season

R Markdown

rm(list = ls())
library(lmerTest)

## 载入需要的程辑包：lme4

## 载入需要的程辑包：Matrix

## 
## 载入程辑包：'lmerTest'

## The following object is masked from 'package:lme4':
## 
##     lmer

## The following object is masked from 'package:stats':
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##     step

library(tidyverse)

## ── Attaching core tidyverse packages ──────────────────────── tidyverse 2.0.0 ──
## ✔ dplyr     1.1.4     ✔ readr     2.1.5
## ✔ forcats   1.0.0     ✔ stringr   1.5.1
## ✔ ggplot2   3.5.1     ✔ tibble    3.2.1
## ✔ lubridate 1.9.3     ✔ tidyr     1.3.1
## ✔ purrr     1.0.2

## ── Conflicts ────────────────────────────────────────── tidyverse_conflicts() ──
## ✖ tidyr::expand() masks Matrix::expand()
## ✖ dplyr::filter() masks stats::filter()
## ✖ dplyr::lag()    masks stats::lag()
## ✖ tidyr::pack()   masks Matrix::pack()
## ✖ tidyr::unpack() masks Matrix::unpack()
## ℹ Use the conflicted package (<http://conflicted.r-lib.org/>) to force all conflicts to become errors

library(splines)
library(lubridate) 
library(sp)
library(gstat)
library(raster)

## 
## 载入程辑包：'raster'
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## The following object is masked from 'package:dplyr':
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##     select
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## The following object is masked from 'package:lme4':
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##     getData

library(dplyr)

setwd("D:/R/sperm quality and temperature")
data <- read.csv("D:/R/sperm quality and temperature/data_for_analysis.csv", fileEncoding = "GB18030")

data$sumab<-data$sumab/sd(data$sumab)
data$sumabc<-data$sumabc/sd(data$sumabc)
data$density<-log(data$density)/sd(na.omit(log(data$density)))
data$semencount<-log(data$semencount)/sd(na.omit(log(data$semencount)))
data$totalmotilecount<-log(data$totalmotilecount)/sd(na.omit(log(data$totalmotilecount)))
data$progemotilecount<-log(data$progemotilecount)/sd(na.omit(log(data$progemotilecount)))

daytemaver_linear_plot<-ggplot(output,aes(x=window,y=Estimate,color=factor(window))) + geom_point() +
  geom_errorbar(aes(ymin=Estimate-1.96*Std..Error,ymax=Estimate+1.96*Std..Error),width = 0.0) +
  facet_grid(cols = vars(outcome),scales = "free",labeller = labeller(outcome = outcome)) +
  geom_hline(aes(yintercept=0),color="#00BFC4",linetype="dashed") +
  labs(x = "Exposure windows average daytem",y = "Regression coefficient") +
  scale_x_discrete(labels=c("0-90 days","0-9 days","10-14 days","70-90 days")) +
  scale_colour_discrete(name="Exposure window average daytem") +
  theme(legend.position="bottom",legend.title=element_text(size=10),legend.text =element_text(size=8),legend.background = element_rect(fill="transparent",colour=NA),
        legend.key = element_rect(fill = "transparent", colour = "transparent"),legend.direction = "horizontal") +
  theme(axis.text.x = element_text(angle = 20))

tiff(filename="C:/Users/32276/Desktop/xiebianliang/daytemaver_linear_result_season.tiff",width=16.4,height=3.28,unit="in",res=900,compression="lzw")
daytemaver_linear_plot
dev.off()

## png 
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