This vignette shows how to generate a Latin square
design using both the FielDHub Shiny App and the scripting
function latin_square()
from the FielDHub
package.
To launch the app you need to run either
::run_app() FielDHub
or
library(FielDHub)
run_app()
Once the app is running, go to Other Designs > Latin Square Design
Then, follow the following steps where we show how to generate this kind of design by an example with 5 treatments and 2 reps.
If the selection is No
, that means the app is going
to generate synthetic data for entries and names of the treatment based
on the user inputs.
If the selection is Yes
, the entries list must
fulfill a specific format and must be a .csv
file. The file
must have the three columns: ROW
, COLUMN
and
TREATMENT
. All of those columns contain a list of unique
names that identify each treatment. Duplicate values are not allowed,
all entries must be unique. In the following table, we show an example
of the entries list format. This example has an entry list with 5
treatments.
ROW | COLUMN | TREATMENT |
---|---|---|
Period1 | Cow1 | Diet1 |
Period2 | Cow2 | Diet2 |
Period3 | Cow3 | Diet3 |
Period4 | Cow4 | Diet4 |
Period5 | Cow5 | Diet5 |
Input the number of treatments in the Input # of Treatments box. In the alpha lattice design, the number of treatments must be a composite number.
Select the number of replications of these treatments with the Input # of Full Reps box. The number of treatments and the number of full reps set the dimensions of the field.
Select serpentine
or cartesian
in the
Plot Order Layout. For this example we will use the
default serpentine
layout.
Enter the starting plot number in the Starting Plot Number box. If the experiment has multiple locations, you must enter a comma separated list of numbers the length of the number of locations for the input to be valid.
Enter a name for the location of the experiment in the Input Location box. A completely randomized design can only be run in a single location at a time.
To ensure that randomizations are consistent across sessions, we
can set a seed number in the box labeled Seed Number.
In this example, we will set it to 123
.
Once we have entered the information for our experiment on the left side panel, click the Run! button to run the design.
After you run a Latin square design in FielDHub, there are several ways to display the information contained in the field book.
When you first click the run button on a Latin square design,
FielDHub displays the Field Layout tab, which shows the entries and
their arrangement in the field. In the box below the display, you can
change the layout of the field. You can also display a heatmap over the
field by changing Type of Plot to Heatmap
.
To view a heatmap, you must first simulate an experiment over the
described field with the Simulate! button. A pop-up
window will appear where you can enter what variable you want to
simulate along with minimum and maximum values.
The Field Book displays all the information on the experimental design in a table format. It contains the specific plot number and the row and column address of each entry, as well as the corresponding treatment on that plot. This table is searchable, and we can filter the data in relevant columns. If we have simulated data for a heatmap, an additional column for that variable appears in the field book.
FielDHub
function:
latin_square()
You can run the same design with a function in the FielDHub package,
latin_square()
.
First, you need to load the FielDHub
package typing,
library(FielDHub)
Then, you can enter the information describing the above design like this:
<- latin_square(
lsd t = 5,
reps = 2,
plotNumber = 101,
planter = "serpentine",
seed = 1238
)
latin_square()
abovet = 5
is the number of treatments.reps = 2
is the number of replications (squares).plotNumber = 101
is the starting plot number.planter = "cartesian"
is the plot order layout.locationNames = "FARGO"
is an optional name for the
location.seed = 1238
is the seed number to replicate identical
randomizations.lsd
objectprint(lsd)
Latin Square Design:
Information on the design parameters:
List of 4
$ treatments : int 5
$ squares : num 2
$ locationName: NULL
$ seed : num 1238
10 First observations of the data frame with the latin_square field book:
ID LOCATION PLOT SQUARE ROW COLUMN TREATMENT
1 1 1 101 1 Row 1 Column 1 T5
2 2 1 102 1 Row 1 Column 2 T1
3 3 1 103 1 Row 1 Column 3 T2
4 4 1 104 1 Row 1 Column 4 T4
5 5 1 105 1 Row 1 Column 5 T3
6 6 1 110 1 Row 2 Column 1 T4
7 7 1 109 1 Row 2 Column 2 T2
8 8 1 108 1 Row 2 Column 3 T3
9 9 1 107 1 Row 2 Column 4 T1
10 10 1 106 1 Row 2 Column 5 T5
lsd
objectThe latin_square()
function returns a list consisting of
all the information displayed in the output tabs in the FielDHub app:
design information, plot layout, plot numbering, entries list, and field
book. These are accessible by the $
operator,
i.e. lsd$layoutRandom
or lsd$fieldBook
.
lsd$fieldBook
is a list containing information about
every plot in the field, with information about the location of the plot
and the treatment in each plot. As seen in the output below, the field
book has columns for ID
, LOCATION
,
PLOT
, SQUARE
, ROW
,
COLUMN
, and TREATMENT
.
<- lsd$fieldBook
field_book head(lsd$fieldBook, 10)
ID LOCATION PLOT SQUARE ROW COLUMN TREATMENT
1 1 1 101 1 Row 1 Column 1 T5
2 2 1 102 1 Row 1 Column 2 T1
3 3 1 103 1 Row 1 Column 3 T2
4 4 1 104 1 Row 1 Column 4 T4
5 5 1 105 1 Row 1 Column 5 T3
6 6 1 110 1 Row 2 Column 1 T4
7 7 1 109 1 Row 2 Column 2 T2
8 8 1 108 1 Row 2 Column 3 T3
9 9 1 107 1 Row 2 Column 4 T1
10 10 1 106 1 Row 2 Column 5 T5
For plotting the layout in function of the coordinates
ROW
and COLUMN
, you can use the the generic
function plot()
as follow,
plot(lsd)