bump up to v0.1.5 (corrected)

rsinghlab · Feb 8, 2024 · a1849ce · a1849ce
1 parent 7102709
commit a1849ce
Show file tree

Hide file tree

Showing 12 changed files with 223 additions and 8,345 deletions.
diff --git a/docs/source/tutorials/tutorial_atacseq.ipynb b/docs/source/tutorials/tutorial_atacseq.ipynb
diff --git a/docs/source/tutorials/tutorial_bloodchemistry.ipynb b/docs/source/tutorials/tutorial_bloodchemistry.ipynb
diff --git a/docs/source/tutorials/tutorial_dnam_illumina_human_array.ipynb b/docs/source/tutorials/tutorial_dnam_illumina_human_array.ipynb
diff --git a/docs/source/tutorials/tutorial_dnam_illumina_mammalian_array.ipynb b/docs/source/tutorials/tutorial_dnam_illumina_mammalian_array.ipynb
diff --git a/docs/source/tutorials/tutorial_dnam_rrbs.ipynb b/docs/source/tutorials/tutorial_dnam_rrbs.ipynb
diff --git a/docs/source/tutorials/tutorial_histonemarkchipseq.ipynb b/docs/source/tutorials/tutorial_histonemarkchipseq.ipynb
diff --git a/docs/source/tutorials/tutorial_rnaseq.ipynb b/docs/source/tutorials/tutorial_rnaseq.ipynb
diff --git a/docs/source/tutorials/tutorial_utils.ipynb b/docs/source/tutorials/tutorial_utils.ipynb
diff --git a/poetry.lock b/poetry.lock
diff --git a/pyaging/predict/_pred_utils.py b/pyaging/predict/_pred_utils.py
@@ -154,11 +154,13 @@ def check_features_in_adata(
     """
 
     # Preallocate the data matrix
-    X_model = np.empty((adata.n_obs, len(model.features)), order='F')
+    X_model = np.empty((adata.n_obs, len(model.features)), order="F")
 
     # Find indices of matching features in adata.var_names
     feature_indices = {feature: i for i, feature in enumerate(adata.var_names)}
-    model_feature_indices = np.array([feature_indices.get(feature, -1) for feature in model.features])
+    model_feature_indices = np.array(
+        [feature_indices.get(feature, -1) for feature in model.features]
+    )
 
     # Identify missing features
     missing_features_mask = model_feature_indices == -1
@@ -167,11 +169,15 @@ def check_features_in_adata(
     # Assign values for existing features
     existing_features_mask = ~missing_features_mask
     existing_features_indices = model_feature_indices[existing_features_mask]
-    X_model[:, existing_features_mask] = np.asfortranarray(adata.X)[:, existing_features_indices]
+    X_model[:, existing_features_mask] = np.asfortranarray(adata.X)[
+        :, existing_features_indices
+    ]
 
     # Handle missing features
     if model.reference_values is not None:
-        X_model[:, missing_features_mask] = np.array(model.reference_values)[missing_features_mask]
+        X_model[:, missing_features_mask] = np.array(model.reference_values)[
+            missing_features_mask
+        ]
     else:
         X_model[:, missing_features_mask] = 0
 

diff --git a/pyaging/preprocess/_preprocess_utils.py b/pyaging/preprocess/_preprocess_utils.py
@@ -79,12 +79,14 @@ def impute_missing_values(
             ),
             "knn": KNNImputer(),
         }
-    
+
         # Select the appropriate imputer
         imputer = imputers.get(strategy)
         if not imputer:
             raise ValueError(f"Invalid imputer strategy: {strategy}")
-        logger.info(f"Imputing missing values using {strategy} strategy", indent_level=2)
+        logger.info(
+            f"Imputing missing values using {strategy} strategy", indent_level=2
+        )
         adata.X = imputer.fit_transform(adata.X)
         adata.layers["X_imputed"] = adata.X