Add one to each variable to be inclusive of entire set

lottery_predictor/analyze.py

@@ -1,15 +1,16 @@
-from collections import Counter
 from datetime import datetime
-from itertools import combinations
+from collections import Counter
 
 import numpy as np
 import pandas as pd
-from sklearn.ensemble import RandomForestRegressor
+from sklearn.ensemble import RandomForestClassifier
 from sqlalchemy import select
 
-from data.database import Base, dal
+from data.database import Base, dal, project_variables
 import util.drawing as drawutil
 
+RANDOM_SEED = 42
+
 
 def load_dataframe(
         table_name: str, start_date: datetime | None = None, end_date: datetime | None = None
@@ -124,78 +125,3 @@ def get_cold_numbers(probabilities: dict[int, float], bottom: int = 5) -> list[t
     :returns list of tuples: A list of the hot numbers and their raw score
     """
     return sorted(probabilities.items(), key=lambda item: item[1])[:bottom]
-
-
-"""
-def extract_features(row):
-    balls = [row['main_ball1'], row['main_ball2'], row['main_ball3'], row['main_ball4'], row['main_ball5']]
-    pd.Series({
-        'sum': sum(balls),
-        'mean': np.mean(balls),
-        'std': np.std(balls),
-        'even_count': len([b for b in balls if b % 2 == 0]),
-        'range': max(balls) - min(balls)
-    })
-
-# Melt the 5 ball columns into one long column of numbers
-melted = df.melt(id_vars=['draw_date'], value_vars=['ball1', 'ball2', 'ball3', 'ball4', 'ball5'], value_name='number')
-
-# Find the most recent date each number appeared
-last_seen = melted.groupby('number')['draw_date'].max()
-
-# calculate days overdue relative to today
-current_date = datetime.now()
-overdue_days = (current_date - last_seen).dt.days
-
-# sort to find the "most overdue" at the top
-most_overdue = overdue_days.sort_values(ascending=False)
-
-# print the 10 most overdue
-print(most_overdue.head(10))
-
-game_ball_last_seen = df.groupby('powerball')['draw_date'].max() # or 'mega-ball'
-game_ball_overdue = (current_date - game_ball_last_seen).dt.days.soft_values(ascending=False)
-
-features = np.apply(extract_features, axis=1)
-y = np.ones(len(data_frame))
-# train a model to recognize what a "winning" set looks like
-model = RandomForestRegressor(n_estimators=100)
-model.fit(features, y)
-
-# Sample: Generate combinations from the top 15 most frequent/overdue numbers
-target_numbers = most_overdue.head(15).index.tolist()
-candidate_sets = list(combinations(target_numbers, 2))
-
-results = []
-for s in candidate_sets:
-    # Create features for this hypothetical set
-    s_feat = extract_features({'main_ball1': s[0], 'main_ball2': s[1], 'main_ball3': s[2], 'main_ball4': s[3],
-        'main_ball5': s[4]})
-
-    # Model predicts how closely this matches historical 'winning' patterns
-    score = model.predict(s_feat.values.reshape(1, -1))[0]
-    results.append({'set': s, 'score': score})
-
-# Rank by score
-ranked_sets = pd.DataFrame(results).sort_values(by='score', ascending=False)
-
-# Get frequency counts
-counts = melted['number'].value_counts(normalize=True)
-
-def calc_prob(s):
-    return np.prod([counts.get(num, 0) for num in s])
-
-ranked_sets['statistical_prob'] = ranked_sets['set'].apply(calc_prob)
-
-game_counts = df['game_ball'].value_counts(normalize=True)
-
-def calc_total_prob(row):
-    # calculate prob for the 5 main balls
-    five_ball_prob = np.prod([counts.get(num, 0) for num in row['set']])
-    # multiply the prob of the specific game ball
-    game_prob = game_counts.get(row['game_ball'], 0)
-    return five_ball_prob * game_prob
-
-ranked_sets['total_prob'] = ranked_sets.apply(calc_total_prob, axis=1)
-
-"""

lottery_predictor/draw.py

@@ -11,6 +11,6 @@ def generate_random_ticket(max_main: int, max_game: int, num_main: int = 5) -> t
 
     :returns: A tuple of (main_balls, game_ball)
     """
-    main_balls = random.sample(range(1, max_main), num_main)
+    main_balls = random.sample(range(1, max_main + 1), num_main)
-    game_ball = random.randint(1, max_game)
+    game_ball = random.randint(1, max_game + 1)
     return sorted(main_balls), game_ball