PieChart笔划的默认颜色是白色,如何更改为透明?
请参见示例代码https://google.github.io/charts/flutter/example/pie_charts/donut.html
答案 0 :(得分:1)
好吧,笔划颜色是由构造函数设置的,因此这是一个解决方法。 创建一个扩展ArcRendererConfig的新类,并使用所需的值创建一个新的构造函数,如下所示:
#install if necessary
source("http://bioconductor.org/biocLite.R")
biocLite("Rsamtools")
#load library
library(Rsamtools)
#read in entire BAM file
bam <- scanBam("~/sample5.sam-uniq.sorted.bam")
#names of the BAM fields
names(bam[[1]])
# [1] "qname" "flag" "rname" "strand" "pos" "qwidth" "mapq" "cigar"
# [9] "mrnm" "mpos" "isize" "seq" "qual"
#distribution of BAM flags
table(bam[[1]]$flag)
# 0 4 16
#1472261 775200 1652949
#function for collapsing the list of lists into a single list
#as per the Rsamtools vignette
.unlist <- function (x){
## do.call(c, ...) coerces factor to integer, which is undesired
x1 <- x[[1L]]
if (is.factor(x1)){
structure(unlist(x), class = "factor", levels = levels(x1))
} else {
do.call(c, x)
}
}
#store names of BAM fields
bam_field <- names(bam[[1]])
#go through each BAM field and unlist
list <- lapply(bam_field, function(y) .unlist(lapply(bam, "[[", y)))
#store as data frame
bam_df <- do.call("DataFrame", list)
names(bam_df) <- bam_field
dim(bam_df)
#[1] 3900410 13
#---------
#use chr22 as an example
#how many entries on the negative strand of chr22?
###table(bam_df$rname == 'chr22' & bam_df$flag == 16)
# FALSE TRUE
#3875997 24413
#function for checking negative strand
check_neg <- function(x){
if (intToBits(x)[5] == 1){
return(T)
} else {
return(F)
}
}
#test neg function with subset of chr22
test <- subset(bam_df)#, rname == 'chr22')
dim(test)
#[1] 56426 13
table(apply(as.data.frame(test$flag), 1, check_neg))
#number same as above
#FALSE TRUE
#32013 24413
#function for checking positive strand
check_pos <- function(x){
if (intToBits(x)[3] == 1){
return(F)
} else if (intToBits(x)[5] != 1){
return(T)
} else {
return(F)
}
}
#check pos function
table(apply(as.data.frame(test$flag), 1, check_pos))
#looks OK
#FALSE TRUE
#24413 32013
#store the mapped positions on the plus and minus strands
neg <- bam_df[apply(as.data.frame(bam_df$flag), 1, check_neg),
'pos'
]
length(neg)
#[1] 24413
pos <- bam_df[apply(as.data.frame(bam_df$flag), 1, check_pos),
'pos'
]
length(pos)
#[1] 32013
#calculate the densities
neg_density <- density(neg)
pos_density <- density(pos)
#display the negative strand with negative values
neg_density$y <- neg_density$y * -1
plot(pos_density,
ylim = range(c(neg_density$y, pos_density$y)),
main = "Coverage plot of Sample 5",
xlab = "lenght 21",
col = 'blue',
type='h')
lines(neg_density, type='h', col = 'red')