https://github.com/adrientaudiere/mitemaptools

https://github.com/adrientaudiere/mitemaptools

Repository

README.Rmd

---
output: github_document
editor_options: 
  chunk_output_type: console
---


```{r, include = FALSE}
knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  fig.path = "man/figures/README-",
  out.width = "100%"
)
```

# MiteMapTools

The goal of MiteMapTools is to ...

[Masier et al. 2022](https://onlinelibrary.wiley.com/doi/10.1002/jez.2651)

https://github.com/LR69/MiteMap/tree/MiteMap.v6

## Installation

You can install the development version of MiteMapTools from [GitHub](https://github.com/) with:

```{r, eval=FALSE}
# install.packages("pak")
pak::pak("adrientaudiere/MiteMapTools")
```

## Example

This is a basic example which shows you how to solve a common problem:

```{r example}
library(MiteMapTools)

MM_filtered_centered <- filter_mitemap(MM_example, center_x = -20, center_y = -20)
vioplot_mitemap(MM_filtered_centered)
```

A input folder for MiteMapTools consist of a
 - a metadata file (in xlsx or csv) with 8 columns:
    - Run number
    - File name (must be present in the list of zip files)
    - Date
    - Start time
    - Farm
    - MiteMap number
    - Bag
    - Modality 

 - a list of zip files with 4 files compressed inside
    - A raw data file with 4 columns
        - The time in second (position is recorded every 0.2s)
        - The position in x (in mm)
        - The position in y (in mm)
        - Boolean variable indicating if the individual has remained immobile since the last record (1 if immobile)
    - A png file figuring the position of the individual using an heatmap 
    - A processed data file called "formeD" (also called HH) compute the time spent in an area 
    defined by the half side of the arena (see figure \@ref(fig:cars-plot)).
        - The date and hour of the experiment
        - The name of the MiteMap run
        - Total time spent in the half containing the odor source (second)
        - Total time spent in the opposite half (second)
        - Time spent immobile in the half containing the odor source (second)
        - Time spent immobile in the opposite half (second)
        - Total distance traveled in the half containing the odor source (mm)
        - Total distance traveled in the opposite half (mm)
    - A processed data file called "formeC" (also called CH) compute the time spent in an area 
    defined by a circle center on the odor source (see figure \@ref(fig:cars-plot)) encompassing half of the 
    arena surface.
        - The date and hour of the experiment
        - The name of the MiteMap run
        - Total time spent in the half containing the odor source (second)
        - Total time spent in the opposite half (second)
        - Time spent immobile in the half containing the odor source (second)
        - Time spent immobile in the opposite half (second)
        - Total distance traveled in the half containing the odor source (mm)
        - Total distance traveled in the opposite half (mm)
        
```{r shape, echo=FALSE}
library(tidyverse)
library(patchwork)
circleFun <- function(center = c(0, 0), diameter = 1, npoints = 100) {
  r <- diameter / 2
  tt <- seq(0, 2 * pi, length.out = npoints)
  xx <- center[1] + r * cos(tt)
  yy <- center[2] + r * sin(tt)
  return(data.frame(x = xx, y = yy))
}

dat <- circleFun(c(0, 0), 40, npoints = 1000)
dat_C_interm <- circleFun(c(-20, 0), (26.0714 * 40 / 22.5), npoints = 1000)

# compute value of intersection (-6.57, 18.89) https://planetcalc.com/8098/
dat_C <- dat_C_interm[dat_C_interm$x > -6.57, ]
dat_C2 <- dat[dat$x < -6.57, ]
dat_C <- rbind(dat_C, dat_C2)


ggplot(dat, aes(x, y)) +
  geom_path() +
  coord_fixed() +
  theme_minimal() +
  geom_vline(xintercept = 0) +
  geom_polygon(data = mutate(dat, x = ifelse(x > 0, 0, x)), fill = "green") +
  geom_polygon(data = dat_C, fill = "blue", alpha = 0.4) +
  geom_point(x = -19.5, y = 0, size = 7, shape = 8, color = "red") +
  geom_label(x = -14, y = 0, label = "Odor source", color = "red") +
  geom_label(x = 5, y = 0, label = "CH shape", color = "blue", hjust = 0) +
  geom_label(x = 1, y = 18, label = "HH shape", color = "green", hjust = 0) +
  xlab("x (in mm)") +
  ylab("y (in mm)")
```

        

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