Description Usage Arguments Details Value Author(s) See Also Examples

Function plots a set of Procrustes shape variables in tangent space along their principal component axes

1 2 |

`A` |
A 3D array (p x k x n) containing Procrustes shape variables for a set of specimens |

`axis1` |
A value indicating which PC axis should be displayed as the X-axis (default = PC1) |

`axis2` |
A value indicating which PC axis should be displayed as the Y-axis (default = PC2) |

`warpgrids` |
A logical value indicating whether deformation grids for shapes along X-axis should be displayed |

`mesh` |
A mesh3d object to be warped to represent shape deformation along X-axis (when warpgrids=TRUE)
as described in |

`label` |
An optional vector indicating labels for each specimen are to be displayed (or if TRUE, numerical addresses are given) |

`groups` |
An optional factor vector specifying group identity for each specimen (see example) |

`legend` |
A logical value for whether to add a legend to the plot (only when groups are assigned). |

`...` |
Arguments passed on to |

The function performs a principal components analysis of shape variation and plots two dimensions of tangent space for a set of Procrustes shape variables (default is PC1 vs. PC2). The percent variation along each PC-axis is returned. Additionally (and optionally, warpgrids=T), deformation grids can be requested, which display the shape of specimens at the ends of the range of variability along PC1. If groups are provided, specimens from each group are plotted using distinct colors based on the order in which the groups are found in the dataset, and using R's standard color palette: black, red, green, blue, cyan, magenta, yellow, and gray. NOTE: to change the colors of the groups, simply substitute a vector of the desired colors for each specimen (see example below).

The function `gm.prcomp`

can also be used to generate principal components plots of
tangent space, and will yield plots identical to those of the current function. Notice that in the next release of geomorph, **plotTangentSpace will be deprecated** and replaced by gm.prcomp.

NOTE: previous versions of plotTangentSpace had option 'verbose' to return the PC scores and PC shapes. From version 3.0.2 this is automatic when assigned to an object.

If user assigns function to object, returned is a list of the following components:

`pc.summary` |
A table summarizing the percent variation explained by each pc axis, equivalent to summary of |

`pc.scores` |
The set of principal component scores for all specimens. |

`pc.shapes` |
A list with the shape coordinates of the extreme ends of all PC axes, e.g. $PC1min |

`sdev` |
The standard deviations of the principal components (i.e., the square roots of the eigenvalues of the
covariance/correlation matrix, as per |

`rotation` |
The matrix of variable loadings, as per |

Dean Adams & Emma Sherratt

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 | ```
data(plethodon)
Y.gpa<-gpagen(plethodon$land) #GPA-alignment
gp <- interaction(plethodon$species, plethodon$site) # group must be a factor
plotTangentSpace(Y.gpa$coords, groups = gp)
## To save and use output
PCA <- plotTangentSpace(Y.gpa$coords, groups = gp, legend=TRUE)
summary(PCA)
PCA$pc.shapes
PCA$rotation
##To change colors of groups
col.gp <- rainbow(length(levels(gp)))
names(col.gp) <- levels(gp)
col.gp <- col.gp[match(gp, names(col.gp))] # col.gp must NOT be a factor
plotTangentSpace(Y.gpa$coords, groups = col.gp)
## To plot residual shapes from an allometry regression (note: must add mean back in!)
plotTangentSpace(arrayspecs(resid(lm(two.d.array(Y.gpa$coords)~log(Y.gpa$Csize)))+
predict(lm(two.d.array(Y.gpa$coords)~1)),12,2))
``` |

geomorphR/geomorph documentation built on June 5, 2019, 11:30 a.m.

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