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NEWS.Rmd
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NEWS.Rmd
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---
output: github_document
---
<!-- NEWS.md is generated from NEWS.Rmd. Please edit that file -->
```{r, include = FALSE}
library(FielDHub)
knitr::opts_chunk$set(
collapse = TRUE,
comment = NA,
fig.path = "man/figures/README-",
out.width = "100%"
)
```
# Changelog
# FielDHub 1.3.1
### New Features in the Shiny App
* Added a module to generate **Sparse allocation**.
* Added a module for generating **Optimized Multi-Location Partially Replicated (p-rep)**.
* Added **vignettes and help documentation** for all the new modules; Sparse Allocations and Optimized Multi-Location Partially Replicated (p-rep) Designs in the app.
### Enhancements:
* Renamed the **Partially Replicated** module to **Single and Multi-Location p-rep**
* Improved the usability of the field dimensions dropdown menu by reordering the options based on the absolute value of the difference between the number of rows and columns for each option. This affects unreplicated and partially replicated design modules.
### Fix bugs:
* Fixed issue: Upload data in the CRD module.
### New Features in the `FielDHub` Package:
### Standalone Functions
* Created the `do_optim()` function. This function generates the sparse or p-rep allocation to multiple locations. It optimized the allocation by using incomplete blocks.
* Created the `sparse_allocation()` function. This new function uses the other function, `do_optim()`, to generate the sparse allocation, then uses the function `diagonal_arrangement()` to create unreplicated designs across multiple locations.
* Created the `multi_location_prep()` function. It uses within the optimization function
`do_optim()` to generate the partially replicated (p-rep) allocation, then uses the function `partially_replicated()` to create the p-rep designs across multiple locations.
* Created the `pairs_distance()` function. This function calculates pairwise distances between all elements in a matrix that appears twice or more.
* Created the `swap_pairs()` function. It swaps pairs in a matrix of integers and optimizes the p-rep design. This function modifies the input matrix $X$ to ensure that the distance between any two occurrences of the same integer is at least a distance $d$, by swapping one of the occurrences with a random occurrence of a different integer that is at least $d$ away. The function
starts with starting dist at $d = 3$ and increases it by $1$ until the algorithm no longer
converges or the max number of iterations have been performed.
* Created the `search_matrix_values()` function. It looks for values that appear in the same row in a matrix and return the row number, value, and frequency.
* Added optimization process for the partially replicated (p-rep) designs. It uses the function `swap_pairs()`.
* Added **vignettes and help documentation** for all the new functions.
### Enhancements:
* `partially_replicated()` accepts custom field dimensions at each location. For example,
`nrows = c(23, 20, 20)` and `ncols = c(20, 23, 23)` are the field rows and columns for the three environments.
* Code refactoring on the `diagonal_arrangement()` function.
* Code refactoring on the utility function `pREP()`.
* Avoid cyclic reps in incomplete block designs when the number of treatments is square.
# FielDHub 1.2.0
### Shiny App
* Added a `help` menu option in the app that connect you directly to the documentation available in our GitHub repository.
* Added **vignettes and help documentation** for all standard functions and modules available for all designs in the app.
* Added capability for making multiple randomizations across different **locations** to the unreplicated, partially replicated, lattice, RCBD, factorial, split-plot, split-split-plot, strip-plot, IBD, and RCD designs.
* Added capability to produce **heatmap visualizations** of simulated data for all experimental designs.
* Added action buttons to **copy and save field maps and field book outputs to Excel.**
* Added **factorization options that aid users in the creation of randomizations and mapping layouts** for the unreplicated and partially replicated designs. Previous version required users to do the * mathematical calculation a priori.
* Added **filters and search** boxes for the field book tables.
* Updated UI/UX design for home page.
* Grouped single diagonal arrangement, multiple diagonal arrangement, optimized arrangement and augmented RCB designs under one single module.
* Added action run button to all experimental designs to prevent reactivity issues with the application.
* Improved and standardized user experience features and readability access.
* Improved error logging messages. Added features to inform end-users on the utilization of correct input data file formats and associated metadata/columns, checking for duplicate values in input files, as well as data type verification.
* Added the plot() method to the FielDHub package to display the field layout of the field book for all designs.
* Added **additional field layout visualization/map options** to all experimental designs. Previous version only had mapping options for unreplicated and p-rep designs.
* Added a drop-down menu to display a **multiple layout mapping option shown by entry number and by plot** for all experimental designs. This means, that now you can visualize each randomization layout option for each of the locations you input.
* Added an option for repeating whole entries/experiments in the unreplicated diagonal arrangement design with multiple experiments (previously called decision blocks).
* Added a check box feature in the Augmented RCB design to allow for the creation of nurseries with the option of randomizing experimental entries or not. If user decides to leave this option unchecked, only the checks will be randomized, and the experimental entries will be shown in consecutive order.
* Added a check box option to the RCB design to allow for a continuous plot numbering independently of the rep or block number. Previous version coded the replication into the plot number (i.e., 101 =rep1, 201=rep2, etc.).
* Fixed a restriction in the RCBD mapping layout to allow for the use of more than 25 entries. PS: There are better designs when the number of entries is higher than 25 (for more info go to: [FIELD PLOT DESIGN I](https://www.ndsu.edu/faculty/horsley/)).
### Standalone Functions in `FielDHub` Package
* `partially_replicated()` now generates randomization across multiple locations/sites.
* `diagonal_arrangement()` now generates randomization across multiple locations/sites.
* `optimized_arrangement()` now generates randomization across multiple locations/sites.
* `partially_replicated()` now allows that all entries/treatments have replicates. Before, it required at least some unreplicated entries.
* Functions `optimized_arrangement()`, `diagonal_arrangement()` and `partially_replicated()` now return feedback if the input dimensions `nrows` and `ncols` are incorrect.
* `RCBD()` now includes an argument (`continuous`) to manage the way it sets up the plotting number.
* `RCBD_augmented()` now allows customization of the field dimensions by inputting the number of rows and columns through `nrows` and `ncols` arguments.
* `RCBD_augmented()` now returns feedback if the input dimensions `nrows` and `ncols` do not match the data entered.
* `RCBD_augmented()` when `random = FALSE` now allows only randomizing the checks/controls if the user wants.
* Fixed a bug in `full_factorial()` for the CRD factorial design that prevented the option of including all possible factorial combinations.
* Added a method `print()` of class `fieldLayout`. See [print()](https://didiermurillof.github.io/FielDHub/reference/print.fieldLayout.html).
* Added a method `plot()` of class `FieldHub` that returns an object of class `fieldLayout`.
See [plot()](https://didiermurillof.github.io/FielDHub/reference/plot.FielDHub.html). The method `plot()` can plot a field layout for any of the designs output. It is possible to pass arguments such as the location, layout order and others. For more detail see
[plot(), print() and summary() methods in FielDHub](https://didiermurillof.github.io/FielDHub/articles/methods.html).
* Fixed a bug in `diagonal_arrangement()` when `kindExpt = DBUDC`. The problem affected the random distribution of the checks for the case of unbalanced control plot numbers for each experiment.
* Fixed a bug in `diagonal_arrangement()` when `kindExpt = DBUDC`. The problem affected merging data between the user data and randomization data when users wanted replicated entries across experiments.
# FielDHub 0.1.0
CRAN release.