Merge pull request #449 from mj-will/update-ruff

MAINT: update ruff

.github/workflows/lint.yml

@@ -15,6 +15,7 @@ jobs:
     runs-on: ubuntu-latest
     steps:
       - uses: actions/checkout@v4
-      - uses: chartboost/ruff-action@v1
+      - uses: astral-sh/ruff-action@v3
         with:
+          version: "0.9.x"
           args: 'format --check'

.pre-commit-config.yaml

@@ -8,7 +8,7 @@ repos:
     -   id: check-added-large-files
 - repo: https://github.com/astral-sh/ruff-pre-commit
   # Ruff version.
-  rev: v0.6.4
+  rev: v0.9.0
   hooks:
     # Run the linter.
     - id: ruff

src/nessai/evidence.py

@@ -30,7 +30,7 @@ def logsubexp(x, y):
     """
     if np.any(x < y):
         raise RuntimeError(
-            "cannot take log of negative number " f"{str(x)!s} - {str(y)!s}"
+            f"cannot take log of negative number {str(x)!s} - {str(y)!s}"
         )
 
     return x + np.log1p(-np.exp(y - x))
@@ -237,8 +237,7 @@ def plot(self, filename=None):
         fig = plt.figure()
         plt.plot(self.log_vols, self.logLs)
         plt.title(
-            f"log Z={self.logZ:.2f} "
-            f"H={self.info[-1] * np.log2(np.e):.2f} bits"
+            f"log Z={self.logZ:.2f} H={self.info[-1] * np.log2(np.e):.2f} bits"
         )
         plt.grid(which="both")
         plt.xlabel("log prior-volume")

src/nessai/flows/realnvp.py

@@ -155,7 +155,7 @@ def create_net(in_features, out_features):
                 )
             if dropout_probability:
                 logger.warning(
-                    "Dropout not supported for MLP, " "will be ignored"
+                    "Dropout not supported for MLP, will be ignored"
                 )
             hidden_features = num_blocks_per_layer * [hidden_features]
 
@@ -169,7 +169,7 @@ def create_net(in_features, out_features):
 
         else:
             raise ValueError(
-                f"Unknown nn type: {net}. " "Choose from: {resnet, mlp}."
+                f"Unknown nn type: {net}. Choose from: {{resnet, mlp}}."
             )
 
         layers = []

src/nessai/flowsampler.py

@@ -246,11 +246,9 @@ def _resume_from_file(
                 )
             except RuntimeError as e:
                 logger.error(
-                    "Could not load old resume " f"file from: {self.output}"
-                )
-                raise RuntimeError(
-                    "Could not resume sampler " f"with error: {e}"
+                    f"Could not load old resume file from: {self.output}"
                 )
+                raise RuntimeError(f"Could not resume sampler with error: {e}")
         return ns
 
     def _resume_from_data(
@@ -398,7 +396,7 @@ def run_standard_sampler(
             rng=self.rng,
         )
         logger.info(
-            f"Returned {self.posterior_samples.size} " "posterior samples"
+            f"Returned {self.posterior_samples.size} posterior samples"
         )
 
         if save:

src/nessai/model.py

@@ -825,11 +825,11 @@ def verify_model(self):
 
         if self.log_prior(x) is None:
             raise RuntimeError(
-                "Log-prior function did not return " "a prior value"
+                "Log-prior function did not return a prior value"
             )
         if self.log_likelihood(x) is None:
             raise RuntimeError(
-                "Log-likelihood function did not return " "a likelihood value"
+                "Log-likelihood function did not return a likelihood value"
             )
 
         if self.allow_multi_valued_likelihood:

src/nessai/proposal/flowproposal/base.py

@@ -422,8 +422,7 @@ def configure_reparameterisations(self, reparameterisations):
         for k, cfg in _reparameterisations.items():
             if k in self.model.names:
                 logger.debug(
-                    f"Found parameter {k} in model, "
-                    "assuming it is a parameter"
+                    f"Found parameter {k} in model, assuming it is a parameter"
                 )
                 if isinstance(cfg, str) or cfg is None:
                     rc, default_config = self.get_reparameterisation(cfg)
@@ -575,10 +574,7 @@ def names(self):
     @property
     def rescaled_names(self):
         warn(
-            (
-                "`rescaled_names` is deprecated, use `prime_parameters` "
-                "instead"
-            ),
+            ("`rescaled_names` is deprecated, use `prime_parameters` instead"),
             FutureWarning,
         )
         return self.prime_parameters

src/nessai/samplers/importancesampler.py

@@ -1156,8 +1156,7 @@ def draw_n_samples(self, n: int, **kwargs):
             unit_hypercube=True,
         )
         logger.debug(
-            "Min. log-likelihood of new samples: "
-            f"{np.min(new_points['logL'])}"
+            f"Min. log-likelihood of new samples: {np.min(new_points['logL'])}"
         )
         if not np.isfinite(new_points["logL"]).all():
             logger.warning("Log-likelihood contains infs")
@@ -1221,7 +1220,7 @@ def add_and_update_points(self, n: int):
         self._current_proposal_entropy = differential_entropy(-log_q[:, -1])
 
         logger.debug(
-            "New samples ESS: " f"{effective_sample_size(new_samples['logW'])}"
+            f"New samples ESS: {effective_sample_size(new_samples['logW'])}"
         )
 
         if self.plot and self.plot_pool:

tests/test_gw/test_gw_proposal.py

@@ -162,7 +162,7 @@ def test_augmented_reparameterisation_prime_prior(augmented_proposal):
     augmented_proposal._reparameterisation = MagicMock()
 
     with patch(
-        "nessai.proposal.flowproposal.FlowProposal." "x_prime_log_prior"
+        "nessai.proposal.flowproposal.FlowProposal.x_prime_log_prior"
     ) as mock:
         AugmentedGWFlowProposal.x_prime_log_prior(augmented_proposal, 1)