diff test-data/test-db/metaphlan-db/customizemapping.py @ 2:5ae955d5bd2b draft

planemo upload for repository https://github.com/galaxyproject/tools-iuc/tree/master/tools/humann commit 0966faf8782e9043772acfa32f4a4281687a19dd

--- /dev/null	Thu Jan 01 00:00:00 1970 +0000
+++ b/test-data/test-db/metaphlan-db/customizemapping.py	Tue Feb 07 19:40:59 2023 +0000
@@ -0,0 +1,50 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# Script to generate a extract a custom mapping file from input mapping file.
+# Mostly used for a reduced-size demo data generation.
+
+
+import argparse
+from pathlib import Path
+
+
+if __name__ == '__main__':
+    # Read command line
+    parser = argparse.ArgumentParser(description='Customize HUMAnN utility mapping')
+    parser.add_argument('--in_mapping', help="Path to mapping file to reduce")
+    parser.add_argument('--features', help="Path to tabular file with features to keep in first column")
+    parser.add_argument('--elements', help="Path to tabular file with elements to keep in other columns")
+    parser.add_argument('--out_mapping', help="Path to reduced mapping file")
+    args = parser.parse_args()
+
+    in_mapping_fp = Path(args.in_mapping)
+    feature_fp = Path(args.features)
+    element_fp = Path(args.elements)
+    out_mapping_fp = Path(args.out_mapping)
+
+    # extract features to keep
+    features = set()
+    with open(feature_fp, 'r') as feature_f:
+        for line in feature_f.readlines():
+            features.add(line.split("\t")[0])
+    print(features)
+
+    # extract elements to keep
+    elements = set()
+    with open(element_fp, 'r') as element_f:
+        for line in element_f.readlines():
+            elements.add(line.split("\t")[0])
+    print(elements)
+
+    # write mapping for features to keep while keeping only elements
+    with open(in_mapping_fp, 'r') as in_mapping_f:
+        with open(out_mapping_fp, 'w') as out_mapping_f:
+            for line in in_mapping_f.readlines():
+                l_split = line.split("\t")
+                feat = l_split[0]
+                if feat in features:
+                    to_write = [feat]
+                    for e in l_split[1:]:
+                        if e in elements:
+                            to_write.append(e)
+                    out_mapping_f.write("%s\n" % '\t'.join(to_write))