fixed drift

Author: Sigrid Tofte Thiis

.venv/Lib/site-packages/__editable___loop_algorithm_to_python_adaptive_0_0_1_finder.py

@@ -13,7 +13,7 @@
 
 class _EditableFinder:  # MetaPathFinder
     @classmethod
-    def find_spec(cls, fullname: str, path=None, target=None) -> ModuleSpec | None:  # type: ignore
+    def find_spec(cls, fullname: str, _path=None, _target=None) -> ModuleSpec | None:
         # Top-level packages and modules (we know these exist in the FS)
         if fullname in MAPPING:
             pkg_path = MAPPING[fullname]
@@ -59,7 +59,7 @@ def _paths(cls, fullname: str) -> list[str]:
         return [*paths, PATH_PLACEHOLDER]
 
     @classmethod
-    def find_spec(cls, fullname: str, target=None) -> ModuleSpec | None:  # type: ignore
+    def find_spec(cls, fullname: str, _target=None) -> ModuleSpec | None:
         if fullname in NAMESPACES:
             spec = ModuleSpec(fullname, None, is_package=True)
             spec.submodule_search_locations = cls._paths(fullname)

.venv/Lib/site-packages/__pycache__/__editable___loop_algorithm_to_python_adaptive_0_0_1_finder.cpython-310.pyc

@@ -1,9 +1,7 @@
-Metadata-Version: 2.4
+Metadata-Version: 2.1
 Name: loop-algorithm-to-python-adaptive
 Version: 0.0.1
 Summary: Adaptive wrapper around loop_to_python_api; currently backed by Sigridtt/LoopAlgorithmToPython.
 Requires-Python: >=3.10
-Requires-Dist: loop_to_python_api @ git+https://github.com/Sigridtt/LoopAlgorithmToPython.git@main
-Dynamic: requires-dist
-Dynamic: requires-python
-Dynamic: summary
+Requires-Dist: loop-to-python-api @ git+https://github.com/Sigridtt/LoopAlgorithmToPython.git@main
+

.venv/Lib/site-packages/loop_algorithm_to_python_adaptive-0.0.1.dist-info/METADATA

@@ -1,10 +1,10 @@
 __editable__.loop_algorithm_to_python_adaptive-0.0.1.pth,sha256=NLHFYcF1BYwgg8E0qHlcpxY3gaBQP5nqM473fvzFzWg,137
-__editable___loop_algorithm_to_python_adaptive_0_0_1_finder.py,sha256=PtEbSIGcwcyEC7o4zye2JxgUY5hh5uQBTrH3jOZsxx0,3488
+__editable___loop_algorithm_to_python_adaptive_0_0_1_finder.py,sha256=ntv3GaHlThcDfsqj07VCmjvm7_Wq-2bc2401L25LgZ8,3459
 __pycache__/__editable___loop_algorithm_to_python_adaptive_0_0_1_finder.cpython-310.pyc,,
 loop_algorithm_to_python_adaptive-0.0.1.dist-info/INSTALLER,sha256=zuuue4knoyJ-UwPPXg8fezS7VCrXJQrAP7zeNuwvFQg,4
-loop_algorithm_to_python_adaptive-0.0.1.dist-info/METADATA,sha256=p-K0zbktXM0eL6QpOdidSj_1zLXWe_CeJ75T5_7F5PQ,379
+loop_algorithm_to_python_adaptive-0.0.1.dist-info/METADATA,sha256=FJ0Cg-f533SwuqzC-3w8C09eAVJSMiLK_4ONhqkqAaM,313
 loop_algorithm_to_python_adaptive-0.0.1.dist-info/RECORD,,
 loop_algorithm_to_python_adaptive-0.0.1.dist-info/REQUESTED,sha256=47DEQpj8HBSa-_TImW-5JCeuQeRkm5NMpJWZG3hSuFU,0
-loop_algorithm_to_python_adaptive-0.0.1.dist-info/WHEEL,sha256=YCfwYGOYMi5Jhw2fU4yNgwErybb2IX5PEwBKV4ZbdBo,91
+loop_algorithm_to_python_adaptive-0.0.1.dist-info/WHEEL,sha256=Z4pYXqR_rTB7OWNDYFOm1qRk0RX6GFP2o8LgvP453Hk,91
 loop_algorithm_to_python_adaptive-0.0.1.dist-info/direct_url.json,sha256=j2jQexxlR_yrauPWl0SLW8l25_1T8b_H4sHDctuVMVI,116
 loop_algorithm_to_python_adaptive-0.0.1.dist-info/top_level.txt,sha256=p951YDFEMeriNiVzWVyr4CZDv9BG_ycPUjuk8d-MOmo,24

.venv/Lib/site-packages/loop_algorithm_to_python_adaptive-0.0.1.dist-info/RECORD

@@ -1,5 +1,5 @@
 Wheel-Version: 1.0
-Generator: setuptools (82.0.0)
+Generator: setuptools (70.3.0)
 Root-Is-Purelib: true
 Tag: py3-none-any
 

.venv/Lib/site-packages/loop_algorithm_to_python_adaptive-0.0.1.dist-info/WHEEL

@@ -20,7 +20,7 @@
 from typing import Any, Optional
 
 import numpy as np
-
+from loop_to_python_adaptive.autotune_prep import (AutotunePrepConfig, prepare_for_autotune_isf, )
 
 @dataclass(frozen=True)
 class AutotuneISFConfig:
@@ -251,6 +251,8 @@ def run_autotune_isf_iterations(
     df_windows: list,                   # list of pd.DataFrames, one per day
     *,
     loop_algorithm_inputs: list[dict],  # one per window, aligned with df_windows
+    pump_isf: float | None = None,      # original pump ISF, never changes
+    isf_current: float | None = None,   # yesterday's tuned ISF, carries forward
     n_iterations: int = 1,              # number of passes
     cfg: AutotuneISFConfig = AutotuneISFConfig(),
     json_history_list: list[list[dict]] | None = None,
@@ -279,14 +281,17 @@ def run_autotune_isf_iterations(
         isf_history  : List of ISF values after each iteration (length = n_iterations).
         last_result  : Full result dict from the final tune_isf() call.
     """
-    from loop_to_python_adaptive.autotune_prep import (
-        AutotunePrepConfig,
-        prepare_for_autotune_isf,
-    )
-    pump_isf = extract_pump_isf(loop_algorithm_inputs[0])
+
+    # pump_isf is the unchanging anchor for safety caps
+    if pump_isf is None:
+        pump_isf = extract_pump_isf(loop_algorithm_inputs[0])
     pump_basal = extract_pump_basal(loop_algorithm_inputs[0])
     pump_cr = extract_pump_cr(loop_algorithm_inputs[0])
 
+    # isf_current is what we tune from — starts at pump_isf on day 1
+    if isf_current is None:
+        isf_current = pump_isf   
+
     isf_current = pump_isf
     isf_history: list[float] = []
     last_result: dict[str, Any] = {}
@@ -313,6 +318,10 @@ def run_autotune_isf_iterations(
             if json_history_list is not None and i < len(json_history_list)
             else None
             )
+            carb_entries = loop_input.get("carbEntries", [])
+            print(f"    carb entries in loop_input: {len(carb_entries)}")
+            if carb_entries:
+                print(f"    first: {carb_entries[0]}")
             result = prepare_for_autotune_isf(
                 df_window,
                 loop_algorithm_input=loop_input,
@@ -322,6 +331,7 @@ def run_autotune_isf_iterations(
             window_isf_points = result["ISFGlucoseData"]
             all_isf_points.extend(window_isf_points)
             print(f"{len(window_isf_points)} ISF points")
+            print(f"    CSF={len(result['CSFGlucoseData'])} ISF={len(result['ISFGlucoseData'])} basal={len(result['basalGlucoseData'])} UAM={len(result['UAMGlucoseData'])}")
 
         print(f"  Total ISF points this iteration: {len(all_isf_points)}")
 

loop_to_python_adaptive/__pycache__/autotune_isf.cpython-310.pyc

@@ -139,7 +139,11 @@ def generate_bgi_series_from_predictions(
       - It is consistent with oref0's intent (BGI = expected BG change per 5min
         from insulin alone)
     """
+    # In generate_bgi_series_from_predictions, add this as the first line after `out = _to_utc_index(df)`:
+    
     out = _to_utc_index(df)
+    if not json_history:
+        return pd.Series(float("nan"), index=out.index, dtype="float64")
 
     bgi_points: dict[pd.Timestamp, float] = {}