| import os |
| import pandas as pd |
| import re |
|
|
| data_dir = os.path.join(os.getcwd(), "data_units") |
|
|
| species_list = ["rat_SD", "mouse_BALB_c", "mouse_C57BL_6", "human"] |
|
|
| for species in species_list: |
| print(f"Downloading {species} files") |
| species_url_file = os.path.join(data_dir, species + ".txt") |
| with open(species_url_file, "r") as f: |
| i = 0 |
| os.makedirs(species, exist_ok=True) |
| for csv_file in f.readlines(): |
| print(csv_file) |
| filename = os.path.basename(csv_file) |
| run_id = str(re.search(r"^(.*)_[Pp]aired", filename)[1]) |
| url = csv_file |
| run_data = pd.read_csv( |
| url, |
| header=1, |
| compression="gzip", |
| on_bad_lines="warn", |
| low_memory=False, |
| ) |
| run_data = run_data[ |
| [ |
| "sequence_alignment_aa_heavy", |
| "cdr1_aa_heavy", |
| "cdr2_aa_heavy", |
| "cdr3_aa_heavy", |
| "sequence_alignment_aa_light", |
| "cdr1_aa_light", |
| "cdr2_aa_light", |
| "cdr3_aa_light", |
| ] |
| ] |
| run_data = run_data.dropna() |
| run_data.insert(0, "data_unit", run_id) |
| print(run_data.shape) |
| output_path = os.path.join(species, "train_" + str(i) + ".parquet") |
| run_data.to_parquet(output_path, index=False) |
| i += 1 |
|
|
|
|
