Calculate procrustes distance between corresponding landmarks of each specimen's original and mirrored endocasts

Once specimens are procrustes aligned and semi-landmarks are slid you can calculate the procrustes distance between landmarks for each specimen's original and mirrored versions.

morton1103ProcDist <- rep(NA, 969)
 for (i in 1:969){morton1103ProcDist[[i]] <- sqrt(sum((morton1103alignedproc[,,2][i,]-morton1103alignedproc[,,1][i,])^2))}
morton1188ProcDist <- rep(NA, 969)
 for (i in 1:969){morton1188ProcDist[[i]] <- sqrt(sum((morton1188alignedproc[,,2][i,]-morton1188alignedproc[,,1][i,])^2))}
morton1192ProcDist <- rep(NA, 969)
for (i in 1:969){morton1192ProcDist[[i]] <- sqrt(sum((morton1192alignedproc[,,2][i,]-morton1192alignedproc[,,1][i,])^2))}
morton1306ProcDist <- rep(NA, 969)
for (i in 1:969){morton1306ProcDist[[i]] <- sqrt(sum((morton1306alignedproc[,,2][i,]-morton1306alignedproc[,,1][i,])^2))}
morton1319ProcDist <- rep(NA, 969)
for (i in 1:969){morton1319ProcDist[[i]] <- sqrt(sum((morton1319alignedproc[,,2][i,]-morton1319alignedproc[,,1][i,])^2))}
 morton1329ProcDist <- rep(NA, 969)
 for (i in 1:969){morton1329ProcDist[[i]] <- sqrt(sum((morton1329alignedproc[,,2][i,]-morton1329alignedproc[,,1][i,])^2))}
morton1486ProcDist <- rep(NA, 969)
for (i in 1:969){morton1486ProcDist[[i]] <- sqrt(sum((morton1486alignedproc[,,2][i,]-morton1486alignedproc[,,1][i,])^2))}
 morton1973ProcDist <- rep(NA, 969)
for (i in 1:969){morton1973ProcDist[[i]] <- sqrt(sum((morton1973alignedproc[,,2][i,]-morton1973alignedproc[,,1][i,])^2))}
 morton25ProcDist <- rep(NA, 969)
 for (i in 1:969){morton25ProcDist[[i]] <- sqrt(sum((morton25alignedproc[,,2][i,]-morton25alignedproc[,,1][i,])^2))}
 morton413ProcDist <- rep(NA, 969)
 for (i in 1:969){morton413ProcDist[[i]] <- sqrt(sum((morton413alignedproc[,,2][i,]-morton413alignedproc[,,1][i,])^2))}
 morton422ProcDist <- rep(NA, 969)
 for (i in 1:969){morton422ProcDist[[i]] <- sqrt(sum((morton422alignedproc[,,2][i,]-morton422alignedproc[,,1][i,])^2))}
 morton432ProcDist <- rep(NA, 969)
 for (i in 1:969){morton432ProcDist[[i]] <- sqrt(sum((morton432alignedproc[,,2][i,]-morton432alignedproc[,,1][i,])^2))}
 morton434ProcDist <- rep(NA, 969)
 for (i in 1:969){morton434ProcDist[[i]] <- sqrt(sum((morton434alignedproc[,,2][i,]-morton434alignedproc[,,1][i,])^2))}
 morton451ProcDist <- rep(NA, 969)
 for (i in 1:969){morton451ProcDist[[i]] <- sqrt(sum((morton451alignedproc[,,2][i,]-morton451alignedproc[,,1][i,])^2))}
 morton51ProcDist <- rep(NA, 969)
 for (i in 1:969){morton51ProcDist[[i]] <- sqrt(sum((morton51alignedproc[,,2][i,]-morton51alignedproc[,,1][i,])^2))}
 morton547ProcDist <- rep(NA, 969)
 for (i in 1:969){morton547ProcDist[[i]] <- sqrt(sum((morton547alignedproc[,,2][i,]-morton547alignedproc[,,1][i,])^2))}
 morton631ProcDist <- rep(NA, 969)
 for (i in 1:969){morton631ProcDist[[i]] <- sqrt(sum((morton631alignedproc[,,2][i,]-morton631alignedproc[,,1][i,])^2))}
 morton645ProcDist <- rep(NA, 969)
 for (i in 1:969){morton645ProcDist[[i]] <- sqrt(sum((morton645alignedproc[,,2][i,]-morton645alignedproc[,,1][i,])^2))}
 morton646ProcDist <- rep(NA, 969)
 for (i in 1:969){morton646ProcDist[[i]] <- sqrt(sum((morton646alignedproc[,,2][i,]-morton646alignedproc[,,1][i,])^2))}
 morton762ProcDist <- rep(NA, 969)
 for (i in 1:969){morton762ProcDist[[i]] <- sqrt(sum((morton762alignedproc[,,2][i,]-morton762alignedproc[,,1][i,])^2))}
 morton772ProcDist <- rep(NA, 969)
 for (i in 1:969){morton772ProcDist[[i]] <- sqrt(sum((morton772alignedproc[,,2][i,]-morton772alignedproc[,,1][i,])^2))}
 morton778ProcDist <- rep(NA, 969)
 for (i in 1:969){morton778ProcDist[[i]] <- sqrt(sum((morton778alignedproc[,,2][i,]-morton778alignedproc[,,1][i,])^2))}
 morton787ProcDist <- rep(NA, 969)
 for (i in 1:969){morton787ProcDist[[i]] <- sqrt(sum((morton787alignedproc[,,2][i,]-morton787alignedproc[,,1][i,])^2))}
 morton808ProcDist <- rep(NA, 969)
 for (i in 1:969){morton808ProcDist[[i]] <- sqrt(sum((morton808alignedproc[,,2][i,]-morton808alignedproc[,,1][i,])^2))}
 morton901ProcDist <- rep(NA, 969)
 for (i in 1:969){morton901ProcDist[[i]] <- sqrt(sum((morton901alignedproc[,,2][i,]-morton901alignedproc[,,1][i,])^2))}
 morton902ProcDist <- rep(NA, 969)
 for (i in 1:969){morton902ProcDist[[i]] <- sqrt(sum((morton902alignedproc[,,2][i,]-morton902alignedproc[,,1][i,])^2))}
 morton913ProcDist <- rep(NA, 969)
 for (i in 1:969){morton913ProcDist[[i]] <- sqrt(sum((morton913alignedproc[,,2][i,]-morton913alignedproc[,,1][i,])^2))}
 morton915ProcDist <- rep(NA, 969)
 for (i in 1:969){morton915ProcDist[[i]] <- sqrt(sum((morton915alignedproc[,,2][i,]-morton915alignedproc[,,1][i,])^2))}

ProcDistLandmarks_all_matrix <- matrix(c(morton1103ProcDist,morton1188ProcDist, morton1192ProcDist, morton1306ProcDist, morton1319ProcDist, morton1329ProcDist, morton1486ProcDist, morton1973ProcDist, morton25ProcDist, morton413ProcDist, morton422ProcDist, morton432ProcDist, morton434ProcDist, morton451ProcDist, morton51ProcDist, morton547ProcDist, morton631ProcDist, morton645ProcDist, morton646ProcDist, morton762ProcDist, morton772ProcDist, morton778ProcDist, morton787ProcDist, morton808ProcDist, morton901ProcDist, morton902ProcDist, morton913ProcDist, morton915ProcDist),nrow=length(morton1103ProcDist))

ProcDistLandmarks_all_mean <- apply(ProcDistLandmarks_all_matrix, 1, mean)

ProcDistLandmarks_males <- matrix(c(morton1188ProcDist, morton1306ProcDist, morton1319ProcDist, morton1486ProcDist, morton1973ProcDist, morton413ProcDist, morton432ProcDist, morton434ProcDist, morton645ProcDist, morton762ProcDist, morton772ProcDist, morton808ProcDist, morton901ProcDist, morton915ProcDist),nrow=length(morton1103ProcDist))

ProcDistLandmarks_females <- matrix(c(morton1103ProcDist,morton1192ProcDist,    morton1329ProcDist, morton25ProcDist, morton422ProcDist,   morton451ProcDist, morton51ProcDist, morton547ProcDist, morton631ProcDist,  morton646ProcDist, morton778ProcDist, morton787ProcDist, morton902ProcDist, morton913ProcDist),nrow=length(morton1103ProcDist))

ProcDistLandmarks_males_mean <- apply(ProcDistLandmarks_males, 1, mean)

ProcDistLandmarks_females_mean <- apply(ProcDistLandmarks_females, 1, mean)