#' @importFrom stats complete.cases
# error checks for function parameters
check_diagram <- (d,ret){
# error checks for a diagram d stored as a data frame, and conversion
(((d) && (((d) == 1 && ((d) %in% "diagram") && ((d$diagram,"diagram")) || (d$diagram,"data.frame")) || (((d) == 4 && ((d) %in% ("diagram","birthLocation","deathLocation","cycleLocation")) && (d$diagram,"diagram"))))) || ((d,"matrix") && (d,"array") & ((d) %in% ("dimension","birth","death"))))
{
# d is the output from a TDA/TDAstats calculation
d <- (d)
}
{
(!(d,"data.frame"))
{
("Diagrams must either be the output of a TDA/TDAstats computation or a data frame.")
}
}
# if(nrow(d) == 0)
# {
# stop("Every diagram must be non-empty.")
# }
((d) != 3)
{
("Every diagram must have three columns.")
}
(!(d,1L]) | !(d,2L]) | !(d,3L]))
{
("Diagrams must have numeric columns.")
}
(((d,1L] != (d,1L]))) > 0)
{
("Homology dimensions must be whole numbers.")
}
(((d,1L] < 0)) > 0)
{
("Homology dimensions must be >= 0.")
}
(((d,2L] < 0)) > 0 | ((d,3L] < 0)) > 0)
{
("Birth and death radii must be >= 0.")
}
(((::(d) == T)) != (d))
{
("Diagrams can't have missing values.")
}
(((d,3L] <= d,2L])) > 0)
{
("Death values must always be larger than birth values.")
}
# if(length(which(is.infinite(d[,3L]))) > 0)
# {
# stop("Death values must be finite.")
# }
(ret == T)
{
(d)
}
}
all_diagrams <- (diagram_groups,inference){
# function to make sure all diagram groups are lists or vectors of diagrams,
# to convert the diagrams to data frames and to error check each diagram.
# diagram_groups is a vector or list of vectors or lists of diagrams
# inference is a string, either 'difference' for the permutation test or
# 'independence' for the independence test
(inference == "difference")
{
# compute cumulative sums of groups lengths in order to correctly compute diagram indices
csum_group_sizes <- (((diagram_groups,FUN = )))
csum_group_sizes <- (0,csum_group_sizes)
}
# loop through all diagram groups
(g 1:(diagram_groups))
{
# loop through each diagram in each group
( 1:(diagram_groups[g]]))
{
# check to make sure each diagram is actually the output of some TDA/TDAstats computation or a data frame
check_diagram(diagram_groups[g]][diag]],ret = F) # will stop here if there is an error
diagram_groups[g]][diag]] <- check_diagram(diagram_groups[g]][diag]],ret = T)
# if of the right form, format into a data frame and store diagram index for difference inference
(inference == "difference")
{
diagram_groups[g]][diag]] <- ( = diagram_groups[g]][diag]],
ind = csum_group_sizes[g] + )
}
}
}
# return diagram groups with reformatted diagrams
(diagram_groups)
}
check_param <- (param_name,param,){
extra_params <- ()
# check if a single parameter satisfies certain constraints
(!(param) & (!(param) | (param) == 1))
{
((param))
{
((param_name," must not be NULL."))
}
((param))
{
((param_name," must not be NA/NaN."))
}
}
(param_name == "diagrams" | param_name == "other_diagrams" | param_name == "diagram_groups" | param_name == "new_diagrams")
{
(!(param) | (param) < extra_params$min_length)
{
((param_name," must be a list of persistence diagrams of length at least ",extra_params$min_length,"."))
}
}
("multiple" %in% (extra_params))
{
(extra_params$multiple == F & (param) > 1)
{
((param_name," must be a single value."))
}
}
(param_name == "distance")
{
((param) | (param) > 1 | (param %in% ("wasserstein","fisher")) == F)
{
("distance must either be \'wasserstein\' or \'fisher\'.")
}
}
("numeric" %in% (extra_params))
{
(extra_params$ == T)
{
((param) == F)
{
((param_name," must be numeric."))
}
}
{
((param) == F)
{
((param_name," must be T or F."))
}
}
}
("numeric" %in% (extra_params) & "whole_numbers" %in% (extra_params))
{
(extra_params$ == T & extra_params$whole_numbers == T & (((param) != param)) > 0)
{
((param_name," must be whole numbers."))
}
}
("finite" %in% (extra_params))
{
(extra_params$ == T & ((!(param))) > 0)
{
((param_name," must be finite."))
}
}
("non_negative" %in% (extra_params))
{
(extra_params$non_negative == T & ((param < 0)) > 0)
{
((param_name," must be non-negative"))
}
}
("positive" %in% (extra_params))
{
(extra_params$positive == T & ((param <= 0)) > 0)
{
((param_name," must be positive."))
}
}
("at_least_one" %in% (extra_params))
{
(extra_params$at_least_one == T & ((param < 1)) > 0)
{
((param_name," must be at least one."))
}
}
}
#' @importFrom stats complete.cases
check_matrix <- (M,, = "kernel",symmetric = T){
( == "kernel")
{
((M,"kernelMatrix") == F)
{
((," must be of type kernelMatrix."))
}
}
{
((M,"matrix") == F)
{
((," must be of type matrix."))
}
}
((M)*(M) == 0)
{
((," must have at least one row and column."))
}
(((::(M) == F)) > 0)
{
((," must not have missing values."))
}
(symmetric == T)
{
( == "kernel")
{
((((M) != (1,(M)))) > 0)
{
((," must have 1's on its diagonal."))
}
}
{
((((M) != (0,(M)))) > 0)
{
((," must have 0's on its diagonal."))
}
}
((M) != (M))
{
((," must have the same number of rows and columns."))
}
( == "kernel")
{
(M) = "matrix"
}
((M) == F)
{
((," must be symmetric."))
}
( == "kernel")
{
(M) = "kernelMatrix"
}
}
}
# function for cv in diagram_ksvm
# copied from kernlab package v0.9-29
.classAgreement <- function (tab) {
n <- (tab)
if (!((tab))) {
lev <- ((tab), (tab))
p0 <- ((tab[lev, lev])) / n
} {
m <- ((tab))
p0 <- ((tab[1:m, 1:m])) / n
}
(p0)
}
