system("cd data; unzip Processed_K50_dG_datasets.zip")


ThermoMPNN_splits <- arrow::read_parquet("intermediate/ThermoMPNN_splits.parquet")


### Dataset1 ###

# Dataset1 consists of all cDNA proteolysis measurements of stability
dataset1 <- readr::read_csv(
    file = "data/Processed_K50_dG_datasets/Tsuboyama2023_Dataset1_20230416.csv",
    show_col_types = FALSE)

# note that some of the log10_K50_trypsin_ML and log10_K50_chmotrypsin_ML values are "-" and ">2.5".
# to maintain these non-standard values, we keep them as strings for the full dataset

dataset1 |>
    arrow::write_parquet(
        "intermediate/dataset1.parquet")



### Dataset2 and Dataset3 ###

# Dataset2 (for dG ML) consists of cDNA proteolysis measurements of stability that are of class G0 + G1
# Datase3 (for ddG ML) consists of cDNA proteolysis measurements of stability that are of class G0
#    G0: Good (wild-type ΔG values below 4.75 kcal mol^−1), 325,132 ΔG measurements at 17,093 sites in 365 domains
#    G1: Good but WT outside dynamic range

dataset2 <- readr::read_csv(
    file = "data/Processed_K50_dG_datasets/Tsuboyama2023_Dataset2_Dataset3_20230416.csv",
    show_col_types = FALSE) |>
    dplyr::mutate(
        log10_K50_trypsin_ML = as.numeric(log10_K50_trypsin_ML),
        log10_K50_chymotrypsin_ML = as.numeric(log10_K50_chymotrypsin_ML),
        dG_ML = as.numeric(dG_ML),
        ddG_ML = as.numeric(ddG_ML))
# 776,298 rows

dataset2 |>
    arrow::write_parquet(
        "intermediate/dataset2.parquet")
    

dataset3 <- dataset2 |>
    dplyr::filter(!is.na(ddG_ML))

dataset3 |>
    arrow::write_parquet(
        "intermediate/dataset3.parquet")



dataset3_single <- dataset3 |>
    dplyr::filter(!(mut_type |> stringr::str_detect("(ins|del|[:])")))
        

ThermoMPNN_splits |> dplyr::group_by(split_name) |>
    dplyr::do({
        split <- .
        split_name <- split$split_name[1]
        mutant_set <- dataset3_single |>
            dplyr::filter(mut_type != "wt") |>
            dplyr::semi_join(split, by = c("WT_name" = "id"))
        cat("Writing out split ", split_name, ", nrow: ", nrow(mutant_set), "\n", sep = "")
        
        arrow::write_parquet(
            x = mutant_set,
            sink = paste0("intermediate/dataset3_single_", split_name, ".parquet"))
        data.frame()
    })


####

system("cd data && unzip AlphaFold_model_PDBs.zip")


assemble_models <- function(
    data_path,
    dataset_tag,
    pattern,
    output_path) {

    cat(
        "data path: ", data_path, "\n",
        "dataset_tag: ", dataset_tag, "\n",
        "pattern: ", pattern, "\n",
        "output path: ", output_path, "\n",
        sep = "")

    file_index <- 1
    models <- list.files(
        path = data_path,
        full.names = TRUE,
        pattern = pattern,
        recursive = TRUE) |>
        purrr::map_dfr(.f = function(path) {
            file_handle <- path |>
                file(open = "rb") |>
                gzcon()

            if( file_index %% 10 == 0) {
                cat("Reading  '", path, "' ", file_index, "\n", sep = "")
            }
            file_index <<- file_index + 1

            lines <- file_handle |> readLines()
            file_handle |> close()

            data.frame(
                dataset_tag = dataset_tag,
                id = path |> basename() |> stringr::str_replace(".pdb", ""),
                pdb = lines |> paste0(collapse = "\n"))
        })
    models |> arrow::write_parquet(output_path)
}


assemble_models(
    data_path = "data/AlphaFold_model_PDBs",
    dataset_tag = "all",
    pattern = "*.pdb",
    output_path = "intermediate/all_pdbs.parquet")

# 
# assemble_models(
#     data_path = "data/AlphaFold_model_PDBs",
#     dataset_tag = "EA",
#     pattern = "EA[:]run.*pdb",
#     output_path = "intermediate/EA_pdbs.parquet")
# 
# 
# assemble_models(
#     data_path = "data/AlphaFold_model_PDBs",
#     dataset_tag = "EEHEE",
#     pattern = "EEHEE.*pdb",
#     output_path = "intermediate/EEHEE_pdbs.parquet")
# 
# 
# assemble_models(
#     data_path = "data/AlphaFold_model_PDBs",
#     dataset_tag = "EHEE",
#     pattern = "EHEE.*pdb",
#     output_path = "intermediate/EHEE_pdbs.parquet")
# 
# 
# assemble_models(
#     data_path = "data/AlphaFold_model_PDBs",
#     dataset_tag = "GG",
#     pattern = "GG[:]run.*pdb",
#     output_path = "intermediate/GG_pdbs.parquet")
# 
# 
# assemble_models(
#     data_path = "data/AlphaFold_model_PDBs",
#     dataset_tag = "HEEH_KT",
#     pattern = "HEEH_KT_rd.*pdb",
#     output_path = "intermediate/HEEH_KT_pdbs.parquet")
# 
# assemble_models(
#     data_path = "data/AlphaFold_model_PDBs",
#     dataset_tag = "HEEH",
#     pattern = "HEEH_rd.*pdb",
#     output_path = "intermediate/HEEH_pdbs.parquet")