67 lines
1.5 KiB
Python
67 lines
1.5 KiB
Python
# Lotto prediction with Genetic Algorithm and Mersenne Twister (MT19937)
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# Go Namhyeon <gnh1201@gmail.com>
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# first created: 2021-04-04
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# last updated: 2022-09-02
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# download excel data: https://dhlottery.co.kr/gameResult.do?method=byWin
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import math
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import random
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import pandas as pd
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import numpy as np
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cols = [13, 14, 15, 16, 17, 18, 19] # included bonus number
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df = pd.read_excel('excel.xlsx', skiprows=2, usecols=cols, names=[0, 1, 2, 3, 4, 5, 6])
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rows = df.values[:100]
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def step1():
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data = []
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i = 0
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while i < len(rows):
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cur = rows[i]
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_rows = list(rows)[i+1:i+11]
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showns = []
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for row in _rows:
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showns = sorted(list(set(showns) | set(row)))
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notShowns = sorted(list(set(range(1, 46)) - set(showns)))
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data.append({
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'showns': showns,
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'notShowns': notShowns
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})
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i = i + 1
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return data
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data = step1()
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def get_numbers(lastData):
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num = random.sample(range(1, 46), 7)
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notShowns = lastData['notShowns']
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return random.sample(list(set(num) | set(notShowns)), 6)
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def evaluate(nums):
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_rows = list(rows)
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score = 0
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for row in _rows:
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result = len(list(set(nums) & set(row)))
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if result > 5:
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score += 100
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elif result > 4:
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score += 75
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elif result > 3:
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score += 50
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elif result > 2:
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score += 25
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return str(round((score / len(rows)) * 50, 2)) + '%'
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k = 0
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while k < 10:
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nums = get_numbers(data[0])
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k = k + 1
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print (evaluate(nums), nums)
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