Connectivity for n2s

flatironinstitute · May 22, 2023 · b2d61f5 · b2d61f5
1 parent be63dab
commit b2d61f5
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Showing 7 changed files with 19 additions and 10 deletions.
diff --git a/inferelator_velocity/program_graph.py b/inferelator_velocity/program_graph.py
@@ -21,6 +21,7 @@ def global_graph(
     neighbors=None,
     npcs=None,
     use_sparse=True,
+    connectivity=False,
     verbose=False
 ):
     """
@@ -40,6 +41,9 @@ def global_graph(
         Will densify a sparse expression matrix (faster, more memory) if False,
         defaults to True
     :type use_sparse: bool
+    :param connectivity: Use a connectivity graph instead of a distance graph,
+        defaults to False
+    :type connectivity: bool, optional
     :param verbose: Print detailed status, defaults to False
     :type verbose: bool, optional
     :return: AnnData object with `noise2self` obps and uns key
@@ -58,7 +62,8 @@ def global_graph(
         neighbors=neighbors,
         npcs=npcs,
         verbose=verbose,
-        use_sparse=use_sparse
+        use_sparse=use_sparse,
+        connectivity=connectivity
     )
 
     vprint(
@@ -83,6 +88,7 @@ def program_graphs(
     neighbors=None,
     npcs=None,
     use_sparse=True,
+    connectivity=False,
     verbose=False
 ):
     """
@@ -106,7 +112,10 @@ def program_graphs(
     :param use_sparse: Use sparse data structures (slower).
         Will densify a sparse expression matrix (faster, more memory) if False,
         defaults to True
-    :type use_sparse: bool
+    :type use_sparse: bool, optional
+    :param connectivity: Use a connectivity graph instead of a distance graph,
+        defaults to False
+    :type connectivity: bool, optional
     :param verbose: Print detailed status, defaults to False
     :type verbose: bool, optional
     :return: AnnData object with `program_{id}_distances` obps key
@@ -143,7 +152,8 @@ def program_graphs(
             neighbors=neighbors,
             npcs=npcs,
             verbose=verbose,
-            use_sparse=use_sparse
+            use_sparse=use_sparse,
+            connectivity=connectivity
         )
 
         vprint(

diff --git a/inferelator_velocity/programs.py b/inferelator_velocity/programs.py
@@ -300,7 +300,7 @@ def _leiden_cluster(
     leiden_kws['adjacency'] = knn_connect
     leiden_kws['random_state'] = leiden_kws.get('random_state', random_state)
 
-    ad_arr = ad.AnnData(dist_array, dtype=float)
+    ad_arr = ad.AnnData(dist_array.astype(float))
 
     sc.tl.leiden(ad_arr, **leiden_kws)
 

diff --git a/inferelator_velocity/tests/test_noise2self.py b/inferelator_velocity/tests/test_noise2self.py
@@ -46,7 +46,7 @@
 EXPR = BASE + NOISE
 DIST = sklearn.metrics.pairwise_distances(EXPR, metric='cosine')
 
-ADATA = ad.AnnData(EXPR, dtype=int)
+ADATA = ad.AnnData(EXPR.astype(int))
 
 
 def _knn(k):

diff --git a/inferelator_velocity/tests/test_programs.py b/inferelator_velocity/tests/test_programs.py
@@ -29,7 +29,7 @@
 EXPRESSION[:, 5] = np.arange(N) * 2 + 10
 
 
-EXPRESSION_ADATA = ad.AnnData(EXPRESSION.astype(int), dtype=int)
+EXPRESSION_ADATA = ad.AnnData(EXPRESSION.astype(int))
 
 ADATA_UNS_PROGRAM_KEYS = [
     'metric',

diff --git a/inferelator_velocity/tests/test_times.py b/inferelator_velocity/tests/test_times.py
@@ -59,8 +59,7 @@ class TestProgramTimes(unittest.TestCase):
     def setUp(self) -> None:
 
         self.adata = ad.AnnData(
-            EXPR,
-            dtype=EXPR.dtype
+            EXPR
         )
 
         self.adata.obs['group'] = LAB

diff --git a/inferelator_velocity/times.py b/inferelator_velocity/times.py
@@ -240,7 +240,7 @@ def calculate_times(
 
     # Construct an adata object and normalize it
     adata = standardize_data(
-        ad.AnnData(count_data, dtype=float)
+        ad.AnnData(count_data.astype(float))
     )
 
     # Calculate chosen PCA & neighbor graph

diff --git a/inferelator_velocity/utils/misc.py b/inferelator_velocity/utils/misc.py
@@ -177,7 +177,7 @@ def copy_count_layer(data, layer):
             "these results will be nonsense."
         )
 
-    d = ad.AnnData(lref, dtype=float)
+    d = ad.AnnData(lref.astype(float))
     d.layers['counts'] = lref.copy()
     d.var = data.var.copy()