---
tags: real experiments
---

# Male dehydration 16April2020

##### one day baseline three days dehydration

Cage 0 - 22g - 16.05g - 68M

Cage 1 - 20.97g - 16.52g - 81M

Cage 2 - 25.14g - 19.18g - 63M

Cage 3 - 24.74g -19.32g - 55M

Cage 4 - 21.14g - 15.56g - 8M

Cage 5 - 25.24g - 19.97g - 26M

Cage 6 - 22.58g - 16.32g - 30M

library(tidyverse)
library(lubridate)
library(readr)	

cageweight0 <- 22
cageweight1 <- 20.97
cageweight3 <- 25.14
cageweight2 <- 24.74
cageweight4 <- 21.14
cageweight5 <- 25.24
cageweight6 <- 22.58

animalID0 <- "68M"
animalID1 <- "81M"
animalID3 <- "63M"
animalID2 <- "55M"
animalID4 <- "8M"
animalID5 <- "26M"
animalID6 <- "30M"

datafile <- "~/Dropbox/Cactus_Mouse_Physiology/data/20April20/20_april_2020_4.csv"
apr20 <- read_csv(datafile, 
col_types = cols(Animal = col_double(), 
    StartDate = col_date(format = "%m/%d/%Y"),
    deltaCO2 = col_double(), 
    deltaH2O = col_double(),
    H2Oml = col_double(),
    VCO2 = col_double(),
    StartTime = col_time(format = "%H:%M:%S")))

'%!in%' <- function(x,y)!('%in%'(x,y))

apr20 <- apr20 %>% 
mutate(EE = 0.06*(3.941*VO2 + 1.106*VCO2)) %>% 
mutate(RQ = VCO2/VO2) %>%
mutate(animal = round(Animal, digits=0)) %>%
mutate(Animal = NULL) %>%
unite("DateTime", StartDate:StartTime, remove = FALSE, sep =  " ") %>%
mutate(weight = 
    ifelse(animal == 0, cageweight0, 
    ifelse(animal == 1, cageweight1,
    ifelse(animal == 2, cageweight2,
    ifelse(animal == 3, cageweight3,
    ifelse(animal == 4, cageweight4,
    ifelse(animal == 5, cageweight5,
    ifelse(animal == 6, cageweight6, NA)))))))) %>% 
mutate(Animal_ID =
    ifelse(animal == 7, 'baseline',
    ifelse(animal == 0, animalID0, 
    ifelse(animal == 1, animalID1,
    ifelse(animal == 2, animalID2,
    ifelse(animal == 3, animalID3,
    ifelse(animal == 4, animalID4,
    ifelse(animal == 5, animalID5,
    ifelse(animal == 6, animalID6, NA))))))))) %>% 
mutate(corEE = EE/weight) %>%
mutate(sex = "Male")

metric <- "corEE"

target <- c(0,1,2,3,4,5,6)
cages20apr <- apr20 %>% filter(animal %in% target)

measurement <- cages20apr %>%  select(metric)
df<-as.data.frame(measurement[[metric]])
legend_title <- "Animal ID"

p <- ggplot(data = cages20apr,aes(as.POSIXct(StartDate + hms(StartTime)), y = measurement[[metric]], group=animal, color=animal))
p <- p + geom_point(aes(group=as.factor(Animal_ID), color=as.factor(Animal_ID)), size = 3)
p <- p + theme_grey(base_size = 15)
p <- p + geom_smooth(data=df$V1, method='loess', span=.3)
p <- p + labs(x = "", y = metric)
p <- p + scale_color_brewer(legend_title, palette="Paired")
p <- p + scale_x_datetime(date_breaks = "2 hours", date_labels = "%H:%M")
#p <- p + geom_hline(yintercept = 0.8907387, color='coral', size=2)
p