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

A function that "digitizes curves" by calculating equidistant two-dimensional or three-dimensional semilandmarks along a curve. These landmarks will be treated as "sliders" in Generalized Procrustes analysis `gpagen`

. This type of semilandmark "slides" along curves lacking known landmarks (see Bookstein 1997 for algorithm details). Each sliding semilandmark ("sliders") will slide between two designated points, along a line tangent to the specified curvature, as specified by `define.sliders`

.

1 | ```
digit.curves(start, curve, nPoints, closed = TRUE)
``` |

`start` |
A numeric vector of x,y,(z) coordinates for the landmark defining the start of the curve (can be simply first point on open outline: curve[1,]) |

`curve` |
A matrix (p x k) of 2D or 3D coordinates for a set of ordered points defining a curve |

`nPoints` |
Numeric how many semilandmarks to place equidistantly along the curve |

`closed` |
Logical Whether the curve is closed (TRUE) or open (FALSE) |

The function is based upon tpsDig2 'resample curve by length' for 2D data by James Rohlf (Rohlf 2015).
The start of the curve is a fixed landmark on the curve that is equivalent (homologous) in each specimen in the sample (and will be treated as a fixed point during Procrustes Superimposition using `gpagen`

). Then nPoints are calculated along the curve at equidistant points from the start to the end.

'curve' is a p-x-k matrix of 2D or 3D coordinates for a set of ordered points defining a curve. This can be the pixels of an outline calculated in ImageJ (save xy coordinates) or any other reasonable way of obtaining ordered coordinates along a curve (including sampling by hand using
`digit.fixed`

or `digitize2d`

- but note that there should be more points defining the curve than nPoints in order to accurately calculate the semilandmarks).

If 'closed = T', the function returns the coordinates of the 'start' landmark plus nPoints. If 'closed = F', the function returns the coordinates of the 'start' landmark, plus nPoints and the end of the curve.

If unsure if the points defining the curve are ordered, then plot and colour them using the rainbow function, e.g. plot(curve, pch=19, cex=0.1, col=rainbow(nrow(outline))), and it should be easy to visualise.

Function returns a matrix of coordinates for nPoints equally spaced semilandmarks sampled along the curve (plus start and end if 'closed = F', or only including start if 'closed = T')

Emma Sherratt

Bookstein, F. J. 1997 Landmark Methods for Forms without Landmarks: Morphometrics of Group Differences in Outline Shape. Medical Image Analysis 1(3):225-243.

Rohlf, F.J., 2015. The tps series of software. Hystrix 26(1):9-12.

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