def sequential(graph_stats):
prev = graph_stats[0]
for curr in graph_stats[1:]:
comparator = GraphPairCompare(prev, curr)
delta = comparator.deltacon0()
yield delta
prev = curr
if __name__ == '__main__':
base_path = '/data/infinity-mirror/'
dataset = 'clique-ring-500-4'
models = ['CNRG', 'Chung-Lu', 'Erdos-Renyi', 'SBM', 'HRG', 'NetGAN']
output_path = os.path.join(base_path, 'stats/deltacon/')
mkdir_output(output_path)
cols = ['model', 'gen', 'trial_id', 'deltacon']
g1 = nx.ring_of_cliques(500, 4)
g2 = nx.ring_of_cliques(500, 4)
gpc1 = GraphPairCompare(GraphStats(g1, 1), GraphStats(g1, 1))
print('should def be 0', gpc1.deltacon0())
gpc2 = GraphPairCompare(GraphStats(g1, 1), GraphStats(g2, 1))
print('should probably be 0', gpc2.deltacon0())
exit()
for model in models[:1]:
abs_delta = []
trials = []
rows = {col: [] for col in cols}
for root, trial in load_data(base_path, dataset, model, True, False):
# graph_stats = compute_graph_stats(root)
if isinstance(root, list):
root_graph = root[0]
descendants = root[1:]
def absolute(graph_stats):
for gs in graph_stats[1:]:
comparator = GraphPairCompare(graph_stats[0], gs)
delta = comparator.deltacon0()
yield delta
def main(base_path, dataset, models):
if 'GraphRNN' in models:
#path = os.path.join(base_path, 'GraphRNN')
#for subdir, dirs, files in os.walk(path):
# if dataset == subdir.split('/')[-1].split('_')[0]:
# print(subdir)
# for filename in files:
# print(filename)
models.remove('GraphRNN')
for model in models:
path = os.path.join(base_path, dataset, model)
for subdir, dirs, files in os.walk(path):
for filename in files:
if 'seq' not in filename:
run_id = int(filename.split('.')[0].split('_')[-1])
string = subdir.split('/')[-2:]
file = os.path.join(subdir, filename)
newfile = file.split('.')[0]
if 'rob' in file:
newfile += '_seq_rob.pkl.gz'
else:
newfile += '_seq.pkl.gz'
print(f'starting\t{string[-2]}\t{string[-1]}\t{filename} ... ', end='', flush=True)
root = load_pickle(file)
node = root
try:
node.stats_seq
except AttributeError:
if type(node) is LightTreeNode:
node_graph_stats = GraphStats(run_id=run_id, graph=node.graph)
comparator = GraphPairCompare(GraphStats(graph=root.graph, run_id=run_id), \
GraphStats(graph=root.graph, run_id=run_id))
stats = {}
stats['lambda_dist'] = comparator.lambda_dist()
stats['node_diff'] = comparator.node_diff()
stats['edge_diff'] = comparator.edge_diff()
stats['pgd_pearson'] = comparator.pgd_pearson()
stats['pgd_spearman'] = comparator.pgd_spearman()
stats['deltacon0'] = comparator.deltacon0()
stats['degree_cvm'] = comparator.cvm_degree()
stats['pagerank_cvm'] = comparator.cvm_pagerank()
node = TreeNode(name=node.name, graph=node.graph, stats=stats, stats_seq={}, parent=node.parent, children=node.children)
elif type(node) is TreeNode:
node = TreeNode(name=node.name, graph=node.graph, stats=node.stats, stats_seq={}, parent=node.parent, children=node.children)
else:
print(f'node has unknown type: {type(node)}')
exit()
if node.stats_seq is None or node.stats_seq == {}:
node.stats_seq = {}
while len(node.children) > 0:
child = node.children[0]
try:
child.stats_seq = {}
except AttributeError:
child = TreeNode(name=child.name, graph=child.graph, stats=child.stats, stats_seq={}, parent=child.parent, children=child.children)
comparator = GraphPairCompare(GraphStats(graph=node.graph, run_id=run_id), \
GraphStats(graph=child.graph, run_id=run_id))
child.stats_seq['lambda_dist'] = comparator.lambda_dist()
child.stats_seq['node_diff'] = comparator.node_diff()
child.stats_seq['edge_diff'] = comparator.edge_diff()
child.stats_seq['pgd_pearson'] = comparator.pgd_pearson()
child.stats_seq['pgd_spearman'] = comparator.pgd_spearman()
child.stats_seq['deltacon0'] = comparator.deltacon0()
child.stats_seq['degree_cvm'] = comparator.cvm_degree()
child.stats_seq['pagerank_cvm'] = comparator.cvm_pagerank()
node = child
with open(newfile, 'wb') as f:
pickle.dump(root, f)
print(f'\tdone')