---
title: "Analyzing WRIC Data: Zero Tests and Methanol Burns"
output: rmarkdown::html_vignette
vignette: >
  %\VignetteIndexEntry{test_analysis}
  %\VignetteEngine{knitr::rmarkdown}
  %\VignetteEncoding{UTF-8}
---

```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>"
)
```

```{r setup}
library(wrictools)
```

# Introduction

This vignette shows how to analyze **Zero Tests** and **Methanol Burn experiments** using `analyse_zero_test()` and `analyse_methanol_burn()`.

---

# Zero Test Analysis

A zero test checks the baseline VO2 and VCO2 of the WRIC system, the mean should be 0 and the standard deviation low and both should be constant over time. Use `analyse_zero_test()` with a data file to get plots and statistics.

```{r}
# Example file included with the package
filepath <- system.file("extdata", "data.txt", package = "wrictools")

# Analyse zero test
zero_stats <- analyse_zero_test(filepath)

print(zero_stats)
```

As you can see the example data provided with this package does not look like a zero test, which you can also see when looking at the statistics. This vignette is intended as a quick example on how to use the package. If you change the file to your own zero test you can quickly assess whether the mean is 0, the standard deviation or whether there is an offset. 

# Methanol Burn Analysis

Methanol burns validate energy measurements in the WRIC. Use `analyse_methanol_burn()` with a WRIC data file and a methanol measurement file. The measurement file needs two columns named `datetime`and `methanol`. Datetime by default assume this format "2023-11-13 22:00", but you can specify your own dateformat and give it as a parameter to the function.

```{r}
# Example WRIC file
data_txt <- system.file("extdata", "data.txt", package = "wrictools")

# Made up methanol measurements to show functionality
methanol_df <- data.frame(
  datetime = as.POSIXct(c(
    "2023-11-13 22:00", "2023-11-13 23:30", "2023-11-14 03:00", "2023-11-14 06:00", "2023-11-14 08:00"
  ), format = "%Y-%m-%d %H:%M"),
  methanol = c(4842.9, 4785.7, 4758.6, 4675.1, 4629.2)
)
methanol_file <- tempfile(fileext = ".csv")
write.csv(methanol_df, methanol_file, row.names = FALSE)

# Analyse methanol burn
methanol_results <- analyse_methanol_burn(filepath = data_txt, methanolfilepath = methanol_file)

print(methanol_results)
```
Again these results are non-sense because the wric-data we're analyzing is not a methanol burn and the methanol measurements are fictional as well. But you can easily see the information the function returns. 

We can see the different measurements and most importantly the deviation between calculated and measured VO2 and VCO2 for each interval, meaning each time period between two measurements in the methanol measurement file. This deviation should ideally be 0. If it is not, check whether this might be at the beginning or end of the file where a door or hatch might have been opened. There is an additional table showing the same measurements for the entire period - if you use these values make sure to cut of any time in the beginning or end that might show noise from the door opening. You can easily do that by specifying start and end parameters.

Additionally, 4 plots are created showing predicted vs measured O2 and CO2 over time. It is important to note that the value from one interval is plotted at the end point of that interval. The other two plots show RER over time and the methanol burn rate.