Create main_special.py

main_special.py

@@ -0,0 +1,67 @@
+# Lotto prediction with Genetic Algorithm and Mersenne Twister (MT19937)
+# Go Namhyeon <gnh1201@gmail.com>
+# first created: 2021-04-04
+# last updated: 2022-05-26
+# download excel data: https://dhlottery.co.kr/gameResult.do?method=byWin
+
+import math
+import random
+import pandas as pd
+import numpy as np
+from geneticalgorithm2 import geneticalgorithm2 as ga
+
+cols = [13, 14, 15, 16, 17, 18, 19]  # included bonus number
+df = pd.read_excel('excel.xlsx', skiprows=2, usecols=cols, names=[0, 1, 2, 3, 4, 5, 6])
+rows = df.values[:100]
+
+def step1():
+    data = []
+
+    i = 0
+    while i < len(rows):
+        cur = rows[i]
+
+        _rows = list(rows)[i+1:i+11]
+
+        showns = []
+        for row in _rows:
+            showns = sorted(list(set(showns) | set(row)))
+        notShowns = sorted(list(set(range(1, 46)) - set(showns)))
+        data.append({
+            'showns': showns,
+            'notShowns': notShowns
+        })
+
+        i = i + 1
+
+    return data
+
+data = step1()
+
+def get_numbers(lastData):
+    num = random.sample(range(1, 46), 7)
+    notShowns = lastData['notShowns']
+    return random.sample(list(set(num) | set(notShowns)), 6)
+
+def evaluate(nums):
+    _rows = list(rows)
+
+    score = 0
+    for row in _rows:
+        result = len(list(set(nums) & set(row)))
+        if result > 5:
+            score += 100
+        elif result > 4:
+            score += 75
+        elif result > 3:
+            score += 50
+        elif result > 2:
+            score += 25
+
+    return str(round((score / len(rows)) * 50, 2)) + '%'
+
+k = 0
+while k < 10:
+    nums = get_numbers(data[0])
+    k = k  + 1
+    print (evaluate(nums), nums)