## ----setup, include = FALSE---------------------------------------------------
library(rirods)
library(purrr)
library(kableExtra)
library(httptest2)
start_vignette("metadata")

knitr::opts_chunk$set(
  collapse = TRUE,
  comment = "#>",
  eval=is_irods_demo_running()
)

knitr::opts_knit$set(
  root.dir = tempdir()
)

options(knitr.kable.NA = "")

## ----setup2, include=FALSE----------------------------------------------------
# # set user config directory to temporary location
# withr::local_envvar(
#   R_USER_CONFIG_DIR = tempdir()
# )
# eval(substitute(create_irods(x, overwrite = TRUE), list(x = rirods:::.irods_host)))
# iauth("rods", "rods")
# 
# filter_ils <- function(pattern, ils_output = ils()) {
#   stopifnot(inherits(ils_output, "irods_df"))
#   ils_df <- as.data.frame(ils_output)
#   if (length(pattern) == 1) {
#     filtered <- ils_df[grepl(pattern, ils_df$logical_path),]
#   } else {
#     filtered <- ils_df[basename(ils_df$logical_path) %in% pattern,]
#   }
#   rirods:::new_irods_df(filtered)
# }
# 
# if (length(ils())> 0) {
#   for (file in ils()$logical_path) {
#     irm(file, recursive = TRUE)
#   }
# }
# 
# patterns <- c("X_ID", "X_NAME", "X_CREATE_TIME", "X_MODIFY_TIME", "X_SIZE",
#               paste0("META_X_ATTR_", c("NAME", "VALUE", "UNITS")),
#               paste0("META_X_", c("ID", "CREATE_TIME", "MODIFY_TIME")))
# possible_columns <- data.frame(
#   attribute = c("id", "name", "creation time", "modification time", "size",
#                 "attribute name", "value", "units", "id", "creation time", "modification time"),
#   collection = gsub("X", "COLL", patterns),
#   data_object = gsub("X", "DATA", patterns)
# )
# possible_columns[5,"collection"] <- NA

## -----------------------------------------------------------------------------
# ils()

## -----------------------------------------------------------------------------
# set.seed(1234)
# fake_data <- data.frame(x = rnorm(20, mean = 1))
# fake_data$y <- fake_data$x * 2 + 3 - rnorm(20, sd = 0.6)
# m <- lm(y ~ x, data = fake_data)
# m

## ----include=FALSE------------------------------------------------------------
# change_state()

## -----------------------------------------------------------------------------
# data_path <- "data.csv"
# lm_path <- "analysis/linear_model.rds"
# write.csv(fake_data, data_path) # write locally
# iput(data_path, data_path) # transfer to iRODS
# imkdir("analysis") # create directory
# # save directly as rds
# isaveRDS(m, lm_path)

## -----------------------------------------------------------------------------
# ils(metadata=TRUE)
# ils("analysis", metadata=TRUE)

## ----include=FALSE------------------------------------------------------------
# change_state()

## -----------------------------------------------------------------------------
# imeta(data_path, operations = list(
#   list(operation = "add", attribute = "nrow", value = as.character(nrow(fake_data)))
#   ))
# filter_ils(data_path, ils(metadata=TRUE))

## ----include=FALSE------------------------------------------------------------
# change_state()

## -----------------------------------------------------------------------------
# imeta(data_path, operations = list(
#   list(operation = "add", attribute = "size", value = as.character(nrow(fake_data)), units = "rows"),
#   list(operation = "add", attribute = "size", value = as.character(length(fake_data)), units = "columns"),
#   list(operation = "remove", attribute = "nrow", value = as.character(nrow(fake_data)))
#   ))
# filter_ils(data_path, ils(metadata=TRUE))

## -----------------------------------------------------------------------------
# lm_meta <- data.frame(
#   attribute = c("size", "size", "data_file", "model_type"),
#   value = c(as.character(nrow(fake_data)), 1, data_path, "linear regression"),
#   units = c("observations", "predictors", "", "")
# )
# lm_meta

## ----include=FALSE------------------------------------------------------------
# change_state()

## -----------------------------------------------------------------------------
# lm_meta$operation <- "add"
# imeta(lm_path, operations = lm_meta)
# filter_ils("linear_model", ils("analysis", metadata=TRUE))

## ----include=FALSE------------------------------------------------------------
# change_state()

## ----message=FALSE, results="hide"--------------------------------------------
# file_md <- data.frame(
#   path = c(data_path, lm_path),
#   type = c("dataframe", "lm"),
#   responsible = c("abby", "bob")
# )
# pwalk(file_md, function(path, type, responsible) {
#   imeta(path, operations = list(
#     list(
#       operation = "add",
#       attribute = "type",
#       value = type
#     ),
#     list(
#       operation = "add",
#       attribute = "responsible",
#       value = responsible
#     )
#   ))
# })

## -----------------------------------------------------------------------------
# ils(metadata=TRUE)
# ils("analysis", metadata=TRUE)

## ----include=FALSE------------------------------------------------------------
# change_state()

## -----------------------------------------------------------------------------
# imeta(
#   "analysis",
#   operations = list(
#     list(operation = "add", attribute = "dataset", value = data_path)
#   ))
# ils(metadata=TRUE)

## -----------------------------------------------------------------------------
# iquery("SELECT COLL_NAME, DATA_NAME")

## -----------------------------------------------------------------------------
# iquery("SELECT COLL_NAME, DATA_NAME, META_COLL_ATTR_VALUE WHERE META_COLL_ATTR_NAME LIKE 'data%'")

## -----------------------------------------------------------------------------
# iquery("SELECT DATA_NAME, DATA_SIZE, META_DATA_ATTR_VALUE, META_DATA_ATTR_UNITS WHERE META_DATA_ATTR_NAME = 'size'")

## -----------------------------------------------------------------------------
# iq <- iquery("SELECT COLL_NAME, DATA_NAME, DATA_CREATE_TIME, DATA_SIZE WHERE COLL_NAME LIKE '%analysis' AND DATA_SIZE < '8000'")
# iq
# class(iq$DATA_CREATE_TIME)
# class(iq$DATA_SIZE)

## ----echo = FALSE-------------------------------------------------------------
# kbl(possible_columns,
#     col.names = c("Attribute", "Collection", "Data object")) |>
#   pack_rows(index = c("Entity level" = 5, "Metadata level" = 6)
#   )

## -----------------------------------------------------------------------------
# iq$PATH <- file.path(iq$COLL_NAME, iq$DATA_NAME)
# iq

## ----cleanup, include=FALSE---------------------------------------------------
# file.remove(data_path)
# for (file in ils()$logical_path) {
#   irm(file, recursive = TRUE)
# }
# httptest2::end_vignette()
# unlink(rirods:::path_to_irods_conf())