fix: stop get_layout from mutating global rng state (#53)

CHANGELOG.md

@@ -4,6 +4,7 @@
 
 ### Bug Fixes
 
+- `LONVisualizer.get_layout()` with a `seed`, and therefore `plot_2d()`, `plot_3d()`, `create_rotation_gif()` and `visualize_all()`, no longer reseeds the global NumPy RNG or leaves a seeded RNG installed in igraph. The seed now applies only to the layout, and igraph's default RNG is restored afterwards. Seeded layouts are unchanged (#53).
 - Continuous sampling now handles failed local searches explicitly. A local search fails when `minimize` raises `ValueError` or returns a non-finite fitness. A failed initial local search fails its run, and a failed search after a perturbation is rejected and counts as a non-improving iteration. Previously, runs starting at a `nan` minimum silently vanished, and an `inf` minimum made `LON.from_trace_data()` fail after all sampling had finished. Results with `success=False` and a finite fitness are still used as local optima. Each failed local search emits a warning with its context and reason (#44).
 - `StepSizeEstimator` divides each sample's escape count by its number of evaluated perturbations instead of `n_perturbations`, so failed local searches no longer bias the escape rate down. Samples whose initial local search fails are skipped, and `RuntimeError` is raised if no sample can be evaluated, instead of returning `nan` (#44).
 - Runs without accepted transitions are no longer dropped from the LON and its performance metrics. `BasinHoppingSampler` and `ILSSampler` now record such a run as a single trace row from its initial local optimum to itself. `LON.from_trace_data()` drops self-loops, so the optimum becomes a vertex without edges and the run counts towards `success` and `deviation`. Basin-Hopping runs with a non-finite initial minimum are still skipped. Seeded traces and LONs change only when some run had no accepted transitions. Set `preserve_runs_without_transitions=False` in either sampler config to restore the earlier behavior, excluding these runs from both the graph and performance metrics (#39).

src/lonkit/visualization.py

@@ -148,10 +148,13 @@ def get_layout(self, graph, seed: int | None = None) -> np.ndarray:
         """Get 2D layout coordinates, with shape ``(0, 2)`` for an empty graph."""
         if graph.vcount() == 0:
             return np.empty((0, 2))
-        if seed is not None:
-            np.random.seed(seed)
-            ig.set_random_number_generator(random.Random(seed))
-        layout = graph.layout_auto()
+        if seed is None:
+            return np.array(graph.layout_auto().coords)
+        ig.set_random_number_generator(random.Random(seed))
+        try:
+            layout = graph.layout_auto()
+        finally:
+            ig.set_random_number_generator(random)
         return np.array(layout.coords)
 
     def plot_2d(

tests/test_visualization.py

@@ -1,5 +1,7 @@
+import random
 from pathlib import Path
 
+import igraph as ig
 import matplotlib.pyplot as plt
 import numpy as np
 import pytest
@@ -28,6 +30,36 @@ def test_layout_different_seeds_give_different_coordinates(
         coords2 = visualizer.get_layout(rastrigin_lon.graph, seed=SEED + 1)
         assert not np.array_equal(coords1, coords2)
 
+    def test_layout_does_not_change_global_numpy_rng(
+        self, rastrigin_lon: LON, visualizer: LONVisualizer
+    ) -> None:
+        np.random.seed(123)
+        expected = np.random.rand(5)
+
+        np.random.seed(123)
+        visualizer.get_layout(rastrigin_lon.graph, seed=SEED)
+        np.testing.assert_array_equal(np.random.rand(5), expected)
+
+    def test_layout_restores_igraph_rng(
+        self, rastrigin_lon: LON, visualizer: LONVisualizer
+    ) -> None:
+        ig.set_random_number_generator(random)
+        random.seed(123)
+        expected = ig.Graph.Erdos_Renyi(n=50, m=100).get_edgelist()
+
+        random.seed(123)
+        visualizer.get_layout(rastrigin_lon.graph, seed=SEED)
+        assert ig.Graph.Erdos_Renyi(n=50, m=100).get_edgelist() == expected
+
+    def test_layout_same_seed_ignores_global_numpy_state(
+        self, rastrigin_lon: LON, visualizer: LONVisualizer
+    ) -> None:
+        np.random.seed(1)
+        coords1 = visualizer.get_layout(rastrigin_lon.graph, seed=SEED)
+        np.random.seed(2)
+        coords2 = visualizer.get_layout(rastrigin_lon.graph, seed=SEED)
+        np.testing.assert_array_equal(coords1, coords2)
+
 
 class TestPlot2DReproducibility:
     def test_plot_2d_same_seed_same_figure(