Ruff fix and version change

Author: DOKOS-TAYOS

examples/einsum_demo.py

@@ -204,8 +204,7 @@ def parse_args() -> argparse.Namespace:
         choices=("auto", "manual"),
         default="auto",
         help=(
-            "Trace construction mode: auto uses tv.einsum, "
-            "manual uses pair_tensor + torch.einsum."
+            "Trace construction mode: auto uses tv.einsum, manual uses pair_tensor + torch.einsum."
         ),
     )
     parser.add_argument(

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "tensor-network-visualization"
-version = "1.3.0"
+version = "1.3.3"
 description = "Minimal Matplotlib visualizations for TensorKrowch, TensorNetwork, Quimb, and TeNPy tensor networks."
 authors = [{ name = "Alejandro Mata Ali" }]
 readme = "README.md"

scripts/clean.py

@@ -27,15 +27,17 @@ def main() -> int:
     root = Path(__file__).resolve().parent.parent
     venv = root / ".venv"
 
-    dir_names = frozenset({
-        "__pycache__",
-        ".pytest_cache",
-        ".ruff_cache",
-        ".tmp",
-        ".pip_tmp",
-        "build",
-        "dist",
-    })
+    dir_names = frozenset(
+        {
+            "__pycache__",
+            ".pytest_cache",
+            ".ruff_cache",
+            ".tmp",
+            ".pip_tmp",
+            "build",
+            "dist",
+        }
+    )
     file_suffixes = (".pyc", ".pyo", ".pyd")
 
     print("Cleaning project caches and temporary files...")
@@ -47,8 +49,10 @@ def main() -> int:
             continue
         if _should_skip(path, venv):
             continue
-        if path.name in dir_names or path.name.endswith(".egg-info") or path.name.startswith(
-            "pytest-cache-files-"
+        if (
+            path.name in dir_names
+            or path.name.endswith(".egg-info")
+            or path.name.startswith("pytest-cache-files-")
         ):
             dirs_to_remove.append(path)
 

src/tensor_network_viz/_core/_draw_common.py

@@ -225,9 +225,7 @@ def _draw_edges(
             _perpendicular_3d(direction) if dimensions == 3 else _perpendicular_2d(direction)
         )
         perpendicular = perpendicular / np.linalg.norm(perpendicular)
-        if (dimensions == 2 and perpendicular[1] < 0) or (
-            dimensions == 3 and perpendicular[2] < 0
-        ):
+        if (dimensions == 2 and perpendicular[1] < 0) or (dimensions == 3 and perpendicular[2] < 0):
             perpendicular = -perpendicular
         plotter.plot_text(
             midpoint + perpendicular * p.label_offset,
@@ -321,9 +319,7 @@ class _DrawScaleParams:
 def _draw_scale_params(config: PlotConfig, scale: float, *, is_3d: bool) -> _DrawScaleParams:
     """Compute scale-dependent drawing parameters from config."""
     r = (
-        config.node_radius
-        if config.node_radius is not None
-        else PlotConfig.DEFAULT_NODE_RADIUS
+        config.node_radius if config.node_radius is not None else PlotConfig.DEFAULT_NODE_RADIUS
     ) * scale
     stub = (
         config.stub_length if config.stub_length is not None else PlotConfig.DEFAULT_STUB_LENGTH

src/tensor_network_viz/_core/_nodes_edges_common.py

@@ -85,9 +85,7 @@ def _build_graph_from_nodes_edges(
     for node in node_refs:
         name = _stringify(_require_attr(node, "name", "node"))
         node_edges = tuple(_iterable_attr(node, "edges", "node"))
-        axes_names = tuple(
-            _stringify(item) for item in _iterable_attr(node, axis_attr, "node")
-        )
+        axes_names = tuple(_stringify(item) for item in _iterable_attr(node, axis_attr, "node"))
         if len(node_edges) != len(axes_names):
             raise TypeError(
                 f"Node {name!r} has {len(node_edges)} edges but {len(axes_names)} {axis_attr}."

src/tensor_network_viz/_core/curves.py

@@ -54,9 +54,7 @@ def _ellipse_points_3d(
 ) -> Vector:
     theta = np.linspace(0.0, 2.0 * math.pi, samples)
     return (
-        center
-        + np.outer(np.cos(theta), axis_a) * width
-        + np.outer(np.sin(theta), axis_b) * height
+        center + np.outer(np.cos(theta), axis_a) * width + np.outer(np.sin(theta), axis_b) * height
     )
 
 

src/tensor_network_viz/_core/graph.py

@@ -64,9 +64,7 @@ def _make_dangling_edge(
     label: str | None | object = _DEFAULT_LABEL,
 ) -> _EdgeData:
     resolved_label = endpoint.axis_name or name
-    edge_label = (
-        resolved_label if label is _DEFAULT_LABEL else cast(str | None, label)
-    )
+    edge_label = resolved_label if label is _DEFAULT_LABEL else cast(str | None, label)
     return _EdgeData(
         name=name,
         kind="dangling",
@@ -91,9 +89,7 @@ def _make_contraction_edge(
     )
     endpoints = (left_endpoint, right_endpoint)
     resolved_label = _build_edge_label(kind=kind, endpoints=endpoints, edge_name=name)
-    edge_label = (
-        resolved_label if label is _DEFAULT_LABEL else cast(str | None, label)
-    )
+    edge_label = resolved_label if label is _DEFAULT_LABEL else cast(str | None, label)
     return _EdgeData(
         name=name,
         kind=kind,

src/tensor_network_viz/_core/graph_utils.py

@@ -37,11 +37,7 @@ def _extract_unique_items(
         raw_items = source
         should_sort = _is_unordered_collection(raw_items)
     else:
-        extra = (
-            f", or an object with '{attr_sources[0]}' attribute."
-            if attr_sources
-            else "."
-        )
+        extra = f", or an object with '{attr_sources[0]}' attribute." if attr_sources else "."
         raise TypeError(f"Input must be an iterable of {backend_name} {type_name}{extra}.")
 
     iterable = raw_items.values() if isinstance(raw_items, dict) else raw_items

src/tensor_network_viz/_core/layout.py

@@ -424,9 +424,7 @@ def _best_attachment_position_2d(
 ) -> np.ndarray:
     leaf_node_ids = {node_id for node_id, _ in component.trimmed_leaf_parents}
     direction_options = (
-        candidates
-        if component.structure_kind == "chain"
-        else (*candidates, axis, -axis)
+        candidates if component.structure_kind == "chain" else (*candidates, axis, -axis)
     )
     used_dirs = []
     for neighbor_id in component.contraction_graph.neighbors(parent_id):
@@ -458,13 +456,10 @@ def _best_attachment_position_2d(
         candidate = origin + direction * distance
         score = 0.8 * float(np.dot(direction[:2], outward_dir))
         score -= 2.5 * sum(
-            max(0.0, float(np.dot(direction[:2], used_dir)))
-            for used_dir in used_dirs
+            max(0.0, float(np.dot(direction[:2], used_dir))) for used_dir in used_dirs
         )
         score -= 2.0 * sum(
-            1.0
-            for target in assigned_targets
-            if np.linalg.norm(candidate[:2] - target[:2]) < 0.3
+            1.0 for target in assigned_targets if np.linalg.norm(candidate[:2] - target[:2]) < 0.3
         )
         score -= 4.0 * sum(
             1.0
@@ -722,9 +717,7 @@ def _compute_free_directions_3d(
     components = _analyze_layout_components(graph)
     assigned_segments: list[tuple[np.ndarray, np.ndarray]] = []
     component_by_node = {
-        node_id: component
-        for component in components
-        for node_id in component.node_ids
+        node_id: component for component in components for node_id in component.node_ids
     }
 
     for node_id, node in graph.nodes.items():
@@ -772,9 +765,7 @@ def _compute_free_directions_3d(
                 break
             else:
                 fallback = (
-                    named_direction
-                    if named_direction is not None
-                    else _orthogonal_unit(axis)
+                    named_direction if named_direction is not None else _orthogonal_unit(axis)
                 )
                 if not _direction_has_space(fallback, used_dirs):
                     fallback = -fallback
@@ -825,8 +816,7 @@ def _used_axis_directions(
 
 def _direction_has_space(direction: np.ndarray, used_dirs: list[np.ndarray]) -> bool:
     overlap = sum(
-        max(0.0, float(np.dot(direction, used_direction)))
-        for used_direction in used_dirs
+        max(0.0, float(np.dot(direction, used_direction))) for used_direction in used_dirs
     )
     return overlap < _FREE_DIR_OVERLAP_THRESHOLD
 

src/tensor_network_viz/_core/layout_structure.py

@@ -290,10 +290,7 @@ def _detect_grid(nx_graph: nx.Graph) -> dict[int, tuple[int, int]] | None:
         mapping = nx.vf2pp_isomorphism(nx_graph, grid_graph)
         if mapping is None:
             continue
-        return {
-            node_id: (grid_col, grid_row)
-            for node_id, (grid_row, grid_col) in mapping.items()
-        }
+        return {node_id: (grid_col, grid_row) for node_id, (grid_row, grid_col) in mapping.items()}
     return None