fix links to renamed files

Author: derrik-gratz

src/FHIL_python_utils/__init__.py

@@ -21,29 +21,29 @@
 
 # # Import functions from submodules
 # from .svm import (
-#     featureWeightHeatmap,
-#     classesFromProba,
-#     annotateClustersByConsensus,
-#     confusionBubbleMatrix
+#     feature_weight_heatmap,
+#     classes_from_probability_matrix,
+#     annotate_clusters_by_consensus,
+#     confusion_bubble_matrix
 # )
 
 # from .plotting import (
-#     confusionMatrix,
-#     anndataGridplot,
-#     rotateAxisLabels
+#     confusion_matrix_plot,
+#     anndata_gridplot,
+#     rotate_x_axis_labels
 # )
 
 # # Define what gets imported with "from FHIL_python_utils import *"
 # __all__ = [
 #     # SVM functions
-#     'featureWeightHeatmap',
-#     'classesFromProba', 
-#     'annotateClustersByConsensus',
-#     'confusionBubbleMatrix',
+#     'feature_weight_heatmap',
+#     'classes_from_probability_matrix', 
+#     'annotate_clusters_by_consensus',
+#     'confusion_bubble_matrix',
 #     # Plotting functions
-#     'confusionMatrix',
-#     'anndataGridplot',
-#     'rotateAxisLabels',
+#     'confusion_matrix_plot',
+#     'anndata_gridplot',
+#     'rotate_x_axis_labels',
 # ]
 
 from ._version import version as __version__

src/FHIL_python_utils/plotting/__init__.py

@@ -5,12 +5,12 @@
 for multiple AnnData objects, commonly used in spatial transcriptomics analysis.
 """
 
-from .confusionMatrix import confusionMatrix
-from .anndataGridplot import anndataGridplot
-from .rotateXAxisLabels import rotateAxisLabels
+from .confusion_matrix_plot import confusion_matrix_plot
+from .anndata_gridplot import anndata_gridplot
+from .rotate_x_axis_labels import rotate_x_axis_labels
 
 __all__ = [
-    'confusionMatrix',
-    'anndataGridplot',
-    'rotateAxisLabels'
+    'confusion_matrix_plot',
+    'anndata_gridplot',
+    'rotate_x_axis_labels'
 ]

src/FHIL_python_utils/plotting/confusion_matrix_plot.py

@@ -62,10 +62,10 @@ def confusion_matrix_plot(
     >>> pred_labels = ['A', 'B', 'A', 'B', 'B']
     >>> 
     >>> # Plot confusion matrix
-    >>> confusionMatrix(true_labels, pred_labels)   
+    >>> confusion_matrix_plot(true_labels, pred_labels)   
     >>> 
     >>> # Plot normalized confusion matrix
-    >>> confusionMatrix(true_labels, pred_labels, normalize=True)
+    >>> confusion_matrix_plot(true_labels, pred_labels, normalize=True)
     """
     # Convert inputs to categorical for consistent handling
     x_cat = pd.Categorical(x)

src/FHIL_python_utils/sc/__init__.py

@@ -2,10 +2,11 @@
 Utilities for single-cell analyses
 """
 
-from .nmadFilter import nmadFilter
-from .ridgePlot import ridgePlot
+from .nmad_filter import nmad_filter
+from .ridge_plot import ridge_plot
+from .daniel_processing import daniel_processing
 
 __all__ = [
-    'nmadFilter',
-    'ridgePlot'
+    'nmad_filter',
+    'ridge_plot'
 ]

…ython_utils/sc/daniel_processing_umap.py …HIL_python_utils/sc/daniel_processing.pysrc/FHIL_python_utils/sc/daniel_processing_umap.py renamed to src/FHIL_python_utils/sc/daniel_processing.py src/FHIL_python_utils/sc/daniel_processing_umap.py renamed to src/FHIL_python_utils/sc/daniel_processing.py

@@ -5,14 +5,14 @@
 and performing consensus-based cluster annotation.
 """
 
-from .featureWeightHeatmap import featureWeightHeatmap
-from .classesFromProba import classesFromProba
-from .annotateClustersByConsensus import annotateClustersByConsensus
-from .confusionBubbleMatrix import confusionBubbleMatrix
+from .feature_weight_heatmap import feature_weight_heatmap
+from .classes_from_probability_matrix import classes_from_probability_matrix
+from .annotate_clusters_by_consensus import annotate_clusters_by_consensus
+from .confusion_bubble_matrix import confusion_bubble_matrix
 
 __all__ = [
-    'featureWeightHeatmap',
-    'classesFromProba',
-    'annotateClustersByConsensus',
-    'confusionBubbleMatrix'
+    'feature_weight_heatmap',
+    'classes_from_probability_matrix',
+    'annotate_clusters_by_consensus',
+    'confusion_bubble_matrix'
 ]

src/FHIL_python_utils/svm/__init__.py

@@ -56,7 +56,7 @@ def feature_weight_heatmap(
     >>> model = {'svc': ovo_svm}
     >>> 
     >>> # Generate feature weight heatmap
-    >>> featureWeightingHeatmap(model, n=10)
+    >>> feature_weight_heatmap(model, n=10)
     """
     # Extract model components
     svc = model['svc']