add parameter ranges to all representations

Author: christinadionysio

src/main/python/systemds/scuro/representations/timeseries_representations.py

@@ -184,7 +184,7 @@ def compute_feature(self, signal):
 @register_representation([ModalityType.TIMESERIES])
 class SpectralCentroid(TimeSeriesRepresentation):
     def __init__(self, fs=1.0):
-        super().__init__("SpectralCentroid", parameters={"fs": [1.0]})
+        super().__init__("SpectralCentroid", parameters={"fs": [0.5, 1.0, 2.0]})
         self.fs = fs
 
     def compute_feature(self, signal):
@@ -199,7 +199,8 @@ def compute_feature(self, signal):
 class BandpowerFFT(TimeSeriesRepresentation):
     def __init__(self, fs=1.0, f1=0.0, f2=0.5):
         super().__init__(
-            "BandpowerFFT", parameters={"fs": [1.0], "f1": [0.0], "f2": [0.5]}
+            "BandpowerFFT",
+            parameters={"fs": [0.5, 1.0], "f1": [0.0, 1.0], "f2": [0.5, 1.0]},
         )
         self.fs = fs
         self.f1 = f1

src/main/python/systemds/scuro/representations/vgg.py

@@ -53,14 +53,14 @@ def forward(self, input_: torch.Tensor) -> torch.Tensor:
         self.model.fc = Identity()
 
     def _get_parameters(self):
-        parameters = {"layer_name": []}
-
-        parameters["layer_name"] = [
-            "features.35",
-            "classifier.0",
-            "classifier.3",
-            "classifier.6",
-        ]
+        parameters = {
+            "layer_name": [
+                "features.35",
+                "classifier.0",
+                "classifier.3",
+                "classifier.6",
+            ]
+        }
 
         return parameters
 

src/main/python/systemds/scuro/representations/window_aggregation.py

@@ -171,7 +171,7 @@ def window_aggregate_nested_level(self, instance, new_length):
 class StaticWindow(Window):
     def __init__(self, aggregation_function="mean", num_windows=100):
         super().__init__("StaticWindow", aggregation_function)
-        self.parameters["num_windows"] = [num_windows]
+        self.parameters["num_windows"] = [10, num_windows]
         self.num_windows = int(num_windows)
 
     def execute(self, modality):
@@ -202,7 +202,7 @@ def execute(self, modality):
 class DynamicWindow(Window):
     def __init__(self, aggregation_function="mean", num_windows=100):
         super().__init__("DynamicWindow", aggregation_function)
-        self.parameters["num_windows"] = [num_windows]
+        self.parameters["num_windows"] = [10, num_windows]
         self.num_windows = int(num_windows)
 
     def execute(self, modality):