mandatory linting

src/chainconsumer/chain.py

@@ -10,11 +10,11 @@
 from __future__ import annotations
 
 import logging
-from typing import TYPE_CHECKING, Any, TypeAlias, Optional, List
+from typing import TYPE_CHECKING, Any, Optional, TypeAlias
 
+import arviz as az
 import numpy as np
 import pandas as pd
-import arviz as az
 from pydantic import Field, field_validator, model_validator
 
 from .base import BetterBase
@@ -396,7 +396,7 @@ def from_numpyro(
         cls,
         mcmc: numpyro.infer.MCMC,
         name: str,
-        var_names: Optional[List[str]] = [],
+        var_names: Optional[list[str]] = [],
         **kwargs: Any,
     ) -> Chain:
         """Constructor from numpyro samples
@@ -413,15 +413,17 @@ def from_numpyro(
         """
 
         var_names = _filter_var_names(var_names, list(mcmc.get_samples().keys()))
-        df = pd.DataFrame.from_dict({key: np.ravel(value) for key, value in mcmc.get_samples().items() if key in var_names})
+        df = pd.DataFrame.from_dict(
+            {key: np.ravel(value) for key, value in mcmc.get_samples().items() if key in var_names}
+        )
         return cls(samples=df, name=name, **kwargs)
 
     @classmethod
     def from_arviz(
         cls,
         arviz_id: arviz.InferenceData,
         name: str,
-        var_names: Optional[List[str]] = [],
+        var_names: Optional[list[str]] = [],
         **kwargs: Any,
     ) -> Chain:
         """Constructor from an arviz InferenceData object
@@ -457,7 +459,7 @@ def vec_coordinate(self) -> np.ndarray:
         return np.array(list(self.coordinate.values()))
 
 
-def _filter_var_names(var_names: List[str], all_vars: List[str]):
+def _filter_var_names(var_names: list[str], all_vars: list[str]):
     """
     Helper function to return the var_names to allows filtering parameters names.
     """
@@ -466,10 +468,12 @@ def _filter_var_names(var_names: List[str], all_vars: List[str]):
         return all_vars
 
     elif var_names:
-        if not (all([var.startswith('~') for var in var_names]) or all([not var.startswith('~') for var in var_names])):
-            raise ValueError("all values in var_names must start with ~ to exclude a subset OR none of them to keep a subset")
+        if not (all([var.startswith("~") for var in var_names]) or all([not var.startswith("~") for var in var_names])):
+            raise ValueError(
+                "all values in var_names must start with ~ to exclude a subset OR none of them to keep a subset"
+            )
 
-        if all([var.startswith('~') for var in var_names]):
+        if all([var.startswith("~") for var in var_names]):
             # remove the ~ from the var names
             var_names = [var[1:] for var in var_names]
             var_names = [var for var in all_vars if var not in var_names]

tests/test_translators.py

@@ -87,7 +87,7 @@ def test_drop_on_arviz_translator(self):
         numpyro_mcmc = run_numpyro_mcmc(self.n_steps, self.n_chains)
         arviz_id = az.from_numpyro(numpyro_mcmc)
         chain = Chain.from_arviz(arviz_id, "Arviz", var_names=["mu"])
-        assert ("mu" in chain.samples.columns) and not ("sigma" in chain.samples.columns)
+        assert ("mu" in chain.samples.columns) and "sigma" not in chain.samples.columns
 
         chain = Chain.from_arviz(arviz_id, "Arviz", var_names=["~mu"])
         assert ("mu" not in chain.samples.columns) and ("sigma" in chain.samples.columns)
@@ -101,7 +101,7 @@ def test_numpyro_translator(self):
     def test_drop_on_numpyro_translator(self):
         numpyro_mcmc = run_numpyro_mcmc(self.n_steps, self.n_chains)
         chain = Chain.from_numpyro(numpyro_mcmc, "numpyro", var_names=["mu"])
-        assert ("mu" in chain.samples.columns) and not ("sigma" in chain.samples.columns)
+        assert ("mu" in chain.samples.columns) and "sigma" not in chain.samples.columns
 
         chain = Chain.from_numpyro(numpyro_mcmc, "numpyro", var_names=["~mu"])
         assert ("mu" not in chain.samples.columns) and ("sigma" in chain.samples.columns)