CAL.PLOTS.V2.0.steinke.Rmd

---
title: "CAL Plots [VERSION 1]"
author: "Corey A. Rynders, PhD"
date: "02-APR-2022"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)

```

# Instructions:

------------------------------------------------------------

## Step 1: Customize the location of your files

**Note that this step only needs to be completed if this is the first time you are running the program on your computer**

```{r}

#Please copy and paste the pathname of the INPUT folder on your computer between parentheses in the line of code below
input.dir <- "/Users/stein/Desktop/CAL PLOT/INPUT_EU"


#Please copy and paste the pathname of the INPUT folder on your computer between parentheses in the line of code below
input_comp.dir <- "/Users/stein/Desktop/CAL PLOT/INPUT_OF"


#Please copy and paste the pathname of the ARCHIVE folder on your computer between parentheses in the line of code below
archive.dir <- "/Users/stein/Desktop/CAL PLOT/ARCHIVE"

#Please copy and paste the pathname of the OUTPUT folder on your computer between parentheses in the line of code below
output.dir <-  "/Users/stein/Desktop/CAL PLOT/OUTPUT"

#Note that there should NOT be a "/" or "\" at the end of each pathname!!

```

------------------------------------------------------------

------------------------------------------------------------

## Step 2: Check Nameing Convention Compliance 

**Before running this program please make sure that the chamber files have the correct naming convention.**

**Format all ARROW study file names like this  -> PID_Condition_ProtocolDay_extracted -> 91001_EU_N6_extracted or 91001_EU_D7_extracted or 91001_OF_N6_extracted or 91001_OF_D7_extracted**

------------------------------------------------------------

------------------------------------------------------------

## Step 3: Place a copy of the .txt file that you want analyzed in the INPUT folder

------------------------------------------------------------

------------------------------------------------------------

## Step 4: Run the program

Select RUN (see top right-hand corner of the code viewer pane) -> RUN ALL

------------------------------------------------------------

------------------------------------------------------------
PROGRAM CODE BELOW (DO NOT MODIFY ANYTHING BELOW THIS LINE)
------------------------------------------------------------

## Import Data 

```{r}

#RUN FOR THE EU CONDITION

#Names of the files in the input directory
input.file <- list.files(input.dir, full.names = TRUE)

#Name of the .txt file
txt.file <-
  list.files(path = input.dir,
             pattern = "*.txt",
             full.names = TRUE)

#Library needed to execute the import function
library(data.table)

#Funtion that imports a .txt file and creates a new column with the name of the source file
import.fx <- function(x) {
  out <- fread(x, header = TRUE)
  out$source_file <- x
  return(out)
}

#Import the chamber data into a data.frame for analysis
ch <- import.fx(txt.file)

#Libraries needed to move the new chamber test data to the archived folder
library(stringr)
library(filesstrings)

#Move the files from the input folder to the archive
file.move(input.file, archive.dir)
```


## Import comparison data

```{r}
#RUN FOR THE OF CONDITION


#Names of the files in the input directory
input_comp.file <- list.files(input_comp.dir, full.names = TRUE)

#Name of the .txt file
txt.file <-
  list.files(path = input_comp.dir,
             pattern = "*.txt",
             full.names = TRUE)

#Library needed to execute the import function
library(data.table)

#Import the chamber data into a data.frame for analysis
ch_comp <- import.fx(txt.file)

#Libraries needed to move the new chamber test data to the archived folder
library(stringr)
library(filesstrings)

#Move the files from the input folder to the archive
file.move(input_comp.file, archive.dir)
```




## Calculations and Results Table

```{r}

library(tidyverse)
#-------------------------------------------
#EU condition
ch  <- ch %>% 
  mutate(index = row_number()) 
#OF condition
ch_comp  <- ch_comp %>% 
  mutate(index = row_number()) 
#-------------------------------------------

#Minutes of data collected
#EU condition
duration <- length(ch$kcal_min)
#OF condition
duration_comp <- length(ch_comp$kcal_min)

#-------------------------------------------
#Sum of VO2 column
#EU condition
VO2_actual <- sum(ch$VO2)
#OF condition
VO2_actual_comp <- sum(ch_comp$VO2)

#-------------------------------------------
#Sum of VCO2 column
#EU condition
VCO2_actual <- sum(ch$VCO2)
#OF condition
VCO2_actual_comp <- sum(ch_comp$VCO2)

#-------------------------------------------
#Sum of EE column
#EU condition
EE_actual <- sum(ch$kcal_min)
#OF condition
EE_actual_comp <- sum(ch_comp$kcal_min)

#-------------------------------------------

#EE total / total duration
#EU condition
EE_kcal_min_actual <- EE_actual / duration
#OF condition
EE_kcal_min_actual_comp <- EE_actual_comp / duration_comp
#-------------------------------------------

#EE 24
#EU condition
EE_actual <- EE_kcal_min_actual * 1440
#OF condition
EE_actual_comp <- EE_kcal_min_actual_comp * 1440

#-------------------------------------------
#EU condition
RER_actual <- mean(ch$RQ)
#OF condition
RER_actual_comp <- mean(ch_comp$RQ)

RER_expected <- NA     #check here if something fails

#-------------------------------------------
#EU condition
RER_sd <- sd(ch$RQ)
#OF condition
RER_sd_comp <- sd(ch_comp$RQ)

#-------------------------------------------
#EU condition
RER_cv <- (RER_sd / RER_actual) * 100
#OF condition
RER_cv_comp <- (RER_sd_comp / RER_actual_comp) * 100

#-------------------------------------------
#EU condition
RER_min <- min(ch$RQ)
#OF condition
RER_min_comp <- min(ch_comp$RQ)

#-------------------------------------------
#EU condition
RER_max <- max(ch$RQ)
#OF condition
RER_max_comp <- max(ch_comp$RQ)

#-------------------------------------------
#EU condition
EU_rows <-
  c(
    "EU_Test Duration, min",
#    "Propane Burned, g",
#    "Burn Rate, g/min",
    "EU_VO2, l",
    "EU_VCO2, l",
    "EU_EE, kcal/24h",
    "EU_EE, kcal/min",
    "EU_RER",
    "EU_RER, SD",
    "EU_RER, CV",
    "EU_RER, minimum",
    "EU_RER, maximum"
  )

OF_rows <-
  c(
    "OF_Test Duration, min",
#    "Propane Burned, g",
#    "Burn Rate, g/min",
    "OF_VO2, l",
    "OF_VCO2, l",
    "OF_EE, kcal/24h",
    "OF_EE, kcal/min",
    "OF_RER",
    "OF_RER, SD",
    "OF_RER, CV",
    "OF_RER, minimum",
    "OF_RER, maximum"
  )

empty <- NA

#-------------------------------------------
#EU condition
c2 <-
  rbind(
    duration,
#    propane_burned,
#    burn_rate,
    VO2_actual,
    VCO2_actual,
    EE_actual,
    EE_kcal_min_actual,
    RER_actual,
    RER_sd,
    RER_cv,
    RER_min,
    RER_max
  )

#OF condition
c2_comp <-
  rbind(
    duration_comp,
#    propane_burned,
#    burn_rate,
    VO2_actual_comp,
    VCO2_actual_comp,
    EE_actual_comp,
    EE_kcal_min_actual_comp,
    RER_actual_comp,
    RER_sd_comp,
    RER_cv_comp,
    RER_min_comp,
    RER_max_comp
  )

#-------------------------------------------
#Set up the data frames
results <- as.data.frame(cbind(EU_rows, c2))
results_comp <- as.data.frame(cbind(OF_rows, c2_comp))

rownames(results) <- c()
rownames(results_comp) <- c()

colnames(results) <-
  c("EU_Variable", "EU_Values")
colnames(results_comp) <-
  c("OF_Variable", "OF_Values")

results$EU_Values <-
  round(as.numeric(results$EU_Values), 2)
results_comp$OF_Values <-
  round(as.numeric(results_comp$OF_Values), 2)

#results$Values <-
#  round(as.numeric(results$Values), 2)
#results_comp$Values <-
#  round(as.numeric(results_comp$Values), 2)



#Uncomment below to view the dataframes:
results
results_comp

```


## Create a comparision data frame

```{r}

combo<-cbind(results,results_comp)

```



## Plots

```{r}
#------------------------------------------------
o2 <- melt(ch,
           id = c("index") ,
           measure = c("O21", "O22"))
o2_comp <- melt(ch_comp,
           id = c("index") ,
           measure = c("O21", "O22"))



o2$Channel <- o2$variable
o2_comp$Channel <- o2_comp$variable

o2$variable    <-
  factor(o2$variable,
         levels = c("O21", "O22"),
         labels = c("O21", "O22"))
o2_comp$variable    <-
  factor(o2_comp$variable,
         levels = c("O21", "O22"),
         labels = c("O21", "O22"))

#seperate and group the data based on the variable (channel as well)

#for O21 variable:
strip_o21_OF<-o2_comp%>%
  filter(variable=='O21')
strip_o21_EU<-o2%>%
  filter(variable=='O21')
join_o2<-left_join(strip_021_EU,strip_o21_OF,by='index')
join_o2_o21<-join_o2%>%
  select(index,variable.x,value.x,Channel.x,value.y)%>%
  rename(variable=variable.x,value_EU=value.x,channel=Channel.x,value_OF=value.y)

#for O22 variable:
strip_o22_OF<-o2_comp%>%
  filter(variable=='O22')
strip_022_EU<-o2%>%
  filter(variable=='O22')
join_o2_2<-left_join(strip_022_EU,strip_o22_OF,by='index')
join_o2_o22<-join_o2_2%>%
  select(index,variable.x,value.x,Channel.x,value.y)%>%
  rename(variable=variable.x,value_EU=value.x,channel=Channel.x,value_OF=value.y)

#total_o2<-rbind(join_o2_o21,join_o2_o22)


v1<-
  ggplot()+
  geom_line(data=join_o2_o21,aes(x=index,y=value_EU,color='EU Channel 1'))+
  geom_line(data=join_o2_o22,aes(x=index,y=value_EU,color='EU Channel 2'),linetype='twodash')+
  geom_line(data=join_o2_o21,aes(x=index,y=value_OF,color='OF Channel 1'))+
  geom_line(data=join_o2_o22,aes(x=index,y=value_OF,color='OF Channel 2'),linetype='twodash')+
  #geom_line(data = total_o2,aes(x=index,y=value_EU,color='EU',linetype=channel))+
  #geom_line(data = total_o2,aes(x=index,y=value_OF,color='OF',linetype=channel))+
  scale_color_manual(name='Condition and Channel',
                     values=c('red','blue','green','black'))+
  scale_x_continuous(limits = c(0, 1380), breaks = (c(seq(0, 1380, 120)))) +
  labs(x = "Time, Minutes", y = "O2, %")+
  ggtitle("O2: Channels 1 and 2") +
  theme(axis.title.x = element_blank(),
        axis.text.x = element_blank()) +
  theme(legend.position="top")+
  theme_minimal()

#------------------------------------------------
#For CO2
co2 <- melt(ch,
            id = c("index") ,
            measure = c("CO21", "CO22"))
co2_comp <- melt(ch_comp,
            id = c("index") ,
            measure = c("CO21", "CO22"))

co2$Channel <- co2$variable
co2_comp$Channel <- co2_comp$variable

co2$variable    <-
  factor(co2$variable,
         levels = c("CO21", "CO22"),
         labels = c("CO21", "CO22"))
co2_comp$variable    <-
  factor(co2_comp$variable,
         levels = c("CO21", "CO22"),
         labels = c("CO21", "CO22"))

strip_co21_OF<-co2_comp%>%
  filter(variable=='CO21')
strip_co21_EU<-co2%>%
  filter(variable=='CO21')
join_co2<-left_join(strip_co21_EU,strip_co21_OF,by='index')
join_co2_o21<-join_co2%>%
  select(index,variable.x,value.x,Channel.x,value.y)%>%
  rename(variable=variable.x,value_EU=value.x,channel=Channel.x,value_OF=value.y)

#for cO22 variable:
strip_co22_OF<-co2_comp%>%
  filter(variable=='CO22')
strip_co22_EU<-co2%>%
  filter(variable=='CO22')
join_co2_2<-left_join(strip_co22_EU,strip_co22_OF,by='index')
join_co2_o22<-join_co2_2%>%
  select(index,variable.x,value.x,Channel.x,value.y)%>%
  rename(variable=variable.x,value_EU=value.x,channel=Channel.x,value_OF=value.y)

#total_co2<-rbind(join_co2_o21,join_co2_o22)

#For CO2:
v2<-ggplot()+
  geom_line(data=join_co2_o21,aes(x=index,y=value_EU,color='EU Channel 1'))+
  geom_line(data=join_co2_o22,aes(x=index,y=value_EU,color='EU Channel 2'),linetype='twodash')+
  geom_line(data=join_co2_o21,aes(x=index,y=value_OF,color='OF Channel 1'))+
  geom_line(data=join_co2_o22,aes(x=index,y=value_OF,color='OF Channel 2'),linetype='twodash')+
  #geom_line(data = total_co2,aes(x=index,y=value_EU,color='EU',linetype=channel))+
  #geom_line(data = total_co2,aes(x=index,y=value_OF,color='OF',linetype=channel))+
  scale_color_manual(name='Condition and Channel',
                     values=c('red','blue','green','black'))+
  scale_x_continuous(limits = c(0, 1380), breaks = (c(seq(0, 1380, 120)))) +
  labs(x = "Time, Minutes", y = "CO2, %")+
  ggtitle("CO2: Channels 1 and 2") +
  theme(axis.title.x = element_blank(),
        axis.text.x = element_blank()) +
  theme(legend.position="top")+
  theme_minimal()


#------------------------------------------------
wvp <- melt(ch,
            id = c("index") ,
            measure = c("WVP1", "WVP2"))
wvp_comp <- melt(ch_comp,
            id = c("index") ,
            measure = c("WVP1", "WVP2"))

wvp$Channel <- wvp$variable
wvp_comp$Channel <- wvp_comp$variable

wvp$variable    <-
  factor(wvp$variable,
         levels = c("WVP1", "WVP2"),
         labels = c("WVP1", "WVP2"))
wvp_comp$variable    <-
  factor(wvp_comp$variable,
         levels = c("WVP1", "WVP2"),
         labels = c("WVP1", "WVP2"))

strip_wvp_OF<-wvp_comp%>%
  filter(variable=='WVP1')
strip_wvp_EU<-wvp%>%
  filter(variable=='WVP1')
join_wvp<-left_join(strip_wvp_EU,strip_wvp_OF,by='index')

join_wvp1<-join_wvp%>%
  select(index,variable.x,value.x,Channel.x,value.y)%>%
  rename(variable=variable.x,value_EU=value.x,channel=Channel.x,value_OF=value.y)

#for wvp2 variable:
strip_wvp2_OF<-wvp_comp%>%
  filter(variable=='WVP2')
strip_wvp2_EU<-wvp%>%
  filter(variable=='WVP2')
join_wvp2<-left_join(strip_wvp2_EU,strip_wvp2_OF,by='index')

join_wvp22<-join_wvp2%>%
  select(index,variable.x,value.x,Channel.x,value.y)%>%
  rename(variable=variable.x,value_EU=value.x,channel=Channel.x,value_OF=value.y)

#total_co2<-rbind(join_wvp1,join_wvp22)


#plotting water vapor pressure:

v4<-ggplot()+
  geom_line(data=join_wvp1,aes(x=index,y=value_EU,color='EU Channel 1'))+
  geom_line(data=join_wvp22,aes(x=index,y=value_EU,color='EU Channel 2'),linetype='twodash')+
  geom_line(data=join_wvp1,aes(x=index,y=value_OF,color='OF Channel 1'))+
  geom_line(data=join_wvp22,aes(x=index,y=value_OF,color='OF Channel 2'),linetype='twodash')+
  #geom_line(data = total_co2,aes(x=index,y=value_EU,color='EU',linetype=channel))+
  #geom_line(data = total_co2,aes(x=index,y=value_OF,color='OF',linetype=channel))+
  scale_color_manual(name='Condition and Channel',
                     values=c('red','blue','green','black'))+
  scale_x_continuous(limits = c(0, 1380), breaks = (c(seq(0, 1380, 120)))) +
  labs(x = "Time, Minutes", y = "Water Vapor Pressure") +
  ggtitle("Water Vapor Pressure: Channels 1 and 2") +
  theme(axis.title.x = element_blank(),
        axis.text.x = element_blank()) +
  theme_minimal()

#------------------------------------------------

ss <- melt(ch,
           id = c("index") ,
           measure = c("SFR1", "SFR2"))
ss_comp <- melt(ch_comp,
           id = c("index") ,
           measure = c("SFR1", "SFR2"))

ss$Channel <- ss$variable
ss_comp$Channel <- ss_comp$variable

ss$variable    <-
  factor(ss$variable,
         levels = c("SFR1", "SFR2"),
         labels = c("SFR1", "SFR2"))
ss_comp$variable    <-
  factor(ss_comp$variable,
         levels = c("SFR1", "SFR2"),
         labels = c("SFR1", "SFR2"))

##Combining the data:
strip_ss_OF<-ss_comp%>%
  filter(variable=='SFR1')
strip_ss_EU<-ss%>%
  filter(variable=='SFR1')
join_ss<-left_join(strip_ss_EU,strip_ss_OF,by='index')

join_ss1<-join_ss%>%
  select(index,variable.x,value.x,Channel.x,value.y)%>%
  rename(variable=variable.x,value_EU=value.x,channel=Channel.x,value_OF=value.y)

#for wvp2 variable:
strip_ss2_OF<-ss_comp%>%
  filter(variable=='SFR2')
strip_ss2_EU<-ss%>%
  filter(variable=='SFR2')
join_ss2<-left_join(strip_ss2_EU,strip_ss2_OF,by='index')

join_ss22<-join_ss2%>%
  select(index,variable.x,value.x,Channel.x,value.y)%>%
  rename(variable=variable.x,value_EU=value.x,channel=Channel.x,value_OF=value.y)

#total_co2<-rbind(join_wvp1,join_wvp22)

## Plotting

v3<-ggplot()+
  geom_line(data=join_ss1,aes(x=index,y=value_EU,color='EU Channel 1'))+
  geom_line(data=join_ss22,aes(x=index,y=value_EU,color='EU Channel 2'),linetype='twodash')+
  geom_line(data=join_ss1,aes(x=index,y=value_OF,color='OF Channel 1'))+
  geom_line(data=join_ss22,aes(x=index,y=value_OF,color='OF Channel 2'),linetype='twodash')+
  #geom_line(data = total_co2,aes(x=index,y=value_EU,color='EU',linetype=channel))+
  #geom_line(data = total_co2,aes(x=index,y=value_OF,color='OF',linetype=channel))+
  scale_color_manual(name='Condition and Channel',
                     values=c('red','blue','green','black'))+
  scale_x_continuous(limits = c(0, 1380), breaks = (c(seq(0, 1380, 120)))) +
  labs(x = "Time, Minutes", y = "SS Flow Rate, ml/min") +
  ggtitle("SS Flow Rate: Channels 1 and 2") +
  theme(axis.title.x = element_blank(),
        axis.text.x = element_blank()) +
  theme_minimal()


#------------------------------------------------
#For the ratio of oxygen to carbon dioxide:

vo2_vco2 <- melt(ch,
                 id = c("index") ,
                 measure = c("VO2", "VCO2"))
vo2_vco2_comp <- melt(ch_comp,
                 id = c("index") ,
                 measure = c("VO2", "VCO2"))

vo2_vco2$Channel <- vo2_vco2$variable
vo2_vco2_comp$Channel <- vo2_vco2_comp$variable

vo2_vco2$variable    <-
  factor(
    vo2_vco2$variable,
    levels = c("VO2", "VCO2"),
    labels = c("VO2", "VCO2")
  )
vo2_vco2_comp$variable    <-
  factor(
    vo2_vco2_comp$variable,
    levels = c("VO2", "VCO2"),
    labels = c("VO2", "VCO2")
  )
#Combining the data:
strip_ratio_OF<-vo2_vco2_comp%>%
  filter(variable=='VO2')
strip_ratio_EU<-vo2_vco2%>%
  filter(variable=='VO2')
join_ratio<-left_join(strip_ratio_EU,strip_ratio_OF,by='index')

join_ratio1<-join_ratio%>%
  select(index,variable.x,value.x,Channel.x,value.y)%>%
  rename(variable=variable.x,value_EU=value.x,channel=Channel.x,value_OF=value.y)

#for second ratio variable:
strip_ratio2_OF<-vo2_vco2_comp%>%
  filter(variable=='VCO2')
strip_ratio2_EU<-vo2_vco2%>%
  filter(variable=='VCO2')
join_ratio2<-left_join(strip_ratio2_EU,strip_ratio2_OF,by='index')

join_ratio2_2<-join_ratio2%>%
  select(index,variable.x,value.x,Channel.x,value.y)%>%
  rename(variable=variable.x,value_EU=value.x,channel=Channel.x,value_OF=value.y)


#Plotting

v6<-
  ggplot()+
  geom_line(data=join_ratio1,aes(x=index,y=value_EU,color='EU Channel 1'))+
  geom_line(data=join_ratio2_2,aes(x=index,y=value_EU,color='EU Channel 2'),linetype='twodash')+
  geom_line(data=join_ratio1,aes(x=index,y=value_OF,color='OF Channel 1'))+
  geom_line(data=join_ratio2_2,aes(x=index,y=value_OF,color='OF Channel 2'),linetype='twodash')+
  #geom_line(data = total_co2,aes(x=index,y=value_EU,color='EU',linetype=channel))+
  #geom_line(data = total_co2,aes(x=index,y=value_OF,color='OF',linetype=channel))+
  scale_color_manual(name='Condition and Channel',
                     values=c('red','blue','green','black'))+
  scale_x_continuous(limits = c(0, 1380), breaks = (c(seq(0, 1380, 120)))) +
  labs(x = "Time, Minutes", y = "VO2 and VCO2") +
  ggtitle("VO2 and VCO2") +
  theme(axis.title.x = element_blank(),
        axis.text.x = element_blank()) +
  theme_minimal()

#------------------------------------------------
#Plotting flow rate

v5<-ggplot()+
  geom_line(data=ch,aes(x=index,y=FR,color='EU'))+
  geom_line(data=ch_comp,aes(x=index,y=FR,color='OF'))+
  scale_color_manual(name='Condition',
                     values=c('red','blue'))+
  scale_x_continuous(limits = c(0, 1380), breaks = (c(seq(0, 1380, 120)))) +
  labs(x = "Time, Minutes", y = "Flow Rate") +
  ggtitle("Flow Rate") +
  theme(axis.title.x = element_blank(),
        axis.text.x = element_blank()) +
  theme_minimal()


#------------------------------------------------
#Plotting energy expenditure:

v7 <- ggplot() +
  geom_line(data=ch, aes(x = index, y = kcal_min,color='EU')) +
  geom_line(data=ch_comp, aes(x = index, y = kcal_min,color='OF')) +
  scale_color_manual(name='condition',
                     values=c("blue", "red")) +
  scale_x_continuous(limits = c(0, 1380), breaks = (c(seq(0, 1380, 120)))) +
  labs(x = "Time, Minutes", y = "EE") +
  ggtitle("Energy Expenditure") +
  theme(axis.title.x = element_blank(),
        axis.text.x = element_blank()) +
  theme_minimal()

#------------------------------------------------
#plotting RER

v8 <- ggplot() +
  geom_line(data=ch, aes(x = index, y = RQ,color="EU")) +
  geom_line(data=ch_comp, aes(x = index, y = RQ,color='OF')) +
  scale_color_manual(name='condition',
                     values=c("blue", "red")) +
  scale_x_continuous(limits = c(0, 1380), breaks = (c(seq(0, 1380, 120)))) +
  labs(x = "Time, Minutes", y = "RER") +
  ggtitle("RER") +
  theme(axis.title.x = element_blank(),
        axis.text.x = element_blank()) +
  theme_minimal() 

```

## Generate the report

```{r}
library(patchwork)

library(ggpmisc)

t1 <- ggplot() +
annotate(geom = "table",
           x = 0,
           y = 0,
           label = list(combo))  +
  ggtitle("Results") +
  theme_void()


#f <- (t1 | v1 | v2) / (v3 | v4 | v5) / (v6 | v7 | v8) + plot_annotation(tag_levels = "1", tag_suffix = '.')
f <- (t1 | v1 ) / (v2|v3)/(v4 | v5) / (v6 | v7)/(v8) + plot_annotation(tag_levels = "1", tag_suffix = '.')

#f <- (v1 | v2 | v3) / (v4 | v5 | v6) / (v7 | v8 | v9) / (v10 | v11)+ plot_annotation(tag_levels = "1", tag_suffix = '.')

library("stringr")
output.file <- str_replace_all(txt.file,"INPUT_OF", "OUTPUT") 

output.file <- str_replace_all(output.file,".txt", ".pdf") 
output.file <- str_replace_all(output.file,"OF", "EU_OF_COMP") 

ggsave(
  f,
  file = output.file,
  width = 20 * 1.9,
  height = 25.4 * 1.9,
  units = "cm",
  dpi = 300
)

```