Jiarui Li
f729f05190
- Added `model.py` containing the DelphiBERT architecture, including TabularEncoder and AutoDiscretization classes for handling tabular features. - Introduced `prepare_data.R` for merging disease and other data from UK Biobank, ensuring proper column selection and data integrity. - Created `prepare_data.py` to process UK Biobank data, including mapping field IDs, handling date variables, and preparing tabular features and event data for model training.
26 lines
1.0 KiB
R
26 lines
1.0 KiB
R
library(data.table)
|
|
setDTthreads(40)
|
|
library(readr)
|
|
field_id <- read.csv("field_id.txt", header = FALSE)
|
|
uid <- field_id$V1
|
|
big_path <- "/mnt/storage/shared_data/UKBB/20230518-from-zhourong/HHdata_221103_0512.csv"
|
|
header_dt <- fread(big_path, nrows = 0) # Read 0 rows => only column names
|
|
all_names <- names(header_dt)
|
|
keep_names <- intersect(all_names,uid)
|
|
ukb_disease <- fread(big_path,
|
|
select = keep_names,
|
|
showProgress = TRUE)
|
|
|
|
field_id <- read.csv("field_id.txt", header = FALSE)
|
|
uid <- field_id$V1
|
|
big_path <- "/mnt/storage/shared_data/UKBB/20230518-from-zhourong/HH_data_220812_0512.csv"
|
|
header_dt <- fread(big_path, nrows = 0) # Read 0 rows => only column names
|
|
all_names <- names(header_dt)
|
|
keep_names <- intersect(all_names,uid)
|
|
ukb_others <- fread(big_path,
|
|
select = keep_names,
|
|
showProgress = TRUE)
|
|
|
|
# merge disease and other data by "eid"
|
|
ukb_data <- merge(ukb_disease, ukb_others, by = "eid", all = TRUE)
|
|
fwrite(ukb_data, "ukb_data.csv") |