Adds script to convert shed data into csv.

util/shed_process

+#!/usr/bin/env python
+
+import csv
+import json
+import sys
+from argparse import ArgumentParser
+from collections import defaultdict, namedtuple
+from itertools import groupby
+from os import path
+
+import networkx as nx
+
+def main(args):
+    seers = set()
+    observations = set()
+    with open(args['csv_path']) as csv_file:
+        csv_file = csv.DictReader(csv_file)
+        for row in csv_file:
+            time = int(row[args['time_column']])
+            seer = row[args['seer_column']]
+            seen = row[args['seen_column']]
+            if time >= 0:
+                seers.add(seer)
+                observations.add((time, seer, seen))
+
+    graph = nx.Graph()
+    for time, seer, seen in observations:
+        if seen not in seers:
+            continue
+
+        if not graph.has_edge(seer, seen):
+            graph.add_edge(seer, seen, {'times': set()})
+        graph[seer][seen]['times'].add(time)
+
+    nodes = max(nx.connected_components(graph), key=len)
+    nodes = {node: index for index, node in enumerate(nodes)}
+
+    contacts = []
+
+    for node_a, node_b, times in graph.edges(nbunch=nodes, data='times'):
+        times = sorted(times)
+        node_a, node_b = nodes[node_a], nodes[node_b]
+
+        for _, group in groupby(enumerate(times), lambda p: p[0]-p[1]):
+            contact = list(map(lambda g: g[1], group))
+            contacts.append((contact[0], node_a, node_b, True))
+            contacts.append((contact[-1] + 1, node_a, node_b, False))
+
+    contacts.sort(key=lambda c: c[0])
+
+    start = contacts[0][0]
+    duration = contacts[-1][0] - start
+
+    metadata = {
+        'nodes': len(nodes),
+        'contacts': len(contacts)/2,  # account for both up and down
+        'duration': duration,
+    }
+
+    meta_path = path.join(args['outdir'], 'metadata.json')
+    with open(meta_path, 'w') as meta_file:
+        json.dump(metadata, meta_file)
+        print('wrote: %s' % meta_path)
+
+    contact_path = path.join(args['outdir'], 'contact.csv')
+    with open(contact_path, 'w') as contact_file:
+        writer = csv.writer(contact_file)
+        writer.writerow(['time','a','b','join'])
+        for contact in contacts:
+            contact = list(map(int, contact))
+            contact[0] = (contact[0] - start) * args['duty_cycle_length']
+            print(contact)
+            writer.writerow(contact)
+        print('wrote: %s' % contact_path)
+
+
+def parse_args(args):
+    parser = ArgumentParser()
+
+    parser.add_argument('csv_path',
+                        help='path to csv to process')
+
+    parser.add_argument('outdir',
+                        help='directory to output metadata and contacts')
+
+    parser.add_argument('time_column',
+                        help='column used for time slots')
+
+    parser.add_argument('seer_column',
+                        help='column used for devices that scan for others.')
+
+    parser.add_argument('seen_column',
+                        help='column used for devices are seen during a scan.')
+
+    parser.add_argument('--duty_cycle_length', default=300, type=int)
+
+    return vars(parser.parse_args(args))
+
+if __name__ == '__main__':
+    exit(main(parse_args(sys.argv[1:])))