| plot.can_cor | R Documentation | 
Graphs of the Canonical Correlation Analysis
## 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,
  ...
)
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.  | 
An object of class gg, ggplot.
Tiago Olivoto tiagoolivoto@gmail.com
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)
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