Adding function converting topology to .npz

GenNet_utils/Convert_topology_npz.py

@@ -0,0 +1,43 @@
+import argparse
+import numpy as np
+import pandas as pd
+import sys
+import os
+import scipy
+import h5py
+import tables
+from scipy import stats
+
+def main():
+    """
+    args: 
+    snp: the name of the column in the topology.csv dataset with the ID for the SNP column
+    gene: the name of the column in the topology.csv dataset with the ID for the gene column
+    direc: (Optional) the directory where the topology.csv file is located, if omitted it takes the current directory
+
+    Return: SNP_gene_mask.npz, the .npz file corresponding to the topology.csv
+    """
+    parser = argparse.ArgumentParser(description="A simple script with command-line arguments")
+    parser.add_argument("--snp", help="Your snp", required=True)
+    parser.add_argument("--gene", help="Your gene", required=True)
+    parser.add_argument("--direc", help="Your Directory", required=False)
+    args = parser.parse_args()
+    if args.direc:
+        try:
+            os.chdir(args.direc)
+            print(f"Navigated to directory: {os.getcwd()}")
+        except FileNotFoundError:
+            print(f"Directory '{args.direc}' not found.")
+
+    snp_level = args.snp #"layer0_node"
+    gene_level = args.gene #"layer1_node"
+    topology = pd.read_csv("topology.csv")
+    data = np.ones(len(topology), np.bool)
+    coord = ( topology[snp_level].values, topology[gene_level].values )
+    SNP_gene_matrix = scipy.sparse.coo_matrix(((data),coord),  shape = (topology[snp_level].max()+1, topology[gene_level].max()+1 ))
+    scipy.sparse.save_npz('SNP_gene_mask', SNP_gene_matrix)
+
+if __name__ == "__main__":
+    main()
+
+