plot_CV | R Documentation |
Either with frequencies (or percentages) plus marginal sums,
and values as heatmaps. Used in Momocs for plotting cross-validation tables
but may be used for any table (likely with freq=FALSE
).
plot_CV(
x,
freq = FALSE,
rm0 = FALSE,
pc = FALSE,
fill = TRUE,
labels = TRUE,
axis.size = 10,
axis.x.angle = 45,
cell.size = 2.5,
signif = 2,
...
)
## Default S3 method:
plot_CV(
x,
freq = FALSE,
rm0 = FALSE,
pc = FALSE,
fill = TRUE,
labels = TRUE,
axis.size = 10,
axis.x.angle = 45,
cell.size = 2.5,
signif = 2,
...
)
## S3 method for class 'LDA'
plot_CV(
x,
freq = TRUE,
rm0 = TRUE,
pc = TRUE,
fill = TRUE,
labels = TRUE,
axis.size = 10,
axis.x.angle = 45,
cell.size = 2.5,
signif = 2,
...
)
x |
a (cross-validation table) or an LDA object |
freq |
logical whether to display frequencies (within an actual class) or counts |
rm0 |
logical whether to remove zeros |
pc |
logical whether to multiply proportion by 100, ie display percentages |
fill |
logical whether to fill cell according to count/freq |
labels |
logical whether to add text labels on cells |
axis.size |
numeric to adjust axis labels |
axis.x.angle |
numeric to rotate x-axis labels |
cell.size |
numeric to adjust text labels on cells |
signif |
numeric to round frequencies using signif |
... |
useless here |
a ggplot object
LDA, plot.LDA, and (pretty much the same) plot_table.
h <- hearts %>%
fgProcrustes(0.01) %>% coo_slide(ldk=2) %T>% stack %>%
efourier(6, norm=FALSE) %>% LDA(~aut)
h %>% plot_CV()
h %>% plot_CV(freq=FALSE, rm0=FALSE, fill=FALSE)
# you can customize the returned gg with some ggplot2 functions
h %>% plot_CV(labels=FALSE, fill=TRUE, axis.size=5) + ggplot2::ggtitle("A confusion matrix")
# or build your own using the prepared data_frame:
df <- h %>% plot_CV() %$% data
df
# you can even use it as a cross-table plotter
bot$fac %>% table %>% plot_CV()
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