[FIX] resample NEG supports

NINAnor · Mar 18, 2024 · 4c058e4 · 4c058e4
1 parent 16a48d7
commit 4c058e4
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Showing 2 changed files with 13 additions and 15 deletions.
diff --git a/evaluate/_utils_compute.py b/evaluate/_utils_compute.py
@@ -9,7 +9,6 @@
 from datamodules.TestDCASEDataModule import DCASEDataModule, AudioDatasetDCASE
 
 import pytorch_lightning as pl
-pl.utilities.seed.seed_everything(42, workers=True)
 
 def to_dataframe(features, labels):
     # Load the saved array and map the features and labels into a single dataframe

diff --git a/evaluate/evaluateDCASE.py b/evaluate/evaluateDCASE.py
@@ -21,7 +21,7 @@
 from datamodules.TestDCASEDataModule import DCASEDataModule, AudioDatasetDCASE
 
 import pytorch_lightning as pl
-pl.utilities.seed.seed_everything(42, workers=True)
+pl.utilities.seed.seed_everything(0, workers=True)
 
 from callbacks.callbacks import MilestonesFinetuning
 
@@ -61,6 +61,7 @@ def compute(
         n_shot=3,
         n_query=2,
         n_subsample=cfg["data"]["n_subsample"],
+        n_task_train=cfg["data"]["n_task_train"]
     )
     label_dic = custom_dcasedatamodule.get_label_dic()
     pos_index = label_dic["POS"]
@@ -162,22 +163,20 @@ def compute(
         df_extension_pos["category"] = "POS"
 
         # # Detect NEG samples
-        # detected_neg_indices = np.where(p_values_pos == 0)[0]
+        df_neg = df_support[df_support["category"] == "NEG"]
+        num_pos_samples = len(detected_pos_indices)
 
-        # # Randomly sample NEG samples to match the number of POS samples
-        # num_pos_samples = len(detected_pos_indices)
-
-        # if num_pos_samples > 0 and len(detected_neg_indices) > num_pos_samples:
-        #     sampled_neg_indices = np.random.choice(detected_neg_indices, size=num_pos_samples, replace=False)
-        # else:
-        #     sampled_neg_indices = detected_neg_indices
-
-        # df_extension_neg = df_query.iloc[sampled_neg_indices].copy()
-        # df_extension_neg["category"] = "NEG"
+        if num_pos_samples > 0 and len(df_neg) > num_pos_samples:
+            sampled_neg_indices = np.random.choice(range(0, len(df_neg)), size=num_pos_samples, replace=False)
+            df_extension_neg = df_query.iloc[sampled_neg_indices].copy()
+            df_extension_neg["category"] = "NEG"
+        else:
+            print(df_neg)
+            df_extension_neg = df_neg
 
         # Append both POS and NEG samples to the support set
-        # df_support_extended = df_support.append([df_extension_pos, df_extension_neg], ignore_index=True)
-        df_support_extended = df_support.append([df_extension_pos], ignore_index=True)
+        df_support_extended = df_support.append([df_extension_pos, df_extension_neg], ignore_index=True)
+
         ########################
         # RECALCULATE THE ECDF #
         ########################