Fix remaining mambular references in docstrings and tests

ChrisW09 · ChrisW09 · commit 4f3b7a6132a5 · 2025-11-11T22:10:55.000+01:00
- Update all docstring examples in model files from mambular to deeptabular
- Update test_configs.py import paths
- All Python files now compile without syntax errors
diff --git a/deeptabular/models/autoint.py b/deeptabular/models/autoint.py
@@ -15,7 +15,7 @@ class and uses the AutoInt model with the default AutoInt
         configuration.
         """,
         examples="""
-        >>> from mambular.models import AutoIntRegressor
+        >>> from deeptabular.models import AutoIntRegressor
         >>> model = AutoIntRegressor(d_model=64, n_layers=8)
         >>> model.fit(X_train, y_train)
         >>> preds = model.predict(X_test)
@@ -33,7 +33,7 @@ class AutoIntClassifier(SklearnBaseClassifier):
         """AutoInt Classifier. This class extends the SklearnBaseClassifier class
         and uses the AutoInt model with the default AutoInt configuration.""",
         examples="""
-        >>> from mambular.models import AutoIntClassifier
+        >>> from deeptabular.models import AutoIntClassifier
         >>> model = AutoIntClassifier(d_model=64, n_layers=8)
         >>> model.fit(X_train, y_train)
         >>> preds = model.predict(X_test)
@@ -52,7 +52,7 @@ class AutoIntLSS(SklearnBaseLSS):
         This class extends the SklearnBaseLSS class and uses the
         AutoInt model with the default AutoInt configuration.""",
         examples="""
-        >>> from mambular.models import AutoIntLSS
+        >>> from deeptabular.models import AutoIntLSS
         >>> model = AutoIntLSS(d_model=64, n_layers=8)
         >>> model.fit(X_train, y_train, family="normal")
         >>> preds = model.predict(X_test)
diff --git a/deeptabular/models/enode.py b/deeptabular/models/enode.py
@@ -14,7 +14,7 @@ class ENODERegressor(SklearnBaseRegressor):
         with the default ENODE configuration.
         """,
         examples="""
-        >>> from mambular.models import ENODERegressor
+        >>> from deeptabular.models import ENODERegressor
         >>> model = ENODERegressor()
         >>> model.fit(X_train, y_train)
         >>> preds = model.predict(X_test)
@@ -35,7 +35,7 @@ class ENODEClassifier(SklearnBaseClassifier):
         with the default ENODE configuration.
         """,
         examples="""
-        >>> from mambular.models import ENODEClassifier
+        >>> from deeptabular.models import ENODEClassifier
         >>> model = ENODEClassifier()
         >>> model.fit(X_train, y_train)
         >>> preds = model.predict(X_test)
@@ -56,7 +56,7 @@ class ENODELSS(SklearnBaseLSS):
         with the default ENODE configuration.
         """,
         examples="""
-        >>> from mambular.models import ENODELSS
+        >>> from deeptabular.models import ENODELSS
         >>> model = ENODELSS()
         >>> model.fit(X_train, y_train, family='normal')
         >>> preds = model.predict(X_test)
diff --git a/deeptabular/models/fttransformer.py b/deeptabular/models/fttransformer.py
@@ -15,7 +15,7 @@ class and uses the FTTransformer model with the default FTTransformer
         configuration.
         """,
         examples="""
-        >>> from mambular.models import FTTransformerRegressor
+        >>> from deeptabular.models import FTTransformerRegressor
         >>> model = FTTransformerRegressor(d_model=64, n_layers=8)
         >>> model.fit(X_train, y_train)
         >>> preds = model.predict(X_test)
@@ -35,7 +35,7 @@ class FTTransformerClassifier(SklearnBaseClassifier):
         """FTTransformer Classifier. This class extends the SklearnBaseClassifier class
         and uses the FTTransformer model with the default FTTransformer configuration.""",
         examples="""
-        >>> from mambular.models import FTTransformerClassifier
+        >>> from deeptabular.models import FTTransformerClassifier
         >>> model = FTTransformerClassifier(d_model=64, n_layers=8)
         >>> model.fit(X_train, y_train)
         >>> preds = model.predict(X_test)
@@ -56,7 +56,7 @@ class FTTransformerLSS(SklearnBaseLSS):
         This class extends the SklearnBaseLSS class and uses the
         FTTransformer model with the default FTTransformer configuration.""",
         examples="""
-        >>> from mambular.models import FTTransformerLSS
+        >>> from deeptabular.models import FTTransformerLSS
         >>> model = FTTransformerLSS(d_model=64, n_layers=8)
         >>> model.fit(X_train, y_train, family="normal")
         >>> preds = model.predict(X_test)
diff --git a/deeptabular/models/mambattention.py b/deeptabular/models/mambattention.py
@@ -14,7 +14,7 @@ class MambAttentionRegressor(SklearnBaseRegressor):
         with the default MambAttention configuration.
         """,
         examples="""
-        >>> from mambular.models import MambAttentionRegressor
+        >>> from deeptabular.models import MambAttentionRegressor
         >>> model = MambAttentionRegressor(d_model=64, n_layers=8)
         >>> model.fit(X_train, y_train)
         >>> preds = model.predict(X_test)
diff --git a/deeptabular/models/mambular.py b/deeptabular/models/mambular.py
@@ -14,7 +14,7 @@ class MambularRegressor(SklearnBaseRegressor):
         with the default Mambular configuration.
         """,
         examples="""
-        >>> from mambular.models import MambularRegressor
+        >>> from deeptabular.models import MambularRegressor
         >>> model = MambularRegressor(d_model=64, n_layers=8)
         >>> model.fit(X_train, y_train)
         >>> preds = model.predict(X_test)
@@ -34,7 +34,7 @@ class MambularClassifier(SklearnBaseClassifier):
         with the default Mambular configuration.
         """,
         examples="""
-        >>> from mambular.models import MambularClassifier
+        >>> from deeptabular.models import MambularClassifier
         >>> model = MambularClassifier(d_model=64, n_layers=8)
         >>> model.fit(X_train, y_train)
         >>> preds = model.predict(X_test)
@@ -54,7 +54,7 @@ class MambularLSS(SklearnBaseLSS):
         with the default Mambular configuration.
         """,
         examples="""
-        >>> from mambular.models import MambularLSS
+        >>> from deeptabular.models import MambularLSS
         >>> model = MambularLSS(d_model=64, n_layers=8)
         >>> model.fit(X_train, y_train, family='normal')
         >>> preds = model.predict(X_test)
diff --git a/deeptabular/models/mlp.py b/deeptabular/models/mlp.py
@@ -14,7 +14,7 @@ class MLPRegressor(SklearnBaseRegressor):
         with the default MLP configuration.
         """,
         examples="""
-        >>> from mambular.models import MLPRegressor
+        >>> from deeptabular.models import MLPRegressor
         >>> model = MLPRegressor(d_model=64, n_layers=8)
         >>> model.fit(X_train, y_train)
         >>> preds = model.predict(X_test)
@@ -34,7 +34,7 @@ class MLPClassifier(SklearnBaseClassifier):
         with the default MLP configuration.
         """,
         examples="""
-        >>> from mambular.models import MLPClassifier
+        >>> from deeptabular.models import MLPClassifier
         >>> model = MLPClassifier(d_model=64, n_layers=8)
         >>> model.fit(X_train, y_train)
         >>> preds = model.predict(X_test)
@@ -54,7 +54,7 @@ class MLPLSS(SklearnBaseLSS):
         with the default MLP configuration.
         """,
         examples="""
-        >>> from mambular.models import MLPLSS
+        >>> from deeptabular.models import MLPLSS
         >>> model = MLPLSS(d_model=64, n_layers=8)
         >>> model.fit(X_train, y_train, family='normal')
         >>> preds = model.predict(X_test)
diff --git a/deeptabular/models/modern_nca.py b/deeptabular/models/modern_nca.py
@@ -14,7 +14,7 @@ class ModernNCARegressor(SklearnBaseRegressor):
         with the default ModernNCA configuration.
         """,
         examples="""
-        >>> from mambular.models import ModernNCARegressor
+        >>> from deeptabular.models import ModernNCARegressor
         >>> model = ModernNCARegressor(d_model=64, n_layers=8)
         >>> model.fit(X_train, y_train)
         >>> preds = model.predict(X_test)
@@ -34,7 +34,7 @@ class ModernNCAClassifier(SklearnBaseClassifier):
         with the default ModernNCA configuration.
         """,
         examples="""
-        >>> from mambular.models import ModernNCAClassifier
+        >>> from deeptabular.models import ModernNCAClassifier
         >>> model = ModernNCAClassifier(d_model=64, n_layers=8)
         >>> model.fit(X_train, y_train)
         >>> preds = model.predict(X_test)
@@ -54,7 +54,7 @@ class ModernNCALSS(SklearnBaseLSS):
         with the default ModernNCA configuration.
         """,
         examples="""
-        >>> from mambular.models import ModernNCALSS
+        >>> from deeptabular.models import ModernNCALSS
         >>> model = ModernNCALSS(d_model=64, n_layers=8)
         >>> model.fit(X_train, y_train, family='normal')
         >>> preds = model.predict(X_test)
diff --git a/deeptabular/models/node.py b/deeptabular/models/node.py
@@ -14,7 +14,7 @@ class NODERegressor(SklearnBaseRegressor):
         with the default NODE configuration.
         """,
         examples="""
-        >>> from mambular.models import NODERegressor
+        >>> from deeptabular.models import NODERegressor
         >>> model = NODERegressor()
         >>> model.fit(X_train, y_train)
         >>> preds = model.predict(X_test)
@@ -35,7 +35,7 @@ class NODEClassifier(SklearnBaseClassifier):
         with the default NODE configuration.
         """,
         examples="""
-        >>> from mambular.models import NODEClassifier
+        >>> from deeptabular.models import NODEClassifier
         >>> model = NODEClassifier()
         >>> model.fit(X_train, y_train)
         >>> preds = model.predict(X_test)
@@ -56,7 +56,7 @@ class NODELSS(SklearnBaseLSS):
         with the default NODE configuration.
         """,
         examples="""
-        >>> from mambular.models import NODELSS
+        >>> from deeptabular.models import NODELSS
         >>> model = NODELSS()
         >>> model.fit(X_train, y_train, family='normal')
         >>> preds = model.predict(X_test)
diff --git a/deeptabular/models/resnet.py b/deeptabular/models/resnet.py
@@ -14,7 +14,7 @@ class ResNetRegressor(SklearnBaseRegressor):
         with the default ResNet configuration.
         """,
         examples="""
-        >>> from mambular.models import ResNetRegressor
+        >>> from deeptabular.models import ResNetRegressor
         >>> model = ResNetRegressor()
         >>> model.fit(X_train, y_train)
         >>> preds = model.predict(X_test)
@@ -34,7 +34,7 @@ class ResNetClassifier(SklearnBaseClassifier):
         with the default ResNet configuration.
         """,
         examples="""
-        >>> from mambular.models import ResNetClassifier
+        >>> from deeptabular.models import ResNetClassifier
         >>> model = ResNetClassifier()
         >>> model.fit(X_train, y_train)
         >>> preds = model.predict(X_test)
@@ -54,7 +54,7 @@ class ResNetLSS(SklearnBaseLSS):
         with the default ResNet configuration.
         """,
         examples="""
-        >>> from mambular.models import ResNetLSS
+        >>> from deeptabular.models import ResNetLSS
         >>> model = ResNetLSS()
         >>> model.fit(X_train, y_train, family='normal')
         >>> preds = model.predict(X_test)
diff --git a/deeptabular/models/saint.py b/deeptabular/models/saint.py
@@ -15,7 +15,7 @@ class and uses the SAINT model with the default SAINT
         configuration.
         """,
         examples="""
-        >>> from mambular.models import SAINTRegressor
+        >>> from deeptabular.models import SAINTRegressor
         >>> model = SAINTRegressor(d_model=64, n_layers=8)
         >>> model.fit(X_train, y_train)
         >>> preds = model.predict(X_test)
@@ -33,7 +33,7 @@ class SAINTClassifier(SklearnBaseClassifier):
         """SAINT Classifier. This class extends the SklearnBaseClassifier class
         and uses the SAINT model with the default SAINT configuration.""",
         examples="""
-        >>> from mambular.models import SAINTClassifier
+        >>> from deeptabular.models import SAINTClassifier
         >>> model = SAINTClassifier(d_model=64, n_layers=8)
         >>> model.fit(X_train, y_train)
         >>> preds = model.predict(X_test)
@@ -52,7 +52,7 @@ class SAINTLSS(SklearnBaseLSS):
         This class extends the SklearnBaseLSS class and uses the
         SAINT model with the default SAINT configuration.""",
         examples="""
-        >>> from mambular.models import SAINTLSS
+        >>> from deeptabular.models import SAINTLSS
         >>> model = SAINTLSS(d_model=64, n_layers=8)
         >>> model.fit(X_train, y_train, family="normal")
         >>> preds = model.predict(X_test)
diff --git a/deeptabular/models/tabm.py b/deeptabular/models/tabm.py
@@ -14,7 +14,7 @@ class TabMRegressor(SklearnBaseRegressor):
         with the default TabM configuration.
         """,
         examples="""
-        >>> from mambular.models import TabMRegressor
+        >>> from deeptabular.models import TabMRegressor
         >>> model = TabMRegressor(ensemble_size=32, model_type='full')
         >>> model.fit(X_train, y_train)
         >>> preds = model.predict(X_test)
@@ -34,7 +34,7 @@ class TabMClassifier(SklearnBaseClassifier):
         with the default TabM configuration.
         """,
         examples="""
-        >>> from mambular.models import TabMClassifier
+        >>> from deeptabular.models import TabMClassifier
         >>> model = TabMClassifier(ensemble_size=32, model_type='full')
         >>> model.fit(X_train, y_train)
         >>> preds = model.predict(X_test)
@@ -54,7 +54,7 @@ class TabMLSS(SklearnBaseLSS):
         with the default TabM configuration.
         """,
         examples="""
-        >>> from mambular.models import TabMLSS
+        >>> from deeptabular.models import TabMLSS
         >>> model = TabMLSS(ensemble_size=32, model_type='full')
         >>> model.fit(X_train, y_train, family='normal')
         >>> preds = model.predict(X_test)
diff --git a/deeptabular/models/tabr.py b/deeptabular/models/tabr.py
@@ -14,7 +14,7 @@ class TabRRegressor(SklearnBaseRegressor):
         with the default TabR configuration.
         """,
         examples="""
-        >>> from mambular.models import TabRRegressor
+        >>> from deeptabular.models import TabRRegressor
         >>> model = TabRRegressor()
         >>> model.fit(X_train, y_train)
         >>> preds = model.predict(X_test)
@@ -33,7 +33,7 @@ class TabRClassifier(SklearnBaseClassifier):
         with the default TabR configuration.
         """,
         examples="""
-        >>> from mambular.models import TabRClassifier
+        >>> from deeptabular.models import TabRClassifier
         >>> model = TabRClassifier()
         >>> model.fit(X_train, y_train)
         >>> preds = model.predict(X_test)
@@ -52,7 +52,7 @@ class TabRLSS(SklearnBaseLSS):
         with the default TabR configuration.
         """,
         examples="""
-        >>> from mambular.models import TabRLSS
+        >>> from deeptabular.models import TabRLSS
         >>> model = TabRLSS(d_model=64, family='normal')
         >>> model.fit(X_train, y_train)
         >>> preds = model.predict(X_test)
diff --git a/deeptabular/models/tabtransformer.py b/deeptabular/models/tabtransformer.py
@@ -14,7 +14,7 @@ class TabTransformerRegressor(SklearnBaseRegressor):
         with the default TabTransformer configuration.
         """,
         examples="""
-        >>> from mambular.models import TabTransformerRegressor
+        >>> from deeptabular.models import TabTransformerRegressor
         >>> model = TabTransformerRegressor()
         >>> model.fit(X_train, y_train)
         >>> preds = model.predict(X_test)
@@ -36,7 +36,7 @@ class TabTransformerClassifier(SklearnBaseClassifier):
         with the default TabTransformer configuration.
         """,
         examples="""
-        >>> from mambular.models import TabTransformerClassifier
+        >>> from deeptabular.models import TabTransformerClassifier
         >>> model = TabTransformerClassifier()
         >>> model.fit(X_train, y_train)
         >>> preds = model.predict(X_test)
@@ -58,7 +58,7 @@ class TabTransformerLSS(SklearnBaseLSS):
         with the default TabTransformer configuration.
         """,
         examples="""
-        >>> from mambular.models import TabTransformerLSS
+        >>> from deeptabular.models import TabTransformerLSS
         >>> model = TabTransformerLSS()
         >>> model.fit(X_train, y_train, family='normal')
         >>> preds = model.predict(X_test)
diff --git a/deeptabular/models/tabularnn.py b/deeptabular/models/tabularnn.py
@@ -15,7 +15,7 @@ class and uses the TabulaRNN model with the default TabulaRNN
         configuration.
         """,
         examples="""
-        >>> from mambular.models import TabulaRNNRegressor
+        >>> from deeptabular.models import TabulaRNNRegressor
         >>> model = TabulaRNNRegressor(d_model=64)
         >>> model.fit(X_train, y_train)
         >>> preds = model.predict(X_test)
@@ -36,7 +36,7 @@ class and uses the TabulaRNN model with the default TabulaRNN
         configuration.
         """,
         examples="""
-        >>> from mambular.models import TabulaRNNClassifier
+        >>> from deeptabular.models import TabulaRNNClassifier
         >>> model = TabulaRNNClassifier(d_model=64)
         >>> model.fit(X_train, y_train)
         >>> preds = model.predict(X_test)
diff --git a/deeptabular/models/tangos.py b/deeptabular/models/tangos.py
@@ -14,7 +14,7 @@ class TangosRegressor(SklearnBaseRegressor):
         with the default Tangos configuration.
         """,
         examples="""
-        >>> from mambular.models import TangosRegressor
+        >>> from deeptabular.models import TangosRegressor
         >>> model = TangosRegressor(d_model=64, n_layers=8)
         >>> model.fit(X_train, y_train)
         >>> preds = model.predict(X_test)
@@ -34,7 +34,7 @@ class TangosClassifier(SklearnBaseClassifier):
         with the default Tangos configuration.
         """,
         examples="""
-        >>> from mambular.models import TangosClassifier
+        >>> from deeptabular.models import TangosClassifier
         >>> model = TangosClassifier(d_model=64, n_layers=8)
         >>> model.fit(X_train, y_train)
         >>> preds = model.predict(X_test)
@@ -54,7 +54,7 @@ class TangosLSS(SklearnBaseLSS):
         with the default Tangos configuration.
         """,
         examples="""
-        >>> from mambular.models import TangosLSS
+        >>> from deeptabular.models import TangosLSS
         >>> model = TangosLSS(d_model=64, n_layers=8)
         >>> model.fit(X_train, y_train, family='normal')
         >>> preds = model.predict(X_test)
diff --git a/deeptabular/models/trompt.py b/deeptabular/models/trompt.py
diff --git a/tests/test_configs.py b/tests/test_configs.py
