This vignette shows how to generate a Strip-Plot
Design using both the FielDHub Shiny App and the scripting
function srip_plot()
from the FielDHub
package.
1. Using the FielDHub Shiny App
To launch the app you need to run either
FielDHub::run_app()
or
Once the app is running, go to Other Designs > Strip-Plot Design
Then, follow the following steps where we show how to generate this kind of design by an example with 6 factors for the horizontal strips, 4 factors for the vertical strips and 3 reps. We will run this experiment in just one location.
Inputs
-
Import entries’ list? Choose whether to import a
list with entry numbers and names for treatments.
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 single columnTREATMENT
, containing a list of unique names that identify each treatment. Duplicate values are not allowed, all entries must be unique. In the following, we show an example of the entries list format. This example has an entry list with 10 treatments.
HPLOTS | VPLOTS |
---|---|
A0 | B0 |
A1 | B1 |
A2 | B2 |
A3 | B3 |
A4 | B4 |
Input the number of factors for horizontal strips in the Input # of Horizontal Strips box. Set it to
6
.Input the number of factors for vertical strips in the Input # of Vertical Strips box. Set it to
4
.Select the number of replications of this experiment with the Input # of Full Reps box. Set it to
3
.Enter the number of locations in Input # of Locations. We will run this experiment over a single location, so set it to
1
.Select
serpentine
orcartesian
in the Plot Order Layout. For this example we will use the defaultserpentine
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. For this case, set it to
101
.Enter a name for the location of the experiment in the Input Location box. If there are multiple locations, each name must be in a comma separated list. Set it to
"FARGO"
.To ensure that randomizations are consistent across sessions, we can set a random seed in the box labeled random seed. In this example, we will set it to
1237
.Once we have entered the information for our experiment on the left side panel, click the Run! button to run the design.
Outputs
After you run a strip-plot design in FielDHub, there are several ways to display the information contained in the field book.
Field Layout
When you first click the run button on a strip-plot 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.
Field Book
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.
2. Using the FielDHub
function:
strip_plot()
You can run the same design with a function in the FielDHub package,
strip_plot()
. We can enter the information describing the
above design like this:
You can run the same design with a function in the FielDHub package,
strip_plot()
.
First, you need to load the FielDHub
package typing,
Then, you can enter the information describing the above design like this:
strip <- strip_plot(
Hplots = 6,
Vplots = 4,
b = 3,
l = 1,
plotNumber = 101,
planter = "serpentine",
locationNames = "FARGO",
seed = 1240
)
Details on the inputs entered in strip_plot()
above
The description for the inputs that we used to generate the design,
-
Hplots = 6
is the number of horizontal strips -
Vplots = 4
is the number of vertical strips -
b = 3
is the number of reps -
l = 1
is the number of locations. -
plotNumber = 101
is the starting plot number. -
planter = "cartesian"
is the order layout. -
locationNames = "FARGO"
is an optional name for each location. -
seed = 1240
is the random seed to replicate identical randomizations.
Print strip
object
print(strip)
Strip Plot Design
Information on the design parameters:
List of 6
$ Hplots : int 6
$ Vplots : int 4
$ blocks : num 3
$ numberLocations: num 1
$ nameLocations : chr "FARGO"
$ seed : num 1240
10 First observations of the data frame with the strip_plot field book:
ID LOCATION PLOT REP HSTRIP VSTRIP TRT_COMB
1 1 FARGO 101 1 b1 a0 b1|a0
2 2 FARGO 102 1 b1 a1 b1|a1
3 3 FARGO 103 1 b1 a3 b1|a3
4 4 FARGO 104 1 b1 a2 b1|a2
5 5 FARGO 108 1 b3 a0 b3|a0
6 6 FARGO 107 1 b3 a1 b3|a1
7 7 FARGO 106 1 b3 a3 b3|a3
8 8 FARGO 105 1 b3 a2 b3|a2
9 9 FARGO 109 1 b4 a0 b4|a0
10 10 FARGO 110 1 b4 a1 b4|a1
Access to strip
object
The strip_plot()
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. strip$layoutRandom
or
strip$fieldBook
.
strip$fieldBook
is a list containing information about
every plot in the field, with information about the location of the plot
and the treatment in each plot. As seen in the output below, the field
book has columns for ID
, LOCATION
,
PLOT
, REP
, HSTRIP
,
VSTRIP
, and TRT_COMB
.
field_book <- strip$fieldBook
head(strip$fieldBook, 10)
ID LOCATION PLOT REP HSTRIP VSTRIP TRT_COMB
1 1 FARGO 101 1 b1 a0 b1|a0
2 2 FARGO 102 1 b1 a1 b1|a1
3 3 FARGO 103 1 b1 a3 b1|a3
4 4 FARGO 104 1 b1 a2 b1|a2
5 5 FARGO 108 1 b3 a0 b3|a0
6 6 FARGO 107 1 b3 a1 b3|a1
7 7 FARGO 106 1 b3 a3 b3|a3
8 8 FARGO 105 1 b3 a2 b3|a2
9 9 FARGO 109 1 b4 a0 b4|a0
10 10 FARGO 110 1 b4 a1 b4|a1