Returns the attributes of colspace objects.
# S3 method for class 'colspace'
summary(object, by = NULL, ...)(required) a colspace object.
when the input is in tcs colourspace, by is either
a single value specifying the range of colour points for which
summary tetrahedral-colourspace variables should be calculated (for example, by = 3
indicates summary will be calculated for groups of 3 consecutive colour points (rows)
in the quantum catch colour data frame) or a vector containing identifications for
the rows in the quantum catch colour data frame (in which case summaries will be
calculated for each group of points sharing the same identification). If by
is left blank, the summary statistics are calculated across all colour points in the
data.
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.
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 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)
#> Colorspace & visual model options:
#> * Colorspace: hexagon
#> * Quantal catch: Ei
#> * Visual system, chromatic: apis
#> * Visual system, achromatic: none
#> * Illuminant: ideal, scale = 1 (von Kries colour correction applied)
#> * Background: green
#> * Relative: FALSE
#> * Max possible chromatic volume: NA
#>
#> s m l x
#> Min. :0.01889 Min. :0.1623 Min. :0.1863 Min. :-0.27348
#> 1st Qu.:0.33717 1st Qu.:0.7202 1st Qu.:0.6943 1st Qu.: 0.09593
#> Median :0.47192 Median :0.7827 Median :0.8103 Median : 0.27697
#> Mean :0.46048 Mean :0.7190 Mean :0.7559 Mean : 0.25584
#> 3rd Qu.:0.57925 3rd Qu.:0.8456 3rd Qu.:0.8484 3rd Qu.: 0.40041
#> Max. :0.90735 Max. :0.9112 Max. :0.9001 Max. : 0.66006
#> y h.theta r.vec sec.fine
#> Min. :-0.23770 Min. : 1.103 Min. :0.09195 Min. : 0.0
#> 1st Qu.: 0.06693 1st Qu.: 52.549 1st Qu.:0.23098 1st Qu.: 50.0
#> Median : 0.15522 Median : 61.741 Median :0.32881 Median : 60.0
#> Mean : 0.11077 Mean : 77.206 Mean :0.34600 Mean : 72.5
#> 3rd Qu.: 0.20693 3rd Qu.: 77.511 3rd Qu.:0.45400 3rd Qu.: 72.5
#> Max. : 0.30778 Max. :271.076 Max. :0.70155 Max. :270.0
#> sec.coarse
#> Length:36
#> Class :character
#> Mode :character
#>
#>
#>
# 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))
#> Colorspace & visual model options:
#> * Colorspace: tcs
#> * Quantal catch: Qi
#> * Visual system, chromatic: avg.uv
#> * Visual system, achromatic: none
#> * Illuminant: ideal, scale = 1 (von Kries colour correction not applied)
#> * Background: ideal
#> * Relative: TRUE
#> * Max possible chromatic volume: 0.215735
#>
#> 'avalue' automatically set to 2.6255e-01
#> 'avalue' automatically set to 2.4445e-02
#> 'avalue' automatically set to 1.6251e-01
#> centroid.u centroid.s centroid.m centroid.l c.vol rel.c.vol
#> B 0.14091298 0.04946432 0.3838526 0.4257701 6.281511e-06 2.901306e-05
#> C 0.06947461 0.03144895 0.4054651 0.4936114 4.739152e-06 2.188920e-05
#> T 0.15368451 0.06413428 0.3766734 0.4055078 5.183721e-06 2.394258e-05
#> colspan.m colspan.v huedisp.m huedisp.v mean.ra max.ra
#> B 0.05758429 0.0013841927 0.06717740 0.0011466898 0.8021427 0.9039261
#> C 0.03193253 0.0003263454 0.06164553 0.0013887690 0.8742042 0.9061528
#> T 0.06171418 0.0012215063 0.05595025 0.0005378623 0.7434629 0.8816377
#> a.vol
#> B 4.586381e-06
#> C 1.849436e-06
#> T 2.388383e-06