From 3e2abe83e33bc90ce6e11f0ab38fd27a80b63284 Mon Sep 17 00:00:00 2001
From: quillotm <mathias.quillot@univ-avignon.fr>
Date: Thu, 12 Aug 2021 13:51:34 +0200
Subject: [PATCH] Multiple output for measure action. These multiple output are
 written in json.

---
 volia/clustering.py | 43 +++++++++++++++++++++++++++++--------------
 1 file changed, 29 insertions(+), 14 deletions(-)

diff --git a/volia/clustering.py b/volia/clustering.py
index 7411f48..cf22299 100644
--- a/volia/clustering.py
+++ b/volia/clustering.py
@@ -11,6 +11,7 @@ from sklearn.preprocessing import LabelEncoder
 from sklearn.metrics import v_measure_score
 
 import core.measures
+import json
 
 
 CLUSTERING_METHODS = {
@@ -28,23 +29,37 @@ def disequilibrium_run():
 
 
 def measure_run(measure: str, features: str, lst: str, truelabels: str, model: str, modeltype: str):
+    """
+
+    @param measure:
+    @param features:
+    @param lst:
+    @param truelabels:
+    @param model:
+    @param modeltype:
+    @return:
+    """
     module = CLUSTERING_METHODS[modeltype]
     module.load(model)
-    evaluation = EVALUATION_METHODS[measure]
-    feats_dict = read_features(features)
-    labels_dict = read_labels(truelabels)
-    lst_dict = read_lst(lst)
-    lst_keys = [key for key in lst_dict]
-    feats = np.asarray([feats_dict[key] for key in lst_keys])
-    Y_pred = module.predict(feats)
-    Y_truth = [labels_dict[key][0] for key in lst_keys]
 
-    le = LabelEncoder()
-    le.fit(Y_truth)
-    Y_truth = le.transform(Y_truth)
+    eval = {}
+    for ms in measure:
+        evaluation = EVALUATION_METHODS[ms]
+        feats_dict = read_features(features)
+        labels_dict = read_labels(truelabels)
+        lst_dict = read_lst(lst)
+        lst_keys = [key for key in lst_dict]
+        feats = np.asarray([feats_dict[key] for key in lst_keys])
+        Y_pred = module.predict(feats)
+        Y_truth = [labels_dict[key][0] for key in lst_keys]
+
+        le = LabelEncoder()
+        le.fit(Y_truth)
+        Y_truth = le.transform(Y_truth)
+
+        eval[ms] = evaluation(Y_truth, Y_pred)
 
-    eval = evaluation(Y_truth, Y_pred)
-    print(eval)
+    print(json.dumps(eval))
 
 
 
@@ -125,7 +140,7 @@ if __name__ == "__main__":
 
     parser_measure.add_argument("--measure",
                                 required=True,
-                                type=str,
+                                nargs="+",
                                 choices=[key for key in EVALUATION_METHODS],
                                 help="...")
     parser_measure.add_argument("--features", required=True, type=str, help="...")
-- 
1.8.2.3