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16 changes: 13 additions & 3 deletions R/csv.R
Original file line number Diff line number Diff line change
Expand Up @@ -697,7 +697,13 @@ read_csv_metadata <- function(csv_file) {
for (line in metadata[[1]]) {
if (!startsWith(line, "#") && is.null(csv_file_info[["variables"]])) {
# if no # at the start of line, the line is the CSV header
all_names <- strsplit(line, ",")[[1]]
header_dt <- data.table::fread(
text = line,
header = FALSE,
check.names = FALSE,
data.table = FALSE
)
all_names <- as.character(header_dt[1, ])
if (all(csv_file_info$algorithm != "fixed_param")) {
csv_file_info[["sampler_diagnostics"]] <- all_names[endsWith(all_names, "__")]
csv_file_info[["sampler_diagnostics"]] <- csv_file_info[["sampler_diagnostics"]][!(csv_file_info[["sampler_diagnostics"]] %in% c("lp__", "log_p__", "log_g__", "log_q__"))]
Expand Down Expand Up @@ -915,8 +921,10 @@ check_csv_metadata_matches <- function(csv_metadata) {
NULL
}

# convert names like beta.1.1 to beta[1,1]
# convert names like beta.1.1 or beta(1,1) to beta[1,1]
repair_variable_names <- function(names) {
names <- sub("\\(", "[", names)
names <- gsub("\\)", "", names)
names <- sub("\\.", "[", names)
names <- gsub("\\.", ",", names)
names[grep("\\[", names)] <-
Expand Down Expand Up @@ -983,7 +991,9 @@ variable_dims <- function(variable_names = NULL) {
uniq_variable_names <- unique(gsub("\\[.*\\]", "", variable_names))
var_names <- gsub("\\]", "", variable_names)
for (var in uniq_variable_names) {
pattern <- paste0("^", var, "\\[")
# escape regex symbols
esc_var <- gsub("([][{}()+*?.^$|\\\\])", "\\\\\\1", var)
pattern <- paste0("^", esc_var, "\\[")
var_indices <- var_names[grep(pattern, var_names)]
var_indices <- gsub(pattern, "", var_indices)
if (length(var_indices)) {
Expand Down
66 changes: 66 additions & 0 deletions tests/testthat/test-csv.R
Original file line number Diff line number Diff line change
Expand Up @@ -95,6 +95,19 @@ test_that("read_cmdstan_csv() fails with the no params listed", {
"Supplied CSV file does not contain any variable names or data!")
})

test_that("variable_dims works for standard Stan names", {
vars <- c("beta[1]", "beta[2]", "beta[3]", "sigma")
dims <- variable_dims(vars)
expect_equal(dims$beta, 3)
expect_equal(dims$sigma, 1)
})

test_that("variable_dims handles names with regex metacharacters", {
vars <- c('SIGMA(1,1)[1,2]', 'SIGMA(1,1)[2,2]')
dims <- variable_dims(vars)
expect_equal(dims[["SIGMA(1,1)"]], c(2, 2))
})

test_that("read_cmdstan_csv() matches utils::read.csv", {
csv_files <- c(test_path("resources", "csv", "model1-1-warmup.csv"),
test_path("resources", "csv", "model1-2-warmup.csv"))
Expand Down Expand Up @@ -896,3 +909,56 @@ test_that("read_cmdstan_csv() works with tilde expansion", {
tildified_path <- file.path("~", fs::path_rel(full_path, "~"))
expect_no_error(read_cmdstan_csv(tildified_path))
})

test_that("as_cmdstan_fit handles parameter names with parentheses and indices", {
skip_on_cran()

csv_file <- withr::local_tempfile(fileext = ".csv")
lines <- c(
"# model = norm_model",
"# method = sample (Default)",
"# id = 1",
"# thin = 1",
"# save_warmup = 0",
'lp__,accept_stat__,stepsize__,treedepth__,n_leapfrog__,divergent__,energy__,"Sigma(1,1)","Sigma(1,2)","Sigma(2,1)","Sigma(2,2)"',
"-65.951579,0.92571393,0.77752825,3,7,0,67.391073,0.2808549,-0.95718644,0.080662461,0.58814086",
"-66.417297,0.89632515,0.77752825,2,3,0,68.026905,0.3014893,-0.97834703,0.069719538,0.89573157"
)
writeLines(lines, csv_file)

fit <- as_cmdstan_fit(csv_file, check_diagnostics = FALSE)

vars <- posterior::variables(fit$draws())
expect_true(all(
c("Sigma[1,1]", "Sigma[1,2]", "Sigma[2,1]", "Sigma[2,2]") %in% vars
))

dims <- fit$metadata()$stan_variable_sizes
expect_equal(dims[["Sigma"]], c(2, 2))
})

test_that("as_cmdstan_fit handles variable names with parentheses", {
skip_on_cran()
csv_file <- withr::local_tempfile(fileext = ".csv")
writeLines(c(
"# model = norm_model",
"# method = sample (Default)",
"# id = 1",
"# thin = 1",
"# save_warmup = 0",
"THETA4,SIGMA(1,1)",
"2.00000E+00,2.00000E+00",
"2.00000E+00,2.00000E+00"
), con = csv_file)

expect_no_error({
fit <- as_cmdstan_fit(csv_file, check_diagnostics = FALSE, format = "draws_matrix")
})

draws <- fit$draws()
vars <- posterior::variables(draws)

expect_equal(posterior::ndraws(draws), 2L)
expect_true(any(grepl("THETA4", vars)))
expect_true(any(grepl("SIGMA", vars)))
})