python 查找指定字符串 ，找出相應的數據行
def get_target_Lines(fr, s): f_handle = open(fr, "r") targets = [] #flag = False for num, line in enumerate(f_handle): if line.startswith(s): tmp = num try: if num > tmp and line.rstrip() != "": targets.append(line.rstrip()) elif num > tmp and line.rstrip() == "": # flag = True break except NameError, e: pass #if flag: # break return targets
tgets = get_target_Lines( "outfile_f" , "Inferred ancestry")
用R 自定義函數
用apply， sprintf ， order等函數
> mean
function (x, ...)
UseMethod("mean")
<bytecode: 0x00000000111edea8>
<environment: namespace:base>
> mean.default
function (x, trim = 0, na.rm = FALSE, ...)
{
if (!is.numeric(x) && !is.complex(x) && !is.logical(x)) {
warning("argument is not numeric or logical: returning NA")
return(NA_real_)
}
if (na.rm)
x <- x[!is.na(x)]
if (!is.numeric(trim) || length(trim) != 1L)
stop("'trim' must be numeric of length one")
n <- length(x)
if (trim > 0 && n) {
if (is.complex(x))
stop("trimmed means are not defined for complex data")
if (anyNA(x))
return(NA_real_)
if (trim >= 0.5)
return(stats::median(x, na.rm = FALSE))
lo <- floor(n * trim) + 1
hi <- n + 1 - lo
x <- sort.int(x, partial = unique(c(lo, hi)))[lo:hi]
}
.Internal(mean(x))
}
<bytecode: 0x00000000111ee3c0>
<environment: namespace:base>
/////////////////////////////////////////////////////////////////////
> mt <- function(v){
+ n <- length(v)
+ t1 <- v[1:5]
+ tp <- sum(v[6:n])
+ t2 <- v[6:n]
+ if (tp > 35){
+ max_index = which(t2==max(t2))[1]
+ t2[max_index] = max(t2)- tp + 35
+ }
+ return(c(t1,t2))
+ }
> mt(1:10)
[1] 1 2 3 4 5 6 7 8 9 5
> a <- 1:10
> b <- c(2,5,6,7, 466, 466,466, 34,5,2)
> c <- c(2,5,6,7, 466, 89,14, 56,7,2)
> data1 <- data.frame(a,b,c)
> data1
a b c
1 1 2 2
2 2 5 5
3 3 6 6
4 4 7 7
5 5 466 466
6 6 466 89
7 7 466 14
8 8 34 56
9 9 5 7
10 10 2 2
> apply(data1, 2, mt)
a b c
[1,] 1 2 2
[2,] 2 5 5
[3,] 3 6 6
[4,] 4 7 7
[5,] 5 466 466
[6,] 6 -472 -44
[7,] 7 466 14
[8,] 8 34 56
[9,] 9 5 7
[10,] 5 2 2
> data1 <- data.frame(rbind(a,b,c) )
> data1
X1 X2 X3 X4 X5 X6 X7 X8 X9 X10
a 1 2 3 4 5 6 7 8 9 10
b 2 5 6 7 466 466 466 34 5 2
c 2 5 6 7 466 89 14 56 7 2
> apply(data1, 1, mt)
a b c
X1 1 2 2
X2 2 5 5
X3 3 6 6
X4 4 7 7
X5 5 466 466
X6 6 -472 -44
X7 7 466 14
X8 8 34 56
X9 9 5 7
X10 5 2 2
///////////////////////////////////////////////////////////////////////
> data <- read.table("test_plot.txt", skip=1, stringsAsFactors =F)
> c("A","B",3)
[1] "A" "B" "3"
> mt <- function(v){
n <- length(v)
t1 <- v[1:5]
t2 <- as.numeric(v[6:n])
tp <- sum(t2)
if (tp > 1){
max_index = which(t2==max(t2))[1]
t2[max_index] = max(t2)- tp + 1
} else if (tp < 1){
min_index = which(t2==min(t2))[1]
t2[min_index] = min(t2) + 1 - tp
}
return(c(t1,t2))
}
>
> apply(data[1:3,], 1, mt)
1 2 3
V1 "1" "2" "3"
V2 "100" "101" "102"
V3 "(0)" "(0)" "(0)"
V4 "1" "1" "1"
V5 ":" ":" ":"
"0.663" "0.767" "0.651"
"0.185" "0.042" "0.083"
"0.039" "0.033" "0.062"
"0.113" "0.158" "0.204"
> t(apply(data, 1, mt))
V1 V2 V3 V4 V5
[1,] " 1" "100" "(0)" "1" ":" "0.663" "0.185"
[2,] " 2" "101" "(0)" "1" ":" "0.767" "0.042"
[3,] " 3" "102" "(0)" "1" ":" "0.651" "0.083"
[4,] " 4" "103" "(0)" "1" ":" "0.358" "0.078"
[5,] " 5" "104" "(0)" "1" ":" "0.062" "0.096"
[6,] " 6" "105" "(0)" "1" ":" "0.058" "0.098"
> t <- sprintf( "%.7f", 1.44*1.21)
> t
[1] "1.7424000"
> t <- sprintf( "%.3f", 1.44*1.21)
> t
[1] "1.742"
> mt <- function(v){
+ n <- length(v)
+ t1 <- v[1:5]
+ t2 <- as.numeric(v[6:n])
+ tp <- sum(t2)
+
+ if (tp > 1){
+ max_index <- which(t2==max(t2))[1]
+ t2[max_index] <- sprintf("%.3f", max(t2)-tp+1)
+ } else if (tp < 1){
+ min_index <- which(t2==min(t2))[1]
+ t2[min_index] <- sprintf("%.3f", min(t2) + 1 - tp)
+ }
+ return(c(t1,t2))
+ }
> head(data)
V1 V2 V3 V4 V5 V6 V7 V8 V9
1 1 100 (0) 1 : 0.663 0.185 0.038 0.113
2 2 101 (0) 1 : 0.767 0.042 0.033 0.158
3 3 102 (0) 1 : 0.651 0.083 0.062 0.204
4 4 103 (0) 1 : 0.358 0.078 0.185 0.379
5 5 104 (0) 1 : 0.062 0.096 0.487 0.355
6 6 105 (0) 1 : 0.058 0.098 0.516 0.329
> head(data[,6:9])
V6 V7 V8 V9
1 0.663 0.185 0.038 0.113
2 0.767 0.042 0.033 0.158
3 0.651 0.083 0.062 0.204
4 0.358 0.078 0.185 0.379
5 0.062 0.096 0.487 0.355
6 0.058 0.098 0.516 0.329
> head(t(apply(data, 1, mt)))
V1 V2 V3 V4 V5
[1,] " 1" "100" "(0)" "1" ":" "0.663" "0.185" "0.039" "0.113"
[2,] " 2" "101" "(0)" "1" ":" "0.767" "0.042" "0.033" "0.158"
[3,] " 3" "102" "(0)" "1" ":" "0.651" "0.083" "0.062" "0.204"
[4,] " 4" "103" "(0)" "1" ":" "0.358" "0.078" "0.185" "0.379"
[5,] " 5" "104" "(0)" "1" ":" "0.062" "0.096" "0.487" "0.355"
[6,] " 6" "105" "(0)" "1" ":" "0.058" "0.098" "0.515" "0.329"
> apply(data[,6:9], 1 , sum)
[1] 0.999 1.000 1.000 1.000 1.000 1.001 1.000 1.000 1.000 1.000 1.000 1.000
[13] 1.001 1.000 1.000 1.001 0.999 0.999 1.000 1.000 1.000 1.000 1.000 1.000
[25] 1.001 1.000 1.001 1.000 0.999 1.000 1.000 1.000 1.000 1.000 1.001 1.000
[37] 1.000 1.000 0.999 1.000 0.999 1.001 1.000 0.999 1.000 1.000 1.000 1.000
[49] 1.000 0.999 1.000 1.000 1.001 1.000 1.001 1.000 1.000 1.001 1.000 1.000
[61] 1.000 1.000 1.000 1.001 0.999 1.000 0.999 1.001 0.999 0.999 1.000 1.000
[73] 0.999 1.000 1.000 1.000 0.999 1.000 1.000 1.001 1.000 1.000 1.000 1.001
[85] 1.000 1.001 1.000 1.000 1.000 1.001 1.000 1.000 1.000 1.000 1.000 1.001
[97] 1.001 1.000 1.000 1.000 1.000 1.000 1.001 1.001 1.000 1.001 1.000 1.000
[109] 1.000 1.000 0.999 0.999 1.001 1.000 1.000 1.000 0.999 1.001 1.000 1.000
[121] 1.000 1.000 1.000 1.000 1.000 0.999 1.000 1.000 1.000 1.000 1.000 1.000
[133] 1.000 1.001 1.001 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000 1.000
[145] 1.001 0.999 1.000 0.999 1.000 1.000 0.999 1.000 0.999 1.000 0.999 1.000
[157] 0.999 0.999 1.000 1.001 1.000 1.001 1.000 1.000 1.000 0.999 1.000 1.001
[169] 1.000 1.000 0.999 1.000 1.000 1.000 0.999
> x <- t(apply(data, 1, mt))
> head(x)
V1 V2 V3 V4 V5
[1,] " 1" "100" "(0)" "1" ":" "0.663" "0.185" "0.039" "0.113"
[2,] " 2" "101" "(0)" "1" ":" "0.767" "0.042" "0.033" "0.158"
[3,] " 3" "102" "(0)" "1" ":" "0.651" "0.083" "0.062" "0.204"
[4,] " 4" "103" "(0)" "1" ":" "0.358" "0.078" "0.185" "0.379"
[5,] " 5" "104" "(0)" "1" ":" "0.062" "0.096" "0.487" "0.355"
[6,] " 6" "105" "(0)" "1" ":" "0.058" "0.098" "0.515" "0.329"
> head(x[,6:9])
[1,] "0.663" "0.185" "0.039" "0.113"
[2,] "0.767" "0.042" "0.033" "0.158"
[3,] "0.651" "0.083" "0.062" "0.204"
[4,] "0.358" "0.078" "0.185" "0.379"
[5,] "0.062" "0.096" "0.487" "0.355"
[6,] "0.058" "0.098" "0.515" "0.329"
> m <- apply(data.frame(x[,6:9]), 1, as.numeric)
> apply(m,2,sum)
[1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
[37] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
[73] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
[109] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
[145] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
> n <- apply(data.frame(x[,6:9]), 2, as.numeric)
> apply(n,1,sum)
[1] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
[37] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
[73] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
[109] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
[145] 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1
>
/////////////////////////////////////////////////////////////////////
> x <- t(apply(data, 1, mt))
> head(x)
V1 V2 V3 V4 V5
[1,] " 1" "100" "(0)" "1" ":" "0.663" "0.185" "0.039" "0.113"
[2,] " 2" "101" "(0)" "1" ":" "0.767" "0.042" "0.033" "0.158"
[3,] " 3" "102" "(0)" "1" ":" "0.651" "0.083" "0.062" "0.204"
[4,] " 4" "103" "(0)" "1" ":" "0.358" "0.078" "0.185" "0.379"
[5,] " 5" "104" "(0)" "1" ":" "0.062" "0.096" "0.487" "0.355"
[6,] " 6" "105" "(0)" "1" ":" "0.058" "0.098" "0.515" "0.329"
> x1 <- as.data.frame(x)
> head(x1)
V1 V2 V3 V4 V5 V6 V7 V8 V9
1 1 100 (0) 1 : 0.663 0.185 0.039 0.113
2 2 101 (0) 1 : 0.767 0.042 0.033 0.158
3 3 102 (0) 1 : 0.651 0.083 0.062 0.204
4 4 103 (0) 1 : 0.358 0.078 0.185 0.379
5 5 104 (0) 1 : 0.062 0.096 0.487 0.355
6 6 105 (0) 1 : 0.058 0.098 0.515 0.329
> data_p <- x1[order(x1[,6], decreasing=T),]
> pdf("graph.pdf", height=5, width=15)
> barplot(as.matrix(t(data_p[,6:9])), names.arg=data_p$V2, col=rainbow(4), border= rainbow(4), las=2, cex.names=0.35, cex.axis =0.65)
> dev.off()
null device
1
>繪圖結果：
