permit NaN in embedding coordinates (#1631)

* permit NaN in embedding coordinates

* lint

server/converters/cxgtool.py

@@ -391,13 +391,13 @@ def create_emb(e_name, emb):
 def is_valid_embedding(adata, name, arr):
     """ return True if this layout data is a valid array for front-end presentation:
         * ndarray, with shape (n_obs, >= 2), dtype float/int/uint
-        * contains only finite values
         * follows ScanPy embedding naming conventions
+        * with all values finite or NaN (no +Inf or -Inf)
     """
     is_valid = type(name) == str and name.startswith("X_") and len(name) > 2
     is_valid = is_valid and type(arr) == np.ndarray and arr.dtype.kind in "fiu"
     is_valid = is_valid and arr.shape[0] == adata.n_obs and arr.shape[1] >= 2
-    is_valid = is_valid and np.all(np.isfinite(arr))
+    is_valid = is_valid and not np.any(np.isinf(arr)) and not np.all(np.isnan(arr))
     return is_valid
 
 

server/data_anndata/anndata_adaptor.py

@@ -197,12 +197,13 @@ class AnndataAdaptor(DataAdaptor):
 
     def _is_valid_layout(self, arr):
         """ return True if this layout data is a valid array for front-end presentation:
-            * ndarray, with shape (n_obs, >= 2), dtype float/int/uint
-            * contains only finite values
+            * ndarray, dtype float/int/uint
+            * with shape (n_obs, >= 2)
+            * with all values finite or NaN (no +Inf or -Inf)
         """
         is_valid = type(arr) == np.ndarray and arr.dtype.kind in "fiu"
         is_valid = is_valid and arr.shape[0] == self.data.n_obs and arr.shape[1] >= 2
-        is_valid = is_valid and np.all(np.isfinite(arr))
+        is_valid = is_valid and not np.any(np.isinf(arr)) and not np.all(np.isnan(arr))
         return is_valid
 
     def _validate_data_types(self):
@@ -291,7 +292,7 @@ class AnndataAdaptor(DataAdaptor):
             raise PrepareError("No valid layout data.")
 
         # cap layouts to MAX_LAYOUTS
-        return layouts[0:MAX_LAYOUTS]
+        return valid_layouts[0:MAX_LAYOUTS]
 
     def get_embedding_array(self, ename, dims=2):
         full_embedding = self.data.obsm[f"X_{ename}"]

server/data_common/data_adaptor.py

@@ -328,8 +328,14 @@ class DataAdaptor(metaclass=ABCMeta):
         """
 
         # scale isotropically
-        min = embedding.min(axis=0)
-        max = embedding.max(axis=0)
+        try:
+            min = np.nanmin(embedding, axis=0)
+            max = np.nanmax(embedding, axis=0)
+        except RuntimeError:
+            # indicates entire array was NaN, which should propagate
+            min = np.NaN
+            max = np.NaN
+
         scale = np.amax(max - min)
         normalized_layout = (embedding - min) / scale