Momocs

News

• Momocs is now retiring and, one day, will no longer be supported in favour of Momocs2 and the entire MomX ecosystem. (as of Jan 26)
• I’m available for consulting, training and collaboration, worldwide.
• Momocs is back on CRAN and no longer relies on the retired rgeos dependency
• The tutorial/introduction is back! Download it there

Installation

The last released version can be installed from CRAN with:

install.packages("Momocs")

But I recommend using (and only support) the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("MomX/Momocs")

Example

This is a basic example of a complete analysis doing: inspection, normalization of raw outlines, elliptical Fourier transforms, dimmensionality reduction and classification, using a single line.

library(Momocs)

devtools::load_all()
#> ℹ Loading Momocs
#> Registered S3 method overwritten by 'vegan':
#>   method     from      
#>   rev.hclust dendextend

hearts %T>%                    # A toy dataset
  stack() %>%                  # Take a family picture of raw outlines
  fgProcrustes() %>%           # Full generalized Procrustes alignment
  coo_slide(ldk = 2) %T>%      # Redefine a robust 1st point between the cheeks
  stack() %>%                  # Another picture of aligned outlines
  efourier(6, norm=FALSE) %>%  # Elliptical Fourier Transforms
  PCA() %T>%                   # Principal Component Analysis
  plot_PCA(~aut) %>%           # A PC1:2 plot
  LDA(~aut) %>%                # Linear Discriminant Analysis
  plot_CV()                    # And the confusion matrix after leave one out cross validation