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Generate a Ind x Time + Var data.frame concatenating all variables from input variable

Source: R/df_search.R
get_eigen_spline_matrix.Rd

Generate Ind x Time data.frame for each variable using get_ind_time_matrix and then concatenate all variables rowise. Resulting data.frame contrain Time as columns and Individuals and Variables as rows. Pairs of Individual and Timepoint without a measurement are left as NA. If ncore!=0 the function is parallelised, however the parallelisation overhead cost is high if not required.

Usage

get_eigen_spline_matrix(inputData, ind, time, ncores = 0)

Arguments

inputData

data.frame of measurements with observations as rows and variables as columns

ind

Vector of subject identifier (individual) corresponding to each measurement

time

Vector of time corresponding to each measurement

ncores

(int) Number of cores to use for parallelisation. Default 0 for no parallelisation.

Value

data.frame of measurements for each IND x TIME + VAR. Rows are unique Individual IDs per variable, and columns unique measurement Time. Pairs of (IND,TIME+VAR) without a measurement are left as NA.

Examples

if (FALSE) {
## 6 measurements, 3 subjects, 3 unique time-points, 2 variables
inputData <- matrix(c(1,2,3,4,5,6, 7,8,9,10,11,12), ncol=2)
ind  <- c('ind_1','ind_1','ind_1','ind_2','ind_2','ind_3')
time <- c(0,5,10,0,10,5)
get_eigen_spline_matrix(inputData, ind, time, ncores=0)
#     0   5  10
# 1   1   2   3
# 2   4  NA   5
# 3  NA   6  NA
# 4   7   8   9
# 5  10  NA  11
# 6  NA  12  NA
}