自走棋羁绊搭配算法
作者:互联网
自走棋羁绊搭配算法
#!/usr/bin/python3
# -*- coding: utf-8 -*-
"""
author: tuzichun
ps : zl-sb
"""
import numpy as np
import pandas as pd
from itertools import combinations
class Chess(object):
# 初始化中给对象属性赋值
def __init__(self, trammels_x, trammels_y, name):
self.X = trammels_x
self.Y = trammels_y
self.NAME = name
def __str__(self):
return self.NAME
class Possibility(object):
def __init__(self, chess_list):
self.object_list = chess_list
x_set = set()
y_set = set()
value_set = set()
for wtf in self.object_list:
x_set.add(wtf.X)
y_set.add(wtf.Y)
value_set.add(wtf.NAME)
self.value = len(x_set) + len(y_set)
self.count = len(value_set)
def __str__(self):
result = ""
for wtf in self.object_list:
result = result.join(wtf.NAME) + ","
return result
def generate_chess():
# 读取数据
result = []
csv_result = pd.read_csv("2321.csv", index_col=0)
index_count = csv_result.shape[0]
column_count = csv_result.shape[1]
for wtf_x in range(0, index_count):
for wtf_y in range(0, column_count):
value = csv_result.iloc[wtf_x, wtf_y]
if value != np.NAN:
result.append(Chess(wtf_x, wtf_y, value))
return result
if __name__ == '__main__':
Chess_list = generate_chess()
dataframe_result = pd.DataFrame(columns=['combination', 'value', 'count'])
for x in range(3, 11):
dataframe_result_part = pd.DataFrame(columns=['combination', 'value', 'count'])
a = []
res = list(combinations(Chess_list, x))
if len(res) != 0:
for y in res:
y = list(y)
deal = Possibility(y)
if deal.value != 2 * x:
dataframe_result_part['combination'].append(str(deal))
dataframe_result_part['value'].append(deal.value)
dataframe_result_part['count'].append(deal.count)
else:
continue
dataframe_result.append(dataframe_result_part)
dataframe_result = dataframe_result.sort_values(by=["value", "count"], ascending=(True, False))
dataframe_result.to_csv("1.csv")
标签:__,set,self,羁绊,value,算法,result,wtf,走棋 来源: https://www.cnblogs.com/tuzichun/p/15819551.html