Fits a smoothing spline through a set of antigenic coordinates, and uses this to predict antigenic coordinates for all potential infection time points. This version is more flexible than generate_antigenic_map, and allows the user to specify "clusters" to assume that strains circulating in a given period are all identical, rather than on a continuous path through space as a function of time.
generate_antigenic_map_flexible( antigenic_distances, buckets = 1, clusters = NULL, use_clusters = FALSE, spar = 0.3, year_min = 1968, year_max = 2016 )
| antigenic_distances | a data frame of antigenic coordinates, with columns labelled X, Y and Strain for x coord, y coord and Strain label respectively. "Strain" should be a single number giving the year of circulation of that strain. See |
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| buckets | = 1 the number of epochs per year. 1 means that each year has 1 strain; 12 means that each year has 12 strains (monthly resolution) |
| clusters | = NULL a data frame of cluster labels, indicating which cluster each circulation year belongs to. Note that each row (year) gets repeated by the number of buckets. Column names "year" and "cluster_used" |
| use_clusters | = FALSE if TRUE, uses the clusters data frame above, otherwise just returns as normal |
| spar | = 0.3 to be passed to smooth.spline |
| year_min | = 1968 first year in the antigenic map (usually 1968) |
| year_max | = 2016 last year in the antigenic map |
a fitted antigenic map
Other antigenic_maps:
generate_antigenic_map()
if (FALSE) { antigenic_coords_path <- system.file("extdata", "fonville_map_approx.csv", package = "serosolver") antigenic_coords <- read.csv(antigenic_coords_path, stringsAsFactors=FALSE) antigenic_coords$Strain <- c(68,72,75,77,79,87,89,92,95,97,102,104,105,106) + 1900 antigenic_map <- generate_antigenic_map_flexible(antigenic_coords, buckets=1, year_min=1968, year_max=2015,spar=0.3) times <- 1968:2010 n_times <- length(times) clusters <- rep(1:5, each=10) clusters <- clusters[1:n_times] clusters <- data.frame(year=times, cluster_used=clusters) antigenic_map <- generate_antigenic_map_flexible(antigenic_coords, buckets=1, clusters=clusters,use_clusters=TRUE, year_min=1968, year_max=2010,spar=0.5) }