---
tags: Rscripts, macmanes
---

# Rscript for plotting data

updated...

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

cageweight0 <- 20.1
cageweight1 <- 22.6
cageweight2 <- 21.1
cageweight3 <- 23.1
cageweight4 <- 21.8
cageweight5 <- 15.6
cageweight6 <- 15.4

animalID0 <- 377
animalID1 <- 234
animalID2 <- 748
animalID3 <- 1002
animalID4 <- 870
animalID5 <- 333
animalID6 <- 74

datafile <- "/Volumes/4TB_1/Dropbox/Cactus_Mouse_Physiology/data/20Feb20/feb20.csv"
feb20 <- 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))

feb20 <- feb20 %>% 
	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 == 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(H2Omg_edit = 
		ifelse(hour(StartTime) == 8, H2Omg - 0.09536454,
		ifelse(hour(StartTime) == 7, H2Omg - 0.06536454,
		ifelse(hour(StartTime) == 9, H2Omg - 0.02219424,
		ifelse(hour(StartTime) == 10, H2Omg - 0.03273413,
		ifelse(hour(StartTime) == 19, H2Omg + 0.002130708,
		ifelse(hour(StartTime) == 20, H2Omg + 0.02967473,
		ifelse(hour(StartTime) == 21, H2Omg + 0.02703453,
		ifelse(hour(StartTime) == 22, H2Omg + 0.01412046,
		ifelse(hour(StartTime) %!in% c(7,8,9,10,20,21,22,19), H2Omg, NA)))))))))) %>% 
	mutate_at("H2Omg_edit", as.numeric) %>%
	mutate(corEE = EE/weight)

metric <- "corEE"

target <- c(0,1,2,3,4,5,6)
cages <- feb20 %>% filter(animal %in% target)
#cages <- with( cages ,cages[ hour( StartTime ) >= 0 & hour( StartTime ) < 4 , ] )

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

p <- ggplot(data = cages,aes(x=as.POSIXct(StartTime),y=measurement[[metric]]))
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=.9)
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)
p


#load packages

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


# import data

datafile <- "/Users/macmanes/Desktop/overnight.csv"

# should not have to change below except how you name the dataset e.g., travelingmouse

newdata <- read_csv(datafile, 
	col_types = cols(Animal = col_character(), 
        StartDate = col_date(format = "%m/%d/%y"), 
        StartTime = col_time(format = "%H:%M:%S")))
View(newdata)

# Change variables to plot VO2, in this case.

metric <- "VO2"
SD <- "SD_VO2"

measurement <- waterrandomsampling %>% select(metric)
measurement_SD <- waterrandomsampling %>% select(SD)
waterrandomsampling %>% 
	ggplot(aes(as.POSIXct(with(waterrandomsampling, StartDate + hms(StartTime))), 
		y = measurement[[metric]], group=Animal, color=Animal)) + 
	geom_line() + 
	labs(x = "", y = metric) + 
	scale_color_brewer(palette="Paired") +
	geom_pointrange(aes(ymax = c(measurement[[metric]] + measurement_SD[[SD]]), ymin = c(measurement[[metric]] - measurement_SD[[SD]]))) +
	theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
	scale_x_datetime(date_breaks = "2 hours", date_labels = "%d%b %H:%M")


## If you want to subsample out a single animal

change the metric and SD, and number of animal you want to subsample

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

datafile <- "/Users/macmanes/Desktop/waterrandomsampling.csv"
waterrandomsampling <- read_csv(datafile, 
	col_types = cols(Animal = col_character(), 
        StartDate = col_date(format = "%m/%d/%y"), 
        StartTime = col_time(format = "%H:%M:%S")))
View(waterrandomsampling)

metric <- "VO2"
SD <- "SD_VO2"
animal <- 6

measurement <- waterrandomsampling %>% filter(Animal != animal) %>% select(metric)
measurement_SD <- waterrandomsampling %>% filter(Animal != animal) %>% select(SD)
waterrandomsampling %>% filter(Animal != animal) %>% 
	ggplot(aes(as.POSIXct(with(waterrandomsampling %>% filter(Animal != animal), StartDate + hms(StartTime))), 
		y = measurement[[metric]], group=Animal, color=Animal)) + 
	geom_line() + 
	labs(x = "", y = metric) + 
	scale_color_brewer(palette="Paired") +
	geom_pointrange(aes(ymax = c(measurement[[metric]] + measurement_SD[[SD]]), ymin = c(measurement[[metric]] - measurement_SD[[SD]]))) +
	theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
	scale_x_datetime(date_breaks = "2 hours", date_labels = "%d%b %H:%M")


## This is for plotting data by time, for travelling mouse and similar.

attach(travelingmouse)
newdata <- travelingmouse[order(StartTime),]
plot(newdata$VO2, type="l", ylab="VO2", xaxt="n", xlab="Cage Numbers", frame.plot = F, lwd=3, col='red')
abline(h=0)
axis(1, at=1:27, labels=c(0,1,2,3,4,5,6,0,1,2,3,4,5,6,0,1,2,3,4,5,6,0,1,2,3,4,5))

#### H2O


#### VO2


- [ ] Need to work with Dani/Jocie to make sure at least VO2 makes sense, cause it did in the raw data.. Otherwise this is a macro issue
- [ ] Also note that O2 != VO2, but still..

#### a different way to plot

datafile <- "/Volumes/MACMANES/15Feb20/cages135.csv"
cages135 <- read_csv(datafile, 
	col_types = cols(Animal = col_character(), 
        StartDate = col_date(format = "%m/%d/%y"), 
        StartTime = col_time(format = "%H:%M:%S")))

cages135 <- cages135 %>% mutate(EE = 0.06*(3.941*VO2 + 1.106*VCO2))
cages135 <- cages135 %>% mutate(RQ = VCO2/VO2)
  
metric <- "EE"
SD <- "SD_H2Omg"

target <- c(1,3,5)
cages <- cages135 %>% filter(Animal %in% target)
measurement <- cages %>%  select(metric)
df<-as.data.frame(measurement[[metric]])

p <- ggplot(data = cages,aes(x=as.POSIXct(StartTime),y=measurement[[metric]]))
p <- p + geom_point(aes(group=Animal, color=Animal))
p <- p + geom_smooth(data=df$V1)
p <- p + labs(x = "", y = metric)
p <- p + scale_color_brewer(palette="Paired")
p <- p + scale_x_datetime(date_breaks = "2 hours", date_labels = "%H:%M")
p


metric <- "RQ"
#SD <- "SD_VO2"
measurementRQ <- cages20april %>% select("RQ")
#measurement_SD <- cages20april %>% select(SD)
df<-as.data.frame(measurementRQ[["RQ"]])
legend_title <- "Animal ID"

RQ_all<- cages20april %>% 
  ggplot(aes(as.POSIXct(with(cages20april, StartDate + hms(StartTime))), y=measurementRQ[["RQ"]]))+
  geom_point(aes(group=as.factor(Animal_ID), color=as.factor(Animal_ID)))+
  geom_hline(yintercept = 0.8907387, color='blue', size=1)+
  labs(x = "", y = "RQ") + 
  scale_color_brewer(palette="Paired") +
  #geom_pointrange(aes(ymax = c(measurement[[metric]] + measurement_SD[[SD]]), ymin = c(measurement[[metric]] - measurement_SD[[SD]]))) +
  theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
  ylim(NA, 2)+
  geom_smooth(data=df$V1, method='loess', span=.3)+
  scale_x_datetime(date_breaks = "2 hours", date_labels = "%d%b %H:%M")


metric <- "EE"
#SD <- "SD_VO2"
measurementEE <- cages20april %>% select("EE")
#measurement_SD <- cages20april %>% select(SD)
df<-as.data.frame(measurementEE[["EE"]])
legend_title <- "Animal ID"

EE_all<- cages20april %>% 
  ggplot(aes(as.POSIXct(with(cages20april, StartDate + hms(StartTime))), y=measurementEE[["EE"]]))+
  geom_point(aes(group=as.factor(Animal_ID), color=as.factor(Animal_ID)))+
  labs(x = "", y = "EE") + 
  scale_color_brewer(palette="Paired") +
  #geom_pointrange(aes(ymax = c(measurement[[metric]] + measurement_SD[[SD]]), ymin = c(measurement[[metric]] - measurement_SD[[SD]]))) +
  theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
  geom_smooth(data=df$V1, method='loess', span=.3)+
  scale_x_datetime(date_breaks = "2 hours", date_labels = "%d%b %H:%M")


metric <- "H2Omg"
#SD <- "SD_VO2"
measurementH20 <- cages20april %>% select("H2Omg")
#measurement_SD <- cages20april %>% select(SD)
df<-as.data.frame(measurementH20[["H2Omg"]])
legend_title <- "Animal ID"

H2Omg_all <- cages20april %>% 
  ggplot(aes(as.POSIXct(with(cages20april, StartDate + hms(StartTime))), y=measurementH20[["H2Omg"]]))+
  geom_point(aes(group=as.factor(Animal_ID), color=as.factor(Animal_ID)))+
  labs(x = "", y = "H2Omg") + 
  scale_color_brewer(palette="Paired") +
  #geom_pointrange(aes(ymax = c(measurement[[metric]] + measurement_SD[[SD]]), ymin = c(measurement[[metric]] - measurement_SD[[SD]]))) +
  theme(axis.text.x = element_text(angle = 45, hjust = 1)) +
  geom_smooth(data=df$V1, method='loess', span=.3)+
  scale_x_datetime(date_breaks = "2 hours", date_labels = "%d%b %H:%M")

temp <- cages20april %>% 
  ggplot(aes(as.POSIXct(with(cages20april, StartDate + hms(StartTime))),y=Deg_C))+
  geom_line()

temp/RQ_all/EE_all/H2Omg_all