Default missing summarize MTT flag

src/pyrecest/evaluation/summarize_filter_results.py

@@ -38,7 +38,7 @@ def summarize_filter_results(
         warnings.warn("Using less than 1000 runs. This may lead to unreliable results.")
 
     extract_mean = get_extract_mean(
-        scenario_config["manifold"], mtt_scenario=scenario_config["mtt"]
+        scenario_config["manifold"], mtt_scenario=scenario_config.get("mtt", False)
     )
     distance_function = get_distance_function(scenario_config["manifold"])
     errors_all = determine_all_deviations(

tests/test_evaluation_summarize_missing_mtt.py

@@ -0,0 +1,34 @@
+import numpy as np
+import pytest
+
+import pyrecest.backend
+from pyrecest.evaluation import summarize_filter_results
+
+
+@pytest.mark.skipif(
+    pyrecest.backend.__backend_name__ in ("pytorch", "jax"),
+    reason="Not supported on this backend",
+)
+def test_summarize_filter_results_defaults_missing_mtt_flag():
+    n_runs = 2
+    groundtruths = np.empty((n_runs, 1), dtype=object)
+    for run in range(n_runs):
+        groundtruths[run, 0] = np.array([float(run), 0.0])
+
+    last_estimates = np.array([[[0.0, 0.0], [1.0, 0.0]]])
+    runtimes = np.ones((1, n_runs))
+    run_failed = np.zeros((1, n_runs), dtype=bool)
+    filter_configs = [{"name": "kf", "parameter": None}]
+
+    summarized = summarize_filter_results(
+        scenario_config={"manifold": "Euclidean"},
+        filter_configs=filter_configs,
+        runtimes=runtimes,
+        groundtruths=groundtruths,
+        run_failed=run_failed,
+        last_estimates=last_estimates,
+    )
+
+    assert summarized is filter_configs
+    assert summarized[0]["error_mean"] == 0
+    assert summarized[0]["failure_rate"] == 0