Hotfix class selection with example_ids

config_files/config_test.yml

 # The base configuration of the benchmark
 Base :
   log: True
-  name: ["plausible", "koukou"]
+  name: ["lives_13view", "koukou"]
   label: "_"
   type: ".hdf5"
   views:
-  pathf: "../data/"
+  pathf: "/home/baptiste/Documents/Datasets/Alexis/data/"
   nice: 0
   random_state: 42
   nb_cores: 1
-  full: True
+  full: False
   debug: True
   add_noise: False
   noise_std: 0.0
@@ -21,7 +21,7 @@ Classification:
   split: 0.9
   nb_folds: 2
   nb_class: 2
-  classes:
+  classes: ["EMF", ]
   type: ["multiview", "monoview"]
   algos_monoview: ["decision_tree", "adaboost", "random_forest" ]
   algos_multiview: ["weighted_linear_early_fusion",]

multiview_platform/mono_multi_view_classifiers/utils/dataset.py

@@ -291,8 +291,8 @@ class Dataset():
         new_dataset_file = h5py.File(dataset_file_path,"w")
         self.dataset.copy("Metadata", new_dataset_file)
         if "example_ids" in self.dataset["Metadata"].keys():
-            ex_ids = new_dataset_file["Metadata"]["example_ids"]
-            ex_ids[...] = np.array(self.example_ids)[example_indices].astype(np.dtype("S10"))
+            del new_dataset_file["Metadata"]["example_ids"]
+            ex_ids = new_dataset_file["Metadata"].create_dataset("example_ids", data=np.array(self.example_ids)[example_indices].astype(np.dtype("S10")))
         else:
             new_dataset_file["Metadata"].create_dataset("example_ids",
                                                         (len(self.example_ids), ),