rewrite molecule generation with tested code

deconvolution/generate_fake_molecule_graph.py

 #!/usr/bin/env python3
 
-# generate a bunch of molecules, in the form of python intervals (a,b), i.e. a<=i<b. here, b-a=10
-# then find their overlaps >= 1 bases
+import argparse
+import sys
 
-# rationale for realistic parameters:
-# https://support.10xgenomics.com/de-novo-assembly/datasets/2.1.0/fly
-# drosophila genome, 140 Mbp
-# molecules of 70 kbp 
-# coverage of 70x
-# number of barcodes: 50k (only) (zcat barcoded.fastq.gz | grep "^@" | awk '{print $2}'  | sort | uniq  |wc -l)
-# number of molecule per barcode: 10 (~/10x/drosophila/chen_data_longranger_run_on_ref/outs$ samtools view phased_possorted_bam.bam | python ~/10x-barcode-graph/scripts/sam_stats.py)
-# so in total, 500k molecules
-# i.e. the molecule coverage is around 140Mbp/500kbp = 280x
-# conservatively, it seems that we can get overlaps for at least 20 neighbor molecules
-# so in that setting, considering each molecule as '1bp', i.e. scaling the genome down to 140Mbp/70kbp=2Mbp
-# n = 2000
-# o = 50
+import graph_manipulator as gm
 
 
+def parse_arguments():
+    parser = argparse.ArgumentParser(description='Generate a fake homogenous 10X molecule graph.')
+    parser.add_argument('--num_molecule', '-n', type=int, required=True, help='The number of molecule in the graph')
+    parser.add_argument('--depth', '-d', type=int, required=True, help='The number of melecule linked on each direction of the chain.')
+    parser.add_argument('--output', '-o', help="Output filename")
 
-n = 1500
-o = 6
+    args = parser.parse_args()
+    return args
 
-molecules_intervals = []
-for i in range(n):
-    molecules_intervals += [(i,i+o)]
 
-#print(molecules_intervals)
+def generate_graph(n, d):
+    return gm.generate_d_graph_chain(n, d)
 
-def overlap(a,b):
-    for i in range(*a):
-        if i in range(*b):
-            return True
-    return False
 
-#print(overlap(molecules_intervals[0],molecules_intervals[2]))
-#print(overlap(molecules_intervals[0],molecules_intervals[20]))
+def save_graph(G, outfile):
+    import networkx as nx
+    nx.write_gexf(G, outfile)
 
-import networkx as nx
-G = nx.Graph()
 
-for i,a in enumerate(molecules_intervals):
-    G.add_node(i)
+if __name__ == "__main__":
+    args = parse_arguments()
+    G = generate_graph(args.num_molecule, args.depth)
 
-for i,a in enumerate(molecules_intervals):
-    for j,b in enumerate(molecules_intervals):
-        if i >= j: continue
-        if overlap(a,b):
-            G.add_edge(i,j)
+    outfile = f"simulated_molecules_{args.num_molecule}_{args.depth}.gexf"
+    if args.output:
+        outfile = args.outfile
+    save_graph(G, outfile)
 
-print(G.edges())
-
-nx.write_graphml(G, f"data/simulated_molecules_{n}_{o-1}.graphml")