Sc 41 optimize flowsom clustering (#82)

* SC_41_z_score

* SC_41 plot clusters

* SC_41 flowsom

* SC_41 flowsom clusering visualization

* SC_41 test flowsom

* SC_41 docs

* SC_41 update docstring

* SC_41 docs

* SC_41 docs

src/harpy/image/pixel_clustering/_clustering.py

@@ -59,7 +59,7 @@ def flowsom(
     sdata
         The input SpatialData object.
     img_layer
-        The image layer(s) of `sdata` on which flowsom is run. It is recommended to preprocess the data with `harpy.im.pixel_clustering_preprocess`.
+        The image layer(s) of `sdata` on which flowsom is run. It is recommended to preprocess the data with :func:`harpy.im.pixel_clustering_preprocess`.
     output_layer_clusters
         The output labels layer in `sdata` to which labels layer with predicted flowsom SOM clusters are saved.
     output_layer_metaclusters
@@ -107,7 +107,7 @@ def flowsom(
     Warnings
     --------
     - The function is intended for use with spatial proteomics data. Input data should be appropriately preprocessed
-      (e.g. via `harpy.im.pixel_clustering_preprocess`) to ensure meaningful clustering results.
+      (e.g. via :func:`harpy.im.pixel_clustering_preprocess`) to ensure meaningful clustering results.
     - The cluster and metacluster ID's found in `output_layer_clusters` and `output_layer_metaclusters` count from 1, while they count from 0 in the `FlowSOM` object.
     """
     assert 0 < fraction <= 1, "Value must be between 0 and 1"

src/harpy/plot/_flowsom.py

@@ -41,7 +41,7 @@ def pixel_clusters(
     **kwargs,  # passed to pl.show() of spatialdata_plot
 ):
     """
-    Visualize spatial distribution of pixel clusters based on labels in a `SpatialData` object, obtained using `harpy.im.flowsom`.
+    Visualize spatial distribution of pixel clusters based on labels in a `SpatialData` object, obtained using :func:`harpy.im.flowsom`.
 
     Parameters
     ----------
@@ -163,7 +163,7 @@ def pixel_clusters_heatmap(
     sdata
         The input SpatialData object.
     table_layer
-        The table layer in `sdata` containing cluster intensity for clusters and metaclusters, obtained via `hp.tb.cluster_intensity`.
+        The table layer in `sdata` containing cluster intensity for clusters and metaclusters, obtained via :func:`harpy.tb.cluster_intensity`.
     metaclusters
         Whether to display mean channel intensity per metacluster (`True`) or per cluster (`False`).
     z_score
@@ -172,13 +172,17 @@ def pixel_clusters_heatmap(
         The value to clip the z-scored data to, for better visualization. If `None`, no clipping is performed.
         Ignored if `z_score` is `False`.
     output
-        The path to save the generated heatmap. If `None`, the heatmap will be displayed directly using `plt.show()`.
+        The path to save the generated heatmap. If `None`, the heatmap will be displayed directly using :func:`matplotlib.pyplot.show`.
     figsize
-        Size of the figure in inches (width, height).
+        Tuple specifying the size of the figure in inches as `(width, height)`.
+        The width determines the spacing available for cluster IDs, while the height adjusts space for channels.
+        If labels (cluster IDs or channel names) are truncated, increase the respective dimension.
+        Increase `width` if cluster IDs or are not fully visible.
+        Increase `height` if channel names are not fully visible.
     fig_kwargs
-        Additional keyword arguments passed to `plt.figure`, such as `dpi`.
+        Additional keyword arguments passed to :func:`matplotlib.pyplot.figure`, such as `dpi`.
     **kwargs
-        Additional keyword arguments passed to `sns.heatmap`, such as `annot`, `cmap`, or `cbar_kws`.
+        Additional keyword arguments passed to :func:`seaborn.heatmap`, such as `annot`, `cmap`, or `cbar_kws`.
 
     Returns
     -------