library(neurohcp)
library(plyr)
library(dplyr)
library(readr)
# group = "HCP_900"
# group = "HCP_1200"
# group = "HCP_Retest"
# group = "HCP"
for (group in c("HCP", "HCP_900", "HCP_1200")) {
ids = hcp_ids(group = group)
all_csvs = paste0(group, "/", ids, "/unprocessed/3T/", ids, "_3T.csv")
outdir = file.path("data", paste0(group, "_csvs"))
dir.create(outdir, showWarnings = FALSE)
destfile = file.path(outdir,
basename(all_csvs))
mapply(function(x, y){
if (!file.exists(y)) {
download_hcp_file(path_to_file = x, destfile = y, error = FALSE)
print(y)
}
}, all_csvs, destfile)
destfile = destfile[file.exists(destfile)]
system(paste0("grep -l xml data/", group, "_csvs/*.csv | xargs rm"))
destfile = destfile[file.exists(destfile)]
sizes = sapply(destfile, file.size)
if (any(sizes == 0)){
bad = destfile[ sizes == 0]
file.remove(bad)
}
destfile = destfile[file.exists(destfile)]
types = paste(rep("c", 17), collapse = "")
res = llply(destfile, read_csv,
col_names = FALSE,
col_types = types,
.progress = "text")
ids = gsub("(.*)_3T.*", "\\1", basename(destfile))
res = mapply(function(df, id) {
df$id = id
return(df)
}, res, ids, SIMPLIFY = FALSE)
outname = paste0(tolower(group), "_scanning_info")
df = bind_rows(res)
cn = c("Session_Day",
"Acquisition_Time",
"Session",
"Scan_Number",
"Scan_Type",
"Scan_Description",
"Shim_Group",
"BiasField_group",
"SE_FieldMap_group",
"GE_FieldMap_group",
"PE_Direction",
"Readout_Direction",
"E_Prime_Script",
"Scan_Order",
"Scan_Complete",
"Percent_Complete",
"Percent_Pair_Complete",
"id")
cn = tolower(cn)
colnames(df) = cn
assign(outname, df)
outfile = file.path("data", paste0(outname, ".rda"))
save(list = outname,
file = outfile,
compress = "xz")
}
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.