| summary_index {pliman} | R Documentation |
Summary an object index
Description
If more than one index is available, the function performs a Principal
Component Analysis and produces a plot showing the contribution of the
indexes to the PC1 (see pca()). If an index is declared in
index and a cut point in cut_point, the number and proportion of objects
with mean value of index bellow and above cut_point are returned.
Additionaly, the number and proportion of pixels bellow and above the
cutpoint is shown for each object (id).
Usage
summary_index(
object,
index = NULL,
cut_point = NULL,
select_higher = FALSE,
plot = TRUE,
type = "var",
...
)
Arguments
object |
An object computed with |
index |
The index desired, e.g., |
cut_point |
The cut point. |
select_higher |
If |
plot |
Shows the contribution plot when more than one index is
available? Defaults to |
type |
The type of plot to produce. Defaults to |
... |
Further arguments passed on to |
Value
A list with the following elements:
-
idsThe identification of selected objects. -
between_idA data frame with the following columns-
nThe number of objects. -
nselThe number of selected objects. -
propThe proportion of objects selected. -
mean_index_sel, andmean_index_nselThe mean value ofindexfor the selected and non-selected objects, respectively.
-
-
within_idA data frame with the following columns-
idThe object identification -
n_lessThe number of pixels with values lesser than or equal tocut_point. -
n_greaterThe number of pixels with values greater thancut_point. -
less_ratioThe proportion of pixels with values lesser than or equal tocut_point. -
greater_ratioThe proportion of pixels with values greater thancut_point.
-
-
pca_resAn object computed withpca()
Author(s)
Tiago Olivoto tiagoolivoto@gmail.com
Examples
library(pliman)
soy <- image_pliman("soy_green.jpg")
anal <- analyze_objects(soy, object_index = "G", pixel_level_index = TRUE)
plot_measures(anal, measure = "G")
summary_index(anal, index = "G", cut_point = 0.5)