Function projects data onto vector from anchor one (score of 0) to anchor two (score of 1). For all three arguments, input must be two-dimensional data frame or matrix with rows = specimens, and columns = PC scores.
calc_vs(data, anchor1, anchor2)
| data | PC scores of face(s) for which vector scores are to be calculated |
|---|---|
| anchor1 | PC scores of face(s) which will constitute lower anchor point |
| anchor2 | PC scores of face(s) which will constitute upper anchor point |
Returns tibble with columns "id" and "VS". If data contained rownames, these will be saved as ids.
# CALCULATE FEMALE-MALE VECTOR SCORES data("LondonSet_scores") data("LondonSet_info") fem <- LondonSet_scores %>% dplyr::filter(row.names(LondonSet_scores) %in% LondonSet_info$face_id[which(LondonSet_info$face_sex == "female")]) mal <- LondonSet_scores %>% dplyr::filter(row.names(LondonSet_scores) %in% LondonSet_info$face_id[which(LondonSet_info$face_sex == "male")]) calc_vs(LondonSet_scores, fem, mal)#> # A tibble: 102 x 2 #> id VS #> <chr> <dbl> #> 1 001 -1.06 #> 2 002 0.00299 #> 3 003 -0.250 #> 4 004 0.855 #> 5 005 0.548 #> 6 006 0.582 #> 7 007 -1.16 #> 8 008 1.50 #> 9 009 -1.16 #> 10 010 0.391 #> # … with 92 more rows