From ac8806e1a3427ae3fed1ee0a4ca3dee98d29d1f1 Mon Sep 17 00:00:00 2001
From: Fize Jacques <jacques.fize@cirad.fr>
Date: Wed, 10 Feb 2021 14:14:09 +0100
Subject: [PATCH] Debug Node2vec
---
evalNE_script.py | 10 +++++++---
generate_theoric_random_graph.py | 2 +-
run_eval.py | 5 +++--
3 files changed, 11 insertions(+), 6 deletions(-)
diff --git a/evalNE_script.py b/evalNE_script.py
index 99d70ee..4aa2d08 100644
--- a/evalNE_script.py
+++ b/evalNE_script.py
@@ -42,11 +42,12 @@ log("Building link prediction dataset...")
# Create an evaluator and generate train/test edge split
traintest_split = LPEvalSplit()
try:
- traintest_split.compute_splits(G, split_alg="spanning_tree", train_frac=args.train_frac, fe_ratio=1)
+ traintest_split.compute_splits(G, split_alg="random", train_frac=args.train_frac, fe_ratio=1)
except ValueError:
traintest_split.compute_splits(G, split_alg="fast", train_frac=args.train_frac, fe_ratio=1)
+print("BEFORE", len(traintest_split.test_edges))
nee = LPEvaluator(traintest_split)
-
+print("AFTER",len(traintest_split.test_edges))
log("Dataset Built !")
# Create a Scoresheet to store the results
@@ -93,9 +94,12 @@ if args.network_embedding:
pbar = tqdm(enumerate(methods), disable=(not args.verbose))
for i,method in pbar:
pbar.set_description("Evaluate "+method)
+ is_weighted = nx.is_weighted(G)
command = commands[i] + " --input {} --output {} --representation-size {}"
+ if is_weighted:
+ command = command + " --weighted"
results = nee.evaluate_cmd(method_name=methods[i], method_type='ne', command=command,
- edge_embedding_methods=edge_emb, input_delim=' ', output_delim=' ', verbose=args.verbose,write_weights=nx.is_weighted(G))
+ edge_embedding_methods=edge_emb, input_delim=' ', output_delim=' ', verbose=args.verbose,write_weights=is_weighted)
scoresheet.log_results(results)
except ImportError:
diff --git a/generate_theoric_random_graph.py b/generate_theoric_random_graph.py
index 2a3a2ff..d7f5796 100644
--- a/generate_theoric_random_graph.py
+++ b/generate_theoric_random_graph.py
@@ -18,7 +18,7 @@ args = parser.parse_args()
GRAPH_SIZE = [80,800]
-EDGE_SIZE = [2,3]
+EDGE_SIZE = [2,4,5]
sample_per_params = 4
OUTPUT_DIR = args.output_dir
diff --git a/run_eval.py b/run_eval.py
index 985f55c..121bdcb 100644
--- a/run_eval.py
+++ b/run_eval.py
@@ -16,6 +16,7 @@ parser.add_argument("dataset_dir")
parser.add_argument("output_filename")
parser.add_argument("-f", "--format", default="gexf", choices=["gexf", "gml", "txt"])
parser.add_argument("-t","--train-frac",default=0.9,type=float)
+parser.add_argument("-v","--verbose",action="store_true")
args = parser.parse_args()
fns = sorted(glob.glob(args.dataset_dir + "/*." + args.format))
@@ -24,9 +25,9 @@ all_res = []
pbar = tqdm(fns)
for fn in pbar:
pbar.set_description("run eval on "+ fn)
-
+ verbose_cmd = "-v" if args.v else ""
if not os.path.exists(fn + "_results_lp"):
- command = "python evalNE_script.py {0} -f {1} -n --train-frac {2}".format(fn, args.format,args.train_frac).split()
+ command = "python evalNE_script.py {0} -f {1} -n --train-frac {2} {3}".format(fn, args.format,args.train_frac,verbose_cmd).split()
output = subprocess.run(command)
if not output.returncode == 0:
print("Error! for the command :", " ".join(command))
--
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