Make calibration hotfixes reload-safe

src/pyrecest/calibration/__init__.py

@@ -27,6 +27,30 @@
         "times_s",
     }
 )
+_ORIGINAL_AGGREGATE_SUMMARY_METRIC_ATTR = (
+    "_pyrecest_original_aggregate_summary_metric"
+)
+_ORIGINAL_AGGREGATE_TIME_OFFSET_SWEEPS_ATTR = (
+    "_pyrecest_original_aggregate_time_offset_sweeps"
+)
+_ORIGINAL_BIAS_NUMERIC_ARRAY_ATTR = "_pyrecest_original_bias_as_numeric_array"
+_ORIGINAL_BIAS_NONNEGATIVE_INT_ATTR = "_pyrecest_original_bias_as_nonnegative_int"
+_ORIGINAL_BIAS_NONNEGATIVE_FINITE_FLOAT_ATTR = (
+    "_pyrecest_original_bias_as_nonnegative_finite_float"
+)
+
+if not hasattr(_time_offset_module, _ORIGINAL_AGGREGATE_SUMMARY_METRIC_ATTR):
+    setattr(
+        _time_offset_module,
+        _ORIGINAL_AGGREGATE_SUMMARY_METRIC_ATTR,
+        _time_offset_module._aggregate_summary_metric,
+    )
+if not hasattr(_time_offset_module, _ORIGINAL_AGGREGATE_TIME_OFFSET_SWEEPS_ATTR):
+    setattr(
+        _time_offset_module,
+        _ORIGINAL_AGGREGATE_TIME_OFFSET_SWEEPS_ATTR,
+        _time_offset_module.aggregate_time_offset_sweeps,
+    )
 
 
 def _is_rejected_real_scalar(value: Any) -> bool:
@@ -118,7 +142,9 @@ def _as_nonnegative_summary_count(value: Any, name: str) -> float:
     return result
 
 
-_base_aggregate_summary_metric = _time_offset_module._aggregate_summary_metric
+_base_aggregate_summary_metric = getattr(
+    _time_offset_module, _ORIGINAL_AGGREGATE_SUMMARY_METRIC_ATTR
+)
 
 
 def _aggregate_summary_metric(
@@ -145,9 +171,34 @@ def _aggregate_summary_metric(
 
 from . import bias as _bias_module  # noqa: E402
 
-_base_bias_as_numeric_array = _bias_module._as_numeric_array
-_base_bias_as_nonnegative_int = _bias_module._as_nonnegative_int
-_base_bias_as_nonnegative_finite_float = _bias_module._as_nonnegative_finite_float
+if not hasattr(_bias_module, _ORIGINAL_BIAS_NUMERIC_ARRAY_ATTR):
+    setattr(
+        _bias_module,
+        _ORIGINAL_BIAS_NUMERIC_ARRAY_ATTR,
+        _bias_module._as_numeric_array,
+    )
+if not hasattr(_bias_module, _ORIGINAL_BIAS_NONNEGATIVE_INT_ATTR):
+    setattr(
+        _bias_module,
+        _ORIGINAL_BIAS_NONNEGATIVE_INT_ATTR,
+        _bias_module._as_nonnegative_int,
+    )
+if not hasattr(_bias_module, _ORIGINAL_BIAS_NONNEGATIVE_FINITE_FLOAT_ATTR):
+    setattr(
+        _bias_module,
+        _ORIGINAL_BIAS_NONNEGATIVE_FINITE_FLOAT_ATTR,
+        _bias_module._as_nonnegative_finite_float,
+    )
+
+_base_bias_as_numeric_array = getattr(
+    _bias_module, _ORIGINAL_BIAS_NUMERIC_ARRAY_ATTR
+)
+_base_bias_as_nonnegative_int = getattr(
+    _bias_module, _ORIGINAL_BIAS_NONNEGATIVE_INT_ATTR
+)
+_base_bias_as_nonnegative_finite_float = getattr(
+    _bias_module, _ORIGINAL_BIAS_NONNEGATIVE_FINITE_FLOAT_ATTR
+)
 
 
 def _as_bias_numeric_array(value: Any, name: str) -> np.ndarray:
@@ -194,7 +245,6 @@ def _as_numeric_vector(value: Any, name: str) -> np.ndarray:
     _aggregate_std_metric,
     _validate_error_metric,
 )
-from .time_offset import aggregate_time_offset_sweeps as _aggregate_time_offset_sweeps
 from .time_offset import (  # noqa: E402
     apply_time_offset,
     fit_time_offset,
@@ -205,6 +255,10 @@ def _as_numeric_vector(value: Any, name: str) -> np.ndarray:
     time_offset_sweep,
 )
 
+_base_aggregate_time_offset_sweeps = getattr(
+    _time_offset_module, _ORIGINAL_AGGREGATE_TIME_OFFSET_SWEEPS_ATTR
+)
+
 
 def aggregate_time_offset_sweeps(
     sweeps: Iterable[Iterable[Mapping[str, float]]],
@@ -215,7 +269,7 @@ def aggregate_time_offset_sweeps(
 
     metric = _validate_error_metric(metric)
     materialized_sweeps = [list(sweep) for sweep in sweeps]
-    rows = _aggregate_time_offset_sweeps(materialized_sweeps, metric=metric)
+    rows = _base_aggregate_time_offset_sweeps(materialized_sweeps, metric=metric)
     if metric == "std":
         return rows
 

tests/calibration/test_calibration_reload.py

@@ -0,0 +1,35 @@
+import importlib
+
+import numpy as np
+import pyrecest.calibration as calibration
+
+
+def _summary_row() -> dict[str, float]:
+    return {
+        "time_offset_s": 0.0,
+        "count": 1.0,
+        "mean": 1.0,
+        "std": 0.0,
+        "rmse": 1.0,
+        "p95": 1.0,
+        "max": 1.0,
+    }
+
+
+def test_calibration_hotfixes_are_reload_idempotent():
+    module = calibration
+
+    for _ in range(2):
+        module = importlib.reload(module)
+
+        aggregated = module.aggregate_time_offset_sweeps([[_summary_row()]])
+        assert aggregated[0]["rmse"] == 1.0
+
+        examples = module.make_bias_training_examples(
+            measurement_times_s=np.array([0.0]),
+            measurement_values=np.array([[2.0]]),
+            reference_times_s=np.array([0.0]),
+            reference_values=np.array([[1.0]]),
+            max_time_delta_s=None,
+        )
+        np.testing.assert_array_equal(examples.residual, np.array([[1.0]]))