lintfix, baby one more time

arviz/data/io_cmdstanpy.py

@@ -93,12 +93,9 @@ def posterior_to_xarray(self):
 
         return (
             dict_to_dataset(data, library=self.cmdstanpy, coords=coords, dims=dims),
-            dict_to_dataset(
-                data_warmup, library=self.cmdstanpy, coords=coords, dims=dims
-            ),
+            dict_to_dataset(data_warmup, library=self.cmdstanpy, coords=coords, dims=dims),
         )
 
-
     @requires("posterior")
     def sample_stats_to_xarray(self):
         """Extract sample_stats from prosterior fit."""
@@ -141,14 +138,12 @@ def posterior_predictive_to_xarray(self):
         """Convert posterior_predictive samples to xarray."""
         return self.predictive_to_xarray(self.posterior_predictive, self.posterior)
 
-
     @requires("prior")
     @requires("prior_predictive")
     def prior_predictive_to_xarray(self):
         """Convert prior_predictive samples to xarray."""
         return self.predictive_to_xarray(self.prior_predictive, self.prior)
 
-
     def predictive_to_xarray(self, names, fit):
         """Convert predictive samples to xarray."""
         predictive = _as_set(names)
@@ -279,7 +274,6 @@ def prior_to_xarray(self):
             ),
         )
 
-
     @requires("observed_data")
     def observed_data_to_xarray(self):
         """Convert observed data to xarray."""
@@ -438,6 +432,7 @@ def sample_stats_to_xarray_pre_v_0_9_68(self, fit):
             ),
         )
 
+
 def _as_set(spec):
     """Uniform representation for args which be name or list of names."""
     if spec is None:
@@ -448,7 +443,6 @@ def _as_set(spec):
         return set(spec)
 
 
-
 def _filter(names, spec):
     """Remove names from list of names."""
     if isinstance(spec, str):
@@ -461,12 +455,12 @@ def _filter(names, spec):
             names.remove(item)
     return names
 
+
 def _filter_columns(columns, spec):
     """Parse variable name from column label, removing element index, if any."""
     return [col for col in columns if col.split("[")[0].split(".")[0] in spec]
 
 
-
 def _unpack_fit(fit, items, save_warmup):
     """Transform fit to dictionary containing ndarrays.