gene sets summary route (#2099)

* gene sets summary route

* lint

* clarify return type

* style

local_server/data_anndata/anndata_adaptor.py

@@ -5,6 +5,7 @@ import anndata
 import numpy as np
 from packaging import version
 from pandas.core.dtypes.dtypes import CategoricalDtype
+import pandas as pd
 from scipy import sparse
 from server_timing import Timing as ServerTiming
 
@@ -12,7 +13,7 @@ import local_server.compute.diffexp_generic as diffexp_generic
 from local_server.common.colors import convert_anndata_category_colors_to_cxg_category_colors
 from local_server.common.constants import Axis, MAX_LAYOUTS
 from local_server.common.corpora import corpora_get_props_from_anndata
-from local_server.common.errors import PrepareError, DatasetAccessError, FilterError
+from local_server.common.errors import PrepareError, DatasetAccessError, FilterError, UnsupportedSummaryMethod
 from local_server.common.utils.type_conversion_utils import get_schema_type_hint_of_array
 from local_server.compute.scanpy import scanpy_umap
 from local_server.data_common.data_adaptor import DataAdaptor
@@ -367,3 +368,29 @@ class AnndataAdaptor(DataAdaptor):
     def get_var_keys(self):
         # return list of keys
         return self.data.var.keys().to_list()
+
+    def get_gene_set_summary(self, geneset_name, genes, method):
+        if method != "mean":
+            raise UnsupportedSummaryMethod("Unknown gene set summary method.")
+
+        var_index = self.parameters.get("var_names")
+        obs_selector, var_selector = self._filter_to_mask(
+            {
+                "var": {
+                    "annotation_value": [
+                        {
+                            "name": var_index,
+                            "values": genes,
+                        }
+                    ]
+                }
+            }
+        )
+
+        X = self.get_X_array(obs_selector, var_selector)
+        if sparse.issparse(X):
+            mean = X.mean(axis=1)
+        else:
+            mean = X.mean(axis=1, keepdims=True)
+        col_idx = pd.Index([geneset_name])
+        return encode_matrix_fbs(mean, col_idx=col_idx, row_idx=None)