def upwalker_counter(g, meta, vf_g, arguments): N = g.vcount() progress = progressbar1.DummyProgressBar(end=10, width=15) if arguments.progressbar: progress = progressbar1.AnimatedProgressBar(end=len(meta), width=15) # trace_up_map = {} # random_up_map = {} trace_up_counter = [] random_up_counter = [] for m in meta: progress += 1 progress.show_progress() trace = m[helpers.TRACE] trace_dir = vft.trace_to_string(g, trace) trace_up_count = trace_dir.count('U') trace_up_counter.append(trace_up_count) # trace_up_map[trace_up_count] = trace_up_map.get(trace_up_count, 0) + # 1 s, t = trace[0], trace[-1] s_idx, t_idx = vft.node_to_nodeid(g, s), vft.node_to_nodeid(g, t) random_vf_route = helpers.random_route_walk(vf_g, s_idx, t_idx + N, len(trace), named=False, weight_field='VFweight') random_vf_route = vft.vf_route_converter(random_vf_route, N) random_vf_dir = vft.trace_to_string(g, random_vf_route) random_vf_count = random_vf_dir.count('U') random_up_counter.append(random_vf_count) # random_up_map[random_vf_count] = random_up_map.get(random_vf_count, # 0) + 1 real_counter = collections.Counter(trace_up_counter) real_up = ' '.join( ['%s: %s' % (k, real_counter[k]) for k in sorted(list(real_counter))]) random_counter = collections.Counter(random_up_counter) random_up = ' '.join([ '%s: %s' % (k, random_counter[k]) for k in sorted(list(random_counter)) ]) logger.info('') logger.info('Real trace UP counter: %s' % real_up) logger.info('Random vf trace up counter: %s' % random_up) helpers.save_to_json(arguments.out, { 'REAL': dict(real_counter), 'RANDOM': dict(random_counter) }) keys = sorted(set(list(real_counter) + list(random_counter))) logger.info('IDX;REAL;RANDOM') for k in keys: logger.info('%s;%d;%d' % (k, real_counter[k], random_counter[k]))
def ba_generator(ba_graph, sh_paths, stretch, vf_g, progressbar=False): vf_count = 0 trace_count = 0 lp_count = 0 progress = progressbar1.DummyProgressBar(end=10, width=15) if progressbar: progress = progressbar1.AnimatedProgressBar(end=len(sh_paths), width=15) for (s, t), shl in sh_paths: progress += 1 progress.show_progress() logger.debug('SH from %s to %s is %d' % (s, t, shl)) random_route = helpers.random_route_walk(ba_graph, s, t, shl + stretch) logger.debug('Random route: %s' % random_route) real_stretch = len(random_route) - shl if real_stretch != stretch: continue trace_count += 1 is_vf = vft.is_valley_free(ba_graph, random_route, vfmode=vft.CLOSENESS) logger.debug( 'Trace edge dir: %s' % vft.trace_to_string(ba_graph, random_route, vfmode=vft.CLOSENESS)) logger.debug('Is VF: %s' % is_vf) if is_vf: is_lp = vft.is_local_preferenced(ba_graph, random_route, first_edge=True, vfmode=vft.CLOSENESS, vf_g=vf_g) else: is_lp = 0 logger.debug('Is LP: %s' % is_lp) vf_count += int(is_vf) lp_count += int(is_lp) logger.info('Stretch %d' % stretch) logger.info('Trace count: %d' % trace_count) logger.info('VF count: %d' % vf_count) logger.info('LP count: %d' % lp_count) return (stretch, trace_count, vf_count, lp_count)
def filter(g, traceroutes): results = list() # remove traces with unknown nodes traceroutes = vft.trace_in_vertex_id(g, traceroutes) progress = progressbar1.AnimatedProgressBar(end=len(traceroutes), width=15) for trace in traceroutes: progress += 1 progress.show_progress() if not vft.trace_exists(g, trace): print 'BUG?' continue for x in range(0, g.vcount()): g.vs[x]['traces'] = dict() trace = tuple(trace) s, t = trace[0], trace[-1] sh_len = g.shortest_paths(s, t, mode=i.ALL)[0][0] sh_len += 1 # igraph's hop count to node count all_routes = helpers.dfs_mark(g, s, t, sh_len + 1) # all_routes2 = helpers.dfs_simple(g, s, t, sh_len + 1, ()) # if set(all_routes) - set(all_routes2) != set(all_routes2) - set(all_routes): # print 'AJAJAJ' # print all_routes # print '----------' # print all_routes2 sh_routes = [x for x in all_routes if len(x) == sh_len] all_vf_routes = [x for x in all_routes if vft.is_valley_free(g, x)] prediction_set = set(sh_routes) | set(all_vf_routes) result = [ trace, len(trace), sh_len, len(sh_routes), trace in sh_routes, len(all_vf_routes), trace in all_vf_routes, len(all_routes), trace in all_routes, len(prediction_set), trace in prediction_set, vft.is_valley_free(g, trace), # sh_routes, all_vf_routes, all_routes, vft.trace_to_string(g, trace) ] results.append(result) print >> sys.stderr, ( 'TRACE\tTRACE_LEN\tSH_LEN', '\t#SH_ROUTE\tOK', '\t#ALL_VF\tOK', '\t#ALL_ROUTE\tOK', '\t#PREDICTION_SET\tOK', '\tIS_VF', # '\tSH_ROUTES\tALL_VF_ROUTES\tALL_ROUTE', '\tTRACE_STR') for result in results: result = [str(r) for r in result] print >> sys.stderr, '\t'.join(result) return results
def trace_dir(g, meta, vf_g, arguments): N = g.vcount() vf_sum_lp_w = sum([e['LPweight'] for e in vf_g.es]) out_instead_core = 0 core_instead_out = 0 in_customer = 0 in_customer_but_use_up = 0 progress = progressbar1.DummyProgressBar(end=10, width=15) if arguments.progressbar: progress = progressbar1.AnimatedProgressBar(end=len(meta), width=15) for m in meta: progress += 1 progress.show_progress() trace = m[helpers.TRACE] first_edge = [trace[0], trace[1]] first_hop_type = vft.edge_dir(g, first_edge, vfmode=vft.CLOSENESS) s_idx = vft.node_to_nodeid(g, trace[0]) t_idx = vft.node_to_nodeid(g, trace[-1]) sh_vf = vf_g.get_all_shortest_paths(s_idx + N, t_idx + N) if len(sh_vf) > 0: in_customer += 1 if first_hop_type != LinkDir.D: in_customer_but_use_up += 1 if first_hop_type == LinkDir.D: # 'remove' all downward path: for neighbor in vf_g.neighbors(s_idx + N, mode=igraph.OUT): down_edge = vf_g.get_eid(s_idx + N, neighbor, directed=True) vf_g.es[down_edge]['LPweight_old'] = vf_g.es[down_edge][ 'LPweight'] vf_g.es[down_edge]['LPweight'] = vf_sum_lp_w + 1 lp_sh = vft.get_shortest_vf_route(g, s_idx, t_idx, mode='lp', vf_g=vf_g, vfmode=vft.CLOSENESS) pretty_plotter.pretty_plot(g, trace, lp_sh, []) first_new_edge = [lp_sh[0], lp_sh[1]] first_new_hop_type = vft.edge_dir(g, first_new_edge, vfmode=vft.CLOSENESS) if first_hop_type != first_new_hop_type: out_instead_core += 1 print '' print "Original trace: %s" % trace print 'Original trace dir: %s' % vft.trace_to_string(g, trace) print 'Original closeness: %s' % [ g.vs.find(x)['closeness'] for x in trace ] print 'LP trace: %s' % [g.vs[x]['name'] for x in lp_sh] print 'LP dir: %s' % vft.trace_to_string(g, lp_sh) print 'LP closeness: %s' % [ g.vs.find(x)['closeness'] for x in lp_sh ] # raw_input() for neighbor in vf_g.neighbors(s_idx + N, mode=igraph.OUT): down_edge = vf_g.get_eid(s_idx + N, neighbor, directed=True) vf_g.es[down_edge]['LPweight'] = vf_g.es[down_edge][ 'LPweight_old'] elif first_hop_type == LinkDir.U: lp_sh = vft.get_shortest_vf_route(g, s_idx, t_idx, mode='lp', vf_g=vf_g, vfmode=vft.CLOSENESS) lp_dir = vft.trace_to_string(g, lp_sh) # if lp_dir[1:].startswith('U') or lp_dir[1:].startswith('D'): # continue first_new_edge = [lp_sh[0], lp_sh[1]] first_new_hop_type = vft.edge_dir(g, first_new_edge, vfmode=vft.CLOSENESS) if first_hop_type != first_new_hop_type: core_instead_out += 1 print '' print "Original trace: %s" % trace print 'Original trace dir: %s' % vft.trace_to_string(g, trace) print 'Original closeness: %s' % [ g.vs.find(x)['closeness'] for x in trace ] print 'LP trace: %s' % [g.vs[x]['name'] for x in lp_sh] print 'LP dir: %s' % vft.trace_to_string(g, lp_sh) print 'LP closeness: %s' % [ g.vs.find(x)['closeness'] for x in lp_sh ] pretty_plotter.pretty_plot(g, trace, lp_sh, []) # raw_input() logger.info('Core instead down: %d' % core_instead_out) logger.info('Down instead core: %d' % out_instead_core) logger.info('In customer cone: %d' % in_customer) logger.info('In customer but use UP: %d' % in_customer_but_use_up)
def main(): parser = argparse.ArgumentParser( description=('Syntetic route generator'), formatter_class=argparse.ArgumentDefaultsHelpFormatter) parser.add_argument('--progressbar', action='store_true') parser.add_argument('--verbose', '-v', action='count', default=0) parser.add_argument('network') parser.add_argument('meta') parser.add_argument('all_trace_out', metavar='all-trace-out') parser.add_argument('syntetic_out', metavar='syntetic-out') parser.add_argument('--trace-count', '-tc', type=int, dest='trace_count', default=5000) parser.add_argument('--random-sample', dest='random_sample', action='store_true') parser.add_argument('--closeness-error', '-ce', type=float, dest='closeness_error', default=0.0) parser.add_argument('--core-limit-percentile', '-cl', type=int, dest='core_limit', default=0) parser.add_argument('--toggle-node-error-mode', action='store_true') arguments = parser.parse_args() arguments.verbose = min(len(helpers.LEVELS) - 1, arguments.verbose) logging.getLogger('compnet').setLevel(helpers.LEVELS[arguments.verbose]) show_progress = arguments.progressbar g = helpers.load_network(arguments.network) g = g.simplify() meta = helpers.load_from_json(arguments.meta) if arguments.random_sample: random.shuffle(meta) meta = meta[:arguments.trace_count] N = g.vcount() cl = sorted([x['closeness'] for x in g.vs], reverse=True) logger.info('Min closeness: %s' % np.min(cl)) logger.info('Max closeness: %s' % np.max(cl)) logger.info('Mean closenss: %s' % np.mean(cl)) logger.info('10%% closeness: %s' % np.percentile(cl, 10)) logger.info('90%% closeness: %s' % np.percentile(cl, 90)) logger.info('Core limit: [r]%d%%[/]' % arguments.core_limit) change_probability = 100 * arguments.closeness_error logger.info('Change probability: [r]%6.2f%%[/]' % change_probability) core_limit = np.percentile(cl, arguments.core_limit) logger.info('Core limit in closeness: [bb]%f[/]' % core_limit) if arguments.toggle_node_error_mode: logger.info('[r]Node error mode[/]') msg = ( "If given node's closeness >= core_limit then the new ", "closeness in this node is ", #"rand(closeness_error ... old closeness)" "OLD_CLOSENSS * +/- closeness_error%") logger.info(''.join(msg)) logger.info('Minimum node closeness: [g]%f[/]' % arguments.closeness_error) for n in g.vs: if n['closeness'] < core_limit: continue # sign = -1 if random.uniform(-1, 1) < 0 else 1 # n['closeness'] = n['closeness'] * (1 + sign * arguments.closeness_error) new_closeness = random.uniform(arguments.closeness_error, n['closeness']) n['closeness'] = new_closeness g_labeled = vft.label_graph_edges(g, vfmode=vft.CLOSENESS) peer_edge_count = len([x for x in g_labeled.es if x['dir'] == LinkDir.P]) logger.info('Peer edge count: %d' % peer_edge_count) changed_edges = [] if not arguments.toggle_node_error_mode: msg = ("If the closeness values of the endpoints in given edge is ", "larger than the core_limit and ", "random(0,1) < closeness_error then change the direction ", "for this edge") logger.info(''.join(msg)) changed_u = changed_d = 0 changed_edges = [] changed_edgess = [] for edge in g_labeled.es: s, t = edge.source, edge.target s_cl = g_labeled.vs[s]['closeness'] t_cl = g_labeled.vs[t]['closeness'] if (s_cl < core_limit or t_cl < core_limit): continue if random.uniform(0, 1) > arguments.closeness_error: continue # if abs(s_cl - t_cl) / min(s_cl, t_cl) > 0.02: continue new_edge_dir = LinkDir.U if random.uniform(0, 1) > 0.5 else LinkDir.D if new_edge_dir != edge['dir']: if edge['dir'] == LinkDir.U: changed_u += 1 else: changed_d += 1 edge['dir'] = new_edge_dir changed_edges.append(edge) changed_edgess.append((edge.source, edge.target)) # if edge['dir'] == LinkDir.U: # changed_u += 1 # changed_edgess.append((edge.source, edge.target)) # edge['dir'] = LinkDir.D # changed_edges.append(edge) # elif edge['dir'] == LinkDir.D: # changed_d += 1 # changed_edgess.append((edge.source, edge.target)) # edge['dir'] = LinkDir.U # changed_edges.append(edge) logger.info('E count: %d' % g_labeled.ecount()) logger.info('Changed U: %d' % changed_u) logger.info('Changed D: %d' % changed_d) logger.info('Changed: %d' % (changed_d + changed_u)) changed_e = [(g_labeled.vs[e.source]['name'], g_labeled.vs[e.target]['name']) for e in changed_edges] changed_e = changed_e + [(x[1], x[0]) for x in changed_e] changed_e = set(changed_e) vf_g_closeness = vft.convert_to_vf(g, vfmode=vft.CLOSENESS, labeled_graph=g_labeled) # e_colors = [] # for e in vf_g_closeness.es: # if e.source < N and e.target < N: col = 'grey' # elif e.source < N and e.target >= N: col = 'blue' # elif e.source >= N and e.target >= N: col = 'red' # else: col = 'cyan' # e_colors.append(col) # igraph.plot(vf_g_closeness, "/tmp/closeness.pdf", # vertex_label=vf_g_closeness.vs['name'], # vertex_size=0.2, # edge_color=e_colors) pairs = [(g.vs.find(x[helpers.TRACE][0]).index, g.vs.find(x[helpers.TRACE][-1]).index, tuple(x[helpers.TRACE])) for x in meta] # pairs = list(set(pairs)) # random.shuffle(pairs) # visited = set() # pairs2 = [] # for x in pairs: # k = (x[0], x[1]) # if k in visited: continue # visited.add(k) # visited.add((k[1], k[0])) # pairs2.append(x) # pairs = pairs2 traces = [x[2] for x in pairs] stretches = [] syntetic_traces = [] sh_traces = [] base_traces = [] original_traces = [] bad = 0 progress = progressbar1.DummyProgressBar(end=10, width=15) if show_progress: progress = progressbar1.AnimatedProgressBar(end=len(pairs), width=15) for s, t, trace_original in pairs: progress += 1 progress.show_progress() trace_original_idx = [g.vs.find(x).index for x in trace_original] logger.debug('Original trace: %s -- %s -- %s', [g.vs[x]['name'] for x in trace_original_idx], vft.trace_to_string(g, trace_original_idx, vft.CLOSENESS), [g.vs[x]['closeness'] for x in trace_original_idx]) sh_routes = g.get_all_shortest_paths(s, t) sh_len = len(sh_routes[0]) sh_routes_named = [[g.vs[y]['name'] for y in x] for x in sh_routes] sh_trace_name = random.choice(sh_routes_named) base_trace_name = random.choice(sh_routes_named) candidates = vf_g_closeness.get_all_shortest_paths(s + N, t + N) candidates = [vft.vf_route_converter(x, N) for x in candidates] # candidates = [] if len(candidates) == 0: candidates = vft.get_shortest_vf_route(g_labeled, s, t, mode='vf', vf_g=vf_g_closeness, _all=True, vfmode=vft.CLOSENESS) if len(candidates) == 0: s_name, t_name = g.vs[s]['name'], g.vs[t]['name'] logger.debug("!!!No syntetic route from %s to %s" % (s_name, t_name)) continue logger.debug('Candidates from %s to %s:' % (g.vs[s]['name'], g.vs[t]['name'])) for c in candidates: logger.debug('%s -- %s -- %s' % ([g.vs[x]['name'] for x in c], vft.trace_to_string(g_labeled, c, vft.PRELABELED), [g.vs[x]['closeness'] for x in c])) chosen_one = random.choice(candidates) chosen_one_name = [g.vs[x]['name'] for x in chosen_one] # print chosen_one # print trace_original # pretty_plotter.pretty_plot(g, trace_original_idx, # chosen_one, changed_edgess, # spec_color=(0, 0, 0, 155)) hop_stretch = len(chosen_one) - sh_len stretches.append(hop_stretch) trace_original_e = zip(trace_original, trace_original[1:]) chosen_one_e = zip(chosen_one_name, chosen_one_name[1:]) trace_affected = any([x in changed_e for x in trace_original_e]) chosen_affected = any([x in changed_e for x in chosen_one_e]) logger.debug('Trace affected: %s' % trace_affected) logger.debug('Chosen affected: %s' % chosen_affected) # if hop_stretch > 2: # logger.debug('Base: %s' % trace_to_string(g_labeled, base_trace_name)) # logger.debug('SH: %s' % trace_to_string(g_labeled, sh_trace_name)) # logger.debug('Trace: %s' % trace_to_string(g_labeled, trace_original)) # logger.debug('Syntetic: %s' % trace_to_string(g_labeled, chosen_one_name)) if trace_affected or chosen_affected or hop_stretch > 2: # pretty_plotter.pretty_plot_all(g, traces, # chosen_one, changed_edgess, # spec_color=(0, 0, 0, 255)) bad += 1 syntetic_traces.append(chosen_one_name) sh_traces.append(sh_trace_name) base_traces.append(base_trace_name) original_traces.append(trace_original) logger.debug('From %s to %s chosen one %s' % (g.vs[s]['name'], g.vs[t]['name'], chosen_one_name)) result = zip(base_traces, sh_traces, original_traces, syntetic_traces) helpers.save_to_json(arguments.all_trace_out, result) helpers.save_to_json(arguments.syntetic_out, syntetic_traces) print 'Bad: %d' % bad c = collections.Counter(stretches) trace_count = len(syntetic_traces) logger.info('Stretch dist:') for k in c: logger.info('\t%d: %5.2f%%[%d]' % (k, 100 * c[k] / float(trace_count), c[k])) logger.info('Valid route count: %d' % trace_count) logger.info('Route count parameter: %d' % arguments.trace_count) logger.info('Generated valid pair count: %d' % len(pairs))
def test_trace_to_string(self): trace = [0, 5, 4, 6, 5, 1, 5, 6, 4, 6, 2] trace_str = vft.trace_to_string(self.sample_graph, trace) self.assertEqual(trace_str, 'UUDPDUPUDD')