保姆级手把手教你用python实现关系矩阵的性质判断教程

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 所有的情况都讲完了，下面上完整的示范代码（没有numpy库记得pip install numpy）：

import numpy as np


class RelationMatrix():
    def __init__(self):
        self.matrix = None

    def getMatrix(self):
        GUIDANCE = """请以字符串形式输入关系矩阵,输入python列表形式的字符串,如:
            |1,0,1|
            |1,0,0|
            |0,0,0|
            则输入:[[1,0,1],[1,0,0],[0,0,0]]
            输入数据时不要换行!
        """
        print(GUIDANCE)
        self.matrix = np.array(eval(input("请输入关系矩阵:")))
        print(self.matrix)

    def isReflexive(self):
        if (self.matrix.diagonal() == 1).all():
            return True
        else:
            return False

    def isAntiReflexive(self):
        if (self.matrix.diagonal() == 0).all():
            return True
        else:
            return False

    def isSymmetry(self):
        if (self.matrix.T == self.matrix).all():
            return True
        else:
            return False

    def isAntiSymmetric(self):
        matrix = self.matrix.copy()
        np.fill_diagonal(matrix, 0)
        product = matrix * matrix.T
        if np.count_nonzero(product) == 0:
            return True
        else:
            return False

    def isTransitive(self):
        indexes = (np.argwhere(self.matrix == 1)).tolist()
        for i in indexes:
            for j in indexes:
                if ((i[1] == j[0]) and ([i[0], j[1]] not in indexes)):
                    return False
        return True

    def judgeRelationship(self):
        try:
            self.getMatrix()
            if self.isReflexive():
                print("该矩阵是自反的")
            if self.isAntiReflexive():
                print("该矩阵是反自反的")
            if self.isSymmetry():
                print("该矩阵是对称的")
            if self.isAntiSymmetric():
                print("该矩阵是反对称的")
            if self.isTransitive():
                print("该矩阵是传递的")
        except Exception as err:
            print(err)
            print("输入内容不合法,请核对后重试！")



if __name__ == '__main__':
    rm = RelationMatrix()
    rm.judgeRelationship()

运行效果图：

 

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