minor bug fix

novosparc/__init__.py

@@ -10,7 +10,7 @@
     '[email protected]',
     '[email protected]'
 ])
-__version__ = '0.4.3'
+__version__ = '0.4.4'
 
 from . import plotting as pl
 from . import preprocessing as pp

novosparc/geometry/_geometry.py

@@ -116,7 +116,7 @@ def create_target_space_from_image(image):
     img_height = img.shape[0]
 
     locations = np.array([(x, y) for x in range(img_width) for y in range(img_height)
-                          if sum(img[y, x, :] == np.array([0, 0, 0]))])
+                          if sum(img[y, x, :] == np.array(img.shape[2]))])
 
     return locations
 

novosparc/reconstruction/_reconstruction.py

@@ -73,7 +73,24 @@ def write_sdge_to_disk(sdge, num_cells, num_locations, folder):
     np.savetxt(os.path.join(folder, 'sdge_' + str(num_cells) + '_cells_'
                + str(num_locations) + '_locations.txt'), sdge, fmt='%.4e')
     print ('done (', round(time.time()-start_time, 2), 'seconds )')
-
+
+
+def quantify_clusters_spatially(tissue):
+    """Maps the annotated clusters obtained from the scRNA-seq analysis onto
+    the tissue space.
+
+    Args:
+        tissue: the novosparc tissue object containing the gene expression data,
+                the clusters annotation and the spatial reconstruction. Assumes
+                that the cluster annotation exists in the underlying anndata object.
+
+    Returns:
+        [numpy array]: An array of the cluster annotation per tissue position.
+    """
+    clusters = tissue.dataset.obs['clusters'].to_numpy().flatten()
+    return np.array([np.argmax(np.array([np.median(np.array(tissue.gw[:, location][np.argwhere(clusters == cluster).flatten()]))
+                                         for cluster in np.unique(clusters)])) for location in range(len(tissue.locations))])
+
 
 def find_spatial_archetypes(num_clusters, sdge):
     """Clusters the expression data and finds gene archetypes. Current