From 34713232e391fd18c5d47e0fa4950d8e22731a11 Mon Sep 17 00:00:00 2001
From: Connor Olding <cloningdonor@gmail.com>
Date: Sun, 7 May 2023 06:44:01 -0700
Subject: [PATCH] move experimental scoring method to its own file

---
 thursday/utilities/__init__.py |  1 +
 thursday/utilities/scoring.py  | 47 ++++++++++++++++++++++++++++++++
 thursday/utilities/utils.py    | 49 ----------------------------------
 3 files changed, 48 insertions(+), 49 deletions(-)
 create mode 100644 thursday/utilities/scoring.py

diff --git a/thursday/utilities/__init__.py b/thursday/utilities/__init__.py
index 79b9211..e85f74d 100644
--- a/thursday/utilities/__init__.py
+++ b/thursday/utilities/__init__.py
@@ -1,5 +1,6 @@
 from .colors import *
 from .prog80 import prog
+from .scoring import *
 from .utils import *
 
 try:
diff --git a/thursday/utilities/scoring.py b/thursday/utilities/scoring.py
new file mode 100644
index 0000000..02dd04e
--- /dev/null
+++ b/thursday/utilities/scoring.py
@@ -0,0 +1,47 @@
+def perform_another_experimental_scoring_method(results):
+    if len(results) and len(something := next(iter(results.values()))[0]) == 3:
+        history_length = len(something[2])
+        each = {}
+        # for i in (history_length - 1,):
+        for i in range(history_length):
+            # for k, v in results.items(): for vi in v: assert len(vi) == 3, vi
+            l = {k: [(res[2][i], res[1]) for res in v] for k, v in results.items()}
+            for k, v in perform_another_experimental_scoring_method(l).items():
+                each.setdefault(k, []).append(v)
+        return {k: sum(v) / len(v) for k, v in each.items()}
+
+    new_results = {}
+    all_opt_names = set()
+    for obj_name, obj_res in results.items():
+        all_res = {}
+        for fopt, opt_name in obj_res:
+            all_res.setdefault(fopt, []).append(opt_name)
+            all_opt_names.add(opt_name)
+        new_results[obj_name] = dict(sorted(all_res.items()))
+
+    limited_by_floating_point_precision = 53
+
+    best_ranks_and_counts = {}
+    for outer_rank in range(1, limited_by_floating_point_precision + 1):
+        for obj_name, all_res in new_results.items():
+            for fopt, opt_names in all_res.items():
+                dirty = False
+                for opt_name in set(opt_names):
+                    if opt_name in best_ranks_and_counts:
+                        rank, count = best_ranks_and_counts[opt_name]
+                        if rank == outer_rank:
+                            best_ranks_and_counts[opt_name] = (rank, count + 1)
+                            dirty = True
+                    else:
+                        best_ranks_and_counts[opt_name] = (outer_rank, 1)
+                        dirty = True
+                if dirty:
+                    break
+
+    scores = {k: 0.0 for k in all_opt_names}
+    for opt_name, (rank, count) in best_ranks_and_counts.items():
+        points = 2 ** (1 - rank)
+        count = min(count, limited_by_floating_point_precision)
+        scores[opt_name] = score = sum(points / 2**i for i in range(count))
+
+    return scores
diff --git a/thursday/utilities/utils.py b/thursday/utilities/utils.py
index f46fdc1..d9f7e2e 100644
--- a/thursday/utilities/utils.py
+++ b/thursday/utilities/utils.py
@@ -153,55 +153,6 @@ class AcquireForWriting:
             # move(self._altpath, self.filepath)  # assumes os.rename overwrites files
 
 
-def perform_another_experimental_scoring_method(results):
-    if len(results) and len(something := next(iter(results.values()))[0]) == 3:
-        history_length = len(something[2])
-        each = {}
-        # for i in (history_length - 1,):
-        for i in range(history_length):
-            # for k, v in results.items(): for vi in v: assert len(vi) == 3, vi
-            l = {k: [(res[2][i], res[1]) for res in v] for k, v in results.items()}
-            for k, v in perform_another_experimental_scoring_method(l).items():
-                each.setdefault(k, []).append(v)
-        return {k: sum(v) / len(v) for k, v in each.items()}
-
-    new_results = {}
-    all_opt_names = set()
-    for obj_name, obj_res in results.items():
-        all_res = {}
-        for fopt, opt_name in obj_res:
-            all_res.setdefault(fopt, []).append(opt_name)
-            all_opt_names.add(opt_name)
-        new_results[obj_name] = dict(sorted(all_res.items()))
-
-    limited_by_floating_point_precision = 53
-
-    best_ranks_and_counts = {}
-    for outer_rank in range(1, limited_by_floating_point_precision + 1):
-        for obj_name, all_res in new_results.items():
-            for fopt, opt_names in all_res.items():
-                dirty = False
-                for opt_name in set(opt_names):
-                    if opt_name in best_ranks_and_counts:
-                        rank, count = best_ranks_and_counts[opt_name]
-                        if rank == outer_rank:
-                            best_ranks_and_counts[opt_name] = (rank, count + 1)
-                            dirty = True
-                    else:
-                        best_ranks_and_counts[opt_name] = (outer_rank, 1)
-                        dirty = True
-                if dirty:
-                    break
-
-    scores = {k: 0.0 for k in all_opt_names}
-    for opt_name, (rank, count) in best_ranks_and_counts.items():
-        points = 2 ** (1 - rank)
-        count = min(count, limited_by_floating_point_precision)
-        scores[opt_name] = score = sum(points / 2**i for i in range(count))
-
-    return scores
-
-
 def needs_rerun(key, value):
     if value["duration"] < 0.0 or "history" not in value:
         return True