stulacy

library(stringr)
solve <- function(code) {
    
    # Extract the num
    nums <- as.numeric(strsplit(gsub("[A-Z]", "", code), '')[[1]])
    letters <- unique(strsplit(gsub("[0-9]", "", code), "")[[1]])
    miss_nums <- setdiff(seq(1, 9), nums)
    
    # Generate all permutations of possible solution numbers
    # No permutation function in R so make my own

stulacy

"""
    MAUCpy
    ~~~~~~

    Contains two equations from Hand and Till's 2001 paper on a multi-class
    approach to the AUC. The a_value() function is the probabilistic approximation
    of the AUC found in equation 3, while MAUC() is the pairwise averaging of this
    value for each of the classes. This is equation 7 in their paper.
"""

stulacy

library(reshape2)

formattedtable <- function(x, block, group, value) {
    # Form a dataframe with the mean values and get a logical matrix of the max values
    mean <- setNames(aggregate(x[, value], list(x[, block], x[, group]), mean), c(block, group, "mean"))

    # To get the max values need in wide format
    mean.wide <- dcast(mean, get(block) ~ get(group), value.var="mean")  # get() comes from reshape2, gets string values from variables
    colnames(mean.wide)[1] <- block