Move ReliabilityCalculator class to a separate file

Author: onlaj

core/elo.py

@@ -1,85 +1,4 @@
 # core/elo.py
-import math
-
-import math
-
-import math
-
-
-class ReliabilityCalculator:
-    """
-    Provides improved reliability metrics for ELO-based ranking systems.
-
-    The improved model uses a combination of:
-    - Quick initial gains (logarithmic component)
-    - Steady improvement (linear component)
-    - Asymptotic approach to perfect reliability
-
-    The formula is designed to match observed behavior of ELO and Glicko2 systems.
-    """
-
-    @staticmethod
-    def calculate_reliability(n: int, v: int) -> float:
-        """
-        Calculate current reliability percentage of the ranking system.
-
-        Args:
-            n: Number of media items in the system (n > 0)
-            v: Total number of votes cast (v >= 0)
-
-        Returns:
-            float: Reliability percentage between 0-100
-        """
-        if n <= 0 or v < 0:
-            return 0.0
-
-        # Start from 50% (random ordering)
-        base_reliability = 50.0
-
-        # Quick initial gains component
-        votes_per_item = v / n
-        initial_gain = 25.0 * (1 - math.exp(-votes_per_item / 2))
-
-        # Steady improvement component
-        steady_gain = 20.0 * (1 - math.exp(-votes_per_item / 10))
-
-        # Asymptotic final approach
-        final_gain = 5.0 * (1 - math.exp(-votes_per_item / 50))
-
-        reliability = base_reliability + initial_gain + steady_gain + final_gain
-
-        # Cap at 100%
-        return min(100.0, reliability)
-
-    @staticmethod
-    def calculate_required_votes(n: int, target_reliability: float) -> int:
-        """
-        Calculate votes needed to reach a desired reliability level.
-
-        Args:
-            n: Number of media items in the system (n > 0)
-            target_reliability: Desired reliability percentage (0 < R < 100)
-
-        Returns:
-            int: Minimum votes required (rounded up to nearest integer)
-        """
-        if n <= 0 or target_reliability <= 50 or target_reliability >= 100:
-            return 0
-
-        # Using binary search to find required votes
-        low, high = 0, n * 1000
-        while low < high:
-            mid = (low + high) // 2
-            reliability = ReliabilityCalculator.calculate_reliability(n, mid)
-
-            if abs(reliability - target_reliability) < 0.1:
-                return mid
-            elif reliability < target_reliability:
-                low = mid + 1
-            else:
-                high = mid - 1
-
-        return low
 
 
 class Rating:

core/reliability_calculator.py

@@ -0,0 +1,77 @@
+import math
+
+
+class ReliabilityCalculator:
+    """
+    Provides improved reliability metrics for ELO-based ranking systems.
+
+    The improved model uses a combination of:
+    - Quick initial gains (logarithmic component)
+    - Steady improvement (linear component)
+    - Asymptotic approach to perfect reliability
+
+    The formula is designed to match observed behavior of ELO and Glicko2 systems.
+    """
+
+    @staticmethod
+    def calculate_reliability(n: int, v: int) -> float:
+        """
+        Calculate current reliability percentage of the ranking system.
+
+        Args:
+            n: Number of media items in the system (n > 0)
+            v: Total number of votes cast (v >= 0)
+
+        Returns:
+            float: Reliability percentage between 0-100
+        """
+        if n <= 0 or v < 0:
+            return 0.0
+
+        # Start from 50% (random ordering)
+        base_reliability = 50.0
+
+        # Quick initial gains component
+        votes_per_item = v / n
+        initial_gain = 25.0 * (1 - math.exp(-votes_per_item / 2))
+
+        # Steady improvement component
+        steady_gain = 20.0 * (1 - math.exp(-votes_per_item / 10))
+
+        # Asymptotic final approach
+        final_gain = 5.0 * (1 - math.exp(-votes_per_item / 50))
+
+        reliability = base_reliability + initial_gain + steady_gain + final_gain
+
+        # Cap at 100%
+        return min(100.0, reliability)
+
+    @staticmethod
+    def calculate_required_votes(n: int, target_reliability: float) -> int:
+        """
+        Calculate votes needed to reach a desired reliability level.
+
+        Args:
+            n: Number of media items in the system (n > 0)
+            target_reliability: Desired reliability percentage (0 < R < 100)
+
+        Returns:
+            int: Minimum votes required (rounded up to nearest integer)
+        """
+        if n <= 0 or target_reliability <= 50 or target_reliability >= 100:
+            return 0
+
+        # Using binary search to find required votes
+        low, high = 0, n * 1000
+        while low < high:
+            mid = (low + high) // 2
+            reliability = ReliabilityCalculator.calculate_reliability(n, mid)
+
+            if abs(reliability - target_reliability) < 0.1:
+                return mid
+            elif reliability < target_reliability:
+                low = mid + 1
+            else:
+                high = mid - 1
+
+        return low

db/database.py

@@ -5,7 +5,8 @@
 from pathlib import Path
 from typing import List, Tuple, Optional
 
-from core.elo import ReliabilityCalculator
+from core.reliability_calculator import ReliabilityCalculator
+
 logger = logging.getLogger(__name__)
 
 

gui/albums_tab.py

@@ -8,7 +8,7 @@
 from PyQt6.QtCore import pyqtSignal, Qt, QSortFilterProxyModel, QSize
 import math
 
-from core.elo import ReliabilityCalculator
+from core.reliability_calculator import ReliabilityCalculator
 
 
 class AlbumsTab(QWidget):

gui/voting_tab.py

@@ -5,7 +5,8 @@
 from PyQt6.QtWidgets import (QWidget, QVBoxLayout, QHBoxLayout, QPushButton,
                              QLabel, QFrame, QSizePolicy)
 
-from core.elo import Rating, ReliabilityCalculator
+from core.elo import Rating
+from core.reliability_calculator import ReliabilityCalculator
 from core.media_utils import set_file_info, handle_video_single_click, handle_video_events
 from core.preview_handler import MediaPreview
 from core.media_utils import AspectRatioWidget

tests/test_glicko2.py

@@ -5,7 +5,8 @@
 import numpy as np
 import pytest
 
-from core.elo import ReliabilityCalculator, Rating
+from core.elo import Rating
+from core.reliability_calculator import ReliabilityCalculator
 from core.glicko2 import Glicko2Rating
 
 
@@ -118,7 +119,7 @@ def simulate_and_plot(n: int, seed: int) -> dict:
         total_votes += 1
 
         # Record data every 1 votes
-        if total_votes % 1 == 0:
+        if total_votes % 10 == 0:
             votes_data.append(total_votes)
             calc_reliability_data.append(current_calc)
 

tests/test_reliability.py

@@ -3,7 +3,8 @@
 import matplotlib.pyplot as plt
 import pytest
 
-from core.elo import ReliabilityCalculator, Rating
+from core.elo import Rating
+from core.reliability_calculator import ReliabilityCalculator
 
 
 class Media: