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  </pre> 
 


    #!/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()  </pre> 
 


 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    </pre>