---
title: "Single-Factor Design: CRD"
description: >
  Complete Randomize Design
vignette: >
  %\VignetteIndexEntry{DoE-1_CRD}
  %\VignetteEncoding{UTF-8}
  %\VignetteEngine{quarto::html}
knitr:
  opts_chunk: 
    collapse: true
    comment: '#>'
    echo: false
    warning: false
    message: false
editor_options: 
  chunk_output_type: console
---

```{r setup, include=FALSE}
source("https://raw.githubusercontent.com/Flavjack/inti/master/pkgdown/favicon/docs.r")
```

Planning an experiment follows a reproducible routine:

1. **Load required libraries:** Load `inti`, `knitr`, and `dplyr` packages.
1. **Define factor levels:** Set up lists with genotypes, treatments, and management factors.
1. **Dispatch design generator:** Choose between CRD, RCBD, Split-plot, or Augmented designs.
1. **Plot the field sketch:** Verify spatial layouts and serpentine/zigzag sequences.
1. **Label design:** Design the experimental labels to facilitate the data collection.
5. **Export to Field Book app:** Generate field-ready sheets with trait parameters.

```{r}
#| echo: true

# Install packages and dependencies

library(inti)
library(dplyr)
library(huito)
```

# Completely Randomized Design (CRD)

The Completely Randomized Design is recommended when experimental units are homogeneous, such as germination chambers, lab assays, or controlled greenhouse benches.

```{r, echo=TRUE}
# 1. Define salinity levels (NaCl concentrations in mM)
factors_crd <- list(
  NaCl= c("0", "50", "100", "150", "200")
)

# 2. Generate CRD layout (5 treatments x 4 replications = 20 petri dishes/units)
crd_exp <- design_repblock(
  factors = factors_crd,
  type = "crd",
  rep = 4,
  zigzag = TRUE,
  seed = 2026
)

# Fieldbook preview
crd_exp$fieldbook %>% 
  head(10) %>% 
  knitr::kable(caption = "CRD Fieldbook preview")

# Layout on germination chamber shelves

tarpuy_plotdesign(
  data = crd_exp,
  factor = "NaCl",
  fill = c("plots", "NaCl")
)
```

# Label 

The experimental field book generated by the design is used as the input data for label creation. Each row represents an experimental unit, allowing the automatic generation of individualized labels.

```{r, echo=TRUE}
# Experimental fieldbook
fb <- crd_exp$fieldbook
```

# Customize the label layout

The label layout can be customized by combining text, images and QR codes. Each layer can use values from the experimental field book, allowing automatic generation of labels for every experimental plot.

Load package and import fonts.

```{r, echo=TRUE}
font <- c("Permanent Marker", "Tillana", "Courgette")

huito_fonts(font)
```

> You can find more fonts in <https://fonts.google.com/>

# Label design

```{r}
#| echo: true

label <- fb %>%
  label_layout(
    size = c(5.2, 10)
    ,
    border_color = "#5C0000"
    ,
    border_width = 1.5
  ) %>%
  include_image(
    value = "https://inkaverse.com/img/inkaverse.png"
    ,
    size = c(1.3, 1.5)
    ,
    position = c(0.8, 9.1)
  )  %>%
  include_text(
    value = "plots"
    ,
    position = c(4.2, 9.1)
    ,
    size = 20
    ,
    color = "black"
    ,
    fontface = "bold"
    ,
    font = font[1]
  )  %>%
  include_image(value = "https://huito.inkaverse.com/img/scale.pdf"
                ,
                size = c(5, 1)
                ,
                position = c(2.6, 7.7)) %>%
  include_barcode(value = "qrcode"
                  ,
                  size = c(5, 5)
                  ,
                  position = c(2.6, 4.7)) %>%
  include_text(
    value = "NaCl"
    ,
    position = c(2.6, 1.7)
    ,
    size = 12
    ,
    prefix = "NaCl: "
    ,
    color = "blue"
    ,
    font = font[2]
    , 
    fontface = "bold"
  )  %>%
  include_image(value = "https://huito.inkaverse.com/img/scale.pdf"
                ,
                size = c(5, 1)
                ,
                position = c(2.6, 0.6)) 
```

## Label preview

The preview mode `label_print(mode = "preview")` generate a example of the label design from a random row of the data set.

```{r}
label %>% 
  label_print(mode = "preview")
```

## Generate the complete labels

If you want generate the complete labels list, change: `label_print(mode = "complete")`.

```{r echo = TRUE}
#| eval: false
label %>% 
  label_print(mode = "complete"
              , filename = "vertical-DCA-1"
              , nlabels = 12)
```

<!-- <embed src="vertical-DCA-1.pdf" height="600" width="100%" alt="pdf" pluginspage="http://www.adobe.com/products/acrobat/readstep2.html"> -->

