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Basics verbs are implemented; try the following: ## An Opn object with: ## - $coo: 210 open outlines (99 /- 4 coordinates) ## - $fac: 4 classifiers: ## 'var' (factor 4): Aglan, Cypre, Mou Bo1, Pic Ma. 19 more.## An Opn object with: ## - $coo: 5 open outlines (99 /- 4 coordinates) ## - $fac: 4 classifiers: ## 'var' (factor 1): Aglan. ## 'Ind' (factor 30): O1, O10, O11, O12, O13, O14, O15, O16, O17, O18, O19 ... ## 'ind' (factor 30): O1, O10, O11, O12, O13, O14, O15, O16, O17, O18, O19 ... ## 'ind' (factor 30): O1, O10, O11, O12, O13, O14, O15, O16, O17, O18, O19 ... ## 'fake' (factor 2): a, b.## An Opn object with: ## - $coo: 90 open outlines (100 /- 2 coordinates) ## - $fac: 3 classifiers: ## 'var' (factor 3): Aglan, Cypre, Pic Ma.

19 more.## An Opn object with: ## - $coo: 210 open outlines (99 /- 4 coordinates) ## - $fac: 4 classifiers: ## 'var' (factor 4): Aglan, Cypre, Mou Bo1, Pic Ma. 19 more.## An Opn object with: ## - $coo: 210 open outlines (99 /- 4 coordinates) ## - $fac: 5 classifiers: ## 'var' (factor 4): Aglan, Cypre, Mou Bo1, Pic Ma.

Morphometrics is the ugly job of turning beautiful shapes into quantitative variables. They are all single shapes defined by a matrix of object: visualize it, apply morphometric operations, handle the data it contains, but in the end, a __ morphometric method__ will turn coordinates into coefficients.

Such morphometric operation on coordinates produce a collection of coefficients: a are generic in that they do not depend of the nature of the shape.

Momocs adapts dplyr verbs to its objects, and add new ones. ## 'ind' (factor 30): O1, O10, O11, O12, O13, O14, O15, O16, O17, O18, O19 ... ## 'ind' (factor 30): O1, O10, O11, O12, O13, O14, O15, O16, O17, O18, O19 ...

There are, however, some very important tips to follow when embarking on a speed dating adventure.For instance, calculating elliptical Fourier transforms on a configuration of landmarks would make no sense.Momocs implement this desirable behavior and defines classes and subclasses, as S3 objects.Here we will illustrate outline analysis with some elliptical Fourier transforms (but the less used - and tested - radii variation Fourier transforms, its variant used by Renaud et al., and tangent angle Fourier transforms are also implemented with Amazing but we will do much better afterwards.The question of normalization in elliptical Fourier transforms is central.

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