View source: R/utils_measures.R
summary_index | R Documentation |
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).
summary_index(
object,
index = NULL,
cut_point = NULL,
select_higher = FALSE,
plot = TRUE,
type = "var",
...
)
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 |
A list with the following elements:
ids
The identification of selected objects.
between_id
A data frame with the following columns
n
The number of objects.
nsel
The number of selected objects.
prop
The proportion of objects selected.
mean_index_sel
, and mean_index_nsel
The mean value of index
for the
selected and non-selected objects, respectively.
within_id
A data frame with the following columns
id
The object identification
n_less
The number of pixels with values lesser than or equal to
cut_point
.
n_greater
The number of pixels with values greater than cut_point
.
less_ratio
The proportion of pixels with values lesser than or equal to
cut_point
.
greater_ratio
The proportion of pixels with values greater than
cut_point
.
pca_res
An object computed with pca()
Tiago Olivoto tiagoolivoto@gmail.com
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)
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