本文实例讲述了Python实现的矩阵类。分享给大家供大家参考,具体如下:
科学计算离不开矩阵的运算。当然,python已经有非常好的现成的库:numpy(numpy的简单安装与使用可参考http://www.zzvips.com/article/80457.html)。
我写这个矩阵类,并不是打算重新造一个*,只是作为一个练习,记录在此。
注:这个类的函数还没全部实现,慢慢在完善吧。
全部代码:
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import copy
class Matrix:
'''矩阵类'''
def __init__( self , row, column, fill = 0.0 ):
self .shape = (row, column)
self .row = row
self .column = column
self ._matrix = [[fill] * column for i in range (row)]
# 返回元素m(i, j)的值: m[i, j]
def __getitem__( self , index):
if isinstance (index, int ):
return self ._matrix[index - 1 ]
elif isinstance (index, tuple ):
return self ._matrix[index[ 0 ] - 1 ][index[ 1 ] - 1 ]
# 设置元素m(i,j)的值为s: m[i, j] = s
def __setitem__( self , index, value):
if isinstance (index, int ):
self ._matrix[index - 1 ] = copy.deepcopy(value)
elif isinstance (index, tuple ):
self ._matrix[index[ 0 ] - 1 ][index[ 1 ] - 1 ] = value
def __eq__( self , N):
'''相等'''
# A == B
assert isinstance (N, Matrix), "类型不匹配,不能比较"
return N.shape = = self .shape # 比较维度,可以修改为别的
def __add__( self , N):
'''加法'''
# A + B
assert N.shape = = self .shape, "维度不匹配,不能相加"
M = Matrix( self .row, self .column)
for r in range ( self .row):
for c in range ( self .column):
M[r, c] = self [r, c] + N[r, c]
return M
def __sub__( self , N):
'''减法'''
# A - B
assert N.shape = = self .shape, "维度不匹配,不能相减"
M = Matrix( self .row, self .column)
for r in range ( self .row):
for c in range ( self .column):
M[r, c] = self [r, c] - N[r, c]
return M
def __mul__( self , N):
'''乘法'''
# A * B (或:A * 2.0)
if isinstance (N, int ) or isinstance (N, float ):
M = Matrix( self .row, self .column)
for r in range ( self .row):
for c in range ( self .column):
M[r, c] = self [r, c] * N
else :
assert N.row = = self .column, "维度不匹配,不能相乘"
M = Matrix( self .row, N.column)
for r in range ( self .row):
for c in range (N.column):
sum = 0
for k in range ( self .column):
sum + = self [r, k] * N[k, r]
M[r, c] = sum
return M
def __div__( self , N):
'''除法'''
# A / B
pass
def __pow__( self , k):
'''乘方'''
# A**k
assert self .row = = self .column, "不是方阵,不能乘方"
M = copy.deepcopy( self )
for i in range (k):
M = M * self
return M
def rank( self ):
'''矩阵的秩'''
pass
def trace( self ):
'''矩阵的迹'''
pass
def adjoint( self ):
'''伴随矩阵'''
pass
def invert( self ):
'''逆矩阵'''
assert self .row = = self .column, "不是方阵"
M = Matrix( self .row, self .column * 2 )
I = self .identity() # 单位矩阵
I.show() #############################
# 拼接
for r in range ( 1 ,M.row + 1 ):
temp = self [r]
temp.extend(I[r])
M[r] = copy.deepcopy(temp)
M.show() #############################
# 初等行变换
for r in range ( 1 , M.row + 1 ):
# 本行首元素(M[r, r])若为 0,则向下交换最近的当前列元素非零的行
if M[r, r] = = 0 :
for rr in range (r + 1 , M.row + 1 ):
if M[rr, r] ! = 0 :
M[r],M[rr] = M[rr],M[r] # 交换两行
break
assert M[r, r] ! = 0 , '矩阵不可逆'
# 本行首元素(M[r, r])化为 1
temp = M[r,r] # 缓存
for c in range (r, M.column + 1 ):
M[r, c] / = temp
print ( "M[{0}, {1}] /= {2}" . format (r,c,temp))
M.show()
# 本列上、下方的所有元素化为 0
for rr in range ( 1 , M.row + 1 ):
temp = M[rr, r] # 缓存
for c in range (r, M.column + 1 ):
if rr = = r:
continue
M[rr, c] - = temp * M[r, c]
print ( "M[{0}, {1}] -= {2} * M[{3}, {1}]" . format (rr, c, temp,r))
M.show()
# 截取逆矩阵
N = Matrix( self .row, self .column)
for r in range ( 1 , self .row + 1 ):
N[r] = M[r][ self .row:]
return N
def jieti( self ):
'''行简化阶梯矩阵'''
pass
def transpose( self ):
'''转置'''
M = Matrix( self .column, self .row)
for r in range ( self .column):
for c in range ( self .row):
M[r, c] = self [c, r]
return M
def cofactor( self , row, column):
'''代数余子式(用于行列式展开)'''
assert self .row = = self .column, "不是方阵,无法计算代数余子式"
assert self .row > = 3 , "至少是3*3阶方阵"
assert row < = self .row and column < = self .column, "下标超出范围"
M = Matrix( self .column - 1 , self .row - 1 )
for r in range ( self .row):
if r = = row:
continue
for c in range ( self .column):
if c = = column:
continue
rr = r - 1 if r > row else r
cc = c - 1 if c > column else c
M[rr, cc] = self [r, c]
return M
def det( self ):
'''计算行列式(determinant)'''
assert self .row = = self .column, "非行列式,不能计算"
if self .shape = = ( 2 , 2 ):
return self [ 1 , 1 ] * self [ 2 , 2 ] - self [ 1 , 2 ] * self [ 2 , 1 ]
else :
sum = 0.0
for c in range ( self .column + 1 ):
sum + = ( - 1 ) * * (c + 1 ) * self [ 1 ,c] * self .cofactor( 1 ,c).det()
return sum
def zeros( self ):
'''全零矩阵'''
M = Matrix( self .column, self .row, fill = 0.0 )
return M
def ones( self ):
'''全1矩阵'''
M = Matrix( self .column, self .row, fill = 1.0 )
return M
def identity( self ):
'''单位矩阵'''
assert self .row = = self .column, "非n*n矩阵,无单位矩阵"
M = Matrix( self .column, self .row)
for r in range ( self .row):
for c in range ( self .column):
M[r, c] = 1.0 if r = = c else 0.0
return M
def show( self ):
'''打印矩阵'''
for r in range ( self .row):
for c in range ( self .column):
print ( self [r + 1 , c + 1 ],end = ' ' )
print ()
if __name__ = = '__main__' :
m = Matrix( 3 , 3 ,fill = 2.0 )
n = Matrix( 3 , 3 ,fill = 3.5 )
m[ 1 ] = [ 1. , 1. , 2. ]
m[ 2 ] = [ 1. , 2. , 1. ]
m[ 3 ] = [ 2. , 1. , 1. ]
p = m * n
q = m * 2.1
r = m * * 3
#r.show()
#q.show()
#print(p[1,1])
#r = m.invert()
#s = r*m
print ()
m.show()
print ()
#r.show()
print ()
#s.show()
print ()
print (m.det())
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希望本文所述对大家Python程序设计有所帮助。
原文链接:http://www.cnblogs.com/hhh5460/p/4314231.html