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view gaiac_outlier_removal/gaiac_outlier_removal.py @ 3:2ae74925a4fe draft default tip
planemo upload for repository https://github.com/jaidevjoshi83/gaiac commit e9587f93346c7b55e1be00bad5844bf2db3ed03d-dirty
author | jay |
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date | Thu, 10 Jul 2025 19:40:59 +0000 |
parents | 0a8233db930e |
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import numpy as np import pandas as pd # python 'outlier_removal.py' -I '' -M 'replace' -QU '75' -QL '25' -MU '1.5' def AddMedian(input_data, column_list, out_file, method='drop', Q_UP=75, Q_DOWN=25, Multiplier=1.5, sep='\t'): df = pd.read_csv(input_data, sep=sep) cl = df.columns.tolist() clms = [cl[int(x)-1] for x in column_list.split(',')] Q_UP = float(Q_UP) Q_DOWN = float(Q_DOWN) Multiplier = float(Multiplier) if method == 'replace': for col in clms: q75, q25 = np.percentile(df[col], [Q_UP, Q_DOWN]) intr_qr = q75 - q25 upper_bound = q75 + (Multiplier * intr_qr) lower_bound = q25 - (Multiplier * intr_qr) median_val = np.median(df[col]) df.loc[df[col] < lower_bound, col] = median_val df.loc[df[col] > upper_bound, col] = median_val elif method == "drop": # compute bounds for each column for col in clms: Q1 = np.percentile(df[col], 25, interpolation='midpoint') Q3 = np.percentile(df[col], 75, interpolation='midpoint') IQR = Q3 - Q1 upper_bound = Q3 + (Multiplier * IQR) lower_bound = Q1 - (Multiplier * IQR) # drop rows where col value is an outlier df = df[(df[col] >= lower_bound) & (df[col] <= upper_bound)] else: raise ValueError("Invalid method. Choose 'drop' or 'replace'.") df.to_csv(out_file, sep="\t", index=None) if __name__ == "__main__": import argparse parser = argparse.ArgumentParser(description="Outlier removal or replacement tool") parser.add_argument("-I", "--infile", required=True, help="Path to input TSV file") parser.add_argument("-C", "--column_list", required=True, help="Comma-separated list of 1-based column numbers to process") parser.add_argument("-O", "--outfile", required=True, help="Output TSV file path") parser.add_argument("-M", "--method", required=True, choices=["drop", "replace"], help="Select whether to 'drop' outliers or 'replace' with median") parser.add_argument("-QU", "--upper_quartile", default=75, help="Upper quartile value (default 75)") parser.add_argument("-QL", "--lower_quartile", default=25, help="Lower quartile value (default 25)") parser.add_argument("-MU", "--multiplier_constant", default=1.5, help="IQR multiplier constant (default 1.5)") parser.add_argument("-S", "--sep", default='\t', help="deliminator") args = parser.parse_args() AddMedian(args.infile, args.column_list, args.outfile, args.method, args.upper_quartile, args.lower_quartile, args.multiplier_constant, args.sep)