plot.can_cor {metan} | R Documentation |
Plots an object of class can_cor
Description
Graphs of the Canonical Correlation Analysis
Usage
## S3 method for class 'can_cor'
plot(
x,
type = 1,
plot_theme = theme_metan(),
size.tex.lab = 12,
size.tex.pa = 3.5,
x.lab = NULL,
x.lim = NULL,
x.breaks = waiver(),
y.lab = NULL,
y.lim = NULL,
y.breaks = waiver(),
axis.expand = 1.1,
shape = 21,
col.shape = "orange",
col.alpha = 0.9,
size.shape = 3.5,
size.bor.tick = 0.3,
labels = FALSE,
main = NULL,
...
)
Arguments
x |
The |
type |
The type of the plot. Defaults to |
plot_theme |
The graphical theme of the plot. Default is
|
size.tex.lab |
The size of the text in axis text and labels. |
size.tex.pa |
The size of the text of the plot area. Default is
|
x.lab |
The label of x-axis. Each plot has a default value. New
arguments can be inserted as |
x.lim |
The range of x-axis. Default is |
x.breaks |
The breaks to be plotted in the x-axis. Default is
|
y.lab |
The label of y-axis. Each plot has a default value. New
arguments can be inserted as |
y.lim |
The range of y-axis. Default is |
y.breaks |
The breaks to be plotted in the x-axis. Default is
|
axis.expand |
Multiplication factor to expand the axis limits by to
enable fitting of labels. Default is |
shape |
The shape of points in the plot. Default is |
col.shape |
A vector of length 2 that contains the color of shapes for
genotypes above and below of the mean, respectively. Defaults to
|
col.alpha |
The alpha value for the color. Default is |
size.shape |
The size of the shape in the plot. Default is |
size.bor.tick |
The size of tick of shape. Default is |
labels |
Logical arguments. If |
main |
The title of the plot. Defaults to |
... |
Currently not used. |
Value
An object of class gg, ggplot
.
Author(s)
Tiago Olivoto tiagoolivoto@gmail.com
Examples
library(metan)
cc1 = can_corr(data_ge2,
FG = c(PH, EH, EP),
SG = c(EL, ED, CL, CD, CW, KW, NR))
plot(cc1, 2)
cc2 <-
data_ge2 %>%
mean_by(GEN) %>%
column_to_rownames("GEN") %>%
can_corr(FG = c(PH, EH, EP),
SG = c(EL, ED, CL, CD, CW, KW, NR))
plot(cc2, 2, labels = TRUE)