Rotate Cartesian coordinates obtained from jnd2xyz()
(required) the output from a jnd2xyz() call.
should the vectors for rotation be centered in the achromatic center ("achro") or the data centroid ("mean", the default)?
the cone to be used as a the first reference. May be NULL
(for no first rotation in the 3-dimensional case) or must match name
in the original data that was used for coldist(). Defaults to 'l'.
the cone to be used as a the second reference. May be NULL
(for no first rotation in the 3-dimensional case) or must match name
in the original data that was used for coldist(). Defaults to 'u'.
(only used if data has 3 dimensions).
A vector of length number of cones minus 1 composed of 0's and
1's, with 1's representing the axes (x, y, z) to rotate around. Defaults to
c(1, 1, 0) in 3 dimensions, such that the rotation aligns with the xy plane,
and c(1, 0) in 2 dimentions, such that the rotation is centered on the x
axis. Ignored if ref1 is NULL (in 3-dimensional case only). Ignored for
dichromats.
A vector of length number of cones minus 1 composed of 0's and
1's, with 1's representing the axes (x, y, z) to rotate around. Defaults to
c(0, 0, 1) in 3 dimensions, such that the rotation aligns with the z axis,
and c(0, 1) in 2 dimentions, such that the rotation is centered on the y
axis. Ignored if ref1 is NULL (in 3-dimensional case only). Ignored for
dichromats.
# Load floral reflectance spectra
data(flowers)
# Estimate quantum catches visual phenotype of a Blue Tit
vis.flowers <- vismodel(flowers, visual = "bluetit")
# Estimate noise-weighted colour distances between all flowers
cd.flowers <- coldist(vis.flowers)
#> Quantum catch are relative, distances may not be meaningful
#> Calculating noise-weighted Euclidean distances
# Convert points to Cartesian coordinates in which Euclidean distances are
# noise-weighted, before rotating them about the data centroid
jndrot(jnd2xyz(cd.flowers))
#> x y z
#> Goodenia_heterophylla 0.3043555 -5.516498701 6.8629524
#> Goodenia_geniculata -1.1026561 -2.369014577 -6.5456726
#> Goodenia_gracilis -2.7905115 11.389376711 -22.9236622
#> Xyris_operculata 2.8991598 -1.638522717 -2.8997962
#> Eucalyptus_sp -0.6686084 -3.126709336 3.1550303
#> Faradaya_splendida -1.1554277 0.713583456 -2.8528294
#> Gaultheria_hispida 1.5099700 -4.303035463 -1.1742262
#> Geitonoplesium_cymosum 6.6260719 -8.277622401 8.2932612
#> Euryomyrtus_ramosissima -2.0446299 0.004566434 4.6922247
#> Genista_linifolia -0.9202192 -1.564532987 -2.1501789
#> Genista_monspessulana -0.7558614 -2.941635249 -2.4820412
#> Geranium_sp 8.8177712 5.241977926 10.8297259
#> Glycine_clandestina -0.6533986 -2.560055351 -4.2701064
#> Gompholobium_ecostatum_1 2.3269068 -0.300984437 5.5688334
#> Gompholobium_ecostatum_2 -0.7558888 -1.900221252 -5.3306567
#> Gompholobium_grandiflorum -2.1732134 4.938019815 -6.5433920
#> Gompholobium_huegelii 0.3960794 -1.864201051 6.1230907
#> Gompholobium_virgatum 1.3526063 -1.448665692 5.9025137
#> Gonocarpus_humilis -0.6350125 -3.657225209 -2.6939291
#> Gonocarpus_teucrioides -0.5313327 -2.061150168 2.1280934
#> Hibbertia_obtusifolia -0.7880908 -1.241234118 -2.0026397
#> Zieria_arborescens -2.6488920 9.639320108 8.7021306
#> Goodenia_lanata -2.7785027 8.112480123 -12.6997701
#> Goodenia_ovata -1.1444822 10.925514238 9.6861976
#> Goodenia_rotundifolia 1.5433111 -6.679755139 6.1909786
#> Grevillea_buxifolia 1.7437703 -3.855164992 1.9123426
#> Grevillea_steiglitziana -3.4131666 5.885033918 -1.1327863
#> Grevillea_oleoides -0.7171963 -2.936033254 -4.1570956
#> Gymnostachys_anceps -2.5572567 10.584762035 -9.8694685
#> Hakea_actites -0.1690555 -6.462443652 8.4297774
#> Hardenbergia_violaceae -1.4260671 0.772786755 -3.4332417
#> Hibbertia_acicularis -0.6369595 -3.354876726 1.9458170
#> Hibbertia_bracteata 6.6696068 -3.577994067 1.6605064
#> Hibbertia_empetrifolia -2.1940185 8.619401043 8.8247528
#> Hibbertia_procumbens -0.5525492 -3.263070039 -0.3154626
#> Hibbertia_linearis -0.9766118 -1.926175986 -7.4312733