add run_eval script

run_eval.py

+# coding = utf-8
+
+import glob
+import subprocess
+from lib.helpers import parse_evalne_output
+from lib.utils import load_edgelist
+import os
+import pandas as pd
+from tqdm import tqdm
+
+import argparse
+
+parser = argparse.ArgumentParser()
+parser.add_argument("dataset_dir")
+parser.add_argument("output_filename")
+
+args = parser.parse_args()
+fns = glob.glob(args.dataset_dir + "/*.txt")
+
+all_res = []
+for fn in tqdm(fns):
+    print("run eval on ", fn)
+    command = "python evalNE_script.py {0} -v".format(fn).split()
+    output = subprocess.run(command)
+    if not output.returncode == 0:
+        print("Error! for the command :", " ".join(command))
+        continue
+    df_results = parse_evalne_output(open(fn + "_results_lp").read())
+    name = os.path.basename(fn)
+    edge_len = len(pd.read_csv(fn, sep="\t", header=None))
+    df_results["nb_edge"] = edge_len
+    df_results["filename"] = name
+    all_res.append(df_results)
+
+pd.concat(all_res).to_csv(args.output_filename,sep="\t",index=None)
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