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Momocs aims to provide a complete and convenient toolkit for morphometrics. It is intended for scientists interested in describing quantitatively the shape, and its variations, of the objects they study. Nevertheless, morphometric analyses still have to be carried out using various software packages, for which source code is mostly unavailable or copyrighted. Moreover, most of existing software packages cannot be extended and their bugs are hard to detect and thus correct.

This situation is detrimental to morphometrics; time is wasted, analyses are restricted to available methods, and last but not least, are poorly reproducible. This impedes collaborative effort both in software development and in morphometric studies. By gathering the common morphometric approaches in an open-source environment and welcoming contributions, Momocs is an work-in-progress attempt to solve this twofold problem and to push morphometrics one step further.

It hinges on the core functions published in the must-have Morphometrics with R by Julien Claude , but has been further extended to allow other shape description systems. So far, configurations of landmarks, outlines and open outline analyses, along with some facilities for traditional morphometrics have been implemented. Momocs also has the facility for a wide range of multivariate analyses and production of the companion graphics.

You will need to install the devtools package to get it from my GitHub repository:. Morphometrics is the ugly job of turning beautiful shapes into quantitative variables. A shape is defined as a collection of x; y coordinates. No 3D yet but different families can be handled: They are all single shapes defined by a matrix of x; y coordinates; here are the first points of the moon:. A few dozens of operations on single shapes are implemented such as: But working on single shapes is quite boring.

Shapes can be organized into a collection of coordinates: One can do several things with a Coo object: Morphometrics on coordinates produce a collection collections of coefficients: Thus Coo objects are collections of coordinates that become Coe objects when an appropriate morphometric method is applied on them. The different families of shape sometimes implies or requires particular operations on them.

Some operations on shapes are generic in that they do not depend of the family. For instance, centering a configuration of landmarks or an outline, or calculating their centroid size is, mathematically, the same generic operation. But some operations on shapes are specific to a peculiar family. For instance, calculating elliptical Fourier transforms on a configuration of landmarks makes no sense.

Momocs implement this desirable behavior and defines classes and subclasses , as S3 objects. Finally, generic and specific operations can be applied to the Coe objects, chiefly multivariate methods, capitalicized: These datasets are all Coo objects try class bot , ie collection of shapes. One can do many things on a Coo object, as above, eg printing a summary of it just by typing its name , plotting a family picture with panel or panel2.

Note the 2 that refers to a ggplot2 variant of a given plot. A nice introduction can be found there. It makes things clearer, it: Notice that before the stack operation, we still have a Coo object. And by the way, pipes can also be defined on Momocs objects. A word about data import: Here we do not bother with import since we will use the bot tles outlines dataset bundled with Momocs. Here we will illustrate outline analysis with some elliptical Fourier transforms but the less used - and tested - radii variation Fourier transforms and tangent angle Fourier transforms are also implemented with rfourier and tfourier.

The idea behind elliptical Fourier transforms is to fit the x and y coordinates separately, that is the blue and red curves below:. More details can be found in their respective help files. Now, we can calculate a PCA on the Coe object and plot it, along with morphospaces, calculated on the fly. The question of normalization in elliptical Fourier transforms is central. Normalization can either be done beforehand, with geometric operations, or afterhand, directly on the matrix of Fourier coefficients and consuming the first harmonic.

More can be found in? Here is an example of such bias from the molars dataset generously shared by Cornu and Detroit. And methods that removes the bilateral a symmetry are implemented: Note that opoly and npoly can only be used on simple curves, curves that have at most one y for any x coordinates, at least under a given orientation. Here, we will work on the fertile valves of olive stones, a very partial dataset provided by my colleagues Terral, Ivorra, and others.

They have two orthogonal views a lateral and a dorsal view. See the paper cited in? Now, we gonna calculate opoly on it and plot the result of the PCA. Notice how consistent is the grammar and the objects obtained:. But this is perfectly wrong! We merged the two views are if they were different individuals. Momocs can first chop or filter the whole dataset to separate the two views, do morphometrics on them, and combine them afterwards.

Momocs speed dating Vincent Bonhomme K-means clustering mshapes: Thin Plate Splines ggplot2 Color palettes Frequently asked questions. Preliminaries Abstract Momocs aims to provide a complete and convenient toolkit for morphometrics. See Momocs features. If you use it, cite it: This citation refers to an obsolete version of Momocs, only handling outline analyses. The next one is in preparation. Feel free to contribute to Momocs through GitHub: Feel free to drop me a line, should you need a hand or would like to collaborate with me: You will need to install the devtools package to get it from my GitHub repository: Design Keywords used all accross Momocs are introduced here in bold.

They are all single shapes defined by a matrix of x; y coordinates; here are the first points of the moon: Morphometrics Outline analysis A word about data import: Ptolemy bot[ 1 ]. Procrustes-aligned and slided molars mol. Open outlines Open outlines are curves. Methods actually implemented are:

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Momocs aims to provide a complete and convenient toolkit for morphometrics. It is intended for scientists interested in describing quantitatively the shape, and its variations, of the objects they study.

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