View source: R/summary.colspace.R
summary.colspace | R Documentation |
Returns the attributes of colspace
objects.
## S3 method for class 'colspace'
summary(object, by = NULL, ...)
object |
(required) a |
by |
when the input is in |
... |
class consistency (ignored). |
returns all attributes of the data as mapped to the selected colourspace, including
options specified when calculating the visual model. Also return the default
data.frame
summary, except when the object is the result of tcspace()
,
in which case the following variables are output instead:
centroid.u, .s, .m, .l
the centroids of usml
coordinates of points.
c.vol
the total volume occupied by the points, computed with a convex
hull.
rel.c.vol
volume occupied by the points (convex hull volume) relative to
the tetrahedron volume.
colspan.m
the mean hue span.
colspan.v
the variance in hue span.
huedisp.m
the mean hue disparity.
huedisp.v
the variance in hue disparity.
mean.ra
mean saturation.
max.ra
maximum saturation achieved by the group of points.
a.vol
colour volume computed with \alpha
-shapes.
Rafael Maia rm72@zips.uakron.edu
Stoddard, M. C., & Prum, R. O. (2008). Evolution of avian plumage color in a tetrahedral color space: A phylogenetic analysis of new world buntings. The American Naturalist, 171(6), 755-776.
Endler, J. A., & Mielke, P. (2005). Comparing entire colour patterns as birds see them. Biological Journal Of The Linnean Society, 86(4), 405-431.
Gruson H. (2020). Estimation of colour volumes as concave hypervolumes using
\alpha
-shapes. Methods in Ecology and Evolution, 11(8), 955-963
\Sexpr[results=rd]{tools:::Rd_expr_doi("10.1111/2041-210X.13398")}
# Colour hexagon
data(flowers)
vis.flowers <- vismodel(flowers,
visual = "apis", qcatch = "Ei", relative = FALSE,
vonkries = TRUE, bkg = "green"
)
flowers.hex <- hexagon(vis.flowers)
summary(flowers.hex)
# Tetrahedral model
data(sicalis)
vis.sicalis <- vismodel(sicalis, visual = "avg.uv")
csp.sicalis <- colspace(vis.sicalis)
summary(csp.sicalis, by = rep(c("C", "T", "B"), 7))
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