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