IdentiFlyR

IdentiFlyR can be used to store identification data in an XML file. Later, the data can be read from the XML file and used to identify an unknown sample. An alternative to this package could be to provide all the raw data and use it for identification. For large datasets this may be less convenient, slower and undesirable. Identification is based on linear discriminant analysis (LDA), also known as canonical variate analysis (CVA). The focus of this package is on using LDA to identify an unknown sample, not on exploratory analysis.
Currently IdentiFLyR only supports geometric morphometric data in two dimensions. ## Installation

You can install the development version of IdentiFlyR from GitHub with:

# install.packages("devtools")
devtools::install_github("DrawWing/IdentiFlyR")

Examples

Read identification data from XML file and plot means and confidence ellipses in the first two linear discriminant functions. Identification data consists of: reference, means, covariances and coefficients.

library(IdentiFlyR)
xmlPath = system.file("extdata",
                      "apis-mellifera-queens-workers-drones.dw.xml",
                      package="IdentiFlyR")
idData = xml2gmLdaData(xmlPath)
names(idData)
#> [1] "reference"    "means"        "covariances"  "coefficients"
# transfer means to LDA space
meansLda = idData$means %*% t(idData$coefficients)
covEllipses(meansLda, idData$covariances)

Read raw coordinated of 19 landmarks.

wings <- read.csv("https://zenodo.org/record/8071014/files/IN-raw-coordinates.csv")
wings <- data.frame(wings, row.names = 1)  # move column 1 to row names

Classify the mean of all data. The mean of all rows has been classified as “workers”.

id = gmLdaData2id(idData, wings, average = TRUE)
id$plot

id$id
#>    group         P
#> 1 worker 0.4776823

Classify rows. All 350 rows were classified as “workers”.

id = gmLdaData2id(idData, wings, average = FALSE)
id$plot

head(id$id, 2)
#>                          group         P
#> IN-0001-000243-L.dw.png worker 0.5746041
#> IN-0001-000243-R.dw.png worker 0.3949792
table(id$id$group)
#> 
#> worker 
#>    350

Classify the first row. It was classified as “worker”.

id = gmLdaData2id(idData, wings[1,])
id$id
#>    group         P
#> 1 worker 0.5746041

Create identification data and store it in an XML file.

data(lineages)
grVec = lineages$lineage
coordinates = lineages[,-1] # remove the first column
gmLdaData2xml(coordinates, grVec, "apis-mellifera-lineage.dw.xml")
#> [1] "apis-mellifera-lineage.dw.xml"
id = xml2id("apis-mellifera-lineage.dw.xml", coordinates[1,], average = FALSE)
id$plot

Citation

Please cite this publication if you find this code useful:

Kaur, H., Ganie, S. A., & Tofilski, A. (2024). Morphometric identification of an unknown honey bee colony: an example from north India. Journal of Apicultural Science, 68(2), 155-166. https://doi.org/10.2478/JAS-2024-0013