Fix lint

experiments/cf_nolearn.py

@@ -33,11 +33,7 @@
     SavedProfile,
     is_cuda_ready,
 )
-from emevo.rl.ppo_normal import (
-    NormalPPONet,
-    vmap_apply,
-    vmap_net,
-)
+from emevo.rl.ppo_normal import NormalPPONet, vmap_apply, vmap_net
 from emevo.spaces import BoxSpace
 
 PROJECT_ROOT = Path(__file__).parent.parent

experiments/cf_simple.py

@@ -1,4 +1,5 @@
 """Asexual reward evolution with Circle Foraging"""
+
 import dataclasses
 import json
 from pathlib import Path
@@ -56,11 +57,11 @@ class RewardExtractor:
     _max_norm: jax.Array = dataclasses.field(init=False)
 
     def __post_init__(self) -> None:
-        self._max_norm = jnp.sqrt(jnp.sum(self.act_space.high ** 2, axis=-1))
+        self._max_norm = jnp.sqrt(jnp.sum(self.act_space.high**2, axis=-1))
 
     def normalize_action(self, action: jax.Array) -> jax.Array:
         scaled = self.act_space.sigmoid_scale(action)
-        norm = jnp.sqrt(jnp.sum(scaled ** 2, axis=-1, keepdims=True))
+        norm = jnp.sqrt(jnp.sum(scaled**2, axis=-1, keepdims=True))
         return norm / self._max_norm
 
     def extract(

noxfile.py

@@ -6,7 +6,7 @@
 
 import nox
 
-SOURCES = ["src/emevo", "tests", "smoke-tests", "experiments"]
+SOURCES = ["src/emevo", "tests", "smoke-tests", "experiments", "scripts"]
 
 
 def _sync(session: nox.Session, requirements: str) -> None:

pyproject.toml

@@ -73,5 +73,6 @@ select = ["E", "F", "B", "UP"]
 "__init__.py" = ["F401"]
 "src/emevo/reward_fn.py" = ["B023"]
 # For typer
-"experiments/**/*.py" = ["B008", "UP006", "UP007"]
-"smoke-tests/*.py" = ["B008", "UP006", "UP007"]
+"experiments/*.py" = ["B008", "UP006", "UP007"]
+"smoke-tests/*.py" = ["B008", "UP006", "UP007"]
+"scripts/*.py" = ["UP006", "UP035"]

scripts/make_web_data.py

@@ -7,11 +7,8 @@
 import numpy as np
 import polars as pl
 import typer
-from numpy.typing import NDArray
-from serde import toml
 
 from emevo.analysis.log_plotting import load_log
-from emevo.exp_utils import CfConfig, SavedPhysicsState
 
 PROJECT_ROOT = Path(__file__).parent.parent
 
@@ -106,7 +103,7 @@ def _agg_df(
 
 def main(
     profile_and_rewards_path: Path,
-    starting_points: List[int] = [],
+    starting_points: List[int],
     write_dir: Optional[Path] = None,
     length: int = 100,
 ) -> None:
@@ -127,9 +124,12 @@ def main(
             ldfi,
             index * 1024000,
         )
-        cxy_df.write_parquet(write_dir / f"saved_cpos-{point}.parqut", compression="snappy")
-        sxy_df.write_parquet(write_dir / f"saved_spos-{point}.parqut", compression="snappy")
-
+        cxy_df.write_parquet(
+            write_dir / f"saved_cpos-{point}.parqut", compression="snappy"
+        )
+        sxy_df.write_parquet(
+            write_dir / f"saved_spos-{point}.parqut", compression="snappy"
+        )
 
 
 if __name__ == "__main__":

src/emevo/exp_utils.py

@@ -134,7 +134,7 @@ class GopsConfig:
     path: str
     init_std: float
     init_mean: float
-    params: dict[str, float | dict[str, float]]
+    params: dict[str, float | dict[str, Any]]
     init_kwargs: dict[str, float] = dataclasses.field(default_factory=dict)
 
     def load_model(self) -> gops.Mutation | gops.Crossover: