feat(Aggregate): Added Global Argmax - Contributes to #129

aucmedi/ensemble/aggregate/__init__.py

@@ -58,12 +58,15 @@
 from aucmedi.ensemble.aggregate.averaging_median import Averaging_Median
 from aucmedi.ensemble.aggregate.majority_vote import Majority_Vote
 from aucmedi.ensemble.aggregate.softmax import Softmax
+from aucmedi.ensemble.aggregate.global_argmax import Global_Argmax
 
 #-----------------------------------------------------#
 #       Access Functions to Aggregate Functions       #
 #-----------------------------------------------------#
 aggregate_dict = {"mean": Averaging_Mean,
                   "median": Averaging_Median,
                   "majority_vote": Majority_Vote,
-                  "softmax": Softmax}
+                  "softmax": Softmax,
+                  "global_argmax": Global_Argmax,
+}
 """ Dictionary of implemented Aggregate functions. """

aucmedi/ensemble/aggregate/global_argmax.py

@@ -0,0 +1,58 @@
+#==============================================================================#
+#  Author:       Dominik Müller                                                #
+#  Copyright:    2022 IT-Infrastructure for Translational Medical Research,    #
+#                University of Augsburg                                        #
+#                                                                              #
+#  This program is free software: you can redistribute it and/or modify        #
+#  it under the terms of the GNU General Public License as published by        #
+#  the Free Software Foundation, either version 3 of the License, or           #
+#  (at your option) any later version.                                         #
+#                                                                              #
+#  This program is distributed in the hope that it will be useful,             #
+#  but WITHOUT ANY WARRANTY; without even the implied warranty of              #
+#  MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the               #
+#  GNU General Public License for more details.                                #
+#                                                                              #
+#  You should have received a copy of the GNU General Public License           #
+#  along with this program.  If not, see <http://www.gnu.org/licenses/>.       #
+#==============================================================================#
+#-----------------------------------------------------#
+#                   Library imports                   #
+#-----------------------------------------------------#
+# External libraries
+import numpy as np
+# Internal libraries/scripts
+from aucmedi.ensemble.aggregate.agg_base import Aggregate_Base
+
+#-----------------------------------------------------#
+#               Aggregate: Global Argmax              #
+#-----------------------------------------------------#
+class Global_Argmax(Aggregate_Base):
+    """ Aggregate function based on Global Argmax.
+
+    This class should be passed to a ensemble function/class for combining predictions.
+    """
+    #---------------------------------------------#
+    #                Initialization               #
+    #---------------------------------------------#
+    def __init__(self):
+        # No hyperparameter adjustment required for this method, therefore skip
+        pass
+
+    #---------------------------------------------#
+    #                  Aggregate                  #
+    #---------------------------------------------#
+    def aggregate(self, preds):
+        # Identify global argmax
+        max = np.amax(preds)
+        argmax_flatten = np.argmax(preds)
+        argmax = np.unravel_index(argmax_flatten, preds.shape)[-1]
+
+        # Compute prediction by global argmax and equally distributed remaining
+        # probability for other classes
+        prob_remaining = np.divide(1-max, preds.shape[1]-1)
+        pred = np.full((preds.shape[1],), fill_value=prob_remaining)
+        pred[argmax] = max
+
+        # Return prediction
+        return pred