# -*- coding: utf-8 -*-
"""
learnstock.pyプログラム
単純な帰納的学習の例題プログラム
パターン学習器
100個の学習データを読み込んで、
適合する10桁の2進数パターンを答えます
使い方 C:\>python learnstock.py < ldata.txt
"""
 
# モジュールのインポート
import math
import random
 
# グローバル変数
SETSIZE = 100 # 学習データセットの大きさ
CNO = 10      # 学習データの桁数 (10桁分)
GENMAX = 10000 # 解候補生成回数
SEED = 7       # 乱数のシード
 
# 下請け関数の定義
# readdata()関数
def readdata(data, teacher):
    """学習データセットの読み込み"""
    for i in range(SETSIZE):
        line = input()
        data[i] = [int(num) for num in line.split()]
        teacher[i] = data[i][CNO]
    return
# readdata()関数の終わり
 
# calcscore()関数
def calcscore(data, teacher, answer):
    """解候補パターンのスコア(0~SETSIZE点)の計算"""
    score = 0  # スコア (0~SETSIZE点)
    for i in range(SETSIZE):
        # 一致度計算
        point = 0
        for j in range(CNO):
            if answer[j] == 2:
                point += 1 # ワイルドカード
            elif answer[j] == data[i][j]:
                point += 1 # 一致
        # スコアの計算
        if (point == CNO) and (teacher[i] == 1):
            score += 1
        elif (point != CNO) and (teacher[i] == 0):
            score += 1
    return score
# calcscore()関数の終わり
 
# メイン実行部
score = 0                   # スコア (0~SETSIZE点)
answer = [0 for i in range(CNO)]    # 解候補
data = [[] for i in range(SETSIZE)] # 学習データセット
teacher = [0 for i in range(SETSIZE)] # 教師データ
bestscore = 0                 # スコアの最高値
bestanswer = [0 for i in range(CNO)] # 探索中での最良解
 
# 乱数の初期化
random.seed(SEED)
 
# 学習データセットの読み込み
readdata(data, teacher)
 
# 解候補生成と検査
for i in range(GENMAX):
    # 解候補生成
    for j in range(CNO):
        answer[j] = random.randint(0, 2)
 
    # 検査
    score = calcscore(data, teacher, answer)
 
    # 最良スコアの更新
    if (score > bestscore):
        bestanswer = answer.copy()
        bestscore = score
        print(bestanswer, ":score=", bestscore)
 
# 最良解の出力
print("最良解")
print(bestanswer, ":score=", bestscore)
# learnstock.pyの終わり

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