golden optimizer

meteor/scripts/compute_difference_map.py

@@ -20,10 +20,6 @@
 log = structlog.get_logger()
 
 
-# TO OPTMIZE
-TV_WEIGHTS_TO_SCAN = np.linspace(0.0, 0.1, 101)
-
-
 class TvDiffmapArgParser(DiffmapArgParser):
     def __init__(self, *args: Any, **kwargs: Any) -> None:
         super().__init__(*args, **kwargs)
@@ -153,16 +149,11 @@ def denoise_diffmap_according_to_mode(
     """
     if tv_denoise_mode == WeightMode.optimize:
         log.info(
-            "Searching for max-negentropy TV denoising weight",
-            min=np.min(TV_WEIGHTS_TO_SCAN),
-            max=np.max(TV_WEIGHTS_TO_SCAN),
-            points_to_test=len(TV_WEIGHTS_TO_SCAN),
+            "Searching for max-negentropy TV denoising weight", method="golden ration optimization"
         )
         log.info("This may take some time...")
 
-        final_map, metadata = tv_denoise_difference_map(
-            diffmap, full_output=True, weights_to_scan=TV_WEIGHTS_TO_SCAN
-        )
+        final_map, metadata = tv_denoise_difference_map(diffmap, full_output=True)
 
         log.info(
             "Optimal TV weight found",

meteor/settings.py

@@ -1,12 +1,12 @@
 from __future__ import annotations
 
-TV_WEIGHT_RANGE: tuple[float, float] = (0.0, 1.0)
+TV_WEIGHT_RANGE: tuple[float, float] = (0.0, 0.05)  # for golden optimization
 TV_STOP_TOLERANCE: float = 0.00000005
 TV_MAX_NUM_ITER: int = 50
 MAP_SAMPLING: int = 3
 
 KWEIGHT_PARAMETER_DEFAULT: float = 0.05
-TV_WEIGHT_DEFAULT: float = 0.01  # TO OPTIMIZE
+TV_WEIGHT_DEFAULT: float = 0.01
 
 COMPUTED_MAP_RESOLUTION_LIMIT: float = 1.0
 GEMMI_HIGH_RESOLUTION_BUFFER: float = 1e-6

test/functional/test_compute_difference_map.py

@@ -1,5 +1,4 @@
 from pathlib import Path
-from unittest import mock
 
 import numpy as np
 import pytest
@@ -11,10 +10,7 @@
 from meteor.tv import TvDenoiseResult
 from meteor.utils import filter_common_indices
 
-TV_WEIGHTS_TO_SCAN = np.array([0.005, 0.01, 0.025, 0.5])
 
-
-@mock.patch("meteor.scripts.compute_difference_map.TV_WEIGHTS_TO_SCAN", TV_WEIGHTS_TO_SCAN)
 @pytest.mark.parametrize("kweight_mode", list(WeightMode))
 @pytest.mark.parametrize("tv_weight_mode", list(WeightMode))
 def test_script_produces_consistent_results(

test/unit/scripts/test_compute_difference_map.py

@@ -5,7 +5,6 @@
 from typing import Any
 from unittest import mock
 
-import numpy as np
 import pytest
 
 from meteor.rsmap import Map
@@ -18,10 +17,6 @@
 )
 from meteor.tv import TvDenoiseResult
 
-# ensure tests complete quickly by monkey-patching a limited number of weights
-compute_difference_map.TV_WEIGHTS_TO_SCAN = np.linspace(0.0, 0.1, 6)
-
-
 TV_WEIGHT = 0.1
 
 
@@ -80,7 +75,8 @@ def test_denoise_diffmap_according_to_mode(mode: WeightMode, random_difference_m
     assert isinstance(metadata, TvDenoiseResult)
 
     if mode == WeightMode.optimize:
-        assert metadata.optimal_weight in [0.04, 0.06]  # random test; alternates
+        # random test; changes
+        assert 0.04 < metadata.optimal_weight < 0.06
 
     elif mode == WeightMode.fixed:
         assert metadata.optimal_weight == TV_WEIGHT