do some updates for fixing bugs and add new features.

requirements.txt

@@ -28,7 +28,7 @@ param==1.12.2
 hvplot==0.7.3
 colorcet==2.0.6
 datashader>=0.13.0,<=0.14.1rc1
-anndata==0.7.5
+anndata>=0.7.5
 phenograph==1.5.7
 requests>=2.31.0
 urllib3==1.26.9

stereo/algorithm/ccd/community_clustering_algorithm.py

@@ -234,6 +234,10 @@ def plot_clustering(self):
         labels = np.unique(self.adata.obs[f'tissue_{self.method_key}'].values)
         if 'unknown' in labels:
             labels = labels[labels != 'unknown']
+        if len(labels) > len(self.cluster_palette):
+            logger.warning(f"Number of clusters ({len(labels)}) is larger than pallette size. All clusters will be colored gray.")
+            self.cluster_palette = {l: '#CCCCCC' for l in labels}
+            self.cluster_palette['unknown'] = '#CCCCCC'
         plot_spatial(self.adata, annotation=f'tissue_{self.method_key}', palette=self.cluster_palette,
                      spot_size=self.spot_size, ax=ax, title=f'{self.adata.uns["sample_name"]}')
         handles, labels = ax.get_legend_handles_labels()

stereo/algorithm/community_detection.py

@@ -259,11 +259,11 @@ def _main(self, slices, annotation="annotation", **kwargs):
                     try:
                         algo.plot_stats()
                     except Exception as e:
-                        print('plot_stats raise exception while running multi slice, err=%s', str(e))
+                        print('plot_stats raise exception while running multi slice, err=%s' % str(e))
                     try:
                         algo.plot_celltype_table()
                     except Exception as e:
-                        print('plot_celltype_table raise exception while running multi slice, err=%s', str(e))
+                        print('plot_celltype_table raise exception while running multi slice, err=%s' % str(e))
                 if self.params['plotting'] > 2:
                     algo.plot_cluster_mixtures()
                     algo.boxplot_stats()
@@ -442,6 +442,9 @@ def plot_all_slices(self, img_name, clustering=False):
         for (algo, ax) in zip(self.algo_list, axes.flatten()):
             palette = algo.cluster_palette if clustering else algo.annotation_palette
             annotation = f'tissue_{self.algo_list[0].method_key}' if clustering else self.algo_list[0].annotation
+            clusters = np.unique(algo.adata.obs[annotation].values)
+            if len(clusters) > len(cluster_palette):
+                logger.warning(f"Number of clusters ({len(clusters)}) is larger than pallette size. All clusters will be colored gray.")
             plot_spatial(algo.adata, annotation=annotation, palette=palette, spot_size=algo.spot_size, ax=ax)
             ax.get_legend().remove()
             ax.set_title(f'{algo.filename}', fontsize=6, loc='center', wrap=True)

stereo/core/ms_pipeline.py

@@ -1,3 +1,4 @@
+import os
 from joblib import (
     Parallel,
     delayed,
@@ -6,7 +7,7 @@
 
 from stereo import logger
 from stereo.core import StPipeline
-from stereo.plots.decorator import download
+from stereo.plots.decorator import download, download_only
 
 
 class _scope_slice(object):
@@ -161,6 +162,11 @@ def _run_isolated_method(self, item, *args, **kwargs):
         if new_attr:
             def log_delayed_task(idx, *arg, **kwargs):
                 logger.info(f'data_obj(idx={idx}) in ms_data start to run {item}')
+                if self.__class__.ATTR_NAME == 'plt':
+                    out_path = kwargs.get('out_path', None)
+                    if out_path is not None:
+                        path_name, ext = os.path.splitext(out_path)
+                        kwargs['out_path'] = f'{path_name}_{idx}{ext}'
                 new_attr(*arg, **kwargs)
 
             Parallel(n_jobs=n_jobs, backend='threading', verbose=100)(
@@ -178,6 +184,12 @@ def log_delayed_task(idx, *arg, **kwargs):
             def log_delayed_task(idx, obj, *arg, **kwargs):
                 logger.info(f'data_obj(idx={idx}) in ms_data start to run {item}')
                 new_attr = base.get_attribute_helper(item, obj, obj.tl.result)
+                if base == PlotBase:
+                    out_path = kwargs.get('out_path', None)
+                    if out_path is not None:
+                        path_name, ext = os.path.splitext(out_path)
+                        kwargs['out_path'] = f'{path_name}_{idx}{ext}'
+                    new_attr = download_only(new_attr)
                 if new_attr:
                     new_attr(*arg, **kwargs)
                 else:

stereo/core/st_pipeline.py

@@ -1321,6 +1321,8 @@ def annotation(
         #     df.group.cat.categories = new_annotation_list
 
         cluster_res: pd.DataFrame = self.result[cluster_res_key]
+        if cluster_res['group'].dtype.name != 'category':
+            cluster_res['group'] = cluster_res['group'].astype('category')
 
         if isinstance(annotation_information, (list, np.ndarray)) and \
                 len(annotation_information) != cluster_res['group'].cat.categories.size:
@@ -1333,7 +1335,10 @@ def annotation(
         elif isinstance(annotation_information, dict):
             new_categories_list = []
             for i in cluster_res['group'].cat.categories:
-                new_categories_list.append(annotation_information[i])
+                if i in annotation_information:
+                    new_categories_list.append(annotation_information[i])
+                else:
+                    new_categories_list.append(i)
             new_categories = np.array(new_categories_list, dtype='U')
         else:
             raise TypeError("The type of 'annotation_information' only supports list, ndarray or dict.")

stereo/io/reader.py

@@ -942,7 +942,7 @@ def stereo_to_anndata(
 
     if output is not None:
         adata.write_h5ad(output)
-        logger.info("Finished output to {output}")
+        logger.info(f"Finished output to {output}")
 
     return adata
 

stereo/plots/decorator.py

@@ -83,6 +83,24 @@ def _action(_, figure: Figure):
 
     return wrapped
 
+def download_only(func):
+    @wraps(func)
+    def wrapped(*args, **kwargs):
+        out_path = None
+        dpi = 100
+        if 'out_path' in kwargs:
+            out_path = kwargs['out_path']
+            del kwargs['out_path']
+        if 'out_dpi' in kwargs:
+            dpi = kwargs['out_dpi']
+            del kwargs['out_dpi']
+        fig: Figure = func(*args, **kwargs)
+        if type(fig) is Figure and out_path is not None:
+            fig.savefig(out_path, bbox_inches='tight', dpi=dpi)
+        return fig
+
+    return wrapped
+
 
 def reorganize_coordinate(func):
     @wraps(func)