R语言-找波峰波谷求波长-果蝇心管数据处理

R语言_找波峰波谷求波长_果蝇心管数据处理ZW2024-03-04加载xlsx包&导入Excel数据#载入R包

library(xlsx)

library(ggplot2)

library(ggalt)##RegisteredS3methodsoverwrittenby'ggalt':

##methodfrom

##grid.draw.absoluteGrobggplot2

##grobHeight.absoluteGrobggplot2

##grobWidth.absoluteGrobggplot2

##grobX.absoluteGrobggplot2

##grobY.absoluteGrobggplot2#导入心管界面内径的测量数据

sheets<-getSheets(loadWorkbook("E:\\Desktop\\heart_tube.xlsx"))

#Excel表格名称

names(sheets)##[1]"Sheet1""Sheet2""Sheet3""Sheet4""Sheet5"#每个表格生成变量

for(iin1:length(sheets)){

assign(paste0('Dm_heart_dt','_',i,sep=''),read.xlsx("E:\\Desktop\\heart_tube.xlsx",sheetIndex=i,header=F))

}

#所有表格合并为一个list

Dm_heart_dt<-list(sheet1=Dm_heart_dt_1$X2,sheet2=Dm_heart_dt_2$X2,sheet3=Dm_heart_dt_3$X2,sheet4=Dm_heart_dt_4$X2,sheet5=Dm_heart_dt_5$X2)

#作折线图

plot(Dm_heart_dt_1$X2,type="b")#美化折线图

ggplot(Dm_heart_dt_1,aes(X1,X2))+

geom_xspline(spline_shape=0.5)+

labs(x='Time',y='Length')+

theme_test(base_size=20)+

theme_classic(base_size=18,

base_family='serif')##Warning:Usingthe`size`aestheticinthisgeomwasdeprecatedinggplot23.4.0.

##ℹPleaseuse`linewidth`inthe`default_aes`fieldandelsewhereinstead.

##Thiswarningisdisplayedonceevery8hours.

##Call`lifecycle::last_lifecycle_warnings()`toseewherethiswarningwas

##generated.#保存图片

ggsave("Dm_heart_dt_1.png",width=8,height=5)波峰波谷变量x，波峰=(x-1)<=x&x>=(x+1),波谷=(x-1)>x&x<(x+1)#波峰

peak<-function(x){

x_maxs<-c()

x_max<-c()

x_i<-c()

for(iin2:(length(x)-1)){

if(x[i-1]<=x[i]&x[i]>=x[i+1]){

x_max<-x[i]

x_maxs<-c(x_maxs,x_max)

x_i<-c(x_i,i)

}

}

y<-data.frame(peak_x=x_i,peak_y=x_maxs)

return(y)

}

peak_test<-peak(Dm_heart_dt_1$X2)

#波谷

valley<-function(x){

x_mins<-c()

x_min<-c()

x_i<-c()

for(iin2:(length(x)-1)){

if(x[i-1]>x[i]&x[i]<x[i+1]){

x_min<-x[i]

x_mins<-c(x_mins,x_min)

x_i<-c(x_i,i)

}

}

y<-data.frame(valley_x=x_i,valley_y=x_mins)

return(y)

}

#找波峰波谷简化：#波峰

peak1<-function(x){

x_maxs<-c()

x_max<-c()

for(iin2:(length(x)-1)){

if(x[i-1]<=x[i]&x[i]>=x[i+1]){

x_max<-x[i]

x_maxs<-c(x_maxs,x_max)

}

}

return(x_maxs)

}

peak1_data<-lapply(Dm_heart_dt,peak1)

#波谷

valley1<-function(x){

x_mins<-c()

x_min<-c()

x_i<-c()

for(iin2:(length(x)-1)){

if(x[i-1]>x[i]&x[i]<x[i+1]){

x_min<-x[i]

x_mins<-c(x_mins,x_min)

x_i<-c(x_i,i)

}

}

y<-data.frame(valley_x=x_i,valley_y=x_mins)

return(y)

}

#找波峰波谷求波峰持续时间#分类汇总：求波峰个数，适合波峰值不一致的数据

peak_count_a<-aggregate(x=peak_test$peak_y,by=list(peak_test$peak_y),FUN=length)

#rle函数计算向量中连续重复元素的长度:求波峰个数

peak_count_r<-rle(peak_test$peak_y)$length

peak_counts<-lapply(peak1_data,rle)

#波峰持续时间计算

peak_length<-list()

for(iin1:length(peak_counts)){

peak_length[[i]]<-peak_counts[[i]]$lengths*0.4

}

#改list内的名称

names(peak_length)<-names(sheets)

capture.output(peak_length,file="peak_length.txt")求邻近波峰间距#求邻近波峰间距

wavelength<-function(x){

wl<-c()

for(iin2:(length(x)-2)){

if(x[i-1]<=x[i]&x[i]>x[i+1]){

xiapo<-i

for(minxiapo:(length(x)-2)){

if(x[m-1]<x[m]&x[m]>=x[m+1]){

shangpo<-m

break

}

}

wl<-c(wl,shangpo-xiapo)

}

}

return(wl)

}

#示例

wavelength(Dm_heart_dt_3$X2)##[1]565656566#批量

wave_length<-list()

for(iin1:length(sheets)){

Dm_h_d<