","#FED98E","#FE9929", 

      "#D95F0E","#993404"), space ="Lab")(36)[Dive.Number]) )c("#00FFD4","#00D98E","#880088","#D900ff","#993404")

关于 r：索引值的热图样式可视化

(警告。不是 ggplot2 创作。我从来没有学会用那个模型思考。)我想你可能正在寻找一个可以用颜色编码的二维密度地图，所以我绘制了 GIC.Zoop 和 GIC.Fish。从该结果生成密度图的概念似乎不符合数据的模式，因此我画了线以查看是否存在明显的序列。然后我用 Dive.Number 标记点，用颜色编码：

Dive.Number GIC.Fish GIC.Zoop

[1,]      1   0.83   0.37

[2,]      2   0.88   0.41

[3,]      3   0.98   0.57

[4,]      4   0.90   0.43

[5,]      5   1.00   0.58

[6,]      6   0.92   0.44

[7,]      7   0.71   0.33

[8,]      8   0.99   0.55

[9,]      9   0.94   0.47

[10,]     10   0.95   0.48

[11,]     11   0.91   0.44

[12,]     12   0.96   0.50

[13,]     13   0.86   0.39

[14,]     14   0.94   0.47

[15,]     15   0.91   0.43

[16,]     16   0.89   0.41

[17,]     17   0.92   0.45

[18,]     18   0.94   0.47

[19,]     19   1.00   0.59

[20,]     20   0.96   0.53

[21,]     21   0.96   0.52

[22,]     22   1.00   0.68

[23,]     23   0.99   0.73

[24,]     24   0.98   0.77

[25,]     25   0.96   0.80

[26,]     26   0.83   0.98

[27,]     27   0.72   1.00

[28,]     28   0.98   0.77

[29,]     29   0.44   0.73

[30,]     30   0.29   0.44

[31,]     31   0.31   0.48

[32,]     32   0.64   0.97

[33,]     33   0.08   0.04

[34,]     34   0.09   0.05

[35,]     35   0.61   0.96

[36,]     36   0.36   0.59  p<-ggplot(temp, aes(x=GIC.Fish, y=Dive.Number, fill=GIC.Fish))+

  geom_tile() +

  scale_fill_gradient2(midpoint=.5, low="blue", high="red") +

  guides(fill=FALSE)setInternet2(TRUE)

con = gzcon(url('http://www.systematicportfolio.com/sit.gz', 'rb'))

  source(con)

close(con)

as.matrix(temp)

plot.table(temp, highlight=TRUE, colorbar=TRUE)dat$Dive.Number <- factor(dat$Dive.Number)

library(reshape2)

dat.m <- melt(dat, variable.name ="GIC.type", value.name ="GIC")



p <- ggplot(dat.m, aes(GIC, Dive.Number)) + geom_point(aes(colour = GIC)) +

 scale_colour_gradient(low ="blue", high ="red") +

 facet_wrap(~GIC.type)

pp <- ggplot(dat.m, aes(GIC.type, Dive.Number)) + geom_tile(aes(fill = GIC)) +

 scale_fill_gradient(low ="blue", high ="red")plot(GIC.Fish ~ GIC.Zoop, data=dat, ylim=c(0,1.1) )

with(dat, lines(GIC.Fish ~ GIC.Zoop) )

with(dat, text(GIC.Zoop, GIC.Fish+.05, labels=Dive.Number , 

     col= colorRampPalette( c("#FFFFD4","#FED98E","#FE9929", 

      "#D95F0E","#993404"), space ="Lab")(36)[Dive.Number]) )c("#00FFD4","#00D98E","#880088","#D900ff","#993404")

关于 r：索引值的热图样式可视化

您可以尝试颜色过渡。此颜色矢量提供更多对比度：

Dive.Number GIC.Fish GIC.Zoop

[1,]      1   0.83   0.37

[2,]      2   0.88   0.41

[3,]      3   0.98   0.57

[4,]      4   0.90   0.43

[5,]      5   1.00   0.58

[6,]      6   0.92   0.44

[7,]      7   0.71   0.33

[8,]      8   0.99   0.55

[9,]      9   0.94   0.47

[10,]     10   0.95   0.48

[11,]     11   0.91   0.44

[12,]     12   0.96   0.50

[13,]     13   0.86   0.39

[14,]     14   0.94   0.47

[15,]     15   0.91   0.43

[16,]     16   0.89   0.41

[17,]     17   0.92   0.45

[18,]     18   0.94   0.47

[19,]     19   1.00   0.59

[20,]     20   0.96   0.53

[21,]     21   0.96   0.52

[22,]     22   1.00   0.68

[23,]     23   0.99   0.73

[24,]     24   0.98   0.77

[25,]     25   0.96   0.80

[26,]     26   0.83   0.98

[27,]     27   0.72   1.00

[28,]     28   0.98   0.77

[29,]     29   0.44   0.73

[30,]     30   0.29   0.44

[31,]     31   0.31   0.48

[32,]     32   0.64   0.97

[33,]     33   0.08   0.04

[34,]     34   0.09   0.05

[35,]     35   0.61   0.96

[36,]     36   0.36   0.59  p<-ggplot(temp, aes(x=GIC.Fish, y=Dive.Number, fill=GIC.Fish))+

  geom_tile() +

  scale_fill_gradient2(midpoint=.5, low="blue", high="red") +

  guides(fill=FALSE)setInternet2(TRUE)

con = gzcon(url('http://www.systematicportfolio.com/sit.gz', 'rb'))

  source(con)

close(con)

as.matrix(temp)

plot.table(temp, highlight=TRUE, colorbar=TRUE)dat$Dive.Number <- factor(dat$Dive.Number)

library(reshape2)

dat.m <- melt(dat, variable.name ="GIC.type", value.name ="GIC")



p <- ggplot(dat.m, aes(GIC, Dive.Number)) + geom_point(aes(colour = GIC)) +

 scale_colour_gradient(low ="blue", high ="red") +

 facet_wrap(~GIC.type)

pp <- ggplot(dat.m, aes(GIC.type, Dive.Number)) + geom_tile(aes(fill = GIC)) +

 scale_fill_gradient(low ="blue", high ="red")plot(GIC.Fish ~ GIC.Zoop, data=dat, ylim=c(0,1.1) )

with(dat, lines(GIC.Fish ~ GIC.Zoop) )

with(dat, text(GIC.Zoop, GIC.Fish+.05, labels=Dive.Number , 

     col= colorRampPalette( c("#FFFFD4","#FED98E","#FE9929", 

      "#D95F0E","#993404"), space ="Lab")(36)[Dive.Number]) )c("#00FFD4","#00D98E","#880088","#D900ff","#993404")
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