View source: R/plot_functions.R
plot_var_part_pq | R Documentation |
Graphical representation of the partition of variation obtain with var_par_pq()
.
plot_var_part_pq(
res_varpart,
cutoff = 0,
digits = 1,
digits_quantile = 2,
fill_bg = c("seagreen3", "mediumpurple", "blue", "orange"),
show_quantiles = FALSE,
filter_quantile_zero = TRUE,
show_dbrda_signif = FALSE,
show_dbrda_signif_pval = 0.05,
alpha = 63,
id.size = 1.2,
min_prop_pval_signif_dbrda = 0.95
)
res_varpart |
(required) the result of the functions |
cutoff |
The values below cutoff will not be displayed. |
digits |
The number of significant digits. |
digits_quantile |
The number of significant digits for quantile. |
fill_bg |
Fill colours of ellipses. |
show_quantiles |
Do quantiles are printed ? |
filter_quantile_zero |
Do we filter out value with quantile encompassing the zero value? |
show_dbrda_signif |
Do dbrda significance for each component is printed using *? |
show_dbrda_signif_pval |
(float, |
alpha |
(int, |
id.size |
A numerical value giving the character expansion factor for the names of circles or ellipses. |
min_prop_pval_signif_dbrda |
(float, |
This function is mainly a wrapper of the work of others.
Please make a reference to vegan::varpart()
if you
use this function.
A plot
Adrien Taudière
var_par_rarperm_pq()
, var_par_pq()
if (requireNamespace("vegan")) {
data_fungi_woNA <- subset_samples(data_fungi, !is.na(Time) & !is.na(Height))
res_var_9 <- var_par_rarperm_pq(
data_fungi_woNA,
list_component = list(
"Time" = c("Time"),
"Size" = c("Height", "Diameter")
),
nperm = 9,
dbrda_computation = TRUE
)
res_var_2 <- var_par_rarperm_pq(
data_fungi_woNA,
list_component = list(
"Time" = c("Time"),
"Size" = c("Height", "Diameter")
),
nperm = 2,
dbrda_computation = TRUE
)
res_var0 <- var_par_pq(data_fungi_woNA,
list_component = list(
"Time" = c("Time"),
"Size" = c("Height", "Diameter")
),
dbrda_computation = TRUE
)
plot_var_part_pq(res_var0, digits_quantile = 2, show_dbrda_signif = TRUE)
plot_var_part_pq(res_var_9,
digits_quantile = 2, show_quantiles = TRUE,
show_dbrda_signif = TRUE
)
plot_var_part_pq(
res_var_2,
digits = 5,
digits_quantile = 2,
cutoff = 0,
show_quantiles = TRUE
)
}
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