style: ruff format test_error_messages + test_measurement_error_time_edges

Author: qectorlab

python/tests/test_error_messages.py

@@ -4,18 +4,15 @@
 they mention "unknown", the offending kind, and (for the benchmark dispatcher)
 the list of valid choices.
 """
+
 import numpy as np
 import pytest
 
 from qector_decoder_v3 import codes, dem, result, benchmarking
 
 
 def _small_dem():
-    text = (
-        "error(0.1) D0 L0\n"
-        "error(0.1) D0 D1\n"
-        "error(0.1) D1 L0\n"
-    )
+    text = "error(0.1) D0 L0\nerror(0.1) D0 D1\nerror(0.1) D1 L0\n"
     return dem.parse_dem(text)
 
 
@@ -45,6 +42,4 @@ def test_benchmark_decoder_message_lists_choices():
     msg = str(excinfo.value)
     assert "zzz" in msg
     # message enumerates valid decoder kinds
-    assert "blossom" in msg and "union_find" in msg, (
-        f"message should list valid choices: {msg!r}"
-    )
+    assert "blossom" in msg and "union_find" in msg, f"message should list valid choices: {msg!r}"

python/tests/test_measurement_error_time_edges.py

@@ -10,6 +10,7 @@
 * QECTOR's logical error rate is within a Wilson-CI slack of upstream PyMatching
   on the SAME shots — i.e. the time edges are wired up correctly.
 """
+
 import math
 
 import numpy as np
@@ -47,9 +48,7 @@ def test_measurement_error_time_edges_match_pymatching(d):
     sdem = circ.detector_error_model(decompose_errors=True)
     assert sdem.num_observables >= 1
 
-    det, obs = circ.compile_detector_sampler(seed=2025).sample(
-        shots=N, separate_observables=True
-    )
+    det, obs = circ.compile_detector_sampler(seed=2025).sample(shots=N, separate_observables=True)
     det = det.astype(np.uint8)
     obs = obs.astype(np.uint8)
     assert det.shape == (N, sdem.num_detectors)