BUG: Fixing after breaking regressor name refactor (#88)

* initial commit, implemented

* fixed the follow up bug on gui init

aydin/gui/tabs/qt/denoise.py

@@ -76,7 +76,7 @@ def __init__(self, parent):
             'Noise2SelfCNN-jinet',
             'Noise2SelfFGR-cb',
             'Noise2SelfFGR-lgbm',
-            'Noise2SelfFGR-rf',
+            'Noise2SelfFGR-random_forest',
         ]
 
         self.basic_backend_options_descriptions = []
@@ -136,16 +136,15 @@ def set_advanced_enabled(self, enable: bool = False):
         while self.stacked_widget.count():
             self.stacked_widget.removeWidget(self.stacked_widget.widget(0))
 
-        for index, backend_option in enumerate(
-            self.backend_options if enable else self.basic_backend_options
-        ):
-            self.leftlist.insertItem(index, backend_option)
+        if enable:
+            options = self.backend_options
+            description_list = self.backend_options_descriptions
+        else:
+            options = self.basic_backend_options
+            description_list = self.basic_backend_options_descriptions
 
-            description_list = (
-                self.backend_options_descriptions
-                if enable
-                else self.basic_backend_options_descriptions
-            )
+        for index, backend_option in enumerate(options):
+            self.leftlist.insertItem(index, backend_option)
 
             self.stacked_widget.addWidget(
                 DenoiseTabMethodWidget(

aydin/it/demo/n2s/rf/2D_generic.py

@@ -10,7 +10,7 @@
 from aydin.features.standard_features import StandardFeatureGenerator
 from aydin.io.datasets import normalise, add_noise, pollen, newyork, lizard, characters
 from aydin.it.fgr import ImageTranslatorFGR
-from aydin.regression.rf import RFRegressor
+from aydin.regression.random_forest import RandomForestRegressor
 from aydin.util.log.log import Log
 
 
@@ -26,7 +26,7 @@ def demo(image, name):
 
     generator = StandardFeatureGenerator()
 
-    regressor = RFRegressor(patience=32)
+    regressor = RandomForestRegressor(patience=32)
 
     it = ImageTranslatorFGR(feature_generator=generator, regressor=regressor)
 

aydin/it/test/test_fgr.py

@@ -13,8 +13,8 @@
 from aydin.regression.lgbm import LGBMRegressor
 from aydin.regression.linear import LinearRegressor
 from aydin.regression.nn import NNRegressor
-from aydin.regression.rf import RFRegressor
-from aydin.regression.sv import SVRegressor
+from aydin.regression.random_forest import RandomForestRegressor
+from aydin.regression.support_vector import SupportVectorRegressor
 
 
 @pytest.mark.heavy
@@ -24,13 +24,13 @@ def test_it_fgr_linear():
 
 
 def test_it_fgr_rf():
-    regressor = RFRegressor(max_num_estimators=128)
+    regressor = RandomForestRegressor(max_num_estimators=128)
     do_it_fgr_with_self_supervised(regressor, min_ssim=0.75)
 
 
 @pytest.mark.heavy
 def test_it_fgr_svr():
-    regressor = SVRegressor()
+    regressor = SupportVectorRegressor()
     do_it_fgr_with_self_supervised(regressor, min_psnr=22, min_ssim=0.71)
 
 

aydin/it/test/test_fgr_saveload.py

@@ -16,8 +16,8 @@
 from aydin.regression.lgbm import LGBMRegressor
 from aydin.regression.linear import LinearRegressor
 from aydin.regression.nn import NNRegressor
-from aydin.regression.rf import RFRegressor
-from aydin.regression.sv import SVRegressor
+from aydin.regression.random_forest import RandomForestRegressor
+from aydin.regression.support_vector import SupportVectorRegressor
 
 
 @pytest.mark.heavy
@@ -28,13 +28,13 @@ def test_saveload_Linear():
 
 @pytest.mark.heavy
 def test_saveload_RF():
-    regressor = RFRegressor()
+    regressor = RandomForestRegressor()
     saveload(StandardFeatureGenerator(), regressor, min_ssim=0.75)
 
 
 @pytest.mark.heavy
 def test_saveload_SVR():
-    regressor = SVRegressor()
+    regressor = SupportVectorRegressor()
     saveload(StandardFeatureGenerator(), regressor, min_psnr=22, min_ssim=0.71)
 
 

aydin/regression/rf.py → aydin/regression/random_forest.py

@@ -4,7 +4,7 @@
 from aydin.util.log.log import lsection, lprint
 
 
-class RFRegressor(LGBMRegressor):
+class RandomForestRegressor(LGBMRegressor):
     """Random Forrest Regressor (uses the LGBM library)."""
 
     def __init__(

aydin/regression/sv.py → aydin/regression/support_vector.py

@@ -4,7 +4,7 @@
 from aydin.util.log.log import lprint, lsection
 
 
-class SVRegressor(RegressorBase):
+class SupportVectorRegressor(RegressorBase):
     """Support Vector Regressor.
     \n\n
     Note: Way too slow when non-linear, nearly useless...

aydin/regression/test/deprecated_test_saveload.py

@@ -14,20 +14,20 @@
 from aydin.regression.lgbm import LGBMRegressor
 from aydin.regression.linear import LinearRegressor
 from aydin.regression.nn import NNRegressor
-from aydin.regression.rf import RFRegressor
-from aydin.regression.sv import SVRegressor
+from aydin.regression.random_forest import RandomForestRegressor
+from aydin.regression.support_vector import SupportVectorRegressor
 
 
 def test_linear_saveload():
     saveload(LinearRegressor(), min_ssim=0.70)
 
 
 def test_rf_saveload():
-    saveload(RFRegressor(), min_ssim=0.70)
+    saveload(RandomForestRegressor(), min_ssim=0.70)
 
 
 def test_svr_saveload():
-    saveload(SVRegressor(), min_ssim=0.70)
+    saveload(SupportVectorRegressor(), min_ssim=0.70)
 
 
 def test_gbm_saveload():

aydin/regression/test/test_regressors.py

@@ -13,8 +13,8 @@
 from aydin.regression.lgbm import LGBMRegressor
 from aydin.regression.linear import LinearRegressor
 from aydin.regression.nn import NNRegressor
-from aydin.regression.rf import RFRegressor
-from aydin.regression.sv import SVRegressor
+from aydin.regression.random_forest import RandomForestRegressor
+from aydin.regression.support_vector import SupportVectorRegressor
 
 
 def test_linear_regressor():
@@ -23,12 +23,12 @@ def test_linear_regressor():
 
 
 def test_rf_regressor():
-    regressor = RFRegressor()
+    regressor = RandomForestRegressor()
     with_regressor(regressor, min_ssim=0.6)
 
 
 def test_svr_regressor():
-    regressor = SVRegressor()
+    regressor = SupportVectorRegressor()
     with_regressor(regressor, min_ssim=0.65)
 
 

aydin/restoration/denoise/noise2selffgr.py

@@ -20,8 +20,8 @@
     from aydin.regression.lgbm import LGBMRegressor  # noqa: F401
     from aydin.regression.linear import LinearRegressor  # noqa: F401
     from aydin.regression.nn import NNRegressor  # noqa: F401
-    from aydin.regression.rf import RFRegressor  # noqa: F401
-    from aydin.regression.sv import SVRegressor  # noqa: F401
+    from aydin.regression.random_forest import RandomForestRegressor  # noqa: F401
+    from aydin.regression.support_vector import SupportVectorRegressor  # noqa: F401
 
 
 class Noise2SelfFGR(DenoiseRestorationBase):