DOI: 10.5061/dryad.zgmsbccc1
title: Using Delaunay triangulation to sample whole-specimen color from digital images

description: Color variation is one of the most obvious examples of variation in
 nature, but biologically meaningful quantification and interpretation of
 variation in color and complex patterns is challenging. Many current
 methods for assessing variation in color patterns classify color patterns
 using categorical measures, provide aggregate measures that ignore spatial
 pattern, or both, losing potentially important aspects of color pattern.
 Here, we present Colormesh, a novel method for analyzing complex color
 patterns that offers unique capabilities. Our approach is based on
 unsupervised color quantification combined with geometric morphometrics to
 identify regions of putative spatial homology across samples, from
 histology sections to whole organisms. Colormesh quantifies color at
 individual sampling points across the whole sample. We demonstrate the
 utility of Colormesh using digital images of Trinidadian guppies (Poecilia
 reticulata), for which the evolution of color has been frequently studied.
 Guppies have repeatedly evolved in response to ecological differences
 between up- and downstream locations in Trinidadian rivers, resulting in
 extensive parallel evolution of many phenotypes. Previous studies have,
 for example, compared the area and quantity of discrete color (e.g., area
 of orange, number of black spots) between these up- and downstream
 locations neglecting spatial placement of these areas. Using the Colormesh
 pipeline, we show that patterns of whole-animal color variation do not
 match expectations suggested by previous work. Colormesh can be deployed
 to address a much wider range of questions about color pattern variation
 than previous approaches. Colormesh is thus especially suited for analyses
 that seek to identify the biologically important aspects of color pattern
 when there are multiple competing hypotheses, or even no a priori
 hypotheses at all.
description: This is the dataset used for the guppy example described in the
 manuscript titled: "Using Delaunay triangulation to sample
 whole-specimen color from digital images." This dataset contains the
 RGB values measured from sampling locations determined in an unsupervised
 manner by the Colormesh pipeline. A total of 485 images were processed
 (landmarked and unwarped to a concensus shape) using the TPS Series
 software by James Rohlf. The Colormesh pipeline made 4 passes (i.e.,
 performed 4 rounds of triangulation) and calculated 2,462 sampling
 locations within the consensus shape using Delaunay triangulation. The RGB
 values, on a scale of 0 to 1, were measured at each sampling point for
 each image. For access to the images (*.TIF) that were
 sampled, please email Jennifer Valvo (jv13f@my.fsu.edu). 
description: The RGB_colormesh_data.csv  The color channels
 are identified by either r (red), g(green), or b(blue) in the header and
 the point sampled is given by the numerical value (e.g., the red color
 channel value for point #200 is under the column header r.200, the green
 and blue color channel values are under the headers g.200 and b.200,
 respectively). Information associated with the specimen identification is
 given in the first five columns. 
 X_Y_coords_4DT.csv This file contains the x,y
 coordinates of the 2462 points sampled for color. The first 62 coordinates
 (point_ID 1-62) are the perimeter of the fish. These points are used in
 the first round of Delaunay triangulation. The centroid of the resulting
 trinagles serve as the vertices for the second round of triangulation. To
 generate the data set used in the manuscript, 4 passes of trinagulation
 were performed to produce the 2462 sampling locations. Only the pixel at
 this location was sampled for RGB values for this data set.