Python 实现简单的矩阵

Python 实现简单的矩阵

#!/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