[英]Correlation Corrplot Configuration
I am newbie in R scripts :-) 我是R脚本的新手:-)
I need build a correlation matrix and I´am trying to configurate some parameters to adapt the graph. 我需要建立一个相关矩阵,我试图配置一些参数来适应图形。 I am using the
corrplot
package. 我正在使用
corrplot
包。
I Built a corrplot matrix this way: 我用这种方式构建了一个corrplot矩阵:
corrplot(cor(d1[,2:14], d1[,2:14]), method=c("color"),
bg = "white", addgrid.col = "gray50",
tl.cex=1, type="lower", tl.col = "black",
col = colorRampPalette(c("red","white","blue"))(100))
I need show the values of correlation in the lower matrix inside the color matrix that I built. 我需要在我构建的颜色矩阵内的下部矩阵中显示相关值。 How i can do that?
我怎么能这样做?
Is it possible exclude the main diagonal from the lower matrix? 是否可以从下矩阵中排除主对角线? In this diagonl always we have the perfect correlation.
在这个对角线中,我们始终具有完美的相关性。
The other doubt - I want to show the significant values for the correlation using stars instead of squares. 另一个疑问 - 我想用星星代替正方形显示相关的重要值。 like (*, , *).
喜欢 (*, , *)。 Is it possible?
可能吗?
Can you help me guys? 你能帮帮我们吗?
With a bit of hackery you can do this in a very similar R package, corrgram
. 有点hackery你可以用一个非常相似的R包,
corrgram
来做到这corrgram
。 This one allows you to easily define your own panel functions, and helpfully makes theirs easy to view as templates. 这个允许您轻松定义自己的面板功能,并有助于使它们作为模板轻松查看。 Here's the some code and figure produced:
这是生成的一些代码和数字:
set.seed(42)
library(corrgram)
# This panel adds significance starts, or NS for not significant
panel.signif <- function (x, y, corr = NULL, col.regions, digits = 2, cex.cor,
...) {
usr <- par("usr")
on.exit(par(usr))
par(usr = c(0, 1, 0, 1))
results <- cor.test(x, y, alternative = "two.sided")
est <- results$p.value
stars <- ifelse(est < 5e-4, "***",
ifelse(est < 5e-3, "**",
ifelse(est < 5e-2, "*", "NS")))
cex.cor <- 0.4/strwidth(stars)
text(0.5, 0.5, stars, cex = cex.cor)
}
# This panel combines edits the "shade" panel from the package
# to overlay the correlation value as requested
panel.shadeNtext <- function (x, y, corr = NULL, col.regions, ...)
{
if (is.null(corr))
corr <- cor(x, y, use = "pair")
ncol <- 14
pal <- col.regions(ncol)
col.ind <- as.numeric(cut(corr, breaks = seq(from = -1, to = 1,
length = ncol + 1), include.lowest = TRUE))
usr <- par("usr")
rect(usr[1], usr[3], usr[2], usr[4], col = pal[col.ind],
border = NA)
box(col = "lightgray")
on.exit(par(usr))
par(usr = c(0, 1, 0, 1))
r <- formatC(corr, digits = 2, format = "f")
cex.cor <- .8/strwidth("-X.xx")
text(0.5, 0.5, r, cex = cex.cor)
}
# Generate some sample data
sample.data <- matrix(rnorm(100), ncol=10)
# Call the corrgram function with the new panel functions
# NB: call on the data, not the correlation matrix
corrgram(sample.data, type="data", lower.panel=panel.shadeNtext,
upper.panel=panel.signif)
The code isn't very clean, as it's mostly patched together functions from the package, but it should give you a good start to get the plot you want. 代码不是很干净,因为它主要是从包中修补功能,但它应该为你提供一个良好的开端来获得你想要的情节。 Possibly you can take a similar approach with the
corrplot
package too. 可能你也可以采用与
corrplot
包类似的方法。
update: Here's a version with stars and cor on the same triangle: 更新:这是一个在同一个三角形上有星星和cor的版本:
panel.shadeNtext <- function (x, y, corr = NULL, col.regions, ...)
{
corr <- cor(x, y, use = "pair")
results <- cor.test(x, y, alternative = "two.sided")
est <- results$p.value
stars <- ifelse(est < 5e-4, "***",
ifelse(est < 5e-3, "**",
ifelse(est < 5e-2, "*", "")))
ncol <- 14
pal <- col.regions(ncol)
col.ind <- as.numeric(cut(corr, breaks = seq(from = -1, to = 1,
length = ncol + 1), include.lowest = TRUE))
usr <- par("usr")
rect(usr[1], usr[3], usr[2], usr[4], col = pal[col.ind],
border = NA)
box(col = "lightgray")
on.exit(par(usr))
par(usr = c(0, 1, 0, 1))
r <- formatC(corr, digits = 2, format = "f")
cex.cor <- .8/strwidth("-X.xx")
fonts <- ifelse(stars != "", 2,1)
# option 1: stars:
text(0.5, 0.4, paste0(r,"\n", stars), cex = cex.cor)
# option 2: bolding:
#text(0.5, 0.5, r, cex = cex.cor, font=fonts)
}
# Generate some sample data
sample.data <- matrix(rnorm(100), ncol=10)
# Call the corrgram function with the new panel functions
# NB: call on the data, not the correlation matrix
corrgram(sample.data, type="data", lower.panel=panel.shadeNtext,
upper.panel=NULL)
Also commented out is another way of showing significance, it'll bold those below a threshold rather than using stars. 另外注释出另一种显示重要性的方法,它会将那些低于门槛而不是使用星星的那些加粗。 Might be clearer that way, depending on what you want to show.
可能会更清楚,取决于你想要展示的内容。
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