clean spare codes

codes/stasitic.Rmd

@@ -322,13 +322,9 @@ labs(x = "positions", y = "approaching score")+
 theme_classic() + facet_wrap(~ restriction, ncol = 2)
 Fig_LE_approaching
 ggsave('C:/Users/xiamen/Desktop/modified robogator/result figs/Fig_LE_approaching.svg', plot = Fig_LE_approaching, device = 'svg',dpi = 300)
-<<<<<<< HEAD
-
-=======
 ```
 ## Fig4
 ```{r}
->>>>>>> b86c3dabbc987a1a3471a93de7959760021346f0
 Fig4 <- ggarrange(Fig_LE_leaving, Fig_LE_approaching, ncols=2,labels=c('A','B'), common.legend=TRUE,legend="none")
 Fig4
 ggsave('C:/Users/xiamen/Desktop/modified robogator/result figs/Fig4.svg', plot = Fig4, device = 'svg',dpi = 300, width = 176, height = 140, units = "mm")
@@ -407,24 +403,25 @@ approaching_emm_trials_sex
 
 ## approaching figure_restriction_sex
 ```{r}
-
-LE_Rday1_approaching_M <- ggplot(df.LE_Rday1_approaching_M, aes(x=trials, y=approaching.score, group=rat_ID))
-
-LE_Rday1_approaching_M + 
+fig4c <- ggplot(df.LE_Rday1_approaching_M, aes(x=trials, y=approaching.score, group=rat_ID)) +
 geom_line(color="gray", alpha=0.2)+
 stat_summary(fun = "mean", size = 1, aes(group = restriction, color= restriction), geom = "line", fun.min = 'sd', fun.max = 'sd')+
-stat_summary(fun.data = mean_se, aes(group = restriction, color= restriction), geom = "errorbar", alpha=1, width=0.05)+
-scale_color_manual(values = c("#7fc97f", "#fdc086"))+
+stat_summary(fun.data = mean_se, aes(group = restriction, color= restriction), geom = "errorbar", alpha=1, width=0.05) + 
+scale_color_manual(values = c("#8DA0CB", "#E78AC3"))+ 
 scale_y_continuous(breaks = seq(0, 7, by = 1))+
-theme_minimal() + facet_wrap(~ restriction, ncol = 2)
+labs(x = "positions", y = "approaching score") + theme_classic() + facet_wrap(~restriction, ncol = 2)
+fig4c
 
-LE_Rday1_approaching_F <- ggplot(df.LE_Rday1_approaching_F, aes(x=trials, y=approaching.score, group=rat_ID))
-
-LE_Rday1_approaching_F + 
+fig4d <- ggplot(df.LE_Rday1_approaching_F, aes(x=trials, y=approaching.score, group=rat_ID)) +
 geom_line(color="gray", alpha=0.2)+
 stat_summary(fun = "mean", size = 1, aes(group = restriction, color= restriction), geom = "line", fun.min = 'sd', fun.max = 'sd')+
-stat_summary(fun.data = mean_se, aes(group = restriction, color= restriction), geom = "errorbar", alpha=1, width=0.05)+
-scale_color_manual(values = c("#7fc97f", "#fdc086"))+
+stat_summary(fun.data = mean_se, aes(group = restriction, color= restriction), geom = "errorbar", alpha=1, width=0.05) + 
+scale_color_manual(values = c("#8DA0CB", "#E78AC3"))+ 
 scale_y_continuous(breaks = seq(0, 7, by = 1))+
-theme_minimal() + facet_wrap(~ restriction, ncol = 2)
+labs(x = "positions", y = "approaching score") + theme_classic() + facet_wrap(~restriction, ncol = 2)
+fig4d
+
+Fig4c_d <- ggarrange(Fig_LE_leaving,Fig_LE_approaching,fig4c,fig4d,ncol=2,nrow=2,labels=c('A','B','C','D'),common.legend=TRUE,legend="none")
+Fig4c_d
+ggsave('C:/Users/xiamen/Desktop/modified robogator/result figs/Fig4c_d.svg', plot = Fig4c_d, device = 'svg',dpi = 300, width = 176, height = 140, units = "mm")
 ```

codes/stat_distance_robot.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)
-```
-## loading table
-```{r}
-df <- read_csv('C:/Users/xiamen/Desktop/data_for_R/modified_robogator_paper/robotmod_distance.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))%>%
-          mutate(robot = as.factor(robot))%>%
-         
-        # 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")
-```
-## distance effect
-```{r}
-df.Bline <- df %>% filter(df$baseline.day == 6)
-df.Rday <- df %>% filter(df$robot.day == 1)
-```
-## liner mixed effect model
-```{r}
-robot <- lmer(foraging.score~ sex + trials + robot + sex:trials + sex:robot + trials:robot + (1|rat_ID), df)
-robot_sex_trials <- update(robot, . ~ . - sex:trials)
-
-robot_sex_robot <- update(robot, . ~ . - sex:robot)
-
-robot_trials_robot <- update(robot, . ~ . - trials:robot)
-
-robot_robot <- lmer(foraging.score~ sex + trials + sex:trials + (1|rat_ID), df)
-
-anova(robot, robot_robot)
-
-eta_squared(robot)
-```
-