[pre-commit.ci] auto fixes from pre-commit.com hooks

pre-commit-ci[bot] · pre-commit-ci[bot] · commit 6af4cf6fa17d · 2025-09-22T19:44:07.000Z
for more information, see https://pre-commit.ci
diff --git a/docs/.ipynb_checkpoints/index-checkpoint.md b/docs/.ipynb_checkpoints/index-checkpoint.md
@@ -11,6 +11,7 @@ Tools <api/tools.md>
 Plotting  <api/plotting.md>
 
 ```
+
 ```{toctree}
 :maxdepth: 1
 :caption: Tutorials
@@ -26,4 +27,4 @@ changelog.md
 contributing.md
 references.md
 
-```
+```
diff --git a/docs/api/.ipynb_checkpoints/plotting-checkpoint.md b/docs/api/.ipynb_checkpoints/plotting-checkpoint.md
@@ -8,7 +8,7 @@
 
 .. autosummary::
     :toctree: generated/basic_plots
-    
+
     crosstab
     histogram
     pie
@@ -23,7 +23,7 @@
 ```{eval-rst}
 .. autosummary::
     :toctree: generated/quantification
-    
+
     gene_metric_heatmap
     logfoldratio_over_noise
     metric_scatter
@@ -33,18 +33,15 @@
     moranI_histogram
     diffusion_results
     spatial_inout_expression
-    
-```
-
-
 
+```
 
 ## Source, target and communication
 
 ```{eval-rst}
 .. autosummary::
     :toctree: generated/communication
-    
+
     celltype_communication
     gene_communication
     global_distribution_from_source
@@ -54,25 +51,24 @@
     target_score_by_celltype
     interactions_with_arrows
     spatial_interactions
-    
+
 ```
 
 ## Factor analysis
 
 ```{eval-rst}
 .. autosummary::
     :toctree: generated/factor_analysis
-    
+
     factors_in_cells
     rank_factor_genes_loadings
     rank_factor_genes_loadings_matrixplot
     nmf_factors_exrna_cells_W
     nmf_gene_contributions
     paired_nmf_factors
     apply_exrnaH_to_cellular_to_create_cellularW
- 
-```
 
+```
 
 ## Colormaps & palettes
 
@@ -83,6 +79,3 @@
     get_colormap
     get_palette
 ```
-
-
-
diff --git a/docs/api/.ipynb_checkpoints/preprocessing-checkpoint.md b/docs/api/.ipynb_checkpoints/preprocessing-checkpoint.md
@@ -15,3 +15,4 @@
     pp.define_urna
     pp.filter_urna
     pp.format_adata
+```
diff --git a/docs/api/.ipynb_checkpoints/tools-checkpoint.md b/docs/api/.ipynb_checkpoints/tools-checkpoint.md
@@ -35,7 +35,7 @@
     tl.calculate_target_cells
     tl.compute_target_score
     tl.define_target_by_celltype
-    tl.cluster_distribution_from_source 
+    tl.cluster_distribution_from_source
     tl.get_gene_interaction_strength
     tl.communication_strength
     tl.gene_specific_interactions
@@ -46,7 +46,7 @@
 ```{eval-rst}
 .. autosummary::
     :toctree: generated/cell_scores
-    
+
     tl.compute_contribution_score
 ```
 
@@ -55,7 +55,7 @@
 ```{eval-rst}
 .. autosummary::
     :toctree: generated/factors
-    
+
     tl.factors_to_cells
     tl.latent_factor
 ```
@@ -68,15 +68,14 @@
 
     tl.assess_diffusion
     tl.compute_js_divergence
-    
+
 ```
 
 ## Multimodal quantication
 
 ```{eval-rst}
 .. autosummary::
     :toctree: generated/multimodal
-    
+
     tl.image_intensities_per_transcript
 ```
-
diff --git a/docs/api/plotting.md b/docs/api/plotting.md
@@ -8,7 +8,7 @@
 
 .. autosummary::
     :toctree: generated/basic_plots
-    
+
     crosstab
     histogram
     pie
@@ -23,7 +23,7 @@
 ```{eval-rst}
 .. autosummary::
     :toctree: generated/quantification
-    
+
     gene_metric_heatmap
     logfoldratio_over_noise
     metric_scatter
@@ -33,18 +33,15 @@
     moranI_histogram
     diffusion_results
     spatial_inout_expression
-    
-```
-
-
 
+```
 
 ## Source, target and communication
 
 ```{eval-rst}
 .. autosummary::
     :toctree: generated/communication
-    
+
     celltype_communication
     gene_communication
     global_distribution_from_source
@@ -54,25 +51,24 @@
     target_score_by_celltype
     interactions_with_arrows
     spatial_interactions
-    
+
 ```
 
 ## Factor analysis
 
 ```{eval-rst}
 .. autosummary::
     :toctree: generated/factor_analysis
-    
+
     factors_in_cells
     rank_factor_genes_loadings
     rank_factor_genes_loadings_matrixplot
     nmf_factors_exrna_cells_W
     nmf_gene_contributions
     paired_nmf_factors
     apply_exrnaH_to_cellular_to_create_cellularW
- 
-```
 
+```
 
 ## Colormaps & palettes
 
@@ -83,6 +79,3 @@
     get_colormap
     get_palette
 ```
-
-
-
diff --git a/docs/api/preprocessing.md b/docs/api/preprocessing.md
@@ -15,3 +15,4 @@
     pp.define_urna
     pp.filter_urna
     pp.format_adata
+```
diff --git a/docs/api/tools.md b/docs/api/tools.md
@@ -35,7 +35,7 @@
     tl.calculate_target_cells
     tl.compute_target_score
     tl.define_target_by_celltype
-    tl.cluster_distribution_from_source 
+    tl.cluster_distribution_from_source
     tl.get_gene_interaction_strength
     tl.communication_strength
     tl.gene_specific_interactions
@@ -46,7 +46,7 @@
 ```{eval-rst}
 .. autosummary::
     :toctree: generated/cell_scores
-    
+
     tl.compute_contribution_score
 ```
 
@@ -55,7 +55,7 @@
 ```{eval-rst}
 .. autosummary::
     :toctree: generated/factors
-    
+
     tl.factors_to_cells
     tl.latent_factor
 ```
@@ -68,15 +68,14 @@
 
     tl.assess_diffusion
     tl.compute_js_divergence
-    
+
 ```
 
 ## Multimodal quantication
 
 ```{eval-rst}
 .. autosummary::
     :toctree: generated/multimodal
-    
+
     tl.image_intensities_per_transcript
 ```
-
diff --git a/docs/index.md b/docs/index.md
@@ -11,6 +11,7 @@ Tools <api/tools.md>
 Plotting  <api/plotting.md>
 
 ```
+
 ```{toctree}
 :maxdepth: 1
 :caption: Tutorials
@@ -26,4 +27,4 @@ changelog.md
 contributing.md
 references.md
 
-```
+```
diff --git a/src/troutpy/pl/communication.py b/src/troutpy/pl/communication.py
@@ -7,16 +7,7 @@
 from spatialdata import SpatialData
 
 
-def celltype_communication(
-    sdata,
-    kind="heatmap",
-    celltype_key="cell type",
-    vmax=None,
-    vmin=None,
-    cmap="BuPu",
-    dendrogram_ratio=0.1,
-    **kwargs
-):
+def celltype_communication(sdata, kind="heatmap", celltype_key="cell type", vmax=None, vmin=None, cmap="BuPu", dendrogram_ratio=0.1, **kwargs):
     """Plot cell type-cell type interaction strength as a heatmap or chord diagram."""
     interaction_strength = sdata["source_score"].uns["interaction_strength"]
     source_table = sdata["source_score"]
@@ -28,10 +19,7 @@ def celltype_communication(
 
     # Assign colors to cell types
     try:
-        cols = dict(zip(
-            np.unique(sdata["table"].obs[celltype_key]),
-            sdata["table"].uns[celltype_key + "_colors"], strict=False
-        ))
+        cols = dict(zip(np.unique(sdata["table"].obs[celltype_key]), sdata["table"].uns[celltype_key + "_colors"], strict=False))
         colors = [cols[c] for c in source_table.var.index]
     except KeyError:
         colpalette = plt.get_cmap("tab20")
@@ -48,20 +36,13 @@ def celltype_communication(
             col_colors=colors,
             dendrogram_ratio=dendrogram_ratio,
             cbar_pos=(0.02, 0.8, 0.02, 0.15),  # Adjust colorbar position: (x, y, width, height)
-            **kwargs
+            **kwargs,
         )
         g.fig.suptitle("Interaction Strength", y=1.05)
         g.ax_heatmap.grid(False)  # remove grid from heatmap
 
     elif kind == "chord":
-        chord_diagram(
-            celltype_ints,
-            source_table.var.index,
-            directed=True,
-            fontsize=6,
-            colors=colors,
-            **kwargs
-        )
+        chord_diagram(celltype_ints, source_table.var.index, directed=True, fontsize=6, colors=colors, **kwargs)
         plt.title("Interaction Strength", fontweight="bold")
         plt.grid(False)
 
diff --git a/src/troutpy/tl/.ipynb_checkpoints/quantify_urna-checkpoint.py b/src/troutpy/tl/.ipynb_checkpoints/quantify_urna-checkpoint.py
@@ -51,7 +51,7 @@ def spatial_variability(
     -------
     sdata: spatialdata.SpatialData
         Sdata containing Moran's I values for each gene, indexed by gene names.
-      
+
     """
     if coord_keys is None:
         coord_keys = ["x", "y"]
diff --git a/src/troutpy/tl/.ipynb_checkpoints/source_cell-checkpoint.py b/src/troutpy/tl/.ipynb_checkpoints/source_cell-checkpoint.py
@@ -458,7 +458,7 @@ def store_results_in_sdata(sdata, prob_table, closest_table, extracellular_trans
         sdata["table"].obs['normalized_urna_source_score'] = adata.obs['urna_source_score'] / cell_expr_sum
     except KeyError:
         print('Normalized urna source score could not be computed')
-    
+
 
 
 def compute_contribution_score(sdata):
diff --git a/src/troutpy/tl/factor_analysis.py b/src/troutpy/tl/factor_analysis.py
@@ -139,6 +139,7 @@ def latent_factor(
     sdata[layer] = adata
     return sdata if copy else None
 
+
 def combine_loadings_arrays(gene_loadings_pos: np.ndarray, gene_loadings_neg: np.ndarray) -> np.ndarray:
     """Combines positive and negative gene loading arrays from DRVI analysis"""
     if gene_loadings_pos.shape != gene_loadings_neg.shape:
@@ -152,8 +153,7 @@ def combine_loadings_arrays(gene_loadings_pos: np.ndarray, gene_loadings_neg: np
     # Raise warning if conflicts found
     if np.any(conflict_mask):
         conflict_indices = np.argwhere(conflict_mask)
-        warnings.warn(f"Conflicts found at {len(conflict_indices)} locations. "
-        f"Example: {conflict_indices[:5].tolist()}",stacklevel=2)
+        warnings.warn(f"Conflicts found at {len(conflict_indices)} locations. Example: {conflict_indices[:5].tolist()}", stacklevel=2)
 
     # Initialize combined output
     combined = np.zeros_like(gene_loadings_pos)
@@ -163,7 +163,6 @@ def combine_loadings_arrays(gene_loadings_pos: np.ndarray, gene_loadings_neg: np
     return combined
 
 
-
 def factors_to_cells(
     sdata: SpatialData, extracellular_layer: str = "segmentation_free_table", cellular_layer: str = "table", copy: bool | None = None
 ) -> SpatialData:
diff --git a/src/troutpy/tl/source_cell.py b/src/troutpy/tl/source_cell.py
diff --git a/src/troutpy/tl/target_cell.py b/src/troutpy/tl/target_cell.py
