fix value_type_bug

Author: lhqing

.flake8

@@ -55,6 +55,7 @@ ignore =
     B902
     B023
     D401
+    B028
 exclude = .git,__pycache__,build,docs/_build,dist,ALLCools/sandbox,
 per-file-ignores =
     tests/*: D

ALLCools/mcds/cool_ds.py

@@ -369,10 +369,11 @@ def matrix(
         if samples is not None:
             sel_dict[self.sample_dim] = samples
         if value_type is not None:
-            _da_name = f"{da_name}_value_type"
-            if _da_name not in self.data_vars:
-                _da_name = "value_type"
-            sel_dict[_da_name] = value_type
+            if da_name not in self.data_vars:
+                value_type_dim_name = "value_type"
+            else:
+                value_type_dim_name = f"{da_name}_value_type"
+            sel_dict[value_type_dim_name] = value_type
         if len(sel_dict) > 0:
             sample_da = self.sel(sel_dict)[da_name]
         else:

ALLCools/mcds/mcds.py

@@ -662,7 +662,6 @@ def calculate_hvf_svr(
         self, mc_type=None, var_dim=None, obs_dim=None, n_top_feature=5000, da_name=None, da_suffix="frac", plot=True
     ):
         """Calculate the highly variable features (hvf) with the Support Vector Regression model."""
-        import plotly.graph_objects as go
         from sklearn.svm import SVR
 
         obs_dim = self._verify_dim(obs_dim, mode="obs")
@@ -736,6 +735,13 @@ def calculate_hvf_svr(
             f"({(selected_feature_index.size / judge.size * 100):.1f}%)"
         )
 
+        if plot:
+            try:
+                import plotly.graph_objects as go
+            except ImportError:
+                print("Please install plotly to enable plotting.")
+            plot = False
+
         if plot:
             if hvf_df.shape[0] > 5000:
                 plot_data = hvf_df.sample(5000)

pyproject.toml

@@ -44,7 +44,6 @@ analysis = [
     "leidenalg",
     "networkx",
     "opentsne",
-    "plotly",
     "pynndescent",
     "scanpy",
     "scikit-learn",