style: upgrade to ruff v0.8.4 and fix type hints

.pre-commit-config.yaml

@@ -11,13 +11,13 @@ repos:
         pass_filenames: false
   # ruff check (w/autofix)
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.1.3 # should match version in pyproject.toml
+    rev: v0.8.4 # should match version in pyproject.toml
     hooks:
       - id: ruff
         args: [--fix, --exit-non-zero-on-fix]
   # ruff format
   - repo: https://github.com/astral-sh/ruff-pre-commit
-    rev: v0.1.3 # should match version in pyproject.toml
+    rev: v0.8.4 # should match version in pyproject.toml
     hooks:
       - id: ruff-format
   # # pydoclint - docstring formatting

benchmarks/plot.ipynb

@@ -8,24 +8,13 @@
    "outputs": [],
    "source": [
     "import matplotlib.pyplot as plt\n",
-    "import numpy as np\n",
     "\n",
     "plt.style.use(\"ggplot\")"
    ]
   },
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "c92bf960-ddb5-409f-bd3c-5bce0a03ccd0",
-   "metadata": {},
-   "outputs": [],
-   "source": [
-    "from sequentia import"
-   ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": 79,
    "id": "6649bf2d-7430-401d-8113-f3c1e1cf4779",
    "metadata": {},
    "outputs": [
@@ -48,23 +37,36 @@
     "\n",
     "bars = ax.bar(labels, runtimes, width=0.5, color=\"C1\")\n",
     "ax.set(xlabel=\"Package\", ylabel=\"Runtime (s)\")\n",
-    "ax.set_title(\"Univariate DTW-kNN performance (1,500 FSDD train/test sequences, 16 workers)\", fontsize=11)\n",
+    "ax.set_title(\n",
+    "    (\n",
+    "        \"Univariate DTW-kNN performance \"\n",
+    "        \"(1,500 FSDD train/test sequences, 16 workers)\"\n",
+    "    ),\n",
+    "    fontsize=11,\n",
+    ")\n",
+    "\n",
     "\n",
     "def fmt(s: float) -> str:\n",
+    "    \"\"\"Formats the runtime.\"\"\"\n",
     "    if s < 60:\n",
     "        return f\"{round(s)}s\"\n",
     "    m, s = divmod(s, 60)\n",
     "    return f\"{round(m)}m {round(s)}s\"\n",
     "\n",
+    "\n",
     "for bar in bars:\n",
     "    plt.text(\n",
-    "        bar.get_x() + bar.get_width() / 2, bar.get_height(),\n",
-    "        fmt(bar.get_height()), ha='center', va='bottom', fontsize=9,\n",
+    "        bar.get_x() + bar.get_width() / 2,\n",
+    "        bar.get_height(),\n",
+    "        fmt(bar.get_height()),\n",
+    "        ha=\"center\",\n",
+    "        va=\"bottom\",\n",
+    "        fontsize=9,\n",
     "    )\n",
     "\n",
     "for lab in ax.get_xticklabels():\n",
-    "   if lab.get_text() == \"sequentia\":\n",
-    "      lab.set_fontweight('bold')\n",
+    "    if lab.get_text() == \"sequentia\":\n",
+    "        lab.set_fontweight(\"bold\")\n",
     "\n",
     "plt.tight_layout()\n",
     "plt.savefig(\"benchmark.svg\")\n",

make/lint.py

@@ -33,7 +33,7 @@ def check(c: Config) -> None:
 def format_(c: Config) -> None:
     """Format Python files."""
     commands: list[str] = [
-        "poetry run ruff --fix .",
+        "poetry run ruff check --fix .",
         "poetry run ruff format .",
     ]
     for command in commands:

pyproject.toml

@@ -86,7 +86,7 @@ tox = "4.11.3"
 pre-commit = ">=3"
 
 [tool.poetry.group.lint.dependencies]
-ruff = "0.1.3"
+ruff = "0.8.4"
 pydoclint = "0.3.8"
 
 [tool.poetry.group.docs.dependencies]
@@ -100,8 +100,8 @@ pytest = { version = "^7.4.0" }
 pytest-cov = { version = "^4.1.0" }
 
 [tool.ruff]
-required-version = "0.1.3"
-select = [
+required-version = "0.8.4"
+lint.select = [
     "F",    # pyflakes: https://pypi.org/project/pyflakes/
     "E",    # pycodestyle (error): https://pypi.org/project/pycodestyle/
     "W",    # pycodestyle (warning): https://pypi.org/project/pycodestyle/
@@ -144,7 +144,7 @@ select = [
     "PERF", # perflint: https://pypi.org/project/perflint/
     "RUF",  # ruff
 ]
-ignore = [
+lint.ignore = [
     "ANN401",  # https://beta.ruff.rs/docs/rules/any-type/
     "B905",    # https://beta.ruff.rs/docs/rules/zip-without-explicit-strict/
     "TD003",   # https://beta.ruff.rs/docs/rules/missing-todo-link/
@@ -162,16 +162,15 @@ ignore = [
     "C408",    # Unnecessary `dict` call (rewrite as a literal)
     "D401",    # First line of docstring should be in imperative mood
 ]
-ignore-init-module-imports = true # allow unused imports in __init__.py
 line-length = 79
 
-[tool.ruff.pydocstyle]
+[tool.ruff.lint.pydocstyle]
 convention = "numpy"
 
-[tool.ruff.flake8-annotations]
+[tool.ruff.lint.flake8-annotations]
 allow-star-arg-any = true
 
-[tool.ruff.extend-per-file-ignores]
+[tool.ruff.lint.extend-per-file-ignores]
 "__init__.py" = ["PLC0414", "F403", "F401", "F405"]
 "sequentia/datasets/*.py" = ["B006"]
 "sequentia/enums.py" = ["E501"]

sequentia/_internal/_hmm/topologies.py

@@ -13,10 +13,10 @@
 from sequentia.enums import TopologyMode
 
 __all__ = [
+    "TOPOLOGY_MAP",
     "ErgodicTopology",
     "LeftRightTopology",
     "LinearTopology",
-    "TOPOLOGY_MAP",
 ]
 
 
@@ -36,15 +36,15 @@ class BaseTopology:
     mode: TopologyMode
 
     def __init__(
-        self: BaseTopology,
+        self,
         *,
         n_states: int,
         random_state: np.random.RandomState,
-    ) -> BaseTopology:
+    ) -> None:
         self.n_states = n_states
         self.random_state = random_state
 
-    def uniform_start_probs(self: BaseTopology) -> FloatArray:
+    def uniform_start_probs(self) -> FloatArray:
         """Set the initial state distribution as a discrete uniform
         distribution.
 
@@ -55,7 +55,7 @@ def uniform_start_probs(self: BaseTopology) -> FloatArray:
         """
         return np.ones(self.n_states) / self.n_states
 
-    def random_start_probs(self: BaseTopology) -> FloatArray:
+    def random_start_probs(self) -> FloatArray:
         """Set the initial state distribution by randomly sampling
         probabilities generated by a Dirichlet distribution.
 
@@ -69,7 +69,7 @@ def random_start_probs(self: BaseTopology) -> FloatArray:
             size=1,
         ).flatten()
 
-    def uniform_transition_probs(self: BaseTopology) -> FloatArray:
+    def uniform_transition_probs(self) -> FloatArray:
         """Set the transition matrix as uniform (equal probability of
         transitioning to all other possible states from each state)
         corresponding to the topology.
@@ -81,7 +81,7 @@ def uniform_transition_probs(self: BaseTopology) -> FloatArray:
         """
         raise NotImplementedError
 
-    def random_transition_probs(self: BaseTopology) -> FloatArray:
+    def random_transition_probs(self) -> FloatArray:
         """Set the transition matrix as random (random probability of
         transitioning to all other possible states from each state) by
         sampling probabilitiesfrom a Dirichlet distribution - according
@@ -94,7 +94,7 @@ def random_transition_probs(self: BaseTopology) -> FloatArray:
         """
         raise NotImplementedError
 
-    def check_start_probs(self: BaseTopology, initial: FloatArray, /) -> None:
+    def check_start_probs(self, initial: FloatArray, /) -> None:
         """Validate an initial state distribution according to the
         topology's restrictions.
 
@@ -114,9 +114,7 @@ def check_start_probs(self: BaseTopology, initial: FloatArray, /) -> None:
             raise ValueError(msg)
         return initial
 
-    def check_transition_probs(
-        self: BaseTopology, transitions: FloatArray, /
-    ) -> FloatArray:
+    def check_transition_probs(self, transitions: FloatArray, /) -> FloatArray:
         """Validate a transition matrix according to the topology's
         restrictions.
 
@@ -152,7 +150,7 @@ class ErgodicTopology(BaseTopology):
 
     mode: TopologyMode = TopologyMode.ERGODIC
 
-    def uniform_transition_probs(self: ErgodicTopology) -> FloatArray:
+    def uniform_transition_probs(self) -> FloatArray:
         """Set the transition matrix as uniform (equal probability of
         transitioning to all other possible states from each state)
         corresponding to the topology.
@@ -164,7 +162,7 @@ def uniform_transition_probs(self: ErgodicTopology) -> FloatArray:
         """
         return np.ones((self.n_states, self.n_states)) / self.n_states
 
-    def random_transition_probs(self: ErgodicTopology) -> FloatArray:
+    def random_transition_probs(self) -> FloatArray:
         """Set the transition matrix as random (random probability of
         transitioning to all other possible states from each state) by
         sampling probabilities from a Dirichlet distribution - according
@@ -180,9 +178,7 @@ def random_transition_probs(self: ErgodicTopology) -> FloatArray:
             size=self.n_states,
         )
 
-    def check_transition_probs(
-        self: ErgodicTopology, transitions: FloatArray, /
-    ) -> FloatArray:
+    def check_transition_probs(self, transitions: FloatArray, /) -> FloatArray:
         """Validate a transition matrix according to the topology's
         restrictions.
 
@@ -216,7 +212,7 @@ class LeftRightTopology(BaseTopology):
 
     mode: TopologyMode = TopologyMode.LEFT_RIGHT
 
-    def uniform_transition_probs(self: LeftRightTopology) -> FloatArray:
+    def uniform_transition_probs(self) -> FloatArray:
         """Set the transition matrix as uniform (equal probability of
         transitioning to all other possible states from each state)
         corresponding to the topology.
@@ -233,7 +229,7 @@ def uniform_transition_probs(self: LeftRightTopology) -> FloatArray:
         lower_ones = np.tril(np.ones(self.n_states), k=-1)
         return upper_ones / (upper_divisors + lower_ones)
 
-    def random_transition_probs(self: LeftRightTopology) -> FloatArray:
+    def random_transition_probs(self) -> FloatArray:
         """Set the transition matrix as random (random probability of
         transitioning to all other possible states from each state) by
         sampling probabilities from a Dirichlet distribution, according
@@ -249,9 +245,7 @@ def random_transition_probs(self: LeftRightTopology) -> FloatArray:
             row[i:] = self.random_state.dirichlet(np.ones(self.n_states - i))
         return transitions
 
-    def check_transition_probs(
-        self: LeftRightTopology, transitions: FloatArray, /
-    ) -> FloatArray:
+    def check_transition_probs(self, transitions: FloatArray, /) -> FloatArray:
         """Validate a transition matrix according to the topology's
         restrictions.
 
@@ -281,7 +275,7 @@ class LinearTopology(LeftRightTopology):
 
     mode: TopologyMode = TopologyMode.LINEAR
 
-    def uniform_transition_probs(self: LinearTopology) -> FloatArray:
+    def uniform_transition_probs(self) -> FloatArray:
         """Set the transition matrix as uniform (equal probability of
         transitioning to all other possible states from each state)
         corresponding to the topology.
@@ -297,7 +291,7 @@ def uniform_transition_probs(self: LinearTopology) -> FloatArray:
             row[i : (i + size)] = np.ones(size) / size
         return transitions
 
-    def random_transition_probs(self: LinearTopology) -> FloatArray:
+    def random_transition_probs(self) -> FloatArray:
         """Set the transition matrix as random (random probability of
         transitioning to all other possible states from each state) by
         sampling probabilities from a Dirichlet distribution, according to the
@@ -314,9 +308,7 @@ def random_transition_probs(self: LinearTopology) -> FloatArray:
             row[i : (i + size)] = self.random_state.dirichlet(np.ones(size))
         return transitions
 
-    def check_transition_probs(
-        self: LinearTopology, transitions: FloatArray, /
-    ) -> FloatArray:
+    def check_transition_probs(self, transitions: FloatArray, /) -> FloatArray:
         """Validate a transition matrix according to the topology's
         restrictions.
 

sequentia/_internal/_typing.py

@@ -6,7 +6,7 @@
 import numpy as np
 import numpy.typing as npt
 
-__all__ = ["FloatArray", "IntArray", "Array"]
+__all__ = ["Array", "FloatArray", "IntArray"]
 
 FloatArray = npt.NDArray[np.float64]
 IntArray = npt.NDArray[np.int64]

sequentia/_internal/_validation.py

@@ -20,15 +20,15 @@
 from sequentia._internal._typing import Array, FloatArray, IntArray
 
 __all__ = [
-    "check_random_state",
-    "check_is_fitted",
-    "requires_fit",
-    "check_classes",
     "check_X",
     "check_X_lengths",
-    "check_y",
-    "check_weighting",
+    "check_classes",
+    "check_is_fitted",
+    "check_random_state",
     "check_use_c",
+    "check_weighting",
+    "check_y",
+    "requires_fit",
 ]
 
 
@@ -60,7 +60,7 @@ def check_is_fitted(
 
 def requires_fit(function: t.Callable) -> t.Callable:
     @functools.wraps(function)
-    def wrapper(self: t.Self, *args: t.Any, **kwargs: t.Any) -> t.Any:
+    def wrapper(self, *args: t.Any, **kwargs: t.Any) -> t.Any:  # noqa: ANN001
         check_is_fitted(self)
         return function(self, *args, **kwargs)
 
@@ -106,14 +106,14 @@ def check_X(
     if not isinstance(X, np.ndarray):
         try:
             X = np.array(X).astype(dtype)
-        except Exception as e:  # noqa: BLE001
+        except Exception as e:
             type_ = type(X).__name__
             msg = f"Expected value to be a numpy.ndarray, got {type_!r}"
             raise TypeError(msg) from e
     if (dtype_ := X.dtype) != dtype:
         try:
             X = X.astype(dtype)
-        except Exception as e:  # noqa: BLE001
+        except Exception as e:
             msg = f"Expected array to have dtype {dtype}, got {dtype_}"
             raise TypeError(msg) from e
     if (ndim_ := X.ndim) != 2:
@@ -214,7 +214,7 @@ def check_weighting(
         if x.shape != weights.shape:
             msg = "Weights should have the same shape as inputs"
             raise ValueError(msg)  # noqa: TRY301
-    except Exception as e:  # noqa: BLE001
+    except Exception as e:
         msg = "Invalid weighting function"
         raise ValueError(msg) from e
 

sequentia/datasets/__init__.py

@@ -10,4 +10,4 @@
 from sequentia.datasets.digits import load_digits
 from sequentia.datasets.gene_families import load_gene_families
 
-__all__ = ["data", "load_digits", "load_gene_families", "SequentialDataset"]
+__all__ = ["SequentialDataset", "data", "load_digits", "load_gene_families"]