this code is for practice only, to make figs look better

codes/practice_code.Rmd

+## packages loading
+```{r}
+#General utility packages
+library(tidyverse)
+library(glue)
+library(knitr)
+library(data.table)
+#Stats packages
+library(lme4)
+library(multcomp)
+library(parameters)
+library(effectsize)
+library(performance)
+library(emmeans)
+#Plot packages
+library(ggpubr)
+```
+
+```{r}
+df <- read_csv('C:/Users/xiamen/Desktop/data_for_R/modified_robogator_paper/robotmod_data.csv') %>% 
+          mutate(trials = as.factor(trials)) %>% 
+          mutate(group = as.factor(group)) %>% 
+          mutate(sex = as.factor(sex)) %>% 
+          mutate(rat_ID = as.factor(rat_ID)) %>% 
+          mutate(restriction = as.factor(restriction))%>%
+          mutate(age = as.factor(age))%>%
+          mutate(food.distance.cm = as.factor(food.distance.cm))%>%
+         
+        # Create score based on time. Following log attribution of score as a function of time. 
+          mutate(leaving.score =  case_when(is.na(leaving.sec) ~ 7,
+                                                  leaving.sec >= 200 ~ 6,
+                                                  leaving.sec >= 100 ~ 5,
+                                                  leaving.sec >= 50 ~ 4,
+                                                  leaving.sec >= 25  ~ 3,
+                                                  leaving.sec >= 12.5 ~ 2,
+                                                  leaving.sec >= 6.25 ~ 1,
+                                                  leaving.sec <6.25 ~ 0)) %>% 
+            mutate(approaching.score =  case_when(is.na(approaching.sec) ~ 7,
+                                                  approaching.sec >= 200 ~ 6,
+                                                  approaching.sec >= 100 ~ 5,
+                                                  approaching.sec >= 50 ~ 4,
+                                                  approaching.sec >= 25  ~ 3,
+                                                  approaching.sec >= 12.5 ~ 2,
+                                                  approaching.sec >= 6.25 ~ 1,
+                                                  approaching.sec <6.25 ~ 0)) %>% 
+            mutate(backing.score =  case_when(is.na(backing.sec) ~ 7,
+                                                  backing.sec >= 200 ~ 6,
+                                                  backing.sec >= 100 ~ 5,
+                                                  backing.sec >= 50 ~ 4,
+                                                  backing.sec >= 25  ~ 3,
+                                                  backing.sec >= 12.5 ~ 2,
+                                                  backing.sec >= 6.25 ~ 1,
+                                                  backing.sec <6.25 ~ 0))  %>%
+            mutate(foraging.score =  case_when(is.na(foraging.sec) ~ 7,
+                                                  foraging.sec >= 200 ~ 6,
+                                                  foraging.sec >= 100 ~ 5,
+                                                  foraging.sec >= 50 ~ 4,
+                                                  foraging.sec >= 25  ~ 3,
+                                                  foraging.sec >= 12.5 ~ 2,
+                                                  foraging.sec >= 6.25 ~ 1,
+                                                  foraging.sec <6.25 ~ 0))
+
+#head(df) %>% kable("pipe")
+
+```
+
+```{r}
+df.SD_Rday1 <- df %>% filter(df$robot.day == 1, df$group == "SD")
+
+p_1 <- ggplot(df.SD_Rday1, aes(x=trials, y=foraging.score, group=rat_ID))
+p_1 + geom_point(color="gray")+ geom_line(color="gray")+
+stat_summary(fun=mean, aes(group = age, color= age), geom="line")+
+stat_summary(fun.data = mean_se, aes(group=age, color = age), geom = "errorbar", alpha=1, width=0.05)+
+scale_color_manual(values = c("red", "blue"))+
+  
+scale_y_continuous(breaks = seq(0, 7, by = 1))+
+geom_jitter(alpha = 0.5,width = 0.1) + labs(x = "positions", y = "foraging score") + theme_minimal()
+```
+