Python 实现简单的矩阵
2018-07-20 来源：open-open
#!/usr/bin/python
# -*- coding: utf-8 -*-
'''''
Created on 2015-1-7
@author: beyondzhou
@name: myarray.py
'''
# Implementation of the Matrix ADT using a 2D array
from myarray import Array2D
class Matrix:
# Creates a matrix of size numRows * numCols initialized to 0
def __init__(self, numRows, numCols):
self._theGrid = Array2D(numRows, numCols)
self._theGrid.clear(0)
# Returns the number of rows in the matrix
def numRows(self):
return self._theGrid.numRows()
# Returns the number of columns in the matrix
def numCols(self):
return self._theGrid.numCols()
# Returns the value of element (i, j): x[i, j]
def __getitem__(self, ndxTuple):
return self._theGrid[ndxTuple[0], ndxTuple[1]]
# Sets the value of element (i,j) to the value s: x[i, j] = s
def __setitem__(self, ndxTuple, scalar):
self._theGrid[ndxTuple[0], ndxTuple[1]] = scalar
# Scales the matrix by the given scalar
def scaleBy(self, scalar):
for r in range(self.numRows()):
for c in range(self.numCols()):
self[r,c] *= scalar
# Creates and returns a new matrix that is the transpose of this matrix
def transpose(self):
# Create the new matrix
newMatrix = Matrix(self.numCols(), self.numRows())
# Add the corresponding elements in the two matrices
for r in range(self.numRows()):
for c in range(self.numCols()):
newMatrix[c,r] = self[r,c]
return newMatrix
# Creates and returns a new matrix that results from matrix addition
def __add__(self, rhsMatrix):
assert rhsMatrix.numRows() == self.numRows() and \
rhsMatrix.numCols() == self.numCols(), \
"Matrix sizes not compatible for the add operation."
# Create the new matrix
newMatrix = Matrix(self.numRows(), self.numCols())
# Add the corresponding elements in the two matrices
for r in range(self.numRows()):
for c in range(self.numCols()):
newMatrix[r,c] = self[r,c] + rhsMatrix[r,c]
return newMatrix
# Creates and returns a new matrix that results from matrix sub
def __sub__(self, rhsMatrix):
assert rhsMatrix.numRows() == self.numRows() and \
rhsMatrix.numCols() == self.numCols(), \
"Matrix sizes not compatible for the add operation."
# Create the new matrix
newMatrix = Matrix(self.numRows(), self.numCols())
# Add the corresponding elements in the two matrices
for r in range(self.numRows()):
for c in range(self.numCols()):
newMatrix[r,c] = self[r,c] - rhsMatrix[r,c]
return newMatrix
# Creates and returns a new matrix resulting from matrix multiplcation
def __mul__(self, rhsMatrix):
assert rhsMatrix.numRows() == self.numCols(), \
"Matrix sizes not compatible for the multi operation."
# Create the new matrix
newMatrix = Matrix(self.numRows(), rhsMatrix.numCols())
# Mul the corresponding elements in the two matrices
for r in range(self.numRows()):
for c in range(rhsMatrix.numCols()):
mysum = 0.0
for k in range(self.numCols()):
mysum += self[r,k] * rhsMatrix[k,r]
newMatrix[r,c] = mysum
return newMatrix
#!/usr/bin/python
# -*- coding: utf-8 -*-
'''''
Created on 2015-1-7
@author: beyondzhou
@name: test_matrix.py
'''
def test_matrix():
# Import
from mymatrix import Matrix
import random
# set default value for matrix
aMatrix = Matrix(2,3)
bMatrix = Matrix(2,3)
fMatrix = Matrix(3,2)
for i in range(aMatrix.numRows()):
for j in range(aMatrix.numCols()):
aMatrix[i,j] = random.random()
bMatrix[i,j] = random.random()
for i in range(fMatrix.numRows()):
for j in range(fMatrix.numCols()):
fMatrix[i,j] = random.random()
print 'The primary value of amatrix'
for i in range(aMatrix.numRows()):
for j in range(aMatrix.numCols()):
print '%s ' % aMatrix[i,j],
print '\r'
print '\nThe primary value of bmatrix'
for i in range(bMatrix.numRows()):
for j in range(bMatrix.numCols()):
print '%s ' % bMatrix[i,j],
print '\r'
print '\nThe primary value of fmatrix'
for i in range(fMatrix.numRows()):
for j in range(fMatrix.numCols()):
print '%s ' % fMatrix[i,j],
print '\r'
# add amatrix and bmatrix to cmatrix
cMatrix = aMatrix + bMatrix
print '\nThe value of cMatrix (aMatrix + bMatrix)'
for i in range(cMatrix.numRows()):
for j in range(cMatrix.numCols()):
print '%s ' % cMatrix[i,j],
print '\r'
# sub amatrix and bmatrix to dmatrix
dMatrix = aMatrix - bMatrix
print '\nThe value of dMatrix (aMatrix - bMatrix)'
for i in range(dMatrix.numRows()):
for j in range(dMatrix.numCols()):
print '%s ' % dMatrix[i,j],
print '\r'
# Mul amatrix and fMatrix to ematrix
eMatrix = aMatrix * fMatrix
print '\nThe value of eMatrix (aMatrix * fMatrix)'
for i in range(eMatrix.numRows()):
for j in range(eMatrix.numCols()):
print '%s ' % eMatrix[i,j],
print '\r'
# Scale the amatrix by 3
aMatrix.scaleBy(3)
print '\nThe scale value of amatrix'
for i in range(aMatrix.numRows()):
for j in range(aMatrix.numCols()):
print '%s ' % aMatrix[i,j],
print '\r'
# Transpose the amatrix
dMatrix = aMatrix.transpose()
print '\nThe transpose value of amatrix'
for i in range(dMatrix.numRows()):
for j in range(dMatrix.numCols()):
print '%s ' % dMatrix[i,j],
print '\r'
if __name__ == "__main__":
test_matrix()
Result:
The primary value of amatrix
0.886197406941 0.304295996721 0.293469382347
0.154702139448 0.511075267985 0.387057640727
The primary value of bmatrix
0.574674206609 0.364815615899 0.493367650314
0.438101377839 0.801271107474 0.0891226289712
The primary value of fmatrix
0.00716087704081 0.537519043084
0.451888654276 0.234306298527
0.572987747957 0.479059183861
The value of cMatrix (aMatrix + bMatrix)
1.46087161355 0.66911161262 0.78683703266
0.592803517287 1.31234637546 0.476180269699
The value of dMatrix (aMatrix - bMatrix)
0.311523200332 -0.0605196191784 -0.199898267967
-0.283399238391 -0.290195839489 0.297935011756
The value of eMatrix (aMatrix * fMatrix)
0.31200821961 0.31200821961
0.388327017743 0.388327017743
The scale value of amatrix
2.65859222082 0.912887990162 0.88040814704
0.464106418343 1.53322580395 1.16117292218
The transpose value of amatrix
2.65859222082 0.464106418343
0.912887990162 1.53322580395
0.88040814704 1.16117292218
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