线性代数基础(python3)

作者: 陨星落云 | 来源:发表于2019-02-19 15:52 被阅读0次
    from math import sqrt,acos,pi
    from decimal import Decimal,getcontext
    getcontext().prec =30 #保留30小数
    
    class Vector(object):
        def __init__(self, coordinates):
            try:
                if not coordinates:
                    raise ValueError
                self.coordinates = tuple([Decimal(x) for x in coordinates])
                self.dimension = len(self.coordinates)
            except ValueError:
                raise ValueError('The coordinates must be nonempty')
    
            except TypeError:
                raise TypeError('The coordinates must be an iterable')
        CANNOT_NORMALIZE_ZERO_VECTOR_MSG = 'Cannot normalize the zero vector'
    
        #向量相加
        def plus(self,v):
            new_coordinates = [x+y for x,y in zip(self.coordinates,v.coordinates)]
            return Vector(new_coordinates)
    
        #向量相减
        def minus(self,v):
            new_coordinates = [x-y for x,y in zip(self.coordinates,v.coordinates)]
            return Vector(new_coordinates)
    
        #数乘
        def times_scalar(self,c):
            new_coordinates = [Decimal(c)*x for x in self.coordinates]
            return Vector(new_coordinates)
    
        #向量的模
        def magnitude(self):
            coordinates_squared = [x*x for x in self.coordinates]
            return sqrt(sum(coordinates_squared))
    
        #方向函数(化为单位向量)
        def normalized(self):
            try:
                magnitude = self.magnitude()
                return self.times_scalar(Decimal(1.0)/Decimal(magnitude))
            except ZeroDivisionError:
                raise Exception(self.CANNOT_NORMALIZE_ZERO_VECTOR_MSG)
    
        #向量点乘(内积)
        def dot(self,v):
            return sum([x*y for x,y in zip(self.coordinates,v.coordinates)])
        #向量叉乘(外积、向量积)
        def cross(self,v):
            try:
                x_1,y_1,z_1=self.coordinates
                x_2,y_2,z_2=v.coordinates
                new_coordinates=[y_1*z_2-y_2*z_1,
                                 -(x_1*z_2-x_2*z_1),
                                 x_1*y_2-x_2*y_1]
                return Vector(new_coordinates)
            except ValueError as e:
                msg = str(e)
                if msg == 'need more than 2 values to unpack':
                    self_embedded_in_R3 = Vector(self.coordinates+('0',))
                    v_embedded_in_R3 = Vector(v.coordinates+('0',))
                    return self_embedded_in_R3*v_embedded_in_R3
                elif (msg == 'too many values to unpack' or
                      msg == 'need more than 1 values to unpack'):
                      raise Exception(self.ONLY_DEFINED_IN_TWO_THREE_DIMS_MSG)
                else:
                    raise e
                
        #用于计算两个向量形成的平行四边形的面积
        def area_of_parallelogram_with(self,v):
            cross_product = self.cross(v)
            return cross_product.magnitude()
        
        #用于计算两个向量形成的三角形的面积
        def area_of_triangle_with(self,v):
            return self.area_of_parallelogram_with(v)/2.0
        
        #计算向量夹角
        
        def angle_with(self,v,in_degrees=False):
            try:
                u1=self.normalized()
                u2=v.normalized()
                dots=u1.dot(u2)
                if abs(abs(dots) - 1) < 1e-10:
                    if dots < 0:
                        dots = -1
                    else:
                        dots = 1
                angle_in_radians =acos(dots)
    
                if in_degrees:
                    degrees_per_radian =180./pi
                    return (angle_in_radians*degrees_per_radian)
                else:
                    return(angle_in_radians)
            
            except Exception as e:
                if str(e)==self.CANNOT_NORMALIZE_ZERO_VECTOR_MSG:
                    raise Exception ("Cannot compute an angle with the zero vector")
                else:
                    raise e
                
        #判断两向量之间平行
        def is_parallel_to(self,v):
            return (self.is_zero() or
                    v.is_zero() or
                    self.angle_with(v)==0 or
                    self.angle_with(v)==pi)
        
        def is_zero(self,tolerance=1e-10):#1乘以10的-10次方
            return self.magnitude()<tolerance
    
        #判断两向量正交
        def is_orthogonal_to(self,v,tolerance=1e-10):
            return abs(self.dot(v))<tolerance
    
        #利用向量投影分解的水平向量
        def component_parallel_to(self,basis):
            try:
                u=basis.normalized()
                weight=self.dot(u)
                return u.times_scalar(weight)
            except Exception as e:
                if str(e)==self.CANNOT_NORMALIZE_ZERO_VECTOR_MSG:
                    raise Exception(self.NO_UNIQUE_PARALLEL_COMPONENT_MSG)
                else:
                    raise e
    
        #利用向量投影分解出的垂直向量
        def component_orthogonal_to(self,basis):
            try:
                projection=self.component_parallel_to(basis)
                return self.minus(projection)
            except Exception as e:
                if str(e)==self.NO_UNIQUE_PARALLEL_COMPONENT_MSG:
                    raise Exception(self.NO_UNIQUE_ORTHOGNOAL_COMPONENT_MSG)
                else:
                    raise e
    
        #
        
        
        def __str__(self):
            return 'Vector: {}'.format(self.coordinates)
    
        def __eq__(self, v):
            return self.coordinates == v.coordinates
    
    #向量相加
    vector1 = Vector(['8.218','-9.341'])
    vector2 = Vector(['-1.129','2.111'])
    print (vector1.plus(vector2))#Vector.plus(vector1,vector2)
    
    
    #向量相减
    vector3 = Vector(['7.119','8.215'])
    vector4 = Vector(['-8.223','0.878'])
    print (vector3.minus(vector4))#Vector.minus(vector3,vector4)
    
    #数乘
    vector5 = Vector(['1.671','-1.012','-0.318'])
    c=7.41
    print (vector5.times_scalar(c))#Vector.times_scalar(vector5,c)
    
    #向量的模和方向函数(化为单位向量)
    vector6 = Vector(['3','4'])
    print(Vector.magnitude(vector6))
    print(Vector.normalized(vector6))
    
    
    #向量点乘(内积)
    v = Vector(['7.887','4.138'])
    w = Vector(['-8.802','6.776'])
    print(v.dot(w))
    
    v = Vector(['-5.955','-4.904','-1.874'])
    w = Vector(['-4.496','-8.755','7.103'])
    print(v.dot(w))
    
    #计算向量夹角
    v = Vector(['3.183','-7.627'])
    w =Vector(['-2.668','5.319'])
    print(v.angle_with(w))
    
    v = Vector(['7.6','1','5.188'])
    w = Vector(['2.751','8.259','3.985'])
    print(v.angle_with(w,in_degrees=True))
    
    #判断两向量之间平行或正交
    print('first pair')
    v = Vector(['-7.579','-7.88'])
    w = Vector(['22.737','23.64'])
    print ('is parallel:',v.is_parallel_to(w))
    print ('is orthogonal:',v.is_orthogonal_to(w))
    
    print('second pair')
    v = Vector(['-2.029','9.97','4.172'])
    w = Vector(['-9.231','-6.639','-7.245'])
    print ('is parallel:',v.is_parallel_to(w))
    print ('is orthogonal:',v.is_orthogonal_to(w))
    
    print('third pair')
    v = Vector(['-2.328','-7.284','-1.214'])
    w = Vector(['-1.1821','1.072','-2.94'])
    print ('is parallel:',v.is_parallel_to(w))
    print ('is orthogonal:',v.is_orthogonal_to(w))
    
    print('four pair')
    v = Vector(['2.118','4.827'])
    w = Vector(['0','0'])
    print ('is parallel:',v.is_parallel_to(w))
    print ('is orthogonal:',v.is_orthogonal_to(w))
    
    #利用向量投影分解出一个水平向量、一个垂直向量
    print('\n#1')
    v = Vector(['3.039','1.879'])
    w = Vector(['0.825','2.036'])
    print(v.component_parallel_to(w))
    
    print('\n#2')
    v = Vector(['-9.88','-3.264','-8.159'])
    w = Vector(['-2.155','-9.353','-9.473'])
    print(v.component_orthogonal_to(w))
    
    print('\n#3')
    v = Vector(['3.009','-6.172','3.692','-2.51'])
    w = Vector(['6.404','-9.144','2.759','8.718'])
    vpar = v.component_parallel_to(w)
    vort = v.component_orthogonal_to(w)
    print('parallel component:',vpar)
    print('orthogonal component:',vort)
    

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